| Summary: | Women of African ancestry (AA) experience a greater burden from breast cancer and type 2 diabetes compared to women of European ancestry. Some of the racial disparities observed for these diseases may be explained by AA-specific genetic risk variants. The projects conducted here sought to discover risk variants in AA women for overall and subtype-specific breast cancer and for type 2 diabetes using pathway- and gene-based analytic approaches.
Project 1 evaluated 170,812 mostly rare variants across the exome in 3629 breast cancer cases (1093 estrogen receptor negative (ER-), 1968 ER+, 568 ER unknown) and 4658 controls from the African American Breast Cancer Epidemiology and Risk (AMBER) Consortium. Gene-based analyses found ER- associations with PDE4D (previously identified in GWAS) and FBXL22 (novel), based on very small counts at extremely rare SNPs.
Project 2 evaluated common SNPs in 308 genes in hormone pathways using 3663 breast cancer cases (1098 ER-, 1983 ER+, 582 ER unknown) and 4687 controls from AMBER. Gene-based and single SNP analyses identified eight genes (CALM2, CETP, NR0B1, IGF2R, CYP1B1, PGR, MAPK3, and MAP3K1) that contained common variants associated with overall or subtype-specific breast cancer after gene-level correction for multiple testing.
Project 3 evaluated common SNPs in 69 genes involved in the Wnt pathway using 2632 type 2 diabetes cases and 2596 controls from the Black Women’s Health Study. Gene-based and single SNP analyses were run, and an association was observed between the PSMD2 gene region and type 2 diabetes. Association data on a subset of the top PSMD2 SNPs were available from a large, independent AA sample; associations were in the same direction, but weak and not statistically significant. We also identified a TCF7L2 SNP that may represent a novel, independent association signal seen only in AA populations.
Many of the SNPs identified in the present research are more common in AA populations, possibly explaining their lack of discovery by European ancestry genome-wide association studies. Replication of the associations we observed using independent AA samples is necessary. Future studies should consider the entire gene regions identified in our research rather than focusing solely on the specific variants highlighted.
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