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.

Chromosome 17q12-21 Variants Are Associated with Multiple Wheezing Phenotypes in Childhood.

Rationale: Birth cohort studies have identified several temporal patterns of wheezing, only some of which are associated with asthma. Whether 17q12-21 genetic variants, which are closely associated with asthma, are also associated with childhood wheezing phenotypes remains poorly explored.Objectives: To determine whether wheezing phenotypes, defined by latent class analysis (LCA), are associated with nine 17q12-21 SNPs and if so, whether these relationships differ by race/ancestry.Methods: Data from seven U.S. birth cohorts (n = 3,786) from the CREW (Children's Respiratory Research and Environment Workgroup) were harmonized to represent whether subjects wheezed in each year of life from birth until age 11 years. LCA was then performed to identify wheeze phenotypes. Genetic associations between SNPs and wheeze phenotypes were assessed separately in European American (EA) (n = 1,308) and, for the first time, in African American (AA) (n = 620) children.Measurements and Main Results: The LCA best supported four latent classes of wheeze: infrequent, transient, late-onset, and persistent. Odds of belonging to any of the three wheezing classes (vs. infrequent) increased with the risk alleles for multiple SNPs in EA children. Only one SNP, rs2305480, showed increased odds of belonging to any wheezing class in both AA and EA children.Conclusions: These results indicate that 17q12-21 is a "wheezing locus," and this association may reflect an early life susceptibility to respiratory viruses common to all wheezing children. Which children will have their symptoms remit or reoccur during childhood may be independent of the influence of rs2305480.

Integrating predicted transcriptome from multiple tissues improves association detection.

Integration of genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) studies is needed to improve our understanding of the biological mechanisms underlying GWAS hits, and our ability to identify therapeutic targets. Gene-level association methods such as PrediXcan can prioritize candidate targets. However, limited eQTL sample sizes and absence of relevant developmental and disease context restrict our ability to detect associations. Here we propose an efficient statistical method (MultiXcan) that leverages the substantial sharing of eQTLs across tissues and contexts to improve our ability to identify potential target genes. MultiXcan integrates evidence across multiple panels using multivariate regression, which naturally takes into account the correlation structure. We apply our method to simulated and real traits from the UK Biobank and show that, in realistic settings, we can detect a larger set of significantly associated genes than using each panel separately. To improve applicability, we developed a summary result-based extension called S-MultiXcan, which we show yields highly concordant results with the individual level version when LD is well matched. Our multivariate model-based approach allowed us to use the individual level results as a gold standard to calibrate and develop a robust implementation of the summary-based extension. Results from our analysis as well as software and necessary resources to apply our method are publicly available.

Epigenetic landscape links upper airway microbiota in infancy with allergic rhinitis at 6 years of age.

BACKGROUND: The upper airways present a barrier to inhaled allergens and microbes, which alter immune responses and subsequent risk for diseases, such as allergic rhinitis (AR). OBJECTIVE: We tested the hypothesis that early-life microbial exposures leave a lasting signature in DNA methylation that ultimately influences the development of AR in children. METHODS: We studied upper airway microbiota at 1 week, 1 month, and 3 months of life, and measured DNA methylation and gene expression profiles in upper airway mucosal cells and assessed AR at age 6 years in children in the Copenhagen Prospective Studies on Asthma in Childhood birth cohort. RESULTS: We identified 956 AR-associated differentially methylated CpGs in upper airway mucosal cells at age 6 years, 792 of which formed 3 modules of correlated differentially methylated CpGs. The eigenvector of 1 module was correlated with the expression of genes enriched for lysosome and bacterial invasion of epithelial cell pathways. Early-life microbial diversity was lower at 1 week (richness P = .0079) in children with AR at age 6 years, and reduced diversity at 1 week was also correlated with the same module's eigenvector (ρ = -0.25; P = 3.3 × 10-5). We show that the effect of microbiota richness at 1 week on risk for AR at age 6 years was mediated in part by the epigenetic signature of this module. CONCLUSIONS: Our results suggest that upper airway microbial composition in infancy contributes to the development of AR during childhood, and this trajectory is mediated, at least in part, through altered DNA methylation patterns in upper airway mucosal cells.

