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1. Rare variant contribution to the heritability of coronary artery disease.

Author

Rocheleau, Ghislain, Clarke, Shoa, Auguste, Gaëlle, Hasbani, Natalie, Morrison, Alanna, Heath, Adam, Bielak, Lawrence, Iyer, Kruthika, Young, Erica, Stitziel, Nathan, Jun, Goo, Laurie, Cecelia, Broome, Jai, Khan, Alyna, Arnett, Donna, Becker, Lewis, Bis, Joshua, Boerwinkle, Eric, Bowden, Donald, Carson, April, Ellinor, Patrick, Fornage, Myriam, Franceschini, Nora, Freedman, Barry, Heard-Costa, Nancy, Hou, Lifang, Chen, Yii-Der, Kenny, Eimear, Kooperberg, Charles, Kral, Brian, Loos, Ruth, Lutz, Sharon, Manson, JoAnn, Martin, Lisa, Mitchell, Braxton, Nassir, Rami, Palmer, Nicholette, Post, Wendy, Preuss, Michael, Psaty, Bruce, Raffield, Laura, Regan, Elizabeth, Rich, Stephen, Smith, Jennifer, Taylor, Kent, Yanek, Lisa, Young, Kendra, Hilliard, Austin, Tcheandjieu, Catherine, Peyser, Patricia, Vasan, Ramachandran, Rotter, Jerome, Miller, Clint, Assimes, Themistocles, de Vries, Paul, and Do, Ron

Subjects
Humans, Coronary Artery Disease, Genetic Predisposition to Disease, Linkage Disequilibrium, Polymorphism, Single Nucleotide, Male, Female, Gene Frequency, Genome-Wide Association Study, White People, Case-Control Studies, Whole Genome Sequencing, Genetic Variation, Middle Aged
Abstract

Whole genome sequences (WGS) enable discovery of rare variants which may contribute to missing heritability of coronary artery disease (CAD). To measure their contribution, we apply the GREML-LDMS-I approach to WGS of 4949 cases and 17,494 controls of European ancestry from the NHLBI TOPMed program. We estimate CAD heritability at 34.3% assuming a prevalence of 8.2%. Ultra-rare (minor allele frequency ≤ 0.1%) variants with low linkage disequilibrium (LD) score contribute ~50% of the heritability. We also investigate CAD heritability enrichment using a diverse set of functional annotations: i) constraint; ii) predicted protein-altering impact; iii) cis-regulatory elements from a cell-specific chromatin atlas of the human coronary; and iv) annotation principal components representing a wide range of functional processes. We observe marked enrichment of CAD heritability for most functional annotations. These results reveal the predominant role of ultra-rare variants in low LD on the heritability of CAD. Moreover, they highlight several functional processes including cell type-specific regulatory mechanisms as key drivers of CAD genetic risk.

Published
2024

2. Whole-genome sequencing uncovers two loci for coronary artery calcification and identifies ARSE as a regulator of vascular calcification.

Author

de Vries, Paul, Conomos, Matthew, Singh, Kuldeep, Nicholson, Christopher, Jain, Deepti, Hasbani, Natalie, Jiang, Wanlin, Lee, Sujin, Cardenas, Christian, Lutz, Sharon, Wong, Doris, Guo, Xiuqing, Yao, Jie, Young, Erica, Tcheandjieu, Catherine, Hilliard, Austin, Bis, Joshua, Bielak, Lawrence, Brown, Michael, Musharoff, Shaila, Clarke, Shoa, Terry, James, Palmer, Nicholette, Yanek, Lisa, Xu, Huichun, Heard-Costa, Nancy, Wessel, Jennifer, Selvaraj, Margaret, Li, Rebecca, Sun, Xiao, Turner, Adam, Stilp, Adrienne, Khan, Alyna, Newman, Anne, Rasheed, Asif, Freedman, Barry, Kral, Brian, McHugh, Caitlin, Hodonsky, Chani, Saleheen, Danish, Herrington, David, Jacobs, David, Nickerson, Deborah, Boerwinkle, Eric, Wang, Fei, Heiss, Gerardo, Jun, Goo, Kinney, Greg, Sigurslid, Haakon, Doddapaneni, HarshaVardhan, Hall, Ira, Bensenor, Isabela, Broome, Jai, Crapo, James, Wilson, James, Smith, Jennifer, Blangero, John, Vargas, Jose, Mosquera, Jose, Smith, Joshua, Viaud-Martinez, Karine, Ryan, Kathleen, Young, Kendra, Taylor, Kent, Lange, Leslie, Emery, Leslie, Bittencourt, Marcio, Montasser, May, Yu, Miao, Mahaney, Michael, Mahamdeh, Mohammed, Fornage, Myriam, Franceschini, Nora, Lotufo, Paulo, Natarajan, Pradeep, Wong, Quenna, Mathias, Rasika, Gibbs, Richard, Do, Ron, Mehran, Roxana, Tracy, Russell, Kim, Ryan, Nelson, Sarah, Damrauer, Scott, Kardia, Sharon, Rich, Stephen, Fuster, Valentin, Napolioni, Valerio, Zhao, Wei, Tian, Wenjie, Yin, Xianyong, Min, Yuan-I, Manning, Alisa, Peloso, Gina, Kelly, Tanika, ODonnell, Christopher, Morrison, Alanna, Curran, Joanne, Zapol, Warren, and Bowden, Donald

Abstract

Coronary artery calcification (CAC) is a measure of atherosclerosis and a well-established predictor of coronary artery disease (CAD) events. Here we describe a genome-wide association study (GWAS) of CAC in 22,400 participants from multiple ancestral groups. We confirmed associations with four known loci and identified two additional loci associated with CAC (ARSE and MMP16), with evidence of significant associations in replication analyses for both novel loci. Functional assays of ARSE and MMP16 in human vascular smooth muscle cells (VSMCs) demonstrate that ARSE is a promoter of VSMC calcification and VSMC phenotype switching from a contractile to a calcifying or osteogenic phenotype. Furthermore, we show that the association of variants near ARSE with reduced CAC is likely explained by reduced ARSE expression with the G allele of enhancer variant rs5982944. Our study highlights ARSE as an important contributor to atherosclerotic vascular calcification, and a potential drug target for vascular calcific disease.

Published
2023

3. Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed whole-genome sequencing study.

Author

Wang, Yuxuan, Selvaraj, Margaret, Li, Xihao, Li, Zilin, Holdcraft, Jacob, Arnett, Donna, Bis, Joshua, Blangero, John, Boerwinkle, Eric, Bowden, Donald, Cade, Brian, Carlson, Jenna, Carson, April, Chen, Yii-Der, Curran, Joanne, de Vries, Paul, Dutcher, Susan, Ellinor, Patrick, Floyd, James, Fornage, Myriam, Freedman, Barry, Gabriel, Stacey, Germer, Soren, Gibbs, Richard, Guo, Xiuqing, He, Jiang, Heard-Costa, Nancy, Hildalgo, Bertha, Hou, Lifang, Irvin, Marguerite, Joehanes, Roby, Kaplan, Robert, Kardia, Sharon, Kelly, Tanika, Kim, Ryan, Kooperberg, Charles, Kral, Brian, Levy, Daniel, Li, Changwei, Liu, Chunyu, Lloyd-Jone, Don, Loos, Ruth, Mahaney, Michael, Martin, Lisa, Mathias, Rasika, Minster, Ryan, Mitchell, Braxton, Montasser, May, Morrison, Alanna, Murabito, Joanne, Naseri, Take, OConnell, Jeffrey, Palmer, Nicholette, Preuss, Michael, Psaty, Bruce, Raffield, Laura, Rao, Dabeeru, Redline, Susan, Reiner, Alexander, Rich, Stephen, Ruepena, Muagututia, Sheu, Wayne, Smith, Jennifer, Smith, Albert, Tiwari, Hemant, Tsai, Michael, Viaud-Martinez, Karine, Wang, Zhe, Yanek, Lisa, Zhao, Wei, Lin, Xihong, Natarajan, Pradeep, Peloso, Gina, and Rotter, Jerome

Subjects
association, blood lipid, cholesterol, lncRNA, rare variants, whole-genome sequencing, Humans, RNA, Long Noncoding, Genome-Wide Association Study, Precision Medicine, Whole Genome Sequencing, Lipids, Polymorphism, Single Nucleotide
Abstract

Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions in lipid metabolism. Large-scale whole-genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess more associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with measurement of blood lipids and lipoproteins (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare-variant aggregate association tests using the STAAR (variant-set test for association using annotation information) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare-coding variants in nearby protein-coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500-kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variation and rare protein-coding variation at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNAs.

Published
2023

4. Genetic modification of inflammation- and clonal hematopoiesis-associated cardiovascular risk.

Author

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

Subjects
Cardiology, Cardiovascular disease, Genetics, Mouse models, Population genetics, Humans, Animals, Mice, Cardiovascular Diseases, Clonal Hematopoiesis, Risk Factors, Inflammasomes, Hematopoiesis, Inflammation, Heart Disease Risk Factors, Mutation
Abstract

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

Published
2023

5. Investigating Gene-Diet Interactions Impacting the Association Between Macronutrient Intake and Glycemic Traits.

Author

Westerman, Kenneth E, Walker, Maura E, Gaynor, Sheila M, Wessel, Jennifer, DiCorpo, Daniel, Ma, Jiantao, Alonso, Alvaro, Aslibekyan, Stella, Baldridge, Abigail S, Bertoni, Alain G, Biggs, Mary L, Brody, Jennifer A, Chen, Yii-Der Ida, Dupuis, Joseé, Goodarzi, Mark O, Guo, Xiuqing, Hasbani, Natalie R, Heath, Adam, Hidalgo, Bertha, Irvin, Marguerite R, Johnson, W Craig, Kalyani, Rita R, Lange, Leslie, Lemaitre, Rozenn N, Liu, Ching-Ti, Liu, Simin, Moon, Jee-Young, Nassir, Rami, Pankow, James S, Pettinger, Mary, Raffield, Laura M, Rasmussen-Torvik, Laura J, Selvin, Elizabeth, Senn, Mackenzie K, Shadyab, Aladdin H, Smith, Albert V, Smith, Nicholas L, Steffen, Lyn, Talegakwar, Sameera, Taylor, Kent D, de Vries, Paul S, Wilson, James G, Wood, Alexis C, Yanek, Lisa R, Yao, Jie, Zheng, Yinan, Boerwinkle, Eric, Morrison, Alanna C, Fornage, Miriam, Russell, Tracy P, Psaty, Bruce M, Levy, Daniel, Heard-Costa, Nancy L, Ramachandran, Vasan S, Mathias, Rasika A, Arnett, Donna K, Kaplan, Robert, North, Kari E, Correa, Adolfo, Carson, April, Rotter, Jerome I, Rich, Stephen S, Manson, JoAnn E, Reiner, Alexander P, Kooperberg, Charles, Florez, Jose C, Meigs, James B, Merino, Jordi, Tobias, Deirdre K, Chen, Han, and Manning, Alisa K

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Nutrition, Diabetes, Human Genome, Minority Health, Genetics, Cardiovascular, Health Disparities, Prevention, Precision Medicine, Clinical Research, Metabolic and endocrine, Good Health and Well Being, Humans, Glycated Hemoglobin, Diet, Diabetes Mellitus, Eating, Guanine Nucleotide Dissociation Inhibitors, Genome-Wide Association Study, Medical and Health Sciences, Endocrinology & Metabolism, Biomedical and clinical sciences
Abstract

Few studies have demonstrated reproducible gene-diet interactions (GDIs) impacting metabolic disease risk factors, likely due in part to measurement error in dietary intake estimation and insufficient capture of rare genetic variation. We aimed to identify GDIs across the genetic frequency spectrum impacting the macronutrient-glycemia relationship in genetically and culturally diverse cohorts. We analyzed 33,187 participants free of diabetes from 10 National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program cohorts with whole-genome sequencing, self-reported diet, and glycemic trait data. We fit cohort-specific, multivariable-adjusted linear mixed models for the effect of diet, modeled as an isocaloric substitution of carbohydrate for fat, and its interactions with common and rare variants genome-wide. In main effect meta-analyses, participants consuming more carbohydrate had modestly lower glycemic trait values (e.g., for glycated hemoglobin [HbA1c], -0.013% HbA1c/250 kcal substitution). In GDI meta-analyses, a common African ancestry-enriched variant (rs79762542) reached study-wide significance and replicated in the UK Biobank cohort, indicating a negative carbohydrate-HbA1c association among major allele homozygotes only. Simulations revealed that >150,000 samples may be necessary to identify similar macronutrient GDIs under realistic assumptions about effect size and measurement error. These results generate hypotheses for further exploration of modifiable metabolic disease risk in additional cohorts with African ancestry.Article highlightsWe aimed to identify genetic modifiers of the dietary macronutrient-glycemia relationship using whole-genome sequence data from 10 Trans-Omics for Precision Medicine program cohorts. Substitution models indicated a modest reduction in glycemia associated with an increase in dietary carbohydrate at the expense of fat. Genome-wide interaction analysis identified one African ancestry-enriched variant near the FRAS1 gene that may interact with macronutrient intake to influence hemoglobin A1c. Simulation-based power calculations accounting for measurement error suggested that substantially larger sample sizes may be necessary to discover further gene-macronutrient interactions.

