VarExp: estimating variance explained by genome-wide GxE summary statistics.

Summary: Many genome-wide association studies and genome-wide screening for gene-environment (GxE) interactions have been performed to elucidate the underlying mechanisms of human traits and diseases. When the analyzed outcome is quantitative, the overall contribution of identified genetic variants to the outcome is often expressed as the percentage of phenotypic variance explained. This is commonly done using individual-level genotype data but it is challenging when results are derived through meta-analyses. Here, we present R package, 'VarExp', that allows for the estimation of the percentage of phenotypic variance explained using summary statistics only. It allows for a range of models to be evaluated, including marginal genetic effects, GxE interaction effects and both effects jointly. Its implementation integrates all recent methodological developments and does not need external data to be uploaded by users. Availability and implementation: The R package is available at https://gitlab.pasteur.fr/statistical-genetics/VarExp.git. Supplementary information: Supplementary data are available at Bioinformatics online.

Multiancestry association study identifies new asthma risk loci that colocalize with immune-cell enhancer marks.

We examined common variation in asthma risk by conducting a meta-analysis of worldwide asthma genome-wide association studies (23,948 asthma cases, 118,538 controls) of individuals from ethnically diverse populations. We identified five new asthma loci, found two new associations at two known asthma loci, established asthma associations at two loci previously implicated in the comorbidity of asthma plus hay fever, and confirmed nine known loci. Investigation of pleiotropy showed large overlaps in genetic variants with autoimmune and inflammatory diseases. The enrichment in enhancer marks at asthma risk loci, especially in immune cells, suggested a major role of these loci in the regulation of immunologically related mechanisms.

Childhood incident asthma and traffic-related air pollution at home and school.

BACKGROUND: Traffic-related air pollution has been associated with adverse cardiorespiratory effects, including increased asthma prevalence. However, there has been little study of effects of traffic exposure at school on new-onset asthma. OBJECTIVES: We evaluated the relationship of new-onset asthma with traffic-related pollution near homes and schools. METHODS: Parent-reported physician diagnosis of new-onset asthma (n = 120) was identified during 3 years of follow-up of a cohort of 2,497 kindergarten and first-grade children who were asthma- and wheezing-free at study entry into the Southern California Children's Health Study. We assessed traffic-related pollution exposure based on a line source dispersion model of traffic volume, distance from home and school, and local meteorology. Regional ambient ozone, nitrogen dioxide (NO(2)), and particulate matter were measured continuously at one central site monitor in each of 13 study communities. Hazard ratios (HRs) for new-onset asthma were scaled to the range of ambient central site pollutants and to the residential interquartile range for each traffic exposure metric. RESULTS: Asthma risk increased with modeled traffic-related pollution exposure from roadways near homes [HR 1.51; 95% confidence interval (CI), 1.25-1.82] and near schools (HR 1.45; 95% CI, 1.06-1.98). Ambient NO(2) measured at a central site in each community was also associated with increased risk (HR 2.18; 95% CI, 1.18-4.01). In models with both NO(2) and modeled traffic exposures, there were independent associations of asthma with traffic-related pollution at school and home, whereas the estimate for NO(2) was attenuated (HR 1.37; 95% CI, 0.69-2.71). CONCLUSIONS: Traffic-related pollution exposure at school and homes may both contribute to the development of asthma.

Prolonged postoperative ileus-definition, risk factors, and predictors after surgery.

BACKGROUND: Postoperative ileus (POI) remains an inevitable consequence of abdominal surgery. Although the pathogenesis of delayed gastrointestinal transit in the postoperative period has been the subject of considerable study, a clinically useful definition of what constitutes a pathologically prolonged ileus has yet to be established. The objectives of this study were to describe a definition for an abnormally prolonged ileus and to identify risk factors and predictors of prolonged ileus in patients undergoing abdominal surgery. MATERIALS AND METHODS: Over a 12-month period 88 patients who had abdominal surgery were retrospectively reviewed. The association of clinical factors with the duration of POI was examined with statistical tests. RESULTS: The mean time to commencing the consumption of unrestricted clear fluids after surgery was 2.3 +/- SD 1.6 days. The median duration of POI was 5 days (median 6 days), with an interquartile range of 3-6 days. Univariate regression analysis demonstrated significant correlations between duration of POI and estimated blood loss (EBL), total surgical time, and total opiate dose (TOD) (p = 0.009, p = 0.045, and p = 0.041, respectively). Multiple regression analysis identified EBL and TOD as independent predictors of duration of POI. CONCLUSIONS: We have identified two risk factors (EBL and TOD) that are independently associated with duration of POI. Our data suggest that with the definition of abnormal prolonged postoperative ileus as the number of days above the 3rd quartile, an ileus greater than 6 days serves as a better clinical definition of prolonged POI than 3 days, the measure that has previously been suggested.