Association of HLA-DRB1∗09:01 with tIgE levels among African-ancestry individuals with asthma.

BACKGROUND: Asthma is a complex chronic inflammatory disease of the airways. Association studies between HLA and asthma were first reported in the 1970s, and yet, the precise role of HLA alleles in asthma is not fully understood. Numerous genome-wide association studies were recently conducted on asthma, but were always limited to simple genetic markers (single nucleotide polymorphisms) and not complex HLA gene polymorphisms (alleles/haplotypes), therefore not capturing the biological relevance of this complex locus for asthma pathogenesis. OBJECTIVE: To run the first HLA-centric association study with asthma and specific asthma-related phenotypes in a large cohort of African-ancestry individuals. METHODS: We collected high-density genomics data for the Consortium on Asthma among African-ancestry Populations in the Americas (N = 4993) participants. Using computer-intensive machine-learning attribute bagging methods to infer HLA alleles, and Easy-HLA to infer HLA 5-gene haplotypes, we conducted a high-throughput HLA-centric association study of asthma susceptibility and total serum IgE (tIgE) levels in subjects with and without asthma. RESULTS: Among the 1607 individuals with asthma, 972 had available tIgE levels, with a mean tIgE level of 198.7 IU/mL. We could not identify any association with asthma susceptibility. However, we showed that HLA-DRB1∗09:01 was associated with increased tIgE levels (P = 8.5 × 10-4; weighted effect size, 0.51 [0.15-0.87]). CONCLUSIONS: We identified for the first time an HLA allele associated with tIgE levels in African-ancestry individuals with asthma. Our report emphasizes that by leveraging powerful computational machine-learning methods, specific/extreme phenotypes, and population diversity, we can explore HLA gene polymorphisms in depth and reveal the full extent of complex disease associations.

An admixture mapping meta-analysis implicates genetic variation at 18q21 with asthma susceptibility in Latinos.

BACKGROUND: Asthma is a common but complex disease with racial/ethnic differences in prevalence, morbidity, and response to therapies. OBJECTIVE: We sought to perform an analysis of genetic ancestry to identify new loci that contribute to asthma susceptibility. METHODS: We leveraged the mixed ancestry of 3902 Latinos and performed an admixture mapping meta-analysis for asthma susceptibility. We replicated associations in an independent study of 3774 Latinos, performed targeted sequencing for fine mapping, and tested for disease correlations with gene expression in the whole blood of more than 500 subjects from 3 racial/ethnic groups. RESULTS: We identified a genome-wide significant admixture mapping peak at 18q21 in Latinos (P = 6.8 × 10-6), where Native American ancestry was associated with increased risk of asthma (odds ratio [OR], 1.20; 95% CI, 1.07-1.34; P = .002) and European ancestry was associated with protection (OR, 0.86; 95% CI, 0.77-0.96; P = .008). Our findings were replicated in an independent childhood asthma study in Latinos (P = 5.3 × 10-3, combined P = 2.6 × 10-7). Fine mapping of 18q21 in 1978 Latinos identified a significant association with multiple variants 5' of SMAD family member 2 (SMAD2) in Mexicans, whereas a single rare variant in the same window was the top association in Puerto Ricans. Low versus high SMAD2 blood expression was correlated with case status (13.4% lower expression; OR, 3.93; 95% CI, 2.12-7.28; P < .001). In addition, lower expression of SMAD2 was associated with more frequent exacerbations among Puerto Ricans with asthma. CONCLUSION: Ancestry at 18q21 was significantly associated with asthma in Latinos and implicated multiple ancestry-informative noncoding variants upstream of SMAD2 with asthma susceptibility. Furthermore, decreased SMAD2 expression in blood was strongly associated with increased asthma risk and increased exacerbations.

Association Tests for Rare Variants.

