Genetics of Allergic Diseases

Ortiz, Romina; Barnes, Kathleen C.

doi:10.1016/j.iac.2014.09.014

Cited by 59 publications

(47 citation statements)

References 194 publications

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“…Close to 40 GWAS in asthma have also been performed to date, 175 leading to the validation of several genes previously identified through positional cloning or candidate-gene studies ( IL13, IL1RL1, DPP10 , and HLA-DQ ) 176 and to the discovery of several novel loci, the most replicated of which is the 17q21 locus. In 2007, Moffatt et al were the first to identify the 17q21 region as the site of an asthma susceptibility locus.…”

Section: Gene-environment Interactions In Atopic Disordersmentioning

confidence: 99%

Resolving the etiology of atopic disorders by using genetic analysis of racial ancestry

Gupta

Johansson

Bernstein

et al. 2016

Journal of Allergy and Clinical Immunology

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Atopic dermatitis (AD), food allergy (FA), allergic rhinitis (AR) and asthma are common atopic disorders of complex etiology. The frequently observed “atopic march” from early AD to asthma and/or AR later in life as well as the extensive comorbidity of atopic disorders, suggests common causal mechanisms in addition to distinct ones. Indeed, both disease-specific and shared genomic regions exist for atopic disorders. Their prevalence also varies among races; for example, AD and asthma have a higher prevalence in African-Americans when compared to European-Americans. Whether this disparity stems from true genetic or race-specific environmental risk factors or both is unknown. Thus far, the majority of the genetic studies on atopic diseases have utilized populations of European ancestry, limiting their generalizability. Large cohort initiatives and new analytic methods such as admixture mapping are currently being employed to address this knowledge gap. Here we discuss the unique and shared genetic risk factors for atopic disorders in the context of ancestry variations, and the promise of high-throughput “-omics” based systems biology approach in providing greater insight to deconstruct into their genetic and non-genetic etiologies. Future research will also focus on deep phenotyping and genotyping of diverse racial ancestry, gene-environment, and gene-gene interactions.

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Section: Gene-environment Interactions In Atopic Disordersmentioning

confidence: 99%

Resolving the etiology of atopic disorders by using genetic analysis of racial ancestry

Gupta

Johansson

Bernstein

et al. 2016

Journal of Allergy and Clinical Immunology

View full text Add to dashboard Cite

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“…Although dozens of genes that confer susceptibility to asthma or asthma morbidity have been recently identified 4 , single nucleotide polymorphisms (SNPs) in such genes account for as little as 10–50% of the disease’s heritability. One potential reason for this “missing heritability” is gene-by-environment (G×E) interactions, as certain genetic variants may confer risk only in the presence of certain environmental exposures.…”

Section: Introductionmentioning

confidence: 99%

Genome-wide interaction study of dust mite allergen on lung function in children with asthma

Forno

Sordillo

Brehm

et al. 2017

Journal of Allergy and Clinical Immunology

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Background Childhood asthma is likely the result of gene-by-environment (G×E) interactions. Dust mite is a known risk factor for asthma morbidity. Yet, there have been no genome-wide G×E studies of dust mite allergen on asthma-related phenotypes. Objective To identify genetic variants whose effects on lung function in children with asthma are modified by level of dust mite allergen exposure. Methods A genome-wide interaction analysis of dust mite allergen level and lung function was performed in a cohort of Puerto Rican children with asthma (PRGOAL). Replication was attempted in two independent cohorts, the Childhood Asthma Management Program (CAMP) and the Genetics of Asthma in Costa Rica Study. Results SNP rs117902240 showed a significant interaction with dust mite allergen level on FEV1 in PRGOAL (interaction P=3.1×10−8), and replicated in the same direction in CAMP White children and CAMP Hispanic children (combined interaction P=0.0065 for replication cohorts and 7.4×10−9 for all cohorts). Rs117902240 was positively associated with FEV1 in children exposed to low dust mite allergen levels, but negatively associated with FEV1 in children exposed to high levels. This SNP is on chromosome 8q24, adjacent to a binding site for CEBPβ, a transcription factor that forms part of the IL-17 signaling pathway. None of the SNPs identified for FEV1/FVC replicated in the independent cohorts. Conclusions Dust mite allergen exposure modifies the estimated effect of rs117902240 on FEV1 in children with asthma. Analysis of existing data suggests this SNP may have transcription factor regulatory functions.

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“…Biomarkers involved in Th2 ( IL13 ), Th1 ( IFNG and IL12A ), Th17 ( IL17A ), regulatory T cell ( IL10 ), and inflammatory pathways ( IL6 , CHI3L1 , and TNF ) are critical for diagnosing and monitoring asthma development [8]. Genetic markers identified through GWAS and biomarkers identified through expression analyses and functional studies are not completely overlapped [8,9]. Correlation between expression of asthma susceptibility genes and asthma or asthma severity has not been systemically studied in asthma-relevant tissues from subjects with asthma.…”

Section: Introductionmentioning

confidence: 99%

Expression of asthma susceptibility genes in bronchial epithelial cells and bronchial alveolar lavage in the Severe Asthma Research Program (SARP) cohort

Hawkins

Moore

et al. 2016

Journal of Asthma

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Objective Genome-wide association studies (GWASs) have identified genes associated with asthma, however expression of these genes in asthma-relevant tissues has not been studied. This study tested expression and correlation between GWAS-identified asthma genes and asthma or asthma severity. Methods Correlation analyses of expression levels of GWAS-identified asthma genes and asthma-related biomarkers were performed in cells from human bronchial epithelial biopsy (BEC, n=107) and bronchial alveolar lavage (BAL, n=94). Results Expression levels of asthma genes between BEC and BAL and with asthma or asthma severity were weakly correlated. The expression levels of IL18R1 were consistently higher in asthma than controls or in severe asthma than mild/moderate asthma in BEC and BAL (p<0.05). In RAD50-IL13 region, the expression levels of RAD50, not IL4, IL5, or IL13, were positively correlated between BEC and BAL (rho=0.53, P=4.5×10−6). The expression levels of IL13 were positively correlated with IL5 in BEC (rho=0.35, P=1.9×10−4) and IL4 in BAL (rho=0.42, P=2.5×10−5), respectively. rs3798134 in RAD50, a GWAS-identified SNP, was correlated with IL13 expression and the expression levels of IL13 were correlated with asthma (P=0.03). rs17772583 in RAD50 was significantly correlated with RAD50 expression in BAL and BEC (P=7.4×10−7 and 0.04) but was not associated with asthma. Conclusions This is the first report studying the expression of GWAS-identified asthma genes in BEC and BAL. IL13, rather than RAD50, IL4, or IL5, is more likely to be the asthma susceptibility gene. Our study illustrates tissue-specific expression of asthma-related genes. Therefore, whenever possible, disease-relevant tissues should be used for transcription analysis.

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Genetics of Allergic Diseases

Cited by 59 publications

References 194 publications

Resolving the etiology of atopic disorders by using genetic analysis of racial ancestry

Resolving the etiology of atopic disorders by using genetic analysis of racial ancestry

Genome-wide interaction study of dust mite allergen on lung function in children with asthma

Expression of asthma susceptibility genes in bronchial epithelial cells and bronchial alveolar lavage in the Severe Asthma Research Program (SARP) cohort

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