What did we learn from multiple omics studies in asthma?

Galectin-10 in serum extracellular vesicles reflects asthma pathophysiology

BACKGROUND

Novel biomarkers (BMs) are urgently needed for bronchial asthma (BA) with various phenotypes and endotypes.

OBJECTIVE

We sought to identify novel BMs reflecting tissue pathology from serum extracellular vesicles (EVs).

METHODS

We performed data-independent acquisition of serum EVs from 4 healthy controls, 4 noneosinophilic asthma (NEA) patients, and 4 eosinophilic asthma (EA) patients to identify novel BMs for BA. We confirmed EA-specific BMs via data-independent acquisition validation in 61 BA patients and 23 controls. To further validate these findings, we performed data-independent acquisition for 6 patients with chronic rhinosinusitis without nasal polyps and 7 patients with chronic rhinosinusitis with nasal polyps.

RESULTS

We identified 3032 proteins, 23 of which exhibited differential expression in EA. Ingenuity pathway analysis revealed that protein signatures from each phenotype reflected disease characteristics. Validation revealed 5 EA-specific BMs, including galectin-10 (Gal10), eosinophil peroxidase, major basic protein, eosinophil-derived neurotoxin, and arachidonate 15-lipoxygenase. The potential of Gal10 in EVs was superior to that of eosinophils in terms of diagnostic capability and detection of airway obstruction. In rhinosinusitis patients, 1752 and 8413 proteins were identified from EVs and tissues, respectively. Among 11 BMs identified in EVs and tissues from patients with chronic rhinosinusitis with nasal polyps, 5 (including Gal10 and eosinophil peroxidase) showed significant correlations between EVs and tissues. Gal10 release from EVs was implicated in eosinophil extracellular trapped cell death in vitro and in vivo.

CONCLUSION

Novel BMs such as Gal10 from serum EVs reflect disease pathophysiology in BA and may represent a new target for liquid biopsy approaches.

Lipid species profiling of bronchoalveolar lavage fluid cells of horses housed on two different bedding materials

The lipidome of equine BALF cells has not been described. The objectives of this prospective repeated-measures study were to explore the BALF cells' lipidome in horses and to identify lipids associated with progression or resolution of airway inflammation. BALF cells from 22 horses exposed to two bedding materials (Peat 1-Wood shavings [WS]-Peat 2) were studied by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The effects of bedding on lipid class and species compositions were tested with rmANOVA. Correlations between lipids and cell counts were examined. The BALF cells' lipidome showed bedding-related differences for molar percentage (mol%) of 60 species. Whole phosphatidylcholine (PC) class and its species PC 32:0 (main molecular species 16:0_16:0) had higher mol% after Peat 2 compared with WS. Phosphatidylinositol 38:4 (main molecular species 18:0_20:4) was higher after WS compared with both peat periods. BALF cell count correlated positively with mol% of the lipid classes phosphatidylserine, sphingomyelin, ceramide, hexosylceramide, and triacylglycerol but negatively with PC. BALF cell count correlated positively with phosphatidylinositol 38:4 mol%. In conclusion, equine BALF cells' lipid profiles explored with MS-based lipidomics indicated subclinical inflammatory changes after WS. Inflammatory reactions in the cellular lipid species composition were detected although cytological responses indicating inflammation were weak.

GOAT: Gene-level biomarker discovery from multi-Omics data using graph ATtention neural network for eosinophilic asthma subtype

MOTIVATION

Asthma is a heterogeneous disease where various subtypes are established and molecular biomarkers of the subtypes are yet to be discovered. Recent availability of multi-omics data paved a way to discover molecular biomarkers for the subtypes. However, multi-omics biomarker discovery is challenging because of the complex interplay between different omics layers.