Over the past few years, interest in the identification of rare variants that influence human phenotype has led to the development of many statistical methods for testing for association between sets of rare variants and binary or quantitative traits. Here, I review some of the most important ideas that underlie these methods and the most relevant issues when choosing a method for analysis. In addition to the tests for association, I review crucial issues in performing a rare variant study, from experimental design to interpretation and validation. I also discuss the many challenges of these studies, some of their limitations, and future research directions.

Imputing Gene Expression in Uncollected Tissues Within and Beyond GTEx.

Gene expression and its regulation can vary substantially across tissue types. In order to generate knowledge about gene expression in human tissues, the Genotype-Tissue Expression (GTEx) program has collected transcriptome data in a wide variety of tissue types from post-mortem donors. However, many tissue types are difficult to access and are not collected in every GTEx individual. Furthermore, in non-GTEx studies, the accessibility of certain tissue types greatly limits the feasibility and scale of studies of multi-tissue expression. In this work, we developed multi-tissue imputation methods to impute gene expression in uncollected or inaccessible tissues. Via simulation studies, we showed that the proposed methods outperform existing imputation methods in multi-tissue expression imputation and that incorporating imputed expression data can improve power to detect phenotype-expression correlations. By analyzing data from nine selected tissue types in the GTEx pilot project, we demonstrated that harnessing expression quantitative trait loci (eQTLs) and tissue-tissue expression-level correlations can aid imputation of transcriptome data from uncollected GTEx tissues. More importantly, we showed that by using GTEx data as a reference, one can impute expression levels in inaccessible tissues in non-GTEx expression studies.

Survey of the Heritability and Sparse Architecture of Gene Expression Traits across Human Tissues.

Understanding the genetic architecture of gene expression traits is key to elucidating the underlying mechanisms of complex traits. Here, for the first time, we perform a systematic survey of the heritability and the distribution of effect sizes across all representative tissues in the human body. We find that local h2 can be relatively well characterized with 59% of expressed genes showing significant h2 (FDR < 0.1) in the DGN whole blood cohort. However, current sample sizes (n ≤ 922) do not allow us to compute distal h2. Bayesian Sparse Linear Mixed Model (BSLMM) analysis provides strong evidence that the genetic contribution to local expression traits is dominated by a handful of genetic variants rather than by the collective contribution of a large number of variants each of modest size. In other words, the local architecture of gene expression traits is sparse rather than polygenic across all 40 tissues (from DGN and GTEx) examined. This result is confirmed by the sparsity of optimal performing gene expression predictors via elastic net modeling. To further explore the tissue context specificity, we decompose the expression traits into cross-tissue and tissue-specific components using a novel Orthogonal Tissue Decomposition (OTD) approach. Through a series of simulations we show that the cross-tissue and tissue-specific components are identifiable via OTD. Heritability and sparsity estimates of these derived expression phenotypes show similar characteristics to the original traits. Consistent properties relative to prior GTEx multi-tissue analysis results suggest that these traits reflect the expected biology. Finally, we apply this knowledge to develop prediction models of gene expression traits for all tissues. The prediction models, heritability, and prediction performance R2 for original and decomposed expression phenotypes are made publicly available (https://github.com/hakyimlab/PrediXcan).

Gene Expression Profiling in Blood Provides Reproducible Molecular Insights into Asthma Control.

