Association of NO2 and Other Air Pollution Exposures With the Risk of Parkinson Disease

Air pollution exposure and mortality from neurodegenerative diseases in the Netherlands: A population-based cohort study

BACKGROUND

Long-term exposure to ambient air pollution has been linked with all-cause mortality and cardiovascular and respiratory diseases. Suggestive associations between ambient air pollutants and neurodegeneration have also been reported, but due to the small effect and relatively rare outcomes evidence is yet inconclusive. Our aim was to investigate the associations between long-term air pollution exposure and mortality from neurodegenerative diseases.

METHODS

A Dutch national cohort of 10.8 million adults aged ≥30 years was followed from 2013 until 2019. Annual average concentrations of air pollutants (ultra-fine particles (UFP), nitrogen dioxide (NO2), fine particles (PM2.5 and PM10) and elemental carbon (EC)) were estimated at the home address at baseline, using land-use regression models. The outcome variables were mortality due to amyotrophic lateral sclerosis (ALS), Parkinson's disease, non-vascular dementia, Alzheimer's disease, and multiple sclerosis (MS). Hazard ratios (HR) were estimated using Cox models, adjusting for individual and area-level socio-economic status covariates.

RESULTS

We had a follow-up of 71 million person-years. The adjusted HRs for non-vascular dementia were significantly increased for NO2 (1.03; 95% confidence interval (CI) 1.02-1.05) and PM2.5 (1.02; 95%CI 1.01-1.03) per interquartile range (IQR; 6.52 and 1.47 μg/m3, respectively). The association with PM2.5 was also positive for ALS (1.02; 95%CI 0.97-1.07). These associations remained positive in sensitivity analyses and two-pollutant models. UFP was not associated with any outcome. No association with air pollution was found for Parkinson's disease and MS. Inverse associations were found for Alzheimer's disease.

CONCLUSION

Our findings, using a cohort of more than 10 million people, provide further support for associations between long-term exposure to air pollutants (PM2.5 and particularly NO2) and mortality of non-vascular dementia. No associations were found for Parkinson and MS and an inverse association was observed for Alzheimer's disease.

The enigma of mitochondrial epigenetic alterations in air pollution-induced neurodegenerative diseases

The incidence of neurodegenerative diseases is a growing concern worldwide, affecting individuals from diverse backgrounds. Although these pathologies are primarily associated with aging and genetic susceptibility, their severity varies among the affected population. Numerous studies have indicated air pollution as a significant contributor to the increasing prevalence of neurodegeneration. Cohort studies have provided compelling evidence of the association between prolonged exposure to different air toxicants and cognitive decline, behavioural deficits, memory impairment, and overall neuronal health deterioration. Furthermore, molecular research has revealed that air pollutants can disrupt the body's protective mechanisms, participate in neuroinflammatory pathways, and cause neuronal epigenetic modifications. The mitochondrial epigenome is particularly interesting to the scientific community due to its potential to significantly impact our understanding of neurodegenerative diseases' pathogenesis and their release in the peripheral circulation. While protein hallmarks have been extensively studied, the possibility of using circulating epigenetic signatures, such as methylated DNA fragments, miRNAs, and genome-associated factors, as diagnostic tools and therapeutic targets requires further groundwork. The utilization of circulating epigenetic signatures holds promise for developing novel prognostic strategies, creating paramount point-of-care devices for disease diagnosis, identifying therapeutic targets, and developing clinical data-based disease models utilizing multi-omics technologies and artificial intelligence, ultimately mitigating the threat and prevalence of neurodegeneration.

Machine Learning-Based Prediction of Neurodegenerative Disease in Patients With Type 2 Diabetes by Derivation and Validation in 2 Independent Korean Cohorts: Model Development and Validation Study

BACKGROUND

Several machine learning (ML) prediction models for neurodegenerative diseases (NDs) in type 2 diabetes mellitus (T2DM) have recently been developed. However, the predictive power of these models is limited by the lack of multiple risk factors.

OBJECTIVE

This study aimed to assess the validity and use of an ML model for predicting the 3-year incidence of ND in patients with T2DM.

METHODS

We used data from 2 independent cohorts-the discovery cohort (1 hospital; n=22,311) and the validation cohort (2 hospitals; n=2915)-to predict ND. The outcome of interest was the presence or absence of ND at 3 years. We selected different ML-based models with hyperparameter tuning in the discovery cohort and conducted an area under the receiver operating characteristic curve (AUROC) analysis in the validation cohort.

RESULTS

The study dataset included 22,311 (discovery) and 2915 (validation) patients with T2DM recruited between 2008 and 2022. ND was observed in 133 (0.6%) and 15 patients (0.5%) in the discovery and validation cohorts, respectively. The AdaBoost model had a mean AUROC of 0.82 (95% CI 0.79-0.85) in the discovery dataset. When this result was applied to the validation dataset, the AdaBoost model exhibited the best performance among the models, with an AUROC of 0.83 (accuracy of 78.6%, sensitivity of 78.6%, specificity of 78.6%, and balanced accuracy of 78.6%). The most influential factors in the AdaBoost model were age and cardiovascular disease.

CONCLUSIONS

This study shows the use and feasibility of ML for assessing the incidence of ND in patients with T2DM and suggests its potential for use in screening patients. Further international studies are required to validate these findings.

Causal relationships between genetically predicted particulate air pollutants and neurodegenerative diseases: A two-sample Mendelian randomization study

Accumulating observational studies have linked particulate air pollutants to neurodegenerative diseases (NDDs). However, the causal links and the direction of their associations remain unclear. Therefore, we adopted a two-sample Mendelian randomization (TSMR) design using the GWAS-based genetic instruments of particulate air pollutants (PM2.5 and PM10) from the UK Biobank to explore their causal influence on four common neurodegenerative diseases. Estimates of causative relationships were generated by the Inverse variance weighted (IVW) method with multiple sensitive analyses. The heterogeneity and pleiotropy tests were additionally performed to verify whether our findings were robust. Genetically predicted PM2.5 and PM10 could elevate the occurrence of AD (odds ratio [OR] = 2.22, 95 % confidence interval [CI] 1.53-3.22, PIVW = 2.85×10-5, PFalsediscovery rate[FDR]= 2.85×10-4 and OR = 2.41, 95 % CI: 1.26-4.60, PIVW = 0.008, PFDR=0.039, respectively). The results were robust in sensitive analysis. However, no evidence of causality was found for other NDDs. Our present study suggests that PM2.5 and PM10 have a detrimental effect on AD, which indicates that improving air quality to prevent AD may have pivotal public health implications.

Ambient temperature and the risk of childhood epilepsy hospitalizations: Potentially neglected risk of temperature extremes and modifying effects of air pollution

PURPOSE

Extreme temperatures and air pollution are increasingly important risk factors for human health in the background of climate change, with limited evidence available for neurological disorders. This study intended to investigate the short-term effects of extreme temperatures on childhood epilepsy and explore the potential modifying effect of air pollution.

METHODS

Daily childhood epilepsy hospitalization, meteorological and air pollution data were collected from 10 cities in Anhui Province of China during 2016-2018. We firstly employed a space-time-stratified case-crossover design and conditional logistic regression model to fit the short-term relationship between temperature and epilepsy. Then, we conducted stratified analyses by the level of air pollution and individual characteristics.

RESULTS

Both extreme heat and extreme cold increased the risk of hospitalization for childhood epilepsy. The effect of extreme heat [97.5th vs. minimum hospitalization temperature (MHT)] on hospitalization was acute and emerged at lag0 [OR: 1.229 (95 %CI: 1.035 to 1.459)], while the effect of extreme cold (2.5th vs. MHT) was delayed and appeared at lag5 [OR: 1.098 (95 %CI: 1.043 to 1.156)]. We also found children aged 6-18 years were more susceptible to extreme cold than children aged 0-5 years. Besides, extreme heat and cold effects differed by the level of air pollutants.

CONCLUSION

This study suggests that extreme temperatures might be the novel but currently neglected risk factor for childhood epilepsy, and air pollution could further amplify the adverse effect of temperature.

Nitrogen-Doped Indium Oxide Electrochemical Sensor for Stable and Selective NO2 Detection

Efficient gas sensors are critical for environmental monitoring and industrial safety. While metal oxide semiconductor (MOS) sensors are cost-effective, they struggle with poor selectivity, high operating temperatures, and limited stability. Electrochemical sensors, though selective and energy-efficient, face high costs, and stability issues due to precious metal catalysts like platinum on carbon (Pt/C). Herein, a novel, cost-effective electrochemical sensor using nitrogen-doped indium oxide In2O3- xN2 x /3Vx /3 (0.01≤x≤0.14), synthesized with varying nitriding times is presented. The optimized In2O3 N-40 min sensor demonstrates a remarkable response current of 771 nA to 10 ppm nitrogen dioxide (NO2) at ambient temperature, with outstanding long-term stability (over 30 days) and rapid response/recovery times (5/16 s). Compared to Pt/C sensors, it shows 84% and 67% reductions in response and recovery times, respectively, and maintains 98% performance after a month, versus 68% for Pt/C. This cost-effective sensor presents a promising alternative for electrochemical gas sensing, eliminating the need for precious metal catalysts.

