Dr Stefan Gräf
Principal Research Associate / Principal Investigator
Email: sg550@cam.ac.uk
X (Twitter): @StGraef
LinkedIn: https://www.linkedin.com/in/stefan-graef
Biography:
Stefan is a computational biologist with a background in biophysics and molecular biology particularly interested in analysing population-scale data sets to pave the way for personalised genomic in vascular medicine. Early on in his postdoctoral scientific career he contributed to major national and international collaborative efforts (Ensembl, Encode, BioSapiens) in the field of genomics while working as a scientific programmer at the EMBL - European Bioinformatics Institute. Stefan then decided to shift his focus towards medical research by taking advantage of the gained expertise in managing big data sets with the aim to translate results into the clinic. Initially, he contributed to the seminal molecular reclassification of more than 2,000 breast cancer samples (METABRIC). In 2012 Stefan moved on to establish his own research group in the cardiorespiratory field, investigating the genetic causes of rare diseases like pulmonary hypertension (PH, high blood pressure in the lungs) or cerebral small vessel disease (CSVD, rare strokes), both conditions that are characterised by the dysregulation of the underlying molecular networks of the vascular bed. This work helped streamlining the genetic diagnosis in the national healthcare system and uncovering missing genetic heritability.
Research approaches:
computational genomics, genomic medicine, bioinformatics, machine learning, artificial intelligence, genotype-phenotype association studies
Current projects:
Stefan's research group focuses on the characterisation of the underlying molecular networks of small vessels (microcirculation) in health and disease like high blood pressure in the lungs (pulmonary hypertension (PH)) or small vessel strokes (cerebral small vessel disease (CSVD)) through computational integration of population-scale genetic, multi-omic, imaging, phenotype and other health records and real-world data. Deepening our understanding of the causes of incomplete penetrance, variable expressivity and sex- and gender-related health disparities holds the potential to advance personalised vascular genomic medicine. Current research comprises:
- Sex-aware integration of population-scale genetic, multi-omic and health data to identify the biological, environmental and social factors leading to differences in vascular health and disease outcomes.
- Deep learning of regulatory elements to advance clinical genetic interpretation of variation in the non-coding regions of the genome.
- Identification of the molecular networks associated with the adaptation of the right heart to elevated pressure in the lung through the integration of population-scale genetic and imaging data.
- Implementation of secure data science infrastructure solutions to support the necessary logistics of these large-scale projects as well as the development of new computational approaches to process and analyse the high-dimensional data generated by high-throughput screens, i.e. exploring big data solutions using the Hadoop framework.
Selected Publications
2. Austin ED, …, Gräf S, …, Chung WK. Genetics and precision genomics approaches to pulmonary hypertension. Eur Respir J. 2024 Oct;64(4). doi: 10.1183/13993003.01370-2024. Print 2024 Oct. Review. PubMed PMID: 39209481; PubMed Central PMCID: PMC11525347. [PubMed]
3. Swietlik EM, Greene D, Zhu N, Megy K, Cogliano M, …, Gräf S. Bayesian Inference Associates Rare Variants with Specific Phenotypes in Pulmonary Arterial Hypertension. Circ Genom Precis Med. 2020. doi:10.1161/CIRCGEN.120.003155. [PubMed]
4. Turro E, Astle WJ, Megy K, Gräf S, et al. Whole-genome sequencing of patients with rare diseases in a national health system. Nature. 2020;583: 96–102. doi:10.1038/s41586-020-2434-2. [PubMed]
5. Gräf S, Haimel M, Bleda M, Hadinnapola C, Southgate L, Li W, et al. Identification of rare sequence variation underlying heritable pulmonary arterial hypertension. Nat Commun. 2018;9: 1416. doi:10.1038/s41467-018-03672-4. [PubMed]
Research collaboratorations:
International Consortium for Genetic Studies in PAH (PAH-ICON)
BHF UK National Cohort Study for idiopathic and heritable PAH
NIHR BioResource for Translational Research – Rare Diseases
BHF Cardiovascular Centre of Research Excellence
NIHR Cambridge Biomedical Research Centre
University of Cambridge Research Computing Services