RATIONALE: Maintaining optimal symptom control remains the primary objective of asthma treatment. Better understanding of the biologic underpinnings of asthma control may lead to the development of improved clinical and pharmaceutical approaches. OBJECTIVES: To identify molecular pathways and interrelated genes whose differential expression was associated with asthma control. METHODS: We performed gene set enrichment analyses of asthma control in 1,170 adults with asthma, each with gene expression data derived from either whole blood (WB) or unstimulated CD4+ T lymphocytes (CD4), and a self-reported asthma control score representing either the preceding 6 months (chronic) or 7 days (acute). Our study comprised a discovery WB cohort (n = 245, chronic) and three independent, nonoverlapping replication cohorts: a second WB set (n = 448, acute) and two CD4 sets (n = 300, chronic; n = 77, acute). MEASUREMENTS AND MAIN RESULTS: In the WB discovery cohort, we found significant overrepresentation of genes associated with asthma control in 1,106 gene sets from the Molecular Signatures Database (false discovery rate, <5%). Of these, 583 (53%) replicated in at least one replication cohort (false discovery rate, <25%). Suboptimal control was associated with signatures of eosinophilic and granulocytic inflammatory signals, whereas optimal control signatures were enriched for immature lymphocytic patterns. These signatures included two related biologic processes related to activation by TREM-1 (triggering receptor expressed on myeloid cells 1) and lipopolysaccharide. CONCLUSIONS: Together, these results demonstrate the existence of specific, reproducible transcriptomic components in blood that vary with degree of asthma control and implicate a novel biologic target (TREM-1).

Genome-Wide Methylation Study Identifies an IL-13-induced Epigenetic Signature in Asthmatic Airways.

RATIONALE: Epigenetic changes to airway cells have been proposed as important modulators of the effects of environmental exposures on airway diseases, yet no study to date has shown epigenetic responses to exposures in the airway that correlate with disease state. The type 2 cytokine IL-13 is a key mediator of allergic airway diseases, such as asthma, and is up-regulated in response to many asthma-promoting exposures. OBJECTIVES: To directly study the epigenetic response of airway epithelial cells (AECs) to IL-13 and test whether IL-13-induced epigenetic changes differ between individuals with and without asthma. METHODS: Genome-wide DNA methylation and gene expression patterns were studied in 58 IL-13-treated and untreated primary AEC cultures and validated in freshly isolated cells of subjects with and without asthma using the Illumina Human Methylation 450K and HumanHT-12 BeadChips. IL-13-mediated comethylation modules were identified and correlated with clinical phenotypes using weighted gene coexpression network analysis. MEASUREMENTS AND MAIN RESULTS: IL-13 altered global DNA methylation patterns in cultured AECs and were significantly enriched near genes associated with asthma. Importantly, a significant proportion of this IL-13 epigenetic signature was validated in freshly isolated AECs from subjects with asthma and clustered into two distinct modules, with module 1 correlated with asthma severity and lung function and module 2 with eosinophilia. CONCLUSIONS: These results suggest that a single exposure of IL-13 may selectively induce long-lasting DNA methylation changes in asthmatic airways that alter specific AEC pathways and contribute to asthma phenotypes.

Genome-wide interaction studies reveal sex-specific asthma risk alleles.

Asthma is a complex disease with sex-specific differences in prevalence. Candidate gene studies have suggested that genotype-by-sex interaction effects on asthma risk exist, but this has not yet been explored at a genome-wide level. We aimed to identify sex-specific asthma risk alleles by performing a genome-wide scan for genotype-by-sex interactions in the ethnically diverse participants in the EVE Asthma Genetics Consortium. We performed male- and female-specific genome-wide association studies in 2653 male asthma cases, 2566 female asthma cases and 3830 non-asthma controls from European American, African American, African Caribbean and Latino populations. Association tests were conducted in each study sample, and the results were combined in ancestry-specific and cross-ancestry meta-analyses. Six sex-specific asthma risk loci had P-values < 1 × 10(-6), of which two were male specific and four were female specific; all were ancestry specific. The most significant sex-specific association in European Americans was at the interferon regulatory factor 1 (IRF1) locus on 5q31.1. We also identify a Latino female-specific association in RAP1GAP2. Both of these loci included single-nucleotide polymorphisms that are known expression quantitative trait loci and have been associated with asthma in independent studies. The IRF1 locus is a strong candidate region for male-specific asthma susceptibility due to the association and validation we demonstrate here, the known role of IRF1 in asthma-relevant immune pathways and prior reports of sex-specific differences in interferon responses.

Rhinovirus wheezing illness and genetic risk of childhood-onset asthma.

