The Evolution of a Large Biobank at Mass General Brigham.

The Mass General Brigham Biobank (formerly Partners HealthCare Biobank) is a large repository of biospecimens and data linked to extensive electronic health record data and survey data. Its objective is to support and enable translational research focused on genomic, environmental, biomarker and family history associations with disease phenotypes. The Biobank has enrolled more than 135,000 participants, generated genomic data on more than 65,000 of its participants, distributed approximately 153,000 biospecimens, and served close to 450 institutional studies with biospecimens or data. Although the Biobank has been successful, based on some measures of output, this has required substantial institutional investment. In addition, several challenges are ongoing, including: (1) developing a sustainable cost model that doesn't rely as heavily on institutional funding; (2) integrating Biobank operations into clinical workflows; and (3) building a research resource that is diverse and promotes equity in research. Here, we describe the evolution of the Biobank and highlight key lessons learned that may inform other efforts to build biobanking efforts in health system contexts.

Reanalysis of eMERGE phase III sequence variants in 10,500 participants and infrastructure to support the automated return of knowledge updates.

PURPOSE: The clinical genomics knowledgebase is dynamic with variant classifications changing as newly identified cases, additional population data, and other evidence become available. This is a challenge for the clinical laboratory because of limited resource availability for variant reassessment. METHODS: Throughout the Electronic Medical Records and Genomics phase III program, clinical sites associated with the Mass General Brigham/Broad sequencing center received automated, real-time notifications when reported variants were reclassified. In this study, we summarized the nature of these reclassifications and described the proactive reassessment framework we used for the Electronic Medical Records and Genomics program data set to identify variants most likely to undergo reclassification. RESULTS: Reanalysis of 1855 variants led to the reclassification of 2% (n = 45) of variants, affecting 0.6% (n = 67) of participants. Of these reclassifications, 78% (n = 35) were high-impact changes affecting reportability, with 8 variants downgraded from likely pathogenic/pathogenic to variants of uncertain significance (VUS) and 27 variants upgraded from VUS to likely pathogenic/pathogenic. Most upgraded variants (67%) were initially classified as VUS-Favor Pathogenic, highlighting the benefit of VUS subcategorization. The most common reason for reclassification was new published case data and/or functional evidence. CONCLUSION: Our results highlight the importance of periodic sequence variant reevaluation and the need for automated approaches to advance routine implementation of variant reevaluations in clinical practice.

Randomized prospective evaluation of genome sequencing versus standard-of-care as a first molecular diagnostic test.

PURPOSE: To evaluate the diagnostic yield and clinical relevance of clinical genome sequencing (cGS) as a first genetic test for patients with suspected monogenic disorders. METHODS: We conducted a prospective randomized study with pediatric and adult patients recruited from genetics clinics at Massachusetts General Hospital who were undergoing planned genetic testing. Participants were randomized into two groups: standard-of-care genetic testing (SOC) only or SOC and cGS. RESULTS: Two hundred four participants were enrolled, 202 were randomized to one of the intervention arms, and 99 received cGS. In total, cGS returned 16 molecular diagnoses that fully or partially explained the indication for testing in 16 individuals (16.2% of the cohort, 95% confidence interval [CI] 8.9-23.4%), which was not significantly different from SOC (18.2%, 95% CI 10.6-25.8%, P = 0.71). An additional eight molecular diagnoses reported by cGS had uncertain relevance to the participant's phenotype. Nevertheless, referring providers considered 20/24 total cGS molecular diagnoses (83%) to be explanatory for clinical features or worthy of additional workup. CONCLUSION: cGS is technically suitable as a first genetic test. In our cohort, diagnostic yield was not significantly different from SOC. Further studies addressing other variant types and implementation challenges are needed to support feasibility and utility of broad-scale cGS adoption.

Remote Fingerstick Blood Collection for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Antibody Testing.

The rapid worldwide spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has propelled the rapid development of serologic tests that can detect anti-SARS-CoV-2 antibodies. These have been used for studying the prevalence and spread of infection in different populations, and helping establish a recent diagnosis of coronavirus disease 2019 (COVID-19), and will likely be used to confirm humoral immunity after infection or vaccination. However, nearly all lab-based high-throughput SARS-CoV-2 serologic assays require a serum sample from venous blood draw, limiting their applications and scalability. Here, we present a method that enables large-scale SARS-CoV-2 serologic studies by combining self or office collection of fingerprick blood with a volumetric absorptive microsampling device (Mitra, Neoteryx LLC) with a high-throughput electrochemiluminescence-based SARS-CoV-2 total antibody assay (Roche Elecsys, Roche Diagnostics Inc) that is emergency use authorization approved for use on serum samples and widely used by clinical laboratories around the world. We found that the Roche Elecsys assay has a high dynamic range that allows for accurate detection of SARS-CoV-2 antibodies in serum samples diluted 1:20 as well as contrived dried blood extracts. Extracts of dried blood from Mitra devices acquired in a community seroprevalence study showed near identical sensitivity and specificity in detection of SARS-CoV-2 antibodies compared with neat sera using predefined thresholds for each specimen type. Overall, this study affirms the use of Mitra dried blood collection device with the Roche Elecsys SARS-CoV-2 total antibody assay for remote or at-home testing as well as large-scale community seroprevalence studies.

Next generation sequencing-based copy number analysis reveals low prevalence of deletions and duplications in 46 genes associated with genetic cardiomyopathies.

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.

VisCap: inference and visualization of germ-line copy-number variants from targeted clinical sequencing data.

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. 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. 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. 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.Genetics in Medicine (2016); 18 7, 712-719. doi:10.1038/gim.2015.156.

The landscape of genetic variation in dilated cardiomyopathy as surveyed by clinical DNA sequencing.

PURPOSE: Dilated cardiomyopathy is characterized by substantial locus, allelic, and clinical heterogeneity that necessitates testing of many genes across clinically overlapping diseases. Few studies have sequenced sufficient individuals; thus, the contributions of individual genes and the pathogenic variant spectrum are still poorly defined. We analyzed 766 dilated cardiomyopathy patients tested over 5 years in our molecular diagnostics laboratory. METHODS: Patients were tested using gene panels of increasing size from 5 to 46 genes, including 121 cases tested with a multiple-cardiomyopathy next-generation panel covering 46 genes. All variants were reassessed using our current clinical-grade scoring system to eliminate false-positive disease associations that afflict many older analyses. RESULTS: Up to 37% of dilated cardiomyopathy cases carry a clinically relevant variant in one of 20 genes, titin (TTN) being the largest contributor (up to 14%). Desmoplakin (DSP), an arrhythmogenic right ventricular cardiomyopathy gene, contributed 2.4%, illustrating the utility of multidisease testing. The clinical sensitivity increased from 10 to 37% as gene panel sizes increased. However, the number of inconclusive cases also increased from 4.6 to 51%. CONCLUSION: Our data illustrate the utility of broad gene panels for genetically and clinically heterogeneous diseases but also highlight challenges as molecular diagnostics moves toward genome-wide testing.