Gene Expression Profiling in Blood Provides Reproducible Molecular Insights into Asthma Control

Gasdermin B, an asthma-susceptibility gene, promotes MAVS-TBK1 signalling and airway inflammation

RATIONALE

Respiratory virus-induced inflammation is the leading cause of asthma exacerbation, frequently accompanied by induction of interferon-stimulated genes (ISGs). How asthma-susceptibility genes modulate cellular response upon viral infection by fine-tuning ISG induction and subsequent airway inflammation in genetically susceptible asthma patients remains largely unknown.

OBJECTIVES

To decipher the functions of gasdermin B (encoded by GSDMB) in respiratory virus-induced lung inflammation.

METHODS

In two independent cohorts, we analysed expression correlation between GSDMB and ISG s. In human bronchial epithelial cell line or primary bronchial epithelial cells, we generated GSDMB-overexpressing and GSDMB-deficient cells. A series of quantitative PCR, ELISA and co-immunoprecipitation assays were performed to determine the function and mechanism of GSDMB for ISG induction. We also generated a novel transgenic mouse line with inducible expression of human unique GSDMB gene in airway epithelial cells and infected the mice with respiratory syncytial virus to determine the role of GSDMB in respiratory syncytial virus-induced lung inflammation in vivo.

RESULTS

GSDMB is one of the most significant asthma-susceptibility genes at 17q21 and acts as a novel RNA sensor, promoting mitochondrial antiviral-signalling protein (MAVS)-TANK binding kinase 1 (TBK1) signalling and subsequent inflammation. In airway epithelium, GSDMB is induced by respiratory viral infections. Expression of GSDMB and ISGs significantly correlated in respiratory epithelium from two independent asthma cohorts. Notably, inducible expression of human GSDMB in mouse airway epithelium led to enhanced ISGs induction and increased airway inflammation with mucus hypersecretion upon respiratory syncytial virus infection.

CONCLUSIONS

GSDMB promotes ISGs expression and airway inflammation upon respiratory virus infection, thereby conferring asthma risk in risk allele carriers.

Methyl-TWAS: A powerful method for in silico transcriptome-wide association studies (TWAS) using long-range DNA methylation

In silico transcriptome-wide association studies (TWAS) are commonly used to test whether expression of specific genes is linked to a complex trait. However, genotype-based in silico TWAS such as PrediXcan, exhibit low prediction accuracy for a majority of genes because genotypic data lack tissue- and disease-specificity and are not affected by the environment. Because methylation is tissue-specific and, like gene expression, can be modified by environment or disease status, methylation should predict gene expression with more accuracy than SNPs. Therefore, we propose Methyl-TWAS, the first approach that utilizes long-range methylation markers to impute gene expression for in silico TWAS through penalized regression. Methyl-TWAS 1) predicts epigenetically regulated/associated expression (eGReX), which incorporates tissue-specific expression and both genetically- (GReX) and environmentally-regulated expression to identify differentially expressed genes (DEGs) that could not be identified by genotype-based methods; and 2) incorporates both cis- and trans- CpGs, including various regulatory regions to identify DEGs that would be missed using cis- methylation only. Methyl-TWAS outperforms PrediXcan and two other methods in imputing gene expression in the nasal epithelium, particularly for immunity-related genes and DEGs in atopic asthma. Methyl-TWAS identified 3,681 (85.2%) of the 4,316 DEGs identified in a previous TWAS of atopic asthma using measured expression, while PrediXcan could not identify any gene. Methyl-TWAS also outperforms PrediXcan for expression imputation as well as in silico TWAS in white blood cells. Methyl-TWAS is a valuable tool for in silico TWAS, leveraging a growing body of publicly available genome-wide DNA methylation data for a variety of human tissues.

Neutrophil extracellular trap production and CCL4L2 expression influence corticosteroid response in asthma

The association between neutrophil extracellular traps (NETs) and response to inhaled corticosteroids (ICS) in asthma is unclear. To better understand this relationship, we analyzed the blood transcriptomes from children with controlled and uncontrolled asthma in the Taiwanese Consortium of Childhood Asthma Study using weighted gene coexpression network analysis and pathway enrichment methods. We identified 298 uncontrolled asthma-specific differentially expressed genes and one gene module associated with neutrophil-mediated immunity, highlighting a potential role for neutrophils in uncontrolled asthma. We also found that NET abundance was associated with nonresponse to ICS in patients. In a neutrophilic airway inflammation murine model, steroid treatment could not suppress neutrophilic inflammation and airway hyperreactivity. However, NET disruption with deoxyribonuclease I (DNase I) efficiently inhibited airway hyperreactivity and inflammation. Using neutrophil-specific transcriptomic profiles, we found that CCL4L2 was associated with ICS nonresponse in asthma, which was validated in human and murine lung tissue. CCL4L2 expression was also negatively correlated with pulmonary function change after ICS treatment. In summary, steroids fail to suppress neutrophilic airway inflammation, highlighting the potential need to use alternative therapies such as leukotriene receptor antagonists or DNase I that target the neutrophil-associated phenotype. Furthermore, these results highlight CCL4L2 as a potential therapeutic target for individuals with asthma refractory to ICS.

Identification of autoantigens and their potential post-translational modification in EGPA and severe eosinophilic asthma

Background

The chronic airway inflammation in severe eosinophilic asthma (SEA) suggests potential autoimmune aetiology with unidentified autoantibodies analogous to myeloperoxidase (MPO) in ANCA-positive EGPA (eosinophilic granulomatosis with polyangiitis). Previous research has shown that oxidative post-translational modification (oxPTM) of proteins is an important mechanism by which autoantibody responses may escape immune tolerance. Autoantibodies to oxPTM autoantigens in SEA have not previously been studied.

Methods

Patients with EGPA and SEA were recruited as well as healthy control participants. Autoantigen agnostic approach: Participant serum was incubated with slides of unstimulated and PMA-stimulated neutrophils and eosinophils, and autoantibodies to granulocytes were identified by immunofluorescence with anti-human IgG FITC antibody. Target autoantigen approach: Candidate proteins were identified from previous literature and FANTOM5 gene set analysis for eosinophil expressed proteins. Serum IgG autoantibodies to these proteins, in native and oxPTM form, were detected by indirect ELISA.

Results

Immunofluorescence studies showed that serum from patients with known ANCA stained for IgG against neutrophils as expected. In addition, serum from 9 of 17 tested SEA patients stained for IgG to PMA-stimulated neutrophils undergoing NETosis. Immunofluorescent staining of eosinophil slides was evident with serum from all participants (healthy and with eosinophilic disease) with diffuse cytoplasmic staining except for one SEA individual in whom subtle nuclear staining was evident. FANTOM5 gene set analysis identified TREM1 (triggering receptor expressed on myeloid cells 1) and IL-1 receptor 2 (IL1R2) as eosinophil-specific targets to test for autoantibody responses in addition to MPO, eosinophil peroxidase (EPX), and Collagen-V identified from previous literature. Indirect ELISAs found high concentrations of serum autoantibodies to Collagen-V, MPO, and TREM1 in a higher proportion of SEA patients than healthy controls. High concentrations of serum autoantibodies to EPX were evident in serum from both healthy and SEA participants. The proportion of patients with positive autoantibody ELISAs was not increased when examining oxPTM compared to native proteins.

