Asthma is a chronic inflammatory respiratory disease that affects over 300 million people worldwide. Glucocorticoids are a mainstay therapy for asthma because they exert anti-inflammatory effects in multiple lung tissues, including the airway smooth muscle (ASM). However, the mechanism by which glucocorticoids suppress inflammation in ASM remains poorly understood. Using RNA-Seq, a high-throughput sequencing method, we characterized transcriptomic changes in four primary human ASM cell lines that were treated with dexamethasone—a potent synthetic glucocorticoid (1 µM for 18 hours). Based on a Benjamini-Hochberg corrected p-value <0.05, we identified 316 differentially expressed genes, including both well known (DUSP1, KLF15, PER1, TSC22D3) and less investigated (C7, CCDC69, CRISPLD2) glucocorticoid-responsive genes. CRISPLD2, which encodes a secreted protein previously implicated in lung development and endotoxin regulation, was found to have SNPs that were moderately associated with inhaled corticosteroid resistance and bronchodilator response among asthma patients in two previously conducted genome-wide association studies. Quantitative RT-PCR and Western blotting showed that dexamethasone treatment significantly increased CRISPLD2 mRNA and protein expression in ASM cells. CRISPLD2 expression was also induced by the inflammatory cytokine IL1β, and small interfering RNA-mediated knockdown of CRISPLD2 further increased IL1β-induced expression of IL6 and IL8. Our findings offer a comprehensive view of the effect of a glucocorticoid on the ASM transcriptome and identify CRISPLD2 as an asthma pharmacogenetics candidate gene that regulates anti-inflammatory effects of glucocorticoids in the ASM.
While accurate measures of heritability are needed to understand the pharmacogenetic basis of drug treatment response, these are generally not available, since it is unfeasible to give medications to individuals for which treatment is not indicated. Using a polygenic linear mixed modeling approach, we estimated lower-bounds on asthma heritability and the heritability of two related drug-response phenotypes, bronchodilator response and airway hyperreactivity, using genome-wide SNP data from existing asthma cohorts. Our estimate of the heritability for bronchodilator response is 28.5% (se 16%, p = 0.043) and airway hyperresponsiveness is 51.1% (se 34%, p = 0.064), while we estimate asthma genetic liability at 61.5% (se 16%, p < 0.001). Our results agree with previously published estimates of the heritability of these traits, suggesting that the LMM method is useful for computing the heritability of other pharmacogenetic traits. Furthermore, our results indicate that multiple SNP main-effects, including SNPs as yet unidentified by GWAS methods, together explain a sizable portion of the heritability of these traits.
Asthma; Pharmacogenetics; Heritability; Bronchodilator Response; Airway Hyperresponsiveness
Immunoglobulin E (IgE) is both a marker and mediator of allergic inflammation. Despite reported differences in serum total IgE levels by race-ethnicity, African American and Latino individuals have not been well represented in genetic studies of total IgE.
To identify the genetic predictors of serum total IgE levels.
We used genome wide association (GWA) data from 4,292 individuals (2,469 African Americans, 1,564 European Americans, and 259 Latinos) in the EVE Asthma Genetics Consortium. Tests for association were performed within each cohort by race-ethnic group (i.e., African American, Latino, and European American) and asthma status. The resulting p-values were meta-analyzed accounting for sample size and direction of effect. Top single nucleotide polymorphism (SNP) associations from the meta-analysis were reassessed in six additional cohorts comprising 5,767 individuals.
We identified 10 unique regions where the combined association statistic was associated with total serum IgE levels (P-value <5.0×10−6) and the minor allele frequency was ≥5% in two or more population groups. Variant rs9469220, corresponding to HLA-DQB1, was the most significantly associated SNP with serum total IgE levels when assessed in both the replication cohorts and the discovery and replication sets combined (P-value = 0.007 and 2.45×10−7, respectively). In addition, findings from earlier GWA studies were also validated in the current meta-analysis.
