Modeling the ACMG/AMP variant classification guidelines as a Bayesian classification framework.
ABSTRACT: PURPOSE:We evaluated the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) variant pathogenicity guidelines for internal consistency and compatibility with Bayesian statistical reasoning. METHODS:The ACMG/AMP criteria were translated into a naive Bayesian classifier, assuming four levels of evidence and exponentially scaled odds of pathogenicity. We tested this framework with a range of prior probabilities and odds of pathogenicity. RESULTS:We modeled the ACMG/AMP guidelines using biologically plausible assumptions. Most ACMG/AMP combining criteria were compatible. One ACMG/AMP likely pathogenic combination was mathematically equivalent to pathogenic and one ACMG/AMP pathogenic combination was actually likely pathogenic. We modeled combinations that include evidence for and against pathogenicity, showing that our approach scored some combinations as pathogenic or likely pathogenic that ACMG/AMP would designate as variant of uncertain significance (VUS). CONCLUSION:By transforming the ACMG/AMP guidelines into a Bayesian framework, we provide a mathematical foundation for what was a qualitative heuristic. Only 2 of the 18 existing ACMG/AMP evidence combinations were mathematically inconsistent with the overall framework. Mixed combinations of pathogenic and benign evidence could yield a likely pathogenic, likely benign, or VUS result. This quantitative framework validates the approach adopted by the ACMG/AMP, provides opportunities to further refine evidence categories and combining rules, and supports efforts to automate components of variant pathogenicity assessments.
Project description:Additional variant interpretation tools are required to effectively harness genomic sequencing for clinical applications. The American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP) published guidelines for clinical sequence variant interpretation, incorporating different types of data that lend varying levels of support towards a benign or pathogenic interpretation. Variants of uncertain significance (VUS) are those with either contradictory or insufficient evidence, and their uncertainty complicates patient counseling and management. Functional assays may provide a solution to evidence gaps relegating variants to the VUS category, but the impact of functional evidence in this framework has not been assessed. We employ an algorithmic analysis of the ACMG/AMP combining rules to assess how the availability of strong functional evidence could theoretically improve the ability to make a benign or pathogenic assertion. We follow this with analysis of actual evidence combinations met by variants through expert curations as part of the Clinical Genome Resource (ClinGen). We also examine the impact of functional evidence in a Bayesian adaptation of the ACMG/AMP framework. This lays the groundwork for an evidence-based prioritization of assay development and variant assessment by identifying genes and variants that may benefit the most from functional data.
Project description:Evaluating the pathogenicity of a variant is challenging given the plethora of types of genetic evidence that laboratories consider. Deciding how to weigh each type of evidence is difficult, and standards have been needed. In 2015, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) published guidelines for the assessment of variants in genes associated with Mendelian diseases. Nine molecular diagnostic laboratories involved in the Clinical Sequencing Exploratory Research (CSER) consortium piloted these guidelines on 99 variants spanning all categories (pathogenic, likely pathogenic, uncertain significance, likely benign, and benign). Nine variants were distributed to all laboratories, and the remaining 90 were evaluated by three laboratories. The laboratories classified each variant by using both the laboratory's own method and the ACMG-AMP criteria. The agreement between the two methods used within laboratories was high (K-alpha = 0.91) with 79% concordance. However, there was only 34% concordance for either classification system across laboratories. After consensus discussions and detailed review of the ACMG-AMP criteria, concordance increased to 71%. Causes of initial discordance in ACMG-AMP classifications were identified, and recommendations on clarification and increased specification of the ACMG-AMP criteria were made. In summary, although an initial pilot of the ACMG-AMP guidelines did not lead to increased concordance in variant interpretation, comparing variant interpretations to identify differences and having a common framework to facilitate resolution of those differences were beneficial for improving agreement, allowing iterative movement toward increased reporting consistency for variants in genes associated with monogenic disease.
Project description:Wilson disease (WD) is one of the most prevalent genetic diseases with an estimated global carrier frequency of 1 in 90 and a prevalence of 1 in 30,000. The disease owes its genesis to Kinnier Wilson who described the disease, and is caused by accumulation of Copper (Cu) in various organs including the liver, central nervous system, cornea, kidney, joints and cardiac muscle which contribute to the characteristic clinical features of WD. A number of studies have reported genetic variants in the ATP7B gene from diverse ethnic and geographical origins. The recent advent of next-generation sequencing approaches has also enabled the discovery of a large number of novel variants in the gene associated with the disease. Previous attempts have been made to compile the knowledgebase and spectrum of genetic variants from across the multitude of publications, but have been limited by the utility due to the significant differences in approaches used to qualify pathogenicity of variants in each of the publications. The recent formulation of guidelines and algorithms for assessment of the pathogenicity of variants jointly put forward by the American College of Medical Genetics and the Association of Molecular Pathologists (ACMG &) has provided a framework for evidence based and systematic assessment of pathogenicity of variants. In this paper, we describe a comprehensive resource of genetic variants in ATP7B gene manually curated from literature and data resources and systematically annotated using the ACMG & AMP guidelines for assessing pathogenicity. The resource therefore serves as a central point for clinicians and geneticists working on WD and to the best of our knowledge is the most comprehensive and only clinically annotated resource for WD. The resource is available at URL http://clingen.igib.res.in/WilsonGen/. We compiled a total of 3662 genetic variants from publications and databases associated with WD. Of these variants compiled, a total of 1458 were found to be unique entries. This is the largest WD database comprising 656 pathogenic/likely pathogenic variants reported classified according to ACMG & AMP guidelines. We also mapped all the pathogenic variants corresponding to ATP7B protein from literature and other databases. In addition, geographical origin and distribution of ATP7B pathogenic variants reported are also mapped in the database.
