Challenges and opportunities in genome-wide environmental interaction (GWEI) studies

dc.contributor.authorAschard, Hugues
dc.contributor.authorLutz, Sharon M.
dc.contributor.authorMaus, Bärbel
dc.contributor.authorDuell, Eric J.
dc.contributor.authorFingerlin, Tasha E.
dc.contributor.authorChatterjee, Nilanjan
dc.contributor.authorKraft, Peter
dc.contributor.authorSteen, Kristel Van
dc.date.accessioned2018-09-06T07:16:37Z
dc.date.available2018-09-06T07:16:37Z
dc.date.issued2012-10-01
dc.date.updated2018-07-24T12:53:05Z
dc.description.abstractThe interest in performing gene-environment interaction studies has seen a significant increase with the increase of advanced molecular genetics techniques. Practically, it became possible to investigate the role of environmental factors in disease risk and hence to investigate their role as genetic effect modifiers. The understanding that genetics is important in the uptake and metabolism of toxic substances is an example of how genetic profiles can modify important environmental risk factors to disease. Several rationales exist to set up gene-environment interaction studies and the technical challenges related to these studies-when the number of environmental or genetic risk factors is relatively small-has been described before. In the post-genomic era, it is now possible to study thousands of genes and their interaction with the environment. This brings along a whole range of new challenges and opportunities. Despite a continuing effort in developing efficient methods and optimal bioinformatics infrastructures to deal with the available wealth of data, the challenge remains how to best present and analyze genome-wide environmental interaction (GWEI) studies involving multiple genetic and environmental factors. Since GWEIs are performed at the intersection of statistical genetics, bioinformatics and epidemiology, usually similar problems need to be dealt with as for genome-wide association gene-gene interaction studies. However, additional complexities need to be considered which are typical for large-scale epidemiological studies, but are also related to "joining" two heterogeneous types of data in explaining complex disease trait variation or for prediction purposes.
dc.format.extent35 p.
dc.format.mimetypeapplication/pdf
dc.identifier.pmid22760307
dc.identifier.urihttps://hdl.handle.net/2445/124328
dc.language.isoeng
dc.publisherSpringer
dc.relation.isformatofVersió postprint del document publicat a: https://doi.org/10.1007/s00439-012-1192-0
dc.relation.ispartofHuman Genetics, 2012, vol. 131, num. 10, p. 1591-1613
dc.relation.urihttps://doi.org/10.1007/s00439-012-1192-0
dc.rights(c) Springer-Verlag, 2012
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.sourceArticles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL))
dc.subject.classificationHerència i medi
dc.subject.classificationGenètica molecular
dc.subject.otherNature and nurture
dc.subject.otherMolecular genetics
dc.titleChallenges and opportunities in genome-wide environmental interaction (GWEI) studies
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/acceptedVersion

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