ArticleHeliyon2023
Urinary microbiota and serum metabolite analysis in patients with diabetic kidney disease.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- The urinary microbiome in association with diabetes and diabetic kidney disease: A systematic review.PloS one · 2025Pooled it
- Urobiome composition after renal transplantation: an exploratory study.BMC microbiology · 2026Article
- Renal tissue microbiota and metabolite profiling reveal dysregulated signatures in diabetic kidney disease.Frontiers in microbiology · 2026Article
- Urobiome of patients with diabetic kidney disease in different stages is revealed by 2bRAD-M.Journal of translational medicine · 2025Article
- Urinary metabolomics analysis based on LC-MS for the diagnosis and monitoring of acute coronary syndrome.Frontiers in molecular biosciences · 2025Article
- Metabolome-wide Mendelian randomization reveals causal effects of betaine and N-acetylornithine on impairment of renal function.Frontiers in nutrition · 2024Article
- Impact of coexisting type 2 diabetes mellitus on the urinary microbiota of kidney stone patients.PeerJ · 2024Article
- Emerging role of the host microbiome in neuropsychiatric disorders: overview and future directions.Molecular psychiatry · 2023Review
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Diabetic kidney disease (DKD) is a common and potentially fatal consequence of diabetes. Chronic renal failure or end-stage renal disease may result over time. Numerous studies have demonstrated the function of the microbiota in health and disease. The use of advanced urine culture techniques revealed the presence of resident microbiota in the urinary tract, undermining the idea of urine sterility. Studies have demonstrated that the urine microbiota is related with urological illnesses; nevertheless, the fundamental mechanisms by which the urinary microbiota influences the incidence and progression of DKD remain unclear. The purpose of this research was to describe key characteristics of the patients with DKD urinary microbiota in order to facilitate the development of diagnostic and therapeutic for DKD. Methods: We evaluated the structure and composition of the microbiota extracted from urine samples taken from DKD patients (n = 19) and matched healthy controls (n = 15) using 16S rRNA gene sequencing. Meanwhile, serum metabolite profiles were compared using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Associations between clinical characteristics, urine microbiota, and serum metabolites were also examined. Finally, the interaction between urine microbiota and serum metabolites was clarified based on differential metabolite abundance analysis. Results: The findings indicated that the DKD had a distinct urinary microbiota from the healthy controls (HC). Taxonomic investigations indicated that the DKD microbiome had less alpha diversity than a control group. Proteobacteria and Acidobacteria phyla increased in the DKD, while Firmicutes and Bacteroidetes decreased significantly ( Conclusions: This study placed the urinary microbiota and serum metabolite of DKD patients into a functional framework and identified the most abundant microbiota in DKD (Proteobacteria and Acidobacteria). Arginine metabolites may have a major effect on DKD patients, which correlated with the progression of DKD.
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