| Title: | GWAS and multi-omics integrative analysis reveal novel loci and their molecular mechanisms for circulating fatty acids |
| Journal: | Human Genetics and Genomics Advances |
| Published: | 21 Jun 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40545721/ |
| DOI: | https://doi.org/10.1016/j.xhgg.2025.100470 |
Publication 16415
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Abstract
Previous genome-wide association studies (GWAS) have identified genetic loci associated with the circulating levels of fatty acids (FAs), but the biological mechanisms of these genetic associations remain largely unexplored. Here, we conducted GWAS to identify additional genetic loci for 19 circulating FA traits in UK Biobank participants of European ancestry (n = 239,268) and five other ancestries (n = 508-4,663). We leveraged the GWAS findings to characterize genetic correlations and colocalized regions among FAs, explore sex differences, examine FA loci influenced by lipoprotein metabolism, and apply statistical fine-mapping to pinpoint putative causal variants. We integrated GWAS signals with multi-omics quantitative trait loci (QTL) to reveal intermediate molecular phenotypes mediating the associations between the genetic loci and FA levels. We identified 215 genome-wide significant, independent loci for polyunsaturated fatty acid (PUFA)-related traits in European participants, 163 loci for monounsaturated fatty acid (MUFA)-related traits, and 119 loci for saturated fatty acid (SFA)-related traits, including 70, 61, and 54 novel loci, respectively. A novel locus for total FAs, the percentage of omega-6 PUFAs in total FAs, and total MUFAs (around genes GSTT1/2/2B) colocalized with QTL signals for all six molecular phenotypes examined, including gene expression, protein abundance, DNA methylation, splicing, histone modification, and chromatin accessibility. Across 19 FA traits, 35% of GWAS loci colocalized with QTL signals for at least one molecular phenotype. Our study identifies novel genetic loci for circulating FA levels and systematically uncovers their underlying molecular mechanisms.</p>
3 Authors
- Yitang Sun
- Huifang Xu
- Kaixiong Ye
1 Application
| Application ID | Title |
|---|---|
| 48818 | Evaluate the causal effects of diet-modifiable biomarkers on clinical outcomes using Mendelian randomization |
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