Journal of Toxicology 5 Table 5: Regression analyses of initial autism severity versus urinary metal excretion and initial glutathione. In the regression equation, the suﬃxes for the metals refer to the value at Baseline (B) and after the 9th (9) dose of DMSA in Phase 1. ATEC SAS ADOS (comm. + social) PDD-BI (modiﬁed autism score) ∗∗P < .01, ∗P < .05 ADOS- Sociability ADOS- Commun. ADOS-Play ADOS-SBRI 0.22 0.36 0.45 0.25 0.41 0.37 0.24 0.21 24.1–6.17 HgB + 76.6 SbB + 0.593 Pb9 + 3.97 Hg9 + 0.27 As9 4.81 + 1.70 PbB + 4.87 TlB − 0.640 HgB + 5.48 SbB − 1.87 CdB − 0.0237 AlB − 0.114 Pb9 − 3.14 Tl9 + 6.07 Sb9 13.19–4.29 HgB + 24.1 SbB − 3.67 WB − 0.0673 AlB + 2.75 Hg9 + 6.60 W9 − 0.0539 As9 + 0.0054 Glut −131.8 + 70.4 WB − 0.789 Sn9 + 18.8 Hg9 + 255 Sb9 + 21.8 W9 Sb9∗∗, WB∗, Sn9∗ 8.70 +1.20 PbB + 0.217 SnB + 12.7 TlB − 1.64 HgB − 10.2 SbB − 2.61 CdB − 0.631 AlB − 0.186 Pb9 − 7.13 Tl9 + 6.27 Sb9 +6.15 W9 +3.62 Cd9 2.39–2.57 HgB + 23.1 SbB + 2.32 Hg9 + .0048 Glut 1.20 + 0.540 PbB + 4.23 Sb9 + 0.0017 Glut 4.64–0.897 HgB − 2.63 CdB − 0.26 AlB + 0.050 Pb9 + 0.730 Hg9 Most signiﬁcant variables SbB∗∗, Pb9∗ PbB∗∗ HgB∗∗, SbB∗, Hg9∗, W9∗ Most signiﬁcant variables W9∗∗∗, AlB∗∗, TlB∗, HgB∗, Pb9∗, Tl9∗ HgB∗∗, Hg9∗∗, SbB∗∗ PbB∗ Adjusted R2 P-value Equation Adjusted R2 P-value Equation .003 .002 .0003 .004 0.004 0.0003 0.004 0.02 Table 6: Regression analyses of initial ados subscales versus urinary metal excretion and initial glutathione. In the regression equation, the suﬃxes for the metals refer to the value at Baseline (B) and after the 9th (9) dose of DMSA in Phase 1. ∗∗∗P < .001, ∗∗P < .01, ∗P < .05 (each of which was taken form a sample of size 40 or more) would come from a distribution with mean 0 and standard deviation equal to 0.02. Under those conditions, the P-value for a mean correlation coeﬃcient of 0.14 is less that 10−10, so again it is extremely likely that there is a high overall positive correlation between the severity measures as a group and the biological measures taken as a group. Since multiple correlations were obtained, it was decided to conduct regression analyses, which are discussed in the next section. Basically, a regression analysis allows for the simultaneous consideration of multiple factors, such as how well certain combinations of diﬀerent toxic metal excretions can predict values of a speciﬁc autism severity measure. 3.3. Regression Analyses of Initial Severity of Autism. Table 5 shows the results of stepwise linear regression analyses for the various autism severity scales as a function of urinary excretion of toxic metals (at baseline and after the 9th dose of DMSA) and initial glutathione. All of the analyses found that the variations in the severity of autism could be partially explained by the urinary excretion of toxic metals and initial glutathione, with adjusted R2 values ranging from 0.22 to 0.45, and P-values all below .005. For the ADOS (which had the highest adjusted R2), the most signiﬁcant variables were mercury (Hg) and antimony (Sb) at baseline and mercury and tungsten (W) at the 9th dose. Since the ADOS score had the highest adjusted R2 values, we also conducted a similar regression analysis on the subscales—(a) language and communication; (b) reciprocal social interaction; (c) play; (d) stereotyped behaviors and restricted interests (SBRIs). Those results are show in Table 6. The variation in all four of the ADOS subscales could also be partially explained by urinary excretion of toxic metals and RBC glutathione (adjusted R2 of 0.21–0.41, P < .02 in all cases). The ADOS Sociability and the ADOS Communication subscales had the highest adjusted R2 (0.41 and 0.37, resp.). For the ADOS Sociability subscale, the most signiﬁcant variable was tungsten at the 9th dose, followed by tungsten, aluminum, and thallium at baseline and lead and thallium at the 9th dose. For the ADOS Communication subscale, the most signiﬁcant variables were mercury (at baseline and 9th dose) and antimony (Sb) at baseline. Since the toxic metal excretions exhibit considerable cor- relation amongst themselves [10], one should refrain from reading too much into the relationships between speciﬁc metals and severity of autism and instead should interpret the results as indicating a general relationship between autism severity and urinary excretion of toxic metals. 4. Discussion The diﬀerent assessment tools were found to be highly correlated, which generally supports the validity of each of the assessment tools. The correlations were the highest between the modiﬁed PDD-BI and the ATEC, suggesting that those scales are very consistent. The ADOS had a lower correlation with the other scales; this at least partly due to