ReviewThe Korean journal of internal medicine2024
Steps to understanding diabetes kidney disease: a focus on metabolomics.
Review in The Korean journal of internal medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Biomarkers in Diabetic Kidney Disease: Early Detection, Prognostic Assessment, and Integration with Multi-Omics Signatures.Life (Basel, Switzerland) · 2026Review
- Clinical benefits and future directions of medium cut-off membranes in hemodialysis: a comprehensive review.The Korean journal of internal medicine · 2025Review
- Crosstalk between ferroptosis and innate immune in diabetic kidney disease: mechanisms and therapeutic implications.Frontiers in immunology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diabetic nephropathy (DN), a leading cause of chronic kidney disease and end-stage kidney disease (ESKD), poses global health challenges given its increasing prevalence. DN increases the risk of mortality and cardiovascular events. Early identification and appropriate DN management are crucial. However, current diagnostic methods rely on general traditional markers, highlighting the need for DN-specific diagnostics. Metabolomics, the study of small molecules produced by metabolic activity, promises to identify specific biomarkers that distinguish DN from other kidney diseases, decode the underlying disease mechanisms, and predict the disease course. Profound changes in metabolic pathways are apparent in individuals with DN, alterations in the tricarboxylic acid cycle and amino acid and lipid metabolism, suggestive of mitochondrial dysfunction. Metabolomics aids prediction of chronic kidney disease progression; several metabolites serve as indicators of renal functional decline and the risk of ESKD. Integration of such information with other omics data will further enhance our understanding of DN, paving the way to personalized treatment. In summary, metabolomics and multi-omics offer valuable insights into DN and are promising diagnostic and prognostic tools.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.