Clinical Research Directory

Dongzong Cardiovascular Bio-imaging Registry Study

The DAILY project is a large-scale, multicenter, prospective initiative designed to establish a comprehensive bio-imaging database that integrates multidimensional data, including living environments, psychosocial and cognitive assessments, psychosocial and cognitive assessments, panvascular and body imaging (fundus, carotid artery, chest, abdomen, and heart), electrocardiograms, multi-omics profiles, clinical medication and surgical records, and health outcomes. Leveraging this extensive, multiscale dataset, the project aims to elucidate the intricate interplay between genetic biology and environmental factors in driving downstream biological alterations, thereby shaping lung and cardiovascular structural and functional phenotypes, and ultimately influencing the onset and progression of cardiovascular diseases (CVD). Through a systematic exploration and understanding of this complex network, the project seeks to identify critical intervention points and develop innovative strategies for the prevention and management of CVD.

Multi-Omics Study of COPD Stages and Traditional Chinese Medicine Syndromes

This is a multicenter, prospective, observational cohort study of patients with chronic obstructive pulmonary disease (COPD), individuals with pre-COPD, and healthy participants. The study will enroll approximately 400 participants, including individuals with pre-COPD, patients with stable COPD at different GOLD stages, patients with acute exacerbation of COPD, and healthy controls. Participants will not be assigned to any study intervention. Clinical information, pulmonary function, imaging information, traditional Chinese medicine syndrome assessment, and biological samples will be collected according to the study protocol. Multi-omics analyses, including metagenomics, metabolomics, transcriptomics, and proteomics, will be used to characterize molecular features associated with COPD stages and traditional Chinese medicine syndromes. Participants will be followed to evaluate clinical characteristics, exacerbations, pulmonary function changes, and multi-omics features over time.

Multi-Omics Inflammatory Phenotype for ABPA Recurrence Risk Prediction

To develop and externally validate a machine learning model for predicting the 1-year risk of relapse in patients with stable ABPA, and to further evaluate its value in risk stratification and clinical decision-making.

Neurophenotype Predicts CD Disease Progression

The goal of this observational study is aimed to develop a novel multimodal neuroimaging-based model to characterize the neurophenotype of Crohn's Disease patients and assess its ability for predicting disease progression, using multiomics data to interpret the model. Participants will be followed-up of at least six months for patients without disease progression to assess the relationship between neurophenotype and intestinal outcomes.