Neurodegenerative hospital admissions and long-term exposure to ambient fine particle air pollution

Personal Exposure to Source-Specific Particulate Polycyclic Aromatic Hydrocarbons and Systemic Inflammation: A Cross-Sectional Study of Urban-Dwelling Older Adults in China

Environmental exposure to ambient polycyclic aromatic hydrocarbons (PAHs) can disturb the immune response. However, the evidence on adverse health effects caused by exposure to PAHs emitted from specific sources among different vulnerable subpopulations is limited. In this cross-sectional study, we aimed to evaluate whether exposure to source-specific PAHs could increase systemic inflammation in older adults. The present study included community-dwelling older adults and collected filter samples of personal exposure to PM2.5 during the winter of 2011. Blood samples were collected after the PM2.5 sample collection. We analyzed PM2.5 bound PAHs and serum inflammatory cytokines (interleukin (IL)1β, IL6, and tumor necrosis factor alpha levels. The Positive Matrix Factorization model was used to identify PAH sources. We used a linear regression model to assess the relative effects of source-specific PM2.5 bound PAHs on the levels of measured inflammatory cytokines. After controlling for confounders, exposure to PAHs emitted from biomass burning or diesel vehicle emission was significantly associated with increased serum inflammatory cytokines and systemic inflammation. These findings highlight the importance of considering exposure sources in epidemiological studies and controlling exposures to organic materials from specific sources.

Ambient air pollution and clinical dementia: systematic review and meta-analysis

OBJECTIVE

To investigate the role of air pollutants in risk of dementia, considering differences by study factors that could influence findings.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

EMBASE, PubMed, Web of Science, Psycinfo, and OVID Medline from database inception through July 2022.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Studies that included adults (≥18 years), a longitudinal follow-up, considered US Environmental Protection Agency criteria air pollutants and proxies of traffic pollution, averaged exposure over a year or more, and reported associations between ambient pollutants and clinical dementia. Two authors independently extracted data using a predefined data extraction form and assessed risk of bias using the Risk of Bias In Non-randomised Studies of Exposures (ROBINS-E) tool. A meta-analysis with Knapp-Hartung standard errors was done when at least three studies for a given pollutant used comparable approaches.

RESULTS

2080 records identified 51 studies for inclusion. Most studies were at high risk of bias, although in many cases bias was towards the null. 14 studies could be meta-analysed for particulate matter <2.5 µm in diameter (PM2.5). The overall hazard ratio per 2 μg/m3 PM2.5 was 1.04 (95% confidence interval 0.99 to 1.09). The hazard ratio among seven studies that used active case ascertainment was 1.42 (1.00 to 2.02) and among seven studies that used passive case ascertainment was 1.03 (0.98 to 1.07). The overall hazard ratio per 10 μg/m3 nitrogen dioxide was 1.02 ((0.98 to 1.06); nine studies) and per 10 μg/m3 nitrogen oxide was 1.05 ((0.98 to 1.13); five studies). Ozone had no clear association with dementia (hazard ratio per 5 μg/m3 was 1.00 (0.98 to 1.05); four studies).

CONCLUSION

PM2.5 might be a risk factor for dementia, as well as nitrogen dioxide and nitrogen oxide, although with more limited data. The meta-analysed hazard ratios are subject to limitations that require interpretation with caution. Outcome ascertainment approaches differ across studies and each exposure assessment approach likely is only a proxy for causally relevant exposure in relation to clinical dementia outcomes. Studies that evaluate critical periods of exposure and pollutants other than PM2.5, and studies that actively assess all participants for outcomes are needed. Nonetheless, our results can provide current best estimates for use in burden of disease and regulatory setting efforts.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42021277083.

