Correlation of serum protein biomarkers with disease activity in psoriatic arthritis
Autor: | DoQuyen Huynh, John Temple, P S Eastman, A. Kavanaugh, David L. Boyle, Joshua Hillman, E H Sasso, R Bolce, F Qureshi, T A Boyd |
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Rok vydání: | 2020 |
Předmět: |
Adult
Male Oncology medicine.medical_specialty Immunology Arthritis Disease Cohort Studies Young Adult Psoriatic arthritis Psoriasis Internal medicine medicine Humans Immunology and Allergy Chitinase-3-Like Protein 1 Biomarker Analysis Aged Body surface area Serum Amyloid A Protein Interleukin-6 business.industry Arthritis Psoriatic Middle Aged medicine.disease Cross-Sectional Studies Rheumatoid arthritis Cohort Disease Progression Female business Biomarkers |
Zdroj: | Expert Review of Clinical Immunology. 16:335-341 |
ISSN: | 1744-8409 1744-666X |
Popis: | Objective: To assess the correlation of serum protein biomarkers with disease activity across different domains of psoriatic arthritis (PsA).Material and methods: A cross-sectional cohort of 45 adult patients with PsA fulfilling the classification for psoriatic arthritis (CASPAR) criteria was recruited from University of California San Diego (UCSD) Arthritis Clinics. Clinical data and serum samples were collected and serum was analyzed for protein biomarkers hypothesized to be relevant to disease activity in PsA. Correlations were evaluated for clinical disease activity measures across disease domains.Results: Biomarkers with the highest correlation to the composite indices and disease domains were SAA, IL-6, YKL-40, and ICAM-1. In addition, several biomarkers were moderately correlated with individual composite indices and/or disease domains. Low or no correlation was observed with some biomarkers, e.g. MMP-3, MMP-1, EGF, VEGF, and IL-6R. In contrast, the correlation of all biomarkers with certain disease domains was low; specifically, pain, percent body surface area of psoriasis, and patient global assessment. The multi-biomarker disease activity score (MBDA) developed for rheumatoid arthritis (RA) showed high correlations with most composite indices and some disease domains in PsA.Conclusions: These data suggest biomarker analysis can reflect disease activity across disease domains in PsA. Certain domains would likely benefit from the evaluation of additional biomarkers. |
Databáze: | OpenAIRE |
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