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PLoS One. 2013 Dec 31;8(12):e85642. doi: 10.1371/journal.pone.0085642. eCollection 2013.

Joint effect of multiple common SNPs predicts melanoma susceptibility.

Author information

  • 1Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
  • 2Department of Dermatology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America ; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America ; Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America.
  • 3Department of Dermatology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
  • 4Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
  • 5Geisel College of Medicine, Community and Family Medicine, Dartmouth College, Lebanon, New Hampshire, United States of America.

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.

PMID:
24392023
[PubMed - in process]
PMCID:
PMC3877376
Free PMC Article

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