Placental DNA methylation signatures of prenatal air pollution exposure and potential effects on birth outcomes: an analysis of three prospective cohorts.

BACKGROUND: Pregnancy air pollution exposure (PAPE) has been linked to a wide range of adverse birth and childhood outcomes, but there is a paucity of data on its influence on the placental epigenome, which can regulate the programming of physiological functions and affect child development. This study aimed to investigate the association between prenatal air pollutant exposure concentrations and changes in placental DNA methylation patterns, and to explore the potential windows of susceptibility and sex-specific alterations. METHODS: This multi-site study used three prospective population-based mother-child cohorts: EDEN, PELAGIE, and SEPAGES, originating from four French geographical regions (Nancy, Poitiers, Brittany, and Grenoble). Pregnant women were included between 2003 and 2006 for EDEN and PELAGIE, and between 2014 and 2017 for SEPAGES. The main eligibility criteria were: being older than 18 years, having a singleton pregnancy, and living and planning to deliver in one of the maternity clinics in one of the study areas. A total of 1539 mother-child pairs were analysed, measuring placental DNA methylation using Illumina BeadChips. We used validated spatiotemporally resolved models to estimate PM2·5, PM10, and NO2 exposure over each trimester of pregnancy at the maternal residential address. We conducted a pooled adjusted epigenome-wide association study to identify differentially methylated 5'-C-phosphate-G-3' (CpG) sites and regions (assessed using the Infinium HumanMethylationEPIC BeadChip array, n=871), including sex-specific and sex-linked alterations, and independently validated our results (assessed using the Infinium HumanMethylation450 BeadChip array, n=668). FINDINGS: We identified four CpGs and 28 regions associated with PAPE in the total population, 469 CpGs and 87 regions in male infants, and 150 CpGs and 66 regions in female infants. We validated 35% of the CpGs available. More than 30% of the identified CpGs were related to one (or more) birth outcome and most significant alterations were enriched for neural development, immunity, and metabolism related genes. The 28 regions identified for both sexes overlapped with imprinted genes (four genes), and were associated with neurodevelopment (nine genes), immune system (seven genes), and metabolism (five genes). Most associations were observed for the third trimester for female infants (134 of 150 CpGs), and throughout pregnancy (281 of 469 CpGs) and the first trimester (237 of 469 CpGs) for male infants. INTERPRETATION: These findings highlight the molecular pathways through which PAPE might affect child health in a widespread and sex-specific manner, identifying the genes involved in the major physiological functions of a developing child. Further studies are needed to elucidate whether these epigenetic changes persist and affect health later in life. FUNDING: French Agency for National Research, Fondation pour la Recherche Médicale, Fondation de France, and the Plan Cancer.

Oxidative potential of particulate matter and its association to respiratory health endpoints in high-altitude cities in Bolivia.

Exposure to particulate matter (PM) pollution is a significant health risk, driving the search for innovative metrics that more accurately reflect the potential harm to human health. Among these, oxidative potential (OP) has emerged as a promising health-based metric, yet its application and relevance across different environments remain to be further explored. This study, set in two high-altitude Bolivian cities, aims to identify the most significant sources of PM-induced oxidation in the lungs and assess the utility of OP in assessing PM health impacts. Utilizing two distinct assays, OPDTT and OPDCFH, we measured the OP of PM samples, while also examining the associations between PM mass, OP, and black carbon (BC) concentrations with hospital visits for acute respiratory infections (ARI) and pneumonia over a range of exposure lags (0-2 weeks) using a Poisson regression model adjusted for meteorological conditions. The analysis also leveraged Positive Matrix Factorization (PMF) to link these health outcomes to specific PM sources, building on a prior source apportionment study utilizing the same dataset. Our findings highlight anthropogenic combustion, particularly from traffic and biomass burning, as the primary contributors to OP in these urban sites. Significant correlations were observed between both OPDTT and PM2.5 concentration exposure and ARI hospital visits, alongside a notable association with pneumonia cases and OPDTT levels. Furthermore, PMF analysis demonstrated a clear link between traffic-related pollution and increased hospital admissions for respiratory issues, affirming the health impact of these sources. These results underscore the potential of OPDTT as a valuable metric for assessing the health risks associated with acute PM exposure, showcasing its broader application in environmental health studies.

Environmental and social inequities in continental France: an analysis of exposure to heat, air pollution, and lack of vegetation.

