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1. Multivariable Mendelian randomization with incomplete measurements on the exposure variables in the Hispanic Community Health Study/Study of Latinos

Author

Yilun Li, Kin Yau Wong, Annie Green Howard, Penny Gordon-Larsen, Heather M. Highland, Mariaelisa Graff, Kari E. North, Carolina G. Downie, Christy L. Avery, Bing Yu, Kristin L. Young, Victoria L. Buchanan, Robert Kaplan, Lifang Hou, Brian Thomas Joyce, Qibin Qi, Tamar Sofer, Jee-Young Moon, and Dan-Yu Lin

Subjects
causal inference, correlated exposures, detection limits, instrumental variables, missing data, unmeasured confounders, Genetics, QH426-470
Abstract

Summary: Multivariable Mendelian randomization allows simultaneous estimation of direct causal effects of multiple exposure variables on an outcome. When the exposure variables of interest are quantitative omic features, obtaining complete data can be economically and technically challenging: the measurement cost is high, and the measurement devices may have inherent detection limits. In this paper, we propose a valid and efficient method to handle unmeasured and undetectable values of the exposure variables in a one-sample multivariable Mendelian randomization analysis with individual-level data. We estimate the direct causal effects with maximum likelihood estimation and develop an expectation-maximization algorithm to compute the estimators. We show the advantages of the proposed method through simulation studies and provide an application to the Hispanic Community Health Study/Study of Latinos, which has a large amount of unmeasured exposure data.

Published
2024
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2. Advancements in genetic research by the Hispanic Community Health Study/Study of Latinos: A 10-year retrospective review

Author

Hridya Rao, Margaret C. Weiss, Jee Young Moon, Krista M. Perreira, Martha L. Daviglus, Robert Kaplan, Kari E. North, Maria Argos, Lindsay Fernández-Rhodes, and Tamar Sofer

Subjects
Genetics, QH426-470
Abstract

The Hispanic Community Health Study/Study of Latinos (HCHS/SOL) is a multicenter, longitudinal cohort study designed to evaluate environmental, lifestyle, and genetic risk factors as they relate to cardiometabolic and other chronic diseases among Hispanic/Latino populations in the United States. Since the study’s inception in 2008, as a result of the study’s robust genetic measures, HCHS/SOL has facilitated major contributions to the field of genetic research. This 10-year retrospective review highlights the major findings for genotype-phenotype relationships and advancements in statistical methods owing to the HCHS/SOL. Furthermore, we discuss the ethical and societal challenges of genetic research, especially among Hispanic/Latino adults in the United States. Continued genetic research, ancillary study expansion, and consortia collaboration through HCHS/SOL will further drive knowledge and advancements in human genetics research.

Published
2025
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3. A parametric bootstrap approach for computing confidence intervals for genetic correlations with application to genetically determined protein-protein networks

Author

Yi-Ting Tsai, Yana Hrytsenko, Michael Elgart, Usman A. Tahir, Zsu-Zsu Chen, James G. Wilson, Robert E. Gerszten, and Tamar Sofer

Subjects
genetic correlation, heritability, parametric bootstrap, sampling, protein-protein network, Genetics, QH426-470
Abstract

Summary: Genetic correlation refers to the correlation between genetic determinants of a pair of traits. When using individual-level data, it is typically estimated based on a bivariate model specification where the correlation between the two variables is identifiable and can be estimated from a covariance model that incorporates the genetic relationship between individuals, e.g., using a pre-specified kinship matrix. Inference relying on asymptotic normality of the genetic correlation parameter estimates may be inaccurate when the sample size is low, when the genetic correlation is close to the boundary of the parameter space, and when the heritability of at least one of the traits is low. We address this problem by developing a parametric bootstrap procedure to construct confidence intervals for genetic correlation estimates. The procedure simulates paired traits under a range of heritability and genetic correlation parameters, and it uses the population structure encapsulated by the kinship matrix. Heritabilities and genetic correlations are estimated using the close-form, method of moment, Haseman-Elston regression estimators. The proposed parametric bootstrap procedure is especially useful when genetic correlations are computed on pairs of thousands of traits measured on the same exact set of individuals. We demonstrate the parametric bootstrap approach on a proteomics dataset from the Jackson Heart Study.

Published
2024
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4. Ancestry-driven metabolite variation provides insights into disease states in admixed populations

Author

Kaylia M. Reynolds, Andrea R. V. R. Horimoto, Bridget M. Lin, Ying Zhang, Nuzulul Kurniansyah, Bing Yu, Eric Boerwinkle, Qibin Qi, Robert Kaplan, Martha Daviglus, Lifang Hou, Laura Y. Zhou, Jianwen Cai, Saame Raza Shaikh, Tamar Sofer, Sharon R. Browning, and Nora Franceschini

Subjects
Admixture mapping, Local ancestry, Metabolites, Hispanics/Latino populations, Medicine, Genetics, QH426-470
Abstract

Abstract Background Metabolic pathways are related to physiological functions and disease states and are influenced by genetic variation and environmental factors. Hispanics/Latino individuals have ancestry-derived genomic regions (local ancestry) from their recent admixture that have been less characterized for associations with metabolite abundance and disease risk. Methods We performed admixture mapping of 640 circulating metabolites in 3887 Hispanic/Latino individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Metabolites were quantified in fasting serum through non-targeted mass spectrometry (MS) analysis using ultra-performance liquid chromatography-MS/MS. Replication was performed in 1856 nonoverlapping HCHS/SOL participants with metabolomic data. Results By leveraging local ancestry, this study identified significant ancestry-enriched associations for 78 circulating metabolites at 484 independent regions, including 116 novel metabolite-genomic region associations that replicated in an independent sample. Among the main findings, we identified Native American enriched genomic regions at chromosomes 11 and 15, mapping to FADS1/FADS2 and LIPC, respectively, associated with reduced long-chain polyunsaturated fatty acid metabolites implicated in metabolic and inflammatory pathways. An African-derived genomic region at chromosome 2 was associated with N-acetylated amino acid metabolites. This region, mapped to ALMS1, is associated with chronic kidney disease, a disease that disproportionately burdens individuals of African descent. Conclusions Our findings provide important insights into differences in metabolite quantities related to ancestry in admixed populations including metabolites related to regulation of lipid polyunsaturated fatty acids and N-acetylated amino acids, which may have implications for common diseases in populations.

Published
2023
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5. Mendelian randomization with incomplete measurements on the exposure in the Hispanic Community Health Study/Study of Latinos

Author

Yilun Li, Kin Yau Wong, Annie Green Howard, Penny Gordon-Larsen, Heather M. Highland, Mariaelisa Graff, Kari E. North, Carolina G. Downie, Christy L. Avery, Bing Yu, Kristin L. Young, Victoria L. Buchanan, Robert Kaplan, Lifang Hou, Brian Thomas Joyce, Qibin Qi, Tamar Sofer, Jee-Young Moon, and Dan-Yu Lin

Subjects
causal inference, detection limits, instrumental variables, metabolomics, missing data, unmeasured confounding, Genetics, QH426-470
Abstract

Summary: Mendelian randomization has been widely used to assess the causal effect of a heritable exposure variable on an outcome of interest, using genetic variants as instrumental variables. In practice, data on the exposure variable can be incomplete due to high cost of measurement and technical limits of detection. In this paper, we propose a valid and efficient method to handle both unmeasured and undetectable values of the exposure variable in one-sample Mendelian randomization analysis with individual-level data. We estimate the causal effect of the exposure variable on the outcome using maximum likelihood estimation and develop an expectation maximization algorithm for the computation of the estimator. Simulation studies show that the proposed method performs well in making inference on the causal effect. We apply our method to the Hispanic Community Health Study/Study of Latinos, a community-based prospective cohort study, and estimate the causal effect of several metabolites on phenotypes of interest.

Published
2024
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6. Gene-educational attainment interactions in a multi-population genome-wide meta-analysis identify novel lipid loci

Author

Lisa de las Fuentes, Karen L. Schwander, Michael R. Brown, Amy R. Bentley, Thomas W. Winkler, Yun Ju Sung, Patricia B. Munroe, Clint L. Miller, Hugo Aschard, Stella Aslibekyan, Traci M. Bartz, Lawrence F. Bielak, Jin Fang Chai, Ching-Yu Cheng, Rajkumar Dorajoo, Mary F. Feitosa, Xiuqing Guo, Fernando P. Hartwig, Andrea Horimoto, Ivana Kolčić, Elise Lim, Yongmei Liu, Alisa K. Manning, Jonathan Marten, Solomon K. Musani, Raymond Noordam, Sandosh Padmanabhan, Tuomo Rankinen, Melissa A. Richard, Paul M. Ridker, Albert V. Smith, Dina Vojinovic, Alan B. Zonderman, Maris Alver, Mathilde Boissel, Kaare Christensen, Barry I. Freedman, Chuan Gao, Franco Giulianini, Sarah E. Harris, Meian He, Fang-Chi Hsu, Brigitte Kühnel, Federica Laguzzi, Xiaoyin Li, Leo-Pekka Lyytikäinen, Ilja M. Nolte, Alaitz Poveda, Rainer Rauramaa, Muhammad Riaz, Antonietta Robino, Tamar Sofer, Fumihiko Takeuchi, Bamidele O. Tayo, Peter J. van der Most, Niek Verweij, Erin B. Ware, Stefan Weiss, Wanqing Wen, Lisa R. Yanek, Yiqiang Zhan, Najaf Amin, Dan E. Arking, Christie Ballantyne, Eric Boerwinkle, Jennifer A. Brody, Ulrich Broeckel, Archie Campbell, Mickaël Canouil, Xiaoran Chai, Yii-Der Ida Chen, Xu Chen, Kumaraswamy Naidu Chitrala, Maria Pina Concas, Ulf de Faire, Renée de Mutsert, H. Janaka de Silva, Paul S. de Vries, Ahn Do, Jessica D. Faul, Virginia Fisher, James S. Floyd, Terrence Forrester, Yechiel Friedlander, Giorgia Girotto, C. Charles Gu, Göran Hallmans, Sami Heikkinen, Chew-Kiat Heng, Georg Homuth, Steven Hunt, M. Arfan Ikram, David R. Jacobs, Maryam Kavousi, Chiea Chuen Khor, Tuomas O. Kilpeläinen, Woon-Puay Koh, Pirjo Komulainen, Carl D. Langefeld, Jingjing Liang, Kiang Liu, Jianjun Liu, Kurt Lohman, Reedik Mägi, Ani W. Manichaikul, Colin A. McKenzie, Thomas Meitinger, Yuri Milaneschi, Matthias Nauck, Christopher P. Nelson, Jeffrey R. O’Connell, Nicholette D. Palmer, Alexandre C. Pereira, Thomas Perls, Annette Peters, Ozren Polašek, Olli T. Raitakari, Kenneth Rice, Treva K. Rice, Stephen S. Rich, Charumathi Sabanayagam, Pamela J. Schreiner, Xiao-Ou Shu, Stephen Sidney, Mario Sims, Jennifer A. Smith, John M. Starr, Konstantin Strauch, E. Shyong Tai, Kent D. Taylor, Michael Y. Tsai, André G. Uitterlinden, Diana van Heemst, Melanie Waldenberger, Ya-Xing Wang, Wen-Bin Wei, Gregory Wilson, Deng Xuan, Jie Yao, Caizheng Yu, Jian-Min Yuan, Wei Zhao, Diane M. Becker, Amélie Bonnefond, Donald W. Bowden, Richard S. Cooper, Ian J. Deary, Jasmin Divers, Tõnu Esko, Paul W. Franks, Philippe Froguel, Christian Gieger, Jost B. Jonas, Norihiro Kato, Timo A. Lakka, Karin Leander, Terho Lehtimäki, Patrik K. E. Magnusson, Kari E. North, Ioanna Ntalla, Brenda Penninx, Nilesh J. Samani, Harold Snieder, Beatrice Spedicati, Pim van der Harst, Henry Völzke, Lynne E. Wagenknecht, David R. Weir, Mary K. Wojczynski, Tangchun Wu, Wei Zheng, Xiaofeng Zhu, Claude Bouchard, Daniel I. Chasman, Michele K. Evans, Ervin R. Fox, Vilmundur Gudnason, Caroline Hayward, Bernardo L. Horta, Sharon L. R. Kardia, Jose Eduardo Krieger, Dennis O. Mook-Kanamori, Patricia A. Peyser, Michael M. Province, Bruce M. Psaty, Igor Rudan, Xueling Sim, Blair H. Smith, Rob M. van Dam, Cornelia M. van Duijn, Tien Yin Wong, Donna K. Arnett, Dabeeru C. Rao, James Gauderman, Ching-Ti Liu, Alanna C. Morrison, Jerome I. Rotter, and Myriam Fornage

Subjects
educational attainment, lipids, cholesterol, triglycerides, genome-wide association study, meta-analysis, Genetics, QH426-470
Abstract

Introduction: Educational attainment, widely used in epidemiologic studies as a surrogate for socioeconomic status, is a predictor of cardiovascular health outcomes.Methods: A two-stage genome-wide meta-analysis of low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and triglyceride (TG) levels was performed while accounting for gene-educational attainment interactions in up to 226,315 individuals from five population groups. We considered two educational attainment variables: “Some College” (yes/no, for any education beyond high school) and “Graduated College” (yes/no, for completing a 4-year college degree). Genome-wide significant (p < 5 × 10−8) and suggestive (p < 1 × 10−6) variants were identified in Stage 1 (in up to 108,784 individuals) through genome-wide analysis, and those variants were followed up in Stage 2 studies (in up to 117,531 individuals).Results: In combined analysis of Stages 1 and 2, we identified 18 novel lipid loci (nine for LDL, seven for HDL, and two for TG) by two degree-of-freedom (2 DF) joint tests of main and interaction effects. Four loci showed significant interaction with educational attainment. Two loci were significant only in cross-population analyses. Several loci include genes with known or suggested roles in adipose (FOXP1, MBOAT4, SKP2, STIM1, STX4), brain (BRI3, FILIP1, FOXP1, LINC00290, LMTK2, MBOAT4, MYO6, SENP6, SRGAP3, STIM1, TMEM167A, TMEM30A), and liver (BRI3, FOXP1) biology, highlighting the potential importance of brain-adipose-liver communication in the regulation of lipid metabolism. An investigation of the potential druggability of genes in identified loci resulted in five gene targets shown to interact with drugs approved by the Food and Drug Administration, including genes with roles in adipose and brain tissue.Discussion: Genome-wide interaction analysis of educational attainment identified novel lipid loci not previously detected by analyses limited to main genetic effects.

Published
2023
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7. Canonical correlation analysis for multi-omics: Application to cross-cohort analysis.

Author

Min-Zhi Jiang, François Aguet, Kristin Ardlie, Jiawen Chen, Elaine Cornell, Dan Cruz, Peter Durda, Stacey B Gabriel, Robert E Gerszten, Xiuqing Guo, Craig W Johnson, Silva Kasela, Leslie A Lange, Tuuli Lappalainen, Yongmei Liu, Alex P Reiner, Josh Smith, Tamar Sofer, Kent D Taylor, Russell P Tracy, David J VanDenBerg, James G Wilson, Stephen S Rich, Jerome I Rotter, Michael I Love, Laura M Raffield, Yun Li, and NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Analysis Working Group

Subjects
Genetics, QH426-470
Abstract

Integrative approaches that simultaneously model multi-omics data have gained increasing popularity because they provide holistic system biology views of multiple or all components in a biological system of interest. Canonical correlation analysis (CCA) is a correlation-based integrative method designed to extract latent features shared between multiple assays by finding the linear combinations of features-referred to as canonical variables (CVs)-within each assay that achieve maximal across-assay correlation. Although widely acknowledged as a powerful approach for multi-omics data, CCA has not been systematically applied to multi-omics data in large cohort studies, which has only recently become available. Here, we adapted sparse multiple CCA (SMCCA), a widely-used derivative of CCA, to proteomics and methylomics data from the Multi-Ethnic Study of Atherosclerosis (MESA) and Jackson Heart Study (JHS). To tackle challenges encountered when applying SMCCA to MESA and JHS, our adaptations include the incorporation of the Gram-Schmidt (GS) algorithm with SMCCA to improve orthogonality among CVs, and the development of Sparse Supervised Multiple CCA (SSMCCA) to allow supervised integration analysis for more than two assays. Effective application of SMCCA to the two real datasets reveals important findings. Applying our SMCCA-GS to MESA and JHS, we identified strong associations between blood cell counts and protein abundance, suggesting that adjustment of blood cell composition should be considered in protein-based association studies. Importantly, CVs obtained from two independent cohorts also demonstrate transferability across the cohorts. For example, proteomic CVs learned from JHS, when transferred to MESA, explain similar amounts of blood cell count phenotypic variance in MESA, explaining 39.0% ~ 50.0% variation in JHS and 38.9% ~ 49.1% in MESA. Similar transferability was observed for other omics-CV-trait pairs. This suggests that biologically meaningful and cohort-agnostic variation is captured by CVs. We anticipate that applying our SMCCA-GS and SSMCCA on various cohorts would help identify cohort-agnostic biologically meaningful relationships between multi-omics data and phenotypic traits.

