Air pollution and mortality in a University of Michigan amyotrophic lateral sclerosis cohort: a survival analysis.

Objectives To investigate the clinical and genetic factors influencing the survival of amyotrophic lateral sclerosis (ALS) patients in China. Methods Patients were enrolled in the study between December 2013 and December 2018. Clinical variables were recorded upon patient diagnosis. Causative genes related to ALS were screened by whole-exome sequencing and validated by Sanger sequencing. Each patient was followed up every 3–6 months until the endpoint (death or tracheotomy) or the last connection time on 31 December 2020. Propensity score matching analysis was performed to match the genetic and non-genetic ALS patients. The Kaplan–Meier method and multivariable Cox regression were performed for survival analysis. Results A total of 337 patients, including 32 with genetic ALS and 305 with non-genetic ALS, were enrolled in the study. Before matching, in univariate analysis, age of onset (P < 0.001), site of onset (P = 0.036), diagnostic delay (P < 0.001), ALSFRS-R score at diagnosis (P < 0.001), ΔALSFRS-R (P < 0.001), and causative mutations (P = 0.020) were significant prognostic factors. These factors remained statistically significant after multivariate analysis. After matching, in the multivariate analysis, age of onset (P = 0.003), site of onset (P = 0.014), diagnostic delay (P = 0.007), ALSFRS-R score at diagnosis (P = 0.010), ΔALSFRS-R (P = 0.007), and causative mutations (P = 0.003) were found to be significant prognostic factors. Conclusion Both clinical factors and genetic factors influenced survival in our ALS cohort. Clarifying of the underlying mechanisms is crucial for the development of future therapies.

IntroductionDespite decades of research, causes of ALS remain unclear. To evaluate recent hypotheses of plausible environmental factors, the aim of this study was to synthesize and appraise literature on the potential associations between the surrounding environment, including urbanization, air pollution and water pollution, and ALS.MethodsWe conducted a series (n = 3) of systematic reviews in PubMed and Scopus to identify epidemiological studies assessing relationships between urbanization, air pollution and water pollution with the development of ALS.ResultsThe combined search strategy led to the inclusion of 44 articles pertaining to at least one exposure of interest. Of the 25 included urbanization studies, four of nine studies on living in rural areas and three of seven studies on living in more highly urbanized/dense areas found positive associations to ALS. There were also three of five studies for exposure to electromagnetic fields and/or proximity to powerlines that found positive associations to ALS. Three case-control studies for each of diesel exhaust and nitrogen dioxide found positive associations with the development of ALS, with the latter showing a dose-response in one study. Three studies for each of high selenium content in drinking water and proximity to lakes prone to cyanobacterial blooms also found positive associations to ALS.ConclusionWhereas markers of air and water pollution appear as potential risk factors for ALS, results are mixed for the role of urbanization.

Air Pollution and Recent Onset Asthma

Recent studies have reported associations between particulate air pollution and daily mortality rates. Population-based, cross-sectional studies of metropolitan areas in the United States have also found associations between particulate air pollution and annual mortality rates, but these studies have been criticized, in part because they did not directly control for cigarette smoking and other health risks. In this prospective cohort study, we estimated the effects of air pollution on mortality, while controlling for individual risk factors. Survival analysis, including Cox proportional-hazards regression modeling, was conducted with data from a 14-to-16-year mortality follow-up of 8111 adults in six U.S. cities. Mortality rates were most strongly associated with cigarette smoking. After adjusting for smoking and other risk factors, we observed statistically significant and robust associations between air pollution and mortality. The adjusted mortality-rate ratio for the most polluted of the cities as compared with the least polluted was 1.26 (95 percent confidence interval, 1.08 to 1.47). Air pollution was positively associated with death from lung cancer and cardiopulmonary disease but not with death from other causes considered together. Mortality was most strongly associated with air pollution with fine particulates, including sulfates. Although the effects of other, unmeasured risk factors cannot be excluded with certainty, these results suggest that fine-particulate air pollution, or a more complex pollution mixture associated with fine particulate matter, contributes to excess mortality in certain U.S. cities.

