Understanding the Molecular Mechanisms of Asthma through Transcriptomics

Integration of metabolomics and transcriptomics to reveal the mechanism of Gerberae piloselloidis herba in alleviating bronchial asthma

ETHNOPHARMACOLOGICAL RELEVANCE

Gerberae Piloselloides Herba (GPH) is derived from Gerbera piloselloides (Linn.) Cass. It is a commonly used traditional medicine in China, featured by its special bioactivities as antitussive, expectorant, anti-asthma, anti-bacterial and anti-tumor. It is often used as an effective treatment for cough and sore throat as well as bronchial asthma (BA) in China. It was demonstrated in our previous studies that GPH exerted significant effects on the treatment of BA, but its underlying mechanism remains unclear.

AIM OF THE STUDY

This study was aimed at revealing the mechanism through which GPH protects against BA.

MATERIALS AND METHODS

The protective effect of GPH against BA was evaluated in a mouse model of BA induced by ovalbumin. Through integrated metabolomics and transcriptomics analysis, the most critical pathways were discovered. The effects of GPH in regulating these pathways was verified through molecular biology experiments and molecular docking.

RESULTS

GPH have anti-BA effects. In plasma and lung tissue, 5 and 17 differentially expressed metabolites (DEMs), respectively, showed a reversed tendency in the GPH group compared with the model group; apart from gamma-aminobutyric acid and butyrylcarnitine, these DEMs might aid in BA diagnosis. The DEMs were involved primarily in the regulation of lipid metabolism, followed by glucose metabolism and amino acid metabolism. Transcriptomic analysis indicated that GPH modulated 268 differentially expressed genes (DEGs). Integration analysis of metabolomics and transcriptomics revealed that GPH might regulate the PPAR signaling pathway, thus affecting the expression of key gene targets such as Cyp4a12a, Cyp4a12b, Adh7, Acaa1b and Gpat2; controlling fatty acid degradation, unsaturated fatty acid biosynthesis, glycerophospholipid metabolism and other lipid metabolic pathways; and ameliorating BA. This possibility was confirmed through reverse-transcription quantitative polymerase chain reaction, western blotting, immunofluorescence and molecular docking.

CONCLUSION

GPH was found to activate the PPAR signaling pathway, decrease the levels of Cyp4a12a and Cyp4a12b, and increase the levels of Adh7, Acaa1b and Gpat2, thereby regulating lipid metabolism disorder, decreasing the generation of inflammatory mediators and limiting lung injury.

Single-cell RNA sequencing of bronchoscopy specimens: development of a rapid minimal handling protocol

Single-cell RNA sequencing (scRNA-seq) is an important tool for understanding disease pathophysiology, including airway diseases. Currently, the majority of scRNA-seq studies in airway diseases have used invasive methods (airway biopsy, surgical resection), which carry inherent risks and thus present a major limitation to scRNA-seq investigation of airway pathobiology. Bronchial brushing, where the airway mucosa is sampled using a cytological brush, is a viable, less invasive method of obtaining airway cells for scRNA-seq. Here we describe the development of a rapid and minimal handling protocol for preparing single-cell suspensions from bronchial brush specimens for scRNA-seq. Our optimized protocol maximizes cell recovery and cell quality and facilitates large-scale profiling of the airway transcriptome at single-cell resolution.

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.

Transcriptome analysis of sputum cells reveals two distinct molecular phenotypes of “asthma and chronic obstructive pulmonary disease overlap” in the elderly

Background

Little is known about the pathogenesis of asthma and chronic obstructive pulmonary disease (COPD) overlap (ACO). This study examined the molecular phenotypes of ACO in the elderly.

Methods

A genome-wide investigation of gene expression in sputum cells from the elderly with asthma, ACO, or COPD was performed using gene set variation analysis (GSVA) with predefined asthma- or COPD-specific gene signatures. We then performed a subsequent cluster analysis using enrichment scores (ESs) to identify molecular clusters in the elderly with ACO. Finally, a second GSVA was conducted with curated gene signatures to gain insight into the pathogenesis of ACO associated with the identified molecular clusters.

Results

Seventy elderly individuals were enrolled (17 with asthma, 41 with ACO, and 12 with COPD). Two distinct molecular clusters of ACO were identified. Clinically, ACO cluster 1 (N = 23) was characterized by male and smoker dominance, more obstructive lung function, and higher proportions of both neutrophil and eosinophil in induced sputum compared to ACO cluster 2 (N = 18). ACO cluster 1 had molecular features similar to both asthma and COPD, with mitochondria and peroxisome dysfunction as important mechanisms in the pathogenesis of these diseases. The molecular features of ACO cluster 2 differed from those of asthma and COPD, with enhanced innate immune reactions to microorganisms identified as being important in the pathogenesis of this form of ACO.

Conclusion

Recognition of the unique biological pathways associated with the two distinct molecular phenotypes of ACO will deepen our understanding of ACO in the elderly.

The Role of Systems Biology in Deciphering Asthma Heterogeneity

Asthma is one of the most common and lifelong and chronic inflammatory diseases characterized by inflammation, bronchial hyperresponsiveness, and airway obstruction episodes. It is a heterogeneous disease of varying and overlapping phenotypes with many confounding factors playing a role in disease susceptibility and management. Such multifactorial disorders will benefit from using systems biology as a strategy to elucidate molecular insights from complex, quantitative, massive clinical, and biological data that will help to understand the underlying disease mechanism, early detection, and treatment planning. Systems biology is an approach that uses the comprehensive understanding of living systems through bioinformatics, mathematical, and computational techniques to model diverse high-throughput molecular, cellular, and the physiologic profiling of healthy and diseased populations to define biological processes. The use of systems biology has helped understand and enrich our knowledge of asthma heterogeneity and molecular basis; however, such methods have their limitations. The translational benefits of these studies are few, and it is recommended to reanalyze the different studies and omics in conjugation with one another which may help understand the reasons for this variation and help overcome the limitations of understanding the heterogeneity in asthma pathology. In this review, we aim to show the different factors that play a role in asthma heterogeneity and how systems biology may aid in understanding and deciphering the molecular basis of asthma.

