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9 results on '"Global Lipids Genetics Consortium"'

1. A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids

Author

Ramdas, Shweta, Judd, Jonathan, Graham, Sarah E, Kanoni, Stavroula, Wang, Yuxuan, Surakka, Ida, Wenz, Brandon, Clarke, Shoa L, Chesi, Alessandra, Wells, Andrew, Bhatti, Konain Fatima, Vedantam, Sailaja, Winkler, Thomas W, Locke, Adam E, Marouli, Eirini, Zajac, Greg JM, Wu, Kuan-Han H, Ntalla, Ioanna, Hui, Qin, Klarin, Derek, Hilliard, Austin T, Wang, Zeyuan, Xue, Chao, Thorleifsson, Gudmar, Helgadottir, Anna, Gudbjartsson, Daniel F, Holm, Hilma, Olafsson, Isleifur, Hwang, Mi Yeong, Han, Sohee, Akiyama, Masato, Sakaue, Saori, Terao, Chikashi, Kanai, Masahiro, Zhou, Wei, Brumpton, Ben M, Rasheed, Humaira, Havulinna, Aki S, Veturi, Yogasudha, Pacheco, Jennifer Allen, Rosenthal, Elisabeth A, Lingren, Todd, Feng, QiPing, Kullo, Iftikhar J, Narita, Akira, Takayama, Jun, Martin, Hilary C, Hunt, Karen A, Trivedi, Bhavi, Haessler, Jeffrey, Giulianini, Franco, Bradford, Yuki, Miller, Jason E, Campbell, Archie, Lin, Kuang, Millwood, Iona Y, Rasheed, Asif, Hindy, George, Faul, Jessica D, Zhao, Wei, Weir, David R, Turman, Constance, Huang, Hongyan, Graff, Mariaelisa, Choudhury, Ananyo, Sengupta, Dhriti, Mahajan, Anubha, Brown, Michael R, Zhang, Weihua, Yu, Ketian, Schmidt, Ellen M, Pandit, Anita, Gustafsson, Stefan, Yin, Xianyong, Luan, Jian’an, Zhao, Jing-Hua, Matsuda, Fumihiko, Jang, Hye-Mi, Yoon, Kyungheon, Medina-Gomez, Carolina, Pitsillides, Achilleas, Hottenga, Jouke Jan, Wood, Andrew R, Ji, Yingji, Gao, Zishan, Haworth, Simon, Mitchell, Ruth E, Chai, Jin Fang, Aadahl, Mette, Bjerregaard, Anne A, Yao, Jie, Manichaikul, Ani, Lee, Wen-Jane, Hsiung, Chao Agnes, Warren, Helen R, Ramirez, Julia, Bork-Jensen, Jette, Kårhus, Line L, Goel, Anuj, and Sabater-Lleal, Maria

Subjects
Human Genome, Biotechnology, Genetics, 2.1 Biological and endogenous factors, Aetiology, Chromatin, Genome-Wide Association Study, Genomics, Humans, Lipids, Polymorphism, Single Nucleotide, Million Veterans Program, Global Lipids Genetics Consortium, complex traits, fine-mapping, functional genomics, lipid biology, post-GWAS, regulatory mechanism, variant prioritization, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.

Published
2022

2. Rare and low-frequency coding variants alter human adult height

Author

Marouli, Eirini, Graff, Mariaelisa, Medina-Gomez, Carolina, Lo, Ken Sin, Wood, Andrew R, Kjaer, Troels R, Fine, Rebecca S, Lu, Yingchang, Schurmann, Claudia, Highland, Heather M, Rüeger, Sina, Thorleifsson, Gudmar, Justice, Anne E, Lamparter, David, Stirrups, Kathleen E, Turcot, Valérie, Young, Kristin L, Winkler, Thomas W, Esko, Tõnu, Karaderi, Tugce, Locke, Adam E, Masca, Nicholas GD, Ng, Maggie CY, Mudgal, Poorva, Rivas, Manuel A, Vedantam, Sailaja, Mahajan, Anubha, Guo, Xiuqing, Abecasis, Goncalo, Aben, Katja K, Adair, Linda S, Alam, Dewan S, Albrecht, Eva, Allin, Kristine H, Allison, Matthew, Amouyel, Philippe, Appel, Emil V, Arveiler, Dominique, Asselbergs, Folkert W, Auer, Paul L, Balkau, Beverley, Banas, Bernhard, Bang, Lia E, Benn, Marianne, Bergmann, Sven, Bielak, Lawrence F, Blüher, Matthias, Boeing, Heiner, Boerwinkle, Eric, Böger, Carsten A, Bonnycastle, Lori L, Bork-Jensen, Jette, Bots, Michiel L, Bottinger, Erwin P, Bowden, Donald W, Brandslund, Ivan, Breen, Gerome, Brilliant, Murray H, Broer, Linda, Burt, Amber A, Butterworth, Adam S, Carey, David J, Caulfield, Mark J, Chambers, John C, Chasman, Daniel I, Chen, Yii-Der Ida, Chowdhury, Rajiv, Christensen, Cramer, Chu, Audrey Y, Cocca, Massimiliano, Collins, Francis S, Cook, James P, Corley, Janie, Galbany, Jordi Corominas, Cox, Amanda J, Cuellar-Partida, Gabriel, Danesh, John, Davies, Gail, de Bakker, Paul IW, de Borst, Gert J, de Denus, Simon, de Groot, Mark CH, de Mutsert, Renée, Deary, Ian J, Dedoussis, George, Demerath, Ellen W, den Hollander, Anneke I, Dennis, Joe G, Di Angelantonio, Emanuele, Drenos, Fotios, Du, Mengmeng, Dunning, Alison M, Easton, Douglas F, Ebeling, Tapani, Edwards, Todd L, Ellinor, Patrick T, Elliott, Paul, Evangelou, Evangelos, Farmaki, Aliki-Eleni, and Faul, Jessica D

