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  • Associate Professor
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  • Clinical Research Nurse
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  • Nursing Staff
  • Permanent Researcher
  • Pharmacist
  • PhD Student
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  • Post-doc
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  • Research Engineer
  • Retired scientist
  • Technician
  • Undergraduate Student
  • Veterinary
  • Visiting Scientist
  • Deputy Director of Center
  • Deputy Director of Department
  • Deputy Director of National Reference Center
  • Deputy Head of Facility
  • Director of Center
  • Director of Department
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© Research
Publication : American journal of human genetics

Inclusion of gene-gene and gene-environment interactions unlikely to dramatically improve risk prediction for complex diseases.

Scientific Fields
Diseases
Organisms
Applications
Technique

Published in American journal of human genetics - 08 Jun 2012

Aschard H, Chen J, Cornelis MC, Chibnik LB, Karlson EW, Kraft P,

Link to Pubmed [PMID] – 22633398

Link to DOI – 10.1016/j.ajhg.2012.04.017

Am J Hum Genet 2012 Jun; 90(6): 962-72

Genome-wide association studies have identified hundreds of common genetic variants associated with the risk of multifactorial diseases. However, their impact on discrimination and risk prediction is limited. It has been suggested that the identification of gene-gene (G-G) and gene-environment (G-E) interactions would improve disease prediction and facilitate prevention. We conducted a simulation study to explore the potential improvement in discrimination if G-G and G-E interactions exist and are known. We used three diseases (breast cancer, type 2 diabetes, and rheumatoid arthritis) as motivating examples. We show that the inclusion of G-G and G-E interaction effects in risk-prediction models is unlikely to dramatically improve the discrimination ability of these models.