Clustering Patients With Gout Based on Comorbidities and Biomarkers: A Cross-Sectional Study

Area of Science:

• Rheumatology
• Clinical Immunology
• Biochemistry

Background:

• Gout is a complex inflammatory arthritis with diverse clinical presentations.
• Understanding patient heterogeneity is crucial for effective management and treatment strategies.

Purpose of the Study:

• To identify distinct patient clusters based on phenotypes and pathophysiology in gout.
• To investigate the role of oxidative stress and inflammatory markers in gout subtypes.

Main Methods:

• Hierarchical cluster analysis of clinical and biological data from gout patients.
• Assay of serum and plasma samples for inflammatory markers and oxidative stress metabolites.
• Statistical comparison of identified subgroups using ANOVA and chi-square tests.

Main Results:

• Three distinct patient clusters were identified: Cluster 1 (early-onset gout, dyslipidemia, hypertension), Cluster 2 (hypertension, dyslipidemia, nephrolithiasis, obesity), and Cluster 3 (multiple comorbidities, tophi).
• Significant differences in oxidative stress markers (e.g., 3-nitrotyrosine) and inflammatory cytokines (e.g., TNF, IL-1β, IL-6) were observed among the clusters.
• Reclustering confirmed the stability of these identified patient subgroups.

Conclusions:

• Oxidative stress and inflammatory marker levels are associated with the development and clinical phenotypes of gout.
• Measurement of oxidative stress and inflammatory cytokines can serve as adjunctive biomarkers for early gout identification and management.