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Lookup NU author(s): Dr Ashley RiderORCiD, Dr Henry Grantham, Dr Graham SmithORCiD, John CasementORCiD, Dr Simon CockellORCiD, Wasim Iqbal, Dr Tom EwenORCiD, Dr Shoba AmarnathORCiD, Dr Paolo Zuliani, Professor Nick ReynoldsORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© The Author(s) 2026.Background: Despite increased understanding of psoriasis pathogenesis, molecular classification of clinical phenotypes and disease severity is poorly defined. Knowledge gaps include whether molecular endotypes of psoriasis underlie distinct clinical phenotypes and the positive and negative molecular regulators of disease severity across tissue compartments. Methods: We performed comprehensive RNA sequencing of skin and blood (n = 718) from prospectively-recruited, deeply-phenotyped discovery and replication cohorts of 146 subjects with moderate-to-severe chronic plaque psoriasis initiating TNF-inhibitor (adalimumab) or IL-12/23-inhibitor (ustekinumab) therapy. Results: Here we show, using two complementary dimensionality reduction methods, that co-expressed gene modules and factors within skin and blood are significantly associated with psoriasis phenotypes and disease severity. We identify a 14-gene signature negatively associated with BMI in nonlesional skin and with disease severity in lesional skin. Genotype integration reveals that HLA-DQA1*01 and HLA-DRB1*15 genotypes are positively associated with baseline psoriasis severity. Using explainable machine learning models, we define two disease severity-associated gene modules in lesional skin - one positive, one negatively-associated - and a 9-gene signature in lesional skin predictive of disease severity. Disease severity signatures in blood are only seen following adalimumab exposure, suggesting greater systemic impact of adalimumab compared to ustekinumab, in line with its side effect profile. In contrast, a gene signature in blood linked to HLA-C*06:02 status is independent of disease severity or drug. Conclusions: These findings delineate gene-environmental and genetic effects on the psoriasis transcriptome linked to disease severity.
Author(s): Rider A, Grantham HJ, Smith GR, Watson DS, Casement J, Cockell SJ, Gisby J, Foulkes AC, Henkin R, Iqbal WA, Ewen T, Amarnath S, Ng S, Zuliani P, Dand N, Stocken D, Traini C, Thomas E, Kalyana-Sundaram S, Rajpal DK, Smith KM, Barker JN, Griffiths CEM, Di Meglio P, Smith CH, Warren RB, Barnes MR, Reynolds NJ, Di Meglio P
Publication type: Article
Publication status: Published
Journal: Communications Medicine
Year: 2026
Volume: 6
Issue: 1
Online publication date: 21/01/2026
Acceptance date: 09/12/2025
Date deposited: 09/03/2026
ISSN (electronic): 2730-664X
Publisher: Springer Nature
URL: https://doi.org/10.1038/s43856-025-01325-4
DOI: 10.1038/s43856-025-01325-4
Data Access Statement: Data analysis scripts can be found on our GitHub repository (https://github.com/C4TB/PSORT), along with extended supplemental markdown documents. These are also deposited87 on Zenodo (https://doi.org/10.5281/zenodo.15847636). For the remaining data access statement, please see the article https://doi.org/10.1038/s43856-025-01325-4
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