Unraveling neuroprotection in Parkinson's disease: Nrf2-Keap1 pathway's vital role amidst pathogenic pathways

Parkinson's disease (PD) is an age-related chronic neurological condition characterized by progressive degeneration of dopaminergic neurons and the presence of Lewy bodies, primarily composed of alpha-synuclein and ubiquitin. The pathophysiology of PD encompasses alpha-synuclein aggregation, oxidative stress, neuroinflammation, mitochondrial dysfunction, and impaired autophagy and ubiquitin-proteasome systems. Among these, the Keap1-Nrf2 pathway is a key regulator of antioxidant defense mechanisms. Nrf2 has emerged as a crucial factor in managing oxidative stress and inflammation, and it also influences ubiquitination through p62 expression. Keap1 negatively regulates Nrf2 by targeting it for degradation via the ubiquitin-proteasome system. Disruption of the Nrf2-Keap1 pathway in PD affects cellular responses to oxidative stress and inflammation, thereby playing a critical role in disease progression. In addition, the role of neuroinflammation in PD has gained significant attention, highlighting the interplay between immune responses and neurodegeneration. This review discusses the various mechanisms responsible for neuronal degeneration in PD, with a special emphasis on the neuroprotective role of the Nrf2-Keap1 pathway. Furthermore, it explores the implications of inflammopharmacology in modulating these pathways to provide therapeutic insights for PD.

Acute effects of ambient nitrogen dioxide pollution on outpatient visits for neurological diseases in Xinxiang, China

BACKGROUND

Accumulating evidence suggests that exposure to air pollution acts as a potential trigger for neurological diseases (NDs), yet the current knowledge regarding the impact of ambient nitrogen dioxide (NO2) on the patients with NDs remains limited. In this study, we conducted a time-series study to evaluate the association between short-term exposure to NO2 and hospital visits for NDs in Xinxiang, China.

METHODS

An over-dispersed Poisson generalized additive model was used to analyze the association between ambient NO2 concentrations and daily outpatient visits for NDs from January 1, 2015 to December 31, 2017. The model adjusted for meteorological factors, temporal trends, day of the week, and public holidays. The concentrations of air pollutants were collected from four air quality stations in Xinxiang.

RESULTS

A total of 38, 865 outpatient visits for NDs were retrieved during the study period. 86.5% of the patients were below the age of 65 years. It was revealed that a 10 µg/m3 increase in NO2 at lag 0 was associated with a significant rise of 1.50% (95% CI: 0.45-2.56%) in outpatient visits for NDs, which was stronger during the cold season. However, the overall results from stratified analyses did not reach statistical significance.

CONCLUSIONS

Short-term exposure to NO2 is associated with increased outpatient visits for NDs. These findings underscore the need for implementing mitigating measures to reduce the neurological health effects of air pollutants.

Association Between Body Mass Index Changes and All-Cause Mortality in Parkinson's Disease

Background

Whether body weight changes are associated with Parkinson's disease (PD) mortality remains uncertain.

Objective

To investigate the association between changes in body mass index (BMI) and all-cause mortality in patients with PD.

Methods

This nationwide cohort study enrolled 20,703 individuals with new-onset PD (ICD-10 code: G20 and a rare intractable disease registration code: V124) who underwent health screening program by the Korean National Health Insurance Service within two years from pre- and post-PD diagnosis. We identified nine BMI change groups based on three BMI status: underweight (BMI <  18.5 kg/m2), normal or overweight (18.5 kg/m2≤BMI <  25 kg/m2), and obese (BMI≥25 kg/m2).

Results

Of 20,703 individuals, 3,789 (18.0%) died during the follow-up period. Excessive weight loss to underweight in the obese group (hazard ratio [HR] = 3.36, 95% CI:1.60-7.08), weight loss in the normal to overweight group (HR = 2.04, 95% CI:1.75-2.39), sustained underweight status (HR = 2.05, 95% CI:1.67-2.52), and weight gain from underweight to normal or overweight (HR = 1.52, 95% CI:1.15-2.02) were associated with increased mortality. Sustained obese status (HR = 0.80, 95% CI:0.74-0.87) and weight gain in the normal to overweight group (HR = 0.82, 95% CI:0.71-0.95) were associated with reduced mortality.

Conclusions

We found that BMI change at diagnosis was associated with mortality in patients with PD. Specifically, being underweight either before or after diagnosis as well as experiencing weight loss, were associated with increased mortality. These findings provide valuable insights for weight management planning in PD, highlighting the importance of individualized approach that consider pre-diagnosis BMI.

Air Pollution and Parkinson Disease in a Population-Based Study

Importance

The role of air pollution in risk and progression of Parkinson disease (PD) is unclear.

Objective

To assess whether air pollution is associated with increased risk of PD and clinical characteristics of PD.

Design, Setting, and Participants

This population-based case-control study included patients with PD and matched controls from the Rochester Epidemiology Project from 1998 to 2015. Data were analyzed from January to June 2024.

Exposures

Mean annual exposure to particulate matter with a diameter of 2.5 µm or less (PM2.5) from 1998 to 2015 and mean annual exposure to nitrogen dioxide (NO2) from 2000 to 2014.

Main Outcomes and Measures

Outcomes of interest were PD risk, all-cause mortality, presence of tremor-predominant vs akinetic rigid PD, and development of dyskinesia. Models were adjusted for age, sex, race and ethnicity, year of index, and urban vs rural residence.

Results

A total of 346 patients with PD (median [IQR] age 72 [65-80] years; 216 [62.4%] male) were identified and matched on age and sex with 4813 controls (median [IQR] age, 72 [65-79] years, 2946 [61.2%] male). Greater PM2.5 exposure was associated with increased PD risk, and this risk was greatest after restricting to populations within metropolitan cores (odds ratio [OR], 1.23; 95% CI, 1.11-1.35) for the top quintile of PM2.5 exposure compared with the bottom quintile. Greater NO2 exposure was also associated with increased PD risk when comparing the top quintile with the bottom quintile (OR, 1.13; 95% CI, 1.07-1.19). Air pollution was associated with a 36% increased risk of akinetic rigid presentation (OR per each 1-μg/m3 increase in PM2.5, 1.36; 95% CI, 1.02-1.80). In analyses among patients with PD only, higher PM2.5 exposure was associated with greater risk for developing dyskinesia (HR per 1-μg/m3 increase in PM2.5, 1.42; 95% CI, 1.17-1.73), as was increased NO2 exposure (HR per 1 μg/m3 increase in NO2, 1.13; 95% CI, 1.06-1.19). There was no association between PM2.5 and all-cause mortality among patients with PD.

Conclusions and Relevance

In this case-control study of air pollution and PD, higher levels of PM2.5 and NO2 exposure were associated with increased risk of PD; also, higher levels of PM2.5 exposure were associated with increased risk of developing akinetic rigid PD and dyskinesia compared with patients with PD exposed to lower levels. These findings suggest that reducing air pollution may reduce risk of PD, modify the PD phenotype, and reduce risk of dyskinesia.

Association between air pollution and cerebrospinal fluid alpha-synuclein in urban elders: the CABLE study

Introduction

Increasing evidence suggests that air pollution has a significant impact on the development of synucleinopathies, but the potential neurobiological mechanisms are unknown. We aimed to explore the associations of air pollution (including ozone [O3], nitrogen dioxide [NO2], and particulate matter [PM2.5]) with CSF α-syn levels in urban older adults.

Methods

We included 933 urban participants from the Chinese Alzheimer's Biomarker and LifestylE study. The 5-year average levels of air pollution exposure were estimated in the areas of residence. Multivariate linear regression was conducted to detect the correlation of air pollution with CSF α-syn levels. Subgroup analyses by age, gender, season, and history of coronary heart disease (CHD) were performed. Moreover, restricted cubic spline (RCS) models were applied to explore the potential nonlinear relationships.

Results

We found a significant correlation of CSF α-syn level with PM2.5 in urban participants. Specifically, multiple linear regression showed a significant negative association between PM2.5 and CSF α-syn level (p = 0.029), which was more significant in female, midlife, non-CHD, and cold season subgroups. Besides, RCS models showed that O3 had an inverse J-shaped association with CSF α-syn levels in urban participants (p for nonlinearity = 0.040), and the harmful effect possibly appeared when O3 was above 37.9 ppb.

Discussion

Long-term exposure to air pollution was associated with lower CSF α-syn levels, which may offer a new direction for exploring and preventing synucleinopathies.

