Association of mold levels in urban children's homes with difficult-to-control asthma.

BACKGROUND: Mold sensitization and exposure are associated with asthma severity, but the specific species that contribute to difficult-to-control (DTC) asthma are unknown. OBJECTIVE: We sought to determine the association between overall and specific mold levels in the homes of urban children and DTC asthma. METHODS: The Asthma Phenotypes in the Inner-City study recruited participants, aged 6 to 17 years, from 8 US cities and classified each participant as having either DTC asthma or easy-to-control (ETC) asthma on the basis of treatment step level. Dust samples had been collected in each participant's home (n = 485), and any dust remaining (n = 265 samples), after other analyses, was frozen at -20oC. The dust samples (n = 265) were analyzed using quantitative PCR to determine the concentrations of the 36 molds in the Environmental Relative Moldiness Index. Logistic regression was performed to discriminate specific mold content of dust from homes of children with DTC versus ETC asthma. RESULTS: Frozen-dust samples were available from 54% of homes of children with DTC (139 of 253) and ETC asthma (126 of 232). Only the average concentration of the mold Mucor was significantly (P < .001) greater in homes of children with DTC asthma. In homes with window air-conditioning units, the Mucor concentration contributed about a 22% increase (1.6 odds ratio; 95% CI, 1.2-2.2) in the ability to discriminate between cases of DTC and ETC asthma. CONCLUSIONS: Mucor levels in the homes of urban youth were a predictor of DTC asthma, and these higher Mucor levels were more likely in homes with a window air-conditioner.

Development of a Rhinovirus Inoculum Using a Reverse Genetics Approach.

BACKGROUND: Experimental inoculation is an important tool for common cold and asthma research. Producing rhinovirus (RV) inocula from nasal secretions has required prolonged observation of the virus donor to exclude extraneous pathogens. We produced a RV-A16 inoculum using reverse genetics and determined the dose necessary to cause moderate colds in seronegative volunteers. METHODS: The consensus sequence of RV-A16 from a previous inoculum was cloned, and inoculum virus was produced using reverse genetics techniques. After safety testing, volunteers were inoculated with either RV-A16 (n = 26) or placebo (n = 10), Jackson cold scores were recorded, and nasal secretions were tested for shedding of RV-A16 ribonucleic acid. RESULTS: The reverse genetics process produced infectious virus that was neutralized by specific antisera and had a mutation rate similar to conventional virus growth techniques. The 1000 median tissue culture infectious dose (TCID50) dose produced moderate colds in most individuals with effects similar to that of a previously tested conventional RV-A16 inoculum. CONCLUSIONS: Reverse genetics techniques produced a RV-A16 inoculum that can cause clinical colds in seronegative volunteers, and they also serve as a stable source of virus for laboratory use. The recombinant production procedures eliminate the need to derive seed virus from nasal secretions, thus precluding introduction of extraneous pathogens through this route.

Asthma phenotypes in inner-city children.

BACKGROUND: Children with asthma in low-income urban areas have high morbidity. Phenotypic analysis in these children is lacking, but may identify characteristics to inform successful tailored management approaches. OBJECTIVE: We sought to identify distinct asthma phenotypes among inner-city children receiving guidelines-based management. METHODS: Nine inner-city asthma consortium centers enrolled 717 children aged 6 to 17 years. Data were collected at baseline and prospectively every 2 months for 1 year. Participants' asthma and rhinitis were optimally managed by study physicians on the basis of guidelines. Cluster analysis using 50 baseline and 12 longitudinal variables was performed in 616 participants completing 4 or more follow-up visits. RESULTS: Five clusters (designated A through E) were distinguished by indicators of asthma and rhinitis severity, pulmonary physiology, allergy (sensitization and total serum IgE), and allergic inflammation. In comparison to other clusters, cluster A was distinguished by lower allergy/inflammation, minimally symptomatic asthma and rhinitis, and normal pulmonary physiology. Cluster B had highly symptomatic asthma despite high step-level treatment, lower allergy and inflammation, and mildly altered pulmonary physiology. Cluster C had minimally symptomatic asthma and rhinitis, intermediate allergy and inflammation, and mildly impaired pulmonary physiology. Clusters D and E exhibited progressively higher asthma and rhinitis symptoms and allergy/inflammation. Cluster E had the most symptomatic asthma while receiving high step-level treatment and had the highest total serum IgE level (median, 733 kU/L), blood eosinophil count (median, 400 cells/mm3), and allergen sensitizations (15 of 22 tested). CONCLUSIONS: Allergy distinguishes asthma phenotypes in urban children. Severe asthma often coclusters with highly allergic children. However, a symptomatic phenotype with little allergy or allergic inflammation was identified.

