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1. Validation of human telomere length multi-ancestry meta-analysis association signals identifies POP5 and KBTBD6 as human telomere length regulation genes

Author: Rebecca Keener, Surya B. Chhetri, Carla J. Connelly, Margaret A. Taub, Matthew P. Conomos, Joshua Weinstock, Bohan Ni, Benjamin Strober, Stella Aslibekyan, Paul L. Auer, Lucas Barwick, Lewis C. Becker, John Blangero, Eugene R. Bleecker, Jennifer A. Brody, Brian E. Cade, Juan C. Celedon, Yi-Cheng Chang, L. Adrienne Cupples, Brian Custer, Barry I. Freedman, Mark T. Gladwin, Susan R. Heckbert, Lifang Hou, Marguerite R. Irvin, Carmen R. Isasi, Jill M. Johnsen, Eimear E. Kenny, Charles Kooperberg, Ryan L. Minster, Take Naseri, Satupa’itea Viali, Sergei Nekhai, Nathan Pankratz, Patricia A. Peyser, Kent D. Taylor, Marilyn J. Telen, Baojun Wu, Lisa R. Yanek, Ivana V. Yang, Christine Albert, Donna K. Arnett, Allison E. Ashley-Koch, Kathleen C. Barnes, Joshua C. Bis, Thomas W. Blackwell, Eric Boerwinkle, Esteban G. Burchard, April P. Carson, Zhanghua Chen, Yii-Der Ida Chen, Dawood Darbar, Mariza de Andrade, Patrick T. Ellinor, Myriam Fornage, Bruce D. Gelb, Frank D. Gilliland, Jiang He, Talat Islam, Stefan Kaab, Sharon L. R. Kardia, Shannon Kelly, Barbara A. Konkle, Rajesh Kumar, Ruth J. F. Loos, Fernando D. Martinez, Stephen T. McGarvey, Deborah A. Meyers, Braxton D. Mitchell, Courtney G. Montgomery, Kari E. North, Nicholette D. Palmer, Juan M. Peralta, Benjamin A. Raby, Susan Redline, Stephen S. Rich, Dan Roden, Jerome I. Rotter, Ingo Ruczinski, David Schwartz, Frank Sciurba, M. Benjamin Shoemaker, Edwin K. Silverman, Moritz F. Sinner, Nicholas L. Smith, Albert V. Smith, Hemant K. Tiwari, Ramachandran S. Vasan, Scott T. Weiss, L. Keoki Williams, Yingze Zhang, Elad Ziv, Laura M. Raffield, Alexander P. Reiner, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Hematology and Hemostasis Working Group, TOPMed Structural Variation Working Group, Marios Arvanitis, Carol W. Greider, Rasika A. Mathias, and Alexis Battle
Subjects: Science
Abstract: Abstract Genome-wide association studies (GWAS) have become well-powered to detect loci associated with telomere length. However, no prior work has validated genes nominated by GWAS to examine their role in telomere length regulation. We conducted a multi-ancestry meta-analysis of 211,369 individuals and identified five novel association signals. Enrichment analyses of chromatin state and cell-type heritability suggested that blood/immune cells are the most relevant cell type to examine telomere length association signals. We validated specific GWAS associations by overexpressing KBTBD6 or POP5 and demonstrated that both lengthened telomeres. CRISPR/Cas9 deletion of the predicted causal regions in K562 blood cells reduced expression of these genes, demonstrating that these loci are related to transcriptional regulation of KBTBD6 and POP5. Our results demonstrate the utility of telomere length GWAS in the identification of telomere length regulation mechanisms and validate KBTBD6 and POP5 as genes affecting telomere length regulation.
Published: 2024
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2. Epigenome-wide DNA methylation association study of circulating IgE levels identifies novel targets for asthmaResearch in context

Author: Kathryn Recto, Priyadarshini Kachroo, Tianxiao Huan, David Van Den Berg, Gha Young Lee, Helena Bui, Dong Heon Lee, Jessica Gereige, Chen Yao, Shih-Jen Hwang, Roby Joehanes, Scott T. Weiss, George T. O’Connor, Daniel Levy, Dawn L. DeMeo, Namiko Abe, Gonçalo Abecasis, Francois Aguet, Christine Albert, Laura Almasy, Alvaro Alonso, Seth Ament, Peter Anderson, Pramod Anugu, Deborah Applebaum-Bowden, Kristin Ardlie, Dan Arking, Donna K. Arnett, Allison Ashley-Koch, Stella Aslibekyan, Tim Assimes, Paul Auer, Dimitrios Avramopoulos, Najib Ayas, Adithya Balasubramanian, John Barnard, Kathleen Barnes, R. Graham Barr, Emily Barron-Casella, Lucas Barwick, Terri Beaty, Gerald Beck, Diane Becker, Lewis Becker, Rebecca Beer, Amber Beitelshees, Emelia Benjamin, Takis Benos, Marcos Bezerra, Larry Bielak, Joshua Bis, Thomas Blackwell, John Blangero, Nathan Blue, Eric Boerwinkle, Donald W. Bowden, Russell Bowler, Jennifer Brody, Ulrich Broeckel, Jai Broome, Deborah Brown, Karen Bunting, Esteban Burchard, Carlos Bustamante, Erin Buth, Brian Cade, Jonathan Cardwell, Vincent Carey, Julie Carrier, April P. Carson, Cara Carty, Richard Casaburi, Juan P. Casas Romero, James Casella, Peter Castaldi, Mark Chaffin, Christy Chang, Yi-Cheng Chang, Daniel Chasman, Sameer Chavan, Bo-Juen Chen, Wei-Min Chen, Yii-Der Ida Chen, Michael Cho, Seung Hoan Choi, Lee-Ming Chuang, Mina Chung, Ren-Hua Chung, Clary Clish, Suzy Comhair, Matthew Conomos, Elaine Cornell, Adolfo Correa, Carolyn Crandall, James Crapo, L. Adrienne Cupples, Joanne Curran, Jeffrey Curtis, Brian Custer, Coleen Damcott, Dawood Darbar, Sean David, Colleen Davis, Michelle Daya, Mariza de Andrade, Lisa de las Fuentes, Paul de Vries, Michael DeBaun, Ranjan Deka, Dawn DeMeo, Scott Devine, Huyen Dinh, Harsha Doddapaneni, Qing Duan, Shannon Dugan-Perez, Ravi Duggirala, Jon Peter Durda, Susan K. Dutcher, Charles Eaton, Lynette Ekunwe, Adel El Boueiz, Patrick Ellinor, Leslie Emery, Serpil Erzurum, Charles Farber, Jesse Farek, Tasha Fingerlin, Matthew Flickinger, Myriam Fornage, Nora Franceschini, Chris Frazar, Mao Fu, Stephanie M. Fullerton, Lucinda Fulton, Stacey Gabriel, Weiniu Gan, Shanshan Gao, Yan Gao, Margery Gass, Heather Geiger, Bruce Gelb, Mark Geraci, Soren Germer, Robert Gerszten, Auyon Ghosh, Richard Gibbs, Chris Gignoux, Mark Gladwin, David Glahn, Stephanie Gogarten, Da-Wei Gong, Harald Goring, Sharon Graw, Kathryn J. Gray, Daniel Grine, Colin Gross, C. Charles Gu, Yue Guan, Xiuqing Guo, Namrata Gupta, Jeff Haessler, Michael Hall, Yi Han, Patrick Hanly, Daniel Harris, Nicola L. Hawley, Jiang He, Ben Heavner, Susan Heckbert, Ryan Hernandez, David Herrington, Craig Hersh, Bertha Hidalgo, James Hixson, Brian Hobbs, John Hokanson, Elliott Hong, Karin Hoth, Chao (Agnes) Hsiung, Jianhong Hu, Yi-Jen Hung, Haley Huston, Chii Min Hwu, Marguerite Ryan Irvin, Rebecca Jackson, Deepti Jain, Cashell Jaquish, Jill Johnsen, Andrew Johnson, Craig Johnson, Rich Johnston, Kimberly Jones, Hyun Min Kang, Robert Kaplan, Sharon Kardia, Shannon Kelly, Eimear Kenny, Michael Kessler, Alyna Khan, Ziad Khan, Wonji Kim, John Kimoff, Greg Kinney, Barbara Konkle, Charles Kooperberg, Holly Kramer, Christoph Lange, Ethan Lange, Leslie Lange, Cathy Laurie, Cecelia Laurie, Meryl LeBoff, Jiwon Lee, Sandra Lee, Wen-Jane Lee, Jonathon LeFaive, David Levine, Joshua Lewis, Xiaohui Li, Yun Li, Henry Lin, Honghuang Lin, Xihong Lin, Simin Liu, Yongmei Liu, Yu Liu, Ruth J.F. Loos, Steven Lubitz, Kathryn Lunetta, James Luo, Ulysses Magalang, Michael Mahaney, Barry Make, Ani Manichaikul, Alisa Manning, JoAnn Manson, Lisa Martin, Melissa Marton, Susan Mathai, Rasika Mathias, Susanne May, Patrick McArdle, Merry-Lynn McDonald, Sean McFarland, Stephen McGarvey, Daniel McGoldrick, Caitlin McHugh, Becky McNeil, Hao Mei, James Meigs, Vipin Menon, Luisa Mestroni, Ginger Metcalf, Deborah A. Meyers, Emmanuel Mignot, Julie Mikulla, Nancy Min, Mollie Minear, Ryan L. Minster, Braxton D. Mitchell, Matt Moll, Zeineen Momin, May E. Montasser, Courtney Montgomery, Donna Muzny, Josyf C. Mychaleckyj, Girish Nadkarni, Rakhi Naik, Take Naseri, Pradeep Natarajan, Sergei Nekhai, Sarah C. Nelson, Bonnie Neltner, Caitlin Nessner, Deborah Nickerson, Osuji Nkechinyere, Kari North, Jeff O'Connell, Tim O'Connor, Heather Ochs-Balcom, Geoffrey Okwuonu, Allan Pack, David T. Paik, Nicholette Palmer, James Pankow, George Papanicolaou, Cora Parker, Gina Peloso, Juan Manuel Peralta, Marco Perez, James Perry, Ulrike Peters, Patricia Peyser, Lawrence S. Phillips, Jacob Pleiness, Toni Pollin, Wendy Post, Julia Powers Becker, Meher Preethi Boorgula, Michael Preuss, Bruce Psaty, Pankaj Qasba, Dandi Qiao, Zhaohui Qin, Nicholas Rafaels, Laura Raffield, Mahitha Rajendran, Vasan S. Ramachandran, D.C. Rao, Laura Rasmussen-Torvik, Aakrosh Ratan, Susan Redline, Robert Reed, Catherine Reeves, Elizabeth Regan, Alex Reiner, Muagututi‘a Sefuiva Reupena, Ken Rice, Stephen Rich, Rebecca Robillard, Nicolas Robine, Dan Roden, Carolina Roselli, Jerome Rotter, Ingo Ruczinski, Alexi Runnels, Pamela Russell, Sarah Ruuska, Kathleen Ryan, Ester Cerdeira Sabino, Danish Saleheen, Shabnam Salimi, Sejal Salvi, Steven Salzberg, Kevin Sandow, Vijay G. Sankaran, Jireh Santibanez, Karen Schwander, David Schwartz, Frank Sciurba, Christine Seidman, Jonathan Seidman, Frédéric Sériès, Vivien Sheehan, Stephanie L. Sherman, Amol Shetty, Aniket Shetty, Wayne Hui-Heng Sheu, M. Benjamin Shoemaker, Brian Silver, Edwin Silverman, Robert Skomro, Albert Vernon Smith, Jennifer Smith, Josh Smith, Nicholas Smith, Tanja Smith, Sylvia Smoller, Beverly Snively, Michael Snyder, Tamar Sofer, Nona Sotoodehnia, Adrienne M. Stilp, Garrett Storm, Elizabeth Streeten, Jessica Lasky Su, Yun Ju Sung, Jody Sylvia, Adam Szpiro, Daniel Taliun, Hua Tang, Margaret Taub, Kent Taylor, Matthew Taylor, Simeon Taylor, Marilyn Telen, Timothy A. Thornton, Machiko Threlkeld, Lesley Tinker, David Tirschwell, Sarah Tishkoff, Hemant Tiwari, Catherine Tong, Russell Tracy, Michael Tsai, Dhananjay Vaidya, Peter VandeHaar, Scott Vrieze, Tarik Walker, Robert Wallace, Avram Walts, Fei Fei Wang, Heming Wang, Jiongming Wang, Karol Watson, Jennifer Watt, Daniel E. Weeks, Joshua Weinstock, Bruce Weir, Lu-Chen Weng, Jennifer Wessel, Cristen Willer, Kayleen Williams, L. Keoki Williams, Scott Williams, Carla Wilson, James Wilson, Lara Winterkorn, Quenna Wong, Baojun Wu, Joseph Wu, Huichun Xu, Lisa Yanek, Ivana Yang, Ketian Yu, Seyedeh Maryam Zekavat, Yingze Zhang, Snow Xueyan Zhao, Wei Zhao, Xiaofeng Zhu, Elad Ziv, Michael Zody, and Sebastian Zoellner
Subjects: EWAS, DNA methylation, IgE, Asthma, RNA-Sequencing, Mendelian randomization, Medicine, Medicine (General), R5-920
Abstract: Summary: Background: Identifying novel epigenetic signatures associated with serum immunoglobulin E (IgE) may improve our understanding of molecular mechanisms underlying asthma and IgE-mediated diseases. Methods: We performed an epigenome-wide association study using whole blood from Framingham Heart Study (FHS; n = 3,471, 46% females) participants and validated results using the Childhood Asthma Management Program (CAMP; n = 674, 39% females) and the Genetic Epidemiology of Asthma in Costa Rica Study (CRA; n = 787, 41% females). Using the closest gene to each IgE-associated CpG, we highlighted biologically plausible pathways underlying IgE regulation and analyzed the transcription patterns linked to IgE-associated CpGs (expression quantitative trait methylation loci; eQTMs). Using prior UK Biobank summary data from genome-wide association studies of asthma and allergy, we performed Mendelian randomization (MR) for causal inference testing using the IgE-associated CpGs from FHS with methylation quantitative trait loci (mQTLs) as instrumental variables. Findings: We identified 490 statistically significant differentially methylated CpGs associated with IgE in FHS, of which 193 (39.3%) replicated in CAMP and CRA (FDR < 0.05). Gene ontology analysis revealed enrichment in pathways related to transcription factor binding, asthma, and other immunological processes. eQTM analysis identified 124 cis-eQTMs for 106 expressed genes (FDR < 0.05). MR in combination with drug-target analysis revealed CTSB and USP20 as putatively causal regulators of IgE levels (Bonferroni adjusted P
Published: 2023
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3. 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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4. Whole genome sequence association analysis of fasting glucose and fasting insulin levels in diverse cohorts from the NHLBI TOPMed program