This meta-analysis independently identified a variant near HLA-DQB1 as a predictor of total serum IgE in multiple race-ethnic groups. This study also extends and confirms the findings of earlier GWA analyses in African American and Latino individuals.
meta-analysis; genome wide association study; total immunoglobulin E; race-ethnicity; continental population groups
Genome-wide association studies of asthma have implicated many genetic risk factors, with
well-replicated associations at approximately 10 loci that account for only a small proportion of
the genetic risk.
We aimed to identify additional asthma risk loci by performing an extensive replication
study of the results from the EVE Consortium meta-analysis.
We selected 3186 SNPs for replication based on the p-values from the EVE Consortium
meta-analysis. These SNPs were genotyped in ethnically diverse replication samples from nine
different studies, totaling to 7202 cases, 6426 controls, and 507 case-parent trios. Association
analyses were conducted within each participating study and the resulting test statistics were
combined in a meta-analysis.
Two novel associations were replicated in European Americans: rs1061477 in the
KLK3 gene on chromosome 19 (combined OR = 1.18; 95% CI 1.10 – 1.25)
and rs9570077 (combined OR =1.20 95% CI 1.12–1.29) on chromosome 13q21. We could not
replicate any additional associations in the African American or Latino individuals.
This extended replication study identified two additional asthma risk loci in populations
of European descent. The absence of additional loci for African Americans and Latino individuals
highlights the difficulty in replicating associations in admixed populations.
Asthma; genetic risk factors; meta-analysis; KLK3
Airway hyperresponsiveness (AHR), a primary characteristic of asthma, involves increased airway smooth muscle contractility in response to certain exposures. We sought to determine whether common genetic variants were associated with AHR severity.
A genome-wide association study (GWAS) of AHR, quantified as the natural log of the dosage of methacholine causing a 20% drop in FEV1, was performed with 994 non-Hispanic white asthmatic subjects from three drug clinical trials: CAMP, CARE, and ACRN. Genotyping was performed on Affymetrix 6.0 arrays, and imputed data based on HapMap Phase 2, was used to measure the association of SNPs with AHR using a linear regression model. Replication of primary findings was attempted in 650 white subjects from DAG, and 3,354 white subjects from LHS. Evidence that the top SNPs were eQTL of their respective genes was sought using expression data available for 419 white CAMP subjects.
The top primary GWAS associations were in rs848788 (P-value 7.2E-07) and rs6731443 (P-value 2.5E-06), located within the ITGB5 and AGFG1 genes, respectively. The AGFG1 result replicated at a nominally significant level in one independent population (LHS P-value 0.012), and the SNP had a nominally significant unadjusted P-value (0.0067) for being an eQTL of AGFG1.
Based on current knowledge of ITGB5 and AGFG1, our results suggest that variants within these genes may be involved in modulating AHR. Future functional studies are required to confirm that our associations represent true biologically significant findings.
Asthma; Airway hyperresponsiveness; Genome-wide association study; ITGB5; AGFG1
The innate immune pathway is important in the pathogenesis of asthma and eczema. However, only a few variants in these genes have been associated with either disease. We investigate the association between polymorphisms of genes in the innate immune pathway with childhood asthma and eczema. In addition, we compare individual associations with those discovered using a multivariate approach.
Using a novel method, case control based association testing (C2BAT), 569 single nucleotide polymorphisms (SNPs) in 44 innate immune genes were tested for association with asthma and eczema in children from the Boston Home Allergens and Asthma Study and the Connecticut Childhood Asthma Study. The screening algorithm was used to identify the top SNPs associated with asthma and eczema. We next investigated the interaction of innate immune variants with asthma and eczema risk using Bayesian networks.
After correction for multiple comparisons, 7 SNPs in 6 genes (CARD25, TGFB1, LY96, ACAA1, DEFB1, and IFNG) were associated with asthma (adjusted p-value<0.02), while 5 SNPs in 3 different genes (CD80, STAT4, and IRAKI) were significantly associated with eczema (adjusted p-value < 0.02). None of these SNPs were associated with both asthma and eczema. Bayesian network analysis identified 4 SNPs that were predictive of asthma and 10 SNPs that predicted eczema. Of the genes identified using Bayesian networks, only CD80 was associated with eczema in the single-SNP study. Using novel methodology that allows for screening and replication in the same population, we have identified associations of innate immune genes with asthma and eczema. Bayesian network analysis suggests that additional SNPs influence disease susceptibility via SNP interactions.