Subjects
Ecological Applications, Environmental Sciences, Genetics, Biological Sciences, Human Genome, 2.1 Biological and endogenous factors, ADAMTS Proteins, Adult, Alleles, Body Height, Cell Adhesion Molecules, Female, Gene Frequency, Genetic Variation, Genome, Human, Glycoproteins, Glycosaminoglycans, Hedgehog Proteins, Humans, Intercellular Signaling Peptides and Proteins, Interferon Regulatory Factors, Interleukin-11 Receptor alpha Subunit, Male, Multifactorial Inheritance, NADPH Oxidase 4, NADPH Oxidases, Phenotype, Pregnancy-Associated Plasma Protein-A, Procollagen N-Endopeptidase, Proteoglycans, Proteolysis, Receptors, Androgen, Somatomedins, EPIC-InterAct Consortium, CHD Exome+ Consortium, ExomeBP Consortium, T2D-Genes Consortium, GoT2D Genes Consortium, Global Lipids Genetics Consortium, ReproGen Consortium, MAGIC Investigators, General Science & Technology
Abstract

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

Published
2017

3. Platelet-Related Variants Identified by Exomechip Meta-analysis in 157,293 Individuals

Author

Eicher, John D, Chami, Nathalie, Kacprowski, Tim, Nomura, Akihiro, Chen, Ming-Huei, Yanek, Lisa R, Tajuddin, Salman M, Schick, Ursula M, Slater, Andrew J, Pankratz, Nathan, Polfus, Linda, Schurmann, Claudia, Giri, Ayush, Brody, Jennifer A, Lange, Leslie A, Manichaikul, Ani, Hill, W David, Pazoki, Raha, Elliot, Paul, Evangelou, Evangelos, Tzoulaki, Ioanna, Gao, He, Vergnaud, Anne-Claire, Mathias, Rasika A, Becker, Diane M, Becker, Lewis C, Burt, Amber, Crosslin, David R, Lyytikäinen, Leo-Pekka, Nikus, Kjell, Hernesniemi, Jussi, Kähönen, Mika, Raitoharju, Emma, Mononen, Nina, Raitakari, Olli T, Lehtimäki, Terho, Cushman, Mary, Zakai, Neil A, Nickerson, Deborah A, Raffield, Laura M, Quarells, Rakale, Willer, Cristen J, Peloso, Gina M, Abecasis, Goncalo R, Liu, Dajiang J, Consortium, Global Lipids Genetics, Deloukas, Panos, Samani, Nilesh J, Schunkert, Heribert, Erdmann, Jeanette, Consortium, CARDIoGRAM Exome, Consortium, Myocardial Infarction Genetics, Fornage, Myriam, Richard, Melissa, Tardif, Jean-Claude, Rioux, John D, Dube, Marie-Pierre, de Denus, Simon, Lu, Yingchang, Bottinger, Erwin P, Loos, Ruth JF, Smith, Albert Vernon, Harris, Tamara B, Launer, Lenore J, Gudnason, Vilmundur, Edwards, Digna R Velez, Torstenson, Eric S, Liu, Yongmei, Tracy, Russell P, Rotter, Jerome I, Rich, Stephen S, Highland, Heather M, Boerwinkle, Eric, Li, Jin, Lange, Ethan, Wilson, James G, Mihailov, Evelin, Mägi, Reedik, Hirschhorn, Joel, Metspalu, Andres, Esko, Tõnu, Vacchi-Suzzi, Caterina, Nalls, Mike A, Zonderman, Alan B, Evans, Michele K, Engström, Gunnar, Orho-Melander, Marju, Melander, Olle, O’Donoghue, Michelle L, Waterworth, Dawn M, Wallentin, Lars, White, Harvey D, Floyd, James S, Bartz, Traci M, Rice, Kenneth M, Psaty, Bruce M, Starr, JM, Liewald, David CM, Hayward, Caroline, and Deary, Ian J

Subjects
Biological Sciences, Genetics, Hematology, Clinical Research, Cardiovascular, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Blood, Blood Platelets, Exome, Female, Genetic Variation, Genome-Wide Association Study, Humans, Male, Mean Platelet Volume, Platelet Count, Global Lipids Genetics Consortium, CARDIoGRAM Exome Consortium, Myocardial Infarction Genetics Consortium, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Platelet production, maintenance, and clearance are tightly controlled processes indicative of platelets' important roles in hemostasis and thrombosis. Platelets are common targets for primary and secondary prevention of several conditions. They are monitored clinically by complete blood counts, specifically with measurements of platelet count (PLT) and mean platelet volume (MPV). Identifying genetic effects on PLT and MPV can provide mechanistic insights into platelet biology and their role in disease. Therefore, we formed the Blood Cell Consortium (BCX) to perform a large-scale meta-analysis of Exomechip association results for PLT and MPV in 157,293 and 57,617 individuals, respectively. Using the low-frequency/rare coding variant-enriched Exomechip genotyping array, we sought to identify genetic variants associated with PLT and MPV. In addition to confirming 47 known PLT and 20 known MPV associations, we identified 32 PLT and 18 MPV associations not previously observed in the literature across the allele frequency spectrum, including rare large effect (FCER1A), low-frequency (IQGAP2, MAP1A, LY75), and common (ZMIZ2, SMG6, PEAR1, ARFGAP3/PACSIN2) variants. Several variants associated with PLT/MPV (PEAR1, MRVI1, PTGES3) were also associated with platelet reactivity. In concurrent BCX analyses, there was overlap of platelet-associated variants with red (MAP1A, TMPRSS6, ZMIZ2) and white (PEAR1, ZMIZ2, LY75) blood cell traits, suggesting common regulatory pathways with shared genetic architecture among these hematopoietic lineages. Our large-scale Exomechip analyses identified previously undocumented associations with platelet traits and further indicate that several complex quantitative hematological, lipid, and cardiovascular traits share genetic factors.

