Pathways activated during human asthma exacerbation as revealed by gene expression patterns in blood

Innate immune responses are increased in children with acute asthma exacerbation

BACKGROUND

Little is known about the immune responses during acute asthma exacerbation. In this study, we examined immune responses in children following an acute asthma exacerbation.

METHODS

We evaluated pro-inflammatory cytokine levels and gene expression profiles in blood samples from pediatric patients admitted for acute asthma exacerbation. Viral PCR was performed to differentiate between viral or non-viral-associated exacerbations.

RESULTS

Following informed consent, clinical data were obtained from 20 children with asthma (median [interquartile range, IQR]: age 11.5 [8.0, 14.2]) years and 14 healthy age-matched controls (10.5 [7.0, 13.0]). Twelve had positive nasopharyngeal Polymerase chain reaction (PCR) for viral infection (11 rhinoviruses and 1 respiratory syncytial virus (RSV)). Nine were in the pediatric intensive care unit (PICU) and among them five required continuous positive airway pressure (CPAP). Mean (±SD) days on systemic steroids before drawing blood sample were 2.5 ± 1.6. Twelve had history of environmental allergies with 917 (274, 1396) IU/mL total IgE (median (IQR)). Compared with controls, IL-1RA and IL-10 levels were significantly increased and TNF-α significantly decreased in asthma subjects (p < .05 for all). RNA-seq analysis revealed 852 differentially expressed genes in subjects with asthma. Pathway analysis found upregulated genes and pathways involved in innate immune responses in subjects with asthma. Significantly reduced genes included pathways associated with T helper cell differentiation and activation.

CONCLUSIONS

In acute asthma exacerbation, innate immune pathways remained increased while adaptive immune responses related to T helper cells are blunted and are independent of trigger or asthma severity. Our novel findings highlight the need to identify new therapies to target persistent innate immune responses to improve outcomes in acute asthma.

Blood transcriptome differentiates clinical clusters for asthma

Background

In previous studies, several asthma phenotypes were identified using clinical and demographic parameters. Transcriptional phenotypes were mainly identified using sputum and bronchial cells.

Objective

We aimed to investigate asthma phenotypes via clustering analysis using clinical variables and compare the transcription levels among clusters using gene expression profiling of the blood.

Methods

Clustering analysis was performed using 6 parameters: age of asthma onset, body mass index, pack-years of smoking, forced expiratory volume in 1 s (FEV1), FEV1/forced vital capacity, and blood eosinophil counts. Peripheral blood mononuclear cells (PBMCs) were isolated from whole blood samples and RNA was extracted from selected PBMCs. Transcriptional profiles were generated (Illumina NovaSeq 6000) and analyzed using the reference genome and gene annotation files (hg19.refGene.gft). Pathway enrichment analysis was conducted using GO, KEGG, and REACTOME databases.

Results

In total, 355 patients with asthma were included in the analysis, of whom 72 (20.3%) had severe asthma. Clustering of the 6 parameters revealed 4 distinct subtypes. Cluster 1 (n = 63) had lower predicted FEV1 % and higher pack-years of smoking and neutrophils in sputum. Cluster 2 (n = 43) had a higher proportion and number of eosinophils in sputum and blood, and severe airflow limitation. Cluster 3 (n = 110) consisted of younger subjects with atopic features. Cluster 4 (n = 139) included features of late-onset mild asthma. Differentially expressed genes between clusters 1 and 2 were related to inflammatory responses and cell activation. Th17 cell differentiation and interferon gamma-mediated signaling pathways were related to neutrophilic inflammation in asthma.

Conclusion

Four clinical clusters were differentiated based on clinical parameters and blood eosinophils in adult patients with asthma form the Cohort for Reality and Evolution of Adult Asthma in Korea (COREA) cohort. Gene expression profiling and molecular pathways are novel means of classifying asthma phenotypes.

Omics technologies in allergy and asthma research: An EAACI position paper

Allergic diseases and asthma are heterogenous chronic inflammatory conditions with several distinct complex endotypes. Both environmental and genetic factors can influence the development and progression of allergy. Complex pathogenetic pathways observed in allergic disorders present a challenge in patient management and successful targeted treatment strategies. The increasing availability of high-throughput omics technologies, such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics allows studying biochemical systems and pathophysiological processes underlying allergic responses. Additionally, omics techniques present clinical applicability by functional identification and validation of biomarkers. Therefore, finding molecules or patterns characteristic for distinct immune-inflammatory endotypes, can subsequently influence its development, progression, and treatment. There is a great potential to further increase the effectiveness of single omics approaches by integrating them with other omics, and nonomics data. Systems biology aims to simultaneously and longitudinally understand multiple layers of a complex and multifactorial disease, such as allergy, or asthma by integrating several, separated data sets and generating a complete molecular profile of the condition. With the use of sophisticated biostatistics and machine learning techniques, these approaches provide in-depth insight into individual biological systems and will allow efficient and customized healthcare approaches, called precision medicine. In this EAACI Position Paper, the Task Force "Omics technologies in allergic research" broadly reviewed current advances and applicability of omics techniques in allergic diseases and asthma research, with a focus on methodology and data analysis, aiming to provide researchers (basic and clinical) with a desk reference in the field. The potential of omics strategies in understanding disease pathophysiology and key tools to reach unmet needs in allergy precision medicine, such as successful patients' stratification, accurate disease prognosis, and prediction of treatment efficacy and successful prevention measures are highlighted.

