Perinatal Exposure to Traffic-Related Air Pollution and Autism Spectrum Disorders

Observational methods for human studies of transgenerational effects

There are substantial challenges in studying human transgenerational epigenetic outcomes resulting from environmental conditions. The task requires specialized methods and tools that incorporate specific knowledge of multigenerational relationship combinations of probands and their ancestors, phenotype data for individuals, environmental information of ancestors and their descendants, which can span historical to present datasets, and informative environmental data that chronologically aligns with ancestors and descendants over space and time. As a result, there are few epidemiologic studies of potential transgenerational effects in human populations, thus limiting the knowledge of ancestral environmental conditions and the potential impacts we face with modern human health outcomes. In an effort to overcome some of the challenges in studying human transgenerational effects, we present two transgenerational study designs: transgenerational space-time cluster detection and transgenerational case-control study design. Like other epidemiological methods, these methods determine whether there are statistical associations between phenotypic outcomes (e.g., adverse health outcomes) among probands and the shared environments and environmental factors facing their ancestors. When the ancestor is a paternal grandparent, a statistically significant association provides some evidence that a transgenerational inheritable factor may be involved. Such results may generate useful hypotheses that can be explored using epigenomic data to establish conclusive evidence of transgenerational heritable effects. Both methods are proband-centric: They are designed around the phenotype of interest in the proband generation for case selection and family pedigree creation. In the examples provided, we incorporate at least three generations of paternal lineage in both methods to observe a potential transgenerational effect.

Association between prenatal air pollutant exposure and autism spectrum disorders in young children: a matched case-control study in Canada

The direction and magnitude of association between maternal exposure to ambient air pollutants across gestational windows and offspring risk of autism spectrum disorders (ASD) remains unclear. We sought to evaluate the time-varying effects of prenatal air pollutant exposure on ASD. We conducted a matched case-control study of singleton term children born in Ontario, Canada from 1-Apr-2012 to 31-Dec-2016. Provincial birth registry data were linked with applied behavioural analysis services and ambient air pollutant datasets to ascertain prenatal exposure to nitrogen dioxide (NO2), ground-level ozone (O3), fine particulate matter (PM2.5), and ASD diagnoses. Covariate balance between cases and controls was established using coarsened exact matching. Conditional logistic regression was used to assess the association between prenatal air pollutant exposure and ASD. Distributed lag non-linear models (DLNM) were used to examine the effects of single-pollutant exposure by prenatal week. Sensitivity analyses were conducted to assess the impact of exposure period on the observed findings. The final sample included 1,589 ASD cases and 7,563 controls. Compared to controls, cases were more likely to be born to mothers living in urban areas, delivered by Caesarean section, and assigned male sex at birth. NO2 was a consistent and significant contributor to ASD risk after accounting for co-exposure to O3, PM2.5 and covariates. The odds ratio per interquartile range increase was 2.1 (95%CI 1.8-2.3) pre-conception, 2.2 (2.0-2.5) for the 1st trimester, 2.2 (1.9-2.5) for the 2nd trimester, and 2.1 (1.9-2.4) for the 3rd trimester. In contrast, findings for O3 and PM2.5 with ASD were inconsistent. Findings from DLNM and sensitivity analyses were similar. Exposure to NO2 before and during pregnancy was significantly associated with ASD in offspring. The relationship between prenatal O3 and PM2.5 exposure and ASD remains unclear. Further investigation into the combined effects of multi-pollutant exposure on child neurodevelopment is warranted.

The contribution of environmental pollutants to the risk of autism and other neurodevelopmental disorders: a systematic review of case-control studies

Exposure to environmental pollutants, such as metals, pesticides, and air pollutants during early life, is a risk factor for neurodevelopmental disorders (NDDs), including Autism Spectrum Disorder (ASD). Our systematic review aimed to select and summarize more recent case-control studies that examined the association between prenatal and early postnatal exposure to environmental pollutants and NDDs. We searched five databases (Web of Science, PubMed, Embase, Scopus, Ovid), screened 2,261 records, and included 24 eligible case-control studies. Meta-analyses were conducted on subgroups of at least three studies that shared both the outcome and the exposure. A noteworthy discovery from this literature review is the existence of non-linear or non-monotonic dose-response relationships between the exposure to certain metals and the risk of ASD. The meta-analysis revealed a significant association between exposure to particular matter (PM)10 during the first year of life and the risk of ASD. Overall, studies included in our systematic review indicate that exposure to several pollutants within the first three years of life was significantly associated with the risk of NDDs.

Causal effects of PM2.5 exposure on neuropsychiatric disorders and the mediation via gut microbiota: A Mendelian randomization study

BACKGROUND

Growing evidence has revealed the impacts of exposure to fine particulate matter (PM2.5) and dysbiosis of gut microbiota on neuropsychiatric disorders, but the causal inference remains controversial due to residual confounders in observational studies.

METHODS

This study aimed to examine the causal effects of exposure to PM2.5 on 4 major neuropsychiatric disorders (number of cases = 18,381 for autism spectrum disorder [ASD], 38,691 for attention deficit hyperactivity disorder [ADHD], 67,390 for schizophrenia, and 21,982 cases for Alzheimer's disease [AD]), and the mediation pathway through gut microbiota. Two-sample Mendelian randomization (MR) analyses were performed, in which genetic instruments were identified from genome-wide association studies (GWASs). The included GWASs were available from (1) MRC Integrative Epidemiology Unit (MRC-IEU) for PM2.5, PMcoarse, PM10, and NOX; (2) the Psychiatric Genomics Consortium (PGC) for ASD, ADHD, and schizophrenia; (3) MRC-IEU for AD; and (4) MiBioGen for gut microbiota. Multivariable MR analyses were conducted to adjust for exposure to NOX, PMcoarse, and PM10. We also examined the mediation effects of gut microbiota in the associations between PM2.5 exposure levels and neuropsychiatric disorders, using two-step MR analyses.

RESULTS

Each 1 standard deviation (1.06 ug/m3) increment in PM2.5 concentrations was associated with elevated risk of ASD (odds ratio [OR] 1.42, 95% confidence interval [CI] 1.00-2.02), ADHD (1.51, 1.15-1.98), schizophrenia (1.47, 1.15-1.87), and AD (1.57, 1.16-2.12). For all the 4 neurodevelopmental disorders, the results were robust under various sensitivity analyses, while the MR-Egger method yielded non-significant outcomes. The associations remained significant for all the 4 neuropsychiatric disorders after adjusting for PMcoarse, while non-significant after adjusting for NOX and PM10. The effects of PM2.5 exposure on ADHD and schizophrenia were partially mediated by Lachnospiraceae and Barnesiella, with the proportions ranging from 8.31% to 15.77%.

CONCLUSIONS

This study suggested that exposure to PM2.5 would increase the risk of neuropsychiatric disorders, partially by influencing the profile of gut microbiota. Comprehensive regulations on air pollutants are needed to help prevent neuropsychiatric disorders.

Ultrafine particulate matter exposure during second year of life, but not before, associated with increased risk of autism spectrum disorder in BKMR mixtures model of multiple air pollutants

Prenatal and early postnatal air pollution exposures have been shown to be associated with autism spectrum disorder (ASD) risk but results regarding specific air pollutants and exposure timing are mixed and no study has investigated the effects of combined exposure to multiple air pollutants using a mixtures approach. We aimed to evaluate prenatal and early life multipollutant mixtures for the drivers of associations of air pollution with ASD. This study examined 484 typically developing (TD) and 660 ASD children from the CHARGE case-control study. Daily air concentrations for NO2, O3, ultrafine (PM0.1), fine (PM0.1-2.5), and coarse (PM2.5-10) particles were predicted from chemical transport models with statistical bias adjustment based on ground-based monitors. Daily averages were calculated for each exposure period (pre-pregnancy, each trimester of pregnancy, first and second year of life) between 2000 and 2016. Air pollution variables were natural log-transformed and then standardized. Individual and joint effects of pollutant exposure with ASD, and potential interactions, were evaluated for each period using hierarchical Bayesian Kernel Machine Regression (BKMR) models, with three groups: PM size fractions (PM0.1, PM0.1-2.5, PM2.5-10), NO2, and O3. In BKMR models, the PM group was associated with ASD in year 2 (group posterior inclusion probability (gPIP) = 0.75), and marginally associated in year 1 (gPIP = 0.497). PM2.5-10 appeared to drive the association (conditional PIP (cPIP) = 0.64) in year 1, while PM0.1 appeared to drive the association in year 2 (cPIP = 0.76), with both showing a moderately strong increased risk. Pre-pregnancy O3 showed a slight J-shaped risk of ASD (gPIP = 0.55). No associations were observed for exposures during pregnancy. Pre-pregnancy O3 and year 2 p.m.0.1 exposures appear to be associated with an increased risk of ASD. Future research should examine ultrafine particulate matter in relation to ASD.

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

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.

