ArticleThe journal of nutrition, health & aging2024
Identification of novel serum metabolic signatures to predict chronic kidney disease among Chinese elders using UPLC-Orbitrap-MS.
Article in The journal of nutrition, health & aging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 3 citations in OpenAlex.
- Current Appraisal and Gaps in Knowledge in Cardio-Kidney Metabolic Syndrome Definition.International journal of molecular sciences · 2026Review
- [n-butanol fraction of ethanol extract ofNan fang yi ke da xue xue bao = Journal of Southern Medical University · 2025Article
- Metabolic Rewiring and Post-Translational Modifications: Unlocking the Mechanisms of Bone Turnover in Osteoporosis.Aging and disease · 2025Review
- Metabolomic and Physiological Effects of a Cardiorenal Protective Diet Intervention in African American Adults with Chronic Kidney Disease.Metabolites · 2024Article
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Authors and funding
16 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundChronic kidney disease (CKD) is a major public health concern. However, validated and broadly applicable biomarkers for early CKD diagnosis are currently not available. We aimed to identify serum metabolic signatures at an early stage of CKD to provide a reference for future investigations into the early diagnostic biomarkers.
methodsSerum metabolites were extracted from 65 renal dysfunction (RD) patients and 121 healthy controls (discovery cohort: 12 RD patients and 55 health participants; validation cohort: 53 RD patients and 66 health participants). Metabolite extracts were analyzed by ultraperformance liquid chromatography coupled with quadrupole-electrostatic field orbital trap mass spectrometry (UPLC-QE-Orbitrap MS) for untargeted metabolomics. Orthogonal partial least squares-discriminant analysis (OPLS-DA) was performed to detect different compounds between groups. Receiver operating characteristic (ROC) curve analysis was carried out to determine the diagnostic value of the validated differential metabolites between groups. We referred to the Kyoto Encyclopedia of Gene and Genomes (KEGG) to elucidate the metabolic pathways of the validated differential metabolites.
resultsA total of 22 and 23 metabolites had significantly different abundances in the discovery and validation cohort, respectively. Six of them (creatinine, L-proline, citrulline, butyrylcarnitine, 1-methylhistidine, and valerylcarnitine) in the RD group was more abundant than that of the health group in both cohorts. The combination of the six validated differential metabolites were able to accurately detect RD (AUC 0.86). Three of the six metabolites are involved in the metabolism of arginine and proline.
conclusionsThe present study highlights that creatinine, L-proline, citrulline, butyrylcarnitine, 1-methylhistidine, and valerylcarnitine are metabolite indicators with potential predictive value for CKD.
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