Comprehensive genetic analysis of the human lipidome identifies loci associated with lipid homeostasis with links to coronary artery disease

Gemma Cadby; Corey Giles; Phillip E Melton; Kevin Huynh; Natalie A Mellett; Thy Duong; Anh Nguyen; Michelle Cinel; Alex Smith; Gavriel Olshansky; Tingting Wang; Marta Brozynska; Mike Inouye; Nina S McCarthy; Amir Ariff; Joseph Hung; Jennie Hui; John Beilby; Marie-Pierre Dubé; Gerald F Watts; Sonia Shah; Naomi R Wray; Wei Ling Florence Lim; Pratishtha Chatterjee; Ian Martins; Simon M Laws; Tenielle Porter; Michael Vacher; Ashley I Bush; Christopher C Rowe; Victor L Villemagne; David Ames; Colin L Masters; Kevin Taddei; Matthias Arnold; Gabi Kastenmüller; Kwangsik Nho; Andrew J Saykin; Xianlin Han; Rima Kaddurah-Daouk; Ralph N Martins; John Blangero; Peter J Meikle; Eric K Moses

doi:10.1038/s41467-022-30875-7

Comprehensive genetic analysis of the human lipidome identifies loci associated with lipid homeostasis with links to coronary artery disease

Nat Commun. 2022 Jun 6;13(1):3124. doi: 10.1038/s41467-022-30875-7.

Authors

Gemma Cadby^#¹, Corey Giles^#^{2

3}, Phillip E Melton^{1

4}, Kevin Huynh^{2

3}, Natalie A Mellett², Thy Duong², Anh Nguyen², Michelle Cinel², Alex Smith², Gavriel Olshansky^{2

3}, Tingting Wang^{2

3}, Marta Brozynska², Mike Inouye², Nina S McCarthy⁵, Amir Ariff⁶, Joseph Hung^{7

8

9}, Jennie Hui^{9

10}, John Beilby^{9

10}, Marie-Pierre Dubé¹¹, Gerald F Watts^{7

12}, Sonia Shah¹³, Naomi R Wray^{13

14}, Wei Ling Florence Lim^{15

16}, Pratishtha Chatterjee^{15

17

18}, Ian Martins¹⁵, Simon M Laws^{19

20

21}, Tenielle Porter^{19

20

21}, Michael Vacher^{19

20

22}, Ashley I Bush²³, Christopher C Rowe^{23

24}, Victor L Villemagne^{24

25}, David Ames^{26

27}, Colin L Masters²³, Kevin Taddei¹⁵, Matthias Arnold^{28

29}, Gabi Kastenmüller²⁹, Kwangsik Nho^{30

31

32}, Andrew J Saykin^{30

32

33}, Xianlin Han³⁴, Rima Kaddurah-Daouk^{28

35

36}, Ralph N Martins^{15

16

17

18}, John Blangero³⁷, Peter J Meikle^{38

39

40}, Eric K Moses^{41

42}

Affiliations

¹ School of Population and Global Health, University of Western Australia, Crawley, WA, Australia.
² Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.
³ Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, VIC, Australia.
⁴ Menzies Research Institute, University of Tasmania, Hobart, TAS, Australia.
⁵ School of Biomedical Sciences, University of Western Australia, Crawley, WA, Australia.
⁶ School of Women's and Children's Health, University of New South Wales, Sydney, NSW, Australia.
⁷ School of Medicine, The University of Western Australia, Crawley, WA, Australia.
⁸ Department of Cardiovascular Medicine, Sir Charles Gairdner Hospital, Perth, WA, Australia.
⁹ Busselton Population Medical Research Institute Inc., Perth, WA, Australia.
¹⁰ PathWest Laboratory Medicine WA, Perth, WA, Australia.
¹¹ Université de Montréal Beaulieu-Saucier Pharmacogenomics Centre, Montreal Heart Institute, Montreal, QC, Canada.
¹² Lipid Disorders Clinic, Department of Cardiology, Royal Perth Hospital, Perth, WA, Australia.
¹³ Institute for Molecular Biosciences, University of Queensland, Brisbane, QLD, Australia.
¹⁴ Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia.
¹⁵ School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia.
¹⁶ Cooperative research Centre (CRC) for Mental Health, Joondalup, WA, Australia.
¹⁷ Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, Australia.
¹⁸ KaRa Institute of Neurological Disease, Sydney, Macquarie Park, NSW, Australia.
¹⁹ Centre for Precision Health, Edith Cowan University, Joondalup, WA, Australia.
²⁰ Collaborative Genomics Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia.
²¹ Curtin Health Innovation Research Institute, Curtin University, Perth, WA, Australia.
²² The Australian e-Health Research Centre, Health and Biosecurity, CSIRO, Floreat, WA, Australia.
²³ The Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, Australia.
²⁴ Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, VIC, Australia.
²⁵ Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, VIC, Australia.
²⁶ National Ageing Research Institute, Parkville, VIC, Australia.
²⁷ University of Melbourne Academic Unit for Psychiatry of Old Age, St George's Hospital, Kew, VIC, Australia.
²⁸ Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA.
²⁹ Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
³⁰ Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.
³¹ Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.
³² Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA.
³³ Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA.
³⁴ Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
³⁵ Duke Institute of Brain Sciences, Duke University, Durham, NC, USA.
³⁶ Department of Medicine, Duke University, Durham, NC, USA.
³⁷ South Texas Diabetes and Obesity Institute, The University of Texas Rio Grande Valley, Brownsville, TX, USA.
³⁸ Baker Heart and Diabetes Institute, Melbourne, VIC, Australia. peter.meikle@baker.edu.au.
³⁹ Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, VIC, Australia. peter.meikle@baker.edu.au.
⁴⁰ Monash University, Melbourne, VIC, Australia. peter.meikle@baker.edu.au.
⁴¹ Menzies Research Institute, University of Tasmania, Hobart, TAS, Australia. eric.moses@utas.edu.au.
⁴² School of Biomedical Sciences, University of Western Australia, Crawley, WA, Australia. eric.moses@utas.edu.au.

^# Contributed equally.

Abstract

We integrated lipidomics and genomics to unravel the genetic architecture of lipid metabolism and identify genetic variants associated with lipid species putatively in the mechanistic pathway for coronary artery disease (CAD). We quantified 596 lipid species in serum from 4,492 individuals from the Busselton Health Study. The discovery GWAS identified 3,361 independent lipid-loci associations, involving 667 genomic regions (479 previously unreported), with validation in two independent cohorts. A meta-analysis revealed an additional 70 independent genomic regions associated with lipid species. We identified 134 lipid endophenotypes for CAD associated with 186 genomic loci. Associations between independent lipid-loci with coronary atherosclerosis were assessed in ∼456,000 individuals from the UK Biobank. Of the 53 lipid-loci that showed evidence of association (P < 1 × 10^-3), 43 loci were associated with at least one lipid endophenotype. These findings illustrate the value of integrative biology to investigate the aetiology of atherosclerosis and CAD, with implications for other complex diseases.

Publication types

Meta-Analysis
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Coronary Artery Disease* / genetics
Genetic Loci
Genetic Predisposition to Disease
Genome-Wide Association Study
Homeostasis
Humans
Lipidomics
Lipids
Polymorphism, Single Nucleotide

Substances

Lipids

Abstract

Publication types

MeSH terms

Substances

Grants and funding