Urinary Metabolomics Data for Diabetic Kidney Disease Prognosis

figshare hosts a metabolomics study with data from 96 patients with biopsy-confirmed diabetic nephropathy, 76 patients with type 2 diabetes, and 79 healthy controls. Untargeted analysis identified 148 metabolites, with 101 showing significant differences across groups. The research identifies urinary isoleucine as a key prognostic biomarker for renal survival.

Use Cases

• Analyze associations between urinary isoleucine levels and renal histological scores like tubular injury or interstitial fibrosis.
• Validate the prognostic power of urinary isoleucine for stratifying renal survival in diabetic nephropathy patients using Cox regression models.
• Compare metabolite profiles across the HC–T2D–T2DN continuum to identify progressive changes in branched-chain amino acid pathways.
• Perform targeted quantification to confirm the specificity of urinary versus plasma isoleucine as a biomarker for disease progression.

Strengths

• Clinical validation with 251 total participants, including a biopsy-confirmed patient cohort.
• Analysis of 148 detected metabolites, with 101 showing significant differential expression.
• Prognostic findings are supported by correlation with four specific renal histological scores.

Limitations

• Dataset is small at 1.9 MB, contained within a DOCX file, limiting direct computational analysis.
• No structured tabular data (rows/columns) or sample data is available for immediate machine learning use.
• Findings are specific to type 2 diabetic nephropathy and may not generalize to other kidney diseases.

Provenance

Source

figshare, authored by Yufei Li.

Collection Method

Untargeted urinary metabolomics performed on patient samples, with targeted validation.

Freshness

Last updated March 2026.