References of "Mahachie John, Jestinah"
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See detailAssociation of IL33-IL-1 receptor-like 1 (IL1RL1) pathway polymorphisms with wheezing phenotypes and asthma in childhood.
Savenije, Olga E.; Mahachie John, Jestinah ULg; Granell, Raquel et al

in The Journal of allergy and clinical immunology (2014)

BACKGROUND: Genome-wide association studies identified IL33 and IL-1 receptor-like 1 (IL1RL1)/IL18R1 as asthma susceptibility loci. IL33 and IL1RL1 constitute a single ligand-receptor pathway. OBJECTIVE ... [more ▼]

BACKGROUND: Genome-wide association studies identified IL33 and IL-1 receptor-like 1 (IL1RL1)/IL18R1 as asthma susceptibility loci. IL33 and IL1RL1 constitute a single ligand-receptor pathway. OBJECTIVE: In 2 birth cohorts, the Prevalence and Incidence of Asthma and Mite Allergy (PIAMA) study and Avon Longitudinal Study of Parents and Children (ALSPAC), we analyzed associations of longitudinal wheezing phenotypes and asthma with single nucleotide polymorphisms (SNPs) of 8 genes encoding IL-33, IL1RL1, its coreceptor IL1RAcP, its adaptors myeloid differentiation primary response gene 88 (MyD88) and Toll-IL-11 receptor domain containing adaptor protein (TIRAP), and the downstream IL-1 receptor-associated kinase 1, IL-1 receptor-associated kinase 4, and TNF receptor-associated factor 6 (TRAF6). Furthermore, we investigated whether SNPs in this pathway show replicable evidence of gene-gene interaction. METHODS: Ninety-four SNPs were investigated in 2007 children in the PIAMA study and 7247 children in ALSPAC. Associations with wheezing phenotypes and asthma at 8 years of age were analyzed in each cohort and subsequently meta-analyzed. Gene-gene interactions were assessed through model-based multifactor dimensionality reduction in the PIAMA study, and gene-gene interactions of 10 SNP pairs were further evaluated. RESULTS: Intermediate-onset wheeze was associated with SNPs in several genes in the IL33-IL1RL1 pathway after applying multiple testing correction in the meta-analysis: 2 IL33 SNPs (rs4742170 and rs7037276), 1 IL-1 receptor accessory protein (IL1RAP) SNP (rs10513854), and 1 TRAF6 SNP (rs5030411). Late-onset wheeze was associated with 2 IL1RL1 SNPs (rs10208293 and rs13424006), and persistent wheeze was associated with 1 IL33 SNP (rs1342326) and 1 IL1RAP SNP (rs9290936). IL33 and IL1RL1 SNPs were nominally associated with asthma. Three SNP pairs showed interaction for asthma in the PIAMA study but not in ALSPAC. CONCLUSIONS: IL33-IL1RL1 pathway polymorphisms are associated with asthma and specific wheezing phenotypes; that is, most SNPs are associated with intermediate-onset wheeze, a phenotype closely associated with sensitization. We speculate that IL33-IL1RL1 pathway polymorphisms affect development of wheeze and subsequent asthma through sensitization in early childhood. [less ▲]

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See detailGenome-wide environmental interaction analysis using multidimensional data reduction principles to identify asthma pharmacogenetic loci in relation to corticosteroid therapy
Van Lishout, François ULg; Bessonov, Kyrylo ULg; Duan, Quingling et al

Poster (2013, October 25)

Genome-wide gene-environment (GxE) and gene-gene (GxG) interaction studies share a lot of challenges via the common genetic component they involve. GWEI studies may therefore benefit from the abundance of ... [more ▼]

Genome-wide gene-environment (GxE) and gene-gene (GxG) interaction studies share a lot of challenges via the common genetic component they involve. GWEI studies may therefore benefit from the abundance of methodologies that are available in the context of genome-wide epistasis detection methods. One of these is Model-Based Multifactor Dimensionality Reduction (MB-MDR), which does not make any assumption about the genetic inheritance model. MB-MDR involves reducing a high-dimensional GxE space to GxE factor levels that either exhibit high or low or no evidence for their association to disease outcome. In contrast to logistic regression and random forests, MB-MDR can be used to detect GxE interactions in the absence of any main effects or when sample sizes are too small to be able to model all main and GxE interaction effects. In this ongoing study, we demonstrate the opportunities and challenges of MB-MDR for genome-wide GxE interaction analysis and analyzed the difference in prebronchodilator FEV1 following 8 weeks of inhaled corticosteroid therapy, for 565 pediatric Caucasian CAMP (ages 5-12) from the SHARE project. [less ▲]

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See detailTherapeutic Strategy and Patient Outcome during the First 2 Years of Pediatric Crohn’s Disease
Veereman, G; Mahachie John, Jestinah ULg; De Greef, E et al

in Journal of Pediatric Gastroenterology and Nutrition (2013, May)

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See detailAn efficient algorithm to perform multiple testing in epistasis screening
Van Lishout, François ULg; Mahachie John, Jestinah ULg; Gusareva, Elena ULg et al

in BMC Bioinformatics (2013), 14

Background: Research in epistasis or gene-gene interaction detection for human complex traits has grown over the last few years. It has been marked by promising methodological developments, improved ... [more ▼]

Background: Research in epistasis or gene-gene interaction detection for human complex traits has grown over the last few years. It has been marked by promising methodological developments, improved translation efforts of statistical epistasis to biological epistasis and attempts to integrate different omics information sources into the epistasis screening to enhance power. The quest for gene-gene interactions poses severe multiple-testing problems. In this context, the maxT algorithm is one technique to control the false-positive rate. However, the memory needed by this algorithm rises linearly with the amount of hypothesis tests. Gene-gene interaction studies will require a memory proportional to the squared number of SNPs. A genome-wide epistasis search would therefore require terabytes of memory. Hence, cache problems are likely to occur, increasing the computation time. In this work we present a new version of maxT, requiring an amount of memory independent from the number of genetic effects to be investigated. This algorithm was implemented in C++ in our epistasis screening software MBMDR-3.0.3. We evaluate the new implementation in terms of memory efficiency and speed using simulated data. The software is illustrated on real-life data for Crohn's disease. Results: In the case of a binary (affected/unaffected) trait, the parallel workflow of MBMDR-3.0.3 analyzes all gene-gene interactions with a dataset of 100,000 SNPs typed on 1000 individuals within 4 days and 9 hours, using 999 permutations of the trait to assess statistical significance, on a cluster composed of 10 blades, containing each four Quad-Core AMD Opteron Processor 2352 2.1 GHz. In the case of a continuous trait, a similar run takes 9 days. Our program found 14 SNP-SNP interactions with a multiple-testing corrected p-value of less than 0.05 on real-life Crohn's disease data. Conclusions: Our software is the first implementation of the MB-MDR methodology able to solve large-scale SNP-SNP interactions problems within a few days, without using much memory, while adequately controlling the type I error rates. A new implementation to reach genome-wide epistasis screening is under construction. In the context of Crohn's disease, MBMDR-3.0.3 could identify epistasis involving regions that are well known in the field and could be explained from a biological point of view. This demonstrates the power of our software to find relevant phenotype-genotype higher-order associations. [less ▲]

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See detailTherapeutic Strategy and Patient Outcome during the First 2 Years of Pediatric Crohn’s Disease
Veereman, G; Mahachie John, Jestinah ULg; De Greef, E et al

in Acta Gastro-Enterologica Belgica (2013)

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See detailProfile of pediatric Crohn's disease in Belgium.
De Greef, E.; Mahachie John, Jestinah ULg; Hoffman, I. et al

in Journal of Crohn's & colitis (2013), 7(11), 588-98

AIM: A Belgian registry for pediatric Crohn's disease, BELCRO, was created. This first report aims at describing disease presentation and phenotype and determining associations between variables at ... [more ▼]

