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


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-12

AUTHORS

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

ABSTRACT

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 (R(2) 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 (R(2) 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. More... »

PAGES

203

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s12967-016-0960-3

DOI

http://dx.doi.org/10.1186/s12967-016-0960-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1011805145

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/27378474


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    "description": "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.\nMETHODS: Liquid chromatography-tandem mass spectrometry metabolomics was performed on serum samples. Data from patients with type 2 diabetes and microalbuminuria (n\u00a0=\u00a049) treated with irbesartan 300\u00a0mg/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\u00a0=\u00a050) treated with losartan 100\u00a0mg/day. Molecular process analysis was performed to link metabolites to molecular mechanisms contributing to ARB response.\nRESULTS: In discovery, median change in urinary albumin excretion (UAE) was -42\u00a0% [Q1-Q3: -69 to -8]. The classifier, consisting of 21 metabolites, was significantly associated with UAE response to irbesartan (p\u00a0<\u00a00.001) and improved prediction of UAE response on top of the clinical reference model (R(2) increase from 0.10 to 0.70; p\u00a0<\u00a00.001). In external validation, median change in UAE was -43\u00a0% [Q1-Q35: -63 to -23]. The classifier improved prediction of UAE response to losartan (R(2) increase from 0.20 to 0.59; p\u00a0<\u00a00.001). Specifically ADMA impacting eNOS activity appears to be a relevant factor in ARB response.\nCONCLUSIONS: A serum metabolite classifier was discovered and externally validated to significantly improve prediction of albuminuria response to ARBs in diabetes mellitus.", 
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