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The advancement of precision medicine requires new methods to coordinate and deliver genetic data from heterogeneous sources to physicians and patients. The eMERGE III Network enrolled >25,000 participants from biobank and prospective cohorts of predominantly healthy individuals for clinical genetic testing to determine clinically actionable findings. The network developed protocols linking together the 11 participant collection sites and 2 clinical genetic testing laboratories. DNA capture panels targeting 109 genes were used for testing of DNA and sample collection, data generation, interpretation, reporting, delivery, and storage were each harmonized. A compliant and secure network enabled ongoing review and reconciliation of clinical interpretations, while maintaining communication and data sharing between clinicians and investigators. A total of 202 individuals had positive diagnostic findings relevant to the indication for testing and 1,294 had additional/secondary findings of medical significance deemed to be returnable, establishing data return rates for other testing endeavors. This study accomplished integration of structured genomic results into multiple electronic health record (EHR) systems, setting the stage for clinical decision support to enable genomic medicine. Further, the established processes enable different sequencing sites to harmonize technical and interpretive aspects of sequencing tests, a critical achievement toward global standardization of genomic testing. The eMERGE protocols and tools are available for widespread dissemination.

Diagnostic next-generation sequencing (NGS)-based gene panels are increasingly used for prevalent disorders with genetic and clinical heterogeneity. Clinical development, validation, and quality management of these panels ideally includes reference samples containing prevalent pathogenic variants; however, clinical domain expertise to select appropriate variants may not be present, samples are often not publicly available, and their inclusion is associated with added cost. Expert-designed, multiplexed controls can remedy some of these challenges. One approach relies on spiking biosynthetic fragments carrying desired variants into human genomic DNA. We piloted the utility of this approach for hypertrophic cardiomyopathy. Data from >3000 previously sequenced probands were used to select 10 common pathogenic and/or technically challenging variants in the top hypertrophic cardiomyopathy genes. Multiplexed controls were constructed across a range of ideal and realistic allelic fractions for heterozygous germline variants. NGS was performed in quadruplicate, and results were compared with diagnostic NGS data for the source patient samples. Overall, results were indistinguishable from patient-derived data with variants being detected at or reasonably close to the targeted allelic fraction ratios. The exception was a common 25-bp deletion in MYBPC3, underscoring the importance of including such variants in test development. These controls may be an attractive addition to the repertoire of materials for development, validation, and quality monitoring of clinical NGS assays.

Variant interpretation depends on accurate annotations using biologically relevant transcripts. We have developed a systematic strategy for designating primary transcripts and have applied it to 109 hearing loss–associated genes that were divided into three categories. Category 1 genes (n = 38) had a single transcript; category 2 genes (n = 33) had multiple transcripts, but a single transcript was sufficient to represent all exons; and category 3 genes (n = 38) had multiple transcripts with unique exons. Transcripts were curated with respect to gene expression reported in the literature and the Genotype-Tissue Expression Project. In addition, high-frequency loss-of-function variants in the Genome Aggregation Database and disease-causing variants in ClinVar and the Human Gene Mutation Database across the 109 genes were queried. These data were used to classify exons as clinically significant, insignificant, or of uncertain significance. Interestingly, 6% of all exons, containing 124 reportedly disease-causing variants, were of uncertain significance. Finally, we used exon-level next-generation sequencing quality metrics generated at two clinical laboratories and identified a total of 43 technically challenging exons in 20 different genes that had inadequate coverage and/or homology issues that might lead to false-variant calls. We have demonstrated that transcript analysis plays a critical role in accurate clinical variant interpretation.

