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Am J Hum Genet. 2019 Oct 30. pii: S0002-9297(19)30389-1. doi: 10.1016/j.ajhg.2019.10.001. [Epub ahead of print]

Multivariate Genome-Wide Association Analysis of a Cytokine Network Reveals Variants with Widespread Immune, Haematological, and Cardiometabolic Pleiotropy.

Author information

1
Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia; Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, United Kingdom; Department of Microbiology and Immunology, University of Melbourne, Parkville, Victoria 3010, Australia. Electronic address: artika.nath@baker.edu.au.
2
Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia; Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, United Kingdom.
3
Cambridge Institute of Therapeutic Immunology and Infectious Disease, Department of Medicine, University of Cambridge, Cambridge CB2 0AW, United Kingdom.
4
Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia.
5
Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia; Department of Clinical Pathology, University of Melbourne, Parkville, Victoria 3010, Australia.
6
Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA; Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland.
7
Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki 00014, Finland; Nightingale Health Ltd., Helsinki 00300, Finland.
8
Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland; National Institute of Health and Welfare, Helsinki 00271, Finland.
9
Medicity Research Laboratory, Department of Medical Microbiology and Immunology, University of Turku, Turku 20520, Finland.
10
Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku 20520, Finland.
11
Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland.
12
Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland; Department of Clinical Physiology, Tampere University Hospital, Tampere 33521, Finland.
13
Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland; Department of Public Health, University of Helsinki, Helsinki 00014, Finland; Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
14
Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland; Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114, USA; Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts 02114, USA; Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts 02114, USA.
15
Department of Medicine, University of Turku, Turku 20520, Finland; Division of Medicine, Turku University Hospital, Turku 20520, Finland.
16
Medicity Research Laboratory and Institute of Biomedicine, University of Turku, Turku 20520, Finland.
17
Cambridge Institute of Therapeutic Immunology and Infectious Disease, Department of Medicine, University of Cambridge, Cambridge CB2 0AW, United Kingdom; MRC Biostatistics Unit, Institute of Public Health, Cambridge CB2 0SR, United Kingdom.
18
Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku 20520, Finland; The Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku 20520, Finland.
19
Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia; Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, United Kingdom; Department of Clinical Pathology, University of Melbourne, Parkville, Victoria 3010, Australia.
20
Medicity Research Laboratory, Department of Medical Microbiology and Immunology, University of Turku, Turku 20520, Finland; Computational Medicine, Centre for Life Course Health Research, University of Oulu, Oulu 90014, Finland; NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio 70211, Finland; Biocenter Oulu, University of Oulu, Oulu 90014, Finland.
21
Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia; Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, United Kingdom; Department of Clinical Pathology, University of Melbourne, Parkville, Victoria 3010, Australia; The Alan Turing Institute, London, United Kingdom. Electronic address: mi336@medschl.cam.ac.uk.

Abstract

Cytokines are essential regulatory components of the immune system, and their aberrant levels have been linked to many disease states. Despite increasing evidence that cytokines operate in concert, many of the physiological interactions between cytokines, and the shared genetic architecture that underlies them, remain unknown. Here, we aimed to identify and characterize genetic variants with pleiotropic effects on cytokines. Using three population-based cohorts (n = 9,263), we performed multivariate genome-wide association studies (GWAS) for a correlation network of 11 circulating cytokines, then combined our results in meta-analysis. We identified a total of eight loci significantly associated with the cytokine network, of which two (PDGFRB and ABO) had not been detected previously. In addition, conditional analyses revealed a further four secondary signals at three known cytokine loci. Integration, through the use of Bayesian colocalization analysis, of publicly available GWAS summary statistics with the cytokine network associations revealed shared causal variants between the eight cytokine loci and other traits; in particular, cytokine network variants at the ABO, SERPINE2, and ZFPM2 loci showed pleiotropic effects on the production of immune-related proteins, on metabolic traits such as lipoprotein and lipid levels, on blood-cell-related traits such as platelet count, and on disease traits such as coronary artery disease and type 2 diabetes.

KEYWORDS:

GWAS; blood cell traits; cardiometabolic diseases; colocalisation analysis; cytokines; eQTLs; metabolites; multivariate analysis; protein QTLs

PMID:
31679650
DOI:
10.1016/j.ajhg.2019.10.001

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