TY - JOUR
T1 - Significant association of urinary toxic metals and autism-related symptoms - A nonlinear statistical analysis with cross validation
AU - Adams, James
AU - Howsmon, Daniel P.
AU - Kruger, Uwe
AU - Geis, Elizabeth
AU - Gehn, Eva
AU - Fimbres, Valeria
AU - Pollard, Elena
AU - Mitchell, Jessica
AU - Ingram, Julie
AU - Hellmers, Robert
AU - Quig, David
AU - Hahn, Juergen
N1 - Funding Information:
The ASU portion of this study was funded by a gift from the Autism Research Institute (ARI), www.autism.com. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The RPI portion of the study was not funded. David Quig and Robert Hellmers are employees of Doctors Data and Arizona Allergy Associates, respectively, but those agencies only provided support of their salaries, and those companies did not have any additional role in study design, data collection, analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the 'author contributions' section.
PY - 2017/1
Y1 - 2017/1
N2 - 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). Autismrelated 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 R2 values ranging from 0.12-0.48.
AB - 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). Autismrelated 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 R2 values ranging from 0.12-0.48.
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U2 - 10.1371/journal.pone.0169526
DO - 10.1371/journal.pone.0169526
M3 - Article
C2 - 28068407
AN - SCOPUS:85009070638
VL - 12
JO - PLoS One
JF - PLoS One
SN - 1932-6203
IS - 1
M1 - e0169526
ER -