ArticleJournal of diabetes investigation2023
Ultra-high performance liquid chromatography coupled to tandem mass spectrometry-based metabolomics study of diabetic distal symmetric polyneuropathy.
Article in Journal of diabetes investigation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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.
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Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- Associations between circulating metabolites and pca: a bidirectional two-sample Mendelian randomization study.Discover oncology · 2025Article
- Metabolomics in Pathogenic Pathways and Targeted Therapies for Diabetic Neuropathy: A Comprehensive Review.Metabolites · 2025Review
- Advances in diagnostic methods for early-stage diabetic polyneuropathy.Journal of diabetes investigation · 2024Article
- Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
AIMS/
introductionDistal symmetric polyneuropathy (DSPN) is a common complication of type 2 diabetes mellitus, but the underlining mechanisms have not yet been elucidated. The current study was designed to screen the feature metabolites classified as potential biomarkers, and to provide deeper insights into the underlying distinctive metabolic changes during disease progression. MATERIALS AND
methodsPlasma metabolite profiles were obtained by the ultra-high liquid chromatography coupled to tandem mass spectrometry method from healthy control participants, patients with type 2 diabetes mellitus and patients with DSPN. Potential biomarkers were selected through comprehensive analysis of statistically significant differences between groups.
resultsOverall, 938 metabolites were identified. Among them, 12 metabolites (dimethylarginine, N6-acetyllysine, N-acetylhistidine, N,N,N-trimethyl-alanylproline betaine, cysteine, 7-methylguanine, N6-carbamoylthreonyladenosine, pseudouridine, 5-methylthioadenosine, N2,N2-dimethylguanosine, aconitate and C-glycosyl tryptophan) were identified as the specific biomarkers. The content of 12 metabolites were significantly higher in the DSPN group compared with the other two groups. Additionally, they showed good performance to discriminate the DSPN state. Correlation analyses showed that the levels of 12 metabolites might be more closely related to the glucose metabolic changes, followed by the levels of lipid metabolism.
conclusionsThe finding of the 12 signature metabolites might provide a novel perspective for the pathogenesis of DSPN. Future studies are required to test this observation further.
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