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Genome Med. 2015 Aug 1;7(1):74. doi: 10.1186/s13073-015-0188-5. eCollection 2015.

Explaining, not just predicting, drives interest in personal genomics.

Author information

1
Cancer Research UK Health Behaviour Research Centre, Department of Epidemiology and Public Health, University College London, London, UK.
2
Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02115 USA ; Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115 USA.
3
Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029 USA.
4
Millennium Health, San Diego, CA 92127 USA.
5
23andMe, Inc., 899 West Evelyn Avenue, Mountain View, CA 94041 USA.
6
Department of Health Behavior & Health Education, University of Michigan School of Public Health, Ann Arbor, MI 48109 USA.
7
Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02115 USA ; Harvard Medical School, Boston, MA 02115 USA ; Partners Personalized Medicine, EC Alumnae Building, Suite 301, 41 Avenue Louis Pasteur, Boston, MA 02115 USA.

Abstract

BACKGROUND:

There is a widespread assumption that risk prediction is the major driver of customer interest in personal genomic testing (PGT). However, some customers may also be motivated by finding out whether their existing diseases have a genetic etiology. We evaluated the impact of an existing medical diagnosis on customer interest in condition-specific results from PGT.

METHODS:

Using a prospective online survey of PGT customers, we measured customer interest prior to receiving PGT results for 11 health conditions, and examined the association between interest and personal medical history of these conditions using logistic regression.

RESULTS:

We analyzed data from 1,538 PGT customers, mean age 48.7 years, 61 % women, 90 % White, and 47 % college educated. The proportion of customers who were 'very interested' in condition-specific PGT varied considerably, from 28 % for ulcerative colitis to 68% for heart disease. After adjusting for demographic and personal characteristics including family history, having a diagnosis of the condition itself was significantly associated with interest in genetic testing for risk of that condition, with odds ratios ranging from 2.07 (95 % CI 1.28-3.37) for diabetes to 19.99 (95 % CI 4.57-87.35) for multiple sclerosis.

CONCLUSIONS:

PGT customers are particularly interested in genetic markers for their existing medical conditions, suggesting that the value of genetic testing is not only predictive, but also explanatory.

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