A systematic literature review on the association between exposures to toxic elements and an autism spectrum disorder

Shiani, Amir; Sharafi, Kiomars; Omer, Abdullah Khalid; Kiani, Amir; Massahi, Tooraj; Ebrahimzadeh, Gholamreza

doi:10.1016/j.scitotenv.2022.159246

Cited by 24 publications

(7 citation statements)

References 89 publications

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“…Moreover, there is a lack of studies demonstrating chemical-chemical interactions in this context. Previous studies have shown an association between heavy metals, like cadmium, and ASD 72, 73 . Kern et al discovered that cadmium and other trace elements were significantly lower in the hair of children with autism than others 74 .…”

Section: Discussionmentioning

confidence: 92%

Machine learning assisted discovery of synergistic interactions between environmental pesticides, phthalates, phenols, and trace elements in child neurodevelopment

Midya

Alcala

Rechtman

et al. 2023

Preprint

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A growing body of literature suggests that higher developmental exposure to individual or mixtures of environmental chemicals (ECs) is associated with autism spectrum disorder (ASD). However, the effect of interactions among these ECs is challenging to study. We introduced a composition of the classical exposure-mixture Weighted Quantile Sum (WQS) regression, and a machine-learning method called signed iterative random forest (SiRF) to discover synergistic interactions between ECs that are (1) associated with higher odds of ASD diagnosis, (2) mimic toxicological interactions, and (3) are present only in a subset of the sample whose chemical concentrations are higher than certain thresholds. In the case-control Childhood Autism Risks from Genetics and Environment study, we evaluated multi-ordered synergistic interactions among 62 ECs measured in the urine samples of 479 children in association with increased odds for ASD diagnosis (yes vs. no). WQS-SiRF discovered two synergistic two-ordered interactions between (1) trace-element cadmium(Cd) and alkyl-phosphate pesticide - diethyl-phosphate(DEP); and (2) 2,4,6-trichlorophenol(TCP-246) and DEP metabolites. Both interactions were suggestively associated with increased odds of ASD diagnosis in a subset of children with urinary concentrations of Cd, DEP, and TCP-246 above the 75th percentile. This study demonstrates a novel method that combines the inferential power of WQS and the predictive accuracy of machine-learning algorithms to discover interpretable EC interactions associated with ASD.

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Section: Discussionmentioning

confidence: 92%

Machine learning assisted discovery of synergistic interactions between environmental pesticides, phthalates, phenols, and trace elements in child neurodevelopment

Midya

Alcala

Rechtman

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Previous studies have shown an association between heavy metals, like cadmium, and ASD. 83,84 Kern et al discovered that cadmium and other trace elements were significantly lower in the hair of children with autism than others. 85 This supports the concept that children with autism may have issues excreting cadmium, resulting in a higher body burden that could contribute to symptoms of autism.…”

Section: ■ Discussionmentioning

confidence: 99%

Machine Learning Assisted Discovery of Interactions between Pesticides, Phthalates, Phenols, and Trace Elements in Child Neurodevelopment

Midya,

Alcala,

Rechtman

et al. 2023

Environ. Sci. Technol.

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A growing body of literature suggests that developmental exposure to individual or mixtures of environmental chemicals (ECs) is associated with autism spectrum disorder (ASD). However, investigating the effect of interactions among these ECs can be challenging. We introduced a combination of the classical exposure-mixture Weighted Quantile Sum (WQS) regression and a machine-learning method termed Signed iterative Random Forest (SiRF) to discover synergistic interactions between ECs that are (1) associated with higher odds of ASD diagnosis, (2) mimic toxicological interactions, and (3) are present only in a subset of the sample whose chemical concentrations are higher than certain thresholds. In a case-control Childhood Autism Risks from Genetics and Environment (CHARGE) study, we evaluated multiordered synergistic interactions among 62 ECs measured in the urine samples of 479 children in association with increased odds for ASD diagnosis (yes vs no). WQS-SiRF identified two synergistic two-ordered interactions between (1) trace-element cadmium (Cd) and the organophosphate pesticide metabolite diethyl-phosphate (DEP); and (2) 2,4,6-trichlorophenol (TCP-246) and DEP. Both interactions were suggestively associated with increased odds of ASD diagnosis in the subset of children with urinary concentrations of Cd, DEP, and TCP-246 above the 75th percentile. This study demonstrates a novel method that combines the inferential power of WQS and the predictive accuracy of machine-learning algorithms to discover potentially biologically relevant chemical–chemical interactions associated with ASD.

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“…Ding M et al (2023) [29] provide a quantitative synthesis of data from included studies, potentially offering more conclusive evidence on the associations between specific heavy metals and child autistic disorder. The study by Amir Shiani et al (2023) [30] shows that individuals with ASD have significantly elevated levels of lead, mercury, and cadmium in their blood compared to healthy controls. This emphasizes the importance of controlling exposure to these elements in mothers before and during pregnancy and in infants.…”

Section: Examples Of Using Hmamentioning

confidence: 99%

Chemical Elements in Hair and Their Association with Autism Spectrum Disorder: A Comprehensive Systematic Review

Chojnacka,

Mikulewicz

2023

Pollutants

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Background: Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition with increasing prevalence. This review aims to systematically investigate the relationship between the levels of toxic and trace elements in hair and the occurrence of ASD. Methods: Original articles reporting trace element levels in hair were included. A comprehensive search was conducted in databases such as Medline (via PubMed), Scopus, Web of Science, and Google Scholar, covering publications from 1 January 2000, to 2 January 2023. Keywords including “hair element analysis”, “trace elements”, and “autism”, were utilized in the search. Results: A direct comparison of the data was not possible due to the variety of methodologies observed in the available studies, including variations in sample sizes and analytical procedures. Conclusions: Exposure to toxic elements, notably Mercury (Hg) and Lead (Pb), which act as neurotoxicants, was found to be associated with the pathogenesis of ASD. Furthermore, a significant correlation was identified between the Zinc (Zn) to Copper (Cu) ratio and ASD.

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A systematic literature review on the association between exposures to toxic elements and an autism spectrum disorder

Cited by 24 publications

References 89 publications

Machine learning assisted discovery of synergistic interactions between environmental pesticides, phthalates, phenols, and trace elements in child neurodevelopment

Machine learning assisted discovery of synergistic interactions between environmental pesticides, phthalates, phenols, and trace elements in child neurodevelopment

Machine Learning Assisted Discovery of Interactions between Pesticides, Phthalates, Phenols, and Trace Elements in Child Neurodevelopment

Chemical Elements in Hair and Their Association with Autism Spectrum Disorder: A Comprehensive Systematic Review

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