Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (G×E) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between variance effects (P), G×E interaction effects (with smoking and physical activity), and marginal genetic effects (P). Correlations between P and P were stronger for SNPs with established marginal effects (Spearman's ρ = 0.401 for triglycerides, and ρ = 0.236 for BMI) compared to all SNPs. When P and P were compared for all pruned SNPs, only BMI was statistically significant (Spearman's ρ = 0.010). Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the P distribution (P <0.05). SNPs from the top 1% of the P distribution for BMI had more significant Pv values (P = 1.46×10$\mathrm{<mrow\; data-mjx-texclass="ORD">-5</mrow>}$), and the odds ratio of SNPs with nominally significant (<0.05) P and P was 1.33 (95% CI: 1.12, 1.57) for BMI. Moreover, BMI SNPs with nominally significant G×E interaction P-values (P<0.05) were enriched with nominally significant P values (P = 8.63×10$\mathrm{<mrow\; data-mjx-texclass="ORD">-9</mrow>}$ and 8.52×10$\mathrm{<mrow\; data-mjx-texclass="ORD">-7</mrow>}$ for SNP × smoking and SNP × physical activity, respectively). We conclude that some loci with strong marginal effects may be good candidates for G×E, and variance-based prioritization can be used to identify them.