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. 2013 Apr 4;92(4):547-57.
doi: 10.1016/j.ajhg.2013.03.003. Epub 2013 Mar 28.

The benefits of using genetic information to design prevention trials

Youna Hu  1 , Li Li, Margaret G Ehm, Nan Bing, Kijoung Song, Matthew R Nelson, Philippa J Talmud, Aroon D Hingorani, Meena Kumari, Mika Kivimäki, Chun-Fang Xu, Dawn M Waterworth, John C Whittaker, Gonçalo R Abecasis, Cathie Spino, Hyun Min Kang
Affiliations

The benefits of using genetic information to design prevention trials

Youna Hu et al. Am J Hum Genet. .

Abstract

Clinical trials for preventative therapies are complex and costly endeavors focused on individuals likely to develop disease in a short time frame, randomizing them to treatment groups, and following them over time. In such trials, statistical power is governed by the rate of disease events in each group and cost is determined by randomization, treatment, and follow-up. Strategies that increase the rate of disease events by enrolling individuals with high risk of disease can significantly reduce study size, duration, and cost. Comprehensive study of common, complex diseases has resulted in a growing list of robustly associated genetic markers. Here, we evaluate the utility--in terms of trial size, duration, and cost--of enriching prevention trial samples by combining clinical information with genetic risk scores to identify individuals at greater risk of disease. We also describe a framework for utilizing genetic risk scores in these trials and evaluating the associated cost and time savings. With type 1 diabetes (T1D), type 2 diabetes (T2D), myocardial infarction (MI), and advanced age-related macular degeneration (AMD) as examples, we illustrate the potential and limitations of using genetic data for prevention trial design. We illustrate settings where incorporating genetic information could reduce trial cost or duration considerably, as well as settings where potential savings are negligible. Results are strongly dependent on the genetic architecture of the disease, but we also show that these benefits should increase as the list of robustly associated markers for each disease grows and as large samples of genotyped individuals become available.

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Figures

Figure 1
Figure 1
Frameworks of Conventional and Genetically Enriched Prevention Trials (A) Conventional prevention trial not utilizing genetic information. (B) Standard genetic enrichment trial following up only individuals at high genetic risk after genetic screening. (C) Biobank-based enrichment trial where DNA information is available a priori and used for inviting individuals at the beginning of trial.
Figure 2
Figure 2
Distribution of Genetic Risk Scores from Currently Known Risk Variants for Four Disease Traits The x axis represent the genetic risk score with respect to the individuals with the lowest risk genotypes. The y axis represents the fraction of individuals with disease based on their risk score. The 95% confidence intervals account for variations in the odds ratio estimates.
Figure 3
Figure 3
Sample Size and Total Cost of Genetically Enriched Prevention Trials Using Currently Known Risk Variants x axis represents the targeted proportion of individuals at high genetic risk, and the left y axis, corresponding to solid lines, represents sample size for a conventional trial (red), on-trial sample size for a genetic enrichment trial (blue), and screening sample size for a genetic enrichment trial (green). The right y axis, corresponding to dashed lines, represents the total cost of the genetic enrichment trial given targeted proportion.
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