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See detailGenetic variations in toll-like receptor pathway and lung function decline in Cystic fibrosis patients.
Haerynck, F.; Mahachie John, Jestinah ULg; Van Steen, Kristel ULg et al

in Human immunology (2013), 74(12), 1649-55

The toll-like receptor (TLR) family maintains pulmonary homeostasis by pathogen recognition, clearance and regulation of inflammation. Genes affecting inflammation response play a key role in modifying ... [more ▼]

The toll-like receptor (TLR) family maintains pulmonary homeostasis by pathogen recognition, clearance and regulation of inflammation. Genes affecting inflammation response play a key role in modifying Cystic fibrosis (CF) lung disease severity. We assessed the impact of single nucleotide polymorphisms (SNPs) of TLR genes (TLR1 to TLR10, CD14, lipopolyssacharide-binding protein (LBP)) on lung function in CF patients. Each SNP was tested for time-dependent effect on FEV1, using six genetic models. In addition, we investigated associations between SNP genotypes and extreme subject specific slopes of FEV1 decline. Variant alleles of polymorphisms of TLR2 rs1898830, rs5743708, and rs3804100 demonstrated a consistent association with lung disease severity (p = 0.008, p = 0.006 and p = 0.029 respectively). Patients homozygous for variant C allele of TLR5 polymorphism rs5744174 are more frequently associated with extreme fast FEV1 decline (OR: 20 (95% Confidence Interval:1.85-216.18)). Patients homozygous AA for TLR1 polymorphism rs5743551 are more frequently associated with faster decline of FEV1 compared to heterozygous genotype (OR:7.33 (95% CI:1.63-33.11). Our findings indicate that variations in TLR1, TLR2 and TLR5 genes may influence CF lung function decline. Further functional analysis is required to provide new insights into the pathogenesis of TLRs in CF lung disease severity. [less ▲]

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See detailLarge Sample Size, Wide Variant Spectrum, and Advanced Machine-Learning Technique Boost Risk Prediction for Inflammatory Bowel Disease.
Wei, Zhi; Wang, Wei; Bradfield, Jonathan et al

in American Journal of Human Genetics (2013)

We performed risk assessment for Crohn's disease (CD) and ulcerative colitis (UC), the two common forms of inflammatory bowel disease (IBD), by using data from the International IBD Genetics Consortium's ... [more ▼]

We performed risk assessment for Crohn's disease (CD) and ulcerative colitis (UC), the two common forms of inflammatory bowel disease (IBD), by using data from the International IBD Genetics Consortium's Immunochip project. This data set contains ?17,000 CD cases, ?13,000 UC cases, and ?22,000 controls from 15 European countries typed on the Immunochip. This custom chip provides a more comprehensive catalog of the most promising candidate variants by picking up the remaining common variants and certain rare variants that were missed in the first generation of GWAS. Given this unprecedented large sample size and wide variant spectrum, we employed the most recent machine-learning techniques to build optimal predictive models. Our final predictive models achieved areas under the curve (AUCs) of 0.86 and 0.83 for CD and UC, respectively, in an independent evaluation. To our knowledge, this is the best prediction performance ever reported for CD and UC to date. [less ▲]

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See detailSurvival analysis: finding relevant epistatic SNP pairs using Model- Based Multifactor Dimensionality Reduction
Van Lishout, François ULg; Vens, Céline; Urrea, Victor et al

Conference (2012, December 03)

Analyzing the combined effects of genes (and/or environmental factors) on the development of complex diseases is quite challenging, both from the statistical and computational perspective, even using a ... [more ▼]

Analyzing the combined effects of genes (and/or environmental factors) on the development of complex diseases is quite challenging, both from the statistical and computational perspective, even using a relatively small number of genetic and non-genetic exposures. Several data-mining methods have been proposed for interaction analysis, among them, the Multifactor Dimensionality Reduction Method (MDR). Model-Based Multifactor Dimensionality Reduction (MB-MDR), a relatively new dimensionality reduction technique, is able to unify the best of both nonparametric and parametric worlds, and has proven its utility in a variety of theoretical and practical settings. Until now, MB-MDR software has only accommodated traits that are measured on a binary or interval scale. Time-to-event data could therefore not be analyzed with the MB-MDR methodology. MB-MDR-3.0.0 overcomes this shortcoming of earlier versions. We show the added value of MB-MDR for censored traits by comparing the implemented strategies with more classical methods such as those based on a parametric regression paradigm. The simulation results are supplemented with an application to real-life data. [less ▲]

