Multi-omics colocalization with genome-wide association studies reveals a context-specific genetic mechanism at a childhood onset asthma risk locus

CheekAge: a next-generation buccal epigenetic aging clock associated with lifestyle and health

Epigenetic aging clocks are computational models that predict age using DNA methylation information. Initially, first-generation clocks were developed to make predictions using CpGs that change with age. Over time, next-generation clocks were created using CpGs that relate to both age and health. Since existing next-generation clocks were constructed in blood, we sought to develop a next-generation clock optimized for prediction in cheek swabs, which are non-invasive and easy to collect. To do this, we collected MethylationEPIC data as well as lifestyle and health information from 8045 diverse adults. Using a novel simulated annealing approach that allowed us to incorporate lifestyle and health factors into training as well as a combination of CpG filtering, CpG clustering, and clock ensembling, we constructed CheekAge, an epigenetic aging clock that has a strong correlation with age, displays high test-retest reproducibility across replicates, and significantly associates with a plethora of lifestyle and health factors, such as BMI, smoking status, and alcohol intake. We validated CheekAge in an internal dataset and multiple publicly available datasets, including samples from patients with progeria or meningioma. In addition to exploring the underlying biology of the data and clock, we provide a free online tool that allows users to mine our methylomic data and predict epigenetic age.

Skin, gut, and lung barrier: Physiological interface and target of intervention for preventing and treating allergic diseases

The epithelial barriers of the skin, gut, and respiratory tract are critical interfaces between the environment and the host, and they orchestrate both homeostatic and pathogenic immune responses. The mechanisms underlying epithelial barrier dysfunction in allergic and inflammatory conditions, such as atopic dermatitis, food allergy, eosinophilic oesophagitis, allergic rhinitis, chronic rhinosinusitis, and asthma, are complex and influenced by the exposome, microbiome, individual genetics, and epigenetics. Here, we review the role of the epithelial barriers of the skin, digestive tract, and airways in maintaining homeostasis, how they influence the occurrence and progression of allergic and inflammatory conditions, how current treatments target the epithelium to improve symptoms of these disorders, and what the unmet needs are in the identification and treatment of epithelial disorders.

Gasdermin B, an asthma-susceptibility gene, promotes MAVS-TBK1 signalling and airway inflammation

RATIONALE

Respiratory virus-induced inflammation is the leading cause of asthma exacerbation, frequently accompanied by induction of interferon-stimulated genes (ISGs). How asthma-susceptibility genes modulate cellular response upon viral infection by fine-tuning ISG induction and subsequent airway inflammation in genetically susceptible asthma patients remains largely unknown.

OBJECTIVES

To decipher the functions of gasdermin B (encoded by GSDMB) in respiratory virus-induced lung inflammation.

METHODS

In two independent cohorts, we analysed expression correlation between GSDMB and ISG s. In human bronchial epithelial cell line or primary bronchial epithelial cells, we generated GSDMB-overexpressing and GSDMB-deficient cells. A series of quantitative PCR, ELISA and co-immunoprecipitation assays were performed to determine the function and mechanism of GSDMB for ISG induction. We also generated a novel transgenic mouse line with inducible expression of human unique GSDMB gene in airway epithelial cells and infected the mice with respiratory syncytial virus to determine the role of GSDMB in respiratory syncytial virus-induced lung inflammation in vivo.

RESULTS

GSDMB is one of the most significant asthma-susceptibility genes at 17q21 and acts as a novel RNA sensor, promoting mitochondrial antiviral-signalling protein (MAVS)-TANK binding kinase 1 (TBK1) signalling and subsequent inflammation. In airway epithelium, GSDMB is induced by respiratory viral infections. Expression of GSDMB and ISGs significantly correlated in respiratory epithelium from two independent asthma cohorts. Notably, inducible expression of human GSDMB in mouse airway epithelium led to enhanced ISGs induction and increased airway inflammation with mucus hypersecretion upon respiratory syncytial virus infection.

