Dino Ferrari Centre, Neuroscience Section, Department of Pathophysiology and Transplantation (DEPT), University of Milan, Via Francesco Sforza 35, 20122 Milan, Italy.
Stroke Unit, Neurology Unit, Neuroscience and Mental Health Department, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy.
Int J Mol Sci. 2023 Feb 8;24(4):3419. doi: 10.3390/ijms24043419.
Cerebrovascular diseases represent a leading cause of disability, morbidity, and death worldwide. In the last decade, the advances in endovascular procedures have not only improved acute ischemic stroke care but also conceded a thorough analysis of patients' thrombi. Although early anatomopathological and immunohistochemical analyses have provided valuable insights into thrombus composition and its correlation with radiological features, response to reperfusion therapies, and stroke etiology, these results have been inconclusive so far. Recent studies applied single- or multi-omic approaches-such as proteomics, metabolomics, transcriptomics, or a combination of these-to investigate clot composition and stroke mechanisms, showing high predictive power. Particularly, one pilot studies showed that combined deep phenotyping of stroke thrombi may be superior to classic clinical predictors in defining stroke mechanisms. Small sample sizes, varying methodologies, and lack of adjustments for potential confounders still represent roadblocks to generalizing these findings. However, these techniques hold the potential to better investigate stroke-related thrombogenesis and select secondary prevention strategies, and to prompt the discovery of novel biomarkers and therapeutic targets. In this review, we summarize the most recent findings, overview current strengths and limitations, and present future perspectives in the field.
脑血管疾病是全球范围内导致残疾、发病和死亡的主要原因。在过去的十年中，血管内治疗技术的进步不仅改善了急性缺血性脑卒中的治疗，而且还可以对患者的血栓进行全面分析。尽管早期的解剖病理学和免疫组织化学分析为血栓成分及其与影像学特征、再灌注治疗反应和卒中病因的相关性提供了有价值的见解，但到目前为止，这些结果尚无定论。最近的研究应用了单一或多组学方法，如蛋白质组学、代谢组学、转录组学或这些方法的组合，来研究血栓成分和卒中机制，显示出较高的预测能力。特别是，一项初步研究表明，对卒中血栓进行联合深度表型分析可能优于经典的临床预测因子来确定卒中机制。样本量小、方法多样以及缺乏对潜在混杂因素的调整仍然是推广这些发现的障碍。然而，这些技术有可能更好地研究与卒中相关的血栓形成，并选择二级预防策略，并促使发现新的生物标志物和治疗靶点。在这篇综述中，我们总结了最新的发现，概述了当前的优势和局限性，并提出了该领域的未来展望。
