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MicroRNAs expressed in depression and their associated pathways: A systematic review and a bioinformatics analysis

Camila Perelló Ferrúa, Roberta Giorgi, Laísa Camerini da Rosa

    Journal of Chemical Neuroanatomy
    |May 25, 2019
    PubMed

    Insights

    This review identifies microRNAs (miRNAs) altered in depression. It highlights specific miRNAs and pathways involved, advancing understanding of depression

    Area of Science:

    • Neuroscience
    • Genetics
    • Molecular Biology

    Background:

    • Depression is a widespread mental illness with complex biological underpinnings.
    • MicroRNAs (miRNAs) are increasingly recognized as key regulators in various biological processes, including neurological disorders.
    • Understanding the role of miRNAs in depression is crucial for developing novel therapeutic strategies.

    Purpose of the Study:

    • To systematically review and identify microRNAs (miRNAs) associated with depression.
    • To analyze the biological pathways linked to dysregulated miRNAs in depressed individuals.
    • To create a comprehensive panel of altered miRNAs and their related pathways in depression.

    Main Methods:

    • Systematic literature search across major scientific databases (PubMed, Scopus, PsycINFO, etc.).
    • Inclusion of studies investigating microRNAs in relation to depression.
    • Bioinformatic analysis of up-regulated and down-regulated miRNAs and their associated pathways.

    Main Results:

    • Out of 77 cited miRNAs, 54 showed altered levels in depressed individuals.
    • 30 miRNAs were up-regulated and 24 were down-regulated in depression.
    • miR-17-5p and let-7a-5p were frequently identified in statistically significant pathways.

    Conclusions:

    • A significant number of microRNAs are dysregulated in depression, pointing to their involvement in the disease.
    • Bioinformatic analysis revealed distinct pathways associated with up- and down-regulated miRNAs.
    • This study provides a curated panel of altered miRNAs and pathways, contributing to a deeper understanding of miRNA networks in depression.
    Keywords:
    BioinformaticDepressive disorderSignaling pathwaySystematic reviewmicroRNAs

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