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Publications

Journal Article Ahead of print

PubMed: 42162424 DOI: 10.1038/s41586-026-10535-2

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

Nature

Authors: 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

Affiliations

  • Institute for Diabetes and Cancer (IDC), Helmholtz Munich, German Research Center for Environmental Health, Neuherberg, Germany.
  • Joint Heidelberg-IDC Translational Diabetes Program, Heidelberg University Hospital, Heidelberg, Germany.
  • German Center for Diabetes Research (DZD), Neuherberg, Germany.
  • Institute for Intelligent Biotechnologies, Helmholtz Munich, German Research Center for Environmental Health, Neuherberg, Germany.
  • TUM School of Computation, Information and Technology (CIT), Technical University of Munich, Munich, Germany.
  • Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany.
  • Munich Medical Research School (MMRS), Munich, Germany.
  • Institute of Computational Biology, Helmholtz Munich, Neuherberg, Germany.
  • School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany.
  • Institute of Anatomy, University of Leipzig, Leipzig, Germany.
  • Helmholtz AI, Helmholtz Munich, Neuherberg, Germany.
  • Department for Quantitative Biomedicine, University of Zurich, Zurich, Switzerland.
  • AI for Image-Guided Diagnosis and Therapy, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany.
  • Hertie Institute for AI in Brain Health, University of Tübingen, Tübingen, Germany.
  • Department of Industrial and Molecular Pharmaceutics, Purdue University, West Lafayette, IN, USA.
  • Purdue University Institute for Cancer Research, West Lafayette, IN, USA.
  • Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China.
  • Department of Computing, Imperial College London, London, United Kingdom.
  • Chair for AI in Healthcare and Medicine, Technical University of Munich (TUM) and TUM University Hospital, Munich, Germany.
  • Chair Molecular Metabolic Control, TU, Munich, Germany.
  • Department of Radiology, Weill Cornell Medicine, New York, NY, USA.
  • Cornell Tech, New York, NY, USA.
  • Institute for Intelligent Biotechnologies, Helmholtz Munich, German Research Center for Environmental Health, Neuherberg, Germany.
  • Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany.
  • School of Medicine, Koç University, Istanbul, Turkey.
  • Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.
  • Deep Piction, Munich, Germany.

Abstract

Many diseases, including obesity, have systemic effects that perturb multiple organ systems throughout the body 1,2. 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.

MeSH

Cells, Multiple Chronic Conditions, Trigeminal Ganglion, Axons, Deep Learning, Obesity, Learning, Tissues