The Role of the Cerebellum in Schizophrenia

Andreasen, Nancy C.; Pierson, Ronald

doi:10.1016/j.biopsych.2008.01.003

Cited by 592 publications

(516 citation statements)

References 77 publications

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“…Our results in MeanTS, which is an expression of functional connectivity that is homogenous over the involved regions, also support the presence of subcortical‐to‐cortical connection associations in both directions. Under the rubric of specific functional brain networks or cortico‐subcortical feedback loops associated with neurodevelopment (i.e., the cortico‐cerebellar‐thalamic‐cortical circuit [CCTCC]; Andreasen & Pierson, 2008; Ullsperger, Danielmeier, & Jocham, 2014), the presence of both positive and negative associations between cortical and subcortical regions may be expected. Maturing feedback loops involving similar functions would show increasing connectivity with age, whereas those involved in different functions would show less age‐related functional connectivity.…”

Section: Discussionmentioning

confidence: 99%

Differential patterns of age‐related cortical and subcortical functional connectivity in 6‐to‐10 year old children: A connectome‐wide association study

et al. 2018

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IntroductionTypical brain development is characterized by specific patterns of maturation of functional networks. Cortico‐cortical connectivity generally increases, whereas subcortico‐cortical connections often decrease. Little is known about connectivity changes amongst different subcortical regions in typical development.MethodsThis study examined age‐ and gender‐related differences in functional connectivity between and within cortical and subcortical regions using two different approaches. The participants included 411 six‐ to ten‐year‐old typically developing children sampled from the population‐based Generation R study. Functional connectomes were defined in native space using regions of interest from subject‐specific FreeSurfer segmentations. Connections were defined as: (a) the correlation between regional mean time‐series; and (b) the focal maximum of voxel‐wise correlations within FreeSurfer regions. The association of age and gender with each functional connection was determined using linear regression. The preprocessing included the exclusion of children with excessive head motion and scrubbing to reduce the influence of minor head motion during scanning.ResultsCortico‐cortical associations echoed previous findings that connectivity shifts from short to long‐range with age. Subcortico‐cortical associations with age were primarily negative in the focal network approach but were both positive and negative in the mean time‐series network approach. Between subcortical regions, age‐related associations were negative in both network approaches. Few connections had significant associations with gender.ConclusionsThe present study replicates previously reported age‐related patterns of connectivity in a relatively narrow age‐range of children. In addition, we extended these findings by demonstrating decreased connectivity within the subcortex with increasing age. Lastly, we show the utility of a more focal approach that challenges the spatial assumptions made by the traditional mean time series approach.

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Section: Discussionmentioning

confidence: 99%

Differential patterns of age‐related cortical and subcortical functional connectivity in 6‐to‐10 year old children: A connectome‐wide association study

et al. 2018

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“…Association between greymatter heterogeneity and cerebellar volume has been observed in autism too (Radulescu et al, 2013) and therefore may be indexing a parallel neural system for which an aberrant neurodevelopmental trajectory is shared between schizophrenia and autism. Speculatively, the expression of social cognitive deficits and abnormal mental coordination (i.e., 'cognitive dysmetria'; Andreasen and Pierson 2008) in both these two disorders may arise from a common genetic basis (Psychiatric Genomics Consortium, 2013). Our findings in this study also broadly converge with those of an earlier study, which used different MRI textural features to differentiate the scans of patients with schizophrenia from those of controls (Kovalev et al, 2003).…”

Section: Discussionmentioning

confidence: 99%

Grey-matter texture abnormalities and reduced hippocampal volume are distinguishing features of schizophrenia

Radulescu

Ganeshan

Shergill

et al. 2014

Psychiatry Research: Neuroimaging

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(2014) Grey-matter texture abnormalities and reduced hippocampal volume are distinguishing features of schizophrenia. Psychiatry Research: Neuroimaging, 223 (3). pp. [179][180][181][182][183][184][185][186] This version is available from Sussex Research Online: http://sro.sussex.ac.uk/50754/ This document is made available in accordance with publisher policies and may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the URL above for details on accessing the published version. Copyright and reuse:Sussex Research Online is a digital repository of the research output of the University.Copyright and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable, the material made available in SRO has been checked for eligibility before being made available.Copies of full text items generally can be reproduced, displayed or performed and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. were also used as covariates in VBM analyses to test for correspondence with regional brain Author's Accepted Manuscriptvolume. Linear discriminant analysis tested if texture and volumetric data predicted diagnostic group membership (schizophrenia or control). We found that uniformity and entropy of grey matter differed significantly between individuals with schizophrenia and controls at the fine spatial scale (filter width below 2 mm). Within the schizophrenia group, these texture parameters correlated with volumes of the left hippocampus, right amygdala and cerebellum. The best predictor of diagnostic group membership was the combination of fine texture heterogeneity and left hippocampal size. This study highlights the presence of distributed grey-matter abnormalities in schizophrenia, and their relation to focal structural abnormality of the hippocampus. The conjunction of these features has potential as a neuroimaging endophenotype of schizophrenia.

