1. Brain mapping across 16 autism mouse models reveals a spectrum of functional connectivity subtypes
- Author
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Michela Fagiolini, Fritjof Helmchen, Jason P. Lerch, Davide Pozzi, Michela Matteoli, Alberto Galbusera, Marco Pagani, Giovanni Provenzano, Abhishek Banerjee, J. Ellegood, Maria Luisa Scattoni, Marija Markicevic, Markus Rudin, Nicole Wenderoth, Valerio Zerbi, Alessandro Gozzi, M. Albert Basson, Yuri Bozzi, University of Zurich, and Gozzi, A
- Subjects
Autism Spectrum Disorder ,Personalized treatment ,Population ,2804 Cellular and Molecular Neuroscience ,610 Medicine & health ,Biology ,Brain mapping ,2738 Psychiatry and Mental Health ,Mice ,Cellular and Molecular Neuroscience ,Functional brain ,Neural Pathways ,mental disorders ,1312 Molecular Biology ,medicine ,Animals ,10064 Neuroscience Center Zurich ,Autistic Disorder ,education ,Molecular Biology ,Brain Mapping ,education.field_of_study ,10242 Brain Research Institute ,Functional connectivity ,Brain ,medicine.disease ,Magnetic Resonance Imaging ,Psychiatry and Mental health ,Autism spectrum disorder ,570 Life sciences ,biology ,Autism ,Identification (biology) ,Neuroscience - Abstract
Autism Spectrum Disorder (ASD) is characterized by substantial, yet highly heterogeneous abnormalities in functional brain connectivity. However, the origin and significance of this phenomenon remain unclear. To unravel ASD connectopathy and relate it to underlying etiological heterogeneity, we carried out a bi-center cross-etiological investigation of fMRI-based connectivity in the mouse, in which specific ASD-relevant mutations can be isolated and modeled minimizing environmental contributions. By performing brain-wide connectivity mapping across 16 mouse mutants, we show that different ASD-associated etiologies cause a broad spectrum of connectional abnormalities in which diverse, often diverging, connectivity signatures are recognizable. Despite this heterogeneity, the identified connectivity alterations could be classified into four subtypes characterized by discrete signatures of network dysfunction. Our findings show that etiological variability is a key determinant of connectivity heterogeneity in ASD, hence reconciling conflicting findings in clinical populations. The identification of etiologically-relevant connectivity subtypes could improve diagnostic label accuracy in the non-syndromic ASD population and paves the way for personalized treatment approaches., Molecular Psychiatry, 26 (12), ISSN:1359-4184, ISSN:1476-5578
- Published
- 2021
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