Autism spectrum disorder (ASD) is a developmental disorder with symptoms that range from social and communication impairments to restricted interests and repetitive behavior and is the 4th most disabling condition for children aged 5-14. Risk factors of ASD are not fully understood. Environmental risk factors are believed to play a significant role in the ASD epidemic.Research focusing on air pollution exposure as an early-life risk factor of autism is growing, with numerous studies finding associations of traffic and industrial emissions with an increased risk of ASD. One of the possible mechanisms linking autism and air pollution exposure is metabolic dysfunction. However, there were no consensus about the key metabolic pathways and corresponding metabolite signatures in mothers and children that are altered by air pollution exposure and cause the ASD. Therefore, we performed a review of published papers examining the metabolomic signatures and metabolic pathways that are associated with either air pollution exposure or ASD risk in human studies.In conclusion, we found that dysregulated lipid, fatty acid, amino acid, neurotransmitter, and microbiome metabolisms are associated with both short-term and long-term air pollution exposure and the risk of ASD. These dysregulated metabolisms may provide insights into ASD etiology related to air pollution exposure, particularly during the perinatal period in which neurodevelopment is highly susceptible to damage from oxidative stress and inflammation.

Few studies have examined the association between greenness exposure and birth outcomes. This study aims to identify critical exposure time windows during preconception and pregnancy for the association between greenness exposure and birth weight. A cohort of 13 890 pregnant women and newborns in Shanghai, China from 2016–2019 were included in the study. We assessed greenness exposure using Normalized Difference Vegetation Index (NDVI) during the preconception and gestational periods, and evaluated the association with term birthweight, birthweight z -score, small-for-gestational age, and large-for-gestational age using linear and logistic regressions adjusting for key maternal and newborn covariates. Ambient temperature, relative humidity, ambient levels of fine particles (PM _2.5 ) and nitrogen dioxide (NO _2 ) assessed during the same period were adjusted for as sensitivity analyses. Furthermore, we explored the potential different effects by urbanicity and park accessibility through stratified analysis. We found that higher greenness exposure at the second trimester of pregnancy and averaged exposure during the entire pregnancy were associated with higher birthweight and birthweight Z -score. Specifically, a 0.1 unit increase in second trimester averaged NDVI value was associated with an increase in birthweight of 10.2 g (95% CI: 1.8–18.5 g) and in birthweight Z -score of 0.024 (0.003–0.045). A 0.1 unit increase in an averaged NDVI during the entire pregnancy was associated with 10.1 g (95% CI: 1.0–19.2 g) increase in birthweight and 0.025 (0.001–0.048) increase in birthweight Z -score. Moreover, the associations were larger in effect size among urban residents than suburban residents and among residents without park accessibility within 500 m compared to those with park accessibility within 500 m. Our findings suggest that increased greenness exposure, particularly during the second trimester, may be beneficial to birth weight in a metropolitan area.

Keywords: Metabolomics, Autism spectrum disorder, air pollution exposure, pregnancy, oxidative stress. Background: Prenatal PM2.5 and near-roadway air pollution (NRAP) exposures, particularly nonfreeway NRAP, have been associated with increased autism spectrum disorder (ASD) risk in children. However, the underlying biological mechanism is unclear. Aim: To investigate neonatal metabolic pathways altered by prenatal PM2.5 and NRAP exposures that increase ASD risk. Method: Using electronic medical records, 50 ASD cases diagnosed before age 5 and 50 controls matched on birth year, medical center, sex, and race/ethnicity were randomly selected from all children born at Kaiser Permanente Southern California between 2007-2009. Weekly PM2.5 and monthly nonfreeway NRAP exposures during pregnancy were estimated based on residential history using spatiotemporal prediction and California line-source dispersion models, respectively. Untargeted, high-resolution metabolomics was analyzed in archived newborn dry blood spots, resulting in 26,578 HILIC-positive and 27,614 C18-negative metabolomic features. Conditional logistic regression was used to identify metabolomic features associated with ASD diagnosis. Linear regression was used to investigate associations between prenatal air pollution exposure and metabolomic features. Beyond matching factors, maternal age, education level and household income categories were adjusted in the analyses. Mummichog pathway analysis was performed to identify metabolic pathways associated with prenatal air pollution exposure and ASD. Results: Dysregulated aspartate and asparagine metabolism was associated with increased ASD risk(p=0.01) and higher PM2.5 exposure during the 1st trimester and the entire pregnancy(p<0.001). Glutamate metabolism was associated with PM2.5 during pregnancy(p=0.028) and increased ASD risk(p=0.03). Prenatal nonfreeway NRAP was associated with altered nitrogen (p=0.027) and sialic acid metabolism(p=0.038), while nitrogen metabolism was also associated with increased ASD risk(p=0.02). Conclusion: Dysregulated metabolism reflected in aspartate, asparagine and glutamate was associated with both prenatal air pollution exposure, particularly PM2.5, and increased ASD risk, suggesting newborn oxidative stress and inflammation may be pathways of effects of prenatal air pollution exposure.

