Allergy-specific Phenome-Wide Association Study for Immunogenes in Turkish Children

Gut-lung axis and asthma: A historical review on mechanism and future perspective

BACKGROUND

Gut microbiota are closely related to the development and regulation of the host immune system by regulating the maturation of immune cells and the resistance to pathogens, which affects the host immunity. Early use of antibiotics disrupts the homeostasis of gut microbiota and increases the risk of asthma. Gut microbiota actively interact with the host immune system via the gut-lung axis, a bidirectional communication pathway between the gut and lung. The manipulation of gut microbiota through probiotics, helminth therapy, and fecal microbiota transplantation (FMT) to combat asthma has become a hot research topic. BODY: This review mainly describes the current immune pathogenesis of asthma, gut microbiota and the role of the gut-lung axis in asthma. Moreover, the potential of manipulating the gut microbiota and its metabolites as a treatment strategy for asthma has been discussed.

CONCLUSION

The gut-lung axis has a bidirectional effect on asthma. Gut microecology imbalance contributes to asthma through bacterial structural components and metabolites. Asthma, in turn, can also cause intestinal damage through inflammation throughout the body. The manipulation of gut microbiota through probiotics, helminth therapy, and FMT can inform the treatment strategies for asthma by regulating the maturation of immune cells and the resistance to pathogens.

Toward Precision Medicine in Atopic Dermatitis Using Molecular-Based Approaches

Atopic dermatitis is the most common chronic inflammatory skin disorder, affecting up to 20% of children and 10% of adults in developed countries. The pathophysiology of atopic dermatitis is complex and involves a strong genetic predisposition and T-cell driven inflammation. Although our understanding of the pathology and drivers of this disease has improved in recent years, there are still knowledge gaps in the immune pathways involved. Therefore, advances in new omics technologies in atopic dermatitis will play a key role in understanding the pathogenesis of this burden disease and could develop preventive strategies and personalized treatment strategies. In this review, we discuss the latest developments in genetics, transcriptomics, epigenomics, proteomics, and metagenomics and understand how integrating multiple omics datasets will identify potential biomarkers and uncover nets of associations between several molecular levels.

Toward Precision Medicine in Atopic Dermatitis Using Molecular-Based Approaches

Atopic dermatitis is the most common chronic inflammatory skin disorder, affecting up to 20% of children and 10% of adults in developed countries. The pathophysiology of atopic dermatitis is complex and involves a strong genetic predisposition and T-cell driven inflammation. Although our understanding of the pathology and drivers of this disease has improved in recent years, there are still knowledge gaps in the immune pathways involved. Therefore, advances in new omics technologies in atopic dermatitis will play a key role in understanding the pathogenesis of this burden disease and could develop preventive strategies and personalized treatment strategies. In this review, we discuss the latest developments in genetics, transcriptomics, epigenomics, proteomics, and metagenomics and understand how integrating multiple omics datasets will identify potential biomarkers and uncover nets of associations between several molecular levels.

The Association of IgE Levels with ADAM33 Genetic Polymorphisms among Asthmatic Patients

Total serum immunoglobulin E (IgE) is elevated in multiple allergic diseases and is considered a good predictor of atopy. Several studies have been performed on the association of IgE levels with the polymorphism of the ADAM33 gene in asthmatic patients. The aim of this study was to determine whether there is an association between IgE levels and the genetic polymorphisms of the ADAM33 gene (T1, T2, T + 1, V4, S1, S2, and Q-1) in both healthy and asthmatic patients among Jordanians. The clinical data were collected for this case–control study from 267 asthmatic patients and 225 control subjects. Seven genetic polymorphisms (T1, T2, T + 1, V4, S1, S2, and Q-1) of the gene ADAM33 were analyzed using the polymerase chain reaction/restriction fragment length polymorphism method. The minor alleles (G) of T1, (A) of T2, T + 1, and (G) of V4 polymorphisms were associated with a significant increase in total serum IgE levels in adults but not children. The V4 genetic polymorphism, however, showed a significant association with IgE levels in both adults and children. The S1 polymorphism was significantly associated with the codominant module only in the adults. The S2 polymorphism showed a significant association (p-value < 0.05) in both codominant and recessive models. However, in the dominant model for both pediatric control and asthmatic patients, the association between the IgE and S2 polymorphism was insignificant (p-value = 0.7271 and 0.5259, respectively). This study found a statistically significant association between multiple ADAM33 genetic polymorphisms and IgE levels. Such findings add to the growing evidence that the ADAM33 gene has a major impact on IgE levels among asthmatic patients of Jordanian origin.