RESULTS

We propose a deep attention model named Gene-level biomarker discovery from multi-Omics data using graph ATtention neural network (GOAT) for identifying molecular biomarkers for eosinophilic asthma subtypes with multi-omics data. GOAT identifies genes that discriminate subtypes using a graph neural network by modeling complex interactions among genes as the attention mechanism in the deep learning model. In experiments with multi-omics profiles of the COREA (Cohort for Reality and Evolution of Adult Asthma in Korea) asthma cohort of 300 patients, GOAT outperforms existing models and suggests interpretable biological mechanisms underlying asthma subtypes. Importantly, GOAT identified genes that are distinct only in terms of relationship with other genes through attention. To better understand the role of biomarkers, we further investigated two transcription factors, CTNNB1 and JUN, captured by GOAT. We were successful in showing the role of the transcription factors in eosinophilic asthma pathophysiology in a network propagation and transcriptional network analysis, which were not distinct in terms of gene expression level differences.

AVAILABILITY AND IMPLEMENTATION

Source code is available https://github.com/DabinJeong/Multi-omics_biomarker. The preprocessed data underlying this article is accessible in data folder of the github repository. Raw data are available in Multi-Omics Platform at http://203.252.206.90:5566/, and it can be accessible when requested.

Asthma

Asthma is one of the most common chronic non-communicable diseases worldwide and is characterised by variable airflow obstruction, causing dyspnoea and wheezing. Highly effective therapies are available; asthma morbidity and mortality have vastly improved in the past 15 years, and most patients can attain good asthma control. However, undertreatment is still common, and improving patient and health-care provider understanding of when and how to adjust treatment is crucial. Asthma management consists of a cycle of assessment of asthma control and risk factors and adjustment of medications accordingly. With the introduction of biological therapies, management of severe asthma has entered the precision medicine era-a shift that is driving clinical ambitions towards disease remission. Patients with severe asthma often have co-existing conditions contributing to their symptoms, mandating a multidimensional management approach. In this Seminar, we provide a clinically focused overview of asthma; epidemiology, pathophysiology, diagnosis, and management in children and adults.

Precision Medicine Intervention in Severe Asthma (PRISM) study: molecular phenotyping of patients with severe asthma and response to biologics

Severe asthma represents an important clinical unmet need despite the introduction of biologic agents. Although advanced omics technologies have aided researchers in identifying clinically relevant molecular pathways, there is a lack of an integrated omics approach in severe asthma particularly in terms of its evolution over time. The collaborative Korea-UK research project Precision Medicine Intervention in Severe Asthma (PRISM) was launched in 2020 with the aim of identifying molecular phenotypes of severe asthma by analysing multi-omics data encompassing genomics, epigenomics, transcriptomics, proteomics, metagenomics and metabolomics. PRISM is a prospective, observational, multicentre study involving patients with severe asthma attending severe asthma clinics in Korea and the UK. Data including patient demographics, inflammatory phenotype, medication, lung function and control status of asthma will be collected along with biological samples (blood, sputum, urine, nasal epithelial cells and exhaled breath condensate) for omics analyses. Follow-up evaluations will be performed at baseline, 1 month, 4-6 months and 10-12 months to assess the stability of phenotype and treatment responses for those patients who have newly begun biologic therapy. Standalone and integrated omics data will be generated from the patient samples at each visit, paired with clinical information. By analysing these data, we will identify the molecular pathways that drive lung function, asthma control status, acute exacerbations and the requirement for daily oral corticosteroids, and that are involved in the therapeutic response to biological therapy. PRISM will establish a large multi-omics dataset of severe asthma to identify potential key pathophysiological pathways of severe asthma.

Precision Medicine in Asthma Therapy

Asthma is a complex, heterogeneous disease that necessitates a proper patient evaluation to decide the correct treatment and optimize disease control. The recent introduction of new target therapies for the most severe form of the disease has heralded a new era of treatment options, intending to treat and control specific molecular pathways in asthma pathophysiology. Precision medicine, using omics sciences, investigates biological and molecular mechanisms to find novel biomarkers that can be used to guide treatment selection and predict response. The identification of reliable biomarkers indicative of the pathological mechanisms in asthma is essential to unravel new potential treatment targets. In this chapter, we provide a general description of the currently available -omics techniques, focusing on their implications in asthma therapy.

