Systematic evaluation of gene variants linked to hearing loss based on allele frequency threshold and filtering allele frequency.
ABSTRACT: As the number of genes identified for linkage to hearing loss has been increasing and more public databases have become available, we aimed to systematically evaluate all variants reported for nonsyndromic hearing loss (NSHL) based on their allele frequencies (AFs) in the general population. Among the 3,549 variants in 97 NSHL genes reported as pathogenic/likely pathogenic in ClinVar and HGMD, 1,618 were found in public databases (gnomAD, ExAC, EVS, and 1000G). To evaluate the pathogenicity of these variants, we employed AF thresholds and NSHL-optimized ACMG guidelines. AF thresholds were determined using a high-resolution variant frequency framework and Hardy-Weinberg equilibrium calculation: 0.6% and 0.1% for recessive and dominant genes, respectively. Filtering AFs of variants linked to NSHL were obtained based on AFs reported in gnomAD and ExAC. We found that 48 variants in 23 genes had filtering AFs above the suggested thresholds and assumed that these variants might be benign based on their filtering AFs. 47 variants, except for one notorious high-frequency GJB2 mutation (c.109G?>?A; p.Val37Ile), were confirmed to be benign/likely benign by the NSHL-optimized ACMG guidelines. The proposed systematic approach will aid in precise evaluation of NSHL variant pathogenicity in the context of filtering AFs, AF thresholds, and NSHL-specific ACMG guidelines, thus improving NSHL diagnostics.
Project description:Genome-scale high-throughput sequencing enables the detection of unprecedented numbers of sequence variants. Variant filtering and interpretation are facilitated by mutation databases, in silico tools, and population-based reference datasets such as ExAC/gnomAD, while variants are classified using the ACMG/AMP guidelines. These methods, however, pose clinically relevant challenges. We queried the gnomAD dataset for (likely) pathogenic variants in genes causing autosomal-dominant disorders. Furthermore, focusing on the fibrillinopathies Marfan syndrome (MFS) and congenital contractural arachnodactyly (CCA), we screened 500 genomes of our patients for co-occurring variants in FBN1 and FBN2. In gnomAD, we detected 2653 (likely) pathogenic variants in 253 genes associated with autosomal-dominant disorders, enabling the estimation of variant-filtering thresholds and disease predisposition/prevalence rates. In our database, we discovered two families with hitherto unreported co-occurrence of FBN1/FBN2 variants causing phenotypes with mixed or modified MFS/CCA clinical features. We show that (likely) pathogenic gnomAD variants may be more frequent than expected and are challenging to classify according to the ACMG/AMP guidelines as well as that fibrillinopathies are likely underdiagnosed and may co-occur. Consequently, selection of appropriate frequency cutoffs, recognition of digenic variants, and variant classification represent considerable challenges in variant interpretation. Neglecting these challenges may lead to incomplete or missed diagnoses.
Project description:We aimed to investigate the pathogenicity of cardiac ion channel variants previously associated with SIDS. We reviewed SIDS-associated variants previously reported in databases and the literature in three large population-based cohorts; The ExAC database, the Inter99 study, and the UK Biobank (UKBB). Variants were classified according to the American College of Medical Genetics and Genomics (ACMG) guidelines. Of the 92 SIDS-associated variants, 59 (64%) were present in ExAC, 18 (20%) in Inter99, and 24 (26%) in UKBB. Using the Inter99 cohort, we found no difference in J-point amplitude and QTc-interval between carriers and non-carriers for 14/18 variants. There was no difference in the risk of syncope (P?=?0.32), malignant ventricular arrhythmia (P?=?0.96), and all-cause mortality (P?=?0.59) between carriers and non-carriers. The ACMG guidelines reclassified 75% of all variants as variant-of-uncertain significance, likely benign, and benign. We identified ~2/3 of variants previously associated with SIDS and found no significant associations with electrocardiographic traits, syncope, malignant ventricular arrhythmia, or all-cause mortality. These data indicate that many of these variants are not highly penetrant, monogenic causes of SIDS and underline the importance of frequent reappraisal of genetic variants to avoid future misdiagnosis.
