Liyanage, U, MacGregor, S, Bishop, DT orcid.org/0000-0002-8752-8785 et al. (24 more authors) (2022) Multi-trait genetic analysis identifies auto-immune loci associated with cutaneous melanoma. The Journal of investigative dermatology, 142 (8). pp. 1607-1616. ISSN 0022-202X
Abstract
Genome-wide association studies (GWAS) have identified a number of risk loci for cutaneous melanoma. Cutaneous melanoma shares overlapping genetic risk (genetic correlation) with a number of other traits, including with its risk factors such as sunburn propensity. This genetic correlation can be exploited to identify additional cutaneous melanoma risk loci by multi-trait analysis of GWAS (MTAG).
We used bivariate LD-score regression to identify traits that are genetically correlated with clinically-confirmed cutaneous melanoma, and then used publicly available GWAS for these traits in a MTAG. MTAG allows GWAS to be combined while accounting for sample overlap and incomplete genetic correlation.
We identified a total of 74 genome-wide independent loci; 19 of them were not previously reported in the input cutaneous melanoma GWAS-meta-analysis. 55 of these loci were replicated (P < 0.05/74), Bonferroni corrected P -value in two independent cutaneous melanoma replication cohorts from Melanoma Institute Australia and 23andMe, Inc. Among the new cutaneous melanoma loci are ones that have also been associated with autoimmune traits including rs715199 near LPP, and rs10858023 near AP4B1.
Our analysis indicates genetic correlation between traits can be leveraged to identify new risk genes for cutaneous melanoma.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2021 The Authors. Published by Elsevier, Inc. on behalf of the Society for Investigative Dermatology. This is an open access article under the CC BY-NC-ND IGO license (http://creativecommons.org/licenses/by-nc-nd/3.0/igo/). |
Keywords: | Autoimmune; genetic correlation; Melanoma; Multi-trait analysis of GWAS; Pigmentation |
Dates: |
|
Institution: | The University of Leeds |
Funding Information: | Funder Grant number Cancer Research UK c588/A19167 |
Depositing User: | Symplectic Publications |
Date Deposited: | 16 Dec 2021 14:03 |
Last Modified: | 12 Jul 2022 10:11 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.jid.2021.08.449 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:181336 |