Discussion

Although none of the target proteins studied showed high sensitivity for SEA, the high proportion of patients positive for at least one serum autoantibody shows the potential of more research on autoantibody serology to improve diagnostic testing for severe asthma.

Clinical trial registration

ClinicalTrials.gov, identifier, NCT04671446.

ACDC: a general approach for detecting phenotype or exposure associated co-expression

Background

Existing module-based differential co-expression methods identify differences in gene-gene relationships across phenotype or exposure structures by testing for consistent changes in transcription abundance. Current methods only allow for assessment of co-expression variation across a singular, binary or categorical exposure or phenotype, limiting the information that can be obtained from these analyses.

Methods

Here, we propose a novel approach for detection of differential co-expression that simultaneously accommodates multiple phenotypes or exposures with binary, ordinal, or continuous data types.

Results

We report an application to two cohorts of asthmatic patients with varying levels of asthma control to identify associations between gene co-expression and asthma control test scores. Results suggest that both expression levels and covariances of ADORA3, ALOX15, and IDO1 are associated with asthma control.

Conclusion

ACDC is a flexible extension to existing methodology that can detect differential co-expression across varying external variables.

Transcriptome-wide association study of circulating IgE levels identifies novel targets for asthma and allergic diseases

Measurement of circulating immunoglobulin E (IgE) concentration is helpful for diagnosing and treating asthma and allergic diseases. Identifying gene expression signatures associated with IgE might elucidate novel pathways for IgE regulation. To this end, we performed a discovery transcriptome-wide association study to identify differentially expressed genes associated with circulating IgE levels in whole-blood derived RNA from 5,345 participants in the Framingham Heart Study across 17,873 mRNA gene-level transcripts. We identified 216 significant transcripts at a false discovery rate <0.05. We conducted replication using the meta-analysis of two independent external studies: the Childhood Asthma Management Program (n=610) and the Genetic Epidemiology of Asthma in Costa Rica Study (n=326); we then reversed the discovery and replication cohorts, which revealed 59 significant genes that replicated in both directions. Gene ontology analysis revealed that many of these genes were implicated in immune function pathways, including defense response, inflammatory response, and cytokine production. Mendelian randomization (MR) analysis revealed four genes (CLC, CCDC21, S100A13, and GCNT1) as putatively causal (p<0.05) regulators of IgE levels. GCNT1 (beta=1.5, p=0.01)-which is a top result in the MR analysis of expression in relation to asthma and allergic diseases-plays a role in regulating T helper type 1 cell homing, lymphocyte trafficking, and B cell differentiation. Our findings build upon prior knowledge of IgE regulation and provide a deeper understanding of underlying molecular mechanisms. The IgE-associated genes that we identified-particularly those implicated in MR analysis-can be explored as promising therapeutic targets for asthma and IgE-related diseases.

Asthma Susceptibility Gene ORMDL3 Promotes Autophagy in Human Bronchial Epithelium

The genome-wide association study (GWAS)-identified asthma susceptibility risk alleles on chromosome 17q21 increase the expression of ORMDL3 (ORMDL sphingolipid biosynthesis regulator 3) in lung tissue. Given the importance of epithelial integrity in asthma, we hypothesized that ORMDL3 directly impacted bronchial epithelial function. To determine whether and how ORMDL3 expression impacts the bronchial epithelium, in studies using both primary human bronchial epithelial cells and human bronchial epithelial cell line, 16HBE (16HBE14o-), we assessed the impact of ORMDL3 on autophagy. Studies included: autophagosome detection by electron microscopy, RFP-GFP-LC3B to assess autophagic activity, and Western blot analysis of autophagy-related proteins. Mechanistic assessments included immunoprecipitation assays, intracellular calcium mobilization assessments, and cell viability assays. Coexpression of ORMDL3 and autophagy-related genes was measured in primary human bronchial epithelial cells derived from 44 subjects. Overexpressing ORMDL3 demonstrated increased numbers of autophagosomes and increased levels of autophagy-related proteins LC3B, ATG3, ATG7, and ATG16L1. ORMDL3 overexpression promotes autophagy and subsequent cell death by impairing intracellular calcium mobilization through interacting with SERCA2. Strong correlation was observed between expression of ORMDL3 and autophagy-related genes in patient-derived bronchial epithelial cells. Increased ORMDL3 expression induces autophagy, possibly through interacting with SERCA2, thereby inhibiting intracellular calcium influx, and induces cell death, impairing bronchial epithelial function in asthma.

Transcriptomic and metabolomic associations with exposures to air pollutants among young adults with childhood asthma history

Ambient air pollutants are well-known risk factors for childhood asthma and asthma exacerbation. It is unknown whether different air pollutants individually or jointly affect pathophysiological mechanisms of asthma. In this study, we aim to integrate transcriptome and untargeted metabolome to identify dysregulated genetic and metabolic pathways that are associated with exposures to a mixture of ambient and traffic-related air pollutants among adults with asthma history. In this cross-sectional study, 102 young adults with childhood asthma history were enrolled from southern California in 2012. Whole blood transcriptome was measured with 20,869 expression signatures, and serum untargeted metabolomics including 937 metabolites were analyzed by Metabolon, Inc. Participants' exposures to regional air pollutants (NO₂, O₃, PM₁₀, PM_2.5) and near-roadway air pollutants averaged at one month and one year before study visit were estimated based on residential addresses. xMWAS network analysis and joint-pathway analysis were performed to identify subnetworks and genetic and metabolic pathways that were associated with exposure to air pollutants adjusted for socio-characteristic covariates. Network analysis found that exposures to air pollutants mixture were connected to 357 gene markers and 92 metabolites. One-year and one-month averaged PM_2.5 and NO₂ were associated with several amino acids related to serine, glycine, and beta-alanine metabolism. Lower serum levels of carnosine and aspartate, which are involved in the beta-alanine metabolic pathway, as well as choline were also associated with worse asthma control (p < 0.05). One-year and one-month averaged PM₁₀ and one-month averaged O₃ were associated with higher gene expression levels of HSPA5, LGMN, CTSL and HLA-DPB1, which are involved in antigen processing and presentation. These results indicate that exposures to various air pollutants are associated with altered genetic and metabolic pathways that affect anti-oxidative capacity and immune response and can potentially contribute to asthma-related pathophysiology.

