%0 Journal Article %J medRxiv %D 2024 %T Association analysis of mitochondrial DNA heteroplasmic variants: methods and application. %A Sun, Xianbang %A Bulekova, Katia %A Yang, Jian %A Lai, Meng %A Pitsillides, Achilleas N %A Liu, Xue %A Zhang, Yuankai %A Guo, Xiuqing %A Yong, Qian %A Raffield, Laura M %A Rotter, Jerome I %A Rich, Stephen S %A Abecasis, Goncalo %A Carson, April P %A Vasan, Ramachandran S %A Bis, Joshua C %A Psaty, Bruce M %A Eric Boerwinkle %A Fitzpatrick, Annette L %A Satizabal, Claudia L %A Arking, Dan E %A Ding, Jun %A Levy, Daniel %A Liu, Chunyu %X
We rigorously assessed a comprehensive association testing framework for heteroplasmy, employing both simulated and real-world data. This framework employed a variant allele fraction (VAF) threshold and harnessed multiple gene-based tests for robust identification and association testing of heteroplasmy. Our simulation studies demonstrated that gene-based tests maintained an appropriate type I error rate at α=0.001. Notably, when 5% or more heteroplasmic variants within a target region were linked to an outcome, burden-extension tests (including the adaptive burden test, variable threshold burden test, and z-score weighting burden test) outperformed the sequence kernel association test (SKAT) and the original burden test. Applying this framework, we conducted association analyses on whole-blood derived heteroplasmy in 17,507 individuals of African and European ancestries (31% of African Ancestry, mean age of 62, with 58% women) with whole genome sequencing data. We performed both cohort- and ancestry-specific association analyses, followed by meta-analysis on both pooled samples and within each ancestry group. Our results suggest that mtDNA-encoded genes/regions are likely to exhibit varying rates in somatic aging, with the notably strong associations observed between heteroplasmy in the and genes (<0.001) and advance aging by the Original Burden test. In contrast, SKAT identified significant associations (<0.001) between diabetes and the aggregated effects of heteroplasmy in several protein-coding genes. Further research is warranted to validate these findings. In summary, our proposed statistical framework represents a valuable tool for facilitating association testing of heteroplasmy with disease traits in large human populations.
%B medRxiv %8 2024 Jan 13 %G eng %1 https://www.ncbi.nlm.nih.gov/pubmed/38260412?dopt=Abstract %R 10.1101/2024.01.12.24301233 %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 %XMutations 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 %XBackground 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 JAMA Cardiol %D 2023 %T Association of Rare Protein-Truncating DNA Variants in APOB or PCSK9 With Low-density Lipoprotein Cholesterol Level and Risk of Coronary Heart Disease. %A Dron, Jacqueline S %A Patel, Aniruddh P %A Zhang, Yiyi %A Jurgens, Sean J %A Maamari, Dimitri J %A Wang, Minxian %A Eric Boerwinkle %A Morrison, Alanna C %A de Vries, Paul S %A Fornage, Myriam %A Hou, Lifang %A Lloyd-Jones, Donald M %A Psaty, Bruce M %A Tracy, Russell P %A Bis, Joshua C %A Vasan, Ramachandran S %A Levy, Daniel %A Heard-Costa, Nancy %A Rich, Stephen S %A Guo, Xiuqing %A Taylor, Kent D %A Richard A Gibbs %A Rotter, Jerome I %A Willer, Cristen J %A Oelsner, Elizabeth C %A Moran, Andrew E %A Peloso, Gina M %A Natarajan, Pradeep %A Khera, Amit V %K Adult %K Aged %K Apolipoproteins B %K Cholesterol, LDL %K Coronary Disease %K DNA %K Female %K Humans %K Male %K Middle Aged %K Proprotein Convertase 9 %K Prospective Studies %XIMPORTANCE: Protein-truncating variants (PTVs) in apolipoprotein B (APOB) and proprotein convertase subtilisin/kexin type 9 (PCSK9) are associated with significantly lower low-density lipoprotein (LDL) cholesterol concentrations. The association of these PTVs with coronary heart disease (CHD) warrants further characterization in large, multiracial prospective cohort studies.
OBJECTIVE: To evaluate the association of PTVs in APOB and PCSK9 with LDL cholesterol concentrations and CHD risk.
DESIGN, SETTING, AND PARTICIPANTS: This studied included participants from 5 National Heart, Lung, and Blood Institute (NHLBI) studies and the UK Biobank. NHLBI study participants aged 5 to 84 years were recruited between 1971 and 2002 across the US and underwent whole-genome sequencing. UK Biobank participants aged 40 to 69 years were recruited between 2006 and 2010 in the UK and underwent whole-exome sequencing. Data were analyzed from June 2021 to October 2022.
EXPOSURES: PTVs in APOB and PCSK9.
MAIN OUTCOMES AND MEASURES: Estimated untreated LDL cholesterol levels and CHD.
RESULTS: Among 19 073 NHLBI participants (10 598 [55.6%] female; mean [SD] age, 52 [17] years), 139 (0.7%) carried an APOB or PCSK9 PTV, which was associated with 49 mg/dL (95% CI, 43-56) lower estimated untreated LDL cholesterol level. Over a median (IQR) follow-up of 21.5 (13.9-29.4) years, incident CHD was observed in 12 of 139 carriers (8.6%) vs 3029 of 18 934 noncarriers (16.0%), corresponding to an adjusted hazard ratio of 0.51 (95% CI, 0.28-0.89; P = .02). Among 190 464 UK Biobank participants (104 831 [55.0%] female; mean [SD] age, 57 [8] years), 662 (0.4%) carried a PTV, which was associated with 45 mg/dL (95% CI, 42-47) lower estimated untreated LDL cholesterol level. Estimated CHD risk by age 75 years was 3.7% (95% CI, 2.0-5.3) in carriers vs 7.0% (95% CI, 6.9-7.2) in noncarriers, corresponding to an adjusted hazard ratio of 0.51 (95% CI, 0.32-0.81; P = .004).
CONCLUSIONS AND RELEVANCE: Among 209 537 individuals in this study, 0.4% carried an APOB or PCSK9 PTV that was associated with less exposure to LDL cholesterol and a 49% lower risk of CHD.
%B JAMA Cardiol %V 8 %P 258-267 %8 2023 Mar 01 %G eng %N 3 %1 https://www.ncbi.nlm.nih.gov/pubmed/36723951?dopt=Abstract %R 10.1001/jamacardio.2022.5271 %0 Journal Article %J Nature %D 2023 %T Author Correction: Clonal haematopoiesis and risk of chronic liver disease. %A Wong, Waihay J %A Emdin, Connor %A Bick, Alexander G %A Zekavat, Seyedeh M %A Niroula, Abhishek %A Pirruccello, James P %A Dichtel, Laura %A Griffin, Gabriel %A Uddin, Md Mesbah %A Gibson, Christopher J %A Kovalcik, Veronica %A Lin, Amy E %A McConkey, Marie E %A Vromman, Amelie %A Sellar, Rob S %A Kim, Peter G %A Agrawal, Mridul %A Weinstock, Joshua %A Long, Michelle T %A Yu, Bing %A Banerjee, Rajarshi %A Nicholls, Rowan C %A Dennis, Andrea %A Kelly, Matt %A Loh, Po-Ru %A McCarroll, Steve %A Eric Boerwinkle %A Vasan, Ramachandran S %A Jaiswal, Siddhartha %A Johnson, Andrew D %A Chung, Raymond T %A Corey, Kathleen %A Levy, Daniel %A Ballantyne, Christie %A Ebert, Benjamin L %A Natarajan, Pradeep %B Nature %V 619 %P E47 %8 2023 Jul %G eng %N 7970 %1 https://www.ncbi.nlm.nih.gov/pubmed/37400552?dopt=Abstract %R 10.1038/s41586-023-06375-z %0 Journal Article %J Nature %D 2023 %T Clonal haematopoiesis and risk of chronic liver disease. %A Wong, Waihay J %A Emdin, Connor %A Bick, Alexander G %A Zekavat, Seyedeh M %A Niroula, Abhishek %A Pirruccello, James P %A Dichtel, Laura %A Griffin, Gabriel %A Uddin, Md Mesbah %A Gibson, Christopher J %A Kovalcik, Veronica %A Lin, Amy E %A McConkey, Marie E %A Vromman, Amelie %A Sellar, Rob S %A Kim, Peter G %A Agrawal, Mridul %A Weinstock, Joshua %A Long, Michelle T %A Yu, Bing %A Banerjee, Rajarshi %A Nicholls, Rowan C %A Dennis, Andrea %A Kelly, Matt %A Loh, Po-Ru %A McCarroll, Steve %A Eric Boerwinkle %A Vasan, Ramachandran S %A Jaiswal, Siddhartha %A Johnson, Andrew D %A Chung, Raymond T %A Corey, Kathleen %A Levy, Daniel %A Ballantyne, Christie %A Ebert, Benjamin L %A Natarajan, Pradeep %K Animals %K Clonal Hematopoiesis %K Disease Progression %K Disease Susceptibility %K Hepatitis %K Inflammation %K Liver Cirrhosis %K Mice %K Non-alcoholic Fatty Liver Disease %K Odds Ratio %XChronic liver disease is a major public health burden worldwide. Although different aetiologies and mechanisms of liver injury exist, progression of chronic liver disease follows a common pathway of liver inflammation, injury and fibrosis. Here we examined the association between clonal haematopoiesis of indeterminate potential (CHIP) and chronic liver disease in 214,563 individuals from 4 independent cohorts with whole-exome sequencing data (Framingham Heart Study, Atherosclerosis Risk in Communities Study, UK Biobank and Mass General Brigham Biobank). CHIP was associated with an increased risk of prevalent and incident chronic liver disease (odds ratio = 2.01, 95% confidence interval (95% CI) [1.46, 2.79]; P < 0.001). Individuals with CHIP were more likely to demonstrate liver inflammation and fibrosis detectable by magnetic resonance imaging compared to those without CHIP (odds ratio = 1.74, 95% CI [1.16, 2.60]; P = 0.007). To assess potential causality, Mendelian randomization analyses showed that genetic predisposition to CHIP was associated with a greater risk of chronic liver disease (odds ratio = 2.37, 95% CI [1.57, 3.6]; P < 0.001). In a dietary model of non-alcoholic steatohepatitis, mice transplanted with Tet2-deficient haematopoietic cells demonstrated more severe liver inflammation and fibrosis. These effects were mediated by the NLRP3 inflammasome and increased levels of expression of downstream inflammatory cytokines in Tet2-deficient macrophages. In summary, clonal haematopoiesis is associated with an elevated risk of liver inflammation and chronic liver disease progression through an aberrant inflammatory response.
