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L1CAM 阳性细胞外囊泡中急性缺血性脑卒中的小 RNA 特征。

Small RNA signatures of acute ischemic stroke in L1CAM positive extracellular vesicles.

机构信息

Department of Neurology, University of Texas Health Science Center, Houston, TX, 77030, USA.

Department of Neurology, University of California-San Francisco, San Francisco, CA, 94158, USA.

出版信息

Sci Rep. 2024 Jun 12;14(1):13560. doi: 10.1038/s41598-024-63633-4.

DOI:10.1038/s41598-024-63633-4
PMID:38866905
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11169361/
Abstract

L1CAM-positive extracellular vesicles (L1EV) are an emerging biomarker that may better reflect ongoing neuronal damage than other blood-based biomarkers. The physiological roles and regulation of L1EVs and their small RNA cargoes following stroke is unknown. We sought to characterize L1EV small RNAs following stroke and assess L1EV RNA signatures for diagnosing stroke using weighted gene co-expression network analysis and random forest (RF) machine learning algorithms. Interestingly, small RNA sequencing of plasma L1EVs from patients with stroke and control patients (n = 28) identified micro(mi)RNAs known to be enriched in the brain. Weighted gene co-expression network analysis (WGCNA) revealed small RNA transcript modules correlated to diagnosis, initial NIH stroke scale, and age. L1EV RNA signatures associated with the diagnosis of AIS were derived from WGCNA and RF classification. These small RNA signatures demonstrated a high degree of accuracy in the diagnosis of AIS with an area under the curve (AUC) of the signatures ranging from 0.833 to 0.932. Further work is necessary to understand the role of small RNA L1EV cargoes in the response to brain injury, however, this study supports the utility of L1EV small RNA signatures as a biomarker of stroke.

摘要

L1CAM 阳性细胞外囊泡 (L1EV) 是一种新兴的生物标志物,它可能比其他基于血液的生物标志物更好地反映持续的神经元损伤。L1EV 及其小 RNA 货物在中风后的生理作用和调节尚不清楚。我们试图描述中风后 L1EV 的小 RNA,并使用加权基因共表达网络分析和随机森林 (RF) 机器学习算法评估 L1EV RNA 特征用于诊断中风。有趣的是,对来自中风患者和对照患者(n=28)的血浆 L1EV 的小 RNA 测序确定了已知在大脑中富集的 micro(mi)RNA。加权基因共表达网络分析 (WGCNA) 显示与诊断、初始 NIH 中风量表和年龄相关的小 RNA 转录模块。与 AIS 诊断相关的 L1EV RNA 特征来自 WGCNA 和 RF 分类。这些小 RNA 特征在 AIS 的诊断中具有很高的准确性,其曲线下面积 (AUC) 范围从 0.833 到 0.932。进一步的工作需要了解小 RNA L1EV 货物在脑损伤反应中的作用,然而,这项研究支持 L1EV 小 RNA 特征作为中风生物标志物的效用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/212c/11169361/ba66e9e7f953/41598_2024_63633_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/212c/11169361/4e88701c2011/41598_2024_63633_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/212c/11169361/81d4a42e0885/41598_2024_63633_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/212c/11169361/ba66e9e7f953/41598_2024_63633_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/212c/11169361/4e88701c2011/41598_2024_63633_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/212c/11169361/81d4a42e0885/41598_2024_63633_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/212c/11169361/ba66e9e7f953/41598_2024_63633_Fig3_HTML.jpg

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