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1. Epigenetic age acceleration is associated with blood lipid levels in a multi-ancestry sample of older U.S. adults

Author

Lisha Lin, Jenna Kiryakos, Farah Ammous, Scott M. Ratliff, Erin B. Ware, Jessica D. Faul, Sharon L.R. Kardia, Wei Zhao, Kira S. Birditt, and Jennifer A. Smith

Subjects
Epigenetic age acceleration, DNA methylation, Lipids, Cholesterol, HDL cholesterol, LDL cholesterol, Internal medicine, RC31-1245, Genetics, QH426-470
Abstract

Abstract Background Dyslipidemia, which is characterized by an unfavorable lipid profile, is a key risk factor for cardiovascular disease (CVD). Understanding the relationships between epigenetic aging and lipid levels may help guide early prevention and treatment efforts for dyslipidemia. Methods We used weighted linear regression to cross-sectionally investigate the associations between five measures of epigenetic age acceleration estimated from whole blood DNA methylation (HorvathAge Acceleration, HannumAge Acceleration, PhenoAge Acceleration, GrimAge Acceleration, and DunedinPACE) and four blood lipid measures (total cholesterol (TC), LDL-C, HDL-C, and triglycerides (TG)) in 3,813 participants (mean age = 70 years) from the Health and Retirement Study (HRS). As a sensitivity analysis, we examined the same associations in participants who fasted prior to the blood draw (n = 2,531) and in participants who did not take lipid-lowering medication (n = 1,869). Using interaction models, we also examined whether demographic factors including age, sex, and educational attainment modified the relationships between epigenetic age acceleration and blood lipids. Results After adjusting for age, race/ethnicity, sex, fasting status, and lipid-lowering medication use, greater epigenetic age acceleration was associated with lower TC, HDL-C, and LDL-C, and higher TG (p

Published
2024
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2. Epigenome-Wide Meta-Analysis Reveals Differential DNA Methylation Associated With Estimated Glomerular Filtration Rate Among African American Men With HIV

Author

Junyu Chen, Qin Hui, Zeyuan Wang, Francis P. Wilson, Kaku So-Armah, Matthew S. Freiberg, Amy C. Justice, Ke Xu, Wei Zhao, Farah Ammous, Jennifer A. Smith, Sharon L.R. Kardia, Marta Gwinn, Vincent C. Marconi, and Yan V. Sun

Subjects
African ancestry, DNA methylation, eGFR, EWAS, HIV, Diseases of the genitourinary system. Urology, RC870-923
Abstract

Introduction: People with HIV (PWH) of African ancestry have faster decline of kidney function and faster progression to end-stage renal disease than PWH of European ancestry. DNA methylation have been associated with kidney function in the general population, however, their relationships are unclear for PWH of African ancestry. Methods: We performed epigenome-wide association studies (EWAS) of estimated glomerular filtration rate (eGFR) among PWH of African ancestry in 2 subsets of the Veterans Aging Cohort Study cohort (N = 885), followed by a meta-analysis to combine the results. Replication was conducted among independent African American samples without HIV. Results: DNA methylation sites cg17944885 near Zinc Finger Family Member 788 (ZNF788) and Zinc Finger Protein 20 (ZNF20), and cg06930757 in SHANK1 were significantly associated with eGFR among PWH of African ancestry (false discovery rate < 0.05). DNA methylation site cg17944885 was also associated with eGFR among different populations including African Americans without HIV. Conclusions: Our study attempted to address an important gap in the literature and to understand the role of DNA methylation in renal diseases in PWH of African ancestry. Replication of cg17944885 among different populations suggests there may be a common pathway for renal diseases progression among PWH and people without HIV, and across different ancestral groups. Our results suggest that genes ZNF788/ZNF20 and SHANK1 could be involved in a pathway linking DNA methylation to renal diseases among PWH and are worth further investigation.

Published
2023
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3. Large-scale exome array summary statistics resources for glycemic traits to aid effector gene prioritization [version 1; peer review: 2 approved]

Author

Natasha H. J. Ng, Sara M. Willems, Jian'an Luan, Rebecca S. Fine, Juan Fernandez, Jennifer Wessel, Eleanor Wheeler, Gaelle Marenne, Hidetoshi Kitajima, Hanieh Yaghootkar, Xueling Sim, Ian J. Deary, Sai Chen, Shuai Wang, Yii-Der Ida Chen, Caroline Hayward, Yuning Chen, Jennifer L. Asimit, Claudia Langenberg, Tibor V. Varga, Archie Campbell, Rona J. Strawbridge, Shuang Feng, Tarunveer S. Ahluwalia, Erica L. Kleinbrink, Emil V. Appel, Ping An, Lawrence F. Bielak, Dan E. Arking, Jennifer A. Brody, Nathan A. Bihlmeyer, David Porteous, Ayse Demirkan, Audrey Y. Chu, Franco Giulianini, James S. Floyd, Stefan Gustafsson, Xiuqing Guo, Johanna Jakobsdottir, Anne U. Jackson, Stavroula Kanoni, Richard A. Jensen, Igor Rudan, Man Li, Sirkka Keinanen-Kiukaanniemi, Alisa K. Manning, Yingchang Lu, Karina Meidtner, Jonathan Marten, Giorgio Pistis, Taulant Muka, Kenneth M. Rice, Bram Prins, Albert Vernon Smith, Serena Sanna, Lorraine Southam, Jennifer A. Smith, Vinicius Tragante, Heather M. Stringham, Helen R. Warren, Sander W. van der Laan, Andrianos M. Yiorkas, Jie Yao, Wei Zhao, Weihua Zhang, Heather M. Highland, Mariaelisa Graff, Eirini Marouli, Anne E. Justice, Wesam A. Alhejily, Saima Afaq, Folkert W. Asselbergs, Najaf Amin, Michiel L. Bots, Lori L. Bonnycastle, Ji Chen, Ivan Brandslund, Abbas Dehghan, John Danesh, Tapani Ebeling, Jessica D. Faul, Aliki-Eleni Farmaki, Steve Franks, Paul W. Franks, Anette P. Gjesing, Andreas Fritsche, Göran Hallmans, Mark O. Goodarzi, Karl-Heinz Herzig, Tamara B. Harris, Min A Jhun, Marie-France Hivert, Marit E. Jørgensen, Torben Jørgensen, Eero Kajantie, Pekka Jousilahti, Sharon L.R. Kardia, Maria Karaleftheri, Heikki A. Koistinen, Leena Kinnunen, Peter Kovacs, Pirjo Komulainen, Markku Laakso, Johanna Kuusisto, Aaron Leong, Lenore J. Launer, Jocelyn E. Manning Fox, Jaana Lindström, Nisa M. Maruthur, Satu Männistö, Antonella Mulas, Leena Moilanen, Matthew Neville, Mike A. Nalls, Alison Pattie, James S. Pankow, Hannu Puolijoki, Eva R.B. Petersen, Paul Redmond, Asif Rasheed, Michael Roden, Frida Renström, Juha Saltevo, Danish Saleheen, Sylvain Sebert, Kai Savonen, Alena Stančáková, Kerrin S. Small, Konstantin Strauch, Jakob Stokholm, Betina H. Thuesen, Juha Auvinen, E-Shyong Tai, Emmanouil Tsafantakis, Anke Tönjes, Jaakko Tuomilehto, Tiinamaija Tuomi, Marja Vääräsmäki, Matti Uusitupa, Magdalena Zoledziewska, Ilonca Vaartjes, Beverley Balkau, Goncalo Abecasis, Alexandra I. Blakemore, Hans Bisgaard, Heiner Boeing, Ruth J.F. Loos, Matthias Blüher, Klaus Bønnelykke, Eric Boerwinkle, Mark J. Caulfield, Erwin P. Bottinger, Daniel I. Chasman, John C. Chambers, Francis S. Collins, Ching-Yu Cheng, Francesco Cucca, Josef Coresh, George Dedoussis, Gert J. de Borst, Hester M. den Ruijter, Panos Deloukas, Ele Ferrannini, Michele K. Evans, Harald Grallert, Oscar H. Franco, Arfan Ikram, Joel N. Hirschhorn, Fredrik Karpe, Erik Ingelsson, Wieland Kiess, Carolina Medina-Gomez, Kay-Tee Kaw, Antje Körner, Jaspal S. Kooner, Cecilia M. Lindgren, Timo Lakka, Ching-Ti Liu, Leonard Lipovich, Patrick E. MacDonald, Jun Liu, Andrew D. Morris, Karen L. Mohlke, Alison Murray, Patricia B. Munroe, Gerard Pasterkamp, Colin N. A . Palmer, Patricia A. Peyser, Oluf Pedersen, Paul M. Ridker, Rainer Rauramaa, Patrik Rorsman, Olov Rolandsson, Veikko Salomaa, Frits R. Rosendaal, Robert Sladek, Matthias B. Schulze, Michael Stumvoll, Timothy D. Spector, Mark Walker, Cornelia M. van Duijn, David R. Weir, Nick J. Wareham, Tien Yin Wong, James G. Wilson, Alan B. Zonderman, Eleftheria Zeggini, Andrew P. Morris, Jerome I. Rotter, Jose C. Florez, Michael Boehnke, James B. Meigs, Mark I. McCarthy, Robert A. Scott, Anubha Mahajan, Inês Barroso, Anna L. Gloyn, Michael A. Province, Niels Grarup, Ruifang Li-Gao, Jette Bork-Jensen, Yongmei Liu, Allan Linneberg, Leslie A. Lange, Sandosh Padmanabhan, Gail Davies, Lars Lind, Bruce M. Psaty, Tea Skaaby, Torben Hansen, Ozren Polasek, John M. Starr, Dennis O. Mook-Kanamori, Vilmundur Gudnason, Kent D. Taylor, Marjo-Riitta Järvelin, Renée de Mutsert, Paul Elliott, Josée Dupuis, Blair H. Smith, and Andrew T. Hattersley

Subjects
exome chip, glycaemic traits, genetic discovery, effector genes, summary statistics resources, eng, Medicine, Science
Abstract

Background Genome-wide association studies for glycemic traits have identified hundreds of loci associated with these biomarkers of glucose homeostasis. Despite this success, the challenge remains to link variant associations to genes, and underlying biological pathways. Methods To identify coding variant associations which may pinpoint effector genes at both novel and previously established genome-wide association loci, we performed meta-analyses of exome-array studies for four glycemic traits: glycated hemoglobin (HbA1c, up to 144,060 participants), fasting glucose (FG, up to 129,665 participants), fasting insulin (FI, up to 104,140) and 2hr glucose post-oral glucose challenge (2hGlu, up to 57,878). In addition, we performed network and pathway analyses. Results Single-variant and gene-based association analyses identified coding variant associations at more than 60 genes, which when combined with other datasets may be useful to nominate effector genes. Network and pathway analyses identified pathways related to insulin secretion, zinc transport and fatty acid metabolism. HbA1c associations were strongly enriched in pathways related to blood cell biology. Conclusions Our results provided novel glycemic trait associations and highlighted pathways implicated in glycemic regulation. Exome-array summary statistic results are being made available to the scientific community to enable further discoveries.

Published
2023
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4. 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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5. Epigenome-wide association study identifies DNA methylation sites associated with target organ damage in older African Americans

Author

Farah Ammous, Wei Zhao, Scott M. Ratliff, Minjung Kho, Lulu Shang, Alana C. Jones, Ninad S. Chaudhary, Hemant K. Tiwari, Marguerite R. Irvin, Donna K. Arnett, Thomas H. Mosley, Lawrence F. Bielak, Sharon L.R. Kardia, Xiang Zhou, and Jennifer Smith

Subjects
target organ damage, dna methylation, estimated glomerular filtration rate, urinary albumin-creatinine ratio, left ventricular mass, relative wall thickness, Genetics, QH426-470
Abstract

Target organ damage (TOD) manifests as vascular injuries in the body organ systems associated with long-standing hypertension. DNA methylation in peripheral blood leukocytes can capture inflammatory processes and gene expression changes underlying TOD. We investigated the association between epigenome-wide DNA methylation and five measures of TOD (estimated glomerular filtration rate (eGFR), urinary albumin-creatinine ratio (UACR), left ventricular mass index (LVMI), relative wall thickness (RWT), and white matter hyperintensity (WMH)) in 961 African Americans from hypertensive sibships. A multivariate (multi-trait) model of eGFR, UACR, LVMI, and RWT identified seven CpGs associated with at least one of the traits (cg21134922, cg04816311 near C7orf50, cg09155024, cg10254690 near OAT, cg07660512, cg12661888 near IFT43, and cg02264946 near CATSPERD) at FDR q

Published
2021
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6. 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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7. Genome-wide Association Study of 24-Hour Urinary Excretion of Calcium, Magnesium, and Uric Acid

Author

Erin B. Ware, PhD, MPH, Jennifer A. Smith, PhD, MPH, Wei Zhao, PhD, Ron T. Ganesvoort, MD, PhD, Gary C. Curhan, MD, ScD, Martin Pollak, MD, David B. Mount, MD, Stephen T. Turner, MD, Guotao Chen, MD, Ronak Jagdeep Shah, MBBS, Sharon L.R. Kardia, PhD, and John C. Lieske, MD

Subjects
Medicine (General), R5-920
Abstract

Objectives: The urinary excretion of organic and inorganic substances and their concentrations have attracted extensive attention for their role in the pathogenesis of urinary stone disease. The urinary excretion of specific factors associates with sex and age and seems to have a hereditary component, but the precise genomic determinants remain ill-defined. Methods: Genome-wide association studies previously conducted in 3 cohorts (Genetic Epidemiology Network of Arteriopathy study, January 1, 2006, through December 31, 2012; the combined Nurses’ Health Study (NHS), NHS II, and Health Professionals Follow-up Study, January 1, 1994, through December 31, 2003; and the Prevention of Renal and Vascular End-stage Disease study, January 1, 1997, through December 31, 1998) were combined into meta-analyses to evaluate genetic associations with available urinary phenotypes relevant to stone pathogenesis (calcium, magnesium, and uric acid excretion; total urine volume). Results: One region on chromosome 9q21.13 showed strong evidence of an association with urinary magnesium excretion. The strongest signal in this region was near TRPM6, whose protein product mediates magnesium transport in the colon and kidney, and C9orf40, C9orf41, NMRK1, and OSTF1 (rs1176815; P=1.70×10–14, with each copy of the A allele corresponding to a daily 5.29-mg decrease in magnesium excretion). The single nucleotide polymorphism (SNP) that achieved genome-wide significance for calcium excretion (rs17216707 on chromosome 20; P=1.12×10–8) was previously associated with fibroblast growth factor 23 levels, which regulate phosphorus and vitamin D metabolism. Urine volume and uric acid excretion did not have any genome-wide significant SNPs. Conclusion: Common variants near genes important for magnesium metabolism and bone health associate with urinary magnesium and calcium excretion.

Published
2019
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8. Insulin Resistance Exacerbates Genetic Predisposition to Nonalcoholic Fatty Liver Disease in Individuals Without Diabetes

Author

Llilda Barata, Mary F. Feitosa, Lawrence F. Bielak, Brian Halligan, Abigail S. Baldridge, Xiuqing Guo, Laura M. Yerges‐Armstrong, Albert V. Smith, Jie Yao, Nicholette D. Palmer, Lisa B. VanWagner, J. Jeffrey Carr, Yii‐Der I. Chen, Matthew Allison, Matthew J. Budoff, Samuel K. Handelman, Sharon L.R. Kardia, Thomas H. Mosley Jr., Kathleen Ryan, Tamara B. Harris, Lenore J. Launer, Vilmundur Gudnason, Jerome I. Rotter, Myriam Fornage, Laura J. Rasmussen‐Torvik, Ingrid B. Borecki, Jeffrey R. O’Connell, Patricia A. Peyser, Elizabeth K. Speliotes, and Michael A. Province

Subjects
Diseases of the digestive system. Gastroenterology, RC799-869
Abstract

The accumulation of excess fat in the liver (hepatic steatosis) in the absence of heavy alcohol consumption causes nonalcoholic fatty liver disease (NAFLD), which has become a global epidemic. Identifying metabolic risk factors that interact with the genetic risk of NAFLD is important for reducing disease burden. We tested whether serum glucose, insulin, insulin resistance, triglyceride (TG), low‐density lipoprotein cholesterol, high‐density lipoprotein cholesterol, body mass index (BMI), and waist‐to‐hip ratio adjusted for BMI interact with genetic variants in or near the patatin‐like phospholipase domain containing 3 (PNPLA3) gene, the glucokinase regulatory protein (GCKR) gene, the neurocan/transmembrane 6 superfamily member 2 (NCAN/TM6SF2) gene, and the lysophospholipase‐like 1 (LYPLAL1) gene to exacerbate hepatic steatosis, estimated by liver attenuation. We performed association analyses in 10 population‐based cohorts separately and then meta‐analyzed results in up to 14,751 individuals (11,870 of European ancestry and 2,881 of African ancestry). We found that PNPLA3‐rs738409 significantly interacted with insulin, insulin resistance, BMI, glucose, and TG to increase hepatic steatosis in nondiabetic individuals carrying the G allele. Additionally, GCKR‐rs780094 significantly interacted with insulin, insulin resistance, and TG. Conditional analyses using the two largest European ancestry cohorts in the study showed that insulin levels accounted for most of the interaction of PNPLA3‐rs738409 with BMI, glucose, and TG in nondiabetic individuals. Insulin, PNPLA3‐rs738409, and their interaction accounted for at least 8% of the variance in hepatic steatosis in these two cohorts. Conclusion: Insulin resistance, either directly or through the resultant elevated insulin levels, more than other metabolic traits, appears to amplify the PNPLA3‐rs738409‐G genetic risk for hepatic steatosis. Improving insulin resistance in nondiabetic individuals carrying PNPLA3‐rs738409‐G may preferentially decrease hepatic steatosis.

Published
2019
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9. Novel DNA methylation sites associated with cigarette smoking among African Americans

Author

Veronica Barcelona, Yunfeng Huang, Kristen Brown, Jiaxuan Liu, Wei Zhao, Miao Yu, Sharon L.R. Kardia, Jennifer A. Smith, Jacquelyn Y. Taylor, and Yan V. Sun

Subjects
dna methylation, smoking, epigenomics, african americans, women, obesity, Genetics, QH426-470
Abstract

Introduction: Cigarette smoking has been associated with adverse health outcomes for mothers and children and is a major contributor to heart disease. Although cigarette smoking is known to affect the epigenome, few studies have been done in African American populations. In this study, we investigated the association between cigarette smoking and DNA methylation (DNAm) among African Americans from the Intergenerational Impact of Genetic and Psychological Factors on Blood Pressure Study (InterGEN), and the Genetic Epidemiology Network of Arteriopathy (GENOA). Methods: The InterGEN study aims to examine the effects of genetic and psychological factors on blood pressure among African American women and their children. Current cigarette smoking was assessed at baseline. DNAm of saliva was assessed using the 850K EPIC Illumina BeadChip for Epigenome-Wide Association analyses. A replication study was conducted among 1100 participants in the GENOA study using the same BeadChip. Results: After controlling for age, body mass index, population structure and cell composition, 26 epigenome-wide significant sites (FDR q

Published
2019
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10. 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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11. Polymorphisms in Renal Ammonia Metabolism Genes Correlate With 24-Hour Urine pH

Author

Benjamin K. Canales, Jennifer A. Smith, I. David Weiner, Erin B. Ware, Wei Zhao, Sharon L.R. Kardia, Gary C. Curhan, Stephen T. Turner, MD, Majuran Perinpam, BS, and John C. Lieske

Subjects
acid-base, diabetes mellitus, genetics, kidney stone disease, uric acid, urine pH, Diseases of the genitourinary system. Urology, RC870-923
Abstract

Urine pH is critical for net acid and solute excretion, but the genetic factors that contribute to its regulation are incompletely understood. Methods: We tested the association of single nucleotide polymorphisms (SNPs) from 16 genes related to ammonia (NH3) metabolism (15 biological candidates selected a priori, 1 selected from a previous genome-wide association study analysis) to that of 24-hour urine pH in 2493 individuals of European descent across 2 different cohorts using linear regression, adjusting for age, sex, and body mass index. Results: Of 2871 total SNPs in these genes, 13 SNPs in ATP6V0A4 (a4 subunit of hydrogen− adenosine triphosphatase), SLC9A3 (sodium/hydrogen exchanger, isoform 3), and RHCG (Rhesus C glycoprotein), and 12 SNPs from insulin-like growth factor binding protein 7 (IGFBP7) had a meta-analysis P value

Published
2017
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12. Contribution of regulatory and structural variations in APOE to predicting dyslipidemia

Author

Jari H. Stengård, Sharon L.R. Kardia, Sara C. Hamon, Ruth Frikke-Schmidt, Anne Tybjærg-Hansen, Veikko Salomaa, Eric Boerwinkle, and Charles F. Sing

Subjects
apolipoprotein E gene, pleiotropy, data mining, regulation, lipids, Biochemistry, QD415-436
Abstract

The objective of this study was to evaluate 1) whether non single nucleotide polymorphisms-coding (non-cSNP) in the apolipoprotein E gene (APOE) identified by resequencing studies contribute to statistically explaining dyslipidemia if variations in the two cSNPs in exon 4 that define the ϵ2, ϵ3, and ϵ4 alleles are ignored, and 2) whether the contribution of these additional SNPs persists when variations in the cSNPs are considered. We used an ecological, multiple-population, data-mining strategy to identify single-SNP and two-SNP genotypes that distinguish between high and low levels of plasma lipids in three training samples, European-Americans from Rochester, MN, African-Americans from Jackson, MS, and Europeans from North Karelia, Finland. We found that a pair of SNPs located in the 5′ region define genotypes A560T832/A560T832, A560T832/A560G832, and A560T832/T560T832, which distinguish between high and low levels of HDL-cholesterol (HDL-C), triglycerides (TG), and/or total cholesterol (T-C). The A560T832/- genotypes predicted high TG and high T-C in both genders in a large independent test sample from Copenhagen, Denmark. Prediction of high T-C in the Danish females was dependent on genotypes defined by the cSNPs. Our study suggests that both regulatory and structural variations should be considered when evaluating the utility of APOE for predicting dyslipidemia in the population at large.

