| Title: | Genome-wide variance quantitative trait locus analysis suggests small interaction effects in blood pressure traits |
| Journal: | Scientific Reports |
| Published: | 25 Jul 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/35879408/ |
| DOI: | https://doi.org/10.1038/s41598-022-16908-7 |
| URL: | https://www.nature.com/articles/s41598-022-16908-7.pdf |
Publication 10373
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Abstract
Genome-wide variance quantitative trait loci (vQTL) analysis complements genome-wide association study (GWAS) and has the potential to identify novel variants associated with the trait, explain additional trait variance and lead to the identification of factors that modulate the genetic effects. I conducted genome-wide analysis of the UK Biobank data and identified 27 vQTLs associated with systolic blood pressure (SBP), diastolic blood pressure (DBP) and pulse pressure (PP). The top single-nucleotide polymorphisms (SNPs) are enriched for expression QTLs (eQTLs) or splicing QTLs (sQTLs) annotated by GTEx, suggesting their regulatory roles in mediating the associations with blood pressure (BP). Of the 27 vQTLs, 14 are known BP-associated QTLs discovered by GWASs. The heteroscedasticity effects of the 13 novel vQTLs are larger than their genetic main effects, which were not detected by existing GWASs. The total R-squared of the 27 top SNPs due to variance heteroscedasticity is 0.28%, compared with 0.50% owing to their main effects. The overall effect size of the variance heteroscedasticity is small in GWAS SNPs compared with their main effects. For the 411, 384 and 285 GWAS SNPs associated with SBP, DBP and PP, respectively, their heteroscedasticity effects were 0.52%, 0.43%, and 0.16%, and their main effects were 5.13%, 5.61%, and 3.75%, respectively. The number and effects of the vQTLs are small, which suggests that the effects of gene-environment and gene-gene interactions are small. The main effects of the SNPs remain the major source of genetic variance for BP, which would probably be true for other complex traits as well.</p>
1 Author
- Gang Shi
1 Application
| Application ID | Title |
|---|---|
| 44080 | SNP-Biomarker Interactions in Blood Pressure Regulation |
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