23andMe Research Innovation Collaborations Program
In addition to providing direct-to-consumer genetic testing through the 23andMe® Service, 23andMe endeavors to advance biomedical science through genetic research.
Some of those discoveries have and will come from our own scientists, but others will come from collaborations with academic researchers.
The 23andMe Research Innovation Collaborations Program pairs up academic researchers with 23andMe scientists to perform analyses. Through this program, academic researchers can access de-identified, aggregated data from the 23andMe Research Cohort.
The 23andMe database is a rich resource, with genotypic and phenotypic information from more than 5 million of our customers, 80 percent of whom consent to participate in 23andMe Research. By consenting to participate, our customers agree to make their de-identified genetic data available for study in aggregate and take part in online research under a protocol approved by an external institutional review board (IRB). These research participants also answer online survey questions on a variety of topics, and to date have contributed over 1 billion phenotypic data points.
Recent Collaboration Highlights
Over the years, we have participated in over 100 collaborations with academic institutions on a wide variety of topics. Here are select examples of projects we are currently pursuing or have recently completed:
- In collaboration with Danielle Posthuma at Vrije University Amsterdam, 23andMe contributed to the largest GWAS of insomnia, which identified almost 1000 genes that might be linked to this prevalent mental disorder.
- 23andMe scientists are working with Noah Zaitlen at UCSF, Alkes Price at Harvard School of Public Health, and Bogdan Pasaniuc at UCLA To refine computational methods that identify risk loci, train risk prediction models, and fine-map variants based on summary statistics.
- We have investigated the genetic underpinnings of the onset of puberty in both boys (age of voice-breaking) and girls (age at menarche) as part of a collaboration with Dr. John Perry at the University of Cambridge.
Our research team has published or collaborated on over 100 scientific papers. For a complete list, visit our Publications page.
We accept applications from academic researchers on a rolling basis. In June and December, we hold a scientific review to evaluate proposals for the limited number of collaborative projects we can initiate. By opening this opportunity to the greater scientific community, we hope to widen our perspective, spark new innovation, and generate meaningful discoveries from the 23andMe database. In particular, we are interested in collaborations that have the potential to catalyze novel findings beyond what we can accomplish on our own. This includes analyses with collaborators willing to share complementary data resources, new methodologies, or approaches that validate our findings.
What data can be found in the 23andMe database?
We have collected genotypic and phenotypic data from more than 5 million research participants, a cohort that continues to grow. Phenotypic data is self-reported by 23andMe research participants who have responded to surveys hosted on the 23andMe website. A supplement with an overview of the types of phenotype data we collect can be found here.
What type of collaboration is of interest to 23andMe?
We seek collaborators who will enable new discovery from our database with complementary datasets, expertise, and analytic techniques. We are particularly interested in developing and establishing the personal and clinical utility of genetics-based risk models. Example collaborations could involve:
- Incorporating data from an ethnically diverse and/or deeply phenotyped cohort to enhance or validate risk prediction
- The development of new methods for creating or evaluating genetic risk scores
- Investigations of genetic risk score clinical utility in observational or interventional studies
These collaborations will leverage 23andMe’s database and infrastructure to demonstrate the real-world utility of genetic risk models, and may lead to new 23andMe Health or Wellness reports. We are also interested in collaborations on the following topics:
- Identification of rare variants with whole-genome sequencing data
- Fine-mapping of causal variants with targeted sequencing data
- Application of genotypic data from select ancestry or disease cohorts to enhance ancestry inference and/or disease risk prediction
- Validation of survey responses through clinical assessment