Our findings suggest that innate immune genes contribute to the pathogenesis of asthma and eczema, and that these diseases likely have different genetic determinants.
asthma; Bayesian network; genetic association; eczema; innate immunity
The response to treatment for asthma is characterized by wide interindividual variability, with a significant number of patients who have no response. We hypothesized that a genomewide association study would reveal novel pharmacogenetic determinants of the response to inhaled glucocorticoids.
We analyzed a small number of statistically powerful variants selected on the basis of a family-based screening algorithm from among 534,290 single-nucleotide polymorphisms (SNPs) to determine changes in lung function in response to inhaled glucocorticoids. A significant, replicated association was found, and we characterized its functional effects.
We identified a significant pharmacogenetic association at SNP rs37972, replicated in four independent populations totaling 935 persons (P = 0.0007), which maps to the glucocorticoid-induced transcript 1 gene (GLCCI1) and is in complete linkage disequilibrium (i.e., perfectly correlated) with rs37973. Both rs37972 and rs37973 are associated with decrements in GLCCI1 expression. In isolated cell systems, the rs37973 variant is associated with significantly decreased luciferase reporter activity. Pooled data from treatment trials indicate reduced lung function in response to inhaled glucocorticoids in subjects with the variant allele (P = 0.0007 for pooled data). Overall, the mean (± SE) increase in forced expiratory volume in 1 second in the treated subjects who were homozygous for the mutant rs37973 allele was only about one third of that seen in similarly treated subjects who were homozygous for the wild-type allele (3.2 ± 1.6% vs. 9.4 ± 1.1%), and their risk of a poor response was significantly higher (odds ratio, 2.36; 95% confidence interval, 1.27 to 4.41), with genotype accounting for about 6.6% of overall inhaled glucocorticoid response variability.
A functional GLCCI1 variant is associated with substantial decrements in the response to inhaled glucocorticoids in patients with asthma. (Funded by the National Institutes of Health and others; ClinicalTrials.gov number, NCT00000575.)
To assess the feasibility of developing a Combined Clinical and Pharmacogenetic Predictive Test, comprised of multiple single nucleotide polymorphisms (SNPs) that is associated with poor bronchodilator response (BDR).
We genotyped SNPs that tagged the whole genome of the parents and children in the Childhood Asthma Management Program (CAMP) and implemented an algorithm using a family-based association test that ranked SNPs by statistical power. The top eight SNPs that were associated with BDR comprised the Pharmacogenetic Predictive Test. The Clinical Predictive Test was comprised of baseline forced expiratory volume in 1 s (FEV1). We evaluated these predictive tests and a Combined Clinical and Pharmacogenetic Predictive Test in three distinct populations: the children of the CAMP trial and two additional clinical trial populations of asthma. Our outcome measure was poor BDR, defined as BDR of less than 20th percentile in each population. BDR was calculated as the percent difference between the prebronchodilator and postbronchodilator (two puffs of albuterol at 180 μg/puff) FEV1 value. To assess the predictive ability of the test, the corresponding area under the receiver operating characteristic curves (AUROCs) were calculated for each population.
The AUROC values for the Clinical Predictive Test alone were not significantly different from 0.50, the AUROC of a random classifier. Our Combined Clinical and Pharmacogenetic Predictive Test comprised of genetic polymorphisms in addition to FEV1 predicted poor BDR with an AUROC of 0.65 in the CAMP children (n= 422) and 0.60 (n= 475) and 0.63 (n= 235) in the two independent populations. Both the Combined Clinical and Pharmacogenetic Predictive Test and the Pharmacogenetic Predictive Test were significantly more accurate than the Clinical Predictive Test (AUROC between 0.44 and 0.55) in each of the populations.
Our finding that genetic polymorphisms with a clinical trait are associated with BDR suggests that there is promise in using multiple genetic polymorphisms simultaneously to predict which asthmatics are likely to respond poorly to bronchodilators.
asthma; bronchodilator response; personalized medicine; pharmacogenetic test; predictive medicine
Atopy and plasma IgE concentration are genetically complex traits, and the specific genetic risk factors that lead to IgE dysregulation and clinical atopy are an area of active investigation.
