James Godwin
PhD student

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

MSc in Health Data Science (Exeter, 2021)
BSc (Hons) in Mathematics and Economics (York, 2020)

Research interests

Machine learning
Precision medicine
Causal inference

Supervisors

Prof Alex Smith

Dr Simon Crouch

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 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 - ongoing

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

James Godwin PhD student