Published
2006
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13. Genomics and Public Health: Development of Web-based Training

Author

Janice V. Bach, MS, Aaron Goldenberg, MA, MPH, Toby Citrin, JD, Sarah F. Raup, MPH, Jennifer Bodzin, MPH, and Sharon L.R. Kardia, PhD

Subjects
Web-based training, public health, chronic disease prevention, genomics, Public aspects of medicine, RA1-1270
Abstract

In 2001, the Centers for Disease Control and Prevention funded three Centers for Genomics and Public Health to develop training tools for increasing genomic awareness. Over the past three years, the centers, working together with the Centers for Disease Control and Preventions Office of Genomics and Disease Prevention, have developed tools to increase awareness of the impact genomics will have on public health practice, to provide a foundation for understanding basic genomic advances, and to translate the relevance of that information to public health practitioners own work. These training tools serve to communicate genomic advances and their potential for integration into public heath practice. This paper highlights two of these training tools: 1) Genomics for Public Health Practitioners: The Practical Application of Genomics in Public Health Practice, a Web-based introduction to genomics, and 2) Six Weeks to Genomic Awareness, an in-depth training module on public health genomics. This paper focuses on the processes and collaborative efforts by which these live presentations were developed and delivered as Web-based training sessions.

Published
2005

14. DNA methylation analysis is used to identify novel genetic loci associated with circulating fibrinogen levels in blood

Author

Julie Hahn, Jan Bressler, Arce Domingo-Relloso, Ming-Huei Chen, Daniel L. McCartney, Alexander Teumer, Jenny van Dongen, Marcus E. Kleber, Dylan Aïssi, Brenton R. Swenson, Jie Yao, Wei Zhao, Jian Huang, Yujing Xia, Michael R. Brown, Ricardo Costeira, Eco J.C. de Geus, Graciela E. Delgado, Dre'Von A. Dobson, Paul Elliott, Hans J. Grabe, Xiuqing Guo, Sarah E. Harris, Jennifer E. Huffman, Sharon L.R. Kardia, Yongmei Liu, Stefan Lorkowski, Riccardo E. Marioni, Matthias Nauck, Scott M. Ratliff, Maria Sabater-Lleal, Tim D. Spector, Pierre Suchon, Kent D. Taylor, Florian Thibord, David-Alexandre Trégouët, Kerri L. Wiggins, Gonneke Willemsen, Jordana T. Bell, Dorret I. Boomsma, Shelley A. Cole, Simon R. Cox, Abbas Dehghan, Andreas Greinacher, Karin Haack, Winfried März, Pierre-Emmanuel Morange, Jerome I. Rotter, Nona Sotoodehnia, Maria Tellez-Plaza, Ana Navas-Acien, Jennifer A. Smith, Andrew D. Johnson, Myriam Fornage, Nicholas L. Smith, Alisa S. Wolberg, Alanna C. Morrison, Paul S. de Vries, Biological Psychology, Amsterdam Reproduction & Development, APH - Mental Health, APH - Personalized Medicine, AMS - Ageing & Vitality, AMS - Sports, APH - Health Behaviors & Chronic Diseases, and APH - Methodology

Subjects
DNA methylation, Hematology, genetics [Fibrinogen], methods [Genome-Wide Association Study], epigenome-wide association study, Epigenesis, Genetic, genetics [Inflammation], SDG 3 - Good Health and Well-being, Genetic Loci, inflammation, Mendelian randomization, Humans, CpG Islands, ddc:610, fibrinogen
Abstract

Background: Fibrinogen plays an essential role in blood coagulation and inflammation. Circulating fibrinogen levels may be determined based on interindividual differences in DNA methylation at cytosine-phosphate-guanine (CpG) sites and vice versa. Objectives: To perform an EWAS to examine an association between blood DNA methylation levels and circulating fibrinogen levels to better understand its biological and pathophysiological actions. Methods: We performed an epigenome-wide association study of circulating fibrinogen levels in 18 037 White, Black, American Indian, and Hispanic participants, representing 14 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium. Circulating leukocyte DNA methylation was measured using the Illumina 450K array in 12 904 participants and using the EPIC array in 5133 participants. In each study, an epigenome-wide association study of fibrinogen was performed using linear mixed models adjusted for potential confounders. Study-specific results were combined using array-specific meta-analysis, followed by cross-replication of epigenome-wide significant associations. We compared models with and without CRP adjustment to examine the role of inflammation. Results: We identified 208 and 87 significant CpG sites associated with fibrinogen levels from the 450K (p < 1.03 × 10−7) and EPIC arrays (p < 5.78 × 10−8), respectively. There were 78 associations from the 450K array that replicated in the EPIC array and 26 vice versa. After accounting for overlapping sites, there were 83 replicated CpG sites located in 61 loci, of which only 4 have been previously reported for fibrinogen. The examples of genes located near these CpG sites were SOCS3 and AIM2, which are involved in inflammatory pathways. The associations of all 83 replicated CpG sites were attenuated after CRP adjustment, although many remained significant. Conclusion: We identified 83 CpG sites associated with circulating fibrinogen levels. These associations are partially driven by inflammatory pathways shared by both fibrinogen and CRP.

Published
2023

15. METRO: Multi-ancestry transcriptome-wide association studies for powerful gene-trait association detection

Author

Zheng Li, Wei Zhao, Lulu Shang, Thomas H. Mosley, Sharon L.R. Kardia, Jennifer A. Smith, and Xiang Zhou

Subjects
Likelihood Functions, Diabetes Mellitus, Type 2, Quantitative Trait Loci, Genetics, Humans, Genetic Predisposition to Disease, Transcriptome, Polymorphism, Single Nucleotide, Article, Genetics (clinical), Genome-Wide Association Study
Abstract

Integrative analysis of genome-wide association studies (GWASs) and gene expression studies in the form of a transcriptome-wide association study (TWAS) has the potential to better elucidate the molecular mechanisms underlying disease etiology. Here we present a method, METRO, that can leverage gene expression data collected from multiple genetic ancestries to enhance TWASs. METRO incorporates expression prediction models constructed in different genetic ancestries through a likelihood-based inference framework, producing calibrated p values with substantially improved TWAS power. We illustrate the benefits of METRO in both simulations and applications to seven complex traits and diseases obtained from four GWASs. These GWASs include two of primarily European ancestry (n = 188,577 and 339,226) and two of primarily African ancestry (n = 42,752 and 23,827). In the real data applications, we leverage gene expression data measured on 1,032 African Americans and 801 European Americans from the Genetic Epidemiology Network of Arteriopathy (GENOA) study to identify a substantially larger number of gene-trait associations as compared to existing TWAS approaches. The benefits of METRO are most prominent in applications to GWASs of African ancestry where the sample size is much smaller than GWASs of European ancestry and where a more powerful TWAS method is crucial. Among the identified associations are high-density lipoprotein-associated genes including PLTP and PPARG that are critical for maintaining lipid homeostasis and the type II diabetes-associated gene MAPT that supports microtubule-associated protein tau as a key component underlying impaired insulin secretion.

Published
2022

17. Bayesian Sparse Mediation Analysis with Targeted Penalization of Natural Indirect Effects

Author

Jian Kang, Yanyi Song, Jennifer A. Smith, Wei Zhao, Bhramar Mukherjee, Belinda L. Needham, Sharon L.R. Kardia, Yongmei Liu, John D. Meeker, Xiang Zhou, Max T. Aung, and Min Zhang

Subjects
FOS: Computer and information sciences, Statistics and Probability, Computer science, Gaussian, Bayesian probability, Inference, Machine learning, computer.software_genre, Statistics - Applications, 01 natural sciences, Article, 010104 statistics & probability, 03 medical and health sciences, symbols.namesake, Prior probability, Applications (stat.AP), 0101 mathematics, Bayesian paradigm, Selection (genetic algorithm), 030304 developmental biology, 0303 health sciences, business.industry, Disease mechanisms, Identification (information), symbols, Artificial intelligence, Statistics, Probability and Uncertainty, business, computer
Abstract

Causal mediation analysis aims to characterize an exposure's effect on an outcome and quantify the indirect effect that acts through a given mediator or a group of mediators of interest. With the increasing availability of measurements on a large number of potential mediators, like the epigenome or the microbiome, new statistical methods are needed to simultaneously accommodate high-dimensional mediators while directly target penalization of the natural indirect effect (NIE) for active mediator identification. Here, we develop two novel prior models for identification of active mediators in high-dimensional mediation analysis through penalizing NIEs in a Bayesian paradigm. Both methods specify a joint prior distribution on the exposure-mediator effect and mediator-outcome effect with either (a) a four-component Gaussian mixture prior or (b) a product threshold Gaussian prior. By jointly modelling the two parameters that contribute to the NIE, the proposed methods enable penalization on their product in a targeted way. Resultant inference can take into account the four-component composite structure underlying the NIE. We show through simulations that the proposed methods improve both selection and estimation accuracy compared to other competing methods. We applied our methods for an in-depth analysis of two ongoing epidemiologic studies: the Multi-Ethnic Study of Atherosclerosis (MESA) and the LIFECODES birth cohort. The identified active mediators in both studies reveal important biological pathways for understanding disease mechanisms.

Published
2021

18. Regulations and Norms for Reuse of Residual Clinical Biospecimens and Health Data

Author

Marcelline R. Harris, Sharon L.R. Kardia, Elizabeth Umberfield, Andrea K. Thomer, and Yun Jiang

Subjects
Medical education, Informed Consent, Nursing research, Secondary research, 06 humanities and the arts, Reuse, 0603 philosophy, ethics and religion, Residual, Health data, 03 medical and health sciences, 0302 clinical medicine, Humans, 060301 applied ethics, 030212 general & internal medicine, Business, Confidentiality, General Nursing
Abstract

Nurse scientists are increasingly interested in conducting secondary research using real world collections of biospecimens and health data. The purposes of this scoping review are to (a) identify federal regulations and norms that bear authority or give guidance over reuse of residual clinical biospecimens and health data, (b) summarize domain experts’ interpretations of permissions of such reuse, and (c) summarize key issues for interpreting regulations and norms. Final analysis included 25 manuscripts and 23 regulations and norms. This review illustrates contextual complexity for reusing residual clinical biospecimens and health data, and explores issues such as privacy, confidentiality, and deriving genetic information from biospecimens. Inconsistencies make it difficult to interpret, which regulations or norms apply, or if applicable regulations or norms are congruent. Tools are necessary to support consistent, expert-informed consent processes and downstream reuse of residual clinical biospecimens and health data by nurse scientists.

Published
2021

19. Accelerated DNA methylation age and medication use among African Americans

Author

Scott M. Ratliff, Wei Zhao, Patricia A. Peyser, Dima Chaar, Jennifer A. Smith, Yi Zhe Wang, Sharon L.R. Kardia, Thomas H. Mosley, and Minjung Kho

Subjects
Adult, Male, Aging, medicine.medical_specialty, methylation age, medication use, Internal medicine, Diabetes mellitus, Hyperlipidemia, medicine, Humans, Epigenetics, African Americans, Sex Characteristics, Medication use, DNA methylation, business.industry, Anti-Inflammatory Agents, Non-Steroidal, dNaM, Cell Biology, Chronological age, Middle Aged, medicine.disease, Black or African American, Pharmaceutical Preparations, Genetic epidemiology, Multivariate Analysis, Female, business, epigenetic clock, Research Paper
Abstract

DNA methylation age acceleration, the discrepancy between epigenetic age and chronological age, is associated with mortality and chronic diseases, including diabetes, hypertension, and hyperlipidemia. In this study, we investigate whether medications commonly used to treat these diseases in 15 drug categories are associated with four epigenetic age acceleration measures: HorvathAge acceleration (HorvathAA), HannumAge acceleration (HannumAA), PhenoAge acceleration, and GrimAge acceleration (GrimAA) using cross-sectional (Phase 1, N=1,100) and longitudinal (Phases 1 and 2, N=266) data from African Americans in the Genetic Epidemiology Network of Arteriopathy (GENOA) study. In cross-sectional analyses, the use of calcium channel blockers was associated with 1.27 years lower HannumAA after adjusting for covariates including hypertension (p=0.001). Longitudinal analyses showed that, compared to those who never used antihypertensives, those who started to take antihypertensives after Phase 1 had a 0.97-year decrease in GrimAA (p=0.007). In addition, compared to those who never used NSAID analgesics, those who started to take them after Phase 1 had a 2.61-year increase in HorvathAA (p=0.0005). Our study demonstrates that three commonly used medications are associated with DNAm age acceleration in African Americans and sheds light on the potential epigenetic effects of pharmaceuticals on aging at the cellular level.

Published
2021

20. Associations between polygenic risk score for age at menarche and menopause, reproductive timing, and serum hormone levels in multiple race/ethnic groups

Author

Miao Yu, Lawrence F. Bielak, Edward A. Ruiz-Narváez, Patricia A. Peyser, Michelle M Hood, Jennifer A. Smith, Sharon L.R. Kardia, Siobán D. Harlow, and Wei Zhao

Subjects
Adult, General Mathematics, Ethnic group, 030209 endocrinology & metabolism, Single-nucleotide polymorphism, Article, 03 medical and health sciences, Race (biology), 0302 clinical medicine, Risk Factors, Ethnicity, medicine, Humans, Genetic association, Menarche, 030219 obstetrics & reproductive medicine, business.industry, Applied Mathematics, Age Factors, Obstetrics and Gynecology, Middle Aged, medicine.disease, Hormones, Menopause, Female, Polygenic risk score, business, Genome-Wide Association Study, Demography, Hormone
Abstract

OBJECTIVE We assessed associations of genetic loci that contribute to age at menarche and menopause with sentinel menopausal traits in multiple race/ethnic groups. METHODS Genetic data from the Study of Women's Health Across the Nation include 738 White, 366 Black, 139 Chinese, and 145 Japanese women aged 42 to 52 at baseline. We constructed standardized polygenic risk scores (PRSs) using single nucleotide polymorphisms identified from large-scale genome-wide association studies meta-analyses of ages at menopause and menarche, evaluating associations with each trait within each race/ethnic group. RESULTS Menopause PRS was significantly associated with age at menopause in White women after Bonferroni correction (P

Published
2021

21. Allele-specific variation at APOE increases nonalcoholic fatty liver disease and obesity but decreases risk of Alzheimer’s disease and myocardial infarction

Author

Vilmundur Gudnason, Solomon K. Musani, Yi-Ping Fu, Albert V. Smith, Yii-Der Ida Chen, Annapurna Kuppa, Xiuqing Guo, Matthew A. Allison, Sharon L.R. Kardia, Donald W. Bowden, Gudny Eirksdottir, Jill M. Norris, Jian Yang, Bratati Kahali, Yanhua Chen, Thomas H. Mosley, Elizabeth K. Speliotes, Lenore J. Launer, James G. Terry, Brian D. Halligan, Jerome I. Rotter, Matthew J. Budoff, Kent D. Taylor, Kathleen A. Ryan, Breland F. Crudup, Adolfo Correa, Lawrence F. Bielak, Jeffrey R. O'Connell, Michael A. Province, Patricia A. Peyser, Nicholette D. Palmer, Christopher J. O'Donnell, Mary F. Feitosa, Lynne E. Wagenknecht, J. Jeffrey Carr, and Xiaomeng Du

Subjects
Liver Cirrhosis, 0301 basic medicine, Apolipoprotein E, Aging, Cirrhosis, Myocardial Infarction, Disease, Neurodegenerative, Alzheimer's Disease, Chronic liver disease, Medical and Health Sciences, Gastroenterology, Oral and gastrointestinal, Hepatitis, Liver disease, 0302 clinical medicine, Gene Frequency, Risk Factors, Non-alcoholic Fatty Liver Disease, Databases, Genetic, Nonalcoholic fatty liver disease, 2.1 Biological and endogenous factors, Exome, Aetiology, Association Studies Article, Genetics (clinical), Genetics & Heredity, Liver Disease, Fatty liver, Alanine Transaminase, Single Nucleotide, General Medicine, Biological Sciences, Prognosis, Phenotype, Liver, Biotechnology, medicine.medical_specialty, Chronic Liver Disease and Cirrhosis, Biology, Polymorphism, Single Nucleotide, Databases, 03 medical and health sciences, Apolipoproteins E, Genetic, Alzheimer Disease, Internal medicine, Acquired Cognitive Impairment, Genetics, medicine, Humans, Obesity, Polymorphism, Molecular Biology, Triglycerides, Alleles, Prevention, Human Genome, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), medicine.disease, Brain Disorders, 030104 developmental biology, Dementia, Steatosis, Digestive Diseases, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Nonalcoholic fatty liver disease (NAFLD) is a leading cause of chronic liver disease and is highly correlated with metabolic disease. NAFLD results from environmental exposures acting on a susceptible polygenic background. This study performed the largest multiethnic investigation of exonic variation associated with NAFLD and correlated metabolic traits and diseases. An exome array meta-analysis was carried out among eight multiethnic population-based cohorts (n = 16 492) with computed tomography (CT) measured hepatic steatosis. A fixed effects meta-analysis identified five exome-wide significant loci (P

Published
2021

22. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program

Author

Nancy L. Heard-Costa, Lucas Barwick, Clary B. Clish, Celeste Eng, Joanne M. Murabito, Esteban G. Burchard, Yii-Der Ida Chen, Daniel I. Chasman, Robert C. Kaplan, James B. Meigs, Deborah A. Nickerson, Cashell E. Jaquish, Eric Boerwinkle, Jennifer A. Brody, Charles Kooperberg, Mark T. Gladwin, Sebastian Schoenherr, Keng-Han Lin, John Barnard, Ryan D. Hernandez, Andrew D. Johnson, Edwin K. Silverman, Mollie A. Minear, Michelle Daya, Barbara A. Konkle, Sharon R. Browning, Daniel E. Weeks, Wendy S. Post, Alexander P. Reiner, Kathryn L. Lunetta, Gina M. Peloso, David Van Den Berg, Dan E. Arking, Seung-been Lee, Leslie A. Lange, Cristen J. Willer, Zachary A. Szpiech, Tasha E. Fingerlin, Wayne E. Clarke, Xutong Zhao, Stephen S. Rich, Nora Franceschini, Sudha Seshadri, Chloé Sarnowski, Hyun Min Kang, Sayantan Das, Michael C. Zody, Stephanie M. Fullerton, Dean Bobo, Alanna C. Morrison, Brian Custer, Nona Sotoodehnia, Shannon Kelly, Thomas W. Blackwell, Bruce M. Psaty, Yingze Zhang, Susan R. Heckbert, Robert E. Gerszten, M. Benjamin Shoemaker, Daniel Taliun, Leslie S. Emery, André Corvelo, Michael H. Cho, Braxton D. Mitchell, Xiaoming Liu, Stella Aslibekyan, Paul L. Auer, Brandon Chalazan, Sarah C. Nelson, Seung Hoan Choi, Jeong-Sun Seo, Matthew P. Conomos, Anne-Katrin Emde, Lawrence F. Bielak, Alisa K. Manning, Allison E. Ashley-Koch, Diane Fatkin, Xiaowen Tian, Emelia J. Benjamin, D. C. Rao, Mina K. Chung, Myriam Fornage, Daniel Levy, Michael D. Kessler, Weihong Tang, Daniel J. Gottlieb, Pradeep Natarajan, Jessica Lasky-Su, Amol C. Shetty, Cathy C. Laurie, Dan M. Roden, Timothy D. O’Connor, Jedidiah Carlson, Lewis C. Becker, Achilleas N. Pitsillides, Karine A. Viaud-Martinez, Raul Torres, Adolfo Correa, Christian Fuchsberger, Deborah A. Meyers, Alvaro Alonso, Sanghamitra Mohanty, Jonathon LeFaive, Soren Germer, Julie L. Mikulla, François Aguet, Susan K. Dutcher, Sarah A Gagliano Taliun, Ani Manichaikul, Lori Garman, Xiuqing Guo, Timothy A. Thornton, David D. McManus, Albert V. Smith, Kristin G. Ardlie, Anna Köttgen, Sharon L.R. Kardia, Quenna Wong, Jill M. Johnsen, Andrea Natale, Richard A. Gibbs, Douglas P. Kiel, Ingo Ruczinski, Susan Redline, Lukas Forer, Scott I. Vrieze, May E. Montasser, Rasika A. Mathias, Jerome I. Rotter, Jacob Pleiness, Chunyu Liu, Brian L. Browning, James G. Wilson, Weiniu Gan, Christine M. Albert, Marilyn J. Telen, Courtney G. Montgomery, Steven A. Lubitz, Robert Klemmer, Ramachandran S. Vasan, Nathan Pankratz, Mariza de Andrade, Vivien A. Sheehan, Kenneth Rice, Xihong Lin, Eimear E. Kenny, Stephanie M. Gogarten, John Blangero, Donna K. Arnett, Jiang He, Pankaj Qasba, James F. Casella, Patrick T. Ellinor, Nicholette D. Palmer, R. Graham Barr, Scott T. Weiss, Joanne E. Curran, Bruce S. Weir, Kari E. North, L. Adrienne Cupples, Dawn L. DeMeo, Tanika N. Kelly, Angel C.Y. Mak, Russell P. Tracy, David A. Schwartz, Kent D. Taylor, Rebecca L. Beer, Daniel N. Harris, George J. Papanicolaou, Marguerite R. Irvin, Stephen T. McGarvey, Sebastian Zöllner, Patricia A. Peyser, Brian E. Cade, Ruth J. F. Loos, Douglas Loesch, Nicholas L. Smith, Gonçalo R. Abecasis, Jennifer A. Smith, Michael E. Hall, Lu-Chen Weng, Jeffrey R. O'Connell, Adrienne M. Stilp, Donald W. Bowden, Kathleen C. Barnes, Stacey Gabriel, Michael Boehnke, Wayne Huey-Herng Sheu, and Dawood Darbar

Subjects
Quality Control, Heterozygote, Genomics, Computational biology, Biology, Polymorphism, Single Nucleotide, Genome, Article, DNA sequencing, INDEL Mutation, Loss of Function Mutation, Genetics research, Genetic variation, Humans, Precision Medicine, Genetic association, Population Density, Multidisciplinary, Whole Genome Sequencing, Genome, Human, Genetic Variation, Rare variants, United States, Genetic architecture, Phenotype, Cytochrome P-450 CYP2D6, Haplotypes, Mutagenesis, Sample Size, Next-generation sequencing, National Heart, Lung, and Blood Institute (U.S.), Imputation (genetics), Reference genome
Abstract

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%., The goals, resources and design of the NHLBI Trans-Omics for Precision Medicine (TOPMed) programme are described, and analyses of rare variants detected in the first 53,831 samples provide insights into mutational processes and recent human evolutionary history.

Published
2021

23. Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts

Author

Daniel DiCorpo, Jessica LeClair, Joanne B. Cole, Chloé Sarnowski, Fariba Ahmadizar, Lawrence F. Bielak, Anneke Blokstra, Erwin P. Bottinger, Layal Chaker, Yii-Der I. Chen, Ye Chen, Paul S. de Vries, Tariq Faquih, Mohsen Ghanbari, Valborg Gudmundsdottir, Xiuqing Guo, Natalie R. Hasbani, Dorina Ibi, M. Arfan Ikram, Maryam Kavousi, Hampton L. Leonard, Aaron Leong, Josep M. Mercader, Alanna C. Morrison, Girish N. Nadkarni, Mike A. Nalls, Raymond Noordam, Michael Preuss, Jennifer A. Smith, Stella Trompet, Petra Vissink, Jie Yao, Wei Zhao, Eric Boerwinkle, Mark O. Goodarzi, Vilmundur Gudnason, J. Wouter Jukema, Sharon L.R. Kardia, Ruth J.F. Loos, Ching-Ti Liu, Alisa K. Manning, Dennis Mook-Kanamori, James S. Pankow, H. Susan J. Picavet, Naveed Sattar, Eleanor M. Simonsick, W.M. Monique Verschuren, Ko Willems van Dijk, Jose C. Florez, Jerome I. Rotter, James B. Meigs, Josée Dupuis, Miriam S. Udler, Epidemiology, and Internal Medicine

Subjects
Endocrinology, Diabetes and Metabolism, Cardiovascular, Medical and Health Sciences, Endocrinology & Metabolism, SDG 3 - Good Health and Well-being, Internal Medicine, Diabetes Mellitus, Genetics, Humans, 2.1 Biological and endogenous factors, Obesity, Aetiology, Alleles, Heart Disease - Coronary Heart Disease, Metabolic and endocrine, Nutrition, Advanced and Specialized Nursing, Liver Disease, Prevention, Diabetes, Cross-Sectional Studies, Heart Disease, Good Health and Well Being, Diabetes Mellitus, Type 2, Pharmaceutical Preparations, Genetic Loci, Digestive Diseases, Type 2
Abstract

OBJECTIVE Type 2 diabetes (T2D) has heterogeneous patient clinical characteristics and outcomes. In previous work, we investigated the genetic basis of this heterogeneity by clustering 94 T2D genetic loci using their associations with 47 diabetes-related traits and identified five clusters, termed β-cell, proinsulin, obesity, lipodystrophy, and liver/lipid. The relationship between these clusters and individual-level metabolic disease outcomes has not been assessed. RESEARCH DESIGN AND METHODS Here we constructed individual-level partitioned polygenic scores (pPS) for these five clusters in 12 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (n = 454,193) and tested for cross-sectional association with T2D-related outcomes, including blood pressure, renal function, insulin use, age at T2D diagnosis, and coronary artery disease (CAD). RESULTS Despite all clusters containing T2D risk-increasing alleles, they had differential associations with metabolic outcomes. Increased obesity and lipodystrophy cluster pPS, which had opposite directions of association with measures of adiposity, were both significantly associated with increased blood pressure and hypertension. The lipodystrophy and liver/lipid cluster pPS were each associated with CAD, with increasing and decreasing effects, respectively. An increased liver/lipid cluster pPS was also significantly associated with reduced renal function. The liver/lipid cluster includes known loci linked to liver lipid metabolism (e.g., GCKR, PNPLA3, and TM6SF2), and these findings suggest that cardiovascular disease risk and renal function may be impacted by these loci through their shared disease pathway. CONCLUSIONS Our findings support that genetically driven pathways leading to T2D also predispose differentially to clinical outcomes.

Published
2022

24. The public’s comfort with sharing health data with third-party commercial companies

Author

Jodyn Platt, M. Grace Trinidad, and Sharon L.R. Kardia

Subjects
020205 medical informatics, Higher education, media_common.quotation_subject, Internet privacy, MEDLINE, Ethnic group, 02 engineering and technology, Article, Health data, lcsh:Social Sciences, 03 medical and health sciences, 0302 clinical medicine, Health care, lcsh:AZ20-999, 0202 electrical engineering, electronic engineering, information engineering, Quality (business), 030212 general & internal medicine, General Psychology, media_common, Third party, business.industry, General Arts and Humanities, General Social Sciences, General Business, Management and Accounting, lcsh:History of scholarship and learning. The humanities, Data sharing, lcsh:H, business, General Economics, Econometrics and Finance
Abstract

Healthcare systems are using big data-driven methods to realize the vision of learning health systems and improve care quality. In so doing, many are partnering with third-party commercial companies to provide novel data processing and analysis capabilities, while also providing personal health information to a for-profit industry that may store and sell data. In this research we describe the public’s comfort with sharing health data with third-party commercial companies for patient and business purposes and how this comfort is associated with demographic factors (sex, age, race/ethnicity, education, employment, income, insurance status, and self-reported health status), perceived healthcare access, and concerns about privacy. We surveyed the US public (n = 1841) to assess comfort with sharing health data with third-party commercial companies for patient or business purposes and examined whether there was a difference between comfort with data sharing for patient or business purposes. Univariate and stepwise regression modeling is used here to estimate the relationship between comfort with third-party commercial companies for patient and business purposes (outcomes) and demographic factors, self-reported health status, perceived healthcare access, and privacy concerns. The public is more comfortable sharing health data with third party commercial companies for patient purposes as compared to business purposes (paired t = 39.84, p β = 0.205, p β = −0.145, p = 0.079). An inverse relationship exists between privacy concerns and comfort with sharing health data for both patient (β = −0.223, p β = −0.246, p β = −0.154, p = 0.0012) than participants aged 18–29. Proactive acknowledgment of privacy concerns and better communication of the steps being taken to protect the privacy of health data can increase patient comfort. Healthcare systems may be able to increase public and patient comfort with sharing health data with third-party commercial companies by emphasizing the patient-centered benefits of these partnerships.

Published
2020

25. Detecting fitness epistasis in recently admixed populations with genome-wide data

Author

Xiaofeng Zhu, Craig L. Hanis, Hua Tang, Mengshi Zhou, Karen Y. He, Sharon L.R. Kardia, Heming Wang, Uli Broeckel, Richard S. Cooper, Xumin Ni, and Susan Redline

Subjects
Linkage disequilibrium, lcsh:QH426-470, lcsh:Biotechnology, ved/biology.organism_classification_rank.species, Population, Genome-wide association study, Biology, Genome, Polymorphism, Single Nucleotide, Fitness epistasis, Linkage Disequilibrium, Receptors, G-Protein-Coupled, 03 medical and health sciences, 0302 clinical medicine, lcsh:TP248.13-248.65, Genetics, Humans, Computer Simulation, Model organism, education, Gene, 030304 developmental biology, 0303 health sciences, education.field_of_study, Admixed population, ved/biology, Chromosomes, Human, Pair 10, Chromosome, Epistasis, Genetic, Diseases/traits, Black or African American, Co-evolution, lcsh:Genetics, Admixture linkage disequilibrium, Evolutionary biology, Chromosomes, Human, Pair 1, Epistasis, Genetic Fitness, 030217 neurology & neurosurgery, Biotechnology, Research Article, Genome-Wide Association Study
Abstract

Background Fitness epistasis, the interaction effect of genes at different loci on fitness, makes an important contribution to adaptive evolution. Although fitness interaction evidence has been observed in model organisms, it is more difficult to detect and remains poorly understood in human populations as a result of limited statistical power and experimental constraints. Fitness epistasis is inferred from non-independence between unlinked loci. We previously observed ancestral block correlation between chromosomes 4 and 6 in African Americans. The same approach fails when examining ancestral blocks on the same chromosome due to the strong confounding effect observed in a recently admixed population. Results We developed a novel approach to eliminate the bias caused by admixture linkage disequilibrium when searching for fitness epistasis on the same chromosome. We applied this approach in 16,252 unrelated African Americans and identified significant ancestral correlations in two pairs of genomic regions (P-value− 7) on chromosomes 1 and 10. The ancestral correlations were not explained by population admixture. Historical African-European crossover events are reduced between pairs of epistatic regions. We observed multiple pairs of co-expressed genes shared by the two regions on each chromosome, including ADAR being co-expressed with IFI44 in almost all tissues and DARC being co-expressed with VCAM1, S1PR1 and ELTD1 in multiple tissues in the Genotype-Tissue Expression (GTEx) data. Moreover, the co-expressed gene pairs are associated with the same diseases/traits in the GWAS Catalog, such as white blood cell count, blood pressure, lung function, inflammatory bowel disease and educational attainment. Conclusions Our analyses revealed two instances of fitness epistasis on chromosomes 1 and 10, and the findings suggest a potential approach to improving our understanding of adaptive evolution.

Published
2020

26. Genetic Architecture of Gene Expression in European and African Americans: An eQTL Mapping Study in GENOA

Author

Sharon L.R. Kardia, Lulu Shang, Thomas H. Mosley, Minjung Kho, Xiang Zhou, Stephen T. Turner, Wei Zhao, and Jennifer A. Smith

Subjects
Male, Quantitative Trait Loci, Population, Quantitative trait locus, Biology, Polymorphism, Single Nucleotide, White People, Article, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Genetics, Humans, SNP, Genetic Predisposition to Disease, education, Gene, Genetics (clinical), 030304 developmental biology, Genetic association, 0303 health sciences, education.field_of_study, Chromosome Mapping, Heritability, Genetic architecture, Black or African American, Gene Expression Regulation, Evolutionary biology, Expression quantitative trait loci, Female, Transcriptome, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Most existing expression quantitative trait locus (eQTL) mapping studies have been focused on individuals of European ancestry and are underrepresented in other populations including populations with African ancestry. Lack of large-scale well-powered eQTL mapping studies in populations with African ancestry can both impede the dissemination of eQTL mapping results that would otherwise benefit individuals with African ancestry and hinder the comparable analysis for understanding how gene regulation is shaped through evolution. We fill this critical knowledge gap by performing a large-scale in-depth eQTL mapping study on 1,032 African Americans (AA) and 801 European Americans (EA) in the GENOA cohort. We identified a total of 354,931 eSNPs in AA and 371,309 eSNPs in EA, with 112,316 eSNPs overlapped between the two. We found that eQTL harboring genes (eGenes) are enriched in metabolic pathways and tend to have higher SNP heritability compared to non-eGenes. We found that eGenes that are common in the two populations tend to be less conserved than eGenes that are unique to one population, which are less conserved than non-eGenes. Through conditional analysis, we found that eGenes in AA tend to harbor more independent eQTLs than eGenes in EA, suggesting potentially diverse genetic architecture underlying expression variation in the two populations. Finally, the large sample sizes in GENOA allow us to construct accurate expression prediction models in both AA and EA, facilitating powerful transcriptome-wide association studies. Overall, our results represent an important step toward revealing the genetic architecture underlying expression variation in African Americans.

Published
2020

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

Author

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

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

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

Published
2022

28. Are we teaching our students visual communication? Evaluation of writing assignments in public health

Author

Kashvi Gupta, Sharon L.R. Kardia, Ella August, and Olivia S. Anderson

Subjects
medicine.medical_specialty, Medical education, 030505 public health, 020205 medical informatics, Visual Arts and Performing Arts, Communication, Writing, Public health, 02 engineering and technology, Health Professions (miscellaneous), 03 medical and health sciences, Medical Illustration, 0202 electrical engineering, electronic engineering, information engineering, medicine, Humans, Visual communication, Public Health, 0305 other medical science, Psychology
Abstract

Visuals are an important means through which public health data can be communicated to diverse audiences, yet many public health students are not trained to develop effective visuals. We evaluated writing assignments from courses taught in public health schools and programmes accredited by the Council on Education for Public Health during the 2016-2017 academic year to identify whether they mentioned a visual element, whether the assignment explained how to create the visual, and if the visual element was worth points. Only 13 of 44 writing assignments mentioned a visual element and only two provided some instructions about how to create the visual element(s). Five assignments awarded points for visual elements. The lack of emphasis on visual elements in writing assignments is significant since visual communication is a key skill needed by practitioners to accompany writing to convey important public health information. Visual communication requires a critical thinking process and therefore time to develop the skills to create effective visuals is necessary. Thus, there is a crucial need for dedicated instruction for public health students to establish competence in visual communication.

Published
2019

29. Genome-wide Association Study of 24-Hour Urinary Excretion of Calcium, Magnesium, and Uric Acid

Author

Sharon L.R. Kardia, Erin B. Ware, Ron T. Ganesvoort, John C. Lieske, Jennifer A. Smith, Guotao Chen, Martin R. Pollak, Wei Zhao, Ronak Jagdeep Shah, David B. Mount, Gary C. Curhan, and Stephen T. Turner

Subjects
Fibroblast growth factor 23, Urinary system, BMI, body mass index, GDUL, Genetic Determinants of Urinary Lithogenicity, Physiology, chemistry.chemical_element, Single-nucleotide polymorphism, 030204 cardiovascular system & hematology, Calcium, Excretion, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, HPFS, Health Professionals Follow-up Study, FGF23, fibroblast growth factor 23, Medicine, NHS, Nurses’ Health Study, 030212 general & internal medicine, Kidney, lcsh:R5-920, business.industry, CKD, chronic kidney disease, QQ, quantile-quantile, SNP, single nucleotide polymorphism, 3. Good health, medicine.anatomical_structure, chemistry, Uric acid, PREVEND, Prevention of Renal and Vascular End-stage Disease, Nurses' Health Study, Original Article, business, lcsh:Medicine (General), GENOA, Genetic Epidemiology Network of Arteriopathy, GWAS, Genome-wide association study
Abstract

Objectives The urinary excretion of organic and inorganic substances and their concentrations have attracted extensive attention for their role in the pathogenesis of urinary stone disease. The urinary excretion of specific factors associates with sex and age and seems to have a hereditary component, but the precise genomic determinants remain ill-defined. Methods Genome-wide association studies previously conducted in 3 cohorts (Genetic Epidemiology Network of Arteriopathy study, January 1, 2006, through December 31, 2012; the combined Nurses' Health Study (NHS), NHS II, and Health Professionals Follow-up Study, January 1, 1994, through December 31, 2003; and the Prevention of Renal and Vascular End-stage Disease study, January 1, 1997, through December 31, 1998) were combined into meta-analyses to evaluate genetic associations with available urinary phenotypes relevant to stone pathogenesis (calcium, magnesium, and uric acid excretion; total urine volume). Results One region on chromosome 9q21.13 showed strong evidence of an association with urinary magnesium excretion. The strongest signal in this region was near TRPM6, whose protein product mediates magnesium transport in the colon and kidney, and C9orf40, C9orf41, NMRK1, and OSTF1 (rs1176815; P=1.70×10–14, with each copy of the A allele corresponding to a daily 5.29-mg decrease in magnesium excretion). The single nucleotide polymorphism (SNP) that achieved genome-wide significance for calcium excretion (rs17216707 on chromosome 20; P=1.12×10–8) was previously associated with fibroblast growth factor 23 levels, which regulate phosphorus and vitamin D metabolism. Urine volume and uric acid excretion did not have any genome-wide significant SNPs. Conclusion Common variants near genes important for magnesium metabolism and bone health associate with urinary magnesium and calcium excretion.

Published
2019

30. Genetic Contributions to Early and Late Onset Ischemic Stroke

Author

Cristina Sanchez-Mora, Jie Hu, Philippe Amouyel, Annette Peters, Charles C Hong, Mary Cushman, Kathleen A. Ryan, Jiang Li, Liming Li, Thomas Jaworek, Sylvia Wassertheil-Smoller, Tiina Metso, Martin Soderholm, Kathryn M. Rexrode, Nicholas L. Smith, Jane Maguire, Martina Müller-Nurasyid, Agnieszka Slowik, Marguerite R. Irvin, Adam S. Butterworth, Martin O’Donnell, Leema Reddy Peddareddygari, Rainer Malik, Ralph L. Sacco, Brady Gaynor, Christian Geiger, Debashree Ray, Anne-Katrin Giese, John W. Cole, Jon Peter Durda, Vincent Thijs, Jukka Putaala, Michiaki Kubo, O. Colin Stine, Rebecca D. Jackson, Israel Fernandez-Cadenas, Reinhold Schmidt, Aki S. Havulinna, Kuang Lin, Christopher Levi, Steven Bell, Timothy O’Connor, Daniel Woo, Jara Cárcel-Márquez, Braxton D. Mitchell, Christina Jern, Jonathan Rosand, Sharon L.R. Kardia, Pankaj Sharma, Mina A. Jacob, Masaru Koido, Vida Abedi, Yoichiro Kamatani, Kristiina Rannikmäe, Michael Chong, Nuria P. Torres-Aguila, Cathie L. M. Sudlow, Ramin Zand, Elizabeth Holliday, Tatjana Rundek, Jessica D. Faul, Leslie Lange, Gunnar Engstrom, Marc C. Hochberg, Bradford B. Worrall, Hugh S. Markus, Joanna Pera, Jordi Jimenez-Conde, Caitrin W. McDonough, Raji P. Grewal, Owen Ross, Robin G. Walters, David J. Duggan, Guillaume Paré, Turgut Tatlisumak, Laura Heitsch, Jin-Moo Lee, Natalie Fecteau, Robin Lemmens, Jennifer A. Smith, Daniel Strbian, Patrick F. McArdle, Martin Dichgans, Jan H. Veldink, Liisa Tomppo, Arne G. Lindgren, Zhengming Chen, Chikashi Terao, Ulrike Grittner, Marta Ribasés, David R. Weir, James F. Meschia, Sothear Luke, Raquel Rabionet Janssen, Tara M. Stanne, Stephanie Debette, Nicole D. Armstrong, James A. Perry, Julie A. Johnson, Huichun Xu, Christopher D. Anderson, Giorgio B. Boncoraglio, Christian Enzinger, Haley Lopez, Anil Man Tuladhar, Oscar R. Benavente, Veikko Salomaa, David-Alexandre Trégouët, John Danesh, F-E de Leeuw, John Attia, Peter M. Rothwell, Steven J. Kittner, Andreea Ilinca, and Carlos Cruchaga

Subjects
0303 health sciences, medicine.medical_specialty, business.industry, Late onset, Locus (genetics), 030204 cardiovascular system & hematology, medicine.disease, 3. Good health, 03 medical and health sciences, Venous thrombosis, 0302 clinical medicine, ABO blood group system, Internal medicine, Ischemic stroke, medicine, Cardiology, SNP, business, Stroke, 030304 developmental biology, Genetic association
Abstract

ObjectiveTo determine the contribution of common genetic variants to risk of early onset ischemic stroke (IS).MethodsWe performed a meta-analysis of genome-wide association studies of early onset IS, ages 18-59, using individual level data or summary statistics in 16,927 cases and 576,353 non-stroke controls from 48 different studies across North America, Europe, and Asia. We further compared effect sizes at our most genome-wide significant loci between early and late onset IS and compared polygenic risk scores for venous thromboembolism between early versus later onset IS.ResultsWe observed an association between early onset IS and ABO, a known stroke locus. The effect size of the peak ABO SNP, rs8176685, was significantly larger in early compared to late onset IS (OR 1.17 (95% C.I.: 1.11-1.22) vs 1.05 (0.99-1.12); p for interaction = 0.008). Analysis of genetically determined ABO blood groups revealed that early onset IS cases were more likely to have blood group A and less likely to have blood group O compared to both non-stroke controls and to late onset IS cases. Using polygenic risk scores, we observed that greater genetic risk for venous thromboembolism, another prothrombotic condition, was more strongly associated with early, compared to late, onset IS (p=0.008).ConclusionThe ABO locus, genetically predicted blood group A, and higher genetic propensity for venous thrombosis are more strongly associated with early onset IS, compared with late onset IS, supporting a stronger role of prothrombotic factors in early onset IS.

