We know that too much sun is bad for you, but a new statistical model that combines not just data on sun exposure but genetic and other kinds of data can better predict skin cancer risk, according to new research by 23andMe.
Pierre Fontanillas, Ph.D., and a senior statistical geneticist at 23andMe presented these new findings last week at the American Society of Human Genetics‘ annual meeting in San Diego.
“We aimed to validate previously known skin cancer risk factors, add detail to these and explore potential new ones, and find out whether and how these factors might interact with genetic risk,” Pierre said.
Using genetic and phenotypic data from more than 210,000 23andMe customers who consented to participate in research, the team created a statistical model that used a genetic risk score incorporating not just 150 genetic variants associated with three forms of skin cancer, but also other data on such things as family cancer history, skin pigmentation, and sun exposure.
The model offered much stronger risk estimates for all three forms of skin cancer than genetic factors alone.
Because this initial work included data primarily from customers with European ancestry, the researchers plan to expand the study to include data from individuals with non-European ancestry. Also, they hope to improve how they estimate sun exposure and further refine the genetic risk score. The goal is to develop risk estimates accurate enough to be used clinically and at an individual level, according to the researchers.
23andMe at ASHG
Among the nine thousand people who converged on San Diego for the annual meeting of the American Society of Human Genetics, were more than 50 scientists and researchers from 23andMe.
In addition to two presentations, one on skin cancer by Pierre Fontanillas, Ph.D., (see post), and another on uniparental disomy done by former 23andMe intern, Priyanka Nakka, Ph.D., 23andMe had more than a dozen presentations on wide variety of findings around mosquito attractiveness and bite response, the genetic architecture of BMI, as well as genetic association for sleep apnea.
You can see more details on all of our posters and presentations here.