rs6504950

A hospital-based case-control study in rural and urban India (1,204 cases; 1,212 controls) examined genetic and lifestyle risk factors for breast cancer. Four SNPs in FGFR2 (rs1219648, rs2420946, rs2981575, rs2981582) showed positive associations with breast cancer (ORs 1.32-1.47). Additional SNPs in obesity and metabolic genes (rs374748 in FBN2, rs2922763 in HNF4G, rs2116830 in KCNMA1, rs11121832 in MTHFR, rs16886165 in MAP3K1, rs11594610 in TCF7L2, rs2274459 in MLN) were associated with increased breast cancer risk. Waist-to-hip ratio ≥0.95 showed strong association (OR 3.78; 95% CI 2.92-4.89), and women living first 20 years in rural areas showed protective effect (OR 0.77).

Population-based case-control study of 1,484 breast cancer cases and 1,307 controls examining 13 GWAS-identified SNPs for breast cancer susceptibility. Confirmed associations for 7 SNPs (rs13387042, rs4973768, rs10941679, rs2981582, rs3817198, rs3803662, rs6504950), with women in the highest quintile of a polygenic risk score having 2.2-fold increased breast cancer risk (95% CI: 1.67-2.88) compared to the lowest quintile. No significant interactions were detected between genetic loci and reproductive/menstrual risk factors.

This paper applies a bias correction method for odds ratio estimates from GWAS discovery data, demonstrating that the 'winner's curse' affects initial effect size estimates. The authors applied conditional maximum likelihood estimation to correct bias in GWAS findings from multiple complex diseases (breast cancer, colorectal cancer, lung cancer, prostate cancer, type I and II diabetes) and show that bias-adjusted odds ratios are substantially more consistent with subsequent replication studies, with selection-adjusted confidence intervals providing better uncertainty quantification than uncorrected estimates.