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

Akl C Fahed^#^{1

2

3

4

5}, Minxian Wang^#^{4

5}, Julian R Homburger^#⁶, Aniruddh P Patel^{1

2

3

4

5}, Alexander G Bick^{1

3

4

5}, Cynthia L Neben⁶, Carmen Lai⁶, Deanna Brockman^{1

4

5}, Anthony Philippakis^{4

5}, Patrick T Ellinor^{2

3

4

5}, Christopher A Cassa⁷, Matthew Lebo⁸, Kenney Ng⁹, Eric S Lander^{4

5

10

11}, Alicia Y Zhou⁶, Sekar Kathiresan^{2

3

5

12}, Amit V Khera^{13

14

15

16

17}

Affiliations

¹ Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
² Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
³ Department of Medicine, Harvard Medical School, Boston, MA, USA.
⁴ Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁵ Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁶ Color Genomics, Burlingame, CA, USA.
⁷ Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
⁸ Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Boston, MA, USA.
⁹ Center for Computational Health, IBM Research, Cambridge, MA, USA.
¹⁰ Department of Biology, MIT, Cambridge, MA, USA.
¹¹ Department of Systems Biology, Harvard Medical School, Boston, MA, USA.
¹² Verve Therapeutics, Cambridge, MA, USA.
¹³ Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA. avkhera@mgh.harvard.edu.
¹⁴ Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA. avkhera@mgh.harvard.edu.
¹⁵ Department of Medicine, Harvard Medical School, Boston, MA, USA. avkhera@mgh.harvard.edu.
¹⁶ Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA. avkhera@mgh.harvard.edu.
¹⁷ Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA. avkhera@mgh.harvard.edu.

^# Contributed equally.

PMID: 32820175
PMCID: PMC7441381
DOI: 10.1038/s41467-020-17374-3

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

Akl C Fahed et al. Nat Commun. 2020.

. 2020 Aug 20;11(1):3635.

doi: 10.1038/s41467-020-17374-3.

Authors

Affiliations

¹ Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
² Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
³ Department of Medicine, Harvard Medical School, Boston, MA, USA.
⁴ Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁵ Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁶ Color Genomics, Burlingame, CA, USA.
⁷ Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
⁸ Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Boston, MA, USA.
⁹ Center for Computational Health, IBM Research, Cambridge, MA, USA.
¹⁰ Department of Biology, MIT, Cambridge, MA, USA.
¹¹ Department of Systems Biology, Harvard Medical School, Boston, MA, USA.
¹² Verve Therapeutics, Cambridge, MA, USA.
¹³ Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA. avkhera@mgh.harvard.edu.
¹⁴ Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA. avkhera@mgh.harvard.edu.
¹⁵ Department of Medicine, Harvard Medical School, Boston, MA, USA. avkhera@mgh.harvard.edu.
¹⁶ Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA. avkhera@mgh.harvard.edu.
¹⁷ Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA. avkhera@mgh.harvard.edu.

^# Contributed equally.

PMID: 32820175
PMCID: PMC7441381
DOI: 10.1038/s41467-020-17374-3

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.

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Conflict of interest statement

A.C.F. is a consultant and holds equity in Goodpath. J.R.H., C.L.N., C.L., and A.Y.Z. are employees of Color Genomics. A.P. is a Venture Partner at GV, a subsidiary of Alphabet Corporation. P.T.E. is supported by a grant from Bayer AG to the Broad Institute focused on the genetics and therapeutics of cardiovascular diseases, and has served on advisory boards or consulted for Bayer AG, Quest Diagnostics, and Novartis. K.N. is an employee of IBM Research. E.S.L. serves on the Board of Directors for Codiak; serves on the Scientific Advisory Board of F-Prime Capital Partners and Third Rock Ventures; serves on the Board of Directors of the Innocence Project, Count Me In, and Biden Cancer Initiative; and serves on the Board of Trustees for the Parker Institute for Cancer Immunotherapy. S.K. is an employee of Verve Therapeutics, and holds equity in Verve Therapeutics, Maze Therapeutics, Catabasis, and San Therapeutics. He is a member of the scientific advisory boards for Regeneron Genetics Center and Corvidia Therapeutics; he has served as a consultant for Acceleron, Eli Lilly, Novartis, Merck, Novo Nordisk, Novo Ventures, Ionis, Alnylam, Aegerion, Haug Partners, Noble Insights, Leerink Partners, Bayer Healthcare, Illumina, Color Genomics, MedGenome, Quest, and Medscape; he reports patents related to a method of identifying and treating a person having a predisposition to or afflicted with cardiometabolic disease (20180010185) and a genetics risk predictor (20190017119). A.V.K. has served as a consultant to Sanofi, Medicines Company, Maze Pharmaceuticals, Navitor Pharmaceuticals, Verve Therapeutics, Amgen, and Color Genomics; received speaking fees from Illumina, the Novartis Institute for Biomedical Research; received sponsored research agreements from the Novartis Institute for Biomedical Research and IBM Research, and reports a patent related to a genetic risk predictor (20190017119). The remaining authors have no disclosures.

