The use of pharmacogenomics, epigenomics, and transcriptomics to improve childhood asthma management: Where do we stand?

A Wolf in Sheep's Clothing: Idealisations and the aims of polygenic scores

Research in pharmacogenomics and precision medicine has recently introduced the concept of Polygenic Scores (PGSs), namely, indexes that aggregate the effects that many genetic variants are predicted to have on individual disease risk. The popularity of PGSs is increasing rapidly, but surprisingly little attention has been paid to the idealisations they make about phenotypic development. Indeed, PGSs rely on quantitative genetics models and methods, which involve considerable theoretical assumptions that have been questioned on various grounds. This comes with epistemological and ethical concerns about the use of PGSs in clinical decision-making. In this paper, I investigate to what extent idealisations in genetics models can impact the data gathering and clinical interpretation of genomics findings, particularly the calculation and predictive accuracy of PGSs. Although idealisations are considered ineliminable components of scientific models, they may be legitimate or not depending on the epistemic aims of a model. I thus analyse how various idealisations have been introduced in classical models and progressively readapted throughout the history of genetic theorising. Notably, this process involved important changes in the epistemic purpose of such idealisations, which raises the question of whether they are legitimate in the context of contemporary genomics.

Severe Asthma and Biological Therapies: Now and the Future

Recognition of phenotypic variability in pediatric asthma allows for a more personalized therapeutic approach. Knowledge of the underlying pathophysiological and molecular mechanisms (endotypes) of corresponding biomarkers and new treatments enables this strategy to progress. Biologic therapies for children with severe asthma are becoming more relevant in this sense. The T2 phenotype is the most prevalent in childhood and adolescence, and non-T2 phenotypes are usually rare. This document aims to review the mechanism of action, efficacy, and potential predictive and monitoring biomarkers of biological drugs, focusing on the pediatric population. The drugs currently available are omalizumab, mepolizumab, benralizumab, dupilumab, and 1ezepelumab, with some differences in administrative approval prescription criteria between the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA). Previously, we described the characteristics of severe asthma in children and its diagnostic and therapeutic management.

Application of Asthma Prediction Tools in a Cohort of Infants with Severe Bronchiolitis

Background: Severe bronchiolitis is a strong childhood asthma risk factor. Early and accurate asthma prediction is key. We applied the Asthma Predictive Index (API), the modified Asthma Predictive Index (mAPI), and the Pediatric Asthma Risk Score (PARS) in a cohort of high-risk infants to predict asthma at age 6 years. Methods: We conducted a 17-center cohort of infants (age <1 year) hospitalized with severe bronchiolitis during 2011-2014. We used only infancy data to predict asthma at age 6 years. Results: The prevalence of parent-reported asthma at age 6 years was 328/880 (37%). The prevalences of a positive index/score for stringent and loose API, mAPI, and PARS were 21%, 51%, 11%, and 34%, respectively. Area under the receiver operating characteristic curves [95% confidence interval (CI)] ranged from 0.57 (95% CI 0.55-0.60) for mAPI to 0.66 (95% CI 0.63-0.70) for PARS. Conclusions: An asthma prediction tool for high-risk infants is needed to identify those who would benefit most from asthma prevention interventions.

Pharmacogenetics of childhood uncontrolled asthma

INTRODUCTION

Asthma is a heterogeneous, multifactorial disease with multiple genetic and environmental risk factors playing a role in pathogenesis and therapeutic response. Understanding of pharmacogenetics can help with matching individualized treatments to specific genotypes of asthma to improve therapeutic outcomes especially in uncontrolled or severe asthma.

AREAS COVERED

In this review, we outline novel information about biology, pathways, and mechanisms related to interindividual variability in drug response (corticosteroids, bronchodilators, leukotriene modifiers, and biologics) for childhood asthma. We discuss candidate gene, genome-wide association studies and newer omics studies including epigenomics, transcriptomics, proteomics, and metabolomics as well as integrative genomics and systems biology methods related to childhood asthma. The articles were obtained after a series of searches, last updated November 2022, using database PubMed/CINAHL DB.

EXPERT OPINION

Implementation of pharmacogenetic algorithms can improve therapeutic targeting in children with asthma, particularly with severe or uncontrolled asthma who typically have challenges in clinical management and carry considerable financial burden. Future studies focusing on potential biomarkers both clinical and pharmacogenetic can help formulate a prognostic test for asthma treatment response that would represent true bench to bedside clinical implementation.

