Document Type

Journal Article

Publication Title

Nature Communications

Volume

13

Issue

1

PubMed ID

35668104

Publisher

Nature

School

School of Medical and Health Sciences / Centre for Precision Health

RAS ID

43321

Funders

National Health and Medical Research Council of Australia Grants: 1101320, 1157607, APP1161706 / Edith Cowan University (ECU) /

Further funding information available at:

https://doi.org/10.1038/s41467-022-30875-7

Grant Number

NHMRC Numbers : 1101320, 1157607, APP1161706

Comments

Cadby, G., Giles, C., Melton, P. E., Huynh, K., Mellett, N. A., Duong, T., ... & Moses, E. K. (2022). Comprehensive genetic analysis of the human lipidome identifies loci associated with lipid homeostasis with links to coronary artery disease. Nature Communications, 13(1), 1-17.

https://doi.org/10.1038/s41467-022-30875-7

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.

DOI

10.1038/s41467-022-30875-7

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Research Themes

Health

Priority Areas

Multidisciplinary biological approaches to personalised disease diagnosis, prognosis and management

Included in

Diseases Commons

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