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See detailPrognostic Value of Serologic and Histologic Markers on Clinical Relapse in Ulcerative Colitis Patients With Mucosal Healing
Bessissow, Talat; Lemmens, Bart; Ferrante, Marc et al

in American Journal of Gastroenterology (2012), 11(107), 1684-92

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See detailActive Foxp3 (+) Regulatory T Cells Rather Than Other Foxp3 (+) T Cells Subsets CorrelateWith Clinical Response To Infliximab Therapy For IBD
Li, Z; Vermeire, S; Bullens, D et al

Poster (2012, October)

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See detailRestoration Of B Cells Correlates With Clinical Response To Anti-Tnf Therapy
Li, Z; Vermeire, S; Bullens, D et al

Poster (2012, October)

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See detailIntegrating biological information in genome-wide association interaction (GWAI) studies.
Gusareva, Elena ULg; Van Steen, Kristel ULg

Poster (2012, May 30)

Genome-wide association (GWA) studies of Crohn's disease have identified numerous genes. However, a substantial portion of the heritability of this disease remains unexplained. Some gene variants, not ... [more ▼]

Genome-wide association (GWA) studies of Crohn's disease have identified numerous genes. However, a substantial portion of the heritability of this disease remains unexplained. Some gene variants, not detectable via main effects GWA study, may manifest themselves only in interaction with other variants. To search for interacting genes involved in the regulation of Crohn's disease, we performed GWA epistasis screening in a large human cohort (1851 cases/2938 controls) belonging to the Wellcome Trust Case Control Consortium (WTCCC). All subjects were genotyped with the GeneChip 500K Mapping Array Set (Affymetrix chip). SNPs that passed our quality control (359,479 SNPs) were processed in Biofilter (a software package that looks for candidate epistatic genes contributing to disease risk) giving rise to 14,185 SNPs. Subsequent MB-MDR epistasis screening, highlighted evidence for statistical epistasis for 6 SNP pairs. Four of these pairs involve interaction on between the HTR3B and USP28 genes (chromosome 11). One pair involves an interaction between the SLED1 and ACSL1 genes (chromosome 4). Another pair involves an interaction between PTPN22 (chromosome 1) and a SNP located between USPL1 and ALOX5AP (chromosome 13). Notably, when mapped to the same genomic regions, the interacting SNPs were not in linkage disequilibrium (r^2 < 0.11). All results were corrected for potential main SNP effects and were corrected for multiple testing on 7072 SNPs (i.e., 25,003,056 pairs). We investigated the consistency of these findings using different methodologies, including information-based, LD comparison-based and regression-based approaches. We also investigated the utility of using prior information from biological interaction data bases in novel epistasis discoveries, as well as the utility of biological data bases in interpreting a posterior identified statistical epistasis pairs. Our findings may provide new leads on important pathways involved in Crohn's disease. [less ▲]

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See detailFactors determining therapeutic strategy at diagnosis and evolution of disease severity in a cohort of Belgian pediatric Crohn's disease patients (BELCRO)
De Greef, E; Mahachie John, Jestinah; Hoffman, I et al

in Gastroenterology (2012)

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See detailSequential T2 Relaxometry as a Non-Invasive Assessment of Transmural Inflammation in a Murine Model of Chronically Relapsing Colitis
Breynaert, C; Dresselaers, T; Cremer, J et al

Poster (2012, May)

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See detailRepeated cycles of DSS inducing a chronically relapsing inflammation: a novel model to study fibrosis using in vivo MRI T2 relaxometry
Breynaert, C; Dresselaers, T; Cremer, J et al

Poster (2012, May)

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See detailApplication of mixed polygenic model to control for cryptic/genuine relatedness and population stratification.
Gusareva, Elena ULg; Mahachie John, Jestinah ULg; Isaacs, Aaron et al

Poster (2012, March 12)

In genome-wide association studies (GWAs), population stratification may cause inflated type I errors and overly-optimistic test results, when not properly corrected for. During the past decade, several ... [more ▼]

