%0 Journal Article %J Nature %D 2023 %T Aberrant activation of TCL1A promotes stem cell expansion in clonal haematopoiesis. %A Weinstock, Joshua S %A Gopakumar, Jayakrishnan %A Burugula, Bala Bharathi %A Uddin, Md Mesbah %A Jahn, Nikolaus %A Belk, Julia A %A Bouzid, Hind %A Daniel, Bence %A Miao, Zhuang %A Ly, Nghi %A Mack, Taralynn M %A Luna, Sofia E %A Prothro, Katherine P %A Mitchell, Shaneice R %A Laurie, Cecelia A %A Broome, Jai G %A Taylor, Kent D %A Guo, Xiuqing %A Sinner, Moritz F %A von Falkenhausen, Aenne S %A Kääb, Stefan %A Shuldiner, Alan R %A O'Connell, Jeffrey R %A Lewis, Joshua P %A Eric Boerwinkle %A Barnes, Kathleen C %A Chami, Nathalie %A Kenny, Eimear E %A Loos, Ruth J F %A Fornage, Myriam %A Hou, Lifang %A Lloyd-Jones, Donald M %A Redline, Susan %A Cade, Brian E %A Psaty, Bruce M %A Bis, Joshua C %A Brody, Jennifer A %A Silverman, Edwin K %A Yun, Jeong H %A Qiao, Dandi %A Palmer, Nicholette D %A Freedman, Barry I %A Bowden, Donald W %A Cho, Michael H %A DeMeo, Dawn L %A Vasan, Ramachandran S %A Yanek, Lisa R %A Becker, Lewis C %A Kardia, Sharon L R %A Peyser, Patricia A %A He, Jiang %A Rienstra, Michiel %A van der Harst, Pim %A Kaplan, Robert %A Heckbert, Susan R %A Smith, Nicholas L %A Wiggins, Kerri L %A Arnett, Donna K %A Irvin, Marguerite R %A Tiwari, Hemant %A Cutler, Michael J %A Knight, Stacey %A Muhlestein, J Brent %A Correa, Adolfo %A Raffield, Laura M %A Gao, Yan %A de Andrade, Mariza %A Rotter, Jerome I %A Rich, Stephen S %A Tracy, Russell P %A Konkle, Barbara A %A Johnsen, Jill M %A Wheeler, Marsha M %A Smith, J Gustav %A Melander, Olle %A Nilsson, Peter M %A Custer, Brian S %A Duggirala, Ravindranath %A Curran, Joanne E %A Blangero, John %A McGarvey, Stephen %A Williams, L Keoki %A Xiao, Shujie %A Yang, Mao %A Gu, C Charles %A Chen, Yii-Der Ida %A Lee, Wen-Jane %A Marcus, Gregory M %A Kane, John P %A Pullinger, Clive R %A Shoemaker, M Benjamin %A Darbar, Dawood %A Roden, Dan M %A Albert, Christine %A Kooperberg, Charles %A Zhou, Ying %A Manson, JoAnn E %A Desai, Pinkal %A Johnson, Andrew D %A Mathias, Rasika A %A Blackwell, Thomas W %A Abecasis, Gonçalo R %A Smith, Albert V %A Kang, Hyun M %A Satpathy, Ansuman T %A Natarajan, Pradeep %A Kitzman, Jacob O %A Whitsel, Eric A %A Reiner, Alexander P %A Bick, Alexander G %A Jaiswal, Siddhartha %K Alleles %K Animals %K Clonal Hematopoiesis %K Genome-Wide Association Study %K Hematopoiesis %K Hematopoietic Stem Cells %K Humans %K Mice %K Mutation %K Promoter Regions, Genetic %X

Mutations in a diverse set of driver genes increase the fitness of haematopoietic stem cells (HSCs), leading to clonal haematopoiesis. These lesions are precursors for blood cancers, but the basis of their fitness advantage remains largely unknown, partly owing to a paucity of large cohorts in which the clonal expansion rate has been assessed by longitudinal sampling. Here, to circumvent this limitation, we developed a method to infer the expansion rate from data from a single time point. We applied this method to 5,071 people with clonal haematopoiesis. A genome-wide association study revealed that a common inherited polymorphism in the TCL1A promoter was associated with a slower expansion rate in clonal haematopoiesis overall, but the effect varied by driver gene. Those carrying this protective allele exhibited markedly reduced growth rates or prevalence of clones with driver mutations in TET2, ASXL1, SF3B1 and SRSF2, but this effect was not seen in clones with driver mutations in DNMT3A. TCL1A was not expressed in normal or DNMT3A-mutated HSCs, but the introduction of mutations in TET2 or ASXL1 led to the expression of TCL1A protein and the expansion of HSCs in vitro. The protective allele restricted TCL1A expression and expansion of mutant HSCs, as did experimental knockdown of TCL1A expression. Forced expression of TCL1A promoted the expansion of human HSCs in vitro and mouse HSCs in vivo. Our results indicate that the fitness advantage of several commonly mutated driver genes in clonal haematopoiesis may be mediated by TCL1A activation.

%B Nature %V 616 %P 755-763 %8 2023 Apr %G eng %N 7958 %1 https://www.ncbi.nlm.nih.gov/pubmed/37046083?dopt=Abstract %R 10.1038/s41586-023-05806-1 %0 Journal Article %J J Am Heart Assoc %D 2023 %T Association Between Whole Blood-Derived Mitochondrial DNA Copy Number, Low-Density Lipoprotein Cholesterol, and Cardiovascular Disease Risk. %A Liu, Xue %A Sun, Xianbang %A Zhang, Yuankai %A Jiang, Wenqing %A Lai, Meng %A Wiggins, Kerri L %A Raffield, Laura M %A Bielak, Lawrence F %A Zhao, Wei %A Pitsillides, Achilleas %A Haessler, Jeffrey %A Zheng, Yinan %A Blackwell, Thomas W %A Yao, Jie %A Guo, Xiuqing %A Qian, Yong %A Thyagarajan, Bharat %A Pankratz, Nathan %A Rich, Stephen S %A Taylor, Kent D %A Peyser, Patricia A %A Heckbert, Susan R %A Seshadri, Sudha %A Eric Boerwinkle %A Grove, Megan L %A Larson, Nicholas B %A Smith, Jennifer A %A Vasan, Ramachandran S %A Fitzpatrick, Annette L %A Fornage, Myriam %A Ding, Jun %A Carson, April P %A Abecasis, Goncalo %A Dupuis, Josée %A Reiner, Alexander %A Kooperberg, Charles %A Hou, Lifang %A Psaty, Bruce M %A Wilson, James G %A Levy, Daniel %A Rotter, Jerome I %A Bis, Joshua C %A Satizabal, Claudia L %A Arking, Dan E %A Liu, Chunyu %K Cardiovascular Diseases %K Cholesterol, HDL %K Cholesterol, LDL %K Coronary Disease %K Cross-Sectional Studies %K Diabetes Mellitus %K DNA Copy Number Variations %K DNA, Mitochondrial %K Humans %K Hypertension %K Obesity %K Risk Factors %X

Background The relationship between mitochondrial DNA copy number (mtDNA CN) and cardiovascular disease remains elusive. Methods and Results We performed cross-sectional and prospective association analyses of blood-derived mtDNA CN and cardiovascular disease outcomes in 27 316 participants in 8 cohorts of multiple racial and ethnic groups with whole-genome sequencing. We also performed Mendelian randomization to explore causal relationships of mtDNA CN with coronary heart disease (CHD) and cardiometabolic risk factors (obesity, diabetes, hypertension, and hyperlipidemia). <0.01 was used for significance. We validated most of the previously reported associations between mtDNA CN and cardiovascular disease outcomes. For example, 1-SD unit lower level of mtDNA CN was associated with 1.08 (95% CI, 1.04-1.12; <0.001) times the hazard for developing incident CHD, adjusting for covariates. Mendelian randomization analyses showed no causal effect from a lower level of mtDNA CN to a higher CHD risk (β=0.091; =0.11) or in the reverse direction (β=-0.012; =0.076). Additional bidirectional Mendelian randomization analyses revealed that low-density lipoprotein cholesterol had a causal effect on mtDNA CN (β=-0.084; <0.001), but the reverse direction was not significant (=0.059). No causal associations were observed between mtDNA CN and obesity, diabetes, and hypertension, in either direction. Multivariable Mendelian randomization analyses showed no causal effect of CHD on mtDNA CN, controlling for low-density lipoprotein cholesterol level (=0.52), whereas there was a strong direct causal effect of higher low-density lipoprotein cholesterol on lower mtDNA CN, adjusting for CHD status (β=-0.092; <0.001). Conclusions Our findings indicate that high low-density lipoprotein cholesterol may underlie the complex relationships between mtDNA CN and vascular atherosclerosis.

%B J Am Heart Assoc %V 12 %P e029090 %8 2023 Oct 17 %G eng %N 20 %1 https://www.ncbi.nlm.nih.gov/pubmed/37804200?dopt=Abstract %R 10.1161/JAHA.122.029090 %0 Journal Article %J Nat Commun %D 2023 %T Deleterious heteroplasmic mitochondrial mutations are associated with an increased risk of overall and cancer-specific mortality. %A Hong, Yun Soo %A Battle, Stephanie L %A Shi, Wen %A Puiu, Daniela %A Pillalamarri, Vamsee %A Xie, Jiaqi %A Pankratz, Nathan %A Lake, Nicole J %A Lek, Monkol %A Rotter, Jerome I %A Rich, Stephen S %A Kooperberg, Charles %A Reiner, Alex P %A Auer, Paul L %A Heard-Costa, Nancy %A Liu, Chunyu %A Lai, Meng %A Murabito, Joanne M %A Levy, Daniel %A Grove, Megan L %A Alonso, Alvaro %A Richard A Gibbs %A Dugan-Perez, Shannon %A Gondek, Lukasz P %A Guallar, Eliseo %A Arking, Dan E %K DNA, Mitochondrial %K Heteroplasmy %K Humans %K Leukemia %K Mitochondria %K Mutation %X

Mitochondria carry their own circular genome and disruption of the mitochondrial genome is associated with various aging-related diseases. Unlike the nuclear genome, mitochondrial DNA (mtDNA) can be present at 1000 s to 10,000 s copies in somatic cells and variants may exist in a state of heteroplasmy, where only a fraction of the DNA molecules harbors a particular variant. We quantify mtDNA heteroplasmy in 194,871 participants in the UK Biobank and find that heteroplasmy is associated with a 1.5-fold increased risk of all-cause mortality. Additionally, we functionally characterize mtDNA single nucleotide variants (SNVs) using a constraint-based score, mitochondrial local constraint score sum (MSS) and find it associated with all-cause mortality, and with the prevalence and incidence of cancer and cancer-related mortality, particularly leukemia. These results indicate that mitochondria may have a functional role in certain cancers, and mitochondrial heteroplasmic SNVs may serve as a prognostic marker for cancer, especially for leukemia.

%B Nat Commun %V 14 %P 6113 %8 2023 Sep 30 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/37777527?dopt=Abstract %R 10.1038/s41467-023-41785-7 %0 Journal Article %J bioRxiv %D 2023 %T Genetic control of mRNA splicing as a potential mechanism for incomplete penetrance of rare coding variants. %A Einson, Jonah %A Glinos, Dafni %A Eric Boerwinkle %A Castaldi, Peter %A Darbar, Dawood %A de Andrade, Mariza %A Ellinor, Patrick %A Fornage, Myriam %A Gabriel, Stacey %A Germer, Soren %A Richard A Gibbs %A Hersh, Craig P %A Johnsen, Jill %A Kaplan, Robert %A Konkle, Barbara A %A Kooperberg, Charles %A Nassir, Rami %A Loos, Ruth J F %A Meyers, Deborah A %A Mitchell, Braxton D %A Psaty, Bruce %A Vasan, Ramachandran S %A Rich, Stephen S %A Rienstra, Michael %A Rotter, Jerome I %A Saferali, Aabida %A Shoemaker, M Benjamin %A Silverman, Edwin %A Smith, Albert Vernon %A Mohammadi, Pejman %A Castel, Stephane E %A Iossifov, Ivan %A Lappalainen, Tuuli %X

Exonic variants present some of the strongest links between genotype and phenotype. However, these variants can have significant inter-individual pathogenicity differences, known as variable penetrance. In this study, we propose a model where genetically controlled mRNA splicing modulates the pathogenicity of exonic variants. By first cataloging exonic inclusion from RNA-seq data in GTEx v8, we find that pathogenic alleles are depleted on highly included exons. Using a large-scale phased WGS data from the TOPMed consortium, we observe that this effect may be driven by common splice-regulatory genetic variants, and that natural selection acts on haplotype configurations that reduce the transcript inclusion of putatively pathogenic variants, especially when limiting to haploinsufficient genes. Finally, we test if this effect may be relevant for autism risk using families from the Simons Simplex Collection, but find that splicing of pathogenic alleles has a penetrance reducing effect here as well. Overall, our results indicate that common splice-regulatory variants may play a role in reducing the damaging effects of rare exonic variants.

%B bioRxiv %8 2023 Jan 31 %G eng %1 https://www.ncbi.nlm.nih.gov/pubmed/36778406?dopt=Abstract %R 10.1101/2023.01.31.526505 %0 Journal Article %J Genetics %D 2023 %T Genetic control of mRNA splicing as a potential mechanism for incomplete penetrance of rare coding variants. %A Einson, Jonah %A Glinos, Dafni %A Eric Boerwinkle %A Castaldi, Peter %A Darbar, Dawood %A de Andrade, Mariza %A Ellinor, Patrick %A Fornage, Myriam %A Gabriel, Stacey %A Germer, Soren %A Richard A Gibbs %A Hersh, Craig P %A Johnsen, Jill %A Kaplan, Robert %A Konkle, Barbara A %A Kooperberg, Charles %A Nassir, Rami %A Loos, Ruth J F %A Meyers, Deborah A %A Mitchell, Braxton D %A Psaty, Bruce %A Vasan, Ramachandran S %A Rich, Stephen S %A Rienstra, Michael %A Rotter, Jerome I %A Saferali, Aabida %A Shoemaker, Moore Benjamin %A Silverman, Edwin %A Smith, Albert Vernon %A Mohammadi, Pejman %A Castel, Stephane E %A Iossifov, Ivan %A Lappalainen, Tuuli %K Alternative Splicing %K Exons %K Genotype %K Penetrance %K RNA Splice Sites %K RNA Splicing %K RNA, Messenger %X

Exonic variants present some of the strongest links between genotype and phenotype. However, these variants can have significant inter-individual pathogenicity differences, known as variable penetrance. In this study, we propose a model where genetically controlled mRNA splicing modulates the pathogenicity of exonic variants. By first cataloging exonic inclusion from RNA-sequencing data in GTEx V8, we find that pathogenic alleles are depleted on highly included exons. Using a large-scale phased whole genome sequencing data from the TOPMed consortium, we observe that this effect may be driven by common splice-regulatory genetic variants, and that natural selection acts on haplotype configurations that reduce the transcript inclusion of putatively pathogenic variants, especially when limiting to haploinsufficient genes. Finally, we test if this effect may be relevant for autism risk using families from the Simons Simplex Collection, but find that splicing of pathogenic alleles has a penetrance reducing effect here as well. Overall, our results indicate that common splice-regulatory variants may play a role in reducing the damaging effects of rare exonic variants.

%B Genetics %V 224 %8 2023 Aug 09 %G eng %N 4 %1 https://www.ncbi.nlm.nih.gov/pubmed/37348055?dopt=Abstract %R 10.1093/genetics/iyad115 %0 Journal Article %J Sci Adv %D 2023 %T The genetic determinants of recurrent somatic mutations in 43,693 blood genomes. %A Weinstock, Joshua S %A Laurie, Cecelia A %A Broome, Jai G %A Taylor, Kent D %A Guo, Xiuqing %A Shuldiner, Alan R %A O'Connell, Jeffrey R %A Lewis, Joshua P %A Eric Boerwinkle %A Barnes, Kathleen C %A Chami, Nathalie %A Kenny, Eimear E %A Loos, Ruth J F %A Fornage, Myriam %A Redline, Susan %A Cade, Brian E %A Gilliland, Frank D %A Chen, Zhanghua %A Gauderman, W James %A Kumar, Rajesh %A Grammer, Leslie %A Schleimer, Robert P %A Psaty, Bruce M %A Bis, Joshua C %A Brody, Jennifer A %A Silverman, Edwin K %A Yun, Jeong H %A Qiao, Dandi %A Weiss, Scott T %A Lasky-Su, Jessica %A DeMeo, Dawn L %A Palmer, Nicholette D %A Freedman, Barry I %A Bowden, Donald W %A Cho, Michael H %A Vasan, Ramachandran S %A Johnson, Andrew D %A Yanek, Lisa R %A Becker, Lewis C %A Kardia, Sharon %A He, Jiang %A Kaplan, Robert %A Heckbert, Susan R %A Smith, Nicholas L %A Wiggins, Kerri L %A Arnett, Donna K %A Irvin, Marguerite R %A Tiwari, Hemant %A Correa, Adolfo %A Raffield, Laura M %A Gao, Yan %A de Andrade, Mariza %A Rotter, Jerome I %A Rich, Stephen S %A Manichaikul, Ani W %A Konkle, Barbara A %A Johnsen, Jill M %A Wheeler, Marsha M %A Custer, Brian S %A Duggirala, Ravindranath %A Curran, Joanne E %A Blangero, John %A Gui, Hongsheng %A Xiao, Shujie %A Williams, L Keoki %A Meyers, Deborah A %A Li, Xingnan %A Ortega, Victor %A McGarvey, Stephen %A Gu, C Charles %A Chen, Yii-Der Ida %A Lee, Wen-Jane %A Shoemaker, M Benjamin %A Darbar, Dawood %A Roden, Dan %A Albert, Christine %A Kooperberg, Charles %A Desai, Pinkal %A Blackwell, Thomas W %A Abecasis, Gonçalo R %A Smith, Albert V %A Kang, Hyun M %A Mathias, Rasika %A Natarajan, Pradeep %A Jaiswal, Siddhartha %A Reiner, Alexander P %A Bick, Alexander G %K Germ-Line Mutation %K Hematopoiesis %K Humans %K Middle Aged %K Mutation %K Mutation, Missense %K Phenotype %X

Nononcogenic somatic mutations are thought to be uncommon and inconsequential. To test this, we analyzed 43,693 National Heart, Lung and Blood Institute Trans-Omics for Precision Medicine blood whole genomes from 37 cohorts and identified 7131 non-missense somatic mutations that are recurrently mutated in at least 50 individuals. These recurrent non-missense somatic mutations (RNMSMs) are not clearly explained by other clonal phenomena such as clonal hematopoiesis. RNMSM prevalence increased with age, with an average 50-year-old having 27 RNMSMs. Inherited germline variation associated with RNMSM acquisition. These variants were found in genes involved in adaptive immune function, proinflammatory cytokine production, and lymphoid lineage commitment. In addition, the presence of eight specific RNMSMs associated with blood cell traits at effect sizes comparable to Mendelian genetic mutations. Overall, we found that somatic mutations in blood are an unexpectedly common phenomenon with ancestry-specific determinants and human health consequences.

%B Sci Adv %V 9 %P eabm4945 %8 2023 Apr 28 %G eng %N 17 %1 https://www.ncbi.nlm.nih.gov/pubmed/37126548?dopt=Abstract %R 10.1126/sciadv.abm4945 %0 Journal Article %J Diabetes %D 2023 %T Investigating Gene-Diet Interactions Impacting the Association Between Macronutrient Intake and Glycemic Traits. %A Westerman, Kenneth E %A Walker, Maura E %A Gaynor, Sheila M %A Wessel, Jennifer %A DiCorpo, Daniel %A Ma, Jiantao %A Alonso, Alvaro %A Aslibekyan, Stella %A Baldridge, Abigail S %A Bertoni, Alain G %A Biggs, Mary L %A Brody, Jennifer A %A Chen, Yii-Der Ida %A Dupuis, Josée %A Goodarzi, Mark O %A Guo, Xiuqing %A Hasbani, Natalie R %A Heath, Adam %A Hidalgo, Bertha %A Irvin, Marguerite R %A Johnson, W Craig %A Kalyani, Rita R %A Lange, Leslie %A Lemaitre, Rozenn N %A Liu, Ching-Ti %A Liu, Simin %A Moon, Jee-Young %A Nassir, Rami %A Pankow, James S %A Pettinger, Mary %A Raffield, Laura M %A Rasmussen-Torvik, Laura J %A Selvin, Elizabeth %A Senn, Mackenzie K %A Shadyab, Aladdin H %A Smith, Albert V %A Smith, Nicholas L %A Steffen, Lyn %A Talegakwar, Sameera %A Taylor, Kent D %A de Vries, Paul S %A Wilson, James G %A Wood, Alexis C %A Yanek, Lisa R %A Yao, Jie %A Zheng, Yinan %A Eric Boerwinkle %A Morrison, Alanna C %A Fornage, Miriam %A Russell, Tracy P %A Psaty, Bruce M %A Levy, Daniel %A Heard-Costa, Nancy L %A Ramachandran, Vasan S %A Mathias, Rasika A %A Arnett, Donna K %A Kaplan, Robert %A North, Kari E %A Correa, Adolfo %A Carson, April %A Rotter, Jerome I %A Rich, Stephen S %A Manson, JoAnn E %A Reiner, Alexander P %A Kooperberg, Charles %A Florez, Jose C %A Meigs, James B %A Merino, Jordi %A Tobias, Deirdre K %A Chen, Han %A Manning, Alisa K %K Diabetes Mellitus %K Diet %K Eating %K Genome-Wide Association Study %K Glycated Hemoglobin %K Guanine Nucleotide Dissociation Inhibitors %K Humans %X

UNLABELLED: Few studies have demonstrated reproducible gene-diet interactions (GDIs) impacting metabolic disease risk factors, likely due in part to measurement error in dietary intake estimation and insufficient capture of rare genetic variation. We aimed to identify GDIs across the genetic frequency spectrum impacting the macronutrient-glycemia relationship in genetically and culturally diverse cohorts. We analyzed 33,187 participants free of diabetes from 10 National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program cohorts with whole-genome sequencing, self-reported diet, and glycemic trait data. We fit cohort-specific, multivariable-adjusted linear mixed models for the effect of diet, modeled as an isocaloric substitution of carbohydrate for fat, and its interactions with common and rare variants genome-wide. In main effect meta-analyses, participants consuming more carbohydrate had modestly lower glycemic trait values (e.g., for glycated hemoglobin [HbA1c], -0.013% HbA1c/250 kcal substitution). In GDI meta-analyses, a common African ancestry-enriched variant (rs79762542) reached study-wide significance and replicated in the UK Biobank cohort, indicating a negative carbohydrate-HbA1c association among major allele homozygotes only. Simulations revealed that >150,000 samples may be necessary to identify similar macronutrient GDIs under realistic assumptions about effect size and measurement error. These results generate hypotheses for further exploration of modifiable metabolic disease risk in additional cohorts with African ancestry.

ARTICLE HIGHLIGHTS: We aimed to identify genetic modifiers of the dietary macronutrient-glycemia relationship using whole-genome sequence data from 10 Trans-Omics for Precision Medicine program cohorts. Substitution models indicated a modest reduction in glycemia associated with an increase in dietary carbohydrate at the expense of fat. Genome-wide interaction analysis identified one African ancestry-enriched variant near the FRAS1 gene that may interact with macronutrient intake to influence hemoglobin A1c. Simulation-based power calculations accounting for measurement error suggested that substantially larger sample sizes may be necessary to discover further gene-macronutrient interactions.

%B Diabetes %V 72 %P 653-665 %8 2023 May 01 %G eng %N 5 %1 https://www.ncbi.nlm.nih.gov/pubmed/36791419?dopt=Abstract %R 10.2337/db22-0851 %0 Journal Article %J Nat Genet %D 2023 %T Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies. %A Li, Xihao %A Quick, Corbin %A Zhou, Hufeng %A Gaynor, Sheila M %A Liu, Yaowu %A Chen, Han %A Selvaraj, Margaret Sunitha %A Sun, Ryan %A Dey, Rounak %A Arnett, Donna K %A Bielak, Lawrence F %A Bis, Joshua C %A Blangero, John %A Eric Boerwinkle %A Bowden, Donald W %A Brody, Jennifer A %A Cade, Brian E %A Correa, Adolfo %A Cupples, L Adrienne %A Curran, Joanne E %A de Vries, Paul S %A Duggirala, Ravindranath %A Freedman, Barry I %A Göring, Harald H H %A Guo, Xiuqing %A Haessler, Jeffrey %A Kalyani, Rita R %A Kooperberg, Charles %A Kral, Brian G %A Lange, Leslie A %A Manichaikul, Ani %A Martin, Lisa W %A McGarvey, Stephen T %A Mitchell, Braxton D %A Montasser, May E %A Morrison, Alanna C %A Naseri, Take %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Peyser, Patricia A %A Psaty, Bruce M %A Raffield, Laura M %A Redline, Susan %A Reiner, Alexander P %A Reupena, Muagututi'a Sefuiva %A Rice, Kenneth M %A Rich, Stephen S %A Sitlani, Colleen M %A Smith, Jennifer A %A Taylor, Kent D %A Vasan, Ramachandran S %A Willer, Cristen J %A Wilson, James G %A Yanek, Lisa R %A Zhao, Wei %A Rotter, Jerome I %A Natarajan, Pradeep %A Peloso, Gina M %A Li, Zilin %A Lin, Xihong %K Exome Sequencing %K Genome-Wide Association Study %K Lipids %K Phenotype %K Whole Genome Sequencing %X

Meta-analysis of whole genome sequencing/whole exome sequencing (WGS/WES) studies provides an attractive solution to the problem of collecting large sample sizes for discovering rare variants associated with complex phenotypes. Existing rare variant meta-analysis approaches are not scalable to biobank-scale WGS data. Here we present MetaSTAAR, a powerful and resource-efficient rare variant meta-analysis framework for large-scale WGS/WES studies. MetaSTAAR accounts for relatedness and population structure, can analyze both quantitative and dichotomous traits and boosts the power of rare variant tests by incorporating multiple variant functional annotations. Through meta-analysis of four lipid traits in 30,138 ancestrally diverse samples from 14 studies of the Trans Omics for Precision Medicine (TOPMed) Program, we show that MetaSTAAR performs rare variant meta-analysis at scale and produces results comparable to using pooled data. Additionally, we identified several conditionally significant rare variant associations with lipid traits. We further demonstrate that MetaSTAAR is scalable to biobank-scale cohorts through meta-analysis of TOPMed WGS data and UK Biobank WES data of ~200,000 samples.

%B Nat Genet %V 55 %P 154-164 %8 2023 Jan %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/36564505?dopt=Abstract %R 10.1038/s41588-022-01225-6 %0 Journal Article %J medRxiv %D 2023 %T Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed Whole Genome Sequencing Study. %A Wang, Yuxuan %A Selvaraj, Margaret Sunitha %A Li, Xihao %A Li, Zilin %A Holdcraft, Jacob A %A Arnett, Donna K %A Bis, Joshua C %A Blangero, John %A Eric Boerwinkle %A Bowden, Donald W %A Cade, Brian E %A Carlson, Jenna C %A Carson, April P %A Chen, Yii-Der Ida %A Curran, Joanne E %A de Vries, Paul S %A Dutcher, Susan K %A Ellinor, Patrick T %A Floyd, James S %A Fornage, Myriam %A Freedman, Barry I %A Gabriel, Stacey %A Germer, Soren %A Richard A Gibbs %A Guo, Xiuqing %A He, Jiang %A Heard-Costa, Nancy %A Hildalgo, Bertha %A Hou, Lifang %A Irvin, Marguerite R %A Joehanes, Roby %A Kaplan, Robert C %A Kardia, Sharon Lr %A Kelly, Tanika N %A Kim, Ryan %A Kooperberg, Charles %A Kral, Brian G %A Levy, Daniel %A Li, Changwei %A Liu, Chunyu %A Lloyd-Jone, Don %A Loos, Ruth Jf %A Mahaney, Michael C %A Martin, Lisa W %A Mathias, Rasika A %A Minster, Ryan L %A Mitchell, Braxton D %A Montasser, May E %A Morrison, Alanna C %A Murabito, Joanne M %A Naseri, Take %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Preuss, Michael H %A Psaty, Bruce M %A Raffield, Laura M %A Rao, Dabeeru C %A Redline, Susan %A Reiner, Alexander P %A Rich, Stephen S %A Ruepena, Muagututi'a Sefuiva %A Sheu, Wayne H-H %A Smith, Jennifer A %A Smith, Albert %A Tiwari, Hemant K %A Tsai, Michael Y %A Viaud-Martinez, Karine A %A Wang, Zhe %A Yanek, Lisa R %A Zhao, Wei %A Rotter, Jerome I %A Lin, Xihong %A Natarajan, Pradeep %A Peloso, Gina M %X

Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions. Large-scale whole genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess the associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with blood lipid levels (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare variant aggregate association tests using the STAAR (variant-Set Test for Association using Annotation infoRmation) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare coding variants in nearby protein coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500 kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variations and rare protein coding variations at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNA, implicating new therapeutic opportunities.

%B medRxiv %8 2023 Jun 29 %G eng %1 https://www.ncbi.nlm.nih.gov/pubmed/37425772?dopt=Abstract %R 10.1101/2023.06.28.23291966 %0 Journal Article %J Am J Hum Genet %D 2023 %T Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed whole-genome sequencing study. %A Wang, Yuxuan %A Selvaraj, Margaret Sunitha %A Li, Xihao %A Li, Zilin %A Holdcraft, Jacob A %A Arnett, Donna K %A Bis, Joshua C %A Blangero, John %A Eric Boerwinkle %A Bowden, Donald W %A Cade, Brian E %A Carlson, Jenna C %A Carson, April P %A Chen, Yii-Der Ida %A Curran, Joanne E %A de Vries, Paul S %A Dutcher, Susan K %A Ellinor, Patrick T %A Floyd, James S %A Fornage, Myriam %A Freedman, Barry I %A Gabriel, Stacey %A Germer, Soren %A Richard A Gibbs %A Guo, Xiuqing %A He, Jiang %A Heard-Costa, Nancy %A Hildalgo, Bertha %A Hou, Lifang %A Irvin, Marguerite R %A Joehanes, Roby %A Kaplan, Robert C %A Kardia, Sharon Lr %A Kelly, Tanika N %A Kim, Ryan %A Kooperberg, Charles %A Kral, Brian G %A Levy, Daniel %A Li, Changwei %A Liu, Chunyu %A Lloyd-Jone, Don %A Loos, Ruth Jf %A Mahaney, Michael C %A Martin, Lisa W %A Mathias, Rasika A %A Minster, Ryan L %A Mitchell, Braxton D %A Montasser, May E %A Morrison, Alanna C %A Murabito, Joanne M %A Naseri, Take %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Preuss, Michael H %A Psaty, Bruce M %A Raffield, Laura M %A Rao, Dabeeru C %A Redline, Susan %A Reiner, Alexander P %A Rich, Stephen S %A Ruepena, Muagututi'a Sefuiva %A Sheu, Wayne H-H %A Smith, Jennifer A %A Smith, Albert %A Tiwari, Hemant K %A Tsai, Michael Y %A Viaud-Martinez, Karine A %A Wang, Zhe %A Yanek, Lisa R %A Zhao, Wei %A Rotter, Jerome I %A Lin, Xihong %A Natarajan, Pradeep %A Peloso, Gina M %K Genome-Wide Association Study %K Humans %K Lipids %K Polymorphism, Single Nucleotide %K Precision Medicine %K RNA, Long Noncoding %K Whole Genome Sequencing %X

Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions in lipid metabolism. Large-scale whole-genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess more associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with measurement of blood lipids and lipoproteins (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare-variant aggregate association tests using the STAAR (variant-set test for association using annotation information) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare-coding variants in nearby protein-coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500-kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variation and rare protein-coding variation at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNAs.

%B Am J Hum Genet %V 110 %P 1704-1717 %8 2023 Oct 05 %G eng %N 10 %1 https://www.ncbi.nlm.nih.gov/pubmed/37802043?dopt=Abstract %R 10.1016/j.ajhg.2023.09.003 %0 Journal Article %J bioRxiv %D 2023 %T A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies. %A Li, Xihao %A Chen, Han %A Selvaraj, Margaret Sunitha %A Van Buren, Eric %A Zhou, Hufeng %A Wang, Yuxuan %A Sun, Ryan %A McCaw, Zachary R %A Yu, Zhi %A Arnett, Donna K %A Bis, Joshua C %A Blangero, John %A Eric Boerwinkle %A Bowden, Donald W %A Brody, Jennifer A %A Cade, Brian E %A Carson, April P %A Carlson, Jenna C %A Chami, Nathalie %A Chen, Yii-Der Ida %A Curran, Joanne E %A de Vries, Paul S %A Fornage, Myriam %A Franceschini, Nora %A Freedman, Barry I %A Gu, Charles %A Heard-Costa, Nancy L %A He, Jiang %A Hou, Lifang %A Hung, Yi-Jen %A Irvin, Marguerite R %A Kaplan, Robert C %A Kardia, Sharon L R %A Kelly, Tanika %A Konigsberg, Iain %A Kooperberg, Charles %A Kral, Brian G %A Li, Changwei %A Loos, Ruth J F %A Mahaney, Michael C %A Martin, Lisa W %A Mathias, Rasika A %A Minster, Ryan L %A Mitchell, Braxton D %A Montasser, May E %A Morrison, Alanna C %A Palmer, Nicholette D %A Peyser, Patricia A %A Psaty, Bruce M %A Raffield, Laura M %A Redline, Susan %A Reiner, Alexander P %A Rich, Stephen S %A Sitlani, Colleen M %A Smith, Jennifer A %A Taylor, Kent D %A Tiwari, Hemant %A Vasan, Ramachandran S %A Wang, Zhe %A Yanek, Lisa R %A Yu, Bing %A Rice, Kenneth M %A Rotter, Jerome I %A Peloso, Gina M %A Natarajan, Pradeep %A Li, Zilin %A Liu, Zhonghua %A Lin, Xihong %X

Large-scale whole-genome sequencing (WGS) studies have improved our understanding of the contributions of coding and noncoding rare variants to complex human traits. Leveraging association effect sizes across multiple traits in WGS rare variant association analysis can improve statistical power over single-trait analysis, and also detect pleiotropic genes and regions. Existing multi-trait methods have limited ability to perform rare variant analysis of large-scale WGS data. We propose MultiSTAAR, a statistical framework and computationally-scalable analytical pipeline for functionally-informed multi-trait rare variant analysis in large-scale WGS studies. MultiSTAAR accounts for relatedness, population structure and correlation among phenotypes by jointly analyzing multiple traits, and further empowers rare variant association analysis by incorporating multiple functional annotations. We applied MultiSTAAR to jointly analyze three lipid traits (low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides) in 61,861 multi-ethnic samples from the Trans-Omics for Precision Medicine (TOPMed) Program. We discovered new associations with lipid traits missed by single-trait analysis, including rare variants within an enhancer of and an intergenic region on chromosome 1.

%B bioRxiv %8 2023 Nov 02 %G eng %1 https://www.ncbi.nlm.nih.gov/pubmed/37961350?dopt=Abstract %R 10.1101/2023.10.30.564764 %0 Journal Article %J Circ Genom Precis Med %D 2023 %T Whole Genome Analysis of Venous Thromboembolism: the Trans-Omics for Precision Medicine Program. %A Seyerle, Amanda A %A Laurie, Cecelia A %A Coombes, Brandon J %A Jain, Deepti %A Conomos, Matthew P %A Brody, Jennifer %A Chen, Ming-Huei %A Gogarten, Stephanie M %A Beutel, Kathleen M %A Gupta, Namrata %A Heckbert, Susan R %A Jackson, Rebecca D %A Johnson, Andrew D %A Ko, Darae %A Manson, JoAnn E %A McKnight, Barbara %A Ginger A Metcalf %A Morrison, Alanna C %A Reiner, Alexander P %A Sofer, Tamar %A Tang, Weihong %A Wiggins, Kerri L %A Eric Boerwinkle %A de Andrade, Mariza %A Gabriel, Stacey B %A Richard A Gibbs %A Laurie, Cathy C %A Psaty, Bruce M %A Vasan, Ramachandran S %A Rice, Ken %A Kooperberg, Charles %A Pankow, James S %A Smith, Nicholas L %A Pankratz, Nathan %K Gene Frequency %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Precision Medicine %K Venous Thromboembolism %X

BACKGROUND: Risk for venous thromboembolism has a strong genetic component. Whole genome sequencing from the TOPMed program (Trans-Omics for Precision Medicine) allowed us to look for new associations, particularly rare variants missed by standard genome-wide association studies.

METHODS: The 3793 cases and 7834 controls (11.6% of cases were individuals of African, Hispanic/Latino, or Asian ancestry) were analyzed using a single variant approach and an aggregate gene-based approach using our primary filter (included only loss-of-function and missense variants predicted to be deleterious) and our secondary filter (included all missense variants).

RESULTS: Single variant analyses identified associations at 5 known loci. Aggregate gene-based analyses identified only (odds ratio, 6.2 for carriers of rare variants; =7.4×10) when using our primary filter. Employing our secondary variant filter led to a smaller effect size at (odds ratio, 3.8; =1.6×10), while excluding variants found only in rare isoforms led to a larger one (odds ratio, 7.5). Different filtering strategies improved the signal for 2 other known genes: became significant (minimum =1.8×10 with the secondary filter), while did not (minimum =4.4×10 with minor allele frequency <0.0005). Results were largely the same when restricting the analyses to include only unprovoked cases; however, one novel gene, , became significant (=4.4×10 using all missense variants with minor allele frequency <0.0005).