Peripheral blood transcriptomic clusters uncovered immune phenotypes of asthma

BACKGROUND

Transcriptomic analysis has been used to elucidate the complex pathogenesis of heterogeneous disease and may also contribute to identify potential therapeutic targets by delineating the hub genes. This study aimed to investigate whether blood transcriptomic clustering can distinguish clinical and immune phenotypes of asthmatics, and microbiome in asthmatics.

METHODS

Transcriptomic expression of peripheral blood mononuclear cells (PBMCs) from 47 asthmatics and 21 non-asthmatics was measured using RNA sequencing. A hierarchical clustering algorithm was used to classify asthmatics. Differentially expressed genes, clinical phenotypes, immune phenotypes, and microbiome of each transcriptomic cluster were assessed.

RESULTS

In asthmatics, three distinct transcriptomic clusters with numerously different transcriptomic expressions were identified. The proportion of severe asthmatics was highest in cluster 3 as 73.3%, followed by cluster 2 (45.5%) and cluster 1 (28.6%). While cluster 1 represented clinically non-severe T2 asthma, cluster 3 tended to include severe non-T2 asthma. Cluster 2 had features of both T2 and non-T2 asthmatics characterized by the highest serum IgE level and neutrophil-dominant sputum cell population. Compared to non-asthmatics, cluster 1 showed higher CCL23 and IL1RL1 expression while the expression of TREML4 was suppressed in cluster 3. CTSD and ALDH2 showed a significant positive linear relationship across three clusters in the order of cluster 1 to 3. No significant differences in the diversities of lung and gut microbiomes were observed among transcriptomic clusters of asthmatics and non-asthmatics. However, our study has limitations in that small sample size data were analyzed with unmeasured confounding factors and causal relationships or function pathways were not verified.

CONCLUSIONS

Genetic clustering based on the blood transcriptome may provide novel immunological insight, which can be biomarkers of asthma immune phenotypes. Trial registration Retrospectively registered.

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.

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.

Potential Metabolic Biomarkers in Adult Asthmatics

Asthma is the most common chronic airway inflammation, with multiple phenotypes caused by complicated interactions of genetic, epigenetic, and environmental factors. To date, various determinants have been suggested for asthma pathogenesis by a new technology termed omics, including genomics, transcriptomics, proteomics, and metabolomics. In particular, the systematic analysis of all metabolites in a biological system, such as carbohydrates, amino acids, and lipids, has helped identify a novel pathway related to complex diseases. These metabolites are involved in the regulation of hypermethylation, response to hypoxia, and immune reactions in the pathogenesis of asthma. Among them, lipid metabolism has been suggested to be related to lung dysfunction in mild-to-moderate asthma. Sphingolipid metabolites are an important mediator contributing to airway inflammation in obese asthma and aspirin-exacerbated respiratory disease. Although how these molecular variants impact the disease has not been completely determined, identification of new causative factors may possibly lead to more-personalized and precise pathway-specific approaches for better diagnosis and treatment of asthma. In this review, perspectives of metabolites related to asthma and clinical implications have been highlighted according to various phenotypes.

Single-cell characterization of a model of poly I:C-stimulated peripheral blood mononuclear cells in severe asthma

Background

Asthma has been associated with impaired interferon response. Multiple cell types have been implicated in such response impairment and may be responsible for asthma immunopathology. However, existing models to study the immune response in asthma are limited by bulk profiling of cells. Our objective was to Characterize a model of peripheral blood mononuclear cells (PBMCs) of patients with severe asthma (SA) and its response to the TLR3 agonist Poly I:C using two single-cell methods.

Methods

Two complementary single-cell methods, DropSeq for single-cell RNA sequencing (scRNA-Seq) and mass cytometry (CyTOF), were used to profile PBMCs of SA patients and healthy controls (HC). Poly I:C-stimulated and unstimulated cells were analyzed in this study.

Results

PBMCs (n = 9414) from five SA (n = 6099) and three HC (n = 3315) were profiled using scRNA-Seq. Six main cell subsets, namely CD4 + T cells, CD8 + T cells, natural killer (NK) cells, B cells, dendritic cells (DCs), and monocytes, were identified. CD4 + T cells were the main cell type in SA and demonstrated a pro-inflammatory profile characterized by increased JAK1 expression. Following Poly I:C stimulation, PBMCs from SA had a robust induction of interferon pathways compared with HC. CyTOF profiling of Poly I:C stimulated and unstimulated PBMCs (n = 160,000) from the same individuals (SA = 5; HC = 3) demonstrated higher CD8 + and CD8 + effector T cells in SA at baseline, followed by a decrease of CD8 + effector T cells after poly I:C stimulation.

Conclusions

Single-cell profiling of an in vitro model using PBMCs in patients with SA identified activation of pro-inflammatory pathways at baseline and strong response to Poly I:C, as well as quantitative changes in CD8 + effector cells. Thus, transcriptomic and cell quantitative changes are associated with immune cell heterogeneity in this model to evaluate interferon responses in severe asthma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-021-01709-9.

Towards a personalised treatment approach for asthma attacks

Asthma attacks (exacerbations) are common, accounting for over 90 000 UK hospital admissions per annum. They kill nearly 1500 people per year in the UK, have significant associated direct and indirect costs and lead to accelerated and permanent loss of lung function. The recognition of asthma as a heterogeneous condition with multiple phenotypes has revolutionised the approach to the long-term management of the condition, with greater emphasis on personalised treatment and the introduction of the treatable traits concept. In contrast asthma attacks are poorly defined and understood and our treatment approach consists of bronchodilators and systemic corticosteroids. This review aims to explore the current limitations in the description, assessment and management of asthma attacks. We will outline the risk factors for attacks, strategies to modify this risk and describe the recognised characteristics of attacks as a first step towards the development of an approach for phenotyping and personalising the treatment of these critically important events. By doing this, we hope to gradually improve asthma attack treatment and reduce the adverse effects associated with recurrent courses of 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.

