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Cust AE, Drummond M, Kanetsky PA, Goldstein AM, Barrett JH, MacGregor S, Law MH, Iles MM, Bui M, Hopper JL, Brossard M, Demenais F, Taylor JC, Hoggart C, Brown KM, Landi MT, Newton-Bishop JA, Mann GJ, Bishop DT. Assessing the Incremental Contribution of Common Genomic Variants to Melanoma Risk Prediction in Two Population-Based Studies. J Invest Dermatol 2018; 138:2617-2624. [PMID: 29890168 PMCID: PMC6249137 DOI: 10.1016/j.jid.2018.05.023] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Revised: 05/29/2018] [Accepted: 05/30/2018] [Indexed: 01/02/2023]
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 United Kingdom (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, center, and ancestry. Adding the polygenic risk score to a model with traditional risk factors increased the area under the 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.
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Affiliation(s)
- Anne E Cust
- Cancer Epidemiology and Prevention Research, Sydney School of Public Health, The University of Sydney, Sydney, Australia; Melanoma Institute Australia, The University of Sydney, Sydney, Australia.
| | - Martin Drummond
- Cancer Epidemiology and Prevention Research, Sydney School of Public Health, The University of Sydney, Sydney, Australia; Melanoma Institute Australia, The University of Sydney, Sydney, Australia
| | - Peter A Kanetsky
- Department of Cancer Epidemiology, Moffitt Cancer Center and Research Institute, Tampa, Florida, USA
| | - Alisa M Goldstein
- Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Jennifer H Barrett
- Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
| | - Stuart MacGregor
- Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Matthew H Law
- Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Mark M Iles
- Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
| | - Minh Bui
- Centre for Epidemiology and Biostatistics, Melbourne School of Population Health, University of Melbourne, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population Health, University of Melbourne, Australia
| | - Myriam Brossard
- INSERM, UMR 946, Genetic Variation and Human Diseases Unit, Paris, France; Institut Universitaire d'Hématologie, Université Paris Diderot, Sorbonne Paris Cité, Paris, France
| | - Florence Demenais
- INSERM, UMR 946, Genetic Variation and Human Diseases Unit, Paris, France; Institut Universitaire d'Hématologie, Université Paris Diderot, Sorbonne Paris Cité, Paris, France
| | - John C Taylor
- Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
| | - Clive Hoggart
- Section of Paediatrics, Division of Infectious Diseases, Department of Medicine, Imperial College London, London, UK
| | - Kevin M Brown
- Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Maria Teresa Landi
- Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Julia A Newton-Bishop
- Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
| | - Graham J Mann
- Melanoma Institute Australia, The University of Sydney, Sydney, Australia; Centre for Cancer Research, Westmead Institute for Medical Research, The University of Sydney, Sydney, Australia
| | - D Timothy Bishop
- Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
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