Causality of particulate matter on cardiovascular diseases and cardiovascular biomarkers

The role of individual and regional environment factors on levels of a cardiovascular risk predictor in middle-aged and older Chinese adults

Background

Cardiovascular disease (CVD) remains the leading cause of death in China and worldwide. However, a large proportion of CVD can be prevented by regulating the levels of cardiovascular risk predictors. Despite the contribution of well-established factors to changes in cardiovascular risk predictors, the role of the regional environment and its combined effects with individual factors, which could affect health outcomes, remain unclear.

Methods

We included 10 308 middle-aged and older Chinese adults from the 2015 China Health and Retirement Longitudinal Study. High-sensitivity C-reactive protein (hs-CRP) is a cardiovascular risk predictor. Related potential factors including individual characteristics, regional air pollution, and regional socioeconomic status characteristics were also collected. The geographical detector method was used to quantify the explanatory power of individual and regional factors separately and in pairs in the hs-CRP levels according to regions (southern vs. northern China).

Results

Blood triglyceride had the highest explanatory power for hs-CRP levels. Regional environment factors, including air pollution and socioeconomic status, significantly affected hs-CRP levels, and the results differed by region. Indoor air pollution and regional industrial structure had a stronger effect on hs-CRP levels in the south, whereas outdoor air pollution and economic level had a greater effect in the north. The interactions between any two of the paired factors enhanced the effects.

Conclusions

Spatial stratified heterogeneity of the leading risk factors for hs-CRP, a powerful cardiovascular risk predictor, was found. The combined effect of individual factors and regional environment enhanced the explanatory power of each risk factor. The results suggest that policymakers should choose different optimal approaches to regulate the cardiovascular risk predictor levels of middle-aged and older Chinese adults in different regions and the interaction effects between individual factors and the regional environment should be considered.

Genetic insights into the causal relationship between air pollutants and atrial fibrillation: a Mendelian randomization study

Previous observational studies reported associations between air pollutants and atrial fibrillation (AF), but their causal relationships remain unclear. We conducted a two-sample Mendelian randomization (MR) analysis using genome-wide association studies (GWAS) summary data from the UK Biobank and IEU Open GWAS databases to investigate the genetic causality between air pollutants and AF. Air pollutants were subdivided into nitrogen dioxide (NO2) and particulate matter (PM2.5 and PM10), with single-nucleotide polymorphisms (SNPs) associated with each pollutant identified as instrumental variables (IVs). Subsequently, MR methods including MR-Egger, weighted median, inverse variance weighted (IVW), simple mode, and weighted mode were applied to assess genetic causality, while pleiotropy, heterogeneity, and reliability were also evaluated. IVW findings indicate a consequential correlation between NO2 and increased AF risk, as evidenced by an odds ratio (OR 1.948 [95% confidence interval [CI] 1.011-3.756]; p = 0.046). Conversely, the causal effect of PM2.5 (OR 1.274 [95% CI 0.651-2.493; p = 0.480) and PM10 (OR 1.162 [95% CI 0.891-1.517]; p = 0.268) with AF was not statistically significant. The analysis revealed the absence of pleiotropy (p > 0.05). However, PM2.5 displayed significant heterogeneity (p = 0.2385), whereas NO2 (p = 0.5365) and PM10 (p = 0.7789) did not. This MR analysis suggested a causal effect of NO2 on AF, but not for PM2.5 or PM10.

Air pollution and coronary atherosclerosis

The recently introduced concept of 'exposome' emphasizes the impact of non-traditional threats onto cardiovascular health. Among these, air pollutants - particularly fine particulate matter < 2.5 μm (PM2.5) - have emerged as significant environmental risk factors for cardiovascular disease and mortality. PM2.5 exposure has been shown to induce endothelial dysfunction, chronic low-grade inflammation, and cardiometabolic impairment, contributing to the development and destabilization of atherosclerotic plaques. Both short- and long-term exposure to air pollution considerably increase the incidence of ischemic heart disease (IHD)-related events, with clinical evidence linking pollution to higher mortality and adverse prognosis, especially in vulnerable populations. In this review, we explore the mechanistic pathways through which air pollutants exacerbate atherosclerotic cardiovascular disease (ASCVD) and discuss their clinical impact.Furthermore, special attention will be directed to the outcomes and prognosis of patients with pollution-aggravated coronary atherosclerosis, as well as the potential role of targeted public health interventions.

