Genetic analysis in European ancestry individuals identifies 517 loci associated with liver enzymes
LifeLines Cohort Study; the VA Million Veteran Program
(2021) Nature Communications, volume 12, issue 1, pp. 1 - 12
(Article)
Abstract
Serum concentration of hepatic enzymes are linked to liver dysfunction, metabolic and cardiovascular diseases. We perform genetic analysis on serum levels of alanine transaminase (ALT), alkaline phosphatase (ALP) and gamma-glutamyl transferase (GGT) using data on 437,438 UK Biobank participants. Replication in 315,572 individuals from European descent from the Million Veteran
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Program, Rotterdam Study and Lifeline study confirms 517 liver enzyme SNPs. Genetic risk score analysis using the identified SNPs is strongly associated with serum activity of liver enzymes in two independent European descent studies (The Airwave Health Monitoring study and the Northern Finland Birth Cohort 1966). Gene-set enrichment analysis using the identified SNPs highlights involvement in liver development and function, lipid metabolism, insulin resistance, and vascular formation. Mendelian randomization analysis shows association of liver enzyme variants with coronary heart disease and ischemic stroke. Genetic risk score for elevated serum activity of liver enzymes is associated with higher fat percentage of body, trunk, and liver and body mass index. Our study highlights the role of molecular pathways regulated by the liver in metabolic disorders and cardiovascular disease.
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Keywords: Aged, Alanine Transaminase/blood, Alkaline Phosphatase/blood, Cardiovascular Diseases/enzymology, Cohort Studies, Databases, Genetic, Female, Gene Expression Regulation, Enzymologic/genetics, Genetic Predisposition to Disease, Genetic Testing, Genome-Wide Association Study, Humans, Insulin Resistance/genetics, Lipid Metabolism/genetics, Liver/enzymology, Male, Mendelian Randomization Analysis, Metabolic Diseases/enzymology, Middle Aged, Polymorphism, Single Nucleotide, Risk Factors, Whites, gamma-Glutamyltransferase/blood, Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't, Research Support, U.S. Gov't, Non-P.H.S.
ISSN: 2041-1723
Publisher: Nature Publishing Group
Note: Funding Information: This research has been conducted using the UKB Resource under application number 236 granting access to the corresponding UKB genetic and phenotype data (released 17 Nov. 2016). See Supplementary information for details of cohorts, GWAS resources, and funding. This research has been conducted using the UKB Resource under applications number 10035 and 236 granting access to the corresponding UKB genetic and phenotype data (released 17 Nov. 2016). UK Biobank genotyping was supported by the British Heart Foundation (grant SP/13/2/30111) for Large-scale comprehensive genotyping of UKB for cardiometabolic traits and diseases: UK CardioMetabolic Consortium. P.E. is Director of the Medical Research Council Centre for Environment and Health and acknowledges support from the Medical Research Council and Public Health England (MR/L01341X/1 and MR/S019669/1). P.E. also acknowledges support from the National Institute of Health Research Imperial Biomedical Research Centre. P.E. is a UK Dementia Research Institute professor, UK Dementia Research Institute at Imperial College London. The DRI receives funding from UK Dementia Research Institute Ltd funded by the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK. P.E. is associate director of Health Data Research UK-London funded by a consortium led by the UK Medical Research Council. This work used the computing resources of the UK MEDical BIOinformatics partnership (UK MED-BIO), which is supported by the Medical Research Council (MR/L01632X/1). R.P. holds a fellowship supported by Rutherford Fund from Medical Research Council (MR/R0265051/1). The main replication sample was based on data from the Million Veteran Program (MVP), Office of Research and Development, Veterans Health Administration. The outlined work performed in MVP was supported by funding from the Department of Veterans Affairs Office of Research and Development, Million Veteran Program via #MVP000 and I01-BX003362 (P.S.T. and K.M.-C.) with additional support from the NIH/NIDDK (DK101478, B.F.V.; 1K23DK115897-01, M.S.), the NIH/NHGRI (HG010067, B.F.V.), NIH/NIAAA (RO1 AA026302, R.M.C.), Linda Pechenik Montague Investigator award (B.F.V.), and VA Informatics and Computing Infrastructure (VINCI) VA HSR RES 130457. The content of this manuscript does not represent the views of the Department of Veterans Affairs or the United States Government. The LifeLines Cohort Study, and generation and management of GWAS genotype data for the LifeLines Cohort Study is supported by the Netherlands Organization of Scientific Research NWO (grant 175.010.2007.006), the Economic Structure Enhancing Fund (FES) of the Dutch government, the Ministry of Economic Affairs, the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the Northern Netherlands Collaboration of Provinces (SNN), the Province of Groningen, University Medical Center Groningen, the University of Groningen, Dutch Kidney Foundation and Dutch Diabetes Research Foundation. The authors wish to acknowledge the services of the Lifelines Cohort Study, the contributing research centers delivering data to Lifelines, and all the study participants. NFBC1966 received financial support from the Academy of Finland (EGEA-project, no 285547), University Hospital Oulu, University of Oulu, Finland (75617), NHLBI grant 5R01HL087679-02 (STAMPEED program, 1RL1MH083268-01), the Medical Research Council, UK (PREcisE, JPI HDHL, MR/S03658X/1), H2020 DynaHEALTH action (Grant Agreement 633595), H2020 ALEC Action (Grant Agreement 633212) and H2020 EUCAN Connect (Grant Agreement 824989). Publisher Copyright: © 2021, The Author(s).
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