调查邻里社会经济地位和种系遗传对前列腺癌风险的作用

Jonathan Judd, Jeffrey P Spence, Jonathan K Pritchard, Linda Kachuri, John S Witte
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引用次数: 0

摘要

背景:遗传因素在前列腺癌(PCa)的发病过程中起着重要作用,多基因风险评分(PRS)可预测不同遗传背景下的发病风险。然而,目前几乎没有令人信服的 PCa 可改变因素,而且人们对这些因素与遗传风险之间的潜在相互作用知之甚少。我们分析了英国生物库(UKB)队列中欧洲和非洲血统的 PC 病例(6155 例)和对照组(98257 例),以评估邻里社会经济状况(nSES)在 PCa 风险中的作用及其如何与 PRS 相互影响。方法:我们评估了包含 269 个遗传变异的多家系 PCa PRS,以了解英国生物库中种系遗传学与 PCa 的关联。我们使用英国贫困指数(EnglishIndices of Deprivation)--一套量化地理区域内资源匮乏程度的有效指标--进行了逻辑回归,以研究nSES贫困程度、PCa PRS和PCa之间的主效应和相互作用。结果发现PCa PRS 与 PCa 密切相关(OR=2.04;95%CI=2.00-2.09;P<0.001)。此外,nSES 贫困指数与 PCa 呈反向关系:就业(OR=0.91;95%CI=0.86-0.96;P<;0.001)、教育(OR=0.94;95%CI=0.83-0.98;P<;0.001)、健康(OR=0.91;95%CI=0.86-0.96;P<;0.001)和收入(OR=0.91;95%CI=0.86-0.96;P<;0.001)。除汤森指数(P=0.03)外,PRS效应在不同社会经济剥夺指数之间几乎没有异质性:我们再次证实遗传是 PCa 的风险因素,并确定了影响 PCa 检测的 nSES 贫乏领域,这些领域可能与 PCa 风险因素之一的环境暴露相关。这些发现还表明,nSES 和 PCa 的遗传风险因素是独立作用的。
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Investigating the Role of Neighborhood Socioeconomic Status and Germline Genetics on Prostate Cancer Risk
Background: Genetic factors play an important role in prostate cancer (PCa) development with polygenic risk scores (PRS) predicting disease risk across genetic ancestries. However, there are few convincing modifiable factors for PCa and little is known about their potential interaction with genetic risk. We analyzed incident PCa cases (n=6,155) and controls (n=98,257) of European and African ancestry from the UK Biobank (UKB) cohort to evaluate the role of neighborhood socioeconomic status (nSES)-and how it may interact with PRS-on PCa risk. Methods: We evaluated a multi-ancestry PCa PRS containing 269 genetic variants to understand the association of germline genetics with PCa in UKB. Using the English Indices of Deprivation, a set of validated metrics that quantify lack of resources within geographical areas, we performed logistic regression to investigate the main effects and interactions between nSES deprivation, PCa PRS, and PCa. Results: The PCa PRS was strongly associated with PCa (OR=2.04; 95%CI=2.00-2.09; P<0.001). Additionally, nSES deprivation indices were inversely associated with PCa: employment (OR=0.91; 95%CI=0.86-0.96; P<0.001), education (OR=0.94; 95%CI=0.83-0.98; P<0.001), health (OR=0.91; 95%CI=0.86-0.96; P<0.001), and income (OR=0.91; 95%CI=0.86-0.96; P<0.001). The PRS effects showed little heterogeneity across nSES deprivation indices, except for the Townsend Index (P=0.03) Conclusions: We reaffirmed genetics as a risk factor for PCa and identified nSES deprivation domains that influence PCa detection and are potentially correlated with environmental exposures that are a risk factor for PCa. These findings also suggest that nSES and genetic risk factors for PCa act independently.
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