RESUMEN
We investigated whether machine learning methods could potentially identify a subgroup of persons with autism spectrum disorder (ASD) who show vitamin B6 responsiveness by selected phenotype variables. We analyzed the existing data from our intervention study with 17 persons. First, we focused on signs and biomarkers that have been identified as candidates for vitamin B6 responsiveness indicators. Second, we conducted hypothesis testing among these selected variables and their combinations. Finally, we further investigated the results by conducting cluster analyses with two different algorithms, affinity propagation and k-medoids. Statistically significant variables for vitamin B6 responsiveness, including combination of hypersensitivity to sound and clumsiness, and plasma glutamine level, were included. As an a priori variable, the Pervasive Developmental Disorders Autism Society Japan Rating Scale (PARS) scores was also included. The affinity propagation analysis showed good classification of three potential vitamin B6-responsive persons with ASD. The k-medoids analysis also showed good classification. To our knowledge, this is the first study to attempt to identify subgroup of persons with ASD who show specific treatment responsiveness using selected phenotype variables. We applied machine learning methods to further investigate these variables' ability to identify this subgroup of ASD, even when only a small sample size was available.
Asunto(s)
Trastorno del Espectro Autista/tratamiento farmacológico , Aprendizaje Automático , Vitamina B 6/uso terapéutico , Aminoácidos/sangre , Trastorno del Espectro Autista/sangre , Niño , Análisis por Conglomerados , Femenino , Humanos , Masculino , Fenotipo , Análisis de Componente PrincipalRESUMEN
We examined brain magnetic resonance imaging (MRI) in a cohort of seven patients with ornithine transcarbamylase deficiency (OTCD), and correlated MRI findings with clinical manifestations. Seven patients with OTCD, aged 3-27 years, all with a missense mutation, were involved in the study. We classified the OTCD patients clinically into four stages. MR study was performed with a 1.5-T superconducting magnet during asymptomatic periods. MRI revealed white matter lesions in two patients with an advanced clinical stage, i.e. T1 and T2 prolongated round lesions in the deep white matter and posterolateral angle of the lateral ventricle in one patient; small foci of T2 and T1 prolongation in the subcortical white matter in another. Parenchymal lesions, and cerebral and cerebellar atrophy were not found in the other five patients. MRI might be normal in the early stage of the disease, and progress in proportion to the clinical stage of OTCD. OTCD should be considered as a differential diagnosis of small foci in the white matter in children.