Published
2021

31. Whole genome sequence analysis of blood lipid levels in >66,000 individuals

Author

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

Subjects
Genetics, Whole genome sequencing, Genome Scan, Blood lipids, Biology, medicine.disease, Genome, symbols.namesake, Mendelian inheritance, symbols, medicine, lipids (amino acids, peptides, and proteins), Allele, Gene, Dyslipidemia
Abstract

Plasma lipids are heritable modifiable causal factors for coronary artery disease, the leading cause of death globally. Despite the well-described monogenic and polygenic bases of dyslipidemia, limitations remain in discovery of lipid-associated alleles using whole genome sequencing, partly due to limited sample sizes, ancestral diversity, and interpretation of potential clinical significance. Increasingly larger whole genome sequence datasets with plasma lipids coupled with methodologic advances enable us to more fully catalog the allelic spectrum for lipids. Here, among 66,329 ancestrally diverse (56% non-European ancestry) participants, we associate 428M variants from deep-coverage whole genome sequences with plasma lipids. Approximately 400M of these variants were not studied in prior lipids genetic analyses. We find multiple lipid-related genes strongly associated with plasma lipids through analysis of common and rare coding variants. We additionally discover several significantly associated rare non-coding variants largely at Mendelian lipid genes. Notably, we detect rareLDLRintronic variants associated with markedly increased LDL-C, similar to rareLDLRexonic variants. In conclusion, we conducted a systematic whole genome scan for plasma lipids expanding the alleles linked to lipids for multiple ancestries and characterize a clinically-relevant rare non-coding variant model for lipids.

Published
2021

32. Epidemiologic and Genetic Associations of Erythropoietin With Blood Pressure, Hypertension, and Coronary Artery Disease

Author

Adrienne Tin, Yan Zhang, Yong Huo, Zesen Lin, Y. Eugene Chen, Sharon L.R. Kardia, Jia Jia, Bing Yu, Michael R. Brown, Nitin Kumar, Qiwen Zheng, Eric Boerwinkle, Alanna C. Morrison, Pengfei Sun, Kristina L. Hunker, Jing Zhao, Josef Coresh, Xiang Zhou, Rami Khoriaty, Min-Lee Yang, Lawrence F. Bielak, and Santhi K. Ganesh

Subjects
Male, medicine.medical_specialty, Vascular smooth muscle, Receptor, Platelet-Derived Growth Factor alpha, Population, Blood Pressure, Coronary Artery Disease, Hematocrit, Article, Coronary artery disease, chemistry.chemical_compound, Mice, Internal medicine, Internal Medicine, medicine, Animals, Humans, Prospective Studies, education, Erythropoietin, education.field_of_study, medicine.diagnostic_test, Cholesterol, business.industry, Serine Endopeptidases, Membrane Proteins, Odds ratio, Middle Aged, medicine.disease, Mice, Inbred C57BL, Blood pressure, Endocrinology, Cross-Sectional Studies, chemistry, Vasoconstriction, Hypertension, Female, business, medicine.drug
Abstract

While exogenous administration of recombinant erythropoietin has been associated with increased risk of hypertension, coronary artery disease, and mortality, it is not known if endogenous circulating erythropoietin level is associated with coronary artery disease and its risk factors. We measured and analyzed epidemiological and genetic associations of circulating plasma erythropoietin levels in 2 population cohorts, from China (N=4329) and the United States (N=3671). In vitro smooth muscle cell responses and in vivo murine studies of erythropoietin exposure were performed. Erythropoietin levels were positively and linearly associated with blood pressure traits and inversely associated with cholesterol levels and red cell indices. Higher erythropoietin level was associated with higher prevalence of hypertension (odds ratio, 1.20 [95% CI, 1.12–1.29], P =4.41×10 −7 ) and coronary artery disease (odds ratio, 1.16 [95% CI, 1.00–1.34], P =0.046). In a discovery stage genetic association study of erythropoietin level, we identified a previously reported locus on chromosome 6 (rs7776054 near HBS1L-MYB , P =4.86×10 −25 ) and a new locus on chromosome 4 (rs172629 near PDGFRA-KIT , P =2.1×10 −8 ), which was independently replicated. Meta-analysis of discovery and replication genetic association results identified a locus on chromosome 22 (rs855791 near TMPRSS6 , P =3.60×10 −9 ). Erythropoietin administration, within a physiological range of hematocrit achieved, induced hypertension in vivo and increased contraction of vascular smooth muscle cells in vitro. In conclusion, endogenous circulating erythropoietin level is influenced by common genetic variation and is associated with blood pressure traits, hypertension, and coronary artery disease. Vascular effects of erythropoietin demonstrated in vitro and in vivo support a newly discovered mechanism of hypertension and cardiovascular risk with potential implications for erythropoietic support in the clinic. Graphic Abstract: An online graphic abstract is available for this article.

Published
2021

33. Bayesian hierarchical models for high-dimensional mediation analysis with coordinated selection of correlated mediators

Author

John D. Meeker, Jian Kang, Yongmei Liu, Jennifer A. Smith, Bhramar Mukherjee, Xiang Zhou, Wei Zhao, Yanyi Song, Belinda L. Needham, Sharon L.R. Kardia, Max T. Aung, and Min Zhang

Subjects
Statistics and Probability, FOS: Computer and information sciences, Epidemiology, Computer science, Bayesian probability, Gene regulatory network, Machine learning, computer.software_genre, 01 natural sciences, Statistics - Applications, Article, Correlation, 010104 statistics & probability, 03 medical and health sciences, symbols.namesake, Humans, Applications (stat.AP), 0101 mathematics, Selection (genetic algorithm), 030304 developmental biology, 0303 health sciences, Mediation Analysis, business.industry, Bayes Theorem, Environmental exposure, Mixture model, Identification (information), symbols, Artificial intelligence, business, computer, Algorithms, Gibbs sampling
Abstract

We consider Bayesian high-dimensional mediation analysis to identify among a large set of correlated potential mediators the active ones that mediate the effect from an exposure variable to an outcome of interest. Correlations among mediators are commonly observed in modern data analysis; examples include the activated voxels within connected regions in brain image data, regulatory signals driven by gene networks in genome data, and correlated exposure data from the same source. When correlations are present among active mediators, mediation analysis that fails to account for such correlation can be suboptimal and may lead to a loss of power in identifying active mediators. Building upon a recent high-dimensional mediation analysis framework, we propose two Bayesian hierarchical models, one with a Gaussian mixture prior that enables correlated mediator selection and the other with a Potts mixture prior that accounts for the correlation among active mediators in mediation analysis. We develop efficient sampling algorithms for both methods. Various simulations demonstrate that our methods enable effective identification of correlated active mediators, which could be missed by using existing methods that assume prior independence among active mediators. The proposed methods are applied to the LIFECODES birth cohort and the Multi-Ethnic Study of Atherosclerosis (MESA) and identified new active mediators with important biological implications.

Published
2021

34. Genetic insights into biological mechanisms governing human ovarian ageing

Author

Unnur Styrkarsdottir, Lynda M. Rose, Rehannah Borup, Anne B. Newman, Georgia Chenevix-Trench, Chikashi Terao, Jeremy A. Daniel, Christa Meisinger, Albert V. Smith, Emil Peter Thrane Hertz, Raymond Noordam, Wei He, Jennifer A. Smith, Mikael Eriksson, Konstantin Strauch, Daniel I. Chasman, Nicholas J. Timpson, Melissa A. Troester, Claudia Langenberg, Montserrat Garcia-Closas, Mohammad Arfan Ikram, Sara Lindström, Gad Rennert, Pascal Guénel, Kristina W. Olsen, Pierre Fontanillas, Ozren Polasek, Daniel F. Gudbjartsson, Frank B. Hu, Archie Campbell, Celine M. Vachon, Sheila Ulivi, Robin N Beaumont, Robert Karlsson, Lenore J. Launer, Renée de Mutsert, Annette Peters, David Schlessinger, Stefania Bandinelli, Rico Rueedi, Joop S.E. Laven, Pascal Timshel, Joanne M. Murabito, Kuang Lin, Jazib Hussain, Dennis O. Mook-Kanamori, Manjeet K. Bolla, Catherine E. Aiken, Javier Martin Gonzalez, Simon S. Cross, Immaculata De Vivo, Paul M. Ridker, Christopher A. Haiman, Gerardo Heiss, Jessica Tyrrell, Paul R. H. J. Timmers, Hironori Abe, Mike A. Nalls, Luigi Ferrucci, Natalia Perjakova, Jouke J. Hottenga, Robin G. Walters, Reedik Mägi, Niclas Håkansson, Miriam Dwek, Barbara McKnight, Sandra Turon, Stasa Stankovic, Linda Broer, Stephen J. Chanock, Martina La Bianca, Jenny Chang-Claude, Loic Le Marchand, Hamdi Mbarek, Doris Stöckl, Andrew F. Olshan, Graham G. Giles, James F. Wilson, Micaella Joaquim, Amruta Shrikhande, Eva Hoffmann, Stefania Benonisdottir, Ana Martínez-Marchal, Anthony J. Swerdlow, David Karasik, Nicholas J. Wareham, Peter A. Fasching, Jane L. Tarry-Adkins, Charles Kooperberg, Peter Vollenweider, Douglas F. Easton, Paula Aguilera, Jessica D. Faul, Patrik K. E. Magnusson, Emmanouil Saloustros, Alpa V. Patel, Ellen W. Demerath, Qin Wang, Aditya Sankar, Christopher G. Scott, Iffat Rahman, Sharon L.R. Kardia, Peter K. Joshi, Caterina Barbieri, Claus Yding Andersen, Tõnu Esko, Massimo Mezzavilla, Nicholas G. Martin, Rebecca D. Jackson, Alison D. Murray, Marina Ciullo, Nicholas Bowker, Anna Murray, Patrick Deelen, Zoltán Kutalik, Alicja Wolk, Manuela Gago-Dominguez, Eleonora Porcu, Laura Crisponi, Michela Traglia, Katharina E. Schraut, Antonietta Robino, Chunyan He, Bruce H. R. Wolffenbuttel, Henry Völzke, Daniela Ruggiero, John R. B. Perry, Lude Franke, Igor Rudan, Angela Cox, Unnur Þorsteinsdottir, Christian Gieger, David R. Weir, Jodie N. Painter, Martha S. Linet, Massimo Mangino, Melissa C. Southey, Petr Solc, Tim D. Spector, Christiana Kartsonaki, Momoko Horikoshi, Meir J. Stampfer, Eulalia Catamo, Mònica Ferrer-Roda, Ko Willems van Dijk, Daniela Toniolo, Caroline Hayward, Lili Milani, Chloé Sarnowski, Jian'an Luan, Behrooz Z. Alizadeh, Jenny A. Visser, Stig E. Bojesen, Genevieve Lachance, Ulrike Peters, Antonella Mulas, John J. Spinelli, Elnaz Naderi, Andrew R. Wood, Paul D.P. Pharoah, Elinor J. Sawyer, Annique Claringbould, Saleh Shekari, David G. Hunter, Marie Louise Grøndahl, Vilmundur Gudnason, Nora Franceschini, Dale P. Sandler, Dale R. Nyholt, Jacques E. Rossouw, Amber N. Wilcox, Thomas U. Ahearn, Hedy S. Rennert, Olivier B. Bakker, Jingmei Li, Francesco Cucca, Eric Boerwinkle, Matthias W. Beckmann, Cristina Menni, Minouk J. Schoemaker, Esther M. John, Tune H. Pers, Andrés J. López-Contreras, Tanguy Corre, Jonathan Marten, Alice M. Arnold, N. Charlotte Onland-Moret, Lucie Knoblochova, Anna Pujol, Kathryn L. Lunetta, Marjanka K. Schmidt, Teresa Nutile, Serena Sanna, Gonneke Willemsen, Roger L. Milne, Kristan J. Aronson, Frits R. Rosendaal, Murielle Bochud, Ken K. Ong, Susan M. Ring, Nancy L. Pedersen, Blair H. Smith, Ivana Kolcic, Annelie Augustinsson, Jose E. Castelao, Alexander Teumer, Felix R. Day, Sven Bergmann, Timothy M. Frayling, Lauren R. Teras, George Davey Smith, Thomas Meitinger, Alison M. Dunning, Ignasi Roig, Dorret I. Boomsma, Harald Grallert, Toshiko Tanaka, Katherine S. Ruth, Julie E. Buring, Marek Zygmunt, Uwe Völker, Irene L. Andrulis, Håkan Olsson, Harry Campbell, Cari M. Kitahara, Annika Lindblom, Yvonne T. van der Schouw, Cinzia Sala, Debbie A Lawlor, Joe Dennis, Yongmei Liu, Yan Huang, Stephen Burgess, Brumat Marco, Veronique Vitart, Kari Stefansson, Susan E. Ozanne, Kamila Czene, Simin Liu, John L. Hopper, Joyce B. J. van Meurs, Satoshi H. Namekawa, Miya Kudo Høffding, Fergus J. Couch, Ajuna Azad, Eco J. C. de Geus, Liming Li, Grant W. Montgomery, Peter Kraft, André G. Uitterlinden, Arto Mannermaa, Heiko Becher, Allison W. Kurian, Vallari Shukla, Zhengming Chen, Per Hall, Jennifer A. Brody, Rossella Sorice, Wei Zhao, Andres Metspalu, Sarah E. Medland, Tricia Lindstrom, Clarice R. Weinberg, Bruce M. Psaty, Thérèse Truong, Anna Marie Mulligan, Deborah J. Thompson, Patrick Sulem, Internal Medicine, Epidemiology, Obstetrics & Gynecology, Hoffmann, Eva R [0000-0002-2588-0652], Murray, Anna [0000-0002-2351-2522], Roig, Ignasi [0000-0003-0313-3581], Perry, John RB [0000-0001-6483-3771], Apollo - University of Cambridge Repository, Life Course Epidemiology (LCE), Real World Studies in PharmacoEpidemiology, -Genetics, -Economics and -Therapy (PEGET), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Center for Liver, Digestive and Metabolic Diseases (CLDM), Stem Cell Aging Leukemia and Lymphoma (SALL), Biological Psychology, APH - Mental Health, APH - Methodology, APH - Personalized Medicine, and APH - Health Behaviors & Chronic Diseases

Subjects
Gerontology, Aging, Far East, Endocrinology, Diabetes and Metabolism, Menopause, Premature, Genome-wide association study, VARIANTS, Primary Ovarian Insufficiency, Inbred C57BL, Bioinformatics, DISEASE, Healthy Aging, genetics of ovarian aging, Fragile X Mental Retardation Protein, Mice, Endocrinology, Medicine, EARLY MENOPAUSE, media_common, RISK, Multidisciplinary, Asia, Eastern, Reproduction, Longevity, Middle Aged, Europe, MENDELIAN RANDOMIZATION, Medical genetics, Female, ICEP, Menopause, Adult, Alleles, Animals, Bone and Bones, Checkpoint Kinase 1, Checkpoint Kinase 2, Diabetes Mellitus, Type 2, Diet, Fertility, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Mice, Inbred C57BL, Ovary, Uterus, Type 2, medicine.medical_specialty, media_common.quotation_subject, MEDLINE, Biology, Premature ovarian insufficiency, Article, genome-wide meta-analysis, SDG 3 - Good Health and Well-being, GERMLINE, Diabetes Mellitus, Genetic predisposition, Ovarian reserve, Premature, business.industry, Human genetics, CHROMOSOME SYNAPSIS, DNA-DAMAGE, Ageing, EXPRESSION ANALYSIS, business, MEIOTIC CELL-CYCLE
Abstract

Reproductive longevity is essential for fertility and influences healthy ageing in women1,2, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations3. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease. Hundreds of genetic loci associated with age at menopause, combined with experimental evidence in mice, highlight mechanisms of reproductive ageing across the lifespan.

Published
2021

35. Multiethnic Genome-Wide Association Study of Subclinical Atherosclerosis in Individuals With Type 2 Diabetes

Author

Stefan Weiss, Gauti Kjartan Gislason, Matthew J. Budoff, Valborg Gudmundsdottir, Xiuqing Guo, Lawrence F. Bielak, Joshua C. Bis, Jie Yao, Latchezar Dimitrov, Leslie A. Lange, Patricia A. Peyser, Lingyi Lu, Vilmundur Gudnason, Jerome I. Rotter, Barry I. Freedman, Lihua Wang, M. Arfan Ikram, Mohsen Ghanbari, Yingchang Lu, Jiaxi Zhu, Elias F Gudmundsson, Gerardo Heiss, Yi-Ping Fu, Maryam Kavousi, Shih-Jen Hwang, Sharon L.R. Kardia, Laura M. Raffield, André G. Uitterlinden, Carl D. Langefeld, Donald W. Bowden, Ping An, Daniel Bos, Kent D. Taylor, Ulf Schminke, Albert V. Smith, Bruce M. Psaty, James G. Wilson, Shyh-Huei Chen, Maggie C.Y. Ng, Christopher J. O'Donnell, Mary F. Feitosa, Nora Franceschini, Epidemiology, Radiology & Nuclear Medicine, and Internal Medicine

Subjects
0301 basic medicine, Aging, Carotid arteries, Genome-wide association study, Type 2 diabetes, 030204 cardiovascular system & hematology, Cardiovascular, Coronary artery disease, 0302 clinical medicine, 2.1 Biological and endogenous factors, Aetiology, Diabetes, General Medicine, Heart Disease, cardiovascular system, Cardiology, medicine.symptom, Type 2, coronary artery disease, medicine.medical_specialty, carotid intima-media thickness, Black People, Asymptomatic, White People, Article, Diabetes Complications, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Internal medicine, Diabetes Mellitus, Genetics, medicine, Humans, Genetic Predisposition to Disease, cardiovascular diseases, Heart Disease - Coronary Heart Disease, genome-wide association study, business.industry, Prevention, Human Genome, nutritional and metabolic diseases, Atherosclerosis, medicine.disease, Good Health and Well Being, 030104 developmental biology, Diabetes Mellitus, Type 2, Genetic Loci, Subclinical atherosclerosis, Coronary artery calcification, business, Genome-Wide Association Study
Abstract

Background: Coronary artery calcification (CAC) and carotid artery intima-media thickness (cIMT) are measures of subclinical atherosclerosis in asymptomatic individuals and strong risk factors for cardiovascular disease. Type 2 diabetes (T2D) is an independent cardiovascular disease risk factor that accelerates atherosclerosis. Methods: We performed meta-analyses of genome-wide association studies in up to 2500 T2D individuals of European ancestry (EA) and 1590 T2D individuals of African ancestry with or without exclusion of prevalent cardiovascular disease, for CAC measured by cardiac computed tomography, and 3608 individuals of EA and 838 individuals of African ancestry with T2D for cIMT measured by ultrasonography within the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium. Results: We replicated 2 loci (rs9369640 and rs9349379 near PHACTR1 and rs10757278 near CDKN2B ) for CAC and one locus for cIMT (rs7412 and rs445925 near APOE-APOC1 ) that were previously reported in the general EA populations. We identified one novel CAC locus (rs8000449 near CSNK1A1L/LINC00547/POSTN at 13q13.3) at P =2.0×10 -8 in EA. No additional loci were identified with the meta-analyses of EA and African ancestry. The expression quantitative trait loci analysis with nearby expressed genes derived from arterial wall and metabolic tissues from the Genotype-Tissue Expression project pinpoints POSTN , encoding a matricellular protein involved in bone formation and bone matrix organization, as the potential candidate gene at this locus. In addition, we found significant associations ( P -4 ) for 3 previously reported coronary artery disease loci for these subclinical atherosclerotic phenotypes (rs2891168 near CDKN2B-AS1 and rs11170820 near FLJ12825 for CAC, and rs7412 near APOE for cIMT). Conclusions: Our results provide potential biological mechanisms that could link CAC and cIMT to increased cardiovascular disease risk in individuals with T2D.

