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Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions

Authors :
Shungin, Dmitry
Deng, Wei Q.
Varga, Tibor V.
Luan, Jian'an
Mihailov, Evelin
Metspalu, Andres
Morris, Andrew P.
Forouhi, Nita G.
Lindgren, Cecilia
Magnusson, Patrik K. E.
Pedersen, Nancy L.
Hallmans, Göran
Chu, Audrey Y.
Justice, Anne E.
Graff, Mariaelisa
Winkler, Thomas W.
Rose, Lynda M.
Langenberg, Claudia
Cupples, L. Adrienne
Ridker, Paul M.
Wareham, Nicholas J.
Ong, Ken K.
Loos, Ruth J. F.
Chasman, Daniel I.
Ingelsson, Erik
Kilpeläinen, Tuomas O.
Scott, Robert A.
Magi, Reedik
Pare, Guillaume
Franks, Paul W.
Shungin, Dmitry
Deng, Wei Q.
Varga, Tibor V.
Luan, Jian'an
Mihailov, Evelin
Metspalu, Andres
Morris, Andrew P.
Forouhi, Nita G.
Lindgren, Cecilia
Magnusson, Patrik K. E.
Pedersen, Nancy L.
Hallmans, Göran
Chu, Audrey Y.
Justice, Anne E.
Graff, Mariaelisa
Winkler, Thomas W.
Rose, Lynda M.
Langenberg, Claudia
Cupples, L. Adrienne
Ridker, Paul M.
Wareham, Nicholas J.
Ong, Ken K.
Loos, Ruth J. F.
Chasman, Daniel I.
Ingelsson, Erik
Kilpeläinen, Tuomas O.
Scott, Robert A.
Magi, Reedik
Pare, Guillaume
Franks, Paul W.
Publication Year :
2017

Abstract

Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (GxE) 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), GxE 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 rho = 0.401 for triglycerides, and rho = 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 rho = 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 (Pmann-Whitney = 1.46x10(-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 GxE interaction P-values (Pint < 0.05) were enriched with nominally significant P-v values (P-binomial = 8.63x10(-9) and 8.52x10(-7) for SNP x smoking and SNP x physical activity, respectively). We conclude that some loci with strong marginal effects may be good candidates for GxE, and variance-based prioritization can be used to identify them.

Details

Database :
OAIster
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1233371119
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.1371.journal.pgen.1006812