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Explaining behavior change after genetic testing: the problem of collinearity between test and risk estimates

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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  • Thomas Fanshawe
  • Toby Prevost
  • Scott Roberts
  • Robert Green
  • David Armstrong
  • Theresa Marteau
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<mark>Journal publication date</mark>09/2008
<mark>Journal</mark>Genetic Testing
Issue number3
Volume12
Number of pages6
Pages (from-to)381-386
Publication StatusPublished
<mark>Original language</mark>English

Abstract

This paper explores whether and how the behavioral impact of genotype disclosure can be disentangled from the impact of numerical risk estimates generated by genetic tests. Secondary data analyses are presented from a randomized controlled trial of 162 first-degree relatives of Alzheimer's disease (AD) patients. Each participant received a lifetime risk estimate of AD. Control group estimates were based on age, gender, family history, and assumed ε4-negative apolipoprotein E (APOE) genotype; intervention group estimates were based upon the first three variables plus true APOE genotype, which was also disclosed. AD-specific self-reported behavior change (diet, exercise, and medication use) was assessed at 12 months. Behavior change was significantly more likely with increasing risk estimates, and also more likely, but not significantly so, in ε4-positive intervention group participants (53% changed behavior) than in control group participants (31%). Intervention group participants receiving ε4-negative genotype feedback (24% changed behavior) and control group participants had similar rates of behavior change and risk estimates, the latter allowing assessment of the independent effects of genotype disclosure. However, collinearity between risk estimates and ε4-positive genotypes, which engender high-risk estimates, prevented assessment of the independent effect of the disclosure of an ε4 genotype. Novel study designs are proposed to determine whether genotype disclosure has an impact upon behavior beyond that of numerical risk estimates.