Author: Daniel DiCorpo, Sheila M. Gaynor, Emily M. Russell, Kenneth E. Westerman, Laura M. Raffield, Timothy D. Majarian, Peitao Wu, Chloé Sarnowski, Heather M. Highland, Anne Jackson, Natalie R. Hasbani, Paul S. de Vries, Jennifer A. Brody, Bertha Hidalgo, Xiuqing Guo, James A. Perry, Jeffrey R. O’Connell, Samantha Lent, May E. Montasser, Brian E. Cade, Deepti Jain, Heming Wang, Ricardo D’Oliveira Albanus, Arushi Varshney, Lisa R. Yanek, Leslie Lange, Nicholette D. Palmer, Marcio Almeida, Juan M. Peralta, Stella Aslibekyan, Abigail S. Baldridge, Alain G. Bertoni, Lawrence F. Bielak, Chung-Shiuan Chen, Yii-Der Ida Chen, Won Jung Choi, Mark O. Goodarzi, James S. Floyd, Marguerite R. Irvin, Rita R. Kalyani, Tanika N. Kelly, Seonwook Lee, Ching-Ti Liu, Douglas Loesch, JoAnn E. Manson, Ryan L. Minster, Take Naseri, James S. Pankow, Laura J. Rasmussen-Torvik, Alexander P. Reiner, Muagututi’a Sefuiva Reupena, Elizabeth Selvin, Jennifer A. Smith, Daniel E. Weeks, Huichun Xu, Jie Yao, Wei Zhao, Stephen Parker, Alvaro Alonso, Donna K. Arnett, John Blangero, Eric Boerwinkle, Adolfo Correa, L. Adrienne Cupples, Joanne E. Curran, Ravindranath Duggirala, Jiang He, Susan R. Heckbert, Sharon L. R. Kardia, Ryan W. Kim, Charles Kooperberg, Simin Liu, Rasika A. Mathias, Stephen T. McGarvey, Braxton D. Mitchell, Alanna C. Morrison, Patricia A. Peyser, Bruce M. Psaty, Susan Redline, Alan R. Shuldiner, Kent D. Taylor, Ramachandran S. Vasan, Karine A. Viaud-Martinez, Jose C. Florez, James G. Wilson, Robert Sladek, Stephen S. Rich, Jerome I. Rotter, Xihong Lin, Josée Dupuis, James B. Meigs, Jennifer Wessel, and Alisa K. Manning
Subjects: Biology (General), QH301-705.5
Abstract: This study of 23,000 non-diabetic individuals highlights loci associated with fasting glucose and fasting insulin in diverse cohorts with whole genome sequence data.
Published: 2022
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5. Lymphocyte activation gene-3-associated protein networks are associated with HDL-cholesterol and mortality in the Trans-omics for Precision Medicine program

Author: Ani Manichaikul, Honghuang Lin, Chansuk Kang, Chaojie Yang, Stephen S. Rich, Kent D. Taylor, Xiuqing Guo, Jerome I. Rotter, W. Craig Johnson, Elaine Cornell, Russell P. Tracy, J. Peter Durda, Yongmei Liu, Ramachandran S. Vasan, L. Adrienne Cupples, Robert E. Gerszten, Clary B. Clish, Deepti Jain, Matthew P. Conomos, Thomas Blackwell, George J. Papanicolaou, and Annabelle Rodriguez
Subjects: Biology (General), QH301-705.5
Abstract: Rodriguez et al. use whole genome sequencing and plasma proteomics from the Multi-Ethnic Study of Atherosclerosis (MESA) and the Framingham Heart Study (FHS) cohorts of the Trans-Omics for Precision Medicine program and perform in situ Hi-C chromatin capture in cell lines isolated from four MESA participants. They demonstrate that lymphocyte activation gene-3 protein networks are associated with HDL-cholesterol and mortality, which could guide the development of precision medicine.
Published: 2022
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6. Whole-exome sequence analysis of anthropometric traits illustrates challenges in identifying effects of rare genetic variants

Author: Kristin L. Young, Virginia Fisher, Xuan Deng, Jennifer A. Brody, Misa Graff, Elise Lim, Bridget M. Lin, Hanfei Xu, Najaf Amin, Ping An, Stella Aslibekyan, Alison E. Fohner, Bertha Hidalgo, Petra Lenzini, Robert Kraaij, Carolina Medina-Gomez, Ivana Prokić, Fernando Rivadeneira, Colleen Sitlani, Ran Tao, Jeroen van Rooij, Di Zhang, Jai G. Broome, Erin J. Buth, Benjamin D. Heavner, Deepti Jain, Albert V. Smith, Kathleen Barnes, Meher Preethi Boorgula, Sameer Chavan, Dawood Darbar, Mariza De Andrade, Xiuqing Guo, Jeffrey Haessler, Marguerite R. Irvin, Rita R. Kalyani, Sharon L.R. Kardia, Charles Kooperberg, Wonji Kim, Rasika A. Mathias, Merry-Lynn McDonald, Braxton D. Mitchell, Patricia A. Peyser, Elizabeth A. Regan, Susan Redline, Alexander P. Reiner, Stephen S. Rich, Jerome I. Rotter, Jennifer A. Smith, Scott Weiss, Kerri L. Wiggins, Lisa R. Yanek, Donna Arnett, Nancy L. Heard-Costa, Suzanne Leal, Danyu Lin, Barbara McKnight, Michael Province, Cornelia M. van Duijn, Kari E. North, L. Adrienne Cupples, and Ching-Ti Liu
Subjects: body mass index, central obesity, height, exome sequencing, Genetics, QH426-470
Abstract: Summary: Anthropometric traits, measuring body size and shape, are highly heritable and significant clinical risk factors for cardiometabolic disorders. These traits have been extensively studied in genome-wide association studies (GWASs), with hundreds of genome-wide significant loci identified. We performed a whole-exome sequence analysis of the genetics of height, body mass index (BMI) and waist/hip ratio (WHR). We meta-analyzed single-variant and gene-based associations of whole-exome sequence variation with height, BMI, and WHR in up to 22,004 individuals, and we assessed replication of our findings in up to 16,418 individuals from 10 independent cohorts from Trans-Omics for Precision Medicine (TOPMed). We identified four trait associations with single-nucleotide variants (SNVs; two for height and two for BMI) and replicated the LECT2 gene association with height. Our expression quantitative trait locus (eQTL) analysis within previously reported GWAS loci implicated CEP63 and RFT1 as potential functional genes for known height loci. We further assessed enrichment of SNVs, which were monogenic or syndromic variants within loci associated with our three traits. This led to the significant enrichment results for height, whereas we observed no Bonferroni-corrected significance for all SNVs. With a sample size of ∼20,000 whole-exome sequences in our discovery dataset, our findings demonstrate the importance of genomic sequencing in genetic association studies, yet they also illustrate the challenges in identifying effects of rare genetic variants.
Published: 2023
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7. Rare coding variants in RCN3 are associated with blood pressure

Author: Karen Y. He, Tanika N. Kelly, Heming Wang, Jingjing Liang, Luke Zhu, Brian E. Cade, Themistocles L. Assimes, Lewis C. Becker, Amber L. Beitelshees, Lawrence F. Bielak, Adam P. Bress, Jennifer A. Brody, Yen-Pei Christy Chang, Yi-Cheng Chang, Paul S. de Vries, Ravindranath Duggirala, Ervin R. Fox, Nora Franceschini, Anna L. Furniss, Yan Gao, Xiuqing Guo, Jeffrey Haessler, Yi-Jen Hung, Shih-Jen Hwang, Marguerite Ryan Irvin, Rita R. Kalyani, Ching-Ti Liu, Chunyu Liu, Lisa Warsinger Martin, May E. Montasser, Paul M. Muntner, Stanford Mwasongwe, Take Naseri, Walter Palmas, Muagututi’a Sefuiva Reupena, Kenneth M. Rice, Wayne H.-H. Sheu, Daichi Shimbo, Jennifer A. Smith, Beverly M. Snively, Lisa R. Yanek, Wei Zhao, John Blangero, Eric Boerwinkle, Yii-Der Ida Chen, Adolfo Correa, L. Adrienne Cupples, Joanne E. Curran, Myriam Fornage, Jiang He, Lifang Hou, Robert C. Kaplan, Sharon L. R. Kardia, Eimear E. Kenny, Charles Kooperberg, Donald Lloyd-Jones, Ruth J. F. Loos, Rasika A. Mathias, Stephen T. McGarvey, Braxton D. Mitchell, Kari E. North, Patricia A. Peyser, Bruce M. Psaty, Laura M. Raffield, D. C. Rao, Susan Redline, Alex P. Reiner, Stephen S. Rich, Jerome I. Rotter, Kent D. Taylor, Russell Tracy, Ramachandran S. Vasan, The Samoan Obesity, Lifestyle and Genetic Adaptations Study (OLaGA) Group, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Alanna C. Morrison, Daniel Levy, Aravinda Chakravarti, Donna K. Arnett, and Xiaofeng Zhu
Subjects: Rare variant analysis, Blood pressure, Whole genome sequencing, Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract: Abstract Background While large genome-wide association studies have identified nearly one thousand loci associated with variation in blood pressure, rare variant identification is still a challenge. In family-based cohorts, genome-wide linkage scans have been successful in identifying rare genetic variants for blood pressure. This study aims to identify low frequency and rare genetic variants within previously reported linkage regions on chromosomes 1 and 19 in African American families from the Trans-Omics for Precision Medicine (TOPMed) program. Genetic association analyses weighted by linkage evidence were completed with whole genome sequencing data within and across TOPMed ancestral groups consisting of 60,388 individuals of European, African, East Asian, Hispanic, and Samoan ancestries. Results Associations of low frequency and rare variants in RCN3 and multiple other genes were observed for blood pressure traits in TOPMed samples. The association of low frequency and rare coding variants in RCN3 was further replicated in UK Biobank samples (N = 403,522), and reached genome-wide significance for diastolic blood pressure (p = 2.01 × 10− 7). Conclusions Low frequency and rare variants in RCN3 contributes blood pressure variation. This study demonstrates that focusing association analyses in linkage regions greatly reduces multiple-testing burden and improves power to identify novel rare variants associated with blood pressure traits.
Published: 2022
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8. Genome sequencing unveils a regulatory landscape of platelet reactivity

Author: Ali R. Keramati, Ming-Huei Chen, Benjamin A. T. Rodriguez, Lisa R. Yanek, Arunoday Bhan, Brady J. Gaynor, Kathleen Ryan, Jennifer A. Brody, Xue Zhong, Qiang Wei, NHLBI Trans-Omics for Precision (TOPMed) Consortium, Kai Kammers, Kanika Kanchan, Kruthika Iyer, Madeline H. Kowalski, Achilleas N. Pitsillides, L. Adrienne Cupples, Bingshan Li, Thorsten M. Schlaeger, Alan R. Shuldiner, Jeffrey R. O’Connell, Ingo Ruczinski, Braxton D. Mitchell, Nauder Faraday, Margaret A. Taub, Lewis C. Becker, Joshua P. Lewis, Rasika A. Mathias, and Andrew D. Johnson
Subjects: Science
Abstract: Platelet aggregation is associated with myocardial infarction and stroke. Here, the authors have conducted a whole genome sequencing association study on platelet aggregation, discovering a locus in RGS18, where enhancer assays suggest an effect on activity of haematopoeitic lineage transcription factors.
Published: 2021
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9. Variant-specific inflation factors for assessing population stratification at the phenotypic variance level

Author: Tamar Sofer, Xiuwen Zheng, Cecelia A. Laurie, Stephanie M. Gogarten, Jennifer A. Brody, Matthew P. Conomos, Joshua C. Bis, Timothy A. Thornton, Adam Szpiro, Jeffrey R. O’Connell, Ethan M. Lange, Yan Gao, L. Adrienne Cupples, Bruce M. Psaty, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, and Kenneth M. Rice
Subjects: Science
Abstract: Pooling participant-level genetic data into a single analysis can result in variance stratification, reducing statistical performance. Here, the authors develop variant-specific inflation factors to assess variance stratification and apply this to pooled individual-level data from whole genome sequencing.
Published: 2021
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10. 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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11. Revisiting methods for modeling longitudinal and survival data: Framingham Heart Study

Author: Julius S. Ngwa, Howard J. Cabral, Debbie M. Cheng, David R. Gagnon, Michael P. LaValley, and L. Adrienne Cupples
Subjects: Joint longitudinal and survival model, Cox model, Two-step approach, Mixed effect modeling, Time dependent covariate models, Weibull distribution, Medicine (General), R5-920
Abstract: Abstract Background Statistical methods for modeling longitudinal and time-to-event data has received much attention in medical research and is becoming increasingly useful. In clinical studies, such as cancer and AIDS, longitudinal biomarkers are used to monitor disease progression and to predict survival. These longitudinal measures are often missing at failure times and may be prone to measurement errors. More importantly, time-dependent survival models that include the raw longitudinal measurements may lead to biased results. In previous studies these two types of data are frequently analyzed separately where a mixed effects model is used for the longitudinal data and a survival model is applied to the event outcome. Methods In this paper we compare joint maximum likelihood methods, a two-step approach and a time dependent covariate method that link longitudinal data to survival data with emphasis on using longitudinal measures to predict survival. We apply a Bayesian semi-parametric joint method and maximum likelihood joint method that maximizes the joint likelihood of the time-to-event and longitudinal measures. We also implement the Two-Step approach, which estimates random effects separately, and a classic Time Dependent Covariate Model. We use simulation studies to assess bias, accuracy, and coverage probabilities for the estimates of the link parameter that connects the longitudinal measures to survival times. Results Simulation results demonstrate that the Two-Step approach performed best at estimating the link parameter when variability in the longitudinal measure is low but is somewhat biased downwards when the variability is high. Bayesian semi-parametric and maximum likelihood joint methods yield higher link parameter estimates with low and high variability in the longitudinal measure. The Time Dependent Covariate method resulted in consistent underestimation of the link parameter. We illustrate these methods using data from the Framingham Heart Study in which lipid measurements and Myocardial Infarction data were collected over a period of 26 years. Conclusions Traditional methods for modeling longitudinal and survival data, such as the time dependent covariate method, that use the observed longitudinal data, tend to provide downwardly biased estimates. The two-step approach and joint models provide better estimates, although a comparison of these methods may depend on the underlying residual variance.
Published: 2021
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12. Loss-of-function genomic variants highlight potential therapeutic targets for cardiovascular disease

