Seizures occur in approximately 30% of individuals with Autism spectrum disorders (ASD); electroencephalographic abnormalities in an even higher percentage (about 60%). Onset of seizures in ASD shows bimodal distribution, with one peak occurring before 5 years and a later onset after 10 years. This comorbidity has led to identify an Autism-Epilepsy Phenotype (AEP) suggesting common pathogenetic pathways. However, the relationship between autism and epilepsy remains strongly elusive, making it difficult to detect shared pathophysiological and genetic underpinnings, mainly due to complexity of phenotypes.
Objectives:
We examined the phenotypic characteristics of ASD children, with and without epilepsy or EEG abnormalities, to assess whether autism-epilepsy represents a distinct clinical condition within the autistic spectrum. By reducing phenotypic complexity we attempted to subgroup AEP individuals, and provide new insight on the meaning of this comorbidity.
Methods:
A sample of 171 individuals with idiopathic ASD was divided in three experimental groups: 1. ASD and seizures; 2. ASD and EEG abnormalities, without seizures; 3. ASD, without seizures and with normal EEG. ASD diagnoses were confirmed using the Autism Diagnostic Observation Schedule (ADOS). Cognitive and socio-behavioral symptoms, as well as electroclinical and anthropometric parameters, were investigated to identify differences among groups, and the features that increase seizures risk in ASD. Continuous and categorical variables were analyzed respectively through ANOVA and post-hoc multiple comparisons, and Chi-squared test. A correspondence analysis was used to decompose significant Chi-squared and reduce variables dimensions.
Results:
The percentage of children with seizures (30.4%), and EEG abnormalities without seizures (32.2%), agreed with literature data, confirming that the prevalence of epilepsy in ASD clearly exceeds that of the general population (0.5 to 1%). No differences emerged among groups at ADOS scores, showing that epilepsy (or EEG anomalies) as comorbid condition does not affect the core behavioral, communicative and social features which define ASD. Severe intellectual disability was also associated with seizures (p 0.030). The rate of high stature (18%), moreover, was higher than expected in the general population (3%), showing that overgrowth in ASD may not be limited to the brain, but be more global involving the whole body.
The most relevant result was the significant association between isolated high stature (without macrocephaly) and EEG abnormalities (p = 0.013). Only 2/13 children with isolated high stature displayed seizures, at 10.8 and 15.1 years, therefore in the late peak of onset. Therefore, isolated high stature seems to be a risk factor for EEG abnormalities (without seizures), or for late onset seizures in ASD. Isolated macrocephaly, however, was equally distributed among groups, whereas only when accompanied by high stature was associated with seizures, with onset in the early peak.
Conclusions:
These results contribute to distinguish phenotypes within ASD heterogeneity. Seizures in ASD might be correlated with growth pattern. High stature could therefore be a potential biomarker of susceptibility to EEG abnormalities or late onset seizures in ASD. The “high stature\EEG abnormalities” phenotype could perhaps represent a distinct pathophysiological and genetic subtype in the autism spectrum.
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