Mechanisms underlying the effects of traffic-related air pollution on people with asthma remain largely unknown, despite the abundance of observational and controlled studies reporting associations between traffic sources and asthma exacerbation and hospitalizations. To identify molecular pathways perturbed following traffic pollution exposures, we analyzed data as part of the Atlanta Commuters Exposure (ACE-2) study, a crossover panel of commuters with and without asthma. We measured 27 air pollutants and conducted high-resolution metabolomics profiling on blood samples from 45 commuters before and after each exposure session. We evaluated metabolite and metabolic pathway perturbations using an untargeted metabolome-wide association study framework with pathway analyses and chemical annotation. Most of the measured pollutants were elevated in highway commutes (p < 0.05). From both negative and positive ionization modes, 17,586 and 9087 metabolic features were extracted from plasma, respectively. 494 and 220 unique features were associated with at least 3 of the 27 exposures, respectively (p < 0.05), after controlling confounders and false discovery rates. Pathway analysis indicated alteration of several inflammatory and oxidative stress related metabolic pathways, including leukotriene, vitamin E, cytochrome P450, and tryptophan metabolism. We identified and annotated 45 unique metabolites enriched in these pathways, including arginine, histidine, and methionine. Most of these metabolites were not only associated with multiple pollutants, but also differentially expressed between participants with and without asthma. The analysis indicated that these metabolites collectively participated in an interrelated molecular network centering on arginine metabolism, underlying the impact of traffic-related pollutants on individuals with asthma. We detected numerous significant metabolic perturbations associated with in-vehicle exposures during commuting and validated metabolites that were closely linked to several inflammatory and redox pathways, elucidating the potential molecular mechanisms of traffic-related air pollution toxicity. These results support future studies of metabolic markers of traffic exposures and the corresponding molecular mechanisms.

We sought datasets with granular age distributions of rotavirus-positive disease presentations among children <5 years of age, before the introduction of rotavirus vaccines. We identified 117 datasets and fit parametric age distributions to each country dataset and mortality stratum. We calculated the median age and the cumulative proportion of rotavirus gastroenteritis events expected to occur at ages between birth and 5.0 years. The median age of rotavirus-positive hospital admissions was 38 weeks (interquartile range [IQR], 25–58 weeks) in countries with very high child mortality and 65 weeks (IQR, 40–107 weeks) in countries with very low or low child mortality. In countries with very high child mortality, 69% of rotavirus-positive admissions in children <5 years of age were in the first year of life, with 3% by 10 weeks, 8% by 15 weeks, and 27% by 26 weeks. This information is critical for assessing the potential benefits of alternative rotavirus vaccination schedules in different countries and for monitoring program impact.

Advances in liquid chromatography-mass spectrometry (LC-MS) have enabled high-resolution metabolomics (HRM) to emerge as a sensitive tool for measuring environmental exposures and corresponding biological response. Using measurements collected as part of a large, panel-based study of car commuters, the current analysis examines in-vehicle air pollution concentrations, targeted inflammatory biomarker levels, and metabolomic profiles to trace potential metabolic perturbations associated with on-road traffic exposures. A 60-person panel of adults participated in a crossover study, where each participant conducted a highway commute and randomized to either a side-street commute or clinic exposure session. In addition to in-vehicle exposure characterizations, participants contributed pre- and post-exposure dried blood spots for 2-hr changes in targeted proinflammatory and vascular injury biomarkers and 10-hr changes in the plasma metabolome. Samples were analyzed on a Thermo QExactive MS system in positive and negative electrospray ionization (ESI) mode. Data were processed and analyzed in R using apLCMS, xMSanalyzer, and limma. Features associated with environmental exposures or biological endpoints were identified with a linear mixed effects model and annotated through human metabolic pathway analysis in mummichog. HRM detected 10-hr perturbations in 110 features associated with in-vehicle, particulate metal exposures (Al, Pb, and Fe) which reflect changes in arachidonic acid, leukotriene, and tryptophan metabolism. Two-hour changes in proinflammatory biomarkers hs-CRP, IL-6, IL-8, and IL-1β were also associated with 10-hr changes in the plasma metabolome, suggesting diverse amino acid, leukotriene, and antioxidant metabolism effects. A putatively identified metabolite, 20-OH-LTB4, decreased after in-vehicle exposure to particulate metals, suggesting a subclinical immune response. Acute exposures to traffic-related air pollutants are associated with broad inflammatory response, including several traditional markers of inflammation.

