Neuroanatomical abnormalities in schizophrenia: a multimodal voxelwise meta-analysis and meta-regression analysis

NRN1 epistasis with BDNF and CACNA1C: mediation effects on symptom severity through neuroanatomical changes in schizophrenia

The expression of Neuritin-1 (NRN1), a neurotrophic factor crucial for neurodevelopment and synaptic plasticity, is enhanced by the Brain Derived Neurotrophic Factor (BDNF). Although the receptor of NRN1 remains unclear, it is suggested that NRN1's activation of the insulin receptor (IR) pathway promotes the transcription of the calcium voltage-gated channel subunit alpha1 C (CACNA1C). These three genes have been independently associated with schizophrenia (SZ) risk, symptomatology, and brain differences. However, research on how they synergistically modulate these phenotypes is scarce. We aimed to study whether the genetic epistasis between these genes affects the risk and clinical presentation of the disorder via its effect on brain structure. First, we tested the epistatic effect of NRN1 and BDNF or CACNA1C on (i) the risk for SZ, (ii) clinical symptoms severity and functionality (onset, PANSS, CGI and GAF), and (iii) brain cortical structure (thickness, surface area and volume measures estimated using FreeSurfer) in a sample of 86 SZ patients and 89 healthy subjects. Second, we explored whether those brain clusters influenced by epistatic effects mediate the clinical profiles. Although we did not find a direct epistatic impact on the risk, our data unveiled significant effects on the disorder's clinical presentation. Specifically, the NRN1-rs10484320 x BDNF-rs6265 interplay influenced PANSS general psychopathology, and the NRN1-rs4960155 x CACNA1C-rs1006737 interaction affected GAF scores. Moreover, several interactions between NRN1 SNPs and BDNF-rs6265 significantly influenced the surface area and cortical volume of the frontal, parietal, and temporal brain regions within patients. The NRN1-rs10484320 x BDNF-rs6265 epistasis in the left lateral orbitofrontal cortex fully mediated the effect on PANSS general psychopathology. Our study not only adds clinical significance to the well-described molecular relationship between NRN1 and BDNF but also underscores the utility of deconstructing SZ into biologically validated brain-imaging markers to explore their mediation role in the path from genetics to complex clinical manifestation.

Psychosis superspectrum II: neurobiology, treatment, and implications

Alternatives to traditional categorical diagnoses have been proposed to improve the validity and utility of psychiatric nosology. This paper continues the companion review of an alternative model, the psychosis superspectrum of the Hierarchical Taxonomy of Psychopathology (HiTOP). The superspectrum model aims to describe psychosis-related psychopathology according to data on distributions and associations among signs and symptoms. The superspectrum includes psychoticism and detachment spectra as well as narrow subdimensions within them. Auxiliary domains of cognitive deficit and functional impairment complete the psychopathology profile. The current paper reviews evidence on this model from neurobiology, treatment response, clinical utility, and measure development. Neurobiology research suggests that psychopathology included in the superspectrum shows similar patterns of neural alterations. Treatment response often mirrors the hierarchy of the superspectrum with some treatments being efficacious for psychoticism, others for detachment, and others for a specific subdimension. Compared to traditional diagnostic systems, the quantitative nosology shows an approximately 2-fold increase in reliability, explanatory power, and prognostic accuracy. Clinicians consistently report that the quantitative nosology has more utility than traditional diagnoses, but studies of patients with frank psychosis are currently lacking. Validated measures are available to implement the superspectrum model in practice. The dimensional conceptualization of psychosis-related psychopathology has implications for research, clinical practice, and public health programs. For example, it encourages use of the cohort study design (rather than case-control), transdiagnostic treatment strategies, and selective prevention based on subclinical symptoms. These approaches are already used in the field, and the superspectrum provides further impetus and guidance for their implementation. Existing knowledge on this model is substantial, but significant gaps remain. We identify outstanding questions and propose testable hypotheses to guide further research. Overall, we predict that the more informative, reliable, and valid characterization of psychopathology offered by the superspectrum model will facilitate progress in research and clinical care.

