Integrative analysis of aging and brain diseases using multi-organ and multi-omic biomedical data

The advent of artificial intelligence (AI) has ushered in a transformative era for human brain mapping. Integrating imaging, genetics, and proteomics with advanced computational techniques has opened unprecedented avenues for research, offering a more refined and multi-omics perspective on the brain and related diseases. Building on prior discussions on biological age and imaging-derived disease subtypes, this presentation by Dr. Wen explores the next step: combining AI-driven imaging endophenotypes with additional omics layers, including genetics and proteomics (PMID: 38718880). Dr. Wen will highlight approaches to integrating multi-organ imaging, genetic, and proteomic data, unraveling the genetic and molecular mechanisms of human aging and brain diseases. Two main topics will be discussed, including the multi-organ and multi-omics biological age derived by AI (PMID: 38942983; 38521789) and disease subtypes of four brain disorders (i.e., Alzheimer’s disease, autism, schizophrenia, and late-life depression; PMID: 37662256). The talk aims to shed light on the interplay between AI, multi-omics, and the complex processes driving aging and disease by bridging these data sources. Ultimately, this presentation seeks to demonstrate the potential of AI-powered, multi-omics, and multi-organ frameworks in providing a comprehensive understanding of the human brain and its intricate connections to systemic health and disease.