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A deep-learning framework reveals whole-body perturbations at cell level

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...

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Autori principali: Kaltenecker, Doris (Autore) , Horvath, Izabela (Autore) , Al-Maskari, Rami (Autore) , Chen, Ying (Autore) , Kolabas, Zeynep Ilgin (Autore) , Hoeher, Luciano (Autore) , Todorov, Mihail (Autore) , Minde, David-Paul (Autore) , Kapoor, Saketh (Autore) , Turhan, Sena Gül (Autore) , Kuemmerle, Louis B. (Autore) , Steinke, Hanno (Autore) , Wohlgemuth, Tim (Autore) , Ali, Mayar (Autore) , Kofler, Florian (Autore) , Morigny, Pauline (Autore) , Geppert, Julia (Autore) , Jeridi, Denise (Autore) , Wittmann, Bastian (Autore) , Luo, Jie (Autore) , Shit, Suprosanna (Autore) , Cigankova, Carolina (Autore) , Kolenic, Victor Miro (Autore) , Gür, Nilsu (Autore) , Aydeniz, Eren (Autore) , Yücecan, Alara (Autore) , Ertürk, Melissa (Autore) , Simons, Laurent H. A. (Autore) , Pan, Chenchen (Autore) , Piraud, Marie (Autore) , Rueckert, Daniel (Autore) , Rohm, Maria (Autore) , Hellal, Farida (Autore) , Elsner, Markus (Autore) , Bhatia, Harsharan Singh (Autore) , Bechmann, Ingo (Autore) , Menze, Bjoern H. (Autore) , Herzig, Stephan (Autore) , Paetzold, Johannes Christian (Autore) , Berriel Diaz, Mauricio (Autore) , Ertürk, Ali (Autore)
Natura: Article (Journal)
Lingua:inglese
Pubblicazione: 20 May 2026
In: Nature
Year: 2026, Volume: 655, Fascicolo: 8124, Pages: 1016-1026
ISSN:1476-4687
DOI:10.1038/s41586-026-10535-2
Accesso online:Verlag, kostenfrei, Volltext: https://doi.org/10.1038/s41586-026-10535-2
Verlag, kostenfrei, Volltext: https://www.nature.com/articles/s41586-026-10535-2
Testo
Note sull'autore:Doris Kaltenecker, Izabela Horvath, Rami Al-Maskari, Ying Chen, Zeynep Ilgin Kolabas, Luciano Hoeher, Mihail Todorov, David-Paul Minde, Saketh Kapoor, Sena Gül Turhan, Louis B. Kuemmerle, Hanno Steinke, Tim Wohlgemuth, Mayar Ali, Florian Kofler, Pauline Morigny, Julia Geppert, Denise Jeridi, Bastian Wittmann, Jie Luo, Suprosanna Shit, Carolina Cigankova, Victor Miro Kolenic, Nilsu Gür, Eren Aydeniz, Alara Yücecan, Melissa Ertürk, Laurent H.A. Simons, Chenchen Pan, Marie Piraud, Daniel Rueckert, Maria Rohm, Farida Hellal, Markus Elsner, Harsharan Singh Bhatia, Ingo Bechmann, Bjoern H. Menze, Stephan Herzig, Johannes Christian Paetzold, Mauricio Berriel Diaz, Ali Ertürk
Descrizione
Riassunto: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.
Descrizione del documento:Gesehen am 24.09.2026
Descrizione fisica:Online Resource
ISSN:1476-4687
DOI:10.1038/s41586-026-10535-2

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