To ascertain the genetic risk factors which lead to IgE dysregulation.
A genome wide association study (GWAS) was performed in 6,819 participants from the Framingham Heart Study (FHS). Seventy of the top SNPs were selected based on p-values and linkage disequilibrium among neighboring SNPs and evaluated in a meta-analysis with five independent populations from the KORA, B58C, and CAMP cohorts.
Thirteen SNPs located in the region of three genes, FCER1A, STAT6, and IL-13, were found to have genome-wide significance in the FHS GWAS. The most significant SNPs from the three regions were rs2251746 (FCER1A, p-value 2.11×10-12), rs1059513 (STAT6, p-value 2.87×10-08), and rs1295686 (IL-13, p-value 3.55×10-08). Four additional gene regions - HLA-G, HLA-DQA2, HLA-A, and DARC - reached genome-wide statistical significance in meta-analysis combining FHS and replication cohorts, although the DARC association did not appear independent of SNPs in the nearby FCER1A gene.
This GWAS of the FHS has identified genetic loci in HLA genes that may have a role in the pathogenesis of IgE dysregulation and atopy. It also confirmed the association of known susceptibility loci, FCER1A, STAT6, and IL-13, for the dysregulation of total IgE.
total IgE; atopy; asthma; GWAS
The genetic risk factors for chronic obstructive pulmonary disease (COPD) are still largely unknown. To date, genome-wide association studies (GWASs) of limited size have identified several novel risk loci for COPD at CHRNA3/CHRNA5/IREB2, HHIP and FAM13A; additional loci may be identified through larger studies. We performed a GWAS using a total of 3499 cases and 1922 control subjects from four cohorts: the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE); the Normative Aging Study (NAS) and National Emphysema Treatment Trial (NETT); Bergen, Norway (GenKOLS); and the COPDGene study. Genotyping was performed on Illumina platforms with additional markers imputed using 1000 Genomes data; results were summarized using fixed-effect meta-analysis. We identified a new genome-wide significant locus on chromosome 19q13 (rs7937, OR = 0.74, P = 2.9 × 10−9). Genotyping this single nucleotide polymorphism (SNP) and another nearby SNP in linkage disequilibrium (rs2604894) in 2859 subjects from the family-based International COPD Genetics Network study (ICGN) demonstrated supportive evidence for association for COPD (P = 0.28 and 0.11 for rs7937 and rs2604894), pre-bronchodilator FEV1 (P = 0.08 and 0.04) and severe (GOLD 3&4) COPD (P = 0.09 and 0.017). This region includes RAB4B, EGLN2, MIA and CYP2A6, and has previously been identified in association with cigarette smoking behavior.
Asthma is a common chronic respiratory disease characterized by airway hyperresponsiveness (AHR). The genetics of asthma have been widely studied in mouse and human, and homologous genomic regions have been associated with mouse AHR and human asthma-related phenotypes. Our goal was to identify asthma-related genes by integrating AHR associations in mouse with human genome-wide association study (GWAS) data. We used Efficient Mixed Model Association (EMMA) analysis to conduct a GWAS of baseline AHR measures from males and females of 31 mouse strains. Genes near or containing SNPs with EMMA p-values <0.001 were selected for further study in human GWAS. The results of the previously reported EVE consortium asthma GWAS meta-analysis consisting of 12,958 diverse North American subjects from 9 study centers were used to select a subset of homologous genes with evidence of association with asthma in humans. Following validation attempts in three human asthma GWAS (i.e., Sepracor/LOCCS/LODO/Illumina, GABRIEL, DAG) and two human AHR GWAS (i.e., SHARP, DAG), the Kv channel interacting protein 4 (KCNIP4) gene was identified as nominally associated with both asthma and AHR at a gene- and SNP-level. In EVE, the smallest KCNIP4 association was at rs6833065 (P-value 2.9e-04), while the strongest associations for Sepracor/LOCCS/LODO/Illumina, GABRIEL, DAG were 1.5e-03, 1.0e-03, 3.1e-03 at rs7664617, rs4697177, rs4696975, respectively. At a SNP level, the strongest association across all asthma GWAS was at rs4697177 (P-value 1.1e-04). The smallest P-values for association with AHR were 2.3e-03 at rs11947661 in SHARP and 2.1e-03 at rs402802 in DAG. Functional studies are required to validate the potential involvement of KCNIP4 in modulating asthma susceptibility and/or AHR. Our results suggest that a useful approach to identify genes associated with human asthma is to leverage mouse AHR association data.
