Perng Wei, Hivert Marie-France, Michelotti Gregory, Oken Emily, Dabelea Dana
Lifcourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.
Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.
Metabolites. 2022 Apr 29;12(5):404. doi: 10.3390/metabo12050404.
Here, we seek to identify metabolite predictors of dysglycemia in youth. In the discovery analysis among 391 youth in the Exploring Perinatal Outcomes among CHildren (EPOCH) cohort, we used reduced rank regression (RRR) to identify sex-specific metabolite predictors of impaired fasting glucose (IFG) and elevated fasting glucose (EFG: Q4 vs. Q1 fasting glucose) 6 years later and compared the predictive capacity of four models: Model 1: ethnicity, parental diabetes, in utero exposure to diabetes, and body mass index (BMI); Model 2: Model 1 covariates + baseline waist circumference, insulin, lipids, and Tanner stage; Model 3: Model 2 + baseline fasting glucose; Model 4: Model 3 + baseline metabolite concentrations. RRR identified 19 metabolite predictors of fasting glucose in boys and 14 metabolite predictors in girls. Most compounds were on lipid, amino acid, and carbohydrate metabolism pathways. In boys, no improvement in aurea under the receiver operating characteristics curve AUC occurred until the inclusion of metabolites in Model 4, which increased the AUC for prediction of IFG (7.1%) from 0.81 to 0.97 ( = 0.002). In girls, %IFG was too low for regression analysis (3.1%), but we found similar results for EFG. We replicated the results among 265 youth in the Project Viva cohort, focusing on EFG due to low %IFG, suggesting that the metabolite profiles identified herein have the potential to improve the prediction of glycemia in youth.
在此，我们旨在确定青少年血糖异常的代谢物预测指标。在“儿童围产期结局探索（EPOCH）队列”中对391名青少年进行的发现分析中，我们使用降秩回归（RRR）来确定6年后空腹血糖受损（IFG）和空腹血糖升高（EFG：空腹血糖四分位数Q4与Q1相比）的性别特异性代谢物预测指标，并比较了四个模型的预测能力：模型1：种族、父母糖尿病史、子宫内糖尿病暴露情况和体重指数（BMI）；模型2：模型1的协变量+基线腰围、胰岛素、血脂和坦纳分期；模型3：模型2+基线空腹血糖；模型4：模型3+基线代谢物浓度。RRR确定了男孩中有19种空腹血糖的代谢物预测指标，女孩中有14种。大多数化合物涉及脂质、氨基酸和碳水化合物代谢途径。在男孩中，直到模型4纳入代谢物后，受试者工作特征曲线下面积（AUC）才有改善，这使得IFG预测的AUC从0.81增加到0.97（增加了7.1%，P = 0.002）。在女孩中，IFG发生率过低无法进行回归分析（3.1%），但我们在EFG方面发现了类似结果。我们在“生命项目（Project Viva）队列”的265名青少年中重复了这些结果，由于IFG发生率低，重点关注EFG，这表明本文确定的代谢物谱有潜力改善青少年血糖水平的预测。
