The genetic contribution of the X chromosome in age-related hearing loss.

Age-related (AR) hearing loss (HL) is the most common sensory impairment with heritability of 55%. The aim of this study was to identify genetic variants on chromosome X associated with ARHL through the analysis of data obtained from the UK Biobank. We performed association analysis between self-reported measures of HL and genotyped and imputed variants on chromosome X from ∼460,000 white Europeans.

Rare-variant association analysis reveals known and new age-related hearing loss genes.

Age-related (AR) hearing loss (HL) is a prevalent sensory deficit in the elderly population. Several studies showed that common variants increase ARHL susceptibility. Here, we demonstrate that rare-variants play a crucial role in ARHL etiology.

Whole genome sequencing identifies candidate genes for familial essential tremor and reveals biological pathways implicated in essential tremor aetiology.

Background: Essential tremor (ET), one of the most common neurological disorders, has a phenotypically heterogeneous presentation characterized by bilateral kinetic tremor of the arms and, in some patients, tremor involving other body regions (e.g., head, voice).

Regulatory variants in TCF7L2 are associated with thoracic aortic aneurysm.

Thoracic aortic aneurysm (TAA) is characterized by dilation of the aortic root or ascending/descending aorta. TAA is a heritable disease that can be potentially life threatening. While 10%-20% of TAA cases are caused by rare, pathogenic variants in single genes, the origin of the majority of TAA cases remains unknown.

A quantitative trait rare variant nonparametric linkage method with application to age-at-onset of Alzheimer's disease.

To analyze pedigrees with quantitative trait (QT) and sequence data, we developed a rare variant (RV) quantitative nonparametric linkage (QNPL) method, which evaluates sharing of minor alleles. RV-QNPL has greater power than the traditional QNPL that tests for excess sharing of minor and major alleles. RV-QNPL is robust to population substructure and admixture, locus heterogeneity, and inclusion of nonpathogenic variants and can be readily applied outside of coding regions.

A Rare Variant Nonparametric Linkage Method for Nuclear and Extended Pedigrees with Application to Late-Onset Alzheimer Disease via WGS Data.

To analyze family-based whole-genome sequence (WGS) data for complex traits, we developed a rare variant (RV) non-parametric linkage (NPL) analysis method, which has advantages over association methods. The RV-NPL differs from the NPL in that RVs are analyzed, and allele sharing among affected relative-pairs is estimated only for minor alleles. Analyzing families can increase power because causal variants with familial aggregation usually have larger effect sizes than those underlying sporadic diseases.

SEQSpark: A Complete Analysis Tool for Large-Scale Rare Variant Association Studies Using Whole-Genome and Exome Sequence Data.

Massively parallel sequencing technologies provide great opportunities for discovering rare susceptibility variants involved in complex disease etiology via large-scale imputation and exome and whole-genome sequence-based association studies. Due to modest effect sizes, large sample sizes of tens to hundreds of thousands of individuals are required for adequately powered studies. Current analytical tools are obsolete when it comes to handling these large datasets.

The Rare-Variant Generalized Disequilibrium Test for Association Analysis of Nuclear and Extended Pedigrees with Application to Alzheimer Disease WGS Data.

Whole-genome and exome sequence data can be cost-effectively generated for the detection of rare-variant (RV) associations in families. Causal variants that aggregate in families usually have larger effect sizes than those found in sporadic cases, so family-based designs can be a more powerful approach than population-based designs. Moreover, some family-based designs are robust to confounding due to population admixture or substructure.

Shared Genetic Risk Factors of Intracranial, Abdominal, and Thoracic Aneurysms.

Background: Intracranial aneurysms (IAs), abdominal aortic aneurysms (AAAs), and thoracic aortic aneurysms (TAAs) all have a familial predisposition. Given that aneurysm types are known to co-occur, we hypothesized that there may be shared genetic risk factors for IAs, AAAs, and TAAs.

