Cerebellar volume and cerebellocerebral structural covariance in schizophrenia: a multisite mega-analysis of 983 patients and 1349 healthy controls

Genetic common variants associated with cerebellar volume and their overlap with mental disorders: a study on 33,265 individuals from the UK-Biobank

Interest in the cerebellum is expanding given evidence of its contributions to cognition and emotion, and dysfunction in various psychopathologies. However, research into its genetic architecture and shared influences with liability for mental disorders is lacking. We conducted a genome-wide association study (GWAS) of total cerebellar volume and underlying cerebellar lobe volumes in 33,265 UK-Biobank participants. Total cerebellar volume was heritable (h2SNP = 50.6%), showing moderate genetic homogeneity across lobes (h2SNP from 35.4% to 57.1%; mean genetic correlation between lobes rg ≈ 0.44). We identified 33 GWAS signals associated with total cerebellar volume, of which 6 are known to alter protein-coding gene structure, while a further five mapped to genomic regions known to alter cerebellar tissue gene expression. Use of summary data-based Mendelian randomisation further prioritised genes whose change in expression appears to mediate the SNP-trait association. In total, we highlight 21 unique genes of greatest interest for follow-up analyses. Using LD-regression, we report significant genetic correlations between total cerebellar volume and brainstem, pallidum and thalamus volumes. While the same approach did not result in significant correlations with psychiatric phenotypes, we report enrichment of schizophrenia, bipolar disorder and autism spectrum disorder associated signals within total cerebellar GWAS results via conditional and conjunctional-FDR analysis. Via these methods and GWAS catalogue, we identify which of our cerebellar genomic regions also associate with psychiatric traits. Our results provide important insights into the common allele architecture of cerebellar volume and its overlap with other brain volumes and psychiatric phenotypes.

Structural covariance networks in schizophrenia: A systematic review Part I

BACKGROUND

Schizophrenia is proposed as a disorder of dysconnectivity. However, examination of complexities of dysconnectivity has been challenging. Structural covariance networks (SCN) provide important insights into the nature of dysconnectivity. This systematic review examines the SCN studies that employed statistical approaches to elucidate covariation of regional morphometric variations.

METHODS

A systematic search of literature was conducted for peer-reviewed publications using different keywords and keyword combinations for schizophrenia. Fifty-two studies met the criteria.

RESULTS

Early SCN studies began using correlational structure of selected regions. Over the last 3 decades, methodological approaches have grown increasingly sophisticated from examining selected brain regions using correlation tests on small sample sizes to recent approaches that use advanced statistical methods to examine covariance structure of whole-brain parcellations on larger samples. Although the results are not fully consistent across all studies, a pattern of fronto-temporal, fronto-parietal and fronto-thalamic covariation is reported. Attempts to associate SCN alterations with functional connectivity, to differentiate between disease-related and neurodevelopment-related morphometric changes, and to develop "causality-based" models are being reported. Clinical correlation with outcome, psychotic symptoms, neurocognitive and social cognitive performance are also reported.

CONCLUSIONS

Application of advanced statistical methods are beginning to provide insights into interesting patterns of regional covariance including correlations with clinical and cognitive data. Although these findings appear similar to morphometric studies, SCNs have the advantage of highlighting topology of these regions and their relationship to the disease and associated variables. Further studies are needed to investigate neurobiological underpinnings of shared covariance, and causal links to clinical domains.

Cerebellar Coordination of Neuronal Communication in Cerebral Cortex

Cognitive processes involve precisely coordinated neuronal communications between multiple cerebral cortical structures in a task specific manner. Rich new evidence now implicates the cerebellum in cognitive functions. There is general agreement that cerebellar cognitive function involves interactions between the cerebellum and cerebral cortical association areas. Traditional views assume reciprocal interactions between one cerebellar and one cerebral cortical site, via closed-loop connections. We offer evidence supporting a new perspective that assigns the cerebellum the role of a coordinator of communication. We propose that the cerebellum participates in cognitive function by modulating the coherence of neuronal oscillations to optimize communications between multiple cortical structures in a task specific manner.

Cerebellar gray matter volume changes in patients with schizophrenia: A voxel-based meta-analysis

BACKGROUND

In schizophrenia, the structural changes in the cerebellum are associated with patients' cognition and motor deficits. However, the findings are inconsistent owing to the heterogeneity in sample size, magnetic resonance imaging (MRI) scanners, and other factors among them. In this study, we conducted a meta-analysis to characterize the anatomical changes in cerebellar subfields in patients with schizophrenia.

METHODS

Systematic research was conducted to identify studies that compare the gray matter volume (GMV) differences in the cerebellum between patients with schizophrenia and healthy controls with a voxel-based morphometry (VBM) method. A coordinate-based meta-analysis was adopted based on seed-based d mapping (SDM) software. An exploratory meta-regression analysis was conducted to associate clinical and demographic features with cerebellar changes.

RESULTS

Of note, 25 studies comprising 996 patients with schizophrenia and 1,109 healthy controls were included in the present meta-analysis. In patients with schizophrenia, decreased GMVs were demonstrated in the left Crus II, right lobule VI, and right lobule VIII, while no increased GMV was identified. In the meta-regression analysis, the mean age and illness duration were negatively associated with the GMV in the left Crus II in patients with schizophrenia.

CONCLUSION

The most significant structural changes in the cerebellum are mainly located in the posterior cerebellar hemisphere in patients with schizophrenia. The decreased GMVs of these regions might partly explain the cognitive deficits and motor symptoms in patients with schizophrenia.

Associations between Brain Structural Alterations, Executive Dysfunction, and General Psychopathology in a Healthy and Cross-Diagnostic Adult Patient Sample

BACKGROUND

A general psychopathology 'p' factor captures shared variance across mental disorders in diverse samples and may partly reflect executive dysfunction. Higher p factor scores have been related to structural alterations within the visual association cortex (VAC) and a cerebello-thalamo-cerebrocortical circuit (CTCC), both of which are important for executive control. Here, we tested replicability of these direct associations as well as the indirect role of executive functioning in a sample of healthy and cross-diagnostic adult patients.

METHODS

We conducted hypothesis-driven (i.e., region-of-interest) and exploratory whole-brain structural neuroimaging analyses using data from the Consortium for Neuropsychiatric Phenomics study of 272 adults who met diagnostic criteria for schizophrenia, bipolar disorder, or attention deficit-hyperactivity disorder or were healthy controls. Using structural equation modeling, we examined direct and indirect relations between structural neural alterations (within regions-of-interest and regions identified from exploratory analyses) and p and executive function factors.

RESULTS

Higher levels of p were associated with decreased executive functioning and VAC grey matter volume, replicating previous research. In contrast, we failed to replicate prior negative relations between the p factor and CTCC structure. A significant indirect relation between VAC grey matter volume and p via executive function also emerged. Whole-brain analyses identified additional structural alterations in supplementary motor area/cingulate cortex, anterior corona radiata, and corpus callosum genu related to the p factor.

CONCLUSIONS

Executive dysfunction may be one mechanism underlying relations between brain structure and general psychopathology. Replication of VAC structural alterations related to p encourages further focus on this brain structure.

OUP accepted manuscript

Mutations of the mitochondrial DNA are an important cause of inherited diseases that can severely affect the tissue’s homeostasis and integrity. The m.3243A > G mutation is the most commonly observed across mitochondrial disorders and is linked to multisystemic complications, including cognitive deficits. In line with in vitro experiments demonstrating the m.3243A > G’s negative impact on neuronal energy production and integrity, m.3243A > G patients show cerebral grey matter tissue changes. However, its impact on the most neuron dense, and therefore energy-consuming brain structure—the cerebellum—remains elusive. In this work, we used high-resolution structural and functional data acquired using 7 T MRI to characterize the neurodegenerative and functional signatures of the cerebellar cortex in m.3243A > G patients. Our results reveal altered tissue integrity within distinct clusters across the cerebellar cortex, apparent by their significantly reduced volume and longitudinal relaxation rate compared with healthy controls, indicating macroscopic atrophy and microstructural pathology. Spatial characterization reveals that these changes occur especially in regions related to the frontoparietal brain network that is involved in information processing and selective attention. In addition, based on resting-state functional MRI data, these clusters exhibit reduced functional connectivity to frontal and parietal cortical regions, especially in patients characterized by (i) a severe disease phenotype and (ii) reduced information-processing speed and attention control. Combined with our previous work, these results provide insight into the neuropathological changes and a solid base to guide longitudinal studies aimed to track disease progression.

Structural covariance pattern abnormalities of insula in major depressive disorder: A CAN-BIND study report

BACKGROUND AND METHODS

Investigation of the insula may inform understanding of the etiopathogenesis of major depressive disorder (MDD). In the present study, we introduced a novel gray matter volume (GMV) based structural covariance technique, and applied it to a multi-centre study of insular subregions of 157 patients with MDD and 93 healthy controls from the Canadian Biomarker Integration Network in Depression (CAN-BIND, https://www.canbind.ca/). Specifically, we divided the unilateral insula into three subregions, and investigated their coupling with whole-brain GMV-based structural brain networks (SBNs). We compared between-group difference of the structural coupling patterns between the insular subregions and SBNs.