Utility of biomarkers in the diagnosis and monitoring of asthmatic children

Asthma imposes a heavy morbidity burden during childhood; it affects over 10% of children in Europe and North America and it is estimated to exceed 400 million people worldwide by the year 2025. In clinical practice, diagnosis of asthma in children is mostly based on clinical criteria; nevertheless, assessment of both physiological and pathological processes through biomarkers, support asthma diagnosis, aid monitoring, and further lead to better treatment outcomes and reduced morbidity. Recently, identification and validation of biomarkers in pediatric asthma has emerged as a top priority across leading experts, researchers, and clinicians. Moreover, the implementation of non-invasive biomarkers for the assessment and monitoring of paediatric patients with asthma, has been prioritized; however, only a proportion of them are currently included in the clinical practise. Although, the use of non-invasive biomarkers is highly supported in recent asthma guidelines for documenting diagnosis and supporting monitoring of asthmatic patients, data on the Pediatric population are limited. In the present report, the Pediatric Asthma Committee of the World Allergy Organization (WAO), aims to summarize and discuss available data for the implementation of non-invasive biomarkers in the diagnosis and monitoring in children with asthma. Information on the most studied biomarkers, including spirometry, oscillometry, markers of allergic sensitization, fractional exhaled nitric oxide, and the most recent exhaled breath markers and "omic" approaches, will be reviewed. Practical limitations and considerations based on both experts' opinion and critical review of the literature, on the utility of all "well-known" and newly introduced non-invasive biomarkers will be presented. A critical commentary on biomarkers' use in diagnosing and monitoring asthma during the COVID-19 pandemic, cost and availability of biomarkers in different settings and in developing countries, the differences on the biomarkers use between Primary Practitioners, Pediatricians, and Specialists and their role on the longitudinal aspect of asthma is provided.

Recent miRNA Research in Asthma

PURPOSE OF REVIEW

The study of microRNA in asthma has revealed a vibrant new level of gene regulation underlying asthma pathology. Several miRNAs have been shown to be important in asthma, influencing various biological mechanisms which lead to asthma pathology and symptoms. In addition, miRNAs have been proposed as biomarkers of asthma affection status, asthma severity, and asthma treatment response. We review all recent asthma-miRNA work, while also presenting comprehensive tables of all miRNA results related to asthma.

RECENT FINDINGS

We here reviewed 63 recent studies published reporting asthma and miRNA research, and an additional 14 reviews of the same. We summarized the information for both adult and childhood asthma, as well as research on miRNAs in asthma-COPD overlap syndrome (ACOs), and virus-induced asthma exacerbations. We attempted to present a comprehensive collection of recently published asthma-associated miRNAs as well as tables of all published asthma-related miRNA results.

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.

Challenges in severe asthma: Do we need new drugs or new biomarkers?

Severe asthma is a complex, heterogenous airway condition. There have been significant advances in severe asthma management in the past decade using monoclonal antibody therapies that target the inflammatory component of the disease. Patient selection has been paramount for the success of these biologicals, leading to significant interest in biomarkers to guide treatment. Some severe asthmatics remain suboptimally controlled despite trials of biologicals and many of these patients still require chronic systemic corticosteroids. New therapeutics are currently in development to address this unmet need. However, whether these patients could be better treated by using novel biomarkers that inform selection among currently available biologics, and that objectively measure disease control is unclear. In this review, we examine the currently used biomarkers that guide severe asthma management and emerging biomarkers that may improve asthma therapy in the future.

Recent insights in the role of biomarkers in severe asthma management

Contemporary asthma management requires a proactive and individualized approach, combining precision diagnosis and personalized treatment. The introduction of biologic therapies for severe asthma to everyday clinical practice, increases the need for specific patient selection, prediction of outcomes and monitoring of these costly and long-lasting therapies. Several biomarkers have been used in asthma in disease identification, prediction of asthma severity and prognosis, and response to treatment. Novel advances in the area of personalized medicine regarding disease phenotyping and endotyping, encompass the development and application of reliable biomarkers, accurately quantified using robust and reproducible methods. The availability of powerful omics technologies, together with integrated and network-based genome data analysis, and microbiota changes quantified in serum, body fluids and exhaled air, will lead to a better classification of distinct phenotypes or endotypes. Herein, in this review we discuss on currently used and novel biomarkers for the diagnosis and treatment of asthma.