Published
2023

6. Multi-tissue epigenetic analysis identifies distinct associations underlying insulin resistance and Alzheimer’s disease at CPT1A locus

Author

Sarnowski, Chloé, Huan, Tianxiao, Ma, Yiyi, Joehanes, Roby, Beiser, Alexa, DeCarli, Charles S, Heard-Costa, Nancy L, Levy, Daniel, Lin, Honghuang, Liu, Ching-Ti, Liu, Chunyu, Meigs, James B, Satizabal, Claudia L, Florez, Jose C, Hivert, Marie-France, Dupuis, Josée, De Jager, Philip L, Bennett, David A, Seshadri, Sudha, and Morrison, Alanna C

Subjects
Biological Sciences, Genetics, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Dementia, Neurodegenerative, Alzheimer's Disease, Human Genome, Aging, Brain Disorders, Acquired Cognitive Impairment, Neurosciences, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Neurological, Humans, Alzheimer Disease, Diabetes Mellitus, Type 2, DNA Methylation, Epigenesis, Genetic, Genetic Markers, Genome-Wide Association Study, Insulin Resistance, Epigenetics, Insulin resistance, Alzheimer's disease, FHS, ROSMAP, DNA methylation, Alzheimer’s disease, Clinical Sciences, Paediatrics and Reproductive Medicine
Abstract

BackgroundInsulin resistance (IR) is a major risk factor for Alzheimer's disease (AD) dementia. The mechanisms by which IR predisposes to AD are not well-understood. Epigenetic studies may help identify molecular signatures of IR associated with AD, thus improving our understanding of the biological and regulatory mechanisms linking IR and AD.MethodsWe conducted an epigenome-wide association study of IR, quantified using the homeostatic model assessment of IR (HOMA-IR) and adjusted for body mass index, in 3,167 participants from the Framingham Heart Study (FHS) without type 2 diabetes at the time of blood draw used for methylation measurement. We identified DNA methylation markers associated with IR at the genome-wide level accounting for multiple testing (P

Published
2023

7. Deleterious heteroplasmic mitochondrial mutations are associated with an increased risk of overall and cancer-specific mortality

Author

Hong, Yun Soo, Battle, Stephanie L, Shi, Wen, Puiu, Daniela, Pillalamarri, Vamsee, Xie, Jiaqi, Pankratz, Nathan, Lake, Nicole J, Lek, Monkol, Rotter, Jerome I, Rich, Stephen S, Kooperberg, Charles, Reiner, Alex P, Auer, Paul L, Heard-Costa, Nancy, Liu, Chunyu, Lai, Meng, Murabito, Joanne M, Levy, Daniel, Grove, Megan L, Alonso, Alvaro, Gibbs, Richard, Dugan-Perez, Shannon, Gondek, Lukasz P, Guallar, Eliseo, and Arking, Dan E

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Genetics, Cancer, Human Genome, Hematology, 2.1 Biological and endogenous factors, Good Health and Well Being, Humans, Mitochondria, DNA, Mitochondrial, Heteroplasmy, Leukemia, Mutation
Abstract

Mitochondria carry their own circular genome and disruption of the mitochondrial genome is associated with various aging-related diseases. Unlike the nuclear genome, mitochondrial DNA (mtDNA) can be present at 1000 s to 10,000 s copies in somatic cells and variants may exist in a state of heteroplasmy, where only a fraction of the DNA molecules harbors a particular variant. We quantify mtDNA heteroplasmy in 194,871 participants in the UK Biobank and find that heteroplasmy is associated with a 1.5-fold increased risk of all-cause mortality. Additionally, we functionally characterize mtDNA single nucleotide variants (SNVs) using a constraint-based score, mitochondrial local constraint score sum (MSS) and find it associated with all-cause mortality, and with the prevalence and incidence of cancer and cancer-related mortality, particularly leukemia. These results indicate that mitochondria may have a functional role in certain cancers, and mitochondrial heteroplasmic SNVs may serve as a prognostic marker for cancer, especially for leukemia.

Published
2023

8. Whole-exome sequence analysis of anthropometric traits illustrates challenges in identifying effects of rare genetic variants

Author

Young, Kristin L, Fisher, Virginia, Deng, Xuan, Brody, Jennifer A, Graff, Misa, Lim, Elise, Lin, Bridget M, Xu, Hanfei, Amin, Najaf, An, Ping, Aslibekyan, Stella, Fohner, Alison E, Hidalgo, Bertha, Lenzini, Petra, Kraaij, Robert, Medina-Gomez, Carolina, Prokić, Ivana, Rivadeneira, Fernando, Sitlani, Colleen, Tao, Ran, van Rooij, Jeroen, Zhang, Di, Broome, Jai G, Buth, Erin J, Heavner, Benjamin D, Jain, Deepti, Smith, Albert V, Barnes, Kathleen, Boorgula, Meher Preethi, Chavan, Sameer, Darbar, Dawood, De Andrade, Mariza, Guo, Xiuqing, Haessler, Jeffrey, Irvin, Marguerite R, Kalyani, Rita R, Kardia, Sharon LR, Kooperberg, Charles, Kim, Wonji, Mathias, Rasika A, McDonald, Merry-Lynn, Mitchell, Braxton D, Peyser, Patricia A, Regan, Elizabeth A, Redline, Susan, Reiner, Alexander P, Rich, Stephen S, Rotter, Jerome I, Smith, Jennifer A, Weiss, Scott, Wiggins, Kerri L, Yanek, Lisa R, Arnett, Donna, Heard-Costa, Nancy L, Leal, Suzanne, Lin, Danyu, McKnight, Barbara, Province, Michael, van Duijn, Cornelia M, North, Kari E, Cupples, L Adrienne, and Liu, Ching-Ti

Subjects
Biological Sciences, Genetics, Clinical Research, Biotechnology, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Generic health relevance, Good Health and Well Being, Humans, Genome-Wide Association Study, Exome, Body Mass Index, Quantitative Trait Loci, Anthropometry, Intercellular Signaling Peptides and Proteins, Cell Cycle Proteins, body mass index, central obesity, exome sequencing, height
Abstract

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

9. Correlations between complex human phenotypes vary by genetic background, gender, and environment

Author

Elgart, Michael, Goodman, Matthew O, Isasi, Carmen, Chen, Han, Morrison, Alanna C, de Vries, Paul S, Xu, Huichun, Manichaikul, Ani W, Guo, Xiuqing, Franceschini, Nora, Psaty, Bruce M, Rich, Stephen S, Rotter, Jerome I, Lloyd-Jones, Donald M, Fornage, Myriam, Correa, Adolfo, Heard-Costa, Nancy L, Vasan, Ramachandran S, Hernandez, Ryan, Kaplan, Robert C, Redline, Susan, Consortium, The Trans-Omics for Precision Medicine, and Sofer, Tamar

Subjects
Biomedical and Clinical Sciences, Genetic Testing, Clinical Research, Genetics, Good Health and Well Being, Humans, Male, Female, Phenotype, Genetic Background, Trans-Omics for Precision Medicine (TOPMed) Consortium, Haseman-Elston regression, Hispanic Community Health Study/Study of Latinos, Trans-Omics in Precision Medicine, admixed population, genetic architecture, genetic background, genetic correlation, heritability, household correlation, multi-ethnic, Biomedical and clinical sciences
Abstract

We develop a closed-form Haseman-Elston estimator for genetic and environmental correlation coefficients between complex phenotypes, which we term HEc, that is as precise as GCTA yet ∼20× faster. We estimate genetic and environmental correlations between over 7,000 phenotype pairs in subgroups from the Trans-Omics in Precision Medicine (TOPMed) program. We demonstrate substantial differences in both heritabilities and genetic correlations for multiple phenotypes and phenotype pairs between individuals of self-reported Black, Hispanic/Latino, and White backgrounds. We similarly observe differences in many of the genetic and environmental correlations between genders. To estimate the contribution of genetics to the observed phenotypic correlation, we introduce "fractional genetic correlation" as the fraction of phenotypic correlation explained by genetics. Finally, we quantify the enrichment of correlations between phenotypic domains, each of which is comprised of multiple phenotypes. Altogether, we demonstrate that the observed correlations between complex human phenotypes depend on the genetic background of the individuals, their gender, and their environment.

Published
2022

10. Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention.

Author

Wang, Zhe, Emmerich, Andrew, Pillon, Nicolas, Moore, Tim, Hemerich, Daiane, Cornelis, Marilyn, Mazzaferro, Eugenia, Broos, Siacia, Ahluwalia, Tarunveer, Bartz, Traci, Bentley, Amy, Bielak, Lawrence, Chong, Mike, Chu, Audrey, Berry, Diane, Dorajoo, Rajkumar, Dueker, Nicole, Kasbohm, Elisa, Feenstra, Bjarke, Feitosa, Mary, Gieger, Christian, Graff, Mariaelisa, Hall, Leanne, Haller, Toomas, Hartwig, Fernando, Hillis, David, Huikari, Ville, Heard-Costa, Nancy, Holzapfel, Christina, Jackson, Anne, Johansson, Åsa, Jørgensen, Anja, Kaakinen, Marika, Karlsson, Robert, Kerr, Kathleen, Kim, Boram, Koolhaas, Chantal, Kutalik, Zoltan, Lagou, Vasiliki, Lind, Penelope, Lorentzon, Mattias, Lyytikäinen, Leo-Pekka, Mangino, Massimo, Metzendorf, Christoph, Monroe, Kristine, Pacolet, Alexander, Pérusse, Louis, Pool, Rene, Richmond, Rebecca, Rivera, Natalia, Robiou-du-Pont, Sebastien, Schraut, Katharina, Schulz, Christina-Alexandra, Stringham, Heather, Tanaka, Toshiko, Teumer, Alexander, Turman, Constance, van der Most, Peter, Vanmunster, Mathias, van Rooij, Frank, van Vliet-Ostaptchouk, Jana, Zhang, Xiaoshuai, Zhao, Jing-Hua, Zhao, Wei, Balkhiyarova, Zhanna, Balslev-Harder, Marie, Baumeister, Sebastian, Beilby, John, Blangero, John, Boomsma, Dorret, Brage, Soren, Braund, Peter, Brody, Jennifer, Bruinenberg, Marcel, Ekelund, Ulf, Liu, Ching-Ti, Cole, John, Collins, Francis, Cupples, L, Esko, Tõnu, Enroth, Stefan, Faul, Jessica, Fernandez-Rhodes, Lindsay, Fohner, Alison, Franco, Oscar, Galesloot, Tessel, Gordon, Scott, Grarup, Niels, Hartman, Catharina, Heiss, Gerardo, Hui, Jennie, Illig, Thomas, Jago, Russell, James, Alan, Joshi, Peter, Jung, Taeyeong, Kähönen, Mika, Kilpeläinen, Tuomas, Koh, Woon-Puay, and Kolcic, Ivana

Subjects
Actinin, Cross-Sectional Studies, Exercise, Genome-Wide Association Study, Humans, Leisure Activities, Sedentary Behavior
Abstract

Although physical activity and sedentary behavior are moderately heritable, little is known about the mechanisms that influence these traits. Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training. A missense variant in ACTN3 makes the alpha-actinin-3 filaments more flexible, resulting in lower maximal force in isolated type IIA muscle fibers, and possibly protection from exercise-induced muscle damage. Finally, Mendelian randomization analyses show that beneficial effects of lower LST and higher MVPA on several risk factors and diseases are mediated or confounded by body mass index (BMI). Our results provide insights into physical activity mechanisms and its role in disease prevention.

Published
2022

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

Author

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

Published
2023
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12. Whole-Genome Sequencing Association Analyses of Stroke and Its Subtypes in Ancestrally Diverse Populations From Trans-Omics for Precision Medicine Project

Author

Hu, Yao, Haessler, Jeffrey W, Manansala, Regina, Wiggins, Kerri L, Moscati, Arden, Beiser, Alexa, Heard-Costa, Nancy L, Sarnowski, Chloe, Raffield, Laura M, Chung, Jaeyoon, Marini, Sandro, Anderson, Christopher D, Rosand, Jonathan, Xu, Huichun, Sun, Xiao, Kelly, Tanika N, Wong, Quenna, Lange, Leslie A, Rotter, Jerome I, Correa, Adolfo, Vasan, Ramachandran S, Seshadri, Sudha, Rich, Stephen S, Do, Ron, Loos, Ruth JF, Longstreth, William T, Bis, Joshua C, Psaty, Bruce M, Tirschwell, David L, Assimes, Themistocles L, Silver, Brian, Liu, Simin, Jackson, Rebecca, Wassertheil-Smoller, Sylvia, Mitchell, Braxton D, Fornage, Myriam, Auer, Paul L, Reiner, Alex P, Kooperberg, Charles, and Group, the NHLBI Trans-Omics for Precision Medicine Consortium the Trans-Omics for Precision Medicine Stroke Working

Subjects
Epidemiology, Health Sciences, Human Genome, Neurosciences, Brain Disorders, Stroke, Genetics, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Aged, Aged, 80 and over, Female, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Precision Medicine, Racial Groups, Whole Genome Sequencing, atherosclerosis, blood pressure, cause of death, embolic stroke, sample size, Trans-Omics for Precision Medicine (TOPMed) Stroke Working Group, the NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Neurology & Neurosurgery, Clinical sciences, Allied health and rehabilitation science
Abstract

Background and purposeStroke is the leading cause of death and long-term disability worldwide. Previous genome-wide association studies identified 51 loci associated with stroke (mostly ischemic) and its subtypes among predominantly European populations. Using whole-genome sequencing in ancestrally diverse populations from the Trans-Omics for Precision Medicine (TOPMed) Program, we aimed to identify novel variants, especially low-frequency or ancestry-specific variants, associated with all stroke, ischemic stroke and its subtypes (large artery, cardioembolic, and small vessel), and hemorrhagic stroke and its subtypes (intracerebral and subarachnoid).MethodsWhole-genome sequencing data were available for 6833 stroke cases and 27 116 controls, including 22 315 European, 7877 Black, 2616 Hispanic/Latino, 850 Asian, 54 Native American, and 237 other ancestry participants. In TOPMed, we performed single variant association analysis examining 40 million common variants and aggregated association analysis focusing on rare variants. We also combined TOPMed European populations with over 28 000 additional European participants from the UK BioBank genome-wide array data through meta-analysis.ResultsIn the single variant association analysis in TOPMed, we identified one novel locus 13q33 for large artery at whole-genome-wide significance (P

Published
2022

13. Whole genome sequence analysis of platelet traits in the NHLBI Trans-Omics for Precision Medicine (TOPMed) initiative

Author

Little, Amarise, Hu, Yao, Sun, Quan, Jain, Deepti, Broome, Jai, Chen, Ming-Huei, Thibord, Florian, McHugh, Caitlin, Surendran, Praveen, Blackwell, Thomas W, Brody, Jennifer A, Bhan, Arunoday, Chami, Nathalie, de Vries, Paul S, Ekunwe, Lynette, Heard-Costa, Nancy, Hobbs, Brian D, Manichaikul, Ani, Moon, Jee-Young, Preuss, Michael H, Ryan, Kathleen, Wang, Zhe, Wheeler, Marsha, Yanek, Lisa R, Abecasis, Goncalo R, Almasy, Laura, Beaty, Terri H, Becker, Lewis C, Blangero, John, Boerwinkle, Eric, Butterworth, Adam S, Choquet, Hélène, Correa, Adolfo, Curran, Joanne E, Faraday, Nauder, Fornage, Myriam, Glahn, David C, Hou, Lifang, Jorgenson, Eric, Kooperberg, Charles, Lewis, Joshua P, Lloyd-Jones, Donald M, Loos, Ruth JF, Min, Yuan-I, Mitchell, Braxton D, Morrison, Alanna C, Nickerson, Deborah A, North, Kari E, O'Connell, Jeffrey R, Pankratz, Nathan, Psaty, Bruce M, Vasan, Ramachandran S, Rich, Stephen S, Rotter, Jerome I, Smith, Albert V, Smith, Nicholas L, Tang, Hua, Tracy, Russell P, Conomos, Matthew P, Laurie, Cecelia A, Mathias, Rasika A, Li, Yun, Auer, Paul L, Consortium, NHLBI Trans-Omics for Precision Medicine, Thornton, Timothy, Reiner, Alexander P, Johnson, Andrew D, and Raffield, Laura M

Subjects
Biological Sciences, Genetics, Hematology, Biotechnology, Clinical Research, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Blood Platelets, Genome-Wide Association Study, Humans, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Polymorphism, Single Nucleotide, Precision Medicine, United States, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Medical and Health Sciences, Genetics & Heredity
Abstract

Platelets play a key role in thrombosis and hemostasis. Platelet count (PLT) and mean platelet volume (MPV) are highly heritable quantitative traits, with hundreds of genetic signals previously identified, mostly in European ancestry populations. We here utilize whole genome sequencing (WGS) from NHLBI's Trans-Omics for Precision Medicine initiative (TOPMed) in a large multi-ethnic sample to further explore common and rare variation contributing to PLT (n = 61 200) and MPV (n = 23 485). We identified and replicated secondary signals at MPL (rs532784633) and PECAM1 (rs73345162), both more common in African ancestry populations. We also observed rare variation in Mendelian platelet-related disorder genes influencing variation in platelet traits in TOPMed cohorts (not enriched for blood disorders). For example, association of GP9 with lower PLT and higher MPV was partly driven by a pathogenic Bernard-Soulier syndrome variant (rs5030764, p.Asn61Ser), and the signals at TUBB1 and CD36 were partly driven by loss of function variants not annotated as pathogenic in ClinVar (rs199948010 and rs571975065). However, residual signal remained for these gene-based signals after adjusting for lead variants, suggesting that additional variants in Mendelian genes with impacts in general population cohorts remain to be identified. Gene-based signals were also identified at several genome-wide association study identified loci for genes not annotated for Mendelian platelet disorders (PTPRH, TET2, CHEK2), with somatic variation driving the result at TET2. These results highlight the value of WGS in populations of diverse genetic ancestry to identify novel regulatory and coding signals, even for well-studied traits like platelet traits.

