Performance of model-based multifactor dimensionality reduction methods for epistasis detection by controlling population structure.

Background: In genome-wide association studies the extent and impact of confounding due to population structure have been well recognized. Inadequate handling of such confounding is likely to lead to spurious associations, hampering replication, and the identification of causal variants. Several strategies have been developed for protecting associations against confounding, the most popular one is based on Principal Component Analysis.

Confounding of linkage disequilibrium patterns in large scale DNA based gene-gene interaction studies.

Background: In Genome-Wide Association Studies (GWAS), the concept of linkage disequilibrium is important as it allows identifying genetic markers that tag the actual causal variants. In Genome-Wide Association Interaction Studies (GWAIS), similar principles hold for pairs of causal variants. However, Linkage Disequilibrium (LD) may also interfere with the detection of genuine epistasis signals in that there may be complete confounding between Gametic Phase Disequilibrium (GPD) and interaction.

Principals about principal components in statistical genetics.

Principal components (PCs) are widely used in statistics and refer to a relatively small number of uncorrelated variables derived from an initial pool of variables, while explaining as much of the total variance as possible. Also in statistical genetics, principal component analysis (PCA) is a popular technique. To achieve optimal results, a thorough understanding about the different implementations of PCA is required and their impact on study results, compared to alternative approaches.

Pit pattern analysis with high-definition chromoendoscopy and narrow-band imaging for optical diagnosis of dysplasia in patients with ulcerative colitis.

Background And Aims: Patients with longstanding ulcerative colitis (UC) are at increased risk of developing colorectal neoplasia. Chromoendoscopy (CE) increases detection of lesions, and Kudo pit pattern classification I and II have been suggested to be predictive of benign polyps in UC. Little is known on the use of this classification in nonmagnified high-definition (HD) (virtual) CE and narrow-band Imaging (NBI) or on the interobserver agreement.

A roadmap to multifactor dimensionality reduction methods.

Complex diseases are defined to be determined by multiple genetic and environmental factors alone as well as in interactions. To analyze interactions in genetic data, many statistical methods have been suggested, with most of them relying on statistical regression models. Given the known limitations of classical methods, approaches from the machine-learning community have also become attractive.

Genome-wide association interaction analysis for Alzheimer's disease.

We propose a minimal protocol for exhaustive genome-wide association interaction analysis that involves screening for epistasis over large-scale genomic data combining strengths of different methods and statistical tools. The different steps of this protocol are illustrated on a real-life data application for Alzheimer's disease (AD) (2259 patients and 6017 controls from France). Particularly, in the exhaustive genome-wide epistasis screening we identified AD-associated interacting SNPs-pair from chromosome 6q11.

Risk of malignancies in patients with inflammatory bowel disease treated with thiopurines or anti-TNF alpha antibodies.

Purpose: We aimed to analyse malignancy rates and predictors for the development of malignancies in a large German inflammatory bowel disease (IBD) cohort treated with thiopurines and/or anti-tumour necrosis factor (TNF) antibodies.

Methods: De novo malignancies in 666 thiopurine-treated and/or anti-TNF-treated IBD patients were analysed. Patients (n = 262) were treated with thiopurines alone and never exposed to anti-TNF antibodies (TP group).

Association of IL33-IL-1 receptor-like 1 (IL1RL1) pathway polymorphisms with wheezing phenotypes and asthma in childhood.

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).

Molecular reclassification of Crohn's disease: a cautionary note on population stratification.

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.

Genetic and microbial factors modulating the ubiquitin proteasome system in inflammatory bowel disease.

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.

A robustness study of parametric and non-parametric tests in model-based multifactor dimensionality reduction for epistasis detection.

Background: Applying a statistical method implies identifying underlying (model) assumptions and checking their validity in the particular context. One of these contexts is association modeling for epistasis detection. Here, depending on the technique used, violation of model assumptions may result in increased type I error, power loss, or biased parameter estimates.

An efficient algorithm to perform multiple testing in epistasis screening.

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.

Does pet ownership in infancy lead to asthma or allergy at school age? Pooled analysis of individual participant data from 11 European birth cohorts.

Objective: To examine the associations between pet keeping in early childhood and asthma and allergies in children aged 6-10 years.

