Transcriptomic profiling and machine learning uncover gene signatures of psoriasis endotypes and disease severity.

ABSTRACT:

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

SUBMITTER: Rider A 

PROVIDER: S-EPMC12852803 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature