Transcriptomics of atopy and atopic asthma in white blood cells from children and adolescents

An integrated molecular risk score early in life for subsequent childhood asthma risk

BACKGROUND

Numerous children present with early wheeze symptoms, yet solely a subgroup develops childhood asthma. Early identification of children at risk is key for clinical monitoring, timely patient-tailored treatment, and preventing chronic, severe sequelae. For early prediction of childhood asthma, we aimed to define an integrated risk score combining established risk factors with genome-wide molecular markers at birth, complemented by subsequent clinical symptoms/diagnoses (wheezing, atopic dermatitis, food allergy).

METHODS

Three longitudinal birth cohorts (PAULINA/PAULCHEN, n = 190 + 93 = 283, PASTURE, n = 1133) were used to predict childhood asthma (age 5-11) including epidemiological characteristics and molecular markers: genotype, DNA methylation and mRNA expression (RNASeq/NanoString). Apparent (ap) and optimism-corrected (oc) performance (AUC/R2) was assessed leveraging evidence from independent studies (Naïve-Bayes approach) combined with high-dimensional logistic regression models (LASSO).

RESULTS

Asthma prediction with epidemiological characteristics at birth (maternal asthma, sex, farm environment) yielded an ocAUC = 0.65. Inclusion of molecular markers as predictors resulted in an improvement in apparent prediction performance, however, for optimism-corrected performance only a moderate increase was observed (upto ocAUC = 0.68). The greatest discriminate power was reached by adding the first symptoms/diagnosis (up to ocAUC = 0.76; increase of 0.08, p = .002). Longitudinal analysis of selected mRNA expression in PASTURE (cord blood, 1, 4.5, 6 years) showed that expression at age six had the strongest association with asthma and correlation of genes getting larger over time (r = .59, p < .001, 4.5-6 years).

CONCLUSION

Applying epidemiological predictors alone showed moderate predictive abilities. Molecular markers from birth modestly improved prediction. Allergic symptoms/diagnoses enhanced the power of prediction, which is important for clinical practice and for the design of future studies with molecular markers.

Gene-based association study of rare variants in children of diverse ancestries implicates TNFRSF21 in the development of allergic asthma

BACKGROUND

Most genetic studies of asthma and allergy have focused on common variation in individuals primarily of European ancestry. Studying the role of rare variation in quantitative phenotypes and in asthma phenotypes in populations of diverse ancestries can provide additional, important insights into the development of these traits.

OBJECTIVE

We sought to examine the contribution of rare variants to different asthma- or allergy-associated quantitative traits in children with diverse ancestries and explore their role in asthma phenotypes.

METHODS

We examined whole-genome sequencing data from children participants in longitudinal studies of asthma (n = 1035; parent-identified as 67% Black and 25% Hispanic) to identify rare variants (minor allele frequency < 0.01). We assigned variants to genes and tested for associations using an omnibus variant-set test between each of 24,902 genes and 8 asthma-associated quantitative traits. On combining our results with external data on predicted gene expression in humans and mouse knockout studies, we identified 3 candidate genes. A burden of rare variants in each gene and in a combined 3-gene score was tested for its associations with clinical phenotypes of asthma. Finally, published single-cell gene expression data in lower airway mucosal cells after allergen challenge were used to assess transcriptional responses to allergen.

RESULTS

Rare variants in USF1 were significantly associated with blood neutrophil count (P = 2.18 × 10-7); rare variants in TNFRSF21 with total IgE (P = 6.47 × 10-6) and PIK3R6 with eosinophil count (P = 4.10 × 10-5) reached suggestive significance. These 3 findings were supported by independent data from human and mouse studies. A burden of rare variants in TNFRSF21 and in a 3-gene score was associated with allergy-related phenotypes in cohorts of children with mild and severe asthma. Furthermore, TNFRSF21 was significantly upregulated in bronchial basal epithelial cells from adults with allergic asthma but not in adults with allergies (but not asthma) after allergen challenge.

CONCLUSIONS

We report novel associations between rare variants in genes and allergic and inflammatory phenotypes in children with diverse ancestries, highlighting TNFRSF21 as contributing to the development of allergic asthma.

The Role of Rab GTPases in the development of genetic and malignant diseases

Small GTPases have been shown to play an important role in several cellular functions, including cytoskeletal remodeling, cell polarity, intracellular trafficking, cell-cycle, progression and lipid transformation. The Ras-associated binding (Rab) family of GTPases constitutes the largest family of GTPases and consists of almost 70 known members of small GTPases in humans, which are known to play an important role in the regulation of intracellular membrane trafficking, membrane identity, vesicle budding, uncoating, motility and fusion of membranes. Mutations in Rab genes can cause a wide range of inherited genetic diseases, ranging from neurodegenerative diseases, such as Parkinson's disease (PD) and Alzheimer's disease (AD) to immune dysregulation/deficiency syndromes, like Griscelli Syndrome Type II (GS-II) and hemophagocytic lymphohistiocytosis (HLH), as well as a variety of cancers. Here, we provide an extended overview of human Rabs, discussing their function and diseases related to Rabs and Rab effectors, as well as focusing on effects of (aberrant) Rab expression. We aim to underline their importance in health and the development of genetic and malignant diseases by assessing their role in cellular structure, regulation, function and biology and discuss the possible use of stem cell gene therapy, as well as targeting of Rabs in order to treat malignancies, but also to monitor recurrence of cancer and metastasis through the use of Rabs as biomarkers. Future research should shed further light on the roles of Rabs in the development of multifactorial diseases, such as diabetes and assess Rabs as a possible treatment target.

Methyl-TWAS: A powerful method for in silico transcriptome-wide association studies (TWAS) using long-range DNA methylation

In silico transcriptome-wide association studies (TWAS) are commonly used to test whether expression of specific genes is linked to a complex trait. However, genotype-based in silico TWAS such as PrediXcan, exhibit low prediction accuracy for a majority of genes because genotypic data lack tissue- and disease-specificity and are not affected by the environment. Because methylation is tissue-specific and, like gene expression, can be modified by environment or disease status, methylation should predict gene expression with more accuracy than SNPs. Therefore, we propose Methyl-TWAS, the first approach that utilizes long-range methylation markers to impute gene expression for in silico TWAS through penalized regression. Methyl-TWAS 1) predicts epigenetically regulated/associated expression (eGReX), which incorporates tissue-specific expression and both genetically- (GReX) and environmentally-regulated expression to identify differentially expressed genes (DEGs) that could not be identified by genotype-based methods; and 2) incorporates both cis- and trans- CpGs, including various regulatory regions to identify DEGs that would be missed using cis- methylation only. Methyl-TWAS outperforms PrediXcan and two other methods in imputing gene expression in the nasal epithelium, particularly for immunity-related genes and DEGs in atopic asthma. Methyl-TWAS identified 3,681 (85.2%) of the 4,316 DEGs identified in a previous TWAS of atopic asthma using measured expression, while PrediXcan could not identify any gene. Methyl-TWAS also outperforms PrediXcan for expression imputation as well as in silico TWAS in white blood cells. Methyl-TWAS is a valuable tool for in silico TWAS, leveraging a growing body of publicly available genome-wide DNA methylation data for a variety of human tissues.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Construction and verification of atopic dermatitis diagnostic model based on pyroptosis related biological markers using machine learning methods

OBJECTIVE

The aim of this study was to construct a model used for the accurate diagnosis of Atopic dermatitis (AD) using pyroptosis related biological markers (PRBMs) through the methods of machine learning.

