Yongjie Xia

Size-fractionated particulate air pollution and circulating biomarkers of inflammation, coagulation, and vasoconstriction in a panel of young adults.

Background: Short-term associations between size-fractionated particulate air pollution and circulating biomarkers are not well established, especially in developing countries with high levels of particulate matter (PM). Methods: We designed a panel study involving 34 healthy young adults to evaluate acute effects of size-fractionated PM on 13 circulating biomarkers of inflammation, coagulation, and vasoconstriction. We measured real-time, size-fractionated number concentrations of PM (aerodynamic diameters from 0.25 to 10 &mgr;m, mass concentrations of PM < 10 &mgr;m) over four follow-up measurements. The short-term associations between size-fractionated PM and biomarkers were assessed using linear mixed effect models. Results: We found positive associations between short-term exposure to PM and 10 biomarkers. PM with smaller size had stronger associations. The size fractions with the strongest associations were 0.25–0.40 &mgr;m for number concentrations and <1 &mgr;m for mass concentrations. For example, an interquartile range increase in 24-hour-average number concentrations of PM0.25–0.40 was associated with a 7%–32% increase in biomarkers of inflammation, 34%–68% of blood coagulation, and 45% of vasoconstriction. Similar estimates were found for mass concentrations of PM1. Furthermore, our results demonstrated an apparent acute effect on circulating biomarkers, even 2 hours after exposure. The effects were strongest within the first 12–24 hours, and effects on inflammation occurred more quickly than on coagulation and vasoconstriction. Conclusions: Our results provided potentially vital insights into the size and temporal characteristics of PM that could modify subclinical cardiovascular effects. These findings may have implications on disease prevention and environmental regulation in China.

Personal exposure to fine particulate matter and blood pressure: A role of angiotensin converting enzyme and its DNA methylation.

BACKGROUND The underlying intermediate mechanisms about the association between fine particulate matter (PM2.5) air pollution and blood pressure (BP) were unclear. Few epidemiological studies have explored the potential mediation effects of angiotensin-converting enzyme (ACE) and its DNA methylation. METHODS We designed a longitudinal panel study with 4 follow-ups among 36 healthy college students in Shanghai, China from December 17, 2014 to July 11, 2015. We measured personal real-time exposure to PM2.5, serum ACE level, and blood methylation of ACE gene and the repetitive elements. We applied linear mixed-effects models to examine the effects of PM2.5 on ACE protein, DNA methylation and BP markers. Furthermore, we conducted mediation analyses to evaluate the potential pathways. RESULTS An interquartile range increase (26.78μg/m(3)) in 24-h average exposure to PM2.5 was significantly associated with 1.12 decreases in ACE average methylation (%5mC), 13.27% increase in ACE protein, and increments of 1.13mmHg in systolic BP, 0.66mmHg in diastolic BP and 0.82mmHg in mean arterial pressure. ACE hypomethylation mediated 11.78% (P=0.03) of the elevated ACE protein by PM2.5. Increased ACE protein accounted for 3.90~13.44% (P=0.35~0.68) of the elevated BP by PM2.5. Repetitive-element methylation was also decreased but did not significantly mediate the association between PM2.5 and BP. CONCLUSIONS This investigation provided strong evidence that short-term exposure to PM2.5 was significantly associated with BP, ACE protein and ACE methylation. Our findings highlighted a possible involvement of ACE and ACE methylation in the effects of PM2.5 on elevating BP.

Ambient air pollution, blood mitochondrial DNA copy number and telomere length in a panel of diabetes patients.

Abstract Context: Several previous studies proposed a link between particulate matter (PM) pollution and mitochondrial DNA copy number (MtDNAcn) and telomere length (TL). However, this evidence is quite limited and inconsistent, especially on how the particle size affects the associations and on whether there exists such an association with gaseous pollutants. Objective: We aimed to investigate the short-term associations of size-fractionated PM and gaseous pollutants with blood MtDNAcn and TL. Methods: We conducted a longitudinal panel study involving 6 repeated measurements among 35 Type 2 diabetes patients in Shanghai, China from April to June 2013. We measured the real-time concentrations of size-fractionated PM (0.25–10 μm) and criteria gaseous pollutants. Blood MtDNAcn and TL were tested by a quantitative real-time PCR–based assay. Linear mixed-effect models were used to explore their short-term associations using multiple lag periods, after controlling for individual characteristics, time trends and weather conditions. Results: In general, there were inverse but statistically non-significant associations between all pollutants and MtDNAcn. Coarse PM appeared to be more closely linked with MtDNAcn than smaller PM. The associations between various air pollutants and TL were generally positive but very weak. There were no clear lag patterns for these associations. The associations between air pollutants and MtDNAcn and TL were strengthened but still not significant among those who did not take statins regularly. Conclusions: This study did not support short-term associations of PM or gaseous pollutants with blood MtDNAcn and TL in type 2 diabetes patients.

