To clarify the involvement of the cerebellum in impaired sensory integration in patients with schizophrenia, 52 first-episode patients with schizophrenia and 52 age- and sex-matched healthy controls underwent a verified sensory integration imaging task to examine the whole-brain dysfunction underlying impaired sensory integration. The familiality of cerebellar activation when integrating sensory stimuli was investigated in 25 siblings of the patients with schizophrenia, while the heritability of cerebellar activation was estimated in 56 monozygotic twins and 56 dizygotic twins. In addition, the functional connectivity between the cerebellum and the remaining regions of the whole brain was explored with psychophysiological interaction analysis. Relative to healthy controls, patients with schizophrenia showed reduced cerebellar activation when performing the sensory integration task in the whole-brain analysis. This reduced cerebellar activation was also found in the siblings of patients with schizophrenia, but to a lesser extent compared with schizophrenia patients. Cerebellar activation during sensory integration was also found to be significantly heritable. Furthermore, dysconnectivity within the cerebellum was found in patients with schizophrenia when integrating auditory and visual stimuli. These findings highlight the role of cerebellar dysfunction in the pathophysiology of schizophrenia symptoms and its potential role as an endophenotype of schizophrenia spectrum disorders. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Background: Schizophrenia has been characterized as a neurodevelopmental disorder of brain disconnectivity. However, whether disrupted integrity of white matter tracts in schizophrenia can potentially serve as individual discriminative biomarkers remains unclear. Methods: A random forest algorithm was applied to tractography-based diffusion properties obtained from a cohort of 65 patients with first-episode schizophrenia (FES) and 60 healthy individuals to investigate the machine-learning discriminative power of white matter disconnectivity. Recursive feature elimination was used to select the ultimate white matter features in the classification. Relationships between algorithm-predicted probabilities and clinical characteristics were also examined in the FES group. Results: The classifier was trained by 80% of the sample. Patients were distinguished from healthy individuals with an overall accuracy of 71.0% (95% confident interval: 61.1%, 79.6%), a sensitivity of 67.3%, a specificity of 75.0%, and the area under receiver operating characteristic curve (AUC) was 79.3% (chi(2) p < 0.001). In validation using the held-up 20% of the sample, patients were distinguished from healthy individuals with an overall accuracy of 76.0% (95% confident interval: 54.9%, 90.6%), a sensitivity of 76.9%, a specificity of 75.0%, and an AUC of 73.1% (chi(2) p = 0.012). Diffusion properties of inter-hemispheric fibres, the cerebello-thalamo-cortical circuits and the long association fibres were identified to be the most discriminative in the classification. Higher predicted probability scores were found in younger patients. Conclusions: Our findings suggest that the widespread connectivity disruption observed in FES patients, especially in younger patients, might be considered potential individual discriminating biomarkers.

Minor physical anomalies (MPAs) are subtle signs of fetal developmental abnormalities that have been considered to be among the most replicated risk markers for schizophrenia-spectrum disorders. However, quantitative approaches are needed to measure craniofacial MPAs. The present study adopted an imaging-based quantitative approach to examine craniofacial MPAs across the spectrum of schizophrenia and affective disorders, to address their sensitivity and specificity. We sampled 31 patients with schizophrenia, 30 of their unaffected relatives, and 30 individuals with schizotypal personality traits, as well as 37 non-schizotypal controls. We also examined 17 patients with bipolar disorder and 19 patients with major depressive disorder. Five craniofacial MPAs were measured on anterior-posterior commissure-aligned T1-weighted images of an individual's native brain space: medial-ocular distance, lateral-ocular distance, optical angle, maximum skull length, and skull-base width. Compared to non-schizotypal controls, patients with schizophrenia and their relatives showed a trend toward having smaller optical angles and medial-ocular distance, while no difference was found in patients with bipolar or major depressive disorders, suggesting some degree of specificity to schizophrenia. Our approach may benefit future research on craniofacial MPAs as risk markers for schizophrenia-spectrum disorders, and may eventually be useful in strategies to enhance risk stratification using multiple risk markers.

The fornix is the primary subcortical output fiber system of the hippocampal formation. In children with 22q11.2 deletion syndrome (22q11.2DS), hippocampal volume reduction has been commonly reported, but few studies as yet have evaluated the integrity of the fornix. Therefore, we investigated the fornix of 45 school-aged children with 22q11.2DS and 38 matched typically developing (TD) children. Probabilistic diffusion tensor imaging (DTI) tractography was used to reconstruct the body of the fornix in each child׳s brain native space. Compared with children, significantly lower fractional anisotropy (FA) and higher radial diffusivity (RD) was observed bilaterally in the body of the fornix in children with 22q11.2DS. Irregularities were especially prominent in the posterior aspect of the fornix where it emerges from the hippocampus. Smaller volumes of the hippocampal formations were also found in the 22q11.2DS group. The reduced hippocampal volumes were correlated with lower fornix FA and higher fornix RD in the right hemisphere. Our findings provide neuroanatomical evidence of disrupted hippocampal connectivity in children with 22q11.2DS, which may help to further understand the biological basis of spatial impairments, affective regulation, and other factors related to the ultra-high risk for schizophrenia in this population.

Background: The clinical presentation of common symptoms during depressive episodes in bipolar disorder (BD) and major depressive disorder (MDD) poses challenges for accurate diagnosis. Disorder-specific neuroanatomical features may aid the development of reliable discrimination between these two clinical conditions.Methods: For our sample of 16 BD patients, 19 MDD patients and 29 healthy volunteers, we adopted vertex-wise cortical based brain imaging techniques to examine cortical thickness and surface area, two components of cortical volume with distinct genetic determinants. Based on specific characteristics of neuroanatomical features, we then used support vector machine (SVM) algorithm to discriminate between patients with BD and MDD.Results: Compared to MDD patients, BD patients showed significantly larger cortical surface area in the left bankssts, precuneus, precentral, inferior parietal, superior parietal and the right middle temporal gyri. In addition, larger volumes of subcortical regions were found in BD patients. In SVM discriminative analyses, the overall accuracy was 74.3 %, with a sensitivity of 62.5 % and a specificity of 84.2 % (p = 0.028). Compared to controls, larger surface area in the temporo-parietal regions were observed in BD patients, and thinner cortices in fronto-temporal regions were observed in MDD patients, especially in the medial orbito-frontal area.Conclusions: These findings have demonstrated distinct spatially distributed variations in cortical thickness and surface area in patients with BD and MDD, suggesting potentially varying etiological and neuropathological processes in these two conditions. The employment of multimodal classification on disorder-specific biological features has shed light to the development of potential classification tools that could aid diagnostic decisions.

Anhedonia is an enduring trait accounting for the reduced capacity to experience pleasure. Few studies have investigated the brain structural features associated with trait anhedonia. In this study, the relationships between cortical thickness, volume of subcortical structures and scores on the Chapman physical and social anhedonia scales were examined in a non-clinical sample (n=72, 35 males). FreeSurfer was used to examine the cortical thickness and the volume of six identified subcortical structures related to trait anhedonia. We found that the cortical thickness of the superior frontal gyrus and the volume of the pallidum in the left hemisphere were correlated with anhedonia scores in both physical and social aspects. Specifically, positive correlations were found between levels of social anhedonia and the thickness of the postcentral and the inferior parietal gyri. Cortico-subcortical inter-correlations between these clusters were also observed. Our findings revealed distinct correlation patterns of neural substrates with trait physical and social anhedonia in a non-clinical sample. These findings contribute to the understanding of the pathologies underlying the anhedonia phenotype in schizophrenia and other psychiatric disorders.