BACKGROUND: Cumulative environmental exposures and social deprivation increase health vulnerability and limit the capacity of populations to adapt to climate change. OBJECTIVE: Our study aimed at providing a fine-scale characterization of exposure to heat, air pollution, and lack of vegetation in continental France between 2000 and 2018, describing spatiotemporal trends and environmental hotspots (i.e., areas that cumulate the highest levels of overexposure), and exploring any associations with social deprivation. METHODS: The European (EDI) and French (FDep) social deprivation indices, the normalized difference vegetation index, daily ambient temperatures, particulate matter (PM2.5 and PM10), nitrogen dioxide, and ozone (O3) concentrations were estimated for 48,185 French census districts. Reference values were chosen to characterize (over-)exposure. Hotspots were defined as the areas cumulating the highest overexposure to temperature, air pollution, and lack of vegetation. Associations between heat overexposure or hotspots and social deprivation were assessed using logistic regressions. RESULTS: Overexposure to heat was higher in 2015-2018 compared with 2000-2014. Exposure to all air pollutants except for O3 decreased during the study period. In 2018, more than 79% of the urban census districts exceeded the 2021 WHO air quality guidelines. The evolution of vegetation density between 2000 and 2018 was heterogeneous across continental France. In urban areas, the most deprived census districts were at a higher risk of being hotspots (odds ratio (OR): 10.86, 95% CI: 9.87-11.98 using EDI and OR: 1.07, 95% CI: 1.04-1.11 using FDep). IMPACT STATEMENT: We studied cumulative environmental exposures and social deprivation in French census districts. The 2015-2018 period showed the highest overexposure to heat between 2000 and 2018. In 2018, the air quality did not meet the 2021 WHO guidelines in most census districts and 8.6 million people lived in environmental hotspots. Highly socially deprived urban areas had a higher risk of being in a hotspot. This study proposes for the first time, a methodology to identify hotspots of exposure to heat, air pollution, and lack of vegetation and their associations with social deprivation at a national level.

Prenatal and childhood exposure to ambient air pollution and cognitive function in school-age children: Examining sensitive windows and sex-specific associations.

BACKGROUND: Combined effect of both prenatal and early postnatal exposure to ambient air pollution on child cognition has rarely been investigated and periods of sensitivity are unknown. This study explores the temporal relationship between pre- and postnatal exposure to PM10, PM2.5, NO2 and child cognitive function. METHODS: Using validated spatiotemporally resolved exposure models, pre- and postnatal daily PM2.5, PM10 (satellite based, 1 km resolution) and NO2 (chemistry-transport model, 4 km resolution) concentrations at the mother's residence were estimated for 1271 mother-child pairs from the French EDEN and PELAGIE cohorts. Scores representative of children's General, Verbal and Non-Verbal abilities at 5-6 years were constructed based on subscale scores from the WPPSI-III, WISC-IV or NEPSY-II batteries, using confirmatory factor analysis (CFA). Associations of both prenatal (first 35 gestational weeks) and postnatal (60 months after birth) exposure to air pollutants with child cognition were explored using Distributed Lag Non-linear Models adjusted for confounders. RESULTS: Increased maternal exposure to PM10, PM2.5 and NO2, during sensitive windows comprised between the 15th and the 33rd gestational weeks, was associated with lower males' General and Non-verbal abilities. Higher postnatal exposure to PM2.5 between the 35th and 52nd month of life was associated with lower males' General, Verbal and Non-verbal abilities. Some protective associations were punctually observed for the very first gestational weeks or months of life for both males and females and the different pollutants and cognitive scores. DISCUSSION: These results suggest poorer cognitive function at 5-6 years among males following increased maternal exposure to PM10, PM2.5 and NO2 during mid-pregnancy and child exposure to PM2.5 around 3-4 years. Apparent protective associations observed are unlikely to be causal and might be due to live birth selection bias, chance finding or residual confounding.

Association of Prenatal and Postnatal Exposures to Warm or Cold Air Temperatures With Lung Function in Young Infants.

