Exploring a Circulating miRNA Signature for PMM2-CDG: Initial Insights Toward Diagnosis, Stratification, and...

Area of Science:

• Biochemistry
• Genetics
• Molecular Biology

Background:

• Phosphomannomutase deficiency (PMM2-CDG) is the most common congenital disorder of glycosylation, presenting with diverse neurological and multi-organ symptoms.
• Current biomarkers for PMM2-CDG lack prognostic and monitoring capabilities, highlighting the need for novel diagnostic tools.
• MicroRNAs (miRNAs), regulators of gene expression, have not been explored in PMM2-CDG.

Purpose of the Study:

• To identify a circulating miRNA signature capable of differentiating PMM2-CDG patients from healthy individuals.
• To establish a preliminary miRNA-based predictive model for PMM2-CDG.
• To explore the biological pathways influenced by dysregulated miRNAs in PMM2-CDG.

Main Methods:

• Differential gene expression analysis to identify significant differentially expressed (DE) miRNAs in PMM2-CDG patients.
• Machine learning models (LASSO, XGBoost) were employed to construct a predictive miRNA signature.
• Analysis of miRNA pathway enrichment to understand affected biological processes and tissues.

Main Results:

• Six DE miRNAs were identified between 28 PMM2-CDG patients and 67 controls.
• The XGBoost model demonstrated high performance (AUC 0.917) in predicting PMM2-CDG.
• DE miRNAs were found to impact neurological, endocrinological, immunological, and cellular pathways relevant to PMM2-CDG, with miR-122-5p showing particular promise.

Conclusions:

• Circulating miRNAs present a promising, minimally invasive biomarker candidate for PMM2-CDG.
• The identified miRNA signature shows potential for diagnostic utility and warrants further validation in larger cohorts.
• This research lays the groundwork for future biomarker-driven personalized medicine approaches in PMM2-CDG.