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Assessing the Incremental Contribution of Common Genomic Variants to Melanoma Risk Prediction in Two Population-Based Studies.
Cust, Anne E; Drummond, Martin; Kanetsky, Peter A; Goldstein, Alisa M; Barrett, Jennifer H; MacGregor, Stuart; Law, Matthew H; Iles, Mark M; Bui, Minh; Hopper, John L; Brossard, Myriam; Demenais, Florence; Taylor, John C; Hoggart, Clive; Brown, Kevin M; Landi, Maria Teresa; Newton-Bishop, Julia A; Mann, Graham J; Bishop, D Timothy.
Afiliação
  • Cust AE; 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. Electronic address: anne.cust@sydney.edu.au.
  • Drummond M; 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.
  • Kanetsky PA; Department of Cancer Epidemiology, Moffitt Cancer Center and Research Institute, Tampa, Florida, USA.
  • Goldstein AM; Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA.
  • Barrett JH; Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK.
  • MacGregor S; Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
  • Law MH; Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
  • Iles MM; Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK.
  • Bui M; Centre for Epidemiology and Biostatistics, Melbourne School of Population Health, University of Melbourne, Australia.
  • Hopper JL; Centre for Epidemiology and Biostatistics, Melbourne School of Population Health, University of Melbourne, Australia.
  • Brossard M; INSERM, UMR 946, Genetic Variation and Human Diseases Unit, Paris, France; Institut Universitaire d'Hématologie, Université Paris Diderot, Sorbonne Paris Cité, Paris, France.
  • Demenais F; INSERM, UMR 946, Genetic Variation and Human Diseases Unit, Paris, France; Institut Universitaire d'Hématologie, Université Paris Diderot, Sorbonne Paris Cité, Paris, France.
  • Taylor JC; Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK.
  • Hoggart C; Section of Paediatrics, Division of Infectious Diseases, Department of Medicine, Imperial College London, London, UK.
  • Brown KM; Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA.
  • Landi MT; Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA.
  • Newton-Bishop JA; Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK.
  • Mann GJ; Melanoma Institute Australia, The University of Sydney, Sydney, Australia; Centre for Cancer Research, Westmead Institute for Medical Research, The University of Sydney, Sydney, Australia.
  • Bishop DT; Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK.
J Invest Dermatol ; 138(12): 2617-2624, 2018 12.
Article em En | MEDLINE | ID: mdl-29890168
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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Cutâneas / Grupos Populacionais / Patologia Molecular / Melanoma Tipo de estudo: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Aspecto: Determinantes_sociais_saude Limite: Adolescent / Adult / Aged / Female / Humans / Male / Middle aged País/Região como assunto: Europa / Oceania Idioma: En Revista: J Invest Dermatol Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Cutâneas / Grupos Populacionais / Patologia Molecular / Melanoma Tipo de estudo: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Aspecto: Determinantes_sociais_saude Limite: Adolescent / Adult / Aged / Female / Humans / Male / Middle aged País/Região como assunto: Europa / Oceania Idioma: En Revista: J Invest Dermatol Ano de publicação: 2018 Tipo de documento: Article