Serum metabolites predict response to angiotensin II receptor blockers in patients with diabetes mellitus

Michelle J. Pena, Andreas Heinzel, Peter Rossing, Hans-Henrik Parving, Guido Dallmann, Kasper Rossing, Steen Andersen, Bernd Mayer, Hiddo J. L. Heerspink*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Background: Individual patients show a large variability in albuminuria response to angiotensin receptor blockers (ARB). Identifying novel biomarkers that predict ARB response may help tailor therapy. We aimed to discover and validate a serum metabolite classifier that predicts albuminuria response to ARBs in patients with diabetes mellitus and micro- or macroalbuminuria.

Methods: Liquid chromatography-tandem mass spectrometry metabolomics was performed on serum samples. Data from patients with type 2 diabetes and microalbuminuria (n = 49) treated with irbesartan 300 mg/day were used for discovery. LASSO and ridge regression were performed to develop the classifier. Improvement in albuminuria response prediction was assessed by calculating differences in R-2 between a reference model of clinical parameters and a model with clinical parameters and the classifier. The classifier was externally validated in patients with type 1 diabetes and macroalbuminuria (n = 50) treated with losartan 100 mg/day. Molecular process analysis was performed to link metabolites to molecular mechanisms contributing to ARB response.

Results: In discovery, median change in urinary albumin excretion (UAE) was -42 % [Q1-Q3: -69 to -8]. The classifier, consisting of 21 metabolites, was significantly associated with UAE response to irbesartan (p <0.001) and improved prediction of UAE response on top of the clinical reference model (R2 increase from 0.10 to 0.70; p <0.001). In external validation, median change in UAE was -43 % [Q1-Q35: -63 to -23]. The classifier improved prediction of UAE response to losartan (R2 increase from 0.20 to 0.59; p <0.001). Specifically ADMA impacting eNOS activity appears to be a relevant factor in ARB response.

Conclusions: A serum metabolite classifier was discovered and externally validated to significantly improve prediction of albuminuria response to ARBs in diabetes mellitus.

Original languageEnglish
Article number203
Pages (from-to)203
Number of pages11
JournalJournal of translational medicine
Issue number1
Publication statusPublished - 5-Jul-2016


  • Metabolomics
  • Albuminuria
  • ARB response
  • RISK

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