Design: Pooled analysis of individual participant data of 11 prospective European birth cohorts that recruited a total of over 22,000 children in the 1990s. EXPOSURE DEFINITION: Ownership of only cats, dogs, birds, rodents, or cats/dogs combined during the first 2 years of life.

Comparison of genetic association strategies in the presence of rare alleles.

In the quest for the missing heritability of most complex diseases, rare variants have received increased attention. Advances in large-scale sequencing have led to a shift from the common disease/common variant hypothesis to the common disease/rare variant hypothesis or have at least reopened the debate about the relevance and importance of rare variants for gene discoveries. The investigation of modeling and testing approaches to identify significant disease/rare variant associations is in full motion.

Lower-order effects adjustment in quantitative traits model-based multifactor dimensionality reduction.

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.

Genetic variation in the autophagy gene ULK1 and risk of Crohn's disease.

Background: The autophagy pathway has been linked with Crohn's disease (CD) through association of the ATG16L1 and IRGM genes with susceptibility for CD, and also to the Nod2 pathway, involved in CD. Our aim was to investigate polymorphisms in selected autophagy genes for their association with susceptibility to CD.

Methods: We prioritized all known human homologs of yeast autophagy (Atg) genes according to their location in a known inflammatory bowel disease (IBD) locus or in a genomic region detected in a genome-wide association study (GWAS) or GWAS-meta-analysis.

Model-Based Multifactor Dimensionality Reduction to detect epistasis for quantitative traits in the presence of error-free and noisy data.

Detecting gene-gene interactions or epistasis in studies of human complex diseases is a big challenge in the area of epidemiology. To address this problem, several methods have been developed, mainly in the context of data dimensionality reduction. One of these methods, Model-Based Multifactor Dimensionality Reduction, has so far mainly been applied to case-control studies.

Levels of C-reactive protein are associated with response to infliximab therapy in patients with Crohn's disease.

Background & Aims: Infliximab is an antibody against tumor necrosis factor-α that is used to treat patients with moderate to severe Crohn's disease (CD). C-reactive protein (CRP) is a marker used to identify and follow individuals with CD. We analyzed changes in levels of CRP in a large cohort of patients with CD undergoing treatment with infliximab.

Model-based multifactor dimensionality reduction for detecting epistasis in case-control data in the presence of noise.

Analyzing the combined effects of genes and/or environmental factors on the development of complex diseases is a great challenge from both the statistical and computational perspective, even using a relatively small number of genetic and nongenetic exposures. Several data-mining methods have been proposed for interaction analysis, among them, the Multifactor Dimensionality Reduction Method (MDR) has proven its utility in a variety of theoretical and practical settings. Model-Based Multifactor Dimensionality Reduction (MB-MDR), a relatively new MDR-based technique that is able to unify the best of both nonparametric and parametric worlds, was developed to address some of the remaining concerns that go along with an MDR analysis.

Molecular reclassification of Crohn's disease by cluster analysis of genetic variants.

Background: Crohn's Disease (CD) has a heterogeneous presentation, and is typically classified according to extent and location of disease. The genetic susceptibility to CD is well known and genome-wide association scans (GWAS) and meta-analysis thereof have identified over 30 susceptibility loci. Except for the association between ileal CD and NOD2 mutations, efforts in trying to link CD genetics to clinical subphenotypes have not been very successful.

FAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals.

We propose a novel multifactor dimensionality reduction method for epistasis detection in small or extended pedigrees, FAM-MDR. It combines features of the Genome-wide Rapid Association using Mixed Model And Regression approach (GRAMMAR) with Model-Based MDR (MB-MDR). We focus on continuous traits, although the method is general and can be used for outcomes of any type, including binary and censored traits.

Fast MR arthrography using VIBE sequences to evaluate the rotator cuff.

Purpose: The purpose of this paper was to evaluate if short volumetric interpolated breath-hold examination (VIBE) sequences can be used as a substitute for T1-weighted with fat saturation (T1-FS) sequences when performing magnetic resonance (MR) arthrography to diagnose rotator cuff tears.

Materials And Methods: Eighty-two patients underwent direct MR arthrography of the shoulder joint using VIBE (acquisition time of 13 s) and T1-FS (acquisition time of 5 min) sequences in the axial and paracoronal plane on a 1.0-T MR unit.