Body Mass Index Is Associated with the Immunometabolic Profile in Psoriatic Arthritis: Real-Life Data

Background: Psoriatic arthritis (PsA) is a chronic inflammatory disease frequently associated with obesity and metabolic comorbidities. Increasing evidence suggests that obesity is associated with systemic inflammation, insulin resistance, and adverse clinical outcomes; however, the immunometabolic profile associated with obesity in PsA has not been fully characterized. Objective: To investigate the relationship between obesity, inflammatory biomarkers, cytokine profiles, metabolic parameters, insulin resistance, and disease-related characteristics in patients with PsA. Methods: In this monocentric cross-sectional study, 224 consecutive patients fulfilling the Classification Criteria for Psoriatic Arthritis (CASPAR) for PsA were evaluated. Clinical, inflammatory, metabolic, and cytokine-related variables were analyzed within an integrated immunometabolic framework. Patients were stratified according to obesity status based on body mass index (BMI ≥ 30 kg/m2). Correlation analyses, multivariable regression analyses, and exploratory machine-learning approaches were applied to identify multidimensional patterns associated with obesity. Adjusted multivariable regression analyses were performed to account for available demographic, clinical, comorbidity-related, and therapeutic covariates. Results: Ninety-four patients (42.0%) were classified as obese and 130 (58.0%) as non-obese. Compared with non-obese patients, obese individuals exhibited significantly higher levels of C-reactive protein (CRP; 0.31 vs. 0.13 mg/dL, p < 0.001), erythrocyte sedimentation rate (ESR; 15.0 vs. 10.0 mm/h, p = 0.006), serum amyloid A (SAA; 7.7 vs. 6.4 mg/L, p = 0.008), insulin (8.0 vs. 6.1 μU/mL, p < 0.001), glycated hemoglobin (HbA1c; 38.0 vs. 37.0 mmol/mol, p = 0.003), Homeostasis Model Assessment of Insulin Resistance (HOMA-IR; 1.29 vs. 1.21, p = 0.007), triglycerides (106.0 vs. 85.0 mg/dL, p = 0.019), and Health Assessment Questionnaire (HAQ) scores (p < 0.001). Obese patients also showed a higher prevalence of hypertension (18.1% vs. 6.9%, p = 0.018). BMI was positively correlated with several inflammatory, metabolic, and disease-related variables, including CRP (ρ = 0.383), interleukin-6 (IL-6; ρ = 0.295), insulin (ρ = 0.289), ESR (ρ = 0.245), SAA (ρ = 0.228), HbA1c (ρ = 0.199), HAQ score (ρ = 0.351), and Disease Activity Index for Psoriatic Arthritis (DAPSA) score (ρ = 0.183), while showing an inverse correlation with high-density lipoprotein cholesterol (HDL-C) (ρ = −0.189). After adjustment for age, sex, disease duration, DAPSA, hypertension, type 2 diabetes mellitus, and current therapy class, obesity remained associated with higher CRP and fasting insulin levels and with greater odds of belonging to a higher HAQ category. Machine-learning analyses identified inflammatory biomarkers, insulin resistance indices, and lipid-related parameters as the most informative features associated with obesity-related phenotypes. Conclusions: Obesity in PsA was associated with a broader immunometabolic phenotype characterized by increased inflammatory burden, metabolic dysfunction, and worse functional outcomes. These findings support the integration of metabolic and cardiovascular assessment into routine rheumatology practice and highlight obesity as an important marker of increased immunometabolic and clinical burden in PsA. Although the cross-sectional design precludes causal inference, the observed associations may help identify patients requiring closer metabolic and cardiovascular assessment.