CONCLUSIONS

GSDMB promotes ISGs expression and airway inflammation upon respiratory virus infection, thereby conferring asthma risk in risk allele carriers.

Effect of air pollution on asthma

Asthma is a chronic inflammatory airway disease characterized by respiratory symptoms, variable airflow obstruction, bronchial hyperresponsiveness, and airway inflammation. Exposure to air pollution has been linked to an increased risk of asthma development and exacerbation. This review aims to comprehensively summarize recent data on the impact of air pollution on asthma development and exacerbation. Specifically, we reviewed the effects of air pollution on the pathogenic pathways of asthma, including type 2 and non-type 2 inflammatory responses, and airway epithelial barrier dysfunction. Air pollution promotes the release of epithelial cytokines, driving TH2 responses, and induces oxidative stress and the production of proinflammatory cytokines. The enhanced type 2 inflammation, furthered by air pollution-induced dysfunction of the airway epithelial barrier, may be associated with the exacerbation of asthma. Disruption of the TH17/regulatory T cell balance by air pollutants is also related to asthma exacerbation. As the effects of air pollution exposure may accumulate over time, with potentially stronger impacts in the development of asthma during certain sensitive life periods, we also reviewed the effects of air pollution on asthma across the lifespan. Future research is needed to better characterize the sensitive period contributing to the development of air pollution-induced asthma and to map air pollution-associated epigenetic biomarkers contributing to the epigenetic ages onto asthma-related genes.

Causal relationships of metabolites with allergic diseases: a trans-ethnic Mendelian randomization study

BACKGROUND

Allergic diseases exert a considerable impact on global health, thus necessitating investigations into their etiology and pathophysiology for devising effective prevention and treatment strategies. This study employs a Mendelian randomization (MR) analysis and meta-analysis to identify metabolite targets potentially associated with allergic diseases.

METHODS

A two-sample MR analysis was conducted to explore potential causal relationships between circulating and urinary metabolites and allergic diseases. Exposures were derived from a genome-wide association study (GWAS) of 486 circulating metabolites and a GWAS of 55 targeted urinary metabolites. Outcome data for allergic diseases, including atopic dermatitis (AD), allergic rhinitis (AR), and asthma, were obtained from the FinnGen biobank in Europe (cohort 1) and the Biobank Japan in Asia (cohort 2). MR results from both cohorts were combined using a meta-analysis.

RESULTS

MR analysis identified 50 circulating metabolites and 6 urinary metabolites in cohort 1 and 54 circulating metabolites and 2 urinary metabolites in cohort 2 as potentially causally related to allergic diseases. A meta-analysis of the MR results revealed stearoylcarnitine (OR 8.654; 95% CI 4.399-17.025; P = 4.06E-10) and 1-arachidonoylglycerophosphoinositol (OR 2.178; 95% CI 1.388-3.419; P = 7.15E-04) as the most reliable causal circulating metabolites for asthma and AR, respectively. Further, histidine (OR 0.734; 95% CI: 0.594-0.907; P = 0.004), tyrosine (OR 0.601; 95% CI: 0.380-0.952; P = 0.030), and alanine (OR 0.280; 95% CI: 0.125-0.628; P = 0.002) emerged as urinary metabolites with the greatest protective effects against asthma, AD, and AR, respectively.

CONCLUSIONS

Imbalances in numerous circulating and urinary metabolites may be implicated in the development and progression of allergic diseases. These findings have significant implications for the development of targeted strategies for the prevention and treatment of allergic diseases.

