Showing papers by "Florence Demenais published in 2017"

Vitamin D levels and susceptibility to asthma, elevated immunoglobulin E levels, and atopic dermatitis: A Mendelian randomization study.

Abstract: Background Low circulating vitamin D levels have been associated with risk of asthma, atopic dermatitis, and elevated total immunoglobulin E (IgE). These epidemiological associations, if true, would have public health importance, since vitamin D insufficiency is common and correctable. Methods and findings We aimed to test whether genetically lowered vitamin D levels were associated with risk of asthma, atopic dermatitis, or elevated serum IgE levels, using Mendelian randomization (MR) methodology to control bias owing to confounding and reverse causation. The study employed data from the UK Biobank resource and from the SUNLIGHT, GABRIEL and EAGLE eczema consortia. Using four single-nucleotide polymorphisms (SNPs) strongly associated with 25-hydroxyvitamin D (25OHD) levels in 33,996 individuals, we conducted MR studies to estimate the effect of lowered 25OHD on the risk of asthma (n = 146,761), childhood onset asthma (n = 15,008), atopic dermatitis (n = 40,835), and elevated IgE level (n = 12,853) and tested MR assumptions in sensitivity analyses. None of the four 25OHD-lowering alleles were associated with asthma, atopic dermatitis, or elevated IgE levels (p ≥ 0.2). The MR odds ratio per standard deviation decrease in log-transformed 25OHD was 1.03 (95% confidence interval [CI] 0.90–1.19, p = 0.63) for asthma, 0.95 (95% CI 0.69–1.31, p = 0.76) for childhood-onset asthma, and 1.12 (95% CI 0.92–1.37, p = 0.27) for atopic dermatitis, and the effect size on log-transformed IgE levels was −0.40 (95% CI −1.65 to 0.85, p = 0.54). These results persisted in sensitivity analyses assessing population stratification and pleiotropy and vitamin D synthesis and metabolism pathways. The main limitations of this study are that the findings do not exclude an association between the studied outcomes and 1,25-dihydoxyvitamin D, the active form of vitamin D, the study was underpowered to detect effects smaller than an OR of 1.33 for childhood asthma, and the analyses were restricted to white populations of European ancestry. This research has been conducted using the UK Biobank Resource and data from the SUNLIGHT, GABRIEL and EAGLE Eczema consortia. Conclusions In this study, we found no evidence that genetically determined reduction in 25OHD levels conferred an increased risk of asthma, atopic dermatitis, or elevated total serum IgE, suggesting that efforts to increase vitamin D are unlikely to reduce risks of atopic disease.

Functional variation in allelic methylomes underscores a strong genetic contribution and reveals novel epigenetic alterations in the human epigenome.

Abstract: Following publication of the original article [1], the authors reported an error in Additional file 1.

SigMod: an exact and efficient method to identify a strongly interconnected disease-associated module in a gene network

Abstract: Motivation Apart from single marker-based tests classically used in genome-wide association studies (GWAS), network-assisted analysis has become a promising approach to identify a set of genes associated with disease. To date, most network-assisted methods aim at finding genes connected in a background network, whatever the density or strength of their connections. This can hamper the findings as sparse connections are non-robust against noise from either the GWAS results or the network resource. Results We present SigMod, a novel and efficient method integrating GWAS results and gene network to identify a strongly interconnected gene module enriched in high association signals. Our method is formulated as a binary quadratic optimization problem, which can be solved exactly through graph min-cut algorithms. Compared to existing methods, SigMod has several desirable properties: (i) edge weights quantifying confidence of connections between genes are taken into account, (ii) the selection path can be computed rapidly, (iii) the identified gene module is strongly interconnected, hence includes genes of high functional relevance, and (iv) the method is robust against noise from either the GWAS results or the network resource. We applied SigMod to both simulated and real data. It was found to outperform state-of-the-art network-assisted methods in identifying disease-associated genes. When SigMod was applied to childhood-onset asthma GWAS results, it successfully identified a gene module enriched in consistently high association signals and made of functionally related genes that are biologically relevant for asthma. Availability and implementation An R package SigMod is available at: https://github.com/YuanlongLiu/SigMod. Contact yuanlong.liu@inserm.fr. Supplementary information Supplementary data are available at Bioinformatics online.

Adult onset asthma and interaction between genes and active tobacco smoking: The GABRIEL consortium

Abstract: BACKGROUND: Genome-wide association studies have identified novel genetic associations for asthma, but without taking into account the role of active tobacco smoking. This study aimed to identify novel genes that interact with ever active tobacco smoking in adult onset asthma. METHODS: We performed a genome-wide interaction analysis in six studies participating in the GABRIEL consortium following two meta-analyses approaches based on 1) the overall interaction effect and 2) the genetic effect in subjects with and without smoking exposure. We performed a discovery meta-analysis including 4,057 subjects of European descent and replicated our findings in an independent cohort (LifeLines Cohort Study), including 12,475 subjects. RESULTS: First approach: 50 SNPs were selected based on an overall interaction effect at p<10-4. The most pronounced interaction effect was observed for rs9969775 on chromosome 9 (discovery meta-analysis: ORint = 0.50, p = 7.63*10-5, replication: ORint = 0.65, p = 0.02). Second approach: 35 SNPs were selected based on the overall genetic effect in exposed subjects (p <10-4). The most pronounced genetic effect was observed for rs5011804 on chromosome 12 (discovery meta-analysis ORint = 1.50, p = 1.21*10-4; replication: ORint = 1.40, p = 0.03). CONCLUSIONS: Using two genome-wide interaction approaches, we identified novel polymorphisms in non-annotated intergenic regions on chromosomes 9 and 12, that showed suggestive evidence for interaction with active tobacco smoking in the onset of adult asthma.