Published
2023
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8. Polygenic risk scores and kidney traits in the Hispanic/Latino population: The Hispanic Community Health Study/Study of Latinos

Author

Laura Y. Zhou, Tamar Sofer, Andrea R.V.R. Horimoto, Gregory A. Talavera, James P. Lash, Jianwen Cai, and Nora Franceschini

Subjects
eGFR, CKD, PRS, admixed, Hispanic/Latino population, GWAS, Genetics, QH426-470
Abstract

Summary: Estimated glomerular filtration rate (eGFR) is used to evaluate kidney function and determine the presence of chronic kidney disease (CKD), a highly prevalent disease in the US1,2,3 that varies among subgroups of Hispanic/Latino individuals.4,5 The polygenic risk score (PRS) is a popular method that uses large genome-wide association studies (GWASs) to provide a strong estimate of disease risk.7 However, due to the limited availability of summary statistics from GWAS meta-analyses based on Hispanic/Latino populations, PRSs can only be computed using different ancestry GWASs. The performance of eGFR PRSs derived from other GWAS reference populations for Hispanic/Latino population has not been examined. We compared PRS constructions for eGFR prediction in Hispanic/Latino individuals using GWAS-significant variants, clumping and thresholding (C&T),8 and PRS-CS,22 as well as a combination of PRSs calculated with different reference GWAS meta-analyses from European and multi-ethnic studies in Hispanic/Latino individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). All eGFR PRSs were highly associated with eGFR (p

Published
2023
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9. Awareness and utilization of genetic testing among Hispanic and Latino adults living in the US: The Hispanic Community Health Study/Study of Latinos

Author

Kurt D. Christensen, Mengran Zhang, Lauren N. Galbraith, Einat Granot-Hershkovitz, Sarah C. Nelson, Sara Gonzalez, Maria Argos, Krista M. Perreira, Martha L. Daviglus, Carmen R. Isasi, Jianwen Cai, Gregory A. Talavera, Carrie L. Blout Zawatsky, Robert C. Green, Rosario Isasi, Robert Kaplan, and Tamar Sofer

Subjects
genetic testing, ELSI, Hispanic or Latino, awareness, survey, perceived usefulness, population-based study, Genetics, QH426-470
Abstract

Summary: We investigated the awareness, perceived usefulness, and use of genetic testing among Hispanic and Latino individuals. Annual follow-up surveys for the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) from 2019 to April 2020 assessed participants’ level of awareness and use of genetic tests to determine disease risks, likelihood of passing disease to children, disease treatment, or drug selection. They also were asked to rate the usefulness of the tests for managing a person’s health on a 1 (not at all useful) to 10 (extremely useful) scale. There were 5,769 HCHS/SOL participants who completed at least one survey question. Of the target population, 55.2% was aware of at least one type of genetic test. Awareness varied between HCHS/SOL enrollment sites and was higher among individuals who had higher educational attainment and had higher incomes. Only 3.3% of the target population reported receiving one or more of the tests described. HCHS/SOL individuals rated the usefulness as 8.4, on average, with lower scores observed among U.S.-born individuals compared to individuals born outside the United States, with differences by HCHS/SOL enrollment sites. In conclusion, while awareness of genetic testing among Hispanic and Latino individuals varies by location, education, and income, perceptions about its usefulness are high while experiences with testing are rare. Results identify groups and locations that may benefit from greater outreach about the capabilities of genetic testing and precision medicine.

Published
2023
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10. Ancestral diversity improves discovery and fine-mapping of genetic loci for anthropometric traits—The Hispanic/Latino Anthropometry Consortium

Author

Lindsay Fernández-Rhodes, Mariaelisa Graff, Victoria L. Buchanan, Anne E. Justice, Heather M. Highland, Xiuqing Guo, Wanying Zhu, Hung-Hsin Chen, Kristin L. Young, Kaustubh Adhikari, Nicholette D. Palmer, Jennifer E. Below, Jonathan Bradfield, Alexandre C. Pereira, LáShauntá Glover, Daeeun Kim, Adam G. Lilly, Poojan Shrestha, Alvin G. Thomas, Xinruo Zhang, Minhui Chen, Charleston W.K. Chiang, Sara Pulit, Andrea Horimoto, Jose E. Krieger, Marta Guindo-Martínez, Michael Preuss, Claudia Schumann, Roelof A.J. Smit, Gabriela Torres-Mejía, Victor Acuña-Alonzo, Gabriel Bedoya, Maria-Cátira Bortolini, Samuel Canizales-Quinteros, Carla Gallo, Rolando González-José, Giovanni Poletti, Francisco Rothhammer, Hakon Hakonarson, Robert Igo, Sharon G. Adler, Sudha K. Iyengar, Susanne B. Nicholas, Stephanie M. Gogarten, Carmen R. Isasi, George Papnicolaou, Adrienne M. Stilp, Qibin Qi, Minjung Kho, Jennifer A. Smith, Carl D. Langefeld, Lynne Wagenknecht, Roberta Mckean-Cowdin, Xiaoyi Raymond Gao, Darryl Nousome, David V. Conti, Ye Feng, Matthew A. Allison, Zorayr Arzumanyan, Thomas A. Buchanan, Yii-Der Ida Chen, Pauline M. Genter, Mark O. Goodarzi, Yang Hai, Willa Hsueh, Eli Ipp, Fouad R. Kandeel, Kelvin Lam, Xiaohui Li, Jerry L. Nadler, Leslie J. Raffel, Kathryn Roll, Kevin Sandow, Jingyi Tan, Kent D. Taylor, Anny H. Xiang, Jie Yao, Astride Audirac-Chalifour, Jose de Jesus Peralta Romero, Fernando Hartwig, Bernando Horta, John Blangero, Joanne E. Curran, Ravindranath Duggirala, Donna E. Lehman, Sobha Puppala, Laura Fejerman, Esther M. John, Carlos Aguilar-Salinas, Noël P. Burtt, Jose C. Florez, Humberto García-Ortíz, Clicerio González-Villalpando, Josep Mercader, Lorena Orozco, Teresa Tusié-Luna, Estela Blanco, Sheila Gahagan, Nancy J. Cox, Craig Hanis, Nancy F. Butte, Shelley A. Cole, Anthony G. Comuzzie, V. Saroja Voruganti, Rebecca Rohde, Yujie Wang, Tamar Sofer, Elad Ziv, Struan F.A. Grant, Andres Ruiz-Linares, Jerome I. Rotter, Christopher A. Haiman, Esteban J. Parra, Miguel Cruz, Ruth J.F. Loos, and Kari E. North

Subjects
Genetics, QH426-470
Published
2023
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11. Leveraging pleiotropy to discover and interpret GWAS results for sleep-associated traits.

Author

Sung Chun, Sebastian Akle, Athanasios Teodosiadis, Brian E Cade, Heming Wang, Tamar Sofer, Daniel S Evans, Katie L Stone, Sina A Gharib, Sutapa Mukherjee, Lyle J Palmer, David Hillman, Jerome I Rotter, Craig L Hanis, John A Stamatoyannopoulos, Susan Redline, Chris Cotsapas, and Shamil R Sunyaev

Subjects
Genetics, QH426-470
Abstract

Genetic association studies of many heritable traits resulting from physiological testing often have modest sample sizes due to the cost and burden of the required phenotyping. This reduces statistical power and limits discovery of multiple genetic associations. We present a strategy to leverage pleiotropy between traits to both discover new loci and to provide mechanistic hypotheses of the underlying pathophysiology. Specifically, we combine a colocalization test with a locus-level test of pleiotropy. In simulations, we show that this approach is highly selective for identifying true pleiotropy driven by the same causative variant, thereby improves the chance to replicate the associations in underpowered validation cohorts and leads to higher interpretability. Here, as an exemplar, we use Obstructive Sleep Apnea (OSA), a common disorder diagnosed using overnight multi-channel physiological testing. We leverage pleiotropy with relevant cellular and cardio-metabolic phenotypes and gene expression traits to map new risk loci in an underpowered OSA GWAS. We identify several pleiotropic loci harboring suggestive associations to OSA and genome-wide significant associations to other traits, and show that their OSA association replicates in independent cohorts of diverse ancestries. By investigating pleiotropic loci, our strategy allows proposing new hypotheses about OSA pathobiology across many physiological layers. For example, we identify and replicate the pleiotropy across the plateletcrit, OSA and an eQTL of DNA primase subunit 1 (PRIM1) in immune cells. We find suggestive links between OSA, a measure of lung function (FEV1/FVC), and an eQTL of matrix metallopeptidase 15 (MMP15) in lung tissue. We also link a previously known genome-wide significant peak for OSA in the hexokinase 1 (HK1) locus to hematocrit and other red blood cell related traits. Thus, the analysis of pleiotropic associations has the potential to assemble diverse phenotypes into a chain of mechanistic hypotheses that provide insight into the pathogenesis of complex human diseases.

Published
2022
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12. The impact of Mendelian sleep and circadian genetic variants in a population setting.

Author

Michael N Weedon, Samuel E Jones, Jacqueline M Lane, Jiwon Lee, Hanna M Ollila, Amy Dawes, Jess Tyrrell, Robin N Beaumont, Timo Partonen, Ilona Merikanto, Stephen S Rich, Jerome I Rotter, Timothy M Frayling, Martin K Rutter, Susan Redline, Tamar Sofer, Richa Saxena, and Andrew R Wood

Subjects
Genetics, QH426-470
Abstract

Rare variants in ten genes have been reported to cause Mendelian sleep conditions characterised by extreme sleep duration or timing. These include familial natural short sleep (ADRB1, DEC2/BHLHE41, GRM1 and NPSR1), advanced sleep phase (PER2, PER3, CRY2, CSNK1D and TIMELESS) and delayed sleep phase (CRY1). The association of variants in these genes with extreme sleep conditions were usually based on clinically ascertained families, and their effects when identified in the population are unknown. We aimed to determine the effects of these variants on sleep traits in large population-based cohorts. We performed genetic association analysis of variants previously reported to be causal for Mendelian sleep and circadian conditions. Analyses were performed using 191,929 individuals with data on sleep and whole-exome or genome-sequence data from 4 population-based studies: UK Biobank, FINRISK, Health-2000-2001, and the Multi-Ethnic Study of Atherosclerosis (MESA). We identified sleep disorders from self-report, hospital and primary care data. We estimated sleep duration and timing measures from self-report and accelerometery data. We identified carriers for 10 out of 12 previously reported pathogenic variants for 8 of the 10 genes. They ranged in frequency from 1 individual with the variant in CSNK1D to 1,574 individuals with a reported variant in the PER3 gene in the UK Biobank. No carriers for variants reported in NPSR1 or PER2 were identified. We found no association between variants analyzed and extreme sleep or circadian phenotypes. Using sleep timing as a proxy measure for sleep phase, only PER3 and CRY1 variants demonstrated association with earlier and later sleep timing, respectively; however, the magnitude of effect was smaller than previously reported (sleep midpoint ~7 mins earlier and ~5 mins later, respectively). We also performed burden tests of protein truncating (PTVs) or rare missense variants for the 10 genes. Only PTVs in PER2 and PER3 were associated with a relevant trait (for example, 64 individuals with a PTV in PER2 had an odds ratio of 4.4 for being "definitely a morning person", P = 4x10-8; and had a 57-minute earlier midpoint sleep, P = 5x10-7). Our results indicate that previously reported variants for Mendelian sleep and circadian conditions are often not highly penetrant when ascertained incidentally from the general population.

Published
2022
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13. Whole-genome association analyses of sleep-disordered breathing phenotypes in the NHLBI TOPMed program

Author

Brian E. Cade, Jiwon Lee, Tamar Sofer, Heming Wang, Man Zhang, Han Chen, Sina A. Gharib, Daniel J. Gottlieb, Xiuqing Guo, Jacqueline M. Lane, Jingjing Liang, Xihong Lin, Hao Mei, Sanjay R. Patel, Shaun M. Purcell, Richa Saxena, Neomi A. Shah, Daniel S. Evans, Craig L. Hanis, David R. Hillman, Sutapa Mukherjee, Lyle J. Palmer, Katie L. Stone, Gregory J. Tranah, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Gonçalo R. Abecasis, Eric A. Boerwinkle, Adolfo Correa, L. Adrienne Cupples, Robert C. Kaplan, Deborah A. Nickerson, Kari E. North, Bruce M. Psaty, Jerome I. Rotter, Stephen S. Rich, Russell P. Tracy, Ramachandran S. Vasan, James G. Wilson, Xiaofeng Zhu, Susan Redline, and TOPMed Sleep Working Group

Subjects
Sleep-disordered breathing, Sleep apnea, Whole-genome sequencing, WGS, Genome-wide association study, GWAS, Medicine, Genetics, QH426-470
Abstract

Abstract Background Sleep-disordered breathing is a common disorder associated with significant morbidity. The genetic architecture of sleep-disordered breathing remains poorly understood. Through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, we performed the first whole-genome sequence analysis of sleep-disordered breathing. Methods The study sample was comprised of 7988 individuals of diverse ancestry. Common-variant and pathway analyses included an additional 13,257 individuals. We examined five complementary traits describing different aspects of sleep-disordered breathing: the apnea-hypopnea index, average oxyhemoglobin desaturation per event, average and minimum oxyhemoglobin saturation across the sleep episode, and the percentage of sleep with oxyhemoglobin saturation

Published
2021
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14. AFA: Ancestry-specific allele frequency estimation in admixed populations: The Hispanic Community Health Study/Study of Latinos

Author

Einat Granot-Hershkovitz, Quan Sun, Maria Argos, Hufeng Zhou, Xihong Lin, Sharon R. Browning, and Tamar Sofer

Subjects
Admixed population, Hispanic/Latinos, Amerindian, European, African, Allele frequency, Genetics, QH426-470
Abstract

Summary: Allele frequency estimates in admixed populations, such as Hispanics and Latinos, rely on the sample’s specific admixture composition and thus may differ between two seemingly similar populations. However, ancestry-specific allele frequencies, i.e., pertaining to the ancestral populations of an admixed group, may be particularly useful for prioritizing genetic variants for genetic discovery and personalized genomic health. We developed a method, ancestry-specific allele frequency estimation in admixed populations (AFA), to estimate the frequencies of biallelic variants in admixed populations with an unlimited number of ancestries. AFA uses maximum-likelihood estimation by modeling the conditional probability of having an allele given proportions of genetic ancestries. It can be applied using either local ancestry interval proportions encompassing the variant (local-ancestry-specific allele frequency estimations in admixed populations [LAFAs]) or global proportions of genetic ancestries (global-ancestry-specific allele frequency estimations in admixed populations [GAFAs]), which are easier to compute and are more widely available. Simulations and comparisons to existing software demonstrated the high accuracy of the method. We implemented AFA on high-quality imputed data of ∼9,000 Hispanics and Latinos from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), an understudied, admixed population with three predominant continental ancestries: Amerindian, European, and African. Comparison of the European and African estimated frequencies to the respective gnomAD frequencies demonstrated high correlations (Pearson R2 = 0.97–0.99). We provide a genome-wide dataset of the estimated ancestry-specific allele frequencies for available variants with allele frequency between 5% and 95% in at least one of the three ancestral populations. Association analysis of Amerindian-enriched variants with cardiometabolic traits identified five loci associated with lipid traits in Hispanics and Latinos, demonstrating the utility of ancestry-specific allele frequencies in admixed populations.

Published
2022
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15. Ancestral diversity improves discovery and fine-mapping of genetic loci for anthropometric traits—The Hispanic/Latino Anthropometry Consortium

Author

Lindsay Fernández-Rhodes, Mariaelisa Graff, Victoria L. Buchanan, Anne E. Justice, Heather M. Highland, Xiuqing Guo, Wanying Zhu, Hung-Hsin Chen, Kristin L. Young, Kaustubh Adhikari, Nicholette D. Palmer, Jennifer E. Below, Jonathan Bradfield, Alexandre C. Pereira, LáShauntá Glover, Daeeun Kim, Adam G. Lilly, Poojan Shrestha, Alvin G. Thomas, Xinruo Zhang, Minhui Chen, Charleston W.K. Chiang, Sara Pulit, Andrea Horimoto, Jose E. Krieger, Marta Guindo-Martínez, Michael Preuss, Claudia Schumann, Roelof A.J. Smit, Gabriela Torres-Mejía, Victor Acuña-Alonzo, Gabriel Bedoya, Maria-Cátira Bortolini, Samuel Canizales-Quinteros, Carla Gallo, Rolando González-José, Giovanni Poletti, Francisco Rothhammer, Hakon Hakonarson, Robert Igo, Sharon G. Adler, Sudha K. Iyengar, Susanne B. Nicholas, Stephanie M. Gogarten, Carmen R. Isasi, George Papnicolaou, Adrienne M. Stilp, Qibin Qi, Minjung Kho, Jennifer A. Smith, Carl D. Langefeld, Lynne Wagenknecht, Roberta Mckean-Cowdin, Xiaoyi Raymond Gao, Darryl Nousome, David V. Conti, Ye Feng, Matthew A. Allison, Zorayr Arzumanyan, Thomas A. Buchanan, Yii-Der Ida Chen, Pauline M. Genter, Mark O. Goodarzi, Yang Hai, Willa Hsueh, Eli Ipp, Fouad R. Kandeel, Kelvin Lam, Xiaohui Li, Jerry L. Nadler, Leslie J. Raffel, Kathryn Roll, Kevin Sandow, Jingyi Tan, Kent D. Taylor, Anny H. Xiang, Jie Yao, Astride Audirac-Chalifour, Jose de Jesus Peralta Romero, Fernando Hartwig, Bernando Horta, John Blangero, Joanne E. Curran, Ravindranath Duggirala, Donna E. Lehman, Sobha Puppala, Laura Fejerman, Esther M. John, Carlos Aguilar-Salinas, Noël P. Burtt, Jose C. Florez, Humberto García-Ortíz, Clicerio González-Villalpando, Josep Mercader, Lorena Orozco, Teresa Tusié-Luna, Estela Blanco, Sheila Gahagan, Nancy J. Cox, Craig Hanis, Nancy F. Butte, Shelley A. Cole, Anthony G. Comuzzie, V. Saroja Voruganti, Rebecca Rohde, Yujie Wang, Tamar Sofer, Elad Ziv, Struan F.A. Grant, Andres Ruiz-Linares, Jerome I. Rotter, Christopher A. Haiman, Esteban J. Parra, Miguel Cruz, Ruth J.F. Loos, and Kari E. North

Subjects
Hispanic/Latino, anthropometrics, obesity, diversity, trans-ancestral or trans-ethnic, fine-mapping, Genetics, QH426-470
Abstract

Hispanic/Latinos have been underrepresented in genome-wide association studies (GWAS) for anthropometric traits despite their notable anthropometric variability, ancestry proportions, and high burden of growth stunting and overweight/obesity. To address this knowledge gap, we analyzed densely imputed genetic data in a sample of Hispanic/Latino adults to identify and fine-map genetic variants associated with body mass index (BMI), height, and BMI-adjusted waist-to-hip ratio (WHRadjBMI). We conducted a GWAS of 18 studies/consortia as part of the Hispanic/Latino Anthropometry (HISLA) Consortium (stage 1, n = 59,771) and generalized our findings in 9 additional studies (stage 2, n = 10,538). We conducted a trans-ancestral GWAS with summary statistics from HISLA stage 1 and existing consortia of European and African ancestries. In our HISLA stage 1 + 2 analyses, we discovered one BMI locus, as well as two BMI signals and another height signal each within established anthropometric loci. In our trans-ancestral meta-analysis, we discovered three BMI loci, one height locus, and one WHRadjBMI locus. We also identified 3 secondary signals for BMI, 28 for height, and 2 for WHRadjBMI in established loci. We show that 336 known BMI, 1,177 known height, and 143 known WHRadjBMI (combined) SNPs demonstrated suggestive transferability (nominal significance and effect estimate directional consistency) in Hispanic/Latino adults. Of these, 36 BMI, 124 height, and 11 WHRadjBMI SNPs were significant after trait-specific Bonferroni correction. Trans-ancestral meta-analysis of the three ancestries showed a small-to-moderate impact of uncorrected population stratification on the resulting effect size estimates. Our findings demonstrate that future studies may also benefit from leveraging diverse ancestries and differences in linkage disequilibrium patterns to discover novel loci and additional signals with less residual population stratification.

