title: Classification and adaptive behavior prediction of children with autism spectrum disorder based upon multivariate data analysis of markers of oxidative stress and DNA methylation.
abstract: The number of diagnosed cases of Autism Spectrum Disorders (ASD) has increased dramatically over the last four decades; however, there is still considerable debate regarding the underlying pathophysiology of ASD. This lack of biological knowledge restricts diagnoses to be made based on behavioral observations and psychometric tools. However, physiological measurements should support these behavioral diagnoses in the future in order to enable earlier and more accurate diagnoses. Stepping towards this goal of incorporating biochemical data into ASD diagnosis, this paper analyzes measurements of metabolite concentrations of the folate-dependent one-carbon metabolism and transulfuration pathways taken from blood samples of 83 participants with ASD and 76 age-matched neurotypical peers. Fisher Discriminant Analysis enables multivariate classification of the participants as on the spectrum or neurotypical which results in 96.1% of all neurotypical participants being correctly identified as such while still correctly identifying 97.6% of the ASD cohort. Furthermore, kernel partial least squares is used to predict adaptive behavior, as measured by the Vineland Adaptive Behavior Composite score, where measurement of five metabolites of the pathways was sufficient to predict the Vineland score with an R2 of 0.45 after cross-validation. This level of accuracy for classification as well as severity prediction far exceeds any other approach in this field and is a strong indicator that the metabolites under consideration are strongly correlated with an ASD diagnosis but also that the statistical analysis used here offers tremendous potential for extracting important information from complex biochemical data sets.
authors.affiliation: Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, New York, United States of America.|Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, New York, United States of America.
authors.forename: Daniel P
authors.identifier: 0000-0002-7177-1342
authors.initials: DP
authors.lastname: Howsmon
authors.affiliation: Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, New York, United States of America.
authors.forename: Uwe
authors.identifier: 0000-0001-5664-9499
authors.initials: U
authors.lastname: Kruger
authors.affiliation: Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, Arkansas, United States of America.
authors.forename: Stepan
authors.initials: S
authors.lastname: Melnyk
authors.affiliation: Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, Arkansas, United States of America.
authors.forename: S Jill
authors.initials: SJ
authors.lastname: James
authors.affiliation: Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, New York, United States of America.|Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, New York, United States of America.|Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, New York, United States of America.
authors.forename: Juergen
authors.initials: J
authors.lastname: Hahn
mesh_terms: D000067877:Autism Spectrum Disorder / Q000097:blood* / Q000175:diagnosis* / Q000276:immunology; D015415:Biomarkers / Q000097:blood; D002648:Child; D002675:Child, Preschool; D019175:DNA Methylation / Q000276:immunology*; D003627:Data Interpretation, Statistical; D005260:Female; D005492:Folic Acid / Q000097:blood*; D006801:Humans; D008297:Male; D015999:Multivariate Analysis; D018384:Oxidative Stress / Q000276:immunology*; D015203:Reproducibility of Results; D012307:Risk Factors; D012680:Sensitivity and Specificity
chemical_list: D015415:Biomarkers; D005492:Folic Acid