Literature DB >> 19636253

Evaluation of risk prediction updates from commercial genome-wide scans.

Raluca Mihaescu1, Mandy van Hoek, Eric J G Sijbrands, André G Uitterlinden, Jacqueline C M Witteman, Albert Hofman, Cornelia M van Duijn, A Cecile J W Janssens.   

Abstract

PURPOSE: Commercial internet-based companies offer genome-wide scans to predict the risk of common diseases and personalize nutrition and lifestyle recommendations. These risk estimates are updated with every new gene discovery.
METHODS: To assess the benefits of updating risk information in commercial genome-wide scans, we compared type 2 diabetes risk predictions based on TCF7L2 alone, 18 polymorphisms alone, and 18 polymorphisms plus age, sex, and body mass index. Analyses were performed using data from the Rotterdam study, a prospective, population-based study among individuals aged 55 years and older. Data were available from 5297 participants.
RESULTS: The actual prevalence of type 2 diabetes in the study population was 20%. Predicted risks were below average for carriers of the TCF7L2 CC genotype (predicted risk 17.6%) and above average for the CT and TT genotypes (20.8% and 28.0%). Adding the other 17 polymorphisms caused 34% of participants to be reclassified (i.e., switched between below and above average): 24% of the CC carriers changed to increased risk, 52% and 6% of the CT and TT carriers changed to decreased risk. Including information on age, sex, and body mass index caused 29% to change categories (27%, 31%, and 19% for CC, CT, and TT carriers, respectively). In total, 39% of participants changed categories once when risk factors were updated, and 11% changed twice, i.e., back to their initial risk category.
CONCLUSION: Updating risk factors may produce contradictory information about an individual's risk status over time, which is undesirable if lifestyle and nutritional recommendations vary accordingly.

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Year:  2009        PMID: 19636253     DOI: 10.1097/GIM.0b013e3181b13a4f

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


  34 in total

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Journal:  J Genet Couns       Date:  2011-12-08       Impact factor: 2.537

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4.  Is there a doctor in the house? : The presence of physicians in the direct-to-consumer genetic testing context.

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5.  Legislation on direct-to-consumer genetic testing in seven European countries.

Authors:  Pascal Borry; Rachel E van Hellemondt; Dominique Sprumont; Camilla Fittipaldi Duarte Jales; Emmanuelle Rial-Sebbag; Tade Matthias Spranger; Liam Curren; Jane Kaye; Herman Nys; Heidi Howard
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6.  Which way for genetic-test regulation? Assign regulation appropriate to the level of risk.

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7.  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

8.  Role of genomics in cardiovascular medicine.

Authors:  Giuseppe Novelli; Irene M Predazzi; Ruggiero Mango; Francesco Romeo; Jawahar L Mehta
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9.  Direct-to-consumer personal genomic testing: a case study and practical recommendations for “genomic counseling”.

Authors:  Amy C Sturm; Kandamurugu Manickam
Journal:  J Genet Couns       Date:  2012-06       Impact factor: 2.537

10.  Evaluation of genetic tests for susceptibility to common complex diseases: why, when and how?

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Journal:  Hum Genet       Date:  2009-11-20       Impact factor: 4.132

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