Published
2022

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

Author

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

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Epidemiology, Health Sciences, Biotechnology, Heart Disease - Coronary Heart Disease, Cardiovascular, Heart Disease, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Alleles, Cholesterol, LDL, Genome-Wide Association Study, Humans, Lipids, Whole Genome Sequencing, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium
Abstract

Blood lipids are heritable modifiable causal factors for coronary artery disease. Despite well-described monogenic and polygenic bases of dyslipidemia, limitations remain in discovery of lipid-associated alleles using whole genome sequencing (WGS), partly due to limited sample sizes, ancestral diversity, and interpretation of clinical significance. Among 66,329 ancestrally diverse (56% non-European) participants, we associate 428M variants from deep-coverage WGS with lipid levels; ~400M variants were not assessed in prior lipids genetic analyses. We find multiple lipid-related genes strongly associated with blood lipids through analysis of common and rare coding variants. We discover several associated rare non-coding variants, largely at Mendelian lipid genes. Notably, we observe rare LDLR intronic variants associated with markedly increased LDL-C, similar to rare LDLR exonic variants. In conclusion, we conducted a systematic whole genome scan for blood lipids expanding the alleles linked to lipids for multiple ancestries and characterize a clinically-relevant rare non-coding variant model for lipids.

Published
2022

15. A System for Phenotype Harmonization in the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) Program

Author

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

Subjects
Epidemiology, Health Sciences, Human Genome, Lung, Genetics, Clinical Research, Cardiovascular, Good Health and Well Being, Data Aggregation, Genetic Association Studies, Humans, Information Dissemination, National Heart, Lung, and Blood Institute (U.S.), Phenomics, Phenotype, Precision Medicine, Program Evaluation, United States, cardiovascular disease, common data elements, hematologic disease, information dissemination, lung diseases, phenotypes, sleep-wake disorders, Mathematical Sciences, Medical and Health Sciences
Abstract

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

Published
2021

16. Whole-genome sequencing in diverse subjects identifies genetic correlates of leukocyte traits: The NHLBI TOPMed program

Author

Mikhaylova, Anna V, McHugh, Caitlin P, Polfus, Linda M, Raffield, Laura M, Boorgula, Meher Preethi, Blackwell, Thomas W, Brody, Jennifer A, Broome, Jai, Chami, Nathalie, Chen, Ming-Huei, Conomos, Matthew P, Cox, Corey, Curran, Joanne E, Daya, Michelle, Ekunwe, Lynette, Glahn, David C, Heard-Costa, Nancy, Highland, Heather M, Hobbs, Brian D, Ilboudo, Yann, Jain, Deepti, Lange, Leslie A, Miller-Fleming, Tyne W, Min, Nancy, Moon, Jee-Young, Preuss, Michael H, Rosen, Jonathon, Ryan, Kathleen, Smith, Albert V, Sun, Quan, Surendran, Praveen, de Vries, Paul S, Walter, Klaudia, Wang, Zhe, Wheeler, Marsha, Yanek, Lisa R, Zhong, Xue, Abecasis, Goncalo R, Almasy, Laura, Barnes, Kathleen C, Beaty, Terri H, Becker, Lewis C, Blangero, John, Boerwinkle, Eric, Butterworth, Adam S, Chavan, Sameer, Cho, Michael H, Choquet, Hélène, Correa, Adolfo, Cox, Nancy, DeMeo, Dawn L, Faraday, Nauder, Fornage, Myriam, Gerszten, Robert E, Hou, Lifang, Johnson, Andrew D, Jorgenson, Eric, Kaplan, Robert, Kooperberg, Charles, Kundu, Kousik, Laurie, Cecelia A, Lettre, Guillaume, Lewis, Joshua P, Li, Bingshan, Li, Yun, Lloyd-Jones, Donald M, Loos, Ruth JF, Manichaikul, Ani, Meyers, Deborah A, Mitchell, Braxton D, Morrison, Alanna C, Ngo, Debby, Nickerson, Deborah A, Nongmaithem, Suraj, North, Kari E, O’Connell, Jeffrey R, Ortega, Victor E, Pankratz, Nathan, Perry, James A, Psaty, Bruce M, Rich, Stephen S, Soranzo, Nicole, Rotter, Jerome I, Silverman, Edwin K, Smith, Nicholas L, Tang, Hua, Tracy, Russell P, Thornton, Timothy A, Vasan, Ramachandran S, Zein, Joe, Mathias, Rasika A, Consortium, NHLBI Trans-Omics for Precision Medicine, Reiner, Alexander P, and Auer, Paul L

Subjects
Human Genome, Genetics, Aetiology, 2.1 Biological and endogenous factors, Inflammatory and immune system, Good Health and Well Being, Asthma, Biomarkers, Dermatitis, Atopic, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Leukocytes, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Polymorphism, Single Nucleotide, Prognosis, Proteome, Pulmonary Disease, Chronic Obstructive, Quantitative Trait Loci, United Kingdom, United States, Whole Genome Sequencing, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, blood-cell counts, whole-genome sequencing, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

Many common and rare variants associated with hematologic traits have been discovered through imputation on large-scale reference panels. However, the majority of genome-wide association studies (GWASs) have been conducted in Europeans, and determining causal variants has proved challenging. We performed a GWAS of total leukocyte, neutrophil, lymphocyte, monocyte, eosinophil, and basophil counts generated from 109,563,748 variants in the autosomes and the X chromosome in the Trans-Omics for Precision Medicine (TOPMed) program, which included data from 61,802 individuals of diverse ancestry. We discovered and replicated 7 leukocyte trait associations, including (1) the association between a chromosome X, pseudo-autosomal region (PAR), noncoding variant located between cytokine receptor genes (CSF2RA and CLRF2) and lower eosinophil count; and (2) associations between single variants found predominantly among African Americans at the S1PR3 (9q22.1) and HBB (11p15.4) loci and monocyte and lymphocyte counts, respectively. We further provide evidence indicating that the newly discovered eosinophil-lowering chromosome X PAR variant might be associated with reduced susceptibility to common allergic diseases such as atopic dermatitis and asthma. Additionally, we found a burden of very rare FLT3 (13q12.2) variants associated with monocyte counts. Together, these results emphasize the utility of whole-genome sequencing in diverse samples in identifying associations missed by European-ancestry-driven GWASs.

Published
2021

17. Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes.

Author

Goodrich, Julia K, Singer-Berk, Moriel, Son, Rachel, Sveden, Abigail, Wood, Jordan, England, Eleina, Cole, Joanne B, Weisburd, Ben, Watts, Nick, Caulkins, Lizz, Dornbos, Peter, Koesterer, Ryan, Zappala, Zachary, Zhang, Haichen, Maloney, Kristin A, Dahl, Andy, Aguilar-Salinas, Carlos A, Atzmon, Gil, Barajas-Olmos, Francisco, Barzilai, Nir, Blangero, John, Boerwinkle, Eric, Bonnycastle, Lori L, Bottinger, Erwin, Bowden, Donald W, Centeno-Cruz, Federico, Chambers, John C, Chami, Nathalie, Chan, Edmund, Chan, Juliana, Cheng, Ching-Yu, Cho, Yoon Shin, Contreras-Cubas, Cecilia, Córdova, Emilio, Correa, Adolfo, DeFronzo, Ralph A, Duggirala, Ravindranath, Dupuis, Josée, Garay-Sevilla, Ma Eugenia, García-Ortiz, Humberto, Gieger, Christian, Glaser, Benjamin, González-Villalpando, Clicerio, Gonzalez, Ma Elena, Grarup, Niels, Groop, Leif, Gross, Myron, Haiman, Christopher, Han, Sohee, Hanis, Craig L, Hansen, Torben, Heard-Costa, Nancy L, Henderson, Brian E, Hernandez, Juan Manuel Malacara, Hwang, Mi Yeong, Islas-Andrade, Sergio, Jørgensen, Marit E, Kang, Hyun Min, Kim, Bong-Jo, Kim, Young Jin, Koistinen, Heikki A, Kooner, Jaspal Singh, Kuusisto, Johanna, Kwak, Soo-Heon, Laakso, Markku, Lange, Leslie, Lee, Jong-Young, Lee, Juyoung, Lehman, Donna M, Linneberg, Allan, Liu, Jianjun, Loos, Ruth JF, Lyssenko, Valeriya, Ma, Ronald CW, Martínez-Hernández, Angélica, Meigs, James B, Meitinger, Thomas, Mendoza-Caamal, Elvia, Mohlke, Karen L, Morris, Andrew D, Morrison, Alanna C, Ng, Maggie CY, Nilsson, Peter M, O'Donnell, Christopher J, Orozco, Lorena, Palmer, Colin NA, Park, Kyong Soo, Post, Wendy S, Pedersen, Oluf, Preuss, Michael, Psaty, Bruce M, Reiner, Alexander P, Revilla-Monsalve, Cristina, Rich, Stephen S, Rotter, Jerome I, Saleheen, Danish, Schurmann, Claudia, Sim, Xueling, Sladek, Rob, and Small, Kerrin S

Subjects
AMP-T2D-GENES Consortia, Humans, Diabetes Mellitus, Type 2, Genetic Predisposition to Disease, Risk Assessment, Genotype, Multifactorial Inheritance, Penetrance, Adult, Dyslipidemias, Exome, Biomarkers, Biological Variation, Population
Abstract

Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias.

Published
2021

18. Whole-genome sequencing association analysis of quantitative red blood cell phenotypes: The NHLBI TOPMed program

Author

Hu, Yao, Stilp, Adrienne M, McHugh, Caitlin P, Rao, Shuquan, Jain, Deepti, Zheng, Xiuwen, Lane, John, de Bellefon, Sébastian Méric, Raffield, Laura M, Chen, Ming-Huei, Yanek, Lisa R, Wheeler, Marsha, Yao, Yao, Ren, Chunyan, Broome, Jai, Moon, Jee-Young, de Vries, Paul S, Hobbs, Brian D, Sun, Quan, Surendran, Praveen, Brody, Jennifer A, Blackwell, Thomas W, Choquet, Hélène, Ryan, Kathleen, Duggirala, Ravindranath, Heard-Costa, Nancy, Wang, Zhe, Chami, Nathalie, Preuss, Michael H, Min, Nancy, Ekunwe, Lynette, Lange, Leslie A, Cushman, Mary, Faraday, Nauder, Curran, Joanne E, Almasy, Laura, Kundu, Kousik, Smith, Albert V, Gabriel, Stacey, Rotter, Jerome I, Fornage, Myriam, Lloyd-Jones, Donald M, Vasan, Ramachandran S, Smith, Nicholas L, North, Kari E, Boerwinkle, Eric, Becker, Lewis C, Lewis, Joshua P, Abecasis, Goncalo R, Hou, Lifang, O’Connell, Jeffrey R, Morrison, Alanna C, Beaty, Terri H, Kaplan, Robert, Correa, Adolfo, Blangero, John, Jorgenson, Eric, Psaty, Bruce M, Kooperberg, Charles, Walton, Russell T, Kleinstiver, Benjamin P, Tang, Hua, Loos, Ruth JF, Soranzo, Nicole, Butterworth, Adam S, Nickerson, Debbie, Rich, Stephen S, Mitchell, Braxton D, Johnson, Andrew D, Auer, Paul L, Li, Yun, Mathias, Rasika A, Lettre, Guillaume, Pankratz, Nathan, Laurie, Cathy C, Laurie, Cecelia A, Bauer, Daniel E, Conomos, Matthew P, Reiner, Alexander P, and Consortium, NHLBI Trans-Omics for Precision Medicine

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Biotechnology, Clinical Research, Hematology, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Adult, Aged, Chromosomes, Human, Pair 16, Datasets as Topic, Erythrocytes, Female, Gene Editing, Genetic Variation, Genome-Wide Association Study, HEK293 Cells, Humans, Male, Middle Aged, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Quality Control, Reproducibility of Results, United States, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, base editing, red blood cell traits, whole-genome sequencing, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Whole-genome sequencing (WGS), a powerful tool for detecting novel coding and non-coding disease-causing variants, has largely been applied to clinical diagnosis of inherited disorders. Here we leveraged WGS data in up to 62,653 ethnically diverse participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and assessed statistical association of variants with seven red blood cell (RBC) quantitative traits. We discovered 14 single variant-RBC trait associations at 12 genomic loci, which have not been reported previously. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, and G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these discovered variants are rare/low frequency, and several are observed disproportionately among non-European Ancestry (African, Hispanic/Latino, or East Asian) populations. We identified a 3 bp indel p.Lys2169del (g.88717175_88717177TCT[4]) (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis (MIM: 194380), associated with higher mean corpuscular hemoglobin concentration (MCHC). In stepwise conditional analysis and in gene-based rare variant aggregated association analysis, we identified several of the variants in HBB, HBA1, TMPRSS6, and G6PD that represent the carrier state for known coding, promoter, or splice site loss-of-function variants that cause inherited RBC disorders. Finally, we applied base and nuclease editing to demonstrate that the sentinel variant rs112097551 (nearest gene RPN1) acts through a cis-regulatory element that exerts long-range control of the gene RUVBL1 which is essential for hematopoiesis. Together, these results demonstrate the utility of WGS in ethnically diverse population-based samples and gene editing for expanding knowledge of the genetic architecture of quantitative hematologic traits and suggest a continuum between complex trait and Mendelian red cell disorders.

