Abstract
Circulating miRNAs have potential as minimally invasive biomarkers for diagnosing various diseases, including ageing-related disorders such as Alzheimer's disease (AD). However, the lack of standardization in the common analysis method, RT-qPCR, and specifically in the normalization step, has resulted in inconsistent data across studies, hindering miRNA clinical implementation as well as basic research. To address this issue, this study proposes an optimized protocol for key steps in miRNA profiling, which incorporates absorbance-based haemolysis detection for assessing sample quality, double spike-in controls for miRNA isolation and reverse transcription, and the use of 7 stable normalizers verified in an aging population, including healthy subjects and individuals at different stages of Alzheimer's disease (140 subjects). The stability of these 7 normalizers was demonstrated using our novel method called BestmiRNorm for identifying optimal normalizers. BestmiRNorm, developed utilizing the Python programming language, enables the assessment of up to 11 potential normalizers. The standardized application of this optimized RT-qPCR protocol and the recommended normalizers are crucial for the development of miRNAs as biomarkers for AD and other ageing-related diseases in clinical diagnostics and basic research.