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1. Genome-wide discovery and integrative genomic characterization of insulin resistance loci using serum triglycerides to HDL-cholesterol ratio as a proxy

Author

Natalie DeForest, Yuqi Wang, Zhiyi Zhu, Jacqueline S. Dron, Ryan Koesterer, Pradeep Natarajan, Jason Flannick, Tiffany Amariuta, Gina M. Peloso, and Amit R. Majithia

Subjects
Science
Abstract

Abstract Insulin resistance causes multiple epidemic metabolic diseases, including type 2 diabetes, cardiovascular disease, and fatty liver, but is not routinely measured in epidemiological studies. To discover novel insulin resistance genes in the general population, we conducted genome-wide association studies in 382,129 individuals for triglyceride to HDL-cholesterol ratio (TG/HDL), a surrogate marker of insulin resistance calculable from commonly measured serum lipid profiles. We identified 251 independent loci, of which 62 were more strongly associated with TG/HDL compared to TG or HDL alone, suggesting them as insulin resistance loci. Candidate causal genes at these loci were prioritized by fine mapping with directions-of-effect and tissue specificity annotated through analysis of protein coding and expression quantitative trait variation. Directions-of-effect were corroborated in an independent cohort of individuals with directly measured insulin resistance. We highlight two phospholipase encoding genes, PLA2G12A and PLA2G6, which liberate arachidonic acid and improve insulin sensitivity, and VGLL3, a transcriptional co-factor that increases insulin resistance partially through enhanced adiposity. Finally, we implicate the anti-apoptotic gene TNFAIP8 as a sex-dimorphic insulin resistance factor, which acts by increasing visceral adiposity, specifically in females. In summary, our study identifies several candidate modulators of insulin resistance that have the potential to serve as biomarkers and pharmacological targets.

Published
2024
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2. Proteome-wide association studies for blood lipids and comparison with transcriptome-wide association studies

Author

Daiwei Zhang, Boran Gao, Qidi Feng, Ani Manichaikul, Gina M. Peloso, Russell P. Tracy, Peter Durda, Kent D. Taylor, Yongmei Liu, W. Craig Johnson, Stacey Gabriel, Namrata Gupta, Joshua D. Smith, Francois Aguet, Kristin G. Ardlie, Thomas W. Blackwell, Robert E. Gerszten, Stephen S. Rich, Jerome I. Rotter, Laura J. Scott, Xiang Zhou, and Seunggeun Lee

Subjects
blood lipids, Multi-omics, proteome-wide association studies, transcriptome-wide association studies, Genetics, QH426-470
Abstract

Summary: Blood lipid traits are treatable and heritable risk factors for heart disease, a leading cause of mortality worldwide. Although genome-wide association studies (GWASs) have discovered hundreds of variants associated with lipids in humans, most of the causal mechanisms of lipids remain unknown. To better understand the biological processes underlying lipid metabolism, we investigated the associations of plasma protein levels with total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein (LDL) cholesterol in blood. We trained protein prediction models based on samples in the Multi-Ethnic Study of Atherosclerosis (MESA) and applied them to conduct proteome-wide association studies (PWASs) for lipids using the Global Lipids Genetics Consortium (GLGC) data. Of the 749 proteins tested, 42 were significantly associated with at least one lipid trait. Furthermore, we performed transcriptome-wide association studies (TWASs) for lipids using 9,714 gene expression prediction models trained on samples from peripheral blood mononuclear cells (PBMCs) in MESA and 49 tissues in the Genotype-Tissue Expression (GTEx) project. We found that although PWASs and TWASs can show different directions of associations in an individual gene, 40 out of 49 tissues showed a positive correlation between PWAS and TWAS signed p values across all the genes, which suggests high-level consistency between proteome-lipid associations and transcriptome-lipid associations.

Published
2025
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3. Lipid levels and risk of acute pancreatitis using bidirectional Mendelian randomization

Author

Biqi Wang, Jacqueline S. Dron, Yuxuan Wang, Seung Hoan Choi, Jennifer E. Huffman, Kelly Cho, Peter W. F. Wilson, Pradeep Natarajan, and Gina M. Peloso

Subjects
Lipids, Acute pancreatitis, Mendelian randomization, Medicine, Science
Abstract

Abstract Previous studies found lipid levels, especially triglycerides (TG), are associated with acute pancreatitis, but their causalities and bi-directions were not fully examined. We determined whether abnormal levels of TG, high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) are precursors and/or consequences of acute pancreatitis using bidirectional two-sample Mendelian randomization (MR) with two non-overlapping genome-wide association study (GWAS) summary statistics for lipid levels and acute pancreatitis. We found phenotypic associations that both higher TG levels and lower HDL-C levels contributed to increased risk of acute pancreatitis. Our GWAS meta-analysis of acute pancreatitis identified seven independent signals. Genetically predicted TG was positively associated with acute pancreatitis when using the variants specifically associated with TG using univariable MR [Odds ratio (OR), 95% CI 2.02, 1.22–3.31], but the reversed direction from acute pancreatitis to TG was not observed (mean difference = 0.003, SE = 0.002, P-value = 0.138). However, a bidirectional relationship of HDL-C and acute pancreatitis was observed: A 1-SD increment of genetically predicted HDL-C was associated with lower risk of acute pancreatitis (OR, 95% CI 0.84, 0.76–0.92) and genetically predisposed individuals with acute pancreatitis have, on average, 0.005 SD lower HDL-C (mean difference = − 0.005, SE = 0.002, P-value = 0.004). Our MR analysis confirms the evidence of TG as a risk factor of acute pancreatitis but not a consequence. A potential bidirectional relationship of HDL-C and acute pancreatitis occurs and raises the prospect of HDL-C modulation in the acute pancreatitis prevention and treatment.

Published
2024
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4. Expression quantitative trait methylation analysis elucidates gene regulatory effects of DNA methylation: the Framingham Heart Study

Author

Amena Keshawarz, Helena Bui, Roby Joehanes, Jiantao Ma, Chunyu Liu, Tianxiao Huan, Shih-Jen Hwang, Brandon Tejada, Meera Sooda, Paul Courchesne, Peter J. Munson, Cumhur Y. Demirkale, Chen Yao, Nancy L. Heard-Costa, Achilleas N. Pitsillides, Honghuang Lin, Ching-Ti Liu, Yuxuan Wang, Gina M. Peloso, Jessica Lundin, Jeffrey Haessler, Zhaohui Du, Michael Cho, Craig P. Hersh, Peter Castaldi, Laura M. Raffield, Jia Wen, Yun Li, Alexander P. Reiner, Mike Feolo, Nataliya Sharopova, Ramachandran S. Vasan, Dawn L. DeMeo, April P. Carson, Charles Kooperberg, and Daniel Levy

Subjects
Medicine, Science
Abstract

Abstract Expression quantitative trait methylation (eQTM) analysis identifies DNA CpG sites at which methylation is associated with gene expression. The present study describes an eQTM resource of CpG-transcript pairs derived from whole blood DNA methylation and RNA sequencing gene expression data in 2115 Framingham Heart Study participants. We identified 70,047 significant cis CpG-transcript pairs at p

Published
2023
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5. Genome-wide association analysis and Mendelian randomization proteomics identify drug targets for heart failure

Author

Danielle Rasooly, Gina M. Peloso, Alexandre C. Pereira, Hesam Dashti, Claudia Giambartolomei, Eleanor Wheeler, Nay Aung, Brian R. Ferolito, Maik Pietzner, Eric H. Farber-Eger, Quinn Stanton Wells, Nicole M. Kosik, Liam Gaziano, Daniel C. Posner, A. Patrícia Bento, Qin Hui, Chang Liu, Krishna Aragam, Zeyuan Wang, Brian Charest, Jennifer E. Huffman, Peter W. F. Wilson, Lawrence S. Phillips, John Whittaker, Patricia B. Munroe, Steffen E. Petersen, Kelly Cho, Andrew R. Leach, María Paula Magariños, John Michael Gaziano, VA Million Veteran Program, Claudia Langenberg, Yan V. Sun, Jacob Joseph, and Juan P. Casas

Subjects
Science
Abstract

Abstract We conduct a large-scale meta-analysis of heart failure genome-wide association studies (GWAS) consisting of over 90,000 heart failure cases and more than 1 million control individuals of European ancestry to uncover novel genetic determinants for heart failure. Using the GWAS results and blood protein quantitative loci, we perform Mendelian randomization and colocalization analyses on human proteins to provide putative causal evidence for the role of druggable proteins in the genesis of heart failure. We identify 39 genome-wide significant heart failure risk variants, of which 18 are previously unreported. Using a combination of Mendelian randomization proteomics and genetic cis-only colocalization analyses, we identify 10 additional putatively causal genes for heart failure. Findings from GWAS and Mendelian randomization-proteomics identify seven (CAMK2D, PRKD1, PRKD3, MAPK3, TNFSF12, APOC3 and NAE1) proteins as potential targets for interventions to be used in primary prevention of heart failure.

Published
2023
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6. Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Author

Stavroula Kanoni, Sarah E. Graham, Yuxuan Wang, Ida Surakka, Shweta Ramdas, Xiang Zhu, Shoa L. Clarke, Konain Fatima Bhatti, Sailaja Vedantam, Thomas W. Winkler, Adam E. Locke, Eirini Marouli, Greg J. M. Zajac, Kuan-Han H. Wu, Ioanna Ntalla, Qin Hui, Derek Klarin, Austin T. Hilliard, Zeyuan Wang, Chao Xue, Gudmar Thorleifsson, Anna Helgadottir, Daniel F. Gudbjartsson, Hilma Holm, Isleifur Olafsson, Mi Yeong Hwang, Sohee Han, Masato Akiyama, Saori Sakaue, Chikashi Terao, Masahiro Kanai, Wei Zhou, Ben M. Brumpton, Humaira Rasheed, Aki S. Havulinna, Yogasudha Veturi, Jennifer Allen Pacheco, Elisabeth A. Rosenthal, Todd Lingren, QiPing Feng, Iftikhar J. Kullo, Akira Narita, Jun Takayama, Hilary C. Martin, Karen A. Hunt, Bhavi Trivedi, Jeffrey Haessler, Franco Giulianini, Yuki Bradford, Jason E. Miller, Archie Campbell, Kuang Lin, Iona Y. Millwood, Asif Rasheed, George Hindy, Jessica D. Faul, Wei Zhao, David R. Weir, Constance Turman, Hongyan Huang, Mariaelisa Graff, Ananyo Choudhury, Dhriti Sengupta, Anubha Mahajan, Michael R. Brown, Weihua Zhang, Ketian Yu, Ellen M. Schmidt, Anita Pandit, Stefan Gustafsson, Xianyong Yin, Jian’an Luan, Jing-Hua Zhao, Fumihiko Matsuda, Hye-Mi Jang, Kyungheon Yoon, Carolina Medina-Gomez, Achilleas Pitsillides, Jouke Jan Hottenga, Andrew R. Wood, Yingji Ji, Zishan Gao, Simon Haworth, Noha A. Yousri, Ruth E. Mitchell, Jin Fang Chai, Mette Aadahl, Anne A. Bjerregaard, Jie Yao, Ani Manichaikul, Chii-Min Hwu, Yi-Jen Hung, Helen R. Warren, Julia Ramirez, Jette Bork-Jensen, Line L. Kårhus, Anuj Goel, Maria Sabater-Lleal, Raymond Noordam, Pala Mauro, Floris Matteo, Aaron F. McDaid, Pedro Marques-Vidal, Matthias Wielscher, Stella Trompet, Naveed Sattar, Line T. Møllehave, Matthias Munz, Lingyao Zeng, Jianfeng Huang, Bin Yang, Alaitz Poveda, Azra Kurbasic, Claudia Lamina, Lukas Forer, Markus Scholz, Tessel E. Galesloot, Jonathan P. Bradfield, Sanni E. Ruotsalainen, EWarwick Daw, Joseph M. Zmuda, Jonathan S. Mitchell, Christian Fuchsberger, Henry Christensen, Jennifer A. Brody, Miguel Vazquez-Moreno, Mary F. Feitosa, Mary K. Wojczynski, Zhe Wang, Michael H. Preuss, Massimo Mangino, Paraskevi Christofidou, Niek Verweij, Jan W. Benjamins, Jorgen Engmann, Noah L. Tsao, Anurag Verma, Roderick C. Slieker, Ken Sin Lo, Nuno R. Zilhao, Phuong Le, Marcus E. Kleber, Graciela E. Delgado, Shaofeng Huo, Daisuke D. Ikeda, Hiroyuki Iha, Jian Yang, Jun Liu, Ayşe Demirkan, Hampton L. Leonard, Jonathan Marten, Mirjam Frank, Börge Schmidt, Laura J. Smyth, Marisa Cañadas-Garre, Chaolong Wang, Masahiro Nakatochi, Andrew Wong, Nina Hutri-Kähönen, Xueling Sim, Rui Xia, Alicia Huerta-Chagoya, Juan Carlos Fernandez-Lopez, Valeriya Lyssenko, Suraj S. Nongmaithem, Swati Bayyana, Heather M. Stringham, Marguerite R. Irvin, Christopher Oldmeadow, Han-Na Kim, Seungho Ryu, Paul R. H. J. Timmers, Liubov Arbeeva, Rajkumar Dorajoo, Leslie A. Lange, Gauri Prasad, Laura Lorés-Motta, Marc Pauper, Jirong Long, Xiaohui Li, Elizabeth Theusch, Fumihiko Takeuchi, Cassandra N. Spracklen, Anu Loukola, Sailalitha Bollepalli, Sophie C. Warner, Ya Xing Wang, Wen B. Wei, Teresa Nutile, Daniela Ruggiero, Yun Ju Sung, Shufeng Chen, Fangchao Liu, Jingyun Yang, Katherine A. Kentistou, Bernhard Banas, Giuseppe Giovanni Nardone, Karina Meidtner, Lawrence F. Bielak, Jennifer A. Smith, Prashantha Hebbar, Aliki-Eleni Farmaki, Edith Hofer, Maoxuan Lin, Maria Pina Concas, Simona Vaccargiu, Peter J. van der Most, Niina Pitkänen, Brian E. Cade, Sander W. van der Laan, Kumaraswamy Naidu Chitrala, Stefan Weiss, Amy R. Bentley, Ayo P. Doumatey, Adebowale A. Adeyemo, Jong Young Lee, Eva R. B. Petersen, Aneta A. Nielsen, Hyeok Sun Choi, Maria Nethander, Sandra Freitag-Wolf, Lorraine Southam, Nigel W. Rayner, Carol A. Wang, Shih-Yi Lin, Jun-Sing Wang, Christian Couture, Leo-Pekka Lyytikäinen, Kjell Nikus, Gabriel Cuellar-Partida, Henrik Vestergaard, Bertha Hidalgo, Olga Giannakopoulou, Qiuyin Cai, Morgan O. Obura, Jessica van Setten, Xiaoyin Li, Jingjing Liang, Hua Tang, Natalie Terzikhan, Jae Hun Shin, Rebecca D. Jackson, Alexander P. Reiner, Lisa Warsinger Martin, Zhengming Chen, Liming Li, Takahisa Kawaguchi, Joachim Thiery, Joshua C. Bis, Lenore J. Launer, Huaixing Li, Mike A. Nalls, Olli T. Raitakari, Sahoko Ichihara, Sarah H. Wild, Christopher P. Nelson, Harry Campbell, Susanne Jäger, Toru Nabika, Fahd Al-Mulla, Harri Niinikoski, Peter S. Braund, Ivana Kolcic, Peter Kovacs, Tota Giardoglou, Tomohiro Katsuya, Dominique de Kleijn, Gert J. de Borst, Eung Kweon Kim, Hieab H. H. Adams, M. Arfan Ikram, Xiaofeng Zhu, Folkert W. Asselbergs, Adriaan O. Kraaijeveld, Joline W. J. Beulens, Xiao-Ou Shu, Loukianos S. Rallidis, Oluf Pedersen, Torben Hansen, Paul Mitchell, Alex W. Hewitt, Mika Kähönen, Louis Pérusse, Claude Bouchard, Anke Tönjes, Yii-Der Ida Chen, Craig E. Pennell, Trevor A. Mori, Wolfgang Lieb, Andre Franke, Claes Ohlsson, Dan Mellström, Yoon Shin Cho, Hyejin Lee, Jian-Min Yuan, Woon-Puay Koh, Sang Youl Rhee, Jeong-Taek Woo, Iris M. Heid, Klaus J. Stark, Martina E. Zimmermann, Henry Völzke, Georg Homuth, Michele K. Evans, Alan B. Zonderman, Ozren Polasek, Gerard Pasterkamp, Imo E. Hoefer, Susan Redline, Katja Pahkala, Albertine J. Oldehinkel, Harold Snieder, Ginevra Biino, Reinhold Schmidt, Helena Schmidt, Stefania Bandinelli, George Dedoussis, Thangavel Alphonse Thanaraj, Sharon L. R. Kardia, Patricia A. Peyser, Norihiro Kato, Matthias B. Schulze, Giorgia Girotto, Carsten A. Böger, Bettina Jung, Peter K. Joshi, David A. Bennett, Philip L. De Jager, Xiangfeng Lu, Vasiliki Mamakou, Morris Brown, Mark J. Caulfield, Patricia B. Munroe, Xiuqing Guo, Marina Ciullo, Jost B. Jonas, Nilesh J. Samani, Jaakko Kaprio, Päivi Pajukanta, Teresa Tusié-Luna, Carlos A. Aguilar-Salinas, Linda S. Adair, Sonny Augustin Bechayda, H. Janaka de Silva, Ananda R. Wickremasinghe, Ronald M. Krauss, Jer-Yuarn Wu, Wei Zheng, Anneke Iden Hollander, Dwaipayan Bharadwaj, Adolfo Correa, James G. Wilson, Lars Lind, Chew-Kiat Heng, Amanda E. Nelson, Yvonne M. Golightly, James F. Wilson, Brenda Penninx, Hyung-Lae Kim, John Attia, Rodney J. Scott, D. C. Rao, Donna K. Arnett, Steven C. Hunt, Mark Walker, Heikki A. Koistinen, Giriraj R. Chandak, Josep M. Mercader, Maria C. Costanzo, Dongkeun Jang, Noël P. Burtt, Clicerio Gonzalez Villalpando, Lorena Orozco, Myriam Fornage, EShyong Tai, Rob M. van Dam, Terho Lehtimäki, Nish Chaturvedi, Mitsuhiro Yokota, Jianjun Liu, Dermot F. Reilly, Amy Jayne McKnight, Frank Kee, Karl-Heinz Jöckel, Mark I. McCarthy, Colin N. A. Palmer, Veronique Vitart, Caroline Hayward, Eleanor Simonsick, Cornelia M. van Duijn, Zi-Bing Jin, Jia Qu, Haretsugu Hishigaki, Xu Lin, Winfried März, Vilmundur Gudnason, Jean-Claude Tardif, Guillaume Lettre, Leen M.‘t Hart, Petra J. M. Elders, Scott M. Damrauer, Meena Kumari, Mika Kivimaki, Pim van der Harst, Tim D. Spector, Ruth J. F. Loos, Michael A. Province, Esteban J. Parra, Miguel Cruz, Bruce M. Psaty, Ivan Brandslund, Peter P. Pramstaller, Charles N. Rotimi, Kaare Christensen, Samuli Ripatti, Elisabeth Widén, Hakon Hakonarson, Struan F. A. Grant, Lambertus A. L. M. Kiemeney, Jacqueline de Graaf, Markus Loeffler, Florian Kronenberg, Dongfeng Gu, Jeanette Erdmann, Heribert Schunkert, Paul W. Franks, Allan Linneberg, J. Wouter Jukema, Amit V. Khera, Minna Männikkö, Marjo-Riitta Jarvelin, Zoltan Kutalik, Cucca Francesco, Dennis O. Mook-Kanamori, Ko Willems van Dijk, Hugh Watkins, David P. Strachan, Niels Grarup, Peter Sever, Neil Poulter, Lee-Ming Chuang, Jerome I. Rotter, Thomas M. Dantoft, Fredrik Karpe, Matt J. Neville, Nicholas J. Timpson, Ching-Yu Cheng, Tien-Yin Wong, Chiea Chuen Khor, Hengtong Li, Charumathi Sabanayagam, Annette Peters, Christian Gieger, Andrew T. Hattersley, Nancy L. Pedersen, Patrik K. E. Magnusson, Dorret I. Boomsma, Allegonda H. M. Willemsen, LAdrienne Cupples, Joyce B. J. van Meurs, Mohsen Ghanbari, Penny Gordon-Larsen, Wei Huang, Young Jin Kim, Yasuharu Tabara, Nicholas J. Wareham, Claudia Langenberg, Eleftheria Zeggini, Johanna Kuusisto, Markku Laakso, Erik Ingelsson, Goncalo Abecasis, John C. Chambers, Jaspal S. Kooner, Paul S. de Vries, Alanna C. Morrison, Scott Hazelhurst, Michèle Ramsay, Kari E. North, Martha Daviglus, Peter Kraft, Nicholas G. Martin, John B. Whitfield, Shahid Abbas, Danish Saleheen, Robin G. Walters, Michael V. Holmes, Corri Black, Blair H. Smith, Aris Baras, Anne E. Justice, Julie E. Buring, Paul M. Ridker, Daniel I. Chasman, Charles Kooperberg, Gen Tamiya, Masayuki Yamamoto, David A. van Heel, Richard C. Trembath, Wei-Qi Wei, Gail P. Jarvik, Bahram Namjou, M. Geoffrey Hayes, Marylyn D. Ritchie, Pekka Jousilahti, Veikko Salomaa, Kristian Hveem, Bjørn Olav Åsvold, Michiaki Kubo, Yoichiro Kamatani, Yukinori Okada, Yoshinori Murakami, Bong-Jo Kim, Unnur Thorsteinsdottir, Kari Stefansson, Jifeng Zhang, YEugene Chen, Yuk-Lam Ho, Julie A. Lynch, Daniel J. Rader, Philip S. Tsao, Kyong-Mi Chang, Kelly Cho, Christopher J. O’Donnell, John M. Gaziano, Peter W. F. Wilson, Timothy M. Frayling, Joel N. Hirschhorn, Sekar Kathiresan, Karen L. Mohlke, Yan V. Sun, Andrew P. Morris, Michael Boehnke, Christopher D. Brown, Pradeep Natarajan, Panos Deloukas, Cristen J. Willer, Themistocles L. Assimes, and Gina M. Peloso

Subjects
Cholesterol, Lipids, Genetics, Genome-wide association study, GWAS, Biology (General), QH301-705.5, QH426-470
Abstract

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.