Integration of Genomic Risk Scores to Improve the Prediction of Childhood Asthma Diagnosis

Genome-wide and epigenome-wide association studies have identified genetic variants and differentially methylated nucleotides associated with childhood asthma. Incorporation of such genomic data may improve performance of childhood asthma prediction models which use phenotypic and environmental data. Using genome-wide genotype and methylation data at birth from the Isle of Wight Birth Cohort (n = 1456), a polygenic risk score (PRS), and newborn (nMRS) and childhood (cMRS) methylation risk scores, were developed to predict childhood asthma diagnosis. Each risk score was integrated with two previously published childhood asthma prediction models (CAPE and CAPP) and were validated in the Manchester Asthma and Allergy Study. Individually, the genomic risk scores demonstrated modest-to-moderate discriminative performance (area under the receiver operating characteristic curve, AUC: PRS = 0.64, nMRS = 0.55, cMRS = 0.54), and their integration only marginally improved the performance of the CAPE (AUC: 0.75 vs. 0.71) and CAPP models (AUC: 0.84 vs. 0.82). The limited predictive performance of each genomic risk score individually and their inability to substantially improve upon the performance of the CAPE and CAPP models suggests that genetic and epigenetic predictors of the broad phenotype of asthma are unlikely to have clinical utility. Hence, further studies predicting specific asthma endotypes are warranted.

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.

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.

Advances and highlights in biomarkers of allergic diseases

During the past years, there has been a global outbreak of allergic diseases, presenting a considerable medical and socioeconomical burden. A large fraction of allergic diseases is characterized by a type 2 immune response involving Th2 cells, type 2 innate lymphoid cells, eosinophils, mast cells, and M2 macrophages. Biomarkers are valuable parameters for precision medicine as they provide information on the disease endotypes, clusters, precision diagnoses, identification of therapeutic targets, and monitoring of treatment efficacies. The availability of powerful omics technologies, together with integrated data analysis and network‐based approaches can help the identification of clinically useful biomarkers. These biomarkers need to be accurately quantified using robust and reproducible methods, such as reliable and point‐of‐care systems. Ideally, samples should be collected using quick, cost‐efficient and noninvasive methods. In recent years, a plethora of research has been directed toward finding novel biomarkers of allergic diseases. Promising biomarkers of type 2 allergic diseases include sputum eosinophils, serum periostin and exhaled nitric oxide. Several other biomarkers, such as pro‐inflammatory mediators, miRNAs, eicosanoid molecules, epithelial barrier integrity, and microbiota changes are useful for diagnosis and monitoring of allergic diseases and can be quantified in serum, body fluids and exhaled air. Herein, we review recent studies on biomarkers for the diagnosis and treatment of asthma, chronic urticaria, atopic dermatitis, allergic rhinitis, chronic rhinosinusitis, food allergies, anaphylaxis, drug hypersensitivity and allergen immunotherapy. In addition, we discuss COVID‐19 and allergic diseases within the perspective of biomarkers and recommendations on the management of allergic and asthmatic patients during the COVID‐19 pandemic.

Severe acute asthma at the pediatric intensive care unit: can we link the clinical phenotypes to immunological endotypes?

INTRODUCTION

The clinical phenotype of severe acute asthma at the pediatric intensive care unit (PICU) is highly heterogeneous. However, current treatment is still based on a 'one-size-fits-all approach'.

AREAS COVERED

We aim to give a comprehensive description of the clinical characteristics of pediatric patients with severe acute asthma admitted to the PICU and available immunological biomarkers, providing the first steps toward precision medicine for this patient population. A literature search was performed using PubMed for relevant studies on severe acute (pediatric) asthma.

EXPERT OPINION

Omics technologies should be used to investigate the relationship between cellular molecules and pathways, and their clinical phenotypes. Inflammatory phenotypes might guide bedside decisions regarding the use of corticosteroids, neutrophil modifiers and/or type of beta-agonist. A next step toward precision medicine should be inclusion of these patients in clinical trials on biologics.