Chronic Ambient Ozone Exposure Aggravates Autism-Like Symptoms in a Susceptible Mouse Model

Although there is evidence that exposure to ground-level ozone (O3) may cause an increased risk of neurological disorders (e.g., autistic spectrum disorder), low-dose chronic ozone exposure and its adverse effects on the nervous system have not been fully understood. Here, we evaluated the potential neurotoxic effects of long-term exposure to environmentally relevant O3 concentration (200 μg/m3 via a whole-body inhalation system, 12 h/day for 5 days/week) using a susceptible mouse model of autism induced by valproic acid. Various indicators of oxidative stress, mitochondria, and synapse in the brain tissues were then measured to determine the overall damage of O3 to the mouse brain. The results showed an aggravated risk of autism in mice offspring, which was embodied in decreased antioxidant contents, disturbed energy generation in mitochondria, as well as reduced expressions of protein kinase Mζ (PKMζ) and synaptic proteins [e.g., Synapsin 1 (SYN 1), postsynaptic density protein-95 (PSD-95)]. Overall, our study indicates that prenatal exposure to environmentally relevant O3 may exacerbate the symptoms of autism, shedding light on possible molecular mechanisms and providing valuable insights into the pathogenesis of autism, especially concerning low-dose levels of those pollutants.

The evolution of atmospheric particulate matter in an urban landscape since the Industrial Revolution

Atmospheric particulate matter (PM) causes 3.7 million annual deaths worldwide and potentially damages every organ in the body. The cancer-causing potential of fine particulates (PM_2.5) highlights the inextricable link between air quality and human health. With over half of the world's population living in cities, PM_2.5 emissions are a major concern, however, our understanding of exposure to urban PM is restricted to relatively recent (post-1990) air quality monitoring programmes. To investigate how the composition and toxicity of PM has varied within an urban region, over timescales encompassing changing patterns of industrialisation and urbanisation, we reconstructed air pollution records spanning 200 years from the sediments of urban ponds in Merseyside (NW England), a heartland of urbanisation since the Industrial Revolution. These archives of urban environmental change across the region demonstrate a key shift in PM emissions from coarse carbonaceous 'soot' that peaked during the mid-twentieth century, to finer combustion-derived PM_2.5 post-1980, mirroring changes in urban infrastructure. The evolution of urban pollution to a recent enhanced PM_2.5 signal has important implications for understanding lifetime pollution exposures for urban populations over generational timescales.

Air pollution exposure and social responsiveness in childhood: The cincinnati combined childhood cohorts

Autism Spectrum Disorder (ASD) affects about 1 in 44 children and environmental exposures may contribute to disease onset. Air pollution has been associated with adverse neurobehavioral outcomes, yet little research has examined its association with autistic-like behaviors. Therefore, our objective was to examine the association between exposure to air pollution, including NO2 and PM2.5, during pregnancy and the first year of life to ASD-like behaviors during childhood. Participants (n = 435) enrolled in the Cincinnati Childhood Allergy and Air Pollution Study and the Health Outcomes and Measures of the Environment Study were included in the analysis. Daily exposures to NO2 and PM2.5 at the residential addresses of participants were estimated using validated spatiotemporal models and averaged to obtain prenatal and first year exposure estimates. ASD-like behaviors were assessed via the Social Responsiveness Scale (SRS) questionnaire at age 12. Linear regression models adjusting for confounders were applied to estimate the association between pollutants and SRS scores. After adjusting for covariates, the association between NO2 and PM2.5 and SRS scores remained positive but were no longer statistically significant. Prenatal and first year exposure to NO2 were associated with total SRS T-scores with an estimated 0.4 point increase (95% CI: -0.7, 1.6) per 5.2 ppb increase in NO2 exposure and 0.7 point (95% CI: -0.3, 1.6) per 4.2 ppb increase in NO2 exposure, respectively. For PM2.5, a 2.6 μg/m3 increase in prenatal exposure was associated with a 0.1 point increase (95% CI: -1.1, 1.4) in SRS Total T-scores and a 1.3 μg/m3 increase first year of life was associated with a 1 point increase (95% CI: -0.2, 2.3). In summary, exposure to NO2 and PM2.5 during pregnancy and the first year of life were not significantly associated with higher autistic-like behaviors measured with SRS scores after adjustment of covariates. Additional research is warranted given prior studies suggesting air pollution contributes to ASD.

The Effect of Maternal Exposure to Air Pollutants and Heavy Metals during Pregnancy on the Risk of Neurological Disorders Using the National Health Insurance Claims Data of South Korea

The objective of this study was to evaluate the effects of high levels of maternal exposure to ambient air pollution and heavy metals on risks of autism spectrum disorder (ASD) and epilepsy using the National Health Insurance claims data of South Korea. The data of mothers and their newborns from 2016 to 2018 provided by the National Health Insurance Service were used (n = 843,134). Data on exposure to ambient air pollutants (PM2.5, CO, SO₂, NO₂, and O₃) and heavy metals (Pb, Cd, Cr, Cu, Mn, Fe, Ni, and As) during pregnancy were matched based on the mother's National Health Insurance registration area. SO₂ (OR: 2.723, 95% CI: 1.971-3.761) and Pb (OR: 1.063, 95% CI: 1.019-1.11) were more closely associated with the incidence of ASD when infants were exposed to them in the third trimester of pregnancy. Pb (OR: 1.109, 95% CI: 1.043-1.179) in the first trimester of pregnancy and Cd (OR: 2.193, 95% CI: 1.074-4.477) in the third trimester of pregnancy were associated with the incidence of epilepsy. Thus, exposure to SO₂, NO₂, and Pb during pregnancy could affect the development of a neurologic disorder based on the timing of exposure, suggesting a relationship with fetal development. However, further research is needed.

Iodine Deficiency, Maternal Hypothyroxinemia and Endocrine Disrupters Affecting Fetal Brain Development: A Scoping Review

This scoping review critically discusses the publications of the last 30 years on the impact of mild to moderate iodine deficiency and the additional impact of endocrine disrupters during pregnancy on embryonal/fetal brain development. An asymptomatic mild to moderate iodine deficiency and/or isolated maternal hypothyroxinemia might affect the development of the embryonal/fetal brain. There is sufficient evidence underlining the importance of an adequate iodine supply for all women of childbearing age in order to prevent negative mental and social consequences for their children. An additional threat to the thyroid hormone system is the ubiquitous exposure to endocrine disrupters, which might exacerbate the effects of iodine deficiency in pregnant women on the neurocognitive development of their offspring. Ensuring adequate iodine intake is therefore essential not only for healthy fetal and neonatal development in general, but it might also extenuate the effects of endocrine disruptors. Individual iodine supplementation of women of childbearing age living in areas with mild to moderate iodine deficiency is mandatory as long as worldwide universal salt iodization does not guarantee an adequate iodine supply. There is an urgent need for detailed strategies to identify and reduce exposure to endocrine disrupters according to the "precautional principle".

Exposure to local, source-specific ambient air pollution during pregnancy and autism in children: a cohort study from southern Sweden

Evidence of air pollution exposure, namely, ambient particulate matter (PM), during pregnancy and an increased risk of autism in children is growing; however, the unique PM sources that contribute to this association are currently unknown. The aim of the present study was to investigate local, source-specific ambient PM exposure during pregnancy and its associations with childhood autism, specifically, and autism spectrum disorders (ASD) as a group. A cohort of 40,245 singleton births from 2000 to 2009 in Scania, Sweden, was combined with data on locally emitted PM with an aerodynamic diameter < 2.5 µm (PM_2.5). A flat, two-dimensional dispersion model was used to assess local PM_2.5 concentrations (all-source PM_2.5, small-scale residential heating- mainly wood burning, tailpipe exhaust, and vehicle wear-and-tear) at the mother's residential address during pregnancy. Associations were analyzed using binary logistic regression. Exposure to local PM_2.5 during pregnancy from each of the investigated sources was associated with childhood autism in the fully adjusted models. For ASD, similar, but less pronounced, associations were found. The results add to existing evidence that exposure to air pollution during pregnancy may be associated with an increased risk of childhood autism. Further, these findings suggest that locally produced emissions from both residential wood burning and road traffic-related sources (tailpipe exhaust and vehicle wear-and-tear) contribute to this association.

Particulate matter exposure during pregnancy and infancy and risks of autism spectrum disorder in children: A systematic review and meta-analysis

PURPOSE

This meta-analysis aimed to clarify the relationship between particulate matter (PM) and autism spectrum disorder (ASD) in detail.

METHODS

A systematic literature search was performed using eight databases before April 9, 2022. The estimated effects were combined separately according to the PM type. Subgroup analyses were conducted in terms of the study design type, study location, exposure window, birth year, and sex.

