Slice Testing-Considerations from Ordering to Reporting: A Joint Report of the Association for Molecular Pathology, College of American Pathologists, and National Society of Genetic Counselors.

As the number of genes associated with various germline disorders continues to grow, it is becoming more difficult for clinical laboratories to maintain separate assays for interrogating disease-focused gene panels. One solution to this challenge is termed slice testing, where capture backbone is used to analyze data specific to a set of genes, and for this article, we will focus on exome. A key advantage to this strategy is greater flexibility by adding genes as they become associated with disease or the ability to accommodate specific provider requests. Here, we provide expert consensus recommendations and results from an Association for Molecular Pathology-sponsored survey of clinical laboratories performing exome sequencing to compare a slice testing approach with traditional static gene panels and comprehensive exome analysis. We explore specific considerations for slices, including gene selection, analytic performance, coverage, quality, and interpretation. Our goal is to provide comprehensive guidance for clinical laboratories interested in designing and using slice tests as a diagnostic.

Implementation, Evolution, and Laboratory Performance of Methods-Based Proficiency Testing for Next-Generation Sequencing Detection of Germline Sequence Variants.

CONTEXT.­: Next-generation sequencing (NGS)-based assays are used for diagnosis of diverse inherited disorders. Limited data are available pertaining to interlaboratory analytical performance of these assays. OBJECTIVE.­: To report on the College of American Pathologists (CAP) NGS Germline Program, which is methods based, and explore the evolution in laboratory testing practices. DESIGN.­: Results from the NGS Germline Program from 2016-2020 were analyzed for interlaboratory analytical performance. Self-reported laboratory testing practices were also evaluated. RESULTS.­: From 2016-2020, a total of 297 laboratories participated in at least 1 program mailing. Of the 289 laboratories that provided information on tests offered, 138 (47.8%) offered only panel testing throughout their enrollment, while 35 (12.1%) offered panels and exome testing, 30 (10.4%) offered only exomes, 9 (3.1%) offered only genomes, and 15 (5.2%) offered panels, exomes, and genomes. The remainder (62 laboratories, 21.4%) changed their test offerings during the 2016-2020 timeframe. Considering each genomic position/interval, the median detection percentage at variant positions across the 2016-2020 mailings ranged from 94.3% to 100%, while at reference positions (no variant detected), the median correct response percentage was 100% across all mailings. When considering performance of individual laboratories, 89.5% (136 of 152) to 98.0% (149 of 152) of laboratories successfully met the detection threshold (≥90% of the variants present), while 94.6% (87 of 92) to 100% (163 of 163) of laboratories met the 95% specificity threshold across mailings. CONCLUSIONS.­: Since the inception of this program, laboratories have consistently performed well. The median sensitivity and specificity of detection of sequence variants included in this program (eg, single nucleotide variants, insertions, and deletions) were 100.0%.

The penetrance of rare variants in cardiomyopathy-associated genes: A cross-sectional approach to estimating penetrance for secondary findings.

Understanding the penetrance of pathogenic variants identified as secondary findings (SFs) is of paramount importance with the growing availability of genetic testing. We estimated penetrance through large-scale analyses of individuals referred for diagnostic sequencing for hypertrophic cardiomyopathy (HCM; 10,400 affected individuals, 1,332 variants) and dilated cardiomyopathy (DCM; 2,564 affected individuals, 663 variants), using a cross-sectional approach comparing allele frequencies against reference populations (293,226 participants from UK Biobank and gnomAD). We generated updated prevalence estimates for HCM (1:543) and DCM (1:220). In aggregate, the penetrance by late adulthood of rare, pathogenic variants (23% for HCM, 35% for DCM) and likely pathogenic variants (7% for HCM, 10% for DCM) was substantial for dominant cardiomyopathy (CM). Penetrance was significantly higher for variant subgroups annotated as loss of function or ultra-rare and for males compared to females for variants in HCM-associated genes. We estimated variant-specific penetrance for 316 recurrent variants most likely to be identified as SFs (found in 51% of HCM- and 17% of DCM-affected individuals). 49 variants were observed at least ten times (14% of affected individuals) in HCM-associated genes. Median penetrance was 14.6% (±14.4% SD). We explore estimates of penetrance by age, sex, and ancestry and simulate the impact of including future cohorts. This dataset reports penetrance of individual variants at scale and will inform the management of individuals undergoing genetic screening for SFs. While most variants had low penetrance and the costs and harms of screening are unclear, some individuals with highly penetrant variants may benefit from SFs.

