Atopic asthmatic patients are reported to be more sensitive to the effects of environmental endotoxin (LPS) than healthy volunteers (HVs). It is unknown whether this sensitivity is due to dysregulated inflammatory responses after LPS exposure in atopic asthmatic patients.
We sought to test the hypothesis that atopic asthmatic patients respond differentially to inhaled LPS challenge compared with HVs.
Thirteen allergic asthmatic (AA) patients and 18 nonallergic nonasthmatic subjects (healthy volunteers [HVs]) underwent an inhalation challenge to 20,000 endotoxin units of Clinical Center Reference Endotoxin (LPS). Induced sputum and peripheral blood were obtained at baseline and 6 hours after inhaled LPS challenge. Sputum and blood samples were assayed for changes in inflammatory cell numbers and cytokine and cell-surface marker levels on monocytes and macrophages.
The percentage of neutrophils in sputum (%PMN) in induced sputum similarly and significantly increased in both HVs and AA patients after inhaled LPS challenge. However, the absolute numbers of leukocytes and PMNs recruited to the airways were significantly lower in AA patients compared with those seen in HVs with inhaled LPS challenge. Sputum levels of IL-6 and TNF-α were significantly increased in both cohorts, but levels of IL-1β and IL-18 were only significantly increased in the HV group. Cell-surface expression of Toll-like receptors 4 and 2 were significantly enhanced only in the HV group.
The airway inflammatory response to inhaled LPS challenge is blunted in AA patients compared with that seen in HVs and accompanied by reductions in airway neutrophilia and inflammasome-dependent cytokine production. These factors might contribute to increased susceptibility to airway microbial infection or colonization in AA patients.
Asthma; LPS; induced sputum; inflammasome; innate immunity
Two-stage design is a well-known cost-effective way for conducting biomedical studies when the exposure variable is expensive or difficult to measure. Recent research development further allowed one or both stages of the two-stage design to be outcome dependent on a continuous outcome variable. This outcome-dependent sampling feature enables further efficiency gain in parameter estimation and overall cost reduction of the study (e.g. Wang, X. and Zhou, H., 2010. Design and inference for cancer biomarker study with an outcome and auxiliary-dependent subsampling. Biometrics
66, 502–511; Zhou, H., Song, R., Wu, Y. and Qin, J., 2011. Statistical inference for a two-stage outcome-dependent sampling design with a continuous outcome. Biometrics
67, 194–202). In this paper, we develop a semiparametric mixed effect regression model for data from a two-stage design where the second-stage data are sampled with an outcome-auxiliary-dependent sample (OADS) scheme. Our method allows the cluster- or center-effects of the study subjects to be accounted for. We propose an estimated likelihood function to estimate the regression parameters. Simulation study indicates that greater study efficiency gains can be achieved under the proposed two-stage OADS design with center-effects when compared with other alternative sampling schemes. We illustrate the proposed method by analyzing a dataset from the Collaborative Perinatal Project.
Center effect; Mixed model; Outcome-auxiliary-dependent sampling; Validation sample
To characterize the relation between an exposure and a continuous outcome, the sampling of subjects can be done much as it is in a case-control study, such that the sample is enriched with subjects who are especially informative. In an outcome dependent sampling (ODS) design, observations made on a judiciously chosen subset of the base population can provide nearly the same statistical efficiency as observing the entire base population. Reaping the benefits of such sampling, however, requires use of an analysis that accounts for the ODS design. In this report, the authors examined the statistical efficiency of a plain random sample analyzed with standard methods, compared with that of data collected with an ODS design and analyzed by either of two appropriate methods. In addition, three real datasets were analyzed using an ODS approach. The results demonstrate the improved statistical efficiency obtained by using an ODS approach and its applicability in a wide range of settings. An ODS design, coupled with an appropriate analysis, can offer a cost-efficient approach to studying the determinants of a continuous outcome.
biased sampling; continuous outcome; empirical likelihood; epidemiologic methods; epidemiologic research design; semiparametric
Acute lung injury (ALI) is a major factor determining morbidity following burns and inhalational injury. In experimental models, factors potentially contributing to ALI risk include inhalation of toxins directly causing cell damage; inflammation; and infection. However, few studies have been done in humans.