%B Nature %V 616 %P 747-754 %8 2023 Apr %G eng %N 7958 %1 https://www.ncbi.nlm.nih.gov/pubmed/37046084?dopt=Abstract %R 10.1038/s41586-023-05857-4 %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 %XExonic 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 %XExonic 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 %XNononcogenic 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 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 %XMeta-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 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 %XLarge-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 Type 2 Diabetes Modifies the Association of CAD Genomic Risk Variants With Subclinical Atherosclerosis. %A Hasbani, Natalie R %A Westerman, Kenneth E %A Kwak, Soo Heon %A Chen, Han %A Li, Xihao %A Di Corpo, Daniel %A Wessel, Jennifer %A Bis, Joshua C %A Sarnowski, Chloe %A Wu, Peitao %A Bielak, Lawrence F %A Guo, Xiuqing %A Heard-Costa, Nancy %A Kinney, Gregory L %A Mahaney, Michael C %A Montasser, May E %A Palmer, Nicholette D %A Raffield, Laura M %A Terry, James G %A Yanek, Lisa R %A Bon, Jessica %A Bowden, Donald W %A Brody, Jennifer A %A Duggirala, Ravindranath %A Jacobs, David R %A Kalyani, Rita R %A Lange, Leslie A %A Mitchell, Braxton D %A Smith, Jennifer A %A Taylor, Kent D %A Carson, April P %A Curran, Joanne E %A Fornage, Myriam %A Freedman, Barry I %A Gabriel, Stacey %A Richard A Gibbs %A Gupta, Namrata %A Kardia, Sharon L R %A Kral, Brian G %A Momin, Zeineen %A Newman, Anne B %A Post, Wendy S %A Viaud-Martinez, Karine A %A Young, Kendra A %A Becker, Lewis C %A Bertoni, Alain G %A Blangero, John %A Carr, John J %A Pratte, Katherine %A Psaty, Bruce M %A Rich, Stephen S %A Wu, Joseph C %A Malhotra, Rajeev %A Peyser, Patricia A %A Morrison, Alanna C %A Vasan, Ramachandran S %A Lin, Xihong %A Rotter, Jerome I %A Meigs, James B %A Manning, Alisa K %A de Vries, Paul S %K Atherosclerosis %K Carotid Intima-Media Thickness %K Coronary Artery Disease %K Diabetes Mellitus, Type 2 %K Genomics %K Humans %K Plaque, Atherosclerotic %K Risk Factors %XBACKGROUND: Individuals with type 2 diabetes (T2D) have an increased risk of coronary artery disease (CAD), but questions remain about the underlying pathology. Identifying which CAD loci are modified by T2D in the development of subclinical atherosclerosis (coronary artery calcification [CAC], carotid intima-media thickness, or carotid plaque) may improve our understanding of the mechanisms leading to the increased CAD in T2D.
METHODS: We compared the common and rare variant associations of known CAD loci from the literature on CAC, carotid intima-media thickness, and carotid plaque in up to 29 670 participants, including up to 24 157 normoglycemic controls and 5513 T2D cases leveraging whole-genome sequencing data from the Trans-Omics for Precision Medicine program. We included first-order T2D interaction terms in each model to determine whether CAD loci were modified by T2D. The genetic main and interaction effects were assessed using a joint test to determine whether a CAD variant, or gene-based rare variant set, was associated with the respective subclinical atherosclerosis measures and then further determined whether these loci had a significant interaction test.
RESULTS: Using a Bonferroni-corrected significance threshold of <1.6×10, we identified 3 genes (, , and ) associated with CAC and 2 genes ( and ) associated with carotid intima-media thickness and carotid plaque, respectively, through gene-based rare variant set analysis. Both and also had significantly different associations for CAC in T2D cases versus controls. No significant interaction tests were identified through the candidate single-variant analysis.
CONCLUSIONS: These results highlight T2D as an important modifier of rare variant associations in CAD loci with CAC.
%B Circ Genom Precis Med %V 16 %P e004176 %8 2023 Dec %G eng %N 6 %1 https://www.ncbi.nlm.nih.gov/pubmed/38014529?dopt=Abstract %R 10.1161/CIRCGEN.123.004176 %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 %XBACKGROUND: 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 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 %XDiabetic 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 Hum Mol Genet %D 2022 %T Assessing the contribution of rare genetic variants to phenotypes of chronic obstructive pulmonary disease using whole-genome sequence data. %A Kim, Wonji %A Hecker, Julian %A Barr, R Graham %A Eric Boerwinkle %A Cade, Brian %A Correa, Adolfo %A Dupuis, Josée %A Gharib, Sina A %A Lange, Leslie %A London, Stephanie J %A Morrison, Alanna C %A O'Connor, George T %A Oelsner, Elizabeth C %A Psaty, Bruce M %A Vasan, Ramachandran S %A Redline, Susan %A Rich, Stephen S %A Rotter, Jerome I %A Yu, Bing %A Lange, Christoph %A Manichaikul, Ani %A Zhou, Jin J %A Sofer, Tamar %A Silverman, Edwin K %A Qiao, Dandi %A Cho, Michael H %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Phenotype %K Polymorphism, Single Nucleotide %K Pulmonary Disease, Chronic Obstructive %XRATIONALE: Genetic variation has a substantial contribution to chronic obstructive pulmonary disease (COPD) and lung function measurements. Heritability estimates using genome-wide genotyping data can be biased if analyses do not appropriately account for the nonuniform distribution of genetic effects across the allele frequency and linkage disequilibrium (LD) spectrum. In addition, the contribution of rare variants has been unclear.
OBJECTIVES: We sought to assess the heritability of COPD and lung function using whole-genome sequence data from the Trans-Omics for Precision Medicine program.
METHODS: Using the genome-based restricted maximum likelihood method, we partitioned the genome into bins based on minor allele frequency and LD scores and estimated heritability of COPD, FEV1% predicted and FEV1/FVC ratio in 11 051 European ancestry and 5853 African-American participants.
MEASUREMENTS AND MAIN RESULTS: In European ancestry participants, the estimated heritability of COPD, FEV1% predicted and FEV1/FVC ratio were 35.5%, 55.6% and 32.5%, of which 18.8%, 19.7%, 17.8% were from common variants, and 16.6%, 35.8%, and 14.6% were from rare variants. These estimates had wide confidence intervals, with common variants and some sets of rare variants showing a statistically significant contribution (P-value < 0.05). In African-Americans, common variant heritability was similar to European ancestry participants, but lower sample size precluded calculation of rare variant heritability.
CONCLUSIONS: Our study provides updated and unbiased estimates of heritability for COPD and lung function, and suggests an important contribution of rare variants. Larger studies of more diverse ancestry will improve accuracy of these estimates.
