{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T15:10:36Z","timestamp":1788966636640,"version":"build-2803163510"},"reference-count":24,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T00:00:00Z","timestamp":1788912000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Scientific Research Projects Coordination Unit of Kutahya Health Sciences University","award":["THD-2026-336"],"award-info":[{"award-number":["THD-2026-336"]}]},{"award":["THD-2026-336"],"award-info":[{"award-number":["THD-2026-336"]}],"id":[{"id":"https:\/\/ror.org\/01fxqs415","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Clin. Med.","JCM"],"abstract":"<jats:p>Background: The classification of metabolic risk solely based on body mass index (BMI) fails to acknowledge the heterogeneity inherent in obesity. Soluble urokinase plasminogen activator receptor (suPAR) has been proposed as a stable biomarker of chronic inflammation; however, its behaviour across metabolic obesity phenotypes defined jointly by adiposity and insulin resistance remains uncertain. Methods: In this cross-sectional study, 190 adults aged 18 to 60 years attending internal medicine outpatient clinics were stratified by BMI (\u226530 kg\/m2) and homeostasis model assessment of insulin resistance (HOMA-IR \u2265 2.5) into four phenotypes: non-obese insulin-sensitive (NOIS, n = 64), non-obese insulin-resistant (NOIR, n = 50), obese insulin-sensitive (OIS, n = 33), and obese insulin-resistant (OIR, n = 43). Serum suPAR, interleukin-6 (IL-6), and C-X-C motif chemokine ligand 10 (CXCL10) were measured using enzyme-linked immunosorbent assays. Group comparisons, rank-based two-factor analyses, correlation analyses, logistic regression, and receiver operating characteristic (ROC) analyses were performed. Results: Serum suPAR did not differ across the four phenotypes (p = 0.19) and was not correlated with HOMA-IR (\u03c1 = \u22120.09, p = 0.24). IL-6 was lower in the OIR group than in the NOIS group (p = 0.012). CXCL10 was higher in both obese phenotypes than in both non-obese phenotypes (p &lt; 0.001), and rank-based two-factor analysis attributed this difference to obesity (p &lt; 0.001) rather than insulin resistance (p = 0.71). CXCL10 correlated with BMI (\u03c1 = 0.29, p &lt; 0.001) and remained associated with obesity after adjustment for age, sex, and C-reactive protein (odds ratio per 10 ng\/L, 1.12; 95% confidence interval, 1.06 to 1.18). CXCL10 discriminated obesity with an area under the ROC curve of 0.74 (95% CI, 0.66 to 0.81). None of the three biomarkers discriminated insulin resistance (areas under the curve, 0.43 to 0.50). The association between CXCL10 and obesity was consistent in both sexes and unchanged with alternative HOMA-IR cutoffs of 2.0 and 3.0. Conclusions: In this cohort, circulating CXCL10 tracked adiposity rather than insulin resistance, whereas suPAR and IL-6 did not separate metabolic obesity phenotypes. These findings do not support suPAR as a marker of insulin resistance independently of body fat.<\/jats:p>","DOI":"10.3390\/jcm15186990","type":"journal-article","created":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T14:02:48Z","timestamp":1788962568000},"page":"6990","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Evaluation of Serum Soluble Urokinase Plasminogen Activator Receptor (suPAR) Levels in Different Metabolic Obesity Phenotypes and Their Association with Inflammatory Cytokines: A Cross-Sectional Study"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9395-3366","authenticated-orcid":false,"given":"Aycan","family":"Acet","sequence":"first","affiliation":[{"name":"Department of Internal Medicine, Faculty of Medicine, Kutahya Health Sciences University, 43100 Kutahya, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cagla","family":"Ozdemir","sequence":"additional","affiliation":[{"name":"Department of Family Medicine, Faculty of Medicine, Kutahya Health Sciences University, 43100 Kutahya, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hatice","family":"Solak","sequence":"additional","affiliation":[{"name":"Department of Physiology, Faculty of Medicine, Kutahya Health Sciences University, 43100 Kutahya, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1027","DOI":"10.1016\/S0140-6736(23)02750-2","article-title":"Worldwide trends in underweight and obesity from 1990 to 2022: A pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults","volume":"403","author":"Phelps","year":"2024","journal-title":"Lancet"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"860","DOI":"10.1038\/nature05485","article-title":"Inflammation and metabolic disorders","volume":"444","author":"Hotamisligil","year":"2006","journal-title":"Nature"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/S2213-8587(13)70062-7","article-title":"Metabolically healthy obesity: Epidemiology, mechanisms, and clinical implications","volume":"1","author":"Stefan","year":"2013","journal-title":"Lancet Diabetes Endocrinol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"bnaa004","DOI":"10.1210\/endrev\/bnaa004","article-title":"Metabolically Healthy Obesity","volume":"41","year":"2020","journal-title":"Endocr. 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