Clinical Interpretation Of Sequence Variants Research Articles

Clinical phenotype and genetic analysis of patients with left ventricular noncompaction caused by the biallelic mutation of MYBPC3 and MYH7

Objective: To explore the relationship between pathogenic gene, mutation and phenotype of left ventricular noncompaction (LVNC) patients and their family members. Methods: The subjects were the proband with LVNC and her family members. The medical history including electrocardiogram, echocardiography and cardiac magnetic resonance examination of the proband and family members were collected. Whole exome sequencing of the proband was performed, bioinformatics analysis focused on the genes related to hereditary cardiomyopathy. Candidate pathogenic sites were validated by Sanger sequencing. The clinical interpretation of sequence variants were classified according to American College of Medical Genetics and Genomics (ACMG) guidelines. Results: The proband carried a heterozygous variation of the MYBPC3 gene c.C2827T and the MYH7 gene c.G2221C. The proband's sister carried heterozygous variation of MYBPC3 gene c.C2827T. According to the ACMG guidelines, the variant was determined to be pathogenic. Conclusion: The missense variant of MYBPC3 gene c.C2827T and MYH7 gene c.G2221C are identified from the proband with LVNC and her family member, which provides a genetic basis for clinical diagnosis and genetic counseling of the patients and the family members with LVNC.

Specifications and validation of the ACMG/AMP criteria for clinical interpretation of sequence variants in collagen genes associated with joint hypermobility

Deleterious variants in collagen genes are the most common cause of hereditary connective tissue disorders (HCTD). Adaptations of the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) criteria are still lacking. A multidisciplinary team was set up for developing specifications of the ACMG/AMP criteria for COL1A1, COL1A2, COL2A1, COL3A1, COL5A1, COL5A2, COL11A1, COL11A2 and COL12A1, associated with various forms of HCTD featuring joint hypermobility, which is becoming one of the most common reasons of referral for molecular testing in this field. Such specifications were validated against 209 variants, and resulted effective for classifying as pathogenic and likely pathogenic null alleles without downgrading of the PVS1 level of strength and recurrent Glycine substitutions. Adaptations of selected criteria reduced uncertainties on private Glycine substitutions, intronic variants predicted to affect the splicing, and null alleles with a downgraded PVS1 level of strength. Segregation and multigene panel sequencing data mitigated uncertainties on non-Glycine substitutions by the attribution of one or more benignity criteria. These specifications may improve the clinical utility of molecular testing in HCTD by reducing the number of variants with neutral/conflicting interpretations. Close interactions between laboratory and clinicians are crucial to estimate the a priori utility of molecular test and to improve medical reports.

Clinical Interpretation of Sequence Variants.

Clinical interpretation of DNA sequence variants is a critical step in reporting clinical genetic testing results. Application of next-generation sequencing technology in molecular genetic testing has facilitated diagnoses of genetic disorders in clinical practice. However, the large number of DNA sequence variants detected in clinical specimens, many of which have never been seen before, make clinical interpretation challenging. Recommendations by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) have been widely adopted by clinical laboratories around the world to guide clinical interpretation of sequence variants. The ClinGen Sequence Variant Interpretation Working Group and various disease-specific variant curation expert panels have also developed specifications for the ACMG/AMP recommendations. Despite these efforts to standardize variant interpretation in clinical practice, different laboratories may subjectively use professional judgment to determine which criteria are applicable when classifying a variant. In addition, clinicians and researchers who are not familiar with the variant interpretation process may have difficulty understanding clinical genetic reports and communicating the clinical significance of genetic testing results. Here we provide a step-by-step protocol for clinical interpretation of sequence variants, including practical examples. By following this protocol, clinical laboratory geneticists can interpret the clinical significance of sequence variants according to the ACMG/AMP recommendations and ClinGen framework. Furthermore, this article will help clinicians and researchers to understand variant classification in clinical genetic testing reports and evaluate the quality of the reports. © 2020 by John Wiley & Sons, Inc. Basic Protocol: Interpreting the clinical significance of sequence variants Support Protocol: Reevaluating the clinical significance of sequence variants.

