Miss Charli Stoneman
Postgraduate Research Student
RILD Building Level 3
University of Exeter Medical School, RILD Building, RD&E Hospital Wonford, Barrack Road, Exeter, EX2 5DW, UK
Office hours: Monday - Friday: 8.30am - 17.00pm
Monday - Friday: 8.30am - 17.00pm
Charli graduated with a First-Class Batchelor’s degree in Biochemistry from the University of Cardiff, before studying for an MSc in Genomic Medicine at the University of Exeter, Medical School.
She has joined Professor Tim Frayling’s team as a MRC CASE PhD student at the University of Exeter Medical School on a research project to determine the role of common genetic variants for predicting the modulation of cardiovascular outcome. Her industrial sponsors are GSK, the pharmaceutical company. Charli has a keen interest in genomics and chronic diseases with a particular focus on diabetes and cardiovascular diseases.
During her project, Charli aims to undertake a wide-range of statistical genetic techniques, from genome-wide association studies and meta-analysis to Mendelian Randomisation, using large-scale genotypic and phenotypic data from resources including UKBiobank (N=500,000), Exeter10000 (N=7,200) and PREVEND (N=2500). She will also be working closely with GSK to derive measures of adverse cardiac events using electronic medical records. The hopes of the project are to use human genetic variants to help inform the drug discovery pipeline. The identification of key genetics variants and causal associations will provide evidence that increasing or decreasing certain protein levels through particular drugs can alter the risk of adverse cardiovascular diseases.
2016 - 2017: 2.1 in an MSc in Genomic Medicine at University of Exeter
2012 - 2015: 1st class Hons BSc in Biochemistry at the University of Cardiff. Charli obtained 2 academic prizes in her final year for being the top student studying Biochemistry or Biology and for achieving the top marks in the Protein folding and structure module. She also achieved Merit awards during her 1st and 2nd year for outstanding achievements.
Charli's main research interests lie in human genetics and complex diseases which have been further consolidated during relevant modules during her undergraduate degree and Master's. She also has a key interest in drug discovery and patient care/impact where she likes to see research being translated into medical care and make a real difference to patient treatment. Despite coming from a wet-lab undergraduate project background, Charli thrived during her Master's in the Bioinformatics module and also undertook a computer-based research project based on RNA-sequencing to further enhance her skill-set. This further consolidated her interest in statistical techniques, bioinfomatics, programming and computer-based research and hence her interest in carrying out her PhD project.
PhD project: Using human genetics to inform the drug discovery pipeline
This research focuses on identifying genetic variants that influence circulating factors, like erythropoietin (EPO) and pro-adrenomedullin (Pro-ADM), which are altered in chronic kidney disease (CKD) and adverse cardiac outcomes. These variants will then be used as instruments to carry out Mendelian Randomisation to test the causal relationship between higher levels of circulating EPO, pro-ADM and haemoglobin and adverse cardiac outcomes. Data will be obtained from the UK Biobank alongside the InCHIANTI, PREVEND and HealthABC studies.
Supervisor: Prof Tim Frayling, University of Exeter Medical School, Dr Dawn Waterworth, GSK, Dr Vickas Patel, GSK.
Funding: Medical Research Council
Meta-analysis of genome-wide association studies for body fat distribution in 694,649 individuals of European ancestry
We performed a genome-wide association study meta-analysis of body fat distribution, measured by waist-to-hip ratio adjusted for BMI (WHRadjBMI), and identified 463 signals in 346 loci. Heritability and variant effects were generally stronger in women than men, and the 5% of individuals carrying the most WHRadjBMI-increasing alleles were ~1.62 times more likely than the bottom 5% to have a WHR above the thresholds used for metabolic syndrome. These data, made publicly available, will inform the biology of body fat distribution and its relationship with disease.