Dysregulation of lipid metabolism is as an important –and modifiable– risk factor for multiple diseases, including type 2 diabetes, cardiovascular disease and age-related dementia. While the metabolic pathways of lipids are well characterised, dysregulation of these pathways due to environmental and genetic influences is not well understood. To address this issue, we have applied an integrative approach to link genetic variants with altered lipid metabolism and metabolic disease.
Using lipidomic profiling data from 4,492 genotyped individuals from the Busselton Family Health Study, we performed genome-wide association analysis of 596 lipid species and 33 lipid classes using linear-mixed models, correcting for age, sex, their interactions. To account for lipoprotein mediated associations, the analysis was repeated with HDL-C, triglycerides and total cholesterol as covariates. Validation of genome-wide significant associations was supported by replication and meta-analyses in the Australian Imaging, Biomarker & Lifestyle Study of Ageing (n=1,112) and Alzheimer's Disease Neuroimaging Initiative (n=757) cohorts.
Over 70,000 genome-wide significant (p<5e-08) associations were identified, with 543 lipid species in 737 independent genomic regions, of which 509 have not previously been reported in metabolic-QTL analyses. Using the ProGeM framework, biologically plausible genes were identified in 573 genomic regions. Approximately 70% of the observed associations were independent of lipoprotein measures. Pleiotropic associations of genetic variants were determined by integration of results from expression-QTL and protein-QTL studies.
New insights into the function and specificity of established lipid metabolic pathways were revealed by associations with novel lipid species. Genetic correlations between lipid species and cardiovascular disease in the UK Biobank and CARDIoGRAMplusC4D consortium highlight the shared genetic effects. Colocalisation analyses then identified 47 shared causal variants for coronary artery disease and lipid species, demonstrating the potential to identify targets for monitoring, prevention and treatment of cardiometabolic disease.