Faculty Bibliography

The chitinase-like protein YKL-40 mediates airway inflammation and serum levels are associated with asthma severity. However, asthma phenotypes associated with YKL-40 levels have not been precisely defined.We conducted an unsupervised cluster analysis of asthma patients treated at the Yale Center for Asthma and Airways Disease (n=156) to identify subgroups according to YKL-40 level. The resulting YKL-40 clusters were cross-validated in cohorts from the Severe Asthma Research Programme (n=167) and the New York University/Bellevue Asthma Repository (n=341). A sputum transcriptome analysis revealed molecular pathways associated with YKL-40 subgroups.Four YKL-40 clusters (C1-C4) were identified. C3 and C4 had high serum YKL-40 levels compared with C1 and C2. C3 was associated with earlier onset and longer duration of disease, severe airflow obstruction, and near-fatal asthma exacerbations. C4 had the highest serum YKL-40 levels, adult onset and less airflow obstruction, but frequent exacerbations. An airway transcriptome analysis in C3 and C4 showed activation of non-type 2 inflammatory pathways.Elevated serum YKL-40 levels were associated with two distinct clinical asthma phenotypes: one with irreversible airway obstruction and another with severe exacerbations. The YKL-40 clusters are potentially useful for identification of individuals with severe or exacerbation-prone asthma.

The feasibility of using mobile health applications to conduct observational clinical studies requires rigorous validation. Here, we report initial findings from the Asthma Mobile Health Study, a research study, including recruitment, consent, and enrollment, conducted entirely remotely by smartphone. We achieved secure bidirectional data flow between investigators and 7,593 participants from across the United States, including many with severe asthma. Our platform enabled prospective collection of longitudinal, multidimensional data (e.g., surveys, devices, geolocation, and air quality) in a subset of users over the 6-month study period. Consistent trending and correlation of interrelated variables support the quality of data obtained via this method. We detected increased reporting of asthma symptoms in regions affected by heat, pollen, and wildfires. Potential challenges with this technology include selection bias, low retention rates, reporting bias, and data security. These issues require attention to realize the full potential of mobile platforms in research and patient care.

In our recent Asthma Mobile Health Study (AMHS), thousands of asthma patients across the country contributed medical data through the iPhone Asthma Health App on a daily basis for an extended period of time. The collected data included daily self-reported asthma symptoms, symptom triggers, and real time geographic location information. The AMHS is just one of many studies occurring in the context of now many thousands of mobile health apps aimed at improving wellness and better managing chronic disease conditions, leveraging the passive and active collection of data from mobile, handheld smart devices. The ability to identify patient groups or patterns of symptoms that might predict adverse outcomes such as asthma exacerbations or hospitalizations from these types of large, prospectively collected data sets, would be of significant general interest. However, conventional clustering methods cannot be applied to these types of longitudinally collected data, especially survey data actively collected from app users, given heterogeneous patterns of missing values due to: 1) varying survey response rates among different users, 2) varying survey response rates over time of each user, and 3) non-overlapping periods of enrollment among different users. To handle such complicated missing data structure, we proposed a probability imputation model to infer missing data. We also employed a consensus clustering strategy in tandem with the multiple imputation procedure. Through simulation studies under a range of scenarios reflecting real data conditions, we identified favorable performance of the proposed method over other strategies that impute the missing value through low-rank matrix completion. When applying the proposed new method to study asthma triggers and symptoms collected as part of the AMHS, we identified several patient groups with distinct phenotype patterns. Further validation of the methods described in this paper might be used to identify clinically important patterns in large data sets with complicated missing data structure, improving the ability to use such data sets to identify at-risk populations for potential intervention.

Background. Exposure to World Trade Center (WTC) dust and fumes is associated with the onset of asthma-like respiratory symptoms in rescue and recovery workers and exposed community members. Eosinophilic inflammation with increased lung and peripheral eosinophils has been described in subpopulations with asthma. We hypothesized that persistent asthma-like symptoms in WTC-exposed individuals would be associated with systemic inflammation characterized by peripheral eosinophils. Methods. The WTC Environmental Health Center (WTC EHC) is a treatment program for local residents, local workers, and cleanup workers with presumed WTC-related symptoms. Patients undergo a standardized evaluation including questionnaires and complete blood count. Between September 2005 and March 2009, 2462 individuals enrolled in the program and were available for analysis. Individuals with preexisting respiratory symptoms or lung disease diagnoses prior to September 2001 and current or significant tobacco use were excluded, Results. One thousand five hundred and seventeen individuals met the inclusion criteria. Patients had a mean age of 47 years, were mostly female (51%), and had a diverse race/ethnicity. Respiratory symptoms that developed after WTC dust/fume exposure and remained persistent included dyspnea on exertion (68%), cough (57%), chest tightness (47%), and wheeze (33%). A larger percentage of patients with wheeze had elevated peripheral eosinophils compared with those without wheeze (21% vs. 13%, p < .0001). Individuals with elevated peripheral eosinophils were more likely to have airflow obstruction on spirometry (16% vs. 7%, p = .0003). Conclusion. Peripheral eosinophils were associated with wheeze and airflow obstruction in a diverse WTC-exposed population. These data suggest that eosinophils may participate in lung inflammation in this population with symptoms consistent with WTC-related asthma.

