Additive effects of 10-year exposures to PM2.5 and NO2 and primary cancer incidence in American older adults.

Epidemiologic evidence on the relationships between air pollution and the risks of primary cancers other than lung cancer remained largely lacking. We aimed to examine associations of 10-year exposures to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) with risks of breast, prostate, colorectal, and endometrial cancers. Methods: For each cancer, we constructed a separate cohort among the national Medicare beneficiaries during 2000 to 2016. We simultaneously examined the additive associations of six exposures, namely, moving average exposures to PM2.5 and NO2 over the year of diagnosis and previous 2 years, previous 3 to 5 years, and previous 6 to 10 years, with the risk of first cancer diagnosis after 10 years of follow-up, during which there was no cancer diagnosis. Results: The cohorts included 2.2 to 6.5 million subjects for different cancers. Exposures to PM2.5 and NO2 were associated with increased risks of colorectal and prostate cancers but were not associated with endometrial cancer risk. NO2 was associated with a decreased risk of breast cancer, while the association for PM2.5 remained inconclusive. At exposure levels below the newly updated World Health Organization Air Quality Guideline, we observed substantially larger associations between most exposures and the risks of all cancers, which were translated to hundreds to thousands new cancer cases per year within the cohort per unit increase in each exposure. Conclusions: These findings suggested substantial cancer burden was associated with exposures to PM2.5 and NO2, emphasizing the urgent need for strategies to mitigate air pollution levels.

Incident dementia and long-term exposure to constituents of fine particle air pollution: A national cohort study in the United States.

Growing evidence suggests that fine particulate matter (PM2.5) likely increases the risks of dementia, yet little is known about the relative contributions of different constituents. Here, we conducted a nationwide population-based cohort study (2000 to 2017) by integrating the Medicare Chronic Conditions Warehouse database and two independently sourced datasets of high-resolution PM2.5 major chemical composition, including black carbon (BC), organic matter (OM), nitrate (NO3-), sulfate (SO42-), ammonium (NH4+), and soil dust (DUST). To investigate the impact of long-term exposure to PM2.5 constituents on incident all-cause dementia and Alzheimer's disease (AD), hazard ratios for dementia and AD were estimated using Cox proportional hazards models, and penalized splines were used to evaluate potential nonlinear concentration-response (C-R) relationships. Results using two exposure datasets consistently indicated higher rates of incident dementia and AD for an increased exposure to PM2.5 and its major constituents. An interquartile range increase in PM2.5 mass was associated with a 6 to 7% increase in dementia incidence and a 9% increase in AD incidence. For different PM2.5 constituents, associations remained significant for BC, OM, SO42-, and NH4+ for both end points (even after adjustments of other constituents), among which BC and SO42- showed the strongest associations. All constituents had largely linear C-R relationships in the low exposure range, but most tailed off at higher exposure concentrations. Our findings suggest that long-term exposure to PM2.5 is significantly associated with higher rates of incident dementia and AD and that SO42-, BC, and OM related to traffic and fossil fuel combustion might drive the observed associations.

Associations between long-term air pollution exposure and the incidence of cardiovascular diseases among American older adults.

