Project description:This project aims to study exomes from families and trios with
congenital heart disease (CHD). The samples have been collected under
the Competence Network - Congenital Heart Defects in Berlin, Germany.
The phenotypes are mainly left ventricular outflow obstruction (aortic
stenosis, bicuspd aortic valve disease coarctation and hypoplastic
left heart), but will also include samples with hypoplastic right
heart and atrioventricular septal defects. We will perform whole exome
sequencing using Agilent sequence capture and Illumina HiSeq
sequencing.
Project description:Congenital heart diseases (CHD) are a class of birth defects affecting ~1% of live births. These conditions are hallmarked by extreme genetic heterogeneity, and therefore, despite a strong genetic component, only a very handful of at-risk loci in CHD have been identified. We herein introduced systems analyses to uncover the hidden organization on biological networks of genomic mutations in CHD, and leveraged network analysis techniques to integrate the human interactome, large-scale patient exomes, the fetal heart spatial transcriptomes, and single-cell transcriptomes of clinical samples. We identified a highly connected network in CHD where most of the member proteins had previously uncharacterized functions in regulating fetal heart development. While genes on the network displayed strong enrichment for heart-specific functions, a sub-group, active specifically at early developmental stages, also regulates fetal brain development, thereby providing mechanistic insights into the clinical comorbidities between CHD and neurodevelopmental conditions. At a small scale, we experimentally verified previously uncharacterized cardiac functions of several novel proteins employing cellular assays and gene editing techniques. At a global scale, our study revealed developmental dynamics of the identified CHD network and observed the strongest enrichment for pathogenic mutations in the network specific to hypoplastic left heart syndrome (HLHS). Our single-cell transcriptome analysis further identified pervasive dysregulation of the network in cardiac endothelial cells and the conduction system in the HLHS left ventricle. Taken together, our systems analyses identified novel factors in CHD, revealed key molecular mechanisms in HLHS, and provides a generalizable framework readily applicable to studying many other complex diseases.
Project description:Congenital Heart Disease (CHD) accounts for 1% of birth defects, and while large-scale genetic studies have uncovered genes associated with CHDs, identifying causal mutations remains a challenge. We hypothesized that genetic determinants for CHDs could be found in the protein interactomes of GATA4 and TBX5, two cardiac transcription factors (TFs) associated with CHDs. Defining their interactomes in human cardiac progenitors via affinity purification-mass spectrometry and integrating the results with genetic data from the Pediatric Cardiac Genomic Consortium (PCGC) revealed an enrichment of de novo variants among proteins that interact with GATA4 or TBX5. A consolidative score designed to prioritize TF interactome members based on distinctive variant, gene and proband features identified numerous likely CHD-causing genes, including the epigenetic reader GLYR1. GLYR1 and GATA4 widely co-occupied cardiac developmental genes resulting in co-activation and the GLYR1 variant associated with CHD disrupted interaction with GATA4. This integrative proteomic and genetic approach provides a framework for prioritizing and interrogating the contribution of genetic variants in CHD and can be extended to other genetic diseases.
Project description:Congenital heart disease (CHD) is the most frequent birth defect and affects nearly 1% of newborns. The etiology of CHD is largely unknown and only a small percentage can be assigned to environmental risk factors such as maternal diseases or exposure to mutagenic agents during pregnancy. Chromosomal imbalances have been identified in many forms of syndromic CHD, but next to nothing is known about the impact of DNA copy number changes in non-syndromic CHD. Here we present a sub-megabase resolution array CGH screen of a cohort with CHD as the sole abnormality at the time of diagnosis. Keywords: array CGH In this BAC array CGH study 104 patients with congenital heart disease and some of their parents were screened for DNA copy number changes at submegabase resolution. No dye swap was performed.
Project description:We used Affymetrix CytoScan750K array to detect the pathogenic copy number variations in 7 Chinese children with congenital heart disease