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

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-derived 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- 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. Plasma from humans with acute ischemic stroke within 24 hours or control patients with cardiovascular risk factors was drawn and frozen. Extracellular vesicles (EVs) were isolated from 250 ul of frozen plasma and subjected to co-immunoprecipitation with L1CAM. L1CAM- EVs were lysed and small RNA isolated (Paris mirvana kit, invitrogen) and sequenced on DNBSeq pipeline (BGI Americas). Reads were aligned with human genome (v38) and small RNA counts generated by the MANATEE pipeline(Handzlik et al. 2020). Data were analyzed with respect to clinical annotations including diagnosis, sex, clinical severity, and comorbidities.