Article open access publication

Urinary proteomics for prediction of mortality in patients with type 2 diabetes and microalbuminuria

Cardiovascular Diabetology, Springer Nature, ISSN 1475-2840

Volume 17, 1, 2018

DOI:10.1186/s12933-018-0697-9, Dimensions: pub.1103148600, PMC: PMC5889591, PMID: 29625564,



  1. (1) University of Glasgow, grid.8756.c
  2. (2) Steno Diabetes Center, grid.419658.7, Capital Region
  3. (3) Mosaiques diagnostics and therapeutics AG (Germany), grid.421873.b
  4. (4) Aarhus University, grid.7048.b, AU
  5. (5) University of Copenhagen, grid.5254.6, KU


United Kingdom






BACKGROUND: The urinary proteomic classifier CKD273 has shown promise for prediction of progressive diabetic nephropathy (DN). Whether it is also a determinant of mortality and cardiovascular disease in patients with microalbuminuria (MA) is unknown. METHODS: Urine samples were obtained from 155 patients with type 2 diabetes and confirmed microalbuminuria. Proteomic analysis was undertaken using capillary electrophoresis coupled to mass spectrometry to determine the CKD273 classifier score. A previously defined CKD273 threshold of 0.343 for identification of DN was used to categorise the cohort in Kaplan-Meier and Cox regression models with all-cause mortality as the primary endpoint. Outcomes were traced through national health registers after 6 years. RESULTS: CKD273 correlated with urine albumin excretion rate (UAER) (r = 0.481, p = <0.001), age (r = 0.238, p = 0.003), coronary artery calcium (CAC) score (r = 0.236, p = 0.003), N-terminal pro-brain natriuretic peptide (NT-proBNP) (r = 0.190, p = 0.018) and estimated glomerular filtration rate (eGFR) (r = 0.265, p = 0.001). On multivariate analysis only UAER (β = 0.402, p < 0.001) and eGFR (β = - 0.184, p = 0.039) were statistically significant determinants of CKD273. Twenty participants died during follow-up. CKD273 was a determinant of mortality (log rank [Mantel-Cox] p = 0.004), and retained significance (p = 0.048) after adjustment for age, sex, blood pressure, NT-proBNP and CAC score in a Cox regression model. CONCLUSION: A multidimensional biomarker can provide information on outcomes associated with its primary diagnostic purpose. Here we demonstrate that the urinary proteomic classifier CKD273 is associated with mortality in individuals with type 2 diabetes and MA even when adjusted for other established cardiovascular and renal biomarkers.


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