Hemodynamic Biomarkers of Healthy and Diseased Aging

项目摘要 这份K25提案是一个为期五年的指导培训计划，使来自加州大学洛杉矶分校的Ariana安德森博士能够 从统计学家到独立调查员的过渡，有积极的研究计划， 认知能力下降和衰老的功能性生物标志物。安德森博士的建议包括一个全面的 培训计划，涉及校准功能磁共振成像，功能磁共振成像数据收集，神经心理学的正式培训 评估，志愿服务，指导阅读，课程，指导，会议和职业发展， 旨在补充和完成申请人以前的数学培训， 统计这项研究提出了一个影响几乎所有功能磁共振成像研究的重要问题， 假设对神经元刺激的模拟血流反应在年龄、基因型和 疾病，尽管我们知道这个假设是绝对错误的。这就降低了 fMRI研究，增加了必要的样本量，并引入偏见到疾病和衰老的fMRI研究。 此外，对健康患者血流动力学随年龄变化的认识不足， 不健康衰老的生物标志物很难。我们将使用脑血流量测量（ASL），高碳酸血症和 血液动力学变化，沿着遗传风险因素，作为预测未来认知能力下降的生物标志物。的 血流动力学反应、认知能力下降、衰老和疾病之间的关系将被揭开 通过以下三个目标。目标1.）创建年龄校正的血流动力学反应函数， 调整扫描期间记录的心脏和呼吸伪影，以便未来的年龄研究可以使用 年龄校正的血流模型。我们将在有和没有遗传风险的受试者中估计这一点， 老年痴呆症校正后的血流动力学反应函数将减少偏倚， 功率（增加灵敏度，和/或减少所需的样本量）。目标2）评估年龄是否- 血流动力学异常预示认知能力异常。模拟正常的血液动力学可以让我们 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志物。目标3） 创建一个新的HRF模型来解释年龄相关的CBF变化，使用校准的fMRI。异常 血液动力学可以更好地预测哪些患者更有可能经历认知能力下降， 早期治疗。

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.