Genetic Disease Risk Impacted by Entire Genome, Study Reveals

In people with a single-gene variant that contributes to high genetic disease risk – specifically for heart disease, breast cancer, or colorectal cancer – the rest of the genome can alter that risk, according to a study published in Nature Communications.  

Some individuals are genetically predisposed to disease, but these disease predictions aren’t always accurate as not everyone carrying these high-risk single-gene variants develops the disease.

A team from the Broad Institute of MIT and Harvard, Massachusetts General Hospital (MGH), Harvard Medical School collaborated with IBM Research and Color to determine why this occurs. The group focused on three conditions: familial hypercholesterolemia, where single-gene variants prevent the body from clearing cholesterol from the bloodstream, elevating heart disease risk; Lynch syndrome; and hereditary breast cancer.

Most individuals with these high-risk variants remain unaware of their inborn risk, and they can’t be reliably identified through family history or other risk factors.

Researchers studied genetic and clinical data from 80,298 individuals. The team looked for people with a particular high-risk variant, calculated their polygenic score for the disease, and then ascertained if the individual developed disease or not through their medical records.

The results showed that for a small subset of people with a high-risk single-gene, or monogenic variant for disease, a high polygenic score more than doubled their overall disease risk from an estimated average of 35 to 41 percent up to 80 percent.

"Patients and clinicians often assume that having a high-risk variant makes eventually getting the disease all but inevitable, but an important subset actually go on to live their lives normally," said Akl Fahed, co-first author of the study, who is a cardiology fellow at MGH, and a postdoctoral fellow in Broad's Program in Medical and Population Genetics (MPG).

"The traditional approach is to focus on a single base pair mutation linked to disease, but there are 3 billion base pairs in the genome. So we asked whether the rest of your genome can help explain the differing rates of disease we see in these patients, and the answer was a clear yes."

Across all three diseases analyzed in the study, researchers found that a favorable polygenic background lowered disease risk, bringing it closer to that of an average person without the high-risk variant.

"The changes in risk are striking," said senior author Amit V. Khera, a physician-scientist leading a research group in the Center for Genomic Medicine at MGH and associate director of the Broad MPG.

"For breast cancer, whether a woman's risk is 13 percent or 76 percent may be very important in terms of whether she chooses to get a mastectomy or undergo frequent screening via imaging. Also, for Lynch syndrome, a more precise risk estimate could similarly be a deciding factor for removing the colon entirely or frequent screening colonoscopies."

Researchers also noted that the study would not have been possible without access to a vast, comprehensive dataset.

"In trying to do these kinds of studies in the past, there were two main barriers," said Khera.

"You needed very large datasets of participants with and without high-risk variants, and you needed high-quality polygenic scores calculated in these people to quantify their genetic background. The genetics community is only now beginning to have access to these key tools."

The results of the study provide a scientific foundation for a new approach for assessing disease risk, where accounting for genetic background increases accuracy of risk estimation, even for those with a high-risk variant. Beyond genetic factors, the researchers plan to build models accounting for additional non-genetic factors that are also associated with disease risk.

"We studied the interplay of monogenic and polygenic disease risk," Fahed said. "But genetics is only part of the story. For heart disease, risk involves other factors like blood pressure and lifestyle risks such as smoking. It is important to account for these as well and develop more fully integrated risk models."

As polygenic scores and disease risk models make their way into routine medical practice, researchers noted that these tools can help patients better understand, predict, and prevent disease using genetic information.

"We are thrilled to be able to offer state-of-the-art genetic risk assessment to our patients in the coming months. One of our next steps is to educate doctors and patients on more advanced types of genetic risk predictors, such as polygenic scores. But there's also important work to be done to further validate integrated genetic risk models in additional populations,” Khera said.

“The ability to reliably classify monogenic variants as high-risk and stratify the population using polygenic scores is higher in people of European ancestry than other groups, just because that is where most of our training data comes from. So, we need to diversify datasets and improve the models so that they work well for people from different ancestries, ensuring that genomic risk stratification benefits everyone."