Colorectal Cancer Genetics Image Dr Susan Farrington - Reader Research in a Nutshell The overall aim is to target appropriate clinical screening to those people most at risk of developing colorectal cancer, as this has proven efficacy. This can only be done, by better understanding of the risk factors associated with the disease, both at the genetic/heritable level and environmental factors influencing disease and indeed the ways they can interact and modify disease risk. Identification of the pathways involved in tumour initiation and progression using model systems, will help us further our ability to stratify screening by risk. Research Programme Image People Susan FarringtonPrincipal Investigator and ReaderAnna-Maria OchockaResearch FellowVidya RajasekaranResearch FellowVictoria SvintiBioinformaticianMaria TimofeevaStatistician (shared role: Farrington and Dunlop)Marion WalkerLaboratory ManagerStuart ReidResearch TechnicianRuby OsbornPhD studentPeter Vaughan-ShawClinical Research PhD studentPaz Friele (shared role: Farhat Din/Susan Farrington/Malcolm Dunlop/Mark Arends/ Kevin Myant) Susan Farrington - Research Information CollaborationsProfessor Malcolm Dunlop, University of EdinburghProfessor Harry Campbell, University of EdinburghDr Farhat Din, University of EdinburghProfessor Colin Semple, University of EdinburghDr Evropi Theodoratou, University of EdinburghProfessor Mark Arends, University of EdinburghProfessor Martin Taylor, University of EdinburghProfessor Ian Jackson, University of Edinuburgh Dr Carmel Moran, University of Edinburgh Professor Albert Tenesa, University of EdinburghDr Lina Zgaga, University College DublinProfessor Ian Tomlinson, University of OxfordProfessor Richard Houlston, ICRProfessor Maurizio Genuardi via InSiGHT variant Interpretation CommitteePartners and FundersCRUK/Programme/5yrs/£3.3MMRC/Project/3yrs/£1.1MMelville Trust/Project/1yr/£8.1KScientific ThemesColorectal cancer, genetics, environmental, mechanisms of risk, risk stratification, models of risk allelesTechnology ExpertiseGenomics approaches (GWAS, eQTL analysis) This article was published on 2024-09-23