RESULTS

The insula was divided into three subregions, including an anterior one, a superior-posterior one and an inferior-posterior one. In the comparison between MDD patients and controls we found that patients' right anterior insula showed increased inter-network coupling with the default mode network, and it showed decreased inter-network coupling with the central executive network; whereas patients' right ventral-posterior insula showed decreased inter-network coupling with the default mode network, and it showed increased inter-network coupling with the central executive network. We also demonstrated that patients' loading parameters of the right ventral-posterior insular structural covariance negatively correlated with their suicidal ideation scores; and controls' loading parameters of the right ventral-posterior insular structural covariance positively correlated with their motor and psychomotor speed scores, whereas these phenomena were not found in patients. Additionally, we did not find significant inter-network coupling between the whole-brain SBNs, including salience network, default mode network, and central executive network.

CONCLUSIONS

Our work proposed a novel technique to investigate the structural covariance coupling between large-scale structural covariance networks, and provided further evidence that MDD is a system-level disorder that shows disrupted structural coupling between brain networks.

Resolving heterogeneity in schizophrenia through a novel systems approach to brain structure: individualized structural covariance network analysis

Reliable mapping of system-level individual differences is a critical first step toward precision medicine for complex disorders such as schizophrenia. Disrupted structural covariance indicates a system-level brain maturational disruption in schizophrenia. However, most studies examine structural covariance at the group level. This prevents subject-level inferences. Here, we introduce a Network Template Perturbation approach to construct individual differential structural covariance network (IDSCN) using regional gray-matter volume. IDSCN quantifies how structural covariance between two nodes in a patient deviates from the normative covariance in healthy subjects. We analyzed T1 images from 1287 subjects, including 107 first-episode (drug-naive) patients and 71 controls in the discovery datasets and established robustness in 213 first-episode (drug-naive), 294 chronic, 99 clinical high-risk patients, and 494 controls from the replication datasets. Patients with schizophrenia were highly variable in their altered structural covariance edges; the number of altered edges was related to severity of hallucinations. Despite this variability, a subset of covariance edges, including the left hippocampus-bilateral putamen/globus pallidus edges, clustered patients into two distinct subgroups with opposing changes in covariance compared to controls, and significant differences in their anxiety and depression scores. These subgroup differences were stable across all seven datasets with meaningful genetic associations and functional annotation for the affected edges. We conclude that the underlying physiology of affective symptoms in schizophrenia involves the hippocampus and putamen/pallidum, predates disease onset, and is sufficiently consistent to resolve morphological heterogeneity throughout the illness course. The two schizophrenia subgroups identified thus have implications for the nosology and clinical treatment.

Cerebellar theta burst stimulation for the treatment of negative symptoms of schizophrenia: A multicenter, double-blind, randomized controlled trial

Given the importance of the cerebellum in the pathophysiology of schizophrenia, the cerebellar vermis has been proposed as a new rTMS stimulation site for negative symptoms. In this study, 64 patients from 7 psychiatric hospitals were randomized into the study (n=32) or control (n=32) group. Intermittent theta burst stimulation (iTBS) (or sham stimulation) to the cerebellar midline was administered 5 times/week for 2 weeks. Psychotic symptoms were assessed with the Positive and Negative Symptoms Scale (PANSS) at baseline, the end of treatment, and 2, 6, 12, and 24 weeks after the treatment. Regarding the negative symptoms, the interaction effect between group and time was statistically significant, with the scores in the study group significantly lower than those in the control group at the 4 follow-ups after treatment, and the group difference was maximal at 24 weeks of follow-up. The main effect of time was significant; however, the main effect of group did not show statistical significance. Our study revealed that cerebellar iTBS may improve negative symptoms in schizophrenia patients, and the effect was more pronounced at 24 weeks after the end of treatment, which provides preliminary empirical evidence for the maintenance of efficacy after stimulation of this new site.

Lessons Learned From Neuroimaging Studies of Copy Number Variants: A Systematic Review

Pathogenic copy number variants (CNVs) and aneuploidies alter gene dosage and are associated with neurodevelopmental psychiatric disorders such as autism spectrum disorder and schizophrenia. Brain mechanisms mediating genetic risk for neurodevelopmental psychiatric disorders remain largely unknown, but there is a rapid increase in morphometry studies of CNVs using T1-weighted structural magnetic resonance imaging. Studies have been conducted one mutation at a time, leaving the field with a complex catalog of brain alterations linked to different genomic loci. Our aim was to provide a systematic review of neuroimaging phenotypes across CNVs associated with developmental psychiatric disorders including autism and schizophrenia. We included 76 structural magnetic resonance imaging studies on 20 CNVs at the 15q11.2, 22q11.2, 1q21.1 distal, 16p11.2 distal and proximal, 7q11.23, 15q11-q13, and 22q13.33 (SHANK3) genomic loci as well as aneuploidies of chromosomes X, Y, and 21. Moderate to large effect sizes on global and regional brain morphometry are observed across all genomic loci, which is in line with levels of symptom severity reported for these variants. This is in stark contrast with the much milder neuroimaging effects observed in idiopathic psychiatric disorders. Data also suggest that CNVs have independent effects on global versus regional measures as well as on cortical surface versus thickness. Findings highlight a broad diversity of regional morphometry patterns across genomic loci. This heterogeneity of brain patterns provides insight into the weak effects reported in magnetic resonance imaging studies of cognitive dimension and psychiatric conditions. Neuroimaging studies across many more variants will be required to understand links between gene function and brain morphometry.

The Role of the Posterior Cerebellum in Dysfunctional Social Sequencing

Recent advances in social neuroscience have highlighted the critical role of the cerebellum in social cognition, and especially the posterior cerebellum. Studies have supported the view that the posterior cerebellum builds internal action models of our social interactions to predict how other people's actions will be executed and what our most likely responses are to these actions. This mechanism allows to better anticipate action sequences during social interactions in an automatic and intuitive way and to fine-tune these anticipations, making it easier to understand other's social behaviors and mental states (e.g., beliefs, intentions, traits). In this paper, we argue that the central role of the posterior cerebellum in identifying and automatizing social action sequencing provides a fruitful starting point for investigating social dysfunctions in a variety of clinical pathologies, such as autism, obsessive-compulsive and bipolar disorder, depression, and addiction. Our key hypothesis is that dysfunctions of the posterior cerebellum lead to under- or overuse of inflexible social routines and lack of plasticity for learning new, more adaptive, social automatisms. We briefly review past research supporting this view and propose a program of research to test our hypothesis. This approach might alleviate a variety of mental problems of individuals who suffer from inflexible automatizations that stand in the way of adjustable and intuitive social behavior, by increasing posterior cerebellar plasticity using noninvasive neurostimulation or neuro-guided training programs.

Cortical surface abnormalities are different depending on the stage of schizophrenia: A cross-sectional vertexwise mega-analysis of thickness, area and gyrification

BACKGROUND

Brain magnetic resonance imaging studies have not investigated the cortical surface comprehensively in schizophrenia subjects by assessing thickness, surface area and gyrification separately during the first-episode of psychosis (FEP) or chronic schizophrenia (ChSch).

METHODS

We investigated cortical surface abnormalities in 137 FEP patients and 240 ChSch subjects compared to 297 Healthy Controls (HC) contributed by five cohorts. Maps showing results of vertexwise between-group comparisons of cortical thickness, area, and gyrification were produced using T1-weighted datasets processed using FreeSurfer 5.3, followed by validated quality control protocols.

RESULTS

FEP subjects showed large clusters of increased area and gyrification relative to HC in prefrontal and insuli cortices (Cohen's d: 0.049 to 0.28). These between-group differences occurred partially beyond the effect of sample. ChSch subjects displayed reduced cortical thickness relative to HC in smaller fronto-temporal foci (d: -0.73 to -0.35), but not beyond the effect of sample. Differences between FEP and HC subjects were associated with male gender, younger age, and earlier illness onset, while differences between ChSch and HC were associated with treatment-resistance and first-generation antipsychotic (FGA) intake independently of sample effect.

CONCLUSIONS

Separate assessments of FEP and ChSch revealed abnormalities that differed in regional distribution, phenotypes affected and effect size. In FEP, associations of greater cortical area and gyrification abnormalities with earlier age of onset suggest an origin on anomalous neurodevelopment, while thickness reductions in ChSch are at least partially explained by treatment-resistance and FGA intake. Associations of between-group differences with clinical variables retained statistical significance beyond the effect of sample.

Genetic Association Between Schizophrenia and Cortical Brain Surface Area and Thickness

Importance

Schizophrenia is a complex heritable disorder associated with many genetic variants, each with a small effect. While cortical differences between patients with schizophrenia and healthy controls are consistently reported, the underlying molecular mechanisms remain elusive.

Objective

To investigate the extent of shared genetic architecture between schizophrenia and brain cortical surface area (SA) and thickness (TH) and to identify shared genomic loci.