Authors

Institutions

Publication Details

Journal
Diseases
Published
2026-08-17
DOI
https://doi.org/10.3390/diseases14080296
Primary Topic
Spondyloarthritis Studies and Treatments
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Body Mass Index Is Associated with the Immunometabolic Profile in Psoriatic Arthritis: Real-Life Data

María Infantino, Serena Guiducci, Maurizio Benucci, Edda Russo et al.
Diseases
Spondyloarthritis Studies and Treatments
article

Body Mass Index Is Associated with the Immunometabolic Profile in Psoriatic Arthritis: Real-Life Data

María Infantino, Serena Guiducci, Maurizio Benucci, Edda Russo, Francesca Li Gobbi, Viola Svelti, Christian D’Elia, Giada Santagata, Mariangela Manfredi
article en

Abstract

Background: Psoriatic arthritis (PsA) is a chronic inflammatory disease frequently associated with obesity and metabolic comorbidities. Increasing evidence suggests that obesity is associated with systemic inflammation, insulin resistance, and adverse clinical outcomes; however, the immunometabolic profile associated with obesity in PsA has not been fully characterized. Objective: To investigate the relationship between obesity, inflammatory biomarkers, cytokine profiles, metabolic parameters, insulin resistance, and disease-related characteristics in patients with PsA. Methods: In this monocentric cross-sectional study, 224 consecutive patients fulfilling the Classification Criteria for Psoriatic Arthritis (CASPAR) for PsA were evaluated. Clinical, inflammatory, metabolic, and cytokine-related variables were analyzed within an integrated immunometabolic framework. Patients were stratified according to obesity status based on body mass index (BMI ≥ 30 kg/m2). Correlation analyses, multivariable regression analyses, and exploratory machine-learning approaches were applied to identify multidimensional patterns associated with obesity. Adjusted multivariable regression analyses were performed to account for available demographic, clinical, comorbidity-related, and therapeutic covariates. Results: Ninety-four patients (42.0%) were classified as obese and 130 (58.0%) as non-obese. Compared with non-obese patients, obese individuals exhibited significantly higher levels of C-reactive protein (CRP; 0.31 vs. 0.13 mg/dL, p < 0.001), erythrocyte sedimentation rate (ESR; 15.0 vs. 10.0 mm/h, p = 0.006), serum amyloid A (SAA; 7.7 vs. 6.4 mg/L, p = 0.008), insulin (8.0 vs. 6.1 μU/mL, p < 0.001), glycated hemoglobin (HbA1c; 38.0 vs. 37.0 mmol/mol, p = 0.003), Homeostasis Model Assessment of Insulin Resistance (HOMA-IR; 1.29 vs. 1.21, p = 0.007), triglycerides (106.0 vs. 85.0 mg/dL, p = 0.019), and Health Assessment Questionnaire (HAQ) scores (p < 0.001). Obese patients also showed a higher prevalence of hypertension (18.1% vs. 6.9%, p = 0.018). BMI was positively correlated with several inflammatory, metabolic, and disease-related variables, including CRP (ρ = 0.383), interleukin-6 (IL-6; ρ = 0.295), insulin (ρ = 0.289), ESR (ρ = 0.245), SAA (ρ = 0.228), HbA1c (ρ = 0.199), HAQ score (ρ = 0.351), and Disease Activity Index for Psoriatic Arthritis (DAPSA) score (ρ = 0.183), while showing an inverse correlation with high-density lipoprotein cholesterol (HDL-C) (ρ = −0.189). After adjustment for age, sex, disease duration, DAPSA, hypertension, type 2 diabetes mellitus, and current therapy class, obesity remained associated with higher CRP and fasting insulin levels and with greater odds of belonging to a higher HAQ category. Machine-learning analyses identified inflammatory biomarkers, insulin resistance indices, and lipid-related parameters as the most informative features associated with obesity-related phenotypes. Conclusions: Obesity in PsA was associated with a broader immunometabolic phenotype characterized by increased inflammatory burden, metabolic dysfunction, and worse functional outcomes. These findings support the integration of metabolic and cardiovascular assessment into routine rheumatology practice and highlight obesity as an important marker of increased immunometabolic and clinical burden in PsA. Although the cross-sectional design precludes causal inference, the observed associations may help identify patients requiring closer metabolic and cardiovascular assessment.

DiseasesVol. 14(8)
Azienda Usl Toscana Centro (IT), University of Florence (IT)
Good health and well-being
Openalex Percentile: Top 8%
Spondyloarthritis Studies and Treatments
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.