An attentional and working memory theory of hallucination vulnerability in frontotemporal dementia

The rate and prevalence of hallucinations in behavioural variant frontotemporal dementia is well established. The mechanisms for underlying vulnerability however are the least well described in FTD compared with other neuropsychiatric conditions, despite the presence of these features significantly complicating the diagnostic process. As such, this present study aimed to provide a detailed characterization of the neural, cognitive and behavioural profile associated with a predisposition to hallucinatory experiences in behavioural variant frontotemporal dementia. In total, 153 patients with behavioural variant frontotemporal dementia were recruited sequentially for this study. A group of patients with well characterized hallucinations and good-quality volumetric MRI scans (n = 23) were genetically and demographically matched to a group without hallucinations (n = 23) and a healthy control cohort (n = 23). All patients were assessed at their initial visit by means of a detailed clinical interview, a comprehensive battery of neuropsychological tests and MRI. Data were analysed according to three levels: (i) the relationship between neural structures, cognition, behaviour and hallucinations in behavioural variant frontotemporal dementia; (ii) the impact of the C9orf72 expansion; and (iii) hallucination subtype on expression of hallucinations. Basic and complex attentional (including divided attention and working memory) and visual function measures differed between groups (all P < 0.001) with hallucinators demonstrating poorer performance, along with evidence of structural changes centred on the prefrontal cortex, caudate and cerebellum (corrected for False Discovery Rate at P < 0.05 with a cluster threshold of 100 contiguous voxels). Attentional processes were also implicated in C9orf72 carriers with hallucinations with structural changes selectively involving the thalamus. Patients with visual hallucinations in isolation showed a similar pattern with emphasis on cerebellar atrophy. Our findings provided novel insights that attentional and visual function subsystems and related distributed brain structures are implicated in the generation of hallucinations in behavioural variant frontotemporal dementia, that dissociate across C9orf72, sporadic behavioural variant frontotemporal dementia and for the visual subtype of hallucinations. This loading on attentional and working memory measures is in line with current mechanistic models of hallucinations that frequently suggest a failure of integration of cognitive and perceptual processes. We therefore propose a novel cognitive and neural model for hallucination predisposition in behavioural variant frontotemporal dementia that aligns with a transdiagnostic model for hallucinations across neurodegeneration and psychiatry.

Longitudinal reduction in brain volume in patients with schizophrenia and its association with cognitive function

Establishing a brain biomarker for schizophrenia is strongly desirable not only to support diagnosis by psychiatrists but also to help track the progressive changes in the brain over the course of the illness. A brain morphological signature of schizophrenia was reported in a recent study and is defined by clusters of brain regions with reduced volume in schizophrenia patients compared to healthy individuals. This signature was proven to be effective at differentiating patients with schizophrenia from healthy individuals, suggesting that it is a good candidate brain biomarker of schizophrenia. However, the longitudinal characteristics of this signature have remained unclear. In this study, we examined whether these changes occurred over time and whether they were associated with clinical outcomes. We found a significant change in the brain morphological signature in schizophrenia patients with more brain volume loss than the natural, age-related reduction in healthy individuals, suggesting that this change can capture a progressive morphological change in the brain. We further found a significant association between changes in the brain morphological signature and changes in the full-scale intelligence quotient (IQ). The patients with IQ improvement showed preserved brain morphological signatures, whereas the patients without IQ improvement showed progressive changes in the brain morphological signature, suggesting a link between potential recovery of intellectual abilities and the speed of brain pathology progression. We conclude that the brain morphological signature is a brain biomarker that can be used to evaluate progressive changes in the brain that are associated with cognitive impairment due to schizophrenia.

Structural brain abnormalities and aggressive behaviour in schizophrenia: Mega-analysis of data from 2095 patients and 2861 healthy controls via the ENIGMA consortium

Background

Schizophrenia is associated with an increased risk of aggressive behaviour, which may partly be explained by illness-related changes in brain structure. However, previous studies have been limited by group-level analyses, small and selective samples of inpatients and long time lags between exposure and outcome.

Methods

This cross-sectional study pooled data from 20 sites participating in the international ENIGMA-Schizophrenia Working Group. Sites acquired T1-weighted and diffusion-weighted magnetic resonance imaging scans in a total of 2095 patients with schizophrenia and 2861 healthy controls. Measures of grey matter volume and white matter microstructural integrity were extracted from the scans using harmonised protocols. For each measure, normative modelling was used to calculate how much patients deviated (in z-scores) from healthy controls at the individual level. Ordinal regression models were used to estimate the associations of these deviations with concurrent aggressive behaviour (as odds ratios [ORs] with 99% confidence intervals [CIs]). Mediation analyses were performed for positive symptoms (i.e., delusions, hallucinations and disorganised thinking), impulse control and illness insight. Aggression and potential mediators were assessed with the Positive and Negative Syndrome Scale, Scale for the Assessment of Positive Symptoms or Brief Psychiatric Rating Scale.

