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抵抗素与脂联素比值联合尿酸在评估2型糖尿病患者代谢综合征中的作用

The role of resistin and adiponectin ratios with uric acid in assessing metabolic syndrome in type 2 diabetes.

作者信息

Fajkić Almir, Lepara Orhan, Jahić Rijad, Ejubović Malik, Kurtović Avdo, Džidić-Krivić Amina, Ejubović Amira Jagodić, Hadžović-Džuvo Almira, Sher Emina Karahmet

机构信息

Department of Pathophysiology, Faculty of Medicine, University of Sarajevo, 71000, Sarajevo, Bosnia and Herzegovina.

International Society of Engineering Science and Technology, Nottingham, UK.

出版信息

Mol Cell Biochem. 2025 Jun;480(6):3683-3694. doi: 10.1007/s11010-024-05200-z. Epub 2025 Jan 7.

Abstract

Metabolic syndrome (MetS) is a growing global healthcare burden. Patients with type 2 diabetes mellitus (T2DM) are more likely to acquire MetS than the general population. Recent research suggests that the interaction of adipose tissue products, such as adiponectin resistin and uric acid, is essential in MetS onset. To examine the role of resistin and adiponectin ratios with uric acid in predicting MetS onset T2DM patients. In a two-year prospective study, 72 T2DM patients were categorised into MetS and non-MetS, according to MetS development. The levels of resistin, adiponectin, uric acid (UA), fasting glucose, high-density lipoprotein cholesterol, and triglycerides were analysed from serum samples. ROC curves and their corresponding areas under the curve (AUC) were utilised to establish the best cut-off values of biomarkers for distinguishing MetS patients and non-MetS patients. The logistic regression analysis was performed to predict the onset of MetS in patients with T2DM. T2DM patients with and without MetS showed significant differences in resistin/UA (p = 0.017), adiponectin/UA (p < 0.001) and adiponectin levels. The Resistin/UA ROC Curve yielded an AUC of 0.825 (p < 0.001), 86.7% sensitivity and 76.2% specificity at a cut-off point of 0.99. Multivariable logistic regression analysis identified resistin /UA ratio [OR 8.631 95% CI 0.450-165.42; p = 0.001] and adiponectin/UA ratio [OR 0.022 95% CI 0.003-0.188; p < 0.001] as independent predictors of MetS. This study confirms the role of resistin-uric acid and adiponectin-uric acid ratios as predictors of MetS development in T2DM patients.

摘要

代谢综合征(MetS)是一个日益加重的全球医疗负担。2型糖尿病(T2DM)患者比普通人群更易患代谢综合征。近期研究表明,脂联素、抵抗素和尿酸等脂肪组织产物之间的相互作用在代谢综合征的发病过程中至关重要。为了研究抵抗素和脂联素与尿酸的比值在预测T2DM患者代谢综合征发病中的作用。在一项为期两年的前瞻性研究中,根据代谢综合征的发展情况,将72例T2DM患者分为代谢综合征组和非代谢综合征组。从血清样本中分析抵抗素、脂联素、尿酸(UA)、空腹血糖、高密度脂蛋白胆固醇和甘油三酯的水平。利用受试者工作特征曲线(ROC曲线)及其相应的曲线下面积(AUC)来确定区分代谢综合征患者和非代谢综合征患者的生物标志物的最佳临界值。进行逻辑回归分析以预测T2DM患者代谢综合征的发病情况。患有和未患有代谢综合征的T2DM患者在抵抗素/尿酸(p = 0.017)、脂联素/尿酸(p < 0.001)和脂联素水平上存在显著差异。抵抗素/尿酸ROC曲线的AUC为0.825(p < 0.001),在临界值为0.99时,敏感性为86.7%,特异性为76.2%。多变量逻辑回归分析确定抵抗素/尿酸比值[比值比(OR)8.631,95%置信区间(CI)0.450 - 165.42;p = 0.001]和脂联素/尿酸比值[OR 0.022,95% CI 0.003 - 0.188;p < 0.001]是代谢综合征的独立预测因素。本研究证实了抵抗素 - 尿酸和脂联素 - 尿酸比值在预测T2DM患者代谢综合征发展中的作用。

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