Design, Setting, and Participants

Independent genome-wide association study data on schizophrenia (Psychiatric Genomics Consortium and CLOZUK: n = 105 318) and SA and TH (UK Biobank: n = 33 735) were obtained. The extent of polygenic overlap was investigated using MiXeR. The specific shared genomic loci were identified by conditional/conjunctional false discovery rate analysis and were further examined in 3 independent cohorts. Data were collected from December 2019 to February 2021, and data analysis was performed from May 2020 to February 2021.

Main Outcomes and Measures

The primary outcomes were estimated fractions of polygenic overlap between schizophrenia, total SA, and average TH and a list of functionally characterized shared genomic loci.

Results

Based on genome-wide association study data from 139 053 participants, MiXeR estimated schizophrenia to be more polygenic (9703 single-nucleotide variants [SNVs]) than total SA (2101 SNVs) and average TH (1363 SNVs). Most SNVs associated with total SA (1966 of 2101 [93.6%]) and average TH (1322 of 1363 [97.0%]) may be associated with the development of schizophrenia. Subsequent conjunctional false discovery rate analysis identified 44 and 23 schizophrenia risk loci shared with total SA and average TH, respectively. The SNV associations of shared loci between schizophrenia and total SA revealed en masse concordant association between the discovery and independent cohorts. After removing high linkage disequilibrium regions, such as the major histocompatibility complex region, the shared loci were enriched in immunologic signature gene sets. Polygenic overlap and shared loci between schizophrenia and schizophrenia-associated regions of interest for SA (superior frontal and middle temporal gyri) and for TH (superior temporal, inferior temporal, and superior frontal gyri) were also identified.

Conclusions and Relevance

This study demonstrated shared genetic loci between cortical morphometry and schizophrenia, among which a subset are associated with immunity. These findings provide an insight into the complex genetic architecture and associated with schizophrenia.

Unique Morphometric Features of the Cerebellum and Cerebellocerebral Structural Correlation Between Autism Spectrum Disorder and Schizophrenia

Background

Although cerebellar morphological involvement has been increasingly recognized in autism spectrum disorder (ASD) and schizophrenia (SZ), the extent to which there are morphological differences between them has not been definitively quantified. Furthermore, although previous studies have demonstrated increased anatomical cerebellocerebral correlations in both conditions, differences between their associations have not been well characterized.

Methods

We compared cerebellar volume between males with ASD (n = 31), males with SZ (n = 28), and typically developing males (n = 49). A total of 31 cerebellar subregions were investigated with the cerebellum segmented into their constituent lobules, in gray matter (GM) and white matter (WM) separately. Additionally, structural correlations with the contralateral cerebrum were analyzed for each cerebellar lobule.

Results

We found significantly larger WM volume in the bilateral lobules VI and Crus I in the ASD group than in other groups. While WM or GM volumes of these right lobules had positive associations with ASD symptoms, there was a negative association between GM volume of the right Crus I and SZ symptoms. We further observed, in the ASD group specifically, significant correlations between WM of the right lobule VI and WM of the left frontal pole (r = 0.67) and between GM of the right lobule VI and the left caudate (r = 0.60).

Conclusions

Our findings support evidence that cerebellar morphology is involved in ASD and SZ with different mechanisms. Furthermore, this study showed that these biological differences require consideration when determining diagnostic criteria and treatment for these disorders.

Functional Territories of Human Dentate Nucleus

Anatomical connections link the cerebellar cortex with multiple sensory, motor, association, and paralimbic cerebral areas. The majority of fibers that exit cerebellar cortex synapse in dentate nuclei (DN) before reaching extracerebellar structures such as cerebral cortex, but the functional neuroanatomy of human DN remains largely unmapped. Neuroimaging research has redefined broad categories of functional division in the human brain showing that primary processing, attentional (task positive) processing, and default-mode (task negative) processing are three central poles of neural macroscale functional organization. This broad spectrum of human neural processing categories is represented not only in the cerebral cortex, but also in the thalamus, striatum, and cerebellar cortex. Whether functional organization in DN obeys a similar set of macroscale divisions, and whether DN are yet another compartment of representation of a broad spectrum of human neural processing categories, remains unknown. Here, we show for the first time that human DN are optimally divided into three functional territories as indexed by high spatio-temporal resolution resting-state MRI in 77 healthy humans, and that these three distinct territories contribute uniquely to default-mode, salience-motor, and visual cerebral cortical networks. Our findings provide a systems neuroscience substrate for cerebellar output to influence multiple broad categories of neural control.

Impaired cerebro-cerebellar white matter connectivity and its associations with cognitive function in patients with schizophrenia

Schizophrenia is a complex brain disorder of unknown etiology. Based on the notion of “cognitive dysmetria,” we aimed to investigate aberrations in structural white matter (WM) connectivity that links the cerebellum to cognitive dysfunction in patients with schizophrenia. A total of 112 participants (65 patients with schizophrenia and 47 healthy controls [HCs]) were enrolled and underwent diffusion tensor imaging. Between-group voxel-wise comparisons of cerebellar WM regions (superior/middle [MCP]/inferior cerebellar peduncle and pontine crossing fibers) were performed using Tract-Based Spatial Statistics. Cognitive function was assessed using the Trail Making Test Part A/B (TMT-A/B), Wisconsin Card Sorting Test (WCST), and Rey-Kim Memory Test in 46 participants with schizophrenia. WM connectivity, measured as fractional anisotropy (FA), was significantly lower in the MCP in participants with schizophrenia than in HCs. The mean FAs extracted from the significant MCP cluster were inversely correlated with poorer cognitive performance, particularly longer time to complete the TMB-B (r = 0.559, p < 0.001) and more total errors in the WCST (r = 0.442, p = 0.003). Our findings suggest that aberrant cerebro-cerebellar communication due to disrupted WM connectivity may contribute to cognitive impairments, a core characteristic of schizophrenia. Our results may expand our understanding of the neurobiology of schizophrenia based on the cerebro-cerebellar interconnectivity of the brain.

Volumetric differences in gray and white matter of cerebellar Crus I/II across the different clinical stages of schizophrenia

AIM

Schizophrenia is considered to be a disorder of progressive structural brain abnormalities. Previous studies have indicated that the cerebellar Crus I/II plays a critical role in schizophrenia. We aimed to investigate how specific morphological features in the Crus I/II at different critical stages of the schizophrenia spectrum contribute to the disease.

METHODS

The study involved 73 participants on the schizophrenia spectrum (28 with ultra-high risk for psychosis [UHR], 17 with first-episode schizophrenia [FES], and 28 with chronic schizophrenia) and 79 healthy controls. We undertook a detailed investigation into differences in Crus I/II volume using a semiautomated segmentation method optimized for the cerebellum. We analyzed the effects of group and sex, as well as their interaction, on Crus I/II volume in gray matter (GM) and white matter (WM).

RESULTS

Significant group × sex interactions were found in WM volumes of the bilateral Crus I/II; the males with UHR demonstrated significantly larger WM volumes compared with the other male groups, whereas no significant group differences were found in the female groups. Additionally, WM and GM volumes of the Crus I/II had positive associations with symptom severity in the UHR group, whereas, in contrast, GM volumes in the FES group were negatively associated with symptom severity.

CONCLUSIONS

The present findings provide evidence that the morphology of Crus I/II is involved in schizophrenia in a sex- and disease stage-dependent manner. Additionally, alterations of WM volumes of Crus I/II may have potential as a biological marker of early detection and treatment for individuals with UHR.

White Matter Microstructural Properties of the Cerebellar Peduncles Predict Change in Symptoms of Psychopathology in Adolescent Girls

Internalizing symptoms typically emerge in adolescence and are more prevalent in females than in males; in contrast, externalizing symptoms typically emerge in childhood and are more commonly observed in males. Previous research has implicated aspects of white matter organization, including fractional anisotropy (FA), of cerebral tracts in both internalizing and externalizing symptoms. Although the cerebellum has been posited to integrate limbic and cortical regions, its role in psychopathology is not well understood. In this longitudinal study, we investigated whether FA of the superior (SCP), middle (MCP), and inferior cerebellar peduncles (ICP) predict change in symptoms and whether sex moderates this association. One hundred eleven adolescents completed the Youth Self-Report, assessing symptoms at baseline (ages 9-13 years) and again 2 years later. Participants also underwent diffusion-weighted imaging at baseline. We used deterministic tractography to segment and compute mean FA of the cerebellar peduncles. Lower FA of the right SCP at baseline predicted increases in internalizing symptoms in females only. Lower FA in the right SCP and ICP also predicted increases in externalizing symptoms in females, but these associations did not survive multiple comparison correction. There was no association between FA of the cerebellar peduncles and change in symptoms in males or between MCP FA and symptom changes in males or females. Organizational properties of the SCP may be a sex-specific marker of internalizing symptom changes in adolescence. The cerebellar peduncles should be explored further in future studies to elucidate sex differences in symptoms.