Circulating MicroRNAs and T-Cell Cytokine Expression Are Associated With the Characteristics of Asthma Exacerbation

Purpose

Immunological mechanisms underlying asthma exacerbation have not been elucidated. The aim of this study was to assess the associations of various asthma exacerbation traits with selected serum microRNA (miRNA) expression and T-cell subpopulations.

Methods

Twenty-one asthmatics were studied during asthma exacerbation (exacerbation visit [EV] and the follow-up visit [FV] at 6 weeks). At both visits, spirometry was performed, fractional exhaled nitric oxide (FeNO) was measured, and nasopharyngeal and blood samples were collected. In nasopharyngeal samples, respiratory viruses were assayed by multiplex polymerase chain reaction (PCR), and bacterial cultures were performed. Serum miRNAs were assayed with real-time PCR. T-cell surface markers, eosinophil progenitors and intracellular cytokines were assessed by flow cytometry.

Results

Two-thirds of patients had moderate or severe exacerbation and the FV, overall improvement in asthma control was observed. The mean expression of serum miRNA-126a, miRNA-16 and miRNA-21 was significantly lower at the EV than at the FV. At EV, miRNA-29b correlated with FeNO (r = 0.44, P < 0.05), and 5 of 7 miRNA tested correlated with pulmonary function tests. The number of cluster of differentiation (CD)45+CD4+interleukin (IL)4+ cells was significantly higher at the EV than at the FV, and positive correlations of T-regulatory cells and eosinophil progenitors with asthma control was found. At the EV, serum miRNAs negatively correlated with the number of T cells expressing IL-4, IL-17, IL-22 and interferon gamma, while at the FV both positive and negative correlations with T-cell subsets were observed. No association of detected pathogen (viruses and bacteria) in nasopharyngeal fluid with clinical, functional and immunological parameters was found.

Conclusions

Epigenetic dysregulation during asthma exacerbation could be related to respiratory function, airway inflammation and T-cell cytokine expression.

MicroRNA-221 is overexpressed in the equine asthmatic airway smooth muscle and modulates smooth muscle cell proliferation

Airway wall remodeling, including hyperplasia and hypertrophy of smooth muscle (ASM) cells leading to an increased smooth muscle mass, is considered central to asthma. However, molecular pathways responsible for ASM remodeling remain poorly understood. MicroRNAs (miRNAs) have emerged as key regulators of inflammatory and repair processes affecting the lungs and can downregulate protein expression by inhibiting target mRNA translation. We therefore hypothesized that miRNAs are involved in ASM remodeling in asthma by modulating ASM proliferation. We have analyzed the expression of miRNAs in bronchial smooth muscle from asthmatic horses during disease exacerbation and remission and from controls. Their involvement in ASM cell proliferation was then studied. Our results shown that miR-26a, miR-133, and miR-221 were upregulated in ASM from horses with asthma exacerbation compared with asthma remission and controls. MiR-221 induced cell hyperproliferation and reduced the expression of contractile gene markers in ASM cells. These changes were associated with the decreased mRNA expression of cell cycle regulatory genes (p53, p21, and p27). In conclusion, we demonstrated for the first time an upregulation of miR-221 in asthmatic airway smooth muscle and confirm the involvement of miR-221 in ASM cell proliferation by regulation of the cell cycle arrest genes. Targeting miR-221 network genes may represent a novel approach for the treatment of ASM remodeling in 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.

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.

Gene expression data analysis identifies multiple deregulated pathways in patients with asthma

Asthma is a chronic inflammatory disorder associated with airway hyper-responsiveness. Although a number of studies have investigated asthma at the molecular level, the molecular immune signatures associated with asthma severity or with the response to corticosteroids are still being unraveled. The present study integrated four asthma-related gene expression datasets from the Gene Expression Omnibus and identified immune-gene signatures associated with asthma development, severity, or response to treatment. Normal and mild asthmatic patients clustered separately from the severe asthma group, suggesting substantial progression-related changes in gene expression. Pathway analysis of up-regulated severe asthma-related genes identified multiple cellular processes, such as polymorphism, T-cell development, and transforming growth factor-β signaling. Comparing gene expression profiles of bronchoalveolar lavage cells in response to corticosteroid treatment, showed substantial reductions in genes related to the inflammatory response, including tumor necrosis factor signaling in the corticosteroid sensitive versus resistant patients, suggesting a defective immune response to corticosteroids. The data highlight the multifactorial nature of asthma, but revealed no significant overlap with the gene expression profiles from different datasets interrogated in current studies. The presented profile suggests that genes involved in asthma progression are different from those involved in the response to corticosteroids and this could affect the clinical management of different groups of patients with asthma.

A time for everything and everything in its time - exploring the mechanisms underlying seasonality of COPD exacerbations

Across Europe, COPD affects 23 million people leading to annual health care costs of ~€25.1 billion. This burden is particularly severe during winter months in association with the peak incidence of exacerbation events. Seasonal variation in the health status of patients with COPD places additional and often critical pressure on already strained health care resources. COPD exacerbations are characterized by worsening day-to-day symptoms of an individual and often triggered by respiratory infections, but the process by which this occurs in a seasonal fashion is likely to be multifactorial. In this review, we discuss recent population studies that highlight the impact of seasonality in COPD and review the proposed biological mechanisms underlying this. An appraisal of the role of the host susceptibility and response, environmental triggers and the biology of respiratory pathogens is detailed. The impact of each aspect is considered, and an integrated model of the context for the whole individual and society in general is explored.