RESULTS

PM_2.5 was associated with an increased risk of ASD, while PM₁₀ was not. PMc, PM₁, and diesel particulate matter (DPM) were also associated with an increased risk of ASD. Specifically, a 10 μg/m³ increase in PM_2.5 was associated with a 1.337-fold increased risk of ASD in children, and a 10 μg/m³ increase in PMc and PM₁ may increase the risk of ASD by 1.062 and 3.643 times, respectively. PM_2.5 exposure may increase the risk of ASD in boys. Exposure to PMc might increase the risk of ASD in children born after the year 2000. The combined results of different PM differed between studies with continuous and non-continuous data for different study design type, study location, and birth year. The sensitive window for PM_2.5 exposure to increase the risk of ASD may be from the first, second, and third trimesters to the first year of the postnatal period. Exposure to PMc during pregnancy was significantly associated with ASD.

CONCLUSION

Exposure to PM_2.5 may increase the risk of ASD in boys. Exposure to PM_2.5 during the first, second, and third trimesters and postnatally increased the risk of ASD.

Evidence of transgenerational effects on autism spectrum disorder using multigenerational space-time cluster detection

Background

Transgenerational epigenetic risks associated with complex health outcomes, such as autism spectrum disorder (ASD), have attracted increasing attention. Transgenerational environmental risk exposures with potential for epigenetic effects can be effectively identified using space-time clustering. Specifically applied to ancestors of individuals with disease outcomes, space-time clustering characterized for vulnerable developmental stages of growth can provide a measure of relative risk for disease outcomes in descendants.

Objectives

(1) Identify space-time clusters of ancestors with a descendent with a clinical ASD diagnosis and matched controls. (2) Identify developmental windows of ancestors with the highest relative risk for ASD in descendants. (3) Identify how the relative risk may vary through the maternal or paternal line.

Methods

Family pedigrees linked to residential locations of ASD cases in Utah have been used to identify space-time clusters of ancestors. Control family pedigrees of none-cases based on age and sex have been matched to cases 2:1. The data have been categorized by maternal or paternal lineage at birth, childhood, and adolescence. A total of 3957 children, both parents, and maternal and paternal grandparents were identified. Bernoulli space-time binomial relative risk (RR) scan statistic was used to identify clusters. Monte Carlo simulation was used for statistical significance testing.

Results

Twenty statistically significant clusters were identified. Thirteen increased RR (> 1.0) space-time clusters were identified from the maternal and paternal lines at a p-value < 0.05. The paternal grandparents carry the greatest RR (2.86–2.96) during birth and childhood in the 1950’s–1960, which represent the smallest size clusters, and occur in urban areas. Additionally, seven statistically significant clusters with RR < 1 were relatively large in area, covering more rural areas of the state.

Conclusion

This study has identified statistically significant space-time clusters during critical developmental windows that are associated with ASD risk in descendants. The geographic space and time clusters family pedigrees with over 3 + generations, which we refer to as a person’s geographic legacy, is a powerful tool for studying transgenerational effects that may be epigenetic in nature. Our novel use of space-time clustering can be applied to any disease where family pedigree data is available.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12942-022-00313-4.

Maternal exposure to cooking oil fumes during pregnancy and autistic-like behaviors in Chinese preschoolers

There is growing evidence that cooking oil fumes (COFs) are harmful indoor air pollutants. However, there is a dearth of research investigating whether maternal COFs exposure during pregnancy may affect children's autistic-like behaviors in China. This study aimed to explore this association, and examine the effects of different cooking fuels and ventilation methods used by mothers on the presence of autistic-like behaviors. This study analyzed the survey data of the Longhua Child Cohort Study in 2017 with a total of 62,372 mothers enrolled in this study. A self-administrative questionnaire was used to collect information on socio-demographic characteristics, cooking habits during pregnancy, and autistic-like behaviors (measured using the Autism Behavior Checklist). After adjusting for potential confounders, the results showed that compared with children whose mothers never cooked during pregnancy, children whose mothers cooked sometimes, often, always during pregnancy had the higher risk of autistic-like behaviors. As the amounts of COFs exposed to and the frequency of cooking during pregnancy increased, the risk of a child's autistic-like behaviors also increased. Mothers using natural gas as cooking fuels had a lower risk of their child having autistic-like behaviors, compared with mothers using coal or other cooking fuels. Furthermore, pregnant women using ventilation measures during cooking significantly decreased likelihood of the presence of autistic-like behaviors in their children. These results suggest that maternal exposure to COFs during pregnancy may increase the likelihood of the presence of autistic-like behaviors in offspring. These findings support a recommendation that pregnant women should avoid exposure to COFs and use clean fuels and ventilation equipment in kitchens to reduce the risk of autistic-like behaviors in children.

The epidemiological evidence linking exposure to ambient particulate matter with neurodevelopmental disorders: A systematic review and meta-analysis

BACKGROUND

There has been increasing attention on the associations between ambient particulate matter (PM) in early-life and neurodevelopmental disorders (NDDs). However, the associations remained unclear when considering different types of NDDs and different sizes of PM, and vulnerable exposure windows during early-life were not identified yet.

OBJECTIVE

To synthesize the published literature on the associations between ambient particulate matter (PM) and risk of different types of neurodevelopmental disorders (NDDs) in a systematic review and meta-analysis.

METHODS

A systematic search of Medline, Embase, PubMed, Cochrane Library, and Web of Science was performed from inception through 24 January 2022. Two reviewers conducted the study selection, data extraction, and quality appraisal. A random-effects model was used for meta-analyses with two quality-of-evidence assessments (the Grading of Recommendations Assessment, Development, and Evaluation system and the best evidence synthesis system).

RESULTS

A total of 6554 articles were screened, of which 31 were included in the review, and 20 provided adequate data for meta-analyses. Exposures to particulate matter of 2.5 μm or less (PM_2.5) during prenatal periods (OR, 1.32 [95%CI, 1.03-1.69]), the first year after birth (OR, 1.62 [95%CI, 1.22-2.15]) and the second year after birth (OR, 3.13 [95%CI, 1.47-6.67]) were associated with increased risk of autism spectrum disorders (ASD) in children. The quality of evidence for these associations during early postnatal periods was somewhat moderate with limited studies. We found inconsistent evidence when considering other types of NDDs and different sizes of PM.

CONCLUSIONS AND RELEVANCE

Current evidence indicated that there might be an association between PM_2.5 exposure and higher risk of ASD, and early postnatal periods appeared to be the critical exposure window. High-quality studies are needed to assess the evidence for other types of NDDs.

Evidence of susceptibility to autism risks associated with early life ambient air pollution: A systematic review

BACKGROUND

Many studies have found associations between early life air pollution exposure and subsequent onset of autism spectrum disorder (ASD). However, characteristics that affect susceptibility remain unclear.

OBJECTIVE

This systematic review examined epidemiologic studies on the modifying roles of social, child, genetic and maternal characteristics in associations between prenatal and early postnatal air pollution exposure and ASD.

METHODS

A systematic literature search in PubMed and Embase was conducted. Studies that examined modifiers of the association between air pollution and ASD were included.

RESULTS

A total of 19 publications examined modifiers of the associations between early life air pollution exposures and ASD. In general, estimates of effects on risk of ASD in boys were larger than in girls (based on 11 studies). Results from studies of effects of family education (2 studies) and neighborhood deprivation (2 studies) on air pollution-ASD associations were inconsistent. Limited data (1 study) suggest pregnant women with insufficient folic acid intake might be more susceptible to ambient particulate matter less than 2.5 μm (PM_2.5) and 10 μm (PM₁₀) in aerodynamic diameter, and to nitrogen dioxide (NO₂). Children of mothers with gestational diabetes had increased risk of ozone-associated ASD (1 study). Two genetic studies reported that copy number variations may amplify the effect of ozone, and MET rs1858830 CC genotype may augment effects of PM and near-roadway pollutants on ASD.

CONCLUSIONS

Child's sex, maternal nutrition or diabetes, socioeconomic factors, and child risk genotypes were reported to modify the effect of early-life air pollutants on ASD risk in the epidemiologic literature. However, the sparsity of studies on comparable modifying hypotheses precludes conclusive findings. Further research is needed to identify susceptible populations and potential targets for preventive intervention.

Maternal levels of acute phase proteins in early pregnancy and risk of autism spectrum disorders in offspring

Previous research supports a contribution of early-life immune disturbances in the etiology of autism spectrum disorders (ASD). Biomarker studies of the maternal innate (non-adaptive) immune status related to ASD risk have focused on one of the acute phase proteins (APP), C-reactive protein (CRP), with conflicting results. We evaluated levels of eight different APP in first-trimester maternal serum samples, from 318 mothers to ASD cases and 429 mothers to ASD-unaffected controls, nested within the register-based Stockholm Youth Cohort. While no overall associations between high levels of APP and ASD were observed, associations varied across diagnostic sub-groups based on co-occurring conditions. Maternal levels of CRP in the lowest compared to the middle tertile were associated with increased risk of ASD without ID or ADHD in offspring (OR = 1.92, 95% CI 1.08-3.42). Further, levels of maternal ferritin in the lowest (OR = 1.78, 95% CI 1.18-2.69) and highest (OR = 1.64, 95% CI 1.11-2.43) tertiles were associated with increased risk of any ASD diagnosis in offspring, with stronger associations still between the lowest (OR = 3.81, 95% CI 1.91-7.58) and highest (OR = 3.36, 95% CI 1.73-6.53) tertiles of ferritin and risk of ASD with ID. The biological interpretation of lower CRP levels among mothers to ASD cases is not clear but might be related to the function of the maternal innate immune system. The finding of aberrant levels of ferritin conferring risk of ASD-phenotypes indicates a plausibly important role of iron during neurodevelopment.