Author: Jonas B. Nielsen, Oren Rom, Ida Surakka, Sarah E. Graham, Wei Zhou, Tanmoy Roychowdhury, Lars G. Fritsche, Sarah A. Gagliano Taliun, Carlo Sidore, Yuhao Liu, Maiken E. Gabrielsen, Anne Heidi Skogholt, Brooke Wolford, William Overton, Ying Zhao, Jin Chen, He Zhang, Whitney E. Hornsby, Akua Acheampong, Austen Grooms, Amanda Schaefer, Gregory J. M. Zajac, Luis Villacorta, Jifeng Zhang, Ben Brumpton, Mari Løset, Vivek Rai, Pia R. Lundegaard, Morten S. Olesen, Kent D. Taylor, Nicholette D. Palmer, Yii-Der Chen, Seung H. Choi, Steven A. Lubitz, Patrick T. Ellinor, Kathleen C. Barnes, Michelle Daya, Nicholas Rafaels, Scott T. Weiss, Jessica Lasky-Su, Russell P. Tracy, Ramachandran S. Vasan, L. Adrienne Cupples, Rasika A. Mathias, Lisa R. Yanek, Lewis C. Becker, Patricia A. Peyser, Lawrence F. Bielak, Jennifer A. Smith, Stella Aslibekyan, Bertha A. Hidalgo, Donna K. Arnett, Marguerite R. Irvin, James G. Wilson, Solomon K. Musani, Adolfo Correa, Stephen S. Rich, Xiuqing Guo, Jerome I. Rotter, Barbara A. Konkle, Jill M. Johnsen, Allison E. Ashley-Koch, Marilyn J. Telen, Vivien A. Sheehan, John Blangero, Joanne E. Curran, Juan M. Peralta, Courtney Montgomery, Wayne H-H Sheu, Ren-Hua Chung, Karen Schwander, Seyed M. Nouraie, Victor R. Gordeuk, Yingze Zhang, Charles Kooperberg, Alexander P. Reiner, Rebecca D. Jackson, Eugene R. Bleecker, Deborah A. Meyers, Xingnan Li, Sayantan Das, Ketian Yu, Jonathon LeFaive, Albert Smith, Tom Blackwell, Daniel Taliun, Sebastian Zollner, Lukas Forer, Sebastian Schoenherr, Christian Fuchsberger, Anita Pandit, Matthew Zawistowski, Sachin Kheterpal, Chad M. Brummett, Pradeep Natarajan, David Schlessinger, Seunggeun Lee, Hyun Min Kang, Francesco Cucca, Oddgeir L. Holmen, Bjørn O. Åsvold, Michael Boehnke, Sekar Kathiresan, Goncalo R. Abecasis, Y. Eugene Chen, Cristen J. Willer, and Kristian Hveem
Subjects: Science
Abstract: Drugs targeting cardiovascular disease (CVD) can have negative consequences for liver function. Here, the authors combine genome wide analyses on 69,479 individuals to identify loss-of-function variants with beneficial effects on CVD-related traits without negative impacts on liver function.
Published: 2020
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13. Whole genome sequence analysis of pulmonary function and COPD in 19,996 multi-ethnic participants

Author: Xutong Zhao, Dandi Qiao, Chaojie Yang, Silva Kasela, Wonji Kim, Yanlin Ma, Nick Shrine, Chiara Batini, Tamar Sofer, Sarah A. Gagliano Taliun, Phuwanat Sakornsakolpat, Pallavi P. Balte, Dmitry Prokopenko, Bing Yu, Leslie A. Lange, Josée Dupuis, Brian E. Cade, Jiwon Lee, Sina A. Gharib, Michelle Daya, Cecelia A. Laurie, Ingo Ruczinski, L. Adrienne Cupples, Laura R. Loehr, Traci M. Bartz, Alanna C. Morrison, Bruce M. Psaty, Ramachandran S. Vasan, James G. Wilson, Kent D. Taylor, Peter Durda, W. Craig Johnson, Elaine Cornell, Xiuqing Guo, Yongmei Liu, Russell P. Tracy, Kristin G. Ardlie, François Aguet, David J. VanDenBerg, George J. Papanicolaou, Jerome I. Rotter, Kathleen C. Barnes, Deepti Jain, Deborah A. Nickerson, Donna M. Muzny, Ginger A. Metcalf, Harshavardhan Doddapaneni, Shannon Dugan-Perez, Namrata Gupta, Stacey Gabriel, Stephen S. Rich, George T. O’Connor, Susan Redline, Robert M. Reed, Cathy C. Laurie, Martha L. Daviglus, Liana K. Preudhomme, Kristin M. Burkart, Robert C. Kaplan, Louise V. Wain, Martin D. Tobin, Stephanie J. London, Tuuli Lappalainen, Elizabeth C. Oelsner, Goncalo R. Abecasis, Edwin K. Silverman, R. Graham Barr, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Lung Working Group, Michael H. Cho, and Ani Manichaikul
Subjects: Science
Abstract: Chronic obstructive pulmonary disease is a leading cause of morbidity and mortality. Here, the authors analyse whole genome sequence data and find new loci associated with lung function and COPD.
Published: 2020
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14. Genetic determinants of telomere length from 109,122 ancestrally diverse whole-genome sequences in TOPMed

Author: Margaret A. Taub, Matthew P. Conomos, Rebecca Keener, Kruthika R. Iyer, Joshua S. Weinstock, Lisa R. Yanek, John Lane, Tyne W. Miller-Fleming, Jennifer A. Brody, Laura M. Raffield, Caitlin P. McHugh, Deepti Jain, Stephanie M. Gogarten, Cecelia A. Laurie, Ali Keramati, Marios Arvanitis, Albert V. Smith, Benjamin Heavner, Lucas Barwick, Lewis C. Becker, Joshua C. Bis, John Blangero, Eugene R. Bleecker, Esteban G. Burchard, Juan C. Celedón, Yen Pei C. Chang, Brian Custer, Dawood Darbar, Lisa de las Fuentes, Dawn L. DeMeo, Barry I. Freedman, Melanie E. Garrett, Mark T. Gladwin, Susan R. Heckbert, Bertha A. Hidalgo, Marguerite R. Irvin, Talat Islam, W. Craig Johnson, Stefan Kaab, Lenore Launer, Jiwon Lee, Simin Liu, Arden Moscati, Kari E. North, Patricia A. Peyser, Nicholas Rafaels, Christine Seidman, Daniel E. Weeks, Fayun Wen, Marsha M. Wheeler, L. Keoki Williams, Ivana V. Yang, Wei Zhao, Stella Aslibekyan, Paul L. Auer, Donald W. Bowden, Brian E. Cade, Zhanghua Chen, Michael H. Cho, L. Adrienne Cupples, Joanne E. Curran, Michelle Daya, Ranjan Deka, Celeste Eng, Tasha E. Fingerlin, Xiuqing Guo, Lifang Hou, Shih-Jen Hwang, Jill M. Johnsen, Eimear E. Kenny, Albert M. Levin, Chunyu Liu, Ryan L. Minster, Take Naseri, Mehdi Nouraie, Muagututi‘a Sefuiva Reupena, Ester C. Sabino, Jennifer A. Smith, Nicholas L. Smith, Jessica Lasky-Su, James G. Taylor, VI, Marilyn J. Telen, Hemant K. Tiwari, Russell P. Tracy, Marquitta J. White, Yingze Zhang, Kerri L. Wiggins, Scott T. Weiss, Ramachandran S. Vasan, Kent D. Taylor, Moritz F. Sinner, Edwin K. Silverman, M. Benjamin Shoemaker, Wayne H.-H. Sheu, Frank Sciurba, David A. Schwartz, Jerome I. Rotter, Daniel Roden, Susan Redline, Benjamin A. Raby, Bruce M. Psaty, Juan M. Peralta, Nicholette D. Palmer, Sergei Nekhai, Courtney G. Montgomery, Braxton D. Mitchell, Deborah A. Meyers, Stephen T. McGarvey, Angel C.Y. Mak, Ruth J.F. Loos, Rajesh Kumar, Charles Kooperberg, Barbara A. Konkle, Shannon Kelly, Sharon L.R. Kardia, Robert Kaplan, Jiang He, Hongsheng Gui, Frank D. Gilliland, Bruce D. Gelb, Myriam Fornage, Patrick T. Ellinor, Mariza de Andrade, Adolfo Correa, Yii-Der Ida Chen, Eric Boerwinkle, Kathleen C. Barnes, Allison E. Ashley-Koch, Donna K. Arnett, Christine Albert, Cathy C. Laurie, Goncalo Abecasis, Deborah A. Nickerson, James G. Wilson, Stephen S. Rich, Daniel Levy, Ingo Ruczinski, Abraham Aviv, Thomas W. Blackwell, Timothy Thornton, Jeff O’Connell, Nancy J. Cox, James A. Perry, Mary Armanios, Alexis Battle, Nathan Pankratz, Alexander P. Reiner, and Rasika A. Mathias
Subjects: telomeres, telomere length genetics, trans-population genome-wide association study, Genetics, QH426-470, Internal medicine, RC31-1245
Abstract: Summary: Genetic studies on telomere length are important for understanding age-related diseases. Prior GWASs for leukocyte TL have been limited to European and Asian populations. Here, we report the first sequencing-based association study for TL across ancestrally diverse individuals (European, African, Asian, and Hispanic/Latino) from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. We used whole-genome sequencing (WGS) of whole blood for variant genotype calling and the bioinformatic estimation of telomere length in n = 109,122 individuals. We identified 59 sentinel variants (p < 5 × 10−9) in 36 loci associated with telomere length, including 20 newly associated loci (13 were replicated in external datasets). There was little evidence of effect size heterogeneity across populations. Fine-mapping at OBFC1 indicated that the independent signals colocalized with cell-type-specific eQTLs for OBFC1 (STN1). Using a multi-variant gene-based approach, we identified two genes newly implicated in telomere length, DCLRE1B (SNM1B) and PARN. In PheWAS, we demonstrated that our TL polygenic trait scores (PTSs) were associated with an increased risk of cancer-related phenotypes.
Published: 2022
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15. Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration

Author: Raymond Noordam, Maxime M. Bos, Heming Wang, Thomas W. Winkler, Amy R. Bentley, Tuomas O. Kilpeläinen, Paul S. de Vries, Yun Ju Sung, Karen Schwander, Brian E. Cade, Alisa Manning, Hugues Aschard, Michael R. Brown, Han Chen, Nora Franceschini, Solomon K. Musani, Melissa Richard, Dina Vojinovic, Stella Aslibekyan, Traci M. Bartz, Lisa de las Fuentes, Mary Feitosa, Andrea R. Horimoto, Marjan Ilkov, Minjung Kho, Aldi Kraja, Changwei Li, Elise Lim, Yongmei Liu, Dennis O. Mook-Kanamori, Tuomo Rankinen, Salman M. Tajuddin, Ashley van der Spek, Zhe Wang, Jonathan Marten, Vincent Laville, Maris Alver, Evangelos Evangelou, Maria E. Graff, Meian He, Brigitte Kühnel, Leo-Pekka Lyytikäinen, Pedro Marques-Vidal, Ilja M. Nolte, Nicholette D. Palmer, Rainer Rauramaa, Xiao-Ou Shu, Harold Snieder, Stefan Weiss, Wanqing Wen, Lisa R. Yanek, Correa Adolfo, Christie Ballantyne, Larry Bielak, Nienke R. Biermasz, Eric Boerwinkle, Niki Dimou, Gudny Eiriksdottir, Chuan Gao, Sina A. Gharib, Daniel J. Gottlieb, José Haba-Rubio, Tamara B. Harris, Sami Heikkinen, Raphaël Heinzer, James E. Hixson, Georg Homuth, M. Arfan Ikram, Pirjo Komulainen, Jose E. Krieger, Jiwon Lee, Jingmin Liu, Kurt K. Lohman, Annemarie I. Luik, Reedik Mägi, Lisa W. Martin, Thomas Meitinger, Andres Metspalu, Yuri Milaneschi, Mike A. Nalls, Jeff O’Connell, Annette Peters, Patricia Peyser, Olli T. Raitakari, Alex P. Reiner, Patrick C. N. Rensen, Treva K. Rice, Stephen S. Rich, Till Roenneberg, Jerome I. Rotter, Pamela J. Schreiner, James Shikany, Stephen S. Sidney, Mario Sims, Colleen M. Sitlani, Tamar Sofer, Konstantin Strauch, Morris A. Swertz, Kent D. Taylor, André G. Uitterlinden, Cornelia M. van Duijn, Henry Völzke, Melanie Waldenberger, Robert B. Wallance, Ko Willems van Dijk, Caizheng Yu, Alan B. Zonderman, Diane M. Becker, Paul Elliott, Tõnu Esko, Christian Gieger, Hans J. Grabe, Timo A. Lakka, Terho Lehtimäki, Kari E. North, Brenda W. J. H. Penninx, Peter Vollenweider, Lynne E. Wagenknecht, Tangchun Wu, Yong-Bing Xiang, Wei Zheng, Donna K. Arnett, Claude Bouchard, Michele K. Evans, Vilmundur Gudnason, Sharon Kardia, Tanika N. Kelly, Stephen B. Kritchevsky, Ruth J. F. Loos, Alexandre C. Pereira, Mike Province, Bruce M. Psaty, Charles Rotimi, Xiaofeng Zhu, Najaf Amin, L. Adrienne Cupples, Myriam Fornage, Ervin F. Fox, Xiuqing Guo, W. James Gauderman, Kenneth Rice, Charles Kooperberg, Patricia B. Munroe, Ching-Ti Liu, Alanna C. Morrison, Dabeeru C. Rao, Diana van Heemst, and Susan Redline
Subjects: Science
Abstract: Sleep duration is associated with an adverse lipid profile. Here, the authors perform genome-wide gene-by-sleep interaction analysis and find 49 previously unreported lipid loci when considering short or long total sleep time.
Published: 2019
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16. Association of mitochondrial DNA copy number with cardiometabolic diseases

