Helen Colhoun Research Group
Diabetes Medical Informatics and Epidemiology
Section: Biomedical Genomics (HGU) / Translational Epidemiology (CGEM)
Research in a Nutshell
Our research programme uses large scale population based approaches to further our understanding of the pathogenesis and means of prevention of diabetes complications. A main component of our current work harnesses the increasing availability of e-health record data (EHR) and new technologies for acquiring high dimensional molecular ‘omics data. We quantify contemporaneous absolute risks of complications, evaluate risk factors for complications, and build prediction models using e-health record data. These data are used to inform current health care policy and clinical practice in diabetes. We also use large bioresources linked to these data to quantify the marginal improvement gained by genetics and biomarker panels beyond that achieved by EHR data. Our aim is that these prediction algorithms will then be incorporated into prediction tools for clinical and self-management, and will be useful in clinical trial design. These genetics and biomarker studies also yield important information on the pathogenesis of diabetes complications, that, with more detailed wet-lab research with colleagues in the Institute of Genetics and Cancer, can inform future development of new therapies. Our research programme also encompasses the design and conduct of clinical trials of new drugs and approaches for preventing diabetes complications.
During the COVID-19 global pandemic she has Co-Chaired the COVID-19 Modelling & Research cell at Public Health Scotland.
Follow our work on Twitter: @med_inform
- Principal Investigator: Professor Helen Colhoun Helen.Colhoun@ed.ac.uk
- Administrative group contact: Agnieszka Czechon Agnieszka.Czechon@ed.ac.uk
SDRN Type 1 Bioresource Participants
- Please, get in touch with the following email address: SDRNT1BIO@ed.ac.uk
Projects and collaborations
1. Scottish Diabetes Research Network (SDRN)- Epidemiology Studies
The SDRN-epidemiology group conducts diabetes research using de-identified electronic health care records linked to other datasets. It operates as a subgroup of NRS Scotland diabetes research (https://www.nhsresearchscotland.org.uk/research-areas/diabetes). The group includes clinicians and researchers across Scotland. The Diabetes Informatics and Epidemiology team at University of Edinburgh led by Helen Colhoun curates the data and provides access to authorised users in a secure setting.
Examples of current work of the Diabetes Informatics and Epidemiology team are:
- Pharmacoepidemiology of diabetes drugs - analyses of real world efficacy and safety of drugs used in people with diabetes.
- COVID-19 and diabetes: Includes for example analyses of association of COVID-19 exposure with incident diabetes, impact of past infection on diabetes outcomes, description of extent of epidemic and excess deaths in diabetes.
- Disease prediction from retinal imaging: Analyses of whether predictors learned from retinal imaging are useful in the prediction of risk of other outcomes in diabetes including CVD, kidney disease. Analyses of whether deep learning can be used to improve the autograder used for the screening programme and reduce NHS workload.
- Glycaemia trajectories in type-1 diabetes and association with complications: examining determinants of individual trajectories of glycaemic control across the spectrum of age and diabetes duration and the prospective association of glycaemic control with risk of acute and chronic complications.
- EXCEED - A Pan-European Post-Authorisation Safety Study: Risk Of Pancreatic Cancer Among Type 2 Diabetes Patients Who Initiated Exenatide As Compared With Those Who Initiated Other Non-Glucagon-Like Peptide 1 Receptor Agonists Based Glucose Lowering Drugs.
Read more about EXCEED on the study website:
Publications by the Scottish Diabetes Research Network (SDRN) Epidemiology Group:
2. SDRNT1BIO - The SDRN Type 1 Bioresource
A cohort of people with type 1 diabetes in Scotland who kindly donated biosamples and access to their data for research into the pathogenenesis and prevention of diabetes and its complications. See https://www.ed.ac.uk/mrc-human-genetics-unit/research/colhoun-group/sdrn-type1-bioresource.
Current studies include:
- A UK/Canada Collaboration on the genetics of long-term diabetes complications and their risks factors amongst people with type -1 diabetes. This study aims to understand the genetic basis for variability residual beta-cell function as measured by C-peptide levels, age at diabetes onset and glycaemic control in type 1 diabetes (T1D) and its contribution to diabetes complications in collaboration with colleagues in Canada (PI: Professor Andrew Paterson).
- Harnessing genetic information in the SDRNT1BIO to understand Type 1 diabetes and its complications. This study uses genetic association studies in the SDRNT1BIO to yield insight into the pathways involved in type 1 diabetes and its complications so that new treatments that interfere with these pathways can be designed.
Publications by the SDRN-Epi group (ORCID):
3. Hypo-RESOLVE: Hypoglycaemia – Redefining SOLutions for better liVEs
Hypo-RESOLVE research consortium working together to address the problem of hypoglycaemia in type-1 diabetes patients. Hypoglycaemia, also called low blood sugar, is a condition strongly affects patients with type-1 diabetes, especially if they take insulin. Hypoglycaemia can cause cognitive dysfunction, coma, and cardiac arrhythmia, cardiovascular complications, and death. The aim of this study is to bring multilevel expertise from academic and industry partners to reduce the burden of hypoglycaemia amongst patients with diabetes.
Specific objectives include:
- Create a secure, sustainable database
- Conduct a series of systematic statistical analyses
- Establish most reliable and accurate approach to reporting hypoglycaemia
- Determine psychological burden of hypoglycaemia
- Establish the true economic/quality of life burden of hypoglycaemia
- Progress our understanding of the mechanisms and consequences of hypoglycaemia
- Combine our finding and reclassifications of hypoglycaemia.
Read more about the Hypo-RESOLVE research consortium on the project website:
4. REACT-SCOT: Epidemiology of COVID-19
During the pandemic we worked with Public Health Scotland on the Epidemiology of COVID-19 and created the REACT-SCOT case control study.
REACT-SCOT: Epidemiology of COVID -19 publications:
Partners and Funders
- AXA Research Fund
- Diabetes UK
- EU Commission: Innovative Medicines Initiative
- Medical Research Council
- Novo Nordisk
- Scottish Government
Diabetes, Risk Prediction, Epidemiology, Medical Statistics, ‘Omics, Genetics, Disease Stratification, Covid-19, Machine Learning, Artificial Intelligence
|Helen Colhoun||Leading Professor of the Helen Colhoun Research Group|
Professor of Statistical Genetics, Centre for Population Health Sciences, University of Edinburgh
|Stuart McGurnaghan||Senior Software Developer and Data Analyst|
|Luke Blackbourn||Software and Database Analyst|
|Agnieszka Czechon||Project Manager and Personal Assistant to Professor Helen Colhoun|
Diabetes UK Sir George Alberti Clinical Research Fellow, University of Edinburgh
|Alan Fleming||Biostatistician / Researcher|
Biostatistician / Machine Learning Specialist, based at the Centre for Population Health Sciences, University of Edinburgh
Machine Learning Specialist, based at the Centre for Population Health Sciences, University of Edinburgh
|Ioanna Thoma||PhD Student, Precision Medicine Doctoral Training Programme|
|Andrii Iakoliev||Research Fellow (Informatics / Software Development), based at the Centre for Population Health Sciences, University of Edinburgh|
Chancellor’s Fellow in Data-Driven Innovation at the Usher Institute for Population Health Sciences and Informatics, University of Edinburgh