Published
2021

36. A multi-ethnic epigenome-wide association study of leukocyte DNA methylation and blood lipids

Author

Rui Xia, Jordana T. Bell, Roby Joehanes, Abbas Dehghan, Sharon L.R. Kardia, Erin B. Ware, Deugi Zhi, Devin Absher, Annette Peters, Martina Müller-Nurasyid, Daniel Levy, Nona Sotoodehnia, Wei Chen, Coleen M. Damcott, Lifang Hou, Donna K. Arnett, Weihua Guan, Jincheng Shen, Steve Horvath, Rory P. Wilson, Kim Valeska Emilie Braun, Lars Lind, Wei Zhao, Myriam Fornage, Shengxu Li, Mina A. Jhun, Paula Singmann, Elena Carnero-Montoro, Michael M. Mendelson, Jennifer A. Smith, Xiaoping Zhao, Marguerite R. Irvin, Bruce M. Psaty, Andrea A. Baccarelli, Jeffrey R. O'Connell, Mohammad Arfan Ikram, Traci M. Bartz, Erik Ingelsson, Klodian Dhana, Melanie Waldenberger, Stefan Gustafsson, Yii-Der Ida Chen, Thomas Meitinger, Themistocles L. Assimes, Elias Salfati, Tao Zhang, Pfeiffer Liliane, Dianjianyi Sun, Rahul Gondalia, Eric Boerwinkle, Philip S. Tsao, Christian Gieger, Eric A. Whitsel, Chen Yao, Tim D. Spector, Alan R. Shuldiner, Åsa K. Hedman, Joyce B. J. van Meurs, May E. Montasser, Anh N. Do, Mohsen Ghanbari, André G. Uitterlinden, Megan L. Grove, Jennifer A. Brody, Epidemiology, and Internal Medicine

Subjects
Adult, Epigenomics, Male, 0301 basic medicine, Science, Concordance, Quantitative Trait Loci, Ethnic group, General Physics and Astronomy, Blood lipids, 030204 cardiovascular system & hematology, Biology, Article, White People, General Biochemistry, Genetics and Molecular Biology, Epigenesis, Genetic, Epigenome, 03 medical and health sciences, 0302 clinical medicine, Genetics, Leukocytes, Humans, Dyslipidaemias, Aged, Medicinsk genetik, Genetic association, Multidisciplinary, Carnitine O-Palmitoyltransferase, Hispanic or Latino, General Chemistry, DNA Methylation, Middle Aged, Lipids, Black or African American, 030104 developmental biology, Meta-analysis, DNA methylation, Epigenetics, CpG Islands, Female, Lipoproteins, HDL, Medical Genetics
Abstract

Here we examine the association between DNA methylation in circulating leukocytes and blood lipids in a multi-ethnic sample of 16,265 subjects. We identify 148, 35, and 4 novel associations among Europeans, African Americans, and Hispanics, respectively, and an additional 186 novel associations through a trans-ethnic meta-analysis. We observe a high concordance in the direction of effects across racial/ethnic groups, a high correlation of effect sizes between high-density lipoprotein and triglycerides, a modest overlap of associations with epigenome-wide association studies of other cardio-metabolic traits, and a largely non-overlap with lipid loci identified to date through genome-wide association studies. Thirty CpGs reached significance in at least 2 racial/ethnic groups including 7 that showed association with the expression of an annotated gene. CpGs annotated to CPT1A showed evidence of being influenced by triglycerides levels. DNA methylation levels of circulating leukocytes show robust and consistent association with blood lipid levels across multiple racial/ethnic groups., Abnormal blood lipid levels are important risk factors for cardiovascular and other various diseases. Here the authors conduct a large-scale multi-ethnic epigenome-wide association study combined with epigenetic (cis-QTL and eQTM) data, and identify CpG-lipid traits associations that are specific to or common across racial/ethnic groups.

Published
2021

37. Lessons Learned for Identifying and Annotating Permissions in Clinical Consent Forms

Author

Marcelline R. Harris, Yun Jiang, Kathleen Ford, Kaycee Crist, Sharon L.R. Kardia, Cooper Stansbury, Susan H. Fenton, Elizabeth Umberfield, and Andrea K. Thomer

Subjects
030213 general clinical medicine, media_common.quotation_subject, Health Informatics, Permission, computer.software_genre, Consent Forms, 03 medical and health sciences, 0302 clinical medicine, Health Information Management, Complete Agreement, 030212 general & internal medicine, Set (psychology), media_common, Retrospective Studies, Structure (mathematical logic), Point (typography), business.industry, Ambiguity, Computer Science Applications, Artificial intelligence, business, Psychology, computer, Sentence, Natural language processing, Meaning (linguistics)
Abstract

Background The lack of machine-interpretable representations of consent permissions precludes development of tools that act upon permissions across information ecosystems, at scale. Objectives To report the process, results, and lessons learned while annotating permissions in clinical consent forms. Methods We conducted a retrospective analysis of clinical consent forms. We developed an annotation scheme following the MAMA (Model-Annotate-Model-Annotate) cycle and evaluated interannotator agreement (IAA) using observed agreement (A o), weighted kappa (κw ), and Krippendorff's α. Results The final dataset included 6,399 sentences from 134 clinical consent forms. Complete agreement was achieved for 5,871 sentences, including 211 positively identified and 5,660 negatively identified as permission-sentences across all three annotators (A o = 0.944, Krippendorff's α = 0.599). These values reflect moderate to substantial IAA. Although permission-sentences contain a set of common words and structure, disagreements between annotators are largely explained by lexical variability and ambiguity in sentence meaning. Conclusion Our findings point to the complexity of identifying permission-sentences within the clinical consent forms. We present our results in light of lessons learned, which may serve as a launching point for developing tools for automated permission extraction.

Published
2021

38. Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging

Author

Jacob K. Kresovich, Jerome I. Rotter, James S. Pankow, Laura M. Raffield, André G. Uitterlinden, Hemant K. Tiwari, Dorret I. Boomsma, Marguerite R. Irvin, Kaare Christensen, Lili Milani, Jonas Mengel-From, Scott M. Ratliff, Peter Durda, James G. Wilson, Xiaochuan Wang, Rui Xia, Jordana T. Bell, Jenny van Dongen, Pamela R. Matias-Garcia, Alexander P. Reiner, Andrew M. McIntosh, Toshiko Tanaka, Sharon L.R. Kardia, Rebecca C Richmond, Konstantin Strauch, Rosie M. Walker, Dale P. Sandler, Amit Patki, Teemu Palviainen, Wei Chen, Pei-Chien Tsai, Medea Imboden, Stefania Bandinelli, Mika Kähönen, Xiuqing Guo, Stephen S. Rich, Oliver Robinson, Riccardo E. Marioni, Jie Yao, Debbie A Lawlor, Pierre Antoine Dugué, Roger L. Milne, Yunzhang Wang, Jennifer A. Smith, Nancy L. Pedersen, Matthijs D. van der Zee, Pashupati P. Mishra, Pei-Lun Kuo, Steve Horvath, Miina Ollikainen, Massimo Mangino, Melissa C. Southey, Ayoung Jeong, Linda Broer, Dianjianyi Sun, Tom G. Richardson, David Van Den Berg, Jack A. Taylor, Beate Ritz, Jeesun Jung, Caroline L Relton, Sarah E. Harris, Josine L. Min, Caroline Hayward, Eric Boerwinkle, Jaakko Kaprio, Melanie Waldenberger, David J. Porteous, Seyma Katrinli, Gibran Hemani, Olli T. Raitakari, Paolo Vineis, Silvia Polidoro, Karen N. Conneely, Christian Gieger, Donna K. Arnett, Marianne Nygaard, Maria K. Sobczyk, Therese Tillin, Falk W. Lohoff, Adolfo Correa, Wei Zhao, Elina Sillanpää, Zongli Xu, Joanne M. Murabito, John Wright, Gail Davies, Sara Hägg, Mette Soerensen, Alexandra M. Binder, Ann Zenobia Moore, Eco J. C. de Geus, Terho Lehtimäki, Dan Mason, Daniel L. McCartney, Myriam Fornage, Ian J. Deary, Alicia K. Smith, Joyce B. J. van Meurs, Ake T. Lu, Hannah R Elliott, Annette Peters, Silva Kasela, Idil Yet, Luigi Ferrucci, Shengxu Li, Nicole Probst-Hensch, Paul Elliott, Kathryn L. Lunetta, Tampere University, Department of Clinical Chemistry, Clinical Medicine, Department of Clinical Physiology and Nuclear Medicine, Institute for Molecular Medicine Finland, Genetic Epidemiology, Helsinki Institute of Life Science HiLIFE, Department of Public Health, Medical Research Council (MRC), Home Office, Imperial College Healthcare NHS Trust- BRC Funding, Internal Medicine, Epidemiology, Biological Psychology, APH - Mental Health, APH - Personalized Medicine, and APH - Methodology

Subjects
Aging, Multifactorial Inheritance, BLOOD, Epigenetic clock, 05 Environmental Sciences, biomarkkerit, Genome-wide association study, QH426-470, Epigenesis, Genetic, 0302 clinical medicine, Biomarkers of aging, GWAS, Biology (General), Adiposity, Genetics, 11832 Microbiology and virology, 0303 health sciences, 318 Medical biotechnology, DNA methylation, 1184 Genetics, developmental biology, physiology, genomiikka, Dna Methylation, Epigenetic Clock, Gwas, ddc, DNA-metylaatio, INSIGHTS, C-Reactive Protein, epigenetiikka, MENDELIAN RANDOMIZATION, Educational Status, ICEP, Genetic Markers, PROVIDES, SUSCEPTIBILITY LOCI, Bioinformatics, QH301-705.5, Genomics, Biology, 03 medical and health sciences, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, AGE, SDG 3 - Good Health and Well-being, Plasminogen Activator Inhibitor 1, REGRESSION, Humans, Epigenetics, Gene, METAANALYSIS, 030304 developmental biology, Genome, Human, Research, Genetics of DNA Methylation Consortium, 06 Biological Sciences, Lipid Metabolism, Human genetics, Genetic architecture, Immunity, Innate, ikääntyminen, Genetic Loci, CpG Islands, 08 Information and Computing Sciences, 3111 Biomedicine, ENRICHMENT, epigenetic clock, 030217 neurology & neurosurgery, Biomarkers, Genome-Wide Association Study, Granulocytes
Abstract

Background Biological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field. Results Leveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels. Conclusion This study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.

Published
2021

39. The public’s trust and information brokers in health care, public health and research

Author

Jodyn Platt, Sharon L.R. Kardia, and Minakshi Raj

Subjects
medicine.medical_specialty, business.industry, Health Policy, Public health, Information sharing, 010102 general mathematics, Public relations, 01 natural sciences, Value of information, Data sharing, 03 medical and health sciences, 0302 clinical medicine, Health care, Public trust, medicine, Business, Management and Accounting (miscellaneous), 030212 general & internal medicine, 0101 mathematics, business, Psychosocial, Health care quality
Abstract

Purpose Nations such as the USA are investing in technologies such as electronic health records in order to collect, store and transfer information across boundaries of health care, public health and research. Health information brokers such as health care providers, public health departments and university researchers function as “access points” to manage relationships between the public and the health system. The relationship between the public and health information brokers is influenced by trust; and this relationship may predict the trust that the public has in the health system as a whole, which has implications for public trust in the system, and consequently, legitimacy of involved institutions, under circumstances of health information data sharing in the future. This paper aims to discuss these issues. Design/methodology/approach In this study, the authors aimed to examine characteristics of trustors (i.e. the public) that predict trust in health information brokers; and further, to identify the factors that influence trust in brokers that also predict system trust. The authors developed a survey that was administered to US respondents in 2014 using GfK’s nationally representative sample, with a final sample of 1,011 participants and conducted ordinary least squares regression for data analyses. Findings Results suggest that health care providers are the most trusted information brokers of those examined. Beliefs about medical deceptive behavior were negatively associated with trust in each of the information brokers examined; however, psychosocial factors were significantly associated with trust in brokers, suggesting that individual attitudes and beliefs are influential on trust in brokers. Positive views of information sharing and the expectation of benefits of information sharing for health outcomes and health care quality are associated with system trust. Originality/value This study suggests that demonstrating the benefits and value of information sharing could be beneficial for building public trust in the health system; however, trust in brokers of information are variable across the public; that is, knowledge, attitudes and beliefs are associated with the level of trust different individuals have in various health information brokers – suggesting that the need for a personalized approach to building trust.

Published
2019

40. Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration

Author

Sina A. Gharib, Kenneth Rice, Donna K. Arnett, Tõnu Esko, Annemarie I. Luik, Niki Dimou, Dabeeru C. Rao, Pamela J. Schreiner, Melissa A. Richard, Reedik Mägi, Nicholette D. Palmer, Stefan Weiss, Han Chen, Solomon K. Musani, W. James Gauderman, Christian Gieger, Kari E. North, Salman M. Tajuddin, Diana van Heemst, Rainer Rauramaa, Stephen B. Kritchevsky, Henry Völzke, Minjung Kho, Michele K. Evans, Ruth J. F. Loos, Correa Adolfo, Pedro Marques-Vidal, Diane M. Becker, Claude Bouchard, José Haba-Rubio, Georg Homuth, Kurt Lohman, Nora Franceschini, Caizheng Yu, Peter Vollenweider, Ervin F. Fox, Thomas Meitinger, Karen Schwander, Heming Wang, Morris A. Swertz, Aldi T. Kraja, José Eduardo Krieger, Xiuqing Guo, Tangchun Wu, Raymond Noordam, Yongmei Liu, Michael R. Brown, Patrick C.N. Rensen, Annette Peters, Jingmin Liu, Tuomo Rankinen, Robert B. Wallance, Timo A. Lakka, Stephen S. Rich, Yun Ju Sung, Meian He, Till Roenneberg, Wanqing Wen, Dennis O. Mook-Kanamori, M. A. Province, Evangelos Evangelou, L. Adrienne Cupples, Maxime M Bos, Paul S. de Vries, Hans J. Grabe, Lisa R. Yanek, Jiwon Lee, Mario Sims, Bruce M. Psaty, Treva Rice, Tanika N. Kelly, Brenda W.J.H. Penninx, Brigitte Kühnel, Maria E. Graff, Alexandre C. Pereira, Daniel J. Gottlieb, Charles N. Rotimi, Lynne E. Wagenknecht, Ashley van der Spek, Lisa W. Martin, Jeffrey R. O'Connell, Changwei Li, James E. Hixson, Chuan Gao, Alisa K. Manning, Sharon L.R. Kardia, Stella Aslibekyan, Andres Metspalu, Sami Heikkinen, Maris Alver, Xiao-Ou Shu, Amy R. Bentley, Susan Redline, Konstantin Strauch, Tamara B. Harris, Yuri Milaneschi, L.F. Bielak, Marjan Ilkov, Myriam Fornage, Ilja M. Nolte, André G. Uitterlinden, Dina Vojinovic, Hugues Aschard, Paul Elliott, Kent D. Taylor, Najaf Amin, James M. Shikany, Yong-Bing Xiang, Jerome I. Rotter, Vilmundur Gudnason, Cornelia M. van Duijn, Ko Willems van Dijk, Andrea R. V. R. Horimoto, Jonathan Marten, Olli T. Raitakari, Vincent Laville, Pirjo Komulainen, Zhe Wang, Traci M. Bartz, Mary F. Feitosa, Mike A. Nalls, Eric Boerwinkle, Alanna C. Morrison, Melanie Waldenberger, Alexander P. Reiner, Christie M. Ballantyne, Wei Zheng, Raphael Heinzer, M. Arfan Ikram, Colleen M. Sitlani, Lisa de las Fuentes, Patricia B. Munroe, Patricia A. Peyser, Brian E. Cade, Tamar Sofer, Xiaofeng Zhu, Nienke R. Biermasz, Harold Snieder, Elise Lim, Tuomas O. Kilpeläinen, Ching-Ti Liu, Terho Lehtimäki, Thomas W. Winkler, Leo-Pekka Lyytikäinen, Gudny Eiriksdottir, Stephen Sidney, Alan B. Zonderman, Charles Kooperberg, Leiden University Medical Center (LUMC), Universiteit Leiden, Brigham & Women’s Hospital [Boston] (BWH), Harvard Medical School [Boston] (HMS), Universität Regensburg (UR), National Institutes of Health [Bethesda] (NIH), University of Copenhagen = Københavns Universitet (UCPH), Icahn School of Medicine at Mount Sinai [New York] (MSSM), The University of Texas Health Science Center at Houston (UTHealth), Washington University School of Medicine in St. Louis, Washington University in Saint Louis (WUSTL), Massachusetts General Hospital [Boston], Harvard T.H. Chan School of Public Health, Centre de Bioinformatique, Biostatistique et Biologie Intégrative (C3BI), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC), University of Mississippi Medical Center (UMMC), Erasmus University Medical Center [Rotterdam] (Erasmus MC), University of Alabama at Birmingham [ Birmingham] (UAB), University of Washington [Seattle], Universidade de São Paulo Medical School (FMUSP), Icelandic Heart Association [Kopavogur, Iceland] (IHA), University of Michigan [Ann Arbor], University of Michigan System, University of Georgia [USA], School of Public Health [Boston], Boston University [Boston] (BU), Wake Forest University, Pennington Biomedical Research Center, Louisiana State University (LSU), University of Edinburgh, University of Tartu, Imperial College London, University of Ioannina, Huazhong University of Science and Technology [Wuhan] (HUST), Helmholtz Zentrum München = German Research Center for Environmental Health, Fimlab Laboratories [Tampere, Finland], University of Tampere [Finland], Lausanne University Hospital, University of Groningen [Groningen], This project was supported by a grant from the US National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (R01HL118305). This research was supported in part by the Intramural Research Program of the National Human Genome Research Institute, National Institutes of Health. Tuomas O. Kilpeläinen was supported by the Danish Council for Independent Research (DFF–6110-00183) and the Novo Nordisk Foundation (NNF18CC0034900, NNF17OC0026848 and NNF15CC0018486). Diana van Heemst was supported by the European Commission funded project HUMAN (Health-2013-INNOVATION-1-602757). Susan Redline was supported in part by NIH R35HL135818 and HL11338., European Project: 602757,EC:FP7:HEALTH,FP7-HEALTH-2013-INNOVATION-1,HUMAN(2013), Epidemiology, Radiology & Nuclear Medicine, Internal Medicine, Life Course Epidemiology (LCE), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Psychiatry, APH - Mental Health, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Digital Health, University of Copenhagen = Københavns Universitet (KU), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Helmholtz-Zentrum München (HZM), Van Duijn, CM, Wang, Heming [0000-0002-1486-7495], Bentley, Amy R [0000-0002-0827-9101], Schwander, Karen [0000-0002-0193-4134], Manning, Alisa [0000-0003-0247-902X], Aschard, Hugues [0000-0002-7554-6783], Richard, Melissa [0000-0003-0129-9860], de Las Fuentes, Lisa [0000-0002-4689-325X], Feitosa, Mary [0000-0002-0933-2410], van der Spek, Ashley [0000-0001-7136-0159], Wang, Zhe [0000-0002-8046-4969], Marten, Jonathan [0000-0001-6916-2014], Laville, Vincent [0000-0003-4946-698X], Evangelou, Evangelos [0000-0002-5488-2999], He, Meian [0000-0002-2096-921X], Lyytikäinen, Leo-Pekka [0000-0002-7200-5455], Marques-Vidal, Pedro [0000-0002-4548-8500], Nolte, Ilja M [0000-0001-5047-4077], Palmer, Nicholette D [0000-0001-8883-2511], Snieder, Harold [0000-0003-1949-2298], Weiss, Stefan [0000-0002-3553-4315], Yanek, Lisa R [0000-0001-7117-1075], Adolfo, Correa [0000-0002-9501-600X], Dimou, Niki [0000-0003-1678-9328], Heikkinen, Sami [0000-0002-6083-2402], Ikram, M Arfan [0000-0003-0372-8585], Krieger, Jose E [0000-0001-5464-1792], Lee, Jiwon [0000-0002-4079-7494], Liu, Jingmin [0000-0003-0001-6013], Martin, Lisa W [0000-0003-4352-0914], Metspalu, Andres [0000-0002-3718-796X], Rensen, Patrick CN [0000-0002-8455-4988], Rich, Stephen S [0000-0003-3872-7793], Rotter, Jerome I [0000-0001-7191-1723], Sofer, Tamar [0000-0001-8520-8860], Taylor, Kent D [0000-0002-2756-4370], Uitterlinden, André G [0000-0002-7276-3387], van Dijk, Ko Willems [0000-0002-2172-7394], Elliott, Paul [0000-0002-7511-5684], Esko, Tõnu [0000-0003-1982-6569], Grabe, Hans J [0000-0003-3684-4208], Zheng, Wei [0000-0003-1226-070X], Bouchard, Claude [0000-0002-0048-491X], Gudnason, Vilmundur [0000-0001-5696-0084], Loos, Ruth JF [0000-0002-8532-5087], Cupples, L Adrienne [0000-0003-0273-7965], Munroe, Patricia B [0000-0002-4176-2947], Liu, Ching-Ti [0000-0002-0703-0742], Apollo - University of Cambridge Repository, Læknadeild (HÍ), Faculty of Medicine (UI), Heilbrigðisvísindasvið (HÍ), School of Health Sciences (UI), Háskóli Íslands, University of Iceland, Home Office, Imperial College Healthcare NHS Trust- BRC Funding, Medical Research Council (MRC), and UK DRI Ltd

