title: Prediction of urinary protein markers in lupus nephritis.
abstract: BACKGROUND
  Lupus nephritis is divided into six classes and scored according to activity and chronicity indices based on histologic findings. Treatment differs based on the pathologic findings. Renal biopsy is currently the only way to accurately predict class and activity and chronicity indices. We propose to use patterns of abundance of urine proteins to identify class and disease indices.
  
  
  METHODS
  Urine was collected from 20 consecutive patients immediately prior to biopsy for evaluation of lupus nephritis. The International Society of Nephrology/Renal Pathology Society (ISN/RPS) class of lupus nephritis, activity, and chronicity indices were determined by a renal pathologist. Proteins were separated by two-dimensional gel electrophoresis. Artificial neural networks were trained on normalized spot abundance values.
  
  
  RESULTS
  Biopsy specimens were classified in the database according to ISN/RPS class, activity, and chronicity. Nine samples had characteristics of more than one class present. Receiver operating characteristic (ROC) curves of the trained networks demonstrated areas under the curve ranging from 0.85 to 0.95. The sensitivity and specificity for the ISN/RPS classes were class II 100%, 100%; III 86%, 100%; IV 100%, 92%; and V 92%, 50%. Activity and chronicity indices had r values of 0.77 and 0.87, respectively. A list of spots was obtained that provided diagnostic sensitivity to the analysis.
  
  
  CONCLUSIONS
  We have identified a list of protein spots that can be used to develop a clinical assay to predict ISN/RPS class and chronicity for patients with lupus nephritis. An assay based on antibodies against these spots could eliminate the need for renal biopsy, allow frequent evaluation of disease status, and begin specific therapy for patients with lupus nephritis.
authors.affiliation: Department of Medicine, Medical University of South Carolina and Ralph H. Johnson VA Medical Center, Charleston, Charleston, SC 29425, USA. arthurj@musc.edu
authors.forename: Jim C
authors.initials: JC
authors.lastname: Oates
authors.forename: Sanju
authors.initials: S
authors.lastname: Varghese
authors.forename: Alison M
authors.initials: AM
authors.lastname: Bland
authors.forename: Timothy P
authors.initials: TP
authors.lastname: Taylor
authors.forename: Sally E
authors.initials: SE
authors.lastname: Self
authors.forename: Romesh
authors.initials: R
authors.lastname: Stanislaus
authors.forename: Jonas S
authors.initials: JS
authors.lastname: Almeida
authors.forename: John M
authors.initials: JM
authors.lastname: Arthur
mesh_terms: D000328:Adult; D015415:Biomarkers / Q000652:urine*; D003950:Diagnostic Techniques, Urological / Q000295:instrumentation; D015180:Electrophoresis, Gel, Two-Dimensional; D006801:Humans; D008181:Lupus Nephritis / Q000175:diagnosis* / Q000652:urine*; D016571:Neural Networks, Computer; D011237:Predictive Value of Tests; D011507:Proteinuria / Q000175:diagnosis* / Q000652:urine*
chemical_list: D015415:Biomarkers