Statistics to prioritize rare variants in family-based sequencing studies with disease subtypes.

Family-based sequencing studies are increasingly used to find rare genetic variants of high risk for disease traits with familial clustering. In some studies, families with multiple disease subtypes are collected and the exomes of affected relatives are sequenced for shared rare variants (RVs). Since different families can harbor different causal variants and each family harbors many RVs, tests to detect causal variants can have low power in this study design.

Inference of gene-environment interaction from heterogeneous case-parent trios.

In genetic epidemiology, log-linear models of population risk may be used to study the effect of genotypes and exposures on the relative risk of a disease. Such models may also include gene-environment interaction terms that allow the genotypes to modify the effect of the exposure, or equivalently, the exposure to modify the effect of genotypes on the relative risk. When a measured test locus is in linkage disequilibrium with an unmeasured causal locus, exposure-related genetic structure in the population can lead to spurious gene-environment interaction; that is, to apparent gene-environment interaction at the test locus in the absence of true gene-environment interaction at the causal locus.

Association Between HLA-DPB1 and Antineutrophil Cytoplasmic Antibody-Associated Vasculitis in Children.

Objective: Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a rare, life-threatening inflammation of blood vessels that can affect both adults and children. Compared to adult-onset disease, AAV is especially rare in children, with an annual prevalence of 0.5-6.

An exploration of linkage fine-mapping on sequences from case-control studies.

Linkage analysis maps genetic loci for a heritable trait by identifying genomic regions with excess relatedness among individuals with similar trait values. Analysis may be conducted on related individuals from families, or on samples of unrelated individuals from a population. For allelically heterogeneous traits, population-based linkage analysis can be more powerful than genotypic-association analysis.

Datasets for a simulated family-based exome-sequencing study.

We present simulated exome-sequencing data for 150 families from a North American admixed population, ascertained to contain at least four members affected with lymphoid cancer. These data include information on the ascertained families as well as single-nucleotide variants on the exome of affected family members. We provide a brief overview of the simulation steps and links to the associated software scripts.

Different Disease Endotypes in Phenotypically Similar Vasculitides Affecting Small-to-Medium Sized Blood Vessels.

Chronic primary vasculitis describes a group of complex and rare diseases that are characterized by blood vessel inflammation. Classification of vasculitis subtypes is based predominantly on the size of the involved vessels and clinical phenotype. There is a recognized need to improve classification, especially for small-to-medium sized vessel vasculitides, that, ideally, is based on the underlying biology with a view to informing treatment.

perfectphyloR: An R package for reconstructing perfect phylogenies.

Background: A perfect phylogeny is a rooted binary tree that recursively partitions sequences. The nested partitions of a perfect phylogeny provide insight into the pattern of ancestry of genetic sequence data. For example, sequences may cluster together in a partition indicating that they arise from a common ancestral haplotype.

SimRVSequences: an R package to simulate genetic sequence data for pedigrees.

Summary: We present the R package SimRVSequences to simulate sequence data for pedigrees. SimRVSequences allows for simulations of large numbers of single-nucleotide variants (SNVs) and scales well with increasing numbers of pedigrees. Users provide a sample of pedigrees and SNV data from a sample of unrelated individuals.

The Contribution Plot: Decomposition and Graphical Display of the RV Coefficient, with Application to Genetic and Brain Imaging Biomarkers of Alzheimer's Disease.

Background/aims: Alzheimer's disease (AD) is a chronic neurodegenerative disease that causes memory loss and a decline in cognitive abilities. AD is the sixth leading cause of death in the USA, affecting an estimated 5 million Americans. To assess the association between multiple genetic variants and multiple measurements of structural changes in the brain, a recent study of AD used a multivariate measure of linear dependence, the RV coefficient.

Identification of Novel Adenosine Deaminase 2 Gene Variants and Varied Clinical Phenotype in Pediatric Vasculitis.

Objective: Individuals with deficiency of adenosine deaminase 2 (DADA2), a recently recognized autosomal recessive disease, present with various systemic vascular and inflammatory manifestations, often with young age at disease onset or with early onset of recurrent strokes. Their clinical features and histologic findings overlap with those of childhood-onset polyarteritis nodosa (PAN), a primary "idiopathic" systemic vasculitis. Despite similar clinical presentation, individuals with DADA2 may respond better to biologic therapy than to traditional immunosuppression.

S100A12 Serum Levels and PMN Counts Are Elevated in Childhood Systemic Vasculitides Especially Involving Proteinase 3 Specific Anti-neutrophil Cytoplasmic Antibodies.

Chronic primary systemic vasculitidies (CPV) are a collection of rare diseases involving inflammation in blood vessels, often in multiple organs. CPV can affect adults and children and may be life- or organ-threatening. Treatments for adult CPV, although effective, have known severe potential toxicities; safety and efficacy of these drugs in pediatric patients is not fully understood.

Simulating pedigrees ascertained for multiple disease-affected relatives.

Background: Studies that ascertain families containing multiple relatives affected by disease can be useful for identification of causal, rare variants from next-generation sequencing data.

Results: We present the R package SimRVPedigree, which allows researchers to simulate pedigrees ascertained on the basis of multiple, affected relatives. By incorporating the ascertainment process in the simulation, SimRVPedigree allows researchers to better understand the within-family patterns of relationship amongst affected individuals and ages of disease onset.

Using Gene Genealogies to Localize Rare Variants Associated with Complex Traits in Diploid Populations.

Background And Aims: Many methods can detect trait association with causal variants in candidate genomic regions; however, a comparison of their ability to localize causal variants is lacking. We extend a previous study of the detection abilities of these methods to a comparison of their localization abilities.

Methods: Through coalescent simulation, we compare several popular association methods.

