United Kingdom

The University of Edinburgh has been rated 18th in the 2019 QS World Rankings of Universities. The University was 4th in the most recent UK national rankings, confirming its position as a place of excellence for research. Helen Colhoun is affiliated to the MRC Institute of Genetics and Molecular Medicine, one of the largest aggregates of human molecular genetics research in the UK. Paul McKeigue is affiliated to the Usher Institute of Population Health Sciences and Informatics, a high-energy, interdisciplinary environment dedicated to improving the health of individuals and populations locally and globally through transformative research, education, knowledge exchange and innovation. The institution has a leading reputation working with electronic health care data and has developed a range of staff training programmes in research data management and planning. Within the frame of the overall Hypo-RESOLVE work programme, Professors Helen Colhoun and Paul McKeigue and their team at the University of Edinburgh will use extensive clinical trial data to build predictive models of hypoglycaemia and predictive models of hypoglycaemia consequences.

Prof. Helen Colhoun

MB BCh BAO, MD, MFMHM FRCP (Ed) is an internationally respected clinical epidemiologist whose research focuses on diabetes and its complications. She holds a prestigious AXA Research Fund personal endowed Chair in Medical Informatics and Epidemiology and is well established as a trialist having led the international guideline changing CARDS trial of atorvastatin in diabetes. She sits on the Steering Committee of various important international trials in diabetes, on which she has provided design and analysis input, including the ongoing REWIND trial (Eli Lilly – dulaglutide CVD endpoint trial), REMOVAL trial (JDRF – metformin in type 1 diabetes recently completed), and the ODYSSEY Phase 3 a programme of Alirocumab funded by Sanofi/ Regeneron. She has extensive experience in complex data analysis in diabetes and co-led the IMI funded SUMMIT programme. She sits on many advisory boards and grant giving bodies and is currently a Chair of the Wellcome Trust Science Interview panel, a member of the Diabetes UK research Committee and the Wellcome Trust Science Strategy panel. She recently led the MRC-funded Farr Scotland pharmacoepidemiology research programme and national databasing programme for drugs. She has recently sat on a Scottish Government Short Life Working group on medical Informatics for national drugs policy. She will oversee all activities being led by Edinburgh e.g. refining the design and analysis plans, overseeing data analysis, reviewing and checking analysis output, lead regular teleconferences with all key persons to discuss the results.

Prof. Paul McKeigue

MB BCh, PhD, FFPHM, FRCP (Ed), Professor of Genetic Epidemiology and Statistical Genetics, has extensive methodological expertise in statistical methods, especially predictive modelling, as well as having a background in diabetes research. He has an international reputation in statistics and machine learning and has worked closely with Colhoun in the analysis of biomarker data in the SUMMIT programme including bringing together genetic and biomarker data. He will supervise the Edinburgh scientific staff contributing to the data analyses and outputs, and take part in regular telecons with PI Colhoun and other collaborators. He will work with Colhoun to design the analysis plans and provide expertise in relation to study design, interpretation of results, and the relevance/application of findings.

Hannah Parkin

Project co-ordinator, will coordinate the agreed consortium activities.

Thomas Caparrotta

Epidemiologist, will liaise with participants in other HypoRESOLVE teams to agree clinical definitions and with the statisticians in specifying analysis plans and drafting reports and publications.

Anita Jeyam

Statistician, will prepare statistical analysis plans, write analysis code and generate data outputs for reports and publications.

Colette Mair

Statistician, will prepare statistical analysis plans, write analysis code and generate data outputs for reports and publications.