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ClinVar database of global familial hypercholesterolemia-associated DNA variants.

Citation
Iacocca, M. A., et al. “Clinvar Database Of Global Familial Hypercholesterolemia-Associated Dna Variants.”. Human Mutation, pp. 1631-1640.
Center Stanford University
Author Michael A Iacocca, Joana R Chora, Alain Carrié, Tomáš Freiberger, Sarah E Leigh, Joep C Defesche, Lisa Kurtz, Marina T DiStefano, Raul D Santos, Steve E Humphries, Pedro Mata, Cinthia E Jannes, Amanda J Hooper, Katherine A Wilemon, Pascale Benlian, Robert O'Connor, John Garcia, Hannah Wand, Lukáš Tichy, Eric J Sijbrands, Robert A Hegele, Mafalda Bourbon, Joshua W Knowles, ClinGen FH Variant Curation Expert Panel
Keywords ClinVar, Clinical Genome Resource, familial hypercholesterolemia, variant interpretation
Abstract

Accurate and consistent variant classification is imperative for incorporation of rapidly developing sequencing technologies into genomic medicine for improved patient care. An essential requirement for achieving standardized and reliable variant interpretation is data sharing, facilitated by a centralized open-source database. Familial hypercholesterolemia (FH) is an exemplar of the utility of such a resource: it has a high incidence, a favorable prognosis with early intervention and treatment, and cascade screening can be offered to families if a causative variant is identified. ClinVar, an NCBI-funded resource, has become the primary repository for clinically relevant variants in Mendelian disease, including FH. Here, we present the concerted efforts made by the Clinical Genome Resource, through the FH Variant Curation Expert Panel and global FH community, to increase submission of FH-associated variants into ClinVar. Variant-level data was categorized by submitter, variant characteristics, classification method, and available supporting data. To further reform interpretation of FH-associated variants, areas for improvement in variant submissions were identified; these include a need for more detailed submissions and submission of supporting variant-level data, both retrospectively and prospectively. Collaborating to provide thorough, reliable evidence-based variant interpretation will ultimately improve the care of FH patients.

Year of Publication
2018
Journal
Human mutation
Volume
39
Issue
11
Number of Pages
1631-1640
Date Published
12/2018
ISSN Number
1098-1004
DOI
10.1002/humu.23634
Alternate Journal
Hum. Mutat.
PMID
30311388
PMCID
PMC6206854
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