Not ready for prime time ... yet
All three researchers agreed that this risk-prediction model is merely the first step.
For one thing, the model they created was based on people of European ancestry, i.e., Caucasians, since that group was much larger in the studies they analyzed.
“At the beginning, we were not as advanced as to understand how to analyze multi-ethnic populations,” said Peters, who put the project in motion about a decade ago. “We’re much better set up now. We have better understanding and statistical methods to do this and we’re very eager to expand.”
Their next step will be to create risk-prediction models that include genetic variants for other ethnic groups, such as African-Americans, Hispanics, Asians and Native Americans. Each risk model will differ slightly since each ethnic group has different genetic risk factors, Hsu said.
“This is a very important point,” Peters said. “It’s really important to validate and evaluate this model in other ancestral [or ethnic] groups. Our model needs to be fine-tuned and it needs to be evaluated in those groups separately.”
The researchers are aware that there are people who may want to DIY their own risk prediction model now, using commercial genetic tests, which have become more widely available.
It’s not that simple, Peters said.
“I can understand the frustration of an individual who might want to use genetic information right now," she said. "But physicians are not trained on what to do with this information yet and public providers do not provide a genetic risk-prediction model. So that’s not the solution at this point.”
But it’s expected that genomic information will one day be included in the medical record, she said, and “precision prevention can be realized.”
Until then, people can embrace the science at hand — i.e., continue to follow current screening guidelines and work to reduce lifestyle and environment risks — and ready themselves for a screening sea change.
“We’re laying out a road map to move personalized prediction into the clinic and public health space,” Peters said. “We have a very solid approach in showing how we can integrate environmental, lifestyle and genetic data for risk prediction. And we don’t want to stop there."
In the future, Peters and her team hope to integrate additional genetic, biomarker and microbiome data to further improve the risk-prediction model for colorectal cancer — and other diseases.
"Once the genetic information is added to the medical record," she said, "it can be used to screen for many common, complex diseases — other cancers, cardiovascular disease, type 2 diabetes and more.”