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Introduction Myocardial infarction (MI), a potentially fatal cardiovascular condition, develops when the blood flow through the coronary arteries is diminished due to various factors, leading to inadequate oxygen supply to [...], BACKGROUND: Unraveling gene--environment interaction can provide a novel insight into early disease prevention. Nevertheless, current understanding of the interplay between genetic predisposition and air pollution in relation to myocardial infarction (MI) risk remains limited. Furthermore, the potential long-term influence of air pollutants on MI incidence risk warrants more conclusive evidence in a community population. OBJECTIVE: We investigated interactions between genetic predisposition and exposure to air pollutants on MI incidence. METHODS: This study incorporated a sample of 456,354 UK Biobank participants and annual mean air pollution ([PM.sub.2.5], [PM.sub.10], [NO.sub.2], and [NO.sub.x]) from the UK Department for Environment, Food and Rural Affairs (2006-2021). The Cox proportional hazards model was employed to explore MI incidence after chronic air pollutants exposure. By quantifying genetic risk through the calculation of polygenic risk score (PRS), this study further examined the interactions between genetic risk and exposure to air pollutants in the development of MI on both additive and multiplicative scales. RESULTS: Among 456,354 participants, 9,114 incident MI events were observed during a median follow-up of 12.08 y. Chronic exposure to air pollutants was linked with an increased risk of MI occurrence. Specifically, the hazard ratios (per interquartile range) were 1.12 (95% CI: 1.10, 1.13) for [PM.sub.2.5], 1.20 (95% CI: 1.19, 1.22) for [PM.sub.10], 1.13 (95% CI: 1.12, 1.15) for [NO.sub.2], and 1.12 (95% CI: 1.11, 1.13) for [NO.sub.x]. In terms of the joint effects, participants with high PRS and high level of air pollution exposure exhibited the greatest risk of MI among all study participants ( ~ 255% to 324%). Remarkably, both multiplicative and additive interactions were detected in the ambient air pollutants exposure and genetic risk on the incidence of MI. DISCUSSION: There were interactions between exposure to ambient air pollutants and genetic susceptibility on the risk of MI onset. Moreover, the joint effects of these two exposures were greater than the effect of each factor alone. https://doi.org/10.1289/EHP14291

Objective: There are few existing studies that investigate the risk of systemic lupus erythematosus (SLE) associated with long‐term exposure to air pollutants. This study aimed to explore associations between long‐term exposure to air pollutants and incident SLE and further evaluate interactions and joint effects of genetic risk and air pollutants. Methods: A total of 459,815 participants were included from UK Biobank. The concentrations of air pollutants (fine particulate matter with diameter ≤2.5 μm [PM2.5], particulate matter diameter ≤10 μm [PM10], nitrogen dioxide [NO2], and nitrogen oxides [NOx]) were estimated by land‐use regression model. We applied Cox proportional hazards model to explore linkages of air pollutants and incident SLE. The polygenic risk score (PRS) was used for further assessing the interactions and joint effects of genetic risk and air pollutants. Results: A total of 399 patients with SLE were identified during a median follow‐up of 11.77 years. There were positive associations between air pollutant exposure and incident SLE, as the adjusted hazard ratios were 1.18 (95% confidence interval [95% CI] 1.06–1.32), 1.23 (1.10–1.39), 1.27 (1.14–1.41), and 1.13 (1.03–1.23) for each interquartile range increase in PM2.5, PM10, NO2, and NOx, respectively. Moreover, participants with high genetic risk and high air pollution exposure had the highest risk of incident SLE compared with those with low genetic risk and low air pollution exposure (adjusted hazard ratio: PM2.5, 4.16 [95% CI 2.67–6.49]; PM10, 5.31 [95% CI 3.30,–8.55]; NO2, 5.61 [95% CI 3.45–9.13]; and NOx, 4.80 [95% CI 3.00–7.66]). There was a significant multiplicative interaction between NO2 and PRS. Conclusion: Long‐term exposure to air pollutants (PM2.5, PM10, NO2, and NOx) may increase the risk of developing SLE. [ABSTRACT FROM AUTHOR]

Background: Evidence linking air pollutants and the risk of schizophrenia remains limited and inconsistent, and no studies have investigated the joint effect of air pollutant exposure and genetic factors on schizophrenia risk. Aims: To investigate how exposure to air pollution affects schizophrenia risk and the potential effect modification of genetic susceptibility. Method: Our study was conducted using data on 485 288 participants from the UK Biobank. Cox proportional hazards models were used to estimate the schizophrenia risk as a function of long-term air pollution exposure presented as a time-varying variable. We also derived the schizophrenia polygenic risk score (PRS) utilising data provided by the UK Biobank, and investigated the modification effect of genetic susceptibility. Results: During a median follow-up period of 11.9 years, 417 individuals developed schizophrenia (mean age 55.57 years, s.d. = 8.68; 45.6% female). Significant correlations were observed between long-term exposure to four air pollutants (PM2.5; PM10; nitrogen oxides, NOx; nitrogen dioxide, NO2) and the schizophrenia risk in each genetic risk group. Interactions between genetic factors and the pollutants NO2 and NOx had an effect on schizophrenia events. Compared with those with low PRS and low air pollution, participants with high PRS and high air pollution had the highest risk of incident schizophrenia (PM2.5: hazard ratio = 6.25 (95% CI 5.03–7.76); PM10: hazard ratio = 7.38 (95% CI 5.86–9.29); NO2: hazard ratio = 6.31 (95% CI 5.02–7.93); NOx: hazard ratio = 6.62 (95% CI 5.24–8.37)). Conclusions: Long-term exposure to air pollutants was positively related to the schizophrenia risk. Furthermore, high genetic susceptibility could increase the effect of NO2 and NOx on schizophrenia risk. [ABSTRACT FROM AUTHOR]