Outdoor light at night and autism spectrum disorder in Shanghai, China: A matched case-control study

BACKGROUND

Several environmental factors have been identified to be associated with autism spectrum disorder (ASD) over the past decades. However, evidence is limited for the effect of exposure to outdoor light at night (LAN) on ASD in China and even elsewhere in the world.

METHODS

Participants in this study were from a multi-stage sampling survey on ASD conducted between June 2014 and October 2014 among children aged 3-12 years in Shanghai, China. All participants underwent a two-stage screening of ASD via questionnaire, and then, suspected cases were finally diagnosed by clinical examination. For data analyses, each ASD case was randomly matched with 10 healthy controls by age and sex. The LAN data were extracted from the stable lights product of the US Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) according to geolocation information of residential addresses. Mean levels of exposure to LAN during the 3 years after birth and 1 year before birth were calculated. We used conditional logistic regression models to examine the association between LAN and ASD.

RESULTS

We investigated 84,934 children from 96 kindergartens, 55 primary schools, and 28 special education schools, and 203 children were diagnosed as ASD cases. A total of 1727 children (157 ASD cases and 1570 healthy controls) were included in the final analyses. Brighter LAN exposures after and before birth were significantly associated with higher risk of ASD. After adjusting for potential covariates, adjusted odd ratios and 95% confidence intervals associated with per unit increase in LAN were 1.066 (1.027, 1.107) during the 3 years after birth and 1.046 (1.018, 1.075) during the 1 year before birth.

CONCLUSIONS

Results of our study concluded brighter LAN exposure was significantly associated with higher risk of ASD among Chinese children, which suggested that outdoor LAN could be a potential risk factor of ASD.

Environmental exposures to pesticides, phthalates, phenols and trace elements are associated with neurodevelopment in the CHARGE study

OBJECTIVE

To determine if higher exposures measured in early childhood to environmental phenols, phthalates, pesticides, and/or trace elements, are associated with increased odds of having a diagnosis of Autism Spectrum Disorder (ASD), Developmental Delay (DD), or Other Early Concerns (OEC) compared to typically developing children (TD).

METHODS

This study included 627 children between the ages of 2-5 who participated in the Childhood Autism Risks from Genetics and Environment (CHARGE) study. Urine samples were collected at the same study visit where diagnostic assessments to confirm diagnosis indicated during the recruitment process were performed. Adjusted multinomial regression models of each chemical with diagnosis as the outcome were conducted. Additionally, two methods were used to analyze mixtures: repeated holdout multinomial weighted quantile sum (WQS) regression for each chemical class; and a total urinary mixture effect was assessed with repeated holdout random subset WQS.

RESULTS

Many urinary chemicals were associated with increased odds of ASD, DD or OEC compared to TD; however, most did not remain significant after false discovery rate adjustment. Repeated holdout WQS indices provided evidence for associations of both a phenol/paraben mixture effect and a trace element mixture effect on DD independently. In analyses adjusted for confounders and other exposures, results suggested an association of a pesticide mixture effect with increased risk for ASD. Results also suggested associations of a total urinary mixture with greater odds of both ASD and DD separately.

CONCLUSION

Higher concentrations of urinary biomarkers were associated with ASD, DD, and OEC compared to TD, with consistency of the results comparing single chemical analyses and mixture analyses. Given that the biospecimens used for chemical analysis were generally collected many months after diagnoses were made, the direction of any causal association is unknown. Hence findings may reflect higher exposures among children with non-typical development than TD children due to differences in behaviors, metabolism, or toxicokinetics.

In utero exposure to near-roadway air pollution and autism spectrum disorder in children

IMPORTANCE

Previous studies have reported associations between in utero exposure to regional air pollution and autism spectrum disorders (ASD). In utero exposure to components of near-roadway air pollution (NRAP) has been linked to adverse neurodevelopment in animal models, but few studies have investigated NRAP association with ASD risk.

OBJECTIVE

To identify ASD risk associated with in utero exposure to NRAP in a large, representative birth cohort.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective pregnancy cohort study included 314,391 mother-child pairs of singletons born between 2001 and 2014 at Kaiser Permanente Southern California (KPSC) hospitals. Maternal and child data were extracted from KPSC electronic medical records. Children were followed until: clinical diagnosis of ASD, non-KPSC membership, death, or December 31, 2019, whichever came first. Exposure to the complex NRAP mixture during pregnancy was assessed using line-source dispersion models to estimate fresh vehicle emissions from freeway and non-freeway sources at maternal addresses during pregnancy. Vehicular traffic load exposure was characterized using advanced telematic models combining traditional traffic counts and travel-demand models with cell phone and vehicle GPS data. Cox proportional-hazard models estimated hazard ratios (HR) of ASD associated with near-roadway traffic load and dispersion-modeled NRAP during pregnancy, adjusted for covariates. Non-freeway NRAP was analyzed using quintile distribution due to nonlinear associations with ASD.

EXPOSURES

Average NRAP and traffic load exposure during pregnancy at maternal residential addresses.

MAIN OUTCOMES

Clinical diagnosis of ASD.

RESULTS

A total of 6,291 children (5,114 boys, 1,177 girls) were diagnosed with ASD. The risk of ASD was associated with pregnancy-average exposure to total NRAP [HR(95% CI): 1.03(1.00,1.05) per 5 ppb increase in dispersion-modeled NOx] and to non-freeway NRAP [HR(95% CI) comparing the highest to the lowest quintile: 1.19(1.11, 1.27)]. Total NRAP had a stronger association in boys than in girls, but the association with non-freeway NRAP did not differ by sex. The association of freeway NRAP with ASD risk was not statistically significant. Non-freeway traffic load exposure demonstrated associations with ASD consistent with those of NRAP and ASD.

CONCLUSIONS

In utero exposure to near-roadway air pollution, particularly from non-freeway sources, may increase ASD risk in children.

Adverse effects of prenatal exposure to residential dust on post-natal brain development

BACKGROUND

Previous studies have shown an association between prenatal exposure to particulate matter (PM) and adverse brain development. However, it is unclear whether gestational exposure to community-sampled residential PM has an impact on the developing brain.

OBJECTIVES

We aimed to test whether in utero exposure to PM from residential roof spaces (ceiling voids) alters critical foetal neurodevelopmental processes.

METHODS

Pregnant C57BL/6 mice were intranasally exposed to 100 μg of roof space particles (~5 mg kg^-1) in 50 μl of saline, or saline alone under light methoxyflurane anaesthesia, throughout mid-to-late gestation. At 2 weeks post-natal age, pups were sacrificed and assessed for body and brain growth. The brain tissue was collected and examined for a range of neurodevelopmental markers for synaptogenesis, synaptic plasticity, gliogenic events and myelination by immunohistochemistry.

RESULTS

Gestational exposure to roof space PM reduced post-natal body and brain weights. There was no significant effect of roof space PM exposure on synaptogenesis, synaptic plasticity or astrocyte density. However, PM exposure caused increased myelin load in the white matter and elevated microglial density which was dependent on the PM sample. These effects were found to be consistent between male and female mice.

CONCLUSIONS

Our data suggest that exposure to residential roof space PM during pregnancy impairs somatic growth and causes neuropathological changes in the developing brain.

Interdisciplinary data science to advance environmental health research and improve birth outcomes

Rates of preterm birth and low birthweight continue to rise in the United States and pose a significant public health problem. Although a variety of environmental exposures are known to contribute to these and other adverse birth outcomes, there has been a limited success in developing policies to prevent these outcomes. A better characterization of the complexities between multiple exposures and their biological responses can provide the evidence needed to inform public health policy and strengthen preventative population-level interventions. In order to achieve this, we encourage the establishment of an interdisciplinary data science framework that integrates epidemiology, toxicology and bioinformatics with biomarker-based research to better define how population-level exposures contribute to these adverse birth outcomes. The proposed interdisciplinary research framework would 1) facilitate data-driven analyses using existing data from health registries and environmental monitoring programs; 2) develop novel algorithms with the ability to predict which exposures are driving, in this case, adverse birth outcomes in the context of simultaneous exposures; and 3) refine biomarker-based research, ultimately leading to new policies and interventions to reduce the incidence of adverse birth outcomes.

