Bingjin Zhang1, Lingling Xing2, Beibei Wang3. 1. Department of Paediatrics, Shengli Oilfield Central Hospital, Dongying, China. 2. Department of Paediatrics, Dongying District People's Hospital, Dongying, China. 3. Department of Endocrinology, Shengli Oilfield Central Hospital, Dongying, China.
Abstract
INTRODUCTION: Obesity is a major risk factor for metabolic disorders in children. Therefore, it is particularly important to study the abnormal regulation of circulating miR-24-3p in obese children and its predictive value for metabolic syndrome. METHODS: Serum samples were obtained from children with obesity (n = 45), obese children with metabolic syndrome (n = 52), and healthy controls (n = 50). The expression levels of miR-24-3p were detected by reverse transcription quantitative PCR. The ROC curve was used to evaluate the diagnostic value of miR-24-3p. Pearson's correlation analysis was performed to evaluate the relationship between serum miR-24-3p and different clinical parameters. Logistic regression analysis was used to evaluate the relationship between miR-24-3p and obesity with metabolic syndrome in children. RESULTS: The expression of miR-24-3p was the highest in obese children with metabolic syndrome. ROC results showed that miR-24-3p had the ability to distinguish healthy individuals from obese children (area under the curve [AUC] = 0.951) and can predict the occurrence of metabolic syndrome for obese children (AUC = 0.890). The expression level of miR-24-3p was positively correlated with body mass index (r = 0.817, p < 0.001), fasting blood glucose (r = 0.798, p < 0.001), triglycerides (r = 0.773, p < 0.001), systolic blood pressure (r = 0.746, p < 0.001), and diastolic blood pressure (r = 0.623, p < 0.001), respectively. Logistic regression analysis showed that miR-24-3p was an independent influence factor for the occurrence of metabolic syndrome in obese children. DISCUSSION/ CONCLUSION: MiR-24-3p is a potential noninvasive marker for children with obesity and has predictive value for the occurrence of metabolic syndrome.
INTRODUCTION: Obesity is a major risk factor for metabolic disorders in children. Therefore, it is particularly important to study the abnormal regulation of circulating miR-24-3p in obese children and its predictive value for metabolic syndrome. METHODS: Serum samples were obtained from children with obesity (n = 45), obese children with metabolic syndrome (n = 52), and healthy controls (n = 50). The expression levels of miR-24-3p were detected by reverse transcription quantitative PCR. The ROC curve was used to evaluate the diagnostic value of miR-24-3p. Pearson's correlation analysis was performed to evaluate the relationship between serum miR-24-3p and different clinical parameters. Logistic regression analysis was used to evaluate the relationship between miR-24-3p and obesity with metabolic syndrome in children. RESULTS: The expression of miR-24-3p was the highest in obese children with metabolic syndrome. ROC results showed that miR-24-3p had the ability to distinguish healthy individuals from obese children (area under the curve [AUC] = 0.951) and can predict the occurrence of metabolic syndrome for obese children (AUC = 0.890). The expression level of miR-24-3p was positively correlated with body mass index (r = 0.817, p < 0.001), fasting blood glucose (r = 0.798, p < 0.001), triglycerides (r = 0.773, p < 0.001), systolic blood pressure (r = 0.746, p < 0.001), and diastolic blood pressure (r = 0.623, p < 0.001), respectively. Logistic regression analysis showed that miR-24-3p was an independent influence factor for the occurrence of metabolic syndrome in obese children. DISCUSSION/ CONCLUSION: MiR-24-3p is a potential noninvasive marker for children with obesity and has predictive value for the occurrence of metabolic syndrome.
Authors: Silvia Garavelli; Sara Bruzzaniti; Elena Tagliabue; Dario Di Silvestre; Francesco Prattichizzo; Enza Mozzillo; Valentina Fattorusso; Lucia La Sala; Antonio Ceriello; Annibale A Puca; Pierluigi Mauri; Rocky Strollo; Marco Marigliano; Claudio Maffeis; Alessandra Petrelli; Emanuele Bosi; Adriana Franzese; Mario Galgani; Giuseppe Matarese; Paola de Candia Journal: Diabetologia Date: 2020-07-29 Impact factor: 10.122