Systems biology of asthma and allergic diseases: a multiscale approach

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.

The association of infant urinary adrenal steroids with the risk of childhood asthma development

BACKGROUND

Adrenal steroids play important roles in early-life development. However, our understanding of the effects of perinatal adrenal steroids on the development of childhood asthma is incomplete.

OBJECTIVE

To evaluate the associations between early-life adrenal steroid levels and childhood asthma.

METHODS

Participants included the Infant Susceptibility to Pulmonary Infections and Asthma following Respiratory Syncytial Virus Exposure birth cohort children with untargeted urinary metabolomics data measured during early infancy (n = 264) and nasal immune mediator data measured concurrently at age 2 to 6 months (n = 76). A total of 11 adrenal steroid compounds were identified using untargeted metabolomics and 6 asthma-relevant nasal immune mediators from multiplex assays were a priori selected. Current asthma at ages 5 and 6 years was ascertained using validated questionnaires. Associations were tested using logistic and linear regression with confounders adjustment.

RESULTS

Pregnenetriol disulfate (adjusted odds ratio [aOR] = 0.20, 95% CI = 0.06-0.68) and 3a,21-dihydroxy-5b-pregnane-11,20-dione-21-glucuronide (aOR = 0.34, 95% CI = 0.14-0.75) were inversely associated with childhood asthma at 5 and 6 years after multiple testing adjustment. There was a significant interaction effect of pregnanediol-3-glucuronide by biological sex assigned at birth (aOR = 0.11, 95% CI = 0.02-0.51, for those with female sex) on childhood asthma. Pregnenetriol disulfate was inversely associated with granulocyte-macrophage colony-stimulating factor (β = -0.45, q-value = 0.05). 3a,21-dihydroxy-5b-pregnane-11,20-dione 21-glucuronide was inversely associated with interleukin [IL]-4 (β = -0.29, q-value = 0.02), IL-5 (β = -0.35, q-value = 0.006), IL-13 (β = -0.26, q-value = 0.02), granulocyte-macrophage colony-stimulating factor (β = -0.35, q-value = 0.006), and fibroblast growth factor-β (β = -0.24, q-value = 0.01) after multiple testing adjustment.

CONCLUSION

The inverse association between adrenal steroids downstream of progesterone and 17-hydroxypregnenolone and the odds of childhood asthma and nasopharyngeal type 2 immune biomarkers suggest that increased early-life adrenal steroids may suppress type 2 inflammation and protect against the development of childhood asthma.

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

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

Epigenomic and epigenetic investigations of food allergy

As a potential link between genetic predisposition, environmental exposures, and food allergy outcomes, epigenetics has been a molecular variable of interest in ongoing efforts to understand food allergy mechanisms and outcomes. Here we review population-based investigations of epigenetic loci associated with food allergy, focusing on established clinical food allergy. We first provide an overview of epigenetic mechanisms that have been studied in cohorts with food allergy, predominantly DNA methylation but also microRNA. We then discuss investigations that have implemented epigenome-wide approaches aimed at genome-wide profiling and discovery. Such epigenome-wide studies have collectively identified differentially methylated and differentially regulated loci associated with T cell development, antigen presentation, reaction severity, and causal mediation in food allergy. We then discuss candidate-gene investigations that have honed in on Th1, Th2, T regulatory, and innate genes of a priori interest in food allergy. These studies have highlighted methylation changes in specific candidate genes as associated with T regulatory cell activity as well as differential methylation of Type 1 and Type 2 cytokine genes associated with various food allergies. Intriguingly, epigenetic loci associated with food allergy have also been explored as potential biomarkers for the clinical management of food allergy. We conclude by highlighting several priority directions for advancing population-based epigenomic and epigenetic understandings of food allergy.

Bronchial Asthma, Airway Remodeling and Lung Fibrosis as Successive Steps of One Process

Bronchial asthma is a heterogeneous disease characterized by persistent respiratory system inflammation, airway hyperreactivity, and airflow obstruction. Airway remodeling, defined as changes in airway wall structure such as extensive epithelial damage, airway smooth muscle hypertrophy, collagen deposition, and subepithelial fibrosis, is a key feature of asthma. Lung fibrosis is a common occurrence in the pathogenesis of fatal and long-term asthma, and it is associated with disease severity and resistance to therapy. It can thus be regarded as an irreversible consequence of asthma-induced airway inflammation and remodeling. Asthma heterogeneity presents several diagnostic challenges, particularly in distinguishing between chronic asthma and other pulmonary diseases characterized by disruption of normal lung architecture and functions, such as chronic obstructive pulmonary disease. The search for instruments that can predict the development of irreversible structural changes in the lungs, such as chronic components of airway remodeling and fibrosis, is particularly difficult. To overcome these challenges, significant efforts are being directed toward the discovery and investigation of molecular characteristics and biomarkers capable of distinguishing between different types of asthma as well as between asthma and other pulmonary disorders with similar structural characteristics. The main features of bronchial asthma etiology, pathogenesis, and morphological characteristics as well as asthma-associated airway remodeling and lung fibrosis as successive stages of one process will be discussed in this review. The most common murine models and biomarkers of asthma progression and post-asthmatic fibrosis will also be covered. The molecular mechanisms and key cellular players of the asthmatic process described and systematized in this review are intended to help in the search for new molecular markers and promising therapeutic targets for asthma prediction and therapy.

Basis of preventive and non-pharmacological interventions in asthma

Asthma is one of the most common atopic disorders in all stages of life. Its etiology is likely due to a complex interaction between genetic, environmental, and lifestyle factors. Due to this, different non-pharmacological interventions can be implemented to reduce or alleviate the symptoms caused by this disease. Thus, the present narrative review aimed to analyze the preventive and non-pharmacological interventions such as physical exercise, physiotherapy, nutritional, ergonutritional, and psychological strategies in asthma treatment. To reach these aims, an extensive narrative review was conducted. The databases used were MedLine (PubMed), Cochrane (Wiley), Embase, PsychINFO, and CinAhl. Asthma is an immune-mediated inflammatory condition characterized by increased responsiveness to bronchoconstrictor stimuli. Different factors have been shown to play an important role in the pathogenesis of asthma, however, the treatments used to reduce its incidence are more controversial. Physical activity is focused on the benefits that aerobic training can provide, while physiotherapy interventions recommend breathing exercises to improve the quality of life of patients. Nutritional interventions are targeted on implement diets that prioritize the consumption of fruits and vegetables and supplementation with antioxidants. Psychological interventions have been proposed as an essential non-pharmacological tool to reduce the emotional problems associated with asthma.