Methods And Results: We performed a mega-analysis of 1000 Genomes Project-imputed genome-wide association study (GWAS) data of 4 previously published aneurysm cohorts: 2 IA cohorts (in total 1516 cases, 4305 controls), 1 AAA cohort (818 cases, 3004 controls), and 1 TAA cohort (760 cases, 2212 controls), and observed associations of 4 known IA, AAA, and/or TAA risk loci (9p21, 18q11, 15q21, and 2q33) with consistent effect directions in all 4 cohorts.

Rare variant associations with waist-to-hip ratio in European-American and African-American women from the NHLBI-Exome Sequencing Project.

Waist-to-hip ratio (WHR), a relative comparison of waist and hip circumferences, is an easily accessible measurement of body fat distribution, in particular central abdominal fat. A high WHR indicates more intra-abdominal fat deposition and is an established risk factor for cardiovascular disease and type 2 diabetes. Recent genome-wide association studies have identified numerous common genetic loci influencing WHR, but the contributions of rare variants have not been previously reported.

Generation of sequence-based data for pedigree-segregating Mendelian or Complex traits.

Motivation: There is great interest in analyzing next generation sequence data that has been generated for pedigrees. However, unlike for population-based data there are only a limited number of rare variant methods to analyze pedigree data. One limitation is the ability to evaluate type I and II errors for family-based methods, due to lack of software that can simulate realistic sequence data for pedigrees.

Rare A2ML1 variants confer susceptibility to otitis media.

A duplication variant within the middle ear-specific gene A2ML1 cosegregates with otitis media in an indigenous Filipino pedigree (LOD score = 7.5 at reduced penetrance) and lies within a founder haplotype that is also shared by 3 otitis-prone European-American and Hispanic-American children but is absent in non-otitis-prone children and >62,000 next-generation sequences. We identified seven additional A2ML1 variants in six otitis-prone children.

Collapsed haplotype pattern method for linkage analysis of next-generation sequence data.

Recent advances in next-generation sequencing (NGS) make it possible to directly sequence genomes and exomes of individuals with Mendelian diseases and screen sequence data for causal variants. With the reduction in cost of NGS, DNA samples from entire families can be sequenced and linkage analysis can be performed directly using NGS data. Inspired by 'burden' tests, which are used for complex trait rare variant association studies, we developed the collapsed haplotype pattern (CHP) method for linkage analysis.

Challenges and solutions for gene identification in the presence of familial locus heterogeneity.

Next-generation sequencing (NGS) of exomes and genomes has accelerated the identification of genes involved in Mendelian phenotypes. However, many NGS studies fall short of identifying causal variants, with estimates for success rates as low as 25% for uncovering the pathological variant underlying disease etiology. An important reason for such failures is familial locus heterogeneity, where within a single pedigree causal variants in two or more genes underlie Mendelian trait etiology.

RNF213 rare variants in an ethnically diverse population with Moyamoya disease.

Background And Purpose: Moyamoya disease (MMD) is a rare, genetically heterogeneous cerebrovascular disease resulting from occlusion of the distal internal carotid arteries. A variant in the Ring Finger 213 gene (RNF213), altering arginine at position 4810 (p.R4810K), is associated with MMD in Asian populations.

Variant association tools for quality control and analysis of large-scale sequence and genotyping array data.

Currently there is great interest in detecting associations between complex traits and rare variants. In this report, we describe Variant Association Tools (VAT) and the VAT pipeline, which implements best practices for rare-variant association studies. Highlights of VAT include variant-site and call-level quality control (QC), summary statistics, phenotype- and genotype-based sample selection, variant annotation, selection of variants for association analysis, and a collection of rare-variant association methods for analyzing qualitative and quantitative traits.

Power analysis and sample size estimation for sequence-based association studies.

Motivation: Statistical methods have been developed to test for complex trait rare variant (RV) associations, in which variants are aggregated across a region, which is typically a gene. Power analysis and sample size estimation for sequence-based RV association studies are challenging because of the necessity to realistically model the underlying allelic architecture of complex diseases within a suitable analytical framework to assess the performance of a variety of RV association methods in an unbiased manner.

Summary: We developed SEQPower, a software package to perform statistical power analysis for sequence-based association data under a variety of genetic variant and disease phenotype models.