title: Two classifiers based on serum peptide pattern for prediction of HBV-induced liver cirrhosis using MALDI-TOF MS.
abstract: Chronic infection with hepatitis B virus (HBV) is associated with the majority of cases of liver cirrhosis (LC) in China. Although liver biopsy is the reference method for evaluation of cirrhosis, it is an invasive procedure with inherent risk. The aim of this study is to discover novel noninvasive specific serum biomarkers for the diagnosis of HBV-induced LC. We performed bead fractionation/MALDI-TOF MS analysis on sera from patients with LC. Thirteen feature peaks which had optimal discriminatory performance were obtained by using support-vector-machine-(SVM-) based strategy. Based on the previous results, five supervised machine learning methods were employed to construct classifiers that discriminated proteomic spectra of patients with HBV-induced LC from those of controls. Here, we describe two novel methods for prediction of HBV-induced LC, termed LC-NB and LC-MLP, respectively. We obtained a sensitivity of 90.9%, a specificity of 94.9%, and overall accuracy of 93.8% on an independent test set. Comparisons with the existing methods showed that LC-NB and LC-MLP held better accuracy. Our study suggests that potential serum biomarkers can be determined for discriminating LC and non-LC cohorts by using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. These two classifiers could be used for clinical practice in HBV-induced LC assessment.
authors.affiliation: Department of Laboratory Medicine, Jinan Military General Hospital, Jinan, Shandong 250031, China.
authors.forename: Yuan
authors.initials: Y
authors.lastname: Cao
authors.forename: Kun
authors.initials: K
authors.lastname: He
authors.forename: Ming
authors.initials: M
authors.lastname: Cheng
authors.forename: Hai-Yan
authors.initials: HY
authors.lastname: Si
authors.forename: He-Lin
authors.initials: HL
authors.lastname: Zhang
authors.forename: Wei
authors.initials: W
authors.lastname: Song
authors.forename: Ai-Ling
authors.initials: AL
authors.lastname: Li
authors.forename: Cheng-Jin
authors.initials: CJ
authors.lastname: Hu
authors.forename: Na
authors.initials: N
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D015415:Biomarkers / Q000097:blood; D016022:Case-Control Studies; D002681:China; D019295:Computational Biology / Q000379:methods; D006509:Hepatitis B / Q000097:blood* / Q000150:complications; D006515:Hepatitis B virus; D006801:Humans; D008103:Liver Cirrhosis / Q000097:blood* / Q000150:complications / Q000821:virology; D010455:Peptides / Q000097:blood* / Q000737:chemistry; D040901:Proteomics / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods*; D060388:Support Vector Machine
chemical_list: D015415:Biomarkers; D010455:Peptides