Background Diagnostic testing for genetic cardiomyopathies has undergone dramatic changes in the last decade with next generation sequencing (NGS) expanding the number of genes that can be interrogated simultaneously. Exon resolution copy number analysis is increasingly incorporated into routine diagnostic testing via cytogenomic arrays and more recently via NGS. While NGS is an attractive option for laboratories that have no access to array platforms, its higher false positive rate requires weighing the added cost incurred by orthogonal confirmation against the magnitude of the increase in diagnostic yield. Although copy number variants (CNVs) have been reported in various cardiomyopathy genes, their contribution has not been systematically studied. Methods We performed single exon resolution NGS‐based deletion/duplication analysis for up to 46 cardiomyopathy genes in >1400 individuals with cardiomyopathies including HCM, DCM, ARVC, RCM, and LVNC. Results and Conclusion Clinically significant deletions and duplications were identified in only 9 of 1425 (0.63%) individuals. The majority of those (6/9) represented intragenic events. We conclude that the added benefit of exon level deletion/duplication analysis is low for currently known cardiomyopathy genes and may not outweigh the increased cost and complexity of incorporating it into routine diagnostic testing for these disorders.

RASopathies include a group of syndromes caused by pathogenic germline variants in RAS-MAPK pathway genes and typically present with facial dysmorphology, cardiovascular disease, and musculoskeletal anomalies. Recently, variants in RASopathy-associated genes have been reported in individuals with apparently nonsyndromic cardiomyopathy, suggesting that subtle features may be overlooked. To determine the utility and burden of adding RASopathy-associated genes to cardiomyopathy panels, we tested 11 RASopathy-associated genes by next-generation sequencing (NGS), including NGS-based copy number variant assessment, in 1,111 individuals referred for genetic testing for hypertrophic cardiomyopathy (HCM) or dilated cardiomyopathy (DCM). Disease-causing variants were identified in 0.6% (four of 692) of individuals with HCM, including three missense variants in the PTPN11, SOS1, and BRAF genes. Overall, 36 variants of uncertain significance (VUSs) were identified, averaging ∼3VUSs/100 cases. This study demonstrates that adding a subset of the RASopathy-associated genes to cardiomyopathy panels will increase clinical diagnoses without significantly increasing the number of VUSs/case.

Over the last decade, the field of molecular diagnostics has undergone tremendous transformation, catalyzed by the clinical implementation of next generation sequencing (NGS). As technical capabilities are enhanced and current limitations are addressed, NGS is increasingly capable of detecting most variant types and will therefore continue to consolidate and simplify diagnostic testing. It is likely that genome sequencing will eventually serve as a universal first line test for disorders with a suspected genetic origin. Academic Medical Centers (AMCs), which have been at the forefront of this paradigm shift are now presented with challenges to keep up with increasing technical, bioinformatic and interpretive complexity of NGS-based tests in a highly competitive market. Additional complexity may arise from altered regulatory oversight, also triggered by the unprecedented scope of NGS-based testing, which requires new approaches. However, these challenges are balanced by unique opportunities, particularly at the interface between clinical and research operations, where AMCs can capitalize on access to cutting edge research environments and establish collaborations to facilitate rapid diagnostic innovation. This article reviews present and future challenges and opportunities for AMC associated molecular diagnostic laboratories from the perspective of the Partners HealthCare Laboratory for Molecular Medicine (LMM).

Purpose: To develop and validate VisCap, a software program targeted to clinical laboratories for inference and visualization of germ-line copy-number variants (CNVs) from targeted next-generation sequencing data. Genet Med 18 7, 712–719. Methods: VisCap calculates the fraction of overall sequence coverage assigned to genomic intervals and computes log2 ratios of these values to the median of reference samples profiled using the same test configuration. Candidate CNVs are called when log2 ratios exceed user-defined thresholds. Genet Med 18 7, 712–719. Results: We optimized VisCap using 14 cases with known CNVs, followed by prospective analysis of 1,104 cases referred for diagnostic DNA sequencing. To verify calls in the prospective cohort, we used droplet digital polymerase chain reaction (PCR) to confirm 10/27 candidate CNVs and 72/72 copy-neutral genomic regions scored by VisCap. We also used a genome-wide bead array to confirm the absence of CNV calls across panels applied to 10 cases. To improve specificity, we instituted a visual scoring system that enabled experienced reviewers to differentiate true-positive from false-positive calls with minimal impact on laboratory workflow. Genet Med 18 7, 712–719. Conclusions: VisCap is a sensitive method for inferring CNVs from targeted sequence data from targeted gene panels. Visual scoring of data underlying CNV calls is a critical step to reduce false-positive calls for follow-up testing. Genet Med 18 7, 712–719.