We carried out a prospective observational study of patients admitted to the NC Jaycees Burn Center who were intubated and on mechanical ventilation for burns and suspected inhalational injury. Subjects were enrolled over an 8-month period and followed till discharge or death. Serial bronchial washings from clinically-indicated bronchoscopies were collected and analyzed for markers of cell injury and inflammation. These markers were compared with clinical markers of ALI.
Forty-three consecutive patients were studied, with a spectrum of burn and inhalation injury severity. Visible soot at initial bronchoscopy and gram negative bacteria in the lower respiratory tract were associated with ALI in univariate analyses. Subsequent multivariate analysis also controlled for % body surface area burns, infection, and inhalation severity. Elevated IL-10 and reduced IL-12p70 in bronchial washings were statistically significantly associated with ALI.
Independently of several factors including initial inhalational injury severity, infection, and extent of surface burns, high early levels of IL-10 and low levels of IL-12p70 in the central airways are associated with ALI in patients intubated after acute burn/inhalation injury. Lower airway secretions can be collected serially in critically ill burn/inhalation injury patients and may yield important clues to specific pathophysiologic pathways.
In this paper, we develop a nonparametric method, called adjusted exponentially tilted likelihood, and apply it to the analysis of morphometric measures. The adjusted exponential tilting estimator is shown to have the same first order asymptotic properties as that of the original exponentially tilted likelihood. The adjusted exponentially tilted likelihood ratio statistic is applied to test linear hypotheses of unknown parameters, such as the associations of brain measures (e.g., cortical and subcortical surfaces) with covariates of interest, such as age, gender, and gene. Simulation studies show that the adjusted exponential tilted likelihood ratio statistic performs as well as the t-test when the imaging data are symmetrically distributed, while it is superior when the imaging data have skewed distribution. We demonstrate the application of our new statistical methods to the detection of statistically significant differences in the morphology of the hippocampus between two schizophrenia groups and healthy subjects.
Adjusted exponential tilted likelihood; Hypothesis testing; M-rep; Morphometric measure
The area under the ROC curve (AUC) and partial area under the ROC curve (pAUC) are summary measures used to assess the accuracy of a biomarker in discriminating true disease status. The standard sampling approach used in biomarker validation studies is often inefficient and costly, especially when ascertaining the true disease status is costly and invasive. To improve efficiency and reduce the cost of biomarker validation studies, we consider a test-result-dependent sampling (TDS) scheme, in which subject selection for determining the disease state is dependent on the result of a biomarker assay. We first estimate the test-result distribution using data arising from the TDS design. With the estimated empirical test-result distribution, we propose consistent nonparametric estimators for AUC and pAUC and establish the asymptotic properties of the proposed estimators. Simulation studies show that the proposed estimators have good finite sample properties and that the TDS design yields more efficient AUC and pAUC estimates than a simple random sampling (SRS) design. A data example based on an ongoing cancer clinical trial is provided to illustrate the TDS design and the proposed estimators. This work can find broad applications in design and analysis of biomarker validation studies.
Area under ROC curve (AUC); Empirical likelihood; Nonparametric; Partial area under ROC curve (pAUC); Simple random sampling; Test-result-dependent sampling
The purpose of this review is to highlight recent data regarding the impact of exposure to tobacco smoke on influenza virus infection. This is timely because of the continuing pattern for influenza to cause epidemics and pandemics.
Experimental animal studies suggest that tobacco smoke severity of respiratory disease with influenza. The interaction is complex and dependent on dose and chronicity of both virus and smoke exposure. Smoke-induced oxidant stress and suppression of innate immunity are mechanistic factors leading to worse disease. Experiments using human respiratory cells show that tobacco smoke increases viral replication through mechanisms including suppression of antiviral pathways and altered cytokine patterns in cell types with central roles in mucosal innate immunity, such as epithelium, dendritic cells and natural killer cells. Studies also suggest a role for antioxidant strategies in reducing risk. Human volunteer studies using live attenuated influenza virus as a model appear to corroborate many of these findings.
Exposure to tobacco smoke remains extremely prevalent worldwide. While avoidance of exposure is a primary goal, it is important to understand the mechanisms underlying increased infection risk with tobacco smoke and other pollutant exposures, so that novel preventive or treatment strategies can be developed.
