乳腺 X 线密度表型的细胞类型感知全转录组关联研究

Background : Mammographic density (MD) phenotypes are highly heritable and strongly associated with breast cancer risk. Genetic variants identified by genome-wide association studies (GWAS) explain only a small fraction of the heritability, and the responsible genes remain largely unknown. Transcriptome-wide association studies (TWAS) can improve power and identify genes associated with MD through their genetically regulated gene expression (GReX) levels. However, cell type heterogeneity in bulk tissue samples can obscure disease associations. Here, we conduct TWAS of MD phenotypes using standard approaches and a new cell-type-aware framework. Methods : The study population included 24,158 women of European ancestry who underwent screening with Hologic (n=20,282) or GE (n=3,876) digital mammography and participated in Kaiser's Research Program on Genes Environment and Health. Dense area (DA), nondense area (NDA), and percent density (PD) were measured centrally using Cumulus6. Tissue-level gene expression was estimated using standard elastic-net models. Cell-type-specific expression in mammary epithelial, fibroblast, and adipocyte cells was estimated using MiXcan. Linear regression was used to assess associations of GReX levels with MD phenotypes, adjusted for age, BMI, and other covariates. Significance was determined by controlling the false-discovery rate at 0.05. Results : A total of 20 unique genes at 16 loci were significantly associated with MD phenotypes, including 10 genes at 7 loci for DA and 8 different genes at 7 loci for NDA. Of the 7 genes for PD, 2 also were associated with DA and 3 with NDA. Standard TWAS methods identified 8 genes whose tissue-level expression was significantly associated with MD phenotypes. In contrast, cell-type-aware analyses using MiXcan identified 10, 12, and 7 genes, respectively, using epithelial, fibroblast, or adipocyte models. Among the 12 genes identified by MiXcan but not standard methods, 2 showed opposite directions of association between different cell types. Conclusion : This TWAS identified novel genes for MD phenotypes, and prioritized genes at known GWAS loci that are likely to be causally associated through their expression levels in mammary epithelial, fibroblast, or adipocyte cells. Disentangling the distinct effects of gene expression in different mammary cell types through cell-type-aware analysis can yield new gene discoveries and insights into the biological basis of dense vs. nondense breast tissue.