title: The feature selection approach for evaluation of potential rheumatoid arthritis markers using MALDI-TOF datasets.
abstract: BACKGROUND
  The selection of the most representative mass profiles, in rheumatoid arthritis (RA) serum samples was developed. This allows for selection and identification of potential biomarkers in RA serum samples.
  
  
  METHODS
  The RA and controls samples were analyzed using MALDI-TOF. Two different protein elution procedures utilizing ZipTips (E1 and E2) were examined. The statistical evaluation of data was performed using different feature selection (FS) methods in combination with different classifiers, while identification of selected masses was performed using MALDI-TOF-TOF.
  
  
  RESULTS
  Utilization of proposed statistical strategy allowed for the selection of different masses according to FS method and elution procedure. Obtained masses were further subjected for targeted identification. The panel of proteins were identified as potential markers. The role of these proteins was discussed in relation to pathomechanism of RA.
  
  
  CONCLUSIONS
  Application of advanced biostatistical analysis of obtained MALDI-TOF datasets, resulted with targeted selection of potential RA biomarkers. Five proteins were identified due the E1 procedure, and six proteins were identified due the E2 procedure, respectively. The panel of identified proteins suggest that presented statistical methodology and proteomic strategy was correct and gave valid results. Obtained results may contribute to development of clinically useful multicomponent diagnostic tool.
authors.affiliation: Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 6 Grunwaldzka Street, 60-780 Poznan, Poland. Electronic address: burbaniak@ump.edu.pl.
authors.forename: Bartosz
authors.initials: B
authors.lastname: Urbaniak
authors.affiliation: Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 6 Grunwaldzka Street, 60-780 Poznan, Poland. Electronic address: pnowicki.pn@gmail.com.
authors.forename: Piotr
authors.initials: P
authors.lastname: Nowicki
authors.affiliation: Clinics of Rheumatology and Rehabilitation, Poznan University of Medical Sciences, 28 Czerwca 1956 Street No. 135/147, 61-545 Poznan, Poland. Electronic address: dorotasikorska@ump.edu.pl.
authors.forename: Dorota
authors.initials: D
authors.lastname: Sikorska
authors.affiliation: Clinics of Rheumatology and Rehabilitation, Poznan University of Medical Sciences, 28 Czerwca 1956 Street No. 135/147, 61-545 Poznan, Poland. Electronic address: samborskiw@o2.pl.
authors.forename: Włodzimierz
authors.initials: W
authors.lastname: Samborski
authors.affiliation: Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 6 Grunwaldzka Street, 60-780 Poznan, Poland. Electronic address: zkokot@ump.edu.pl.
authors.forename: Zenon J
authors.initials: ZJ
authors.lastname: Kokot
mesh_terms: D000328:Adult; D000368:Aged; D001172:Arthritis, Rheumatoid / Q000097:blood* / Q000175:diagnosis*; D015415:Biomarkers / Q000097:blood*; D001798:Blood Proteins / Q000032:analysis*; D016022:Case-Control Studies; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D040901:Proteomics / Q000379:methods; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods*; D055815:Young Adult
chemical_list: D015415:Biomarkers; D001798:Blood Proteins
keywords: Biomarkers discovery; Feature selection statistical strategy; MALDI-TOF; Peptide profiling; Rheumatoid arthritis