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| Página principal > Artículos > Artículos publicados > Exploring a circulating miRNA signature for PMM2-CDG: Initial insights toward diagnosis, stratification, and monitoring |
(Flomics Biotech) (Institut Català de Paleontologia Miquel Crusafont) (Institut de Recerca Sant Joan de Déu)
| Fecha: | 2025 |
| Resumen: | Phosphomannomutase deficiency (PMM2-CDG) is the most common congenital disorder of glycosylation, characterized by variable early-onset neurological (hypotonia, cerebellar syndrome, developmental delay) and multi-organ manifestations. Although several clinical trials are ongoing, current biomarkers lack prognostic or monitoring utility. Emerging transcriptomic studies suggest dysregulated pathways in PMM2-CDG, but miRNAs, key gene expression regulators, remain unexplored. This cross-sectional study aims to investigate a circulating miRNA signature that may distinguish PMM2-CDG patients from unaffected controls, providing an initial framework for future studies on potential predictive and monitoring tools. Differential gene expression analysis was used to identify significant differentially expressed (DE) miRNAs, while machine learning models (LASSO, XGBoost) were applied to create an miRNA predictive signature. Dysregulated miRNA pathways analysis provided insights into affected tissues and cellular mechanisms. An optimized protocol addressing challenges in pediatric blood samples was implemented. miRNA profiles from blood samples of 28 PMM2-CDG patients and 67 unaffected controls were analyzed, identifying six DE miRNAs. Regarding machine learning models, XGBoost achieved the best performance (AUC 0. 917). Biological analysis revealed that DE miRNAs influence neurological, endocrinological, immunological, and cellular pathways related to the PMM2-CDG phenotype. Notably, miR-122-5p emerged as a highly predictive marker, indicating liver and neurological involvement. Circulating miRNAs represent a promising, minimally invasive avenue for further investigation. While preliminary evidence of their potential diagnostic utility is provided, additional validation in larger and more diverse populations is required to determine their relevance for clinical stratification or monitoring in PMM2-CDG, contributing to future biomarker-driven personalized medicine efforts in this disease. |
| Ayudas: | Ministerio de Economía y Competitividad PI14/00021 Instituto de Salud Carlos III PI21/00068 Instituto de Salud Carlos III FI22/00218 Agencia Estatal de Investigación CEX2020-001049-S Generalitat de Catalunya SLT008/18/00194 Agència de Gestió d'Ajuts Universitaris i de Recerca 2019/DI-091 |
| Derechos: | Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.  |
| Lengua: | Anglès |
| Documento: | Article ; recerca ; Versió publicada |
| Materia: | Biomarkers ; Machine learning ; Mirna ; Pathway dysregulation ; PMM2-CDG ; Transcriptomic |
| Publicado en: | Journal of Inherited Metabolic Disease, Vol. 48, Issue 6 (November 2025) , art. e70104, ISSN 1573-2665 |