Published
2022
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16. Association of mitochondrial DNA copy number with cardiometabolic diseases

Author

Xue Liu, Ryan J. Longchamps, Kerri L. Wiggins, Laura M. Raffield, Lawrence F. Bielak, Wei Zhao, Achilleas Pitsillides, Thomas W. Blackwell, Jie Yao, Xiuqing Guo, Nuzulul Kurniansyah, Bharat Thyagarajan, Nathan Pankratz, Stephen S. Rich, Kent D. Taylor, Patricia A. Peyser, Susan R. Heckbert, Sudha Seshadri, L. Adrienne Cupples, Eric Boerwinkle, Megan L. Grove, Nicholas B. Larson, Jennifer A. Smith, Ramachandran S. Vasan, Tamar Sofer, Annette L. Fitzpatrick, Myriam Fornage, Jun Ding, Adolfo Correa, Goncalo Abecasis, Bruce M. Psaty, James G. Wilson, Daniel Levy, Jerome I. Rotter, Joshua C. Bis, Claudia L. Satizabal, Dan E. Arking, and Chunyu Liu

Subjects
mitochondrial DNA copy number, cardiometabolic disease, whole-genome sequencing, whole-exom sequencing, aging, white blood cell counts, Genetics, QH426-470, Internal medicine, RC31-1245
Abstract

Summary: Mitochondrial DNA (mtDNA) is present in multiple copies in human cells. We evaluated cross-sectional associations of whole-blood mtDNA copy number (CN) with several cardiometabolic disease traits in 408,361 participants of multiple ancestries in TOPMed and UK Biobank. Age showed a threshold association with mtDNA CN: each additional 10 years of age was associated with a 0.03 SD higher level of mtDNA CN (p = 0.0014) among younger participants (younger than 65 years) versus a 0.14 SD lower level of mtDNA CN (p = 1.82 × 10−13) among older participants (65 years and older). At lower mtDNA CN levels, we found age-independent associations with increased odds of obesity (p = 5.6 × 10−238), hypertension (p = 2.8 × 10−50), diabetes (p = 3.6 × 10−7), and hyperlipidemia (p = 6.3 × 10−56). The observed decline in mtDNA CN after 65 years of age may be a key to understanding age-related diseases.

Published
2021
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17. BinomiRare: A robust test for association of a rare genetic variant with a binary outcome for mixed models and any case-control proportion

Author

Tamar Sofer, Jiwon Lee, Nuzulul Kurniansyah, Deepti Jain, Cecelia A. Laurie, Stephanie M. Gogarten, Matthew P. Conomos, Ben Heavner, Yao Hu, Charles Kooperberg, Jeffrey Haessler, Ramachandran S. Vasan, L. Adrienne Cupples, Brandon J. Coombes, Amanda Seyerle, Sina A. Gharib, Han Chen, Jeffrey R. O’Connell, Man Zhang, Daniel J. Gottlieb, Bruce M. Psaty, W.T. Longstreth, Jr., Jerome I. Rotter, Kent D. Taylor, Stephen S. Rich, Xiuqing Guo, Eric Boerwinkle, Alanna C. Morrison, James S. Pankow, Andrew D. Johnson, Nathan Pankratz, Alex P. Reiner, Susan Redline, Nicholas L. Smith, Kenneth M. Rice, and Elizabeth D. Schifano

Subjects
genome sequencing, rare variant assocaition testing, diverse populations, targeted gene analysis, mixed models, Genetics, QH426-470
Abstract

Summary: Whole-genome sequencing (WGS) and whole-exome sequencing studies have become increasingly available and are being used to identify rare genetic variants associated with health and disease outcomes. Investigators routinely use mixed models to account for genetic relatedness or other clustering variables (e.g., family or household) when testing genetic associations. However, no existing tests of the association of a rare variant with a binary outcome in the presence of correlated data control the type 1 error where there are (1) few individuals harboring the rare allele, (2) a small proportion of cases relative to controls, and (3) covariates to adjust for. Here, we address all three issues in developing a framework for testing rare variant association with a binary trait in individuals harboring at least one risk allele. In this framework, we estimate outcome probabilities under the null hypothesis and then use them, within the individuals with at least one risk allele, to test variant associations. We extend the BinomiRare test, which was previously proposed for independent observations, and develop the Conway-Maxwell-Poisson (CMP) test and study their properties in simulations. We show that the BinomiRare test always controls the type 1 error, while the CMP test sometimes does not. We then use the BinomiRare test to test the association of rare genetic variants in target genes with small-vessel disease (SVD) stroke, short sleep, and venous thromboembolism (VTE), in whole-genome sequence data from the Trans-Omics for Precision Medicine (TOPMed) program.

Published
2021
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18. Genetic architecture of lipid traits in the Hispanic community health study/study of Latinos

Author

Mariaelisa Graff, Leslie S. Emery, Anne E. Justice, Esteban Parra, Jennifer E. Below, Nicholette D. Palmer, Chuan Gao, Qing Duan, Adan Valladares-Salgado, Miguel Cruz, Alanna C. Morrison, Eric Boerwinkle, Eric A. Whitsel, Charles Kooperberg, Alex Reiner, Yun Li, Carlos Jose Rodriguez, Gregory A. Talavera, Carl D. Langefeld, Lynne E. Wagenknecht, Jill M. Norris, Kent D. Taylor, George Papanicolaou, Eimear Kenny, Ruth J. F. Loos, Yii-Der Ida Chen, Cathy Laurie, Tamar Sofer, and Kari E. North

Subjects
HDL, LDL, Triglycerides, Cholesterol, Genetics, Ancestry, Nutritional diseases. Deficiency diseases, RC620-627
Abstract

Abstract Background Despite ethnic disparities in lipid profiles, there are few genome-wide association studies investigating genetic variation of lipids in non-European ancestry populations. In this study, we present findings from genetic association analyses for total cholesterol, low density lipoprotein cholesterol (LDL), high density lipoprotein cholesterol (HDL), and triglycerides in a large Hispanic/Latino cohort in the U.S., the Hispanic Community Health Study / Study of Latinos (HCHS/SOL). Methods We estimated a heritability of approximately 20% for each lipid trait, similar to previous estimates in Europeans. To search for novel lipid loci, we performed conditional association analysis in which the statistical model was adjusted for previously reported SNPs associated with any of the four lipid traits. SNPs that remained genome-wide significant (P

Published
2017
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19. Associations of variants In the hexokinase 1 and interleukin 18 receptor regions with oxyhemoglobin saturation during sleep.

Author

Brian E Cade, Han Chen, Adrienne M Stilp, Tin Louie, Sonia Ancoli-Israel, Raanan Arens, Richard Barfield, Jennifer E Below, Jianwen Cai, Matthew P Conomos, Daniel S Evans, Alexis C Frazier-Wood, Sina A Gharib, Kevin J Gleason, Daniel J Gottlieb, David R Hillman, W Craig Johnson, David J Lederer, Jiwon Lee, Jose S Loredo, Hao Mei, Sutapa Mukherjee, Sanjay R Patel, Wendy S Post, Shaun M Purcell, Alberto R Ramos, Kathryn J Reid, Ken Rice, Neomi A Shah, Tamar Sofer, Kent D Taylor, Timothy A Thornton, Heming Wang, Kristine Yaffe, Phyllis C Zee, Craig L Hanis, Lyle J Palmer, Jerome I Rotter, Katie L Stone, Gregory J Tranah, James G Wilson, Shamil R Sunyaev, Cathy C Laurie, Xiaofeng Zhu, Richa Saxena, Xihong Lin, and Susan Redline

Subjects
Genetics, QH426-470
Abstract

Sleep disordered breathing (SDB)-related overnight hypoxemia is associated with cardiometabolic disease and other comorbidities. Understanding the genetic bases for variations in nocturnal hypoxemia may help understand mechanisms influencing oxygenation and SDB-related mortality. We conducted genome-wide association tests across 10 cohorts and 4 populations to identify genetic variants associated with three correlated measures of overnight oxyhemoglobin saturation: average and minimum oxyhemoglobin saturation during sleep and the percent of sleep with oxyhemoglobin saturation under 90%. The discovery sample consisted of 8,326 individuals. Variants with p < 1 × 10(-6) were analyzed in a replication group of 14,410 individuals. We identified 3 significantly associated regions, including 2 regions in multi-ethnic analyses (2q12, 10q22). SNPs in the 2q12 region associated with minimum SpO2 (rs78136548 p = 2.70 × 10(-10)). SNPs at 10q22 were associated with all three traits including average SpO2 (rs72805692 p = 4.58 × 10(-8)). SNPs in both regions were associated in over 20,000 individuals and are supported by prior associations or functional evidence. Four additional significant regions were detected in secondary sex-stratified and combined discovery and replication analyses, including a region overlapping Reelin, a known marker of respiratory complex neurons.These are the first genome-wide significant findings reported for oxyhemoglobin saturation during sleep, a phenotype of high clinical interest. Our replicated associations with HK1 and IL18R1 suggest that variants in inflammatory pathways, such as the biologically-plausible NLRP3 inflammasome, may contribute to nocturnal hypoxemia.

Published
2019
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20. Correction: Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations.

Author

Jingjing Liang, Thu H Le, Digna R Velez Edwards, Bamidele O Tayo, Kyle J Gaulton, Jennifer A Smith, Yingchang Lu, Richard A Jensen, Guanjie Chen, Lisa R Yanek, Karen Schwander, Salman M Tajuddin, Tamar Sofer, Wonji Kim, James Kayima, Colin A McKenzie, Ervin Fox, Michael A Nalls, J Hunter Young, Yan V Sun, Jacqueline M Lane, Sylvia Cechova, Jie Zhou, Hua Tang, Myriam Fornage, Solomon K Musani, Heming Wang, Juyoung Lee, Adebowale Adeyemo, Albert W Dreisbach, Terrence Forrester, Pei-Lun Chu, Anne Cappola, Michele K Evans, Alanna C Morrison, Lisa W Martin, Kerri L Wiggins, Qin Hui, Wei Zhao, Rebecca D Jackson, Erin B Ware, Jessica D Faul, Alex P Reiner, Michael Bray, Joshua C Denny, Thomas H Mosley, Walter Palmas, Xiuqing Guo, George J Papanicolaou, Alan D Penman, Joseph F Polak, Kenneth Rice, Ken D Taylor, Eric Boerwinkle, Erwin P Bottinger, Kiang Liu, Neil Risch, Steven C Hunt, Charles Kooperberg, Alan B Zonderman, Cathy C Laurie, Diane M Becker, Jianwen Cai, Ruth J F Loos, Bruce M Psaty, David R Weir, Sharon L R Kardia, Donna K Arnett, Sungho Won, Todd L Edwards, Susan Redline, Richard S Cooper, D C Rao, Jerome I Rotter, Charles Rotimi, Daniel Levy, Aravinda Chakravarti, Xiaofeng Zhu, and Nora Franceschini

Subjects
Genetics, QH426-470
Abstract

[This corrects the article DOI: 10.1371/journal.pgen.1006728.].

Published
2018
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21. Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations.

Author

Jingjing Liang, Thu H Le, Digna R Velez Edwards, Bamidele O Tayo, Kyle J Gaulton, Jennifer A Smith, Yingchang Lu, Richard A Jensen, Guanjie Chen, Lisa R Yanek, Karen Schwander, Salman M Tajuddin, Tamar Sofer, Wonji Kim, James Kayima, Colin A McKenzie, Ervin Fox, Michael A Nalls, J Hunter Young, Yan V Sun, Jacqueline M Lane, Sylvia Cechova, Jie Zhou, Hua Tang, Myriam Fornage, Solomon K Musani, Heming Wang, Juyoung Lee, Adebowale Adeyemo, Albert W Dreisbach, Terrence Forrester, Pei-Lun Chu, Anne Cappola, Michele K Evans, Alanna C Morrison, Lisa W Martin, Kerri L Wiggins, Qin Hui, Wei Zhao, Rebecca D Jackson, Erin B Ware, Jessica D Faul, Alex P Reiner, Michael Bray, Joshua C Denny, Thomas H Mosley, Walter Palmas, Xiuqing Guo, George J Papanicolaou, Alan D Penman, Joseph F Polak, Kenneth Rice, Ken D Taylor, Eric Boerwinkle, Erwin P Bottinger, Kiang Liu, Neil Risch, Steven C Hunt, Charles Kooperberg, Alan B Zonderman, Cathy C Laurie, Diane M Becker, Jianwen Cai, Ruth J F Loos, Bruce M Psaty, David R Weir, Sharon L R Kardia, Donna K Arnett, Sungho Won, Todd L Edwards, Susan Redline, Richard S Cooper, D C Rao, Jerome I Rotter, Charles Rotimi, Daniel Levy, Aravinda Chakravarti, Xiaofeng Zhu, and Nora Franceschini

Subjects
Genetics, QH426-470
Abstract

Hypertension is a leading cause of global disease, mortality, and disability. While individuals of African descent suffer a disproportionate burden of hypertension and its complications, they have been underrepresented in genetic studies. To identify novel susceptibility loci for blood pressure and hypertension in people of African ancestry, we performed both single and multiple-trait genome-wide association analyses. We analyzed 21 genome-wide association studies comprised of 31,968 individuals of African ancestry, and validated our results with additional 54,395 individuals from multi-ethnic studies. These analyses identified nine loci with eleven independent variants which reached genome-wide significance (P < 1.25×10-8) for either systolic and diastolic blood pressure, hypertension, or for combined traits. Single-trait analyses identified two loci (TARID/TCF21 and LLPH/TMBIM4) and multiple-trait analyses identified one novel locus (FRMD3) for blood pressure. At these three loci, as well as at GRP20/CDH17, associated variants had alleles common only in African-ancestry populations. Functional annotation showed enrichment for genes expressed in immune and kidney cells, as well as in heart and vascular cells/tissues. Experiments driven by these findings and using angiotensin-II induced hypertension in mice showed altered kidney mRNA expression of six genes, suggesting their potential role in hypertension. Our study provides new evidence for genes related to hypertension susceptibility, and the need to study African-ancestry populations in order to identify biologic factors contributing to hypertension.

Published
2017
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22. Genome-wide association study of red blood cell traits in Hispanics/Latinos: The Hispanic Community Health Study/Study of Latinos.

Author

Chani J Hodonsky, Deepti Jain, Ursula M Schick, Jean V Morrison, Lisa Brown, Caitlin P McHugh, Claudia Schurmann, Diane D Chen, Yong Mei Liu, Paul L Auer, Cecilia A Laurie, Kent D Taylor, Brian L Browning, Yun Li, George Papanicolaou, Jerome I Rotter, Ryo Kurita, Yukio Nakamura, Sharon R Browning, Ruth J F Loos, Kari E North, Cathy C Laurie, Timothy A Thornton, Nathan Pankratz, Daniel E Bauer, Tamar Sofer, and Alex P Reiner

Subjects
Genetics, QH426-470
Abstract

Prior GWAS have identified loci associated with red blood cell (RBC) traits in populations of European, African, and Asian ancestry. These studies have not included individuals with an Amerindian ancestral background, such as Hispanics/Latinos, nor evaluated the full spectrum of genomic variation beyond single nucleotide variants. Using a custom genotyping array enriched for Amerindian ancestral content and 1000 Genomes imputation, we performed GWAS in 12,502 participants of Hispanic Community Health Study and Study of Latinos (HCHS/SOL) for hematocrit, hemoglobin, RBC count, RBC distribution width (RDW), and RBC indices. Approximately 60% of previously reported RBC trait loci generalized to HCHS/SOL Hispanics/Latinos, including African ancestral alpha- and beta-globin gene variants. In addition to the known 3.8kb alpha-globin copy number variant, we identified an Amerindian ancestral association in an alpha-globin regulatory region on chromosome 16p13.3 for mean corpuscular volume and mean corpuscular hemoglobin. We also discovered and replicated three genome-wide significant variants in previously unreported loci for RDW (SLC12A2 rs17764730, PSMB5 rs941718), and hematocrit (PROX1 rs3754140). Among the proxy variants at the SLC12A2 locus we identified rs3812049, located in a bi-directional promoter between SLC12A2 (which encodes a red cell membrane ion-transport protein) and an upstream anti-sense long-noncoding RNA, LINC01184, as the likely causal variant. We further demonstrate that disruption of the regulatory element harboring rs3812049 affects transcription of SLC12A2 and LINC01184 in human erythroid progenitor cells. Together, these results reinforce the importance of genetic study of diverse ancestral populations, in particular Hispanics/Latinos.

