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揭示1型糖尿病中的隐匿性动脉粥样硬化:糖蛋白和脂蛋白脂质组学以及心脏自主神经病变的作用

Unveiling Silent Atherosclerosis in Type 1 Diabetes: The Role of Glycoprotein and Lipoprotein Lipidomics, and Cardiac Autonomic Neuropathy.

作者信息

de Lope Quiñones Sara, Luque-Ramírez Manuel, Michael Fernández Antonio Carlos, Quintero Tobar Alejandra, Quiñones-Silva Jhonatan, Martínez García María Ángeles, Insenser Nieto María, Dorado Avendaño Beatriz, Escobar-Morreale Héctor F, Nattero-Chávez Lía

机构信息

Diabetes, Obesity and Human Reproduction Research Group, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS) & Centro de Investigación Biomédica en Red Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Universidad de Alcalá, 28034 Madrid, Spain.

Department of Endocrinology and Nutrition, Hospital Universitario Ramón y Cajal, 28034 Madrid, Spain.

出版信息

Metabolites. 2025 Jan 16;15(1):55. doi: 10.3390/metabo15010055.

Abstract

This study aimed to evaluate whether glycoprotein and lipoprotein lipidomics profiles could enhance a clinical predictive model for carotid subclinical atherosclerosis in patients with type 1 diabetes (T1D). Additionally, we assessed the influence of cardiac autonomic neuropathy (CAN) on these predictive models. We conducted a cross-sectional study including 256 patients with T1D. Serum glycoprotein and lipoprotein lipidomics profiles were determined using H-NMR spectroscopy. Subclinical atherosclerosis was defined as carotid intima-media thickness (cIMT) ≥ 1.5 mm. CAN was identified using the Clarke score. Predictive models were built and their performance evaluated using receiver operating characteristic curves and cross-validation. Subclinical atherosclerosis was detected in 32% of participants. Patients with both CAN and atherosclerosis were older, had a longer duration of diabetes, and were more likely to present with bilateral carotid disease. Clinical predictors such as age, duration of diabetes, and smoking status remained the strongest determinants of subclinical atherosclerosis [AUC = 0.88 (95%CI: 0.84-0.93)]. While glycoprotein and lipoprotein lipidomics profiles were associated with atherosclerosis, their inclusion in the clinical model did not significantly improve its diagnostic performance. Stratification by the presence of CAN revealed no impact on the model's ability to predict subclinical atherosclerosis, underscoring its robustness across different risk subgroups. In a cohort of patients with T1D, subclinical atherosclerosis was strongly associated with traditional clinical risk factors. Advanced glycoprotein and lipoprotein lipidomics profiling, although associated with atherosclerosis, did not enhance the diagnostic accuracy of predictive models beyond clinical variables. The predictive model remained effective even in the presence of CAN, highlighting its reliability as a screening tool for identifying patients at risk of subclinical atherosclerosis.

摘要

本研究旨在评估糖蛋白和脂蛋白脂质组学谱是否能增强1型糖尿病(T1D)患者颈动脉亚临床动脉粥样硬化的临床预测模型。此外,我们评估了心脏自主神经病变(CAN)对这些预测模型的影响。我们进行了一项横断面研究,纳入了256例T1D患者。使用H-NMR光谱法测定血清糖蛋白和脂蛋白脂质组学谱。亚临床动脉粥样硬化定义为颈动脉内膜中层厚度(cIMT)≥1.5mm。使用克拉克评分法识别CAN。构建预测模型,并使用受试者工作特征曲线和交叉验证评估其性能。32%的参与者检测到亚临床动脉粥样硬化。同时患有CAN和动脉粥样硬化的患者年龄更大,糖尿病病程更长,更有可能出现双侧颈动脉疾病。年龄、糖尿病病程和吸烟状况等临床预测因素仍然是亚临床动脉粥样硬化的最强决定因素[AUC = 0.88(95%CI:0.84-0.93)]。虽然糖蛋白和脂蛋白脂质组学谱与动脉粥样硬化有关,但将它们纳入临床模型并未显著提高其诊断性能。按是否存在CAN进行分层显示,对模型预测亚临床动脉粥样硬化的能力没有影响,强调了其在不同风险亚组中的稳健性。在一组T1D患者中,亚临床动脉粥样硬化与传统临床风险因素密切相关。先进的糖蛋白和脂蛋白脂质组学分析虽然与动脉粥样硬化有关,但并未提高预测模型的诊断准确性,超出临床变量。即使存在CAN,预测模型仍然有效,突出了其作为识别亚临床动脉粥样硬化风险患者的筛查工具的可靠性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd7f/11767205/0f27958239a5/metabolites-15-00055-g001.jpg

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