Wang Wenbin, Liu Lin, Qiu Weida, Chen Chaolei, Huang Yuqing, Cai Anping, Nie Zhiqiang, Ou Yanqiu, Zhu Yicheng, Feng Yingqing
Department of Cardiology, Hypertension Research Laboratory, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, People's Republic of China.
Department of Medicine, The University of Hong Kong, Hong Kong, China.
Risk Manag Healthc Policy. 2024 Jul 30;17:1889-1901. doi: 10.2147/RMHP.S465135. eCollection 2024.
Traditional clinical risk factors are insufficient to estimate the residual risk of large-vessel ischemic stroke. Non-targeted lipidomic techniques provide an opportunity to evaluate these risks.
Plasma samples were collected from 113 hypertensive individuals, including 55 individuals at high risk of ischemic stroke and 58 matched individuals, in a prospective nested case-control cohort. To identify dysregulated lipid metabolites, we conducted multivariate and univariate analyses. A classifier based on a cross-validated procedure was employed to select the optimal combination of lipid species and their ratios.
We identified 23 dysregulated lipid species in patients with and without ischemic stroke, including 16 (69.6%) up-regulated and 7 (30.4%) down-regulated lipid species. Through internal cross-validation, the optimal combination of two lipid features (phosphatidylcholine 34:2 and triglyceride 18:1/18:1/22:1 / phosphatidylcholine 34:2, referred to as ischemic stroke-related 2 lipid features - IS2LP) was selected, leading to a more precise prediction probability for ischemic stroke within 3.9 years. In the comparison of different risk factors, the traditional risk score, the IS2LP risk score, and the combination of the traditional risk score with IS2LP yield AUC values of 0.613(95% CI:0.509-0.717), 0.833(95% CI:0.755-0.911), and 0.843(95% CI:0.777-0.916), respectively. The combination of the traditional risk score and IS2LP exhibited significantly improved discriminative performance, with an integrated discrimination improvement (IDI) of 0.31 (<0.001) and a continuous net reclassification improvement (NRI) of 1.06 ( < 0.001) compared to the traditional risk score.
We identified new lipidomic biomarkers associated with the futural event of large-vessel ischemic stroke. These lipid species could serve as potential blood biomarkers for assessing the residual risk of ischemic stroke in hypertensive individuals.
传统临床风险因素不足以评估大血管缺血性卒中的残余风险。非靶向脂质组学技术为评估这些风险提供了契机。
在一项前瞻性巢式病例对照队列研究中，收集了113名高血压患者的血浆样本，其中包括55名缺血性卒中高危个体和58名匹配个体。为了识别失调的脂质代谢物，我们进行了多变量和单变量分析。采用基于交叉验证程序的分类器来选择脂质种类及其比例的最佳组合。
我们在有和没有缺血性卒中的患者中识别出23种失调的脂质种类，包括16种（69.6%）上调和7种（30.4%）下调的脂质种类。通过内部交叉验证，选择了两种脂质特征（磷脂酰胆碱34:2和甘油三酯18:1/18:1/22:1 /磷脂酰胆碱34:2，称为缺血性卒中相关2脂质特征-IS2LP）的最佳组合，从而对3.9年内的缺血性卒中产生更精确的预测概率。在不同风险因素的比较中，传统风险评分、IS2LP风险评分以及传统风险评分与IS2LP的组合产生的AUC值分别为0.613（95%CI：0.509 - 0.717）、0.833（95%CI：0.755 - 0.911）和0.843（95%CI：0.777 - 0.916）。与传统风险评分相比，传统风险评分与IS2LP的组合表现出显著改善的判别性能，综合判别改善（IDI）为0.31（<0.001），连续净重新分类改善（NRI）为1.06（<0.001）。
我们识别出与大血管缺血性卒中未来事件相关的新脂质组学生物标志物。这些脂质种类可作为潜在的血液生物标志物，用于评估高血压个体缺血性卒中的残余风险。
