Autistic Disorders and Schizophrenia: Related or Remote? An Anatomical Likelihood Estimation

Shared genetic and environmental risk factors have been identified for autistic spectrum disorders (ASD) and schizophrenia. Social interaction, communication, emotion processing, sensorimotor gating and executive function are disrupted in both, stimulating debate about whether these are related conditions. Brain imaging studies constitute an informative and expanding resource to determine whether brain structural phenotype of these disorders is distinct or overlapping. We aimed to synthesize existing datasets characterizing ASD and schizophrenia within a common framework, to quantify their structural similarities. In a novel modification of Anatomical Likelihood Estimation (ALE), 313 foci were extracted from 25 voxel-based studies comprising 660 participants (308 ASD, 352 first-episode schizophrenia) and 801 controls. The results revealed that, compared to controls, lower grey matter volumes within limbic-striato-thalamic circuitry were common to ASD and schizophrenia. Unique features of each disorder included lower grey matter volume in amygdala, caudate, frontal and medial gyrus for schizophrenia and putamen for autism. Thus, in terms of brain volumetrics, ASD and schizophrenia have a clear degree of overlap that may reflect shared etiological mechanisms. However, the distinctive neuroanatomy also mapped in each condition raises the question about how this is arrived in the context of common etiological pressures

MRI Study of Minor Physical Anomaly in Childhood Autism Implicates Aberrant Neurodevelopment in Infancy

Background: MPAs (minor physical anomalies) frequently occur in neurodevelopmental disorders because both face and brain are derived from neuroectoderm in the first trimester. Conventionally, MPAs are measured by evaluation of external appearance. Using MRI can help overcome inherent observer bias, facilitate multi-centre data acquisition, and explore how MPAs relate to brain dysmorphology in the same individual. Optical MPAs exhibit a tightly synchronized trajectory through fetal, postnatal and adult life. As head size enlarges with age, inter-orbital distance increases, and is mostly completed before age 3 years. We hypothesized that optical MPAs might afford a retrospective 'window' to early neurodevelopment; specifically, inter-orbital distance increase may represent a biomarker for early brain dysmaturation in autism. Methods: We recruited 91 children aged 7-16; 36 with an autism spectrum disorder and 55 age- and gender-matched typically developing controls. All children had normal IQ. Inter-orbital distance was measured on T1-weighted MRI scans. This value was entered into a voxel-by-voxel linear regression analysis with grey matter segmented from a bimodal MRI data-set. Age and total brain tissue volume were entered as covariates. Results: Intra-class coefficient for measurement of the inter-orbital distance was 0.95. Inter-orbital distance was significantly increased in the autism group (p = 0.03, 2-tailed). The autism group showed a significant relationship between inter-orbital distance grey matter volume of bilateral amygdalae extending to the unci and inferior temporal poles. Conclusions: Greater inter-orbital distance in the autism group compared with healthy controls is consistent with infant head size expansion in autism. Inter-orbital distance positively correlated with volume of medial temporal lobe structures, suggesting a link to "social brain" dysmorphology in the autism group. We suggest these data support the role of optical MPAs as a "fossil record" of early aberrant neurodevelopment, and potential biomarker for brain dysmaturation in autism. © 2011 Cheung et al.published_or_final_versio

Developing Consensus-Based Priority Outcome Domains for Trials in Kidney Transplantation:A Multinational Delphi Survey With Patients, Caregivers, and Health Professionals

Background: Inconsistencies in outcome reporting and frequent omission of patient-centered outcomes can diminish the value of trials in treatment decision-making. We identified critically important outcome domains in kidney transplantation based on the shared priorities of patients/caregivers and health professionals. Methods: In a 3-round Delphi survey, patients/caregivers and health professionals rated the importance of outcome domains for trials in kidney transplantation on a 9-point Likert scale and provided comments. During Round 2 and 3, participants re-rated the outcomes after reviewing their own score, the distribution of the respondents’ scores, and comments. We calculated the median, mean, and proportion rating 7-9 (critically important), and analyzed comments thematically. Results: 1018 participants (461 [45%] patients/caregivers and 557 [55%] health professionals) from 79 countries completed Round 1, and 779 (77%) completed Round 3. The top eight outcomes that met the consensus criteria in Round 3 (mean ≥7.5, median ≥8 and proportion >85%) in both groups were graft loss, graft function, chronic rejection, acute rejection, mortality, infection, cancer (excluding skin) and cardiovascular disease. Compared with health professionals, patients/caregivers gave higher priority to six outcomes (mean difference of 0.5 or more): skin cancer, surgical complications, cognition, blood pressure, depression, and ability to work. We identified five themes: capacity to control and inevitability, personal relevance, debilitating repercussions, gaining awareness of risks, and addressing knowledge gaps. Conclusions: Graft complications and severe comorbidities were critically important for both stakeholder groups. These stakeholder-prioritized outcomes will inform the core outcome set to improve the consistency and relevance of trials in kidney transplantation

