Hugues Aschard

Effect of 17q21 Variants and Smoking Exposure in Early-Onset Asthma

BACKGROUND A genomewide association study has shown an association between variants at chromosome 17q21 and an increased risk of asthma. To elucidate the relationship between this locus and disease, we examined a large, family-based data set that included extensive phenotypic and environmental data from the Epidemiological Study on the Genetics and Environment of Asthma. METHODS We tested 36 single-nucleotide polymorphisms (SNPs) in the 17q21 region in 1511 subjects from 372 families for an association with asthma. We also tested for genetic heterogeneity according to the age at the onset of asthma and exposure to environmental tobacco smoke in early life. RESULTS Eleven SNPs were significantly associated with asthma (P<0.01), of which three (rs8069176, rs2305480, and rs4795400) were strongly associated (P<0.001). Ordered-subset regression analysis led us to select an onset at 4 years of age or younger to classify patients as having early-onset asthma. Association with early-onset asthma was highly significant (P<10(-5) for four SNPs), whereas no association was found with late-onset asthma. With respect to exposure to environmental tobacco smoke in early life, we observed a significant association with early-onset asthma only in exposed subjects (P<5x10(-5) for six SNPs). Under the best-fitting recessive model, homozygous status (GG) at the most strongly associated SNP (rs8069176) conferred an increase in risk by a factor of 2.9, as compared with other genotypes (AG and AA) in the group exposed to environmental tobacco smoke (P=2.8x10(-6); P=0.006 for the test for heterogeneity of the SNP effect on early-onset asthma between groups with tobacco exposure and those without such exposure). CONCLUSIONS This study shows that the increased risk of asthma conferred by 17q21 genetic variants is restricted to early-onset asthma and that the risk is further increased by early-life exposure to environmental tobacco smoke. These findings provide a greater understanding of the functional role of the 17q21 variants in the pathophysiology of asthma.

Fungal microbiota dysbiosis in IBD

Objective The bacterial intestinal microbiota plays major roles in human physiology and IBDs. Although some data suggest a role of the fungal microbiota in IBD pathogenesis, the available data are scarce. The aim of our study was to characterise the faecal fungal microbiota in patients with IBD. Design Bacterial and fungal composition of the faecal microbiota of 235 patients with IBD and 38 healthy subjects (HS) was determined using 16S and ITS2 sequencing, respectively. The obtained sequences were analysed using the Qiime pipeline to assess composition and diversity. Bacterial and fungal taxa associated with clinical parameters were identified using multivariate association with linear models. Correlation between bacterial and fungal microbiota was investigated using Spearmans test and distance correlation. Results We observed that fungal microbiota is skewed in IBD, with an increased Basidiomycota/Ascomycota ratio, a decreased proportion of Saccharomyces cerevisiae and an increased proportion of Candida albicans compared with HS. We also identified disease-specific alterations in diversity, indicating that a Crohns disease-specific gut environment may favour fungi at the expense of bacteria. The concomitant analysis of bacterial and fungal microbiota showed a dense and homogenous correlation network in HS but a dramatically unbalanced network in IBD, suggesting the existence of disease-specific inter-kingdom alterations. Conclusions Besides bacterial dysbiosis, our study identifies a distinct fungal microbiota dysbiosis in IBD characterised by alterations in biodiversity and composition. Moreover, we unravel here disease-specific inter-kingdom network alterations in IBD, suggesting that, beyond bacteria, fungi might also play a role in IBD pathogenesis.

Challenges and opportunities in genome-wide environmental interaction (GWEI) studies

The interest in performing gene–environment interaction studies has seen a significant increase with the increase of advanced molecular genetics techniques. Practically, it became possible to investigate the role of environmental factors in disease risk and hence to investigate their role as genetic effect modifiers. The understanding that genetics is important in the uptake and metabolism of toxic substances is an example of how genetic profiles can modify important environmental risk factors to disease. Several rationales exist to set up gene–environment interaction studies and the technical challenges related to these studies—when the number of environmental or genetic risk factors is relatively small—has been described before. In the post-genomic era, it is now possible to study thousands of genes and their interaction with the environment. This brings along a whole range of new challenges and opportunities. Despite a continuing effort in developing efficient methods and optimal bioinformatics infrastructures to deal with the available wealth of data, the challenge remains how to best present and analyze genome-wide environmental interaction (GWEI) studies involving multiple genetic and environmental factors. Since GWEIs are performed at the intersection of statistical genetics, bioinformatics and epidemiology, usually similar problems need to be dealt with as for genome-wide association gene–gene interaction studies. However, additional complexities need to be considered which are typical for large-scale epidemiological studies, but are also related to “joining” two heterogeneous types of data in explaining complex disease trait variation or for prediction purposes.