Blood miRNAs Are Linked to Frequent Asthma Exacerbations in Childhood Asthma and Adult COPD

MicroRNAs have been independently associated with asthma and COPD; however, it is unclear if microRNA associations will overlap when evaluating retrospective acute exacerbations. Objective: We hypothesized that peripheral blood microRNAs would be associated with retrospective acute asthma exacerbations in a pediatric asthma cohort and that such associations may also be relevant to acute COPD exacerbations. Methods: We conducted small-RNA sequencing on 374 whole-blood samples from children with asthma ages 6-14 years who participated in the Genetics of Asthma in Costa Rica Study (GACRS) and 450 current and former adult smokers with and without COPD who participated in the COPDGene study. Measurements and Main Results: After QC, we had 351 samples and 649 microRNAs for Differential Expression (DE) analysis between the frequent (n = 183) and no or infrequent exacerbation (n = 168) groups in GACRS. Fifteen upregulated miRs had odds ratios (OR) between 1.22 and 1.59 for a doubling of miR counts, while five downregulated miRs had ORs between 0.57 and 0.8. These were assessed for generalization in COPDGene, where three of the upregulated miRs (miR-532-3p, miR-296-5p, and miR-766-3p) and two of the downregulated miRs (miR-7-5p and miR-451b) replicated. Pathway enrichment analysis showed MAPK and PI3K-Akt signaling pathways were strongly enriched for target genes of DE miRNAs and miRNAs generalizing to COPD exacerbations, as well as infection response pathways to various pathogens. Conclusion: miRs (451b; 7-5p; 532-3p; 296-5p and 766-3p) associated with both childhood asthma and adult COPD exacerbations may play a vital role in airflow obstruction and exacerbations and point to shared genomic regulatory machinery underlying exacerbations in both diseases.

Multi-Omics Profiling Approach to Asthma: An Evolving Paradigm

Asthma is a complex multifactorial and heterogeneous respiratory disease. Although genetics is a strong risk factor of asthma, external and internal exposures and their interactions with genetic factors also play important roles in the pathophysiology of asthma. Over the past decades, the application of high-throughput omics approaches has emerged and been applied to the field of asthma research for screening biomarkers such as genes, transcript, proteins, and metabolites in an unbiased fashion. Leveraging large-scale studies representative of diverse population-based omics data and integrating with clinical data has led to better profiling of asthma risk. Yet, to date, no omic-driven endotypes have been translated into clinical practice and management of asthma. In this article, we provide an overview of the current status of omics studies of asthma, namely, genomics, transcriptomics, epigenomics, proteomics, exposomics, and metabolomics. The current development of the multi-omics integrations of asthma is also briefly discussed. Biomarker discovery following multi-omics profiling could be challenging but useful for better disease phenotyping and endotyping that can translate into advances in asthma management and clinical care, ultimately leading to successful precision medicine approaches.

Plasma proteins elevated in severe asthma despite oral steroid use and unrelated to Type-2 inflammation

Rationale

Asthma phenotyping requires novel biomarker discovery.

Objectives

To identify plasma biomarkers associated with asthma phenotypes by application of a new proteomic panel to samples from two well-characterised cohorts of severe (SA) and mild-to-moderate (MMA) asthmatics, COPD subjects and healthy controls (HCs).

Methods

An antibody-based array targeting 177 proteins predominantly involved in pathways relevant to inflammation, lipid metabolism, signal transduction and extracellular matrix was applied to plasma from 525 asthmatics and HCs in the U-BIOPRED cohort, and 142 subjects with asthma and COPD from the validation cohort BIOAIR. Effects of oral corticosteroids (OCS) were determined by a 2-week, placebo-controlled OCS trial in BIOAIR, and confirmed by relation to objective OCS measures in U-BIOPRED.

Results

In U-BIOPRED, 110 proteins were significantly different, mostly elevated, in SA compared to MMA and HCs. 10 proteins were elevated in SA versus MMA in both U-BIOPRED and BIOAIR (alpha-1-antichymotrypsin, apolipoprotein-E, complement component 9, complement factor I, macrophage inflammatory protein-3, interleukin-6, sphingomyelin phosphodiesterase 3, TNF receptor superfamily member 11a, transforming growth factor-β and glutathione S-transferase). OCS treatment decreased most proteins, yet differences between SA and MMA remained following correction for OCS use. Consensus clustering of U-BIOPRED protein data yielded six clusters associated with asthma control, quality of life, blood neutrophils, high-sensitivity C-reactive protein and body mass index, but not Type-2 inflammatory biomarkers. The mast cell specific enzyme carboxypeptidase A3 was one major contributor to cluster differentiation.

Conclusions

The plasma proteomic panel revealed previously unexplored yet potentially useful Type-2-independent biomarkers and validated several proteins with established involvement in the pathophysiology of SA.

Application of new proteomic panel in two established European asthma cohorts identifies plasma proteins associated with disease severity independently of Type-2 inflammation, suggesting potentially useful novel biomarkers and therapeutic targets.https://bit.ly/3jtTq5m

PTGDR2 Expression in Peripheral Blood as a Potential Biomarker in Adult Patients with Asthma

Background: Precision medicine is a promising strategy to identify biomarkers, stratify asthmatic patients according to different endotypes, and match them with the appropriate therapy. This proof-of-concept study aimed to investigate whether gene expression in peripheral blood could provide a valuable noninvasive approach for the molecular phenotyping of asthma. Methods: We performed whole-transcriptome RNA sequencing on peripheral blood of 30 non-atopic non-asthmatic controls and 30 asthmatic patients. A quantitative PCR (qPCR) validation study of PTGDR2 that encodes for CRTH2 receptor, expressed in cells involved in T2 inflammation, was developed in a cohort of 361 independent subjects: 94 non-asthmatic non-atopic controls, 187 asthmatic patients [including 82 with chronic rhinosinusitis with nasal polyposis (CRSwNP) and 24 with aspirin-exacerbated respiratory disease (AERD)], 52 with allergic rhinitis, and 28 with CRSwNP without asthma. Results: PTGDR2 was one of the most differentially overexpressed genes in asthmatic patients’ peripheral blood (p-value 2.64 × 10⁶). These results were confirmed by qPCR in the validation study, where PTGDR2 transcripts were significantly upregulated in asthmatic patients (p < 0.001). This upregulation was mainly detected in some subgroups such as allergic asthma, asthma with CRSwNP, AERD, eosinophilic asthma, and severe persistent asthma. PTGDR2 expression was detected in different blood cell types, and its correlation with eosinophil counts showed differences in some groups of asthmatic patients. Conclusions: We found that PTGDR2 expression levels could identify asthma patients, introduce a minimally invasive biomarker for adult asthma molecular phenotyping, and add additional information to blood eosinophils. Although further studies are required, analyzing PTGDR2 expression levels in peripheral blood of asthmatics might assist in selecting patients for treatment with specific antagonists.

A Transcriptome-Wide Association Study Identifies Candidate Susceptibility Genes for Pancreatic Cancer Risk

Pancreatic cancer is among the most well-characterized cancer types, yet a large proportion of the heritability of pancreatic cancer risk remains unclear. Here, we performed a large transcriptome-wide association study to systematically investigate associations between genetically predicted gene expression in normal pancreas tissue and pancreatic cancer risk. Using data from 305 subjects of mostly European descent in the Genotype-Tissue Expression Project, we built comprehensive genetic models to predict normal pancreas tissue gene expression, modifying the UTMOST (unified test for molecular signatures). These prediction models were applied to the genetic data of 8,275 pancreatic cancer cases and 6,723 controls of European ancestry. Thirteen genes showed an association of genetically predicted expression with pancreatic cancer risk at an FDR ≤ 0.05, including seven previously reported genes (INHBA, SMC2, ABO, PDX1, RCCD1, CFDP1, and PGAP3) and six novel genes not yet reported for pancreatic cancer risk [6q27: SFT2D1 OR (95% confidence interval (CI), 1.54 (1.25-1.89); 13q12.13: MTMR6 OR (95% CI), 0.78 (0.70-0.88); 14q24.3: ACOT2 OR (95% CI), 1.35 (1.17-1.56); 17q12: STARD3 OR (95% CI), 6.49 (2.96-14.27); 17q21.1: GSDMB OR (95% CI), 1.94 (1.45-2.58); and 20p13: ADAM33 OR (95% CI): 1.41 (1.20-1.66)]. The associations for 10 of these genes (SFT2D1, MTMR6, ACOT2, STARD3, GSDMB, ADAM33, SMC2, RCCD1, CFDP1, and PGAP3) remained statistically significant even after adjusting for risk SNPs identified in previous genome-wide association study. Collectively, this analysis identified novel candidate susceptibility genes for pancreatic cancer that warrant further investigation. SIGNIFICANCE: A transcriptome-wide association analysis identified seven previously reported and six novel candidate susceptibility genes for pancreatic cancer risk.