%B Hum Mol Genet %V 31 %P 3873-3885 %8 2022 Nov 10 %G eng %N 22 %1 https://www.ncbi.nlm.nih.gov/pubmed/35766891?dopt=Abstract %R 10.1093/hmg/ddac117 %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 %XLarge-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 Am J Hum Genet %D 2022 %T Polygenic transcriptome risk scores for COPD and lung function improve cross-ethnic portability of prediction in the NHLBI TOPMed program. %A Hu, Xiaowei %A Qiao, Dandi %A Kim, Wonji %A Moll, Matthew %A Balte, Pallavi P %A Lange, Leslie A %A Bartz, Traci M %A Kumar, Rajesh %A Li, Xingnan %A Yu, Bing %A Cade, Brian E %A Laurie, Cecelia A %A Sofer, Tamar %A Ruczinski, Ingo %A Nickerson, Deborah A %A Donna M Muzny %A Ginger A Metcalf %A Harshavardhan Doddapaneni %A Gabriel, Stacy %A Gupta, Namrata %A Dugan-Perez, Shannon %A Cupples, L Adrienne %A Loehr, Laura R %A Jain, Deepti %A Rotter, Jerome I %A Wilson, James G %A Psaty, Bruce M %A Fornage, Myriam %A Morrison, Alanna C %A Vasan, Ramachandran S %A Washko, George %A Rich, Stephen S %A O'Connor, George T %A Bleecker, Eugene %A Kaplan, Robert C %A Kalhan, Ravi %A Redline, Susan %A Gharib, Sina A %A Meyers, Deborah %A Ortega, Victor %A Dupuis, Josée %A London, Stephanie J %A Lappalainen, Tuuli %A Oelsner, Elizabeth C %A Silverman, Edwin K %A Barr, R Graham %A Thornton, Timothy A %A Wheeler, Heather E %A Cho, Michael H %A Im, Hae Kyung %A Manichaikul, Ani %K Humans %K Lung %K National Heart, Lung, and Blood Institute (U.S.) %K Pulmonary Disease, Chronic Obstructive %K Risk Factors %K Transcriptome %K United States %XWhile polygenic risk scores (PRSs) enable early identification of genetic risk for chronic obstructive pulmonary disease (COPD), predictive performance is limited when the discovery and target populations are not well matched. Hypothesizing that the biological mechanisms of disease are shared across ancestry groups, we introduce a PrediXcan-derived polygenic transcriptome risk score (PTRS) to improve cross-ethnic portability of risk prediction. We constructed the PTRS using summary statistics from application of PrediXcan on large-scale GWASs of lung function (forced expiratory volume in 1 s [FEV] and its ratio to forced vital capacity [FEV/FVC]) in the UK Biobank. We examined prediction performance and cross-ethnic portability of PTRS through smoking-stratified analyses both on 29,381 multi-ethnic participants from TOPMed population/family-based cohorts and on 11,771 multi-ethnic participants from TOPMed COPD-enriched studies. Analyses were carried out for two dichotomous COPD traits (moderate-to-severe and severe COPD) and two quantitative lung function traits (FEV and FEV/FVC). While the proposed PTRS showed weaker associations with disease than PRS for European ancestry, the PTRS showed stronger association with COPD than PRS for African Americans (e.g., odds ratio [OR] = 1.24 [95% confidence interval [CI]: 1.08-1.43] for PTRS versus 1.10 [0.96-1.26] for PRS among heavy smokers with ≥ 40 pack-years of smoking) for moderate-to-severe COPD. Cross-ethnic portability of the PTRS was significantly higher than the PRS (paired t test p < 2.2 × 10 with portability gains ranging from 5% to 28%) for both dichotomous COPD traits and across all smoking strata. Our study demonstrates the value of PTRS for improved cross-ethnic portability compared to PRS in predicting COPD risk.
%B Am J Hum Genet %V 109 %P 857-870 %8 2022 May 05 %G eng %N 5 %1 https://www.ncbi.nlm.nih.gov/pubmed/35385699?dopt=Abstract %R 10.1016/j.ajhg.2022.03.007 %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 %XLarge-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 %XBACKGROUND: 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 Am J Respir Crit Care Med %D 2022 %T Targeted Genome Sequencing Identifies Multiple Rare Variants in Caveolin-1 Associated with Obstructive Sleep Apnea. %A Liang, Jingjing %A Wang, Heming %A Cade, Brian E %A Kurniansyah, Nuzulul %A He, Karen Y %A Lee, Jiwon %A Sands, Scott A %A A Brody, Jennifer %A Chen, Han %A Gottlieb, Daniel J %A Evans, Daniel S %A Guo, Xiuqing %A Gharib, Sina A %A Hale, Lauren %A Hillman, David R %A Lutsey, Pamela L %A Mukherjee, Sutapa %A Ochs-Balcom, Heather M %A Palmer, Lyle J %A Purcell, Shaun %A Saxena, Richa %A Patel, Sanjay R %A Stone, Katie L %A Tranah, Gregory J %A Eric Boerwinkle %A Lin, Xihong %A Liu, Yongmei %A Psaty, Bruce M %A Vasan, Ramachandran S %A Manichaikul, Ani %A Rich, Stephen S %A Rotter, Jerome I %A Sofer, Tamar %A Redline, Susan %A Zhu, Xiaofeng %K Caveolin 1 %K High-Throughput Nucleotide Sequencing %K Humans %K Sequence Analysis, DNA %K Sleep Apnea, Obstructive %XObstructive sleep apnea (OSA) is a common disorder associated with increased risk for cardiovascular disease, diabetes, and premature mortality. There is strong clinical and epidemiologic evidence supporting the importance of genetic factors influencing OSA but limited data implicating specific genes. To search for rare variants contributing to OSA severity. Leveraging high-depth genomic sequencing data from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and imputed genotype data from multiple population-based studies, we performed linkage analysis in the CFS (Cleveland Family Study), followed by multistage gene-based association analyses in independent cohorts for apnea-hypopnea index (AHI) in a total of 7,708 individuals of European ancestry. Linkage analysis in the CFS identified a suggestive linkage peak on chromosome 7q31 (LOD = 2.31). Gene-based analysis identified 21 noncoding rare variants in (Caveolin-1) associated with lower AHI after accounting for multiple comparisons ( = 7.4 × 10). These noncoding variants together significantly contributed to the linkage evidence ( < 10). Follow-up analysis revealed significant associations between these variants and increased expression, and increased expression in peripheral monocytes was associated with lower AHI ( = 0.024) and higher minimum overnight oxygen saturation ( = 0.007). Rare variants in , a membrane-scaffolding protein essential in multiple cellular and metabolic functions, are associated with higher gene expression and lower OSA severity, suggesting a novel target for modulating OSA severity.
%B Am J Respir Crit Care Med %V 206 %P 1271-1280 %8 2022 Nov 15 %G eng %N 10 %1 https://www.ncbi.nlm.nih.gov/pubmed/35822943?dopt=Abstract %R 10.1164/rccm.202203-0618OC %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 %XPolygenic 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 %XBlood 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 Cell Genom %D 2021 %T Association of mitochondrial DNA copy number with cardiometabolic diseases. %A Liu, Xue %A Longchamps, Ryan J %A Wiggins, Kerri L %A Raffield, Laura M %A Bielak, Lawrence F %A Zhao, Wei %A Pitsillides, Achilleas %A Blackwell, Thomas W %A Yao, Jie %A Guo, Xiuqing %A Kurniansyah, Nuzulul %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 Cupples, L Adrienne %A Eric Boerwinkle %A Grove, Megan L %A Larson, Nicholas B %A Smith, Jennifer A %A Vasan, Ramachandran S %A Sofer, Tamar %A Fitzpatrick, Annette L %A Fornage, Myriam %A Ding, Jun %A Correa, Adolfo %A Abecasis, Goncalo %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 %XMitochondrial DNA (mtDNA) is present in multiple copies in human cells. We evaluated cross-sectional associations of whole blood mtDNA copy number (CN) with several cardiometabolic disease traits in 408,361 participants of multiple ancestries in TOPMed and UK Biobank. Age showed a threshold association with mtDNA CN: among younger participants (<65 years of age), each additional 10 years of age was associated with 0.03 standard deviation (s.d.) higher level of mtDNA CN ( = 0.0014) versus a 0.14 s.d. lower level of mtDNA CN ( = 1.82 × 10) among older participants (≥65 years). At lower mtDNA CN levels, we found age-independent associations with increased odds of obesity ( = 5.6 × 10), hypertension ( = 2.8 × 10), diabetes ( = 3.6 × 10), and hyperlipidemia ( = 6.3 × 10). The observed decline in mtDNA CN after 65 years of age may be a key to understanding age-related diseases.