Robust, scalable, and informative clustering for diverse biological networks

Clustering molecular data into informative groups is a primary step in extracting robust conclusions from big data. However, due to foundational issues in how they are defined and detected, such clusters are not always reliable, leading to unstable conclusions. We compare popular clustering algorithms across thousands of synthetic and real biological datasets, including a new consensus clustering algorithm-SpeakEasy2: Champagne. These tests identify trends in performance, show no single method is universally optimal, and allow us to examine factors behind variation in performance. Multiple metrics indicate SpeakEasy2 generally provides robust, scalable, and informative clusters for a range of applications.

The SunBEAm birth cohort: Protocol design

Background

Food allergy (FA) and atopic dermatitis (AD) are common conditions that often present in the first year of life. Identification of underlying mechanisms and environmental determinants of FA and AD is essential to develop and implement effective prevention and treatment strategies. Objectives: We sought to describe the design of the Systems Biology of Early Atopy (SunBEAm) birth cohort.

Methods

Funded by the National Institute of Allergy and Infectious Diseases (NIAID) and administered through the Consortium for Food Allergy Research (CoFAR), SunBEAm is a US population-based, multicenter birth cohort that enrolls pregnant mothers, fathers, and their newborns and follows them to 3 years. Questionnaire and biosampling strategies were developed to apply a systems biology approach to identify environmental, immunologic, and multiomic determinants of AD, FA, and other allergic outcomes.

Results

Enrollment is currently underway. On the basis of an estimated FA prevalence of 6%, the enrollment goal is 2500 infants. AD is defined on the basis of questionnaire and assessment, and FA is defined by an algorithm combining history and testing. Although any FA will be recorded, we focus on the diagnosis of egg, milk, and peanut at 5 months, adding wheat, soy, cashew, hazelnut, walnut, codfish, shrimp, and sesame starting at 12 months. Sampling includes blood, hair, stool, dust, water, tape strips, skin swabs, nasal secretions, nasal swabs, saliva, urine, functional aspects of the skin, and maternal breast milk and vaginal swabs.

Conclusions

The SunBEAm birth cohort will provide a rich repository of data and specimens to interrogate mechanisms and determinants of early allergic outcomes, with an emphasis on FA, AD, and systems biology.

Positive rate of wheat allergens in the Chinese allergic population: a systematic review and meta-analysis

In recent years, the prevalence of allergic diseases has increased significantly, causing great concern, and wheat, as one of the top 8 food allergens, is a common allergy trigger. Nevertheless, reliable estimates of the positivity rate of wheat allergens in the allergic population in China are still lacking. The systematic review and meta-analysis aims to evaluate the positive detection rate of wheat allergens in the Chinese allergic population and further provide a reference for the prevention of allergy. CNKI, CQVIP, WAN-FANG DATA, Sino Med, PubMed, Web of Science, Cochrane Library, and Embase databases were retrieved. Related research and case reports about the positive rate of wheat allergen in the Chinese allergic population published from inception to June 30, 2022, were searched, and meta-analysis was performed using Stata software. The pooled positive rate of wheat allergens and 95% confidence interval were calculated by random effect models, and the publication bias was evaluated using Egger's test. A total of 13 articles were included for the final meta-analysis, in which wheat allergen detection methods involved only serum sIgE testing and SPT assessment. The results showed that the wheat allergen positivity detection rate in Chinese allergic patients was 7.30% (95% CI 5.68-8.92%). Subgroup analysis showed that the positivity rate of wheat allergens was influenced by region, but hardly by age and assessment method. The positive rates of wheat allergy in the population with allergic diseases were 2.74% (95% CI 0.90-4.58%) and 11.47% (95% CI 7.08-15.87%) in southern and northern China, respectively. In particular, the positive rates of wheat allergens were greater than 10% in Shaanxi, Henan and Nei Mongol, all of which belong to the northern region. These results suggest that wheat allergens are an important cause of sensitization in allergic populations from northern China, and therefore attention should be paid to early prevention in high-risk populations.

From big data to better patient outcomes

Among medical specialties, laboratory medicine is the largest producer of structured data and must play a crucial role for the efficient and safe implementation of big data and artificial intelligence in healthcare. The area of personalized therapies and precision medicine has now arrived, with huge data sets not only used for experimental and research approaches, but also in the "real world". Analysis of real world data requires development of legal, procedural and technical infrastructure. The integration of all clinical data sets for any given patient is important and necessary in order to develop a patient-centered treatment approach. Data-driven research comes with its own challenges and solutions. The Findability, Accessibility, Interoperability, and Reusability (FAIR) Guiding Principles provide guidelines to make data findable, accessible, interoperable and reusable to the research community. Federated learning, standards and ontologies are useful to improve robustness of artificial intelligence algorithms working on big data and to increase trust in these algorithms. When dealing with big data, the univariate statistical approach changes to multivariate statistical methods significantly shifting the potential of big data. Combining multiple omics gives previously unsuspected information and provides understanding of scientific questions, an approach which is also called the systems biology approach. Big data and artificial intelligence also offer opportunities for laboratories and the In Vitro Diagnostic industry to optimize the productivity of the laboratory, the quality of laboratory results and ultimately patient outcomes, through tools such as predictive maintenance and "moving average" based on the aggregate of patient results.

Advancing Exposomic Research in Prenatal Respiratory Disease Programming

Disease programming reflects interactions between genes and the environment. Unlike the genome, environmental exposures and our response to exposures change over time. Starting in utero, the respiratory system and related processes develop sequentially in a carefully timed cascade, thus effects depend on both exposure dose and timing. A multitude of environmental and microbial exposures influence respiratory disease programming. Effects result from toxin-induced shifts in a host of molecular, cellular, and physiologic states and their interacting systems. Moreover, pregnant women and the developing child are not exposed to a single toxin, but to complex mixtures.

