Associate Professor Robin Walters
MA, PhD, PgDip
Robin Walters completed degrees in Natural Sciences (Cambridge) and in Genetics (Liverpool) before working for 17 years on the biophysics, biochemistry and genetics of plant photosynthesis, first in Sheffield and then in Oxford. He then held a post as a Research Fellow at Imperial College London, where his work focussed on investigating the contribution of structural variation in the human genome to disease risk and phenotypic variation, with a particular focus on diabetes and obesity.
He joined the Clinical Trial Service Unit and Epidemiological Studies Unit in June 2012. As Senior Scientist in Statistical Genetics and Genetic Epidemiology for the China Kadoorie Biobank (CKB), he leads the establishment and development of CKB genomics resources, and directs diverse genomics research projects ranging from genome-wide association studies and contributions to large international consortia, to Mendelian randomisation and phenome-wide association studies for drug target prioritisation and assessment.
Current research interests focus using trans-ancestry analyses of multiple biobanks including UK Biobank to investigate the aetiology and genetic architecture of chronic diseases, with particular emphasis on cardiovascular diseases and their risk factors including adiposity, blood pressure, and blood lipids. He is co-lead of the Fine-Mapping and Trans-ancestry Meta-analysis Working Group of the Genetic Investigation of ANthropometric Traits (GIANT) consortium. He is also a member of the Board of Examiners for the MSc in Global Health Science and Epidemiology.
Modeling biological age using blood biomarkers and physical measurements in Chinese adults.
Chen L. et al, (2023), EBioMedicine, 89
Genetically Predicted Differences in Systolic Blood Pressure and Risk of Cardiovascular and Noncardiovascular Diseases: A Mendelian Randomization Study in Chinese Adults.
Clarke R. et al, (2023), Hypertension
Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.
Kanoni S. et al, (2022), Genome Biol, 23
Publisher Correction: Stroke genetics informs drug discovery and risk prediction across ancestries.
Mishra A. et al, (2022), Nature
Multi-ancestry genome-wide association study improves resolution of genes, pathways and pleiotropy for lung function and chronic obstructive pulmonary disease
Pozarickij A. et al, (2022), Nature Genetics