Cargando…
Urine myo-inositol as a novel prognostic biomarker for diabetic kidney disease: a targeted metabolomics study using nuclear magnetic resonance
BACKGROUND: As a leading cause of chronic kidney disease, clinical demand for noninvasive biomarkers of diabetic kidney disease (DKD) beyond proteinuria is increasing. Metabolomics is a popular method to identify mechanisms and biomarkers. We investigated urinary targeted metabolomics in DKD patient...
Autores principales: | , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Korean Society of Nephrology
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10407640/ https://www.ncbi.nlm.nih.gov/pubmed/37551126 http://dx.doi.org/10.23876/j.krcp.22.152 |
_version_ | 1785086011344158720 |
---|---|
author | Kwon, Soie Hyeon, Jin Seong Jung, Youngae Li, Lilin An, Jung Nam Kim, Yong Chul Yang, Seung Hee Kim, Tammy Kim, Dong Ki Lim, Chun Soo Hwang, Geum-Sook Lee, Jung Pyo |
author_facet | Kwon, Soie Hyeon, Jin Seong Jung, Youngae Li, Lilin An, Jung Nam Kim, Yong Chul Yang, Seung Hee Kim, Tammy Kim, Dong Ki Lim, Chun Soo Hwang, Geum-Sook Lee, Jung Pyo |
author_sort | Kwon, Soie |
collection | PubMed |
description | BACKGROUND: As a leading cause of chronic kidney disease, clinical demand for noninvasive biomarkers of diabetic kidney disease (DKD) beyond proteinuria is increasing. Metabolomics is a popular method to identify mechanisms and biomarkers. We investigated urinary targeted metabolomics in DKD patients. METHODS: We conducted a targeted metabolomics study of 26 urinary metabolites in consecutive patients with DKD stage 1 to 5 (n = 208) and healthy controls (n = 26). The relationships between estimated glomerular filtration rate (eGFR) or urine protein-creatinine ratio (UPCR) and metabolites were evaluated. Multivariate Cox analysis was used to estimate relationships between urinary metabolites and the target outcome, end-stage renal disease (ESRD). C statistics and time-dependent receiver operating characteristics (ROC) were used to assess diagnostic validity. RESULTS: During a median 4.5 years of follow-up, 103 patients (44.0%) progressed to ESRD and 65 (27.8%) died. The median fold changes of nine metabolites belonged to monosaccharide and tricarboxylic acid (TCA) cycle metabolites tended to increase with DKD stage. Myo-inositol, choline, and citrates were correlated with eGFR and choline, while mannose and myo-inositol were correlated with UPCR. Elevated urinary monosaccharide and TCA cycle metabolites showed associations with increased morality and ESRD progression. The predictive power of ESRD progression was high, in the order of choline, myo-inositol, and citrate. Although urinary metabolites alone were less predictive than serum creatinine or UPCR, myo-inositol had additive effect with serum creatinine and UPCR. In time-dependent ROC, myo-inositol was more predictive than UPCR of 1-year ESRD progression prediction. CONCLUSION: Myo-inositol can be used as an additive biomarker of ESRD progression in DKD. |
format | Online Article Text |
id | pubmed-10407640 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Korean Society of Nephrology |
record_format | MEDLINE/PubMed |
spelling | pubmed-104076402023-08-09 Urine myo-inositol as a novel prognostic biomarker for diabetic kidney disease: a targeted metabolomics study using nuclear magnetic resonance Kwon, Soie Hyeon, Jin Seong Jung, Youngae Li, Lilin An, Jung Nam Kim, Yong Chul Yang, Seung Hee Kim, Tammy Kim, Dong Ki Lim, Chun Soo Hwang, Geum-Sook Lee, Jung Pyo Kidney Res Clin Pract Original Article BACKGROUND: As a leading cause of chronic kidney disease, clinical demand for noninvasive biomarkers of diabetic kidney disease (DKD) beyond proteinuria is increasing. Metabolomics is a popular method to identify mechanisms and biomarkers. We investigated urinary targeted metabolomics in DKD patients. METHODS: We conducted a targeted metabolomics study of 26 urinary metabolites in consecutive patients with DKD stage 1 to 5 (n = 208) and healthy controls (n = 26). The relationships between estimated glomerular filtration rate (eGFR) or urine protein-creatinine ratio (UPCR) and metabolites were evaluated. Multivariate Cox analysis was used to estimate relationships between urinary metabolites and the target outcome, end-stage renal disease (ESRD). C statistics and time-dependent receiver operating characteristics (ROC) were used to assess diagnostic validity. RESULTS: During a median 4.5 years of follow-up, 103 patients (44.0%) progressed