Genome-wide association analysis identifies TXNRD2, ATXN2 and FOXC1 as susceptibility loci for primary open-angle glaucoma

Primary open-angle glaucoma (POAG) is a leading cause of blindness worldwide. To identify new susceptibility loci, we performed meta-analysis on genome-wide association study (GWAS) results from eight independent studies from the United States (3,853 cases and 33,480 controls) and investigated the most significantly associated SNPs in two Australian studies (1,252 cases and 2,592 controls), three European studies (875 cases and 4,107 controls) and a Singaporean Chinese study (1,037 cases and 2,543 controls). A meta-analysis of the top SNPs identified three new associated loci: rs35934224[T] in TXNRD2 (odds ratio (OR) = 0.78, P = 4.05 × 10−11) encoding a mitochondrial protein required for redox homeostasis; rs7137828[T] in ATXN2 (OR = 1.17, P = 8.73 × 10−10); and rs2745572[A] upstream of FOXC1 (OR = 1.17, P = 1.76 × 10−10). Using RT-PCR and immunohistochemistry, we show TXNRD2 and ATXN2 expression in retinal ganglion cells and the optic nerve head. These results identify new pathways underlying POAG susceptibility and suggest new targets for preventative therapies.

Maximizing the Power of Principal-Component Analysis of Correlated Phenotypes in Genome-wide Association Studies

Many human traits are highly correlated. This correlation can be leveraged to improve the power of genetic association tests to identify markers associated with one or more of the traits. Principal component analysis (PCA) is a useful tool that has been widely used for the multivariate analysis of correlated variables. PCA is usually applied as a dimension reduction method: the few top principal components (PCs) explaining most of total trait variance are tested for association with a predictor of interest, and the remaining components are not analyzed. In this study we review the theoretical basis of PCA and describe the behavior of PCA when testing for association between a SNP and correlated traits. We then use simulation to compare the power of various PCA-based strategies when analyzing up to 100 correlated traits. We show that contrary to widespread practice, testing only the top PCs often has low power, whereas combining signal across all PCs can have greater power. This power gain is primarily due to increased power to detect genetic variants with opposite effects on positively correlated traits and variants that are exclusively associated with a single trait. Relative to other methods, the combined-PC approach has close to optimal power in all scenarios considered while offering more flexibility and more robustness to potential confounders. Finally, we apply the proposed PCA strategy to the genome-wide association study of five correlated coagulation traits where we identify two candidate SNPs that were not found by the standard approach.

A Comprehensive Analysis of In Vitro and In Vivo Genetic Fitness of Pseudomonas aeruginosa Using High-Throughput Sequencing of Transposon Libraries

High-throughput sequencing of transposon (Tn) libraries created within entire genomes identifies and quantifies the contribution of individual genes and operons to the fitness of organisms in different environments. We used insertion-sequencing (INSeq) to analyze the contribution to fitness of all non-essential genes in the chromosome of Pseudomonas aeruginosa strain PA14 based on a library of ∼300,000 individual Tn insertions. In vitro growth in LB provided a baseline for comparison with the survival of the Tn insertion strains following 6 days of colonization of the murine gastrointestinal tract as well as a comparison with Tn-inserts subsequently able to systemically disseminate to the spleen following induction of neutropenia. Sequencing was performed following DNA extraction from the recovered bacteria, digestion with the MmeI restriction enzyme that hydrolyzes DNA 16 bp away from the end of the Tn insert, and fractionation into oligonucleotides of 1,200–1,500 bp that were prepared for high-throughput sequencing. Changes in frequency of Tn inserts into the P. aeruginosa genome were used to quantify in vivo fitness resulting from loss of a gene. 636 genes had <10 sequencing reads in LB, thus defined as unable to grow in this medium. During in vivo infection there were major losses of strains with Tn inserts in almost all known virulence factors, as well as respiration, energy utilization, ion pumps, nutritional genes and prophages. Many new candidates for virulence factors were also identified. There were consistent changes in the recovery of Tn inserts in genes within most operons and Tn insertions into some genes enhanced in vivo fitness. Strikingly, 90% of the non-essential genes were required for in vivo survival following systemic dissemination during neutropenia. These experiments resulted in the identification of the P. aeruginosa strain PA14 genes necessary for optimal survival in the mucosal and systemic environments of a mammalian host.

