Network models to capture multiple outcomes resulting from multi-component, salutogenic interventions
网络模型捕捉多成分有益干预措施产生的多种结果
基本信息
- 批准号:10721644
- 负责人:
- 金额:$ 15.55万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-08-04 至 2028-07-31
- 项目状态:未结题
- 来源:
- 关键词:8-hydroxy-2&apos-deoxyguanosineAffectAgeAge-associated memory impairmentAgingAnimalsAttenuatedBehavioralBiochemicalBloodBotanicalsC-reactive proteinCognitionCognitiveComplementary HealthComputer ModelsControl GroupsDataDevelopmentDiseaseDisease ProgressionExerciseFemaleFutureGenesGoalsGotu kolaGraphHealthHealth Care ResearchHealth PromotionHealth StatusHippocampusHumanImpaired cognitionIndividualInflammationInflammatoryIntegrative MedicineInterventionLaboratoriesLearningMeasurementMeasuresMediatingMemoryMethodologyMethodsModelingMolecularMolecular ProfilingMusMusculoskeletalOrganOrganismOutcomeOxidative StressPathogenesisPathway interactionsPersonal SatisfactionProcessRandomizedResearchRunningSystemSystems BiologyTestingTherapeutic InterventionTissuesTrainingWaterWhole Organismage relatedagedanimal tissuebody systemcareercognitive changecognitive enhancementcognitive functioncognitive taskdeep learning modeldesigndrinking waterdynamic systemexperienceexperimental studyglobal healthhealth dataimprovedinsightinterestmalemetabolomicsmodel buildingmodel organismmolecular domainmorris water mazemouse modelnetwork modelsprogramspromote resilienceresponserestorationsextranscriptomicswhole health
项目摘要
Project Summary
Health care research has extensively studied disease pathogenesis, but very little is known about the
complementary process of health restoration, or salutogenesis. Salutogenesis may involve the use of single or
multiple interventions. These may affect multiple targets to restore specific functions as well as affect whole
person health. This project aims to develop methods to study multisystem signatures of health restoration
obtained through multiple interventions both at the level of the organ and the whole organism. Currently, there
is considerable interest in identifying non-pharmaceutical interventions to improve resilience to cognitive
decline during aging. The proposed project will use a mouse model of age-related cognitive decline to study
molecular signatures and functional changes associated with restoration of healthy cognitive function. We will
evaluate two interventions that have previously been demonstrated to improve cognition in aged mice i.e.
exercise and a water extract (CAW) of the botanical Centella asiatica. Eighteen month old C57BL/6 male and
female mice will be randomized into an exercise group (voluntary access to a running wheel), a CAW group
(1000 mg/kg/day, administered in the drinking water), a group that receives both CAW and exercise, and a
control group that receives neither intervention each for a period of 35 days. Untreated male and female young
(4 month old) mice will serve as young controls. We will assess the impact of these two interventions,
separately and combined, on four health measures: cognition, global inflammatory status, global oxidative
stress and mobility using Morris Water Maze test, blood C-reactive protein, blood 8-hydroxydeoxyguanosine
and DigiGait respectively. At the conclusion of treatment, hippocampal tissue from the animals will be collected
and transcriptomics and metabolomics analysis will be performed. We will initially identify genes or metabolites
(singly or in clusters) that are significantly altered by the treatments. This -omics data will then be integrated
with the behavioral and blood data to create computational models that will be used to derive the unique
molecular signatures and health data associated with improved cognition. We will also explore whether the
molecular signature changes associated with cognitive improvement are a reversal of those seen in cognitive
decline (young vs old untreated animals), or represent a new salutogenic pathway. A heterogenous multi-level
network (HMLN) model will be used to describe and evaluate the correlations between all health outcomes
described here and the molecular data. Ultimately, similar HMLN models can be used as a basis to identify the
timing and types of interventions that are optimal for restoring cognitive health. The methodology developed in
these experiments can then be expanded beyond cognition to encompass other aspects of whole organism
health.
Template Version: 9/16/2021
Research Abstract Version: 1
项目摘要
卫生保健研究已经广泛地研究了疾病的发病机制,但很少有人知道,
健康恢复的补充过程,或salutogenesis。健康发生可能涉及使用单一或
多重干预。这些可能会影响多个目标,以恢复特定的功能,以及影响整个
人的健康。该项目旨在开发研究健康恢复的多系统特征的方法
通过在器官和整个生物体水平上的多重干预获得。目前
是相当大的兴趣,确定非药物干预,以提高弹性的认知
在衰老过程中衰退。该项目将使用与年龄相关的认知能力下降的小鼠模型来研究
与健康认知功能恢复相关的分子特征和功能变化。我们将
评估先前已证明可改善老年小鼠认知的两种干预措施,即
运动和一种植物性的积雪草的水提取物。18月龄C57 BL/6雄性,
将雌性小鼠随机分为运动组(自愿使用转轮)、CAW组
(1000 mg/kg/天,在饮用水中给药),接受CAW和运动的组,以及
对照组在35天内不接受任何干预。未给药的雄性和雌性幼仔
(4个月大)小鼠将作为年轻对照。我们将评估这两种干预措施的影响,
分别和组合,对四个健康指标:认知,整体炎症状态,整体氧化
Morris水迷宫试验、C反应蛋白、8-羟脱氧鸟苷
和DigiGait分别。处理结束时,将采集动物的海马组织
并进行转录组学和代谢组学分析。我们将首先确定基因或代谢物
(单个或成簇),其被处理显著改变。这些组学数据将被整合到
用行为和血液数据来创建计算模型,
分子特征和健康数据与认知能力的提高有关。我们亦会探讨
与认知改善相关的分子特征变化是认知障碍中所见的逆转。
下降(年轻与未治疗的老年动物),或代表一种新的促健康途径。一种异构多层次
网络(HMLN)模型将用于描述和评估所有健康结果之间的相关性
和分子数据。最终,类似的HMLN模型可以用作识别
最适合恢复认知健康的干预措施的时机和类型。年制定的方法
然后,这些实验可以扩展到认知之外,包括整个有机体的其他方面。
健康
模板版本:2021年9月16日
研究摘要版本:1
项目成果
期刊论文数量(0)
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专利数量(0)
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