Exposure to outdoor air pollution contributes to childhood asthma development, but many studies lack the geographic, racial and ethnic, and socioeconomic diversity to evaluate susceptibility by individual-level and community-level contextual factors. To examine early life exposure to fine particulate matter (PM2.5) and nitrogen oxide (NO2) air pollution and asthma risk by early and middle childhood, and whether individual and community-level characteristics modify associations between air pollution exposure and asthma. This cohort study included children enrolled in cohorts participating in the Children's Respiratory and Environmental Workgroup consortium. The birth cohorts were located throughout the US, recruited between 1987 and 2007, and followed up through age 11 years. The survival analysis was adjusted for mother's education, parental asthma, smoking during pregnancy, child's race and ethnicity, sex, neighborhood characteristics, and cohort. Statistical analysis was performed from February 2022 to December 2023. Early-life exposures to PM2.5 and NO2 according to participants' birth address. Caregiver report of physician-diagnosed asthma through early (age 4 years) and middle (age 11 years) childhood. Among 5279 children included, 1659 (31.4%) were Black, 835 (15.8%) were Hispanic, 2555 (48.4%) where White, and 229 (4.3%) were other race or ethnicity; 2721 (51.5%) were male and 2596 (49.2%) were female; 1305 children (24.7%) had asthma by 11 years of age and 954 (18.1%) had asthma by 4 years of age. Mean values of pollutants over the first 3 years of life were associated with asthma incidence. A 1 IQR increase in NO2 (6.1 μg/m3) was associated with increased asthma incidence among children younger than 5 years (HR, 1.25 [95% CI, 1.03-1.52]) and children younger than 11 years (HR, 1.22 [95% CI, 1.04-1.44]). A 1 IQR increase in PM2.5 (3.4 μg/m3) was associated with increased asthma incidence among children younger than 5 years (HR, 1.31 [95% CI, 1.04-1.66]) and children younger than 11 years (OR, 1.23 [95% CI, 1.01-1.50]). Associations of PM2.5 or NO2 with asthma were increased when mothers had less than a high school diploma, among Black children, in communities with fewer child opportunities, and in census tracts with higher percentage Black population and population density; for example, there was a significantly higher association between PM2.5 and asthma incidence by younger than 5 years of age in Black children (HR, 1.60 [95% CI, 1.15-2.22]) compared with White children (HR, 1.17 [95% CI, 0.90-1.52]). In this cohort study, early life air pollution was associated with increased asthma incidence by early and middle childhood, with higher risk among minoritized families living in urban communities characterized by fewer opportunities and resources and multiple environmental coexposures. Reducing asthma risk in the US requires air pollution regulation and reduction combined with greater environmental, educational, and health equity at the community level.

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 in aerodynamic diameter [fine particulate matter ()] 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 concentrations estimated by a prediction model at a 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 exposure. We allowed for nonlinear exposure–outcome relationships using penalized splines and accounted for potential confounders.Results:We found a positive nonlinear association that plateaued above (, 95% CI: 1.04, 1.14 for a increase from 8.1 to ). We also found a linear positive association (, 95% CI: 1.01, 1.09 per 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 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 concentrations may contribute to clinical aggravation of PD and ALS. Importantly, the average annual concentration in our study was , below the current American national standards, suggesting the standards may not adequately protect the aging population. https://doi.org/10.1289/EHP7425

Air pollutants have been reported to have a potential relationship with amyotrophic lateral sclerosis (ALS). The causality and underlying mechanism remained unknown despite several existing observational studies. We aimed to investigate the potential causality between air pollutants (PM2.5, NOX, and NO2) and the risk of ALS and elucidate the underlying mechanisms associated with this relationship. The data utilized in our study were obtained from publicly available genome-wide association study data sets, in which single nucleotide polymorphisms (SNPs) were employed as the instrumental variantswith three principles. Two-sample Mendelian randomization and transcriptome-wide association (TWAS) analyses were conducted to evaluate the effects of air pollutants on ALS and identify genes associated with both pollutants and ALS, followed by regulatory network prediction. We observed that exposure to a high level of PM2.5 (OR: 2.40 [95% CI: 1.26-4.57], p = 7.46E-3) and NOx (OR: 2.35 [95% CI: 1.32-4.17], p = 3.65E-3) genetically increased the incidence of ALS in MR analysis, while the effects of NO2 showed a similar trend but without sufficient significance. In the TWAS analysis, TMEM175 and USP35 turned out to be the genes shared between PM2.5 and ALS in the same direction. Higher exposure to PM2.5 and NOX might causally increase the risk of ALS. Avoiding exposure to air pollutants and air cleaning might be necessary for ALS prevention.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease with a complex etiology. Although a range of genetic and lifestyle factors have been implicated, the potential role of environmental airborne pollution exposure is uncertain. This study examined the association between long-term ambient exposure to air pollutants and the incidence of ALS in UK Biobank participants. This prospective cohort study was based on the UK Biobank participants aged 40-69 years. The analytical sample comprised participants free of ALS at baseline and had complete data on air pollution exposure. Long-term exposure (2006-2021) to nitrogen dioxide (NO2), nitrogen oxides (NOX), fine particulate matter (PM2.5; <2.5 µm), and coarse particulate matter (PM10; <10 µm) was assessed using data from the UK Department for Environment, Food and Rural Affairs at a spatial resolution of 1 × 1 km. To evaluate the association between these pollutants and ALS risk, we used multivariable time-varying Cox proportional hazards models. Several sensitivity analyses were conducted to assess the robustness of the results. We also examined for gene-environment interaction stratified by C9orf72 status and UNC13A genotype. Among the 501,308 participants with a mean age of 56.5 (SD 8.1) years at baseline, 272,764 (54.4%) were female. Over a median follow-up of 8.4 years, 687 individuals developed ALS. We did not observe any associations for any of the examined pollutants and ALS risk. Specifically, the hazard ratios per SD increment for PM10, PM2.5, NOX, and NO2 were 1.03 (95% CI 0.92-1.15), 1.00 (95% CI 0.88-1.14), 1.01 (95% CI 0.90-1.13), and 1.00 (95% CI 0.89-1.12), respectively. Individuals living in areas with the highest tertile of air pollutant exposure, compared with those in the lowest tertile, did not show a higher risk of ALS across any of the pollutants examined (p for trend >0.05). Restricted cubic spline analyses revealed no nonlinear associations between air pollution and ALS risk (all p for nonlinearity >0.05). These results remained robust in various subgroup and sensitivity analyses. No evidence of gene-environment interaction was found. In this large population-based study with high statistical power, ambient air pollution was not a risk factor for the development of ALS.