Published
2022
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7. Whole genome DNA and RNA sequencing of whole blood elucidates the genetic architecture of gene expression underlying a wide range of diseases

Author

Chunyu Liu, Roby Joehanes, Jiantao Ma, Yuxuan Wang, Xianbang Sun, Amena Keshawarz, Meera Sooda, Tianxiao Huan, Shih-Jen Hwang, Helena Bui, Brandon Tejada, Peter J. Munson, Cumhur Y. Demirkale, Nancy L. Heard-Costa, Achilleas N. Pitsillides, Gina M. Peloso, Michael Feolo, Nataliya Sharopova, Ramachandran S. Vasan, and Daniel Levy

Subjects
Medicine, Science
Abstract

Abstract To create a scientific resource of expression quantitative trail loci (eQTL), we conducted a genome-wide association study (GWAS) using genotypes obtained from whole genome sequencing (WGS) of DNA and gene expression levels from RNA sequencing (RNA-seq) of whole blood in 2622 participants in Framingham Heart Study. We identified 6,778,286 cis-eQTL variant-gene transcript (eGene) pairs at p

Published
2022
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8. Bayesian multivariate genetic analysis improves translational insights

Author

Sarah M. Urbut, Satoshi Koyama, Whitney Hornsby, Rohan Bhukar, Sumeet Kheterpal, Buu Truong, Margaret S. Selvaraj, Benjamin Neale, Christopher J. O’Donnell, Gina M. Peloso, and Pradeep Natarajan

Subjects
Human genetics, Biocomputational method, Computational bioinformatics, Genomic analysis, Association analysis, Science
Abstract

Summary: While lipid traits are known essential mediators of cardiovascular disease, few approaches have taken advantage of their shared genetic effects. We apply a Bayesian multivariate size estimator, mash, to GWAS of four lipid traits in the Million Veterans Program (MVP) and provide posterior mean and local false sign rates for all effects. These estimates borrow information across traits to improve effect size accuracy. We show that controlling local false sign rates accurately and powerfully identifies replicable genetic associations and that multivariate control furthers the ability to explain complex diseases. Our application yields high concordance between independent datasets, more accurately prioritizes causal genes, and significantly improves polygenic prediction beyond state-of-the-art methods by up to 59% for lipid traits. The use of Bayesian multivariate genetic shrinkage has yet to be applied to human quantitative trait GWAS results, and we present a staged approach to prediction on a polygenic scale.

Published
2023
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9. Genetic modification of inflammation- and clonal hematopoiesis–associated cardiovascular risk

Author

Zhi Yu, Trevor P. Fidler, Yunfeng Ruan, Caitlyn Vlasschaert, Tetsushi Nakao, Md Mesbah Uddin, Taralynn Mack, Abhishek Niroula, J. Brett Heimlich, Seyedeh M. Zekavat, Christopher J. Gibson, Gabriel K. Griffin, Yuxuan Wang, Gina M. Peloso, Nancy Heard-Costa, Daniel Levy, Ramachandran S. Vasan, François Aguet, Kristin G. Ardlie, Kent D. Taylor, Stephen S. Rich, Jerome I. Rotter, Peter Libby, Siddhartha Jaiswal, Benjamin L. Ebert, Alexander G. Bick, Alan R. Tall, and Pradeep Natarajan

Subjects
Cardiology, Genetics, Medicine
Abstract

Clonal hematopoiesis of indeterminate potential (CHIP) is associated with an increased risk of cardiovascular diseases (CVDs), putatively via inflammasome activation. We pursued an inflammatory gene modifier scan for CHIP-associated CVD risk among 424,651 UK Biobank participants. We identified CHIP using whole-exome sequencing data of blood DNA and modeled as a composite, considering all driver genes together, as well as separately for common drivers (DNMT3A, TET2, ASXL1, and JAK2). We developed predicted gene expression scores for 26 inflammasome-related genes and assessed how they modify CHIP-associated CVD risk. We identified IL1RAP as a potential key molecule for CHIP-associated CVD risk across genes and increased AIM2 gene expression leading to heightened JAK2- and ASXL1-associated CVD risk. We show that CRISPR-induced Asxl1-mutated murine macrophages had a particularly heightened inflammatory response to AIM2 agonism, associated with an increased DNA damage response, as well as increased IL-10 secretion, mirroring a CVD-protective effect of IL10 expression in ASXL1 CHIP. Our study supports the role of inflammasomes in CHIP-associated CVD and provides evidence to support gene-specific strategies to address CHIP-associated CVD risk.

Published
2023
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10. Whole genome sequence analysis of blood lipid levels in >66,000 individuals

Author

Margaret Sunitha Selvaraj, Xihao Li, Zilin Li, Akhil Pampana, David Y. Zhang, Joseph Park, Stella Aslibekyan, Joshua C. Bis, Jennifer A. Brody, Brian E. Cade, Lee-Ming Chuang, Ren-Hua Chung, Joanne E. Curran, Lisa de las Fuentes, Paul S. de Vries, Ravindranath Duggirala, Barry I. Freedman, Mariaelisa Graff, Xiuqing Guo, Nancy Heard-Costa, Bertha Hidalgo, Chii-Min Hwu, Marguerite R. Irvin, Tanika N. Kelly, Brian G. Kral, Leslie Lange, Xiaohui Li, Martin Lisa, Steven A. Lubitz, Ani W. Manichaikul, Preuss Michael, May E. Montasser, Alanna C. Morrison, Take Naseri, Jeffrey R. O’Connell, Nicholette D. Palmer, Patricia A. Peyser, Muagututia S. Reupena, Jennifer A. Smith, Xiao Sun, Kent D. Taylor, Russell P. Tracy, Michael Y. Tsai, Zhe Wang, Yuxuan Wang, Wei Bao, John T. Wilkins, Lisa R. Yanek, Wei Zhao, Donna K. Arnett, John Blangero, Eric Boerwinkle, Donald W. Bowden, Yii-Der Ida Chen, Adolfo Correa, L. Adrienne Cupples, Susan K. Dutcher, Patrick T. Ellinor, Myriam Fornage, Stacey Gabriel, Soren Germer, Richard Gibbs, Jiang He, Robert C. Kaplan, Sharon L. R. Kardia, Ryan Kim, Charles Kooperberg, Ruth J. F. Loos, Karine A Viaud-Martinez, Rasika A. Mathias, Stephen T. McGarvey, Braxton D. Mitchell, Deborah Nickerson, Kari E. North, Bruce M. Psaty, Susan Redline, Alexander P. Reiner, Ramachandran S. Vasan, Stephen S. Rich, Cristen Willer, Jerome I. Rotter, Daniel J. Rader, Xihong Lin, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Gina M. Peloso, and Pradeep Natarajan

Subjects
Science
Abstract

Although the common genetic variants contributing to blood lipid levels have been studied, the contribution of rare variants is less understood. Here, the authors perform a rare coding and noncoding variant association study of blood lipid levels using whole genome sequencing data.

Published
2022
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11. Non-linear machine learning models incorporating SNPs and PRS improve polygenic prediction in diverse human populations

Author

Michael Elgart, Genevieve Lyons, Santiago Romero-Brufau, Nuzulul Kurniansyah, Jennifer A. Brody, Xiuqing Guo, Henry J. Lin, Laura Raffield, Yan Gao, Han Chen, Paul de Vries, Donald M. Lloyd-Jones, Leslie A. Lange, Gina M. Peloso, Myriam Fornage, Jerome I. Rotter, Stephen S. Rich, Alanna C. Morrison, Bruce M. Psaty, Daniel Levy, Susan Redline, the NHLBI’s Trans-Omics in Precision Medicine (TOPMed) Consortium, and Tamar Sofer

Subjects
Biology (General), QH301-705.5
Abstract

Combining a standard polygenic risk score (PRS) as a feature in a machine learning model increases the percentage variance explained for those traits, helping to account for non-linearities or interaction effects in genetics-based prediction models.

Published
2022
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12. Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices

Author

Pradeep Natarajan, Akhil Pampana, Sarah E. Graham, Sanni E. Ruotsalainen, James A. Perry, Paul S. de Vries, Jai G. Broome, James P. Pirruccello, Michael C. Honigberg, Krishna Aragam, Brooke Wolford, Jennifer A. Brody, Lucinda Antonacci-Fulton, Moscati Arden, Stella Aslibekyan, Themistocles L. Assimes, Christie M. Ballantyne, Lawrence F. Bielak, Joshua C. Bis, Brian E. Cade, Ron Do, Harsha Doddapaneni, Leslie S. Emery, Yi-Jen Hung, Marguerite R. Irvin, Alyna T. Khan, Leslie Lange, Jiwon Lee, Rozenn N. Lemaitre, Lisa W. Martin, Ginger Metcalf, May E. Montasser, Jee-Young Moon, Donna Muzny, Jeffrey R. O’Connell, Nicholette D. Palmer, Juan M. Peralta, Patricia A. Peyser, Adrienne M. Stilp, Michael Tsai, Fei Fei Wang, Daniel E. Weeks, Lisa R. Yanek, James G. Wilson, Goncalo Abecasis, Donna K. Arnett, Lewis C. Becker, John Blangero, Eric Boerwinkle, Donald W. Bowden, Yi-Cheng Chang, Yii-Der I. Chen, Won Jung Choi, Adolfo Correa, Joanne E. Curran, Mark J. Daly, Susan K. Dutcher, Patrick T. Ellinor, Myriam Fornage, Barry I. Freedman, Stacey Gabriel, Soren Germer, Richard A. Gibbs, Jiang He, Kristian Hveem, Gail P. Jarvik, Robert C. Kaplan, Sharon L. R. Kardia, Eimear Kenny, Ryan W. Kim, Charles Kooperberg, Cathy C. Laurie, Seonwook Lee, Don M. Lloyd-Jones, Ruth J. F. Loos, Steven A. Lubitz, Rasika A. Mathias, Karine A. Viaud Martinez, Stephen T. McGarvey, Braxton D. Mitchell, Deborah A. Nickerson, Kari E. North, Aarno Palotie, Cheol Joo Park, Bruce M. Psaty, D. C. Rao, Susan Redline, Alexander P. Reiner, Daekwan Seo, Jeong-Sun Seo, Albert V. Smith, Russell P. Tracy, Ramachandran S. Vasan, Sekar Kathiresan, L. Adrienne Cupples, Jerome I. Rotter, Alanna C. Morrison, Stephen S. Rich, Samuli Ripatti, Cristen Willer, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, FinnGen, and Gina M. Peloso

Subjects
Science
Abstract

The influence of X chromosome genetic variation on blood lipids and coronary heart disease (CHD) is not well understood. Here, the authors analyse X chromosome sequencing data across 65,322 multi-ancestry individuals, identifying associations of the Xq23 locus with lipid changes and reduced risk of CHD and diabetes mellitus.

Published
2021
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13. Genetic Loci Associated With COVID-19 Positivity and Hospitalization in White, Black, and Hispanic Veterans of the VA Million Veteran Program

Author

Gina M. Peloso, Catherine Tcheandjieu, John E. McGeary, Daniel C. Posner, Yuk-Lam Ho, Jin J. Zhou, Austin T. Hilliard, Jacob Joseph, Christopher J. O’Donnell, Jimmy T. Efird, Dana C. Crawford, Wen-Chih Wu, Mehrdad Arjomandi, VA Million Veteran Program COVID-19 Science Initiative, Yan V. Sun, Themistocles L Assimes, and Jennifer E. Huffman

Subjects
COVID-19, genome-wide association study, million veteran program, hospitalization, ABO, Genetics, QH426-470
Abstract

SARS-CoV-2 has caused symptomatic COVID-19 and widespread death across the globe. We sought to determine genetic variants contributing to COVID-19 susceptibility and hospitalization in a large biobank linked to a national United States health system. We identified 19,168 (3.7%) lab-confirmed COVID-19 cases among Million Veteran Program participants between March 1, 2020, and February 2, 2021, including 11,778 Whites, 4,893 Blacks, and 2,497 Hispanics. A multi-population genome-wide association study (GWAS) for COVID-19 outcomes identified four independent genetic variants (rs8176719, rs73062389, rs60870724, and rs73910904) contributing to COVID-19 positivity, including one novel locus found exclusively among Hispanics. We replicated eight of nine previously reported genetic associations at an alpha of 0.05 in at least one population-specific or the multi-population meta-analysis for one of the four MVP COVID-19 outcomes. We used rs8176719 and three additional variants to accurately infer ABO blood types. We found that A, AB, and B blood types were associated with testing positive for COVID-19 compared with O blood type with the highest risk for the A blood group. We did not observe any genome-wide significant associations for COVID-19 severity outcomes among those testing positive. Our study replicates prior GWAS findings associated with testing positive for COVID-19 among mostly White samples and extends findings at three loci to Black and Hispanic individuals. We also report a new locus among Hispanics requiring further investigation. These findings may aid in the identification of novel therapeutic agents to decrease the morbidity and mortality of COVID-19 across all major ancestral populations.

Published
2022
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14. Genome-wide and phenome-wide analysis of ideal cardiovascular health in the VA Million Veteran Program

Author

Rose D. L. Huang, Xuan-Mai T. Nguyen, Gina M. Peloso, Mark Trinder, Daniel C. Posner, Krishna G. Aragam, Yuk-Lam Ho, Julie A. Lynch, Scott M. Damrauer, Kyong-Mi Chang, Philip S. Tsao, Pradeep Natarajan, Themistocles Assimes, J. Michael Gaziano, Luc Djousse, Kelly Cho, Peter W. F. Wilson, Jennifer E. Huffman, Christopher J. O’Donnell, and on behalf of the Veterans Affairs’ Million Veteran Program

Subjects
Medicine, Science
Abstract

Background Genetic studies may help identify causal pathways; therefore, we sought to identify genetic determinants of ideal CVH and their association with CVD outcomes in the multi-population Veteran Administration Million Veteran Program. Methods An ideal health score (IHS) was calculated from 3 clinical factors (blood pressure, total cholesterol, and blood glucose levels) and 3 behavioral factors (smoking status, physical activity, and BMI), ascertained at baseline. Multi-population genome-wide association study (GWAS) was performed on IHS and binary ideal health using linear and logistic regression, respectively. Using the genome-wide significant SNPs from the IHS GWAS, we created a weighted IHS polygenic risk score (PRSIHS) which was used (i) to conduct a phenome-wide association study (PheWAS) of associations between PRSIHS and ICD-9 phenotypes and (ii) to further test for associations with mortality and selected CVD outcomes using logistic and Cox regression and, as an instrumental variable, in Mendelian Randomization. Results The discovery and replication cohorts consisted of 142,404 (119,129 European American (EUR); 16,495 African American (AFR)), and 45,766 (37,646 EUR; 5,366 AFR) participants, respectively. The mean age was 65.8 years (SD = 11.2) and 92.7% were male. Overall, 4.2% exhibited ideal CVH based on the clinical and behavioral factors. In the multi-population meta-analysis, variants at 17 loci were associated with IHS and each had known GWAS associations with multiple components of the IHS. PheWAS analysis in 456,026 participants showed that increased PRSIHS was associated with a lower odds ratio for many CVD outcomes and risk factors. Both IHS and PRSIHS measures of ideal CVH were associated with significantly less CVD outcomes and CVD mortality. Conclusion A set of high interest genetic variants contribute to the presence of ideal CVH in a multi-ethnic cohort of US Veterans. Genetically influenced ideal CVH is associated with lower odds of CVD outcomes and mortality.

Published
2022

15. Genome-wide discovery for diabetes-dependent triglycerides-associated loci.

Author

Margaret Sunitha Selvaraj, Kaavya Paruchuri, Sara Haidermota, Rachel Bernardo, Stephen S Rich, Gina M Peloso, and Pradeep Natarajan

Subjects
Medicine, Science
Abstract

PurposeWe aimed to discover loci associated with triglyceride (TG) levels in the context of type 2 diabetes (T2D). We conducted a genome-wide association study (GWAS) in 424,120 genotyped participants of the UK Biobank (UKB) with T2D status and TG levels.MethodsWe stratified the cohort based on T2D status and conducted association analyses of TG levels for genetic variants with minor allele count (MAC) at least 20 in each stratum. Effect differences of genetic variants by T2D status were determined by Cochran's Q-test and we validated the significantly associated variants in the Mass General Brigham Biobank (MGBB).ResultsAmong 21,176 T2D and 402,944 non-T2D samples from UKB, stratified GWAS identified 19 and 315 genomic risk loci significantly associated with TG levels, respectively. Only chr6p21.32 exhibited genome-wide significant heterogeneity (I2 = 98.4%; pheterogeneity = 2.1x10-15), with log(TG) effect estimates of -0.066 (95%CI: -0.082, -0.050) and 0.002 (95%CI: -0.002, 0.006) for T2D and non-T2D, respectively. The lead variant rs9274619:A (allele frequency 0.095) is located 2Kb upstream of the HLA-DQB1 gene, between HLA-DQB1 and HLA-DQA2 genes. We replicated this finding among 25,137 participants (6,951 T2D cases) of MGBB (pheterogeneity = 9.5x10-3). Phenome-wide interaction association analyses showed that the lead variant was strongly associated with a concomitant diagnosis of type 1 diabetes (T1D) as well as diabetes-associated complications.ConclusionIn conclusion, we identified an intergenic variant near HLA-DQB1/DQA2 significantly associates with decreased triglycerides only among those with T2D and highlights an immune overlap with T1D.

Published
2022
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17. EDEM3 Modulates Plasma Triglyceride Level through Its Regulation of LRP1 Expression

Author

Yu-Xin Xu, Gina M. Peloso, Taylor H. Nagai, Taiji Mizoguchi, Amy Deik, Kevin Bullock, Honghuang Lin, Kiran Musunuru, Qiong Yang, Ramachandran S. Vasan, Robert E. Gerszten, Clary B. Clish, Daniel Rader, and Sekar Kathiresan

Subjects
Science
Abstract

Summary: Human genetics studies have uncovered genetic variants that can be used to guide biological research and prioritize molecular targets for therapeutic intervention for complex diseases. We have identified a missense variant (P746S) in EDEM3 associated with lower blood triglyceride (TG) levels in >300,000 individuals. Functional analyses in cell and mouse models show that EDEM3 deficiency strongly increased the uptake of very-low-density lipoprotein and thereby reduced the plasma TG level, as a result of up-regulated expression of LRP1 receptor. We demonstrate that EDEM3 deletion up-regulated the pathways for RNA and endoplasmic reticulum protein processing and transport, and consequently increased the cell surface mannose-containing glycoproteins, including LRP1. Metabolomics analyses reveal a cellular TG accumulation under EDEM3 deficiency, a profile consistent with individuals carrying EDEM3 P746S. Our study identifies EDEM3 as a regulator of blood TG, and targeted inhibition of EDEM3 may provide a complementary approach for lowering elevated blood TG concentrations. : Genetics; Diabetology; Specialized Functions of Cells; Metabolomics Subject Areas: Genetics, Diabetology, Specialized Functions of Cells, Metabolomics

Published
2020
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18. Beverage Consumption and Longitudinal Changes in Lipoprotein Concentrations and Incident Dyslipidemia in US Adults: The Framingham Heart Study

Author

Danielle E. Haslam, Gina M. Peloso, Mark A. Herman, Josée Dupuis, Alice H. Lichtenstein, Caren E. Smith, and Nicola M. McKeown

Subjects
carbohydrates, dyslipidemia, fruit juice, low‐calorie sweetened beverages, nutrition, observational study, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Background Limited data are available on the prospective relationship between beverage consumption and plasma lipid and lipoprotein concentrations. Two major sources of sugar in the US diet are sugar‐sweetened beverages (SSBs) and 100% fruit juices. Low‐calorie sweetened beverages are common replacements. Methods and Results Fasting plasma lipoprotein concentrations were measured in the FOS (Framingham Offspring Study) (1991–2014; N=3146) and Generation Three (2002–2001; N=3584) cohorts. Beverage intakes were estimated from food frequency questionnaires and grouped into 5 intake categories. Mixed‐effect linear regression models were used to examine 4‐year changes in lipoprotein measures, and Cox proportional hazard models were used to estimate hazard ratios for incident dyslipidemia, adjusting for potential confounding factors. We found that regular (>1 serving per day) versus low (

Published
2020
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19. Evaluation of a phenotype imputation approach using GAW20 simulated data

Author

Yuning Chen, Gina M. Peloso, and Josée Dupuis

Subjects
Medicine, Science
Abstract

Abstract Statistical power, which is the probability of correctly rejecting a false null hypothesis, is a limitation of genome-wide association studies (GWAS). Sample size is a major component of statistical power that can be easily affected by missingness in phenotypic data and restrain the ability to detect associated single-nucleotide polymorphisms (SNPs) with small effect sizes. Although some phenotypes are hard to collect because of cost and loss to follow-up, correlated phenotypes that are easily collected can be leveraged for association analysis. In this paper, we evaluate a phenotype imputation method that incorporates family structure and correlation between multiple phenotypes using GAW20 simulated data. The distribution of missing values is derived using information contained in the missing sample’s relatives and additional correlated phenotypes. We show that this imputation method can improve power in the association analysis compared with excluding observations with missing data, while achieving the correct Type I error rate. We also examine factors that may affect the imputation accuracy.

Published
2018
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20. Network analysis of drug effect on triglyceride-associated DNA methylation

Author

Elise Lim, Hanfei Xu, Peitao Wu, Daniel Posner, Jiayi Wu, Gina M. Peloso, Achilleas N. Pitsillides, Anita L. DeStefano, L. Adrienne Cupples, and Ching-Ti Liu

Subjects
Medicine, Science
Abstract

Abstract Background DNA methylation, an epigenetic modification, can be affected by environmental factors and thus regulate gene expression levels that can lead to alterations of certain phenotypes. Network analysis has been used successfully to discover gene sets that are expressed differently across multiple disease states and suggest possible pathways of disease progression. We applied this framework to compare DNA methylation levels before and after lipid-lowering medication and to identify modules that differ topologically between the two time points, revealing the association between lipid medication and these triglyceride-related methylation sites. Methods We performed quality control using beta-mixture quantile normalization on 463,995 cytosine-phosphate-guanine (CpG) sites and deleted problematic sites, resulting in 423,004 probes. We identified 14,850 probes that were nominally associated with triglycerides prior to treatment and performed weighted gene correlation network analysis (WGCNA) to construct pre- and posttreatment methylation networks of these probes. We then applied both WGCNA module preservation and generalized Hamming distance (GHD) to identify modules with topological differences between the pre- and posttreatment. For modules with structural changes between 2 time points, we performed pathway-enrichment analysis to gain further insight into the biological function of the genes from these modules. Results Six triglyceride-associated modules were identified using pretreatment methylation probes. The same 3 modules were not preserved in posttreatment data using both the module-preservation and the GHD methods. Top-enriched pathways for the 3 differentially methylated modules are sphingolipid signaling pathway, proteoglycans in cancer, and metabolic pathways (p values

Published
2018
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21. Deep-coverage whole genome sequences and blood lipids among 16,324 individuals

Author

Pradeep Natarajan, Gina M. Peloso, Seyedeh Maryam Zekavat, May Montasser, Andrea Ganna, Mark Chaffin, Amit V. Khera, Wei Zhou, Jonathan M. Bloom, Jesse M. Engreitz, Jason Ernst, Jeffrey R. O’Connell, Sanni E. Ruotsalainen, Maris Alver, Ani Manichaikul, W. Craig Johnson, James A. Perry, Timothy Poterba, Cotton Seed, Ida L. Surakka, Tonu Esko, Samuli Ripatti, Veikko Salomaa, Adolfo Correa, Ramachandran S. Vasan, Manolis Kellis, Benjamin M. Neale, Eric S. Lander, Goncalo Abecasis, Braxton Mitchell, Stephen S. Rich, James G. Wilson, L. Adrienne Cupples, Jerome I. Rotter, Cristen J. Willer, Sekar Kathiresan, and NHLBI TOPMed Lipids Working Group

Subjects
Science
Abstract

Common genetic variants associated with plasma lipids have been extensively studied for a better understanding of common diseases. Here, the authors use whole-genome sequencing of 16,324 individuals to analyze rare variant associations and to determine their monogenic and polygenic contribution to lipid traits.