Associations of long-term exposure to low-level PM2.5 and brain disorders in 260,922 middle-aged and older adults

Long-term exposure to high-level ambient PM2.5 was associated with increased risks of brain disorders, while the associations remain uncertain when the exposure is lower than current air quality standards in numerous countries. This study aimed to assess the effects of PM2.5 exposure on the brain system in the population with annual mean concentrations ≤15 μg/m3. We analyzed data from 260,922 participants without preexisting brain diseases at baseline in the UK Biobank. The geographical distribution of PM2.5 in 2010 was estimated by a land use regression model and linked with individual residential address. We investigated associations of ambient PM2.5 with incident neurological (dementia, Parkinson's diseases [PD], epilepsy, and migraine) and psychiatric (major depressive disorder [MDD] and anxiety disorder) diseases through Cox proportional hazard models. We further estimated the links with brain imaging phenotypes by neuroimaging analysis. Results showed that in the population with PM2.5 concentrations ≤15 μg/m3, each interquartile range (IQR, 1.28 μg/m3) increment in PM2.5 was related to incidence risks of dementia, epilepsy, migraine, MDD, and anxiety disorder with hazard ratios of 1.08 (95% confidence interval [CI]: 1.03, 1.13), 1.12 (1.05, 1.20), 1.07 (1.00, 1.13), 1.06 (1.03, 1.09), and 1.05 (1.02, 1.08), respectively. We did not observe a significant association with PD. The association with dementia was stronger among the population with poor cardiovascular health (measured by Life's Essential 8) than the counterpart (P for interaction = 0.037). Likewise, per IQR increase was associated with specific brain imaging phenotypes, including volumes of total brain (β = -0.036; 95% CI: -0.050, -0.022), white matter (-0.030; -0.046, -0.014), grey matter (-0.030; -0.042, -0.017), respectively. The findings suggest long-term exposure to ambient PM2.5 at low-level still has an adverse impact on the neuro-psychiatric systems. The brain-relevant epidemiological assessment suggests that each country should update the standard for ambient PM2.5 following the World Health Organization Air Quality Guidelines 2021.

Air pollution, greenspace exposure and risk of Parkinson's disease: a prospective study of 441,462 participants

BACKGROUND

The current understandings of the relationship between air pollution (AP), greenspace exposure and Parkinson's Disease (PD) remain inconclusive.

METHODS

We engaged 441,462 participants from the UK Biobank who were not diagnosed with PD. Utilizing Cox proportional hazard regression model, relationships between AP [nitrogen dioxide (NO2), and nitrogen oxides (NOX), particulate matter < 2.5 μm in aerodynamic diameter(PM2.5), coarse particulate matter between 2.5 μm and 10 μm in aerodynamic diameter(PM2.5-10), particulate matter < 10 μm in aerodynamic diameter(PM10)], greenspace exposure, and PD risk were determined independently. Our analyses comprised three models, adjusted for covariates, and affirmed through six sensitivity analyses to bolster the robustness of our findings. Moreover, mediation analysis was deployed to discern the mediating effect of AP between greenspaces and PD.

RESULTS

During a median follow-up of 12.23 years (5,574,293 person-years), there were 3,293 PD events. Each interquartile (IQR) increment in NO2 and PM10 concentrations were associated with 10% and 8% increase in PD onset risk, while the increases in NOX, PM2.5 and PM2.5-10 were not associated with PD risk. Additionally, greenspace may safeguard by reducing NO2 and PM10 levels, with the effect mediated by NO2 and PM10 in greenspace-PD relationship.

CONCLUSION

Our findings indicate that an IQR increase in ambient NO2 and PM10 concentrations was associated with risk of PD development, while other pollutants (NOX, PM2.5 and PM2.5-10) were not associated with PD risk. Firstly, we find that augmented exposure to greenspace was associated with the lower PD risk by reducing NO2 and PM10 levels.

Causal association between air pollution and allergic rhinitis, asthma: a Mendelian randomization study

Backgrounds

Observational studies suggest that air pollutants, including particulate matter and nitrogen compounds, could elevate asthma and allergic rhinitis health risks. Nevertheless, the exact nature of the causal relationship between air pollution and asthma and allergic rhinitis remains unknown. This study utilizes the Mendelian randomization (MR) technique to explore the potential causal links between air pollution components (PM2.5, PM2.5-10, PM10, NO₂, and nitrogen dioxide) and the incidence of allergic rhinitis and asthma.

Methods

A MR study utilized summary statistics from GWAS that are publicly accessible. The inverse variance weighting (IVW) approach served as the foundational analysis technique. To ensure robustness, supplementary methodologies such as the weighted median, MR-Egger regression, simple mode, and weighted model were also applied. Heterogeneity was evaluated using Cochran's Q test, and the presence of pleiotropy was determined through MR-Egger regression. The MR-PRESSO test was employed for outlier detection, and the analysis's sensitivity was scrutinized via a leave-one-out strategy.

Results

The IVW technique showed a strong correlation between PM10 and asthma (OR = 0.625, 95% CI = 0.396-0.988, p = 0.044). No significant associations were found between asthma and other air pollutants such as PM2.5, PM2.5-10, NO₂, or nitrogen dioxide. Similarly, allergic rhinitis showed no causal relationships with any studied air pollution metrics. Pleiotropy was absent in the findings. Sensitivity analyses, employing the leave-one-out method, confirmed the stability of these results, unaffected by individual single nucleotide polymorphisms (SNPs).

Conclusion

This Mendelian randomization study establishes a causal link between PM10 exposure and asthma, suggesting that interventions to reduce air pollution may decelerate the adverse progression of asthma.

Association Between Exposure to Particulate Matter and the Incidence of Parkinson's Disease: A Nationwide Cohort Study in Taiwan

OBJECTIVE

Emerging evidence suggests that air pollution exposure may increase the risk of Parkinson's disease (PD). We aimed to investigate the association between exposure to fine particulate matter (PM2.5) and the risk of incident PD nationwide.

METHODS

We utilized data from the Taiwan National Health Insurance Research Database, which is spatiotemporally linked with air quality data from the Taiwan Environmental Protection Administration website. The study population consisted of participants who were followed from the index date (January 1, 2005) until the occurrence of PD or the end of the study period (December 31, 2017). Participants who were diagnosed with PD before the index date were excluded. To evaluate the association between exposure to PM2.5 and incident PD risk, we employed Cox regression to estimate the hazard ratio and 95% confidence interval (CI).

RESULTS

A total of 454,583 participants were included, with a mean (standard deviation) age of 63.1 (9.9) years and a male proportion of 50%. Over a mean follow-up period of 11.1 (3.6) years, 4% of the participants (n = 18,862) developed PD. We observed a significant positive association between PM2.5 exposure and the risk of PD, with a hazard ratio of 1.22 (95% CI, 1.20-1.23) per interquartile range increase in exposure (10.17 μg/m3) when adjusting for both SO2 and NO2.

CONCLUSION

We provide further evidence of an association between PM2.5 exposure and the risk of PD. These findings underscore the urgent need for public health policies aimed at reducing ambient air pollution and its potential impact on PD.

Knowledge, Attitudes, and Practices Regarding Air Pollution among Medical Students

Background: Air pollution has emerged as a global public health concern. Specifically, in Medellín, Colombia, episodes of elevated air pollution have been documented. Medical students' knowledge of air pollution is paramount for implementing future interventions directed toward patients. The aim of this research was to delineate the knowledge, attitudes, and practices regarding air pollution among medical students at a private university in Medellín. Methods: A cross-sectional study involving 352 medical students was conducted. A questionnaire was administered, generating scores ranging from 0 to 100, where a higher score signified better knowledge, attitudes, and practices. Data were analyzed using frequencies, summary measures, non-parametric tests, and linear regression. Results: In total, 31% rated the education received at the university on the relationship between health and air quality as fair to poor, and 81% perceived the air quality in the city as poor. The knowledge score was 77.8 (IQR 71.1-85.6), with 90% acknowledging that exposure to air pollution increases the risk of various diseases. The attitudes score was 82.1 (IQR 71.8-87.2), and 25.9% believed that air pollution is a multifactorial problem, rendering their actions ineffective. In terms of practices, the score was 50 (IQR 42.9-57.1), indicating that students either did not employ protective measures against pollution or used inappropriate practices such as masks or air purifiers. Regression analysis revealed no association between knowledge and practices. Conclusion: The findings of this study underscore that medical students possess commendable knowledge regarding the health effects of air pollution. However, their adoption of inappropriate practices for self-protection is evident. The lack of correlation between knowledge and practices highlights the necessity of educational initiatives to be complemented by regulatory and cultural interventions.

Causal association between long-term exposure to air pollution and incident Parkinson's disease

Epidemiological evidence for long-term air pollution exposure and Parkinson's disease (PD) is controversial, and analysis of causality is limited. We identified 293,888 participants who were free of PD at baseline in the UK Biobank (2006-2010). Time-varying air pollution [fine particulate (PM2.5) and ozone (O3)] exposures were estimated using spatio-temporal models. Incident cases of PD were identified using validated algorithms. Four methods were used to investigate the associations between air pollution and PD, including (1) standard time-varying Cox proportional-hazard model; (2) Cox models weighted by generalized propensity score (GPS) and inverse-probability weights (IPW); (3) instrumental variable (IV) analysis; and (4) negative control outcome analysis. During a median of 11.6 years of follow-up, 1822 incident PD cases were identified. Based on standard Cox regression, the hazard ratios (95% confidence interval) for a 1 µg/m3 or ppb increase in PM2.5 and O3 were 1.23 (1.17, 1.30) and 1.02 (0.98, 1.05), respectively. Consistent results were found in models weighted by GPS and IPW, and in IV analysis. There were no significant associations between air pollution and negative control outcomes. This study provides evidence to support a causal association between PM2.5 exposure and PD. Mitigation of air pollution could be a protective measure against PD.