Published
2017
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23. Social and scientific motivations to move beyond groups in allele frequencies: The TOPMed experience

Author

Sarah C. Nelson, Stephanie M. Gogarten, Stephanie M. Fullerton, Carmen R. Isasi, Braxton D. Mitchell, Kari E. North, Stephen S. Rich, Matthew R.G. Taylor, Sebastian Zöllner, and Tamar Sofer

Subjects
Motivation, Gene Frequency, Perspective, Ethnicity, Genetics, Humans, Genomics, Precision Medicine, Genetics (clinical)
Abstract

For the genomics community, allele frequencies within defined groups (or "strata") are useful across multiple research and clinical contexts. Benefits include allowing researchers to identify populations for replication or "look up" studies, enabling researchers to compare population-specific frequencies to validate findings, and facilitating assessment of variant pathogenicity in clinical contexts. However, there are potential concerns with stratified allele frequencies. These include potential re-identification (determining whether or not an individual participated in a given research study based on allele frequencies and individual-level genetic data), harm from associating stigmatizing variants with specific groups, potential reification of race as a biological rather than a socio-political category, and whether presenting stratified frequencies-and the downstream applications that this presentation enables-is consistent with participants' informed consents. The NHLBI Trans-Omics for Precision Medicine (TOPMed) program considered the scientific and social implications of different approaches for adding stratified frequencies to the TOPMed BRAVO (Browse All Variants Online) variant server. We recommend a novel approach of presenting ancestry-specific allele frequencies using a statistical method based upon local genetic ancestry inference. Notably, this approach does not require grouping individuals by either predominant global ancestry or race/ethnicity and, therefore, mitigates re-identification and other concerns as the mixture distribution of ancestral allele frequencies varies across the genome. Here we describe our considerations and approach, which can assist other genomics research programs facing similar issues of how to define and present stratified frequencies in publicly available variant databases.

Published
2022

24. Assessing the contribution of rare genetic variants to phenotypes of chronic obstructive pulmonary disease using whole-genome sequence data

Author

Wonji, Kim, Julian, Hecker, R Graham, Barr, Eric, Boerwinkle, Brian, Cade, Adolfo, Correa, Josée, Dupuis, Sina A, Gharib, Leslie, Lange, Stephanie J, London, Alanna C, Morrison, George T, O'Connor, Elizabeth C, Oelsner, Bruce M, Psaty, Ramachandran S, Vasan, Susan, Redline, Stephen S, Rich, Jerome I, Rotter, Bing, Yu, Christoph, Lange, Ani, Manichaikul, Jin J, Zhou, Tamar, Sofer, Edwin K, Silverman, Dandi, Qiao, and Michael H, Cho

Subjects
Pulmonary Disease, Chronic Obstructive, Phenotype, Genetics, Humans, Genetic Predisposition to Disease, Original Article, General Medicine, Polymorphism, Single Nucleotide, Molecular Biology, Genetics (clinical), Genome-Wide Association Study
Abstract

Rationale: Genetic variation has a substantial contribution to chronic obstructive pulmonary disease (COPD) and lung function measurements. Heritability estimates using genome-wide genotyping data can be biased if analyses do not appropriately account for the nonuniform distribution of genetic effects across the allele frequency and linkage disequilibrium (LD) spectrum. In addition, the contribution of rare variants has been unclear. Objectives: We sought to assess the heritability of COPD and lung function using whole-genome sequence data from the Trans-Omics for Precision Medicine program. Methods: Using the genome-based restricted maximum likelihood method, we partitioned the genome into bins based on minor allele frequency and LD scores and estimated heritability of COPD, FEV1% predicted and FEV1/FVC ratio in 11 051 European ancestry and 5853 African-American participants. Measurements and Main Results: In European ancestry participants, the estimated heritability of COPD, FEV1% predicted and FEV1/FVC ratio were 35.5%, 55.6% and 32.5%, of which 18.8%, 19.7%, 17.8% were from common variants, and 16.6%, 35.8%, and 14.6% were from rare variants. These estimates had wide confidence intervals, with common variants and some sets of rare variants showing a statistically significant contribution (P-value

Published
2022

25. Genetic loci of beta-aminoisobutyric acid are associated with aging-related mild cognitive impairment

Author

Einat Granot-Hershkovitz, Brian Spitzer, Yunju Yang, Wassim Tarraf, Bing Yu, Eric Boerwinkle, Myriam Fornage, Thomas H. Mosley, Charles DeCarli, Bruce S. Kristal, Hector M. González, and Tamar Sofer

Subjects
Aging, Human Genome, Clinical Sciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Single Nucleotide, Neurodegenerative, Alzheimer's Disease, Brain Disorders, Cellular and Molecular Neuroscience, Psychiatry and Mental health, Genetic Loci, Clinical Research, Acquired Cognitive Impairment, Genetics, Public Health and Health Services, Humans, 2.1 Biological and endogenous factors, Psychology, Dementia, Polymorphism, Aetiology, Biological Psychiatry, Genome-Wide Association Study
Abstract

We studied the genetic associations of a previously developed Metabolomic Risk Score (MRS) for Mild Cognitive Impairment (MCI) and beta-aminoisobutyric acid metabolite (BAIBA)—the metabolite highlighted by results from a genome-wide association study (GWAS) of the MCI-MRS, and assessed their association with MCI in datasets of diverse race/ethnicities. We first performed a GWAS for the MCI-MRS and BAIBA, in Hispanic/Latino adults (n = 3890) from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). We identified ten independent genome-wide significant (p value −8) variants associated with MCI-MRS or BAIBA. Variants associated with the MCI-MRS are located in the Alanine-Glyoxylate Aminotransferase 2 (AGXT2 gene), which is known to be associated with BAIBA metabolism. Variants associated with BAIBA are located in the AGXT2 gene and in the SLC6A13 gene. Next, we tested the variants’ association with MCI in independent datasets of n = 3178 HCHS/SOL older individuals, n = 3775 European Americans, and n = 1032 African Americans from the Atherosclerosis Risk In Communities (ARIC) study. Variants were considered associated with MCI if their p value AGXT2 region were associated with MCI. Mediation analysis supported the mediation effect of BAIBA between the two genetic variants and MCI (p value = 0.004 for causal mediated effect). In summary, genetic variants in the AGXT2 region are associated with MCI in Hispanic/Latino, African, and European American populations in the USA, and their effect is likely mediated by changes in BAIBA levels.

Published
2023

26. Interaction analysis of ancestry-enriched variants with APOE-ɛ4 on MCI in the Study of Latinos-Investigation of Neurocognitive Aging

Author

Einat Granot-Hershkovitz, Rui Xia, Yunju Yang, Brian Spitzer, Wassim Tarraf, Priscilla M. Vásquez, Richard B. Lipton, Martha Daviglus, Maria Argos, Jianwen Cai, Robert Kaplan, Myriam Fornage, Charles DeCarli, Hector M. Gonzalez, and Tamar Sofer

Subjects
Aging, Multidisciplinary, Prevention, Apolipoprotein E4, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Hispanic or Latino, Neurodegenerative, Alzheimer's Disease, Atherosclerosis, Cardiovascular, Brain Disorders, Alzheimer Disease, Acquired Cognitive Impairment, Genetics, Humans, 2.1 Biological and endogenous factors, Cognitive Dysfunction, Dementia, Aetiology
Abstract

APOE-ɛ4 risk on Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD) differs between race/ethnic groups, presumably due to ancestral genomic background surrounding the APOE locus. We studied whether African and Amerindian ancestry-enriched genetic variants in the APOE region modify the effect of the APOE-ɛ4 alleles on Mild Cognitive Impairment (MCI) in Hispanics/Latinos. We defined African and Amerindian ancestry-enriched variants as those common in one Hispanic/Latino parental ancestry and rare in the other two. We identified such variants in the APOE region with a predicted moderate impact based on the SnpEff tool. We tested their interaction with APOE-ɛ4 on MCI in the Study of Latinos-Investigation of Neurocognitive Aging (SOL-INCA) population and African Americans from the Atherosclerosis Risk In Communities (ARIC) study. We identified 5 Amerindian and 14 African enriched variants with an expected moderate effect. A suggestive significant interaction (p-value = 0.01) was found for one African-enriched variant, rs8112679, located in the ZNF222 gene fourth exon. Our results suggest there are no ancestry-enriched variants with large effect sizes of interaction effects with APOE-ɛ4 on MCI in the APOE region in the Hispanic/Latino population. Further studies are needed in larger datasets to identify potential interactions with smaller effect sizes.

Published
2023

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

Author

Xiaowei Hu, Dandi Qiao, Wonji Kim, Matthew Moll, Pallavi P. Balte, Leslie A. Lange, Traci M. Bartz, Rajesh Kumar, Xingnan Li, Bing Yu, Brian E. Cade, Cecelia A. Laurie, Tamar Sofer, Ingo Ruczinski, Deborah A. Nickerson, Donna M. Muzny, Ginger A. Metcalf, Harshavardhan Doddapaneni, Stacy Gabriel, Namrata Gupta, Shannon Dugan-Perez, L. Adrienne Cupples, Laura R. Loehr, Deepti Jain, Jerome I. Rotter, James G. Wilson, Bruce M. Psaty, Myriam Fornage, Alanna C. Morrison, Ramachandran S. Vasan, George Washko, Stephen S. Rich, George T. O’Connor, Eugene Bleecker, Robert C. Kaplan, Ravi Kalhan, Susan Redline, Sina A. Gharib, Deborah Meyers, Victor Ortega, Josée Dupuis, Stephanie J. London, Tuuli Lappalainen, Elizabeth C. Oelsner, Edwin K. Silverman, R. Graham Barr, Timothy A. Thornton, Heather E. Wheeler, Michael H. Cho, Hae Kyung Im, and Ani Manichaikul

Subjects
Pulmonary Disease, Chronic Obstructive, Risk Factors, Genetics, Humans, National Heart, Lung, and Blood Institute (U.S.), Transcriptome, Lung, Article, United States, Genetics (clinical)
Abstract

While polygenic risk scores (PRSs) enable early identification of genetic risk for chronic obstructive pulmonary disease (COPD), predictive performance is limited when the discovery and target populations are not well matched. Hypothesizing that the biological mechanisms of disease are shared across ancestry groups, we introduce a PrediXcan-derived polygenic transcriptome risk score (PTRS) to improve cross-ethnic portability of risk prediction. We constructed the PTRS using summary statistics from application of PrediXcan on large-scale GWASs of lung function (forced expiratory volume in 1 s [FEV(1)] and its ratio to forced vital capacity [FEV(1)/FVC]) in the UK Biobank. We examined prediction performance and cross-ethnic portability of PTRS through smoking-stratified analyses both on 29,381 multi-ethnic participants from TOPMed population/family-based cohorts and on 11,771 multi-ethnic participants from TOPMed COPD-enriched studies. Analyses were carried out for two dichotomous COPD traits (moderate-to-severe and severe COPD) and two quantitative lung function traits (FEV(1) and FEV(1)/FVC). While the proposed PTRS showed weaker associations with disease than PRS for European ancestry, the PTRS showed stronger association with COPD than PRS for African Americans (e.g., odds ratio [OR] = 1.24 [95% confidence interval [CI]: 1.08–1.43] for PTRS versus 1.10 [0.96–1.26] for PRS among heavy smokers with ≥ 40 pack-years of smoking) for moderate-to-severe COPD. Cross-ethnic portability of the PTRS was significantly higher than the PRS (paired t test p

Published
2022

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

Author

Daniel H. Katz, Usman A. Tahir, Alexander G. Bick, Akhil Pampana, Debby Ngo, Mark D. Benson, Zhi Yu, Jeremy M. Robbins, Zsu-Zsu Chen, Daniel E. Cruz, Shuliang Deng, Laurie Farrell, Sumita Sinha, Alec A. Schmaier, Dongxiao Shen, Yan Gao, Michael E. Hall, Adolfo Correa, Russell P. Tracy, Peter Durda, Kent D. Taylor, Yongmei Liu, W. Craig Johnson, Xiuqing Guo, Jie Yao, Yii-Der Ida Chen, Ani W. Manichaikul, Deepti Jain, Claude Bouchard, Mark A. Sarzynski, Stephen S. Rich, Jerome I. Rotter, Thomas J. Wang, James G. Wilson, Pradeep Natarajan, Robert E. Gerszten, Namiko Abe, Gonçalo Abecasis, Francois Aguet, Christine Albert, Laura Almasy, Alvaro Alonso, Seth Ament, Peter Anderson, Pramod Anugu, Deborah Applebaum-Bowden, Kristin Ardlie, Dan Arking, Donna K. Arnett, Allison Ashley-Koch, Stella Aslibekyan, Tim Assimes, Paul Auer, Dimitrios Avramopoulos, Najib Ayas, Adithya Balasubramanian, John Barnard, Kathleen Barnes, R. Graham Barr, Emily Barron-Casella, Lucas Barwick, Terri Beaty, Gerald Beck, Diane Becker, Lewis Becker, Rebecca Beer, Amber Beitelshees, Emelia Benjamin, Takis Benos, Marcos Bezerra, Larry Bielak, Joshua Bis, Thomas Blackwell, John Blangero, Eric Boerwinkle, Donald W. Bowden, Russell Bowler, Jennifer Brody, Ulrich Broeckel, Jai Broome, Deborah Brown, Karen Bunting, Esteban Burchard, Carlos Bustamante, Erin Buth, Brian Cade, Jonathan Cardwell, Vincent Carey, Julie Carrier, April Carson, Cara Carty, Richard Casaburi, Juan P. Casas Romero, James Casella, Peter Castaldi, Mark Chaffin, Christy Chang, Yi-Cheng Chang, Daniel Chasman, Sameer Chavan, Bo-Juen Chen, Wei-Min Chen, Michael Cho, Seung Hoan Choi, Lee-Ming Chuang, Mina Chung, Ren-Hua Chung, Clary Clish, Suzy Comhair, Matthew Conomos, Elaine Cornell, Carolyn Crandall, James Crapo, L. Adrienne Cupples, Joanne Curran, Jeffrey Curtis, Brian Custer, Coleen Damcott, Dawood Darbar, Sean David, Colleen Davis, Michelle Daya, Mariza de Andrade, Lisa de las Fuentes, Paul de Vries, Michael DeBaun, Ranjan Deka, Dawn DeMeo, Scott Devine, Huyen Dinh, Harsha Doddapaneni, Qing Duan, Shannon Dugan-Perez, Ravi Duggirala, Jon Peter Durda, Susan K. Dutcher, Charles Eaton, Lynette Ekunwe, Adel El Boueiz, Patrick Ellinor, Leslie Emery, Serpil Erzurum, Charles Farber, Jesse Farek, Tasha Fingerlin, Matthew Flickinger, Myriam Fornage, Nora Franceschini, Chris Frazar, Mao Fu, Stephanie M. Fullerton, Lucinda Fulton, Stacey Gabriel, Weiniu Gan, Shanshan Gao, Margery Gass, Heather Geiger, Bruce Gelb, Mark Geraci, Soren Germer, Robert Gerszten, Auyon Ghosh, Richard Gibbs, Chris Gignoux, Mark Gladwin, David Glahn, Stephanie Gogarten, Da-Wei Gong, Harald Goring, Sharon Graw, Kathryn J. Gray, Daniel Grine, Colin Gross, C. Charles Gu, Yue Guan, Namrata Gupta, David M. Haas, Jeff Haessler, Michael Hall, Yi Han, Patrick Hanly, Daniel Harris, Nicola L. Hawley, Jiang He, Ben Heavner, Susan Heckbert, Ryan Hernandez, David Herrington, Craig Hersh, Bertha Hidalgo, James Hixson, Brian Hobbs, John Hokanson, Elliott Hong, Karin Hoth, Chao (Agnes) Hsiung, Jianhong Hu, Yi-Jen Hung, Haley Huston, Chii Min Hwu, Marguerite Ryan Irvin, Rebecca Jackson, Cashell Jaquish, Jill Johnsen, Andrew Johnson, Craig Johnson, Rich Johnston, Kimberly Jones, Hyun Min Kang, Robert Kaplan, Sharon Kardia, Shannon Kelly, Eimear Kenny, Michael Kessler, Alyna Khan, Ziad Khan, Wonji Kim, John Kimoff, Greg Kinney, Barbara Konkle, Charles Kooperberg, Holly Kramer, Christoph Lange, Ethan Lange, Leslie Lange, Cathy Laurie, Cecelia Laurie, Meryl LeBoff, Jiwon Lee, Sandra Lee, Wen-Jane Lee, Jonathon LeFaive, David Levine, Dan Levy, Joshua Lewis, Xiaohui Li, Yun Li, Henry Lin, Honghuang Lin, Xihong Lin, Simin Liu, Yu Liu, Ruth J.F. Loos, Steven Lubitz, Kathryn Lunetta, James Luo, Ulysses Magalang, Michael Mahaney, Barry Make, Ani Manichaikul, Alisa Manning, JoAnn Manson, Lisa Martin, Melissa Marton, Susan Mathai, Rasika Mathias, Susanne May, Patrick McArdle, Merry-Lynn McDonald, Sean McFarland, Stephen McGarvey, Daniel McGoldrick, Caitlin McHugh, Becky McNeil, Hao Mei, James Meigs, Vipin Menon, Luisa Mestroni, Ginger Metcalf, Deborah A. Meyers, Emmanuel Mignot, Julie Mikulla, Nancy Min, Mollie Minear, Ryan L. Minster, Braxton D. Mitchell, Matt Moll, Zeineen Momin, May E. Montasser, Courtney Montgomery, Donna Muzny, Josyf C. Mychaleckyj, Girish Nadkarni, Rakhi Naik, Take Naseri, Sergei Nekhai, Sarah C. Nelson, Bonnie Neltner, Caitlin Nessner, Deborah Nickerson, Osuji Nkechinyere, Kari North, Jeff O’Connell, Tim O’Connor, Heather Ochs-Balcom, Geoffrey Okwuonu, Allan Pack, David T. Paik, Nicholette Palmer, James Pankow, George Papanicolaou, Cora Parker, Gina Peloso, Juan Manuel Peralta, Marco Perez, James Perry, Ulrike Peters, Patricia Peyser, Lawrence S. Phillips, Jacob Pleiness, Toni Pollin, Wendy Post, Julia Powers Becker, Meher Preethi Boorgula, Michael Preuss, Bruce Psaty, Pankaj Qasba, Dandi Qiao, Zhaohui Qin, Nicholas Rafaels, Laura Raffield, Mahitha Rajendran, Vasan S. Ramachandran, D.C. Rao, Laura Rasmussen-Torvik, Aakrosh Ratan, Susan Redline, Robert Reed, Catherine Reeves, Elizabeth Regan, Alex Reiner, Muagututi’a Sefuiva Reupena, Ken Rice, Stephen Rich, Rebecca Robillard, Nicolas Robine, Dan Roden, Carolina Roselli, Jerome Rotter, Ingo Ruczinski, Alexi Runnels, Pamela Russell, Sarah Ruuska, Kathleen Ryan, Ester Cerdeira Sabino, Danish Saleheen, Shabnam Salimi, Sejal Salvi, Steven Salzberg, Kevin Sandow, Vijay G. Sankaran, Jireh Santibanez, Karen Schwander, David Schwartz, Frank Sciurba, Christine Seidman, Jonathan Seidman, Frédéric Sériès, Vivien Sheehan, Stephanie L. Sherman, Amol Shetty, Aniket Shetty, Wayne Hui-Heng Sheu, M. Benjamin Shoemaker, Brian Silver, Edwin Silverman, Robert Skomro, Albert Vernon Smith, Jennifer Smith, Josh Smith, Nicholas Smith, Tanja Smith, Sylvia Smoller, Beverly Snively, Michael Snyder, Tamar Sofer, Nona Sotoodehnia, Adrienne M. Stilp, Garrett Storm, Elizabeth Streeten, Jessica Lasky Su, Yun Ju Sung, Jody Sylvia, Adam Szpiro, Daniel Taliun, Hua Tang, Margaret Taub, Matthew Taylor, Simeon Taylor, Marilyn Telen, Timothy A. Thornton, Machiko Threlkeld, Lesley Tinker, David Tirschwell, Sarah Tishkoff, Hemant Tiwari, Catherine Tong, Russell Tracy, Michael Tsai, Dhananjay Vaidya, David Van Den Berg, Peter VandeHaar, Scott Vrieze, Tarik Walker, Robert Wallace, Avram Walts, Fei Fei Wang, Heming Wang, Jiongming Wang, Karol Watson, Jennifer Watt, Daniel E. Weeks, Joshua Weinstock, Bruce Weir, Scott T. Weiss, Lu-Chen Weng, Jennifer Wessel, Cristen Willer, Kayleen Williams, L. Keoki Williams, Carla Wilson, James Wilson, Lara Winterkorn, Quenna Wong, Joseph Wu, Huichun Xu, Lisa Yanek, Ivana Yang, Ketian Yu, Seyedeh Maryam Zekavat, Yingze Zhang, Snow Xueyan Zhao, Wei Zhao, Xiaofeng Zhu, Michael Zody, and Sebastian Zoellner