Project description:Ethnic-specific differences in minor allele frequency impact variant categorization for genetic screening of nonsyndromic hearing loss (NSHL) and other genetic disorders. We sought to evaluate all previously reported pathogenic NSHL variants in the context of a large number of controls from ethnically distinct populations sequenced with orthogonal massively parallel sequencing methods. We used HGMD, ClinVar, and dbSNP to generate a comprehensive list of reported pathogenic NSHL variants and re-evaluated these variants in the context of 8,595 individuals from 12 populations and 6 ethnically distinct major human evolutionary phylogenetic groups from three sources (Exome Variant Server, 1000 Genomes project, and a control set of individuals created for this study, the OtoDB). Of the 2,197 reported pathogenic deafness variants, 325 (14.8%) were present in at least one of the 8,595 controls, indicating a minor allele frequency (MAF) > 0.00006. MAFs ranged as high as 0.72, a level incompatible with pathogenicity for a fully penetrant disease like NSHL. Based on these data, we established MAF thresholds of 0.005 for autosomal-recessive variants (excluding specific variants in GJB2) and 0.0005 for autosomal-dominant variants. Using these thresholds, we recategorized 93 (4.2%) of reported pathogenic variants as benign. Our data show that evaluation of reported pathogenic deafness variants using variant MAFs from multiple distinct ethnicities and sequenced by orthogonal methods provides a powerful filter for determining pathogenicity. The proposed MAF thresholds will facilitate clinical interpretation of variants identified in genetic testing for NSHL. All data are publicly available to facilitate interpretation of genetic variants causing deafness.
Project description:<h4>Objective</h4>To assist the interpretation of genomic data for common epilepsies, we asked whether variants implicated in mild epilepsies in autosomal dominant families are present in the general population.<h4>Methods</h4>We studied 12 genes for the milder epilepsies and identified published variants with strong segregation support (de novo germline mutation or ?4 affected family members). These variants were checked in the Exome Aggregation Consortium (ExAC), a database of genetic variation in over 60,000 individuals. We subsequently evaluated variants in these epilepsy genes that lacked strong segregation support. To determine whether the findings in epilepsies were representative of other diseases, we also assessed the presence of variants in other dominant neurologic disorders (e.g., CADASIL).<h4>Results</h4>Published epilepsy variants with strong segregation support (n = 65) were absent (n = 61) or present once (n = 4) in ExAC. By contrast, of 46 published epilepsy variants without strong segregation support, 8 occurred recurrently (2-186 times). Similarly, none of the 45 disease-associated variants from other neurologic disorders with strong segregation support occurred more than once in ExAC. Reanalysis using the larger ExAC V2 plus gnomAD reference cohort showed consistent results.<h4>Conclusions</h4>Variants causing autosomal dominant epilepsies are ultra-rare in the general population. Variants observed more than once in ExAC were only found among reports without strong segregation support, suggesting that they may be benign. Clinicians are increasingly faced with the interpretation of genetic variants of unknown significance. These data illustrate that variants present more than once in ExAC are less likely to be pathogenic, reinforcing the valuable clinical role of ExAC.
Project description:Genetic testing for congenital long QT syndrome (LQTS) has become common. Recent studies have shown that some variants labelled as pathogenic might be misclassified due to sparse case reports and relatively common allele frequencies (AF) in the general population. This study aims to evaluate the presence of LQTS-associated variants in the Genome Aggregation Database (gnomAD) population, and assess the functional impact of these variants.Variants associated with LQTS from the Human Gene Mutation Database were extracted and matched to the gnomAD to evaluate population-based AF. We used MetaSVM to predict the function of LQTS variants. Allele distribution by protein topology in KCNQ1, KCNH2, and SCN5A was compared between gnomAD (n = 123,136) and a cohort of LQTS patients aggregated from eight published studies (n = 2,683). Among the 1,415 LQTS-associated single nucleotide variants in 30 genes, 347 (25%) are present in gnomAD; 24% of the 347 variants were predicted as functionally tolerated compared with 4% of variants not present in gnomAD (P < 0.001). Of the 347 pathogenic variants in gnomAD, seven (2%) had an AF of ? 0.001 and 65 (19%) variants had an AF of ? 0.0001. In KCNQ1, KCNH2, and SCN5A, allele distribution by protein functional region was significantly different with gnomAD alleles appearing less frequently in highly pathogenic domains than case alleles.A significant number of LQTS variants have insufficient evidence for pathogenicity and relatively common AF in the general population. Caution should be used when ascribing pathogenicity to these variants.
Project description:Next-generation sequencing continues to grow in importance for researchers. Exome sequencing became a widespread tool to further study the genomic basis of Mendelian diseases. In an effort to identify pathogenic variants, reject benign variants and better predict variant effects in downstream analysis, the American College of Medical Genetics (ACMG) published a set of criteria in 2015. While there are multiple publicly available software's available to assign the ACMG criteria, most of them do not take into account multi-sample variant calling formats. Here we present a tool for assessment and prioritisation in exome studies (TAPES, https://github.com/a-xavier/tapes), an open-source tool designed for small-scale exome studies. TAPES can quickly assign ACMG criteria using ANNOVAR or VEP annotated files and implements a model to transform the categorical ACMG criteria into a continuous probability, allowing for a more accurate classification of pathogenicity or benignity of variants. In addition, TAPES can work with cohorts sharing a common phenotype by utilising a simple enrichment analysis, requiring no controls as an input as well as providing powerful filtering and reporting options. Finally, benchmarks showed that TAPES outperforms available tools to detect both pathogenic and benign variants, while also integrating the identification of enriched variants in study cohorts compared to the general population, making it an ideal tool to evaluate a smaller cohort before using bigger scale studies.