Published
2021

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

Author

Taliun, Daniel, Harris, Daniel N, Kessler, Michael D, Carlson, Jedidiah, Szpiech, Zachary A, Torres, Raul, Taliun, Sarah A Gagliano, Corvelo, André, Gogarten, Stephanie M, Kang, Hyun Min, Pitsillides, Achilleas N, LeFaive, Jonathon, Lee, Seung-been, Tian, Xiaowen, Browning, Brian L, Das, Sayantan, Emde, Anne-Katrin, Clarke, Wayne E, Loesch, Douglas P, Shetty, Amol C, Blackwell, Thomas W, Smith, Albert V, Wong, Quenna, Liu, Xiaoming, Conomos, Matthew P, Bobo, Dean M, Aguet, François, Albert, Christine, Alonso, Alvaro, Ardlie, Kristin G, Arking, Dan E, Aslibekyan, Stella, Auer, Paul L, Barnard, John, Barr, R Graham, Barwick, Lucas, Becker, Lewis C, Beer, Rebecca L, Benjamin, Emelia J, Bielak, Lawrence F, Blangero, John, Boehnke, Michael, Bowden, Donald W, Brody, Jennifer A, Burchard, Esteban G, Cade, Brian E, Casella, James F, Chalazan, Brandon, Chasman, Daniel I, Chen, Yii-Der Ida, Cho, Michael H, Choi, Seung Hoan, Chung, Mina K, Clish, Clary B, Correa, Adolfo, Curran, Joanne E, Custer, Brian, Darbar, Dawood, Daya, Michelle, de Andrade, Mariza, DeMeo, Dawn L, Dutcher, Susan K, Ellinor, Patrick T, Emery, Leslie S, Eng, Celeste, Fatkin, Diane, Fingerlin, Tasha, Forer, Lukas, Fornage, Myriam, Franceschini, Nora, Fuchsberger, Christian, Fullerton, Stephanie M, Germer, Soren, Gladwin, Mark T, Gottlieb, Daniel J, Guo, Xiuqing, Hall, Michael E, He, Jiang, Heard-Costa, Nancy L, Heckbert, Susan R, Irvin, Marguerite R, Johnsen, Jill M, Johnson, Andrew D, Kaplan, Robert, Kardia, Sharon LR, Kelly, Tanika, Kelly, Shannon, Kenny, Eimear E, Kiel, Douglas P, Klemmer, Robert, Konkle, Barbara A, Kooperberg, Charles, Köttgen, Anna, Lange, Leslie A, Lasky-Su, Jessica, Levy, Daniel, Lin, Xihong, Lin, Keng-Han, Liu, Chunyu, and Loos, Ruth JF

Subjects
Genetics, Biotechnology, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Generic health relevance, Good Health and Well Being, Cytochrome P-450 CYP2D6, Genetic Variation, Genome, Human, Genomics, Haplotypes, Heterozygote, Humans, INDEL Mutation, Loss of Function Mutation, Mutagenesis, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Polymorphism, Single Nucleotide, Population Density, Precision Medicine, Quality Control, Sample Size, United States, Whole Genome Sequencing, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, General Science & Technology
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%.

Published
2021

20. De novo mutations across 1,465 diverse genomes reveal mutational insights and reductions in the Amish founder population

Author

Kessler, Michael D, Loesch, Douglas P, Perry, James A, Heard-Costa, Nancy L, Taliun, Daniel, Cade, Brian E, Wang, Heming, Daya, Michelle, Ziniti, John, Datta, Soma, Celedón, Juan C, Soto-Quiros, Manuel E, Avila, Lydiana, Weiss, Scott T, Barnes, Kathleen, Redline, Susan S, Vasan, Ramachandran S, Johnson, Andrew D, Mathias, Rasika A, Hernandez, Ryan, Wilson, James G, Nickerson, Deborah A, Abecasis, Goncalo, Browning, Sharon R, Zöllner, Sebastian, O’Connell, Jeffrey R, Mitchell, Braxton D, Lung, and Blood Institute Trans-Omics for Precision Medicine Consortium National Heart, Group, TOPMed Population Genetics Working, O’Connor, Timothy D, Aalbers, Sanne, Abdalla, Moustafa, Abdul-Rahman, Omar, Abecasis, Gonçalo, Abhyankar, Avinash, Adrianto, Indra, Aguet, Francois, Akers, Rachel, Al-Tobasei, Rafet, Albert, Christine, Aldred, Micheala, Almasy, Laura, Almeida, Marcio, Alonso, Alvaro, Ament, Seth, Ampleford, Elizabeth, An, Ping, Anderson, Christopher D, Andersson, Charlotte, Anugu, Pramod, Appelbaum, Elizabeth, Ardlie, Kristin, Arking, Dan, Armasu, Sebastian M, Arnett, Donna K, Arruda, Heather, Arvanitis, Marios, Ashley-Koch, Allison, Ashrani, Aneel, Aslibekyan, Stella, Assimes, Tim, Atkinson, Elizabeth, Auer, Paul, Austin, Thomas R, Avery, Christy, Avila-Pacheco, Julian, Avillach, Paul, Aviv, Abraham, Avramopoulos, Dimitrios, Ballantyne, Christie, Balte, Pallavi, Bamshad, Michael, Bancks, Mike, Barnard, John, Barr, R Graham, Barron-Casella, Emily, Bartz, Traci, Barwick, Lucas, Basu, Saonli, Battle, Alexis, Baumann, Michael, Beame, David, Beaty, Terri, Beck, Gerald, Becker, Lewis, Becker, Diane, Beer, Rebecca, Begum, Ferdouse, Beiser, Alexa, Beitelshees, Amber, Benjamin, Emelia, Benos, Takis, Berk-Rauch, Hanna, Besich, Zachary M, Bezerra, Marcos, Bhatt, Surya, Bi, Wenjian, Bick, Alexander, and Bielak, Larry

Subjects
Biological Sciences, Genetics, Human Genome, Good Health and Well Being, Adult, Amish, Cohort Studies, DNA Mutational Analysis, Female, Genetics, Population, Genome, Human, Heterozygote, Humans, Male, Mutation, Pedigree, Whole Genome Sequencing, Young Adult, National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Population Genetics Working Group, de novo mutations, diversity, mutation rate, recombination
Abstract

De novo mutations (DNMs), or mutations that appear in an individual despite not being seen in their parents, are an important source of genetic variation whose impact is relevant to studies of human evolution, genetics, and disease. Utilizing high-coverage whole-genome sequencing data as part of the Trans-Omics for Precision Medicine (TOPMed) Program, we called 93,325 single-nucleotide DNMs across 1,465 trios from an array of diverse human populations, and used them to directly estimate and analyze DNM counts, rates, and spectra. We find a significant positive correlation between local recombination rate and local DNM rate, and that DNM rate explains a substantial portion (8.98 to 34.92%, depending on the model) of the genome-wide variation in population-level genetic variation from 41K unrelated TOPMed samples. Genome-wide heterozygosity does correlate with DNM rate, but only explains

