title: Bioinformatic analysis of the urine proteome of acute allograft rejection.
abstract: The urinary proteome in health and disease attracts increasing attention because of the potential diagnostic and pathophysiologic biomarker information carried by specific excreted proteins or their constellations. This cross-sectional study aimed to analyze the urinary proteome in patients with biopsy-proven acute rejection (n = 23) compared with transplant recipients with stable graft function (n = 22) and healthy volunteers (n = 20) and to correlate this with clinical, morphologic, and laboratory data. Urine samples were preadsorbed on four different protein chip surfaces, and the protein composition was analyzed using a surface-enhanced laser desorption/ionization time-of-flight mass spectrometer platform. The data were analyzed using two independent approaches to sample classification. Patients who experienced acute rejection could be distinguished from stable patients with a sensitivity of 90.5 to 91.3% and a specificity of 77.2 to 83.3%, depending on the classifier used. Protein masses that were important in constructing the classification algorithms included those of mass 2003.0, 2802.6, 4756.3, 5872.4, 6990.6, 19,018.8, and 25,665.7 Da. Normal urine was distinguished from transplant urine using a protein marker of mass 78,531.2 Da with both a sensitivity and a specificity of 100%. In conclusion, (1) urine proteome in transplant recipients with stable graft function was significantly different from healthy control subjects, and (2) acute rejections were characterized by a constellation of excreted proteins. Analysis of the urinary proteome may expedite the noninvasive prediction of acute graft rejection, thus importantly assisting in establishing the diagnosis.
authors.affiliation: Renal Research Institute and Division of Nephrology, Department of Medicine, Room C06, Basic Science Building, New York Medical College, 95 Grasslands Road, Valhalla, NY 10595, USA. edmond_oriordan@nymc.edu
authors.forename: Edmond
authors.initials: E
authors.lastname: O'Riordan
authors.forename: Tatyana N
authors.initials: TN
authors.lastname: Orlova
authors.forename: Jianfeng
authors.initials: J
authors.lastname: Mei J
authors.forename: Khalid
authors.initials: K
authors.lastname: Butt
authors.forename: Praveen M
authors.initials: PM
authors.lastname: Chander
authors.forename: Shafiq
authors.initials: S
authors.lastname: Rahman
authors.forename: Muong
authors.initials: M
authors.lastname: Mya
authors.forename: Rena
authors.initials: R
authors.lastname: Hu
authors.forename: Jahangir
authors.initials: J
authors.lastname: Momin
authors.forename: Elizabeth W
authors.initials: EW
authors.lastname: Eng
authors.forename: Dierk J
authors.initials: DJ
authors.lastname: Hampel
authors.forename: Bertram
authors.initials: B
authors.lastname: Hartman
authors.forename: Matthias
authors.initials: M
authors.lastname: Kretzler
authors.forename: Veronica
authors.initials: V
authors.lastname: Delaney
authors.forename: Michael S
authors.initials: MS
authors.lastname: Goligorsky
mesh_terms: D000208:Acute Disease; D019295:Computational Biology; D005260:Female; D006084:Graft Rejection / Q000503:physiopathology*; D006801:Humans; D016030:Kidney Transplantation; D008297:Male; D040081:Protein Array Analysis; D040901:Proteomics; D014184:Transplantation, Homologous; D014556:Urine / Q000737:chemistry*