Medication use in uncontrolled pediatric asthma: Results from the SysPharmPediA study

BACKGROUND

Uncontrolled pediatric asthma has a large impact on patients and their caregivers. More insight into determinants of uncontrolled asthma is needed. We aim to compare treatment regimens, inhaler techniques, medication adherence and other characteristics of children with controlled and uncontrolled asthma in the: Systems Pharmacology approach to uncontrolled Paediatric Asthma (SysPharmPediA) study.

MATERIAL AND METHODS

145 children with moderate to severe doctor-diagnosed asthma (91 uncontrolled and 54 controlled) aged 6-17 years were enrolled in this multicountry, (Germany, Slovenia, Spain, and the Netherlands) observational, case-control study. The definition of uncontrolled asthma was based on asthma symptoms and/or exacerbations in the past year. Patient-reported adherence and clinician-reported medication use were assessed, as well as lung function and inhalation technique. A logistic regression model was fitted to assess determinants of uncontrolled pediatric asthma.

RESULTS

Children in higher asthma treatment steps had a higher risk of uncontrolled asthma (OR (95%CI): 3.30 (1.56-7.19)). The risk of uncontrolled asthma was associated with a larger change in FEV₁% predicted post and pre-salbutamol (OR (95%CI): 1.08 (1.02-1.15)). Adherence and inhaler techniques were not associated with risk of uncontrolled asthma in this population.

CONCLUSION

This study showed that children with uncontrolled moderate-to-severe asthma were treated in higher treatment steps compared to their controlled peers, but still showed a higher reversibility response to salbutamol. Self-reported adherence and inhaler technique scores did not differ between controlled and uncontrolled asthmatic children. Other determinants, such as environmental factors and differences in biological profiles, may influence the risk of uncontrolled asthma in this moderate to severe asthmatic population.

Pharmacogenomics and asthma treatment: acceptability to children, families and healthcare professionals

BACKGROUND

Evidence supporting personalised treatment for asthma based on an individual's genetics is mounting. The views of children and young people (CYP), parents and healthcare professionals (HCPs) about this evolution of clinical care are not known.

METHODS

A pilot prospective questionnaire-based study was undertaken of CYP with asthma, their parents and HCPs at a secondary/tertiary children's hospital in the UK.

RESULTS

Fifty-nine questionnaires were distributed and 50 returned (response rate 84.7%), comprising 26 CYP (10 were 5-11 years, 11 were 12-15 years and 5 were 16-18 years old), 13 parents and 11 HCPs. For all types of data, personal information was ranked as the 'most important' (n=19, 47.5%) and 'most private' (n=16, 40%), but with considerable variation across groups. Within health data, allergies were rated as 'most important' (n=12, 30.8%), and mental health records the 'most private' (n=21, 53.8%), again with variation across groups. A 'personalised genetic asthma plan' was acceptable to the majority overall (n=40, 80.0%). With regard to sharing CYP's genetic data, 23 (46%) of participants were happy for unconditional sharing between HCPs, and 23 (46%) agreed to sharing solely in relation to the CYP's asthma management. Forty-two (84.0%) of participants felt CYP should be informed about genetic data being shared, and the majority felt this should commence by 12 years of age.

CONCLUSION

The use of genetic information to guide management of asthma in CYP is largely acceptable to CYP, parents/guardians and HCPs. However, there are key differences between the opinions of CYP, parents and HCPs.

LTA4H rs2660845 association with montelukast response in early and late-onset asthma

