| Literature DB >> 33006441 |
Joseph H Oved1,2,3, Michele P Lambert1,3, M Anna Kowalska1, Mortimer Poncz1,3, Konrad J Karczewski4,5.
Abstract
Essentials The frequency of predicted loss-of-function (pLoF) variants in platelet-associated genes is unknown in the general population. Datasets like Genome Aggregation Database allow us to analyze pLoF variants with increased resolution. Expected prevalence of significant pLoF variants in platelet-associated genes in 0.329% in the general population. Platelet-associated genes that cause phenotypes due to haploinsufficiency are significantly depleted for deleterious variation. ABSTRACT: Background Inherited platelet disorders are being recognized more frequently as advanced sequencing technologies become more commonplace in clinical scenarios. The prevalence of each inherited platelet disorder and the disorders in aggregate are not known. This deficit in the field makes it difficult for clinicians to discuss results of sequencing assays and provide appropriate anticipatory guidance. Objectives In this study, we aim to calculate the prevalence of predicted loss-of-function variants in platelet-associated genes in the general population. Methods Here, we leverage the aggregation of exomes from the general population in the form of Genome Aggregation Database to assess 58 platelet-associated genes with phenotypic correlates. We use the loss-of-function transcript effect estimator (LOFTEE) to identify predicted loss-of-function mutations in these platelet-associated genes. These variants are curated and we then quantify the frequency of predicted loss-of-function variants in each gene. Results Our data show that 0.329% of the general population have a clinically meaningful predicted loss-of-function variant in a platelet-associated gene. Thus, these individuals are at risk for bleeding disorders that can range from mild to severe. Conclusions These data provide a novel lens through which clinicians can analyze sequencing results in their patients as well as an additional method to curate newly discovered platelet-associated genes in the future.Entities:
Keywords: bioinformatics; bleeding disorders; genomics; platelets; variant prediction
Mesh:
Year: 2020 PMID: 33006441 DOI: 10.1111/jth.15113
Source DB: PubMed Journal: J Thromb Haemost ISSN: 1538-7836 Impact factor: 5.824