%B Cell Genom %V 1 %8 2021 Oct 13 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/35036986?dopt=Abstract %R 10.1016/j.xgen.2021.100006 %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 %XWhole-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 %XAutosomal 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 Nat Commun %D 2021 %T Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes. %A Goodrich, Julia K %A Singer-Berk, Moriel %A Son, Rachel %A Sveden, Abigail %A Wood, Jordan %A England, Eleina %A Cole, Joanne B %A Weisburd, Ben %A Watts, Nick %A Caulkins, Lizz %A Dornbos, Peter %A Koesterer, Ryan %A Zappala, Zachary %A Zhang, Haichen %A Maloney, Kristin A %A Dahl, Andy %A Aguilar-Salinas, Carlos A %A Atzmon, Gil %A Barajas-Olmos, Francisco %A Barzilai, Nir %A Blangero, John %A Eric Boerwinkle %A Bonnycastle, Lori L %A Bottinger, Erwin %A Bowden, Donald W %A Centeno-Cruz, Federico %A Chambers, John C %A Chami, Nathalie %A Chan, Edmund %A Chan, Juliana %A Cheng, Ching-Yu %A Cho, Yoon Shin %A Contreras-Cubas, Cecilia %A Córdova, Emilio %A Correa, Adolfo %A DeFronzo, Ralph A %A Duggirala, Ravindranath %A Dupuis, Josée %A Garay-Sevilla, Ma Eugenia %A García-Ortiz, Humberto %A Gieger, Christian %A Glaser, Benjamin %A González-Villalpando, Clicerio %A Gonzalez, Ma Elena %A Grarup, Niels %A Groop, Leif %A Gross, Myron %A Haiman, Christopher %A Han, Sohee %A Hanis, Craig L %A Hansen, Torben %A Heard-Costa, Nancy L %A Henderson, Brian E %A Hernandez, Juan Manuel Malacara %A Hwang, Mi Yeong %A Islas-Andrade, Sergio %A Jørgensen, Marit E %A Kang, Hyun Min %A Kim, Bong-Jo %A Kim, Young Jin %A Koistinen, Heikki A %A Kooner, Jaspal Singh %A Kuusisto, Johanna %A Kwak, Soo-Heon %A Laakso, Markku %A Lange, Leslie %A Lee, Jong-Young %A Lee, Juyoung %A Lehman, Donna M %A Linneberg, Allan %A Liu, Jianjun %A Loos, Ruth J F %A Lyssenko, Valeriya %A Ma, Ronald C W %A Martínez-Hernández, Angélica %A Meigs, James B %A Meitinger, Thomas %A Mendoza-Caamal, Elvia %A Mohlke, Karen L %A Morris, Andrew D %A Morrison, Alanna C %A Ng, Maggie C Y %A Nilsson, Peter M %A O'Donnell, Christopher J %A Orozco, Lorena %A Palmer, Colin N A %A Park, Kyong Soo %A Post, Wendy S %A Pedersen, Oluf %A Preuss, Michael %A Psaty, Bruce M %A Reiner, Alexander P %A Revilla-Monsalve, Cristina %A Rich, Stephen S %A Rotter, Jerome I %A Saleheen, Danish %A Schurmann, Claudia %A Sim, Xueling %A Sladek, Rob %A Small, Kerrin S %A So, Wing Yee %A Spector, Timothy D %A Strauch, Konstantin %A Strom, Tim M %A Tai, E Shyong %A Tam, Claudia H T %A Teo, Yik Ying %A Thameem, Farook %A Tomlinson, Brian %A Tracy, Russell P %A Tuomi, Tiinamaija %A Tuomilehto, Jaakko %A Tusie-Luna, Teresa %A van Dam, Rob M %A Vasan, Ramachandran S %A Wilson, James G %A Witte, Daniel R %A Wong, Tien-Yin %A Burtt, Noël P %A Zaitlen, Noah %A McCarthy, Mark I %A Boehnke, Michael %A Pollin, Toni I %A Flannick, Jason %A Mercader, Josep M %A O'Donnell-Luria, Anne %A Baxter, Samantha %A Florez, Jose C %A MacArthur, Daniel G %A Udler, Miriam S %K Adult %K Biological Variation, Population %K Biomarkers %K Diabetes Mellitus, Type 2 %K Dyslipidemias %K Exome %K Genetic Predisposition to Disease %K Genotype %K Humans %K Multifactorial Inheritance %K Penetrance %K Risk Assessment %XHundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias.
%B Nat Commun %V 12 %P 3505 %8 2021 Jun 09 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/34108472?dopt=Abstract %R 10.1038/s41467-021-23556-4 %0 Journal Article %J Science %D 2021 %T Population sequencing data reveal a compendium of mutational processes in the human germ line. %A Seplyarskiy, Vladimir B %A Soldatov, Ruslan A %A Koch, Evan %A McGinty, Ryan J %A Goldmann, Jakob M %A Hernandez, Ryan D %A Barnes, Kathleen %A Correa, Adolfo %A Burchard, Esteban G %A Ellinor, Patrick T %A McGarvey, Stephen T %A Mitchell, Braxton D %A Vasan, Ramachandran S %A Redline, Susan %A Silverman, Edwin %A Weiss, Scott T %A Arnett, Donna K %A Blangero, John %A Eric Boerwinkle %A He, Jiang %A Montgomery, Courtney %A Rao, D C %A Rotter, Jerome I %A Taylor, Kent D %A Brody, Jennifer A %A Chen, Yii-Der Ida %A de Las Fuentes, Lisa %A Hwu, Chii-Min %A Rich, Stephen S %A Manichaikul, Ani W %A Mychaleckyj, Josyf C %A Palmer, Nicholette D %A Smith, Jennifer A %A Kardia, Sharon L R %A Peyser, Patricia A %A Bielak, Lawrence F %A O'Connor, Timothy D %A Emery, Leslie S %A Gilissen, Christian %A Wong, Wendy S W %A Kharchenko, Peter V %A Sunyaev, Shamil %K Algorithms %K CpG Islands %K DNA Damage %K DNA Demethylation %K DNA Mutational Analysis %K DNA Replication %K Genetic Variation %K Genome, Human %K Germ Cells %K Germ-Line Mutation %K Humans %K Long Interspersed Nucleotide Elements %K Mutagenesis %K Oocytes %K Transcription, Genetic %XBiological mechanisms underlying human germline mutations remain largely unknown. We statistically decompose variation in the rate and spectra of mutations along the genome using volume-regularized nonnegative matrix factorization. The analysis of a sequencing dataset (TOPMed) reveals nine processes that explain the variation in mutation properties between loci. We provide a biological interpretation for seven of these processes. We associate one process with bulky DNA lesions that are resolved asymmetrically with respect to transcription and replication. Two processes track direction of replication fork and replication timing, respectively. We identify a mutagenic effect of active demethylation primarily acting in regulatory regions and a mutagenic effect of long interspersed nuclear elements. We localize a mutagenic process specific to oocytes from population sequencing data. This process appears transcriptionally asymmetric.
%B Science %V 373 %P 1030-1035 %8 2021 Aug 27 %G eng %N 6558 %1 https://www.ncbi.nlm.nih.gov/pubmed/34385354?dopt=Abstract %R 10.1126/science.aba7408 %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 %XThe 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 %XBACKGROUND: 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 Genome Med %D 2021 %T Whole-genome association analyses of sleep-disordered breathing phenotypes in the NHLBI TOPMed program. %A Cade, Brian E %A Lee, Jiwon %A Sofer, Tamar %A Wang, Heming %A Zhang, Man %A Chen, Han %A Gharib, Sina A %A Gottlieb, Daniel J %A Guo, Xiuqing %A Lane, Jacqueline M %A Liang, Jingjing %A Lin, Xihong %A Mei, Hao %A Patel, Sanjay R %A Purcell, Shaun M %A Saxena, Richa %A Shah, Neomi A %A Evans, Daniel S %A Hanis, Craig L %A Hillman, David R %A Mukherjee, Sutapa %A Palmer, Lyle J %A Stone, Katie L %A Tranah, Gregory J %A Abecasis, Gonçalo R %A Eric Boerwinkle %A Correa, Adolfo %A Cupples, L Adrienne %A Kaplan, Robert C %A Nickerson, Deborah A %A North, Kari E %A Psaty, Bruce M %A Rotter, Jerome I %A Rich, Stephen S %A Tracy, Russell P %A Vasan, Ramachandran S %A Wilson, James G %A Zhu, Xiaofeng %A Redline, Susan %K Alleles %K Chromatin Immunoprecipitation Sequencing %K Female %K Gene Expression Regulation %K Genetic Association Studies %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Genotype %K Humans %K Male %K National Heart, Lung, and Blood Institute (U.S.) %K Phenotype %K Precision Medicine %K Research %K Signal Transduction %K Sleep Apnea Syndromes %K United States %K Whole Genome Sequencing %XBACKGROUND: Sleep-disordered breathing is a common disorder associated with significant morbidity. The genetic architecture of sleep-disordered breathing remains poorly understood. Through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, we performed the first whole-genome sequence analysis of sleep-disordered breathing.
METHODS: The study sample was comprised of 7988 individuals of diverse ancestry. Common-variant and pathway analyses included an additional 13,257 individuals. We examined five complementary traits describing different aspects of sleep-disordered breathing: the apnea-hypopnea index, average oxyhemoglobin desaturation per event, average and minimum oxyhemoglobin saturation across the sleep episode, and the percentage of sleep with oxyhemoglobin saturation < 90%. We adjusted for age, sex, BMI, study, and family structure using MMSKAT and EMMAX mixed linear model approaches. Additional bioinformatics analyses were performed with MetaXcan, GIGSEA, and ReMap.
RESULTS: We identified a multi-ethnic set-based rare-variant association (p = 3.48 × 10) on chromosome X with ARMCX3. Additional rare-variant associations include ARMCX3-AS1, MRPS33, and C16orf90. Novel common-variant loci were identified in the NRG1 and SLC45A2 regions, and previously associated loci in the IL18RAP and ATP2B4 regions were associated with novel phenotypes. Transcription factor binding site enrichment identified associations with genes implicated with respiratory and craniofacial traits. Additional analyses identified significantly associated pathways.
CONCLUSIONS: We have identified the first gene-based rare-variant associations with objectively measured sleep-disordered breathing traits. Our results increase the understanding of the genetic architecture of sleep-disordered breathing and highlight associations in genes that modulate lung development, inflammation, respiratory rhythmogenesis, and HIF1A-mediated hypoxic response.
