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http://dx.doi.org/10.3961/jpmph.2009.42.6.356

Discovering Gene-Environment Interactions in the Post-Genomic Era  

Naidoo, Nirinjini (Centre for Molecular Epidemiology, Department of Epidemiology and Public Health, National University of Singapore)
Chia, Kee-Seng (Centre for Molecular Epidemiology, Department of Epidemiology and Public Health, National University of Singapore)
Publication Information
Journal of Preventive Medicine and Public Health / v.42, no.6, 2009 , pp. 356-359 More about this Journal
Abstract
In the more than 100 genome wide association studies (GWAS) conducted in the past 5 years, more than 250 genetic loci contributing to more than 40 common diseases and traits have been identified. Whilst many genes have been linked to a trait, both their individual and combined effects are small and unable to explain earlier estimates of heritability. Given the rapid changes in disease incidence that cannot be accounted for by changes in diagnostic practises, there is need to have well characterized exposure information in addition to genomic data for the study of gene-environment interactions. The case-control and cohort study designs are most suited for studying associations between risk factors and occurrence of an outcome. However, the case control study design is subject to several biases and hence the preferred choice of the prospective cohort study design in investigating geneenvironment interactions. A major limitation of utilising the prospective cohort study design is the long duration of follow-up of participants to accumulate adequate outcome data. The GWAS paradigm is a timely reminder for traditional epidemiologists who often perform one- or few-at-a-time hypothesis-testing studies with the main hallmarks of GWAS being the agnostic approach and the massive dataset derived through large-scale international collaborations.
Keywords
Genome wide association study; Gene environment interactions; Cohort study;
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