#Autism is often associated with an excess of synapses:
but how does this trait affect large-scale circuit function?

Here's what we found by modelling autism-related pruning deficits across-species🧠🐭
➡️tinyurl.com/y2yfj74o

By @MarcoPagani1985 @mvlombardo & al.

Thread 1/n
Postmortem investigations in idiopathic #Autism have consistently revealed an excess of excitatory synapses
tinyurl.com/y57cc4r5
tinyurl.com/y59mdffp
tinyurl.com/y3t64yfe

2/n
Seminal work form the #Sulzer_Lab @Columbia has shown that postmortem synaptic surplus in #Autism is associated with hyperactive mTOR signalling
➡️this is a molecular pathway often dysregulated in autism and a key point of convergence of many autism-risk genes

3/n
This got us wondering: how does this prevalent form of autism synaptopathy affect macro-scale circuit function?

4/n
As it turns out, mTOR-related synaptopathy can be effectively modelled in the 🐁by knocking out a gene that interacts with mTOR

➡️The gene's name is "Tsc2" and this has been elegantly validated in many previous studies including #Sulzer_Lab
tinyurl.com/yyqaqvqg

5/n
Using fMRI mapping in juvenile Tsc2+/- 🐁 we found that synaptic surplus is associated with fronto-striato-insular hyper-connectivity in these mutants

So this prevalent form of autism synaptopathy DOES affect macroscale circuit function!

6/n
We next asked: what could be causing the observed hyperconnectivity?

We probed structural connectivity in Tsc2 🐁 but we could not find any gross rewiring or white matter alterations either at macroscale (with DTI) or meso-scale (retrograde viral tracing)

7/n
Could synaptic surplus possibly *cause* rsfMRI overconnectivity?

In such case, superabundant spines in Tsc2🐭 should be functioning: @RaffaellaTonini probed AMPA/NMDA ratio - a metric sensitive to synaptic maturation - and found that most Tsc2 spines are indeed non-silent

8/n
Because spines serve as linear integrators of neuronal input in distributed circuits tinyurl.com/y2mkjo4d,
our hypothesis here is that an excess of spines could lead to increase feedforward connectivity and long-range coupling

9/n
To probe the plausibility of this hypothesis @lauraUlysse from the #DecoLab implemented a whole-brain computational model of 🐭rsfMRI connectivity

As predicted, the profile of hyperconnectivity in Tsc2 mice could be modelled by increasing long-range coupling factor "G"

10/n
To causally probe a mechanistic link between synaptic surplus and hyperconnectivity we next attempted to normalize mTOR signaling, using rapamycin

This lead to
➡️ complete rescue of synaptic surplus &
➡️ complete rescue of hyperconnectivity
linking the two phenomena!

11/n
Interestingly, we also found that
➡️Social deficits and increased stereotypies in Tsc2 🐭 are completely rescued by rapamycin
➡️ fronto-cortico-striatal hyper-connectivity is a good predictor of motor stereotypies!

12/n
The results of these 🐭 investigations are exciting because they mechanistically reconcile autism synaptopathy & connectopathy within a unifying multi-scale framework.
But are they clinically relevant?

13/n
The high prevalence of synaptic surplus and mTOR hyperactivity in idiopathic autism suggest that a similar hyperconnectivity signature could be identifiable in patients.

We thus examined fMRI scans from ABIDE-I and found clear hotspots of hyperconnectivity in insular areas

14/n
We next probed the corresponding networks involved and found the children with autism exhibit fronto-striato-insular overconnectivity, like observed in Tsc2 🐭!

This is consistent with our hypothesis, but how can we link this signature to mTOR signalling?

15/n
To do that, we run a gene decoding analysis of the observed hyperconnectivity signature

This analysis revealed that the identified fronto-striato-insular signature is significantly enriched with genes interacting with mTOR and TSC2!

16/n
However autism is heterogenous and not exclusively mTOR-related!

So the observed group-level association MUST be driven by a specific subgroup of patients in which this signature is especially prominent

To test this hypothesis we clustered insular connectivity profiles..

17/n
...and found:
➡️four distinct connectivity profiles (autism is INDEED heterogeneous!)
➡️as predicted only one subtype (#2) exhibits highly enriched mTOR interactome expression --> it drives group level changes!

18/n
So we causally linked mTOR-related synaptic pathology to large-scale circuit alterations, and identified a putatively segregable novel autism subtype!

Very grateful to @SFARIorg for generous funding & @StavrosTrak @LabPasqualetti @alibert_ & all twitterless collaborators!

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More from @Gozzi_Ale

7 Aug
Wondering whether axonal input *drives* fMRI-based functional connectivity? Us too!

Here is what we found using #chemogenetic deconstruction of rsfMRI in the mouse🐁🐭

➡️Cortical silencing results in paradoxical fMRI overconnectivity tinyurl.com/yy269j92

Thread below 1/n
Computational and empirical evidence suggest that structural and functional connectivity are robustly related

➡️ this recent review from @richardfbetzel @misicbata summarizes it all tinyurl.com/yyy5u3zm

2/n
⚠️A key prediction of structurally based models of fMRI coupling is that *inactivation* of a brain node would result in reduced rsfMRI connectivity with its targets⚠️

But is that really the case?

3/n
Read 19 tweets
15 May
**New preprint from the lab**

Regional, layer and cell-class specific connectivity of the mouse default mode network tinyurl.com/yddanw5w

Conceived & majestically led by @DrJigsaww @harrisjuliea @AllenInstitute

Thread covering DMN basics + implications of findings
1/n 👇
What is the Default Mode Network (DMN)?

👉Network identified in human PET/fMRI studies
👉Active and strongly synchronized during rest
👉Desynchronized by goal-oriented tasks
👉Encompasses associative cortices - Prefrontal, Cingulate, Retrosplenial, Parietal, Temporal

2/n
Why study the DMN?

👉Most prominent large-scale network of human brain
👉Pivotal substrate for higher-order cognitive and social functions
👉Key point of vulnerability for autism, schizophrenia, Alzhemier's and other brain disorders (seminal feature review below)

3/n
Read 13 tweets

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