Trends in parkinson's disease mortality in China from 2004 to 2021: a joinpoint analysis

BACKGROUND

This study aimed to analyze the trends of Parkinson's disease (PD) mortality rates among Chinese residents from 2004 to 2021, provide evidence for the formulation of PD prevention and control strategies to improve the quality of life among PD residents.

METHODS

Demographic and sociological data such as gender, urban or rural residency and age were obtained from the National Cause of Death Surveillance Dataset from 2004 to 2021. We then analyzed the trends of PD mortality rates by Joinpoint regression.

RESULTS

The PD mortality and standardized mortality rates in China showed an overall increasing trend during 2004-2021 (average annual percentage change [AAPC] = 7.14%, AAPCASMR=3.21%, P < 0.001). The mortality and standardized mortality rate in male (AAPC = 7.65%, AAPCASMR=3.18%, P < 0.001) were higher than that of female (AAPC = 7.03%, AAPCASMR=3.09%, P < 0.001). The PD standardized mortality rates of urban (AAPC = 5.13%, AAPCASMR=1.76%, P < 0.001) and rural (AAPC = 8.40%, AAPCASMR=4.29%, P < 0.001) residents both increased gradually. In the age analysis, the mortality rate increased with age. And the mortality rates of those aged > 85 years was the highest. Considering gender, female aged > 85 years had the fastest mortality trend (annual percentage change [APC] = 5.69%, P < 0.001). Considering urban/rural, rural aged 80-84 years had the fastest mortality trend (APC = 6.68%, P < 0.001).

CONCLUSIONS

The mortality rate of PD among Chinese residents increased from 2004 to 2021. Male sex, urban residence and age > 85 years were risk factors for PD-related death and should be the primary focus for PD prevention.

α-Synuclein: A Promising Biomarker for Parkinson's Disease and Related Disorders

Mutations in the SNCA gene, which encodes α-synuclein (α-syn), play a key role in the development of genetic Parkinson's disease (PD). α-Syn is a major component of Lewy bodies in PD and glial cytoplasmic inclusions in multiple system atrophy (MSA). Rapid eye movement sleep behavior disorder patients often progress to PD, dementia with Lewy bodies, or MSA, which are collectively known as α-synucleinopathies. The loss of dopaminergic neurons with Lewy bodies precedes motor dysfunction in these diseases, but the mechanisms of neurodegeneration due to α-syn aggregation are poorly understood. Monitoring α-syn aggregation in vivo could serve as a diagnostic biomarker and help elucidate pathogenesis, necessitating a simple and accurate detection method. Seed amplification assays (SAAs), such as real-time quaking-induced conversion and protein misfolding cyclic amplification, are used to detect small amounts of abnormally structured α-syn protofibrils, which are central to aggregation. These methods are promising for the early diagnosis of α-synucleinopathy. Differences in α-syn filament structures between α-synucleinopathies, as observed through transmission electron microscopy and cryo-electron microscopy, suggest their role in the pathogenesis of neurodegeneration. SAAs may differentiate between subtypes of α-synucleinopathy and other diseases. Efforts are also being made to identify α-syn from blood using various methods. This review introduces body fluid α-syn biomarkers based on pathogenic α-syn seeds, which are expected to redefine α-synucleinopathy diagnosis and staging, improving clinical research accuracy and facilitating biomarker development.

Role of the Exposome in Neurodegenerative Disease: Recent Insights and Future Directions

Neurodegenerative diseases are increasing in prevalence and place a significant burden on society. The causes are multifactorial and complex, and increasing evidence suggests a dynamic interplay between genes and the environment, emphasizing the importance of identifying and understanding the role of lifelong exposures, known as the exposome, on the nervous system. This review provides an overview of recent advances toward defining neurodegenerative disease exposomes, focusing on Parkinson's disease, amyotrophic lateral sclerosis, and Alzheimer's disease. We present the current state of the field based on emerging data, elaborate on key themes and potential mechanisms, and conclude with limitations and future directions. ANN NEUROL 2024;95:635-652.

Association of Long-Term Exposure to Ambient Air Pollution With the Risk of Acute Primary Angle Closure

Purpose

The purpose of this study was to investigate the association between long-term exposure to ambient air pollutants and the risk of acute primary angle closure (APAC).

Methods

Two hundred eighty-one (281) patients with APAC and 730 age- and sex-matched controls hospitalized between January 2017 and December 2019 were enrolled in this retrospective case-control study. Residential exposure to ambient air pollutants, including fine particulate matter (PM2.5), inhalable particulate (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone were estimated by satellite-models or ground measurement. Multivariate regression analyses explored the association between annual air pollutants exposure and the risk of APAC.

Results

Of the 1011 participants (31.1% were male subjects), the average age was 64.0 years. Long-term exposure to PM2.5, PM10, and SO2 were significantly associated with an increased risk of APAC. The adjusted odds ratios (aORs) for each interquartile range (IQR) increment of PM2.5, PM10, and SO2 were 1.28 (95% confidence interval [CI] = 1.06-1.57), 1.26 (95% CI = 1.06-1.50), and 1.30 (95% CI = 1.04-1.62) separately, after controlling for confounders. Robust associations were observed for a longer lag 2-year exposure.

Conclusions

Long-term exposure to PM2.5, PM10, and SO2 was associated with an increased risk of APAC in a Chinese population. Our findings provide epidemiological implications on the adverse effects of air pollution on ocular diseases.

Translational Relevance

Long-term exposure to ambient air pollutants increased the risk of APAC.

Depressive Symptoms and the Subsequent Risk of Parkinson's Disease: A Nationwide Cohort Study

OBJECTIVE

Only a few studies have focused on depressive symptoms and Parkinson's disease (PD) risk. As a time lag exists from the onset of depressive symptoms to the diagnosis of depression, elucidating the association between depressive symptoms and PD development might be helpful for the early prediction of PD. We investigate the association between depressive symptoms and subsequent PD risk using nationwide population-based cohort database.

DESIGN AND SETTING

Cohort study using the Korean National Health Insurance Service data between 2007 and 2017, with longitudinal follow-up until 2019.

PARTICIPANTS

A total of 98,296 elderly people responded to a self-reported questionnaire from the National Health Screening Program on depressive symptoms.

MEASUREMENTS

The association between depressive symptoms such as 1) decreased activity or motivation, 2) worthlessness, and 3) hopelessness and PD risk was analyzed.

RESULTS

During median 5.06-year follow-up, 839 PD cases occurred: 230 in individuals with depressive symptoms and 609 in those without symptoms. Results showed an increased risk of PD development in those with depressive symptoms (HR = 1.47, 95% CI, 1.26-1.71), with dose-response association between the number of depressive symptoms and PD risk. Even in those already diagnosed with depression, combined depressive symptoms were linked to a higher risk compared to those without symptoms (with symptoms, HR = 2.71, 95% CI, 2.00-3.68; without symptoms, HR = 1.84, 95% CI, 1.43-2.36).

CONCLUSION

Individuals with depressive symptoms were at an increased risk of developing PD, and there was a dose-response association between the number of depressive symptoms and PD risk.

Trafficking in Disease: More Evidence for Air Pollution-Parkinson's Association

Research using Sister Study data has implicated nitrogen dioxide (vehicle exhaust is a major source), and possibly fine particulate matter, in increased risk for Parkinson's disease.

Genetic susceptibility modifies the association of long-term air pollution exposure on Parkinson's disease

Inconsistent findings exist regarding the potential association between polluted air and Parkinson's disease (PD), with unclear insights into the role of inherited sensitivity. This study sought to explore the potential link between various air pollutants and PD risk, investigating whether genetic susceptibility modulates these associations. The population-based study involved 312,009 initially PD-free participants with complete genotyping data. Annual mean concentrations of PM2.5, PM10, NO2, and NOx were estimated, and a polygenic risk score (PRS) was computed to assess individual genetic risks for PD. Cox proportional risk models were employed to calculate hazard ratios (HR) and 95% confidence intervals (CI) for the associations between ambient air pollutants, genetic risk, and incident PD. Over a median 12.07-year follow-up, 2356 PD cases (0.76%) were observed. Compared to the lowest quartile of air pollution, the highest quartiles of NO2 and PM10 pollution showed HRs and 95% CIs of 1.247 (1.089-1.427) and 1.201 (1.052-1.373) for PD incidence, respectively. Each 10 μg/m3 increase in NO2 and PM10 yielded elevated HRs and 95% CIs for PD of 1.089 (1.026-1.155) and 1.363 (1.043-1.782), respectively. Individuals with significant genetic and PM10 exposure risks had the highest PD development risk (HR: 2.748, 95% CI: 2.145-3.520). Similarly, those with substantial genetic and NO2 exposure risks were over twice as likely to develop PD compared to minimal-risk counterparts (HR: 2.414, 95% CI: 1.912-3.048). Findings suggest that exposure to air contaminants heightens PD risk, particularly in individuals genetically predisposed to high susceptibility.

Traffic-related air pollution and Parkinson's disease in central California

BACKGROUND

Prior studies suggested that air pollution exposure may increase the risk of Parkinson's Disease (PD). We investigated the long-term impacts of traffic-related and multiple sources of particulate air pollution on PD in central California.

