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A comprehensive bioinformatic analysis of 126 patients with an inherited platelet disorder to identify both sequence and copy number genetic variants
Author(s) -
Almazni Ibrahim,
Stapley Rachel J.,
Khan Abdullah O.,
Morgan Neil V.
Publication year - 2020
Publication title -
human mutation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.981
H-Index - 162
eISSN - 1098-1004
pISSN - 1059-7794
DOI - 10.1002/humu.24114
Subject(s) - biology , copy number variation , exome sequencing , platelet disorder , genetics , gene , genetic heterogeneity , genetic variation , exome , clinical significance , blood platelet disorders , genetic testing , platelet , computational biology , bioinformatics , phenotype , immunology , genome , medicine , platelet aggregation
Abstract Inherited bleeding disorders (IBDs) comprise an extremely heterogeneous group of diseases that reflect abnormalities of blood vessels, coagulation proteins, and platelets. Previously the UK‐GAPP study has used whole‐exome sequencing in combination with deep platelet phenotyping to identify pathogenic genetic variants in both known and novel genes in approximately 40% of the patients. To interrogate the remaining “unknown” cohort and improve this detection rate, we employed an IBD‐specific gene panel of 119 genes using the Congenica Clinical Interpretation Platform to detect both single‐nucleotide variants and copy number variants in 126 patients. In total, 135 different heterozygous variants in genes implicated in bleeding disorders were identified. Of which, 22 were classified pathogenic, 26 likely pathogenic, and the remaining were of uncertain significance. There were marked differences in the number of reported variants in individuals between the four patient groups: platelet count (35), platelet function (43), combined platelet count and function (59), and normal count (17). Additionally, we report three novel copy number variations (CNVs) not previously detected. We show that a combined single‐nucleotide variation (SNV)/CNV analysis using the Congenica platform not only improves detection rates for IBDs, suggesting that such an approach can be applied to other genetic disorders where there is a high degree of heterogeneity.