Skip navigation
Skip navigation

Genes or environment? The difficulties of disentangling these effects in human genetic data analysis

Wilson, Susan

Description

Biostatistical methodology to accommodate genotype by environment (G-E) interactions in planned breeding trials for animals and for plants (such as crop variety trials) is well-advanced. Incorporation of environmental effects into genetic models for human data is generally more problematic. For continuous traits, such as height, IQ, blood pressure and cholesterol level measurements (to name a few), there is a vast literature on approaches that can be traced back over 80 years. However, many of...[Show more]

dc.contributor.authorWilson, Susan
dc.date.accessioned2015-12-13T23:41:31Z
dc.identifier.issn1180-4009
dc.identifier.urihttp://hdl.handle.net/1885/94944
dc.description.abstractBiostatistical methodology to accommodate genotype by environment (G-E) interactions in planned breeding trials for animals and for plants (such as crop variety trials) is well-advanced. Incorporation of environmental effects into genetic models for human data is generally more problematic. For continuous traits, such as height, IQ, blood pressure and cholesterol level measurements (to name a few), there is a vast literature on approaches that can be traced back over 80 years. However, many of the more modern approaches to realistic biostatistical modelling have not penetrated recent analyses of such data. For complex traits, like autoimmune diseases, cancer, cardiovascular disorders, obesity, psychiatric disorders, for example, recent emphasis has been on mapping supposed susceptibility (genetic) loci. Massive enterprises have been undertaken, but the outcomes have been mixed, and usually only applicable for subforms of the disease under study. Nevertheless, there is currently great enthusiasm for undertaking linkage studies for these diseases. Here a brief overview of some of the difficulties in realistically disentangling environmental and genetic effects in models for human genetic data is given.
dc.publisherJohn Wiley & Sons Inc
dc.sourceEnvironmetrics
dc.subjectKeywords: Epidemiology; Gene-environment (G-E) interaction; Gene-environment covariation; Human genome map; Linkage; Mendelian; Monogenic inheritance; Oligogenic inheritance; Polygenic inheritance
dc.titleGenes or environment? The difficulties of disentangling these effects in human genetic data analysis
dc.typeJournal article
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.citationvolume10
dc.date.issued1999
local.identifier.absfor010202 - Biological Mathematics
local.identifier.ariespublicationMigratedxPub24657
local.type.statusPublished Version
local.contributor.affiliationWilson, Susan, College of Physical and Mathematical Sciences, ANU
local.description.embargo2037-12-31
local.bibliographicCitation.issue6
local.bibliographicCitation.startpage685
local.bibliographicCitation.lastpage693
local.identifier.doi10.1002/(SICI)1099-095X(199911/12)10:6<685::AID-ENV384>3.0.CO;2-Q
dc.date.updated2015-12-12T09:32:51Z
local.identifier.scopusID2-s2.0-0032747713
CollectionsANU Research Publications

Download

File Description SizeFormat Image
01_Wilson_Genes_or_environment?_The_1999.pdf104.33 kBAdobe PDF    Request a copy


Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  19 May 2020/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator