| Title: | Genetic architecture of human plasma lipidome and its link to cardiovascular disease |
| Journal: | Nature Communications |
| Published: | 24 Sep 2019 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/31551469/ |
| DOI: | https://doi.org/10.1038/s41467-019-11954-8 |
| URL: | https://www.nature.com/articles/s41467-019-11954-8.pdf |
Publication 8898
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
Understanding genetic architecture of plasma lipidome could provide better insights into lipid metabolism and its link to cardiovascular diseases (CVDs). Here, we perform genome-wide association analyses of 141 lipid species (n = 2,181 individuals), followed by phenome-wide scans with 25 CVD related phenotypes (n = 511,700 individuals). We identify 35 lipid-species-associated loci (P <5 ×10−8), 10 of which associate with CVD risk including five new loci-COL5A1, GLTPD2, SPTLC3, MBOAT7 and GALNT16 (false discovery rate<0.05). We identify loci for lipid species that are shown to predict CVD e.g., SPTLC3 for CER(d18:1/24:1). We show that lipoprotein lipase (LPL) may more efficiently hydrolyze medium length triacylglycerides (TAGs) than others. Polyunsaturated lipids have highest heritability and genetic correlations, suggesting considerable genetic regulation at fatty acids levels. We find low genetic correlations between traditional lipids and lipid species. Our results show that lipidomic profiles capture information beyond traditional lipids and identify genetic variants modifying lipid levels and risk of CVD.</p>
28 Authors
- Rubina Tabassum
- Joel T. Rämö
- Pietari Ripatti
- Jukka T. Koskela
- Mitja Kurki
- Juha Karjalainen
- Priit Palta
- Shabbeer Hassan
- Javier Nunez-Fontarnau
- Tuomo T. J. Kiiskinen
- Sanni Söderlund
- Niina Matikainen
- Mathias J. Gerl
- Michal A. Surma
- Christian Klose
- Nathan O. Stitziel
- Hannele Laivuori
- Aki S. Havulinna
- Susan K. Service
- Veikko Salomaa
- Matti Pirinen
- Matti Jauhiainen
- Mark J. Daly
- Nelson B. Freimer
- Aarno Palotie
- Marja-Riitta Taskinen
- Kai Simons
- Samuli Ripatti
1 Application
| Application ID | Title |
|---|---|
| 22627 | Fine-mapping genotype-phenotype associations |
Enabling scientific discoveries that improve human health