Supplementary Material for: Considerations for Designing a Prototype Genetic Test for Use in Translational Research
datasetposted on 03.09.2009 by Wade C.H., McBride C.M., Kardia S.L.R., Brody L.C.
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Background: Translational research is needed to explore how people will respond to personal genetic susceptibility information related to common health conditions. Maximizing the rigor of this research will require that genetic test results be returned to study participants. Currently, there is no established method that guides the selection of genetic variants to be used in research with these objectives. Methods and Results: To address this question, we designed a process to identify gene variants and health conditions to be included in a prototype genetic test for use in a larger research effort, the Multiplex Initiative. The intention of this exploration was to facilitate research that generates individual genetic test results that are returned to study participants. Inclusion criteria were developed as part of a transdisciplinary and iterative process that considered the weight of evidential support for genetic association with common health conditions, the appropriateness of use in human subjects research, and the recommendations of expert peer reviewers. Conclusions: The selection process was designed to identify gene variants for the limited purpose of translational research and, therefore, should not be seen as producing a valid clinical test. However, this example of an applied selection process may provide guidance for researchers who are designing studies to evaluate the implications of genetic susceptibility testing through the return of personalized genetic information. As the rate of genomic discoveries increases, such research will be essential in steering the translation of this information towards the greatest public health benefit.