Exposure to particulate matter (PM) in the ambient air and its interactions with APOE alleles may contribute to the acceleration of brain aging and the pathogenesis of Alzheimer's disease (AD). Neurodegenerative effects of particulate air pollutants were examined in a US-wide cohort of older women from the Women's Health Initiative Memory Study (WHIMS) and in experimental mouse models. Residing in places with fine PM exceeding EPA standards increased the risks for global cognitive decline and all-cause dementia respectively by 81 and 92%, with stronger adverse effects in APOE ɛ4/4 carriers. Female EFAD transgenic mice (5xFAD+/−/human APOE ɛ3 or ɛ4+/+) with 225 h exposure to urban nanosized PM (nPM) over 15 weeks showed increased cerebral β-amyloid by thioflavin S for fibrillary amyloid and by immunocytochemistry for Aβ deposits, both exacerbated by APOE ɛ4. Moreover, nPM exposure increased Aβ oligomers, caused selective atrophy of hippocampal CA1 neurites, and decreased the glutamate GluR1 subunit. Wildtype C57BL/6 female mice also showed nPM-induced CA1 atrophy and GluR1 decrease. In vitro nPM exposure of neuroblastoma cells (N2a-APP/swe) increased the pro-amyloidogenic processing of the amyloid precursor protein (APP). We suggest that airborne PM exposure promotes pathological brain aging in older women, with potentially a greater impact in ɛ4 carriers. The underlying mechanisms may involve increased cerebral Aβ production and selective changes in hippocampal CA1 neurons and glutamate receptor subunits.

Background:The effects of exposure to fine particulate matter (PM2.5) during wildland fires are not well understood in comparison with PM2.5 exposures from other sources.Objectives:We examined the cardiopulmonary effects of short-term exposure to PM2.5 on smoke days in the United States to evaluate whether health effects are consistent with those during non-smoke days.Methods:We examined cardiopulmonary hospitalizations among adults ≥65 y of age, in U.S. counties (n=692) within 200km of 123 large wildfires during 2008–2010. We evaluated associations during smoke and non-smoke days and examined variability with respect to modeled and observed exposure metrics. Poisson regression was used to estimate county-specific effects at lag days 0–6 (L0–6), adjusted for day of week, temperature, humidity, and seasonal trend. We used meta-analyses to combine county-specific effects and estimate overall percentage differences in hospitalizations expressed per 10-μg/m3 increase in PM2.5.Results:Exposure to PM2.5, on all days and locations, was associated with increased hospitalizations on smoke and non-smoke days using modeled exposure metrics. The estimated effects persisted across multiple lags, with a percentage increase of 1.08% [95% confidence interval (CI): 0.28, 1.89] on smoke days and 0.67% (95% CI: −0.09, 1.44) on non-smoke days for respiratory and 0.61% (95% CI: 0.09, 1.14) on smoke days and 0.69% (95% CI: 0.19, 1.2) on non-smoke days for cardiovascular outcomes on L1. For asthma-related hospitalizations, the percentage increase was greater on smoke days [6.9% (95% CI: 3.71, 10.11)] than non-smoke days [1.34% (95% CI: −1.10, 3.77)] on L1.Conclusions:The increased risk of PM2.5-related cardiopulmonary hospitalizations was similar on smoke and non-smoke days across multiple lags and exposure metrics, whereas risk for asthma-related hospitalizations was higher during smoke days. https://doi.org/10.1289/EHP3860

Identifying communities vulnerable to adverse health effects from exposure to wildfire smoke may help prepare responses, increase the resilience to smoke and improve public health outcomes during smoke days. We developed a Community Health-Vulnerability Index (CHVI) based on factors known to increase the risks of health effects from air pollution and wildfire smoke exposures. These factors included county prevalence rates for asthma in children and adults, chronic obstructive pulmonary disease, hypertension, diabetes, obesity, percent of population 65 years of age and older, and indicators of socioeconomic status including poverty, education, income and unemployment. Using air quality simulated for the period between 2008 and 2012 over the continental U.S. we also characterized the population size at risk with respect to the level and duration of exposure to fire-originated fine particulate matter (fire-PM) and CHVI. We estimate that 10% of the population (30.5 million) lived in the areas where the contribution of fire-PM to annual average ambient PM was high (>1.5 μg/m) and that 10.3 million individuals experienced unhealthy air quality levels for more than 10 days due to smoke. Using CHVI we identified the most vulnerable counties and determined that these communities experience more smoke exposures in comparison to less vulnerable communities.