Background: Benzene affects human health through environmental exposure in addition to occupational contact. However, few studies have examined the associations between long-term exposure to low concentrations of ambient benzene and mortality risks in nonoccupational settings. Methods: This prospective cohort study consists of 393,042 participants without stroke, myocardial infarction, or cancer at baseline from the UK Biobank. Annual average concentrations of benzene for each year during follow-up were measured using air dispersion models. The main outcomes were all-cause mortality and mortality from specific causes. Cox proportional-hazards models with time-varying exposure measurements were used to estimate the hazard ratios and 95% confidence intervals (CIs) for mortality risks. Restricted cubic spline models were used to estimate exposure–response relationships. Measurements and Main Results: With each interquartile range increase in the average annual concentration of benzene, the adjusted hazard ratios of mortality risk from all causes, cardiovascular disease, cancer, and respiratory disease were 1.26 (95% CI, 1.24–1.27), 1.24 (95% CI, 1.21–1.28), 1.27 (95% CI, 1.25–1.29), and 1.25 (95% CI, 1.20–1.30), respectively. The monotonically increasing exposure–response curves showed no threshold and plateau within the observed concentration range. Furthermore, the effect of benzene exposure on mortality persisted across different subgroups and was somewhat stronger in younger and White people (P for interaction < 0.05). Conclusions: Long-term exposure to low concentrations of ambient benzene significantly increases mortality risk in the general population. Ambient benzene represents a potential threat to public health, and further investigations are needed to support timely pollution regulation and health protection. [ABSTRACT FROM AUTHOR]

Aims Methods and results Conclusion Long‐term fine particulate matter (PM2.5) exposure has been linked to incident heart failure (HF), but the impacts of its constituents remain unknown. We aimed to investigate the associations of PM2.5 constituents with incident HF, and further evaluate the modification effects of genetic susceptibility.PM2.5 and its constituents, including elemental carbon (EC), organic matter (OM), ammonium (NH4+), nitrate (NO3−), and sulfate (SO42−), were estimated using the European Monitoring and Evaluation Programme model applied to the UK (EMEP4UK) driven by Weather and Research Forecast model meteorology. A polygenic risk score (PRS) was calculated to represent genetic susceptibility to HF. We employed Cox models to evaluate the associations of PM2.5 constituents with incident HF. Quantile‐based g‐computation model was used to identify the main contributor of PM2.5 constituents. Among 411 807 individuals in the UK Biobank, 7554 participants developed HF during a median follow‐up of 12.05 years. The adjusted hazard ratios of HF for each interquartile range increase in PM2.5, EC, OM, NH4+, NO3−, and SO42− were 1.50 (1.46–1.54), 1.31 (1.27–1.34), 1.12 (1.09–1.15), 1.42 (1.41–1.44), 1.26 (1.23–1.29), and 1.25 (1.24–1.26), respectively. EC (43%) played the most important role, followed by NH4+ and SO42−. Moreover, synergistic additive interactions accounted for 9–16% of the HF events in individuals exposed to both PM2.5, NH4+, NO3−, and SO42− and PRS.Long‐term exposure to PM2.5 constituents may elevate HF risk, and EC was the major contributor. Additive effects of PM2.5 constituents and PRS on HF risk were revealed. [ABSTRACT FROM AUTHOR]

Little is known about the impacts of specific chemical components on cardiovascular hospitalizations. We examined the relationships of PM 2.5 chemical composition and daily hospitalizations for cardiovascular disease in 184 Chinese cities. Acute PM 2.5 chemical composition exposures were linked to higher cardiovascular disease hospitalizations on the same day and the percentage change of cardiovascular admission was the highest at 1.76% (95% CI, 1.36-2.16%) per interquartile range increase in BC, followed by 1.07% (0.72-1.43%) for SO 4 2- , 1.04% (0.63-1.46%) for NH 4 + , 0.99% (0.55-1.43%) for NO 3 - , 0.83% (0.50-1.17%) for OM, and 0.80% (0.34%-1.26%) for Cl - . Similar findings were observed for all cause-specific major cardiovascular diseases, except for heart rhythm disturbances. Short-term exposures to PM 2.5 chemical composition were related to higher admissions and showed diverse impacts on major cardiovascular diseases.