Asthma epigenetics

Early Prediction of Asthma

The clinical manifestations of asthma in children are highly variable, are associated with different molecular and cellular mechanisms, and are characterized by common symptoms that may diversify in frequency and intensity throughout life. It is a disease that generally begins in the first five years of life, and it is essential to promptly identify patients at high risk of developing asthma by using different prediction models. The aim of this review regarding the early prediction of asthma is to summarize predictive factors for the course of asthma, including lung function, allergic comorbidity, and relevant data from the patient's medical history, among other factors. This review also highlights the epigenetic factors that are involved, such as DNA methylation and asthma risk, microRNA expression, and histone modification. The different tools that have been developed in recent years for use in asthma prediction, including machine learning approaches, are presented and compared. In this review, emphasis is placed on molecular mechanisms and biomarkers that can be used as predictors of asthma in children.

Pathogenesis of allergic diseases and implications for therapeutic interventions

Allergic diseases such as allergic rhinitis (AR), allergic asthma (AAS), atopic dermatitis (AD), food allergy (FA), and eczema are systemic diseases caused by an impaired immune system. Accompanied by high recurrence rates, the steadily rising incidence rates of these diseases are attracting increasing attention. The pathogenesis of allergic diseases is complex and involves many factors, including maternal-fetal environment, living environment, genetics, epigenetics, and the body's immune status. The pathogenesis of allergic diseases exhibits a marked heterogeneity, with phenotype and endotype defining visible features and associated molecular mechanisms, respectively. With the rapid development of immunology, molecular biology, and biotechnology, many new biological drugs have been designed for the treatment of allergic diseases, including anti-immunoglobulin E (IgE), anti-interleukin (IL)-5, and anti-thymic stromal lymphopoietin (TSLP)/IL-4, to control symptoms. For doctors and scientists, it is becoming more and more important to understand the influencing factors, pathogenesis, and treatment progress of allergic diseases. This review aimed to assess the epidemiology, pathogenesis, and therapeutic interventions of allergic diseases, including AR, AAS, AD, and FA. We hope to help doctors and scientists understand allergic diseases systematically.

Identification of candidate aberrant differentially methylated/expressed genes in asthma

BACKGROUND

Asthma is an important non-communicable disease worldwide. DNA methylation is associated with the occurrence and development of asthma. We are aimed at assuring differential expressed genes (DEGs) modified by aberrantly methylated genes (DMGs) and pathways related to asthma by integrating bioinformatics analysis.

METHODS

One mRNA dataset (GSE64913) and one gene methylation dataset (GSE137716) were selected from the Gene Expression Omnibus (GEO) database. Functional enrichment analysis was performed using GeneCodies 4.0 database. All gene expression matrices were analyzed by Gene set enrichment analysis (GSEA) software. STRING was applied to construct a protein-protein interaction (PPI) network to find the hub genes. Then, electronic validation was performed to verify the hub genes, followed by the evaluation of diagnostic value. Eventually, quantitative real-time polymerase chain reaction (qRT-PCR) was utilized to detect the expression of hub genes.

RESULTS

In total, 14 hypomethylated/high-expression genes and 10 hypermethylated/low-expression genes were obtained in asthma. Among them, 10 hub genes were identified in the PPI network. Functional analysis demonstrated that the differentially methylated/expressed genes were primarily associated with the lung development, cytosol and protein binding. Notably, HLA-DOA was enriched in asthma. FKBP5, WNT5A, TM4SF1, PDK4, EPAS1 and GMPR had potential diagnostic value for asthma.

CONCLUSION

The project explored the pathogenesis of asthma, which may provide a research basis for the prediction and the drug development of asthma.

Genetics and Epigenetics in Asthma

Asthma is one of the most common respiratory disease that affects both children and adults worldwide, with diverse phenotypes and underlying pathogenetic mechanisms poorly understood. As technology in genome sequencing progressed, scientific efforts were made to explain and predict asthma’s complexity and heterogeneity, and genome-wide association studies (GWAS) quickly became the preferred study method. Several gene markers and loci associated with asthma susceptibility, atopic and childhood-onset asthma were identified during the last few decades. Markers near the ORMDL3/GSDMB genes were associated with childhood-onset asthma, interleukin (IL)33 and IL1RL1 SNPs were associated with atopic asthma, and the Thymic Stromal Lymphopoietin (TSLP) gene was identified as protective against the risk to TH2-asthma. The latest efforts and advances in identifying and decoding asthma susceptibility are focused on epigenetics, heritable characteristics that affect gene expression without altering DNA sequence, with DNA methylation being the most described mechanism. Other less studied epigenetic mechanisms include histone modifications and alterations of miR expression. Recent findings suggest that the DNA methylation pattern is tissue and cell-specific. Several studies attempt to describe DNA methylation of different types of cells and tissues of asthmatic patients that regulate airway remodeling, phagocytosis, and other lung functions in asthma. In this review, we attempt to briefly present the latest advancements in the field of genetics and mainly epigenetics concerning asthma susceptibility.