Subjects
Male, 0301 basic medicine, Epidemiology, General Physics and Astronomy, Genome-wide association study, Genome-wide association studies, Svefnrannsóknir, 0302 clinical medicine, MESH: Aged, 80 and over, Polymorphism (computer science), lcsh:Science, MESH: Phylogeny, Phylogeny, Aged, 80 and over, Genetics, MESH: Aged, [STAT.AP]Statistics [stat]/Applications [stat.AP], Multidisciplinary, MESH: Middle Aged, medicine.diagnostic_test, MESH: Polymorphism, Single Nucleotide, Chromosome Mapping, Middle Aged, Explained variation, Lipids, Sleep in non-human animals, Blóðfita, ddc, 3. Good health, MESH: Young Adult, Female, lipids (amino acids, peptides, and proteins), Erfðarannsóknir, [STAT.ME]Statistics [stat]/Methodology [stat.ME], Adult, Adolescent, MESH: Sleep, Science, Biology, Polymorphism, Single Nucleotide, MESH: Genetic Loci, Article, General Biochemistry, Genetics and Molecular Biology, Young Adult, 03 medical and health sciences, Phylogenetics, Svefn, medicine, Humans, SNP, Dyslipidaemias, Aged, MESH: Adolescent, MESH: Humans, Faraldsfræði, PCSK9, MESH: Adult, General Chemistry, MESH: Lipids, MESH: Male, 030104 developmental biology, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, Genetic Loci, lcsh:Q, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Sleep, Lipid profile, MESH: Chromosome Mapping, MESH: Female, 030217 neurology & neurosurgery
Abstract

Publisher's version (útgefin grein)., Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles., This project was supported by a grant from the US National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (R01HL118305). This research was supported in part by the Intramural Research Program of the National Human Genome Research Institute, National Institutes of Health. Tuomas O. Kilpeläinen was supported by the Danish Council for Independent Research (DFF–6110-00183) and the Novo Nordisk Foundation (NNF18CC0034900, NNF17OC0026848 and NNF15CC0018486). Diana van Heemst was supported by the European Commission funded project HUMAN (Health-2013-INNOVATION-1-602757). Susan Redline was supported in part by NIH R35HL135818 and HL11338. Study-specific acknowledgements can be found in the Supplementary Notes 2 and 4. The data on coronary artery disease have been contributed by the Myocardial Infarction Genetics and CARDIoGRAM investigators, and have been downloaded from www.CARDIOGRAMPLUSC4D.ORG.

Published
2019

41. The metabolic network coherence of human transcriptomes is associated with genetic variation at the cadherin 18 locus

Author

Marc-Thorsten Hütt, Holger Prokisch, Sharon L.R. Kardia, Hansjörg Baurecht, Lude Franke, Michael Krawczak, Piotr Nyczka, Amke Caliebe, Jennifer A. Smith, Silke Szymczak, Carolin Knecht, Urmo Võsa, Konstantin Strauch, Christian Gieger, Stephan Weidinger, Annette Peters, Annique Claringbould, Sandra Freitag-Wolf, Philip Rosenstiel, Kristina Schlicht, Wei Zhao, Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), and Stem Cell Aging Leukemia and Lymphoma (SALL)

Subjects
Male, SUSCEPTIBILITY LOCI, Quantitative Trait Loci, PROTEIN, Metabolic network, Locus (genetics), Single-nucleotide polymorphism, Genome-wide association study, Computational biology, Quantitative trait locus, Biology, GENOTYPE IMPUTATION, Polymorphism, Single Nucleotide, DISEASE, Cohort Studies, 03 medical and health sciences, ADIPONECTIN, Genetic variation, Genetics, Humans, Gene Regulatory Networks, RECONSTRUCTION, GENOME-WIDE ASSOCIATION, 1000 Genomes Project, Genetics (clinical), Original Investigation, 030304 developmental biology, 0303 health sciences, IDENTIFICATION, 030305 genetics & heredity, KORA, Cadherins, Genetic architecture, Metabolism, Genetic Loci, OBESITY, Female, Transcriptome, Metabolic Networks and Pathways, Genome-Wide Association Study
Abstract

Metabolic coherence (MC) is a network-based approach to dimensionality reduction that can be used, for example, to interpret the joint expression of genes linked to human metabolism. Computationally, the derivation of ‘transcriptomic’ MC involves mapping of an individual gene expression profile onto a gene-centric network derived beforehand from a metabolic network (currently Recon2), followed by the determination of the connectivity of a particular, profile-specific subnetwork. The biological significance of MC has been exemplified previously in the context of human inflammatory bowel disease, among others, but the genetic architecture of this quantitative cellular trait is still unclear. Therefore, we performed a genome-wide association study (GWAS) of MC in the 1000 Genomes/ GEUVADIS data (n = 457) and identified a solitary genome-wide significant association with single nucleotide polymorphisms (SNPs) in the intronic region of the cadherin 18 (CDH18) gene on chromosome 5 (lead SNP: rs11744487, p = 1.2 × 10− 8). Cadherin 18 is a transmembrane protein involved in human neural development and cell-to-cell signaling. Notably, genetic variation at the CDH18 locus has been associated with metabolic syndrome-related traits before. Replication of our genome-wide significant GWAS result was successful in another population study from the Netherlands (BIOS, n = 2661; lead SNP), but failed in two additional studies (KORA, Germany, n = 711; GENOA, USA, n = 411). Besides sample size issues, we surmise that these discrepant findings may be attributable to technical differences. While 1000 Genomes/GEUVADIS and BIOS gene expression profiles were generated by RNA sequencing, the KORA and GENOA data were microarray-based. In addition to providing first evidence for a link between regional genetic variation and a metabolism-related characteristic of human transcriptomes, our findings highlight the benefit of adopting a systems biology-oriented approach to molecular data analysis. Electronic supplementary material The online version of this article (10.1007/s00439-019-01994-x) contains supplementary material, which is available to authorized users.

Published
2019

42. Using Genetic Burden Scores for Gene-by-Methylation Interaction Analysis on Metabolic Syndrome in African Americans

Author

Jennifer A. Smith, Sharon L.R. Kardia, Erin B. Ware, Michelle L. Wright, and Jacquelyn Y. Taylor

Subjects
Male, Genotype, Bioinformatics, Epigenesis, Genetic, 03 medical and health sciences, 0302 clinical medicine, Humans, Medicine, 030212 general & internal medicine, Epigenetics, Aged, 030304 developmental biology, Genetic association, Metabolic Syndrome, 0303 health sciences, Research and Theory, business.industry, Articles, DNA Methylation, Middle Aged, Omics, Black or African American, CpG site, Genetic epidemiology, DNA methylation, Multiple comparisons problem, CpG Islands, Female, business
Abstract

With the rapid advancement of omics-based research, particularly big data such as genome- and epigenome-wide association studies that include extensive environmental and clinical variables, data analytics have become increasingly complex. Researchers face significant challenges regarding how to analyze multifactorial data and make use of the findings for clinical translation. The purpose of this article is to provide a scientific exemplar for use of genetic burden scores as a data analysis method for studies with both genotype and DNA methylation data in which the goal is to evaluate associations with chronic conditions such as metabolic syndrome (MetS). This study included 739 African American men and women from the Genetic Epidemiology Network of Arteriopathy Study who met diagnostic criteria for MetS and had available genetic and epigenetic data. Genetic burden scores for evaluated genes were not significant after multiple testing corrections, but DNA methylation at 2 CpG sites (dihydroorotate dehydrogenase cg22381196 pFDR = .014; CTNNA3 cg00132141 pFDR = .043) was significantly associated with MetS after controlling for multiple comparisons. Interactions between the marginally significant CpG sites and burden scores, however, were not significant. More work is required in this area to identify intermediate biological pathways influenced by environmental, genetic, and epigenetic variation that may explain the high prevalence of MetS among African Americans. This study does serve, however, as an example of the use of the genetic burden score as an alternative data analysis approach for complex studies involving the analysis of genetic and epigenetic data simultaneously.

Published
2019

43. Genome-wide meta-analysis of macronutrient intake of 91,114 European ancestry participants from the cohorts for heart and aging research in genomic epidemiology consortium

Author

Panos Deloukas, Christina-Alexandra Schulz, Caren E. Smith, Lu Qi, Mary F. Feitosa, Melissa E. Garcia, Natalia Pervjakova, Denise K. Houston, Michael A. Province, Stavroula Kanoni, Torben Hansen, Jean Shin, Lynda M. Rose, Oscar H. Franco, Yongmei Liu, Trudy Voortman, Marie-Claude Vohl, Luigi Ferrucci, Chloé Sarnowski, Paul S. de Vries, Jose C. Florez, John C. Lieske, Louis Pérusse, Misa Graff, Jian'an Luan, Nicola M. McKeown, Felix R. Day, L. Adrienne Cupples, Qibin Qi, Frank J. A. van Rooij, Robert A. Scott, Josée Dupuis, Stephen S. Rich, Jorma Viikari, Tarunveer S. Ahluwalia, Leo-Pekka Lyytikäinen, Paul M. Ridker, Tomáš Paus, Stephen Turner, Harri Rissanen, Audrey Y. Chu, Albert Hofman, Olli T. Raitakari, Paul Knekt, Daniel I. Chasman, Nita G. Forouhi, Vera Mikkilä, Toshiko Tanaka, Mika Kähönen, George Dedoussis, Minjung Kho, Yun J. Sung, Anne E. Justice, Julius S. Ngwa, Ani Manichaikul, M. Carola Zillikens, Jordi Merino, Dena G. Hernandez, Rozenn N. Lemaitre, Tao Huang, Sharon L.R. Kardia, Jing Hua Zhao, Stefania Bandinelli, Veikko Salomaa, Arne Astrup, Wei Zhao, David S. Siscovick, John Blangero, Zdenka Pausova, Dabeeru C. Rao, Oluf Pedersen, Craig E. Pennell, Wendy H. Oddy, Jose M. Ordovas, Jessica C. Kiefte-de Jong, Marju Orho-Melander, Hassan S. Dashti, Satu Männistö, Tuomo Rankinen, Constantina Papoutsakis, Sherly X. Li, Antti Jula, Kari E. North, Thorkild I. A. Sørensen, André G. Uitterlinden, Alexis C. Frazier-Wood, Nicholas J. Wareham, Ulrika Ericson, Markus Perola, Ioanna P. Kalafati, Renée de Mutsert, Jinyan Huang, Ruifang Li-Gao, Claudia Langenberg, Mike A. Nalls, Olivia Li, Joanne E. Curran, Dennis O. Mook-Kanamori, Niina Eklund, Jerome I. Rotter, Angelo Tremblay, Claude Bouchard, Jennifer A. Smith, Terho Lehtimäki, Mary K. Wojczynski, Carol A. Wang, Epidemiology, Internal Medicine, Zhao, Jing Hua [0000-0003-4930-3582], Luan, Jian'an [0000-0003-3137-6337], Day, Felix [0000-0003-3789-7651], Langenberg, Claudia [0000-0002-5017-7344], Wareham, Nicholas [0000-0003-1422-2993], Forouhi, Nita [0000-0002-5041-248X], and Apollo - University of Cambridge Repository

Subjects
0301 basic medicine, Male, medicine.medical_specialty, Aging, Calorie, Genotype, Heart Diseases, Receptors, Retinoic Acid, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Locus (genetics), Genome-wide association study, Biology, Polymorphism, Single Nucleotide, Article, White People, Cohort Studies, 03 medical and health sciences, Cellular and Molecular Neuroscience, 0302 clinical medicine, Genetic variation, medicine, Humans, Genetic Predisposition to Disease, Obesity, Molecular Biology, Aged, 2. Zero hunger, Genetics, Family aggregation, Membrane Proteins, Genomics, Nutrients, Middle Aged, medicine.disease, 3. Good health, Fibroblast Growth Factors, Psychiatry and Mental health, 030104 developmental biology, Genetic Loci, Meta-analysis, Medical genetics, Female, Energy Intake, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Macronutrient intake, the proportion of calories consumed from carbohydrate, fat, and protein, is an important risk factor for metabolic diseases with significant familial aggregation. Previous studies have identified two genetic loci for macronutrient intake, but incomplete coverage of genetic variation and modest sample sizes have hindered the discovery of additional loci. Here, we expanded the genetic landscape of macronutrient intake, identifying 12 suggestively significant loci (P < 1 × 10(−6)) associated with intake of any macronutrient in 91,114 European ancestry participants. Four loci replicated and reached genome-wide significance in a combined meta-analysis including 123,659 European descent participants, unraveling two novel loci; a common variant in RARB locus for carbohydrate intake and a rare variant in DRAM1 locus for protein intake, and corroborating earlier FGF21 and FTO findings. In additional analysis of 144,770 participants from the UK Biobank, all identified associations from the two-stage analysis were confirmed except for DRAM1. Identified loci might have implications in brain and adipose tissue biology and have clinical impact in obesity-related phenotypes. Our findings provide new insight into biological functions related to macronutrient intake.

