Breakout Session Leaders: Musa Mhlanga &  Shyam Prabhakar 

This session will explore how longitudinal patient studies, integrated with genetic and molecular data, can advance understanding of disease mechanisms and cellular pathogenesis within HCA 2.0. Participants will discuss the importance of collecting whole genome sequencing (WGS) and histopathology data in parallel with single-cell datasets, and how these complementary data layers can strengthen the identification of disease-associated cell states while helping distinguish correlation from causation in single-cell analyses. The conversation will also examine how approaches such as single-cell eQTL mapping, longitudinal sampling, and multimodal integration can provide deeper insight into disease progression, treatment response, and inter-individual variability. In addition, the session will consider what additional layers of information, including clinical, imaging, environmental, and functional data, may be necessary to build more comprehensive and mechanistic models of human disease across the HCA ecosystem.