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Omics-based biomarkers for diagnosis and prediction of kidney allograft rejection
Kidney transplantation is the preferred treatment for patients with end-stage kidney disease, because it prolongs survival and improves quality of life. Allograft biopsy is the gold standard for diagnosing allograft rejection. However, it is invasive and reactive, and continuous monitoring is unreal...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Association of Internal Medicine
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9082440/ https://www.ncbi.nlm.nih.gov/pubmed/35417937 http://dx.doi.org/10.3904/kjim.2021.518 |
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author | Lim, Jeong-Hoon Chung, Byung Ha Lee, Sang-Ho Jung, Hee-Yeon Choi, Ji-Young Cho, Jang-Hee Park, Sun-Hee Kim, Yong-Lim Kim, Chan-Duck |
author_facet | Lim, Jeong-Hoon Chung, Byung Ha Lee, Sang-Ho Jung, Hee-Yeon Choi, Ji-Young Cho, Jang-Hee Park, Sun-Hee Kim, Yong-Lim Kim, Chan-Duck |
author_sort | Lim, Jeong-Hoon |
collection | PubMed |
description | Kidney transplantation is the preferred treatment for patients with end-stage kidney disease, because it prolongs survival and improves quality of life. Allograft biopsy is the gold standard for diagnosing allograft rejection. However, it is invasive and reactive, and continuous monitoring is unrealistic. Various biomarkers for diagnosing allograft rejection have been developed over the last two decades based on omics technologies to overcome these limitations. Omics technologies are based on a holistic view of the molecules that constitute an individual. They include genomics, transcriptomics, proteomics, and metabolomics. The omics approach has dramatically accelerated biomarker discovery and enhanced our understanding of multifactorial biological processes in the field of transplantation. However, clinical application of omics-based biomarkers is limited by several issues. First, no large-scale prospective randomized controlled trial has been conducted to compare omics-based biomarkers with traditional biomarkers for rejection. Second, given the variety and complexity of injuries that a kidney allograft may experience, it is likely that no single omics approach will suffice to predict rejection or outcome. Therefore, integrated methods using multiomics technologies are needed. Herein, we introduce omics technologies and review the latest literature on omics biomarkers predictive of allograft rejection in kidney transplant recipients. |
format | Online Article Text |
id | pubmed-9082440 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Korean Association of Internal Medicine |
record_format | MEDLINE/PubMed |
spelling | pubmed-90824402022-05-17 Omics-based biomarkers for diagnosis and prediction of kidney allograft rejection Lim, Jeong-Hoon Chung, Byung Ha Lee, Sang-Ho Jung, Hee-Yeon Choi, Ji-Young Cho, Jang-Hee Park, Sun-Hee Kim, Yong-Lim Kim, Chan-Duck Korean J Intern Med Review Kidney transplantation is the preferred treatment for patients with end-stage kidney disease, because it prolongs survival and improves quality of life. Allograft biopsy is the gold standard for diagnosing allograft rejection. However, it is invasive and reactive, and continuous monitoring is unrealistic. Various biomarkers for diagnosing allograft rejection have been developed over the last two decades based on omics technologies to overcome these limitations. Omics technologies are based on a holistic view of the molecules that constitute an individual. They include genomics, transcriptomics, proteomics, and metabolomics. The omics approach has dramatically accelerated biomarker discovery and enhanced our understanding of multifactorial biological processes in the field of transplantation. However, clinical application of omics-based biomarkers is limited by several issues. First, no large-scale prospective randomized controlled trial has been conducted to compare omics-based biomarkers with traditional biomarkers for rejection. Second, given the variety and complexity of injuries that a kidney allograft may experience, it is likely that no single omics approach will suffice to predict rejection or outcome. Therefore, integrated methods using multiomics technologies are needed. Herein, we introduce omics technologies and review the latest literature on omics biomarkers predictive of allograft rejection in kidney transplant recipients. Korean Association of Internal Medicine 2022-05 2022-04-15 /pmc/articles/PMC9082440/ /pubmed/35417937 http://dx.doi.org/10.3904/kjim.2021.518 Text en Copyright © 2022 The Korean Association of Internal Medicine https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Lim, Jeong-Hoon Chung, Byung Ha Lee, Sang-Ho Jung, Hee-Yeon Choi, Ji-Young Cho, Jang-Hee Park, Sun-Hee Kim, Yong-Lim Kim, Chan-Duck Omics-based biomarkers for diagnosis and prediction of kidney allograft rejection |
title | Omics-based biomarkers for diagnosis and prediction of kidney allograft rejection |
title_full | Omics-based biomarkers for diagnosis and prediction of kidney allograft rejection |
title_fullStr | Omics-based biomarkers for diagnosis and prediction of kidney allograft rejection |
title_full_unstemmed | Omics-based biomarkers for diagnosis and prediction of kidney allograft rejection |
title_short | Omics-based biomarkers for diagnosis and prediction of kidney allograft rejection |
title_sort | omics-based biomarkers for diagnosis and prediction of kidney allograft rejection |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9082440/ https://www.ncbi.nlm.nih.gov/pubmed/35417937 http://dx.doi.org/10.3904/kjim.2021.518 |
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