AIM: A Belgian registry for pediatric Crohn's disease, BELCRO, was created. This first report aims at describing disease presentation and phenotype and determining associations between variables at diagnosis and registration in the database. METHODS: Through a collaborative network, children with previously established Crohn's disease and newly diagnosed children and adolescents (under 18 y of age) were recruited over a 2 year period. Data were collected by 23 centers and entered in a database. Statistical association tests analyzed relationships between variables of interest at diagnosis. RESULTS: Two hundred fifty-five patients were included. Median age at diagnosis was 12.5 y (range: 1.6-18 y); median duration of symptoms prior to diagnosis was 3 m (range: 1-12 m). Neonatal history and previous medical history did not influence disease onset nor disease behavior. Fifty three % of these patients presented with a BMI z-score < -1. CRP was an independent predictor of disease severity. Steroids were widely used as initial treatment in moderate to severe and extensive disease. Over time, immunomodulators and biological were prescribed more frequently, reflecting a lower prescription rate for steroids and 5-ASA. A positive family history was the sole significant determinant for earlier use of immunosuppression. CONCLUSION: In Belgium, the median age of children presenting with Crohn's disease is 12.5 y. Faltering growth, extensive disease and upper GI involvement are frequent. CRP is an independent predictive factor of disease activity. A positive family history appears to be the main determinant for initial treatment choice. [less ▲]

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See detailMolecular reclassification of Crohn's disease: a cautionary note on population stratification.
Maus, Barbel; Jung, Camille; Mahachie John, Jestinah ULg et al

in PloS one (2013), 8(10), 77720

Complex human diseases commonly differ in their phenotypic characteristics, e.g., Crohn's disease (CD) patients are heterogeneous with regard to disease location and disease extent. The genetic ... [more ▼]

Complex human diseases commonly differ in their phenotypic characteristics, e.g., Crohn's disease (CD) patients are heterogeneous with regard to disease location and disease extent. The genetic susceptibility to Crohn's disease is widely acknowledged and has been demonstrated by identification of over 100 CD associated genetic loci. However, relating CD subphenotypes to disease susceptible loci has proven to be a difficult task. In this paper we discuss the use of cluster analysis on genetic markers to identify genetic-based subgroups while taking into account possible confounding by population stratification. We show that it is highly relevant to consider the confounding nature of population stratification in order to avoid that detected clusters are strongly related to population groups instead of disease-specific groups. Therefore, we explain the use of principal components to correct for population stratification while clustering affected individuals into genetic-based subgroups. The principal components are obtained using 30 ancestry informative markers (AIM), and the first two PCs are determined to discriminate between continental origins of the affected individuals. Genotypes on 51 CD associated single nucleotide polymorphisms (SNPs) are used to perform latent class analysis, hierarchical and Partitioning Around Medoids (PAM) cluster analysis within a sample of affected individuals with and without the use of principal components to adjust for population stratification. It is seen that without correction for population stratification clusters seem to be influenced by population stratification while with correction clusters are unrelated to continental origin of individuals. [less ▲]

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See detailGenetic and microbial factors modulating the ubiquitin proteasome system in inflammatory bowel disease.
Cleynen, Isabelle; Vazeille, Emilie; Artieda, Marta et al

in Gut (2013)

OBJECTIVE: Altered microbiota composition, changes in immune responses and impaired intestinal barrier functions are observed in IBD. Most of these features are controlled by proteases and their ... [more ▼]

OBJECTIVE: Altered microbiota composition, changes in immune responses and impaired intestinal barrier functions are observed in IBD. Most of these features are controlled by proteases and their inhibitors to maintain gut homeostasis. Unrestrained or excessive proteolysis can lead to pathological gastrointestinal conditions. The aim was to validate the identified protease IBD candidates from a previously performed systematic review through a genetic association study and functional follow-up. DESIGN: We performed a genetic association study in a large multicentre cohort of patients with Crohn's disease (CD) and UC from five European IBD referral centres in a total of 2320 CD patients, 2112 UC patients and 1796 healthy controls. Subsequently, we did an extensive functional assessment of the candidate genes to explore their causality in IBD pathogenesis. RESULTS: Ten single nucleotide polymorphisms (SNPs) in four genes were significantly associated with CD: CYLD, USP40, APEH and USP3. CYLD was the most significant gene with the intronically located rs12324931 the strongest associated SNP (pFDR=1.74e-17, OR=2.24 (1.83 to 2.74)). Five SNPs in four genes were significantly associated with UC: USP40, APEH, DAG1 and USP3. CYLD, as well as some of the other associated genes, is part of the ubiquitin proteasome system (UPS). We therefore determined if the IBD-associated adherent-invasive Escherichia coli (AIEC) can modulate the UPS functioning. Infection of intestinal epithelial cells with the AIEC LF82 reference strain modulated the UPS turnover by reducing poly-ubiquitin conjugate accumulation, increasing 26S proteasome activities and decreasing protein levels of the NF-kappaB regulator CYLD. This resulted in IkappaB-alpha degradation and NF-kappaB activation. This activity was very important for the pathogenicity of AIEC since decreased CYLD resulted in increased ability of AIEC LF82 to replicate intracellularly. CONCLUSIONS: Our results reveal the UPS, and CYLD specifically, as an important contributor to IBD pathogenesis, which is favoured by both genetic and microbial factors. [less ▲]

