Evidence map›Paper›PMID 40735322›Full record

ArticleFrontiers in immunology2025

Plasma proteomics-based risk scores for psoriasis prediction: a novel approach to early diagnosis.

Siyu Wei, Zehong Yue, Chen Sun, Yuping Zou, Haiyan Chen, Junxian Tao, Jing Xu, Yuan Xu, Ning Wang, Yan Guo and 14 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

24 authors.

Siyu Wei *College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Zehong Yue *College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Chen Sun *College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Yuping Zou *College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Haiyan ChenCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Junxian TaoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Jing XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Yuan XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Ning WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Yan GuoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Qinduo RenCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Chang WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Songlin LuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Ye MaCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Yu DongCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Chen ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Hongmei SunCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Guoping TangDepartment of Medical Engineering, the Fourth Affiliated Hospital of School of Medicine, International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu, China.
Fanwu KongDepartment of Nephrology, The Second Affiliated Hospital, Harbin Medical University, Harbin, China.
Wenhua LvCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Zhenwei ShangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Mingming ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Yongshuai JiangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Hongchao LyuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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. 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. 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. 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.

Indexed as

Blood ProteinsProteomicsPsoriasisAdultBiomarkersEarly DiagnosisFemaleHumansMaleMiddle AgedRisk AssessmentRisk FactorsBiomarkersBlood ProteinsLASSOplasma proteomicspopulation attributable fractionprotein risk score modelpsoriasis

Identifiers

PMID40735322
PMCPMC12303817

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.