Influenza; tobacco smoke; interferon
Rationale: Diesel exhaust enhances allergic inflammation, and pollutants are associated with heightened susceptibility to viral respiratory infections. The effects of combined diesel and virus exposure in humans are unknown.
Objectives: Test whether acute exposure to diesel modifies inflammatory responses to influenza virus in normal humans and those with allergies.
Methods: We conducted a double-blind, randomized, placebo-controlled study of nasal responses to live attenuated influenza virus in normal volunteers and those with allergic rhinitis exposed to diesel (100 μg/m3) or clean air for 2 hours, followed by standard dose of virus and serial nasal lavages. Endpoints were inflammatory mediators (ELISA) and virus quantity (quantitative reverse-transcriptase polymerase chain reaction). To test for exposure effect, we used multiple regression with exposure group (diesel vs. air) as the main explanatory variable and allergic status as an additional factor.
Measurements and Main Results: Baseline levels of mediators did not differ among groups. For most postvirus nasal cytokine responses, there was no significant diesel effect, and no significant interaction with allergy. However, diesel was associated with significantly increased IFN-γ responses (P = 0.02), with no interaction with allergy in the regression model. Eotaxin-1 (P = 0.01), eosinophil cationic protein (P < 0.01), and influenza RNA sequences in nasal cells (P = 0.03) were significantly increased with diesel exposure, linked to allergy.
Conclusions: Short-term exposure to diesel exhaust leads to increased eosinophil activation and increased virus quantity after virus inoculation in those with allergic rhinitis. This is consistent with previous literature suggesting a diesel “adjuvant” effect promoting allergic inflammation, and our data further suggest this change may be associated with reduced virus clearance.
Clinical trial registered with www.clinicaltrials.gov (NCT00617110).
diesel; influenza; eosinophil cationic protein; eotaxin-1; interferon-γ
This study identifies transcriptional phenotypes of sputum samples from normal volunteers and atopic asthmatics exposed to ozone. Network analyses suggest that asthmatics elevate immune signaling following oxidative stress, while nonasthmatics attempt to mitigate the ozone-induced response.
Asthma; Ozone; Induced Sputum; Profiling; Oxidative Stress
In many biomedical studies, it is common that due to budget constraints, the primary covariate is only collected in a randomly selected subset from the full study cohort. Often, there is an inexpensive auxiliary covariate for the primary exposure variable that is readily available for all the cohort subjects. Valid statistical methods that make use of the auxiliary information to improve study efficiency need to be developed. To this end, we develop an estimated partial likelihood approach for correlated failure time data with auxiliary information. We assume a marginal hazard model with common baseline hazard function. The asymptotic properties for the proposed estimators are developed. The proof of the asymptotic results for the proposed estimators is nontrivial since the moments used in estimating equation are not martingale-based and the classical martingale theory is not sufficient. Instead, our proofs rely on modern empirical theory. The proposed estimator is evaluated through simulation studies and is shown to have increased efficiency compared to existing methods. The proposed methods are illustrated with a data set from the Framingham study.
Marginal hazard model; Correlated failure time; Validation set; Auxiliary covariate
Exposure to ozone activates innate immune function and causes neutrophilic (PMN) airway inflammation that in some individuals is robustly elevated. The interplay between immuno-inflammatory function and genomic signaling in those with heightened inflammatory responsiveness to ozone is not well understood.
Determine baseline predictors and post exposure discriminators for the immuno-inflammatory response to ozone in inflammatory responsive adult volunteers.
Sputum induction was performed on 27 individuals before and after a two hour chamber exposure to 0.4 ppm ozone. Subjects were classified as inflammatory responders or non-responders to ozone based on their PMN response. Innate immune function, inflammatory cell and cytokine modulation and transcriptional signaling pathways were measured in sputum.
Post exposure, responders showed activated innate immune function (CD16: 31,004 MFI vs 8988 MFI; CD11b: 44,986 MFI vs 24,770 MFI; CD80: 2236 MFI vs 1506 MFI; IL-8: 37,603 pg/ml vs 2828 pg/ml; and IL-1β: 1380 pg/ml vs 318 pg/ml) with muted signaling of immune cell trafficking pathways. In contrast, non-responders displayed decreased innate immune activity (CD16, CD80; phagocytosis: 2 particles/PMN vs 4 particles/PMN) post exposure that was accompanied by a heightened signaling of immune cell trafficking pathways.