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.

IgE-Mediated food allergy: Current diagnostic modalities and novel biomarkers with robust potential

Food allergy (FA) is a serious public health issue afflicting millions of people globally, with an estimated prevalence ranging from 1-10%. Management of FA is challenging due to overly restrictive diets and the lack of diagnostic approaches with high accuracy and prediction. Although measurement of serum-specific antibodies combined with patient medical history and skin prick test is a useful diagnostic tool, it is still an imprecise predictor of clinical reactivity with a high false-positive rate. The double-blind placebo-controlled food challenge represents the gold standard for FA diagnosis; however, it requires large healthcare and involves the risk of acute onset of allergic reactions. Improvement in our understanding of the molecular mechanism underlying allergic disease pathology, development of omics-based methods, and advances in bioinformatics have boosted the generation of a number of robust diagnostic biomarkers of FA. In this review, we discuss how traditional diagnostic modalities guide appropriate diagnosis and management of FA in clinical practice, as well as uncover the potential of the latest biomarkers for the diagnosis, monitoring, and prediction of FA. We also raise perspectives for precise and targeted medical intervention to fill the gap in the diagnosis of FA.

A roadmap for multi-omics data integration using deep learning

High-throughput next-generation sequencing now makes it possible to generate a vast amount of multi-omics data for various applications. These data have revolutionized biomedical research by providing a more comprehensive understanding of the biological systems and molecular mechanisms of disease development. Recently, deep learning (DL) algorithms have become one of the most promising methods in multi-omics data analysis, due to their predictive performance and capability of capturing nonlinear and hierarchical features. While integrating and translating multi-omics data into useful functional insights remain the biggest bottleneck, there is a clear trend towards incorporating multi-omics analysis in biomedical research to help explain the complex relationships between molecular layers. Multi-omics data have a role to improve prevention, early detection and prediction; monitor progression; interpret patterns and endotyping; and design personalized treatments. In this review, we outline a roadmap of multi-omics integration using DL and offer a practical perspective into the advantages, challenges and barriers to the implementation of DL in multi-omics data.

The airway microbiome and pediatric asthma

PURPOSE OF REVIEW

Asthma is the most common chronic disease of childhood. Investigations of the lower and upper airway microbiomes have significantly progressed over recent years, and their roles in pediatric asthma are becoming increasingly clear.

RECENT FINDINGS

Early studies identified the existence of upper and lower airway microbiomes, including imbalances in both associated with pediatric asthma. The infant airway microbiome may offer predictive value for the development of asthma in later childhood, and it may also be influenced by external factors such as respiratory viral illness. The airway microbiome has also been associated with the clinical course of asthma, including rates of exacerbation and level of control. Advances in -omics sciences have enabled improved identification of the airway microbiome's relationships with host response and function in children with asthma. Investigations are now moving toward the application of the above findings to explore risk modification and treatment options.

SUMMARY

The airway microbiome provides an intriguing window into pediatric asthma, offering insights into asthma diagnosis, clinical course, and perhaps treatment. Further investigation is needed to solidify these associations and translate research findings into clinical practice.

Cytokine antibody array-based analysis of IL-37 treatment effects in asthma

Asthma is driven by group 2 innate lymphoid cells, antigen-specific CD4+ T helper type 2 cells and their cytokines such as interleukin (IL)-4, IL-5, IL-13. IL-37 is decreased in asthma and negatively related to Th2 cytokines and other pro-inflammatory cytokines. Our study showed that IL-37 level in asthmatic peripheral blood mononuclear cells was lower than in healthy. Further, IL-37 was negatively correlated with exhaled nitric oxide, asthma control test score, atopy and rhinitis history in asthmatics. Then an OVA-induced asthma mice model treated with rhIL-37 was established. An antibody array was employed to uncover altered cytokines induced by IL-37 in mice lung tissue. 20 proteins differentially expressed after rhIL-37 treatment and five of them were validated in asthmatic peripheral blood mononuclear cells. Consistent with cytokine antibody array, CCL3, CCL4, CCL5 decreased after IL-37 administration. While CXCL9 and CXCL13 were no change. We concluded that IL-37 reduce asthmatic symptoms by inhibit pro-inflammatory cytokine such as CCL3, CCL4, CCL5.

The applications of eHealth technologies in the management of asthma and allergic diseases

Portable devices, such as smartphones and mobile Internet access have become ubiquitous in the last decades. The term 'eHealth' stands for electronic health. The tools included in the eHealth concept utilize phones, computers and the Internet and related applications to improve the health care industry. Implementation of eHealth technologies has been documented for the management of different chronic diseases, including asthma and allergic conditions. Clinicians and patients have gained opportunity to communicate in new ways, which could be used cost-effectively to improve disease control and quality of life of those affected. Additionally, these innovations bring new opportunities to academic researchers. For example, eHealth has allowed researchers to compile data points that were previously unavailable or difficult to access, and analyse them using novel tools, collectively described as 'big data'. The role of eHealth become more important since early 2020, due to the physical distancing rules and the restrictions on mobility that have been applied worldwide as a response to the coronavirus disease 2019 pandemic. In this review, we summarize the most recent developments in various eHealth platforms and their relevance to the speciality of allergy and immunology, from the point of view of three major stakeholders: clinicians, patients and researchers.

Advances in the Relationships Between Cow's Milk Protein Allergy and Gut Microbiota in Infants

Cow's milk protein allergy (CMPA) is an immune response to cow's milk proteins, which is one of the most common food allergies in infants and young children. It is estimated that 2-3% of infants and young children have CMPA. The diet, gut microbiota, and their interactions are believed to be involved in the alterations of mucosal immune tolerance, which might lead to the development of CMPA and other food allergies. In this review, the potential molecular mechanisms of CMPA, including omics technologies used for analyzing microbiota, impacts of early microbial exposures on CMPA development, and microbiota-host interactions, are summarized. The probiotics, prebiotics, synbiotics, fecal microbiota transplantation, and other modulation strategies for gut microbiota and the potential application of microbiota-based design of diets for the CMPA treatment are also discussed. This review not only summarizes the current studies about the interactions of CMPA with gut microbiota but also gives insights into the possible CMPA treatment strategies by modulating gut microbiota, which might help in improving the life quality of CMPA patients in the future.

