ArticleScientific reports2020
Exploring blood alterations in chronic kidney disease and haemodialysis using metabolomics.
Article in Scientific reports, 2020. 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.
- Characterization of residual kidney function in chronic hemodialysis patients using plasma metabolomics.Scientific reports · 2026Article
- Temporal Changes in Blood Metabolome: Understanding Biochemical Changes in Hemodialysis Patients.Kidney international reports · 2025Article
- A clustering approach to improve our understanding of the genetic and phenotypic complexity of chronic kidney disease.Scientific reports · 2024Article
- A clustering approach to improve our understanding of the genetic and phenotypic complexity of chronic kidney disease.medRxiv : the preprint server for health sciences · 2023Article
- Nutritional Strategies to Prevent Muscle Loss and Sarcopenia in Chronic Kidney Disease: What Do We Currently Know?Nutrients · 2023Review
- A Fluorescence-Based Competitive Antibody Binding Assay for Kynurenine, a Potential Biomarker of Kidney Transplant Failure.Diagnostics (Basel, Switzerland) · 2022Article
- CRISP: a deep learning architecture for GC × GC-TOFMS contour ROI identification, simulation and analysis in imaging metabolomics.Briefings in bioinformatics · 2022Article
- Metabolic and Metabo-Clinical Signatures of Type 2 Diabetes, Obesity, Retinopathy, and Dyslipidemia.Diabetes · 2022Article
- Serum Biomarkers for Chronic Renal Failure Screening and Mechanistic Understanding: A Global LC-MS-Based Metabolomics Research.Evidence-based complementary and alternative medicine : eCAM · 2022Article
- Longitudinal metabolomics of human plasma reveals prognostic markers of COVID-19 disease severity.Cell reports. Medicine · 2021Article
- Longitudinal Metabolomics of Human Plasma Reveals Robust Prognostic Markers of COVID-19 Disease Severity.medRxiv : the preprint server for health sciences · 2021Article
- Gaining Insights Into Metabolic Networks Using Chemometrics and Bioinformatics: Chronic Kidney Disease as a Clinical Model.Frontiers in molecular biosciences · 2021Article
- Low Protein Diets and Plant-Based Low Protein Diets: Do They Meet Protein Requirements of Patients with Chronic Kidney Disease?Nutrients · 2020Review
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Chronic kidney disease (CKD) is characterized by retention of uremic solutes. Compared to patients with non-dialysis dependent CKD, those requiring haemodialysis (HD) have increased morbidity and mortality. We wished to characterise metabolic patterns in CKD compared to HD patients using metabolomics. Prevalent non-HD CKD KDIGO stage 3b-4 and stage 5 HD outpatients were screened at a single tertiary hospital. Various liquid chromatography approaches hyphenated with mass spectrometry were used to identify 278 metabolites. Unsupervised and supervised data analyses were conducted to characterize metabolic patterns. 69 patients were included in the CKD group and 35 in the HD group. Unsupervised data analysis showed clear clustering of CKD, pre-dialysis (preHD) and post-dialysis (postHD) patients. Supervised data analysis revealed qualitative as well as quantitative differences in individual metabolites profiles between CKD, preHD and postHD states. An original metabolomics framework could discriminate between CKD stages and highlight HD effect based on 278 identified metabolites. Significant differences in metabolic patterns between CKD and HD patients were found overall as well as for specific metabolites. Those findings could explain clinical discrepancies between patients requiring HD and those with earlier stage of CKD.
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