Inflammatory responsive and non responsive individuals to ozone show an inverse relationship between immune cell trafficking and immuno-inflammatory functional responses to ozone. These distinct genomic signatures may further our understanding about ozone-induced morbidity in individuals with different levels of inflammatory responsiveness.
Air pollution; Environment; Ozone; Gene expression; Human sputum; Immune response; Innate immunity; Systems biology
The outcome dependent sampling scheme has been gaining attention in both the statistical literature and applied fields. Epidemiological and environmental researchers have been using it to select the observations for more powerful and cost-effective studies. Motivated by a study of the effect of in utero exposure to polychlorinated biphenyls on children’s IQ at age 7, in which the effect of an important confounding variable is nonlinear, we consider a semi-parametric regression model for data from an outcome-dependent sampling scheme where the relationship between the response and covariates is only partially parameterized. We propose a penalized spline maximum likelihood estimation (PSMLE) for inference on both the parametric and the nonparametric components and develop their asymptotic properties. Through simulation studies and an analysis of the IQ study, we compare the proposed estimator with several competing estimators. Practical considerations of implementing those estimators are discussed.
Outcome dependent sampling; Estimated likelihood; Semiparametric method; Penalized spline
The outcome-dependent sampling (ODS) design, which allows observation of exposure variable to depend on the outcome, has been shown to be cost efficient. In this article, we propose a new statistical inference method, an estimated penalized likelihood method, for a partial linear model in the setting of a 2-stage ODS with a continuous outcome. We develop the asymptotic properties and conduct simulation studies to demonstrate the performance of the proposed estimator. A real environmental study data set is used to illustrate the proposed method.
Biased sampling; Partial linear model; P-spline; Validation sample; 2-stage
Two-stage design has long been recognized to be a cost-effective way for conducting biomedical studies. In many trials, auxiliary covariate information may also be available, and it is of interest to exploit these auxiliary data to improve the efficiency of inferences. In this paper, we propose a 2-stage design with continuous outcome where the second-stage data is sampled with an “outcome-auxiliary-dependent sampling” (OADS) scheme. We propose an estimator which is the maximizer for an estimated likelihood function. We show that the proposed estimator is consistent and asymptotically normally distributed. The simulation study indicates that greater study efficiency gains can be achieved under the proposed 2-stage OADS design by utilizing the auxiliary covariate information when compared with other alternative sampling schemes. We illustrate the proposed method by analyzing a data set from an environmental epidemiologic study.
Auxiliary covariate; Kernel smoothing; Outcome-auxiliary-dependent sampling; 2-stage sampling design
Nitric oxide (NO) is a reactive gas generated by inflammatory cells and mucosal epithelial cells of the nose and paranasal sinuses and is an important mediator in nonspecific host defense against infectious agents. However, NO also mediates physiologic events such as vasodilation, mucus hypersecretion, and mucosal disruption that are associated with inflammatory conditions, and it is a regulator of ciliary beat frequency. In the present study, we hypothesized that lifestyle exposure to tobacco smoke, whether through active smoking or by inadvertent exposure to secondhand tobacco smoke, would result in higher detectable levels of nasal NO (nNO) than are found in well-documented nonsmokers.
Nasal NO measurements were obtained concomitant with assays of urine cotinine from well-documented nonsmokers, active smokers, and individuals exposed by lifestyle to secondhand smoke. These parameters were statistically analyzed to determine whether increasing levels of tobacco smoke exposure yield higher concentrations of nNO.
Our results and subsequent statistical analyses imply that active smokers who exhibit high urine cotinine levels exhibit significant increases in nNO levels in comparison to both nonsmokers and nonsmokers exposed to secondhand smoke.
