Network study of nasal transcriptome profiles reveals master regulator genes of asthma

Update on asthma biology

This is an exciting time to be conducting asthma research. The recent development of targeted asthma biologics has validated the power of basic research to discover new molecules amenable to therapeutic intervention. Advances in high-throughput sequencing are providing a wealth of "omics" data about genetic and epigenetic underpinnings of asthma, as well as about new cellular interacting networks and potential endotypes in asthma. Airway epithelial cells have emerged not only as key sensors of the outside environment but also as central drivers of dysregulated mucosal immune responses in asthma. Emerging data suggest that the airway epithelium in asthma remembers prior encounters with environmental exposures, resulting in potentially long-lasting changes in structure and metabolism that render asthmatic individuals susceptible to subsequent exposures. Here we summarize recent insights into asthma biology, focusing on studies using human cells or tissue that were published in the past 2 years. The studies are organized thematically into 6 content areas to draw connections and spur future research (on genetics and epigenetics, prenatal and early-life origins, microbiome, immune and inflammatory pathways, asthma endotypes and biomarkers, and lung structural alterations). We highlight recent studies of airway epithelial dysfunction and response to viral infections and conclude with a framework for considering how bidirectional interactions between alterations in airway structure and mucosal immunity can lead to sustained lung dysfunction in asthma.

Analytical challenges in omics research on asthma and allergy: A National Institute of Allergy and Infectious Diseases workshop

Studies of asthma and allergy are generating increasing volumes of omics data for analysis and interpretation. The National Institute of Allergy and Infectious Diseases (NIAID) assembled a workshop comprising investigators studying asthma and allergic diseases using omics approaches, omics investigators from outside the field, and NIAID medical and scientific officers to discuss the following areas in asthma and allergy research: genomics, epigenomics, transcriptomics, microbiomics, metabolomics, proteomics, lipidomics, integrative omics, systems biology, and causal inference. Current states of the art, present challenges, novel and emerging strategies, and priorities for progress were presented and discussed for each area. This workshop report summarizes the major points and conclusions from this NIAID workshop. As a group, the investigators underscored the imperatives for rigorous analytic frameworks, integration of different omics data types, cross-disciplinary interaction, strategies for overcoming current limitations, and the overarching goal to improve scientific understanding and care of asthma and allergic diseases.

Identification of differences in CD4+ T-cell gene expression between people with asthma and healthy controls

Functional enrichment analysis of genome-wide association study (GWAS)-summary statistics has suggested that CD4+ T-cells play an important role in asthma pathogenesis. Despite this, CD4+ T-cells are under-represented in asthma transcriptome studies. To fill the gap, 3'-RNA-Seq was used to generate gene expression data on CD4+ T-cells (isolated within 2 h from collection) from peripheral blood from participants with well-controlled asthma (n = 32) and healthy controls (n = 11). Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify sets of co-expressed genes (modules) associated with the asthma phenotype. We identified three modules associated with asthma, which are strongly enriched for GWAS-identified asthma genes, antigen processing/presentation and immune response to viral infections. Through integration of publicly available eQTL and GWAS summary statistics (colocalisation), and protein-protein interaction (PPI) data, we identified PTPRC, a potential druggable target, as a putative master regulator of the asthma gene-expression profiles. Using a co-expression network approach, with integration of external genetic and PPI data, we showed that CD4+ T-cells from peripheral blood from asthmatics have different expression profiles, albeit small in magnitude, compared to healthy controls, for sets of genes involved in immune response to viral infections (upregulated) and antigen processing/presentation (downregulated).