METHOD

The pyroptosis related genes (PRGs) were acquired from molecular signatures database (MSigDB). The chip data of GSE120721, GSE6012, GSE32924, and GSE153007 were downloaded from gene expression omnibus (GEO) database. The data of GSE120721 and GSE6012 were combined as the training group, while the others were served as the testing groups. Subsequently, the expression of PRGs was extracted from the training group and differentially expressed analysis was conducted. CIBERSORT algorithm calculated the immune cells infiltration and differentially expressed analysis was conducted. Consistent cluster analysis divided AD patients into different modules according to the expression levels of PRGs. Then, weighted correlation network analysis (WGCNA) screened the key module. For the key module, we used Random forest (RF), support vector machines (SVM), Extreme Gradient Boosting (XGB), and generalized linear model (GLM) to construct diagnostic models. For the five PRBMs with the highest model importance, we built a nomogram. Finally, the results of the model were validated using GSE32924, and GSE153007 datasets.

RESULTS

Nine PRGs were significant differences in normal humans and AD patients. Immune cells infiltration showed that the activated CD4+ memory T cells and Dendritic cells (DCs) were significantly higher in AD patients than normal humans, while the activated natural killer (NK) cells and the resting mast cells were significantly lower in AD patients than normal humans. Consistent cluster analysis divided the expressing matrix into 2 modules. Subsequently, WGCNA analysis showed that the turquoise module had a significant difference and high correlation coefficient. Then, the machine model was constructed and the results showed that the XGB model was the optimal model. The nomogram was constructed by using HDAC1, GPALPP1, LGALS3, SLC29A1, and RWDD3 five PRBMs. Finally, the datasets GSE32924 and GSE153007 verified the reliability of this result.

CONCLUSIONS

The XGB model based on five PRBMs can be used for the accurate diagnosis of AD patients.

Timing of Blood Sample Processing Affects the Transcriptomic and Epigenomic Profiles in CD4+ T-cells of Atopic Subjects

Optimal pre-analytical conditions for blood sample processing and isolation of selected cell populations for subsequent transcriptomic and epigenomic studies are required to obtain robust and reproducible results. This pilot study was conducted to investigate the potential effects of timing of CD4⁺ T-cell processing from peripheral blood of atopic and non-atopic adults on their transcriptomic and epigenetic profiles. Two heparinized blood samples were drawn from each of three atopic and three healthy individuals. For each individual, CD4⁺ T-cells were isolated from the first blood sample within 2 h (immediate) or from the second blood sample after 24 h storage (delayed). RNA sequencing (RNA-Seq) and histone H3K27 acetylation chromatin immunoprecipitation sequencing (ChIP-Seq) analyses were performed. A multiplicity of genes was shown to be differentially expressed in immediately processed CD4⁺ T-cells from atopic versus healthy subjects. These differences disappeared when comparing delayed processed cells due to a drastic change in expression levels of atopy-related genes in delayed processed CD4⁺ T-cells from atopic donors. This finding was further validated on the epigenomic level by examining H3K27 acetylation profiles. In contrast, transcriptomic and epigenomic profiles of blood CD4⁺ T-cells of healthy donors remained rather unaffected. Taken together, for successful transcriptomics and epigenomics studies, detailed standard operation procedures developed on the basis of samples from both healthy and disease conditions are implicitly recommended.

Peripheral blood transcriptomic clusters uncovered immune phenotypes of asthma

BACKGROUND

Transcriptomic analysis has been used to elucidate the complex pathogenesis of heterogeneous disease and may also contribute to identify potential therapeutic targets by delineating the hub genes. This study aimed to investigate whether blood transcriptomic clustering can distinguish clinical and immune phenotypes of asthmatics, and microbiome in asthmatics.

METHODS

Transcriptomic expression of peripheral blood mononuclear cells (PBMCs) from 47 asthmatics and 21 non-asthmatics was measured using RNA sequencing. A hierarchical clustering algorithm was used to classify asthmatics. Differentially expressed genes, clinical phenotypes, immune phenotypes, and microbiome of each transcriptomic cluster were assessed.

