Glutamate synaptic deficits are likely early targets for prevention of schizophrenia

Computational neurosciences can form a bridge between the outcomes of pure research and clinical studies in schizophrenia. During SIRS 2018, John Krystal, Connecticut, USA, gave an insightful presentation in which a model of the pathological processes that might underlie schizophrenia was described which underscored the importance of early detection and treatment in schizophrenia.

Glutamate dysfunction – prime schizophrenia suspect

As John Krystal, Connecticut, USA explained, a considerable body of evidence exists that supports glutamate synaptic dysfunction as a prime suspect at the core of schizophrenia. Of particular interest are studies that show that N-methyl-D-aspartate receptor (NMDA-r) activity is essential for the maintenance of working memory, both in patients with schizophrenia, and in health subjects given NMDA-r antagonists and when modelled by computational neurobiologists.

NMDA-r activity is essential for the maintenance of working memory

Glutamate and GABA intimately related

However, as Professor Krystal pointed out, you cannot think of glutamate in isolation. Glutamate and γ –amino butyric acid (GABA) are like the yin and yang of neurobiology. Anything that alters glutamate will likely also alter GABA, he told delegates. Thus, it’s likely that the GABA neuronal population is also likely to be aberrant in schizophrenia.

Glutamate and GABA are the yin and yang of neurobiology

It appears that when working memory functions normally, synaptic glutamate release is inhibited while GABA acts to silence post-synaptic signal noise. However, if glutamate synaptic dysfunction occurs, as in schizophrenia, a noisy signal occurs which is poorly transmitted and may simply degrade (i.e. GABA has also ceased to function properly).

Vulnerability to memory contamination likely contributes to the occurrence of delusions

Modelling this scenario predicts consequences for the working memory: reduced memory precision, distractibility or contamination of memory that likely results in false memories and increased signal noise. That vulnerability to memory contamination contributes to the occurrence of delusions is a potential consequence.

fMRI scanning of normal individuals given an NMDA-r antagonist does indeed promote an increase in cortical noise but is also revealed something interesting. GABA deficits were indeed present but not in all GABA neurons. In some, – the basket cells - there was an increase in resting high frequency oscillations. What could explain this persistent hyperactivity?

Somatostatin’s role in GABA-controlled dendritic cell hyperactivity

Professor Krystal presented studies which showed that somatostatic neurons may have a role to play here. Somatostatin contributes to the input selectivity of GABA-controlled dendritic cells. Deficits in somatostatin can lead to aberrant hyperactivity in the dendritic cells. Thus, somatostatin deficits compromise input selectivity and may create abnormal functional connectivity all of which may, he postulated, contribute to the pathological hyperconnectivity noted in schizophrenia. 

Somatostatin deficits compromise input selectivity and may create abnormal functional connectivity

Hyperconnectivity occurs early in schizophrenia

And what’s most interesting is that hyperconnectivity occurs early in the course of schizophrenia and predicts the extent of the decline in functional connectivity over the course of 12 months. The brain doesn’t tolerate hyperconnectivity and it adapts, Professor Krystal noted. Long-term hyperconnectivity produces cortical volume loss with chronic NMDA-r blockade - features also recorded in Ultra-High Risk(UHR) and early course schizophrenia.

The brain doesn’t tolerate hyperconnectivity and it adapts

Synaptic homeostasis

What this suggests is a form of synaptic homeostasis is being undertaken in the brain - that neurons regulate their conductance to maintain stable active patterns and that their intrinsic properties depend on their history of activation.

Schizophrenia starts early. De novo mutations affect proteins predominantly expressed in the dorsolateral-prefrontal cortex in the prenatal period.

Allostatic neurodevelopmental model

In essence, the model suggests that in the pre-drome phase, glutamate synaptic dysfunctioning causes a glutamate signaling deficit. In the late pre-drome/early prodromal phase, an allostatic adaptation commences that brings about a GABA deficit and programmed synaptic proliferation. The consequences of this are neuronal disinhibition, tuning deficits, oscillation abnormalities and hyperconnectivity all of which cumulate during the occurrence of the syndrome itself.

A subsequent allostatic adaptation would involve synaptic downscaling that compounds pre-programmed synaptic pruning. The consequences of this are that atrophy compounds synaptic deficit, tuning deficits persist and network functions decline.

Glutamate synaptic deficits are likely early targets for prevention of schizophrenia

This raises the possibility that the disinhibitory phase that takes place early in the course of the disease may be amenable to treatments that restore inhibition. However, there is a downside. Restoring inhibition during the atrophic phase (chronic) phase with inhibitory treatments may actually exacerbate deficits in synaptic connectivity, as was noted with use of a metabolic glutamate receptor agonist (mGluR2/3).

The disinhibitory phase that takes place early in the course of the disease may be amenable to treatments

Treat early – later therapies may exacerbate synaptic connectivity

Thus, glutamate synaptic deficits are likely early targets for prevention of disease. So, too, are therapies that target disinhibition and hyperconnectivity, although these also likely must be given early in the course of the disease. Beyond these early stages it might be that therapies for the chronic disorder remain to be discovered.

 

References

Krystal et al. Impaired Tuning of Neural Ensembles and the Pathophysiology of Schizophrenia: A Translational and Computational Neuroscience Perspective. Biol Psychiatry 2017;81(10):873-85.

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