1. Prediction of Melanoma Risk in a Southern European Population Based on a Weighted Genetic Risk Score.
- Author
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Kypreou KP, Stefanaki I, Antonopoulou K, Karagianni F, Ntritsos G, Zaras A, Nikolaou V, Kalfa I, Chasapi V, Polydorou D, Gogas H, Spyrou GM, Bertram L, Lill CM, Ioannidis JPA, Antoniou C, Evangelou E, and Stratigos AI
- Subjects
- Analysis of Variance, Cross-Sectional Studies, Female, Genetic Loci, Genome-Wide Association Study, Genotype, Greece epidemiology, Humans, Incidence, Logistic Models, Male, Melanoma pathology, Predictive Value of Tests, Prognosis, Risk Assessment, Skin Neoplasms pathology, Gene Expression Regulation, Neoplastic, Melanoma epidemiology, Melanoma genetics, Polymorphism, Single Nucleotide, Skin Neoplasms epidemiology, Skin Neoplasms genetics
- Abstract
Many single nucleotide polymorphisms (SNPs) have been described as putative risk factors for melanoma. The aim of our study was to validate the most prominent genetic risk loci in an independent Greek melanoma case-control dataset and to assess their cumulative effect solely or combined with established phenotypic risk factors on individualized risk prediction. We genotyped 59 SNPs in 800 patients and 800 controls and tested their association with melanoma using logistic regression analyses. We constructed a weighted genetic risk score (GRSGWS) based on SNPs that showed genome-wide significant (GWS) association with melanoma in previous studies and assessed their impact on risk prediction. Fifteen independent SNPs from 12 loci were significantly associated with melanoma (P < 0.05). Risk score analysis yielded an odds ratio of 1.36 per standard deviation increase of the GRSGWS (P = 1.1 × 10(-7)). Individuals in the highest 20% of the GRSGWS had a 1.88-fold increase in melanoma risk compared with those in the middle quintile. By adding the GRSGWS to a phenotypic risk model, the C-statistic increased from 0.764 to 0.775 (P = 0.007). In summary, the GRSGWS is associated with melanoma risk and achieves a modest improvement in risk prediction when added to a phenotypic risk model., (Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.)
- Published
- 2016
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