Sidorov Evgeny V, Bejar Cynthia, Xu Chao, Ray Bappaditya, Gordon David, Chainakul Juliane, Sanghera Dharambir K
Department of Neurology, University of Oklahoma Health Sciences Center (OUHSC), 920 S.L.Young Blvd #2040, Oklahoma City, OK, 73014, USA.
Oklahoma Center for Neuroscience, OUHSC, Oklahoma City, OK, USA.
Transl Stroke Res. 2021 Oct;12(5):778-784. doi: 10.1007/s12975-020-00876-z. Epub 2020 Nov 19.
Metabolomics may identify biomarkers for acute ischemic stroke (AIS). Previously, circulating metabolites were compared in AIS and healthy controls without accounting for stroke size. The goal of this study was to identify metabolites that associate with the volume of AIS. We prospectively analyzed 1554 serum metabolites in the acute (72 h) and chronic (3-6 months) stages of 60 ischemic stroke patients. We calculated infarct volume using diffusion-weighted images with MR segmentation software and associated the volume with stage-specific metabolites, acute-to-chronic stage changes, and multiple mixed regression in metabolite concentrations using multivariate regression analysis. We used the two-stage Benjamini and Hochberg (TSBH) procedure for multiple testing. Four unknown metabolites at the acute stage significantly associated with infarct volume: X24541, X24577, X24581, and X2482 (all p < 0.01). Nine metabolites at the chronic stage are significantly associated with infarct volume: indolpropinate, alpha ketoglutaramate, picolinate, X16087, X24637, X24576, X24577, X24582, X24581 (all p < 0.048). Infarct volume is also associated with significant changes in serum concentrations of twenty-seven metabolites, with p values from 0.01 to 1.48 × 10, and on five metabolites using mixed regression model. This prospective pilot study identified several metabolites associated with the volume of ischemic infarction. Confirmation of these findings on a larger dataset would help characterize putative pathways underlying the size of ischemic infarction and facilitate the identification of biomarkers or therapeutic targets.
代谢组学可能识别出急性缺血性中风(AIS)的生物标志物。此前,在未考虑中风大小的情况下,对AIS患者和健康对照者的循环代谢物进行了比较。本研究的目的是识别与AIS体积相关的代谢物。我们对60例缺血性中风患者在急性期(72小时)和慢性期(3 - 6个月)的1554种血清代谢物进行了前瞻性分析。我们使用磁共振分割软件通过扩散加权图像计算梗死体积,并将该体积与特定阶段的代谢物、急性期到慢性期的变化以及使用多变量回归分析的代谢物浓度的多重混合回归相关联。我们使用两阶段的Benjamini和Hochberg(TSBH)程序进行多重检验。急性期有四种未知代谢物与梗死体积显著相关:X24541、X24577、X24581和X2482(所有p < 0.01)。慢性期有九种代谢物与梗死体积显著相关:吲哚丙酸、α - 酮戊二酸、吡啶甲酸、X16087、X24637、X24576、X24577、X24582、X24581(所有p < 0.048)。梗死体积还与27种代谢物血清浓度的显著变化相关,p值从0.01到1.48×10,以及使用混合回归模型的五种代谢物相关。这项前瞻性初步研究确定了几种与缺血性梗死体积相关的代谢物。在更大的数据集中对这些发现进行验证将有助于描绘缺血性梗死大小潜在的假定途径,并有助于识别生物标志物或治疗靶点。