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Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions
Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (G×E) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between varianc...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5489225/ https://www.ncbi.nlm.nih.gov/pubmed/28614350 http://dx.doi.org/10.1371/journal.pgen.1006812 |
Sumario: | Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (G×E) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between variance effects (P(v)), G×E interaction effects (with smoking and physical activity), and marginal genetic effects (P(m)). Correlations between P(v) and P(m) were stronger for SNPs with established marginal effects (Spearman’s ρ = 0.401 for triglycerides, and ρ = 0.236 for BMI) compared to all SNPs. When P(v) and P(m) were compared for all pruned SNPs, only BMI was statistically significant (Spearman’s ρ = 0.010). Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the P(v) distribution (P(binomial) <0.05). SNPs from the top 1% of the P(m) distribution for BMI had more significant P(v) values (P(Mann–Whitney) = 1.46×10(−5)), and the odds ratio of SNPs with nominally significant (<0.05) P(m) and P(v) was 1.33 (95% CI: 1.12, 1.57) for BMI. Moreover, BMI SNPs with nominally significant G×E interaction P-values (P(int)<0.05) were enriched with nominally significant P(v) values (P(binomial) = 8.63×10(−9) and 8.52×10(−7) for SNP × smoking and SNP × physical activity, respectively). We conclude that some loci with strong marginal effects may be good candidates for G×E, and variance-based prioritization can be used to identify them. |
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