The application of multi-omics in the respiratory microbiome: Progresses, challenges and promises

The study of the respiratory microbiome has entered a multi-omic era. Through integrating different omic data types such as metagenome, metatranscriptome, metaproteome, metabolome, culturome and radiome surveyed from respiratory specimens, holistic insights can be gained on the lung microbiome and its interaction with host immunity and inflammation in respiratory diseases. The power of multi-omics have moved the field forward from associative assessment of microbiome alterations to causative understanding of the lung microbiome in the pathogenesis of chronic, acute and other types of respiratory diseases. However, the application of multi-omics in respiratory microbiome remains with unique challenges from sample processing, data integration, and downstream validation. In this review, we first introduce the respiratory sample types and omic data types applicable to studying the respiratory microbiome. We next describe approaches for multi-omic integration, focusing on dimensionality reduction, multi-omic association and prediction. We then summarize progresses in the application of multi-omics to studying the microbiome in respiratory diseases. We finally discuss current challenges and share our thoughts on future promises in the field.

Epigenetic responses to rhinovirus exposure in airway epithelial cells are correlated with key transcriptional pathways in chronic rhinosinusitis

BACKGROUND

Viruses may drive immune mechanisms responsible for chronic rhinosinusitis with nasal polyposis (CRSwNP), but little is known about the underlying molecular mechanisms.

OBJECTIVES

To identify epigenetic and transcriptional responses to a common upper respiratory pathogen, rhinovirus (RV), that are specific to patients with CRSwNP using a primary sinonasal epithelial cell culture model.

METHODS

Airway epithelial cells were collected at surgery from patients with CRSwNP (cases) and from controls without sinus disease, cultured, and then exposed to RV or vehicle for 48 h. Differential gene expression and DNA methylation (DNAm) between cases and controls in response to RV were determined using linear mixed models. Weighted gene co-expression analysis (WGCNA) was used to identify (a) co-regulated gene expression and DNAm signatures, and (b) genes, pathways, and regulatory mechanisms specific to CRSwNP.

RESULTS

We identified 5585 differential transcriptional and 261 DNAm responses (FDR <0.10) to RV between CRSwNP cases and controls. These differential responses formed three co-expression/co-methylation modules that were related to CRSwNP and three that were related to RV (Bonferroni corrected p < .01). Most (95%) of the differentially methylated CpGs (DMCs) were in modules related to CRSwNP, whereas the differentially expressed genes (DEGs) were more equally distributed between the CRSwNP- and RV-related modules. Genes in the CRSwNP-related modules were enriched in known CRS and/or viral response immune pathways.

CONCLUSION

RV activates specific epigenetic programs and correlated transcriptional networks in the sinonasal epithelium of individuals with CRSwNP. These novel observations suggest epigenetic signatures specific to patients with CRSwNP modulate response to viral pathogens at the mucosal environmental interface. Determining how viral response pathways are involved in epithelial inflammation in CRSwNP could lead to therapeutic targets for this burdensome airway disorder.

Genomics of Treatable Traits in Asthma

The astounding number of genetic variants revealed in the 15 years of genome-wide association studies of asthma has not kept pace with the goals of translational genomics. Moving asthma diagnosis from a nonspecific umbrella term to specific phenotypes/endotypes and related traits may provide insights into features that may be prevented or alleviated by therapeutical intervention. This review provides an overview of the different asthma endotypes and phenotypes and the genomic findings from asthma studies using patient stratification strategies and asthma-related traits. Asthma genomic research for treatable traits has uncovered novel and previously reported asthma loci, primarily through studies in Europeans. Novel genomic findings for asthma phenotypes and related traits may arise from multi-trait and specific phenotyping strategies in diverse populations.

Epigenome-wide association studies of allergic disease and the environment

The epigenome is at the intersection of the environment, genotype, and cellular response. DNA methylation of cytosine nucleotides, the most studied epigenetic modification, has been systematically evaluated in human studies by using untargeted epigenome-wide association studies (EWASs) and shown to be both sensitive to environmental exposures and associated with allergic diseases. In this narrative review, we summarize findings from key EWASs previously conducted on this topic; interpret results from recent studies; and discuss the strengths, challenges, and opportunities regarding epigenetics research on the environment-allergy relationship. The majority of these EWASs have systematically investigated select environmental exposures during the prenatal and early childhood periods and allergy-associated epigenetic changes in leukocyte-isolated DNA and more recently in nasal cells. Overall, many studies have found consistent DNA methylation associations across cohorts for certain exposures, such as smoking (eg, aryl hydrocarbon receptor repressor gene [AHRR] gene), and allergic diseases (eg, EPX gene). We recommend the integration of both environmental exposures and allergy or asthma within long-term prospective designs to strengthen causality as well as biomarker development. Future studies should collect paired target tissues to examine compartment-specific epigenetic responses, incorporate genetic influences in DNA methylation (methylation quantitative trait locus), replicate findings across diverse populations, and carefully interpret epigenetic signatures from bulk, target tissue or isolated cells.