BACKGROUND & AIM: Numerous studies have linked air pollution with cardiovascular diseases. Fewer studies examined the associations at low concentration levels or assessed potential modifiers. Some investigations only examined hospitalizations, which can miss incident cases. This study aims to address these gaps through a nationwide cohort study of Medicare enrollees. METHODS: Our study cohort comprise all Medicare enrollees (≥65 years old) continuously enrolled in the fee-for-service program and both Medicare part A and B across the contiguous U.S. from 2000 to 2016. We examined the associations of population-weighted ZIP code-level annual average PM2.5, NO2, and warm-season O3 (May-October), with the first diagnoses of atrial fibrillation (AF), congestive heart failure (CHF), and stroke. We fit multi-pollutant Cox proportional hazards models adjusted for individual demographic characteristics and area-level covariates. We further examined these associations at low pollutant concentration levels and the potential effect modifications by race/ethnicity and comorbidities (diabetes, hypertension, hyperlipidemia). RESULTS: Elevated PM2.5 and NO2 levels were associated with increased incidence of AF, CHF, and stroke. For each 1 µg/m3 increase in annual PM2.5, hazard ratios (HRs) were 1.0059 (95%CI: 1.0054-1.0064), 1.0260 (95%CI: 1.0256-1.0264), and 1.0279 (95%CI: 1.0274-1.0284), respectively. For each1 ppb increase in annual NO2, HRs are 1.0057 (95%CI: 1.0056-1.0059), 1.0112 (95%CI: 1.0110-1.0113), and 1.0095 (95%CI: 1.0093-1.0096), respectively. For warm-season O3, each 1 ppb increase was associated with increased incidence of CHF (HR=1.0035, 95%CI: 1.0033-1.0037) and stroke (HR=1.0026, 95%CI: 1.0023-1.0028). Larger magnitudes of HRs were observed when restricted to pollutants levels lower than NAAQS standards. Generally higher risks were observed for Black people and diabetics. CONCLUSIONS: Long-term exposure to PM2.5, NO2, and warm-season O3 were associated with increased incidence of cardiovascular diseases, even at low pollutant concentration levels. Black people and people with diabetes were found to be vulnerable populations.

Perceived healthcare discrimination and well-being among older adults in the United States and Brazil.

Despite well-documented evidence illustrating the relationship between discrimination and health, less is known about the influence of unfair treatment when receiving medical care. Moreover, our current knowledge of cross-national and racial variations in healthcare discrimination is limited in aging populations. This article addresses these gaps using two harmonized data sets of aging populations to clarify the relationship between healthcare discrimination and health in the United States and Brazil. We use nationally representative, harmonized data from the Health and Retirement Study in the United States and the Brazilian Longitudinal Study of Aging to examine and compare perceived discrimination in the healthcare setting and its relationship to self-rated health, depression diagnosis, and depressive symptoms across national contexts. Using Poisson regression models and population attributable risk percent estimates, we found that aging adults reporting healthcare discrimination were at higher risk of poor self-rated health, diagnosed depression, and depressive symptoms. Our results also suggest that reducing perceived healthcare discrimination may contribute to improved self-rated health and mental well-being in later life across racialized societies. In two comparative settings, we highlight the differential impact of healthcare discrimination on self-rated health and depression. We describe the implications of our study's findings for national public health strategies focused on eliminating discrimination in the healthcare setting, particularly among aging countries.

Long-term air pollution exposure and incident stroke in American older adults: A national cohort study.

Aims: Stroke is a leading cause of death and disability for Americans, and growing evidence suggests that air pollution may play an important role. To facilitate pollution control efforts, the National Academy of Sciences and the World Health Organization have prioritized determining which air pollutants are most toxic. However, evidence is limited for the simultaneous effects of multiple air pollutants on stroke. Methods and results: We constructed a nationwide population-based cohort study, using the Medicare Chronic Conditions Warehouse (2000-2017) and high-resolution air pollution data, to investigate the impact of long-term exposure to ambient PM2.5, NO2, and ground-level O3 on incident stroke. Hazard ratios (HR) for stroke incidence were estimated using single-, bi-, and tri-pollutant Cox proportional hazards models. We identified ~2.2 million incident stroke cases among 17,443,900 fee-for-service Medicare beneficiaries. Per interquartile range (IQR) increase in the annual average PM2.5 (3.7 µg/m3), NO2 (12.4 ppb), and warm-season O3 (6.5 ppb) one-year prior to diagnosis, the HRs were 1.022 (95% CI: 1.017-1.028), 1.060 (95% CI: 1.054-1.065), and 1.021 (95% CI: 1.017-1.024), respectively, from the tri-pollutant model. There was strong evidence of linearity in concentration-response relationships for all three air pollutants in single-pollutant models. This linear relationship remained robust for NO2 and O3 in tri-pollutant models while the effect of PM2.5 attenuated at the lower end of concentrations. Conclusion: Using a large nationwide cohort, our study suggests that long-term exposure to PM2.5, NO2, and O3 may independently increase the risk of stroke among the US elderly, among which traffic-related air pollution plays a particularly crucial role.

Integrating Hi-C and FISH data for modeling of the 3D organization of chromosomes.

The new advances in various experimental techniques that provide complementary information about the spatial conformations of chromosomes have inspired researchers to develop computational methods to fully exploit the merits of individual data sources and combine them to improve the modeling of chromosome structure. Here we propose GEM-FISH, a method for reconstructing the 3D models of chromosomes through systematically integrating both Hi-C and FISH data with the prior biophysical knowledge of a polymer model. Comprehensive tests on a set of chromosomes, for which both Hi-C and FISH data are available, demonstrate that GEM-FISH can outperform previous chromosome structure modeling methods and accurately capture the higher order spatial features of chromosome conformations. Moreover, our reconstructed 3D models of chromosomes revealed interesting patterns of spatial distributions of super-enhancers which can provide useful insights into understanding the functional roles of these super-enhancers in gene regulation.

Developing novel methods to image and visualize 3D genomes.

To investigate three-dimensional (3D) genome organization in prokaryotic and eukaryotic cells, three main strategies are employed, namely nuclear proximity ligation-based methods, imaging tools (such as fluorescence in situ hybridization (FISH) and its derivatives), and computational/visualization methods. Proximity ligation-based methods are based on digestion and re-ligation of physically proximal cross-linked chromatin fragments accompanied by massively parallel DNA sequencing to measure the relative spatial proximity between genomic loci. Imaging tools enable direct visualization and quantification of spatial distances between genomic loci, and advanced implementation of (super-resolution) microscopy helps to significantly improve the resolution of images. Computational methods are used to map global 3D genome structures at various scales driven by experimental data, and visualization methods are used to visualize genome 3D structures in virtual 3D space-based on algorithms. In this review, we focus on the introduction of novel imaging and visualization methods to study 3D genomes. First, we introduce the progress made recently in 3D genome imaging in both fixed cell and live cells based on long-probe labeling, short-probe labeling, RNA FISH, and the CRISPR system. As the fluorescence-capturing capability of a particular microscope is very important for the sensitivity of bioimaging experiments, we also introduce two novel super-resolution microscopy methods, SDOM and low-power super-resolution STED, which have potential for time-lapse super-resolution live-cell imaging of chromatin. Finally, we review some software tools developed recently to visualize proximity ligation-based data. The imaging and visualization methods are complementary to each other, and all three strategies are not mutually exclusive. These methods provide powerful tools to explore the mechanisms of gene regulation and transcription in cell nuclei.

Super-resolution imaging of a 2.5 kb non-repetitive DNA in situ in the nuclear genome using molecular beacon probes.

High-resolution visualization of short non-repetitive DNA in situ in the nuclear genome is essential for studying looping interactions and chromatin organization in single cells. Recent advances in fluorescence in situ hybridization (FISH) using Oligopaint probes have enabled super-resolution imaging of genomic domains with a resolution limit of 4.9 kb. To target shorter elements, we developed a simple FISH method that uses molecular beacon (MB) probes to facilitate the probe-target binding, while minimizing non-specific fluorescence. We used three-dimensional stochastic optical reconstruction microscopy (3D-STORM) with optimized imaging conditions to efficiently distinguish sparsely distributed Alexa-647 from background cellular autofluorescence. Utilizing 3D-STORM and only 29-34 individual MB probes, we observed 3D fine-scale nanostructures of 2.5 kb integrated or endogenous unique DNA in situ in human or mouse genome, respectively. We demonstrated our MB-based FISH method was capable of visualizing the so far shortest non-repetitive genomic sequence in 3D at super-resolution.