Normalization methods for RT‐qPCR assessment of circulating microRNAs in Alzheimer’s and other aging‐related diseases

Abstract

AbstractBackgroundCirculating miRNAs in blood plasma present significant potential for use as minimally‐invasive biomarkers for diagnosis of aging‐related diseases, such as cancer or Alzheimer’s disease (AD). The most sensitive and inexpensive analysis method of circulating miRNA is RT‐qPCR. However, lack of RT‐qPCR standardisation is one of the major causes of data inconsistency across different studies and it hinders progress towards widespread implementation of miRNA biomarkers in clinical use. Normalisation of RT‐qPCR data to stably expressed miRNAs is a key step in data analysis. Current methods of identifying optimal normalisers are lacking in their evaluation of the stability of normalisers and their combinations in aging populations. To address these needs, we created a novel, transparent, method for selecting optimal normalisers in aging populations, using the Python programming language (v. 3.7.3).MethodOur method uses the Python packages: pandas (v. 1.2.3), numpy (v. 1.17.1), scipy (v. 1.3.1). The method uses three measures to evaluate the miRNA Cq values for potential normalisers: Kolmogorov‐Smirnov score (KS‐score), average displacement from a mean of zero and mean standard deviation. In each case, the comparators are two distinct biological groups of interest (such as AD and cognitively normal controls). Before comparison, the group of potential normalisers were normalised according to the log2(2−ΔΔCq) method. The miRNA data were collected from Polish subjects including 44 AD patients and 70 similar‐aged, cognitively normal, controls). Circulating miRNA molecules were isolated from plasma, followed by RT‐qPCR with a selection of 7 miRNAs tested as potential normalisers, along with suitable controls for mRNA isolation and reverse transcription.ResultWe provide a novel method for identification of optimal normalisers with the advantages of: assessments of a greater number of combined potential normalisers (7 in this study), transparency of decision making and the ability for end users to weight that decision making according to their judgment of relative importance.ConclusionWe recommend assessment of plasma miRNA levels in an aging population employing a novel set of normalisers.Work supported by the Polish National Science Centre grant OPUS 2018/29/B/NZ7/02757and by the EU Horizon2020 FETOPEN grant no 737390 (ArrestAD).