CONCLUSIONS: Here, we have demonstrated the importance of using multiple variant filtering strategies, as we detected additional genes when filtering variants based on their predicted deleteriousness, frequency, and presence on the most expressed isoforms. Our primary analyses did not identify new candidate loci; thus larger follow-up studies are needed to replicate the novel locus and to identify additional rare variation associated with venous thromboembolism.

%B Circ Genom Precis Med %V 16 %P e003532 %8 2023 Apr %G eng %N 2 %1 https://www.ncbi.nlm.nih.gov/pubmed/36960714?dopt=Abstract %R 10.1161/CIRCGEN.121.003532 %0 Journal Article %J bioRxiv %D 2023 %T Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium. %A Jiang, Min-Zhi %A Gaynor, Sheila M %A Li, Xihao %A Van Buren, Eric %A Stilp, Adrienne %A Buth, Erin %A Wang, Fei Fei %A Manansala, Regina %A Gogarten, Stephanie M %A Li, Zilin %A Polfus, Linda M %A Salimi, Shabnam %A Bis, Joshua C %A Pankratz, Nathan %A Yanek, Lisa R %A Durda, Peter %A Tracy, Russell P %A Rich, Stephen S %A Rotter, Jerome I %A Mitchell, Braxton D %A Lewis, Joshua P %A Psaty, Bruce M %A Pratte, Katherine A %A Silverman, Edwin K %A Kaplan, Robert C %A Avery, Christy %A North, Kari %A Mathias, Rasika A %A Faraday, Nauder %A Lin, Honghuang %A Wang, Biqi %A Carson, April P %A Norwood, Arnita F %A Richard A Gibbs %A Kooperberg, Charles %A Lundin, Jessica %A Peters, Ulrike %A Dupuis, Josée %A Hou, Lifang %A Fornage, Myriam %A Benjamin, Emelia J %A Reiner, Alexander P %A Bowler, Russell P %A Lin, Xihong %A Auer, Paul L %A Raffield, Laura M %X

Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38,465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program. We identified 22 distinct single-variant associations across 6 traits - E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin - that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.

%B bioRxiv %8 2023 Sep 12 %G eng %1 https://www.ncbi.nlm.nih.gov/pubmed/37745480?dopt=Abstract %R 10.1101/2023.09.10.555215 %0 Journal Article %J Hum Mol Genet %D 2023 %T Whole-exome sequencing study identifies four novel gene loci associated with diabetic kidney disease. %A Pan, Yang %A Sun, Xiao %A Mi, Xuenan %A Huang, Zhijie %A Hsu, Yenchih %A Hixson, James E %A Munzy, Donna %A Ginger A Metcalf %A Franceschini, Nora %A Tin, Adrienne %A Köttgen, Anna %A Francis, Michael %A Brody, Jennifer A %A Kestenbaum, Bryan %A Sitlani, Colleen M %A Mychaleckyj, Josyf C %A Kramer, Holly %A Lange, Leslie A %A Guo, Xiuqing %A Hwang, Shih-Jen %A Irvin, Marguerite R %A Smith, Jennifer A %A Yanek, Lisa R %A Vaidya, Dhananjay %A Chen, Yii-Der Ida %A Fornage, Myriam %A Lloyd-Jones, Donald M %A Hou, Lifang %A Mathias, Rasika A %A Mitchell, Braxton D %A Peyser, Patricia A %A Kardia, Sharon L R %A Arnett, Donna K %A Correa, Adolfo %A Raffield, Laura M %A Vasan, Ramachandran S %A Cupple, L Adrienne %A Levy, Daniel %A Kaplan, Robert C %A North, Kari E %A Rotter, Jerome I %A Kooperberg, Charles %A Reiner, Alexander P %A Psaty, Bruce M %A Tracy, Russell P %A Richard A Gibbs %A Morrison, Alanna C %A Feldman, Harold %A Eric Boerwinkle %A He, Jiang %A Kelly, Tanika N %K Aminopeptidases %K Diabetes Mellitus %K Diabetic Nephropathies %K Exome Sequencing %K Humans %K Kidney %K Renal Insufficiency, Chronic %X

Diabetic kidney disease (DKD) is recognized as an important public health challenge. However, its genomic mechanisms are poorly understood. To identify rare variants for DKD, we conducted a whole-exome sequencing (WES) study leveraging large cohorts well-phenotyped for chronic kidney disease and diabetes. Our two-stage WES study included 4372 European and African ancestry participants from the Chronic Renal Insufficiency Cohort and Atherosclerosis Risk in Communities studies (stage 1) and 11 487 multi-ancestry Trans-Omics for Precision Medicine participants (stage 2). Generalized linear mixed models, which accounted for genetic relatedness and adjusted for age, sex and ancestry, were used to test associations between single variants and DKD. Gene-based aggregate rare variant analyses were conducted using an optimized sequence kernel association test implemented within our mixed model framework. We identified four novel exome-wide significant DKD-related loci through initiating diabetes. In single-variant analyses, participants carrying a rare, in-frame insertion in the DIS3L2 gene (rs141560952) exhibited a 193-fold increased odds [95% confidence interval (CI): 33.6, 1105] of DKD compared with noncarriers (P = 3.59 × 10-9). Likewise, each copy of a low-frequency KRT6B splice-site variant (rs425827) conferred a 5.31-fold higher odds (95% CI: 3.06, 9.21) of DKD (P = 2.72 × 10-9). Aggregate gene-based analyses further identified ERAP2 (P = 4.03 × 10-8) and NPEPPS (P = 1.51 × 10-7), which are both expressed in the kidney and implicated in renin-angiotensin-aldosterone system modulated immune response. In the largest WES study of DKD, we identified novel rare variant loci attaining exome-wide significance. These findings provide new insights into the molecular mechanisms underlying DKD.

%B Hum Mol Genet %V 32 %P 1048-1060 %8 2023 Mar 06 %G eng %N 6 %1 https://www.ncbi.nlm.nih.gov/pubmed/36444934?dopt=Abstract %R 10.1093/hmg/ddac290 %0 Journal Article %J Nat Methods %D 2022 %T A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies. %A Li, Zilin %A Li, Xihao %A Zhou, Hufeng %A Gaynor, Sheila M %A Selvaraj, Margaret Sunitha %A Arapoglou, Theodore %A Quick, Corbin %A Liu, Yaowu %A Chen, Han %A Sun, Ryan %A Dey, Rounak %A Arnett, Donna K %A Auer, Paul L %A Bielak, Lawrence F %A Bis, Joshua C %A Blackwell, Thomas W %A Blangero, John %A Eric Boerwinkle %A Bowden, Donald W %A Brody, Jennifer A %A Cade, Brian E %A Conomos, Matthew P %A Correa, Adolfo %A Cupples, L Adrienne %A Curran, Joanne E %A de Vries, Paul S %A Duggirala, Ravindranath %A Franceschini, Nora %A Freedman, Barry I %A Göring, Harald H H %A Guo, Xiuqing %A Kalyani, Rita R %A Kooperberg, Charles %A Kral, Brian G %A Lange, Leslie A %A Lin, Bridget M %A Manichaikul, Ani %A Manning, Alisa K %A Martin, Lisa W %A Mathias, Rasika A %A Meigs, James B %A Mitchell, Braxton D %A Montasser, May E %A Morrison, Alanna C %A Naseri, Take %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Peyser, Patricia A %A Psaty, Bruce M %A Raffield, Laura M %A Redline, Susan %A Reiner, Alexander P %A Reupena, Muagututi'a Sefuiva %A Rice, Kenneth M %A Rich, Stephen S %A Smith, Jennifer A %A Taylor, Kent D %A Taub, Margaret A %A Vasan, Ramachandran S %A Weeks, Daniel E %A Wilson, James G %A Yanek, Lisa R %A Zhao, Wei %A Rotter, Jerome I %A Willer, Cristen J %A Natarajan, Pradeep %A Peloso, Gina M %A Lin, Xihong %K Genetic Variation %K Genome %K Genome-Wide Association Study %K Humans %K Phenotype %K Whole Genome Sequencing %X

Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 TOPMed samples. We also analyze five non-lipid TOPMed traits.

%B Nat Methods %V 19 %P 1599-1611 %8 2022 Dec %G eng %N 12 %1 https://www.ncbi.nlm.nih.gov/pubmed/36303018?dopt=Abstract %R 10.1038/s41592-022-01640-x %0 Journal Article %J Nat Commun %D 2022 %T Genetic analyses of the electrocardiographic QT interval and its components identify additional loci and pathways. %A Young, William J %A Lahrouchi, Najim %A Isaacs, Aaron %A Duong, ThuyVy %A Foco, Luisa %A Ahmed, Farah %A Brody, Jennifer A %A Salman, Reem %A Noordam, Raymond %A Benjamins, Jan-Walter %A Haessler, Jeffrey %A Lyytikäinen, Leo-Pekka %A Repetto, Linda %A Concas, Maria Pina %A van den Berg, Marten E %A Weiss, Stefan %A Baldassari, Antoine R %A Bartz, Traci M %A Cook, James P %A Evans, Daniel S %A Freudling, Rebecca %A Hines, Oliver %A Isaksen, Jonas L %A Lin, Honghuang %A Mei, Hao %A Moscati, Arden %A Müller-Nurasyid, Martina %A Nursyifa, Casia %A Qian, Yong %A Richmond, Anne %A Roselli, Carolina %A Ryan, Kathleen A %A Tarazona-Santos, Eduardo %A Thériault, Sébastien %A van Duijvenboden, Stefan %A Warren, Helen R %A Yao, Jie %A Raza, Dania %A Aeschbacher, Stefanie %A Ahlberg, Gustav %A Alonso, Alvaro %A Andreasen, Laura %A Bis, Joshua C %A Eric Boerwinkle %A Campbell, Archie %A Catamo, Eulalia %A Cocca, Massimiliano %A Cutler, Michael J %A Darbar, Dawood %A De Grandi, Alessandro %A De Luca, Antonio %A Ding, Jun %A Ellervik, Christina %A Ellinor, Patrick T %A Felix, Stephan B %A Froguel, Philippe %A Fuchsberger, Christian %A Gögele, Martin %A Graff, Claus %A Graff, Mariaelisa %A Guo, Xiuqing %A Hansen, Torben %A Heckbert, Susan R %A Huang, Paul L %A Huikuri, Heikki V %A Hutri-Kähönen, Nina %A Ikram, M Arfan %A Jackson, Rebecca D %A Junttila, Juhani %A Kavousi, Maryam %A Kors, Jan A %A Leal, Thiago P %A Lemaitre, Rozenn N %A Lin, Henry J %A Lind, Lars %A Linneberg, Allan %A Liu, Simin %A Macfarlane, Peter W %A Mangino, Massimo %A Meitinger, Thomas %A Mezzavilla, Massimo %A Mishra, Pashupati P %A Mitchell, Rebecca N %A Mononen, Nina %A Montasser, May E %A Morrison, Alanna C %A Nauck, Matthias %A Nauffal, Victor %A Navarro, Pau %A Nikus, Kjell %A Paré, Guillaume %A Patton, Kristen K %A Pelliccione, Giulia %A Pittman, Alan %A Porteous, David J %A Pramstaller, Peter P %A Preuss, Michael H %A Raitakari, Olli T %A Reiner, Alexander P %A Ribeiro, Antonio Luiz P %A Rice, Kenneth M %A Risch, Lorenz %A Schlessinger, David %A Schotten, Ulrich %A Schurmann, Claudia %A Shen, Xia %A Shoemaker, M Benjamin %A Sinagra, Gianfranco %A Sinner, Moritz F %A Soliman, Elsayed Z %A Stoll, Monika %A Strauch, Konstantin %A Tarasov, Kirill %A Taylor, Kent D %A Tinker, Andrew %A Trompet, Stella %A Uitterlinden, Andre %A Völker, Uwe %A Völzke, Henry %A Waldenberger, Melanie %A Weng, Lu-Chen %A Whitsel, Eric A %A Wilson, James G %A Avery, Christy L %A Conen, David %A Correa, Adolfo %A Cucca, Francesco %A Dörr, Marcus %A Gharib, Sina A %A Girotto, Giorgia %A Grarup, Niels %A Hayward, Caroline %A Jamshidi, Yalda %A Jarvelin, Marjo-Riitta %A Jukema, J Wouter %A Kääb, Stefan %A Kähönen, Mika %A Kanters, Jørgen K %A Kooperberg, Charles %A Lehtimäki, Terho %A Lima-Costa, Maria Fernanda %A Liu, Yongmei %A Loos, Ruth J F %A Lubitz, Steven A %A Mook-Kanamori, Dennis O %A Morris, Andrew P %A O'Connell, Jeffrey R %A Olesen, Morten Salling %A Orini, Michele %A Padmanabhan, Sandosh %A Pattaro, Cristian %A Peters, Annette %A Psaty, Bruce M %A Rotter, Jerome I %A Stricker, Bruno %A van der Harst, Pim %A van Duijn, Cornelia M %A Verweij, Niek %A Wilson, James F %A Arking, Dan E %A Ramirez, Julia %A Lambiase, Pier D %A Sotoodehnia, Nona %A Mifsud, Borbala %A Newton-Cheh, Christopher %A Munroe, Patricia B %K Arrhythmias, Cardiac %K Death, Sudden, Cardiac %K Electrocardiography %K Genetic Testing %K Humans %K Male %X

The QT interval is an electrocardiographic measure representing the sum of ventricular depolarization and repolarization, estimated by QRS duration and JT interval, respectively. QT interval abnormalities are associated with potentially fatal ventricular arrhythmia. Using genome-wide multi-ancestry analyses (>250,000 individuals) we identify 177, 156 and 121 independent loci for QT, JT and QRS, respectively, including a male-specific X-chromosome locus. Using gene-based rare-variant methods, we identify associations with Mendelian disease genes. Enrichments are observed in established pathways for QT and JT, and previously unreported genes indicated in insulin-receptor signalling and cardiac energy metabolism. In contrast for QRS, connective tissue components and processes for cell growth and extracellular matrix interactions are significantly enriched. We demonstrate polygenic risk score associations with atrial fibrillation, conduction disease and sudden cardiac death. Prioritization of druggable genes highlight potential therapeutic targets for arrhythmia. Together, these results substantially advance our understanding of the genetic architecture of ventricular depolarization and repolarization.

%B Nat Commun %V 13 %P 5144 %8 2022 Sep 01 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/36050321?dopt=Abstract %R 10.1038/s41467-022-32821-z %0 Journal Article %J Hypertension %D 2022 %T Insights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension. %A Kelly, Tanika N %A Sun, Xiao %A He, Karen Y %A Brown, Michael R %A Taliun, Sarah A Gagliano %A Hellwege, Jacklyn N %A Irvin, Marguerite R %A Mi, Xuenan %A Brody, Jennifer A %A Franceschini, Nora %A Guo, Xiuqing %A Hwang, Shih-Jen %A de Vries, Paul S %A Gao, Yan %A Moscati, Arden %A Nadkarni, Girish N %A Yanek, Lisa R %A Elfassy, Tali %A Smith, Jennifer A %A Chung, Ren-Hua %A Beitelshees, Amber L %A Patki, Amit %A Aslibekyan, Stella %A Blobner, Brandon M %A Peralta, Juan M %A Assimes, Themistocles L %A Palmas, Walter R %A Liu, Chunyu %A Bress, Adam P %A Huang, Zhijie %A Becker, Lewis C %A Hwa, Chii-Min %A O'Connell, Jeffrey R %A Carlson, Jenna C %A Warren, Helen R %A Das, Sayantan %A Giri, Ayush %A Martin, Lisa W %A Craig Johnson, W %A Fox, Ervin R %A Bottinger, Erwin P %A Razavi, Alexander C %A Vaidya, Dhananjay %A Chuang, Lee-Ming %A Chang, Yen-Pei C %A Naseri, Take %A Jain, Deepti %A Kang, Hyun Min %A Hung, Adriana M %A Srinivasasainagendra, Vinodh %A Snively, Beverly M %A Gu, Dongfeng %A Montasser, May E %A Reupena, Muagututi'a Sefuiva %A Heavner, Benjamin D %A LeFaive, Jonathon %A Hixson, James E %A Rice, Kenneth M %A Wang, Fei Fei %A Nielsen, Jonas B %A Huang, Jianfeng %A Khan, Alyna T %A Zhou, Wei %A Nierenberg, Jovia L %A Laurie, Cathy C %A Armstrong, Nicole D %A Shi, Mengyao %A Pan, Yang %A Stilp, Adrienne M %A Emery, Leslie %A Wong, Quenna %A Hawley, Nicola L %A Minster, Ryan L %A Curran, Joanne E %A Munroe, Patricia B %A Weeks, Daniel E %A North, Kari E %A Tracy, Russell P %A Kenny, Eimear E %A Shimbo, Daichi %A Chakravarti, Aravinda %A Rich, Stephen S %A Reiner, Alex P %A Blangero, John %A Redline, Susan %A Mitchell, Braxton D %A Rao, Dabeeru C %A Ida Chen, Yii-Der %A Kardia, Sharon L R %A Kaplan, Robert C %A Mathias, Rasika A %A He, Jiang %A Psaty, Bruce M %A Fornage, Myriam %A Loos, Ruth J F %A Correa, Adolfo %A Eric Boerwinkle %A Rotter, Jerome I %A Kooperberg, Charles %A Edwards, Todd L %A Abecasis, Gonçalo R %A Zhu, Xiaofeng %A Levy, Daniel %A Arnett, Donna K %A Morrison, Alanna C %K Blood Pressure %K Genome-Wide Association Study %K Genomics %K Humans %K Hypertension %K Polymorphism, Single Nucleotide %K Precision Medicine %X

BACKGROUND: The availability of whole-genome sequencing data in large studies has enabled the assessment of coding and noncoding variants across the allele frequency spectrum for their associations with blood pressure.

METHODS: We conducted a multiancestry whole-genome sequencing analysis of blood pressure among 51 456 Trans-Omics for Precision Medicine and Centers for Common Disease Genomics program participants (stage-1). Stage-2 analyses leveraged array data from UK Biobank (N=383 145), Million Veteran Program (N=318 891), and Reasons for Geographic and Racial Differences in Stroke (N=10 643) participants, along with whole-exome sequencing data from UK Biobank (N=199 631) participants.

RESULTS: Two blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings (<5×10). Among them, a rare intergenic variant at novel locus, , was associated with lower systolic blood pressure in stage-1 (beta [SE]=-32.6 [6.0]; =4.99×10) but not stage-2 analysis (=0.11). Furthermore, a novel common variant at the known locus was suggestively associated with diastolic blood pressure in stage-1 (beta [SE]=-0.36 [0.07]; =4.18×10) and attained genome-wide significance in stage-2 (beta [SE]=-0.29 [0.03]; =7.28×10). Nineteen additional signals suggestively associated with blood pressure in meta-analysis of single and aggregate rare variant findings (<1×10 and <1×10, respectively).

DISCUSSION: We report one promising but unconfirmed rare variant for blood pressure and, more importantly, contribute insights for future blood pressure sequencing studies. Our findings suggest promise of aggregate analyses to complement single variant analysis strategies and the need for larger, diverse samples, and family studies to enable robust rare variant identification.

%B Hypertension %V 79 %P 1656-1667 %8 2022 Aug %G eng %N 8 %1 https://www.ncbi.nlm.nih.gov/pubmed/35652341?dopt=Abstract %R 10.1161/HYPERTENSIONAHA.122.19324 %0 Journal Article %J Am J Hum Genet %D 2022 %T Rare coding variants in 35 genes associate with circulating lipid levels-A multi-ancestry analysis of 170,000 exomes. %A Hindy, George %A Dornbos, Peter %A Chaffin, Mark D %A Liu, Dajiang J %A Wang, Minxian %A Selvaraj, Margaret Sunitha %A Zhang, David %A Park, Joseph %A Aguilar-Salinas, Carlos A %A Antonacci-Fulton, Lucinda %A Ardissino, Diego %A Arnett, Donna K %A Aslibekyan, Stella %A Atzmon, Gil %A Ballantyne, Christie M %A Barajas-Olmos, Francisco %A Barzilai, Nir %A Becker, Lewis C %A Bielak, Lawrence F %A Bis, Joshua C %A Blangero, John %A Eric Boerwinkle %A Bonnycastle, Lori L %A Bottinger, Erwin %A Bowden, Donald W %A Bown, Matthew J %A Brody, Jennifer A %A Broome, Jai G %A Burtt, Noël P %A Cade, Brian E %A Centeno-Cruz, Federico %A Chan, Edmund %A Chang, Yi-Cheng %A Chen, Yii-Der I %A Cheng, Ching-Yu %A Choi, Won Jung %A Chowdhury, Rajiv %A Contreras-Cubas, Cecilia %A Córdova, Emilio J %A Correa, Adolfo %A Cupples, L Adrienne %A Curran, Joanne E %A Danesh, John %A de Vries, Paul S %A DeFronzo, Ralph A %A Harshavardhan Doddapaneni %A Duggirala, Ravindranath %A Dutcher, Susan K %A Ellinor, Patrick T %A Emery, Leslie S %A Florez, Jose C %A Fornage, Myriam %A Freedman, Barry I %A Fuster, Valentin %A Garay-Sevilla, Ma Eugenia %A García-Ortiz, Humberto %A Germer, Soren %A Richard A Gibbs %A Gieger, Christian %A Glaser, Benjamin %A Gonzalez, Clicerio %A Gonzalez-Villalpando, Maria Elena %A Graff, Mariaelisa %A Graham, Sarah E %A Grarup, Niels %A Groop, Leif C %A Guo, Xiuqing %A Gupta, Namrata %A Han, Sohee %A Hanis, Craig L %A Hansen, Torben %A He, Jiang %A Heard-Costa, Nancy L %A Hung, Yi-Jen %A Hwang, Mi Yeong %A Irvin, Marguerite R %A Islas-Andrade, Sergio %A Jarvik, Gail P %A Kang, Hyun Min %A Kardia, Sharon L R %A Kelly, Tanika %A Kenny, Eimear E %A Khan, Alyna T %A Kim, Bong-Jo %A Kim, Ryan W %A Kim, Young Jin %A Koistinen, Heikki A %A Kooperberg, Charles %A Kuusisto, Johanna %A Kwak, Soo Heon %A Laakso, Markku %A Lange, Leslie A %A Lee, Jiwon %A Lee, Juyoung %A Lee, Seonwook %A Lehman, Donna M %A Lemaitre, Rozenn N %A Linneberg, Allan %A Liu, Jianjun %A Loos, Ruth J F %A Lubitz, Steven A %A Lyssenko, Valeriya %A Ma, Ronald C W %A Martin, Lisa Warsinger %A Martínez-Hernández, Angélica %A Mathias, Rasika A %A McGarvey, Stephen T %A McPherson, Ruth %A Meigs, James B %A Meitinger, Thomas %A Melander, Olle %A Mendoza-Caamal, Elvia %A Ginger A Metcalf %A Mi, Xuenan %A Mohlke, Karen L %A Montasser, May E %A Moon, Jee-Young %A Moreno-Macias, Hortensia %A Morrison, Alanna C %A Donna M Muzny %A Nelson, Sarah C %A Nilsson, Peter M %A O'Connell, Jeffrey R %A Orho-Melander, Marju %A Orozco, Lorena %A Palmer, Colin N A %A Palmer, Nicholette D %A Park, Cheol Joo %A Park, Kyong Soo %A Pedersen, Oluf %A Peralta, Juan M %A Peyser, Patricia A %A Post, Wendy S %A Preuss, Michael %A Psaty, Bruce M %A Qi, Qibin %A Rao, D C %A Redline, Susan %A Reiner, Alexander P %A Revilla-Monsalve, Cristina %A Rich, Stephen S %A Samani, Nilesh %A Schunkert, Heribert %A Schurmann, Claudia %A Seo, Daekwan %A Seo, Jeong-Sun %A Sim, Xueling %A Sladek, Rob %A Small, Kerrin S %A So, Wing Yee %A Stilp, Adrienne M %A Tai, E Shyong %A Tam, Claudia H T %A Taylor, Kent D %A Teo, Yik Ying %A Thameem, Farook %A Tomlinson, Brian %A Tsai, Michael Y %A Tuomi, Tiinamaija %A Tuomilehto, Jaakko %A Tusie-Luna, Teresa %A Udler, Miriam S %A van Dam, Rob M %A Vasan, Ramachandran S %A Viaud Martinez, Karine A %A Wang, Fei Fei %A Wang, Xuzhi %A Watkins, Hugh %A Weeks, Daniel E %A Wilson, James G %A Witte, Daniel R %A Wong, Tien-Yin %A Yanek, Lisa R %A Kathiresan, Sekar %A Rader, Daniel J %A Rotter, Jerome I %A Boehnke, Michael %A McCarthy, Mark I %A Willer, Cristen J %A Natarajan, Pradeep %A Flannick, Jason A %A Khera, Amit V %A Peloso, Gina M %K Alleles %K Blood Glucose %K Case-Control Studies %K Computational Biology %K Databases, Genetic %K Diabetes Mellitus, Type 2 %K Exome %K Genetic Predisposition to Disease %K Genetic Variation %K Genetics, Population %K Genome-Wide Association Study %K Humans %K Lipid Metabolism %K Lipids %K Liver %K Molecular Sequence Annotation %K Multifactorial Inheritance %K Open Reading Frames %K Phenotype %K Polymorphism, Single Nucleotide %X

Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels.

%B Am J Hum Genet %V 109 %P 81-96 %8 2022 Jan 06 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/34932938?dopt=Abstract %R 10.1016/j.ajhg.2021.11.021 %0 Journal Article %J BMC Genomics %D 2022 %T Rare coding variants in RCN3 are associated with blood pressure. %A He, Karen Y %A Kelly, Tanika N %A Wang, Heming %A Liang, Jingjing %A Zhu, Luke %A Cade, Brian E %A Assimes, Themistocles L %A Becker, Lewis C %A Beitelshees, Amber L %A Bielak, Lawrence F %A Bress, Adam P %A Brody, Jennifer A %A Chang, Yen-Pei Christy %A Chang, Yi-Cheng %A de Vries, Paul S %A Duggirala, Ravindranath %A Fox, Ervin R %A Franceschini, Nora %A Furniss, Anna L %A Gao, Yan %A Guo, Xiuqing %A Haessler, Jeffrey %A Hung, Yi-Jen %A Hwang, Shih-Jen %A Irvin, Marguerite Ryan %A Kalyani, Rita R %A Liu, Ching-Ti %A Liu, Chunyu %A Martin, Lisa Warsinger %A Montasser, May E %A Muntner, Paul M %A Mwasongwe, Stanford %A Naseri, Take %A Palmas, Walter %A Reupena, Muagututi'a Sefuiva %A Rice, Kenneth M %A Sheu, Wayne H-H %A Shimbo, Daichi %A Smith, Jennifer A %A Snively, Beverly M %A Yanek, Lisa R %A Zhao, Wei %A Blangero, John %A Eric Boerwinkle %A Chen, Yii-Der Ida %A Correa, Adolfo %A Cupples, L Adrienne %A Curran, Joanne E %A Fornage, Myriam %A He, Jiang %A Hou, Lifang %A Kaplan, Robert C %A Kardia, Sharon L R %A Kenny, Eimear E %A Kooperberg, Charles %A Lloyd-Jones, Donald %A Loos, Ruth J F %A Mathias, Rasika A %A McGarvey, Stephen T %A Mitchell, Braxton D %A North, Kari E %A Peyser, Patricia A %A Psaty, Bruce M %A Raffield, Laura M %A Rao, D C %A Redline, Susan %A Reiner, Alex P %A Rich, Stephen S %A Rotter, Jerome I %A Taylor, Kent D %A Tracy, Russell %A Vasan, Ramachandran S %A Morrison, Alanna C %A Levy, Daniel %A Chakravarti, Aravinda %A Arnett, Donna K %A Zhu, Xiaofeng %K Blood Pressure %K Genetic Linkage %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Polymorphism, Single Nucleotide %K Precision Medicine %K Whole Genome Sequencing %X

BACKGROUND: While large genome-wide association studies have identified nearly one thousand loci associated with variation in blood pressure, rare variant identification is still a challenge. In family-based cohorts, genome-wide linkage scans have been successful in identifying rare genetic variants for blood pressure. This study aims to identify low frequency and rare genetic variants within previously reported linkage regions on chromosomes 1 and 19 in African American families from the Trans-Omics for Precision Medicine (TOPMed) program. Genetic association analyses weighted by linkage evidence were completed with whole genome sequencing data within and across TOPMed ancestral groups consisting of 60,388 individuals of European, African, East Asian, Hispanic, and Samoan ancestries.

RESULTS: Associations of low frequency and rare variants in RCN3 and multiple other genes were observed for blood pressure traits in TOPMed samples. The association of low frequency and rare coding variants in RCN3 was further replicated in UK Biobank samples (N = 403,522), and reached genome-wide significance for diastolic blood pressure (p = 2.01 × 10).

CONCLUSIONS: Low frequency and rare variants in RCN3 contributes blood pressure variation. This study demonstrates that focusing association analyses in linkage regions greatly reduces multiple-testing burden and improves power to identify novel rare variants associated with blood pressure traits.

%B BMC Genomics %V 23 %P 148 %8 2022 Feb 19 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/35183128?dopt=Abstract %R 10.1186/s12864-022-08356-4 %0 Journal Article %J Hypertension %D 2022 %T Rare Variants in Genes Encoding Subunits of the Epithelial Na Channel Are Associated With Blood Pressure and Kidney Function. %A Blobner, Brandon M %A Kirabo, Annet %A Kashlan, Ossama B %A Sheng, Shaohu %A Arnett, Donna K %A Becker, Lewis C %A Eric Boerwinkle %A Carlson, Jenna C %A Gao, Yan %A Richard A Gibbs %A He, Jiang %A Irvin, Marguerite R %A Kardia, Sharon L R %A Kelly, Tanika N %A Kooperberg, Charles %A McGarvey, Stephen T %A Menon, Vipin K %A Montasser, May E %A Naseri, Take %A Redline, Susan %A Reiner, Alexander P %A Reupena, Muagututi'a S %A Smith, Jennifer A %A Sun, Xiao %A Vaidya, Dhananjay %A Viaud-Martinez, Karine A %A Weeks, Daniel E %A Yanek, Lisa R %A Zhu, Xiaofeng %A Minster, Ryan L %A Kleyman, Thomas R %K Blood Pressure %K Epithelial Sodium Channels %K Humans %K Kidney %K Phenotype %K Sodium %X

BACKGROUND: The epithelial Na channel (ENaC) is intrinsically linked to fluid volume homeostasis and blood pressure. Specific rare mutations in , , and , genes encoding the α, β, and γ subunits of ENaC, respectively, are associated with extreme blood pressure phenotypes. No associations between blood pressure and , which encodes the δ subunit of ENaC, have been reported. A small number of sequence variants in ENaC subunits have been reported to affect functional transport in vitro or blood pressure. The effects of the vast majority of rare and low-frequency ENaC variants on blood pressure are not known.

METHODS: We explored the association of low frequency and rare variants in the genes encoding ENaC subunits, with systolic blood pressure, diastolic blood pressure, mean arterial pressure, and pulse pressure. Using whole-genome sequencing data from 14 studies participating in the Trans-Omics in Precision Medicine Whole-Genome Sequencing Program, and sequence kernel association tests.

RESULTS: We found that variants in and were associated with diastolic blood pressure and mean arterial pressure (<0.00625). Although is poorly expressed in human kidney tissue, variants were associated with systolic blood pressure, diastolic blood pressure, mean arterial pressure, and pulse pressure (<0.00625). ENaC variants in 2 of the 4 subunits ( and ) were also associated with estimated glomerular filtration rate (<0.00625), but not with stroke.

CONCLUSIONS: Our results suggest that variants in extrarenal ENaCs, in addition to ENaCs expressed in kidneys, influence blood pressure and kidney function.

%B Hypertension %V 79 %P 2573-2582 %8 2022 Nov %G eng %N 11 %1 https://www.ncbi.nlm.nih.gov/pubmed/36193739?dopt=Abstract %R 10.1161/HYPERTENSIONAHA.121.18513 %0 Journal Article %J Am J Hum Genet %D 2022 %T TOP-LD: A tool to explore linkage disequilibrium with TOPMed whole-genome sequence data. %A Huang, Le %A Rosen, Jonathan D %A Sun, Quan %A Chen, Jiawen %A Wheeler, Marsha M %A Zhou, Ying %A Min, Yuan-I %A Kooperberg, Charles %A Conomos, Matthew P %A Stilp, Adrienne M %A Rich, Stephen S %A Rotter, Jerome I %A Manichaikul, Ani %A Loos, Ruth J F %A Kenny, Eimear E %A Blackwell, Thomas W %A Smith, Albert V %A Jun, Goo %A Fritz J Sedlazeck %A Ginger A Metcalf %A Eric Boerwinkle %A Raffield, Laura M %A Reiner, Alex P %A Auer, Paul L %A Li, Yun %K Asian People %K Genome-Wide Association Study %K Humans %K Linkage Disequilibrium %K Polymorphism, Single Nucleotide %K Precision Medicine %K Whole Genome Sequencing %X

Current publicly available tools that allow rapid exploration of linkage disequilibrium (LD) between markers (e.g., HaploReg and LDlink) are based on whole-genome sequence (WGS) data from 2,504 individuals in the 1000 Genomes Project. Here, we present TOP-LD, an online tool to explore LD inferred with high-coverage (∼30×) WGS data from 15,578 individuals in the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. TOP-LD provides a significant upgrade compared to current LD tools, as the TOPMed WGS data provide a more comprehensive representation of genetic variation than the 1000 Genomes data, particularly for rare variants and in the specific populations that we analyzed. For example, TOP-LD encompasses LD information for 150.3, 62.2, and 36.7 million variants for European, African, and East Asian ancestral samples, respectively, offering 2.6- to 9.1-fold increase in variant coverage compared to HaploReg 4.0 or LDlink. In addition, TOP-LD includes tens of thousands of structural variants (SVs). We demonstrate the value of TOP-LD in fine-mapping at the GGT1 locus associated with gamma glutamyltransferase in the African ancestry participants in UK Biobank. Beyond fine-mapping, TOP-LD can facilitate a wide range of applications that are based on summary statistics and estimates of LD. TOP-LD is freely available online.

%B Am J Hum Genet %V 109 %P 1175-1181 %8 2022 Jun 02 %G eng %N 6 %1 https://www.ncbi.nlm.nih.gov/pubmed/35504290?dopt=Abstract %R 10.1016/j.ajhg.2022.04.006 %0 Journal Article %J Front Endocrinol (Lausanne) %D 2022 %T The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations. %A Wang, Zhe %A Choi, Shing Wan %A Chami, Nathalie %A Eric Boerwinkle %A Fornage, Myriam %A Redline, Susan %A Bis, Joshua C %A Brody, Jennifer A %A Psaty, Bruce M %A Kim, Wonji %A McDonald, Merry-Lynn N %A Regan, Elizabeth A %A Silverman, Edwin K %A Liu, Ching-Ti %A Vasan, Ramachandran S %A Kalyani, Rita R %A Mathias, Rasika A %A Yanek, Lisa R %A Arnett, Donna K %A Justice, Anne E %A North, Kari E %A Kaplan, Robert %A Heckbert, Susan R %A de Andrade, Mariza %A Guo, Xiuqing %A Lange, Leslie A %A Rich, Stephen S %A Rotter, Jerome I %A Ellinor, Patrick T %A Lubitz, Steven A %A Blangero, John %A Shoemaker, M Benjamin %A Darbar, Dawood %A Gladwin, Mark T %A Albert, Christine M %A Chasman, Daniel I %A Jackson, Rebecca D %A Kooperberg, Charles %A Reiner, Alexander P %A O'Reilly, Paul F %A Loos, Ruth J F %K Gene Frequency %K Genetic Variation %K Genome-Wide Association Study %K Humans %K Obesity %K Whole Genome Sequencing %X

Polygenic risk scores (PRSs) aggregate the effects of genetic variants across the genome and are used to predict risk of complex diseases, such as obesity. Current PRSs only include common variants (minor allele frequency (MAF) ≥1%), whereas the contribution of rare variants in PRSs to predict disease remains unknown. Here, we examine whether augmenting the standard common variant PRS (PRS) with a rare variant PRS (PRS) improves prediction of obesity. We used genome-wide genotyped and imputed data on 451,145 European-ancestry participants of the UK Biobank, as well as whole exome sequencing (WES) data on 184,385 participants. We performed single variant analyses (for both common and rare variants) and gene-based analyses (for rare variants) for association with BMI (kg/m), obesity (BMI ≥ 30 kg/m), and extreme obesity (BMI ≥ 40 kg/m). We built PRSs and PRSs using a range of methods (Clumping+Thresholding [C+T], PRS-CS, lassosum, gene-burden test). We selected the best-performing PRSs and assessed their performance in 36,757 European-ancestry unrelated participants with whole genome sequencing (WGS) data from the Trans-Omics for Precision Medicine (TOPMed) program. The best-performing PRS explained 10.1% of variation in BMI, and 18.3% and 22.5% of the susceptibility to obesity and extreme obesity, respectively, whereas the best-performing PRS explained 1.49%, and 2.97% and 3.68%, respectively. The PRS was associated with an increased risk of obesity and extreme obesity (OR = 1.37 per SD, = 1.7x10; OR = 1.55 per SD, = 3.8x10), which was attenuated, after adjusting for PRS (OR = 1.08 per SD, = 9.8x10; OR= 1.09 per SD, = 0.02). When PRS and PRS are combined, the increase in explained variance attributed to PRS was small (incremental Nagelkerke R = 0.24% for obesity and 0.51% for extreme obesity). Consistently, combining PRS to PRS provided little improvement to the prediction of obesity (PRS AUC = 0.591; PRS AUC = 0.708; PRS AUC = 0.710). In summary, while rare variants show convincing association with BMI, obesity and extreme obesity, the PRS provides limited improvement over PRS in the prediction of obesity risk, based on these large populations.