Published
2020

21. A saturated map of common genetic variants associated with human height

Author

Yengo, Loïc, Vedantam, Sailaja, Marouli, Eirini, Sidorenko, Julia, Bartell, Eric, Sakaue, Saori, Graff, Marielisa, Eliasen, Anders U., Jiang, Yunxuan, Raghavan, Sridharan, Miao, Jenkai, Arias, Joshua D., Graham, Sarah E., Mukamel, Ronen E., Spracklen, Cassandra N., Yin, Xianyong, Chen, Shyh-Huei, Ferreira, Teresa, Highland, Heather H., Ji, Yingjie, Karaderi, Tugce, Lin, Kuang, Lüll, Kreete, Malden, Deborah E., Medina-Gomez, Carolina, Machado, Moara, Moore, Amy, Rüeger, Sina, Sim, Xueling, Vrieze, Scott, Ahluwalia, Tarunveer S., Akiyama, Masato, Allison, Matthew A., Alvarez, Marcus, Andersen, Mette K., Ani, Alireza, Appadurai, Vivek, Arbeeva, Liubov, Bhaskar, Seema, Bielak, Lawrence F., Bollepalli, Sailalitha, Bonnycastle, Lori L., Bork-Jensen, Jette, Bradfield, Jonathan P., Bradford, Yuki, Braund, Peter S., Brody, Jennifer A., Burgdorf, Kristoffer S., Cade, Brian E., Cai, Hui, Cai, Qiuyin, Campbell, Archie, Cañadas-Garre, Marisa, Catamo, Eulalia, Chai, Jin-Fang, Chai, Xiaoran, Chang, Li-Ching, Chang, Yi-Cheng, Chen, Chien-Hsiun, Chesi, Alessandra, Choi, Seung Hoan, Chung, Ren-Hua, Cocca, Massimiliano, Concas, Maria Pina, Couture, Christian, Cuellar-Partida, Gabriel, Danning, Rebecca, Daw, E. Warwick, Degenhard, Frauke, Delgado, Graciela E., Delitala, Alessandro, Demirkan, Ayse, Deng, Xuan, Devineni, Poornima, Dietl, Alexander, Dimitriou, Maria, Dimitrov, Latchezar, Dorajoo, Rajkumar, Ekici, Arif B., Engmann, Jorgen E., Fairhurst-Hunter, Zammy, Farmaki, Aliki-Eleni, Faul, Jessica D., Fernandez-Lopez, Juan-Carlos, Forer, Lukas, Francescatto, Margherita, Freitag-Wolf, Sandra, Fuchsberger, Christian, Galesloot, Tessel E., Gao, Yan, Gao, Zishan, Geller, Frank, Giannakopoulou, Olga, Giulianini, Franco, Gjesing, Anette P., Goel, Anuj, Gordon, Scott D., Gorski, Mathias, Grove, Jakob, Guo, Xiuqing, Gustafsson, Stefan, Haessler, Jeffrey, Hansen, Thomas F., Havulinna, Aki S., Haworth, Simon J., He, Jing, Heard-Costa, Nancy, Hebbar, Prashantha, Hindy, George, Ho, Yuk-Lam A., Hofer, Edith, Holliday, Elizabeth, Horn, Katrin, Hornsby, Whitney E., Hottenga, Jouke-Jan, Huang, Hongyan, Huang, Jie, Huerta-Chagoya, Alicia, Huffman, Jennifer E., Hung, Yi-Jen, Huo, Shaofeng, Hwang, Mi Yeong, Iha, Hiroyuki, Ikeda, Daisuke D., Isono, Masato, Jackson, Anne U., Jäger, Susanne, Jansen, Iris E., Johansson, Ingegerd, Jonas, Jost B., Jonsson, Anna, Jørgensen, Torben, Kalafati, Ioanna-Panagiota, Kanai, Masahiro, Kanoni, Stavroula, Kårhus, Line L., Kasturiratne, Anuradhani, Katsuya, Tomohiro, Kawaguchi, Takahisa, Kember, Rachel L., Kentistou, Katherine A., Kim, Han-Na, Kim, Young Jin, Kleber, Marcus E., Knol, Maria J., Kurbasic, Azra, Lauzon, Marie, Le, Phuong, Lea, Rodney, Lee, Jong-Young, Leonard, Hampton L., Li, Shengchao A., Li, Xiaohui, Li, Xiaoyin, Liang, Jingjing, Lin, Honghuang, Lin, Shih-Yi, Liu, Jun, Liu, Xueping, Lo, Ken Sin, Long, Jirong, Lores-Motta, Laura, Luan, Jian’an, Lyssenko, Valeriya, Lyytikäinen, Leo-Pekka, Mahajan, Anubha, Mamakou, Vasiliki, Mangino, Massimo, Manichaikul, Ani, Marten, Jonathan, Mattheisen, Manuel, Mavarani, Laven, McDaid, Aaron F., Meidtner, Karina, Melendez, Tori L., Mercader, Josep M., Milaneschi, Yuri, Miller, Jason E., Millwood, Iona Y., Mishra, Pashupati P., Mitchell, Ruth E., Møllehave, Line T., Morgan, Anna, Mucha, Soeren, Munz, Matthias, Nakatochi, Masahiro, Nelson, Christopher P., Nethander, Maria, Nho, Chu Won, Nielsen, Aneta A., Nolte, Ilja M., Nongmaithem, Suraj S., Noordam, Raymond, Ntalla, Ioanna, Nutile, Teresa, Pandit, Anita, Christofidou, Paraskevi, Pärna, Katri, Pauper, Marc, Petersen, Eva R. B., Petersen, Liselotte V., Pitkänen, Niina, Polašek, Ozren, Poveda, Alaitz, Preuss, Michael H., Pyarajan, Saiju, Raffield, Laura M., Rakugi, Hiromi, Ramirez, Julia, Rasheed, Asif, Raven, Dennis, Rayner, Nigel W., Riveros, Carlos, Rohde, Rebecca, Ruggiero, Daniela, Ruotsalainen, Sanni E., Ryan, Kathleen A., Sabater-Lleal, Maria, Saxena, Richa, Scholz, Markus, Sendamarai, Anoop, Shen, Botong, Shi, Jingchunzi, Shin, Jae Hun, Sidore, Carlo, Sitlani, Colleen M., Slieker, Roderick C., Smit, Roelof A. J., Smith, Albert V., Smith, Jennifer A., Smyth, Laura J., Southam, Lorraine, Steinthorsdottir, Valgerdur, Sun, Liang, Takeuchi, Fumihiko, Tallapragada, Divya Sri Priyanka, Taylor, Kent D., Tayo, Bamidele O., Tcheandjieu, Catherine, Terzikhan, Natalie, Tesolin, Paola, Teumer, Alexander, Theusch, Elizabeth, Thompson, Deborah J., Thorleifsson, Gudmar, Timmers, Paul R. H. J., Trompet, Stella, Turman, Constance, Vaccargiu, Simona, van der Laan, Sander W., van der Most, Peter J., van Klinken, Jan B., van Setten, Jessica, Verma, Shefali S., Verweij, Niek, Veturi, Yogasudha, Wang, Carol A., Wang, Chaolong, Wang, Lihua, Wang, Zhe, Warren, Helen R., Bin Wei, Wen, Wickremasinghe, Ananda R., Wielscher, Matthias, Wiggins, Kerri L., Winsvold, Bendik S., Wong, Andrew, Wu, Yang, Wuttke, Matthias, Xia, Rui, Xie, Tian, Yamamoto, Ken, Yang, Jingyun, Yao, Jie, Young, Hannah, Yousri, Noha A., Yu, Lei, Zeng, Lingyao, Zhang, Weihua, Zhang, Xinyuan, Zhao, Jing-Hua, Zhao, Wei, Zhou, Wei, Zimmermann, Martina E., Zoledziewska, Magdalena, Adair, Linda S., Adams, Hieab H. H., Aguilar-Salinas, Carlos A., Al-Mulla, Fahd, Arnett, Donna K., Asselbergs, Folkert W., Åsvold, Bjørn Olav, Attia, John, Banas, Bernhard, Bandinelli, Stefania, Bennett, David A., Bergler, Tobias, Bharadwaj, Dwaipayan, Biino, Ginevra, Bisgaard, Hans, Boerwinkle, Eric, Böger, Carsten A., Bønnelykke, Klaus, Boomsma, Dorret I., Børglum, Anders D., Borja, Judith B., Bouchard, Claude, Bowden, Donald W., Brandslund, Ivan, Brumpton, Ben, Buring, Julie E., Caulfield, Mark J., Chambers, John C., Chandak, Giriraj R., Chanock, Stephen J., Chaturvedi, Nish, Chen, Yii-Der Ida, Chen, Zhengming, Cheng, Ching-Yu, Christophersen, Ingrid E., Ciullo, Marina, Cole, John W., Collins, Francis S., Cooper, Richard S., Cruz, Miguel, Cucca, Francesco, Cupples, L. Adrienne, Cutler, Michael J., Damrauer, Scott M., Dantoft, Thomas M., de Borst, Gert J., de Groot, Lisette C. P. G. M., De Jager, Philip L., de Kleijn, Dominique P. V., Janaka de Silva, H., Dedoussis, George V., den Hollander, Anneke I., Du, Shufa, Easton, Douglas F., Elders, Petra J. M., Eliassen, A. Heather, Ellinor, Patrick T., Elmståhl, Sölve, Erdmann, Jeanette, Evans, Michele K., Fatkin, Diane, Feenstra, Bjarke, Feitosa, Mary F., Ferrucci, Luigi, Ford, Ian, Fornage, Myriam, Franke, Andre, Franks, Paul W., Freedman, Barry I., Gasparini, Paolo, Gieger, Christian, Girotto, Giorgia, Goddard, Michael E., Golightly, Yvonne M., Gonzalez-Villalpando, Clicerio, Gordon-Larsen, Penny, Grallert, Harald, Grant, Struan F. A., Grarup, Niels, Griffiths, Lyn, Gudnason, Vilmundur, Haiman, Christopher, Hakonarson, Hakon, Hansen, Torben, Hartman, Catharina A., Hattersley, Andrew T., Hayward, Caroline, Heckbert, Susan R., Heng, Chew-Kiat, Hengstenberg, Christian, Hewitt, Alex W., Hishigaki, Haretsugu, Hoyng, Carel B., Huang, Paul L., Huang, Wei, Hunt, Steven C., Hveem, Kristian, Hyppönen, Elina, Iacono, William G., Ichihara, Sahoko, Ikram, M. Arfan, Isasi, Carmen R., Jackson, Rebecca D., Jarvelin, Marjo-Riitta, Jin, Zi-Bing, Jöckel, Karl-Heinz, Joshi, Peter K., Jousilahti, Pekka, Jukema, J. Wouter, Kähönen, Mika, Kamatani, Yoichiro, Kang, Kui Dong, Kaprio, Jaakko, Kardia, Sharon L. R., Karpe, Fredrik, Kato, Norihiro, Kee, Frank, Kessler, Thorsten, Khera, Amit V., Khor, Chiea Chuen, Kiemeney, Lambertus A. L. M., Kim, Bong-Jo, Kim, Eung Kweon, Kim, Hyung-Lae, Kirchhof, Paulus, Kivimaki, Mika, Koh, Woon-Puay, Koistinen, Heikki A., Kolovou, Genovefa D., Kooner, Jaspal S., Kooperberg, Charles, Köttgen, Anna, Kovacs, Peter, Kraaijeveld, Adriaan, Kraft, Peter, Krauss, Ronald M., Kumari, Meena, Kutalik, Zoltan, Laakso, Markku, Lange, Leslie A., Langenberg, Claudia, Launer, Lenore J., Le Marchand, Loic, Lee, Hyejin, Lee, Nanette R., Lehtimäki, Terho, Li, Huaixing, Li, Liming, Lieb, Wolfgang, Lin, Xu, Lind, Lars, Linneberg, Allan, Liu, Ching-Ti, Liu, Jianjun, Loeffler, Markus, London, Barry, Lubitz, Steven A., Lye, Stephen J., Mackey, David A., Mägi, Reedik, Magnusson, Patrik K. E., Marcus, Gregory M., Vidal, Pedro Marques, Martin, Nicholas G., März, Winfried, Matsuda, Fumihiko, McGarrah, Robert W., McGue, Matt, McKnight, Amy Jayne, Medland, Sarah E., Mellström, Dan, Metspalu, Andres, Mitchell, Braxton D., Mitchell, Paul, Mook-Kanamori, Dennis O., Morris, Andrew D., Mucci, Lorelei A., Munroe, Patricia B., Nalls, Mike A., Nazarian, Saman, Nelson, Amanda E., Neville, Matt J., Newton-Cheh, Christopher, Nielsen, Christopher S., Nöthen, Markus M., Ohlsson, Claes, Oldehinkel, Albertine J., Orozco, Lorena, Pahkala, Katja, Pajukanta, Päivi, Palmer, Colin N. A., Parra, Esteban J., Pattaro, Cristian, Pedersen, Oluf, Pennell, Craig E., Penninx, Brenda W. J. H., Perusse, Louis, Peters, Annette, Peyser, Patricia A., Porteous, David J., Posthuma, Danielle, Power, Chris, Pramstaller, Peter P., Province, Michael A., Qi, Qibin, Qu, Jia, Rader, Daniel J., Raitakari, Olli T., Ralhan, Sarju, Rallidis, Loukianos S., Rao, Dabeeru C., Redline, Susan, Reilly, Dermot F., Reiner, Alexander P., Rhee, Sang Youl, Ridker, Paul M., Rienstra, Michiel, Ripatti, Samuli, Ritchie, Marylyn D., Roden, Dan M., Rosendaal, Frits R., Rotter, Jerome I., Rudan, Igor, Rutters, Femke, Sabanayagam, Charumathi, Saleheen, Danish, Salomaa, Veikko, Samani, Nilesh J., Sanghera, Dharambir K., Sattar, Naveed, Schmidt, Börge, Schmidt, Helena, Schmidt, Reinhold, Schulze, Matthias B., Schunkert, Heribert, Scott, Laura J., Scott, Rodney J., Sever, Peter, Shiroma, Eric J., Shoemaker, M. Benjamin, Shu, Xiao-Ou, Simonsick, Eleanor M., Sims, Mario, Singh, Jai Rup, Singleton, Andrew B., Sinner, Moritz F., Smith, J. Gustav, Snieder, Harold, Spector, Tim D., Stampfer, Meir J., Stark, Klaus J., Strachan, David P., ‘t Hart, Leen M., Tabara, Yasuharu, Tang, Hua, Tardif, Jean-Claude, Thanaraj, Thangavel A., Timpson, Nicholas J., Tönjes, Anke, Tremblay, Angelo, Tuomi, Tiinamaija, Tuomilehto, Jaakko, Tusié-Luna, Maria-Teresa, Uitterlinden, Andre G., van Dam, Rob M., van der Harst, Pim, Van der Velde, Nathalie, van Duijn, Cornelia M., van Schoor, Natasja M., Vitart, Veronique, Völker, Uwe, Vollenweider, Peter, Völzke, Henry, Wacher-Rodarte, Niels H., Walker, Mark, Wang, Ya Xing, Wareham, Nicholas J., Watanabe, Richard M., Watkins, Hugh, Weir, David R., Werge, Thomas M., Widen, Elisabeth, Wilkens, Lynne R., Willemsen, Gonneke, Willett, Walter C., Wilson, James F., Wong, Tien-Yin, Woo, Jeong-Taek, Wright, Alan F., Wu, Jer-Yuarn, Xu, Huichun, Yajnik, Chittaranjan S., Yokota, Mitsuhiro, Yuan, Jian-Min, Zeggini, Eleftheria, Zemel, Babette S., Zheng, Wei, Zhu, Xiaofeng, Zmuda, Joseph M., Zonderman, Alan B., Zwart, John-Anker, Chasman, Daniel I., Cho, Yoon Shin, Heid, Iris M., McCarthy, Mark I., Ng, Maggie C. Y., O’Donnell, Christopher J., Rivadeneira, Fernando, Thorsteinsdottir, Unnur, Sun, Yan V., Tai, E. Shyong, Boehnke, Michael, Deloukas, Panos, Justice, Anne E., Lindgren, Cecilia M., Loos, Ruth J. F., Mohlke, Karen L., North, Kari E., Stefansson, Kari, Walters, Robin G., Winkler, Thomas W., Young, Kristin L., Loh, Po-Ru, Yang, Jian, Esko, Tõnu, Assimes, Themistocles L., Auton, Adam, Abecasis, Goncalo R., Willer, Cristen J., Locke, Adam E., Berndt, Sonja I., Lettre, Guillaume, Frayling, Timothy M., Okada, Yukinori, Wood, Andrew R., Visscher, Peter M., and Hirschhorn, Joel N.

Published
2022
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24. Integrating Genetic and Transcriptomic Data to Identify Genes Underlying Obesity Risk Loci

Author

Xu, Hanfei, primary, Gupta, Shreyash, additional, Dinsmore, Ian, additional, Kollu, Abbey, additional, Cawley, Anne Marie, additional, Anwar, Mohammad Y., additional, Chen, Hung-Hsin, additional, Petty, Lauren E, additional, Seshadri, Sudha, additional, Graff, Misa, additional, Below, Piper, additional, Brody, Jennifer A, additional, Chittoor, Geetha, additional, Fisher-Hoch, Susan P, additional, Heard-Costa, Nancy L, additional, Levy, Daniel, additional, Lin, Honghuang, additional, Loos, Ruth JF, additional, Mccormick, Joseph B, additional, Rotter, Jerome I, additional, Mirshahi, Tooraj, additional, Still, Christopher D, additional, Destefano, Anita, additional, Cupples, L. Adrienne, additional, Mohlke, Karen L, additional, North, Kari E, additional, Justice, Anne E, additional, and Liu, Ching-Ti, additional

Published
2024
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25. Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls

Author

Flannick, Jason, Mercader, Josep M, Fuchsberger, Christian, Udler, Miriam S, Mahajan, Anubha, Wessel, Jennifer, Teslovich, Tanya M, Caulkins, Lizz, Koesterer, Ryan, Barajas-Olmos, Francisco, Blackwell, Thomas W, Boerwinkle, Eric, Brody, Jennifer A, Centeno-Cruz, Federico, Chen, Ling, Chen, Siying, Contreras-Cubas, Cecilia, Córdova, Emilio, Correa, Adolfo, Cortes, Maria, DeFronzo, Ralph A, Dolan, Lawrence, Drews, Kimberly L, Elliott, Amanda, Floyd, James S, Gabriel, Stacey, Garay-Sevilla, Maria Eugenia, García-Ortiz, Humberto, Gross, Myron, Han, Sohee, Heard-Costa, Nancy L, Jackson, Anne U, Jørgensen, Marit E, Kang, Hyun Min, Kelsey, Megan, Kim, Bong-Jo, Koistinen, Heikki A, Kuusisto, Johanna, Leader, Joseph B, Linneberg, Allan, Liu, Ching-Ti, Liu, Jianjun, Lyssenko, Valeriya, Manning, Alisa K, Marcketta, Anthony, Malacara-Hernandez, Juan Manuel, Martínez-Hernández, Angélica, Matsuo, Karen, Mayer-Davis, Elizabeth, Mendoza-Caamal, Elvia, Mohlke, Karen L, Morrison, Alanna C, Ndungu, Anne, Ng, Maggie CY, O’Dushlaine, Colm, Payne, Anthony J, Pihoker, Catherine, Post, Wendy S, Preuss, Michael, Psaty, Bruce M, Vasan, Ramachandran S, Rayner, N William, Reiner, Alexander P, Revilla-Monsalve, Cristina, Robertson, Neil R, Santoro, Nicola, Schurmann, Claudia, So, Wing Yee, Soberón, Xavier, Stringham, Heather M, Strom, Tim M, Tam, Claudia HT, Thameem, Farook, Tomlinson, Brian, Torres, Jason M, Tracy, Russell P, van Dam, Rob M, Vujkovic, Marijana, Wang, Shuai, Welch, Ryan P, Witte, Daniel R, Wong, Tien-Yin, Atzmon, Gil, Barzilai, Nir, Blangero, John, Bonnycastle, Lori L, Bowden, Donald W, Chambers, John C, Chan, Edmund, Cheng, Ching-Yu, Cho, Yoon Shin, Collins, Francis S, de Vries, Paul S, Duggirala, Ravindranath, Glaser, Benjamin, Gonzalez, Clicerio, Gonzalez, Ma Elena, Groop, Leif, Kooner, Jaspal Singh, and Kwak, Soo Heon

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Human Genome, Prevention, Biotechnology, Diabetes, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Animals, Case-Control Studies, Decision Support Techniques, Diabetes Mellitus, Type 2, Exome, Female, Gene Frequency, Genome-Wide Association Study, Humans, Male, Mice, Mice, Knockout, Exome Sequencing, Broad Genomics Platform, DiscovEHR Collaboration, CHARGE, LuCamp, ProDiGY, GoT2D, ESP, SIGMA-T2D, T2D-GENES, AMP-T2D-GENES, General Science & Technology
Abstract

Protein-coding genetic variants that strongly affect disease risk can yield relevant clues to disease pathogenesis. Here we report exome-sequencing analyses of 20,791 individuals with type 2 diabetes (T2D) and 24,440 non-diabetic control participants from 5 ancestries. We identify gene-level associations of rare variants (with minor allele frequencies of less than 0.5%) in 4 genes at exome-wide significance, including a series of more than 30 SLC30A8 alleles that conveys protection against T2D, and in 12 gene sets, including those corresponding to T2D drug targets (P = 6.1 × 10-3) and candidate genes from knockout mice (P = 5.2 × 10-3). Within our study, the strongest T2D gene-level signals for rare variants explain at most 25% of the heritability of the strongest common single-variant signals, and the gene-level effect sizes of the rare variants that we observed in established T2D drug targets will require 75,000-185,000 sequenced cases to achieve exome-wide significance. We propose a method to interpret these modest rare-variant associations and to incorporate these associations into future target or gene prioritization efforts.

