Search

BACKGROUND Polygenic risk scores (PRSs) will have important utility for asthma and other chronic diseases as a tool for predicting disease incidence and subphenotypes. OBJECTIVE We utilized findings from a large multiancestry GWAS of asthma to compute a PRS for asthma with relevance for racially diverse populations. METHODS We derived two PRSs for asthma using a standard approach (based on genome-wide significant variants) and a lasso sum regression approach (allowing all genetic variants to potentially contribute). We used data from the racially diverse Kaiser Permanente GERA cohort (68 638 non-Hispanic Whites, 5874 Hispanics, 6870 Asians and 2760 Blacks). Race was self-reported by questionnaire. RESULTS For the standard PRS, non-Hispanic Whites showed the highest odds ratio for a standard deviation increase in PRS for asthma (OR = 1.16 (95% CI 1.14-1.18)). The standard PRS was also associated with asthma in Hispanic (OR = 1.12 (95% CI 1.05-1.19)) and Asian (OR = 1.10 (95% CI 1.04-1.17)) subjects, with a trend towards increased risk in Blacks (OR = 1.05 (95% CI 0.97-1.15)). We detected an interaction by sex, with men showing a higher risk of asthma with an increase in PRS as compared to women. The lasso sum regression-derived PRS showed stronger associations with asthma in non-Hispanic White subjects (OR = 1.20 (95% CI 1.18-1.23)), Hispanics (OR = 1.17 (95% 1.10-1.26)), Asians (OR = 1.18 (95% CI 1.10-1.27)) and Blacks (OR = 1.10 (95% CI 0.99-1.22)). CONCLUSION Polygenic risk scores across multiple racial/ethnic groups were associated with increased asthma risk, suggesting that PRSs have potential as a tool for predicting disease development.

Genome wide association studies of asthma have not explained environmental risk or variable clinical efficacy of glucocorticoids. Bidirectional enhancer RNA (eRNA) transcription is a widespread response to environmental signals and glucocorticoids. Therefore, we investigated whether single nucleotide polymorphisms (SNPs) within dynamically regulated enhancer RNA (eRNA)-transcribing regions contribute to genetic variation in asthma. Through applying machine-learning methods to a large clinical cohort, we identified novel associations between asthma and 36 SNPs located in eRNA-transcribing regions implicated in regulating diverse cellular processes relevant to asthma. Functional validation established thatrs258760(mean allele frequency = 0.35, asthma odds ratio 0.95; P

The application of large-scale metabolomic profiling provides new opportunities for realizing the potential of omics-based precision medicine for asthma. By leveraging data from over 14,000 individuals in four distinct cohorts, this study identifies and independently replicates 17 steroid metabolites whose levels were significantly reduced in individuals with prevalent asthma. Although steroid levels were reduced among all asthma cases regardless of medication use, the largest reductions were associated with inhaled corticosteroid (ICS) treatment, as confirmed in a 4-year low-dose ICS clinical trial. Effects of ICS treatment on steroid levels were dose dependent; however, significant reductions also occurred with low-dose ICS treatment. Using information from electronic medical records, we found that cortisol levels were substantially reduced throughout the entire 24-hour daily period in patients with asthma who were treated with ICS compared to those who were untreated and to patients without asthma. Moreover, patients with asthma who were treated with ICS showed significant increases in fatigue and anemia as compared to those without ICS treatment. Adrenal suppression in patients with asthma treated with ICS might, therefore, represent a larger public health problem than previously recognized. Regular cortisol monitoring of patients with asthma treated with ICS is needed to provide the optimal balance between minimizing adverse effects of adrenal suppression while capitalizing on the established benefits of ICS treatment.

Background Global gene expression levels are known to be highly dependent upon gross demographic features including age, yet identification of age-related genomic indicators has yet to be comprehensively undertaken in a disease and treatment-specific context. Methods We used gene expression data from CD4+ lymphocytes in the Asthma BioRepository for Integrative Genomic Exploration (Asthma BRIDGE), an open-access collection of subjects participating in genetic studies of asthma with available gene expression data. Replication population participants were Puerto Rico islanders recruited as part of the ongoing Genes environments & Admixture in Latino Americans (GALA II), who provided nasal brushings for transcript sequencing. The main outcome measure was chronic asthma control as derived by questionnaires. Genomic associations were performed using regression of chronic asthma control score on gene expression with age in years as a covariate, including a multiplicative interaction term for gene expression times age. Results The SMARCD1 gene (SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily D member 1) interacted with age to influence chronic asthma control on inhaled corticosteroids, with a doubling of expression leading to an increase of 1.3 units of chronic asthma control per year (95% CI [0.86, 1.74], p = 6 × 10− 9), suggesting worsening asthma control with increasing age. This result replicated in GALA II (p = 3.8 × 10− 8). Cellular assays confirmed the role of SMARCD1 in glucocorticoid response in airway epithelial cells. Conclusion Focusing on age-dependent factors may help identify novel indicators of asthma medication response. Age appears to modulate the effect of SMARCD1 on asthma control with inhaled corticosteroids.

