Genome-wide association studies of gene-environment interaction (GxE GWAS) are becoming popular. As with main effects GWAS, quantile-quantile plots (QQ-plots) and Genomic Control are being used to assess and correct for population substructure. However, in GxE work these approaches can be seriously misleading, as we illustrate; minor model mis-specification may yield QQ-plots that give strong indications of substructure when absolutely none is present. Using simulation and theory, we show how and why spurious QQ-plot inflation occurs in GxE GWAS, and how this differs from main-effects analyses. We also explain how model robust standard errors alleviate this problem.