Neurodevelopmental toxicity induced by PM2.5 Exposure and its possible role in Neurodegenerative and mental disorders

Recent extensive evidence suggests that ambient fine particulate matter (PM2.5, with an aerodynamic diameter ≤2.5 μm) may be neurotoxic to the brain and cause central nervous system damage, contributing to neurodevelopmental disorders, such as autism spectrum disorders, neurodegenerative diseases, such as Alzheimer's disease and Parkinson's disease, and mental disorders, such as schizophrenia, depression, and bipolar disorder. PM2.5 can enter the brain via various pathways, including the blood-brain barrier, olfactory system, and gut-brain axis, leading to adverse effects on the CNS. Studies in humans and animals have revealed that PM2.5-mediated mechanisms, including neuroinflammation, oxidative stress, systemic inflammation, and gut flora dysbiosis, play a crucial role in CNS damage. Additionally, PM2.5 exposure can induce epigenetic alterations, such as hypomethylation of DNA, which may contribute to the pathogenesis of some CNS damage. Through literature analysis, we suggest that promising therapeutic targets for alleviating PM2.5-induced neurological damage include inhibiting microglia overactivation, regulating gut microbiota with antibiotics, and targeting signaling pathways, such as PKA/CREB/BDNF and WNT/β-catenin. Additionally, several studies have observed an association between PM2.5 exposure and epigenetic changes in neuropsychiatric disorders. This review summarizes and discusses the association between PM2.5 exposure and CNS damage, including the possible mechanisms by which PM2.5 causes neurotoxicity.

Estimation of fine particulate matter in an arid area from visibility based on machine learning

BACKGROUND

The absence of air pollution monitoring networks makes it difficult to assess historical fine particulate matter (PM_2.5) exposures for countries in the areas, such as Kuwait, which are severe impacted by desert dust and anthropogenic pollution.

OBJECTIVE

We constructed an ensemble machine learning model to predict daily PM_2.5 concentrations for regions lack of PM_2.5 observations.

METHODS

The model was constructed based on daily PM_2.5, visibility, and other meteorological data collected at two sites in Kuwait. Then, our model was applied to predict the daily level of PM_2.5 concentrations for eight airports located in Kuwait and Iraq from 2013 to 2020.

RESULTS

As compared to traditional statistic models, the proposed machine learning methods improved the accuracy in using visibility to predict daily PM_2.5 concentrations with a cross-validation R² of 0.68. The predicted level of daily PM_2.5 concentrations were consistent with previous measurements. The predicted average yearly PM_2.5 concentration for the eight stations is 50.65 µg/m³. For all stations, the monthly average PM_2.5 concentrations reached their maximum in July and their minimum in November.

SIGNIFICANCE

These findings make it possible to retrospectively estimate daily PM_2.5 exposures using the large-scale databases of historical visibility in regions with few particulate matter monitoring stations.

IMPACT STATEMENT

The scarcity of air pollution ground monitoring networks makes it difficult to assess historical fine particulate matter exposures for countries in arid areas such as Kuwait. Visibility is closely related to atmospheric particulate matter concentrations and historical airport visibility records are commonly available in most countries. Our model make it possible to retrospectively estimate daily PM_2.5 exposures using the large-scale databases of historical visibility in arid regions with few particulate matter ground monitoring stations. The product of such models can be critical for environmental risk assessments and population health studies.

Neurotoxic effects of environmental contaminants-measurements, mechanistic insight, and environmental relevance

Pollution is a significant and growing concern for any population regardless of age because these environmental contaminants exhibit different neurodegenerative effects on persons of different ages. These environmental contaminants are the products of human welfare projects like industry, automobile exhaust, clinical and research laboratory extrudes, and agricultural chemicals. These contaminants are found in various forms in environmental matrices like nanoparticles, particulate matter, lipophilic vaporized toxicants, and ultrafine particulate matter. Because of their small size, they can easily cross blood-brain barriers or use different cellular mechanisms for assistance. Other than this, these contaminants cause an innate immune response in different cells of the central nervous system and cause neurotoxicity. Considering the above critiques and current needs, this review summarizes different protective strategies based on bioactive compounds present in plants. Various bioactive compounds from medicinal plants with neuroprotective capacities are discussed with relevant examples. Many in vitro studies on clinical trials have shown promising outcomes using plant-based bioactive compounds against neurological disorders.

