Mapping the Neuro-Connectional Landscape in Autism with Cross-Species fMRI

Background:

Functional brain mapping using resting-state functional magnetic resonance imaging (rsfMRI) and other imaging techniques has revealed prominent, yet highly heterogeneous abnormalities in interregional connectivity in individuals with autism. However, several fundamental questions as to the origin and significance of this phenomenon remain unaddressed.

Objectives:

This research tackles two major open questions in the field: (a) does genetic or etiological variability associated with autism account for the heterogeneous rsfMRI findings observed network disruption? (b) Can we link individual autism-associated genetic etiologies or pathophysiological motifs to specific patterns of rsfMRI dysconnectivity?

Methods:

We have developed rsfMRI-based methods for connectivity mapping in the laboratory mouse, where genetic determinants and neuronal activity can be controlled with high precision. To probe the translational relevance of our measurements, we have mapped and compared rsfMRI connectivity patterns in human carrier of 16p11.2 deletion (del; SFARI VIP cohort), and a mouse line harboring an orthologous chromosomal deletion. We have next applied our rsfMRI approach to map N = 20 different mouse lines (collaboration with ETH, Zurich) harboring high-penetrance mutations associated to syndromic forms of autism, with the aim to identify etiologically-relevant connectional fingerprints representative of human ASD heterogeneity.

Results:

We observed remarkable correspondences between mouse and human fMRI network organization, enabling a direct extrapolation of imaging features across species. Corroborating the translational relevance of our approach, rsfMRI mapping in human 16p11.2 del patients and a mouse model recapitulating the same genetic defect, revealed highly consistent prefrontal hypoconnectivity. We next applied this approach to multiple mouse lines harboring autism-associated mutations. Results showed that different genetic etiologies can give rise to diverse even diverging, yet classifiable cross-mutational connectivity fingerprints, and that these alterations are associated with disrupted fMRI network dynamics.

Conclusions:

Our results establish a mechanistic link between specific neuro-genetic etiologies and distinct patterns of dysconnectivity and point at a key contribution of etiological variability to the observation of heterogeneous patterns of connectivity in ASD. The implication of these findings for the origin and mechanistic interpretation of rsfMRI findings in human ASD studies will be critically discussed.