Asthma is a common disease with a complex risk architecture including both genetic and environmental factors. We performed a meta-analysis of North American genome-wide association studies (GWAS) of asthma in 5,416 asthma cases representing European Americans, African Americans/African Caribbeans, and Latinos, and replicated five regions among the most significant signals in 12,649 individuals from the same ethnic groups. Four were at previously reported loci on 17q21, and near the IL1RL1, TSLP, and IL33, genes, but we report for the first time that these loci are associated with asthma risk in three ethnic groups. In addition, we identified a novel association with asthma in the PYHIN1, gene that was specific to individuals of African descent (p=3.9×10−9). These results suggest that some asthma susceptibility loci are robust to differences in ancestry when sufficiently large samples sizes are investigated, and that ancestry-specific associations also contribute to the complex genetic architecture of asthma.
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.
Bronchodilator response (BDR) is an important asthma phenotype that measures reversibility of airway obstruction by comparing lung function before and after the administration of short-acting β2-agonists, common medications used for asthma treatment. We performed a genome-wide association study of BDR with 1,644 white asthmatic subjects from six drug clinical trials and attempted to replicate these findings in 1,051 white subjects from two independent cohorts. The most significant associated variant was near the SPATS2L gene. We knocked down SPATS2L mRNA in human airway smooth muscle cells and found that β2-adrenergic receptor levels increased, suggesting that SPATS2L may be a regulator of BDR. Our results highlight the promise of pursuing GWAS results that do not necessarily reach genome-wide significance and are an example of how results from pharmacogenetic GWAS can be studied functionally.
Rationale: β2-agonists, the most common treatment for asthma, have a wide interindividual variability in response, which is partially attributed to genetic factors. We previously identified single nucleotide polymorphisms in the arginase 1 (ARG1) gene, which are associated with β2-agonist bronchodilator response (BDR).
Objectives: To identify cis-acting haplotypes in the ARG1 locus that are associated with BDR in patients with asthma and regulate gene expression in vitro.
Methods: We resequenced ARG1 in 96 individuals and identified three common, 5′ haplotypes (denoted 1, 2, and 3). A haplotype-based association analysis of BDR was performed in three independent, adult asthma drug trial populations. Next, each haplotype was cloned into vectors containing a luciferase reporter gene and transfected into human airway epithelial cells (BEAS-2B) to ascertain its effect on gene expression.
Measurements and Main Results: BDR varied by haplotype in each of the three populations with asthma. Individuals with haplotype 1 were more likely to have higher BDR, compared to those with haplotypes 2 and 3, which is supported by odds ratios of 1.25 (95% confidence interval, 1.03–1.71) and 2.18 (95% confidence interval, 1.34–2.52), respectively. Luciferase expression was 50% greater in cells transfected with haplotype 1 compared to haplotypes 2 and 3.
Conclusions: The identified ARG1 haplotypes seem to alter BDR and differentially regulate gene expression with a concordance of decreased BDR and reporter activity from haplotypes 2 and 3. These findings may facilitate pharmacogenetic tests to predict individuals who may benefit from other therapeutic agents in addition to β2-agonists for optimal asthma management.
Clinical trial registered with www.clinicaltrials.gov (NCT00156819, NCT00046644, and NCT00073840).
pharmacogenetics; asthma; β2-agonist
Epidemiological studies consistently show associations between asthma and obesity. Shared genetics may account for this association.
To identify genetic variants associated with both asthma and obesity.
Based on a literature search, we identified genes from: 1) Genome-wide association studies (GWAS) of Body Mass Index (BMI) (n=17 genes), 2) GWAS of asthma (n=14) and 3) candidate gene studies of BMI and asthma (n=7). We used GWAS data from the Childhood Asthma Management Program (CAMP) to analyze associations between single nucleotide polymorphisms (SNPs) in these genes and asthma (n=359 subjects) and BMI (n=537).
