Ann Chen Wu

Predictors of Symptoms Are Different From Predictors of Severe Exacerbations From Asthma in Children

BACKGROUND Asthma therapy is typically prescribed and titrated based on patient or parent self-report of symptoms. No longitudinal studies have assessed the relationship between symptoms and severe asthma exacerbations in children. The goal of our study was (1) to assess the association of asthma symptoms with severe asthma exacerbations and (2) to compare predictors of persistent asthma symptoms and predictors of severe asthma exacerbations. METHODS The Childhood Asthma Management Program was a multicenter clinical trial of 1,041 children randomized to receive budesonide, nedocromil, or placebo (as-needed β-agonist). We conducted a post hoc analysis of diary cards that were completed by subjects on a daily basis to categorize subjects as having persistent vs intermittent symptoms. We defined a severe asthma exacerbation as an episode requiring ≥ 3 days use of oral corticosteroids, hospitalization, or ED visit due to asthma based on self-report at study visits every 4 months. RESULTS While accounting for longitudinal measures, having persistent symptoms from asthma was significantly associated with having severe asthma exacerbations. Predictors of having persistent symptoms compared with intermittent symptoms included not being treated with inhaled corticosteroids, lower FEV(1)/FVC ratio, and a lower natural logarithm of provocative concentration of methacholine producing a 20% decline in FEV(1) (lnPC(20)). Predictors of having one or more severe asthma exacerbations included younger age, history of hospitalization or ED visit in the prior year, ≥ 3 days use of oral corticosteroids in the prior 3 months, lower FEV(1)/FVC ratio, lower lnPC(20), and higher logarithm to the base 10 eosinophil count; treatment with inhaled corticosteroids was predictive of having no severe asthma exacerbations. CONCLUSIONS Patients with persistent symptoms from asthma were more likely to experience severe asthma exacerbations. Nevertheless, demographic and laboratory predictors of having persistent symptoms are different from predictors of severe asthma exacerbations. Although symptoms and exacerbations are closely related, their predictors are different. The current focus of the National Asthma Education and Prevention Program guidelines on the two separate domains of asthma control, impairment and risk, are supported by our analysis.

Genome-Wide Association Analysis in Asthma Subjects Identifies SPATS2L as a Novel Bronchodilator Response Gene

Bronchodilator response (BDR) is an important asthma phenotype that measures reversibility of airway obstruction by comparing lung function (i.e. FEV1) before and after the administration of a short-acting β2-agonist, the most common rescue medications used for the treatment of asthma. BDR also serves as a test of β2-agonist efficacy. BDR is a complex trait that is partly under genetic control. A genome-wide association study (GWAS) of BDR, quantified as percent change in baseline FEV1 after administration of a β2-agonist, was performed with 1,644 non-Hispanic white asthmatic subjects from six drug clinical trials: CAMP, LOCCS, LODO, a medication trial conducted by Sepracor, CARE, and ACRN. Data for 469,884 single-nucleotide polymorphisms (SNPs) were used to measure the association of SNPs with BDR using a linear regression model, while adjusting for age, sex, and height. Replication of primary P-values was attempted in 501 white subjects from SARP and 550 white subjects from DAG. Experimental evidence supporting the top gene was obtained via siRNA knockdown and Western blotting analyses. The lowest overall combined P-value was 9.7E-07 for SNP rs295137, near the SPATS2L gene. Among subjects in the primary analysis, those with rs295137 TT genotype had a median BDR of 16.0 (IQR = [6.2, 32.4]), while those with CC or TC genotypes had a median BDR of 10.9 (IQR = [5.0, 22.2]). SPATS2L mRNA knockdown resulted in increased β2-adrenergic receptor levels. Our results suggest that SPATS2L may be an important regulator of β2-adrenergic receptor down-regulation and that there is promise in gaining a better understanding of the biological mechanisms of differential response to β2-agonists through GWAS.

