Peanut allergy (PA) is a common and serious food allergy and its prevalence has increased in the past decade. Although there is strong evidence of inheritance, the genetic causes of this disease are not well understood. Previously, a large-scale genome-wide association study described an association between human leukocyte antigen (HLA)-DQB1 and asthma; the aim of this study was to evaluate the association between HLA-DQB1 and PA. Genotypic and allelic profiles were established for 311 Caucasian members of a well-described Canadian group of children with PA and 226 Caucasian controls. Firth's logistic regression analyses showed associations between HLA-DQB1 alleles and PA for DQB1*02 (P=1.1 × 10−8, odds ratio (OR)=0.09 (CI=0.03–0.23)) and DQB1*06:03P alleles (P=2.1 × 10−2, OR=2.82 (CI=1.48–5.45)). This study of HLA in PA demonstrates specific association between two allelic groups of the HLA-DQB1 gene (DQB1*02 and DQB1*06:03P) and PA, highlighting its possible role in the development of this disease.
HLA-DQB1; peanut allergy; Caucasian; association; food allergy
Enterococci are a major cause of health care-associated infections and account for approximately 10% of all bacteremias globally. The aim of this study was to determine the proportion of enterococcal bacteremia isolates in Australia that are antimicrobial resistant, with particular emphasis on susceptibility to ampicillin and the glycopeptides, and to characterize the molecular epidemiology of the Enterococcus faecalis and Enterococcus faecium isolates. From 1 January to 31 December 2011, 1,079 unique episodes of bacteremia were investigated, of which 95.8% were caused by either E. faecalis (61.0%) or E. faecium (34.8%). The majority of bacteremias were health care associated, and approximately one-third were polymicrobial. Ampicillin resistance was detected in 90.4% of E. faecium isolates but was not detected in E. faecalis isolates. Vancomycin nonsusceptibility was reported in 0.6% and 36.5% of E. faecalis and E. faecium isolates, respectively. Unlike Europe and the United States, where vancomycin resistance in E. faecium is predominately due to the acquisition of the vanA operon, 98.4% of E. faecium isolates harboring van genes carried the vanB operon, and 16.1% of the
vanB E. faecium isolates had vancomycin MICs at or below the susceptible breakpoint of the CLSI. Although molecular typing identified 126 E. faecalis pulsed-field gel electrophoresis pulsotypes, >50% belonged to two pulsotypes that were isolated across Australia. E. faecium consisted of 73 pulsotypes from which 43 multilocus sequence types were identified. Almost 90% of the E. faecium isolates were identified as CC17 clones, of which approximately half were characterized as ST203, which was isolated Australia-wide. In conclusion, the Australian Enterococcal Sepsis Outcome Programme (AESOP) study has shown that although they are polyclonal, enterococcal bacteremias in Australia are frequently caused by ampicillin-resistant vanB E. faecium.
The underlying ethos of dbGaP is that access to these data by secondary data analysts facilitates advancement of science. NIH has required that genome-wide association study data be deposited in the Database of Genotypes and Phenotypes (dbGaP) since 2003. In 2013, a proposed updated policy extended this requirement to next-generation sequencing data. However, recent literature and anecdotal reports suggest lingering logistical and ethical concerns about subject identifiability, informed consent, publication embargo enforcement, and difficulty in accessing dbGaP data. We surveyed the International Genetic Epidemiology Society (IGES) membership about their experiences. One hundred and seventy five (175) individuals completed the survey, a response rate of 27%. Of respondents who received data from dbGaP (43%), only 32% perceived the application process as easy but most (75%) received data within five months. Remaining challenges include difficulty in identifying an institutional signing official and an overlong application process. Only 24% of respondents had contributed data to dbGaP. Of these, 31% reported local IRB restrictions on data release; an additional 15% had to reconsent study participants before depositing data. The majority of respondents (56%) disagreed that the publication embargo period was sufficient. In response, we recommend longer embargo periods and use of varied data-sharing models rather than a one-size-fits-all approach.
data sharing; identifiability; GWAS; ELSI; ethics; publication embargo; collaboration
Immunoglobulin E (IgE) is both a marker and mediator of allergic inflammation. Despite reported differences in serum total IgE levels by race-ethnicity, African American and Latino individuals have not been well represented in genetic studies of total IgE.
