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By: David Shifrin, PhD
Science Writer, Filament Life Science Communications
The past few weeks have been filled with articles dealing with the distribution and use of genetic test results. As we have pointed out on this blog, the underlying theme is that gaining a full(er) understanding of the clinical implications of any given genetic variant will require more complete datasets. This, in turn, requires that individuals and genetic testing companies be willing to deposit genetic testing data into databases that are accessible to researchers.
However, just piling up results from people tested for medical reasons leaves out a huge pool of potential information. If someone undergoes genetic testing for BRCA1/2 mutations because of a family history of breast cancer, the results (whether or not any pathological variants are found) are valuable. But, what about the individual who has no indication for genetic testing? His information is equally valuable for research purposes. The question is, will someone like that undergo genetic testing just out of curiosity, and will he allow his results to be used in research?
Those questions were recently asked of 35 individuals by a team led by Saskia Sanderson and Eric Schadt of the Icahn School of Medicine at Mount Sinai. The results, published in the European Journal of Human Genetics, deal with the “motivations, concerns and preferences of personal genome sequencing research participants.”
First, the answer to the question of whether people will undergo whole exome or whole genome sequencing without a direct medical indication is a clear “yes.” Direct to consumer and ancestry testing services prove this point easily. In addition to using it to satisfy general curiosity, genetic testing is being used more preemptively, to seek out potential health risks that have not yet been uncovered in an individual or her family.
It is likely that this is in large part driven by the rapid decrease in the cost of genetic testing. Demand has increased as the cost has gone down, creating a feedback loop that results in growing adoption.
With this rapid expansion of the field, better guidelines are needed, along with “communication strategies” to help convey results to the individuals tested. This all goes hand in hand with the issue of data sharing, because people likely need to be comfortable with the testing and reporting process in order to be willing to consent to sharing.
In the paper, Sanderson and colleagues interviewed 35 participants who received sequencing for a study called HealthSeq, which is “a longitudinal cohort study of individuals receiving personal [whole genome sequencing] results.” A key strength of the study was that it used both qualitative and quantitative metrics to survey the participants. Multiple questionnaires were used throughout the study, but this paper focused on only one set. Individuals were asked to respond free-form to various questions for the qualitative component, and then fill out a quantitative questionnaire.
Several key “motivation themes” came out of the two surveys. In the qualitative part, individuals were interested in undergoing genetic testing in order to uncover potential risk factors, both for themselves and their families. Additionally, pure curiosity and an interest in ancestry were also mentioned, among others. A significant number (43%) also wanted “to contribute to research.”
These results were mirrored in the quantitative questionnaire. A majority of participants indicated that they were interested in being tested to learn about disease risk and uncover ways to improve their health. Additionally, curiosity was “very important” to 71% of the participants in their decision to be tested.
The questions and survey also looked at concerns about genetic testing, and participants’ willingness to share their data. Not surprisingly, privacy and insurance discrimination were significant concerns among many of the individuals. Another concern was “not knowing how I will feel about my results,” which once again points to the importance of finding ways to communicate clearly and empathetically before testing and during genetic counseling post-testing. Not wanting to know may be a valid reason not to undergo testing or not be informed of some or all results, but the field should work to ensure that this concern is minimized in people who are in fact inclined to undergo genetic testing.
Lastly, the authors asked participants about their preferences regarding the use of their data. The vast majority (91%) wanted their personal information to be associated with their results, and were willing for their data to be used by other researchers at the host institution (Mount Sinai) in studies “directly related to the present research.” However, the number of people who were willing to extend that permission to investigators outside of Mount Sinai or internal investigations “not directly related to the present research” declined to 60%. One can wonder whether this indicates a desire on the part of someone undergoing genetic testing to keep track of where and how her results would be used. It seems reasonable that people would have greater levels of trust in their home institution, making them more likely to contribute sensitive information to work going on there.
The concerns about privacy and data sharing also suggest that the field has a ways to go before people are broadly comfortable releasing their personal genetic information. One question that was not addressed is whether participants would be more likely to share their results with external investigators if it was first de-identified. Would the participants be willing to maintain their data locally at Mount Sinai, but then share de-identified results with larger databases, as is being done at some institutions and companies? This is the type of question that must be answered if a clear pipeline of genetic information is to be fully implemented.
While the results from this study are interesting, they do present significant limitations. The sample size was only 35 individuals, which the authors admit is small. Importantly, the authors only captured data from people who might be considered “early adopters” and are not representative of the broader population. 31% of the participants had a doctoral level degree, and 65% made $80,000 or more annually. Whether the issue is participating in research studies or buying a new model smartphone, the attitudes and behaviors of early adopters is significantly different than the far larger proportion of people who are part of the early/late majority. The authors make an oblique reference to this limitation, but never really address it. Therefore, quite a bit more work needs to be done in terms of talking to that latter, much larger group. With that in mind, this study provides some interesting data points with regards to patient opinions on genetic testing, but it the possibility of extrapolating those results is limited.