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

Michelle J. Pena*, Joachim Jankowski, Georg Heinze, Maria Kohl, Andreas Heinzel, Stephan J. L. Bakker, Ron T. Gansevoort, Peter Rossing, Dick de Zeeuw, Hiddo J. Lambers Heerspink, Vera Jankowski

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

19 Citations (Web of Science)

Abstract

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.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.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?
Original languageEnglish
Pages (from-to)2123-2132
JournalJournal of Hypertension
Volume33
Issue number10
DOIs
Publication statusPublished - Oct 2015

Keywords

  • albuminuria
  • biomarkers
  • hypertension
  • nephropathy
  • proteomics
  • type 2 diabetes

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