ArticleJCI insight2024
Preanalytical considerations in quantifying circulating miRNAs that predict end-stage kidney disease in diabetes.
Article in JCI insight, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- miRNAs as cell-intrinsic epigenetic regulators in muscle in type 2 diabetes.Signal transduction and targeted therapy · 2026Article
- Peripheral and Central miRNA Signatures in Alzheimer's Disease: Tissue-Specific Variability, Sex-Associated Differences, and Implications for Blood-Based Biomarkers.International journal of molecular sciences · 2026Review
- MicroRNAs as diagnostic prognostic and therapeutic biomarkers in glioblastoma.Discover oncology · 2026Review
- What a Modern Physician Should Know About microRNAs in the Diagnosis and Treatment of Diabetic Kidney Disease.International journal of molecular sciences · 2025Review
- Circulating MicroRNAs: functional biomarkers for melanoma prognosis and treatment.Molecular cancer · 2025Review
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Our previous study identified 8 risk and 9 protective plasma miRNAs associated with progression to end-stage kidney disease (ESKD) in diabetes. This study aimed to elucidate preanalytical factors that influence the quantification of circulating miRNAs. Using the EdgeSeq platform, which quantifies 2,002 miRNAs in plasma, including ESKD-associated miRNAs, we compared miRNA profiles in whole plasma versus miRNA profiles in RNA extracted from the same plasma specimens. Less than half of the miRNAs were detected in standard RNA extraction from plasma. Detection of individual and concentrations of miRNAs were much lower when RNA extracted from plasma was quantified by RNA sequencing (RNA-Seq) or quantitative reverse transcription PCR (qRT-PCR) platforms compared with EdgeSeq. Plasma profiles of miRNAs determined by the EdgeSeq platform had excellent reproducibility in assessment and had no variation with age, sex, hemoglobin A1c, BMI, and cryostorage time. The risk ESKD-associated miRNAs were detected and measured accurately only in whole plasma and using the EdgeSeq platform. Protective ESKD-associated miRNAs were detected by all platforms except qRT-PCR; however, correlations among concentrations obtained with different platforms were weak or nonexistent. In conclusion, preanalytical factors have a profound effect on detection and quantification of circulating miRNAs in ESKD in diabetes. Quantification of miRNAs in whole plasma and using the EdgeSeq platform may be the preferable method to study profiles of circulating cell-free miRNAs associated with ESKD and possibly other diseases.
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