Large-scale proteomic analysis across the inflammatory skin disease spectrum reveals widespread immune dysregulation with distinct biomarker signatures
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Presented at: Society for Investigative Dermatology 2025
Date: 2025-05-07 00:00:00
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Summary: Abstract Body: Background: Although the molecular characteristics of inflammatory skin diseases are under investigation, a large-scale proteomic expression study of the most common skin conditions is lacking. Objective: To evaluate the tissue proteomic signature of alopecia areata/AA, atopic dermatitis/AD, psoriasis, hidradenitis suppurativa/ HS, and vitiligo and determine biomarkers associated with increased disease severity. Methods: In a cross-sectional study, we assessed 1472 inflammatory, cardiovascular, and exploratory proteins using the OLINK high-throughput Explore panel in moderate-to-severe AA (n=40), AD (n=44), psoriasis (n=32), HS (n=12), and vitiligo patients (n=25) compared to healthy-matched controls (n=52). Results: Our results reveal distinct and shared patterns of immune dysregulation across inflammatory skin diseases. HS contained the greatest dysregulation compared to controls, followed by psoriasis, AA, AD, and vitiligo. Differentially expressed proteins amongst HS and psoriasis patients include markers related to T cell activation (IL2RA/CCL19/CD40LG), innate immunity (IL6R/IL18), Th1 (IFNGR1/CXCL9/CXCL10/CXCL11/IL12B), and Th17 (IL17A/IL17F/PI3/IL19/CCL20). AA and AD contain dysregulated markers related to dendritic cells (ITGAM/CD83), Th1 (IFNGR1/CXCL9/CXCL10/ CXCL11), and Th2 (IL4R/OX40/IL7R/eotaxin-1/CCL13/CCL26; all FDR<.05). Pathway analysis revealed dysregulation across several immune/cardiovascular axes, including JAK/STAT/atherosclerotic proteins. Multiple positive correlations existed between key immune markers (OX40/IL7R/IL17F/TNF/IL6) and clinical severity scores (P<.05). Conclusion: This study revealed shared and distinct molecular protein expression levels across the spectrum of inflammatory skin diseases, suggesting that shared and targeted therapeutic approaches may optimize patient outcomes. Jacob Glickman<sup>1</sup>, Benjamin D. Hu<sup>1</sup>, Eden David<sup>1</sup>, Kristina Navrazhina<sup>1</sup>, Neda Shokrian<sup>1</sup>, Yeriel Estrada<sup>1</sup>, Giselle Singer<sup>1</sup>, James Krueger<sup>2</sup>, Emma Guttman-Yassky<sup>1</sup> 1. Icahn School of Medicine at Mount Sinai, New York, NY, United States. 2. The Rockefeller University, New York, NY, United States. Bioinformatics, Computational Biology, and Imaging