METHODS

Our case-control analysis included 761 PD patients and 910 population controls. We assessed exposure at residential and occupational locations from 1981 to 2016, estimating annual average carbon monoxide (CO) concentrations - a traffic pollution marker - based on the California Line Source Dispersion Model, version 4. Additionally, particulate matter (PM2.5) concentrations were based on a nationwide geospatial chemical transport model. Exposures were assessed as 10-year averages with a 5-year lag time prior to a PD diagnosis for cases and an interview date for controls, subsequently categorized into tertiles. Logistic regression models were used, adjusting for various factors.

RESULTS

Traffic-related CO was associated with an increased odds ratio for PD at residences (OR for T3 vs. T1: 1.58; 95% CI: 1.20, 2.10; p-trend = 0.02) and workplaces (OR for T3 vs. T1: 1.91; 95% CI: 1.22, 3.00; p-trend <0.01). PM2.5 was also positively associated with PD at residences (OR for T3 vs. T1: 1.62; 95% CI: 1.22, 2.15; p-trend <0.01) and workplaces (OR for T3 vs. T1: 1.85; 95% CI: 1.21, 2.85; p-trend <0.01). Associations remained robust after additional adjustments for smoking status and pesticide exposure and were consistent across different exposure periods.

CONCLUSION

We found that long-term modeled exposure to local traffic-related air pollution (CO) and fine particulates from multiple sources (PM2.5) at homes and workplaces in central California was associated with an increased risk of PD.

Parkinson's Disease Is Predominantly an Environmental Disease

Parkinson's disease is the world's fastest growing brain disorder, and exposure to environmental toxicants is the principal reason. In this paper, we consider alternative, but unsatisfactory, explanations for its rise, including improved diagnostic skills, aging populations, and genetic causes. We then detail three environmental toxicants that are likely among the main causes of Parkinson's disease- certain pesticides, the solvent trichloroethylene, and air pollution. All three environmental toxicants are ubiquitous, many affect mitochondrial functioning, and all can access humans via various routes, including inhalation and ingestion. We reach the hopeful conclusion that most of Parkinson's disease is thus preventable and that we can help to create a world where Parkinson's disease is increasingly rare.

Air Pollutants and Risk of Parkinson's Disease among Women in the Sister Study

BACKGROUND

Air pollutants may contribute to the development of Parkinson's disease (PD), but empirical evidence is limited and inconsistent.

OBJECTIVES

This study aimed to prospectively investigate the associations of PD with ambient exposures to fine particulate matter with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ) and nitrogen dioxide (NO 2 ).

METHODS

We analyzed data from 47,108 US women from the Sister Study, enrolled from 2003-2009 (35-80 years of age) and followed through 2018. Exposures of interest included address-level ambient PM 2.5 and NO 2 in 2009 and their cumulative averages from 2009 to PD diagnosis with varying lag-years. The primary outcome was PD diagnosis between 2009 and 2018 (n = 163 ). We used multivariable Cox proportional hazards and time-varying Cox models to calculate hazard ratios (HRs) and 95% confidence intervals (CIs).

RESULTS

NO 2 exposure in 2009 was associated with PD risk in a dose-response manner. The HR and 95% CI were 1.22 (95% CI: 1.03, 1.46) for one interquartile [4.8 parts per billion (ppb)] increment in NO 2 , adjusting for age, race and ethnicity, education, smoking status, alcohol drinking, caffeine intake, body mass index, physical activity, census region, residential area type, area deprivation index (ADI), and self-reported health status. The association was confirmed in secondary analyses with time-varying averaged cumulative exposures. For example, the multivariable adjusted HR for PD per 4.8   ppb increment in NO 2 was 1.25 (95% CI: 1.05, 1.50) in the 2-year lag analysis using cumulative average exposure. Post hoc subgroup analyses overall confirmed the association. However, statistical interaction analyses found that the positive association of NO 2 with PD risk was limited to women in urban, rural, and small town areas and women with ≥ 50 th percentile ADI but not among women from suburban areas or areas with < 50 th percentile ADI. In contrast, PM 2.5 exposure was not associated with PD risk with the possible exception for women from the Midwest region of the US (HR interquartile -range = 2.49 , 95% CI: 1.20, 5.14) but not in other census regions.

DISCUSSION

In this nationwide cohort of US women, higher level exposure to ambient NO 2 is associated with a greater risk of PD. This finding needs to be independently confirmed and the underlying mechanisms warrant further investigation. https://doi.org/10.1289/EHP13009.

The Body, the Brain, the Environment, and Parkinson's Disease

The brain- and body-first models of Lewy body disorders predict that aggregated alpha-synuclein pathology usually begins in either the olfactory system or the enteric nervous system. In both scenarios the pathology seems to arise in structures that are closely connected to the outside world. Environmental toxicants, including certain pesticides, industrial chemicals, and air pollution are therefore plausible trigger mechanisms for Parkinson's disease and dementia with Lewy bodies. Here, we propose that toxicants inhaled through the nose can lead to pathological changes in alpha-synuclein in the olfactory system that subsequently spread and give rise to a brain-first subtype of Lewy body disease. Similarly, ingested toxicants can pass through the gut and cause alpha-synuclein pathology that then extends via parasympathetic and sympathetic pathways to ultimately produce a body-first subtype. The resulting spread can be tracked by the development of symptoms, clinical assessments, in vivo imaging, and ultimately pathological examination. The integration of environmental exposures into the brain-first and body-first models generates testable hypotheses, including on the prevalence of the clinical conditions, their future incidence, imaging patterns, and pathological signatures. The proposed link, though, has limitations and leaves many questions unanswered, such as the role of the skin, the influence of the microbiome, and the effects of ongoing exposures. Despite these limitations, the interaction of exogenous factors with the nose and the gut may explain many of the mysteries of Parkinson's disease and open the door toward the ultimate goal -prevention.

Parkinson's Disease is Predominantly a Genetic Disease

The discovery of a pathogenic variant in the alpha-synuclein (SNCA) gene in the Contursi kindred in 1997 indisputably confirmed a genetic cause in a subset of Parkinson's disease (PD) patients. Currently, pathogenic variants in one of the seven established PD genes or the strongest known risk factor gene, GBA1, are identified in ∼15% of PD patients unselected for age at onset and family history. In this Debate article, we highlight multiple avenues of research that suggest an important - and in some cases even predominant - role for genetics in PD aetiology, including familial clustering, high rates of monogenic PD in selected populations, and complete penetrance with certain forms. At first sight, the steep increase in PD prevalence exceeding that of other neurodegenerative diseases may argue against a predominant genetic etiology. Notably, the principal genetic contribution in PD is conferred by pathogenic variants in LRRK2 and GBA1 and, in both cases, characterized by an overall late age of onset and age-related penetrance. In addition, polygenic risk plays a considerable role in PD. However, it is likely that, in the majority of PD patients, a complex interplay of aging, genetic, environmental, and epigenetic factors leads to disease development.

Exploring the association between air pollution and Parkinson's disease or Alzheimer's disease: a Mendelian randomization study

The correlation between air pollution and neurodegenerative diseases has garnered growing attention. Although observational studies have indicated a potential link between air pollution and neurodegenerative disease, establishing a causal relationship remains uncertain. To address this gap, we performed a two-sample Mendelian randomization analysis utilizing genetic instruments. This analysis aimed to investigate the causal connections between PM2.5, PM10, NO2, and NOX exposure and the occurrence of Parkinson's disease (PD) and Alzheimer's disease (AD). We implemented a series of filtering steps to identify suitable genetic instruments that demonstrated significant associations (P < 5 × 10-8) with PM2.5, PM10, NO2, and NOX. These instruments were derived from a comprehensive genome-wide association study (GWAS) encompassing up to 456,380 participants in the UK Biobank. To obtain summary statistics for PD (N = 482,730) and AD risk (N = 63,926), we utilized the most recent GWAS datasets available. For our primary analysis, we employed the inverse-variance weighted approach for two-sample MR. A multivariable MR (MVMR) was also performed to verify the impact of air pollution exposure on the risk of PD and AD. To ensure the robustness of our findings, sensitivity analyses and heterogeneity assessments were performed. In two-sample MR, by employing the inverse-variance weighted method, our result suggested that genetically NO2 exposure showed a significant association with an elevated risk of PD (OR = 4.07, 95% CI: 1.13 to 19.62, P = 0.034) and genetically PM10 exposure exhibited a significant association with a heightened risk of AD (OR = 1.93, 95% CI: 1.03-3.59, P = 0.040). Further MVMR analysis demonstrated that the causal effect between NO2 and PD disappeared (OR = 3.489, 95% CI: 0.01 to 2.1e + 03, P = 0.703), and only PM10 was associated with an increased risk of AD (OR = 6.500, 95% CI: 1.10 to 38.51, P = 0.039). Sensitivity analysis showed no detectable heterogeneity and pleiotropy (P > 0.05). Our findings demonstrate that NO2 and PM10 exposure may contribute to a risk of PD and AD, respectively. Future research is necessary to elucidate potential physiopathological mechanisms.

Fine Particulate Matter and Parkinson Disease Risk Among Medicare Beneficiaries

BACKGROUND AND OBJECTIVES

Numerous studies suggest that environmental exposures play a critical role in Parkinson disease (PD) pathogenesis, and large, population-based studies have the potential to advance substantially the identification of novel PD risk factors. We sought to study the nationwide geographic relationship between PD and air pollution, specifically PM2.5 (particulate matter with a diameter <2.5 micrometers), using population-based US Medicare data.

