Li Shen, Cui Mengxuan, Liu Yingshu, Liu Xuhan, Luo Lan, Zhao Wei, Gu Xiaolan, Li Linfeng, Liu Chao, Bai Lan, Li Di, Liu Bo, Che Defei, Li Xinyu, Wang Yao, Gao Zhengnan
Department of Central Laboratory, Central Hospital of Dalian University of Technology, Dalian 116000, China.
Yidu Cloud Technology Inc, Beijing 100101, China.
J Clin Endocrinol Metab. 2024 Mar 15;109(4):1051-1059. doi: 10.1210/clinem/dgad643.
The components of metabolic syndrome (MetS) are interrelated and associated with renal complications in patients with type 2 diabetes (T2D).
We aimed to reveal prevalent metabolic profiles in patients with T2D and identify which metabolic profiles were risk markers for renal progression.
A total of 3556 participants with T2D from a hospital (derivation cohort) and 931 participants with T2D from a community survey (external validation cohort) were included. The primary outcome was the onset of diabetic kidney disease (DKD), and secondary outcomes included estimated glomerular filtration rate (eGFR) decline, macroalbuminuria, and end-stage renal disease (ESRD). In the derivation cohort, clusters were identified using the 5 components of MetS, and their relationships with the outcomes were assessed. To validate the findings, participants in the validation cohort were assigned to clusters. Multivariate odds ratios (ORs) of the primary outcome were evaluated in both cohorts, adjusted for multiple covariates at baseline.
In the derivation cohort, 6 clusters were identified as metabolic profiles. Compared with cluster 1, cluster 3 (severe hyperglycemia) had increased risks of DKD (hazard ratio [HR] [95% CI]: 1.72 [1.39-2.12]), macroalbuminuria (2.74 [1.84-4.08]), ESRD (4.31 [1.16-15.99]), and eGFR decline [P < .001]; cluster 4 (moderate dyslipidemia) had increased risks of DKD (1.97 [1.53-2.54]) and macroalbuminuria (2.62 [1.61-4.25]). In the validation cohort, clusters 3 and 4 were replicated to have significantly increased risks of DKD (adjusted ORs: 1.24 [1.07-1.44] and 1.39 [1.03-1.87]).
We identified 6 prevalent metabolic profiles in patients with T2D. Severe hyperglycemia and moderate dyslipidemia were validated as significant risk markers for DKD.
代谢综合征（MetS）的各组分相互关联，且与2型糖尿病（T2D）患者的肾脏并发症相关。
我们旨在揭示T2D患者中普遍存在的代谢特征，并确定哪些代谢特征是肾脏病变进展的风险标志物。
纳入了来自一家医院的3556例T2D患者（衍生队列）和来自一项社区调查的931例T2D患者（外部验证队列）。主要结局是糖尿病肾病（DKD）的发生，次要结局包括估计肾小球滤过率（eGFR）下降、大量蛋白尿和终末期肾病（ESRD）。在衍生队列中，使用MetS的5个组分确定聚类，并评估它们与结局的关系。为验证研究结果，将验证队列中的参与者分配到各个聚类中。在两个队列中评估主要结局的多变量比值比（OR），并在基线时对多个协变量进行调整。
在衍生队列中，6个聚类被确定为代谢特征。与聚类1相比，聚类3（严重高血糖）发生DKD的风险增加（风险比[HR][95%CI]：1.72[1.39 - 2.12]）、大量蛋白尿（2.74[1.84 - 4.08]）、ESRD（4.31[1.16 - 15.99]）和eGFR下降[P <.001]；聚类4（中度血脂异常）发生DKD（1.97[1.53 - 2.54]）和大量蛋白尿（2.62[1.61 - 4.25]）的风险增加。在验证队列中，聚类3和聚类4被再次证实发生DKD的风险显著增加（调整后的OR：1.24[1.07 - 1.44]和1.39[1.03 - 1.87]）。
我们在T2D患者中确定了6种普遍存在的代谢特征。严重高血糖和中度血脂异常被证实是DKD的重要风险标志物。