To identify the genetic predictors of serum total IgE levels.
We used genome wide association (GWA) data from 4,292 individuals (2,469 African Americans, 1,564 European Americans, and 259 Latinos) in the EVE Asthma Genetics Consortium. Tests for association were performed within each cohort by race-ethnic group (i.e., African American, Latino, and European American) and asthma status. The resulting p-values were meta-analyzed accounting for sample size and direction of effect. Top single nucleotide polymorphism (SNP) associations from the meta-analysis were reassessed in six additional cohorts comprising 5,767 individuals.
We identified 10 unique regions where the combined association statistic was associated with total serum IgE levels (P-value <5.0×10−6) and the minor allele frequency was ≥5% in two or more population groups. Variant rs9469220, corresponding to HLA-DQB1, was the most significantly associated SNP with serum total IgE levels when assessed in both the replication cohorts and the discovery and replication sets combined (P-value = 0.007 and 2.45×10−7, respectively). In addition, findings from earlier GWA studies were also validated in the current meta-analysis.
This meta-analysis independently identified a variant near HLA-DQB1 as a predictor of total serum IgE in multiple race-ethnic groups. This study also extends and confirms the findings of earlier GWA analyses in African American and Latino individuals.
meta-analysis; genome wide association study; total immunoglobulin E; race-ethnicity; continental population groups
Both asthma and obesity are complex disorders that are influenced by environmental and genetic factors. Shared genetic factors between asthma and obesity have been proposed to partly explain epidemiological findings of co-morbidity between these conditions.
To identify genetic variants that are associated with body mass index (BMI) in asthmatic children and adults, and to evaluate if there are differences between the genetics of BMI in asthmatics and healthy individuals.
In total, 19 studies contributed with genome-wide analysis study (GWAS) data from more than 23,000 individuals with predominantly European descent, of whom 8,165 are asthmatics.
We report associations between several DENND1B variants (p=2.2×10−7 for rs4915551) on chromosome 1q31 and BMI from a meta-analysis of GWAS data using 2,691 asthmatic children (screening data). The top DENND1B SNPs were next evaluated in seven independent replication data sets comprising 2,014 asthmatics, and rs4915551 was nominally replicated (p<0.05) in two of the seven studies and of borderline significance in one (p=0.059). However, strong evidence of effect heterogeneity was observed and overall, the association between rs4915551 and BMI was not significant in the total replication data set, p=0.71. Using a random effects model, BMI was overall estimated to increase by 0.30 kg/m2 (p=0.01 for combined screening and replication data sets, N=4,705) per additional G allele of this DENND1B SNP. FTO was confirmed as an important gene for adult and childhood BMI regardless of asthma status.
Conclusions and Clinical Relevance
DENND1B was recently identified as an asthma susceptibility gene in a GWAS on children, and here we find evidence that DENND1B variants may also be associated with BMI in asthmatic children. However, the association was overall not replicated in the independent data sets and the heterogeneous effect of DENND1B points to complex associations with the studied diseases that deserve further study.
Association; Asthma; BMI; Genetics; Genome-wide; Obesity
Accelerated lung function decline is a key COPD phenotype; however its genetic control remains largely unknown.
We performed a genome-wide association study using the Illumina Human660W-Quad v.1_A BeadChip. Generalized estimation equations were used to assess genetic contributions to lung function decline over a 5-year period in 4,048 European-American Lung Health Study participants with largely mild COPD. Genotype imputation was performed using reference HapMap II data. To validate regions meeting genome-wide significance, replication of top SNPs was attempted in independent cohorts. Three genes (TMEM26, ANK3 and FOXA1) within the regions of interest were selected for tissue expression studies using immunohistochemistry.