METHODS

We conducted a population-based geographic study of Medicare beneficiaries aged 66-90 years geocoded to US counties and zip+4. We used integrated nested Laplace approximation to create age, sex, race, smoking, and health care utilization-adjusted relative risk (RR) at the county level for geographic analyses with PM2.5 as the primary exposure of interest. We also performed an individual-level analysis using logistic regression with cases and controls with zip+4 centroid PM2.5. We adjusted a priori for the same covariates and verified no confounding by indicators of socioeconomic status or neurologist density.

RESULTS

Among 21,639,190 Medicare beneficiaries, 89,390 had incident PD in 2009. There was a nationwide association between average annual PM2.5 and PD risk whereby the RR of PD was 56% (95% CI 47%-66%) greater for those exposed to the median level of PM2.5 compared with those with the lowest level of PM2.5. This association was linear up to 13 μg/m3 corresponding to a 4.2% (95% CI 3.7%-4.8%) greater risk of PD for each additional μg/m3 of PM2.5 (p trend < 0.0001). We identified a region with high PD risk in the Mississippi-Ohio River Valley, where the risk of PD was 19% greater compared with the rest of the nation. The strongest association between PM2.5 and PD was found in a region with low PD risk in the Rocky Mountains. PM2.5 was also associated with PD in the Mississippi-Ohio River Valley where the association was relatively weaker, due to a possible ceiling effect at average annual PM2.5 levels of ∼13 μg/m3.

DISCUSSION

State-of-the-art geographic analytic techniques revealed an association between PM2.5 and PD that varied in strength by region. A deeper investigation into the specific subfractions of PM2.5 may provide additional insight into regional variability in the PM2.5-PD association.

The challenges in managing co-occurring Parkinson's and schizophrenia spectrum disorders

This article explores the relationship between Parkinson's and schizophrenia spectrum disorders, discussing not only the possibility that they can be comorbid conditions but that the presence of one could increase the chances of developing the other. They are rarely documented together, other than in relation to medication-induced side effects, and this could be due to diagnostic overshadowing, or the widely held belief that these conditions are not able to co-exist. It also briefly discusses treatment options available and gaps identified for future research.

Integrative proteomics and metabolomics analysis of non-observable acute effect level PM2.5 induced accumulative effects in AC16 cells

Chronic exposure to very low ambient PM2.5 has been linked to cardiovascular risks in epidemiological observation, which also brought doubts on its safety threshold. In this study, we approached this question by chronic exposure of AC16 to the non-observable acute effect level (NOAEL) PM2.5 5 μg/mL and its positive reference 50 μg/mL, respectively. The doses were respectively defined on the cell viabilities >95% (p = 0.354) and >90% (p = 0.004) when treated acutely (24 h). To mimic the long-term exposure, AC16 was cultured from the 1st to 30th generations and treated with PM2.5 24 h in every three generations. The integration of proteomic and metabolomic analysis was applied, and 212 proteins and 172 metabolites were significantly altered during the experiments. The NOAEL PM2.5 induced both dose- and time-dependent disruption, which showed the dynamic cellular proteomic response and oxidation accumulation, the main metabolomics changes were ribonucleotide, amino acid, and lipid metabolism that have involved in stressed gene expression, and starving for energy metabolism and lipid oxidation. In summary, these pathways interacted with the monotonically increasing oxidative stress and led to the accumulated damage in AC16 and implied that the safe threshold of PM2.5 may be non-existent when a long-term exposure occurred.

Particulate matter exposure and neurodegenerative diseases: A comprehensive update on toxicity and mechanisms

Exposure to particulate matter (PM) has been associated with a range of health impacts, including neurological abnormalities that affect neurodevelopment, neuroplasticity, and behavior. Recently, there has been growing interest in investigating the possible relationship between PM exposure and the onset and progression of neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, Huntington's disease, and multiple sclerosis. However, the precise mechanism by which PM affects neurodegeneration is still unclear, even though several epidemiological and animal model studies have provided mechanistic insights. This article presents a review of the current research on the neurotoxicity of PM and its impact on neurodegenerative diseases. This review summarizes findings from epidemiological and animal model studies collected through searches in Google Scholar, PubMed, Web of Science, and Scopus. This review paper also discusses the reported effects of PM exposure on the central nervous system and highlights research gaps and future directions. The information presented in this review may inform public health policies aimed at reducing PM exposure and may contribute to the development of new treatments for neurodegenerative diseases. Further mechanistic and therapeutic research will be needed to fully understand the relationship between PM exposure and neurodegenerative diseases.

Assessing traffic-related air pollution-induced fiber-specific white matter degradation associated with motor performance declines in aged rats

Fine particulate matter (PM2.5) is thought to exacerbate Parkinson's disease (PD) in the elderly, and early detection of PD progression may prevent further irreversible damage. Therefore, we used diffusion tensor imaging (DTI) for probing microstructural changes after late-life chronic traffic-related PM2.5 exposure. Herein, 1.5-year-old Fischer 344 rats were exposed to clean air (control), high-efficiency particulate air (HEPA)-filtered ambient air (HEPA group), and ambient traffic-related PM2.5 (PM2.5 group, 9.933 ± 1.021 µg/m3) for 3 months. Rotarod test, DTI tractographic analysis, and immunohistochemistry were performed in the end of study period. Aged rats exposed to PM2.5 exhibited motor impairment with decreased fractional anisotropy and tyrosine hydroxylase expression in olfactory and nigrostriatal circuits, indicating disrupted white matter integrity and dopaminergic (DA) neuronal loss. Additionally, increased radial diffusivity and lower expression of myelin basic protein in PM2.5 group suggested ageing progression of demyelination exacerbated by PM2.5 exposure. Significant production of tumor necrosis factor-α was also observed after PM2.5 exposure, revealing potential inflammation of injury to multiple fiber tracts of DA pathways. Microstructural changes demonstrated potential links between PM2.5-induced inflammatory white matter demyelination and behavioral performance, with indication of pre-manifestation of DTI-based biomarkers for early detection of PD progression in the elderly.

The association between intermediate-term sulfur dioxide exposure and outpatient visits for Parkinson's disease: a time-series study in southwestern China

Parkinson's disease (PD) is the second most common human neurodegenerative disorder, and the pathogenesis of it remains poorly understood. Limited studies have shown that both long- and short-term exposure to air pollutants may be associated with increased risk of PD while lacking evidence on the effects of intermediate-term exposure. In this study, over-dispersed Poisson generalized additive models (GAMs) were applied to explore the association between intermediate-term sulfur dioxide (SO2) exposure and outpatient visits for PD in Chongqing, China, and further stratified analyses were performed by age and gender. A total of 39,984 PD cases from January 1, 2014, to December 31, 2019 (2191 days) were included. The association of intermediate-term SO2 exposure with outpatient visits for PD was statistically significant: per 1 μg/m3 increase of SO2 corresponded to 2.34% (95% CI: 0.88%, 3.80%) elevation in monthly PD outpatient visits at lag 0 (the concurrent month). Stratified analyses showed that the associations between SO2 and PD outpatient visits were stronger in younger (≤ 60 years) and female patients. In conclusion, intermediate-term SO2 exposure can be associated with an increased risk of PD outpatient visits. Our results highlight the importance of recognizing the role of intermediate-term SO2 exposure in the development of PD. In addition to focusing on the effects of long-term or short-term air pollutants, it is necessary to pay more attention to the health effects of intermediate-term exposure time windows of air pollutants, which will facilitate policy formulation and public health interventions for health risks.

Linking environmental risk factors with epigenetic mechanisms in Parkinson's disease

Sporadic Parkinson's disease (PD) is a progressive neurodegenerative disease, with a complex risk structure thought to be influenced by interactions between genetic variants and environmental exposures, although the full aetiology is unknown. Environmental factors, including pesticides, have been reported to increase the risk of developing the disease. Growing evidence suggests epigenetic changes are key mechanisms by which these environmental factors act upon gene regulation, in disease-relevant cell types. We present a systematic review critically appraising and summarising the current body of evidence of the relationship between epigenetic mechanisms and environmental risk factors in PD to inform future research in this area. Epigenetic studies of relevant environmental risk factors in animal and cell models have yielded promising results, however, research in humans is just emerging. While published studies in humans are currently relatively limited, the importance of the field for the elucidation of molecular mechanisms of pathogenesis opens clear and promising avenues for the future of PD research. Carefully designed epidemiological studies carried out in PD patients hold great potential to uncover disease-relevant gene regulatory mechanisms. Therefore, to advance this burgeoning field, we recommend broadening the scope of investigations to include more environmental exposures, increasing sample sizes, focusing on disease-relevant cell types, and recruiting more diverse cohorts.

Long-term exposure to low-level particulate air pollution and Parkinson's disease diagnosis - A Finnish register-based study

BACKGROUND

There is mixed evidence for an association between particulate matter air pollution and Parkinson's disease despite biological plausibility.

OBJECTIVES

We studied the association between particulate air pollution, its components and Parkinson's disease (PD) risk.