Author: Xue Liu, Ryan J. Longchamps, Kerri L. Wiggins, Laura M. Raffield, Lawrence F. Bielak, Wei Zhao, Achilleas Pitsillides, Thomas W. Blackwell, Jie Yao, Xiuqing Guo, Nuzulul Kurniansyah, Bharat Thyagarajan, Nathan Pankratz, Stephen S. Rich, Kent D. Taylor, Patricia A. Peyser, Susan R. Heckbert, Sudha Seshadri, L. Adrienne Cupples, Eric Boerwinkle, Megan L. Grove, Nicholas B. Larson, Jennifer A. Smith, Ramachandran S. Vasan, Tamar Sofer, Annette L. Fitzpatrick, Myriam Fornage, Jun Ding, Adolfo Correa, Goncalo Abecasis, Bruce M. Psaty, James G. Wilson, Daniel Levy, Jerome I. Rotter, Joshua C. Bis, Claudia L. Satizabal, Dan E. Arking, and Chunyu Liu
Subjects: mitochondrial DNA copy number, cardiometabolic disease, whole-genome sequencing, whole-exom sequencing, aging, white blood cell counts, Genetics, QH426-470, Internal medicine, RC31-1245
Abstract: Summary: Mitochondrial DNA (mtDNA) is present in multiple copies in human cells. We evaluated cross-sectional associations of whole-blood mtDNA copy number (CN) with several cardiometabolic disease traits in 408,361 participants of multiple ancestries in TOPMed and UK Biobank. Age showed a threshold association with mtDNA CN: each additional 10 years of age was associated with a 0.03 SD higher level of mtDNA CN (p = 0.0014) among younger participants (younger than 65 years) versus a 0.14 SD lower level of mtDNA CN (p = 1.82 × 10−13) among older participants (65 years and older). At lower mtDNA CN levels, we found age-independent associations with increased odds of obesity (p = 5.6 × 10−238), hypertension (p = 2.8 × 10−50), diabetes (p = 3.6 × 10−7), and hyperlipidemia (p = 6.3 × 10−56). The observed decline in mtDNA CN after 65 years of age may be a key to understanding age-related diseases.
Published: 2021
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17. BinomiRare: A robust test for association of a rare genetic variant with a binary outcome for mixed models and any case-control proportion

Author: Tamar Sofer, Jiwon Lee, Nuzulul Kurniansyah, Deepti Jain, Cecelia A. Laurie, Stephanie M. Gogarten, Matthew P. Conomos, Ben Heavner, Yao Hu, Charles Kooperberg, Jeffrey Haessler, Ramachandran S. Vasan, L. Adrienne Cupples, Brandon J. Coombes, Amanda Seyerle, Sina A. Gharib, Han Chen, Jeffrey R. O’Connell, Man Zhang, Daniel J. Gottlieb, Bruce M. Psaty, W.T. Longstreth, Jr., Jerome I. Rotter, Kent D. Taylor, Stephen S. Rich, Xiuqing Guo, Eric Boerwinkle, Alanna C. Morrison, James S. Pankow, Andrew D. Johnson, Nathan Pankratz, Alex P. Reiner, Susan Redline, Nicholas L. Smith, Kenneth M. Rice, and Elizabeth D. Schifano
Subjects: genome sequencing, rare variant assocaition testing, diverse populations, targeted gene analysis, mixed models, Genetics, QH426-470
Abstract: Summary: Whole-genome sequencing (WGS) and whole-exome sequencing studies have become increasingly available and are being used to identify rare genetic variants associated with health and disease outcomes. Investigators routinely use mixed models to account for genetic relatedness or other clustering variables (e.g., family or household) when testing genetic associations. However, no existing tests of the association of a rare variant with a binary outcome in the presence of correlated data control the type 1 error where there are (1) few individuals harboring the rare allele, (2) a small proportion of cases relative to controls, and (3) covariates to adjust for. Here, we address all three issues in developing a framework for testing rare variant association with a binary trait in individuals harboring at least one risk allele. In this framework, we estimate outcome probabilities under the null hypothesis and then use them, within the individuals with at least one risk allele, to test variant associations. We extend the BinomiRare test, which was previously proposed for independent observations, and develop the Conway-Maxwell-Poisson (CMP) test and study their properties in simulations. We show that the BinomiRare test always controls the type 1 error, while the CMP test sometimes does not. We then use the BinomiRare test to test the association of rare genetic variants in target genes with small-vessel disease (SVD) stroke, short sleep, and venous thromboembolism (VTE), in whole-genome sequence data from the Trans-Omics for Precision Medicine (TOPMed) program.
Published: 2021
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18. Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity

Author: Tuomas O. Kilpeläinen, Amy R. Bentley, Raymond Noordam, Yun Ju Sung, Karen Schwander, Thomas W. Winkler, Hermina Jakupović, Daniel I. Chasman, Alisa Manning, Ioanna Ntalla, Hugues Aschard, Michael R. Brown, Lisa de las Fuentes, Nora Franceschini, Xiuqing Guo, Dina Vojinovic, Stella Aslibekyan, Mary F. Feitosa, Minjung Kho, Solomon K. Musani, Melissa Richard, Heming Wang, Zhe Wang, Traci M. Bartz, Lawrence F. Bielak, Archie Campbell, Rajkumar Dorajoo, Virginia Fisher, Fernando P. Hartwig, Andrea R. V. R. Horimoto, Changwei Li, Kurt K. Lohman, Jonathan Marten, Xueling Sim, Albert V. Smith, Salman M. Tajuddin, Maris Alver, Marzyeh Amini, Mathilde Boissel, Jin Fang Chai, Xu Chen, Jasmin Divers, Evangelos Evangelou, Chuan Gao, Mariaelisa Graff, Sarah E. Harris, Meian He, Fang-Chi Hsu, Anne U. Jackson, Jing Hua Zhao, Aldi T. Kraja, Brigitte Kühnel, Federica Laguzzi, Leo-Pekka Lyytikäinen, Ilja M. Nolte, Rainer Rauramaa, Muhammad Riaz, Antonietta Robino, Rico Rueedi, Heather M. Stringham, Fumihiko Takeuchi, Peter J. van der Most, Tibor V. Varga, Niek Verweij, Erin B. Ware, Wanqing Wen, Xiaoyin Li, Lisa R. Yanek, Najaf Amin, Donna K. Arnett, Eric Boerwinkle, Marco Brumat, Brian Cade, Mickaël Canouil, Yii-Der Ida Chen, Maria Pina Concas, John Connell, Renée de Mutsert, H. Janaka de Silva, Paul S. de Vries, Ayşe Demirkan, Jingzhong Ding, Charles B. Eaton, Jessica D. Faul, Yechiel Friedlander, Kelley P. Gabriel, Mohsen Ghanbari, Franco Giulianini, Chi Charles Gu, Dongfeng Gu, Tamara B. Harris, Jiang He, Sami Heikkinen, Chew-Kiat Heng, Steven C. Hunt, M. Arfan Ikram, Jost B. Jonas, Woon-Puay Koh, Pirjo Komulainen, Jose E. Krieger, Stephen B. Kritchevsky, Zoltán Kutalik, Johanna Kuusisto, Carl D. Langefeld, Claudia Langenberg, Lenore J. Launer, Karin Leander, Rozenn N. Lemaitre, Cora E. Lewis, Jingjing Liang, Lifelines Cohort Study, Jianjun Liu, Reedik Mägi, Ani Manichaikul, Thomas Meitinger, Andres Metspalu, Yuri Milaneschi, Karen L. Mohlke, Thomas H. Mosley, Alison D. Murray, Mike A. Nalls, Ei-Ei Khaing Nang, Christopher P. Nelson, Sotoodehnia Nona, Jill M. Norris, Chiamaka Vivian Nwuba, Jeff O’Connell, Nicholette D. Palmer, George J. Papanicolau, Raha Pazoki, Nancy L. Pedersen, Annette Peters, Patricia A. Peyser, Ozren Polasek, David J. Porteous, Alaitz Poveda, Olli T. Raitakari, Stephen S. Rich, Neil Risch, Jennifer G. Robinson, Lynda M. Rose, Igor Rudan, Pamela J. Schreiner, Robert A. Scott, Stephen S. Sidney, Mario Sims, Jennifer A. Smith, Harold Snieder, Tamar Sofer, John M. Starr, Barbara Sternfeld, Konstantin Strauch, Hua Tang, Kent D. Taylor, Michael Y. Tsai, Jaakko Tuomilehto, André G. Uitterlinden, M. Yldau van der Ende, Diana van Heemst, Trudy Voortman, Melanie Waldenberger, Patrik Wennberg, Gregory Wilson, Yong-Bing Xiang, Jie Yao, Caizheng Yu, Jian-Min Yuan, Wei Zhao, Alan B. Zonderman, Diane M. Becker, Michael Boehnke, Donald W. Bowden, Ulf de Faire, Ian J. Deary, Paul Elliott, Tõnu Esko, Barry I. Freedman, Philippe Froguel, Paolo Gasparini, Christian Gieger, Norihiro Kato, Markku Laakso, Timo A. Lakka, Terho Lehtimäki, Patrik K. E. Magnusson, Albertine J. Oldehinkel, Brenda W. J. H. Penninx, Nilesh J. Samani, Xiao-Ou Shu, Pim van der Harst, Jana V. Van Vliet-Ostaptchouk, Peter Vollenweider, Lynne E. Wagenknecht, Ya X. Wang, Nicholas J. Wareham, David R. Weir, Tangchun Wu, Wei Zheng, Xiaofeng Zhu, Michele K. Evans, Paul W. Franks, Vilmundur Gudnason, Caroline Hayward, Bernardo L. Horta, Tanika N. Kelly, Yongmei Liu, Kari E. North, Alexandre C. Pereira, Paul M. Ridker, E. Shyong Tai, Rob M. van Dam, Ervin R. Fox, Sharon L. R. Kardia, Ching-Ti Liu, Dennis O. Mook-Kanamori, Michael A. Province, Susan Redline, Cornelia M. van Duijn, Jerome I. Rotter, Charles B. Kooperberg, W. James Gauderman, Bruce M. Psaty, Kenneth Rice, Patricia B. Munroe, Myriam Fornage, L. Adrienne Cupples, Charles N. Rotimi, Alanna C. Morrison, Dabeeru C. Rao, and Ruth J. F. Loos
Subjects: Science
Abstract: GWAS have identified more than 500 genetic loci associated with blood lipid levels. Here, the authors report a genome-wide analysis of interactions between genetic markers and physical activity, and find that physical activity modifies the effects of four genetic loci on HDL or LDL cholesterol.
Published: 2019
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19. Small Dense Low‐Density Lipoprotein Cholesterol Is the Most Atherogenic Lipoprotein Parameter in the Prospective Framingham Offspring Study

Author: Hiroaki Ikezaki, Elise Lim, L. Adrienne Cupples, Ching‐Ti Liu, Bela F. Asztalos, and Ernst J. Schaefer
Subjects: atherosclerotic cardiovascular disease, pooled cohort equations, small dense low‐density lipoprotein cholesterol, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract: Background Elevated plasma levels of direct low‐density lipoprotein cholesterol (LDL‐C), small dense LDL‐C (sdLDL‐C), low‐density lipoprotein (LDL) triglycerides, triglycerides, triglyceride‐rich lipoprotein cholesterol, remnant lipoprotein particle cholesterol, and lipoprotein(a) have all been associated with incident atherosclerotic cardiovascular disease (ASCVD). Our goal was to assess which parameters were most strongly associated with ASCVD risk. Methods and Results Plasma total cholesterol, triglycerides, high‐density lipoprotein cholesterol, direct LDL‐C, sdLDL‐C, LDL triglycerides, remnant lipoprotein particle cholesterol, triglyceride‐rich lipoprotein cholesterol, and lipoprotein(a) were measured using standardized automated analysis (coefficients of variation,
Published: 2021
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20. Multi-ancestry genome-wide association study accounting for gene-psychosocial factor interactions identifies novel loci for blood pressure traits

