Optimizing generalizability of biomarker studies for Alzheimer’s disease and related dementias with epidemiologic tools

项目总结 确定阿尔茨海默病和相关痴呆(ADRD)的生物学机制对于 确定预防和治疗痴呆症的有效策略。谨慎和大量的投资已经 能够使用AT(N)框架对临床前阿尔茨海默病(AD)进行表征 生物标记物，但生物标记物研究样本的有限多样性可能会限制从 这些研究。不幸的是，早期增加多样性的尝试并没有解决非 由于不同社会人口群体的选择过程不同，研究结果具有普遍性。因此， 增加研究样本的多样性是必要的，但不是充分的，以实现可概括的研究结果。 我们的总体目标是开发工具和方法来增强ADRD生物标记物的普适性 学习。人们越来越认识到，评估ADRD研究结果的概括性很重要，但 缺乏系统地评估研究结果的概括性的工具阻碍了研究人员的工作。标准 分析方法没有充分利用当前可用的数据，也没有揭示 推论到全体人口时，估计的不确定性。新的流行病学和统计工具， 包括加权和g计算(“运输工具”)，允许将研究结果推广到 感兴趣的外部人群。我们建议应用运输工具来编制人口水平的估计。 ADRD AT(N)生物标志物对认知结果和临床前AD患病率的预测准确性(AIM 1)和危险因素对ADRD AT(N)生物标记物的影响(目标2)，使用阿尔茨海默病的数据 法国纪念队列神经成像倡议(ADNI)和Kaiser健康老龄化和多样化生活 体验(KhandLe)和90后生活(LA90)，这是两个新推出的、异常多样化的ADRD生物标志物 采用协调措施的样品。从研究样本到总体的概括总是增加的 相对于样本中的估计的估计效果的不确定性(例如，更大的可信区间和更小的 功率)，但由于泛化而增加的不确定度大小取决于样品的组成。 目前，还没有工具来评估拟议研究的组成将如何影响统计权力 以检测具有人口代表性的效应(即从拟议的研究中得出可概括的推论)。在AIM 3，我们将开发一个基于社会人口的人口水平估计的功率计算器 建议样本的组成，使研究人员能够评估研究设计中的概括性 舞台。该项目改进了关键分析工具，以提高现有ADRD生物标志物的泛化能力 研究，这可以应用于新的生物标记物，并帮助确定招聘目标的优先顺序。发展交通运输 ADRD生物标记物研究工具将帮助研究人员获得关于如何预防 并在整个人口中有效地治疗ADRD。

PROJECT SUMMARY Characterizing the biological mechanisms of Alzheimer's disease and related dementias (ADRD) is crucial for identifying effective strategies to prevent and treat dementia. Careful and substantial investments have enabled characterization of preclinical Alzheimer's disease (AD) using the AT(N) framework based on biomarkers, but the limited diversity of biomarker study samples may limit generalizability of findings from these studies. Unfortunately, early attempts to increase diversity have not solved the problem of non- generalizable study results due to differential selection processes across sociodemographic groups. Thus, increasing diversity of study samples is necessary, but not sufficient, for achieving generalizable study results. Our overall objective is to develop tools and approaches to enhance the generalizability of ADRD biomarker studies. It is increasingly recognized that evaluating generalizability of ADRD study results is important, but researchers are stymied by lack of tools for systematically evaluating generalizability of findings. Standard analytic methods do not take full advantage of currently available data and do not reveal the extent of uncertainty in estimates when generalizing to the entire population. New epidemiologic and statistical tools, including weighting and g-computation (“transport tools”), allow for generalizing results from a study to an external population of interest. We propose to apply transport tools to develop population-level estimates of the predictive accuracy of ADRD AT(N) biomarkers on cognitive outcomes and prevalence of preclinical AD (Aim 1) and effects of risk factors on ADRD AT(N) biomarkers (Aim 2) using data from Alzheimer's Disease Neuroimaging Initiative (ADNI), the French MEMENTO cohort, and Kaiser Healthy Aging and Diverse Life Experiences (KHANDLE) and Life After 90 (LA90), two newly available, exceptionally diverse ADRD biomarker samples with harmonized measures. Generalizing from a study sample to a population always increases uncertainty in estimated effects relative to estimates in the sample (e.g. wider confidence intervals and reduced power), but the magnitude of added uncertainty due to generalizing depends on the composition of the sample. Currently, there are no tools to evaluate how the composition of a proposed study will impact statistical power to detect population-representative effects (i.e. draw generalizable inferences from the proposed study). In Aim 3, we will develop a power calculator for population-level estimates based on the sociodemographic composition of the proposed sample, enabling researchers to evaluate generalizability in the study design stage. This project advances critical analytic tools to improve generalizability of existing ADRD biomarker studies, which can be applied to novel biomarkers and help prioritize recruitment goals. Developing transport tools for ADRD biomarker research will help researchers obtain the best possible evidence on how to prevent and effectively treat ADRD in the entire population.