Next Article in Journal
Modeling and Thermal Analysis of a Moving Spacecraft Subject to Solar Radiation Effect
Next Article in Special Issue
Can Machine Learning Predict Stress Reduction Based on Wearable Sensors’ Data Following Relaxation at Workplace? A Pilot Study
Previous Article in Journal
The Engineering of Porous Silica and Hollow Silica Nanoparticles to Enhance Drug-loading Capacity
Open AccessFeature PaperArticle

Multivariate Analysis of Plasma Metabolites in Children with Autism Spectrum Disorder and Gastrointestinal Symptoms Before and After Microbiota Transfer Therapy

by James B. Adams 1,*,†, Troy Vargason 2,3,†, Dae-Wook Kang 4,‡, Rosa Krajmalnik-Brown 4,5,6 and Juergen Hahn 2,3,7
1
School for Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, AZ 85287, USA
2
Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
3
Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
4
Biodesign Swette Center for Environmental Biotechnology, Arizona State University, Tempe, AZ 85287, USA
5
Biodesign Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, AZ 85287, USA
6
School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85281, USA
7
Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
*
Author to whom correspondence should be addressed.
James B. Adams and Troy Vargason contributed equally to this manuscript.
Current address: Department of Civil and Environmental Engineering, The University of Toledo, Toledo, OH 43606, USA.
Processes 2019, 7(11), 806; https://doi.org/10.3390/pr7110806
Received: 5 September 2019 / Revised: 21 October 2019 / Accepted: 21 October 2019 / Published: 4 November 2019
(This article belongs to the Special Issue Machine Learning Methods for Modelling Neurological Diseases)
Current diagnosis of autism spectrum disorder (ASD) is based on assessment of behavioral symptoms, although there is strong evidence that ASD affects multiple organ systems including the gastrointestinal (GI) tract. This study used Fisher discriminant analysis (FDA) to evaluate plasma metabolites from 18 children with ASD and chronic GI problems (ASD + GI cohort) and 20 typically developing (TD) children without GI problems (TD − GI cohort). Using three plasma metabolites that may represent three general groups of metabolic abnormalities, it was possible to distinguish the ASD + GI cohort from the TD − GI cohort with 94% sensitivity and 100% specificity after leave-one-out cross-validation. After the ASD + GI participants underwent Microbiota Transfer Therapy with significant improvement in GI and ASD-related symptoms, their metabolic profiles shifted significantly to become more similar to the TD − GI group, indicating potential utility of this combination of plasma metabolites as a biomarker for treatment efficacy. Two of the metabolites, sarcosine and inosine 5′-monophosphate, improved greatly after treatment. The third metabolite, tyramine O-sulfate, showed no change in median value, suggesting it and correlated metabolites to be a possible target for future therapies. Since it is unclear whether the observed differences are due to metabolic abnormalities associated with ASD or with GI symptoms (or contributions from both), future studies aiming to classify ASD should feature TD participants with GI symptoms and have larger sample sizes to improve confidence in the results. View Full-Text
Keywords: autism spectrum disorder; gastrointestinal symptoms; biomarker; Fisher discriminant analysis; multivariate statistics; leave-one-out cross-validation; plasma metabolites; fecal microbiota transplant; co-occurring conditions autism spectrum disorder; gastrointestinal symptoms; biomarker; Fisher discriminant analysis; multivariate statistics; leave-one-out cross-validation; plasma metabolites; fecal microbiota transplant; co-occurring conditions
Show Figures

Figure 1

MDPI and ACS Style

Adams, J.B.; Vargason, T.; Kang, D.-W.; Krajmalnik-Brown, R.; Hahn, J. Multivariate Analysis of Plasma Metabolites in Children with Autism Spectrum Disorder and Gastrointestinal Symptoms Before and After Microbiota Transfer Therapy. Processes 2019, 7, 806.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop