Exposure to various ambient air pollutants increases the risk of venous thromboembolism: A cohort study in UK Biobank

Association of ambient air pollution with hospital admissions for major osteoarthritis diseases: A national case-crossover study in China

OBJECTIVES

To investigate the acute effects of short-term exposure to ambient air pollution on the risk of hospital admissions for osteoarthritis (OA) and its major subtypes.

METHODS

Hospital admission data on OA and its major subtypes were sourced from two major urban medical insurance systems in China, covering the period from 2013 to 2017. A two-stage, time-stratified case-crossover design was used to investigate the acute effects of short-term exposure to ambient air pollutants on hospital admissions for OA across 278 Chinese cities with available hospital admission data over 50 cases. The conditional logistic regression model was utilized to assess city-specific associations, which were subsequently pooled by employing a random-effects model.

RESULTS

A total of 1,404,095 OA-related hospital admissions were included. At the main time windows, per interquartile range increases in PM2.5 (particulate matter with an aerodynamic diameter of ≤ 2.5 μm), PM10 (particulate matter with an aerodynamic diameter of ≤ 10 μm), NO2 (nitrogen dioxide), SO2 (sulfur dioxide), O3 (ozone), and CO (carbon monoxide) were associated with significant increases in OA-related admissions by 0.70 % (95 % CI: 0.12 %, 1.28 %), 1.08 % (95 % CI: 0.47 %, 1.69 %), 4.50 % (95 % CI: 3.36 %, 5.65 %), 2.75 % (95 % CI: 1.79 %, 3.72 %), 1.33 % (95 % CI: 0.57 %, 2.10 %) and 1.77 % (95 % CI: 0.76 %, 2.79 %), respectively. Short-term exposures to ambient air pollutants were also associated with increased hospital admissions for major OA subtypes, especially gonarthrosis. The attributable fractions of OA admissions ranged from 0.87 % for PM2.5 to 6.22 % for NO2.

CONCLUSIONS

Short-term exposure to ambient air pollution is significantly associated with an increased risk and burden of OA admissions.

Genetic evidence for the causal effects of air pollution on the risk of respiratory diseases

BACKGROUND

Epidemiological studies have consistently demonstrated a robust association between long-term exposure to air pollutants and respiratory diseases. However, establishing causal relationships remains challenging due to residual confounding in observational studies. In this study, Mendelian randomization (MR) analysis was used to explore the causal and epigenetic relationships between various air pollutants and common respiratory diseases.

METHODS

We utilized a two-sample Mendelian randomization (TSMR) approach to explore the impact of PM2.5, PM2.5-10, PM10, NO2, and NOX on the incidence of nine respiratory diseases using data from large-scale European GWAS datasets (N = 423,796-456,380 for exposures; N = 162,962-486,484 for outcomes). The primary analytical method was inverse variance weighting (IVW), which explored the exposure-outcome relationship using single nucleotide polymorphisms (SNPs) associated with air pollution. Sensitivity analyses, including MR-Egger regression and leave-one-out analyses, were employed to ensure result consistency. Multivariate MR (MVMR) was performed to adjust for potential smoking-related confounders, such as cigarettes per day, household smoking, exposure to tobacco smoke at home, ever smoked, second-hand smoke, smoking initiation, and age at smoking initiation, as well as the independent effects of each air pollutant. Additionally, methylation and enrichment analyses were conducted to further elucidate the potential effects of air pollution on respiratory diseases.

RESULTS

TSMR analysis revealed that exposure to PM2.5 increased the risk of early-onset chronic obstructive pulmonary disease (COPD), pneumonia, pulmonary embolism and lung cancer. PM2.5-10 exposure was associated with an increased risk of lung cancer, while PM10 exposure increased the risk of pneumonia and bronchiectasis. NO2 exposure was associated with increased risks of lung cancer and adult asthma. Importantly, these associations remained robust even after controlling for potential tobacco-related confounders in the MVMR analyses. In the MVMR analysis adjusting for other pollutants, significant associations persisted between PM2.5 and early-onset COPD, and between PM10 and pneumonia. Genetic co-localization analyses confirmed that methylation of PM2.5-associated CpG loci (cg11386376 near c1orf175, cg11846064 near rfx2, cg18612040 near rptor, and cg19765378 near c7orf50) was associated with an increased risk of early-onset COPD. Finally, SNPs significantly associated with exposure and outcome were selected for enrichment analysis.

CONCLUSIONS

Our findings suggest that exposure to air pollutants may play a causal role in the development of respiratory diseases, with a potential role of epigenomic modifications emphasized. Strengthening comprehensive air pollution regulations by relevant authorities could potentially mitigate the risk of these diseases.

Air pollution and venous thromboembolism: current knowledge and future perspectives

Air pollution, comprising a variable mixture of gaseous and solid particulate material, represents a serious, unmet, global health issue. The Global Burden of Disease study reported that 12% of all deaths occurring in 2019 were related to ambient air pollution, with particulate matter often considered to be the leading cause of harm. As of 2024, over 90% of the world's population are exposed to excessive amounts of particulate matter, based on WHO maximum exposure level guidelines. A substantial body of evidence supports a link between air pollution and cardiovascular disease, with around half of ambient pollution-related deaths thought to be secondary to cardiovascular causes. A possible association between particulate matter and venous thromboembolism has been less clear, but in the past decade, several studies have added to the available literature. In this Review, we discuss the current epidemiological evidence linking air pollution to the development of venous thrombotic events. We consider mechanisms promoting a thromboinflammatory phenotype in these individuals, including platelet dysfunction, dysregulated fibrinolysis, and enhanced thrombin generation. Given the relevance to global health, we also discuss possible strategies required to mitigate the impact of air pollution on human health worldwide.

Epidemiology of pulmonary embolism in China, 2021: a nationwide hospital-based study

Background

Pulmonary embolism (PE) as a preventable and potentially fatal noncommunicable disease was believed to have a lower incidence in Asian populations compared to Western populations. However, the incidence and mortality rates of PE in China and the impact of venous thromboembolism (VTE) prevention system constructions on PE still lack nationwide evidence.

Methods

For this nationwide hospital-based observational study, we used data from the National Hospital Quality Monitoring System (HQMS) and public database in China. We estimated the incidence and in-hospital mortality rates of PE by age group, sex, and regions of geographical and socioeconomic level. VTE prevention and management system constructions were quantified by geographical density. We then calculated the incidence and mortality rates in different conditions of VTE prevention and management system construction.

Findings

During the 12 months period between January and December 2021, a total number of 200,112 PE patients and 14,123 deaths were recorded from 5101 hospitals in the HQMS database. The incidence of PE was 14.19 (200,112, 95% CI 14.13-14.26) per 100,000 population and the mortality rate was 1.00 (95% CI 0.99-1.02) per 100,000 population. The incidence of PE was higher in male patients (14.43 per 100,000 population) than in female patients (13.95 per 100,000 population). Disparities of incidence and mortality rates were shown within age groups and geographical regions. The incidence and mortality rates of PE showed decreasing trend with increasing geographical density of VTE-related facilities and VTE prevention system developments.

Interpretation

China had a substantially large number of PE patients. The incidence and mortality rates of PE showed disparities in terms of sex, age, and geography. The incidence and mortality rates of PE decrease across regions with increasing levels of socioeconomic development, potentially influenced by the existing VTE prevention and management systems. Optimizing the health policies and healthcare investment in VTE prevention may help reduce the disease burden of PE.

Funding

CAMS Innovation Fund for Medical Sciences (CIFMS) (2023-I2M-A-014); National High Level Hospital Clinical Research Funding (2022-NHLHCRF-LX-01-0108); National Key Research and Development Program of China (2023YFC2507200); Discipline-Innovation and Talent-Introduction Program for Colleges and Universities (111 Plan, B23038).

Kidney function mediates the effects of four per-and polyfluoroalkyl substances (PFAS) on atherosclerotic cardiovascular disease

BACKGROUND

PFAS pose a significant threat to cardiovascular health and increase the risk of atherosclerotic cardiovascular disease (ASCVD). However, there is limited research evidence regarding the mechanisms by which PFAS affect the risk of ASCVD and the exposure-risk (E-R) relationship. The effect of kidney function in the relationship between PFAS and ASCVD risk has not been adequately validated.

OBJECTIVE

This study aims to explore the mechanisms by which four PFAS (Perfluorooctanoic acid (PFOA), Perfluorooctanesulfonic acid (PFOS), Perfluorohexanesulfonic acid (PFHS), and Perfluorononanoic acid (PFNA)) affect the risk of ASCVD and to verify and discuss the mediating effect of kidney function in this impact.

METHODS

This study utilizes data from 14,607 participants in the NHANES 2005-2018 to conduct a cross-sectional study. Initially, Generalized Linear Model (GLM) and Restricted Cubic Splines models are used to assess the impact of four PFAS on ASCVD risk and the E-R relationship. Subsequently, the Weighted Quantile Sum regression (WQS) model is used to evaluate the relationship between mixed four PFAS exposure and ASCVD risk. Finally, Directed Acyclic Graphs (DAG) and causal mediation models are used to confirm and analyze whether the decline in kidney function mediates the impact of four PFAS on ASCVD risk.

RESULTS

The results from GLM and WQS models indicate that both singular and mixed four PFAS exposures are associated with an increased risk of ASCVD. The E-R curves between four PFAS singular and mixed exposures and ASCVD risk are all characterized by nonlinearity. The results from DAG and causal mediation models clearly indicate that the decline in kidney function plays a significant mediating role in the relationship between four PFAS and ASCVD risk.

CONCLUSION

Exposure levels of four PFAS do not significantly increase the risk of ASCVD unless they reach a certain threshold, and the decline in kidney function exerts a significant mediating effect in the relationship between four PFAS exposure and ASCVD risk.

Exposure to air pollution increases susceptibility to ulcerative colitis through epigenetic alterations in CXCR2 and MHC class III region

BACKGROUND

This study aims to confirm the associations of air pollution with ulcerative colitis (UC) and Crohn's disease (CD); to explore interactions with genetics and lifestyle; and to characterize potential epigenetic mechanisms.

METHODS

We identified over 450,000 individuals from the UK Biobank and investigated the relationship between air pollution and incident inflammatory bowel disease (IBD). Cox regression was utilized to calculate hazard ratios (HRs), while also exploring potential interactions with genetics and lifestyle factors. Additionally, we conducted epigenetic Mendelian randomization (MR) analyses to examine the association between air pollution-related DNA methylation and UC. Finally, our findings were validated through genome-wide DNA methylation analysis of UC, as well as co-localization and gene expression analyses.

FINDINGS

Higher exposures to NOx (HR = 1.20, 95% CI 1.05-1.38), NO2 (HR = 1.19, 95% CI = 1.03-1.36), PM2.5 (HR = 1.19, 95% CI = 1.05-1.36) and combined air pollution score (HR = 1.26, 95% CI = 1.11-1.45) were associated with incident UC but not CD. Interactions with genetic risk score and lifestyle were observed. In MR analysis, we found five and 22 methylated CpG sites related to PM2.5 and NO2 exposure to be significantly associated with UC. DNA methylation alterations at CXCR2 and sites within the MHC class III region, were validated in genome-wide DNA methylation analysis, co-localization analysis and analysis of colonic tissue.

INTERPRETATION

We report a potential causal association between air pollution and UC, modified by lifestyle and genetic influences. Biological pathways implicated include epigenetic alterations in key genetic loci, including CXCR2 and susceptible loci within MHC class III region.

FUNDING

Xue Li was supported by the Natural Science Fund for Distinguished Young Scholars of Zhejiang Province (LR22H260001) and the National Nature Science Foundation of China (No. 82204019). ET was supported by the CRUK Career Development Fellowship (C31250/A22804) and the Research Foundation Flanders (FWO). JW was supported by Belgium by a PhD Fellowship strategic basic research (SB) grant (1S06023N). JKN was supported by the National Science Center, Poland (No. 2020/39/D/NZ5/02720). The IBD Character was supported by the European Union's Seventh Framework Programme [FP7] grant IBD Character (No. 2858546).

The association between air pollutant exposure and cerebral small vessel disease imaging markers with modifying effects of PRS-defined genetic susceptibility

Studies have highlighted a possible link between air pollution and cerebral small vessel disease (CSVD) imaging markers. However, the exact association and effects of polygenic risk score (PRS) defined genetic susceptibility remains unclear. This cross-sectional study used data from the UK Biobank. Participants aged 40-69 years were recruited between the year 2006 and 2010. The annual average concentrations of NOX, NO2, PM2.5, PM2.5-10, PM2.5 absorbance, and PM10, were estimated, and joint exposure to multiple air pollutants was reflected in the air pollution index (APEX). Air pollutant exposure was classified into the low (T1), intermediate (T2), and high (T3) tertiles. Three CSVD markers were used: white matter hyper-intensity (WMH), mean diffusivity (MD), and fractional anisotropy (FA). The first principal components of the MD and FA measures in the 48 white matter tracts were analysed. The sample consisted of 44,470 participants from the UK Biobank. The median (T1-T3) concentrations of pollutants were as follows: NO2, 25.5 (22.4-28.7) μg/m3; NOx, 41.3 (36.2-46.7) μg/m3; PM10, 15.9 (15.4-16.4) μg/m3; PM2.5, 9.9 (9.5-10.3) μg/m3; PM2.5 absorbance, 1.1 (1.0-1.2) per metre; and PM2.5-10, 6.1 (5.9-6.3) μg/m3. Compared with the low group, the high group's APEX, NOX, and PM2.5 levels were associated with increased WMH volumes, and the estimates (95 %CI) were 0.024 (0.003, 0.044), 0.030 (0.010, 0.050), and 0.032 (0.011, 0.053), respectively, after adjusting for potential confounders. APEX, PM10, PM2.5 absorbance, and PM2.5-10 exposure in the high group were associated with increased FA values compared to that in the low group. Sex-specific analyses revealed associations only in females. Regarding the combined associations of air pollutant exposure and PRS-defined genetic susceptibility with CSVD markers, the associations of NO2, NOX, PM2.5, and PM2.5-10 with WMH were more profound in females with low PRS-defined genetic susceptibility, and the associations of PM10, PM2.5, and PM2.5 absorbance with FA were more profound in females with higher PRS-defined genetic susceptibility. Our study demonstrated that air pollutant exposure may be associated with CSVD imaging markers, with females being more susceptible, and that PRS-defined genetic susceptibility may modify the associations of air pollutants.