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“…It includes the cerebellum, pons, and medulla oblongata, which are structures that control functions as fundamental and diverse as respiration, heart rate, reflex, and voluntary movements. Impaired Hb development and function are associated with many disorders such as autism, ADHD (attention deficit hyperactivity disorder), schizophrenia, cerebral palsy, and various sleep disorders (Berquin et al 1998;Aston-Jones 2005;Andreasen and Pierson 2008). As with other complex diseases and phenotypes, most variants identified by genome-wide association and sequencing population studies are found in noncoding regions of the genome, and therefore suspected to play a role in regulatory control (Cooper and Shendure 2011).…”

Section: [Supplemental Materials Is Available For This Article]mentioning

confidence: 99%

Systematic elucidation and in vivo validation of sequences enriched in hindbrain transcriptional control

et al. 2012

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Illuminating the primary sequence encryption of enhancers is central to understanding the regulatory architecture of genomes. We have developed a machine learning approach to decipher motif patterns of hindbrain enhancers and identify 40,000 sequences in the human genome that we predict display regulatory control that includes the hindbrain. Consistent with their roles in hindbrain patterning, MEIS1, NKX6-1, as well as HOX and POU family binding motifs contributed strongly to this enhancer model. Predicted hindbrain enhancers are overrepresented at genes expressed in hindbrain and associated with nervous system development, and primarily reside in the areas of open chromatin. In addition, 77 (0.2%) of these predictions are identified as hindbrain enhancers on the VISTA Enhancer Browser, and 26,000 (60%) overlap enhancer marks (H3K4me1 or H3K27ac). To validate these putative hindbrain enhancers, we selected 55 elements distributed throughout our predictions and six low scoring controls for evaluation in a zebrafish transgenic assay. When assayed in mosaic transgenic embryos, 51/55 elements directed expression in the central nervous system. Furthermore, 30/34 (88%) predicted enhancers analyzed in stable zebrafish transgenic lines directed expression in the larval zebrafish hindbrain. Subsequent analysis of sequence fragments selected based upon motif clustering further confirmed the critical role of the motifs contributing to the classifier. Our results demonstrate the existence of a primary sequence code characteristic to hindbrain enhancers. This code can be accurately extracted using machine-learning approaches and applied successfully for de novo identification of hindbrain enhancers. This study represents a critical step toward the dissection of regulatory control in specific neuronal subtypes.[Supplemental material is available for this article.]In metazoans, precise spatiotemporal patterns of gene expression are modulated by the exquisite contributions of transcriptional regulatory sequences. These include enhancers that activate transcription in a manner frequently observed to be independent of distance, position, and orientation with respect to the promoter of their target genes (Banerji et al. 1981). Empirically validated enhancers are typically a few hundred base pairs long and comprise binding sites for multiple transcription factors (TFs). In turn, TFs bound to these sequences also interact with common co-activators, communicating with the basal transcription machinery assembled at the promoter, and increasing the rate of transcription (Bulger and Groudine 2011). Identifying the combinatorial protein-DNA and protein-protein interactions that determine spatial and temporal enhancer function is crucial to understanding how distinct cellular and developmental programs are established.The systematic discovery of enhancers has proven challenging, since they are often located at great genomic distances from the genes they regulate (Lettice et al. 2003). The classical approach to enhancer identification invo...

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The Role of the Cerebellum in Schizophrenia

Cited by 592 publications

References 77 publications

Differential patterns of age‐related cortical and subcortical functional connectivity in 6‐to‐10 year old children: A connectome‐wide association study

Differential patterns of age‐related cortical and subcortical functional connectivity in 6‐to‐10 year old children: A connectome‐wide association study

Grey-matter texture abnormalities and reduced hippocampal volume are distinguishing features of schizophrenia

Systematic elucidation and in vivo validation of sequences enriched in hindbrain transcriptional control

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