A comprehensive bioinformatic analysis of 126 patients with an inherited platelet disorder to identify both sequence and copy number genetic variants. Issue 11 (8th October 2020) - Almazni, Ibrahim; Stapley, Rachel J.; Khan, Abdullah O.; Morgan, Neil V.
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. Abstract : We performed a bioinformatic analysis of a cohort of patients with a suspected platelet disorder which has been recruited to the UK‐GAPP (Genotyping and Phenotyping of Platelets) study. Extensive platelet phenotyping and whole‐exome sequencing were performed on 126 patients, resulting in the identification of plausible candidate sequence and structural variants in a known panel of genes. The post‐sequencing analysis used the Congenica interpretation software which allows identification of both single‐nucleotide variations and copy number variations to help to inform patient management.