Web-based, participant-driven studies yield novel genetic associations for common traits. N. Eriksson1, J. M. Macpherson1, J. Tung1, L. Hon1, B. Naughton1, S. Saxonov1, L. Avey1, A. Wojcicki1, I. Pe’er2, J. Mountain1,3
1) 23andMe, Inc., Mountain View, CA; 2) Department of Computer Science, Columbia University, New York, NY; 3) Department of Anthropology, Stanford University, Stanford, CA.
Despite the recent, rapid growth in genome-wide data, much of human variation remains entirely unexplained. A significant challenge in the pursuit of the genetic basis for variation in common human traits is the efficient, coordinated collection of genotype and phenotype data.
We report on initial results from a participant-driven study of 22 common traits based on a novel research framework that facilitates the parallel study of a wide assortment of traits within a single cohort. The approach takes advantage of the interactivity of the web both to gather data and to present genetic information to research participants, while taking care to correct for the population structure inherent to this study design.
We present novel associations for hair curl, “asparagus anosmia” (the inability to smell the methanethiol produced after eating asparagus), and photic sneeze reflex. For hair curl, we identify two independent SNPs: rs17646946 (p-value less than 10-28, near TCHH) and rs7349332 (p-value less than 10-8.4, in WNT10A). For asparagus anosmia, we identify one SNP in a region of olfactory receptors, rs4481887, with a p-value less than 10-16. For photic sneeze reflex, we identify one SNP, rs1040173, with a p-value less than 10-9.7. In order to validate the web-based, self-reporting design, we have in addition replicated associations in the genes OCA2, HERC2, SLC45A2, SLC24A4, IRF4, MC1R, TYR, TYRP1 and ASIP for hair color, eye color, and freckling.
The other traits analyzed in this study include laterality preferences (handedness, footedness, ocular dominance, and hand-clasp), simple physical characteristics (whether participants have had cavities, have worn braces, have had wisdom teeth removed, have astigmatism, wear glasses, have attached earlobes, and suffer from motion sickness while riding in a car), and personality traits and preferences (optimism, a preference for sweet versus salty food, and preference for night-time versus morning-time activity).
Secondly, even if it proves impossible to compete with academic researchers in the medical genomics space, 23andMe and deCODEme (but not Navigenics) do have a fairly good fall-back position: they can generate information about things that fascinate the public, but are difficult to get funding for in the public arena. I’m talking, of course, about both genealogy/ancestry testing and the genetics of normal variation (e.g. pigmentation, handedness, attached versus detached earlobes, that sort of thing).
Genetic genealogy and ancestry testing are huge markets, and 23andMe already seems to do them better than most other companies in the space – certainly their interface is slick, and their investment in this whole-genome analysis of almost 1,000 genetically diverse humans performed by Stanford University researchers demonstrates their commitment to this area. In addition, 23andMe’s customer base will give it substantial power to uncover the genetic determinants of many variable traits that would seem trivial to a grant committee, but that customers would pay good money to explore – especially once scans become cheap enough to run on multiple family members.