Precision Prostate Cancer Screening with Genetically Adjusted Prostate-Specific Antigen Levels

摘要 美国预防服务工作组(USPSTF)最近对前列腺特异性药物的使用情况进行了评级 抗原(PSA)筛查前列腺癌(PCA)的A级：“对于55岁至69岁的男性，决定 定期接受基于PSA的前列腺癌筛查应该是个人的，应该包括 与他们的临床医生讨论筛查的潜在好处和坏处。USPSTF决定PSA 目前的筛查不足以广泛实施。因此，重要的是询问 质疑如何改进PSA筛查以减少过度诊断、过度治疗和前列腺癌死亡率。 有证据表明，将遗传因素纳入PSA筛查决定可以做到这一点。 PSA水平已经被证明是高度可遗传的，但相关的遗传变异已经被证明是 到目前为止发现的只解释了其中的一些变化。此外，解释的差异甚至更小，当 与非欧洲人打交道。如果我们能确定哪些遗传因素使个体容易患上 独立于前列腺癌的高PSA水平，我们可以将其作为新的PSA筛查的一部分来解释 范例。我们建议通过一个大型项目来实现这一点，该项目结合了17项男性研究的数据 无论有没有PCA，所有人都有关于PSA水平和全基因组变异的数据。总而言之， 研究包括653,076名男性，其中包括106,326名非洲裔男性，35,683名拉丁裔男性，以及 亚洲血统的10,001人。在目标1中，我们将进行一项多祖先全基因组关联研究(Gwas) PSA水平是以前任何此类分析的20倍，以及有史以来第一个转录组- PSA水平的广谱关联研究(TWAS)。然后，我们将利用我们样本的多血统性质来 通过精细作图发现与PSA相关的其他遗传变异。在目标2中，我们将评估 GWAS中发现的与PSA相关的SNPs和PSA相关基因的独立性 使用条件分析在第三世界科学院发现的。然后我们将区分遗传因素 使用条件分析和调解分析与PSA和PCA相关的项目。基于 这些发现，我们将创建和测试PSA水平的多基因风险分数，这些分数结合了相关的基因 这些因素共同构成了单一的、强有力的措施。最后，在目标3中，我们将使用测量的PSA水平和基因 考虑PSA中的结构性、非主成分变异性的因素，以开发更准确的模型 预测PCA结果。这些模型将使我们能够评估额外整合基因的好处 关于决定男性是否应该接受前列腺活检的信息。我们的总体目标是 承诺在提高筛查效益的同时减少筛查危害。在翻译中，临床医生和 患者可以做出更明智的决定，从而减少不必要的程序和诊断，以及 防止不良后果的发生。

ABSTRACT The United States Preventive Services Task Force (USPSTF) recently graded the use of prostate-specific antigen (PSA) to screen for prostate cancer (PCa) a “C”: “For men aged 55 to 69 years, the decision to undergo periodic PSA-based screening for prostate cancer should be an individual one and should include discussion of the potential benefits and harms of screening with their clinician.” The USPSTF decided that PSA screening as it currently exists is inadequate for widespread implementation. It is thus important to ask the question how PSA screening can be improved to reduce overdiagnosis, overtreatment, and PCa mortality. Evidence suggests that the incorporation of genetic factors into PSA screening decisions could do just that. PSA levels have been shown to be highly heritable, but the associated genetic variants that have been identified thus far explain only some of the variation. Moreover, the variation explained is even smaller when dealing with non-European populations. If we can determine the genetic factors that predispose individuals to high PSA levels independently of PCa, we could then account for them as part of a new PSA screening paradigm. We propose to do just this with a large-scale project combining data from 17 studies of men both with and without PCa, all of whom have data on both PSA levels and genome-wide variants. In sum, the studies consist of 653,076 men, including 106,326 men of African ancestry, 35,683 of Latino ancestry, and 10,001 of Asian ancestry. In Aim 1, we will undertake a multi-ancestry genome-wide association study (GWAS) of PSA levels that is 20-times larger than any previous such analysis, as well as the first ever transcriptome- wide association study (TWAS) of PSA levels. We will then leverage the multi-ancestry nature of our sample to discover additional genetic variants associated with PSA via fine mapping. In Aim 2 we will evaluate the independence of the SNPs associated with PSA discovered in the GWAS and the genes associated with PSA discovered in the TWAS using conditional analyses. We will then differentiate between genetic factors associated with PSA and those associated with PCa using conditional and mediation analyses. Based on these findings, we will create and test polygenic risk scores for PSA levels that combine associated genetic factors together into single, powerful measures. Finally, in Aim 3, we will use measured PSA levels and genetic factors—accounting for constitutive, non-PCa variability in PSA—to develop models that more accurately predict PCa outcomes. These models will allow us to assess the benefit of additionally incorporating genetic information with respect to deciding whether a man should undergo prostate biopsy. Our aims in aggregate are promising toward reducing screening harms while improving screening benefits. In translation, clinicians and patients could make more informed decisions, thereby reducing unnecessary procedures and diagnoses, and preventing poor outcomes.