{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T21:43:26Z","timestamp":1773265406378,"version":"3.50.1"},"reference-count":56,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T00:00:00Z","timestamp":1773187200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Endocrinol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Hyperuricemia (HUA) and metabolic syndrome (MetS) are increasingly prevalent and closely related. This single-center, retrospective study aims to explore the correlation between HUA and individual MetS components in Chinese patients with type 2 diabetes mellitus (T2DM), and further explores its potential influence on bone metabolism indicators.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Method<\/jats:title>\n                    <jats:p>This retrospective study included patients age 18\u201380 attending Peking University Shenzhen Hospital from March 1, 2023 to May 31, 2024. 426 HUA patients and 1437 normouricemia (NUA) patients were collected and completed clinical and biochemical measurements. Spearman correlation, logistic regression, multiple linear regression, and subgroup analysis were used to verify the relationship between HUA and MetS components (including obesity, hypertension, hyperglycemia, and dyslipidemia). A nomogram and ROC curve were established to identify predictors of HUA risk.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Result<\/jats:title>\n                    <jats:p>The prevalence of HUA was 22.86%. Spearman analysis showed that BMI (r = 0.322) and TG (r = 0.304) had moderate positive correlations with SUA; sex [female%] exhibited a moderate inverse correlation (r = \u20130.444). HDL-C (r = \u20130.218) and eGFR (r = \u20130.283) showed weak inverse correlations. N-MID (r = \u20130.049) and P1NP (r = \u20130.063) showed negligible correlations with SUA, despite statistical significance. Binary logistic regression identified female sex, HbA1c, and eGFR as factors associated with lower HUA risk, while BMI, DBP, TG, and 25(OH)D were associated with increased risk. ROC analysis demonstrated moderate predictive value for BMI (AUC = 0.647), DBP (AUC = 0.602), and 25(OH)D (AUC = 0.578) (all P &amp;lt; 0.001). TG showed an AUC of 0.650 but was not statistically significant (P = 0.502). eGFR (AUC = 0.364) and HbA1c (AUC = 0.489) performed worse than random chance. Multiple linear regression revealed weak positive associations of SUA with BMI (\u03b2 = 0.211) and TG (\u03b2 = 0.151), weak inverse associations with HbA1c (\u03b2 = \u20130.153) and HDL-C (\u03b2 = \u20130.160), and a negligible association with 25(OH)D (\u03b2 = 0.055). Subgroup analysis indicated higher HUA risk in males and those with metabolic abnormalities.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This exploratory study identifies moderate predictive value of BMI, DBP, and 25(OH)D for HUA in Chinese T2DM patients, and a substantially lower risk in females. TG was not an independent predictor. Associations with bone markers and 25(OH)D were negligible. These findings highlight modest interconnections between HUA and metabolic dysregulation, particularly obesity.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fendo.2026.1697721","type":"journal-article","created":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T05:37:31Z","timestamp":1773207451000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Study on the correlation between hyperuricemia and components of metabolic syndrome in T2DM in China: a single-center, observational study"],"prefix":"10.3389","volume":"17","author":[{"given":"Xiao-fen","family":"Lian","sequence":"first","affiliation":[{"name":"Department of Endocrinology, Peking University Shenzhen Hospital","place":["Shenzhen, Guangdong, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jia-yu","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Endocrinology, Peking University Shenzhen 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