From cortical to subcortical: aberrant structural brain organization in autism spectrum disorder acrossdevelopment

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by communication difficulties, social interaction impairments, and stereotyped patterns of behavior. Prior studies have shown that ASD is associated with differences in neuroanatomy in the cerebral cortex and the subcortical regions as well as the connectivity among these regions. However, findings have been mixed due to the varying age group sampled and the methods used to measure these brain structures. In view of the heterogeneous findings in ASD, three cross-sectional design studies were conducted in this thesis to examine brain structural pathologies that may be related to the clinical and behavioural phenotype of the disorder across development. In the childhood and adolescent sample, two studies were carried out. The first one examined cortical thickness using a vertex-wise approach. Results revealed thinner cortex in the occipital, parietal and frontal regions, and thicker cortex in the inferior parietal and caudal anterior cingulate regions. These regions also showed age-related differences that deviated markedly from the typical developmental trajectories observed in the control group. Some of these regions with significant differences in cortical thickness were found to be associated with clinical symptoms in ASD. The second study in the childhood and adolescent sample examined the volume of subcortical structures and CSF using a spatially non-biased parcellation approach. It was found that intracranial volume was enlarged in children with ASD, accompanied by smaller bilateral cerebellum and left thalamus. These regions showed an age-related increase in volume in children with ASD, whereas the typically developing children showed a general age-related decrease in volume of the same regions. The volumes of the cerebellum, thalamus and basal ganglia structures were associated with relatively weaker motor control in ASD, and in particular greater volume of the left thalamus rather than age predicted worse motor performance in the clinical group. The third study was carried out in a large adult sample. The cerebellar white matter system, that interconnects cortical and subcortical targets, was examined. Using a diffusion-tensor imaging tractography approach, the cerebellar input and output white matter pathways were dissected. Both the input and output pathways were observed to be disrupted in ASD, supporting the hypothesis that ASD may be a “disconnectivity disorder”. Lower fractional anisotropy of the left middle cerebellar peduncles was associated with increased difficulties in communication and social interaction, and lower fractional anisotropy in the right superior cerebellar peduncle was linked to worse motor performance in adults with ASD. Therefore, my studies confirmed differences in neuroanatomy of cortical and subcortical regions with altered brain developmental trajectories in children and adolescence with ASD, and revealed disrupted cerebellar network system in adults with ASD. Dysmaturation of cortical and subcortical regions as well as cerebellar white matter pathways may contribute to clinical and motor phenotype of the disorder. Lastly, postmortem and early life imaging studies, together with evidence that prenatal stressors during 21 to 32 weeks of gestation may increase incidence of ASD, lead me to speculate whether the abnormalities reported here may have origins prior to 31 weeks of gestation.published_or_final_versionPsychiatryDoctoralDoctor of Philosoph

Voxel-wise correlates of inter-orbital distance in autism.

<p>Axial view of grey matter brain images. Left of the panel is left hemisphere. Red highlights clusters where inter-orbital distance is positively correlated brain volume in the autism group. Z co-ordinate is given in MNI space.</p

Group differences in inter-orbital distance (n = 91).

<p>CI, 95% confidence interval; ORB, interorbital distance in mm.</p

Sample characteristics (n = 91).

<p>Sample characteristics (n = 91).</p

Scatter plot of grey matter volume against inter-orbital distance of a cluster in left and right amygdala region.

<p>Inter-orbital distance in mm. Grey matter volume in ml. Autism group represented by triangles and controls by circles. Left amygdala cluster volume correlation with inter-orbital distance is shown in the left panel. Right amygdala cluster correlation is shown in the right panel.</p

Measurement of inter-orbital distance in axial and coronal view.

<p>Top panel shows coronal view and lower panel shows the axial view. Measurements were made on the coronal view between A and B, with the axial view used for additional reference.</p