BACKGROUND AND OBJECTIVES: Genome Wide Association Studies (GWAS) have identified genetic polymorphisms associated with bronchodilator response (BDR), but it is unknown how these associations change across life stages. We examined the impact of genetic variants on BDR from childhood to adulthood in asthmatics to uncover potential effect modification by age. METHODS: We searched the National Human Genome Research Institute (NHGRI) catalog of published GWAS to obtain a list of genetic associations with BDR, and tested them for effect modification by age in 604 subjects from the Childhood Asthma Management Program (CAMP), a clinical trial with longitudinal measures of BDR (age range 5 to 30 years). We performed longitudinal analyses using linear mixed models and visualized longitudinal changes in BDR using generalized additive models with repeated measures, adjusting for treatment group, sex, and main effects of age and additive genotype. RESULTS: Increasing age was associated with decreased BDR (−0.24 % per year). Polymorphisms rs295137 near SPATS2L and rs2626393 near ASB3 demonstrated their strongest associations with BDR in early childhood through adolescence, with a large decrease in their magnitude of effect from adolescence onward. The effect estimate for % BDR associated with rs295137 genotype (Beta=1.3; 95% CI 0.6 to 2.1) was diminished by age (interaction term=−0.06, p=0.004). The effect estimate for rs2626393 (Beta=−0.92 (95% CI −1.7 to −0.2) was also modified by age (interaction term= 0.05, p = 0.0004). CONCLUSIONS: Polymorphisms associated with BDR in childhood may not be relevant for predicting adolescent and adult BDR, which could reflect age-related changes in asthma phenotypes. TRIAL REGISTRATION: This work uses data from the previous clinical trial of asthma, the Childhood Asthma Management Program (CAMP), registered at ClinicalTrials.gov, #

IntroductionOlder adults have the greatest burden of asthma and poorest outcomes. The pharmacogenetics of inhaled corticosteroid (ICS) treatment response is not well studied in older adults.MethodsA genome-wide association study of ICS response was performed in asthmatics of European ancestry in Genetic Epidemiology Research on Adult Health and Aging (GERA) by fitting Cox proportional hazards regression models, followed by validation in the Mass General Brigham (MGB) Biobank and Rotterdam Study. ICS response was measured using two definitions in asthmatics on ICS treatment: (1) absence of oral corticosteroid (OCS) bursts using prescription records and (2) absence of asthma-related exacerbations using diagnosis codes. A fixed-effect meta-analysis was performed for each outcome. The validated single-nucleotide polymorphisms (SNPs) were functionally annotated to standard databases.ResultsIn 5710 subjects in GERA, 676 subjects in MGB Biobank, and 465 subjects in the Rotterdam Study, four novel SNPs on chromosome six nearPTCHD4validated across all cohorts and met genome-wide significance on meta-analysis for the OCS burst outcome. In 4541 subjects in GERA and 505 subjects in MGB Biobank, 152 SNPs with p−5were validated across these two cohorts for the asthma-related exacerbation outcome. The validated SNPs included methylation and expression quantitative trait loci forCPED1,CRADDandDSTfor the OCS burst outcome andGM2A,SNW1,CACNA1C,DPH1, andRPS10for the asthma-related exacerbation outcome.ConclusionsMultiple novel SNPs associated with ICS response were identified in older adult asthmatics. Several SNPs annotated to genes previously associated with asthma and other airway or allergic diseases, includingPTCHD4.

The application of large-scale metabolomic profiling provides new opportunities to realize the potential of omics-based precision medicine with regard to asthma. We leveraged over 14,000 individuals from four distinct epidemiological studies. We identified and independently replicated seventeen steroid metabolites that were significantly reduced in individuals with prevalent asthma. Importantly steroid levels were reduced among all individuals with asthma regardless of medication use; however, the largest reduction was associated with inhaled corticosteroids use (ICS) that was further confirmed in a four-year ICS clinical trial. Cortisol levels extracted from electronic medical records confirmed that cortisol is reduced among asthmatics taking ICS over the entire 24-hour period, compared with all other groups. Clinical-grade adrenal suppression in asthmatics on ICS, resulting from substantial reductions in steroid metabolites, represents a larger public health problem than previously recognized. Regular cortisol testing may identify at-risk individuals, enabling personalized treatment modifications and improving overall patient care.

