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Urinary mRNA Signatures as Predictors of Renal Function Decline in Patients With Biopsy-Proven Diabetic Kidney Disease
The clinical manifestations of diabetic kidney disease (DKD) are more heterogeneous than those previously reported, and these observations mandate the need for the recruitment of patients with biopsy-proven DKD in biomarker research. In this study, using the public gene expression omnibus (GEO) repo...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8630698/ https://www.ncbi.nlm.nih.gov/pubmed/34858345 http://dx.doi.org/10.3389/fendo.2021.774436 |
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author | Lee, Yu Ho Seo, Jung-Woo Kim, Miji Tae, Donghyun Seok, Junhee Kim, Yang Gyun Lee, Sang-Ho Kim, Jin Sug Hwang, Hyeon Seok Jeong, Kyung-Hwan Moon, Ju-Young |
author_facet | Lee, Yu Ho Seo, Jung-Woo Kim, Miji Tae, Donghyun Seok, Junhee Kim, Yang Gyun Lee, Sang-Ho Kim, Jin Sug Hwang, Hyeon Seok Jeong, Kyung-Hwan Moon, Ju-Young |
author_sort | Lee, Yu Ho |
collection | PubMed |
description | The clinical manifestations of diabetic kidney disease (DKD) are more heterogeneous than those previously reported, and these observations mandate the need for the recruitment of patients with biopsy-proven DKD in biomarker research. In this study, using the public gene expression omnibus (GEO) repository, we aimed to identify urinary mRNA biomarkers that can predict histological severity and disease progression in patients with DKD in whom the diagnosis and histologic grade has been confirmed by kidney biopsy. We identified 30 DKD-specific mRNA candidates based on the analysis of the GEO datasets. Among these, there were significant alterations in the urinary levels of 17 mRNAs in patients with DKD, compared with healthy controls. Four urinary mRNAs—LYZ, C3, FKBP5, and G6PC—reflected tubulointerstitial inflammation and fibrosis in kidney biopsy and could predict rapid progression to end-stage kidney disease independently of the baseline eGFR (tertile 1 vs. tertile 3; adjusted hazard ratio of 9.68 and 95% confidence interval of 2.85–32.87, p < 0.001). In conclusion, we demonstrated that urinary mRNA signatures have a potential to indicate the pathologic status and predict adverse renal outcomes in patients with DKD. |
format | Online Article Text |
id | pubmed-8630698 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-86306982021-12-01 Urinary mRNA Signatures as Predictors of Renal Function Decline in Patients With Biopsy-Proven Diabetic Kidney Disease Lee, Yu Ho Seo, Jung-Woo Kim, Miji Tae, Donghyun Seok, Junhee Kim, Yang Gyun Lee, Sang-Ho Kim, Jin Sug Hwang, Hyeon Seok Jeong, Kyung-Hwan Moon, Ju-Young Front Endocrinol (Lausanne) Endocrinology The clinical manifestations of diabetic kidney disease (DKD) are more heterogeneous than those previously reported, and these observations mandate the need for the recruitment of patients with biopsy-proven DKD in biomarker research. In this study, using the public gene expression omnibus (GEO) repository, we aimed to identify urinary mRNA biomarkers that can predict histological severity and disease progression in patients with DKD in whom the diagnosis and histologic grade has been confirmed by kidney biopsy. We identified 30 DKD-specific mRNA candidates based on the analysis of the GEO datasets. Among these, there were significant alterations in the urinary levels of 17 mRNAs in patients with DKD, compared with healthy controls. Four urinary mRNAs—LYZ, C3, FKBP5, and G6PC—reflected tubulointerstitial inflammation and fibrosis in kidney biopsy and could predict rapid progression to end-stage kidney disease independently of the baseline eGFR (tertile 1 vs. tertile 3; adjusted hazard ratio of 9.68 and 95% confidence interval of 2.85–32.87, p < 0.001). In conclusion, we demonstrated that urinary mRNA signatures have a potential to indicate the pathologic status and predict adverse renal outcomes in patients with DKD. Frontiers Media S.A. 2021-11-09 /pmc/articles/PMC8630698/ /pubmed/34858345 http://dx.doi.org/10.3389/fendo.2021.774436 Text en Copyright © 2021 Lee, Seo, Kim, Tae, Seok, Kim, Lee, Kim, Hwang, Jeong and Moon https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Endocrinology Lee, Yu Ho Seo, Jung-Woo Kim, Miji Tae, Donghyun Seok, Junhee Kim, Yang Gyun Lee, Sang-Ho Kim, Jin Sug Hwang, Hyeon Seok Jeong, Kyung-Hwan Moon, Ju-Young Urinary mRNA Signatures as Predictors of Renal Function Decline in Patients With Biopsy-Proven Diabetic Kidney Disease |
title | Urinary mRNA Signatures as Predictors of Renal Function Decline in Patients With Biopsy-Proven Diabetic Kidney Disease |
title_full | Urinary mRNA Signatures as Predictors of Renal Function Decline in Patients With Biopsy-Proven Diabetic Kidney Disease |
title_fullStr | Urinary mRNA Signatures as Predictors of Renal Function Decline in Patients With Biopsy-Proven Diabetic Kidney Disease |
title_full_unstemmed | Urinary mRNA Signatures as Predictors of Renal Function Decline in Patients With Biopsy-Proven Diabetic Kidney Disease |
title_short | Urinary mRNA Signatures as Predictors of Renal Function Decline in Patients With Biopsy-Proven Diabetic Kidney Disease |
title_sort | urinary mrna signatures as predictors of renal function decline in patients with biopsy-proven diabetic kidney disease |
topic | Endocrinology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8630698/ https://www.ncbi.nlm.nih.gov/pubmed/34858345 http://dx.doi.org/10.3389/fendo.2021.774436 |
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