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.

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.

Evolving Concept of Severe Asthma: Transition From Diagnosis to Treatable Traits

In recent decades, the concept of severe asthma has evolved from an umbrella term encompassing patients with high-intensity treatment needs to a clinical syndrome with heterogeneous, albeit distinct, pathophysiological processes. Biased and unbiased cluster approaches have been used to identify several clinical phenotypes. In parallel, cellular and molecular approaches allow for the development of biological therapies, especially targeting type 2 (T2) cytokine pathways. Although T2-biologics have significantly improved clinical outcomes for patients with severe asthma in real-world practice, questions on the proper use of biologics remain open. Furthermore, a subset of severe asthma patients remains poorly controlled. The unmet needs require a new approach. The “treatable traits” concept has been suggested to address a diversity of pathophysiological factors in severe asthma and overcome the limitations of existing treatment strategies. With a tailored therapy that targets the treatable traits in individual patients, better personalized medical care and outcomes should be achieved.

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.

Derangement of cell cycle markers in peripheral blood mononuclear cells of asthmatic patients as a reliable biomarker for asthma control

In asthma, most of the identified biomarkers pertain to the Th2 phenotype and no known biomarkers have been verified for severe asthmatics. Therefore, identifying biomarkers using the integrative phenotype-genotype approach in severe asthma is needed. The study aims to identify novel biomarkers as genes or pathways representing the core drivers in asthma development, progression to the severe form, resistance to therapy, and tissue remodeling regardless of the sample cells or tissues examined. Comprehensive reanalysis of publicly available transcriptomic data that later was validated in vitro, and locally recruited patients were used to decipher the molecular basis of asthma. Our in-silicoanalysis revealed a total of 10 genes (GPRC5A, SFN, ABCA1, KRT8, TOP2A, SERPINE1, ANLN, MKI67, NEK2, and RRM2) related to cell cycle and proliferation to be deranged in the severe asthmatic bronchial epithelium and fibroblasts compared to their healthy counterparts. In vitro, RT qPCR results showed that (SERPINE1 and RRM2) were upregulated in severe asthmatic bronchial epithelium and fibroblasts, (SFN, ABCA1, TOP2A, SERPINE1, MKI67, and NEK2) were upregulated in asthmatic bronchial epithelium while (GPRC5A and KRT8) were upregulated only in asthmatic bronchial fibroblasts. Furthermore, MKI76, RRM2, and TOP2A were upregulated in Th2 high epithelium while GPRC5A, SFN, ABCA1 were upregulated in the blood of asthmatic patients. SFN, ABCA1 were higher, while MKI67 was lower in severe asthmatic with wheeze compared to nonasthmatics with wheezes. SERPINE1 and GPRC5A were downregulated in the blood of eosinophilic asthmatics, while RRM2 was upregulated in an acute attack of asthma. Validation of the gene expression in PBMC of locally recruited asthma patients showed that SERPINE1, GPRC5A, SFN, ABCA1, MKI67, and RRM2 were downregulated in severe uncontrolled asthma. We have identified a set of biologically crucial genes to the homeostasis of the lung and in asthma development and progression. This study can help us further understand the complex interplay between the transcriptomic data and the external factors which may deviate our understanding of asthma heterogeneity.

Integration of lncRNA and mRNA profiles to reveal the protective effects of Codonopsis pilosula extract on the gastrointestinal tract of mice subjected to D‑galactose‑induced aging

Codonopsis pilosula is a type of traditional Chinese medicine that exerts an anti‑aging effect and can regulate the gastrointestinal (GI) system. The aim of the present study was to investigate the underlying molecular mechanisms responsible for the anti‑aging effects of Codonopsis pilosula in the GI tract of mice with D‑galactose‑induced aging. First, a successful mouse model of aging was established, and Codonopsis pilosula water extract was then used for treatment. The anti‑aging effects of Codonopsis pilosula on the GI tract were then detected from the perspectives of tissue structure, physiological function and cell ultrastructure. Finally, in order to explore the underlying molecular mechanisms, the expression profiles of lncRNAs and mRNAs in the stomach and intestine were examined using microarray technology. A total of 117 (41 lncRNAs and 76 mRNAs) and 168 (85 lncRNA sand 83 mRNAs) differentially expressed genes associated with the anti‑aging effects of Codonopsis pilosula were identified in the stomach and intestine, respectively. Through integrated analysis of the stomach and intestine, 4 hub RNAs, including 1 lncRNA (LOC105243318) and 3 mRNAs (Fam132a, Rorc and 1200016E24Rik) were identified, which may be associated with the anti‑aging effects of Codonopsis pilosula in the GI tract of aging mice. The Kyoto Encyclopedia of Genes and Genomes analysis revealed that the metabolic pathway was an important pathway underlying the anti‑aging effects of Codonopsis pilosula in the GI tract. On the whole, in the present study, 4 hub RNAs associated with these effects and their regulatory networks were found in the GI tract of aging mice. In addition, the metabolic pathway was found to play an important role in these anti‑aging effects in the GI tract.