There is an increased level of nNO associated with tobacco smoke exposure that may contribute to the inflammatory processes characteristic of disease pathogenesis in smokers.
inflammation; nitric oxide; secondhand smoke; tobacco smoke
Oxidative stress plays a significant role in allergic airway inflammation. Supplementation with alpha-tocopherol (alone or combined with ascorbate/vitamin C) has been assessed as an intervention for allergic airway diseases with conflicting results. Enhancing levels of airway antioxidants with oral supplements has been suggested as an intervention to protect individuals from the effect of inhaled oxidants, although it is unclear whether supplementation changes tocopherol or vitamin C levels in both serum and airway fluids. Our objective was to obtain pilot safety and dosing data from 14 allergic asthmatic volunteers examining the effect of daily combination oral therapy with 500 mg alpha-tocopherol (αT) and 2 g vitamin C for 12 wk. We examined serum and airway fluid and cellular levels of alpha- and gamma-tocopherol (γT) and vitamin C to plan for future studies of these agents in asthma and allergic rhinitis. Six volunteers completed 12 wk of active treatment with αT and vitamin C and 8 completed placebo. Blood and sputum samples were obtained at baseline and at 6 wk and 12 wk of therapy and were analyzed for αT, γT, and vitamin C levels in the serum, sputum supernatant, and sputum cells. Combination treatment increased serum vitamin C and significantly decreased sputum αT and serum γT levels. No changes were found in sputum supernatant or sputum cell vitamin C or serum αT levels in the active treatment group. In conclusion, supplementation with αT and high-dose vitamin C does not augment vitamin C levels in the respiratory-tract lining fluid.
We consider statistical inference on a regression model in which some covariables are measured with errors together with an auxiliary variable. The proposed estimation for the regression coefficients is based on some estimating equations. This new method alleates some drawbacks of previously proposed estimations. This includes the requirment of undersmoothing the regressor functions over the auxiliary variable, the restriction on other covariables which can be observed exactly, among others. The large sample properties of the proposed estimator are established. We further propose a jackknife estimation, which consists of deleting one estimating equation (instead of one obervation) at a time. We show that the jackknife estimator of the regression coefficients and the estimating equations based estimator are asymptotically equivalent. Simulations show that the jackknife estimator has smaller biases when sample size is small or moderate. In addition, the jackknife estimation can also provide a consistent estimator of the asymptotic covariance matrix, which is robust to the heteroscedasticity. We illustrate these methods by applying them to a real data set from marketing science.
Linear regression model; noised variable; measurement error; auxiliary variable; estimating equation; jackknife estimation; asymptotic normality
Recurrent events are frequently encountered in biomedical studies. Evaluating the covariates effects on the marginal recurrent event rate is of practical interest. There are mainly two types of rate models for the recurrent event data: the multiplicative rates model and the additive rates model. We consider a more flexible additive–multiplicative rates model for analysis of recurrent event data, wherein some covariate effects are additive while others are multiplicative. We formulate estimating equations for estimating the regression parameters. The estimators for these regression parameters are shown to be consistent and asymptotically normally distributed under appropriate regularity conditions. Moreover, the estimator of the baseline mean function is proposed and its large sample properties are investigated. We also conduct simulation studies to evaluate the finite sample behavior of the proposed estimators. A medical study of patients with cystic fibrosis suffered from recurrent pulmonary exacerbations is provided for illustration of the proposed method.
Recurrent events; Rate regression; Additive–multiplicative rates model; Counting process; Empirical process
The emergence of air-liquid interface (ALI) culturing of mammalian airway epithelium is a recent innovation for experimental modeling of airway epithelial development, function, and pathogenic mechanisms associated with infectious agent and irritant exposure. This construct provides an experimental platform for in vitro propagation, manipulation, and testing of airway epithelium in a structural and physiologic state that emulates in vivo organization. In this study, we have cultured nasal epithelial biopsies from human subjects with variable histories of tobacco smoke exposure and assessed ciliary beat frequency (CBF) after an extended interval in vitro relative to CBF determined on biopsies from the same subjects immediately upon acquisition. We observed elevated CBF in nasal epithelial biopsies as well as persistence of accelerated CBF in ALI cultures deriving from biopsies of smokers and non-smokers exposed to environmental tobacco smoke compared to CBF in cultures from biopsies of well-documented non-smokers. Moreover, cultures deriving from smokers exhibited reduced ciliation as the cultures matured. These studies document that nasal epithelium cultured in the ALI system retains physiologic and phenotypic characteristics of the epithelial layer in vivo even through rounds of proliferative expansion. These observations suggest that stable epigenetic factors affecting regulation of ciliary function and phenotype commitment may be operative.
