Gene-environment-wide association studies: emerging approaches

被引:480
作者
Thomas, Duncan [1 ]
机构
[1] Univ So Calif, Dept Prevent Med, Los Angeles, CA 90089 USA
关键词
SAMPLE-SIZE REQUIREMENTS; SET ENRICHMENT ANALYSIS; CASE-PARENTS DESIGN; S-TRANSFERASE M1; GENOME-WIDE; BREAST-CANCER; MENDELIAN RANDOMIZATION; MOLECULAR EPIDEMIOLOGY; COMPLEX PATHWAYS; DNA METHYLATION;
D O I
10.1038/nrg2764
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Despite the yield of recent genome-wide association (GWA) studies, the identified variants explain only a small proportion of the heritability of most complex diseases. This unexplained heritability could be partly due to gene-environment (G x E) interactions or more complex pathways involving multiple genes and exposures. This Review provides a tutorial on the available epidemiological designs and statistical analysis approaches for studying specific G x E interactions and choosing the most appropriate methods. I discuss the approaches that are being developed for studying entire pathways and available techniques for mining interactions in GWA data. I also explore methods for marrying hypothesis-driven pathway-based approaches with 'agnostic' GWA studies.
引用
收藏
页码:259 / 272
页数:14
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