Genetics and Epigenetics of Atopic Dermatitis: An Updated Systematic Review

BACKGROUND

Atopic dermatitis is a common inflammatory skin disorder that affects up to 15-20% of the population and is characterized by recurrent eczematous lesions with intense itching. As a heterogeneous disease, multiple factors have been suggested to explain the nature of atopic dermatitis (AD), and its high prevalence makes it necessary to periodically compile and update the new information available. In this systematic review, the focus is set at the genetic and epigenetic studies carried out in the last years.

METHODS

A systematic literature review was conducted in three scientific publication databases (PubMed, Cochrane Library, and Scopus). The search was restricted to publications indexed from July 2016 to December 2019, and keywords related to atopic dermatitis genetics and epigenetics were used.

RESULTS

A total of 73 original papers met the inclusion criteria established, including 9 epigenetic studies. A total of 62 genes and 5 intergenic regions were described as associated with AD.

CONCLUSION

Filaggrin (FLG) polymorphisms are confirmed as key genetic determinants for AD development, but also epigenetic regulation and other genes with functions mainly related to the immune system and extracellular matrix, reinforcing the notion of skin homeostasis breakage in AD.

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.

Phenotypic and Molecular Characterization of Risk Loci Associated With Asthma and Lung Function

Purpose

Respiratory diseases have a highly multifactorial etiology where different mechanisms contribute to the individual's susceptibility. We conducted a deep characterization of loci associated with asthma and lung function by previous genome-wide association studies (GWAS).

Methods

Sixteen variants were selected from previous GWAS of childhood/adult asthma and pulmonary function tests. We conducted a phenome-wide association study of these loci in 4,083 traits assessed in the UK Biobank (n = 361,194 participants). Data from the Genotype-Tissue Expression (GTEx) project were used to conduct a transcriptomic analysis with respect to tissues relevant for asthma pathogenesis. A pediatric cohort assessed with the International Study of Asthma and Allergies in Children (ISAAC) Phase II tools was used to further explore the association of these variants with 116 traits related to asthma comorbidities.

Results

Our phenome-wide association studies (PheWAS) identified 206 phenotypic associations with respect to the 16 variants identified. In addition to the replication of the phenotypes tested in the discovery GWAS, we observed novel associations related to blood levels of immune cells (eosinophils, neutrophils, monocytes, and lymphocytes) for the asthma-related variants. Conversely, the lung-function variants were associated with phenotypes related to body fat mass. In the ISAAC-assessed cohort, we observed that risk alleles associated with increased fat mass can exacerbate allergic reactions in individuals affected by allergic respiratory diseases. The GTEx-based analysis showed that the variants tested affect the transcriptomic regulation of multiple surrounding genes across several tissues.

Conclusions

This study generated novel data regarding the genetics of respiratory diseases and their comorbidities, providing a deep characterization of loci associated with asthma and lung function.

Identification of Novel Biomarkers for Drug Hypersensitivity After Sequencing of the Promoter Area in 16 Genes of the Vitamin D Pathway and the High-Affinity IgE Receptor

The prevalence of allergic diseases and drug hypersensitivity reactions (DHRs) during recent years is increasing. Both, allergic diseases and DHRs seem to be related to an interplay between environmental factors and genetic susceptibility. In recent years, a large effort in the elucidation of the genetic mechanisms involved in these disorders has been made, mostly based on case-control studies, and typically focusing on isolated SNPs. These studies provide a limited amount of information, which now can be greatly expanded by the complete coverage that Next Generation Sequencing techniques offer. In this study, we analyzed the promoters of sixteen genes related to the Vitamin D pathway and the high-affinity IgE receptor, including FCER1A, MS4A2, FCER1G, VDR, GC, CYP2R1, CYP27A1, CYP27B1, CYP24A1, RXRA, RXRB, RXRG, IL4, IL4R, IL13, and IL13RA1. The study group was composed of patients with allergic rhinitis plus asthma (AR+A), patients with hypersensitivity to beta-lactams (BLs), to NSAIDs including selective hypersensitivity (SH) and cross-reactivity (CR), and healthy controls without antecedents of atopy or adverse drug reactions. We identified 148 gene variations, 43 of which were novel. Multinomial analyses revealed that three SNPs corresponding to the genes FCER1G (rs36233990 and rs2070901), and GC (rs3733359), displayed significant associations and, therefore, were selected for a combined dataset study in a cohort of 2,476 individuals. The strongest association was found with the promoter FCER1G rs36233990 SNP that alters a transcription factor binding site. This SNP was over-represented among AR+A patients and among patients with IgE-mediated diseases, as compared with control individuals or with the rest of patients in this study. Classification models based on the above-mentioned SNPs were able to predict correct clinical group allocations in patients with DHRs, and patients with IgE-mediated DHRs. Our findings reveal gene promoter SNPs that are significant predictors of drug hypersensitivity, thus reinforcing the hypothesis of a genetic predisposition for these diseases.