Subjects
Adult, Male, Proteomics, Aging, Whole genome sequence analysis, Proteome, Clinical Sciences, Black People, Disease, Computational biology, race and ethnicity, Cardiorespiratory Medicine and Haematology, Cardiovascular, Article, proteomics, cardiovascular disease, Physiology (medical), Genetics, 2.1 Biological and endogenous factors, Humans, Medicine, Aetiology, Lung, Heart Disease - Coronary Heart Disease, and Blood Institute TOPMed (Trans-Omics for Precision Medicine) Consortium†, business.industry, Prevention, Human Genome, National Heart, Genomics, Blood proteins, Genetic architecture, Heart Disease, Good Health and Well Being, Cardiovascular System & Hematology, Cardiovascular Diseases, Public Health and Health Services, Female, Cardiology and Cardiovascular Medicine, business, Biotechnology, Genome-Wide Association Study
Abstract

Background: Plasma proteins are critical mediators of cardiovascular processes and are the targets of many drugs. Previous efforts to characterize the genetic architecture of the plasma proteome have been limited by a focus on individuals of European descent and leveraged genotyping arrays and imputation. Here we describe whole genome sequence analysis of the plasma proteome in individuals with greater African ancestry, increasing our power to identify novel genetic determinants. Methods: Proteomic profiling of 1301 proteins was performed in 1852 Black adults from the Jackson Heart Study using aptamer-based proteomics (SomaScan). Whole genome sequencing association analysis was ascertained for all variants with minor allele count ≥5. Results were validated using an alternative, antibody-based, proteomic platform (Olink) as well as replicated in the Multi-Ethnic Study of Atherosclerosis and the HERITAGE Family Study (Health, Risk Factors, Exercise Training and Genetics). Results: We identify 569 genetic associations between 479 proteins and 438 unique genetic regions at a Bonferroni-adjusted significance level of 3.8×10 -11 . These associations include 114 novel locus-protein relationships and an additional 217 novel sentinel variant-protein relationships. Novel cardiovascular findings include new protein associations at the APOE gene locus including ZAP70 (sentinel single nucleotide polymorphism [SNP] rs7412-T, β=0.61±0.05, P =3.27×10 -30 ) and MMP-3 (β=-0.60±0.05, P =1.67×10 -32 ), as well as a completely novel pleiotropic locus at the HPX gene, associated with 9 proteins. Further, the associations suggest new mechanisms of genetically mediated cardiovascular disease linked to African ancestry; we identify a novel association between variants linked to APOL1-associated chronic kidney and heart disease and the protein CKAP2 (rs73885319-G, β=0.34±0.04, P =1.34×10 -17 ) as well as an association between ATTR amyloidosis and RBP4 levels in community-dwelling individuals without heart failure. Conclusions: Taken together, these results provide evidence for the functional importance of variants in non-European populations, and suggest new biological mechanisms for ancestry-specific determinants of lipids, coagulation, and myocardial function.

Published
2022

29. An integrated multi-omics analysis of sleep-disordered breathing traits implicates P2XR4 purinergic signaling

Author

Nuzulul Kurniansyah, Danielle A. Wallace, Ying Zhang, Bing Yu, Brian Cade, Heming Wang, Heather M. Ochs-Balcom, Alexander P. Reiner, Alberto R. Ramos, Joshua D. Smith, Jianwen Cai, Martha Daviglus, Phyllis C. Zee, Robert Kaplan, Charles Kooperberg, Stephen S. Rich, Jerome I. Rotter, Sina A. Gharib, Susan Redline, and Tamar Sofer

Subjects
Multifactorial Inheritance, Prevention, Neurosciences, Medicine (miscellaneous), Hispanic or Latino, Multiomics, Cardiovascular, General Biochemistry, Genetics and Molecular Biology, Sleep Apnea Syndromes, Mental Health, Good Health and Well Being, Clinical Research, Oxyhemoglobins, Receptors, Genetics, Humans, 2.1 Biological and endogenous factors, Aetiology, General Agricultural and Biological Sciences, Sleep, Sleep Research, Purinergic P2X7, Lung
Abstract

Sleep Disordered Breathing (SDB) is a common disease associated with increased risk for cardiometabolic, cardiovascular, and cognitive diseases. How SDB affects the molecular environment is still poorly understood. We study the association of three SDB measures with gene expression measured using RNA-seq in multiple blood tissues from the Multi-Ethnic Study of Atherosclerosis. We develop genetic instrumental variables for the associated transcripts as polygenic risk scores (tPRS), then generalize and validate the tPRS in the Women’s Health Initiative. We measure the associations of the validated tPRS with SDB and serum metabolites in Hispanic Community Health Study/Study of Latinos. Here we find differential gene expression by blood cell type in relation to SDB traits and link P2XR4 expression to average oxyhemoglobin saturation during sleep and butyrylcarnitine (C4) levels. These findings can be used to develop interventions to alleviate the effect of SDB on the human molecular environment.

Published
2023

30. Genetic associations between sleep traits and cognitive ageing outcomes in the Hispanic Community Health Study/Study of Latinos

Author

Yuan Zhang, Michael Elgart, Einat Granot-Hershkovitz, Heming Wang, Wassim Tarraf, Alberto R. Ramos, Ariana M. Stickel, Donglin Zeng, Tanya P. Garcia, Fernando D. Testai, Sylvia Wassertheil-Smoller, Carmen R. Isasi, Martha L. Daviglus, Robert Kaplan, Myriam Fornage, Charles DeCarli, Susan Redline, Hector M. González, and Tamar Sofer

Subjects
Aging, Insomnia, Clinical Sciences, Disorders of Excessive Somnolence, Neurodegenerative, Alzheimer's Disease, Basic Behavioral and Social Science, General Biochemistry, Genetics and Molecular Biology, Daytime sleepiness, Cognition, Clinical Research, Sleep Initiation and Maintenance Disorders, Behavioral and Social Science, Genetics, Acquired Cognitive Impairment, Humans, Cognitive Dysfunction, Polygenetic risk score, Sleep duration, Prevention, Human Genome, Mild cognitive impairment, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), General Medicine, Hispanic or Latino, Brain Disorders, Public Health and Health Services, Dementia, Mental health, Self Report, Global cognitive function, Sleep, Sleep Research, Genome-Wide Association Study
Abstract

BackgroundSleep phenotypes have been reported to be associated with cognitive ageing outcomes. However, there is limited research using genetic variants as proxies for sleep traits to study their associations. We estimated associations between Polygenic Risk Scores (PRSs) for sleep duration, insomnia, daytime sleepiness, and obstructive sleep apnoea (OSA) and measures of cogntive ageing in Hispanic/Latino adults.MethodsWe used summary statistics from published genome-wide association studies to construct PRSs representing the genetic basis of each sleep trait, then we studied the association of the PRSs of the sleep phenotypes with cognitive outcomes in the Hispanic Community Healthy Study/Study of Latinos. The primary model adjusted for age, sex, study centre, and measures of genetic ancestry. Associations are highlighted if their p-value

Published
2023

31. Whole-genome association analyses of sleep-disordered breathing phenotypes in the NHLBI TOPMed program

Author

Russell P. Tracy, Katie L. Stone, Sutapa Mukherjee, David R. Hillman, Xiuqing Guo, Eric Boerwinkle, Gonçalo R. Abecasis, L. Adrienne Cupples, Stephen S. Rich, Richa Saxena, Jerome I. Rotter, Adolfo Correa, Xihong Lin, Man Zhang, James G. Wilson, Ramachandran S. Vasan, Brian E. Cade, Jacqueline M. Lane, Tamar Sofer, Shaun Purcell, Daniel J. Gottlieb, Robert C. Kaplan, Daniel S. Evans, Jiwon Lee, Sina A. Gharib, Bruce M. Psaty, Gregory J. Tranah, Jingjing Liang, Sanjay R. Patel, Lyle J. Palmer, Craig L. Hanis, Kari E. North, Xiaofeng Zhu, Heming Wang, Susan Redline, Han Chen, Deborah A. Nickerson, Hao Mei, and Neomi A. Shah

Subjects
Male, Genome-wide association study, QH426-470, Genome, 0302 clinical medicine, and Blood Institute (U.S.), 2.1 Biological and endogenous factors, GWAS, Precision Medicine, Aetiology, Lung, Genetics (clinical), X chromosome, Genetics, 0303 health sciences, Sleep apnea, Phenotype, 3. Good health, medicine.anatomical_structure, Chromatin Immunoprecipitation Sequencing, Molecular Medicine, Medicine, Female, Sleep Research, Signal Transduction, Genotype, Sequence analysis, Clinical Sciences, Biology, TOPMed Sleep Working Group, 03 medical and health sciences, Sleep Apnea Syndromes, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, medicine, Humans, Genetic Predisposition to Disease, Dental/Oral and Craniofacial Disease, Craniofacial, Association (psychology), Sleep-disordered breathing, Molecular Biology, Gene, Alleles, Genetic Association Studies, 030304 developmental biology, Whole-genome sequencing, Whole Genome Sequencing, Family structure, Research, Human Genome, National Heart, medicine.disease, United States, Genetic architecture, DNA binding site, Good Health and Well Being, Gene Expression Regulation, Sleep disordered breathing, National Heart, Lung, and Blood Institute (U.S.), 030217 neurology & neurosurgery, WGS
Abstract

Background Sleep-disordered breathing is a common disorder associated with significant morbidity. The genetic architecture of sleep-disordered breathing remains poorly understood. Through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, we performed the first whole-genome sequence analysis of sleep-disordered breathing. Methods The study sample was comprised of 7988 individuals of diverse ancestry. Common-variant and pathway analyses included an additional 13,257 individuals. We examined five complementary traits describing different aspects of sleep-disordered breathing: the apnea-hypopnea index, average oxyhemoglobin desaturation per event, average and minimum oxyhemoglobin saturation across the sleep episode, and the percentage of sleep with oxyhemoglobin saturation Results We identified a multi-ethnic set-based rare-variant association (p = 3.48 × 10−8) on chromosome X with ARMCX3. Additional rare-variant associations include ARMCX3-AS1, MRPS33, and C16orf90. Novel common-variant loci were identified in the NRG1 and SLC45A2 regions, and previously associated loci in the IL18RAP and ATP2B4 regions were associated with novel phenotypes. Transcription factor binding site enrichment identified associations with genes implicated with respiratory and craniofacial traits. Additional analyses identified significantly associated pathways. Conclusions We have identified the first gene-based rare-variant associations with objectively measured sleep-disordered breathing traits. Our results increase the understanding of the genetic architecture of sleep-disordered breathing and highlight associations in genes that modulate lung development, inflammation, respiratory rhythmogenesis, and HIF1A-mediated hypoxic response.

Published
2021

32. Genome-wide association study of body fat distribution traits in Hispanics/Latinos from the HCHS/SOL

Author

Esteban J. Parra, Craig L. Hanis, Lisa Sanchez-Johnsen, Kristin L. Young, Misa Graff, Yujie Wang, Adán Valladares, Lauren E. Petty, Yii-Der Ida Chen, Xiuqing Guo, Mark O. Goodarzi, Miguel Cruz, Kari E. North, Anny H. Xiang, Leslie J. Raffel, Matthew A. Allison, Tamar Sofer, Yann C. Klimentidis, Shelly Ann Love, Anne E. Justice, Stephanie M. Gogarten, Fernando Pires Hartwig, Thomas A. Buchanan, Jennifer E. Below, Jingyi Tan, Jie Yao, Jerome I. Rotter, Willa A. Hsueh, Eli Ipp, Walter Palmas, Kent D. Taylor, Heather M. Highland, and Carmen R. Isasi

Subjects
AcademicSubjects/SCI01140, Waist, Ethnic group, 030209 endocrinology & metabolism, Genome-wide association study, Biology, Polymorphism, Single Nucleotide, 03 medical and health sciences, Quantitative Trait, Heritable, 0302 clinical medicine, Genetics, medicine, Body Fat Distribution, Humans, Association Studies Article, Molecular Biology, Alleles, Genetics (clinical), Adiposity, 030304 developmental biology, Body fat distribution, 0303 health sciences, Hispanic latino, Hispanic or Latino, General Medicine, medicine.disease, Hchs sol, Obesity, Body mass index, Genome-Wide Association Study, Demography
Abstract

Author(s): Justice, Anne E; Young, Kristin; Gogarten, Stephanie M; Sofer, Tamar; Graff, Misa; Love, Shelly Ann M; Wang, Yujie; Klimentidis, Yann C; Cruz, Miguel; Guo, Xiuqing; Hartwig, Fernando; Petty, Lauren; Yao, Jie; Allison, Matthew A; Below, Jennifer E; Buchanan, Thomas A; Chen, Yii-Der Ida; Goodarzi, Mark O; Hanis, Craig; Highland, Heather M; Hsueh, Willa A; Ipp, Eli; Parra, Esteban; Palmas, Walter; Raffel, Leslie J; Rotter, Jerome I; Tan, Jingyi; Taylor, Kent D; Valladares, Adan; Xiang, Anny H; Sanchez-Johnsen, Lisa; Isasi, Carmen R; North, Kari E | Abstract: Central obesity is a leading health concern with a great burden carried by ethnic minority populations, especially Hispanics/Latinos. Genetic factors contribute to the obesity burden overall and to inter-population differences. We aimed to identify loci associated with central adiposity measured as waist-to-hip ratio (WHR), waist circumference (WC), and hip circumference (HIP) adjusted for body mass index (adjBMI), using the Hispanic Community Health Study/Study of Latinos (HCHS/SOL); determine if differences in associations differ by background group within HCHS/SOL; and determine whether previously reported associations generalize to HCHS/SOL. Our analyses included 7472 women and 5200 men of mainland (Mexican, Central and South American) and Caribbean (Puerto Rican, Cuban, and Dominican) background residing in the US. We performed genome-wide association analyses stratified and combined across sexes using linear mixed-model regression. We identified 16 variants for WHRadjBMI, 22 for WCadjBMI, and 28 for HIPadjBMI that reached suggestive significance (P l 1x10-6). Many loci exhibited differences in strength of associations by ethnic background and sex. We brought a total of 66 variants forward for validation in cohorts (N = 34 161) with participants of Hispanic/Latino, African and European descent. We confirmed 4 novel loci (P l 0.05 and consistent direction of effect, and P l 5x10-8 after meta-analysis), including 2 for WHRadjBMI (rs13301996, rs79478137); 1 for WCadjBMI (rs3168072); and 1 for HIPadjBMI (rs28692724). Also, we generalized previously reported associations to HCHS/SOL, (8 for WHRadjBMI; 10 for WCadjBMI; 12 for HIPadjBMI). Our study highlights the importance of large-scale genomic studies in ancestrally diverse Hispanic/Latino populations for identifying and characterizing central obesity-susceptibility that may be ancestry-specific.

Published
2021

33. Mendelian randomization analysis of arsenic metabolism and pulmonary function within the Hispanic Community Health Study/Study of Latinos

Author

Maria Argos, Naresh M. Punjabi, Donglin Zeng, H. Dean Hosgood, Yasmin Mossavar-Rahmani, Tamar Sofer, Majid Afshar, Martha L. Daviglus, and Molly Scannell Bryan

Subjects
0301 basic medicine, Adult, Male, Vital capacity, Science, Vital Capacity, Physiology, chemistry.chemical_element, Urine, 010501 environmental sciences, Quantitative trait, 01 natural sciences, Article, Pulmonary function testing, Arsenic, 03 medical and health sciences, Mendelian randomization, Genetics, Medicine, Cacodylic Acid, Humans, 0105 earth and related environmental sciences, Asthma, Multidisciplinary, business.industry, Dietary Arsenic, Chronic obstructive pulmonary disease, food and beverages, Mendelian Randomization Analysis, Oryza, Hispanic or Latino, Middle Aged, medicine.disease, United States, 030104 developmental biology, chemistry, Female, business
Abstract

Arsenic exposure has been linked to poor pulmonary function, and inefficient arsenic metabolizers may be at increased risk. Dietary rice has recently been identified as a possible substantial route of exposure to arsenic, and it remains unknown whether it can provide a sufficient level of exposure to affect pulmonary function in inefficient metabolizers. Within 12,609 participants of HCHS/SOL, asthma diagnoses and spirometry-based measures of pulmonary function were assessed, and rice consumption was inferred from grain intake via a food frequency questionnaire. After stratifying by smoking history, the relationship between arsenic metabolism efficiency [percentages of inorganic arsenic (%iAs), monomethylarsenate (%MMA), and dimethylarsinate (%DMA) species in urine] and the measures of pulmonary function were estimated in a two-sample Mendelian randomization approach (genotype information from an Illumina HumanOmni2.5-8v1-1 array), focusing on participants with high inferred rice consumption. Among never-smoking high inferred consumers of rice (n = 1395), inefficient metabolism was associated with past asthma diagnosis and forced vital capacity below the lower limit of normal (LLN) (OR 1.40, p = 0.0212 and OR 1.42, p = 0.0072, respectively, for each percentage-point increase in %iAs; OR 1.26, p = 0.0240 and OR 1.24, p = 0.0193 for %MMA; OR 0.87, p = 0.0209 and OR 0.87, p = 0.0123 for the marker of efficient metabolism, %DMA). Among ever-smoking high inferred consumers of rice (n = 1127), inefficient metabolism was associated with peak expiratory flow below LLN (OR 1.54, p = 0.0108/percentage-point increase in %iAs, OR 1.37, p = 0.0097 for %MMA, and OR 0.83, p = 0.0093 for %DMA). Less efficient arsenic metabolism was associated with indicators of pulmonary dysfunction among those with high inferred rice consumption, suggesting that reductions in dietary arsenic could improve respiratory health.