Results

Aggressive behaviour was significantly associated with reductions in total cortical volume (OR [99% CI] = 0.88 [0.78, 0.98], p = .003) and global white matter integrity (OR [99% CI] = 0.72 [0.59, 0.88], p = 3.50 × 10-5) and additional reductions in dorsolateral prefrontal cortex volume (OR [99% CI] = 0.85 [0.74, 0.97], p =.002), inferior parietal lobule volume (OR [99% CI] = 0.76 [0.66, 0.87], p = 2.20 × 10-7) and internal capsule integrity (OR [99% CI] = 0.76 [0.63, 0.92], p = 2.90 × 10-4). Except for inferior parietal lobule volume, these associations were largely mediated by increased severity of positive symptoms and reduced impulse control.

Conclusions

This study provides evidence that the co-occurrence of positive symptoms, poor impulse control and aggressive behaviour in schizophrenia has a neurobiological basis, which may inform the development of therapeutic interventions.

Relationships among the gut microbiome, brain networks, and symptom severity in schizophrenia patients: A mediation analysis

The microbiome-gut-brain axis (MGBA) plays a critical role in schizophrenia (SZ). However, the underlying mechanisms of the interactions among the gut microbiome, brain networks, and symptom severity in SZ patients remain largely unknown. Fecal samples, structural and functional magnetic resonance imaging (MRI) data, and Positive and Negative Syndrome Scale (PANSS) scores were collected from 38 SZ patients and 38 normal controls, respectively. The data of 16S rRNA gene sequencing were used to analyze the abundance of gut microbiome and the analysis of human brain networks was applied to compute the nodal properties of 90 brain regions. A total of 1,691,280 mediation models were constructed based on 261 gut bacterial, 810 nodal properties, and 4 PANSS scores in SZ patients. A strong correlation between the gut microbiome and brain networks (r = 0.89, false discovery rate (FDR) -corrected p < 0.05) was identified. Importantly, the PANSS scores were linearly correlated with both the gut microbiome (r = 0.5, FDR-corrected p < 0.05) and brain networks (r = 0.59, FDR-corrected p < 0.05). The abundance of genus Sellimonas significantly affected the PANSS negative scores of SZ patients via the betweenness centrality of white matter networks in the inferior frontal gyrus and amygdala. Moreover, 19 significant mediation models demonstrated that the nodal properties of 7 brain regions, predominately from the systems of visual, language, and control of action, showed significant mediating effects on the PANSS scores with the gut microbiome as mediators. Together, our findings indicated the tripartite relationships among the gut microbiome, brain networks, and PANSS scores and suggested their potential role in the neuropathology of SZ.

Fibre density and fibre-bundle cross-section of the corticospinal tract are distinctly linked to psychosis-specific symptoms in antipsychotic-naïve patients with first-episode schizophrenia

Multiple lines of research support the dysconnectivity hypothesis of schizophrenia. However, findings on white matter (WM) alterations in patients with schizophrenia are widespread and non-specific. Confounding factors from magnetic resonance image (MRI) processing, clinical diversity, antipsychotic exposure, and substance use may underlie some of the variability. By application of refined methodology and careful sampling, we rectified common confounders investigating WM and symptom correlates in a sample of strictly antipsychotic-naïve first-episode patients with schizophrenia. Eighty-six patients and 112 matched controls underwent diffusion MRI. Using fixel-based analysis (FBA), we extracted fibre-specific measures such as fibre density and fibre-bundle cross-section. Group differences on fixel-wise measures were examined with multivariate general linear modelling. Psychopathology was assessed with the Positive and Negative Syndrome Scale. We separately tested multivariate correlations between fixel-wise measures and predefined psychosis-specific versus anxio-depressive symptoms. Results were corrected for multiple comparisons. Patients displayed reduced fibre density in the body of corpus callosum and in the middle cerebellar peduncle. Fibre density and fibre-bundle cross-section of the corticospinal tract were positively correlated with suspiciousness/persecution, and negatively correlated with delusions. Fibre-bundle cross-section of isthmus of corpus callosum and hallucinatory behaviour were negatively correlated. Fibre density and fibre-bundle cross-section of genu and splenium of corpus callosum were negative correlated with anxio-depressive symptoms. FBA revealed fibre-specific properties of WM abnormalities in patients and differentiated associations between WM and psychosis-specific versus anxio-depressive symptoms. Our findings encourage an itemised approach to investigate the relationship between WM microstructure and clinical symptoms in patients with schizophrenia.

Network-Based Spreading of Gray Matter Changes Across Different Stages of Psychosis

Importance

Psychotic illness is associated with anatomically distributed gray matter reductions that can worsen with illness progression, but the mechanisms underlying the specific spatial patterning of these changes is unknown.

Objective

To test the hypothesis that brain network architecture constrains cross-sectional and longitudinal gray matter alterations across different stages of psychotic illness and to identify whether certain brain regions act as putative epicenters from which volume loss spreads.

Design, Settings, and Participants

This case-control study included 534 individuals from 4 cohorts, spanning early and late stages of psychotic illness. Early-stage cohorts included patients with antipsychotic-naive first-episode psychosis (n = 59) and a group of patients receiving medications within 3 years of psychosis onset (n = 121). Late-stage cohorts comprised 2 independent samples of people with established schizophrenia (n = 136). Each patient group had a corresponding matched control group (n = 218). A sample of healthy adults (n = 356) was used to derive representative structural and functional brain networks for modeling of network-based spreading processes. Longitudinal illness-related and antipsychotic-related gray matter changes over 3 and 12 months were examined using a triple-blind randomized placebo-control magnetic resonance imaging study of the antipsychotic-naive patients. All data were collected between April 29, 2008, and January 15, 2020, and analyses were performed between March 1, 2021, and January 14, 2023.

Main Outcomes and Measures

Coordinated deformation models were used to estimate the extent of gray matter volume (GMV) change in each of 332 parcellated areas by the volume changes observed in areas to which they were structurally or functionally coupled. To identify putative epicenters of volume loss, a network diffusion model was used to simulate the spread of pathology from different seed regions. Correlations between estimated and empirical spatial patterns of GMV alterations were used to quantify model performance.

Results

Of 534 included individuals, 354 (66.3%) were men, and the mean (SD) age was 28.4 (7.4) years. In both early and late stages of illness, spatial patterns of cross-sectional volume differences between patients and controls were more accurately estimated by coordinated deformation models constrained by structural, rather than functional, network architecture (r range, >0.46 to <0.57; P < .01). The same model also robustly estimated longitudinal volume changes related to illness (r ≥ 0.52; P < .001) and antipsychotic exposure (r ≥ 0.50; P < .004). Network diffusion modeling consistently identified, across all 4 data sets, the anterior hippocampus as a putative epicenter of pathological spread in psychosis. Epicenters of longitudinal GMV loss were apparent in posterior cortex early in the illness and shifted to the prefrontal cortex with illness progression.

Conclusion and Relevance

These findings highlight a central role for white matter fibers as conduits for the spread of pathology across different stages of psychotic illness, mirroring findings reported in neurodegenerative conditions. The structural connectome thus represents a fundamental constraint on brain changes in psychosis, regardless of whether these changes are caused by illness or medication. Moreover, the anterior hippocampus represents a putative epicenter of early brain pathology from which dysfunction may spread to affect connected areas.

Neural correlates of mental state decoding and mental state reasoning in schizophrenia

Theory of mind skills are disrupted in schizophrenia. However, various theory of mind tasks measure different neurocognitive domains. This multimodal neuroimaging study aimed to investigate the neuroanatomical correlates of mental state decoding and reasoning components of theory of mind in schizophrenia and healthy controls (HCs) using T1-weighted and diffusion-weighted (DTI) magnetic resonance imaging (MRI). Sixty-two patients with schizophrenia and 34 HCs were included. The Reading the Mind in the Eyes (RMET) and Hinting tests were used to evaluate mental state decoding and reasoning, respectively. Correlations between social cognition and cortical parameters (thickness, volume, surface area), or DTI scalars (fractional anisotropy, axial diffusivity, radial diffusivity) were cluster-based corrected for multiple comparisons. In schizophrenia, RMET scores showed positive correlations in 3 clusters, including left insula thickness, right superior-temporal thickness, left superior-temporal-sulcus volume, and DTI analysis revealed that fractional anisotropy showed positive correlations in 3 clusters, including right inferior-fronto-occipital fasciculus, left forceps-major, left inferior-fronto-occipital fasciculus. In schizophrenia, Hinting test scores showed positive correlations in 3 clusters in T1-weighted MRI, including left superior-temporal-sulcus volume, left superior-temporal-sulcus surface area, left pars-orbitalis volume. In conclusion, this study provided evidence for the involvement of particular cortical regions and white matter tracts in mental state decoding and reasoning.

Brain functional alterations in patients with anorexia nervosa: A meta-analysis of task-based functional MRI studies

The goal of this study was to discern the neural activation patterns associated with anorexia nervosa (AN) in response to tasks related to body-, food-, emotional-, cognitive-, and reward- processing. A meta-analysis was performed on task-based fMRI studies, revealing that patients with AN showed increased activity in the left superior temporal gyrus and bilaterally in the ACC during a reward-related task. During cognitive-related tasks, patients with AN also showed increased activity in the left superior parietal gyrus, right middle temporal gyrus, but decreased activity in the MCC. Additionally, patients with AN showed increased activity bilaterally in the cerebellum, MCC, and decreased activity bilaterally in the bilateral precuneus/PCC, right middle temporal gyrus, left ACC when they viewed food images. During emotion-related tasks, patients with AN showed increased activity in the left cerebellum, but decreased activity bilaterally in the striatum, right mPFC, and right superior parietal gyrus. Patients with AN also showed increased activity in the right striatum and decreased activity in the right inferior temporal gyrus and bilaterally in the mPFC during body-related tasks. The present meta-analysis provides a comprehensive overview of the patterns of brain activity evoked by task stimuli, thereby augmenting the current comprehension of the pathophysiology in AN.

Cortical anatomical variations, gene expression profiles, and clinical phenotypes in patients with schizophrenia

BACKGROUND AND HYPOTHESIS

Schizophrenia (SZ) patients display significant structural brain abnormalities; nevertheless, the genetic mechanisms regulating cortical anatomical variations and their correlation with the disease phenotype are still ambiguous.

STUDY DESIGN

We characterized anatomical variation using a surface-based method derived from structural magnetic resonance imaging of patients with SZ and age- and sex-matched healthy controls (HCs). Partial least-squares regression was performed across cortex regions between anatomical variation and average transcriptional profiles of SZ risk genes and all qualified genes from the Allen Human Brain Atlas. The morphological features of each brain region were correlated to symptomology variables in patients with SZ using partial correlation analysis.

STUDY RESULTS

A total of 203 SZ and 201 HCs were included in the final analysis. We observed significant variation of 55 regions of cortical thickness, 23 regions of volume, 7 regions of area, and 55 regions of local gyrification index (LGI) between SZ and HC groups. Expression profiles of 4 SZ risk genes and 96 genes from all qualified genes showed a correlation to anatomical variability, however, after multiple comparisons, the correlations were no longer significant. LGI variability in multiple frontal subregions was associated with specific symptoms of SZ, whereas cognitive function involving attention/vigilance was linked to LGI variability across nine brain regions.

CONCLUSIONS

Cortical anatomical variation of patients with schizophrenia is associated with gene transcriptome profiles as well as clinical phenotypes.

Approach to schizophrenia

Schizophrenia is the most common of a group of psychotic disorders that occur in approximately 3% of the population over the lifespan. It has clear genetic antecedents, which are shared across the spectrum of psychotic disorders; however, a range of other biological and social factors influence the onset and treatment of the disorder. Schizophrenia is diagnosed by a characteristic set of symptoms (positive, negative, disorganisation, cognitive and affective) accompanied by a functional decline. Investigations are used to exclude other organic causes of psychosis and to provide a baseline for the negative effects of pharmacological treatments. Treatment requires a combination of pharmacological and psychosocial interventions. Physical health is poor in this group of people and this is not helped by inconsistent care from health services. Although earlier intervention has improved the immediate outcomes, the longer-term outcome has not significantly shifted.

The Poly I:C maternal immune stimulation model shows unique patterns of brain metabolism, morphometry, and plasticity in female rats

Introduction: Prenatal infections are associated with an increased risk of the onset of schizophrenia. Rodent models of maternal immune stimulation (MIS) have been extensively used in preclinical studies. However, many of these studies only include males, omitting pathophysiological features unique to females. The aim of this study is to characterize the MIS model in female rats using positron emission tomography (PET), structural magnetic resonance imaging (MR), and neuroplasticiy studies. Methods: In gestational day 15, Poly I:C (or Saline) was injected into pregnant Wistar rats to induce the MIS model. Imaging studies: [¹⁸F]-fluoro-2-deoxy-D-glucose-PET scans of female-offspring were acquired at post-natal day (PND) 35 and PND100. Furthermore, T2-MR brain images were acquired in adulthood. Differences in FDG uptake and morphometry between groups were assessed with SPM12 and Regions of Interest (ROI) analyses. Ex vivo study: The density of parvalbumin expressing interneurons (PV), perineuronal nets (PNN), and parvalbumin expressing interneurons surrounded by perineuronal nets (PV-PNN) were evaluated in the prelimbic cortex and basolateral amygdala using confocal microscopy. ROIs and neuroplasticity data were analyzed by 2-sample T-test and 2-way-ANOVA analyses, respectively. Results: A significant increase in brain metabolism was found in all animals at adulthood compared to adolescence. MIS hardly modified brain glucose metabolism in females, highlighting a significant hypometabolism in the thalamus at adulthood. In addition, MIS induced gray matter (GM) enlargements in the pituitary, hippocampus, substantia nigra, and cingulate cortex, and GM shrinkages in some thalamic nuclei, cerebelar areas, and brainstem. Moreover, MIS induced white matter shrinkages in the cerebellum, brainstem and corpus callosum, along with cerebrospinal fluid enlargements in the lateral and 4th ventricles. Finally, MIS reduced the density of PV, PNN, and PV-PNN in the basolateral amygdala. Conclusion: Our work showed in vivo the differential pattern of functional and morphometric affectation in the MIS model in females, as well as the deficits caused at the synaptic level according to sex. The differences obtained highlight the relevance of including both sexes in psychiatric research in order to consider their pathophysiological particularities and successfully extend the benefits obtained to the entire patient population.

