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

Lisa de Las Fuentes, Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St. Louis, MO, United States.
Karen L. Schwander, Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States.
Michael R. Brown, Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States.
Amy R. Bentley, Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, United States.
Thomas W. Winkler, Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.
Yun Ju Sung, Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States.
Patricia B. Munroe, Clinical Pharmacology, Queen Mary University of London, London, United Kingdom.
Clint L. Miller, Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, United States.
Hugo Aschard, Department of Epidemiology, Harvard School of Public Health, Boston, MA, United States.
Stella Aslibekyan, School of Public Health, Epidemiology, University of Alabama at Birmingham, Birmingham, AL, United States.
Traci M. Bartz, Cardiovascular Health Research Unit, University of Washington, Seattle, WA, United States.
Lawrence F. Bielak, Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States.
Jin Fang Chai, Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.
Ching-Yu Cheng, Ocular Epidemiology, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore.
Rajkumar Dorajoo, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore.
Mary F. Feitosa, Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States.
Xiuqing Guo, Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Los Angeles, CA, United States.
Fernando P. Hartwig, Postgraduate Programme in Epidemiology, Faculty of Medicine, Federal University of Pelotas, Pelotas, RS, Brazil.
Andrea Horimoto, Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of Sao Paulo Medical School, Sao Paulo, SP, Brazil.
Ivana Kolčić, University of Split School of Medicine, Split, Croatia.
Elise Lim, Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States.
Yongmei Liu, Division of Cardiology, Department of Medicine, Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC, United States.
Alisa K. Manning, Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, United States.
Jonathan Marten, Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom.
Solomon K. Musani, Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, United States.
Raymond Noordam, Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, Netherlands.
Sandosh Padmanabhan, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom.
Tuomo Rankinen, Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, United States.
Melissa A. Richard, Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, United States.
Paul M. Ridker, Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, United States.
Albert V. Smith, Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States.
Dina Vojinovic, Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, Netherlands.

Document Type

Journal Article

Publication Date

1-1-2023

Journal

Frontiers in genetics

Volume

14

DOI

10.3389/fgene.2023.1235337

Keywords

cholesterol; educational attainment; genome-wide association study; lipids; meta-analysis; triglycerides

Abstract

Educational attainment, widely used in epidemiologic studies as a surrogate for socioeconomic status, is a predictor of cardiovascular health outcomes. 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 ( < 5 × 10) and suggestive ( < 1 × 10) 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). 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 (), brain (), and liver () 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. Genome-wide interaction analysis of educational attainment identified novel lipid loci not previously detected by analyses limited to main genetic effects.

Department

Exercise and Nutrition Sciences

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