Detecting synergistic effects of pharmacological and non-pharmacological interventions for AD/ADRD

项目概要 阿尔茨海默病 (AD) 和相关痴呆 (AD/ADRD) 是一种多因素和异质性疾病。大多数 目前的研究重点是 AD/ADRD 的药物干预，目前还没有药物干预 (PI) 发现研究已转化为有效的治疗方法。然而，越来越多的证据表明 非药物干预（NPI），例如睡眠、饮食、膳食补充剂、有氧运动、 芳香疗法、光疗法、认知训练都是可以修改的，因此提供了替代机会 用于 AD/ADRD 预防。因此，该项目的目标是开发转化信息学方法 使用多模式汇总、标准化和发现药物和 NPI 候选药物对 AD/ADRD 的影响 数据资源（即生物医学文献、电子病历、临床试验），然后进行动物模型验证。达到 为了我们的目标，我们提出以下目标： 1）构建全面的药理学和非 生物医学文献中的阿尔茨海默病药理干预知识图谱 (PANIA-KG) 和其他知识库； 2) 检测、理解和可视化 PI 的药物再利用信号， NPI 及其使用 PANIA-KG 对 AD/ADRD 的协同效应； 3）重新排名和验证个人 以及使用多模式数据源和动物模型的协同药物再利用信号。成功者 该项目的完成将提供全面的 NPI 知识图、新颖的信息学方法、 对候选药物和 NPI 进行排名，并使用多模式数据源验证协同干预。 生成的方法、PANIA-KG 和排名列表可以进一步促进我们的临床研究和临床试验 设计重点关注药物和 NPI 对 AD/ADRD 的协同作用。

PROJECT SUMMARY Alzheimer's disease (AD) and related dementia (AD/ADRD) is a multifactorial and heterogeneous disorder. Most current studies focus on drug interventions for AD/ADRD and currently none of pharmacological intervention (PI) discovery research has been translated into effective treatments. However, increasing evidence demonstrates that non-pharmacological interventions (NPI), such as sleep, diet, dietary supplements, aerobic exercise, aromatherapy, light therapy, cognitive training, are potentially modifiable and thus offer alternative opportunities for AD/ADRD prevention. Thus, the objective of this project is to develop translational informatics approaches to aggregate, standardize and discover the effects of drug and NPI candidates on AD/ADRD using multi-modal data resources (i.e., biomedical literature, EHR, clinical trials) followed by animal model validation. To achieve our goal, we propose the following aims: 1) constructing a comprehensive Pharmacological And Non- Pharmacological Interventions for Alzheimer's Disease Knowledge Graph (PANIA-KG) from biomedical literature and other knowledge bases; 2) detecting, understanding, and visualization of drug repurposing signals of PIs, NPIs, and their synergistical effects for AD/ADRD using the PANIA-KG; 3) re-ranking and validating individual and synergistical drug repurposing signals using multimodal data sources and animal models. The successful completion of this project will deliver a comprehensive NPI knowledge graph, novel informatics approaches, ranked list of drug and NPI candidates, and validated synergistic intervention using multi-modal data sources. The generated approaches, PANIA-KG and ranked lists can further our clinical investigations and clinical trial design which focuses on synergistic effects of drug and NPIs for AD/ADRD.