Published
2018
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22. Deep coverage whole genome sequences and plasma lipoprotein(a) in individuals of European and African ancestries

Author

Seyedeh M. Zekavat, Sanni Ruotsalainen, Robert E. Handsaker, Maris Alver, Jonathan Bloom, Timothy Poterba, Cotton Seed, Jason Ernst, Mark Chaffin, Jesse Engreitz, Gina M. Peloso, Ani Manichaikul, Chaojie Yang, Kathleen A. Ryan, Mao Fu, W. Craig Johnson, Michael Tsai, Matthew Budoff, Ramachandran S. Vasan, L. Adrienne Cupples, Jerome I. Rotter, Stephen S. Rich, Wendy Post, Braxton D. Mitchell, Adolfo Correa, Andres Metspalu, James G. Wilson, Veikko Salomaa, Manolis Kellis, Mark J. Daly, Benjamin M. Neale, Steven McCarroll, Ida Surakka, Tonu Esko, Andrea Ganna, Samuli Ripatti, Sekar Kathiresan, Pradeep Natarajan, and NHLBI TOPMed Lipids Working Group

Subjects
Science
Abstract

Circulating lipoprotein(a) is an important risk factor for cardiovascular disease and shows variability between different ethnic groups. Here, Zekavat et al. perform whole-genome sequencing in individuals of European and African ancestries and find ancestry-specific genetic determinants for lipoprotein(a) levels.

Published
2018
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23. Genetically elevated high‐density lipoprotein cholesterol through the cholesteryl ester transfer protein gene does not associate with risk of Alzheimer's disease

Author

Gina M. Peloso, Sven J. van derLee, International Genomics of Alzheimer's Project (IGAP), R. Sims, S.J. van derLee, A.C. Naj, C. Bellenguez, N. Badarinarayan, J. Jakobsdottir, B.W. Kunkle, A. Boland, R. Raybould, J.C. Bis, E.R. Martin, B. Grenier‐Boley, S. Heilmann‐Heimbach, V. Chouraki, A.B. Kuzma, K. Sleegers, M. Vronskaya, A. Ruiz, R.R. Graham, R. Olaso, P. Hoffmann, M.L. Grove, B.N. Vardarajan, M. Hiltunen, M.M. Nöthen, C.C. White, K.L. Hamilton‐Nelson, J. Epelbaum, W. Maier, S.H. Choi, G.W. Beecham, C. Dulary, S. Herms, A.V. Smith, C.C. Funk, Derbois, A.J. Forstner, S. Ahmad, H. Li, D. Bacq, D. Harold, C.L. Satizabal, O. Valladares, A. Squassina, R. Thomas, J.A. Brody, L. Qu, P. Sánchez‐Juan, T. Morgan, F.J. Wolters, Y. Zhao, F.S. Garcia, N. Denning, M. Fornage, J. Malamon, M.C.D. Naranjo, E. Majounie, T.H. Mosley, B. Dombroski, D. Wallon, M.K. Lupton, J. Dupuis, P. Whitehead, L. Fratiglioni, C. Medway, X. Jian, S. Mukherjee, L. Keller, K. Brown, H. Lin, L.B. Cantwell, F. Panza, B. McGuinness, S. Moreno‐Grau, J.D. Burgess, V. Solfrizzi, P. Proitsi, H.H. Adams, M. Allen, D. Seripa, P. Pastor, L.A. Cupples, N.D. Price, D. Hannequin, A. Frank‐García, D. Levy, P. Chakrabarty, P. Caffarra, I. Giegling, A.S. Beiser, V. Giedraitis, H. Hampel, M.E. Garcia, X. Wang, L. Lannfelt, P. Mecocci, G. Eiriksdottir, P.K. Crane, F. Pasquier, V. Boccardi, I. Henández, R.C. Barber, M. Scherer, L. Tarraga, P.M. Adams, M. Leber, Y. Chen, M.S. Albert, S. Riedel‐Heller, V. Emilsson, D. Beekly, A. Braae, R. Schmidt, D. Blacker, C. Masullo, H. Schmidt, R.S. Doody, G. Spalletta, W.T. Longstreth Jr., T.J. Fairchild, P. Bossù, O.L. Lopez, M.P. Frosch, E. Sacchinelli, B. Ghetti, Q. Yang, R.M. Huebinger, F. Jessen, S. Li, M.I. Kamboh, J. Morris, O. Sotolongo‐Grau, M.J. Katz, C. Corcoran, M. Dunstan, A. Braddel, C. Thomas, A. Meggy, R. Marshall, A. Gerrish, J. Chapman, M. Aguilar, S. Taylor, M. Hill, M.D. Fairén, A. Hodges, B. Vellas, H. Soininen, I. Kloszewska, M. Daniilidou, J. Uphill, Y. Patel, J.T. Hughes, J. Lord, J. Turton, A.M. Hartmann, R. Cecchetti, C. Fenoglio, M. Serpente, M. Arcaro, C. Caltagirone, M.D. Orfei, A. Ciaramella, S. Pichler, M. Mayhaus, W. Gu, A. Lleó, J. Fortea, R. Blesa, I.S. Barber, K. Brookes, C. Cupidi, R.G. Maletta, D. Carrell, S. Sorbi, S. Moebus, M. Urbano, A. Pilotto, J. Kornhuber, P. Bosco, S. Todd, D. Craig, J. Johnston, M. Gill, B. Lawlor, A. Lynch, N.C. Fox, J. Hardy, ARUK Consortium, R.L. Albin, L.G. Apostolova, S.E. Arnold, S. Asthana, C.S. Atwood, C.T. Baldwin, L.L. Barnes, S. Barral, T.G. Beach, J.T. Becker, E.H. Bigio, T.D. Bird, B.F. Boeve, J.D. Bowen, A. Boxer, J.R. Burke, J.M. Burns, J.D. Buxbaum, N.J. Cairns, C. Cao, C.S. Carlson, C.M. Carlsson, R.M. Carney, M.M. Carrasquillo, S.L. Carroll, C.C. Diaz, H.C. Chui, D.G. Clark, D.H. Cribbs, E.A. Crocco, C. DeCarli, M. Dick, R. Duara, D.A. Evans, K.M. Faber, K.B. Fallon, D.W. Fardo, M.R. Farlow, S. Ferris, T.M. Foroud, D.R. Galasko, M. Gearing, D.H. Geschwind, J.R. Gilbert, N.R. Graff‐Radford, R.C. Green, J.H. Growdon, R.L. Hamilton, L.E. Harrell, L.S. Honig, M.J. Huentelman, C.M. Hulette, B.T. Hyman, G.P. Jarvik, E. Abner, L.W. Jin, G. Jun, A. Karydas, J.A. Kaye, R. Kim, N.W. Kowall, J.H. Kramer, F.M. LaFerla, J.J. Lah, J.B. Leverenz, A.I. Levey, G. Li, A.P. Lieberman, K.L. Lunetta, C.G. Lyketsos, D.C. Marson, F. Martiniuk, D.C. Mash, E. Masliah, W.C. McCormick, S.M. McCurry, A.N. McDavid, A.C. McKee, M. Mesulam, B.L. Miller, C.A. Miller, J.W. Miller, J.C. Morris, J.R. Murrell, A.J. Myers, S. O'Bryant, J.M. Olichney, V.S. Pankratz, J.E. Parisi, H.L. Paulson, W. Perry, E. Peskind, A. Pierce, W.W. Poon, H. Potter, J.F. Quinn, A. Raj, M. Raskind, B. Reisberg, C. Reitz, J.M. Ringman, E.D. Roberson, E. Rogaeva, H.J. Rosen, R.N. Rosenberg, M.A. Sager, A.J. Saykin, J.A. Schneider, L.S. Schneider, W.W. Seeley, A.G. Smith, J.A. Sonnen, S. Spina, R.A. Stern, R.H. Swerdlow, R.E. Tanzi, T.A. Thornton‐Wells, J.Q. Trojanowski, J.C. Troncoso, V.M. Van Deerlin, L.J. Van Eldik, H.V. Vinters, J.P. Vonsattel, S. Weintraub, K.A. Welsh‐Bohmer, K.C. Wilhelmsen, J. Williamson, T.S. Wingo, R.L. Woltjer, C.B. Wright, C.E. Yu, L. Yu, F. Garzia, F. Golamaully, G. Septier, S. Engelborghs, R. Vandenberghe, P.P. De Deyn, C.M. Fernadez, Y.A. Benito, H. Thonberg, C. Forsell, L. Lilius, A. Kinhult‐Stählbom, L. Kilander, R. Brundin, L. Concari, S. Helisalmi, A.M. Koivisto, A. Haapasalo, V. Dermecourt, N. Fievet, O. Hanon, C. Dufouil, A. Brice, K. Ritchie, B. Dubois, J.J. Himali, C.D. Keene, J. Tschanz, A.L. Fitzpatrick, W.A. Kukull, M. Norton, T. Aspelund, E.B. Larson, R. Munger, J.I. Rotter, R.B. Lipton, M.J. Bullido, A. Hofman, T.J. Montine, E. Coto, E. Boerwinkle, R.C. Petersen, V. Alvarez, F. Rivadeneira, E.M. Reiman, M. Gallo, C.J. O'Donnell, J.S. Reisch, A.C. Bruni, D.R. Royall, M. Dichgans, M. Sano, D. Galimberti, P. St George‐Hyslop, E. Scarpini, D.W. Tsuang, M. Mancuso, U. Bonuccelli, A.R. Winslow, A. Daniele, C.K. Wu, GERAD/PERADES, CHARGE, ADGC, EADI, O. Peters, B. Nacmias, M. Riemenschneider, R. Heun, C. Brayne, D.C. Rubinsztein, J. Bras, R. Guerreiro, A. Al‐Chalabi, C.E. Shaw, J. Collinge, D. Mann, M. Tsolaki, J. Clarimón, R. Sussams, S. Lovestone, M.C. O'Donovan, M.J. Owen, T.W. Behrens, S. Mead, A.M. Goate, A.G. Uitterlinden, C. Holmes, C. Cruchaga, M. Ingelsson, D.A. Bennett, J. Powell, T.E. Golde, C. Graff, P.L. De Jager, K. Morgan, N. Ertekin‐Taner, O. Combarros, B.M. Psaty, P. Passmore, S.G. Younkin, C. Berr, V. Gudnason, D. Rujescu, D.W. Dickson, J.F. Dartigues, A.L. DeStefano, S. Ortega‐Cubero, H. Hakonarson, D. Campion, M. Boada, J.K. Kauwe, L.A. Farrer, C. Van Broeckhoven, M.A. Ikram, L. Jones, J.L. Haines, C. Tzourio, L.J. Launer, V. Escott‐Price, R. Mayeux, J.F. Deleuze, N. Amin, P.A. Holmans, M.A. Pericak‐Vance, P. Amouyel, C.M. vanDuijn, A. Ramirez, L.S. Wang, J.C. Lambert, S. Seshadri, J. Williams, G.D. Schellenberg, Anita L. Destefano, and Sudha Seshardi

Subjects
Genetics, HDL‐C, Single nucleotide polymorphisms, Instrumental variables, Cholesteryl ester transfer protein, Neurology. Diseases of the nervous system, RC346-429, Geriatrics, RC952-954.6
Abstract

Abstract Introduction There is conflicting evidence whether high‐density lipoprotein cholesterol (HDL‐C) is a risk factor for Alzheimer's disease (AD) and dementia. Genetic variation in the cholesteryl ester transfer protein (CETP) locus is associated with altered HDL‐C. We aimed to assess AD risk by genetically predicted HDL‐C. Methods Ten single nucleotide polymorphisms within the CETP locus predicting HDL‐C were applied to the International Genomics of Alzheimer's Project (IGAP) exome chip stage 1 results in up 16,097 late onset AD cases and 18,077 cognitively normal elderly controls. We performed instrumental variables analysis using inverse variance weighting, weighted median, and MR‐Egger. Results Based on 10 single nucleotide polymorphisms distinctly predicting HDL‐C in the CETP locus, we found that HDL‐C was not associated with risk of AD (P > .7). Discussion Our study does not support the role of HDL‐C on risk of AD through HDL‐C altered by CETP. This study does not rule out other mechanisms by which HDL‐C affects risk of AD.

Published
2018
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24. Publisher Correction: Deep coverage whole genome sequences and plasma lipoprotein(a) in individuals of European and African ancestries

Author

Seyedeh M. Zekavat, Sanni Ruotsalainen, Robert E. Handsaker, Maris Alver, Jonathan Bloom, Timothy Poterba, Cotton Seed, Jason Ernst, Mark Chaffin, Jesse Engreitz, Gina M. Peloso, Ani Manichaikul, Chaojie Yang, Kathleen A. Ryan, Mao Fu, W. Craig Johnson, Michael Tsai, Matthew Budoff, Ramachandran S. Vasan, L. Adrienne Cupples, Jerome I. Rotter, Stephen S. Rich, Wendy Post, Braxton D. Mitchell, Adolfo Correa, Andres Metspalu, James G. Wilson, Veikko Salomaa, Manolis Kellis, Mark J. Daly, Benjamin M. Neale, Steven McCarroll, Ida Surakka, Tonu Esko, Andrea Ganna, Samuli Ripatti, Sekar Kathiresan, Pradeep Natarajan, and NHLBI TOPMed Lipids Working Group

Subjects
Science
Abstract

The original version of this article contained an error in the name of the author Ramachandran S. Vasan, which was incorrectly given as Vasan S. Ramachandran. This has now been corrected in both the PDF and HTML versions of the article.

Published
2018
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25. Publisher Correction: Deep coverage whole genome sequences and plasma lipoprotein(a) in individuals of European and African ancestries

Author

Seyedeh M. Zekavat, Sanni Ruotsalainen, Robert E. Handsaker, Maris Alver, Jonathan Bloom, Timothy Poterba, Cotton Seed, Jason Ernst, Mark Chaffin, Jesse Engreitz, Gina M. Peloso, Ani Manichaikul, Chaojie Yang, Kathleen A. Ryan, Mao Fu, W. Craig Johnson, Michael Tsai, Matthew Budoff, Ramachandran S. Vasan, L. Adrienne Cupples, Jerome I. Rotter, Stephen S. Rich, Wendy Post, Braxton D. Mitchell, Adolfo Correa, Andres Metspalu, James G. Wilson, Veikko Salomaa, Manolis Kellis, Mark J. Daly, Benjamin M. Neale, Steven McCarroll, Ida Surakka, Tonu Esko, Andrea Ganna, Samuli Ripatti, Sekar Kathiresan, Pradeep Natarajan, and NHLBI TOPMed Lipids Working Group

Subjects
Science
Abstract

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Published
2020
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26. History of Suicide Attempts and COVID-19 Infection in Veterans with Schizophrenia or Schizoaffective Disorder: Moderating Effects of Age and Body Mass Index

Author

Roseann E. Peterson, Olaoluwa O. Okusaga, Brian G. Mitchell, Jared D. Bernard, Gina M. Peloso, Tim B. Bigdeli, Rachel L. Kember, Annette Walder, and Marijana Vujkovic

Subjects
medicine.medical_specialty, Schizoaffective disorder, Coronavirus disease 2019 (COVID-19), business.industry, COVID-19, General Medicine, medicine.disease, Schizophrenia, medicine, Suicide attempt, business, Psychiatry, Body mass index, Research Article, Veterans
Abstract

Introduction: Relative to the general population, patients with schizophrenia or schizoaffective disorder have higher rates of suicide attempts and mortality from COVID-19 infection. Therefore, determining whether a history of suicide attempt is associated with COVID-19 in patients with schizophrenia or schizoaffective disorder has implications for COVID-19 vulnerability stratification in this patient population. Methods: We carried out cross-sectional analyses of electronic health records of veterans with a diagnosis of schizophrenia or schizoaffective disorder that received treatment at any United States Veterans Affairs Medical Center between January 1, 2020, and January 31, 2021. We used logistic regression to estimate unadjusted and adjusted (including age, sex, race, marital status, body mass index (BMI), and a medical comorbidity score) odds ratios (ORs) for COVID-19 positivity in suicide attempters relative to nonattempters. Results: A total of 101,032 veterans (mean age 56.67 ± 13.13 years; males 91,715 [90.8%]) were included in the analyses. There were 2,703 (2.7%) suicide attempters and 719 (0.7%) patients were positive for COVID-19. The association between history of suicide attempt and COVID-19 positivity was modified by age and BMI, such that the relationship was only significant in patients younger than 59 years, and in obese (BMI ≥30) patients (adjusted OR 3.42, 95% CI 2.02–5.79 and OR 2.85, 95% CI 1.65–4.94, respectively). Conclusions: Higher rates of COVID-19 in young or obese suicide attempters with a diagnosis of schizophrenia or schizoaffective disorder might be due to the elevated risk for the infection in this subgroup of patients.

Published
2021

27. Structured mating: Patterns and implications.

Author

Ronnie Sebro, Gina M Peloso, Josée Dupuis, and Neil J Risch

Subjects
Genetics, QH426-470
Abstract

Genetic similarity of spouses can reflect factors influencing mate choice, such as physical/behavioral characteristics, and patterns of social endogamy. Spouse correlations for both genetic ancestry and measured traits may impact genotype distributions (Hardy Weinberg and linkage equilibrium), and therefore genetic association studies. Here we evaluate white spouse-pairs from the Framingham Heart Study (FHS) original and offspring cohorts (N = 124 and 755, respectively) to explore spousal genetic similarity and its consequences. Two principal components (PCs) of the genome-wide association (GWA) data were identified, with the first (PC1) delineating clines of Northern/Western to Southern European ancestry and the second (PC2) delineating clines of Ashkenazi Jewish ancestry. In the original (older) cohort, there was a striking positive correlation between the spouses in PC1 (r = 0.73, P = 3x10(-22)) and also for PC2 (r = 0.80, P = 7x10(-29)). In the offspring cohort, the spouse correlations were lower but still highly significant for PC1 (r = 0.38, P = 7x10(-28)) and for PC2 (r = 0.45, P = 2x10(-39)). We observed significant Hardy-Weinberg disequilibrium for single nucleotide polymorphisms (SNPs) loading heavily on PC1 and PC2 across 3 generations, and also significant linkage disequilibrium between unlinked SNPs; both decreased with time, consistent with reduced ancestral endogamy over generations and congruent with theoretical calculations. Ignoring ancestry, estimates of spouse kinship have a mean significantly greater than 0, and more so in the earlier generations. Adjusting kinship estimates for genetic ancestry through the use of PCs led to a mean spouse kinship not different from 0, demonstrating that spouse genetic similarity could be fully attributed to ancestral assortative mating. These findings also have significance for studies of heritability that are based on distantly related individuals (kinship less than 0.05), as we also demonstrate the poor correlation of kinship estimates in that range when ancestry is or is not taken into account.

Published
2017
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28. Common genetic variation in multiple metabolic pathways influences susceptibility to low HDL-cholesterol and coronary heart disease[S]

Author

Gina M. Peloso, Serkalem Demissie, Dorothea Collins, Daniel B. Mirel, Stacey B. Gabriel, L. Adrienne Cupples, Sander J. Robins, Ernst J. Schaefer, and Margaret E. Brousseau

Subjects
genetics, high density lipoprotein cholesterol, candidate genes, Biochemistry, QD415-436
Abstract

A low level of HDL-C is the most common plasma lipid abnormality observed in men with established coronary heart disease (CHD). To identify allelic variants associated with susceptibility to low HDL-C and CHD, we examined 60 candidate genes with key roles in HDL metabolism, insulin resistance, and inflammation using samples from the Veterans Affairs HDL Intervention Trial (VA-HIT; cases, n = 699) and the Framingham Offspring Study (FOS; controls, n = 705). VA-HIT was designed to examine the benefits of HDL-raising with gemfibrozil in men with low HDL-C (≤40 mg/dl) and established CHD. After adjustment for multiple testing within each gene, single-nucleotide polymorphisms (SNP) significantly associated with case status were identified in the genes encoding LIPC (rs4775065, P < 0.0001); CETP (rs5882, P = 0.0002); RXRA (rs11185660, P = 0.0021); ABCA1 (rs2249891, P = 0.0126); ABCC6 (rs150468, P = 0.0206; rs212077, P = 0.0443); CUBN (rs7893395, P = 0.0246); APOA2 (rs3813627, P = 0.0324); SELP (rs732314, P = 0.0376); and APOC4 (rs10413089, P = 0.0425). Included among the novel findings of this study are the identification of susceptibility alleles for low HDL-C/CHD risk in the genes encoding CUBN and RXRA, and the observation that genetic variation in SELP may influence CHD risk through its effects on HDL.

