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J Invest Dermatol. 2016 Mar;136(3):690-5. doi: 10.1016/j.jid.2015.12.007. Epub 2015 Dec 14.

Prediction of Melanoma Risk in a Southern European Population Based on a Weighted Genetic Risk Score.

Author information

1
1st Department of Dermatology, Andreas Syggros Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece.
2
Clinical and Molecular Epidemiology Unit, Department of Hygiene and Epidemiology, School of Medicine, University of Ioannina, Ioannina, Greece, GR.
3
Blood Donation Unit, Laikon Hospital, Athens, Greece.
4
Department of Internal Medicine, University of Athens, Laikon Hospital, Athens, Greece.
5
Biomedical Informatics Unit, Biomedical Research Foundation, Academy of Athens, Athens, Greece.
6
Platform for Genome Analytics, Institutes of Neurogenetics & Integrative and Experimental Genomics, University of Lübeck, Lübeck, Germany; School of Public Health, Faculty of Medicine, Imperial College London, London, United Kingdom.
7
Institute of Neurogenetics, University of Lübeck, Lübeck, Germany.
8
Stanford Prevention Research Center, Department of Medicine and Department of Health Research and Policy, Stanford University School of Medicine, and Department of Statistics, Stanford University School of Humanities and Sciences, Stanford, USA.
9
Clinical and Molecular Epidemiology Unit, Department of Hygiene and Epidemiology, School of Medicine, University of Ioannina, Ioannina, Greece, GR; Department of Epidemiology and Biostatistics, Imperial College London, St. Mary's Campus, London, United Kingdom.
10
1st Department of Dermatology, Andreas Syggros Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece. Electronic address: alstrat@hol.gr.

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.

PMID:
27015455
DOI:
10.1016/j.jid.2015.12.007
[Indexed for MEDLINE]
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