Measurements and Main Results
Two intergenic SNPs (rs10761570, rs7911302) on chromosome 10 and one SNP on chromosome 14 (rs177852) met genome-wide significance after Bonferroni. Further support for the chromosome 10 region was obtained by imputation, the most significantly associated imputed SNPs (rs10761571, rs7896712) being flanked by observed markers rs10761570 and rs7911302. Results were not replicated in four general population cohorts or a smaller cohort of subjects with moderate to severe COPD; however, we show novel expression of genes near regions of significantly associated SNPS, including TMEM26 and FOXA1 in airway epithelium and lung parenchyma, and ANK3 in alveolar macrophages. Levels of expression were associated with lung function and COPD status.
We identified two novel regions associated with lung function decline in mild COPD. Genes within these regions were expressed in relevant lung cells and their expression related to airflow limitation suggesting they may represent novel candidate genes for COPD susceptibility.
COPD; lung function decline; GWAS; genome wide association; genes; polymorphisms
Non-Hodgkin lymphomas (NHL) are a heterogeneous group of solid tumours of lymphoid cell origin. Three important aspects of lymphocyte development include immunity and inflammation, DNA repair, and programmed cell death. We have used a previously established case-control study of NHL to ask whether genetic variation in genes involved in these three important processes influences risk of this cancer. 118 genes in these three categories were tagged with single nucleotide polymorphisms (SNPs), which were tested for association with NHL and its subtypes. The main analysis used logistic regression (additive model) to estimate odds ratios in European-ancestry cases and controls. 599 SNPs and 1116 samples (569 cases and 547 controls) passed quality control measures and were included in analyses. Following multiple-testing correction, one SNP in MSH3, a mismatch repair gene, showed an association with diffuse large B-cell lymphoma (OR: 1.91; 95% CI: 1.41–2.59; uncorrected p = 0.00003; corrected p = 0.010). This association was not replicated in an independent European-ancestry sample set of 251 diffuse large B-cell lymphoma cases and 737 controls, indicating this result was likely a false positive. It is likely that moderate sample size, inter-subtype and other genetic heterogeneity, and small true effect sizes account for the lack of replicable findings.
Clonal mosaicism for large chromosomal anomalies (duplications, deletions and uniparental disomy) was detected using SNP microarray data from over 50,000 subjects recruited for genome-wide association studies. This detection method requires a relatively high frequency of cells (>5–10%) with the same abnormal karyotype (presumably of clonal origin) in the presence of normal cells. The frequency of detectable clonal mosaicism in peripheral blood is low (<0.5%) from birth until 50 years of age, after which it rises rapidly to 2–3% in the elderly. Many of the mosaic anomalies are characteristic of those found in hematological cancers and identify common deleted regions that pinpoint the locations of genes previously associated with hematological cancers. Although only 3% of subjects with detectable clonal mosaicism had any record of hematological cancer prior to DNA sampling, those without a prior diagnosis have an estimated 10-fold higher risk of a subsequent hematological cancer (95% confidence interval = 6–18).
Genome-wide association studies (GWAS) have identified loci reproducibly associated with pulmonary diseases; however, the molecular mechanism underlying these associations are largely unknown. The objectives of this study were to discover genetic variants affecting gene expression in human lung tissue, to refine susceptibility loci for asthma identified in GWAS studies, and to use the genetics of gene expression and network analyses to find key molecular drivers of asthma. We performed a genome-wide search for expression quantitative trait loci (eQTL) in 1,111 human lung samples. The lung eQTL dataset was then used to inform asthma genetic studies reported in the literature. The top ranked lung eQTLs were integrated with the GWAS on asthma reported by the GABRIEL consortium to generate a Bayesian gene expression network for discovery of novel molecular pathways underpinning asthma. We detected 17,178 cis- and 593 trans- lung eQTLs, which can be used to explore the functional consequences of loci associated with lung diseases and traits. Some strong eQTLs are also asthma susceptibility loci. For example, rs3859192 on chr17q21 is robustly associated with the mRNA levels of GSDMA (P = 3.55×10−151). The genetic-gene expression network identified the SOCS3 pathway as one of the key drivers of asthma. The eQTLs and gene networks identified in this study are powerful tools for elucidating the causal mechanisms underlying pulmonary disease. This data resource offers much-needed support to pinpoint the causal genes and characterize the molecular function of gene variants associated with lung diseases.