Importance: Little is known about long-term associations of early-life exposure to extreme temperatures with child health and lung function. Objectives: To investigate the association of prenatal and postnatal heat or cold exposure with newborn lung function and identify windows of susceptibility. Design, Setting, and Participants: This population-based cohort study (SEPAGES) recruited pregnant women in France between July 8, 2014, and July 24, 2017. Data on temperature exposure, lung function, and covariates were available from 343 mother-child dyads. Data analysis was performed from January 1, 2021, to December 31, 2021. Exposures: Mean, SD, minimum, and maximum temperatures at the mother-child's residence, estimated using a state-of-the-art spatiotemporally resolved model. Main Outcomes and Measures: Outcome measures were tidal breathing analysis and nitrogen multiple-breath washout test measured at 2 months of age. Adjusted associations between both long-term (35 gestational weeks and first 4 weeks after delivery) and short-term (7 days before lung function test) exposure to ambient temperature and newborn lung function were analyzed using distributed lag nonlinear models. Results: A total of 343 mother-child pairs were included in the analyses (median [IQR] maternal age at conception, 32 [30.0-35.2] years; 183 [53%] male newborns). A total of 246 mothers and/or fathers (72%) held at least a master's degree. Among the 160 female newborns (47%), long-term heat exposure (95th vs 50th percentile of mean temperature) was associated with decreased functional residual capacity (-39.7 mL; 95% CI, -68.6 to -10.7 mL for 24 °C vs 12 °C at gestational weeks 20-35 and weeks 0-4 after delivery) and increased respiratory rate (28.0/min; 95% CI, 4.2-51.9/min for 24 °C vs 12 °C at gestational weeks 14-35 and weeks 0-1 after delivery). Long-term cold exposure (5th vs 50th percentile of mean temperature) was associated with lower functional residual capacity (-21.9 mL; 95% CI, -42.4 to -1.3 mL for 1 °C vs 12 °C at gestational weeks 15-29), lower tidal volume (-23.8 mL; 95% CI, -43.1 to -4.4 mL for 1 °C vs 12 °C at gestational weeks 14-35 and weeks 0-4 after delivery), and increased respiratory rate (45.5/min; 95% CI, 10.1-81.0/min for 1 °C vs 12 °C at gestational weeks 6-35 and weeks 0-1 after delivery) in female newborns as well. No consistent association was observed for male newborns or short-term exposure to cold or heat. Conclusions and Relevance: In this cohort study, long-term heat and cold exposure from the second trimester until 4 weeks after birth was associated with newborn lung volumes, especially among female newborns.

Individuality and stability of the koala (Phascolarctos cinereus) faecal microbiota through time.

Gut microbiota studies often rely on a single sample taken per individual, representing a snapshot in time. However, we know that gut microbiota composition in many animals exhibits intra-individual variation over the course of days to months. Such temporal variations can be a confounding factor in studies seeking to compare the gut microbiota of different wild populations, or to assess the impact of medical/veterinary interventions. To date, little is known about the variability of the koala (Phascolarctos cinereus) gut microbiota through time. Here, we characterise the gut microbiota from faecal samples collected at eight timepoints over a month for a captive population of South Australian koalas (n individuals = 7), and monthly over 7 months for a wild population of New South Wales koalas (n individuals = 5). Using 16S rRNA gene sequencing, we found that microbial diversity was stable over the course of days to months. Each koala had a distinct faecal microbiota composition which in the captive koalas was stable across days. The wild koalas showed more variation across months, although each individual still maintained a distinct microbial composition. Per koala, an average of 57 (±16) amplicon sequence variants (ASVs) were detected across all time points; these ASVs accounted for an average of 97% (±1.9%) of the faecal microbial community per koala. The koala faecal microbiota exhibits stability over the course of days to months. Such knowledge will be useful for future studies comparing koala populations and developing microbiota interventions for this regionally endangered marsupial.

Early delivery following chronic and acute ambient temperature exposure: a comprehensive survival approach.

BACKGROUND: Ambient temperature, particularly heat, is increasingly acknowledged as a trigger for preterm delivery but study designs have been limited and results mixed. We aimed to comprehensively evaluate the association between ambient temperature throughout pregnancy and preterm delivery. METHODS: We estimated daily temperature throughout pregnancy using a cutting-edge spatiotemporal model for 5347 live singleton births from three prospective cohorts in France, 2002-2018. We performed Cox regression (survival analysis) with distributed lags to evaluate time-varying associations with preterm birth simultaneously controlling for exposure during the first 26 weeks and last 30 days of pregnancy. We examined weekly mean, daytime, night-time and variability of temperature, and heatwaves accounting for adaptation to location and season. RESULTS: Preterm birth risk was higher following cold (5th vs 50th percentile of mean temperature) 7-9 weeks after conception [relative risk (RR): 1.3, 95% CI: 1.0-1.6 for 2°C vs 11.6°C] and 10-4 days before delivery (RR: 1.6, 95% CI: 1.1-2.1 for 1.2°C vs 12.1°C). Night-time heat (95th vs 50th percentile of minimum temperature; 15.7°C vs 7.4°C) increased risk when exposure occurred within 5 weeks of conception (RR: 2.0, 95% CI: 1.05-3.8) or 20-26 weeks after conception (RR: 2.9, 95% CI: 1.2-6.8). Overall and daytime heat (high mean and maximum temperature) showed consistent effects. We found no clear associations with temperature variability or heatwave indicators, suggesting they may be less relevant for preterm birth. CONCLUSIONS: In a temperate climate, night-time heat and chronic and acute cold exposures were associated with increased risk of preterm birth. These results suggest night-time heat as a relevant indicator. In the context of rising temperatures and more frequent weather hazards, these results should inform public health policies to reduce the growing burden of preterm births.

