Brain mapping across 16 autism mouse models reveals a spectrum of functional connectivity subtypes

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 carr...

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Vydáno v:Molecular psychiatry Ročník 26; číslo 12; s. 7610 - 7620
Hlavní autoři: Zerbi, V, Pagani, M, Markicevic, M, Matteoli, M, Pozzi, D, Fagiolini, M, Bozzi, Y, Galbusera, A, Scattoni, M L, Provenzano, G, Banerjee, A, Helmchen, F, Basson, M A, Ellegood, J, Lerch, J P, Rudin, M, Gozzi, A, Wenderoth, N
Médium: Journal Article
Jazyk:angličtina
Vydáno: England Nature Publishing Group 01.12.2021
Témata:
Animal models
Animals
Autism
Autism Spectrum Disorder - diagnostic imaging
Autism Spectrum Disorder - genetics
Autistic Disorder - diagnostic imaging
Autistic Disorder - genetics
Brain
Brain Mapping
Etiology
Functional magnetic resonance imaging
Magnetic Resonance Imaging
Mice
Neural networks
Neural Pathways
ISSN:1359-4184, 1476-5578, 1476-5578
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Shrnutí: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.
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ISSN:1359-4184
1476-5578
1476-5578
DOI:10.1038/s41380-021-01245-4