Endophenotype Network-based Approaches to Prediction and Population-based Validation of in Silico Drug Repurposing for Alzheimers Disease

基于内表型网络的方法对阿尔茨海默病的计算机药物重新利用进行预测和基于群体的验证

基本信息

  • 批准号:
    10339430
  • 负责人:
  • 金额:
    $ 77.14万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2020
  • 资助国家:
    美国
  • 起止时间:
    2020-04-15 至 2024-12-31
  • 项目状态:
    已结题

项目摘要

Although researchers have conducted more than 400 human trials for potential treatments of Alzheimer’s disease (AD) in the last two decades, the attrition rate is estimated at over 99%. Furthermore, the “one gene, one drug, one disease” reductionism-informed paradigm overlooks the inherent complexity of the disease and continues to challenge drug discovery for AD. The predisposition to AD involves a complex, polygenic, and pleiotropic genetic architecture. Recent studies have suggested that AD often has common underlying mechanisms, sharing intermediate endophenotypes with many other complex diseases. These endophenotypes, such as amyloidosis and tauopathy, have essential roles in many neurodegenerative diseases. Systematic identification and characterization of novel underlying pathogenesis and disease modules, more so than mutated genes, will serve as a foundation for generating actionable targets as input for drug repurposing and rational design of combination therapy in AD. Integration of the genome, transcriptome, proteome, and the human interactome are essential for such identification. Given our preliminary results, we posit that network- based identification of novel risk genes and endophenotype modules that share degree between amyloid and tau offer unexpected opportunities for drug therapy in AD comparing to targeting amyloid and tau separately. To address the underlying hypothesis, we propose to establish an integrated interdisciplinary research plan with three specific aims. Aim 1 will explore amyloid and tau-mediated endophenotype modules for AD -- We will test the network module hypothesis for amyloid and tau using our recently developed Bayesian framework that integrates multi-omics data (i.e., genome-wide association studies [GWAS] loci, single cell sequencing, and human brain Hi-C data) and the human interactome. Aim 2 will be capable of searching existing drugs and combination therapies for AD using network proximity approaches -- We will emphasize the uses of network proximity approaches (i.e., Genome-wide Positioning Systems network [GPSnet]) to identify repurposable drugs and efficacious combination regimens. This will be accomplished by integrating AD endophenotype module findings, public drug-target databases, the human interactome, and the large-scale patient longitudinal Claims- Electronic Medical Record data (over 200 million patients from the MarketScan database). Aim 3 will evaluate brain penetration and target network engagement for repurposable drugs -- We will use the humanized in vitro blood-brain barrier, resected brain tissues (ex vivo/in situ), and transgenic AD models (i.e., TgF344-AD rats) to experimentally evaluate brain penetration and target network engagement. Evaluation will be based upon network proximity to the AD-related endophenotype modules that are relevant to maximizing efficacy and to minimizing side effects. The successful completion of this project will offer powerful network methodologies and bioinformatics tools for prediction and population-based validation of in silico drug repurposing. It will also allow for the identification of novel repurposable drugs and clinically relevant combination therapies toward AD trials.
尽管研究人员已经对阿尔茨海默氏症的潜在治疗方法进行了400多次人体试验

项目成果

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科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Feixiong Cheng其他文献

Feixiong Cheng的其他文献

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{{ truncateString('Feixiong Cheng', 18)}}的其他基金

Alzheimer's Disease and Related Dementia-like Sequelae of SARS-CoV-2 Infection: Virus-Host Interactome, Neuropathobiology, and Drug Repurposing
阿尔茨海默病和 SARS-CoV-2 感染的相关痴呆样后遗症:病毒-宿主相互作用组、神经病理生物学和药物再利用
  • 批准号:
    10661931
  • 财政年份:
    2023
  • 资助金额:
    $ 77.14万
  • 项目类别:
Microglial Activation and Inflammatory Endophenotypes Underlying Sex Differences of Alzheimer’s Disease
阿尔茨海默病性别差异背后的小胶质细胞激活和炎症内表型
  • 批准号:
    10755779
  • 财政年份:
    2023
  • 资助金额:
    $ 77.14万
  • 项目类别:
Precision Medicine Digital Twins for Alzheimer’s Target and Drug Discovery and Longevity
用于阿尔茨海默氏症靶点和药物发现及长寿的精准医学数字孪生
  • 批准号:
    10727793
  • 财政年份:
    2023
  • 资助金额:
    $ 77.14万
  • 项目类别:
TREM2 Genotype-Informed Drug Repurposing and Combination Therapy Design for Alzheimers Disease
基于 TREM2 基因型的阿尔茨海默病药物再利用和联合治疗设计
  • 批准号:
    10418459
  • 财政年份:
    2022
  • 资助金额:
    $ 77.14万
  • 项目类别:
TREM2 Genotype-Informed Drug Repurposing and Combination Therapy Design for Alzheimers Disease
基于 TREM2 基因型的阿尔茨海默病药物再利用和联合治疗设计
  • 批准号:
    10665664
  • 财政年份:
    2022
  • 资助金额:
    $ 77.14万
  • 项目类别:
Endophenotype Network-based Approaches to Prediction and Population-based Validation of In Silico Drug Repurposing for Alzheimer's Disease
基于内表型网络的方法对阿尔茨海默病的计算机药物重新利用进行预测和基于群体的验证
  • 批准号:
    10409194
  • 财政年份:
    2020
  • 资助金额:
    $ 77.14万
  • 项目类别:
Endophenotype Network-based Approaches to Prediction and Population-based Validation of in Silico Drug Repurposing for Alzheimers Disease
基于内表型网络的方法对阿尔茨海默病的计算机药物重新利用进行预测和基于群体的验证
  • 批准号:
    10569077
  • 财政年份:
    2020
  • 资助金额:
    $ 77.14万
  • 项目类别:
An individualized network medicine infrastructure for precision cardio-oncology
用于精准心脏肿瘤学的个性化网络医学基础设施
  • 批准号:
    9755498
  • 财政年份:
    2017
  • 资助金额:
    $ 77.14万
  • 项目类别:
An individualized network medicine infrastructure for precision cardio-oncology
用于精准心脏肿瘤学的个性化网络医学基础设施
  • 批准号:
    9371272
  • 财政年份:
    2017
  • 资助金额:
    $ 77.14万
  • 项目类别:

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利用技术解决慢性阻塞性肺病退伍军人接受和坚持传统医院肺康复的问题
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