Significant Association of Urinary Toxic Metals and Autism-Related Symptoms-A Nonlinear Statistical Analysis with Cross Validation.
James AdamsMichael S SacksUwe KrugerElizabeth GeisEva GehnValeria FimbresElena PollardJessica MitchellJulie IngramRobert HellmersDavid QuigJuergen HahnPublished in: PloS one (2017)
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.
Keyphrases
- autism spectrum disorder
- intellectual disability
- attention deficit hyperactivity disorder
- machine learning
- deep learning
- human health
- health risk
- health risk assessment
- emergency department
- risk assessment
- depressive symptoms
- climate change
- physical activity
- heavy metals
- sleep quality
- electronic health record
- neural network