Network-assisted analysis of GWAS data identifies a functionally-relevant gene module for childhood-onset asthma

Abstract: The number of genetic factors associated with asthma remains limited. To identify new genes with an undetected individual effect but collectively influencing asthma risk, we conducted a network-assisted analysis that integrates outcomes of genome-wide association studies (GWAS) and protein-protein interaction networks. We used two GWAS datasets, each consisting of the results of a meta-analysis of nine childhood-onset asthma GWASs (5,924 and 6,043 subjects, respectively). We developed a novel method to compute gene-level P-values (fastCGP), and proposed a parallel dense-module search and cross-selection strategy to identify an asthma-associated gene module. We identified a module of 91 genes with a significant joint effect on childhood-onset asthma (P < 10−5). This module contained a core subnetwork including genes at known asthma loci and five peripheral subnetworks including relevant candidates. Notably, the core genes were connected to APP (encoding amyloid beta precursor protein), a major player in Alzheimer’s disease that is known to have immune and inflammatory components. Functional analysis of the module genes revealed four gene clusters involved in innate and adaptive immunity, chemotaxis, cell-adhesion and transcription regulation, which are biologically meaningful processes that may underlie asthma risk. Our findings provide important clues for future research into asthma aetiology.

Gain of power of the general regression model compared to Cochran-Armitage Trend tests: simulation study and application to bipolar disorder

Abstract: Most genome-wide association studies assumed an additive model of inheritance which may result in significant loss of power when there is a strong departure from additivity. The General Regression Model (GRM), which allows performing an assumption-free test for association by testing for both additive effect and deviation from additive effect, may be more appropriate for association tests. Additionally, GRM allows testing the underlying genetic model. We compared the power of GRM association test to additive and other Cochran-Armitage Trend (CAT) tests through simulations and by applying GRM to a large case/control sample, the bipolar Welcome Trust Case Control Cohort data. Simulations were performed on two sets of case/control samples (1000/1000 and 2000/2000), using a large panel of genetic models. Four association tests (GRM and additive, recessive and dominant CAT tests) were applied to all replicates. We showed that GRM power to detect association was similar or greater than the additive CAT test, in particular in case of recessive inheritance, with up to 67% gain in power. GRM analysis of genome-wide bipolar disorder Welcome Trust Consortium data (1998 cases/3004 controls) showed significant association in the 16p12 region (rs420259; P = 3.4E-7) which has not been identified using the additive CAT test. As expected, rs42025 fitted a non-additive (recessive) model. GRM provides increased power compared to the additive CAT test for association studies and is easily applicable.

A novel role for ciliary function in atopy: ADGRV1 and DNAH5 interactions

Abstract: BACKGROUND: Atopy, an endotype underlying allergic diseases, has a substantial genetic component. OBJECTIVE: Our goal was to identify novel genes associated with atopy in asthma-ascertained families. METHODS: We implemented a three-step analysis strategy in three datasets: The Epidemiological study on the Genetics and Environment of Asthma (EGEA) dataset: 1,660 subjects; The Saguenay-Lac-Saint-Jean (SLSJ) dataset: 1,138 subjects; and The Medical Research Council (MRC) dataset: 446 subjects). This strategy included a single-SNP genome-wide association study (GWAS), the selection of related gene pairs based on statistical filtering of GWAS results and text-mining filtering using GRAIL and SNP-SNP interaction analysis of selected gene pairs. RESULTS: We identified the 5q14 locus, harboring the adhesion G protein-coupled receptor V1 (ADGRV1) gene, that showed genome-wide significant association with atopy (rs4916831; Pmeta=6.8x10-9). Statistical filtering of GWAS results followed by text-mining filtering revealed relationships between ADGRV1 and three genes showing suggestive association with atopy (P≤10-4). SNP-SNP interaction analysis between ADGRV1 and these three genes showed significant interaction between ADGRV1 rs17554723 and two correlated SNPs (rs2134256 and rs1354187) within dynein axonemal heavy chain 5 (DNAH5) gene (Pmeta-int=3.6x10-5 and 6.1x10-5, that met the multiple-testing corrected threshold of 7.3x10-5). Further conditional analysis indicated that rs2134256 alone accounted for the interaction signal with rs17554723. CONCLUSION: As both DNAH5 and ADGRV1 contribute to function of cilia, this study suggests that cilia dysfunction may represent a novel mechanism underlying atopy. Combining GWAS and epistasis analysis driven by statistical and knowledge-based evidence represents a promising approach for identifying new genes involved in complex traits.