Published
2016

4. Pleiotropic genes for metabolic syndrome and inflammation

Author

Kraja, Aldi T, Chasman, Daniel I, North, Kari E, Reiner, Alexander P, Yanek, Lisa R, Kilpeläinen, Tuomas O, Smith, Jennifer A, Dehghan, Abbas, Dupuis, Josée, Johnson, Andrew D, Feitosa, Mary F, Tekola-Ayele, Fasil, Chu, Audrey Y, Nolte, Ilja M, Dastani, Zari, Morris, Andrew, Pendergrass, Sarah A, Sun, Yan V, Ritchie, Marylyn D, Vaez, Ahmad, Lin, Honghuang, Ligthart, Symen, Marullo, Letizia, Rohde, Rebecca, Shao, Yaming, Ziegler, Mark A, Im, Hae Kyung, Group, Cross Consortia Pleiotropy, Heart and, the Cohorts for, Epidemiology, Aging Research in Genetic, Consortium, the Genetic Investigation of Anthropometric Traits, Consortium, the Global Lipids Genetics, the Meta-Analyses of Glucose, Consortium, Insulin-related traits, Consortium, the Global BPgen, Consortium, The ADIPOGen, Study, the Women's Genome Health, Study, the Howard University Family, Schnabel, Renate B, Jørgensen, Torben, Jørgensen, Marit E, Hansen, Torben, Pedersen, Oluf, Stolk, Ronald P, Snieder, Harold, Hofman, Albert, Uitterlinden, Andre G, Franco, Oscar H, Ikram, M Arfan, Richards, J Brent, Rotimi, Charles, Wilson, James G, Lange, Leslie, Ganesh, Santhi K, Nalls, Mike, Rasmussen-Torvik, Laura J, Pankow, James S, Coresh, Josef, Tang, Weihong, Kao, WH Linda, Boerwinkle, Eric, Morrison, Alanna C, Ridker, Paul M, Becker, Diane M, Rotter, Jerome I, Kardia, Sharon LR, Loos, Ruth JF, Larson, Martin G, Hsu, Yi-Hsiang, Province, Michael A, Tracy, Russell, Voight, Benjamin F, Vaidya, Dhananjay, O'Donnell, Christopher J, Benjamin, Emelia J, Alizadeh, Behrooz Z, Prokopenko, Inga, Meigs, James B, and Borecki, Ingrid B

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Prevention, Diabetes, Cardiovascular, Obesity, Clinical Research, Human Genome, Nutrition, 2.1 Biological and endogenous factors, Humans, Biomarkers, Computational Biology, Gene Regulatory Networks, Genetic Pleiotropy, Genetic Predisposition to Disease, Genome-Wide Association Study, Inflammation, Metabolic Syndrome, Phenotype, Quantitative Trait, Heritable, Metabolic syndrome, Inflammatory markers, Pleiotropic associations, Meta-analysis, Regulome, Cross Consortia Pleiotropy Group, Cohorts for Heart and, Aging Research in Genetic Epidemiology, Genetic Investigation of Anthropometric Traits Consortium, Global Lipids Genetics Consortium, Meta-Analyses of Glucose, Insulin-related traits Consortium, Global BPgen Consortium, ADIPOGen Consortium, Women's Genome Health Study, Howard University Family Study, Clinical Sciences, Genetics & Heredity, Clinical sciences
Abstract

Metabolic syndrome (MetS) has become a health and financial burden worldwide. The MetS definition captures clustering of risk factors that predict higher risk for diabetes mellitus and cardiovascular disease. Our study hypothesis is that additional to genes influencing individual MetS risk factors, genetic variants exist that influence MetS and inflammatory markers forming a predisposing MetS genetic network. To test this hypothesis a staged approach was undertaken. (a) We analyzed 17 metabolic and inflammatory traits in more than 85,500 participants from 14 large epidemiological studies within the Cross Consortia Pleiotropy Group. Individuals classified with MetS (NCEP definition), versus those without, showed on average significantly different levels for most inflammatory markers studied. (b) Paired average correlations between 8 metabolic traits and 9 inflammatory markers from the same studies as above, estimated with two methods, and factor analyses on large simulated data, helped in identifying 8 combinations of traits for follow-up in meta-analyses, out of 130,305 possible combinations between metabolic traits and inflammatory markers studied. (c) We performed correlated meta-analyses for 8 metabolic traits and 6 inflammatory markers by using existing GWAS published genetic summary results, with about 2.5 million SNPs from twelve predominantly largest GWAS consortia. These analyses yielded 130 unique SNPs/genes with pleiotropic associations (a SNP/gene associating at least one metabolic trait and one inflammatory marker). Of them twenty-five variants (seven loci newly reported) are proposed as MetS candidates. They map to genes MACF1, KIAA0754, GCKR, GRB14, COBLL1, LOC646736-IRS1, SLC39A8, NELFE, SKIV2L, STK19, TFAP2B, BAZ1B, BCL7B, TBL2, MLXIPL, LPL, TRIB1, ATXN2, HECTD4, PTPN11, ZNF664, PDXDC1, FTO, MC4R and TOMM40. Based on large data evidence, we conclude that inflammation is a feature of MetS and several gene variants show pleiotropic genetic associations across phenotypes and might explain a part of MetS correlated genetic architecture. These findings warrant further functional investigation.

Published
2014

5. Discovery and refinement of loci associated with lipid levels

Author

Willer, Cristen J, Schmidt, Ellen M, Sengupta, Sebanti, Peloso, Gina M, Gustafsson, Stefan, Kanoni, Stavroula, Ganna, Andrea, Chen, Jin, Buchkovich, Martin L, Mora, Samia, Beckmann, Jacques S, Bragg-Gresham, Jennifer L, Chang, Hsing-Yi, Demirkan, Ayşe, Den Hertog, Heleen M, Do, Ron, Donnelly, Louise A, Ehret, Georg B, Esko, Tõnu, Feitosa, Mary F, Ferreira, Teresa, Fischer, Krista, Fontanillas, Pierre, Fraser, Ross M, Freitag, Daniel F, Gurdasani, Deepti, Heikkilä, Kauko, Hyppönen, Elina, Isaacs, Aaron, Jackson, Anne U, Johansson, Åsa, Johnson, Toby, Kaakinen, Marika, Kettunen, Johannes, Kleber, Marcus E, Li, Xiaohui, Luan, Jian’an, Lyytikäinen, Leo-Pekka, Magnusson, Patrik KE, Mangino, Massimo, Mihailov, Evelin, Montasser, May E, Müller-Nurasyid, Martina, Nolte, Ilja M, O’Connell, Jeffrey R, Palmer, Cameron D, Perola, Markus, Petersen, Ann-Kristin, Sanna, Serena, Saxena, Richa, Service, Susan K, Shah, Sonia, Shungin, Dmitry, Sidore, Carlo, Song, Ci, Strawbridge, Rona J, Surakka, Ida, Tanaka, Toshiko, Teslovich, Tanya M, Thorleifsson, Gudmar, Van den Herik, Evita G, Voight, Benjamin F, Volcik, Kelly A, Waite, Lindsay L, Wong, Andrew, Wu, Ying, Zhang, Weihua, Absher, Devin, Asiki, Gershim, Barroso, Inês, Been, Latonya F, Bolton, Jennifer L, Bonnycastle, Lori L, Brambilla, Paolo, Burnett, Mary S, Cesana, Giancarlo, Dimitriou, Maria, Doney, Alex SF, Döring, Angela, Elliott, Paul, Epstein, Stephen E, Ingi Eyjolfsson, Gudmundur, Gigante, Bruna, Goodarzi, Mark O, Grallert, Harald, Gravito, Martha L, Groves, Christopher J, Hallmans, Göran, Hartikainen, Anna-Liisa, Hayward, Caroline, Hernandez, Dena, Hicks, Andrew A, Holm, Hilma, Hung, Yi-Jen, Illig, Thomas, Jones, Michelle R, Kaleebu, Pontiano, Kastelein, John JP, Khaw, Kay-Tee, and Kim, Eric