%B Genome Med %V 13 %P 136 %8 2021 Aug 26 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/34446064?dopt=Abstract %R 10.1186/s13073-021-00917-8 %0 Journal Article %J Nat Genet %D 2020 %T Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale. %A Li, Xihao %A Li, Zilin %A Zhou, Hufeng %A Gaynor, Sheila M %A Liu, Yaowu %A Chen, Han %A Sun, Ryan %A Dey, Rounak %A Arnett, Donna K %A Aslibekyan, Stella %A Ballantyne, Christie M %A Bielak, Lawrence F %A Blangero, John %A Eric Boerwinkle %A Bowden, Donald W %A Broome, Jai G %A Conomos, Matthew P %A Correa, Adolfo %A Cupples, L Adrienne %A Curran, Joanne E %A Freedman, Barry I %A Guo, Xiuqing %A Hindy, George %A Irvin, Marguerite R %A Kardia, Sharon L R %A Kathiresan, Sekar %A Khan, Alyna T %A Kooperberg, Charles L %A Laurie, Cathy C %A Liu, X Shirley %A Mahaney, Michael C %A Manichaikul, Ani W %A Martin, Lisa W %A Mathias, Rasika A %A McGarvey, Stephen T %A Mitchell, Braxton D %A Montasser, May E %A Moore, Jill E %A Morrison, Alanna C %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Pampana, Akhil %A Peralta, Juan M %A Peyser, Patricia A %A Psaty, Bruce M %A Redline, Susan %A Rice, Kenneth M %A Rich, Stephen S %A Smith, Jennifer A %A Tiwari, Hemant K %A Tsai, Michael Y %A Vasan, Ramachandran S %A Wang, Fei Fei %A Weeks, Daniel E %A Weng, Zhiping %A Wilson, James G %A Yanek, Lisa R %A Neale, Benjamin M %A Sunyaev, Shamil R %A Abecasis, Gonçalo R %A Rotter, Jerome I %A Willer, Cristen J %A Peloso, Gina M %A Natarajan, Pradeep %A Lin, Xihong %K Cholesterol, LDL %K Computer Simulation %K Genetic Predisposition to Disease %K Genetic Variation %K Genome %K Genome-Wide Association Study %K Humans %K Models, Genetic %K Molecular Sequence Annotation %K Phenotype %K Whole Genome Sequencing %XLarge-scale whole-genome sequencing studies have enabled the analysis of rare variants (RVs) associated with complex phenotypes. Commonly used RV association tests have limited scope to leverage variant functions. We propose STAAR (variant-set test for association using annotation information), a scalable and powerful RV association test method that effectively incorporates both variant categories and multiple complementary annotations using a dynamic weighting scheme. For the latter, we introduce 'annotation principal components', multidimensional summaries of in silico variant annotations. STAAR accounts for population structure and relatedness and is scalable for analyzing very large cohort and biobank whole-genome sequencing studies of continuous and dichotomous traits. We applied STAAR to identify RVs associated with four lipid traits in 12,316 discovery and 17,822 replication samples from the Trans-Omics for Precision Medicine Program. We discovered and replicated new RV associations, including disruptive missense RVs of NPC1L1 and an intergenic region near APOC1P1 associated with low-density lipoprotein cholesterol.
%B Nat Genet %V 52 %P 969-983 %8 2020 Sep %G eng %N 9 %1 https://www.ncbi.nlm.nih.gov/pubmed/32839606?dopt=Abstract %R 10.1038/s41588-020-0676-4 %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 %XAge 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 Nat Commun %D 2020 %T Whole genome sequence analysis of pulmonary function and COPD in 19,996 multi-ethnic participants. %A Zhao, Xutong %A Qiao, Dandi %A Yang, Chaojie %A Kasela, Silva %A Kim, Wonji %A Ma, Yanlin %A Shrine, Nick %A Batini, Chiara %A Sofer, Tamar %A Taliun, Sarah A Gagliano %A Sakornsakolpat, Phuwanat %A Balte, Pallavi P %A Prokopenko, Dmitry %A Yu, Bing %A Lange, Leslie A %A Dupuis, Josée %A Cade, Brian E %A Lee, Jiwon %A Gharib, Sina A %A Daya, Michelle %A Laurie, Cecelia A %A Ruczinski, Ingo %A Cupples, L Adrienne %A Loehr, Laura R %A Bartz, Traci M %A Morrison, Alanna C %A Psaty, Bruce M %A Vasan, Ramachandran S %A Wilson, James G %A Taylor, Kent D %A Durda, Peter %A Johnson, W Craig %A Cornell, Elaine %A Guo, Xiuqing %A Liu, Yongmei %A Tracy, Russell P %A Ardlie, Kristin G %A Aguet, Francois %A VanDenBerg, David J %A Papanicolaou, George J %A Rotter, Jerome I %A Barnes, Kathleen C %A Jain, Deepti %A Nickerson, Deborah A %A Donna M Muzny %A Ginger A Metcalf %A Harshavardhan Doddapaneni %A Dugan-Perez, Shannon %A Gupta, Namrata %A Gabriel, Stacey %A Rich, Stephen S %A O'Connor, George T %A Redline, Susan %A Reed, Robert M %A Laurie, Cathy C %A Daviglus, Martha L %A Preudhomme, Liana K %A Burkart, Kristin M %A Kaplan, Robert C %A Wain, Louise V %A Tobin, Martin D %A London, Stephanie J %A Lappalainen, Tuuli %A Oelsner, Elizabeth C %A Abecasis, Gonçalo R %A Silverman, Edwin K %A Barr, R Graham %A Cho, Michael H %A Manichaikul, Ani %K Adult %K Aged %K Aged, 80 and over %K Alpha-Ketoglutarate-Dependent Dioxygenase FTO %K Black or African American %K Calcium-Binding Proteins %K Feasibility Studies %K Female %K Follow-Up Studies %K Genetic Loci %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Intracellular Signaling Peptides and Proteins %K Lung %K Male %K Middle Aged %K Polymorphism, Single Nucleotide %K Protein Inhibitors of Activated STAT %K Pulmonary Disease, Chronic Obstructive %K Respiratory Physiological Phenomena %K Small Ubiquitin-Related Modifier Proteins %K Whole Genome Sequencing %XChronic obstructive pulmonary disease (COPD), diagnosed by reduced lung function, is a leading cause of morbidity and mortality. We performed whole genome sequence (WGS) analysis of lung function and COPD in a multi-ethnic sample of 11,497 participants from population- and family-based studies, and 8499 individuals from COPD-enriched studies in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program. We identify at genome-wide significance 10 known GWAS loci and 22 distinct, previously unreported loci, including two common variant signals from stratified analysis of African Americans. Four novel common variants within the regions of PIAS1, RGN (two variants) and FTO show evidence of replication in the UK Biobank (European ancestry n ~ 320,000), while colocalization analyses leveraging multi-omic data from GTEx and TOPMed identify potential molecular mechanisms underlying four of the 22 novel loci. Our study demonstrates the value of performing WGS analyses and multi-omic follow-up in cohorts of diverse ancestry.
%B Nat Commun %V 11 %P 5182 %8 2020 Oct 14 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/33057025?dopt=Abstract %R 10.1038/s41467-020-18334-7 %0 Journal Article %J Am J Epidemiol %D 2019 %T The Consortium of Metabolomics Studies (COMETS): Metabolomics in 47 Prospective Cohort Studies. %A Yu, Bing %A Zanetti, Krista A %A Temprosa, Marinella %A Albanes, Demetrius %A Appel, Nathan %A Barrera, Clara Barrios %A Ben-Shlomo, Yoav %A Eric Boerwinkle %A Casas, Juan P %A Clish, Clary %A Dale, Caroline %A Dehghan, Abbas %A Derkach, Andriy %A Eliassen, A Heather %A Elliott, Paul %A Fahy, Eoin %A Gieger, Christian %A Gunter, Marc J %A Harada, Sei %A Harris, Tamara %A Herr, Deron R %A Herrington, David %A Hirschhorn, Joel N %A Hoover, Elise %A Hsing, Ann W %A Johansson, Mattias %A Kelly, Rachel S %A Khoo, Chin Meng %A Kivimaki, Mika %A Kristal, Bruce S %A Langenberg, Claudia %A Lasky-Su, Jessica %A Lawlor, Deborah A %A Lotta, Luca A %A Mangino, Massimo %A Le Marchand, Loïc %A Mathé, Ewy %A Matthews, Charles E %A Menni, Cristina %A Mucci, Lorelei A %A Murphy, Rachel %A Oresic, Matej %A Orwoll, Eric %A Ose, Jennifer %A Pereira, Alexandre C %A Playdon, Mary C %A Poston, Lucilla %A Price, Jackie %A Qi, Qibin %A Rexrode, Kathryn %A Risch, Adam %A Sampson, Joshua %A Seow, Wei Jie %A Sesso, Howard D %A Shah, Svati H %A Shu, Xiao-Ou %A Smith, Gordon C S %A Sovio, Ulla %A Stevens, Victoria L %A Stolzenberg-Solomon, Rachael %A Takebayashi, Toru %A Tillin, Therese %A Travis, Ruth %A Tzoulaki, Ioanna %A Ulrich, Cornelia M %A Vasan, Ramachandran S %A Verma, Mukesh %A Wang, Ying %A Wareham, Nick J %A Wong, Andrew %A Younes, Naji %A Zhao, Hua %A Zheng, Wei %A Moore, Steven C %K Adolescent %K Adult %K Aged %K Aged, 80 and over %K Biomarkers %K Body Mass Index %K Child %K Epidemiologic Methods %K Epidemiology %K Female %K Global Health %K Health Behavior %K Hematologic Tests %K Humans %K Longitudinal Studies %K Male %K Metabolomics %K Middle Aged %K Prospective Studies %K Socioeconomic Factors %K Young Adult %XThe Consortium of Metabolomics Studies (COMETS) was established in 2014 to facilitate large-scale collaborative research on the human metabolome and its relationship with disease etiology, diagnosis, and prognosis. COMETS comprises 47 cohorts from Asia, Europe, North America, and South America that together include more than 136,000 participants with blood metabolomics data on samples collected from 1985 to 2017. Metabolomics data were provided by 17 different platforms, with the most frequently used labs being Metabolon, Inc. (14 cohorts), the Broad Institute (15 cohorts), and Nightingale Health (11 cohorts). Participants have been followed for a median of 23 years for health outcomes including death, cancer, cardiovascular disease, diabetes, and others; many of the studies are ongoing. Available exposure-related data include common clinical measurements and behavioral factors, as well as genome-wide genotype data. Two feasibility studies were conducted to evaluate the comparability of metabolomics platforms used by COMETS cohorts. The first study showed that the overlap between any 2 different laboratories ranged from 6 to 121 metabolites at 5 leading laboratories. The second study showed that the median Spearman correlation comparing 111 overlapping metabolites captured by Metabolon and the Broad Institute was 0.79 (interquartile range, 0.56-0.89).
