Meta-analysis can be a useful tool for interpreting multiple tests of a G×E hypothesis, when best practice is followed. Meta-analyses should table the universe of publications testing the G×E interaction, explaining in a transparent way why each was analyzed or omitted. The subsample analyzed should represent the distribution of positive and negative results in the literature. Metaregression should be undertaken to evaluate methodological sources of variation among findings. Methodological evaluation should be guided by long-established cautions. For example, large samples often suffer poor measurement quality, and large exposure-to-outcome correlations often signal measurement bias, not validity. It should be appreciated that when the sample of studies is small, a statistical test for heterogeneity is underpowered and its nonsignificance does not contraindicate metaregression. If methodological heterogeneity is ruled out, metaregression should investigate substantive sources of variation among findings (e.g., sex, age, exposure severity), and if these are uncovered, variation in genetic model should be considered in relation to the substantive findings. Meta-analyses of the 5-HTTLPR G×E hypothesis have been reported (142, 143), but did not follow best practice (17, 151–155).