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.

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.

A genome-by-environment interaction classifier for precision medicine: personal transcriptome response to rhinovirus identifies children prone to asthma exacerbations

OBJECTIVE

To introduce a disease prognosis framework enabled by a robust classification scheme derived from patient-specific transcriptomic response to stimulation.

MATERIALS AND METHODS

Within an illustrative case study to predict asthma exacerbation, we designed a stimulation assay that reveals individualized transcriptomic response to human rhinovirus. Gene expression from peripheral blood mononuclear cells was quantified from 23 pediatric asthmatic patients and stimulated in vitro with human rhinovirus. Responses were obtained via the single-subject gene set testing methodology "N-of-1-pathways." The classifier was trained on a related independent training dataset (n = 19). Novel visualizations of personal transcriptomic responses are provided.

RESULTS

Of the 23 pediatric asthmatic patients, 12 experienced recurrent exacerbations. Our classifier, using individualized responses and trained on an independent dataset, obtained 74% accuracy (area under the receiver operating curve of 71%; 2-sided P = .039). Conventional classifiers using messenger RNA (mRNA) expression within the viral-exposed samples were unsuccessful (all patients predicted to have recurrent exacerbations; accuracy of 52%).

DISCUSSION

Prognosis based on single time point, static mRNA expression alone neglects the importance of dynamic genome-by-environment interplay in phenotypic presentation. Individualized transcriptomic response quantified at the pathway (gene sets) level reveals interpretable signals related to clinical outcomes.

CONCLUSION

The proposed framework provides an innovative approach to precision medicine. We show that quantifying personal pathway-level transcriptomic response to a disease-relevant environmental challenge predicts disease progression. This genome-by-environment interaction assay offers a noninvasive opportunity to translate omics data to clinical practice by improving the ability to predict disease exacerbation and increasing the potential to produce more effective treatment decisions.

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.

A Four-Biomarker Blood Signature Discriminates Systemic Inflammation Due to Viral Infection Versus Other Etiologies

The innate immune system of humans and other mammals responds to pathogen-associated molecular patterns (PAMPs) that are conserved across broad classes of infectious agents such as bacteria and viruses. We hypothesized that a blood-based transcriptional signature could be discovered indicating a host systemic response to viral infection. Previous work identified host transcriptional signatures to individual viruses including influenza, respiratory syncytial virus and dengue, but the generality of these signatures across all viral infection types has not been established. Based on 44 publicly available datasets and two clinical studies of our own design, we discovered and validated a four-gene expression signature in whole blood, indicative of a general host systemic response to many types of viral infection. The signature’s genes are: Interferon Stimulated Gene 15 (ISG15), Interleukin 16 (IL16), 2′,5′-Oligoadenylate Synthetase Like (OASL), and Adhesion G Protein Coupled Receptor E5 (ADGRE5). In each of 13 validation datasets encompassing human, macaque, chimpanzee, pig, mouse, rat and all seven Baltimore virus classification groups, the signature provides statistically significant (p < 0.05) discrimination between viral and non-viral conditions. The signature may have clinical utility for differentiating host systemic inflammation (SI) due to viral versus bacterial or non-infectious causes.

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).

Personalized management of asthma exacerbations: lessons from genetic studies

INTRODUCTION

The genetics of severe asthma and asthma exacerbations are distinct from milder forms of asthma. Gene-environmental interactions contribute to the complexity and heterogeneity of severe asthma and asthma exacerbations, and pharmacogenomic studies have also identified genes that affect susceptibility to asthma exacerbations.

AREAS COVERED

Studies on the genetics, gene-environment interactions, and pharmacogenomics of asthma exacerbations are reviewed. Multiple individual genetic variants have been identified to be associated with asthma exacerbations but each genetic polymorphism explains only a fraction of the disease and by itself is not able to translate into clinical practice. Research is shifting from candidate gene studies and genome wide association studies towards more integrative approaches to translate genetic findings into clinical diagnostic and therapeutic tools.

EXPERT COMMENTARY

Integrative approaches combining polygenic or genomic data with multi-omics technologies have the potential to discover new biologic mechanisms and biomarkers for severe asthma and asthma exacerbations. Greater understanding of genomics and underlying biologic pathways will also lead to improved prevention and treatment, lowering costs, morbidity, and mortality. The utilization of genomic testing and personalized medicine may revolutionize asthma management, in particular for patients with severe, refractory asthma.

Respiratory viral infections and host responses; insights from genomics

Respiratory viral infections are a leading cause of disease and mortality. The severity of these illnesses can vary markedly from mild or asymptomatic upper airway infections to severe wheezing, bronchiolitis or pneumonia. In this article, we review the viral sensing pathways and organizing principles that govern the innate immune response to infection. Then, we reconstruct the molecular networks that differentiate symptomatic from asymptomatic respiratory viral infections, and identify the underlying molecular drivers of these networks. Finally, we discuss unique aspects of the biology and pathogenesis of infections with respiratory syncytial virus, rhinovirus and influenza, drawing on insights from genomics.