Racial/Ethnic variation in parent perceptions of asthma.

OBJECTIVE Black and Latino children with asthma have worse morbidity and receive less controller medication than their white peers. Scant information exists on racial/ethnic differences in parent perceptions of asthma. To compare parent perceptions among black, Latino, and white children with asthma in 4 domains: (1) expectations for functioning with asthma; (2) concerns about medications; (3) interactions with providers; and (4) competing family priorities. METHODS In this cross-sectional study, we conducted telephone interviews with parents of children with persistent asthma in a Medicaid health plan and a multispecialty provider group in Massachusetts. To measure expectations for functioning and other domains, we adapted multi-item scales from past studies. Associations between race/ethnicity and these domains were evaluated in multivariate analyses that controlled for age, gender, household income, parental education, insurance, and language. The response rate was 72%. RESULTS Of the 739 study children, 24% were black, 21% Latino, and 43% white. Parents of black and Latino children had lower expectations for their childrens functioning with asthma (P < .001), higher levels of worry about their childrens asthma (P < .001), and more competing family priorities (P = .004) compared with parents of white children. Parents of Latino children had higher levels of concern about medications for asthma than parents of black or white children (P = .002). There were no differences among racial/ethnic groups in reports of interactions with the provider of their childrens asthma care. CONCLUSIONS Efforts to eliminate disparities in childhood asthma may need to address variation in expectations and competing priorities between minority and white families.

Primary Adherence to Controller Medications for Asthma Is Poor

RATIONALE Few previous studies have evaluated primary adherence (whether a new prescription is filled within 30 d) to controller medications in individuals with persistent asthma. OBJECTIVE To compare adherence to the major controller medication regimens for asthma. METHODS This was a retrospective cohort study of enrollees from five large health plans. We used electronic medical data on patients of all ages with asthma who had experienced an asthma-related exacerbation in the prior 12 months. We studied adherence measures including proportion of days covered and primary adherence (first prescription filled within 30 d). MEASUREMENTS AND MAIN RESULTS Our population included 69,652 subjects who had probable persistent asthma and were prescribed inhaled corticosteroids (ICSs), leukotriene antagonists (LTRAs), or ICS/long-acting β-agonists (ICS/LABAs). The mean age was 37 years and 58% were female. We found that 14-20% of subjects who were prescribed controller medicines for the first time did not fill their prescriptions. The mean proportion of days covered was 19% for ICS, 30% for LTRA, and 25% for ICS/LABA over 12 months. Using multivariate logistic regression, subjects prescribed LTRA were less likely to be primary adherent than subjects prescribed ICS (odds ratio, 0.82; 95% confidence interval, 0.74-0.92) or ICS/LABA (odds ratio, 0.88; 95% confidence interval, 0.80-0.97). Black and Latino patients were less likely to fill the prescription compared with white patients. CONCLUSIONS Adherence to controller medications for asthma is poor. In this insured population, primary adherence to ICSs was better than to LTRAs and ICS/LABAs. Adherence as measured by proportion of days covered was better for LTRAs and ICS/LABAs than for ICSs.

Fungal Exposure Modulates the Effect of Polymorphisms of Chitinases on Emergency Department Visits and Hospitalizations