Author: Daokun Sun, Melissa A. Richard, Solomon K. Musani, Yun Ju Sung, Thomas W. Winkler, Karen Schwander, Jin Fang Chai, Xiuqing Guo, Tuomas O. Kilpeläinen, Dina Vojinovic, Hugues Aschard, Traci M. Bartz, Lawrence F. Bielak, Michael R. Brown, Kumaraswamy Chitrala, Fernando P. Hartwig, Andrea R.V.R. Horimoto, Yongmei Liu, Alisa K. Manning, Raymond Noordam, Albert V. Smith, Sarah E. Harris, Brigitte Kühnel, Leo-Pekka Lyytikäinen, Ilja M. Nolte, Rainer Rauramaa, Peter J. van der Most, Rujia Wang, Erin B. Ware, Stefan Weiss, Wanqing Wen, Lisa R. Yanek, Dan E. Arking, Donna K. Arnett, Ana Barac, Eric Boerwinkle, Ulrich Broeckel, Aravinda Chakravarti, Yii-Der Ida Chen, L. Adrienne Cupples, Martha L. Davigulus, Lisa de las Fuentes, Renée de Mutsert, Paul S. de Vries, Joseph A.C. Delaney, Ana V. Diez Roux, Marcus Dörr, Jessica D. Faul, Amanda M. Fretts, Linda C. Gallo, Hans Jörgen Grabe, C. Charles Gu, Tamara B. Harris, Catharina C.A. Hartman, Sami Heikkinen, M. Arfan Ikram, Carmen Isasi, W. Craig Johnson, Jost Bruno Jonas, Robert C. Kaplan, Pirjo Komulainen, Jose E. Krieger, Daniel Levy, Jianjun Liu, Kurt Lohman, Annemarie I. Luik, Lisa W. Martin, Thomas Meitinger, Yuri Milaneschi, Jeff R. O’Connell, Walter R. Palmas, Annette Peters, Patricia A. Peyser, Laura Pulkki-Råback, Leslie J. Raffel, Alex P. Reiner, Kenneth Rice, Jennifer G. Robinson, Frits R. Rosendaal, Carsten Oliver Schmidt, Pamela J. Schreiner, Lars Schwettmann, James M. Shikany, Xiao-ou Shu, Stephen Sidney, Mario Sims, Jennifer A. Smith, Nona Sotoodehnia, Konstantin Strauch, E. Shyong Tai, Kent D. Taylor, André G. Uitterlinden, Cornelia M. van Duijn, Melanie Waldenberger, Hwee-Lin Wee, Wen-Bin Wei, Gregory Wilson, Deng Xuan, Jie Yao, Donglin Zeng, Wei Zhao, Xiaofeng Zhu, Alan B. Zonderman, Diane M. Becker, Ian J. Deary, Christian Gieger, Timo A. Lakka, Terho Lehtimäki, Kari E. North, Albertine J. Oldehinkel, Brenda W.J.H. Penninx, Harold Snieder, Ya-Xing Wang, David R. Weir, Wei Zheng, Michele K. Evans, W. James Gauderman, Vilmundur Gudnason, Bernardo L. Horta, Ching-Ti Liu, Dennis O. Mook-Kanamori, Alanna C. Morrison, Alexandre C. Pereira, Bruce M. Psaty, Najaf Amin, Ervin R. Fox, Charles Kooperberg, Xueling Sim, Laura Bierut, Jerome I. Rotter, Sharon L.R. Kardia, Nora Franceschini, Dabeeru C. Rao, and Myriam Fornage
Subjects: gene-environment interaction, genome-wide association study, blood pressure, hypertension, psychosocial factors, depressive symptoms, Genetics, QH426-470
Abstract: Summary: Psychological and social factors are known to influence blood pressure (BP) and risk of hypertension and associated cardiovascular diseases. To identify novel BP loci, we carried out genome-wide association meta-analyses of systolic, diastolic, pulse, and mean arterial BP, taking into account the interaction effects of genetic variants with three psychosocial factors: depressive symptoms, anxiety symptoms, and social support. Analyses were performed using a two-stage design in a sample of up to 128,894 adults from five ancestry groups. In the combined meta-analyses of stages 1 and 2, we identified 59 loci (p value < 5e−8), including nine novel BP loci. The novel associations were observed mostly with pulse pressure, with fewer observed with mean arterial pressure. Five novel loci were identified in African ancestry, and all but one showed patterns of interaction with at least one psychosocial factor. Functional annotation of the novel loci supports a major role for genes implicated in the immune response (PLCL2), synaptic function and neurotransmission (LIN7A and PFIA2), as well as genes previously implicated in neuropsychiatric or stress-related disorders (FSTL5 and CHODL). These findings underscore the importance of considering psychological and social factors in gene discovery for BP, especially in non-European populations.
Published: 2021
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21. Proteomic Signatures of Lifestyle Risk Factors for Cardiovascular Disease: A Cross‐Sectional Analysis of the Plasma Proteome in the Framingham Heart Study

Author: Laura Corlin, Chunyu Liu, Honghuang Lin, Dominick Leone, Qiong Yang, Debby Ngo, Daniel Levy, L. Adrienne Cupples, Robert E. Gerszten, Martin G. Larson, and Ramachandran S. Vasan
Subjects: alcohol consumption, lifestyle, physical activity, proteomics, smoking, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract: Background Proteomic biomarkers related to cardiovascular disease risk factors may offer insights into the pathogenesis of cardiovascular disease. We investigated whether modifiable lifestyle risk factors for cardiovascular disease are associated with distinctive proteomic signatures. Methods and Results We analyzed 1305 circulating plasma proteomic biomarkers (assayed using the SomaLogic platform) in 897 FHS (Framingham Heart Study) Generation 3 participants (mean age 46±8 years; 56% women; discovery sample) and 1121 FOS (Framingham Offspring Study) participants (mean age 52 years; 54% women; validation sample). Participants were free of hypertension, diabetes mellitus, and clinical cardiovascular disease. We used linear mixed effects models (adjusting for age, sex, body mass index, and family structure) to relate levels of each inverse‐log transformed protein to 3 lifestyle factors (ie, smoking, alcohol consumption, and physical activity). A Bonferroni‐adjusted P value indicated statistical significance (based on number of proteins and traits tested, P
Published: 2021
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22. Disclosing genetic risk for Alzheimer's dementia to individuals with mild cognitive impairment

Author: Kurt D. Christensen, Jason Karlawish, J. Scott Roberts, Wendy R. Uhlmann, Kristin Harkins, Elisabeth M. Wood, Thomas O. Obisesan, Lan Q. Le, L. Adrienne Cupples, Emilie S. Zoltick, Megan S. Johnson, Margaret K. Bradbury, Leo B. Waterston, Clara A. Chen, Sara Feldman, Denise L. Perry, Robert C. Green, and for the REVEAL Study Group
Subjects: Alzheimer's disease, anxiety, apolipoprotein E4, cognitive dysfunction, dementia, depression, Neurology. Diseases of the nervous system, RC346-429, Geriatrics, RC952-954.6
Abstract: Abstract Introduction The safety of predicting conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) dementia using apolipoprotein E (APOE) genotyping is unknown. Methods We randomized 114 individuals with MCI to receive estimates of 3‐year risk of conversion to AD dementia informed by APOE genotyping (disclosure arm) or not (non‐disclosure arm) in a non‐inferiority clinical trial. Primary outcomes were anxiety and depression scores. Secondary outcomes included other psychological measures. Results Upper confidence limits for randomization arm differences were 2.3 on the State Trait Anxiety Index and 0.5 on the Geriatric Depression Scale, below non‐inferiority margins of 3.3 and 1.0. Moreover, mean scores were lower in the disclosure arm than non‐disclosure arm for test‐related positive impact (difference: ‐1.9, indicating more positive feelings) and AD concern (difference: ‐0.3). Discussion Providing genetic information to individuals with MCI about imminent risk for AD does not increase risks of anxiety or depression and may provide psychological benefits.
Published: 2020
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23. 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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24. Do changes in DNA methylation mediate or interact with SNP variation? A pharmacoepigenetic analysis

Author: Virginia A. Fisher, Lan Wang, Xuan Deng, Chloé Sarnowski, L. Adrienne Cupples, and Ching-Ti Liu
Subjects: Causal modeling, Genomic data integration, Gene-methylation interaction, Indirect effects, Triglycerides, Genofibrate treatment, Genetics, QH426-470
Abstract: Abstract Background In studies with multi-omics data available, there is an opportunity to investigate interdependent mechanisms of biological causality. The GAW20 data set includes both DNA genotype and methylation measures before and after fenofibrate treatment. Using change in triglyceride (TG) levels pre- to posttreatment as outcome, we present a mediation analysis that incorporates methylation. This approach allows us to simultaneously consider a mediation hypothesis that genotype affects change in TG level by means of its effect on methylation, and an interaction hypothesis that the effect of change in methylation on change in TG levels differs by genotype. We select 322 single-nucleotide polymorphism–cytosine-phosphate-guanine (SNP-CpG) site pairs for mediation analysis on the basis of proximity and marginal genome-wide association study (GWAS) and epigenome-wide association study (EWAS) significance, and present results from the real-data sample of 407 individuals with complete genotype, methylation, TG levels, and covariate data. Results We identified 3 SNP-CpG site pairs with significant interaction effects at a Bonferroni-corrected significance threshold of 1.55E-4. None of the analyzed sites showed significant evidence of mediation. Power analysis by simulation showed that a sample size of at least 19,500 is needed to detect nominally significant indirect effects with true effect sizes equal to the point estimates at the locus with strongest evidence of mediation. Conclusions These results suggest that there is stronger evidence for interaction between genotype and methylation on change in triglycerides than for methylation mediating the effect of genotype.
Published: 2018
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25. 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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26. 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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27. Genome-wide association study in 79,366 European-ancestry individuals informs the genetic architecture of 25-hydroxyvitamin D levels

Author: Xia Jiang, Paul F. O’Reilly, Hugues Aschard, Yi-Hsiang Hsu, J. Brent Richards, Josée Dupuis, Erik Ingelsson, David Karasik, Stefan Pilz, Diane Berry, Bryan Kestenbaum, Jusheng Zheng, Jianan Luan, Eleni Sofianopoulou, Elizabeth A. Streeten, Demetrius Albanes, Pamela L. Lutsey, Lu Yao, Weihong Tang, Michael J. Econs, Henri Wallaschofski, Henry Völzke, Ang Zhou, Chris Power, Mark I. McCarthy, Erin D. Michos, Eric Boerwinkle, Stephanie J. Weinstein, Neal D. Freedman, Wen-Yi Huang, Natasja M. Van Schoor, Nathalie van der Velde, Lisette C. P. G. M. de Groot, Anke Enneman, L. Adrienne Cupples, Sarah L. Booth, Ramachandran S. Vasan, Ching-Ti Liu, Yanhua Zhou, Samuli Ripatti, Claes Ohlsson, Liesbeth Vandenput, Mattias Lorentzon, Johan G. Eriksson, M. Kyla Shea, Denise K. Houston, Stephen B. Kritchevsky, Yongmei Liu, Kurt K. Lohman, Luigi Ferrucci, Munro Peacock, Christian Gieger, Marian Beekman, Eline Slagboom, Joris Deelen, Diana van Heemst, Marcus E. Kleber, Winfried März, Ian H. de Boer, Alexis C. Wood, Jerome I. Rotter, Stephen S. Rich, Cassianne Robinson-Cohen, Martin den Heijer, Marjo-Riitta Jarvelin, Alana Cavadino, Peter K. Joshi, James F. Wilson, Caroline Hayward, Lars Lind, Karl Michaëlsson, Stella Trompet, M. Carola Zillikens, Andre G. Uitterlinden, Fernando Rivadeneira, Linda Broer, Lina Zgaga, Harry Campbell, Evropi Theodoratou, Susan M. Farrington, Maria Timofeeva, Malcolm G. Dunlop, Ana M. Valdes, Emmi Tikkanen, Terho Lehtimäki, Leo-Pekka Lyytikäinen, Mika Kähönen, Olli T. Raitakari, Vera Mikkilä, M. Arfan Ikram, Naveed Sattar, J. Wouter Jukema, Nicholas J. Wareham, Claudia Langenberg, Nita G. Forouhi, Thomas E. Gundersen, Kay-Tee Khaw, Adam S. Butterworth, John Danesh, Timothy Spector, Thomas J. Wang, Elina Hyppönen, Peter Kraft, and Douglas P. Kiel
Subjects: Science
Abstract: Vitamin D deficiency is associated with multiple human pathologic conditions. In a genome-wide association study of 79,366 individuals, Jiang et al. replicate four and identify two new genetic loci for serum levels of 25-hydroxyvitamin D and find evidence for a shared genetic basis with autoimmune diseases.
Published: 2018
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28. A comparison of time dependent Cox regression, pooled logistic regression and cross sectional pooling with simulations and an application to the Framingham Heart Study

Author: Julius S. Ngwa, Howard J. Cabral, Debbie M. Cheng, Michael J. Pencina, David R. Gagnon, Michael P. LaValley, and L. Adrienne Cupples
Subjects: Time dependent covariate model (TDCM), Cross sectional pooling (CSP), Pooled logistic regression (PLR), Longitudinal and survival data, Medicine (General), R5-920
Abstract: Abstract Background Typical survival studies follow individuals to an event and measure explanatory variables for that event, sometimes repeatedly over the course of follow up. The Cox regression model has been used widely in the analyses of time to diagnosis or death from disease. The associations between the survival outcome and time dependent measures may be biased unless they are modeled appropriately. Methods In this paper we explore the Time Dependent Cox Regression Model (TDCM), which quantifies the effect of repeated measures of covariates in the analysis of time to event data. This model is commonly used in biomedical research but sometimes does not explicitly adjust for the times at which time dependent explanatory variables are measured. This approach can yield different estimates of association compared to a model that adjusts for these times. In order to address the question of how different these estimates are from a statistical perspective, we compare the TDCM to Pooled Logistic Regression (PLR) and Cross Sectional Pooling (CSP), considering models that adjust and do not adjust for time in PLR and CSP. Results In a series of simulations we found that time adjusted CSP provided identical results to the TDCM while the PLR showed larger parameter estimates compared to the time adjusted CSP and the TDCM in scenarios with high event rates. We also observed upwardly biased estimates in the unadjusted CSP and unadjusted PLR methods. The time adjusted PLR had a positive bias in the time dependent Age effect with reduced bias when the event rate is low. The PLR methods showed a negative bias in the Sex effect, a subject level covariate, when compared to the other methods. The Cox models yielded reliable estimates for the Sex effect in all scenarios considered. Conclusions We conclude that survival analyses that explicitly account in the statistical model for the times at which time dependent covariates are measured provide more reliable estimates compared to unadjusted analyses. We present results from the Framingham Heart Study in which lipid measurements and myocardial infarction data events were collected over a period of 26 years.
Published: 2016
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29. 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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30. New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk

