Study on PAD and CAS Based on Omics and Imaging

Overview

This study aims to investigate the pathogenesis of Peripheral Artery Disease (PAD) and Carotid Artery Stenosis (CAS) using a comprehensive multi-omics and multi-modal imaging approach. The study will enroll patients diagnosed with PAD or CAS and perform advanced imaging techniques, including NIR-II Imaging, DUS-based V-flow Imaging, and Laser Speckle Imaging, to assess vascular structure and function. Simultaneously, single-cell transcriptomics, metabolomics, lipidomics, and proteomics analyses will be conducted on patient samples to identify key molecular targets and pathways involved in disease progression. Machine learning algorithms will be employed to integrate imaging and multi-omics data, enabling the development of predictive models for more accurate disease diagnosis and stratification. The findings from this study are expected to provide novel insights into the molecular mechanisms underlying PAD and CAS and contribute to the development of personalized therapeutic strategies.

Background and Rationale Peripheral Artery Disease (PAD) and Carotid Artery Stenosis (CAS) are prevalent vascular disorders associated with significant morbidity and mortality. Despite advances in diagnostic and therapeutic approaches, the molecular mechanisms driving these diseases remain poorly understood. This study leverages cutting-edge multi-omics technologies and advanced imaging modalities to unravel the complex pathogenesis of PAD and CAS, with the ultimate goal of identifying novel biomarkers and therapeutic targets. Study Objectives Primary Objective: To integrate multi-modal imaging data (NIR-II Imaging, DUS-based V-flow Imaging, and Laser Speckle Imaging) with multi-omics data using machine learning algorithms for improved disease prediction and stratification. Study Design This is a prospective, observational study involving patients diagnosed with PAD or CAS. The study will include the following components: Imaging Analysis: 1. NIR-II Imaging: To visualize deep tissue vascular structures and hemodynamics. 2. DUS-based V-flow Imaging: To assess blood flow dynamics and vascular stenosis. 3. Laser Speckle Imaging: To evaluate microvascular perfusion and endothelial function. Multi-Omics Analysis: 1. Single-cell Transcriptomics: To profile gene expression at the single-cell level and identify cell-type-specific changes. 2. Metabolomics and Lipidomics: To characterize metabolic and lipid profiles associated with disease progression. 3. Proteomics: To identify differentially expressed proteins and signaling pathways. 4. Data Integration and Machine Learning: Imaging and multi-omics data will be integrated using advanced machine learning algorithms to develop predictive models for disease diagnosis, progression, and therapeutic response. Study Population The study will enroll patients diagnosed with PAD or CAS, along with age- and sex-matched healthy controls. Inclusion and exclusion criteria will be applied to ensure a homogeneous study population. Expected Outcomes 1. Identification of key molecular and cellular pathways involved in PAD and CAS pathogenesis. 2. Development of a multi-modal predictive model for accurate disease diagnosis and stratification. 3. Discovery of novel biomarkers and therapeutic targets for personalized medicine. Ethical Considerations The study protocol has been reviewed and approved by the Institutional Review Board (IRB) to ensure the protection of human subjects. Informed consent will be obtained from all participants prior to their enrollment in the study. Significance This study represents a pioneering effort to integrate multi-omics and multi-modal imaging data for a comprehensive understanding of PAD and CAS. The findings are expected to advance the field of vascular biology and contribute to the development of precision medicine approaches for these debilitating diseases.