Epigenome-wide DNA methylation association study of circulating IgE levels identifies novel targets for asthma

BACKGROUND

Identifying novel epigenetic signatures associated with serum immunoglobulin E (IgE) may improve our understanding of molecular mechanisms underlying asthma and IgE-mediated diseases.

METHODS

We performed an epigenome-wide association study using whole blood from Framingham Heart Study (FHS; n = 3,471, 46% females) participants and validated results using the Childhood Asthma Management Program (CAMP; n = 674, 39% females) and the Genetic Epidemiology of Asthma in Costa Rica Study (CRA; n = 787, 41% females). Using the closest gene to each IgE-associated CpG, we highlighted biologically plausible pathways underlying IgE regulation and analyzed the transcription patterns linked to IgE-associated CpGs (expression quantitative trait methylation loci; eQTMs). Using prior UK Biobank summary data from genome-wide association studies of asthma and allergy, we performed Mendelian randomization (MR) for causal inference testing using the IgE-associated CpGs from FHS with methylation quantitative trait loci (mQTLs) as instrumental variables.

FINDINGS

We identified 490 statistically significant differentially methylated CpGs associated with IgE in FHS, of which 193 (39.3%) replicated in CAMP and CRA (FDR < 0.05). Gene ontology analysis revealed enrichment in pathways related to transcription factor binding, asthma, and other immunological processes. eQTM analysis identified 124 cis-eQTMs for 106 expressed genes (FDR < 0.05). MR in combination with drug-target analysis revealed CTSB and USP20 as putatively causal regulators of IgE levels (Bonferroni adjusted P < 7.94E-04) that can be explored as potential therapeutic targets.

INTERPRETATION

By integrating eQTM and MR analyses in general and clinical asthma populations, our findings provide a deeper understanding of the multidimensional inter-relations of DNA methylation, gene expression, and IgE levels.

FUNDING

US NIH/NHLBI grants: P01HL132825, K99HL159234. N01-HC-25195 and HHSN268201500001I.

A functional genomics pipeline to identify high-value asthma and allergy CpGs in the human methylome

BACKGROUND

DNA methylation of cytosines at cytosine-phosphate-guanine (CpG) dinucleotides (CpGs) is a widespread epigenetic mark, but genome-wide variation has been relatively unexplored due to the limited representation of variable CpGs on commercial high-throughput arrays.

OBJECTIVES

To explore this hidden portion of the epigenome, this study combined whole-genome bisulfite sequencing with in silico evidence of gene regulatory regions to design a custom array of high-value CpGs. This study focused on airway epithelial cells from children with and without allergic asthma because these cells mediate the effects of inhaled microbes, pollution, and allergens on asthma and allergic disease risk.

METHODS

This study identified differentially methylated regions from whole-genome bisulfite sequencing in nasal epithelial cell DNA from a total of 39 children with and without allergic asthma of both European and African ancestries. This study selected CpGs from differentially methylated regions, previous allergy or asthma epigenome-wide association studies (EWAS), or genome-wide association study loci, and overlapped them with functional annotations for inclusion on a custom Asthma&Allergy array. This study used both the custom and EPIC arrays to perform EWAS of allergic sensitization (AS) in nasal epithelial cell DNA from children in the URECA (Urban Environment and Childhood Asthma) birth cohort and using the custom array in the INSPIRE [Infant Susceptibility to Pulmonary Infections and Asthma Following RSV Exposure] birth cohort. Each CpG on the arrays was assigned to its nearest gene and its promotor capture Hi-C interacting gene and performed expression quantitative trait methylation (eQTM) studies for both sets of genes.

