PATH-SCAN: a reporting tool for identifying clinically actionable variants.
ABSTRACT: The American College of Medical Genetics and Genomics (ACMG) recently released guidelines regarding the reporting of incidental findings in sequencing data. Given the availability of Direct to Consumer (DTC) genetic testing and the falling cost of whole exome and genome sequencing, individuals will increasingly have the opportunity to analyze their own genomic data. We have developed a web-based tool, PATH-SCAN, which annotates individual genomes and exomes for ClinVar designated pathogenic variants found within the genes from the ACMG guidelines. Because mutations in these genes predispose individuals to conditions with actionable outcomes, our tool will allow individuals or researchers to identify potential risk variants in order to consult physicians or genetic counselors for further evaluation. Moreover, our tool allows individuals to anonymously submit their pathogenic burden, so that we can crowd source the collection of quantitative information regarding the frequency of these variants. We tested our tool on 1092 publicly available genomes from the 1000 Genomes project, 163 genomes from the Personal Genome Project, and 15 genomes from a clinical genome sequencing research project. Excluding the most commonly seen variant in 1000 Genomes, about 20% of all genomes analyzed had a ClinVar designated pathogenic variant that required further evaluation.
Project description:PURPOSE:We studied the penetrance of pathogenically classified variants in an elderly Dutch population from the Rotterdam Study, for which deep phenotyping is available. We screened the 59 actionable genes for which reporting of known pathogenic variants was recommended by the American College of Medical Genetics and Genomics (ACMG), and demonstrate that determining what constitutes a known pathogenic variant can be quite challenging. METHODS:We defined "known pathogenic" as classified pathogenic by both ClinVar and the Human Gene Mutation Database (HGMD). In 2628 individuals, we performed exome sequencing and identified known pathogenic variants. We investigated the clinical records of carriers and evaluated clinical events during 25 years of follow-up for evidence of variant pathogenicity. RESULTS:Of 3815 variants detected in the 59 ACMG genes, 17 variants were considered known pathogenic. For 14/17 variants the ClinVar classification had changed over time. Of 24 confirmed carriers of these variants, we observed at least one clinical event possibly caused by the variant in only three participants (13%). CONCLUSION:We show that the definition of "known pathogenic" is often unclear and should be approached carefully. Additionally variants marked as known pathogenic do not always have clinical impact on their carriers. Definition and classification of true (individual) expected pathogenic impact should be defined carefully.
Project description:Sequencing tests assaying panels of genes or whole exomes are widely available for cancer risk evaluation. However, methods for classification of variants resulting from this testing are not well studied. We evaluated the ability of a variant-classification methodology based on American College of Medical Genetics and Genomics (ACMG) guidelines to define the rate of mutations and variants of uncertain significance (VUS) in 180 medically relevant genes, including all ACMG-designated reportable cancer and non-cancer-associated genes, in individuals who met guidelines for hereditary cancer risk evaluation. We performed whole-exome sequencing in 404 individuals in 253 families and classified 1,640 variants. Potentially clinically actionable (likely pathogenic [LP] or pathogenic [P]) versus nonactionable (VUS, likely benign, or benign) calls were 95% concordant with locus-specific databases and Clinvar. LP or P mutations were identified in 12 of 25 breast cancer susceptibility genes in 26 families without identified BRCA1/2 mutations (11%). Evaluation of 84 additional genes associated with autosomal-dominant cancer susceptibility identified LP or P mutations in only two additional families (0.8%). However, individuals from 10 of 253 families (3.9%) had incidental LP or P mutations in 32 non-cancer-associated genes, and 9% of individuals were monoallelic carriers of a rare LP or P mutation in 39 genes associated with autosomal-recessive cancer susceptibility. Furthermore, 95% of individuals had at least one VUS. In summary, these data support the clinical utility of ACMG variant-classification guidelines. Additionally, evaluation of extended panels of cancer-associated genes in breast/ovarian cancer families leads to only an incremental clinical benefit but substantially increases the complexity of the results.
