Systems-based approaches for investigating tissue communication during exercise

用于研究运动期间组织通讯的基于系统的方法

基本信息

批准号：
10264084
负责人：
Andrea L Hevener
金额：
$ 35.45万
依托单位：
UNIVERSITY OF CALIFORNIA LOS ANGELES
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：
2020-09-30 至 2023-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10264084
关键词：
Acute Adipose tissue Animals Area Bayesian Analysis Bioinformatics Cardiac Chronic Chronic Disease Collaborations Communication Communities Complex Data Data Set Development Disease Endocrine Exercise Exercise Physiology Fatty acid glycerol esters Female Generations Genetic Health Homeostasis Human Hybrids In Vitro Inbred Mouse Inbred Strains Mice Inbreeding Individual Informatics Insulin Resistance Intervention Liver Metabolic Metabolic dysfunction Metabolism Molecular Molecular Biology Mouse Strains Mus Myocardium Non-Insulin-Dependent Diabetes Mellitus Pathway interactions Physical activity Physiological Plasma Productivity Proteome Proteomics Publications Publishing Rattus Recombinants Refractory Research Research Personnel Resources Rodent Sampling Scientist Skeletal Muscle System Tissue Banks Tissues Training Transducers Universities Validation Variant Work advanced system base biobank data hub data repository data resource endurance exercise exercise training experience human data human subject in vivo male metabolomics multiple omics new therapeutic target next generation novel prevent response sex skeletal tissue resource tool trait transcriptomics validation studies

项目摘要

ABSTRACT Daily physical activity is a known intervention to prevent or ameliorate complications associated with metabolic-related diseases. However, the mechanisms underlying metabolic adaptations to chronic exercise training remain inadequately understood. Moreover, human studies show a broad range of exercise adaptation with some individuals refractory to specific metabolic improvements associated with training. Since conventional animal studies have focused primarily on few rodent strains, in the current application we will interrogate exercise training adaptations in ~100 diverse male and female strains of inbred mice known as the UCLA Hybrid Mouse Diversity Panel (HMDP), and integrate these data with existing MoTrPAC data repositories at the Bioinformatics Center (BIC), Stanford University. In Aim 1 we will determine the regulatory loci controlling exercise metabolism and integrate several “omics” platforms (transcriptomics, proteomics, metabolomics) using Bayesian analyses and Mergeomics to identify regulatory networks and key driver nodes underlying exercise training in mice and validate these findings with publicly available data from the MoTrPAC consortium studies of exercise training in rats and humans. In Aim 2 we will use Quantitative Endocrine Network Interaction Estimation (QENIE) to functionally annotate novel inter-tissue communication circuits (between cardiac and skeletal muscle, and liver, and fat) that are critical for endurance exercise adaptation. Our findings provided herein show remarkable, sex-specific tissue crosstalk that occurs to maintain metabolic homeostasis and in response to exercise. We will construct communication networks between the four tissues in mouse and validate these against the plasma proteome of human and rat (provided by the MoTrPAC consortium BIC) similar to multi-species validation studies published previously by our group (PMCID6399495, 5935137). Moreover, we will also perform molecular validation studies confirming exercise-stimulated changes in novel circulating factors, and determine functionality of these communication networks using conventional loss and gain of expression approaches. Our findings will be of strong scientific impact as we will identify novel exercise-induced regulatory nodes and key driver pathways underlying improvements in metabolism, determine novel exercise driven endocrine interactions, and generate a mouse sample biobank and data repository that will be integrated into the MoTrPAC data hub for novel hypothesis generation by the entire research community.

抽象的日常身体活动是预防或改善与以下疾病相关的并发症的已知干预措施然而，慢性运动的代谢适应机制。此外，人类研究表明锻炼的范围很广。适应一些难以适应与训练相关的特定代谢改善的个体。由于传统的动物研究主要集中在少数啮齿动物品系上，因此在当前的应用中我们将研究约 100 种不同的雄性和雌性近交系小鼠的运动训练适应性称为 UCLA 混合小鼠多样性面板 (HMDP)，并将这些数据与现有的 MoTrPAC 集成斯坦福大学生物信息学中心 (BIC) 的数据存储库在目标 1 中，我们将确定控制运动代谢和整合多个“组学”平台（转录组学、蛋白质组学、代谢组学）使用贝叶斯分析和合并组学来识别调控网络和小鼠运动训练的关键驱动节点，并用公开数据验证这些发现来自 MoTrPAC 联盟对大鼠和人类运动训练的研究，我们将在目标 2 中使用。定量内分泌网络相互作用估计（QENIE）对新组织间的功能进行注释通讯回路（心脏和骨骼肌之间、肝脏和脂肪之间）对于维持生命至关重要我们在此提供的研究结果显示了耐力、性别特异性组织串扰。我们将构建维持代谢稳态和对运动的反应。小鼠四个组织之间的通信网络，并针对血浆验证这些网络人类和大鼠的蛋白质组（由 MoTrPAC 联盟 BIC 提供）类似于多物种验证我们小组之前发表的研究（PMCID6399495，5935137）此外，我们还将进行。分子验证研究证实了运动刺激的新型循环因子的变化，以及使用传统的表达损失和增益来确定这些通信网络的功能我们的研究结果将具有强大的科学影响，因为我们将确定新的运动诱发方法。调节节点和关键途径驱动新陈代谢的根本改善，确定新的运动驱动的内分泌相互作用，并生成小鼠样本生物库和数据存储库，集成到 MoTrPAC 数据中心，以便整个研究界生成新的假设。