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Peer-reviewedCC BYNature Neuroscience

Autism subtypes identified using cross-species functional connectivity analyses

  • Marco Pagani1,2,3
  • Valerio Zerbi4,5
  • Silvia Gini6,2
  • Filomena Grazia Alvino2
  • Abhishek Banerjee7,8,9
  • Andrea Barberis10
  • M. Albert Basson11,12
  • Yuri Bozzi6
  • Alberto Galbusera2
  • Jacob Ellegood13
  • Michela Fagiolini14,15
  • Jason P. Lerch16,17,18
11 more authors
  • Michela Matteoli19,20
  • Caterina Montani2,21
  • Davide Pozzi20
  • Giovanni Provenzano22
  • María Luisa Scattoni23
  • Nicole Wenderoth24
  • Ting Xu25
  • Michael Vincent Lombardo26
  • Michael Peter Milham27,25
  • Adriana Di Martino1
  • Alessandro Gozzi28
28 affiliations
  1. 1Autism Center, Child Mind Institute, New York, NY, USA
  2. 2Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, CNCS@UNITN, Rovereto, Italy
  3. 3IMT School for Advanced Studies, Lucca, Italy
  4. 4Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland
  5. 5Department of Psychiatry, University of Geneva, Geneva, Switzerland
  6. 6Center for Mind and Brain Sciences (CIMeC), University of Trento, Rovereto, Italy
  7. 7Adaptive Decisions Lab, Blizard Institute, Queen Mary University of London, London, UK
  8. 8Brain Research Institute, University of Zurich, Zurich, Switzerland
  9. 9Department of Pharmacology, University of Oxford, Oxford, UK
  10. 10Synaptic Plasticity of Inhibitory Networks, Istituto Italiano di Tecnologia, Genova, Italy
  11. 11Centre for Craniofacial and Regenerative Biology, King's College London, London, UK
  12. 12Department of Clinical and Biomedical Sciences, University of Exeter, Exeter, UK
  13. 13Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada
  14. 14Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
  15. 15International Research Center for Neurointelligence, University of Tokyo, Tokyo, Japan
  16. 16Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
  17. 17Mouse Imaging Centre, The Hospital for Sick Children, Toronto, Ontario, Canada
  18. 18Oxford Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
  19. 19Department of Biomedical Sciences, Humanitas University, Milan, Italy
  20. 20IRCCS Humanitas Research Hospital, Milan, Italy
  21. 21IRCCS Ospedale Policlinico San Martino, Genova, Italy
  22. 22Department of Cellular, Computational and Integrative Biology. University of Trento, Trento, Italy
  23. 23National Center for Rare Diseases, Istituto Superiore di Sanità, Rome, Italy
  24. 24Neural Control of Movement Lab, ETH Zürich, Zurich, Switzerland
  25. 25Center for Integrative Developmental Neuroscience, Child Mind Institute, New York, NY, USA
  26. 26Laboratory for Autism and Neurodevelopmental Disorders, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, Rovereto, Italy
  27. 27Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
  28. 28Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, CNCS@UNITN, Rovereto, Italy. [email protected]
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Abstract

It is often assumed that phenotypic heterogeneity in autism reflects underlying pathobiological variation. However, direct evidence supporting this link is lacking. Leveraging cross-species functional neuroimaging, we show that brain dysconnectivity patterns in autism can be parsed into biologically dissociable subtypes. Specifically, we found that functional magnetic resonance imaging (fMRI) connectivity alterations in 20 distinct genetic mouse models of autism cluster into hypoconnectivity-dominant and hyperconnectivity-dominant subtypes. These subtypes are linked to distinct biological pathways, with hypoconnectivity being associated with synaptic dysfunction and hyperconnectivity reflecting transcriptional and immune-related alterations. Here we identified analogous hypoconnectivity and hyperconnectivity subtypes in a multicenter human fMRI dataset of n = 940 individuals with idiopathic autism and n = 1,036 neurotypical individuals. The human autism subtypes are highly replicable, are associated with distinct functional network architectures and behavioral profiles and recapitulate the synaptic and immune-related pathways identified in the rodent dataset. Our work provides a new empirical framework for targeted subtyping of the autism spectrum.

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Cite

BibTeXRIS
BibTeX
@article{pagani2026autism,
  title = {{Autism subtypes identified using cross-species functional connectivity analyses}},
  author = {Marco Pagani and Valerio Zerbi and Silvia Gini and Filomena Grazia Alvino and Abhishek Banerjee and Andrea Barberis and M. Albert Basson and Yuri Bozzi and Alberto Galbusera and Jacob Ellegood and Michela Fagiolini and Jason P. Lerch and Michela Matteoli and Caterina Montani and Davide Pozzi and Giovanni Provenzano and María Luisa Scattoni and Nicole Wenderoth and Ting Xu and Michael Vincent Lombardo and Michael Peter Milham and Adriana Di Martino and Alessandro Gozzi},
  journal = {Nature Neuroscience},
  year = {2026},
  month = may,
  doi = {10.1038/s41593-026-02287-z},
  url = {https://doi.org/10.1038/s41593-026-02287-z},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Autism subtypes identified using cross-species functional connectivity analyses
AU  - Marco Pagani
AU  - Valerio Zerbi
AU  - Silvia Gini
AU  - Filomena Grazia Alvino
AU  - Abhishek Banerjee
AU  - Andrea Barberis
AU  - M. Albert Basson
AU  - Yuri Bozzi
AU  - Alberto Galbusera
AU  - Jacob Ellegood
AU  - Michela Fagiolini
AU  - Jason P. Lerch
AU  - Michela Matteoli
AU  - Caterina Montani
AU  - Davide Pozzi
AU  - Giovanni Provenzano
AU  - María Luisa Scattoni
AU  - Nicole Wenderoth
AU  - Ting Xu
AU  - Michael Vincent Lombardo
AU  - Michael Peter Milham
AU  - Adriana Di Martino
AU  - Alessandro Gozzi
PY  - 2026
DA  - 2026/05/15
JO  - Nature Neuroscience
DO  - 10.1038/s41593-026-02287-z
UR  - https://doi.org/10.1038/s41593-026-02287-z
AB  - It is often assumed that phenotypic heterogeneity in autism reflects underlying pathobiological variation. However, direct evidence supporting this link is lacking. Leveraging cross-species functional neuroimaging, we show that brain dysconnectivity patterns in autism can be parsed into biologically dissociable subtypes. Specifically, we found that functional magnetic resonance imaging (fMRI) connectivity alterations in 20 distinct genetic mouse models of autism cluster into hypoconnectivity-dominant and hyperconnectivity-dominant subtypes. These subtypes are linked to distinct biological pathways, with hypoconnectivity being associated with synaptic dysfunction and hyperconnectivity reflecting transcriptional and immune-related alterations. Here we identified analogous hypoconnectivity and hyperconnectivity subtypes in a multicenter human fMRI dataset of n = 940 individuals with idiopathic autism and n = 1,036 neurotypical individuals. The human autism subtypes are highly replicable, are associated with distinct functional network architectures and behavioral profiles and recapitulate the synaptic and immune-related pathways identified in the rodent dataset. Our work provides a new empirical framework for targeted subtyping of the autism spectrum.
SN  - 1097-6256
SN  - 1546-1726
ER  -