Background-Ambient particulate matter (PM) exposure has been associated with respiratory function decline in epidemiological studies. We hypothesize that a possible underlying mechanism is the perturbation of airway microbiome by PM exposure. Methods-During October 2016-October 2017, on two human cohorts (n = 115 in total) in Shanghai China, we systematically collected three categories of data (1) respiratory functions, (2)

Water-soluble inorganic (WSI) ions are major components of ambient air PM 2.5 (particulate matter of diameter ≤2.5 μm); however, their potential health effects are understudied. On C57BL/6 mice, we quantified the effect of three major PM 2.5 WSIs (NO 3 − , SO 4 2− , and NH 4 + ) on respiratory systems. Exposure scenarios include different WSI types, concentrations, animal development stages (young vs adult), and sex. The exposure effects were comprehensively assessed, with special focus on the respiratory function and tissue/cell level changes. Chronic PM 2.5 NO 3 − exposure produced significant respiratory function decline, mainly presented as airflow obstruction. The decline was more profound in young mice than in adult mice. In young mice, exposure to 22 μg/m 3 PM 2.5 NO 3 − reduced FEV 0.05 (forced expiratory volume in 0.05 s) by 11.3% (p = 9.6 × 10 −3 ) and increased pulmonary neutrophil infiltration by 7.9% (p = 7.1 × 10 −3 ). Causality tests identified that neutrophil infiltration was involved in the biological mechanism underlying PM 2.5 NO 3 − toxicity. In contrast, the effects of PM 2.5 SO 4 2− were considerably weaker than NO 3 − . PM 2.5 NO 3 − exposure was 3.4 times more potent than PM 2.5 SO 4 2− in causing reduction of the peak expiratory flow. PM 2.5 NH 4 + exposure had no statistically significant effects on the respiratory function. In summary, this study provided strong evidence on the adverse impacts of PM 2.5 WSIs, where the impacts were most profound in young mice exposed to PM 2.5 NO 3 − . If confirmed in humans, toxicity of PM 2.5 WSI will have broad implications in environment health and policy making.

Background-Impaired in utero fetal growth trajectory may have long term health consequences of the newborns and increase risk of adulthood metabolic diseases. Prenatal exposure to air pollution has been linked to fetal development restriction; however, the impact of exposure to ambient air pollutants on the entire course of intrauterine fetal development has not been comprehensively investigated.Methods-During 2015 -2018, two cohorts of mother-infant dyads (N=678 and 227) were recruited in Shanghai China, from which three categories of data were systematically collected: (1) daily exposure to six air pollutants during pregnancy, (2) fetal biometry in the 2 nd (gestational week 24, [GW24]) and 3 rd trimester (GW36), and (3) neonatal outcomes at birth. We investigated the impact of prenatal exposure to air pollutant mixture on the trajectory of fetal development during the course of gestation, adjusting for a broad set of potential confounds.Results-Prenatal exposure to PM 2.5 , PM 10 , SO 2 and O 3 significantly reduced fetal biometry at GW24, where SO 2 had the most potent effect. For every 10 ug/m 3 increment increase of daily SO 2 exposure during the 1 st trimester shortened femur length by 2.20 mm (p=6.7E-21) translating to 5.3% reduction from the average of the study cohort. Prenatal air pollution exposure also decreased fetal biometry at GW36 with attenuated effect size. Comparing to the lowest exposed quartile, fetus in the highest exposed quartile had 6.3% (p=3.5E-5) and 2.1% (p=2.4E-3) lower estimated intrauterine weight in GW24 and GW36, respectively; however, no difference in birth weight was observed, indicating a rapid catch-up growth in the 3 rd trimester.Conclusions-To our knowledge, for the first time, we demonstrated the impact of prenatal exposure to ambient air pollutants on the course of intrauterine fetal development. The altered growth trajectory and rapid catch-up growth in associated with high prenatal exposure may lead to long-term predisposition for adulthood metabolic disorders.