Metabolomics, Microbiota, and In Vivo and In Vitro Biomarkers in Type 2 Severe Asthma: A Perspective Review

Precision medicine refers to the tailoring of therapeutic strategies to the individual characteristics of each patient; thus, it could be a new approach for the management of severe asthma that considers individual variability in genes, environmental exposure, and lifestyle. Precision medicine would also assist physicians in choosing the right treatment, the best timing of administration, consequently trying to maximize drug efficacy, and, possibly, reducing adverse events. Metabolomics is the systematic study of low molecular weight (bio)chemicals in a given biological system and offers a powerful approach to biomarker discovery and elucidating disease mechanisms. In this point of view, metabolomics could play a key role in targeting precision medicine.

Metabolomics, Microbiota, and In Vivo and In Vitro Biomarkers in Type 2 Severe Asthma: A Perspective Review

Precision medicine refers to the tailoring of therapeutic strategies to the individual characteristics of each patient; thus, it could be a new approach for the management of severe asthma that considers individual variability in genes, environmental exposure, and lifestyle. Precision medicine would also assist physicians in choosing the right treatment, the best timing of administration, consequently trying to maximize drug efficacy, and, possibly, reducing adverse events. Metabolomics is the systematic study of low molecular weight (bio)chemicals in a given biological system and offers a powerful approach to biomarker discovery and elucidating disease mechanisms. In this point of view, metabolomics could play a key role in targeting precision medicine.

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.

Differences and similarities between the upper and lower airway: focusing on innate immunity

The nose is the first respiratory barrier to external pathogens, allergens, pollutants, or cigarette smoke, and vigorous immune responses are triggered when external pathogens come in contact with the nasal epithelium. The mucosal epithelial cells of the nose are essential to the innate immune response against external pathogens and transmit signals that modulate the adaptive immune response. The upper and lower airways share many physiological and immunological features, but there are also numerous differences. It is crucial to understand these differences and their contribution to pathophysiology in order to optimize treatments for inflammatory diseases of the respiratory tract. This review summarizes important differences in the embryological development, histological features, microbiota, immune responses, and cellular subtypes of mucosal epithelial cells of the nose and lungs.

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.

Childhood asthma in the new omics era: challenges and perspectives

Purpose of review

Childhood asthma is a heterogeneous inflammatory disease comprising different phenotypes and endotypes and, particularly in its severe forms, has a large impact on the quality-of-life of patients and caregivers. The application of advanced omics technologies provides useful insights into underlying asthma endotypes and may provide potential clinical biomarkers to guide treatment and move towards a precision medicine approach.

Recent findings

The current article addresses how novel omics approaches have shaped our current understanding of childhood asthma and highlights recent findings from (pharmaco)genomics, epigenomics, transcriptomics, and metabolomics studies on childhood asthma and their potential clinical implications to guide treatment in severe asthmatics.

Summary

Until now, omics studies have largely expanded our view on asthma heterogeneity, helped understand cellular processes underlying asthma, and brought us closer towards identifying (bio)markers that will allow the prediction of treatment responsiveness and disease progression. There is a clinical need for biomarkers that will guide treatment at the individual level, particularly in the field of biologicals. The integration of multiomics data together with clinical data could be the next promising step towards development individual risk prediction models to guide treatment. However, this requires large-scale collaboration in a multidisciplinary setting.

Guided extraction of genome-scale metabolic models for the integration and analysis of omics data

Omics data can be integrated into a reference model using various model extraction methods (MEMs) to yield context-specific genome-scale metabolic models (GEMs). How to chose the appropriate MEM, thresholding rule and threshold remains a challenge. We integrated mouse transcriptomic data from a Cyp51 knockout mice diet experiment (GSE58271) using five MEMs (GIMME, iMAT, FASTCORE, INIT an tINIT) in a combination with a recently published mouse GEM iMM1865. Except for INIT and tINIT, the size of extracted models varied with the MEM used (t-test: p-value < 0.001). The Jaccard index of iMAT models ranged from 0.27 to 1.0. Out of the three factors under study in the experiment (diet, gender and genotype), gender explained most of the variability ( > 90%) in PC1 for FASTCORE. In iMAT, each of the three factors explained less than 40% of the variability within PC1, PC2 and PC3. Among all the MEMs, FASTCORE captured the most of the true variability in the data by clustering samples by gender. Our results show that for the efficient use of MEMs in the context of omics data integration and analysis, one should apply various MEMs, thresholding rules, and thresholding values to select the MEM and its configuration that best captures the true variability in the data. This selection can be guided by the methodology as proposed and used in this paper. Moreover, we describe certain approaches that can be used to analyse the results obtained with the selected MEM and to put these results in a biological context.

