Abstract P2-11-06: Differential gene expression patterns in healthy breast tissue exhibiting epigenetic age acceleration

Abstract

Abstract Introduction: Breast tissue age, measured with DNA methylation-based estimates, is accelerated in healthy women compared with matched peripheral blood samples. While we have shown that the degree of acceleration in breast epigenetic age is related to hormonal factors including elevated body mass index and earlier age at menarche, no prior work has examined alterations in gene expression that accompany breast epigenetic aging. In this study, we examine gene expression patterns associated with epigenetic age acceleration in healthy breast using six epigenetic clocks. Methods: Using the AllPrep (Qiagen) DNA/RNA Kit, we extracted DNA and RNA from the same breast tissue specimens from 192 healthy women aged 19-90 years who donated breast tissue to the Susan G. Komen Tissue Bank at the Indiana University Simon Comprehensive Cancer Center. Transcriptome analysis was performed using the QuantSeq 3’MRNA-SeqFWD kit to generate RNA sequencing libraries. DNA methylation was quantified using the Illumina EPIC 850K array platform, and methylation age was estimated using beta-values from these experiments. Age acceleration is defined using the residuals of a linear regression of methylation age on chronologic age, and samples with positive residuals were characterized as exhibiting epigenetic age acceleration. Differential gene expression analysis was performed using DESeq2 bioconductor software to estimate variance-mean dependence in count data and using a negative binomial distribution model to test for differential gene expression in samples with accelerated epigenetic age in 6 epigenetic clocks: the Horvath pan-tissue clock, Hannum Age, Phenotypic Age, Grim Age, Skin and Blood clock, and the Epigenetic Pacemaker clock (EPM) , a newly developed clock that accounts for curvilinearity in methylation-based estimates of age over time. Results: Principal components analysis revealed that a large proportion of the variance in gene expression was explained by the first two components (PC1 8.6%, PC2 8.2%). Using a false discovery rate cutoff of 0.05, we found 17 (pan-tissue), 909 (Hannum), 3573 (Phenotypic), 1459 (Grim), 3081 (Skin and Blood), and 227 (EPM) genes differentially expressed with the presence of epigenetic age acceleration for each clock. Examining overlap of these genes revealed distinct groups of genes differentially expressed with acceleration in each clock, with no genes in common for all clocks, Phenotypic and Skin and Blood clocks sharing 1137 genes; Phenotypic, Grim, and Skin and Blood clocks sharing 726 genes; and few genes shared by 5 out of 6 clocks (41 genes in all clocks except pan-tissue, 5 genes in all clocks except EPM). Gene set enrichment analysis revealed activation of pathways involved in cellular respiration, oxidative phosphorylation, energy derivation, organic acid metabolic processes, and immune response, and suppression of genes involved in embryonic epithelial morphogenesis, epidermal cell differentiation, chromatin organization, and lipoprotein transport. Conclusion: We identified significant alterations in gene expression patterns that accompany breast epigenetic acceleration in healthy female breast, with distinct patterns observed for six epigenetic clocks examined. Pathways involved include epithelial morphogenesis and differentiation, potentially representing a mechanistic link between breast accelerated aging and carcinogenesis. Citation Format: Mary Elizabeth Sehl, Wenbin Guo, Colin Farrell, Natascia Marino, Jill E. Henry, Anna Maria Storniolo, Jeannette Papp, Jingyi Jessica Li, Matteo Pellegrini, Steve Horvath, Patricia A. Ganz. Differential gene expression patterns in healthy breast tissue exhibiting epigenetic age acceleration [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-11-06.