Causal Effects of Air Pollution, Noise, and Shift Work on Unstable Angina and Myocardial Infarction: A Mendelian Randomization Study

Cardiovascular disease continues to be a major contributor to global morbidity and mortality, with environmental and occupational factors such as air pollution, noise, and shift work increasingly recognized as potential contributors. Using a two-sample Mendelian randomization (MR) approach, this study investigates the causal relationships of these risk factors with the risks of unstable angina (UA) and myocardial infarction (MI). Leveraging single nucleotide polymorphisms (SNPs) as genetic instruments, a comprehensive MR study was used to assess the causal influence of four major air pollutants (PM2.5, PM10, NO2, and NOx), noise, and shift work on unstable angina and myocardial infarction. Summary statistics were derived from large genome-wide association studies (GWASs) from the UK Biobank and the FinnGen consortium (Helsinki, Finland), with replication using an independent GWAS data source for myocardial infarction. The inverse-variance weighted (IVW) approach demonstrated a significant positive correlation between shift work and the increased risk of both unstable angina (OR with 95% CI: 1.62 [1.12-2.33], p = 0.010) and myocardial infarction (OR with 95% CI: 1.46 [1.00-2.14], p = 0.052). MR-PRESSO analysis identified outliers, and after correction, the association between shift work and myocardial infarction strengthened (OR with 95% CI: 1.58 [1.11-2.27], p = 0.017). No notable causal associations were identified for air pollution or noise with either outcome. The replication of myocardial infarction findings using independent data supported a possible causal link between shift work and myocardial infarction (OR with 95% CI: 1.41 [1.08-1.84], p = 0.012). These results provide novel evidence supporting shift work as a likely causal risk factor for unstable angina and myocardial infarction, underscoring the need for targeted public health strategies to mitigate its cardiovascular impact. However, further investigation is necessary to elucidate the role of air pollution and noise in cardiovascular outcomes.

Influence of air pollution on the nonaccidental death before and after the outbreak of COVID-19

BACKGROUND

During the COVID-19 pandemic, non-therapeutic interventions (NPIs), such as traffic restrictions, work stoppages, and school suspensions, have led to a sharp decline in the concentration of air pollutants in the epidemic sites. However, few studies focused on the impact of air pollutant changes on the risk of nonaccidental death.

METHOD

We selected Yancheng City, China, as the study site and applied a Generalized Additive Model (GAM) based on the quasi-Poisson distribution to evaluate the impact of atmospheric pollutants exposure on the nonaccidental death of local residents. The time span of this study was set from January 1, 2013, to December 21, 2022, that is, before and after the outbreak of COVID-19.

RESULTS

The concentration of some air pollutants has greatly varied after the outbreak of COVID-19, with a significant decline for PM2.5 (- 43.4%), PM10 (- 38.5%), SO2 (- 62.9%), and NO2 (- 22.6%), but an increase for O3 (+ 4.3%). Comparative analysis showed that PM2.5 contributed to an increased risk of nonaccidental death after the outbreak of COVID-19. With an increase in PM2.5 by 10 µg/m³, the excess relative risks (ER) of nonaccidental death of residents increased by 1.01% (95%CI: 0.19%,1.84%). The stratified analysis revealed that air pollutants impacted nonaccidental deaths in both men and women before the outbreak of COVID-19. After the outbreak of COVID-19, PM10 had a significant effect on male nonaccidental deaths. The concentrations of PM2.5, PM10, and SO2 increased by 10 µg/m³, the ER of PM2.5, PM10, and SO2 on female nonaccidental death increased by 1.52% (0.38%,2.67%), 0.58% (0.02%,1.13%), and 15.09% (5.73%,25.28%), respectively. Before the outbreak of COVID-19, five air pollutants had an impact on the death of residents from cardiovascular disease (CVD). After the outbreak of COVID-19, only PM10 significantly affected the death risk of CVD. In addition, we discovered that PM2.5, PM10, and SO2 significantly impacted the risk of death due to respiratory diseases before and after the outbreak of COVID-19.