Autism spectrum disorder and air pollution: A systematic review and meta-analysis

Despite the widely-known effects of air pollution, pollutants exposure surrounding pregnancy and the risk for autism spectrum disorder (ASD) in newborns remains controversial. The purpose of our study was to carry out a systematic review and meta-analyses of the risk of ASD in newborns following air pollution exposure during the perinatal period (preconception to second year of life). The PubMed, Cochrane Library, Embase and ScienceDirect databases were searched for articles, published up to July 2020, with the keywords "air pollution" and "autism". Three models were used for each meta-analysis: a global model based on all risks listed in included articles, a pessimistic model based on less favorable data only, and an optimistic model based on the most favorable data only. 28 studies corresponding to a total of 758 997 newborns were included (47190 ASD and 703980 controls). Maternal exposure to all pollutants was associated with an increased risk of ASD in newborns by 3.9% using the global model and by 12.3% using the optimistic model, while the pessimistic model found no change. Each increase of 5 μg/m³ in particulate matter <2.5 μm (PM2.5) was associated with an increased risk of ASD in newborns, regardless of the model used (global +7%, pessimistic +5%, optimistic +15%). This risk increased during preconception (global +17%), during pregnancy (global +5%, and optimistic +16%), and during the postnatal period (global +11% and optimistic +16%). Evidence levels were poor for other pollutants (PM10, NOx, O3, metals, solvents, styrene, PAHs, pesticides). PM2.5 was associated with a greater risk than PM10 (coefficient 0.20, 95CI -0.02 to 0.42), NOx (0.29, 0.08 to 0.50) or solvents (0.24, 0.04 to 0.44). All models revealed that exposure to pollutants, notably PM2.5 during pregnancy, was associated with an increased risk of ASD in newborns. Pregnancy and postnatal periods seem to be the most at-risk periods.

Assessing the Impact of Wildfires on the Use of Black Carbon as an Indicator of Traffic Exposures in Environmental Epidemiology Studies

Epidemiological studies frequently use black carbon (BC) as a proxy for traffic-related air pollution (TRAP). However, wildfire smoke (WFS) represents an important source of BC not often considered when using BC as a proxy for TRAP. Here, we examined the potential for WFS to bias TRAP exposure assessments based on BC measurements. Weekly integrated BC samples were collected across the Denver, CO region from May to November 2018. We collected 609 filters during our sampling campaigns, 35% of which were WFS-impacted. For each filter we calculated an average BC concentration. We assessed three GIS-based indicators of TRAP for each sampling location: annual average daily traffic within a 300 m buffer, the minimum distance to a highway, and the sum of the lengths of roadways within 300 m. Median BC concentrations were 9% higher for WFS-impacted filters (median = 1.14 μg/m3, IQR = 0.23 μg/m3) than nonimpacted filters (median = 1.04 μg/m3, IQR = 0.48 μg/m3). During WFS events, BC concentrations were elevated and expected spatial gradients in BC were reduced. We conducted a simulation study to estimate TRAP exposure misclassification as the result of regional WFS. Our results suggest that linear health effect estimates were biased away from the null when WFS was present. Thus, exposure assessments relying on BC as a proxy for TRAP may be biased by wildfire events. Alternative metrics that account for the influence of "brown" carbon associated with biomass burning may better isolate the effects of traffic emissions from those of other black carbon sources.

Prenatal air pollution exposure and neurodevelopment: A review and blueprint for a harmonized approach within ECHO

BACKGROUND

Air pollution exposure is ubiquitous with demonstrated effects on morbidity and mortality. A growing literature suggests that prenatal air pollution exposure impacts neurodevelopment. We posit that the Environmental influences on Child Health Outcomes (ECHO) program will provide unique opportunities to fill critical knowledge gaps given the wide spatial and temporal variability of ECHO participants.

OBJECTIVES

We briefly describe current methods for air pollution exposure assessment, summarize existing studies of air pollution and neurodevelopment, and synthesize this information as a basis for recommendations, or a blueprint, for evaluating air pollution effects on neurodevelopmental outcomes in ECHO.

METHODS

We review peer-reviewed literature on prenatal air pollution exposure and neurodevelopmental outcomes, including autism spectrum disorder, attention deficit hyperactivity disorder, intelligence, general cognition, mood, and imaging measures. ECHO meta-data were compiled and evaluated to assess frequency of neurodevelopmental assessments and prenatal and infancy residential address locations. Cohort recruitment locations and enrollment years were summarized to examine potential spatial and temporal variation present in ECHO.

DISCUSSION

While the literature provides compelling evidence that prenatal air pollution affects neurodevelopment, limitations in spatial and temporal exposure variation exist for current published studies. As >90% of the ECHO cohorts have collected a prenatal or infancy address, application of advanced geographic information systems-based models for common air pollutant exposures may be ideal to address limitations of published research.

CONCLUSIONS

In ECHO we have the opportunity to pioneer unifying exposure assessment and evaluate effects across multiple periods of development and neurodevelopmental outcomes, setting the standard for evaluation of prenatal air pollution exposures with the goal of improving children's health.

Early life exposure to air pollution impacts neuronal and glial cell function leading to impaired neurodevelopment

The World Health Organisation recently listed air pollution as the most significant threat to human health. Air pollution comprises particulate matter (PM), metals, black carbon and gases such as ozone (O₃ ), nitrogen dioxide (NO₂ ) and carbon monoxide (CO). In addition to respiratory and cardiovascular disease, PM exposure is linked with increased risk of neurodegeneration as well as neurodevelopmental impairments. Critically, studies suggest that PM crosses the placenta, making direct in utero exposure a reality. Rodent models reveal that neuroinflammation, neurotransmitter imbalance and oxidative stress are triggered following gestational/early life exposure to PM, and may be exacerbated by concomitant mitochondrial dysfunction. Gestational PM exposure (potentiated by mitochondrial impairment in the metabolically active neonatal brain) not only impacts neurodevelopment but may sensitise the brain to subsequent cognitive impairment. Having reviewed this field, we conclude that strategies are urgently required to reduce exposure to PM during this sensitive developmental period.

A Spatiotemporal Prediction Model for Black Carbon in the Denver Metropolitan Area, 2009-2020

Studies on health effects of air pollution from local sources require exposure assessments that capture spatial and temporal trends. To facilitate intraurban studies in Denver, Colorado, we developed a spatiotemporal prediction model for black carbon (BC). To inform our model, we collected more than 700 weekly BC samples using personal air samplers from 2018 to 2020. The model incorporated spatial and spatiotemporal predictors and smoothed time trends to generate point-level weekly predictions of BC concentrations for the years 2009-2020. Our results indicate that our model reliably predicted weekly BC concentrations across the region during the year in which we collected data. We achieved a 10-fold cross-validation R² of 0.83 and a root-mean-square error of 0.15 μg/m³ for weekly BC concentrations predicted at our sampling locations. Predicted concentrations displayed expected temporal trends, with the highest concentrations predicted during winter months. Thus, our prediction model improves on typical land use regression models that generally only capture spatial gradients. However, our model is limited by a lack of long-term BC monitoring data for full validation of historical predictions. BC predictions from the weekly spatiotemporal model will be used in traffic-related air pollution exposure-disease associations more precisely than previous models for the region have allowed.

Early-Life Exposure to Environmental Air Pollution and Autism Spectrum Disorder: A Review of Available Evidence

The number of children diagnosed with Autism Spectrum Disorder (ASD) has rapidly increased globally. Genetic and environmental factors both contribute to the development of ASD. Several studies showed linkage between prenatal, early postnatal air pollution exposure and the risk of developing ASD. We reviewed the available literature concerning the relationship between early-life exposure to air pollutants and ASD onset in childhood. We searched on Medline and Scopus for cohort or case-control studies published in English from 1977 to 2020. A total of 20 articles were selected for the review. We found a strong association between maternal exposure to particulate matter (PM) during pregnancy or in the first years of the children’s life and the risk of the ASD. This association was found to be stronger with PM_2.5 and less evident with the other pollutants. Current evidence suggest that pregnancy is the period in which exposure to environmental pollutants seems to be most impactful concerning the onset of ASD in children. Air pollution should be considered among the emerging risk factors for ASD. Further epidemiological and toxicological studies should address molecular pathways involved in the development of ASD and determine specific cause–effect associations.

Autism spectrum disorder in the United Arab Emirates: potential environmental links

Autism spectrum disorder (ASD) has been experiencing an increase in global prevalence in recent decades. While many factors could account for this reality, certain environmental links have been shown to contribute to ASD development and etiology. The Middle East has had relatively little published research on ASD etiology although statistics indicate that ASD affects 1 in 146 births in the United Arab Emirates (UAE). This review therefore aims to examine potential causes of ASD within the UAE specifically, focusing on environmental links that may contribute to the rise in ASD cases in this population. Significantly, suboptimal breastfeeding practices, high levels of vitamin D deficiency, increased exposure to pollution, pesticides and heavy metals within the UAE may all be potentially important contributing factors to ASD in this population. Our findings support the notion that there are key links between various environmental factors and ASD prevalence in the UAE. The lack of knowledge and much research on ASD within the UAE deeply necessitates further studies on its etiology as it poses a serious public health challenge in the region and globally.

