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...
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Frontiers Media S.A.
2021
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oai:doaj.org-article:4b84dde031734255ac9c92485d37d0502021-11-09T06:15:13ZUrinary mRNA Signatures as Predictors of Renal Function Decline in Patients With Biopsy-Proven Diabetic Kidney Disease1664-239210.3389/fendo.2021.774436https://doaj.org/article/4b84dde031734255ac9c92485d37d0502021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fendo.2021.774436/fullhttps://doaj.org/toc/1664-2392The 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.Yu Ho LeeJung-Woo SeoMiji KimDonghyun TaeJunhee SeokYang Gyun KimSang-Ho LeeJin Sug KimHyeon Seok HwangKyung-Hwan JeongJu-Young MoonFrontiers Media S.A.articlediabetic kidney diseasemRNAurinebiomarkerrenal pathologyDiseases of the endocrine glands. Clinical endocrinologyRC648-665ENFrontiers in Endocrinology, Vol 12 (2021) |
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DOAJ |
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diabetic kidney disease mRNA urine biomarker renal pathology Diseases of the endocrine glands. Clinical endocrinology RC648-665 |
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diabetic kidney disease mRNA urine biomarker renal pathology Diseases of the endocrine glands. Clinical endocrinology RC648-665 Yu Ho Lee Jung-Woo Seo Miji Kim Donghyun Tae Junhee Seok Yang Gyun Kim Sang-Ho Lee Jin Sug Kim Hyeon Seok Hwang Kyung-Hwan Jeong Ju-Young Moon Urinary mRNA Signatures as Predictors of Renal Function Decline in Patients With Biopsy-Proven Diabetic Kidney Disease |
| 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 |
article |
| author |
Yu Ho Lee Jung-Woo Seo Miji Kim Donghyun Tae Junhee Seok Yang Gyun Kim Sang-Ho Lee Jin Sug Kim Hyeon Seok Hwang Kyung-Hwan Jeong Ju-Young Moon |
| author_facet |
Yu Ho Lee Jung-Woo Seo Miji Kim Donghyun Tae Junhee Seok Yang Gyun Kim Sang-Ho Lee Jin Sug Kim Hyeon Seok Hwang Kyung-Hwan Jeong Ju-Young Moon |
| author_sort |
Yu Ho Lee |
| title |
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_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_sort |
urinary mrna signatures as predictors of renal function decline in patients with biopsy-proven diabetic kidney disease |
| publisher |
Frontiers Media S.A. |
| publishDate |
2021 |
| url |
https://doaj.org/article/4b84dde031734255ac9c92485d37d050 |
| work_keys_str_mv |
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