comprehensive mass spectrometry based biomarker discovery and validation platform as applied to diabetic kidney disease

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ID: 196323
2017
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Abstract
A protein biomarker discovery workflow was applied to plasma samples from patients at different stages of diabetic kidney disease. The proteomics platform produced a panel of significant plasma biomarkers that were statistically scrutinised against the current gold standard tests on an analysis of 572 patients. Five proteins were significantly associated with diabetic kidney disease defined by albuminuria, renal impairment (eGFR) and chronic kidney disease staging (CKD Stage ≥1, ROC curve of 0.77). The results prove the suitability and efficacy of the process used, and introduce a biomarker panel with the potential to improve diagnosis of diabetic kidney disease.
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bringans2017eupacomprehensive Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Scott D. Bringans;Jun Ito;Thomas Stoll;Kaye Winfield;Michael Phillips;Kirsten Peters;Wendy A. Davis;Timothy M.E. Davis;Richard J. Lipscombe
Journal technological and economic development of economy
Year 2017
DOI
10.1016/j.euprot.2016.12.001
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