There is increasing evidence of an association between air pollution, particularly nitrogen dioxide (NO2), and the development of amyotrophic lateral sclerosis (ALS). However, investigation into sulfur dioxide (SO2) remains understudied. Also, empirical identification of confounding variables to adjust for in ALS environmental studies is largely absent. Thus, we created a multifactorial database, mapped hypothesized direct effects of air pollutants, and conducted a matched case-control study in New Brunswick, Canada to investigate the association between long-term exposure to various air pollutants and the development of ALS. Odds of ALS onset was significantly associated with increased SO2 exposure (OR=1.23; 95% CI: 1.02-1.47, per IQR increase of 0.14ppb) in adjusted direct effect models, but not associated with exposure to NO2 (OR=1.09; 95% CI: 0.87-1.41, per IQR increase of 2.79ppb), ozone (O3) (OR=0.99; 95% CI: 0.80-1.22, per IQR increase of 2.31ppb), fine particulate matter (PM2.5) (OR=0.99; 95% CI: 0.80-1.23, per IQR increase of 0.52μg/m3) or PM2.5(smoke) (OR=1.05; 95% CI: 0.83-1.35, per IQR increase of 0.68μg/m3). As for recency models, SO2 remained significantly associated with ALS in both 5-year (OR=1.21; 95% CI: 1.03-1.43) and 10-year prior to onset sensitivity models (OR=1.23; 95% CI: 1.02-1.47). Our findings support the association between long-term exposure to air pollutants, particularly SO2, and the development of ALS, supporting the need for improved air pollution control measures.

Background:Recently, there has been increasing evidence that exposure to air pollution is linked to neurodegenerative diseases, but little is known about the association with amyotrophic lateral sclerosis (ALS).Objectives:We investigated the association between long-term exposure to air pollution and risk of developing ALS.Methods:A population-based case–control study was conducted in Netherlands from 1 January 2006 to 1 January 2013. Data from 917 ALS patients and 2,662 controls were analyzed. Annual mean air pollution concentrations were assessed by land use regression (LUR) models developed as part of the European Study of Cohorts for Air Pollution Effects (ESCAPE). Exposure estimates included nitrogen oxides (, ), particulate matter (PM) with diameters of (), (), between and (), and absorbance. We performed conditional logistic regression analysis using two different multivariate models (model 1 adjusted for age, gender, education, smoking status, alcohol use, body mass index, and socioeconomic status; model 2 additionally adjusted for urbanization degree).Results:Risk of ALS was significantly increased for individuals in the upper exposure quartile of absorbance [; 95% confidence interval (CI): 1.27, 2.18], (; 95% CI: 1.32, 2.30), and concentrations (; 95% CI: 1.07, 1.77). These results, except for , remained significant after adjusting additionally for urbanization degree.Conclusions:Based on a large population-based case–control study, we report evidence for the association between long-term exposure to traffic-related air pollution and increased susceptibility to ALS. Our findings further support the necessity for regulatory public health interventions to combat air pollution levels and provide additional insight into the potential pathophysiology of ALS. https://doi.org/10.1289/EHP1115