%B Am J Epidemiol %V 188 %P 991-1012 %8 2019 Jun 01 %G eng %N 6 %1 https://www.ncbi.nlm.nih.gov/pubmed/31155658?dopt=Abstract %R 10.1093/aje/kwz028 %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 %XWith 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 Nature %D 2019 %T Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls. %A Flannick, Jason %A Mercader, Josep M %A Fuchsberger, Christian %A Udler, Miriam S %A Mahajan, Anubha %A Wessel, Jennifer %A Teslovich, Tanya M %A Caulkins, Lizz %A Koesterer, Ryan %A Barajas-Olmos, Francisco %A Blackwell, Thomas W %A Eric Boerwinkle %A Brody, Jennifer A %A Centeno-Cruz, Federico %A Chen, Ling %A Chen, Siying %A Contreras-Cubas, Cecilia %A Córdova, Emilio %A Correa, Adolfo %A Cortes, Maria %A DeFronzo, Ralph A %A Dolan, Lawrence %A Drews, Kimberly L %A Elliott, Amanda %A Floyd, James S %A Gabriel, Stacey %A Garay-Sevilla, Maria Eugenia %A García-Ortiz, Humberto %A Gross, Myron %A Han, Sohee %A Heard-Costa, Nancy L %A Jackson, Anne U %A Jørgensen, Marit E %A Kang, Hyun Min %A Kelsey, Megan %A Kim, Bong-Jo %A Koistinen, Heikki A %A Kuusisto, Johanna %A Leader, Joseph B %A Linneberg, Allan %A Liu, Ching-Ti %A Liu, Jianjun %A Lyssenko, Valeriya %A Manning, Alisa K %A Marcketta, Anthony %A Malacara-Hernandez, Juan Manuel %A Martínez-Hernández, Angélica %A Matsuo, Karen %A Mayer-Davis, Elizabeth %A Mendoza-Caamal, Elvia %A Mohlke, Karen L %A Morrison, Alanna C %A Ndungu, Anne %A Ng, Maggie C Y %A O'Dushlaine, Colm %A Payne, Anthony J %A Pihoker, Catherine %A Post, Wendy S %A Preuss, Michael %A Psaty, Bruce M %A Vasan, Ramachandran S %A Rayner, N William %A Reiner, Alexander P %A Revilla-Monsalve, Cristina %A Robertson, Neil R %A Santoro, Nicola %A Schurmann, Claudia %A So, Wing Yee %A Soberón, Xavier %A Stringham, Heather M %A Strom, Tim M %A Tam, Claudia H T %A Thameem, Farook %A Tomlinson, Brian %A Torres, Jason M %A Tracy, Russell P %A van Dam, Rob M %A Vujkovic, Marijana %A Wang, Shuai %A Welch, Ryan P %A Witte, Daniel R %A Wong, Tien-Yin %A Atzmon, Gil %A Barzilai, Nir %A Blangero, John %A Bonnycastle, Lori L %A Bowden, Donald W %A Chambers, John C %A Chan, Edmund %A Cheng, Ching-Yu %A Cho, Yoon Shin %A Collins, Francis S %A de Vries, Paul S %A Duggirala, Ravindranath %A Glaser, Benjamin %A Gonzalez, Clicerio %A Gonzalez, Ma Elena %A Groop, Leif %A Kooner, Jaspal Singh %A Kwak, Soo Heon %A Laakso, Markku %A Lehman, Donna M %A Nilsson, Peter %A Spector, Timothy D %A Tai, E Shyong %A Tuomi, Tiinamaija %A Tuomilehto, Jaakko %A Wilson, James G %A Aguilar-Salinas, Carlos A %A Bottinger, Erwin %A Burke, Brian %A Carey, David J %A Chan, Juliana C N %A Dupuis, Josée %A Frossard, Philippe %A Heckbert, Susan R %A Hwang, Mi Yeong %A Kim, Young Jin %A Kirchner, H Lester %A Lee, Jong-Young %A Lee, Juyoung %A Loos, Ruth J F %A Ma, Ronald C W %A Morris, Andrew D %A O'Donnell, Christopher J %A Palmer, Colin N A %A Pankow, James %A Park, Kyong Soo %A Rasheed, Asif %A Saleheen, Danish %A Sim, Xueling %A Small, Kerrin S %A Teo, Yik Ying %A Haiman, Christopher %A Hanis, Craig L %A Henderson, Brian E %A Orozco, Lorena %A Tusie-Luna, Teresa %A Dewey, Frederick E %A Baras, Aris %A Gieger, Christian %A Meitinger, Thomas %A Strauch, Konstantin %A Lange, Leslie %A Grarup, Niels %A Hansen, Torben %A Pedersen, Oluf %A Zeitler, Philip %A Dabelea, Dana %A Abecasis, Goncalo %A Bell, Graeme I %A Cox, Nancy J %A Seielstad, Mark %A Sladek, Rob %A Meigs, James B %A Rich, Steve S %A Rotter, Jerome I %A Altshuler, David %A Burtt, Noël P %A Scott, Laura J %A Morris, Andrew P %A Florez, Jose C %A McCarthy, Mark I %A Boehnke, Michael %K Animals %K Case-Control Studies %K Decision Support Techniques %K Diabetes Mellitus, Type 2 %K Exome %K Exome Sequencing %K Female %K Gene Frequency %K Genome-Wide Association Study %K Humans %K Male %K Mice %K Mice, Knockout %XProtein-coding genetic variants that strongly affect disease risk can yield relevant clues to disease pathogenesis. Here we report exome-sequencing analyses of 20,791 individuals with type 2 diabetes (T2D) and 24,440 non-diabetic control participants from 5 ancestries. We identify gene-level associations of rare variants (with minor allele frequencies of less than 0.5%) in 4 genes at exome-wide significance, including a series of more than 30 SLC30A8 alleles that conveys protection against T2D, and in 12 gene sets, including those corresponding to T2D drug targets (P = 6.1 × 10) and candidate genes from knockout mice (P = 5.2 × 10). Within our study, the strongest T2D gene-level signals for rare variants explain at most 25% of the heritability of the strongest common single-variant signals, and the gene-level effect sizes of the rare variants that we observed in established T2D drug targets will require 75,000-185,000 sequenced cases to achieve exome-wide significance. We propose a method to interpret these modest rare-variant associations and to incorporate these associations into future target or gene prioritization efforts.
