Asthma and allergy are common conditions with complex etiologies involving both genetic and environmental contributions. Recent genome‐wide association studies (GWAS) and meta‐analyses of GWAS have ...begun to shed light on both common and distinct pathways that contribute to asthma and allergic diseases. Associations with variation in genes encoding the epithelial cell‐derived cytokines, interleukin‐33 (IL‐33) and thymic stromal lymphopoietin (TSLP), and the IL1RL1 gene encoding the IL‐33 receptor, ST2, highlight the central roles for innate immune response pathways that promote the activation and differentiation of T‐helper 2 cells in the pathogenesis of both asthma and allergic diseases. In contrast, variation at the 17q21 asthma locus, encoding the ORMDL3 and GSDML genes, is specifically associated with risk for childhood onset asthma. These and other genetic findings are providing a list of well‐validated asthma and allergy susceptibility genes that are expanding our understanding of the common and unique biological pathways that are dysregulated in these related conditions. Ongoing studies will continue to broaden our understanding of asthma and allergy and unravel the mechanisms for the development of these complex traits.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK
Lessons Learned From GWAS of Asthma Kim, Kyung Won; Ober, Carole
Allergy, asthma & immunology research,
03/2019, Volume:
11, Issue:
2
Journal Article
Peer reviewed
Open access
Asthma is a common complex disease of the airways. Genome-wide association studies (GWASs) of asthma have identified many risk alleles and loci that have been replicated in worldwide populations. ...Although the risk alleles identified by GWAS have small effects and explain only a small portion of prevalence, the discovery of asthma loci can provide an understanding of its genetic architecture and the molecular pathways involved in disease pathogenesis. These discoveries can translate into advances in clinical care by identifying therapeutic targets, preventive strategies and ultimately approaches for personalized medicine. In this review, we summarize results from GWAS of asthma from the past 10 years and the insights gleaned from these discoveries.
Many environmental risk factors for common, complex human diseases have been revealed by epidemiologic studies, but how genotypes at specific loci modulate individual responses to environmental risk ...factors is largely unknown. Gene–environment interactions will be missed in genome-wide association studies and could account for some of the ‘missing heritability’ for these diseases. In this review, we focus on asthma as a model disease for studying gene–environment interactions because of relatively large numbers of candidate gene–environment interactions with asthma risk in the literature. Identifying these interactions using genome-wide approaches poses formidable methodological problems, and elucidating molecular mechanisms for these interactions has been challenging. We suggest that studying gene–environment interactions in animal models, although more tractable, might not be sufficient to shed light on the genetic architecture of human diseases. Lastly, we propose avenues for future studies to find gene–environment interactions.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Childhood-onset and adult-onset asthma differ with respect to severity and comorbidities. Whether they also differ with respect to genetic risk factors has not been previously investigated in large ...samples. The goals of this study were to identify shared and distinct genetic risk loci for childhood-onset and adult-onset asthma, and to identify the genes that might mediate the effects of associated variation.
We did genome-wide and transcriptome-wide studies, using data from the UK Biobank, in individuals with asthma, including adults with childhood-onset asthma (onset before 12 years of age), adults with adult-onset asthma (onset between 26 and 65 years of age), and adults without asthma (controls; aged older than 38 years). We did genome-wide association studies (GWAS) for childhood-onset asthma and adult-onset asthma each compared with shared controls, and for age of asthma onset in all asthma cases, with a genome-wide significance threshold of p<5 × 10
. Enrichment studies determined the tissues in which genes at GWAS loci were most highly expressed, and PrediXcan, a transcriptome-wide gene-based test, was used to identify candidate risk genes.
Of 376 358 British white individuals from the UK Biobank, we included 37 846 with self-reports of doctor-diagnosed asthma: 9433 adults with childhood-onset asthma; 21 564 adults with adult-onset asthma; and an additional 6849 young adults with asthma with onset between 12 and 25 years of age. For the first and second GWAS analyses, 318 237 individuals older than 38 years without asthma were used as controls. We detected 61 independent asthma loci: 23 were childhood-onset specific, one was adult-onset specific, and 37 were shared. 19 loci were associated with age of asthma onset. The most significant asthma-associated locus was at 17q12 (odds ratio 1·406, 95% CI 1·365-1·448; p=1·45 × 10
) in the childhood-onset GWAS. Genes at the childhood onset-specific loci were most highly expressed in skin, blood, and small intestine; genes at the adult onset-specific loci were most highly expressed in lung, blood, small intestine, and spleen. PrediXcan identified 113 unique candidate genes at 22 of the 61 GWAS loci. Single-nucleotide polymorphism-based heritability estimates were more than three times larger for childhood-onset asthma (0·327) than for adult-onset disease (0·098). The onset of disease in childhood was associated with additional genes with relatively large effect sizes, with the largest odds ratio observed at the FLG locus at 1q21.3 (1·970, 95% CI 1·823-2·129).
Genetic risk factors for adult-onset asthma are largely a subset of the genetic risk for childhood-onset asthma but with overall smaller effects, suggesting a greater role for non-genetic risk factors in adult-onset asthma. Combined with gene expression and tissue enrichment patterns, we suggest that the establishment of disease in children is driven more by dysregulated allergy and epithelial barrier function genes, whereas the cause of adult-onset asthma is more lung-centred and environmentally determined, but with immune-mediated mechanisms driving disease progression in both children and adults.
US National Institutes of Health.
