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  4. Polygenic approaches to detect gene-environment interactions when external information is unavailable
 
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Polygenic approaches to detect gene-environment interactions when external information is unavailable

Journal
Briefings in bioinformatics
Journal Volume
20
Journal Issue
6
Pages
2236
Date Issued
2019
Author(s)
WAN-YU LIN  
Huang, Ching-Chieh
Liu, Yu-Li
Tsai, Shih-Jen
PO-HSIU KUO  
DOI
10.1093/bib/bby086
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/493744
URL
https://api.elsevier.com/content/abstract/scopus_id/85064229480
Abstract
The exploration of 'gene-environment interactions' (G × E) is important for disease prediction and prevention. The scientific community usually uses external information to construct a genetic risk score (GRS), and then tests the interaction between this GRS and an environmental factor (E). However, external genome-wide association studies (GWAS) are not always available, especially for non-Caucasian ethnicity. Although GRS is an analysis tool to detect G × E in GWAS, its performance remains unclear when there is no external information. Our 'adaptive combination of Bayes factors method' (ADABF) can aggregate G × E signals and test the significance of G × E by a polygenic test. We here explore a powerful polygenic approach for G × E when external information is unavailable, by comparing our ADABF with the GRS based on marginal effects of SNPs (GRS-M) and GRS based on SNP × E interactions (GRS-I). ADABF is the most powerful method in the absence of SNP main effects, whereas GRS-M is generally the best test when single-nucleotide polymorphisms main effects exist. GRS-I is the least powerful test due to its data-splitting strategy. Furthermore, we apply these methods to Taiwan Biobank data. ADABF and GRS-M identified gene × alcohol and gene × smoking interactions on blood pressure (BP). BP-increasing alleles elevate more BP in drinkers (smokers) than in nondrinkers (nonsmokers). This work provides guidance to choose a polygenic approach to detect G × E when external information is unavailable.
Subjects
Taiwan Biobank; diastolic blood pressure; gene–alcohol interaction; gene–smoking interaction; multiple-testing correction; systolic blood pressure
SDGs

[SDGs]SDG3

Other Subjects
blood pressure; drinking behavior; genotype environment interaction; human; single nucleotide polymorphism; smoking; Alcohol Drinking; Blood Pressure; Gene-Environment Interaction; Humans; Polymorphism, Single Nucleotide; Smoking
Publisher
OXFORD UNIV PRESS
Type
journal article

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