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评估常见基因组变异在两项基于人群的研究中对黑色素瘤风险预测的附加贡献。

Assessing the Incremental Contribution of Common Genomic Variants to Melanoma Risk Prediction in Two Population-Based Studies.

机构信息

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.

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.

出版信息

J Invest Dermatol. 2018 Dec;138(12):2617-2624. doi: 10.1016/j.jid.2018.05.023. Epub 2018 Jun 8.

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.

摘要

目前尚不清楚基因组和传统(表型和环境)风险因素在预测黑色素瘤风险方面的重叠程度。我们评估了常见基因组变异(在色素沉着、痣和其他途径中)及其与传统风险因素的重叠程度对黑色素瘤风险的增量贡献,使用了来自澳大利亚(n=1035)和英国(n=1460)的两项基于人群的病例对照研究的数据,这些研究使用了相同的问卷。多基因风险评分来自与黑色素瘤相关的 21 个基因区域,比值比来自已发表的荟萃分析。逻辑回归模型调整了年龄、性别、中心和祖源。在包含传统风险因素的模型中加入多基因风险评分,使澳大利亚的受试者工作特征曲线(ROC)下面积(AUC)增加了 2.3%(P=0.003),使利兹的 AUC 增加了 2.8%(P=0.002)。色素沉着途径中的基因变异,特别是 MC1R,是导致增量改善的主要原因。在多基因和传统三分位风险评分的交叉列表中,59%(澳大利亚)和 49%(利兹)的参与者被归入相同(一致)的三分位。在传统低风险的参与者中,9%(澳大利亚)和 21%(利兹)具有高多基因风险。尽管没有传统的表型风险特征,但基因组变异的检测可以识别出易患黑色素瘤的人群。

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