Vitamin D Supplementation: Oxidative Stress Modulation in a Mouse Model of Ovalbumin-Induced Acute Asthmatic Airway Inflammation

Asthma oxidative stress disturbances seem to enable supplementary proinflammatory pathways, thus contributing to disease development and severity. The current study analyzed the impact of two types of oral vitamin D (VD) supplementation regimens on the redox balance using a murine model of acute ovalbumin-induced (OVA-induced) asthmatic inflammation. The experimental prevention group received a long-term daily dose of 50 µg/kg (total dose of 1300 µg/kg), whereas the rescue group underwent a short-term daily dose of 100 µg/kg (total dose of 400 µg/kg). The following oxidative stress parameters were analyzed in serum, bronchoalveolar lavage fluid (BALF) and lung tissue homogenate (LTH): total oxidative status, total antioxidant response, oxidative stress index, malondialdehyde and total thiols. Results showed that VD significantly reduced oxidative forces and increased the antioxidant capacity in the serum and LTH of treated mice. There was no statistically significant difference between the two types of VD supplementation. VD also exhibited an anti-inflammatory effect in all treated mice, reducing nitric oxide formation in serum and the expression of nuclear factor kappa B p65 in the lung. In conclusion, VD supplementation seems to exhibit a protective role in oxidative stress processes related to OVA-induced acute airway inflammation.

Evaluation of Sensitivity and Specificity of Interleukins 25 and 33 in Diagnosis of Pediatric Asthma

The roles of interleukin 25 (a member of the interleukin 17 family) and interleukin 33 (a member of the interleukin 1 family) in asthma and airway hyperresponsiveness are yet to be fully understood. The aim of this study was to investigate the roles of IL- 25 and IL- 33 in the diagnosis of pediatric asthma and their association with severity and treatment of the disease. This was a case-control study comprising 74 children with asthma as the patient group and 75 healthy children as the control group. The age of the participants ranged from 1 to 15 years. Levels of IL- 25 and IL- 33 in the serum were measured using ELISA kits. The highest positive predictive values (88.9%) occurred in IL- 25 with sensitivity and specificity of about 97.3% and 88.0% respectively, while the sensitivity and specificity of IL- 33 were about 51.4% and 66.0% respectively, with a positive predictive value of about (60.3%). The present study thus found that IL- 25 had higher diagnostic sensitivity and specificity values than IL- 33 in children with asthma. In addition, both interleukins were found to have a statistical significance regarding treatment of the disease in children.

Basophil activation test: Assay precision and BI 1002494 SYK inhibition in healthy and mild asthmatics

BACKGROUND

Application of basophil activation test (BAT) in clinical trials requires assay validity. Whether assay variability differs between healthy and asthmatic subjects is mostly unknown. This study compares basophil stimulation using blood from healthy and asthmatic subjects with or without inhibition of spleen tyrosine kinase (SYK).

METHODS

Whole blood of healthy and mild asthmatic subjects was stimulated with anti-dinitrophenyl (DNP) IgE/DNP bovine serum albumin and anti-IgE. Basophil activation was detected by CD63 and CD203c expression. CD63 expression levels were compared with serum IgE levels. Three operators repeated experiments with three subjects each from both groups at 3 days to observe assay precision. The effect of the SYK inhibitor BI 1002494 was assessed in BAT for both healthy and asthmatic subjects.

RESULTS

BAT was reproducible in both groups. Acceptance criteria of <25% CV were mostly fulfilled. Stimulation with anti-DNP (p < 0.001, r = -0.80) but not anti-IgE (p = 0.74, r = 0.05) was related to serum IgE with levels > 200 IU/ml limiting anti-DNP stimulation. BI 1002494 IC₅₀ values were 497 nM and 1080 nM in healthy and 287 nM and 683 nM in asthmatics for anti-DNP and anti-IgE stimulation, respectively.

CONCLUSION

BAT, performed with blood from healthy or asthmatic subjects, is a robust test for the measurement of a physiological response in clinical trials. Blood from asthmatic donors with serum IgE > 200 IU/ml is less feasible when using anti-DNP stimulation. SYK inhibition was not affected by disease status.

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

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

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

Next Generation Exome Sequencing of Pediatric Asthma Identifies Rare and Novel Variants in Candidate Genes

Multiple genes have been implicated to have a role in asthma predisposition by association studies. Pediatric patients often manifest a more extensive form of this disease and a particularly severe disease course. It is likely that genetic predisposition could play a more substantial role in this group. This study is aimed at identifying the spectrum of rare and novel variation in known pediatric asthma susceptibility genes using whole exome sequencing analysis in nine individual cases of childhood onset allergic asthma. DNA samples from the nine children with a history of bronchial asthma diagnosis underwent whole exome sequencing on Ion Proton. For each patient, the entire complement of rare variation within strongly associated candidate genes was catalogued. The analysis showed 21 variants in the subjects, 13 had been previously identified, and 8 were novel. Also, among of which, nineteen were nonsynonymous and 2 were nonsense. With regard to the novel variants, the 2 nonsynonymous variants in the PRKG1 gene (PRKG1: p.C519W and PRKG1: p.G520W) were presented in 4 cases, and a nonsynonymous variant in the MAVS gene (MAVS: p.A45V) was identified in 3 cases. The variants we found in this study will enrich the variant spectrum and build up the database in the Saudi population. Novel eight variants were identified in the study which provides more evidence in the genetic susceptibility in asthma among Saudi children, providing a genetic screening map for the molecular genetic determinants of allergic disease in Saudi children, with the goal of reducing the impact of chronic diseases on the health and the economy. We believe that the advanced specified statistical filtration/annotation programs used in this study succeeded to release such results in a preliminary study, exploring the genetic map of that disease in Saudi children.