Published
2010
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29. Rare coding variants in 35 genes associate with circulating lipid levels-A multi-ancestry analysis of 170,000 exomes

Author

George Hindy, Peter Dornbos, Mark D. Chaffin, Dajiang J. Liu, Minxian Wang, Margaret Sunitha Selvaraj, David Zhang, Joseph Park, Carlos A. Aguilar-Salinas, Lucinda Antonacci-Fulton, Diego Ardissino, Donna K. Arnett, Stella Aslibekyan, Gil Atzmon, Christie M. Ballantyne, Francisco Barajas-Olmos, Nir Barzilai, Lewis C. Becker, Lawrence F. Bielak, Joshua C. Bis, John Blangero, Eric Boerwinkle, Lori L. Bonnycastle, Erwin Bottinger, Donald W. Bowden, Matthew J. Bown, Jennifer A. Brody, Jai G. Broome, Noël P. Burtt, Brian E. Cade, Federico Centeno-Cruz, Edmund Chan, Yi-Cheng Chang, Yii-Der I. Chen, Ching-Yu Cheng, Won Jung Choi, Rajiv Chowdhury, Cecilia Contreras-Cubas, Emilio J. Córdova, Adolfo Correa, L. Adrienne Cupples, Joanne E. Curran, John Danesh, Paul S. de Vries, Ralph A. DeFronzo, Harsha Doddapaneni, Ravindranath Duggirala, Susan K. Dutcher, Patrick T. Ellinor, Leslie S. Emery, Jose C. Florez, Myriam Fornage, Barry I. Freedman, Valentin Fuster, Ma. Eugenia Garay-Sevilla, Humberto García-Ortiz, Soren Germer, Richard A. Gibbs, Christian Gieger, Benjamin Glaser, Clicerio Gonzalez, Maria Elena Gonzalez-Villalpando, Mariaelisa Graff, Sarah E. Graham, Niels Grarup, Leif C. Groop, Xiuqing Guo, Namrata Gupta, Sohee Han, Craig L. Hanis, Torben Hansen, Jiang He, Nancy L. Heard-Costa, Yi-Jen Hung, Mi Yeong Hwang, Marguerite R. Irvin, Sergio Islas-Andrade, Gail P. Jarvik, Hyun Min Kang, Sharon L.R. Kardia, Tanika Kelly, Eimear E. Kenny, Alyna T. Khan, Bong-Jo Kim, Ryan W. Kim, Young Jin Kim, Heikki A. Koistinen, Charles Kooperberg, Johanna Kuusisto, Soo Heon Kwak, Markku Laakso, Leslie A. Lange, Jiwon Lee, Juyoung Lee, Seonwook Lee, Donna M. Lehman, Rozenn N. Lemaitre, Allan Linneberg, Jianjun Liu, Ruth J.F. Loos, Steven A. Lubitz, Valeriya Lyssenko, Ronald C.W. Ma, Lisa Warsinger Martin, Angélica Martínez-Hernández, Rasika A. Mathias, Stephen T. McGarvey, Ruth McPherson, James B. Meigs, Thomas Meitinger, Olle Melander, Elvia Mendoza-Caamal, Ginger A. Metcalf, Xuenan Mi, Karen L. Mohlke, May E. Montasser, Jee-Young Moon, Hortensia Moreno-Macías, Alanna C. Morrison, Donna M. Muzny, Sarah C. Nelson, Peter M. Nilsson, Jeffrey R. O’Connell, Marju Orho-Melander, Lorena Orozco, Colin N.A. Palmer, Nicholette D. Palmer, Cheol Joo Park, Kyong Soo Park, Oluf Pedersen, Juan M. Peralta, Patricia A. Peyser, Wendy S. Post, Michael Preuss, Bruce M. Psaty, Qibin Qi, D.C. Rao, Susan Redline, Alexander P. Reiner, Cristina Revilla-Monsalve, Stephen S. Rich, Nilesh Samani, Heribert Schunkert, Claudia Schurmann, Daekwan Seo, Jeong-Sun Seo, Xueling Sim, Rob Sladek, Kerrin S. Small, Wing Yee So, Adrienne M. Stilp, E. Shyong Tai, Claudia H.T. Tam, Kent D. Taylor, Yik Ying Teo, Farook Thameem, Brian Tomlinson, Michael Y. Tsai, Tiinamaija Tuomi, Jaakko Tuomilehto, Teresa Tusié-Luna, Miriam S. Udler, Rob M. van Dam, Ramachandran S. Vasan, Karine A. Viaud Martinez, Fei Fei Wang, Xuzhi Wang, Hugh Watkins, Daniel E. Weeks, James G. Wilson, Daniel R. Witte, Tien-Yin Wong, Lisa R. Yanek, Sekar Kathiresan, Daniel J. Rader, Jerome I. Rotter, Michael Boehnke, Mark I. McCarthy, Cristen J. Willer, Pradeep Natarajan, Jason A. Flannick, Amit V. Khera, Gina M. Peloso, NIH - National Heart, Lung, and Blood Institute (NHLBI) (Estados Unidos), Centre of Excellence in Complex Disease Genetics, HUS Abdominal Center, Institute for Molecular Medicine Finland, Leif Groop Research Group, Clinicum, Department of Medicine, HUS Internal Medicine and Rehabilitation, University of Helsinki, and Department of Public Health

Subjects
APOC3, Blood Glucose, Multifactorial Inheritance, gene-based association, Polymorphism, Single Nucleotide, Article, Open Reading Frames, ANGPTL3, lipid, OF-FUNCTION MUTATIONS, BINDING, Databases, Genetic, SEQUENCE VARIANTS, Genetics, Humans, Exome, Genetic Predisposition to Disease, SINUSOIDAL ENDOTHELIAL-CELLS, Genetics (clinical), Alleles, RISK, IDENTIFICATION, 1184 Genetics, developmental biology, physiology, association, cholesterol, Genetic Variation, Computational Biology, Molecular Sequence Annotation, PERILIPIN, Lipid Metabolism, Lipids, Genetics, Population, Phenotype, Diabetes Mellitus, Type 2, Liver, Case-Control Studies, exome sequencing, TRIGLYCERIDES, Genome-Wide Association Study
Abstract

Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels. This work was supported by a grant from the Swedish Research Council (2016-06830) and grants from the National Heart, Lung, and Blood Institute (NHLBI): R01HL142711 and R01HL127564. Please refer to the supplemental information for the full acknowledgements. Sí

Published
2022
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30. Systematic cell-based phenotyping of missense alleles empowers rare variant association studies: a case for LDLR and myocardial infarction.

Author

Aenne S Thormaehlen, Christian Schuberth, Hong-Hee Won, Peter Blattmann, Brigitte Joggerst-Thomalla, Susanne Theiss, Rosanna Asselta, Stefano Duga, Pier Angelica Merlini, Diego Ardissino, Eric S Lander, Stacey Gabriel, Daniel J Rader, Gina M Peloso, Rainer Pepperkok, Sekar Kathiresan, and Heiko Runz

Subjects
Genetics, QH426-470
Abstract

A fundamental challenge to contemporary genetics is to distinguish rare missense alleles that disrupt protein functions from the majority of alleles neutral on protein activities. High-throughput experimental tools to securely discriminate between disruptive and non-disruptive missense alleles are currently missing. Here we establish a scalable cell-based strategy to profile the biological effects and likely disease relevance of rare missense variants in vitro. We apply this strategy to systematically characterize missense alleles in the low-density lipoprotein receptor (LDLR) gene identified through exome sequencing of 3,235 individuals and exome-chip profiling of 39,186 individuals. Our strategy reliably identifies disruptive missense alleles, and disruptive-allele carriers have higher plasma LDL-cholesterol (LDL-C). Importantly, considering experimental data refined the risk of rare LDLR allele carriers from 4.5- to 25.3-fold for high LDL-C, and from 2.1- to 20-fold for early-onset myocardial infarction. Our study generates proof-of-concept that systematic functional variant profiling may empower rare variant-association studies by orders of magnitude.

Published
2015
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31. A system for phenotype harmonization in the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) program

Author

Tanika N. Kelly, May E Montasser, Alyna T. Khan, Laura M. Raffield, Carla Wilson, Elizabeth C. Oelsner, Kerri L. Wiggins, Ming-Huei Chen, Gina M. Peloso, Adolfo Correa, Andrew D. Johnson, Donna K. Arnett, Xiuqing Guo, Jai G. Broome, Daniel E. Weeks, Rebecca D. Jackson, Lucia Juarez, Stephen T. McGarvey, Pradeep Natarajan, Braxton D. Mitchell, Kent D. Taylor, Bruce M. Psaty, Santhi K Ganesh, Cathy C. Laurie, Nicola L. Hawley, Leslie S. Emery, Adrienne M. Stilp, Alanna C. Morrison, Jennifer A Smith, Charles Kooperberg, Catherine M. D’Augustine, Jan Graffelman, Paul S. de Vries, Chancellor Hohensee, Sharon L R Kardia, Patricia A Peyser, Wan-Ling Hsu, Erin J Buth, Kathleen C. Barnes, Susan R. Heckbert, Ramachandran S. Vasan, Nathan Pankratz, Karen M. Mutalik, Quenna Wong, Brian E. Cade, Jingmin Liu, Joshua C. Bis, Cecelia A. Laurie, Kari E. North, Fei Fei Wang, Mariza de Andrade, Nancy L. Heard-Costa, William Craig Johnson, L. Adrienne Cupples, Scott T. Weiss, Seyed Mehdi Nouraie, Patrick T. Ellinor, Jerome I. Rotter, Weiniu Gan, Shannon Kelly, Stephen S. Rich, Cashell E. Jaquish, Dongquan Chen, Nora Franceschini, Lisa R. Yanek, Jiwon Lee, Alexander P. Reiner, Megan L. Grove, Stella Aslibekyan, Myriam Fornage, Lawrence F Bielak, Rasika A. Mathias, Universitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa, and Universitat Politècnica de Catalunya. COSDA-UPC - COmpositional and Spatial Data Analysis

Subjects
0301 basic medicine, Program evaluation, Computer science, Epidemiology, common data elements, hematologic disease, Matemàtiques i estadística::Matemàtica aplicada a les ciències [Àrees temàtiques de la UPC], Medical and Health Sciences, Mathematical Sciences, 0302 clinical medicine, Documentation, cardiovascular disease, and Blood Institute (U.S.), 030212 general & internal medicine, Phenomics, Precision Medicine, Lung, lung diseases, Sleep-wake disorders, phenotypes, 92 Biology and other natural sciences::92B Mathematical biology in general [Classificació AMS], Common data elements, Cardiovascular disease, Phenotype, Phenotypes, Biomatemàtica, Information Dissemination, Harmonization, 62 Statistics::62D05 Sampling theory, sample surveys [Classificació AMS], Hematologic disease, 03 medical and health sciences, Data Aggregation, Clinical Research, Controlled vocabulary, Genetics, Humans, AcademicSubjects/MED00860, sleep-wake disorders, Sampling (Statistics), Genetic Association Studies, Lung diseases, Biomathematics, Data collection, Study Design, Matemàtiques i estadística::Estadística aplicada::Estadística biosanitària [Àrees temàtiques de la UPC], Information dissemination, Human Genome, National Heart, Precision medicine, Data science, United States, 030104 developmental biology, Good Health and Well Being, National Heart, Lung, and Blood Institute (U.S.), Mostreig (Estadística), Program Evaluation
Abstract

Genotype-phenotype association studies often combine phenotype data from multiple studies to increase statistical power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data-set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data-sharing mechanisms. This system was developed for the National Heart, Lung, and Blood Institute’s Trans-Omics for Precision Medicine (TOPMed) program, which is generating genomic and other -omics data for more than 80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants (recruited in 1948–2012) from up to 17 studies per phenotype. Here we discuss challenges in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include 1) the software code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify, or extend these harmonizations to additional studies, and 2) the results of labeling thousands of phenotype variables with controlled vocabulary terms.

Published
2021

32. Best practices and joint calling of the HumanExome BeadChip: the CHARGE Consortium.

Author

Megan L Grove, Bing Yu, Barbara J Cochran, Talin Haritunians, Joshua C Bis, Kent D Taylor, Mark Hansen, Ingrid B Borecki, L Adrienne Cupples, Myriam Fornage, Vilmundur Gudnason, Tamara B Harris, Sekar Kathiresan, Robert Kraaij, Lenore J Launer, Daniel Levy, Yongmei Liu, Thomas Mosley, Gina M Peloso, Bruce M Psaty, Stephen S Rich, Fernando Rivadeneira, David S Siscovick, Albert V Smith, Andre Uitterlinden, Cornelia M van Duijn, James G Wilson, Christopher J O'Donnell, Jerome I Rotter, and Eric Boerwinkle

Subjects
Medicine, Science
Abstract

Genotyping arrays are a cost effective approach when typing previously-identified genetic polymorphisms in large numbers of samples. One limitation of genotyping arrays with rare variants (e.g., minor allele frequency [MAF]

Published
2013
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33. Publisher Correction: Deep coverage whole genome sequences and plasma lipoprotein(a) in individuals of European and African ancestries

Author

Adolfo Correa, Sekar Kathiresan, James G. Wilson, Jonathan M. Bloom, Ramachandran S. Vasan, Steven A. McCarroll, Mark Chaffin, Benjamin M. Neale, Jason Ernst, Braxton D. Mitchell, Mao Fu, Mark J. Daly, Timothy Poterba, Stephen S. Rich, Jerome I. Rotter, Jesse M. Engreitz, Ida Surakka, Veikko Salomaa, Pradeep Natarajan, Samuli Ripatti, Robert E. Handsaker, Matthew J. Budoff, Andrea Ganna, Tõnu Esko, Wendy S. Post, Andres Metspalu, Gina M. Peloso, Sanni Ruotsalainen, L. Adrienne Cupples, Chaojie Yang, Kathleen A. Ryan, Maris Alver, W. Craig Johnson, Seyedeh M. Zekavat, Michael Y. Tsai, Manolis Kellis, Ani Manichaikul, and Cotton Seed

Subjects
Plasma lipoprotein, DNA Copy Number Variations, Population genetics, Science, Quantitative Trait Loci, General Physics and Astronomy, Black People, Gene Expression, Computational biology, 01 natural sciences, Genome, Polymorphism, Single Nucleotide, General Biochemistry, Genetics and Molecular Biology, White People, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Humans, 030212 general & internal medicine, 0101 mathematics, lcsh:Science, 030304 developmental biology, Genetic association study, 0303 health sciences, Multidisciplinary, Whole Genome Sequencing, Genome, Human, Published Erratum, 010102 general mathematics, General Chemistry, Cholesterol, LDL, Atherosclerosis, Publisher Correction, NHLBI TOPMed Lipids Working Group, Adaptor Proteins, Vesicular Transport, Geography, Cardiovascular Diseases, 030220 oncology & carcinogenesis, ComputingMethodologies_DOCUMENTANDTEXTPROCESSING, lcsh:Q, Fat metabolism, Ramachandran plot, Genome-Wide Association Study, Lipoprotein(a)
Abstract

Lipoprotein(a), Lp(a), is a modified low-density lipoprotein particle that contains apolipoprotein(a), encoded by LPA, and is a highly heritable, causal risk factor for cardiovascular diseases that varies in concentrations across ancestries. Here, we use deep-coverage whole genome sequencing in 8392 individuals of European and African ancestry to discover and interpret both single-nucleotide variants and copy number (CN) variation associated with Lp(a). We observe that genetic determinants between Europeans and Africans have several unique determinants. The common variant rs12740374 associated with Lp(a) cholesterol is an eQTL for SORT1 and independent of LDL cholesterol. Observed associations of aggregates of rare non-coding variants are largely explained by LPA structural variation, namely the LPA kringle IV 2 (KIV2)-CN. Finally, we find that LPA risk genotypes confer greater relative risk for incident atherosclerotic cardiovascular diseases compared to directly measured Lp(a), and are significantly associated with measures of subclinical atherosclerosis in African Americans.

Published
2020

34. Beverage Consumption and Longitudinal Changes in Lipoprotein Concentrations and Incident Dyslipidemia in US Adults: The Framingham Heart Study

Author

Gina M. Peloso, Josée Dupuis, Nicola M. McKeown, Caren E. Smith, Danielle E. Haslam, Mark A. Herman, and Alice H. Lichtenstein

Subjects
Adult, Epidemiology, Lipoproteins, carbohydrates, 030204 cardiovascular system & hematology, fruit juice, Beverages, 03 medical and health sciences, 0302 clinical medicine, Framingham Heart Study, Dietary Sucrose, Plasma lipids, medicine, Humans, 030212 general & internal medicine, Food science, Longitudinal Studies, Sugar, Original Research, Diet and Nutrition, Dyslipidemias, Sugar-Sweetened Beverages, Beverage consumption, Lipids and Cholesterol, business.industry, dyslipidemia, medicine.disease, Lipids, low‐calorie sweetened beverages, sugar‐sweetened beverages, nutrition, Fruit juice, observational study, Cardiology and Cardiovascular Medicine, business, Dyslipidemia, Lipoprotein
Abstract

Background Limited data are available on the prospective relationship between beverage consumption and plasma lipid and lipoprotein concentrations. Two major sources of sugar in the US diet are sugar‐sweetened beverages ( SSBs ) and 100% fruit juices. Low‐calorie sweetened beverages are common replacements. Methods and Results Fasting plasma lipoprotein concentrations were measured in the FOS (Framingham Offspring Study) (1991–2014; N=3146) and Generation Three (2002–2001; N=3584) cohorts. Beverage intakes were estimated from food frequency questionnaires and grouped into 5 intake categories. Mixed‐effect linear regression models were used to examine 4‐year changes in lipoprotein measures, and Cox proportional hazard models were used to estimate hazard ratios for incident dyslipidemia, adjusting for potential confounding factors. We found that regular (>1 serving per day) versus low (SSB consumption was associated with a greater mean decrease in high‐density lipoprotein cholesterol (β±standard error −1.6±0.4 mg/dL; P trend P trend =0.003) concentrations. Long‐term regular SSB consumers also had a higher incidence of high triglyceride (hazard ratio, 1.52; 95% CI, 1.03–2.25) compared with low consumers. Although recent regular low‐calorie sweetened beverage consumers had a higher incidence of high non–high‐density lipoprotein cholesterol (hazard ratio, 1.40; 95% CI , 1.17–1.69) and low‐density lipoprotein cholesterol (hazard ratio, 1.27; 95% CI, 1.05–1.53) concentrations compared with low consumers, cumulative average intakes of low‐calorie sweetened beverages were not associated with changes in non–high‐density lipoprotein cholesterol, low‐density lipoprotein cholesterol concentrations, or incident dyslipidemias. Conclusions SSB intake was associated with adverse changes in high‐density lipoprotein cholesterol and triglyceride concentrations, along with a higher risk of incident dyslipidemia, suggesting that increased SSB consumption may contribute to the development of dyslipidemia.

Published
2020

35. Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals.