An unaddressed and important issue is the role age plays in modulating response to short acting &beta, 2-agonists in individuals with asthma. The objective of this study was to identify whether age modifies genetic associations of single nucleotide polymorphisms (SNPs) with bronchodilator response (BDR) to &beta, 2-agonists. Using three cohorts with a total of 892 subjects, we ran a genome wide interaction study (GWIS) for each cohort to examine SNP by age interactions with BDR. A fixed effect meta-analysis was used to combine the results. In order to determine if previously identified BDR SNPs had an age interaction, we also examined 16 polymorphisms in candidate genes from two published genome wide association studies (GWAS) of BDR. There were no significant SNP by age interactions on BDR using the genome wide significance level of 5 &times, 10&minus, 8. Using a suggestive significance level of 5 &times, 6, three interactions, including one for a SNP within PRAG1 (rs4840337), were significant and replicated at the significance level of 0.05. Considering candidate genes from two previous GWAS of BDR, three SNPs (rs10476900 (near ADRB2) [p-value = 0.009], rs10827492 (CREM) [p-value = 0.02], and rs72646209 (NCOA3) [p-value = 0.02]) had a marginally significant interaction with age on BDR (p &lt, 0.05). Our results suggest age may be an important modifier of genetic associations for BDR in asthma.

While genome-wide association studies have identified genes involved in differential treatment responses to inhaled corticosteroids (ICS) in asthma, few studies have evaluated the potential effects of age in this context. A significant proportion of asthmatics experience exacerbations (hospitalizations and emergency department visits) during ICS treatment. We evaluated the interaction of genetic variation and age on ICS response (measured by the occurrence of exacerbations) through a genome-wide interaction study (GWIS) of 1,321 adult and child asthmatic patients of European ancestry. We identified 107 genome-wide suggestive (P

Background: Asthma is known to display different phenotypes across the life-course, suggesting that age related changes are particularly relevant to understanding asthma pathogenesis and remission. We have previously demonstrated that a lung function phenotype associated with asthma, bronchodilator response, is reduced with age, at rate of 0.24 percent per year. Methods: In this study, we interrogated the serum metabolome, to determine whether circulating metabolites mediate age-related changes in bronchodilator response (BDR) for individuals with asthma. We used data on 295 participants from the follow-up phase of the CAMP clinical trial (age 12.2–25.9 years; mean BDR of 8%, standard deviation 7%). Using a counterfactual framework, we analyzed over 500 pareto-scaled metabolites using mediation analysis to identify indirect effects of age through potential metabolite mediators. Results: There was a significant indirect effect of age on BDR through 4 plasmalogens (C36:1 PC and related metabolites) (Indirect Effect Beta = −0.001, p = 0.006). Conclusions: Our findings suggest that plasmalogens may contribute to age-related asthma phenotypes, and may also serve as potential pharmacologic targets for enhancement of lung function in individuals with asthma. Trial Registration: This work uses data from the previous clinical trial of asthma, the Childhood Asthma Management Program (CAMP), registered at ClinicalTrials.gov, # NCT00000575.

Rationale: Albuterol, a bronchodilator medication, is the first-line therapy for asthma worldwide. There are significant racial/ethnic differences in albuterol drug response. Objectives: To identify genetic variants important for bronchodilator drug response (BDR) in racially diverse children. Methods: We performed the first whole-genome sequencing pharmacogenetics study from 1,441 children with asthma from the tails of the BDR distribution to identify genetic association with BDR. Measurements and Main Results: We identified population-specific and shared genetic variants associated with BDR, including genome-wide significant (P

