TY - JOUR T1 - 162 Combinatorial analysis of exome sequencing data and copy number variants in congenital heart disease patients JF - Heart JO - Heart SP - A115 LP - A117 DO - 10.1136/heartjnl-2017-311726.161 VL - 103 IS - Suppl 5 AU - Elisavet Fotiou AU - Simon Williams AU - Bernard Keavney Y1 - 2017/06/01 UR - http://heart.bmj.com/content/103/Suppl_5/A115.3.abstract N2 - Congenital heart disease (CHD) is the most common type of birth defect in humans. Most cases of CHD are sporadic with the specific interactions between genetic variants and environmental factors involved in their pathogenesis uncharacterised. Various whole exome sequencing studies have identified de novo mutations in different genes; however they have only explained a small percentage of CHD cases.Previous work from the group and others has identified chromosomal regions where rare copy number variants (CNVs) were significantly enriched in CHD cases compared to controls. We hypothesise that utilising available CNV data to prioritise candidate regions within which we will interrogate exome sequencing data in CHD cases will be a productive means of identifying causative genes. In this study we have undertaken various refinement steps to narrow down potentially causative candidate gene/s within deleted (DEL) and duplicated (DUP) CNV regions that have been previously shown to be highly associated with non-syndromic CHD patients. Firstly, we have generated case DEL and DUP CNV lists. This was done by updating a published meta-analysis study (our group have contributed to this study) though utilisation of DECIPHER, ISCA, ECARUCA databases and published studies, using different key terms to identify further non-syndromic CHD patients. We then utilised BedTools to compare these case lists with the corresponding control CNV lists generated by using controls from published literature, DECIPHER, the Database of Genomic Variants and the 1000Genome Phase 3 CNVs. The resulting unique cases CNV regions were annotated and compared against an in-house list of candidate genes (containing novel or rare variants) generated from an exome data analysis of 850 Tetralogy of Fallot (ToF) patients. Genes were further prioritised based on whether they have already an assigned human phenotype, on their ExAC CNV scores, probability of haploinsufficiency (pHI) and loss of function (LoF) intolerance scores. Initially, we have identified 10 586 genes for which 1986 genes are present in both DEL and DUP CNV regions, 2772 genes are unique in DUP and 3842 genes unique in DEL regions (Figure 1). Further analysis of genes in DEL regions and genes present in both types of CNVs revealed that 1,150/3,842 genes and 588/1,986 genes respectively have LoF variants in our ToF exome data. Additional filtering with pHI and pLI scores resulted in 57 genes collectively. This is an on-going work and our plan is to design a next-generation sequencing panel to screen our final candidate gene list in an additional 2000 CHD cases. We will focus on the most promising candidate gene emerging from the discovery experiment to perform functional work. Our experimental strategy will vary depending on what is known about the gene, and whether its involved or not in any well-known signalling pathway during heart development such as the Wnt and VEGF pathways.Abstract 162 Figure 1 Flowchart of the initial filtering of CNV regions to genes. ER -