Elective genomic testing: Practice resource of the National Society of Genetic Counselors.

Genetic counseling for patients who are pursuing genetic testing in the absence of a medical indication, referred to as elective genomic testing (EGT), is becoming more common. This type of testing has the potential to detect genetic conditions before there is a significant health impact permitting earlier management and/or treatment. Pre- and post-test counseling for EGT is similar to indication-based genetic testing. Both require a complete family and medical history when ordering a test or interpreting a result. However, EGT counseling has some special considerations including greater uncertainties around penetrance and clinical utility and a lack of published guidelines. While certain considerations in the selection of a high-quality genetic testing laboratory are universal, there are some considerations that are unique to the selection of a laboratory performing EGT. This practice resource intends to provide guidance for genetic counselors and other healthcare providers caring for adults seeking pre- or post-test counseling for EGT. Genetic counselors and other genetics trained healthcare providers are the ideal medical professionals to supply accurate information to individuals seeking counseling about EGT enabling them to make informed decisions about testing and follow-up.

A Framework of Critical Considerations in Clinical Exome Reanalyses by Clinical and Laboratory Standards Institute.

Exome reanalysis is useful for providing molecular diagnoses for previously uninformative samples. However, challenges exist in implementing a practical solution for clinicians and laboratories. This study complements the current literature by providing practical considerations for patient-level and cohort-level reanalyses. The Clinical and Laboratory Standards Institute assembled the Document Development Committee and an interpretation working group that developed the framework for reevaluation of exome-based data. We describe two distinct but complementary approaches toward exome reanalyses: clinician-initiated patient-level reanalysis, and laboratory-initiated cohort-level reanalysis. We highlight the advantages and constraints for both approaches, and provide a high-level conceptual guide for ordering clinicians and laboratories through the critical decision pathways. Because clinical exome sequencing continues to be the standard of care in genetics, exome reanalysis would be critical in increasing the overall diagnostic yield. A systematic guide will facilitate the efficient adoption of reevaluation of exome data for laboratories, health care professionals, genetic counselors, and clinicians.

Creation of an Expert Curated Variant List for Clinical Genomic Test Development and Validation: A ClinGen and GeT-RM Collaborative Project.

Modern genomic sequencing tests often interrogate large numbers of genes. Identification of appropriate reference materials for development, validation studies, and quality assurance of these tests poses a significant challenge for laboratories. It is difficult to develop and maintain expert knowledge to identify all variants that must be validated to ensure analytic and clinical validity. Additionally, it is usually not possible to procure appropriate and characterized genomic DNA reference materials containing the number and scope of variants required. To address these challenges, the Centers for Disease Control and Prevention's Genetic Testing Reference Material Program (GeT-RM) has partnered with the Clinical Genome Resource (ClinGen) to develop a publicly available list of expert curated, clinically important variants. ClinGen Variant Curation Expert Panels nominated 546 variants found in 84 disease-associated genes, including common pathogenic and difficult-to-detect variants. Variant types nominated included 346 single nucleotide variants, 104 deletions, 37 copy number variants, 25 duplications, 18 deletion-insertions, 5 inversions, 4 insertions, 2 complex rearrangements, 3 difficult-to-sequence regions, and 2 fusions. This expert-curated variant list is a resource that provides a foundation for designing comprehensive validation studies and for creating in silico reference materials for clinical genomic test development and validation.

The genetic architecture of Plakophilin 2 cardiomyopathy.

PURPOSE: The genetic architecture of Plakophilin 2 (PKP2) cardiomyopathy can inform our understanding of its variant pathogenicity and protein function. METHODS: We assess the gene-wide and regional association of truncating and missense variants in PKP2 with arrhythmogenic cardiomyopathy (ACM), and arrhythmogenic right ventricular cardiomyopathy (ARVC) specifically. A discovery data set compares genetic testing requisitions to gnomAD. Validation is performed in a rigorously phenotyped definite ARVC cohort and non-ACM individuals in the Geisinger MyCode cohort. RESULTS: The etiologic fraction (EF) of ACM-related diagnoses from truncating variants in PKP2 is significant (0.85 [0.80,0.88], p < 2 × 10-16), increases for ARVC specifically (EF = 0.96 [0.94,0.97], p < 2 × 10-16), and is highest in definite ARVC versus non-ACM individuals (EF = 1.00 [1.00,1.00], p < 2 × 10-16). Regions of missense variation enriched for ACM probands include known functional domains and the C-terminus, which was not previously known to contain a functional domain. No regional enrichment was identified for truncating variants. CONCLUSION: This multicohort evaluation of the genetic architecture of PKP2 demonstrates the specificity of PKP2 truncating variants for ARVC within the ACM disease spectrum. We identify the PKP2 C-terminus as a potential functional domain and find that truncating variants likely cause disease irrespective of transcript position.