Pyroptosis participates in PM2.5-induced air-blood barrier dysfunction

Epidemiological studies have shown that particulate matters with diameter less than 2.5 μm (PM_2.5) play an important role in inducing and promoting respiratory diseases, but its underlying mechanism remains to be explored. The air-blood barrier, also known as the alveolar-capillary barrier, is the key element of the lung, working as the site of oxygen and carbon dioxide exchange between pulmonary vasculatures. In this study, a mouse PM_2.5 exposure model was established, which leads to an induced lung injury and air-blood barrier disruption. Oxidative stress and pyroptosis were observed in this process. After reducing the oxidative stress by N-acetyl-L-cysteine (NAC) treatment, the air-blood barrier function was improved and the effect of PM_2.5 was alleviated. The level of pyroptosis and related pathway were also effectively relieved. These results indicate that acute PM_2.5 exposure can cause lung injury and the alveolar-capillary barrier disruption by inducing reactive oxygen species (ROS) with the participation of pyroptosis pathway.

PM2.5 exposure in association with AD-related neuropathology and cognitive outcomes

Particulate matter with a diameter of less than 2.5 μm or PM2.5 is recognized worldwide as a cause of public health problems, mainly associated with respiratory and cardiovascular diseases. There is accumulating evidence to show that exposure to PM2.5 has a crucial causative role in various neurological disorders, the main ones being dementia and Alzheimer's disease (AD). PM2.5 can activate glial and microglial activity, resulting in neuroinflammation, increased intracellular ROS production, and ultimately neuronal apoptosis. PM2.5 also causes the alteration of neuronal morphology and synaptic changes and increases AD biomarkers, including amyloid-beta and hyperphosphorylated-tau, as well as raising the levels of enzymes involved in the amyloidogenic pathway. Clinical trials have highlighted the correlation between exposure to PM2.5, dementia, and AD diagnosis. This correlation is also displayed by concordant evidence from animal models, as indicated by increased AD biomarkers in cerebrospinal fluid and markers of vascular injury. Blood-brain barrier disruption is another aggravated phenomenon demonstrated in people at risk who are exposed to PM2.5. This review summarizes and discusses studies from in vitro, in vivo, and clinical studies on causative relationships of PM2.5 exposure to AD-related neuropathology. Conflicting data are also examined in order to determine the actual association between ambient air pollution and neurodegenerative diseases.

A national cohort study (2000-2018) of long-term air pollution exposure and incident dementia in older adults in the United States

Air pollution may increase risk of Alzheimer’s disease and related dementias (ADRD) in the U.S., but the extent of this relationship is unclear. Here, we constructed two national U.S. population-based cohorts of those aged ≥65 from the Medicare Chronic Conditions Warehouse (2000–2018), combined with high-resolution air pollution datasets, to investigate the association of long-term exposure to ambient fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), and ozone (O₃) with dementia and AD incidence, respectively. We identified ~2.0 million incident dementia cases (N = 12,233,371; dementia cohort) and ~0.8 million incident AD cases (N = 12,456,447; AD cohort). Per interquartile range (IQR) increase in the 5-year average PM_2.5 (3.2 µg/m³), NO₂ (11.6 ppb), and warm-season O₃ (5.3 ppb) over the past 5 years prior to diagnosis, the hazard ratios (HRs) were 1.060 (95% confidence interval [CI]: 1.054, 1.066), 1.019 (95% CI: 1.012, 1.026), and 0.990 (95% CI: 0.987, 0.993) for incident dementias, and 1.078 (95% CI: 1.070, 1.086), 1.031 (95% CI: 1.023, 1.039), and 0.982 (95%CI: 0.977, 0.986) for incident AD, respectively, for the three pollutants. For both outcomes, concentration-response relationships for PM_2.5 and NO₂ were approximately linear. Our study suggests that exposures to PM_2.5 and NO₂ are associated with incidence of dementia and AD.

Air pollution has been linked to neurodegenerative disease. Here the authors carried out a population-based cohort study to investigate the association between long-term exposure to PM_2.5, NO₂, and warm-season O₃ on dementia and Alzheimer’s disease incidence in the United States.