Project description:Primary familial brain calcification (PFBC) is a rare cerebral microvascular calcifying disorder with a wide spectrum of motor, cognitive, and neuropsychiatric symptoms. It is typically inherited as an autosomal-dominant trait with four causative genes identified so far: SLC20A2, PDGFRB, PDGFB, and XPR1. Our study aimed at screening the coding regions of these genes in a series of 177 unrelated probands that fulfilled the diagnostic criteria for primary brain calcification regardless of their family history. Sequence variants were classified as pathogenic, likely pathogenic, or of uncertain significance (VUS), based on the ACMG-AMP recommendations. We identified 45 probands (25.4%) carrying either pathogenic or likely pathogenic variants (n?=?34, 19.2%) or VUS (n?=?11, 6.2%). SLC20A2 provided the highest contribution (16.9%), followed by XPR1 and PDGFB (3.4% each), and PDGFRB (1.7%). A total of 81.5% of carriers were symptomatic and the most recurrent symptoms were parkinsonism, cognitive impairment, and psychiatric disturbances (52.3%, 40.9%, and 38.6% of symptomatic individuals, respectively), with a wide range of age at onset (from childhood to 81 years). While the pathogenic and likely pathogenic variants identified in this study can be used for genetic counseling, the VUS will require additional evidence, such as recurrence in unrelated patients, in order to be classified as pathogenic.
Project description:Gene-specific knowledge can enhance genetic variant classification, but may not be routinely incorporated into clinical laboratory practice. For example, FBN1 variants associated with Marfan syndrome may be variably classified depending on knowledge of FBN1-specific critical regions. In order to assess variability in classification of FBN1 variants, 674 FBN1 missense variants from 18 ClinVar submitters were compared and reanalyzed using FBN1-specific criteria and ACMG/AMP 2015 guidelines for variant interpretation. Conflicting variant classifications occurred in 30.7% of the missense variants that had multiple submitters. There were 451 classifications of 361 critical residue missense variants, with 80.0% (361/451) classified as likely pathogenic or pathogenic [(L)P]. Non-cysteine critical residue variants were less likely to be classified as (L)P [55.3% (78/141)] than cysteine variants [91.3% (283/310)] and were more likely to lack evidence citing the functional significance of the amino acid impacted. Application of FBN1-specific knowledge allowed for reclassification or discrepancy resolution in 65/361 (18.0%) critical residue variants. There were 522 classifications of 313 unique missense variants not known to impact a critical residue. Of these, 31.6% (165/522) were likely overclassified as either (L)P or uncertain significance (VUS), especially when minor allele frequency (MAF) was taken into account, and we reclassified or resolved classification discrepancies in 128/313 (40.9%) of these variants. Our results provide a refined framework and resource for FBN1 variant classification, and further supports the more global implications of combining gene-based knowledge with ACMG/AMP criteria and appropriate MAF cutoffs for variant classification that extend beyond FBN1.
Project description:The 2015 ACMG/AMP sequence variant interpretation guideline provided a framework for classifying variants based on several benign and pathogenic evidence criteria, including a pathogenic criterion (PVS1) for predicted loss of function variants. However, the guideline did not elaborate on specific considerations for the different types of loss of function variants, nor did it provide decision-making pathways assimilating information about variant type, its location, or any additional evidence for the likelihood of a true null effect. Furthermore, this guideline did not take into account the relative strengths for each evidence type and the final outcome of their combinations with respect to PVS1 strength. Finally, criteria specifying the genes for which PVS1 can be applied are still missing. Here, as part of the ClinGen Sequence Variant Interpretation (SVI) Workgroup's goal of refining ACMG/AMP criteria, we provide recommendations for applying the PVS1 criterion using detailed guidance addressing the above-mentioned gaps. Evaluation of the refined criterion by seven disease-specific groups using heterogeneous types of loss of function variants (n = 56) showed 89% agreement with the new recommendation, while discrepancies in six variants (11%) were appropriately due to disease-specific refinements. Our recommendations will facilitate consistent and accurate interpretation of predicted loss of function variants.