Advancing Food Allergy Through Omics Sciences

Since the publication of the first draft of the human genome, there has been an explosion of new technologies with increasing power to interrogate the totality of biological molecules (eg, DNA, RNA, proteins, metabolites) and their modifications (eg, DNA methylation, histone modifications). These technologies, collectively called omics, have been widely applied in the last 2 decades to study biological systems to gain deeper insight into mechanisms driving the physiology and pathophysiology of human health and disease. Because of its complex, multifactorial nature, food allergy is especially well suited to be investigated using omics approaches. In this rostrum, we review how omic technologies have been applied to explore diverse aspects of food allergy, including adaptive and innate immune processes in food-allergic responses, the role of the microbiome in food allergy risk, metabolic changes in the gut and blood associated with food allergy, and the identification of biomarkers and potential therapeutic targets for the condition. We discuss the strengths and limitations of the studies performed thus far and the need to adopt systems biology approaches that integrate data from multiple omics to fully leverage the potential of these technologies to advance food allergy research and care.

Role of host genetics and cytokines in Leishmania infection

Cytokines and chemokines are important regulators of innate and specific responses in leishmaniasis, a disease that currently affects 12 million people. We overviewed the current information about influences of genetically engineered mouse models of cytokine and chemokine on leishmaniasis. We found that genetic background of the host, parasite species and sub-strain, as well as experimental design often modify effects of genetically engineered cytokine genes. Next we analyzed genes and QTLs (quantitative trait loci) that control response to Leishmania species in mouse in order to establish relationship between genetic control of cytokine expression and organ pathology. These studies revealed a network-like complexity of the combined effects of the multiple functionally diverse QTLs and their individual specificity. Genetic control of organ pathology and systemic immune response overlap only partially. Some QTLs control both organ pathology and systemic immune response, but the effects of genes and loci with the strongest impact on disease are cytokine-independent, whereas several loci modify cytokines levels in serum without influencing organ pathology. Understanding this genetic control might be important in development of vaccines designed to stimulate certain cytokine spectrum.

Strategic Outlook toward 2030: Japan's research for allergy and immunology - Secondary publication

Strategic Outlook toward 2030: Japan's Research for Allergy and Immunology (Strategy 2030) is the national research strategy based on Japan's Basic Law on Measures Against Allergic Diseases, a first of its kind worldwide. This strategy was established by a multi-disciplinary committee consisting of administrators of the Ministry of Health, Labour and Welfare of Japan, young and senior experts from various research societies and associations, and representatives of patient and public groups. Whereas the issues of transition, integration, and international collaboration have yet to be solved in this research realm in Japan, identification of unmet needs, digitization of information and transparent procedures, and strategic planning for complex problems (a process dubbed MIERUKA by the Toyota Way) are crucial to share and tackle the same vision and goals. The committee developed three specific actions focusing on preemptive treatment, interdisciplinarity and internationality, and life stage. The real success of Strategy 2030 is made by the spontaneous contributions of doctors, dentists, veterinarians, and other medical professionals; basic and clinical research scientists, research supporters, and pharmaceutical/medical device companies; manufacturers of food, healthcare, and home appliances; and patients, their families, and the public. The hope is to establish a stable society in which people can live long, healthy lives, as free as possible from allergic and immunological diseases, at each individual life stage. This article is based on a Japanese review first reported in Arerugi, introduces the developmental process and details of Strategy 2030.

The Hidden Burden of Severe Asthma: From Patient Perspective to New Opportunities for Clinicians

Severe asthma is an important topic in respiratory diseases, due to its high impact on morbidity and mortality as well as on health-care resources. The many challenges that still exist in the management of the most difficult-to-treat forms of the disease, and the acknowledgement of the existence of unexplored areas in the pathophysiological mechanisms and the therapeutic targets represent an opportunity to gather experts in the field with the immediate goals to summarize current understanding about the natural history of severe asthma and to identify gaps in knowledge and research opportunities, with the aim to contribute to improved medical care and health outcomes. This article is a consensus document from the “International Course on Severe Asthma” that took place in Palermo, Italy, on May 10–11, 2019. Emerging topics in severe asthma were addressed and discussed among experts, with special focus on patient’s needs and research opportunities, with the aim to highlight the unanswered questions in the diagnostic process and therapeutic approach.

Gut Microbiome Modulation for Preventing and Treating Pediatric Food Allergies

The increasing prevalence and severity of pediatric food allergies (FA) demands innovative preventive and therapeutic strategies. Emerging evidence suggests a pivotal role for the gut microbiome in modulating susceptibility to FA. Studies have demonstrated that alteration of gut microbiome could precede FA, and that particular microbial community structures early in life could influence also the disease course. The identification of gut microbiome features in pediatric FA patients is driving new prevention and treatment approaches. This review is focused on the potential role of the gut microbiome as a target for FA prevention and treatment.

Machine Learning-Empowered FTIR Spectroscopy Serum Analysis Stratifies Healthy, Allergic, and SIT-Treated Mice and Humans

The unabated global increase of allergic patients leads to an unmet need for rapid and inexpensive tools for the diagnosis of allergies and for monitoring the outcome of allergen-specific immunotherapy (SIT). In this proof-of-concept study, we investigated the potential of Fourier-Transform Infrared (FTIR) spectroscopy, a high-resolution and cost-efficient biophotonic method with high throughput capacities, to detect characteristic alterations in serum samples of healthy, allergic, and SIT-treated mice and humans. To this end, we used experimental models of ovalbumin (OVA)-induced allergic airway inflammation and allergen-specific tolerance induction in BALB/c mice. Serum collected before and at the end of the experiment was subjected to FTIR spectroscopy. As shown by our study, FTIR spectroscopy, combined with deep learning, can discriminate serum from healthy, allergic, and tolerized mice, which correlated with immunological data. Furthermore, to test the suitability of this biophotonic method for clinical diagnostics, serum samples from human patients were analyzed by FTIR spectroscopy. In line with the results from the mouse models, machine learning-assisted FTIR spectroscopy allowed to discriminate sera obtained from healthy, allergic, and SIT-treated humans, thereby demonstrating its potential for rapid diagnosis of allergy and clinical therapeutic monitoring of allergic patients.

