Research Questions:- What are the key biomarkers that can predict, diagnose, and monitor prognosis in autoimmune diseases (AID)?- How do genetic/epigenetic alterations and gut microbiome dysregulation contribute to immune imbalance and disease heterogeneity in AID?- Can multi-omics approaches be integrated to establish predictive models and stratify patients for personalized treatment? Aims:1. Establish a large-scale, multi-center AID cohort with standardized clinical data and biobanking. 2. Identify genetic, epigenetic, microbial, and immunological signatures associated with disease activity, organ involvement, and treatment outcomes. 3. Develop predictive and prognostic models using artificial intelligence and multi-omics data integration. 4. Translate novel biomarkers and targets into diagnostic kits, prediction software, and personalized therapeutic strategies.
The background and scientific rationale
Autoimmune diseases (AID) are highly heterogeneous, often chronic, and associated with substantial morbidity and mortality. They lack effective prevention and treatment guidelines that account for diverse clinical phenotypes and patient subgroups. Currently, robust predictive models and stratified therapeutic strategies are not well established. Preliminary studies from the research team have revealed critical roles of genetic/epigenetic factors, gut microbiota dysbiosis, and immune dysregulation in AID pathogenesis. However, the complex interplay of these factors across different clinical phenotypes remains poorly defined. By establishing a large-scale AID cohort and applying multi-omics analyses, this project aims to uncover novel biomarkers, elucidate disease mechanisms, and establish precision diagnostic and therapeutic strategies. This research will not only address major scientific questions but also fill a critical clinical gap, positioning this work at the forefront of global AID research.
