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Dynamics of Urine Metabolomics and Tubular Inflammatory Cytokines in Type 1 Diabetes Across Disease Durations

  • Tzu Chi University
  • Chang Gung University
  • Chang Gung Memorial Hospital

Research output: Contribution to journalJournal Article peer-review

1 Scopus citations

Abstract

Background/Objectives: Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by sustained inflammation, leading to diabetic kidney disease (DKD). This study investigated urinary tubular injury biomarkers and metabolomic profiles in relation to albuminuria and renal function across varying durations of T1D. Methods: A cross-sectional analysis was conducted in 247 youth-onset T1D patients categorized by disease duration: short ≤ 5 years (T1D-S, n = 62), medium 6–10 years (T1D-M, n = 67), and long > 10 years (T1D-L, n = 118). Urinary cytokines (MCP-1, KIM-1, NGAL) were measured by ELISA. Metabolomic profiling was performed using 1H-NMR spectroscopy. Results: Urinary MCP-1/Cr, KIM-1/Cr, and NGAL/Cr levels were significantly elevated in T1D patients compared with non-diabetic controls, but did not correlate with disease duration. Metabolomic profiling identified distinct urinary signatures across T1D duration. Specifically, N-acetylcysteine (NAC) and N-delta-acetylornithine (NAO) increased progressively, while N-acetylaspartate (NAA) and pyruvic acid decreased with longer disease duration. These four metabolites remained statistically significant after both based on Mann–Whitney tests with false discovery rate (FDR) correction (q < 0.05) and application of a conservative alpha threshold (p < 0.01), suggesting potential disruptions in amino acid and carbohydrate metabolism. Conclusions: Urinary biomarkers (MCP-1/Cr, NGAL/Cr, and KIM-1/Cr) are sensitive indicators of subclinical kidney dysfunction in T1D patients, often preceding albuminuria. Alterations in amino acid-related metabolites (NAC, NAA, and NAO) and pyruvate highlight possible metabolic disturbances associated with T1D duration and oxidative stress. However, given the cross-sectional design, longitudinal studies are needed to confirm causality and clarify their predictive value in DKD progression.

Original languageEnglish
Article number734
JournalMetabolites
Volume15
Issue number11
DOIs
StatePublished - 10 11 2025

Bibliographical note

Publisher Copyright:
© 2025 by the authors.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • amino acid metabolomics
  • diabetic kidney disease
  • Type 1 diabetes
  • urinary tubular biomarkers

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