Data Lab, Clarity Healthcare Intelligence, Jundiaí, SP, Brazil.
Cardiology Division, Faculty of Medical Sciences, State University of Campinas (Unicamp), Campinas, SP, Brazil.
Diabetologia. 2021 Feb;64(2):385-396. doi: 10.1007/s00125-020-05322-1. Epub 2020 Nov 7.
AIMS/HYPOTHESIS: Type 2 diabetes prevention requires the accurate identification of those at high risk. Beyond the association of fasting serum triacylglycerols with diabetes, triacylglycerol-enriched remnant lipoproteins (TRLs) more accurately reflect pathophysiological changes that underlie progression to diabetes, such as hepatic insulin resistance, pancreatic steatosis and systemic inflammation. We hypothesised that TRL-related factors could improve risk prediction for incident diabetes.
We included individuals from the Brazilian Longitudinal Study of Adult Health cohort. We trained a logistic regression model for the risk of incident diabetes in 80% of the cohort using tenfold cross-validation, and tested the model in the remaining 20% of the cohort (test set). Variables included medical history and traits of the metabolic syndrome, followed by TRL-related measurements (plasma concentration, TRL particle diameter, cholesterol and triacylglycerol content). TRL features were measured using NMR spectroscopy. Discrimination was assessed using the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC).
Among 4463 at-risk individuals, there were 366 new cases of diabetes after a mean (±SD) of 3.7 (±0.63) years of follow-up. We derived an 18-variable model with a global AUROC of 0.846 (95% CI: 0.829, 0.869). Overall TRL-related markers were not associated with diabetes. However, TRL particle diameter increased the AUROC, particularly in individuals with HbA <39 mmol/mol (5.7%) (hold-out test set [n = 659]; training-validation set [n = 2638]), but not in individuals with baseline HbA 39-46 mmol/mol (5.7-6.4%) (hold-out test set [n = 233]; training-validation set [n = 933]). In the subgroup with baseline HbA <39 mmol/mol (5.7%), AUROC in the test set increased from 0.717 (95% CI 0.603, 0.818) to 0.794 (95% CI 0.731, 0.862), and AUPRC in the test set rose from 0.582 to 0.701 when using the baseline model and the baseline model plus TRL particle diameter, respectively. TRL particle diameter was highly correlated with obesity, insulin resistance and inflammation in those with impaired fasting glucose at baseline, but less so in those with HbA <39 mmol/mol (5.7%).
CONCLUSIONS/INTERPRETATION: TRL particle diameter improves the prediction of diabetes, but only in individuals with HbA <39 mmol/mol (5.7%) at baseline. These data support TRL particle diameter as a risk factor that is changed early in the course of the pathophysiological processes that lead to the development of type 2 diabetes, even before glucose abnormalities are established. Graphical abstract.
目的/假设:2 型糖尿病的预防需要准确识别高危人群。除了空腹血清三酰甘油与糖尿病有关外,富含三酰甘油的残粒脂蛋白(TRL)更能准确反映导致糖尿病进展的病理生理变化,如肝胰岛素抵抗、胰腺脂肪变性和全身炎症。我们假设 TRL 相关因素可以改善对糖尿病发病的风险预测。
我们纳入了巴西成年人健康纵向研究队列中的个体。我们使用十折交叉验证,在队列的 80%中训练用于预测新发糖尿病风险的逻辑回归模型,并在队列的其余 20%(测试集)中测试该模型。变量包括病史和代谢综合征特征,然后是 TRL 相关测量值(血浆浓度、TRL 颗粒直径、胆固醇和三酰甘油含量)。使用 NMR 光谱法测量 TRL 特征。使用接收者操作特征曲线下的面积(AUROC)和精度-召回曲线下的面积(AUPRC)评估判别能力。
在 4463 名高危人群中,在平均(±SD)3.7(±0.63)年的随访后,有 366 人发生新的糖尿病病例。我们得出了一个包含 18 个变量的模型,其总体 AUROC 为 0.846(95%CI:0.829,0.869)。总体而言,TRL 相关标志物与糖尿病无关。然而,TRL 颗粒直径增加了 AUROC,特别是在 HbA<39mmol/mol(5.7%)的个体中(预留测试集[n=659];训练-验证集[n=2638]),但在基线 HbA 39-46mmol/mol(5.7-6.4%)的个体中(预留测试集[n=233];训练-验证集[n=933])则不然。在基线 HbA<39mmol/mol(5.7%)的亚组中,测试集的 AUROC 从 0.717(95%CI 0.603,0.818)增加到 0.794(95%CI 0.731,0.862),测试集的 AUPRC 从 0.582 上升到 0.701,分别使用基线模型和基线模型加 TRL 颗粒直径。在基线时存在空腹血糖受损的个体中,TRL 颗粒直径与肥胖、胰岛素抵抗和炎症高度相关,但在 HbA<39mmol/mol(5.7%)的个体中相关性较低。
结论/解释:TRL 颗粒直径可改善糖尿病的预测,但仅在基线时 HbA<39mmol/mol(5.7%)的个体中如此。这些数据支持 TRL 颗粒直径作为风险因素,即使在葡萄糖异常尚未确定之前,它也可以在导致 2 型糖尿病发生的病理生理过程早期发生变化。