Food allergy and the microbiome: Current understandings and future directions

Growing evidence points to an important role for the commensal microbiota in susceptibility to food allergy. Epidemiologic studies demonstrate associations between exposures known to modify the microbiome and risk of food allergy. Direct profiling of the gut microbiome in human cohort studies has demonstrated that individuals with food allergy have distinct gut microbiomes compared to healthy control subjects, and dysbiosis precedes the development of food allergy. Mechanistic studies in mouse models of food allergy have confirmed that the composition of the intestinal microbiota can imprint susceptibility or resistance to food allergy on the host and have identified a unique population of microbially responsive RORγt-positive FOXp3-positive regulatory T cells as critical for the maintenance of tolerance to foods. Armed with this new understanding of the role of the microbiota in food allergy and tolerance, therapeutics aimed at modifying the gastrointestinal microbiota are in development. In this article we review key milestones in the development of our current understanding of how the gastrointestinal microbiota contributes to food allergy and discuss our vision for the future of the field.

Novel Comprehensive Bioinformatics Approaches to Determine the Molecular Genetic Susceptibility Profile of Moderate and Severe Asthma

Background: Asthma is a chronic inflammatory condition linked to hyperresponsiveness in the airways. There is currently no cure available for asthma, and therapy choices are limited. Asthma is the result of the interplay between genes and the environment. The exact molecular genetic mechanism of asthma remains elusive. Aims: The aim of this study is to provide a comprehensive, detailed molecular etiology profile for the molecular factors that regulate the severity of asthma and pathogenicity using integrative bioinformatics tools. Methods: The GSE43696 omnibus gene expression dataset, which contains 50 moderate cases, 38 severe cases, and 20 healthy controls, was used to investigate differentially expressed genes (DEGs), susceptible chromosomal loci, gene networks, pathways, gene ontologies, and protein–protein interactions (PPIs) using an intensive bioinformatics pipeline. Results: The PPI network analysis yielded DEGs that contribute to interactions that differ from moderate-to-severe asthma. The combined interaction scores resulted in higher interactions for the genes STAT3, AGO2, COL1A1, CLCN6, and KSR for moderate asthma and JAK2, INSR, ERBB2, NR3C1, and PTK6 for severe asthma. Enrichment analysis (EA) demonstrated differential enrichment between moderate and severe asthma phenotypes; the ion transport regulation pathway was significantly enhanced in severe asthma phenotypes compared to that in moderate asthma phenotypes and involved PER2, GCR, IRS-2, KCNK7, KCNK6, NOX1, and SCN7A. The most enriched common pathway in both moderate and severe asthma is the development of the glucocorticoid receptor (GR) signaling pathway followed by glucocorticoid-mediated inhibition of proinflammatory and proconstrictory signaling in the airway of smooth muscle cell pathways. Gene sets were shared between severe and moderate asthma at 16 chromosome locations, including 17p13.1, 16p11.2, 17q21.31, 1p36, and 19q13.2, while 60 and 48 chromosomal locations were unique for both moderate and severe asthma, respectively. Phylogenetic analysis for DEGs showed that several genes have been intersected in phases of asthma in the same cluster of genes. This could indicate that several asthma-associated genes have a common ancestor and could be linked to the same biological function or gene family, implying the importance of these genes in the pathogenesis of asthma. Conclusion: New genetic risk factors for the development of moderate-to-severe asthma were identified in this study, and these could provide a better understanding of the molecular pathology of asthma and might provide a platform for the treatment of asthma.

Leveraging -omics for asthma endotyping

Asthma is a highly heterogeneous disease, often manifesting with wheeze, dyspnea, chest tightness, and cough as prominent symptoms. The eliciting factors, natural history, underlying molecular biology, and clinical management of asthma vary highly among affected subjects. Because of this variation, many efforts have gone into subtyping asthma. Endotypes are subtypes of disease based on distinct pathophysiologic mechanisms. Endotypes can be clinically useful because they organize our mechanistic understanding of heterogeneous diseases and can direct treatment toward modalities that are likely to be the most effective. Asthma endotyping can be shaped by clinical features, laboratory parameters, and/or -omics approaches. We discuss the application of -omics approaches, including transcriptomics, epigenomics, microbiomics, metabolomics, and proteomics, to asthma endotyping. -Omics approaches have provided supporting evidence for many existing endotyping paradigms and also suggested novel ways to conceptualize asthma endotypes. Although endotypes based on single -omics approaches are relatively common, their integrated multi-omics application to asthma endotyping has been more limited thus far. We discuss paths forward to integrate multi-omics with clinical features and laboratory parameters to achieve the goal of precise asthma endotypes.

Clinical Efficacy Evaluation of 1-Year Subcutaneous Immunotherapy for Artemisia sieversiana Pollen Allergic Rhinitis by Serum Metabolomics

Subcutaneous immunotherapy is the only treatment that improves the natural progression of allergic rhinitis and maintains long-term outcomes after discontinuation of the drug. Metabolomics is increasingly applied in the study of allergic diseases, including allergic rhinitis. However, little is known about the discovery of metabolites that can evaluate clinical efficacy and possible mechanisms of Artemisia sieversiana pollen subcutaneous immunotherapy. Thirty-three patients with Artemisia sieversiana pollen allergic rhinitis significantly improved after 1-year subcutaneous immunotherapy treatment, while ten patients were ineffective. Pre- and post-treatment serum samples from these patients were analyzed by metabolomics based on the combined detection of liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry. As a result, L-Tyrosine can be a potential biomarker because of its opposite trend in effective patients and ineffective patients. And mechanism of immunotherapy may be closely related to NO and nitric oxide synthase. The discovery of potential biomarkers and metabolic pathways has contributed to the in-depth study of mechanisms of subcutaneous immunotherapy treatment of Artemisia sieversiana pollen allergic rhinitis.

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.

