Rare penetrant mutations confer severe risk of common diseases

Author:

Fiziev Petko P.1ORCID,McRae Jeremy1ORCID,Ulirsch Jacob C.1ORCID,Dron Jacqueline S.23ORCID,Hamp Tobias1,Yang Yanshen1,Wainschtein Pierrick14ORCID,Ni Zijian5ORCID,Schraiber Joshua G.1,Gao Hong1ORCID,Cable Dylan6,Field Yair1ORCID,Aguet Francois1ORCID,Fasnacht Marc1,Metwally Ahmed1ORCID,Rogers Jeffrey78ORCID,Marques-Bonet Tomas9101112ORCID,Rehm Heidi L.2313ORCID,O'Donnell-Luria Anne31314ORCID,Khera Amit V.2315ORCID,Farh Kyle Kai-How1ORCID

Affiliation:

1. Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA 92122, USA.

2. Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA.

3. Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.

4. Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia.

5. Department of Statistics, University of Wisconsin–Madison, Madison, WI 53706, USA.

6. Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology (MIT), Cambridge, MA 02142, USA.

7. Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.

8. Wisconsin National Primate Research Center, University of Wisconsin–Madison, Madison, WI 53715, USA.

9. Institute of Evolutionary Biology (UPF-CSIC), 08003 Barcelona, Spain.

10. Catalan Institution of Research and Advanced Studies (ICREA), 08010 Barcelona, Spain.

11. CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain.

12. Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain.

13. Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA.

14. Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA 02115, USA.

15. Verve Therapeutics, Cambridge, MA 02215, USA.

Abstract

We examined 454,712 exomes for genes associated with a wide spectrum of complex traits and common diseases and observed that rare, penetrant mutations in genes implicated by genome-wide association studies confer ~10-fold larger effects than common variants in the same genes. Consequently, an individual at the phenotypic extreme and at the greatest risk for severe, early-onset disease is better identified by a few rare penetrant variants than by the collective action of many common variants with weak effects. By combining rare variants across phenotype-associated genes into a unified genetic risk model, we demonstrate superior portability across diverse global populations compared with common-variant polygenic risk scores, greatly improving the clinical utility of genetic-based risk prediction.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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