Resolving Clinical Phenotypes into Endotypes in Allergy: Molecular and Omics Approaches

Allergic diseases are highly complex with respect to pathogenesis, inflammation, and response to treatment. Current efforts for allergic disease diagnosis have focused on clinical evidence as a binary outcome. Although outcome status based on clinical phenotypes (observable characteristics) is convenient and inexpensive to measure in large studies, it does not adequately provide insight into the complex molecular determinants of allergic disease. Individuals with similar clinical diagnoses do not necessarily have similar disease etiologies, natural histories, or responses to treatment. This heterogeneity contributes to the ineffective response to treatment leading to an annual estimated cost of $350 billion in the USA alone. There has been a recent focus to deconvolute the clinical heterogeneity of allergic diseases into specific endotypes using molecular and omics approaches. Endotypes are a means to classify patients based on the underlying pathophysiological mechanisms involving distinct functions or treatment response. The advent of high-throughput molecular omics, immunophenotyping, and bioinformatics methods including machine learning algorithms is facilitating the development of endotype-based diagnosis. As we move to the next decade, we should truly start treating clinical endotypes not clinical phenotype. This review highlights current efforts taking place to improve allergic disease endotyping via molecular omics profiling, immunophenotyping, and machine learning approaches in the context of precision diagnostics in allergic diseases. Graphical Abstract.

DNA methylation is associated with improvement in lung function on inhaled corticosteroids in pediatric asthmatics

Asthma is the most common chronic disease in children. Inhaled corticosteroids (ICS) are the first-line treatment for asthma control, but up to one-third of children have a poor treatment response. The mechanism of ICS resistance is poorly understood, and the role of DNA methylation in ICS treatment response is not known. We examined the association between peripheral blood DNA methylation and ICS treatment response in 152 pediatric persistent asthmatics from the Childhood Asthma Management Program. Response to ICS was measured by the percentage change in forced expiratory volume in 1 s (FEV1) 8 weeks after treatment initiation. The top CpG sites with a nominal P value less than 0.001 were correlated with gene expression using Pearson's and partial correlations. In 152 participants, mean±SD age was 9.8±2.0 years and median change in FEV1 after ICS initiation was 4.6% (interquartile range: 10.4%). A total of 545 CpG sites were differentially methylated (nominal P<0.05), and seven CpG sites had a nominal P value less than 0.001. Relative hypermethylation of cg20434811, cg02822723, cg14066280, cg27254601, and cg23913400 and relative hypomethylation of cg24937126 and cg24711626 were associated with an increase in FEV1 on ICS treatment. One CpG site was associated with gene expression. Relative hypermethylation of cg27254601 was associated with both an increase in FEV1 and BOLA2 expression (ρ=0.25, P=0.02). We identified a novel association between BOLA2 methylation, gene expression, and ICS response as measured by lung function. Pharmacoepigenetics has the potential to detect treatment sensitivity in persistent childhood asthma.

Expression of SMARCD1 interacts with age in association with asthma control on inhaled corticosteroid therapy

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.

Understanding the Molecular Mechanisms of Asthma through Transcriptomics

The transcriptome represents the complete set of RNA transcripts that are produced by the genome under a specific circumstance or in a specific cell. High-throughput methods, including microarray and bulk RNA sequencing, as well as recent advances in biostatistics based on machine learning approaches provides a quick and effective way of identifying novel genes and pathways related to asthma, which is a heterogeneous disease with diverse pathophysiological mechanisms. In this manuscript, we briefly review how to analyze transcriptome data and then provide a summary of recent transcriptome studies focusing on asthma pathogenesis and asthma drug responses. Studies reviewed here are classified into 2 classes based on the tissues utilized: blood and airway cells.

DNA methylation is associated with inhaled corticosteroid response in persistent childhood asthmatics

BACKGROUND

Response to inhaled corticosteroids is highly variable, and the association between DNA methylation and treatment response is not known.

OBJECTIVE

To examine the association between peripheral blood DNA methylation and inhaled corticosteroid response in children with persistent asthma.

METHODS

Epigenome-wide DNA methylation was analysed in individuals on inhaled corticosteroids in three independent and ethnically diverse cohorts-Childhood Asthma Management Program (CAMP); Children, Allergy, Milieu, Stockholm, Epidemiology (BAMSE); and Genetic Epidemiology of Asthma in Costa Rica Study (GACRS). Treatment response was evaluated using two definitions, the absence of emergency department visits and/or hospitalizations and the absence oral corticosteroid use while on inhaled corticosteroid therapy. CpG sites meeting nominal significance (P < 0.05) for each outcome were combined in a three-cohort meta-analysis with adjustment for multiple testing. DNA methylation was correlated with gene expression using Pearson and partial correlations.

RESULTS

In 154 subjects from CAMP, 72 from BAMSE, and 168 from GACRS, relative hypomethylation of cg00066816 (171 bases upstream of IL12B) was associated with the absence of emergency department visits and/or hospitalizations (Q = 0.03) in all cohorts and lower IL12B expression (ρ = 0.34, P = 0.01) in BAMSE. Relative hypermethylation of cg04256470 (688 bases upstream of CORT) was associated with the absence of oral corticosteroid use (Q = 0.04) in all cohorts and higher CORT expression (ρ = 0.20, P = 0.045) in CAMP.

CONCLUSION AND CLINICAL RELEVANCE

Differential DNA methylation of IL12B and CORT are associated with inhaled corticosteroid treatment response in persistent childhood asthmatics. Pharmaco-methylation can identify novel markers of treatment sensitivity in asthma.

Novel Blood-based Transcriptional Biomarker Panels Predict the Late-Phase Asthmatic Response

RATIONALE

The allergen inhalation challenge is used in clinical trials to test the efficacy of new treatments in attenuating the late-phase asthmatic response (LAR) and associated airway inflammation in subjects with allergic asthma. However, not all subjects with allergic asthma develop the LAR after allergen inhalation. Blood-based transcriptional biomarkers that can identify such individuals may help in subject recruitment for clinical trials as well as provide novel molecular insights.

OBJECTIVES

To identify blood-based transcriptional biomarker panels that can predict an individual's response to allergen inhalation challenge.