Biomarkers for diagnosis and prediction of therapy responses in allergic diseases and asthma

Modern health care requires a proactive and individualized response to diseases, combining precision diagnosis and personalized treatment. Accordingly, the approach to patients with allergic diseases encompasses novel developments in the area of personalized medicine, disease phenotyping and endotyping, and the development and application of reliable biomarkers. A detailed clinical history and physical examination followed by the detection of IgE immunoreactivity against specific allergens still represents the state of the art. However, nowadays, further emphasis focuses on the optimization of diagnostic and therapeutic standards and a large number of studies have been investigating the biomarkers of allergic diseases, including asthma, atopic dermatitis, allergic rhinitis, food allergy, urticaria and anaphylaxis. Various biomarkers have been developed by omics technologies, some of which lead to a better classification of distinct phenotypes or endotypes. The introduction of biologicals to clinical practice increases the need for biomarkers for patient selection, prediction of outcomes and monitoring, to allow for an adequate choice of the duration of these costly and long‐lasting therapies. Escalating healthcare costs together with questions about the efficacy of the current management of allergic diseases require further development of a biomarker‐driven approach. Here, we review biomarkers in diagnosis and treatment of asthma, atopic dermatitis, allergic rhinitis, viral infections, chronic rhinosinusitis, food allergy, drug hypersensitivity and allergen immunotherapy with a special emphasis on specific IgE, the microbiome and the epithelial barrier. In addition, EAACI guidelines on biologicals are discussed within the perspective of biomarkers.

Advances and recent developments in asthma in 2020

In this review, we discuss recent publications on asthma and review the studies that have reported on the different aspects of the prevalence, risk factors and prevention, mechanisms, diagnosis, and treatment of asthma. Many risk and protective factors and molecular mechanisms are involved in the development of asthma. Emerging concepts and challenges in implementing the exposome paradigm and its application in allergic diseases and asthma are reviewed, including genetic and epigenetic factors, microbial dysbiosis, and environmental exposure, particularly to indoor and outdoor substances. The most relevant experimental studies further advancing the understanding of molecular and immune mechanisms with potential new targets for the development of therapeutics are discussed. A reliable diagnosis of asthma, disease endotyping, and monitoring its severity are of great importance in the management of asthma. Correct evaluation and management of asthma comorbidity/multimorbidity, including interaction with asthma phenotypes and its value for the precision medicine approach and validation of predictive biomarkers, are further detailed. Novel approaches and strategies in asthma treatment linked to mechanisms and endotypes of asthma, particularly biologicals, are critically appraised. Finally, due to the recent pandemics and its impact on patient management, we discuss the challenges, relationships, and molecular mechanisms between asthma, allergies, SARS-CoV-2, and COVID-19.

Progress in understanding hypersensitivity reactions to nonsteroidal anti-inflammatory drugs

Nonsteroidal anti-inflammatory drugs (NSAIDs), the medications most commonly used for treating pain and inflammation, are the main triggers of drug hypersensitivity reactions. The latest classification of NSAIDs hypersensitivity by the European Academy of Allergy and Clinical Immunology (EAACI) differentiates between cross-hypersensitivity reactions (CRs), associated with COX-1 inhibition, and selective reactions, associated with immunological mechanisms. Three phenotypes fill into the first group: NSAIDs-exacerbated respiratory disease, NSAIDs-exacerbated cutaneous disease and NSAIDs-induced urticaria/angioedema. Two phenotypes fill into the second one: single-NSAID-induced urticaria/angioedema/anaphylaxis and single-NSAID-induced delayed reactions. Diagnosis of NSAIDs hypersensitivity is hampered by different factors, including the lack of validated in vitro biomarkers and the uselessness of skin tests. The advances achieved over recent years recommend a re-evaluation of the EAACI classification, as it does not consider other phenotypes such as blended reactions (coexistence of cutaneous and respiratory symptoms) or food-dependent NSAID-induced anaphylaxis. In addition, it does not regard the natural evolution of phenotypes and their potential interconversion, the development of tolerance over time or the role of atopy. Here, we address these topics. A state of the art on the underlying mechanisms and on the approaches for biomarkers discovery is also provided, including genetic studies and available information on transcriptomics and metabolomics.