to ESRD and 65 (27.8%) died. The median fold changes of nine metabolites belonged to monosaccharide and tricarboxylic acid (TCA) cycle metabolites tended to increase with DKD stage. Myo-inositol, choline, and citrates were correlated with eGFR and choline, while mannose and myo-inositol were correlated with UPCR. Elevated urinary monosaccharide and TCA cycle metabolites showed associations with increased morality and ESRD progression. The predictive power of ESRD progression was high, in the order of choline, myo-inositol, and citrate. Although urinary metabolites alone were less predictive than serum creatinine or UPCR, myo-inositol had additive effect with serum creatinine and UPCR. In time-dependent ROC, myo-inositol was more predictive than UPCR of 1-year ESRD progression prediction. CONCLUSION: Myo-inositol can be used as an additive biomarker of ESRD progression in DKD. The Korean Society of Nephrology 2023-07 2023-07-25 /pmc/articles/PMC10407640/ /pubmed/37551126 http://dx.doi.org/10.23876/j.krcp.22.152 Text en Copyright © 2023 The Korean Society of Nephrology https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial and No Derivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) ) which permits unrestricted non-commercial use, distribution of the material without any modifications, and reproduction in any medium, provided the original works properly cited. |
spellingShingle | Original Article Kwon, Soie Hyeon, Jin Seong Jung, Youngae Li, Lilin An, Jung Nam Kim, Yong Chul Yang, Seung Hee Kim, Tammy Kim, Dong Ki Lim, Chun Soo Hwang, Geum-Sook Lee, Jung Pyo Urine myo-inositol as a novel prognostic biomarker for diabetic kidney disease: a targeted metabolomics study using nuclear magnetic resonance |
title | Urine myo-inositol as a novel prognostic biomarker for diabetic kidney disease: a targeted metabolomics study using nuclear magnetic resonance |
title_full | Urine myo-inositol as a novel prognostic biomarker for diabetic kidney disease: a targeted metabolomics study using nuclear magnetic resonance |
title_fullStr | Urine myo-inositol as a novel prognostic biomarker for diabetic kidney disease: a targeted metabolomics study using nuclear magnetic resonance |
title_full_unstemmed | Urine myo-inositol as a novel prognostic biomarker for diabetic kidney disease: a targeted metabolomics study using nuclear magnetic resonance |
title_short | Urine myo-inositol as a novel prognostic biomarker for diabetic kidney disease: a targeted metabolomics study using nuclear magnetic resonance |
title_sort | urine myo-inositol as a novel prognostic biomarker for diabetic kidney disease: a targeted metabolomics study using nuclear magnetic resonance |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10407640/ https://www.ncbi.nlm.nih.gov/pubmed/37551126 http://dx.doi.org/10.23876/j.krcp.22.152 |
work_keys_str_mv | AT kwonsoie urinemyoinositolasanovelprognosticbiomarkerfordiabetickidneydiseaseatargetedmetabolomicsstudyusingnuclearmagneticresonance AT hyeonjinseong urinemyoinositolasanovelprognosticbiomarkerfordiabetickidneydiseaseatargetedmetabolomicsstudyusingnuclearmagneticresonance AT jungyoungae urinemyoinositolasanovelprognosticbiomarkerfordiabetickidneydiseaseatargetedmetabolomicsstudyusingnuclearmagneticresonance AT lililin urinemyoinositolasanovelprognosticbiomarkerfordiabetickidneydiseaseatargetedmetabolomicsstudyusingnuclearmagneticresonance AT anjungnam urinemyoinositolasanovelprognosticbiomarkerfordiabetickidneydiseaseatargetedmetabolomicsstudyusingnuclearmagneticresonance AT kimyongchul urinemyoinositolasanovelprognosticbiomarkerfordiabetickidneydiseaseatargetedmetabolomicsstudyusingnuclearmagneticresonance AT yangseunghee urinemyoinositolasanovelprognosticbiomarkerfordiabetickidneydiseaseatargetedmetabolomicsstudyusingnuclearmagneticresonance AT kimtammy urinemyoinositolasanovelprognosticbiomarkerfordiabetickidneydiseaseatargetedmetabolomicsstudyusingnuclearmagneticresonance AT kimdongki urinemyoinositolasanovelprognosticbiomarkerfordiabetickidneydiseaseatargetedmetabolomicsstudyusingnuclearmagneticresonance AT limchunsoo urinemyoinositolasanovelprognosticbiomarkerfordiabetickidneydiseaseatargetedmetabolomicsstudyusingnuclearmagneticresonance AT hwanggeumsook urinemyoinositolasanovelprognosticbiomarkerfordiabetickidneydiseaseatargetedmetabolomicsstudyusingnuclearmagneticresonance AT leejungpyo urinemyoinositolasanovelprognosticbiomarkerfordiabetickidneydiseaseatargetedmetabolomicsstudyusingnuclearmagneticresonance |