Author: Yingchang Lu, Felix R. Day, Stefan Gustafsson, Martin L. Buchkovich, Jianbo Na, Veronique Bataille, Diana L. Cousminer, Zari Dastani, Alexander W. Drong, Tõnu Esko, David M. Evans, Mario Falchi, Mary F. Feitosa, Teresa Ferreira, Åsa K. Hedman, Robin Haring, Pirro G. Hysi, Mark M. Iles, Anne E. Justice, Stavroula Kanoni, Vasiliki Lagou, Rui Li, Xin Li, Adam Locke, Chen Lu, Reedik Mägi, John R. B. Perry, Tune H. Pers, Qibin Qi, Marianna Sanna, Ellen M. Schmidt, William R. Scott, Dmitry Shungin, Alexander Teumer, Anna A. E. Vinkhuyzen, Ryan W. Walker, Harm-Jan Westra, Mingfeng Zhang, Weihua Zhang, Jing Hua Zhao, Zhihong Zhu, Uzma Afzal, Tarunveer Singh Ahluwalia, Stephan J. L. Bakker, Claire Bellis, Amélie Bonnefond, Katja Borodulin, Aron S. Buchman, Tommy Cederholm, Audrey C. Choh, Hyung Jin Choi, Joanne E. Curran, Lisette C. P. G. M. de Groot, Philip L. De Jager, Rosalie A. M. Dhonukshe-Rutten, Anke W. Enneman, Elodie Eury, Daniel S. Evans, Tom Forsen, Nele Friedrich, Frédéric Fumeron, Melissa E. Garcia, Simone Gärtner, Bok-Ghee Han, Aki S. Havulinna, Caroline Hayward, Dena Hernandez, Hans Hillege, Till Ittermann, Jack W. Kent, Ivana Kolcic, Tiina Laatikainen, Jari Lahti, Irene Mateo Leach, Christine G. Lee, Jong-Young Lee, Tian Liu, Youfang Liu, Stéphane Lobbens, Marie Loh, Leo-Pekka Lyytikäinen, Carolina Medina-Gomez, Karl Michaëlsson, Mike A. Nalls, Carrie M. Nielson, Laticia Oozageer, Laura Pascoe, Lavinia Paternoster, Ozren Polašek, Samuli Ripatti, Mark A. Sarzynski, Chan Soo Shin, Nina Smolej Narančić, Dominik Spira, Priya Srikanth, Elisabeth Steinhagen-Thiessen, Yun Ju Sung, Karin M. A. Swart, Leena Taittonen, Toshiko Tanaka, Emmi Tikkanen, Nathalie van der Velde, Natasja M. van Schoor, Niek Verweij, Alan F. Wright, Lei Yu, Joseph M. Zmuda, Niina Eklund, Terrence Forrester, Niels Grarup, Anne U. Jackson, Kati Kristiansson, Teemu Kuulasmaa, Johanna Kuusisto, Peter Lichtner, Jian'an Luan, Anubha Mahajan, Satu Männistö, Cameron D. Palmer, Janina S. Ried, Robert A. Scott, Alena Stancáková, Peter J. Wagner, Ayse Demirkan, Angela Döring, Vilmundur Gudnason, Douglas P. Kiel, Brigitte Kühnel, Massimo Mangino, Barbara Mcknight, Cristina Menni, Jeffrey R. O'Connell, Ben A. Oostra, Alan R. Shuldiner, Kijoung Song, Liesbeth Vandenput, Cornelia M. van Duijn, Peter Vollenweider, Charles C. White, Michael Boehnke, Yvonne Boettcher, Richard S. Cooper, Nita G. Forouhi, Christian Gieger, Harald Grallert, Aroon Hingorani, Torben Jørgensen, Pekka Jousilahti, Mika Kivimaki, Meena Kumari, Markku Laakso, Claudia Langenberg, Allan Linneberg, Amy Luke, Colin A. Mckenzie, Aarno Palotie, Oluf Pedersen, Annette Peters, Konstantin Strauch, Bamidele O. Tayo, Nicholas J. Wareham, David A. Bennett, Lars Bertram, John Blangero, Matthias Blüher, Claude Bouchard, Harry Campbell, Nam H. Cho, Steven R. Cummings, Stefan A. Czerwinski, Ilja Demuth, Rahel Eckardt, Johan G. Eriksson, Luigi Ferrucci, Oscar H. Franco, Philippe Froguel, Ron T. Gansevoort, Torben Hansen, Tamara B. Harris, Nicholas Hastie, Markku Heliövaara, Albert Hofman, Joanne M. Jordan, Antti Jula, Mika Kähönen, Eero Kajantie, Paul B. Knekt, Seppo Koskinen, Peter Kovacs, Terho Lehtimäki, Lars Lind, Yongmei Liu, Eric S. Orwoll, Clive Osmond, Markus Perola, Louis Pérusse, Olli T. Raitakari, Tuomo Rankinen, D. C. Rao, Treva K. Rice, Fernando Rivadeneira, Igor Rudan, Veikko Salomaa, Thorkild I. A. Sørensen, Michael Stumvoll, Anke Tönjes, Bradford Towne, Gregory J. Tranah, Angelo Tremblay, André G. Uitterlinden, Pim van der Harst, Erkki Vartiainen, Jorma S. Viikari, Veronique Vitart, Marie-Claude Vohl, Henry Völzke, Mark Walker, Henri Wallaschofski, Sarah Wild, James F. Wilson, Loïc Yengo, D. Timothy Bishop, Ingrid B. Borecki, John C. Chambers, L. Adrienne Cupples, Abbas Dehghan, Panos Deloukas, Ghazaleh Fatemifar, Caroline Fox, Terrence S. Furey, Lude Franke, Jiali Han, David J. Hunter, Juha Karjalainen, Fredrik Karpe, Robert C. Kaplan, Jaspal S. Kooner, Mark I. McCarthy, Joanne M. Murabito, Andrew P. Morris, Julia A. N. Bishop, Kari E. North, Claes Ohlsson, Ken K. Ong, Inga Prokopenko, J. Brent Richards, Eric E. Schadt, Tim D. Spector, Elisabeth Widén, Cristen J. Willer, Jian Yang, Erik Ingelsson, Karen L. Mohlke, Joel N. Hirschhorn, John Andrew Pospisilik, M. Carola Zillikens, Cecilia Lindgren, Tuomas Oskari Kilpeläinen, and Ruth J. F. Loos
Subjects: Science
Abstract: A genome-wide association meta-analysis study here shows novel genetic loci to be associated to body fat percentage, and describes cross-phenotype association that further demonstrate a close relationship between adiposity and cardiovascular disease risk.
Published: 2016
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31. 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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32. Lipoprotein(a) levels, apo(a) isoform size, and coronary heart disease risk in the Framingham Offspring Study

Author: Stefania Lamon-Fava, Santica M. Marcovina, John J. Albers, Hal Kennedy, Carl DeLuca, Charles C. White, L. Adrienne Cupples, Judith R. McNamara, Leo J. Seman, Vanina Bongard, and Ernst J. Schaefer
Subjects: apolipoprotein, cholesterol, epidemiology, triglycerides, Biochemistry, QD415-436
Abstract: The aim of this study was to assess the independent contributions of plasma levels of lipoprotein(a) (Lp(a)), Lp(a) cholesterol, and of apo(a) isoform size to prospective coronary heart disease (CHD) risk. Plasma Lp(a) and Lp(a) cholesterol levels, and apo(a) isoform size were measured at examination cycle 5 in subjects participating in the Framingham Offspring Study who were free of CHD. After a mean follow-up of 12.3 years, 98 men and 47 women developed new CHD events. In multivariate analysis, the hazard ratio of CHD was approximately two-fold greater in men in the upper tertile of plasma Lp(a) levels, relative to those in the bottom tertile (P < 0.002). The apo(a) isoform size contributed only modestly to the association between Lp(a) and CHD and was not an independent predictor of CHD. In multivariate analysis, Lp(a) cholesterol was not significantly associated with CHD risk in men. In women, no association between Lp(a) and CHD risk was observed. Elevated plasma Lp(a) levels are a significant and independent predictor of CHD risk in men. The assessment of apo(a) isoform size in this cohort does not add significant information about CHD risk. In addition, the cholesterol content in Lp(a) is not a significant predictor of CHD risk.
Published: 2011
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33. ACC2 gene polymorphisms, metabolic syndrome, and gene-nutrient interactions with dietary fat

Author: Catherine M. Phillips, Louisa Goumidi, Sandrine Bertrais, Martyn R. Field, L. Adrienne Cupples, Jose M. Ordovas, Jolene McMonagle, Catherine Defoort, Julie A. Lovegrove, Christian A. Drevon, Ellen E. Blaak, Beata Kiec-Wilk, Ulf Riserus, Jose Lopez-Miranda, Ross McManus, Serge Hercberg, Denis Lairon, Richard Planells, and Helen M. Roche
Subjects: genetic polymorphisms, insulin resistance, fatty acid metabolism, polyunsaturated fatty acids, Biochemistry, QD415-436
Abstract: Acetyl-CoA carboxylase β (ACC2) plays a key role in fatty acid synthesis and oxidation pathways. Disturbance of these pathways is associated with impaired insulin responsiveness and metabolic syndrome (MetS). Gene-nutrient interactions may affect MetS risk. This study determined the relationship between ACC2 polymorphisms (rs2075263, rs2268387, rs2284685, rs2284689, rs2300453, rs3742023, rs3742026, rs4766587, and rs6606697) and MetS risk, and whether dietary fatty acids modulate this in the LIPGENE-SU.VI.MAX study of MetS cases and matched controls (n = 1754). Minor A allele carriers of rs4766587 had increased MetS risk (OR 1.29 [CI 1.08, 1.58], P = 0.0064) compared with the GG homozygotes, which may in part be explained by their increased body mass index (BMI), abdominal obesity, and impaired insulin sensitivity (P < 0.05). MetS risk was modulated by dietary fat intake (P = 0.04 for gene-nutrient interaction), where risk conferred by the A allele was exacerbated among individuals with a high-fat intake (>35% energy) (OR 1.62 [CI 1.05, 2.50], P = 0.027), particularly a high intake (>5.5% energy) of n-6 polyunsaturated fat (PUFA) (OR 1.82 [CI 1.14, 2.94], P = 0.01; P = 0.05 for gene-nutrient interaction). Saturated and monounsaturated fat intake did not modulate MetS risk. Importantly, we replicated some of these findings in an independent cohort. In conclusion, the ACC2 rs4766587 polymorphism influences MetS risk, which was modulated by dietary fat, suggesting novel gene-nutrient interactions.
Published: 2010
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34. 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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35. Gene-nutrient interactions with dietary fat modulate the association between genetic variation of the ACSL1 gene and metabolic syndrome

Author: Catherine M. Phillips, Louisa Goumidi, Sandrine Bertrais, Martyn R. Field, L. Adrienne Cupples, Jose M. Ordovas, Catherine Defoort, Julie A. Lovegrove, Christian A. Drevon, Michael J. Gibney, Ellen E. Blaak, Beata Kiec-Wilk, Britta Karlstrom, Jose Lopez-Miranda, Ross McManus, Serge Hercberg, Denis Lairon, Richard Planells, and Helen M. Roche
Subjects: genetic polymorphisms, insulin resistance, fatty acid metabolism, PUFA, Biochemistry, QD415-436
Abstract: Long-chain acyl CoA synthetase 1 (ACSL1) plays an important role in fatty acid metabolism and triacylglycerol (TAG) synthesis. Disturbance of these pathways may result in dyslipidemia and insulin resistance, hallmarks of the metabolic syndrome (MetS). Dietary fat is a key environmental factor that may interact with genetic determinants of lipid metabolism to affect MetS risk. We investigated the relationship between ACSL1 polymorphisms (rs4862417, rs6552828, rs13120078, rs9997745, and rs12503643) and MetS risk and determined potential interactions with dietary fat in the LIPGENE-SU.VI.MAX study of MetS cases and matched controls (n = 1,754). GG homozygotes for rs9997745 had increased MetS risk {odds ratio (OR) 1.90 [confidence interval (CI) 1.15, 3.13]; P = 0.01}, displayed elevated fasting glucose (P = 0.001) and insulin concentrations (P = 0.002) and increased insulin resistance (P = 0.03) relative to the A allele carriers. MetS risk was modulated by dietary fat, whereby the risk conferred by GG homozygosity was abolished among individuals consuming either a low-fat (5.5% energy). In conclusion, ACSL1 rs9997745 influences MetS risk, most likely via disturbances in fatty acid metabolism, which was modulated by dietary fat consumption, particularly PUFA intake, suggesting novel gene-nutrient interactions.
Published: 2010
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36. Variants at the APOA5 locus, association with carotid atherosclerosis, and modification by obesity: the Framingham Study

Author: Roberto Elosua, Jose M. Ordovas, L. Adrienne Cupples, Chao-Qiang Lai, Serkalem Demissie, Caroline S. Fox, Joseph F. Polak, Philip A. Wolf, Ralph B. D'Agostino, Sr., and Christopher J. O'Donnell
Subjects: apolipoproteins, carotid arteries, epidemiology, genetics, apolipoprotein A5 gene, Biochemistry, QD415-436
Abstract: Genetic variation at the apolipoprotein A5 gene (APOA5) is associated with increased triglyceride concentrations, a risk factor for atherosclerosis. Carotid intimal medial thickness (IMT) is a surrogate measure of atherosclerosis burden. We sought to determine the association of common APOA5 genetic variants with carotid IMT and stenosis. A total of 2,273 Framingham Offspring Study participants underwent carotid ultrasound and had data on at least one of the five APOA5 variants (−1131T>C, −3A>G, 56C>G, IVS3+476G >A, and 1259T>C). Although none of the individual variants was significantly associated with carotid measures, the haplotype defined by the presence of the rare allele of the 56C>G variant was associated with a higher common carotid artery (CCA) IMT compared with the wild-type haplotype (0.75 vs. 0.73 mm; P < 0.05). The rare allele of each of the −1131T >C, −3A>G, IVS3+476G>A, and 1259T>C variants and the haplotype defined by the presence of the rare alleles in these four variants were each significantly associated with CCA IMT in obese participants. These associations remained significant even after adjustment for triglycerides. APOA5 variants were associated with CCA IMT, particularly in obese participants. The mechanism of these associations and the effect modification by obesity are independent of fasting triglyceride levels.
Published: 2006
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37. Genome-wide linkage analyses and candidate gene fine mapping for HDL3 cholesterol: the Framingham Study

Author: Qiong Yang, Chao-Qiang Lai, Laurence Parnell, L. Adrienne Cupples, Xian Adiconis, Yueping Zhu, Peter W.F. Wilson, David E. Housman, Amanda M. Shearman, Ralph B. D'Agostino, and Jose M. Ordovas
Subjects: high density lipoprotein, high density lipoprotein 3, microsatellite marker, single nucleotide polymorphism, PLAGL1, Biochemistry, QD415-436
Abstract: High density lipoprotein cholesterol (HDL-C) is inversely associated with coronary heart disease and has a genetic component; however, linkage to HDL-C is not conclusive. Subfractions of HDL, such as HDL3-C, may be better phenotypes for linkage studies. Using HDL3-C levels measured on 907 Framingham Heart Study subjects from 330 families around 1987, we conducted a genome-wide variance components linkage analysis with 401 microsatellite markers spaced ∼10 centimorgan (cM) apart. Nine candidate genes were identified and annotated using a bioinformatics approach in the region of the highest linkage peak. Twenty-eight single nucleotide polymorphisms (SNPs) were selected from these candidate genes, and linkage and family-based association fine mapping were conducted using these SNPs. The highest multipoint log-of-the-odds (LOD) score from the initial linkage analysis was 3.7 at 133 cM on chromosome 6. Linkage analyses with additional SNPs yielded the highest LOD score of 4.0 at 129 cM on chromosome 6. Family-based association analysis revealed that SNP rs2257104 in PLAGL1 at ∼143 cM was associated with multivariable adjusted HDL3 (P = 0.03).Further study of the linkage region and exploration of other variants in PLAGL1 are warranted to define the potential functional variants of HDL-C metabolism.
Published: 2005
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38. Influence of the APOA5 locus on plasma triglyceride, lipoprotein subclasses, and CVD risk in the Framingham Heart Study

