bioRxivSystems BiologyPreprint
Multiscale analysis of acne connects molecular subnetworks with disease status
Jacob B. HalliD, Aparna A. DivaraniyaiD, Hao-Chih LeeiD, Christine BeckeriD, Benjamin D. McCauleyiD, Patricia K. Glowe, Robert SebraiD, Ana Brânduşa PaveliD, Giselle SingeriD, Amanda M. NelsoniD, Diane M. ThiboutotiD, Ellen S. MarmuriD, Eric E. SchadtiD, Joshua ZeichneriD, Emma Guttman‐YasskyiD, Brian A. KiddiD, Joel T. DudleyiD
Abstract
Acne vulgaris affects millions of individuals and can lead to psychosocial impairment as well as permanent scarring. Previous studies investigating acne pathogenesis have either examined a targeted set of biological parameters in a modest-sized cohort or carried out high-throughput assays on a small number of samples. To develop a more comprehensive understanding of acne pathophysiology, we conducted an in-depth multi-omic study of 56 acne patients and 20 individuals without acne. We collected whole blood, skin punch biopsies, microbiota from skin follicles, and relevant clinical measurements to understand how multiple factors contribute to acne. We provide an integrative analysis of multi-omics data that results in a molecular network of acne. Comparisons of lesional and non-lesional skin highlighted multiple biological processes, including immune cell and inflammatory responses, response to stress, T cell activation, lipid biosynthesis, fatty acid metabolism, keratinocytes, antimicrobial activity, epithelial cell differentiation, and response to wounding, that are differentially altered in acne lesions compared to non-lesions. Our results suggest baseline differences in the skin that may predispose individuals to develop acne. These datasets and findings offer a framework for new target identification and reference for future studies.
- organism: human
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: statistical model
- Citations
- 2
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