Subjects
Biological Sciences, Genetics, Human Genome, Cardiovascular, 2.1 Biological and endogenous factors, Asian People, Black People, Cholesterol, HDL, Cholesterol, LDL, Coronary Artery Disease, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Lipids, Triglycerides, White People, Global Lipids Genetics Consortium, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Levels of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and total cholesterol are heritable, modifiable risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,577 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5 × 10(-8), including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index. Our results demonstrate the value of using genetic data from individuals of diverse ancestry and provide insights into the biological mechanisms regulating blood lipids to guide future genetic, biological and therapeutic research.

Published
2013

6. The power of genetic diversity in genome-wide association studies of lipids

Author

Graham, Sarah E, Clarke, Shoa L, Wu, Kuan-Han H, Kanoni, Stavroula, Zajac, Greg JM, Ramdas, Shweta, Surakka, Ida, Ntalla, Ioanna, Vedantam, Sailaja, Winkler, Thomas W, Locke, Adam E, Marouli, Eirini, Hwang, Mi Yeong, Han, Sohee, Narita, Akira, Choudhury, Ananyo, Bentley, Amy R, Ekoru, Kenneth, Verma, Anurag, Trivedi, Bhavi, Martin, Hilary C, Hunt, Karen A, Hui, Qin, Klarin, Derek, Zhu, Xiang, Thorleifsson, Gudmar, Helgadottir, Anna, Gudbjartsson, Daniel F, Holm, Hilma, Olafsson, Isleifur, Akiyama, Masato, Sakaue, Saori, Terao, Chikashi, Kanai, Masahiro, Zhou, Wei, Brumpton, Ben M, Rasheed, Humaira, Ruotsalainen, Sanni E, Havulinna, Aki S, Veturi, Yogasudha, Feng, QiPing, Rosenthal, Elisabeth A, Lingren, Todd, Pacheco, Jennifer Allen, Pendergrass, Sarah A, Haessler, Jeffrey, Giulianini, Franco, Bradford, Yuki, Miller, Jason E, Campbell, Archie, Lin, Kuang, Millwood, Iona Y, Hindy, George, Rasheed, Asif, Faul, Jessica D, Zhao, Wei, Weir, David R, Turman, Constance, Huang, Hongyan, Graff, Mariaelisa, Mahajan, Anubha, Brown, Michael R, Zhang, Weihua, Yu, Ketian, Schmidt, Ellen M, Pandit, Anita, Gustafsson, Stefan, Yin, Xianyong, Luan, Jian'an, Zhao, Jing-Hua, Matsuda, Fumihiko, Jang, Hye-Mi, Yoon, Kyungheon, Medina-Gomez, Carolina, Pitsillides, Achilleas, Hottenga, Jouke Jan, Willemsen, Gonneke, Wood, Andrew R, Ji, Yingji, Gao, Zishan, Haworth, Simon, Mitchell, Ruth E, Chai, Jin Fang, Aadahl, Mette, Yao, Jie, Manichaikul, Ani, Warren, Helen R, Ramirez, Julia, Bork-Jensen, Jette, Kårhus, Line L, Goel, Anuj, Sabater-Lleal, Maria, Noordam, Raymond, Sidore, Carlo, Fiorillo, Edoardo, McDaid, Aaron F, Marques-Vidal, Pedro, Wielscher, Matthias, Trompet, Stella, and Sattar, Naveed

Subjects
Multifactorial Inheritance, Global Lipids Genetics Consortium, General Science & Technology, Prevention, Human Genome, Single Nucleotide, Cardiovascular, Linkage Disequilibrium, Heart Disease, Good Health and Well Being, Population Groups, Cardiovascular Diseases, VA Million Veteran Program, Genetics, Humans, 2.1 Biological and endogenous factors, Genetic Predisposition to Disease, Polymorphism, Aetiology, Genome-Wide Association Study
Abstract

Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4-23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice.

Published
2021

7. Platelet-Related Variants Identified by Exomechip Meta-analysis in 157,293 Individuals

Author

Anne-Claire Vergnaud, Nauder Faraday, Tim Kacprowski, Lisa R. Yanek, Oscar H. Franco, Yongmei Liu, Andreas Greinacher, Gina M. Peloso, Cristen J. Willer, Leslie A. Lange, Eric S. Torstenson, Reedik Mägi, Jeanette Erdmann, Ethan M. Lange, Deborah A. Nickerson, Henry Völzke, David R. Crosslin, Gunnar Engström, Albert V. Smith, André G. Uitterlinden, Salman M. Tajuddin, W. David Hill, Diane M. Becker, Paul Elliot, Caterina Vacchi-Suzzi, Linda M. Polfus, Traci M. Bartz, Nathalie Chami, Abbas Dehghan, Mike A. Nalls, John D. Eicher, Leo-Pekka Lyytikäinen, Evelin Mihailov, Uwe Völker, Caroline Hayward, Ioanna Tzoulaki, Myriam Fornage, Marju Orho-Melander, Mary Cushman, Lars Wallentin, Terho Lehtimäki, Ayush Giri, Laura M. Raffield, Lewis C. Becker, Yingchang Lu, Emma Raitoharju, Sekar Kathiresan, Simon de Denus, Ruth J. F. Loos, James S. Floyd, Dawn M. Waterworth, James G. Wilson, Nathan Pankratz, Lenore J. Launer, Andrew D. Johnson, Andrew J. Slater, Jean-Claude Tardif, Raha Pazoki, Evangelos Evangelou, Kenneth Rice, Harvey D. White, Marie-Pierre Dubé, Frank J. A. van Rooij, Akihiro Nomura, Tamara B. Harris, Vilmundur Gudnason, Gonçalo R. Abecasis, Alan B. Zonderman, Guillaume Lettre, Todd L. Edwards, Amber A. Burt, Ani Manichaikul, Heribert Schunkert, Ming-Huei Chen, Ian J. Deary, Michelle L. O'Donoghue, Jennifer A. Brody, Russell P. Tracy, Tõnu Esko, Mika Kähönen, Panos Deloukas, Eric Boerwinkle, Rasika A. Mathias, Dajiang J. Liu, Jin Li, Santhi K. Ganesh, David C. Liewald, Paul L. Auer, Digna R. Velez Edwards, Erwin P. Bottinger, Nina Mononen, Claudia Schurmann, Michele K. Evans, John M. Starr, Thomas Thiele, Jussi Hernesniemi, Jerome I. Rotter, Rakale C. Quarells, He Gao, Kjell Nikus, Stephen S. Rich, Heather M. Highland, Bruce M. Psaty, Ursula M. Schick, Andres Metspalu, Melissa A. Richard, Neil A. Zakai, Olle Melander, John D. Rioux, Olli T. Raitakari, Alexander P. Reiner, Joel N. Hirschhorn, Nilesh J. Samani, Epidemiology, Internal Medicine, Home Office, National Institute for Health Research, and Medical Research Council (MRC)

Subjects
0301 basic medicine, Blood Platelets, Male, CARDIoGRAM Exome Consortium, Genome-wide association study, 030204 cardiovascular system & hematology, Biology, Myocardial Infarction Genetics Consortium, Article, 03 medical and health sciences, 0302 clinical medicine, Genetics, Humans, Platelet, Exome, Genetics(clinical), Mean platelet volume, Allele frequency, Genotyping, Genetics (clinical), Genetics & Heredity, Platelet Count, ta1184, Genetic Variation, Global Lipids Genetics Consortium, 11 Medical And Health Sciences, 06 Biological Sciences, FCER1A, Genetic architecture, 030104 developmental biology, Hemostasis, Immunology, Female, Mean Platelet Volume, Genome-Wide Association Study
Abstract

Platelet production, maintenance, and clearance are tightly controlled processes indicative of platelets' important roles in hemostasis and thrombosis. Platelets are common targets for primary and secondary prevention of several conditions. They are monitored clinically by complete blood counts, specifically with measurements of platelet count (PLT) and mean platelet volume (MPV). Identifying genetic effects on PLT and MPV can provide mechanistic insights into platelet biology and their role in disease. Therefore, we formed the Blood Cell Consortium (BCX) to perform a large-scale meta-analysis of Exomechip association results for PLT and MPV in 157,293 and 57,617 individuals, respectively. Using the low-frequency/rare coding variant-enriched Exomechip genotyping array, we sought to identify genetic variants associated with PLT and MPV. In addition to confirming 47 known PLT and 20 known MPV associations, we identified 32 PLT and 18 MPV associations not previously observed in the literature across the allele frequency spectrum, including rare large effect (FCER1A), low-frequency (IQGAP2, MAP1A, LY75), and common (ZMIZ2, SMG6, PEAR1, ARFGAP3/PACSIN2) variants. Several variants associated with PLT/MPV (PEAR1, MRVI1, PTGES3) were also associated with platelet reactivity. In concurrent BCX analyses, there was overlap of platelet-associated variants with red (MAP1A, TMPRSS6, ZMIZ2) and white (PEAR1, ZMIZ2, LY75) blood cell traits, suggesting common regulatory pathways with shared genetic architecture among these hematopoietic lineages. Our large-scale Exomechip analyses identified previously undocumented associations with platelet traits and further indicate that several complex quantitative hematological, lipid, and cardiovascular traits share genetic factors.

Published
2016
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8. Pleiotropic genes for metabolic syndrome and inflammation

Author

Inga Prokopenko, Fasil Tekola-Ayele, Jerome I. Rotter, Audrey Y. Chu, Torben Jørgensen, Paul M. Ridker, Yan V. Sun, Daniel I. Chasman, M. Arfan Ikram, Marit E. Jørgensen, Ruth J. F. Loos, Zari Dastani, Martin G. Larson, Andrew D. Johnson, Jennifer A. Smith, Ahmad Vaez, Albert Hofman, Letizia Marullo, Ilja M. Nolte, Abbas Dehghan, Michael A. Province, Leslie A. Lange, Josef Coresh, Christopher J. O'Donnell, Aldi T. Kraja, Eric Boerwinkle, Torben Hansen, Josée Dupuis, Honghuang Lin, Mary F. Feitosa, Renate B. Schnabel, Emelia J. Benjamin, Sarah A. Pendergrass, Weihong Tang, Ingrid B. Borecki, Yaming Shao, W. H. Linda Kao, Alanna C. Morrison, Alexander P. Reiner, Russell P. Tracy, Diane M. Becker, Yi-Hsiang Hsu, Benjamin F. Voight, Dhananjay Vaidya, James S. Pankow, Tuomas O. Kilpeläinen, Kari E. North, Oscar H. Franco, Lisa R. Yanek, Marylyn D. Ritchie, Sharon L.R. Kardia, Rebecca Rohde, James G. Wilson, Mike A. Nalls, Laura J. Rasmussen-Torvik, James B. Meigs, Symen Ligthart, Harold Snieder, Behrooz Z. Alizadeh, Andrew P. Morris, Charles N. Rotimi, Oluf Pedersen, Ronald P. Stolk, Mark Ziegler, André G. Uitterlinden, J. Brent Richards, Santhi K. Ganesh, Hae Kyung Im, Life Course Epidemiology (LCE), Lifestyle Medicine (LM), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Epidemiology, Public Health, Internal Medicine, and Radiology & Nuclear Medicine

