Web of Science: 17 cites, Scopus: 16 cites, Google Scholar: cites,
Assessing causal relationships in genomics : from Bradford-Hill criteria to complex gene-environment interactions and directed acyclic graphs
Geneletti, Sara (London School of Economics. Department of Statistics)
Gallo, Valentina (Imperial College. Department of Epidemiology and Public Health (Londres, Regne Unit))
Porta, Miquel, 1957- (Universitat Autònoma de Barcelona. Departament de Pediatria, d'Obstetrícia i Ginecologia i de Medicina Preventiva)
Khoury, Muin J. (National Office of Public Health Genomics (Atlanta, Estats Units d'Amèrica))
Vineis, Paolo (Imperial College. Department of Epidemiology and Public Health (Londres, Regne Unit))

Data: 2011
Resum: Observational studies of human health and disease (basic, clinical and epidemiological) are vulnerable to methodological problems -such as selection bias and confounding- that make causal inferences problematic. Gene-disease associations are no exception, as they are commonly investigated using observational designs. A rich body of knowledge exists in medicine and epidemiology on the assessment of causal relationships involving personal and environmental causes of disease; it includes seminal causal criteria developed by Austin Bradford Hill and more recently applied directed acyclic graphs (DAGs). However, such knowledge has seldom been applied to assess causal relationships in clinical genetics and genomics, even in studies aimed at making inferences relevant for human health. Conversely, incorporating genetic causal knowledge into clinical and epidemiological causal reasoning is still a largely unexplored area. As the contribution of genetics to the understanding of disease aetiology becomes more important, causal assessment of genetic and genomic evidence becomes fundamental. The method we develop in this paper provides a simple and rigorous first step towards this goal. The present paper is an example of integrative research, i. e. , research that integrates knowledge, data, methods, techniques, and reasoning from multiple disciplines, approaches and levels of analysis to generate knowledge that no discipline alone may achieve.
Drets: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original. Creative Commons
Llengua: Anglès
Document: Article ; Versió publicada
Publicat a: Emerging themes in epidemiology, Vol. 8, Núm. 5 (June 2011) , p. 1-18, ISSN 1742-7622

DOI: 10.1186/1742-7622-8-5
PMID: 21658235

18 p, 578.2 KB

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