The authors regret that they incorrectly cited the name of one of the authors and the contact number of the corresponding author in the original publication. The name of the first author should have read: Nasheen Naidoo. The correct contact number of the corresponding author, Kee Seng Chia, is (65)6516-4971.

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 gene-environment 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.
Case-Control Studies ; Cohort Studies ; *Environment ; *Environmental Exposure ; *Genome, Human ; Genome-Wide Association Study/*methods ; Humans ; Prospective Studies ; Research Design ; Time Factors