skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: High efficiency classification of children with autism spectrum disorder

Journal Article · · PLoS ONE
; ORCiD logo; ;

Autism spectrum disorder (ASD) is a wide-ranging collection of developmental diseases with varying symptoms and degrees of disability. Currently, ASD is diagnosed mainly with psychometric tools, often unable to provide an early and reliable diagnosis. Recently, biochemical methods are being explored as a means to meet the latter need. For example, an increased predisposition to ASD has been associated with abnormalities of metabolites in folate-dependent one carbon metabolism (FOCM) and transsulfuration (TS). Multiple metabolites in the FOCM/TS pathways have been measured, and statistical analysis tools employed to identify certain metabolites that are closely related to ASD. The prime difficulty in such biochemical studies comes from (i) inefficient determination of which metabolites are most important and (ii) understanding how these metabolites are collectively related to ASD. This paper presents a new method based on scores produced in Support Vector Machine (SVM) modeling combined with High Dimensional Model Representation (HDMR) sensitivity analysis. The new method effectively and efficiently identifies the key causative metabolites in FOCM/TS pathways, ranks their importance, and discovers their independent and correlative action patterns upon ASD. Such information is valuable not only for providing a foundation for a pathological interpretation but also for potentially providing an early, reliable diagnosis ideally leading to a subsequent comprehensive treatment of ASD. With only tens of SVM model runs, the new method can identify the combinations of the most important metabolites in the FOCM/TS pathways that lead to ASD. Previous efforts to find these metabolites required hundreds of thousands of model runs with the same data.

Research Organization:
Princeton Univ., NJ (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
FG02-02ER15344
OSTI ID:
1421311
Alternate ID(s):
OSTI ID: 1499882
Journal Information:
PLoS ONE, Journal Name: PLoS ONE Vol. 13 Journal Issue: 2; ISSN 1932-6203
Publisher:
Public Library of Science (PLoS)Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 10 works
Citation information provided by
Web of Science

References (22)

The Utilization of Multiple Measurements in Problems of Biological Classification journal July 1948
ANOVA kernels and RKHS of zero mean functions for model-based sensitivity analysis journal March 2013
Making best use of model evaluations to compute sensitivity indices journal May 2002
How environmental and genetic factors combine to cause autism: A redox/methylation hypothesis journal January 2008
Estimation of global sensitivity indices for models with dependent variables journal April 2012
A tutorial on support vector regression journal August 2004
Classification and adaptive behavior prediction of children with autism spectrum disorder based upon multivariate data analysis of markers of oxidative stress and DNA methylation journal March 2017
Non-parametric methods for global sensitivity analysis of model output with dependent inputs journal October 2015
Fisher discriminant analysis with kernels
  • Mika, S.; Ratsch, G.; Weston, J.
  • Neural Networks for Signal Processing IX: 1999 IEEE Signal Processing Society Workshop, Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468) https://doi.org/10.1109/NNSP.1999.788121
conference January 1999
General formulation of HDMR component functions with independent and correlated variables journal August 2011
Relationship between sensitivity indices defined by variance- and covariance-based methods journal November 2017
Nonparametric Estimation of Conditional CDF and Quantile Functions With Mixed Categorical and Continuous Data journal October 2008
Significance, P values and t-tests journal October 2013
Identification of infants at high‐risk for autism spectrum disorder using multiparameter multiscale white matter connectivity networks journal September 2015
Childhood Autism Rating Scale (CARS) and Autism Behavior Checklist (ABC) Correspondence and Conflicts with DSM-IV Criteria in Diagnosis of Autism journal December 2004
A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output journal February 1999
Annual Research Review: The role of the environment in the developmental psychopathology of autism spectrum condition journal January 2016
Sensitivity Analysis for Chemical Models journal July 2005
Remarks on a Multivariate Transformation journal September 1952
Global Sensitivity Analysis for Systems with Independent and/or Correlated Inputs journal May 2010
Kernel estimation of multivariate cumulative distribution function journal November 2008
High dimensional model representation constructed by support vector regression. I. Independent variables with known probability distributions journal September 2016

Similar Records

Related Subjects

60 APPLIED LIFE SCIENCES
59 BASIC BIOLOGICAL SCIENCES