Recent genome-wide association studies (GWAS) have identified genetic variants associated with lung diseases. The challenge now is to find the causal genes in GWAS–nominated chromosomal regions and to characterize the molecular function of disease-associated genetic variants. In this paper, we describe an international effort to systematically capture the genetic architecture of gene expression regulation in human lung. By studying lung specimens from 1,111 individuals of European ancestry, we found a large number of genetic variants affecting gene expression in the lung, or lung expression quantitative trait loci (eQTL). These lung eQTLs will serve as an important resource to aid in the understanding of the molecular underpinnings of lung biology and its disruption in disease. To demonstrate the utility of this lung eQTL dataset, we integrated our data with previous genetic studies on asthma. Through integrative techniques, we identified causal variants and genes in GWAS–nominated loci and found key molecular drivers for asthma. We feel that sharing our lung eQTLs dataset with the scientific community will leverage the impact of previous large-scale GWAS on lung diseases and function by providing much needed functional information to understand the molecular changes introduced by the susceptibility genetic variants.
Some have suggested that chronic obstructive pulmonary disease (COPD) is a disease of accelerated aging. Aging is characterized by shortening of telomeres. The relationship of telomere length to important clinical outcomes such as mortality, disease progression and cancer in COPD is unknown. Using quantitative polymerase chain reaction (qPCR), we measured telomere length of peripheral leukocytes in 4,271 subjects with mild to moderate COPD who participated in the Lung Health Study (LHS). The subjects were followed for approximately 7.5 years during which time their vital status, FEV1 and smoking status were ascertained. Using multiple regression methods, we determined the relationship of telomere length to cancer and total mortality in these subjects. We also measured telomere length in healthy “mid-life” volunteers and patients with more severe COPD. The LHS subjects had significantly shorter telomeres than those of healthy “mid-life” volunteers (p<.001). Compared to individuals in the 4th quartile of relative telomere length (i.e. longest telomere group), the remaining participants had significantly higher risk of cancer mortality (Hazard ratio, HR, 1.48; p = 0.0324) and total mortality (HR, 1.29; p = 0.0425). Smoking status did not make a significant difference in peripheral blood cells telomere length. In conclusion, COPD patients have short leukocyte telomeres, which are in turn associated increased risk of total and cancer mortality. Accelerated aging is of particular relevance to cancer mortality in COPD.
Non-Hodgkin lymphomas are a heterogeneous group of solid tumours that constitute the 5th highest cause of cancer mortality in the United States and Canada. Poor control of cell death in lymphocytes can lead to autoimmune disease or cancer, making genes involved in programmed cell death of lymphocytes logical candidate genes for lymphoma susceptibility.
Materials and Methods
We tested for genetic association with NHL and NHL subtypes, of SNPs in lymphocyte cell death genes using an established population-based study. 17 candidate genes were chosen based on biological function, with 123 SNPs tested. These included tagSNPs from HapMap and novel SNPs discovered by re-sequencing 47 cases in genes for which SNP representation was judged to be low. The main analysis, which estimated odds ratios by fitting data to an additive logistic regression model, used European ancestry samples that passed quality control measures (569 cases and 547 controls). A two-tiered approach for multiple testing correction was used: correction for number of tests within each gene by permutation-based methodology, followed by correction for the number of genes tested using the false discovery rate.
Variant rs928883, near miR-155, showed an association (OR per A-allele: 2.80 [95% CI: 1.63–4.82]; pF = 0.027) with marginal zone lymphoma that is significant after correction for multiple testing.
This is the first reported association between a germline polymorphism at a miRNA locus and lymphoma.
