| Title: | Plasma proteomics-based risk scores for psoriasis prediction: a novel approach to early diagnosis |
| Journal: | Frontiers in Immunology |
| Published: | 15 Jul 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40735322/ |
| DOI: | https://doi.org/10.3389/fimmu.2025.1618805 |
| URL: | https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2025.1618805/pdf |
Publication 16170
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Abstract
Introduction: Psoriasis is a chronic immune-mediated inflammatory skin disease with a significant global burden. Current risk assessment lacks integration of proteomic data with genetic and clinical factors. This study aimed to develop a plasma proteomics-based risk score (ProtRS) to improve psoriasis prediction.</p>
Methods: Using data from 53,065 UK Biobank (UKB) participants (1,122 psoriasis cases; 51,943 controls), we integrated 2,923 plasma proteins, polygenic risk score (PRS), and seven clinical risk factors. The Least Absolute Shrinkage and Selection Operator (LASSO) algorithm with 10-fold cross-validation identified stable proteins for ProtRS construction. Population Attributable Fractions (PAFs) for risk factors were calculated.</p>
Results: LASSO regression identified 26 highly stable proteins forming ProtRS-26. ProtRS-26 significantly outperformed PRS and clinical risk factors alone. Combining ProtRS-26 with PRS and clinical factors further improved prediction. Key proteins were enriched in pro-inflammatory pathways and skin-derived. PAF analysis identified hypertension and obesity as major modifiable risk factors.</p>
Discussion: Plasma proteomics significantly enhances psoriasis risk prediction compared to genetic and clinical factors alone. ProtRS-26 provides a robust tool for early screening and personalized prevention.</p>
12 Keywords
- Adult
- Biomarkers
- Blood Proteins
- Early Diagnosis
- Female
- Humans
- Male
- Middle Aged
- Proteomics
- Psoriasis
- Risk Assessment
- Risk Factors
24 Authors
- Siyu Wei
- Zehong Yue
- Chen Sun
- Yuping Zou
- Haiyan Chen
- Junxian Tao
- Jing Xu
- Yuan Xu
- Ning Wang
- Yan Guo
- Qinduo Ren
- Chang Wang
- Songlin Lu
- Ye Ma
- Yu Dong
- Chen Zhang
- Hongmei Sun
- Guoping Tang
- Fanwu Kong
- Wenhua Lv
- Zhenwei Shang
- Mingming Zhang
- Yongshuai Jiang
- Hongchao Lyu
1 Application
| Application ID | Title |
|---|---|
| 89695 | Study on the interactions among genotype, phenotype, drug response and environment |
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