Profile
Biography
James is a PhD student within the
Epidemiology and Cancer Statistics Group (ECSG), studying how the genetics of haematological malignancies can be used to improve the patient pathway. Currently he is trying to use gene expression data and machine learning to provide faster and more accurate diagnoses of aggressive lymphoma subtypes. His interest in this topic of 'precision medicine' came from his Masters degree where he used genetics to stratify groups of people and predict the risk of diabetes, and identify rare disease-causing mutations in sequence data.
James' Masters degree project helped create a dataset of over 600,000 patients with diabetes using routinely-collected health data from Clinical Practice Research Datalink (CPRD). He then performed survival analysis on this data to investigate risk factors for COVID-19 mortality in younger people with diabetes. James received a scholarship from
Health Data Research UK for his Masters degree.
Qualifications
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MSc in Health Data Science (Exeter, 2021)
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BSc (Hons) in Mathematics and Economics (York, 2020)
Research interests
- Machine learning
- Precision medicine
- Causal inference
Supervisors
Funding
Cancer Research UK Studentship
Research
Projects
Lymphomas represent a heterogenous group of malignancies in terms of genetics, treatments and outcomes. Understanding the factors behind this heterogeneity can then help define which subgroups of patients will best respond to a given treatment, thereby improving patient outcomes.
One factor behind this is genetics, for example, genes are expressed in varying amounts across patients - this can often determine the subtype of cancer that has manifested in a patient. If subtypes can be better defined, then treatments which target specific genes can be used to increase survival rates.
Currently James is looking at the beginning of the patient pathway, using gene expression data and machine learning to give more accurate diagnoses of rarer (or difficult to diagnose) subtypes. This will better direct clinicans in the workup of a diagnosis, making the diagnosis process more efficient. This work is a collaboration between epidemiologists and data analysts at the
Haematological Malignancies Research Network (HMRN), and clinicians and data scientists at Leeds Hospitals and the
Haematological Malignanciy Diagnostic Service (HMDS).
Research group(s)
Epidemiology & Cancer Statistics Group (ECSG)
Publications
Selected publications
Conference abstracts
1. In people with type 2 diabetes most risk factors for covid-19 mortality are shared with pneumonia, however ethnicity related risk is very different.
Hopkins, R., Godwin, J., Young, K. G., Mateen, B. A., Vollmer, S. J., Thomas, N. J., Shields, B. M., McGovern, A. P. & Dennis, J. M., 28 Mar 2022, In: Diabetic Medicine. 39, S1, A35.
https://doi.org/10.1111/dme.14809
2. Modifiable risk factors including HbA (1c) and BMI are consistently associated with severe influenza, pneumonia, and Covid-19 infection outcomes in people with type 2 diabetes
Hopkins, R., Young, K. G., Godwin, J., Raja, D., Thomas, N. J., Shields, B. M., Dennis, J. M. & McGovern, A. P., 3 Aug 2022, In: DIABETOLOGIA. 65, 235.
https://link.springer.com/article/10.1007/s00125-022-05755-w
Posters
1. Classification of aggressive B-Cell lymphomas using gene expression profiling
Godwin, J., Barrans, S. L., Davies, J., Crouch, S., Painter, D. E., Smith, A. G., Burton, C., Roman, E. & Westhead, D. R., Sep 2022.
Poster session presented at 22nd Meeting of the European Association for Haematopathology, Florence, Italy. james godwin conference poster florence pdf (PDF 
, 944kb)
Articles
1. Risk factor associations for severe COVID-19, influenza and pneumonia in people with diabetes to inform future pandemic preparations: UK population-based cohort study.
Hopkins R, Young KG, Thomas NJ, Godwin J, Raja D, Mantee BA, Challen RJ, Vollmer SJ, Shields BM, McGovern AP, Dennis JM. Risk factor associations for severe COVID-19, influenza and pneumonia in people with diabetes to inform future pandemic preparations: UK population-based cohort study BMJ Open 2024;14:e078135. doi: 10.1136/bmjopen-2023-078135
External activities
Overview
Health Data Research UK Early Careers Forum 2024
Co-organiser - 20 September 2024
Health Data Research UK Conference 2024: The Grand Challenges in Health Data
Participant - 5-6 March 2024
Data-driven cancer research conference 2024 - Cancer Research UK
Participant - 27-28 February 2024
Health Data Research UK Leadership and Strategy Retreat
Presented a paper - 10-11 May 2023 - Edinburgh
Health Data Research UK Scientific Conference 2022: Data for global health and society
Participant - 14 December 2022
Health Data Research UK
Alumni Network Coordinator
September 2022 - December 2024
White Rose Doctoral Training Programme Annual Conference
Participant - 21 Jun 2022
Leeds/York Translational Haematology Research Meeting
Participant - 27 Apr 2022
Health Data Research UK Annual Scientific Conference 2021
Participant - 23 June 2021
Health Data Research UK ‘One Institute’ Conference 2020
Participant - 16 June 2020
UK Health Data Research Alliance Symposium
Participant - 1 December 2020
