Dr. Merritt is a Research Fellow in Cancer Epidemiology in the Department of Epidemiology and Biostatistics, School of Public Health, Imperial College. She has gained expertise in Epidemiology, Molecular Biology and Bioinformatics. Dr. Merritt completed her doctoral training in Population Health at the Queensland Institute of Medical Research and The University of Queensland in Brisbane, Australia where she was a recipient of an Australian Postgraduate Award.
Dr. Merritt gained experience as a postdoctoral fellow in Molecular Biology at the Brigham and Women's Hospital/ Harvard Medical School, Boston, Massachusetts in the laboratory of Tan Ince where she developed an experimental model to investigate the role of the normal cell of origin in determining ovarian tumor phenotype. She was awarded a postdoctoral fellowship from the Ovarian Cancer Research Foundation and a research grant from the Gynecologic Cancer Foundation for this work. Dr. Merritt trained in the laboratory of John Quackenbush to investigate gene expression signatures of normal ovarian and fallopian tube cell origin and their potential relevance to ovarian cancer. In 2010, she was awarded a Nutritional Epidemiology of Cancer Postdoctoral Fellowship from the Harvard School of Public Health and she carried out research under the mentorship of Daniel Cramer, Kathryn Terry (OB/GYN Epidemiology Center) and Shelley Tworoger (Channing Laboratory) at the Brigham and Women’s Hospital to conduct research focused on dietary and genetic risk factors for ovarian cancer in the New England based case-control study of ovarian cancer and the Nurses' Health Study.
In her current role at Imperial College, Dr. Merritt's research focuses on dietary, reproductive and metabolic risk factors for ovarian and endometrial cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC) under the mentorship of Marc Gunter and Elio Riboli.
et al., 2018, A transcriptome-wide association study among 97,898 women to identify candidate susceptibility genes for epithelial ovarian cancer risk, Cancer Research, Vol:78, ISSN:1538-7445, Pages:5419-5430
et al., 2018, Pre-diagnosis and post-diagnosis use of common analgesics and ovarian cancer prognosis (NHS/NHSII): a cohort study., Lancet Oncol, Vol:19, Pages:1107-1116
et al., 2018, Anti-CA15.3 and anti-CA125 antibodies and ovarian cancer risk: Results from the EPIC cohort, Cancer Epidemiology, Biomarkers and Prevention, Vol:27, ISSN:1055-9965, Pages:790-804
et al., 2018, Meat and haem iron intake in relation to glioma in the European Prospective Investigation into Cancer and Nutrition study, European Journal of Cancer Prevention, Vol:27, ISSN:1473-5709, Pages:379-383
et al., 2018, Tumor-associated autoantibodies as early detection markers for ovarian cancer? A prospective evaluation., International Journal of Cancer, Vol:143, ISSN:0020-7136, Pages:515-526