| Title: | A multi-level gene-diet interaction analysis of fish oil and 14 polyunsaturated fatty acid traits identifies the FADS and GPR12 loci |
| Journal: | Human Genetics and Genomics Advances |
| Published: | 21 May 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40405463/ |
| DOI: | https://doi.org/10.1016/j.xhgg.2025.100459 |
Publication 15285
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Abstract
Fish oil supplements (FOS) are known to alter circulating levels of polyunsaturated fatty acids (PUFAs) but in a heterogeneous manner across individuals. These varied responses may result from unidentified gene-FOS interactions. To identify genetic factors that interact with FOS to alter the circulating levels of PUFAs, we performed a multi-level genome-wide interaction study (GWIS) of FOS on 14 plasma measurements in 200,060 unrelated European-ancestry individuals from the UK Biobank. From our single-variant tests, we identified genome-wide significant interacting SNPs (p < 5 × 10-8) in the FADS1-FADS2 gene cluster for total omega-3, omega-3%, docosapentaenoic acid (DHA), DHA%, and the omega-6 to omega-3 ratio. Among the interaction signals for omega-3%, the lead SNP, rs35473591 (C>CT, CT allele frequency = 0.34), had a lower association effect size in the FOS-taking group (β = 0.35 for allele C) than that in the group without FOS (β = 0.42). Likewise, the effect sizes of associations between FOS and omega-3% varied across the three genotype groups (β = 0.45, 0.50, and 0.59, respectively, in C/C, C/CT, and CT/CT). Our gene-level aggregate and transcriptome-wide interaction analyses identified significant signals at two loci around FADS1-FADS2 and GPR12. The contribution of genome-wide gene-FOS interactions to phenotypic variance was statistically significant in omega-3-related traits. This systematic gene-FOS GWIS contributes to our understanding of the genetic architecture of circulating PUFAs underlying FOS response and informs personalized dietary recommendations.</p>
6 Authors
- Susan Adanna Ihejirika
- Alexandra Huong Chiang
- Aryaman Singh
- Eunice Stephen
- Han Chen
- 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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