The Predictive Genomics blog series provides perspectives on the use and impact of genomics in clinical research for health systems, national initiatives and researchers. Topics focus on the role of genetics, genetic risk screening, pharmacogenomics, and the importance of diversity in genomic databases. To talk with our team on implementing your genetic-based initiatives, please contact us or browse our predictive genomic solutions.
There are several potential advantages for health systems or national research initiatives that invest in genotype-phenotype databases with the option to return results to participants.
Building a monetizable data asset is the most common rationale for investing in a large genotype-phenotype database, but there are several other compelling reasons to move forward, including better risk segmentation and targeting interventions, participant engagement and activation, participant recruitment/retention, “marketing sizzle,” the perception of innovation, and the recruitment/retention of high-quality physician-researchers.
Investing in a large genotype-phenotype research database creates a monetizable data asset, particularly for pharmaceutical companies. The basic hypothesis is that genetics can help drug-makers identify and accelerate the development of relevant molecules that reach the right disease targets, while avoiding investments in programs based on less well-validated targets. In 2012, Amgen acquired deCODE for $415M to “enhance its drug development capability, enabling it to better identify and validate potential drug targets and make medicines using population-scale data.” As evidence of the utility of genetics to drug developers, Amgen recently announced a deCODE discovery leading to a new effort in heart disease, a mutation in a gene called ASGR1 that appears to confer protection against heart attacks and coronary artery disease. Amgen can now prioritize the development of drug candidates to mimic the protective effects of this mutation. In 2019, Amgen extended its genetics investment by partnering with Intermountain Health, a large integrated health system in Utah. Intermountain patients can opt to participate in the HerediGene Initiative, which includes the option for the participant to receive the results identified in their genomes.
Governments and health systems around the world are emulating the Amgen/Decode model. In the U.S., some notable examples include:
- “All of Us” (former President Barack Obama’s Precision Medicine Initiative), part of which aims to collect genomic and other health data from at least a million Americans to find new clues about disease.
- Genomics England’s 100,000 Genomes Project, a collaboration with drugmaker AbbVie.
- Renown Health, a large health system in Nevada, partnered with 23andMe (and Helix) to genotype and return results to participants in their Healthy Nevada Project.
- Geisinger Health System in Pennsylvania partnered with the pharmaceutical company Regeneron. The Collaboration is designed to leverage de-identified clinical information and molecular data for medically relevant associations in a blind fashion that preserves patients’ privacy. For Regeneron, this collaboration was the first step in a planned expansion in the use of human genetics in the research process. Subsequently, Regeneron has partnered with AbbVie, Alnylam Pharmaceuticals, AstraZeneca, Biogen, and Pfizer to invest $10 million each to join the Regeneron-led precompetitive project to sequence samples from the UK Biobank’s 500,000 volunteer participants. Data are coupled with the participants’ detailed and de-identified medical and health records.
Other nations with such initiatives include Ireland, Qatar, Singapore, France, Estonia, China and many others.
Although the primary justification for health systems and governments to invest in the development of a large genotype-phenotype database is its potential value to drug developers, there are several additional value propositions, if results are returned to participants.
Risk segmentation and targeted interventions
One in 50 people with high cholesterol have a genetic form of high cholesterol that imposes a much higher risk of a cardiovascular event at a much younger age, but less than 10% of these individuals are detected by the current standard of care. The Healthy Nevada Project has shown that 90% of individuals with hereditary forms of breast/ovarian cancer, colon cancer and high cholesterol are undetected by current methods. Genetic testing can help identify these high risk patients and provide an opportunity to route them to the appropriate specialist in your system. Half of their relatives may also harbor the mutation, so proper outreach to these at risk-family members can provide prevention opportunities beyond the participant themselves.