BACKGROUND: Both genetic variation at the 17q21 locus and virus-induced respiratory wheezing illnesses are associated with the development of asthma. Our aim was to determine the effects of these two factors on the risk of asthma in the Childhood Origins of Asthma (COAST) and the Copenhagen Prospective Study on Asthma in Childhood (COPSAC) birth cohorts. METHODS: We tested genotypes at the 17q21 locus for associations with asthma and with human rhinovirus (HRV) and respiratory syncytial virus (RSV) wheezing illnesses and tested for interactions between 17q21 genotypes and HRV and RSV wheezing illnesses with respect to the risk of asthma. Finally, we examined genotype-specific expression of 17q21 genes in unstimulated and HRV-stimulated peripheral-blood mononuclear cells (PBMCs). RESULTS: The 17q21 variants were associated with HRV wheezing illnesses in early life, but not with RSV wheezing illnesses. The associations of 17q21 variants with asthma were restricted to children who had had HRV wheezing illnesses, resulting in a significant interaction effect with respect to the risk of asthma. Moreover, the expression levels of ORMDL3 and of GSDMB were significantly increased in HRV-stimulated PBMCs, as compared with unstimulated PBMCs. The expression of these genes was associated with 17q21 variants in both conditions, although the increase with exposure to HRV was not genotype-specific. CONCLUSIONS: Variants at the 17q21 locus were associated with asthma in children who had had HRV wheezing illnesses and with expression of two genes at this locus. The expression levels of both genes increased in response to HRV stimulation, although the relative increase was not associated with the 17q21 genotypes. (Funded by the National Institutes of Health.).

PRIMAL: Fast and accurate pedigree-based imputation from sequence data in a founder population.

Founder populations and large pedigrees offer many well-known advantages for genetic mapping studies, including cost-efficient study designs. Here, we describe PRIMAL (PedigRee IMputation ALgorithm), a fast and accurate pedigree-based phasing and imputation algorithm for founder populations. PRIMAL incorporates both existing and original ideas, such as a novel indexing strategy of Identity-By-Descent (IBD) segments based on clique graphs. We were able to impute the genomes of 1,317 South Dakota Hutterites, who had genome-wide genotypes for ~300,000 common single nucleotide variants (SNVs), from 98 whole genome sequences. Using a combination of pedigree-based and LD-based imputation, we were able to assign 87% of genotypes with >99% accuracy over the full range of allele frequencies. Using the IBD cliques we were also able to infer the parental origin of 83% of alleles, and genotypes of deceased recent ancestors for whom no genotype information was available. This imputed data set will enable us to better study the relative contribution of rare and common variants on human phenotypes, as well as parental origin effect of disease risk alleles in >1,000 individuals at minimal cost.

A unified set-based test with adaptive filtering for gene-environment interaction analyses.

In genome-wide gene-environment interaction (GxE) studies, a common strategy to improve power is to first conduct a filtering test and retain only the SNPs that pass the filtering in the subsequent GxE analyses. Inspired by two-stage tests and gene-based tests in GxE analysis, we consider the general problem of jointly testing a set of parameters when only a few are truly from the alternative hypothesis and when filtering information is available. We propose a unified set-based test that simultaneously considers filtering on individual parameters and testing on the set. We derive the exact distribution and approximate the power function of the proposed unified statistic in simplified settings, and use them to adaptively calculate the optimal filtering threshold for each set. In the context of gene-based GxE analysis, we show that although the empirical power function may be affected by many factors, the optimal filtering threshold corresponding to the peak of the power curve primarily depends on the size of the gene. We further propose a resampling algorithm to calculate P-values for each gene given the estimated optimal filtering threshold. The performance of the method is evaluated in simulation studies and illustrated via a genome-wide gene-gender interaction analysis using pancreatic cancer genome-wide association data.

Noninvasive analysis of the sputum transcriptome discriminates clinical phenotypes of asthma.

