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Significant Association of Urinary Toxic Metals and Autism-Related Symptoms—A Nonlinear Statistical Analysis with Cross Validation
INTRODUCTION: A number of previous studies examined a possible association of toxic metals and autism, and over half of those studies suggest that toxic metal levels are different in individuals with Autism Spectrum Disorders (ASD). Additionally, several studies found that those levels correlate wit...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5222512/ https://www.ncbi.nlm.nih.gov/pubmed/28068407 http://dx.doi.org/10.1371/journal.pone.0169526 |
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author | Adams, James Howsmon, Daniel P. Kruger, Uwe Geis, Elizabeth Gehn, Eva Fimbres, Valeria Pollard, Elena Mitchell, Jessica Ingram, Julie Hellmers, Robert Quig, David Hahn, Juergen |
author_facet | Adams, James Howsmon, Daniel P. Kruger, Uwe Geis, Elizabeth Gehn, Eva Fimbres, Valeria Pollard, Elena Mitchell, Jessica Ingram, Julie Hellmers, Robert Quig, David Hahn, Juergen |
author_sort | Adams, James |
collection | PubMed |
description | INTRODUCTION: A number of previous studies examined a possible association of toxic metals and autism, and over half of those studies suggest that toxic metal levels are different in individuals with Autism Spectrum Disorders (ASD). Additionally, several studies found that those levels correlate with the severity of ASD. METHODS: In order to further investigate these points, this paper performs the most detailed statistical analysis to date of a data set in this field. First morning urine samples were collected from 67 children and adults with ASD and 50 neurotypical controls of similar age and gender. The samples were analyzed to determine the levels of 10 urinary toxic metals (UTM). Autism-related symptoms were assessed with eleven behavioral measures. Statistical analysis was used to distinguish participants on the ASD spectrum and neurotypical participants based upon the UTM data alone. The analysis also included examining the association of autism severity with toxic metal excretion data using linear and nonlinear analysis. “Leave-one-out” cross-validation was used to ensure statistical independence of results. RESULTS AND DISCUSSION: Average excretion levels of several toxic metals (lead, tin, thallium, antimony) were significantly higher in the ASD group. However, ASD classification using univariate statistics proved difficult due to large variability, but nonlinear multivariate statistical analysis significantly improved ASD classification with Type I/II errors of 15% and 18%, respectively. These results clearly indicate that the urinary toxic metal excretion profiles of participants in the ASD group were significantly different from those of the neurotypical participants. Similarly, nonlinear methods determined a significantly stronger association between the behavioral measures and toxic metal excretion. The association was strongest for the Aberrant Behavior Checklist (including subscales on Irritability, Stereotypy, Hyperactivity, and Inappropriate Speech), but significant associations were found for UTM with all eleven autism-related assessments with cross-validation R(2) values ranging from 0.12–0.48. |
format | Online Article Text |
id | pubmed-5222512 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-52225122017-01-19 Significant Association of Urinary Toxic Metals and Autism-Related Symptoms—A Nonlinear Statistical Analysis with Cross Validation Adams, James Howsmon, Daniel P. Kruger, Uwe Geis, Elizabeth Gehn, Eva Fimbres, Valeria Pollard, Elena Mitchell, Jessica Ingram, Julie Hellmers, Robert Quig, David Hahn, Juergen PLoS One Research Article INTRODUCTION: A number of previous studies examined a possible association of toxic metals and autism, and over half of those studies suggest that toxic metal levels are different in individuals with Autism Spectrum Disorders (ASD). Additionally, several studies found that those levels correlate with the severity of ASD. METHODS: In order to further investigate these points, this paper performs the most detailed statistical analysis to date of a data set in this field. First morning urine samples were collected from 67 children and adults with ASD and 50 neurotypical controls of similar age and gender. The samples were analyzed to determine the levels of 10 urinary toxic metals (UTM). Autism-related symptoms were assessed with eleven behavioral measures. Statistical analysis was used to distinguish participants on the ASD spectrum and neurotypical participants based upon the UTM data alone. The analysis also included examining the association of autism severity with toxic metal excretion data using linear and nonlinear analysis. “Leave-one-out” cross-validation was used to ensure statistical independence of results. RESULTS AND DISCUSSION: Average excretion levels of several toxic metals (lead, tin, thallium, antimony) were significantly higher in the ASD group. However, ASD classification using univariate statistics proved difficult due to large variability, but nonlinear multivariate statistical analysis significantly improved ASD classification with Type I/II errors of 15% and 18%, respectively. These results clearly indicate that the urinary toxic metal excretion profiles of participants in the ASD group were significantly different from those of the neurotypical participants. Similarly, nonlinear methods determined a significantly stronger association between the behavioral measures and toxic metal excretion. The association was strongest for the Aberrant Behavior Checklist (including subscales on Irritability, Stereotypy, Hyperactivity, and Inappropriate Speech), but significant associations were found for UTM with all eleven autism-related assessments with cross-validation R(2) values ranging from 0.12–0.48. Public Library of Science 2017-01-09 /pmc/articles/PMC5222512/ /pubmed/28068407 http://dx.doi.org/10.1371/journal.pone.0169526 Text en © 2017 Adams et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Adams, James Howsmon, Daniel P. Kruger, Uwe Geis, Elizabeth Gehn, Eva Fimbres, Valeria Pollard, Elena Mitchell, Jessica Ingram, Julie Hellmers, Robert Quig, David Hahn, Juergen Significant Association of Urinary Toxic Metals and Autism-Related Symptoms—A Nonlinear Statistical Analysis with Cross Validation |
title | Significant Association of Urinary Toxic Metals and Autism-Related Symptoms—A Nonlinear Statistical Analysis with Cross Validation |
title_full | Significant Association of Urinary Toxic Metals and Autism-Related Symptoms—A Nonlinear Statistical Analysis with Cross Validation |
title_fullStr | Significant Association of Urinary Toxic Metals and Autism-Related Symptoms—A Nonlinear Statistical Analysis with Cross Validation |
title_full_unstemmed | Significant Association of Urinary Toxic Metals and Autism-Related Symptoms—A Nonlinear Statistical Analysis with Cross Validation |
title_short | Significant Association of Urinary Toxic Metals and Autism-Related Symptoms—A Nonlinear Statistical Analysis with Cross Validation |
title_sort | significant association of urinary toxic metals and autism-related symptoms—a nonlinear statistical analysis with cross validation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5222512/ https://www.ncbi.nlm.nih.gov/pubmed/28068407 http://dx.doi.org/10.1371/journal.pone.0169526 |
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