ArticleDiabetologia2012
A metabolomic study of low estimated GFR in non-proteinuric type 2 diabetes mellitus.
Article in Diabetologia, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.
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Who cites it
30 citing papers in PubMed, 1 synthesis or guideline pooled it, 78 citations in OpenAlex.
- Metabolite biomarkers of type 2 diabetes mellitus and pre-diabetes: a systematic review and meta-analysis.BMC endocrine disorders · 2020Pooled it
- Biomarkers in Diabetic Kidney Disease: Early Detection, Prognostic Assessment, and Integration with Multi-Omics Signatures.Life (Basel, Switzerland) · 2026Review
- Urinary biomarkers of diabetic kidney disease.World journal of diabetes · 2026Review
- A plasma N-acetyl amino acid panel for type 2 diabetes discrimination built by targeted LC-MS/MS: A case-control study.Frontiers in medicine · 2026Article
- Early detection of feline chronic kidney disease via 3-hydroxykynurenine and machine learning.Scientific reports · 2025Article
- Quantitative, Targeted Analysis of Gut Microbiota Derived Metabolites Provides Novel Biomarkers of Early Diabetic Kidney Disease in Type 2 Diabetes Mellitus Patients.Biomolecules · 2023Article
- A new journey to predict the prognosis of diabetic kidney disease.Kidney research and clinical practice · 2023Article
- The effect of probiotic administration on metabolomics and glucose metabolism in CF patients.Pediatric pulmonology · 2022Article
- Novel biomarkers for diabetic kidney disease.Kidney research and clinical practice · 2022Article
- REG1A and RUNX3 Are Potential Biomarkers for Predicting the Risk of Diabetic Kidney Disease.Frontiers in endocrinology · 2022Article
- Plasma Metabolome and Lipidome Associations with Type 2 Diabetes and Diabetic Nephropathy.Metabolites · 2021Article
- The Role of Gut Microbiota and Microbiota-Related Serum Metabolites in the Progression of Diabetic Kidney Disease.Frontiers in pharmacology · 2021Article
- Article
- Exploring blood alterations in chronic kidney disease and haemodialysis using metabolomics.Scientific reports · 2020Article
- Cohort profile: the Singapore diabetic cohort study.BMJ open · 2020Article
- Statistical Workflow for Feature Selection in Human Metabolomics Data.Metabolites · 2019Review
- Metabolomics Reveals Metabolic Changes Caused by Low-Dose 4-Tert-Octylphenol in Mice Liver.International journal of environmental research and public health · 2018Article
- Might hyperbaric oxygen therapy (HBOT) reduce renal injury in diabetic people with diabetes mellitus? From preclinical models to human metabolomics.Cell stress & chaperones · 2018Article
- Serum metabolites are associated with all-cause mortality in chronic kidney disease.Kidney international · 2018Article
- Biomarkers of diabetic kidney disease.Diabetologia · 2018Review
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aims/hypothesisWe carried out a urinary metabolomic study to gain insight into low estimated GFR (eGFR) in patients with non-proteinuric type 2 diabetes.
methodsPatients were identified as being non-proteinuric using multiple urinalyses. Cases (n = 44) with low eGFR and controls (n = 46) had eGFR values <60 and ≥60 ml min(-1) 1.73 m(-2), respectively, as calculated using the Modification of Diet in Renal Disease formula. Urine samples were analysed by liquid chromatography/mass spectrometry (LC/MS) and GC/MS. False discovery rates were used to adjust for multiple hypotheses testing, and selection of metabolites that best predicted low eGFR status was achieved using least absolute shrinkage and selection operator logistic regression.
resultsEleven GC/MS metabolites were strongly associated with low eGFR after correction for multiple hypotheses testing (smallest adjusted p value = 2.62 × 10(-14), largest adjusted p value = 3.84 × 10(-2)). In regression analysis, octanol, oxalic acid, phosphoric acid, benzamide, creatinine, 3,5-dimethoxymandelic amide and N-acetylglutamine were selected as the best subset for prediction and allowed excellent classification of low eGFR (AUC = 0.996). In LC/MS, 19 metabolites remained significant after multiple hypotheses testing had been taken into account (smallest adjusted p value = 2.04 × 10(-4), largest adjusted p value = 4.48 × 10(-2)), and several metabolites showed stronger evidence of association relative to the uraemic toxin, indoxyl sulphate (adjusted p value = 3.03 × 10(-2)). The potential effect of confounding on the association between metabolites was excluded. CONCLUSIONS/
interpretationOur study has yielded substantial new insight into low eGFR and provided a collection of potential urinary biomarkers for its detection.
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