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July 15, 2026PLoS ONEOpen Access

Transcriptomic characterization of key psoriasis-associated genes based on single-cell RNA-seq and machine learning

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Authors

WWWeixiang WangQZQiang ZhangSXSuting Xu

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Overview

Randomized trial uncovers four critical psoriasis-related genes, suggesting new therapeutic targets.

Key Points

  • This research aims to identify key genes associated with psoriasis using single-cell RNA sequencing and machine learning techniques.
  • Single-cell RNA sequencing datasets were collected from psoriatic and healthy samples via the Gene Expression Omnibus.
  • CIBERSORT was used to estimate cell-type proportions; WGCNA analyzed correlations among cell types and gene expressions.
  • Machine learning algorithms identified four critical genes linked to psoriasis: DEFB4A, GJB2, SERPINB3, and SERPINB13.
  • 271 hub genes related to psoriasis lesions and basal cells were identified through various algorithms.
  • Refinement of the gene list led to the selection of four key psoriasis-associated genes: DEFB4A, GJB2, SERPINB3, and SERPINB13, all of which were found to be upregulated in lesional skin.
  • Potential small-molecule compounds targeting these four genes were proposed, paving the way for new treatment options.

Cite This Study

Wang et al. (2026) studied this question.

synapsesocial.com/papers/6a57245a88b21df875480bfdhttps://doi.org/10.1371/journal.pone.0352663
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Potential marker genes for psoriasis revealed based on single-cell sequencing and Mendelian randomization analysis2025
  2. 2Discovery of biomarkers in the psoriasis through machine learning and dynamic immune infiltration in three types of skin lesions2024 · 17 citations
  3. 3Single-cell transcriptomics identifies keratinocyte-centered lactylation modulation and experimentally validated biomarkers for psoriasis diagnosis2026
  4. 4Core Differentially Expressed Genes in Psoriasis Lesions: An Integrated Analysis of Four GEO Datasets2026
  5. 5Single-Cell RNA Sequencing Revealing Dysregulated Perturbations of Tregs in Psoriasis and Construction of a Treg-Related Diagnostic Model via a 101- Combination Machine Learning Computational Framework2026