Variable responsiveness to zileuton, a leukotriene antagonist used to treat asthma, may be due in part to genetic variation. While individual SNPs were previously associated with zileuton-related lung function changes, specific quantitative trait loci (QTLs) and biological pathways that may contribute have not been identified. In this study, we investigated the hypothesis that genetic variation within biological pathways is associated with zileuton response. We performed an integrative QTL mapping and pathway enrichment study to investigate data from a GWAS of zileuton response, in addition to mRNA expression profiles and leukotriene production data from lymphoblastoid cell lines (LCLs) (derived from asthmatics) that were treated with zileuton or ethanol (control). We identified 1060 QTLs jointly associated with zileuton-related differential LTB4 production in LCLs and lung function change in patients taking zileuton, of which eight QTLs were also significantly associated with persistent LTB4 production in LCLs following zileuton treatment (i.e., ‘poor’ responders). Four nominally significant trans-eQTLs were predicted to regulate three candidate genes (SELL, MTF2, and GAL), the expression of which was significantly reduced in LCLs following zileuton treatment. Gene and pathway enrichment analyses of QTL associations identified multiple genes and pathways, predominantly related to phosphatidyl inositol signaling via PI3K. We validated the PI3K pathway activation status in a subset of LCLs demonstrating variable zileuton-related LTB4 production, and show that in contrast to LCLs that responded to zileuton, the PI3K pathway was activated in poor responder LCLs. Collectively, these findings demonstrate a role for the PIK3 pathway and its targets as important determinants of differential responsiveness to zileuton.

In this large, multi-ethnic GWAS of asthma, we identified novel associations with potential functional relevance for asthma susceptibility in older adults of diverse racial backgrounds.

Environmental factors play an important role in the development and exacerbation of allergic rhinitis (AR) in childhood. Indoor air pollution, such as house dust mites and secondhand smoke, can significantly increase the onset of AR, while pet dander may affect the exacerbation of AR symptoms in children. Furthermore, traffic related air pollution and pollen are outdoor air pollutants that can affect immune competency and airway responsiveness, increasing the risk of AR in children. Climate change has increased AR in children, as growth patterns of allergenic species have changed, resulting in longer pollen seasons. More extreme and frequent weather events also contribute to the deterioration of indoor air quality due to climate change. Additionally, viruses provoke respiratory tract infections, worsening the symptoms of AR, while viral infections alter the immune system. Although viruses and pollution influence development and exacerbation of AR, a variety of treatment and prevention options are available for AR patients. The protective influence of vegetation (greenness) is heavily associated with air pollution mitigation, relieving AR exacerbations, while the use of air filters can reduce allergic triggers. Oral antihistamines and intranasal corticosteroids are common pharmacotherapy for AR symptoms. In this review, we discuss the environmental risk factors for AR and summarize treatment strategies for preventing and managing AR in children.

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 role of metabolism in modifying age-related differential responses to asthma medications is insufficiently understood. The objective of this study was to determine the role of the metabolome in modifying the effect of age on bronchodilator response (BDR) in individuals with asthma. We used longitudinal measures of BDR and plasma metabolomic profiling in 565 children with asthma from the Childhood Asthma Management Program (CAMP) to identify age by metabolite interactions on BDR. The mean ages at the three studied time-points across 16 years of follow-up in CAMP were 8.8, 12.8, and 16.8 years, the mean BDRs were 11%, 9% and 8%, respectively. Of 501 identified metabolites, 39 (7.8%) demonstrated a significant interaction with age on BDR (p-value &lt, 0.05). We were able to validate two significant interactions in 320 children with asthma from the Genetics of Asthma in Costa Rica Study, 2-hydroxyglutarate, a compound involved in butanoate metabolism (interaction, CAMP: &beta, = &minus, 0.004, p = 1.8 &times, 10&minus, 4, GACRS: &beta, 0.015, p = 0.018), and a cholesterol ester, CE C18:1 (CAMP: &beta, = 0.005, p = 0.006, = 0.023, p = 0.041) Five additional metabolites had a p-value &lt, 0.1 in GACRS, including Gammaminobutyric acid (GABA), C16:0 CE, C20:4 CE, C18.0 CE and ribothymidine. These findings suggest Cholesterol esters and GABA may modify the estimated effect of age on bronchodilator response.

BACKGROUND Human Epstein-Barr virus-transformed lymphoblastoid cell lines (LCLs) have been thought to be a useful model system for pharmacogenomics studies. The purpose of this study was to determine the effect of Epstein-Barr virus transformation on gene expression changes by dexamethasone (Dex) in LCLs and primary B cells (PBCs) derived from the same individuals. PATIENTS AND METHODS We prepared LCLs and purified PBCs from the same six male donors participating in the Childhood Asthma Management Program clinical trial, and compared mRNA profiles after 6 h incubation with Dex (10 mol/l) or sham buffer. We assessed differential expression and put the list of differentially expressed genes into the web interface of ConsensusPathDB to find the pathway-level interpretation of our genes specified. As a supplementary analysis, we looked at the expression of the Dex-regulated (inducing or repressing) genes in treatment-naive PBCs and LCLs (pre-Dex treatment) from the GSE30916 dataset. RESULTS By hierarchical clustering, we found clustering of probes by cell types but not by individuals irrespective of Dex treatment. We observed that the Dex-regulated genes significantly overlapped in PBCs and LCLs. In addition, the expression of these genes showed significant correlations between treatment-naive PBCs and LCLs. Common genes showing significantly decreased expressions by the Dex treatment in both cells were enriched in immune responses and proinflammatory signaling pathways. CONCLUSION Taken together, these results suggest the uses of LCLs are representative of the primary biologic effects of corticosteroids treatment.

