Dr Stefan Gräf

My group's research ambition is to characterise the underlying dysregulated molecular networks of rare vasculopathies like pulmonary arterial hypertension (PAH, high blood pressure in the lungs) through computational integration of genetic and other 'omic data layers. With this, we aim to advance precision genomic medicine.

At the beginning of this century, two independent groups discovered mutations in the bone morphogenetic protein receptor type II (BMPR2) gene, a transforming growth factor beta (TGFß) cell surface receptor that increases the risk of developing pulmonary arterial hypertension (PAH). Since then, additional disease-causing genetic variation has been identified in genes belonging to the TGFß/BMP-signalling pathways (i.e. ACVRL1 (ALK1), ENG, SMAD9) and more recently also in genes not directly associated with these molecular pathways (i.e. CAV1, KCNK3 (TASK1), EIF2AK4 (GCN2)).

The recent focus of my group has been the sequencing of more than a thousand whole genomes of adults and children diagnosed with PAH as part of the NIHR BioResource – a whole-genome sequencing (WGS) project for Rare Diseases. In order to maximise the number of available patients with this rare condition all PAH specialist centres across the UK have formed a national consortium, the National Cohort Study of Idiopathic and Heritable PAH, for patient enrolment, sample collection, and in-depth phenotype capture. To investigate the genotype-phenotype relationship of both the protein-coding and non-coding fraction of the genome, the data integration and genome-wide association is enriched by additional functional multi-omics annotation derived from blood outgrowth endothelial cells (BOECs) in collaboration with the Blueprint Project and other consortium partners.

My group's work also covers the implementation of infrastructure solutions to support the necessary logistics of these large-scale projects as well as the development of new bioinformatics approaches to process and analyse the vast amount of data generated by these high-throughput screens, i.e. exploring big data solutions using the Hadoop framework. On these topics, we are closely collaborating with the University of Cambridge High-Performance Computing Service (HPCS).