%B Nature %V 570 %P 71-76 %8 2019 Jun %G eng %N 7759 %1 https://www.ncbi.nlm.nih.gov/pubmed/31118516?dopt=Abstract %R 10.1038/s41586-019-1231-2 %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 %XHemoglobin 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 %XIn 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 Hum Genet %D 2019 %T Sequencing Analysis at 8p23 Identifies Multiple Rare Variants in DLC1 Associated with Sleep-Related Oxyhemoglobin Saturation Level. %A Liang, Jingjing %A Cade, Brian E %A He, Karen Y %A Wang, Heming %A Lee, Jiwon %A Sofer, Tamar %A Williams, Stephanie %A Li, Ruitong %A Chen, Han %A Gottlieb, Daniel J %A Evans, Daniel S %A Guo, Xiuqing %A Gharib, Sina A %A Hale, Lauren %A Hillman, David R %A Lutsey, Pamela L %A Mukherjee, Sutapa %A Ochs-Balcom, Heather M %A Palmer, Lyle J %A Rhodes, Jessica %A Purcell, Shaun %A Patel, Sanjay R %A Saxena, Richa %A Stone, Katie L %A Tang, Weihong %A Tranah, Gregory J %A Eric Boerwinkle %A Lin, Xihong %A Liu, Yongmei %A Psaty, Bruce M %A Vasan, Ramachandran S %A Cho, Michael H %A Manichaikul, Ani %A Silverman, Edwin K %A Barr, R Graham %A Rich, Stephen S %A Rotter, Jerome I %A Wilson, James G %A Redline, Susan %A Zhu, Xiaofeng %K Chromosomes, Human, Pair 8 %K Genetic Linkage %K Genome-Wide Association Study %K GTPase-Activating Proteins %K Humans %K Oxyhemoglobins %K Sleep %K Tumor Suppressor Proteins %K Whole Genome Sequencing %XAverage arterial oxyhemoglobin saturation during sleep (AvSpOS) is a clinically relevant measure of physiological stress associated with sleep-disordered breathing, and this measure predicts incident cardiovascular disease and mortality. Using high-depth whole-genome sequencing data from the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) project and focusing on genes with linkage evidence on chromosome 8p23, we observed that six coding and 51 noncoding variants in a gene that encodes the GTPase-activating protein (DLC1) are significantly associated with AvSpOS and replicated in independent subjects. The combined DLC1 association evidence of discovery and replication cohorts reaches genome-wide significance in European Americans (p = 7.9 × 10). A risk score for these variants, built on an independent dataset, explains 0.97% of the AvSpOS variation and contributes to the linkage evidence. The 51 noncoding variants are enriched in regulatory features in a human lung fibroblast cell line and contribute to DLC1 expression variation. Mendelian randomization analysis using these variants indicates a significant causal effect of DLC1 expression in fibroblasts on AvSpOS. Multiple sources of information, including genetic variants, gene expression, and methylation, consistently suggest that DLC1 is a gene associated with AvSpOS.
%B Am J Hum Genet %V 105 %P 1057-1068 %8 2019 Nov 07 %G eng %N 5 %1 https://www.ncbi.nlm.nih.gov/pubmed/31668705?dopt=Abstract %R 10.1016/j.ajhg.2019.10.002 %0 Journal Article %J Nat Genet %D 2017 %T Analysis commons, a team approach to discovery in a big-data environment for genetic epidemiology. %A Brody, Jennifer A %A Morrison, Alanna C %A Bis, Joshua C %A O'Connell, Jeffrey R %A Brown, Michael R %A Huffman, Jennifer E %A Ames, Darren C %A Carroll, Andrew %A Conomos, Matthew P %A Gabriel, Stacey %A Richard A Gibbs %A Gogarten, Stephanie M %A Gupta, Namrata %A Jaquish, Cashell E %A Johnson, Andrew D %A Lewis, Joshua P %A Liu, Xiaoming %A Manning, Alisa K %A Papanicolaou, George J %A Pitsillides, Achilleas N %A Rice, Kenneth M %A Salerno, William %A Sitlani, Colleen M %A Smith, Nicholas L %A Heckbert, Susan R %A Laurie, Cathy C %A Mitchell, Braxton D %A Vasan, Ramachandran S %A Rich, Stephen S %A Rotter, Jerome I %A Wilson, James G %A Eric Boerwinkle %A Psaty, Bruce M %A Cupples, L Adrienne %K big data %K Fibrinogen %K Genetics, Population %K Genome %K Humans %K Information Dissemination %K Mobile Applications %K Molecular Epidemiology %K Regression Analysis %K Software %K Workflow %XThe exploding volume of whole-genome sequence (WGS) and multi-omics data requires new approaches for analysis. As one solution, we have created a cloud-based Analysis Commons, which brings together genotype and phenotype data from multiple studies in a setting that is accessible by multiple investigators. This framework addresses many of the challenges of multi-center WGS analyses, including data sharing mechanisms, phenotype harmonization, integrated multi-omics analyses, annotation, and computational flexibility. In this setting, the computational pipeline facilitates a sequence-to-discovery analysis workflow illustrated here by an analysis of plasma fibrinogen levels in 3996 individuals from the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) WGS program. The Analysis Commons represents a novel model for transforming WGS resources from a massive quantity of phenotypic and genomic data into knowledge of the determinants of health and disease risk in diverse human populations.
%B Nat Genet %V 49 %P 1560-1563 %8 2017 Oct 27 %G eng %N 11 %1 https://www.ncbi.nlm.nih.gov/pubmed/29074945?dopt=Abstract %R 10.1038/ng.3968 %0 Journal Article %J Eur J Hum Genet %D 2016 %T Association of the IGF1 gene with fasting insulin levels. %A Willems, Sara M %A Cornes, Belinda K %A Brody, Jennifer A %A Morrison, Alanna C %A Lipovich, Leonard %A Dauriz, Marco %A Chen, Yuning %A Liu, Ching-Ti %A Rybin, Denis V %A Richard A Gibbs %A Donna M Muzny %A Pankow, James S %A Psaty, Bruce M %A Eric Boerwinkle %A Rotter, Jerome I %A Siscovick, David S %A Vasan, Ramachandran S %A Kaplan, Robert C %A Isaacs, Aaron %A Dupuis, Josée %A van Duijn, Cornelia M %A Meigs, James B %K Adult %K Aged %K Fasting %K Female %K Humans %K Insulin %K Insulin-Like Growth Factor I %K Male %K Middle Aged %K Polymorphism, Single Nucleotide %XInsulin-like growth factor 1 (IGF-I) has been associated with insulin resistance. Genome-wide association studies (GWASs) of fasting insulin (FI) identified single-nucleotide variants (SNVs) near the IGF1 gene, raising two hypotheses: (1) these associations are mediated by IGF-I levels and (2) these noncoding variants either tag other functional variants in the region or are directly functional. In our study, analyses including 5141 individuals from population-based cohorts suggest that FI associations near IGF1 are not mediated by IGF-I. Analyses of targeted sequencing data in 3539 individuals reveal a large number of novel rare variants at the IGF1 locus and show a FI association with a subset of rare nonsynonymous variants (PSKAT=5.7 × 10(-4)). Conditional analyses suggest that this association is partly explained by the GWAS signal and the presence of a residual independent rare variant effect (Pconditional=0.019). Annotation using ENCODE data suggests that the GWAS variants may have a direct functional role in insulin biology. In conclusion, our study provides insight into variation present at the IGF1 locus and into the genetic architecture underlying FI levels, suggesting that FI associations of SNVs near IGF1 are not mediated by IGF-I and suggesting a role for both rare nonsynonymous and common functional variants in insulin biology.
%B Eur J Hum Genet %V 24 %P 1337-43 %8 2016 Aug %G eng %N 9 %1 https://www.ncbi.nlm.nih.gov/pubmed/26860063?dopt=Abstract %R 10.1038/ejhg.2016.4 %0 Journal Article %J PLoS Genet %D 2016 %T Discovery of Genetic Variation on Chromosome 5q22 Associated with Mortality in Heart Failure. %A Smith, J Gustav %A Felix, Janine F %A Morrison, Alanna C %A Kalogeropoulos, Andreas %A Trompet, Stella %A Wilk, Jemma B %A Gidlöf, Olof %A Wang, Xinchen %A Morley, Michael %A Mendelson, Michael %A Joehanes, Roby %A Ligthart, Symen %A Shan, Xiaoyin %A Bis, Joshua C %A Wang, Ying A %A Sjögren, Marketa %A Ngwa, Julius %A Brandimarto, Jeffrey %A Stott, David J %A Aguilar, David %A Rice, Kenneth M %A Sesso, Howard D %A Demissie, Serkalem %A Buckley, Brendan M %A Taylor, Kent D %A Ford, Ian %A Yao, Chen %A Liu, Chunyu %A Sotoodehnia, Nona %A van der Harst, Pim %A Stricker, Bruno H Ch %A Kritchevsky, Stephen B %A Liu, Yongmei %A Gaziano, J Michael %A Hofman, Albert %A Moravec, Christine S %A Uitterlinden, André G %A Kellis, Manolis %A van Meurs, Joyce B %A Margulies, Kenneth B %A Dehghan, Abbas %A Levy, Daniel %A Olde, Björn %A Psaty, Bruce M %A Cupples, L Adrienne %A Jukema, J Wouter %A Djousse, Luc %A Franco, Oscar H %A Eric Boerwinkle %A Boyer, Laurie A %A Newton-Cheh, Christopher %A Butler, Javed %A Vasan, Ramachandran S %A Cappola, Thomas P %A Smith, Nicholas L %K Alleles %K Basic Helix-Loop-Helix Transcription Factors %K Black or African American %K Chromosomes, Human, Pair 5 %K DNA Methylation %K Female %K Gene Expression Regulation %K Gene Knockdown Techniques %K Genetic Predisposition to Disease %K Genetic Variation %K Genome-Wide Association Study %K Genotype %K Heart Failure %K HEK293 Cells %K Humans %K Male %K Middle Aged %K Polymorphism, Single Nucleotide %K Receptors, Cytokine %XFailure of the human heart to maintain sufficient output of blood for the demands of the body, heart failure, is a common condition with high mortality even with modern therapeutic alternatives. To identify molecular determinants of mortality in patients with new-onset heart failure, we performed a meta-analysis of genome-wide association studies and follow-up genotyping in independent populations. We identified and replicated an association for a genetic variant on chromosome 5q22 with 36% increased risk of death in subjects with heart failure (rs9885413, P = 2.7x10-9). We provide evidence from reporter gene assays, computational predictions and epigenomic marks that this polymorphism increases activity of an enhancer region active in multiple human tissues. The polymorphism was further reproducibly associated with a DNA methylation signature in whole blood (P = 4.5x10-40) that also associated with allergic sensitization and expression in blood of the cytokine TSLP (P = 1.1x10-4). Knockdown of the transcription factor predicted to bind the enhancer region (NHLH1) in a human cell line (HEK293) expressing NHLH1 resulted in lower TSLP expression. In addition, we observed evidence of recent positive selection acting on the risk allele in populations of African descent. Our findings provide novel genetic leads to factors that influence mortality in patients with heart failure.
