[Show abstract][Hide abstract] ABSTRACT: 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).
[Show abstract][Hide abstract] ABSTRACT: Author Summary A systematic way of recording data use conditions that are based on consent permissions as found in the datasets of the main public genome archives (NCBI dbGaP and EMBL-EBI/CRG EGA).
[Show abstract][Hide abstract] ABSTRACT: Academic medical centers require many interconnected systems to fully support genetic testing processes. We provide an overview of the end-to-end support that has been established surrounding a genetic testing laboratory within our environment, including both laboratory and clinician facing infrastructure. We explain key functions that we have found useful in the supporting systems. We also consider ways that this infrastructure could be enhanced to enable deeper assessment of genetic test results in both the laboratory and clinic.
[Show abstract][Hide abstract] ABSTRACT: 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.
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.
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.
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 advance online publication 17 December 2015Genetics in Medicine (2015); doi:10.1038/gim.2015.156.
Full-text · Article · Dec 2015 · Genetics in medicine: official journal of the American College of Medical Genetics
[Show abstract][Hide abstract] ABSTRACT: Purpose:
With next generation sequencing technology improvement and cost reductions, it has become technically feasible to sequence a large number of genes in one diagnostic test. This is especially relevant for diseases with large genetic and/or phenotypic heterogeneity, such as hearing loss. However, variant interpretation remains the major bottleneck. This is further exacerbated by the lack in the clinical genetics community of consensus criteria for defining the evidence necessary to include genes on targeted disease panels or in genomic reports, and the consequent risk of reporting variants in genes with no relevance to disease.
We describe a systematic evidence-based approach for assessing gene-disease associations and for curating relevant genes for different disease aspects, including mode of inheritance, phenotypic severity, and mutation spectrum.
By applying this approach to clinically available hearing loss gene panels with a total of 163 genes, we show that a significant number (45%) of genes lack sufficient evidence of association with disease and thus are expected to increase uncertainty and patient anxiety, in addition to intensifying the interpretation burden. Information about all curated genes is summarized. Our retrospective analysis of 539 hearing loss cases tested by our previous OtoGenomeV2 panel demonstrates the impact of including genes with weak disease association in laboratory wet-bench and interpretation processes.
Our study is, to our knowledge, the first to highlight the urgent need for defining the clinical validity of gene-disease relationships for more efficient and accurate clinical testing and reporting.Genet Med advance online publication 12 November 2015Genetics in Medicine (2015); doi:10.1038/gim.2015.141.
No preview · Article · Nov 2015 · Genetics in medicine: official journal of the American College of Medical Genetics
[Show abstract][Hide abstract] ABSTRACT: The recent explosion of genetic and clinical data generated from tumor genome analysis presents an unparalleled opportunity to enhance our understanding of cancer, but this opportunity is compromised by the reluctance of many in the scientific community to share datasets and the lack of interoperability between different data platforms. The Global Alliance for Genomics and Health is addressing these barriers and challenges through a cooperative framework that encourages “team science” and responsible data sharing, complemented by the development of a series of application program interfaces that link different data platforms, thus breaking down traditional silos and liberating the data to enable new discoveries and ultimately benefit patients.
[Show abstract][Hide abstract] ABSTRACT: Background:
There are 346 serologically defined red blood cell (RBC) antigens and 33 serologically defined platelet (PLT) antigens, most of which have known genetic changes in 45 RBC or six PLT genes that correlate with antigen expression. Polymorphic sites associated with antigen expression in the primary literature and reference databases are annotated according to nucleotide positions in cDNA. This makes antigen prediction from next-generation sequencing data challenging, since it uses genomic coordinates.
Study design and methods:
The conventional cDNA reference sequences for all known RBC and PLT genes that correlate with antigen expression were aligned to the human reference genome. The alignments allowed conversion of conventional cDNA nucleotide positions to the corresponding genomic coordinates. RBC and PLT antigen prediction was then performed using the human reference genome and whole genome sequencing (WGS) data with serologic confirmation.
Some major differences and alignment issues were found when attempting to convert the conventional cDNA to human reference genome sequences for the following genes: ABO, A4GALT, RHD, RHCE, FUT3, ACKR1 (previously DARC), ACHE, FUT2, CR1, GCNT2, and RHAG. However, it was possible to create usable alignments, which facilitated the prediction of all RBC and PLT antigens with a known molecular basis from WGS data. Traditional serologic typing for 18 RBC antigens were in agreement with the WGS-based antigen predictions, providing proof of principle for this approach.
Detailed mapping of conventional cDNA annotated RBC and PLT alleles can enable accurate prediction of RBC and PLT antigens from whole genomic sequencing data.
[Show abstract][Hide abstract] ABSTRACT: Precision medicine has the potential to profoundly improve the practice of medicine. However, the advances required will take time to implement. Genetics is already being used to direct clinical decision-making and its contribution is likely to increase. To accelerate these advances, fundamental changes are needed in the infrastructure and mechanisms for data collection, storage and sharing. This will create a continuously learning health-care system with seamless cycling between clinical care and research. Patients must be educated about the benefits of sharing data. The building blocks for such a system are already forming and they will accelerate the adoption of precision medicine.