Possible Mediation by Methylation in Acute Inflammation Following Personal Exposure to Fine Particulate Air Pollution

Air pollution may increase cardiovascular and respiratory risk through inflammatory pathways, but evidence for acute effects has been weak and indirect. Between December 2014 and July 2015, we enrolled 36 healthy, nonsmoking college students for a panel study in Shanghai, China, a city with highly variable levels of air pollution. We measured personal exposure to particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM2.5) continuously for 72 hours preceding each of 4 clinical visits that included phlebotomy. We measured 4 inflammation proteins and DNA methylation at nearby regulatory cytosine-phosphate-guanine (CpG) loci. We applied linear mixed-effect models to examine associations over various lag times. When results suggested mediation, we evaluated methylation as mediator. Increased PM2.5 concentration was positively associated with all 4 inflammation proteins and negatively associated with DNA methylation at regulatory loci for tumor necrosis factor alpha (TNF-α) and soluble intercellular adhesion molecule-1. A 10-μg/m3 increase in average PM2.5 during the 24 hours preceding blood draw corresponded to a 4.4% increase in TNF-α and a statistically significant decrease in methylation at one of the two studied candidate CpG loci for TNF-α. Epigenetics may play an important role in mediating effects of PM2.5 on inflammatory pathways.

Estimation of personal ozone exposure using ambient concentrations and influencing factors

Evidence is limited regarding whether ambient monitoring can properly represent personal ozone exposure. We conducted a longitudinal panel study to measure personal exposure to ozone using real-time personal ozone monitors. Corresponding ambient ozone concentrations and possible influencing factors (meteorological conditions and activity patterns) were also collected. We used linear mixed-effect models to analyze personal-ambient ozone concentration associations and possible influencing factors. Ambient ozone concentrations were around two to three times higher than personal ozone (43.1 μg/m3 on average) and their correlations were weak with small slopes (0.35) and marginal R square (RM2) values (0.24). Larger RM2 values were found under high temperature (>29.5 °C), low humidity (<62.1%), good ventilation conditions (>4 h) and for individuals spent longer time outdoors (>0.6 h). In final model, personal ozone exposure was positively associated with ambient concentrations and ventilation conditions, but inversely correlated with ambient temperature and humidity. The models explained >50% of personal ozone concentration variabilities. Our results highlight that ambient ozone concentration alone is not a suitable surrogate for individual exposure assessment. Meteorological conditions (temperature and humidity) and activity patterns (windows opening and outdoor activities) that affecting personal ozone exposure should be taken into account.

Effects of Personal Short-Term Exposure to Ambient Ozone on Blood Pressure and Vascular Endothelial Function: A Mechanistic Study Based on DNA Methylation and Metabolomics

Short-term exposure to ambient ozone is associated with adverse cardiovascular effects, with inconsistent evidence on the molecular mechanisms. We conducted a longitudinal panel study among 43 college students in Shanghai to explore the effects of personal ozone exposure on blood pressure (BP), vascular endothelial function, and the potential molecular mechanisms. We measured real-time personal ozone exposure levels, serum angiotensin-converting enzyme (ACE) and endothelin-1 (ET-1), and locus-specific DNA methylation of ACE and EDN1 (coding ET-1). We used an untargeted metabolomic approach to explore potentially important metabolites. We applied linear mixed-effect models to examine the effects of ozone on the above biomarkers. An increase in 2 h-average ozone exposure was significantly associated with elevated levels of BP, ACE, and ET-1. ACE and EDN1 methylation decreased with ozone exposure, but the magnitude differed by genomic loci. Metabolomics analysis showed significant changes in serum lipid metabolites following ozone exposure that are involved in maintaining vascular endothelial function. Our findings suggested that acute exposure to ambient ozone can elevate serum levels of ACE and ET-1, decrease their DNA methylation, and alter the lipid metabolism, which may be partly responsible for the effects of ozone on BP and vascular endothelial function.