This review focuses on genome-wide association studies (GWASs) of asthma and allergic diseases published between January 1, 2018, and June 30, 2019. During this time period, there were 38 GWASs ...reported in 19 articles, including the largest performed to date for many of these conditions. Overall, we learned that childhood-onset asthma is associated with the most independent loci compared with other defined groups of asthma and allergic disease cases; adult-onset asthma and moderate-to-severe asthma are associated with fewer genes, which are largely a subset of those associated with childhood-onset asthma. There is significant genetic overlap between asthma and allergic diseases, particularly with respect to childhood-onset asthma, which involves genes that reflect the importance of barrier function biology, and to HLA region genes, which are the most frequently associated genes overall in both groups of diseases. Although the largest GWASs in African American and Latino/Hispanic populations were reported during this period, they are still significantly underpowered compared with studies reported in populations of European ancestry, highlighting the need for larger studies, particularly in patients with childhood-onset asthma and allergic diseases, in these important populations that carry the greatest burden of disease.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Sexual dimorphism in anatomical, physiological and behavioural traits are characteristics of many vertebrate species. In humans, sexual dimorphism is also observed in the prevalence, course and ...severity of many common diseases, including cardiovascular diseases, autoimmune diseases and asthma. Although sex differences in the endocrine and immune systems probably contribute to these observations, recent studies suggest that sex-specific genetic architecture also influences human phenotypes, including reproductive, physiological and disease traits. It is likely that an underlying mechanism is differential gene regulation in males and females, particularly in sex steroid-responsive genes. Genetic studies that ignore sex-specific effects in their design and interpretation could fail to identify a significant proportion of the genes that contribute to risk for complex diseases.
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DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Asthma is a heterogeneous clinical syndrome that includes subtypes of disease with different underlying causes and disease mechanisms. Asthma is caused by a complex interaction between genes and ...environmental exposures; early-life exposures in particular play an important role. Asthma is also heritable, and a number of susceptibility variants have been discovered in genome-wide association studies, although the known risk alleles explain only a small proportion of the heritability. In this review, we present evidence supporting the hypothesis that focusing on more specific asthma phenotypes, such as childhood asthma with severe exacerbations, and on relevant exposures that are involved in gene-environment interactions (GEIs), such as rhinovirus infections, will improve detection of asthma genes and our understanding of the underlying mechanisms. We will discuss the challenges of considering GEIs and the advantages of studying responses to asthma-associated exposures in clinical birth cohorts, as well as in cell models of GEIs, to dissect the context-specific nature of genotypic risks, to prioritize variants in genome-wide association studies, and to identify pathways involved in pathogenesis in subgroups of patients. We propose that such approaches, in spite of their many challenges, present great opportunities for better understanding of asthma pathogenesis and heterogeneity and, ultimately, for improving prevention and treatment of disease.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Studies in mice and humans have revealed intriguing associations between host genetics and the microbiome. Here we report a 16S rRNA-based analysis of the gut microbiome in 1,126 twin pairs, a subset ...of which was previously reported. Tripling the sample narrowed the confidence intervals around heritability estimates and uncovered additional heritable taxa, some of which are validated in other studies. Repeat sampling of subjects showed heritable taxa to be temporally stable. A candidate gene approach uncovered associations between heritable taxa and genes related to diet, metabolism, and olfaction. We replicate an association between Bifidobacterium and the lactase (LCT) gene locus and identify an association between the host gene ALDH1L1 and the bacteria SHA-98, suggesting a link between formate production and blood pressure. Additional genes detected are involved in barrier defense and self/non-self recognition. Our results indicate that diet-sensing, metabolism, and immune defense are important drivers of human-microbiome co-evolution.
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•16S rRNA-based analysis of the gut microbiome in 1,126 twin pairs•Heritable bacterial taxa are temporally stable•Bifidobacterium associates with lactase gene variants; formate production links to blood pressure•Gene-microbe links involve genes related to diet, metabolism, olfaction, and defense
Does host genotype shape the microbiome? Goodrich et al. present a gut microbiome analysis of 1,126 twin pairs, which extends the association between host genetics and select bacterial taxa. Lactase nonpersistence was linked to higher levels of Bifidobacteria. Other gene/microbe links relate to diet and barrier defense.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The bacterial composition of the human fecal microbiome is influenced by many lifestyle factors, notably diet. It is less clear, however, what role host genetics plays in dictating the composition of ...bacteria living in the gut. In this study, we examined the association of ~200K host genotypes with the relative abundance of fecal bacterial taxa in a founder population, the Hutterites, during two seasons (n = 91 summer, n = 93 winter, n = 57 individuals collected in both). These individuals live and eat communally, minimizing variation due to environmental exposures, including diet, which could potentially mask small genetic effects. Using a GWAS approach that takes into account the relatedness between subjects, we identified at least 8 bacterial taxa whose abundances were associated with single nucleotide polymorphisms in the host genome in each season (at genome-wide FDR of 20%). For example, we identified an association between a taxon known to affect obesity (genus Akkermansia) and a variant near PLD1, a gene previously associated with body mass index. Moreover, we replicate a previously reported association from a quantitative trait locus (QTL) mapping study of fecal microbiome abundance in mice (genus Lactococcus, rs3747113, P = 3.13 x 10-7). Finally, based on the significance distribution of the associated microbiome QTLs in our study with respect to chromatin accessibility profiles, we identified tissues in which host genetic variation may be acting to influence bacterial abundance in the gut.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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