Statins, statin-related gene, and Parkinson's disease risk

描述(申请人提供)：帕金森病(PD)是美国第二常见的神经退行性疾病，影响着100多万美国人；由于人口老龄化，这个数字还在增长。大多数患者最终发展为严重残疾，这显著影响了他们和他们的照顾者的生活质量。清华大学迫切需要开发疾病修正或神经保护疗法。在我们之前的研究中，我们发现经常使用他汀类药物的人患帕金森病的风险较低。然而，我们以前分析的一个主要局限性是，我们没有关于特定他汀类药物使用的信息，这些信息是从2004年开始在我们的队列中收集的。由于他汀类药物穿越血脑屏障的能力不同，检查它们与帕金森病风险的具体关联是很重要的。 此外，以前的研究表明，他汀类药物的个体间存在相当大的差异。 响应性，这很大程度上受遗传变异的影响。然而，到目前为止，还没有研究来检验这些与他汀类药物相关的遗传因素在帕金森病风险中的作用。因此，我们建议扩展我们之前的研究，在为期10年(2004-2014)的随访中，在护士健康研究(NHS)和卫生专业人员随访研究(HPFS)的约17万名积极参与者中，检查特定他汀类药物对帕金森病风险的潜在影响。我们预计将确认765例帕金森病新发病例(283名男性和482名女性)。我们将进一步研究他汀类药物对那些在基线水平有一种或多种帕金森病运动前症状的患者是否仍有保护作用。这项分析将提供关于他汀类药物是否可以减缓帕金森病从临床前阶段进展到临床阶段的第一个证据。值得注意的是，观察到的他汀类药物与帕金森病之间的联系可能会被适应症混淆，这是理解他汀类药物在帕金森病治疗中的治疗潜力的关键。为了回答这个极其重要但尚未解决的问题，我们还将研究他汀类药物的使用与与他汀类药物反应相关的基因之间的相互作用，以及与帕金森病风险的关系。为了测试这种基因与他汀类基因的相互作用，我们将使用一种新的方法-基因-环境集关联测试，在该方法中，所有SNP将使用核机器方法组合成一个SNP集，从而测试这些SNP的联合效应。这种方法同时利用了SNP集中所有SNP的遗传信息，导致了自由度减少的更强大的测试。与根据一组建议的风险等位基因创建单一遗传分数的方法不同，GESAT方法的一个好处是它不需要对变种的方向性先验知识。更好地了解他汀类药物和他汀类药物相关基因在帕金森病风险中的潜在作用，无疑将有助于了解帕金森病的病因和个性化预防和早期治疗策略的发展。

DESCRIPTION (provided by applicant): Parkinson disease (PD) is the second most common neurodegenerative disease in the United States (US) and affects over one million Americans; this number is growing due to population aging. Most patients eventually develop severe disability, which markedly affects their quality of life and that of their caregivers. There is thu a compelling need to develop disease modifying or neuroprotective treatments. In our previous study, we found that PD risk is lower among individuals who regularly use statins. However a major limitation of our previous analyses is that we did not have information on use of specific statins, which was collected in our cohorts only starting in 2004. As statins differ in their abiliy to cross the blood brain barrier, it is important to examine their specific associations with PD risk. Further, previous studies have shown that there is considerable interindividual variation in statin responsiveness, which is strongly influenced by genetic variations. However there are no studies to examine the role of these statin-related genetic factors in PD risk to date. We therefore propose to expand our previous study to examine the potential effects of specific statins on PD risk among ~170,000 active participants in the Nurses' Health Study (NHS), and Health Professionals Follow-up Study (HPFS) during 10 years of follow-up (2004-2014). We expect to confirm 765 new incident cases of PD (283 Men and 482 women). We will further examine whether protective effects of statins remain among those with one or more PD pre-motor symptoms at the baseline. This analysis will provide the first evidence regarding whether statins could slow PD progression from pre-clinical to clinical stage. It is worth noting that the observed association between statins and PD could be confounded by indication, which is key to understanding of the therapeutic potential of statins in PD treatment. To answer this extremely important but unsolved question, we will also examine the interaction between use of statins and genes associated with statin responsiveness, in relation to PD risk. To test this gene-statin interaction, we will employ a novel method, the gene-environment set association test, in which all SNPs will be grouped together into a SNP-set using the kernel machine approach and thus the joint effect of these SNPs will be tested. This approach utilizes genetic information from all SNPs in a SNP-set simultaneously, leading to a more powerful test with reduced degrees of freedom. In contrast to methods that create a single genetic score from a set of proposed risk alleles, a benefit of the GESAT approach is that it does not require a priori knowledge of directionality for the variants. A better understanding of the potential role of statins, and statin-related genes, in PD risk will undoubtedly shed some light on the PD etiology and development of personalized prevention and early treatment strategies.