Multi-omic characterization of the immune mechanisms driving human atheroprogression

驱动人类动脉粥样硬化进展的免疫机制的多组学特征

• 批准号: 512461526
• 负责人: Dr. Marios Georgakis, Ph.D.
• 金额: --
• 依托单位: Institut für Schlaganfall- und Demenzforschung (ISD)
• 依托单位国家: 德国
• 项目类别: Independent Junior Research Groups
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/512461526?language=en
• 关键词: Multi; omic; characterization; immune; mechanisms

Atherosclerotic cardiovascular disease (CVD) is the leading cause of mortality and morbidity worldwide. The medical management of atherosclerosis has dramatically improved in recent decades with the development of effective cholesterol-lowering strategies and the aggressive management of other vascular risk factors. However, the residual rates of CVD continue being unacceptably high thus calling for new treatment paradigms in lowering risk. An extensive line of research supports that an immune response within the arterial wall drives atheroprogression and recent trials provided proof-of-concept that immunotherapeutic agents can lower CVD risk. However, the clinical translation of atheroprotective immunotherapies is lagging behind due to the lack of drugs that precisely modulate the immune response underlying atheroprogression and the lack of specific biomarkers of atheroinflammation that could be used to personalize treatments. This proposal is focused on addressing these two key challenges. The overarching goals are to detect novel drug targets for immunotherapies and uncover endophenotypes of atheroinflammation. Extending and scaling a pipeline established by my previous work, I will first aim to dissect immune pathways underlying CVD by leveraging large-scale proteomic, single-cell transcriptomic, and metabolomic data and anchoring them to genetic information. Integrating omics data from human atherosclerotic samples I will explore proteomic, transcriptomic, and cellular endophenotypic signatures of atheroinflammation that mediate the effects of modulating promising drug targets on risk of CVD. Utilizing cutting-edge single-cell and spatial transcriptomic technologies, I will then explore the molecular immune signatures of human carotid atherosclerotic plaques that reflect atheroprogression. Finally, by integrating these high-resolution molecular data with carotid MRI and peripheral blood proteomic analyses in a machine learning framework, I will aim to detect accessible in vivo biomarkers of the immune landscape of atherosclerosis. The findings from the proposed research will open the road for the clinical translation of more precise and personalized immunotherapeutic strategies with the ultimate goal of lowering the global burden of CVD.

动脉粥样硬化性心血管疾病（CVD）是全球死亡率和发病率的主要原因。近几十年来，随着有效降胆固醇策略的发展和其他血管危险因素的积极管理，动脉粥样硬化的医疗管理得到了显着改善。然而，CVD的残留率仍然高得不可接受，因此需要新的治疗模式来降低风险。广泛的研究支持动脉壁内的免疫反应驱动动脉粥样硬化进展，最近的试验提供了免疫抑制剂可以降低CVD风险的概念验证。然而，由于缺乏精确调节动脉粥样硬化进展相关免疫反应的药物以及缺乏可用于个性化治疗的动脉粥样硬化炎症特异性生物标志物，动脉粥样硬化保护免疫疗法的临床转化滞后。本建议的重点是应对这两个关键挑战。总体目标是检测免疫疗法的新药物靶点并揭示动脉粥样硬化炎症的内表型。扩展和扩展我以前的工作建立的管道，我将首先通过利用大规模蛋白质组学，单细胞转录组学和代谢组学数据并将其锚定到遗传信息来剖析CVD的免疫途径。整合来自人类动脉粥样硬化样本的组学数据，我将探索动脉粥样硬化炎症的蛋白质组学、转录组学和细胞内表型特征，这些特征介导调节有前景的药物靶点对CVD风险的影响。利用最先进的单细胞和空间转录组技术，我将探索人类颈动脉粥样硬化斑块的分子免疫特征，反映动脉粥样硬化的进展。最后，通过在机器学习框架中将这些高分辨率分子数据与颈动脉MRI和外周血蛋白质组学分析相结合，我的目标是检测动脉粥样硬化免疫景观的体内生物标志物。这项研究的结果将为更精确和个性化的免疫策略的临床转化开辟道路，最终目标是降低CVD的全球负担。