ArticleJournal of inherited metabolic disease2025
Exploring a Circulating miRNA Signature for PMM2-CDG: Initial Insights Toward Diagnosis, Stratification, and Monitoring.
Article in Journal of inherited metabolic disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Reimagining paediatric care: technology, trust, and the global movement for child-centred innovation.Frontiers in medicine · 2026Review
- Exploring a Circulating miRNA Signature for PMM2-CDG: Initial Insights Toward Diagnosis, Stratification, and Monitoring.Journal of inherited metabolic disease · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.