%B PLoS Genet %V 12 %P e1006034 %8 2016 May %G eng %N 5 %1 https://www.ncbi.nlm.nih.gov/pubmed/27149122?dopt=Abstract %R 10.1371/journal.pgen.1006034 %0 Journal Article %J Nat Commun %D 2016 %T An exome array study of the plasma metabolome. %A Rhee, Eugene P %A Yang, Qiong %A Yu, Bing %A Liu, Xuan %A Cheng, Susan %A Deik, Amy %A Pierce, Kerry A %A Bullock, Kevin %A Ho, Jennifer E %A Levy, Daniel %A Florez, Jose C %A Kathiresan, Sek %A Larson, Martin G %A Vasan, Ramachandran S %A Clish, Clary B %A Wang, Thomas J %A Eric Boerwinkle %A O'Donnell, Christopher J %A Gerszten, Robert E %K Exome %K Female %K Gene Frequency %K Genome-Wide Association Study %K Humans %K Male %K Metabolome %K Middle Aged %K Plasma %K Polymorphism, Single Nucleotide %K Ribonucleosides %K Xanthines %XThe study of rare variants may enhance our understanding of the genetic determinants of the metabolome. Here, we analyze the association between 217 plasma metabolites and exome variants on the Illumina HumanExome Beadchip in 2,076 participants in the Framingham Heart Study, with replication in 1,528 participants of the Atherosclerosis Risk in Communities Study. We identify an association between GMPS and xanthosine using single variant analysis and associations between HAL and histidine, PAH and phenylalanine, and UPB1 and ureidopropionate using gene-based tests (P<5 × 10(-8) in meta-analysis), highlighting novel coding variants that may underlie inborn errors of metabolism. Further, we show how an examination of variants across the spectrum of allele frequency highlights independent association signals at select loci and generates a more integrated view of metabolite heritability. These studies build on prior metabolomics genome wide association studies to provide a more complete picture of the genetic architecture of the plasma metabolome.
%B Nat Commun %V 7 %P 12360 %8 2016 Jul 25 %G eng %1 https://www.ncbi.nlm.nih.gov/pubmed/27453504?dopt=Abstract %R 10.1038/ncomms12360 %0 Journal Article %J Circ Cardiovasc Genet %D 2010 %T Genomic variation associated with mortality among adults of European and African ancestry with heart failure: the cohorts for heart and aging research in genomic epidemiology consortium. %A Morrison, Alanna C %A Felix, Janine F %A Cupples, L Adrienne %A Glazer, Nicole L %A Loehr, Laura R %A Dehghan, Abbas %A Demissie, Serkalem %A Bis, Joshua C %A Rosamond, Wayne D %A Aulchenko, Yurii S %A Wang, Ying A %A Haritunians, Talin %A Folsom, Aaron R %A Rivadeneira, Fernando %A Benjamin, Emelia J %A Lumley, Thomas %A Couper, David %A Stricker, Bruno H %A O'Donnell, Christopher J %A Rice, Kenneth M %A Chang, Patricia P %A Hofman, Albert %A Levy, Daniel %A Rotter, Jerome I %A Fox, Ervin R %A Uitterlinden, André G %A Wang, Thomas J %A Psaty, Bruce M %A Willerson, James T %A van Duijn, Cornelia M %A Boerwinkle, Eric %A Witteman, Jacqueline C M %A Vasan, Ramachandran S %A Smith, Nicholas L %K Aged %K Aged, 80 and over %K Black or African American %K Chemokines %K Cohort Studies %K Female %K Genome-Wide Association Study %K Genotype %K Heart Failure %K Humans %K Introns %K Male %K MARVEL Domain-Containing Proteins %K Membrane Proteins %K Middle Aged %K Polymorphism, Single Nucleotide %K Risk Factors %K White People %XBACKGROUND: Prognosis and survival are significant concerns for individuals with heart failure (HF). To better understand the pathophysiology of HF prognosis, the association between 2,366,858 single-nucleotide polymorphisms (SNPs) and all-cause mortality was evaluated among individuals with incident HF from 4 community-based prospective cohorts: the Atherosclerosis Risk in Communities Study, the Cardiovascular Health Study, the Framingham Heart Study, and the Rotterdam Study.
METHODS AND RESULTS: Participants were 2526 individuals of European ancestry and 466 individuals of African ancestry who experienced an incident HF event during follow-up in the respective cohorts. Within each study, the association between genetic variants and time to mortality among individuals with HF was assessed by Cox proportional hazards models that included adjustment for sex and age at the time of the HF event. Prospective fixed-effect meta-analyses were conducted for the 4 study populations of European ancestry (N=1645 deaths) and for the 2 populations of African ancestry (N=281 deaths). Genome-wide significance was set at P=5.0x10(-7). Meta-analytic findings among individuals of European ancestry revealed 1 genome-wide significant locus on chromosome 3p22 in an intron of CKLF-like MARVEL transmembrane domain containing 7 (CMTM7, P=3.2x10(-7)). Eight additional loci in individuals of European ancestry and 4 loci in individuals of African ancestry were identified by high-signal SNPs (P<1.0x10(-5)) but did not meet genome-wide significance.
CONCLUSIONS: This study identified a novel locus associated with all-cause mortality among individuals of European ancestry with HF. This finding warrants additional investigation, including replication, in other studies of HF.
%B Circ Cardiovasc Genet %V 3 %P 248-55 %8 2010 Jun %G eng %N 3 %1 https://www.ncbi.nlm.nih.gov/pubmed/20400778?dopt=Abstract %R 10.1161/CIRCGENETICS.109.895995 %0 Journal Article %J Hum Mol Genet %D 2010 %T Large-scale genomic studies reveal central role of ABO in sP-selectin and sICAM-1 levels. %A Barbalic, Maja %A Dupuis, Josée %A Dehghan, Abbas %A Bis, Joshua C %A Hoogeveen, Ron C %A Schnabel, Renate B %A Nambi, Vijay %A Bretler, Monique %A Smith, Nicholas L %A Peters, Annette %A Lu, Chen %A Tracy, Russell P %A Aleksic, Nena %A Heeriga, Jan %A Keaney, John F %A Rice, Kenneth %A Lip, Gregory Y H %A Vasan, Ramachandran S %A Glazer, Nicole L %A Larson, Martin G %A Uitterlinden, André G %A Yamamoto, Jennifer %A Durda, Peter %A Haritunians, Talin %A Psaty, Bruce M %A Boerwinkle, Eric %A Hofman, Albert %A Koenig, Wolfgang %A Jenny, Nancy S %A Witteman, Jacqueline C %A Ballantyne, Christie %A Benjamin, Emelia J %K ABO Blood-Group System %K Blood Platelets %K Enzyme-Linked Immunosorbent Assay %K Fluorescence %K Genome-Wide Association Study %K Humans %K Intercellular Adhesion Molecule-1 %K P-Selectin %K White People %XP-selectin and intercellular adhesion molecule-1 (ICAM-1) participate in inflammatory processes by promoting adhesion of leukocytes to vascular wall endothelium. Their soluble levels have been associated with adverse cardiovascular events. To identify loci affecting soluble levels of P-selectin (sP-selectin) and ICAM-1 (sICAM-1), we performed a genome-wide association study in a sample of 4115 (sP-selectin) and 9813 (sICAM-1) individuals of European ancestry as a part of The Cohorts for Heart and Aging Research in Genome Epidemiology consortium. The most significant SNP association for sP-selectin was within the SELP gene (rs6136, P = 4.05 x 10(-61)) and for sICAM-1 levels within the ICAM-1 gene (rs3093030, P = 3.53 x 10(-23)). Both sP-selectin and sICAM-1 were associated with ABO gene variants (rs579459, P = 1.86 x 10(-41) and rs649129, P = 1.22 x 10(-15), respectively) and in both cases the observed associations could be accounted for by the A1 allele of the ABO blood group. The absence of an association between ABO blood group and platelet-bound P-selectin levels in an independent subsample (N = 1088) from the ARIC study, suggests that the ABO blood group may influence cleavage of the P-selectin protein from the cell surface or clearance from the circulation, rather than its production and cellular presentation. These results provide new insights into adhesion molecule biology.
%B Hum Mol Genet %V 19 %P 1863-72 %8 2010 May 01 %G eng %N 9 %1 https://www.ncbi.nlm.nih.gov/pubmed/20167578?dopt=Abstract %R 10.1093/hmg/ddq061