Effects of eight neuropsychiatric copy number variants on human brain structure

Many copy number variants (CNVs) confer risk for the same range of neurodevelopmental symptoms and psychiatric conditions including autism and schizophrenia. Yet, to date neuroimaging studies have typically been carried out one mutation at a time, showing that CNVs have large effects on brain anatomy. Here, we aimed to characterize and quantify the distinct brain morphometry effects and latent dimensions across 8 neuropsychiatric CNVs. We analyzed T1-weighted MRI data from clinically and non-clinically ascertained CNV carriers (deletion/duplication) at the 1q21.1 (n = 39/28), 16p11.2 (n = 87/78), 22q11.2 (n = 75/30), and 15q11.2 (n = 72/76) loci as well as 1296 non-carriers (controls). Case-control contrasts of all examined genomic loci demonstrated effects on brain anatomy, with deletions and duplications showing mirror effects at the global and regional levels. Although CNVs mainly showed distinct brain patterns, principal component analysis (PCA) loaded subsets of CNVs on two latent brain dimensions, which explained 32 and 29% of the variance of the 8 Cohen's d maps. The cingulate gyrus, insula, supplementary motor cortex, and cerebellum were identified by PCA and multi-view pattern learning as top regions contributing to latent dimension shared across subsets of CNVs. The large proportion of distinct CNV effects on brain morphology may explain the small neuroimaging effect sizes reported in polygenic psychiatric conditions. Nevertheless, latent gene brain morphology dimensions will help subgroup the rapidly expanding landscape of neuropsychiatric variants and dissect the heterogeneity of idiopathic conditions.

Association between age of cannabis initiation and gray matter covariance networks in recent onset psychosis

Cannabis use during adolescence is associated with an increased risk of developing psychosis. According to a current hypothesis, this results from detrimental effects of early cannabis use on brain maturation during this vulnerable period. However, studies investigating the interaction between early cannabis use and brain structural alterations hitherto reported inconclusive findings. We investigated effects of age of cannabis initiation on psychosis using data from the multicentric Personalized Prognostic Tools for Early Psychosis Management (PRONIA) and the Cannabis Induced Psychosis (CIP) studies, yielding a total sample of 102 clinically-relevant cannabis users with recent onset psychosis. GM covariance underlies shared maturational processes. Therefore, we performed source-based morphometry analysis with spatial constraints on structural brain networks showing significant alterations in schizophrenia in a previous multisite study, thus testing associations of these networks with the age of cannabis initiation and with confounding factors. Earlier cannabis initiation was associated with more severe positive symptoms in our cohort. Greater gray matter volume (GMV) in the previously identified cerebellar schizophrenia-related network had a significant association with early cannabis use, independent of several possibly confounding factors. Moreover, GMV in the cerebellar network was associated with lower volume in another network previously associated with schizophrenia, comprising the insula, superior temporal, and inferior frontal gyrus. These findings are in line with previous investigations in healthy cannabis users, and suggest that early initiation of cannabis perturbs the developmental trajectory of certain structural brain networks in a manner imparting risk for psychosis later in life.

Little cells of the little brain: microglia in cerebellar development and function

Microglia are long-lived resident macrophages of the brain with diverse roles that span development, adulthood, and aging. Once thought to be a relatively homogeneous population, there is a growing recognition that microglia are highly specialized to suit their specific brain region. Cerebellar microglia represent an example of such specialization, exhibiting a dynamical, transcriptional, and immunological profile that differs from that of other microglial populations. Here we review the evidence that cerebellar microglia shape the cerebellar environment and are in turn shaped by it. We examine the roles microglia play in cerebellar function, development, and aging. The emerging findings on cerebellar microglia may also provide insights into disease processes involving cerebellar dysfunction.

A Characterization of the Effects of Minocycline Treatment During Adolescence on Structural, Metabolic, and Oxidative Stress Parameters in a Maternal Immune Stimulation Model of Neurodevelopmental Brain Disorders

BACKGROUND

Minocycline (MIN) is a tetracycline with antioxidant, anti-inflammatory, and neuroprotective properties. Given the likely involvement of inflammation and oxidative stress (IOS) in schizophrenia, MIN has been proposed as a potential adjuvant treatment in this pathology. We tested an early therapeutic window, during adolescence, as prevention of the schizophrenia-related deficits in the maternal immune stimulation (MIS) animal model.

METHODS

On gestational day 15, Poly I:C or vehicle was injected in pregnant Wistar rats. A total 93 male offspring received MIN (30 mg/kg) or saline from postnatal day (PND) 35-49. At PND70, rats were submitted to the prepulse inhibition test. FDG-PET and T2-weighted MRI brain studies were performed at adulthood. IOS markers were evaluated in frozen brain tissue.

RESULTS

MIN treatment did not prevent prepulse inhibition test behavioral deficits in MIS offspring. However, MIN prevented morphometric abnormalities in the third ventricle but not in the hippocampus. Additionally, MIN reduced brain metabolism in cerebellum and increased it in nucleus accumbens. Finally, MIN reduced the expression of iNOS (prefrontal cortex, caudate-putamen) and increased the levels of KEAP1 (prefrontal cortex), HO1 and NQO1 (amygdala, hippocampus), and HO1 (caudate-putamen).

CONCLUSIONS

MIN treatment during adolescence partially counteracts volumetric abnormalities and IOS deficits in the MIS model, likely via iNOS and Nrf2-ARE pathways, also increasing the expression of cytoprotective enzymes. However, MIN treatment during this peripubertal stage does not prevent sensorimotor gating deficits. Therefore, even though it does not prevent all the MIS-derived abnormalities evaluated, our results suggest the potential utility of early treatment with MIN in other schizophrenia domains.

Replicating extensive brain structural heterogeneity in individuals with schizophrenia and bipolar disorder

Identifying brain processes involved in the risk and development of mental disorders is a major aim. We recently reported substantial interindividual heterogeneity in brain structural aberrations among patients with schizophrenia and bipolar disorder. Estimating the normative range of voxel-based morphometry (VBM) data among healthy individuals using a Gaussian process regression (GPR) enables us to map individual deviations from the healthy range in unseen datasets. Here, we aim to replicate our previous results in two independent samples of patients with schizophrenia (n1 = 94; n2 = 105), bipolar disorder (n1 = 116; n2 = 61), and healthy individuals (n1 = 400; n2 = 312). In line with previous findings with exception of the cerebellum our results revealed robust group level differences between patients and healthy individuals, yet only a small proportion of patients with schizophrenia or bipolar disorder exhibited extreme negative deviations from normality in the same brain regions. These direct replications support that group level-differences in brain structure disguise considerable individual differences in brain aberrations, with important implications for the interpretation and generalization of group-level brain imaging findings to the individual with a mental disorder.

Brain volumetric and fractal analysis of synthetic MRI: A comparative study with conventional 3D T1-weighted images

PURPOSE

The estimation of brain volumetric measurements based on Synthetic MRI (SyMRI) is easy and fast, however, the consistency of brain volumetric and morphologic measurements based on SyMRI and 3D T1WI should be further addressed. The current study evaluated the impact of spatial resolution on brain volumetric and morphologic measurements using SyMRI, and test whether the brain measurements derived from SyMRI were consistent with those resulted from 3D T1WI.

METHOD

Brain volumetric and fractal analysis were applied to thirty healthy subjects, each underwent four SyMRI acquisitions with different spatial resolutions (1 × 1 × 2 mm, 1 × 1x3mm, 1 × 1 × 4 mm, 2 × 2 × 2 mm) and a 3D T1WI (1 × 1 × 1 mm isotropic). The consistency of the SyMRI measurements was tested using one-way non-parametric Kruskal-Wallis test and post hoc Dwass-Steel-Critchlow-Fligner test. The association between SyMRI and 3D T1WI derived measurements was evaluated using linear regression models.

RESULTS

Our results demonstrated that both in- and through-plane resolutions show an impact on brain volumetric measurements, while brain parenchymal volume showed high consistency across the SyMRI acquisitions, and high association with the measurements from 3D T1WI. In addition, SyMRI with 1 × 1 × 4 mm resolution showed the strongest association with 3D T1WI compared to other SyMRI acquisitions in both volumetric and fractal analyses. Moreover, substantial differences were found in fractal dimension of both gray and white matter between the SyMRI and 3D T1WI tissue segmentations.

CONCLUSIONS

Our results suggested that the measurements from SyMRI with relatively higher in-plane and lower through-plane resolution (1 × 1 × 4 mm) are much closer to 3D T1WI.

Abnormal Function in Dentate Nuclei Precedes the Onset of Psychosis: A Resting-State fMRI Study in High-Risk Individuals

OBJECTIVE

The cerebellum serves a wide range of functions and is suggested to be composed of discrete regions dedicated to unique functions. We recently developed a new parcellation of the dentate nuclei (DN), the major output nuclei of the cerebellum, which optimally divides the structure into 3 functional territories that contribute uniquely to default-mode, motor-salience, and visual processing networks as indexed by resting-state functional connectivity (RsFc). Here we test for the first time whether RsFc differences in the DN, precede the onset of psychosis in individuals at risk of developing schizophrenia.