Phenomic Impact of Genetically-Determined Euthyroid Function and Molecular Differences between Thyroid Disorders

BACKGROUND

The thyroid plays a key role in development and homeostasis, but it has been difficult to establish causality with diseases and phenotypic traits because of several potential confounders.

METHODS

To determine the causal effect of euthyroid function, we conducted a two-sample Mendelian randomization study of euthyroid thyrotropin (TSH) and free thyroxine (FT4) levels with respect to 2419 traits assessed in 337,199 individuals from UK Biobank. Additionally, we investigated the molecular differences between hypothyroidism and hyperthyroidism using genome-wide data.

RESULTS

After multiple testing correction, sixteen traits appear to be affected by genetically-determined euthyroid TSH, including multiple thyroid-related traits, e.g., hypothyroidism (p = 2.39 × 10-17), height (p = 2.76 × 10-10), body fat distribution (impedance of whole body, p = 4.43 × 10-8), pulse rate (p = 2.84 × 10-8), female infertility (p = 4.91 × 10-6), and hearing aid use (p = 7.10 × 10-5). Moreover, we found a consistent genetic correlation between hypothyroidism and hyperthyroidism (rg = 0.45, p = 5.45 × 10-6) with several immune pathways shared between these diseases. Two molecular pathways survived multiple testing correction for specificity to hyperthyroidism, JAK/STAT signaling (p = 1.02 × 10-6) and Rac guanyl-nucleotide exchange factor activity (p = 4.39 × 10-6).

CONCLUSION

Our data shed new light on the inter-individual variability of euthyroid function and the molecular mechanisms of the two thyroid disorders investigated.

Gut Microbiota and Mucosal Immunity in the Neonate

Gut microbiota colonization is a complex, dynamic, and step-wise process that is in constant development during the first years of life. This microbial settlement occurs in parallel with the maturation of the immune system, and alterations during this period, due to environmental and host factors, are considered to be potential determinants of health-outcomes later in life. Given that host–microbe interactions are mediated by the immune system response, it is important to understand the close relationship between immunity and the microbiota during birth, lactation, and early infancy. This work summarizes the evidence to date on early gut microbiota colonization, and how it influences the maturation of the infant immune system and health during the first 1000 days of life. This review will also address the influence of perinatal antibiotic intake and the importance of delivery mode and breastfeeding for an appropriate development of gut immunity.

A simulation study investigating power estimates in phenome-wide association studies

Background

Phenome-wide association studies (PheWAS) are a high-throughput approach to evaluate comprehensive associations between genetic variants and a wide range of phenotypic measures. PheWAS has varying sample sizes for quantitative traits, and variable numbers of cases and controls for binary traits across the many phenotypes of interest, which can affect the statistical power to detect associations. The motivation of this study is to investigate the various parameters which affect the estimation of statistical power in PheWAS, including sample size, case-control ratio, minor allele frequency, and disease penetrance.

Results

We performed a PheWAS simulation study, where we investigated variations in statistical power based on different parameters, such as overall sample size, number of cases, case-control ratio, minor allele frequency, and disease penetrance. The simulation was performed on both binary and quantitative phenotypic measures. Our simulation on binary traits suggests that the number of cases has more impact on statistical power than the case to control ratio; also, we found that a sample size of 200 cases or more maintains the statistical power to identify associations for common variants. For quantitative traits, a sample size of 1000 or more individuals performed best in the power calculations. We focused on common genetic variants (MAF > 0.01) in this study; however, in future studies, we will be extending this effort to perform similar simulations on rare variants.