Aspirin intolerance is a severe and relatively rare asthmatic endotype, with prevalence rates of 10% in the adult asthmatic population and up to 25% in patients with severe, persistent asthma1–4. Consistent with the classification of asthma as a set of individual subtypes of diseases of varying symptoms and severity, Aspirin Exacerbated Respiratory Disease (AERD) is distinguished from other types of severe asthma primarily by its clinical characteristics. The clinical features of AERD include airway obstruction, increased exacerbations, chronic rhinosinusitis, the presence of nasal polyps, eosinophilia, increased need for systemic glucocorticoids and poor response to asthma controller medication, and an increase in urinary leukotrienes (LTs), both in comparison to Aspirin Tolerant Asthma (ATA) and following aspirin challenge and symptom exacerbations5,6. Due to the discovery that increased production of LTs is a characteristic of AERD, the leukotriene and prostaglandin production pathways were among the first to be investigated, and the subsequent identification of polymorphisms in LT-related genes in affected patients suggested a pivotal role for genetic variation in the development of AERD6–8. As a result, variation in patient genetics has received considerable focus as a potential determinant of AERD pathogenesis. The observation that severely asthmatic subjects responded favorably to anti-leukotriene asthma medications contributed further evidence toward a mechanistic role for the LTs, while also providing an opportunity for clinicians to more appropriately tailor treatment to a specific patient group 7,9–12. Subsequent genetic studies revealed considerable evidence for genetic variation in AERD pathophysiology across multiple biological pathways7,13, as well as variation in inter-individual treatment responses to multiple asthma drug classes including leukotriene modifiers and inhibitors14. However, the exact mechanisms by which LT synthesis becomes dysregulated in AERD are still unknown. Due to corresponding alteration of immune molecules (e.g. Th2 cytokines), prostaglandins (e.g. PGE2), and other inflammatory biomarkers (e.g. IL-5, periostin, IgE, ApoA1 and others), multiple interacting pathways and mechanisms likely also contribute. Evidence that AERD has a heritable basis is minimal, and only two studies reported that 1–6% of individuals with AERD had an affected family member4,15. The adult onset of AERD, combined with the low genetic penetrance and inconsistent replication of results from genetic associations point toward involvement of environmental exposures and epigenetic factors in its progression. Achieving a better understanding of the genetic and epigenetic determinants of heterogeneity of AERD through genome-wide and epigenome-wide interrogation is therefore anticipated to improve strategies to develop more precisely tailored therapeutic agents, treatment regimens, and potentially cures, for the disease.

BACKGROUND: Identifying metabolomic profiles of children with asthma has the potential to increase understanding of asthma pathophysiology. OBJECTIVE: To identify differences in plasma metabolites between children with and without current asthma at mid-childhood. METHODS: We used untargeted mass spectrometry to measure plasma metabolites in 237 children (46 current asthma cases and 191 controls) in Project Viva, a birth cohort from eastern Massachusetts, USA. Current asthma was assessed at mid-childhood (mean age 8.0 years). The ability of a broad spectrum metabolic profile to distinguish between cases and controls was assessed using partial least squares discriminant analysis. We used logistic regression models to identify individual metabolites that were differentially abundant by case-control status. We tested significant metabolites for replication in 411 children from the VDAART clinical trial. RESULTS: There was no evidence of a systematic difference in the metabolome of children reporting current asthma vs. healthy controls according to partial least squares discriminant analysis. However, several metabolites were associated with odds of current asthma at a nominally significant threshold (p