In Search of 'Birth Month Genes': Using Existing Data Repositories to Locate Genes Underlying Birth Month-Disease Relationships

Prenatal and perinatal exposures vary seasonally (e.g., sunlight, allergens) and many diseases are linked with variance in exposure. Epidemiologists often measure these changes using birth month as a proxy for seasonal variance. Likewise, Genome-Wide Association Studies have associated or implicated these same diseases with many genes. Both disparate data types (epidemiological and genetic) can provide key insights into the underlying disease biology. We developed an algorithm that links 1) epidemiological data from birth month studies with 2) genetic data from published gene-disease association studies. Our framework uses existing data repositories - PubMed, DisGeNET and Gene Ontology - to produce a bipartite network that connects enriched seasonally varying biofactorss with birth month dependent diseases (BMDDs) through their overlapping developmental gene sets. As a proof-of-concept, we investigate 7 known BMDDs and highlight three important biological networks revealed by our algorithm and explore some interesting genetic mechanisms potentially responsible for the seasonal contribution to BMDDs.

CTNNA3 and SEMA3D: Promising loci for asthma exacerbation identified through multiple genome-wide association studies

BACKGROUND

Asthma exacerbations are a major cause of morbidity and medical cost.

OBJECTIVE

The objective of this study was to identify genetic predictors of exacerbations in asthmatic subjects.

METHODS

We performed a genome-wide association study meta-analysis of acute asthma exacerbation in 2 pediatric clinical trials: the Childhood Asthma Management Program (n = 581) and the Childhood Asthma Research and Education (n = 205) network. Acute asthma exacerbations were defined as treatment with a 5-day course of oral steroids. We obtained a replication cohort from Biobank of Vanderbilt University Medical Center (BioVU; n = 786), the Vanderbilt University electronic medical record-linked DNA biobank. We used CD4(+) lymphocyte genome-wide mRNA expression profiling to identify associations of top single nucleotide polymorphisms with mRNA abundance of nearby genes.

RESULTS

A locus in catenin (cadherin-associated protein), alpha 3 (CTNNA3), reached genome-wide significance (rs7915695, P = 2.19 × 10(-8); mean exacerbations, 6.05 for minor alleles vs 3.71 for homozygous major alleles). Among the 4 top single nucleotide polymorphisms replicated in BioVU, rs993312 in Sema domain, immunoglobulin domain (Ig), short basic domain, secreted, (semaphorin) 3D (SEMA3D) was significant (P = .0083) and displayed stronger association among African Americans (P = .0004 in BioVU [mean exacerbations, 3.91 vs 1.53]; P = .0089 in the Childhood Asthma Management Program [mean exacerbations, 6.0 vs 3.25]). CTNNA3 variants did not replicate in BioVU. A regulatory variant in the CTNNA3 locus was associated with CTNNA3 mRNA expression in CD4(+) cells from asthmatic patients (P = .00079). CTNNA3 appears to be active in the immune response, and SEMA3D has a plausible role in airway remodeling. We also provide a replication of a previous association of purinergic receptor P2X, ligand-gated ion channel, 7 (P2RX7), with asthma exacerbation.

CONCLUSIONS

We identified 2 loci associated with exacerbations through a genome-wide association study. CTNNA3 met genome-wide significance thresholds, and SEMA3D replicated in a clinical biobank database.

A nonmuscle myosin light chain kinase-dependent gene signature in peripheral blood mononuclear cells is linked to human asthma severity and exacerbation status

Asthma is increasingly recognized as a heterogeneous disease influenced by complex genetic and environmental contributions. Myosin light chain kinase (MLCK; gene symbol, MYLK), especially the nonmuscle isoform nmMLCK, is a cytoskeleton protein known to be related to human asthma susceptibility and severity, findings confirmed in preclinical models of asthmatic inflammation. In this study, we define the central capacity for a nmMLCK-influenced gene signature in human peripheral blood mononuclear cells to predict human asthma severity and exacerbation status. We refined this signature from a list of nmMLCK-influenced genes identified in lung tissues of nmMLCK knockout mice exposed to inflammatory stimuli (ventilator-induced lung injury), with subsequent identification of nmMLCK-influenced genes in a list of human asthma severity-related genes expressed in blood. The enriched nmMLCK-influenced gene signature successfully predicted human asthma severity and exacerbation status in both discovery and validation human asthma cohorts. These findings validate the central role played by nmMLCK in asthma susceptibility, severity, and exacerbation and further provide novel gene signatures as effective asthma biomarkers for severity, exacerbation, and prognosis.

Widespread seasonal gene expression reveals annual differences in human immunity and physiology

Seasonal variations are rarely considered a contributing component to human tissue function or health, although many diseases and physiological process display annual periodicities. Here we find more than 4,000 protein-coding mRNAs in white blood cells and adipose tissue to have seasonal expression profiles, with inverted patterns observed between Europe and Oceania. We also find the cellular composition of blood to vary by season, and these changes, which differ between the United Kingdom and The Gambia, could explain the gene expression periodicity. With regards to tissue function, the immune system has a profound pro-inflammatory transcriptomic profile during European winter, with increased levels of soluble IL-6 receptor and C-reactive protein, risk biomarkers for cardiovascular, psychiatric and autoimmune diseases that have peak incidences in winter. Circannual rhythms thus require further exploration as contributors to various aspects of human physiology and disease.

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

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

Transcriptome analysis of controlled and therapy-resistant childhood asthma reveals distinct gene expression profiles

BACKGROUND

Children with problematic severe asthma have poor disease control despite high doses of inhaled corticosteroids and additional therapy, leading to personal suffering, early deterioration of lung function, and significant consumption of health care resources. If no exacerbating factors, such as smoking or allergies, are found after extensive investigation, these children are given a diagnosis of therapy-resistant (or therapy-refractory) asthma (SA).