RESULTS

Custom array CpGs were enriched for intermediate methylation levels compared to EPIC CpGs. Intermediate methylation CpGs were further enriched among those associated with AS and for eQTMs on both arrays.

CONCLUSIONS

This study revealed signature features of high-value CpGs and evidence for epigenetic regulation of genes at AS EWAS loci that are robust to race/ethnicity, ascertainment, age, and geography.

meQTL mapping in the GENOA study reveals genetic determinants of DNA methylation in African Americans

Identifying genetic variants that are associated with variation in DNA methylation, an analysis commonly referred to as methylation quantitative trait locus (meQTL) mapping, is an important first step towards understanding the genetic architecture underlying epigenetic variation. Most existing meQTL mapping studies have focused on individuals of European ancestry and are underrepresented in other populations, with a particular absence of large studies in populations with African ancestry. We fill this critical knowledge gap by performing a large-scale cis-meQTL mapping study in 961 African Americans from the Genetic Epidemiology Network of Arteriopathy (GENOA) study. We identify a total of 4,565,687 cis-acting meQTLs in 320,965 meCpGs. We find that 45% of meCpGs harbor multiple independent meQTLs, suggesting potential polygenic genetic architecture underlying methylation variation. A large percentage of the cis-meQTLs also colocalize with cis-expression QTLs (eQTLs) in the same population. Importantly, the identified cis-meQTLs explain a substantial proportion (median = 24.6%) of methylation variation. In addition, the cis-meQTL associated CpG sites mediate a substantial proportion (median = 24.9%) of SNP effects underlying gene expression. Overall, our results represent an important step toward revealing the co-regulation of methylation and gene expression, facilitating the functional interpretation of epigenetic and gene regulation underlying common diseases in African Americans.

Decoding the genetic and epigenetic basis of asthma

Asthma is a complex and heterogeneous chronic inflammatory disease of the airways. Alongside environmental factors, asthma susceptibility is strongly influenced by genetics. Given its high prevalence and our incomplete understanding of the mechanisms underlying disease susceptibility, asthma is frequently studied in genome-wide association studies (GWAS), which have identified thousands of genetic variants associated with asthma development. Virtually all these genetic variants reside in non-coding genomic regions, which has obscured the functional impact of asthma-associated variants and their translation into disease-relevant mechanisms. Recent advances in genomics technology and epigenetics now offer methods to link genetic variants to gene regulatory elements embedded within non-coding regions, which have started to unravel the molecular mechanisms underlying the complex (epi)genetics of asthma. Here, we provide an integrated overview of (epi)genetic variants associated with asthma, focusing on efforts to link these disease associations to biological insight into asthma pathophysiology using state-of-the-art genomics methodology. Finally, we provide a perspective as to how decoding the genetic and epigenetic basis of asthma has the potential to transform clinical management of asthma and to predict the risk of asthma development.

Incorporating genetics in identifying peanut allergy risk and tailoring allergen immunotherapy: A perspective on the genetic findings from the LEAP trial

Examining the genetics of peanut allergy (PA) in the context of clinical trial interventions and outcomes provides an opportunity to not only understand gene-environment interactions for PA risk but to also understand the benefit of allergen immunotherapy. A consistent theme in the genetics of food allergy is that in keeping with the dual allergen exposure hypothesis, barrier- and immune-related genes are most commonly implicated in food allergy and tolerance. With a focus on PA, we review how genetic risk factors across 3 genes (FLG, MALT1, and HLA-DQA1) have helped delineate distinct allergic characteristics and outcomes in the context of environmental interventions in the Learning Early about Peanut Allergy (LEAP) study and other clinical trials. We specifically consider and present a framework for genetic risk prediction for the development of PA and discuss how genetics, age, and oral consumption intertwine to predict PA outcome. Although there is some promise in this proposed framework, a better understanding of the mechanistic pathways by which PA develops and persists is needed to develop targeted therapeutics for established disease. Only by understanding the mechanisms by which PA develops, persists, and resolves can we identify adjuvants to oral immunotherapy to make older children and adults immunologically similar to their younger, more malleable counterparts and thus more likely to achieve long-term tolerance.

