Harnessing human genomic, transcriptomic and proteomic data to identify novel therapeutic targets

Supporting human genetic data for novel therapeutic targets has been shown to double the success rate for subsequent clinical translation. We have used this approach for Dupuytren's disease, a common fibrotic disease of the hand. Multiple genome-wide association studies (GWAS) have shown the importance of Wnt signaling in this disorder. We identified TNF as a therapeutic target using diseased and control human tissue and showed that only myofibroblasts from Dupuytren's patients signalled via the canonical Wnt pathway. We went on to complete successful phase 2 clinical trials, meeting both the primary and a key secondary endpoint in the phase 2b.

This project will focus on discovering novel therapeutic targets for diseases by integrating human multi-omics data with laboratory data based on human tissue, cells, and preclinical models.

We will develop novel statistical methods to harness the wealth of omic-data in multi-ancestry large-scale biobank and consortium data. Through integrative analyses of genetic, transcriptome, proteomic, and clinical data, this approach promises an improved understanding of disease aetiology in a context-specific framework. 

KEYWORDS

OMICs, immune-mediated diseases, biobanks, QTLs

TRAINING OPPORTUNITIES

The successful candidate will benefit from dual supervision by an expert in genomics and computational biology, and a surgeon scientist with a focus on translational medicine. You will be based in the purpose-built labs at The Kennedy Institute of Rheumatology, a world-leading centre in the fields of cytokine biology and inflammation, with a strong emphasis on clinical translation.

This project is ideally suited for students with a background in statistical genetics who wish to expand their applied knowledge in the biological sciences, as well as those with a background in biology or clinical science who are interested in integrating biology with data science.

Comprehensive training will be provided in data science techniques, including statistical data analysis and visualization with R, developing computational pipelines with Python/NextFlow, and utilizing high-performance computing clusters. The student will gain expertise in analyzing advanced sequencing datasets, such as whole genome, RNA, and proteomic sequencing.

The Kennedy Institute offers a vibrant PhD program, featuring a weekly journal club, seminars, student symposia, and regular internal presentations and training sessions. A core curriculum of lectures will provide a solid foundation in diverse subjects, including data analysis, statistical methods, and immunology summer school. In addition to institutional support, the successful applicant will benefit from the University of Oxford's college system. Students will also have the opportunity to collaborate closely with both computational and experimental scientists. 

KEY PUBLICATIONS

Nanchahal J, Ball C, Rombach I, Williams L, Kenealy N, Dakin H, O’Connor H, Davidson D, Werker P, Dutton SJ, Feldmann M, Lamb SE. (2022)

Anti-Tumour Necrosis Factor Therapy for Early Stage Dupuytren’s Disease (RIDD): a phase 2b randomised double blind, placebo-controlled trial.

Lancet Rheumatology. 4(6): e407-16

Luo, Y. et al. A high-resolution HLA reference panel capturing global population diversity enables multi-ethnic fine-mapping in HIV host response. Nature Genetics (2021)

Ishigaki, K., Sakaue, S., Terao, C. Luo, Y. et al. Multi-ancestry genome-wide association analyses identify novel genetic mechanisms in rheumatoid arthritis. Nat Genet 54, 1640–1651 (2022). https://doi.org/10.1038/s41588-022-01213-w

Riesmeijer S, Kamali Z, Ng M, Drichel D, Piersma B, Becker K, Layton T, Nanchahal J, Nothnagel M, Vaez A, Hennies H, Werker P, Furniss D, Nolte I. A genome-wide association meta-analysis implicates Hedgehog and Notch signaling in Dupuytren's disease (2024). Nature Communications 15(1): 199

Verjee LS, Verhoekx J, Chan J, Krausgruber T, Nicolaidou V, Izadi D, Davidson D, Feldmann M, Midwood KS, Nanchahal J (2013). Unraveling the signaling pathways promoting fibrosis in Dupuytren’s disease reveals TNF as a novel therapeutic target.

Proceedings of the National Academy of Sciences, USA. 110: E928-937

THEMES

Genetics and genomics, Translational medicine, Molecular, cell and systems biology, Physiology, cellular and molecular biology

CONTACT INFORMATION OF ALL SUPERVISORS

yang.luo@kennedy.ox.ac.uk

jagdeep.nanchahal@kennedy.ox.ac.uk

The Kennedy Institute is a proud supporter of the Academic Futures scholarship programme, designed to address under-representation and help improve equality, diversity and inclusion in our graduate student body.  The Kennedy and the wider University rely on bringing the very best minds from across the world together, whatever their race, gender, religion or background to create new ideas, insights and innovations to change the world for the better. Up to 50 full awards are available across the three programme streams, and you can find further information on each stream on their individual tabs (Academic futures | Graduate access | University of Oxford).

How to Apply

Please contact the relevant supervisor(s), to register your interest in the project, and the departmental Education Team (graduate.studies@ndorms.ox.ac.uk), who will be able to advise you of the essential requirements for the programme and provide further information on how to make an official application.

Interested applicants should have, or expect to obtain, a first or upper second-class BSc degree or equivalent in a relevant subject and will also need to provide evidence of English language competence (where applicable). The application guide and form is found online and the DPhil or MSc by research will commence in October 2025.

Applications should be made to the following programme using the specified course code.

D.Phil in Molecular and Cellular Medicine (course code: RD_MP1)

For further information, please visit http://www.ox.ac.uk/admissions/graduate/applying-to-oxford.

Interviews to be held week commencing 13^th January 2025.