Non-coding RNAs as prognostic biomarkers in autoimmune disease.

Area of Science:

• Immunology
• Genomics
• Molecular Biology

Background:

• Autoimmune diseases involve immune system malfunction attacking self-tissues, leading to tissue damage.
• Current diagnostic tools lack sensitivity and specificity for predicting disease severity or therapy response.
• Non-coding RNAs (ncRNAs) are emerging as key regulators and potential biomarkers in autoimmune pathology.

Purpose of the Study:

• To review the prognostic value of ncRNAs in autoimmune diseases.
• To highlight the potential of ncRNAs in predicting clinical outcomes like disease severity and organ damage.
• To explore the mechanisms and clinical applications of ncRNAs as biomarkers.

Main Methods:

• Literature review synthesizing current evidence on ncRNA prognostic value.
• Analysis of multi-omics data (genomic, transcriptomic, epigenetic) for novel biomarker discovery.
• Exploration of machine-learning-driven analyses for developing prognostic signatures.

Main Results:

• ncRNAs demonstrate potential in predicting disease severity, organ-specific damage, and flare likelihood.
• Specific ncRNAs influence key pathogenic processes in autoimmune diseases.
• ncRNAs show promise as stable biomarkers in liquid biopsies for clinical applications.

Conclusions:

• ncRNAs hold significant prognostic value for autoimmune diseases.
• Advanced molecular markers, including ncRNAs, are crucial for improving diagnosis and prognosis.
• Future research should integrate multi-omics and machine learning in large-scale studies for robust biomarker development.