Many diseases, including obesity, have systemic effects that perturb multiple organ systems throughout the body1,2.
However, tools for comprehensive, high-resolution analysis of
disease-associated changes at the whole-body scale have been lacking.
Here we developed MouseMapper, a suite of foundation-model-based
deep-learning algorithms enabling multi-system analysis of disease
across the entire mouse body. MouseMapper enables whole-body
quantitative analysis of nerves and immune cells, resolving fine axonal
branches and immune-cell clusters while automatically segmenting 31
organs and tissues. We used MouseMapper to study diet-induced obesity,
and identified structural alterations of the infraorbital branch of the
trigeminal ganglia. This structural impairment in infraorbital nerves
was associated with functional sensory deficits in whisker sensing.
Furthermore, we identified proteomic changes in the trigeminal ganglion
affecting axon remodelling and complement pathways both in mice and
humans. MouseMapper also generated detailed three-dimensional
inflammation maps by characterizing immune cell cluster compositions
across tissues. The MouseMapper framework demonstrates robust
generalizability across different imaging resolutions and datasets. Our
study provides a powerful, scalable approach for identifying and
quantifying systemic pathologies, bridging molecular insights from
animal models to human conditions.