Using ClinVar as a Resource to Support Variant Interpretation

Harrison, Steven M.; Riggs, Erin Rooney; Maglott, Donna; Lee, Jennifer M.; Azzariti, Danielle R.; Niehaus, Annie; Ramos, Erin M.; Martin, Christa Lese; Landrum, Melissa; Rehm, Heidi L.

doi:10.1002/0471142905.hg0816s89

Cited by 101 publications

(93 citation statements)

References 8 publications

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“…If available, previous publications reporting pathogenicity of the variant should be cited (MacArthur et al 2014). Often this is performed through literature or database searches, using online tools such as MITOMAP (Lott et al 2013) and ClinVar (Harrison et al 2016). If the variant is novel, and prediction programs such as PolyPhen and SIFT are used, the specific versions and tools should be cited because, occasionally, multiple programs may issue conflicting predictions.…”

Section: Exercise Physiologymentioning

confidence: 99%

Common data elements for clinical research in mitochondrial disease: a National Institute for Neurological Disorders and Stroke project

Karaa

Rahman

Lombès

et al. 2017

J of Inher Metab Disea

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ObjectivesThe common data elements (CDE) project was developed by the National Institute of Neurological Disorders and Stroke (NINDS) to provide clinical researchers with tools to improve data quality and allow for harmonization of data collected in different research studies. CDEs have been created for several neurological diseases; the aim of this project was to develop CDEs specifically curated for mitochondrial disease (Mito) to enhance clinical research.MethodsNine working groups (WGs), composed of international mitochondrial disease experts, provided recommendations for Mito clinical research. They initially reviewed existing NINDS CDEs and instruments, and developed new data elements or instruments when needed. Recommendations were organized, internally reviewed by the Mito WGs, and posted online for external public comment for a period of eight weeks. The final version was again reviewed by all WGs and the NINDS CDE team prior to posting for public use.ResultsThe NINDS Mito CDEs and supporting documents are publicly available on the NINDS CDE website (https://commondataelements.ninds.nih.gov/), organized into domain categories such as Participant/Subject Characteristics, Assessments, and Examinations.ConclusionWe developed a comprehensive set of CDE recommendations, data definitions, case report forms (CRFs), and guidelines for use in Mito clinical research. The widespread use of CDEs is intended to enhance Mito clinical research endeavors, including natural history studies, clinical trial design, and data sharing. Ongoing international collaboration will facilitate regular review, updates and online publication of Mito CDEs, and support improved consistency of data collection and reporting.

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Section: Exercise Physiologymentioning

confidence: 99%

Common data elements for clinical research in mitochondrial disease: a National Institute for Neurological Disorders and Stroke project

Karaa

Rahman

Lombès

et al. 2017

J of Inher Metab Disea

View full text Add to dashboard Cite

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“…Decision support tools enable more flexible, interactive analyses and generally provide easier means to analyse variant data in the context of external resources such as ExAC, OMIM and ClinVar, which greatly empower clinical decision-making. Academic examples include iobio 14 and Variation Viewer 105 . Commercial tools increasingly have an important role in this domain, partly because of the complexity and cost of developing such software.…”

Section: Current Challenges and Emerging Solutionsmentioning

confidence: 99%

Settling the score: variant prioritization and Mendelian disease

2017

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When investigating Mendelian disease using exome or genome sequencing, distinguishing disease-causing genetic variants from the multitude of candidate variants is a complex, multidimensional task. Many prioritization tools and online interpretation resources exist, and professional organizations have offered clinical guidelines for review and return of prioritization results. In this Review, we describe the strengths and weaknesses of widely used computational approaches, explain their roles in the diagnostic and discovery process and discuss how they can inform (and misinform) expert reviewers. We place variant prioritization in the wider context of gene prioritization, burden testing and genotype–phenotype association, and we discuss opportunities and challenges introduced by whole-genome sequencing.

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“…In this study, deleteriousness of a mutation or variant was assessed based on sequential decision through several definitive and predictive analyses. Weight was given to the availability of references in deleterious mutation information bases such as HGMD (www.biobase-international.com/hgmd), and ClinVar annotations (19,20). General population frequency estimates of the mutations were referred from ExAC and 1000 genome database (21).…”

Section: Library Preparation Formentioning

confidence: 99%

Targeted Gene Sequencing of Gallbladder Carcinoma Identifies High-impact Somatic and Rare Germline Mutations

Yadav

Sarkar

Kumari

et al. 2017

CGP

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Abstract. Background: Gallbladder carcinoma (GBC) isGallbladder carcinoma (GBC) is a type of biliary tract cancer, characterized by rapid progression and high mortality. Significant risk factors for GBC include presence of gallstones, chronic inflammation, anomalous pancreatobiliary ductal junctions, advancing age and female gender (1).Incidence and prevalence of GBC exhibit remarkable ethnic and geographical variability. This variability has been attributed to genetic predisposition and lifestyle habits or environmental exposure. The high incidence of GBC in the Indo-Gangetic belt and its poorly characterized molecular pathology have resulted in its reputation as an enigmatic Indian carcinoma (2). Until 2010, the genomic studies of GBC were limited to scanning a few common mutations in wellknown cancer-associated genes such as tumor protein p53 (TP53) and KRAS proto-oncogene, GTPase (KRAS) (3-5). Advancements in massively parallel sequencing technology, or next-generation sequencing (NGS), have propelled the area of cancer genomics and have greatly improved the understanding of tumorigenesis and tumor evolution linked with disease progression (6, 7). Application of NGS provides a means of high-throughput identification of cancer drivers and other genes that may be clinically relevant and or actionable for precision medicine (6). During the past decade, several large-scale cancer mutational landscape studies have contributed to the understanding of the existence of clonal variability within and across tumors in various common cancer types (8). However, GBC remains one of the understudied cancer types, with only a few studies on a limited number of samples (9-11). These studies and previous candidate gene-sequencing investigations indicate that GBC tumors from patients from different geographic regions may have different genetic architectures, suggesting the need for mutation exploration using a high-throughput NGS approach from varied populations (5, 12).The current treatment for patients with GBC is operative resection. However, resection is limited to cases that present at an early stage. GBCs which have progressed are largely incurable and the treatment mostly relies on focal radiation therapy and/or generic chemotherapy (12). The overall survival rate for patients with advanced GBC (stage 3 and 4) is very poor, and fewer than 10% survive for 5 years post 495 This article is freely accessible online.

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Using ClinVar as a Resource to Support Variant Interpretation

Cited by 101 publications

References 8 publications

Common data elements for clinical research in mitochondrial disease: a National Institute for Neurological Disorders and Stroke project

Common data elements for clinical research in mitochondrial disease: a National Institute for Neurological Disorders and Stroke project

Settling the score: variant prioritization and Mendelian disease

Targeted Gene Sequencing of Gallbladder Carcinoma Identifies High-impact Somatic and Rare Germline Mutations

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