BACKGROUND AND AIM: Prenatal exposure to fine particulate matter (PM₂.₅), especially during second trimester, has been associated with lower birth weight in Maternal and Developmental Risks from Environmental and Social Stressors (MADRES) study. This study aims to investigate potential maternal metabolic pathways in third trimester mediating the association between second-trimester PM₂.₅ exposure and lower birth weight. METHOD: Based on the ongoing MADRES study in Los Angeles, 421 maternal serum samples collected at third trimester were analyzed for untargeted metabolomics using LC-MS. Daily estimates of PM₂.₅ concentrations were assigned to each participant's residential address using inverse-distance-squared weighted spatial interpolation and calculated as second-trimester averages. Birth weight and covariates were retrieved from electronic medical records or questionnaires. Metabolome-wide association studies were conducted using linear regression to identify metabolomic features associated with second-trimester PM₂.₅ exposure and birth weight Z-score, respectively. Metabolic pathways common to prenatal PM₂.₅ exposure and birth weight were identified using Mummichog pathway analysis. RESULTS: Numbers of metabolomic features associated with second-trimester PM₂.₅ exposure and birth weight Z-score were 692 and 356 for HILIC positive mode, and 779 and 495 for C-18 negative mode, respectively (p0.05). 35 positive-mode and 40 negative-mode metabolomic features were found to be associated with both PM₂.₅ exposure and birth weight. The most significant pathways associated with second-trimester PM₂.₅ exposure were ascorbate (vitamin C) and aldarate metabolism (p=0.01) and C21-steroid hormone biosynthesis and metabolism (p0.01). Dysregulated metabolism of glycerophospholipid (p=0.01) and vitamin D3 (cholecalciferol) (p0.01) was associated with birth weight Z-score. Ascorbate (vitamin C) and aldarate metabolism was a common metabolic pathway associated with both PM₂.₅ exposure and birth weight Z-score. CONCLUSIONS: Metabolomics analysis suggested a potential mediating role of maternal oxidative stress during pregnancy in the association between prenatal PM₂.₅ exposure and lower birth weight.

Background Few studies have assessed air pollution exposure association with birthweight during both preconception and gestational periods. Methods Leveraging a preconception cohort consisting of 14220 pregnant women and newborn children in Shanghai, China during 2016–2018, we aim to assess associations of NO 2 and PM 2.5 exposure, derived from high-resolution spatial-temporal models, during preconception and gestational periods with outcomes including term birthweight, birthweight Z-score, small-for-gestational age (SGA) and large-for-gestational age (LGA). Linear and logistic regressions were used to estimate 3-month preconception and trimester-averaged air pollution exposure associations; and distributed lag models (DLM) were used to identify critical exposure windows at the weekly resolution from preconception to delivery. Two-pollutant models and children’s sex-specific associations were explored. Results After controlling for covariates, one standard deviation (SD) (11.5 μg/m 3 , equivalent to 6.1 ppb) increase in NO 2 exposure during the second and the third trimester was associated with 13% (95% confidence interval: 2 – 26%) and 14% (95% CI: 1 – 29%) increase in SGA, respectively; and one SD (9.6 μg/m 3 ) increase in PM 2.5 exposure during the third trimester was associated with 15% (95% CI: 1 – 31%) increase in SGA. No association have been found for outcomes of birthweight, birthweight Z-score and LGA. DLM found that gestational weeks 22–32 were a critical window, when NO 2 exposure had strongest associations with SGA. The associations of air pollution exposure tended to be stronger in female newborns than in male newborns. However, no significant associations of air pollution exposure during preconception period on birthweight outcomes were found. Conclusion Consistent with previous studies, we found that air pollution exposure during mid-to-late pregnancy was associated with adverse birthweight outcomes.

BACKGROUND AND AIM: Few studies have assessed air pollution exposure association with birthweight during both preconception and gestational periods. In this study, we aim to identify critical periods of air pollution exposure during preconception and gestational period on birthweight outcomes. METHOD: Leveraging a preconception cohort consisting of 14,220 pregnant women and newborns in Shanghai, China during 2016 – 2018, we assessed effects of NO₂ and PM₂.₅ exposure, derived from high-resolution spatial-temporal models, during preconception and gestational periods on outcomes including term birthweight, birthweight Z-score, small-for-gestational age (SGA) and large-for-gestational age (LGA). Linear and logistic regression approaches were used to estimate 3-month preconception and trimester-averaged air pollution exposure associations; and distributed lag models (DLM) were used to identify critical exposure time windows at the weekly period from preconception to delivery. Two-pollutant models and effect modifications of children's sex were explored. RESULTS: One standard deviation (SD) (11.5 µg/m³, equivalent to 6.1 ppb) increase in NO₂ exposures during the second and third trimesters were associated with 13% (95% confidence interval: 2 % – 26%) and 14% (95% CI: 1% – 29%) increase in SGA, respectively; and one SD (9.6 µg/m3) increase in PM2.5 exposure during the third trimester was associated with 15% (95% CI: 1% – 31%) increase in SGA. DLM found that gestational weeks 22 – 32 a critical exposure time window, when NO₂ exposure had strongest associations with SGA. The effects of air pollution exposure tended to be stronger in female newborns than in male newborns (p-value 0.05). CONCLUSIONS: We found that air pollution exposure during mid-to-late pregnancy was associated with adverse birthweight outcomes.