Personal ozone exposure and respiratory inflammatory response: the role of DNA methylation in the arginase–nitric oxide synthase pathway

Little is known regarding the molecular mechanisms behind respiratory inflammatory response induced by ozone. We performed a longitudinal panel study with four repeated measurements among 43 young adults in Shanghai, China from May to October in 2016. We collected buccal samples and measured the fractional exhaled nitric oxide (FeNO) after 3-day personal ozone monitoring. In buccal samples, we measured concentrations of inducible nitric oxide synthase (iNOS) and arginase (ARG), and DNA methylation of NOS2A and ARG2. We used linear mixed-effect models to analyze the effects of ozone on FeNO, two enzymes and their DNA methylation. A 10 ppb increase in ozone (lag 0-8 h) was significantly associated with a 3.89% increase in FeNO, a 36.33% increase in iNOS, and a decrease of 0.36 in the average methylation (%5mC) of NOS2A. Ozone was associated with decreased ARG and elevated ARG2 methylation, but the associations were not significant. These effects were more pronounced among allergic subjects than healthy subjects. The effects were much stronger when using personal exposure monitoring than fixed-site measurements. Our study demonstrated that personal short-term exposure to ozone may result in acute respiratory inflammation, which may be mainly modulated by NOS2A hypomethylation in the arginase-nitric oxide synthase pathway.

Fine particulate matter constituents and stress hormones in the hypothalamus–pituitary–adrenal axis

Fine particulate matter (PM2.5) has recently been associated with the activation of the hypothalamus-pituitary-adrenal (HPA) axis, increasing cardiometabolic risks. However, it is unknown which constituents of PM2.5 were mainly responsible for these associations. In a longitudinal panel study with 4 repeated measurements among 43 college students in Shanghai, China, we measured serum levels of corticotropin releasing hormone (CRH), adrenocorticotropic hormone (ACTH) and cortisol, as indicators of HPA axis activation. Then, we evaluated the associations of 22 constituents of PM2.5 with these stress hormones using linear mixed-effect models. During the study period, the average daily concentration of PM2.5 was 41.1 μg/m3. We found that short-term exposure to PM2.5 was associated with elevated levels of the 3 stress hormones. We observed that water-soluble inorganic ions, especially nitrate (NO3-) and ammonium, had stronger influences on 3 hormones. Six metallic elements, including Zn, Mn, Cu, Fe, Br, and Cr, had positive but generally instable associations with 3 hormones. The effects of organic carbon and elemental carbon on hormones were generally weak. When correcting for multiple comparisons using false discovery rate, NO3- was still significantly associated with CRH, but other important associations turned to be insignificant. An interquartile range increase in NO3- on the previous day were associated with 12.13% increase (95% confidence interval: 4.45%, 20.37%) in CRH. Our findings suggested that water-soluble inorganic constituents of PM2.5 (especially, NO3-) might have stronger influences on the activation of HPA axis than carbonaceous and elemental components.

Estimation of personal PM 2.5 and BC exposure by a modeling approach – Results of a panel study in Shanghai, China

BACKGROUND Epidemiologic studies of PM2.5 (particulate matter with aerodynamic diameter ≤2.5 μm) and black carbon (BC) typically use ambient measurements as exposure proxies given that individual measurement is infeasible among large populations. Failure to account for variation in exposure will bias epidemiologic study results. The ability of ambient measurement as a proxy of exposure in regions with heavy pollution is untested. OBJECTIVE We aimed to investigate effects of potential determinants and to estimate PM2.5 and BC exposure by a modeling approach. METHODS We collected 417 24 h personal PM2.5 and 130 72 h personal BC measurements from a panel of 36 nonsmoking college students in Shanghai, China. Each participant underwent 4 rounds of three consecutive 24-h sampling sessions through December 2014 to July 2015. We applied backwards regression to construct mixed effect models incorporating all accessible variables of ambient pollution, climate and time-location information for exposure prediction. All models were evaluated by marginal R2 and root mean square error (RMSE) from a leave-one-out-cross-validation (LOOCV) and a 10-fold cross-validation (10-fold CV). RESULTS Personal PM2.5 was 47.6% lower than ambient level, with mean (±Standard Deviation, SD) level of 39.9 (±32.1) μg/m3; whereas personal BC (6.1 (±2.8) μg/m3) was about one-fold higher than the corresponding ambient concentrations. Ambient levels were the most significant determinants of PM2.5 and BC exposure. Meteorological and season indicators were also important predictors. Our final models predicted 75% of the variance in 24 h personal PM2.5 and 72 h personal BC. LOOCV analysis showed an R2 (RMSE) of 0.73 (0.40) for PM2.5 and 0.66 (0.27) for BC. Ten-fold CV analysis showed a R2 (RMSE) of 0.73 (0.41) for PM2.5 and 0.68 (0.26) for BC. CONCLUSION We used readily accessible data and established intuitive models that can predict PM2.5 and BC exposure. This modeling approach can be a feasible solution for PM exposure estimation in epidemiological studies.