Published
2019

26. Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution

Author

Justice, Anne E, Karaderi, Tugce, Highland, Heather M, Young, Kristin L, Graff, Mariaelisa, Lu, Yingchang, Turcot, Valérie, Auer, Paul L, Fine, Rebecca S, Guo, Xiuqing, Schurmann, Claudia, Lempradl, Adelheid, Marouli, Eirini, Mahajan, Anubha, Winkler, Thomas W, Locke, Adam E, Medina-Gomez, Carolina, Esko, Tõnu, Vedantam, Sailaja, Giri, Ayush, Lo, Ken Sin, Alfred, Tamuno, Mudgal, Poorva, Ng, Maggie CY, Heard-Costa, Nancy L, Feitosa, Mary F, Manning, Alisa K, Willems, Sara M, Sivapalaratnam, Suthesh, Abecasis, Goncalo, Alam, Dewan S, Allison, Matthew, Amouyel, Philippe, Arzumanyan, Zorayr, Balkau, Beverley, Bastarache, Lisa, Bergmann, Sven, Bielak, Lawrence F, Blüher, Matthias, Boehnke, Michael, Boeing, Heiner, Boerwinkle, Eric, Böger, Carsten A, Bork-Jensen, Jette, Bottinger, Erwin P, Bowden, Donald W, Brandslund, Ivan, Broer, Linda, Burt, Amber A, Butterworth, Adam S, Caulfield, Mark J, Cesana, Giancarlo, Chambers, John C, Chasman, Daniel I, Chen, Yii-Der Ida, Chowdhury, Rajiv, Christensen, Cramer, Chu, Audrey Y, Collins, Francis S, Cook, James P, Cox, Amanda J, Crosslin, David S, Danesh, John, de Bakker, Paul IW, Denus, Simon de, Mutsert, Renée de, Dedoussis, George, Demerath, Ellen W, Dennis, Joe G, Denny, Josh C, Di Angelantonio, Emanuele, Dörr, Marcus, Drenos, Fotios, Dubé, Marie-Pierre, Dunning, Alison M, Easton, Douglas F, Elliott, Paul, Evangelou, Evangelos, Farmaki, Aliki-Eleni, Feng, Shuang, Ferrannini, Ele, Ferrieres, Jean, Florez, Jose C, Fornage, Myriam, Fox, Caroline S, Franks, Paul W, Friedrich, Nele, Gan, Wei, Gandin, Ilaria, Gasparini, Paolo, Giedraitis, Vilmantas, Girotto, Giorgia, Gorski, Mathias, Grallert, Harald, Grarup, Niels, Grove, Megan L, Gustafsson, Stefan, Haessler, Jeff, Hansen, Torben, and Hattersley, Andrew T

Subjects
Clinical Research, Obesity, Genetics, Nutrition, Prevention, Biotechnology, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Cardiovascular, Animals, Body Fat Distribution, Body Mass Index, Case-Control Studies, Drosophila, Exome, Female, Gene Frequency, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Homeostasis, Humans, Lipids, Male, Proteins, Risk Factors, Waist-Hip Ratio, CHD Exome+ Consortium, Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium, EPIC-CVD Consortium, ExomeBP Consortium, Global Lipids Genetic Consortium, GoT2D Genes Consortium, InterAct, ReproGen Consortium, T2D-Genes Consortium, MAGIC Investigators, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF

Published
2019

27. Genome-wide association meta-analysis identifies 48 risk variants and highlights the role of the stria vascularis in hearing loss

Author

Metspalu, Andres, Nelis, Mari, Mägi, Reedik, Esko, Tõnu, Trpchevska, Natalia, Freidin, Maxim B., Broer, Linda, Oosterloo, Berthe C., Yao, Shuyang, Zhou, Yitian, Vona, Barbara, Bishop, Charles, Bizaki-Vallaskangas, Argyro, Canlon, Barbara, Castellana, Fabio, Chasman, Daniel I., Cherny, Stacey, Christensen, Kaare, Concas, Maria Pina, Correa, Adolfo, Elkon, Ran, Mengel-From, Jonas, Gao, Yan, Giersch, Anne B.S., Girotto, Giorgia, Gudjonsson, Alexander, Gudnason, Vilmundur, Heard-Costa, Nancy L., Hertzano, Ronna, Hjelmborg, Jacob v.B., Hjerling-Leffler, Jens, Hoffman, Howard J., Kaprio, Jaakko, Kettunen, Johannes, Krebs, Kristi, Kähler, Anna K., Lallemend, Francois, Launer, Lenore J., Lee, I-Min, Leonard, Hampton, Li, Chuan-Ming, Lowenheim, Hubert, Magnusson, Patrik K.E., van Meurs, Joyce, Milani, Lili, Morton, Cynthia C., Mäkitie, Antti, Nalls, Mike A., Nardone, Giuseppe Giovanni, Nygaard, Marianne, Palviainen, Teemu, Pratt, Sheila, Quaranta, Nicola, Rämö, Joel, Saarentaus, Elmo, Sardone, Rodolfo, Satizabal, Claudia L., Schweinfurth, John M., Seshadri, Sudha, Shiroma, Eric, Shulman, Eldad, Simonsick, Eleanor, Spankovich, Christopher, Tropitzsch, Anke, Lauschke, Volker M., Sullivan, Patrick F., Goedegebure, Andre, Cederroth, Christopher R., Williams, Frances M.K., and Nagtegaal, Andries Paul

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

Author

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

Published
2022
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30. Association of Severe Hypercholesterolemia and Familial Hypercholesterolemia Genotype With Risk of Coronary Heart Disease

Author

Zhang, Yiyi, Dron, Jacqueline S., Bellows, Brandon K., Khera, Amit V., Liu, Junxiu, Balte, Pallavi P., Oelsner, Elizabeth C., Amr, Sami Samir, Lebo, Matthew S., Nagy, Anna, Peloso, Gina M., Natarajan, Pradeep, Rotter, Jerome I., Willer, Cristen, Boerwinkle, Eric, Ballantyne, Christie M., Lutsey, Pamela L., Fornage, Myriam, Lloyd-Jones, Donald M., Hou, Lifang, Psaty, Bruce M., Bis, Joshua C., Floyd, James S., Vasan, Ramachandran S., Heard-Costa, Nancy L., Carson, April P., Hall, Michael E., Rich, Stephen S., Guo, Xiuqing, Kazi, Dhruv S., de Ferranti, Sarah D., and Moran, Andrew E.

Published
2023
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32. De novo mutations across 1,465 diverse genomes reveal mutational insights and reductions in the Amish founder population

Author

National Heart Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Population Genetics Working Group, Kessler, Michael D., Loesch, Douglas P., Perry, James A., Heard-Costa, Nancy L., Taliun, Daniel, Cade, Brian E., Wang, Heming, Daya, Michelle, Ziniti, John, Datta, Soma, Celedón, Juan C., Soto-Quiros, Manuel E., Avila, Lydiana, Weiss, Scott T., Barnes, Kathleen, Redline, Susan S., Vasan, Ramachandran S., Johnson, Andrew D., Mathias, Rasika A., Hernandez, Ryan, Wilson, James G., Nickerson, Deborah A., Abecasis, Goncalo, Browning, Sharon R., Zöllne, Sebastian, O’Connell, Jeffrey R., Mitchell, Braxton D., and O’Connor, Timothy D.

Published
2020

33. Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults.

Author

Graff, Mariaelisa, Scott, Robert A, Justice, Anne E, Young, Kristin L, Feitosa, Mary F, Barata, Llilda, Winkler, Thomas W, Chu, Audrey Y, Mahajan, Anubha, Hadley, David, Xue, Luting, Workalemahu, Tsegaselassie, Heard-Costa, Nancy L, den Hoed, Marcel, Ahluwalia, Tarunveer S, Qi, Qibin, Ngwa, Julius S, Renström, Frida, Quaye, Lydia, Eicher, John D, Hayes, James E, Cornelis, Marilyn, Kutalik, Zoltan, Lim, Elise, Luan, Jian'an, Huffman, Jennifer E, Zhang, Weihua, Zhao, Wei, Griffin, Paula J, Haller, Toomas, Ahmad, Shafqat, Marques-Vidal, Pedro M, Bien, Stephanie, Yengo, Loic, Teumer, Alexander, Smith, Albert Vernon, Kumari, Meena, Harder, Marie Neergaard, Justesen, Johanne Marie, Kleber, Marcus E, Hollensted, Mette, Lohman, Kurt, Rivera, Natalia V, Whitfield, John B, Zhao, Jing Hua, Stringham, Heather M, Lyytikäinen, Leo-Pekka, Huppertz, Charlotte, Willemsen, Gonneke, Peyrot, Wouter J, Wu, Ying, Kristiansson, Kati, Demirkan, Ayse, Fornage, Myriam, Hassinen, Maija, Bielak, Lawrence F, Cadby, Gemma, Tanaka, Toshiko, Mägi, Reedik, van der Most, Peter J, Jackson, Anne U, Bragg-Gresham, Jennifer L, Vitart, Veronique, Marten, Jonathan, Navarro, Pau, Bellis, Claire, Pasko, Dorota, Johansson, Åsa, Snitker, Søren, Cheng, Yu-Ching, Eriksson, Joel, Lim, Unhee, Aadahl, Mette, Adair, Linda S, Amin, Najaf, Balkau, Beverley, Auvinen, Juha, Beilby, John, Bergman, Richard N, Bergmann, Sven, Bertoni, Alain G, Blangero, John, Bonnefond, Amélie, Bonnycastle, Lori L, Borja, Judith B, Brage, Søren, Busonero, Fabio, Buyske, Steve, Campbell, Harry, Chines, Peter S, Collins, Francis S, Corre, Tanguy, Smith, George Davey, Delgado, Graciela E, Dueker, Nicole, Dörr, Marcus, Ebeling, Tapani, Eiriksdottir, Gudny, Esko, Tõnu, and Faul, Jessica D

Subjects
CHARGE Consortium, EPIC-InterAct Consortium, PAGE Consortium, Humans, Obesity, Genetic Predisposition to Disease, Body Mass Index, Waist-Hip Ratio, Exercise, Genotype, Female, Male, Adiposity, Waist Circumference, Genome-Wide Association Study, Epigenomics, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Genetics, Developmental Biology
Abstract

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.

Published
2017

34. Multiethnic genome-wide meta-analysis of ectopic fat depots identifies loci associated with adipocyte development and differentiation

Author

Chu, Audrey Y, Deng, Xuan, Fisher, Virginia A, Drong, Alexander, Zhang, Yang, Feitosa, Mary F, Liu, Ching-Ti, Weeks, Olivia, Choh, Audrey C, Duan, Qing, Dyer, Thomas D, Eicher, John D, Guo, Xiuqing, Heard-Costa, Nancy L, Kacprowski, Tim, Kent, Jack W, Lange, Leslie A, Liu, Xinggang, Lohman, Kurt, Lu, Lingyi, Mahajan, Anubha, O'Connell, Jeffrey R, Parihar, Ankita, Peralta, Juan M, Smith, Albert V, Zhang, Yi, Homuth, Georg, Kissebah, Ahmed H, Kullberg, Joel, Laqua, René, Launer, Lenore J, Nauck, Matthias, Olivier, Michael, Peyser, Patricia A, Terry, James G, Wojczynski, Mary K, Yao, Jie, Bielak, Lawrence F, Blangero, John, Borecki, Ingrid B, Bowden, Donald W, Carr, John Jeffrey, Czerwinski, Stefan A, Ding, Jingzhong, Friedrich, Nele, Gudnason, Vilmunder, Harris, Tamara B, Ingelsson, Erik, Johnson, Andrew D, Kardia, Sharon LR, Langefeld, Carl D, Lind, Lars, Liu, Yongmei, Mitchell, Braxton D, Morris, Andrew P, Mosley, Thomas H, Rotter, Jerome I, Shuldiner, Alan R, Towne, Bradford, Völzke, Henry, Wallaschofski, Henri, Wilson, James G, Allison, Matthew, Lindgren, Cecilia M, Goessling, Wolfram, Cupples, L Adrienne, Steinhauser, Matthew L, and Fox, Caroline S

Subjects
Nutrition, Human Genome, Genetics, Adipocytes, Animals, Body Fat Distribution, Cell Differentiation, Cohort Studies, Ethnicity, Female, Genetic Loci, Genetic Markers, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Mice, Mice, Inbred C57BL, Obesity, Phenotype, Polymorphism, Single Nucleotide, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Variation in body fat distribution contributes to the metabolic sequelae of obesity. The genetic determinants of body fat distribution are poorly understood. The goal of this study was to gain new insights into the underlying genetics of body fat distribution by conducting sample-size-weighted fixed-effects genome-wide association meta-analyses in up to 9,594 women and 8,738 men of European, African, Hispanic and Chinese ancestry, with and without sex stratification, for six traits associated with ectopic fat (hereinafter referred to as ectopic-fat traits). In total, we identified seven new loci associated with ectopic-fat traits (ATXN1, UBE2E2, EBF1, RREB1, GSDMB, GRAMD3 and ENSA; P < 5 × 10-8; false discovery rate < 1%). Functional analysis of these genes showed that loss of function of either Atxn1 or Ube2e2 in primary mouse adipose progenitor cells impaired adipocyte differentiation, suggesting physiological roles for ATXN1 and UBE2E2 in adipogenesis. Future studies are necessary to further explore the mechanisms by which these genes affect adipocyte biology and how their perturbations contribute to systemic metabolic disease.

Published
2017

35. Key variants via the Alzheimer's Disease Sequencing Project whole genome sequence data

Author

Wang, Yanbing, Sarnowski, Chloé, Lin, Honghuang, Pitsillides, Achilleas N., Heard-Costa, Nancy L., Choi, Seung Hoan, Wang, Dongyu, Bis, Joshua C., Blue, Elizabeth E., Alzheimer's Disease Neuroimaging Initiative (ADNI), Boerwinkle, Eric, De Jager, Philip L., Fornage, Myriam, Wijsman, Ellen M., Seshadri, Sudha, Dupuis, Josée, Peloso, Gina M., DeStefano, Anita L., Alzheimer's Disease Sequencing Project (ADSP), Wang, Yanbing, Sarnowski, Chloé, Lin, Honghuang, Pitsillides, Achilleas N., Heard-Costa, Nancy L., Choi, Seung Hoan, Wang, Dongyu, Bis, Joshua C., Blue, Elizabeth E., Alzheimer's Disease Neuroimaging Initiative (ADNI), Boerwinkle, Eric, De Jager, Philip L., Fornage, Myriam, Wijsman, Ellen M., Seshadri, Sudha, Dupuis, Josée, Peloso, Gina M., DeStefano, Anita L., and Alzheimer's Disease Sequencing Project (ADSP)

Abstract

INTRODUCTION Genome-wide association studies (GWAS) have identified loci associated with Alzheimer's disease (AD) but did not identify specific causal genes or variants within those loci. Analysis of whole genome sequence (WGS) data, which interrogates the entire genome and captures rare variations, may identify causal variants within GWAS loci. METHODS We performed single common variant association analysis and rare variant aggregate analyses in the pooled population (N cases = 2184, N controls = 2383) and targeted analyses in subpopulations using WGS data from the Alzheimer's Disease Sequencing Project (ADSP). The analyses were restricted to variants within 100 kb of 83 previously identified GWAS lead variants. RESULTS Seventeen variants were significantly associated with AD within five genomic regions implicating the genes OARD1/NFYA/TREML1, JAZF1, FERMT2, and SLC24A4. KAT8 was implicated by both single variant and rare variant aggregate analyses. DISCUSSION This study demonstrates the utility of leveraging WGS to gain insights into AD loci identified via GWAS.