Figures

**Fig. 1. Interplay of monogenic and polygenic risk for coronary artery disease.**
a Risk of coronary artery disease by monogenic and polygenic risk strata (case-control study; n = 12,852). Carriers and noncarriers were stratified into three groups according to their polygenic score—low, intermediate, or high defined as the lowest quintile, the middle three quintiles, and the highest quintile of the polygenic score distribution, respectively. The odds ratio was assessed in a logistic regression model with age, sex, and the first four principal components of ancestry as covariates. Noncarriers with intermediate polygenic score served as the reference group. The black boxes indicate the adjusted odds ratio. The horizontal lines around the black boxes indicate the 95% confidence intervals. b Predicted odds ratio for coronary artery disease in each percentile (dots) of the polygenic score distribution for carriers (blue) and noncarriers (black) of familial hypercholesterolemia variants in the cohort study derived from the UK Biobank (n = 48,812). Noncarriers with median polygenic score served as the reference group. c Predicted probability of coronary artery disease by age 75 years in each percentile (dots) of the polygenic score distribution for carriers (blue) and noncarriers (black) of familial hypercholesterolemia variants in the cohort study derived from the UK Biobank (n = 48,812). The shaded area around the dots represents the 95% confidence interval. The horizontal dashed lines show the probability of disease for people with average polygenic risk score. FH familial hypercholesterolemia. p-values in the figure were estimated by the Wald Test. Statistical significance was set at p < .05, and two-sided p values were used.

**Fig. 2. Interplay of monogenic and polygenic risk for breast cancer.**
a Risk of breast cancer by monogenic and polygenic strata (case-control study; n = 19,264). Carriers and noncarriers were stratified into three groups according to their polygenic score—low, intermediate, or high defined as the lowest quintile, the middle three quintiles, and the highest quintile of the polygenic score distribution, respectively. The odds ratio was assessed in a logistic regression model with age and the first four principal components of ancestry as covariates. Noncarriers with intermediate polygenic score served as the reference group. The black boxes indicate the adjusted odds ratio. The horizontal lines around the black boxes indicate the 95% confidence intervals. b Predicted odds ratio for breast cancer in each percentile (dots) of the polygenic score distribution for carriers (blue) and noncarriers (black) of hereditary breast and ovarian cancer variants in the cohort study derived from the UK Biobank (n = 26,597). Noncarriers with median polygenic score served as the reference group. c Predicted probability of coronary artery disease by age 75 years in each percentile (dots) of the polygenic score distribution for carriers (blue) and noncarriers (black) of hereditary breast and ovarian cancer variants in the cohort study derived from the UK Biobank (n = 26,597). The shaded area around the dots represents the 95% confidence interval. The horizontal dashed lines show the probability of disease for people with average polygenic risk score. HBOC hereditary breast and ovarian cancer. p-values in the figure were estimated by the Wald Test. Statistical significance was set at p < .05, and two-sided p values were used.

**Fig. 3. Interplay of monogenic and polygenic risk for colorectal cancer.**
a Predicted odds ratio for colorectal cancer in each percentile (dots) of the polygenic score distribution for carriers (blue) and noncarriers (black) of Lynch syndrome variants in the cohort study derived from the UK Biobank (n = 48,812). Noncarriers with median polygenic score served as the reference group. b Predicted probability of colorectal cancer by age 75 years in each percentile (dots) of the polygenic score distribution for carriers (blue) and noncarriers (black) of Lynch syndrome variants in the cohort study derived from the UK Biobank (n = 48,812). The shaded area around the dots represents the 95% confidence interval. The horizontal dashed lines show the probability of disease for people with average polygenic risk score.

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References

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

Affiliations

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

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

Publication types

MeSH terms

Grants and funding

LinkOut - more resources

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