title: A serum protein-based algorithm for the detection of Alzheimer disease.
abstract: OBJECTIVE
  To develop an algorithm that separates patients with Alzheimer disease (AD) from controls.
  
  
  METHODS
  Longitudinal case-control study.
  
  
  METHODS
  The Texas Alzheimer's Research Consortium project. Patients  We analyzed serum protein-based multiplex biomarker data from 197 patients diagnosed with AD and 203 controls. Main Outcome Measure  The total sample was randomized equally into training and test sets and random forest methods were applied to the training set to create a biomarker risk score.
  
  
  RESULTS
  The biomarker risk score had a sensitivity and specificity of 0.80 and 0.91, respectively, and an area under the curve of 0.91 in detecting AD. When age, sex, education, and APOE status were added to the algorithm, the sensitivity, specificity, and area under the curve were 0.94, 0.84, and 0.95, respectively.
  
  
  CONCLUSIONS
  These initial data suggest that serum protein-based biomarkers can be combined with clinical information to accurately classify AD. A disproportionate number of inflammatory and vascular markers were weighted most heavily in the analyses. Additionally, these markers consistently distinguished cases from controls in significant analysis of microarray, logistic regression, and Wilcoxon analyses, suggesting the existence of an inflammatory-related endophenotype of AD that may provide targeted therapeutic opportunities for this subset of patients.
authors.affiliation: Texas Tech University Health Science Center, Department of Neurology, Lubbock, TX 79430, USA. sid.obryant@ttuhsc.edu
authors.forename: Sid E
authors.initials: SE
authors.lastname: O'Bryant
authors.forename: Guanghua
authors.initials: G
authors.lastname: Xiao
authors.forename: Robert
authors.initials: R
authors.lastname: Barber
authors.forename: Joan
authors.initials: J
authors.lastname: Reisch
authors.forename: Rachelle
authors.initials: R
authors.lastname: Doody
authors.forename: Thomas
authors.initials: T
authors.lastname: Fairchild
authors.forename: Perrie
authors.initials: P
authors.lastname: Adams
authors.forename: Steven
authors.initials: S
authors.lastname: Waring
authors.forename: Ramon
authors.initials: R
authors.lastname: Diaz-Arrastia
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D000544:Alzheimer Disease / Q000097:blood / Q000175:diagnosis*; D001057:Apolipoproteins E / Q000097:blood; D015415:Biomarkers / Q000097:blood*; D001798:Blood Proteins / Q000032:analysis*; D016022:Case-Control Studies; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D016015:Logistic Models; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D012680:Sensitivity and Specificity
chemical_list: D001057:Apolipoproteins E; D015415:Biomarkers; D001798:Blood Proteins