Project description:Clinical mutation screening of the BRCA1 and BRCA2 genes for the presence of germline inactivating mutations is used to identify individuals at elevated risk of breast and ovarian cancer. Variants identified during screening are usually classified as pathogenic (increased risk of cancer) or not pathogenic (no increased risk of cancer). However, a significant proportion of genetic tests yields variants of uncertain significance (VUS) that have undefined risk of cancer. Individuals carrying these VUS cannot benefit from individualized cancer risk assessment. Recently, a quantitative "posterior probability model" for assessing the clinical relevance of VUS in BRCA1 or BRCA2, which integrates multiple forms of genetic evidence has been developed. Here, we provide a detailed review of this model. We describe the components of the model and explain how these can be combined to calculate a posterior probability of pathogenicity for each VUS. We explain how the model can be applied to public data and provide tables that list the VUS that have been classified as not pathogenic or pathogenic using this method. While we use BRCA1 and BRCA2 VUS as examples, the method can be used as a framework for classification of the pathogenicity of VUS in other cancer genes.
Project description:The variant curation guidelines published in 2015 by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) provided the genetics community with a framework to assess variant pathogenicity; however, these rules are not gene specific. Germline pathogenic variants in the CDH1 gene cause hereditary diffuse gastric cancer and lobular breast cancer, a clinically challenging cancer predisposition syndrome that often requires a multidisciplinary team of experts to be properly managed. Given this challenge, the Clinical Genome Resource (ClinGen) Hereditary Cancer Domain prioritized the development of the CDH1 variant curation expert panel (VCEP) to develop and implement rules for CDH1 variant classifications. Here, we describe the CDH1 specifications of the ACMG/AMP guidelines, which were developed and validated after a systematic evaluation of variants obtained from a cohort of clinical laboratory data encompassing ?827,000 CDH1 sequenced alleles. Comparing previously reported germline variants that were classified using the 2015 ACMG/AMP guidelines to the CDH1 VCEP recommendations resulted in reduced variants of uncertain significance and facilitated resolution of variants with conflicted assertions in ClinVar. The ClinGen CDH1 VCEP recommends the use of these CDH1-specific guidelines for the assessment and classification of variants identified in this clinically actionable gene.
Project description:PURPOSE:Standardized and accurate variant assessment is essential for effective medical care. To that end, Clinical Genome (ClinGen) Resource clinical domain working groups (CDWGs) are systematically reviewing disease-associated genes for sufficient evidence to support disease causality and creating disease-specific specifications of American College of Medical Genetics and Genomics-Association for Molecular Pathology (ACMG-AMP) guidelines for consistent and accurate variant classification. METHODS:The ClinGen RASopathy CDWG established an expert panel to curate gene information and generate gene- and disease-specific specifications to ACMG-AMP variant classification framework. These specifications were tested by classifying 37 exemplar pathogenic variants plus an additional 66 variants in ClinVar distributed across nine RASopathy genes. RESULTS:RASopathy-related specifications were applied to 16 ACMG-AMP criteria, with 5 also having adjustable strength with availability of additional evidence. Another 5 criteria were deemed not applicable. Key adjustments to minor allele frequency thresholds, multiple de novo occurrence events and/or segregation, and strength adjustments impacted 60% of variant classifications. Unpublished case-level data from participating laboratories impacted 45% of classifications supporting the need for data sharing. CONCLUSION:RAS-specific ACMG-AMP specifications optimized the utility of available clinical evidence and Ras/MAPK pathway-specific characteristics to consistently classify RASopathy-associated variants. These specifications highlight how grouping genes by shared features promotes rapid multigenic variant assessment without sacrificing specificity and accuracy.
Project description:BACKGROUND:Catecholaminergic polymorphic ventricular tachycardia (CPVT) is often a life-threatening arrhythmia disorder with variable penetrance and expressivity. Little is known about the incidence or outcomes of CPVT patients with ?2 variants. METHODS:The phenotypes, genotypes and outcomes of patients in the Pediatric and Congenital Electrophysiology Society CPVT Registry with ?2 variants in genes linked to CPVT were ascertained. The American College of Medical Genetics & Genomics (ACMG) criteria and structural mapping were used to predict the pathogenicity of variants (3D model of pig RyR2 in open-state). RESULTS:Among 237 CPVT subjects, 193 (81%) had genetic testing. Fifteen patients (8%) with a median age of 9 years (IQR 5-12) had ?2 variants. Sudden cardiac arrest occurred in 11 children (73%), although none died during a median follow-up of 4.3 years (IQR 2.5-6.1). Thirteen patients (80%) had at least two RYR2 variants, while the remaining two patients had RYR2 variants plus variants in other CPVT-linked genes. Among all variants identified, re-classification of the commercial laboratory interpretation using ACMG criteria led to the upgrade from variant of unknown significance (VUS) to pathogenic/likely pathogenic (P/LP) for 5 variants, and downgrade from P/LP to VUS for 6 variants. For RYR2 variants, 3D mapping using the RyR2 model suggested that 2 VUS by ACMG criteria were P/LP, while 2 variants were downgraded to likely benign. CONCLUSIONS:This severely affected cohort demonstrates that a minority of CPVT cases are related to ?2 variants, which may have implications on family-based genetic counselling. While multi-variant CPVT patients were at high-risk for sudden cardiac arrest, there are insufficient data to conclude that this genetic phenomenon has prognostic implications at present. Further research is needed to determine the significance and generalizability of this observation. This study also shows that a rigorous approach to variant re-classification using the ACMG criteria and 3D mapping is important in reaching an accurate diagnosis, especially in the multi-variant population.