%B Front Endocrinol (Lausanne) %V 13 %P 863893 %8 2022 %G eng %1 https://www.ncbi.nlm.nih.gov/pubmed/35592775?dopt=Abstract %R 10.3389/fendo.2022.863893 %0 Journal Article %J Nat Commun %D 2022 %T Whole genome sequence analysis of blood lipid levels in >66,000 individuals. %A Selvaraj, Margaret Sunitha %A Li, Xihao %A Li, Zilin %A Pampana, Akhil %A Zhang, David Y %A Park, Joseph %A Aslibekyan, Stella %A Bis, Joshua C %A Brody, Jennifer A %A Cade, Brian E %A Chuang, Lee-Ming %A Chung, Ren-Hua %A Curran, Joanne E %A de Las Fuentes, Lisa %A de Vries, Paul S %A Duggirala, Ravindranath %A Freedman, Barry I %A Graff, Mariaelisa %A Guo, Xiuqing %A Heard-Costa, Nancy %A Hidalgo, Bertha %A Hwu, Chii-Min %A Irvin, Marguerite R %A Kelly, Tanika N %A Kral, Brian G %A Lange, Leslie %A Li, Xiaohui %A Lisa, Martin %A Lubitz, Steven A %A Manichaikul, Ani W %A Michael, Preuss %A Montasser, May E %A Morrison, Alanna C %A Naseri, Take %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Peyser, Patricia A %A Reupena, Muagututia S %A Smith, Jennifer A %A Sun, Xiao %A Taylor, Kent D %A Tracy, Russell P %A Tsai, Michael Y %A Wang, Zhe %A Wang, Yuxuan %A Bao, Wei %A Wilkins, John T %A Yanek, Lisa R %A Zhao, Wei %A Arnett, Donna K %A Blangero, John %A Eric Boerwinkle %A Bowden, Donald W %A Chen, Yii-Der Ida %A Correa, Adolfo %A Cupples, L Adrienne %A Dutcher, Susan K %A Ellinor, Patrick T %A Fornage, Myriam %A Gabriel, Stacey %A Germer, Soren %A Richard A Gibbs %A He, Jiang %A Kaplan, Robert C %A Kardia, Sharon L R %A Kim, Ryan %A Kooperberg, Charles %A Loos, Ruth J F %A Viaud-Martinez, Karine A %A Mathias, Rasika A %A McGarvey, Stephen T %A Mitchell, Braxton D %A Nickerson, Deborah %A North, Kari E %A Psaty, Bruce M %A Redline, Susan %A Reiner, Alexander P %A Vasan, Ramachandran S %A Rich, Stephen S %A Willer, Cristen %A Rotter, Jerome I %A Rader, Daniel J %A Lin, Xihong %A Peloso, Gina M %A Natarajan, Pradeep %K Alleles %K Cholesterol, LDL %K Genome-Wide Association Study %K Humans %K Lipids %K Whole Genome Sequencing %X

Blood lipids are heritable modifiable causal factors for coronary artery disease. Despite well-described monogenic and polygenic bases of dyslipidemia, limitations remain in discovery of lipid-associated alleles using whole genome sequencing (WGS), partly due to limited sample sizes, ancestral diversity, and interpretation of clinical significance. Among 66,329 ancestrally diverse (56% non-European) participants, we associate 428M variants from deep-coverage WGS with lipid levels; ~400M variants were not assessed in prior lipids genetic analyses. We find multiple lipid-related genes strongly associated with blood lipids through analysis of common and rare coding variants. We discover several associated rare non-coding variants, largely at Mendelian lipid genes. Notably, we observe rare LDLR intronic variants associated with markedly increased LDL-C, similar to rare LDLR exonic variants. In conclusion, we conducted a systematic whole genome scan for blood lipids expanding the alleles linked to lipids for multiple ancestries and characterize a clinically-relevant rare non-coding variant model for lipids.

%B Nat Commun %V 13 %P 5995 %8 2022 Oct 11 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/36220816?dopt=Abstract %R 10.1038/s41467-022-33510-7 %0 Journal Article %J Nature %D 2021 %T Author Correction: Inherited causes of clonal haematopoiesis in 97,691 whole genomes. %A Bick, Alexander G %A Weinstock, Joshua S %A Nandakumar, Satish K %A Fulco, Charles P %A Bao, Erik L %A Zekavat, Seyedeh M %A Szeto, Mindy D %A Liao, Xiaotian %A Leventhal, Matthew J %A Nasser, Joseph %A Chang, Kyle %A Laurie, Cecelia %A Burugula, Bala Bharathi %A Gibson, Christopher J %A Niroula, Abhishek %A Lin, Amy E %A Taub, Margaret A %A Aguet, Francois %A Ardlie, Kristin %A Mitchell, Braxton D %A Barnes, Kathleen C %A Moscati, Arden %A Fornage, Myriam %A Redline, Susan %A Psaty, Bruce M %A Silverman, Edwin K %A Weiss, Scott T %A Palmer, Nicholette D %A Vasan, Ramachandran S %A Burchard, Esteban G %A Kardia, Sharon L R %A He, Jiang %A Kaplan, Robert C %A Smith, Nicholas L %A Arnett, Donna K %A Schwartz, David A %A Correa, Adolfo %A de Andrade, Mariza %A Guo, Xiuqing %A Konkle, Barbara A %A Custer, Brian %A Peralta, Juan M %A Gui, Hongsheng %A Meyers, Deborah A %A McGarvey, Stephen T %A Chen, Ida Yii-Der %A Shoemaker, M Benjamin %A Peyser, Patricia A %A Broome, Jai G %A Gogarten, Stephanie M %A Wang, Fei Fei %A Wong, Quenna %A Montasser, May E %A Daya, Michelle %A Kenny, Eimear E %A North, Kari E %A Launer, Lenore J %A Cade, Brian E %A Bis, Joshua C %A Cho, Michael H %A Lasky-Su, Jessica %A Bowden, Donald W %A Cupples, L Adrienne %A Mak, Angel C Y %A Becker, Lewis C %A Smith, Jennifer A %A Kelly, Tanika N %A Aslibekyan, Stella %A Heckbert, Susan R %A Tiwari, Hemant K %A Yang, Ivana V %A Heit, John A %A Lubitz, Steven A %A Johnsen, Jill M %A Curran, Joanne E %A Wenzel, Sally E %A Weeks, Daniel E %A Rao, Dabeeru C %A Darbar, Dawood %A Moon, Jee-Young %A Tracy, Russell P %A Buth, Erin J %A Rafaels, Nicholas %A Loos, Ruth J F %A Durda, Peter %A Liu, Yongmei %A Hou, Lifang %A Lee, Jiwon %A Kachroo, Priyadarshini %A Freedman, Barry I %A Levy, Daniel %A Bielak, Lawrence F %A Hixson, James E %A Floyd, James S %A Whitsel, Eric A %A Ellinor, Patrick T %A Irvin, Marguerite R %A Fingerlin, Tasha E %A Raffield, Laura M %A Armasu, Sebastian M %A Wheeler, Marsha M %A Sabino, Ester C %A Blangero, John %A Williams, L Keoki %A Levy, Bruce D %A Sheu, Wayne Huey-Herng %A Roden, Dan M %A Eric Boerwinkle %A Manson, JoAnn E %A Mathias, Rasika A %A Desai, Pinkal %A Taylor, Kent D %A Johnson, Andrew D %A Auer, Paul L %A Kooperberg, Charles %A Laurie, Cathy C %A Blackwell, Thomas W %A Smith, Albert V %A Zhao, Hongyu %A Lange, Ethan %A Lange, Leslie %A Rich, Stephen S %A Rotter, Jerome I %A Wilson, James G %A Scheet, Paul %A Kitzman, Jacob O %A Lander, Eric S %A Engreitz, Jesse M %A Ebert, Benjamin L %A Reiner, Alexander P %A Jaiswal, Siddhartha %A Abecasis, Goncalo %A Sankaran, Vijay G %A Kathiresan, Sekar %A Natarajan, Pradeep %B Nature %V 591 %P E27 %8 2021 Mar %G eng %N 7851 %1 https://www.ncbi.nlm.nih.gov/pubmed/33707633?dopt=Abstract %R 10.1038/s41586-021-03280-1 %0 Journal Article %J HGG Adv %D 2021 %T BinomiRare: A robust test for association of a rare genetic variant with a binary outcome for mixed models and any case-control proportion. %A Sofer, Tamar %A Lee, Jiwon %A Kurniansyah, Nuzulul %A Jain, Deepti %A Laurie, Cecelia A %A Gogarten, Stephanie M %A Conomos, Matthew P %A Heavner, Ben %A Hu, Yao %A Kooperberg, Charles %A Haessler, Jeffrey %A Vasan, Ramachandran S %A Cupples, L Adrienne %A Coombes, Brandon J %A Seyerle, Amanda %A Gharib, Sina A %A Chen, Han %A O'Connell, Jeffrey R %A Zhang, Man %A Gottlieb, Daniel J %A Psaty, Bruce M %A Longstreth, W T %A Rotter, Jerome I %A Taylor, Kent D %A Rich, Stephen S %A Guo, Xiuqing %A Eric Boerwinkle %A Morrison, Alanna C %A Pankow, James S %A Johnson, Andrew D %A Pankratz, Nathan %A Reiner, Alex P %A Redline, Susan %A Smith, Nicholas L %A Rice, Kenneth M %A Schifano, Elizabeth D %X

Whole-genome sequencing (WGS) and whole-exome sequencing studies have become increasingly available and are being used to identify rare genetic variants associated with health and disease outcomes. Investigators routinely use mixed models to account for genetic relatedness or other clustering variables (e.g., family or household) when testing genetic associations. However, no existing tests of the association of a rare variant with a binary outcome in the presence of correlated data control the type 1 error where there are (1) few individuals harboring the rare allele, (2) a small proportion of cases relative to controls, and (3) covariates to adjust for. Here, we address all three issues in developing a framework for testing rare variant association with a binary trait in individuals harboring at least one risk allele. In this framework, we estimate outcome probabilities under the null hypothesis and then use them, within the individuals with at least one risk allele, to test variant associations. We extend the BinomiRare test, which was previously proposed for independent observations, and develop the Conway-Maxwell-Poisson (CMP) test and study their properties in simulations. We show that the BinomiRare test always controls the type 1 error, while the CMP test sometimes does not. We then use the BinomiRare test to test the association of rare genetic variants in target genes with small-vessel disease (SVD) stroke, short sleep, and venous thromboembolism (VTE), in whole-genome sequence data from the Trans-Omics for Precision Medicine (TOPMed) program.

%B HGG Adv %V 2 %8 2021 Jul 08 %G eng %N 3 %1 https://www.ncbi.nlm.nih.gov/pubmed/34337551?dopt=Abstract %R 10.1016/j.xhgg.2021.100040 %0 Journal Article %J Nat Commun %D 2021 %T Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices. %A Natarajan, Pradeep %A Pampana, Akhil %A Graham, Sarah E %A Ruotsalainen, Sanni E %A Perry, James A %A de Vries, Paul S %A Broome, Jai G %A Pirruccello, James P %A Honigberg, Michael C %A Aragam, Krishna %A Wolford, Brooke %A Brody, Jennifer A %A Antonacci-Fulton, Lucinda %A Arden, Moscati %A Aslibekyan, Stella %A Assimes, Themistocles L %A Ballantyne, Christie M %A Bielak, Lawrence F %A Bis, Joshua C %A Cade, Brian E %A Do, Ron %A Harshavardhan Doddapaneni %A Emery, Leslie S %A Hung, Yi-Jen %A Irvin, Marguerite R %A Khan, Alyna T %A Lange, Leslie %A Lee, Jiwon %A Lemaitre, Rozenn N %A Martin, Lisa W %A Ginger A Metcalf %A Montasser, May E %A Moon, Jee-Young %A Donna M Muzny %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Peralta, Juan M %A Peyser, Patricia A %A Stilp, Adrienne M %A Tsai, Michael %A Wang, Fei Fei %A Weeks, Daniel E %A Yanek, Lisa R %A Wilson, James G %A Abecasis, Goncalo %A Arnett, Donna K %A Becker, Lewis C %A Blangero, John %A Eric Boerwinkle %A Bowden, Donald W %A Chang, Yi-Cheng %A Chen, Yii-Der I %A Choi, Won Jung %A Correa, Adolfo %A Curran, Joanne E %A Daly, Mark J %A Dutcher, Susan K %A Ellinor, Patrick T %A Fornage, Myriam %A Freedman, Barry I %A Gabriel, Stacey %A Germer, Soren %A Richard A Gibbs %A He, Jiang %A Hveem, Kristian %A Jarvik, Gail P %A Kaplan, Robert C %A Kardia, Sharon L R %A Kenny, Eimear %A Kim, Ryan W %A Kooperberg, Charles %A Laurie, Cathy C %A Lee, Seonwook %A Lloyd-Jones, Don M %A Loos, Ruth J F %A Lubitz, Steven A %A Mathias, Rasika A %A Martinez, Karine A Viaud %A McGarvey, Stephen T %A Mitchell, Braxton D %A Nickerson, Deborah A %A North, Kari E %A Palotie, Aarno %A Park, Cheol Joo %A Psaty, Bruce M %A Rao, D C %A Redline, Susan %A Reiner, Alexander P %A Seo, Daekwan %A Seo, Jeong-Sun %A Smith, Albert V %A Tracy, Russell P %A Vasan, Ramachandran S %A Kathiresan, Sekar %A Cupples, L Adrienne %A Rotter, Jerome I %A Morrison, Alanna C %A Rich, Stephen S %A Ripatti, Samuli %A Willer, Cristen %A Peloso, Gina M %K Cardiometabolic Risk Factors %K Chromosomes, Human, X %K Eye Proteins %K Female %K Gene Expression Regulation %K Genetic Association Studies %K Genetic Loci %K Genetic Predisposition to Disease %K Genotype %K Humans %K Lipids %K Male %K Middle Aged %K Nerve Tissue Proteins %K Phenomics %K Polymorphism, Single Nucleotide %K Subcutaneous Tissue %K Whole Genome Sequencing %X

Autosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids.

%B Nat Commun %V 12 %P 2182 %8 2021 Apr 12 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/33846329?dopt=Abstract %R 10.1038/s41467-021-22339-1 %0 Journal Article %J Hum Mol Genet %D 2021 %T Epigenome-wide association study of mitochondrial genome copy number. %A Wang, Penglong %A Castellani, Christina A %A Yao, Jie %A Huan, Tianxiao %A Bielak, Lawrence F %A Zhao, Wei %A Haessler, Jeffrey %A Joehanes, Roby %A Sun, Xianbang %A Guo, Xiuqing %A Longchamps, Ryan J %A Manson, JoAnn E %A Grove, Megan L %A Bressler, Jan %A Taylor, Kent D %A Lappalainen, Tuuli %A Kasela, Silva %A Van Den Berg, David J %A Hou, Lifang %A Reiner, Alexander %A Liu, Yongmei %A Eric Boerwinkle %A Smith, Jennifer A %A Peyser, Patricia A %A Fornage, Myriam %A Rich, Stephen S %A Rotter, Jerome I %A Kooperberg, Charles %A Arking, Dan E %A Levy, Daniel %A Liu, Chunyu %K Aged %K DNA Copy Number Variations %K DNA Methylation %K DNA, Mitochondrial %K Epigenome %K Female %K Genome, Mitochondrial %K Humans %K Male %K Middle Aged %X

We conducted cohort- and race-specific epigenome-wide association analyses of mitochondrial deoxyribonucleic acid (mtDNA) copy number (mtDNA CN) measured in whole blood from participants of African and European origins in five cohorts (n = 6182, mean age = 57-67 years, 65% women). In the meta-analysis of all the participants, we discovered 21 mtDNA CN-associated DNA methylation sites (CpG) (P < 1 × 10-7), with a 0.7-3.0 standard deviation increase (3 CpGs) or decrease (18 CpGs) in mtDNA CN corresponding to a 1% increase in DNA methylation. Several significant CpGs have been reported to be associated with at least two risk factors (e.g. chronological age or smoking) for cardiovascular disease (CVD). Five genes [PR/SET domain 16, nuclear receptor subfamily 1 group H member 3 (NR1H3), DNA repair protein, DNA polymerase kappa and decaprenyl-diphosphate synthase subunit 2], which harbor nine significant CpGs, are known to be involved in mitochondrial biosynthesis and functions. For example, NR1H3 encodes a transcription factor that is differentially expressed during an adipose tissue transition. The methylation level of cg09548275 in NR1H3 was negatively associated with mtDNA CN (effect size = -1.71, P = 4 × 10-8) and was positively associated with the NR1H3 expression level (effect size = 0.43, P = 0.0003), which indicates that the methylation level in NR1H3 may underlie the relationship between mtDNA CN, the NR1H3 transcription factor and energy expenditure. In summary, the study results suggest that mtDNA CN variation in whole blood is associated with DNA methylation levels in genes that are involved in a wide range of mitochondrial activities. These findings will help reveal molecular mechanisms between mtDNA CN and CVD.

%B Hum Mol Genet %V 31 %P 309-319 %8 2021 Dec 27 %G eng %N 2 %1 https://www.ncbi.nlm.nih.gov/pubmed/34415308?dopt=Abstract %R 10.1093/hmg/ddab240 %0 Journal Article %J HGG Adv %D 2021 %T Multi-Ancestry Genome-wide Association Study Accounting for Gene-Psychosocial Factor Interactions Identifies Novel Loci for Blood Pressure Traits. %A Sun, Daokun %A Richard, Melissa %A Musani, Solomon K %A Sung, Yun Ju %A Winkler, Thomas W %A Schwander, Karen %A Chai, Jin Fang %A Guo, Xiuqing %A Kilpeläinen, Tuomas O %A Vojinovic, Dina %A Aschard, Hugues %A Bartz, Traci M %A Bielak, Lawrence F %A Brown, Michael R %A Chitrala, Kumaraswamy %A Hartwig, Fernando P %A Horimoto, Andrea R V R %A Liu, Yongmei %A Manning, Alisa K %A Noordam, Raymond %A Smith, Albert V %A Harris, Sarah E %A Kühnel, Brigitte %A Lyytikäinen, Leo-Pekka %A Nolte, Ilja M %A Rauramaa, Rainer %A van der Most, Peter J %A Wang, Rujia %A Ware, Erin B %A Weiss, Stefan %A Wen, Wanqing %A Yanek, Lisa R %A Arking, Dan E %A Arnett, Donna K %A Barac, Ana %A Eric Boerwinkle %A Broeckel, Ulrich %A Chakravarti, Aravinda %A Chen, Yii-Der Ida %A Cupples, L Adrienne %A Davigulus, Martha L %A de Las Fuentes, Lisa %A de Mutsert, Renée %A de Vries, Paul S %A Delaney, Joseph A C %A Roux, Ana V Diez %A Dörr, Marcus %A Faul, Jessica D %A Fretts, Amanda M %A Gallo, Linda C %A Grabe, Hans Jörgen %A Gu, C Charles %A Harris, Tamara B %A Hartman, Catharina C A %A Heikkinen, Sami %A Ikram, M Arfan %A Isasi, Carmen %A Johnson, W Craig %A Jonas, Jost Bruno %A Kaplan, Robert C %A Komulainen, Pirjo %A Krieger, Jose E %A Levy, Daniel %A Liu, Jianjun %A Lohman, Kurt %A Luik, Annemarie I %A Martin, Lisa W %A Meitinger, Thomas %A Milaneschi, Yuri %A O'Connell, Jeff R %A Palmas, Walter R %A Peters, Annette %A Peyser, Patricia A %A Pulkki-Råback, Laura %A Raffel, Leslie J %A Reiner, Alex P %A Rice, Kenneth %A Robinson, Jennifer G %A Rosendaal, Frits R %A Schmidt, Carsten Oliver %A Schreiner, Pamela J %A Schwettmann, Lars %A Shikany, James M %A Shu, Xiao-Ou %A Sidney, Stephen %A Sims, Mario %A Smith, Jennifer A %A Sotoodehnia, Nona %A Strauch, Konstantin %A Tai, E Shyong %A Taylor, Kent %A Uitterlinden, André G %A van Duijn, Cornelia M %A Waldenberger, Melanie %A Wee, Hwee-Lin %A Wei, Wen-Bin %A Wilson, Gregory %A Xuan, Deng %A Yao, Jie %A Zeng, Donglin %A Zhao, Wei %A Zhu, Xiaofeng %A Zonderman, Alan B %A Becker, Diane M %A Deary, Ian J %A Gieger, Christian %A Lakka, Timo A %A Lehtimäki, Terho %A North, Kari E %A Oldehinkel, Albertine J %A Penninx, Brenda W J H %A Snieder, Harold %A Wang, Ya-Xing %A Weir, David R %A Zheng, Wei %A Evans, Michele K %A Gauderman, W James %A Gudnason, Vilmundur %A Horta, Bernardo L %A Liu, Ching-Ti %A Mook-Kanamori, Dennis O %A Morrison, Alanna C %A Pereira, Alexandre C %A Psaty, Bruce M %A Amin, Najaf %A Fox, Ervin R %A Kooperberg, Charles %A Sim, Xueling %A Bierut, Laura %A Rotter, Jerome I %A Kardia, Sharon L R %A Franceschini, Nora %A Rao, Dabeeru C %A Fornage, Myriam %X

Psychological and social factors are known to influence blood pressure (BP) and risk of hypertension and associated cardiovascular diseases. To identify novel BP loci, we carried out genome-wide association meta-analyses of systolic, diastolic, pulse, and mean arterial BP taking into account the interaction effects of genetic variants with three psychosocial factors: depressive symptoms, anxiety symptoms, and social support. Analyses were performed using a two-stage design in a sample of up to 128,894 adults from 5 ancestry groups. In the combined meta-analyses of Stages 1 and 2, we identified 59 loci (p value <5e-8), including nine novel BP loci. The novel associations were observed mostly with pulse pressure, with fewer observed with mean arterial pressure. Five novel loci were identified in African ancestry, and all but one showed patterns of interaction with at least one psychosocial factor. Functional annotation of the novel loci supports a major role for genes implicated in the immune response (), synaptic function and neurotransmission (), as well as genes previously implicated in neuropsychiatric or stress-related disorders (). These findings underscore the importance of considering psychological and social factors in gene discovery for BP, especially in non-European populations.

%B HGG Adv %V 2 %8 2021 Jan 14 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/34734193?dopt=Abstract %R 10.1016/j.xhgg.2020.100013 %0 Journal Article %J Mol Psychiatry %D 2021 %T Multi-ancestry genome-wide gene-sleep interactions identify novel loci for blood pressure. %A Wang, Heming %A Noordam, Raymond %A Cade, Brian E %A Schwander, Karen %A Winkler, Thomas W %A Lee, Jiwon %A Sung, Yun Ju %A Bentley, Amy R %A Manning, Alisa K %A Aschard, Hugues %A Kilpeläinen, Tuomas O %A Ilkov, Marjan %A Brown, Michael R %A Horimoto, Andrea R %A Richard, Melissa %A Bartz, Traci M %A Vojinovic, Dina %A Lim, Elise %A Nierenberg, Jovia L %A Liu, Yongmei %A Chitrala, Kumaraswamynaidu %A Rankinen, Tuomo %A Musani, Solomon K %A Franceschini, Nora %A Rauramaa, Rainer %A Alver, Maris %A Zee, Phyllis C %A Harris, Sarah E %A van der Most, Peter J %A Nolte, Ilja M %A Munroe, Patricia B %A Palmer, Nicholette D %A Kühnel, Brigitte %A Weiss, Stefan %A Wen, Wanqing %A Hall, Kelly A %A Lyytikäinen, Leo-Pekka %A O'Connell, Jeff %A Eiriksdottir, Gudny %A Launer, Lenore J %A de Vries, Paul S %A Arking, Dan E %A Chen, Han %A Eric Boerwinkle %A Krieger, Jose E %A Schreiner, Pamela J %A Sidney, Stephen %A Shikany, James M %A Rice, Kenneth %A Chen, Yii-Der Ida %A Gharib, Sina A %A Bis, Joshua C %A Luik, Annemarie I %A Ikram, M Arfan %A Uitterlinden, André G %A Amin, Najaf %A Xu, Hanfei %A Levy, Daniel %A He, Jiang %A Lohman, Kurt K %A Zonderman, Alan B %A Rice, Treva K %A Sims, Mario %A Wilson, Gregory %A Sofer, Tamar %A Rich, Stephen S %A Palmas, Walter %A Yao, Jie %A Guo, Xiuqing %A Rotter, Jerome I %A Biermasz, Nienke R %A Mook-Kanamori, Dennis O %A Martin, Lisa W %A Barac, Ana %A Wallace, Robert B %A Gottlieb, Daniel J %A Komulainen, Pirjo %A Heikkinen, Sami %A Mägi, Reedik %A Milani, Lili %A Metspalu, Andres %A Starr, John M %A Milaneschi, Yuri %A Waken, R J %A Gao, Chuan %A Waldenberger, Melanie %A Peters, Annette %A Strauch, Konstantin %A Meitinger, Thomas %A Roenneberg, Till %A Völker, Uwe %A Dörr, Marcus %A Shu, Xiao-Ou %A Mukherjee, Sutapa %A Hillman, David R %A Kähönen, Mika %A Wagenknecht, Lynne E %A Gieger, Christian %A Grabe, Hans J %A Zheng, Wei %A Palmer, Lyle J %A Lehtimäki, Terho %A Gudnason, Vilmundur %A Morrison, Alanna C %A Pereira, Alexandre C %A Fornage, Myriam %A Psaty, Bruce M %A van Duijn, Cornelia M %A Liu, Ching-Ti %A Kelly, Tanika N %A Evans, Michele K %A Bouchard, Claude %A Fox, Ervin R %A Kooperberg, Charles %A Zhu, Xiaofeng %A Lakka, Timo A %A Esko, Tõnu %A North, Kari E %A Deary, Ian J %A Snieder, Harold %A Penninx, Brenda W J H %A Gauderman, W James %A Rao, Dabeeru C %A Redline, Susan %A van Heemst, Diana %K Blood Pressure %K Genetic Loci %K Genome-Wide Association Study %K Humans %K Hypertension %K Polymorphism, Single Nucleotide %K Sleep %X

Long and short sleep duration are associated with elevated blood pressure (BP), possibly through effects on molecular pathways that influence neuroendocrine and vascular systems. To gain new insights into the genetic basis of sleep-related BP variation, we performed genome-wide gene by short or long sleep duration interaction analyses on four BP traits (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure) across five ancestry groups in two stages using 2 degree of freedom (df) joint test followed by 1df test of interaction effects. Primary multi-ancestry analysis in 62,969 individuals in stage 1 identified three novel gene by sleep interactions that were replicated in an additional 59,296 individuals in stage 2 (stage 1 + 2 P < 5 × 10), including rs7955964 (FIGNL2/ANKRD33) that increases BP among long sleepers, and rs73493041 (SNORA26/C9orf170) and rs10406644 (KCTD15/LSM14A) that increase BP among short sleepers (P < 5 × 10). Secondary ancestry-specific analysis identified another novel gene by long sleep interaction at rs111887471 (TRPC3/KIAA1109) in individuals of African ancestry (P = 2 × 10). Combined stage 1 and 2 analyses additionally identified significant gene by long sleep interactions at 10 loci including MKLN1 and RGL3/ELAVL3 previously associated with BP, and significant gene by short sleep interactions at 10 loci including C2orf43 previously associated with BP (P < 10). 2df test also identified novel loci for BP after modeling sleep that has known functions in sleep-wake regulation, nervous and cardiometabolic systems. This study indicates that sleep and primary mechanisms regulating BP may interact to elevate BP level, suggesting novel insights into sleep-related BP regulation.

%B Mol Psychiatry %V 26 %P 6293-6304 %8 2021 Nov %G eng %N 11 %1 https://www.ncbi.nlm.nih.gov/pubmed/33859359?dopt=Abstract %R 10.1038/s41380-021-01087-0 %0 Journal Article %J Nat Genet %D 2021 %T Publisher Correction: Discovery of rare variants associated with blood pressure regulation through meta-analysis of 1.3 million individuals. %A Surendran, Praveen %A Feofanova, Elena V %A Lahrouchi, Najim %A Ntalla, Ioanna %A Karthikeyan, Savita %A Cook, James %A Chen, Lingyan %A Mifsud, Borbala %A Yao, Chen %A Kraja, Aldi T %A Cartwright, James H %A Hellwege, Jacklyn N %A Giri, Ayush %A Tragante, Vinicius %A Thorleifsson, Gudmar %A Liu, Dajiang J %A Prins, Bram P %A Stewart, Isobel D %A Cabrera, Claudia P %A Eales, James M %A Akbarov, Artur %A Auer, Paul L %A Bielak, Lawrence F %A Bis, Joshua C %A Braithwaite, Vickie S %A Brody, Jennifer A %A Daw, E Warwick %A Warren, Helen R %A Drenos, Fotios %A Nielsen, Sune Fallgaard %A Faul, Jessica D %A Fauman, Eric B %A Fava, Cristiano %A Ferreira, Teresa %A Foley, Christopher N %A Franceschini, Nora %A Gao, He %A Giannakopoulou, Olga %A Giulianini, Franco %A Gudbjartsson, Daniel F %A Guo, Xiuqing %A Harris, Sarah E %A Havulinna, Aki S %A Helgadottir, Anna %A Huffman, Jennifer E %A Hwang, Shih-Jen %A Kanoni, Stavroula %A Kontto, Jukka %A Larson, Martin G %A Li-Gao, Ruifang %A Lindström, Jaana %A Lotta, Luca A %A Lu, Yingchang %A Luan, Jian'an %A Mahajan, Anubha %A Malerba, Giovanni %A Masca, Nicholas G D %A Mei, Hao %A Menni, Cristina %A Mook-Kanamori, Dennis O %A Mosen-Ansorena, David %A Müller-Nurasyid, Martina %A Paré, Guillaume %A Paul, Dirk S %A Perola, Markus %A Poveda, Alaitz %A Rauramaa, Rainer %A Richard, Melissa %A Richardson, Tom G %A Sepúlveda, Nuno %A Sim, Xueling %A Smith, Albert V %A Smith, Jennifer A %A Staley, James R %A Stanáková, Alena %A Sulem, Patrick %A Thériault, Sébastien %A Thorsteinsdottir, Unnur %A Trompet, Stella %A Varga, Tibor V %A Velez Edwards, Digna R %A Veronesi, Giovanni %A Weiss, Stefan %A Willems, Sara M %A Yao, Jie %A Young, Robin %A Yu, Bing %A Zhang, Weihua %A Zhao, Jing-Hua %A Zhao, Wei %A Zhao, Wei %A Evangelou, Evangelos %A Aeschbacher, Stefanie %A Asllanaj, Eralda %A Blankenberg, Stefan %A Bonnycastle, Lori L %A Bork-Jensen, Jette %A Brandslund, Ivan %A Braund, Peter S %A Burgess, Stephen %A Cho, Kelly %A Christensen, Cramer %A Connell, John %A Mutsert, Renée de %A Dominiczak, Anna F %A Dörr, Marcus %A Eiriksdottir, Gudny %A Farmaki, Aliki-Eleni %A Gaziano, J Michael %A Grarup, Niels %A Grove, Megan L %A Hallmans, Goran %A Hansen, Torben %A Have, Christian T %A Heiss, Gerardo %A Jørgensen, Marit E %A Jousilahti, Pekka %A Kajantie, Eero %A Kamat, Mihir %A Käräjämäki, Annemari %A Karpe, Fredrik %A Koistinen, Heikki A %A Kovesdy, Csaba P %A Kuulasmaa, Kari %A Laatikainen, Tiina %A Lannfelt, Lars %A Lee, I-Te %A Lee, Wen-Jane %A Linneberg, Allan %A Martin, Lisa W %A Moitry, Marie %A Nadkarni, Girish %A Neville, Matt J %A Palmer, Colin N A %A Papanicolaou, George J %A Pedersen, Oluf %A Peters, James %A Poulter, Neil %A Rasheed, Asif %A Rasmussen, Katrine L %A Rayner, N William %A Mägi, Reedik %A Renstrom, Frida %A Rettig, Rainer %A Rossouw, Jacques %A Schreiner, Pamela J %A Sever, Peter S %A Sigurdsson, Emil L %A Skaaby, Tea %A Sun, Yan V %A Sundström, Johan %A Thorgeirsson, Gudmundur %A Esko, Tõnu %A Trabetti, Elisabetta %A Tsao, Philip S %A Tuomi, Tiinamaija %A Turner, Stephen T %A Tzoulaki, Ioanna %A Vaartjes, Ilonca %A Vergnaud, Anne-Claire %A Willer, Cristen J %A Wilson, Peter W F %A Witte, Daniel R %A Yonova-Doing, Ekaterina %A Zhang, He %A Aliya, Naheed %A Almgren, Peter %A Amouyel, Philippe %A Asselbergs, Folkert W %A Barnes, Michael R %A Blakemore, Alexandra I %A Boehnke, Michael %A Bots, Michiel L %A Bottinger, Erwin P %A Buring, Julie E %A Chambers, John C %A Chen, Yii-Der Ida %A Chowdhury, Rajiv %A Conen, David %A Correa, Adolfo %A Davey Smith, George %A Boer, Rudolf A de %A Deary, Ian J %A Dedoussis, George %A Deloukas, Panos %A Di Angelantonio, Emanuele %A Elliott, Paul %A Felix, Stephan B %A Ferrieres, Jean %A Ford, Ian %A Fornage, Myriam %A Franks, Paul W %A Franks, Stephen %A Frossard, Philippe %A Gambaro, Giovanni %A Gaunt, Tom R %A Groop, Leif %A Gudnason, Vilmundur %A Harris, Tamara B %A Hayward, Caroline %A Hennig, Branwen J %A Herzig, Karl-Heinz %A Ingelsson, Erik %A Tuomilehto, Jaakko %A Jarvelin, Marjo-Riitta %A Jukema, J Wouter %A Kardia, Sharon L R %A Kee, Frank %A Kooner, Jaspal S %A Kooperberg, Charles %A Launer, Lenore J %A Lind, Lars %A Loos, Ruth J F %A Majumder, Abdulla Al Shafi %A Laakso, Markku %A McCarthy, Mark I %A Melander, Olle %A Mohlke, Karen L %A Murray, Alison D %A Nordestgaard, Børge Grønne %A Orho-Melander, Marju %A Packard, Chris J %A Padmanabhan, Sandosh %A Palmas, Walter %A Polasek, Ozren %A Porteous, David J %A Prentice, Andrew M %A Province, Michael A %A Relton, Caroline L %A Rice, Kenneth %A Ridker, Paul M %A Rolandsson, Olov %A Rosendaal, Frits R %A Rotter, Jerome I %A Rudan, Igor %A Salomaa, Veikko %A Samani, Nilesh J %A Sattar, Naveed %A Sheu, Wayne H-H %A Smith, Blair H %A Soranzo, Nicole %A Spector, Timothy D %A Starr, John M %A Sebert, Sylvain %A Taylor, Kent D %A Lakka, Timo A %A Timpson, Nicholas J %A Tobin, Martin D %A van der Harst, Pim %A van der Meer, Peter %A Ramachandran, Vasan S %A Verweij, Niek %A Virtamo, Jarmo %A Völker, Uwe %A Weir, David R %A Zeggini, Eleftheria %A Charchar, Fadi J %A Wareham, Nicholas J %A Langenberg, Claudia %A Tomaszewski, Maciej %A Butterworth, Adam S %A Caulfield, Mark J %A Danesh, John %A Edwards, Todd L %A Holm, Hilma %A Hung, Adriana M %A Lindgren, Cecilia M %A Liu, Chunyu %A Manning, Alisa K %A Morris, Andrew P %A Morrison, Alanna C %A O'Donnell, Christopher J %A Psaty, Bruce M %A Saleheen, Danish %A Stefansson, Kari %A Eric Boerwinkle %A Chasman, Daniel I %A Levy, Daniel %A Newton-Cheh, Christopher %A Munroe, Patricia B %A Howson, Joanna M M %B Nat Genet %V 53 %P 762 %8 2021 May %G eng %N 5 %1 https://www.ncbi.nlm.nih.gov/pubmed/33727701?dopt=Abstract %R 10.1038/s41588-021-00832-z %0 Journal Article %J Genetics %D 2021 %T Robust, flexible, and scalable tests for Hardy-Weinberg equilibrium across diverse ancestries. %A Kwong, Alan M %A Blackwell, Thomas W %A LeFaive, Jonathon %A de Andrade, Mariza %A Barnard, John %A Barnes, Kathleen C %A Blangero, John %A Eric Boerwinkle %A Burchard, Esteban G %A Cade, Brian E %A Chasman, Daniel I %A Chen, Han %A Conomos, Matthew P %A Cupples, L Adrienne %A Ellinor, Patrick T %A Eng, Celeste %A Gao, Yan %A Guo, Xiuqing %A Irvin, Marguerite Ryan %A Kelly, Tanika N %A Kim, Wonji %A Kooperberg, Charles %A Lubitz, Steven A %A Mak, Angel C Y %A Manichaikul, Ani W %A Mathias, Rasika A %A Montasser, May E %A Montgomery, Courtney G %A Musani, Solomon %A Palmer, Nicholette D %A Peloso, Gina M %A Qiao, Dandi %A Reiner, Alexander P %A Roden, Dan M %A Shoemaker, M Benjamin %A Smith, Jennifer A %A Smith, Nicholas L %A Su, Jessica Lasky %A Tiwari, Hemant K %A Weeks, Daniel E %A Weiss, Scott T %A Scott, Laura J %A Smith, Albert V %A Abecasis, Gonçalo R %A Boehnke, Michael %A Kang, Hyun Min %K Alleles %K Gene Frequency %K Genetics, Population %K Genotype %K Humans %K Linkage Disequilibrium %K Models, Genetic %K Models, Statistical %K Phenotype %K Software %X

Traditional Hardy-Weinberg equilibrium (HWE) tests (the χ2 test and the exact test) have long been used as a metric for evaluating genotype quality, as technical artifacts leading to incorrect genotype calls often can be identified as deviations from HWE. However, in data sets composed of individuals from diverse ancestries, HWE can be violated even without genotyping error, complicating the use of HWE testing to assess genotype data quality. In this manuscript, we present the Robust Unified Test for HWE (RUTH) to test for HWE while accounting for population structure and genotype uncertainty, and to evaluate the impact of population heterogeneity and genotype uncertainty on the standard HWE tests and alternative methods using simulated and real sequence data sets. Our results demonstrate that ignoring population structure or genotype uncertainty in HWE tests can inflate false-positive rates by many orders of magnitude. Our evaluations demonstrate different tradeoffs between false positives and statistical power across the methods, with RUTH consistently among the best across all evaluations. RUTH is implemented as a practical and scalable software tool to rapidly perform HWE tests across millions of markers and hundreds of thousands of individuals while supporting standard VCF/BCF formats. RUTH is publicly available at https://www.github.com/statgen/ruth.

