ArticlePloS one2019
Metabolomics biomarkers and the risk of overall mortality and ESRD in CKD: Results from the Progredir Cohort.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 31 citations in OpenAlex.
- A guide to uraemic toxicity.Nature reviews. Nephrology · 2026Review
- Metabolomic signatures in adults with metabolic syndrome indicate preclinical disruptions in pathways associated with high-density lipoprotein cholesterol, sugar alcohols.Cardiovascular diabetology. Endocrinology reports · 2025Article
- Metabolomics to Identify Unclassified Uremic Toxins: A Comprehensive Literature Review.Kidney medicine · 2025Review
- Metabolomics-Based Machine Learning for Predicting Mortality: Unveiling Multisystem Impacts on Health.International journal of molecular sciences · 2024Article
- Plasma metabolites and physical function in patients undergoing hemodialysis.Scientific reports · 2024Article
- The characteristics of extrachromosomal circular DNA in patients with end-stage renal disease.European journal of medical research · 2023Article
- An Untargeted Metabolomics Approach on Carfilzomib-Induced Nephrotoxicity.Molecules (Basel, Switzerland) · 2022Article
- GC × GC-TOFMS metabolomics analysis identifies elevated levels of plasma sugars and sugar alcohols in diabetic mellitus patients with kidney failure.The Journal of biological chemistry · 2022Article
- Serum Metabolites and Kidney Outcomes: The Atherosclerosis Risk in Communities Study.Kidney medicine · 2022Article
- NMR-Based Metabolomics in Differential Diagnosis of Chronic Kidney Disease (CKD) Subtypes.Metabolites · 2022Article
- New Potential Biomarkers for Chronic Kidney Disease Management-A Review of the Literature.International journal of molecular sciences · 2020Review
- Untargeted GC-MS investigation of serum metabolomics of coronary artery disease patients.Saudi journal of biological sciences · 2020Article
- Serum metabolomics approach to monitor the changes in metabolite profiles following renal transplantation.Scientific reports · 2020Article
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Authors and funding
10 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionStudies on metabolomics and CKD have primarily addressed CKD incidence defined as a decline on eGFR or appearance of albuminuria in the general population, with very few evaluating hard outcomes. In the present study, we investigated the association between metabolites and mortality and ESRD in a CKD cohort. SETTING AND
methodsData on 454 participants of the Progredir Cohort Study, Sao Paulo, Brazil were used. Metabolomics was performed by GC-MS (Agilent MassHunter) and metabolites were identified using Agilent Fiehn GC/MS and NIST libraries. After excluding metabolites present in <50% of participants, 293 metabolites were analyzed. An FDR q value <0.05 criteria was applied in Cox models on the composite outcome (mortality or incident renal replacement therapy) adjusted for batch effect, resulting in 34 metabolites associated with the outcome. Multivariable-adjusted Cox models were then built for the composite outcome, death, and ESRD incident events. Competing risk analysis was also performed for ESRD.
resultsMean age was 68±12y, mean eGFR-CKDEPI was 38.4±14.6 ml/min/1.73m2 and 57% were diabetic. After adjustments (GC-MS batch, sex, age, DM and eGFR), 18 metabolites remained significantly associated with the composite outcome. Nine metabolites were independently associated with death: D-malic acid (HR 1.84, 95%CI 1.32-2.56, p = 0.0003), acetohydroxamic acid (HR 1.90, 95%CI 1.30-2.78, p = 0.0008), butanoic acid (HR 1.59, 95%CI 1.17-2.15, p = 0.003), and docosahexaenoic acid (HR 0.58, 95%CI 0.39-0.88, p = 0.009), among the top associations. Lactose (SHR 1.49, 95%CI 1.04-2.12, p = 0.03), 2-O-glycerol-α-D-galactopyranoside (SHR 1.76, 95%CI 1.06-2.92, p = 0.03), and tyrosine (SHR 0.52, 95%CI 0.31-0.88, p = 0.02) were associated to ESRD risk, while D-threitol, mannitol and myo-inositol presented strong borderline associations.
conclusionOur results identify specific metabolites related to hard outcomes in a CKD population. These findings point to the need of further exploration of these metabolites as biomarkers in CKD and the understanding of the underlying biological mechanisms related to the observed associations.
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