METHODS

We used the magnetic resonance imaging (MRI) dataset from the Shanghai At Risk for Psychosis study that included subjects at high risk to develop schizophrenia (N = 144), with longitudinal follow-up to determine which subjects developed a psychotic episode within 1 year of their functional magnetic resonance imaging (fMRI) scan (converters N = 23). Analysis used the 3 functional parcels (default-mode, salience-motor, and visual territory) from the DN as seed regions of interest for whole-brain RsFc analysis.

RESULTS

RsFc analysis revealed abnormalities at baseline in high-risk individuals who developed psychosis, compared to high-risk individuals who did not develop psychosis. The nature of the observed abnormalities was found to be anatomically specific such that abnormal RsFc was localized predominantly in cerebral cortical networks that matched the 3 functional territories of the DN that were evaluated.

CONCLUSIONS

We show for the first time that abnormal RsFc of the DN may precede the onset of psychosis. This new evidence highlights the role of the cerebellum as a potential target for psychosis prediction and prevention.

Aberrant cerebellar neural activity and cerebro-cerebellar functional connectivity involving executive dysfunction in schizophrenia with primary negative symptoms

Deficit schizophrenia (DS) is a distinct subtype of schizophrenia characterized by primary and enduring negative symptoms. More severe executive dysfunctions were observed in DS patients, however, the associated neuroimaging characteristics, especially cerebellar functional anomalies in DS, remain largely unknown. We employed resting-state functional and structural MRI data of 106 male participants, including data from 29 DS patients, 39 non-deficit schizophrenia (NDS) patients and 38 healthy controls (HCs). Z-standardized fractional amplitude of low-frequency fluctuation (zfALFF) values were calculated in order to examine spontaneous regional brain activity. Cerebro-cerebellar functional connectivity and changes in the volume of gray matter in the cerebellum were also examined. Relative to the HCs, both DS and NDS patients exhibited decreased zfALFF in the bilateral cerebellar lobules VIII and IX. The zfALFF in the left Crus II was lower in DS patients compared to NDS patients. No significant difference was observed in the volume of cerebellar gray matter among the three groups. Compared with NDS patients, cerebro-cerebellar functional connectivity analysis revealed increased connectivity in the left orbital medial frontal cortex and right putamen regions in DS patients. Reduced zfALFF in the left Crus II in the DS group was significantly positively correlated with Stroop Color and Word scores, while negatively correlated with Trail-Making Test part B scores. The increased functional connectivity in the right putamen in DS patients was significantly positively correlated with Animal Naming Test and semantic Verbal Fluency Test scores. These results highlight cerebellar functional abnormality in DS patients and provide insight into the pathophysiological mechanism of executive dysfunction.

Strategies to solve the reverse inference fallacy in future MRI studies of schizophrenia: a review

Few advances in schizophrenia research have been translated into clinical practice, despite 60 years of serum biomarkers studies and 50 years of genetic studies. During the last 30 years, neuroimaging studies on schizophrenia have gradually increased, partly due to the beautiful prospect that the pathophysiology of schizophrenia could be explained entirely by the Human Connectome Project (HCP). However, the fallacy of reverse inference has been a critical problem of the HCP. For this reason, there is a dire need for new strategies or research "bridges" to further schizophrenia at the biological level. To understand the importance of research "bridges," it is vital to examine the strengths and weaknesses of the recent literature. Hence, in this review, our team has summarized the recent literature (1995-2018) about magnetic resonance imaging (MRI) of schizophrenia in terms of regional and global structural and functional alterations. We have also provided a new proposal that may supplement the HCP for studying schizophrenia. As postulated, despite the vast number of MRI studies in schizophrenia, the lack of homogeneity between the studies, along with the relatedness of schizophrenia with other neurological disorders, has hindered the study of schizophrenia. In addition, the reverse inference cannot be used to diagnose schizophrenia, further limiting the clinical impact of findings from medical imaging studies. We believe that multidisciplinary technologies may be used to develop research "bridges" to further investigate schizophrenia at the single neuron or neuron cluster levels. We have postulated about future strategies for overcoming the current limitations and establishing the research "bridges," with an emphasis on multimodality imaging, molecular imaging, neuron cluster signals, single transmitter biomarkers, and nanotechnology. These research "bridges" may help solve the reverse inference fallacy and improve our understanding of schizophrenia for future studies.

Sparse deep neural networks on imaging genetics for schizophrenia case-control classification

Deep learning methods hold strong promise for identifying biomarkers for clinical application. However, current approaches for psychiatric classification or prediction do not allow direct interpretation of original features. In the present study, we introduce a sparse deep neural network (DNN) approach to identify sparse and interpretable features for schizophrenia (SZ) case–control classification. An L₀‐norm regularization is implemented on the input layer of the network for sparse feature selection, which can later be interpreted based on importance weights. We applied the proposed approach on a large multi‐study cohort with gray matter volume (GMV) and single nucleotide polymorphism (SNP) data for SZ classification. A total of 634 individuals served as training samples, and the classification model was evaluated for generalizability on three independent datasets of different scanning protocols (N = 394, 255, and 160, respectively). We examined the classification power of pure GMV features, as well as combined GMV and SNP features. Empirical experiments demonstrated that sparse DNN slightly outperformed independent component analysis + support vector machine (ICA + SVM) framework, and more effectively fused GMV and SNP features for SZ discrimination, with an average error rate of 28.98% on external data. The importance weights suggested that the DNN model prioritized to select frontal and superior temporal gyrus for SZ classification with high sparsity, with parietal regions further included with lower sparsity, echoing previous literature. The results validate the application of the proposed approach to SZ classification, and promise extended utility on other data modalities and traits which ultimately may result in clinically useful tools.

Association between complement component 4A expression, cognitive performance and brain imaging measures in UK Biobank

Abstract.

BACKGROUND

Altered expression of the complement component C4A gene is a known risk factor for schizophrenia. Further, predicted brain C4A expression has also been associated with memory function highlighting that altered C4A expression in the brain may be relevant for cognitive and behavioral traits.

METHODS

We obtained genetic information and performance measures on seven cognitive tasks for up to 329 773 individuals from the UK Biobank, as well as brain imaging data for a subset of 33 003 participants. Direct genotypes for variants (n = 3213) within the major histocompatibility complex region were used to impute C4 structural variation, from which predicted expression of the C4A and C4B genes in human brain tissue were predicted. We investigated if predicted brain C4A or C4B expression were associated with cognitive performance and brain imaging measures using linear regression analyses.

RESULTS

We identified significant negative associations between predicted C4A expression and performance on select cognitive tests, and significant associations with MRI-based cortical thickness and surface area in select regions. Finally, we observed significant inconsistent partial mediation of the effects of predicted C4A expression on cognitive performance, by specific brain structure measures.

CONCLUSIONS

These results demonstrate that the C4 risk locus is associated with the central endophenotypes of cognitive performance and brain morphology, even when considered independently of other genetic risk factors and in individuals without mental or neurological disorders.

Gene Expression Meta-Analysis of Cerebellum Samples Supports the FKBP5 Gene-Environment Interaction Model for Schizophrenia

BACKGROUND

One of the most studied molecular models of gene-environment interactions is that of FKBP5, which has been shown to interact with childhood adversity to increase the risk of psychiatric disorders, and has been implicated in schizophrenia. While the model predicts up-regulation of FKBP5, previous brain samples gene expression studies yielded inconsistent results.

METHODS

We performed a systematic gene expression meta-analysis of FKBP5 and NR3C1, a glucocorticoid receptor inhibited by FKBP5, in cerebellum samples of patients with schizophrenia. The gene expression databases GEO, SMRI and those of NIMH were searched, and out of six screened datasets, three were eligible for the meta-analysis (overall 69 with schizophrenia and 78 controls).

RESULTS

We detected up-regulation of FKBP5 and down-regulation of NR3C1 in schizophrenia, and a negative correlation between their expression patterns. Correlation analysis suggested that the detected differential expression did not result from potential confounding factors.

CONCLUSIONS

Our results give significant support to the FKBP5 gene-environment interaction model for schizophrenia, which provides a molecular mechanism by which childhood adversity is involved in the development of the disorder. To explore FKBP5's potential as a therapeutic target, a mapping of its differential expression patterns in different brain regions of schizophrenia patients is needed.

Ablation of STAT3 in Purkinje cells reorganizes cerebellar synaptic plasticity in long-term fear memory network

Emotional memory processing engages a large neuronal network of brain regions including the cerebellum. However, the molecular and cellular mechanisms of the cerebellar cortex modulating the fear memory network are unclear. Here, we illustrate that synaptic signaling in cerebellar Purkinje cells (PCs) via STAT3 regulates long-term fear memory. Transcriptome analyses revealed that PC-specific STAT3 knockout (STAT3PKO) results in transcriptional changes that lead to an increase in the expression of glutamate receptors. The amplitude of AMPA receptor-mediated excitatory postsynaptic currents at parallel fiber (PF) to PC synapses was larger in STAT3PKO mice than in wild-type (WT) littermates. Fear conditioning induced long-term depression of PF-PC synapses in STAT3PKO mice while the same manipulation induced long-term potentiation in WT littermates. STAT3PKO mice showed an aberrantly enhanced long-term fear memory. Neuronal activity in fear-related regions increased in fear-conditioned STAT3PKO mice. Our data suggest that STAT3-dependent molecular regulation in PCs is indispensable for proper expression of fear memory.