Published
2021

34. Life-Course Associations between Blood Pressure-Related Polygenic Risk Scores and Hypertension in the Bogalusa Heart Study

Author

Xiao Sun, Yang Pan, Ruiyuan Zhang, Ileana De Anda-Duran, Zhijie Huang, Changwei Li, Mengyao Shi, Alexander C. Razavi, Lydia A. Bazzano, Jiang He, Tamar Sofer, and Tanika N. Kelly

Subjects
Risk Factors, Hypertension, Genetics, Humans, Blood Pressure, Blood Pressure Determination, Longitudinal Studies, Genetics (clinical), hypertension, polygenic risk score, genetic predisposition, blood pressure, childhood risk factor, genetics
Abstract

Genetic information may help to identify individuals at increased risk for hypertension in early life, prior to the manifestation of elevated blood pressure (BP) values. We examined 369 Black and 832 White Bogalusa Heart Study (BHS) participants recruited in childhood and followed for approximately 37 years. The multi-ancestry genome-wide polygenic risk scores (PRSs) for systolic BP (SBP), diastolic BP (DBP), and hypertension were tested for an association with incident hypertension and stage 2 hypertension using Cox proportional hazards models. Race-stratified analyses were adjusted for baseline age, age2, sex, body mass index, genetic principal components, and BP. In Black participants, each standard deviation increase in SBP and DBP PRS conferred a 38% (p = 0.009) and 22% (p = 0.02) increased risk of hypertension and a 74% (p < 0.001) and 50% (p < 0.001) increased risk of stage 2 hypertension, respectively, while no association was observed with the hypertension PRSs. In Whites, each standard deviation increase in SBP, DBP, and hypertension PRS conferred a 24% (p < 0.05), 29% (p = 0.01), and 25% (p < 0.001) increased risk of hypertension, and a 27% (p = 0.08), 29% (0.01), and 42% (p < 0.001) increased risk of stage 2 hypertension, respectively. The addition of BP PRSs to the covariable-only models generally improved the C-statistics (p < 0.05). Multi-ancestry BP PRSs demonstrate the utility of genomic information in the early life prediction of hypertension.

Published
2022
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35. Genome-wide association study of neck circumference identifies sex-specific loci independent of generalized adiposity

Author

David R. Hillman, Xiaoyu Zhang, Diane T. Smelser, Ching-Ti Liu, Jiwon Lee, H. Lester Kirchner, Yaowu Liu, Hufeng Zhou, Xihong Lin, Brian E. Cade, Tamar Sofer, Sutapa Mukherjee, Susan Redline, and Han Chen

Subjects
0301 basic medicine, Oncology, Adult, Male, medicine.medical_specialty, Adolescent, Endocrinology, Diabetes and Metabolism, Medicine (miscellaneous), Locus (genetics), Genome-wide association study, 030204 cardiovascular system & hematology, Biology, Development, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Sex Factors, Internal medicine, medicine, Genetics, Body Size, Humans, Human height, Gene, Adiposity, Aged, Aged, 80 and over, Nutrition and Dietetics, Anthropometry, Middle Aged, medicine.disease, Sexual dimorphism, Obstructive sleep apnea, 030104 developmental biology, Phenotype, Chromosome 3, Female, Neck, Genome-Wide Association Study
Abstract

Background/objectives Neck circumference, an index of upper airway fat, has been suggested to be an important measure of body-fat distribution with unique associations with health outcomes such as obstructive sleep apnea and metabolic disease. This study aims to study the genetic bases of neck circumference. Methods We conducted a multi-ethnic genome-wide association study of neck circumference, adjusted and unadjusted for BMI, in up to 15,090 European Ancestry (EA) and African American (AA) individuals. Because sexually dimorphic associations have been observed for anthropometric traits, we conducted both sex-combined and sex-specific analysis. Results We identified rs227724 near the Noggin (NOG) gene as a possible quantitative locus for neck circumference in men (N = 8831, P = 1.74 × 10−9) but not in women (P = 0.08). The association was replicated in men (N = 1554, P = 0.045) in an independent dataset. This locus was previously reported to be associated with human height and with self-reported snoring. We also identified rs13087058 on chromosome 3 as a suggestive locus in sex-combined analysis (N = 15090, P = 2.94 × 10−7; replication P =0.049). This locus was also associated with electrocardiogram-assessed PR interval and is a cis-expression quantitative locus for the PDZ Domain-containing ring finger 2 (PDZRN3) gene. Both NOG and PDZRN3 interact with members of transforming growth factor-beta superfamily signaling proteins. Conclusions Our study suggests that neck circumference may have unique genetic basis independent of BMI.

Published
2021

36. The impact of Mendelian sleep and circadian genetic variants in a population setting

Author

Michael N. Weedon, Samuel E. Jones, Jacqueline M. Lane, Jiwon Lee, Hanna M. Ollila, Amy Dawes, Jess Tyrrell, Robin N. Beaumont, Timo Partonen, Ilona Merikanto, Stephen S. Rich, Jerome I. Rotter, Timothy M. Frayling, Martin K. Rutter, Susan Redline, Tamar Sofer, Richa Saxena, Andrew R. Wood, Barsh, Gregory S, Institute for Molecular Medicine Finland, HUS Psychiatry, Research Programs Unit, Faculty Common Matters (Faculty of Medicine), and SLEEPWELL Research Program

Subjects
Sleep Wake Disorders, Cancer Research, Human Genome, 1184 Genetics, developmental biology, physiology, Circadian Rhythm, Receptors, G-Protein-Coupled, G-Protein-Coupled, Phenotype, Clinical Research, Mutation, Receptors, Genetics, 2.1 Biological and endogenous factors, Humans, Aetiology, Sleep Research, Sleep, Molecular Biology, Genetics (clinical), Ecology, Evolution, Behavior and Systematics, Metabolic and endocrine, Developmental Biology
Abstract

Rare variants in ten genes have been reported to cause Mendelian sleep conditions characterised by extreme sleep duration or timing. These include familial natural short sleep (ADRB1, DEC2/BHLHE41, GRM1 and NPSR1), advanced sleep phase (PER2, PER3, CRY2, CSNK1D and TIMELESS) and delayed sleep phase (CRY1). The association of variants in these genes with extreme sleep conditions were usually based on clinically ascertained families, and their effects when identified in the population are unknown. We aimed to determine the effects of these variants on sleep traits in large population-based cohorts. We performed genetic association analysis of variants previously reported to be causal for Mendelian sleep and circadian conditions. Analyses were performed using 191,929 individuals with data on sleep and whole-exome or genome-sequence data from 4 population-based studies: UK Biobank, FINRISK, Health-2000-2001, and the Multi-Ethnic Study of Atherosclerosis (MESA). We identified sleep disorders from self-report, hospital and primary care data. We estimated sleep duration and timing measures from self-report and accelerometery data. We identified carriers for 10 out of 12 previously reported pathogenic variants for 8 of the 10 genes. They ranged in frequency from 1 individual with the variant in CSNK1D to 1,574 individuals with a reported variant in the PER3 gene in the UK Biobank. No carriers for variants reported in NPSR1 or PER2 were identified. We found no association between variants analyzed and extreme sleep or circadian phenotypes. Using sleep timing as a proxy measure for sleep phase, only PER3 and CRY1 variants demonstrated association with earlier and later sleep timing, respectively; however, the magnitude of effect was smaller than previously reported (sleep midpoint ~7 mins earlier and ~5 mins later, respectively). We also performed burden tests of protein truncating (PTVs) or rare missense variants for the 10 genes. Only PTVs in PER2 and PER3 were associated with a relevant trait (for example, 64 individuals with a PTV in PER2 had an odds ratio of 4.4 for being “definitely a morning person”, P = 4x10-8; and had a 57-minute earlier midpoint sleep, P = 5x10-7). Our results indicate that previously reported variants for Mendelian sleep and circadian conditions are often not highly penetrant when ascertained incidentally from the general population.

Published
2022

37. BinomiRare: A robust test for association of a rare genetic variant with a binary outcome for mixed models and any case-control proportion

Author

Ramachandran S. Vasan, Nathan Pankratz, Eric Boerwinkle, Charles Kooperberg, Nicholas L. Smith, Jiwon Lee, Xiuqing Guo, Elizabeth D. Schifano, Matthew P. Conomos, Man Zhang, Andrew D. Johnson, Kent D. Taylor, Jeffrey Haessler, Yao Hu, Alanna C. Morrison, Jeffrey R. O'Connell, W. T. Longstreth, Brandon J. Coombes, Jerome I. Rotter, Deepti Jain, James S. Pankow, Nuzulul Kurniansyah, Amanda A. Seyerle, Stephen S. Rich, Ben Heavner, Daniel J. Gottlieb, Sina A. Gharib, Bruce M. Psaty, Stephanie M. Gogarten, Han Chen, L. Adrienne Cupples, Kenneth Rice, Tamar Sofer, Cecelia A. Laurie, Alexander P. Reiner, and Susan Redline

Subjects
Genetics, Mixed model, mixed models, Disease, Biology, QH426-470, DNA sequencing, Article, targeted gene analysis, Test (assessment), genome sequencing, Covariate, Molecular Medicine, diverse populations, Allele, Null hypothesis, rare variant assocaition testing, Genetics (clinical), Type I and type II errors
Abstract

Summary: Whole-genome sequencing (WGS) and whole-exome sequencing studies have become increasingly available and are being used to identify rare genetic variants associated with health and disease outcomes. Investigators routinely use mixed models to account for genetic relatedness or other clustering variables (e.g., family or household) when testing genetic associations. However, no existing tests of the association of a rare variant with a binary outcome in the presence of correlated data control the type 1 error where there are (1) few individuals harboring the rare allele, (2) a small proportion of cases relative to controls, and (3) covariates to adjust for. Here, we address all three issues in developing a framework for testing rare variant association with a binary trait in individuals harboring at least one risk allele. In this framework, we estimate outcome probabilities under the null hypothesis and then use them, within the individuals with at least one risk allele, to test variant associations. We extend the BinomiRare test, which was previously proposed for independent observations, and develop the Conway-Maxwell-Poisson (CMP) test and study their properties in simulations. We show that the BinomiRare test always controls the type 1 error, while the CMP test sometimes does not. We then use the BinomiRare test to test the association of rare genetic variants in target genes with small-vessel disease (SVD) stroke, short sleep, and venous thromboembolism (VTE), in whole-genome sequence data from the Trans-Omics for Precision Medicine (TOPMed) program.

Published
2021

38. Blood metabolites predicting Mild Cognitive Impairment in the Study of Latinos-Investigation of Neurocognitive Aging (HCHS/SOL)

Author

María J. Marquine, Melissa Lamar, Charles DeCarli, Jan Bressler, Tamar Sofer, Tianyi Huang, Jianwen Cai, Donglin Zeng, Yu Shrike Zhang, Thomas H. Mosley, Yu B, Einat G, Sylvia Wassertheil-Smoller, Gonzalez Hm, Bruce S. Kristal, Wassim Tarraf, Boerwinkle E, Robert C. Kaplan, Martha L. Daviglus, Myriam Fornage, and He S

Subjects
Oncology, Aging, medicine.medical_specialty, Hispanics/Latinos, Hispanics, Neurodegenerative, Alzheimer's Disease, Basic Behavioral and Social Science, risk prediction, mild cognitive impairment, Clinical Research, Cognitive change, Internal medicine, Behavioral and Social Science, Acquired Cognitive Impairment, Genetics, Medicine, Latinos, Cognitive impairment, Penalized regression, Framingham Risk Score, metabolite biomarkers, business.industry, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Hchs sol, Brain Disorders, Psychiatry and Mental health, Good Health and Well Being, metabolomic risk score, Biomedical Imaging, global cognitive change, Dementia, Neurology (clinical), business, Neurocognitive
Abstract

INTRODUCTIONBlood metabolomics-based biomarkers may be useful to predict measures of neurocognitive aging.METHODSWe tested the association between 707 blood metabolites measured in 1,451 participants from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), with MCI and global cognitive change assessed seven years later. We further used Lasso penalized regression to construct a metabolomics risk score (MRS) that predicts MCI, potentially identifying a different set of metabolites than those discovered in individual-metabolite analysis.RESULTSWe identified 20 metabolites associated with MCI and/or global cognitive change. Six of them were novel and 14 were previously reported as associated with neurocognitive aging outcomes. The MCI MRS comprised 61 metabolites and improved prediction accuracy from 84% (minimally adjusted model) to 89% in the entire dataset and from 75% to 87% among APOE-ε4 carriers.DISCUSSIONBlood metabolites may serve as biomarkers identifying individuals at risk for MCI among U.S. Hispanics/Latinos.

Published
2021

39. Variant-specific inflation factors for assessing population stratification at the phenotypic variance level

Author

Jiang He, Ruth Loos, Stephanie Gogarten, C. Charles Gu, Alexi Runnels, Xiuwen Zheng, Pradeep Natarajan, Vipin Menon, James Pankow, Matthew Conomos, Karin Hoth, Joanne Curran, Marilyn Telen, Jennifer Body, Gregory Kinney, Tamar Sofer, Zeineen Momin, Frank Sciurba, Stephen Rich, Yi-Cheng Chang, Albert Vernon Smith, LEE-MING CHUANG, and Harshavardhan Doddapaneni

Subjects
0301 basic medicine, Statistical methods, Science, General Physics and Astronomy, Genome-wide association study, 030105 genetics & heredity, Biology, Population stratification, Genome-wide association studies, Article, General Biochemistry, Genetics and Molecular Biology, Statistical power, 03 medical and health sciences, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Gene Frequency, Genetics research, Statistics, False positive paradox, Genetics, Humans, Computer Simulation, Allele frequency, Genetic association, Multidisciplinary, Human Genome, Genetic Variation, General Chemistry, Variance (accounting), 030104 developmental biology, Phenotype, Good Health and Well Being, Sample size determination, Sample Size, Next-generation sequencing, Generic health relevance, Algorithms, Genome-Wide Association Study
Abstract

In modern Whole Genome Sequencing (WGS) epidemiological studies, participant-level data from multiple studies are often pooled and results are obtained from a single analysis. We consider the impact of differential phenotype variances by study, which we term ‘variance stratification’. Unaccounted for, variance stratification can lead to both decreased statistical power, and increased false positives rates, depending on how allele frequencies, sample sizes, and phenotypic variances vary across the studies that are pooled. We develop a procedure to compute variant-specific inflation factors, and show how it can be used for diagnosis of genetic association analyses on pooled individual level data from multiple studies. We describe a WGS-appropriate analysis approach, implemented in freely-available software, which allows study-specific variances and thereby improves performance in practice. We illustrate the variance stratification problem, its solutions, and the proposed diagnostic procedure, in simulations and in data from the Trans-Omics for Precision Medicine Whole Genome Sequencing Program (TOPMed), used in association tests for hemoglobin concentrations and BMI., Pooling participant-level genetic data into a single analysis can result in variance stratification, reducing statistical performance. Here, the authors develop variant-specific inflation factors to assess variance stratification and apply this to pooled individual-level data from whole genome sequencing.

Published
2021

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

Author

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

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

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

Published
2019

41. Sequencing Analysis at 8p23 Identifies Multiple Rare Variants in DLC1 Associated with Sleep-Related Oxyhemoglobin Saturation Level

Author

Daniel S. Evans, Edwin K. Silverman, Stephanie Williams, Han Chen, R. Graham Barr, Ruitong Li, Karen Y. He, Daniel J. Gottlieb, Brian E. Cade, Tamar Sofer, Yongmei Liu, Shaun Purcell, Heather M. Ochs-Balcom, Jessica A Rhodes, Ani Manichaikul, Lauren Hale, Gregory J. Tranah, Sutapa Mukherjee, Xihong Lin, Eric Boerwinkle, Richa Saxena, Katie L. Stone, James G. Wilson, Ramachandran S. Vasan, Jiwon Lee, Jingjing Liang, Weihong Tang, Lyle J. Palmer, Sanjay R. Patel, Jerome I. Rotter, Michael H. Cho, Xiuqing Guo, Stephen S. Rich, Bruce M. Psaty, Pamela L. Lutsey, Heming Wang, David R. Hillman, Susan Redline, Sina A. Gharib, and Xiaofeng Zhu

Subjects
0301 basic medicine, Genetic Linkage, Disease, Biology, 03 medical and health sciences, 0302 clinical medicine, Genetic linkage, Report, Gene expression, Genetics, Humans, Gene, Genetics (clinical), Framingham Risk Score, Whole Genome Sequencing, Tumor Suppressor Proteins, GTPase-Activating Proteins, Chromosome, Mendelian Randomization Analysis, Methylation, 030104 developmental biology, 030228 respiratory system, Oxyhemoglobins, Sleep, Chromosomes, Human, Pair 8, Genome-Wide Association Study
Abstract

Average arterial oxyhemoglobin saturation during sleep (AvSpO(2)S) is a clinically relevant measure of physiological stress associated with sleep-disordered breathing, and this measure predicts incident cardiovascular disease and mortality. Using high-depth whole-genome sequencing data from the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) project and focusing on genes with linkage evidence on chromosome 8p23,1, 2 we observed that six coding and 51 noncoding variants in a gene that encodes the GTPase-activating protein (DLC1) are significantly associated with AvSpO(2)S and replicated in independent subjects. The combined DLC1 association evidence of discovery and replication cohorts reaches genome-wide significance in European Americans (p = 7.9 × 10(−7)). A risk score for these variants, built on an independent dataset, explains 0.97% of the AvSpO(2)S variation and contributes to the linkage evidence. The 51 noncoding variants are enriched in regulatory features in a human lung fibroblast cell line and contribute to DLC1 expression variation. Mendelian randomization analysis using these variants indicates a significant causal effect of DLC1 expression in fibroblasts on AvSpO(2)S. Multiple sources of information, including genetic variants, gene expression, and methylation, consistently suggest that DLC1 is a gene associated with AvSpO(2)S.

