ArticleClinical and translational science2012
A pilot metabolic profiling study in serum of patients with chronic kidney disease based on (1) H-NMR-spectroscopy.
Article in Clinical and translational science, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Metabolomic Prediction of Cadmium Nephrotoxicity in the SnailMetabolites · 2024Article
- Blood biomarkers improve the prediction of prevalent and incident severe chronic kidney disease.Journal of nephrology · 2024Article
- Interpretable machine learning identifies metabolites associated with glomerular filtration rate in type 2 diabetes patients.Frontiers in endocrinology · 2024Article
- Metabolomic Investigation of Blood and Urinary Amino Acids and Derivatives in Patients with Type 2 Diabetes Mellitus and Early Diabetic Kidney Disease.Biomedicines · 2023Article
- Metabolomics profiling distinctively identified end-stage renal disease patients from chronic kidney disease patients.Scientific reports · 2023Article
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- The Role of Betaine in Patients With Chronic Kidney Disease: a Narrative Review.Current nutrition reports · 2022Review
- Blood Levels of Endocannabinoids, Oxylipins, and Metabolites Are Altered in Hemodialysis Patients.International journal of molecular sciences · 2022Article
- Change in Urinary Myoinositol/Citrate Ratio Associates with Progressive Loss of Renal Function in ADPKD Patients.American journal of nephrology · 2022Article
- Isolation, Characterization, and Metabolic Profiling ofMycobiology · 2022Article
- Estimating Glomerular Filtration Rate from Serum Myo-Inositol, Valine, Creatinine and Cystatin C.Diagnostics (Basel, Switzerland) · 2021Article
- Healthy and Chronic Kidney Disease (CKD) Dogs Have Differences in Serum Metabolomics and Renal Diet May Have Slowed Disease Progression.Metabolites · 2021Article
- Renal function is associated with plasma trimethylamine-N-oxide, choline, L-carnitine and betaine: a pilot study.International urology and nephrology · 2021Article
- Serum Myo-Inositol, Dimethyl Sulfone, and Valine in Combination with Creatinine Allow Accurate Assessment of Renal Insufficiency-A Proof of Concept.Diagnostics (Basel, Switzerland) · 2021Article
- Plasma metabolites associated with chronic kidney disease and renal function in adults from the Baltimore Longitudinal Study of Aging.Metabolomics : Official journal of the Metabolomic Society · 2021Article
- Metabolomics: An emerging potential approach to decipher critical illnesses.Biophysical chemistry · 2020Review
- Machine learning distilled metabolite biomarkers for early stage renal injury.Metabolomics : Official journal of the Metabolomic Society · 2019Article
- Identification of serum metabolites associating with chronic kidney disease progression and anti-fibrotic effect of 5-methoxytryptophan.Nature communications · 2019 · on this mapArticle
- Review
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6 authors.
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Abstract
backgroundChronic kidney disease (CKD) is the end point of a number of renal and systemic diseases. The metabolomics with a highly multiplexed and efficient manner is a challenging goal in nephrology.
methodsA (1) H-NMR based metabolomics approach was applied to establish a human CKD serum metabolic profile. Serum samples were obtained from CKD patients with four stages (N= 80) and healthy controls (N= 28). The data acquired by CMPG spectrum were further processed by pattern recognition (PR) analysis. Principal components analysis (PCA) and partial least-squares-discriminant analysis (PLS-DA) was capable of clustering the disease groups and establishing disease-specific metabolites profile.
resultsThe classification models could grade CKD patients with considerably high value of Q(2) and R(2) . The significant endogenous metabolites that contributed to distinguish CKD in different stages included the products of glycolysis (glucose, lactate), amino acids (valine, alanine, glutamate, glycine), organic osmolytes (betaine, myo-inositol, taurine, glycerophosphcholine), and so on. Based on these metabolites, the model for diagnosing patients with CKD achieved the sensitivity and specificity of 100%.
conclusionThe study illustrated that serum metabolic profile was altered in response to renal dysfunction and the progression of CKD. The identified metabolic biomarkers may provide useful information for the diagnosis of CKD, especially in early stages.
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