Background Genetic variants in the chromosomal region 17q21 are consistently associated with asthma. However, mechanistic studies have not yet linked any of the associated variants to a function that could influence asthma, and as a result, the identity of the asthma gene(s) remains elusive. Objectives We sought to identify and characterize functional variants in the 17q21 locus. Methods We used the Exome Aggregation Consortium browser to identify coding (amino acid–changing) variants in the 17q21 locus. We obtained asthma association measures for these variants in both the Genetic Epidemiology Research in Adult Health and Aging (GERA) cohort (16,274 cases and 38,269 matched controls) and the EVE Consortium study (5,303 asthma cases and 12,560 individuals). Gene expression and protein localization were determined by quantitative RT-PCR and fluorescence immunostaining, respectively. Molecular and cellular studies were performed to determine the functional effects of coding variants. Results Two coding variants (rs2305480 and rs11078928) of the gasdermin B ( GSDMB ) gene in the 17q21 locus were associated with lower asthma risk in both GERA (odds ratio, 0.92; P = 1.01 × 10 −6 ) and EVE (odds ratio, 0.85; joint P EVE = 1.31 × 10 −13 ). In GERA, rs11078928 had a minor allele frequency (MAF) of 0.45 in unaffected (nonasthmatic) controls and 0.43 in asthma cases. For European Americans in EVE, the MAF of rs2305480 was 0.45 for controls and 0.39 for cases; for all EVE subjects, the MAF was 0.32 for controls and 0.27 for cases. GSDMB is highly expressed in differentiated airway epithelial cells, including the ciliated cells. We found that, when the GSDMB protein is cleaved by inflammatory caspase-1 to release its N-terminal fragment, potent pyroptotic cell death is induced. The splice variant rs11078928 deletes the entire exon 6, which encodes 13 amino acids in the critical N-terminus, and abolishes the pyroptotic activity of the GSDMB protein. Conclusions Our study identified a functional asthma variant in the GSDMB gene of the 17q21 locus and implicates GSDMB-mediated epithelial cell pyroptosis in pathogenesis.

Inhaled corticosteroids (ICS) are the most effective controller medications for asthma, and variability in ICS response is associated with genetic variation. Despite ICS treatment, some patients with poor asthma control experience severe asthma exacerbations, defined as a hospitalization or emergency room visit. We hypothesized that some individuals may be at increased risk of asthma exacerbations, despite ICS use, due to genetic factors. A GWAS of 237,726 common, independent markers was conducted in 806 Caucasian asthmatic patients from two population‐based biobanks: BioVU, at Vanderbilt University Medical Center (VUMC) in Tennessee (369 patients), and Personalized Medicine Research Project (PMRP) at the Marshfield Clinic in Wisconsin (437 patients). Using a case–control study design, the association of each SNP locus with the outcome of asthma exacerbations (defined as asthma‐related emergency department visits or hospitalizations concurrent with oral corticosteroid use), was evaluated for each population by logistic regression analysis, adjusting for age, gender and the first four principal components. A meta‐analysis of the results was conducted. Validation of expression of selected candidate genes was determined by evaluating an independent microarray expression data set. Our study identified six novel SNPs associated with differential risk of asthma exacerbations (P

Heterogeneous therapeutic responses to leukotriene modifiers (LTMs) are likely due to variation in patient genetics. Although prior candidate gene studies implicated multiple pharmacogenetic loci, to date, no genome-wide association study (GWAS) of LTM response was reported. In this study, DNA and phenotypic information from two placebo-controlled trials (total N=526) of zileuton response were interrogated. Using a gene-environment (G × E) GWAS model, we evaluated 12-week change in forced expiratory volume in 1 second (ΔFEV1) following LTM treatment. The top 50 single-nucleotide polymorphism associations were replicated in an independent zileuton treatment cohort, and two additional cohorts of montelukast response. In a combined analysis (discovery+replication), rs12436663 in MRPP3 achieved genome-wide significance (P=6.28 × 10(-08)); homozygous rs12436663 carriers showed a significant reduction in mean ΔFEV1 following zileuton treatment. In addition, rs517020 in GLT1D1 was associated with worsening responses to both montelukast and zileuton (combined P=1.25 × 10(-07)). These findings implicate previously unreported loci in determining therapeutic responsiveness to LTMs.

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.

We show here that combining two existing genome wide association studies (GWAS) yields additional biologically relevant information, beyond that obtained by either GWAS separately. We propose Joint GWAS Analysis, a method that compares a pair of GWAS for similarity among the top SNP associations, top genes identified, gene functional clusters, and top biological pathways. We show that Joint GWAS Analysis identifies additional enriched biological pathways that would be missed by traditional Single-GWAS analysis. Furthermore, we examine the similarities of six complex genetic disorders at the SNP-level, gene-level, gene-cluster-level, and pathway-level. We make concrete hypotheses regarding novel pathway associations for several complex disorders considered, based on the results of Joint GWAS Analysis. Together, these results demonstrate that common complex disorders share substantially more genomic architecture than has been previously realized and that the meta-analysis of GWAS needs not be limited to GWAS of the same phenotype to be informative.