Leukotrienes play a central pathophysiological role in both paediatric and adult asthma. However, 35% to 78% of asthmatics do not respond to leukotriene inhibitors. In this study we tested the role of the LTA4H regulatory variant rs2660845 and age of asthma onset in response to montelukast in ethnically diverse populations. We identified and genotyped 3,594 asthma patients treated with montelukast (2,514 late-onset and 1,080 early-onset) from seven cohorts (UKBiobank, GoSHARE, BREATHE, Tayside RCT, PAGES, GALA II and SAGE). Individuals under montelukast treatment experiencing at least one exacerbation in a 12-month period were compared against individuals with no exacerbation, using logistic regression for each cohort and meta-analysis. While no significant association was found with European late-onset subjects, a meta-analysis of 523 early-onset individuals from European ancestry demonstrated the odds of experiencing asthma exacerbations by carriers of at least one G allele, despite montelukast treatment, were increased (odds-ratio = 2.92, 95%confidence interval (CI): 1.04–8.18, I2 = 62%, p = 0.0412) compared to those in the AA group. When meta-analysing with other ethnic groups, no significant increased risk of asthma exacerbations was found (OR = 1.60, 95% CI: 0.61–4.19, I2 = 85%, p = 0.342). Our study demonstrates that genetic variation in LTA4H, together with timing of asthma onset, may contribute to variability in montelukast response. European individuals with early-onset (≤18y) carrying at least one copy of rs2660845 have increased odd of exacerbation under montelukast treatment, presumably due to the up-regulation of LTA4H activity. These findings support a precision medicine approach for the treatment of asthma with montelukast.

Pharmacogenomic associations of adverse drug reactions in asthma: systematic review and research prioritisation

A systematic review of pharmacogenomic studies capturing adverse drug reactions (ADRs) related to asthma medications was undertaken, and a survey of Pharmacogenomics in Childhood Asthma (PiCA) consortia members was conducted. Studies were eligible if genetic polymorphisms were compared with suspected ADR(s) in a patient with asthma, as either a primary or secondary outcome. Five studies met the inclusion criteria. The ADRs and polymorphisms identified were change in lung function tests (rs1042713), adrenal suppression (rs591118), and decreased bone mineral density (rs6461639) and accretion (rs9896933, rs2074439). Two of these polymorphisms were replicated within the paper, but none had external replication. Priorities from PiCA consortia members (representing 15 institution in eight countries) for future studies were tachycardia (SABA/LABA), adrenal suppression/crisis and growth suppression (corticosteroids), sleep/behaviour disturbances (leukotriene receptor antagonists), and nausea and vomiting (theophylline). Future pharmacogenomic studies in asthma should collect relevant ADR data as well as markers of efficacy.

Childhood asthma heterogeneity at the era of precision medicine: Modulating the immune response or the microbiota for the management of asthma attack

Exacerbations are a main characteristic of asthma. In childhood, the risk is increasing with severity. Exacerbations are a strong phenotypic marker, particularly of severe and therapy-resistant asthma. These early-life events may influence the evolution and be involved in lung function decline.

In children, asthma attacks are facilitated by exposure to allergens and pollutants, but are mainly triggered by microbial agents. Multiple studies have assessed immune responses to viruses, and to a lesser extend bacteria, during asthma exacerbation. Research has identified impairment of innate immune responses in children, related to altered pathogen recognition, interferon release, or anti-viral response. Influence of this host-microbiota dialog on the adaptive immune response may be crucial, leading to the development of biased T helper (Th)2 inflammation. These dynamic interactions may impact the presentations of asthma attacks, and have long-term consequences.

The aim of this review is to synthesize studies exploring immune mechanisms impairment against viruses and bacteria promoting asthma attacks in children. The potential influence of the nature of infectious agents and/or preexisting microbiota on the development of exacerbation is also addressed. We then discuss our understanding of how these diverse host-microbiota interactions in children may account for the heterogeneity of endotypes and clinical presentations. Finally, improving the knowledge of the pathophysiological processes induced by infections has led to offer new opportunities for the development of preventive or curative therapeutics for acute asthma. A better definition of asthma endotypes associated with precision medicine might lead to substantial progress in the management of severe childhood asthma.

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

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

Precision Medicine in Childhood Asthma: Omic Studies of Treatment Response

Asthma is a heterogeneous and multifactorial respiratory disease with an important impact on childhood. Difficult-to-treat asthma is not uncommon among children, and it causes a high burden to the patient, caregivers, and society. This review aims to summarize the recent findings on pediatric asthma treatment response revealed by different omic approaches conducted in 2018–2019. A total of 13 studies were performed during this period to assess the role of genomics, epigenomics, transcriptomics, metabolomics, and the microbiome in the response to short-acting beta agonists, inhaled corticosteroids, and leukotriene receptor antagonists. These studies have identified novel associations of genetic markers, epigenetic modifications, metabolites, bacteria, and molecular mechanisms involved in asthma treatment response. This knowledge will allow us establishing molecular biomarkers that could be integrated with clinical information to improve the management of children with asthma.