Replicability of structural brain alterations associated with general psychopathology: evidence from a population-representative birth cohort

Transdiagnostic research has identified a general psychopathology factor-often called the 'p' factor-that accounts for shared variation across internalizing, externalizing, and thought disorders in diverse samples. It has been argued that the p factor may reflect dysfunctional thinking present in serious mental illness. In support of this, we previously used a theory-free, data-driven multimodal neuroimaging approach to find that higher p factor scores are associated with structural alterations within a cerebello-thalamo-cortical circuit (CTCC) and visual association cortex, both of which are important for monitoring and coordinating information processing in the service of executive control. Here we attempt to replicate these associations by conducting region-of-interest analyses using data from 875 members of the Dunedin Longitudinal Study, a five-decade study of a population-representative birth cohort, collected when they were 45 years old. We further sought to replicate a more recent report that p factor scores can be predicted by patterns of distributed cerebellar morphology as estimated through independent component analysis. We successfully replicated associations between higher p factor scores and both reduced gray matter volume of the visual association cortex and fractional anisotropy of pontine white matter pathways within the CTCC. In contrast, we failed to replicate prior associations between cerebellar structure and p factor scores. Collectively, our findings encourage further focus on the CTCC and visual association cortex as core neural substrates and potential biomarkers of general psychopathology.

Emotional disorders and the cerebellum: Neurobiological substrates, neuropsychiatry, and therapeutic implications

The notion that the cerebellum is devoted exclusively to motor control has been replaced by a more sophisticated understanding of its role in neurological function, one that includes cognition and emotion. Early clinical reports, as well as physiological and behavioral studies in animal models, raised the possibility of a nonmotor role for the cerebellum. Anatomical studies demonstrate cerebellar connectivity with the distributed neural circuits linked with autonomic, sensorimotor, vestibular, associative, and limbic/paralimbic brain areas. Identification of the cerebellar cognitive affective syndrome in adults and children underscored the clinical relevance of the role of the cerebellum in cognition and emotion. It opened new avenues of investigation into higher-order deficits that accompany the ataxias and other cerebellar diseases, as well as the contribution of cerebellar dysfunction to neuropsychiatric and neurocognitive disorders. Brain imaging studies have demonstrated the complexity of cerebellar functional topography, revealing a double representation of the sensorimotor cerebellum in the anterior lobe and lobule VIII and a triple cognitive representation in the cerebellar posterior lobe, as well as representation in the cerebellum of the intrinsic connectivity networks identified in the cerebral hemispheres. This paradigm shift in thinking about the cerebellum has been advanced by the theories of dysmetria of thought and the universal cerebellar transform, harmonizing the dual anatomic realities of homogeneously repeating cerebellar cortical microcircuitry set against the heterogeneous and topographically arranged cerebellar connections with extracerebellar structures. This new appreciation of cerebellar incorporation into circuits that subserve cognition and emotion mandates a deeper understanding of the cerebellum by practitioners in behavioral neurology and neuropsychiatry because it impacts the understanding and diagnosis of disorders of emotion and intellect and has potential for novel cerebellar-based approaches to therapy.

Aberrant Resting-State Cerebellar-Cerebral Functional Connectivity in Unmedicated Patients With Obsessive-Compulsive Disorder

Background: Although abnormality of cerebellar-cerebral functional connectivity at rest in obsessive-compulsive disorder (OCD) has been hypothesized, only a few studies have investigated the neural mechanism. To verify the findings of previous studies, a large sample of patients with OCD was studied because OCD shows possible heterogeneity. Methods: Forty-seven medication-free patients with OCD and 62 healthy controls (HCs) underwent resting-state functional magnetic imaging scans. Seed-based connectivity was examined to investigate differences in cerebellar-cerebral functional connectivity in OCD patients compared with HCs. Correlations between functional connectivity and the severity of obsessive-compulsive symptoms were analyzed. Results: In OCD, we found significantly increased functional connectivity between the right lobule VI and the left precuneus, which is a component of the default mode network (DMN), compared to HCs. However, there was no correlation between the connectivity of the right lobule VI-left precuneus and obsessive-compulsive severity. Conclusions: These findings suggest that altered functional connectivity between the cerebellum and DMN might cause changes in intrinsic large-scale brain networks related to the traits of OCD.

A Multimodal Fusion Analysis of Pretreatment Anatomical and Functional Cortical Abnormalities in Responsive and Non-responsive Schizophrenia

Background: Antipsychotic medications provide limited long-term benefit to ~30% of schizophrenia patients. Multimodal magnetic resonance imaging (MRI) data have been used to investigate brain features between responders and nonresponders to antipsychotic treatment; however, these analytical techniques are unable to weigh the interrelationships between modalities. Here, we used multiset canonical correlation and joint independent component analysis (mCCA + jICA) to fuse MRI data to examine the shared and specific multimodal features between the patients and healthy controls (HCs) and between the responders and non-responders. Method: Resting-state functional and structural MRI data were collected from 55 patients with drug-naïve first-episode schizophrenia (FES) and demographically matched HCs. Based on the decrease in Positive and Negative Syndrome Scale scores from baseline to the 1-year follow-up, FES patients were divided into a responder group (RG) and a non-responder group (NRG). Gray matter volume (GMV), fractional amplitude of low-frequency fluctuation (fALFF), and regional homogeneity (ReHo) maps were used as features in mCCA + jICA. Results: Between FES patients and HCs, there were three modality-specific discriminative independent components (ICs) showing the difference in mixing coefficients (GMV-IC7, GMV-IC8, and fALFF-IC5). The fusion analysis indicated one modality-shared IC (GMV-IC2 and ReHo-IC2) and three modality-specific ICs (GMV-IC1, GMV-IC3, and GMV-IC6) between the RG and NRG. The right postcentral gyrus showed a significant difference in GMV features between FES patients and HCs and modality-shared features (GMV and ReHo) between responders and nonresponders. The modality-shared component findings were highlighted by GMV, mainly in the bilateral temporal gyrus and the right cerebellum associated with ReHo in the right postcentral gyrus. Conclusions: This study suggests that joint anatomical and functional features of the cortices may reflect an early pathophysiological mechanism that is related to a 1-year treatment response.

SS-Detect: Development and Validation of a New Strategy for Source-Based Morphometry in Multiscanner Studies

BACKGROUND AND PURPOSE

Source-based morphometry(SBM) has been used in multicenter studies pooling magnetic resonance imaging data across different scanners to advance the reproducibility of neuroscience research. In the present study, we developed an analysis strategy for Scanner-Specific Detection (SS-Detect) of SBPs in multiscanner studies, and evaluated its performance relative to a conventional strategy.

METHODS

In the first experiment, the SimTB toolbox was used to generate simulated datasets mimicking 20 different scanners with common and scanner-specific SBPs. In the second experiment, we generated one simulated SBP from empirical gray matter volume (GMV) datasets from two different scanners. Moreover, we applied two strategies to compare SBPs between schizophrenia patients' and healthy controls' GMV from two scanners.

RESULTS

The outputs of the conventional strategy were limited to whole-sample-level results across all scanners; the outputs of SS-Detect included whole-sample-level and scanner-specific results. In the first simulation experiment, SS-Detect successfully estimated all simulated SBPs, including the common and scanner-specific SBPs, whereas the conventional strategy detected only some of the whole-sample SBPs. The second simulation experiment showed that both strategies could detect the simulated SBP. Quantitative evaluations of both experiments demonstrated greater accuracy of the SS-Detect in estimating spatial SBPs and subject-specific loading parameters. In the third experiment, SS-Detect detected more significant between-group SBPs, and these SBPs corresponded with the results from voxel-based morphometry analysis, suggesting that SS-Detect has higher sensitivity in detecting between-group differences.

CONCLUSIONS

SS-Detect outperformed the conventional strategy and can be considered advantageous when SBM is applied to a multiscanner study.

Support vector machine-based classification of schizophrenia patients and healthy controls using structural magnetic resonance imaging from two independent sites

Structural brain alterations have been repeatedly reported in schizophrenia; however, the pathophysiology of its alterations remains unclear. Multivariate pattern recognition analysis such as support vector machines can classify patients and healthy controls by detecting subtle and spatially distributed patterns of structural alterations. We aimed to use a support vector machine to distinguish patients with schizophrenia from control participants on the basis of structural magnetic resonance imaging data and delineate the patterns of structural alterations that significantly contributed to the classification performance. We used independent datasets from different sites with different magnetic resonance imaging scanners, protocols and clinical characteristics of the patient group to achieve a more accurate estimate of the classification performance of support vector machines. We developed a support vector machine classifier using the dataset from one site (101 participants) and evaluated the performance of the trained support vector machine using a dataset from the other site (97 participants) and vice versa. We assessed the performance of the trained support vector machines in each support vector machine classifier. Both support vector machine classifiers attained a classification accuracy of >70% with two independent datasets indicating a consistently high performance of support vector machines even when used to classify data from different sites, scanners and different acquisition protocols. The regions contributing to the classification accuracy included the bilateral medial frontal cortex, superior temporal cortex, insula, occipital cortex, cerebellum, and thalamus, which have been reported to be related to the pathogenesis of schizophrenia. These results indicated that the support vector machine could detect subtle structural brain alterations and might aid our understanding of the pathophysiology of these changes in schizophrenia, which could be one of the diagnostic findings of schizophrenia.

