Xia Jiang, Harvard University
Hilary K. Finucane, Harvard University
Fredrick R. Schumacher, Case Western Reserve University
Stephanie L. Schmit, H. Lee Moffitt Cancer Center and Research Institute
Jonathan P. Tyrer, University of Cambridge, UK
Younghun Han, Dartmouth College
Kyriaki Michailidou, University of Cambridge, UK
Corina Lesseur, International Agency for Research on Cancer, France
Karoline B. Kuchenbaecker, University College London, UK
Joe Dennis, University of Cambridge, UK
David V. Conti, University of Southern California
Graham Casey, University of Virginia
Mia M. Gaudet, American Cancer Society
Jeroen R. Huyghe, Fred Hutchinson Cancer Research Center
Demetrius Albanes, National Cancer Institute
Melinda C. Aldrich, Vanderbilt University
Angeline S. Andrew, Dartmouth-Hitchcock Medical Center
Irene L. Andrulis, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Canada
Hoda Anton-Culver, University of California - Irvine
Antonis C. Antoniou, University of Cambridge, UK
Natalia N. Antonenkova, N. N. Alexandrov Research Institute of Oncology and Medical Radiology, Belarus
Susanne M. Arnold, University of KentuckyFollow
Kristan J. Aronson, Queen’s University, Canada
Banu K. Arun, The University of Texas MD Anderson Cancer Center
Elisa V. Bandera, Rutgers Cancer Institute of New Jersey
Rosa B. Barkardottir, Landspitali, Iceland
Daniel R. Barnes, University of Cambridge, UK
Jyotsna Batra, Australian Prostate Cancer Research Centre, Australia
Matthias W. Beckmann, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
Javier Benitez, Spanish National Cancer Research Centre, Spain


Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (rg = 0.57, p = 4.6 × 10−8), breast and ovarian cancer (rg = 0.24, p = 7 × 10−5), breast and lung cancer (rg = 0.18, p =1.5 × 10−6) and breast and colorectal cancer (rg = 0.15, p = 1.1 × 10−4). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.

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Notes/Citation Information

Published in Nature Communications, v. 10, article no. 431, p. 1-23.

© The Author(s) 2019

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit

Due to the large number of authors, only the first 30 and the authors affiliated with the University of Kentucky are listed in the author section above. For the complete list of authors, please download this article or visit:

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Funding Information

The breast cancer genome-wide association analyses: BCAC is funded by Cancer Research UK [C1287/A16563, C1287/A10118], the European Union’s Horizon 2020 Research and Innovation Programme (grant numbers 634935 and 633784 for BRIDGES and B-CAST, respectively), and by the European Community’s Seventh Framework Programme under grant agreement number 223175 (grant number HEALTH-F2-2009-223175) (COGS).

Due to the large number of funding sources, only the first few are listed in this section. For the complete list of funding sources, please download this article.

Related Content

The datasets generated during and/or analyzed during the current study are available from the authors on request. Breast cancer: summary results for all variants are available at Requests for further data should be made through the Data Access Coordination Committee ( Ovarian cancer: summary results are available from the Ovarian Cancer Association Consortium (OCAC) ( Requests for further data can be made to the Data Access Coordination Committee ( Prostate cancer: summary results are publicly available at the PRACTICAL website ( Lung cancer: genotype data for lung cancer are available at the database of Genotypes and Phenotypes (dbGaP) under accession phs001273.v1.p1. Readers interested in obtaining a copy of the original data can do so by completing the proposal request form at Head/neck cancer: genotype data for the oral and pharyngeal OncoArray study have been deposited at the database of Genotypes and Phenotypes (dbGaP) under accession phs001202.v1.p1. Colorectal cancer: genotype data have been deposited at the database of Genotypes and Phenotypes (dbGaP) under accession number phs001415.v1.p1 and phs001078.v1.p1.

Supplementary Information accompanies this paper at 018-08054-4.

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Supplementary Information

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Description of Additional Supplementary Files

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Supplementary Data 1

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Supplementary Data 2

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Supplementary Data 3

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Supplementary Data 4

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Supplementary Data 5

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Reporting Summary

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Peer Review Files