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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 detailGenomic Association Screening Methodology for High-Dimensional and Complex Data Structures: Detecting n-Order Interactions
Mahachie John, Jestinah ULg

Doctoral thesis (2012)

We developed a data-mining method, Model-Based Multifactor Dimensionality Reduction (MB-MDR) to detect epistatic interactions for different types of traits. MB-MDR enables the fast identification of gene ... [more ▼]

We developed a data-mining method, Model-Based Multifactor Dimensionality Reduction (MB-MDR) to detect epistatic interactions for different types of traits. MB-MDR enables the fast identification of gene-gene interactions among 1000nds of SNPs, without the need to make restrictive assumptions about the genetic modes of inheritance. This thesis primarily focused on applying Model-Based Multifactor Dimensionality Reduction for quantitative traits, its performance and application to a variety of data problems. We carried out several simulation studies to evaluate quantitative MB-MDR in terms of power and type I error, when data are noisy, non-normal or skewed and when important main effects are present. Firstly, we assessed the performance of MB-MDR in the presence of noisy data. The error sources considered were missing genotypes, genotyping error, phenotypic mixtures and genetic heterogeneity. Results from this study showed that MB-MDR is least affected by presence of small percentages of missing data and genotyping errors but much affected in the presence of phenotypic mixtures and genetic heterogeneity. This is in line with a similar study performed for binary traits. Although both Multifactor Dimensionality Reduction (MDR) and MB-MDR are data reduction techniques with a common basis, their ways of deriving significant interactions are substantially different. Nevertheless, effects on power of introducing error sources were quite similar. Irrespective of the trait under consideration, epistasis screening methodologies such as MB-MDR and MDR mainly suffer from the presence of phenotypic mixtures and genetic heterogeneity. Secondly, we extensively addressed the issue of adjusting for lower-order genetic effects during epistasis screening, using different adjustment strategies for SNPs in the functional SNP-SNP interaction pair, and/or for additional important SNPs. Since, in this thesis, we restrict attention to 2-locus interactions only, adjustment for lower-order effects always (and only) implies adjustment for main genetic effects. Unfortunately most data dimensionality reduction techniques based on MDR do not explicitly require that lower-order effects are included in the ‘model’ when investigating higher-order effects (a prerequisite for most traditional, especially regression-based, methods). However, epistasis results may be hampered by the presence of significant lower-order effects. Results from this study showed hugely increased type I errors when main effects were not taken into account or were not properly accounted for. We observed that additive coding (the most commonly used coding in practice) in main effects adjustment does not remove all of the potential main effects that deviate from additive genetic variance. In addition, also adjusting for main effects prior to MB-MDR (via a regression framework), whatever coding is adopted, does not control type I error in all scenarios. From this study, we concluded that correction for lower-order effects should preferentially be done via codominant coding, to reduce the chance of false positive epistasis findings. The recommended way of performing an MB-MDR epistasis screening is to always adjust the analysis for lower-order effects of the SNPs under investigation, “on-the-fly”. This correction avoids overcorrection for other SNPs, which are not part of the interacting SNP pair under study. Thirdly, we assessed the cumulative effect of trait deviations from normality and homoscedasticity on the overall performance of quantitative MB-MDR to detect 2-locus epistasis signals in the absence of main effects. Although MB-MDR itself is a non-parametric method, in the sense that no assumptions are made regarding genetic modes of inheritance, the data reduction part in MB-MDR relies on association tests. In particular, for quantitative traits, the default MB-MDR way is to use the Student’s t-test (steps 1 and 2 of MB-MDR). Also when correcting for lower-order effects during quantitative MB-MDR analysis, we intrinsically maneuver within a regression framework. Since the Student’s t-statistic is the square root of the ANOVA F-statistic. Hence, along these lines, for MB-MDR to give valid results, ANOVA assumptions have to be met. Therefore, we simulated data from normal and non-normal distributions, with constant and non-constant variances, and performed association tests via the student’s t-test as well as the unequal variance t-test, commonly known as the Welch’s t-test. At first somewhat surprising, the results of this study showed that MB-MDR maintains adequate type I errors, irrespective of data distribution or association test used. On the other hand, MB-MDR give rise to lower power results for non-normal data compared to normal data. With respect to the association tests used within MB-MDR, in most cases, Welch’s t-test led to lower power compared to student’s t-test. To maintain the balance between power and type I error, we concluded that when performing MB-MDR analysis with quantitative traits, one ideally first rank-transforms traits to normality and then applies MB-MDR modeling with Student’s t-test as choice of association test. Clearly, before embarking on using a method in practice, there is a need to extensively check the applicability of the method to the data at hand. This is a common practice in biostatistics, but often a forgotten standard operating procedure in genetic epidemiology, in particular in GWAI studies. In addition to the presentation of extensive simulation studies, we also presented some MB-MDR applications to real-life data problems. These analyses involved MB-MDR analyses on quantitative as well as binary complex disease traits, primarily in the context of asthma/allergy and Crohn’s disease. In two of the presented analyses, MB-MDR confirmed logistic regression and transmission disequilibrium test (TDT) results. Part of the aforementioned methodological developments was initiated on the basis of observations of MB-MDR behavior on real-life data. Both the practical and theoretical components of this thesis confirm our belief in the potential of MB-MDR as a promising and versatile tool for the identification of epistatic effects, irrespective of the design (family-based or unrelated individuals) and irrespective of the targeted disease trait (binary, continuous, censored, categorical, multivariate). A thorough characterization of the different faces of MB-MDR this versatility gives rise to is work in progress. [less ▲]

