Multi-omics

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.

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, advanced lung and cardiovascular imaging, 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.

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.