Assessing uncertainty in spatial exposure models for air pollution health effects assessment.

BACKGROUND: Although numerous epidemiologic studies now use models of intraurban exposure, there has been little systematic evaluation of the performance of different models. OBJECTIVES: In this present article we proposed a modeling framework for assessing exposure model performance and the role of spatial autocorrelation in the estimation of health effects. METHODS: We obtained data from an exposure measurement substudy of subjects from the Southern California Children's Health Study. We examined how the addition of spatial correlations to a previously described unified exposure and health outcome modeling framework affects estimates of exposure-response relationships using the substudy data. The methods proposed build upon the previous work, which developed measurement-error techniques to estimate long-term nitrogen dioxide exposure and its effect on lung function in children. In this present article, we further develop these methods by introducing between- and within-community spatial autocorrelation error terms to evaluate effects of air pollution on forced vital capacity. The analytical methods developed are set in a Bayesian framework where multistage models are fitted jointly, properly incorporating parameter estimation uncertainty at all levels of the modeling process. RESULTS: Results suggest that the inclusion of residual spatial error terms improves the prediction of adverse health effects. These findings also demonstrate how residual spatial error may be used as a diagnostic for comparing exposure model performance.

Traffic, susceptibility, and childhood asthma.

Results from studies of traffic and childhood asthma have been inconsistent, but there has been little systematic evaluation of susceptible subgroups. In this study, we examined the relationship of local traffic-related exposure and asthma and wheeze in southern California school children (5-7 years of age). Lifetime history of doctor-diagnosed asthma and prevalent asthma and wheeze were evaluated by questionnaire. Parental history of asthma and child's history of allergic symptoms, sex, and early-life exposure (residence at the same home since 2 years of age) were examined as susceptibility factors. Residential exposure was assessed by proximity to a major road and by modeling exposure to local traffic-related pollutants. Residence within 75 m of a major road was associated with an increased risk of lifetime asthma [odds ratio (OR)=1.29; 95% confidence interval (CI), 1.01-1.86], prevalent asthma (OR=1.50; 95% CI, 1.16-1.95), and wheeze (OR=1.40; 95% CI, 1.09-1.78). Susceptibility increased in long-term residents with no parental history of asthma for lifetime asthma (OR=1.85; 95% CI, 1.11-3.09), prevalent asthma (OR=2.46; 95% CI, 0.48-4.09), and recent wheeze (OR=2.74; 95% CI, 1.71-4.39). The higher risk of asthma near a major road decreased to background rates at 150-200 m from the road. In children with a parental history of asthma and in children moving to the residence after 2 years of age, there was no increased risk associated with exposure. Effect of residential proximity to roadways was also larger in girls. A similar pattern of effects was observed with traffic-modeled exposure. These results indicate that residence near a major road is associated with asthma. The reason for larger effects in those with no parental history of asthma merits further investigation.

Bayesian modeling of air pollution health effects with missing exposure data.

The authors propose a new statistical procedure that utilizes measurement error models to estimate missing exposure data in health effects assessment. The method detailed in this paper follows a Bayesian framework that allows estimation of various parameters of the model in the presence of missing covariates in an informative way. The authors apply this methodology to study the effect of household-level long-term air pollution exposures on lung function for subjects from the Southern California Children's Health Study pilot project, conducted in the year 2000. Specifically, they propose techniques to examine the long-term effects of nitrogen dioxide (NO2) exposure on children's lung function for persons living in 11 southern California communities. The effect of nitrogen dioxide exposure on various measures of lung function was examined, but, similar to many air pollution studies, no completely accurate measure of household-level long-term nitrogen dioxide exposure was available. Rather, community-level nitrogen dioxide was measured continuously over many years, but household-level nitrogen dioxide exposure was measured only during two 2-week periods, one period in the summer and one period in the winter. From these incomplete measures, long-term nitrogen dioxide exposure and its effect on health must be inferred. Results show that the method improves estimates when compared with standard frequentist approaches.