Environmental toxicants and autism spectrum disorders: a systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although the involvement of genetic abnormalities in autism spectrum disorders (ASD) is well-accepted, recent studies point to an equal contribution by environmental factors, particularly environmental toxicants. However, these toxicant-related studies in ASD have not been systematically reviewed to date. Therefore, we compiled publications investigating potential associations between environmental toxicants and ASD and arranged these publications into the following three categories: (a) studies examining estimated toxicant exposures in the environment during the preconceptional, gestational and early childhood periods; (b) studies investigating biomarkers of toxicants; and (c) studies examining potential genetic susceptibilities to toxicants. A literature search of nine electronic scientific databases through November 2013 was performed. In the first category examining ASD risk and estimated toxicant exposures in the environment, the majority of studies (34/37; 92%) reported an association. Most of these studies were retrospective case-control, ecological or prospective cohort studies, although a few had weaker study designs (for example, case reports or series). Toxicants implicated in ASD included pesticides, phthalates, polychlorinated biphenyls (PCBs), solvents, toxic waste sites, air pollutants and heavy metals, with the strongest evidence found for air pollutants and pesticides. Gestational exposure to methylmercury (through fish exposure, one study) and childhood exposure to pollutants in water supplies (two studies) were not found to be associated with ASD risk. In the second category of studies investigating biomarkers of toxicants and ASD, a large number was dedicated to examining heavy metals. Such studies demonstrated mixed findings, with only 19 of 40 (47%) case-control studies reporting higher concentrations of heavy metals in blood, urine, hair, brain or teeth of children with ASD compared with controls. Other biomarker studies reported that solvent, phthalate and pesticide levels were associated with ASD, whereas PCB studies were mixed. Seven studies reported a relationship between autism severity and heavy metal biomarkers, suggesting evidence of a dose-effect relationship. Overall, the evidence linking biomarkers of toxicants with ASD (the second category) was weaker compared with the evidence associating estimated exposures to toxicants in the environment and ASD risk (the first category) because many of the biomarker studies contained small sample sizes and the relationships between biomarkers and ASD were inconsistent across studies. Regarding the third category of studies investigating potential genetic susceptibilities to toxicants, 10 unique studies examined polymorphisms in genes associated with increased susceptibilities to toxicants, with 8 studies reporting that such polymorphisms were more common in ASD individuals (or their mothers, 1 study) compared with controls (one study examined multiple polymorphisms). Genes implicated in these studies included paraoxonase (PON1, three of five studies), glutathione S-transferase (GSTM1 and GSTP1, three of four studies), δ-aminolevulinic acid dehydratase (one study), SLC11A3 (one study) and the metal regulatory transcription factor 1 (one of two studies). Notably, many of the reviewed studies had significant limitations, including lack of replication, limited sample sizes, retrospective design, recall and publication biases, inadequate matching of cases and controls, and the use of nonstandard tools to diagnose ASD. The findings of this review suggest that the etiology of ASD may involve, at least in a subset of children, complex interactions between genetic factors and certain environmental toxicants that may act synergistically or in parallel during critical periods of neurodevelopment, in a manner that increases the likelihood of developing ASD. Because of the limitations of many of the reviewed studies, additional high-quality epidemiological studies concerning environmental toxicants and ASD are warranted to confirm and clarify many of these findings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it