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Gene-Lifestyle Interactions in Complex Diseases: Design and Description of the GLACIER and VIKING Studies.

Kurbasic, Azra LU ; Poveda, Alaitz LU ; Chen, Yan LU ; Agren, Asa; Engberg, Elisabeth; Hu, Frank B; Johansson, Ingegerd; Barroso, Ines; Brändström, Anders and Hallmans, Göran, et al. (2014) In Current nutrition reports 3(4). p.400-411
Abstract
Most complex diseases have well-established genetic and non-genetic risk factors. In some instances, these risk factors are likely to interact, whereby their joint effects convey a level of risk that is either significantly more or less than the sum of these risks. Characterizing these gene-environment interactions may help elucidate the biology of complex diseases, as well as to guide strategies for their targeted prevention. In most cases, the detection of gene-environment interactions will require sample sizes in excess of those needed to detect the marginal effects of the genetic and environmental risk factors. Although many consortia have been formed, comprising multiple diverse cohorts to detect gene-environment interactions, few... (More)
Most complex diseases have well-established genetic and non-genetic risk factors. In some instances, these risk factors are likely to interact, whereby their joint effects convey a level of risk that is either significantly more or less than the sum of these risks. Characterizing these gene-environment interactions may help elucidate the biology of complex diseases, as well as to guide strategies for their targeted prevention. In most cases, the detection of gene-environment interactions will require sample sizes in excess of those needed to detect the marginal effects of the genetic and environmental risk factors. Although many consortia have been formed, comprising multiple diverse cohorts to detect gene-environment interactions, few robust examples of such interactions have been discovered. This may be because combining data across studies, usually through meta-analysis of summary data from the contributing cohorts, is often a statistically inefficient approach for the detection of gene-environment interactions. Ideally, single, very large and well-genotyped prospective cohorts, with validated measures of environmental risk factor and disease outcomes should be used to study interactions. The presence of strong founder effects within those cohorts might further strengthen the capacity to detect novel genetic effects and gene-environment interactions. Access to accurate genealogical data would also aid in studying the diploid nature of the human genome, such as genomic imprinting (parent-of-origin effects). Here we describe two studies from northern Sweden (the GLACIER and VIKING studies) that fulfill these characteristics. (Less)
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Current nutrition reports
volume
3
issue
4
pages
400 - 411
external identifiers
  • PMID:25396097
ISSN
2161-3311
DOI
10.1007/s13668-014-0100-8
language
English
LU publication?
yes
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6f57b2ac-451e-40e6-94e5-ea721c8a652b (old id 4816693)
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http://www.ncbi.nlm.nih.gov/pubmed/25396097?dopt=Abstract
date added to LUP
2014-12-02 17:22:33
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@misc{6f57b2ac-451e-40e6-94e5-ea721c8a652b,
  abstract     = {Most complex diseases have well-established genetic and non-genetic risk factors. In some instances, these risk factors are likely to interact, whereby their joint effects convey a level of risk that is either significantly more or less than the sum of these risks. Characterizing these gene-environment interactions may help elucidate the biology of complex diseases, as well as to guide strategies for their targeted prevention. In most cases, the detection of gene-environment interactions will require sample sizes in excess of those needed to detect the marginal effects of the genetic and environmental risk factors. Although many consortia have been formed, comprising multiple diverse cohorts to detect gene-environment interactions, few robust examples of such interactions have been discovered. This may be because combining data across studies, usually through meta-analysis of summary data from the contributing cohorts, is often a statistically inefficient approach for the detection of gene-environment interactions. Ideally, single, very large and well-genotyped prospective cohorts, with validated measures of environmental risk factor and disease outcomes should be used to study interactions. The presence of strong founder effects within those cohorts might further strengthen the capacity to detect novel genetic effects and gene-environment interactions. Access to accurate genealogical data would also aid in studying the diploid nature of the human genome, such as genomic imprinting (parent-of-origin effects). Here we describe two studies from northern Sweden (the GLACIER and VIKING studies) that fulfill these characteristics.},
  author       = {Kurbasic, Azra and Poveda, Alaitz and Chen, Yan and Agren, Asa and Engberg, Elisabeth and Hu, Frank B and Johansson, Ingegerd and Barroso, Ines and Brändström, Anders and Hallmans, Göran and Renström, Frida and Franks, Paul},
  issn         = {2161-3311},
  language     = {eng},
  number       = {4},
  pages        = {400--411},
  series       = {Current nutrition reports},
  title        = {Gene-Lifestyle Interactions in Complex Diseases: Design and Description of the GLACIER and VIKING Studies.},
  url          = {http://dx.doi.org/10.1007/s13668-014-0100-8},
  volume       = {3},
  year         = {2014},
}