Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
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
_version_ 1784607413411774464
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
work_keys_str_mv AT leeyuho urinarymrnasignaturesaspredictorsofrenalfunctiondeclineinpatientswithbiopsyprovendiabetickidneydisease
AT seojungwoo urinarymrnasignaturesaspredictorsofrenalfunctiondeclineinpatientswithbiopsyprovendiabetickidneydisease
AT kimmiji urinarymrnasignaturesaspredictorsofrenalfunctiondeclineinpatientswithbiopsyprovendiabetickidneydisease
AT taedonghyun urinarymrnasignaturesaspredictorsofrenalfunctiondeclineinpatientswithbiopsyprovendiabetickidneydisease
AT seokjunhee urinarymrnasignaturesaspredictorsofrenalfunctiondeclineinpatientswithbiopsyprovendiabetickidneydisease
AT kimyanggyun urinarymrnasignaturesaspredictorsofrenalfunctiondeclineinpatientswithbiopsyprovendiabetickidneydisease
AT leesangho urinarymrnasignaturesaspredictorsofrenalfunctiondeclineinpatientswithbiopsyprovendiabetickidneydisease
AT kimjinsug urinarymrnasignaturesaspredictorsofrenalfunctiondeclineinpatientswithbiopsyprovendiabetickidneydisease
AT hwanghyeonseok urinarymrnasignaturesaspredictorsofrenalfunctiondeclineinpatientswithbiopsyprovendiabetickidneydisease
AT jeongkyunghwan urinarymrnasignaturesaspredictorsofrenalfunctiondeclineinpatientswithbiopsyprovendiabetickidneydisease
AT moonjuyoung urinarymrnasignaturesaspredictorsofrenalfunctiondeclineinpatientswithbiopsyprovendiabetickidneydisease