RESULTS

In asthmatics, three distinct transcriptomic clusters with numerously different transcriptomic expressions were identified. The proportion of severe asthmatics was highest in cluster 3 as 73.3%, followed by cluster 2 (45.5%) and cluster 1 (28.6%). While cluster 1 represented clinically non-severe T2 asthma, cluster 3 tended to include severe non-T2 asthma. Cluster 2 had features of both T2 and non-T2 asthmatics characterized by the highest serum IgE level and neutrophil-dominant sputum cell population. Compared to non-asthmatics, cluster 1 showed higher CCL23 and IL1RL1 expression while the expression of TREML4 was suppressed in cluster 3. CTSD and ALDH2 showed a significant positive linear relationship across three clusters in the order of cluster 1 to 3. No significant differences in the diversities of lung and gut microbiomes were observed among transcriptomic clusters of asthmatics and non-asthmatics. However, our study has limitations in that small sample size data were analyzed with unmeasured confounding factors and causal relationships or function pathways were not verified.

CONCLUSIONS

Genetic clustering based on the blood transcriptome may provide novel immunological insight, which can be biomarkers of asthma immune phenotypes. Trial registration Retrospectively registered.

Robust and accurate estimation of cellular fraction from tissue omics data via ensemble deconvolution

MOTIVATION

Tissue-level omics data such as transcriptomics and epigenomics are an average across diverse cell types. To extract cell-type-specific (CTS) signals, dozens of cellular deconvolution methods have been proposed to infer cell-type fractions from tissue-level data. However, these methods produce vastly different results under various real data settings. Simulation-based benchmarking studies showed no universally best deconvolution approaches. There have been attempts of ensemble methods, but they only aggregate multiple single-cell references or reference-free deconvolution methods.

RESULTS

To achieve a robust estimation of cellular fractions, we proposed EnsDeconv (Ensemble Deconvolution), which adopts CTS robust regression to synthesize the results from 11 single deconvolution methods, 10 reference datasets, 5 marker gene selection procedures, 5 data normalizations and 2 transformations. Unlike most benchmarking studies based on simulations, we compiled four large real datasets of 4937 tissue samples in total with measured cellular fractions and bulk gene expression from different tissues. Comprehensive evaluations demonstrated that EnsDeconv yields more stable, robust and accurate fractions than existing methods. We illustrated that EnsDeconv estimated cellular fractions enable various CTS downstream analyses such as differential fractions associated with clinical variables. We further extended EnsDeconv to analyze bulk DNA methylation data.

AVAILABILITY AND IMPLEMENTATION

EnsDeconv is freely available as an R-package from https://github.com/randel/EnsDeconv. The RNA microarray data from the TRAUMA study are available and can be accessed in GEO (GSE36809). The demographic and clinical phenotypes can be shared on reasonable request to the corresponding authors. The RNA-seq data from the EVAPR study cannot be shared publicly due to the privacy of individuals that participated in the clinical research in compliance with the IRB approval at the University of Pittsburgh. The RNA microarray data from the FHS study are available from dbGaP (phs000007.v32.p13). The RNA-seq data from ROS study is downloaded from AD Knowledge Portal.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Rab44 regulates murine mast cell-driven anaphylaxis through kinesin-1-dependent secretory granule translocation

BACKGROUND

Mast cells (MCs) are key effectors of the allergic response. Following the cross-linking of IgE receptors (FcεRIs), they release crucial inflammatory mediators through degranulation. Although degranulation depends critically on secretory granule (SG) trafficking towards the plasma membrane, the molecular machinery underlying this transport has not been fully characterized.

OBJECTIVE

Here, we analyzed the function of Rab44, a large atypical Rab GTPase highly expressed in MC, in MC degranulation process.

METHODS

Murine KO mouse models (KO^Rab44 and DKO^Kif5b/Rab44) were used to perform passive cutaneous anaphylaxis (PCA) experiments and analyze granule translocation in derived bone-marrow-derived MCs (BMMCs) during degranulation.

RESULTS

We demonstrate that mice lacking Rab44 (KO^Rab44) in their BMMCs are impaired in their ability to translocate and degranulate SGs at the plasma membrane upon FcεRI stimulation. Accordingly, KO^Rab44 mice were less sensitive to IgE-mediated passive cutaneous anaphylaxis in vivo. A lack of Rab44 did not impair early FcεRI-stimulated signaling pathways, microtubule reorganization, lipid mediator or cytokine secretion. Mechanistically, Rab44 appears to interact with and function as part of the previously described kinesin-1-dependent transport pathway.