Project description:There is a significant interest in the standardized classification of human genetic variants. We used whole-genome sequence data from 10,495 unrelated individuals to contrast population frequency of pathogenic variants to the expected population prevalence of the disease. Analyses included the ACMG-recommended 59 gene-condition sets for incidental findings and 463 genes associated with 265 OrphaNet conditions. A total of 25,505 variants were used to identify patterns of inflation (i.e., excess genetic risk and misclassification). Inflation increases as the level of evidence supporting the pathogenic nature of the variant decreases. We observed up to 11.5% of genetic disorders with inflation in pathogenic variant sets and up to 92.3% for the variant set with conflicting interpretations. This improved to 7.7% and 57.7%, respectively, after filtering for disease-specific allele frequency. The patterns of inflation were replicated using public data from more than 138,000 genomes. The burden of rare variants was a main contributing factor of the observed inflation, indicating collective misclassified rare variants. We also analyzed the dynamics of re-classification of variant pathogenicity in ClinVar over time, which indicates progressive improvement in variant classification. The study shows that databases include a significant proportion of wrongly ascertained variants; however, it underscores the critical role of ClinVar to contrast claims and foster validation across submitters.
Project description:Besides its growing importance in clinical diagnostics and understanding the genetic basis of Mendelian and complex diseases, whole exome sequencing (WES) is a rich source of additional information of potential clinical utility for physicians, patients and their families. We analyzed the frequency and nature of single nucleotide variants (SNVs) considered secondary findings and recessive disease allele carrier status in the exomes of 8554 individuals from a large, randomly sampled cohort study and 2514 patients from a study of presumed Mendelian disease having undergone WES.We used the same sequencing platform and data processing pipeline to analyze all samples and characterized the distributions of reported pathogenic (ClinVar, Human Gene Mutation Database (HGMD)) and predicted deleterious variants in the pre-specified American College of Medical Genetics and Genomics (ACMG) secondary findings and recessive disease genes in different ethnic groups.In the 56 ACMG secondary findings genes, the average number of predicted deleterious variants per individual was 0.74, and the mean number of ClinVar reported pathogenic variants was 0.06. We observed an average of 10 deleterious and 0.78 ClinVar reported pathogenic variants per individual in 1423 autosomal recessive disease genes. By repeatedly sampling pairs of exomes, 0.5 % of the randomly generated couples were at 25 % risk of having an affected offspring for an autosomal recessive disorder based on the ClinVar variants.By investigating reported pathogenic and novel, predicted deleterious variants we estimated the lower and upper limits of the population fraction for which exome sequencing may reveal additional medically relevant information. We suggest that the observed wide range for the lower and upper limits of these frequency numbers will be gradually reduced due to improvement in classification databases and prediction algorithms.
Project description:The deleterious genetic variants contributing to certain diseases may differ in terms of number and allele frequency from population to population depending on their evolutionary background. Here, we prioritize the deleterious variants from Pakistani population in manually curated gene list already reported to be associated with common, Mendelian, and congenital cardiovascular diseases (CVDs) using the genome/exome sequencing data of Pakistani individuals publically available in 1000 Genomes Project (PJL), and Exome Aggregation Consortium (ExAC) South Asia. By applying a set of tools such as Combined Annotation Dependent Depletion (CADD), ANNOVAR, and Variant Effect Predictor (VEP), we highlighted 561 potentially detrimental variants from PJL data, and 7374 variants from ExAC South Asian data. Likewise, filtration from ClinVar for CVDs revealed 03 pathogenic and 02 likely pathogenic variants from PJL and 112 pathogenic and 42 likely pathogenic variants from ExAC South Asians. The comparison of derived allele frequencies (DAF) revealed many of these prioritized variants having two fold and higher DAF in Pakistani individuals than in other populations. The highest number of deleterious variants contributing to common CVDs in descending order includes hypertension, atherosclerosis, heart failure, aneurysm, and coronary heart disease, and for Mendelian and congenital CVDs cardiomyopathies, cardiac arrhythmias, and atrioventricular septal defects.
Project description:Next-generation sequencing (NGS) became an effective approach for finding novel causative genomic variants of genetic disorders and is increasingly used for diagnostic purposes. Public variant databases that gather data of pathogenic variants are being relied upon as a source for clinical diagnosis. However, research of pathogenic variants using public databases data could be carried out not only in patients, but also in healthy people. This could provide insights into the most common recessive disorders in populations. The study aim was to use NGS and data from the ClinVar database for the identification of pathogenic variants in the exomes of healthy individuals from the Lithuanian population. To achieve this, 96 exomes were sequenced. An average of 42 139 single-nucleotide variants (SNVs) and 2306 short INDELs were found in each individual exome. Pooled data of study exomes provided a total of 243 192 unique SNVs and 31 623 unique short INDELs. Three hundred and twenty-one unique SNVs were classified as pathogenic. Comparison of the European data from the 1000 Genomes Project with our data revealed five pathogenic genomic variants that are inherited in an autosomal recessive pattern and that statistically significantly differ from the European population data.