Participant engagement and activation
When the Health Nevada Project launched, it recruited 10,000 participants in less than 24 hours—a rate unprecedented in research recruitment. What was different about the Healthy Nevada Project? It gave participants something in return and created a sense of “community good.” The Healthy Nevada Project offers participants, at no cost, the opportunity to learn about their ancestry, diet insights and genetic risks linked to heart disease and certain cancers, including prevention strategies. The invitation to participate draws on a sense of community and philanthropy by explaining that “contribution to this study allows us to create a robust set of data and enables us to draw new conclusions about how to improve the health of the entire Nevada population.”
The patients in your catchment or citizens in your district want to see drugs developed more quickly and less expensively. They want scientists to understand disease better and doctors to have better treatments for disease. Given the opportunity, they want to help. As a health system, genetics can help your brand be associated with a sense of community mission and create a partnership with your patients that improves health care for all.
In addition, research participants are self-selected “activated” participants. They choose to learn more about their health by opting into the program. These activated participants may be more likely to respond to suggested lifestyle and behavioral changes from their health care providers or prompts to comply with scheduled screenings. This information could be used to guide outreach campaigns or tailor primary care visits. Moreover, receiving genetic information about oneself has been shown to increase medication compliance with statins and antidepressants.1,2
Lastly, the most common action a consumer takes after receiving genetic information about themselves is to have a discussion with their extended family about their health risks. This results in a thorough discussion of disease history in the family, which, in turn, can be shared with each person’s health care providers for better health risk assessments.
Participant recruitment and retention
The MyCode Community Health Initiative offers genetic results to research participants at Geisinger Health System. The landing page explains, “With such a large body of data, we hope to find ways to make healthcare better—for you, your family, your community and individuals around the world. We do this through research and, where appropriate, through the application of that research to your personal care. For example, we are already improving healthcare by finding ways to diagnose medical conditions earlier—even before symptoms appear—and also to help find new treatments or medications to manage these diseases.” The participant testimonials illuminate the participants’ gratitude and pride in their health system. This creates a narrative that can be leveraged for participant retention and recruitment.
The health systems that have initiated genomics programs promote it heavily in their marketing materials to evoke a sense of “cutting-edge care.” This commercial from Inova Health in Virginia demonstrates how health systems leverage genomics for marketing sizzle. Health systems that neighbor institutions like Inova report that they are feeling market pressure to be able to claim that they, too, are cutting-edge and provide “precision medicine.”
Recruitment and retention of high-quality physician-researchers
In the past, physician-researchers either conducted research in a lab (in vitro) or as clinical trials (in vivo). In the 21st century, research is frequently being done in silico based on large, multidimensional data sets, such as genotype-phenotype databases. To stay relevant and competitive, high-quality physician-researchers need access to these large data sets. This has enabled health systems in relatively remote areas of the country to recruit and retain talent that would have typically gone to the coasts to practice.
Thermo Fisher Scientific: Powering predictive genomics studies globally
As outlined above, the success of building a large genotype-phenotype data set has a number of important considerations
- Recruitment of a large number of participants
- Engagement of those participants over time
- Returning high-value information back to participants
Thermo Fisher Scientific technology has historically been used to build the data sets of some of the biggest biobanks in the world. As stakeholders who are responsible for the health of a large population, such as a health system or government, partnering with Thermo Fisher Scientific enables you to:
- Access technology that’s both broad, with over 800,000 markers, as well as deep and specific for actionable variants.
- Make recruitment and engagement of your participants faster and easier.
- Customize and control your participants’ experience of the initiative and return only the results that you deem relevant to your cohort.
- Build a genetic database asset that’s unique to you and specific to your cohort. This will potentially create novel research and commercialization opportunities.
Talk to us about how we can partner with you on your population genomics studies.
1. Kullo, I.J., et al. (2016) “Incorporating a genetic risk score into coronary heart disease risk estimates: Effect on LDL cholesterol levels (the MIGENES clinical trial),” Circulation 133(12), pp. 1181–1188.
2. Winner, J.G., et al. (2015) “Combinatorial pharmacogenomic guidance for psychiatric medications reduces overall pharmacy costs in a 1 year prospective evaluation,” Current Medical Research and Opinion, 31(9), pp. 1633–1643, DOI: 10.1185/03007995.2015.1063483