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.
| Original language | English |
|---|---|
| Article number | 3124 |
| Number of pages | 17 |
| Journal | Nature Communications |
| Volume | 13 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Dec 2022 |
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In: Nature Communications, Vol. 13, No. 1, 3124, 12.2022.
Research output: Contribution to journal › Article › Research › peer-review
TY - JOUR
T1 - Comprehensive genetic analysis of the human lipidome identifies loci associated with lipid homeostasis with links to coronary artery disease
AU - Cadby, Gemma
AU - Giles, Corey
AU - Melton, Phillip E.
AU - Huynh, Kevin
AU - Mellett, Natalie A.
AU - Duong, Thy
AU - Nguyen, Anh
AU - Cinel, Michelle
AU - Smith, Alex
AU - Olshansky, Gavriel
AU - Wang, Tingting
AU - Brozynska, Marta
AU - Inouye, Mike
AU - McCarthy, Nina S.
AU - Ariff, Amir
AU - Hung, Joseph
AU - Hui, Jennie
AU - Beilby, John
AU - Dubé, Marie Pierre
AU - Watts, Gerald F.
AU - Shah, Sonia
AU - Wray, Naomi R.
AU - Lim, Wei Ling Florence
AU - Chatterjee, Pratishtha
AU - Martins, Ian
AU - Laws, Simon M.
AU - Porter, Tenielle
AU - Vacher, Michael
AU - Bush, Ashley I.
AU - Rowe, Christopher C.
AU - Villemagne, Victor L.
AU - Ames, David
AU - Masters, Colin L.
AU - Taddei, Kevin
AU - Arnold, Matthias
AU - Kastenmüller, Gabi
AU - Nho, Kwangsik
AU - Saykin, Andrew J.
AU - Han, Xianlin
AU - Kaddurah-Daouk, Rima
AU - Martins, Ralph N.
AU - Blangero, John
AU - Meikle, Peter J.
AU - Moses, Eric K.
N1 - Funding Information: Support was provided by the National Health and Medical Research Council of Australia (#1101320 and 1157607) and the Dementia Australia Research Foundation (K.H.; #1197190). This work was also supported in part by the Victorian Government’s Operational Infrastructure Support Program, and the Royal Perth Hospital Research Foundation. The BHS acknowledges the generous support for the 1994/95 Busselton follow-up studies from HealthWay, the Department of Health, PathWest Laboratory Medicine of WA, The Great Wine Estates of the Margaret River region of Western Australia, the Busselton community volunteers who assisted with data collection, and the study participants from the Shire of Busselton. Statistical analyses performed in this work were supported by resources provided by The Pawsey Supercomputing Centre with funding from the Australian Government and the Government of Western Australia. We wish to thank the staff at the Western Australian Data Linkage Branch and Death Registrations and Hospital Morbidity Data Collection for the provision of linked health data. Funding for the AIBL study was provided in part by the study partners [Commonwealth. Scientific Industrial and research Organization (CSIRO), Edith Cowan University (ECU), Mental Health Research institute (MHRI), National Ageing Research Institute (NARI), Austin Health, CogState Ltd]. The AIBL study has also received support from the National Health and Medical Research Council (NHMRC) and the Dementia Collaborative Research Centres program (DCRC2), as well as funding from the Science and Industry Endowment Fund (SIEF) and the Cooperative Research Centre (CRC) for Mental Health—funded through the CRC Program (Grant ID:20100104), an Australian Government Initiative. Support for AIBL genetic data acquisition and analysis was provided by a grant from the NHMRC (APP1161706) awarded to S.M.L. and through the CRC for Mental Health (Grant ID:20100104). T.P. is supported by ECU strategic research funding. Support for the metabolomics sample processing, assays and analytics reported here was provided by grants from the National Institute on Aging (NIA); NIA supported the Alzheimer’s Disease Metabolomics Consortium which is a part of NIA’s national initiatives AMP-AD and M2OVE-AD (R01 AG046171, RF1 AG051550, RF1 AG057452, and 3U01 AG024904-09S4). Additional NIH support from the NIA, NLM and NCI for analysis includes P30 AG10133, R01 AG19771, R01 LM012535, R03 AG054936, R01 AG061788, K01 AG049050, and R01 CA129769. M.A. is supported by National Institute on Aging grants RF1 AG057452, RF1 AG058942, RF1 AG059093, 1U19AG063744, and U01 AG061359. K.N. is supported by NLM R01 LM012535 and NIA R03AG054936. Data collection and sharing for the ADNI was supported by National Institutes of Health Grant U01 AG024904. ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd; Janssen Alzheimer Immunotherapy Research & Development, LLC; Johnson & Johnson Pharmaceutical Research & Development LLC; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health ( www.fnih.org ). The grantee organisation is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. This study was only possible with the help of the AIBL research group. The authors who made direct contribution to this study have been listed as authors in this article. Members of the AIBL group who did not participate in the analysis or writing of this report are listed here: https://aibl.csiro.au/about/aibl-research-team/ . Part of the data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). The authors who made direct contribution to this study have been listed as authors in this article. As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wpcontent/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf . Part of the data used in preparation of this article were generated by the Alzheimer’s Disease Metabolomics Consortium (ADMC). The authors who made direct contribution to this study have been listed as authors in this article. Investigators within the ADMC provided data but did not participate in analysis or writing of this report can be found at https://sites.duke.edu/adnimetab/team/ . Metabolomics data and results from the ADNI study have been made accessible through the AMP-AD Knowledge Portal ( https://ampadportal.org ). The AMP-AD Knowledge Portal is the distribution site for data, analysis results, analytical methodology, and research tools generated by the AMP-AD Target Discovery and Preclinical Validation Consortium and multiple Consortia and research programs supported by the National Institute on Aging. Publisher Copyright: © 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85131318347&partnerID=8YFLogxK
U2 - 10.1038/s41467-022-30875-7
DO - 10.1038/s41467-022-30875-7
M3 - Article
C2 - 35668104
AN - SCOPUS:85131318347
SN - 2041-1723
VL - 13
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 3124
ER -