Consumers Interested in Raw Genetic Data, Third Party Interpretation Tools
Consumers of direct-to-consumer (DTC) genetic testing download raw data at high rates and frequently use third-party interpretation (TPI) tools, according to a study published June 13 in the American Journal of Human Genetics. Given that individuals will have increasing routes to access their raw genetic data, the authors say it is important to understand how consumers use raw data given the expanding number of available TPI services. “Rather than taking sides in a potential ensuing ‘culture war’ about raw data, the professional genetics community has an opportunity to proactively engage with users, understand the complexity of their motivations for pursing third-party analysis, and ultimately educate them about potential limitations,” write the authors led by Sarah Nelson, from University of Washington in Seattle. In the near future, it is likely that patients will have access to their raw genetic data from an increasing number of sources. There are indications that the the direct access right granted under the Health Insurance Portability and Accountability Act of 1996 includes sequencing data. Further, national-level bodies, like the National Academies of Sciences, Engineering, and Medicine, issued recommendations supporting returning “individual research results,” while large-scale, research-based, sequencing efforts, like the National Institutes of Health’s All of […]
Consumers of direct-to-consumer (DTC) genetic testing download raw data at high rates and frequently use third-party interpretation (TPI) tools, according to a study published June 13 in the American Journal of Human Genetics. Given that individuals will have increasing routes to access their raw genetic data, the authors say it is important to understand how consumers use raw data given the expanding number of available TPI services.
“Rather than taking sides in a potential ensuing ‘culture war’ about raw data, the professional genetics community has an opportunity to proactively engage with users, understand the complexity of their motivations for pursing third-party analysis, and ultimately educate them about potential limitations,” write the authors led by Sarah Nelson, from University of Washington in Seattle.
In the near future, it is likely that patients will have access to their raw genetic data from an increasing number of sources. There are indications that the the direct access right granted under the Health Insurance Portability and Accountability Act of 1996 includes sequencing data. Further, national-level bodies, like the National Academies of Sciences, Engineering, and Medicine, issued recommendations supporting returning “individual research results,” while large-scale, research-based, sequencing efforts, like the National Institutes of Health’s All of Us, indicated plans to make raw genetic data available to participants.
Emergence of Hybrid Model Changes the Genetic Testing Landscape
While direct-to-consumer genetic testing garners headlines and the ire of the clinical laboratory industry, a new hybrid model for genetic testing emerged, relatively unnoticed, according to a Viewpoint published May 30 in the Journal of the American Medical Association.
The National Institutes of Health’s genetic testing registry estimates that there are nearly 300 U.S. laboratories performing genetic testing, with the most falling into the traditional laboratory model. However, the emergence and growth of the hybrid model that combines features of direct-to-consumer testing and traditional laboratory models has significant implications for clinicians, consumers, policymakers, and payers.
The authors highlight Invitae (San Francisco, Calif.) as a high-profile example of the hybrid model. In SEC filings, the company, which has a stated goal of making “medical genetics affordable and accessible for everyone,” reported year-to-year growth in volume and revenue of more than 100 percent from 2017 to 2018. Testing volume over the period grew from 145,000 to 292,000 with revenue increasing from $68.2 million to $147.7 million.
The hybrid model provides clinical-grade testing and relies on clinicians to order tests and communicate results. However, the hybrid model facilitates enhanced, consumer-driven access by facilitating connections to physicians in the laboratory’s own network, rather than relying on the consumer’s usual care physician.
While there are not published studies, comparing the three models, the authors, led by Kathryn A. Phillips, Ph.D., from University of California, San Francisco, say the hybrid model holds the potential for increasing access to testing, providing greater convenience to both patients and clinicians unburdened with prior authorizations for out-of-pocket testing, and potentially lowering costs. Concerns about the model include potential reductions in continuity of care, as well as potentially abbreviated counseling and unnecessary testing.
Genetic researchers wishing to better understand the implications of returning raw sequencing data can understand individuals’ use of this information by studying DTC customers’ behavior.
The researchers recruited 1,137 DTC customers (October and November 2017) through social media to take part in a survey assessing raw data access and third-party tool usage following DTC genetic testing. The authors acknowledge that recruitment methods may have skewed results by identifying “likely highly motivated individuals” who were active in genetic online forums.
The researchers found that the vast majority of survey respondents (89 percent) reported downloading their raw data. Among raw data downloaders, 94 percent used at least one tool, most commonly GEDmatch (84 percent), Promethease (63 percent) or, and DNA.Land (53 percent). Most used multiple tools, with 76 percent (623 of 820) using two or more tools. More than half of participants (56 percent) used both health-related and non-health-related tools (genealogy and ancestry).
“We found that individuals who are initially motivated to learn about ancestry and genealogy frequently end up engaging with health interpretations of their genetic data, too,” said senior author S. Malia Fullerton in a statement. “This has implications for the regulation of such testing and interpretation practices.”
Across all tools, respondents reported positive outcomes from using these tools, including increasing their understanding of genetics in general (76 percent) and, more specifically, for how DTC companies interpret genetic data (67 percent). Most were satisfied with the information received (88 percent). However, some reported feeling confused (35 percent) or upset (6 percent) after receiving information.
After receiving results, most participants reported sharing the results with a family member (85 percent) or non-family member friend or loved one (71 percent). More than half (55 percent) pursued additional analysis using another analysis tool, while 33 percent pursued more genetic testing and 35 percent participated in a genetic research study. Few respondents reported making changes to either health insurance (0.9 percent) or other types of insurance (e.g., life or long-term care; 1 percent).
Only 15 percent of respondents reported sharing results with a health care provider. When shared with a health care provider, results were most commonly shared with a general practitioner (79 percent), while 11 percent reported sharing results with a medical geneticist or genetic counselor. Results were also shared with other practitioners from non-genetics specialties (e.g., cardiologist, gastroenterologist, ophthalmologist), psychiatry/psychology, and alternative medicine practitioners).
“This will present challenges for primary care physicians, especially given that TPI reports are typically longer and harder to digest compared to DTC company reports,” the authors write.
Takeaway: While the authors say future research should evaluate how individuals’ interactions with their raw data compare across DTC testing, clinical sequencing, and return of results from research, there is preliminary evidence that consumers are interested in receiving raw data and using TPI tools to learn more health, ancestry, and genealogy.
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