A Metabolomics study of metabolites associated with the glomerular filtration rate.
Biomarker
Chronic kidney disease (CKD)
Glomerular filtration rate (GFR)
Metabolite
Metabolomics
Journal
BMC nephrology
ISSN: 1471-2369
Titre abrégé: BMC Nephrol
Pays: England
ID NLM: 100967793
Informations de publication
Date de publication:
21 04 2023
21 04 2023
Historique:
received:
18
09
2022
accepted:
31
03
2023
medline:
25
4
2023
pubmed:
22
4
2023
entrez:
21
04
2023
Statut:
epublish
Résumé
Chronic kidney disease (CKD) is a global public health issue. The diagnosis of CKD would be considerably enhanced by discovering novel biomarkers used to determine the glomerular filtration rate (GFR). Small molecule metabolites related to kidney filtration function that might be utilized as biomarkers to measure GFR more accurately could be found via a metabolomics analysis of blood samples taken from individuals with varied glomerular filtration rates. An untargeted metabolomics study of 145 plasma samples was performed using ultrahigh-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS). The 145 samples were divided into four groups based on the patient's measured glomerular filtration rates (mGFRs) determined by the iohexol plasma clearance rate. The data were analyzed using random forest analyses and six other unique statistical analyses. Principal component analysis (PCA) was conducted using R software. A large number of metabolites involved in various metabolic pathways changed significantly between groups with different GFRs. These included metabolites involved in tryptophan or pyrimidine metabolism. The top 30 metabolites that best distinguished between the four groups in a random forest plot analysis included 13 amino acids, 9 nucleotides, and 3 carbohydrates. A panel of metabolites (including hydroxyaparagine, pseudouridine, C-glycosyltryptophan, erythronate, N-acetylalanine, and 7-methylguanidine) for estimating GFR was selected for future testing in targeted analyses by combining the candidate lists with the six other statistical analyses. Both hydroxyasparagine and N,N-dimethyl-proline-proline are unique biomarkers shown to be inversely associated with kidney function that have not been reported previously. In contrast, 1,5-anhydroglucitol (1,5-AG) decreases with impaired renal function. This global untargeted metabolomics study of plasma samples from patients with different degrees of renal function identified potential metabolite biomarkers related to kidney filtration. These novel potential metabolites provide more insight into the underlying pathophysiologic processes that may contribute to the progression of CKD, lead to improvements in the estimation of GFR and provide potential therapeutic targets to improve kidney function.
Sections du résumé
BACKGROUND
Chronic kidney disease (CKD) is a global public health issue. The diagnosis of CKD would be considerably enhanced by discovering novel biomarkers used to determine the glomerular filtration rate (GFR). Small molecule metabolites related to kidney filtration function that might be utilized as biomarkers to measure GFR more accurately could be found via a metabolomics analysis of blood samples taken from individuals with varied glomerular filtration rates.
METHODS
An untargeted metabolomics study of 145 plasma samples was performed using ultrahigh-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS). The 145 samples were divided into four groups based on the patient's measured glomerular filtration rates (mGFRs) determined by the iohexol plasma clearance rate. The data were analyzed using random forest analyses and six other unique statistical analyses. Principal component analysis (PCA) was conducted using R software.
RESULTS
A large number of metabolites involved in various metabolic pathways changed significantly between groups with different GFRs. These included metabolites involved in tryptophan or pyrimidine metabolism. The top 30 metabolites that best distinguished between the four groups in a random forest plot analysis included 13 amino acids, 9 nucleotides, and 3 carbohydrates. A panel of metabolites (including hydroxyaparagine, pseudouridine, C-glycosyltryptophan, erythronate, N-acetylalanine, and 7-methylguanidine) for estimating GFR was selected for future testing in targeted analyses by combining the candidate lists with the six other statistical analyses. Both hydroxyasparagine and N,N-dimethyl-proline-proline are unique biomarkers shown to be inversely associated with kidney function that have not been reported previously. In contrast, 1,5-anhydroglucitol (1,5-AG) decreases with impaired renal function.
CONCLUSIONS
This global untargeted metabolomics study of plasma samples from patients with different degrees of renal function identified potential metabolite biomarkers related to kidney filtration. These novel potential metabolites provide more insight into the underlying pathophysiologic processes that may contribute to the progression of CKD, lead to improvements in the estimation of GFR and provide potential therapeutic targets to improve kidney function.
Identifiants
pubmed: 37085754
doi: 10.1186/s12882-023-03147-9
pii: 10.1186/s12882-023-03147-9
pmc: PMC10122376
doi:
Substances chimiques
C-glycosyltryptophan
0
Biomarkers
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
105Informations de copyright
© 2023. The Author(s).
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