Conclusions

This study provides a series of PheWAS simulation analyses that can be used to estimate statistical power for some potential scenarios. These results can be used to provide guidelines for appropriate study design for future PheWAS analyses.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2135-0) contains supplementary material, which is available to authorized users.

Current Scope and Challenges in Phenome-Wide Association Studies

PURPOSE OF REVIEW

Over many decades, researchers have been designing studies to investigate the relationship between genotypes and phenotypes to gain an understanding about the effect of genetics on disease. Recently, a high-throughput approach called phenome-wide associations studies (PheWAS) have been extensively used to identify associations between genetic variants and many diseases and traits simultaneously. In this review, we describe the value of PheWAS along with methodological issues and challenges in interpretation for current applications of PheWAS.

RECENT FINDINGS

PheWAS have uncovered a paradigm to identify new associations for genetic loci across many diseases. The application of PheWAS have been effective with phenotype data from electronic health records, epidemiological studies, and clinical trials data.

SUMMARY

The key strength of a PheWAS is to identify the association of one or more genetic variants with multiple phenotypes, which can showcase interconnections among the phenotypes due to shared genetic associations. While the PheWAS approach appears promising, there are a number of challenges that need to be addressed to provide additional robustness to PheWAS findings.

The association between MICA/MICB polymorphism and respiratory syncytial virus infection in children

MICA/MICB gene polymorphisms are related to several cancers and infectious diseases, but there are no reports on the association between MICA/MICB gene polymorphisms and respiratory syncytial virus (RSV) infection. To clarify the association between MICA/MICB gene polymorphisms and infection of RSV in children, we collected fresh blood samples from paediatric patients with and without pneumonia after RSV infection. The MICA/MICB alleles were characterized by PCR sequence-specific primers (PCR-SSP) and PCR sequence-based genotyping (PCR-SBT), and then, the frequency of the MICA/MICB alleles and haplotypes was calculated. The results showed that the frequencies of MICA*002:01 and MICA-A9 in RSV-infected patients were significantly lower than in controls (9% vs. 20%, pc = 0.04). The allele frequency of MICA*002:01 in pneumonia patients (8%) and nonpneumonia patients (9%) was significantly lower than in controls (20%, pc = 0.02). MICA*002:01-MICB*008(Δrel = 0.616), MICA*009-MICB*016 (Δrel = 0.506), and MICA*045-MICB*014 (Δrel = 0.700) showed linkage disequilibrium in patients infected with RSV. The haplotype frequency of MICA*002:01-MICB*005:02 in RSV-infected patients was significantly lower than in controls (10% vs. 16%, pc = 0.033). In conclusion, allele MICA*002:01/A9 and haplotype MICA*002:01-MICB*005:02 were negatively associated with RSV respiratory tract infections.

Phenome-wide association study for CYP2A6 alleles: rs113288603 is associated with hearing loss symptoms in elderly smokers

To identify novel phenotypic associations related to Cytochrome P450 Family 2 Subfamily A Member 6 (CYP2A6), we investigated the human phenome in a total of 11,271 individuals. Initially, we conducted a phenome-wide association study in 3,401 nicotine-exposed elderly subjects considering 358 phenotypic traits. We identified a significant association between CYP2A6 rs113288603 and hearing loss symptoms (p = 5.75 × 10⁻⁵). No association was observed in a sample of 3,245 nicotine-unexposed individuals from the same discovery cohort, consistent with the conclusion that the finding is related to CYP2A6 involvement in nicotine metabolism. Consistent results were obtained (p < 0.1) in an independent sample of 2,077 nicotine-exposed elderly subjects, and similarly, no significance was observed in the nicotine-unexposed sample (n = 2,548) of the replication cohort. Additional supporting evidence for this association was provided by gene expression data: rs113288603 is associated with increased CYP2A6 expression in cerebellar hemispheres (p = 7.8 × 10⁻⁴). There is a well-known correlation between smoking and age-related hearing loss. Cigarette smoking is associated with structural changes in the brain and CYP2A6 mediates these changes. In this context, the regulatory role of rs113288603 in cerebellum appears to be consistent with the known involvement of this brain region in auditory function.