Prospects for Use of Single-Cell Sequencing to Assess DNA Methylation in Asthma

Asthma is a complex disease with an increasing prevalence rate caused by the interaction of multiple genetically inherited and environmental factors. Epigenetics link genetic susceptibility and environmental factors. DNA methylation is an epigenetic modification that plays a crucial role in the regulation of growth and development, gene expression, and disease. Relatively little is known about DNA methylation in asthma, with few studies to date using single-cell sequencing to analyze the molecular mechanism by which DNA methylation regulates asthma. Cells with similar phenotypes may be heterogeneous in function and transcription, as may their genetic information. Although multi-omics methods, such as studies of the genome, transcriptome, and epigenome, can be used to evaluate biological processes, these methods are applicable only to groups of cells or tissues and provide averages that may obscure direct correlations among multiple layers of data. Single-cell sequencing technology can clarify the methylation and expression of genes in different populations of cells, in contrast to traditional multi-omics sequencing, which can determine only average values of cell populations. Single-cell sequence can therefore better reflect the pathogenesis of asthma, as it can clarify the function and regulatory mechanism of DNA methylation in asthma, and detect new genes and molecular markers that may become therapeutic targets in this disease.

Genome‑wide analysis of DNA methylation and gene expression changes in an ovalbumin‑induced asthma mouse model

The aim of the present study was to establish an integrated network of DNA methylation and RNA expression in an ovalbumin (OVA)-induced asthma model, and to investigate the epigenetically-regulated genes involved in asthma development. Genome-wide CpG-DNA methylation profiling was conducted through the use of a methylated DNA immunoprecipitation microarray and RNA sequencing was performed using three lung samples from mice with OVA-induced asthma. A total of 35,401 differentially methylated regions (DMRs) were identified between mice with OVA-induced asthma and control mice. Of these, 3,060 were located in promoter regions and 370 of the genes containing these DMRs demonstrated an inverse correlation between methylation and gene expression. Kyoto Encyclopedia of Genes and Genomes pathway analysis identified that 368 genes were upregulated or downregulated in OVA-induced asthma samples, including genes involved in ‘chemokine signalling pathway’, ‘focal adhesion’, ‘leukocyte transendothelial migration’ and ‘vascular smooth muscle contraction signaling’ pathways. Integrated network analysis identified four hub genes, consisting of three upregulated genes [forkhead box O1 (FOXO1), SP1 transcription factor (SP1) and amyloid β precursor protein (APP)], and one downregulated gene [RUNX family transcription factor 1 (RUNX1)], all of which demonstrated an association between DNA methylation and gene expression. These genes were highly interconnected nodes in the Ingenuity Pathway Analysis module and were functionally significant. A total of four interconnected hub genes, FOXO1, RUNX1, SP1 and APP, were identified from the integrated DNA methylation and gene expression networks involved in asthma development. These results suggested that modulating these four genes could effectively control the development of asthma.

Association of two polymorphisms of miRNA-146a rs2910164 (G > C) and miRNA-499 rs3746444 (T > C) with asthma: a meta-analysis

OBJECTIVE

To conduct a meta-analysis to determine the association between two single nucleotide polymorphisms (SNPs) miRNA146a rs2910164 (G > C) and miRNA-499 rs3746444 (T > C) and asthma risk.

DATA SOURCES

PubMed and Embase (updated May 17, 2019).

KEYWORDS

(microRNA OR microRNAs) AND (polymorphism OR polymorphisms) AND (Asthmas OR Bronchial Asthma OR Asthma, Bronchial).

RESULTS

Six eligible case-control studies (2441 asthma cases and 3044 controls) met our inclusion criteria. A trend of increased asthma risk was indicated by the heterozygote model (miR-499: TC versus TT, OR = 1.38, 95% CI = 1.06-1.79, P < 0.01) and the dominant model (miR-499: TC + CC versus TT, OR = 1.60, 95% CI = 1.07-2.39, P < 0.01) of miRNA-499 rs3746444. Polymorphisms rs2910164 in miRNA-146a of the allele model (miR-146a: C versus G, OR = 0.84, 95% CI = 0.74-0.96, P = 0.238), homozygote model (miR-146a: CC versus GG, OR = 0.68, 95% CI = 0.51-0.91, P = 0.213), recessive model (miR-146a: CC versus GC + GG, OR = 0.75, 95% CI = 0.60-0.94, P = 0.149) indicated a decreased risk of asthma.

CONCLUSIONS

The miR-499 rs3746444 (T > C) polymorphism is associated with asthma susceptibility and miRNA-146a rs2910164 (G > C) polymorphism has a protective role against susceptibility to asthma.

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.

Histone modifications and their role in epigenetics of atopy and allergic diseases

This review covers basic aspects of histone modification and the role of posttranslational histone modifications in the development of allergic diseases, including the immune mechanisms underlying this development. Together with DNA methylation, histone modifications (including histone acetylation, methylation, phosphorylation, ubiquitination, etc.) represent the classical epigenetic mechanisms. However, much less attention has been given to histone modifications than to DNA methylation in the context of allergy. A systematic review of the literature was undertaken to provide an unbiased and comprehensive update on the involvement of histone modifications in allergy and the mechanisms underlying this development. In addition to covering the growing interest in the contribution of histone modifications in regulating the development of allergic diseases, this review summarizes some of the evidence supporting this contribution. There are at least two levels at which the role of histone modifications is manifested. One is the regulation of cells that contribute to the allergic inflammation (T cells and macrophages) and those that participate in airway remodeling [(myo-) fibroblasts]. The other is the direct association between histone modifications and allergic phenotypes. Inhibitors of histone-modifying enzymes may potentially be used as anti-allergic drugs. Furthermore, epigenetic patterns may provide novel tools in the diagnosis of allergic disorders.