Comparative analysis of functional assay evidence use by ClinGen Variant Curation Expert Panels

BackgroundThe 2015 American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) guidelines for clinical sequence variant interpretation state that “well-established” functional studies can be used as evidence in variant classification. These guidelines articulated key attributes of functional data, including that assays should reflect the biological environment and be analytically sound; however, details of how to evaluate these attributes were left to expert judgment. The Clinical Genome Resource (ClinGen) designates Variant Curation Expert Panels (VCEPs) in specific disease areas to make gene-centric specifications to the ACMG/AMP guidelines, including more specific definitions of appropriate functional assays. We set out to evaluate the existing VCEP guidelines for functional assays.MethodsWe evaluated the functional criteria (PS3/BS3) of six VCEPs (CDH1, Hearing Loss, Inherited Cardiomyopathy-MYH7, PAH, PTEN, RASopathy). We then established criteria for evaluating functional studies based on disease mechanism, general class of assay, and the characteristics of specific assay instances described in the primary literature. Using these criteria, we extensively curated assay instances cited by each VCEP in their pilot variant classification to analyze VCEP recommendations and their use in the interpretation of functional studies.ResultsUnsurprisingly, our analysis highlighted the breadth of VCEP-approved assays, reflecting the diversity of disease mechanisms among VCEPs. We also noted substantial variability between VCEPs in the method used to select these assays and in the approach used to specify strength modifications, as well as differences in suggested validation parameters. Importantly, we observed discrepancies between the parameters VCEPs specified as required for approved assay instances and the fulfillment of these requirements in the individual assays cited in pilot variant interpretation.ConclusionsInterpretation of the intricacies of functional assays often requires expert-level knowledge of the gene and disease, and current VCEP recommendations for functional assay evidence are a useful tool to improve the accessibility of functional data by providing a starting point for curators to identify approved functional assays and key metrics. However, our analysis suggests that further guidance is needed to standardize this process and ensure consistency in the application of functional evidence.

Molecular diagnostic workflow, clinical interpretation of sequence variants, and data repository procedures in 140 individuals with familial cerebral cavernous malformations

Familial cerebral cavernous malformation (FCCM) is an autosomal dominant vascular disorder caused by heterozygous deleterious variants in KRIT1, CCM2 or PDCD10. In a previous study, we presented the clinical and molecular findings in 140 FCCM individuals. In the present work, we report supporting information on (a) applied diagnostic workflow; (b) clinical significance of molecular findings according to the American College of Medical Genetics and Genomics/Association for Molecular Pathology recommendations; (c) standardization of molecular and clinical data according to the Human Phenotype Ontology; (d) preliminary genotype-phenotype correlations on a subgroup of patients by considering sex, age at diagnosis, neurological symptoms, and number and anatomical site(s) of vascular anomalies; (e) datasets submitted to the Leiden Open Variation Database. An overview of the changes of our diagnostic approach before and after the transition to next-generation sequencing is also reported. This work presents the full procedure that we apply for molecular testing, data interpretation and storing in public databases in FCCM.

Sudden infant death as the most severe phenotype caused by genetic modulation in a family with atrial fibrillation

AimsTo assess the functional impact of two combined KCNH2 variants involved in atrial fibrillation, syncope and sudden infant death syndrome. Methods and resultsGenetic testing of a 4-month old SIDS victim identified a rare missense heterozygous in KCNH2 variant (V483I) and a missense homozygous polymorphism (K897T) which is often described as a genetic modifier. Electrophysiological characterisation of heterologous HERG channels representing two different KCNH2 genotypes within the family, showed significant differences in both voltage and time dependence of activation and inactivation with a global gain-of-function effect of mutant versus wild type channels and, also, differences between both types of recombinant channels. ConclusionsThe rare variant V483I in combination with K897T produces a gain-of-function effect that represents a pathological substrate for atrial fibrillation, syncope and sudden infant death syndrome events in this family. Ascertaining the genotype-phenotype correlation of genetic variants is imperative for the correct assessment of genetic testing and counselling. Translational perspectiveAccording to the current guidelines for clinical interpretation of sequence variants, functional studies are an essential tool for the ascertainment of variant pathogenicity. They are especially relevant in the context of sudden infant death syndrome and sudden cardiac death, where individuals cannot be clinically evaluated. The patch-clamp technique is a gold-standard for analysis of the biophysical mechanisms of ion channels.

