Evidence map›Paper›PMID 42038754›Full record

ArticleMolecular syndromology2026

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

Harun Bayrak, Parisa Sharafi, Mustafa Kılıç

Abstract read
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Article in Molecular syndromology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Harun BayrakDepartment of Molecular Medicine, Graduate School of Health Sciences, TOBB University of Economics and Technology, Ankara, Turkey.
Parisa SharafiDepartment of Medical Biology and Genetics, Faculty of Medicine, TOBB University of Economics and Technology, Ankara, Turkey.
Mustafa KılıçDepartment of Pediatric Metabolic Diseases, University of Health Sciences, Ankara Etlik City Hospital, Ankara, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 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 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.

Indexed as

Amino acidBioinformaticsInborn errors of amino acid metabolismmiRNAPathway analysisRNA

Identifiers

PMID42038754
PMCPMC13105711

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