Small-Magnitude Effect Sizes in Epigenetic End Points are Important in Children's Environmental Health Studies: The Children's Environmental Health and Disease Prevention Research Center's Epigenetics Working Group

BACKGROUND

Characterization of the epigenome is a primary interest for children's environmental health researchers studying the environmental influences on human populations, particularly those studying the role of pregnancy and early-life exposures on later-in-life health outcomes.

OBJECTIVES

Our objective was to consider the state of the science in environmental epigenetics research and to focus on DNA methylation and the collective observations of many studies being conducted within the Children's Environmental Health and Disease Prevention Research Centers, as they relate to the Developmental Origins of Health and Disease (DOHaD) hypothesis.

METHODS

We address the current laboratory and statistical tools available for epigenetic analyses, discuss methods for validation and interpretation of findings, particularly when magnitudes of effect are small, question the functional relevance of findings, and discuss the future for environmental epigenetics research.

DISCUSSION

A common finding in environmental epigenetic studies is the small-magnitude epigenetic effect sizes that result from such exposures. Although it is reasonable and necessary that we question the relevance of such small effects, we present examples in which small effects persist and have been replicated across populations and across time. We encourage a critical discourse on the interpretation of such small changes and further research on their functional relevance for children's health.

CONCLUSION

The dynamic nature of the epigenome will require an emphasis on future longitudinal studies in which the epigenome is profiled over time, over changing environmental exposures, and over generations to better understand the multiple ways in which the epigenome may respond to environmental stimuli.

Association between histone hyperacetylation status in memory T lymphocytes and allergen-induced eosinophilic airway inflammation

BACKGROUND AND OBJECTIVE

T lymphocytes, which are characterized by longevity and immune memory, play an important role in airway inflammation in asthma. Here, we assessed the association between immune memory and histone deacetylation and/or acetylation status.

METHODS

CD4 + CD45RB(low) cells (memory T (Tm)) obtained from the spleens of asthma mice models were co-cultured with glucocorticoids (GCs), trichostatin A (TSA) or anacardic acid (AA) and adoptively transferred to naïve mice. Interleukin (IL)-4, 5 and 13 and IFN-γ concentrations were measured in culture supernatants and bronchoalveolar lavage fluid (BALF). Histone deacetylase (HDAC) and histone acetyltransferase (HAT) activities and the expression of T-bet, GATA-3, HDACs 1-11 and alveolar eosinophilic inflammation index (AEII) were determined in lung tissues.

RESULTS

Culture supernatants and the BALF showed similar cytokine profiles. AA and GCs significantly inhibited HAT activity (P = 0.002 and P = 0.018), whereas TSA inhibited and GCs promoted HDAC activity (P = 0.004 and P = 0.025). HDACs 7, 9 and 10 were upregulated by AA and GCs (all P < 0.032), while HDAC11 was upregulated by GCs (P = 0.028). GC-induced inhibition of Tm histone acetylation alleviated AEII by downregulating IL-4, 5 and 13, similar to the effect of AA.

CONCLUSION

Histone hyperacetylation status induced by low expression of HDACs 7, 9 and 10 in allergen-specific Tm cells contributes to eosinophilic airway inflammation. The mechanism by which GCs improve airway inflammation involves the upregulation of HDACs 7, 9, 10 and 11 and especially HDAC-10. The role of individual HDACs and AA as novel therapeutic agents for allergic asthma needs to be explored in the future.

Systems biology of asthma and allergic diseases: a multiscale approach

Systems biology is an approach to understanding living systems that focuses on modeling diverse types of high-dimensional interactions to develop a more comprehensive understanding of complex phenotypes manifested by the system. High-throughput molecular, cellular, and physiologic profiling of populations is coupled with bioinformatic and computational techniques to identify new functional roles for genes, regulatory elements, and metabolites in the context of the molecular networks that define biological processes associated with system physiology. Given the complexity and heterogeneity of asthma and allergic diseases, a systems biology approach is attractive, as it has the potential to model the myriad connections and interdependencies between genetic predisposition, environmental perturbations, regulatory intermediaries, and molecular sequelae that ultimately lead to diverse disease phenotypes and treatment responses across individuals. The increasing availability of high-throughput technologies has enabled system-wide profiling of the genome, transcriptome, epigenome, microbiome, and metabolome, providing fodder for systems biology approaches to examine asthma and allergy at a more holistic level. In this article we review the technologies and approaches for system-wide profiling, as well as their more recent applications to asthma and allergy. We discuss approaches for integrating multiscale data through network analyses and provide perspective on how individually captured health profiles will contribute to more accurate systems biology views of asthma and allergy.