Predicting particulate matter, nitrogen dioxide, and ozone across Great Britain with high spatiotemporal resolution based on random forest models

In Great Britain, limited studies have employed machine learning methods to predict air pollution especially ozone (O3) with high spatiotemporal resolution. This study aimed to address this gap by developing random forest models for four key pollutants (fine and inhalable particulate matter [PM2.5 and PM10], nitrogen dioxide [NO2] and O3) by integrating multiple-source predictors at a daily level and 1-km resolution. The out-of-bag R2 (root mean squared error, RMSE) between predictions from models and measurements from monitoring stations in 2006-2013 was 0.85 (3.63 μg/m3) for PM2.5, 0.77 (6.00 μg/m3) for PM10, 0.85 (9.71 μg/m3) for NO2, and 0.85 (9.39 μg/m3) for maximum daily 8-h average (MDA8) O3 at daily level, and the predicting accuracy was higher at monthly and annual level. The high-resolution predictions captured characterized spatiotemporal patterns of the four pollutants. Higher concentrations of PM2.5, PM10, and NO2 were distributed in densely populated southern regions of Great Britain while O3 showed an inverse spatial pattern in general, which could not be fully depicted by monitoring stations. Therefore, predictions produced in this study could improve exposure assessment with less exposure misclassification and flexible exposure windows for future epidemiological studies to investigate the impact of air pollution across Great Britain.

Impact of ambient air pollution on colorectal cancer risk and survival: insights from a prospective cohort and epigenetic Mendelian randomization study

BACKGROUND

This study investigates the associations between air pollution and colorectal cancer (CRC) risk and survival from an epigenomic perspective.

METHODS

Using a newly developed Air Pollutants Exposure Score (APES), we utilized a prospective cohort study (UK Biobank) to investigate the associations of individual and combined air pollution exposures with CRC incidence and survival, followed by an up-to-date systematic review with meta-analysis to verify the associations. In epigenetic two-sample Mendelian randomization analyses, we examine the associations between genetically predicted DNA methylation related to air pollution and CRC risk. Further genetic colocalization and gene-environment interaction analyses provided different insights to disentangle pathogenic effects of air pollution via epigenetic modification.

FINDINGS

During a median 12.97-year follow-up, 5767 incident CRC cases among 428,632 participants free of baseline CRC and 533 deaths in 2401 patients with CRC were documented in the UK Biobank. A higher APES score was associated with an increased CRC risk (HR, 1.03, 95% CI = 1.01-1.06; P = 0.016) and poorer survival (HR, 1.13, 95% CI = 1.03-1.23; P = 0.010), particularly among participants with insufficient physical activity and ever smokers (Pinteraction > 0.05). A subsequent meta-analysis of seven observational studies, including UK Biobank data, corroborated the association between PM2.5 exposure (per 10 μg/m3 increment) and elevated CRC risk (RR,1.42, 95% CI = 1.12-1.79; P = 0.004; I2 = 90.8%). Genetically predicted methylation at PM2.5-related CpG site cg13835894 near TMBIM1/PNKD and cg16235962 near CXCR5, and NO2-related cg16947394 near TMEM110 were associated with an increased CRC risk. Gene-environment interaction analysis confirmed the epigenetic modification of aforementioned CpG sites with CRC risk and survival.