Published
2019

44. Multiancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions

Author

Alexandre C. Pereira, Jie Yao, Makoto Hirata, Ozren Polasek, Dragana Vuckovic, Mariaelisa Graff, Jing Hua Zhao, Michael R. Brown, Xuan Deng, Barbara V. Howard, Vilmundur Gudnason, Tuomo Rankinen, Yuan Shi, Timo A. Lakka, Ulrich Broeckel, Anuradhani Kasturiratne, Eric Boerwinkle, Charles Kooperberg, Hugues Aschard, Stephen S. Rich, Pamela J. Schreiner, Dan E. Arking, Hans J. Grabe, Ilaria Gandin, Mario Sims, Carl D. Langefeld, Yii-Der Ida Chen, Meian He, W. James Gauderman, Bruce M. Psaty, Kent D. Taylor, Tõnu Esko, Olli T. Raitakari, Saima Afaq, Maik Pietzner, Federica Laguzzi, Dennis O. Mook-Kanamori, Gregory P. Wilson, Xiuqing Guo, Jaspal S. Kooner, David R. Jacobs, Yajuan Wang, Raha Pazoki, Wei Zhao, Andres Metspalu, Mary F. Feitosa, Jost B. Jonas, Tin Aung, Tamara B. Harris, Karin Leander, Nancy L. Pedersen, Charles B. Eaton, Sharon L.R. Kardia, Bernardo L. Horta, Candace M. Kammerer, Terrence Forrester, Alexander P. Reiner, Paul W. Franks, Tanika N. Kelly, Igor Rudan, Ruben N. Eppinga, Melissa A. Richard, Colin A. McKenzie, Christine Williams, Christian Gieger, Joseph H. Lee, Brigitte Kühnel, Christopher P. Nelson, Wen Bin Wei, Antonietta Robino, Anne U. Jackson, E. Shyong Tai, Alisa K. Manning, Lisa R. Yanek, Paul Elliott, Lynne E. Wagenknecht, Ananda R. Wickremasinghe, José Eduardo Krieger, Peter S. Sever, Nora Franceschini, André G. Uitterlinden, Paul M. Ridker, Yun J. Sung, Karen L. Mohlke, Thomas H. Mosley, Nilesh J. Samani, Patricia B. Munroe, Jennifer A. Smith, John M. C. Connell, H. Janaka de Silva, Nicholas Y. Q. Tan, Jian'an Luan, Jennifer E. Huffman, Anna F. Dominiczak, Carsten Oliver Schmidt, Christie M. Ballantyne, Peter J. van der Most, Anuj Goel, Jerome I. Rotter, Amy R. Bentley, Lihua Wang, Rajkumar Dorajoo, Lenore J. Launer, Yechiel Friedlander, Mickaël Canouil, Traci M. Bartz, Thomas Meitinger, Robert A. Scott, Mike A. Nalls, Xueling Sim, Sarah E. Harris, Michael A. Province, Chew-Kiat Heng, Zhe Wang, Norihiro Kato, Evangelos Evangelou, Philippe Froguel, Virginia Fisher, Leslie J. Raffel, Renée de Mutsert, Michele K. Evans, Brenda W.J.H. Penninx, Yih Chung Tham, Tin Louie, Nana Matoba, Lawrence F. Bielak, Andrea R. V. R. Horimoto, Jingmin Liu, Lynda M. Rose, Nona Sotoodehnia, Daniel I. Chasman, Jasmin Divers, John M. Starr, Patricia A. Peyser, Ervin R. Fox, Barry I. Freedman, Megan L. Grove, Jeffrey R. O'Connell, Rob M. van Dam, Michiaki Kubo, Jessica D. Faul, Fang-Chi Hsu, Yize Li, Ilja M. Nolte, Caroline Hayward, Paolo Gasparini, Chiea Chuen Khor, Changwei Li, Xu Chen, James E. Hixson, Patrik K. E. Magnusson, John C. Chambers, Yoichiro Kamatani, Sami Heikkinen, M. Abdullah Said, Martin Farrall, Alena Stančáková, Konstantin Strauch, Albert V. Smith, Yik Ying Teo, Bamidele O. Tayo, Tamar Sofer, Caizheng Yu, Maris Alver, Oscar H. Franco, Yongmei Liu, Ioanna Ntalla, Myriam Fornage, W. Craig Johnson, Dina Vojinovic, William R. Scott, David R. Weir, Yanick Hagemeijer, Raymond Noordam, Mathilde Boissel, Cornelia M. van Duijn, Karen Schwander, Jingzhong Ding, James Scott, Diana van Heemst, Ching-Yu Cheng, Woon-Puay Koh, Jianjun Liu, Kenneth J. Mukamal, Blair H. Smith, Claude Bouchard, Claudia Langenberg, Jingjing Liang, Wei Zheng, Najaf Amin, Ulf de Faire, Bing Yu, Archie Campbell, Kari E. North, Salman M. Tajuddin, Fernando Pires Hartwig, Steve B. Kritchevsky, Tibor V. Varga, Pirjo Komulainen, Hugh Watkins, Johanna Kuusisto, Kurt Lohman, Rozenn N. Lemaitre, Ani Manichaikul, Dabeeru C. Rao, Kenneth Rice, Weihua Zhang, Franco Giulianini, Reedik Mägi, Solomon K. Musani, Wanqing Wen, Nicholas J. Wareham, Charles N. Rotimi, Marzyeh Amini, Rainer Rauramaa, Nicholette D. Palmer, Annette Peters, Neil R Poulter, Benjamin Lehne, Matthias Nauck, Harold Snieder, Donald W. Bowden, M. Arfan Ikram, Lisa de las Fuentes, C. Charles Gu, Xiaofeng Zhu, Markku Laakso, Tuomas O. Kilpeläinen, Ching-Ti Liu, Michael Boehnke, Jin-Fang Chai, Lili Milani, L. Adrienne Cupples, Yuri Milaneschi, Kiang Liu, Stephen Sidney, Alan B. Zonderman, Thomas W. Winkler, Ian J. Deary, Fumihiko Takeuchi, Mary K. Wojczynski, Pim van der Harst, Leo-Pekka Lyytikäinen, Jennifer G. Robinson, Chuan Gao, Xiao-Ou Shu, Diane M. Becker, Mohsen Ghanbari, Alanna C. Morrison, Jian-Min Yuan, Tomohiro Katsuya, Ivana Kolcic, Melanie Waldenberger, Terho Lehtimäki, Heikki A. Koistinen, Erin B. Ware, Ya Xing Wang, Marie Loh, Treva Rice, Qing Duan, Aldi T. Kraja, Sabanayagam Charumathi, Tien Yin Wong, Paul S. de Vries, Yujie Wang, Muhammad Riaz, Home Office, Action on Hearing Loss, Imperial College Healthcare NHS Trust- BRC Funding, British Heart Foundation, Medical Research Council (MRC), Wellcome Trust, National Institute for Health Research, Luan, Jian'an [0000-0003-3137-6337], Pietzner, Maik [0000-0003-3437-9963], Zhao, Jing Hua [0000-0003-4930-3582], Langenberg, Claudia [0000-0002-5017-7344], Wareham, Nicholas [0000-0003-1422-2993], Apollo - University of Cambridge Repository, APH - Mental Health, Psychiatry, APH - Digital Health, The University of Texas Health Science Center at Houston (UTHealth), National Institutes of Health [Bethesda] (NIH), Washington University in Saint Louis (WUSTL), University of Regensburg, Queen Mary University of London (QMUL), Washington University School of Medicine in St. Louis, Harbor UCLA Medical Center [Torrance, Ca.], University of North Carolina at Chapel Hill (UNC), Singapore National Eye Centre and Duke-NUS [Singapore], Singapore Eye Research Institute [Singapore] (SERI), National University of Singapore (NUS), Erasmus University Medical Center [Rotterdam] (Erasmus MC), Département de Biologie Computationnelle - Department of Computational Biology, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), University Management, Department of Medicine, University of Helsinki, Endokrinologian yksikkö, HUS Abdominal Center, Lifelines Cohort, Groningen, The Netherlands (Lifelines Cohort Study), Epidemiology, Neurology, Radiology & Nuclear Medicine, Internal Medicine, Life Course Epidemiology (LCE), Cardiovascular Centre (CVC), de Vries, Paul S, Brown, Michael R, Bentley, Amy R, Sung, Yun J, Winkler, Thomas W, Ntalla, Ioanna, Schwander, Karen, Kraja, Aldi T, Guo, Xiuqing, Franceschini, Nora, Cheng, Ching-Yu, Sim, Xueling, Vojinovic, Dina, Huffman, Jennifer E, Musani, Solomon K, Li, Changwei, Feitosa, Mary F, Richard, Melissa A, Noordam, Raymond, Aschard, Hugue, Bartz, Traci M, Bielak, Lawrence F, Deng, Xuan, Dorajoo, Rajkumar, Lohman, Kurt K, Manning, Alisa K, Rankinen, Tuomo, Smith, Albert V, Tajuddin, Salman M, Evangelou, Evangelo, Graff, Mariaelisa, Alver, Mari, Boissel, Mathilde, Chai, Jin Fang, Chen, Xu, Divers, Jasmin, Gandin, Ilaria, Gao, Chuan, Goel, Anuj, Hagemeijer, Yanick, Harris, Sarah E, Hartwig, Fernando P, He, Meian, Horimoto, Andrea R V R, Hsu, Fang-Chi, Jackson, Anne U, Kasturiratne, Anuradhani, Komulainen, Pirjo, Kühnel, Brigitte, Laguzzi, Federica, Lee, Joseph H, Luan, Jian'An, Lyytikäinen, Leo-Pekka, Matoba, Nana, Nolte, Ilja M, Pietzner, Maik, Riaz, Muhammad, Said, M Abdullah, Scott, Robert A, Sofer, Tamar, Stancáková, Alena, Takeuchi, Fumihiko, Tayo, Bamidele O, van der Most, Peter J, Varga, Tibor V, Wang, Yajuan, Ware, Erin B, Wen, Wanqing, Yanek, Lisa R, Zhang, Weihua, Zhao, Jing Hua, Afaq, Saima, Amin, Najaf, Amini, Marzyeh, Arking, Dan E, Aung, Tin, Ballantyne, Christie, Boerwinkle, Eric, Broeckel, Ulrich, Campbell, Archie, Canouil, Mickaël, Charumathi, Sabanayagam, Chen, Yii-Der Ida, Connell, John M, de Faire, Ulf, de Las Fuentes, Lisa, de Mutsert, Renée, de Silva, H Janaka, Ding, Jingzhong, Dominiczak, Anna F, Duan, Qing, Eaton, Charles B, Eppinga, Ruben N, Faul, Jessica D, Fisher, Virginia, Forrester, Terrence, Franco, Oscar H, Friedlander, Yechiel, Ghanbari, Mohsen, Giulianini, Franco, Grabe, Hans J, Grove, Megan L, Gu, C Charle, Harris, Tamara B, Heikkinen, Sami, Heng, Chew-Kiat, Hirata, Makoto, Hixson, James E, Howard, Barbara V, Ikram, M Arfan, Jacobs, David R, Johnson, Craig, Jonas, Jost Bruno, Kammerer, Candace M, Katsuya, Tomohiro, Khor, Chiea Chuen, Kilpeläinen, Tuomas O, Koh, Woon-Puay, Koistinen, Heikki A, Kolcic, Ivana, Kooperberg, Charle, Krieger, Jose E, Kritchevsky, Steve B, Kubo, Michiaki, Kuusisto, Johanna, Lakka, Timo A, Langefeld, Carl D, Langenberg, Claudia, Launer, Lenore J, Lehne, Benjamin, Lemaitre, Rozenn N, Li, Yize, Liang, Jingjing, Liu, Jianjun, Liu, Kiang, Loh, Marie, Louie, Tin, Mägi, Reedik, Manichaikul, Ani W, Mckenzie, Colin A, Meitinger, Thoma, Metspalu, Andre, Milaneschi, Yuri, Milani, Lili, Mohlke, Karen L, Mosley, Thomas H, Mukamal, Kenneth J, Nalls, Mike A, Nauck, Matthia, Nelson, Christopher P, Sotoodehnia, Nona, O'Connell, Jeff R, Palmer, Nicholette D, Pazoki, Raha, Pedersen, Nancy L, Peters, Annette, Peyser, Patricia A, Polasek, Ozren, Poulter, Neil, Raffel, Leslie J, Raitakari, Olli T, Reiner, Alex P, Rice, Treva K, Rich, Stephen S, Robino, Antonietta, Robinson, Jennifer G, Rose, Lynda M, Rudan, Igor, Schmidt, Carsten O, Schreiner, Pamela J, Scott, William R, Sever, Peter, Shi, Yuan, Sidney, Stephen, Sims, Mario, Smith, Blair H, Smith, Jennifer A, Snieder, Harold, Starr, John M, Strauch, Konstantin, Tan, Nichola, Taylor, Kent D, Teo, Yik Ying, Tham, Yih Chung, Uitterlinden, André G, van Heemst, Diana, Vuckovic, Dragana, Waldenberger, Melanie, Wang, Lihua, Wang, Yujie, Wang, Zhe, Wei, Wen Bin, Williams, Christine, Wilson, Gregory, Wojczynski, Mary K, Yao, Jie, Yu, Bing, Yu, Caizheng, Yuan, Jian-Min, Zhao, Wei, Zonderman, Alan B, Becker, Diane M, Boehnke, Michael, Bowden, Donald W, Chambers, John C, Deary, Ian J, Esko, Tõnu, Farrall, Martin, Franks, Paul W, Freedman, Barry I, Froguel, Philippe, Gasparini, Paolo, Gieger, Christian, Horta, Bernardo L, Kamatani, Yoichiro, Kato, Norihiro, Kooner, Jaspal S, Laakso, Markku, Leander, Karin, Lehtimäki, Terho, Magnusson, Patrik K E, Penninx, Brenda, Pereira, Alexandre C, Rauramaa, Rainer, Samani, Nilesh J, Scott, Jame, Shu, Xiao-Ou, van der Harst, Pim, Wagenknecht, Lynne E, Wang, Ya Xing, Wareham, Nicholas J, Watkins, Hugh, Weir, David R, Wickremasinghe, Ananda R, Zheng, Wei, Elliott, Paul, North, Kari E, Bouchard, Claude, Evans, Michele K, Gudnason, Vilmundur, Liu, Ching-Ti, Liu, Yongmei, Psaty, Bruce M, Ridker, Paul M, van Dam, Rob M, Kardia, Sharon L R, Zhu, Xiaofeng, Rotimi, Charles N, Mook-Kanamori, Dennis O, Fornage, Myriam, Kelly, Tanika N, Fox, Ervin R, Hayward, Caroline, van Duijn, Cornelia M, Tai, E Shyong, Wong, Tien Yin, Liu, Jingmin, Rotter, Jerome I, Gauderman, W Jame, Province, Michael A, Munroe, Patricia B, Rice, Kenneth, Chasman, Daniel I, Cupples, L Adrienne, Rao, Dabeeru C, Morrison, Alanna C, and Academic Medical Center

Subjects
Male, Epidemiology, Genome-wide association study, Cardiovascular, MESH: Genotype, Substance Misuse, Alcohol Use and Health, 0302 clinical medicine, Aetiology, triglycerides, 11 Medical and Health Sciences, Public, Environmental & Occupational Health, [STAT.AP]Statistics [stat]/Applications [stat.AP], MESH: Middle Aged, MESH: Life Style, genome wide, gene-alcohol interaction, lipid levels, Lipid Measurement, Lifelines Cohort, DENSITY-LIPOPROTEIN CHOLESTEROL, MESH: Young Adult, 030220 oncology & carcinogenesis, Kexin, LOW-FREQUENCY, MESH: Cholesterol, HDL, MESH: Cholesterol, LDL, MESH: Triglycerides, HDL, Alcohol Drinking, Genotype, alcohol consumption, MESH: Phenotype, LDL, lipids, 03 medical and health sciences, Genetics, Humans, Life Style, METAANALYSIS, 01 Mathematical Sciences, Aged, MESH: Adolescent, HDL CHOLESTEROL, MESH: Humans, Science & Technology, Cholesterol, APOBEC1, Lifelines Cohort, Groningen, The Netherlands (Lifelines Cohort Study), MESH: Vascular Endothelial Growth Factor B, Racial Groups, cholesterol, The Netherlands, MESH: Adult, CONSUMPTION, chemistry, MESH: Genome-Wide Association Study, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Lipid profile, MESH: Female, MESH: Alcohol Drinking, MESH: Continental Population Groups, Vascular Endothelial Growth Factor B, Original Contributions, Blood lipids, VEGF-B, Medical and Health Sciences, Mathematical Sciences, BLOOD-LIPIDS, chemistry.chemical_compound, 2.1 Biological and endogenous factors, 030212 general & internal medicine, MESH: Aged, medicine.diagnostic_test, PLASMA, gene-environment interactions, Middle Aged, 3142 Public health care science, environmental and occupational health, Alcoholism, Phenotype, Female, gene-lifestyle interactions, genome-wide association studies, [STAT.ME]Statistics [stat]/Methodology [stat.ME], Life Sciences & Biomedicine, Groningen, Adult, Adolescent, Biology, Young Adult, medicine, CORONARY-HEART-DISEASE, Human Genome, Cholesterol, HDL, Lipid metabolism, Cholesterol, LDL, InterAct Consortium, MESH: Lipids, MESH: Male, INDIVIDUALS, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Genome-Wide Association Study
Abstract

© The Author(s) 2019. A person's lipid profile is influenced by genetic variants and alcohol consumption, but the contribution of interactions between these exposures has not been studied. We therefore incorporated gene-Alcohol interactions into a multiancestry genome-wide association study of levels of high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. We included 45 studies in stage 1 (genome-wide discovery) and 66 studies in stage 2 (focused follow-up), for a total of 394,584 individuals from 5 ancestry groups. Analyses covered the period July 2014-November 2017. Genetic main effects and interaction effects were jointly assessed by means of a 2- degrees-of-freedom (df) test, and a 1-df test was used to assess the interaction effects alone. Variants at 495 loci were at least suggestively associated (P < 1 × 10?6) with lipid levels in stage 1 and were evaluated in stage 2, followed by combined analyses of stage 1 and stage 2. In the combined analysis of stages 1 and 2, a total of 147 independent loci were associated with lipid levels at P < 5 × 10?8 using 2-df tests, of which 18 were novel. No genome-wide-significant associations were found testing the interaction effect alone. The novel loci included several genes (proprotein convertase subtilisin/kexin type 5 (PCSK5), vascular endothelial growth factor B (VEGFB), and apolipoprotein B mRNA editing enzyme, catalytic polypeptide 1 (APOBEC1) complementation factor (A1CF)) that have a putative role in lipid metabolism on the basis of existing evidence from cellular and experimental models. National Heart, Lung, and Blood Institute; American Heart Association Grant

Published
2019

45. A Peripheral Blood DNA Methylation Signature of Hepatic Fat Reveals a Potential Causal Pathway for Nonalcoholic Fatty Liver Disease

Author

Oscar H. Franco, Yongmei Liu, Patricia A. Peyser, Lawrence F. Bielak, Wei Zhao, Jingzhong Ding, Ci Song, Sharon L.R. Kardia, Frank B. Hu, Liming Liang, Yinan Zheng, Taulant Muka, Donald M. Lloyd-Jones, J. Jeffrey Carr, Lisa B. VanWagner, Chunyu Liu, Jennifer A. Smith, Michael M. Mendelson, Tianxiao Huan, Jiantao Ma, Roby Joehanes, Hongyan Ning, Rachel Hennein, Scott M. Ratliff, Lindsay M. Reynolds, Abbas Dehghan, Jana Nano, Lifang Hou, Philip Greenland, Elizabeth K. Speliotes, Mohsen Ghanbari, Daniel Levy, Michelle T. Long, Alice H. Lichtenstein, Louise J. M. Alferink, Sarwa Darwish Murad, Joyce B. J. van Meurs, Epidemiology, Internal Medicine, and Gastroenterology & Hepatology

Subjects
Male, 0301 basic medicine, medicine.medical_specialty, Endocrinology, Diabetes and Metabolism, Population, Lipopolysaccharide Receptors, 030209 endocrinology & metabolism, Type 2 diabetes, Fats, 03 medical and health sciences, 0302 clinical medicine, Non-alcoholic Fatty Liver Disease, Risk Factors, Internal medicine, Diabetes mellitus, Mendelian randomization, Nonalcoholic fatty liver disease, Internal Medicine, medicine, Humans, Risk factor, education, education.field_of_study, business.industry, Genetics/Genomes/Proteomics/Metabolomics, DNA Methylation, Middle Aged, medicine.disease, 030104 developmental biology, Endocrinology, Diabetes Mellitus, Type 2, Liver, CpG site, DNA methylation, Female, business, Biomarkers
Abstract

Nonalcoholic fatty liver disease (NAFLD) is a risk factor for type 2 diabetes (T2D). We aimed to identify the peripheral blood DNA methylation signature of hepatic fat. We conducted epigenome-wide association studies of hepatic fat in 3,400 European ancestry (EA) participants and in 401 Hispanic ancestry and 724 African ancestry participants from four population-based cohort studies. Hepatic fat was measured using computed tomography or ultrasound imaging and DNA methylation was assessed at >400,000 cytosine-guanine dinucleotides (CpGs) in whole blood or CD14+ monocytes using a commercial array. We identified 22 CpGs associated with hepatic fat in EA participants at a false discovery rate

Published
2019

46. Genetic variants predictive of reproductive aging are associated with vasomotor symptoms in a multiracial/ethnic cohort

Author

Edward A. Ruiz-Narváez, Michelle M Hood, Carolyn J. Crandall, Miao Yu, Sharon L.R. Kardia, Patricia A. Peyser, Rebecca C. Thurston, Jennifer A. Smith, Wei Zhao, and Siobán D. Harlow

Subjects
Aging, Vasomotor, business.industry, Applied Mathematics, General Mathematics, Ethnic group, Obstetrics and Gynecology, Single-nucleotide polymorphism, Odds ratio, medicine.disease, Article, Menopause, Vasomotor System, Cohort, Hot Flashes, Menarche, Medicine, Humans, Women's Health, Female, business, Demography, Genetic association, Genome-Wide Association Study
Abstract

Objective Vasomotor symptoms (VMS), hot flashes, and night sweats are cardinal symptoms of the menopausal transition. Little is known about genetic influences on VMS. This study evaluated whether previously identified genetic factors predictive of VMS, age at menarche, and age at menopause were associated with VMS in a multiracial/ethnic cohort. Methods For 702 White, 306 Black, 126 Chinese, and 129 Japanese women from the Study of Women's Health Across the Nation (SWAN) Genomic Substudy, we created polygenic risk scores (PRSs) from genome-wide association studies of VMS and ages at menarche and menopause. PRSs and single nucleotide polymorphisms (SNPs) from a previously identified VMS locus (tachykinin receptor 3 [TACR3]) were evaluated for associations with frequent VMS (VMS ≥6 days in the past 2 weeks at any visit) and with VMS trajectories (persistently low, early onset, final menstrual period onset, persistently high). Results The C-allele of rs74827081 in TACR3 was associated with reduced likelihood of frequent VMS in White women (odds ratio [OR] = 0.49 [95% CI, 0.29-0.83]). With higher menarche PRS (later menarche), Black women were less likely (OR = 0.55 [95% CI, 0.38-0.78]) to report frequent VMS. With higher PRS for age at menarche, Black women were also less likely to have a persistently high VMS trajectory (OR = 0.55 [95% CI, 0.34-0.91]), whereas White women (OR = 0.75 [95% CI, 0.58-0.98]) were less likely to have a final menstrual period onset trajectory (vs persistently low). Chinese women with higher menopause PRS were more likely to have frequent VMS (OR = 2.29 [95% CI, 1.39-3.78]). Associations were substantively similar after excluding rs74827081 C-allele carriers. Conclusions Genetic factors predictive of reproductive aging are also associated with VMS, suggesting that VMS have a polygenic architecture. Further study in this area may help to identify new targets for novel VMS therapies. Video Summary:http://links.lww.com/MENO/A761.

Published
2021

47. Publisher Correction: A meta-analysis of genome-wide association studies identifies multiple longevity genes

Author

Sarah Cubaynes, Joanne M. Murabito, Eric S. Orwoll, Iris E. Jansen, Joanna Collerton, Vilmundur Gudnason, Mikko Hurme, Paola Sebastiani, Carol Jagger, Carmen Martin-Ruiz, Douglas P. Kiel, Henne Holstege, Kenny Ye, Pilar Galan, Wolfgang Lieb, Diana van Heemst, Janina Dose, Wanlin Zheng, Ilkka Seppälä, Ashley van der Spek, Jessica D. Faul, Nir Barzilai, David R. Weir, James W. Vaupel, Wiesje M. van der Flier, Dan E. Arking, Terho Lehtimäki, Marja Jylhä, Thomas B. L. Kirkwood, Andrew Kingston, Marcel J. T. Reinders, Jean-François Deleuze, Cornelia M. van Duijn, Hélène Blanché, Anne B. Newman, Chao Nie, Elizabeth J. Becker, Daniel S. Evans, P. Eline Slagboom, Marianne Nygaard, Lene Christiansen, Jean Marie Robine, Junxia Min, Almut Nebel, Tamara B. Harris, Lenore J. Launer, Mary K. Wojczynski, Ellen A. Nohr, Alice M. Arnold, Olli T. Raitakari, Birgit Debrabant, Jerome I. Rotter, Thorkild I. A. Sørensen, André G. Uitterlinden, Steven R. Cummings, Kristin L. Ayers, Jennifer A. Smith, Joris Deelen, Yi Zeng, Chloé Sarnowski, Heather J. Cordell, Karen Davies, Kent D. Taylor, Mika Kähönen, Albert V. Smith, Najaf Amin, Rachel Duncan, Michael A. Province, Leo-Pekka Lyytikäinen, Kathryn L. Lunetta, Kaare Christensen, Sharon L.R. Kardia, Thomas T. Perls, Erin B. Ware, Martijn Huisman, Mary L. Biggs, Marian Beekman, Sven J. van der Lee, David Karasik, Niccolò Tesi, Xiaomin Liu, Gil Atzmon, Claudio Franceschi, and Bruce M. Psaty

Subjects
Apolipoprotein E2, Science, Apolipoprotein E4, Longevity, MEDLINE, General Physics and Astronomy, Genome-wide association study, Diseases, Computational biology, Biology, Longevity genes, Genome-wide association studies, GeneralLiterature_MISCELLANEOUS, General Biochemistry, Genetics and Molecular Biology, SNP, Humans, Endoplasmic Reticulum Chaperone BiP, Heat-Shock Proteins, Multidisciplinary, Published Erratum, General Chemistry, Publisher Correction, Ageing, ComputingMethodologies_PATTERNRECOGNITION, Risk factors, Meta-analysis, ComputingMethodologies_DOCUMENTANDTEXTPROCESSING, Genome-Wide Association Study
Abstract

Human longevity is heritable, but genome-wide association (GWA) studies have had limited success. Here, we perform two meta-analyses of GWA studies of a rigorous longevity phenotype definition including 11,262/3484 cases surviving at or beyond the age corresponding to the 90th/99th survival percentile, respectively, and 25,483 controls whose age at death or at last contact was at or below the age corresponding to the 60th survival percentile. Consistent with previous reports, rs429358 (apolipoprotein E (ApoE) ε4) is associated with lower odds of surviving to the 90th and 99th percentile age, while rs7412 (ApoE ε2) shows the opposite. Moreover, rs7676745, located near GPR78, associates with lower odds of surviving to the 90th percentile age. Gene-level association analysis reveals a role for tissue-specific expression of multiple genes in longevity. Finally, genetic correlation of the longevity GWA results with that of several disease-related phenotypes points to a shared genetic architecture between health and longevity.

