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冠心病合并 2 型糖尿病患者的血浆脂质组指纹图谱:CORDIOPREV 研究。

Plasma lipidic fingerprint associated with type 2 diabetes in patients with coronary heart disease: CORDIOPREV study.

机构信息

Lipids and Atherosclerosis Unit, Department of Internal Medicine, Reina Sofia University Hospital, University of Cordoba, Cordoba, Spain.

Department of Medical and Surgical Sciences, University of Cordoba, Cordoba, Spain.

出版信息

Cardiovasc Diabetol. 2023 Aug 3;22(1):199. doi: 10.1186/s12933-023-01933-1.

Abstract

OBJECTIVE

We aimed to identify a lipidic profile associated with type 2 diabetes mellitus (T2DM) development in coronary heart disease (CHD) patients, to provide a new, highly sensitive model which could be used in clinical practice to identify patients at T2DM risk.

METHODS

This study considered the 462 patients of the CORDIOPREV study (CHD patients) who were not diabetic at the beginning of the intervention. In total, 107 of them developed T2DM after a median follow-up of 60 months. They were diagnosed using the American Diabetes Association criteria. A novel lipidomic methodology employing liquid chromatography (LC) separation followed by HESI, and detection by mass spectrometry (MS) was used to annotate the lipids at the isomer level. The patients were then classified into a Training and a Validation Set (60-40). Next, a Random Survival Forest (RSF) was carried out to detect the lipidic isomers with the lowest prediction error, these lipids were then used to build a Lipidomic Risk (LR) score which was evaluated through a Cox. Finally, a production model combining the clinical variables of interest, and the lipidic species was carried out.

RESULTS

LC-tandem MS annotated 440 lipid species. From those, the RSF identified 15 lipid species with the lowest prediction error. These lipids were combined in an LR score which showed association with the development of T2DM. The LR hazard ratio per unit standard deviation was 2.87 and 1.43, in the Training and Validation Set respectively. Likewise, patients with higher LR Score values had lower insulin sensitivity (P = 0.006) and higher liver insulin resistance (P = 0.005). The receiver operating characteristic (ROC) curve obtained by combining clinical variables and the selected lipidic isomers using a generalised lineal model had an area under the curve (AUC) of 81.3%.

CONCLUSION

Our study showed the potential of comprehensive lipidomic analysis in identifying patients at risk of developing T2DM. In addition, the lipid species combined with clinical variables provided a new, highly sensitive model which can be used in clinical practice to identify patients at T2DM risk. Moreover, these results also indicate that we need to look closely at isomers to understand the role of this specific compound in T2DM development. Trials registration NCT00924937.

摘要

目的

本研究旨在确定与冠心病(CHD)患者 2 型糖尿病(T2DM)发展相关的脂质谱,为临床实践中识别 T2DM 高危患者提供一种新的、高度敏感的模型。

方法

本研究纳入了 CORDIOPREV 研究中的 462 例 CHD 患者(研究开始时无糖尿病),这些患者在中位随访 60 个月后,有 107 例发展为 T2DM。采用美国糖尿病协会标准进行诊断。采用液相色谱(LC)分离、电喷雾(ESI)、质谱(MS)检测的新型脂质组学方法对异构体水平的脂质进行注释。随后,将患者分为训练集和验证集(60-40)。接着,采用随机生存森林(RSF)检测预测误差最低的脂质异构体,将这些脂质用于构建脂质风险(LR)评分,并通过 Cox 分析进行评估。最后,构建了一个结合临床变量和脂质特征的生产模型。

结果

LC-MS/MS 注释了 440 种脂质。其中,RSF 确定了 15 种预测误差最低的脂质异构体。将这些脂质组成一个 LR 评分,与 T2DM 的发生相关。LR 每单位标准差的风险比在训练集和验证集分别为 2.87 和 1.43。同样,LR 评分较高的患者胰岛素敏感性较低(P=0.006),肝脏胰岛素抵抗较高(P=0.005)。采用广义线性模型结合临床变量和选定的脂质异构体的受试者工作特征(ROC)曲线的曲线下面积(AUC)为 81.3%。

结论

本研究表明综合脂质组学分析在识别 T2DM 高危患者方面具有潜力。此外,将脂质特征与临床变量相结合,提供了一种新的、高度敏感的模型,可用于临床实践中识别 T2DM 高危患者。此外,这些结果还表明,我们需要仔细研究异构体,以了解该特定化合物在 T2DM 发展中的作用。

试验注册

NCT00924937。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cfb/10401778/57efba6055d5/12933_2023_1933_Fig1_HTML.jpg

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