Published
2019

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

Author

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

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

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

Published
2019

43. Associations between SLC16A11 variants and diabetes in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

Author

Adam A. Szpiro, Jerome I. Rotter, Kari E. North, Bertha Hidalgo, M. Larissa Avilés-Santa, George J. Papanicolaou, Qibin Qi, Neil Schneiderman, Adrienne M. Stilp, Donna K. Arnett, Jianwen Cai, Bing Yu, Cathy C. Laurie, Robert C. Kaplan, Eric Boerwinkle, Tamar Sofer, and Y.-D. Ida Chen

Subjects
0301 basic medicine, Monocarboxylic Acid Transporters, Ethnic group, lcsh:Medicine, Genome-wide association study, Type 2 diabetes, Biology, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, 0302 clinical medicine, Clinical Research, Genotype, Diabetes Mellitus, Genetics, medicine, 2.1 Biological and endogenous factors, SNP, Humans, Genetic Predisposition to Disease, Polymorphism, Aetiology, Allele, lcsh:Science, Metabolic and endocrine, Genetic Association Studies, Nutrition, Multidisciplinary, Genetic heterogeneity, Prevention, Diabetes, Haplotype, lcsh:R, Single Nucleotide, Hispanic or Latino, medicine.disease, United States, 3. Good health, 030104 developmental biology, Diabetes Mellitus, Type 2, Haplotypes, lcsh:Q, Type 2, 030217 neurology & neurosurgery, Demography
Abstract

Five sequence variants in SLC16A11 (rs117767867, rs13342692, rs13342232, rs75418188, and rs75493593), which occur in two non-reference haplotypes, were recently shown to be associated with diabetes in Mexicans from the SIGMA consortium. We aimed to determine whether these previous findings would replicate in the HCHS/SOL Mexican origin group and whether genotypic effects were similar in other HCHS/SOL groups. We analyzed these five variants in 2492 diabetes cases and 5236 controls from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), which includes U.S. participants from six diverse background groups (Mainland groups: Mexican, Central American, and South American; and Caribbean groups: Puerto Rican, Cuban, and Dominican). We estimated the SNP-diabetes association in the six groups and in the combined sample. We found that the risk alleles occur in two non-reference haplotypes in HCHS/SOL, as in the SIGMA Mexicans. The haplotype frequencies were very similar between SIGMA Mexicans and the HCHS/SOL Mainland groups, but different in the Caribbean groups. The SLC16A11 sequence variants were significantly associated with risk for diabetes in the Mexican origin group (P = 0.025), replicating the SIGMA findings. However, these variants were not significantly associated with diabetes in a combined analysis of all groups, although the power to detect such effects was 85% (assuming homogeneity of effects among the groups). Additional analyses performed separately in each of the five non-Mexican origin groups were not significant. We also analyzed (1) exclusion of young controls and, (2) SNP by BMI interactions, but neither was significant in the HCHS/SOL data. The previously reported effects of SLC16A11 variants on diabetes in Mexican samples was replicated in a large Mexican-American sample, but these effects were not significant in five non-Mexican Hispanic/Latino groups sampled from U.S. populations. Lack of replication in the HCHS/SOL non-Mexicans, and in the entire HCHS/SOL sample combined may represent underlying genetic heterogeneity. These results indicate a need for future genetic research to consider heterogeneity of the Hispanic/Latino population in the assessment of disease risk, but add to the evidence suggesting SLC16A11 as a potential therapeutic target for type 2 diabetes.

Published
2019

44. Benchmarking association analyses of continuous exposures with RNA-seq in observational studies

Author

Jerome I. Rotter, Deborah A. Nickerson, Susan Redline, Joshua D. Smith, Yongmei Liu, Sina A. Gharib, Peter Durda, Stephen S. Rich, Kristin Ardlie, François Aguet, Kent D. Taylor, Nuzulul Kurniansyah, and Tamar Sofer

Subjects
Computer science, Pipeline (computing), Web Browser, computer.software_genre, 0302 clinical medicine, Risk Factors, Resampling, Null distribution, RNA-Seq, Other Information and Computing Sciences, Lung, 0303 health sciences, Confounding, High-Throughput Nucleotide Sequencing, Contrast (statistics), Benchmarking, Phenotype, Problem Solving Protocol, Disease Susceptibility, Data mining, empirical P-values, Sequence Analysis, Algorithms, Information Systems, Bioinformatics, Correlation and dependence, Risk Assessment, 03 medical and health sciences, Linear regression, Genetics, Humans, Genetic Predisposition to Disease, Computer Simulation, continuous exposure, observational studies, Molecular Biology, 030304 developmental biology, Sequence Analysis, RNA, non-normality, Prevention, Human Genome, Computation Theory and Mathematics, Atherosclerosis, Mutation, Multiple comparisons problem, RNA, Observational study, Biochemistry and Cell Biology, computer, Software, 030217 neurology & neurosurgery, Quantile
Abstract

Large datasets of hundreds to thousands of individuals measuring RNA-seq in observational studies are becoming available. Many popular software packages for analysis of RNA-seq data were constructed to study differences in expression signatures in an experimental design with well-defined conditions (exposures). In contrast, observational studies may have varying levels of confounding transcript-exposure associations; further, exposure measures may vary from discrete (exposed, yes/no) to continuous (levels of exposure), with non-normal distributions of exposure. We compare popular software for gene expression—DESeq2, edgeR and limma—as well as linear regression-based analyses for studying the association of continuous exposures with RNA-seq. We developed a computation pipeline that includes transformation, filtering and generation of empirical null distribution of association P-values, and we apply the pipeline to compute empirical P-values with multiple testing correction. We employ a resampling approach that allows for assessment of false positive detection across methods, power comparison and the computation of quantile empirical P-values. The results suggest that linear regression methods are substantially faster with better control of false detections than other methods, even with the resampling method to compute empirical P-values. We provide the proposed pipeline with fast algorithms in an R package Olivia, and implemented it to study the associations of measures of sleep disordered breathing with RNA-seq in peripheral blood mononuclear cells in participants from the Multi-Ethnic Study of Atherosclerosis.

Published
2021

45. The trans-ancestral genomic architecture of glycemic traits

Author

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

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

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

Published
2021

46. Cutting the fat: advances and challenges in sleep apnoea genetics

Author

Tamar Sofer, Matthew Goodman, Heming Wang, and Susan Redline

Subjects
Pulmonary and Respiratory Medicine, Genetics, Sleep Apnea, Obstructive, business.industry, MEDLINE, Disease, medicine.disease, Biobank, Sleep in non-human animals, Obesity, 03 medical and health sciences, 0302 clinical medicine, Sleep Apnea Syndromes, 030228 respiratory system, Medicine, Humans, 030212 general & internal medicine, business
Abstract

Comments on a FinnGen sleep apnoea genetics study: need to disambiguate causal and pleiotropic associations with obesity/cardiometabolic diseases and opportunities for biobanks (and deeper phenotyping) to discover new treatments and disease subtypeshttps://bit.ly/3dntk0I

Published
2020

47. Multi-ancestry genome-wide gene-sleep interactions identify novel loci for blood pressure

Author

Lisa W. Martin, Tuomas O. Kilpeläinen, Xiuqing Guo, Kurt Lohman, Ching-Ti Liu, Jerome I. Rotter, Pirjo Komulainen, Lili Milani, Ilja M. Nolte, Yuri Milaneschi, Andres Metspalu, Yii-Der Ida Chen, Tõnu Esko, Jovia L. Nierenberg, Mika Kähönen, Marjan Ilkov, Dennis O. Mook-Kanamori, Karen Schwander, W. James Gauderman, Hanfei Xu, Vilmundur Gudnason, Alisa K. Manning, Gudny Eiriksdottir, David R. Hillman, Elise Lim, Hugues Aschard, John M. Starr, Michael R. Brown, Alanna C. Morrison, Eric Boerwinkle, Stefan Weiss, Maris Alver, Konstantin Strauch, Thomas Meitinger, Tuomo Rankinen, Timo A. Lakka, Harold Snieder, Stephen S. Rich, Yun Ju Sung, Diana van Heemst, Wanqing Wen, Marcus Dörr, Peter J. van der Most, Terho Lehtimäki, Nora Franceschini, Treva Rice, Amy R. Bentley, Dan E. Arking, Susan Redline, Nienke R. Biermasz, Sarah E. Harris, Melanie Waldenberger, Claude Bouchard, M. Arfan Ikram, Walter Palmas, Lynne E. Wagenknecht, Bruce M. Psaty, Daniel Levy, Cornelia M. van Duijn, Joshua C. Bis, Kelly A. Hall, José Eduardo Krieger, Tanika N. Kelly, Kari E. North, Brigitte Kühnel, Phyllis C. Zee, Melissa A. Richard, Lyle J. Palmer, Till Roenneberg, Alexandre C. Pereira, Yongmei Liu, Andrea R. V. R. Horimoto, Jie Yao, Han Chen, Jiang He, Pamela J. Schreiner, Patricia B. Munroe, Wei Zheng, Charles Kooperberg, Paul S. de Vries, Ana Barac, Rainer Rauramaa, Leo-Pekka Lyytikäinen, James M. Shikany, Brian E. Cade, Christian Gieger, Stephen Sidney, Alan B. Zonderman, Tamar Sofer, Chuan Gao, Thomas W. Winkler, Xiao-Ou Shu, Ian J. Deary, Uwe Völker, RJ Waken, Heming Wang, Myriam Fornage, Brenda W.J.H. Penninx, Gregory P. Wilson, Dina Vojinovic, Robert B. Wallace, Kenneth Rice, Ervin R. Fox, Jeffrey R. O'Connell, Annemarie I. Luik, Traci M. Bartz, Xiaofeng Zhu, Najaf Amin, Nicholette D. Palmer, Sami Heikkinen, Kumaraswamynaidu Chitrala, Raymond Noordam, Jiwon Lee, André G. Uitterlinden, Sutapa Mukherjee, Hans J. Grabe, Mario Sims, Sina A. Gharib, Daniel J. Gottlieb, Dabeeru C. Rao, Annette Peters, Reedik Mägi, Solomon K. Musani, Michele K. Evans, Lenore J. Launer, Harvard Medical School [Boston] (HMS), Broad Institute [Cambridge], Harvard University-Massachusetts Institute of Technology (MIT), Hallym University, Department of Educational Psychology and Counseling, National Taiwan Normal University (NTNU), Département de Biologie Computationnelle - Department of Computational Biology, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Leiden University Medical Center (LUMC), Universiteit Leiden, This project was supported by the US National Heart, Lung, and Blood Institute (NHLBI) R01HL118305. HW and SR were supported by NHLBI R35HL135818. BEC was supported by NHLBI K01HL135405. ARB was supported by the Intramural Research Program of the National Institutes of Health in the Center for Research on Genomics and Global Health (CRGGH). The CRGGH is supported by the National Human Genome Research Institute, the National Institute of Diabetes and Digestive and Kidney Diseases, the Center for Information Technology, and the Office of the Director at the National Institutes of Health (1ZIAHG200362). D.v.H. was supported by the European Commission funded project HUMAN (Health-2013-INNOVATION-1-602757). The CHARGE cohorts were supported in part by NHLBI infrastructure grant HL105756. Study-specific acknowledgments can be found in the Supplementary Notes., European Project: 602757,EC:FP7:HEALTH,FP7-HEALTH-2013-INNOVATION-1,HUMAN(2013), Life Course Epidemiology (LCE), Epidemiology, Radiology & Nuclear Medicine, Internal Medicine, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Mental Health, APH - Digital Health, Massachusetts Institute of Technology (MIT)-Harvard University [Cambridge], Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Tampere University, Department of Clinical Chemistry, Clinical Medicine, and Department of Clinical Physiology and Nuclear Medicine

Subjects
0301 basic medicine, Mean arterial pressure, Diastole, Blood Pressure, Biology, 3121 Internal medicine, Genome, Polymorphism, Single Nucleotide, Elevated blood, 3124 Neurology and psychiatry, Article, Cellular and Molecular Neuroscience, 03 medical and health sciences, TRPC3, 0302 clinical medicine, SDG 3 - Good Health and Well-being, Humans, Molecular Biology, Gene, 030304 developmental biology, Genetics, 0303 health sciences, [STAT.AP]Statistics [stat]/Applications [stat.AP], Short sleep, Sleep in non-human animals, Pulse pressure, Psychiatry and Mental health, 030104 developmental biology, Blood pressure, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, Genetic Loci, Hypertension, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, 3111 Biomedicine, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Sleep, [STAT.ME]Statistics [stat]/Methodology [stat.ME], 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Long and short sleep duration are associated with elevated blood pressure (BP), possibly through effects on molecular pathways that influence neuroendocrine and vascular systems. To gain new insights into the genetic basis of sleep-related BP variation, we performed genome-wide gene by short or long sleep duration interaction analyses on four BP traits (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure) across five ancestry groups using 1 degree of freedom (1df) interaction and 2df joint tests. Primary multi-ancestry analyses in 62,969 individuals in stage 1 identified 3 novel loci that were replicated in an additional 59,296 individuals in stage 2, including rs7955964 (FIGNL2/ANKRD33) showing significant 1df interactions with long sleep duration and rs73493041 (SNORA26/C9orf170) and rs10406644 (KCTD15/LSM14A) showing significant 1df interactions with short sleep duration (Pint < 5×10−8). Secondary ancestry-specific two-stage analyses and combined stage 1 and 2 analyses additionally identified 23 novel loci that need external replication, including 3 and 5 loci showing significant 1df interactions with long and short sleep duration, respectively (Pint < 5×10−8). Multiple genes mapped to our 26 novel loci have known functions in sleep-wake regulation, nervous and cardiometabolic systems. We also identified new gene by long sleep interactions near five known BP loci (≤1Mb) including NME7, FAM208A, MKLN1, CEP164, and RGL3/ELAVL3 (Pint < 5×10−8). This study indicates that sleep and primary mechanisms regulating BP may interact to elevate BP level, suggesting novel insights into sleep-related BP regulation.

Published
2020

48. Low oxygen saturation during sleep reduces CD1D and RAB20 expressions that are reversed by CPAP therapy

Author

Stephen S. Rich, Ruitong Li, Reena Mehra, Daniel Levy, Adam C. Gower, Jerome I. Rotter, Nuzulul Kurniansyah, Sina A. Gharib, Daniel J. Gottlieb, Susan Redline, Roby Joehanes, Stephanie Williams, Jiwon Lee, Stuart F. Quan, Avrum Spira, Sanjay R. Patel, Yongmei Liu, Brian E. Cade, Tamar Sofer, Heming Wang, and Honghuang Lin

Subjects
0301 basic medicine, Male, Aging, Research paper, medicine.medical_treatment, lcsh:Medicine, Cardiovascular, Hypoxemia, 0302 clinical medicine, Medicine, 2.1 Biological and endogenous factors, Continuous positive airway pressure, Longitudinal Studies, Prospective Studies, Aetiology, Lung, lcsh:R5-920, Continuous Positive Airway Pressure, Apnea, General Medicine, Middle Aged, Sleep in non-human animals, 030220 oncology & carcinogenesis, Cardiology, Public Health and Health Services, Female, medicine.symptom, lcsh:Medicine (General), Sleep Research, medicine.medical_specialty, Obstructive Sleep Apnea, Heartbeat, Offspring, Clinical Sciences, Down-Regulation, CD1d, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, Sleep Apnea Syndromes, Clinical Research, Internal medicine, Genetics, Humans, cardiovascular diseases, Antigens, Aged, business.industry, Gene Expression Profiling, lcsh:R, medicine.disease, nervous system diseases, respiratory tract diseases, Obstructive sleep apnea, 030104 developmental biology, Apnea–hypopnea index, rab GTP-Binding Proteins, Oxyhemoglobins, Gene expression, Antigens, CD1d, business
Abstract

Background Sleep Disordered Breathing (SDB) is associated with a wide range of pathophysiological changes due, in part, to hypoxemia during sleep. We sought to identify gene transcription associations with measures of SDB and hypoxemia during sleep, and study their response to treatment. Methods In two discovery cohorts, Framingham Offspring Study (FOS; N = 571) and the Multi-Ethnic Study of Atherosclerosis (MESA; N = 580), we studied gene expression in peripheral blood mononuclear cells in association with three measures of SDB: Apnea Hypopnea Index (AHI); average oxyhemoglobin saturation (avgO2) during sleep; and minimum oxyhemoglobin saturation (minO2) during sleep. Associated genes were used for analysis of gene expression in the blood of 15 participants with moderate or severe obstructive sleep apnea (OSA) from the Heart Biomarkers In Apnea Treatment (HeartBEAT) trial. These genes were studied pre- and post-treatment (three months) with continuous positive airway pressure (CPAP). We also performed Gene Set Enrichment Analysis (GSEA) on all traits and cohort analyses. Findings Twenty-two genes were associated with SDB traits in both MESA and FOS. Of these, lower expression of CD1D and RAB20 was associated with lower avgO2 in MESA and FOS. CPAP treatment increased the expression of these genes in HeartBEAT participants. Immunity and inflammation pathways were up-regulated in subjects with lower avgO2; i.e., in those with a more severe SDB phenotype (MESA), whereas immuno-inflammatory processes were down-regulated following CPAP treatment (HeartBEAT). Interpretation Low oxygen saturation during sleep is associated with alterations in gene expression and transcriptional programs that are partially reversed by CPAP treatment.

