title: A urinary peptide biomarker set predicts worsening of albuminuria in type 2 diabetes mellitus.
abstract: OBJECTIVE
  Microalbuminuria is considered the first clinical sign of kidney dysfunction and is associated with a poor renal and cardiovascular prognosis in type 2 diabetes. Detection of patients who are prone to develop micro- or macroalbuminuria may represent an effective strategy to start or optimise therapeutic intervention. Here we assessed the value of a urinary proteomic-based risk score (classifier) in predicting the development and progression of microalbuminuria.
  
  
  METHODS
  We conducted a prospective case-control study. Cases (n = 44) and controls (n = 44) were selected from the PREVEND (Prevention of Renal and Vascular End-stage Disease) study and from the Steno Diabetes Center (Gentofte, Denmark). Cases were defined by transition from normo- to microalbuminuria or from micro- to macroalbuminuria over a follow-up of 3 years. Controls with no transitions in albuminuria were pair-matched for age, sex and albuminuria status. A model for the progression of albuminuria was built using a proteomic classifier based on 273 urinary peptides.
  
  
  RESULTS
  The proteomic classifier was independently associated with transition to micro- or macroalbuminuria (OR 1.35 [95% CI 1.02, 1.79], p = 0.035). The classifier predicted the development and progression of albuminuria on top of albuminuria and estimated GFR (eGFR, area under the receiver operating characteristic [ROC] curve increase of 0.03, p = 0.002; integrated discrimination index [IDI]: 0.105, p = 0.002). Fragments of collagen and α-2-HS-glycoprotein showed significantly different expression between cases and controls.
  
  
  CONCLUSIONS
  Although limited by the relatively small sample size, these results suggest that analysis of a urinary biomarker set enables early renal risk assessment in patients with diabetes. Further work is required to confirm the role of urinary proteomics in the prevention of renal failure in diabetes.
authors.affiliation: Department of Clinical Pharmacology, University Medical Center Groningen, University of Groningen, Antonius Deusinglaan 1, Groningen, the Netherlands. s.s.roscioni@umcg.nl
authors.forename: S S
authors.initials: SS
authors.lastname: Roscioni
authors.forename: D
authors.initials: D
authors.lastname: de Zeeuw
authors.forename: M E
authors.initials: ME
authors.lastname: Hellemons
authors.forename: H
authors.initials: H
authors.lastname: Mischak
authors.forename: P
authors.initials: P
authors.lastname: Zürbig
authors.forename: S J L
authors.initials: SJ
authors.lastname: Bakker
authors.forename: R T
authors.initials: RT
authors.lastname: Gansevoort
authors.forename: H
authors.initials: H
authors.lastname: Reinhard
authors.forename: F
authors.initials: F
authors.lastname: Persson
authors.forename: M
authors.initials: M
authors.lastname: Lajer
authors.forename: P
authors.initials: P
authors.lastname: Rossing
authors.forename: H J
authors.initials: HJ
authors.lastname: Lambers Heerspink
mesh_terms: D000368:Aged; D000419:Albuminuria / Q000473:pathology / Q000652:urine*; D015415:Biomarkers / Q000652:urine*; D016022:Case-Control Studies; D003924:Diabetes Mellitus, Type 2 / Q000473:pathology / Q000652:urine*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010455:Peptides / Q000652:urine*; D011446:Prospective Studies; D040901:Proteomics / Q000379:methods
chemical_list: D015415:Biomarkers; D010455:Peptides