Literature DB >> 18666860

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

Thomas R Fanshawe1, A Toby Prevost, J Scott Roberts, Robert C Green, David Armstrong, Theresa M Marteau.   

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 epsilon4-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 epsilon4-positive intervention group participants (53% changed behavior) than in control group participants (31%). Intervention group participants receiving epsilon4-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 epsilon4-positive genotypes, which engender high-risk estimates, prevented assessment of the independent effect of the disclosure of an epsilon4 genotype. Novel study designs are proposed to determine whether genotype disclosure has an impact upon behavior beyond that of numerical risk estimates.

Entities:  

Mesh:

Substances:

Year:  2008        PMID: 18666860      PMCID: PMC2925186          DOI: 10.1089/gte.2007.0103

Source DB:  PubMed          Journal:  Genet Test        ISSN: 1090-6576


  22 in total

1.  A vision for the future of genomics research.

Authors:  Francis S Collins; Eric D Green; Alan E Guttmacher; Mark S Guyer
Journal:  Nature       Date:  2003-04-14       Impact factor: 49.962

Review 2.  Pragmatic versus explanatory trials.

Authors:  K D MacRae
Journal:  Int J Technol Assess Health Care       Date:  1989       Impact factor: 2.188

3.  Will genetic testing for complex diseases increase motivation to quit smoking? Anticipated reactions in a survey of smokers.

Authors:  Saskia C Sanderson; Jane Wardle
Journal:  Health Educ Behav       Date:  2005-10

4.  A written case simulation of osteoarthritis as a predictor of prescribing behavior among family practitioners.

Authors:  W S Holt; S A Mazzuca
Journal:  Acad Med       Date:  1992-06       Impact factor: 6.893

5.  Video-based versus written situational judgment tests: a comparison in terms of predictive validity.

Authors:  Filip Lievens; Paul R Sackett
Journal:  J Appl Psychol       Date:  2006-09

6.  An intervention study of smoking cessation with feedback on genetic cancer susceptibility in Japan.

Authors:  Hidemi Ito; Keitaro Matsuo; Kenji Wakai; Toshiko Saito; Hiroshi Kumimoto; Katashi Okuma; Kazuo Tajima; Nobuyuki Hamajima
Journal:  Prev Med       Date:  2005-12-02       Impact factor: 4.018

7.  Health behavior changes after genetic risk assessment for Alzheimer disease: The REVEAL Study.

Authors:  Serena Chao; J Scott Roberts; Theresa M Marteau; Rebecca Silliman; L Adrienne Cupples; Robert C Green
Journal:  Alzheimer Dis Assoc Disord       Date:  2008 Jan-Mar       Impact factor: 2.703

8.  Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease. A meta-analysis. APOE and Alzheimer Disease Meta Analysis Consortium.

Authors:  L A Farrer; L A Cupples; J L Haines; B Hyman; W A Kukull; R Mayeux; R H Myers; M A Pericak-Vance; N Risch; C M van Duijn
Journal:  JAMA       Date:  1997 Oct 22-29       Impact factor: 56.272

9.  Estimating risks of common complex diseases across genetic and environmental factors: the example of Crohn disease.

Authors:  C M Lewis; S C L Whitwell; A Forbes; J Sanderson; C G Mathew; T M Marteau
Journal:  J Med Genet       Date:  2007-07-27       Impact factor: 6.318

10.  The impact of genetic testing for Crohn's disease, risk magnitude and graphical format on motivation to stop smoking: an experimental analogue study.

Authors:  A J Wright; C Takeichi; S C L Whitwell; M Hankins; T M Marteau
Journal:  Clin Genet       Date:  2008-02-05       Impact factor: 4.438

View more
  10 in total

1.  The prospect of genome-guided preventive medicine: a need and opportunity for genetic counselors.

Authors:  Julianne M O'Daniel
Journal:  J Genet Couns       Date:  2010-05-04       Impact factor: 2.537

2.  Considerations for the impact of personal genome information: a study of genomic profiling among genetics and genomics professionals.