%B Genetics %V 218 %8 2021 May 17 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/33720349?dopt=Abstract %R 10.1093/genetics/iyab044 %0 Journal Article %J Nature %D 2021 %T Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program. %A Taliun, Daniel %A Harris, Daniel N %A Kessler, Michael D %A Carlson, Jedidiah %A Szpiech, Zachary A %A Torres, Raul %A Taliun, Sarah A Gagliano %A Corvelo, André %A Gogarten, Stephanie M %A Kang, Hyun Min %A Pitsillides, Achilleas N %A LeFaive, Jonathon %A Lee, Seung-Been %A Tian, Xiaowen %A Browning, Brian L %A Das, Sayantan %A Emde, Anne-Katrin %A Clarke, Wayne E %A Loesch, Douglas P %A Shetty, Amol C %A Blackwell, Thomas W %A Smith, Albert V %A Wong, Quenna %A Liu, Xiaoming %A Conomos, Matthew P %A Bobo, Dean M %A Aguet, Francois %A Albert, Christine %A Alonso, Alvaro %A Ardlie, Kristin G %A Arking, Dan E %A Aslibekyan, Stella %A Auer, Paul L %A Barnard, John %A Barr, R Graham %A Barwick, Lucas %A Becker, Lewis C %A Beer, Rebecca L %A Benjamin, Emelia J %A Bielak, Lawrence F %A Blangero, John %A Boehnke, Michael %A Bowden, Donald W %A Brody, Jennifer A %A Burchard, Esteban G %A Cade, Brian E %A Casella, James F %A Chalazan, Brandon %A Chasman, Daniel I %A Chen, Yii-Der Ida %A Cho, Michael H %A Choi, Seung Hoan %A Chung, Mina K %A Clish, Clary B %A Correa, Adolfo %A Curran, Joanne E %A Custer, Brian %A Darbar, Dawood %A Daya, Michelle %A de Andrade, Mariza %A DeMeo, Dawn L %A Dutcher, Susan K %A Ellinor, Patrick T %A Emery, Leslie S %A Eng, Celeste %A Fatkin, Diane %A Fingerlin, Tasha %A Forer, Lukas %A Fornage, Myriam %A Franceschini, Nora %A Fuchsberger, Christian %A Fullerton, Stephanie M %A Germer, Soren %A Gladwin, Mark T %A Gottlieb, Daniel J %A Guo, Xiuqing %A Hall, Michael E %A He, Jiang %A Heard-Costa, Nancy L %A Heckbert, Susan R %A Irvin, Marguerite R %A Johnsen, Jill M %A Johnson, Andrew D %A Kaplan, Robert %A Kardia, Sharon L R %A Kelly, Tanika %A Kelly, Shannon %A Kenny, Eimear E %A Kiel, Douglas P %A Klemmer, Robert %A Konkle, Barbara A %A Kooperberg, Charles %A Köttgen, Anna %A Lange, Leslie A %A Lasky-Su, Jessica %A Levy, Daniel %A Lin, Xihong %A Lin, Keng-Han %A Liu, Chunyu %A Loos, Ruth J F %A Garman, Lori %A Gerszten, Robert %A Lubitz, Steven A %A Lunetta, Kathryn L %A Mak, Angel C Y %A Manichaikul, Ani %A Manning, Alisa K %A Mathias, Rasika A %A McManus, David D %A McGarvey, Stephen T %A Meigs, James B %A Meyers, Deborah A %A Mikulla, Julie L %A Minear, Mollie A %A Mitchell, Braxton D %A Mohanty, Sanghamitra %A Montasser, May E %A Montgomery, Courtney %A Morrison, Alanna C %A Murabito, Joanne M %A Natale, Andrea %A Natarajan, Pradeep %A Nelson, Sarah C %A North, Kari E %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Pankratz, Nathan %A Peloso, Gina M %A Peyser, Patricia A %A Pleiness, Jacob %A Post, Wendy S %A Psaty, Bruce M %A Rao, D C %A Redline, Susan %A Reiner, Alexander P %A Roden, Dan %A Rotter, Jerome I %A Ruczinski, Ingo %A Sarnowski, Chloe %A Schoenherr, Sebastian %A Schwartz, David A %A Seo, Jeong-Sun %A Seshadri, Sudha %A Sheehan, Vivien A %A Sheu, Wayne H %A Shoemaker, M Benjamin %A Smith, Nicholas L %A Smith, Jennifer A %A Sotoodehnia, Nona %A Stilp, Adrienne M %A Tang, Weihong %A Taylor, Kent D %A Telen, Marilyn %A Thornton, Timothy A %A Tracy, Russell P %A Van Den Berg, David J %A Vasan, Ramachandran S %A Viaud-Martinez, Karine A %A Vrieze, Scott %A Weeks, Daniel E %A Weir, Bruce S %A Weiss, Scott T %A Weng, Lu-Chen %A Willer, Cristen J %A Zhang, Yingze %A Zhao, Xutong %A Arnett, Donna K %A Ashley-Koch, Allison E %A Barnes, Kathleen C %A Eric Boerwinkle %A Gabriel, Stacey %A Richard A Gibbs %A Rice, Kenneth M %A Rich, Stephen S %A Silverman, Edwin K %A Qasba, Pankaj %A Gan, Weiniu %A Papanicolaou, George J %A Nickerson, Deborah A %A Browning, Sharon R %A Zody, Michael C %A Zöllner, Sebastian %A Wilson, James G %A Cupples, L Adrienne %A Laurie, Cathy C %A Jaquish, Cashell E %A Hernandez, Ryan D %A O'Connor, Timothy D %A Abecasis, Gonçalo R %K Cytochrome P-450 CYP2D6 %K Genetic Variation %K Genome, Human %K Genomics %K Haplotypes %K Heterozygote %K Humans %K INDEL Mutation %K Loss of Function Mutation %K Mutagenesis %K National Heart, Lung, and Blood Institute (U.S.) %K Phenotype %K Polymorphism, Single Nucleotide %K Population Density %K Precision Medicine %K Quality Control %K Sample Size %K United States %K Whole Genome Sequencing %X

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes). In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.

%B Nature %V 590 %P 290-299 %8 2021 Feb %G eng %N 7845 %1 https://www.ncbi.nlm.nih.gov/pubmed/33568819?dopt=Abstract %R 10.1038/s41586-021-03205-y %0 Journal Article %J EBioMedicine %D 2021 %T Whole genome sequence analyses of eGFR in 23,732 people representing multiple ancestries in the NHLBI trans-omics for precision medicine (TOPMed) consortium. %A Lin, Bridget M %A Grinde, Kelsey E %A Brody, Jennifer A %A Breeze, Charles E %A Raffield, Laura M %A Mychaleckyj, Josyf C %A Thornton, Timothy A %A Perry, James A %A Baier, Leslie J %A de Las Fuentes, Lisa %A Guo, Xiuqing %A Heavner, Benjamin D %A Hanson, Robert L %A Hung, Yi-Jen %A Qian, Huijun %A Hsiung, Chao A %A Hwang, Shih-Jen %A Irvin, Margaret R %A Jain, Deepti %A Kelly, Tanika N %A Kobes, Sayuko %A Lange, Leslie %A Lash, James P %A Li, Yun %A Liu, Xiaoming %A Mi, Xuenan %A Musani, Solomon K %A Papanicolaou, George J %A Parsa, Afshin %A Reiner, Alex P %A Salimi, Shabnam %A Sheu, Wayne H-H %A Shuldiner, Alan R %A Taylor, Kent D %A Smith, Albert V %A Smith, Jennifer A %A Tin, Adrienne %A Vaidya, Dhananjay %A Wallace, Robert B %A Yamamoto, Kenichi %A Sakaue, Saori %A Matsuda, Koichi %A Kamatani, Yoichiro %A Momozawa, Yukihide %A Yanek, Lisa R %A Young, Betsi A %A Zhao, Wei %A Okada, Yukinori %A Abecasis, Gonzalo %A Psaty, Bruce M %A Arnett, Donna K %A Eric Boerwinkle %A Cai, Jianwen %A Yii-Der Chen, Ida %A Correa, Adolfo %A Cupples, L Adrienne %A He, Jiang %A Kardia, Sharon Lr %A Kooperberg, Charles %A Mathias, Rasika A %A Mitchell, Braxton D %A Nickerson, Deborah A %A Turner, Steve T %A Vasan, Ramachandran S %A Rotter, Jerome I %A Levy, Daniel %A Kramer, Holly J %A Köttgen, Anna %A Rich, Stephen S %A Lin, Dan-Yu %A Browning, Sharon R %A Franceschini, Nora %K Alleles %K Gene Frequency %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Genomics %K Glomerular Filtration Rate %K Humans %K Male %K National Heart, Lung, and Blood Institute (U.S.) %K Polymorphism, Single Nucleotide %K Precision Medicine %K Public Health Surveillance %K Quantitative Trait, Heritable %K United States %K Whole Genome Sequencing %X

BACKGROUND: Genetic factors that influence kidney traits have been understudied for low frequency and ancestry-specific variants.

METHODS: We combined whole genome sequencing (WGS) data from 23,732 participants from 10 NHLBI Trans-Omics for Precision Medicine (TOPMed) Program multi-ethnic studies to identify novel loci for estimated glomerular filtration rate (eGFR). Participants included European, African, East Asian, and Hispanic ancestries. We applied linear mixed models using a genetic relationship matrix estimated from the WGS data and adjusted for age, sex, study, and ethnicity.

FINDINGS: When testing single variants, we identified three novel loci driven by low frequency variants more commonly observed in non-European ancestry (PRKAA2, rs180996919, minor allele frequency [MAF] 0.04%, P = 6.1 × 10; METTL8, rs116951054, MAF 0.09%, P = 4.5 × 10; and MATK, rs539182790, MAF 0.05%, P = 3.4 × 10). We also replicated two known loci for common variants (rs2461702, MAF=0.49, P = 1.2 × 10, nearest gene GATM, and rs71147340, MAF=0.34, P = 3.3 × 10, CDK12). Testing aggregated variants within a gene identified the MAF gene. A statistical approach based on local ancestry helped to identify replication samples for ancestry-specific variants.

INTERPRETATION: This study highlights challenges in studying variants influencing kidney traits that are low frequency in populations and more common in non-European ancestry.

%B EBioMedicine %V 63 %P 103157 %8 2021 Jan %G eng %1 https://www.ncbi.nlm.nih.gov/pubmed/33418499?dopt=Abstract %R 10.1016/j.ebiom.2020.103157 %0 Journal Article %J Nat Genet %D 2020 %T Discovery of rare variants associated with blood pressure regulation through meta-analysis of 1.3 million individuals. %A Surendran, Praveen %A Feofanova, Elena V %A Lahrouchi, Najim %A Ntalla, Ioanna %A Karthikeyan, Savita %A Cook, James %A Chen, Lingyan %A Mifsud, Borbala %A Yao, Chen %A Kraja, Aldi T %A Cartwright, James H %A Hellwege, Jacklyn N %A Giri, Ayush %A Tragante, Vinicius %A Thorleifsson, Gudmar %A Liu, Dajiang J %A Prins, Bram P %A Stewart, Isobel D %A Cabrera, Claudia P %A Eales, James M %A Akbarov, Artur %A Auer, Paul L %A Bielak, Lawrence F %A Bis, Joshua C %A Braithwaite, Vickie S %A Brody, Jennifer A %A Daw, E Warwick %A Warren, Helen R %A Drenos, Fotios %A Nielsen, Sune Fallgaard %A Faul, Jessica D %A Fauman, Eric B %A Fava, Cristiano %A Ferreira, Teresa %A Foley, Christopher N %A Franceschini, Nora %A Gao, He %A Giannakopoulou, Olga %A Giulianini, Franco %A Gudbjartsson, Daniel F %A Guo, Xiuqing %A Harris, Sarah E %A Havulinna, Aki S %A Helgadottir, Anna %A Huffman, Jennifer E %A Hwang, Shih-Jen %A Kanoni, Stavroula %A Kontto, Jukka %A Larson, Martin G %A Li-Gao, Ruifang %A Lindström, Jaana %A Lotta, Luca A %A Lu, Yingchang %A Luan, Jian'an %A Mahajan, Anubha %A Malerba, Giovanni %A Masca, Nicholas G D %A Mei, Hao %A Menni, Cristina %A Mook-Kanamori, Dennis O %A Mosen-Ansorena, David %A Müller-Nurasyid, Martina %A Paré, Guillaume %A Paul, Dirk S %A Perola, Markus %A Poveda, Alaitz %A Rauramaa, Rainer %A Richard, Melissa %A Richardson, Tom G %A Sepúlveda, Nuno %A Sim, Xueling %A Smith, Albert V %A Smith, Jennifer A %A Staley, James R %A Stanáková, Alena %A Sulem, Patrick %A Thériault, Sébastien %A Thorsteinsdottir, Unnur %A Trompet, Stella %A Varga, Tibor V %A Velez Edwards, Digna R %A Veronesi, Giovanni %A Weiss, Stefan %A Willems, Sara M %A Yao, Jie %A Young, Robin %A Yu, Bing %A Zhang, Weihua %A Zhao, Jing-Hua %A Zhao, Wei %A Zhao, Wei %A Evangelou, Evangelos %A Aeschbacher, Stefanie %A Asllanaj, Eralda %A Blankenberg, Stefan %A Bonnycastle, Lori L %A Bork-Jensen, Jette %A Brandslund, Ivan %A Braund, Peter S %A Burgess, Stephen %A Cho, Kelly %A Christensen, Cramer %A Connell, John %A Mutsert, Renée de %A Dominiczak, Anna F %A Dörr, Marcus %A Eiriksdottir, Gudny %A Farmaki, Aliki-Eleni %A Gaziano, J Michael %A Grarup, Niels %A Grove, Megan L %A Hallmans, Goran %A Hansen, Torben %A Have, Christian T %A Heiss, Gerardo %A Jørgensen, Marit E %A Jousilahti, Pekka %A Kajantie, Eero %A Kamat, Mihir %A Käräjämäki, Annemari %A Karpe, Fredrik %A Koistinen, Heikki A %A Kovesdy, Csaba P %A Kuulasmaa, Kari %A Laatikainen, Tiina %A Lannfelt, Lars %A Lee, I-Te %A Lee, Wen-Jane %A Linneberg, Allan %A Martin, Lisa W %A Moitry, Marie %A Nadkarni, Girish %A Neville, Matt J %A Palmer, Colin N A %A Papanicolaou, George J %A Pedersen, Oluf %A Peters, James %A Poulter, Neil %A Rasheed, Asif %A Rasmussen, Katrine L %A Rayner, N William %A Mägi, Reedik %A Renstrom, Frida %A Rettig, Rainer %A Rossouw, Jacques %A Schreiner, Pamela J %A Sever, Peter S %A Sigurdsson, Emil L %A Skaaby, Tea %A Sun, Yan V %A Sundström, Johan %A Thorgeirsson, Gudmundur %A Esko, Tõnu %A Trabetti, Elisabetta %A Tsao, Philip S %A Tuomi, Tiinamaija %A Turner, Stephen T %A Tzoulaki, Ioanna %A Vaartjes, Ilonca %A Vergnaud, Anne-Claire %A Willer, Cristen J %A Wilson, Peter W F %A Witte, Daniel R %A Yonova-Doing, Ekaterina %A Zhang, He %A Aliya, Naheed %A Almgren, Peter %A Amouyel, Philippe %A Asselbergs, Folkert W %A Barnes, Michael R %A Blakemore, Alexandra I %A Boehnke, Michael %A Bots, Michiel L %A Bottinger, Erwin P %A Buring, Julie E %A Chambers, John C %A Chen, Yii-Der Ida %A Chowdhury, Rajiv %A Conen, David %A Correa, Adolfo %A Davey Smith, George %A Boer, Rudolf A de %A Deary, Ian J %A Dedoussis, George %A Deloukas, Panos %A Di Angelantonio, Emanuele %A Elliott, Paul %A Felix, Stephan B %A Ferrieres, Jean %A Ford, Ian %A Fornage, Myriam %A Franks, Paul W %A Franks, Stephen %A Frossard, Philippe %A Gambaro, Giovanni %A Gaunt, Tom R %A Groop, Leif %A Gudnason, Vilmundur %A Harris, Tamara B %A Hayward, Caroline %A Hennig, Branwen J %A Herzig, Karl-Heinz %A Ingelsson, Erik %A Tuomilehto, Jaakko %A Jarvelin, Marjo-Riitta %A Jukema, J Wouter %A Kardia, Sharon L R %A Kee, Frank %A Kooner, Jaspal S %A Kooperberg, Charles %A Launer, Lenore J %A Lind, Lars %A Loos, Ruth J F %A Majumder, Abdulla Al Shafi %A Laakso, Markku %A McCarthy, Mark I %A Melander, Olle %A Mohlke, Karen L %A Murray, Alison D %A Nordestgaard, Børge Grønne %A Orho-Melander, Marju %A Packard, Chris J %A Padmanabhan, Sandosh %A Palmas, Walter %A Polasek, Ozren %A Porteous, David J %A Prentice, Andrew M %A Province, Michael A %A Relton, Caroline L %A Rice, Kenneth %A Ridker, Paul M %A Rolandsson, Olov %A Rosendaal, Frits R %A Rotter, Jerome I %A Rudan, Igor %A Salomaa, Veikko %A Samani, Nilesh J %A Sattar, Naveed %A Sheu, Wayne H-H %A Smith, Blair H %A Soranzo, Nicole %A Spector, Timothy D %A Starr, John M %A Sebert, Sylvain %A Taylor, Kent D %A Lakka, Timo A %A Timpson, Nicholas J %A Tobin, Martin D %A van der Harst, Pim %A van der Meer, Peter %A Ramachandran, Vasan S %A Verweij, Niek %A Virtamo, Jarmo %A Völker, Uwe %A Weir, David R %A Zeggini, Eleftheria %A Charchar, Fadi J %A Wareham, Nicholas J %A Langenberg, Claudia %A Tomaszewski, Maciej %A Butterworth, Adam S %A Caulfield, Mark J %A Danesh, John %A Edwards, Todd L %A Holm, Hilma %A Hung, Adriana M %A Lindgren, Cecilia M %A Liu, Chunyu %A Manning, Alisa K %A Morris, Andrew P %A Morrison, Alanna C %A O'Donnell, Christopher J %A Psaty, Bruce M %A Saleheen, Danish %A Stefansson, Kari %A Eric Boerwinkle %A Chasman, Daniel I %A Levy, Daniel %A Newton-Cheh, Christopher %A Munroe, Patricia B %A Howson, Joanna M M %K Blood Pressure %K GATA5 Transcription Factor %K Gene Frequency %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Genotype %K Humans %K Hypertension %K Mutation %K Phospholipase C beta %K Polymorphism, Single Nucleotide %X

Genetic studies of blood pressure (BP) to date have mainly analyzed common variants (minor allele frequency > 0.05). In a meta-analysis of up to ~1.3 million participants, we discovered 106 new BP-associated genomic regions and 87 rare (minor allele frequency ≤ 0.01) variant BP associations (P < 5 × 10), of which 32 were in new BP-associated loci and 55 were independent BP-associated single-nucleotide variants within known BP-associated regions. Average effects of rare variants (44% coding) were ~8 times larger than common variant effects and indicate potential candidate causal genes at new and known loci (for example, GATA5 and PLCB3). BP-associated variants (including rare and common) were enriched in regions of active chromatin in fetal tissues, potentially linking fetal development with BP regulation in later life. Multivariable Mendelian randomization suggested possible inverse effects of elevated systolic and diastolic BP on large artery stroke. Our study demonstrates the utility of rare-variant analyses for identifying candidate genes and the results highlight potential therapeutic targets.

%B Nat Genet %V 52 %P 1314-1332 %8 2020 Dec %G eng %N 12 %1 https://www.ncbi.nlm.nih.gov/pubmed/33230300?dopt=Abstract %R 10.1038/s41588-020-00713-x %0 Journal Article %J Nature %D 2020 %T Inherited causes of clonal haematopoiesis in 97,691 whole genomes. %A Bick, Alexander G %A Weinstock, Joshua S %A Nandakumar, Satish K %A Fulco, Charles P %A Bao, Erik L %A Zekavat, Seyedeh M %A Szeto, Mindy D %A Liao, Xiaotian %A Leventhal, Matthew J %A Nasser, Joseph %A Chang, Kyle %A Laurie, Cecelia %A Burugula, Bala Bharathi %A Gibson, Christopher J %A Lin, Amy E %A Taub, Margaret A %A Aguet, Francois %A Ardlie, Kristin %A Mitchell, Braxton D %A Barnes, Kathleen C %A Moscati, Arden %A Fornage, Myriam %A Redline, Susan %A Psaty, Bruce M %A Silverman, Edwin K %A Weiss, Scott T %A Palmer, Nicholette D %A Vasan, Ramachandran S %A Burchard, Esteban G %A Kardia, Sharon L R %A He, Jiang %A Kaplan, Robert C %A Smith, Nicholas L %A Arnett, Donna K %A Schwartz, David A %A Correa, Adolfo %A de Andrade, Mariza %A Guo, Xiuqing %A Konkle, Barbara A %A Custer, Brian %A Peralta, Juan M %A Gui, Hongsheng %A Meyers, Deborah A %A McGarvey, Stephen T %A Chen, Ida Yii-Der %A Shoemaker, M Benjamin %A Peyser, Patricia A %A Broome, Jai G %A Gogarten, Stephanie M %A Wang, Fei Fei %A Wong, Quenna %A Montasser, May E %A Daya, Michelle %A Kenny, Eimear E %A North, Kari E %A Launer, Lenore J %A Cade, Brian E %A Bis, Joshua C %A Cho, Michael H %A Lasky-Su, Jessica %A Bowden, Donald W %A Cupples, L Adrienne %A Mak, Angel C Y %A Becker, Lewis C %A Smith, Jennifer A %A Kelly, Tanika N %A Aslibekyan, Stella %A Heckbert, Susan R %A Tiwari, Hemant K %A Yang, Ivana V %A Heit, John A %A Lubitz, Steven A %A Johnsen, Jill M %A Curran, Joanne E %A Wenzel, Sally E %A Weeks, Daniel E %A Rao, Dabeeru C %A Darbar, Dawood %A Moon, Jee-Young %A Tracy, Russell P %A Buth, Erin J %A Rafaels, Nicholas %A Loos, Ruth J F %A Durda, Peter %A Liu, Yongmei %A Hou, Lifang %A Lee, Jiwon %A Kachroo, Priyadarshini %A Freedman, Barry I %A Levy, Daniel %A Bielak, Lawrence F %A Hixson, James E %A Floyd, James S %A Whitsel, Eric A %A Ellinor, Patrick T %A Irvin, Marguerite R %A Fingerlin, Tasha E %A Raffield, Laura M %A Armasu, Sebastian M %A Wheeler, Marsha M %A Sabino, Ester C %A Blangero, John %A Williams, L Keoki %A Levy, Bruce D %A Sheu, Wayne Huey-Herng %A Roden, Dan M %A Eric Boerwinkle %A Manson, JoAnn E %A Mathias, Rasika A %A Desai, Pinkal %A Taylor, Kent D %A Johnson, Andrew D %A Auer, Paul L %A Kooperberg, Charles %A Laurie, Cathy C %A Blackwell, Thomas W %A Smith, Albert V %A Zhao, Hongyu %A Lange, Ethan %A Lange, Leslie %A Rich, Stephen S %A Rotter, Jerome I %A Wilson, James G %A Scheet, Paul %A Kitzman, Jacob O %A Lander, Eric S %A Engreitz, Jesse M %A Ebert, Benjamin L %A Reiner, Alexander P %A Jaiswal, Siddhartha %A Abecasis, Goncalo %A Sankaran, Vijay G %A Kathiresan, Sekar %A Natarajan, Pradeep %K Adult %K Africa %K Aged %K Aged, 80 and over %K alpha Karyopherins %K Black People %K Cell Self Renewal %K Clonal Hematopoiesis %K Dioxygenases %K DNA-Binding Proteins %K Female %K Genetic Predisposition to Disease %K Genome, Human %K Germ-Line Mutation %K Hematopoietic Stem Cells %K Humans %K Intracellular Signaling Peptides and Proteins %K Male %K Middle Aged %K National Heart, Lung, and Blood Institute (U.S.) %K Phenotype %K Precision Medicine %K Proto-Oncogene Proteins %K Tripartite Motif Proteins %K United States %K Whole Genome Sequencing %X

Age is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown. The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer and coronary heart disease-this phenomenon is termed clonal haematopoiesis of indeterminate potential (CHIP). Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues.

%B Nature %V 586 %P 763-768 %8 2020 Oct %G eng %N 7831 %1 https://www.ncbi.nlm.nih.gov/pubmed/33057201?dopt=Abstract %R 10.1038/s41586-020-2819-2 %0 Journal Article %J Circ Genom Precis Med %D 2020 %T Role of Rare and Low-Frequency Variants in Gene-Alcohol Interactions on Plasma Lipid Levels. %A Wang, Zhe %A Chen, Han %A Bartz, Traci M %A Bielak, Lawrence F %A Chasman, Daniel I %A Feitosa, Mary F %A Franceschini, Nora %A Guo, Xiuqing %A Lim, Elise %A Noordam, Raymond %A Richard, Melissa A %A Wang, Heming %A Cade, Brian %A Cupples, L Adrienne %A de Vries, Paul S %A Giulanini, Franco %A Lee, Jiwon %A Lemaitre, Rozenn N %A Martin, Lisa W %A Reiner, Alex P %A Rich, Stephen S %A Schreiner, Pamela J %A Sidney, Stephen %A Sitlani, Colleen M %A Smith, Jennifer A %A Willems van Dijk, Ko %A Yao, Jie %A Zhao, Wei %A Fornage, Myriam %A Kardia, Sharon L R %A Kooperberg, Charles %A Liu, Ching-Ti %A Mook-Kanamori, Dennis O %A Province, Michael A %A Psaty, Bruce M %A Redline, Susan %A Ridker, Paul M %A Rotter, Jerome I %A Eric Boerwinkle %A Morrison, Alanna C %K Adolescent %K Adult %K Aged %K Aged, 80 and over %K Alcohol Drinking %K Apolipoproteins E %K Cholesterol, HDL %K Female %K Gene Frequency %K Genetic Loci %K Genome-Wide Association Study %K Humans %K Lipids %K Male %K Middle Aged %K Polymorphism, Single Nucleotide %K Proprotein Convertase 9 %K Triglycerides %K White People %K Young Adult %X

BACKGROUND: Alcohol intake influences plasma lipid levels, and such effects may be moderated by genetic variants. We aimed to characterize the role of aggregated rare and low-frequency protein-coding variants in gene by alcohol consumption interactions associated with fasting plasma lipid levels.

METHODS: In the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, fasting plasma triglycerides and high- and low-density lipoprotein cholesterol were measured in 34 153 individuals with European ancestry from 5 discovery studies and 32 277 individuals from 6 replication studies. Rare and low-frequency functional protein-coding variants (minor allele frequency, ≤5%) measured by an exome array were aggregated by genes and evaluated by a gene-environment interaction test and a joint test of genetic main and gene-environment interaction effects. Two dichotomous self-reported alcohol consumption variables, current drinker, defined as any recurrent drinking behavior, and regular drinker, defined as the subset of current drinkers who consume at least 2 drinks per week, were considered.

RESULTS: We discovered and replicated 21 gene-lipid associations at 13 known lipid loci through the joint test. Eight loci (, , , , , , , and ) remained significant after conditioning on the common index single-nucleotide polymorphism identified by previous genome-wide association studies, suggesting an independent role for rare and low-frequency variants at these loci. One significant gene-alcohol interaction on triglycerides in a novel locus was significantly discovered (=6.65×10 for the interaction test) and replicated at nominal significance level (=0.013) in .

CONCLUSIONS: In conclusion, this study applied new gene-based statistical approaches and suggested that rare and low-frequency genetic variants interacted with alcohol consumption on lipid levels.

%B Circ Genom Precis Med %V 13 %P e002772 %8 2020 Aug %G eng %N 4 %1 https://www.ncbi.nlm.nih.gov/pubmed/32510982?dopt=Abstract %R 10.1161/CIRCGEN.119.002772 %0 Journal Article %J Am J Hum Genet %D 2019 %T Efficient Variant Set Mixed Model Association Tests for Continuous and Binary Traits in Large-Scale Whole-Genome Sequencing Studies. %A Chen, Han %A Huffman, Jennifer E %A Brody, Jennifer A %A Wang, Chaolong %A Lee, Seunggeun %A Li, Zilin %A Gogarten, Stephanie M %A Sofer, Tamar %A Bielak, Lawrence F %A Bis, Joshua C %A Blangero, John %A Bowler, Russell P %A Cade, Brian E %A Cho, Michael H %A Correa, Adolfo %A Curran, Joanne E %A de Vries, Paul S %A Glahn, David C %A Guo, Xiuqing %A Johnson, Andrew D %A Kardia, Sharon %A Kooperberg, Charles %A Lewis, Joshua P %A Liu, Xiaoming %A Mathias, Rasika A %A Mitchell, Braxton D %A O'Connell, Jeffrey R %A Peyser, Patricia A %A Post, Wendy S %A Reiner, Alex P %A Rich, Stephen S %A Rotter, Jerome I %A Silverman, Edwin K %A Smith, Jennifer A %A Vasan, Ramachandran S %A Wilson, James G %A Yanek, Lisa R %A Redline, Susan %A Smith, Nicholas L %A Eric Boerwinkle %A Borecki, Ingrid B %A Cupples, L Adrienne %A Laurie, Cathy C %A Morrison, Alanna C %A Rice, Kenneth M %A Lin, Xihong %K Chromosomes, Human, Pair 4 %K Cloud Computing %K Female %K Fibrinogen %K Genetic Association Studies %K Genetics, Population %K Humans %K Male %K Models, Genetic %K National Heart, Lung, and Blood Institute (U.S.) %K Precision Medicine %K Research Design %K Time Factors %K United States %K Whole Genome Sequencing %X

With advances in whole-genome sequencing (WGS) technology, more advanced statistical methods for testing genetic association with rare variants are being developed. Methods in which variants are grouped for analysis are also known as variant-set, gene-based, and aggregate unit tests. The burden test and sequence kernel association test (SKAT) are two widely used variant-set tests, which were originally developed for samples of unrelated individuals and later have been extended to family data with known pedigree structures. However, computationally efficient and powerful variant-set tests are needed to make analyses tractable in large-scale WGS studies with complex study samples. In this paper, we propose the variant-set mixed model association tests (SMMAT) for continuous and binary traits using the generalized linear mixed model framework. These tests can be applied to large-scale WGS studies involving samples with population structure and relatedness, such as in the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine (TOPMed) program. SMMATs share the same null model for different variant sets, and a virtue of this null model, which includes covariates only, is that it needs to be fit only once for all tests in each genome-wide analysis. Simulation studies show that all the proposed SMMATs correctly control type I error rates for both continuous and binary traits in the presence of population structure and relatedness. We also illustrate our tests in a real data example of analysis of plasma fibrinogen levels in the TOPMed program (n = 23,763), using the Analysis Commons, a cloud-based computing platform.

%B Am J Hum Genet %V 104 %P 260-274 %8 2019 Feb 07 %G eng %N 2 %1 https://www.ncbi.nlm.nih.gov/pubmed/30639324?dopt=Abstract %R 10.1016/j.ajhg.2018.12.012 %0 Journal Article %J Am J Hum Genet %D 2019 %T Impact of Rare and Common Genetic Variants on Diabetes Diagnosis by Hemoglobin A1c in Multi-Ancestry Cohorts: The Trans-Omics for Precision Medicine Program. %A Sarnowski, Chloe %A Leong, Aaron %A Raffield, Laura M %A Wu, Peitao %A de Vries, Paul S %A DiCorpo, Daniel %A Guo, Xiuqing %A Xu, Huichun %A Liu, Yongmei %A Zheng, Xiuwen %A Hu, Yao %A Brody, Jennifer A %A Goodarzi, Mark O %A Hidalgo, Bertha A %A Highland, Heather M %A Jain, Deepti %A Liu, Ching-Ti %A Naik, Rakhi P %A O'Connell, Jeffrey R %A Perry, James A %A Porneala, Bianca C %A Selvin, Elizabeth %A Wessel, Jennifer %A Psaty, Bruce M %A Curran, Joanne E %A Peralta, Juan M %A Blangero, John %A Kooperberg, Charles %A Mathias, Rasika %A Johnson, Andrew D %A Reiner, Alexander P %A Mitchell, Braxton D %A Cupples, L Adrienne %A Vasan, Ramachandran S %A Correa, Adolfo %A Morrison, Alanna C %A Eric Boerwinkle %A Rotter, Jerome I %A Rich, Stephen S %A Manning, Alisa K %A Dupuis, Josée %A Meigs, James B %K Cohort Studies %K Diabetes Mellitus %K Female %K Genetic Variation %K Glycated Hemoglobin %K Humans %K Male %K Polymorphism, Single Nucleotide %K Population Groups %K Precision Medicine %X

Hemoglobin A1c (HbA1c) is widely used to diagnose diabetes and assess glycemic control in individuals with diabetes. However, nonglycemic determinants, including genetic variation, may influence how accurately HbA1c reflects underlying glycemia. Analyzing the NHLBI Trans-Omics for Precision Medicine (TOPMed) sequence data in 10,338 individuals from five studies and four ancestries (6,158 Europeans, 3,123 African-Americans, 650 Hispanics, and 407 East Asians), we confirmed five regions associated with HbA1c (GCK in Europeans and African-Americans, HK1 in Europeans and Hispanics, FN3K and/or FN3KRP in Europeans, and G6PD in African-Americans and Hispanics) and we identified an African-ancestry-specific low-frequency variant (rs1039215 in HBG2 and HBE1, minor allele frequency (MAF) = 0.03). The most associated G6PD variant (rs1050828-T, p.Val98Met, MAF = 12% in African-Americans, MAF = 2% in Hispanics) lowered HbA1c (-0.88% in hemizygous males, -0.34% in heterozygous females) and explained 23% of HbA1c variance in African-Americans and 4% in Hispanics. Additionally, we identified a rare distinct G6PD coding variant (rs76723693, p.Leu353Pro, MAF = 0.5%; -0.98% in hemizygous males, -0.46% in heterozygous females) and detected significant association with HbA1c when aggregating rare missense variants in G6PD. We observed similar magnitude and direction of effects for rs1039215 (HBG2) and rs76723693 (G6PD) in the two largest TOPMed African American cohorts, and we replicated the rs76723693 association in the UK Biobank African-ancestry participants. These variants in G6PD and HBG2 were monomorphic in the European and Asian samples. African or Hispanic ancestry individuals carrying G6PD variants may be underdiagnosed for diabetes when screened with HbA1c. Thus, assessment of these variants should be considered for incorporation into precision medicine approaches for diabetes diagnosis.