Cilia; Epithelium; Tobacco smoke; Inhalation toxicology; Cell culture
How to take advantage of the available auxiliary covariate information when the primary covariate of interest is not measured is a frequently encountered question in biomedical study. In this paper, we consider the multivariate failure times regression analysis in which the primary covariate is assessed only in a validation set but a continuous auxiliary covariate for it is available for all subjects in the study cohort. Under the frame of marginal hazard model, we propose to estimate the induced relative risk function in the nonvalidation set through kernel smoothing method and then obtain an estimated pseudo-partial likelihood function. The proposed estimated pseudo-partial likelihood estimator is shown to be consistent and asymptotically normal. We also give an estimator of the marginal cumulative baseline hazard function. Simulations are conducted to evaluate the finite sample performance of our proposed estimator. The proposed method is illustrated by analyzing a heart disease data from Studies of Left Ventricular Dysfunction (SOLVD).
Multivariate Failure Times; Auxiliary Covariate; Pseudo-Partial Likelihood; Kernel Smoothing; Validation Sample
CD14, a co-receptor for endotoxin, plays a significant role in the inflammatory response to this environmentally important pollutant. The C-159T single nucleotide polymorphism (SNP) in the CD14 gene promoter is reported to affect expression of CD14, with TT homozygous persons having higher CD14 expression. This SNP has been linked to pathogenesis of asthma and with cardiovascular diseases in smokers. We hypothesize that CD14 also plays a role in development of COPD in smokers who are exposed to inhaled endotoxin by cigarette smoking and to endotoxin released from Gram-negative microbes colonizing their airways. To assess the effect of the C-159T SNP of the CD14 gene promoter on lung function and GOLD score in smokers with COPD, we recruited 246 smokers with COPD with a range of 10–156 pack-year smoking exposures. We found that the C-159T single gene polymorphism of the CD14 gene promoter may play a role in modulating severity of obstructive impairment in smokers with COPD: The TT genotype was associated with lower lung function in smokers with a moderate smoking history. However, the CC genotype was associated with decreased lung function in heavy smokers (>56 pack-years). The result on CC genotype in risk for COPD is analogous with the effect of this genotype in risk for asthma. CD14 may be a factor in the pathophysiology of COPD, as it is in asthma and smoking-related cardiovascular diseases.
Modified function of immune cells in nasal secretions may play a role in the enhanced susceptibility to respiratory viruses that is seen in smokers. Innate immune cells in nasal secretions have largely been characterized by cellular differentials using morphologic criteria alone, which have successfully identified neutrophils as a significant cell population within nasal lavage fluid (NLF) cells. However, flow cytometry may be a superior method to fully characterize NLF immune cells. We therefore characterized immune cells in NLF by flow cytometry, determined the effects of live attenuated influenza virus (LAIV) on NLF and peripheral blood immune cells, and compared responses in samples obtained from smokers and nonsmokers.
In a prospective observational study, we characterized immune cells in NLF of nonsmokers at baseline using flow cytometry and immunohistochemistry. Nonsmokers and smokers were inoculated with LAIV on day 0 and serial nasal lavages were collected on days 1-4 and day 9 post-LAIV. LAIV-induced changes of NLF cells were characterized using flow cytometry. Cell-free NLF was analyzed for immune mediators by bioassay. Peripheral blood natural killer (NK) cells from nonsmokers and smokers at baseline were stimulated in vitro with LAIV followed by flow cytometric and mediator analyses.
CD45(+)CD56(-)CD16(+) neutrophils and CD45(+)CD56(+) NK cells comprised median 4.62% (range 0.33-14.52) and 23.27% (18.29-33.97), respectively, of non-squamous NLF cells in nonsmokers at baseline. LAIV did not induce changes in total NK cell or neutrophil percentages in either nonsmokers or smokers. Following LAIV inoculation, CD16(+) NK cell percentages and granzyme B levels increased in nonsmokers, and these effects were suppressed in smokers. LAIV inoculation enhanced expression of activating receptor NKG2D and chemokine receptor CXCR3 on peripheral blood NK cells from both nonsmokers and smokers in vitro but did not induce changes in CD16(+) NK cells or granzyme B activity in either group.