Author

Zari Dastani, Marie-France Hivert, Nicholas Timpson, John R B Perry, Xin Yuan, Robert A Scott, Peter Henneman, Iris M Heid, Jorge R Kizer, Leo-Pekka Lyytikäinen, Christian Fuchsberger, Toshiko Tanaka, Andrew P Morris, Kerrin Small, Aaron Isaacs, Marian Beekman, Stefan Coassin, Kurt Lohman, Lu Qi, Stavroula Kanoni, James S Pankow, Hae-Won Uh, Ying Wu, Aurelian Bidulescu, Laura J Rasmussen-Torvik, Celia M T Greenwood, Martin Ladouceur, Jonna Grimsby, Alisa K Manning, Ching-Ti Liu, Jaspal Kooner, Vincent E Mooser, Peter Vollenweider, Karen A Kapur, John Chambers, Nicholas J Wareham, Claudia Langenberg, Rune Frants, Ko Willems-Vandijk, Ben A Oostra, Sara M Willems, Claudia Lamina, Thomas W Winkler, Bruce M Psaty, Russell P Tracy, Jennifer Brody, Ida Chen, Jorma Viikari, Mika Kähönen, Peter P Pramstaller, David M Evans, Beate St Pourcain, Naveed Sattar, Andrew R Wood, Stefania Bandinelli, Olga D Carlson, Josephine M Egan, Stefan Böhringer, Diana van Heemst, Lyudmyla Kedenko, Kati Kristiansson, Marja-Liisa Nuotio, Britt-Marie Loo, Tamara Harris, Melissa Garcia, Alka Kanaya, Margot Haun, Norman Klopp, H-Erich Wichmann, Panos Deloukas, Efi Katsareli, David J Couper, Bruce B Duncan, Margreet Kloppenburg, Linda S Adair, Judith B Borja, DIAGRAM+ Consortium, MAGIC Consortium, GLGC Investigators, MuTHER Consortium, James G Wilson, Solomon Musani, Xiuqing Guo, Toby Johnson, Robert Semple, Tanya M Teslovich, Matthew A Allison, Susan Redline, Sarah G Buxbaum, Karen L Mohlke, Ingrid Meulenbelt, Christie M Ballantyne, George V Dedoussis, Frank B Hu, Yongmei Liu, Bernhard Paulweber, Timothy D Spector, P Eline Slagboom, Luigi Ferrucci, Antti Jula, Markus Perola, Olli Raitakari, Jose C Florez, Veikko Salomaa, Johan G Eriksson, Timothy M Frayling, Andrew A Hicks, Terho Lehtimäki, George Davey Smith, David S Siscovick, Florian Kronenberg, Cornelia van Duijn, Ruth J F Loos, Dawn M Waterworth, James B Meigs, Josee Dupuis, J Brent Richards, Benjamin F Voight, Laura J Scott, Valgerdur Steinthorsdottir, Christian Dina, Ryan P Welch, Eleftheria Zeggini, Cornelia Huth, Yurii S Aulchenko, Gudmar Thorleifsson, Laura J McCulloch, Teresa Ferreira, Harald Grallert, Najaf Amin, Guanming Wu, Cristen J Willer, Soumya Raychaudhuri, Steve A McCarroll, Oliver M Hofmann, Ayellet V Segrè, Mandy van Hoek, Pau Navarro, Kristin Ardlie, Beverley Balkau, Rafn Benediktsson, Amanda J Bennett, Roza Blagieva, Eric Boerwinkle, Lori L Bonnycastle, Kristina Bengtsson Boström, Bert Bravenboer, Suzannah Bumpstead, Noël P Burtt, Guillaume Charpentier, Peter S Chines, Marilyn Cornelis, Gabe Crawford, Alex S F Doney, Katherine S Elliott, Amanda L Elliott, Michael R Erdos, Caroline S Fox, Christopher S Franklin, Martha Ganser, Christian Gieger, Niels Grarup, Todd Green, Simon Griffin, Christopher J Groves, Candace Guiducci, Samy Hadjadj, Neelam Hassanali, Christian Herder, Bo Isomaa, Anne U Jackson, Paul R V Johnson, Torben Jørgensen, Wen H L Kao, Augustine Kong, Peter Kraft, Johanna Kuusisto, Torsten Lauritzen, Man Li, Aloysius Lieverse, Cecilia M Lindgren, Valeriya Lyssenko, Michel Marre, Thomas Meitinger, Kristian Midthjell, Mario A Morken, Narisu Narisu, Peter Nilsson, Katharine R Owen, Felicity Payne, Ann-Kristin Petersen, Carl Platou, Christine Proença, Inga Prokopenko, Wolfgang Rathmann, N William Rayner, Neil R Robertson, Ghislain Rocheleau, Michael Roden, Michael J Sampson, Richa Saxena, Beverley M Shields, Peter Shrader, Gunnar Sigurdsson, Thomas Sparsø, Klaus Strassburger, Heather M Stringham, Qi Sun, Amy J Swift, Barbara Thorand, Jean Tichet, Tiinamaija Tuomi, Rob M van Dam, Timon W van Haeften, Thijs van Herpt, Jana V van Vliet-Ostaptchouk, G Bragi Walters, Michael N Weedon, Cisca Wijmenga, Jacqueline Witteman, Richard N Bergman, Stephane Cauchi, Francis S Collins, Anna L Gloyn, Ulf Gyllensten, Torben Hansen, Winston A Hide, Graham A Hitman, Albert Hofman, David J Hunter, Kristian Hveem, Markku Laakso, Andrew D Morris, Colin N A Palmer, Igor Rudan, Eric Sijbrands, Lincoln D Stein, Jaakko Tuomilehto, Andre Uitterlinden, Mark Walker, Richard M Watanabe, Goncalo R Abecasis, Bernhard O Boehm, Harry Campbell, Mark J Daly, Andrew T Hattersley, Oluf Pedersen, Inês Barroso, Leif Groop, Rob Sladek, Unnur Thorsteinsdottir, James F Wilson, Thomas Illig, Philippe Froguel, Cornelia M van Duijn, Kari Stefansson, David Altshuler, Michael Boehnke, Mark I McCarthy, Nicole Soranzo, Eleanor Wheeler, Nicole L Glazer, Nabila Bouatia-Naji, Reedik Mägi, Joshua Randall, Paul Elliott, Denis Rybin, Abbas Dehghan, Jouke Jan Hottenga, Kijoung Song, Anuj Goel, Taina Lajunen, Alex Doney, Christine Cavalcanti-Proença, Meena Kumari, Nicholas J Timpson, Carina Zabena, Erik Ingelsson, Ping An, Jeffrey O'Connell, Jian'an Luan, Amanda Elliott, Steven A McCarroll, Rosa Maria Roccasecca, François Pattou, Praveen Sethupathy, Yavuz Ariyurek, Philip Barter, John P Beilby, Yoav Ben-Shlomo, Sven Bergmann, Murielle Bochud, Amélie Bonnefond, Knut Borch-Johnsen, Yvonne Böttcher, Eric Brunner, Suzannah J Bumpstead, Yii-Der Ida Chen, Peter Chines, Robert Clarke, Lachlan J M Coin, Matthew N Cooper, Laura Crisponi, Ian N M Day, Eco J C de Geus, Jerome Delplanque, Annette C Fedson, Antje Fischer-Rosinsky, Nita G Forouhi, Maria Grazia Franzosi, Pilar Galan, Mark O Goodarzi, Jürgen Graessler, Scott Grundy, Rhian Gwilliam, Göran Hallmans, Naomi Hammond, Xijing Han, Anna-Liisa Hartikainen, Caroline Hayward, Simon C Heath, Serge Hercberg, David R Hillman, Aroon D Hingorani, Jennie Hui, Joe Hung, Marika Kaakinen, Jaakko Kaprio, Y Antero Kesaniemi, Mika Kivimaki, Beatrice Knight, Seppo Koskinen, Peter Kovacs, Kirsten Ohm Kyvik, G Mark Lathrop, Debbie A Lawlor, Olivier Le Bacquer, Cécile Lecoeur, Yun Li, Robert Mahley, Massimo Mangino, María Teresa Martínez-Larrad, Jarred B McAteer, Ruth McPherson, Christa Meisinger, David Melzer, David Meyre, Braxton D Mitchell, Sutapa Mukherjee, Silvia Naitza, Matthew J Neville, Marco Orrù, Ruth Pakyz, Giuseppe Paolisso, Cristian Pattaro, Daniel Pearson, John F Peden, Nancy L Pedersen, Andreas F H Pfeiffer, Irene Pichler, Ozren Polasek, Danielle Posthuma, Simon C Potter, Anneli Pouta, Michael A Province, Nigel W Rayner, Kenneth Rice, Samuli Ripatti, Fernando Rivadeneira, Olov Rolandsson, Annelli Sandbaek, Manjinder Sandhu, Serena Sanna, Avan Aihie Sayer, Paul Scheet, Udo Seedorf, Stephen J Sharp, Beverley Shields, Gunnar Sigurðsson, Eric J G Sijbrands, Angela Silveira, Laila Simpson, Andrew Singleton, Nicholas L Smith, Ulla Sovio, Amy Swift, Holly Syddall, Ann-Christine Syvänen, Anke Tönjes, André G Uitterlinden, Ko Willems van Dijk, Dhiraj Varma, Sophie Visvikis-Siest, Veronique Vitart, Nicole Vogelzangs, Gérard Waeber, Peter J Wagner, Andrew Walley, Kim L Ward, Hugh Watkins, Sarah H Wild, Gonneke Willemsen, Jaqueline C M Witteman, John W G Yarnell, Diana Zelenika, Björn Zethelius, Guangju Zhai, Jing Hua Zhao, M Carola Zillikens, DIAGRAM Consortium, GIANT Consortium, Global B Pgen Consortium, Ingrid B Borecki, Pierre Meneton, Patrik K E Magnusson, David M Nathan, Gordon H Williams, Kaisa Silander, Stefan R Bornstein, Peter Schwarz, Joachim Spranger, Fredrik Karpe, Alan R Shuldiner, Cyrus Cooper, Manuel Serrano-Ríos, Lars Lind, Lyle J Palmer, Paul W Franks, Shah Ebrahim, Michael Marmot, W H Linda Kao, Peter Paul Pramstaller, Alan F Wright, Michael Stumvoll, Anders Hamsten, Procardis Consortium, Thomas A Buchanan, Timo T Valle, Jerome I Rotter, Brenda W J H Penninx, Dorret I Boomsma, Antonio Cao, Angelo Scuteri, David Schlessinger, Manuela Uda, Aimo Ruokonen, Marjo-Riitta Jarvelin, Leena Peltonen, Vincent Mooser, Robert Sladek, MAGIC investigators, GLGC Consortium, Kiran Musunuru, Albert V Smith, Andrew C Edmondson, Ioannis M Stylianou, Masahiro Koseki, James P Pirruccello, Daniel I Chasman, Christopher T Johansen, Sigrid W Fouchier, Gina M Peloso, Maja Barbalic, Sally L Ricketts, Joshua C Bis, Mary F Feitosa, Marju Orho-Melander, Olle Melander, Xiaohui Li, Mingyao Li, Yoon Shin Cho, Min Jin Go, Young Jin Kim, Jong-Young Lee, Taesung Park, Kyunga Kim, Xueling Sim, Rick Twee-Hee Ong, Damien C Croteau-Chonka, Leslie A Lange, Joshua D Smith, Andreas Ziegler, Weihua Zhang, Robert Y L Zee, John B Whitfield, John R Thompson, Ida Surakka, Tim D Spector, Johannes H Smit, Juha Sinisalo, James Scott, Juha Saharinen, Chiara Sabatti, Lynda M Rose, Robert Roberts, Mark Rieder, Alex N Parker, Guillaume Pare, Christopher J O'Donnell, Markku S Nieminen, Deborah A Nickerson, Grant W Montgomery, Wendy McArdle, David Masson, Nicholas G Martin, Fabio Marroni, Gavin Lucas, Robert Luben, Marja-Liisa Lokki, Guillaume Lettre, Lenore J Launer, Edward G Lakatta, Reijo Laaksonen, Kirsten O Kyvik, Inke R König, Kay-Tee Khaw, Lee M Kaplan, Åsa Johansson, A Cecile J W Janssens, Wilmar Igl, G Kees Hovingh, Christian Hengstenberg, Aki S Havulinna, Nicholas D Hastie, Tamara B Harris, Talin Haritunians, Alistair S Hall, Leif C Groop, Elena Gonzalez, Nelson B Freimer, Jeanette Erdmann, Kenechi G Ejebe, Angela Döring, Anna F Dominiczak, Serkalem Demissie, Panagiotis Deloukas, Ulf de Faire, Gabriel Crawford, Yii-der I Chen, Mark J Caulfield, S Matthijs Boekholdt, Themistocles L Assimes, Thomas Quertermous, Mark Seielstad, Tien Y Wong, E-Shyong Tai, Alan B Feranil, Christopher W Kuzawa, Herman A Taylor, Stacey B Gabriel, Hilma Holm, Vilmundur Gudnason, Ronald M Krauss, Jose M Ordovas, Patricia B Munroe, Jaspal S Kooner, Alan R Tall, Robert A Hegele, John J P Kastelein, Eric E Schadt, David P Strachan, Muredach P Reilly, Nilesh J Samani, Heribert Schunkert, L Adrienne Cupples, Manjinder S Sandhu, Paul M Ridker, Daniel J Rader, and Sekar Kathiresan

Subjects
Genetics, QH426-470
Abstract

Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8)-1.2×10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p

Published
2012
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36. Genome-wide association study for multiple phenotype analysis

Author

Gina M. Peloso, Ching-Ti Liu, Virginia Fisher, Adrienne Cupples, Xuan Deng, and Biqi Wang

Subjects
0301 basic medicine, Multivariate statistics, lcsh:R, Multiple traits, lcsh:Medicine, Genome-wide association study, General Medicine, Computational biology, 030105 genetics & heredity, Biology, Phenotype, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, 030104 developmental biology, Marginal Analysis, Chromosome (genetic algorithm), lcsh:Q, lcsh:Science, Genetic association, Type I and type II errors
Abstract

Genome-wide association studies often collect multiple phenotypes for complex diseases. Multivariate joint analyses have higher power to detect genetic variants compared with the marginal analysis of each phenotype and are also able to identify loci with pleiotropic effects. We extend the unified score-based association test to incorporate family structure, apply different approaches to analyze multiple traits in GAW20 real samples, and compare the results. Through simulation studies, we confirm that the Type I error rate of the pedigree-based unified score association test is appropriately controlled. In marginalanalysis of triglyceride levels, we found 1 subgenome-wide significant variant on chromosome 6. Joint analyses identified several suggestive genome-wide significant signals, with the pedigree-based unified score association test yielding the greatest number of significant results.

Published
2018
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37. Deep-coverage whole genome sequences and blood lipids among 16,324 individuals

Author

Jeffrey R. O'Connell, James A. Perry, Mark Chaffin, Cotton Seed, Maris Alver, L. Adrienne Cupples, May E. Montasser, Jesse M. Engreitz, Seyedeh M. Zekavat, Stephen S. Rich, W. Craig Johnson, Adolfo Correa, Sekar Kathiresan, Benjamin M. Neale, Andrea Ganna, James G. Wilson, Ramachandran S. Vasan, Braxton D. Mitchell, Wei Zhao, Gina M. Peloso, Amit Khera, Gonçalo R. Abecasis, Jason Ernst, Cristen J. Willer, Eric S. Lander, Ida Surakka, Veikko Salomaa, Pradeep Natarajan, Ani Manichaikul, Jonathan M. Bloom, Timothy Poterba, Manolis Kellis, Tõnu Esko, Samuli Ripatti, Jerome I. Rotter, Sanni Ruotsalainen, Institute for Molecular Medicine Finland, Samuli Olli Ripatti / Principal Investigator, Centre of Excellence in Complex Disease Genetics, Clinicum, Doctoral Programme in Population Health, Biostatistics Helsinki, and Complex Disease Genetics

Subjects
0301 basic medicine, PREDICTION, POLYGENIC RISK SCORES, EFFICIENT, General Physics and Astronomy, Blood lipids, Genome-wide association study, Cardiovascular, Genome, chemistry.chemical_compound, 0302 clinical medicine, Gene Frequency, Models, GENETIC-VARIANTS, Genotype, WIDE ASSOCIATION, 2.1 Biological and endogenous factors, Aetiology, FAMILIAL HYPERCHOLESTEROLEMIA, lcsh:Science, GENERAL-POPULATION, Genetics, 0303 health sciences, Multidisciplinary, High-Throughput Nucleotide Sequencing, Lipids, NHLBI TOPMed Lipids Working Group, 3. Good health, Cholesterol, symbols, LOW-FREQUENCY, lipids (amino acids, peptides, and proteins), Human, Biotechnology, Science, Genomics, Locus (genetics), Quantitative trait locus, Biology, General Biochemistry, Genetics and Molecular Biology, Article, LDL, 03 medical and health sciences, symbols.namesake, Genetic, medicine, Humans, Gene, 030304 developmental biology, Whole genome sequencing, Models, Genetic, Base Sequence, Genome, Human, Human Genome, General Chemistry, Cholesterol, LDL, DIVERSE POPULATIONS, medicine.disease, Atherosclerosis, 030104 developmental biology, chemistry, Mutation, Mendelian inheritance, lcsh:Q, 3111 Biomedicine, RARE-VARIANT ASSOCIATION, Digestive Diseases, 030217 neurology & neurosurgery, Imputation (genetics), Dyslipidemia, Genome-Wide Association Study
Abstract

Large-scale deep-coverage whole-genome sequencing (WGS) is now feasible and offers potential advantages for locus discovery. We perform WGS in 16,324 participants from four ancestries at mean depth >29X and analyze genotypes with four quantitative traits—plasma total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides. Common variant association yields known loci except for few variants previously poorly imputed. Rare coding variant association yields known Mendelian dyslipidemia genes but rare non-coding variant association detects no signals. A high 2M-SNP LDL-C polygenic score (top 5th percentile) confers similar effect size to a monogenic mutation (~30 mg/dl higher for each); however, among those with severe hypercholesterolemia, 23% have a high polygenic score and only 2% carry a monogenic mutation. At these sample sizes and for these phenotypes, the incremental value of WGS for discovery is limited but WGS permits simultaneous assessment of monogenic and polygenic models to severe hypercholesterolemia., Common genetic variants associated with plasma lipids have been extensively studied for a better understanding of common diseases. Here, the authors use whole-genome sequencing of 16,324 individuals to analyze rare variant associations and to determine their monogenic and polygenic contribution to lipid traits.

Published
2018
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38. Deep coverage whole genome sequences and plasma lipoprotein(a) in individuals of European and African ancestries

Author

Cashell E. Jaquish, Craig P. Hersh, Emily Barron-Casella, Larry Phillips, James S. Pankow, JoAnn E. Manson, Mariza de Andrade, Vivien A. Sheehan, Norann A. Zaghloul, Yongmei Liu, Sergei Nekhai, Russell P. Tracy, Bruce S. Weir, Pankaj Qasba, Adrienne M. Stilp, Tasha E. Fingerlin, Heather M. Ochs-Balcom, L. Adrienne Cupples, Rongze Yang, David A. Schwartz, Shannon Kelly, Scott E. Devine, Tanja Smith, G.L. Kinney, Beverly Snively, Kent D. Taylor, Manolis Kellis, Ruth J. F. Loos, Seth A. Ament, Kathleen C. Barnes, Robert C. Kaplan, Ulrich Broeckel, Hemant K. Tiwari, Karin F. Hoth, Peter Durda, Julie L. Mikulla, Charles B. Eaton, Cotton Seed, Merry Lynn McDonald, Eric Boerwinkle, Josh Smith, Honghuang Lin, Ingrid B. Borecki, Jeffrey L. Curtis, Emelia J. Benjamin, Kenneth Rice, Sharon L.R. Kardia, Nicholas L. Smith, Coleen M. Damcott, Jeffrey Haessler, Kimberly L. Jones, Elaine Cornell, Nona Sotoodehnia, Adolfo Correa, Rich Johnston, C. Charles Gu, Chii Min Hwu, Peter C. Anderson, Lesley F. Tinker, Colleen Davis, R. Graham Barr, Scott T. Weiss, Leanna Farnam, Chao Hsiung, Brian Silver, Patrick F. McArdle, Lisa W. Martin, Yii-Der Ida Chen, John Barnard, Holly Kramer, Sekar Kathiresan, Gonçalo R. Abecasis, Barry Make, Michael C. Mahaney, Marco V Perez, Donna K. Arnett, Mark Chaffin, Xiuqing Guo, Joshua C. Bis, Pamela Russell, Paul L. Auer, James G. Wilson, Marilyn J. Telen, David K. Levine, Jennifer A. Smith, Christopher Scheller, Meher Preethi Boorgula, Aakrosh Ratan, Kari E. North, Dan E. Arking, Elizabeth A. Regan, Margaret G. Parker, Andres Metspalu, Jai G. Broome, Daniel Taliun, Lynette Ekunwe, Alyna T. Khan, Hao Mei, Dhananjay Vaidya, Ellen M. Schmidt, Stanford Mwasongwe, Joshua P. Lewis, Stacey Gabriel, Christine E. Seidman, Margery Gass, Deborah A. Nickerson, Nicola L. Hawley, Rebecca L. Beer, Afshin Parsa, Steven L. Salzberg, Terri H. Beaty, Stella Aslibekyan, Girish N. Nadkarni, Wei Zhao, David L. Tirschwell, Karen Bunting, Dawn L. DeMeo, Laura J. Rasmussen-Torvik, Julia Powers Becker, Dmitry Prokopenko, Karen Schwander, Bruce D. Gelb, Stephanie Krauter, Laura M. Raffield, Michael E. Hall, Frank C. Sciurba, Lauren Margolin, Nora Franceschini, Daniel N. Harris, Seyedeh M. Zekavat, Dawood Darbar, Keng-Han Lin, Haley Huston, Steven A. Lubitz, Andrea Ganna, Carole Sztalryd, Cathy C. Laurie, Christy Chang, James E. Hixson, Steven A. McCarroll, Barbara A. Konkle, Michael D. Kessler, Scott I. Vrieze, Yingze Zhang, Sarah Ruuska, George J. Papanicolaou, Weiniu Gan, Maris Alver, Elizabeth A. Streeten, Fei Fei Wang, Lu-Chen Weng, Braxton D. Mitchell, Lee-Ming Chuang, Sean P. David, Wei-Min Chen, Susan R. Heckbert, Ryan D. Hernandez, Andrew D. Johnson, Cristen J. Willer, Ani Manichaikul, Jonathan M. Bloom, Timothy D. O’Connor, Sylvia Smoller, Marguerite R. Irvin, Seung Hoan Choi, Ida Surakka, Veikko Salomaa, Diane M. Becker, Ron Do, W. Craig Johnson, Cecelia A. Laurie, Meryl S. LeBoff, Aniket Shetty, Tõnu Esko, Michael C. Zody, Xiaoqi Geng, Da Wei Gong, Snow Xueyan Zhao, Esteban G. Burchard, Xiuwen Zheng, Cara L. Carty, Alexander P. Reiner, Tim Assimes, Deborah A. Meyers, Mina K. Chung, Harald H H Göring, Benjamin M. Neale, Pradeep Natarajan, Yan Gao, Stephen S. Rich, Yun Ju Sung, Susan K. Dutcher, Ferdouse Begum, Stephanie M. Gogarten, John Blangero, Jonathan Cardwell, Kayleen Williams, Rakhi P. Naik, Amol C. Shetty, Sayantan Das, Myriam Fornage, May E. Montasser, Michelle Daya, Edwin K. Silverman, Daniel E. Weeks, Laura J. Kaufman, Dimitrios Avramopoulos, Michael Y. Tsai, Christine M. Albert, Vijay G. Sankaran, Jeffrey R. O'Connell, Thomas W. Blackwell, Stephen T. McGarvey, Robert M. Reed, Leslie A. Lange, Qing Duan, Bruce M. Psaty, Leslie S. Emery, Bertha Hidalgo, Jennifer A. Brody, L. Keoki Williams, Soren Germer, Zhaohui S. Qin, Deepti Jain, Deborah Applebaum-Bowden, Carla Wilson, Degui Zhi, Christoph Lange, Elliott Hong, L.F. Bielak, Wen Jane Lee, Yue Guan, Tarik Walker, Rebecca D. Jackson, Charles R. Farber, Mark J. Daly, Stephanie M. Fullerton, John E. Hokanson, Karol E. Watson, James Luo, Richard Casaburi, Seunggeun Lee, Jill M. Johnsen, Margaret A. Taub, Ryan L. Minster, Ravi Duggirala, Susan K. Mathai, Yun Li, Quenna Wong, Matthew Flickinger, Huichun Xu, Susan Redline, Ulrike Peters, Ivana V. Yang, Jesse M. Engreitz, Sanni Ruotsalainen, Sean K. McFarland, Avram D Walts, Patricia A. Peyser, Allison E. Ashley-Koch, Lewis C. Becker, Nicholette Palmer Allred, James A. Perry, Jody S. Sylvia, Tamar Sofer, Vasan S. Ramachandran, Laura Almasy, Matthew J. Budoff, Ranjan Deka, David M. Herrington, Simeon I. Taylor, Daniel Levy, Chaojie Yang, Sameer Chavan, Kathleen A. Ryan, Josyf C. Mychaleckyj, Ingo Ruczinski, Sebastian Zoellner, Michael Preuss, Tim Poterba, Wendy S. Post, Amber L. Beitelshees, Ben Heavner, Carolina Roselli, Namiko Abe, Jonathon LeFaive, Mark T. Gladwin, Brian Custer, Robert B. Wallace, Simin Liu, Michael H. Cho, Robert E. Handsaker, Dabeeru C. Rao, Bo Juen Chen, Wayne Hui Heng Sheu, Xiang Zhou, Marcos Bezerra, Solomon K. Musani, Eimear E. Kenny, James F. Casella, Kathryn L. Lunetta, Nancy Min, Nicholas Rafaels, Lisa R. Yanek, Min A. Jhun, David C. Glahn, Rasika A. Mathias, Mollie A. Minear, Russell P. Bowler, Jason Ernst, Carolyn J. Crandall, Sara Penchev, Alvaro Alonso, Timothy A. Thornton, Toni I. Pollin, Charles Kooperberg, Ethan M. Lange, Juan M. Peralta, Pramod Anugu, Lucinda Fulton, Adam A. Szpiro, Michael R. DeBaun, M. Benjamin Shoemaker, Sam Phillips, Dan M. Roden, Mao Fu, Daniel I. Chasman, James D. Crapo, Hua Tang, Gina M. Peloso, Hyun Min Kang, Samuli Ripatti, Phuwanat Sakornsakolpat, Christopher R. Gignoux, Peter VandeHaar, Jerome I. Rotter, Dandi Qiao, Emily S. Wan, Shabnam Salimi, Kevin Sandow, Jiang He, Patrick T. Ellinor, Joanne E. Curran, Institute for Molecular Medicine Finland, Samuli Olli Ripatti / Principal Investigator, University of Helsinki, Centre of Excellence in Complex Disease Genetics, Clinicum, Doctoral Programme in Population Health, Department of Public Health, and Complex Disease Genetics

Subjects
0301 basic medicine, Apolipoprotein B, General Physics and Astronomy, Gene Expression, Genome-wide association study, 030204 cardiovascular system & hematology, Cardiovascular, Lipoprotein particle, chemistry.chemical_compound, 0302 clinical medicine, Risk Factors, GENETIC-VARIANTS, 2.1 Biological and endogenous factors, WIDE ASSOCIATION, Aetiology, lcsh:Science, African Continental Ancestry Group, Genetics, Multidisciplinary, Genome, biology, CHOLESTEROL, Adaptor Proteins, Lipoprotein(a), Single Nucleotide, NHLBI TOPMed Lipids Working Group, 3142 Public health care science, environmental and occupational health, 3. Good health, Cholesterol, Heart Disease, Cardiovascular Diseases, CARDIOVASCULAR-DISEASE, RARE VARIANTS, lipids (amino acids, peptides, and proteins), LOW-FREQUENCY, Human, DNA Copy Number Variations, Science, Quantitative Trait Loci, European Continental Ancestry Group, Black People, POPULATION-SCALE, Quantitative trait locus, Article, White People, General Biochemistry, Genetics and Molecular Biology, LDL, Structural variation, 03 medical and health sciences, COMPONENTS-ANALYSIS, RISK-FACTOR, Humans, CORONARY-HEART-DISEASE, Polymorphism, Whole Genome Sequencing, Prevention, Human Genome, General Chemistry, Atherosclerosis, Vesicular Transport, Good Health and Well Being, 030104 developmental biology, chemistry, biology.protein, lcsh:Q, 3111 Biomedicine, Lipoprotein, Genome-Wide Association Study
Abstract

Lipoprotein(a), Lp(a), is a modified low-density lipoprotein particle that contains apolipoprotein(a), encoded by LPA, and is a highly heritable, causal risk factor for cardiovascular diseases that varies in concentrations across ancestries. Here, we use deep-coverage whole genome sequencing in 8392 individuals of European and African ancestry to discover and interpret both single-nucleotide variants and copy number (CN) variation associated with Lp(a). We observe that genetic determinants between Europeans and Africans have several unique determinants. The common variant rs12740374 associated with Lp(a) cholesterol is an eQTL for SORT1 and independent of LDL cholesterol. Observed associations of aggregates of rare non-coding variants are largely explained by LPA structural variation, namely the LPA kringle IV 2 (KIV2)-CN. Finally, we find that LPA risk genotypes confer greater relative risk for incident atherosclerotic cardiovascular diseases compared to directly measured Lp(a), and are significantly associated with measures of subclinical atherosclerosis in African Americans., Circulating lipoprotein(a) is an important risk factor for cardiovascular disease and shows variability between different ethnic groups. Here, Zekavat et al. perform whole-genome sequencing in individuals of European and African ancestries and find ancestry-specific genetic determinants for lipoprotein(a) levels.