One top BMI GWAS SNP from the literature, rs10938397 near GNPDA2, was associated with both BMI (p=4 × 10−4) and asthma (p=0.03). Of the top asthma GWAS SNPs and the candidate gene SNPs, none was found to be associated with both BMI and asthma. Gene-based analyses that included all available SNPs in each gene found associations (p<0.05) with both phenotypes for several genes: NEGR1, ROBO1, DGKG, FAIM2, FTO and CHST8 among the BMI GWAS genes; ILRL1/IL18R1, DPP10, PDE4D, MYB, PDE10A, IL33 and especially PTPRD among the asthma GWAS genes; and PRKCA among the BMI and asthma candidate genes.
SNPs within several genes showed associations to BMI and asthma at a gene level, but none of these associations were significant after correction for multiple testing. Our analysis of known candidate genes reveals some evidence for shared genetics between asthma and obesity, but other shared genetic determinants are likely to be identified in novel loci.
Association; Asthma; BMI; Children; Genetics; GWAS; Obesity; Polymorphism; SNP
Personalized health-care promises tailored health-care solutions to individual patients based on their genetic background and/or environmental exposure history. To date, disease prediction has been based on a few environmental factors and/or single nucleotide polymorphisms (SNPs), while complex diseases are usually affected by many genetic and environmental factors with each factor contributing a small portion to the outcome. We hypothesized that the use of random forests classifiers to select SNPs would result in an improved predictive model of asthma exacerbations. We tested this hypothesis in a population of childhood asthmatics.
In this study, using emergency room visits or hospitalizations as the definition of a severe asthma exacerbation, we first identified a list of top Genome Wide Association Study (GWAS) SNPs ranked by Random Forests (RF) importance score for the CAMP (Childhood Asthma Management Program) population of 127 exacerbation cases and 290 non-exacerbation controls. We predict severe asthma exacerbations using the top 10 to 320 SNPs together with age, sex, pre-bronchodilator FEV1 percentage predicted, and treatment group.
Testing in an independent set of the CAMP population shows that severe asthma exacerbations can be predicted with an Area Under the Curve (AUC) = 0.66 with 160-320 SNPs in comparison to an AUC score of 0.57 with 10 SNPs. Using the clinical traits alone yielded AUC score of 0.54, suggesting the phenotype is affected by genetic as well as environmental factors.
Our study shows that a random forests algorithm can effectively extract and use the information contained in a small number of samples. Random forests, and other machine learning tools, can be used with GWAS studies to integrate large numbers of predictors simultaneously.
The relationships between total serum IgE levels and gene expression patterns in peripheral blood CD4+ T cells (in all subjects and within each sex specifically) are not known.
Peripheral blood CD4+ T cells from 223 participants from the Childhood Asthma Management Program (CAMP) with simultaneous measurement of IgE. Total RNA was isolated, and expression profiles were generated with Illumina HumanRef8 v2 BeadChip arrays. Modeling of the relationship between genome-wide gene transcript levels and IgE levels was performed in all subjects, and stratified by sex.
Among all subjects, significant evidence for association between gene transcript abundance and IgE was identified for a single gene, the interleukin 17 receptor B (IL17RB), explaining 12% of the variance (r2) in IgE measurement (p value = 7 × 10-7, 9 × 10-3 after adjustment for multiple testing). Sex stratified analyses revealed that the correlation between IL17RB and IgE was restricted to males only (r2 = 0.19, p value = 8 × 10-8; test for sex-interaction p < 0.05). Significant correlation between gene transcript abundance and IgE level was not found in females. Additionally we demonstrated substantial sex-specific differences in IgE when considering multi-gene models, and in canonical pathway analyses of IgE level.
Our results indicate that IL17RB may be the only gene expressed in CD4+ T cells whose transcript measurement is correlated with the variation in IgE level in asthmatics. These results provide further evidence sex may play a role in the genomic regulation of IgE.
