ArticleCommunications biology2025
An integrated multi-omics analysis identifies protein biomarkers and potential drug targets for psoriatic arthritis.
Article in Communications biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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Who cites it
6 citing papers in PubMed.
- Integrated multi-omics strategies for identifying novel therapies in psoriasis.Bioinformatics (Oxford, England) · 2026Article
- Multi‑omics and their integration in psoriasis research (Review).Molecular medicine reports · 2026Review
- The Clinical Significance and Therapeutic Management of Dactylitis and Enthesitis in Psoriatic Arthritis.Mediterranean journal of rheumatology · 2026Review
- Nrf2 as a redox checkpoint in autoimmune joint inflammation: microenvironmental redox control across the arthritis spectrum.Frontiers in immunology · 2026Review
- Multi-omics insights into spondyloarthritis and psoriatic arthritis: integrating genomics, transcriptomics, proteomics, and the microbiome for immunological and clinical translation.Frontiers in immunology · 2026Review
- Integrative Analysis of Plasma Proteomics and Transcriptomics Reveals Potential Therapeutic Targets for Psoriasis.Biomedicines · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Psoriatic arthritis (PsA) is a complex, chronic immune-mediated inflammatory arthropathy that currently lacks definitive biomarkers and treatment targets. Identifying biomarkers and treatment targets is urgently needed for effectively managing PsA. Here, we conducted a multi-omics approach to identify protein biomarkers and potential drug targets for psoriatic arthritis. Proteome-wide Mendelian randomization (MR) analysis revealed seven plasma protein biomarkers significantly associated with PsA. Specifically, genetically predicted lower levels of NEO1 were linked to an increased PsA risk, whereas the remaining six proteins (IL23R, ERAP2, IFNLR1, KIR2DL3, CLSTN3, and POLR2F) exhibited a positive association with PsA risk. PPI analysis further supported these findings. Notably, druggability assessment revealed that scopoletin and esculetin were the two most significant drugs associated with ERAP2. Single-cell RNA-seq analysis revealed expression of IL23R, ERAP2, CLSTN3, and POLR2F in distinct T-cell subgroups of PBMCs derived from PsA patients. Furthermore, phenome-wide association studies (PheWAS) analysis assessed the potential side effects and safety as potential drug targets. Interestingly, experimental evidence showed that IFNLR1 expression is significantly upregulated under simulated inflammatory conditions. This study employed proteome-wide mendelian randomization to identify seven plasma proteins associated with PsA, including IL23R, ERAP2 and IFNLR1, offering potential insights for personalized PsA treatment strategies.
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Registered trials
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