Subjects
Endocrinology, Diabetes and Metabolism, NF-KAPPA-B, Inflammatory markers, Women's Genome Health Study, Genome-wide association study, BLOOD-PRESSURE, Research & Experimental Medicine, Bioinformatics, Biochemistry, Endocrinology, Cohorts for Heart and, Pleiotropy, Genetic Investigation of Anthropometric Traits Consortium, Gene Regulatory Networks, Meta-Analyses of Glucose, Genetics, Genetics & Heredity, Pleiotropic associations, INSULIN-RESISTANCE, Metabolic Syndrome X, Genetic Pleiotropy, Global Lipids Genetics Consortium, Insulin-related traits Consortium, Metabolic syndrome, C-REACTIVE PROTEIN, Phenotype, Medicine, Research & Experimental, DENSITY-LIPOPROTEIN CHOLESTEROL, CARDIOVASCULAR-DISEASE, CORONARY-ARTERY-DISEASE, CIRCULATING ADIPONECTIN, ADIPOGen Consortium, Life Sciences & Biomedicine, Aging Research in Genetic Epidemiology, Howard University Family Study, Single-nucleotide polymorphism, Quantitative trait locus, Biology, Article, Endocrinology & Metabolism, Quantitative Trait, Heritable, Meta-Analysis as Topic, SDG 3 - Good Health and Well-being, medicine, SNP, Humans, Cross Consortia Pleiotropy Group, Genetic Predisposition to Disease, GENOME-WIDE ASSOCIATION, Molecular Biology, Global BPgen Consortium, Inflammation, Science & Technology, Computational Biology, Regulome, 1103 Clinical Sciences, medicine.disease, Genetic architecture, DIABETES SUSCEPTIBILITY LOCI, Meta-analysis, Biomarkers, Genome-Wide Association Study
Abstract

Metabolic syndrome (MetS) has become a health and financial burden worldwide. The MetS definition captures clustering of risk factors that predict higher risk for diabetes mellitus and cardiovascular disease. Our study hypothesis is that additional to genes influencing individual MetS risk factors, genetic variants exist that influence MetS and inflammatory markers forming a predisposing MetS genetic network. To test this hypothesis a staged approach was undertaken. (a) We analyzed 17 metabolic and inflammatory traits in more than 85,500 participants from 14 large epidemiological studies within the Cross Consortia Pleiotropy Group. Individuals classified with MetS (NCEP definition), versus those without, showed on average significantly different levels for most inflammatory markers studied. (b) Paired average correlations between 8 metabolic traits and 9 inflammatory markers from the same studies as above, estimated with two methods, and factor analyses on large simulated data, helped in identifying 8 combinations of traits for follow-up in meta-analyses, out of 130,305 possible combinations between metabolic traits and inflammatory markers studied. (c) We performed correlated meta-analyses for 8 metabolic traits and 6 inflammatory markers by using existing GWAS published genetic summary results, with about 2.5 million SNPs from twelve predominantly largest GWAS consortia. These analyses yielded 130 unique SNPs/genes with pleiotropic associations (a SNP/gene associating at least one metabolic trait and one inflammatory marker). Of them twenty-five variants (seven loci newly reported) are proposed as MetS candidates. They map to genes MACF1, KIAA0754, GCKR, GRB14, COBLL1, LOC646736-IRS1, SLC39A8, NELFE, SKIV2L, STK19, TFAP2B, BAZ1B, BCL7B, TBL2, MLXIPL, LPL, TRIB1, ATXN2, HECTD4, PTPN11, ZNF664, PDXDC1, FTO, MC4R and TOMM40. Based on large data evidence, we conclude that inflammation is a feature of MetS and several gene variants show pleiotropic genetic associations across phenotypes and might explain a part of MetS correlated genetic architecture. These findings warrant further functional investigation. (C) 2014 Elsevier Inc. All rights reserved.

Published
2014
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9. Discovery and refinement of loci associated with lipid levels