Pharmacogenetics of Pediatric Asthma: Current Perspectives

Asthma is a chronic respiratory disease that affects 339 million people worldwide and has a considerable impact on the pediatric population. Asthma symptoms can be controlled by pharmacological treatment. However, some patients do not respond to therapy and continue suffering from symptoms, which impair the quality of life of patients and limit their daily activity. Genetic variation has been shown to have a role in treatment response. The aim of this review is to update the main findings described in pharmacogenetic studies of pediatric asthma published from January 1, 2018 to December 31, 2019. During this period, the response to short-acting beta-agonists and inhaled corticosteroids in childhood asthma has been evaluated by eleven candidate-gene studies, one meta-analysis of a candidate gene, and six pharmacogenomic studies. The findings have allowed validating the association of genes previously related to asthma treatment response (ADRB2, GSDMB, FCER2, VEGFA, SPAT2SL, ASB3, and COL2A1), and identifying novel associations (PRKG1, DNAH5, IL1RL1, CRISPLD2, MMP9, APOBEC3B-APOBEC3C, EDDM3B, and BBS9). However, some results are not consistent across studies, highlighting the need to conduct larger studies in diverse populations with more homogeneous definitions of treatment response. Once stronger evidence was established, genetic variants will have the potential to be applied in clinical practice as biomarkers of treatment response enhancing asthma management and improving the quality of life of asthma patients.

Recent findings in the genetics and epigenetics of asthma and allergy

In asthma and allergy genetics, a trend towards a few main topics developed over the last 2 years. First, a number of studies have been published recently which focus on overlapping and/or very specific phenotypes: within the allergy spectrum but also reaching beyond, looking for common genetic traits shared between different diseases or disease entities. Secondly, an urgently needed focus has been put on asthma and allergy genetics in populations genetically different from European ancestry. This acknowledges that the majority of new asthma patients today are not white and asthma is a truly worldwide disease. In epigenetics, recent years have seen several large-scale epigenome-wide association studies (EWAS) being published and a further focus was on the interaction between the environment and epigenetic signatures. And finally, the major trends in current asthma and allergy genetics and epigenetics comes from the field of pharmacogenetics, where it is necessary to understand the susceptibility for and mechanisms of current asthma and allergy therapies while at the same time, we need to have scientific answers to the recent availability of novel drugs that hold the promise for a more individualized therapy.

Systems biology and big data in asthma and allergy: recent discoveries and emerging challenges

Asthma is a common condition caused by immune and respiratory dysfunction, and it is often linked to allergy. A systems perspective may prove helpful in unravelling the complexity of asthma and allergy. Our aim is to give an overview of systems biology approaches used in allergy and asthma research. Specifically, we describe recent "omic"-level findings, and examine how these findings have been systematically integrated to generate further insight.Current research suggests that allergy is driven by genetic and epigenetic factors, in concert with environmental factors such as microbiome and diet, leading to early-life disturbance in immunological development and disruption of balance within key immuno-inflammatory pathways. Variation in inherited susceptibility and exposures causes heterogeneity in manifestations of asthma and other allergic diseases. Machine learning approaches are being used to explore this heterogeneity, and to probe the pathophysiological patterns or "endotypes" that correlate with subphenotypes of asthma and allergy. Mathematical models are being built based on genomic, transcriptomic and proteomic data to predict or discriminate disease phenotypes, and to describe the biomolecular networks behind asthma.The use of systems biology in allergy and asthma research is rapidly growing, and has so far yielded fruitful results. However, the scale and multidisciplinary nature of this research means that it is accompanied by new challenges. Ultimately, it is hoped that systems medicine, with its integration of omics data into clinical practice, can pave the way to more precise, personalised and effective management of asthma.

