TREM2 Genotype-Informed Drug Repurposing and Combination Therapy Design for Alzheimers Disease
TREM2 Genotype-Informed Drug Repurposing and Combination Therapy Design for Alzheimers Disease
批准号:
10418459
负责人:
Feixiong Cheng
金额:
$83.15万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-07-15 至 2027-03-31
关键词:
3-DimensionalAKT inhibitionAffectAfrican AmericanAgeAllelesAlzheimer&aposs DiseaseAlzheimer&aposs disease pathologyAlzheimer&aposs disease patientAlzheimer&aposs disease riskAlzheimer&aposs disease therapeuticAlzheimer&aposs disease therapyAmericanAmyloidAmyloid beta-ProteinAnti-Inflammatory AgentsAreaAsthmaAttentionBiologyBrainCell LineCell NucleusCellsCerebrumClinicClinicalClinical TrialsCombination Drug TherapyCombined Modality TherapyCommunicationComputersDataDatabasesDevelopmentDiseaseDisease OutcomeDisease ProgressionDisease associated microgliaDoseDrug CombinationsDrug ScreeningDrug TargetingDrug usageElectronic Health RecordGene TargetingGenerationsGenesGeneticGenetic TranscriptionGenomeGenomicsGenotypeHealth systemHumanHuman GeneticsImmuneIncidenceInflammationInflammatoryIntelligenceInterventionInvestigationKnock-in MouseKnowledge PortalLate Onset Alzheimer DiseaseLeadLinkMachine LearningMedicineMethodologyMethodsMicrogliaMolecularMolecular TargetMusMutationNatureNerve DegenerationNetwork-basedNeurodegenerative DisordersNeurogliaNew York CityObservational StudyOrganoidsPathogenesisPatientsPenetrationPersonsPharmaceutical PreparationsPharmacoepidemiologyPharmacologyPharmacotherapyPlayPopulationProcessPropertyResearchRiskRoleSignal TransductionSourceSystemSystems BiologyTREM2 geneTauopathiesTestingToxic effectUnited StatesValidationVariantanalytical toolbasebench to bedsidebrain endothelial cellcell typeclinical efficacycohortdeep learningdrug candidatedrug discoverydrug repurposingdrug testingexperimental studyfluticasonegenome-widegenomic datahuman diseasein vitro Assayinduced pluripotent stem cellknowledge graphmetropolitanmolecular targeted therapiesmouse modelmultimodalitymultiple omicsmutantneuroinflammationnovelpopulation basedpreclinical efficacypreventrisk variantside effectsuccesstargeted treatmenttau Proteinstherapy designtranscriptome sequencingtreatment effecttrial design
中文摘要
项目总结
累积的证据表明,神经炎症在阿尔茨海默病(AD)和抗阿尔茨海默病(AD)中起着至关重要的作用。
炎症剂(即小胶质细胞靶向治疗)显示了治疗AD的潜在方法。治疗方法
由于小胶质细胞生物学的性质,小胶质细胞靶向治疗的窗口至少可能在AD晚些时候打开。
如果淀粉样蛋白-β是AD的触发因素,tau是刽子手,那么小胶质细胞就是疾病的加速器
进步。针对小胶质细胞的方法在轻到中度疾病中有更好的成功机会
与必须在AD早期预防触发的抗淀粉样蛋白治疗相比。在小胶质细胞基因中,
触发髓系细胞上表达的受体2(TREM2)已受到广泛关注,因为半合子
TREM2的R47H变异(TREM2R47H)在包括非洲人在内的不同人群中使AD风险增加2-7倍
美国人。我们的初步单核RNA测序(SnRNAseq)研究确定了与疾病相关的
具有增强的AD促炎信号(即激活Akt信号)的小胶质细胞(DAM)与
TREM2R47H变异体和药理Akt抑制逆转TREM2R47H诱导的炎症,
展示了TREM2R47H在AD中靶向药物发现的概念证明。使用多模式SnRNAseq分析,
我们确定了两种已获批准的抗炎哮喘药物(氟替卡松和莫美松)。
调制DAM分子网络与电子健康记录中AD发病率的降低有关
(EHR)700万患者的数据。因此,我们假设,对AD相关突变(即,
TREM2R47H)增强小胶质细胞毒性可能有助于理解小胶质细胞如何变得适应不良/毒性
以及开发针对迟发性散发性AD的小胶质细胞靶向治疗策略。这
应用需要新的小胶质细胞靶向药物再利用和联合疗法治疗AD
成熟的基于多组学和深度学习的EHR方法,以及AD的功能观察
患者诱导的多能干细胞(IPSCs)、脑器官和小鼠模型,有三个特定的目标。
Aim 1将测试TREM2R47H信息的小胶质细胞靶向治疗假说,以确定细胞类型特异性
基于多组学证据的AD分子驱动因素/网络、可再利用药物和联合疗法
聚合。这些分析将利用我们现有的SnRNAseq数据(n=24个TREM2R47H和n=23个常见
变异(CV)-具有匹配的年龄、AD病理和APOE基因型的TREM2)和来自
广告知识门户。AIM 2将利用高通量确定可重复使用的药物和联合疗法
基于EHR的假设生成和基于序列深度学习的倾向得分匹配方法。
我们将利用Insight网络中已取消身份的EHR(纽约市5个地区约1,100万名患者
卫生系统和大都市地区)。AIM 3将使用AD患者筛选、测试和验证药物-
衍生的携带TREM2R47H的IPSC系与脑器官和小鼠模型相结合。成功者
该项目的完成将提供一种可行的战略,将AD药物的再利用从工作台迅速转移到床边。
1
英文摘要
PROJECT SUMMARY
The cumulative evidence indicates neuro-inflammation play crucial roles in Alzheimer’s disease (AD) and anti-
inflammatory agents (i.e., microglia-targeted therapies) show potential treatments for AD. The treatment
window for microglia-targeted therapies may at least be open later in AD due to the nature of microglial biology.
If amyloid-β is the trigger for AD, and tau is the executioner, then microglia are accelerators of disease
progression. Microglia-targeted approaches have a better chance of success in mild to moderate disease
compared to anti-amyloid therapies that have to prevent the trigger early in AD. Among the microglial genes,
triggering receptor expressed on myeloid cells 2 (TREM2) has received much attention because a hemizygous
R47H variant of TREM2 (TREM2R47H) increases the AD risk by 2-7 folds in various populations, including African
American. Our preliminary single-nucleus RNA-sequencing (snRNAseq) study identified disease-associated
microglia (DAM) with enhanced AD pro-inflammatory signatures (i.e., activation of Akt-signaling) associated with
the TREM2R47H variant and pharmacological Akt inhibition reversed the TREM2R47H induced inflammation,
showing proof-of-concept of TREM2R47H targeted drug discovery in AD. Using multimodal snRNAseq analysis,
we identified two approved anti-inflammatory asthma drugs (fluticasone and mometasone) that were predicted
to modulate DAM molecular networks are associated with a reduced incidence of AD in electronic health record
(EHR) data of 7 million patients. We therefore posit that understanding how the AD-linked mutations (i.e.,
TREM2R47H) enhance microglial toxicity could lead to understanding how microglia become maladaptive/toxic
and development of microglia-targeted therapeutic strategy for late-onset sporadic AD in general. This
application calls for novel microglia-targeted drug repurposing and combination therapies for AD using our
well-established multi-omics and deep learning-based EHR approaches, and functional observations in AD
patient-induced pluripotent stem cells (iPSCs), cerebral organoids, and mouse models, with three specific Aims.
Aim 1 will test the TREM2R47H informed microglia-targeted therapeutic hypothesis for identifying cell type-specific
molecular drivers/networks, repurposable drugs, and combination therapies for AD using multi-omics evidence
aggregation. These analyses will leverage our existing snRNAseq data (n = 24 TREM2R47H and n = 23 common
variant (CV)-TREM2 with matched age, AD pathology and APOE genotypes) and public genomic data from the
AD knowledge portal. Aim 2 will identify repurposable drugs and combination therapies using high-throughput
EHR-based hypothesis generation and sequential deep learning-based propensity score matching approaches.
We will leverage de-identified EHRs from the INSIGHT networks (~11 million patients across New York City’s 5
health systems and the greater metropolitan area). Aim 3 will screen, test and validate drugs using AD patient-
derived iPSC lines carrying TREM2R47H in conjunction with cerebral organoid and mouse models. The successful
completion of this project will offer a viable strategy to move AD drug repurposing from bench to bedside rapidly.
1
期刊论文(0)
专著(0)
科研奖励(0)
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