OBJECTIVE

We sought to deepen our understanding of childhood SA by analyzing gene expression and modeling the underlying regulatory transcription factor networks in peripheral blood leukocytes.

METHODS

Gene expression was analyzed by using Cap Analysis of Gene Expression in children with SA (n = 13), children with controlled persistent asthma (n = 15), and age-matched healthy control subjects (n = 9). Cap Analysis of Gene Expression sequencing detects the transcription start sites of known and novel mRNAs and noncoding RNAs.

RESULTS

Sample groups could be separated by hierarchical clustering on 1305 differentially expressed transcription start sites, including 816 known genes and several novel transcripts. Ten of 13 tested novel transcripts were validated by means of RT-PCR and Sanger sequencing. Expression of RAR-related orphan receptor A (RORA), which has been linked to asthma in genome-wide association studies, was significantly upregulated in patients with SA. Gene network modeling revealed decreased glucocorticoid receptor signaling and increased activity of the mitogen-activated protein kinase and Jun kinase cascades in patients with SA.

CONCLUSION

Circulating leukocytes from children with controlled asthma and those with SA have distinct gene expression profiles, demonstrating the possible development of specific molecular biomarkers and supporting the need for novel therapeutic approaches.

Genomic architecture of asthma differs by sex

Asthma comprised of highly heterogeneous subphenotypes resulting from complex interplay between genetic and environmental stimuli. While much focus has been placed on extrinsic environmental stimuli, intrinsic environment such as sex can interact with genes to influence asthma risk. However, few studies have examined sex-specific genetic effects. The overall objective of this study was to evaluate if sex-based differences exist in genomic associations with asthma. We tested 411 asthmatics and 297 controls for presence of interactions and sex-stratified effects in 51 genes using both SNP and gene expression data. Logistic regression was used to test for association. Over half (55%) of the genetic variants identified in sex-specific analyses were not identified in the sex-combined analysis. Further, sex-stratified genetic analyses identified associations with significantly higher median effect sizes than sex-combined analysis for girls (p-value=6.5E-15) and for boys (p-value=1.0E-7). When gene expression data were analyzed to identify genes that were differentially expressed in asthma versus non-asthma, nearly one third (31%) of the probes identified in the sex-specific analyses were not identified in the sex-combined analysis. Both genetic and gene expression data suggest that the biologic underpinnings for asthma may differ by sex. Failure to recognize sex interactions in asthma greatly decreases the ability to detect significant genomic variation and may result in significant misrepresentation of genes and pathways important in asthma in different environments.

Data-driven asthma endotypes defined from blood biomarker and gene expression data

The diagnosis and treatment of childhood asthma is complicated by its mechanistically distinct subtypes (endotypes) driven by genetic susceptibility and modulating environmental factors. Clinical biomarkers and blood gene expression were collected from a stratified, cross-sectional study of asthmatic and non-asthmatic children from Detroit, MI. This study describes four distinct asthma endotypes identified via a purely data-driven method. Our method was specifically designed to integrate blood gene expression and clinical biomarkers in a way that provides new mechanistic insights regarding the different asthma endotypes. For example, we describe metabolic syndrome-induced systemic inflammation as an associated factor in three of the four asthma endotypes. Context provided by the clinical biomarker data was essential in interpreting gene expression patterns and identifying putative endotypes, which emphasizes the importance of integrated approaches when studying complex disease etiologies. These synthesized patterns of gene expression and clinical markers from our research may lead to development of novel serum-based biomarker panels.

Exacerbating factors induce different gene expression profiles in peripheral blood mononuclear cells from asthmatics, patients with chronic obstructive pulmonary disease and healthy subjects

BACKGROUND

Despite several common phenotypic features, chronic obstructive pulmonary disease (COPD) and severe asthma differ with regard to their causative factors and pathophysiology. Both diseases may be exacerbated by environmental factors, however, the molecular profiles of disease episodes have not been comprehensively studied. We identified differences in gene and protein expression profiles expressed by peripheral blood mononuclear cells (PBMC) of COPD patients, patients with atopic asthma and healthy subjects when challenged with exacerbating factors in vitro: lipopolysaccharide (LPS), house dust mite (HDM) and cat allergen.

METHODS

PBMC isolated from patients with severe atopic asthma and COPD, as well as healthy subjects were stimulated with rDer p 1 DG, rFel d 1 DG and LPS. The changes in the expression of 47 genes belonging to five groups (phospholipase A2, eicosanoids, transcription factors, cytokines and airway remodeling) were studied using TaqMan low density array cards. Immunoblotting was used to study relative protein expression.

RESULTS

rDer p 1 significantly up-regulated the expression of PLA2G4A, PLA2G6, PLA2G15, CYSLTR1, LB4R2, PTGS1, PTGS2, FOXP1, GATA3, HDAC2, IREB2, PPARG, STAT4, TSLP and CHI3L1 genes in asthmatics in comparison to healthy subjects. LPS induced significant expression of ANXA1 and LTA4H in asthmatics when compared to COPD patients and healthy subjects. SOX6,STAT4 and IL1RL1 were induced in COPD after LPS stimulation. Analysis of protein expression revealed a pattern similar to mRNA expression.

CONCLUSIONS

LPS-induced exacerbation of asthma and COPD is characterized by differential expression of selected genes in PBMC. HDM allergen changed the expression profile of inflammatory genes between patients with asthma of atopic origin and healthy controls.

Differential gene expression profiles of peripheral blood mononuclear cells in childhood asthma

OBJECTIVE

Asthma is a common childhood disease with strong genetic components. This study compared whole-genome expression differences between asthmatic young children and healthy controls to identify gene signatures of childhood asthma.

