Identification of three potential novel biomarkers for early diagnosis of acute ischemic stroke via plasma lipidomics,Metabolomics

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Identification of three potential novel biomarkers for early diagnosis of acute ischemic stroke via plasma lipidomics
Metabolomics ( IF 3.5 ) Pub Date : 2023-03-30 , DOI: 10.1007/s11306-023-01990-3
Yi Yu ₁ , Xue Wen ₂ , Jin-Guang Lin ₂ , Jun Liu ₂ , Hong-Feng Liang ₂ , Shan-Wen Lin ₂ , Qiu-Gui Xu ₂ , Ji-Cheng Li _{2,

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Affiliation

Introduction

Acute ischemic stroke (AIS) accounts for the majority of all stroke, globally the second leading cause of death. Due to its rapid development after onset, its early diagnosis is crucial.

Objectives

We aim to identify potential highly reliable blood-based biomarkers for early diagnosis of AIS using quantitative plasma lipid profiling via a machine learning approach.

Methods

Lipidomics was used for quantitative plasma lipid profiling, based on ultra-performance liquid chromatography tandem mass spectrometry. Our samples were divided into a discovery and a validation set, each containing 30 AIS patients and 30 health controls (HC). Differentially expressed lipid metabolites were screened based on the criteria VIP > 1, p < 0.05, and fold change > 1.5 or < 0.67. The least absolute shrinkage and selection operator (LASSO) and random forest algorithms in machine learning were used to select differential lipid metabolites as potential biomarkers.

Results

Three key differential lipid metabolites, CarnitineC10:1, CarnitineC10:1-OH and Cer(d18:0/16:0), were identified as potential biomarkers for early diagnosis of AIS. The former two, associated with thermogenesis, were down-regulated, whereas the latter, associated with necroptosis and sphingolipd metabolism, was upregulated. Univariate and multivariate logistic regressions showed that these three lipid metabolites and the resulting diagnostic model exhibited a strong ability in discriminating between AIS patients and HCs in both the discovery and validation sets, with an area under the curve above 0.9.

Conclusions

Our work provides valuable information on the pathophysiology of AIS and constitutes an important step toward clinical application of blood-based biomarkers for diagnosing AIS.

中文翻译：

通过血浆脂质组学鉴定三种用于早期诊断急性缺血性中风的潜在新型生物标志物

介绍

急性缺血性中风 (AIS) 占所有中风的大部分，是全球第二大死亡原因。由于发病后发展迅速，早期诊断至关重要。

目标

我们的目标是通过机器学习方法使用定量血浆脂质分析来识别潜在的高度可靠的血液生物标志物，用于 AIS 的早期诊断。

方法

基于超高效液相色谱串联质谱法，脂质组学用于定量血浆脂质分析。我们的样本分为发现集和验证集，每个包含 30 名 AIS 患者和 30 名健康对照 (HC)。根据 VIP > 1、p < 0.05 和倍数变化 > 1.5 或 < 0.67 的标准筛选差异表达的脂质代谢物。使用机器学习中的最小绝对收缩和选择算子 (LASSO) 和随机森林算法来选择差异脂质代谢物作为潜在的生物标志物。

结果

三种关键的差异脂质代谢物 CarnitineC10:1、CarnitineC10:1-OH 和 Cer(d18:0/16:0) 被确定为 AIS 早期诊断的潜在生物标志物。前两者与产热相关，被下调，而后者与坏死性凋亡和鞘脂代谢相关，被上调。单变量和多变量逻辑回归表明，这三种脂质代谢物和由此产生的诊断模型在发现和验证集中均表现出很强的区分 AIS 患者和 HC 的能力，曲线下面积均高于 0.9。