Daniel Barnes

Daniel Barnes is a Senior Research Associate statistician at the Centre for Cancer Genetic Epidemiology within the Department of Public Health and Primary Care at the University of Cambridge, where he has been working since 2016. He holds Chartered Statistician (CStat) accreditation from the Royal Statistical Society and is actively involved in international research collaborations including CIMBA, BCAC, and OCAC.

• Current Affiliation: Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge
• Previous Positions: Statistician at MRC Epidemiology Unit, Research Associate at Cardiovascular Epidemiology Unit
• Education: BSc and MSc from University of Leicester, PhD from University of Cambridge

Dr. Barnes' research focuses on genetic epidemiology, medical statistics, and statistical genetics, with particular emphasis on understanding modifiers of cancer risk for BRCA1 and BRCA2 pathogenic variant carriers. His work primarily investigates breast, ovarian, and prostate cancer risks using genome-wide association studies and polygenic risk score methodologies. His research has significant implications for personalized cancer risk prediction and prevention strategies for individuals with high-risk genetic mutations.

Analysis of his recent publications shows a consistent focus on genetic modifiers of cancer risk, with particular attention to how polygenic risk scores can refine risk prediction for BRCA1/BRCA2 mutation carriers. His work spans multiple cancer types and has contributed to large-scale international consortia efforts to identify genetic risk factors.

• Chartered Statistician (CStat) accreditation from the Royal Statistical Society
• Multiple high-impact publications in JAMA, Nature Communications, and Journal of the National Cancer Institute

Dr. Barnes' research is supported through collaborative international consortia funding, with primary work conducted through the Centre for Cancer Genetic Epidemiology. His methodology-focused approach to analyzing genetic associations with cancer risk has positioned him as a key contributor to large-scale genetic epidemiology studies. The Centre for Cancer Genetic Epidemiology provides a rich interdisciplinary environment for his work, connecting statistical methodology with clinical applications in cancer prevention.