Advanced serum lipoprotein and glycoprotein profiling for cardiovascular event prediction in type 2 diabetes mellitus: the LIPOCAT study.

IF 8.5 1区医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS

Cardiovascular Diabetology Pub Date : 2025-02-21 DOI:10.1186/s12933-025-02636-5

Núria Amigó, Esmeralda Castelblanco, Josep Julve, Neus Martínez-Micaelo, Núria Alonso, Marta Hernández, Josep Ribalta, Montse Guardiola, Pere Torán-Monserrat, Victor Lopez-Lifante, Cecilia Herrero-Alonso, Ingrid Arteaga, Emilio Ortega, Josep Franch-Nadal, Didac Mauricio

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引用次数: 0

Abstract

Background: Traditional risk factors cannot accurately predict cardiovascular events (CVE) in type 2 diabetes (T2D). The LIPOCAT study aimed to prospectively evaluate the clinical utility of advanced lipoprotein characteristics and glycoproteins to predict future cardiovascular events (CVE) in a large cohort of subjects with type 2 diabetes mellitus (T2D).

Methods: From four different Spanish prospective cohorts, a total of 933 T2D subjects were selected to form the LIPOCAT study. Advanced 1H-Nuclear Magnetic Resonance (1H-NMR) analysis included lipoprotein (Liposcale®) and glycoprotein (Glycoscale) profiling. Random forest classification models and Area Under the Receiver Operating Characteristics (AUROC) analysis were used to assess the differential contribution of advanced variables in predicting CVE. Validation was performed using an external cohort.

Results: Out of 933 T2D subjects, 104 reported a CVE during follow-up. Analysis of Liposcale®/Glycoscale uncovered elevations in the circulating VLDL-cholesterol(C), remnant IDL-triglycerides (TG) and LDL-TG in subjects with CVE, along with glycoproteins (Glyc) A and B. Moreover, the incorporation of advanced Liposcale® variables to a base model constructed with traditional risk factors significantly improved the prediction of CVE, as evidenced by 1.5-fold increase in the C statistic (AUROC), reaching AUROC values of 0.756. In the independent validation cohort, similar improvements in AUROC values were observed by adding the advanced variables to the traditional models.

Conclusions: Advanced 1H-NMR analysis revealed previously hidden lipoprotein and glycoprotein characteristics associated with CVE in T2D subjects.

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背景：传统的风险因素无法准确预测2型糖尿病（T2D）患者的心血管事件（CVE）。LIPOCAT 研究旨在前瞻性地评估高级脂蛋白特征和糖蛋白对预测大型 2 型糖尿病（T2D）患者未来心血管事件（CVE）的临床效用：方法：从西班牙四个不同的前瞻性队列中，共筛选出 933 名 2 型糖尿病受试者组成 LIPOCAT 研究。先进的 1H 核磁共振（1H-NMR）分析包括脂蛋白（Liposcale®）和糖蛋白（Glycoscale）分析。随机森林分类模型和接收者操作特征下面积（AUROC）分析用于评估高级变量对预测CVE的不同贡献。结果：结果：在933名T2D受试者中，有104人在随访期间报告了CVE。Liposcale®/Glycoscale分析发现，CVE受试者的循环VLDL-胆固醇（C）、残余IDL-甘油三酯（TG）和LDL-TG以及糖蛋白（Glyc）A和B均升高。此外，在使用传统风险因素构建的基础模型中加入高级 Liposcale® 变量后，C 统计量（AUROC）增加了 1.5 倍，AUROC 值达到了 0.756，从而显著提高了 CVE 的预测能力。在独立验证队列中，通过在传统模型中添加高级变量，AUROC值也得到了类似的改善：结论：高级 1H-NMR 分析揭示了与 T2D 受试者 CVE 相关的先前隐藏的脂蛋白和糖蛋白特征。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cardiovascular Diabetology 医学-内分泌学与代谢

CiteScore

12.30

自引率

15.10%

发文量

240

审稿时长

1 months

期刊介绍： Cardiovascular Diabetology is a journal that welcomes manuscripts exploring various aspects of the relationship between diabetes, cardiovascular health, and the metabolic syndrome. We invite submissions related to clinical studies, genetic investigations, experimental research, pharmacological studies, epidemiological analyses, and molecular biology research in this field.