Letter to the Editor: Comment on "Maternal exposure to air pollution and risk of autism in children: A systematic review and meta-analysis"

Comment on "Maternal exposure to air pollution and risk of autism in children: A systematic review and meta-analysis". Some points and/or limitations of their review and meta-analysis should be discussed.

Ambient Air Pollution Increases the Risk of Cerebrovascular and Neuropsychiatric Disorders through Induction of Inflammation and Oxidative Stress

Exposure to ambient air pollution is a well-established determinant of health and disease. The Lancet Commission on pollution and health concludes that air pollution is the leading environmental cause of global disease and premature death. Indeed, there is a growing body of evidence that links air pollution not only to adverse cardiorespiratory effects but also to increased risk of cerebrovascular and neuropsychiatric disorders. Despite being a relatively new area of investigation, overall, there is mounting recent evidence showing that exposure to multiple air pollutants, in particular to fine particles, may affect the central nervous system (CNS) and brain health, thereby contributing to increased risk of stroke, dementia, Parkinson's disease, cognitive dysfunction, neurodevelopmental disorders, depression and other related conditions. The underlying molecular mechanisms of susceptibility and disease remain largely elusive. However, emerging evidence suggests inflammation and oxidative stress to be crucial factors in the pathogenesis of air pollution-induced disorders, driven by the enhanced production of proinflammatory mediators and reactive oxygen species in response to exposure to various air pollutants. From a public health perspective, mitigation measures are urgent to reduce the burden of disease and premature mortality from ambient air pollution.

Maternal exposure to air pollution and risk of autism in children: A systematic review and meta-analysis

BACKGROUND

The number of children diagnosed with autism spectrum disorder (ASD) has been increasing. Previous studies suggested potential association between pregnancy air pollution exposure and ASD. This systematic review and meta-analysis is intended to summarize the association between maternal exposure to outdoor air pollution and ASD in children by trimester based on recent studies.

METHODS

A systematic literature search in 3 databases (Medline, Embase, and Web of Science) was performed using subject headings related to ASD and air pollution since 2007. Eligible studies were screened and evaluated based on predetermined criteria. For meta-analyses, the studies were grouped by air pollutant and exposure time (prenatal period and trimesters). Within-group studies were standardized by log odds ratio (OR) and then combined by three meta-analysis methods: frequentist fixed and random effects models, and Bayesian random effects model.

RESULTS

Initial search identified 1564 papers, of which 25 studies remained for final analysis after duplicates and ineligible studies were removed. Of the 25 studies, 13, 14, 12, and 7 studies investigated ASD in children associated with PM_2.5, PM₁₀, NO₂, and ozone, respectively. The frequentist and Bayesian random effects models resulted in different statistical significance. For prenatal period, frequentist meta-analysis returned significant pooled ORs with 95% confidence intervals, 1.06(1.01,1.11) for PM_2.5 and 1.02(1.01,1.04) for NO₂, whereas Bayesian meta-analysis showed similar ORs with wider 95% posterior intervals, 1.06(1.00,1.13) for PM_2.5 and 1.02(1.00,1.05) for NO₂. Third trimester appeared to have higher pooled ORs for PM_2.5, PM₁₀, and ozone, but patterns in the time-varying associations over the trimester were inconsistent.

CONCLUSIONS

For positive association between maternal exposure to ambient air pollution and ASD in children, there is some evidence for PM_2.5, weak evidence for NO₂ and little evidence for PM₁₀ and ozone. However, patterns in associations over trimesters were inconsistent among studies and among air pollutants.

Prenatal exposure to air pollution as a potential risk factor for autism and ADHD

Genetic and environmental factors both contribute to the development of Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD). One suggested environmental risk factor for ASD and ADHD is air pollution, but knowledge of its effects, especially in low-exposure areas, are limited. Here, we investigate risks for ASD and ADHD associated with prenatal exposure to air pollution in an area with air pollution levels generally well below World Health Organization (WHO) air quality guidelines. We used an epidemiological database (MAPSS) consisting of virtually all (99%) children born between 1999 and 2009 (48,571 births) in the study area, in southern Sweden. MAPSS consists of data on modelled nitrogen oxide (NO_x) levels derived from a Gaussian dispersion model; maternal residency during pregnancy; perinatal factors collected from a regional birth registry; and socio-economic factors extracted from Statistics Sweden. All ASD and ADHD diagnoses in our data were undertaken at the Malmö and Lund Departments of Child and Adolescent Psychiatry, using standardized diagnostic instruments. We used logistic regression analyses to obtain estimates of the risk of developing ASD and ADHD associated with different air pollution levels, with adjustments for potential perinatal and socio-economic confounders. In this longitudinal cohort study, we found associations between air pollution exposure during the prenatal period and and the risk of developing ASD. For example, an adjusted Odds Ratio (OR) of 1.40 and its 95% Confidence Interval (CI) (95% CI: 1.02-1.93) were found when comparing the fourth with the first quartile of NO_x exposure. We did not find similar associations on the risk of developing ADHD. This study contributes to the growing evidence of a link between prenatal exposure to air pollution and autism spectrum disorders, suggesting that prenatal exposure even below current WHO air quality guidelines may increase the risk of autism spectrum disorders.

Pharmacological, non-pharmacological and stem cell therapies for the management of autism spectrum disorders: A focus on human studies

In the last decade, the prevalence of autism spectrum disorders (ASD) has dramatically escalated worldwide. Currently available drugs mainly target some co-occurring symptoms of ASD, but are not effective on the core symptoms, namely impairments in communication and social interaction, and the presence of restricted and repetitive behaviors. On the other hand, transplantation of hematopoietic and mesenchymal stem cells in ASD children has been shown promising to stimulate the recruitment, proliferation, and differentiation of tissue-residing native stem cells, reducing inflammation, and improving some ASD symptoms. Moreover, several comorbidities have also been associated with ASD, such as immune dysregulation, gastrointestinal issues and gut microbiota dysbiosis. Non-pharmacological approaches, such as dietary supplementations with certain vitamins, omega-3 polyunsaturated fatty acids, probiotics, some phytochemicals (e.g., luteolin and sulforaphane), or overall diet interventions (e.g., gluten free and casein free diets) have been considered for the reduction of such comorbidities and the management of ASD. Here, interventional studies describing pharmacological and non-pharmacological treatments in ASD children and adolescents, along with stem cell-based therapies, are reviewed.

Air pollution, neighborhood deprivation, and autism spectrum disorder in the Study to Explore Early Development

Background

To examine whether neighborhood deprivation modifies the association between early life air pollution exposure and autism spectrum disorder (ASD), we used resources from a multisite case-control study, the Study to Explore Early Development.

Methods

Cases were 674 children with confirmed ASD born in 2003-2006; controls were 855 randomly sampled children born during the same time period and residents of the same geographic areas as cases. Air pollution was assessed by roadway proximity and particulate matter <2.5 μm (PM_2.5) exposure during pregnancy and first year of life. To characterize neighborhood deprivation, an index was created based on eight census tract-level socioeconomic status-related parameters. The continuous index was categorized into tertiles, representing low, moderate, and high deprivation. Logistic regression was used to estimate odds ratios (ORs) and corresponding 95% confidence intervals (CIs).

Results

Neighborhood deprivation modified (P _{for interaction} = 0.08) the association between PM_2.5 exposure during the first year of life and ASD, with a stronger association for those living in high (OR = 2.42, 95% CI = 1.20, 4.86) rather than moderate (OR=1.21, 95% CI = 0.67, 2.17) or low (OR=1.46, 95% CI = 0.80, 2.65) deprivation neighborhoods. Departure from additivity or multiplicativity was not observed for roadway proximity or exposures during pregnancy.

Conclusion

These results provide suggestive evidence of interaction between neighborhood deprivation and PM_2.5 exposure during the first year of life in association with ASD.

Airborne Particulate Matter: Human Exposure and Health Effects

OBJECTIVE

Exposure to airborne particulate matter (PM) is estimated to cause millions of premature deaths annually. This work conveys known routes of exposure to PM and resultant health effects.

METHODS

A review of available literature.

RESULTS

Estimates for daily PM exposure are provided. Known mechanisms by which insoluble particles are transported and removed from the body are discussed. Biological effects of PM, including immune response, cytotoxicity, and mutagenicity, are reported. Epidemiological studies that outline the systemic health effects of PM are presented.

CONCLUSION

While the integrated, per capita, exposure of PM for a large fraction of the first-world may be less than 1 mg per day, links between several syndromes, including attention deficit hyperactivity disorder (ADHD), autism, loss of cognitive function, anxiety, asthma, chronic obstructive pulmonary disease (COPD), hypertension, stroke, and PM exposure have been suggested. This article reviews and summarizes such links reported in the literature.

