Literature DB >> 14726808

An epidemiologic assessment of genomic profiling for measuring susceptibility to common diseases and targeting interventions.

Muin J Khoury1, Quanhe Yang, Marta Gwinn, Julian Little, W Dana Flanders.   

Abstract

PURPOSE: The current clinical value of genomic profiling (testing for genotypes at multiple loci) for assessing susceptibility to common diseases and targeting behavioral and medical interventions is questionable. As common diseases result from many gene-environment interactions, epidemiologic studies should be used to examine the value of genomic profiling in terms of clinical validity (future disease positive and negative predictive value stratified by exposure), clinical utility (targeted interventions to reduce disease risk among persons with the profile) and public health utility (comparing reduction of disease burden in the population based on genomic profiling to population-wide interventions).
METHODS: We investigate these parameters for a hypothetical common disease (5% lifetime risk), for which 3 genetic variants at different loci and one environmental exposure are risk factors.
RESULTS: We show that even for modest effects of each variant alone (risk ratios from 1.5-3.0) and modest interactions between the exposure and the genes, the disease predictive value for people with 2 or more variants (especially 3) can be quite high (50-100%) in the presence of a modifiable exposure. Individual risks can then be reduced by targeted exposure intervention among persons with the genotype. However, the predictive value for multiple genotypes is much lower for rarer diseases (< 1 per 1000). Also, with increasing number of genes in a profile, the population impact of disease reduction for targeted intervention based on genotype will be smaller, especially for rare genotypes, weak associations, and weak interactions.
CONCLUSION: To assess the value of genomic profiling, well-designed epidemiologic studies are needed to quantify disease risks, in addition to costs, benefits, and risks for testing and interventions.

Entities:  

Mesh:

Year:  2004        PMID: 14726808     DOI: 10.1097/01.gim.0000105751.71430.79

Source DB:  PubMed          Journal:  Genet Med        ISSN: 1098-3600            Impact factor:   8.822


  29 in total

1.  The prediction of disease risk in genomic medicine.

Authors:  Wayne D Hall; Katherine I Morley; Jayne C Lucke
Journal:  EMBO Rep       Date:  2004-10       Impact factor: 8.807

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

Authors:  Hugues Aschard; Jinbo Chen; Marilyn C Cornelis; Lori B Chibnik; Elizabeth W Karlson; Peter Kraft
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3.  National Biobanks: Clinical Labor, Risk Production, and the Creation of Biovalue.

Authors:  Robert Mitchell
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4.  A research agenda for assessing the potential contribution of genomic medicine to tobacco control.

Authors:  Wayne D Hall
Journal:  Tob Control       Date:  2007-02       Impact factor: 7.552

5.  Public attitudes towards genomic risk profiling as a component of routine population screening.

Authors:  S G Nicholls; B J Wilson; S M Craigie; H Etchegary; D Castle; J C Carroll; B K Potter; L Lemyre; J Little
Journal:  Genome       Date:  2013-08-31       Impact factor: 2.166

6.  Evaluation of the discriminative accuracy of genomic profiling in the prediction of common complex diseases.

Authors:  Ramal Moonesinghe; Tiebin Liu; Muin J Khoury
Journal:  Eur J Hum Genet       Date:  2009-11-25       Impact factor: 4.246

7.  Prediction of individual genetic risk to disease from genome-wide association studies.

Authors:  Naomi R Wray; Michael E Goddard; Peter M Visscher
Journal:  Genome Res       Date:  2007-09-04       Impact factor: 9.043

Review 8.  Genetic testing and common disorders in a public health framework: how to assess relevance and possibilities. Background Document to the ESHG recommendations on genetic testing and common disorders.

Authors:  Frauke Becker; Carla G van El; Dolores Ibarreta; Eleni Zika; Stuart Hogarth; Pascal Borry; Anne Cambon-Thomsen; Jean Jacques Cassiman; Gerry Evers-Kiebooms; Shirley Hodgson; A Cécile J W Janssens; Helena Kaariainen; Michael Krawczak; Ulf Kristoffersson; Jan Lubinski; Christine Patch; Victor B Penchaszadeh; Andrew Read; Wolf Rogowski; Jorge Sequeiros; Lisbeth Tranebjaerg; Irene M van Langen; Helen Wallace; Ron Zimmern; Jörg Schmidtke; Martina C Cornel
Journal:  Eur J Hum Genet       Date:  2011-04       Impact factor: 4.246

9.  Integrating genetic studies of nicotine addiction into public health practice: stakeholder views on challenges, barriers and opportunities.

Authors:  M J Dingel; A D Hicks; M E Robinson; B A Koenig
Journal:  Public Health Genomics       Date:  2011-07-09       Impact factor: 2.000

10.  Comparison of risk perceptions and beliefs across common chronic diseases.

Authors:  Catharine Wang; Suzanne M O'Neill; Nan Rothrock; Robert Gramling; Ananda Sen; Louise S Acheson; Wendy S Rubinstein; Donald E Nease; Mack T Ruffin
Journal:  Prev Med       Date:  2008-11-25       Impact factor: 4.018

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