METHODS

Total RNA extracted from peripheral blood mononuclear cells (PBMC) was subjected to microarray analysis. QRT-PCR was performed to verify the microarray results. Classification and functional characterization of differential genes were illustrated by hierarchical clustering and gene ontology analysis. Multiple logistic regression (MLR) analysis, receiver operating characteristic (ROC) curve analysis, and discriminate power were used to scan asthma-specific diagnostic markers.

RESULTS

For fold-change>2 and p < 0.05, there were 758 named differential genes. The results of QRT-PCR confirmed successfully the array data. Hierarchical clustering divided 29 highly possible genes into seven categories and the genes in the same cluster were likely to possess similar expression patterns or functions. Gene ontology analysis presented that differential genes primarily enriched in immune response, response to stress or stimulus, and regulation of apoptosis in biological process. MLR and ROC curve analysis revealed that the combination of ADAM33, Smad7, and LIGHT possessed excellent discriminating power.

CONCLUSIONS

The combination of ADAM33, Smad7, and LIGHT would be a reliable and useful childhood asthma model for prediction and diagnosis.

Future clinical implications emerging from recent genome-wide expression studies in asthma

Host susceptibility to environmental triggers is the most likely explanation for the development of asthma. Quantifying gene expression levels in disease-relevant tissues and cell types using fast evolving genomic technologies have generated new hypotheses about the pathogenesis of asthma and identified new therapeutic targets to treat asthma and asthma-exacerbations. New biomarkers and distinct transcriptomic phenotypes in blood, sputum and other tissues were also identified and proved effective to refine asthma classification and guide targeted therapies. The wealth of information provided by transcriptomic studies in asthma is yet to be fully exploited, but discoveries in this field may soon be implemented in clinical settings to improve diagnosis and treatment of patients afflicted with this common disease.

CGBayesNets: conditional Gaussian Bayesian network learning and inference with mixed discrete and continuous data

Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com.

Asthmatics with exacerbation during acute respiratory illness exhibit unique transcriptional signatures within the nasal mucosa

BACKGROUND

Acute respiratory illness is the leading cause of asthma exacerbations yet the mechanisms underlying this association remain unclear. To address the deficiencies in our understanding of the molecular events characterizing acute respiratory illness-induced asthma exacerbations, we undertook a transcriptional profiling study of the nasal mucosa over the course of acute respiratory illness amongst individuals with a history of asthma, allergic rhinitis and no underlying respiratory disease.

METHODS

Transcriptional profiling experiments were performed using the Agilent Whole Human Genome 4X44K array platform. Time point-based microarray and principal component analyses were conducted to identify and distinguish acute respiratory illness-associated transcriptional profiles over the course of our study. Gene enrichment analysis was conducted to identify biological processes over-represented within each acute respiratory illness-associated profile, and gene expression was subsequently confirmed by quantitative polymerase chain reaction.

RESULTS

We found that acute respiratory illness is characterized by dynamic, time-specific transcriptional profiles whose magnitudes of expression are influenced by underlying respiratory disease and the mucosal repair signature evoked during acute respiratory illness. Most strikingly, we report that people with asthma who experience acute respiratory illness-induced exacerbations are characterized by a reduced but prolonged inflammatory immune response, inadequate activation of mucosal repair, and the expression of a newly described exacerbation-specific transcriptional signature.

CONCLUSION

Findings from our study represent a significant contribution towards clarifying the complex molecular interactions that typify acute respiratory illness-induced asthma exacerbations.

Decision tree-based method for integrating gene expression, demographic, and clinical data to determine disease endotypes

Background

Complex diseases are often difficult to diagnose, treat and study due to the multi-factorial nature of the underlying etiology. Large data sets are now widely available that can be used to define novel, mechanistically distinct disease subtypes (endotypes) in a completely data-driven manner. However, significant challenges exist with regard to how to segregate individuals into suitable subtypes of the disease and understand the distinct biological mechanisms of each when the goal is to maximize the discovery potential of these data sets.

Results

A multi-step decision tree-based method is described for defining endotypes based on gene expression, clinical covariates, and disease indicators using childhood asthma as a case study. We attempted to use alternative approaches such as the Student’s t-test, single data domain clustering and the Modk-prototypes algorithm, which incorporates multiple data domains into a single analysis and none performed as well as the novel multi-step decision tree method. This new method gave the best segregation of asthmatics and non-asthmatics, and it provides easy access to all genes and clinical covariates that distinguish the groups.

Conclusions

The multi-step decision tree method described here will lead to better understanding of complex disease in general by allowing purely data-driven disease endotypes to facilitate the discovery of new mechanisms underlying these diseases. This application should be considered a complement to ongoing efforts to better define and diagnose known endotypes. When coupled with existing methods developed to determine the genetics of gene expression, these methods provide a mechanism for linking genetics and exposomics data and thereby accounting for both major determinants of disease.