METHODS

We applied RNA sequencing to total RNA from whole blood (n = 36) collected before and after allergen challenge and generated both genome-guided and de novo datasets: genes, gene-isoforms (University of California, Santa Cruz, UCSC Genome Browser), Ensembl, and Trinity. Candidate biomarker panels were validated using the NanoString platform in an independent cohort of 33 subjects.

MEASUREMENTS AND MAIN RESULTS

The Trinity biomarker panel consisting of known and novel biomarker transcripts had an area under the receiver operating characteristic curve of greater than 0.70 in both the discovery and validation cohorts. The Trinity biomarker panel was useful in predicting the response of subjects that elicited different responses (accuracy between 0.65 and 0.71) and subjects that elicit a dual response (accuracy between 0.70 and 0.75) upon repeated allergen inhalation challenges.

CONCLUSIONS

Interestingly, the biomarker panel containing novel transcripts successfully validated compared with panels with known, well-characterized genes. These biomarker-blood tests may be used to identify subjects with asthma who develop the LAR, and may also represent members of novel molecular mechanisms that can be targeted for therapy.

The Genetics and Genomics of Asthma

Asthma is a common, clinically heterogeneous disease with strong evidence of heritability. Progress in defining the genetic underpinnings of asthma, however, has been slow and hampered by issues of inconsistency. Recent advances in the tools available for analysis-assaying transcription, sequence variation, and epigenetic marks on a genome-wide scale-have substantially altered this landscape. Applications of such approaches are consistent with heterogeneity at the level of causation and specify patterns of commonality with a wide range of alternative disease traits. Looking beyond the individual as the unit of study, advances in technology have also fostered comprehensive analysis of the human microbiome and its varied roles in health and disease. In this article, we consider the implications of these technological advances for our current understanding of the genetics and genomics of asthma.

Transcriptomics of atopy and atopic asthma in white blood cells from children and adolescents

Early allergic sensitisation (atopy) is the first step in the development of allergic diseases such as atopic asthma later in life. Genes and pathways associated with atopy and atopic asthma in children and adolescents have not been well characterised.A transcriptome-wide association study (TWAS) of atopy and atopic asthma in white blood cells (WBCs) or whole blood was conducted in a cohort of 460 Puerto Ricans aged 9-20 years (EVA-PR study) and in a cohort of 250 Swedish adolescents (BAMSE study). Pathway enrichment and network analyses were conducted to further assess top findings, and classification models of atopy and atopic asthma were built using expression levels for the top differentially expressed genes (DEGs).In a meta-analysis of the study cohorts, both previously implicated genes (e.g. IL5RA and IL1RL1) and genes not previously reported in TWASs (novel) were significantly associated with atopy and/or atopic asthma. Top novel genes for atopy included SIGLEC8 (p=8.07×10^-13), SLC29A1 (p=7.07×10^-12) and SMPD3 (p=1.48×10^-11). Expression quantitative trait locus analyses identified multiple asthma-relevant genotype-expression pairs, such as rs2255888/ALOX15 Pathway enrichment analysis uncovered 16 significantly enriched pathways at adjusted p<0.01, including those relevant to T-helper cell type 1 (Th1) and Th2 immune responses. Classification models built using the top DEGs and a few demographic/parental history variables accurately differentiated subjects with atopic asthma from nonatopic control subjects (area under the curve 0.84).We have identified genes and pathways for atopy and atopic asthma in children and adolescents, using transcriptome-wide data from WBCs and whole blood samples.

Epigenome-wide association studies in asthma: A systematic review

OBJECTIVE

Asthma is a common chronic respiratory airway disease influenced by environmental factors and possibly their interaction with the human genome causing epigenetic changes. Epigenome-wide association studies (EWAS) have mainly investigated DNA methylation and its association with disease or traits, exposure factors or gene expression. This systematic review aimed to identify all EWAS assessing differentially methylated sites associated with asthma in humans.

DESIGN

Structured systematic literature search following PRISMA guidelines, Newcastle-Ottawa Scale (NOS) for cohort studies was used for bias assessment.

DATA SOURCES

We searched PubMed and Embase databases from 2005 to 2019.

ELIGIBILITY CRITERIA

Epigenome-wide association studies testing association between differential methylation and asthma in humans.

RESULTS

Overall, we identified 16 EWAS studies complying with our search criteria. Twelve studies were conducted on children, and 10 were conducted on sample sizes <150 subjects. Four hundred and nineteen CpGs were reported in children studies after correction for multiple testing. In the adult studies, thousands of differentially methylated sites were identified. Differential methylation in inflammatory-related genes correlated with higher levels of gene expressions of inflammatory modulators in asthma. Differentially methylated genes associated with asthma included SMAD3, SERPINC1, PROK1, IL13, RUNX3 and TIGIT. Forty-one CpGs were replicated at least once in blood samples, and 28 CpGs were replicated in nasal samples.

CONCLUSION

Although many differentially methylated CpGs in genes known to be involved in asthma have been identified in EWAS to date, we conclude that further studies of larger sample sizes and analyses of differential methylation between different phenotypes are needed in order to comprehensively evaluate the role of epigenetic factors in the pathophysiology and heterogeneity of asthma, and the potential clinical utility to predict or classify patients with asthma.

IFN-stimulated Gene Expression, Type 2 Inflammation, and Endoplasmic Reticulum Stress in Asthma

RATIONALE

Quantification of type 2 inflammation provided a molecular basis for heterogeneity in asthma. Non-type 2 pathways that contribute to asthma pathogenesis are not well understood.

OBJECTIVES

To identify dysregulated pathways beyond type 2 inflammation.

METHODS

We applied RNA sequencing to airway epithelial brushings obtained from subjects with stable mild asthma not on corticosteroids (n = 19) and healthy control subjects (n = 16). Sequencing reads were mapped to human and viral genomes. In the same cohort, and in a separate group with severe asthma (n = 301), we profiled blood gene expression with microarrays.

MEASUREMENTS AND MAIN RESULTS

In airway brushings from mild asthma on inhaled corticosteroids, RNA sequencing yielded 1,379 differentially expressed genes (false discovery rate < 0.01). Pathway analysis revealed increased expression of type 2 markers, IFN-stimulated genes (ISGs), and endoplasmic reticulum (ER) stress-related genes. Airway epithelial ISG expression was not associated with type 2 inflammation in asthma or with viral transcripts but was associated with reduced lung function by FEV₁ (ρ = -0.72; P = 0.0004). ER stress was confirmed by an increase in XBP1 (X-box binding protein 1) splicing in mild asthma and was associated with both type 2 inflammation and ISG expression. ISGs were also the most activated genes in blood cells in asthma and were correlated with airway ISG expression (ρ = 0.55; P = 0.030). High blood ISG expression in severe asthma was similarly unrelated to type 2 inflammation.

CONCLUSIONS

ISG activation is prominent in asthma, independent of viral transcripts, orthogonal to type 2 inflammation, and associated with distinct clinical features. ER stress is associated with both type 2 inflammation and ISG expression.

Phenotypes/endotypes-driven treatment in asthma

PURPOSE OF REVIEW

Target therapy is the necessary step towards personalized medicine. The definition of asthma phenotypes and underlying mechanisms (endotypes) represent a key point in the development of new asthma treatments. Big data analysis, biomarker research and the availability of monoclonal antibodies, targeting specific cytokines is leading to the rapid evolution of knowledge. In this review, we sought to outline many of the recent advances in the field.

