title: Normalization panels for the reliable quantification of circulating microRNAs by RT-qPCR.
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.
authors.affiliation: *Department of Vascular Medicine, Department of Experimental Vascular Medicine, Department of Experimental Cardiology, and Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands; and Department of Plasma Proteins, Sanquin, Amsterdam, The Netherlands.
authors.forename: Maayke G M
authors.initials: MG
authors.lastname: Kok
authors.affiliation: *Department of Vascular Medicine, Department of Experimental Vascular Medicine, Department of Experimental Cardiology, and Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands; and Department of Plasma Proteins, Sanquin, Amsterdam, The Netherlands.
authors.forename: Amalia
authors.initials: A
authors.lastname: Halliani
authors.affiliation: *Department of Vascular Medicine, Department of Experimental Vascular Medicine, Department of Experimental Cardiology, and Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands; and Department of Plasma Proteins, Sanquin, Amsterdam, The Netherlands.
authors.forename: Perry D
authors.initials: PD
authors.lastname: Moerland
authors.affiliation: *Department of Vascular Medicine, Department of Experimental Vascular Medicine, Department of Experimental Cardiology, and Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands; and Department of Plasma Proteins, Sanquin, Amsterdam, The Netherlands.
authors.forename: Joost C M
authors.initials: JC
authors.lastname: Meijers
authors.affiliation: *Department of Vascular Medicine, Department of Experimental Vascular Medicine, Department of Experimental Cardiology, and Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands; and Department of Plasma Proteins, Sanquin, Amsterdam, The Netherlands.
authors.forename: Esther E
authors.initials: EE
authors.lastname: Creemers
authors.affiliation: *Department of Vascular Medicine, Department of Experimental Vascular Medicine, Department of Experimental Cardiology, and Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands; and Department of Plasma Proteins, Sanquin, Amsterdam, The Netherlands s.j.pinto@amc.uva.nl.
authors.forename: Sara-Joan
authors.initials: SJ
authors.lastname: Pinto-Sietsma
mesh_terms: D000465:Algorithms; D030541:Databases, Genetic; D005260:Female; D006801:Humans; D008297:Male; D035683:MicroRNAs / Q000097:blood*; D012342:RNA, Small Nuclear / Q000097:blood*; D020133:Reverse Transcriptase Polymerase Chain Reaction / Q000379:methods* / Q000592:standards*
chemical_list: C505362:MIRN16 microRNA, human; D035683:MicroRNAs; D012342:RNA, Small Nuclear
keywords: coronary artery disease; platelets; serum; whole blood