RATIONALE Chitinases are enzymes that cleave chitin, which is present in fungal cells. Two types of human chitinases, chitotriosidase and acidic mammalian chitinase, and the chitinase-like protein, YKL-40, seem to play an important role in asthma. We hypothesized that exposure to environmental fungi may modulate the effect of chitinases in individuals with asthma. OBJECTIVES To explore whether interactions between high fungal exposure and common genetic variants in the two chitinases in humans, CHIT1 and CHIA, and the chitinase 3-like 1 gene, CHI3L1, are associated with severe asthma exacerbations and other asthma-related outcomes. METHODS Forty-eight single nucleotide polymorphisms (SNPs) in CHIT1, CHIA, and CHI3L1 and one CHIT1 duplication were genotyped in 395 subjects and their parents as part of the Childhood Asthma Management Program. Household levels of mold (an index of fungal exposure) were determined on house dust samples. We conducted family-based association tests with gene-environment interactions. Our outcome was severe exacerbation, defined as emergency department visits and hospitalizations from asthma over a 4-year period, and our secondary outcomes included indices of lung function and allergy-related phenotypes. MEASUREMENTS AND MAIN RESULTS Of the 395 subjects who had mold levels at randomization, 24% (95 subjects) had levels that were greater than 25,000 units per gram of house dust (high mold exposure). High mold exposure significantly modified the relation between three SNPs in CHIT1 (rs2486953, rs4950936, and rs1417149) and severe exacerbations (P for interaction 0.0010 for rs2486953, 0.0008 for rs4950936, and 0.0005 for rs1417149). High mold exposure did not significantly modify the relationship between any of the other variants and outcomes. CONCLUSIONS Environmental exposure to fungi, modifies the effect of CHIT1 SNPs on severe asthma exacerbations.

Asthma Metabolomics and the Potential for Integrative Omics in Research and the Clinic

&NA; Asthma is a complex disease well‐suited to metabolomic profiling, both for the development of novel biomarkers and for the improved understanding of pathophysiology. In this review, we summarize the 21 existing metabolomic studies of asthma in humans, all of which reported significant findings and concluded that individual metabolites and metabolomic profiles measured in exhaled breath condensate, urine, plasma, and serum could identify people with asthma and asthma phenotypes with high discriminatory ability. There was considerable consistency across the studies in terms of the reported biomarkers, regardless of biospecimen, profiling technology, and population age. In particular, acetate, adenosine, alanine, hippurate, succinate, threonine, and trans‐aconitate, and pathways relating to hypoxia response, oxidative stress, immunity, inflammation, lipid metabolism and the tricarboxylic acid cycle were all identified as significant in at least two studies. There were also a number of nonreplicated results; however, the literature is not yet sufficiently developed to determine whether these represent spurious findings or reflect the substantial heterogeneity and limited statistical power in the studies and their methods to date. This review highlights the need for additional asthma metabolomic studies to explore these issues, and, further, the need for standardized methods in the way these studies are conducted. We conclude by discussing the potential of translation of these metabolomic findings into clinically useful biomarkers and the crucial role that integrated omics is likely to play in this endeavor.

The metabolomics of asthma control: a promising link between genetics and disease

Short‐acting β agonists (e.g., albuterol) are the most commonly used medications for asthma, a disease that affects over 300 million people in the world. Metabolomic profiling of asthmatics taking β agonists presents a new and promising resource for identifying the molecular determinants of asthma control. The objective is to identify novel genetic and biochemical predictors of asthma control using an integrative “omics” approach. We generated lipidomic data by liquid chromatography tandem mass spectrometry (LC‐MS), using plasma samples from 20 individuals with asthma. The outcome of interest was a binary indicator of asthma control defined by the use of albuterol inhalers in the preceding week. We integrated metabolomic data with genome‐wide genotype, gene expression, and methylation data of this cohort to identify genomic and molecular indicators of asthma control. A Conditional Gaussian Bayesian Network (CGBN) was generated using the strongest predictors from each of these analyses. Integrative and metabolic pathway over‐representation analyses (ORA) identified enrichment of known biological pathways within the strongest molecular determinants. Of the 64 metabolites measured, 32 had known identities. The CGBN model based on four SNPs (rs9522789, rs7147228, rs2701423, rs759582) and two metabolites—monoHETE_0863 and sphingosine‐1‐phosphate (S1P) could predict asthma control with an AUC of 95%. Integrative ORA identified 17 significantly enriched pathways related to cellular immune response, interferon signaling, and cytokine‐related signaling, for which arachidonic acid, PGE2 and S1P, in addition to six genes (CHN1, PRKCE, GNA12, OASL, OAS1, and IFIT3) appeared to drive the pathway results. Of these predictors, S1P, GNA12, and PRKCE were enriched in the results from integrative and metabolic ORAs. Through an integrative analysis of metabolomic, genomic, and methylation data from a small cohort of asthmatics, we implicate altered metabolic pathways, related to sphingolipid metabolism, in asthma control. These results provide insight into the pathophysiology of asthma control.

