Hemodynamic Biomarkers of Healthy and Diseased Aging

项目摘要 这份K25提案是为了一项为期五年的导师培训计划，使加州大学洛杉矶分校的Ariana Anderson博士能够 从统计员转变为独立调查员，并制定积极的研究计划以确定 认知衰退和衰老的功能性生物标志物。安德森博士的建议包括一项全面的 培训计划包括校准fMRI、fMRI数据收集、神经心理学方面的正式培训 评估、志愿服务、定向阅读、课程作业、指导、会议和职业发展， 这些课程旨在补充和完成申请人之前的数学培训和 统计数据。这项拟议的研究解决了一个影响几乎所有功能磁共振研究的重要问题； 模拟的血流对神经元刺激的反应被假设为不同年龄、不同基因型和不同年龄的恒定 疾病，尽管我们知道这一假设是绝对错误的。这降低了统计能力 功能磁共振研究，增加必要的样本量，并将偏差引入疾病和衰老的功能磁共振研究。 此外，对健康患者血液动力学随年龄变化的了解不足，使识别 不健康衰老的生物标记物很难。我们将使用脑血流测量(ASL)、高碳酸血症和 血流动力学变化，以及遗传风险因素，作为预测未来认知能力下降的生物标志物。这个 血流动力学反应、认知功能减退、衰老和疾病之间的关系将被解开 通过以下三个目标。目标1。)创建年龄校正的血流动力学响应函数，在 调整扫描期间记录的心脏和呼吸伪影，以便将来的年龄研究可以使用 经过年龄修正的血液流动模型。我们将在有和没有遗传风险的受试者中进行评估 阿尔茨海默氏症。年龄校正的血流动力学反应函数将减少偏差并增加统计学意义 功率(增加灵敏度，和/或减少所需的样品大小)。目标2。)评估年龄是否- 血流动力学异常预示着认知能力的异常。对正常血流动力学进行建模将使我们能够 识别异常血流动力学，为血管性痴呆等特定疾病创建生物标记物。目标3。) 使用校准的功能磁共振成像创建一个新的HRF模型，以解释与年龄相关的CBF变化。异常 血流动力学可能更好地预测哪些患者更有可能经历认知能力下降，导致 更早的治疗。

Project Summary This K25 proposal is for a five-year mentored training program to enable Dr. Ariana Anderson from UCLA to transition from a statistician to an independent investigator, with an active research plan in identifying functional biomarkers of cognitive decline and aging. Dr. Anderson's proposal includes a comprehensive training program involving formal training in calibrated fMRI, fMRI data collection, neuropsychological assessments, volunteering, directed readings, coursework, mentoring, conferences, and career development, which are designed to complement and complete the applicant's previous training in mathematics and statistics. The proposed research addresses an important issue that affects nearly all fMRI studies; the modeled blood-flow response to neuronal stimuli is assumed to be constant across ages, genotypes and diseases, even though we know that this assumption is categorically false. This lowers the statistical power of fMRI studies, increases necessary sample sizes, and introduces bias into fMRI studies of disease and aging. Moreover, a poor understanding of hemodynamic change with age in healthy patients makes identifying biomarkers of unhealthy aging difficult. We will use cerebral blood flow measurements (ASL), hypercapnic and hemodynamic changes, along with genetic risk factors, as biomarkers to predict future cognitive decline. The relationship between the hemodynamic response, cognitive decline, aging and disease will be unraveled through the following three aims. Aim 1.) Create age-corrected hemodynamic response functions, after adjusting for cardiac and respiratory artifacts recorded during scan-time, so that future age studies can use age-corrected models of blood flow. We will estimate this in subjects with and without genetic risk for Alzheimer's disease. Age-corrected hemodynamic response functions will reduce bias and increase statistical power (increase the sensitivity, and/or reduce the required sample sizes). Aim 2.) Evaluate whether age- abnormal hemodynamics predict abnormal cognitive ability. Modeling normal hemodynamics will allow us to identify abnormal hemodynamics, creating biomarkers for specific diseases such as vascular dementia. Aim 3.) Create a new HRF model to account for age-related CBF changes, using calibrated fMRI. Abnormal hemodynamics may better predict which patients are more likely to experience cognitive decline, leading to earlier treatment.