I. M. Elfaki, L. Kellman, R. Meyers, L. Ducoli, M. Fu, K. Obbad, S. Mondal, X. Yang, D. F. Porter, D. Reynolds, S. Srinivasan, T. Nakase, M. Ota, T. Fabo, J. Meyers, L. Yang, N. Sinnot-Armstrong, K. Westerman, L. Kachuri, P. Khavari
Insight into population-level gene-environment (GxE) interactions is a major goal in understanding polygenic diseases, such as breast cancer. We integrated massively parallel reporter assays (MPRA), chromatin profiling, and network analysis to identify estrogen-responsive breast cancer variants. Screening 1,604 GWAS-identified breast cancer variants identified 73 estrogen-modulated SNVs (emSNVs). Chromatin accessibility modeling validated allele-specific effects, identifying variants that disrupt pioneer factor binding to chromatin and others that modulate transcription factor (TF) recruitment to pre-accessible enhancers. emSNV targets converged on pathways including mitochondrial metabolism, NF-{kappa}B signaling, and chromatin regulation. Aggregating emSNVs into a polygenic risk score (PRSE2) revealed interactions with reproductive risk factors in 13,026 post-menopausal BRCA cases and 108,265 controls, including age at first birth (p=0.0052); a control PRS lacking estrogen-responsive variants showed no interactions. This framework bridges molecular and epidemiological GxE studies to uncover variants whose disease associations depend on environmental context, with implications for understanding polygenic disease risk.