Poorly controlled asthma - Easy wins and future prospects for addressing fungal allergy

Poorly controlled asthma is especially common in low resource countries. Aside from lack of access to, or poor technique with, inhaled beta-2 agonists and corticosteroids, the most problematic forms of asthma are frequently associated with both fungal allergy and exposure, especially in adults leading to more asthma exacerbations and worse asthma. The umbrella term 'fungal asthma' describes many disorders linked to fungal exposure and/or allergy to fungi. One fungal asthma endotype, ABPA, is usually marked by a very high IgE and its differential diagnosis is reviewed. Both ABPA and fungal bronchitis in bronchiectasis are marked by thick excess airway mucus production. Dermatophyte skin infection can worsen asthma and eradication of the skin infection improves asthma. Exposure to fungi in the workplace, home and schools, often in damp or water-damaged buildings worsens asthma, and remediation improves symptom control and reduces exacerbations. Antifungal therapy is beneficial for fungal asthma as demonstrated in nine of 13 randomised controlled studies, reducing symptoms, corticosteroid need and exacerbations while improving lung function. Other useful therapies include azithromycin and some biologics approved for the treatment of severe asthma. If all individuals with poorly controlled and severe asthma could be 'relieved' of their fungal allergy and infection through antifungal therapy without systemic corticosteroids, the health benefits would be enormous and relatively inexpensive, improving the long term health of over 20 million adults and many children. Antifungal therapy carries some toxicity, drug interactions and triazole resistance risks, and data are incomplete. Here we summarise what is known and what remains uncertain about this complex topic.

Integrated study of systemic and local airway transcriptomes in asthma reveals causal mediation of systemic effects by airway key drivers

BACKGROUND

Systemic and local profiles have each been associated with asthma, but parsing causal relationships between system-wide and airway-specific processes can be challenging. We sought to investigate systemic and airway processes in asthma and their causal relationships.

METHODS

Three hundred forty-one participants with persistent asthma and non-asthmatic controls were recruited and underwent peripheral blood mononuclear cell (PBMC) collection and nasal brushing. Transcriptome-wide RNA sequencing of the PBMC and nasal samples and a series of analyses were then performed using a discovery and independent test set approach at each step to ensure rigor. Analytic steps included differential expression analyses, coexpression and probabilistic causal (Bayesian) network constructions, key driver analyses, and causal mediation models.

RESULTS

Among the 341 participants, the median age was 13 years (IQR = 10-16), 164 (48%) were female, and 200 (58.7%) had persistent asthma with mean Asthma Control Test (ACT) score 16.6 (SD = 4.2). PBMC genes associated with asthma were enriched in co-expression modules for NK cell-mediated cytotoxicity (fold enrichment = 4.5, FDR = 6.47 × 10-32) and interleukin production (fold enrichment = 2.0, FDR = 1.01 × 10-15). Probabilistic causal network and key driver analyses identified NK cell granule protein (NKG7, fold change = 22.7, FDR = 1.02 × 10-31) and perforin (PRF1, fold change = 14.9, FDR = 1.31 × 10-22) as key drivers predicted to causally regulate PBMC asthma modules. Nasal genes associated with asthma were enriched in the tricarboxylic acid (TCA) cycle module (fold enrichment = 7.5 FDR = 5.09 × 10-107), with network analyses identifying G3BP stress granule assembly factor 1 (G3BP1, fold change = 9.1 FDR = 2.77 × 10-5) and InaD-like protein (INADL, fold change = 5.3 FDR = 2.98 × 10-9) as nasal key drivers. Causal mediation analyses revealed that associations between PBMC key drivers and asthma are causally mediated by nasal key drivers (FDR = 0.0076 to 0.015).

CONCLUSIONS

Integrated study of the systemic and airway transcriptomes in a well-phenotyped asthma cohort identified causal key drivers of asthma among PBMC and nasal transcripts. Associations between PBMC key drivers and asthma are causally mediated by nasal key drivers.

Transcriptomic Differentiation of Phenotypes in Chronic Rhinosinusitis and Its Implications for Understanding the Underlying Mechanisms