Project description:PURPOSE:We aimed to estimate the carrier frequency of Zellweger spectrum disorder (ZSD), a rare autosomal recessive disease, and the associated disease incidence based on data from the Exome Aggregation Consortium (ExAC) of approximately 60,000 individuals. METHODS:We obtained variants from ExAC in 13 PEX genes associated with ZSD. Potentially pathogenic missense variants were identified with computational variant analysis tools according to three stringency levels. Using variants classified as potentially pathogenic, we estimated the carrier frequency and the associated incidence for the entire ExAC population and its subpopulations. We also evaluated variants based on pathogenicity criteria for sequence variant interpretation outlined by the American College of Medical Genetics and Genomics (ACMG) and calculated the carrier frequency and incidence based on those variants. RESULTS:The bioinformatically estimated incidence rate of ZSD in the ExAC population is 1 in 83,841 using our least stringent pathogenicity cutoff. Under clinical guidelines outlined by ACMG, the estimated incidence is 1 in 3,275,751 births. CONCLUSION:We outlined a process for estimating the ZSD disease carrier frequency and incidence in a large consortium using bioinformatics tools. Our results are close to current newborn screening estimates in New York of 1 in 90,000 births, estimated from 1.08 million screenings.
Project description:Recent advances in targeted genomic enrichment with massively parallel sequencing (TGE+MPS) have made comprehensive genetic testing for non-syndromic hearing loss (NSHL) possible. After excluding NSHL subjects with causative mutations in GJB2 and the MT-RNR1 (1555A>G) variant by Sanger sequencing, we completed TGE+MPS on 194 probands with presumed NSHL identified across Japan. We used both publicly available minor allele frequency (MAF) datasets and ethnic-specific MAF filtering against an in-house database of 200 normal-hearing Japanese controls. Ethnic-specific MAF filtering allowed us to re-categorize as common 203 variants otherwise annotated as rare or novel in non-Japanese ethnicities. This step minimizes false-positive results and improves the annotation of identified variants. Causative variants were identified in 27% of probands with solve rates of 35%, 35% and 19% for dominant, recessive and sporadic NSHL, respectively. Mutations in MYO15A and CDH23 follow GJB2 as the frequent causes of recessive NSHL; copy number variations in STRC are a major cause of mild-to-moderate NSHL. Ethnic-specific filtering by allele frequency is essential to optimize the interpretation of genetic data.
Project description:Rare inherited variations in multiplex families with Gilles de la Tourette syndrome (GTS) are suggested to play an important role in the genetic etiology of GTS. In order to explore the rare inherited variations with the risk of GTS, whole-exome sequencing (WES) was performed in a family with three affected patients with GTS. Among the five novel rare variations identified by WES, <i>CLCN2</i> G161S was presented in three patients, but not in four unaffected individuals, and thus co-segregated with GTS. A validation study was also performed in a cohort of Chinses Han population to further examine the identified rare variants. <i>CLCN2</i> G161S was genotyped in 207 sporadic patients with tic disorder including 111 patients with GTS and 489 healthy controls. Compared with that in controls [allele frequency (AF) = 0], <i>CLCN2</i> G161S had higher variant AF in patients with tic (AF = 0.00483) and in patients with GTS (0.00900), respectively. However, this variant was absent from the current 1000 Genome databases, and the variant AF is very low in the current public databases including ExAC (AF = 0.00001) and gnomAD (AF = 0.00003). Our results suggest that <i>CLCN2</i> G161S might play a major role in the genetic etiology of GTS, at least in a Chinese Han population.
Project description:PurposeWhole-exome and whole-genome sequencing have transformed the discovery of genetic variants that cause human Mendelian disease, but discriminating pathogenic from benign variants remains a daunting challenge. Rarity is recognized as a necessary, although not sufficient, criterion for pathogenicity, but frequency cutoffs used in Mendelian analysis are often arbitrary and overly lenient. Recent very large reference datasets, such as the Exome Aggregation Consortium (ExAC), provide an unprecedented opportunity to obtain robust frequency estimates even for very rare variants.MethodsWe present a statistical framework for the frequency-based filtering of candidate disease-causing variants, accounting for disease prevalence, genetic and allelic heterogeneity, inheritance mode, penetrance, and sampling variance in reference datasets.ResultsUsing the example of cardiomyopathy, we show that our approach reduces by two-thirds the number of candidate variants under consideration in the average exome, without removing true pathogenic variants (false-positive rate<0.001).ConclusionWe outline a statistically robust framework for assessing whether a variant is "too common" to be causative for a Mendelian disorder of interest. We present precomputed allele frequency cutoffs for all variants in the ExAC dataset.