Multi-omic characterization of the immune mechanisms driving human atheroprogression

• Applicant: Marios Georgakis, Ph.D.
• Subject Area: Cardiology, Angiology ; Epidemiology and Medical Biometry/Statistics ; Human Genetics
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 512461526

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.

• DFG Programme: Independent Junior Research Groups