Harmonizing the Collection of Clinical Data on Genetic Testing Requisition Forms to Enhance Variant Interpretation in Hypertrophic Cardiomyopathy (HCM): A Study from the ClinGen Cardiomyopathy Variant Curation Expert Panel.

Diagnostic laboratories gather phenotypic data through requisition forms, but there is no consensus as to which data are essential for variant interpretation. The ClinGen Cardiomyopathy Variant Curation Expert Panel defined a phenotypic data set for hypertrophic cardiomyopathy (HCM) variant interpretation, with the goal of standardizing requisition forms. Phenotypic data elements listed on requisition forms from nine leading cardiomyopathy testing laboratories were compiled to assess divergence in data collection. A pilot of 50 HCM cases was implemented to determine the feasibility of harmonizing data collection. Laboratory directors were surveyed to gauge potential for adoption of a minimal data set. Wide divergence was observed in the phenotypic data fields in requisition forms. The 50-case pilot showed that although demographics and assertion of a clinical diagnosis of HCM had 86% to 98% completion, specific phenotypic features, such as degree of left ventricular hypertrophy, ejection fraction, and suspected syndromic disease, were completed only 24% to 44% of the time. Nine data elements were deemed essential for variant classification by the expert panel. Participating laboratories unanimously expressed a willingness to adopt these data elements in their requisition forms. This study demonstrates the value of comparing and sharing best practices through an expert group, such as the ClinGen Program, to enhance variant interpretation, providing a foundation for leveraging cumulative case-level data in public databases and ultimately improving patient care.

Systematic large-scale assessment of the genetic architecture of left ventricular noncompaction reveals diverse etiologies.

PURPOSE: To characterize the genetic architecture of left ventricular noncompaction (LVNC) and investigate the extent to which it may represent a distinct pathology or a secondary phenotype associated with other cardiac diseases. METHODS: We performed rare variant association analysis with 840 LVNC cases and 125,748 gnomAD population controls, and compared results to similar analyses on dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM). RESULTS: We observed substantial genetic overlap indicating that LVNC often represents a phenotypic variation of DCM or HCM. In contrast, truncating variants in MYH7, ACTN2, and PRDM16 were uniquely associated with LVNC and may reflect a distinct LVNC etiology. In particular, MYH7 truncating variants (MYH7tv), generally considered nonpathogenic for cardiomyopathies, were 20-fold enriched in LVNC cases over controls. MYH7tv heterozygotes identified in the UK Biobank and healthy volunteer cohorts also displayed significantly greater noncompaction compared with matched controls. RYR2 exon deletions and HCN4 transmembrane variants were also enriched in LVNC, supporting prior reports of association with arrhythmogenic LVNC phenotypes. CONCLUSION: LVNC is characterized by substantial genetic overlap with DCM/HCM but is also associated with distinct noncompaction and arrhythmia etiologies. These results will enable enhanced application of LVNC genetic testing and help to distinguish pathological from physiological noncompaction.

An assessment of the role of vinculin loss of function variants in inherited cardiomyopathy.