Distinguishing characteristics of difficult-to-control asthma in inner-city children and adolescents.

BACKGROUND: Treatment levels required to control asthma vary greatly across a population with asthma. The factors that contribute to variability in treatment requirements of inner-city children have not been fully elucidated. OBJECTIVE: We sought to identify the clinical characteristics that distinguish difficult-to-control asthma from easy-to-control asthma. METHODS: Asthmatic children aged 6 to 17 years underwent baseline assessment and bimonthly guideline-based management visits over 1 year. Difficult-to-control and easy-to-control asthma were defined as daily therapy with 500 µg of fluticasone or greater with or without a long-acting ß-agonist versus 100 µg or less assigned on at least 4 visits. Forty-four baseline variables were used to compare the 2 groups by using univariate analyses and to identify the most relevant features of difficult-to-control asthma by using a variable selection algorithm. Nonlinear seasonal variation in longitudinal measures (symptoms, pulmonary physiology, and exacerbations) was examined by using generalized additive mixed-effects models. RESULTS: Among 619 recruited participants, 40.9% had difficult-to-control asthma, 37.5% had easy-to-control asthma, and 21.6% fell into neither group. At baseline, FEV1 bronchodilator responsiveness was the most important characteristic distinguishing difficult-to-control asthma from easy-to-control asthma. Markers of rhinitis severity and atopy were among the other major discriminating features. Over time, difficult-to-control asthma was characterized by high exacerbation rates, particularly in spring and fall; greater daytime and nighttime symptoms, especially in fall and winter; and compromised pulmonary physiology despite ongoing high-dose controller therapy. CONCLUSIONS: Despite good adherence, difficult-to-control asthma showed little improvement in symptoms, exacerbations, or pulmonary physiology over the year. In addition to pulmonary physiology measures, rhinitis severity and atopy were associated with high-dose asthma controller therapy requirement.

Pathways through which asthma risk factors contribute to asthma severity in inner-city children.

BACKGROUND: Pathway analyses can be used to determine how host and environmental factors contribute to asthma severity. OBJECTIVE: To investigate pathways explaining asthma severity in inner-city children. METHODS: On the basis of medical evidence in the published literature, we developed a conceptual model to describe how 8 risk-factor domains (allergen sensitization, allergic inflammation, pulmonary physiology, stress, obesity, vitamin D, environmental tobacco smoke [ETS] exposure, and rhinitis severity) are linked to asthma severity. To estimate the relative magnitude and significance of hypothesized relationships among these domains and asthma severity, we applied a causal network analysis to test our model in an Inner-City Asthma Consortium study. Participants comprised 6- to 17-year-old children (n = 561) with asthma and rhinitis from 9 US inner cities who were evaluated every 2 months for 1 year. Asthma severity was measured by a longitudinal composite assessment of day and night symptoms, exacerbations, and controller usage. RESULTS: Our conceptual model explained 53.4% of the variance in asthma severity. An allergy pathway (linking allergen sensitization, allergic inflammation, pulmonary physiology, and rhinitis severity domains to asthma severity) and the ETS exposure pathway (linking ETS exposure and pulmonary physiology domains to asthma severity) exerted significant effects on asthma severity. Among the domains, pulmonary physiology and rhinitis severity had the largest significant standardized total effects on asthma severity (-0.51 and 0.48, respectively), followed by ETS exposure (0.30) and allergic inflammation (0.22). Although vitamin D had modest but significant indirect effects on asthma severity, its total effect was insignificant (0.01). CONCLUSIONS: The standardized effect sizes generated by a causal network analysis quantify the relative contributions of different domains and can be used to prioritize interventions to address asthma severity.