Tung et al. Efficient Replication of over 180 Genetic Associations with Self-Reported Medical Data. PLoS One. 2011;6(8):e23473.
While the cost and speed of generating genetic data have come down dramatically in recent years, the slow pace of collecting medical data for large numbers continues to hamper genetic research.
In this study the investigators evaluated a novel online framework for obtaining large amounts of medical information from people by assessing their ability to replicate genetic disease associations using these data.
Using web-based questionnaires, they gathered self-reported data on 50 medical phenotypes (diseases and traits) from a generally unselected group of 20,000 individuals.
Of a list of genetic associations they successfully replicated about 75% of the diseases associations that they expected to.
Altogether they replicated over 180 previously reported associations, including many for type 2 diabetes, prostate cancer, cholesterol levels, and MS.
They also demonstrated that we could improve the replication success by taking advantage of their ability to recontact the subjects, offering more in-depth questions to refine self-reported diagnoses.
Their data suggest that online collection of self-reported data from a recontactable cohort may be a viable method for both broad and deep phenotyping in large populations.
“This is a amazing study; we need to jump on the band wagon.”
“It helps to have money; the founder of 23andme is the partner of Sergey Brin, one of the founders of Google.”