%B Am J Hum Genet %V 105 %P 706-718 %8 2019 Oct 03 %G eng %N 4 %1 https://www.ncbi.nlm.nih.gov/pubmed/31564435?dopt=Abstract %R 10.1016/j.ajhg.2019.08.010 %0 Journal Article %J Hum Genet %D 2019 %T Leveraging linkage evidence to identify low-frequency and rare variants on 16p13 associated with blood pressure using TOPMed whole genome sequencing data. %A He, Karen Y %A Li, Xiaoyin %A Kelly, Tanika N %A Liang, Jingjing %A Cade, Brian E %A Assimes, Themistocles L %A Becker, Lewis C %A Beitelshees, Amber L %A Bress, Adam P %A Chang, Yen-Pei Christy %A Chen, Yii-Der Ida %A de Vries, Paul S %A Fox, Ervin R %A Franceschini, Nora %A Furniss, Anna %A Gao, Yan %A Guo, Xiuqing %A Haessler, Jeffrey %A Hwang, Shih-Jen %A Irvin, Marguerite Ryan %A Kalyani, Rita R %A Liu, Ching-Ti %A Liu, Chunyu %A Martin, Lisa Warsinger %A Montasser, May E %A Muntner, Paul M %A Mwasongwe, Stanford %A Palmas, Walter %A Reiner, Alex P %A Shimbo, Daichi %A Smith, Jennifer A %A Snively, Beverly M %A Yanek, Lisa R %A Eric Boerwinkle %A Correa, Adolfo %A Cupples, L Adrienne %A He, Jiang %A Kardia, Sharon L R %A Kooperberg, Charles %A Mathias, Rasika A %A Mitchell, Braxton D %A Psaty, Bruce M %A Vasan, Ramachandran S %A Rao, D C %A Rich, Stephen S %A Rotter, Jerome I %A Wilson, James G %A Chakravarti, Aravinda %A Morrison, Alanna C %A Levy, Daniel %A Arnett, Donna K %A Redline, Susan %A Zhu, Xiaofeng %K Alternative Splicing %K Blood Pressure %K Chromosomes, Human, Pair 16 %K Exome %K Female %K Follow-Up Studies %K Genetic Linkage %K Genetic Variation %K Genome, Human %K Genome-Wide Association Study %K High-Throughput Nucleotide Sequencing %K Humans %K Male %K Recombinases %K RNA Splicing Factors %X

In this study, we investigated low-frequency and rare variants associated with blood pressure (BP) by focusing on a linkage region on chromosome 16p13. We used whole genome sequencing (WGS) data obtained through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program on 395 Cleveland Family Study (CFS) European Americans (CFS-EA). By analyzing functional coding variants and non-coding rare variants with CADD score > 10 residing within the chromosomal region in families with linkage evidence, we observed 25 genes with nominal statistical evidence (burden or SKAT p < 0.05). One of the genes is RBFOX1, an evolutionarily conserved RNA-binding protein that regulates tissue-specific alternative splicing that we previously reported to be associated with BP using exome array data in CFS. After follow-up analysis of the 25 genes in ten independent TOPMed studies with individuals of European, African, and East Asian ancestry, and Hispanics (N = 29,988), we identified variants in SLX4 (p = 2.19 × 10) to be significantly associated with BP traits when accounting for multiple testing. We also replicated the associations previously reported for RBFOX1 (p = 0.007). Follow-up analysis with GTEx eQTL data shows SLX4 variants are associated with gene expression in coronary artery, multiple brain tissues, and right atrial appendage of the heart. Our study demonstrates that linkage analysis of family data can provide an efficient approach for detecting rare variants associated with complex traits in WGS data.

%B Hum Genet %V 138 %P 199-210 %8 2019 Feb %G eng %N 2 %1 https://www.ncbi.nlm.nih.gov/pubmed/30671673?dopt=Abstract %R 10.1007/s00439-019-01975-0 %0 Journal Article %J Am J Epidemiol %D 2019 %T Multiancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions. %A de Vries, Paul S %A Brown, Michael R %A Bentley, Amy R %A Sung, Yun J %A Winkler, Thomas W %A Ntalla, Ioanna %A Schwander, Karen %A Kraja, Aldi T %A Guo, Xiuqing %A Franceschini, Nora %A Cheng, Ching-Yu %A Sim, Xueling %A Vojinovic, Dina %A Huffman, Jennifer E %A Musani, Solomon K %A Li, Changwei %A Feitosa, Mary F %A Richard, Melissa A %A Noordam, Raymond %A Aschard, Hugues %A Bartz, Traci M %A Bielak, Lawrence F %A Deng, Xuan %A Dorajoo, Rajkumar %A Lohman, Kurt K %A Manning, Alisa K %A Rankinen, Tuomo %A Smith, Albert V %A Tajuddin, Salman M %A Evangelou, Evangelos %A Graff, Mariaelisa %A Alver, Maris %A Boissel, Mathilde %A Chai, Jin Fang %A Chen, Xu %A Divers, Jasmin %A Gandin, Ilaria %A Gao, Chuan %A Goel, Anuj %A Hagemeijer, Yanick %A Harris, Sarah E %A Hartwig, Fernando P %A He, Meian %A Horimoto, Andrea R V R %A Hsu, Fang-Chi %A Jackson, Anne U %A Kasturiratne, Anuradhani %A Komulainen, Pirjo %A Kühnel, Brigitte %A Laguzzi, Federica %A Lee, Joseph H %A Luan, Jian'an %A Lyytikäinen, Leo-Pekka %A Matoba, Nana %A Nolte, Ilja M %A Pietzner, Maik %A Riaz, Muhammad %A Said, M Abdullah %A Scott, Robert A %A Sofer, Tamar %A Stančáková, Alena %A Takeuchi, Fumihiko %A Tayo, Bamidele O %A van der Most, Peter J %A Varga, Tibor V %A Wang, Yajuan %A Ware, Erin B %A Wen, Wanqing %A Yanek, Lisa R %A Zhang, Weihua %A Zhao, Jing Hua %A Afaq, Saima %A Amin, Najaf %A Amini, Marzyeh %A Arking, Dan E %A Aung, Tin %A Ballantyne, Christie %A Eric Boerwinkle %A Broeckel, Ulrich %A Campbell, Archie %A Canouil, Mickaël %A Charumathi, Sabanayagam %A Chen, Yii-Der Ida %A Connell, John M %A de Faire, Ulf %A de Las Fuentes, Lisa %A de Mutsert, Renée %A de Silva, H Janaka %A Ding, Jingzhong %A Dominiczak, Anna F %A Duan, Qing %A Eaton, Charles B %A Eppinga, Ruben N %A Faul, Jessica D %A Fisher, Virginia %A Forrester, Terrence %A Franco, Oscar H %A Friedlander, Yechiel %A Ghanbari, Mohsen %A Giulianini, Franco %A Grabe, Hans J %A Grove, Megan L %A Gu, C Charles %A Harris, Tamara B %A Heikkinen, Sami %A Heng, Chew-Kiat %A Hirata, Makoto %A Hixson, James E %A Howard, Barbara V %A Ikram, M Arfan %A Jacobs, David R %A Johnson, Craig %A Jonas, Jost Bruno %A Kammerer, Candace M %A Katsuya, Tomohiro %A Khor, Chiea Chuen %A Kilpeläinen, Tuomas O %A Koh, Woon-Puay %A Koistinen, Heikki A %A Kolcic, Ivana %A Kooperberg, Charles %A Krieger, Jose E %A Kritchevsky, Steve B %A Kubo, Michiaki %A Kuusisto, Johanna %A Lakka, Timo A %A Langefeld, Carl D %A Langenberg, Claudia %A Launer, Lenore J %A Lehne, Benjamin %A Lemaitre, Rozenn N %A Li, Yize %A Liang, Jingjing %A Liu, Jianjun %A Liu, Kiang %A Loh, Marie %A Louie, Tin %A Mägi, Reedik %A Manichaikul, Ani W %A McKenzie, Colin A %A Meitinger, Thomas %A Metspalu, Andres %A Milaneschi, Yuri %A Milani, Lili %A Mohlke, Karen L %A Mosley, Thomas H %A Mukamal, Kenneth J %A Nalls, Mike A %A Nauck, Matthias %A Nelson, Christopher P %A Sotoodehnia, Nona %A O'Connell, Jeff R %A Palmer, Nicholette D %A Pazoki, Raha %A Pedersen, Nancy L %A Peters, Annette %A Peyser, Patricia A %A Polasek, Ozren %A Poulter, Neil %A Raffel, Leslie J %A Raitakari, Olli T %A Reiner, Alex P %A Rice, Treva K %A Rich, Stephen S %A Robino, Antonietta %A Robinson, Jennifer G %A Rose, Lynda M %A Rudan, Igor %A Schmidt, Carsten O %A Schreiner, Pamela J %A Scott, William R %A Sever, Peter %A Shi, Yuan %A Sidney, Stephen %A Sims, Mario %A Smith, Blair H %A Smith, Jennifer A %A Snieder, Harold %A Starr, John M %A Strauch, Konstantin %A Tan, Nicholas %A Taylor, Kent D %A Teo, Yik Ying %A Tham, Yih Chung %A Uitterlinden, André G %A van Heemst, Diana %A Vuckovic, Dragana %A Waldenberger, Melanie %A Wang, Lihua %A Wang, Yujie %A Wang, Zhe %A Wei, Wen Bin %A Williams, Christine %A Wilson, Gregory %A Wojczynski, Mary K %A Yao, Jie %A Yu, Bing %A Yu, Caizheng %A Yuan, Jian-Min %A Zhao, Wei %A Zonderman, Alan B %A Becker, Diane M %A Boehnke, Michael %A Bowden, Donald W %A Chambers, John C %A Deary, Ian J %A Esko, Tõnu %A Farrall, Martin %A Franks, Paul W %A Freedman, Barry I %A Froguel, Philippe %A Gasparini, Paolo %A Gieger, Christian %A Horta, Bernardo L %A Kamatani, Yoichiro %A Kato, Norihiro %A Kooner, Jaspal S %A Laakso, Markku %A Leander, Karin %A Lehtimäki, Terho %A Magnusson, Patrik K E %A Penninx, Brenda %A Pereira, Alexandre C %A Rauramaa, Rainer %A Samani, Nilesh J %A Scott, James %A Shu, Xiao-Ou %A van der Harst, Pim %A Wagenknecht, Lynne E %A Wang, Ya Xing %A Wareham, Nicholas J %A Watkins, Hugh %A Weir, David R %A Wickremasinghe, Ananda R %A Zheng, Wei %A Elliott, Paul %A North, Kari E %A Bouchard, Claude %A Evans, Michele K %A Gudnason, Vilmundur %A Liu, Ching-Ti %A Liu, Yongmei %A Psaty, Bruce M %A Ridker, Paul M %A van Dam, Rob M %A Kardia, Sharon L R %A Zhu, Xiaofeng %A Rotimi, Charles N %A Mook-Kanamori, Dennis O %A Fornage, Myriam %A Kelly, Tanika N %A Fox, Ervin R %A Hayward, Caroline %A van Duijn, Cornelia M %A Tai, E Shyong %A Wong, Tien Yin %A Liu, Jingmin %A Rotter, Jerome I %A Gauderman, W James %A Province, Michael A %A Munroe, Patricia B %A Rice, Kenneth %A Chasman, Daniel I %A Cupples, L Adrienne %A Rao, Dabeeru C %A Morrison, Alanna C %K Adolescent %K Adult %K Aged %K Alcohol Drinking %K Cholesterol, HDL %K Cholesterol, LDL %K Female %K Genome-Wide Association Study %K Genotype %K Humans %K Life Style %K Lipids %K Male %K Middle Aged %K Phenotype %K Racial Groups %K Triglycerides %K Vascular Endothelial Growth Factor B %K Young Adult %X

A person's lipid profile is influenced by genetic variants and alcohol consumption, but the contribution of interactions between these exposures has not been studied. We therefore incorporated gene-alcohol interactions into a multiancestry genome-wide association study of levels of high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. We included 45 studies in stage 1 (genome-wide discovery) and 66 studies in stage 2 (focused follow-up), for a total of 394,584 individuals from 5 ancestry groups. Analyses covered the period July 2014-November 2017. Genetic main effects and interaction effects were jointly assessed by means of a 2-degrees-of-freedom (df) test, and a 1-df test was used to assess the interaction effects alone. Variants at 495 loci were at least suggestively associated (P < 1 × 10-6) with lipid levels in stage 1 and were evaluated in stage 2, followed by combined analyses of stage 1 and stage 2. In the combined analysis of stages 1 and 2, a total of 147 independent loci were associated with lipid levels at P < 5 × 10-8 using 2-df tests, of which 18 were novel. No genome-wide-significant associations were found testing the interaction effect alone. The novel loci included several genes (proprotein convertase subtilisin/kexin type 5 (PCSK5), vascular endothelial growth factor B (VEGFB), and apolipoprotein B mRNA editing enzyme, catalytic polypeptide 1 (APOBEC1) complementation factor (A1CF)) that have a putative role in lipid metabolism on the basis of existing evidence from cellular and experimental models.

%B Am J Epidemiol %V 188 %P 1033-1054 %8 2019 Jun 01 %G eng %N 6 %1 https://www.ncbi.nlm.nih.gov/pubmed/30698716?dopt=Abstract %R 10.1093/aje/kwz005 %0 Journal Article %J Nat Genet %D 2019 %T Multi-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids. %A Bentley, Amy R %A Sung, Yun J %A Brown, Michael R %A Winkler, Thomas W %A Kraja, Aldi T %A Ntalla, Ioanna %A Schwander, Karen %A Chasman, Daniel I %A Lim, Elise %A Deng, Xuan %A Guo, Xiuqing %A Liu, Jingmin %A Lu, Yingchang %A Cheng, Ching-Yu %A Sim, Xueling %A Vojinovic, Dina %A Huffman, Jennifer E %A Musani, Solomon K %A Li, Changwei %A Feitosa, Mary F %A Richard, Melissa A %A Noordam, Raymond %A Baker, Jenna %A Chen, Guanjie %A Aschard, Hugues %A Bartz, Traci M %A Ding, Jingzhong %A Dorajoo, Rajkumar %A Manning, Alisa K %A Rankinen, Tuomo %A Smith, Albert V %A Tajuddin, Salman M %A Zhao, Wei %A Graff, Mariaelisa %A Alver, Maris %A Boissel, Mathilde %A Chai, Jin Fang %A Chen, Xu %A Divers, Jasmin %A Evangelou, Evangelos %A Gao, Chuan %A Goel, Anuj %A Hagemeijer, Yanick %A Harris, Sarah E %A Hartwig, Fernando P %A He, Meian %A Horimoto, Andrea R V R %A Hsu, Fang-Chi %A Hung, Yi-Jen %A Jackson, Anne U %A Kasturiratne, Anuradhani %A Komulainen, Pirjo %A Kühnel, Brigitte %A Leander, Karin %A Lin, Keng-Hung %A Luan, Jian'an %A Lyytikäinen, Leo-Pekka %A Matoba, Nana %A Nolte, Ilja M %A Pietzner, Maik %A Prins, Bram %A Riaz, Muhammad %A Robino, Antonietta %A Said, M Abdullah %A Schupf, Nicole %A Scott, Robert A %A Sofer, Tamar %A Stančáková, Alena %A Takeuchi, Fumihiko %A Tayo, Bamidele O %A van der Most, Peter J %A Varga, Tibor V %A Wang, Tzung-Dau %A Wang, Yajuan %A Ware, Erin B %A Wen, Wanqing %A Xiang, Yong-Bing %A Yanek, Lisa R %A Zhang, Weihua %A Zhao, Jing Hua %A Adeyemo, Adebowale %A Afaq, Saima %A Amin, Najaf %A Amini, Marzyeh %A Arking, Dan E %A Arzumanyan, Zorayr %A Aung, Tin %A Ballantyne, Christie %A Barr, R Graham %A Bielak, Lawrence F %A Eric Boerwinkle %A Bottinger, Erwin P %A Broeckel, Ulrich %A Brown, Morris %A Cade, Brian E %A Campbell, Archie %A Canouil, Mickaël %A Charumathi, Sabanayagam %A Chen, Yii-Der Ida %A Christensen, Kaare %A Concas, Maria Pina %A Connell, John M %A de Las Fuentes, Lisa %A de Silva, H Janaka %A de Vries, Paul S %A Doumatey, Ayo %A Duan, Qing %A Eaton, Charles B %A Eppinga, Ruben N %A Faul, Jessica D %A Floyd, James S %A Forouhi, Nita G %A Forrester, Terrence %A Friedlander, Yechiel %A Gandin, Ilaria %A Gao, He %A Ghanbari, Mohsen %A Gharib, Sina A %A Gigante, Bruna %A Giulianini, Franco %A Grabe, Hans J %A Gu, C Charles %A Harris, Tamara B %A Heikkinen, Sami %A Heng, Chew-Kiat %A Hirata, Makoto %A Hixson, James E %A Ikram, M Arfan %A Jia, Yucheng %A Joehanes, Roby %A Johnson, Craig %A Jonas, Jost Bruno %A Justice, Anne E %A Katsuya, Tomohiro %A Khor, Chiea Chuen %A Kilpeläinen, Tuomas O %A Koh, Woon-Puay %A Kolcic, Ivana %A Kooperberg, Charles %A Krieger, Jose E %A Kritchevsky, Stephen B %A Kubo, Michiaki %A Kuusisto, Johanna %A Lakka, Timo A %A Langefeld, Carl D %A Langenberg, Claudia %A Launer, Lenore J %A Lehne, Benjamin %A Lewis, Cora E %A Li, Yize %A Liang, Jingjing %A Lin, Shiow %A Liu, Ching-Ti %A Liu, Jianjun %A Liu, Kiang %A Loh, Marie %A Lohman, Kurt K %A Louie, Tin %A Luzzi, Anna %A Mägi, Reedik %A Mahajan, Anubha %A Manichaikul, Ani W %A McKenzie, Colin A %A Meitinger, Thomas %A Metspalu, Andres %A Milaneschi, Yuri %A Milani, Lili %A Mohlke, Karen L %A Momozawa, Yukihide %A Morris, Andrew P %A Murray, Alison D %A Nalls, Mike A %A Nauck, Matthias %A Nelson, Christopher P %A North, Kari E %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Papanicolau, George J %A Pedersen, Nancy L %A Peters, Annette %A Peyser, Patricia A %A Polasek, Ozren %A Poulter, Neil %A Raitakari, Olli T %A Reiner, Alex P %A Renstrom, Frida %A Rice, Treva K %A Rich, Stephen S %A Robinson, Jennifer G %A Rose, Lynda M %A Rosendaal, Frits R %A Rudan, Igor %A Schmidt, Carsten O %A Schreiner, Pamela J %A Scott, William R %A Sever, Peter %A Shi, Yuan %A Sidney, Stephen %A Sims, Mario %A Smith, Jennifer A %A Snieder, Harold %A Starr, John M %A Strauch, Konstantin %A Stringham, Heather M %A Tan, Nicholas Y Q %A Tang, Hua %A Taylor, Kent D %A Teo, Yik Ying %A Tham, Yih Chung %A Tiemeier, Henning %A Turner, Stephen T %A Uitterlinden, André G %A van Heemst, Diana %A Waldenberger, Melanie %A Wang, Heming %A Wang, Lan %A Wang, Lihua %A Wei, Wen Bin %A Williams, Christine A %A Wilson, Gregory %A Wojczynski, Mary K %A Yao, Jie %A Young, Kristin %A Yu, Caizheng %A Yuan, Jian-Min %A Zhou, Jie %A Zonderman, Alan B %A Becker, Diane M %A Boehnke, Michael %A Bowden, Donald W %A Chambers, John C %A Cooper, Richard S %A de Faire, Ulf %A Deary, Ian J %A Elliott, Paul %A Esko, Tõnu %A Farrall, Martin %A Franks, Paul W %A Freedman, Barry I %A Froguel, Philippe %A Gasparini, Paolo %A Gieger, Christian %A Horta, Bernardo L %A Juang, Jyh-Ming Jimmy %A Kamatani, Yoichiro %A Kammerer, Candace M %A Kato, Norihiro %A Kooner, Jaspal S %A Laakso, Markku %A Laurie, Cathy C %A Lee, I-Te %A Lehtimäki, Terho %A Magnusson, Patrik K E %A Oldehinkel, Albertine J %A Penninx, Brenda W J H %A Pereira, Alexandre C %A Rauramaa, Rainer %A Redline, Susan %A Samani, Nilesh J %A Scott, James %A Shu, Xiao-Ou %A van der Harst, Pim %A Wagenknecht, Lynne E %A Wang, Jun-Sing %A Wang, Ya Xing %A Wareham, Nicholas J %A Watkins, Hugh %A Weir, David R %A Wickremasinghe, Ananda R %A Wu, Tangchun %A Zeggini, Eleftheria %A Zheng, Wei %A Bouchard, Claude %A Evans, Michele K %A Gudnason, Vilmundur %A Kardia, Sharon L R %A Liu, Yongmei %A Psaty, Bruce M %A Ridker, Paul M %A van Dam, Rob M %A Mook-Kanamori, Dennis O %A Fornage, Myriam %A Province, Michael A %A Kelly, Tanika N %A Fox, Ervin R %A Hayward, Caroline %A van Duijn, Cornelia M %A Tai, E Shyong %A Wong, Tien Yin %A Loos, Ruth J F %A Franceschini, Nora %A Rotter, Jerome I %A Zhu, Xiaofeng %A Bierut, Laura J %A Gauderman, W James %A Rice, Kenneth %A Munroe, Patricia B %A Morrison, Alanna C %A Rao, Dabeeru C %A Rotimi, Charles N %A Cupples, L Adrienne %K Adolescent %K Adult %K Aged %K Aged, 80 and over %K Female %K Genome-Wide Association Study %K Genotype %K Humans %K Life Style %K Linkage Disequilibrium %K Lipids %K Male %K Middle Aged %K Smoking %K Young Adult %X

The concentrations of high- and low-density-lipoprotein cholesterol and triglycerides are influenced by smoking, but it is unknown whether genetic associations with lipids may be modified by smoking. We conducted a multi-ancestry genome-wide gene-smoking interaction study in 133,805 individuals with follow-up in an additional 253,467 individuals. Combined meta-analyses identified 13 new loci associated with lipids, some of which were detected only because association differed by smoking status. Additionally, we demonstrate the importance of including diverse populations, particularly in studies of interactions with lifestyle factors, where genomic and lifestyle differences by ancestry may contribute to novel findings.

%B Nat Genet %V 51 %P 636-648 %8 2019 Apr %G eng %N 4 %1 https://www.ncbi.nlm.nih.gov/pubmed/30926973?dopt=Abstract %R 10.1038/s41588-019-0378-y %0 Journal Article %J Nat Commun %D 2019 %T Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration. %A Noordam, Raymond %A Bos, Maxime M %A Wang, Heming %A Winkler, Thomas W %A Bentley, Amy R %A Kilpeläinen, Tuomas O %A de Vries, Paul S %A Sung, Yun Ju %A Schwander, Karen %A Cade, Brian E %A Manning, Alisa %A Aschard, Hugues %A Brown, Michael R %A Chen, Han %A Franceschini, Nora %A Musani, Solomon K %A Richard, Melissa %A Vojinovic, Dina %A Aslibekyan, Stella %A Bartz, Traci M %A de Las Fuentes, Lisa %A Feitosa, Mary %A Horimoto, Andrea R %A Ilkov, Marjan %A Kho, Minjung %A Kraja, Aldi %A Li, Changwei %A Lim, Elise %A Liu, Yongmei %A Mook-Kanamori, Dennis O %A Rankinen, Tuomo %A Tajuddin, Salman M %A van der Spek, Ashley %A Wang, Zhe %A Marten, Jonathan %A Laville, Vincent %A Alver, Maris %A Evangelou, Evangelos %A Graff, Maria E %A He, Meian %A Kühnel, Brigitte %A Lyytikäinen, Leo-Pekka %A Marques-Vidal, Pedro %A Nolte, Ilja M %A Palmer, Nicholette D %A Rauramaa, Rainer %A Shu, Xiao-Ou %A Snieder, Harold %A Weiss, Stefan %A Wen, Wanqing %A Yanek, Lisa R %A Adolfo, Correa %A Ballantyne, Christie %A Bielak, Larry %A Biermasz, Nienke R %A Eric Boerwinkle %A Dimou, Niki %A Eiriksdottir, Gudny %A Gao, Chuan %A Gharib, Sina A %A Gottlieb, Daniel J %A Haba-Rubio, José %A Harris, Tamara B %A Heikkinen, Sami %A Heinzer, Raphaël %A Hixson, James E %A Homuth, Georg %A Ikram, M Arfan %A Komulainen, Pirjo %A Krieger, Jose E %A Lee, Jiwon %A Liu, Jingmin %A Lohman, Kurt K %A Luik, Annemarie I %A Mägi, Reedik %A Martin, Lisa W %A Meitinger, Thomas %A Metspalu, Andres %A Milaneschi, Yuri %A Nalls, Mike A %A O'Connell, Jeff %A Peters, Annette %A Peyser, Patricia %A Raitakari, Olli T %A Reiner, Alex P %A Rensen, Patrick C N %A Rice, Treva K %A Rich, Stephen S %A Roenneberg, Till %A Rotter, Jerome I %A Schreiner, Pamela J %A Shikany, James %A Sidney, Stephen S %A Sims, Mario %A Sitlani, Colleen M %A Sofer, Tamar %A Strauch, Konstantin %A Swertz, Morris A %A Taylor, Kent D %A Uitterlinden, André G %A van Duijn, Cornelia M %A Völzke, Henry %A Waldenberger, Melanie %A Wallance, Robert B %A van Dijk, Ko Willems %A Yu, Caizheng %A Zonderman, Alan B %A Becker, Diane M %A Elliott, Paul %A Esko, Tõnu %A Gieger, Christian %A Grabe, Hans J %A Lakka, Timo A %A Lehtimäki, Terho %A North, Kari E %A Penninx, Brenda W J H %A Vollenweider, Peter %A Wagenknecht, Lynne E %A Wu, Tangchun %A Xiang, Yong-Bing %A Zheng, Wei %A Arnett, Donna K %A Bouchard, Claude %A Evans, Michele K %A Gudnason, Vilmundur %A Kardia, Sharon %A Kelly, Tanika N %A Kritchevsky, Stephen B %A Loos, Ruth J F %A Pereira, Alexandre C %A Province, Mike %A Psaty, Bruce M %A Rotimi, Charles %A Zhu, Xiaofeng %A Amin, Najaf %A Cupples, L Adrienne %A Fornage, Myriam %A Fox, Ervin F %A Guo, Xiuqing %A Gauderman, W James %A Rice, Kenneth %A Kooperberg, Charles %A Munroe, Patricia B %A Liu, Ching-Ti %A Morrison, Alanna C %A Rao, Dabeeru C %A van Heemst, Diana %A Redline, Susan %K Adolescent %K Adult %K Aged %K Aged, 80 and over %K Chromosome Mapping %K Female %K Genetic Loci %K Humans %K Lipids %K Male %K Middle Aged %K Phylogeny %K Polymorphism, Single Nucleotide %K Sleep %K Young Adult %X

Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles.

%B Nat Commun %V 10 %P 5121 %8 2019 Nov 12 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/31719535?dopt=Abstract %R 10.1038/s41467-019-12958-0 %0 Journal Article %J Nat Genet %D 2019 %T Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. %A Turcot, Valérie %A Lu, Yingchang %A Highland, Heather M %A Schurmann, Claudia %A Justice, Anne E %A Fine, Rebecca S %A Bradfield, Jonathan P %A Esko, Tõnu %A Giri, Ayush %A Graff, Mariaelisa %A Guo, Xiuqing %A Hendricks, Audrey E %A Karaderi, Tugce %A Lempradl, Adelheid %A Locke, Adam E %A Mahajan, Anubha %A Marouli, Eirini %A Sivapalaratnam, Suthesh %A Young, Kristin L %A Alfred, Tamuno %A Feitosa, Mary F %A Masca, Nicholas G D %A Manning, Alisa K %A Medina-Gomez, Carolina %A Mudgal, Poorva %A Ng, Maggie C Y %A Reiner, Alex P %A Vedantam, Sailaja %A Willems, Sara M %A Winkler, Thomas W %A Abecasis, Goncalo %A Aben, Katja K %A Alam, Dewan S %A Alharthi, Sameer E %A Allison, Matthew %A Amouyel, Philippe %A Asselbergs, Folkert W %A Auer, Paul L %A Balkau, Beverley %A Bang, Lia E %A Barroso, Inês %A Bastarache, Lisa %A Benn, Marianne %A Bergmann, Sven %A Bielak, Lawrence F %A Blüher, Matthias %A Boehnke, Michael %A Boeing, Heiner %A Eric Boerwinkle %A Böger, Carsten A %A Bork-Jensen, Jette %A Bots, Michiel L %A Bottinger, Erwin P %A Bowden, Donald W %A Brandslund, Ivan %A Breen, Gerome %A Brilliant, Murray H %A Broer, Linda %A Brumat, Marco %A Burt, Amber A %A Butterworth, Adam S %A Campbell, Peter T %A Cappellani, Stefania %A Carey, David J %A Catamo, Eulalia %A Caulfield, Mark J %A Chambers, John C %A Chasman, Daniel I %A Chen, Yii-Der I %A Chowdhury, Rajiv %A Christensen, Cramer %A Chu, Audrey Y %A Cocca, Massimiliano %A Collins, Francis S %A Cook, James P %A Corley, Janie %A Galbany, Jordi Corominas %A Cox, Amanda J %A Crosslin, David S %A Cuellar-Partida, Gabriel %A D'Eustacchio, Angela %A Danesh, John %A Davies, Gail %A Bakker, Paul I W %A Groot, Mark C H %A Mutsert, Renée %A Deary, Ian J %A Dedoussis, George %A Demerath, Ellen W %A Heijer, Martin %A Hollander, Anneke I %A Ruijter, Hester M %A Dennis, Joe G %A Denny, Josh C %A Di Angelantonio, Emanuele %A Drenos, Fotios %A Du, Mengmeng %A Dube, Marie-Pierre %A Dunning, Alison M %A Easton, Douglas F %A Edwards, Todd L %A Ellinghaus, David %A Ellinor, Patrick T %A Elliott, Paul %A Evangelou, Evangelos %A Farmaki, Aliki-Eleni %A Farooqi, I Sadaf %A Faul, Jessica D %A Fauser, Sascha %A Feng, Shuang %A Ferrannini, Ele %A Ferrieres, Jean %A Florez, Jose C %A Ford, Ian %A Fornage, Myriam %A Franco, Oscar H %A Franke, Andre %A Franks, Paul W %A Friedrich, Nele %A Frikke-Schmidt, Ruth %A Galesloot, Tessel E %A Gan, Wei %A Gandin, Ilaria %A Gasparini, Paolo %A Gibson, Jane %A Giedraitis, Vilmantas %A Gjesing, Anette P %A Gordon-Larsen, Penny %A Gorski, Mathias %A Grabe, Hans-Jörgen %A Grant, Struan F A %A Grarup, Niels %A Griffiths, Helen L %A Grove, Megan L %A Gudnason, Vilmundur %A Gustafsson, Stefan %A Haessler, Jeff %A Hakonarson, Hakon %A Hammerschlag, Anke R %A Hansen, Torben %A Harris, Kathleen Mullan %A Harris, Tamara B %A Hattersley, Andrew T %A Have, Christian T %A Hayward, Caroline %A He, Liang %A Heard-Costa, Nancy L %A Heath, Andrew C %A Heid, Iris M %A Helgeland, Øyvind %A Hernesniemi, Jussi %A Hewitt, Alex W %A Holmen, Oddgeir L %A Hovingh, G Kees %A Howson, Joanna M M %A Hu, Yao %A Huang, Paul L %A Huffman, Jennifer E %A Ikram, M Arfan %A Ingelsson, Erik %A Jackson, Anne U %A Jansson, Jan-Håkan %A Jarvik, Gail P %A Jensen, Gorm B %A Jia, Yucheng %A Johansson, Stefan %A Jørgensen, Marit E %A Jørgensen, Torben %A Jukema, J Wouter %A Kahali, Bratati %A Kahn, René S %A Kähönen, Mika %A Kamstrup, Pia R %A Kanoni, Stavroula %A Kaprio, Jaakko %A Karaleftheri, Maria %A Kardia, Sharon L R %A Karpe, Fredrik %A Kathiresan, Sekar %A Kee, Frank %A Kiemeney, Lambertus A %A Kim, Eric %A Kitajima, Hidetoshi %A Komulainen, Pirjo %A Kooner, Jaspal S %A Kooperberg, Charles %A Korhonen, Tellervo %A Kovacs, Peter %A Kuivaniemi, Helena %A Kutalik, Zoltán %A Kuulasmaa, Kari %A Kuusisto, Johanna %A Laakso, Markku %A Lakka, Timo A %A Lamparter, David %A Lange, Ethan M %A Lange, Leslie A %A Langenberg, Claudia %A Larson, Eric B %A Lee, Nanette R %A Lehtimäki, Terho %A Lewis, Cora E %A Li, Huaixing %A Li, Jin %A Li-Gao, Ruifang %A Lin, Honghuang %A Lin, Keng-Hung %A Lin, Li-An %A Lin, Xu %A Lind, Lars %A Lindström, Jaana %A Linneberg, Allan %A Liu, Ching-Ti %A Liu, Dajiang J %A Liu, Yongmei %A Lo, Ken S %A Lophatananon, Artitaya %A Lotery, Andrew J %A Loukola, Anu %A Luan, Jian'an %A Lubitz, Steven A %A Lyytikäinen, Leo-Pekka %A Männistö, Satu %A Marenne, Gaëlle %A Mazul, Angela L %A McCarthy, Mark I %A McKean-Cowdin, Roberta %A Medland, Sarah E %A Meidtner, Karina %A Milani, Lili %A Mistry, Vanisha %A Mitchell, Paul %A Mohlke, Karen L %A Moilanen, Leena %A Moitry, Marie %A Montgomery, Grant W %A Mook-Kanamori, Dennis O %A Moore, Carmel %A Mori, Trevor A %A Morris, Andrew D %A Morris, Andrew P %A Müller-Nurasyid, Martina %A Munroe, Patricia B %A Nalls, Mike A %A Narisu, Narisu %A Nelson, Christopher P %A Neville, Matt %A Nielsen, Sune F %A Nikus, Kjell %A Njølstad, Pål R %A Nordestgaard, Børge G %A Nyholt, Dale R %A O'Connel, Jeffrey R %A O'Donoghue, Michelle L %A Loohuis, Loes M Olde %A Ophoff, Roel A %A Owen, Katharine R %A Packard, Chris J %A Padmanabhan, Sandosh %A Palmer, Colin N A %A Palmer, Nicholette D %A Pasterkamp, Gerard %A Patel, Aniruddh P %A Pattie, Alison %A Pedersen, Oluf %A Peissig, Peggy L %A Peloso, Gina M %A Pennell, Craig E %A Perola, Markus %A Perry, James A %A Perry, John R B %A Pers, Tune H %A Person, Thomas N %A Peters, Annette %A Petersen, Eva R B %A Peyser, Patricia A %A Pirie, Ailith %A Polasek, Ozren %A Polderman, Tinca J %A Puolijoki, Hannu %A Raitakari, Olli T %A Rasheed, Asif %A Rauramaa, Rainer %A Reilly, Dermot F %A Renstrom, Frida %A Rheinberger, Myriam %A Ridker, Paul M %A 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An amendment to this paper has been published and can be accessed via a link at the top of the paper.

%B Nat Genet %V 51 %P 1191-1192 %8 2019 Jul %G eng %N 7 %1 https://www.ncbi.nlm.nih.gov/pubmed/31160809?dopt=Abstract %R 10.1038/s41588-019-0447-2 %0 Journal Article %J PLoS Genet %D 2019 %T Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations. %A Kowalski, Madeline H %A Qian, Huijun %A Hou, Ziyi %A Rosen, Jonathan D %A Tapia, Amanda L %A Shan, Yue %A Jain, Deepti %A Argos, Maria %A Arnett, Donna K %A Avery, Christy %A Barnes, Kathleen C %A Becker, Lewis C %A Bien, Stephanie A %A Bis, Joshua C %A Blangero, John %A Eric Boerwinkle %A Bowden, Donald W %A Buyske, Steve %A Cai, Jianwen %A Cho, Michael H %A Choi, Seung Hoan %A Choquet, Hélène %A Cupples, L Adrienne %A Cushman, Mary %A Daya, Michelle %A de Vries, Paul S %A Ellinor, Patrick T %A Faraday, Nauder %A Fornage, Myriam %A Gabriel, Stacey %A Ganesh, Santhi K %A Graff, Misa %A Gupta, Namrata %A He, Jiang %A Heckbert, Susan R %A Hidalgo, Bertha %A Hodonsky, Chani J %A Irvin, Marguerite R %A Johnson, Andrew D %A Jorgenson, Eric %A Kaplan, Robert %A Kardia, Sharon L R %A Kelly, Tanika N %A Kooperberg, Charles %A Lasky-Su, Jessica A %A Loos, Ruth J F %A Lubitz, Steven A %A Mathias, Rasika A %A McHugh, Caitlin P %A Montgomery, Courtney %A Moon, Jee-Young %A Morrison, Alanna C %A Palmer, Nicholette D %A Pankratz, Nathan %A Papanicolaou, George J %A Peralta, Juan M %A Peyser, Patricia A %A Rich, Stephen S %A Rotter, Jerome I %A Silverman, Edwin K %A Smith, Jennifer A %A Smith, Nicholas L %A Taylor, Kent D %A Thornton, Timothy A %A Tiwari, Hemant K %A Tracy, Russell P %A Wang, Tao %A Weiss, Scott T %A Weng, Lu-Chen %A Wiggins, Kerri L %A Wilson, James G %A Yanek, Lisa R %A Zöllner, Sebastian %A North, Kari E %A Auer, Paul L %A Raffield, Laura M %A Reiner, Alexander P %A Li, Yun %K Adult %K Aged %K Aged, 80 and over %K beta-Globins %K Black or African American %K Computational Biology %K Databases, Genetic %K Female %K Gene Frequency %K Genetic Predisposition to Disease %K Genetics, Population %K Genome-Wide Association Study %K Genotyping Techniques %K Hispanic or Latino %K Humans %K Linkage Disequilibrium %K Male %K Middle Aged %K Precision Medicine %K United States %K Whole Genome Sequencing %X

Most genome-wide association and fine-mapping studies to date have been conducted in individuals of European descent, and genetic studies of populations of Hispanic/Latino and African ancestry are limited. In addition, these populations have more complex linkage disequilibrium structure. In order to better define the genetic architecture of these understudied populations, we leveraged >100,000 phased sequences available from deep-coverage whole genome sequencing through the multi-ethnic NHLBI Trans-Omics for Precision Medicine (TOPMed) program to impute genotypes into admixed African and Hispanic/Latino samples with genome-wide genotyping array data. We demonstrated that using TOPMed sequencing data as the imputation reference panel improves genotype imputation quality in these populations, which subsequently enhanced gene-mapping power for complex traits. For rare variants with minor allele frequency (MAF) < 0.5%, we observed a 2.3- to 6.1-fold increase in the number of well-imputed variants, with 11-34% improvement in average imputation quality, compared to the state-of-the-art 1000 Genomes Project Phase 3 and Haplotype Reference Consortium reference panels. Impressively, even for extremely rare variants with minor allele count <10 (including singletons) in the imputation target samples, average information content rescued was >86%. Subsequent association analyses of TOPMed reference panel-imputed genotype data with hematological traits (hemoglobin (HGB), hematocrit (HCT), and white blood cell count (WBC)) in ~21,600 African-ancestry and ~21,700 Hispanic/Latino individuals identified associations with two rare variants in the HBB gene (rs33930165 with higher WBC [p = 8.8x10-15] in African populations, rs11549407 with lower HGB [p = 1.5x10-12] and HCT [p = 8.8x10-10] in Hispanics/Latinos). By comparison, neither variant would have been genome-wide significant if either 1000 Genomes Project Phase 3 or Haplotype Reference Consortium reference panels had been used for imputation. Our findings highlight the utility of the TOPMed imputation reference panel for identification of novel rare variant associations not previously detected in similarly sized genome-wide studies of under-represented African and Hispanic/Latino populations.

