Journal of the American Heart AssociationGenetic & Genomic MedicinePeer-reviewed journal article
Lipidome- and genome-wide study to understand sex differences in circulatory lipids
Rubina TabassumiD, Sanni RuotsalaineniD, Linda OttensmanniD, Mathias J. GerliD, Christian D. KloseiD, Taru TukiaineniD, Matti PirineniD, Kai SimonsiD, Elisabeth WidéniD, Samuli RipattiiD
Abstract
Despite well-recognized difference in the atherosclerotic cardiovascular disease (ASCVD) risk between men and women, sex differences in risk factors and sex specific mechanisms in the pathophysiology of ASCVD remain poorly understood. Lipid metabolism plays a central role in the development of ASCVD. Understanding sex differences in lipids and their genetic determinants could provide mechanistic insights into sex differences in ASCVD and aid in precise risk assessment. Thus, we examined sex differences in plasma levels of 179 lipid species from 7,266 participants and performed sex-stratified genome-wide association studies (GWAS) to evaluate contribution of genetic factors in sex differences. We sought for replication using independent data from 2,045 participants. Significant sex differences in levels of 141 lipid species were observed (P<7.0x10-4). Interestingly, 121 lipid species showed significant age-sex interactions with opposite age-related changes in 39 lipid species. In general, most of the cholesteryl esters, ceramides, lysophospholipids and glycerides were higher in 45-50-year-old men compared with women of same age, but the sex-differences narrowed down or reversed with age. We did not observe any major differences in genetic effect in the sex stratified GWAS which suggests that common genetic variants do not have a major role in sex differences in lipidome. In conclusion, our study provides a comprehensive view of sex differences in circulatory lipids pointing to potential sex differences in lipid metabolism, highlighting need for sex- and age-specific prevention strategies.
- organism: human
- assay: metabolomics
- research focus: GWAS / association mapping
- research focus: differential expression
- research focus: benchmarking
- approach: statistical model
- Citations
- 67
- FWCI
- 12.65
- Field percentile
- top 1%
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