Weaker Cerebellocortical Connectivity Within Sensorimotor and Executive Networks in Schizophrenia Compared to Healthy Controls: Relationships with Processing Speed

Background: The cognitive dysmetria theory of schizophrenia proposes that communication between the cerebellum and cerebral cortex is disrupted by structural and functional abnormalities, resulting in psychotic symptoms and cognitive deficits. Methods: Using publicly available data, resting-state functional connectivity (rsFC) was calculated from 20 hemispheric cerebellar lobules as seed regions of interest to the rest of the brain. Group differences in rsFC between individuals with schizophrenia (SZ) and healthy controls (HCs) were computed, and relationships between rsFC and symptom severity and cognitive functioning were explored. Results: HCs demonstrated stronger connectivity than SZ between several cerebellar lobules and cortical regions, most robustly between motor-related cerebellar lobules (V and VIIIa/b) and temporal and parietal cortices. In addition, seven of nine lobules in which reduced cerebellocortical connectivity was observed showed diagnosis × processing speed interactions; HC showed a positive relationship between connectivity and processing speed, whereas SZ did not show this relationship. Other cognitive domains and symptom severity did not show relationships with connectivity. Conclusions: These findings partially support the cognitive dysmetria theory, and suggest that disrupted cerebellocortical connectivity is associated with slowed processing speed in schizophrenia. Impact statement We show in this work that in chronic schizophrenia, there is weaker functional connectivity between previously unstudied inferior posterior cerebellar lobules and cortical association areas. These findings align and extend previous work showing abnormal connectivity of anterior cerebellar lobules. Further, we present a novel finding that these connectivity deficits are differentially associated with processing speed in the schizophrenia versus healthy control groups. Findings provide further evidence for cerebellocortical dysconnectivity and processing speed deficits as biomarkers of schizophrenia, which may have implications for downstream effects on higher order cognitive functions, in line with the cognitive dysmetria theory.

Reliability and comparability of human brain structural covariance networks

Structural covariance analysis is a widely used structural MRI analysis method which characterises the co-relations of morphology between brain regions over a group of subjects. To our knowledge, little has been investigated in terms of the comparability of results between different data sets of healthy human subjects, as well as the reliability of results over the same subjects in different rescan sessions, image resolutions, or FreeSurfer versions. In terms of comparability, our results show substantial differences in the structural covariance matrix between data sets of age- and sex-matched healthy human adults. These differences persist after univariate site correction, they are exacerbated by low sample sizes, and they are most pronounced when using average cortical thickness as a morphological measure. Down-stream graph theoretic analyses further show statistically significant differences. In terms of reliability, substantial differences were also found when comparing repeated scan sessions of the same subjects, image resolutions, and even FreeSurfer versions of the same image. We could further estimate the relative measurement error and showed that it is largest when using cortical thickness as a morphological measure. Using simulated data, we argue that cortical thickness is least reliable because of larger relative measurement errors. Practically, we make the following recommendations (1) combining subjects across sites into one group should be avoided, particularly if sites differ in image resolutions, subject demographics, or preprocessing steps; (2) surface area and volume should be preferred as morphological measures over cortical thickness; (3) a large number of subjects (n≫30 for the Desikan-Killiany parcellation) should be used to estimate structural covariance; (4) measurement error should be assessed where repeated measurements are available; (5) if combining sites is critical, univariate (per ROI) site-correction is insufficient, but error covariance (between ROIs) should be explicitly measured and modelled.

Altered cerebellocerebral structural covariance in individuals with attenuated psychosis syndrome

BACKGROUND

Reduced cerebellar volumes and altered cerebellocerebral structural covariance have been reported in patients with schizophrenia. However, it is not clear whether such altered cerebellocerebral structural covariance would be observed before the onset of psychosis. We examined brain structural changes, including cerebral and cerebellar volumes, and cerebellocerebral structural covariance in individuals with attenuated psychosis syndrome (APS).

MATERIALS AND METHODS

Twenty-one individuals with APS and 24 healthy controls (HC) were recruited and underwent structural MRI brain scan. Differences in voxel-based grey matter (GM) volume and cerebellar volume between the APS and HC groups were examined. The correlation between cerebellar volumes and voxel-based cerebral GM volumes were calculated to measure cerebellocerebral structural covariance in each group followed by group comparisons.

RESULTS

Compared with HC, individuals with APS exhibited extensive GM volume reduction in the frontal and striatal areas and reduced cerebellar volume. Structural covariance analysis indicated that the anterior and posterior parts of the cerebellum showed disparate correlation with cerebral voxel-based GM volumes. Abnormal cerebellar-cerebral correlation was also found in individuals with APS at the medial prefrontal gyrus.

CONCLUSIONS

Our findings suggest that prefrontal and striatal structural changes as well as cerebellar structural covariance at the medial prefrontal gyrus may underpin the risk for psychosis and may serve as a potential target for early intervention in individuals at-risk for psychosis.

Higher Body-Mass Index and Lower Gray Matter Volumes in First Episode of Psychosis

BACKGROUND

Neurostructural alterations are often reported in first episode of psychosis (FEP), but there is heterogeneity in the direction and location of findings between individual studies. The reasons for this heterogeneity remain unknown. Obesity is disproportionately frequent already early in the course of psychosis and is associated with smaller brain volumes. Thus, we hypothesized that obesity may contribute to brain changes in FEP.

METHOD

We analyzed MRI scans from 120 participants with FEP and 114 healthy participants. In primary analyses, we performed voxel-based morphometry (VBM) with small volume corrections to regions associated with FEP or obesity in previous meta-analyses. In secondary analyses, we performed whole-brain VBM analyses.

RESULTS

In primary analyses, we found that when controlling for BMI, FEP had lower GM volume than healthy participants in a) left fronto-temporal region (pTFCE = 0.008) and b) left postcentral gyrus (pTFCE = 0.043). When controlling for FEP, BMI was associated with lower GM volume in left cerebellum (pTFCE < 0.001). In secondary analyses, we found that when controlling for BMI, FEP had lower GM volume than healthy participants in the a) cerebellum (pTFCE = 0.004), b) left frontal (pTFCE = 0.024), and c) right temporal cortex (pTFCE = 0.031). When controlling for FEP, BMI was associated with lower GM volume in cerebellum (pTFCE = 0.004). Levels of C-reactive protein, HDL and LDL-cholesterol correlated with obesity related neurostructural alterations.

CONCLUSIONS

This study suggests that higher BMI, which is frequent in FEP, may contribute to cerebellar alterations in schizophrenia. As previous studies showed that obesity-related brain alterations may be reversible, our findings raise the possibility that improving the screening for and treatment of obesity and associated metabolic changes could preserve brain structure in FEP.

Compression of Cerebellar Functional Gradients in Schizophrenia

Our understanding of cerebellar involvement in brain disorders has evolved from motor processing to high-level cognitive and affective processing. Recent neuroscience progress has highlighted hierarchy as a fundamental principle for the brain organization. Despite substantial research on cerebellar dysfunction in schizophrenia, there is a need to establish a neurobiological framework to better understand the co-occurrence and interaction of low- and high-level functional abnormalities of cerebellum in schizophrenia. To help to establish such a framework, we investigated the abnormalities in the distribution of sensorimotor-supramodal hierarchical processing topography in the cerebellum and cerebellar-cerebral circuits in schizophrenia using a novel gradient-based resting-state functional connectivity (FC) analysis (96 patients with schizophrenia vs 120 healthy controls). We found schizophrenia patients showed a compression of the principal motor-to-supramodal gradient. Specifically, there were increased gradient values in sensorimotor regions and decreased gradient values in supramodal regions, resulting in a shorter distance (compression) between the sensorimotor and supramodal poles of this gradient. This pattern was observed in intra-cerebellar, cerebellar-cerebral, and cerebral-cerebellar FC. Further investigation revealed hyper-connectivity between sensorimotor and cognition areas within cerebellum, between cerebellar sensorimotor and cerebral cognition areas, and between cerebellar cognition and cerebral sensorimotor areas, possibly contributing to the observed compressed pattern. These findings present a novel mechanism that may underlie the co-occurrence and interaction of low- and high-level functional abnormalities of cerebellar and cerebro-cerebellar circuits in schizophrenia. Within this framework of abnormal motor-to-supramodal organization, a cascade of impairments stemming from disrupted low-level sensorimotor system may in part account for high-level cognitive cerebellar dysfunction in schizophrenia.