Sensitization to inhaled allergens in asthmatic children in southern Jordan: a cross-sectional study

BACKGROUND

Sensitization to inhaled allergens in children with bronchial asthma significantly affects asthma pathogenesis, severity and persistence into late childhood and adulthood. The present study determined the prevalence of sensitization to inhaled allergens in children with bronchial asthma and wheezing episodes in order to investigate the effect of positive sensitization on the severity and control of asthma symptoms and to screen for other associated allergic conditions.

METHODS

A cross-sectional study was conducted, including children between 6 months and 14 years of age attending the chest clinic of Al-Karak, south of Jordan, between November 2013 and February 2016. Skin prick tests (SPTs) using 11 standardized allergen extracts were conducted in 277 children. The severity of asthma was determined based on the Global Initiative for Asthma (GINA) assessment and the Childhood Asthma Control Test (C-ACT) in addition to the history of use of systemic steroids and hospital admissions within the past 12 months.

RESULTS

Sixty-seven percent of children with bronchial asthma reported sensitization to one or more of the inhaled allergens. The most common allergens were olive pollens (18%), cat fur (13.5%), and Dermatophagoides pteronyssinus (11.9%). There was a significant increase in allergen sensitization with age (p < 0.001). The most common concomitant allergic condition among children was allergic rhinitis (71.5%); however, allergic conjunctivitis was the only allergic condition that correlated with the skin test reactivity (p = 0.01). A family history of bronchial asthma was confirmed in 40.4% of children. Children with positive SPTs had lower ACT scores and reported more frequent use of systemic steroids and admissions to hospital within the past 12 months; however, this effect was not statistically significant (p > 0.05).

CONCLUSIONS

Sensitization to inhaled allergens is highly prevalent in children with asthma and wheezing episodes in southern Jordan and may be correlated with the severity of the disease. Therefore, appropriate measures to recognize and avoid these allergens are highly recommended. Most children in our study suffered from concomitant allergic rhinitis, indicating that an appropriate diagnosis and treatment of allergic rhinitis could significantly improve asthma control and thus the quality of life of these children.

TRIAL REGISTRATION

This study is not a clinical trial.

Evolution of Immune Responses in Food Immunotherapy

Food allergies are a growing public health concern affecting approximately 8% of children and 10% of adults in the United States. Several immunotherapy approaches are under active investigation, including oral immunotherapy, epicutaneous immunotherapy, and sublingual immunotherapy. Each of these approaches uses a similar strategy of administering small, increasing amounts of allergen to the allergic subject. Immunologic studies have described changes in the T-cell compartment, serum and salivary immunoglobulin profile, and mast cell and basophil degranulation status in response to allergens. This review highlights the immunologic changes induced by food allergen-specific immunotherapy and discusses future directions in this field.

Thinking bigger: How early-life environmental exposures shape the gut microbiome and influence the development of asthma and allergic disease

Imbalance, or dysbiosis, of the gut microbiome of infants has been linked to an increased risk of asthma and allergic diseases. Most studies to date have provided a wealth of data showing correlations between early-life risk factors for disease and changes in the structure of the gut microbiome that disrupt normal immunoregulation. These studies have typically focused on one specific risk factor, such as mode of delivery or early-life antibiotic use. Such "micro-level" exposures have a considerable impact on affected individuals but not necessarily the whole population. In this review, we place these mechanisms under a larger lens that takes into account the influence of upstream "macro-level" environmental factors such as air pollution and the built environment. While these exposures likely have a smaller impact on the microbiome at an individual level, their ubiquitous nature confers them with a large influence at the population level. We focus on features of the indoor and outdoor human-made environment, their microbiomes and the research challenges inherent in integrating the built environment microbiomes with the early-life gut microbiome. We argue that an exposome perspective integrating internal and external microbiomes with macro-level environmental factors can provide a more comprehensive framework to define how environmental exposures can shape the gut microbiome and influence the development of allergic disease.

The nuts and bolts of omics for the clinical allergist

OBJECTIVE

Omics, aka multi-omics, is an emerging area of research that is advancing the use of personalized medicine in clinical practice and is therefore relevant for the practicing allergist.

DATA SOURCES

We performed a literature search of a selection of scientific findings in omics and allergy, including variants that may be important to allergy outcomes in the genome, transcriptome, metabolome, microbiome, epigenome, and exposome, among others.

STUDY SELECTIONS

Basic science papers and review articles.

RESULTS

The use of multi-omic data in clinical practice is changing how clinicians treat their patients whereby more personalized approaches are becoming standard in medical practice and has the potential to transform the treatment of allergies.

CONCLUSION

Multi-omic data are relevant and will become increasingly important for the clinical allergist.

NeTFactor, a framework for identifying transcriptional regulators of gene expression-based biomarkers

Biological and regulatory mechanisms underlying many multi-gene expression-based disease biomarkers are often not readily evident. We describe an innovative framework, NeTFactor, that combines network analyses with gene expression data to identify transcription factors (TFs) that significantly and maximally regulate such a biomarker. NeTFactor uses a computationally-inferred context-specific gene regulatory network and applies topological, statistical, and optimization methods to identify regulator TFs. Application of NeTFactor to a multi-gene expression-based asthma biomarker identified ETS translocation variant 4 (ETV4) and peroxisome proliferator-activated receptor gamma (PPARG) as the biomarker's most significant TF regulators. siRNA-based knock down of these TFs in an airway epithelial cell line model demonstrated significant reduction of cytokine expression relevant to asthma, validating NeTFactor's top-scoring findings. While PPARG has been associated with airway inflammation, ETV4 has not yet been implicated in asthma, thus indicating the possibility of novel, disease-relevant discovery by NeTFactor. We also show that NeTFactor's results are robust when the gene regulatory network and biomarker are derived from independent data. Additionally, our application of NeTFactor to a different disease biomarker identified TF regulators of interest. These results illustrate that the application of NeTFactor to multi-gene expression-based biomarkers could yield valuable insights into regulatory mechanisms and biological processes underlying disease.

