Background: The greater presence of neurodevelopmental antecedants may differentiate schizophrenia from bipolar disorders (BD). Machine learning/pattern recognition allows us to estimate the biological age of the brain from structural magnetic resonance imaging scans (MRI). The discrepancy between brain and chronological age could contribute to early detection and differentiation of BD and schizophrenia. Methods: We estimated brain age in 2 studies focusing on early stages of schizophrenia or BD. In the first study, we recruited 43 participants with first episode of schizophrenia-spectrum disorders (FES) and 43 controls. In the second study, we included 96 offspring of bipolar parents (48 unaffected, 48 affected) and 60 controls. We used relevance vector regression trained on an independent sample of 504 controls to estimate the brain age of study participants from structural MRI. We calculated the brain-age gap estimate (BrainAGE) score by subtracting the chronological age from the brain age. Results: Participants with FES had higher BrainAGE scores than controls (F(1, 83) = 8.79, corrected P = .008, Cohen's d = 0.64). Their brain age was on average 2.64 ± 4.15 years greater than their chronological age (matched t(42) = 4.36, P < .001). In contrast, participants at risk or in the early stages of BD showed comparable BrainAGE scores to controls (F(2,149) = 1.04, corrected P = .70, η2 = 0.01) and comparable brain and chronological age. Conclusions: Early stages of schizophrenia, but not early stages of BD, were associated with advanced BrainAGE scores. Participants with FES showed neurostructural alterations, which made their brains appear 2.64 years older than their chronological age. BrainAGE scores could aid in early differential diagnosis between BD and schizophrenia.

• MeSH
• Bipolar Disorder diagnostic imaging   MeSH
• Diagnosis, Differential MeSH
• Adult MeSH
• Humans MeSH
• Magnetic Resonance Imaging methods   MeSH
• Adolescent MeSH
• Young Adult MeSH
• Psychotic Disorders diagnostic imaging   MeSH
• Risk MeSH
• Schizophrenia diagnostic imaging   MeSH
• Machine Learning * MeSH
• Age Factors MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Comparative Study MeSH

OBJECTIVE: This study aimed to examine differences in the clinical presentation of very-early-onset (VEO) and early-onset (EO) bipolar disorder (BD) not fully explored previously. METHODS: We selected two groups of subjects with BD from the Maritime Bipolar Registry based on age at onset of first major mood episode (VEO with onset prior to age 15 years; EO ranging from 15 to 18 years) and compared them with a reference group (onset after 18 years of age). There were 363 subjects (240 with bipolar I disorder and 123 with bipolar II disorder; mean age 44.2 ± 12.8 (SD) years), with 41 subjects in the VEO and 95 in the EO groups. RESULTS: In comparison with the EO and reference groups, more subjects in the VEO group developed major depression as an index episode (88% for the VEO group versus 61% for the EO group and 54% for the reference group), and had an unremitting clinical course (65% versus 42% and 42%, respectively), rapid cycling (54% versus 34% and 28%, respectively), and comorbid attention-deficit hyperactivity disorder (17% versus 1% and 3%, respectively); a higher proportion of the VEO group had first-degree relatives with affective disorders compared with the EO and reference groups (0.41 versus 0.32 and 0.29, respectively), and they had lower scores on the Global Assessment of Functioning scale (mean scores of 64 versus 70 and 70). Overall, the EO group was similar to the reference group on most measures, except for increased suicidal behavior VEO 53%, EO 44% and reference group 25%). The results of polychotomous logistic regression also support the view that VEO BD represents a rather specific subtype of BD. CONCLUSIONS: Our results suggest the recognized correlates of early-onset BD may be driven by subjects at the lowest end of the age at onset spectrum.

• MeSH
• Bipolar Disorder * diagnosis   epidemiology   psychology   MeSH
• Depressive Disorder, Major diagnosis   epidemiology   psychology   MeSH
• Adult MeSH
• Attention Deficit Disorder with Hyperactivity * diagnosis   epidemiology   psychology   MeSH
• Comorbidity MeSH
• Middle Aged MeSH
• Humans MeSH
• Adolescent MeSH
• Mood Disorders diagnosis   epidemiology   psychology   MeSH
• Psychiatric Status Rating Scales MeSH
• Psychopathology MeSH
• Family psychology   MeSH
• Age of Onset MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Adolescent MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Geographicals
• Canada MeSH

• MeSH
• Autistic Disorder * diagnosis   MeSH
• Child MeSH
• Play and Playthings psychology   MeSH
• Humans MeSH
• Child Behavior Disorders diagnosis   MeSH
• Psychological Techniques classification   MeSH
• Psychological Tests MeSH
• Check Tag
• Child MeSH
• Humans MeSH

• MeSH
• Autistic Disorder diagnostic imaging   MeSH
• Child MeSH
• Humans MeSH
• Magnetic Resonance Imaging MeSH
• Brain * abnormalities   pathology   MeSH
• Check Tag
• Child MeSH
• Humans MeSH

• MeSH
• Autistic Disorder complications   MeSH
• Child MeSH
• Adult MeSH
• Epilepsy complications   MeSH
• Humans MeSH
• Adolescent MeSH
• Check Tag
• Child MeSH
• Adult MeSH
• Humans MeSH
• Adolescent MeSH
• Publication type
• Comparative Study MeSH