Dysregulation of Synaptic Plasticity Markers in Schizophrenia

Schizophrenia is a mental disorder characterized by cognitive impairment resulting in compromised quality of life. Since the regulation of synaptic plasticity has functional implications in various aspects of cognition such as learning, memory, and neural circuit maturation, the dysregulation of synaptic plasticity is considered as a pathobiological feature of schizophrenia. The findings from our recently concluded studies indicate that there is an alteration in levels of synaptic plasticity markers such as neural cell adhesion molecule-1 (NCAM-1), Neurotropin-3 (NT-3) and Matrix-mettaloproteinase-9 (MMP-9) in schizophrenia patients. The objective of the present article is to review the role of markers of synaptic plasticity in schizophrenia. PubMed database (http;//www.ncbi.nlm.nih.gov/pubmed) was used to perform an extensive literature search using the keywords schizophrenia and synaptic plasticity. We conclude that markers of synaptic plasticity are altered in schizophrenia and may lead to complications of schizophrenia including cognitive dysfunction.

Hearing voices in the head: Two meta-analyses on structural correlates of auditory hallucinations in schizophrenia

Past voxel-based morphometry (VBM) studies demonstrate reduced grey matter volume (GMV) in schizophrenia (SZ) patients' brains in various cortical and subcortical regions. Probably due to SZ symptoms' heterogeneity, these results are often inconsistent and difficult to integrate. We hypothesized that focusing on auditory verbal hallucinations (AVH) - one of the most common SZ symptoms - would allow reducing heterogeneity and discovering further compelling evidence of SZ neural correlates. We carried out two voxel-based meta-analyses of past studies that investigated the structural correlates of AVH in SZ. The review of whole-brain VBM studies published until June 2022 in PubMed and PsychInfo databases yielded (a) 13 studies on correlations between GMV and AVH severity in SZ patients (n = 472; 86 foci), and (b) 11 studies involving comparisons between hallucinating SZ patients (n = 504) and healthy controls (n = 524; 74 foci). Data were analyzed using the Activation Likelihood Estimation method. AVH severity was associated with decreased GMV in patients' left superior temporal gyrus (STG) and left posterior insula. Compared with healthy controls, hallucinating SZ patients showed reduced GMV on the left anterior insula and left inferior frontal gyrus (IFG). Our findings revealed important structural dysfunctions in a left lateralized cluster of brain regions, including the insula and temporo-frontal regions, that significantly contribute to the severity and persistence of AVH. Structural atrophy found in circuits involved in generating and perceiving speech, as well as in auditory signal processing, might reasonably be considered a biological marker of AVH in SZ.

Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review

Autism spectrum disorder (ASD) is a brain condition characterized by diverse signs and symptoms that appear in early childhood. ASD is also associated with communication deficits and repetitive behavior in affected individuals. Various ASD detection methods have been developed, including neuroimaging modalities and psychological tests. Among these methods, magnetic resonance imaging (MRI) imaging modalities are of paramount importance to physicians. Clinicians rely on MRI modalities to diagnose ASD accurately. The MRI modalities are non-invasive methods that include functional (fMRI) and structural (sMRI) neuroimaging methods. However, diagnosing ASD with fMRI and sMRI for specialists is often laborious and time-consuming; therefore, several computer-aided design systems (CADS) based on artificial intelligence (AI) have been developed to assist specialist physicians. Conventional machine learning (ML) and deep learning (DL) are the most popular schemes of AI used for diagnosing ASD. This study aims to review the automated detection of ASD using AI. We review several CADS that have been developed using ML techniques for the automated diagnosis of ASD using MRI modalities. There has been very limited work on the use of DL techniques to develop automated diagnostic models for ASD. A summary of the studies developed using DL is provided in the Supplementary Appendix. Then, the challenges encountered during the automated diagnosis of ASD using MRI and AI techniques are described in detail. Additionally, a graphical comparison of studies using ML and DL to diagnose ASD automatically is discussed. We suggest future approaches to detecting ASDs using AI techniques and MRI neuroimaging.

Structural network alterations and their association with neurological soft signs in schizophrenia: Evidence from clinical patients and unaffected siblings

BACKGROUND

Grey matter abnormalities and neurological soft signs (NSS) have been found in schizophrenia patients and their unaffected relatives. Evidence suggested that NSS are associated with grey matter morphometrical alterations in multiple regions in schizophrenia. However, the association between NSS and structural abnormalities at network level remains largely unexplored, especially in the schizophrenia and unaffected siblings.

