Search

BACKGROUND: Offspring exposed to prenatal maternal depression (PMD) are vulnerable to depression across their lifespan. The underlying cause(s) for this elevated intergenerational risk is most likely complex. However, depression is underpinned by a dysfunctional frontal-limbic network, associated with core information processing biases (e.g. attending more to sad stimuli). Aberrations in this network might mediate transmission of this vulnerability in infants exposed to PMD. In this study, we aimed to explore the association between foetal exposure to PMD and frontal-limbic network function in infancy, hypothesising that, in response to emotional sounds, infants exposed to PMD would exhibit atypical activity in these regions, relative to those not exposed to PMD. METHOD: We employed a novel functional magnetic resonance imaging sequence to compare brain function, whilst listening to emotional sounds, in 78 full-term infants (3-6 months of age) born to mothers with and without a diagnosis of PMD. RESULTS: After exclusion of 19 datasets due to infants waking up, or moving excessively, we report between-group brain activity differences, between 29 infants exposed to PMD and 29 infants not exposed to PMD, occurring in temporal, striatal, amygdala/parahippocampal and frontal regions (p < 0.005). The offspring exposed to PMD exhibited a relative increase in activation to sad sounds and reduced (or unchanged) activation to happy sounds in frontal-limbic clusters. CONCLUSIONS: Findings of a differential response to positive and negative valanced sounds by 3-6 months of age may have significant implications for our understanding of neural mechanisms that underpin the increased risk for later-life depression in this population.

22q11.2 Deletion Syndrome (22q11.2DS) is the most common microdeletion in humans, with a heterogenous clinical presentation including medical, behavioural and psychiatric conditions. Previous neuroimaging studies examining the neuroanatomical underpinnings of 22q11.2DS show alterations in cortical volume (CV), cortical thickness (CT) and surface area (SA). The aim of this study was to identify (1) the spatially distributed networks of differences in CT and SA in 22q11.2DS compared to controls, (2) their unique and spatial overlap, as well as (3) their relative contribution to observed differences in CV. Structural MRI scans were obtained from 62 individuals with 22q11.2DS and 57 age-and-gender-matched controls (aged 6-31). Using FreeSurfer, we examined differences in vertex-wise estimates of CV, CT and SA at each vertex, and compared the frequencies of vertices with a unique or overlapping difference for each morphometric feature. Our findings indicate that CT and SA make both common and unique contributions to volumetric differences in 22q11.2DS, and in some areas, their strong opposite effects mask differences in CV. By identifying the neuroanatomic variability in 22q11.2DS, and the separate contributions of CT and SA, we can start exploring the shared and distinct mechanisms that mediate neuropsychiatric symptoms across disorders, e.g. 22q11.2DS-related ASD and/or psychosis/schizophrenia.

Objective: Attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. The authors sought to directly compare these disorders using structural brain imaging data from ENIGMA consortium data. Methods: Structural T1-weighted whole-brain MRI data from healthy control subjects (N=5,827) and from patients with ADHD (N=2,271), ASD (N=1,777), and OCD (N=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. The authors examined subcortical volume, cortical thickness, and cortical surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults, using linear mixed-effects models adjusting for age, sex, and site (and intracranial volume for subcortical and surface area measures). Results: No shared differences were found among all three disorders, and shared differences between any two disorders did not survive correction for multiple comparisons. Children with ADHD compared with those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller intracranial volume than control subjects and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared with adult control subjects and other clinical groups. No OCD-specific differences were observed across different age groups and surface area differences among all disorders in childhood and adulthood. Conclusions: The study findings suggest robust but subtle differences across different age groups among ADHD, ASD, and OCD. ADHD-specific intracranial volume and hippocampal differences in children and adolescents, and ASD-specific cortical thickness differences in the frontal cortex in adults, support previous work emphasizing structural brain differences in these disorders.

22q11.2 Deletion Syndrome (22q11.2DS) is the most common microdeletion in humans, with a heterogenous clinical presentation including medical, behavioural and psychiatric conditions. Previous neuroimaging studies examining the neuroanatomical underpinnings of 22q11.2DS show alterations in cortical volume (CV), cortical thickness (CT) and surface area (SA). The aim of this study was to identify (1) the spatially distributed networks of differences in CT and SA in 22q11.2DS compared to controls, (2) their unique and spatial overlap, as well as (3) their relative contribution to observed differences in CV. Structural MRI scans were obtained from 62 individuals with 22q11.2DS and 57 age-and-gender-matched controls (aged 6-31). Using FreeSurfer, we examined differences in vertex-wise estimates of CV, CT and SA at each vertex, and compared the frequencies of vertices with a unique or overlapping difference for each morphometric feature. Our findings indicate that CT and SA make both common and unique contributions to volumetric differences in 22q11.2DS, and in some areas, their strong opposite effects mask differences in CV. By identifying the neuroanatomic variability in 22q11.2DS, and the separate contributions of CT and SA, we can start exploring the shared and distinct mechanisms that mediate neuropsychiatric symptoms across disorders, e.g. 22q11.2DS-related ASD and/or psychosis/schizophrenia.

