Brain AVMs-Related microRNAs: Machine Learning Algorithm for Expression Profiles of Target Genes

Area of Science:

• Biochemistry and Molecular Biology
• Genetics and Genomics
• Vascular Biology

Background:

• MicroRNAs (miRNAs) are key regulators of gene expression with critical roles in disease.
• Emerging evidence highlights the involvement of miRNAs in the development and progression of brain arteriovenous malformations (bAVMs).
• Understanding miRNA signatures in bAVMs is essential for clinical management.

Purpose of the Study:

• To investigate miRNA expression profiles associated with bAVMs.
• To identify potential diagnostic and prognostic biomarkers for bAVMs.
• To explore the therapeutic implications of miRNAs in bAVM treatment.

Main Methods:

• A PRISMA-based literature review was conducted using PubMed/Medline.
• Search terms included "brain arteriovenous malformations", "cerebral arteriovenous malformations", "microRNA", and "miRNA".
• Bioinformatic analyses utilized miRWalk, miRTarBase, and KEGG database.

Main Results:

• Decreased miR-18a in bAVM endothelial cells correlates with increased VEGF and growth signals.
• Downregulation of miR-137 and miR-195* in VSMCs may promote inflammation and angiogenesis.
• Overexpression of specific miRNAs (miR-7-5p, miR-629-5p, etc.) in peripheral blood is linked to endothelial proliferation and nidus development.
• Machine learning confirmed miRNA networks' association with vascular remodeling and bAVM progression.

Conclusions:

• miRNA expression is critical for regulating post-transcriptional signals in bAVMs.
• Identified miRNA signatures may serve as novel prognostic and diagnostic tools.
• Further research into bAVM miRNA signatures could lead to targeted molecular therapies.