Polygenic background modifies penetrance of monogenic variants for tier 1 genomic conditions

Akl C. Fahed, Minxian Wang, Julian R. Homburger, Aniruddh P. Patel, Alexander G. Bick, Cynthia L. Neben, Carmen Lai, Deanna Brockman, Anthony Philippakis, Patrick T. Ellinor, Christopher A. Cassa, Matthew Lebo, Kenney Ng, Eric S. Lander, Alicia Y. Zhou, Sekar Kathiresan and Amit V. Khera ()
Additional contact information
Akl C. Fahed: Massachusetts General Hospital
Minxian Wang: Broad Institute of MIT and Harvard
Julian R. Homburger: Color Genomics
Aniruddh P. Patel: Massachusetts General Hospital
Alexander G. Bick: Massachusetts General Hospital
Cynthia L. Neben: Color Genomics
Carmen Lai: Color Genomics
Deanna Brockman: Massachusetts General Hospital
Anthony Philippakis: Broad Institute of MIT and Harvard
Patrick T. Ellinor: Massachusetts General Hospital
Christopher A. Cassa: Harvard Medical School
Matthew Lebo: Partners HealthCare Personalized Medicine
Kenney Ng: IBM Research
Eric S. Lander: Broad Institute of MIT and Harvard
Alicia Y. Zhou: Color Genomics
Sekar Kathiresan: Massachusetts General Hospital
Amit V. Khera: Massachusetts General Hospital

Nature Communications, 2020, vol. 11, issue 1, 1-9

Abstract: Abstract Genetic variation can predispose to disease both through (i) monogenic risk variants that disrupt a physiologic pathway with large effect on disease and (ii) polygenic risk that involves many variants of small effect in different pathways. Few studies have explored the interplay between monogenic and polygenic risk. Here, we study 80,928 individuals to examine whether polygenic background can modify penetrance of disease in tier 1 genomic conditions — familial hypercholesterolemia, hereditary breast and ovarian cancer, and Lynch syndrome. Among carriers of a monogenic risk variant, we estimate substantial gradients in disease risk based on polygenic background — the probability of disease by age 75 years ranged from 17% to 78% for coronary artery disease, 13% to 76% for breast cancer, and 11% to 80% for colon cancer. We propose that accounting for polygenic background is likely to increase accuracy of risk estimation for individuals who inherit a monogenic risk variant.

Date: 2020
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DOI: 10.1038/s41467-020-17374-3

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