A Systematic Bioinformatic Analysis of the miRNA Pathway in Inborn Errors of Amino Acid Metabolism Disorders

Introduction: Inborn errors of amino acid metabolism (IEAAM) are genetic defects that lead to the toxic accumulation of metabolites. While the genetic basis of these intoxication-type disorders is well-established, the regulatory role of microRNAs (miRNAs) in their pathogenesis remains poorly synthesized. This systematic bioinformatic analysis aims to identify and validate specific miRNA-gene interactions that modulate key metabolic pathways in IEAAM. Methods: A systematic literature search was conducted across PubMed and Scopus databases. We integrated identified miRNAs with metabolic genes using prediction tools (e.g., miRWalk, miRDB) and validated these interactions through functional pathway analysis using KEGG, DisGeNET, and PubChem database integration. Results: Our analysis identified a consistent network of miRNAs associated with amino acid metabolism. Specifically, six miRNAs (mmu-miR-409-5p, hsa-miR-3944-3p, rno-miR-125b-5p, hsa-miR-145-5p, hsa-miR-5195-3p, and hsa-miR-1202) were bioinformatically validated to target key genes such as FAH, DBT, CBS, PSAT1, and ARG1. These miRNAs are significantly enriched in metabolic pathways (KEGG) and associated with clinical phenotypes including epilepsy and intoxication-related metabolic crises. Conclusion: This computational study provides the first systematic evidence of a conserved miRNA-gene regulatory network in aminoacidopathies. By identifying these six key regulatory miRNAs, our findings offer novel insights into the epigenetic modulation of metabolic blocks and highlight potential targets for future miRNA-based therapeutic interventions in IEAAM.