METHOD

We used source-based morphometry (SBM) to examine the association of structural brain network characteristics with NSS in 62 schizophrenia patients, 25 unaffected siblings, and 60 healthy controls.

RESULTS

Two components, namely the IC-5 (superior temporal gyrus, inferior frontal gyrus and insula network) and the IC-10 (parahippocampal gyrus, fusiform, thalamus and insula network) showed significant grey matter reductions in schizophrenia patients compared to healthy controls and unaffected siblings. Further association analysis demonstrated separate NSS-related grey matter covarying patterns in schizophrenia, unaffected siblings and healthy controls. Specifically, NSS were negatively associated with IC-1 (hippocampus, caudate and thalamus network) and IC-5 in schizophrenia, but with IC-3 (caudate, superior and middle frontal cortices network) in unaffected siblings and with IC-5 in healthy controls.

CONCLUSION

Our results confirmed the key cortical and subcortical network abnormalities and NSS-related grey matter covarying patterns in the schizophrenia and unaffected siblings. Our findings suggest that brain regions implicating genetic liability to schizophrenia are partly separated from brain regions implicating neural abnormalities.

Facial emotion perception abilities are related to grey matter volume in the culmen of cerebellum anterior lobe in drug-naïve patients with first-episode schizophrenia

Impaired capability for understanding and interpreting the expressions on other people's faces manifests itself as a core feature of schizophrenia, contributing to social dysfunction. With the purpose of better understanding of the neurobiological basis of facial emotion perception deficits in schizophrenia, we investigated facial emotion perception abilities and regional structural brain abnormalities in drug-naïve patients with first-episode schizophrenia, and then examined the correlation between them. Fifty-two drug-naive patients with first-episode schizophrenia and 29 group-matched healthy controls were examined for facial emotion perception abilities assessed with the Facial Emotion Categorization and performed magnetic resonance imaging. The Facial Emotion Categorization data were inserted into a logistic function model so as to calculate shift point and slope as outcome measurements. Voxel-based morphometry was applied to investigate regional grey matter volume (GMV) alterations. The relationship between facial emotion perception and GMV was explored in patients using voxel-wise correlation analysis within brain regions that showed a significant GMV alterations in patients compared with controls. The schizophrenic patients performed differently on Facial Emotion Categorization tasks from the controls and presented a higher shift point and a steeper slope. Relative to the controls, patients showed GMV reductions in the superior temporal gyrus, middle occipital gyrus, parahippocampa gyrus, posterior cingulate, the culmen of cerebellum anterior lobe, cerebellar tonsil, and the declive of cerebellum posterior lobe. Importantly, abnormal performance on Facial Emotion Categorization was found correlated with GMV alterations in the culmen of cerebellum anterior lobe in schizophrenia. This study suggests that reduced GMV in the culmen of cerebellum anterior lobe occurs in first-episode schizophrenia, constituting a potential neuropathological basis for the impaired facial emotion perception in schizophrenia.

Tract-specific white matter microstructural alterations in subjects with schizophrenia and unaffected first-degree relatives

White matter tracts alterations have been reported in schizophrenia (SZ), but whether such abnormalities are associated with the effects of the disorder itself and/or genetic vulnerability remains unclear. Moreover, the specific patterns of different parts of these altered tracts have been less well studied. Thus, diffusion-weighted images were acquired from 38 healthy controls (HCs), 48 schizophrenia patients, and 33 unaffected first-degree relatives of SZs (FDRs). Diffusion properties of the 25 major tracts automatically extracted with probabilistic tractography were calculated and compared among groups. Regarding the peripheral regions of the tracts, significantly higher diffusivity values in the left superior longitudinal fasciculus (SLF) and the left anterior thalamic radiation (ATR) were observed in SZs than in HCs and unaffected FDRs. However, there were no significant differences between HCs and FDRs in these two tracts. While no main effects of group with respect to the core regions of the 25 tracts survived multiple comparisons correction, FDRs had significantly higher diffusivity values in the left medial lemniscus and lower diffusivity values in the middle cerebellar peduncle than HCs and SZs. These findings enhance the understanding of the abnormal patterns in the peripheral and core regions of the tracts in SZs and those at high genetic risk for schizophrenia. Our results suggest that alterations in the peripheral regions of the left SLF and ATR are features of established illness rather than genetic predisposition, which may serve as critical neural substrates for the psychopathology of schizophrenia.