RECENT FINDINGS

Several attempts have been made to identify asthma phenotypes, sometimes with contrasting results. More success has been obtained concerning the pathogenetic mechanism of specific asthma patterns with the consequent identification of biomarkers and development of effective ad hoc treatment.

SUMMARY

We are in the middle of an extraordinary revolution of our mode of thinking about and approaching asthma. All the effort in the identification of clusters of patients with different disease clinical patterns, prognosis and response to treatment is closely linked to the identification of endotypes (Th2-low and Th2-high). This approach has allowed the development of the specific treatments (anti IgE, Anti IL5 and IL5R) that are now available and is leading to new ones.

Genetic-Epigenetic Interactions in Asthma Revealed by a Genome-Wide Gene-Centric Search

OBJECTIVES

There is evidence to suggest that asthma pathogenesis is affected by both genetic and epigenetic variation independently, and there is some evidence to suggest that genetic-epigenetic interactions affect risk of asthma. However, little research has been done to identify such interactions on a genome-wide scale. The aim of this studies was to identify genes with genetic-epigenetic interactions associated with asthma.

METHODS

Using asthma case-control data, we applied a novel nonparametric gene-centric approach to test for interactions between multiple SNPs and CpG sites simultaneously in the vicinities of 18,178 genes across the genome.

RESULTS

Twelve genes, PF4, ATF3, TPRA1, HOPX, SCARNA18, STC1, OR10K1, UPK1B, LOC101928523, LHX6, CHMP4B, and LANCL1, exhibited statistically significant SNP-CpG interactions (false discovery rate = 0.05). Of these, three have previously been implicated in asthma risk (PF4, ATF3, and TPRA1). Follow-up analysis revealed statistically significant pairwise SNP-CpG interactions for several of these genes, including SCARNA18, LHX6, and LOC101928523 (p = 1.33E-04, 8.21E-04, 1.11E-03, respectively).

CONCLUSIONS

Joint effects of genetic and epigenetic variation may play an important role in asthma pathogenesis. Statistical methods that simultaneously account for multiple variations across chromosomal regions may be needed to detect these types of effects on a genome-wide scale.

Gene Coexpression Networks in Whole Blood Implicate Multiple Interrelated Molecular Pathways in Obesity in People with Asthma

OBJECTIVE

Asthmatic children who develop obesity through adolescence have poorer disease outcomes compared with those who do not. This study aimed to characterize the biology of childhood asthma complicated by adult obesity.

METHODS

Gene expression networks are powerful statistical tools for characterizing human disease that leverage the putative coregulatory relationships of genes to infer relevant biological pathways. Weighted gene coexpression network analysis of gene expression data was performed in whole blood from 514 adult asthmatic subjects. Then, module preservation and association replication analyses were performed in 418 subjects from two independent asthma cohorts (one pediatric and one adult).

RESULTS

A multivariate model was identified in which three gene coexpression network modules were associated with incident obesity in the discovery cohort (each P < 0.05). Two module memberships were enriched for genes in pathways related to platelets, integrins, extracellular matrix, smooth muscle, NF-κB signaling, and Hedgehog signaling. The network structures of each of the obesity modules were significantly preserved in both replication cohorts (permutation P = 9.999E-05). The corresponding module gene sets were significantly enriched for differential expression in subjects with obesity in both replication cohorts (each P < 0.05).

CONCLUSIONS

The gene coexpression network profiles thus implicate multiple interrelated pathways in the biology of an important endotype of asthma with obesity.

Novel eosinophilic gene expression networks associated with IgE in two distinct asthma populations

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.

An Integrative Transcriptomic and Metabolomic Study of Lung Function in Children With Asthma

BACKGROUND

Single omic analyses have provided some insight into the basis of lung function in children with asthma, but the underlying biologic pathways are still poorly understood.

METHODS

Weighted gene coexpression network analysis (WGCNA) was used to identify modules of coregulated gene transcripts and metabolites in blood among 325 children with asthma from the Genetic Epidemiology of Asthma in Costa Rica study. The biology of modules associated with lung function as measured by FEV₁, the FEV₁/FVC ratio, bronchodilator response, and airway responsiveness to methacholine was explored. Significantly correlated gene-metabolite module pairs were then identified, and their constituent features were analyzed for biologic pathway enrichments.

RESULTS

WGCNA clustered 25,060 gene probes and 8,185 metabolite features into eight gene modules and eight metabolite modules, where four and six, respectively, were associated with lung function (P ≤ .05). The gene modules were enriched for immune, mitotic, and metabolic processes and asthma-associated microRNA targets. The metabolite modules were enriched for lipid and amino acid metabolism. Integration of correlated gene-metabolite modules expanded the single omic findings, linking the FEV₁/FVC ratio with ORMDL3 and dysregulated lipid metabolism. This finding was replicated in an independent population.

CONCLUSIONS

The results of this hypothesis-generating study suggest a mechanistic basis for multiple asthma genes, including ORMDL3, and a role for lipid metabolism. They demonstrate that integrating multiple omic technologies may provide a more informative picture of asthmatic lung function biology than single omic analyses.

Genetic profiles of transcriptomic clusters of childhood asthma determine specific severe subtype

BACKGROUND

Previous studies have defined transcriptomic subtypes of adult asthma using samples of induced sputum and bronchial epithelium; however, those procedures are not readily applicable in the clinic, especially for childhood asthma.

OBJECTIVE

We aim to dissect the transcriptomic clusters of childhood asthma using highly variably expressed genes of peripheral blood mononuclear cells (PBMC) among patients.

METHODS

Gene expression of PBMC from 133 asthmatic children and 11 healthy controls was measured with Illumina microarrays. We applied the k-means clustering algorithm of 2048 genes to assign asthmatic children into clusters. Genes with differential expression between asthma clusters and healthy controls were used to investigate whether they could identify severe asthma of children and adults.

RESULTS

We identified 3 asthma clusters with distinct inflammatory profiles in peripheral blood. Cluster 1 had the highest eosinophil count. Cluster 2 showed lower counts of both eosinophils and neutrophils. Cluster 3 had the highest neutrophil count and the poorest treatment control. Compared with other patients, Cluster 3 exhibited a unique gene expression pattern which was associated with changes in the glucocorticoid signalling and activation of the T helper 1/T helper 17 (T_H 1/T_H 17) immune pathways. In the validation studies, an 84-gene signature could identify severe asthma in children on leucocytes, as well as severe asthma in adults on CD8⁺ T cells.

CONCLUSIONS AND CLINICAL RELEVANCE

Gene expression profiling of PBMC is useful for the identification of T_H 1/T_H 17-mediated asthma with poor treatment control. PBMC and CD8⁺ T cells could be important targets for the investigation and identification of severe asthma.

Systems biology and in vitro validation identifies family with sequence similarity 129 member A (FAM129A) as an asthma steroid response modulator

BACKGROUND

Variation in response to the most commonly used class of asthma controller medication, inhaled corticosteroids, presents a serious challenge in asthma management, particularly for steroid-resistant patients with little or no response to treatment.

OBJECTIVE

We applied a systems biology approach to primary clinical and genomic data to identify and validate genes that modulate steroid response in asthmatic children.