Chronic rhinosinusitis (CRS) is a multifaceted disease with variable clinical courses and outcomes. We aimed to determine CRS-associated nasal-tissue transcriptome in clinically well-characterized and phenotyped individuals, to gain a novel insight into the biological pathways of the disease. RNA-sequencing of tissue samples of patients with CRS with polyps (CRSwNP), without polyps (CRSsNP), and controls were performed. Characterization of differently expressed genes (DEGs) and functional and pathway analysis was undertaken. We identified 782 common CRS-associated nasal-tissue DEGs, while 375 and 328 DEGs were CRSwNP- and CRSsNP-specific, respectively. Common key DEGs were found to be involved in dendritic cell maturation, the neuroinflammation pathway, and the inhibition of the matrix metalloproteinases. Distinct CRSwNP-specific DEGs were involved in NF-kβ canonical pathways, Toll-like receptor signaling, HIF1α regulation, and the Th2 pathway. CRSsNP involved the NFAT pathway and changes in the calcium pathway. Our findings offer new insights into the common and distinct molecular mechanisms underlying CRSwNP and CRSsNP, providing further understanding of the complex pathophysiology of the CRS, with future research directions for novel treatment strategies.

Co-Expression Analysis of Airway Epithelial Transcriptome in Asthma Patients with Eosinophilic vs. Non-Eosinophilic Airway Infiltration

Asthma heterogeneity complicates the search for targeted treatment against airway inflammation and remodeling. We sought to investigate relations between eosinophilic inflammation, a phenotypic feature frequent in severe asthma, bronchial epithelial transcriptome, and functional and structural measures of airway remodeling. We compared epithelial gene expression, spirometry, airway cross-sectional geometry (computed tomography), reticular basement membrane thickness (histology), and blood and bronchoalveolar lavage (BAL) cytokines of n = 40 moderate to severe eosinophilic (EA) and non-eosinophilic asthma (NEA) patients distinguished by BAL eosinophilia. EA patients showed a similar extent of airway remodeling as NEA but had an increased expression of genes involved in the immune response and inflammation (e.g., KIR3DS1), reactive oxygen species generation (GYS2, ATPIF1), cell activation and proliferation (ANK3), cargo transporting (RAB4B, CPLX2), and tissue remodeling (FBLN1, SOX14, GSN), and a lower expression of genes involved in epithelial integrity (e.g., GJB1) and histone acetylation (SIN3A). Genes co-expressed in EA were involved in antiviral responses (e.g., ATP1B1), cell migration (EPS8L1, STOML3), cell adhesion (RAPH1), epithelial-mesenchymal transition (ASB3), and airway hyperreactivity and remodeling (FBN3, RECK), and several were linked to asthma in genome- (e.g., MRPL14, ASB3) or epigenome-wide association studies (CLC, GPI, SSCRB4, STRN4). Signaling pathways inferred from the co-expression pattern were associated with airway remodeling (e.g., TGF-β/Smad2/3, E2F/Rb, and Wnt/β-catenin).

Recent progress in the genetic and epigenetic underpinnings of atopy

In the past 2 years, there continue to be advances in our understanding of the genetic and epigenetic underpinnings of atopy pertaining to disease risk and disease severity. The joint role of genetics and the environment has been emphasized in multiple studies. Combining genetics with family history, biomarkers, and comorbidities is further refining our ability to predict the development of individual atopic diseases as well as the advancement of the atopic march. Polygenic risk scores will be an important next step for the field moving toward clinical translation of the genetic findings thus far. A systems biology approach, as illustrated by studies of the microbiome and epigenome, will be necessary to fully understand disease development and to develop increasingly targeted therapeutics.

Examination of host genetic effects on nasal microbiome composition

BACKGROUND

Genetic predisposition increases risk for asthma, and distinct nasal microbial compositions are associated with asthma. Host genetics might shape nasal microbiome composition.

OBJECTIVE

We examined associations between host genetics and nasal microbiome composition.

METHODS

Nasal samples were collected from 584 participants from the Mount Sinai Health System, New York. Seventy-seven follow-up samples were collected from a subset of 40 participants. 16S rRNA sequencing and RNA sequencing were performed on nasal samples. Beta diversity was calculated, variant calling on RNA sequencing data was performed, and genetic relatedness between individuals was determined. Using linear regression models, we tested for associations between genetic relatedness and nasal microbiome composition.

