Fig. 1 Overview of study design. (A) Study participants recruited from Sweden (Swe) (twin–co-twin discovery set) and from the United States and UK (case-control replication sets). (B) Collected deciduous teeth were analyzed using laser ablation inductively coupled plasma mass spectrometry (LA-ICPMS) to generate temporal profiles of metal uptake during fetal and postnatal development. (C) Example exposure profile in one subject (top) ranging from −89 to 300 days since birth (TSB; time since birth in days). Dashed line indicates birth, while black arrows indicate a period of approximately 10 days. Bottom: Magnified region from −39 to 56 TSB to highlight cycles in elemental concentration varying on a roughly 10-day period. (D) Top: Example elemental exposure profiles in a single subject for two elements (Zn, blue line; Cu, green line) simultaneously sampled and overlaid from −126 to 290 TSB. Bottom: Magnified region from −126 to −64 TSB showing concentration of both elements rising and falling in synchrony. (E) Recurrence plot generated from single element trace in (C). This graphical analytical tool, analogous to a spectrogram, presents cyclical processes as diagonal lines to allow the timing and distribution of cycles to be analyzed and contrasted with singular moments that do not repeat (represented as white space), points that recur only once (singular black points), or periods of stability where concentrations are relatively constant over time (vertical or horizontal lines); these structures are emphasized in the circular inset. During recurrence quantification analysis (RQA), the duration of cycles is captured by measuring MDL, robustness (determinism), and complexity (entropy). (F) Cross-recurrence plot for the dual element cycles presented in (D).
Fig. 2 Disruption of zinc-copper cycles in ASD cases and controls. (A to C) Mean diagonal length (A), entropy (B), and determinism (C) are reduced in autism cases (squares) compared to controls (circles) in all study populations, indicating that zinc-copper cycles are of shorter duration, lower complexity, and reduced regularity in cases. Pooled estimates generated by combining data from all studies. Data are means ± 95% confidence intervals.
Fig. 3 Performance of WQS-regression and penalized logistic regression algorithms in classifying ASD cases and controls. (A) Receiver operating characteristic curve showing classification performance of the WQS algorithm with varying threshold values applied to the holdout data set (15% of data). AUC, area under the curve. (B) Classification performance of a penalized logistic regression algorithm applied to a holdout data set (15% of data) following 10-fold cross-validation in a training data set (85% of data). (C) Model performance characteristics.
- Table 1 Characteristics of study participants.
N/A, not available.
Study Location Design N (cases) Male/female Mean gestational days (SD) RATSS Stockholm, Sweden National prospective twin cohort 75 (20) 46:29 247 (9) ALSPAC Bristol, UK Case-control nested in prospective cohort 50 (25) 36:14 271 (21) Seaver Autism Center New York, USA Hospital-based case-control 18 (10) 12:6 258 (21) Autism Tooth Fairy Study Texas, USA Community-based case-control 50 (25) 25:25 N/A
Supplementary Materials
Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/4/5/eaat1293/DC1
Supplementary Materials and Methods
Supplementary Results
fig. S1. Disruption of zinc-lead cycles in ASD.
fig. S2. Recurrence quantification analysis.
fig. S3. Equivalence testing of control group means across studies.
fig. S4. Model fit and weight of variables contributing to the WQS regression model.
table S1. Results of cross-recurrence analyses.
table S2. Results of single-recurrence analyses.
table S3. Laser ablation analyses of teeth.
table S4. Main effects and interactions across elemental pathways.
table S5. Features preserved in the penalized logistic regression classifier.
References (35–56)
Additional Files
Supplementary Materials
This PDF file includes:
- Supplementary Materials and Methods
- Supplementary Results
- fig. S1. Disruption of zinc-lead cycles in ASD.
- fig. S2. Recurrence quantification analysis.
- fig. S3. Equivalence testing of control group means across studies.
- fig. S4. Model fit and weight of variables contributing to the WQS regression model.
- table S1. Results of cross-recurrence analyses.
- table S2. Results of single-recurrence analyses.
- table S3. Laser ablation analyses of teeth.
- table S4. Main effects and interactions across elemental pathways.
- table S5. Features preserved in the penalized logistic regression classifier.
- References (35–56)
Files in this Data Supplement:
- Supplementary Materials and Methods