Food allergy and omics

Food allergy (FA) prevalence has been increasing over the last few decades and is now a global health concern. Current diagnostic methods for FA result in a high number of false-positive results, and the standard of care is either allergen avoidance or use of epinephrine on accidental exposure, although currently with no other approved treatments. The increasing prevalence of FA, lack of robust biomarkers, and inadequate treatments warrants further research into the mechanism underlying food allergies. Recent technological advances have made it possible to move beyond traditional biological techniques to more sophisticated high-throughput approaches. These technologies have created the burgeoning field of omics sciences, which permit a more systematic investigation of biological problems. Omics sciences, such as genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiomics, and exposomics, have enabled the construction of regulatory networks and biological pathway models. Parallel advances in bioinformatics and computational techniques have enabled the integration, analysis, and interpretation of these exponentially growing data sets and opens the possibility of personalized or precision medicine for FA.

Effects of particulate matter (PM) on childhood asthma exacerbation and control in Xiamen, China

BACKGROUND

The short-term effects of particulate matter (PM) exposure on childhood asthma exacerbation and disease control rate is not thoroughly assessed in Chinese population yet. The previous toxic effects of PM exposure are either based on long-term survey or experimental data from cell lines or mouse models, which also needs to be validated by real-world evidences.

METHODS

We evaluated the short-term effects of PM exposure on asthma exacerbation in a Chinese population of 3106 pediatric outpatientsand disease control rate (DCR) in a population of 3344 children using case-crossover design. All the subjects enrolled are non-hospitalized outpatients. All data for this study were collected from the electronic health record (EHR) in the period between January 1, 2016 and June 30, 2018 in Xiamen, China.

RESULTS

We found that exposure to PM2.5 and PM10 within the past two weeks was significantly associated with elevated risk of exacerbation (OR = 1.049, p < 0.001 for PM2.5and OR = 1.027, p < 0.001 for PM10). In addition, exposure to PM10 was associated with decreased DCR (OR = 0.976 for PM10, p < 0.001).

CONCLUSIONS

Our results suggest that exposure to both PM10 and PM2.5 has significant short-term effects on childhood asthma exacerbation and DCR, which serves as useful epidemiological parameters for clinical management of asthma risk in the sensitive population.

Multiomics Data Triangulation for Asthma Candidate Biomarkers and Precision Medicine

Asthma is a common complex disorder and has been subject to intensive omics research for disease susceptibility and therapeutic innovation. Candidate biomarkers of asthma and its precision treatment demand that they stand the test of multiomics data triangulation before they can be prioritized for clinical applications. We classified the biomarkers of asthma after a search of the literature and based on whether or not a given biomarker candidate is reported in multiple omics platforms and methodologies, using PubMed and Web of Science, we identified omics studies of asthma conducted on diverse platforms using keywords, such as asthma, genomics, metabolomics, and epigenomics. We extracted data about asthma candidate biomarkers from 73 articles and developed a catalog of 190 potential asthma biomarkers (167 human, 23 animal data), comprising DNA loci, transcripts, proteins, metabolites, epimutations, and noncoding RNAs. The data were sorted according to 13 omics types: genomics, epigenomics, transcriptomics, proteomics, interactomics, metabolomics, ncRNAomics, glycomics, lipidomics, environmental omics, pharmacogenomics, phenomics, and integrative omics. Importantly, we found that 10 candidate biomarkers were apparent in at least two or more omics levels, thus promising potential for further biomarker research and development and precision medicine applications. This multiomics catalog reported herein for the first time contributes to future decision-making on prioritization of biomarkers and validation efforts for precision medicine in asthma. The findings may also facilitate meta-analyses and integrative omics studies in the future.

Genomic Predictors of Asthma Phenotypes and Treatment Response

Asthma is a complex respiratory disease considered as the most common chronic condition in children. A large genetic contribution to asthma susceptibility is predicted by the clustering of asthma and allergy symptoms among relatives and the large disease heritability estimated from twin studies, ranging from 55 to 90%. Genetic basis of asthma has been extensively investigated in the past 40 years using linkage analysis and candidate-gene association studies. However, the development of dense arrays for polymorphism genotyping has enabled the transition toward genome-wide association studies (GWAS), which have led the discovery of several unanticipated asthma genes in the last 11 years. Despite this, currently known risk variants identified using many thousand samples from distinct ethnicities only explain a small proportion of asthma heritability. This review examines the main findings of the last 2 years in genomic studies of asthma using GWAS and admixture mapping studies, as well as the direction of studies fostering integrative perspectives involving omics data. Additionally, we discuss the need for assessing the whole spectrum of genetic variation in association studies of asthma susceptibility, severity, and treatment response in order to further improve our knowledge of asthma genes and predictive biomarkers. Leveraging the individual's genetic information will allow a better understanding of asthma pathogenesis and will facilitate the transition toward a more precise diagnosis and treatment.

The gut microbiome in food allergy

OBJECTIVE

To review observational human, murine, and interventional trial studies that have examined the gut microbiome in food allergy, and to provide perspective on future investigations in this field.

DATA SOURCES

A review of the published literature was performed with PubMed, and clinical studies catalogued at ClinicalTrials.gov were also reviewed.

STUDY SELECTIONS

The most recent relevant studies, seminal works, and topical clinical trials were selected.

RESULTS

Gut dysbiosis likely precedes the development of food allergy, and the timing of such dysbiosis is critical. Gut microbiota associated with individual food allergies may be distinct. Murine models support the importance of gut microbiota in shaping immune maturation and tolerance. Gut microbiota may affect food allergy susceptibility by modulating type 2 immunity, influencing immune development and tolerance, regulating basophil populations, and promoting intestinal barrier function. Ongoing and future interventional trials of probiotics, prebiotics, synbiotics, and fecal microbiota transfer will help translate our understanding of the gut microbiome in food allergy to clinical practice. Future work in this area will include deepening of current research foci, as well as expansion of efforts to include the virome, mycobiome, and interactions between the microbiome, host, and environment. Robust and consistent study designs, multidimensional profiling, and systems biology approaches will enable this future work.

CONCLUSION

By advancing research on the microbiome in food allergy, we can further our understanding of food allergy and derive new approaches for its prevention and therapy.