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

Scott D. Bringans; Jun Ito; Thomas Stoll; Kaye Winfield; Michael Phillips; Kirsten Peters; Wendy A. Davis; Timothy M E Davis; Richard J. Lipscombe

doi:10.1016/j.euprot.2016.12.001

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

Scott D. Bringans, Jun Ito, Thomas Stoll, Kaye Winfield, Michael Phillips, Kirsten Peters, Wendy A. Davis, Timothy M E Davis, Richard J. Lipscombe

UWA Medical School

Research output: Contribution to journal › Article › peer-review

27 Citations (Scopus)

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.

Original language	English
Pages (from-to)	1-10
Number of pages	10
Journal	EuPA Open Proteomics
Volume	14
DOIs	https://doi.org/10.1016/j.euprot.2016.12.001
Publication status	Published - 1 Mar 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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AU - Phillips, Michael

AU - Peters, Kirsten

AU - Davis, Wendy A.

AU - Davis, Timothy M E

AU - Lipscombe, Richard J.

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AB - 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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Comprehensive mass spectrometry based biomarker discovery and validation platform as applied to diabetic kidney disease

Abstract

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