Dataset Information

Quantitative, Targeted Analysis of Gut Microbiota Derived Metabolites Provides Novel Biomarkers of Early Diabetic Kidney Disease in Type 2 Diabetes Mellitus Patients.

ABSTRACT: Diabetic kidney disease (DKD) is one of the most debilitating complications of type 2 diabetes mellitus (T2DM), as it progresses silently to end-stage renal disease (ESRD). The discovery of novel biomarkers of early DKD becomes acute, as its incidence is reaching catastrophic proportions. Our study aimed to quantify previously identified metabolites from serum and urine through untargeted ultra-high-performance liquid chromatography coupled with electrospray ionization-quadrupole-time of flight-mass spectrometry (UHPLC-QTOF-ESI+-MS) techniques, such as the following: arginine, dimethylarginine, hippuric acid, indoxyl sulfate, p-cresyl sulfate, L-acetylcarnitine, butenoylcarnitine and sorbitol. The study concept was based on the targeted analysis of selected metabolites, using the serum and urine of 20 healthy subjects and 90 T2DM patients with DKD in different stages (normoalbuminuria-uACR < 30 mg/g; microalbuminuria-uACR 30-300 mg/g; macroalbuminuria-uACR > 300 mg/g). The quantitative evaluation of metabolites was performed with pure standards, followed by the validation methods such as the limit of detection (LOD) and the limit of quantification (LOQ). The following metabolites from this study resulted as possible biomarkers of early DKD: in serum-arginine, dimethylarginine, hippuric acid, indoxyl sulfate, butenoylcarnitine and sorbitol and in urine-p-cresyl sulfate.

SUBMITTER: Balint L

PROVIDER: S-EPMC10377254 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Quantitative, Targeted Analysis of Gut Microbiota Derived Metabolites Provides Novel Biomarkers of Early Diabetic Kidney Disease in Type 2 Diabetes Mellitus Patients.

Balint Lavinia L Socaciu Carmen C Socaciu Andreea Iulia AI Vlad Adrian A Gadalean Florica F Bob Flaviu F Milas Oana O Cretu Octavian Marius OM Suteanu-Simulescu Anca A Glavan Mihaela M Ienciu Silvia S Mogos Maria M Jianu Dragos Catalin DC Petrica Ligia L

Biomolecules 20230707 7

Diabetic kidney disease (DKD) is one of the most debilitating complications of type 2 diabetes mellitus (T2DM), as it progresses silently to end-stage renal disease (ESRD). The discovery of novel biomarkers of early DKD becomes acute, as its incidence is reaching catastrophic proportions. Our study aimed to quantify previously identified metabolites from serum and urine through untargeted ultra-high-performance liquid chromatography coupled with electrospray ionization-quadrupole-time of flight- ...[more]

PMID: 37509122

Similar Datasets

Project description:Objective: Diabetic kidney disease (DKD) has become the major cause of end-stage renal disease (ESRD) associated with the progression of renal fibrosis. As gut microbiota dysbiosis is closely related to renal damage and fibrosis, we investigated the role of gut microbiota and microbiota-related serum metabolites in DKD progression in this study. Methods: Fecal and serum samples obtained from predialysis DKD patients from January 2017 to December 2019 were detected using 16S rRNA gene sequencing and liquid chromatography-mass spectrometry, respectively. Forty-one predialysis patients were divided into two groups according to their estimated glomerular filtration rate (eGFR): the DKD non-ESRD group (eGFR ≥ 15 ml/min/1.73 m2) (n = 22), and the DKD ESRD group (eGFR < 15 ml/min/1.73 m2) (n = 19). The metabolic pathways related to differential serum metabolites were obtained by the KEGG pathway analysis. Differences between the two groups relative to gut microbiota profiles and serum metabolites were investigated, and associations between gut microbiota and metabolite concentrations were assessed. Correlations between clinical indicators and both microbiota-related metabolites and gut microbiota were calculated by Spearman rank correlation coefficient and visualized by heatmap. Results: Eleven different intestinal floras and 239 different serum metabolites were identified between the two groups. Of 239 serum metabolites, 192 related to the 11 different intestinal flora were mainly enriched in six metabolic pathways, among which, phenylalanine and tryptophan metabolic pathways were most associated with DKD progression. Four microbiota-related metabolites in the phenylalanine metabolic pathway [hippuric acid (HA), L-(-)-3-phenylactic acid, trans-3-hydroxy-cinnamate, and dihydro-3-coumaric acid] and indole-3 acetic acid (IAA) in the tryptophan metabolic pathway positively correlated with DKD progression, whereas L-tryptophan in the tryptophan metabolic pathway had a negative correlation. Intestinal flora g_Abiotrophia and g_norank_f_Peptococcaceae were positively correlated with the increase in renal function indicators and serum metabolite HA. G_Lachnospiraceae_NC2004_Group was negatively correlated with the increase in renal function indicators and serum metabolites [L-(-)-3-phenyllactic acid and IAA]. Conclusions: This study highlights the interaction among gut microbiota, serum metabolites, and clinical indicators in predialysis DKD patients, and provides new insights into the role of gut microbiota and microbiota-related serum metabolites that were enriched in the phenylalanine and tryptophan metabolic pathways, which correlated with the progression of DKD.

Project description:Background Gut microbiota has been reported to play an important role in diabetic kidney disease (DKD), however, the alterations of gut bacteria have not been determined. Methods Studies comparing the differences of gut microbiome between patients with DKD and non-DKD individuals using high-throughput sequencing technology, were systematically searched and reviewed. Outcomes were set as gut bacterial diversity, microbial composition, and correlation with clinical parameters of DKD. Qualitative data were summarized and compared through a funnel R script, and quantitative data were estimated by meta-analysis. Results A total of 15 studies and 1640 participants were included, the comparisons were conducted between DKD, diabetes mellitus (DM), non-diabetic kidney disease (NDKD), and healthy controls. There were no significant differences of α-diversity between DKD and DM, and between DKD and NDKD, however, significant lower microbial richness was found in DKD compared to healthy controls. Different bacterial compositions were found between DKD and non-DKD subjects. The phylum Actinobacteria were found to be enriched in DKD compared to healthy controls. At the genus level, we found the enrichment of Hungatella, Bilophila, and Escherichia in DKD compared to DM, patients with DKD showed lower abundances of Faecalibacterium compared to those with NDKD. The genera Butyricicoccus, Faecalibacterium, and Lachnospira were depleted in DKD compared to healthy controls, whereas Hungatella, Escherichia, and lactobacillus were significantly enriched. The genus Ruminococcus torques group was demonstrated to be inversely correlated with estimated glomerular filtration rate of DKD. Conclusions Gut bacterial alterations was demonstrated in DKD, characterized by the enrichment of the genera Hungatella and Escherichia, and the depletion of butyrate-producing bacteria, which might be associated with the occurrence and development of DKD. Further studies are still needed to validate these findings, due to substantial heterogeneity. Systematic review registration https://www.crd.york.ac.uk/prospero/, identifier CRD42022340870.

Dataset Information

Quantitative, Targeted Analysis of Gut Microbiota Derived Metabolites Provides Novel Biomarkers of Early Diabetic Kidney Disease in Type 2 Diabetes Mellitus Patients.

Publications

Quantitative, Targeted Analysis of Gut Microbiota Derived Metabolites Provides Novel Biomarkers of Early Diabetic Kidney Disease in Type 2 Diabetes Mellitus Patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets