title: Predicting diabetic nephropathy by serum proteomic profiling in patients with type 2 diabetes.
abstract: OBJECTIVE
  The purpose of this work is to examine the serum proteomic profiles associated with the subsequent development of diabetic nephropathy (DN) in patients with type 2 diabetes and to develop and validate a decision tree based on the profiles to predict the risk of DN in advance by albuminuria.
  
  
  METHODS
  Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry was used to obtain the proteomic profiles from baseline serum samples of 84 patients with type 2 diabetes with normal albuminuria, including 42 case subjects who developed DN after 4 years and 42 control subjects who remained normoalbuminuric over the same 4 years. From signatures of protein mass, a decision tree was established for predicting DN.
  
  
  RESULTS
  At baseline, urinary albumin/creatinine ratio was similar between the case and control groups. The intensities of 5 peaks detected by CM10 chips appeared up-regulated, whereas 18 peaks were down-regulated more than twofold in the case group than compared with the control group in the training set. An optimum discriminatory decision tree for case subjects created with four nodes using four distinct masses was challenged with testing set. The positive predictive value was 77.8% (7/9), and the negative predictive value was 72.7% (8/11).
  
  
  CONCLUSIONS
  We developed and validated a decision tree to predict DN in patients with type 2 diabetes.
authors.affiliation: Institute of Endocrinology and Diabetology, Department of Endocrinology, Huashan Hospital, Fudan University, Shanghai, 200040, P.R. China.
authors.forename: Yehong
authors.initials: Y
authors.lastname: Yang
authors.affiliation: Institute of Endocrinology and Diabetology, Department of Endocrinology, Huashan Hospital, Fudan University, Shanghai, 200040, P.R. China.
authors.forename: Shuo
authors.initials: S
authors.lastname: Zhang
authors.affiliation: Institute of Endocrinology and Diabetology, Department of Endocrinology, Huashan Hospital, Fudan University, Shanghai, 200040, P.R. China.
authors.forename: Bin
authors.initials: B
authors.lastname: Lu
authors.affiliation: Institute of Endocrinology and Diabetology, Department of Endocrinology, Huashan Hospital, Fudan University, Shanghai, 200040, P.R. China.
authors.forename: Wei
authors.initials: W
authors.lastname: Gong
authors.affiliation: Institute of Endocrinology and Diabetology, Department of Endocrinology, Huashan Hospital, Fudan University, Shanghai, 200040, P.R. China.
authors.forename: Xuehong
authors.initials: X
authors.lastname: Dong
authors.affiliation: Institute of Endocrinology and Diabetology, Department of Endocrinology, Huashan Hospital, Fudan University, Shanghai, 200040, P.R. China.
authors.forename: Xiaoyan
authors.initials: X
authors.lastname: Song
authors.affiliation: Institute of Endocrinology and Diabetology, Department of Endocrinology, Huashan Hospital, Fudan University, Shanghai, 200040, P.R. China.
authors.forename: Weiwei
authors.initials: W
authors.lastname: Zhao
authors.affiliation: Proteome research section, Liver Cancer Institute, Zhongshan Hospital, Fudan University, 136 Yi Xue Yuan Road, Shanghai, 200032, P.R. China.
authors.forename: Jiefeng
authors.initials: J
authors.lastname: Cui
authors.affiliation: Proteome research section, Liver Cancer Institute, Zhongshan Hospital, Fudan University, 136 Yi Xue Yuan Road, Shanghai, 200032, P.R. China.
authors.forename: Yinkun
authors.initials: Y
authors.lastname: Liu
authors.affiliation: , 12 Middle Wurumuqi Road, Shanghai, 200040, P.R. China. renminghu@fudan.edu.cn.
authors.forename: Renming
authors.initials: R
authors.lastname: Hu
mesh_terms: D001798:Blood Proteins / Q000378:metabolism*; D015984:Causality; D002681:China / Q000453:epidemiology; D015897:Comorbidity; D020000:Decision Support Systems, Clinical; D003920:Diabetes Mellitus / Q000097:blood* / Q000175:diagnosis / Q000453:epidemiology*; D003928:Diabetic Nephropathies / Q000097:blood* / Q000175:diagnosis / Q000453:epidemiology*; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D005260:Female; D020869:Gene Expression Profiling / Q000706:statistics & numerical data; D006801:Humans; D015994:Incidence; D008137:Longitudinal Studies; D008297:Male; D011379:Prognosis; D020543:Proteome / Q000378:metabolism*; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods; D012680:Sensitivity and Specificity
chemical_list: D001798:Blood Proteins; D020543:Proteome
keywords: Decision tree; Diabetic nephropathy; Prediction; Proteomic profiling; Surface-enhanced laser desorption/ionization