Published
2018
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39. Searching for parent-of-origin effects on cardiometabolic traits in imprinted genomic regions

Author

Josée Dupuis, Inga Peter, James B. Meigs, Ching-Ti Liu, Peitao Wu, Hagit Hochner, Ramachandran S. Vasan, Yechiel Friedlander, David S. Siscovick, Gina M. Peloso, Daniel Levy, Einat Granot-Hershkovitz, David Karasik, and L. Adrienne Cupples

Subjects
Genetics, Male, Metabolic Syndrome, Quantitative Trait Loci, Maternal effect, Pedigree chart, Single-nucleotide polymorphism, Genome-wide association study, Biology, Polymorphism, Single Nucleotide, Genetic architecture, Article, Pedigree, Genomic Imprinting, Framingham Heart Study, Genetic variation, Paternal Inheritance, Body Size, Humans, Female, Maternal Inheritance, Genetics (clinical), Genetic association
Abstract

Cardiometabolic traits pose a major global public health burden. Large-scale genome-wide association studies (GWAS) have identified multiple loci accounting for up to 30% of the genetic variance in complex traits such as cardiometabolic traits. However, the contribution of parent-of-origin effects (POEs) to complex traits has been largely ignored in GWAS. Family-based studies enable the assessment of POEs in genetic association analyses. We investigated POEs on a range of complex traits in 3 family-based studies. The discovery phase was carried out in large pedigrees from the Kibbutzim Family Study (n = 901 individuals) and in 872 parent–offspring trios from the Jerusalem Perinatal Study. Focusing on imprinted genomic regions, we examined parent-specific associations with 12 complex traits (i.e., body-size, blood pressure, lipids), mostly cardiometabolic risk traits. Forty five of the 11,967 SNPs initially found to have POE were evaluated for replication (p value

Published
2020

40. Heterozygous ATP-binding Cassette Transporter G5 Gene Deficiency and Risk of Coronary Artery Disease

Author

Diego Ardissino, Daniel J. Rader, Gina M. Peloso, Hayato Tada, Masa-aki Kawashiri, Heribert Schunkert, Matthew J. Bown, Svati H. Shah, Stacey Gabriel, John Danesh, Ruth McPherson, Pradeep Natarajan, Danish Saleheen, Nilesh J. Samani, Adolfo Correa, Akihiro Nomura, Jeanette Erdmann, Amit Khera, Connor A. Emdin, Roberto Elosua, Sekar Kathiresan, Namrata Gupta, Hong-Hee Won, and Hugh Watkins

Subjects
medicine.medical_specialty, Blood lipids, Pedigree chart, ABCG8, 030204 cardiovascular system & hematology, 03 medical and health sciences, symbols.namesake, 0302 clinical medicine, Internal medicine, medicine, 030304 developmental biology, 0303 health sciences, biology, business.industry, Odds ratio, medicine.disease, 3. Good health, Minor allele frequency, Endocrinology, ABCG5, biology.protein, Mendelian inheritance, symbols, lipids (amino acids, peptides, and proteins), business, Sitosterolemia
Abstract

BackgroundFamilial sitosterolemia is a rare, recessive Mendelian disorder characterized by hyperabsorption and decreased biliary excretion of dietary sterols. Affected individuals typically have complete genetic deficiency – homozygous loss-of-function (LoF) variants — in the ATP-binding cassette transporter G5 (ABCG5) or G8 (ABCG8) genes, and have substantially elevated plasma sitosterol and low-density lipoprotein cholesterol (LDL-C) levels. The impact of partial genetic deficiency ofABCG5orABCG8, as occurs in heterozygous carriers of LoF variants, on LDL-C and risk of coronary artery disease (CAD) has remained uncertain.MethodsWe first recruited nine sitosterolemia families, identified causative LoF variants inABCG5orABCG8, and evaluated the associations of theseABCG5orABCG8LoF variants with plasma phytosterols and lipid levels. We next assessed for LoF variants inABCG5orABCG8in CAD cases (n=29,361) versus controls (n=357,326). We tested the association of rare LoF variants inABCG5orABCG8with blood lipids and risk for CAD. Rare LoF variants were defined as protein-truncating variants with minor allele frequency less than 0.1% inABCG5orABCG8.ResultsIn sitosterolemia families, seven pedigrees harbored causative LoF variants inABCG5and two pedigrees inABCG8. Homozygous LoF variants in eitherABCG5orABCG8led to marked elevations in sitosterol and LDL-C. Of those sitosterolemia families, heterozygous carriers ofABCG5LoF variants exhibited increased sitosterol and LDL-C levels compared to non-carriers. Within the large-scale CAD case-control cohorts, prevalence of rare LoF variants inABCG5and inABCG8were approximately 0.1% each.ABCG5heterozygous LoF variant carriers had significantly elevated LDL-C levels (24.7 mg/dL; 95% confidence interval [CI] 14 to 35; P=1.1×10−6), and were at two-fold increased risk of CAD (odds ratio 2.06, 95% CI 1.27 to 3.35; P=0.004). By contrast,ABCG8heterozygous LoF carrier status was not associated with increased LDL-C or risk of CAD.ConclusionsAlthough familial sitosterolemia is traditionally considered as a recessive disorder, we observed that heterozygous carriers of a LoF variant inABCG5had significantly increased sitosterol and LDL-C levels and a two-fold increase in risk of CAD.

Published
2019
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41. Beverage Consumption and Longitudinal Changes in Lipid Concentrations and Incident Dyslipidemia in U.S. Adults: The Framingham Heart Study (P18-017-19)

Author

Nicola M. McKeown, Alice H. Lichtenstein, Gina M. Peloso, Mark A. Herman, Danielle E. Haslam, Caren E. Smith, and Josée Dupuis

Subjects
Beverage consumption, Nutrition and Dietetics, Calorie, business.industry, Offspring, Medicine (miscellaneous), Ecological study, medicine.disease, Framingham Heart Study, Medicine, LDL Cholesterol Lipoproteins, Nutritional Epidemiology, Fruit juice, Food science, business, Dyslipidemia, Food Science
Abstract

OBJECTIVES: Limited data are available on the prospective relationship between beverage consumption and plasma lipid and lipoprotein concentrations in population-based studies. Two major sources of sugar in the US diet are sugar-sweetened beverages (SSB; sodas and fruit drinks) and 100% fruit juices (FJ). Low-calorie sweetened beverages (LCSB) are common replacements for SSB and FJ. METHODS: Fasting plasma triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) concentrations were measured at up to 5 exams in the Framingham Heart Study offspring and up to 2 exams in generation 3 cohorts (1998–2005; N = 6730). Consumption of SSB, FJ, and LCSB were estimated from food frequency questionnaires and intakes were categorized. Mixed-effect linear regression models were used to examine changes in lipid concentrations, and Cox proportional hazard models were used to estimate hazard ratios (HR) for incident dyslipidemia, adjusting for potential confounding factors. Results were statistically significant at a Bonferroni-corrected P-value 1 serving/day) vs. low intake category (

Published
2019

42. Rare protein-truncating variants in APOB, lower low-density lipoprotein cholesterol, and protection against coronary heart disease

Author

John Danesh, Joseph B. Leader, David J. Carey, Danish Saleheen, Frederick E. Dewey, Ruth McPherson, Tanya M. Teslovich, Jaume Marrugat, Amit Khera, Diego Ardissino, Mark Chaffin, Heribert Schunkert, Akihiro Nomura, Jeanette Erdmann, Masa-aki Kawashiri, Hugh Watkins, Shane A. McCarthy, Nilesh J. Samani, Atsushi Nohara, Aris Baras, Hong-Hee Won, H. Lester Kirchner, Sekar Kathiresan, James G. Wilson, Gina M. Peloso, Hayato Tada, Danesh, John [0000-0003-1158-6791], and Apollo - University of Cambridge Repository

Subjects
Male, Apolipoprotein B, Coronary Disease, 030204 cardiovascular system & hematology, medicine.disease_cause, chemistry.chemical_compound, 0302 clinical medicine, Japan, Risk Factors, genetics, 030212 general & internal medicine, triglycerides, Mutation, biology, Genetic disorder, hypobetalipoproteinemia, General Medicine, Middle Aged, 3. Good health, ddc, Pedigree, Female, lipids (amino acids, peptides, and proteins), Adult, medicine.medical_specialty, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, Internal medicine, Genetic variation, medicine, Humans, human, Gene, Aged, Apolipoproteins B, business.industry, Cholesterol, Case-control study, cholesterol, Genetic Variation, Cholesterol, LDL, medicine.disease, Endocrinology, chemistry, Case-Control Studies, biology.protein, Hypobetalipoproteinemia, business
Abstract

Background Familial hypobetalipoproteinemia is a genetic disorder caused by rare protein-truncating variants (PTV) in the gene encoding APOB (apolipoprotein B), the major protein component of LDL (low-density lipoprotein) and triglyceride-rich lipoprotein particles. Whether heterozygous APOB deficiency is associated with decreased risk for coronary heart disease (CHD) is uncertain. We combined family-based and large scale gene-sequencing to characterize the association of rare PTVs in APOB with circulating LDL-C (LDL cholesterol), triglycerides, and risk for CHD. Methods We sequenced the APOB gene in 29 Japanese hypobetalipoproteinemia families, as well as 57 973 individuals derived from 12 CHD case-control studies-18 442 with early-onset CHD and 39 531 controls. We defined PTVs as variants that lead to a premature stop, disrupt canonical splice-sites, or lead to insertions/deletions that shift reading frame. We tested the association of rare APOB PTV carrier status with blood lipid levels and CHD. Results Among 29 familial hypobetalipoproteinemia families, 8 families harbored APOB PTVs. Carrying 1 APOB PTV was associated with 55 mg/dL lower LDL-C ( P=3×10-5) and 53% lower triglyceride level ( P=2×10-4). Among 12 case-control studies, an APOB PTV was present in 0.038% of CHD cases as compared to 0.092% of controls. APOB PTV carrier status was associated with a 43 mg/dL lower LDL-C ( P=2×10-7), a 30% decrease in triglycerides ( P=5×10-4), and a 72% lower risk for CHD (odds ratio, 0.28; 95% CI, 0.12-0.64; P=0.002). Conclusions Rare PTV mutations in APOB which are associated with lower LDL-C and reduced triglycerides also confer protection against CHD. Dr Peloso is supported by the National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health under Award Number K01HL125751. Dr Nomura was supported by the Yoshida Scholarship Foundation. Dr Khera is supported by an institutional grant from the Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard (BroadIgnite), a K08 from the National Human Genome Research Institute (K08HG010155), and a Junior Faculty Award from the National Lipid Association. Dr Kathiresan is supported by a research scholar award from the Massachusetts General Hospital, the Donovan Family Foundation, and grant R01 HL127564 from the NHLBI. Funding for the EOMI study (Exome Sequencing Project Early-Onset Myocardial Infarction) was provided by grants RC2 HL103010 (HeartGO, Heart Grand Opportunity), RC2 HL102923 (LungGO, Lung Grand Opportunity), and RC2 HL102924 (WHISP) from the NHLBI. Exome sequencing was performed through grants RC2 HL102925 (BroadGO, Broad Grand Opportunity) and RC2 HL102926 (SeattleGO, Seattle Grand Opportunity) from the NHLBI. Exome sequencing in ATVB (Italian Atherosclerosis, Thrombosis, and Vascular Biology), the PROCARDIS study (Precocious Coronary Artery Disease), the OHS (Ottawa Heart Study), PROMIS (Pakistan Risk of Myocardial Infarction Study), South German MI study (South German Myocardial Infarction), and the JHS (Jackson Heart Study) was supported by grant 5U54HG003067 from the National Institutes of Health. Fieldwork, genotyping, and standard clinical chemistry assays in PROMIS were principally supported by grants awarded to the University of Cambridge from the British Heart Foundation, UK Medical Research Council, Wellcome Trust, European Union (EU) Framework 6–funded Bloodomics Integrated Project, Pfizer, Novartis, and Merck. Additional support for PROMIS was provided by the UK Medical Research Council (MR/L003120/1), British Heart Foundation (RG/13/13/30194), UK National Institute for Health Research Cambridge Biomedical Research Centre, European Research Council (268834), and European Commission Framework Programme 7 (HEALTH-F2-2012–279233). The Jackson Heart Study is supported by contracts HHSN268201300046C, HHSN268201300047C, HHSN268201300048C, HHSN268201300049C, and HHSN268201300050C from the NHLBI and the National Institute on Minority Health and Health Disparities. Dr Wilson is supported by U54GM115428 from the National Institute of General Medical Sciences. REGICOR study (Registre Gironí del COR [Gerona Heart Registry]) was supported by the Spanish Ministry of Economy and Innovation through the Carlos III Health Institute (Red Investigación Cardiovascular RD12/0042, PI09/90506), European Funds for Development (ERDF-FEDER), and by the Catalan Research and Technology Innovation Interdepartmental Commission (2014SGR240). Samples for the Leicester (Leicester Myocardial Infarction) cohort were collected as part of projects funded by the British Heart Foundation (British Heart Foundation Family Heart Study, RG2000010; UK Aneurysm Growth Study, CS/14/2/30841) and the National Institute for Health Research (NIHR Leicester Cardiovascular Biomedical Research Unit Biomedical Research Informatics Centre for Cardiovascular Science, IS_BRU_0211_20033). The South MI Study is supported by the German Federal Ministry of Education and Research (BMBF) in the context of the e:Med program (e:AtheroSysMed) and the FP7 European Union project CVgenes@target (261123). Additional grants were received from the Fondation Leducq (CADgenomics: Understanding Coronary Artery Disease Genes, 12CVD02). This study was also supported through the Deutsche Forschungsgemeinschaft cluster of excellence Inflammation at Interfaces and SFB 1123. The ATVB study was supported by a grant from RFPS-2007-3-644382 and Programma di ricerca Regione-Università 2010–2012 Area 1–Strategic Programmes–Regione Emilia-Romagna. The authors would like to thank the MyCode Community Health Initiative participants for their permission to utilize their health and genomics information in the DiscovEHR (DiscovEHR partnership of the Regeneron Genetics Center and Geisinger Health System) collaboration. The DiscovEHR study was funded, in part, by the Regeneron Genetics Center.

Published
2019

43. Network analysis of drug effect on triglyceride-associated DNA methylation

Author

Anita L. DeStefano, Elise Lim, Gina M. Peloso, Achilleas N. Pitsillides, Jiayi Wu, L. Adrienne Cupples, Daniel Posner, Ching-Ti Liu, Hanfei Xu, and Peitao Wu

Subjects
0301 basic medicine, lcsh:R, lcsh:Medicine, General Medicine, Methylation, Computational biology, Biology, Phenotype, General Biochemistry, Genetics and Molecular Biology, 3. Good health, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Proceedings, CpG site, 030220 oncology & carcinogenesis, DNA methylation, Gene expression, lcsh:Q, Epigenetics, lcsh:Science, Gene, Quantile normalization
Abstract

Background DNA methylation, an epigenetic modification, can be affected by environmental factors and thus regulate gene expression levels that can lead to alterations of certain phenotypes. Network analysis has been used successfully to discover gene sets that are expressed differently across multiple disease states and suggest possible pathways of disease progression. We applied this framework to compare DNA methylation levels before and after lipid-lowering medication and to identify modules that differ topologically between the two time points, revealing the association between lipid medication and these triglyceride-related methylation sites. Methods We performed quality control using beta-mixture quantile normalization on 463,995 cytosine-phosphate-guanine (CpG) sites and deleted problematic sites, resulting in 423,004 probes. We identified 14,850 probes that were nominally associated with triglycerides prior to treatment and performed weighted gene correlation network analysis (WGCNA) to construct pre- and posttreatment methylation networks of these probes. We then applied both WGCNA module preservation and generalized Hamming distance (GHD) to identify modules with topological differences between the pre- and posttreatment. For modules with structural changes between 2 time points, we performed pathway-enrichment analysis to gain further insight into the biological function of the genes from these modules. Results Six triglyceride-associated modules were identified using pretreatment methylation probes. The same 3 modules were not preserved in posttreatment data using both the module-preservation and the GHD methods. Top-enriched pathways for the 3 differentially methylated modules are sphingolipid signaling pathway, proteoglycans in cancer, and metabolic pathways (p values

Published
2018

44. FastSKAT: Sequence kernel association tests for very large sets of markers

Author

Thomas Lumley, Kenneth Rice, Jennifer A. Brody, Alanna C. Morrison, and Gina M. Peloso

Subjects
0301 basic medicine, Genetic Markers, Time Factors, Epidemiology, Statistics as Topic, 01 natural sciences, Article, Histones, 010104 statistics & probability, 03 medical and health sciences, Matrix (mathematics), Null distribution, Chromosomes, Human, Humans, 0101 mathematics, Genetics (clinical), Eigenvalues and eigenvectors, Genetic Association Studies, 030304 developmental biology, Mathematics, 0303 health sciences, Sequence, Covariance matrix, Lanczos algorithm, Sequence Analysis, DNA, Covariance, Singular value, 030104 developmental biology, Kernel (image processing), Algorithm, Algorithms
Abstract

The Sequence Kernel Association Test (SKAT) is widely used to test for associations between a phenotype and a set of genetic variants, that are usually rare. Evaluating tail probabilities or quantiles of the null distribution for SKAT requires computing the eigenvalues of a matrix related to the genotype covariance between markers. Extracting the full set of eigenvalues of this matrix (an n × n matrix, for n subjects) has computational complexity proportional to n3. As SKAT is often used when n > 104, this step becomes a major bottleneck in its use in practice. We therefore propose fastSKAT, a new computationally-inexpensive but accurate approximations to the tail probabilities, in which the k largest eigenvalues of a weighted genotype covariance matrix or the largest singular values of a weighted genotype matrix are extracted, and a single term based on the Satterthwaite approximation is used for the remaining eigenval-ues. While the method is not particularly sensitive to the choice of k, we also describe how to choose its value, and show how fastSKAT can automatically alert users to the rare cases where the choice may affect results. As well as providing faster implementation of SKAT, the new method also enables entirely new applications of SKAT, that were not possible before; we give examples grouping variants by topologically assisted domains, and comparing chromosome-wide association by class of histone marker.

