Improving Risk Stratification in Familial Hypercholesterolemia (RISK-FH)

项目摘要 家族性高胆固醇血症(FH)是一种诊断和治疗不足的疾病。 早发动脉粥样硬化性心血管疾病(ASCVD)的原因。遗传学研究的最新进展和结果 从基于人群的FH研究表明，FH的广义表型定义，严重升高的低 密度脂蛋白胆固醇(LDL-C)，以及早产ASCVD或高胆固醇的阳性家族史， 包括四种不同的临床亚型：1)由FH基因的致病变异引起的单基因FH，2) 由多种常见等位基因的累积遗传引起的多基因高胆固醇血症 低密度脂蛋白-C的递增，3)脂蛋白(A)(Lp(A))升高和严重的高胆固醇血症，以及4)严重 无遗传原因的高胆固醇血症。我们假设发生ASCVD的风险不同 存在于四种FH亚型中。FH的风险评估变得越来越复杂，涉及多个因素 影响预后的因素：低密度脂蛋白水平、存在基因变异、存在其他ASCVD危险因素、 Lp(A)水平、既往ASCVD、年龄和性别。进一步使风险评估复杂化的是健康差异 与年龄、性别、乡村和种族有关。目前FH护理方面的不足表明有两个紧迫的需求： 更准确的风险评估和策略，将风险信息传达给不同的人群 受到了影响。这项建议的目的是：1)证明FH亚型对ASCVD预后的影响； 2)研究向临床医生和患者传达这一复杂的FH风险信息的最佳方式， 考虑将健康差异作为临床医生和患者护理的障碍。 在目标1中，这项提案将为实现这些目标奠定基础，方法是创建 超过80万人使用来自Mt.盖辛格的个人级别数据。西奈半岛和英国生物库与 来自ClinVar遗传数据库的变异水平数据，允许对FH亚型ASCVD进行分子分配 表型和风险的表征。我们预期的研究样本将包括大约2500个 具有致病性FH变异的个人和具有变异阴性FH亚型的50,000人。在目标2中，我们 将使用这一队列来确定ASCVD在四个亚型中的结果，包括评估 与血脂无关的ASCVD的常规危险因素和多基因风险。我们亦会评估 健康差距对结果的影响。同时，在目标3中，我们将使用实施科学来 调查盖辛格和Mt.在传播预防性卫生信息方面的障碍和促进者。 西奈半岛。我们将重点关注患者和提供者的态度和看法，重点是已知的护理 差异及其对护理的影响。这项提议将显示精确的基因组特征的好处 FH风险，以及额外ASCVD风险评估的价值。通过了解护理的障碍 临床医生和患者水平以及考虑已知差异的价值，我们将演示最佳实践 以一种改善临床实践和患者理解的方式交流这一信息。

Project Summary It is now well understood that familial hypercholesterolemia (FH) is an under diagnosed and under treated cause of premature atherosclerotic cardiovascular disease (ASCVD). Recent advances in genetics and results from population-based studies of FH suggest that the broad phenotypic definition of FH, severely elevated low density lipoprotein cholesterol (LDL-C), and positive family history of premature ASCVD or high cholesterol, encompasses four distinct clinical subtypes: 1) monogenic FH caused by a pathogenic variant in an FH gene, 2) polygenic hypercholesterolemia caused by the cumulative inheritance of many common alleles associated with incremental increases in LDL-C, 3) elevated lipoprotein (a) (Lp(a)) and severe hypercholesteremia, and 4) severe hypercholesteremia in the absence of a genetic cause. We hypothesize that differences in risk of incident ASCVD exist among the four FH subtypes. Risk assessment in FH has become increasingly complex with multiple factors influencing outcomes: LDL-C level, presence of a genetic variant, presence of additional ASCVD risk factors, Lp(a) level, pre-existing ASCVD, age, and gender. Further complicating risk assessment are health disparities related to age, sex, rurality, and race/ethnicity. Current shortcomings in FH care suggest two immediate needs: more accurate risk assessment and strategies to communicate this risk information to the diverse population impacted. The goals of this proposal are to 1) demonstrate the impact of FH subtype on ASCVD prognosis, and 2) study the best ways to communicate this complex FH risk information to clinicians and patients, with consideration of health disparities as barriers to care for both clinicians and patients. In Aim 1, this proposal will develop a foundation for accomplishing these goals by creating a cohort of over 800K people using individual-level data from Geisinger, Mt. Sinai, and the UK Biobank integrated with variant-level data from the ClinVar genetic database, allowing molecular assignment of FH subtypes, ASCVD phenotyping, and characterization of risk. Our anticipated study sample will include approximately 2,500 individuals with a pathogenic FH variant and 50,000 individuals with a variant-negative FH subtype. In Aim 2, we will use this cohort to determine ASCVD outcomes in the four subtypes, including assessment of the impact of conventional risk factors and polygenic risk for ASCVD independent of blood lipids. We will also assess the impact of health disparities on outcomes. At the same time, in Aim 3 we will use implementation science to investigate barriers and facilitators to the communication of preventative health information at Geisinger and Mt. Sinai. We will focus on attitudes and perceptions of patients and providers with an emphasis on known care disparities and their impact on care. This proposal will show the benefit of a precise genomic characterization of FH risk, and the value of additional ASCVD risk assessment. By understanding the barriers to care at the clinician and patient level and the value of accounting for known disparities, we will demonstrate best practices for communicating this information in a way that improves clinical practice and patient understanding.