These data are the first to identify NK cells as a major immune cell type in the NLF cell population and demonstrate that mucosal NK cell cytotoxic function is suppressed in smokers following LAIV. Altered NK cell function in smokers suggests a potential mechanism that may enhance susceptibility to respiratory viruses.
The Glutathione-S-Transferase Mu 1 null genotype has been reported to be a risk factor for acute respiratory disease associated with increases in ambient air ozone. Ozone is known to cause an immediate decrease in lung function and increased airway inflammation. However, it is not known if GSTM1 modulates these ozone responses in vivo in humans
The purpose of this study was to determine if the GSTM1 null genotype modulates ozone responses in humans.
Thirty-five normal volunteers were genotyped for the GSTM1 null mutation and underwent a standard ozone exposure protocol to determine if lung function and inflammatory responses to ozone were different between the 19 GSTM1 normal and 16 GSTM1 null volunteers.
GSTM1 did not modulate lung function responses to acute ozone. Granulocyte influx 4 hours after challenge was similar between GSTM1 normal and null volunteers. However, GSTM1 null volunteers had significantly increased airway neutrophils 24 hours after challenge, as well as increased expression of HLA-DR on airway macrophages and dendritic cells.
The GSTM1 null genotype is associated with increased airways inflammation 24 hours following ozone exposure, consistent with the lag time observed between increased ambient air ozone exposure and exacerbations of lung disease.
These observations suggest that the GSTM1 null genotype likely confers increased risk for exacerbation of ozone-induced lung disease through promoting an enhanced neutrophilic and monocytic inflammatory response to ozone.
The GSTM1 null genotype is associated with increased risk for ozone-induced lung disease. We report the GSTM1 genotype modulates ozone-induced inflammation but not lung function, and may predict persons at risk for environmental lung disease.
Glutathione-S-Transferase Mu 1; Ozone; Pollution; Inflammation; Polymorphonuclear Neutrophil; Macrophage; Dendritic cell
Epidemiologic evidence links tobacco smoke and increased risk for influenza in humans, but the specific host defense pathways involved are unclear.
We developed a model to examine influenza-induced innate immune responses in humans and test the hypothesis that exposure to cigarette smoke alters nasal inflammatory and antiviral responses to live attenuated influenza virus (LAIV).
This was an observational cohort study comparing nasal mucosal responses to LAIV among young adult active smokers (n = 17), nonsmokers exposed to secondhand smoke (SHS; n = 20), and unexposed controls (n = 23). Virus RNA and inflammatory factors were measured in nasal lavage fluids (NLF) serially after LAIV inoculation. For key end points, peak and total (area under curve) responses were compared among groups.
Compared with controls, NLF interleukin-6 (IL-6) responses to LAIV (peak and total) were suppressed in smokers. Virus RNA in NLF cells was significantly increased in smokers, as were interferon-inducible protein 10:virus ratios. Responses in SHS-exposed subjects were generally intermediate between controls and smokers. We observed significant associations between urine cotinine and NLF IL-6 responses (negative correlation) or virus RNA in NLF cells (positive correlation) for all subjects combined.
Nasal inoculation with LAIV results in measurable inflammatory and antiviral responses in human volunteers, thus providing a model for investigating environmental effects on influenza infections in humans. Exposure to cigarette smoke was associated with suppression of specific nasal inflammatory and antiviral responses, as well as increased virus quantity, after nasal inoculation with LAIV. These data suggest mechanisms for increased susceptibility to influenza infection among persons exposed to tobacco smoke.
influenza; interferon-inducible protein 10; interleukin-6; tobacco smoke; virus clearance
As biological studies become more expensive to conduct, statistical methods that take advantage of existing auxiliary information about an expensive exposure variable are desirable in practice. Such methods should improve the study efficiency and increase the statistical power for a given number of assays. In this paper, we consider an inference procedure for multivariate failure time with auxiliary covariate information. We propose an estimated pseudo-partial likelihood estimator under the marginal hazard model framework and develop the asymptotic properties for the proposed estimator. We conduct simulation studies to evaluate the performance of the proposed method in practical situations and demonstrate the proposed method with a data set from the Studies of Left Ventricular Dysfunction (SOLVD,1991).
Auxiliary covariate; Marginal hazard model; Multivariate data; Pseudo-partial likelihood; Validation sample