A mechanistic 3D AI-powered map of genetic chILD

ABSTRACT/SUMMARY Leveraging the technologies and infrastructure in our previous LungMAP phases, we will construct a multi-scale map of developing acinar and alveolar structures during normal childhood and in the setting of childhood interstitial lung disease (chILD) characterized by aberrant lung morphogenesis. Linked to gene variants, chILD

provides a unique opportunity to understand key genetic pathways and cellular interactions of human acinar and alveolar development, in turn informing injury-repair associated with lung diseases throughout the lifespan. Working in a collaborative LungMAP3 consortium, including other Research Centers, the Data Coordinating

Center (DCC), the Human Tissue Core (HTC), our LungMAP3 project will use single-cell and spatial multiomics, high-resolution confocal and electron microscopy, patient-derived iPSCs, and bioinformatics including AI tools to define, model, and predict normal and diseased lung development. The resulting mechanistic insights and

enabling technologies will be disseminated to the entire lung community via disease atlases and web portals, as we have done during LungMAP1 and 2, to accelerate lung biology discoveries and disease therapies.