To accurately assess micronutrient status, it is necessary to characterize the effects of inflammation and the acute-phase response on nutrient biomarkers. Within a norovirus human challenge study, we aimed to model the inflammatory response of C-reactive protein (CRP) and α-1-acid glycoprotein (AGP) by infection status, model kinetics of micronutrient biomarkers by inflammation status, and evaluate associations between inflammation and micronutrient biomarkers from 0 to 35 d post–norovirus exposure. Fifty-two healthy adults were enrolled into challenge studies in a hospital setting and followed longitudinally; all were exposed to norovirus, half were infected. Post hoc analysis of inflammatory and nutritional biomarkers was performed. Subjects were stratified by inflammation resulting from norovirus exposure. Smoothed regression models analyzed the kinetics of CRP and AGP by infection status, and nutritional biomarkers by inflammation. Linear mixed-effects models were used to analyze the independent relations between CRP, AGP, and biomarkers for iron, vitamin A, vitamin D, vitamin B-12, and folate from 0 to 35 d post–norovirus exposure. Norovirus-infected subjects had median (IQR) peak concentrations for CRP [16.0 (7.9–29.5) mg/L] and AGP [0.9 (0.8–1.2) g/L] on day 3 and day 4 postexposure, respectively. Nutritional biomarkers that differed (P < 0.05) from baseline within the inflamed group were ferritin (elevated day 3), hepcidin (elevated days 2, 3), serum iron (depressed days 2–4), transferrin saturation (depressed days 2–4), and retinol (depressed days 3, 4, and 7). Nutritional biomarker concentrations did not differ over time within the uninflamed group. In mixed models, CRP was associated with ferritin (positive) and serum iron and retinol (negative, P < 0.05). Using an experimental infectious challenge model in healthy adults, norovirus infection elicited a time-limited inflammatory response associated with altered serum concentrations of certain iron and vitamin A biomarkers, confirming the need to consider adjustments of these biomarkers to account for inflammation when assessing nutritional status. These trials were registered at clinicaltrials.gov as NCT00313404 and NCT00674336.

Introduction : Advances in the development of high-resolution metabolomics (HRM) have provided new opportunities for their use in characterizing exposures to environmental air pollutants and air pollution-related disease etiologies. Exposure assessment studies have considered blood, breath, and saliva as biological matrices suitable for measuring responses to air pollution exposures. The current study examines comparability among these three matrices using HRM and explores their potential for measuring mobile-source air toxics. Methods : Four participants provided saliva, exhaled breath concentrate (EBC), and plasma before and after a 2 h road traffic exposure. Samples were analyzed on a Thermo Scientific QExactive MS system in positive electrospray ionization mode and resolution of 70 000 full-width at half-maximum with C18 chromatography. Data were processed using an apLCMS and xMSanalyzer on the R statistical platform. Results : The analysis yielded 7110, 6019, and 7747 reproducible features in plasma, EBC, and saliva, respectively. Correlations were moderate-to-strong (R = 0.41–0.80) across all pairwise comparisons of feature intensity within profiles, with the strongest between EBC and saliva. The associations of mean intensities between matrix pairs were positive and significant, controlling for subject and sampling time effects. Six out of 20 features shared in all three matrices putatively matched a list of known mobile-source air toxics. Conclusions : Plasma, saliva, and EBC have largely comparable metabolic profiles measurable through HRM. These matrices have the potential to be used in identification and measurement of exposures to mobile-source air toxics, though further, targeted study is needed.