Published
2020

49. Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci

Author

Yongmei Liu, Tuomas O. Kilpeläinen, Kenneth Rice, Ching-Ti Liu, Jin-Fang Chai, Donna K. Arnett, Dhananjay Vaidya, Nicholette D. Palmer, Lili Milani, Yuri Milaneschi, Leo-Pekka Lyytikäinen, Colleen M. Sitlani, Richard S. Cooper, Gudny Eiriksdottir, Daniel Levy, Jerome I. Rotter, Lihua Wang, Sven Bergmann, Yih Chung Tham, Thomas Meitinger, Lynne E. Wagenknecht, Virginia Fisher, Babatunde L. Salako, Vilmundur Gudnason, Bamidele O. Tayo, Caizheng Yu, Barry I. Freedman, Muhammad Riaz, Kaare Christensen, Ulrich Broeckel, W. James Gauderman, Massimiliano Cocca, Eric Boerwinkle, Meian He, Rob M. van Dam, M. Arfan Ikram, Lisa de las Fuentes, Jiang He, Aldi T. Kraja, Nancy L. Pedersen, Albert V. Smith, Woon-Puay Koh, Bernardo L. Horta, He Gao, Traci M. Bartz, Mike A. Nalls, Federica Laguzzi, Raymond Noordam, Paul M. Ridker, Tien Yin Wong, Patricia B. Munroe, Paul S. de Vries, Adolfo Correa, Maris Alver, Dan E. Arking, Colin A. McKenzie, John M. Starr, Chi Charles Gu, Dongfeng Gu, Stefan Weiss, Patricia A. Peyser, Jessica D. Faul, Xu Chen, Jill M. Norris, Patrik K. E. Magnusson, Tamar Sofer, Ioanna Ntalla, Xiuqing Guo, Paul Elliott, Lawrence F. Bielak, Konstantin Strauch, Xueling Sim, Norihiro Kato, Evangelos Evangelou, Ilja M. Nolte, Steven C. Hunt, Mario Sims, Giorgia Girotto, Chuan Gao, Pamela J. Schreiner, Philippe Froguel, Archie Campbell, Xiao-Ou Shu, Claude Bouchard, Kurt Lohman, David R. Weir, José Eduardo Krieger, Yii-Der Ida Chen, Rainer Rauramaa, Walter Palmas, Cornelia M. van Duijn, James M. Shikany, Michael M. Province, Jennifer A. Smith, Wei Zheng, Xiaofeng Zhu, Jianjun Liu, Ozren Polasek, Alexandre C. Pereira, Diane M. Becker, Kari E. North, Salman M. Tajuddin, Deng Xuan, Leslie J. Raffel, Jie Yao, Astrid Petersmann, Ervin F. Fox, Mark J. Caulfield, Daniel I. Chasman, Jasmin Divers, Claudia P. Cabrera, Rico Rueedi, M. Yldau van der Ende, Carl D. Langefeld, Mika Kähönen, Terrence Forrester, Tangchun Wu, Harold Snieder, Caroline Hayward, Tamara B. Harris, Fang-Chi Hsu, Helen R. Warren, Brenda W.J.H. Penninx, Chiea Chuen Khor, Ruifang Li-Gao, Changwei Li, Sami Heikkinen, Jeffrey R. O'Connell, Christian Gieger, Michele K. Evans, Ching-Yu Cheng, Jingjing Liang, Stephen B. Kritchevsky, Gregory L. Burke, Donald W. Bowden, Alexander Teumer, Marcus Dörr, Alanna C. Morrison, Jian-Min Yuan, Annette Peters, Dennis O. Mook-Kanamori, Pedro Marques-Vidal, Pirjo Komulainen, Lisa R. Yanek, Melanie Waldenberger, Alisa K. Manning, Charles N. Rotimi, Chew-Kiat Heng, Tõnu Esko, Franco Giulianini, Miao Li Chee, Treva Rice, David J. Porteous, Yechiel Friedlander, Bing Yu, Myriam Fornage, Karin Leander, Dina Vojinovic, Sharon L.R. Kardia, Xiaoyin Li, Najaf Amin, Karen Schwander, Thomas T. Perls, Oscar Leonel Rueda-Ochoa, Erin B. Ware, Ya Xing Wang, Sandosh Padmanabhan, H. Janaka de Silva, André G. Uitterlinden, Rajkumar Dorajoo, Bruna Gigante, Jennifer A. Brody, Paolo Gasparini, Maryam Kavousi, Wanqing Wen, Stephen Sidney, Alan B. Zonderman, Michael R. Brown, Tuomo Rankinen, Timo A. Lakka, Yun Ju Sung, Alaitz Poveda, Bruce M. Psaty, Terho Lehtimäki, Tanika N. Kelly, Igor Rudan, Brigitte Kühnel, Christopher P. Nelson, John M. C. Connell, Mickaël Canouil, Niek Verweij, Thomas W. Winkler, Ian J. Deary, Marco Brumat, Yize Li, Fumihiko Takeuchi, Wei Zhao, Andres Metspalu, Marguerite R. Irvin, David C. Liewald, Pim van der Harst, Hugues Aschard, Candace M. Kammerer, Melissa A. Richard, Adesola Ogunniyi, Wen Bin Wei, Morris A. Swertz, Fernando Pires Hartwig, Dabeeru C. Rao, Reedik Mägi, Solomon K. Musani, Mathilde Boissel, Jonathan Marten, Nilesh J. Samani, Amy R. Bentley, Sarah E. Harris, Charumathi Sabanayagam, Mary F. Feitosa, Jost B. Jonas, Andrea R. V. R. Horimoto, Paul W. Franks, E. Shyong Tai, Medical Research Council (MRC), de las Fuentes, L., Sung, Y. J., Noordam, R., Winkler, T., Feitosa, M. F., Schwander, K., Bentley, A. R., Brown, M. R., Guo, X., Manning, A., Chasman, D. I., Aschard, H., Bartz, T. M., Bielak, L. F., Campbell, A., Cheng, C. -Y., Dorajoo, R., Hartwig, F. P., Horimoto, A. R. V. R., Li, C., Li-Gao, R., Liu, Y., Marten, J., Musani, S. K., Ntalla, I., Rankinen, T., Richard, M., Sim, X., Smith, A. V., Tajuddin, S. M., Tayo, B. O., Vojinovic, D., Warren, H. R., Xuan, D., Alver, M., Boissel, M., Chai, J. -F., Chen, X., Christensen, K., Divers, J., Evangelou, E., Gao, C., Girotto, G., Harris, S. E., He, M., Hsu, F. -C., Kuhnel, B., Laguzzi, F., Li, X., Lyytikainen, L. -P., Nolte, I. M., Poveda, A., Rauramaa, R., Riaz, M., Rueedi, R., Shu, X. -O., Snieder, H., Sofer, T., Takeuchi, F., Verweij, N., Ware, E. B., Weiss, S., Yanek, L. R., Amin, N., Arking, D. E., Arnett, D. K., Bergmann, S., Boerwinkle, E., Brody, J. A., Broeckel, U., Brumat, M., Burke, G., Cabrera, C. P., Canouil, M., Chee, M. L., Chen, Y. -D. I., Cocca, M., Connell, J., de Silva, H. J., de Vries, P. S., Eiriksdottir, G., Faul, J. D., Fisher, V., Forrester, T., Fox, E. F., Friedlander, Y., Gao, H., Gigante, B., Giulianini, F., Gu, C. C., Gu, D., Harris, T. B., He, J., Heikkinen, S., Heng, C. -K., Hunt, S., Ikram, M. A., Irvin, M. R., Kahonen, M., Kavousi, M., Khor, C. C., Kilpelainen, T. O., Koh, W. -P., Komulainen, P., Kraja, A. T., Krieger, J. E., Langefeld, C. D., Li, Y., Liang, J., Liewald, D. C. M., Liu, C. -T., Liu, J., Lohman, K. K., Magi, R., Mckenzie, C. A., Meitinger, T., Metspalu, A., Milaneschi, Y., Milani, L., Mook-Kanamori, D. O., Nalls, M. A., Nelson, C. P., Norris, J. M., O'Connell, J., Ogunniyi, A., Padmanabhan, S., Palmer, N. D., Pedersen, N. L., Perls, T., Peters, A., Petersmann, A., Peyser, P. A., Polasek, O., Porteous, D. J., Raffel, L. J., Rice, T. K., Rotter, J. I., Rudan, I., Rueda-Ochoa, O. -L., Sabanayagam, C., Salako, B. L., Schreiner, P. J., Shikany, J. M., Sidney, S. S., Sims, M., Sitlani, C. M., Smith, J. A., Starr, J. M., Strauch, K., Swertz, M. A., Teumer, A., Tham, Y. C., Uitterlinden, A. G., Vaidya, D., van der Ende, M. Y., Waldenberger, M., Wang, L., Wang, Y. -X., Wei, W. -B., Weir, D. R., Wen, W., Yao, J., Yu, B., Yu, C., Yuan, J. -M., Zhao, W., Zonderman, A. B., Becker, D. M., Bowden, D. W., Deary, I. J., Dorr, M., Esko, T., Freedman, B. I., Froguel, P., Gasparini, P., Gieger, C., Jonas, J. B., Kammerer, C. M., Kato, N., Lakka, T. A., Leander, K., Lehtimaki, T., Magnusson, P. K. E., Marques-Vidal, P., Penninx, B. W. J. H., Samani, N. J., van der Harst, P., Wagenknecht, L. E., Wu, T., Zheng, W., Zhu, X., Bouchard, C., Cooper, R. S., Correa, A., Evans, M. K., Gudnason, V., Hayward, C., Horta, B. L., Kelly, T. N., Kritchevsky, S. B., Levy, D., Palmas, W. R., Pereira, A. C., Province, M. M., Psaty, B. M., Ridker, P. M., Rotimi, C. N., Tai, E. S., van Dam, R. M., van Duijn, C. M., Wong, T. Y., Rice, K., Gauderman, W. J., Morrison, A. C., North, K. E., Kardia, S. L. R., Caulfield, M. J., Elliott, P., Munroe, P. B., Franks, P. W., Rao, D. C., Fornage, M., Washington University in Saint Louis (WUSTL), Leiden University Medical Center (LUMC), University of Regensburg, Washington University School of Medicine in St. Louis, National Institutes of Health [Bethesda] (NIH), Harbor UCLA Medical Center [Torrance, Ca.], Massachusetts General Hospital [Boston], Département de Biologie Computationnelle - Department of Computational Biology, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Harvard School of Public Health, Metabolic functional (epi)genomics and molecular mechanisms involved in type 2 diabetes and related diseases - UMR 8199 - UMR 1283 (GI3M), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), The University of Texas Health Science Center at Houston (UTHealth), Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Mental Health, APH - Digital Health, Universiteit Leiden, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Metabolic functional (epi)genomics and molecular mechanisms involved in type 2 diabetes and related diseases - UMR 8199 - UMR 1283 (EGENODIA (GI3M)), Lifelines Cohort Study, Epidemiology, Radiology & Nuclear Medicine, Internal Medicine, Life Course Epidemiology (LCE), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), and Cardiovascular Centre (CVC)

Subjects
0301 basic medicine, CORONARY-HEART-DISEASE, SOCIOECONOMIC-STATUS, RISK-FACTORS, CARDIOVASCULAR-DISEASE, ESSENTIAL-HYPERTENSION, C825T POLYMORPHISM, SOCIAL-CLASS, ASSOCIATION, EXPRESSION, VARIANTS, Blood Pressure, Genome, 0302 clinical medicine, 11 Medical and Health Sciences, Genetics, Psychiatry, [STAT.AP]Statistics [stat]/Applications [stat.AP], 17 Psychology and Cognitive Sciences, Psychiatry and Mental health, Meta-analysis, Hypertension, [STAT.ME]Statistics [stat]/Methodology [stat.ME], Life Sciences & Biomedicine, GNB3, Biochemistry & Molecular Biology, Biology, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, Cellular and Molecular Neuroscience, Lifelines Cohort Study, SDG 3 - Good Health and Well-being, Humans, Risk factor, Molecular Biology, Gene, Science & Technology, Neurosciences, Epistasis, Genetic, 06 Biological Sciences, Genetic architecture, Educational attainment, 030104 developmental biology, Blood pressure, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, Genetic Loci, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Neurosciences & Neurology, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Blood Pressure/genetics, Genome-Wide Association Study, Hypertension/genetics, 030217 neurology & neurosurgery
Abstract

Educational attainment is widely used as a surrogate for socioeconomic status (SES). Low SES is a risk factor for hypertension and high blood pressure (BP). To identify novel BP loci, we performed multi-ancestry meta-analyses accounting for gene-educational attainment interactions using two variables, "Some College" (yes/no) and "Graduated College" (yes/no). Interactions were evaluated using both a 1 degree of freedom (DF) interaction term and a 2DF joint test of genetic and interaction effects. Analyses were performed for systolic BP, diastolic BP, mean arterial pressure, and pulse pressure. We pursued genome-wide interrogation in Stage 1 studies (N = 117 438) and follow-up on promising variants in Stage 2 studies (N = 293 787) in five ancestry groups. Through combined meta-analyses of Stages 1 and 2, we identified 84 known and 18 novel BP loci at genome-wide significance level (P < 5 × 10 -8 ). Two novel loci were identified based on the 1DF test of interaction with educational attainment, while the remaining 16 loci were identified through the 2DF joint test of genetic and interaction effects. Ten novel loci were identified in individuals of African ancestry. Several novel loci show strong biological plausibility since they involve physiologic systems implicated in BP regulation. They include genes involved in the central nervous system-adrenal signaling axis (ZDHHC17, CADPS, PIK3C2G), vascular structure and function (GNB3, CDON), and renal function (HAS2 and HAS2-AS1, SLIT3). Collectively, these findings suggest a role of educational attainment or SES in further dissection of the genetic architecture of BP.

Published
2020

50. Whole genome sequence analysis of pulmonary function and COPD in 19,996 multi-ethnic participants

Author

Namrata Gupta, Peter Durda, Elizabeth C. Oelsner, Martha L. Daviglus, Martin D. Tobin, James G. Wilson, Liana K. Preudhomme, Laura R. Loehr, Ingo Ruczinski, Pallavi Balte, Ramachandran S. Vasan, R. Graham Barr, Phuwanat Sakornsakolpat, Stephanie J. London, Robert M. Reed, Elaine Cornell, Josée Dupuis, Dandi Qiao, Dmitry Prokopenko, Russell P. Tracy, Alanna C. Morrison, Robert C. Kaplan, Cathy C. Laurie, Sina A. Gharib, Donna M. Muzny, Kent D. Taylor, Cecelia A. Laurie, Wonji Kim, Stephen S. Rich, Brian E. Cade, Kristin M. Burkart, Tamar Sofer, George T. O'Connor, Chiara Batini, Louise V. Wain, Leslie A. Lange, Ani Manichaikul, Susan Redline, Yanlin Ma, Bruce M. Psaty, Xutong Zhao, Yongmei Liu, Chaojie Yang, Edwin K. Silverman, David J. Vandenberg, Deborah A. Nickerson, George J. Papanicolaou, Bing Yu, L. Adrienne Cupples, Kathleen C. Barnes, François Aguet, Silva Kasela, Stacey Gabriel, Kristin G. Ardlie, Xiuqing Guo, Gonçalo R. Abecasis, Shannon Dugan-Perez, Harshavardhan Doddapaneni, Jerome I. Rotter, Ginger A. Metcalf, W. Craig Johnson, Michelle Daya, Nick Shrine, Sarah A Gagliano Taliun, Traci M. Bartz, Jiwon Lee, Deepti Jain, Tuuli Lappalainen, and Michael H. Cho

Subjects
0301 basic medicine, Male, TOPMed Lung Working Group, General Physics and Astronomy, Genome-wide association study, Genome-wide association studies, Pulmonary function testing, Pulmonary Disease, Chronic Obstructive, 0302 clinical medicine, Polymorphism (computer science), 80 and over, 2.1 Biological and endogenous factors, DNA sequencing, Aetiology, lcsh:Science, Lung, Genetics, African Americans, Aged, 80 and over, COPD, education.field_of_study, Multidisciplinary, Chronic obstructive pulmonary disease, Intracellular Signaling Peptides and Proteins, Single Nucleotide, Middle Aged, Biobank, Protein Inhibitors of Activated STAT, 030220 oncology & carcinogenesis, Respiratory, Respiratory Physiological Phenomena, Small Ubiquitin-Related Modifier Proteins, Female, Biotechnology, Adult, Chronic Obstructive, Chronic Obstructive Pulmonary Disease, Science, Population, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, and over, Biology, Polymorphism, Single Nucleotide, General Biochemistry, Genetics and Molecular Biology, Article, Pulmonary Disease, 03 medical and health sciences, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, medicine, Humans, Genetic Predisposition to Disease, Polymorphism, education, Aged, Whole genome sequencing, Whole Genome Sequencing, Human Genome, Calcium-Binding Proteins, General Chemistry, Precision medicine, medicine.disease, respiratory tract diseases, Black or African American, 030104 developmental biology, Good Health and Well Being, Genetic Loci, Feasibility Studies, lcsh:Q, 2.4 Surveillance and distribution, Follow-Up Studies, Genome-Wide Association Study
Abstract

Chronic obstructive pulmonary disease (COPD), diagnosed by reduced lung function, is a leading cause of morbidity and mortality. We performed whole genome sequence (WGS) analysis of lung function and COPD in a multi-ethnic sample of 11,497 participants from population- and family-based studies, and 8499 individuals from COPD-enriched studies in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program. We identify at genome-wide significance 10 known GWAS loci and 22 distinct, previously unreported loci, including two common variant signals from stratified analysis of African Americans. Four novel common variants within the regions of PIAS1, RGN (two variants) and FTO show evidence of replication in the UK Biobank (European ancestry n ~ 320,000), while colocalization analyses leveraging multi-omic data from GTEx and TOPMed identify potential molecular mechanisms underlying four of the 22 novel loci. Our study demonstrates the value of performing WGS analyses and multi-omic follow-up in cohorts of diverse ancestry., Chronic obstructive pulmonary disease is a leading cause of morbidity and mortality. Here, the authors analyse whole genome sequence data and find new loci associated with lung function and COPD.

Published
2020

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