Abstract
Circulating microRNAs (miRNAs) have been reported as biomarkers for disease diagnosis. RT-qPCR is most commonly used to detect miRNAs; however, no consensus on the most appropriate method for data normalization exists. Via a standardized selection method, we aimed to determine separate miRNA normalization panels for RT-qPCR measurements on whole blood, platelets, and serum. Candidate miRNAs were selected from studies describing circulating miRNA microarray data in the Gene Expression Omnibus or ArrayExpress. miRNA expression data of healthy controls were retrieved from each study. For each sample type, we selected those miRNAs that were least variable and sufficiently highly expressed in multiple microarray experiments, performed on at least 2 different platforms. Stability of the candidate miRNAs was assessed using NormFinder and geNorm algorithms in a RT-qPCR cohort of 10 patients with coronary artery disease and 10 healthy controls. We selected miRNA normalization panels for RT-qPCR measurements on whole blood, platelets, and serum. As a validation, we assessed the precision of all 3 panels in 3 independent RT-qPCR cohorts and compared this with normalization for miR-16 or RNU6B. The proposed normalization panels for whole blood, platelets, and serum show better precision than normalization for miR-16 or RNU6B.
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