Published
2021

48. The trans-ancestral genomic architecture of glycemic traits

Author

Albertine J. Oldehinkel, Wieland Kiess, Xueling Sim, Norihiro Kato, Philippe Froguel, Astrid van Hylckama Vlieg, Josée Dupuis, Nanette R. Lee, Symen Ligthart, Harry Campbell, Marta E. Alarcón-Riquelme, P. Eline Slagboom, Massimo Mangino, Tian Xie, Niek Verweij, James B. Meigs, Chaolong Wang, Michael Y. Tsai, Erik Ingelsson, Colin N. A. Palmer, Erik B. van den Akker, Fumihiko Matsuda, Rainer Rauramaa, Yi-Cheng Chang, Lars Lind, Stefan R. Bornstein, Mandy Vogel, Sven Bergmann, Ya X. Wang, Ching-Ti Liu, Annette Schürmann, Michael Boehnke, David J. Porteous, Kazuya Setoh, Qibin Qi, Ayse Demirkan, Francesco Cucca, Allan Linneberg, Claire J. Steves, Jun Liu, Leslie A. Lange, Noël P. Burtt, Diana Kuh, Cassandra N. Spracklen, Ken K. Ong, Charumathi Sabanayagam, Jost B. Jonas, Ele Ferrannini, Lawrence J. Beilin, Qing Duan, Blair H. Smith, Isobel D. Stewart, Alexander P. Reiner, Simon P. Mooijaart, Tim D. Spector, Paul W. Franks, E. Shyong Tai, Mark I. McCarthy, Anna L. Gloyn, D.I. Boomsma, Dennis Raven, Nicholas J. Timpson, Rona J. Strawbridge, George Dedoussis, Susan Redline, Jaeyoung Hong, Harald Grallert, Jagadish Vangipurapu, Rico Rueedi, Diane M. Becker, Marian Beekman, Claudia P. Cabrera, Johannes Waage, Jin Fang Chai, Yii-Der Ida Chen, Graciela E. Delgado, Thibaud S. Boutin, Yang Hai, Yoriko Heianza, Wei Zhao, Andres Metspalu, Tien Yin Wong, Mila Desi Anasanti, Inger Njølstad, Hans Bisgaard, Valeriya Lyssenko, Denis Rybin, Wanqing Wen, Torben Hansen, James F. Wilson, Sameline Grimsgaard, Annette Peters, Michele K. Evans, Damia Noce, Sarah C. Nelson, May E. Montasser, Nan Wang, Geltrude Mingrone, Gudny Eiriksdottir, Nicholas J. Wareham, Fouad Kandeel, Linda S. Adair, Kelvin Lam, Jaana Lindström, Eco J. C. de Geus, Debbie A Lawlor, Sara M. Willems, Xu Lin, Harold Snieder, Matt J. Neville, Naveed Sattar, Chelsea K. Raulerson, Paul M. Ridker, Jer-Yuarn Wu, Weihua Zhang, H. Janaka de Silva, Jana V. van Vliet-Ostaptchouk, Elena Tremoli, Toru Nabika, Jing Hua Zhao, Vilmundur Gudnason, Tao Huang, Robert C. Kaplan, Sohee Han, Mohammad Hadi Zafarmand, Aaron Leong, Yen-Feng Chiu, Kumaraswamy Naidu Chitrala, Ivana Kolcic, Franco Giulianini, Tao Wang, Lu Qi, Stephan J. L. Bakker, Laura J Corbin, Zoltán Kutalik, Bruna Gigante, Willa A. Hsueh, Peter J. van der Most, Tin Louie, Yujie Wang, Stella Trompet, Fernando Rivideneira, Yasumasa Ohyagi, Lynne E. Wagenknecht, Jerry L. Nadler, Michael Stumvoll, Mark O. Goodarzi, Sahoko Ichihara, Jeffrey R. O'Connell, Tomohiro Katsuya, Giorgio Pistis, Alice Stanton, Sirkka Keinänen-Kiukaanniemi, Momoko Horikoshi, Honglan Li, Tanja G. M. Vrijkotte, Caroline Hayward, Karen L. Mohlke, Carola Marzi, Girish N. Nadkarni, Laura J. Rasmussen-Torvik, Alain G. Bertoni, Andrew R. Wood, Annique Claringbould, Mi Yeong Hwang, Hugh Watkins, Heikki A. Koistinen, Mattias Frånberg, Jani Heikkinen, Elizabeth Selvin, Donald W. Bowden, Abbas Dehghan, Christian Fuchsberger, Audrey Y. Chu, Kent D. Taylor, Katherine A. Kentistou, Johanna Kuusisto, Jingyi Tan, Huaixing Li, Eric Boerwinkle, Catharina A. Hartman, Archie Campbell, Kari E. North, Oluf Pedersen, Sölve Elmståhl, Emil V. R. Appel, Chang-Hsun Hsieh, Dennis O. Mook-Kanamori, Rob M. van Dam, Pontiano Kaleebu, Corri Black, Jennifer A. Brody, Bengt Sennblad, Shaofeng Huo, M. Larissa Avilés-Santa, Ruth J. F. Loos, Patricia B. Munroe, Chien-Hsiun Chen, Liang Sun, Zorayr Arzumanyan, Rebecca Rohde, Yasuharu Tabara, Albert V. Smith, Betina H. Thuesen, Niels Grarup, Jorgen Engmann, Tatijana Zemunik, M. Arfan Ikram, Marit E. Jørgensen, Christian Herder, Ching-Yu Cheng, Serena Sanna, Damiano Baldassarre, Tarunveer S. Ahluwalia, Mark J. Caulfield, Anne Ndungu, Carl D. Langefeld, Lisa R. Yanek, Luigi Ferrucci, Ananda R. Wickremasinghe, Raymond Noordam, Trevor A. Mori, Tom Wilsgaard, Mika Kivimäki, Rita R. Kalyani, Alan B. Zonderman, Veronique Vitart, Patricia A. Peyser, Shuiqing Lai, Richa Saxena, Li-Ching Chang, Karin Leander, Wei Huang, Peter Vollenweider, Tanya M. Teslovich, Ying Wu, Shufa Du, Brian E. Cade, Patrik K. E. Magnusson, John C. Chambers, Stephen C. J. Parker, Tamar Sofer, Winfried März, Sharon L.R. Kardia, Peter K. Joshi, Neil R. Robertson, Anny H. Xiang, Fumihiko Takeuchi, N. Amin, Jouke-Jan Hottenga, Carol A. Wang, Stefan Gustafsson, Jung Ho Gong, Penny Gordon-Larsen, Yu-Tang Gao, Abhishek Nag, Gonneke Willemsen, Michael A. Province, Aliki-Eleni Farmaki, Segun Fatumo, Antje Körner, Pim van der Harst, Marie Loh, Kei Hang Katie Chan, Gonçalo R. Abecasis, Nicholette D. Palmer, Simin Liu, Ishminder K. Kooner, Javier Gayán, Arne Astrup, Laura J. Scott, Erwin P. Bottinger, Andrew Wong, Inga Prokopenko, Ping An, Markku Laakso, Matthias Blüher, Susan R. Heckbert, Thomas A. Buchanan, Tatsuaki Matsubara, Andrew P. Morris, Brian H. Chen, Kristi Läll, Teresa Tusie, Timo A. Lakka, Jie Yao, Michael Preuss, Teemu Kuulasmaa, Carlos Lorenzo, Stephen S. Rich, Marie Lauzon, Laura M. Raffield, Pankow S. James, Takahisa Kawaguchi, Kathleen A. Ryan, Wei Zheng, Igor Rudan, Thomas Sparsø, Hugoline G. de Haan, Sandosh Padmanabhan, Richard M. Watanabe, Alicia Huerta-Chagoya, Anette P. Gjesing, Andrew A. Hicks, Richard N. Bergman, Mitsuhiro Yokota, Heather M. Stringham, Bruce M. Psaty, Jian'an Luan, Anuj Goel, Eleanor Wheeler, Masahiro Nakatochi, Young-Jin Kim, Xiao-Ou Shu, Mickaël Canouil, Robert A. Scott, Marika Kaakinen, Mari Nelis, Adolfo Correa, Jaspal S. Kooner, Michiya Igase, Anubha Mahajan, Peter E. H. Schwarz, Craig E. Pennell, Claudia Schurmann, Xiaoran Chai, Ji Chen, Lori L. Bonnycastle, Peter S. Sever, Thorkild I. A. Sørensen, André G. Uitterlinden, Ilja M. Nolte, Gaëlle Marenne, Timothy M. Frayling, Bong-Jo Kim, Kerrin S. Small, Cecilia M. Lindgren, Bernhard O. Böhm, Shih-Yi Lin, Katharina E. Schraut, Cornelia M. van Duijn, Sanghoon Moon, Mark Walker, Chiea Chuen Khor, Ruifang Li-Gao, Qiuyin Cai, Neil Schneiderman, Ko Willems van Dijk, Ozren Polasek, W. Craig Johnson, Dermot F. Reilly, Inês Barroso, Anke Tönjes, Manjinder S. Sandhu, Wen B. Wei, Jose C. Florez, Lorraine Southam, Leif Groop, Lawrence F. Bielak, Peter Kovacs, Jianjun Liu, Jouko Saramies, Helen R. Warren, Man Li, Daniel I. Chasman, Eleftheria Zeggini, Xiaoshuai Zhang, Loic Yengo, Shi Jinxiu, Jirong Long, Xiuqing Guo, Meena Kumari, Leslie J. Raffel, Jill M. Norris, Henrik Vestergaard, Jing He, Peter P. Pramstaller, Diana van Heemst, Kevin Sandow, Marjo-Ritta Jarvelin, Carlos A. Aguilar-Salinas, Peitao Wu, Hortensia Moreno-Macías, Jerome I. Rotter, Kathryn Roll, Frits R. Rosendaal, Bernardo L. Horta, Heming Wang, Fernando Pires Hartwig, Richard A. Jensen, Matti Uusitupa, Rozenn N. Lemaitre, Paul R. H. J. Timmers, Timo Saaristo, Jaakko Tuomilehto, Reedik Mägi, Debashree Ray, J. Wouter Jukema, Claudia Langenberg, Marcus E. Kleber, Francis S. Collins, Klaus Bønnelykke, Lenore J. Launer, Arushi Varshney, Anders Hamsten, European Commission, Génétique, génomique fonctionnelle et biotechnologies (UMR 1078) (GGB), Institut Brestois Santé Agro Matière (IBSAM), Université de Brest (UBO)-Université de Brest (UBO)-EFS-Institut National de la Santé et de la Recherche Médicale (INSERM), Sanger Institute, Wellcome Trust, Marenne, Gaëlle [0000-0002-4363-7170], Varshney, Arushi [0000-0001-9177-9707], Corbin, Laura J [0000-0002-4032-9500], Parker, Stephen CJ [0000-0001-8122-0117], Langenberg, Claudia [0000-0002-5017-7344], Wheeler, Eleanor [0000-0002-8616-6444], Morris, Andrew P [0000-0002-6805-6014], Barroso, Inês [0000-0001-5800-4520], Apollo - University of Cambridge Repository, Lifelines Cohort Study, Meta-Analysis of Glucose and Insulin-related Traits Consortium (MAGIC), de Haan, H.G., van den Akker, E., van der Most, P.J., de Geus, EJC, van Dam, R.M., van Heemst, D., van Hylckama Vlieg, A., van Willems van Dijk, K., de Silva, H.J., van der Harst, P., van Duijn, C., Centre of Excellence in Complex Disease Genetics, HUS Abdominal Center, Institute for Molecular Medicine Finland, Leif Groop Research Group, HUS Internal Medicine and Rehabilitation, Department of Medicine, Department of Biochemistry and Developmental Biology, Helsinki University Hospital Area, University of Helsinki, Clinicum, Department of Public Health, Biological Psychology, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, Physiology, AMS - Musculoskeletal Health, AMS - Tissue Function & Regeneration, APH - Mental Health, Nutrition and Health, APH - Methodology, Epidemiology and Data Science, ACS - Atherosclerosis & ischemic syndromes, APH - Aging & Later Life, ARD - Amsterdam Reproduction and Development, Public and occupational health, Epidemiology, Internal Medicine, Life Course Epidemiology (LCE), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Groningen Institute for Organ Transplantation (GIOT), Groningen Kidney Center (GKC), Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Center for Liver, Digestive and Metabolic Diseases (CLDM), and Cardiovascular Centre (CVC)

Subjects
Blood Glucose, Disease risk, Multifactorial Inheritance, Glycated Hemoglobin A, [SDV]Life Sciences [q-bio], Meta-Analysis of Glucose and Insulin-related Traits Consortium (MAGIC), LOCI, Genome-wide association study, Type 2 diabetes, VARIANTS, GLUCOSE, Epigenesis, Genetic, chemistry.chemical_compound, 0302 clinical medicine, Mechanisms, WIDE ASSOCIATION, genetics, Gene-expression, HEMOGLOBIN, ComputingMilieux_MISCELLANEOUS, 11 Medical and Health Sciences, GENE-EXPRESSION, Genetics, Genetics & Heredity, 0303 health sciences, INSULIN-RESISTANCE, Genome, Loci, 1184 Genetics, developmental biology, physiology, Variants, ALSPAC, Physical Chromosome Mapping, Life Sciences & Biomedicine, Human, Quantitative Trait Loci, Wide association study, Biology, Quantitative trait locus, Article, White People, diseases, MECHANISMS, Quantitative Trait, 03 medical and health sciences, Insulin resistance, Quantitative Trait, Heritable, SDG 3 - Good Health and Well-being, Genetic, Lifelines Cohort Study, Diabetes mellitus, medicine, Humans, Hemoglobin, Heritable, METAANALYSIS, Alleles, 030304 developmental biology, Genetic association, Glycemic, Glycated Hemoglobin, Science & Technology, Genome, Human, Whites, Gene Expression Profiling, DISEASE RISK, Settore MED/13 - ENDOCRINOLOGIA, Insulin-resistance, 06 Biological Sciences, medicine.disease, Glucose, chemistry, Blood Glucose/genetics, European Continental Ancestry Group/genetics, Genome-Wide Association Study, Glycated Hemoglobin A/metabolism, Multifactorial Inheritance/genetics, Quantitative Trait Loci/genetics, Glycated hemoglobin, 030217 neurology & neurosurgery, Meta analysis, Epigenesis, Developmental Biology
Abstract

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P-8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.

Published
2021

49. Epigenetic age acceleration is associated with cardiometabolic risk factors and clinical cardiovascular disease risk scores in African Americans

Author

Thomas H. Mosley, Scott M. Ratliff, Jennifer A. Smith, Patricia A. Peyser, Xiang Zhou, Lawrence F. Bielak, Farah Ammous, Wei Zhao, and Sharon L.R. Kardia

Subjects
Adult, Male, Aging, medicine.medical_specialty, Epigenetic age, Risk Assessment, White People, Epigenesis, Genetic, Insulin resistance, Internal medicine, Prevalence, Genetics, medicine, Humans, Genetic Predisposition to Disease, Molecular Biology, Genetics (clinical), Aged, Aged, 80 and over, DNA methylation, Framingham Risk Score, business.industry, Research, Incidence (epidemiology), Hazard ratio, Age Factors, Cardiometabolic Risk Factors, Middle Aged, Cardiovascular disease, medicine.disease, United States, Race Factors, Black or African American, Cross-Sectional Studies, Blood pressure, Age acceleration, Clinical risk scores, Genetic epidemiology, Cardiovascular Diseases, Cohort, Female, business, Dyslipidemia, Developmental Biology
Abstract

Background Cardiovascular disease (CVD) is the leading cause of mortality among US adults. African Americans have higher burden of CVD morbidity and mortality compared to any other racial group. Identifying biomarkers for clinical risk prediction of CVD offers an opportunity for precision prevention and earlier intervention. Results Using linear mixed models, we investigated the cross-sectional association between four measures of epigenetic age acceleration (intrinsic (IEAA), extrinsic (EEAA), PhenoAge (PhenoAA), and GrimAge (GrimAA)) and ten cardiometabolic markers of hypertension, insulin resistance, and dyslipidemia in 1,100 primarily hypertensive African Americans from sibships in the Genetic Epidemiology Network of Arteriopathy (GENOA). We then assessed the association between epigenetic age acceleration and time to self-reported incident CVD using frailty hazard models and investigated CVD risk prediction improvement compared to models with clinical risk scores (Framingham risk score (FRS) and the atherosclerotic cardiovascular disease (ASCVD) risk equation). After adjusting for sex and chronological age, increased epigenetic age acceleration was associated with higher systolic blood pressure (IEAA), higher pulse pressure (EEAA and GrimAA), higher fasting glucose (PhenoAA and GrimAA), higher fasting insulin (EEAA), lower low density cholesterol (GrimAA), and higher triglycerides (GrimAA). A five-year increase in GrimAA was associated with CVD incidence with a hazard ratio of 1.54 (95% CI 1.22–2.01) and remained significant after adjusting for CVD risk factors. The addition of GrimAA to risk score models improved model fit using likelihood ratio tests (P = 0.013 for FRS and P = 0.008 for ASCVD), but did not improve C statistics (P > 0.05). Net reclassification index (NRI) showed small but significant improvement in reassignment of risk categories with the addition of GrimAA to FRS (NRI: 0.055, 95% CI 0.040–0.071) and the ASCVD equation (NRI: 0.029, 95% CI 0.006–0.064). Conclusions Epigenetic age acceleration measures are associated with traditional CVD risk factors in an African-American cohort with a high prevalence of hypertension. GrimAA was associated with CVD incidence and slightly improved prediction of CVD events over clinical risk scores.

Published
2021

50. Within-sibship GWAS improve estimates of direct genetic effects

Author

Ailin Falkmo Hansen, Christina C. Dahm, David M. Evans, Massimo Mangino, Melissa C. Southey, Lawrence F. Bielak, Ben Michael Brumpton, Sharon L.R. Kardia, Archie Campbell, Yoonsu Cho, Tim T Morris, Patrick Turley, Jeffrey S. Reid, Laurence J. Howe, Kaare Christensen, Karri Silventoinen, Sudheer Giddaluru, John K. Hewitt, Philipp Koellinger, W. David Hill, Daniel J. Benjamin, Gibran Hemani, Margaret J. Wright, Scott D. Gordon, Elliot M. Tucker-Drob, Rosa Cheesman, Nicholas G. Martin, Robin G. Walters, Paraskevi Christofidou, Aris Baras, George Davey Smith, Matthew C. Keller, John D. Overton, Deepika R Dokuru, Jennifer A. Smith, Nancy L. Pedersen, Michel G. Nivard, Dorret I. Boomsma, Jaakko Kaprio, Humaira Rasheed, Hyeokmoon Kweon, Sara Hägg, Shona M. Kerr, John L. Hopper, Pekka Martikainen, Teemu Palviainen, Luke M. Evans, Patricia A. Peyser, Jared V. Balbona, Lucija Klaric, Tim D. Spector, Patrik K. E. Magnusson, Melinda Mills, Alexandra Havdahl, Chandra A. Reynolds, Jean-Baptiste Pingault, Zhengming Chen, Shuai Li, Harry Campbell, Travis T. Mallard, Cristen J. Willer, Yunzhang Wang, Yongkang Kim, Robert Plomin, Marianne Nygaard, Michael C. Stallings, Sarah E. Medland, Anne E. Justice, Geetha Chittoor, Debbie A Lawlor, Øyvind Næss, Liming Li, Kuang Lin, Eco J. C. de Geus, Christopher R. Bauer, Matthijs D. van der Zee, Iona Y Millwood, Caroline Hayward, Penelope A. Lind, David J. Porteous, K. Paige Harden, Meike Bartels, Neil M Davies, James F. Wilson, Bjørn Olav Åsvold, Antti Latvala, Scott M. Ratliff, and Kristian Hveem

Subjects
0303 health sciences, education.field_of_study, Assortative mating, Population, Genome-wide association study, Biology, Population stratification, 03 medical and health sciences, 0302 clinical medicine, Evolutionary biology, Genetic variation, Mendelian randomization, Human height, education, 030217 neurology & neurosurgery, 030304 developmental biology, Genetic association
Abstract

Estimates from genome-wide association studies (GWAS) represent a combination of the effect of inherited genetic variation (direct effects), demography (population stratification, assortative mating) and genetic nurture from relatives (indirect genetic effects). GWAS using family-based designs can control for demography and indirect genetic effects, but large-scale family datasets have been lacking. We combined data on 159,701 siblings from 17 cohorts to generate population (between-family) and within-sibship (within-family) estimates of genome-wide genetic associations for 25 phenotypes. We demonstrate that existing GWAS associations for height, educational attainment, smoking, depressive symptoms, age at first birth and cognitive ability overestimate direct effects. We show that estimates of SNP-heritability, genetic correlations and Mendelian randomization involving these phenotypes substantially differ when calculated using within-sibship estimates. For example, genetic correlations between educational attainment and height largely disappear. In contrast, analyses of most clinical phenotypes (e.g. LDL-cholesterol) were generally consistent between population and within-sibship models. We also report compelling evidence of polygenic adaptation on taller human height using within-sibship data. Large-scale family datasets provide new opportunities to quantify direct effects of genetic variation on human traits and diseases.

Published
2021

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