RATIONALE: The airway transcriptome includes genes that contribute to the pathophysiologic heterogeneity seen in individuals with asthma. OBJECTIVES: We analyzed sputum gene expression for transcriptomic endotypes of asthma (TEA), gene signatures that discriminate phenotypes of disease. METHODS: Gene expression in the sputum and blood of patients with asthma was measured using Affymetrix microarrays. Unsupervised clustering analysis based on pathways from the Kyoto Encyclopedia of Genes and Genomes was used to identify TEA clusters. Logistic regression analysis of matched blood samples defined an expression profile in the circulation to determine the TEA cluster assignment in a cohort of children with asthma to replicate clinical phenotypes. MEASUREMENTS AND MAIN RESULTS: Three TEA clusters were identified. TEA cluster 1 had the most subjects with a history of intubation (P = 0.05), a lower prebronchodilator FEV1 (P = 0.006), a higher bronchodilator response (P = 0.03), and higher exhaled nitric oxide levels (P = 0.04) compared with the other TEA clusters. TEA cluster 2, the smallest cluster, had the most subjects that were hospitalized for asthma (P = 0.04). TEA cluster 3, the largest cluster, had normal lung function, low exhaled nitric oxide levels, and lower inhaled steroid requirements. Evaluation of TEA clusters in children confirmed that TEA clusters 1 and 2 are associated with a history of intubation (P = 5.58 × 10(-6)) and hospitalization (P = 0.01), respectively. CONCLUSIONS: There are common patterns of gene expression in the sputum and blood of children and adults that are associated with near-fatal, severe, and milder asthma.

Stress and Bronchodilator Response in Children with Asthma.

RATIONALE: Stress is associated with asthma morbidity in Puerto Ricans (PRs), who have reduced bronchodilator response (BDR). OBJECTIVES: To examine whether stress and/or a gene regulating anxiety (ADCYAP1R1) is associated with BDR in PR and non-PR children with asthma. METHODS: This was a cross-sectional study of stress and BDR (percent change in FEV1 after BD) in 234 PRs ages 9-14 years with asthma. We assessed child stress using the Checklist of Children's Distress Symptoms, and maternal stress using the Perceived Stress Scale. Replication analyses were conducted in two cohorts. Polymorphisms in ADCYAP1R1 were genotyped in our study and six replication studies. Multivariable models of stress and BDR were adjusted for age, sex, income, environmental tobacco smoke, and use of inhaled corticosteroids. MEASUREMENTS AND MAIN RESULTS: High child stress was associated with reduced BDR in three cohorts. PR children who were highly stressed (upper quartile, Checklist of Children's Distress Symptoms) and whose mothers had high stress (upper quartile, Perceived Stress Scale) had a BDR that was 10.2% (95% confidence interval, 6.1-14.2%) lower than children who had neither high stress nor a highly stressed mother. A polymorphism in ADCYAP1R1 (rs34548976) was associated with reduced BDR. This single-nucleotide polymorphism is associated with reduced expression of the gene for the ß2-adrenergic receptor (ADRB2) in CD4(+) lymphocytes of subjects with asthma, and it affects brain connectivity of the amygdala and the insula (a biomarker of anxiety). CONCLUSIONS: High child stress and an ADCYAP1R1 single-nucleotide polymorphism are associated with reduced BDR in children with asthma. This is likely caused by down-regulation of ADRB2 in highly stressed children.

Genome-wide association study of recalcitrant atopic dermatitis in Korean children.

