Autism, epilepsy and tuberous sclerosis complex: a functional model linked to mTOR pathway.
Hospital Infantil Universitario Nino Jesus, 28009 Madrid, Espana.
Tuberous sclerosis complex (TSC) is an autosomal dominant disorder that results from mutations in the TSC1 or TSC2 genes and is associated with hamartoma formation in multiple organ systems. Brain disorders are the origin of more frequent and severe problems and include infantile spasms, intractable epilepsy, brain tumors, cognitive disabilities, and autism. TSC1 or TSC2 encoded proteins modulate cell function via the mTOR signaling cascade and serve as keystones in regulating cell growth and proliferation.
To review the etiopathogenic mechanisms and the natural course of the association of autism and epilepsy in TSC.
Both the clinical and the neuroimaging findings of TSC, including early onset epilepsy and the localization of cortical tubers in the temporal lobes, and the molecular understanding of the mTOR signaling pathway, not only involved in cell growth, but also in synaptogenesis, synaptic plasticity and neuronal functioning, have suggested a multimodal origin of autism in these patients.
CONCLUSIONS. A greater understanding of the pathogenetic mechanisms underlying autism in TSC could help in devising targeted and potentially more effective treatment strategies. Antagonism of the mTOR pathway with rapamycin and everolimus may provide new therapeutic options for these TSC patients.
Neural connectivity abnormalities in autism: Insights from the tuberous sclerosis model.
Autism Spectrum Disorder (ASD) is a behavioral syndrome caused by complex genetic and non-genetic risk factors. It has been proposed that these risk factors lead to alterations in the development and ‘wiring’ of brain circuits and hence, the emergence of ASD.
Although several lines of research lend support to this theory, etiological and clinical heterogeneity, methodological issues and inconsistent findings have led to significant doubts. One of the best established, albeit rare, causes of ASD is the genetic condition Tuberous Sclerosis Complex (TSC), where 40% of individuals develop ASD.
A recent study by Peters and Taquet et al. analyzed electroencephalography (EEG) data using graph theory to model neural ‘connectivity’ in individuals with TSC with and without ASD and cases with ‘idiopathic’ ASD. TSC cases exhibited global under-connectivity and abnormal network topology, whereas individuals with TSC + ASD demonstrated similar connectivity patterns to those seen in individuals with idiopathic ASD: decreased long- over short-range connectivity.
The similarity in connectivity abnormalities in TSC + ASD and ASD suggest a common final pathway and provide further support for ‘mis-wired’ neural circuitry in ASD. The origins of the connectivity changes, and their role in mediating between the neural and the cognitive / behavioral manifestations, will require further study. Please see related research article here http://www.biomedcentral.com/1741-7015/11/54.
Brain functional networks in syndromic and non-syndromic autism: a graph theoretical study of EEG connectivity.
Graph theory has been recently introduced to characterize complex brain networks, making it highly suitable to investigate altered connectivity in neurologic disorders.
A current model proposes autism spectrum disorder (ASD) as a developmental disconnection syndrome, supported by converging evidence in both non-syndromic and syndromic ASD. However, the effects of abnormal connectivity on network properties have not been well studied, particularly in syndromic ASD. To close this gap, brain functional networks of electroencephalographic (EEG) connectivity were studied through graph measures in patients with Tuberous Sclerosis Complex (TSC), a disorder with a high prevalence of ASD, as well as in patients with non-syndromic ASD.
EEG data were collected from TSC patients with ASD (n = 14) and without ASD (n = 29), from patients with non-syndromic ASD (n = 16), and from controls (n = 46). First, EEG connectivity was characterized by the mean coherence, the ratio of inter- over intra-hemispheric coherence and the ratio of long- over short-range coherence. Next, graph measures of the functional networks were computed and a resilience analysis was conducted. To distinguish effects related to ASD from those related to TSC, a two-way analysis of covariance (ANCOVA) was applied, using age as a covariate.
Analysis of network properties revealed differences specific to TSC and ASD, and these differences were very consistent across subgroups. In TSC, both with and without a concurrent diagnosis of ASD, mean coherence, global efficiency, and clustering coefficient were decreased and the average path length was increased. These findings indicate an altered network topology. In ASD, both with and without a concurrent diagnosis of TSC, decreased long- over short-range coherence and markedly increased network resilience were found.
The altered network topology in TSC represents a functional correlate of structural abnormalities and may play a role in the pathogenesis of neurological deficits. The increased resilience in ASD may reflect an excessively degenerate network with local overconnection and decreased functional specialization. This joint study of TSC and ASD networks provides a unique window to common neurobiological mechanisms in autism. Please see related commentary article here http://www.biomedcentral.com/1741-7015/11/55.
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