Published
2024

36. Familial Hypercholesterolemia Variant and Cardiovascular Risk in Individuals With Elevated Cholesterol

Author

Zhang, Yiyi, primary, Dron, Jacqueline S., additional, Bellows, Brandon K., additional, Khera, Amit V., additional, Liu, Junxiu, additional, Balte, Pallavi P., additional, Oelsner, Elizabeth C., additional, Amr, Sami Samir, additional, Lebo, Matthew S., additional, Nagy, Anna, additional, Peloso, Gina M., additional, Natarajan, Pradeep, additional, Rotter, Jerome I., additional, Willer, Cristen, additional, Boerwinkle, Eric, additional, Ballantyne, Christie M., additional, Lutsey, Pamela L., additional, Fornage, Myriam, additional, Lloyd-Jones, Donald M., additional, Hou, Lifang, additional, Psaty, Bruce M., additional, Bis, Joshua C., additional, Floyd, James S., additional, Vasan, Ramachandran S., additional, Heard-Costa, Nancy L., additional, Carson, April P., additional, Hall, Michael E., additional, Rich, Stephen S., additional, Guo, Xiuqing, additional, Kazi, Dhruv S., additional, de Ferranti, Sarah D., additional, and Moran, Andrew E., additional

Published
2024
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37. Rare variant associations with waist-to-hip ratio in European-American and African-American women from the NHLBI-Exome Sequencing Project

Author

Kan, Mengyuan, Auer, Paul L, Wang, Gao T, Bucasas, Kristine L, Hooker, Stanley, Rodriguez, Alejandra, Li, Biao, Ellis, Jaclyn, Adrienne Cupples, L, Ida Chen, Yii-Der, Dupuis, Josée, Fox, Caroline S, Gross, Myron D, Smith, Joshua D, Heard-Costa, Nancy, Meigs, James B, Pankow, James S, Rotter, Jerome I, Siscovick, David, Wilson, James G, Shendure, Jay, Jackson, Rebecca, Peters, Ulrike, Zhong, Hua, Lin, Danyu, Hsu, Li, Franceschini, Nora, Carlson, Chris, Abecasis, Goncalo, Gabriel, Stacey, Bamshad, Michael J, Altshuler, David, Nickerson, Deborah A, North, Kari E, Lange, Leslie A, Reiner, Alexander P, and Leal, Suzanne M

Subjects
Biological Sciences, Genetics, Prevention, Human Genome, Obesity, Clinical Research, Diabetes, 2.1 Biological and endogenous factors, Aetiology, Cardiovascular, Metabolic and endocrine, Adult, Black or African American, Aged, Aged, 80 and over, Alleles, Exome, Female, Humans, I-kappa B Kinase, Middle Aged, Polymorphism, Genetic, Transcription Factors, Waist-Hip Ratio, White People, NHLBI-Exome Sequencing Project, Clinical Sciences, Genetics & Heredity, Clinical sciences
Abstract

Waist-to-hip ratio (WHR), a relative comparison of waist and hip circumferences, is an easily accessible measurement of body fat distribution, in particular central abdominal fat. A high WHR indicates more intra-abdominal fat deposition and is an established risk factor for cardiovascular disease and type 2 diabetes. Recent genome-wide association studies have identified numerous common genetic loci influencing WHR, but the contributions of rare variants have not been previously reported. We investigated rare variant associations with WHR in 1510 European-American and 1186 African-American women from the National Heart, Lung, and Blood Institute-Exome Sequencing Project. Association analysis was performed on the gene level using several rare variant association methods. The strongest association was observed for rare variants in IKBKB (P=4.0 × 10(-8)) in European-Americans, where rare variants in this gene are predicted to decrease WHRs. The activation of the IKBKB gene is involved in inflammatory processes and insulin resistance, which may affect normal food intake and body weight and shape. Meanwhile, aggregation of rare variants in COBLL1, previously found to harbor common variants associated with WHR and fasting insulin, were nominally associated (P=2.23 × 10(-4)) with higher WHR in European-Americans. However, these significant results are not shared between African-Americans and European-Americans that may be due to differences in the allelic architecture of the two populations and the small sample sizes. Our study indicates that the combined effect of rare variants contribute to the inter-individual variation in fat distribution through the regulation of insulin response.

Published
2016

39. The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study.

Author

Winkler, Thomas W, Justice, Anne E, Graff, Mariaelisa, Barata, Llilda, Feitosa, Mary F, Chu, Su, Czajkowski, Jacek, Esko, Tõnu, Fall, Tove, Kilpeläinen, Tuomas O, Lu, Yingchang, Mägi, Reedik, Mihailov, Evelin, Pers, Tune H, Rüeger, Sina, Teumer, Alexander, Ehret, Georg B, Ferreira, Teresa, Heard-Costa, Nancy L, Karjalainen, Juha, Lagou, Vasiliki, Mahajan, Anubha, Neinast, Michael D, Prokopenko, Inga, Simino, Jeannette, Teslovich, Tanya M, Jansen, Rick, Westra, Harm-Jan, White, Charles C, Absher, Devin, Ahluwalia, Tarunveer S, Ahmad, Shafqat, Albrecht, Eva, Alves, Alexessander Couto, Bragg-Gresham, Jennifer L, de Craen, Anton JM, Bis, Joshua C, Bonnefond, Amélie, Boucher, Gabrielle, Cadby, Gemma, Cheng, Yu-Ching, Chiang, Charleston WK, Delgado, Graciela, Demirkan, Ayse, Dueker, Nicole, Eklund, Niina, Eiriksdottir, Gudny, Eriksson, Joel, Feenstra, Bjarke, Fischer, Krista, Frau, Francesca, Galesloot, Tessel E, Geller, Frank, Goel, Anuj, Gorski, Mathias, Grammer, Tanja B, Gustafsson, Stefan, Haitjema, Saskia, Hottenga, Jouke-Jan, Huffman, Jennifer E, Jackson, Anne U, Jacobs, Kevin B, Johansson, Åsa, Kaakinen, Marika, Kleber, Marcus E, Lahti, Jari, Mateo Leach, Irene, Lehne, Benjamin, Liu, Youfang, Lo, Ken Sin, Lorentzon, Mattias, Luan, Jian'an, Madden, Pamela AF, Mangino, Massimo, McKnight, Barbara, Medina-Gomez, Carolina, Monda, Keri L, Montasser, May E, Müller, Gabriele, Müller-Nurasyid, Martina, Nolte, Ilja M, Panoutsopoulou, Kalliope, Pascoe, Laura, Paternoster, Lavinia, Rayner, Nigel W, Renström, Frida, Rizzi, Federica, Rose, Lynda M, Ryan, Kathy A, Salo, Perttu, Sanna, Serena, Scharnagl, Hubert, Shi, Jianxin, Smith, Albert Vernon, Southam, Lorraine, Stančáková, Alena, Steinthorsdottir, Valgerdur, Strawbridge, Rona J, Sung, Yun Ju, and Tachmazidou, Ioanna

Subjects
CHARGE Consortium, DIAGRAM Consortium, GLGC Consortium, Global-BPGen Consortium, ICBP Consortium, MAGIC Consortium, Humans, Genetic Predisposition to Disease, Body Mass Index, Body Size, Waist-Hip Ratio, Chromosome Mapping, Age Factors, Sex Characteristics, Polymorphism, Single Nucleotide, Adult, Aged, Middle Aged, European Continental Ancestry Group, Female, Male, Genome-Wide Association Study, Developmental Biology, Genetics
Abstract

Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR

Published
2015

40. New genetic loci link adipose and insulin biology to body fat distribution

Author

Shungin, Dmitry, Winkler, Thomas W, Croteau-Chonka, Damien C, Ferreira, Teresa, Locke, Adam E, Mägi, Reedik, Strawbridge, Rona J, Pers, Tune H, Fischer, Krista, Justice, Anne E, Workalemahu, Tsegaselassie, Wu, Joseph MW, Buchkovich, Martin L, Heard-Costa, Nancy L, Roman, Tamara S, Drong, Alexander W, Song, Ci, Gustafsson, Stefan, Day, Felix R, Esko, Tonu, Fall, Tove, Kutalik, Zoltán, Luan, Jian’an, Randall, Joshua C, Scherag, André, Vedantam, Sailaja, Wood, Andrew R, Chen, Jin, Fehrmann, Rudolf, Karjalainen, Juha, Kahali, Bratati, Liu, Ching-Ti, Schmidt, Ellen M, Absher, Devin, Amin, Najaf, Anderson, Denise, Beekman, Marian, Bragg-Gresham, Jennifer L, Buyske, Steven, Demirkan, Ayse, Ehret, Georg B, Feitosa, Mary F, Goel, Anuj, Jackson, Anne U, Johnson, Toby, Kleber, Marcus E, Kristiansson, Kati, Mangino, Massimo, Mateo Leach, Irene, Medina-Gomez, Carolina, Palmer, Cameron D, Pasko, Dorota, Pechlivanis, Sonali, Peters, Marjolein J, Prokopenko, Inga, Stančáková, Alena, Ju Sung, Yun, Tanaka, Toshiko, Teumer, Alexander, Van Vliet-Ostaptchouk, Jana V, Yengo, Loïc, Zhang, Weihua, Albrecht, Eva, Ärnlöv, Johan, Arscott, Gillian M, Bandinelli, Stefania, Barrett, Amy, Bellis, Claire, Bennett, Amanda J, Berne, Christian, Blüher, Matthias, Böhringer, Stefan, Bonnet, Fabrice, Böttcher, Yvonne, Bruinenberg, Marcel, Carba, Delia B, Caspersen, Ida H, Clarke, Robert, Warwick Daw, E, Deelen, Joris, Deelman, Ewa, Delgado, Graciela, Doney, Alex SF, Eklund, Niina, Erdos, Michael R, Estrada, Karol, Eury, Elodie, Friedrich, Nele, Garcia, Melissa E, Giedraitis, Vilmantas, Gigante, Bruna, Go, Alan S, Golay, Alain, Grallert, Harald, Grammer, Tanja B, Gräßler, Jürgen, Grewal, Jagvir, Groves, Christopher J, Haller, Toomas, and Hallmans, Goran

Subjects
Genetics, Human Genome, Diabetes, Obesity, Nutrition, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Cardiovascular, Stroke, Adipocytes, Adipogenesis, Adipose Tissue, Age Factors, Body Fat Distribution, Body Mass Index, Epigenesis, Genetic, Europe, Female, Genome, Human, Genome-Wide Association Study, Humans, Insulin, Insulin Resistance, Male, Models, Biological, Neovascularization, Physiologic, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Racial Groups, Sex Characteristics, Transcription, Genetic, Waist-Hip Ratio, ADIPOGen Consortium, CARDIOGRAMplusC4D Consortium, CKDGen Consortium, GEFOS Consortium, GENIE Consortium, GLGC, ICBP, International Endogene Consortium, LifeLines Cohort Study, MAGIC Investigators, MuTHER Consortium, PAGE Consortium, ReproGen Consortium, General Science & Technology
Abstract

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P

Published
2015

41. Association of Common and Rare Variants with Alzheimer's Disease in over 13,000 Diverse Individuals with Whole-Genome Sequencing from the Alzheimer's Disease Sequencing Project

Author

Lee, Wan-Ping, primary, Choi, Seung Hoan, additional, Shea, Margaret G, additional, Cheng, Po-Liang, additional, Dombroski, Beth A, additional, Pitsillides, Achilleas N, additional, Heard-Costa, Nancy L, additional, Wang, Hui, additional, Bulekova, Katia, additional, Kuzma, Amanda B, additional, Leung, Yuk Yee, additional, Farrell, John J, additional, Lin, Honghuang, additional, Naj, Adam, additional, Blue, Elizabeth E, additional, Nusetor, Frederick, additional, Wang, Dongyu, additional, Boerwinkle, Eric, additional, Bush, William S, additional, Zhang, Xiaoling, additional, De Jager, Philip L, additional, Dupuis, Josee, additional, Farrer, Lindsay A, additional, Fornage, Myriam, additional, Martin, Eden, additional, Pericak-Vance, Margaret, additional, Seshadri, Sudha, additional, Wijsman, Ellen M, additional, Wang, Li-San, additional, Schellenberg, Gerard D, additional, Destefano, Anita L, additional, Haines, Jonathan L, additional, and Peloso, Gina M, additional

Published
2023
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43. Genome-Wide Association of Pericardial Fat Identifies a Unique Locus for Ectopic Fat

Author

Fox, Caroline S, White, Charles C, Lohman, Kurt, Heard-Costa, Nancy, Cohen, Paul, Zhang, Yingying, Johnson, Andrew D, Emilsson, Valur, Liu, Ching-Ti, Chen, Y-D Ida, Taylor, Kent D, Allison, Matthew, Budoff, Matthew, Rotter, Jerome I, Carr, J Jeffrey, Hoffmann, Udo, Ding, Jingzhong, Cupples, L Adrienne, and Liu, Yongmei

Subjects
Biological Sciences, Genetics, Atherosclerosis, Prevention, Heart Disease, Aging, Nutrition, Obesity, Cardiovascular, Metabolic and endocrine, Adipose Tissue, Adult, Animals, Asian People, Black People, Body Fat Distribution, Body Mass Index, Calcium-Calmodulin-Dependent Protein Kinases, Coronary Disease, Female, Gene Expression Regulation, Genome-Wide Association Study, Hispanic or Latino, Humans, Intra-Abdominal Fat, Intracellular Signaling Peptides and Proteins, Male, Mice, Middle Aged, Pericardium, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Tomography, X-Ray Computed, White People, CARDIoGRAM Consortium, Developmental Biology
Abstract

Pericardial fat is a localized fat depot associated with coronary artery calcium and myocardial infarction. We hypothesized that genetic loci would be associated with pericardial fat independent of other body fat depots. Pericardial fat was quantified in 5,487 individuals of European ancestry from the Framingham Heart Study (FHS) and the Multi-Ethnic Study of Atherosclerosis (MESA). Genotyping was performed using standard arrays and imputed to ~2.5 million Hapmap SNPs. Each study performed a genome-wide association analysis of pericardial fat adjusted for age, sex, weight, and height. A weighted z-score meta-analysis was conducted, and validation was obtained in an additional 3,602 multi-ethnic individuals from the MESA study. We identified a genome-wide significant signal in our primary meta-analysis at rs10198628 near TRIB2 (MAF 0.49, p = 2.7 × 10(-08)). This SNP was not associated with visceral fat (p = 0.17) or body mass index (p = 0.38), although we observed direction-consistent, nominal significance with visceral fat adjusted for BMI (p = 0.01) in the Framingham Heart Study. Our findings were robust among African ancestry (n = 1,442, p = 0.001), Hispanic (n = 1,399, p = 0.004), and Chinese (n = 761, p = 0.007) participants from the MESA study, with a combined p-value of 5.4E-14. We observed TRIB2 gene expression in the pericardial fat of mice. rs10198628 near TRIB2 is associated with pericardial fat but not measures of generalized or visceral adiposity, reinforcing the concept that there are unique genetic underpinnings to ectopic fat distribution.

