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Meta-Analysis
. 2022 Nov 30:13:1054539.
doi: 10.3389/fimmu.2022.1054539. eCollection 2022.

Biomarkers in psoriatic arthritis: A meta-analysis and systematic review

Theo Wirth  1 , Nathalie Balandraud  1   2 , Laurent Boyer  3 , Pierre Lafforgue  1 , Thao Pham  1
Affiliations
Meta-Analysis

Biomarkers in psoriatic arthritis: A meta-analysis and systematic review

Theo Wirth et al. Front Immunol. .

Abstract

Introduction: Psoriatic arthritis (PsA) is a chronic inflammatory disease that frequently develops in patients with psoriasis (PsO) but can also occur spontaneously. As a result, PsA diagnosis and treatment is commonly delayed, or even missed outright due to the manifold of clinical presentations that patients often experience. This inevitably results in progressive articular damage to axial and peripheral joints and entheses. As such, patients with PsA frequently experience reduced expectancy and quality of life due to disability. More recently, research has aimed to improve PsA diagnosis and prognosis by identifying novel disease biomarkers.

Methods: Here, we conducted a systematic review of the published literature on candidate biomarkers for PsA diagnosis and prognosis in MEDLINE(Pubmed), EMBase and the Cochrane library with the goal to identify clinically applicable PsA biomarkers. Meta-analyses were performed when a diagnostic bone and cartilage turnover biomarker was reported in 2 or moredifferent cohorts of PsA and control.

Results: We identified 1444 publications and 124 studies met eligibility criteria. We highlighted bone and cartilage turnover biomarkers, genetic markers, and autoantibodies used for diagnostic purposes of PsA, as well as acute phase reactant markers and bone and cartilage turnover biomarkers for activity or prognostic severity purposes. Serum cartilage oligometrix metalloproteinase levels were significantly increased in the PsA sera compared to Healthy Control (HC) with a standardized mean difference (SMD) of 2.305 (95%CI 0.795-3.816, p=0.003) and compared to osteoarthritis (OA) with a SMD of 0.783 (95%CI 0.015-1.551, p=0.046). The pooled serum MMP-3 levels were significantly higher in PsA patients than in PsO patients with a SMD of 0.419 (95%CI 0.119-0.719; p=0.006), but no significant difference was highlighted when PsA were compared to HC. While we did not identify any new genetic biomarkers that would be useful in the diagnosis of PsA, recent data with autoantibodies appear to be promising in diagnosis, but no replication studies have been published.

Conclusion: In summary, no specific diagnostic biomarkers for PsA were identified and further studies are needed to assess the performance of potential biomarkers that can distinguish PsA from OA and other chronic inflammatory diseases.

Keywords: arthritis; meta-analysis; psoriasis; psoriatic arthritis; psoriatic biomarker.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flowchart of the study selection.
Figure 2
Figure 2
Meta-analysis of COMP levels. (A) Forest plot of difference in COMP levels means between PsA and HC in meta-analysis. (B) Forest plot of difference in serum COMP levels means between PsA and OA.
Figure 3
Figure 3
Meta-analysis of serum MMP3 levels. (A) Forest plot of difference in serum MMP3 levels means between PsA and HC. (B) Forest plot of difference in serum MMP3 levels means between PsA and PsO.
Figure 4
Figure 4
Meta-analysis of circulating biomarkers. (A) Forest plot of difference in serum RANK-L levels means between PsA and HC. (B) Forrest plot of difference in mean levels of OPG between PsA and HC. (C) Forrest plot of difference in mean levels of OPG between PsA and PsO.
Figure 5
Figure 5
Forest plot of difference in Dkk-1 levels means between PsA and HC in meta-analysis.
See this image and copyright information in PMC

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