The association between particulate matter 2.5 exposure and children with autism spectrum disorder

OBJECTIVE

Particulate matter (PM) as an environmental pollutant is suspected to be associated with autism spectrum disorder (ASD). The aim of this study was to assess whether exposures to PM_2.5 during the first three years of life in relation to the risk and degree of the severity of ASD.

METHODS

A total of two hundred and ninety-seven 3-6 years old Chinese children (99 confirmed autism cases and 198 their age-gender matched control subjects) were included. Children's exposures to PM_2.5 (particulate matter with aerodynamic diameter <2.5 μm) during the first three years after birth were estimated. Logistic regression analysis was used to examine the PM_2.5-ASD association.

RESULTS

The mean levels of PM_2.5 exposures in ASD and typical developmental children during the first three years of life were 89.8[standard deviations (SD): 6.1] μg/m³ and 87.3(6.6) μg/m3, respectively (p = 0.002). A statistically significant positive correlation was found between the serum levels of PM_2.5 and the Childhood Autism Rating Scale (CARS) score indicating severity of autism (r = 0.259; p = 0.010). Based on the receiver operating characteristic (ROC) curve, the optimal cutoff value of PM_2.5 levels as an indicator for auxiliary diagnosis of ASD was projected to be 89.5ug/m³, which yielded a sensitivity of 65.4% and a specificity of 63.2%, with the area under the curve at 0.61 (95% confidence intervals [CIs], 0.54-0.68; P < 0.001). Multivariate analysis models were used to assess ASD risk according to PM_2.5 quartiles (the lowest quartile [Q1] as the reference), with the adjusted odds ratios (ORs) (95% CIs) were recorded. As shown in the Table 2, the 3rd and 4th quartile of PM_2.5 were compared against the Q1, and the risks were increased by 103% (OR = 2.03; 95%CI: 1.13-5.54; p = 0.015) and 311% (4.15; 2.04-9.45; p = 0.002), respectively.

CONCLUSIONS

To conclude, the evidence from this study allowed us to conclude that there was an association between PM_2.5 exposure and ASD risk and severity.

Towards a fuller assessment of benefits to children's health of reducing air pollution and mitigating climate change due to fossil fuel combustion

BACKGROUND

Fossil fuel combustion by-products, including particulate matter (PM_2.5), polycyclic aromatic hydrocarbons (PAH), nitrogen dioxide (NO₂) and carbon dioxide (CO₂), are a significant threat to children's health and equality. Various policies to reduce emissions have been implemented to reduce air pollution and mitigate climate change, with sizeable estimated health and economic benefits. However, only a few adverse outcomes in children have been considered, resulting in an undercounting of the benefits to this vulnerable population.

OBJECTIVES

Our goal was to expand the suite of child health outcomes addressed by programs to assess health and economic benefits, such as the Environmental Protection Agency (EPA) Benefits Mapping and Analysis Program (BenMAP), by identifying concentration-response (C-R) functions for six outcomes related to PM_2.5, NO₂, PAH, and/or PM₁₀: preterm birth (PTB), low birthweight (LBW), autism, attention deficit hyperactivity disorder, IQ reduction, and the development of childhood asthma.

METHODS

We conducted a systematic review of the literature published between January 1, 2000 and April 30, 2018 to identify relevant peer-reviewed case-control and cohort studies and meta-analyses. In some cases meta-analyses were available that provided reliable C-R functions and we assessed their consistency with subsequent studies. Otherwise, we reviewed all eligible studies published between our search dates.

RESULTS

For each pollutant and health outcome, we present the characteristics of each selected study. We distinguish between C-R functions for endpoints having a causal or likely relationship (PTB, LBW, autism, asthma development) with the pollutants for incorporation into primary analyses and endpoints having a suggestive causal relationship with the pollutants (IQ reduction, ADHD) for secondary analyses.

CONCLUSION

We have identified C-R functions for a number of adverse health outcomes in children associated with air pollutants largely from fossil fuel combustion. Their incorporation into expanded assessments of health benefits of clean air and climate mitigation policies will provide an important incentive for preventive action.

Ambient ozone and fine particulate matter exposures and autism spectrum disorder in metropolitan Cincinnati, Ohio

BACKGROUND

Epidemiological studies report fairly consistent associations between various air pollution metrics and autism spectrum disorder (ASD), with some elevated risks reported for different prenatal and postnatal periods.

OBJECTIVES

To examine associations between ASD and ambient fine particulate matter (PM_2.5) and ozone concentrations during the prenatal period through the second year of life in a case-control study.

METHODS

ASD cases (n = 428) diagnosed at Cincinnati Children's Hospital Medical Center were frequency matched (15:1) to 6420 controls from Ohio birth records. We assigned daily PM_2.5 and ozone estimates for 2005-2012 from US EPA's Fused Air Quality Surface Using Downscaling model to each participant for each day based on the mother's census tract of residence at birth. We calculated adjusted odds ratios (aORs) using logistic regression across continuous and categorical exposure window averages (trimesters, first and second postnatal years, and cumulative measure), adjusting for maternal- and birth-related confounders, both air pollutants, and multiple temporal exposure windows.

RESULTS

We detected elevated aORs for PM_2.5 during the 2nd trimester, 1st year of life, and a cumulative period from pregnancy through the 2nd year (aOR ranges across categories: 1.41-1.44, 1.54-1.84, and 1.41-1.52 respectively), and for ozone in the 2nd year of life (aOR range across categories: 1.29-1.42). Per each change in IQR, we observed elevated aORs for ozone in the 3rd trimester, 1st and 2nd years of life, and the cumulative period (aOR range: 1.19-1.27) and for PM_2.5 in the 2nd trimester, 1st year of life, and the cumulative period (aOR range: 1.11-1.17).

DISCUSSION

We saw limited evidence of linear exposure-response relationships for ASD with increasing air pollution, but the elevated aORs detected for PM_2.5 in upper exposure categories and per IQR unit increases were similar in magnitude to those reported in previous studies, especially for postnatal exposures.

Environmental Chemicals and Autism: A Scoping Review of the Human and Animal Research

BACKGROUND

Estimates of autism prevalence have increased dramatically over the past two decades. Evidence suggests environmental factors may contribute to the etiology of the disorder.

OBJECTIVES

This scoping review aimed to identify and categorize primary research and reviews on the association between prenatal and early postnatal exposure to environmental chemicals and the development of autism in epidemiological studies and rodent models of autism.

METHODS

PubMed was searched through 8 February 2018. Included studies assessed exposure to environmental chemicals prior to 2 months of age in humans or 14 d in rodents. Rodent studies were considered relevant if they included at least one measurement of reciprocal social communicative behavior or repetitive and stereotyped behavior. Study details are presented in interactive displays using Tableau Public.

RESULTS

The search returned 21,603 unique studies, of which 54 epidemiological studies, 46 experimental rodent studies, and 50 reviews were deemed relevant, covering 152 chemical exposures. The most frequently studied exposures in humans were particulate matter ([Formula: see text]), mercury ([Formula: see text]), nonspecific air pollution ([Formula: see text]), and lead ([Formula: see text]). In rodent studies, the most frequently studied exposures were chlorpyrifos ([Formula: see text]), mercury ([Formula: see text]), and lead ([Formula: see text]).

DISCUSSION

Although research is growing rapidly, wide variability exists in study design and conduct, exposures investigated, and outcomes assessed. Conclusions focus on recommendations to guide development of best practices in epidemiology and toxicology, including greater harmonization across these fields of research to more quickly and efficiently identify chemicals of concern. In particular, we recommend chlorpyrifos, lead, and polychlorinated biphenyls (PCBs) be systematically reviewed in order to assess their relationship with the development of autism. There is a pressing need to move forward quickly and efficiently to understand environmental influences on autism in order to answer current regulatory questions and inform treatment and prevention efforts. https://doi.org/10.1289/EHP4386.

Association Between Air Pollution Exposure, Cognitive and Adaptive Function, and ASD Severity Among Children with Autism Spectrum Disorder

Prenatal exposure to air pollution has been associated with autism spectrum disorder (ASD) risk but no study has examined associations with ASD severity or functioning. Cognitive ability, adaptive functioning, and ASD severity were assessed in 327 children with ASD from the Childhood Autism Risks from Genetics and the Environment study using the Mullen Scales of Early Learning (MSEL), the Vineland Adaptive Behavior Scales (VABS), and the Autism Diagnostic Observation Schedule calibrated severity score. Estimates of nitrogen dioxide (NO₂), particulate matter (PM_2.5 and PM₁₀), ozone, and near-roadway air pollution were assigned to each trimester of pregnancy and first year of life. Increasing prenatal and first year NO₂ exposures were associated with decreased MSEL and VABS scores. Increasing PM₁₀ exposure in the third trimester was paradoxically associated with improved performance on the VABS. ASD severity was not associated with air pollution exposure.