22q11.2 Deletion Syndrome (22q11.2DS) is a genetic condition associated with a high prevalence of neuropsychiatric conditions that include autism spectrum disorder (ASD). While evidence suggests that clinical phenotypes represent distinct neurodevelopmental outcomes, it remains unknown whether this translates to the level of neurobiology. To fractionate the 22q11.2DS phenotype on the level of neuroanatomy, we examined differences in vertex-wise estimates of cortical volume, surface area, and cortical thickness between 1) individuals with 22q11.2DS (n = 62) and neurotypical controls (n = 57) and 2) 22q11.2DS individuals with ASD symptomatology (n = 30) and those without (n = 25). We firstly observed significant differences in surface anatomy between 22q11.2DS individuals and controls for all 3 neuroanatomical features, predominantly in parietotemporal regions, cingulate and dorsolateral prefrontal cortices. We also established that 22q11.2DS individuals with ASD symptomatology were neuroanatomically distinct from 22q11.2DS individuals without ASD symptoms, particularly in brain regions that have previously been linked to ASD (e.g., dorsolateral prefrontal cortices and the entorhinal cortex). Our findings indicate that different clinical 22q11.2DS phenotypes, including those with ASD symptomatology, may represent different neurobiological subgroups. The spatially distributed patterns of neuroanatomical differences associated with ASD symptomatology in 22q11.2DS may thus provide useful information for patient stratification and the prediction of clinical outcomes.

Autism spectrum disorder (ASD) is a common neurodevelopmental condition, and infant siblings of children with ASD are at a higher risk of developing autistic traits or an ASD diagnosis, when compared to those with typically developing siblings. Reports of differences in brain anatomy and function in high-risk infants which predict later autistic behaviors are emerging, but although cerebellar and subcortical brain regions have been frequently implicated in ASD, no high-risk study has examined these regions. Therefore, in this study, we compared regional MRI volumes across the whole brain in 4-6-month-old infants with (high-risk, n = 24) and without (low-risk, n = 26) a sibling with ASD. Within the high-risk group, we also examined whether any regional differences observed were associated with autistic behaviors at 36 months. We found that high-risk infants had significantly larger cerebellar and subcortical volumes at 4-6-months of age, relative to low-risk infants; and that larger volumes in high-risk infants were linked to more repetitive behaviors at 36 months. Our preliminary observations require replication in longitudinal studies of larger samples. If correct, they suggest that the early subcortex and cerebellum volumes may be predictive biomarkers for childhood repetitive behaviors. Autism Res 2019, 12: 614-627. (c) 2019 The Authors. Autism Research published by International Society for Autism Research published byWiley Periodicals, Inc.

Over the past decade, in-vivo MRI studies have provided many invaluable insights into the neural substrates underlying autism spectrum disorder (ASD), which is now known to be associated with neurodevelopmental variations in brain anatomy, functioning, and connectivity. These systems-level features of ASD pathology seem to develop differentially across the human lifespan so that the cortical abnormalities that occur in children with ASD differ from those noted at other stages of life. Thus, investigation of the brain in ASD poses particular methodological challenges, which must be addressed to enable the comparison of results across studies. Novel analytical approaches are also being developed to facilitate the translation of findings from the research to the clinical setting. In the future, the insights provided by human neuroimaging studies could contribute to biomarker development for ASD and other neurodevelopmental disorders, and to new approaches to diagnosis and treatment.

Over the past decade, in-vivo MRI studies have provided many invaluable insights into the neural substrates underlying autism spectrum disorder (ASD), which is now known to be associated with neurodevelopmental variations in brain anatomy, functioning, and connectivity. These systems-level features of ASD pathology seem to develop differentially across the human lifespan so that the cortical abnormalities that occur in children with ASD differ from those noted at other stages of life. Thus, investigation of the brain in ASD poses particular methodological challenges, which must be addressed to enable the comparison of results across studies. Novel analytical approaches are also being developed to facilitate the translation of findings from the research to the clinical setting. In the future, the insights provided by human neuroimaging studies could contribute to biomarker development for ASD and other neurodevelopmental disorders, and to new approaches to diagnosis and treatment.