Author

Benjamin F. Voight, Stefania Bandinelli, Pascal Bovet, Latonya F. Been, Ci Song, Luigi Ferrucci, Johannes Kettunen, Andrew D. Morris, Mary Susan Burnett, Ronald M. Krauss, Igor Rudan, Heleen M. den Hertog, Stavroula Kanoni, G. Kees Hovingh, Elina Hyppönen, Kauko Heikkilä, Richard S. Cooper, Daniel I. Chasman, Bruna Gigante, Stefan Gustafsson, Jian'an Luan, Sarah H. Wild, Patricia B. Munroe, Göran Hallmans, Jeffrey R. O'Connell, Danish Saleheen, Aarno Palotie, Leena Moilanen, Jerome I. Rotter, Caroline Hayward, Jennifer L. Bragg-Gresham, Nicholas G. Martin, Claudia Langenberg, George Dedoussis, Carlo Sidore, Ulf Gyllensten, Marika Kaakinen, Jing Hua Zhao, Aimo Ruokonen, Diana Kuh, Maria Dimitriou, Shih-Yi Lin, Gina M. Peloso, Marcus E. Kleber, Christopher J. Groves, Alena Stančáková, Michel Burnier, Patrik K. E. Magnusson, John C. Chambers, Giancarlo Cesana, Francis S. Collins, Gabrielle Müller, Angela Döring, Colin A. McKenzie, Paul Elliott, Lars Lind, Vilmundur Gudnason, Dharambir K. Sanghera, Jean Ferrières, Toshiko Tanaka, Stefan R. Bornstein, Gershim Asiki, Jacques S. Beckmann, Anneli Pouta, Timo A. Lakka, Daniel J. Rader, Elizabeth H. Young, Kelly A. Volcik, Dena G. Hernandez, Ann-Kristin Petersen, Kristian Hveem, Amy J. Swift, Murielle Bochud, Pierre Meneton, Paul M. Ridker, Kathleen Stirrups, Stephen S. Rich, Isleifur Olafsson, Ruth J. F. Loos, Serena Sanna, Markus Perola, Meena Kumari, Cameron D. Palmer, Carlos Iribarren, Nancy L. Pedersen, Mark O. Goodarzi, Panos Deloukas, Norman Klopp, Cristina Pomilla, Stephen E. Epstein, Antti Jula, Themistocles L. Assimes, Martina Müller-Nurasyid, Marjo-Riitta Järvelin, Chao A. Hsiung, Sonia Shah, Christian Gieger, Toby Johnson, Cornelia M. van Duijn, Samuli Ripatti, Nicholas J. Wareham, Krista Fischer, Wendy L. McArdle, Linda S. Adair, Kay-Tee Khaw, Bruce M. Psaty, André G. Uitterlinden, Aaron Isaacs, Tõnu Esko, Jennifer L. Bolton, Rebecca N. Nsubuga, Eric Boerwinkle, L. Joost van Pelt, Jouko Saramies, François Mach, Pierre Fontanillas, Teresa Ferreira, Lars Wallentin, Michael Boehnke, Christa Meisinger, Wayne Huey-Herng Sheu, Gonçalo R. Abecasis, Inês Barroso, Franklyn I. Bennett, Dmitry Shungin, Jaakko Kaprio, Kirsten Ohm Kyvik, Deepti Gurdasani, Anne U. Jackson, Paolo Brambilla, Georg Ehret, Cecilia M. Lindgren, Fernando Rivadeneira, Theodore Papamarkou, Jaakko Tuomilehto, Cristen J. Willer, Martin L. Buchkovich, Antero Kesäniemi, Hubert Scharnagl, Xiaohui Li, Elena Tremoli, Nelson B. Freimer, Mika Kähönen, Ron Do, Karen L. Mohlke, Thomas Illig, Gudmar Thorleifsson, Peter J. Koudstaal, Andres Metspalu, Ulf de Faire, Dominique Arveiler, Harald Grallert, Jaana Lindström, Laurence Tiret, Jaspal S. Kooner, Braxton D. Mitchell, Sebanti Sengupta, Gonneke Willemsen, Anna-Liisa Hartikainen, Terho Lehtimäki, Steve E. Humphries, Peter Schwarz, Dorret I. Boomsma, Harry Campbell, Ellen M. Schmidt, Tom Wilsgaard, Janet Seeley, Alex S. F. Doney, Alan R. Shuldiner, John Whitfield, Markku Laakso, Peter Vollenweider, Gudmundur I. Eyjolfsson, Winfried März, Mika Kivimäki, Ying Wu, Johanna Kuusisto, Andrew A. Hicks, Bruce H. R. Wolffenbuttel, May E. Montasser, Bamidele O. Tayo, Unnur Thorsteinsdottir, Muredach P. Reilly, Leo-Pekka Lyytikäinen, Eric Kim, John Danesh, Ida Surakka, Åsa Johansson, Anders Hamsten, Thomas Quertermous, Hsing-Yi Chang, Jin Chen, Agneta Siegbahn, Narisu Narisu, Samia Mora, Erik Ingelsson, Colin N. A. Palmer, Sekar Kathiresan, Manjinder S. Sandhu, Leif Groop, Jose M. Ordovas, Alan B. Feranil, Evelin Mihailov, Hilma Holm, Pontiano Kaleebu, Lindsay L. Waite, Ramaiah Nagaraja, Andrew Wong, Rona J. Strawbridge, David P. Strachan, Yii-Der Ida Chen, Tamara B. Harris, Jackie F. Price, Aravinda Chakravarti, Veikko Salomaa, Sailaja Vedantam, Albert Hofman, Devin Absher, Ross M. Fraser, Kaisa Silander, Pirjo Komulainen, Yi Jen Hung, Peter P. Pramstaller, Kari Stefansson, Aroon D. Hingorani, Tanya M. Teslovich, Matti Uusitupa, L. Adrienne Cupples, Cisca Wijmenga, Lori L. Bonnycastle, Ilja M. Nolte, Andrea Ganna, Ken K. Ong, Inger Njølstad, Bernhard O. Boehm, Nicholas W.J. Wainwright, Richa Saxena, Rainer Rauramaa, Louise A. Donnelly, James F. Wilson, Matthew Jones, Ingrid B. Borecki, Steven C. Hunt, Weihua Zhang, Massimo Mangino, John J.P. Kastelein, Martha L. Gravito, Mark I. McCarthy, Evita G. Van Den Herik, Joel N. Hirschhorn, Nilesh J. Samani, Daniel F. Freitag, Ayse Demirkan, Mary F. Feitosa, Tuomo Nieminen, Tim D. Spector, Paul W. Franks, Chris Power, Biological Psychology, EMGO+ - Lifestyle, Overweight and Diabetes, Life Course Epidemiology (LCE), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Lifestyle Medicine (LM), Center for Liver, Digestive and Metabolic Diseases (CLDM), Willer, C, Schmidt, E, Sengupta, S, Peloso, G, Gustafsson, S, Kanoni, S, Ganna, A, Chen, J, Buchkovich, M, Mora, S, Beckmann, J, Bragg Gresham, J, Chang, H, Demirkan, A, Den Hertog, H, Do, R, Donnelly, L, Ehret, G, Esko, T, Feitosa, M, Ferreira, T, Fischer, K, Fontanillas, P, Fraser, R, Freitag, D, Gurdasani, D, Heikkilä, K, Hyppönen, E, Isaacs, A, Jackson, A, Johansson, A, Johnson, T, Kaakinen, M, Kettunen, J, Kleber, M, Li, X, Luan, J, Lyytikäinen, L, Magnusson, P, Mangino, M, Mihailov, E, Montasser, M, Müller Nurasyid, M, Nolte, I, O'Connell, J, Palmer, C, Perola, M, Petersen, A, Sanna, S, Saxena, R, Service, S, Shah, S, Shungin, D, Sidore, C, Song, C, Strawbridge, R, Surakka, I, Tanaka, T, Teslovich, T, Thorleifsson, G, Van den Herik, E, Voight, B, Volcik, K, Waite, L, Wong, A, Wu, Y, Zhang, W, Absher, D, Asiki, G, Barroso, I, Been, L, Bolton, J, Bonnycastle, L, Brambilla, P, Burnett, M, Cesana, G, Dimitriou, M, Doney, A, Döring, A, Elliott, P, Epstein, S, Eyjolfsson, G, Gigante, B, Goodarzi, M, Grallert, H, Gravito, M, Groves, C, Hallmans, G, Hartikainen, A, Hayward, C, Hernandez, D, Hicks, A, Holm, H, Hung, Y, Illig, T, Jones, M, Kaleebu, P, Kastelein, J, Khaw, K, Kim, E, Klopp, N, Komulainen, P, Kumari, M, Langenberg, C, Lehtimäki, T, Lin, S, Lindström, J, Loos, R, Mach, F, Mcardle, W, Meisinger, C, Mitchell, B, Müller, G, Nagaraja, R, Narisu, N, Nieminen, T, Nsubuga, R, Olafsson, I, Ong, K, Palotie, A, Papamarkou, T, Pomilla, C, Pouta, A, Rader, D, Reilly, M, Ridker, P, Rivadeneira, F, Rudan, I, Ruokonen, A, Samani, N, Scharnagl, H, Seeley, J, Silander, K, Stancáková, A, Stirrups, K, Swift, A, Tiret, L, Uitterlinden, A, van Pelt, L, Vedantam, S, Wainwright, N, Wijmenga, C, Wild, S, Willemsen, G, Wilsgaard, T, Wilson, J, Young, E, Zhao, J, Adair, L, Arveiler, D, Assimes, T, Bandinelli, S, Bennett, F, Bochud, M, Boehm, B, Boomsma, D, Borecki, I, Bornstein, S, Bovet, P, Burnier, M, Campbell, H, Chakravarti, A, Chambers, J, Chen, Y, Collins, F, Cooper, R, Danesh, J, Dedoussis, G, de Faire, U, Feranil, A, Ferrières, J, Ferrucci, L, Freimer, N, Gieger, C, Groop, L, Gudnason, V, Gyllensten, U, Hamsten, A, Harris, T, Hingorani, A, Hirschhorn, J, Hofman, A, Hovingh, G, Hsiung, C, Humphries, S, Hunt, S, Hveem, K, Iribarren, C, Järvelin, M, Jula, A, Kähönen, M, Kaprio, J, Kesäniemi, A, Kivimaki, M, Kooner, J, Koudstaal, P, Krauss, R, Kuh, D, Kuusisto, J, Kyvik, K, Laakso, M, Lakka, T, Lind, L, Lindgren, C, Martin, N, März, W, Mccarthy, M, Mckenzie, C, Meneton, P, Metspalu, A, Moilanen, L, Morris, A, Munroe, P, Njølstad, I, Pedersen, N, Power, C, Pramstaller, P, Price, J, Psaty, B, Quertermous, T, Rauramaa, R, Saleheen, D, Salomaa, V, Sanghera, D, Saramies, J, Schwarz, P, Sheu, W, Shuldiner, A, Siegbahn, A, Spector, T, Stefansson, K, Strachan, D, Tayo, B, Tremoli, E, Tuomilehto, J, Uusitupa, M, van Duijn, C, Vollenweider, P, Wallentin, L, Wareham, N, Whitfield, J, Wolffenbuttel, B, Ordovas, J, Boerwinkle, E, Thorsteinsdottir, U, Chasman, D, Rotter, J, Franks, P, Ripatti, S, Cupples, L, Sandhu, M, Rich, S, Boehnke, M, Deloukas, P, Kathiresan, S, Mohlke, K, Ingelsson, E, Abecasis, G, ACS - Amsterdam Cardiovascular Sciences, Vascular Medicine, Ehret, Georg Benedikt, Mach, François, Epidemiology, Surgery, Public Health, Ophthalmology, Neurology, Medical Microbiology & Infectious Diseases, Obstetrics & Gynecology, Internal Medicine, National Institute for Health Research, Global Lipids Genetics Consortium, Willer, Cristen, Sengupta, Sebanti, Peloso, Gina, Hypponen, Elina Tuulikki, and Abecasis, Gonçalo R