%B PLoS Genet %V 15 %P e1008500 %8 2019 Dec %G eng %N 12 %1 https://www.ncbi.nlm.nih.gov/pubmed/31869403?dopt=Abstract %R 10.1371/journal.pgen.1008500 %0 Journal Article %J Am J Hum Genet %D 2018 %T Genome Analyses of >200,000 Individuals Identify 58 Loci for Chronic Inflammation and Highlight Pathways that Link Inflammation and Complex Disorders. %A Ligthart, Symen %A Vaez, Ahmad %A Võsa, Urmo %A Stathopoulou, Maria G %A de Vries, Paul S %A Prins, Bram P %A van der Most, Peter J %A Tanaka, Toshiko %A Naderi, Elnaz %A Rose, Lynda M %A Wu, Ying %A Karlsson, Robert %A Barbalic, Maja %A Lin, Honghuang %A Pool, René %A Zhu, Gu %A Macé, Aurélien %A Sidore, Carlo %A Trompet, Stella %A Mangino, Massimo %A Sabater-Lleal, Maria %A Kemp, John P %A Abbasi, Ali %A Kacprowski, Tim %A Verweij, Niek %A Smith, Albert V %A Huang, Tao %A Marzi, Carola %A Feitosa, Mary F %A Lohman, Kurt K %A Kleber, Marcus E %A Milaneschi, Yuri %A Mueller, Christian %A Huq, Mahmudul %A Vlachopoulou, Efthymia %A Lyytikäinen, Leo-Pekka %A Oldmeadow, Christopher %A Deelen, Joris %A Perola, Markus %A Zhao, Jing Hua %A Feenstra, Bjarke %A Amini, Marzyeh %A Lahti, Jari %A Schraut, Katharina E %A Fornage, Myriam %A Suktitipat, Bhoom %A Chen, Wei-Min %A Li, Xiaohui %A Nutile, Teresa %A Malerba, Giovanni %A Luan, Jian'an %A Bak, Tom %A Schork, Nicholas %A Del Greco M, Fabiola %A Thiering, Elisabeth %A Mahajan, Anubha %A Marioni, Riccardo E %A Mihailov, Evelin %A Eriksson, Joel %A Ozel, Ayse Bilge %A Zhang, Weihua %A Nethander, Maria %A Cheng, Yu-Ching %A Aslibekyan, Stella %A Ang, Wei %A Gandin, Ilaria %A Yengo, Loic %A Portas, Laura %A Kooperberg, Charles %A Hofer, Edith %A Rajan, Kumar B %A Schurmann, Claudia %A den Hollander, Wouter %A Ahluwalia, Tarunveer S %A Zhao, Jing %A Draisma, Harmen H M %A Ford, Ian %A Timpson, Nicholas %A Teumer, Alexander %A Huang, Hongyan %A Wahl, Simone %A Liu, Yongmei %A Huang, Jie %A Uh, Hae-Won %A Geller, Frank %A Joshi, Peter K %A Yanek, Lisa R %A Trabetti, Elisabetta %A Lehne, Benjamin %A Vozzi, Diego %A Verbanck, Marie %A Biino, Ginevra %A Saba, Yasaman %A Meulenbelt, Ingrid %A O'Connell, Jeff R %A Laakso, Markku %A Giulianini, Franco %A Magnusson, Patrik K E %A Ballantyne, Christie M %A Hottenga, Jouke Jan %A Montgomery, Grant W %A Rivadineira, Fernando %A Rueedi, Rico %A Steri, Maristella %A Herzig, Karl-Heinz %A Stott, David J %A Menni, Cristina %A Frånberg, Mattias %A St Pourcain, Beate %A Felix, Stephan B %A Pers, Tune H %A Bakker, Stephan J L %A Kraft, Peter %A Peters, Annette %A Vaidya, Dhananjay %A Delgado, Graciela %A Smit, Johannes H %A Großmann, Vera %A Sinisalo, Juha %A Seppälä, Ilkka %A Williams, Stephen R %A Holliday, Elizabeth G %A Moed, Matthijs %A Langenberg, Claudia %A Räikkönen, Katri %A Ding, Jingzhong %A Campbell, Harry %A Sale, Michele M %A Chen, Yii-Der I %A James, Alan L %A Ruggiero, Daniela %A Soranzo, Nicole %A Hartman, Catharina A %A Smith, Erin N %A Berenson, Gerald S %A Fuchsberger, Christian %A Hernandez, Dena %A Tiesler, Carla M T %A Giedraitis, Vilmantas %A Liewald, David %A Fischer, Krista %A Mellström, Dan %A Larsson, Anders %A Wang, Yunmei %A Scott, William R %A Lorentzon, Matthias %A Beilby, John %A Ryan, Kathleen A %A Pennell, Craig E %A Vuckovic, Dragana %A Balkau, Beverly %A Concas, Maria Pina %A Schmidt, Reinhold %A Mendes de Leon, Carlos F %A Bottinger, Erwin P %A Kloppenburg, Margreet %A Paternoster, Lavinia %A Boehnke, Michael %A Musk, A W %A Willemsen, Gonneke %A Evans, David M %A Madden, Pamela A F %A Kähönen, Mika %A Kutalik, Zoltán %A Zoledziewska, Magdalena %A Karhunen, Ville %A Kritchevsky, Stephen B %A Sattar, Naveed %A Lachance, Genevieve %A Clarke, Robert %A Harris, Tamara B %A Raitakari, Olli T %A Attia, John R %A van Heemst, Diana %A Kajantie, Eero %A Sorice, Rossella %A Gambaro, Giovanni %A Scott, Robert A %A Hicks, Andrew A %A Ferrucci, Luigi %A Standl, Marie %A Lindgren, Cecilia M %A Starr, John M %A Karlsson, Magnus %A Lind, Lars %A Li, Jun Z %A Chambers, John C %A Mori, Trevor A %A de Geus, Eco J C N %A Heath, Andrew C %A Martin, Nicholas G %A Auvinen, Juha %A Buckley, Brendan M %A de Craen, Anton J M %A Waldenberger, Melanie %A Strauch, Konstantin %A Meitinger, Thomas %A Scott, Rodney J %A McEvoy, Mark %A Beekman, Marian %A Bombieri, Cristina %A Ridker, Paul M %A Mohlke, Karen L %A Pedersen, Nancy L %A Morrison, Alanna C %A Boomsma, Dorret I %A Whitfield, John B %A Strachan, David P %A Hofman, Albert %A Vollenweider, Peter %A Cucca, Francesco %A Jarvelin, Marjo-Riitta %A Jukema, J Wouter %A Spector, Tim D %A Hamsten, Anders %A Zeller, Tanja %A Uitterlinden, André G %A Nauck, Matthias %A Gudnason, Vilmundur %A Qi, Lu %A Grallert, Harald %A Borecki, Ingrid B %A Rotter, Jerome I %A Marz, Winfried %A Wild, Philipp S %A Lokki, Marja-Liisa %A Boyle, Michael %A Salomaa, Veikko %A Melbye, Mads %A Eriksson, Johan G %A Wilson, James F %A Penninx, Brenda W J H %A Becker, Diane M %A Worrall, Bradford B %A Gibson, Greg %A Krauss, Ronald M %A Ciullo, Marina %A Zaza, Gianluigi %A Wareham, Nicholas J %A Oldehinkel, Albertine J %A Palmer, Lyle J %A Murray, Sarah S %A Pramstaller, Peter P %A Bandinelli, Stefania %A Heinrich, Joachim %A Ingelsson, Erik %A Deary, Ian J %A Mägi, Reedik %A Vandenput, Liesbeth %A van der Harst, Pim %A Desch, Karl C %A Kooner, Jaspal S %A Ohlsson, Claes %A Hayward, Caroline %A Lehtimäki, Terho %A Shuldiner, Alan R %A Arnett, Donna K %A Beilin, Lawrence J %A Robino, Antonietta %A Froguel, Philippe %A Pirastu, Mario %A Jess, Tine %A Koenig, Wolfgang %A Loos, Ruth J F %A Evans, Denis A %A Schmidt, Helena %A Smith, George Davey %A Slagboom, P Eline %A Eiriksdottir, Gudny %A Morris, Andrew P %A Psaty, Bruce M %A Tracy, Russell P %A Nolte, Ilja M %A Eric Boerwinkle %A Visvikis-Siest, Sophie %A Reiner, Alex P %A Gross, Myron %A Bis, Joshua C %A Franke, Lude %A Franco, Oscar H %A Benjamin, Emelia J %A Chasman, Daniel I %A Dupuis, Josée %A Snieder, Harold %A Dehghan, Abbas %A Alizadeh, Behrooz Z %K Adolescent %K Adult %K Aged %K Aged, 80 and over %K Biomarkers %K Bipolar Disorder %K Body Mass Index %K C-Reactive Protein %K Child %K Female %K Genetic Loci %K Genome-Wide Association Study %K Humans %K Inflammation %K Liver %K Male %K Mendelian Randomization Analysis %K Metabolic Networks and Pathways %K Middle Aged %K Schizophrenia %K Young Adult %X

C-reactive protein (CRP) is a sensitive biomarker of chronic low-grade inflammation and is associated with multiple complex diseases. The genetic determinants of chronic inflammation remain largely unknown, and the causal role of CRP in several clinical outcomes is debated. We performed two genome-wide association studies (GWASs), on HapMap and 1000 Genomes imputed data, of circulating amounts of CRP by using data from 88 studies comprising 204,402 European individuals. Additionally, we performed in silico functional analyses and Mendelian randomization analyses with several clinical outcomes. The GWAS meta-analyses of CRP revealed 58 distinct genetic loci (p < 5 × 10). After adjustment for body mass index in the regression analysis, the associations at all except three loci remained. The lead variants at the distinct loci explained up to 7.0% of the variance in circulating amounts of CRP. We identified 66 gene sets that were organized in two substantially correlated clusters, one mainly composed of immune pathways and the other characterized by metabolic pathways in the liver. Mendelian randomization analyses revealed a causal protective effect of CRP on schizophrenia and a risk-increasing effect on bipolar disorder. Our findings provide further insights into the biology of inflammation and could lead to interventions for treating inflammation and its clinical consequences.

%B Am J Hum Genet %V 103 %P 691-706 %8 2018 Nov 01 %G eng %N 5 %1 https://www.ncbi.nlm.nih.gov/pubmed/30388399?dopt=Abstract %R 10.1016/j.ajhg.2018.09.009 %0 Journal Article %J PLoS One %D 2018 %T Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries. %A Feitosa, Mary F %A Kraja, Aldi T %A Chasman, Daniel I %A Sung, Yun J %A Winkler, Thomas W %A Ntalla, Ioanna %A Guo, Xiuqing %A Franceschini, Nora %A Cheng, Ching-Yu %A Sim, Xueling %A Vojinovic, Dina %A Marten, Jonathan %A Musani, Solomon K %A Li, Changwei %A Bentley, Amy R %A Brown, Michael R %A Schwander, Karen %A Richard, Melissa A %A Noordam, Raymond %A Aschard, Hugues %A Bartz, Traci M %A Bielak, Lawrence F %A Dorajoo, Rajkumar %A Fisher, Virginia %A Hartwig, Fernando P %A Horimoto, Andrea R V R %A Lohman, Kurt K %A Manning, Alisa K %A Rankinen, Tuomo %A Smith, Albert V %A Tajuddin, Salman M %A Wojczynski, Mary K %A Alver, Maris %A Boissel, Mathilde %A Cai, Qiuyin %A Campbell, Archie %A Chai, Jin Fang %A Chen, Xu %A Divers, Jasmin %A Gao, Chuan %A Goel, Anuj %A Hagemeijer, Yanick %A Harris, Sarah E %A He, Meian %A Hsu, Fang-Chi %A Jackson, Anne U %A Kähönen, Mika %A Kasturiratne, Anuradhani %A Komulainen, Pirjo %A Kühnel, Brigitte %A Laguzzi, Federica %A Luan, Jian'an %A Matoba, Nana %A Nolte, Ilja M %A Padmanabhan, Sandosh %A Riaz, Muhammad %A Rueedi, Rico %A Robino, Antonietta %A Said, M Abdullah %A Scott, Robert A %A Sofer, Tamar %A Stančáková, Alena %A Takeuchi, Fumihiko %A Tayo, Bamidele O %A van der Most, Peter J %A Varga, Tibor V %A Vitart, Veronique %A Wang, Yajuan %A Ware, Erin B %A Warren, Helen R %A Weiss, Stefan %A Wen, Wanqing %A Yanek, Lisa R %A Zhang, Weihua %A Zhao, Jing Hua %A Afaq, Saima %A Amin, Najaf %A Amini, Marzyeh %A Arking, Dan E %A Aung, Tin %A Eric Boerwinkle %A Borecki, Ingrid %A Broeckel, Ulrich %A Brown, Morris %A Brumat, Marco %A Burke, Gregory L %A Canouil, Mickaël %A Chakravarti, Aravinda %A Charumathi, Sabanayagam %A Ida Chen, Yii-Der %A Connell, John M %A Correa, Adolfo %A de Las Fuentes, Lisa %A de Mutsert, Renée %A de Silva, H Janaka %A Deng, Xuan %A Ding, Jingzhong %A Duan, Qing %A Eaton, Charles B %A Ehret, Georg %A Eppinga, Ruben N %A Evangelou, Evangelos %A Faul, Jessica D %A Felix, Stephan B %A Forouhi, Nita G %A Forrester, Terrence %A Franco, Oscar H %A Friedlander, Yechiel %A Gandin, Ilaria %A Gao, He %A Ghanbari, Mohsen %A Gigante, Bruna %A Gu, C Charles %A Gu, Dongfeng %A Hagenaars, Saskia P %A Hallmans, Goran %A Harris, Tamara B %A He, Jiang %A Heikkinen, Sami %A Heng, Chew-Kiat %A Hirata, Makoto %A Howard, Barbara V %A Ikram, M Arfan %A John, Ulrich %A Katsuya, Tomohiro %A Khor, Chiea Chuen %A Kilpeläinen, Tuomas O %A Koh, Woon-Puay %A Krieger, Jose E %A Kritchevsky, Stephen B %A Kubo, Michiaki %A Kuusisto, Johanna %A Lakka, Timo A %A Langefeld, Carl D %A Langenberg, Claudia %A Launer, Lenore J %A Lehne, Benjamin %A Lewis, Cora E %A Li, Yize %A Lin, Shiow %A Liu, Jianjun %A Liu, Jingmin %A Loh, Marie %A Louie, Tin %A Mägi, Reedik %A McKenzie, Colin A %A Meitinger, Thomas %A Metspalu, Andres %A Milaneschi, Yuri %A Milani, Lili %A Mohlke, Karen L %A Momozawa, Yukihide %A Nalls, Mike A %A Nelson, Christopher P %A Sotoodehnia, Nona %A Norris, Jill M %A O'Connell, Jeff R %A Palmer, Nicholette D %A Perls, Thomas %A Pedersen, Nancy L %A Peters, Annette %A Peyser, Patricia A %A Poulter, Neil %A Raffel, Leslie J %A Raitakari, Olli T %A Roll, Kathryn %A Rose, Lynda M %A Rosendaal, Frits R %A Rotter, Jerome I %A Schmidt, Carsten O %A Schreiner, Pamela J %A Schupf, Nicole %A Scott, William R %A Sever, Peter S %A Shi, Yuan %A Sidney, Stephen %A Sims, Mario %A Sitlani, Colleen M %A Smith, Jennifer A %A Snieder, Harold %A Starr, John M %A Strauch, Konstantin %A Stringham, Heather M %A Tan, Nicholas Y Q %A Tang, Hua %A Taylor, Kent D %A Teo, Yik Ying %A Tham, Yih Chung %A Turner, Stephen T %A Uitterlinden, André G %A Vollenweider, Peter %A Waldenberger, Melanie %A Wang, Lihua %A Wang, Ya Xing %A Wei, Wen Bin %A Williams, Christine %A Yao, Jie %A Yu, Caizheng %A Yuan, Jian-Min %A Zhao, Wei %A Zonderman, Alan B %A Becker, Diane M %A Boehnke, Michael %A Bowden, Donald W %A Chambers, John C %A Deary, Ian J %A Esko, Tõnu %A Farrall, Martin %A Franks, Paul W %A Freedman, Barry I %A Froguel, Philippe %A Gasparini, Paolo %A Gieger, Christian %A Jonas, Jost Bruno %A Kamatani, Yoichiro %A Kato, Norihiro %A Kooner, Jaspal S %A Kutalik, Zoltán %A Laakso, Markku %A Laurie, Cathy C %A Leander, Karin %A Lehtimäki, Terho %A Study, Lifelines Cohort %A Magnusson, Patrik K E %A Oldehinkel, Albertine J %A Penninx, Brenda W J H %A Polasek, Ozren %A Porteous, David J %A Rauramaa, Rainer %A Samani, Nilesh J %A Scott, James %A Shu, Xiao-Ou %A van der Harst, Pim %A Wagenknecht, Lynne E %A Wareham, Nicholas J %A Watkins, Hugh %A Weir, David R %A Wickremasinghe, Ananda R %A Wu, Tangchun %A Zheng, Wei %A Bouchard, Claude %A Christensen, Kaare %A Evans, Michele K %A Gudnason, Vilmundur %A Horta, Bernardo L %A Kardia, Sharon L R %A Liu, Yongmei %A Pereira, Alexandre C %A Psaty, Bruce M %A Ridker, Paul M %A van Dam, Rob M %A Gauderman, W James %A Zhu, Xiaofeng %A Mook-Kanamori, Dennis O %A Fornage, Myriam %A Rotimi, Charles N %A Cupples, L Adrienne %A Kelly, Tanika N %A Fox, Ervin R %A Hayward, Caroline %A van Duijn, Cornelia M %A Tai, E Shyong %A Wong, Tien Yin %A Kooperberg, Charles %A Palmas, Walter %A Rice, Kenneth %A Morrison, Alanna C %A Elliott, Paul %A Caulfield, Mark J %A Munroe, Patricia B %A Rao, Dabeeru C %A Province, Michael A %A Levy, Daniel %K Adolescent %K Adult %K Aged %K Aged, 80 and over %K Alcohol Drinking %K Blood Pressure %K Cohort Studies %K Female %K Gene-Environment Interaction %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Hypertension %K Male %K Middle Aged %K Pedigree %K Polymorphism, Single Nucleotide %K Racial Groups %K Young Adult %X

Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.

%B PLoS One %V 13 %P e0198166 %8 2018 %G eng %N 6 %1 https://www.ncbi.nlm.nih.gov/pubmed/29912962?dopt=Abstract %R 10.1371/journal.pone.0198166 %0 Journal Article %J Nat Genet %D 2018 %T Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. %A Turcot, Valérie %A Lu, Yingchang %A Highland, Heather M %A Schurmann, Claudia %A Justice, Anne E %A Fine, Rebecca S %A Bradfield, Jonathan P %A Esko, Tõnu %A Giri, Ayush %A Graff, Mariaelisa %A Guo, Xiuqing %A Hendricks, Audrey E %A Karaderi, Tugce %A Lempradl, Adelheid %A Locke, Adam E %A Mahajan, Anubha %A Marouli, Eirini %A Sivapalaratnam, Suthesh %A Young, Kristin L %A Alfred, Tamuno %A Feitosa, Mary F %A Masca, Nicholas G D %A Manning, Alisa K %A Medina-Gomez, Carolina %A Mudgal, Poorva %A Ng, Maggie C Y %A Reiner, Alex P %A Vedantam, Sailaja %A Willems, Sara M %A Winkler, Thomas W %A Abecasis, Goncalo %A Aben, Katja K %A Alam, Dewan S %A Alharthi, Sameer E %A Allison, Matthew %A Amouyel, Philippe %A Asselbergs, Folkert W %A Auer, Paul L %A Balkau, Beverley %A Bang, Lia E %A Barroso, Inês %A Bastarache, Lisa %A Benn, Marianne %A Bergmann, Sven %A Bielak, Lawrence F %A Blüher, Matthias %A Boehnke, Michael %A Boeing, Heiner %A Eric Boerwinkle %A Böger, Carsten A %A Bork-Jensen, Jette %A Bots, Michiel L %A Bottinger, Erwin P %A Bowden, Donald W %A Brandslund, Ivan %A Breen, Gerome %A Brilliant, Murray H %A Broer, Linda %A Brumat, Marco %A Burt, Amber A %A Butterworth, Adam S %A Campbell, Peter T %A Cappellani, Stefania %A Carey, David J %A Catamo, Eulalia %A Caulfield, Mark J %A Chambers, John C %A Chasman, Daniel I %A Chen, Yii-Der I %A Chowdhury, Rajiv %A Christensen, Cramer %A Chu, Audrey Y %A Cocca, Massimiliano %A Collins, Francis S %A Cook, James P %A Corley, Janie %A Corominas Galbany, Jordi %A Cox, Amanda J %A Crosslin, David S %A Cuellar-Partida, Gabriel %A D'Eustacchio, Angela %A Danesh, John %A Davies, Gail %A Bakker, Paul I W %A Groot, Mark C H %A Mutsert, Renée %A Deary, Ian J %A Dedoussis, George %A Demerath, Ellen W %A Heijer, Martin %A Hollander, Anneke I %A Ruijter, Hester M %A Dennis, Joe G %A Denny, Josh C %A Di Angelantonio, Emanuele %A Drenos, Fotios %A Du, Mengmeng %A Dube, Marie-Pierre %A Dunning, Alison M %A Easton, Douglas F %A Edwards, Todd L %A Ellinghaus, David %A Ellinor, Patrick T %A Elliott, Paul %A Evangelou, Evangelos %A Farmaki, Aliki-Eleni %A Farooqi, I Sadaf %A Faul, Jessica D %A Fauser, Sascha %A Feng, Shuang %A Ferrannini, Ele %A Ferrieres, Jean %A Florez, Jose C %A Ford, Ian %A Fornage, Myriam %A Franco, Oscar H %A Franke, Andre %A Franks, Paul W %A Friedrich, Nele %A Frikke-Schmidt, Ruth %A Galesloot, Tessel E %A Gan, Wei %A Gandin, Ilaria %A Gasparini, Paolo %A Gibson, Jane %A Giedraitis, Vilmantas %A Gjesing, Anette P %A Gordon-Larsen, Penny %A Gorski, Mathias %A Grabe, Hans-Jörgen %A Grant, Struan F A %A Grarup, Niels %A Griffiths, Helen L %A Grove, Megan L %A Gudnason, Vilmundur %A Gustafsson, Stefan %A Haessler, Jeff %A Hakonarson, Hakon %A Hammerschlag, Anke R %A Hansen, Torben %A Harris, Kathleen Mullan %A Harris, Tamara B %A Hattersley, Andrew T %A Have, Christian T %A Hayward, Caroline %A He, Liang %A Heard-Costa, Nancy L %A Heath, Andrew C %A Heid, Iris M %A Helgeland, Øyvind %A Hernesniemi, Jussi %A Hewitt, Alex W %A Holmen, Oddgeir L %A Hovingh, G Kees %A Howson, Joanna M M %A Hu, Yao %A Huang, Paul L %A Huffman, Jennifer E %A Ikram, M Arfan %A Ingelsson, Erik %A Jackson, Anne U %A Jansson, Jan-Håkan %A Jarvik, Gail P %A Jensen, Gorm B %A Jia, Yucheng %A Johansson, Stefan %A Jørgensen, Marit E %A Jørgensen, Torben %A Jukema, J Wouter %A Kahali, Bratati %A Kahn, René S %A Kähönen, Mika %A Kamstrup, Pia R %A Kanoni, Stavroula %A Kaprio, Jaakko %A Karaleftheri, Maria %A Kardia, Sharon L R %A Karpe, Fredrik %A Kathiresan, Sekar %A Kee, Frank %A Kiemeney, Lambertus A %A Kim, Eric %A Kitajima, Hidetoshi %A Komulainen, Pirjo %A Kooner, Jaspal S %A Kooperberg, Charles %A Korhonen, Tellervo %A Kovacs, Peter %A Kuivaniemi, Helena %A Kutalik, Zoltán %A Kuulasmaa, Kari %A Kuusisto, Johanna %A Laakso, Markku %A Lakka, Timo A %A Lamparter, David %A Lange, Ethan M %A Lange, Leslie A %A Langenberg, Claudia %A Larson, Eric B %A Lee, Nanette R %A Lehtimäki, Terho %A Lewis, Cora E %A Li, Huaixing %A Li, Jin %A Li-Gao, Ruifang %A Lin, Honghuang %A Lin, Keng-Hung %A Lin, Li-An %A Lin, Xu %A Lind, Lars %A Lindström, Jaana %A Linneberg, Allan %A Liu, Ching-Ti %A Liu, Dajiang J %A Liu, Yongmei %A Lo, Ken S %A Lophatananon, Artitaya %A Lotery, Andrew J %A Loukola, Anu %A Luan, Jian'an %A Lubitz, Steven A %A Lyytikäinen, Leo-Pekka %A Männistö, Satu %A Marenne, Gaëlle %A Mazul, Angela L %A McCarthy, Mark I %A McKean-Cowdin, Roberta %A Medland, Sarah E %A Meidtner, Karina %A Milani, Lili %A Mistry, Vanisha %A Mitchell, Paul %A Mohlke, Karen L %A Moilanen, Leena %A Moitry, Marie %A Montgomery, Grant W %A Mook-Kanamori, Dennis O %A Moore, Carmel %A Mori, Trevor A %A Morris, Andrew D %A Morris, Andrew P %A Müller-Nurasyid, Martina %A Munroe, Patricia B %A Nalls, Mike A %A Narisu, Narisu %A Nelson, Christopher P %A Neville, Matt %A Nielsen, Sune F %A Nikus, Kjell %A Njølstad, Pål R %A Nordestgaard, Børge G %A Nyholt, Dale R %A O'Connel, Jeffrey R %A O'Donoghue, Michelle L %A Olde Loohuis, Loes M %A Ophoff, Roel A %A Owen, Katharine R %A Packard, Chris J %A Padmanabhan, Sandosh %A Palmer, Colin N A %A Palmer, Nicholette D %A Pasterkamp, Gerard %A Patel, Aniruddh P %A Pattie, Alison %A Pedersen, Oluf %A Peissig, Peggy L %A Peloso, Gina M %A Pennell, Craig E %A Perola, Markus %A Perry, James A %A Perry, John R B %A Pers, Tune H %A Person, Thomas N %A Peters, Annette %A Petersen, Eva R B %A Peyser, Patricia A %A Pirie, Ailith %A Polasek, Ozren %A Polderman, Tinca J %A Puolijoki, Hannu %A Raitakari, Olli T %A Rasheed, Asif %A Rauramaa, Rainer %A Reilly, Dermot F %A Renstrom, Frida %A Rheinberger, Myriam %A Ridker, Paul M %A Rioux, John D %A Rivas, Manuel A %A Roberts, David J %A Robertson, Neil R %A Robino, Antonietta %A Rolandsson, Olov %A Rudan, Igor %A Ruth, Katherine S %A Saleheen, Danish %A Salomaa, Veikko %A Samani, Nilesh J %A Sapkota, Yadav %A Sattar, Naveed %A Schoen, Robert E %A Schreiner, Pamela J %A Schulze, Matthias B %A Scott, Robert A %A Segura-Lepe, Marcelo P %A Shah, Svati H %A Sheu, Wayne H-H %A Sim, Xueling %A Slater, Andrew J %A Small, Kerrin S %A Smith, Albert V %A Southam, Lorraine %A Spector, Timothy D %A Speliotes, Elizabeth K %A Starr, John M %A Stefansson, Kari %A Steinthorsdottir, Valgerdur %A Stirrups, Kathleen E %A Strauch, Konstantin %A Stringham, Heather M %A Stumvoll, Michael %A Sun, Liang %A Surendran, Praveen %A Swift, Amy J %A Tada, Hayato %A Tansey, Katherine E %A Tardif, Jean-Claude %A Taylor, Kent D %A Teumer, Alexander %A Thompson, Deborah J %A Thorleifsson, Gudmar %A Thorsteinsdottir, Unnur %A Thuesen, Betina H %A Tonjes, Anke %A Tromp, Gerard %A Trompet, Stella %A Tsafantakis, Emmanouil %A Tuomilehto, Jaakko %A Tybjaerg-Hansen, Anne %A Tyrer, Jonathan P %A Uher, Rudolf %A Uitterlinden, André G %A Uusitupa, Matti %A Laan, Sander W %A Duijn, Cornelia M %A Leeuwen, Nienke %A van Setten, Jessica %A Vanhala, Mauno %A Varbo, Anette %A Varga, Tibor V %A Varma, Rohit %A Velez Edwards, Digna R %A Vermeulen, Sita H %A Veronesi, Giovanni %A Vestergaard, Henrik %A Vitart, Veronique %A Vogt, Thomas F %A Völker, Uwe %A Vuckovic, Dragana %A Wagenknecht, Lynne E %A Walker, Mark %A Wallentin, Lars %A Wang, Feijie %A Wang, Carol A %A Wang, Shuai %A Wang, Yiqin %A Ware, Erin B %A Wareham, Nicholas J %A Warren, Helen R %A Waterworth, Dawn M %A Wessel, Jennifer %A White, Harvey D %A Willer, Cristen J %A Wilson, James G %A Witte, Daniel R %A Wood, Andrew R %A Wu, Ying %A Yaghootkar, Hanieh %A Yao, Jie %A Yao, Pang %A Yerges-Armstrong, Laura M %A Young, Robin %A Zeggini, Eleftheria %A Zhan, Xiaowei %A Zhang, Weihua %A Zhao, Jing Hua %A Zhao, Wei %A Zhao, Wei %A Zhou, Wei %A Zondervan, Krina T %A Rotter, Jerome I %A Pospisilik, John A %A Rivadeneira, Fernando %A Borecki, Ingrid B %A Deloukas, Panos %A Frayling, Timothy M %A Lettre, Guillaume %A North, Kari E %A Lindgren, Cecilia M %A Hirschhorn, Joel N %A Loos, Ruth J F %K Adult %K Animals %K Body Mass Index %K Drosophila %K Energy Intake %K Energy Metabolism %K Female %K Gene Frequency %K Genetic Variation %K Humans %K Male %K Obesity %K Proteins %K Syndrome %X

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.

%B Nat Genet %V 50 %P 26-41 %8 2018 Jan %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/29273807?dopt=Abstract %R 10.1038/s41588-017-0011-x %0 Journal Article %J Nat Genet %D 2018 %T Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. %A Turcot, Valérie %A Lu, Yingchang %A Highland, Heather M %A Schurmann, Claudia %A Justice, Anne E %A Fine, Rebecca S %A Bradfield, Jonathan P %A Esko, Tõnu %A Giri, Ayush %A Graff, Mariaelisa %A Guo, Xiuqing %A Hendricks, Audrey E %A Karaderi, Tugce %A Lempradl, Adelheid %A Locke, Adam E %A Mahajan, Anubha %A Marouli, Eirini %A Sivapalaratnam, Suthesh %A Young, Kristin L %A Alfred, Tamuno %A Feitosa, Mary F %A Masca, Nicholas G D %A Manning, Alisa K %A Medina-Gomez, Carolina %A Mudgal, Poorva %A Ng, Maggie C Y %A Reiner, Alex P %A Vedantam, Sailaja %A Willems, Sara M %A Winkler, Thomas W %A Abecasis, Goncalo %A Aben, Katja K %A Alam, Dewan S %A Alharthi, Sameer E %A Allison, Matthew %A Amouyel, Philippe %A Asselbergs, Folkert W %A Auer, Paul L %A Balkau, Beverley %A Bang, Lia E %A Barroso, Inês %A Bastarache, Lisa %A Benn, Marianne %A Bergmann, Sven %A Bielak, Lawrence F %A Blüher, Matthias %A Boehnke, Michael %A Boeing, Heiner %A Eric Boerwinkle %A Böger, Carsten A %A Bork-Jensen, Jette %A Bots, Michiel L %A Bottinger, Erwin P %A Bowden, Donald W %A Brandslund, Ivan %A Breen, Gerome %A Brilliant, Murray H %A Broer, Linda %A Brumat, Marco %A Burt, Amber A %A Butterworth, Adam S %A Campbell, Peter T %A Cappellani, Stefania %A Carey, David J %A Catamo, Eulalia %A Caulfield, Mark J %A Chambers, John C %A Chasman, Daniel I %A Chen, Yii-Der I %A Chowdhury, Rajiv %A Christensen, Cramer %A Chu, Audrey Y %A Cocca, Massimiliano %A Collins, Francis S %A Cook, James P %A Corley, Janie %A Corominas Galbany, Jordi %A Cox, Amanda J %A Crosslin, David S %A Cuellar-Partida, Gabriel %A D'Eustacchio, Angela %A Danesh, John %A Davies, Gail %A Bakker, Paul I W %A Groot, Mark C H %A Mutsert, Renée %A Deary, Ian J %A Dedoussis, George %A Demerath, Ellen W %A Heijer, Martin %A Hollander, Anneke I %A Ruijter, Hester M %A Dennis, Joe G %A Denny, Josh C %A Angelantonio, Emanuele %A Drenos, Fotios %A Du, Mengmeng %A Dube, Marie-Pierre %A Dunning, Alison M %A Easton, Douglas F %A Edwards, Todd L %A Ellinghaus, David %A Ellinor, Patrick T %A Elliott, Paul %A Evangelou, Evangelos %A Farmaki, Aliki-Eleni %A Farooqi, I Sadaf %A Faul, Jessica D %A Fauser, Sascha %A Feng, Shuang %A Ferrannini, Ele %A Ferrieres, Jean %A Florez, Jose C %A Ford, Ian %A Fornage, Myriam %A Franco, Oscar H %A Franke, Andre %A Franks, Paul W %A Friedrich, Nele %A Frikke-Schmidt, Ruth %A Galesloot, Tessel E %A Gan, Wei %A Gandin, Ilaria %A Gasparini, Paolo %A Gibson, Jane %A Giedraitis, Vilmantas %A Gjesing, Anette P %A Gordon-Larsen, Penny %A Gorski, Mathias %A Grabe, Hans-Jörgen %A Grant, Struan F A %A Grarup, Niels %A Griffiths, Helen L %A Grove, Megan L %A Gudnason, Vilmundur %A Gustafsson, Stefan %A Haessler, Jeff %A Hakonarson, Hakon %A Hammerschlag, Anke R %A Hansen, Torben %A Harris, Kathleen Mullan %A Harris, Tamara B %A Hattersley, Andrew T %A Have, Christian T %A Hayward, Caroline %A He, Liang %A Heard-Costa, Nancy L %A Heath, Andrew C %A Heid, Iris M %A Helgeland, Øyvind %A Hernesniemi, Jussi %A Hewitt, Alex W %A Holmen, Oddgeir L %A Hovingh, G Kees %A Howson, Joanna M M %A Hu, Yao %A Huang, Paul L %A Huffman, Jennifer E %A Ikram, M Arfan %A Ingelsson, Erik %A Jackson, Anne U %A Jansson, Jan-Håkan %A Jarvik, Gail P %A Jensen, Gorm B %A Jia, Yucheng %A Johansson, Stefan %A Jørgensen, Marit E %A Jørgensen, Torben %A Jukema, J Wouter %A Kahali, Bratati %A Kahn, René S %A Kähönen, Mika %A Kamstrup, Pia R %A Kanoni, Stavroula %A Kaprio, Jaakko %A Karaleftheri, Maria %A Kardia, Sharon L R %A Karpe, Fredrik %A Kathiresan, Sekar %A Kee, Frank %A Kiemeney, Lambertus A %A Kim, Eric %A Kitajima, Hidetoshi %A Komulainen, Pirjo %A Kooner, Jaspal S %A Kooperberg, Charles %A Korhonen, Tellervo %A Kovacs, Peter %A Kuivaniemi, Helena %A Kutalik, Zoltán %A Kuulasmaa, Kari %A Kuusisto, Johanna %A Laakso, Markku %A Lakka, Timo A %A Lamparter, David %A Lange, Ethan M %A Lange, Leslie A %A Langenberg, Claudia %A Larson, Eric B %A Lee, Nanette R %A Lehtimäki, Terho %A Lewis, Cora E %A Li, Huaixing %A Li, Jin %A Li-Gao, Ruifang %A Lin, Honghuang %A Lin, Keng-Hung %A Lin, Li-An %A Lin, Xu %A Lind, Lars %A Lindström, Jaana %A Linneberg, Allan %A Liu, Ching-Ti %A Liu, Dajiang J %A Liu, Yongmei %A Lo, Ken S %A Lophatananon, Artitaya %A Lotery, Andrew J %A Loukola, Anu %A Luan, Jian'an %A Lubitz, Steven A %A Lyytikäinen, Leo-Pekka %A Männistö, Satu %A Marenne, Gaëlle %A Mazul, Angela L %A McCarthy, Mark I %A McKean-Cowdin, Roberta %A Medland, Sarah E %A Meidtner, Karina %A Milani, Lili %A Mistry, Vanisha %A Mitchell, Paul %A Mohlke, Karen L %A Moilanen, Leena %A Moitry, Marie %A Montgomery, Grant W %A Mook-Kanamori, Dennis O %A Moore, Carmel %A Mori, Trevor A %A Morris, Andrew D %A Morris, Andrew P %A Müller-Nurasyid, Martina %A Munroe, Patricia B %A Nalls, Mike A %A Narisu, Narisu %A Nelson, Christopher P %A Neville, Matt %A Nielsen, Sune F %A Nikus, Kjell %A Njølstad, Pål R %A Nordestgaard, Børge G %A Nyholt, Dale R %A O'Connel, Jeffrey R %A O'Donoghue, Michelle L %A Olde Loohuis, Loes M %A Ophoff, Roel A %A Owen, Katharine R %A Packard, Chris J %A Padmanabhan, Sandosh %A Palmer, Colin N A %A Palmer, Nicholette D %A Pasterkamp, Gerard %A Patel, Aniruddh P %A Pattie, Alison %A Pedersen, Oluf %A Peissig, Peggy L %A Peloso, Gina M %A Pennell, Craig E %A Perola, Markus %A Perry, James A %A Perry, John R B %A Pers, Tune H %A Person, Thomas N %A Peters, Annette %A Petersen, Eva R B %A Peyser, Patricia A %A Pirie, Ailith %A Polasek, Ozren %A Polderman, Tinca J %A Puolijoki, Hannu %A Raitakari, Olli T %A Rasheed, Asif %A Rauramaa, Rainer %A Reilly, Dermot F %A Renstrom, Frida %A Rheinberger, Myriam %A Ridker, Paul M %A Rioux, John D %A Rivas, Manuel A %A Roberts, David J %A Robertson, Neil R %A Robino, Antonietta %A Rolandsson, Olov %A Rudan, Igor %A Ruth, Katherine S %A Saleheen, Danish %A Salomaa, Veikko %A Samani, Nilesh J %A Sapkota, Yadav %A Sattar, Naveed %A Schoen, Robert E %A Schreiner, Pamela J %A Schulze, Matthias B %A Scott, Robert A %A Segura-Lepe, Marcelo P %A Shah, Svati H %A Sheu, Wayne H-H %A Sim, Xueling %A Slater, Andrew J %A Small, Kerrin S %A Smith, Albert V %A Southam, Lorraine %A Spector, Timothy D %A Speliotes, Elizabeth K %A Starr, John M %A Stefansson, Kari %A Steinthorsdottir, Valgerdur %A Stirrups, Kathleen E %A Strauch, Konstantin %A Stringham, Heather M %A Stumvoll, Michael %A Sun, Liang %A Surendran, Praveen %A Swift, Amy J %A Tada, Hayato %A Tansey, Katherine E %A Tardif, Jean-Claude %A Taylor, Kent D %A Teumer, Alexander %A Thompson, Deborah J %A Thorleifsson, Gudmar %A Thorsteinsdottir, Unnur %A Thuesen, Betina H %A Tonjes, Anke %A Tromp, Gerard %A Trompet, Stella %A Tsafantakis, Emmanouil %A Tuomilehto, Jaakko %A Tybjaerg-Hansen, Anne %A Tyrer, Jonathan P %A Uher, Rudolf %A Uitterlinden, André G %A Uusitupa, Matti %A Laan, Sander W %A Duijn, Cornelia M %A Leeuwen, Nienke %A van Setten, Jessica %A Vanhala, Mauno %A Varbo, Anette %A Varga, Tibor V %A Varma, Rohit %A Velez Edwards, Digna R %A Vermeulen, Sita H %A Veronesi, Giovanni %A Vestergaard, Henrik %A Vitart, Veronique %A Vogt, Thomas F %A Völker, Uwe %A Vuckovic, Dragana %A Wagenknecht, Lynne E %A Walker, Mark %A Wallentin, Lars %A Wang, Feijie %A Wang, Carol A %A Wang, Shuai %A Wang, Yiqin %A Ware, Erin B %A Wareham, Nicholas J %A Warren, Helen R %A Waterworth, Dawn M %A Wessel, Jennifer %A White, Harvey D %A Willer, Cristen J %A Wilson, James G %A Witte, Daniel R %A Wood, Andrew R %A Wu, Ying %A Yaghootkar, Hanieh %A Yao, Jie %A Yao, Pang %A Yerges-Armstrong, Laura M %A Young, Robin %A Zeggini, Eleftheria %A Zhan, Xiaowei %A Zhang, Weihua %A Zhao, Jing Hua %A Zhao, Wei %A Zhou, Wei %A Zondervan, Krina T %A Rotter, Jerome I %A Pospisilik, John A %A Rivadeneira, Fernando %A Borecki, Ingrid B %A Deloukas, Panos %A Frayling, Timothy M %A Lettre, Guillaume %A North, Kari E %A Lindgren, Cecilia M %A Hirschhorn, Joel N %A Loos, Ruth J F %X

In the published version of this paper, the name of author Emanuele Di Angelantonio was misspelled. This error has now been corrected in the HTML and PDF versions of the article.

