Ambient air pollution and Alzheimer’s disease: the role of the composition of fine particles

Ambient air pollution is the most important environmental risk factor globally due to its well-established burden of respiratory and cardiovascular diseases (1). Within the complex mixture of polluted ambient air, fine ambient particles defined as mass of particles smaller or equal to 2.5 μm in aerodynamic diameter (PM2.5) are an established causal factor. Epidemiological evidence is accumulating that PM2.5 is linked to cognitive decline (2, 3). Recent evidence highlighted that PM2.5 is also associated with neurodegenerative diseases, specifically with Alzheimer’s and Parkinson’s disease (4). In this issue of the journal, Shi et al. investigated the association between constituents of PM2.5 and the incidence of dementia and Alzheimer’s disease (5). Their analyses are based on a cohort assembled from the Medicare and Medicaid records including all inhabitants of the contiguous United States aged 65 y and older for the time period 2000 to 2017. They constructed two separate cohorts: They identified 5.8 Mio cases of incident dementia among 18.5 Mio individuals and 2.8 Mio cases of incident Alzheimer’s disease among 19.2 Mio individuals. They report consistent associations for constituents of PM2.5, namely black carbon, organic matter, sulfates (SO4 ), and ammonium (NH4 ). They conclude that annual average PM2.5 concentrations from traffic and fossil fuel combustion are significantly associated with the development of dementia and Alzheimer’s disease (5). PM2.5 is a complex mixture both with respect to their size ranging down to several nanometers and their composition (6). The composition of combustion-related particles is determined by three factors, the composition of the fuel, the chemical reactions when forming the primary particles, and the substances that are absorbed on the particle surfaces while being dispersed in air. The constituents of PM2.5 assessed by Shi et al. (5) describe the sources of the particles and the toxicological properties. Black carbon is a measure of soot particles produced in combustion processes. As primary particles, they are part of the ultrafine particles (UFP) defined as particles smaller than 100 nm. In this size range, they are characterized by high number concentration and surface area. Particles agglomerate as they age, so that primary ultrafine particles grow into the fine particle fraction. The majority of sulfates, nitrates, and ammonium in PM2.5 are secondary constituents formed from their gaseous precursors and absorbed on the particles. Their concentrations have been consistently associated with adverse health effects, while the toxicity of these constituents is low (6). They are indicators for combustion-related, aged, and regionally transported PM2.5. Shi et al. have used two independent approaches to characterize the spatial variation of annual averages of PM2.5 constituents (5). First, they estimated the annual averages based on an integrated approach combing satellite data, chemical transport models, and ground-based observation with a resolution of 1 km by 1 km. Second, they estimated the annual averages based on nearly 1,000 measurement stations and hundreds of additional predictor variables with a resolution of 50 m by 50 m in urban areas and 1 km by 1 km in rural areas. Both methods yielded comparable correlations between the PM2.5 constituents and PM2.5 mass. The resulting spatial maps provide comparable spatial distributions for all constituents but black carbon. For black carbon, the method relying on chemical transport models assigned the largest values to the industrial southeast and suggests long-range transport of soot-containing particles. In contrast, the method putting most weight on measured constituents implicated that the metropolitan areas had the highest annual averages of black carbon. A key finding of the study by Shi et al (5) is that the hazard ratio for dementia increased 12% (95% CI: 11 to 14%) per 1 μg/m black carbon for the chemical transport-based model and 25% (95% CI: 22 to 27%) per 1 μg/m black carbon for the second model with finer spatial resolution. The hazard ratio for Alzheimer’s disease increased 23% (95% CI: 21 to 25%) per 1 μg/m black carbon for the for the chemical transport-based model and 39% (95% CI: 36 to 43%) based on the second model with finer spatial resolution. The estimates based on the second model with finer resolution are robust against adjustments for the remaining variation in PM2.5 mass. The estimates based on chemical transport-based model are reduced to a null effect when adjusting for the remaining variation in PM2.5 mass. This highlights two important points: First, the observed associations are to a large degree driven by Alzheimer’s disease, and second, the second model captures the role of locally emitted soot particles better than the chemical transport-based model. Considering sulfates as a key indicator for regionally transported, aged PM2.5, the differences are less striking. One μg/m SO4 2− is associated with an increased hazard ratio for dementia of 5.9 % (95% CI: 5.6 to 6.2%) based on the chemical transport-based model and of 6.2 % (95%