Author: Chao-Qiang Lai, Serkalem Demissie, L. Adrienne Cupples, Yueping Zhu, Xian Adiconis, Laurence D. Parnell, Dolores Corella, and Jose M. Ordovas
Subjects: apolipoprotein A-V, triglycerides, cardiovascular disease risk, haplotype, remnant-like particles, Biochemistry, QD415-436
Abstract: Several polymorphisms in the APOA5 gene have been associated with increased plasma triglyceride (TG) concentrations. However, associations between APOA5 and lipoprotein subclasses, remnant-like particles (RLPs), and cardiovascular disease (CVD) risk have been less explored. We investigated associations of five APOA5 single-nucleotide polymorphisms (SNPs; −1131T>C, −3A>G, 56C>G IVS3+ 476G>A, and 1259T>C) with lipoprotein subfractions and CVD risk in 1,129 men and 1,262 women participating in the Framingham Heart Study. Except for the 56C>G SNP, the other SNPs were in significant linkage disequilibria, resulting in three haplotypes (11111, 22122, and 11211) representing 98% of the population. SNP analyses revealed that the −1131T>C and 56C>G SNPs were significantly associated with higher plasma TG concentrations in both men and women. For RLP and lipoprotein subclasses, we observed gender-specific association for the −1131T>C and 56C>G SNPs. Female carriers of the −1131C allele had higher RLP concentrations, whereas in males, significant associations for RLPs were observed for the 56G allele. Moreover, haplotype analyses confirmed these findings and revealed that the 22122 and 11211 haplotypes exhibited different associations with HDL cholesterol concentrations.In women, the −1131C allele was associated with a higher hazard ratio for CVD (1.85; 95% confidence interval, 1.03−3.34; P = 0.04), in agreement with the association of this SNP with higher RLPs.
Published: 2004
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39. Association of APOE genotype with carotid atherosclerosis in men and women

Author: Roberto Elosua, Jose M. Ordovas, L. Adrienne Cupples, Caroline S. Fox, Joseph F. Polak, Philip A. Wolf, Ralph A. D’Agostino, Sr., and Christopher J. O’Donnell
Subjects: genetics, atherosclerosis, carotid artery, lipoprotein, apolipoprotein E genotype, Biochemistry, QD415-436
Abstract: The aim of this study was to determine the association between APOE genotype and carotid atherosclerosis, defined as intimal-medial thickness (IMT) and stenosis, and to assess if other cardiovascular risk factors modify this association. A total of 1,315 men and 1,408 women from the Framingham Offspring Study underwent carotid ultrasound during examination cycle 6 and had complete data on APOE genotype. Three APOE genotype groups were defined: APOE2 (including E2/E2, E3/E2 genotypes), APOE3 (E3/E3), and APOE4 (including E4/E3, E4/E4 genotypes). Carotid IMT and the presence of carotid stenosis > 25% were determined by ultrasonography. In women, the APOE2 group was associated with lower carotid IMT (0.67 vs. 0.73 mm) and lower prevalence of stenosis (odds ratio = 0.49; 95% confidence interval = 0.30–0.81) compared with the APOE3 group. In men, APOE genotype was not associated with carotid IMT or stenosis in the whole group; however, diabetes modified the association between APOE genotype and carotid IMT (P for interaction = 0.044). Among men with diabetes, the APOE4 group was associated with a higher internal carotid artery IMT (1.22 mm) than the APOE3 group (0.90 mm) or the APOE2 group (0.84 mm).The E2 allele was associated with lower carotid atherosclerosis in women, and the E4 allele was associated with higher internal carotid IMT in diabetic men.
Published: 2004
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40. Polymorphisms in the gene encoding lipoprotein lipase in men with low HDL-C and coronary heart disease

Author: Margaret E. Brousseau, Allison L. Goldkamp, Dorothea Collins, Serkalem Demissie, Allison C. Connolly, L. Adrienne Cupples, Jose M. Ordovas, Hanna E. Bloomfield, Sander J. Robins, and Ernst J. Schaefer
Subjects: fibrate, genetics, high density lipoprotein cholesterol, lipids, Biochemistry, QD415-436
Abstract: Our goal was to further define the role of LPL gene polymorphisms in coronary heart disease (CHD) risk. We determined the frequencies of three LPL polymorphisms (D9N, N291S, and S447X) in 899 men from the Veterans Affairs HDL Intervention Trial (VA-HIT), a study that examined the potential benefits of increasing HDL with gemfibrozil in men with established CHD and low high density lipoprotein cholesterol (HDL-C; ≤40 mg/dl), and compared them with those of men without CHD from the Framingham Offspring Study (FOS). In VA-HIT, genotype frequencies for LPL D9N, N291S, and S447X were 5.3, 4.5, and 13.0%, respectively. These values differed from those for men in FOS having an HDL-C of >40, who had corresponding values of 3.2% (P = 0.06), 1.5% (P < 0.01), and 18.2% (P < 0.01). On gemfibrozil, carriers of the LPL N9 allele in VA-HIT had lower levels of large LDL (−32%; P < 0.01) but higher levels of small, dense LDL (+59%; P < 0.003) than did noncarriers. Consequently, mean LDL particle diameter was smaller in LPL N9 carriers than in noncarriers (20.14 ± 0.87 vs. 20.63 ± 0.80 nm; P < 0.003).In men with low HDL-C and CHD: 1) the LPL N9 and S291 alleles are more frequent than in CHD-free men with normal HDL-C, whereas the X447 allele is less frequent, and 2) the LPL N9 allele is associated with the LDL subclass response to gemfibrozil.
Published: 2004
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41. Association of the A-204C polymorphism in the cholesterol 7α-hydroxylase gene with variations in plasma low density lipoprotein cholesterol levels in the Framingham Offspring Study

Author: Patrick Couture, James D. Otvos, L. Adrienne Cupples, Peter W.F. Wilson, Ernst J. Schaefer, and Jose M. Ordovas
Subjects: LDL-cholesterol, cholesterol 7α-hydroxylase, genetic polymorphism, Biochemistry, QD415-436
Abstract: The first reaction of the catabolic pathway of cholesterol is catalyzed by CYP7 and serves as the rate-limiting step and major site of regulation of bile acid synthesis in the liver. A common A to C substitution at position -204 of the promoter of CYP7 gene has been associated with variations in plasma LDL-cholesterol concentrations but the effect of this polymorphism is unknown in the general population. The aim of the present study was therefore to investigate the association of this polymorphism to lipoprotein levels in a population-based sample of 1139 male and 1191 female Framingham Offspring participants. In men, the C variant was associated with higher plasma concentrations of LDL-cholesterol and this association remained significant after adjustment for familial relationship, age, BMI, smoking, alcohol intake, the use of beta-blockers, and apoE genotype. The C variant was also associated with an increased TC/HDL ratio in men. Variance components analysis indicated that allelic variability at nucleotide -204 of the CYP7 gene and polymorphism of the apoE gene accounted for 1 and 5% of the variation of plasma LDL-cholesterol concentrations, respectively. In women, however, there was no relationship between LDL-cholesterol and the A-204C polymorphism but subjects homozygous for the CC genotype had significantly lower triglyceride levels than heterozygotes. Moreover, no significant relationship was found between the A-204C variants and lipoprotein particle diameter or the prevalence of coronary heart disease in both genders. Thus, our results show that the A-204C polymorphism in the CYP7 gene is associated with statistically significant variations in LDL-C and triglyceride concentrations in men and women, respectively, but the cumulative effects of these variations on atherosclerotic risk remain uncertain.—Couture, P., J. D. Otvos, L. A. Cupples, P. W. F. Wilson, E. J. Schaefer, and J. M. Ordovas. Association of the A-204C polymorphism in the cholesterol 7α-hydroxylase gene with variations in plasma low density lipoprotein cholesterol levels in the Framingham Offspring Study. J. Lipid Res. 1999. 40: 1883–1889.
Published: 1999
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42. Generating survival times with time-varying covariates using the Lambert W Function.

Author: Julius S. Ngwa, Howard J. Cabral, Debbie M. Cheng, David R. Gagnon, Michael P. Lavalley, and L. Adrienne Cupples
Published: 2022
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43. The impact of obesity on lung function measurements and respiratory disease: A Mendelian randomization study

Author: Jiayan Liu, Hanfei Xu, L Adrienne Cupples, George T. O’ Connor, and Ching‐Ti Liu
Subjects: Genetics, Genetics (clinical)
Published: 2023

44. Polygenic transcriptome risk scores for COPD and lung function improve cross-ethnic portability of prediction in the NHLBI TOPMed program

Author: Xiaowei Hu, Dandi Qiao, Wonji Kim, Matthew Moll, Pallavi P. Balte, Leslie A. Lange, Traci M. Bartz, Rajesh Kumar, Xingnan Li, Bing Yu, Brian E. Cade, Cecelia A. Laurie, Tamar Sofer, Ingo Ruczinski, Deborah A. Nickerson, Donna M. Muzny, Ginger A. Metcalf, Harshavardhan Doddapaneni, Stacy Gabriel, Namrata Gupta, Shannon Dugan-Perez, L. Adrienne Cupples, Laura R. Loehr, Deepti Jain, Jerome I. Rotter, James G. Wilson, Bruce M. Psaty, Myriam Fornage, Alanna C. Morrison, Ramachandran S. Vasan, George Washko, Stephen S. Rich, George T. O’Connor, Eugene Bleecker, Robert C. Kaplan, Ravi Kalhan, Susan Redline, Sina A. Gharib, Deborah Meyers, Victor Ortega, Josée Dupuis, Stephanie J. London, Tuuli Lappalainen, Elizabeth C. Oelsner, Edwin K. Silverman, R. Graham Barr, Timothy A. Thornton, Heather E. Wheeler, Michael H. Cho, Hae Kyung Im, and Ani Manichaikul
Subjects: Pulmonary Disease, Chronic Obstructive, Risk Factors, Genetics, Humans, National Heart, Lung, and Blood Institute (U.S.), Transcriptome, Lung, Article, United States, Genetics (clinical)
Abstract: While polygenic risk scores (PRSs) enable early identification of genetic risk for chronic obstructive pulmonary disease (COPD), predictive performance is limited when the discovery and target populations are not well matched. Hypothesizing that the biological mechanisms of disease are shared across ancestry groups, we introduce a PrediXcan-derived polygenic transcriptome risk score (PTRS) to improve cross-ethnic portability of risk prediction. We constructed the PTRS using summary statistics from application of PrediXcan on large-scale GWASs of lung function (forced expiratory volume in 1 s [FEV(1)] and its ratio to forced vital capacity [FEV(1)/FVC]) in the UK Biobank. We examined prediction performance and cross-ethnic portability of PTRS through smoking-stratified analyses both on 29,381 multi-ethnic participants from TOPMed population/family-based cohorts and on 11,771 multi-ethnic participants from TOPMed COPD-enriched studies. Analyses were carried out for two dichotomous COPD traits (moderate-to-severe and severe COPD) and two quantitative lung function traits (FEV(1) and FEV(1)/FVC). While the proposed PTRS showed weaker associations with disease than PRS for European ancestry, the PTRS showed stronger association with COPD than PRS for African Americans (e.g., odds ratio [OR] = 1.24 [95% confidence interval [CI]: 1.08–1.43] for PTRS versus 1.10 [0.96–1.26] for PRS among heavy smokers with ≥ 40 pack-years of smoking) for moderate-to-severe COPD. Cross-ethnic portability of the PTRS was significantly higher than the PRS (paired t test p
Published: 2022

45. Data from Polymorphisms in the TOX3/LOC643714 Locus and Risk of Breast Cancer in African-American Women

Author: Julie R. Palmer, Lucile L. Adams-Campbell, L. Adrienne Cupples, Yvette C. Cozier, Lynn Rosenberg, and Edward A. Ruiz-Narváez
Abstract: Background: The rs3803662 single nucleotide polymorphism (SNP) in the TOX3/LOC643714 region was identified as a breast cancer susceptibility genetic variant in recent genome-wide association studies of women of European ancestry and has been replicated in other populations of European ancestry. The position of the causal variant tagged by the rs3803662 marker is still unknown. In fact, because the rs3803662 polymorphism is located between the TOX3 and the LOC643714 loci, it is unclear which gene is the one causally related to the risk of breast cancer. Because linkage disequilibrium blocks are smaller in populations of African ancestry, fine-mapping in African ancestry samples might be an effective approach to narrowing the position of the causal variant(s) in the TOX3/LOC643714 locus.Methods: We evaluated a total of 60 tagging SNPs throughout the TOX3/LOC643714 region in a nested case-control study of breast cancer within the Black Women's Health Study, which included 906 cases and 1,111 controls.Results: No significant association was found for the rs3803662 SNP. However, four other SNPs (rs3104746, rs3112562, rs3104793, and rs8046994), all of them located in the LOC643714 gene, were associated with risk of breast cancer. The strongest association was observed for rs3104746: each copy of the A-rs3104746 allele was associated with a 23% higher risk of breast cancer (odds ratios, 1.23; 95% confidence intervals, 1.05-1.44; P = 0.009).Conclusions: Our results confirm the association observed in genome-wide association studies of European ancestry populations.Impact: The results narrow the locus to a smaller linkage disequilibrium block in the LOC643714 gene. Cancer Epidemiol Biomarkers Prev; 19(5); 1320–7. ©2010 AACR.
Published: 2023

46. Supplementary Figure 2 from Polymorphisms in the TOX3/LOC643714 Locus and Risk of Breast Cancer in African-American Women

Author: Julie R. Palmer, Lucile L. Adams-Campbell, L. Adrienne Cupples, Yvette C. Cozier, Lynn Rosenberg, and Edward A. Ruiz-Narváez
Abstract: Supplementary Figure 2 from Polymorphisms in the TOX3/LOC643714 Locus and Risk of Breast Cancer in African-American Women
Published: 2023