Lung functional development and asthma trajectories

Early life environmental risk factors are associated with chronic respiratory morbidity in child- and adulthood. A possible mechanism for this sustained effect is their influence on early life lung functional growth and development, a susceptible phase of rapid lung growth with increased plasticity. We summarize evidence of hereditary and environmental ante-, peri-, and early postnatal factors on lung functional development, such as air pollution, tobacco exposure, nutrition, intrauterine growth retardation, prematurity, early life infections, microbiome, and allergies and their effect on lung functional trajectories. While some of the factors (e.g., prematurity) directly impair lung growth, the influence of many environmental factors is mediated through inflammatory processes (e.g., recurrent infections or oxidative stress). The timing and nature of these influences and their impact result in degrees of impaired maximal lung functional capacity in early adulthood; and they potentially impact future long-term respiratory morbidity such as chronic asthma or chronic obstructive airway disease (COPD). We discuss possibilities to prevent or modify such early abnormal lung functional growth trajectories and the need for future studies and prevention programs.

Omics for the future in asthma

Asthma is a common, complex, multifaceted disease. It comprises multiple phenotypes, which might benefit from treatment with different types of innovative targeted therapies. Refining these phenotypes and understanding their underlying biological structure would help to apply precision medicine approaches. Using different omics methods, such as (epi)genomics, transcriptomics, proteomics, metabolomics, microbiomics, and exposomics, allowed to view and investigate asthma from diverse angles. Technological advancement led to a large increase in the application of omics studies in the asthma field. Although the use of omics technologies has reduced the gap between bench to bedside, several design and methodological challenges still need to be tackled before omics can be applied in asthma patient care. Collaborating under a centralized harmonized work frame (such as in consortia, under consistent methodologies) could help worldwide research teams to tackle these challenges. In this review, we discuss the transition of single biomarker research to multi-omics studies. In addition, we deliberate challenges such as the lack of standardization of sampling and analytical methodologies and validation of findings, which comes in between omics and personalized patient care. The future of omics in asthma is encouraging but not completely clear with some unanswered questions, which have not been adequately addressed before. Therefore, we highlight these questions and emphasize on the importance of fulfilling them.

The current state of omics technologies in the clinical management of asthma and allergic diseases

OBJECTIVE

To review the state of omics science specific to asthma and allergic diseases and discuss the current and potential applicability of omics in clinical disease prediction, treatment, and management.

DATA SOURCES

Studies and reviews focused on the use of omics technologies in asthma and allergic disease research and clinical management were identified using PubMed.

STUDY SELECTIONS

Publications were included based on relevance, with emphasis placed on the most recent findings.

RESULTS

Omics-based research is increasingly being used to differentiate asthma and allergic disease subtypes, identify biomarkers and pathological mediators, predict patient responsiveness to specific therapies, and monitor disease control. Although most studies have focused on genomics and transcriptomics approaches, increasing attention is being placed on omics technologies that assess the effect of environmental exposures on disease initiation and progression. Studies using omics data to identify biological targets and pathways involved in asthma and allergic disease pathogenesis have primarily focused on a specific omics subtype, providing only a partial view of the disease process.

CONCLUSION

Although omics technologies have advanced our understanding of the molecular mechanisms underlying asthma and allergic disease pathology, omics testing for these diseases are not standard of care at this point. Several important factors need to be addressed before these technologies can be used effectively in clinical practice. Use of clinical decision support systems and integration of these systems within electronic medical records will become increasingly important as omics technologies become more widely used in the clinical setting.