Genomic Risk Factors Boost Prediction of Common Diseases in Finnish Study

by Carol Cruzan Morton

7 May 2020

Many genes can contribute in small ways to increase a person’s risk of a common chronic diseases, such as heart disease, type 2 diabetes or cancer. But how useful is that genetic information when we have the known risk factors checked off in a doctor’s office, such as lab tests, health behaviors and family history?

A new study from scientists at the Institute of Molecular Medicine Finland (FIMM) at the University of Helsinki reports that factoring in a genetic risk score was better at predicting disease in people than traditional clinical risk factors alone.  The findings were published in the April 2020 Nature Medicine.

ripatti
       Samuli Ripatti

In some cases, the combined risk score from many genes, called a polygenic risk score (PRS), identified younger people at high risk of early-onset disease, who slipped through the usual clinical risk models. In other cases, the genetic risk score lowered the risk status of older people, whose age alone tipped them into a traditional high risk group.

Better identification of people at high risk of different common chronic diseases could allow for more personalized prevention and treatment efforts, the study authors concluded.

"In terms of cardiovascular diseases and diabetes, genomic information alone can identify individuals who have a lifetime risk of more than 60% of developing these diseases, which means that most of them will develop these diseases at some point of their lives," said the principal investigator of the study, Samuli Ripatti, in a press release. The higher the PRS, the earlier the disease.

He gave more examples in a Twitter thread. “Individuals in the top 2.5% of the PRS had a lifetime risk at 67% for type 2 diabetes, whereas the bottom 2.5% had a lifetime at 8%,” Ripatti tweeted. 

In 50,000 men with prostate cancer, he noted, “the PRS reclassified 15 percent of younger and 11 percent of older men toward the correct risk class. Importantly, PRS could guide us not only in identifying much better the high-risk men, but also by improving identification of elderly men at low risk.”

In the study, researchers estimated the genetic risk for five common diseases: coronary heart disease, type 2 diabetes, atrial fibrillation, breast cancer and prostate cancer. They based their estimates on numerous large-scale studies in the scientific literature.

Then they investigated the association between the genetic risk scores and disease events within the independent FinnGen study cohort of 135,000 Finnish volunteers.

The team also combined genetic risk data with currently known risk factors and clinical risk calculators. Adding genomic information improved the accuracy of current risk estimation approaches.

“Traditional clinical risk assessment tools are unable to identify most young individuals at high risk,” Ripatti tweeted. “PRS could improve our ability to identify them.”

mars
            Nina Mars

The impact of the genetic risk score was similar across all five diseases. The higher the genetic risk score, the more likely (21% to 38%) and earlier (4 to 9 years) people were to come down with the disease compared to those with an average score.

"Our findings show that the genetic risk profile was a significant factor in predicting the onset of all five diseases studied,” said first author Nina Mars of FIMM in a press release. “A particular benefit was seen in the identification of individuals who develop diseases at a younger age than on average.”

Genomic information offers more personalized risk calculation, Mars said. For example, it could affect the age when breast and prostate cancer screening begins. “One option is to have those with an elevated genetic risk already undergo screening earlier than instructed in the current screening recommendations,” she said. 

“Our findings show the value of PRS in clinical prediction, together with clinical risk factors,” Ripatti tweeted. “It’s time to find the optimal ways for clinical implementation of PRSs, such as stratified screening of common cancers, or stratified prevention of cardiometabolic diseases.”