We describe a statistical approach to predict gender-labeling errors in candidate-gene association studies, when Y-chromosome markers have not been included in the genotyping set. The approach adds value to methods that consider only the heterozygosity of X-chromosome SNPs, by incorporating available information about the intensity of X-chromosome SNPs in candidate genes relative to autosomal SNPs from the same individual. To our knowledge, no published methods formalize a framework in which heterozygosity and relative intensity are simultaneously taken into account. Our method offers the advantage that, in the genotyping set, no additional space is required beyond that already assigned to X-chromosome SNPs in the candidate genes. We also show how the predictions can be used in a two-phase sampling design to estimate the gender-labeling error rates for an entire study, at a fraction of the cost of a conventional design.
candidate-gene association study; gender-labeling errors; X-chromosome SNPs; genotype intensities; heterozygosity; two-phase sampling design; error rates; quality control
COPD; Genetics; Association analysis; Consortium
Summary: We present the Sample-based Laboratory Information Management System (SLIMS), a powerful and user-friendly open source web application that provides all members of a laboratory with an interface to view, edit and create sample information. SLIMS aims to simplify common laboratory tasks with tools such as a user-friendly shopping cart for subjects, samples and containers that easily generates reports, shareable lists and plate designs for genotyping. Further key features include customizable data views, database change-logging and dynamically filled pre-formatted reports. Along with being feature-rich, SLIMS' power comes from being able to handle longitudinal data from multiple time-points and biological sources. This type of data is increasingly common from studies searching for susceptibility genes for common complex diseases that collect thousands of samples generating millions of genotypes and overwhelming amounts of data. LIMSs provide an efficient way to deal with this data while increasing accessibility and reducing laboratory errors; however, professional LIMS are often too costly to be practical. SLIMS gives labs a feasible alternative that is easily accessible, user-centrically designed and feature-rich. To facilitate system customization, and utilization for other groups, manuals have been written for users and developers.
Availability: Documentation, source code and manuals are available at http://genapha.icapture.ubc.ca/SLIMS/index.jsp. SLIMS was developed using Java 1.6.0, JSPs, Hibernate 3.3.1.GA, DB2 and mySQL, Apache Tomcat 6.0.18, NetBeans IDE 6.5, Jasper Reports 3.5.1 and JasperSoft's iReport 3.5.1.
Genetic variants at the vitamin D receptor (VDR) locus are associated with asthma and atopy. We hypothesized that polymorphisms in other genes of the vitamin D pathway are associated with asthma or atopy.
Eleven candidate genes were chosen for this study, five of which code for proteins in the vitamin D metabolism pathway (CYP27A1, CYP27B1, CYP2R1, CYP24A1, GC) and six that are known to be transcriptionally regulated by vitamin D (IL10, IL1RL1, CD28, CD86, IL8, SKIIP). For each gene, we selected a maximally informative set of common SNPs (tagSNPs) using the European-derived (CEU) HapMap dataset. A total of 87 SNPs were genotyped in a French-Canadian family sample ascertained through asthmatic probands (388 nuclear families, 1064 individuals) and evaluated using the Family Based Association Test (FBAT) program. We then sought to replicate the positive findings in four independent samples: two from Western Canada, one from Australia and one from the USA (CAMP).
A number of SNPs in the IL10, CYP24A1, CYP2R1, IL1RL1 and CD86 genes were modestly associated with asthma and atopy (p < 0.05). Two-gene models testing for both main effects and the interaction were then performed using conditional logistic regression. Two-gene models implicating functional variants in the IL10 and VDR genes as well as in the IL10 and IL1RL1 genes were associated with asthma (p < 0.0002). In the replicate samples, SNPs in the IL10 and CYP24A1 genes were again modestly associated with asthma and atopy (p < 0.05). However, the SNPs or the orientation of the risk alleles were different between populations. A two-gene model involving IL10 and VDR was replicated in CAMP, but not in the other populations.
A number of genes involved in the vitamin D pathway demonstrate modest levels of association with asthma and atopy. Multilocus models testing genes in the same pathway are potentially more effective to evaluate the risk of asthma, but the effects are not uniform across populations.
