NEW YORK – Researchers from the Broad Institute, Massachusetts General Hospital, Color, and elsewhere have found that polygenic background can modify the penetrance of disease risk variants in tier 1 genomic conditions such as familial hypercholesterolemia, hereditary breast and ovarian cancer, and Lynch syndrome.
In a paper published on Thursday in Nature Communications, the researchers reported that they studied 80,928 individuals to examine the interplay between polygenic background and monogenic variants. They found that carriers of a monogenic risk variant had substantial gradients in disease risk based on polygenic background: the probability of disease by the age of 75 ranged from 17 percent to 78 percent for coronary artery disease; 13 percent to 76 percent for breast cancer; and 11 percent to 80 percent for colon cancer.
They added that although roughly 1 percent of asymptomatic adults carry pathogenic or likely pathogenic variants related to any of these conditions that are associated with several-fold increased risk of disease, the variants have long been known to have incomplete penetrance and variable expressivity. Therefore, accounting for polygenic background is likely to increase the accuracy of risk estimation for individuals who inherit a monogenic risk variant.
"The changes in risk are striking," senior author Amit Khera, a physician-scientist in the Center for Genomic Medicine at MGH and associate director of the Broad MPG, said in a statement. "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."
The researchers designed two case-control studies from the UK Biobank and Color commercial testing laboratory, and performed an analysis of an independent cohort from the UK Biobank. They also computed newer-generation polygenic scores for coronary artery disease, breast cancer, and colorectal cancer, which enhanced risk prediction over prior scores.
To identify individuals with monogenic variants causal for familial hypercholesterolemia, they sequenced the three genes related to the condition —LDLR, APOB, and PCSK9 —in 6,432 coronary artery disease cases and 6,420 controls from the UK Biobank. They classified 28 distinct genetic variants as pathogenic or likely pathogenic, and these variants were present in 43 (0.67 percent) cases and 13 (0.20 percent) controls.
The presence of a familial hypercholesterolemia variant conferred a 3.21-fold increased risk of coronary artery disease, the researchers found.
But when they examined the effect of the participants' polygenic background on their risk of coronary artery disease, the observed risk varied substantially according to the polygenic score. For example, the risk among mutation carriers ranged from 1.30-fold for those in the lowest quintile of the polygenic score distribution to 12.61-fold in the highest quintile of the polygenic score distribution, when compared to non-mutation carriers with intermediate polygenic scores.
The researchers also applied the same analysis to breast cancer. They first identified monogenic risk variants by sequencing the BRCA1 and BRCA2 genes in 1,920 breast cancer cases and 17,344 controls from the Color testing lab, and identified a pathogenic or likely pathogenic variant in 174 (9.1 percent) cases and 671 (3.9 percent) controls. This corresponded to a 3.48-fold increased risk of breast cancer in variant carriers.
The investigators then calculated polygenic risk for breast cancer and found that disease risk was strongly affected by polygenic background, even for individuals who carried a pathogenic variant. Compared to non-carriers with intermediate polygenic score, increased risk among carriers ranged from 2.40-fold for those in the lowest quintile of the polygenic score distribution to 6.85-fold in the highest quintile.
"Understanding the physiological basis of how polygenic score modifies the penetrance of monogenic variants may suggest therapeutic strategies for monogenic variant carriers in general," the authors wrote. "An important example is the decision about the timing and intensity of lipid-lowering therapy for individuals with familial hypercholesterolemia. Here, we find a broad spectrum of risk of coronary artery disease in those with a monogenic risk variant across percentiles of the polygenic score that may better inform shared decision making."
The researchers did note that data on monogenic risk variants and the development of the polygenic scores has been based primarily on patients of European ancestry, which affects the utility for patients of other ancestries, so it's important that the biomedical community invest in the development of more large studies and databases geared towards acquiring more information on diverse populations and ancestral backgrounds.
They also said that further efforts are required to understand how best to disclose integrated genomic risk assessments to patients and treating clinicians, and how to integrate that data with existing lifestyle or clinical risk factors.
"This research has real clinical implications for genome interpretation," Khera added. "A person's polygenic risk also plays a crucial role in predicting the development of disease. I suspect that evaluating both will soon become standard in clinical practice."
Indeed, Khera is reemphasizing a point he made in December 2019 when he and his co-authors originally published their work on the health sciences preprint server MedRxiv. He noted at the time they were doing work to fine-tune the polygenic scores and, in some cases, understand the biological underpinnings of why the polygenic variants modify risk conferred by the monogenic variants, but that they were looking to translate their findings into the clinic as soon as possible.
Khera led the development of the Preventive Genomics Clinic at Mass General, the primary purpose of which is to implement genomic discoveries into the clinic, rather than asking primary care doctors to figure it out. The team, including Chief Genomics Office Heidi Rehm, consists of genetic counselors, laboratory geneticists, research coordinators, and physicians who are working to determine how to use genetic risk scores to improve patient care.