Metabolic interactions in the vascular wall: an integrated experimental and computational approach

血管壁代谢相互作用：综合实验和计算方法

基本信息

批准号：
10660336
负责人：
Alisa S Morss Clyne
金额：
$ 74.37万
依托单位：
UNIV OF MARYLAND, COLLEGE PARK
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：
2023-05-01 至 2027-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10660336
关键词：
Adult Affect Alzheimer&apos s Disease American Arterial Fatty Streak Biochemical Pathway Biomedical Engineering Blood Blood Glucose Blood Vessels Brain Calcium Signaling Cardiovascular Diseases Cell Communication Cell Membrane Permeability Cell model Cells Cellular Metabolic Process Cholesterol Coculture Techniques Communities Complex Computer Analysis Computer Models Consumption Data Disease Drug Interactions Endothelial Cells Endothelium Engineering Environment Experimental Models Exposure to Fatty Acids Fatty acid glycerol esters Functional disorder Glucose Glutamine Goals Growth Factor Heart Diseases Human In Vitro Individual Ions Isotopes Light Link Malignant Neoplasms Mass Spectrum Analysis Measures Metabolic Metabolic dysfunction Metabolic syndrome Metabolism Methods Modeling Morbidity - disease rate Nutrient Organism Patients Persons Pharmaceutical Preparations Phenotype Physiological Proliferating Risk Signal Transduction Smooth Muscle Myocytes Testing Tissues Triglycerides Tunica Intima Vascular Endothelial Cell Vascular Endothelium Vascular Smooth Muscle blood lead cardiovascular disorder risk cardiovascular disorder therapy cell type computer program design experimental study glucose metabolism glucose uptake in silico in vivo metabolic abnormality assessment migration mortality novel therapy design tissue culture

项目摘要

Project Summary Nearly 1 in 3 American adults has metabolic syndrome, a complex disorder defined by elevations in blood sugar, cholesterol, and triglycerides. Patients with metabolic syndrome have a high cardiovascular disease risk due to interactions among the elevated blood metabolites. However, since we do not have good methods for studying integrated and interacting metabolic changes, we treat each metabolic abnormality individually. As a result, patients are often on multiple medications, potentially decreasing the ability of each drug to normalize blood metabolites and raising the risk for negative drug interactions. In this project, we propose a novel integrated experimental and computational bioengineering approach to study how metabolic abnormalities contribute to cardiovascular disease. Specifically, we will study metabolic interactions between endothelial cells, which line the inside of the blood vessels, and vascular smooth muscle cells, which contribute to cardiovascular disease when they change their function. We will engineer a computational isotope-assisted metabolic flux analysis (iMFA) model, which uses experimental mass spectrometry data to estimate intracellular metabolic fluxes and metabolite transport. The computational model will enable us to develop new hypotheses for and plan studies into how metabolic changes (from altered blood metabolites or therapies) affect the vascular wall. We hypothesize that EC metabolic dysfunction increases the transport of metabolites that promote VSMC to switch from a contractile to a synthetic phenotype. In turn, synthetic vSMC enhance EC metabolite transport to support proliferation. To explore this hypothesis, we will combine in vitro, in silico, and ex vivo studies to: 1) Determine how EC dysfunction in altered metabolic environments impacts metabolite transport; 2) Measure how altered metabolites synergistically shift vSMC to a synthetic phenotype; and 3) Investigate how EC-vSMC crosstalk impacts cell metabolism and phenotype in the vascular wall. We will start with single cell models of endothelial and vascular smooth muscle cells, which will simulate the diversity of human nutrient levels. We will the integrate the two cell types to understand their crosstalk in vitro, in silico, and ex vivo. At each step, we will relate metabolism to cell phenotype and function to link the model to cardiovascular disease. The computational iMFA model of integrated endothelial-vascular smooth muscle cell metabolism, transport, and function will enable us to develop new hypotheses for and plan studies into how metabolic changes from altered blood metabolites or therapies affect the vascular wall. By changing the parenchymal cell type, the model can then be extended to study vascular metabolic interactions in other tissues (e.g., brain) and shed light into other diseases in which integrated EC metabolism and transport (e.g., Alzheimer’s disease).

项目概要近三分之一的美国成年人患有代谢综合征，这是一种以血液升高为特征的复杂疾病糖、胆固醇和甘油三酯患有代谢综合征的患者患有心血管疾病的风险很高。由于血液代谢物升高之间的相互作用，但是，由于我们没有好的方法。通过研究综合和相互作用的代谢变化，我们单独对待每种代谢异常。结果，患者经常服用多种药物，可能会降低每种药物恢复正常的能力血液代谢并增加不良药物相互作用的风险。在这个项目中，我们提出了一种新颖的综合实验和计算生物工程方法研究代谢异常如何导致心血管疾病具体来说，我们将研究代谢。血管内部的内皮细胞与血管平滑肌之间的相互作用当它们改变功能时会导致心血管疾病。计算同位素辅助代谢通量分析 (iMFA) 模型，使用实验质量光谱数据来估计细胞内代谢通量和代谢物运输的计算模型。将使我们能够开发新的假设并计划研究代谢如何变化（从血液代谢物或疗法）影响血管壁。我们发现 EC 代谢功能障碍会增加代谢物的转运，从而促进 VSMC 从收缩表型转变为合成表型反过来，合成 vSMC 增强 EC 代谢物转运。为了探索这一假设，我们将结合体外、计算机和离体研究：1) 确定改变的代谢环境中 EC 功能障碍如何影响代谢物运输；2) 测量如何影响代谢物转运；改变的代谢物协同地将vSMC转变为合成表型；以及3)研究EC-vSMC如何串扰影响血管壁的细胞代谢和表型。我们将从内皮细胞和血管平滑肌细胞的单细胞模型开始，该模型将模拟我们将整合两种细胞类型以了解它们在体外的串扰，在计算机和离体中，我们将代谢与细胞表型和功能联系起来，以将模型连接起来。心血管疾病。整合内皮-血管平滑肌细胞代谢、转运、运输的计算 iMFA 模型和功能将使我们能够开发新的假设并计划研究代谢如何从改变的血液代谢或疗法通过改变实质细胞类型来影响血管壁。然后可以扩展到研究其他组织（例如大脑）中的血管代谢相互作用，并揭示其他整合 EC 代谢和运输的疾病（例如阿尔茨海默病）。