Subtypes of autism by cluster analysis based on structural MRI data |
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Authors: | Michal Hrdlicka Iva Dudova Irena Beranova Jiri Lisy Tomas Belsan Jiri Neuwirth Vladimir Komarek Ludvika Faladova Marketa Havlovicova Zdenek Sedlacek Marek Blatny Tomas Urbanek |
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Affiliation: | (1) Department of Child Psychiatry, Charles University 2nd Medical School, V Uvalu 84, 15006 Prague, Czech Republic;(2) Department of Imaging Methods, Charles University 2nd Medical School, V Uvalu 84, 15006 Prague, Czech Republic;(3) Department of Child Neurology, Charles University 2nd Medical School, V Uvalu 84, 15006 Prague, Czech Republic;(4) Institute of Biology and Medical Genetics, Charles University 2nd Medical School, V Uvalu 84, 15006 Prague, Czech Republic;(5) Institute of Psychology, Academy of Sciences, Veveri 97, 60200 Brno, Czech Republic |
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Abstract: | Abstract The aim of our study was to subcategorize Autistic Spectrum Disorders (ASD) using a multidisciplinary approach. Sixty four autistic patients (mean age 9.4±5.6 years) were entered into a cluster analysis. The clustering analysis was based on MRI data. The clusters obtained did not differ significantly in the overall severity of autistic symptomatology as measured by the total score on the Childhood Autism Rating Scale (CARS). The clusters could be characterized as showing significant differences: Cluster 1: showed the largest sizes of the genu and splenium of the corpus callosum (CC), the lowest pregnancy order and the lowest frequency of facial dysmorphic features. Cluster 2: showed the largest sizes of the amygdala and hippocampus (HPC), the least abnormal visual response on the CARS, the lowest frequency of epilepsy and the least frequent abnormal psychomotor development during the first year of life. Cluster 3: showed the largest sizes of the caput of the nucleus caudatus (NC), the smallest sizes of the HPC and facial dysmorphic features were always present. Cluster 4: showed the smallest sizes of the genu and splenium of the CC, as well as the amygdala, and caput of the NC, the most abnormal visual response on the CARS, the highest frequency of epilepsy, the highest pregnancy order, abnormal psychomotor development during the first year of life was always present and facial dysmorphic features were always present. This multidisciplinary approach seems to be a promising method for subtyping autism. |
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Keywords: | childhood autism pervasive developmental disorders subtyping cluster analysis magnetic resonance imaging |
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