47. Supplementary Figure 1 from Polymorphisms in the TOX3/LOC643714 Locus and Risk of Breast Cancer in African-American Women

Author: Julie R. Palmer, Lucile L. Adams-Campbell, L. Adrienne Cupples, Yvette C. Cozier, Lynn Rosenberg, and Edward A. Ruiz-Narváez
Abstract: Supplementary Figure 1 from Polymorphisms in the TOX3/LOC643714 Locus and Risk of Breast Cancer in African-American Women
Published: 2023

48. Supplementary Table 1 from Polymorphisms in the TOX3/LOC643714 Locus and Risk of Breast Cancer in African-American Women

Author: Julie R. Palmer, Lucile L. Adams-Campbell, L. Adrienne Cupples, Yvette C. Cozier, Lynn Rosenberg, and Edward A. Ruiz-Narváez
Abstract: Supplementary Table 1 from Polymorphisms in the TOX3/LOC643714 Locus and Risk of Breast Cancer in African-American Women
Published: 2023

49. Supplementary Figure 3 from Polymorphisms in the TOX3/LOC643714 Locus and Risk of Breast Cancer in African-American Women

Author: Julie R. Palmer, Lucile L. Adams-Campbell, L. Adrienne Cupples, Yvette C. Cozier, Lynn Rosenberg, and Edward A. Ruiz-Narváez
Abstract: Supplementary Figure 3 from Polymorphisms in the TOX3/LOC643714 Locus and Risk of Breast Cancer in African-American Women
Published: 2023

50. Whole Genome Sequence Analysis of the Plasma Proteome in Black Adults Provides Novel Insights Into Cardiovascular Disease

Author: Daniel H. Katz, Usman A. Tahir, Alexander G. Bick, Akhil Pampana, Debby Ngo, Mark D. Benson, Zhi Yu, Jeremy M. Robbins, Zsu-Zsu Chen, Daniel E. Cruz, Shuliang Deng, Laurie Farrell, Sumita Sinha, Alec A. Schmaier, Dongxiao Shen, Yan Gao, Michael E. Hall, Adolfo Correa, Russell P. Tracy, Peter Durda, Kent D. Taylor, Yongmei Liu, W. Craig Johnson, Xiuqing Guo, Jie Yao, Yii-Der Ida Chen, Ani W. Manichaikul, Deepti Jain, Claude Bouchard, Mark A. Sarzynski, Stephen S. Rich, Jerome I. Rotter, Thomas J. Wang, James G. Wilson, Pradeep Natarajan, Robert E. Gerszten, Namiko Abe, Gonçalo Abecasis, Francois Aguet, Christine Albert, Laura Almasy, Alvaro Alonso, Seth Ament, Peter Anderson, Pramod Anugu, Deborah Applebaum-Bowden, Kristin Ardlie, Dan Arking, Donna K. Arnett, Allison Ashley-Koch, Stella Aslibekyan, Tim Assimes, Paul Auer, Dimitrios Avramopoulos, Najib Ayas, Adithya Balasubramanian, John Barnard, Kathleen Barnes, R. Graham Barr, Emily Barron-Casella, Lucas Barwick, Terri Beaty, Gerald Beck, Diane Becker, Lewis Becker, Rebecca Beer, Amber Beitelshees, Emelia Benjamin, Takis Benos, Marcos Bezerra, Larry Bielak, Joshua Bis, Thomas Blackwell, John Blangero, Eric Boerwinkle, Donald W. Bowden, Russell Bowler, Jennifer Brody, Ulrich Broeckel, Jai Broome, Deborah Brown, Karen Bunting, Esteban Burchard, Carlos Bustamante, Erin Buth, Brian Cade, Jonathan Cardwell, Vincent Carey, Julie Carrier, April Carson, Cara Carty, Richard Casaburi, Juan P. Casas Romero, James Casella, Peter Castaldi, Mark Chaffin, Christy Chang, Yi-Cheng Chang, Daniel Chasman, Sameer Chavan, Bo-Juen Chen, Wei-Min Chen, Michael Cho, Seung Hoan Choi, Lee-Ming Chuang, Mina Chung, Ren-Hua Chung, Clary Clish, Suzy Comhair, Matthew Conomos, Elaine Cornell, Carolyn Crandall, James Crapo, L. Adrienne Cupples, Joanne Curran, Jeffrey Curtis, Brian Custer, Coleen Damcott, Dawood Darbar, Sean David, Colleen Davis, Michelle Daya, Mariza de Andrade, Lisa de las Fuentes, Paul de Vries, Michael DeBaun, Ranjan Deka, Dawn DeMeo, Scott Devine, Huyen Dinh, Harsha Doddapaneni, Qing Duan, Shannon Dugan-Perez, Ravi Duggirala, Jon Peter Durda, Susan K. Dutcher, Charles Eaton, Lynette Ekunwe, Adel El Boueiz, Patrick Ellinor, Leslie Emery, Serpil Erzurum, Charles Farber, Jesse Farek, Tasha Fingerlin, Matthew Flickinger, Myriam Fornage, Nora Franceschini, Chris Frazar, Mao Fu, Stephanie M. Fullerton, Lucinda Fulton, Stacey Gabriel, Weiniu Gan, Shanshan Gao, Margery Gass, Heather Geiger, Bruce Gelb, Mark Geraci, Soren Germer, Robert Gerszten, Auyon Ghosh, Richard Gibbs, Chris Gignoux, Mark Gladwin, David Glahn, Stephanie Gogarten, Da-Wei Gong, Harald Goring, Sharon Graw, Kathryn J. Gray, Daniel Grine, Colin Gross, C. Charles Gu, Yue Guan, Namrata Gupta, David M. Haas, Jeff Haessler, Michael Hall, Yi Han, Patrick Hanly, Daniel Harris, Nicola L. Hawley, Jiang He, Ben Heavner, Susan Heckbert, Ryan Hernandez, David Herrington, Craig Hersh, Bertha Hidalgo, James Hixson, Brian Hobbs, John Hokanson, Elliott Hong, Karin Hoth, Chao (Agnes) Hsiung, Jianhong Hu, Yi-Jen Hung, Haley Huston, Chii Min Hwu, Marguerite Ryan Irvin, Rebecca Jackson, Cashell Jaquish, Jill Johnsen, Andrew Johnson, Craig Johnson, Rich Johnston, Kimberly Jones, Hyun Min Kang, Robert Kaplan, Sharon Kardia, Shannon Kelly, Eimear Kenny, Michael Kessler, Alyna Khan, Ziad Khan, Wonji Kim, John Kimoff, Greg Kinney, Barbara Konkle, Charles Kooperberg, Holly Kramer, Christoph Lange, Ethan Lange, Leslie Lange, Cathy Laurie, Cecelia Laurie, Meryl LeBoff, Jiwon Lee, Sandra Lee, Wen-Jane Lee, Jonathon LeFaive, David Levine, Dan Levy, Joshua Lewis, Xiaohui Li, Yun Li, Henry Lin, Honghuang Lin, Xihong Lin, Simin Liu, Yu Liu, Ruth J.F. Loos, Steven Lubitz, Kathryn Lunetta, James Luo, Ulysses Magalang, Michael Mahaney, Barry Make, Ani Manichaikul, Alisa Manning, JoAnn Manson, Lisa Martin, Melissa Marton, Susan Mathai, Rasika Mathias, Susanne May, Patrick McArdle, Merry-Lynn McDonald, Sean McFarland, Stephen McGarvey, Daniel McGoldrick, Caitlin McHugh, Becky McNeil, Hao Mei, James Meigs, Vipin Menon, Luisa Mestroni, Ginger Metcalf, Deborah A. Meyers, Emmanuel Mignot, Julie Mikulla, Nancy Min, Mollie Minear, Ryan L. Minster, Braxton D. Mitchell, Matt Moll, Zeineen Momin, May E. Montasser, Courtney Montgomery, Donna Muzny, Josyf C. Mychaleckyj, Girish Nadkarni, Rakhi Naik, Take Naseri, Sergei Nekhai, Sarah C. Nelson, Bonnie Neltner, Caitlin Nessner, Deborah Nickerson, Osuji Nkechinyere, Kari North, Jeff O’Connell, Tim O’Connor, Heather Ochs-Balcom, Geoffrey Okwuonu, Allan Pack, David T. Paik, Nicholette Palmer, James Pankow, George Papanicolaou, Cora Parker, Gina Peloso, Juan Manuel Peralta, Marco Perez, James Perry, Ulrike Peters, Patricia Peyser, Lawrence S. Phillips, Jacob Pleiness, Toni Pollin, Wendy Post, Julia Powers Becker, Meher Preethi Boorgula, Michael Preuss, Bruce Psaty, Pankaj Qasba, Dandi Qiao, Zhaohui Qin, Nicholas Rafaels, Laura Raffield, Mahitha Rajendran, Vasan S. Ramachandran, D.C. Rao, Laura Rasmussen-Torvik, Aakrosh Ratan, Susan Redline, Robert Reed, Catherine Reeves, Elizabeth Regan, Alex Reiner, Muagututi’a Sefuiva Reupena, Ken Rice, Stephen Rich, Rebecca Robillard, Nicolas Robine, Dan Roden, Carolina Roselli, Jerome Rotter, Ingo Ruczinski, Alexi Runnels, Pamela Russell, Sarah Ruuska, Kathleen Ryan, Ester Cerdeira Sabino, Danish Saleheen, Shabnam Salimi, Sejal Salvi, Steven Salzberg, Kevin Sandow, Vijay G. Sankaran, Jireh Santibanez, Karen Schwander, David Schwartz, Frank Sciurba, Christine Seidman, Jonathan Seidman, Frédéric Sériès, Vivien Sheehan, Stephanie L. Sherman, Amol Shetty, Aniket Shetty, Wayne Hui-Heng Sheu, M. Benjamin Shoemaker, Brian Silver, Edwin Silverman, Robert Skomro, Albert Vernon Smith, Jennifer Smith, Josh Smith, Nicholas Smith, Tanja Smith, Sylvia Smoller, Beverly Snively, Michael Snyder, Tamar Sofer, Nona Sotoodehnia, Adrienne M. Stilp, Garrett Storm, Elizabeth Streeten, Jessica Lasky Su, Yun Ju Sung, Jody Sylvia, Adam Szpiro, Daniel Taliun, Hua Tang, Margaret Taub, Matthew Taylor, Simeon Taylor, Marilyn Telen, Timothy A. Thornton, Machiko Threlkeld, Lesley Tinker, David Tirschwell, Sarah Tishkoff, Hemant Tiwari, Catherine Tong, Russell Tracy, Michael Tsai, Dhananjay Vaidya, David Van Den Berg, Peter VandeHaar, Scott Vrieze, Tarik Walker, Robert Wallace, Avram Walts, Fei Fei Wang, Heming Wang, Jiongming Wang, Karol Watson, Jennifer Watt, Daniel E. Weeks, Joshua Weinstock, Bruce Weir, Scott T. Weiss, Lu-Chen Weng, Jennifer Wessel, Cristen Willer, Kayleen Williams, L. Keoki Williams, Carla Wilson, James Wilson, Lara Winterkorn, Quenna Wong, Joseph Wu, Huichun Xu, Lisa Yanek, Ivana Yang, Ketian Yu, Seyedeh Maryam Zekavat, Yingze Zhang, Snow Xueyan Zhao, Wei Zhao, Xiaofeng Zhu, Michael Zody, and Sebastian Zoellner
Subjects: Adult, Male, Proteomics, Aging, Whole genome sequence analysis, Proteome, Clinical Sciences, Black People, Disease, Computational biology, race and ethnicity, Cardiorespiratory Medicine and Haematology, Cardiovascular, Article, proteomics, cardiovascular disease, Physiology (medical), Genetics, 2.1 Biological and endogenous factors, Humans, Medicine, Aetiology, Lung, Heart Disease - Coronary Heart Disease, and Blood Institute TOPMed (Trans-Omics for Precision Medicine) Consortium†, business.industry, Prevention, Human Genome, National Heart, Genomics, Blood proteins, Genetic architecture, Heart Disease, Good Health and Well Being, Cardiovascular System & Hematology, Cardiovascular Diseases, Public Health and Health Services, Female, Cardiology and Cardiovascular Medicine, business, Biotechnology, Genome-Wide Association Study
Abstract: Background: Plasma proteins are critical mediators of cardiovascular processes and are the targets of many drugs. Previous efforts to characterize the genetic architecture of the plasma proteome have been limited by a focus on individuals of European descent and leveraged genotyping arrays and imputation. Here we describe whole genome sequence analysis of the plasma proteome in individuals with greater African ancestry, increasing our power to identify novel genetic determinants. Methods: Proteomic profiling of 1301 proteins was performed in 1852 Black adults from the Jackson Heart Study using aptamer-based proteomics (SomaScan). Whole genome sequencing association analysis was ascertained for all variants with minor allele count ≥5. Results were validated using an alternative, antibody-based, proteomic platform (Olink) as well as replicated in the Multi-Ethnic Study of Atherosclerosis and the HERITAGE Family Study (Health, Risk Factors, Exercise Training and Genetics). Results: We identify 569 genetic associations between 479 proteins and 438 unique genetic regions at a Bonferroni-adjusted significance level of 3.8×10 -11 . These associations include 114 novel locus-protein relationships and an additional 217 novel sentinel variant-protein relationships. Novel cardiovascular findings include new protein associations at the APOE gene locus including ZAP70 (sentinel single nucleotide polymorphism [SNP] rs7412-T, β=0.61±0.05, P =3.27×10 -30 ) and MMP-3 (β=-0.60±0.05, P =1.67×10 -32 ), as well as a completely novel pleiotropic locus at the HPX gene, associated with 9 proteins. Further, the associations suggest new mechanisms of genetically mediated cardiovascular disease linked to African ancestry; we identify a novel association between variants linked to APOL1-associated chronic kidney and heart disease and the protein CKAP2 (rs73885319-G, β=0.34±0.04, P =1.34×10 -17 ) as well as an association between ATTR amyloidosis and RBP4 levels in community-dwelling individuals without heart failure. Conclusions: Taken together, these results provide evidence for the functional importance of variants in non-European populations, and suggest new biological mechanisms for ancestry-specific determinants of lipids, coagulation, and myocardial function.
Published: 2022

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