Rationale: Asthma is a chronic inflammatory disease of the airway influenced by genetic variants, environmental factors, and their interactions. Variants of the interleukin-1 receptor antagonist (IL1RN) gene, encoding an anti-inflammatory cytokine, are associated with asthma. We investigated the gene-environment interactions of childhood environmental tobacco smoke (ETS) exposure with IL1RN genotypes of single-nucleotide polymorphisms (SNPs) for asthma susceptibility in an urban adult population. Methods: DNA samples from the NYU/Bellevue Asthma Registry (NYUBAR) were genotyped for six tag SNPs in IL1RN in 259 asthma cases and 182 unrelated healthy controls. Information about childhood ETS exposure and age at onset for doctor diagnosed asthma were collected. Logistic regression was used to assess associations of IL1RN variants (alleles, genotypes, haplotypes) with asthma, adjusting for population admixture and other factors and covariates. Gene-environment interactions (GEIs) for the risk of asthma and early onset asthma were evaluated via stratification on childhood ETS exposure (with/without) and on IL1RN SNP genotypes (rare/common), respectively. Visible patterns of GEIs were displayed using stratified Kaplan-Meier curves for age of asthma onset. Results: Allelic and genotypic association analyses of the IL1RN tag SNPs and asthma susceptibility for the NYUBAR population as a whole resulted in findings that were in accordance with previous publications with protective effects of rare genotypes of candidate SNPs. Stratified analyses based on ETS exposure status indicated that the protective effects of rare genotypes of tag SNPs (e.g. GG in SNP rs392503) were significant only within the groups without childhood ETS exposure (OR=0.179, P=0.009); in contrast, there was a significantly elevated risk for early onset asthma among rare-genotype carriers with ETS exposure (OR=4.02, P=0.019). Importantly, whereas childhood ETS exposure was a risk factor for early onset asthma across all genotype groups of IL1RN (OR=1.74, P=0.03), it dramatically increased the risk within the group carrying rare SNP genotypes of IL1RN with the observed odds ratios (ORs) in the range between 7.3 and 9.1 (Fisher exact P-values<0.05). Conclusion: Analysis of gene-environment interactions between ETS exposure and IL1RN variants indicated that, at population level, childhood ETS exposure disrupted the protective effect of rare tag SNP genotypes of IL1RN for asthma and turned them into high risk genotypes for early onset asthma

The American Lung Association Asthma Clinical Research Centers (ALA-ACRC) is a research network focused on performing clinical trials that directly affect medical care for adults and children with asthma. The group of eighteen clinical research centers and a data-coordinating center perform studies supported by the American Lung Association, the National Institute of Health/National Heart Lung and Blood Institute (NIH/NHLBI), and partnership with industry. The network has completed and published eight clinical trials (seven randomized control trials and one validation study of a diagnostic tool), numerous ancillary studies, and has four ongoing trials at the time of publication of this review. The network's trials have focused on areas such as the relative merits of different adjunctive treatments for asthma not controlled on inhaled corticosteroids (ICS) alone, the effect of treatment of comorbid diseases on asthma care, and studies evaluating techniques used in the conduct of clinical trials of treatments for asthma. This review will describe the accomplishments of our network to date and the effect of those accomplishments on asthma care. 2012 Springer Science+Business Media, LLC

PURPOSE OF REVIEW: Guidelines suggest that asthma medication should be reduced once asthma control is sustained. Moderate-dose inhaled corticosteroids (ICS) can typically be reduced, but questions remain about the lowest effective ICS dose and the role of non-ICS controllers in treatment reduction. Long-acting beta agonist (LABA) safety concerns have created controversy about how to step down patients on ICS/LABA therapy. This review will focus on the current status of these issues. RECENT FINDINGS: Intermittent ICS treatment, often in fixed combination with short-acting beta agonist, is an emerging strategy for control of mild asthma. Addition of leukotriene modifiers, LABAs, and omalizumab to ICS can allow for reduced ICS dosing. Doses of ICS that control symptoms may be inadequate to control exacerbations. Reducing ICS dose before discontinuing LABAs may be the more effective approach for patients on combination therapy. SUMMARY: Use of non-ICS controllers allows for ICS dose reduction with superior outcomes. Tapering of ICS prior to LABA discontinuation may be the favored approach for patients on ICS/LABA therapy, but an understanding of long-term outcomes and further safety data are required. The lowest ICS dose that adequately controls both asthma impairment and risk remains to be determined