Authors:  Julianne M O'Daniel; Susanne B Haga; Huntington F Willard
Journal:  J Genet Couns       Date:  2010-03-30       Impact factor: 2.537

3.  Clinical implications of APOE genotyping for late-onset Alzheimer's disease (LOAD) risk estimation: a review of the literature.

Authors:  Victoria S Marshe; Ilona Gorbovskaya; Sarah Kanji; Maxine Kish; Daniel J Müller
Journal:  J Neural Transm (Vienna)       Date:  2018-10-31       Impact factor: 3.575

4.  Genetic Sample Provision Among National Alzheimer's Coordinating Center Participants.

Authors:  Shoshana H Bardach; Gregory A Jicha; Shama Karanth; Xuan Zhang; Erin L Abner
Journal:  J Alzheimers Dis       Date:  2019       Impact factor: 4.472

5.  Do we know enough? A scientific and ethical analysis of the basis for genetic-based personalized nutrition.

Authors:  Ulf Görman; John C Mathers; Keith A Grimaldi; Jennie Ahlgren; Karin Nordström
Journal:  Genes Nutr       Date:  2013-03-08       Impact factor: 5.523

6.  Effect of communicating DNA based risk assessments for Crohn's disease on smoking cessation: randomised controlled trial.

Authors:  Gareth J Hollands; Sophia C L Whitwell; Richard A Parker; Natalie J Prescott; Alastair Forbes; Jeremy Sanderson; Christopher G Mathew; Cathryn M Lewis; Sally Watts; Stephen Sutton; David Armstrong; Ann Louise Kinmonth; A Toby Prevost; Theresa M Marteau
Journal:  BMJ       Date:  2012-07-20

7.  The impact of MTHFR 677C → T risk knowledge on changes in folate intake: findings from the Food4Me study.

Authors:  Clare B O'Donovan; Marianne C Walsh; Hannah Forster; Clara Woolhead; Carlos Celis-Morales; Rosalind Fallaize; Anna L Macready; Cyril F M Marsaux; Santiago Navas-Carretero; Rodrigo San-Cristobal; Silvia Kolossa; Christina Mavrogianni; Christina P Lambrinou; George Moschonis; Magdalena Godlewska; Agnieszka Surwillo; Jildau Bouwman; Keith Grimaldi; Iwona Traczyk; Christian A Drevon; Hannelore Daniel; Yannis Manios; J Alfredo Martinez; Wim H M Saris; Julie A Lovegrove; John C Mathers; Michael J Gibney; Lorraine Brennan; Eileen R Gibney
Journal:  Genes Nutr       Date:  2016-09-29       Impact factor: 5.523

Review 8.  Psychological, behavioral and social effects of disclosing Alzheimer's disease biomarkers to research participants: a systematic review.

Authors:  S A S A Bemelmans; K Tromp; E M Bunnik; R J Milne; S Badger; C Brayne; M H Schermer; E Richard
Journal:  Alzheimers Res Ther       Date:  2016-11-10       Impact factor: 6.982

9.  Does personalised nutrition advice based on apolipoprotein E and methylenetetrahydrofolate reductase genotype affect dietary behaviour?

Authors:  Alexandra King; Shaghayegh Saifi; Jenna Smith; Leta Pilic; Catherine A-M Graham; Viviane Da Silva Anastacio; Mark Glaister; Yiannis Mavrommatis
Journal:  Nutr Health       Date:  2021-11-24

Review 10.  The impact of communicating genetic risks of disease on risk-reducing health behaviour: systematic review with meta-analysis.

Authors:  Gareth J Hollands; David P French; Simon J Griffin; A Toby Prevost; Stephen Sutton; Sarah King; Theresa M Marteau
Journal:  BMJ       Date:  2016-03-15
  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.