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

项目总结 阿尔茨海默病(AD)及相关痴呆(AD/ADRD)是一种多因素、异质性疾病。多数 目前的研究主要集中在对AD/ADRD的药物干预上，目前还没有药物干预(PI)。 发现研究已经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)，如睡眠、饮食、膳食补充剂、有氧运动、 芳香疗法、光疗法、认知训练可能是可以改变的，因此提供了替代机会。 用于AD/ADRD预防。因此，本项目的目标是开发翻译信息学方法，以 使用多模式汇总、标准化和发现候选药物和NPI对AD/ADRD的影响 数据来源(即生物医学文献、EHR、临床试验)，然后是动物模型验证。要实现 我们的目标，我们提出了以下目标：1)构建一个综合的药理和非 生物医学文献中阿尔茨海默病的药物干预知识图谱(PANIA-KG) 和其他知识库；2)检测、理解和可视化PI的药物再用途信号， NPIS，以及它们对AD/ADRD的协同作用；3)重新排序和验证个体 以及使用多模式数据源和动物模型的药物再利用信号的协同作用。成功者 该项目的完成将提供一个全面的新产品创新知识图谱、新的信息学方法、 对候选药物和NPI进行了排名，并使用多模式数据源验证了协同干预。 生成的方法、PANIA-KG和排序列表可以进一步促进我们的临床研究和临床试验 该设计侧重于药物和NPIs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.