RESULTS

The median age of the cohort was 14.6 (interquartile range 11.2-19.5) years, with participants representing diverse ancestries and 52.7% of the cohort being female. For participants who provided follow-up samples, the median time between samples was 5.1 (interquartile range 1.4-7.2) months. Nasal microbiome composition similarity as reflected by beta diversity was significantly higher within subjects over time versus between subjects (coefficient = 0.091, P = 2.84-7). There was no significant association between genetic relatedness and beta diversity (coefficient = -0.05, P = .29). Additional analyses exploring the relationship between beta diversity and genetic variance yielded similar results.

CONCLUSION

Host genetics has little influence on nasal microbiome composition.

Neutrophil Extracellular Vesicles and Airway Smooth Muscle Proliferation in the Natural Model of Severe Asthma in Horses

Extracellular vesicles (EVs) contribute to intercellular communication through the transfer of their rich cargo to recipient cells. The EVs produced by LPS-stimulated neutrophils from healthy humans and horses increase airway smooth muscle (ASM) proliferation, but the roles of neutrophil EVs in asthma are largely unexplored. The aim of this study was to determine whether neutrophil-derived EVs isolated during the remission or exacerbation of asthma influence ASM proliferation differentially. Peripheral blood neutrophils were collected during remission and exacerbation in eight horses affected by severe asthma. The cells were cultured (±LPS), and their EVs were isolated by ultracentrifugation and characterized by laser scattering microscopy and proteomic analysis. The proliferation of ASM co-incubated with EVs was monitored in real time by electrical impedance. Two proteins were significantly upregulated during disease exacerbation in neutrophil EVs (MAST4 and Lrch4), while LPS stimulation greatly altered the proteomic profile. Those changes involved the upregulation of neutrophil degranulation products, including proteases known to induce myocyte proliferation. In agreement with the proteomic results, EVs from LPS-stimulated neutrophils increased ASM proliferation, without an effect of the disease status. The inhalation of environmental LPS could contribute to asthma pathogenesis by activating neutrophils and leading to ASM hyperplasia.

Identification of key genes and pathways in chronic rhinosinusitis with nasal polyps and asthma comorbidity using bioinformatics approaches

Patients with chronic rhinosinusitis with nasal polyps (CRSwNP) and asthma comorbidity (ACRSwNP) present severe symptoms and are more likely to relapse. However, the pathogenesis of ACRSwNP is not fully understood. The aim of this study was to explore the underlying pathogenesis of ACRSwNP using bioinformatics approaches. ACRSwNP-related differentially expressed genes (DEGs) were identified by the analysis of the GSE23552 dataset. The clusterProfiler R package was used to carry out functional and pathway enrichment analysis. A protein–protein interaction (PPI) network was built using the STRING database to explore key genes in the pathogenesis of ACRSwNP. The bioinformatics analysis results were verified through qRT-PCR. The Connectivity Map (CMap) database was used to predict potential drugs for the treatment of ACRSwNP. A total of 36 DEGs were identified, which were mainly enriched in terms of regulation of immune response and detection sensory perception of taste. Thirteen hub genes including AZGP1, AQP9, GAPT, PIP, and PRR4 were identified as potential hub genes in ACRSwNP from the PPI network. Analysis of the GSE41861 dataset showed that upregulation of CST1 in nasal mucosa was associated with asthma. qRT-PCR detection confirmed the bioinformatics analysis results. Tacrolimus and spaglumic acid were identified as potential drugs for the treatment of ACRSwNP from the CMap database. The findings of this study provide insights into the pathogenesis of ACRSwNP and may provide a basis for the discovery of effective therapeutic modalities for ACRSwNP.

Microbiome Research and Multi-Omics Integration for Personalized Medicine in Asthma