METHODS

We selected 104 inhaled corticosteroid-treated asthmatic non-Hispanic white children and determined a steroid responsiveness endophenotype (SRE) using observations of 6 clinical measures over 4 years. We modeled each subject's cellular steroid response using data from a previously published study of immortalized lymphoblastoid cell lines under dexamethasone (DEX) and sham treatment. We integrated SRE with immortalized lymphoblastoid cell line DEX responses and genotypes to build a genome-scale network using the Reverse Engineering, Forward Simulation modeling framework, identifying 7 genes modulating SRE.

RESULTS

Three of these genes were functionally validated by using a stable nuclear factor κ-light-chain-enhancer of activated B cells luciferase reporter in A549 human lung epithelial cells, IL-1β cytokine stimulation, and DEX treatment. By using small interfering RNA transfection, knockdown of family with sequence similarity 129 member A (FAM129A) produced a reduction in steroid treatment response (P < .001).

CONCLUSION

With this systems-based approach, we have shown that FAM129A is associated with variation in clinical asthma steroid responsiveness and that FAM129A modulates steroid responsiveness in lung epithelial cells.

Impaired type I interferon regulation in the blood transcriptome of recurrent asthma exacerbations

Background

Asthma exacerbations are an important cause of morbidity in asthma. Respiratory infections are often involved in asthma exacerbations in both children and adults. Some individuals with asthma have increased susceptibility to viral infections and as a result increased rates of asthma exacerbations. We sought to identify a transcriptomic signature in the blood associated with asthma exacerbations triggered by respiratory infections (AETRI) and determine its association with increased risk for asthma exacerbations.

Methods

We conducted a two-step study using publicly available, previously generated transcriptomic signatures in peripheral blood mononuclear cells (PBMCs) from asthmatics to identify novel markers of increased risk for asthma exacerbations. In the 1st step, we identified an in vitro PBMC signature in response to rhinovirus. In the 2nd step, we used the in vitro signature to filter PBMC transcripts in response to asthma exacerbations in an independent in vivo cohort. Three different subgroups were identified and studied in the in vivo cohort: 1. Single AETRI; 2. Multiple AETRIs; and 3. Single non-infectious asthma exacerbations. We performed pathway and network analyses in all independent comparisons. We also performed an immunologic gene set enrichment analysis (GSEA) of the comparison between single AETRI and non-infectious asthma exacerbations.

Results

The in vitro signature identified 4354 differentially expressed genes (DEGs) with a fold change (FC) ≥ 1.2, false discovery rate (FDR) < 0.05. Subsequent analyses filtered by this in vitro signature on an independent cohort of adult asthma identified 238 DEGs (FC≥1.1, FDR < 0.1) in subjects with a single AETRI and no DEGs in single non-infectious asthma exacerbations. A comparison between the response in subjects with single and multiple AETRIs identified two discordant gene subsets. In the largest discordant subset (n = 63 genes) we identified an impaired type I interferon and STAT1 response in multiple AETRIs during the acute phase of the exacerbation and an upregulated STAT1 response at baseline. The STAT1 upregulation at baseline in subjects with multiple AETRIs was accompanied by upregulation of pro-inflammatory molecules including IL-15, interferon-stimulated genes (ISGs), several toll-like receptors 2, − 4, − 5 and − 8 and a triggering receptor expressed on myeloid cells 1 (TREM1) network.

Conclusions

Subjects with asthma and multiple AETRIs display a pro-inflammatory signature at baseline, associated with elevated STAT, IL-15 and ISGs, and an impaired STAT1 response during acute asthma exacerbations.

Electronic supplementary material

The online version of this article (10.1186/s12920-018-0340-3) contains supplementary material, which is available to authorized users.

Accelerated reactivity of blood granulocytes in patients with atopic bronchial asthma out of exacerbation

Reactive oxygen species (ROS) are important in bronchial asthma (BA) pathogenesis owing to accumulation of activated granulocytes in the lungs. But the ROS-producing activity of the cells is insufficiently understood in the blood of BA patients. This study analyzes the kinetics of phagocyte respiratory burst in the blood to improve the methods of BA patients monitoring. Patients with atopic BA out of exacerbation (n=60) and healthy controls (n=43) were recruited. The time-course of respiratory response to opsonized zymosan (OZ) was recorded in the whole blood using luminol-dependent chemiluminescence (CL), and its activation kinetics (lag-time, rate, amplitude, ROS production) was calculated. The discriminative power of ROS generation kinetics was defined by Receiver Operating Characteristic (ROC) curve analysis. Standard physiological respiratory parameters of patients did not differ from the controls. More rapid response to OZ was recorded in BA patient samples versus the controls. The primed state of phagocytes in the blood of BA patients was corroborated by significant weakening formyl peptide priming effect. The adhesion of granulocytes to cultured human endothelial cells was two-fold higher in BA patients versus controls. ROC curve analysis exhibited good discriminative effectiveness of the CL kinetics to compare BA individuals with the controls. The highest power (86% sensitivity and 90% specificity) was achieved at a linear combination of the parameters. We assume that the assessment of phagocyte reactivity based on the analysis of the response kinetic profile is a good test for monitoring of the state in BA patients.

Immune monitoring for precision medicine in allergy and asthma

'Precision Medicine' embodies the analyses of extensive data collected from patients and their environments to identify and apply patient-specific prophylactic strategies and medical treatments to improve clinical outcomes and healthcare cost-effectiveness. Many new methods have been developed for evaluating the activity of the human immune system. Such 'immune monitoring' approaches are now being used in studies of allergy and asthma in the hope of identifying better correlates of disease status, predictors of therapeutic outcomes, and potential side-effects of treatment. Together with analyses of family histories, genetic and other biometric data, and measurements of exposures to environmental and other risk factors for developing or exacerbating disease, immune monitoring approaches promise to enable 'Precision Medicine' for allergic diseases and asthma.

Genetics and Genomics of Longitudinal Lung Function Patterns in Individuals with Asthma

RATIONALE

Patterns of longitudinal lung function growth and decline in childhood asthma have been shown to be important in determining risk for future respiratory ailments including chronic airway obstruction and chronic obstructive pulmonary disease.

OBJECTIVES

To determine the genetic underpinnings of lung function patterns in subjects with childhood asthma.

METHODS

We performed a genome-wide association study of 581 non-Hispanic white individuals with asthma that were previously classified by patterns of lung function growth and decline (normal growth, normal growth with early decline, reduced growth, and reduced growth with early decline). The strongest association was also measured in two additional cohorts: a small asthma cohort and a large chronic obstructive pulmonary disease metaanalysis cohort. Interaction between the genomic region encompassing the most strongly associated single-nucleotide polymorphism and nearby genes was assessed by two chromosome conformation capture assays.

MEASUREMENTS AND MAIN RESULTS

An intergenic single-nucleotide polymorphism (rs4445257) on chromosome 8 was strongly associated with the normal growth with early decline pattern compared with all other pattern groups (P = 6.7 × 10^-9; odds ratio, 2.8; 95% confidence interval, 2.0-4.0); replication analysis suggested this variant had opposite effects in normal growth with early decline and reduced growth with early decline pattern groups. Chromosome conformation capture experiments indicated a chromatin interaction between rs4445257 and the promoter of the distal CSMD3 gene.