CONCLUSIONS

Air pollutants have different effects on nonaccidental deaths before and after the COVID-19 outbreak. A decrease in air pollutant concentration due to the NPIs for COVID-19 had a significant effect on the reduction of the risk of nonaccidental death.

Causal effects of exposure to ambient air pollution on cancer risk: Insights from genetic evidence

Air pollution has been increasingly linked to cancer risk. However, the genetic causality between air pollution and cancer risk remains poorly understood. To elucidate the potential roles of air pollution (NOx, NO2, PM2.5, PM course, and PM10) in the risk of 18 specific-site cancers, large-scale genome-wide association studies with a novel Mendelian randomization (MR) method were employed. Our MR analyses revealed significant associations between certain air pollutants and specific types of cancer. Specifically, a positive association was observed between NOx exposure and squamous cell lung cancer (OR: 1.96, 95%CI: 1.07-3.59, p = 0.03) as well as esophageal cancer (OR: 1.002, 95%CI: 1.001-1.003, p = 0.005). Genetically predicted NO2 exposure was found to be a risk factor for endometrial cancer (OR 1.41, 95%CI: 1.03-1.94, p = 0.03) and ovarian cancer (OR: 1.49, 95%CI: 1.14-1.95, p = 0.0037). Additionally, genetically predicted PM2.5 exposure was associated with an increased risk of ER+ breast cancer (OR: 1.24, 95%CI: 1.03-1.5, p = 0.02) and ER- breast cancer (OR: 2.57, 95%CI: 1.05-6.3, p = 0.04). PM course exposure was identified as a risk factor for glioma (OR: 487.28, 95%CI: 13.08-18,153, p = 0.0008), while PM10 exposure exerted a detrimental effect on mesothelioma (OR: 114.75, 95%CI: 1.14-11,500.11, p = 0.04) and esophageal cancer (OR: 1.01, 95%CI: 1.007-1.02, p = 0.03). These findings underscored the importance of mitigating air pollution to reduce the burden of cancer and highlight the need for further investigations to elucidate the underlying mechanisms involved in these associations.

Particulate matter 2.5 causally increased genetic risk of autism spectrum disorder

BACKGROUND

Growing evidence suggested that particulate matter (PM) exhibit an increased risk of autism spectrum disorder (ASD). However, the causal association between PM and ASD risk remains unclear.

METHODS

We performed two-sample Mendelian randomization (MR) analyses, using instrumental variables (IVs) sourced from the largest genome-wide association studies (GWAS) databases. We employed three MR methods: inverse-variance weighted (IVW), weighted median (WM), and MR-Egger, with IVW method serving as our primary MR method. Sensitivity analyses were performed to ensure the stability of these findings.

RESULTS

The MR results suggested that PM2.5 increased the genetic risk of ASD (β = 2.41, OR = 11.13, 95% CI: 2.54-48.76, P < 0.01), and similar result was found for PM2.5 absorbance (β = 1.54, OR = 4.67, 95% CI: 1.21-18.01, P = 0.03). However, no such association was found in PM10 (β = 0.27, OR = 1.30, 95% CI: 0.72-2.36, P = 0.38). After adjusting for the false discovery rate (FDR) correction, our MR results remain consistent. Sensitivity analyses did not find significant heterogeneity or horizontal pleiotropy.

CONCLUSIONS

Our findings indicate that PM2.5 is a potential risk factor for ASD. Effective strategies to mitigate air pollutants might lead to a reduced incidence of ASD.