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Smoking is a major cause of respiratory conditions. To date, the genetic pleiotropy between smoking behavior and lung function/chronic obstructive pulmonary disease (COPD) have not been systematically explored. We leverage large data sets of smoking behavior, lung function and COPD, and addressed two questions, (1) whether the genetic predisposition of nicotine dependence influence COPD risk and lung function; and (2) the genetic pleiotropy follow causal or independent model. We found the genetic predisposition of nicotine dependence was associated with COPD risk, even after adjusting for smoking behavior, indicating genetic pleiotropy and independent model. Two known nicotine dependent loci (15q25.1 and 19q13.2) were associated with smoking adjusted lung function, and 15q25.1 reached genome-wide significance. At various suggestive p-value thresholds, the smoking adjusted lung function traits share association signals with cigarettes per day and former smoking, substantially greater than random chance. Empirical data showed the genetic pleiotropy between nicotine dependence and COPD or lung function. The basis of pleiotropic effect is rather complex, attributable to a large number of genetic variants, and many variants functions through independent model, where the pleiotropic variants directly affect lung function, not mediated by influencing subjects’ smoking behavior.

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Background Impaired in utero fetal growth trajectory may have long term health consequences of the newborns and increase risk of adulthood metabolic diseases. Prenatal exposure to air pollution has been linked to fetal development restriction; however, the impact of exposure to ambient air pollutants on the entire course of intrauterine fetal development has not been comprehensively investigated. Methods During 2015 – 2018, two cohorts of mother-infant dyads (N=678 and 227) were recruited in Shanghai China, from which three categories of data were systematically collected: (1) daily exposure to six air pollutants during pregnancy, (2) fetal biometry in the 2 nd (gestational week 24, [GW24]) and 3 rd trimester (GW36), and (3) neonatal outcomes at birth. We investigated the impact of prenatal exposure to a mixture of air pollutants on the trajectory of fetal development during the course of gestation, adjusting for a broad set of potential confounds. Results Prenatal exposure to PM 2.5 , PM 10 , SO 2 and O 3 significantly reduced fetal biometry at GW24, where SO 2 had the most potent effect. For every 10 ug/m 3 increment increase of daily SO 2 exposure during the 1 st trimester shortened femur length by 2.20 mm (p=6.7E-21) translating to 5.3% reduction from population average. Prenatal air pollution exposure also decreased fetal biometry at GW36 with attenuated effect size. Comparing to the lowest exposed quartile, fetus in the highest exposed quartile had 6.3% (p=3.5E-5) and 2.1% (p=2.4E-3) lower estimated intrauterine weight in GW24 and GW36, respectively; however, no difference in birth weight was observed, indicating a rapid catch-up growth in the 3 rd trimester. Conclusions To our knowledge, for the first time, we demonstrated the impact of prenatal exposure to ambient air pollutants on the course of intrauterine fetal development. The altered growth trajectory and rapid catch-up growth in associated with high prenatal exposure may lead to long-term predisposition for adulthood metabolic disorders.

The UK Biobank (UKBB) is a large population-based cohort that provides a unique opportunity to study the association between environmental exposure and biomarkers and to identify biomarkers as potential instruments for assessing exposure dose, health damage, and disease risks. On 462 063 participants of European ancestry, we characterized the relationship of 38 disease-relevant biomarkers, asthma diagnosis, ambient pollution, traffic factors, and genetic background. The air pollutant exposure on the UKBB cohort was fairly low (e.g., mean PM2.5 concentration at 10.0 μg/m3). Nevertheless, 30 biomarkers were in association with at least one environmental factor; e.g., C-reactive protein levels were positively associated with NO (p adj = 2.99 × 10–4), NO2 (p adj = 4.15 × 10–4), and PM2.5 (p adj = 1.92 × 10–6) even after multiple testing adjustment. Asthma diagnosis was associated with four pollutants (NO, NO2, PM2.5, and PM10). The largest effect size was observed in PM2.5, where a 5 μg/m3 increment of exposure was associated with a 1.52 increase in asthma diagnosis (p = 4.41 × 10–13). Further, environmental exposure and genetic predisposition influenced biomarker levels and asthma diagnosis in an additive model. The exposure–biomarker associations identified in this study could serve as potential indicators for environmental exposure induced health damages. Our results also shed light on possible mechanisms whereby environmental exposure influences disease-causing biomarkers and in turn increases disease risk.