Asthma is a multifactorial inflammatory disorder of the respiratory system characterized by high diversity in clinical manifestations, underlying pathological mechanisms and response to treatment. It is generally established that human microbiota plays an essential role in shaping a healthy immune response, while its perturbation can cause chronic inflammation related to a wide range of diseases, including asthma. Systems biology approaches encompassing microbiome analysis can offer valuable platforms towards a global understanding of asthma complexity and improving patients' classification, status monitoring and therapeutic choices. In the present review, we summarize recent studies exploring the contribution of microbiota dysbiosis to asthma pathogenesis and heterogeneity in the context of asthma phenotypes-endotypes and administered medication. We subsequently focus on emerging efforts to gain deeper insights into microbiota-host interactions driving asthma complexity by integrating microbiome and host multi-omics data. One of the most prominent achievements of these research efforts is the association of refractory neutrophilic asthma with certain microbial signatures, including predominant pathogenic bacterial taxa (such as Proteobacteria phyla, Gammaproteobacteria class, especially species from Haemophilus and Moraxella genera). Overall, despite existing challenges, large-scale multi-omics endeavors may provide promising biomarkers and therapeutic targets for future development of novel microbe-based personalized strategies for diagnosis, prevention and/or treatment of uncontrollable asthma.

Machine learning-driven identification of early-life air toxic combinations associated with childhood asthma outcomes

Air pollution is a well-known contributor to asthma. Air toxics are hazardous air pollutants that cause or may cause serious health effects. Although individual air toxics have been associated with asthma, only a limited number of studies have specifically examined combinations of air toxics associated with the disease. We geocoded air toxic levels from the US National Air Toxics Assessment (NATA) to residential locations for participants of our AiRway in Asthma (ARIA) study. We then applied Data-driven ExposurE Profile extraction (DEEP), a machine learning-based method, to discover combinations of early-life air toxics associated with current use of daily asthma controller medication, lifetime emergency department visit for asthma, and lifetime overnight hospitalization for asthma. We discovered 20 multi-air toxic combinations and 18 single air toxics associated with at least 1 outcome. The multi-air toxic combinations included those containing acrylic acid, ethylidene dichloride, and hydroquinone, and they were significantly associated with asthma outcomes. Several air toxic members of the combinations would not have been identified by single air toxic analyses, supporting the use of machine learning-based methods designed to detect combinatorial effects. Our findings provide knowledge about air toxic combinations associated with childhood asthma.

Transcriptome genetic differences between responders and non-responders before bronchial thermoplasty

BACKGROUND

Bronchial thermoplasty (BT) is an endoscopic therapy used for the treatment of refractory asthma. Some predictive factors, for example the number of activations and severity of disease at baseline, have been used to determine the effectiveness of BT in treating patients with asthma. The aim of the present study was to comprehensively analyze RNA samples from the airway bronchial tissues of patients with severe asthma treated by BT, and to characterize each patient as a BT responder or non-responder.

METHODS

Eight patients with severe asthma scheduled to undergo BT and bronchus biopsies were recruited before the procedures were conducted. Extracted RNA samples from bronchial tissues were sequenced and differential gene expression analysis was carried out.Results/discussion: Subjects with Asthma Quality of Life Questionnaire score changes ≥0.5 for a period of 12 months were considered BT responders. Non-responders had score changes <0.5 for 12 months. Histopathology findings were similar to those reported previously, and no significant differences in the expression of α-smooth muscle actin and protein gene product 9.5 were observed between responders and non-responders. Transcriptome analysis at baseline identified 67 genes that were differentially expressed between responders and non-responders, including SLPI, MMP3, and MUC19, which were upregulated in responders. Although the differentially expressed gene products may have conflicting effects, genes in the airway epithelium and extracellular matrix of patients with severe asthma may determine the BT response. Our results identified possible transcriptomic changes that could be used to identify BT responders.

Regulatory T Cell-Related Gene Biomarkers in the Deterioration of Atherosclerosis

