Frontiers in Neuroscience (Sep 2020)

A Panel of Exosome-Derived miRNAs of Cerebrospinal Fluid for the Diagnosis of Moyamoya Disease

  • Gang Wang,
  • Yunyu Wen,
  • Oluwasijibomi Damola Faleti,
  • Qingshun Zhao,
  • Jingping Liu,
  • Guozhong Zhang,
  • Mingzhou Li,
  • Songtao Qi,
  • Wenfeng Feng,
  • Xiaoming Lyu

DOI
https://doi.org/10.3389/fnins.2020.548278
Journal volume & issue
Vol. 14

Abstract

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BackgroundMoyamoya disease (MMD) is an important cause of stroke in children and young adults in Asia. To date, diagnosis remains challenging due to varying clinical manifestations and unknown pathogenesis. The study aims to identify cerebrospinal fluid (CSF) exosomal microRNAs (exomiRs) that can serve as a novel diagnostic biomarker for diagnosis and assess its clinical applications.MethodsCSF samples were taken from 31 MMD patients and 31 healthy controls. Initial screening of miRNA expression was performed on samples pooled from MMD patients and controls using microarray and validated using quantitative reverse transcription polymerase chain reaction (qRT-PCR). The diagnostic accuracy of the potential exosomal miRNAs was evaluated using receiver operating characteristic curve analyses in an independent patient cohort. The potential pathways regulated by the miRNAs was also determined using bioinformatics analysis.ResultsThe microarray results demonstrated that six exomiRs were dysregulated in the MMD patients compared to the controls. Using qRT-PCR, we validated four of the miRNAs (miR-3679-5p, miR-6165, miR-6760-5p, and miR-574-5p) as a biomarker for MMD diagnosis. The four exomiRs showed enhanced sensitivity (75%) and specificity (93.75%) in terms of differentiating MMD patients from healthy subjects [area under the curve (AUC) = 0.9453]. Pathway enrichment analysis for potential targets of six exomiRs identified proteins involved in cell adhesion and junction formation in the brain.ConclusionsWe identified a novel and highly sensitive exomiRs signature for MMD detection and explored its potential targets using bioinformatics analysis.

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