Analysis of global gene expression changes in human bronchial epithelial cells exposed to spores of the allergenic fungus, Alternaria alternata

Exposure and sensitivity to ubiquitous airborne fungi such as Alternaria alternata have long been implicated in the development, onset, and exacerbation of chronic allergic airway disorders. This present study is the first to investigate global changes in host gene expression during the interaction of cultured human bronchial epithelial cells and live Alternaria spores. In in vitro experiments human bronchial epithelial cells (BEAS-2B) were exposed to spores or media alone for 24 h. RNA was collected from three biological replicates per treatment and was used to assess changes in gene expression patterns using Affymetrix Human Genome U133 Plus 2.0 Arrays. In cells treated with Alternaria spores compared to controls, 613 probe sets representing 460 individual genes were found differentially expressed (p ≤ 0.05). In this set of 460 statistically significant, differentially expressed genes, 397 genes were found to be up-regulated and 63 were down-regulated. Of these 397 up-regulated genes, 156 genes were found to be up-regulated ≥2 fold. Interestingly, none of the 63 down-regulated genes were found differentially expressed at ≤−2 fold. Differentially expressed genes were identified following statistical analysis and subsequently used for pathway and network evaluation. Interestingly, many cytokine and chemokine immune response genes were up-regulated with a particular emphasis on interferon-inducible genes. Genes involved in cell death, retinoic acid signaling, and TLR3 response pathways were also significantly up-regulated. Many of the differentially up-regulated genes have been shown in other systems to be associated with innate immunity, inflammation and/or allergic airway diseases. This study now provides substantial information for further investigating specific genes and innate immune system pathways activated by Alternaria in the context of allergic airway diseases.

Mechanisms of asthma and implications for its prevention and treatment: a personal journey

My research career has focused on the causes of asthma and its treatment. After establishing the key role that mast cells play in the inflammatory response in asthma, attention was turned towards understanding disease chronicity and variability across the lifecourse. Through a combination of studies on airway biopsies and primary cell cultures we have established that asthma is primarily an epithelial disease driven by increased environmental susceptibility to injury and an altered repair response as depicted by sustained activation of the epithelial mesenchymal trophic unit (EMTU) that is invoked in foetal branching morphogenesis. Varied activation of the EMTU connects the origins of asthma to its progression over time with involvement of epithelial susceptibility through impaired barrier and innate immune functions and altered mesenchymal susceptibility as exemplified by polymorphisms of the metalloprotease gene, ADAM33. Taken together these observations have led to a fundamental re-evaluation of asthma pathogenesis. Rather than placing allergic inflammation as the prime abnormality, it is proposed that the airway epithelium lies at the center of asthma pathogenesis, and that in conjunction with the underlying mesenchyme, it is the principle orchestrator of both the induction of asthma and its evolution over the lifecourse. This concept has provided 'the basis for a new preventative and therapeutic approach focused more on increasing the airways resistance to environmental insults rather than suppressing downstream inflammation once it is established.

Pathophysiology of asthma: lessons from genetic research with particular focus on severe asthma

There is good evidence that both inherited and environmental factors influence the risk of developing asthma. Only recently, large well-designed studies have been undertaken with the power to identify the genetic causes for asthma, and methods developed in parallel with the Human Genome Project, such as gene expression and epigenetic studies, have made large-scale analyses of functional genetics possible. In this review, we discuss the recent findings from genetic and genomic research studies of asthma, particularly severe asthma, and highlight specific genes for which there are multiple lines of evidence for involvement in asthma pathogenesis. Bio-ontologic enrichment analyses of the most recently identified asthma-related genes point to attributes such as 'molecular and signal transducer activity' and 'immune system processes', which indicates the importance of immunoregulation and inflammatory response in the pathogenesis of asthma. Finally, we discuss how genetic and environmental factors jointly influence asthma susceptibility and summarize how the results may increase understanding of the pathophysiology of asthma-related diseases.

Allergens and bacteria interaction in the induction of basophil activation: is this the lost ring between allergy and infections in pediatric patients?

PURPOSE OF REVIEW

The aim of this review is to describe the relationships between allergy and infectious diseases, with specific attention on bacterial infection. According to the most recent literature, bacteria could be considered also as one of the major causes of asthma exacerbations that we need to further explore.

RECENT FINDINGS

The availability of novel methods to detect large panels of pathogens, including viruses and bacteria specific for the upper respiratory tract, together with the capacity of evaluating how basophils are activated, has changed the point of view of the mechanisms related to asthma exacerbations. The recent finding that basophils are activated in the presence of suboptimal doses of allergens and bacteria has been recently described and may explain the clinical behavior of allergy exacerbation. Indeed the activation of basophils induces the secretion of mediators, which, at bronchial level, may cause bronchospasm that leads to an asthma exacerbation in patients with infection. The contrary is also true.

SUMMARY

Although the explanations for these facts are numerous, at present, bacteria seem to play a relevant role in the worsening of asthma in infected patients.

Predicting asthma exacerbations in children

PURPOSE OF REVIEW

This review critically assesses recently published literature on predicting asthma exacerbations in children, while also providing general recommendations for future research in this field.

RECENT FINDINGS

Current evidence suggests that every effort should be made to provide optimal treatment to achieve adequate asthma control, as this will significantly reduce the risk of severe disease exacerbations. Children who have had at least one asthma exacerbation in the previous year are at highest risk for subsequent exacerbations, regardless of disease severity and/or control. Although several tools and biomarkers to predict asthma exacerbations have been recently developed, these approaches need further validation and/or have only had partial success in identifying children at risk.

SUMMARY

Although considerable progress has been made, much remains to be done. Future studies should clearly differentiate severe asthma exacerbations due to inadequate asthma control from those occurring in children whose asthma is well controlled, utilize standardized definitions of asthma exacerbations, and use a systematic approach to identify the best predictors after accounting for the multiple dimensions of the problem. Our ability to correctly predict the development of severe asthma exacerbations in an individual child should improve in parallel with increased knowledge and/or understanding of the complex interactions among genetic, environmental (e.g. viral infections) and lifestyle (e.g. adherence to treatment) factors underlying these events.