Subjects
Netherlands Twin Register (NTR), HOMEOSTASIS, BIO/12 - BIOCHIMICA CLINICA E BIOLOGIA MOLECOLARE CLINICA, Blood lipids, Genome-wide association study, Type 2 diabetes, Coronary Artery Disease, 030204 cardiovascular system & hematology, Triglyceride, Coronary artery disease, chemistry.chemical_compound, 0302 clinical medicine, European Continental Ancestry Group/genetics, triglycerides, IDENTIFIES 13, 11 Medical and Health Sciences, African Continental Ancestry Group, 2. Zero hunger, Genetics, Genetics & Heredity, ddc:616, RISK, 0303 health sciences, Cholesterol, HDL/blood, PLASMA, Global Lipids Genetics Consortium, Cholesterol, HDL/blood/genetics, Lipid, Lipids, 3. Good health, LDL/blood, Triglycerides/blood, Lipids/blood/genetics, Cholesterol, Cholesterol, LDL/blood, DENSITY-LIPOPROTEIN CHOLESTEROL, CARDIOVASCULAR-DISEASE, HDL/blood, CORONARY-ARTERY-DISEASE, lipids (amino acids, peptides, and proteins), Life Sciences & Biomedicine, coronary artery disease, TRAITS, Human, Coronary Artery Disease/blood/genetics, Asian Continental Ancestry Group, Genotype, SUSCEPTIBILITY LOCI, European Continental Ancestry Group, Black People, HEART-DISEASE, Biology, Article, White People, lipids, 03 medical and health sciences, Coronary Artery Disease/blood, CORONARY-ARTERY-DISEASE DENSITY-LIPOPROTEIN CHOLESTEROL GENOME-WIDE ASSOCIATION HEART-DISEASE CARDIOVASCULAR-DISEASE SUSCEPTIBILITY LOCI IDENTIFIES 13 RISK GENE METAANALYSIS, Triglycerides/blood/genetics, Asian People, SDG 3 - Good Health and Well-being, Mendelian randomization, medicine, Humans, Asian Continental Ancestry Group/genetics, Genetic Predisposition to Disease, GENOME-WIDE ASSOCIATION, Genotyping, Triglycerides, METAANALYSIS, 030304 developmental biology, Science & Technology, Lipids/blood, Cholesterol, HDL, cholesterol, African Continental Ancestry Group/genetics, Cholesterol, LDL, 06 Biological Sciences, medicine.disease, GENE, chemistry, Cholesterol, LDL/blood/genetics, Lipoprotein, Developmental Biology, Genome-Wide Association Study
Abstract

Levels of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and total cholesterol are heritable, modifiable risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,577 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5 × 10 -8, including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index. Our results demonstrate the value of using genetic data from individuals of diverse ancestry and provide insights into the biological mechanisms regulating blood lipids to guide future genetic, biological and therapeutic research. © 2013 Nature America, Inc. All rights reserved.

Published
2013
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