DNA methylation QTL mapping across diverse human tissues provides molecular links between genetic variation and complex traits

Studies of DNA methylation (DNAm) in solid human tissues are relatively scarce; tissue-specific characterization of DNAm is needed to understand its role in gene regulation and its relevance to complex traits. We generated array-based DNAm profiles for 987 human samples from the Genotype-Tissue Expression (GTEx) project, representing 9 tissue types and 424 subjects. We characterized methylome and transcriptome correlations (eQTMs), genetic regulation in cis (mQTLs and eQTLs) across tissues and e/mQTLs links to complex traits. We identified mQTLs for 286,152 CpG sites, many of which (>5%) show tissue specificity, and mQTL colocalizations with 2,254 distinct GWAS hits across 83 traits. For 91% of these loci, a candidate gene link was identified by integration of functional maps, including eQTMs, and/or eQTL colocalization, but only 33% of loci involved an eQTL and mQTL present in the same tissue type. With this DNAm-focused integrative analysis, we contribute to the understanding of molecular regulatory mechanisms in human tissues and their impact on complex traits.

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.

Application of Bayesian genomic prediction methods to genome-wide association analyses

Background

Bayesian genomic prediction methods were developed to simultaneously fit all genotyped markers to a set of available phenotypes for prediction of breeding values for quantitative traits, allowing for differences in the genetic architecture (distribution of marker effects) of traits. These methods also provide a flexible and reliable framework for genome-wide association (GWA) studies. The objective here was to review developments in Bayesian hierarchical and variable selection models for GWA analyses.

Results

By fitting all genotyped markers simultaneously, Bayesian GWA methods implicitly account for population structure and the multiple-testing problem of classical single-marker GWA. Implemented using Markov chain Monte Carlo methods, Bayesian GWA methods allow for control of error rates using probabilities obtained from posterior distributions. Power of GWA studies using Bayesian methods can be enhanced by using informative priors based on previous association studies, gene expression analyses, or functional annotation information. Applied to multiple traits, Bayesian GWA analyses can give insight into pleiotropic effects by multi-trait, structural equation, or graphical models. Bayesian methods can also be used to combine genomic, transcriptomic, proteomic, and other -omics data to infer causal genotype to phenotype relationships and to suggest external interventions that can improve performance.

Conclusions

Bayesian hierarchical and variable selection methods provide a unified and powerful framework for genomic prediction, GWA, integration of prior information, and integration of information from other -omics platforms to identify causal mutations for complex quantitative traits.

Multi-Omics Profiling Approach to Asthma: An Evolving Paradigm

Asthma is a complex multifactorial and heterogeneous respiratory disease. Although genetics is a strong risk factor of asthma, external and internal exposures and their interactions with genetic factors also play important roles in the pathophysiology of asthma. Over the past decades, the application of high-throughput omics approaches has emerged and been applied to the field of asthma research for screening biomarkers such as genes, transcript, proteins, and metabolites in an unbiased fashion. Leveraging large-scale studies representative of diverse population-based omics data and integrating with clinical data has led to better profiling of asthma risk. Yet, to date, no omic-driven endotypes have been translated into clinical practice and management of asthma. In this article, we provide an overview of the current status of omics studies of asthma, namely, genomics, transcriptomics, epigenomics, proteomics, exposomics, and metabolomics. The current development of the multi-omics integrations of asthma is also briefly discussed. Biomarker discovery following multi-omics profiling could be challenging but useful for better disease phenotyping and endotyping that can translate into advances in asthma management and clinical care, ultimately leading to successful precision medicine approaches.