A recent study from the University of Birmingham has shown that the Congenica platform demonstrated superior performance in identifying the genetic causes of platelet-related bleeding disorders [1].
Whole Exome Sequencing in combination with deep platelet phenotyping has been used in an earlier study (Genotyping and Phenotyping of Platelets, UK-GAPP) to identify pathogenic genetic variants in both known and novel genes in approximately 40% of the patients [2].
Using the Congenica platform, researchers from the Institute of Cardiovascular Sciences have now interrogated the remaining “unknown” cohort of patients and performed a patient bioinformatic analysis to considerably improve the detection rate of inherited platelet-based bleeding disorders.
"We see this as a significant leap forward in the ability to classify hugely complex disorders with a high degree of heterogeneity within the wider scientific community and the potential for providing concise and definitive diagnosis for patients"
Dr Neil Morgan, Principal investigator, University of Birmingham
Inherited bleeding disorders are very difficult to analyze as they are an extremely heterogeneous group of diseases with abnormalities of blood vessels, coagulation proteins and platelets. They reflect abnormalities in blood vessels, coagulation proteins and platelets and often occur after birth or during childhood.
Clinically, such disorders cause variable bleeding tendencies. Most of the inherited bleeding disorders are mainly associated with coagulation factor abnormalities such as haemophilia A and B, while rarer disorders of platelet count and function are still poorly understood.
To investigate the molecular mechanisms of this group of disorders, it is therefore beneficial to start with the genes already implicated in these bleeding disorders in the first instance, and then specifically to investigate how genetic variants can disrupt the gene function.
High-throughput sequencing including Whole Exome Sequencing (WES) and Whole Genome Sequencing (WGS) are valuable tools to uncover new variants in platelet specific genes. Targeted next generation sequencing (NGS) panels can additionally be used to highlight genes that have been previously implicated in bleeding disorders.
However, many of these panels do not search for Copy Number Variations (CNVs). Researchers have not found definitively causative variants in approximately 40-50% patients despite a strongly indicative inherited component for their bleeding. To address this, the Congenica platform was used, which detects both Single Nucleotide Variations (SNVs) and CNVs.
This new study shows Congenica’s utility in interrogating a large cohort of patients recruited to the UK-GAPP research study. The researchers employed an Inherited Bleeding Disorder specific gene panel of 119 genes to detect both single nucleotide variants and copy number variants. This led to the identification of a total of 135 different heterozygous variants in genes that are implicated in bleeding disorders, 22 of which were classified pathogenic and 26 likely pathogenic.
In comparison with other bioinformatics platforms, Congenica showed a superior performance. 25 variants were identified by Congenica as well as other bioinformatic tools and most of them were either pathogenic or likely pathogenic. A further 24 variants were classified as pathogenic or likely pathogenic by the Congenica bioinformatics platform only [1]. These findings showed that Congenica is more robust and reliable tool to analyze WES compared to other bioinformatic tools as it provides a higher variant detection rate. Congenica also comes with the added benefit of detecting CNVs, which is a highly difficult process and valuable in identifying rare causative variants in heterogeneous diseases.
Principal investigator for the study, Dr Neil Morgan of University of Birmingham, concluded: “Congenica's highly sensitive software can be used for detecting SNVs and CNVs in whole exome sequencing data. We see this as a significant leap forward in the ability to classify hugely complex disorders with a high degree of heterogeneity within the wider scientific community and the potential for providing concise and definitive diagnosis for patients.”
Learn how Congenica’s genomic data analysis software enabled bioinformatic analysis that surpassed all others
[1] Almazni I, Stapley R, Khan AO, Morgan NV. A comprehensive bioinformatic analysis of 126 patients with an inherited platelet disorder to identify both sequence and copy number genetic variants. Article accepted for publication and undergone full peer review; https://onlinelibrary.wiley.com/doi/epdf/10.1002/humu.24114 doi: 10.1002/humu.24114
[2] The UK Genotyping and Phenotyping of Platelets study (UK-GAPP) (https://www.birmingham.ac.uk/research/cardiovascularsciences/research/platelet-group/platelet-gapp/index.aspx)