INTERPRETATION

Our study suggests the association between air pollution and CRC incidence and survival, underscoring the possible modifying roles of epigenomic factors. Methylation may partly mediate pathogenic effects of air pollution on CRC, with annotation to epigenetic alterations in protein-coding genes TMBIM1/PNKD, CXCR5 and TMEM110.

FUNDING

Xue Li is supported by the Natural Science Fund for Distinguished Young Scholars of Zhejiang Province (LR22H260001), the National Nature Science Foundation of China (No. 82204019) and Healthy Zhejiang One Million People Cohort (K-20230085). ET is supported by a Cancer Research UK Career Development Fellowship (C31250/A22804). MGD is supported by the MRC Human Genetics Unit Centre Grant (U127527198).

Long-term exposure to air pollutants and new-onset migraine: A large prospective cohort study

BACKGROUNDS

Short-term exposure to air pollutants increases the risk of migraine, but the long-term impacts of exposure to multiple pollutants on migraine have not been established. The aim of this large prospective cohort study was to explore these links.

METHODS

A total of 458,664 participants who were free of migraine at baseline from the UK Biobank were studied. Cox proportional hazards models were used to estimate the risk of new-onset migraine from combined long-term exposure to four pollutants, quantified as an air pollution score using principal component analysis.

RESULTS

During a median (IQR) follow-up of 12.5 (11.8, 13.2) years, a total of 5417 new-onset migraine cases were documented. Long-term exposure to multiple air pollutants was associated with an increased risk of new-onset migraine, as indicated by an increased in the SDs of PM2.5 (hazard ratio (HR): 1.04, 95% CI: 1.01-1.06, P = 0.009), PM10 (HR: 1.07, 95% CI: 1.04-1.10, P < 0.001), NO2 (HR: 1.10, 95% CI: 1.07-1.13, P < 0.001) and NOx (HR: 1.04, 95% CI: 1.01-1.07, P = 0.005) in the main model. The air pollution score showed a doseresponse association with an increased risk of new-onset migraine. Similarly, compared with those of the lowest tertile, the HRs (95% CI) of new-onset migraine were 1.11 (95% CI: 1.04-1.19, P = 0.002) and 1.17 (95% CI: 1.09-1.26, P < 0.001) in tertiles 2 and 3, respectively, according to the main model (P trend < 0.001).

CONCLUSION

Long-term individual and joint exposure to multiple air pollutants is associated with an increased risk of new-onset migraine.

Duration-sensitive association between air pollution exposure and changes in cardiometabolic biomarkers: Evidence from a predominantly African American cohort

BACKGROUND

Ambient fine particulate matter (PM2.5) exposure has been related to cardiometabolic diseases, but the underlying biological pathways remain unclear at the population level.

OBJECTIVE

To investigate the effect of PM2.5 exposure on changes in multiple cardiometabolic biomarkers across different exposure durations.

METHOD

Data from a prospective cohort study were analyzed. Ten cardiometabolic biomarkers were measured, including ghrelin, resistin, leptin, C-peptide, creatine kinase myocardial band (CK-MB), monocyte chemoattractant protein-1 (MCP-1), tumor necrosis factor alpha (TNF-alpha), N-terminal pro B-type natriuretic peptide (NT-proBNP), troponin, and interleukin-6 (IL-6). PM2.5 levels across exposure durations from 1 to 36 months were assessed. Mixed effect model was used to estimate changes in biomarker levels against 1 μg/m3 increase in PM2.5 level across different exposure durations.

RESULTS

Totally, 641 participants were included. The average PM2.5 exposure level was 9 μg/m3. PM2.5 exposure was inversely associated with ghrelin, and positively associated with all other biomarkers. The magnitudes of these associations were duration-sensitive and exhibited a U-shaped or inverted-U-shaped trend. For example, the association of resistin were β = 0.05 (95% CI: 0.00, 0.09) for 1-month duration, strengthened to β = 0.27 (95% CI: 0.14, 0.41) for 13-month duration, and weakened to β = 0.12 (95% CI: -0.03, 0.26) for 24-month duration. Similar patterns were observed for other biomarkers except for CK-MB, of which the association direction switched from negative to positive as the duration increased. Resistin, leptin, MCP-1, TNF-alpha, and troponin had a sensitive exposure duration of nearly 12 months. Ghrelin and C-peptide were more sensitive to longer-term exposure (>18 months), while NT-proBNP and IL-6 were more sensitive to shorter-term exposure (<6 months).

CONCLUSION

PM2.5 exposure was associated with elevated levels in cardiometabolic biomarkers related to insulin resistance, inflammation, and heart injury. The magnitudes of these associations depended on the exposure duration. The most sensitive exposure durations of different biomarkers varied.