CONCLUSIONS

Our results highlight a novel role of Rab44 as a regulator of SG transport during degranulation and anaphylaxis acting through the kinesin-1-dependent microtubule transport machinery. Rab44 can thus be considered as a potential target for modulating MC degranulation and inhibiting IgE-mediated allergic reactions.

Differential gene expression in nasal airway epithelium from overweight or obese youth with asthma

BACKGROUND

The mechanisms underlying the known link between overweight/obesity and childhood asthma are unclear. We aimed to identify differentially expressed genes and pathways associated with obesity-related asthma through a transcriptomic analysis of nasal airway epithelium.

METHODS

We compared the whole transcriptome in nasal airway epithelium of youth with overweight or obesity and asthma with that of youth of normal weight and asthma, using RNA sequencing data from a cohort of 235 Puerto Ricans aged 9-20 years (EVA-PR) and an independent cohort of 66 children aged 6-16 years in Pittsburgh (VDKA). Differential expression analysis adjusting for age, sex, sequencing plate number, and sample sorting protocol, and the first five principal components were performed independently in each cohort. Results from the two cohorts were combined in a transcriptome-wide meta-analysis. Gene enrichment and network analyses were performed on top genes.

RESULTS

In the meta-analysis, 29 genes were associated with obesity-related asthma at an FDR-adjusted p <.05, including pro-inflammatory genes known to be differentially expressed in adipose tissue of obese subjects (e.g., CXCL11, CXCL10, and CXCL9) and several novel genes. Functional enrichment analyses showed that pathways for interferon signaling, and innate and adaptive immune responses were down-regulated in overweight/obese youth with asthma, while pathways related to ciliary structure or function were up-regulated. Upstream regulatory analysis predicted significant inhibition of the IRF7 pathway. Network analyses identified "hub" genes like GBP5 and SOCS1.

CONCLUSION

Our transcriptome-wide analysis of nasal airway epithelium identified biologically plausible genes and pathways for obesity-related asthma in youth.

Plasma proteins elevated in severe asthma despite oral steroid use and unrelated to Type-2 inflammation

Rationale

Asthma phenotyping requires novel biomarker discovery.

Objectives

To identify plasma biomarkers associated with asthma phenotypes by application of a new proteomic panel to samples from two well-characterised cohorts of severe (SA) and mild-to-moderate (MMA) asthmatics, COPD subjects and healthy controls (HCs).

Methods

An antibody-based array targeting 177 proteins predominantly involved in pathways relevant to inflammation, lipid metabolism, signal transduction and extracellular matrix was applied to plasma from 525 asthmatics and HCs in the U-BIOPRED cohort, and 142 subjects with asthma and COPD from the validation cohort BIOAIR. Effects of oral corticosteroids (OCS) were determined by a 2-week, placebo-controlled OCS trial in BIOAIR, and confirmed by relation to objective OCS measures in U-BIOPRED.

Results

In U-BIOPRED, 110 proteins were significantly different, mostly elevated, in SA compared to MMA and HCs. 10 proteins were elevated in SA versus MMA in both U-BIOPRED and BIOAIR (alpha-1-antichymotrypsin, apolipoprotein-E, complement component 9, complement factor I, macrophage inflammatory protein-3, interleukin-6, sphingomyelin phosphodiesterase 3, TNF receptor superfamily member 11a, transforming growth factor-β and glutathione S-transferase). OCS treatment decreased most proteins, yet differences between SA and MMA remained following correction for OCS use. Consensus clustering of U-BIOPRED protein data yielded six clusters associated with asthma control, quality of life, blood neutrophils, high-sensitivity C-reactive protein and body mass index, but not Type-2 inflammatory biomarkers. The mast cell specific enzyme carboxypeptidase A3 was one major contributor to cluster differentiation.