METHODS

We conducted a nested case-control study within the population of Finland using national registers. A total of 22,189 incident PD cases diagnosed between 1996 and 2015 were matched by age, sex and region with up to seven controls (n = 148,009) per case. Time weighted average air pollution exposure to particulate matter and its components was modelled at the residential addresses, accounting for move history, for the 16 years preceding diagnosis. Conditional logistic regression analysis was used to evaluate the association between air pollution and PD. Different exposure periods (6-16 years, 11-16 years, 5-10 years, 0-5 years) before the index date (date of PD diagnosis) were applied.

RESULTS

Time-weighted average exposures were relatively low at 12.1 ± 6.5 μg/m3 (mean ± SD) for PM10 and 7.7 ± 3.2 μg/m3 for PM2.5. No associations were found between PM2.5 or PM10 exposure 6-16 years before index date and PD (OR: 0.99; 95% CI: 0.96, 1.02; per IQR of 3.9 μg/m3 and OR: 0.99; 95% CI: 0.96, 1.01; per IQR of 7.8 μg/m3, respectively). However, inverse associations were observed for the same exposure period with black carbon (OR: 0.96; 95% CI: 0.93, 0.99; per IQR of 0.6 μg/m3), sulphate (OR: 0.79; 95% CI: 0.68, 0.92; per IQR of 1.2 μg/m3), secondary organic aerosols (OR: 0.86; 95% CI: 0.80, 0.93; per IQR of 0.1 μg/m3) and sea salt (OR: 0.92; 95% CI: 0.87, 0.98; per IQR of 0.1 μg/m3).

DISCUSSION

Low-level particulate matter air pollution was not associated with increased risk of incident PD in this Finnish nationwide population. The observed weak inverse associations with specific particle components should be investigated further.

Residential greenness, air pollution and incident neurodegenerative disease: A cohort study in China

BACKGROUND

Neurodegenerative disease has a great adverse impact on population's death and disability worldwide. However, the association of air pollution and residential greenness with neurodegenerative disease and their potential mechanisms still remain uncertain.

METHODS

We used data from a population-based prospective cohort in Ningbo, China. Exposure to PM_2.5, PM₁₀ and NO₂ were assessed by land-use regression (LUR) models and residential greenness was estimated by Normalized Difference Vegetation Index (NDVI). Our primary outcomes were all neurodegenerative diseases, Parkinson's disease (PD) and Alzheimer's disease (AD). Cox proportional hazards regression models were used to examine the association of air pollution and residential greenness with risk of incident neurodegenerative disease. Furthermore, we also explored the potential mediation relationship and effect modification between greenness and air pollutants.

RESULTS

During the follow-up period, we identified a total of 617 incident neurodegenerative diseases, 301 PD and 182 AD. In single-exposure models, PM_2.5 was positively associated with all outcomes (e.g. AD hazard ratio (HR): 1.41, 95 % confidence interval (CI): 1.09-1.84, per interquartile range (IQR) increment), whereas residential greenness showed protective effects (e.g. neurodegenerative disease, HR: 0.82, 95%CI: 0.75-0.90, per IQR increment for NDVI in 1000 m buffer). NO₂ was positively associated with risk of neurodegenerative disease and PM₁₀ was associated with neurodegenerative disease and AD. In two-exposure models, after adjustment for PM_2.5, the association for greenness generally attenuated towards null. Moreover, we identified the significant modification effect of greenness on PM2.5 on additive and multiplicative scales.

CONCLUSION

In this prospective study, we found that exposure to higher residential greenness and lower concentrations of particulate matter were associated with lower risk of neurodegenerative disease, PD and AD. Residential greenness could modify the association of PM_2.5 with neurodegenerative disease.

Long-term cardiometabolic effects of ambient ozone pollution in a large Chinese population

Limited studies investigated the effects of long-term ozone exposure on cardiometabolic health. We aimed to examine the association of long-term ozone exposure with a range of cardiometabolic diseases, as well as the subclinical indicators in Eastern China. The study included 202,042 adults living in 11 prefecture-level areas in Zhejiang Province between 2014 and 2021. Using a satellite-based model with a 1 × 1 km spatial resolution, we estimated residential 5-year average ozone exposures for each subject. Mixed-effects logistic and linear regression models were applied to explore the associations of ozone exposure with cardiometabolic diseases and subclinical indicators, respectively. We found that a 9% [95% confidence interval (95% CI): 7-12%] higher in odds of cardiometabolic disease per 10 μg/m³ increase in ozone exposure. Specifically, we also found higher prevalence of cardiovascular diseases (15%), stroke (19%), hypertension (7%), dyslipidemia (15%), and hypertriglyceridemia (9%) associated with ozone exposure. However, we did not find significant associations between ozone exposure and coronary heart disease, myocardial infarction, or diabetes mellitus. Long-term ozone exposures were also significantly associated with adverse changes in systolic blood pressure, diastolic blood pressure, total serum cholesterol, triglyceride, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, glucose concentration, and body mass index. Our results showed that people with lower education levels, those over 50 years old, and those who were overweight or obese were more susceptible to the effects of ozone on cardiometabolic diseases. Our findings demonstrated the detrimental effects of long-term ozone exposure on cardiometabolic health, emphasizing the need for ozone control strategies to reduce the burden of cardiometabolic diseases.

Semiconducting MOFs on ultraviolet laser-induced graphene with a hierarchical pore architecture for NO2 monitoring

Due to rapid urbanization worldwide, monitoring the concentration of nitrogen dioxide (NO₂), which causes cardiovascular and respiratory diseases, has attracted considerable attention. Developing real-time sensors to detect parts-per-billion (ppb)-level NO₂ remains challenging due to limited sensitivity, response, and recovery characteristics. Herein, we report a hybrid structure of Cu₃HHTP₂, 2D semiconducting metal-organic frameworks (MOFs), and laser-induced graphene (LIG) for high-performance NO₂ sensing. The unique hierarchical pore architecture of LIG@Cu₃HHTP₂ promotes mass transport of gas molecules and takes full advantage of the large surface area and porosity of MOFs, enabling highly rapid and sensitive responses to NO₂. Consequently, LIG@Cu₃HHTP₂ shows one of the fastest responses and lowest limit of detection at room temperature compared with state-of-the-art NO₂ sensors. Additionally, by employing LIG as a growth platform, flexibility and patterning strategies are achieved, which are the main challenges for MOF-based electronic devices. These results provide key insight into applying MOFtronics as high-performance healthcare devices.

UV radiation and air pollution as drivers of major autoimmune conditions

Autoimmune diseases comprise a very heterogeneous group of disorders characterized by disruptive immune responses against self-antigens, chronic morbidity and increased mortality. The incidence and prevalence of major autoimmune conditions are particularly high in the western world, at northern latitudes, and in industrialized countries. This study will mainly focus on five major autoimmune conditions, namely type 1 diabetes, multiple sclerosis, inflammatory bowel diseases, rheumatoid arthritis, and autoimmune thyroid disorders. Epidemiological and experimental evidence suggests a protective role of sunlight exposure on the etiology of major autoimmune conditions mediated by the endogenous production of vitamin D and nitric oxide. A historical perspective shows how the rise of anthropogenic air pollutants is temporally associated with dramatic increases in incidence of these conditions. The scattering caused by ambient particulate matter and the presence of tropospheric ozone can reduce the endogenous production of vitamin D and nitric oxide, which are implicated in maintaining the immune homeostasis. Air pollutants have direct detrimental effects on the human body and are deemed responsible of an increasingly higher portion of the annual burden of human morbidity and mortality. Air pollution contributes in systemic inflammation, activates oxidative pathways, induces epigenetic alterations, and modulates the function and phenotype of dendritic cells, Tregs, and T-cells. In this review, we provide epidemiological and mechanistic insights regarding the role of UV-mediated effects in immunity and how anthropic-derived air pollution may affect major autoimmune conditions through direct and indirect mechanisms.

The pollutome-connectome axis: a putative mechanism to explain pollution effects on neurodegeneration

The study of pollutant effects is extremely important to address the epochal challenges we are facing, where world populations are increasingly moving from rural to urban centers, revolutionizing our world into an urban world. These transformations will exacerbate pollution, thus highlighting the necessity to unravel its effect on human health. Epidemiological studies have reported that pollution increases the risk of neurological diseases, with growing evidence on the risk of neurodegenerative disorders. Air pollution and water pollutants are the main chemicals driving this risk. These chemicals can promote inflammation, acting in synergy with genotype vulnerability. However, the biological underpinnings of this association are unknown. In this review, we focus on the link between pollution and brain network connectivity at the macro-scale level. We provide an updated overview of epidemiological findings and studies investigating brain network changes associated with pollution exposure, and discuss the mechanistic insights of pollution-induced brain changes through neural networks. We explain, in detail, the pollutome-connectome axis that might provide the functional substrate for pollution-induced processes leading to cognitive impairment and neurodegeneration. We describe this model within the framework of two pollutants, air pollution, a widely recognized threat, and polyfluoroalkyl substances, a large class of synthetic chemicals which are currently emerging as new neurotoxic source.

Air pollution nanoparticle and alpha-synuclein fibrils synergistically decrease glutamate receptor A1, depending upon nPM batch activity

Background

Epidemiological studies have variably linked air pollution to increased risk of Parkinson's disease (PD). However, there is little experimental evidence for this association. Alpha-synuclein (α-syn) propagation plays central roles in PD and glutamate receptor A1 (GluA1) is involved in memory and olfaction function.