[Show abstract][Hide abstract] ABSTRACT: Pathogenic variants at the DFNB1 locus encompassing the GJB2 and GJB6 genes account for 50% of autosomal recessive, congenital nonsyndromic hearing loss in the United States. Most cases are caused by sequence variants within the GJB2 gene, but a significant number of DFNB1 patients carry a large deletion (GJB6-D13S1830) in trans with a GJB2 variant. This deletion lies upstream of GJB2 and was shown to reduce GJB2 expression by disrupting unidentified regulatory elements. First-tier genetic testing for hearing loss includes GJB2 sequence and GJB6-D13S1830 deletion analysis; however, several other deletions in this locus, each with distinct breakpoints, have been reported in DFNB1 patients and are missed by current panels. Here, we report the development of a targeted droplet digital PCR-based assay for comprehensive copy number analysis at the DFNB1 locus that detects all deletions reported to date. This assay increased detection rates in a multi-ethnic cohort of 87 hearing loss patients with only one identified pathogenic GJB2 variant. We identify two deletions, one of which is novel, in two patients (2/87 or 2.3%), suggesting that other pathogenic deletions at the DFNB1 locus may be missed. Mapping the assayed DFNB1 deletions also revealed a ∼95 Kb critical region, which may harbor the GJB2 regulatory element(s). This article is protected by copyright. All rights reserved.
[Show abstract][Hide abstract] ABSTRACT: There are few better examples of the need for data sharing than in the rare disease community, where patients, physicians, and researchers must search for “the needle in a haystack” to uncover rare, novel causes of disease within the genome. Impeding the pace of discovery has been the existence of many small siloed datasets within individual research or clinical laboratory databases and/and disease-specific organizations, hoping for serendipitous occasions when two distant investigators happen to learn they have a rare phenotype in common and can “match” these cases to build evidence for causality. However, serendipity has never proven to be a reliable or scalable approach in science. As such, the Matchmaker Exchange (MME) was launched to provide a robust and systematic approach to rare disease gene discovery through the creation of a federated network connecting databases of genotypes and rare phenotypes using a common application programming interface (API). The core building blocks of the MME have been defined and assembled. Three MME services have now been connected through the API and are available for community use. Additional databases that support internal matching are anticipated to join the MME network as it continues to grow. This article is protected by copyright. All rights reserved
[Show abstract][Hide abstract] ABSTRACT: As the utility of genetic and genomic testing in healthcare grows, there is need for a high quality genomic knowledge base to improve the clinical interpretation of genomic variants. Active patient engagement can enhance communication between clinicians, patients and researchers, contributing to knowledge building. It also encourages data sharing by patients and increases the data available for clinicians to incorporate into individualized patient care, clinical laboratories to utilize in test interpretation and investigators to use for research. GenomeConnect is a patient portal supported by the Clinical Genome Resource (ClinGen), providing an opportunity for patients to add to the knowledge base by securely sharing their health history and genetic test results. Data can be matched with queries from clinicians, laboratory personnel and researchers to better interpret the results of genetic testing and build a foundation to support genomic medicine. Participation is online, allowing patients to contribute regardless of location. GenomeConnect supports longitudinal, detailed clinical phenotyping and robust "matching" among research and clinical communities. Phenotype data is gathered using online health questionnaires; genotype data is obtained from genetic test reports uploaded by participants and curated by staff. GenomeConnect empowers patients to actively participate in the improvement of genomic test interpretation and clinical utility. This article is protected by copyright. All rights reserved.
This article is protected by copyright. All rights reserved.
[Show abstract][Hide abstract] ABSTRACT: On autopsy, a patient is found to have hypertrophic cardiomyopathy. The patient's family pursues genetic testing that shows a "likely pathogenic" variant for the condition on the basis of a study in an original research publication. Given the dominant inheritance of the condition and the risk of sudden cardiac death, other family members are tested for the genetic variant to determine their risk. Several family members test negative and are told that they are not at risk for hypertrophic cardiomyopathy and sudden cardiac death, and those who test positive are told that they need to be regularly monitored for cardiomyopathy . . .
No preview · Article · May 2015 · New England Journal of Medicine
[Show abstract][Hide abstract] ABSTRACT: Glycosaminoglycans (GAGs) such as chondroitin are ubiquitous disaccharide carbohydrate chains that contribute to the formation and function of proteoglycans at the cell membrane and in the extracellular matrix. Although GAG-modifying enzymes are required for diverse cellular functions, the role of these proteins in human development and disease is less well understood. Here, we describe two sisters out of seven siblings affected by congenital limb malformation and malignant lymphoproliferative disease. Using Whole-Genome Sequencing (WGS), we identified in the proband deletion of a 55 kb region within chromosome 12q23 that encompasses part of CHST11 (encoding chondroitin-4-sulfotransferase 1) and an embedded microRNA (MIR3922). The deletion was homozygous in the proband but not in each of three unaffected siblings. Genotyping data from the 1000 Genomes Project suggest that deletions inclusive of both CHST11 and MIR3922 are rare events. Given that CHST11 deficiency causes severe chondrodysplasia in mice that is similar to human limb malformation, these results underscore the importance of chondroitin modification in normal skeletal development. Our findings also potentially reveal an unexpected role for CHST11 and/or MIR3922 as tumor suppressors whose disruption may contribute to malignant lymphoproliferative disease.