Almir Fajkić, Orhan Lepara, Rijad Jahić, Malik Ejubović, Avdo Kurtović, Amina Džidić-Krivić, Amira Jagodić Ejubović, Almira Hadžović-Džuvo, Emina Karahmet Sher
{"title":"抵抗素和脂联素比值与尿酸在评估2型糖尿病代谢综合征中的作用。","authors":"Almir Fajkić, Orhan Lepara, Rijad Jahić, Malik Ejubović, Avdo Kurtović, Amina Džidić-Krivić, Amira Jagodić Ejubović, Almira Hadžović-Džuvo, Emina Karahmet Sher","doi":"10.1007/s11010-024-05200-z","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":18724,"journal":{"name":"Molecular and Cellular Biochemistry","volume":" ","pages":"3683-3694"},"PeriodicalIF":3.5000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The role of resistin and adiponectin ratios with uric acid in assessing metabolic syndrome in type 2 diabetes.\",\"authors\":\"Almir Fajkić, Orhan Lepara, Rijad Jahić, Malik Ejubović, Avdo Kurtović, Amina Džidić-Krivić, Amira Jagodić Ejubović, Almira Hadžović-Džuvo, Emina Karahmet Sher\",\"doi\":\"10.1007/s11010-024-05200-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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. 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The role of resistin and adiponectin ratios with uric acid in assessing metabolic syndrome in type 2 diabetes.
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.
期刊介绍:
Molecular and Cellular Biochemistry: An International Journal for Chemical Biology in Health and Disease publishes original research papers and short communications in all areas of the biochemical sciences, emphasizing novel findings relevant to the biochemical basis of cellular function and disease processes, as well as the mechanics of action of hormones and chemical agents. Coverage includes membrane transport, receptor mechanism, immune response, secretory processes, and cytoskeletal function, as well as biochemical structure-function relationships in the cell.
In addition to the reports of original research, the journal publishes state of the art reviews. Specific subjects covered by Molecular and Cellular Biochemistry include cellular metabolism, cellular pathophysiology, enzymology, ion transport, lipid biochemistry, membrane biochemistry, molecular biology, nuclear structure and function, and protein chemistry.