The ACMG/AMP variant classification framework was intended for highly penetrant Mendelian conditions. While it is appreciated that clinically relevant variants exhibit a wide spectrum of penetrance, accurately assessing and expressing the pathogenicity of variants with lower penetrance can be challenging. The vinculin (VCL) gene illustrates these challenges. Model organism data provide evidence that loss of function of VCL may play a role in cardiomyopathy and aggregate case-control studies suggest low penetrance. VCL loss of function variants, however, are rarely identified in affected probands and therefore there is a paucity of family studies clarifying the clinical significance of individual variants. This study, which aggregated data from >18,000 individuals who underwent gene panel or exome testing for inherited cardiomyopathies, identified 32 probands with VCL loss-of-function variants and confirmed enrichment in probands with dilated cardiomyopathy (odds ratio [OR] = 9.01; confidence interval [CI] = 4.93-16.45). Our data revealed that the majority of these individuals (89.5%) had pediatric onset of disease. Family studies demonstrated that heterozygous loss of function of VCL alone is insufficient to cause cardiomyopathy but that these variants do contribute to disease risk. In conclusion, VCL loss-of-function variants should be reported in a diagnostic setting but need to be clearly distinguished as having lower penetrance.

Design and Reporting Considerations for Genetic Screening Tests.

Testing asymptomatic individuals for unsuspected conditions is not new to the medical and public health communities. Protocols to develop screening tests are well established. However, the application of screening principles to inherited diseases presents unique challenges. Unlike most screening tests, the natural history and disease prevalence of most rare inherited diseases in an unselected population are unknown. It is difficult or impossible to obtain a truth set cohort for clinical validation studies. As a result, it is not possible to accurately calculate clinical positive and negative predictive values for likely pathogenic variants, which are commonly returned in genetic screening assays. In addition, many of the genetic conditions included in screening panels do not have clinical confirmatory tests. All these elements are typically required to justify the development of a screening test, according to the World Health Organization screening principles. Nevertheless, as the cost of DNA sequencing continues to fall, more individuals are opting to undergo genomic testing in the absence of a clinical indication. Despite the challenges, reasonable estimates can be deduced and used to inform test design strategies. Herein, we review basic test design principles and apply them to genetic screening.

Reevaluating the Genetic Contribution of Monogenic Dilated Cardiomyopathy.

BACKGROUND: Dilated cardiomyopathy (DCM) is genetically heterogeneous, with >100 purported disease genes tested in clinical laboratories. However, many genes were originally identified based on candidate-gene studies that did not adequately account for background population variation. Here we define the frequency of rare variation in 2538 patients with DCM across protein-coding regions of 56 commonly tested genes and compare this to both 912 confirmed healthy controls and a reference population of 60 706 individuals to identify clinically interpretable genes robustly associated with dominant monogenic DCM. METHODS: We used the TruSight Cardio sequencing panel to evaluate the burden of rare variants in 56 putative DCM genes in 1040 patients with DCM and 912 healthy volunteers processed with identical sequencing and bioinformatics pipelines. We further aggregated data from 1498 patients with DCM sequenced in diagnostic laboratories and the Exome Aggregation Consortium database for replication and meta-analysis. RESULTS: Truncating variants in TTN and DSP were associated with DCM in all comparisons. Variants in MYH7, LMNA, BAG3, TNNT2, TNNC1, PLN, ACTC1, NEXN, TPM1, and VCL were significantly enriched in specific patient subsets, with the last 2 genes potentially contributing primarily to early-onset forms of DCM. Overall, rare variants in these 12 genes potentially explained 17% of cases in the outpatient clinic cohort representing a broad range of adult patients with DCM and 26% of cases in the diagnostic referral cohort enriched in familial and early-onset DCM. Although the absence of a significant excess in other genes cannot preclude a limited role in disease, such genes have limited diagnostic value because novel variants will be uninterpretable and their diagnostic yield is minimal. CONCLUSIONS: In the largest sequenced DCM cohort yet described, we observe robust disease association with 12 genes, highlighting their importance in DCM and translating into high interpretability in diagnostic testing. The other genes analyzed here will need to be rigorously evaluated in ongoing curation efforts to determine their validity as Mendelian DCM genes but have limited value in diagnostic testing in DCM at present. This data will contribute to community gene curation efforts and will reduce erroneous and inconclusive findings in diagnostic testing.

Diagnostic gene sequencing panels: from design to report-a technical standard of the American College of Medical Genetics and Genomics (ACMG).

