Literature DB >> 33629272

Profiling of Serum Exosome MiRNA Reveals the Potential of a MiRNA Panel as Diagnostic Biomarker for Alzheimer's Disease.

Zhiwu Dong1, Hongjun Gu2, Qiang Guo3, Shuang Liang4, Jian Xue2, Feng Yao2, Xianglu Liu4, Feifei Li4, Huiling Liu4, Li Sun4, Kewen Zhao5.   

Abstract

Alzheimer's disease (AD) is the most common neurodegenerative disease in the older adults. Although much effort has been made in the analyses of diagnostic biomarkers, such as amyloid-β, tau, and neurofilament light chain, identifying peripheral blood-based biomarkers is in extremely urgent need for their minimal invasiveness and more convenience. Here we characterized the miRNA profile by RNA sequencing in human serum exosomes from AD patients and healthy controls (HC) to investigate its potential for AD diagnosis. Subsequently, Gene Ontology analysis and pathway analysis were performed for the targeted genes from the differentially expressed miRNAs. These basic functions were differentially enriched, including cell adhesion, regulation of transcription, and the ubiquitin system. Functional network analysis highlighted the pathways of proteoglycans in cancer, viral carcinogenesis, signaling pathways regulating pluripotency of stem cells, and cellular senescence in AD. A total of 24 miRNAs showed significantly differential expression between AD and HC with more than ± 2.0-fold change at p value < 0.05 and at least 50 reads for each sample. Logistic regression analysis established a model for AD prediction by serum exosomal miR-30b-5p, miR-22-3p, and miR-378a-3p. Sequencing results were validated using quantitative reverse transcription PCR. The data showed that miR-30b-5p, miR-22-3p, and miR-378a-3p were significantly deregulated in AD, with area under the curve (AUC) of 0.668, 0.637, and 0.718, respectively. The combination of the three miRs gained a better diagnostic capability with AUC of 0.880. This finding revealed a miR panel as potential biomarker in the peripheral blood to distinguish AD from HC.

Entities:  

Keywords:  Alzheimer’s disease; Gene Ontology analysis; MicroRNA; Pathway analysis; RNA sequencing

Mesh:

Substances:

Year:  2021        PMID: 33629272     DOI: 10.1007/s12035-021-02323-y

Source DB:  PubMed          Journal:  Mol Neurobiol        ISSN: 0893-7648            Impact factor:   5.590


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