Prior studies suggest a role for a variant (rs5743836) in the promoter of toll-like receptor 9 (TLR9) in asthma and other inflammatory diseases. We performed detailed genetic association studies of the functional variant rs5743836 with asthma susceptibility and asthma-related phenotypes in three independent cohorts.
rs5743836 was genotyped in two family-based cohorts of children with asthma and a case-control study of adult asthmatics. Association analyses were performed using chi square, family-based and population-based testing. A luciferase assay was performed to investigate whether rs5743836 genotype influences TLR9 promoter activity.
Contrary to prior reports, rs5743836 was not associated with asthma in any of the three cohorts. Marginally significant associations were found with FEV1 and FVC (p = 0.003 and p = 0.008, respectively) in one of the family-based cohorts, but these associations were not significant after correcting for multiple comparisons. Higher promoter activity of the CC genotype was demonstrated by luciferase assay, confirming the functional importance of this variant.
Although rs5743836 confers regulatory effects on TLR9 transcription, this variant does not appear to be an important asthma-susceptibility locus.
Asthma is a chronic respiratory disease whose genetic basis has been explored for over two decades, most recently via genome-wide association studies. We sought to find asthma-susceptibility variants by using probands from a single population in both family-based and case-control association designs.
We used probands from the Childhood Asthma Management Program (CAMP) in two primary genome-wide association study designs: (1) probands were combined with publicly available population controls in a case-control design, and (2) probands and their parents were used in a family-based design. We followed a two-stage replication process utilizing three independent populations to validate our primary findings.
We found that single nucleotide polymorphisms with similar case-control and family-based association results were more likely to replicate in the independent populations, than those with the smallest p-values in either the case-control or family-based design alone. The single nucleotide polymorphism that showed the strongest evidence for association to asthma was rs17572584, which replicated in 2/3 independent populations with an overall p-value among replication populations of 3.5E-05. This variant is near a gene that encodes an enzyme that has been implicated to act coordinately with modulators of Th2 cell differentiation and is expressed in human lung.
Our results suggest that using probands from family-based studies in case-control designs, and combining results of both family-based and case-control approaches, may be a way to augment our ability to find SNPs associated with asthma and other complex diseases.
Bronchodilator response tests measure the effect of β2-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.
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).
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.
asthma; Bayesian networks; β2-agonists; bronchodilator response; prediction
Identify clinical factors that modulate the risk of progression to COPD among asthma patients using data extracted from electronic medical records.
Demographic information and comorbidities from adult asthma patients who were observed for at least 5 years with initial observation dates between 1988 and 1998, were extracted from electronic medical records of the Partners Healthcare System using tools of the National Center for Biomedical Computing “Informatics for Integrating Biology to the Bedside” (i2b2).
A predictive model of COPD was constructed from a set of 9,349 patients (843 cases, 8,506 controls) using Bayesian networks. The model's predictive accuracy was tested using it to predict COPD in a future independent set of asthma patients (992 patients; 46 cases, 946 controls), who had initial observation dates between 1999 and 2002.
A Bayesian network model composed of age, sex, race, smoking history, and 8 comorbidity variables is able to predict COPD in the independent set of patients with an accuracy of 83.3%, computed as the area under the Receiver Operating Characteristic curve (AUROC).
Our results demonstrate that data extracted from electronic medical records can be used to create predictive models. With improvements in data extraction and inclusion of more variables, such models may prove to be clinically useful.
Cardioembolic stroke is a complex disease resulting from the interaction of numerous factors. Using data from Genes Affecting Stroke Risk and Outcome Study (GASROS), we show that a multivariate predictive model built using Bayesian networks is able to achieve a predictive accuracy of 86% on the fitted values as computed by the area under the receiver operating characteristic curve relative to that of the individual single nucleotide polymorphism with the highest prognostic performance (area under the receiver operating characteristic curve=60%).
