Causality of particulate matter on cardiovascular diseases and cardiovascular biomarkers

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.