Precursors of Stroke Incidence and Prognosis

项目总结/摘要 中风后认知障碍和痴呆（PS-VCID）是阿尔茨海默病的主要原因， 相关性痴呆（ADRD），发生在30%的中风幸存者中。一个人复杂的生命历程 血管危险因素，沿着不同的患病率和心血管危险因素的发生率， 美国人群，研究生命过程中暴露于心血管危险因素和ADRD之间的联系 优先考虑此外，准确估计个体在特定时间点的PS-VCID风险的能力 在生活中，即使在中风发生之前，对于计划个性化和公共卫生干预措施以改善 大脑健康和恢复力肥胖和血脂异常等危险因素在非洲已成为流行病。 美国，但其因果作用和对PS-VCID风险的贡献尚不明确。此外，PS-VCID风险预测 没有使用多模式数据和多种族群体的工具。该提案旨在利用FHS 数据和资源，以了解PS-VCID趋势和决定因素， REGARDS和ARIC研究人员在两个种族的参与者中开发和验证全面的PS- VCID风险预测工具（包括纳入健康的社会决定因素），以研究 肥胖和血脂异常与PS-VCID的因果关系，探索现有药物治疗的再利用， 并为PS-VCID的预防策略和治疗目标提供信息。具体目标包括：目标1，描述 社区居民中PS-VCID风险的趋势;目的2，评估PS-VCID的生命过程相关性。 VCID使用新的机器学习方法来检查重复暴露措施之间的关系， 使用PS-VCID前瞻性研究超过70年，包括i）卒中风险特征组成部分，ii） 脂质分数，iii）肥胖指标，iv）高血压类型，和v）多器官疾病;目的3，开发两个 PS-VCID风险预测工具（PS-VCID风险评分），用于i）临床风险评估（基于心血管风险 因素、肥胖测量和血脂异常）和ii）在研究中的应用（加上脑成像衍生的 量化整体脑小血管疾病负荷、整体灰质体积和皮质厚度的因素， 社会因素（面积剥夺指数）和遗传因素的基础上确定的最佳多基因风险 每个血管风险因素的评分）。将在充分表征的FHS和REGARDS中制定评分 队列，然后在ARIC研究中进行评估和验证。目的4、探讨肥胖与肥胖的因果关系， PS-VCID的血脂异常，并在工具变量分析中探索药物再利用策略 框架.

PROJECT SUMMARY/ABSTRACT Post-stroke cognitive impairment and dementia (PS-VCID) are major contributors to Alzheimer’s disease and related dementias (ADRD), occurring in 30% of stroke survivors. An individual’s complex life-course exposure to vascular risk factors, along with the varying prevalence and incidence of cardiovascular risk factors among the U.S. population, make study of the link between life-course exposure to cardiovascular risk factors and ADRD a priority. Furthermore, the ability to accurately estimate an individual’s risk for PS-VCID at a particular timepoint in life, even before a stroke occurs, is critical for planning personalized and public health interventions to improve brain health and resilience. Risk factors such as obesity and dyslipidemia have gained epidemic proportions in the U.S., but their causal role and contribution to PS-VCID risk are undefined. Further, PS-VCID risk prediction tools using multimodal data and in multiple racial groups are not available. This proposal seeks to leverage FHS data and resources to generate an understanding of PS-VCID trends and determinants, to collaborate with REGARDS and ARIC study investigators to develop and validate in bi-racial participants comprehensive PS- VCID risk prediction tools (including incorporation of a measure of social determinant of health), to study the causal relations of obesity and dyslipidemia with PS-VCID, to explore repurposing of available drug treatments, and to inform prevention strategies and treatment targets for PS-VCID. Specific Aims include: Aim 1, to describe trends in PS-VCID risk in community dwelling individuals; Aim 2, to evaluate the life-course correlates of PS- VCID using novel machine learning methods to exame the relation of repeated exposure measures, assessed prospectively over seven decades, with PS-VCID, including i) Framingham Stroke Risk Profile components, ii) lipid fractions, iii) obesity indicators, iv) hypertension types, and v) multi-organ disease; Aim 3, to develop two PS-VCID risk prediction tools (PS-VCID risk scores) for i) clinical risk assessment (based on cardiovascular risk factors, obesity measures, and dyslipidemia) and ii) use in research (with addition of brain imaging-derived factors quantifying global cerebral small vessel disease burden, global gray matter volume and cortical thickness, social factors (Area deprivation index) and genetic factors based on identification of the optimal polygenic risk score for each vascular risk factor). Scores will be developed in the well-characterized FHS and REGARDS cohorts, and then assessed and validated in the ARIC study. Aim 4, to study the causal relation of obesity and dyslipidemia with PS-VCID and explore drug repurposing strategies in an instrumental variable analyses framework.