Joint effect of multiple common SNPs predicts melanoma susceptibility.
Abstract
Single genetic variants discovered so far have been only weakly associated with melanoma.
This study aims to use multiple single nucleotide polymorphisms (SNPs) jointly to
obtain a larger genetic effect and to improve the predictive value of a conventional
phenotypic model. We analyzed 11 SNPs that were associated with melanoma risk in previous
studies and were genotyped in MD Anderson Cancer Center (MDACC) and Harvard Medical
School investigations. Participants with ≥15 risk alleles were 5-fold more likely
to have melanoma compared to those carrying ≤6. Compared to a model using the most
significant single variant rs12913832, the increase in predictive value for the model
using a polygenic risk score (PRS) comprised of 11 SNPs was 0.07(95% CI, 0.05-0.07).
The overall predictive value of the PRS together with conventional phenotypic factors
in the MDACC population was 0.69 (95% CI, 0.64-0.69). PRS significantly improved the
risk prediction and reclassification in melanoma as compared with the conventional
model. Our study suggests that a polygenic profile can improve the predictive value
of an individual gene polymorphism and may be able to significantly improve the predictive
value beyond conventional phenotypic melanoma risk factors.
Type
Journal articleSubject
HumansMelanoma
Genetic Predisposition to Disease
Computational Biology
Phenotype
Polymorphism, Single Nucleotide
Middle Aged
Female
Male
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https://hdl.handle.net/10161/17998Published Version (Please cite this version)
10.1371/journal.pone.0085642Publication Info
Fang, Shenying; Han, Jiali; Zhang, Mingfeng; Wang, Li-e; Wei, Qingyi; Amos, Christopher
I; & Lee, Jeffrey E (2013). Joint effect of multiple common SNPs predicts melanoma susceptibility. PloS one, 8(12). pp. e85642. 10.1371/journal.pone.0085642. Retrieved from https://hdl.handle.net/10161/17998.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Qingyi Wei
Professor in Population Health Sciences
Qingyi Wei, MD, PhD, Professor in the Department of Medicine, is Associate Director
for Cancer Control and Population Sciences, Co-leader of CCPS and Co-leader of Epidemiology
and Population Genomics (Focus Area 1). He is a professor of Medicine and an internationally
recognized epidemiologist focused on the molecular and genetic epidemiology of head
and neck cancers, lung cancer, and melanoma. His research focuses on biomarkers and
genetic determinants for the DNA repair deficient phenotype and

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