Virtual diagnosis of diabetic nephropathy using metabolomics in place of kidney biopsy: The DIAMOND study
Authors' conclusion
The combination of clinical factors and urinary metabolites is highly valuable for predicting biopsy-confirmed DN in patients with T2DM.
Study context
- Population
- Patients with T2D who underwent kidney biopsy, January 2010–October 2020, single centre11 per metabolomics group
- Participants
- 126 patients
- Exposure
- Biopsy-confirmed diabetic nephropathy (DN) vs IgA nephropathy, membranous nephropathy and healthy controls
- Outcome
- Prediction of biopsy-confirmed DN by clinical factors and urinary metabolites
Methodological detailsdiagnostic prediction study, single-centre, age- and sex-matched metabolomics groups
- Diagnostic prediction study
- Single-centre
- Age- and sex-matched metabolomics groups
Main finding
As reported in the abstract
Predictors of biopsy-confirmed DN
Urinary metabolites predictive of DN (variable importance in projection scores > 1): alanine, choline, N-phenylacetylglycine, trigonelline
4
AUC, multivariate ROC, clinical factors + urinary metabolites
1.000
Observational data: associations, not effects.
Parts of this Brief are withheld: the automatic checks could not confirm them against the abstract.
Original publication
Virtual diagnosis of diabetic nephropathy using metabolomics in place of kidney biopsy: The DIAMOND study. Diabetes Res Clin Pract. Published 28 October 2023. doi:10.
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