Battram T, Hoskins L, Hughes DA et al. Coronary artery disease, genetic risk and the metabolome in young individuals [version 2; peer review: 2 approved]. Wellcome Open Res 2019, 3:114 (https://doi.org/10.12688/wellcomeopenres.14788.2)
Coronary artery disease, genetic risk and the metabolome in young individuals [version 2; peer review: 2 approved]
|Author:||Battram, Thomas1,2; Hoskins, Luke1,2; Hughes, David A.1,2;|
1MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
2Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
3Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
4Biocenter Oulu, University of Oulu, Oulu, Finland
|Online Access:||PDF Full Text (PDF, 1.4 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe202102114496
|Publish Date:|| 2021-02-11
Background: Genome-wide association studies have identified genetic variants associated with coronary artery disease (CAD) in adults — the leading cause of death worldwide. It often occurs later in life, but variants may impact CAD-relevant phenotypes early and throughout the life-course. Cohorts with longitudinal and genetic data on thousands of individuals are letting us explore the antecedents of this adult disease.
Methods: 148 metabolites, with a focus on the lipidome, measured using nuclear magnetic resonance (¹H-NMR) spectroscopy, and genotype data were available from 5,907 individuals at ages 7, 15, and 17 years from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Linear regression was used to assess the association between the metabolites and an adult-derived genetic risk score (GRS) of CAD comprising 146 variants. Individual variant-metabolite associations were also examined.
Results: The CAD-GRS associated with 118 of 148 metabolites (false discovery rate [FDR] < 0.05), the strongest associations being with low-density lipoprotein (LDL) and atherogenic non-LDL subgroups. Nine of 146 variants in the GRS associated with one or more metabolites (FDR < 0.05). Seven of these are within lipid loci: rs11591147 PCSK9, rs12149545 HERPUD1-CETP, rs17091891 LPL, rs515135 APOB, rs602633 CELSR2-PSRC1, rs651821 APOA5, rs7412 APOE-APOC1. All associated with metabolites in the LDL or atherogenic non-LDL subgroups or both including aggregate cholesterol measures. The other two variants identified were rs112635299 SERPINA1 and rs2519093 ABO.
Conclusions: Genetic variants that influence CAD risk in adults are associated with large perturbations in metabolite levels in individuals as young as seven. The variants identified are mostly within lipid-related loci and the metabolites they associated with are primarily linked to lipoproteins. Along with further research, this knowledge could allow for preventative measures, such as increased monitoring of at-risk individuals and perhaps treatment earlier in life, to be taken years before any symptoms of the disease arise.
Wellcome open research
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
3121 General medicine, internal medicine and other clinical medicine
This work was supported by the Wellcome Trust through a Wellcome PhD studentship to TB , a Wellcome Trust Investigator award to NJT , and through the core programme support for The Avon Longitudinal Study for Parents and Children (ALSPAC) .
The UK Medical Research Council, Wellcome and the University of Bristol provide core support for ALSPAC. This publication is the work of the authors and TB and NJT will serve as guarantors for the contents of this paper. A comprehensive list of grants funding (http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf) is available on the ALSPAC website. The collection and processing of the NMR-metabolomics data was funded by the MRC (MC_UU_12013/1).
TB, DAH, SMR, GDS and NJT work in a Unit that receives funds from the University of Bristol and the UK Medical Research Council (MC_UU_12013/1 and MC_UU_12013/2).
NJT is also supported by a Cancer Research UK programme grant (C18281/A19169) and works within the University of Bristol NIHR Biomedical Research Centre (BRC).
GWAS data was generated by Sample Logistics and Genotyping Facilities at Wellcome Sanger Institute and LabCorp (Laboratory Corporation of America) using support from 23andMe.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
© 2019 Battram T et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.