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Article

Multivariate Analysis of Fecal Metabolites from Children with Autism Spectrum Disorder and Gastrointestinal Symptoms before and after Microbiota Transfer Therapy

1
Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
2
Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
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School for Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, AZ 85287, USA
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Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA
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Biodesign Swette Center for Environmental Biotechnology, Arizona State University, Tempe, AZ 85287, USA
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Biodesign Center for Health through Microbiome, Arizona State University, Tempe, AZ 85287, USA
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School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85281, USA
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Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
*
Author to whom correspondence should be addressed.
Current address: Department of Civil and Environmental Engineering, The University of Toledo, Toledo, OH 43606, USA.
J. Pers. Med. 2020, 10(4), 152; https://doi.org/10.3390/jpm10040152
Received: 18 August 2020 / Revised: 11 September 2020 / Accepted: 25 September 2020 / Published: 2 October 2020
Fecal microbiota transplant (FMT) holds significant promise for patients with Autism Spectrum Disorder (ASD) and gastrointestinal (GI) symptoms. Prior work has demonstrated that plasma metabolite profiles of children with ASD become more similar to those of their typically developing (TD) peers following this treatment. This work measures the concentration of 669 biochemical compounds in feces of a cohort of 18 ASD and 20 TD children using ultrahigh performance liquid chromatography-tandem mass spectroscopy. Subsequent measurements were taken from the ASD cohort over the course of 10-week Microbiota Transfer Therapy (MTT) and 8 weeks after completion of this treatment. Univariate and multivariate statistical analysis techniques were used to characterize differences in metabolites before, during, and after treatment. Using Fisher Discriminant Analysis (FDA), it was possible to attain multivariate metabolite models capable of achieving a sensitivity of 94% and a specificity of 95% after cross-validation. Observations made following MTT indicate that the fecal metabolite profiles become more like those of the TD cohort. There was an 82–88% decrease in the median difference of the ASD and TD group for the panel metabolites, and among the top fifty most discriminating individual metabolites, 96% report more comparable values following treatment. Thus, these findings are similar, although less pronounced, as those determined using plasma metabolites. View Full-Text
Keywords: fecal metabolites; ASD; microbiome; gastrointestinal symptoms; Fisher Discriminant Analysis fecal metabolites; ASD; microbiome; gastrointestinal symptoms; Fisher Discriminant Analysis
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MDPI and ACS Style

Qureshi, F.; Adams, J.; Hanagan, K.; Kang, D.-W.; Krajmalnik-Brown, R.; Hahn, J. Multivariate Analysis of Fecal Metabolites from Children with Autism Spectrum Disorder and Gastrointestinal Symptoms before and after Microbiota Transfer Therapy. J. Pers. Med. 2020, 10, 152. https://doi.org/10.3390/jpm10040152

AMA Style

Qureshi F, Adams J, Hanagan K, Kang D-W, Krajmalnik-Brown R, Hahn J. Multivariate Analysis of Fecal Metabolites from Children with Autism Spectrum Disorder and Gastrointestinal Symptoms before and after Microbiota Transfer Therapy. Journal of Personalized Medicine. 2020; 10(4):152. https://doi.org/10.3390/jpm10040152

Chicago/Turabian Style

Qureshi, Fatir, James Adams, Kathryn Hanagan, Dae-Wook Kang, Rosa Krajmalnik-Brown, and Juergen Hahn. 2020. "Multivariate Analysis of Fecal Metabolites from Children with Autism Spectrum Disorder and Gastrointestinal Symptoms before and after Microbiota Transfer Therapy" Journal of Personalized Medicine 10, no. 4: 152. https://doi.org/10.3390/jpm10040152

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