17q21 variants modify the association between early respiratory infections and asthma

Single nucleotide polymorphisms (SNPs) at chromosome 17q21 confer an increased risk of early-onset asthma. The objective was to study whether 17q21 SNPs modify associations between early respiratory infections and asthma. Association analysis was conducted in 499 children (268 with asthma, median age 11 yrs) from the Epidemiological Study on the Genetics and Environment of Asthma (EGEA). The 12-yr follow-up data were used to assess persistent or remittent asthma in young adulthood. Respiratory infection before 2 yrs of age was assessed retrospectively. For the 12 17q21 SNPs studied, the odds ratios (OR) for association between infection and early-onset asthma (age at onset ≤4 yrs) were higher in carriers of risk genotypes (OR 3.42–6.36) than in noncarriers (OR 1.84–2.44; p-value for interaction 0.02–0.04 for five SNPs). Risk genotypes also increased the association between infection and childhood asthma that remits in adulthood (OR 4.84–7.16 in carriers and 1.74–2.25 in noncarriers; p-value for interaction 0.008–0.05 for 10 SNPs). In children with 17q21 risk genotypes and early-life environmental tobacco smoke (ETS) exposure, associations between infection and asthma were further enhanced. 17q21 genetic variants and early ETS exposure enhance the association between early respiratory infections and early-onset asthma and childhood asthma that remits in adulthood.

Adjusting for Heritable Covariates Can Bias Effect Estimates in Genome-Wide Association Studies

In recent years, a number of large-scale genome-wide association studies have been published for human traits adjusted for other correlated traits with a genetic basis. In most studies, the motivation for such an adjustment is to discover genetic variants associated with the primary outcome independently of the correlated trait. In this report, we contend that this objective is fulfilled when the tested variants have no effect on the covariate or when the correlation between the covariate and the outcome is fully explained by a direct effect of the covariate on the outcome. For all other scenarios, an unintended bias is introduced with respect to the primary outcome as a result of the adjustment, and this bias might lead to false positives. Here, we illustrate this point by providing examples from published genome-wide association studies, including large meta-analysis of waist-to-hip ratio and waist circumference adjusted for body mass index (BMI), where genetic effects might be biased as a result of adjustment for body mass index. Using both theory and simulations, we explore this phenomenon in detail and discuss the ramifications for future genome-wide association studies of correlated traits and diseases.

Inclusion of Gene-Gene and Gene-Environment Interactions Unlikely to Dramatically Improve Risk Prediction for Complex Diseases

Genome-wide association studies have identified hundreds of common genetic variants associated with the risk of multifactorial diseases. However, their impact on discrimination and risk prediction is limited. It has been suggested that the identification of gene-gene (G-G) and gene-environment (G-E) interactions would improve disease prediction and facilitate prevention. We conducted a simulation study to explore the potential improvement in discrimination if G-G and G-E interactions exist and are known. We used three diseases (breast cancer, type 2 diabetes, and rheumatoid arthritis) as motivating examples. We show that the inclusion of G-G and G-E interaction effects in risk-prediction models is unlikely to dramatically improve the discrimination ability of these models.

Enhanced in vivo fitness of carbapenem-resistant oprD mutants of Pseudomonas aeruginosa revealed through high-throughput sequencing

Significance It is thought antibiotic resistance carries a fitness cost and reduces microbial virulence. Using high-throughput sequencing analysis of a transposon insertion bank in Pseudomonas aeruginosa, we found enhanced fitness for in vivo mucosal colonization and systemic spread of strains with transposon insertions in the oprD gene. This conferred resistance to carbapenem antibiotics as well as enhanced resistance to killing at acidic pH and by normal human serum along with increased cytotoxicity against murine macrophages. RNA-sequencing analysis revealed that oprD deficiency led to transcriptional changes in numerous genes that may contribute to the enhanced in vivo fitness observed. Thus, if carbapenem resistance develops during antibiotic therapy of P. aeruginosa infections, it may lead to enhanced fitness and virulence in infected hosts. An important question regarding the biologic implications of antibiotic-resistant microbes is how resistance impacts the organism’s overall fitness and virulence. Currently it is generally thought that antibiotic resistance carries a fitness cost and reduces virulence. For the human pathogen Pseudomonas aeruginosa, treatment with carbapenem antibiotics is a mainstay of therapy that can lead to the emergence of resistance, often through the loss of the carbapenem entry channel OprD. Transposon insertion-site sequencing was used to analyze the fitness of 300,000 mutants of P. aeruginosa strain PA14 in a mouse model for gut colonization and systemic dissemination after induction of neutropenia. Transposon insertions in the oprD gene led not only to carbapenem resistance but also to a dramatic increase in mucosal colonization and dissemination to the spleen. These findings were confirmed in vivo with different oprD mutants of PA14 as well as with related pairs of carbapenem-susceptible and -resistant clinical isolates. Compared with OprD+ strains, those lacking OprD were more resistant to killing by acidic pH or normal human serum and had increased cytotoxicity against murine macrophages. RNA-sequencing analysis revealed that an oprD mutant showed dramatic changes in the transcription of genes that may contribute to the various phenotypic changes observed. The association between carbapenem resistance and enhanced survival of P. aeruginosa in infected murine hosts suggests that either drug resistance or host colonization can cause the emergence of more pathogenic, drug-resistant P. aeruginosa clones in a single genetic event.