Can Mouse Imaging Studies Bring Order to Autism Connectivity Chaos?

Abstract

Functional Magnetic Resonance Imaging (fMRI) has consistently highlighted impaired or aberrant functional connectivity across brain regions of autism spectrum disorder (ASD) patients. However, the manifestation and neural substrates of these alterations are highly heterogeneous and often conflicting. Moreover, their neurobiological underpinnings and etiopathological significance remain largely unknown. A deeper understanding of the complex pathophysiological cascade leading to aberrant connectivity in ASD can greatly benefit from the use of model organisms where individual pathophysiological or phenotypic components of ASD can be recreated and investigated via approaches that are either off limits or confounded by clinical heterogeneity. Despite some obvious limitations in reliably modeling the full phenotypic spectrum of a complex developmental disorder like ASD, mouse models have played a central role in advancing our basic mechanistic and molecular understanding of this syndrome. Recent progress in mouse brain connectivity mapping via resting-state fMRI (rsfMRI) offers the opportunity to generate and test mechanistic hypotheses about the elusive origin and significance of connectional aberrations observed in autism. Here we discuss recent progress toward this goal, and illustrate initial examples of how the approach can be employed to establish causal links between ASD-related mutations, developmental processes, and brain connectional architecture. As the spectrum of genetic and pathophysiological components of ASD modeled in the mouse is rapidly expanding, the use of rsfMRI can advance our mechanistic understanding of the origin and significance of the connectional alterations associated with autism, and their heterogeneous expression across patient cohorts.

Deletion of autism risk gene Shank3 disrupts prefrontal connectivity

“…The use of directly translatable measurements of brain function and anatomy represents a distinctive feature of our approach that can be leveraged to cross-fertilize clinical and preclinical investigations of the macroscale substrates affected by ASD-related etiologies. Mouse models recapitulating syndromic forms of human disease-causing mutations can be used to establish causal relations between ASD-related genetic etiologies, abnormal macroscale connectivity and behavioral correlates, thus shedding light on the neurobiological mechanisms underlying ASD (Liska and Gozzi, 2016). Notably, using the same imaging paradigm employed here, we recently showed that orthologous 16p11.2 deletion results in remarkably similar patterns of functional under-connectivity in humans and mice, lending support to the possibility of directly relating neuroimaging readouts across species .…”

“…Functional connectivity based on rsfMRI is a method to map temporal dependency of spontaneous fluctuations of the BOLD signal between brain regions during no-task condition and is widely used in human clinical (Van Den Heuvel and Pol, 2010) and preclinical (Liska and Gozzi, 2016) studies to describe the macroscale functional organization of brain networks in autism and other neuropsychiatric disorders. Here we employed rsfMRI connectivity to detect putative derangements of functional networks associated to Shank3B homozygous mutation.…”

Altered neocortical gene expression, brain overgrowth and functional over-connectivity inChd8haploinsufficient mice

“…Similar rsfMRI studies in ASD mouse models may help bridge the gap between ASD models and the human condition (Liska and Gozzi 2016). As one example, homozygous Cntnap2 mouse mutants exhibit hypo-connectivity of the default mode network (Liska et al 2017), a phenotype often observed in idiopathic ASD patients (Cherkassky et al 2006) and recapitulating analogous clinical observations in humans with CNTNAP2 mutations (Scott- Van Zeeland et al 2010).…”

“…5B) did not significantly differ between Chd8 +/mice and littermate controls, eliminating a confounding contribution of anaesthesia to the observed functional hyper-connectivity. In vivo images were obtained using a 7.0 T MRI scanner (Bruker Biospin, Milan), as previously described (Liska et al 2016). Signal transmission and reception were achieved using a 72mm birdcage transmit coil and a 4-channel solenoid coil.…”

Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis

“…Since its onset in 2011 (Jonckers et al, 2011), mouse rsfMRI has developed in a number of centres and has grown to become a routine method with a number of applications, reviewed in (Chuang and Nasrallah, 2017;Gozzi and Schwarz, 2016;Hoyer et al, 2014;Jonckers et al, 2015Jonckers et al, , 2013Pan et al, 2015). Prominently, mouse rsfMRI has been used to investigate an extensive list of models, including Alzheimer's disease (Grandjean et al, 2014b, Shah et al, 2013, 2016cWiesmann et al, 2016;Zerbi et al, 2014), motor (DeSimone et al, 2016;Li et al, 2017), affective (Grandjean et al, 2016a), autism spectrum Haberl et al, 2015;Liska et al, 2018;Liska and Gozzi, 2016;Michetti et al, 2017;Sforazzini et al, 2016;Zerbi et al, 2018;Zhan et al, 2014), schizophrenia (Errico et al, 2015;Gass et al, 2016), pain (Buehlmann et al, 2018;Komaki et al, 2016), reward (Charbogne et al, 2017;Mechling et al, 2016), and demyelinating disorders (Hübner et al, 2017). Another application of mouse rsfMRI is the elucidation of large-scale functional alterations exerted by pharmacological agents (Razoux et al, 2013;Shah et al, 2016aShah et al, , 2015.…”