Risk and Protective Environmental Factors Associated with Autism Spectrum Disorder: Evidence-Based Principles and Recommendations

Autism Spectrum Disorder (ASD) is a complex condition with early childhood onset, characterized by a set of common behavioral features. The etiology of ASD is not yet fully understood; however, it reflects the interaction between genetics and environment. While genetics is now a well-established risk factor, several data support a contribution of the environment as well. This paper summarizes the conclusions of a consensus conference focused on the potential pathogenetic role of environmental factors and on their interactions with genetics. Several environmental factors have been discussed in terms of ASD risk, namely advanced parental age, assisted reproductive technologies, nutritional factors, maternal infections and diseases, environmental chemicals and toxicants, and medications, as well as some other conditions. The analysis focused on their specific impact on three biologically relevant time windows for brain development: the periconception, prenatal, and early postnatal periods. Possible protective factors that might prevent or modify an ASD trajectory have been explored as well. Recommendations for clinicians to reduce ASD risk or its severity have been proposed. Developments in molecular biology and big data approaches, which are able to assess a large number of coexisting factors, are offering new opportunities to disentangle the gene⁻environment interplay that can lead to the development of ASD.

Association of Prenatal Exposure to Air Pollution With Autism Spectrum Disorder

IMPORTANCE

The etiology of autism spectrum disorder (ASD) is poorly understood, but prior studies suggest associations with airborne pollutants.

OBJECTIVE

To evaluate the association between prenatal exposures to airborne pollutants and ASD in a large population-based cohort.

DESIGN, SETTING, AND PARTICIPANTS

This population-based cohort encompassed nearly all births in Metro Vancouver, British Columbia, Canada, from 2004 through 2009, with follow-up through 2014. Children were diagnosed with ASD using a standardized assessment with the Autism Diagnostic Interview-Revised and Autism Diagnostic Observation Schedule. Monthly mean exposures to particulate matter with a diameter less than 2.5 µm (PM2.5), nitric oxide (NO), and nitrogen dioxide (NO2) at the maternal residence during pregnancy were estimated with temporally adjusted, high-resolution land use regression models. The association between prenatal air pollution exposures and the odds of developing ASD was evaluated using logistic regression adjusted for child sex, birth month, birth year, maternal age, maternal birthplace, and neighborhood-level urbanicity and income band. Data analysis occurred from June 2016 to May 2018.

EXPOSURES

Mean monthly concentrations of ambient PM2.5, NO, and NO2 at the maternal residence during pregnancy, calculated retrospectively using temporally adjusted, high-resolution land use regression models.

MAIN OUTCOMES AND MEASURES

Autism spectrum disorder diagnoses based on standardized assessment of the Autism Diagnostic Interview-Revised and Autism Diagnostic Observation Schedule. The hypothesis being tested was formulated during data collection.

RESULTS

In a cohort of 132 256 births, 1307 children (1.0%) were diagnosed with ASD by the age of 5 years. The final sample size for the PM2.5-adjusted model was 129 439 children, and for NO and NO2, it was 129 436 children; of these, 1276 (1.0%) were diagnosed with ASD. Adjusted odds ratios for ASD per interquartile range (IQR) were not significant for exposure to PM2.5 during pregnancy (1.04 [95% CI, 0.98-1.10] per 1.5 μg/m3 increase [IQR] in PM2.5) or NO2 (1.06 [95% CI, 0.99-1.12] per 4.8 ppb [IQR] increase in NO2) but the odds ratio was significant for NO (1.07 [95% CI, 1.01-1.13] per 10.7 ppb [IQR] increase in NO). Odds ratios for male children were 1.04 (95% CI, 0.98-1.10) for PM2.5; 1.09 (95% CI, 1.02-1.15) for NO; and 1.07 (95% CI, 1.00-1.13) for NO2. For female children, they were for 1.03 (95% CI, 0.90-1.18) for PM2.5; 0.98 (95% CI, 0.83-1.13) for NO; and 1.00 (95% CI, 0.86-1.16) for NO2.

CONCLUSIONS AND RELEVANCE

In a population-based birth cohort, we detected an association between exposure to NO and ASD but no significant association with PM2.5 and NO2.

Air pollution and Autism in Denmark

Supplemental Digital Content is available in the text.

Background:

Previous autism spectrum disorder (ASD) and air pollution studies focused on pregnancy exposures, but another vulnerable period is immediate postnatally. Here, we examined early life exposures to air pollution from the pre- to the postnatal period and ASD/ASD subtypes in the Danish population.

Methods:

With Danish registers, we conducted a nationwide case–control study of 15,387 children with ASD born 1989–2013 and 68,139 population controls matched by birth year and sex identified from the birth registry. We generated air dispersion geographic information system (AirGIS) model estimates for nitrogen dioxide (NO₂), sulfur dioxide (SO₂), particulate matter 2.5 (PM_2.5), and particulate matter 10 (PM₁₀) at mothers’ home from 9 months before to 9 months after pregnancy and calculated odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for parental age, neighborhood socioeconomic indicators, and maternal smoking using conditional logistic regression.

Results:

In models that included all exposure periods, we estimated adjusted ORs for ASD per interquartile range (IQR) increase for 9 months after pregnancy with NO₂ of 1.08 (95% CI = 1.01, 1.15) and with PM_2.5 of 1.06 (95% CI = 1.01, 1.11); associations were smaller for PM₁₀ (1.04; 95% CI = 1.00, 1.09) and strongest for SO₂ (1.21; 95% CI = 1.13, 1.29). Also, associations for pollutants were stronger in more recent years (2000–2013) and in larger cities compared with provincial towns/rural counties. For particles and NO₂, associations were only specific to autism and Asperger diagnoses.

Conclusions:

Our data suggest that air pollutant exposure in early infancy but not during pregnancy increases the risk of being diagnosed with autism and Asperger among children born in Denmark.

Is there a link between air pollution and mental disorders?

Several studies have demonstrated the association between air pollution and different medical conditions including respiratory and cardiovascular diseases. Air pollutants might have a role also in the etiology of mental disorders in the light of their toxicity on central nervous system. Purpose of the present manuscript was to review and summarize available data about an association between psychiatric disorders and air pollution. A research in the main database sources has been conducted to identify relevant papers about the topic. Different air pollutants and in particular PM and nitric oxides have been associated with poor mental health; long exposition to PM_2.5 has been associated with an increased risk of new onset of depressive symptoms (Cohen's effect size d: 0.05-0.81), while increased concentration of nitric dioxide in summer with worsening of existing depressive conditions (Cohen's effect size d: 0.05-1.77). However, the interpretation of these finding should take into account the retrospective design of most of studies, different periods of observations, confounding factors such as advanced age or medical comorbidity. Further studies with rigorous methodology are needed to confirm the results of available literature about this topic.

Local- and regional-scale air pollution modelling (PM10) and exposure assessment for pregnancy trimesters, infancy, and childhood to age 15 years: Avon Longitudinal Study of Parents And Children (ALSPAC)

We established air pollution modelling to study particle (PM₁₀) exposures during pregnancy and infancy (1990-1993) through childhood and adolescence up to age ~15 years (1991-2008) for the Avon Longitudinal Study of Parents And Children (ALSPAC) birth cohort. For pregnancy trimesters and infancy (birth to 6 months; 7 to 12 months) we used local (ADMS-Urban) and regional/long-range (NAME-III) air pollution models, with a model constant for local, non-anthropogenic sources. For longer exposure periods (annually and the average of birth to age ~8 and to age ~15 years to coincide with relevant follow-up clinics) we assessed spatial contrasts in local sources of PM₁₀ with a yearly-varying concentration for all background sources. We modelled PM₁₀ (μg/m³) for 36,986 address locations over 19 years and then accounted for changes in address in calculating exposures for different periods: trimesters/infancy (n = 11,929); each year of life to age ~15 (n = 10,383). Intra-subject exposure contrasts were largest between pregnancy trimesters (5^th to 95^th centile: 24.4-37.3 μg/m³) and mostly related to temporal variability in regional/long-range PM₁₀. PM₁₀ exposures fell on average by 11.6 μg/m³ from first year of life (mean concentration = 31.2 μg/m³) to age ~15 (mean = 19.6 μg/m³), and 5.4 μg/m³ between follow-up clinics (age ~8 to age ~15). Spatial contrasts in 8-year average PM₁₀ exposures (5^th to 95^th centile) were relatively low: 25.4-30.0 μg/m³ to age ~8 years and 20.7-23.9 μg/m³ from age ~8 to age ~15 years. The contribution of local sources to total PM₁₀ was 18.5%-19.5% during pregnancy and infancy, and 14.4%-17.0% for periods leading up to follow-up clinics. Main roads within the study area contributed on average ~3.0% to total PM₁₀ exposures in all periods; 9.5% of address locations were within 50 m of a main road. Exposure estimates will be used in a number of planned epidemiological studies.