Optimization of statin regimens for atherosclerotic cardiovascular disease prevention using polygenic risk scores and real-world evidence

项目总结/摘要 动脉粥样硬化性心血管疾病（ASCVD）是全球死亡的主要原因， 仍然是旨在降低ASCVD风险的胆固醇管理指南的基石。虽然以前的 这些指南的修改增加了他汀类药物合格患者的数量，降低了他汀类药物的阈值。 尚未发现他汀类药物资格可以提高预防ASCVD的需要治疗人数（NNT）。一 精确医学方法，提高他汀类药物合格标准的敏感性和特异性 指南修订（目前未考虑他汀类药物候选者的个体）预计将 有利于降低NNT。他汀类药物随机对照试验遗传子研究的新证据 （随机对照试验）表明，冠心病（CHD）多基因风险评分独立修改他汀类药物 相对风险降低（独立于他汀类药物诱导的致动脉粥样硬化胆固醇降低）， 提高他汀类药物治疗选择的特异性和敏感性的潜力。此外，假设生成 研究结果表明，CHD多基因风险评分可能预测特定类型他汀类药物的获益增强 和剂量。然而，这些结果的普遍性受到缺乏异质性的不利影响。 RCT研究人群人口统计学和他汀类药物治疗方案以及有限的患者随访时间和样本 尺寸进一步的研究是必要的，以更好地了解多基因风险评分如何修改他汀类药物的好处之前， 这种精确的医疗工具可以考虑用于临床实施。 我们在这个项目中的主要目标是将先前的概念验证证据转化为临床相关的， 在ASCVD预防中使用他汀类药物的可行工具，有可能纳入国家 指南为了实现这一目标，我们将利用凯撒永久研究银行（KPRB）的数据。 和退伍军人事务部百万退伍军人计划（MVP），这是两个最大的电子健康记录- 在美国的生物银行。这些前瞻性队列是开发和验证此工具的理想选择 因为他们规模大（每个参与者超过40万），种族多样（约25%的历史上被排斥的群体）， 长期随访（>25年），并包含真实世界数据（全面的电子健康记录）。 在目标1中，我们将评估CHD多基因风险评分与他汀类药物相对风险降低之间的关系 在不同人群中的各种ASCVD结局。在目标2中，我们将确定 CHD多基因风险评分与他汀类药物诱导的ASCVD风险降低之间的相关性与他汀类药物类型有关 和剂量。在目标3中，我们将开发一种精确的药物工具，用于降低他汀类药物诱导的ASCVD相对风险。 这些目标将由一个已建立的多学科专家团队在临床药理学，临床 血脂学、心血管流行病学、统计遗传学和伦理、法律的和社会影响（ELSI）。 研究结果将使用遗传背景+传统ASCVD风险因素来告知（1）他汀类药物的选择， 先前不被认为是合格的个体以及（2）针对他汀类药物使用者的剂量和类型的定制。

PROJECT SUMMARY/ABSTRACT Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of mortality worldwide and statin treatment remains a cornerstone of cholesterol management guidelines aimed at reducing ASCVD risk. While previous modifications of these guidelines have increased the number of statin-eligible patients, a lower threshold for statin eligibility has not been found to improve the number-needed-to-treat (NNT) for ASCVD prevention. A precision medicine approach that improves both the sensitivity and specificity of statin eligibility criteria in future guideline revisions (among individuals not currently considered candidates for statins) would be expected to beneficially reduce NNT. Emerging evidence from genetic substudies of statin randomized controlled trials (RCTs) demonstrates that coronary heart disease (CHD) polygenic risk scores independently modify statin relative risk reduction (independent of statin-induced atherogenic cholesterol lowering) in a manner that has the potential to improve the specificity and sensitivity of statin therapy selection. Furthermore, hypothesis-generating findings suggest that CHD polygenic risk scores may predict enhanced statin benefit from particular statin types and doses. However, the generalizability of these results is adversely impacted by lack of heterogeneity in the RCT study population demographics and statin regimens as well by limited length of patient follow-up and sample size. Further studies are necessary to better understand how polygenic risk scores modify statin benefit before this precision medicine tool can be considered for clinical implementation. Our primary goal in this project is to translate prior proof-of-concept evidence into a clinically-relevant and actionable tool for use of statins in ASCVD prevention that has the potential to be incorporated into national guidelines. To accomplish this goal, we will leverage data from the Kaiser Permanente Research Bank (KPRB) and the Veterans Affairs Million Veteran Program (MVP), which are two of the largest electronic health record- linked biobanks in the United States. These prospective cohorts are ideal for developing and validating this tool because they are large (>400,000 participants each), ethnically diverse (~25% historically excluded groups), have long-term follow-up (>25 years), and contain real-world data (comprehensive electronic health records). In Aim 1, we will assess the relationship between CHD polygenic risk scores and statin relative risk reduction for various ASCVD outcomes in diverse populations. In Aim 2, we will determine the extent to which the association between CHD polygenic risk scores and statin-induced ASCVD risk reduction is related to statin type and dose. In Aim 3, we will develop a precision medicine tool for statin-induced ASCVD relative risk reduction. The aims will be carried out by an established multidisciplinary team of experts in clinical pharmacology, clinical lipidology, cardiovascular epidemiology, statistical genetics, and ethical, legal, and social implications (ELSI). Findings will use genetic background + traditional ASCVD risk factors to inform (1) the selection of statins n individuals not previously considered to be eligible as well as (2) the tailoring of dose and type for statin users.