Conclusions

The plasma proteomic panel revealed previously unexplored yet potentially useful Type-2-independent biomarkers and validated several proteins with established involvement in the pathophysiology of SA.

Application of new proteomic panel in two established European asthma cohorts identifies plasma proteins associated with disease severity independently of Type-2 inflammation, suggesting potentially useful novel biomarkers and therapeutic targets.https://bit.ly/3jtTq5m

Endotyping asthma related to three different work exposures

BACKGROUND

Work exposures play a significant role in adult-onset asthma, but mechanisms of work-related asthma are not fully elucidated.

OBJECTIVE

We aimed to reveal the molecular mechanisms of work-related asthma associated with flour (FA), isocyanate (IA) or welding fume (WA) exposures and identify potential biomarkers that distinguish these groups from each other.

METHODS

We used a combination of clinical tests, transcriptomic analysis and associated pathway analyses to investigate underlying disease mechanisms of the blood immune cells and the airway epithelium of 61 men.

RESULTS

Compared to the healthy controls, the WA patients had more differentially expressed genes than the FA and IA patients both in the airway epithelia and in the blood immune cells. In the airway epithelia, active inflammation was detected only in WA patients. In contrast, large number of differentially expressed genes were detected in all asthma groups in blood cells. Disease-related immune functions in blood cells were suppressed in all the asthma groups including leukocyte migration and inflammatory responses and decreased expression of upstream cytokines such as TNF and IFNγ. In transcriptome-phenotype correlations, hyperresponsiveness (R∼|0.6|) had the highest clinical relevance and associated with a set of exposure-group specific genes. Finally, biomarker subsets of only 5 genes specifically distinguished each of the asthma exposure group.

CONCLUSIONS

This study provides novel data on the molecular mechanisms underlying work-related asthma. We identified set of 5 promising biomarkers in asthma related to flour, isocyanate and welding exposure to be tested and clinically validated in future studies.

Large Rab GTPases: Novel Membrane Trafficking Regulators with a Calcium Sensor and Functional Domains

Rab GTPases are major coordinators of intracellular membrane trafficking, including vesicle transport, membrane fission, tethering, docking, and fusion events. Rab GTPases are roughly divided into two groups: conventional “small” Rab GTPases and atypical “large” Rab GTPases that have been recently reported. Some members of large Rab GTPases in mammals include Rab44, Rab45/RASEF, and Rab46. The genes of these large Rab GTPases commonly encode an amino-terminal EF-hand domain, coiled-coil domain, and the carboxyl-terminal Rab GTPase domain. A common feature of large Rab GTPases is that they express several isoforms in cells. For instance, Rab44’s two isoforms have similar functions, but exhibit differential localization. The long form of Rab45 (Rab45-L) is abundantly distributed in epithelial cells. The short form of Rab45 (Rab45-S) is predominantly present in the testes. Both Rab46 (CRACR2A-L) and the short isoform lacking the Rab domain (CRACR2A-S) are expressed in T cells, whereas Rab46 is only distributed in endothelial cells. Although evidence regarding the function of large Rab GTPases has been accumulating recently, there are only a limited number of studies. Here, we report the recent findings on the large Rab GTPase family concerning their function in membrane trafficking, cell differentiation, related diseases, and knockout mouse phenotypes.

The role of atopy in asthma development and persistence

PURPOSE OF REVIEW

Asthma is the most common chronic disease in pediatric age. Childhood-onset asthma, as opposed to adult-onset asthma, is typically characterized by a personal and often a family history of atopy and related markers of type 2-mediated inflammation. However, the interplay between atopy and asthma development is more complex than a linear dose-response relationship.