Glucocorticoids (GCs)—ligands of the glucocorticoid receptor (GR)—are widely used to treat inflammatory diseases, but suffer from significant side effects and poor responsiveness in certain patient populations. Identification of chemical GR modulators may provide insights into the regulatory mechanisms of anti-inflammatory functions of GR and help improve GC-based therapy. Here we report the development and application of a high-throughput screening to identify compounds that either enhance or suppress the anti-inflammatory effect of GR function. Using a cell-based GR activity assay that measures Dexamethasone (Dex)-mediated NF-κB repression, we have screened ~8,000 compounds and identified several compounds that suppressed GR activity, including multiple GSK3β inhibitors and anti-cancer agent camptothecin. Notably, we also identified two kinase IKK2 inhibitors, including TPCA-1, as GR enhancers that improve the anti-inflammatory effect of GR. In particular, TPCA-1 augmented the activity of Dex in NF-κB repression by attenuating GR down-regulation. Consistent with the observation, siRNA-mediated IKK2 knockdown decreased GR down-regulation and increased GR expression. Together, our results identified chemical compounds as novel modulators of GR and revealed an unexpected role for IKK2 in GR down-regulation. Furthermore, we have established a high-throughput screening platform for discovering GR-modulating compounds that may be repurposed to improve current GC-based therapies.

Background Metabolic homeostasis is substantially disrupted in critical illness. Given the pleiotropic effects of vitamin D, we hypothesized that metabolic profiles differ between critically ill patients relative to their vitamin D status. Methods We performed a metabolomics study on biorepository samples collected from a single academic medical center on 65 adults with systemic inflammatory response syndrome or sepsis treated in a 20-bed medical ICU between 2008 and 2010. To identify key metabolites and metabolic pathways related to vitamin D status in critical illness, we first generated metabolomic data using gas and liquid chromatography mass spectroscopy. We followed this by partial least squares-discriminant analysis to identify individual metabolites that were significant. We then interrogated the entire metabolomics profile using metabolite set enrichment analysis to identify groups of metabolites and pathways that were differentiates of vitamin D status. Finally we performed logistic regression to construct a network model of chemical-protein target interactions important in vitamin D status. Results Metabolomic profiles significantly differed in critically ill patients with 25(OH)D ≤ 15 ng/ml relative to those with levels >15 ng/ml. In particular, increased 1,5-anhydroglucitol, tryptophan betaine, and 3-hydroxyoctanoate as well as decreased 2-arachidonoyl-glycerophosphocholine and N-6-trimethyllysine were strong predictors of 25(OH)D >15 ng/ml. The combination of these five metabolites led to an area under the curve for discrimination for 25(OH)D > 15 ng/ml of 0.82 (95% CI 0.71–0.93). The metabolite pathways related to glutathione metabolism and glutamate metabolism are significantly enriched with regard to vitamin D status. Conclusion Vitamin D status is associated with differential metabolic profiles during critical illness. Glutathione and glutamate pathway metabolism, which play principal roles in redox regulation and immunomodulation, respectively, were significantly altered with vitamin D status. Electronic supplementary material The online version of this article (doi:10.1186/s13054-017-1794-y) contains supplementary material, which is available to authorized users.

Background Asthma represents a significant public health burden; however, novel biological therapies targeting immunoglobulin E (IgE)-mediated pathways have widened clinical treatment options for the disease. Objective In this study, we sought to identify gene transcripts and gene networks involved in the determination of serum IgE levels in people with asthma that can help inform the development of novel therapeutic agents. Methods We analysed gene expression data from a cross-sectional study of 326 Costa Rican children with asthma, aged 6 to 12 years, from the Genetics of Asthma in Costa Rica Study and 610 young adults with asthma, aged 16 to 25 years, from the Childhood Asthma Management Program trial. We utilized differential gene expression analysis and performed weighted gene coexpression network analysis on 25 060 genes, to identify gene transcripts and network modules associated with total IgE, adjusting for age and gender. We used pathway enrichment analyses to identify key biological pathways underlying significant modules. We compared findings that replicated between both populations. Results We identified 31 transcripts associated with total IgE that replicated between the two study cohorts. These results were notable for increased eosinophil-related transcripts (including IL5RA, CLC, SMPD3, CCL23 and CEBPE). Pathway enrichment identified the regulation of T cell tolerance as important in the determination of total IgE levels, supporting a key role for IDO1. Conclusions and clinical relevance These results provide robust evidence that biologically meaningful gene expression profiles (relating to eosinophilic and regulatory T cell pathways in particular) associated with total IgE levels can be identified in individuals diagnosed with asthma during childhood. These profiles and their constituent genes may represent novel therapeutic targets.