Project description:<h4>Purpose</h4>The ClinGen Variant Curation Expert Panels (VCEPs) provide disease-specific rules for accurate variant interpretation. Using the hearing loss-specific American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines, the Hearing Loss VCEP (HL VCEP) illustrates the utility of expert specifications in variant interpretation.<h4>Methods</h4>A total of 157 variants across nine HL genes, previously submitted to ClinVar, were curated by the HL VCEP. The curation process involved collecting published and unpublished data for each variant by biocurators, followed by bimonthly meetings of an expert curation subgroup that reviewed all evidence and applied the HL-specific ACMG/AMP guidelines to reach a final classification.<h4>Results</h4>Before expert curation, 75% (117/157) of variants had single or multiple variants of uncertain significance (VUS) submissions (17/157) or had conflicting interpretations in ClinVar (100/157). After applying the HL-specific ACMG/AMP guidelines, 24% (4/17) of VUS and 69% (69/100) of discordant variants were resolved into benign (B), likely benign (LB), likely pathogenic (LP), or pathogenic (P). Overall, 70% (109/157) variants had unambiguous classifications (B, LB, LP, P). We quantify the contribution of the HL-specified ACMG/AMP codes to variant classification.<h4>Conclusion</h4>Expert specification and application of the HL-specific ACMG/AMP guidelines effectively resolved discordant interpretations in ClinVar. This study highlights the utility of ClinGen VCEPs in supporting more consistent clinical variant interpretation.
Project description:Maroteaux-Lamy syndrome (MPS VI) is an autosomal recessive lysosomal storage disorder caused by pathogenic ARSB gene variants, commonly diagnosed through clinical findings and deficiency of the arylsulfatase B (ASB) enzyme. Detection of ARSB pathogenic variants can independently confirm diagnosis and render genetic counseling possible. In this review, we collect and summarize 908 alleles (201 distinct variants, including 3 polymorphisms previously considered as disease-causing variants) from 478 individuals diagnosed with MPS VI, identified from literature and public databases. Each variant is further analyzed for clinical classification according to American College of Medical Genetics and Genomics (ACMG) guidelines. Results highlight the heterogeneity of ARSB alleles, with most unique variants (59.5%) identified as missense and 31.7% of unique alleles appearing once. Only 18% of distinct variants were previously recorded in public databases with supporting evidence and clinical significance. ACMG recommends publishing clinical and biochemical data that accurately characterize pathogenicity of new variants in association with reporting specific alleles. Variants analyzed were sent to ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/), and MPS VI locus-specific database (http://mps6-database.org) where they will be available. High clinical suspicion coupled with diagnostic testing for deficient ASB activity and timely submission and classification of ARSB variants with biochemical and clinical data in public databases is essential for timely diagnosis of MPS VI.
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:The American College of Medical Genetics and Genomics (ACMG) recommends that clinical sequencing laboratories return secondary findings in 56 genes associated with medically actionable conditions. Our goal was to apply a systematic, stringent approach consistent with clinical standards to estimate the prevalence of pathogenic variants associated with such conditions using a diverse sequencing reference sample. Candidate variants in the 56 ACMG genes were selected from Phase 1 of the 1000 Genomes dataset, which contains sequencing information on 1,092 unrelated individuals from across the world. These variants were filtered using the Human Gene Mutation Database (HGMD) Professional version and defined parameters, appraised through literature review, and examined by a clinical laboratory specialist and expert physician. Over 70,000 genetic variants were extracted from the 56 genes, and filtering identified 237 variants annotated as disease causing by HGMD Professional. Literature review and expert evaluation determined that 7 of these variants were pathogenic or likely pathogenic. Furthermore, 5 additional truncating variants not listed as disease causing in HGMD Professional were identified as likely pathogenic. These 12 secondary findings are associated with diseases that could inform medical follow-up, including cancer predisposition syndromes, cardiac conditions, and familial hypercholesterolemia. The majority of the identified medically actionable findings were in individuals from the European (5/379) and Americas (4/181) ancestry groups, with fewer findings in Asian (2/286) and African (1/246) ancestry groups. Our results suggest that medically relevant secondary findings can be identified in approximately 1% (12/1092) of individuals in a diverse reference sample. As clinical sequencing laboratories continue to implement the ACMG recommendations, our results highlight that at least a small number of potentially important secondary findings can be selected for return. Our results also confirm that understudied populations will not reap proportionate benefits of genomic medicine, highlighting the need for continued research efforts on genetic diseases in these populations.