%0 Journal Article %J Nat Genet %D 2015 %T A comprehensive 1,000 Genomes-based genome-wide association meta-analysis of coronary artery disease. %A Nikpay, Majid %A Goel, Anuj %A Won, Hong-Hee %A Hall, Leanne M %A Willenborg, Christina %A Kanoni, Stavroula %A Saleheen, Danish %A Kyriakou, Theodosios %A Nelson, Christopher P %A Hopewell, Jemma C %A Webb, Thomas R %A Zeng, Lingyao %A Dehghan, Abbas %A Alver, Maris %A Armasu, Sebastian M %A Auro, Kirsi %A Bjonnes, Andrew %A Chasman, Daniel I %A Chen, Shufeng %A Ford, Ian %A Franceschini, Nora %A Gieger, Christian %A Grace, Christopher %A Gustafsson, Stefan %A Huang, Jie %A Hwang, Shih-Jen %A Kim, Yun Kyoung %A Kleber, Marcus E %A Lau, King Wai %A Lu, Xiangfeng %A Lu, Yingchang %A Lyytikäinen, Leo-Pekka %A Mihailov, Evelin %A Morrison, Alanna C %A Pervjakova, Natalia %A Qu, Liming %A Rose, Lynda M %A Salfati, Elias %A Saxena, Richa %A Scholz, Markus %A Smith, Albert V %A Tikkanen, Emmi %A Uitterlinden, Andre %A Yang, Xueli %A Zhang, Weihua %A Zhao, Wei %A de Andrade, Mariza %A de Vries, Paul S %A Van Zuydam, Natalie R %A Anand, Sonia S %A Bertram, Lars %A Beutner, Frank %A Dedoussis, George %A Frossard, Philippe %A Gauguier, Dominique %A Goodall, Alison H %A Gottesman, Omri %A Haber, Marc %A Han, Bok-Ghee %A Huang, Jianfeng %A Jalilzadeh, Shapour %A Kessler, Thorsten %A König, Inke R %A Lannfelt, Lars %A Lieb, Wolfgang %A Lind, Lars %A Lindgren, Cecilia M %A Lokki, Marja-Liisa %A Magnusson, Patrik K %A Mallick, Nadeem H %A Mehra, Narinder %A Meitinger, Thomas %A Memon, Fazal-Ur-Rehman %A Morris, Andrew P %A Nieminen, Markku S %A Pedersen, Nancy L %A Peters, Annette %A Rallidis, Loukianos S %A Rasheed, Asif %A Samuel, Maria %A Shah, Svati H %A Sinisalo, Juha %A Stirrups, Kathleen E %A Trompet, Stella %A Wang, Laiyuan %A Zaman, Khan S %A Ardissino, Diego %A Eric Boerwinkle %A Borecki, Ingrid B %A Bottinger, Erwin P %A Buring, Julie E %A Chambers, John C %A Collins, Rory %A Cupples, L Adrienne %A Danesh, John %A Demuth, Ilja %A Elosua, Roberto %A Epstein, Stephen E %A Esko, Tõnu %A Feitosa, Mary F %A Franco, Oscar H %A Franzosi, Maria Grazia %A Granger, Christopher B %A Gu, Dongfeng %A Gudnason, Vilmundur %A Hall, Alistair S %A Hamsten, Anders %A Harris, Tamara B %A Hazen, Stanley L %A Hengstenberg, Christian %A Hofman, Albert %A Ingelsson, Erik %A Iribarren, Carlos %A Jukema, J Wouter %A Karhunen, Pekka J %A Kim, Bong-Jo %A Kooner, Jaspal S %A Kullo, Iftikhar J %A Lehtimäki, Terho %A Loos, Ruth J F %A Melander, Olle %A Metspalu, Andres %A Marz, Winfried %A Palmer, Colin N %A Perola, Markus %A Quertermous, Thomas %A Rader, Daniel J %A Ridker, Paul M %A Ripatti, Samuli %A Roberts, Robert %A Salomaa, Veikko %A Sanghera, Dharambir K %A Schwartz, Stephen M %A Seedorf, Udo %A Stewart, Alexandre F %A Stott, David J %A Thiery, Joachim %A Zalloua, Pierre A %A O'Donnell, Christopher J %A Reilly, Muredach P %A Assimes, Themistocles L %A Thompson, John R %A Erdmann, Jeanette %A Clarke, Robert %A Watkins, Hugh %A Kathiresan, Sekar %A McPherson, Ruth %A Deloukas, Panos %A Schunkert, Heribert %A Samani, Nilesh J %A Farrall, Martin %K Coronary Artery Disease %K Genome, Human %K Genome-Wide Association Study %K Humans %K Phenotype %X

Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association study (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of ∼185,000 CAD cases and controls, interrogating 6.7 million common (minor allele frequency (MAF) > 0.05) and 2.7 million low-frequency (0.005 < MAF < 0.05) variants. In addition to confirming most known CAD-associated loci, we identified ten new loci (eight additive and two recessive) that contain candidate causal genes newly implicating biological processes in vessel walls. We observed intralocus allelic heterogeneity but little evidence of low-frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD, showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size.

%B Nat Genet %V 47 %P 1121-1130 %8 2015 Oct %G eng %N 10 %1 https://www.ncbi.nlm.nih.gov/pubmed/26343387?dopt=Abstract %R 10.1038/ng.3396 %0 Journal Article %J Nature %D 2015 %T Exome sequencing identifies rare LDLR and APOA5 alleles conferring risk for myocardial infarction. %A Do, Ron %A Stitziel, Nathan O %A Won, Hong-Hee %A Jørgensen, Anders Berg %A Duga, Stefano %A Angelica Merlini, Pier %A Kiezun, Adam %A Farrall, Martin %A Goel, Anuj %A Zuk, Or %A Guella, Illaria %A Asselta, Rosanna %A Lange, Leslie A %A Peloso, Gina M %A Auer, Paul L %A Girelli, Domenico %A Martinelli, Nicola %A Farlow, Deborah N %A DePristo, Mark A %A Roberts, Robert %A Stewart, Alexander F R %A Saleheen, Danish %A Danesh, John %A Epstein, Stephen E %A Sivapalaratnam, Suthesh %A Hovingh, G Kees %A Kastelein, John J %A Samani, Nilesh J %A Schunkert, Heribert %A Erdmann, Jeanette %A Shah, Svati H %A Kraus, William E %A Davies, Robert %A Nikpay, Majid %A Johansen, Christopher T %A Wang, Jian %A Hegele, Robert A %A Hechter, Eliana %A Marz, Winfried %A Kleber, Marcus E %A Huang, Jie %A Johnson, Andrew D %A Li, Mingyao %A Burke, Greg L %A Gross, Myron %A Liu, Yongmei %A Assimes, Themistocles L %A Heiss, Gerardo %A Lange, Ethan M %A Folsom, Aaron R %A Taylor, Herman A %A Olivieri, Oliviero %A Hamsten, Anders %A Clarke, Robert %A Reilly, Dermot F %A Yin, Wu %A Rivas, Manuel A %A Donnelly, Peter %A Rossouw, Jacques E %A Psaty, Bruce M %A Herrington, David M %A Wilson, James G %A Rich, Stephen S %A Bamshad, Michael J %A Tracy, Russell P %A Cupples, L Adrienne %A Rader, Daniel J %A Reilly, Muredach P %A Spertus, John A %A Cresci, Sharon %A Hartiala, Jaana %A Tang, W H Wilson %A Hazen, Stanley L %A Allayee, Hooman %A Reiner, Alex P %A Carlson, Christopher S %A Kooperberg, Charles %A Jackson, Rebecca D %A Eric Boerwinkle %A Lander, Eric S %A Schwartz, Stephen M %A Siscovick, David S %A McPherson, Ruth %A Tybjaerg-Hansen, Anne %A Abecasis, Gonçalo R %A Watkins, Hugh %A Nickerson, Deborah A %A Ardissino, Diego %A Sunyaev, Shamil R %A O'Donnell, Christopher J %A Altshuler, David %A Gabriel, Stacey %A Kathiresan, Sekar %K Age Factors %K Age of Onset %K Alleles %K Apolipoprotein A-V %K Apolipoproteins A %K Case-Control Studies %K Cholesterol, LDL %K Coronary Artery Disease %K Exome %K Female %K Genetic Predisposition to Disease %K Genetics, Population %K Heterozygote %K Humans %K Male %K Middle Aged %K Mutation %K Myocardial Infarction %K National Heart, Lung, and Blood Institute (U.S.) %K Receptors, LDL %K Triglycerides %K United States %X

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

%B Nature %V 518 %P 102-6 %8 2015 Feb 05 %G eng %N 7537 %1 https://www.ncbi.nlm.nih.gov/pubmed/25487149?dopt=Abstract %R 10.1038/nature13917