Multivariate association between single-nucleotide polymorphisms in Alzgene linkage regions and structural changes in the brain: discovery, refinement and validation.

Using publicly-available data from the Alzheimer's Disease Neuroimaging Initiative, we investigate the joint association between single-nucleotide polymorphisms (SNPs) in previously established linkage regions for Alzheimer's disease (AD) and rates of decline in brain structure. In an initial, discovery stage of analysis, we applied a weighted RV test to assess the association between 75,845 SNPs in the Alzgene linkage regions and rates of change in structural MRI measurements for 56 brain regions affected by AD, in 632 subjects. After confirming association, we selected refined lists of 1694 and 22 SNPs via a bootstrap-enhanced sparse canonical correlation analysis.

A Bayesian group sparse multi-task regression model for imaging genetics.

Motivation: Recent advances in technology for brain imaging and high-throughput genotyping have motivated studies examining the influence of genetic variation on brain structure. Wang et al. have developed an approach for the analysis of imaging genomic studies using penalized multi-task regression with regularization based on a novel group l2,1-norm penalty which encourages structured sparsity at both the gene level and SNP level.

Nonrandom occurrence of lymphoid cancer types in 140 families.

We studied 140 families with two or more lymphoid cancers, including non-Hodgkin lymphoma (NHL), Hodgkin lymphoma (HL), chronic lymphocytic leukemia (CLL), and multiple myeloma (MM), for deviation from the population age of onset and lymphoid cancer co-occurrence patterns. Median familial NHL, HL, CLL and MM ages of onset are substantially earlier than comparable population data. NHL, HL and CLL (but not MM) also show earlier age of onset in later generations, known as anticipation.

Sampletrees and Rsampletrees: sampling gene genealogies conditional on SNP genotype data.

Unlabelled: : The program sampletrees is a Markov chain Monte Carlo sampler of gene genealogies conditional on either phased or unphased SNP genotype data. The companion program Rsampletrees is for pre- and post-processing of sampletrees files, including setting up the files for sampletrees and storing and plotting the output of a sampletrees run.

Availability And Implementation: sampletrees is implemented in C ++.

Using gene genealogies to detect rare variants associated with complex traits.

Background And Objective: Standard population genetic theory says that deleterious genetic variants are likely rare and fairly recently introduced. However, can this expectation lead to more powerful tests of association between diseases and rare genetic variation? The gene genealogy describes the relationships between haplotypes sampled from the general population. Although ancestral tree-based methods, inspired by the gene genealogy concept, have been developed for finding associations with common genetic variants, here we ask whether gene genealogies can help in identifying genomic regions containing multiple rare causal variants.

A data-smoothing approach to explore and test gene-environment interaction in case-parent trios.

Complex traits result from an interplay between genes and environment. A better understanding of their joint effects can help refine understanding of the epidemiology of the trait. Various tests have been proposed to assess the statistical interaction between genes and the environment (G×E) in case-parent trio data.

Gene genealogies for genetic association mapping, with application to Crohn's disease.

A gene genealogy describes relationships among haplotypes sampled from a population. Knowledge of the gene genealogy for a set of haplotypes is useful for estimation of population genetic parameters and it also has potential application in finding disease-predisposing genetic variants. As the true gene genealogy is unknown, Markov chain Monte Carlo (MCMC) approaches have been used to sample genealogies conditional on data at multiple genetic markers.

A discovery study of daunorubicin induced cardiotoxicity in a sample of acute myeloid leukemia patients prioritizes P450 oxidoreductase polymorphisms as a potential risk factor.

Anthracyclines are very effective chemotherapeutic agents; however, their use is hampered by the treatment-induced cardiotoxicity. Genetic variants that help define patient's sensitivity to anthracyclines will greatly improve the design of optimal chemotherapeutic regimens. However, identification of such variants is hampered by the lack of analytical approaches that address the complex, multi-genic character of anthracycline induced cardiotoxicity (AIC).

Markov chain Monte Carlo sampling of gene genealogies conditional on unphased SNP genotype data.

The gene genealogy is a tree describing the ancestral relationships among genes sampled from unrelated individuals. Knowledge of the tree is useful for inference of population-genetic parameters and has potential application in gene-mapping. Markov chain Monte Carlo approaches that sample genealogies conditional on observed genetic data typically assume that haplotype data are observed even though commonly-used genotyping technologies provide only unphased genotype data.

Secondary analysis of publicly available data reveals superoxide and oxygen radical pathways are enriched for associations between type 2 diabetes and low-frequency variants.

Genome-wide association studies explain at most 5%-10% of the heritable components of type 2 diabetes. Some of the "missing type 2 diabetes heritability" could be explained by low-frequency variants. We examined the associations between low-frequency variants and type 2 diabetes, using data from 2538 diabetic and 2977 nondiabetic subjects in the publicly available database of Genotypes and Phenotypes.

Single-nucleotide polymorphisms in reductase genes are not associated with response to daunorubicin-based remission induction.

Background: To improve the quality of care for patients with acute myeloid leukemia (AML), biomarkers predictive of response to the standard daunorubicin-based induction therapy are needed. Genetic variants affecting daunorubicin metabolism are attractive candidates for such biomarkers.

Methods: We have previously shown that 13 of the naturally occurring nonsynonymous single-nucleotide polymorphisms (SNP) in the reductase genes affect daunorubicin metabolism in vitro.

CrypticIBDcheck: an R package for checking cryptic relatedness in nominally unrelated individuals.

Background: In population association studies, standard methods of statistical inference assume that study subjects are independent samples. In genetic association studies, it is therefore of interest to diagnose undocumented close relationships in nominally unrelated study samples.

Results: We describe the R package CrypticIBDcheck to identify pairs of closely-related subjects based on genetic marker data from single-nucleotide polymorphisms (SNPs).