Summary: Traditional methods of genetic study design and analysis work well under the scenario that a handful of single nucleotide polymorphisms (SNPs) independently contribute to the risk of disease. For complex diseases, susceptibility may be determined not by a single SNP, but rather a complex interplay between SNPs. For large studies involving hundreds of thousands of SNPs, a brute force search of all possible combinations of SNPs associated with disease is not only inefficient, but also results in a multiple testing paradigm, whereby larger and larger sample sizes are needed to maintain statistical power. Pathway-based methods are an example of one of the many approaches in identifying a subset of SNPs to test for interaction. To help determine which SNP–SNP interactions to test, we developed Path, a software application designed to help researchers interface their data with biological information from several bioinformatics resources. To this end, our application brings together currently available information from nine online bioinformatics resources including the National Center for Biotechnology Information (NCBI), Online Mendelian Inheritance in Man (OMIM), Kyoto Encyclopedia of Genes and Genomes (KEGG), UCSC Genome Browser, Seattle SNPs, PharmGKB, Genetic Association Database, the Single Nucleotide Polymorphism database (dbSNP) and the Innate Immune Database (IIDB).
Availability: The software, example datasets and tutorials are freely available from http://genapha.icapture.ubc.ca/PathTutorial.
T-cell immunoglobulin mucin-3 (TIM3) is a TH1-specific type 1 membrane protein that regulates TH1 proliferation and the development of immunological tolerance. TIM3 and its genetic variants have been suggested to play a role in regulating allergic diseases. Polymorphisms in the TIM3 promoter region have been reported to be associated with allergic phenotypes in several populations. The aims of this study were to examine whether genetic variation in the promoter region of TIM3 influenced transcription of the gene and risk for allergic phenotypes.
We performed 5' rapid amplification of cDNA ends and reverse transcription-polymerase chain reaction. We screened for polymorphisms in the promoter region. Deletion analysis was used to localize the promoter region of TIM3. Genotyping was performed by TaqMan assays in three asthma/allergy population samples.
We found two regions with promoter activity in TIM3. One region was from -214 bp to +58 bp and the other from -1.6 kb to -914 bp relative to the transcription start site. None of the single nucleotide polymorphisms (SNPs) or haplotypes affected the transcriptional activity in reporter gene assays. No association between the SNPs and any phenotype was observed in the study cohorts.
Our findings indicate that SNPs and haplotypes in the TIM3 promoter region do not have a functional effect in vitro and are not associated with allergic diseases. These data suggest that polymorphisms in the TIM3 promoter region are unlikely to play an important role in susceptibility to allergic diseases.
Our goal was to compare methods for tagging single-nucleotide polymorphisms (tagSNPs) with respect to the power to detect disease association under differing haplotype-disease association models. We were also interested in the effect that SNP selection samples, consisting of either cases, controls, or a mixture, would have on power. We investigated five previously described algorithms for choosing tagSNPS: two that picked SNPs based on haplotype structure (Chapman-haplotypic and Stram), two that picked SNPs based on pair-wise allelic association (Chapman-allelic and Cousin), and one control method that chose equally spaced SNPs (Zhai). In two disease-associated regions from the Genetic Analysis Workshop 14 simulated data, we tested the association between tagSNP genotype and disease over the tagSNP sets chosen by each method for each sampling scheme. This was repeated for 100 replicates to estimate power. The two allelic methods chose essentially all SNPs in the region and had nearly optimal power. The two haplotypic methods chose about half as many SNPs. The haplotypic methods had poor performance compared to the allelic methods in both regions. We expected an improvement in power when the selection sample contained cases; however, there was only moderate variation in power between the sampling approaches for each method. Finally, when compared to the haplotypic methods, the reference method performed as well or worse in the region with ancestral disease haplotype structure.
Genetic heterogeneity and complex biologic mechanisms of blood pressure regulation pose significant challenges to the identification of susceptibility loci influencing hypertension. Previous linkage studies have reported regions of interest, but lack consistency across studies. Incorporation of covariates, in particular the interaction between two independent risk factors (gender and BMI) greatly improved our ability to detect linkage.
We report a highly significant signal for linkage to chromosome 2p, a region that has been implicated in previous linkage studies, along with several suggestive linkage regions.
We demonstrate the importance of including covariates in the linkage analysis when the phenotype is complex.