RECENT FINDINGS

Family and personal history of atopic diseases have been confirmed as major risk factors for asthma occurrence and persistence in children. Early life and multiple sensitizations to aeroallergens significantly increase the risk of asthma development in school age. Early life lower respiratory tract viral infections, especially caused by rhinovirus, also increase the susceptibility to atopic asthma in childhood. Human rhinovirus type C receptor CDHR3 polymorphisms have been shown to affect receptor epithelial expression, activation, and asthma development and exacerbation severity in children. Atopic sensitization and respiratory viral infections can synergistically enhance the susceptibility to asthma through multiple mechanisms, including the IgE-mediated inhibition of innate antiviral responses to rhinovirus. Emerging evidence shows that several nonatopic factors are also involved in the asthma pathogenesis in genetically predisposed individuals, including early life exposure to environmental factors, and lung and gut microbiome composition.

SUMMARY

The current review outlines recent data on the complex role of atopy in asthma pathogenesis and persistence, and addresses new research topics such as the role of epigenetics and the lung microbiome.

Childhood asthma in the new omics era: challenges and perspectives

Purpose of review

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

Recent findings

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

Summary

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

Allergic rhinitis

Allergic rhinitis (AR) is caused by immunoglobulin E (IgE)-mediated reactions to inhaled allergens and is one of the most common chronic conditions globally. AR often co-occurs with asthma and conjunctivitis and is a global health problem causing major burden and disability worldwide. Risk factors include inhalant and occupational allergens, as well as genetic factors. AR impairs quality of life, affects social life, school and work, and is associated with substantial economic costs. The Allergic Rhinitis and its Impact on Asthma (ARIA) initiative classified AR into intermittent or persistent and mild or moderate/severe. The diagnosis is based on the clinical history and, if needed in patients with uncontrolled rhinitis despite medications or with long-lasting symptoms, on skin tests or the presence of serum-specific IgE antibodies to allergens. The most frequently used pharmacological treatments include oral, intranasal or ocular H₁-antihistamines, intranasal corticosteroids or a fixed combination of intranasal H₁-antihistamines and corticosteroids. Allergen immunotherapy prescribed by a specialist using high-quality extracts in stratified patients is effective in patients with persistent symptoms. Real-world data obtained by mobile technology offer new insights into AR phenotypes and management. The outlook for AR includes a better understanding of novel multimorbid phenotypes, health technology assessment and patient-centred shared decision-making.

A novel whole blood gene expression signature for asthma, dermatitis, and rhinitis multimorbidity in children and adolescents

BACKGROUND

Allergic diseases often occur in combination (multimorbidity). Human blood transcriptome studies have not addressed multimorbidity. Large-scale gene expression data were combined to retrieve biomarkers and signaling pathways to disentangle allergic multimorbidity phenotypes.

METHODS

Integrated transcriptomic analysis was conducted in 1233 participants with a discovery phase using gene expression data (Human Transcriptome Array 2.0) from whole blood of 786 children from three European birth cohorts (MeDALL), and a replication phase using RNA Sequencing data from an independent cohort (EVA-PR, n = 447). Allergic diseases (asthma, atopic dermatitis, rhinitis) were considered as single disease or multimorbidity (at least two diseases), and compared with no disease.

RESULTS

Fifty genes were differentially expressed in allergic diseases. Thirty-two were not previously described in allergy. Eight genes were consistently overexpressed in all types of multimorbidity for asthma, dermatitis, and rhinitis (CLC, EMR4P, IL5RA, FRRS1, HRH4, SLC29A1, SIGLEC8, IL1RL1). All genes were replicated the in EVA-PR cohort. RT-qPCR validated the overexpression of selected genes. In MeDALL, 27 genes were differentially expressed in rhinitis alone, but none was significant for asthma or dermatitis alone. The multimorbidity signature was enriched in eosinophil-associated immune response and signal transduction. Protein-protein interaction network analysis identified IL5/JAK/STAT and IL33/ST2/IRAK/TRAF as key signaling pathways in multimorbid diseases. Synergistic effect of multimorbidity on gene expression levels was found.

CONCLUSION

A signature of eight genes identifies multimorbidity for asthma, rhinitis, and dermatitis. Our results have clinical and mechanistic implications, and suggest that multimorbidity should be considered differently than allergic diseases occurring alone.