In genome-wide association studies (GWAs), population stratification may cause inflated type I errors and overly-optimistic test results, when not properly corrected for. During the past decade, several methods have been proposed for association testing in the presence of population stratification. Among these, principal components-based approaches are the most popular. Principal component analysis (PCA) allows data transformation to a new coordinate system such that the projection of the data along the first new coordinate (called the PC1) has the largest variance; the second PC has the second largest variance, and so on. In practice, two components are usually enough to adjust or to control for population stratification. They can easily be included in parametric association models as covariates. Despite the success of this strategy, there are still some caveats which need further attention. Among these are that principal component-based methods generally do not account for cryptic relatedness (kinship) between supposedly unrelated individuals, are not straightforwardly adapted to accommodate family-based designs or mixtures of families and unrelated individuals, and do not always take proper account of the trait under investigation. In this work, we present an easy-to-use alternative that addresses the aforementioned issues. For quantitative traits, we propose to first use the mixed polygenic model (possibly taking into account important non-genetic confounders as covariates), second to derive “polygenic” residuals from this model – hereby removing genomic kinship relationships, and third to consider these residuals as new traits in a classical genome-wide QTL analysis for “unrelated individuals”. The polygenic component of the aforementioned mixed polygenic model describes the contribution from multiple independently segregating genes, all having a small additive effect on the trait under investigation. Via an extensive simulation study, with various settings of population stratification and admixture, we show that this approach not only removes most of the “relatedness” between individuals (cryptic relatedness or known relatedness), but also removes most of the remaining substructures caused by population stratification or admixture. As a proof of concept, we demonstrate the efficiency of this robust method to control for population stratification on real-life genome-scale data from the SNP Health Association Resource (SHARe) Asthma Resource project (SHARP) (dbGaP accession number phs000166.v2.p1). We also provide leads to extend this method to dichotomous traits. [less ▲]

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See detailGenetic and functional evidence for a role of CYLD in Crohn’s Disease: results from a European consortium
Cleynen, I; Vazeille, E; Artieda, M et al

in Journal of Crohn’s and Colitis [=JCC] (2012)

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See detailMultiple functional variants at the 3p21 locus contribute to ulcerative colitis: Results from a European consortium
Cleynen, I; Artieda, M; Verspaget, H et al

in Journal of Crohn’s and Colitis [=JCC] (2012)

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See detailRepeated cycles of DSS inducing a chronically relapsing inflammation: A novel model to study fibrosis using in vivo MRI T2 relaxometry
Breynaert, C; Dresselaers, T; Cremer, J et al

Poster (2012, February)

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See detailLower-Order Effects Adjustment in Quantitative Traits Model-Based Multifactor Dimensionality Reduction
Mahachie John, Jestinah ULg; Cattaert, Tom ULg; Van Lishout, François ULg et al

in PLoS ONE (2012)

Identifying gene-gene interactions or gene-environment interactions in studies of human complex diseases remains a big challenge in genetic epidemiology. An additional challenge, often forgotten, is to ... [more ▼]

Identifying gene-gene interactions or gene-environment interactions in studies of human complex diseases remains a big challenge in genetic epidemiology. An additional challenge, often forgotten, is to account for important lower-order genetic effects. These may hamper the identification of genuine epistasis. If lower-order genetic effects contribute to the genetic variance of a trait, identified statistical interactions may simply be due to a signal boost of these effects. In this study, we restrict attention to quantitative traits and bi-allelic SNPs as genetic markers. Moreover, our interaction study focuses on 2- way SNP-SNP interactions. Via simulations, we assess the performance of different corrective measures for lower-order genetic effects in Model-Based Multifactor Dimensionality Reduction epistasis detection, using additive and co-dominant coding schemes. Performance is evaluated in terms of power and familywise error rate. Our simulations indicate that empirical power estimates are reduced with correction of lower-order effects, likewise familywise error rates. Easy-to-use automatic SNP selection procedures, SNP selection based on ‘‘top’’ findings, or SNP selection based on p-value criterion for interesting main effects result in reduced power but also almost zero false positive rates. Always accounting for main effects in the SNP-SNP pair under investigation during Model-Based Multifactor Dimensionality Reduction analysis adequately controls false positive epistasis findings. This is particularly true when adopting a co-dominant corrective coding scheme. In conclusion, automatic search procedures to identify lower-order effects to correct for during epistasis screening should be avoided. The same is true for procedures that adjust for lower-order effects prior to Model-Based Multifactor Dimensionality Reduction and involve using residuals as the new trait. We advocate using ‘‘on-the-fly’’ lower-order effects adjusting when screening for SNP-SNP interactions using Model-Based Multifactor Dimensionality Reduction analysis. [less ▲]

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See detailFactors determining therapeutic strategy at diagnosis and evolution of disease severity in a cohort of Belgian pediatric Crohn’s disease patients (BELCRO)
De Greef, E; Mahachie John, Jestinah; Hoffman, I et al

in Acta Gastro-Enterologica Belgica (2012)

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See detailSafety And Cost Of Infliximab For The Treatment Of Belgian Pediatric Patients With Crohn’s Disease
De Greef, E; Hoffman, I; D'haens, G et al

in Journal of Crohn’s and Colitis (2012)

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See detailEffects of domperidone on QTc interval in infants
Vieira, MC; Miyague, NI; Van Steen, Kristel ULg et al

in Acta Paediatrica (2012), 101(5), 494-496

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