Bayesian networks; genetics; ischemic stroke; prediction; risk factors
The increasing availability of electronic medical records offers opportunities to better characterize patient populations and create predictive tools to individualize health care. We determined which asthma patients suffer exacerbations using data extracted from electronic medical records of the Partners Healthcare System using Natural Language Processing tools from the “Informatics for Integrating Biology to the Bedside” center (i2b2). Univariable and multivariable analysis of data for 11,356 patients (1,394 cases, 9,962 controls) found that race, BMI, smoking history, and age at initial observation are predictors of asthma exacerbations. The area under the receiver operating characteristic curve (AUROC) corresponding to prediction of exacerbations in an independent group of 1,436 asthma patients (106 cases, 1,330 controls) is 0.67. Our findings are consistent with previous characterizations of asthma patients in epidemiological studies, and demonstrate that data extracted by natural language processing from electronic medical records is suitable for the characterization of patient populations.
Rationale: The role of 3-hydroxy-3-methylglutaryl-coenzyme A reductase inhibitors (statins) in the development or progression of interstitial lung disease (ILD) is controversial.
Objectives: To evaluate the association between statin use and ILD.
Methods: We used regression analyses to evaluate the association between statin use and interstitial lung abnormalities (ILA) in a large cohort of smokers from COPDGene. Next, we evaluated the effect of statin pretreatment on bleomycin-induced fibrosis in mice and explored the mechanism behind these observations in vitro.
Measurements and Main Results: In COPDGene, 38% of subjects with ILA were taking statins compared with 27% of subjects without ILA. Statin use was positively associated in ILA (odds ratio, 1.60; 95% confidence interval, 1.03–2.50; P = 0.04) after adjustment for covariates including a history of high cholesterol or coronary artery disease. This association was modified by the hydrophilicity of statin and the age of the subject. Next, we demonstrate that statin administration aggravates lung injury and fibrosis in bleomycin-treated mice. Statin pretreatment enhances caspase-1–mediated immune responses in vivo and in vitro; the latter responses were abolished in bone marrow–derived macrophages isolated from Nlrp3−/− and Casp1−/− mice. Finally, we provide further insights by demonstrating that statins enhance NLRP3-inflammasome activation by increasing mitochondrial reactive oxygen species generation in macrophages.
Conclusions: Statin use is associated with ILA among smokers in the COPDGene study and enhances bleomycin-induced lung inflammation and fibrosis in the mouse through a mechanism involving enhanced NLRP3-inflammasome activation. Our findings suggest that statins may influence the susceptibility to, or progression of, ILD.
Clinical trial registered with www.clinicaltrials.gov (NCT 00608764).
statins; interstitial lung disease; pulmonary fibrosis; inflammasome; mitochondrial reactive oxygen species
Thymic stromal lymphopoietin (TSLP) triggers dendritic cell–mediated T helper (Th) 2 inflammatory responses. A single-nucleotide polymorphism (SNP), rs3806933, in the promoter region of the TSLP gene creates a binding site for the transcription factor activating protein (AP)–1. The variant enhances AP-1 binding to the regulatory element, and increases the promoter–reporter activity of TSLP in response to polyinosinic-polycytidylic acid (poly[I:C]) stimulation in normal human bronchial epithelium (NHBE). We investigated whether polymorphisms including the SNP rs3806933 could affect the susceptibility to and clinical phenotypes of bronchial asthma. We selected three representative (i.e., Tag) SNPs and conducted association studies of the TSLP gene, using two independent populations (639 patients with childhood atopic asthma and 838 control subjects, and 641 patients with adult asthma and 376 control subjects, respectively). We further examined the effects of corticosteroids and a long-acting β2-agonist (salmeterol) on the expression levels of the TSLP gene in response to poly(I:C) in NHBE. We found that the promoter polymorphisms rs3806933 and rs2289276 were significantly associated with disease susceptibility in both childhood atopic and adult asthma. The functional SNP rs3806933 was associated with asthma (meta-analysis, P = 0.000056; odds ratio, 1.29; 95% confidence interval, 1.14–1.47). A genotype of rs2289278 was correlated with pulmonary function. Moreover, the induction of TSLP mRNA and protein expression induced by poly(I:C) in NHBE was synergistically impaired by a corticosteroid and salmeterol. TSLP variants are significantly associated with bronchial asthma and pulmonary function. Thus, TSLP may serve as a therapeutic target molecule for combination therapy.
asthma; TSLP; bronchial epithelial cells; combination therapy; genetic polymorphisms