%B Nat Genet %V 50 %P 765-766 %8 2018 May %G eng %N 5 %1 https://www.ncbi.nlm.nih.gov/pubmed/29549329?dopt=Abstract %R 10.1038/s41588-018-0050-y %0 Journal Article %J Nat Genet %D 2018 %T Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. %A Turcot, Valérie %A Lu, Yingchang %A Highland, Heather M %A Schurmann, Claudia %A Justice, Anne E %A Fine, Rebecca S %A Bradfield, Jonathan P %A Esko, Tõnu %A Giri, Ayush %A Graff, Mariaelisa %A Guo, Xiuqing %A Hendricks, Audrey E %A Karaderi, Tugce %A Lempradl, Adelheid %A Locke, Adam E %A Mahajan, Anubha %A Marouli, Eirini %A Sivapalaratnam, Suthesh %A Young, Kristin L %A Alfred, Tamuno %A Feitosa, Mary F %A Masca, Nicholas G D %A Manning, Alisa K %A Medina-Gomez, Carolina %A Mudgal, Poorva %A Ng, Maggie C Y %A Reiner, Alex P %A Vedantam, Sailaja %A Willems, Sara M %A Winkler, Thomas W %A Abecasis, Goncalo %A Aben, Katja K %A Alam, Dewan S %A Alharthi, Sameer E %A Allison, Matthew %A Amouyel, Philippe %A Asselbergs, Folkert W %A Auer, Paul L %A Balkau, Beverley %A Bang, Lia E %A Barroso, Inês %A Bastarache, Lisa %A Benn, Marianne %A Bergmann, Sven %A Bielak, Lawrence F %A Blüher, Matthias %A Boehnke, Michael %A Boeing, Heiner %A Eric Boerwinkle %A Böger, Carsten A %A Bork-Jensen, Jette %A Bots, Michiel L %A Bottinger, Erwin P %A Bowden, Donald W %A Brandslund, Ivan %A Breen, Gerome %A Brilliant, Murray H %A Broer, Linda %A Brumat, Marco %A Burt, Amber A %A Butterworth, Adam S %A Campbell, Peter T %A Cappellani, Stefania %A Carey, David J %A Catamo, Eulalia %A Caulfield, Mark J %A Chambers, John C %A Chasman, Daniel I %A Chen, Yii-Der I %A Chowdhury, Rajiv %A Christensen, Cramer %A Chu, Audrey Y %A Cocca, Massimiliano %A Collins, Francis S %A Cook, James P %A Corley, Janie %A Corominas Galbany, Jordi %A Cox, Amanda J %A Crosslin, David S %A Cuellar-Partida, Gabriel %A D'Eustacchio, Angela %A Danesh, John %A Davies, Gail %A Bakker, Paul I W %A Groot, Mark C H %A Mutsert, Renée %A Deary, Ian J %A Dedoussis, George %A Demerath, Ellen W %A Heijer, Martin %A Hollander, Anneke I %A Ruijter, Hester M %A Dennis, Joe G %A Denny, Josh C %A Di Angelantonio, Emanuele %A Drenos, Fotios %A Du, Mengmeng %A Dube, Marie-Pierre %A Dunning, Alison M %A Easton, Douglas F %A Edwards, Todd L %A Ellinghaus, David %A Ellinor, Patrick T %A Elliott, Paul %A Evangelou, Evangelos %A Farmaki, Aliki-Eleni %A Farooqi, I Sadaf %A Faul, Jessica D %A Fauser, Sascha %A Feng, Shuang %A Ferrannini, Ele %A Ferrieres, Jean %A Florez, Jose C %A Ford, Ian %A Fornage, Myriam %A Franco, Oscar H %A Franke, Andre %A Franks, Paul W %A Friedrich, Nele %A Frikke-Schmidt, Ruth %A Galesloot, Tessel E %A Gan, Wei %A Gandin, Ilaria %A Gasparini, Paolo %A Gibson, Jane %A Giedraitis, Vilmantas %A Gjesing, Anette P %A Gordon-Larsen, Penny %A Gorski, Mathias %A Grabe, Hans-Jörgen %A Grant, Struan F A %A Grarup, Niels %A Griffiths, Helen L %A Grove, Megan L %A Gudnason, Vilmundur %A Gustafsson, Stefan %A Haessler, Jeff %A Hakonarson, Hakon %A Hammerschlag, Anke R %A Hansen, Torben %A Harris, Kathleen Mullan %A Harris, Tamara B %A Hattersley, Andrew T %A Have, Christian T %A Hayward, Caroline %A He, Liang %A Heard-Costa, Nancy L %A Heath, Andrew C %A Heid, Iris M %A Helgeland, Øyvind %A Hernesniemi, Jussi %A Hewitt, Alex W %A Holmen, Oddgeir L %A Hovingh, G Kees %A Howson, Joanna M M %A Hu, Yao %A Huang, Paul L %A Huffman, Jennifer E %A Ikram, M Arfan %A Ingelsson, Erik %A Jackson, Anne U %A Jansson, Jan-Håkan %A Jarvik, Gail P %A Jensen, Gorm B %A Jia, Yucheng %A Johansson, Stefan %A Jørgensen, Marit E %A Jørgensen, Torben %A Jukema, J Wouter %A Kahali, Bratati %A Kahn, René S %A Kähönen, Mika %A Kamstrup, Pia R %A Kanoni, Stavroula %A Kaprio, Jaakko %A Karaleftheri, Maria %A Kardia, Sharon L R %A Karpe, Fredrik %A Kathiresan, Sekar %A Kee, Frank %A Kiemeney, Lambertus A %A Kim, Eric %A Kitajima, Hidetoshi %A Komulainen, Pirjo %A Kooner, Jaspal S %A Kooperberg, Charles %A Korhonen, Tellervo %A Kovacs, Peter %A Kuivaniemi, Helena %A Kutalik, Zoltán %A Kuulasmaa, Kari %A Kuusisto, Johanna %A Laakso, Markku %A Lakka, Timo A %A Lamparter, David %A Lange, Ethan M %A Lange, Leslie A %A Langenberg, Claudia %A Larson, Eric B %A Lee, Nanette R %A Lehtimäki, Terho %A Lewis, Cora E %A Li, Huaixing %A Li, Jin %A Li-Gao, Ruifang %A Lin, Honghuang %A Lin, Keng-Hung %A Lin, Li-An %A Lin, Xu %A Lind, Lars %A Lindström, Jaana %A Linneberg, Allan %A Liu, Ching-Ti %A Liu, Dajiang J %A Liu, Yongmei %A Lo, Ken S %A Lophatananon, Artitaya %A Lotery, Andrew J %A Loukola, Anu %A Luan, Jian'an %A Lubitz, Steven A %A Lyytikäinen, Leo-Pekka %A Männistö, Satu %A Marenne, Gaëlle %A Mazul, Angela L %A McCarthy, Mark I %A McKean-Cowdin, Roberta %A Medland, Sarah E %A Meidtner, Karina %A Milani, Lili %A Mistry, Vanisha %A Mitchell, Paul %A Mohlke, Karen L %A Moilanen, Leena %A Moitry, Marie %A Montgomery, Grant W %A Mook-Kanamori, Dennis O %A Moore, Carmel %A Mori, Trevor A %A Morris, Andrew D %A Morris, Andrew P %A Müller-Nurasyid, Martina %A Munroe, Patricia B %A Nalls, Mike A %A Narisu, Narisu %A Nelson, Christopher P %A Neville, Matt %A Nielsen, Sune F %A Nikus, Kjell %A Njølstad, Pål R %A Nordestgaard, Børge G %A Nyholt, Dale R %A O'Connel, Jeffrey R %A O'Donoghue, Michelle L %A Olde Loohuis, Loes M %A Ophoff, Roel A %A Owen, Katharine R %A Packard, Chris J %A Padmanabhan, Sandosh %A Palmer, Colin N A %A Palmer, Nicholette D %A Pasterkamp, Gerard %A Patel, Aniruddh P %A Pattie, Alison %A Pedersen, Oluf %A Peissig, Peggy L %A Peloso, Gina M %A Pennell, Craig E %A Perola, Markus %A Perry, James A %A Perry, John R B %A Pers, Tune H %A Person, Thomas N %A Peters, Annette %A Petersen, Eva R B %A Peyser, Patricia A %A Pirie, Ailith %A Polasek, Ozren %A Polderman, Tinca J %A Puolijoki, Hannu %A Raitakari, Olli T %A Rasheed, Asif %A Rauramaa, Rainer %A Reilly, Dermot F %A Renstrom, Frida %A Rheinberger, Myriam %A Ridker, Paul M %A Rioux, John D %A Rivas, Manuel A %A Roberts, David J %A Robertson, Neil R %A Robino, Antonietta %A Rolandsson, Olov %A Rudan, Igor %A Ruth, Katherine S %A Saleheen, Danish %A Salomaa, Veikko %A Samani, Nilesh J %A Sapkota, Yadav %A Sattar, Naveed %A Schoen, Robert E %A Schreiner, Pamela J %A Schulze, Matthias B %A Scott, Robert A %A Segura-Lepe, Marcelo P %A Shah, Svati H %A Sheu, Wayne H-H %A Sim, Xueling %A Slater, Andrew J %A Small, Kerrin S %A Smith, Albert V %A Southam, Lorraine %A Spector, Timothy D %A Speliotes, Elizabeth K %A Starr, John M %A Stefansson, Kari %A Steinthorsdottir, Valgerdur %A Stirrups, Kathleen E %A Strauch, Konstantin %A Stringham, Heather M %A Stumvoll, Michael %A Sun, Liang %A Surendran, Praveen %A Swift, Amy J %A Tada, Hayato %A Tansey, Katherine E %A Tardif, Jean-Claude %A Taylor, Kent D %A Teumer, Alexander %A Thompson, Deborah J %A Thorleifsson, Gudmar %A Thorsteinsdottir, Unnur %A Thuesen, Betina H %A Tonjes, Anke %A Tromp, Gerard %A Trompet, Stella %A Tsafantakis, Emmanouil %A Tuomilehto, Jaakko %A Tybjaerg-Hansen, Anne %A Tyrer, Jonathan P %A Uher, Rudolf %A Uitterlinden, André G %A Uusitupa, Matti %A Laan, Sander W %A Duijn, Cornelia M %A Leeuwen, Nienke %A van Setten, Jessica %A Vanhala, Mauno %A Varbo, Anette %A Varga, Tibor V %A Varma, Rohit %A Velez Edwards, Digna R %A Vermeulen, Sita H %A Veronesi, Giovanni %A Vestergaard, Henrik %A Vitart, Veronique %A Vogt, Thomas F %A Völker, Uwe %A Vuckovic, Dragana %A Wagenknecht, Lynne E %A Walker, Mark %A Wallentin, Lars %A Wang, Feijie %A Wang, Carol A %A Wang, Shuai %A Wang, Yiqin %A Ware, Erin B %A Wareham, Nicholas J %A Warren, Helen R %A Waterworth, Dawn M %A Wessel, Jennifer %A White, Harvey D %A Willer, Cristen J %A Wilson, James G %A Witte, Daniel R %A Wood, Andrew R %A Wu, Ying %A Yaghootkar, Hanieh %A Yao, Jie %A Yao, Pang %A Yerges-Armstrong, Laura M %A Young, Robin %A Zeggini, Eleftheria %A Zhan, Xiaowei %A Zhang, Weihua %A Zhao, Jing Hua %A Zhao, Wei %A Zhao, Wei %A Zhou, Wei %A Zondervan, Krina T %A Rotter, Jerome I %A Pospisilik, John A %A Rivadeneira, Fernando %A Borecki, Ingrid B %A Deloukas, Panos %A Frayling, Timothy M %A Lettre, Guillaume %A North, Kari E %A Lindgren, Cecilia M %A Hirschhorn, Joel N %A Loos, Ruth J F %X

In the version of this article originally published, one of the two authors with the name Wei Zhao was omitted from the author list and the affiliations for both authors were assigned to the single Wei Zhao in the author list. In addition, the ORCID for Wei Zhao (Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA) was incorrectly assigned to author Wei Zhou. The errors have been corrected in the HTML and PDF versions of the article.

%B Nat Genet %V 50 %P 766-767 %8 2018 May %G eng %N 5 %1 https://www.ncbi.nlm.nih.gov/pubmed/29549330?dopt=Abstract %R 10.1038/s41588-018-0082-3 %0 Journal Article %J Nat Genet %D 2017 %T Exome-wide association study of plasma lipids in >300,000 individuals. %A Liu, Dajiang J %A Peloso, Gina M %A Yu, Haojie %A Butterworth, Adam S %A Wang, Xiao %A Mahajan, Anubha %A Saleheen, Danish %A Emdin, Connor %A Alam, Dewan %A Alves, Alexessander Couto %A Amouyel, Philippe %A Di Angelantonio, Emanuele %A Arveiler, Dominique %A Assimes, Themistocles L %A Auer, Paul L %A Baber, Usman %A Ballantyne, Christie M %A Bang, Lia E %A Benn, Marianne %A Bis, Joshua C %A Boehnke, Michael %A Eric Boerwinkle %A Bork-Jensen, Jette %A Bottinger, Erwin P %A Brandslund, Ivan %A Brown, Morris %A Busonero, Fabio %A Caulfield, Mark J %A Chambers, John C %A Chasman, Daniel I %A Chen, Y Eugene %A Chen, Yii-Der Ida %A Chowdhury, Rajiv %A Christensen, Cramer %A Chu, Audrey Y %A Connell, John M %A Cucca, Francesco %A Cupples, L Adrienne %A Damrauer, Scott M %A Davies, Gail %A Deary, Ian J %A Dedoussis, George %A Denny, Joshua C %A Dominiczak, Anna %A Dube, Marie-Pierre %A Ebeling, Tapani %A Eiriksdottir, Gudny %A Esko, Tõnu %A Farmaki, Aliki-Eleni %A Feitosa, Mary F %A Ferrario, Marco %A Ferrieres, Jean %A Ford, Ian %A Fornage, Myriam %A Franks, Paul W %A Frayling, Timothy M %A Frikke-Schmidt, Ruth %A Fritsche, Lars G %A Frossard, Philippe %A Fuster, Valentin %A Ganesh, Santhi K %A Gao, Wei %A Garcia, Melissa E %A Gieger, Christian %A Giulianini, Franco %A Goodarzi, Mark O %A Grallert, Harald %A Grarup, Niels %A Groop, Leif %A Grove, Megan L %A Gudnason, Vilmundur %A Hansen, Torben %A Harris, Tamara B %A Hayward, Caroline %A Hirschhorn, Joel N %A Holmen, Oddgeir L %A Huffman, Jennifer %A Huo, Yong %A Hveem, Kristian %A Jabeen, Sehrish %A Jackson, Anne U %A Jakobsdottir, Johanna %A Jarvelin, Marjo-Riitta %A Jensen, Gorm B %A Jørgensen, Marit E %A Jukema, J Wouter %A Justesen, Johanne M %A Kamstrup, Pia R %A Kanoni, Stavroula %A Karpe, Fredrik %A Kee, Frank %A Khera, Amit V %A Klarin, Derek %A Koistinen, Heikki A %A Kooner, Jaspal S %A Kooperberg, Charles %A Kuulasmaa, Kari %A Kuusisto, Johanna %A Laakso, Markku %A Lakka, Timo %A Langenberg, Claudia %A Langsted, Anne %A Launer, Lenore J %A Lauritzen, Torsten %A Liewald, David C M %A Lin, Li An %A Linneberg, Allan %A Loos, Ruth J F %A Lu, Yingchang %A Lu, Xiangfeng %A Mägi, Reedik %A Mälarstig, Anders %A Manichaikul, Ani %A Manning, Alisa K %A Mäntyselkä, Pekka %A Marouli, Eirini %A Masca, Nicholas G D %A Maschio, Andrea %A Meigs, James B %A Melander, Olle %A Metspalu, Andres %A Morris, Andrew P %A Morrison, Alanna C %A Mulas, Antonella %A Müller-Nurasyid, Martina %A Munroe, Patricia B %A Neville, Matt J %A Nielsen, Jonas B %A Nielsen, Sune F %A Nordestgaard, Børge G %A Ordovas, Jose M %A Mehran, Roxana %A O'Donnell, Christoper J %A Orho-Melander, Marju %A Molony, Cliona M %A Muntendam, Pieter %A Padmanabhan, Sandosh %A Palmer, Colin N A %A Pasko, Dorota %A Patel, Aniruddh P %A Pedersen, Oluf %A Perola, Markus %A Peters, Annette %A Pisinger, Charlotta %A Pistis, Giorgio %A Polasek, Ozren %A Poulter, Neil %A Psaty, Bruce M %A Rader, Daniel J %A Rasheed, Asif %A Rauramaa, Rainer %A Reilly, Dermot F %A Reiner, Alex P %A Renstrom, Frida %A Rich, Stephen S %A Ridker, Paul M %A Rioux, John D %A Robertson, Neil R %A Roden, Dan M %A Rotter, Jerome I %A Rudan, Igor %A Salomaa, Veikko %A Samani, Nilesh J %A Sanna, Serena %A Sattar, Naveed %A Schmidt, Ellen M %A Scott, Robert A %A Sever, Peter %A Sevilla, Raquel S %A Shaffer, Christian M %A Sim, Xueling %A Sivapalaratnam, Suthesh %A Small, Kerrin S %A Smith, Albert V %A Smith, Blair H %A Somayajula, Sangeetha %A Southam, Lorraine %A Spector, Timothy D %A Speliotes, Elizabeth K %A Starr, John M %A Stirrups, Kathleen E %A Stitziel, Nathan %A Strauch, Konstantin %A Stringham, Heather M %A Surendran, Praveen %A Tada, Hayato %A Tall, Alan R %A Tang, Hua %A Tardif, Jean-Claude %A Taylor, Kent D %A Trompet, Stella %A Tsao, Philip S %A Tuomilehto, Jaakko %A Tybjaerg-Hansen, Anne %A Van Zuydam, Natalie R %A Varbo, Anette %A Varga, Tibor V %A Virtamo, Jarmo %A Waldenberger, Melanie %A Wang, Nan %A Wareham, Nick J %A Warren, Helen R %A Weeke, Peter E %A Weinstock, Joshua %A Wessel, Jennifer %A Wilson, James G %A Wilson, Peter W F %A Xu, Ming %A Yaghootkar, Hanieh %A Young, Robin %A Zeggini, Eleftheria %A Zhang, He %A Zheng, Neil S %A Zhang, Weihua %A Zhang, Yan %A Zhou, Wei %A Zhou, Yanhua %A Zoledziewska, Magdalena %A Howson, Joanna M M %A Danesh, John %A McCarthy, Mark I %A Cowan, Chad A %A Abecasis, Goncalo %A Deloukas, Panos %A Musunuru, Kiran %A Willer, Cristen J %A Kathiresan, Sekar %K Coronary Artery Disease %K Diabetes Mellitus, Type 2 %K Exome %K Genetic Association Studies %K Genetic Predisposition to Disease %K Genetic Variation %K Genotype %K Humans %K Lipids %K Macular Degeneration %K Phenotype %K Risk Factors %X

We screened variants on an exome-focused genotyping array in >300,000 participants (replication in >280,000 participants) and identified 444 independent variants in 250 loci significantly associated with total cholesterol (TC), high-density-lipoprotein cholesterol (HDL-C), low-density-lipoprotein cholesterol (LDL-C), and/or triglycerides (TG). At two loci (JAK2 and A1CF), experimental analysis in mice showed lipid changes consistent with the human data. We also found that: (i) beta-thalassemia trait carriers displayed lower TC and were protected from coronary artery disease (CAD); (ii) excluding the CETP locus, there was not a predictable relationship between plasma HDL-C and risk for age-related macular degeneration; (iii) only some mechanisms of lowering LDL-C appeared to increase risk for type 2 diabetes (T2D); and (iv) TG-lowering alleles involved in hepatic production of TG-rich lipoproteins (TM6SF2 and PNPLA3) tracked with higher liver fat, higher risk for T2D, and lower risk for CAD, whereas TG-lowering alleles involved in peripheral lipolysis (LPL and ANGPTL4) had no effect on liver fat but decreased risks for both T2D and CAD.

%B Nat Genet %V 49 %P 1758-1766 %8 2017 Dec %G eng %N 12 %1 https://www.ncbi.nlm.nih.gov/pubmed/29083408?dopt=Abstract %R 10.1038/ng.3977 %0 Journal Article %J Nat Genet %D 2017 %T Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms. %A Howson, Joanna M M %A Zhao, Wei %A Barnes, Daniel R %A Ho, Weang-Kee %A Young, Robin %A Paul, Dirk S %A Waite, Lindsay L %A Freitag, Daniel F %A Fauman, Eric B %A Salfati, Elias L %A Sun, Benjamin B %A Eicher, John D %A Johnson, Andrew D %A Sheu, Wayne H H %A Nielsen, Sune F %A Lin, Wei-Yu %A Surendran, Praveen %A Mälarstig, Anders %A Wilk, Jemma B %A Tybjærg-Hansen, Anne %A Rasmussen, Katrine L %A Kamstrup, Pia R %A Deloukas, Panos %A Erdmann, Jeanette %A Kathiresan, Sekar %A Samani, Nilesh J %A Schunkert, Heribert %A Watkins, Hugh %A Do, Ron %A Rader, Daniel J %A Johnson, Julie A %A Hazen, Stanley L %A Quyyumi, Arshed A %A Spertus, John A %A Pepine, Carl J %A Franceschini, Nora %A Justice, Anne %A Reiner, Alex P %A Buyske, Steven %A Hindorff, Lucia A %A Carty, Cara L %A North, Kari E %A Kooperberg, Charles %A Eric Boerwinkle %A Young, Kristin %A Graff, Mariaelisa %A Peters, Ulrike %A Absher, Devin %A Hsiung, Chao A %A Lee, Wen-Jane %A Taylor, Kent D %A Chen, Ying-Hsiang %A Lee, I-Te %A Guo, Xiuqing %A Chung, Ren-Hua %A Hung, Yi-Jen %A Rotter, Jerome I %A Juang, Jyh-Ming J %A Quertermous, Thomas %A Wang, Tzung-Dau %A Rasheed, Asif %A Frossard, Philippe %A Alam, Dewan S %A Majumder, Abdulla Al Shafi %A Di Angelantonio, Emanuele %A Chowdhury, Rajiv %A Chen, Yii-Der Ida %A Nordestgaard, Børge G %A Assimes, Themistocles L %A Danesh, John %A Butterworth, Adam S %A Saleheen, Danish %K Arteries %K Atherosclerosis %K Cell Adhesion %K Chemotaxis, Leukocyte %K Coronary Artery Disease %K Energy Metabolism %K Female %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Genotype %K Histone Code %K Humans %K Male %K Muscle, Smooth, Vascular %K Polymorphism, Single Nucleotide %K Quantitative Trait Loci %K Risk Factors %X

Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P < 5 × 10, in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms.

%B Nat Genet %V 49 %P 1113-1119 %8 2017 Jul %G eng %N 7 %1 https://www.ncbi.nlm.nih.gov/pubmed/28530674?dopt=Abstract %R 10.1038/ng.3874 %0 Journal Article %J Nat Genet %D 2017 %T Large-scale analyses of common and rare variants identify 12 new loci associated with atrial fibrillation. %A Christophersen, Ingrid E %A Rienstra, Michiel %A Roselli, Carolina %A Yin, Xiaoyan %A Geelhoed, Bastiaan %A Barnard, John %A Lin, Honghuang %A Arking, Dan E %A Smith, Albert V %A Albert, Christine M %A Chaffin, Mark %A Tucker, Nathan R %A Li, Molong %A Klarin, Derek %A Bihlmeyer, Nathan A %A Low, Siew-Kee %A Weeke, Peter E %A Müller-Nurasyid, Martina %A Smith, J Gustav %A Brody, Jennifer A %A Niemeijer, Maartje N %A Dörr, Marcus %A Trompet, Stella %A Huffman, Jennifer %A Gustafsson, Stefan %A Schurmann, Claudia %A Kleber, Marcus E %A Lyytikäinen, Leo-Pekka %A Seppälä, Ilkka %A Malik, Rainer %A Horimoto, Andrea R V R %A Perez, Marco %A Sinisalo, Juha %A Aeschbacher, Stefanie %A Thériault, Sébastien %A Yao, Jie %A Radmanesh, Farid %A Weiss, Stefan %A Teumer, Alexander %A Choi, Seung Hoan %A Weng, Lu-Chen %A Clauss, Sebastian %A Deo, Rajat %A Rader, Daniel J %A Shah, Svati H %A Sun, Albert %A Hopewell, Jemma C %A Debette, Stephanie %A Chauhan, Ganesh %A Yang, Qiong %A Worrall, Bradford B %A Paré, Guillaume %A Kamatani, Yoichiro %A Hagemeijer, Yanick P %A Verweij, Niek %A Siland, Joylene E %A Kubo, Michiaki %A Smith, Jonathan D %A Van Wagoner, David R %A Bis, Joshua C %A Perz, Siegfried %A Psaty, Bruce M %A Ridker, Paul M %A Magnani, Jared W %A Harris, Tamara B %A Launer, Lenore J %A Shoemaker, M Benjamin %A Padmanabhan, Sandosh %A Haessler, Jeffrey %A Bartz, Traci M %A Waldenberger, Melanie %A Lichtner, Peter %A Arendt, Marina %A Krieger, Jose E %A Kähönen, Mika %A Risch, Lorenz %A Mansur, Alfredo J %A Peters, Annette %A Smith, Blair H %A Lind, Lars %A Scott, Stuart A %A Lu, Yingchang %A Bottinger, Erwin B %A Hernesniemi, Jussi %A Lindgren, Cecilia M %A Wong, Jorge A %A Huang, Jie %A Eskola, Markku %A Morris, Andrew P %A Ford, Ian %A Reiner, Alex P %A Delgado, Graciela %A Chen, Lin Y %A Chen, Yii-Der Ida %A Sandhu, Roopinder K %A Li, Man %A Eric Boerwinkle %A Eisele, Lewin %A Lannfelt, Lars %A Rost, Natalia %A Anderson, Christopher D %A Taylor, Kent D %A Campbell, Archie %A Magnusson, Patrik K %A Porteous, David %A Hocking, Lynne J %A Vlachopoulou, Efthymia %A Pedersen, Nancy L %A Nikus, Kjell %A Orho-Melander, Marju %A Hamsten, Anders %A Heeringa, Jan %A Denny, Joshua C %A Kriebel, Jennifer %A Darbar, Dawood %A Newton-Cheh, Christopher %A Shaffer, Christian %A Macfarlane, Peter W %A Heilmann-Heimbach, Stefanie %A Almgren, Peter %A Huang, Paul L %A Sotoodehnia, Nona %A Soliman, Elsayed Z %A Uitterlinden, André G %A Hofman, Albert %A Franco, Oscar H %A Völker, Uwe %A Jöckel, Karl-Heinz %A Sinner, Moritz F %A Lin, Henry J %A Guo, Xiuqing %A Dichgans, Martin %A Ingelsson, Erik %A Kooperberg, Charles %A Melander, Olle %A Loos, Ruth J F %A Laurikka, Jari %A Conen, David %A Rosand, Jonathan %A van der Harst, Pim %A Lokki, Marja-Liisa %A Kathiresan, Sekar %A Pereira, Alexandre %A Jukema, J Wouter %A Hayward, Caroline %A Rotter, Jerome I %A Marz, Winfried %A Lehtimäki, Terho %A Stricker, Bruno H %A Chung, Mina K %A Felix, Stephan B %A Gudnason, Vilmundur %A Alonso, Alvaro %A Roden, Dan M %A Kääb, Stefan %A Chasman, Daniel I %A Heckbert, Susan R %A Benjamin, Emelia J %A Tanaka, Toshihiro %A Lunetta, Kathryn L %A Lubitz, Steven A %A Ellinor, Patrick T %K Atrial Fibrillation %K Black or African American %K Genetic Loci %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Quantitative Trait Loci %K White People %X

Atrial fibrillation affects more than 33 million people worldwide and increases the risk of stroke, heart failure, and death. Fourteen genetic loci have been associated with atrial fibrillation in European and Asian ancestry groups. To further define the genetic basis of atrial fibrillation, we performed large-scale, trans-ancestry meta-analyses of common and rare variant association studies. The genome-wide association studies (GWAS) included 17,931 individuals with atrial fibrillation and 115,142 referents; the exome-wide association studies (ExWAS) and rare variant association studies (RVAS) involved 22,346 cases and 132,086 referents. We identified 12 new genetic loci that exceeded genome-wide significance, implicating genes involved in cardiac electrical and structural remodeling. Our results nearly double the number of known genetic loci for atrial fibrillation, provide insights into the molecular basis of atrial fibrillation, and may facilitate the identification of new potential targets for drug discovery.