Interactive Browser-Based Genomics Data Visualization Tools for Translational and Clinical Laboratory Applications

Visualization-driven data exploration is a highly effective modality for interpreting and discovering insights from high-throughput genomics data sets; however, it is vastly underutilized in routine workflows in clinical and translation settings. We have developed three open-source, browser-based, interactive genomics data visualization widgets that can be used as intuitive stand-alone applications or integrated with existing web-based laboratory information solutions. The widgets were developed in JavaScript using the D3.js library. These widgets run in any modern web browser across desktop and mobile devices for easy accessibility but are designed for client-side data processing to address data privacy concerns. jsProteinMapper plots the location of a variant of interest relative to the protein domains and multiple variant databases, assisting with clinical interpretation of sequence variants. jsComut generates a highly interactive and customizable comutation plot for visual exploration of genomic data sets with clinicopathologic annotations to reveal unique molecular profiles and clinical correlates. jsCodonWheel is an interactive version of the ubiquitous circular codon-to-amino acid translation table, which lets users quickly map nucleotide changes onto resulting amino acid differences. These open-source visualization tools may improve some of the key laboratory workflows that involve the review of large-scale genomics data sets in a high-volume setting. The intuitive and responsive user interface, highly customizable visualizations, and easy integration with existing web-based laboratory software are significant highlights of these tools.

ClinGen Variant Curation Expert Panel experiences and standardized processes for disease and gene‐level specification of the ACMG/AMP guidelines for sequence variant interpretation

Genome-scale sequencing creates vast amounts of genomic data, increasing the challenge of clinical sequence variant interpretation. The demand for high-quality interpretation requires multiple specialties to join forces to accelerate the interpretation of sequence variant pathogenicity. With over 600 international members including clinicians, researchers, and laboratory diagnosticians, the Clinical Genome Resource (ClinGen), funded by the National Institutes of Health, is forming expert groups to systematically evaluate variants in clinically relevant genes. Here, we describe the first ClinGen variant curation expert panels (VCEPs), development of consistent and streamlined processes for establishing new VCEPs, and creation of standard operating procedures for VCEPs to define application of the ACMG/AMP guidelines for sequence variant interpretation in specific genes or diseases. Additionally, ClinGen has created user interfaces to enhance reliability of curation and a Sequence Variant Interpretation Working Group (SVI WG) to harmonize guideline specifications and ensure consistency between groups. The expansion of VCEPs represents the primary mechanism by which curation of a substantial fraction of genomic variants can be accelerated and ultimately undertaken systematically and comprehensively. We welcome groups to utilize our resources and become involved in our effort to create a publicly accessible, centralized resource for clinically relevant genes and variants.

Quantifying the potential of functional evidence to reclassify variants of uncertain significance in the categorical and Bayesian interpretation frameworks.

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.

Navigating the nuances of clinical sequence variant interpretation in Mendelian disease.

Understanding clinical genetic test results in the era of next-generation sequencing has become increasingly complex, necessitating clear and thorough guidelines for sequence variant interpretation. To meet this need the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) published guidelines for a systematic approach for sequence variant interpretation in 2015. This framework is intended to be adaptable to any Mendelian condition, promoting transparency and consistency in variant interpretation, yet its comprehensive nature yields important challenges and caveats that end users must understand. In this review, we address some of these nuances and discuss the evolving efforts to refine and adapt this framework. We also consider the added complexity of distinguishing between variant-level interpretations and case-level conclusions, particularly in the context of the large gene panel approach to clinical diagnostics.

Pathogenic variant burden in the ExAC database: an empirical approach to evaluating population data for clinical variant interpretation

BackgroundThe frequency of a variant in the general population is a key criterion used in the clinical interpretation of sequence variants. With certain exceptions, such as founder mutations, the rarity of a variant is a prerequisite for pathogenicity. However, defining the threshold at which a variant should be considered “too common” is challenging and therefore diagnostic laboratories have typically set conservative allele frequency thresholds.MethodsRecent publications of large population sequencing data, such as the Exome Aggregation Consortium (ExAC) database, provide an opportunity to characterize with accuracy and precision the frequency distributions of very rare disease-causing alleles. Allele frequencies of pathogenic variants in ClinVar, as well as variants expected to be pathogenic through the nonsense-mediated decay (NMD) pathway, were analyzed to study the burden of pathogenic variants in 79 genes of clinical importance.ResultsOf 1364 BRCA1 and BRCA2 variants that are well characterized as pathogenic or that are expected to lead to NMD, 1350 variants had an allele frequency of less than 0.0025%. The remaining 14 variants were previously published founder mutations. Importantly, we observed no difference in the distributions of pathogenic variants expected to be lead to NMD compared to those that are not. Therefore, we expanded the analysis to examine the distributions of NMD expected variants in 77 additional genes. These 77 genes were selected to represent a broad set of clinical areas, modes of inheritance, and penetrance. Among these variants, most (97.3%) had an allele frequency of less than 0.01%. Furthermore, pathogenic variants with allele frequencies greater than 0.01% were well characterized in publications and included many founder mutations.ConclusionsThe observations made in this study suggest that, with certain caveats, a very low allele frequency threshold can be adopted to more accurately interpret sequence variants.