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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 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 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 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 Acta Gastro-Enterologica Belgica (2012), 75(4), 425-31

Biologicals have become an important component in the treatment of Crohn's disease in children. Their increased and long term use raises safety concerns. We describe safety and cost of infliximab in ... [more ▼]

Biologicals have become an important component in the treatment of Crohn's disease in children. Their increased and long term use raises safety concerns. We describe safety and cost of infliximab in Belgian pediatric Crohn's disease patients. All patients on infliximab as part of the present or past treatment for Crohn's Disease until January 1st 2011 were selected from an existing database. Information on disease phenotype, medication and adverse events were extracted. Adverse events occurred in 25.9% of patients exposed to infliximab of which 29.6% were severe. In total 31.7% of patients stopped infliximab therapy. The main reasons for discontinuation were adverse events in 45.4% and loss of response in 30.3%. No malignancies or lethal complications occurred over this 241 patient year observation period. Immunomodulators were concomitant medication in 75% of patients and were discontinued subsequently in 38.4% of them. The cost of infliximab infusions per treated patient per year in the Belgian health care setting is approximately 9 474 euro, including only medication and hospital related costs. Even though infliximab is relatively safe in pediatric CD on the short term, close follow-up and an increased awareness of the possible adverse reactions is highly recommended. Adverse reactions appeared in 25.9% of all patients and were the main reason for discontinuation. Treatment cost has to be balanced against efficacy and modifications in disease course. In the Belgian health care system, the medication is available to all patients with moderate to severe CD. [less ▲]

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See detailDoes pet ownership in infancy lead to asthma or allergy at school age? Pooled analysis of individual participant data from 11 European birth cohorts.
Lødrup Carlsen, Karin; Roll, Stephanie; Carlsen, Kai-Håkon et al

in PLoS ONE (2012)

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