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J Hypertens. 2015 Oct;33(10):2123-32. doi: 10.1097/HJH.0000000000000685.

Plasma proteomics classifiers improve risk prediction for renal disease in patients with hypertension or type 2 diabetes.

Author information

1
aDepartment of Clinical Pharmacy and Pharmacology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands bUniversity Hospital RWTH, Institute for Molecular Cardiovascular Research, Aachen, Germany cCenter for Medical Statistics, Informatics, And Intelligent Systems, Medical University of Vienna, Vienna, Austria dDepartment of Nephrology, University of Erlangen-Nürnberg, Erlangen, Germany eemergentec biodevelopment GmbH, Vienna, Austria fDepartment of Internal Medicine, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands gSteno Diabetes Center, Gentofte hAarhus University, Aarhus iCenter for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark.

Abstract

OBJECTIVE:

Micro and macroalbuminuria are strong risk factors for progression of nephropathy in patients with hypertension or type 2 diabetes. Early detection of progression to micro and macroalbuminuria may facilitate prevention and treatment of renal diseases. We aimed to develop plasma proteomics classifiers to predict the development of micro or macroalbuminuria in hypertension or type 2 diabetes.

METHODS:

Patients with hypertension (n = 125) and type 2 diabetes (n = 82) were selected for this case-control study from the Prevention of REnal and Vascular ENd-stage Disease cohort and the Steno Diabetes Center. Cases transitioned from normo to microalbuminuria, or from micro to macroalbuminuria. Controls, matched for age, sex, and baseline albuminuria stage, did not transition. Follow-up was 3.0 ± 0.9 years. Plasma proteomics profiles were measured by liquid chromatography-electrospray-trap mass-spectrometry. Classifiers were developed and cross-validated for prediction of transition in albuminuria stage. Improvement in risk prediction was tested on top of a reference model of baseline albuminuria, estimated glomerular filtration rate, and renin-angiotensin-aldosterone system intervention.

RESULTS:

In hypertensive patients, the classifier improved risk prediction for transition in albuminuria stage on top of the reference model (C-index from 0.69 to 0.78; P < 0.01). In type 2 diabetes, the classifier improved risk prediction for transition from micro to macroalbuminuria (C-index from 0.73 to 0.80; P = 0.04). In both diseases, the identified peptides were linked to pathways recognized to contribute to nephropathy, including fibrosis, inflammation, angiogenesis, and mineral metabolism.

CONCLUSIONS:

Plasma proteomics predict the transition in albuminuria stage beyond established renal risk markers in hypertension or type 2 diabetes. External validation is needed to assess reproducibility.

PMID:
26237555
DOI:
10.1097/HJH.0000000000000685
[Indexed for MEDLINE]

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