Gene sequencing panels are a powerful diagnostic tool for many clinical presentations associated with genetic disorders. Advances in DNA sequencing technology have made gene panels more economical, flexible, and efficient. Because the genes included on gene panels vary widely between laboratories in gene content (e.g., number, reason for inclusion, evidence level for gene-disease association) and technical completeness (e.g., depth of coverage), standards that address technical and clinical aspects of gene panels are needed. This document serves as a technical standard for laboratories designing, offering, and reporting gene panel testing. Although these principles can apply to multiple indications for genetic testing, the primary focus is on diagnostic gene panels (as opposed to carrier screening or predictive testing) with emphasis on technical considerations for the specific genes being tested. This technical standard specifically addresses the impact of gene panel content on clinical sensitivity, specificity, and validity-in the context of gene evidence for contribution to and strength of evidence for gene-disease association-as well as technical considerations such as sequencing limitations, presence of pseudogenes/gene families, mosaicism, transcript choice, detection of copy-number variants, reporting, and disclosure of assay limitations.

Considerations for clinical curation, classification, and reporting of low-penetrance and low effect size variants associated with disease risk.

PURPOSE: Clinically relevant variants exhibit a wide range of penetrance. Medical practice has traditionally focused on highly penetrant variants with large effect sizes and, consequently, classification and clinical reporting frameworks are tailored to that variant type. At the other end of the penetrance spectrum, where variants are often referred to as "risk alleles," traditional frameworks are no longer appropriate. This has led to inconsistency in how such variants are interpreted and classified. Here, we describe a conceptual framework to begin addressing this gap. METHODS: We used a set of risk alleles to define data elements that can characterize the validity of reported disease associations. We assigned weight to these data elements and established classification categories expressing confidence levels. This framework was then expanded to develop criteria for inclusion of risk alleles on clinical reports. RESULTS: Foundational data elements include cohort size, quality of phenotyping, statistical significance, and replication of results. Criteria for determining inclusion of risk alleles on clinical reports include presence of clinical management guidelines, effect size, severity of the associated phenotype, and effectiveness of intervention. CONCLUSION: This framework represents an approach for classifying risk alleles and can serve as a foundation to catalyze community efforts for refinement.

Regional Variation in RBM20 Causes a Highly Penetrant Arrhythmogenic Cardiomyopathy.

Background Variants in the cardiomyocyte-specific RNA splicing factor RBM20 have been linked to familial cardiomyopathy, but the causative genetic architecture and clinical consequences of this disease are incompletely defined. Methods and Results To define the genetic architecture of RBM20 cardiomyopathy, we first established a database of RBM20 variants associated with cardiomyopathy and compared these to variants observed in the general population with respect to their location in the RBM20 coding transcript. We identified 2 regions significantly enriched for cardiomyopathy-associated variants in exons 9 and 11. We then assembled a registry of 74 patients with RBM20 variants from 8 institutions across the world (44 index cases and 30 from cascade testing). This RBM20 patient registry revealed highly prevalent family history of sudden cardiac death (51%) and cardiomyopathy (72%) among index cases and a high prevalence of composite arrhythmias (including atrial fibrillation, nonsustained ventricular tachycardia, implantable cardiac defibrillator discharge, and sudden cardiac arrest, 43%). Patients harboring variants in cardiomyopathy-enriched regions identified by our variant database analysis were enriched for these findings. Further, these characteristics were more prevalent in the RBM20 registry than in large cohorts of patients with dilated cardiomyopathy and TTNtv cardiomyopathy and not significantly different from a cohort of patients with LMNA-associated cardiomyopathy. Conclusions Our data establish RBM20 cardiomyopathy as a highly penetrant and arrhythmogenic cardiomyopathy. These findings underline the importance of arrhythmia surveillance and family screening in this disease and represent the first step in defining the genetic architecture of RBM20 disease causality on a population level.

Best practices for benchmarking germline small-variant calls in human genomes.

Standardized benchmarking approaches are required to assess the accuracy of variants called from sequence data. Although variant-calling tools and the metrics used to assess their performance continue to improve, important challenges remain. Here, as part of the Global Alliance for Genomics and Health (GA4GH), we present a benchmarking framework for variant calling. We provide guidance on how to match variant calls with different representations, define standard performance metrics, and stratify performance by variant type and genome context. We describe limitations of high-confidence calls and regions that can be used as truth sets (for example, single-nucleotide variant concordance of two methods is 99.7% inside versus 76.5% outside high-confidence regions). Our web-based app enables comparison of variant calls against truth sets to obtain a standardized performance report. Our approach has been piloted in the PrecisionFDA variant-calling challenges to identify the best-in-class variant-calling methods within high-confidence regions. Finally, we recommend a set of best practices for using our tools and evaluating the results.