CONCLUSIONS

Early decline in lung function after normal growth is associated with a genetic polymorphism that may also protect against early decline in reduced growth groups. Clinical trial registered with www.clinicaltrials.gov (NCT00000575).

A Severe Asthma Disease Signature from Gene Expression Profiling of Peripheral Blood from U-BIOPRED Cohorts

RATIONALE

Stratification of asthma at the molecular level, especially using accessible biospecimens, could greatly enable patient selection for targeted therapy.

OBJECTIVES

To determine the value of blood analysis to identify transcriptional differences between clinically defined asthma and nonasthma groups, identify potential patient subgroups based on gene expression, and explore biological pathways associated with identified differences.

METHODS

Transcriptomic profiles were generated by microarray analysis of blood from 610 patients with asthma and control participants in the U-BIOPRED (Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes) study. Differentially expressed genes (DEGs) were identified by analysis of variance, including covariates for RNA quality, sex, and clinical site, and Ingenuity Pathway Analysis was applied. Patient subgroups based on DEGs were created by hierarchical clustering and topological data analysis.

MEASUREMENTS AND MAIN RESULTS

A total of 1,693 genes were differentially expressed between patients with severe asthma and participants without asthma. The differences from participants without asthma in the nonsmoking severe asthma and mild/moderate asthma subgroups were significantly related (r = 0.76), with a larger effect size in the severe asthma group. The majority of, but not all, differences were explained by differences in circulating immune cell populations. Pathway analysis showed an increase in chemotaxis, migration, and myeloid cell trafficking in patients with severe asthma, decreased B-lymphocyte development and hematopoietic progenitor cells, and lymphoid organ hypoplasia. Cluster analysis of DEGs led to the creation of subgroups among the patients with severe asthma who differed in molecular responses to oral corticosteroids.

CONCLUSIONS

Blood gene expression differences between clinically defined subgroups of patients with asthma and individuals without asthma, as well as subgroups of patients with severe asthma defined by transcript profiles, show the value of blood analysis in stratifying patients with asthma and identifying molecular pathways for further study. Clinical trial registered with www.clinicaltrials.gov (NCT01982162).

Spectrum of T-lymphocyte activities regulating allergic lung inflammation

Despite advances in the treatment of asthma, optimization of symptom control remains an unmet need in many patients. These patients, labeled severe asthma, are responsible for a substantial fraction of the disease burden. In these patients, research is needed to define the cellular and molecular pathways contributing to disease which in large part are refractory to corticosteroid treatment. The causes of steroid-resistant asthma are multifactorial and result from complex interactions of genetics, environmental factors, and innate and adaptive immunity. Adaptive immunity, addressed here, integrates the activities of distinct T-cell subsets and by definition is dynamic and responsive to an ever-changing environment and the influences of epigenetic modifications. These T-cell subsets exhibit different susceptibilities to the actions of corticosteroids and, in some, corticosteroids enhance their functional activation. Moreover, these subsets are not fixed in lineage differentiation but can undergo transcriptional reprogramming in a bidirectional manner between protective and pathogenic effector states. Together, these factors contribute to asthma heterogeneity between patients but also in the same patient at different stages of their disease. Only by carefully defining mechanistic pathways, delineating their sensitivity to corticosteroids, and determining the balance between regulatory and effector pathways will precision medicine become a reality with selective and effective application of targeted therapies.

Linking childhood allergic asthma phenotypes with endotype through integrated systems biology: current evidence and research needs

Asthma and other complex diseases results from a complex web of interactions involving inflammation, immunity, cell cycle, apoptosis, and metabolic perturbations across multiple organ systems. The extent to which various degrees of the age at onset, symptom severity, and the natural progression of the disease reflect multiple disease subtypes, influenced by unique process of development remains unknown. One of the most critical challenges to our understanding stems from incomplete understanding of the mechanisms. Within this review, we focus on the phenotypes of childhood allergic asthma as the basis to better understand the endotype for quantitative define subtypes of asthma. We highlight some of the known mechanistic pathways associated with the key hallmark events before the asthma onset. In particular, we examine how the recent advent of multiaxial -omics technologies and systems biology could help to clarify our current understanding of the pathway. We review how a large volume of molecular, genomic data generated by multiaxial technologies could be digested to identify cogent pathophysiologic molecular networks. We highlight some recent successes in application of these technologies within the context of other disease conditions for therapeutic interventions. We conclude by summarizing the research needs for the predictive value of preclinical biomarkers.

Gene Expression Profiling in Blood Provides Reproducible Molecular Insights into Asthma Control

RATIONALE

Maintaining optimal symptom control remains the primary objective of asthma treatment. Better understanding of the biologic underpinnings of asthma control may lead to the development of improved clinical and pharmaceutical approaches.

OBJECTIVES

To identify molecular pathways and interrelated genes whose differential expression was associated with asthma control.

METHODS

We performed gene set enrichment analyses of asthma control in 1,170 adults with asthma, each with gene expression data derived from either whole blood (WB) or unstimulated CD4+ T lymphocytes (CD4), and a self-reported asthma control score representing either the preceding 6 months (chronic) or 7 days (acute). Our study comprised a discovery WB cohort (n = 245, chronic) and three independent, nonoverlapping replication cohorts: a second WB set (n = 448, acute) and two CD4 sets (n = 300, chronic; n = 77, acute).

MEASUREMENTS AND MAIN RESULTS

In the WB discovery cohort, we found significant overrepresentation of genes associated with asthma control in 1,106 gene sets from the Molecular Signatures Database (false discovery rate, <5%). Of these, 583 (53%) replicated in at least one replication cohort (false discovery rate, <25%). Suboptimal control was associated with signatures of eosinophilic and granulocytic inflammatory signals, whereas optimal control signatures were enriched for immature lymphocytic patterns. These signatures included two related biologic processes related to activation by TREM-1 (triggering receptor expressed on myeloid cells 1) and lipopolysaccharide.

CONCLUSIONS

Together, these results demonstrate the existence of specific, reproducible transcriptomic components in blood that vary with degree of asthma control and implicate a novel biologic target (TREM-1).

Asthma Biomarkers: Do They Bring Precision Medicine Closer to the Clinic?

Measurement of biomarkers has been incorporated within clinical research of asthma to characterize the population and to associate the disease with environmental and therapeutic effects. Regrettably, at present, there are no specific biomarkers, none is validated or qualified, and endotype-driven choices overlap. Biomarkers have not yet reached clinical practice and are not included in current asthma guidelines. Last but not least, the choice of the outcome upholding the value of the biomarkers is extremely difficult, since it has to reflect the mechanistic intervention while being relevant to both the disease and the particular person. On the verge of a new age of asthma healthcare standard, we must embrace and adapt to the key drivers of change. Disease endotypes, biomarkers, and precision medicine represent an emerging model of patient care building on large-scale biologic databases, omics and diverse cellular assays, health information technology, and computational tools for analyzing sizable sets of data. A profound transformation of clinical and research pattern from population to individual risk and from investigator-imposed subjective disease clustering (hypothesis driven) to unbiased, data-driven models is facilitated by the endotype/biomarker-driven approach.