Preeclampsia is a leading cause of maternal and fetal mortality worldwide, yet its exact pathogenesis remains elusive. This study, nested within the Vitamin D Antenatal Asthma Reduction Trial (VDAART), aimed to develop integrated omics models of preeclampsia that have utility in both prediction and in the elucidation of underlying biological mechanisms. Metabolomic profiling was performed on first trimester plasma samples of 47 pregnant women from VDAART who subsequently developed preeclampsia and 62 controls with healthy pregnancies, using liquid-chromatography tandem mass-spectrometry. Metabolomic profiles were generated based on logistic regression models and assessed using Received Operator Characteristic Curve analysis. These profiles were compared to profiles from generated using third trimester samples. The first trimester metabolite profile was then integrated with a pre-existing transcriptomic profile using network methods. In total, 72 (0.9%) metabolite features were associated (p

The solute carrier 6 (SLC6) is a family of ion-dependent transporters that mediate uptake into the cell of osmolytes such as neurotransmitters and amino acids. Four SLC6 members transport GABA, a key neurotransmitter that triggers inhibitory signaling pathways via various receptors (e.g., GABA(A)). The GABA transporters (GATs) regulate the concentration of GABA available for signaling and are thus targeted by a variety of anticonvulsant and relaxant drugs. Here, we characterize GAT-2, a transporter that plays a role in peripheral GABAergic mechanisms, by constructing comparative structural models based on crystallographic structures of the leucine transporter LeuT. Models of GAT-2 in two different conformations were constructed and experimentally validated, using site-directed mutagenesis. Computational screening of 594,166 compounds including drugs, metabolites, and fragment-like molecules from the ZINC database revealed distinct ligands for the two GAT-2 models. 31 small molecules, including high scoring compounds and molecules chemically related to known and predicted GAT-2 ligands, were experimentally tested in inhibition assays. Twelve ligands were found, six of which were chemically novel (e.g., homotaurine). Our results suggest that GAT-2 is a high selectivity/low affinity transporter that is resistant to inhibition by typical GABAergic inhibitors. Finally, we compared the binding site of GAT-2 with those of other SLC6 members, including the norepinephrine transporter and other GATs, to identify ligand specificity determinants for this family. Our combined approach may be useful for characterizing interactions between small molecules and other membrane proteins, as well as for describing substrate specificities in other protein families.

In order to improve therapeutic outcomes, there is a tremendous need to identify patients who are likely to respond to a given asthma treatment. Pharmacogenomic studies have explained a portion of the variability in drug response and provided an increasing list of candidate genes and SNPs. However, as phenotypic variation arises from a network of complex interactions among genetic and environmental factors, rather than individual genes or SNPs, a multidisciplinary, systems-level approach is required in order to understand the inter-relationships among these factors. Systems biology, which seeks to capture interactions between genetic factors and other variables, offers a promising approach to improved therapeutic outcomes in asthma. This aritcle will review and update progress in the pharmacogenomics of asthma and then discuss the application of systems biology approaches to asthma pharmacogenomics.

The solute carrier (Slc) superfamily is a major group of membrane transport proteins present in mammalian cells. Although Slc transporters play essential and diverse roles in the central nervous system, the localization and function of the vast majority of Slc genes in the mammalian brain are largely unknown. Using high-throughput in situ hybridization data generated by the Allen Brain Atlas, we systematically and quantitatively analyzed the spatial and cellular distribution of 307 Slc genes, which represent nearly 90% of presently known mouse Slc genes, in the adult C57BL/6J mouse brain. Our analysis showed that 252 (82%) of the 307 Slc genes are present in the brain, and a large proportion of these genes were detected at low to moderate expression levels. Evaluation of 20 anatomical brain subdivisions demonstrated a comparable level of Slc gene complexity but significant difference in transcript enrichment. The distribution of the expressed Slc genes was diverse, ranging from near-ubiquitous to highly localized. Functional annotation in 20 brain regions, including the blood-brain and blood-cerebral spinal fluid (CSF) barriers, suggests major roles of Slc transporters in supporting brain energy utilization, neurotransmission, nutrient supply, and CSF production. Furthermore, hierarchical cluster analysis revealed intricate Slc expression patterns associated with neuroanatomical organization. Our studies also revealed Slc genes present within defined brain microstructures and described the putative cell types expressing individual Slc genes. These results provide a useful resource for investigators to explore the roles of Slc genes in neurophysiological and pathological processes.

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.