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Updated: Jan 27, 2026

Normothermic Ex Vivo Kidney Perfusion for the Preservation of Kidney Grafts prior to Transplantation
Published on: July 15, 2015
MicroRNAs in Kidney Machine Perfusion Fluid as Novel Biomarkers for Graft Function. Normalization Methods for miRNAs
V Gómez-Dos-Santos1, E Ramos-Muñoz2, M L García-Bermejo2
1Urology Department, Surgical Urology and Transplantation Research Group, IRYCIS, Ramón y Cajal Hospital, University of Alcalá, Madrid, Spain.
Abstract:
MicroRNAs (miRNAs) are post-transcriptional regulators that have emerged as promising biomarkers in kidney transplantation. Quantification of miRNAs can be analyzed by means of biological normalization. The purpose of normalization is to remove technical variation in data, which is not related to the biological changes under investigation. Proper normalization is critical for the correct analysis and interpretation of results.
Material And Methods:
A prospective cohort study was conducted on graft dysfunction in kidney transplantation from expanded criteria donors. After RNA extraction quantitative real-time polymerase chain reaction was performed. The exogenous spike-in normalization was used as technical normalization. Relative expression was calculated using the 2-ΔΔCt method and UniSp2 spike-in was used as reference for normalization. Results obtained were further analyzed by the application of the mean expression value that uses the calculated mean of all miRNAs in a given sample.
Results:
The mean expression value approach confirmed the significance of a subset of the miRNAs previously identified for delayed graft function development and composed by miRNAs miR-486-5p, miR-144-3p, miR-142-5p, and miR-144-5p.
Conclusions:
MicroRNAs are becoming increasingly important as biomarkers in multiple disease processes including kidney transplantation. Perfusion fluid, particularly during hypothermic machine perfusion, provides a valuable pretransplantation source for identification of organ viability biomarkers. Although there is no clear consensus concerning the normalization technique, the mean expression value method shows the better normalization strategy.
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