Background: Regulatory T cells (Tregs) have shown to be protective against the development of atherosclerosis, a major pathological cause for cardiovascular events. Here, we aim to explore the roles of Tregs-related genes in atherosclerosis deterioration. Methods and Results: We downloaded the gene expression profile of 29 atherosclerotic samples from the Gene Expression Omnibus database with an accession number of GSE28829. The abundance of Tregs estimated by the CIBERSORT algorithm was negatively correlated with the atherosclerotic stage. Using the limma test and correlation analysis, a total of 159 differentially expressed Tregs-related genes (DETregRGs) between early and advanced atherosclerotic plaques were documented. Functional annotation analysis using the DAVID tool indicated that the DETregRGs were mainly enriched in inflammatory responses, immune-related mechanisms, and pathways such as complement and coagulation cascades, platelet activation, leukocyte trans-endothelial migration, vascular smooth muscle contraction, and so on. A protein-protein interaction network of the DETregRGs was then constructed, and five hub genes (PTPRC, C3AR1, CD53, TLR2, and CCR1) were derived from the network with node degrees ≥20. The expression patterns of these hub DETregRGs were further validated in several independent datasets. Finally, a single sample scoring method was used to build a gene signature for the five DETregRGs, which could distinguish patients with myocardial infarction from those with stable coronary disease. Conclusion: The results of this study will improve our understanding about the Tregs-associated molecular mechanisms in the progression of atherosclerosis and facilitate the discovery of novel biomarkers for acute cardiovascular events.

Merged Affinity Network Association Clustering: Joint multi-omic/clinical clustering to identify disease endotypes

Although clinical and laboratory data have long been used to guide medical practice, this information is rarely integrated with multi-omic data to identify endotypes. We present Merged Affinity Network Association Clustering (MANAclust), a coding-free, automated pipeline enabling integration of categorical and numeric data spanning clinical and multi-omic profiles for unsupervised clustering to identify disease subsets. Using simulations and real-world data from The Cancer Genome Atlas, we demonstrate that MANAclust’s feature selection algorithms are accurate and outperform competitors. We also apply MANAclust to a clinically and multi-omically phenotyped asthma cohort. MANAclust identifies clinically and molecularly distinct clusters, including heterogeneous groups of “healthy controls” and viral and allergy-driven subsets of asthmatic subjects. We also find that subjects with similar clinical presentations have disparate molecular profiles, highlighting the need for additional testing to uncover asthma endotypes. This work facilitates data-driven personalized medicine through integration of clinical parameters with multi-omics. MANAclust is freely available at https://bitbucket.org/scottyler892/manaclust/src/master/.

Clinical data commonly used in medical practice are underutilized in multi-omic analyses to identify disease endotypes. Tyler et al. present a python package called Merged Affinity Network Association Clustering (MANAclust) that automatically processes and integrates categorical and numeric data types, facilitating the inclusion of clinical data in multi-omic endotyping efforts.

Relationship of Pneumocystis antibody responses to paediatric asthma severity

BACKGROUND

Although asthma is the most commonly diagnosed respiratory disease, its pathogenesis is complex, involving both genetic and environmental factors. A role for the respiratory microbiome in modifying asthma severity has been recently recognised. Airway colonisation by Pneumocystis jirovecii has previously been associated with multiple chronic lung diseases, including chronic obstructive pulmonary disease (COPD) and severe asthma (SA). Decreased incidence of Pneumocystis pneumonia in HIV-infected individuals and reduced severity of COPD is associated with naturally occurring antibody responses to the Pneumocystis antigen, Kexin (KEX1).

METHODS

104 paediatric patients were screened for KEX1 IgG reciprocal end point titre (RET), including 51 with SA, 20 with mild/moderate asthma, 20 non-asthma and 13 with cystic fibrosis (CF) in a cross-sectional study.

RESULTS

Patients with SA had significantly reduced Pneumocystis KEX1 titres compared with patients with mild/moderate asthma (p=0.018) and CF (p=0.003). A binary KEX1 RET indicator was determined at a threshold of KEX1 RET=1000. Patients with SA had 4.40 (95% CI 1.28 to 13.25, p=0.014) and 17.92 (95% CI 4.15 to 66.62, p<0.001) times the odds of falling below that threshold compared with mild/moderate asthma and patients with CF, respectively. Moreover, KEX1 IgG RET did not correlate with tetanus toxoid IgG (r=0.21, p=0.82) or total IgE (r=0.03, p=0.76), indicating findings are specific to antibody responses to KEX1.

CONCLUSIONS

Paediatric patients with SA may be at higher risk for chronic Pneumocystis infections and asthma symptom exacerbation due to reduced levels of protective antibodies. Plasma KEX1 IgG titre may be a useful parameter in determining the clinical course of treatment for paediatric patients with asthma.