Published
2018

45. Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes

Author

Ching-Ti Liu, Michael Boehnke, George Dedoussis, Sophie V. Eastwood, Ruth J. F. Loos, Keng-Hung Lin, Denis Rybin, Fredrik Karpe, Martina Müller-Nurasyid, Michael A. Province, Alison D. Murray, Bo Isomaa, Eirini Marouli, Konstantin Strauch, Michael Preuss, Paul M. Ridker, Jette Bork-Jensen, Albert V. Smith, Hugoline G. de Haan, Wayne Huey-Herng Sheu, Barbara Thorand, Wolfgang Rathmann, Lawrence F. Bielak, Peter Kovacs, Marit E. Jørgensen, Jennifer Wessel, Danish Saleheen, Jung-Jin Lee, James B. Meigs, Veikko Salomaa, Alena Stančáková, Tibor V. Varga, Hidetoshi Kitajima, Inês Barroso, Kent D. Taylor, Claudia Langenberg, Yoon Shin Cho, Joanna M. M. Howson, Andrew T. Hattersley, Marie-France Hivert, Markku Laakso, Kai-Uwe Eckardt, Bram P. Prins, Matthias B. Schulze, Andrew D. Morris, Susanne Jäger, Francis S. Collins, Kristi Läll, Xu Lin, Anette Varbo, Benjamin Lehne, Girish N. Nadkarni, Jonathan Marchini, Daniel I. Chasman, Michael Stumvoll, Mark O. Goodarzi, Cécile Lecoeur, Philippe M. Frossard, Noël P. Burtt, Frank Kee, Jasmina Kravic, Alain G. Bertoni, Ivan Brandslund, Najaf Amin, Lenore J. Launer, Oluf Pedersen, Johanna Kuusisto, Line Rode, Eleftheria Zeggini, Yingchang Lu, Markus Perola, Helen R. Warren, André G. Uitterlinden, Hanieh Yaghootkar, Torben Hansen, Harald Grallert, Annemari Käräjämäki, Abbas Dehghan, Gina M. Peloso, Yii-Der Ida Chen, Man Li, Shaofeng Huo, Lars Lind, Karen L. Mohlke, Adrienne Tin, Yang Hai, Renée de Mutsert, Gudmar Thorleifsson, Marie Moitry, Sune F. Nielsen, Sara M. Willems, Matthias Wuttke, Weihua Zhang, Young-Jin Kim, Giovanni Malerba, Richard A. Jensen, Loic Yengo, Mickaël Canouil, Kurt Lohman, Robert A. Scott, Tamara B. Harris, Ruifang Li-Gao, Florian Kronenberg, Anke Tönjes, Bok-Ghee Han, Krista Fischer, Thomas Meitinger, James S. Pankow, Jaakko Tuomilehto, Adam S. Butterworth, Jerome I. Rotter, Olov Rolandsson, Xiuqing Guo, Cramer Christensen, Marie Loh, Elizabeth Selvin, Bong-Jo Kim, Audrey Y. Chu, Reedik Mägi, Josée Dupuis, Anna Köttgen, Jean Ferrières, Jin Li, Robert Sladek, Leslie A. Lange, Niels Grarup, Roberta McKean-Cowdin, Cristen J. Willer, Jose C. Florez, Valgerdur Steinthorsdottir, Karina Meidtner, Annette Peters, Børge G. Nordestgaard, Rajiv Chowdhury, Ioanna Ntalla, Emma Ahlqvist, Leif Groop, Nicholas J. Wareham, Kerrin S. Small, Tiinamaija Tuomi, Cecilia M. Lindgren, Katharine R. Owen, Giovanni Gambaro, Cornelia M. van Duijn, Dennis O. Mook-Kanamori, Kenneth Rice, Erik Ingelsson, Colin N. A. Palmer, Sharon L.R. Kardia, Neil R. Robertson, Dajiang J. Liu, Sebastian Schönherr, Daniel Taliun, Sekar Kathiresan, James G. Wilson, Ping An, Patricia A. Peyser, Matthias Blüher, Frits R. Rosendaal, John C. Chambers, Caroline Hayward, Shoaib Afzal, Fernando Rivadineira, Marielisa Graff, Pranav Yajnik, Vasiliki Mamakou, Juan Fernandez Tajes, Stefan Gustafsson, Heather M. Highland, Vilmantas Giedraitis, Andrew R. Wood, Saima Afaq, Jaspal S. Kooner, Megan L. Grove, Jennifer A. Brody, Andrew P. Morris, James P. Cook, Praveen Surendran, Jennifer Kriebel, Heikki A. Koistinen, Kari Stefansson, Anders Rosengren, Rainer Rauramaa, Satu Männistö, Oscar H. Franco, Yongmei Liu, N. William Rayner, Blair H. Smith, Erwin P. Bottinger, Ayse Demirkan, Allan Linneberg, Jonathan Marten, Huaixing Li, Sung Soo Kim, Sophie Hackinger, Cristina Bombieri, Lia B. Bang, Jun Liu, Asif Rasheed, Tim D. Spector, Paul W. Franks, Mark I. McCarthy, Heiner Boeing, Anne E. Justice, Vilmundur Gudnason, Sohee Han, Unnur Thorsteinsdottir, Panos Deloukas, Naveed Sattar, Eric Boerwinkle, Martin Ingelsson, John Danesh, Vassily Trubetskoy, Marco M Ferrario, Marju Orho-Melander, Wei Gan, Philippe Froguel, Symen Ligthart, Susan R. Heckbert, Jie Yao, Anne Tybjærg-Hansen, Robin Young, Daniel R. Witte, Anubha Mahajan, Peter Almgren, Timothy M. Frayling, Tanya M. Teslovich, Matt Neville, Philippe Amouyel, Wei Zhao, Andres Metspalu, Yao Hu, Olle Melander, Kari Kuulasmaa, Jason Flannick, Torben Jørgensen, Stephen S. Rich, Nicole Soranzo, Bruce M. Psaty, Rohit Varma, Epidemiology, and Internal Medicine

Subjects
0301 basic medicine, Male, Inference, Genome-wide association study, Whole Exome Sequencing, 0302 clinical medicine, type 2 diabetes, coding variant associations signals, mechanistic inference, fine mapping, Coding region, Chromosome Mapping/statistics & numerical data, European Continental Ancestry Group/genetics, CONFERS SUSCEPTIBILITY, Exome sequencing, 11 Medical and Health Sciences, Genetics, Genetics & Heredity, 0303 health sciences, MAGIC Consortium, Chromosome Mapping, Whole Exome Sequencing/statistics & numerical data, Identification (information), RARE VARIANTS, LOW-FREQUENCY, Female, ExomeBP Consortium, Life Sciences & Biomedicine, SUSCEPTIBILITY LOCI, Posterior probability, European Continental Ancestry Group, 030209 endocrinology & metabolism, Context (language use), Computational biology, Biology, GENOTYPE IMPUTATION, Article, White People, GENETIC ARCHITECTURE, 03 medical and health sciences, SDG 3 - Good Health and Well-being, QUALITY-CONTROL, Exome Sequencing, Genome-Wide Association Study/statistics & numerical data, Journal Article, GIANT Consortium, Humans, Genetic Predisposition to Disease, GENOME-WIDE ASSOCIATION, Alleles, Genetic association, 030304 developmental biology, FATTY LIVER-DISEASE, Science & Technology, Genetic Variation, 06 Biological Sciences, Genetic architecture, Minor allele frequency, BODY-MASS INDEX, 030104 developmental biology, Diabetes Mellitus, Type 2, Diabetes Mellitus, Type 2/classification, 030217 neurology & neurosurgery, Coding (social sciences), Genome-Wide Association Study, Developmental Biology
Abstract

Identification of coding variant associations for complex diseases offers a direct route to biological insight, but is dependent on appropriate inference concerning the causal impact of those variants on disease risk. We aggregated coding variant data for 81,412 type 2 diabetes (T2D) cases and 370,832 controls of diverse ancestry, identifying 40 distinct coding variant association signals (at 38 loci) reaching significance (p−7). Of these, 16 represent novel associations mapping outside known genome-wide association study (GWAS) signals. We make two important observations. First, despite a threefold increase in sample size over previous efforts, only five of the 40 signals are driven by variants with minor allele frequency 1.29. Second, we used GWAS data from 50,160 T2D cases and 465,272 controls of European ancestry to fine-map these associated coding variants in their regional context, with and without additional weighting to account for the global enrichment of complex trait association signals in coding exons. At the 37 signals for which we attempted fine-mapping, we demonstrate convincing support (posterior probability >80% under the “annotation-weighted” model) that coding variants are causal for the association at 16 (including novel signals involving POC5 p.His36Arg, ANKH p.Arg187Gln, WSCD2 p.Thr113Ile, PLCB3 p.Ser778Leu, and PNPLA3 p.Ile148Met). However, at 13 of the 37 loci, the associated coding variants represent “false leads” and naïve analysis could have led to an erroneous inference regarding the effector transcript mediating the signal. Accurate identification of validated targets is dependent on correct specification of the contribution of coding and non-coding mediated mechanisms at associated loci.

Published
2018
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46. Whole-Exome Sequencing Identifies Loci Associated with Blood Cell Traits and Reveals a Role for Alternative GFI1B Splice Variants in Human Hematopoiesis

Author

Raha Pazoki, Nora Franceschini, James S. Floyd, Guillaume Lettre, Fernando Rivadeneira, Abbas Dehghan, Leo-Pekka Lyytikäinen, Albert Hofman, Ming-Huei Chen, Eric Boerwinkle, Jill M. Johnsen, Mart Kals, Xiaoling Zhang, Lewis C. Becker, Jennifer A. Brody, Dennis O. Mook-Kanamori, Lu Chen, James G. Wilson, Rajiv K. Khajuria, Vijay G. Sankaran, Nathan Pankratz, Lisa R. Yanek, Leslie A. Lange, Mika Kähönen, Linda M. Polfus, Traci M. Bartz, Nena Matijevic, Oscar H. Franco, Donna M. Muzny, Keolu Fox, Richard A. Gibbs, Narayanan Veeraraghavan, Tõnu Esko, Aoi Wakabayashi, Gina M. Peloso, André G. Uitterlinden, Paul L. Auer, Frank J. A. van Rooij, Kenneth Rice, Santhi K. Ganesh, Terho Lehtimäki, Klaudia Walter, Ruifang Li-Gao, Ginger A. Metcalf, Jie Huang, Stephen S. Rich, Cornelia M. van Duijn, Nicole Soranzo, Bruce M. Psaty, Robert B. Wallace, Ursula M. Schick, Andres Metspalu, Olli T. Raitakari, Christopher J. O'Donnell, Alexander P. Reiner, Andrew D. Johnson, Epidemiology, and Internal Medicine

Subjects
0301 basic medicine, Blood Platelets, Megakaryocyte differentiation, DNA Mutational Analysis, 030204 cardiovascular system & hematology, Biology, Blood cell, 03 medical and health sciences, 0302 clinical medicine, Proto-Oncogene Proteins, Report, medicine, Genetics, CRISPR, Humans, splice, Exome, Genetics(clinical), Progenitor cell, Genetics (clinical), Exome sequencing, Gene Editing, Platelet Count, Alternative splicing, Correction, ta3121, Hematopoietic Stem Cells, Human genetics, 3. Good health, Hematopoiesis, Repressor Proteins, Haematopoiesis, Alternative Splicing, 030104 developmental biology, medicine.anatomical_structure, Genetic Loci, CRISPR-Cas Systems, Megakaryocytes
Abstract

Circulating blood cell counts and indices are important indicators of hematopoietic function and a number of clinical parameters, such as blood oxygen-carrying capacity, inflammation, and hemostasis. By performing whole-exome sequence association analyses of hematologic quantitative traits in 15,459 community-dwelling individuals, followed by in silico replication in up to 52,024 independent samples, we identified two previously undescribed coding variants associated with lower platelet count: a common missense variant in CPS1 (rs1047891, MAF = 0.33, discovery + replication p = 6.38 × 10(-10)) and a rare synonymous variant in GFI1B (rs150813342, MAF = 0.009, discovery + replication p = 1.79 × 10(-27)). By performing CRISPR/Cas9 genome editing in hematopoietic cell lines and follow-up targeted knockdown experiments in primary human hematopoietic stem and progenitor cells, we demonstrate an alternative splicing mechanism by which the GFI1B rs150813342 variant suppresses formation of a GFI1B isoform that preferentially promotes megakaryocyte differentiation and platelet production. These results demonstrate how unbiased studies of natural variation in blood cell traits can provide insight into the regulation of human hematopoiesis.

Published
2016

47. Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity

Author

Alison Pattie, Ailith Pirie, Francis S. Collins, Charles Kooperberg, Nienke van Leeuwen, Carmel Moore, Sharon L.R. Kardia, Neil R. Robertson, Lisa Bastarache, Allan Linneberg, Peter T. Campbell, Helena Kuivaniemi, Struan F.A. Grant, Sascha Fauser, Sekar Kathiresan, Lars Lind, Erin B. Ware, Olli T. Raitakari, Dawn M. Waterworth, James G. Wilson, Markus Perola, Chris J. Packard, Michelle L. O'Donoghue, Fredrik Karpe, Roel A. Ophoff, Sailaja Vedantam, Artitaya Lophatananon, Uwe Völker, Emmanouil Tsafantakis, Hakon Hakonarson, Dajiang J. Liu, Craig E. Pennell, Xueling Sim, Jennifer E. Huffman, Sandosh Padmanabhan, Digna R. Velez Edwards, Michiel L. Bots, Ayush Giri, Renée de Mutsert, Emanuele Di Angelantonio, Nicholas J. Wareham, Jin Li, Gail P. Jarvik, Evangelos Evangelou, Anne Tybjærg-Hansen, Patricia B. Munroe, Penny Gordon-Larsen, Lia E. Bang, Ivan Brandslund, Hester M. den Ruijter, Jussi Hernesniemi, Nancy L. Heard-Costa, Angela L. Mazul, Jonathan Tyrer, Danish Saleheen, Mark J. Caulfield, John Andrew Pospisilik, Annette Peters, Caroline Hayward, Iris M. Heid, J. Wouter Jukema, Valérie Turcot, Matt Neville, Rudolf Uher, Patricia A. Peyser, Jessica D. Faul, Asif Rasheed, Shuai Wang, John C. Chambers, Jordi Corominas Galbany, Murray H. Brilliant, Yucheng Jia, Torben Hansen, Veikko Salomaa, Mary F. Feitosa, Mathias Gorski, Li-An Lin, George Dedoussis, Honghuang Lin, Ethan M. Lange, Veronique Vitart, Bratati Kahali, Alexander Teumer, Jerome I. Rotter, Wayne H-H Sheu, Vilmantas Giedraitis, Aliki-Eleni Farmaki, Lorraine Southam, Ele Ferrannini, Anette P. Gjesing, Krina T. Zondervan, Stavroula Kanoni, David J. Roberts, Rebecca S. Fine, Svati H. Shah, Tugce Karaderi, Claudia Langenberg, Stefan Johansson, Elizabeth K. Speliotes, Alexander P. Reiner, Ching-Ti Liu, Yiqin Wang, Pål R. Njølstad, Gabriel Cuellar-Partida, Amanda J. Cox, Tim D. Spector, Paul W. Franks, Anke Tönjes, John D. Rioux, Jeffrey Haessler, Paul L. Auer, Ingrid B. Borecki, Deborah J. Thompson, Weihua Zhang, John R. B. Perry, Paul Elliott, Folkert W. Asselbergs, Myriam Fornage, Ken Sin Lo, Marie Moitry, Paul Mitchell, Martin den Heijer, Zoltán Kutalik, Tune H. Pers, Kari Stefansson, Kari Kuulasmaa, Robert E. Schoen, Mark C.H. De Groot, Laura M. Yerges-Armstrong, Jing Hua Zhao, Beverley Balkau, Peggy L. Peissig, Michael Boehnke, Janie Corley, Katharine R. Owen, Unnur Thorsteinsdottir, Naveed Sattar, Sita H. Vermeulen, Thomas N. Person, Mark I. McCarthy, Paul I.W. de Bakker, David Lamparter, Poorva Mudgal, Nicholette D. Palmer, Maria Karaleftheri, Jan-Håkan Jansson, Ozren Polasek, Ruth J. F. Loos, Daniel R. Witte, Dermot F. Reilly, Anubha Mahajan, Stella Trompet, James A. Perry, Yingchang Lu, Claudia Schurmann, Yii-Der Ida Chen, Hidetoshi Kitajima, Dale R. Nyholt, John Danesh, Pamela J. Schreiner, Narisu Narisu, Jose C. Florez, Adelheid Lempradl, Gerome Breen, Torben Jørgensen, Anu Loukola, Joe Dennis, Hans-Jörgen Grabe, Vilmundur Gudnason, Timo A. Lakka, Heather M. Highland, Sven Bergmann, Marie-Pierre Dubé, Giovanni Veronesi, Martina Müller-Nurasyid, Jaakko Tuomilehto, Nele Friedrich, Joel N. Hirschhorn, Pia R. Kamstrup, Nilesh J. Samani, Josh C. Denny, Mika Kähönen, Massimiliano Cocca, Liang Sun, Karina Meidtner, Carsten A. Böger, Sara M. Willems, Marcelo P. Segura-Lepe, Johanna Kuusisto, Hanieh Yaghootkar, Konstantin Strauch, Ruth Frikke-Schmidt, Jane Gibson, Matti Uusitupa, Oscar H. Franco, Yongmei Liu, Heather M. Stringham, Rohit Varma, Grant W. Montgomery, Dennis O. Mook-Kanamori, Stefania Cappellani, Paul L. Huang, Albert V. Smith, Eric Kim, Anke R. Hammerschlag, Katherine S. Ruth, Carolina Medina-Gomez, Gerard Pasterkamp, Cristen J. Willer, Alisa K. Manning, Frida Renström, René S. Kahn, Lili Milani, Feijie Wang, Tessel E. Galesloot, Fernando Rivadeneira, Leo-Pekka Lyytikäinen, Adam S. Butterworth, Tamara B. Harris, Matthew A. Allison, Paul M. Ridker, David J. Carey, Todd L. Edwards, Panos Deloukas, Xiuqing Guo, Lawrence F. Bielak, Leena Moilanen, Heiner Boeing, Peter Kovacs, Karen L. Mohlke, Myriam Rheinberger, Cramer Christensen, Betina H. Thuesen, Mike A. Nalls, Erik Ingelsson, Nicholas G. D. Masca, Colin N. A. Palmer, Audrey E. Hendricks, Linda Broer, Vanisha Mistry, Praveen Surendran, Audrey Y. Chu, Rainer Rauramaa, Angela D'Eustacchio, Helen Griffiths, Satu Männistö, Patrick T. Ellinor, Terho Lehtimäki, Katherine E. Tansey, I. Sadaf Farooqi, Gaëlle Marenne, Anneke I. den Hollander, Jessica van Setten, Hannu Puolijoki, Tinca J. C. Polderman, Timothy M. Frayling, Niels Grarup, Eric Boerwinkle, Gonçalo R. Abecasis, Adam E. Locke, Mengmeng Du, Manuel A. Rivas, Philippe Amouyel, Jaakko Kaprio, Leslie A. Lange, Loes M. Olde Loohuis, Trevor A. Mori, Lambertus A. Kiemeney, Wei Zhao, Eva Rb Petersen, Huaixing Li, Thomas W. Winkler, Tellervo Korhonen, Kathleen Stirrups, Jean Ferrières, Wei Zhou, Ian J. Deary, Guillaume Lettre, M. Arfan Ikram, Alex W. Hewitt, Marit E. Jørgensen, Ian Ford, Liang He, Mark Walker, Stefan Gustafsson, Andre Franke, Yao Hu, Jaana Lindström, Jonathan P. Bradfield, Anne E. Justice, Kristin L. Young, Sander W. van der Laan, Shuang Feng, Yadav Sapkota, Douglas F. Easton, Cornelia M. van Duijn, Amy J. Swift, Kjell Nikus, Helen R. Warren, Christian Theil Have, Wei Gan, Steven A. Lubitz, Harvey D. White, Pirjo Komulainen, John M. Starr, Jeffrey R. O'Connel, Anette Varbo, Daniel I. Chasman, Ruifang Li-Gao, Lynne E. Wagenknecht, Matthias Blüher, Xiaowei Zhan, Thomas F. Vogt, Eleftheria Zeggini, Tamuno Alfred, Katja K.H. Aben, Lars Wallentin, Joanna M. M. Howson, Jie Yao, Eulalia Catamo, Henrik Vestergaard, Gina M. Peloso, Markku Laakso, Matthias B. Schulze, Hayato Tada, Jennifer Wessel, Andrew R. Wood, Erwin P. Bottinger, Cora E. Lewis, Robin Young, Carol A. Wang, Oddgeir L. Holmen, Andrew J. Slater, Jean-Claude Tardif, Xu Lin, Inês Barroso, Gail Davies, Tibor V. Varga, Andrew J. Lotery, Igor Rudan, Andrew T. Hattersley, Michael Stumvoll, David Ellinghaus, Andrew C. Heath, Frank Kee, Christopher P. Nelson, Donald W. Bowden, Alison M. Dunning, Marianne Benn, Oluf Pedersen, Amber A. Burt, Aniruddh P. Patel, G. Kees Hovingh, David S. Crosslin, Gorm B. Jensen, Keng-Hung Lin, Dewan S. Alam, Jian'an Luan, Ying Wu, Tõnu Esko, Kathleen Mullan Harris, Antonietta Robino, Anne U. Jackson, Eirini Marouli, Robert A. Scott, Jette Bork-Jensen, Olov Rolandsson, Nanette R. Lee, Gerard Tromp, Megan L. Grove, Suthesh Sivapalaratnam, Sameer E. Al-Harthi, Roberta McKean-Cowdin, Paolo Gasparini, Ellen W. Demerath, Marco Brumat, Maggie C.Y. Ng, Børge G. Nordestgaard, Kari E. North, Rajiv Chowdhury, Mauno Vanhala, Andrew P. Morris, Sarah E. Medland, Sune F. Nielsen, Ilaria Gandin, Øyvind Helgeland, James P. Cook, Kent D. Taylor, Andrew D. Morris, Gudmar Thorleifsson, André G. Uitterlinden, Pang Yao, Valgerdur Steinthorsdottir, Eric B. Larson, Kerrin S. Small, Cecilia M. Lindgren, Dragana Vuckovic, Mariaelisa Graff, Fotios Drenos, Jaspal S. Kooner, Schurmann, Claudia [0000-0003-4158-9192], Justice, Anne E [0000-0002-8903-8712], Giri, Ayush [0000-0002-7786-4670], Locke, Adam E [0000-0001-6227-198X], Young, Kristin L [0000-0003-0070-6145], Medina-Gomez, Carolina [0000-0001-7999-5538], Winkler, Thomas W [0000-0003-0292-5421], Zeggini, Eleftheria [0000-0003-4238-659X], Zhao, Wei [0000-0002-8301-9297], Zondervan, Krina T [0000-0002-0275-9905], Pospisilik, John A [0000-0002-9745-0977], Rivadeneira, Fernando [0000-0001-9435-9441], Deloukas, Panos [0000-0001-9251-070X], Apollo - University of Cambridge Repository, Vascular Medicine, ACS - Amsterdam Cardiovascular Sciences, ACS - Atherosclerosis & ischemic syndromes, Internal Medicine, Epidemiology, Obstetrics & Gynecology, Radiology & Nuclear Medicine, CHD Exome+ Consortium, EPIC-CVD Consortium, ExomeBP Consortium, Global Lipids Genetic Consortium, GoT2D Genes Consortium, EPIC InterAct Consortium, INTERVAL Study, ReproGen Consortium, T2D-Genes Consortium, MAGIC Investigators, Understanding Society Scientific Group, Biological Psychology, Complex Trait Genetics, Amsterdam Neuroscience - Complex Trait Genetics, British Heart Foundation, Wellcome Trust, Medical Research Council (MRC), National Institute for Health Research, Home Office, National Institutes of Health, Imperial College Healthcare NHS Trust- BRC Funding, Turcot, Valérie, Lu, Yingchang, Highland, Heather M., Schurmann, Claudia, Justice, Anne E., Fine, Rebecca S., Bradfield, Jonathan P., Esko, Tõnu, Giri, Ayush, Graff, Mariaelisa, Guo, Xiuqing, Hendricks, Audrey E., Karaderi, Tugce, Lempradl, Adelheid, Locke, Adam E., Mahajan, Anubha, Marouli, Eirini, Sivapalaratnam, Suthesh, Young, Kristin L., Alfred, Tamuno, Feitosa, Mary F., Masca, Nicholas G. D., Manning, Alisa K., Medina-Gomez, Carolina, Mudgal, Poorva, Ng, Maggie C. Y., Reiner, Alex P., Vedantam, Sailaja, Willems, Sara M., Winkler, Thomas W., Abecasis, Gonçalo, Aben, Katja K., Alam, Dewan S., Alharthi, Sameer E., Allison, Matthew, Amouyel, Philippe, Asselbergs, Folkert W., Auer, Paul L., Balkau, Beverley, Bang, Lia E., Barroso, Inê, Bastarache, Lisa, Benn, Marianne, Bergmann, Sven, Bielak, Lawrence F., Blüher, Matthia, Boehnke, Michael, Boeing, Heiner, Boerwinkle, Eric, Böger, Carsten A., Bork-Jensen, Jette, Bots, Michiel L., Bottinger, Erwin P., Bowden, Donald W., Brandslund, Ivan, Breen, Gerome, Brilliant, Murray H., Broer, Linda, Brumat, Marco, Burt, Amber A., Butterworth, Adam S., Campbell, Peter T., Cappellani, Stefania, Carey, David J., Catamo, Eulalia, Caulfield, Mark J., Chambers, John C., Chasman, Daniel I., Chen, Yii-Der I., Chowdhury, Rajiv, Christensen, Cramer, Chu, Audrey Y., Cocca, Massimiliano, Collins, Francis S., Cook, James P., Corley, Janie, Corominas Galbany, Jordi, Cox, Amanda J., Crosslin, David S., Cuellar-Partida, Gabriel, D'Eustacchio, Angela, Danesh, John, Davies, Gail, Bakker, Paul I. W., Groot, Mark C. H., Mutsert, Renée, Deary, Ian J., Dedoussis, George, Demerath, Ellen W., Heijer, Martin, Hollander, Anneke I., Ruijter, Hester M., Dennis, Joe G., Denny, Josh C., Angelantonio, Emanuele, Drenos, Fotio, Du, Mengmeng, Dubé, Marie-Pierre, Dunning, Alison M., Easton, Douglas F., Edwards, Todd L., Ellinghaus, David, Ellinor, Patrick T., Elliott, Paul, Evangelou, Evangelo, Farmaki, Aliki-Eleni, Farooqi, I. Sadaf, Faul, Jessica D., Fauser, Sascha, Feng, Shuang, Ferrannini, Ele, Ferrieres, Jean, Florez, Jose C., Ford, Ian, Fornage, Myriam, Franco, Oscar H., Franke, Andre, Franks, Paul W., Friedrich, Nele, Frikke-Schmidt, Ruth, Galesloot, Tessel E., Gan, Wei, Gandin, Ilaria, Gasparini, Paolo, Gibson, Jane, Giedraitis, Vilmanta, Gjesing, Anette P., Gordon-Larsen, Penny, Gorski, Mathia, Grabe, Hans-Jörgen, Grant, Struan F. A., Grarup, Niel, Griffiths, Helen L., Grove, Megan L., Gudnason, Vilmundur, Gustafsson, Stefan, Haessler, Jeff, Hakonarson, Hakon, Hammerschlag, Anke R., Hansen, Torben, Harris, Kathleen Mullan, Harris, Tamara B., Hattersley, Andrew T., Have, Christian T., Hayward, Caroline, He, Liang, Heard-Costa, Nancy L., Heath, Andrew C., Heid, Iris M., Helgeland, Øyvind, Hernesniemi, Jussi, Hewitt, Alex W., Holmen, Oddgeir L., Hovingh, G. Kee, Howson, Joanna M. M., Hu, Yao, Huang, Paul L., Huffman, Jennifer E., Ikram, M. Arfan, Ingelsson, Erik, Jackson, Anne U., Jansson, Jan-Håkan, Jarvik, Gail P., Jensen, Gorm B., Jia, Yucheng, Johansson, Stefan, Jørgensen, Marit E., Jørgensen, Torben, Jukema, J. Wouter, Kahali, Bratati, Kahn, René S., Kähönen, Mika, Kamstrup, Pia R., Kanoni, Stavroula, Kaprio, Jaakko, Karaleftheri, Maria, Kardia, Sharon L. R., Karpe, Fredrik, Kathiresan, Sekar, Kee, Frank, Kiemeney, Lambertus A., Kim, Eric, Kitajima, Hidetoshi, Komulainen, Pirjo, Kooner, Jaspal S., Kooperberg, Charle, Korhonen, Tellervo, Kovacs, Peter, Kuivaniemi, Helena, Kutalik, Zoltán, Kuulasmaa, Kari, Kuusisto, Johanna, Laakso, Markku, Lakka, Timo A., Lamparter, David, Lange, Ethan M., Lange, Leslie A., Langenberg, Claudia, Larson, Eric B., Lee, Nanette R., Lehtimäki, Terho, Lewis, Cora E., Li, Huaixing, Li, Jin, Li-Gao, Ruifang, Lin, Honghuang, Lin, Keng-Hung, Lin, Li-An, Lin, Xu, Lind, Lar, Lindström, Jaana, Linneberg, Allan, Liu, Ching-Ti, Liu, Dajiang J., Liu, Yongmei, Lo, Ken S., Lophatananon, Artitaya, Lotery, Andrew J., Loukola, Anu, Luan, Jian'An, Lubitz, Steven A., Lyytikäinen, Leo-Pekka, Männistö, Satu, Marenne, Gaëlle, Mazul, Angela L., Mccarthy, Mark I., McKean-Cowdin, Roberta, Medland, Sarah E., Meidtner, Karina, Milani, Lili, Mistry, Vanisha, Mitchell, Paul, Mohlke, Karen L., Moilanen, Leena, Moitry, Marie, Montgomery, Grant W., Mook-Kanamori, Dennis O., Moore, Carmel, Mori, Trevor A., Morris, Andrew D., Morris, Andrew P., Müller-Nurasyid, Martina, Munroe, Patricia B., Nalls, Mike A., Narisu, Narisu, Nelson, Christopher P., Neville, Matt, Nielsen, Sune F., Nikus, Kjell, Njølstad, Pål R., Nordestgaard, Børge G., Nyholt, Dale R., O'Connel, Jeffrey R., O'Donoghue, Michelle L., Olde Loohuis, Loes M., Ophoff, Roel A., Owen, Katharine R., Packard, Chris J., Padmanabhan, Sandosh, Palmer, Colin N. A., Palmer, Nicholette D., Pasterkamp, Gerard, Patel, Aniruddh P., Pattie, Alison, Pedersen, Oluf, Peissig, Peggy L., Peloso, Gina M., Pennell, Craig E., Perola, Marku, Perry, James A., Perry, John R. B., Pers, Tune H., Person, Thomas N., Peters, Annette, Petersen, Eva R. B., Peyser, Patricia A., Pirie, Ailith, Polasek, Ozren, Polderman, Tinca J., Puolijoki, Hannu, Raitakari, Olli T., Rasheed, Asif, Rauramaa, Rainer, Reilly, Dermot F., Renström, Frida, Rheinberger, Myriam, Ridker, Paul M., Rioux, John D., Rivas, Manuel A., Roberts, David J., Robertson, Neil R., Robino, Antonietta, Rolandsson, Olov, Rudan, Igor, Ruth, Katherine S., Saleheen, Danish, Salomaa, Veikko, Samani, Nilesh J., Sapkota, Yadav, Sattar, Naveed, Schoen, Robert E., Schreiner, Pamela J., Schulze, Matthias B., Scott, Robert A., Segura-Lepe, Marcelo P., Shah, Svati H., Sheu, Wayne H. -H., Sim, Xueling, Slater, Andrew J., Small, Kerrin S., Smith, Albert V., Southam, Lorraine, Spector, Timothy D., Speliotes, Elizabeth K., Starr, John M., Stefansson, Kari, Steinthorsdottir, Valgerdur, Stirrups, Kathleen E., Strauch, Konstantin, Stringham, Heather M., Stumvoll, Michael, Sun, Liang, Surendran, Praveen, Swift, Amy J., Tada, Hayato, Tansey, Katherine E., Tardif, Jean-Claude, Taylor, Kent D., Teumer, Alexander, Thompson, Deborah J., Thorleifsson, Gudmar, Thorsteinsdottir, Unnur, Thuesen, Betina H., Tönjes, Anke, Tromp, Gerard, Trompet, Stella, Tsafantakis, Emmanouil, Tuomilehto, Jaakko, Tybjaerg-Hansen, Anne, Tyrer, Jonathan P., Uher, Rudolf, Uitterlinden, André G., Uusitupa, Matti, Laan, Sander W., Duijn, Cornelia M., Leeuwen, Nienke, Van Setten, Jessica, Vanhala, Mauno, Varbo, Anette, Varga, Tibor V., Varma, Rohit, Velez Edwards, Digna R., Vermeulen, Sita H., Veronesi, Giovanni, Vestergaard, Henrik, Vitart, Veronique, Vogt, Thomas F., Völker, Uwe, Vuckovic, Dragana, Wagenknecht, Lynne E., Walker, Mark, Wallentin, Lar, Wang, Feijie, Wang, Carol A., Wang, Shuai, Wang, Yiqin, Ware, Erin B., Wareham, Nicholas J., Warren, Helen R., Waterworth, Dawn M., Wessel, Jennifer, White, Harvey D., Willer, Cristen J., Wilson, James G., Witte, Daniel R., Wood, Andrew R., Wu, Ying, Yaghootkar, Hanieh, Yao, Jie, Yao, Pang, Yerges-Armstrong, Laura M., Young, Robin, Zeggini, Eleftheria, Zhan, Xiaowei, Zhang, Weihua, Zhao, Jing Hua, Zhao, Wei, Zhou, Wei, Zondervan, Krina T, Rotter, Jerome I., Pospisilik, John A., Rivadeneira, Fernando, Borecki, Ingrid B., Deloukas, Pano, Frayling, Timothy M., Lettre, Guillaume, North, Kari E., Lindgren, Cecilia M., Hirschhorn, Joel N., Loos, Ruth J. F., Internal medicine, AGEM - Endocrinology, metabolism and nutrition, Amsterdam Movement Sciences - Rehabilitation & Development, Amsterdam Movement Sciences - Restoration and Development, APH - Aging & Later Life, Physiology, and VU University medical center

