Impact of long-term exposure to PM2.5 on peripheral blood gene expression pathways involved in cell signaling and immune response

The effects of air and transportation noise pollution-related altered blood gene expression, DNA methylation, and protein abundance levels on gastrointestinal diseases risk

INTRODUCTION

Air pollution and transportation noise pollution has been linked to gastrointestinal (GI) diseases, but their relationship remains unclear.

METHODS

We extracted the significantly modulated genes and CpG sites related to air pollution (PM2.5, PM10, and NOx) and transportation noise pollution (aircraft, railway, and traffic road noise) from previous published studies. Genome-wide methylation analysis and colocalization analysis with these CpG sites and GWAS data of GI diseases were performed to disentangle the relationship between pollution-related blood DNA methylation (DNAm) alterations and GI diseases risk. Summary-based Mendelian randomization (SMR) analysis assessed the impact of pollution-related genes on GI diseases risk across methylation, gene expression, and protein levels. Enrichment analysis investigated the implicated biological pathways and immune cell types.

RESULTS

DNAm at cg00227781 [CD300A] (modulated by NOx exposure) and cg19215199 [ZMIZ1] (modulated by PM2.5 exposure) was significantly linked to increased noninfective enteritis and colitis risk, while cg08500171 [BAT2] (modulated by NOx exposure) is significantly associated with an increased gastroesophageal reflux disease (GERD) risk. Colocalization analysis provides strong evidence supporting a shared causal variant between these associations. Multi-omics levels SMR analysis revealed that pollution-modulated lower DNAm at 5 specific CpG sites were associated with increased expression of 4 genes (IL21R, EVPL, SYNGR1, and WDR46), subsequently increasing the risk of GERD, ulcerative colitis, and gastric ulcer. 7 circulating proteins coded by pollution-modulated genes were observed to be associated with 6 GI diseases risk. Enrichment analysis implicates immune and inflammatory responses, MAPK signaling, and telomere maintenance in these pollution-induced effects.

CONCLUSION

We identified potential links between air and transportation noise pollution-related gene methylation, expression, and protein abundance with GI diseases risk, possibly revealing new therapeutic targets.

Different effects of air pollutant concentrations on influenza A and B in Sichuan, China

BACKGROUND

The detrimental effects of air pollution on the respiratory system are well documented. Previous research has established a correlation between air pollutant concentration and the frequency of outpatient visits for influenza-like illness. However, studies investigating the variations in infection among different influenza subtypes remain sparse. We aimed to determine the correlation between air pollutant levels and different influenza subtypes in Sichuan Province, China.

METHODS

A generalized additive model and distributed lag nonlinear model were employed to assess the association between air pollutants and influenza subtypes, utilizing daily influenza data obtained from 30 hospitals across 21 cities in Sichuan Province. The analysis considered the temporal effects and meteorological factors. The study spanned from January 1, 2017, to December 31, 2019. To provide a more precise evaluation of the actual impact of air pollution on different subtypes of influenza, we also performed subgroup analyses based on factors such as gender, age, and geography within the population.

RESULTS

During the investigation, 17,462 specimens from Sichuan Province tested positive for influenza. Among these, 12,607 and 4855 were diagnosed with Flu A and B, respectively. The related risk of influenza A infection significantly increased following exposure to PM2.5 on Lag2 days (RR=1.008, 95 % confidence interval [CI]: 1.000-1.016), SO2 and CO on Lag1 days (RR=1.121, 95 % CI: 1.032-1.219; RR=1.151, 95 % CI: 1.030-1.289), and NO2 on Lag0 day (RR=1.089, 95 % CI: 1.035-1.145). PM10 and SO2 levels on Lag0 day, PM2.5 levels on Lag1 day, and CO levels on Lag6 day, with a reduced risk of influenza B (RR=0.987, 95 % CI: 0.976-0.997; RR=0.817, 95 % CI: 0.676-0.987; RR=0.979, 95 % CI: 0.970-0.989; RR=0.814, 95 % CI: 0.561-0.921).

CONCLUSION

The findings from the overall population and subgroup analyses indicated that the impact of air pollutant concentrations on influenza A and B is inconsistent, with influenza A demonstrating greater susceptibility to these pollutants. Minimizing the levels of SO2, CO, NO2, and PM2.5 can significantly decrease the likelihood of contracting influenza A. Analyzing the influence of environmental contaminants on different influenza subtypes can provide insights into seasonal influenza trends and guide the development of preventive and control strategies.

Guardians under Siege: Exploring Pollution's Effects on Human Immunity

Chemical pollution poses a significant threat to human health, with detrimental effects on various physiological systems, including the respiratory, cardiovascular, mental, and perinatal domains. While the impact of pollution on these systems has been extensively studied, the intricate relationship between chemical pollution and immunity remains a critical area of investigation. The focus of this study is to elucidate the relationship between chemical pollution and human immunity. To accomplish this task, this study presents a comprehensive review that encompasses in vitro, ex vivo, and in vivo studies, shedding light on the ways in which chemical pollution can modulate human immunity. Our aim is to unveil the complex mechanisms by which environmental contaminants compromise the delicate balance of the body's defense systems going beyond the well-established associations with defense systems and delving into the less-explored link between chemical exposure and various immune disorders, adding urgency to our understanding of the underlying mechanisms and their implications for public health.

Associations of socioeconomic status with infectious diseases mediated by lifestyle, environmental pollution and chronic comorbidities: a comprehensive evaluation based on UK Biobank

BACKGROUND

Socioeconomic status (SES) inequity was recognized as a driver of some certain infectious diseases. However, few studies evaluated the association between SES and the burden of overall infections, and even fewer identified preventable mediators. This study aimed to assess the association between SES and overall infectious diseases burden, and the potential roles of factors including lifestyle, environmental pollution, chronic disease history.

METHODS

We included 401,009 participants from the UK Biobank (UKB) and defined the infection status for each participant according to their diagnosis records. Latent class analysis (LCA) was used to define SES for each participant. We further defined healthy lifestyle score, environment pollution score (EPS) and four types of chronic comorbidities. We used multivariate logistic regression to test the associations between the four above covariates and infectious diseases. Then, we performed the mediation and interaction analysis to explain the relationships between SES and other variables on infectious diseases. Finally, we employed seven types of sensitivity analyses, including considering the Townsend deprivation index as an area level SES variable, repeating our main analysis for some individual or composite factors and in some subgroups, as well as in an external data from the US National Health and Nutrition Examination Survey, to verify the main results.

RESULTS

In UKB, 60,771 (15.2%) participants were diagnosed with infectious diseases during follow-up. Lower SES [odds ratio (OR) = 1.5570] were associated with higher risk of overall infections. Lifestyle score mediated 2.9% of effects from SES, which ranged from 2.9 to 4.0% in different infection subtypes, while cardiovascular disease (CVD) mediated a proportion of 6.2% with a range from 2.1 to 6.8%. In addition, SES showed significant negative interaction with lifestyle score (OR = 0.8650) and a history of cancer (OR = 0.9096), while a significant synergy interaction was observed between SES and EPS (OR = 1.0024). In subgroup analysis, we found that males and African (AFR) with lower SES showed much higher infection risk. Results from sensitivity and validation analyses showed relative consistent with the main analysis.

CONCLUSIONS

Low SES is shown to be an important risk factor for infectious disease, part of which may be mediated by poor lifestyle and chronic comorbidities. Efforts to enhance health education and improve the quality of living environment may help reduce burden of infectious disease, especially for people with low SES.