ArticlePloS one2025
Identification of novel biomarkers related to pathogenesis and treatment of psoriasis based on integrated analysis of weighted gene co-expression network analysis and LASSO.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02310750 (A Phase 1, Within Cohort, Randomized, Double Blind, Third-party Open, Placebo-controlled, Single- And Multiple Dose Escalation, Parallel Group Study To Evaluate The Safety, Tolerability, Pharmacokinetics And Pharmacodynamics Of Pf-06700841 In Healthy Subjects And Subjects With Plaque Psoriasis And Bioavailability Of A Tablet Formulation Relative To Suspension Formulation And The Effect Of Food On A Tablet Formulation Of Pf-06700841), which is not on this map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
A Phase 1, Within Cohort, Randomized, Double Blind, Third-party Open, Placebo-controlled, Single- And Multiple Dose Escalation, Parallel Group Study To Evaluate The Safety, Tolerability, Pharmacokinetics And Pharmacodynamics Of Pf-06700841 In Healthy Subjects And Subjects With Plaque Psoriasis And Bioavailability Of A Tablet Formulation Relative To Suspension Formulation And The Effect Of Food On A Tablet Formulation Of Pf-06700841
Who cites it
1 citing paper in PubMed.
- APOA1, DEFB103A_DEFB103B and DSG3 Are Novel Circulating Biomarkers of Psoriasis.International journal of molecular sciences · 2026Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPsoriasis is an inflammatory skin disease, and current treatments have their own limitations, including moderate treatment effectiveness, poor compliance, and potential safety risks, etc. Therefore, the primary focus of this study is to explore novel molecular targets and improve the diagnosis and treatment of psoriasis patients.
methodIn this study, comprehensive bioinformatics analysis was performed on the expression profiles of tissue samples from patients with psoriasis in the clinical trial of TYK2/JAK1 inhibitor treatment (NCT02310750). Weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) regression were performed to identify characteristic genes and construct the diagnostic models. Gene set enrichment analysis (GSEA) was used to identify the biological processes of psoriasis characteristic gene sets. GO and KEGG pathway analysis were combined to elucidate the potential biological significance of differentially expressed genes (DEGs). The accuracy of biomarker identification was further validated using immune cell infiltration and receiver operating characteristic (ROC) curves based on external data (GSE6710\GSE30999\GSE14905).
resultsA total of 5 genes (DEFB103A, OAS3, OASL, SAMD9, STAT1) were co-identified as characteristic genes in psoriasis progression and treatment. The feature of the immune cell infiltration was highly consistent with association of characteristic biomarkers with immune cells. A total of 14 up-regulated genes and 5 down-regulated genes were identified in respective modules (AUC NL/LS = 0.9783; AUC pre/post = 0.9395; AUC external = 0.9469). In addition, 8 genes (DEFB103A, OASL, HERC6, ISG15, MKI67, MX1, MXD1, SCO2) were considered to have statistically significant differences in sensitivity of short-term treatment for psoriasis.
conclusionThe research findings provide an understanding of the role of novel biomarkers and offer a perspective for further in-depth investigation into the progression and treatment of psoriasis.
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