miRNAs in cerebrospinal fluid associated with Alzheimer's disease: A systematic review and pathway analysis using a data mining and machine learning approach.

Autor: Pereira JD; Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil., Teixeira LCR; Faculdade de Farmácia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil., Mamede I; Intituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil., Alves MT; HEMOMINAS, Belo Horizonte, Minas Gerais, Brazil., Caramelli P; Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil., Luizon MR; Intituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil., Veloso AA; Instituto de Ciências Exatas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil., Gomes KB; Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.; Faculdade de Farmácia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
Jazyk: angličtina
Zdroj: Journal of neurochemistry [J Neurochem] 2024 Jun; Vol. 168 (6), pp. 977-994. Date of Electronic Publication: 2024 Feb 23.
DOI: 10.1111/jnc.16060
Abstrakt: Alzheimer's disease (AD) is the most common type and accounts for 60%-70% of the reported cases of dementia. MicroRNAs (miRNAs) are small non-coding RNAs that play a crucial role in gene expression regulation. Although the diagnosis of AD is primarily clinical, several miRNAs have been associated with AD and considered as potential markers for diagnosis and progression of AD. We sought to match AD-related miRNAs in cerebrospinal fluid (CSF) found in the GeoDataSets, evaluated by machine learning, with miRNAs listed in a systematic review, and a pathway analysis. Using machine learning approaches, we identified most differentially expressed miRNAs in Gene Expression Omnibus (GEO), which were validated by the systematic review, using the acronym PECO-Population (P): Patients with AD, Exposure (E): expression of miRNAs, Comparison (C): Healthy individuals, and Objective (O): miRNAs differentially expressed in CSF. Additionally, pathway enrichment analysis was performed to identify the main pathways involving at least four miRNAs selected. Four miRNAs were identified for differentiating between patients with and without AD in machine learning combined to systematic review, and followed the pathways analysis: miRNA-30a-3p, miRNA-193a-5p, miRNA-143-3p, miRNA-145-5p. The pathways epidermal growth factor, MAPK, TGF-beta and ATM-dependent DNA damage response, were regulated by these miRNAs, but only the MAPK pathway presented higher relevance after a randomic pathway analysis. These findings have the potential to assist in the development of diagnostic tests for AD using miRNAs as biomarkers, as well as provide understanding of the relationship between different pathophysiological mechanisms of AD.
(© 2024 International Society for Neurochemistry.)
Databáze: MEDLINE
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