An Analysis of Demographic and Triage Assessment Findings in Bushfire-Affected Koalas (Phascolarctos cinereus) on Kangaroo Island, South Australia, 2019-2020.

In the 2019-2020 Australian bushfires, Kangaroo Island, South Australia, experienced catastrophic bushfires that burnt approximately half the island, with an estimated 80% of the koala population lost. During and after the event, rescued koalas were triaged at a designated facility and a range of initial data were recorded including rescue location and date, sex, estimation of age, body condition and hydration, and assessment of burn severity (n = 304 records available). Koalas were presented to the triage facility over a span of 10 weeks, with 50.2% during the first 14 days of the bushfire response, the majority of which were rescued from regions of lower fire severity. Burns were observed in 67.4% of koalas, with the majority (60.9%) classified as superficial burns, primarily affecting the limbs and face. Poor body condition was recorded in 74.6% of burnt koalas and dehydration in 77.1%. Negative final outcomes (death or euthanasia, at triage or at a later date) occurred in 45.6% of koalas and were significantly associated with higher mean burn score, maximum burn severity, number of body regions burnt, poor body condition score, and dehydration severity. The findings of this retrospective study may assist clinicians in the field with decision making when triaging koalas in future fire rescue efforts.

A multi-resolution air temperature model for France from MODIS and Landsat thermal data.

Understanding and managing the health effects of ambient temperature (Ta) in a warming, urbanizing world requires spatially- and temporally-resolved Ta at high resolutions. This is challenging in a large area like France which includes highly variable topography, rural areas with few weather stations, and heterogeneous urban areas where Ta can vary at fine spatial scales. We have modeled daily Ta from 2000 to 2016 at a base resolution of 1 km2 across continental France and at a 200 × 200 m2 resolution over large urban areas. For each day we predict three Ta measures: minimum (Tmin), mean (Tmean), and maximum (Tmax). We start by using linear mixed models to calibrate daily Ta observations from weather stations with remotely sensed MODIS land surface temperature (LST) and other spatial predictors (e.g. NDVI, elevation) on a 1 km2 grid. We fill gaps where LST is missing (e.g. due to cloud cover) with additional mixed models that capture the relationship between predicted Ta at each location and observed Ta at nearby weather stations. The resulting 1 km Ta models perform very well, with ten-fold cross-validated R2 of 0.92, 0.97, and 0.95, mean absolute error (MAE) of 1.4 °C, 0.9 °C, and 1.4 °C, and root mean square error (RMSE) of 1.9 °C, 1.3 °C, and 1.8 °C (Tmin, Tmean, and Tmax, respectively) for the initial calibration stage. To increase the spatial resolution over large urban areas, we train random forest and extreme gradient boosting models to predict the residuals (R) of the 1 km Ta predictions on a 200 × 200 m2 grid. In this stage we replace MODIS LST and NDVI with composited top-of-atmosphere brightness temperature and NDVI from the Landsat 5, 7, and 8 satellites. We use a generalized additive model to ensemble the random forest and extreme gradient boosting predictions with weights that vary spatially and by the magnitude of the predicted residual. The 200 m models also perform well, with ten-fold cross-validated R2 of 0.79, 0.79, and 0.85, MAE of 0.4, 0.3, and 0.3, and RMSE of 0.6, 0.4, and 0.5 (Rmin, Rmean, and Rmax, respectively). Our model will reduce bias in epidemiological studies in France by improving Ta exposure assessment in both urban and rural areas, and our methodology demonstrates that MODIS and Landsat thermal data can be used to generate gap-free timeseries of daily minimum, maximum, and mean Ta at a 200 × 200 m2 spatial resolution.