Canon Stroke and Vascular Research Center, University at Buffalo, 875 Ellicott Street, Buffalo, NY, 14203, USA.
Department of Pathology and Anatomical Sciences, University at Buffalo, Buffalo, NY, USA.
Mol Diagn Ther. 2024 Jul;28(4):469-477. doi: 10.1007/s40291-024-00716-y. Epub 2024 May 20.
Transcriptomic profiling has emerged as a powerful tool for exploring the molecular landscape of ischemic stroke clots and providing insights into the pathophysiological mechanisms underlying stroke progression and recovery. In this study, we aimed to investigate the relationship between stroke clot transcriptomes and stroke thrombectomy outcome, as measured by early neurological improvement (ENI) 30 (i.e., a 30% reduction in NIHSS at 24 h post-thrombectomy).
We hypothesized that there exist distinct clot gene expression patterns between good and poor neurological outcomes.
Transcriptomic analysis of 32 stroke clots retrieved by mechanical thrombectomy was conducted. Transcriptome data of these clots were analyzed to identify differentially expressed genes (DEGs), defined as those with a log(fold-change) ≥ 1.5 and q < 0.05 between samples with good and poor early neurological outcomes. Gene ontology and bioinformatics analyses were performed on genes with p < 0.01 to identify enriched biological processes and Ingenuity Pathway Analysis canonical pathways. Moreover, AUC analysis assessed the predictive power of DEGs for 90-day function outcome (mRS ≤ 2) and cellular composition of clot was predicted using CIBERSORT. We also assessed whether differential enrichment of immune cell types could indicate patient survival.
A total of 41 DEGs were identified. Bioinformatics showed that enriched biological processes and pathways emphasized the chronic immune response and matrix metalloproteinase inhibition. Moreover, 25 of the DEGs were found to be significant predictors of 90-day mRS. These genes were indicative of monocytes enrichment and neutrophil depletion in patients with poorer outcomes.
Our study revealed a distinct gene expression pattern and dysregulated biological pathways associated with ENI. This expression pattern was also predictive of long-term outcome, suggesting a biological link between those ENIs and 90-day mRS.
转录组谱分析已成为探索缺血性中风血栓分子特征的强大工具，并为中风进展和恢复的病理生理机制提供了深入了解。在这项研究中，我们旨在研究中风血栓转录组与中风血栓切除术结果之间的关系，结果通过早期神经改善（ENI）30 来衡量（即，血栓切除术后 24 小时 NIHSS 降低 30%）。
我们假设在良好和不良神经结局之间存在明显的血栓基因表达模式。
对通过机械血栓切除术获取的 32 个中风血栓进行了转录组分析。对这些血栓的转录组数据进行分析，以确定差异表达基因（DEG），定义为在具有良好和不良早期神经结局的样本之间，对数（倍数变化）≥1.5 和 q < 0.05 的基因。对具有 p < 0.01 的基因进行基因本体论和生物信息学分析，以确定丰富的生物学过程和 Ingenuity 通路分析的经典途径。此外，AUC 分析评估了 DEG 对 90 天功能结局（mRS≤2）的预测能力，使用 CIBERSORT 预测血栓的细胞成分。我们还评估了免疫细胞类型的差异富集是否可以指示患者的生存。
共鉴定出 41 个 DEG。生物信息学显示，丰富的生物学过程和途径强调了慢性免疫反应和基质金属蛋白酶抑制。此外，25 个 DEG 被发现是 90 天 mRS 的显著预测因子。这些基因表明预后较差的患者中单核细胞富集和中性粒细胞耗竭。
我们的研究揭示了与 ENI 相关的独特基因表达模式和失调的生物学途径。这种表达模式也可预测长期结局，表明那些 ENIs 与 90 天 mRS 之间存在生物学联系。
