title: A processual model for functional analyses of carcinogenesis in the prospective cohort design.
abstract: Traditionally, the prospective design has been chosen for risk factor analyses of lifestyle and cancer using mainly estimation by survival analysis methods. With new technologies, epidemiologists can expand their prospective studies to include functional genomics given either as transcriptomics, mRNA and microRNA, or epigenetics in blood or other biological materials. The novel functional analyses should not be assessed using classical survival analyses since the main goal is not risk estimation, but the analysis of functional genomics as part of the dynamic carcinogenic process over time, i.e., a "processual" approach. In the risk factor model, time to event is analysed as a function of exposure variables known at start of follow-up (fixed covariates) or changing over the follow-up period (time-dependent covariates). In the processual model, transcriptomics or epigenetics is considered as functions of time and exposures. The success of this novel approach depends on the development of new statistical methods with the capacity of describing and analysing the time-dependent curves or trajectories for tens of thousands of genes simultaneously. This approach also focuses on multilevel or integrative analyses introducing novel statistical methods in epidemiology. The processual approach as part of systems epidemiology might represent in a near future an alternative to human in vitro studies using human biological material for understanding the mechanisms and pathways involved in carcinogenesis.
authors.affiliation: Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, 9037 Tromsø, Norway. Electronic address: eiliv.lund@uit.no.
authors.forename: Eiliv
authors.initials: E
authors.lastname: Lund
authors.affiliation: The MIA-Jouy Research Unit, INRA, France. Electronic address: sandra.plancade@jouy.inra.fr.
authors.forename: Sandra
authors.initials: S
authors.lastname: Plancade
authors.affiliation: CNRS, INSMI Stochastics and Biology Group (PSB) LPMA, UPMC, Sorbonne University, France. Electronic address: nuel.gregory@math.cnrs.fr.
authors.forename: Gregory
authors.initials: G
authors.lastname: Nuel
authors.affiliation: Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, 9037 Tromsø, Norway. Electronic address: hege.m.bovelstad@uit.no.
authors.forename: Hege
authors.initials: H
authors.lastname: Bøvelstad
authors.affiliation: Department of Applied Mathematics, MAP5, 45 rue des Saints-Peres, University Paris Descartes, 75006 Paris, France. Electronic address: Jean-Christophe.Thalabard@math-info.univ-paris5.fr.
authors.forename: Jean-Christophe
authors.initials: JC
authors.lastname: Thalabard
mesh_terms: D063646:Carcinogenesis; D002273:Carcinogens; D044127:Epigenesis, Genetic; D055106:Genome-Wide Association Study; D006801:Humans; D008019:Life Style; D008962:Models, Theoretical; D009369:Neoplasms / Q000209:etiology / Q000503:physiopathology*; D064887:Observational Studies as Topic; D011446:Prospective Studies; D012044:Regression Analysis; D012107:Research Design; D012307:Risk Factors; D013997:Time Factors; D059467:Transcriptome
chemical_list: D002273:Carcinogens