Parkinson's disease aggravation in association with fine particle components in New York State

BACKGROUND

Long-term exposure to fine particulate matter (PM2.5) has been associated with neurodegenerative diseases, including disease aggravation in Parkinson's disease (PD), but associations with specific PM2.5 components have not been evaluated.

OBJECTIVE

To characterize the association between specific PM2.5 components and PD first hospitalization, a surrogate for disease aggravation.

METHODS

We obtained data on hospitalizations from the New York Department of Health Statewide Planning and Research Cooperative System (2000-2014) to calculate annual first PD hospitalization counts in New York State per county. We used well-validated prediction models at 1 km2 resolution to estimate county level population-weighted annual black carbon (BC), organic matter (OM), nitrate, sulfate, sea salt (SS), and soil particle concentrations. We then used a multi-pollutant mixed quasi-Poisson model with county-specific random intercepts to estimate rate ratios (RR) of one-year exposure to each PM2.5 component and PD disease aggravation. We evaluated potential nonlinear exposure-outcome relationships using penalized splines and accounted for potential confounders.

RESULTS

We observed a total of 197,545 PD first hospitalizations in NYS from 2000 to 2014. The annual average count per county was 212 first hospitalizations. The RR (95% confidence interval) for PD aggravation was 1.06 (1.03, 1.10) per one standard deviation (SD) increase in nitrate concentrations and 1.06 (1.04, 1.09) for the corresponding increase in OM concentrations. We also found a nonlinear inverse association between PD aggravation and BC at concentrations above the 96th percentile. We found a marginal association with SS and no association with sulfate or soil exposure.

CONCLUSION

In this study, we detected associations between the PM2.5 components OM and nitrate with PD disease aggravation. Our findings support that PM2.5 adverse effects on PD may vary by particle composition.

Fine Particle Exposure and Clinical Aggravation in Neurodegenerative Diseases in New York State

BACKGROUND

Adult-onset neurodegenerative diseases affect millions and negatively impact health care systems worldwide. Evidence suggests that air pollution may contribute to aggravation of neurodegeneration, but studies have been limited.

OBJECTIVE

We examined the potential association between long-term exposure to particulate matter ≤ 2.5 μ m in aerodynamic diameter [fine particulate matter (PM 2.5 )] and disease aggravation in Alzheimer's (AD) and Parkinson's (PD) diseases and amyotrophic lateral sclerosis (ALS), using first hospitalization as a surrogate of clinical aggravation.

METHODS

We used data from the New York Department of Health Statewide Planning and Research Cooperative System (SPARCS 2000-2014) to construct annual county counts of first hospitalizations with a diagnosis of AD, PD, or ALS (total, urbanicity-, sex-, and age-stratified). We used annual PM 2.5 concentrations estimated by a prediction model at a 1 -km 2 resolution, which we aggregated to population-weighted county averages to assign exposure to cases based on county of residence. We used outcome-specific mixed quasi-Poisson models with county-specific random intercepts to estimate rate ratios (RRs) for a 1-y PM 2.5 exposure. We allowed for nonlinear exposure-outcome relationships using penalized splines and accounted for potential confounders.

RESULTS

We found a positive nonlinear PM 2.5 - PD association that plateaued above 11   μ g / m 3 (RR = 1.09 , 95% CI: 1.04, 1.14 for a PM 2.5 increase from 8.1 to 10.4   μ g / m 3 ). We also found a linear PM 2.5 - ALS positive association (RR = 1.05 , 95% CI: 1.01, 1.09 per 1 - μ g / m 3 PM 2.5 increase), and suggestive evidence of an association with AD. We found effect modification by age for PD and ALS with a stronger positive association in patients < 70  years of age but found insufficient evidence of effect modification by sex or urbanization level for any of the outcomes.

CONCLUSION

Our findings suggest that annual increase in county-level PM 2.5 concentrations may contribute to clinical aggravation of PD and ALS. Importantly, the average annual PM 2.5 concentration in our study was 8.1   μ g / m 3 , below the current American national standards, suggesting the standards may not adequately protect the aging population. https://doi.org/10.1289/EHP7425.