Gene Expression in Patient-Derived Neural Progenitors Implicates WNT5A Signaling in the Etiology of Schizophrenia

BACKGROUND

Genome-wide association studies of schizophrenia have demonstrated that variations in noncoding regions are responsible for most of the common variation heritability of the disease. It is hypothesized that these risk variants alter gene expression. Therefore, studying alterations in gene expression in schizophrenia may provide a direct approach to understanding the etiology of the disease. In this study we use cultured neural progenitor cells derived from olfactory neuroepithelium (CNON cells) as a genetically unaltered cellular model to elucidate the neurodevelopmental aspects of schizophrenia.

METHODS

We performed a gene expression study using RNA sequencing of CNON cells from 111 control subjects and 144 individuals with schizophrenia. Differentially expressed genes were identified with DESeq2 software, using covariates to correct for sex, age, library batches, and 1 surrogate variable component.

RESULTS

A total of 80 genes were differentially expressed (false discovery rate < 10%), showing enrichment in cell migration, cell adhesion, developmental process, synapse assembly, cell proliferation, and related Gene Ontology categories. Cadherin and Wnt signaling pathways were positive in overrepresentation test, and, in addition, many genes were specifically involved in WNT5A signaling. The differentially expressed genes were modestly, but significantly, enriched in the genes overlapping single nucleotide polymorphisms with genome-wide significant association from the Psychiatric Genomics Consortium genome-wide association study of schizophrenia. We also found substantial overlap with genes associated with other psychiatric disorders or brain development, enrichment in the same Gene Ontology categories as genes with mutations de novo in schizophrenia, and studies of induced pluripotent stem cell-derived neural progenitor cells.

CONCLUSIONS

CNON cells are a good model of the neurodevelopmental aspects of schizophrenia and can be used to elucidate the etiology of the disorder.

Brain Age Prediction Reveals Aberrant Brain White Matter in Schizophrenia and Bipolar Disorder: A Multisample Diffusion Tensor Imaging Study

BACKGROUND

Schizophrenia (SZ) and bipolar disorder (BD) share substantial neurodevelopmental components affecting brain maturation and architecture. This necessitates a dynamic lifespan perspective in which brain aberrations are inferred from deviations from expected lifespan trajectories. We applied machine learning to diffusion tensor imaging (DTI) indices of white matter structure and organization to estimate and compare brain age between patients with SZ, patients with BD, and healthy control (HC) subjects across 10 cohorts.

METHODS

We trained 6 cross-validated models using different combinations of DTI data from 927 HC subjects (18-94 years of age) and applied the models to the test sets including 648 patients with SZ (18-66 years of age), 185 patients with BD (18-64 years of age), and 990 HC subjects (17-68 years of age), estimating the brain age for each participant. Group differences were assessed using linear models, accounting for age, sex, and scanner. A meta-analytic framework was applied to assess the heterogeneity and generalizability of the results.

RESULTS

Tenfold cross-validation revealed high accuracy for all models. Compared with HC subjects, the model including all feature sets significantly overestimated the age of patients with SZ (Cohen's d = -0.29) and patients with BD (Cohen's d = 0.18), with similar effects for the other models. The meta-analysis converged on the same findings. Fractional anisotropy-based models showed larger group differences than the models based on other DTI-derived metrics.

CONCLUSIONS

Brain age prediction based on DTI provides informative and robust proxies for brain white matter integrity. Our results further suggest that white matter aberrations in SZ and BD primarily consist of anatomically distributed deviations from expected lifespan trajectories that generalize across cohorts and scanners.

Maternal cerebellar gray matter volume is associated with daughters' psychotic experience

AIM

A substantial portion of children and adolescents show subthreshold psychotic symptoms called psychotic experience (PE). Because PE shares its biological and environmental risk factors with psychotic spectrum disorders, parental neuroanatomical variation could reflect a heritable biological underpinning of PE that may predict an offspring's PE.

METHODS

A total of 94 participants from 35 families without a diagnosis of major neuropsychiatric disorders were examined, including 14 mother-daughter, 17 mother-son, 12 father-daughter, and 16 father-son dyads. An offspring's PE was assessed with the Atypicality subscale of the Behavior Assessment System for Children - 2nd Edition, Self-Report of Personality form (BASCaty). We examined correlations between voxel-by-voxel parental gray matter volume and their offspring's BASCaty score.

RESULTS

Maternal cerebellar gray matter volume using voxel-based morphometry was positively correlated with their daughters' BASCaty scores. The findings were significant in a more robust approach using cerebellum-specific normalization known. We did not find significant correlation between paternal gray matter volume and BASCaty scores or between offspring gray matter volumes and their BASCaty scores.

CONCLUSION

Expanding upon parent-of-origin effects in psychosis, maternal neuroanatomical variation was associated with daughters' PE. The nature of this sex-specific intergenerational effect is unknown, but maternally transmitted genes may relate cerebellum development to PE pathogenesis.

Synergistic excitability plasticity in cerebellar functioning

The cerebellum, a universal processor for sensory acquisition and internal models, and its association with synaptic and nonsynaptic plasticity have been envisioned as the biological correlates of learning, perception, and even thought. Indeed, the cerebellum is no longer considered merely as the locus of motor coordination and its learning. Here, we introduce the mechanisms underlying the induction of multiple types of plasticity in cerebellar circuit and give an overview focusing on the plasticity of nonsynaptic intrinsic excitability. The discovery of long-term potentiation of synaptic responsiveness in hippocampal neurons led investigations into changes of their intrinsic excitability. This activity-dependent potentiation of neuronal excitability is distinct from that of synaptic efficacy. Systematic examination of excitability plasticity has indicated that the modulation of various types of Ca²⁺ - and voltage-dependent K⁺ channels underlies the phenomenon, which is also triggered by immune activity. Intrinsic plasticity is expressed specifically on dendrites and modifies the integrative processing and filtering effect. In Purkinje cells, modulation of the discordance of synaptic current on soma and dendrite suggested a novel type of cellular learning mechanism. This property enables a plausible synergy between synaptic efficacy and intrinsic excitability, by amplifying electrical conductivity and influencing the polarity of bidirectional synaptic plasticity. Furthermore, the induction of intrinsic plasticity in the cerebellum correlates with motor performance and cognitive processes, through functional connections from the cerebellar nuclei to neocortex and associated regions: for example, thalamus and midbrain. Taken together, recent advances in neuroscience have begun to shed light on the complex functioning of nonsynaptic excitability and the synergy.

Weak correlations between cerebellar tests

Eyeblink conditioning, finger tapping, and prism adaptation are three tasks that have been linked to the cerebellum. Previous research suggests that these tasks recruit distinct but partially overlapping parts of the cerebellum, as well as different extra-cerebellar networks. However, the relationships between the performances on these tasks remain unclear. Here we tested eyeblink conditioning, finger tapping, and prism adaptation in 42 children and 44 adults and estimated the degree of correlation between the performance measures. The results show that performance on all three tasks improves with age in typically developing school-aged children. However, the correlations between the performance measures of the different tasks were consistently weak and without any consistent directions. This reinforces the view that eyeblink conditioning, finger tapping, and prism adaptation rely on distinct mechanisms. Consequently, performance on these tasks cannot be used separately to assess a common cerebellar function or to make general conclusions about cerebellar dysfunction. However, together, these three behavioral tasks have the potential to contribute to a nuanced picture of human cerebellar functions during development.

Positive association between cerebral grey matter metabolism and dopamine D2/D3 receptor availability in healthy and schizophrenia subjects: An 18F-fluorodeoxyglucose and 18F-fallypride positron emission tomography study

Objectives: Overlapping decreases in extrastriatal dopamine D₂/D₃-receptor availability and glucose metabolism have been reported in subjects with schizophrenia. It remains unknown whether these findings are physiologically related or coincidental.Methods: To ascertain this, we used two consecutive ¹⁸F-fluorodeoxyglucose and ¹⁸F-fallypride positron emission tomography scans in 19 healthy and 25 unmedicated schizophrenia subjects. Matrices of correlations between ¹⁸F-fluorodeoxyglucose uptake and ¹⁸F-fallypride binding in voxels at the same xyz location and AFNI-generated regions of interest were evaluated in both diagnostic groups.Results:¹⁸F-fluorodeoxyglucose uptake and ¹⁸F-fallypride binding potential were predominantly positively correlated across the striatal and extrastriatal grey matter in both healthy and schizophrenia subjects. In comparison to healthy subjects, significantly weaker correlations in subjects with schizophrenia were confirmed in the right cingulate gyrus and thalamus, including the mediodorsal, lateral dorsal, anterior, and midline nuclei. Schizophrenia subjects showed decreased D₂/D₃-receptor availability in the hypothalamus, mamillary bodies, thalamus and several thalamic nuclei, and increased glucose uptake in three lobules of the cerebellar vermis.Conclusions: Dopaminergic system may be involved in modulation of grey matter metabolism and neurometabolic coupling in both healthy human brain and psychopathology. Hyperdopaminergic state in untreated schizophrenia may at least partly account for the corresponding decreases in grey matter metabolism.