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Open AccessReview

Diagnostic, Prognostic, and Therapeutic Value of Non-Coding RNA Expression Profiles in Renal Transplantation

1
Pharmacology Ph.D. program, Universidad de Guadalajara, Guadalajara 44340, Mexico
2
CONACyT-Centro de Investigacion Biomedica de Occidente, Instituto Mexicano del Seguro Social, Guadalajara 44340, Mexico
*
Author to whom correspondence should be addressed.
Diagnostics 2020, 10(2), 60; https://doi.org/10.3390/diagnostics10020060
Received: 31 December 2019 / Revised: 17 January 2020 / Accepted: 19 January 2020 / Published: 22 January 2020
(This article belongs to the Collection Biomarkers in Medicine)
End-stage renal disease is a public health problem responsible for millions of deaths worldwide each year. Although transplantation is the preferred treatment for patients in need of renal replacement therapy, long-term allograft survival remains challenging. Advances in high-throughput methods for large-scale molecular data generation and computational analysis are promising to overcome the current limitations posed by conventional diagnostic and disease classifications post-transplantation. Non-coding RNAs (ncRNAs) are RNA molecules that, despite lacking protein-coding potential, are essential in the regulation of epigenetic, transcriptional, and post-translational mechanisms involved in both health and disease. A large body of evidence suggests that ncRNAs can act as biomarkers of renal injury and graft loss after transplantation. Hence, the focus of this review is to discuss the existing molecular signatures of non-coding transcripts and their value to improve diagnosis, predict the risk of rejection, and guide therapeutic choices post-transplantation. View Full-Text
Keywords: Non-coding RNA; renal transplantation; molecular signatures; rejection Non-coding RNA; renal transplantation; molecular signatures; rejection
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MDPI and ACS Style

Franco-Acevedo, A.; Melo, Z.; Echavarria, R. Diagnostic, Prognostic, and Therapeutic Value of Non-Coding RNA Expression Profiles in Renal Transplantation. Diagnostics 2020, 10, 60.

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