%B Nat Genet %V 49 %P 946-952 %8 2017 Jun %G eng %N 6 %1 https://www.ncbi.nlm.nih.gov/pubmed/28416818?dopt=Abstract %R 10.1038/ng.3843 %0 Journal Article %J Nature %D 2017 %T Rare and low-frequency coding variants alter human adult height. %A Marouli, Eirini %A Graff, Mariaelisa %A Medina-Gomez, Carolina %A Lo, Ken Sin %A Wood, Andrew R %A Kjaer, Troels R %A Fine, Rebecca S %A Lu, Yingchang %A Schurmann, Claudia %A Highland, Heather M %A Rüeger, Sina %A Thorleifsson, Gudmar %A Justice, Anne E %A Lamparter, David %A Stirrups, Kathleen E %A Turcot, Valérie %A Young, Kristin L %A Winkler, Thomas W %A Esko, Tõnu %A Karaderi, Tugce %A Locke, Adam E %A Masca, Nicholas G D %A Ng, Maggie C Y %A Mudgal, Poorva %A Rivas, Manuel A %A Vedantam, Sailaja %A Mahajan, Anubha %A Guo, Xiuqing %A Abecasis, Goncalo %A Aben, Katja K %A Adair, Linda S %A Alam, Dewan S %A Albrecht, Eva %A Allin, Kristine H %A Allison, Matthew %A Amouyel, Philippe %A Appel, Emil V %A Arveiler, Dominique %A Asselbergs, Folkert W %A Auer, Paul L %A Balkau, Beverley %A Banas, Bernhard %A Bang, Lia E %A Benn, Marianne %A Bergmann, Sven %A Bielak, Lawrence F %A Blüher, Matthias %A Boeing, Heiner %A Eric Boerwinkle %A Böger, Carsten A %A Bonnycastle, Lori L %A Bork-Jensen, Jette %A Bots, Michiel L %A Bottinger, Erwin P %A Bowden, Donald W %A Brandslund, Ivan %A Breen, Gerome %A Brilliant, Murray H %A Broer, Linda %A Burt, Amber A %A Butterworth, Adam S %A Carey, David J %A Caulfield, Mark J %A Chambers, John C %A Chasman, Daniel I %A Chen, Yii-Der Ida %A Chowdhury, Rajiv %A Christensen, Cramer %A Chu, Audrey Y %A Cocca, Massimiliano %A Collins, Francis S %A Cook, James P %A Corley, Janie %A Galbany, Jordi Corominas %A Cox, Amanda J %A Cuellar-Partida, Gabriel %A Danesh, John %A Davies, Gail %A de Bakker, Paul I W %A de Borst, Gert J %A de Denus, Simon %A de Groot, Mark C H %A de Mutsert, Renée %A Deary, Ian J %A Dedoussis, George %A Demerath, Ellen W %A den Hollander, Anneke I %A Dennis, Joe G %A Di Angelantonio, Emanuele %A Drenos, Fotios %A Du, Mengmeng %A Dunning, Alison M %A Easton, Douglas F %A Ebeling, Tapani %A Edwards, Todd L %A Ellinor, Patrick T %A Elliott, Paul %A Evangelou, Evangelos %A Farmaki, Aliki-Eleni %A Faul, Jessica D %A Feitosa, Mary F %A Feng, Shuang %A Ferrannini, Ele %A Ferrario, Marco M %A Ferrieres, Jean %A Florez, Jose C %A Ford, Ian %A Fornage, Myriam %A Franks, Paul W %A Frikke-Schmidt, Ruth %A Galesloot, Tessel E %A Gan, Wei %A Gandin, Ilaria %A Gasparini, Paolo %A Giedraitis, Vilmantas %A Giri, Ayush %A Girotto, Giorgia %A Gordon, Scott D %A Gordon-Larsen, Penny %A Gorski, Mathias %A Grarup, Niels %A Grove, Megan L %A Gudnason, Vilmundur %A Gustafsson, Stefan %A Hansen, Torben %A Harris, Kathleen Mullan %A Harris, Tamara B %A Hattersley, Andrew T %A Hayward, Caroline %A He, Liang %A Heid, Iris M %A Heikkilä, Kauko %A Helgeland, Øyvind %A Hernesniemi, Jussi %A Hewitt, Alex W %A Hocking, Lynne J %A Hollensted, Mette %A Holmen, Oddgeir L %A Hovingh, G Kees %A Howson, Joanna M M %A Hoyng, Carel B %A Huang, Paul L %A Hveem, Kristian %A Ikram, M Arfan %A Ingelsson, Erik %A Jackson, Anne U %A Jansson, Jan-Håkan %A Jarvik, Gail P %A Jensen, Gorm B %A Jhun, Min A %A Jia, Yucheng %A Jiang, Xuejuan %A Johansson, Stefan %A Jørgensen, Marit E %A Jørgensen, Torben %A Jousilahti, Pekka %A Jukema, J Wouter %A Kahali, Bratati %A Kahn, René S %A Kähönen, Mika %A Kamstrup, Pia R %A Kanoni, Stavroula %A Kaprio, Jaakko %A Karaleftheri, Maria %A Kardia, Sharon L R %A Karpe, Fredrik %A Kee, Frank %A Keeman, Renske %A Kiemeney, Lambertus A %A Kitajima, Hidetoshi %A Kluivers, Kirsten B %A Kocher, Thomas %A Komulainen, Pirjo %A Kontto, Jukka %A Kooner, Jaspal S %A Kooperberg, Charles %A Kovacs, Peter %A Kriebel, Jennifer %A Kuivaniemi, Helena %A Küry, Sébastien %A Kuusisto, Johanna %A La Bianca, Martina %A Laakso, Markku %A Lakka, Timo A %A Lange, Ethan M %A Lange, Leslie A %A Langefeld, Carl D %A Langenberg, Claudia %A Larson, Eric B %A Lee, I-Te %A Lehtimäki, Terho %A Lewis, Cora E %A Li, Huaixing %A Li, Jin %A Li-Gao, Ruifang %A Lin, Honghuang %A Lin, Li-An %A Lin, Xu %A Lind, Lars %A Lindström, Jaana %A Linneberg, Allan %A Liu, Yeheng %A Liu, Yongmei %A Lophatananon, Artitaya %A Luan, Jian'an %A Lubitz, Steven A %A Lyytikäinen, Leo-Pekka %A Mackey, David A %A Madden, Pamela A F %A Manning, Alisa K %A Männistö, Satu %A Marenne, Gaëlle %A Marten, Jonathan %A Martin, Nicholas G %A Mazul, Angela L %A Meidtner, Karina %A Metspalu, Andres %A Mitchell, Paul %A Mohlke, Karen L %A Mook-Kanamori, Dennis O %A Morgan, Anna %A Morris, Andrew D %A Morris, Andrew P %A Müller-Nurasyid, Martina %A Munroe, Patricia B %A Nalls, Mike A %A Nauck, Matthias %A Nelson, Christopher P %A Neville, Matt %A Nielsen, Sune F %A Nikus, Kjell %A Njølstad, Pål R %A Nordestgaard, Børge G %A Ntalla, Ioanna %A O'Connel, Jeffrey R %A Oksa, Heikki %A Loohuis, Loes M Olde %A Ophoff, Roel A %A Owen, Katharine R %A Packard, Chris J %A Padmanabhan, Sandosh %A Palmer, Colin N A %A Pasterkamp, Gerard %A Patel, Aniruddh P %A Pattie, Alison %A Pedersen, Oluf %A Peissig, Peggy L %A Peloso, Gina M %A Pennell, Craig E %A Perola, Markus %A Perry, James A %A Perry, John R B %A Person, Thomas N %A Pirie, Ailith %A Polasek, Ozren %A Posthuma, Danielle %A Raitakari, Olli T %A Rasheed, Asif %A Rauramaa, Rainer %A Reilly, Dermot F %A Reiner, Alex P %A Renstrom, Frida %A Ridker, Paul M %A Rioux, John D %A Robertson, Neil %A Robino, Antonietta %A Rolandsson, Olov %A Rudan, Igor %A Ruth, Katherine S %A Saleheen, Danish %A Salomaa, Veikko %A Samani, Nilesh J %A Sandow, Kevin %A Sapkota, Yadav %A Sattar, Naveed %A Schmidt, Marjanka K %A Schreiner, Pamela J %A Schulze, Matthias B %A Scott, Robert A %A Segura-Lepe, Marcelo P %A Shah, Svati %A Sim, Xueling %A Sivapalaratnam, Suthesh %A Small, Kerrin S %A Smith, Albert Vernon %A Smith, Jennifer A %A Southam, Lorraine %A Spector, Timothy D %A Speliotes, Elizabeth K %A Starr, John M %A Steinthorsdottir, Valgerdur %A Stringham, Heather M %A Stumvoll, Michael %A Surendran, Praveen %A 't Hart, Leen M %A Tansey, Katherine E %A Tardif, Jean-Claude %A Taylor, Kent D %A Teumer, Alexander %A Thompson, Deborah J %A Thorsteinsdottir, Unnur %A Thuesen, Betina H %A Tonjes, Anke %A Tromp, Gerard %A Trompet, Stella %A Tsafantakis, Emmanouil %A Tuomilehto, Jaakko %A Tybjaerg-Hansen, Anne %A Tyrer, Jonathan P %A Uher, Rudolf %A Uitterlinden, André G %A Ulivi, Sheila %A van der Laan, Sander W %A Van Der Leij, Andries R %A van Duijn, Cornelia M %A van Schoor, Natasja M %A van Setten, Jessica %A Varbo, Anette %A Varga, Tibor V %A Varma, Rohit %A Edwards, Digna R Velez %A Vermeulen, Sita H %A Vestergaard, Henrik %A Vitart, Veronique %A Vogt, Thomas F %A Vozzi, Diego %A Walker, Mark %A Wang, Feijie %A Wang, Carol A %A Wang, Shuai %A Wang, Yiqin %A Wareham, Nicholas J %A Warren, Helen R %A Wessel, Jennifer %A Willems, Sara M %A Wilson, James G %A Witte, Daniel R %A Woods, Michael O %A Wu, Ying %A Yaghootkar, Hanieh %A Yao, Jie %A Yao, Pang %A Yerges-Armstrong, Laura M %A Young, Robin %A Zeggini, Eleftheria %A Zhan, Xiaowei %A Zhang, Weihua %A Zhao, Jing Hua %A Zhao, Wei %A Zhao, Wei %A Zheng, He %A Zhou, Wei %A Rotter, Jerome I %A Boehnke, Michael %A Kathiresan, Sekar %A McCarthy, Mark I %A Willer, Cristen J %A Stefansson, Kari %A Borecki, Ingrid B %A Liu, Dajiang J %A North, Kari E %A Heard-Costa, Nancy L %A Pers, Tune H %A Lindgren, Cecilia M %A Oxvig, Claus %A Kutalik, Zoltán %A Rivadeneira, Fernando %A Loos, Ruth J F %A Frayling, Timothy M %A Hirschhorn, Joel N %A Deloukas, Panos %A Lettre, Guillaume %K ADAMTS Proteins %K Adult %K Alleles %K Body Height %K Cell Adhesion Molecules %K Female %K Gene Frequency %K Genetic Variation %K Genome, Human %K Glycoproteins %K Glycosaminoglycans %K Hedgehog Proteins %K Humans %K Intercellular Signaling Peptides and Proteins %K Interferon Regulatory Factors %K Interleukin-11 Receptor alpha Subunit %K Male %K Multifactorial Inheritance %K NADPH Oxidase 4 %K NADPH Oxidases %K Phenotype %K Pregnancy-Associated Plasma Protein-A %K Procollagen N-Endopeptidase %K Proteoglycans %K Proteolysis %K Receptors, Androgen %K Somatomedins %X

Height is a highly heritable, classic polygenic trait with approximately 700 common associated variants identified through genome-wide association studies so far. Here, we report 83 height-associated coding variants with lower minor-allele frequencies (in the range of 0.1-4.8%) and effects of up to 2 centimetres per allele (such as those in IHH, STC2, AR and CRISPLD2), greater than ten times the average effect of common variants. In functional follow-up studies, rare height-increasing alleles of STC2 (giving an increase of 1-2 centimetres per allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes that are mutated in monogenic growth disorders and highlight new biological candidates (such as ADAMTS3, IL11RA and NOX4) and pathways (such as proteoglycan and glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate-to-large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways.

%B Nature %V 542 %P 186-190 %8 2017 Feb 09 %G eng %N 7640 %1 https://www.ncbi.nlm.nih.gov/pubmed/28146470?dopt=Abstract %R 10.1038/nature21039 %0 Journal Article %J Hum Mol Genet %D 2015 %T Association of exome sequences with plasma C-reactive protein levels in >9000 participants. %A Schick, Ursula M %A Auer, Paul L %A Bis, Joshua C %A Lin, Honghuang %A Wei, Peng %A Pankratz, Nathan %A Lange, Leslie A %A Brody, Jennifer %A Stitziel, Nathan O %A Kim, Daniel S %A Carlson, Christopher S %A Fornage, Myriam %A Haessler, Jeffery %A Hsu, Li %A Jackson, Rebecca D %A Kooperberg, Charles %A Leal, Suzanne M %A Psaty, Bruce M %A Eric Boerwinkle %A Tracy, Russell %A Ardissino, Diego %A Shah, Svati %A Willer, Cristen %A Loos, Ruth %A Melander, Olle %A McPherson, Ruth %A Hovingh, Kees %A Reilly, Muredach %A Watkins, Hugh %A Girelli, Domenico %A Fontanillas, Pierre %A Chasman, Daniel I %A Gabriel, Stacey B %A Richard A Gibbs %A Nickerson, Deborah A %A Kathiresan, Sekar %A Peters, Ulrike %A Dupuis, Josée %A Wilson, James G %A Rich, Stephen S %A Morrison, Alanna C %A Benjamin, Emelia J %A Gross, Myron D %A Reiner, Alex P %K Adult %K Black or African American %K C-Reactive Protein %K Cardiovascular Diseases %K Cohort Studies %K Exome %K Female %K Gene Frequency %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Hepatocyte Nuclear Factor 1-alpha %K Humans %K Male %K Plasma %K Polymorphism, Single Nucleotide %K Receptors, Interleukin-6 %K Risk Factors %K White People %X

C-reactive protein (CRP) concentration is a heritable systemic marker of inflammation that is associated with cardiovascular disease risk. Genome-wide association studies have identified CRP-associated common variants associated in ∼25 genes. Our aims were to apply exome sequencing to (1) assess whether the candidate loci contain rare coding variants associated with CRP levels and (2) perform an exome-wide search for rare variants in novel genes associated with CRP levels. We exome-sequenced 6050 European-Americans (EAs) and 3109 African-Americans (AAs) from the NHLBI-ESP and the CHARGE consortia, and performed association tests of sequence data with measured CRP levels. In single-variant tests across candidate loci, a novel rare (minor allele frequency = 0.16%) CRP-coding variant (rs77832441-A; p.Thr59Met) was associated with 53% lower mean CRP levels (P = 2.9 × 10(-6)). We replicated the association of rs77832441 in an exome array analysis of 11 414 EAs (P = 3.0 × 10(-15)). Despite a strong effect on CRP levels, rs77832441 was not associated with inflammation-related phenotypes including coronary heart disease. We also found evidence for an AA-specific association of APOE-ε2 rs7214 with higher CRP levels. At the exome-wide significance level (P < 5.0 × 10(-8)), we confirmed associations for reported common variants of HNF1A, CRP, IL6R and TOMM40-APOE. In gene-based tests, a burden of rare/lower frequency variation in CRP in EAs (P ≤ 6.8 × 10(-4)) and in retinoic acid receptor-related orphan receptor α (RORA) in AAs (P = 1.7 × 10(-3)) were associated with CRP levels at the candidate gene level (P < 2.0 × 10(-3)). This inquiry did not elucidate novel genes, but instead demonstrated that variants distributed across the allele frequency spectrum within candidate genes contribute to CRP levels.

%B Hum Mol Genet %V 24 %P 559-71 %8 2015 Jan 15 %G eng %N 2 %1 https://www.ncbi.nlm.nih.gov/pubmed/25187575?dopt=Abstract %R 10.1093/hmg/ddu450 %0 Journal Article %J Nature %D 2015 %T Exome sequencing identifies rare LDLR and APOA5 alleles conferring risk for myocardial infarction. %A Do, Ron %A Stitziel, Nathan O %A Won, Hong-Hee %A Jørgensen, Anders Berg %A Duga, Stefano %A Angelica Merlini, Pier %A Kiezun, Adam %A Farrall, Martin %A Goel, Anuj %A Zuk, Or %A Guella, Illaria %A Asselta, Rosanna %A Lange, Leslie A %A Peloso, Gina M %A Auer, Paul L %A Girelli, Domenico %A Martinelli, Nicola %A Farlow, Deborah N %A DePristo, Mark A %A Roberts, Robert %A Stewart, Alexander F R %A Saleheen, Danish %A Danesh, John %A Epstein, Stephen E %A Sivapalaratnam, Suthesh %A Hovingh, G Kees %A Kastelein, John J %A Samani, Nilesh J %A Schunkert, Heribert %A Erdmann, Jeanette %A Shah, Svati H %A Kraus, William E %A Davies, Robert %A Nikpay, Majid %A Johansen, Christopher T %A Wang, Jian %A Hegele, Robert A %A Hechter, Eliana %A Marz, Winfried %A Kleber, Marcus E %A Huang, Jie %A Johnson, Andrew D %A Li, Mingyao %A Burke, Greg L %A Gross, Myron %A Liu, Yongmei %A Assimes, Themistocles L %A Heiss, Gerardo %A Lange, Ethan M %A Folsom, Aaron R %A Taylor, Herman A %A Olivieri, Oliviero %A Hamsten, Anders %A Clarke, Robert %A Reilly, Dermot F %A Yin, Wu %A Rivas, Manuel A %A Donnelly, Peter %A Rossouw, Jacques E %A Psaty, Bruce M %A Herrington, David M %A Wilson, James G %A Rich, Stephen S %A Bamshad, Michael J %A Tracy, Russell P %A Cupples, L Adrienne %A Rader, Daniel J %A Reilly, Muredach P %A Spertus, John A %A Cresci, Sharon %A Hartiala, Jaana %A Tang, W H Wilson %A Hazen, Stanley L %A Allayee, Hooman %A Reiner, Alex P %A Carlson, Christopher S %A Kooperberg, Charles %A Jackson, Rebecca D %A Eric Boerwinkle %A Lander, Eric S %A Schwartz, Stephen M %A Siscovick, David S %A McPherson, Ruth %A Tybjaerg-Hansen, Anne %A Abecasis, Gonçalo R %A Watkins, Hugh %A Nickerson, Deborah A %A Ardissino, Diego %A Sunyaev, Shamil R %A O'Donnell, Christopher J %A Altshuler, David %A Gabriel, Stacey %A Kathiresan, Sekar %K Age Factors %K Age of Onset %K Alleles %K Apolipoprotein A-V %K Apolipoproteins A %K Case-Control Studies %K Cholesterol, LDL %K Coronary Artery Disease %K Exome %K Female %K Genetic Predisposition to Disease %K Genetics, Population %K Heterozygote %K Humans %K Male %K Middle Aged %K Mutation %K Myocardial Infarction %K National Heart, Lung, and Blood Institute (U.S.) %K Receptors, LDL %K Triglycerides %K United States %X

Myocardial infarction (MI), a leading cause of death around the world, displays a complex pattern of inheritance. When MI occurs early in life, genetic inheritance is a major component to risk. Previously, rare mutations in low-density lipoprotein (LDL) genes have been shown to contribute to MI risk in individual families, whereas common variants at more than 45 loci have been associated with MI risk in the population. Here we evaluate how rare mutations contribute to early-onset MI risk in the population. We sequenced the protein-coding regions of 9,793 genomes from patients with MI at an early age (≤50 years in males and ≤60 years in females) along with MI-free controls. We identified two genes in which rare coding-sequence mutations were more frequent in MI cases versus controls at exome-wide significance. At low-density lipoprotein receptor (LDLR), carriers of rare non-synonymous mutations were at 4.2-fold increased risk for MI; carriers of null alleles at LDLR were at even higher risk (13-fold difference). Approximately 2% of early MI cases harbour a rare, damaging mutation in LDLR; this estimate is similar to one made more than 40 years ago using an analysis of total cholesterol. Among controls, about 1 in 217 carried an LDLR coding-sequence mutation and had plasma LDL cholesterol > 190 mg dl(-1). At apolipoprotein A-V (APOA5), carriers of rare non-synonymous mutations were at 2.2-fold increased risk for MI. When compared with non-carriers, LDLR mutation carriers had higher plasma LDL cholesterol, whereas APOA5 mutation carriers had higher plasma triglycerides. Recent evidence has connected MI risk with coding-sequence mutations at two genes functionally related to APOA5, namely lipoprotein lipase and apolipoprotein C-III (refs 18, 19). Combined, these observations suggest that, as well as LDL cholesterol, disordered metabolism of triglyceride-rich lipoproteins contributes to MI risk.

%B Nature %V 518 %P 102-6 %8 2015 Feb 05 %G eng %N 7537 %1 https://www.ncbi.nlm.nih.gov/pubmed/25487149?dopt=Abstract %R 10.1038/nature13917 %0 Journal Article %J Nat Genet %D 2015 %T Large-scale genomic analyses link reproductive aging to hypothalamic signaling, breast cancer susceptibility and BRCA1-mediated DNA repair. %A Day, Felix R %A Ruth, Katherine S %A Thompson, Deborah J %A Lunetta, Kathryn L %A Pervjakova, Natalia %A Chasman, Daniel I %A Stolk, Lisette %A Finucane, Hilary K %A Sulem, Patrick %A Bulik-Sullivan, Brendan %A Esko, Tõnu %A Johnson, Andrew D %A Elks, Cathy E %A Franceschini, Nora %A He, Chunyan %A Altmaier, Elisabeth %A Brody, Jennifer A %A Franke, Lude L %A Huffman, Jennifer E %A Keller, Margaux F %A McArdle, Patrick F %A Nutile, Teresa %A Porcu, Eleonora %A Robino, Antonietta %A Rose, Lynda M %A Schick, Ursula M %A Smith, Jennifer A %A Teumer, Alexander %A Traglia, Michela %A Vuckovic, Dragana %A Yao, Jie %A Zhao, Wei %A Albrecht, Eva %A Amin, Najaf %A Corre, Tanguy %A Hottenga, Jouke-Jan %A Mangino, Massimo %A Smith, Albert V %A Tanaka, Toshiko %A Abecasis, Goncalo %A Andrulis, Irene L %A Anton-Culver, Hoda %A Antoniou, Antonis C %A Arndt, Volker %A Arnold, Alice M %A Barbieri, Caterina %A Beckmann, Matthias W %A Beeghly-Fadiel, Alicia %A Benitez, Javier %A Bernstein, Leslie %A Bielinski, Suzette J %A Blomqvist, Carl %A Eric Boerwinkle %A Bogdanova, Natalia V %A Bojesen, Stig E %A Bolla, Manjeet K %A Borresen-Dale, Anne-Lise %A Boutin, Thibaud S %A Brauch, Hiltrud %A Brenner, Hermann %A Brüning, Thomas %A Burwinkel, Barbara %A Campbell, Archie %A Campbell, Harry %A Chanock, Stephen J %A Chapman, J Ross %A Chen, Yii-Der Ida %A Chenevix-Trench, Georgia %A Couch, Fergus J %A Coviello, Andrea D %A Cox, Angela %A Czene, Kamila %A Darabi, Hatef %A De Vivo, Immaculata %A Demerath, Ellen W %A Dennis, Joe %A Devilee, Peter %A Dörk, Thilo %A Dos-Santos-Silva, Isabel %A Dunning, Alison M %A Eicher, John D %A Fasching, Peter A %A Faul, Jessica D %A Figueroa, Jonine %A Flesch-Janys, Dieter %A Gandin, Ilaria %A Garcia, Melissa E %A García-Closas, Montserrat %A Giles, Graham G %A Girotto, Giorgia G %A Goldberg, Mark S %A González-Neira, Anna %A Goodarzi, Mark O %A Grove, Megan L %A Gudbjartsson, Daniel F %A Guénel, Pascal %A Guo, Xiuqing %A Haiman, Christopher A %A Hall, Per %A Hamann, Ute %A Henderson, Brian E %A Hocking, Lynne J %A Hofman, Albert %A Homuth, Georg %A Hooning, Maartje J %A Hopper, John L %A Hu, Frank B %A Huang, Jinyan %A Humphreys, Keith %A Hunter, David J %A Jakubowska, Anna %A Jones, Samuel E %A Kabisch, Maria %A Karasik, David %A Knight, Julia A %A Kolcic, Ivana %A Kooperberg, Charles %A Kosma, Veli-Matti %A Kriebel, Jennifer %A Kristensen, Vessela %A Lambrechts, Diether %A Langenberg, Claudia %A Li, Jingmei %A Li, Xin %A Lindström, Sara %A Liu, Yongmei %A Luan, Jian'an %A Lubinski, Jan %A Mägi, Reedik %A Mannermaa, Arto %A Manz, Judith %A Margolin, Sara %A Marten, Jonathan %A Martin, Nicholas G %A Masciullo, Corrado %A Meindl, Alfons %A Michailidou, Kyriaki %A Mihailov, Evelin %A Milani, Lili %A Milne, Roger L %A Müller-Nurasyid, Martina %A Nalls, Michael %A Neale, Ben M %A Nevanlinna, Heli %A Neven, Patrick %A Newman, Anne B %A Nordestgaard, Børge G %A Olson, Janet E %A Padmanabhan, Sandosh %A Peterlongo, Paolo %A Peters, Ulrike %A Petersmann, Astrid %A Peto, Julian %A Pharoah, Paul D P %A Pirastu, Nicola N %A Pirie, Ailith %A Pistis, Giorgio %A Polasek, Ozren %A Porteous, David %A Psaty, Bruce M %A Pylkäs, Katri %A Radice, Paolo %A Raffel, Leslie J %A Rivadeneira, Fernando %A Rudan, Igor %A Rudolph, Anja %A Ruggiero, Daniela %A Sala, Cinzia F %A Sanna, Serena %A Sawyer, Elinor J %A Schlessinger, David %A Schmidt, Marjanka K %A Schmidt, Frank %A Schmutzler, Rita K %A Schoemaker, Minouk J %A Scott, Robert A %A Seynaeve, Caroline M %A Simard, Jacques %A Sorice, Rossella %A Southey, Melissa C %A Stöckl, Doris %A Strauch, Konstantin %A Swerdlow, Anthony %A Taylor, Kent D %A Thorsteinsdottir, Unnur %A Toland, Amanda E %A Tomlinson, Ian %A Truong, Thérèse %A Tryggvadottir, Laufey %A Turner, Stephen T %A Vozzi, Diego %A Wang, Qin %A Wellons, Melissa %A Willemsen, Gonneke %A Wilson, James F %A Winqvist, Robert %A Wolffenbuttel, Bruce B H R %A Wright, Alan F %A Yannoukakos, Drakoulis %A Zemunik, Tatijana %A Zheng, Wei %A Zygmunt, Marek %A Bergmann, Sven %A Boomsma, Dorret I %A Buring, Julie E %A Ferrucci, Luigi %A Montgomery, Grant W %A Gudnason, Vilmundur %A Spector, Tim D %A van Duijn, Cornelia M %A Alizadeh, Behrooz Z %A Ciullo, Marina %A Crisponi, Laura %A Easton, Douglas F %A Gasparini, Paolo P %A Gieger, Christian %A Harris, Tamara B %A Hayward, Caroline %A Kardia, Sharon L R %A Kraft, Peter %A McKnight, Barbara %A Metspalu, Andres %A Morrison, Alanna C %A Reiner, Alex P %A Ridker, Paul M %A Rotter, Jerome I %A Toniolo, Daniela %A Uitterlinden, André G %A Ulivi, Sheila %A Völzke, Henry %A Wareham, Nicholas J %A Weir, David R %A Yerges-Armstrong, Laura M %A Price, Alkes L %A Stefansson, Kari %A Visser, Jenny A %A Ong, Ken K %A Chang-Claude, Jenny %A Murabito, Joanne M %A Perry, John R B %A Murray, Anna %K Adult %K Age Factors %K Aging %K BRCA1 Protein %K Breast Neoplasms %K DNA Repair %K Female %K Gene Regulatory Networks %K Genetic Predisposition to Disease %K Genetic Variation %K Genome-Wide Association Study %K Genomics %K Genotype %K Humans %K Hypothalamus %K Menopause %K Middle Aged %K Models, Genetic %K Phenotype %K Reproduction %K Signal Transduction %X

Menopause timing has a substantial impact on infertility and risk of disease, including breast cancer, but the underlying mechanisms are poorly understood. We report a dual strategy in ∼70,000 women to identify common and low-frequency protein-coding variation associated with age at natural menopause (ANM). We identified 44 regions with common variants, including two regions harboring additional rare missense alleles of large effect. We found enrichment of signals in or near genes involved in delayed puberty, highlighting the first molecular links between the onset and end of reproductive lifespan. Pathway analyses identified major association with DNA damage response (DDR) genes, including the first common coding variant in BRCA1 associated with any complex trait. Mendelian randomization analyses supported a causal effect of later ANM on breast cancer risk (∼6% increase in risk per year; P = 3 × 10(-14)), likely mediated by prolonged sex hormone exposure rather than DDR mechanisms.

%B Nat Genet %V 47 %P 1294-1303 %8 2015 Nov %G eng %N 11 %1 https://www.ncbi.nlm.nih.gov/pubmed/26414677?dopt=Abstract %R 10.1038/ng.3412 %0 Journal Article %J Blood %D 2015 %T Rare and low-frequency variants and their association with plasma levels of fibrinogen, FVII, FVIII, and vWF. %A Huffman, Jennifer E %A de Vries, Paul S %A Morrison, Alanna C %A Sabater-Lleal, Maria %A Kacprowski, Tim %A Auer, Paul L %A Brody, Jennifer A %A Chasman, Daniel I %A Chen, Ming-Huei %A Guo, Xiuqing %A Lin, Li-An %A Marioni, Riccardo E %A Müller-Nurasyid, Martina %A Yanek, Lisa R %A Pankratz, Nathan %A Grove, Megan L %A de Maat, Moniek P M %A Cushman, Mary %A Wiggins, Kerri L %A Qi, Lihong %A Sennblad, Bengt %A Harris, Sarah E %A Polasek, Ozren %A Riess, Helene %A Rivadeneira, Fernando %A Rose, Lynda M %A Goel, Anuj %A Taylor, Kent D %A Teumer, Alexander %A Uitterlinden, André G %A Vaidya, Dhananjay %A Yao, Jie %A Tang, Weihong %A Levy, Daniel %A Waldenberger, Melanie %A Becker, Diane M %A Folsom, Aaron R %A Giulianini, Franco %A Greinacher, Andreas %A Hofman, Albert %A Huang, Chiang-Ching %A Kooperberg, Charles %A Silveira, Angela %A Starr, John M %A Strauch, Konstantin %A Strawbridge, Rona J %A Wright, Alan F %A McKnight, Barbara %A Franco, Oscar H %A Zakai, Neil %A Mathias, Rasika A %A Psaty, Bruce M %A Ridker, Paul M %A Tofler, Geoffrey H %A Völker, Uwe %A Watkins, Hugh %A Fornage, Myriam %A Hamsten, Anders %A Deary, Ian J %A Eric Boerwinkle %A Koenig, Wolfgang %A Rotter, Jerome I %A Hayward, Caroline %A Dehghan, Abbas %A Reiner, Alex P %A O'Donnell, Christopher J %A Smith, Nicholas L %K Cohort Studies %K Factor VII %K Factor VIII %K Fibrinogen %K Gene Frequency %K Genetic Association Studies %K Genetic Variation %K Humans %K Nerve Tissue Proteins %K Polymorphism, Single Nucleotide %K Potassium Channels %K Potassium Channels, Sodium-Activated %K von Willebrand Factor %X

Fibrinogen, coagulation factor VII (FVII), and factor VIII (FVIII) and its carrier von Willebrand factor (vWF) play key roles in hemostasis. Previously identified common variants explain only a small fraction of the trait heritabilities, and additional variations may be explained by associations with rarer variants with larger effects. The aim of this study was to identify low-frequency (minor allele frequency [MAF] ≥0.01 and <0.05) and rare (MAF <0.01) variants that influence plasma concentrations of these 4 hemostatic factors by meta-analyzing exome chip data from up to 76,000 participants of 4 ancestries. We identified 12 novel associations of low-frequency (n = 2) and rare (n = 10) variants across the fibrinogen, FVII, FVIII, and vWF traits that were independent of previously identified associations. Novel loci were found within previously reported genes and had effect sizes much larger than and independent of previously identified common variants. In addition, associations at KCNT1, HID1, and KATNB1 identified new candidate genes related to hemostasis for follow-up replication and functional genomic analysis. Newly identified low-frequency and rare-variant associations accounted for modest amounts of trait variance and therefore are unlikely to increase predicted trait heritability but provide new information for understanding individual variation in hemostasis pathways.

%B Blood %V 126 %P e19-29 %8 2015 Sep 10 %G eng %N 11 %1 https://www.ncbi.nlm.nih.gov/pubmed/26105150?dopt=Abstract %R 10.1182/blood-2015-02-624551 %0 Journal Article %J Am J Hum Genet %D 2014 %T Association of low-frequency and rare coding-sequence variants with blood lipids and coronary heart disease in 56,000 whites and blacks. %A Peloso, Gina M %A Auer, Paul L %A Bis, Joshua C %A Voorman, Arend %A Morrison, Alanna C %A Stitziel, Nathan O %A Brody, Jennifer A %A Khetarpal, Sumeet A %A Crosby, Jacy R %A Fornage, Myriam %A Isaacs, Aaron %A Jakobsdottir, Johanna %A Feitosa, Mary F %A Davies, Gail %A Huffman, Jennifer E %A Manichaikul, Ani %A Davis, Brian %A Lohman, Kurt %A Joon, Aron Y %A Smith, Albert V %A Grove, Megan L %A Zanoni, Paolo %A Redon, Valeska %A Demissie, Serkalem %A Lawson, Kim %A Peters, Ulrike %A Carlson, Christopher %A Jackson, Rebecca D %A Ryckman, Kelli K %A Mackey, Rachel H %A Robinson, Jennifer G %A Siscovick, David S %A Schreiner, Pamela J %A Mychaleckyj, Josyf C %A Pankow, James S %A Hofman, Albert %A Uitterlinden, André G %A Harris, Tamara B %A Taylor, Kent D %A Stafford, Jeanette M %A Reynolds, Lindsay M %A Marioni, Riccardo E %A Dehghan, Abbas %A Franco, Oscar H %A Patel, Aniruddh P %A Lu, Yingchang %A Hindy, George %A Gottesman, Omri %A Bottinger, Erwin P %A Melander, Olle %A Orho-Melander, Marju %A Loos, Ruth J F %A Duga, Stefano %A Merlini, Piera Angelica %A Farrall, Martin %A Goel, Anuj %A Asselta, Rosanna %A Girelli, Domenico %A Martinelli, Nicola %A Shah, Svati H %A Kraus, William E %A Li, Mingyao %A Rader, Daniel J %A Reilly, Muredach P %A McPherson, Ruth %A Watkins, Hugh %A Ardissino, Diego %A Zhang, Qunyuan %A Wang, Judy %A Tsai, Michael Y %A Taylor, Herman A %A Correa, Adolfo %A Griswold, Michael E %A Lange, Leslie A %A Starr, John M %A Rudan, Igor %A Eiriksdottir, Gudny %A Launer, Lenore J %A Ordovas, Jose M %A Levy, Daniel %A Chen, Y-D Ida %A Reiner, Alexander P %A Hayward, Caroline %A Polasek, Ozren %A Deary, Ian J %A Borecki, Ingrid B %A Liu, Yongmei %A Gudnason, Vilmundur %A Wilson, James G %A van Duijn, Cornelia M %A Kooperberg, Charles %A Rich, Stephen S %A Psaty, Bruce M %A Rotter, Jerome I %A O'Donnell, Christopher J %A Rice, Kenneth %A Eric Boerwinkle %A Kathiresan, Sekar %A Cupples, L Adrienne %K 1-Alkyl-2-acetylglycerophosphocholine Esterase %K Adult %K Aged %K Alleles %K Animals %K Black People %K Cholesterol, HDL %K Cholesterol, LDL %K Cohort Studies %K Coronary Disease %K Female %K Gene Frequency %K Genetic Association Studies %K Genetic Code %K Genetic Variation %K Humans %K Linear Models %K Male %K Mice %K Mice, Inbred C57BL %K Microtubule-Associated Proteins %K Middle Aged %K Phenotype %K Sequence Analysis, DNA %K Subtilisins %K Triglycerides %K White People %X

Low-frequency coding DNA sequence variants in the proprotein convertase subtilisin/kexin type 9 gene (PCSK9) lower plasma low-density lipoprotein cholesterol (LDL-C), protect against risk of coronary heart disease (CHD), and have prompted the development of a new class of therapeutics. It is uncertain whether the PCSK9 example represents a paradigm or an isolated exception. We used the "Exome Array" to genotype >200,000 low-frequency and rare coding sequence variants across the genome in 56,538 individuals (42,208 European ancestry [EA] and 14,330 African ancestry [AA]) and tested these variants for association with LDL-C, high-density lipoprotein cholesterol (HDL-C), and triglycerides. Although we did not identify new genes associated with LDL-C, we did identify four low-frequency (frequencies between 0.1% and 2%) variants (ANGPTL8 rs145464906 [c.361C>T; p.Gln121*], PAFAH1B2 rs186808413 [c.482C>T; p.Ser161Leu], COL18A1 rs114139997 [c.331G>A; p.Gly111Arg], and PCSK7 rs142953140 [c.1511G>A; p.Arg504His]) with large effects on HDL-C and/or triglycerides. None of these four variants was associated with risk for CHD, suggesting that examples of low-frequency coding variants with robust effects on both lipids and CHD will be limited.

%B Am J Hum Genet %V 94 %P 223-32 %8 2014 Feb 06 %G eng %N 2 %1 https://www.ncbi.nlm.nih.gov/pubmed/24507774?dopt=Abstract %R 10.1016/j.ajhg.2014.01.009 %0 Journal Article %J PLoS One %D 2014 %T Prospective associations of coronary heart disease loci in African Americans using the MetaboChip: the PAGE study. %A Franceschini, Nora %A Hu, Yijuan %A Reiner, Alex P %A Buyske, Steven %A Nalls, Mike %A Yanek, Lisa R %A Li, Yun %A Hindorff, Lucia A %A Cole, Shelley A %A Howard, Barbara V %A Stafford, Jeanette M %A Carty, Cara L %A Sethupathy, Praveen %A Martin, Lisa W %A Lin, Dan-Yu %A Johnson, Karen C %A Becker, Lewis C %A North, Kari E %A Dehghan, Abbas %A Bis, Joshua C %A Liu, Yongmei %A Greenland, Philip %A Manson, JoAnn E %A Maeda, Nobuyo %A Garcia, Melissa %A Harris, Tamara B %A Becker, Diane M %A O'Donnell, Christopher %A Heiss, Gerardo %A Kooperberg, Charles %A Eric Boerwinkle %K Adaptor Proteins, Vesicular Transport %K Black or African American %K Coronary Disease %K Female %K Genetic Association Studies %K Genetic Predisposition to Disease %K Humans %K Male %K Oligonucleotide Array Sequence Analysis %K Polymorphism, Single Nucleotide %K Prospective Studies %K Proto-Oncogene Proteins c-myc %X

BACKGROUND: Coronary heart disease (CHD) is a leading cause of morbidity and mortality in African Americans. However, there is a paucity of studies assessing genetic determinants of CHD in African Americans. We examined the association of published variants in CHD loci with incident CHD, attempted to fine map these loci, and characterize novel variants influencing CHD risk in African Americans.

METHODS AND RESULTS: Up to 8,201 African Americans (including 546 first CHD events) were genotyped using the MetaboChip array in the Atherosclerosis Risk in Communities (ARIC) study and Women's Health Initiative (WHI). We tested associations using Cox proportional hazard models in sex- and study-stratified analyses and combined results using meta-analysis. Among 44 validated CHD loci available in the array, we replicated and fine-mapped the SORT1 locus, and showed same direction of effects as reported in studies of individuals of European ancestry for SNPs in 22 additional published loci. We also identified a SNP achieving array wide significance (MYC: rs2070583, allele frequency 0.02, P = 8.1 × 10(-8)), but the association did not replicate in an additional 8,059 African Americans (577 events) from the WHI, HealthABC and GeneSTAR studies, and in a meta-analysis of 5 cohort studies of European ancestry (24,024 individuals including 1,570 cases of MI and 2,406 cases of CHD) from the CHARGE Consortium.

CONCLUSIONS: Our findings suggest that some CHD loci previously identified in individuals of European ancestry may be relevant to incident CHD in African Americans.

%B PLoS One %V 9 %P e113203 %8 2014 %G eng %N 12 %1 https://www.ncbi.nlm.nih.gov/pubmed/25542012?dopt=Abstract %R 10.1371/journal.pone.0113203