Statin Exposure Is Associated with Decreased Asthma-related Emergency Department Visits and Oral Corticosteroid Use

RATIONALE Statins, or HMG-CoA reductase inhibitors, may aid in the treatment of asthma through their pleiotropic antiinflammatory effects. OBJECTIVES To examine the effect of statin therapy on asthma-related exacerbations using a large population-based cohort. METHODS Statin users aged 31 years or greater with asthma were identified from the Population-Based Effectiveness in Asthma and Lung population, which includes data from five health plans. Statin exposure and asthma exacerbations were assessed over a 24-month observation period. Statin users with a statin medication possession ratio greater than or equal to 80% were matched to non-statin users by age, baseline asthma therapy, site of enrollment, season at baseline, and propensity score, which was calculated based on patient demographics and Deyo-Charlson conditions. Asthma exacerbations were defined as two or more oral corticosteroid dispensings, asthma-related emergency department visits, or asthma-related hospitalizations. The association between statin exposure and each of the three outcome measures was assessed using conditional logistic regression. MEASUREMENTS AND MAIN RESULTS Of the 14,566 statin users, 8,349 statin users were matched to a nonuser. After adjusting for Deyo-Charlson conditions that remained unbalanced after matching, among statin users, statin exposure was associated with decreased odds of having asthma-related emergency department visits (odds ratio [OR], 0.64; 95% confidence interval [CI], 0.53-0.77; P < 0.0001) and two or more oral corticosteroid dispensings (OR, 0.90; 95% CI, 0.81-0.99; P = 0.04). There were no differences in asthma-related hospitalizations (OR, 0.91; 95% CI, 0.66-1.24; P = 0.52). CONCLUSIONS Among statin users with asthma, statin exposure was associated with decreased odds of asthma-related emergency department visits and oral corticosteroid dispensings.

Economic Evaluation of Pharmacogenetic Tests

Ever since the sequencing of the human genome was completed, prediction of treatment response in terms of genetic variation has been seen as an important and achievable goal. Pharmacogenetics is the study of how genetic differences affect variation in response to medication. One potential goal of pharmacogenetics is to be able to deliver “personalized medicine” by making management decisions that optimize patient health outcomes based on a patients genetic makeup. Pharmacogenetic tests have the potential to (i) predict intended response, the goal outcome of the medication; (ii) predict unintended response to the medication, such as adverse events; (iii) titrate medication dose; and (iv) inform the development of novel therapeutics.

Predicting response to short-acting bronchodilator medication using Bayesian networks

AIMS Bronchodilator response tests measure the effect of beta(2)-agonists, the most commonly used short-acting reliever drugs for asthma. We sought to relate candidate gene SNP data with bronchodilator response and measure the predictive accuracy of a model constructed with genetic variants. MATERIALS & METHODS Bayesian networks, multivariate models that are able to account for simultaneous associations and interactions among variables, were used to create a predictive model of bronchodilator response using candidate gene SNP data from 308 Childhood Asthma Management Program Caucasian subjects. RESULTS The model found that 15 SNPs in 15 genes predict bronchodilator response with fair accuracy, as established by a fivefold cross-validation area under the receiver-operating characteristic curve of 0.75 (standard error: 0.03). CONCLUSION Bayesian networks are an attractive approach to analyze large-scale pharmacogenetic SNP data because of their ability to automatically learn complex models that can be used for the prediction and discovery of novel biological hypotheses.