The University of Southampton
University of Southampton Institutional Repository

Shared heritability and functional enrichment across six solid cancers

Shared heritability and functional enrichment across six solid cancers
Shared heritability and functional enrichment across six solid cancers
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.
1-23
Eccles, Diana
5b59bc73-11c9-4cf0-a9d5-7a8e523eee23
Jiang, Xia
c9cfc5ce-4db4-4708-87ec-90c4cb7cee7d
et al.
Eccles, Diana
5b59bc73-11c9-4cf0-a9d5-7a8e523eee23
Jiang, Xia
c9cfc5ce-4db4-4708-87ec-90c4cb7cee7d

Jiang, Xia , et al. (2019) Shared heritability and functional enrichment across six solid cancers. Nature Communications, 10, 1-23, [431]. (doi:10.1038/s41467-018-08054-4).

Record type: Article

Abstract

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.

Text
Cancer Gen Corr Main text - Accepted Manuscript
Download (283kB)
Text
s41467-018-08054-4 - Version of Record
Available under License Creative Commons Attribution.
Download (3MB)

More information

Accepted/In Press date: 10 December 2018
e-pub ahead of print date: 25 January 2019

Identifiers

Local EPrints ID: 427919
URI: http://eprints.soton.ac.uk/id/eprint/427919
PURE UUID: 9d53c6d5-f9b4-47fa-9171-e9ccaa74a9cb
ORCID for Diana Eccles: ORCID iD orcid.org/0000-0002-9935-3169

Catalogue record

Date deposited: 04 Feb 2019 17:30
Last modified: 16 Mar 2024 07:27

Export record

Altmetrics

Contributors

Author: Diana Eccles ORCID iD
Author: Xia Jiang
Corporate Author: et al.

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×