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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
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.
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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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