Childhood Asthma: Advances Using Machine Learning and Mechanistic Studies

A paradigm shift brought by the recognition that childhood asthma is an aggregated diagnosis that comprises several different endotypes underpinned by different pathophysiology, coupled with advances in understanding potentially important causal mechanisms, offers a real opportunity for a step change to reduce the burden of the disease on individual children, families, and society. Data-driven methodologies facilitate the discovery of "hidden" structures within "big healthcare data" to help generate new hypotheses. These findings can be translated into clinical practice by linking discovered "phenotypes" to specific mechanisms and clinical presentations. Epidemiological studies have provided important clues about mechanistic avenues that should be pursued to identify interventions to prevent the development or alter the natural history of asthma-related diseases. Findings from cohort studies followed by mechanistic studies in humans and in neonatal mouse models provided evidence that environments such as traditional farming may offer protection by modulating innate immune responses and that impaired innate immunity may increase susceptibility. The key question of which component of these exposures can be translated into interventions requires confirmation. Increasing mechanistic evidence is demonstrating that shaping the microbiome in early life may modulate immune function to confer protection. Iterative dialogue and continuous interaction between experts with different but complementary skill sets, including data scientists who generate information about the hidden structures within "big data" assets, and medical professionals, epidemiologists, basic scientists, and geneticists who provide critical clinical and mechanistic insights about the mechanisms underpinning the architecture of the heterogeneity, are keys to delivering mechanism-based stratified treatments and prevention.

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.

Cell-Specific DNA Methylation Signatures in Asthma

Asthma is a complex trait, often associated with atopy. The genetic contribution has been evidenced by familial occurrence. Genome-wide association studies allowed for associating numerous genes with asthma, as well as identifying new loci that have a minor contribution to its phenotype. Considering the role of environmental exposure on asthma development, an increasing amount of literature has been published on epigenetic modifications associated with this pathology and especially on DNA methylation, in an attempt to better understand its missing heritability. These studies have been conducted in different tissues, but mainly in blood or its peripheral mononuclear cells. However, there is growing evidence that epigenetic changes that occur in one cell type cannot be directly translated into another one. In this review, we compare alterations in DNA methylation from different cells of the immune system and of the respiratory tract. The cell types in which data are obtained influences the global status of alteration of DNA methylation in asthmatic individuals compared to control (an increased or a decreased DNA methylation). Given that several genes were cell-type-specific, there is a great need for comparative studies on DNA methylation from different cells, but from the same individuals in order to better understand the role of epigenetics in asthma pathophysiology.

What did we learn from multiple omics studies in asthma?

More than a decade has passed since the finalization of the Human Genome Project. Omics technologies made a huge leap from trendy and very expensive to routinely executed and relatively cheap assays. Simultaneously, we understood that omics is not a panacea for every problem in the area of human health and personalized medicine. Whilst in some areas of research omics showed immediate results, in other fields, including asthma, it only allowed us to identify the incredibly complicated molecular processes. Along with their possibilities, omics technologies also bring many issues connected to sample collection, analyses and interpretation. It is often impossible to separate the intrinsic imperfection of omics from asthma heterogeneity. Still, many insights and directions from applied omics were acquired-presumable phenotypic clusters of patients, plausible biomarkers and potential pathways involved. Omics technologies develop rapidly, bringing improvements also to asthma research. These improvements, together with our growing understanding of asthma subphenotypes and underlying cellular processes, will likely play a role in asthma management strategies.

Toward clinically applicable biomarkers for asthma: An EAACI position paper

Inflammation, structural, and functional abnormalities within the airways are key features of asthma. Although these processes are well documented, their expression varies across the heterogeneous spectrum of asthma. Type 2 inflammatory responses are characterized by increased levels of eosinophils, FeNO, and type 2 cytokines in blood and/or airways. Presently, type 2 asthma is the best-defined endotype, typically found in patients with allergic asthma, but surprisingly also in nonallergic patients with (severe) asthma. The etiology of asthma with non-type 2 inflammation is less clear. During the past decade, targeted therapies, including biologicals and small molecules, have been increasingly integrated into treatment strategies of severe asthma. These treatments block specific inflammatory pathways or single mediators. Single or composite biomarkers help to identify patients who will benefit from these treatments. So far, only a few inflammatory biomarkers have been validated for clinical application. The European Academy of Allergy & Clinical Immunology Task Force on Biomarkers in Asthma was initiated to review different biomarker sampling methods and to investigate clinical applicability of new and existing inflammatory biomarkers (point-of-care) to support diagnosis, targeted treatment, and monitoring of severe asthma. Subsequently, we discuss existing and novel targeted therapies for asthma as well as applicable biomarkers.