Methods

Each mouse was exposed to one of three different batches of nano-particulate matter (nPM) (300 μg/m³, 5 h/d, 3 d/week), collected at different dates, 2017-2019, in the same urban site. After these experiments, these nPM batches were found to vary in activity. C57BL/6 female mice (3 mo) were injected with pre-formed murine α-synuclein fibrils (PFFs) (0.4 μg), which act as seeds for α-syn aggregation. Two exposure paradigms were used: in Paradigm 1, PFFs were injected into olfactory bulb (OB) prior to 4-week nPM (Batch 5b) exposure and in Paradigm 2, PFFs were injected at 4th week during 10-week nPM exposure (Batches 7 and 9). α-syn pSer129, microglia Iba1, inflammatory cytokines, and Gria1 expression were measured by immunohistochemistry or qPCR assays.

Results

As expected, α-syn pSer129 was detected in ipsilateral OB, anterior olfactory nucleus, amygdala and piriform cortex. One of the three batches of nPM caused a trend for elevated α-syn pSer129 in Paradigm 1, but two other batches showed no effect in Paradigm 2. However, the combination of nPM and PFF significantly decreased Gria1 mRNA in both the ipsi- and contra-lateral OB and frontal cortex for the most active two nPM batches. Neither nPM nor PFFs alone induced responses of microglia Iba1 and expression of Gria1 in the OB and cortex.

Conclusion

Exposures to ambient nPM had weak effect on α-syn propagation in the brain in current experimental paradigms; however, nPM and α-syn synergistically downregulated the expression of Gria1 in both OB and cortex.

Global Epidemiology of Movement Disorders: Rare or Underdiagnosed?

In this manuscript, we review the epidemiology of movement disorders including Parkinson's disease (PD), atypical parkinsonism, essential tremor, dystonia, functional movement disorders, tic disorders, chorea, and ataxias. We emphasize age-, sex-, and geography-based incidence and prevalence, as well as notable trends including the rising incidence and prevalence of PD. Given the growing global interest in refining clinical diagnostic skills in recognizing movement disorders, we highlight some key epidemiological findings that may be of interest to clinicians and health systems tasked with diagnosing and managing the health of patients with movement disorders.

The lived experience of stigma and parkinson's disease in Kenya: a public health challenge

BACKGROUND

As a disease characterised by non-motor and very visible motor symptoms, Parkinson's disease has been associated with multiple forms of stigma, while awareness about the disease globally remains low. The experience of stigma relating to Parkinson's disease from high-income nations is well-documented, while less is known about low- and middle-income countries (LMICs). Literature on stigma and disease from Africa and the Global South has described the added complexities people face resulting from structural violence, as well as perceptions about symptoms and disease associated with supernatural beliefs, which can have significant implications for access to healthcare and support. Stigma is a recognised barrier to health-seeking behaviour and a social determinant of population health.

METHODS

This study draws on qualitative data collected as part of a wider ethnographic study to explore the lived experience of Parkinson's disease in Kenya. Participants include 55 people diagnosed with Parkinson's and 23 caregivers. The paper draws on the Health Stigma and Discrimination Framework as a tool to understand stigma as a process.

RESULTS

Data from interviews identified the drivers and facilitators of stigma, including poor awareness of Parkinson's, lack of clinical capacity, supernatural beliefs, stereotypes, fear of contagion and blame. Participants reported their lived realities of stigma, and experiences of stigma practices, which had significant negative health and social outcomes, including social isolation and difficulty accessing treatment. Ultimately, stigma had a negative and corrosive effect on the health and wellbeing of patients.

CONCLUSION

This paper highlights the interplay of structural constraints and the negative consequences of stigma experienced by people living with Parkinson's in Kenya. The deep understanding of stigma made possible through this ethnographic research leads us to see stigma as a process, something that is embodied and enacted. Targeted and nuanced ways of tackling stigma are suggested, including educational and awareness campaigns, training, and the development of support groups. Importantly, the paper shows that awareness of, and advocacy for the recognition of, Parkinson's globally needs to improve. This recommendation is in line with the World Health Organization's Technical Brief on Parkinson disease, which responds to the growing public health challenge posed by Parkinson's.

Polycyclic aromatic hydrocarbons in urban particle matter exacerbate movement disorder after ischemic stroke via potentiation of neuroinflammation

BACKGROUND

A recent epidemiological study showed that air pollution is closely involved in the prognosis of ischemic stroke. We and others have reported that microglial activation in ischemic stroke plays an important role in neuronal damage. In this study, we investigated the effects of urban aerosol exposure on neuroinflammation and the prognosis of ischemic stroke using a mouse photothrombotic model.

RESULTS

When mice were intranasally exposed to CRM28, urban aerosols collected in Beijing, China, for 7 days, microglial activation was observed in the olfactory bulb and cerebral cortex. Mice exposed to CRM28 showed increased microglial activity and exacerbation of movement disorder after ischemic stroke induction. Administration of core particles stripped of attached chemicals from CRM28 by washing showed less microglial activation and suppression of movement disorder compared with CRM28-treated groups. CRM28 exposure did not affect the prognosis of ischemic stroke in null mice for aryl hydrocarbon receptor, a polycyclic aromatic hydrocarbon (PAH) receptor. Exposure to PM2.5 collected at Yokohama, Japan also exacerbated movement disorder after ischemic stroke.

CONCLUSION

Particle matter in the air is involved in neuroinflammation and aggravation of the prognosis of ischemic stroke; furthermore, PAHs in the particle matter could be responsible for the prognosis exacerbation.

How should future clinical trials be designed in the search for disease-modifying therapies for Parkinson's disease?

INTRODUCTION

Although there has been substantial progress in research and innovations in symptomatic treatments, similar success has not been achieved in disease-modifying therapy (DMT) for Parkinson's disease (PD). Considering the enormous motor, psychosocial and financial burden associated with PD, safe and effective DMT is of paramount importance.

AREAS COVERED

One of the reasons for the lack of progress in DMT for PD is poor or inappropriate design of clinical trials. In the first part of the article, the authors focus on the plausible reasons why the previous trials have failed and in the latter part, they provide their perspectives on future DMT trials.

EXPERT OPINION

There are several potential reasons why previous trials have failed, including broad clinical and etiopathogenic heterogeneity of PD, poor definition and documentation of target engagement, lack of appropriate biomarkers and outcome measures, and short duration of follow-up. To address these deficiencies, future trials may consider- (i) a more customized approach to select the most suitable participants and therapeutic approaches, (ii) explore combination therapies that would target multiple pathogenetic mechanisms, and (iii) moving beyond targeting only motor symptoms to also assessing non-motor features of PD in well-designed longitudinal studies.

Contribution of Solar Radiation and Pollution to Parkinson's Disease

Background. Parkinson's disease (PD) is believed to develop from epigenetic modulation of gene expression through environmental factors that accounts for up to 85% of all PD cases. The main objective of this study was to examine the association between PD onset and a cumulative exposure to potentially modifiable ambient exposures. Methods. The study population comprised 3343 incident PD cases and 31,324 non-PD controls in Southern Israel. The exposures were determined based on the monitoring stations and averaged per year. Their association with PD was modeled using a distributed lag non-linear model and presented as an effect of exposure to the 75th percentile as compared to the 50th percentile of each pollutant, accumulated over the span of 5 years prior to the PD. Results. We recorded an adverse effect of particulate matter of size ≤10 μm in diameter (PM₁₀) and solar radiation (SR) with odds ratio (OR) = 1.06 (95%CI: 1.02; 1.10) and 1.23 (95%CI: 1.08; 1.39), respectively. Ozone (O₃) was also adversely linked to PD, although with a borderline significance, OR: 1.12 (95%CI: 0.99; 1.25). Immigrants arriving in Israel after 1989 appeared to be more vulnerable to exposure to O₃ and SR. The dose response effect of SR, non-existent for Israeli-born (OR = 0.67, 95%CI: 0.40; 1.13), moderate for immigrants before 1989 (OR = 1.17, 95%CI: 0.98; 1.40) and relatively high for new immigrants (OR = 1.25, 95%CI: 1.25; 2.38) indicates an adaptation ability to SR. Conclusions. Our findings supported previous reports on adverse association of PD with exposure to PM₁₀ and O₃. Additionally, we revealed a link of Parkinson's Disease with SR that warrants an extensive analysis by research groups worldwide.

Air Pollution-Related Neurotoxicity Across the Life Span

Air pollution is a complex mixture of gases and particulate matter, with adsorbed organic and inorganic contaminants, to which exposure is lifelong. Epidemiological studies increasingly associate air pollution with multiple neurodevelopmental disorders and neurodegenerative diseases, findings supported by experimental animal models. This breadth of neurotoxicity across these central nervous system diseases and disorders likely reflects shared vulnerability of their inflammatory and oxidative stress-based mechanisms and a corresponding ability to produce brain metal dyshomeo-stasis. Future research to define the responsible contaminants of air pollution underlying this neurotoxicity is critical to understanding mechanisms of these diseases and disorders and protecting public health.