Published
2012

44. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index

Author

Speliotes, Elizabeth K, Willer, Cristen J, Berndt, Sonja I, Monda, Keri L, Thorleifsson, Gudmar, Jackson, Anne U, Allen, Hana Lango, Lindgren, Cecilia M, Luan, Jian'an, Mägi, Reedik, Randall, Joshua C, Vedantam, Sailaja, Winkler, Thomas W, Qi, Lu, Workalemahu, Tsegaselassie, Heid, Iris M, Steinthorsdottir, Valgerdur, Stringham, Heather M, Weedon, Michael N, Wheeler, Eleanor, Wood, Andrew R, Ferreira, Teresa, Weyant, Robert J, Segrè, Ayellet V, Estrada, Karol, Liang, Liming, Nemesh, James, Park, Ju-Hyun, Gustafsson, Stefan, Kilpeläinen, Tuomas O, Yang, Jian, Bouatia-Naji, Nabila, Esko, Tõnu, Feitosa, Mary F, Kutalik, Zoltán, Mangino, Massimo, Raychaudhuri, Soumya, Scherag, Andre, Smith, Albert Vernon, Welch, Ryan, Zhao, Jing Hua, Aben, Katja K, Absher, Devin M, Amin, Najaf, Dixon, Anna L, Fisher, Eva, Glazer, Nicole L, Goddard, Michael E, Heard-Costa, Nancy L, Hoesel, Volker, Hottenga, Jouke-Jan, Johansson, Åsa, Johnson, Toby, Ketkar, Shamika, Lamina, Claudia, Li, Shengxu, Moffatt, Miriam F, Myers, Richard H, Narisu, Narisu, Perry, John RB, Peters, Marjolein J, Preuss, Michael, Ripatti, Samuli, Rivadeneira, Fernando, Sandholt, Camilla, Scott, Laura J, Timpson, Nicholas J, Tyrer, Jonathan P, van Wingerden, Sophie, Watanabe, Richard M, White, Charles C, Wiklund, Fredrik, Barlassina, Christina, Chasman, Daniel I, Cooper, Matthew N, Jansson, John-Olov, Lawrence, Robert W, Pellikka, Niina, Prokopenko, Inga, Shi, Jianxin, Thiering, Elisabeth, Alavere, Helene, Alibrandi, Maria TS, Almgren, Peter, Arnold, Alice M, Aspelund, Thor, Atwood, Larry D, Balkau, Beverley, Balmforth, Anthony J, Bennett, Amanda J, Ben-Shlomo, Yoav, Bergman, Richard N, Bergmann, Sven, Biebermann, Heike, Blakemore, Alexandra IF, Boes, Tanja, Bonnycastle, Lori L, Bornstein, Stefan R, Brown, Morris J, and Buchanan, Thomas A

Subjects
Biological Sciences, Genetics, Prevention, Human Genome, Body Height, Body Mass Index, Body Size, Body Weight, Chromosome Mapping, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Obesity, Polymorphism, Single Nucleotide, White People, MAGIC, Procardis Consortium, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼ 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10⁻⁸), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.

Published
2010

45. Hundreds of variants clustered in genomic loci and biological pathways affect human height

Author

Lango Allen, Hana, Estrada, Karol, Lettre, Guillaume, Berndt, Sonja I, Weedon, Michael N, Rivadeneira, Fernando, Willer, Cristen J, Jackson, Anne U, Vedantam, Sailaja, Raychaudhuri, Soumya, Ferreira, Teresa, Wood, Andrew R, Weyant, Robert J, Segrè, Ayellet V, Speliotes, Elizabeth K, Wheeler, Eleanor, Soranzo, Nicole, Park, Ju-Hyun, Yang, Jian, Gudbjartsson, Daniel, Heard-Costa, Nancy L, Randall, Joshua C, Qi, Lu, Vernon Smith, Albert, Mägi, Reedik, Pastinen, Tomi, Liang, Liming, Heid, Iris M, Luan, Jian’an, Thorleifsson, Gudmar, Winkler, Thomas W, Goddard, Michael E, Sin Lo, Ken, Palmer, Cameron, Workalemahu, Tsegaselassie, Aulchenko, Yurii S, Johansson, Åsa, Carola Zillikens, M, Feitosa, Mary F, Esko, Tõnu, Johnson, Toby, Ketkar, Shamika, Kraft, Peter, Mangino, Massimo, Prokopenko, Inga, Absher, Devin, Albrecht, Eva, Ernst, Florian, Glazer, Nicole L, Hayward, Caroline, Hottenga, Jouke-Jan, Jacobs, Kevin B, Knowles, Joshua W, Kutalik, Zoltán, Monda, Keri L, Polasek, Ozren, Preuss, Michael, Rayner, Nigel W, Robertson, Neil R, Steinthorsdottir, Valgerdur, Tyrer, Jonathan P, Voight, Benjamin F, Wiklund, Fredrik, Xu, Jianfeng, Hua Zhao, Jing, Nyholt, Dale R, Pellikka, Niina, Perola, Markus, Perry, John RB, Surakka, Ida, Tammesoo, Mari-Liis, Altmaier, Elizabeth L, Amin, Najaf, Aspelund, Thor, Bhangale, Tushar, Boucher, Gabrielle, Chasman, Daniel I, Chen, Constance, Coin, Lachlan, Cooper, Matthew N, Dixon, Anna L, Gibson, Quince, Grundberg, Elin, Hao, Ke, Juhani Junttila, M, Kaplan, Lee M, Kettunen, Johannes, König, Inke R, Kwan, Tony, Lawrence, Robert W, Levinson, Douglas F, Lorentzon, Mattias, McKnight, Barbara, Morris, Andrew P, Müller, Martina, Suh Ngwa, Julius, Purcell, Shaun, Rafelt, Suzanne, Salem, Rany M, and Salvi, Erika

Subjects
Biological Sciences, Genetics, Health Sciences, Mathematical Sciences, Statistics, Human Genome, Clinical Research, Biotechnology, Aetiology, 2.1 Biological and endogenous factors, Body Height, Chromosomes, Human, Pair 3, Genetic Loci, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Metabolic Networks and Pathways, Multifactorial Inheritance, Phenotype, Polymorphism, Single Nucleotide, General Science & Technology
Abstract

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P

Published
2010

46. Carriers of rare damaging CCR2 genetic variants are at lower risk of atherosclerotic disease

Author

Georgakis, Marios K, primary, Malik, Rainer, additional, Hasbani, Natalie R, additional, Shakt, Gabrielle, additional, Morrison, Alanna, additional, Tsao, Noah L, additional, Judy, Renae, additional, Mitchell, Braxton D, additional, Xu, Huichun, additional, Montasser, May E, additional, Do, Ron, additional, Kenny, Eimear, additional, Loos, Ruth J.F., additional, Terry, James G, additional, Carr, John Jeffrey, additional, Bis, Joshua C., additional, Psaty, Bruce M., additional, Longstreth, W T, additional, Young, Kendra, additional, Lutz, Sharon M, additional, Cho, Michael, additional, Broome, Jai, additional, Khan, Alyna T, additional, Wang, Fei Fei, additional, Heard-Costa, Nancy, additional, Seshadri, Sudha, additional, Ramachandran, Vasan, additional, Palmer, Nicholette D., additional, Freedman, Barry I, additional, Bowden, Donald W, additional, Yanek, Lisa R, additional, Kral, Brian G, additional, Becker, Lewis C, additional, Peyser, Patricia A, additional, Bielak, Lawrence F, additional, Ammous, Farah, additional, Carson, April P., additional, Hall, Michael E, additional, Raffield, Laura M, additional, Rich, Steve, additional, Post, Wendy, additional, Tracy, Russell, additional, Taylor, Kent, additional, Guo, Xiuqing, additional, Mahaney, Michael, additional, Curran, Joanne E., additional, Blangero, John, additional, Clarke, Shoa L., additional, Haessler, Jeffrey, additional, Hu, Yao, additional, Assimes, Themistocles L, additional, Kooperberg, Charles, additional, Damrauer, Scott M., additional, Rotter, Jerome, additional, de Vries, Paul S, additional, and Dichgans, Martin, additional

Published
2023
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47. Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity

Author

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

Published
2018
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48. Association of Rare Protein-Truncating DNA Variants in APOB or PCSK9 With Low-density Lipoprotein Cholesterol Level and Risk of Coronary Heart Disease

Author

Dron, Jacqueline S., primary, Patel, Aniruddh P., additional, Zhang, Yiyi, additional, Jurgens, Sean J., additional, Maamari, Dimitri J., additional, Wang, Minxian, additional, Boerwinkle, Eric, additional, Morrison, Alanna C., additional, de Vries, Paul S., additional, Fornage, Myriam, additional, Hou, Lifang, additional, Lloyd-Jones, Donald M., additional, Psaty, Bruce M., additional, Tracy, Russell P., additional, Bis, Joshua C., additional, Vasan, Ramachandran S., additional, Levy, Daniel, additional, Heard-Costa, Nancy, additional, Rich, Stephen S., additional, Guo, Xiuqing, additional, Taylor, Kent D., additional, Gibbs, Richard A., additional, Rotter, Jerome I., additional, Willer, Cristen J., additional, Oelsner, Elizabeth C., additional, Moran, Andrew E., additional, Peloso, Gina M., additional, Natarajan, Pradeep, additional, and Khera, Amit V., additional

Published
2023
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49. Deleterious heteroplasmic mitochondrial mutations are associated with an increased risk of overall and cancer-specific mortality.

Author

Hong, Yun, Hong, Yun, Battle, Stephanie, Shi, Wen, Puiu, Daniela, Pillalamarri, Vamsee, Xie, Jiaqi, Pankratz, Nathan, Lake, Nicole, Lek, Monkol, Rich, Stephen, Kooperberg, Charles, Reiner, Alex, Auer, Paul, Heard-Costa, Nancy, Liu, Chunyu, Lai, Meng, Murabito, Joanne, Levy, Daniel, Grove, Megan, Alonso, Alvaro, Gibbs, Richard, Dugan-Perez, Shannon, Gondek, Lukasz, Guallar, Eliseo, Arking, Dan, Rotter, Jerome, Hong, Yun, Hong, Yun, Battle, Stephanie, Shi, Wen, Puiu, Daniela, Pillalamarri, Vamsee, Xie, Jiaqi, Pankratz, Nathan, Lake, Nicole, Lek, Monkol, Rich, Stephen, Kooperberg, Charles, Reiner, Alex, Auer, Paul, Heard-Costa, Nancy, Liu, Chunyu, Lai, Meng, Murabito, Joanne, Levy, Daniel, Grove, Megan, Alonso, Alvaro, Gibbs, Richard, Dugan-Perez, Shannon, Gondek, Lukasz, Guallar, Eliseo, Arking, Dan, and Rotter, Jerome

Abstract

Mitochondria carry their own circular genome and disruption of the mitochondrial genome is associated with various aging-related diseases. Unlike the nuclear genome, mitochondrial DNA (mtDNA) can be present at 1000 s to 10,000 s copies in somatic cells and variants may exist in a state of heteroplasmy, where only a fraction of the DNA molecules harbors a particular variant. We quantify mtDNA heteroplasmy in 194,871 participants in the UK Biobank and find that heteroplasmy is associated with a 1.5-fold increased risk of all-cause mortality. Additionally, we functionally characterize mtDNA single nucleotide variants (SNVs) using a constraint-based score, mitochondrial local constraint score sum (MSS) and find it associated with all-cause mortality, and with the prevalence and incidence of cancer and cancer-related mortality, particularly leukemia. These results indicate that mitochondria may have a functional role in certain cancers, and mitochondrial heteroplasmic SNVs may serve as a prognostic marker for cancer, especially for leukemia.

Published
2023

50. Whole-exome sequence analysis of anthropometric traits illustrates challenges in identifying effects of rare genetic variants

Author

Young, Kristin L., Fisher, Virginia, Deng, Xuan, Brody, Jennifer A., Graff, Misa, Lim, Elise, Lin, Bridget M., Xu, Hanfei, Amin, Najaf, An, Ping, Aslibekyan, Stella, Fohner, Alison E., Hidalgo, Bertha, Lenzini, Petra, Kraaij, Robert, Medina-Gomez, Carolina, Prokić, Ivana, Rivadeneira, Fernando, Sitlani, Colleen, Tao, Ran, van Rooij, Jeroen, Zhang, Di, Broome, Jai G., Buth, Erin J., Heavner, Benjamin D., Jain, Deepti, Smith, Albert V., Barnes, Kathleen, Boorgula, Meher Preethi, Chavan, Sameer, Darbar, Dawood, De Andrade, Mariza, Guo, Xiuqing, Haessler, Jeffrey, Irvin, Marguerite R., Kalyani, Rita R., Kardia, Sharon L.R., Kooperberg, Charles, Kim, Wonji, Mathias, Rasika A., McDonald, Merry Lynn, Mitchell, Braxton D., Peyser, Patricia A., Regan, Elizabeth A., Redline, Susan, Reiner, Alexander P., Rich, Stephen S., Rotter, Jerome I., Smith, Jennifer A., Weiss, Scott, Wiggins, Kerri L., Yanek, Lisa R., Arnett, Donna, Heard-Costa, Nancy L., Leal, Suzanne, Lin, Danyu, McKnight, Barbara, Province, Michael, van Duijn, Cornelia M., North, Kari E., Cupples, L. Adrienne, Liu, Ching Ti, Young, Kristin L., Fisher, Virginia, Deng, Xuan, Brody, Jennifer A., Graff, Misa, Lim, Elise, Lin, Bridget M., Xu, Hanfei, Amin, Najaf, An, Ping, Aslibekyan, Stella, Fohner, Alison E., Hidalgo, Bertha, Lenzini, Petra, Kraaij, Robert, Medina-Gomez, Carolina, Prokić, Ivana, Rivadeneira, Fernando, Sitlani, Colleen, Tao, Ran, van Rooij, Jeroen, Zhang, Di, Broome, Jai G., Buth, Erin J., Heavner, Benjamin D., Jain, Deepti, Smith, Albert V., Barnes, Kathleen, Boorgula, Meher Preethi, Chavan, Sameer, Darbar, Dawood, De Andrade, Mariza, Guo, Xiuqing, Haessler, Jeffrey, Irvin, Marguerite R., Kalyani, Rita R., Kardia, Sharon L.R., Kooperberg, Charles, Kim, Wonji, Mathias, Rasika A., McDonald, Merry Lynn, Mitchell, Braxton D., Peyser, Patricia A., Regan, Elizabeth A., Redline, Susan, Reiner, Alexander P., Rich, Stephen S., Rotter, Jerome I., Smith, Jennifer A., Weiss, Scott, Wiggins, Kerri L., Yanek, Lisa R., Arnett, Donna, Heard-Costa, Nancy L., Leal, Suzanne, Lin, Danyu, McKnight, Barbara, Province, Michael, van Duijn, Cornelia M., North, Kari E., Cupples, L. Adrienne, and Liu, Ching Ti

Abstract

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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