BackgroundEvidence is limited on excess risks of cardiovascular diseases (CVDs) associated with ambient air pollution in diabetic populations. Survival analyses without considering the spatial structure and possible spatial correlations in health and environmental data may affect the precision of estimation of adverse environmental pollution effects. We assessed the association between air pollution and CVDs in type 2 diabetes through a Bayesian spatial survival approach.MethodsTaiwan’s national-level health claims and air pollution databases were utilized. Fine individual-level latitude and longitude were used to determine pollution exposure. The exponential spatial correlation between air pollution and CVDs was analyzed in our Bayesian model compared to traditional Weibull and Cox models.ResultsThere were 2072 diabetic patients included in analyses. PM2.5 and SO2 were significant CVD risk factors in our Bayesian model, but such associations were attenuated or underestimated in traditional models; adjusted hazard ratio (HR) and 95% credible interval (CrI) or confidence interval (CI) of CVDs for a 1 μg/m3 increase in the monthly PM2.5 concentration for our model, the Weibull and Cox models was 1.040 (1.004–1.073), 0.994 (0.984–1.004), and 0.994 (0.984–1.004), respectively. With a 1 ppb increase in the monthly SO2 concentration, adjusted HR (95% CrI or CI) was 1.886 (1.642–2.113), 1.092 (1.022–1.168), and 1.091 (1.021–1.166) for these models, respectively.ConclusionsAgainst traditional non-spatial analyses, our Bayesian spatial survival model enhances the assessment precision for environmental research with spatial survival data to reveal significant adverse cardiovascular effects of air pollution among vulnerable diabetic patients.Graphical abstract

Weight loss is a predictor of shorter survival in amyotrophic lateral sclerosis (ALS). We performed serial measures of body composition using Dual-energy X-ray Absorptiometry (DEXA) in ALS patients to explore its utility as a biomarker of disease progression. DEXA data were obtained from participants with ALS (enrollment, at 6- and 12- months follow ups) and Parkinson's disease (enrollment and at 4-month follow up) as a comparator group. Body mass index, total lean mass index, appendicular lean mass index, total fat mass index, and percentage body fat at enrollment were compared between the ALS and PD cohorts and age-matched normative data obtained from the National Health and Nutrition Examination Survey database. Estimated monthly changes of body composition measures in the ALS cohort were compared to those of the PD cohort and were correlated with disease progression measured by the Revised Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS-R). The ALS cohort (N = 20) had lower baseline total and appendicular lean mass indices compared to the PD cohort (N = 20) and general population. Loss in total and appendicular lean masses were found to be significantly associated with follow-up time. Low baseline percentage body fat (r = 0.72, p = 0.04), loss of percentage body fat (r = 0.81, p = 0.01), and total fat mass index (r = 0.73, p = 0.04) during follow up correlated significantly with monthly decline of ALSFRS-R scores in ALS cohort who had 2 or more follow-ups (N = 8). Measurement of body composition with DEXA might serve as a biomarker for rapid disease progression in ALS.

Background/objectiveWeight loss is a predictor of shorter survival in amyotrophic lateral sclerosis (ALS). We performed serial measures of body composition using Dual-energy X-ray Absorptiometry (DEXA) in ALS patients to explore its utility as a biomarker of disease progression.MethodsDEXA data were obtained from participants with ALS (enrollment, at 6- and 12- months follow ups) and Parkinson’s disease (enrollment and at 4-month follow up) as a comparator group. Body mass index, total lean mass index, appendicular lean mass index, total fat mass index, and percentage body fat at enrollment were compared between the ALS and PD cohorts and age-matched normative data obtained from the National Health and Nutrition Examination Survey database. Estimated monthly changes of body composition measures in the ALS cohort were compared to those of the PD cohort and were correlated with disease progression measured by the Revised Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS-R).ResultsThe ALS cohort (N = 20) had lower baseline total and appendicular lean mass indices compared to the PD cohort (N = 20) and general population. Loss in total and appendicular lean masses were found to be significantly associated with follow-up time. Low baseline percentage body fat (r = 0.72, p = 0.04), loss of percentage body fat (r = 0.81, p = 0.01), and total fat mass index (r = 0.73, p = 0.04) during follow up correlated significantly with monthly decline of ALSFRS-R scores in ALS cohort who had 2 or more follow-ups (N = 8).ConclusionMeasurement of body composition with DEXA might serve as a biomarker for rapid disease progression in ALS.

Air pollution and disease progression in a University of Michigan amyotrophic lateral sclerosis cohort.

Airborne lead and polychlorinated biphenyls (PCBs) are associated with amyotrophic lateral sclerosis (ALS) risk in the U.S