• MeSH
• Autistic Disorder diagnosis   epidemiology   physiopathology   MeSH
• Child MeSH
• Electroencephalography MeSH
• Epilepsy diagnosis   epidemiology   physiopathology   MeSH
• Cognition Disorders diagnosis   epidemiology   MeSH
• Humans MeSH
• Adolescent MeSH
• Brain physiopathology   MeSH
• Regression, Psychology MeSH
• Check Tag
• Child MeSH
• Humans MeSH
• Adolescent MeSH

• MeSH
• Autistic Disorder diagnosis   classification   therapy   MeSH
• Child MeSH
• Electroencephalography utilization   MeSH
• Epilepsy etiology   MeSH
• Humans MeSH
• Speech Disorders diagnosis   etiology   MeSH
• Check Tag
• Child MeSH
• Humans MeSH

• Publication type
• Meeting Abstract MeSH

• MeSH
• Autistic Disorder diagnosis   etiology   MeSH
• Child MeSH
• Electroencephalography instrumentation   MeSH
• Epilepsy diagnosis   drug therapy   MeSH
• Research Support as Topic MeSH
• Intelligence Tests MeSH
• Humans MeSH
• Intellectual Disability MeSH
• Adolescent MeSH
• Surveys and Questionnaires methods   MeSH
• Risk Factors MeSH
• Check Tag
• Child MeSH
• Humans MeSH
• Adolescent MeSH
• Male MeSH
• Female MeSH
• Publication type
• Review MeSH
• Comparative Study MeSH

Východisko. Řada pozorování vede k závěru, že v rozvoji autismu hrají velmi důležitou roli genetické faktory. Dosud ale nebyly přesvědčivě identifikovány žádné genetické markery, které predispozici k této poruše ovlivňují. Komplexní genetická analýza autistických pacientů a jejich rodin proto může vést k odhalení znaků, které mohou pomoci zaměřit hledání predisponujících genů. Metody a výsledky. Analyzovali jsme soubor 20 pacientů s poruchami autistického spektra. Pacienti byli podrobeni klinicko-genetickému vyšetření, cytogenetické analýze a analýzeDNAgenu FMR1. V souboru jsme pozorovali převahu chlapců (15/20), různý stupeň mentální retardace (18/20), vysoký výskyt komplikací v graviditě (10/20) a při porodu (10/20), zvýšený výskyt psychiatrických poruch, abnormit v chování a sebevražd v příbuzenstvu a zvýšený obvod hlavy a neobvykle utvářené uši u probandů. Tři pacienti měli různé chromozomální odchylky nebo varianty (t(21;22), inv(9) a inv(10)). Jeden pacient vykazoval expanzi trinukleotidové repetitivní sekvence v genu FMR1 na úrovni plné mutace svědčící pro syndrom fragilního X a u jedné pacientky je podezření na Rettův syndrom. Závěry. Naše pozorování potvrzují a rozšiřují výsledky uváděné v literatuře. Zajímavé jsou především makrocefalie, která může souviset s recentně popsanými neonatálně zvýšenými hladinami neurálních růstových faktorů u autistů, malformace uší, kterémohou signalizovat odchylky v dráze genuHOXA1, výskyt chromozomálních inverzí opakovaně popisovaných u autismu a zvláštnosti v rodokmenech pacientů.

Background. Many observations indicate that genetic factors play an important role in the aetiology of autism. Up to now, however, no genetic markers have been convincingly identified which influence the predisposition to this disorder. Complex genetic analysis of autistic patients and their families may therefore lead to the identification of features which could help to direct further search for the predisposing genes. Methods and Results. We have analysed a sample of 20 patients with autism spectrum disorders. The patients have been subjected to clinical genetic examination, cytogenetic analysis and DNA analysis of the FMR1 gene. In the sample studied we have observed more boys (15/20), various degree ofmental retardation (18/20), high frequency of complications during pregnancy (10/20) and delivery (10/20), increased incidence of psychiatric disorders, behavioural abnormities and suicides among the relatives, and increased head circumference and unusually formed ears in the probands. Three patients had different chromosomal aberrations or variants (t(21;22), inv(9) and inv(10)). One patient harboured expansion of the trinucleotide repeat sequence in the FMR1 gene on the full mutation level which is characteristic for the fragile X syndrome, and one patient is suspected to suffer from the Rett syndrome. Conclusions. Our observations confirm and extend the results reported in the literature.Most interesting aremainly the macrocephaly which may be associated with the recently described increased neonatal levels of neural growth factors in autistic individuals, ear malformations which may indicate aberrations in the HOXA1 gene pathway, the occurrence of chromosomal inversions recurrent in autism, and peculiarities in the pedigrees of the patients.

• MeSH
• Autistic Disorder diagnosis   etiology   classification   MeSH
• Chromosome Aberrations diagnosis   genetics   complications   MeSH
• Cytogenetic Analysis methods   statistics & numerical data   MeSH
• Child MeSH
• Research Support as Topic MeSH
• Genetic Markers MeSH
• Humans MeSH
• Intellectual Disability diagnosis   genetics   complications   MeSH
• Adolescent MeSH
• Child, Preschool MeSH
• Pedigree MeSH
• Pregnancy MeSH
• Check Tag
• Child MeSH
• Humans MeSH
• Adolescent MeSH
• Male MeSH
• Child, Preschool MeSH
• Pregnancy MeSH
• Female MeSH
• Publication type
• Comparative Study MeSH