Optimized RT-qPCR and a novel normalization method for validating circulating miRNA biomarkers in ageing-related...

Area of Science:

• Biomarkers
• Molecular Diagnostics
• Neurodegenerative Diseases

Background:

• Circulating microRNAs (miRNAs) show promise as minimally invasive biomarkers for diseases like Alzheimer's disease (AD).
• Current RT-qPCR methods lack standardization, particularly in normalization, leading to inconsistent and unreliable miRNA data.
• This inconsistency hinders the clinical application and basic research of miRNAs as diagnostic tools.

Purpose of the Study:

• To develop and validate an optimized RT-qPCR protocol for reliable circulating miRNA profiling.
• To identify and verify stable miRNA normalizers for use in aging populations and AD studies.
• To introduce BestmiRNorm, a novel Python-based method for selecting optimal miRNA normalizers.

Main Methods:

• Incorporated absorbance-based hemolysis detection for sample quality assessment.
• Utilized double spike-in controls for miRNA isolation and reverse transcription efficiency.
• Validated 7 stable normalizers in 140 subjects (healthy and AD at various stages) using the BestmiRNorm method.

Main Results:

• An optimized RT-qPCR protocol was established, addressing key steps in miRNA profiling.
• Seven stable normalizers were identified and validated for use in aging and AD cohorts.
• The BestmiRNorm method was developed in Python to assess normalizer stability.

Conclusions:

• Standardized RT-qPCR protocols and validated normalizers are essential for reliable miRNA biomarker development.
• This optimized approach and recommended normalizers will advance the use of miRNAs in clinical diagnostics for AD and other aging-related diseases.
• BestmiRNorm provides a robust tool for normalizer selection in miRNA research.