title: A strategy focused on MAPT, APP, NCSTN and BACE1 to build blood classifiers for Alzheimer's disease.
abstract: BACKGROUND
  Although Alzheimer's disease (AD) is a brain disorder, a number of peripheral alterations have been found in these patients, including differences in leukocyte gene expression; however, the key genes involved in plaque and tangle formation have shown a relatively small potential as diagnostic markers. We focused on MAPT, APP, NCSTN and BACE1 as the basis to build and compare blood classifiers for AD.
  
  
  METHODS
  We used a combined model to build disease classifiers, using measures of blood pressure and serum glucose, cholesterol and triglyceride levels as well as RT-PCR expression levels of APP, NCSTN and BACE1 in peripheral blood mononuclear cells (PBMCs) from an independent cohort of 36 individuals of cognitively-normal controls, AD and other neuropathologies. Also, a set of genes was carefully selected by molecular interactions with MAPT, APP, NCSTN and BACE1 to test an expression-based classifier in a public microarray dataset of 40 samples (AD and controls). A series of discriminant analyses and classification and regression trees (C&RTs) were used to perform classification tasks.
  
  
  RESULTS
  Using C&RTs, the combined model showed potential to differentially diagnose AD with up to 94.4% accuracy and 100% specificity for our independent sample. Furthermore, a subset of 16 genes showed the best diagnostic potential using a minimum number of expression variables, correctly classifying up to 100% of samples in the public dataset.
  
  
  CONCLUSIONS
  Our unique method of variable selection proves that even elements showing no significant differences between controls and AD, but that have somehow been linked to AD or AD-related elements, still hold a potential to be used in its diagnosis. Sample size and inherent methodological limitations of this study need to be kept in mind. Our classifiers require careful further testing in larger cohorts. Nonetheless, we believe these results provide evidence for the utility of our innovative method, which contributes a different approach to generate promising diagnostic tools for neuropsychiatric disorders.
authors: Centro de Investigaciones Biomédicas, Universidad Veracruzana, Xalapa, Veracruz, Mexico. Electronic address: mariherrera@uv.mx.
authors: Marisol
authors: M
authors: Herrera-Rivero
authors: Centro de Investigaciones Cerebrales, Cuerpo Académico de Neuroquímica, Universidad Veracruzana, Xalapa, Veracruz, Mexico. Electronic address: elenahernandez@uv.mx.
authors: María
authors: M
authors: Elena Hernández-Aguilar
authors: Centro de Investigaciones Cerebrales, Cuerpo Académico de Neuroquímica, Universidad Veracruzana, Xalapa, Veracruz, Mexico. Electronic address: garanda@uv.mx.
authors: Gonzalo
authors: G
authors: Emiliano Aranda-Abreu
mesh_terms: D000544:Alzheimer Disease / Q000097:blood*; D053829:Amyloid Precursor Protein Secretases / Q000096:biosynthesis*; D016564:Amyloid beta-Protein Precursor / Q000096:biosynthesis*; D016282:Aspartic Acid Endopeptidases / Q000096:biosynthesis*; D030541:Databases, Genetic; D005260:Female; D005786:Gene Expression Regulation; D006801:Humans; D007963:Leukocytes, Mononuclear / Q000378:metabolism*; D008297:Male; D008562:Membrane Glycoproteins / Q000096:biosynthesis*; D016875:tau Proteins / Q000096:biosynthesis*
chemical_list: C545487:APP protein, human; D016564:Amyloid beta-Protein Precursor; C054369:MAPT protein, human; D008562:Membrane Glycoproteins; C413604:nicastrin protein; D016875:tau Proteins; D053829:Amyloid Precursor Protein Secretases; D016282:Aspartic Acid Endopeptidases; C509280:BACE1 protein, human
keywords: Alzheimer׳s disease; Classifiers; Diagnosis; Gene expression