Subjects
0301 basic medicine, Male, ReproGen Consortium, MathematicsofComputing_GENERAL, Genome-wide association study, medicine.disease_cause, Sensory disorders Donders Center for Medical Neuroscience [Radboudumc 12], Body Mass Index, genetics [Obesity], 0302 clinical medicine, Gene Frequency, Glucose homeostasis, Adult, Animals, Drosophila/genetics, Energy Intake/genetics, Energy Metabolism/genetics, Female, Genetic Variation, Humans, Obesity/genetics, Proteins/genetics, Syndrome, 11 Medical and Health Sciences, 2. Zero hunger, Genetics, Genetics & Heredity, Mutation, CHD Exome+ Consortium, body mass index, TheoryofComputation_GENERAL, T2D-Genes Consortium, GENOME-WIDE ASSOCIATION, MELANOCORTIN-4 RECEPTOR GENE, DONEPEZIL 23 MG, FRAMESHIFT MUTATION, GLUCOSE-HOMEOSTASIS, HYPOTHALAMIC AMPK, CODING VARIANTS, BLOOD-PRESSURE, RARE, LOCI, Urological cancers Radboud Institute for Health Sciences [Radboudumc 15], Drosophila, ExomeBP Consortium, Life Sciences & Biomedicine, INTERVAL Study, Understanding Society Scientific Group, EPIC InterAct Consortium, genetics [Energy Metabolism], Biology, EPIC-CVD Consortium, Frameshift mutation, 03 medical and health sciences, MAGIC Investigators, All institutes and research themes of the Radboud University Medical Center, Genetic, SDG 3 - Good Health and Well-being, ddc:570, genetics [Drosophila], medicine, Journal Article, Global Lipids Genetic Consortium, Obesity, Gene, Allele frequency, Genetic association, Science & Technology, Proteins, 06 Biological Sciences, genetics [Proteins], Minor allele frequency, 030104 developmental biology, GoT2D Genes Consortium, Energy Intake, Energy Metabolism, genetics [Energy Intake], 030217 neurology & neurosurgery, Developmental Biology
Abstract

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

Published
2018
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48. New Sequencing technologies help revealing unexpected mutations in Autosomal Dominant Hypercholesterolemia

Author

Jean-Pierre Rabès, Mathilde Varret, Catherine Boileau, Marianne Abifadel, Eric Bruckert, Gina M. Peloso, Ali Ben-Djoudi-Ouadda, Josée Hamelin, Nabil G. Seidah, Youmna Ghaleb, Nathan O. Stitziel, Valérie Carreau, Petra El Khoury, Sandy Elbitar, Delia Susan-Resiga, Laboratoire de Recherche Vasculaire Translationnelle (LVTS (UMR_S_1148 / U1148)), Université Paris 13 (UP13)-Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Saint-Joseph de Beyrouth (USJ), Université Paris Diderot - Paris 7 (UPD7), Université de Montréal (UdeM), Boston University [Boston] (BU), The McDonnell Genome Institute (MGI), Washington University in Saint Louis (WUSTL), Université de Versailles Saint-Quentin-en-Yvelines - UFR Sciences de la santé Simone Veil (UVSQ Santé), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Service de Nutrition [CHU Pitié-Salpétrière], Institut E3M [CHU Pitié-Salpêtrière], CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Université Pierre et Marie Curie - Paris 6 (UPMC), AP-HP - Hôpital Bichat - Claude Bernard [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Service de nutrition [CHU Pitié-Salpétrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], and Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)

Subjects
0301 basic medicine, Male, Heterozygote, Apolipoprotein B, lcsh:Medicine, 030204 cardiovascular system & hematology, medicine.disease_cause, Compound heterozygosity, Article, Hyperlipoproteinemia Type II, 03 medical and health sciences, Exon, 0302 clinical medicine, Chromosome Segregation, medicine, Humans, Family, lcsh:Science, Gene, Exome, Exome sequencing, Apolipoproteins B, Genetics, Mutation, Multidisciplinary, biology, lcsh:R, nutritional and metabolic diseases, High-Throughput Nucleotide Sequencing, [SDV.MHEP.EM]Life Sciences [q-bio]/Human health and pathology/Endocrinology and metabolism, 3. Good health, Pedigree, 030104 developmental biology, HEK293 Cells, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, LDL receptor, biology.protein, lcsh:Q, lipids (amino acids, peptides, and proteins), Female, Proprotein Convertase 9
Abstract

Autosomal dominant hypercholesterolemia (ADH) is characterized by elevated LDL-C levels leading to coronary heart disease. Four genes are implicated in ADH: LDLR, APOB, PCSK9 and APOE. Our aim was to identify new mutations in known genes, or in new genes implicated in ADH. Thirteen French families with ADH were recruited and studied by exome sequencing after exclusion, in their probands, of mutations in the LDLR, PCSK9 and APOE genes and fragments of exons 26 and 29 of APOB gene. We identified in one family a p.Arg50Gln mutation in the APOB gene, which occurs in a region not usually associated with ADH. Segregation and in-silico analysis suggested that this mutation is disease causing in the family. We identified in another family with the p.Ala3396Thr mutation of APOB, one patient with a severe phenotype carrying also a mutation in PCSK9: p.Arg96Cys. This is the first compound heterozygote reported with a mutation in APOB and PCSK9. Functional studies proved that the p.Arg96Cys mutation leads to increased LDL receptor degradation. This work shows that Next-Generation Sequencing (exome, genome or targeted sequencing) are powerful tools to find new mutations and identify compound heterozygotes, which will lead to better diagnosis and treatment of ADH.

Published
2018
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49. Association of Triglyceride-Related Genetic Variants with Mitral Annular Calcification

Author

M.J. Budoff, Kevin Luk, Tamara B. Harris, Kathleen F. Kerr, Vilmundur Gudnason, George Thanassoulis, Mehdi Afshar, Jerome I. Rotter, Quenna Wong, Wendy S. Post, James C. Engert, Gina M. Peloso, Christopher J. O'Donnell, Stephen S. Rich, Line Dufresne, L. Adrienne Cupples, Ron Do, David S. Owens, and Albert V. Smith

Subjects
Male, medicine.medical_specialty, Pathology, Heart Valve Diseases, 030204 cardiovascular system & hematology, Article, 03 medical and health sciences, 0302 clinical medicine, Mitral valve stenosis, Risk Factors, Internal medicine, Mitral valve, Mendelian randomization, Genetic predisposition, medicine, Humans, Genetic Predisposition to Disease, Prospective Studies, 030212 general & internal medicine, Risk factor, Triglycerides, Aged, Polymorphism, Genetic, Framingham Risk Score, business.industry, Incidence, Genetic Variation, Mitral Valve Insufficiency, Calcinosis, Odds ratio, Middle Aged, medicine.disease, medicine.anatomical_structure, Cardiology, Mitral Valve, Female, Tomography, X-Ray Computed, Cardiology and Cardiovascular Medicine, Mitral valve regurgitation, business, Follow-Up Studies
Abstract

Background Mitral annular calcium (MAC), commonly identified by cardiac imaging, is associated with cardiovascular events and predisposes to the development of clinically important mitral valve regurgitation and mitral valve stenosis. However, its biological determinants remain largely unknown. Objectives The authors sought to evaluate whether a genetic predisposition to elevations in plasma lipids is associated with the presence of MAC. Methods The authors used 3 separate Mendelian randomization techniques to evaluate the associations of lipid genetic risk scores (GRS) with MAC in 3 large patient cohorts: the Framingham Health Study, MESA (Multiethnic European Study of Atherosclerosis), and the AGE-RS (Age, Gene/Environment Susceptibility-Reykjavik Study). The authors provided cross-ethnicity replication in the MESA Hispanic-American participants. Results MAC was present in 1,149 participants (20.4%). In pooled analyses across all 3 cohorts, a triglyceride GRS was significantly associated with the presence of MAC (odds ratio [OR] per triglyceride GRS unit: 1.73; 95% confidence interval [CI]: 1.24 to 2.41; p = 0.0013). Neither low- nor high-density lipoprotein cholesterol GRS was significantly associated with MAC. Results were consistent in cross-ethnicity analyses among the MESA Hispanic-Americans cohort (OR per triglyceride GRS unit: 2.04; 95% CI: 1.03 to 4.03; p = 0.04). In joint meta-analysis across all included cohorts, the triglyceride GRS was associated with MAC (OR per triglyceride GRS unit: 1.79; 95% CI: 1.32 to 2.41; p = 0.0001). The results were robust to several sensitivity analyses that limit both known and unknown forms of genetic pleiotropy. Conclusions Genetic predisposition to elevated triglyceride levels was associated with the presence of MAC, a risk factor for clinically significant mitral valve disease, suggesting a causal association. Whether reducing triglyceride levels can lower the incidence of clinically significant mitral valve disease requires further study.

Published
2017

50. Protein Truncating Variants at the Cholesteryl Ester Transfer Protein Gene and Risk for Coronary Heart Disease

Author

Jaume Marrugat, Fumihiko Takeuchi, Tanya M. Teslovich, Norihiro Kato, Masa-aki Kawashiri, Jun-Sing Wang, H. Lester Kirchner, Peter S. Braund, Masahiro Nakatochi, Heribert Schunkert, Rosanna Asselta, Danish Saleheen, Daniel R. Lavage, Dustin N. Hartze, Roberto Elosua, Stacey Gabriel, Ingrid B. Borecki, Nilesh J. Samani, Frederick E. Dewey, David J. Carey, Yukihide Momozawa, Chao A. Hsiung, Jerome I. Rotter, Michael F. Murray, Matthew J. Bown, John Danesh, Shane McCarthy, Piera Angelica Merlini, Joseph B. Leader, Namrata Gupta, Tomohiro Katsuya, Gina M. Peloso, Cristen J. Willer, Eitaro Nakashima, Hayato Tada, Gonçalo R. Abecasis, Amit Khera, Pradeep Natarajan, Ken Yamamoto, Derek Klarin, Alistair S. Hall, Connor A. Emdin, Thorsten Kessler, Seyedeh M. Zekavat, Mitsuhiro Yokota, Yii-Der Ida Chen, Akihiro Nomura, Martin Farrall, Hong-Hee Won, Michiaki Kubo, Hugh Watkins, Eric S. Lander, Sekar Kathiresan, James G. Wilson, Ruth McPherson, Masakazu Yamagishi, Kaoru Ito, Adolfo Correa, Jyh-Ming Jimmy Juang, J. Neil Manus, Shih-Yi Lin, Diego Ardissino, Stefano Duga, Daniel J. Rader, Akihiro Inazu, Danesh, John [0000-0003-1158-6791], and Apollo - University of Cambridge Repository

Subjects
0301 basic medicine, Adult, Male, Human dna, Physiology, Clinical Sciences, cholesteryl ester transfer protein, Coronary Disease, Cardiorespiratory Medicine and Haematology, 030204 cardiovascular system & hematology, Cardiovascular, Article, Truncate, lipids, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Cholesterylester transfer protein, Genetics, Humans, Gene, Heart Disease - Coronary Heart Disease, Aged, biology, Chemistry, case-control studies, Genetic Variation, Middle Aged, Atherosclerosis, Coronary heart disease, Cholesterol Ester Transfer Proteins, Heart Disease, 030104 developmental biology, Cardiovascular System & Hematology, Case-Control Studies, Cancer research, biology.protein, lipids (amino acids, peptides, and proteins), Female, Cardiology and Cardiovascular Medicine
Abstract

Rationale : Therapies that inhibit CETP (cholesteryl ester transfer protein) have failed to demonstrate a reduction in risk for coronary heart disease (CHD). Human DNA sequence variants that truncate the CETP gene may provide insight into the efficacy of CETP inhibition. Objective: To test whether protein-truncating variants (PTVs) at the CETP gene were associated with plasma lipid levels and CHD. Methods and Results: We sequenced the exons of the CETP gene in 58 469 participants from 12 case–control studies (18 817 CHD cases, 39 652 CHD-free controls). We defined PTV as those that lead to a premature stop, disrupt canonical splice sites, or lead to insertions/deletions that shift frame. We also genotyped 1 Japanese-specific PTV in 27561 participants from 3 case–control studies (14 286 CHD cases, 13 275 CHD-free controls). We tested association of CETP PTV carrier status with both plasma lipids and CHD. Among 58 469 participants with CETP gene-sequencing data available, average age was 51.5 years and 43% were women; 1 in 975 participants carried a PTV at the CETP gene. Compared with noncarriers, carriers of PTV at CETP had higher high-density lipoprotein cholesterol (effect size, 22.6 mg/dL; 95% confidence interval, 18–27; P −4 ), lower low-density lipoprotein cholesterol (−12.2 mg/dL; 95% confidence interval, −23 to −0.98; P =0.033), and lower triglycerides (−6.3%; 95% confidence interval, −12 to −0.22; P =0.043). CETP PTV carrier status was associated with reduced risk for CHD (summary odds ratio, 0.70; 95% confidence interval, 0.54–0.90; P =5.1×10 −3 ). Conclusions: Compared with noncarriers, carriers of PTV at CETP displayed higher high-density lipoprotein cholesterol, lower low-density lipoprotein cholesterol, lower triglycerides, and lower risk for CHD.

Published
2017

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