InterVar: Clinical Interpretation of Genetic Variants by the 2015 ACMG-AMP Guidelines

In 2015, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) published updated standards and guidelines for the clinical interpretation of sequence variants with respect to human diseases on the basis of 28 criteria. However, variability between individual interpreters can be extensive because of reasons such as the different understandings of these guidelines and the lack of standard algorithms for implementing them, yet computational tools for semi-automated variant interpretation are not available. To address these problems, we propose a suite of methods for implementing these criteria and have developed a tool called InterVar to help human reviewers interpret the clinical significance of variants. InterVar can take a pre-annotated or VCF file as input and generate automated interpretation on 18 criteria. Furthermore, we have developed a companion web server, wInterVar, to enable user-friendly variant interpretation with an automated interpretation step and a manual adjustment step. These tools are especially useful for addressing severe congenital or very early-onset developmental disorders with high penetrance. Using results from a few published sequencing studies, we demonstrate the utility of InterVar in significantly reducing the time to interpret the clinical significance of sequence variants.

Approaches for classifying DNA variants found by Sanger sequencing in a medical genetics laboratory.

Diagnostic applications of DNA sequencing technologies present a powerful tool for the clinical management of patients. Applications range from better diagnostic classification to identification of therapeutic options, prediction of drug response and toxicity, and carrier testing. Although the advent of massively parallel sequencing technologies has increased the complexity of clinical interpretation of sequence variants by an order of magnitude, the annotation and interpretation of the clinical effects of identified genomic variants remain a challenge regardless of the sequencing technologies used to identify them. Here, we survey methodologies which assist in the diagnostic classification of DNA variants and propose a practical decision analytic protocol to assist in the classification of sequencing variants in a clinical setting. The methods include database queries, software tools for protein consequence, evolutionary conservation and pathogenicity prediction, familial segregation, case-control studies, and literature review. These methods are deliberately pragmatic as diagnostic constraints of clinically useful turnaround times generally preclude obtaining evidence from in vivo or in vitro functional experiments for variant assessment. Clinical considerations require that variant classification is stringent and rigorous, as misinterpretation may lead to inappropriate clinical consequences; thus, multiple parameters and lines of evidence are considered to determine potential biological significance.

Bayes analysis provides evidence of pathogenicity for the BRCA1 c.135-1G>T (IVS3-1) and BRCA2 c.7977-1G>C (IVS17-1) variants displaying in vitro splicing results of equivocal clinical significance

Although in vitro splicing assays can provide useful information about the clinical interpretation of sequence variants in high-risk cancer genes such as BRCA1 and BRCA2, results can sometimes be difficult to interpret. The BRCA1 c.135-1G>T (IVS3-1G>T) variant has been shown to give rise to an in-frame deletion of exon 5 (BRCA1 c.135_212del) that is predicted to encode 26 amino acids. BRCA2 c.7977-1G>C (IVS17-1G>C) was shown to increase the expression of two naturally occurring transcripts that contain frameshifts (BRCA2, c.7977_8311del (exon 18 deletion); BRCA2, c.7806_8331del (exon 17&18 deletion)). In this study we conducted multifactorial likelihood analysis to evaluate the clinical significance of these two variants, including assessing variant segregation in families by Bayes analysis, and breast tumor pathology features suggestive of positive mutation status. Multifactorial analysis provided strong evidence for causality for both of these variants. The Bayes scores from a single family with BRCA1 c.135-1G>T was 9528:1, and incorporation of pathology features gave an overall likelihood of causality of 28108:1. The Bayes scores from five informative families with BRCA2 c.7977-1G>C was 47401:1, and the combined Bayes-pathology odds of causality was 29389:1. Multifactorial likelihood analysis indicates that the BRCA1 c.135-1G>T and BRCA2 c.7977-1G>C variants are disease-associated mutations which should be managed clinically in the same fashion as classical truncating mutations.