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Polygenic Background Modifies Penetrance of Monogenic Variants for Tier 1 Genomic Conditions

Written by Malorye Branca | Mar 9, 2021 1:54:49 PM

Primary reference: Fahed et al. Nature Communications, August 20, 2020.

Genetic conditions:  Familial hypercholesterolemia, hereditary breast and ovarian cancer, Lynch syndrome and others.

"Genetic variation can predispose to disease both through monogenic risk variants that disrupt a physiologic pathway with large effect on disease and polygenic risk that involves many variants of small effect in different pathways," write a group of researchers from The Broad Institute. However, there are still many questions about how monogenic and polygenic risk interact. They point out that, for example, common variant background affects the age of disease onset among carriers of high-risk trinucleotide repeats predisposing to Huntington's disease.

To address this question, they studied 80,928 individuals to examine whether polygenic background can modify penetrance of disease in tier 1 genomic conditions such as familial hypercholesterolemia, hereditary breast and ovarian cancer, and Lynch syndrome.

Among carriers of a monogenic risk variant, they estimate substantial gradients in disease risk based on polygenic background: "The probability of disease by age 75 ranged from 17% to 78% for coronary artery disease, 13% to 76% for breast cancer, and 11% to 80% for colon cancer". The researchers propose that: "accounting for polygenic background is likely to increase accuracy of risk estimation for individuals who inherit a monogenic risk variant."

 

Additional resource:

Polygenic risk scores: from research tools to clinical instruments. Lewis and Vassos. Genome Medicine, May 2020. According to these researchers: "Polygenic risk scores have been widely applied in research studies, confirming the association between the scores and disease status, but their clinical utility has yet to be established." They propose that one example where PRS risk scores my be useful is in "cohorts where there is a higher probability of disease. In this review they consider how PRS may be useful along the disease trajectory, giving examples and discussing obstacles.

 

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