Urinary Essential Elements of Young Children with Autism Spectrum Disorder and their Mothers

Abstract

Background: Even though the cause of autism spectrum disorders (ASD) remains unknown, the current understanding points towards complex interactions between environmental and genetic factors. One important environmental factor to consider is intake of toxic and essential elements, and their role in metabolism. Essential elements have received considerably less attention in the literature than the presence of toxins in urine.

Method: The purpose of this investigation is to comprehensively assess the association between urinary element compositions of 28 mothers who had young children with ASD and 29 mothers who had young typically developing (TD) children, and in a subset of their children (21 with ASD and 26 TD).

Results: The results show that there are significant differences between the ASD and TD children cohorts' concentrations for four specific elements (sulfur, phosphorous, molybdenum, and tin). Utilizing multivariate statistical techniques (Fisher's discriminant analysis and support vector machines), it was possible to distinguish the ASD from the TD children groups with an 81% accuracy after cross-validation utilizing the four significantly different elements. However, among the mother cohorts assessed, there were no significant differences between those that had children with ASD and those with TD children. There was a significant correlation of levels of phosphorus and sulfur in the children with ASD (r = 0.63, p = 3.0E-3) and in the TD children (r = 0.47, p = 0.02).

Conclusions: Notable differences were observed between the elemental concentration in urine of children with ASD and their TD peers. Analyzing cellular pathways related to these elements are promising areas of future research.

Keywords: ASD; Essential Elements; Metabolism; Urine Analysis.

Figure 1:

Univariate Test Decision Tree. Protocol for determining univariate statistical test to perform for comparing each element of the ASD and TD cohorts.

Figure 2:

ASD vs TD Probability Density Function. The figures show the probability density functions for the Fisher discriminant analysis models comparing ASD and TD children. (A) Using the essential elements phosphorous, sulfur and molybdenum and (B) Using all significant elements, i.e., phosphorous, sulfur, molybdenum, and tin. For both PDFs the two groups are distinct, but with a significant amount of overlap.

Figure 3:

Results for FDA (A) and SVM (B) analysis. All four significantly different elements (phosphorus, molybdenum, sulfur and tin) were used for these classification tasks. The FDA model attained an AUROC value of 90%, while SVM resulted in 86%. It can be seen, that there is some separation, but also some overlap, between the data for the child ASD and TD groups.

Figure 4:

(A) FDA Confusion Matrix and (B) SVM Confusion Matrix. Both confusion matrices were computed using leave-one-out cross-validation with the four-element model utilizing the child cohorts. The accuracy of both FDA and SVM was determined to be 81%.