Cust, AE, Drummond, M, Kanetsky, PA et al. (18 more authors) (2018) Assessing the incremental contribution of common genomic variants to melanoma risk prediction in two population-based studies. Journal of Investigative Dermatology, 138 (12). pp. 2617-2624. ISSN 0022-202X
Abstract
It is unclear to what degree genomic and traditional (phenotypic and environmental) risk factors overlap in their prediction of melanoma risk. We evaluated the incremental contribution of common genomic variants (in pigmentation, nevus and other pathways) and their overlap with traditional risk factors, using data from two population-based case-control studies from Australia (n=1,035) and the UK (n=1,460) that used the same questionnaires. Polygenic risk scores were derived from 21 gene regions associated with melanoma and odds ratios from published meta-analyses. Logistic regression models were adjusted for age, sex, centre and ancestry. Adding the polygenic risk score to a model with traditional risk factors increased the area under receiver operating characteristic curve (AUC) by 2.3% (p=0.003) for Australia and by 2.8% (p=0.002) for Leeds. Gene variants in the pigmentation pathway, particularly MC1R, were responsible for most of the incremental improvement. In a cross-tabulation of polygenic by traditional tertile risk scores, 59% (Australia) and 49% (Leeds) of participants were categorized in the same (concordant) tertile. Of participants with low traditional risk, 9% (Australia) and 21% (Leeds) had high polygenic risk. Testing of genomic variants can identify people who are susceptible to melanoma despite not having a traditional phenotypic risk profile.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2018 The Authors. Published by Elsevier, Inc. on behalf of the Society for Investigative Dermatology. Under a Creative Commons license (https://creativecommons.org/licenses/by/4.0/) |
Keywords: | genomic; genetic; discrimination; risk prediction; pigmentation; nevi; melanoma; phenotype |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > Institute of Molecular Medicine (LIMM) (Leeds) > Section of Epidemiology and Biostatistics (Leeds) |
Funding Information: | Funder Grant number National Institute of Health - NIH (PHS) 10-17751-99-01-G5 Cancer Research UK c588/A19167 |
Depositing User: | Symplectic Publications |
Date Deposited: | 06 Jun 2018 16:08 |
Last Modified: | 04 Dec 2018 11:23 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.jid.2018.05.023 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:131554 |