BACKGROUND: Atopic dermatitis (AD) is a heterogeneous chronic inflammatory skin disease. Most AD during infancy resolves during childhood, but moderate-to-severe AD with allergic sensitization is more likely to persist into adulthood and more often occurs with other allergic diseases. OBJECTIVE: We sought to find susceptibility loci by performing the first genome-wide association study (GWAS) of AD in Korean children with recalcitrant AD, which was defined as moderate-to-severe AD with allergic sensitization. METHODS: Our study included 246 children with recalcitrant AD and 551 adult control subjects with a negative history of both allergic disease and allergic sensitization. DNA from these subjects was genotyped; sets of common single nucleotide polymorphisms (SNPs) were imputed and used in the GWAS after quality control checks. RESULTS: SNPs at a region on 13q21.31 were associated with recalcitrant AD at a genome-wide threshold of significance (P < 2.0 × 10(-8)). These associated SNPs are more than 1 Mb from the closest gene, protocadherin (PCDH)9. SNPs at 4 additional loci had P values of less than 1 × 10(-6), including SNPs at or near the neuroblastoma amplified sequence (NBAS; 2p24.3), thymus-expressed molecule involved in selection (THEMIS; 6q22.33), GATA3 (10p14), and S-phase cyclin A-associated protein in the ER (SCAPER; 15q24.3) genes. Further analysis of total serum IgE levels suggested 13q21.31 might be primarily an IgE locus, and analyses of published data demonstrated that SNPs at the 15q24.3 region are expression quantitative trait loci for 2 nearby genes, ISL2 and proline-serine-threonine phosphatase interacting protein 1 (PSTPIP1), in immune cells. CONCLUSION: Our GWAS of recalcitrant AD identified new susceptibility regions containing genes involved in epithelial cell function and immune dysregulation, 2 key features of AD, and potentially extend our understanding of their role in pathogenesis.

Genome-wide association study and admixture mapping reveal new loci associated with total IgE levels in Latinos.

BACKGROUND: IgE is a key mediator of allergic inflammation, and its levels are frequently increased in patients with allergic disorders. OBJECTIVE: We sought to identify genetic variants associated with IgE levels in Latinos. METHODS: We performed a genome-wide association study and admixture mapping of total IgE levels in 3334 Latinos from the Genes-environments & Admixture in Latino Americans (GALA II) study. Replication was evaluated in 454 Latinos, 1564 European Americans, and 3187 African Americans from independent studies. RESULTS: We confirmed associations of 6 genes identified by means of previous genome-wide association studies and identified a novel genome-wide significant association of a polymorphism in the zinc finger protein 365 gene (ZNF365) with total IgE levels (rs200076616, P = 2.3 × 10(-8)). We next identified 4 admixture mapping peaks (6p21.32-p22.1, 13p22-31, 14q23.2, and 22q13.1) at which local African, European, and/or Native American ancestry was significantly associated with IgE levels. The most significant peak was 6p21.32-p22.1, where Native American ancestry was associated with lower IgE levels (P = 4.95 × 10(-8)). All but 22q13.1 were replicated in an independent sample of Latinos, and 2 of the peaks were replicated in African Americans (6p21.32-p22.1 and 14q23.2). Fine mapping of 6p21.32-p22.1 identified 6 genome-wide significant single nucleotide polymorphisms in Latinos, 2 of which replicated in European Americans. Another single nucleotide polymorphism was peak-wide significant within 14q23.2 in African Americans (rs1741099, P = 3.7 × 10(-6)) and replicated in non-African American samples (P = .011). CONCLUSION: We confirmed genetic associations at 6 genes and identified novel associations within ZNF365, HLA-DQA1, and 14q23.2. Our results highlight the importance of studying diverse multiethnic populations to uncover novel loci associated with total IgE levels.

Genome-wide association study identifies new susceptibility loci for Crohn disease and implicates autophagy in disease pathogenesis.

We present a genome-wide association study of ileal Crohn disease and two independent replication studies that identify several new regions of association to Crohn disease. Specifically, in addition to the previously established CARD15 and IL23R associations, we identified strong and significantly replicated associations (combined P < 10(-10)) with an intergenic region on 10q21.1 and a coding variant in ATG16L1, the latter of which was also recently reported by another group. We also report strong associations with independent replication to variation in the genomic regions encoding PHOX2B, NCF4 and a predicted gene on 16q24.1 (FAM92B). Finally, we demonstrate that ATG16L1 is expressed in intestinal epithelial cell lines and that functional knockdown of this gene abrogates autophagy of Salmonella typhimurium. Together, these findings suggest that autophagy and host cell responses to intracellular microbes are involved in the pathogenesis of Crohn disease.