Altered expression of circular RNA in patients with cervical artery dissection

Cervical artery dissection (CeAD), a special cerebrovascular disease and the main cause of stroke in young people, can present with ischemic stroke, headache, subarachnoid hemorrhage, and other symptoms, increasing the possibility of misdiagnosis. As a special class of non-coding RNAs, circRNAs are commonly found in organisms and can play regulatory roles in transcription and post-transcription processes, affecting gene expression.CircRNAs have reported to be associated with neurological diseases; however, their role in CeAD has not been discerned. In this study, we aimed to elucidate the pathophysiological changes in patients with CeAD and identify biomarkers. Peripheral blood mononuclear cells from patients with CeAD and healthy controls were sequenced using high-throughput sequencing. We detected 460 differently \ expressed circRNAs in patients with CeAD (p < 0.5, fold difference = 2), of which 240 were upregulated and 220 were downregulated. Four circRNAs showed significant differences in expression, which were validated using qRT-PCR. These results suggested that three circRNAs were consistent with high-throughput sequencing results. Bioinformatics analysis demonstrated that these differentially expressed circRNAs were involved in protein metabolism, regulation, synapses, and other pathophysiological processes during CeAD-induced stroke. Additionally, various pathways related to inflammation were closely associated with circRNAs. Based on our results, we suggest that the aberrant expression of circRNAs in CeAD may serve as a biomarker for its diagnosis and as a potential therapeutic target. Overall design: Peripheral blood mononuclear cells from patients with CeAD and healthy controls were sequenced using high-throughput sequencing. We performed qRT-PCR to detect circRNA expression levels using the SYBR Green qPCR SuperMix and the 7500 Sequence Detection System (Applied Biosystems). GO functional annotations and KEGG pathway enrichment analyses were performed using the clusterProfiler package in the Bioconductor/KOBAS 3.0.