Thalamic and striato-pallidal volumes in schizophrenia patients and individuals at risk for psychosis: A multi-atlas segmentation study

Despite previous neuroimaging studies demonstrating morphological abnormalities of the thalamus and other subcortical structures in patients with schizophrenia, the potential role of the thalamus and its subdivisions in the pathophysiology of this illness remains elusive. It is also unclear whether similar changes of these structures occur in individuals at high risk for psychosis. In this study, magnetic resonance imaging was employed with the Multiple Automatically Generated Templates (MAGeT) brain segmentation algorithm to determine volumes of the thalamic subdivisions, the striatum (caudate, putamen, and nucleus accumbens), and the globus pallidus in 62 patients with schizophrenia, 38 individuals with an at-risk mental state (ARMS) [4 of whom (10.5%) subsequently developed schizophrenia], and 61 healthy subjects. Cognitive function of the patients was assessed by using the Brief Assessment of Cognition in Schizophrenia (BACS) and the Schizophrenia Cognition Rating Scale (SCoRS). Thalamic volume (particularly the medial dorsal and ventral lateral nuclei) was smaller in the schizophrenia group than the ARMS and control groups, while there were no differences for the striatum and globus pallidus. In the schizophrenia group, the reduction of thalamic ventral lateral nucleus volume was significantly associated with lower BACS score. The pallidal volume was positively correlated with the dose of antipsychotic treatment in the schizophrenia group. These results suggest that patients with schizophrenia, but not those with ARMS, exhibit volume reduction in specific thalamic subdivisions, which may underlie core clinical features of this illness.

Structural and diffusion MRI based schizophrenia classification using 2D pretrained and 3D naive Convolutional Neural Networks

The ability of automatic feature learning makes Convolutional Neural Network (CNN) potentially suitable to uncover the complex and widespread brain changes in schizophrenia. Despite that, limited studies have been done on schizophrenia identification using interpretable deep learning approaches on multimodal neuroimaging data. Here, we developed a deep feature approach based on pre-trained 2D CNN and naive 3D CNN models trained from scratch for schizophrenia classification by integrating 3D structural and diffusion magnetic resonance imaging (MRI) data. We found that the naive 3D CNN models outperformed the pretrained 2D CNN models and the handcrafted feature-based machine learning approach using support vector machine during both cross-validation and testing on an independent dataset. Multimodal neuroimaging-based models accomplished performance superior to models based on a single modality. Furthermore, we identified brain grey matter and white matter regions critical for illness classification at the individual- and group-level which supported the salience network and striatal dysfunction hypotheses in schizophrenia. Our findings underscore the potential of CNN not only to automatically uncover and integrate multimodal 3D brain imaging features for schizophrenia identification, but also to provide relevant neurobiological interpretations which are crucial for developing objective and interpretable imaging-based probes for prognosis and diagnosis in psychiatric disorders.

Characteristics of disrupted topological organization in white matter functional connectome in schizophrenia

BACKGROUND

Neuroimaging characteristics have demonstrated disrupted functional organization in schizophrenia (SZ), involving large-scale networks within grey matter (GM). However, previous studies have ignored the role of white matter (WM) in supporting brain function.

METHODS

Using resting-state functional MRI and graph theoretical approaches, we investigated global topological disruptions of large-scale WM and GM networks in 93 SZ patients and 122 controls. Six global properties [clustering coefficient (Cp), shortest path length (Lp), local efficiency (Eloc), small-worldness (σ), hierarchy (β) and synchronization (S) and three nodal metrics [nodal degree (Knodal), nodal efficiency (Enodal) and nodal betweenness (Bnodal)] were utilized to quantify the topological organization in both WM and GM networks.

RESULTS

At the network level, both WM and GM networks exhibited reductions in Eloc, Cp and S in SZ. The SZ group showed reduced σ and β only for the WM network. Furthermore, the Cp, Eloc and S of the WM network were negatively correlated with negative symptoms in SZ. At the nodal level, the SZ showed nodal disturbances in the corpus callosum, optic radiation, posterior corona radiata and tempo-occipital WM tracts. For GM, the SZ manifested increased nodal centralities in frontoparietal regions and decreased nodal centralities in temporal regions.

CONCLUSIONS

These findings provide the first evidence for abnormal global topological properties in SZ from the perspective of a substantial whole brain, including GM and WM. Nodal centralities enhance GM areas, along with a reduction in adjacent WM, suggest that WM functional alterations may be compensated for adjacent GM impairments in SZ.

Impact of low-frequency rTMS on functional connectivity of the dentate nucleus subdomains in schizophrenia patients with auditory verbal hallucination

Despite low-frequency repetitive transcranial magnetic stimulation (rTMS) is effective in treating schizophrenia patients with auditory verbal hallucinations (AVH), the underlying neural mechanisms of the effect still need to be clarified. Using the cerebellar dentate nucleus (DN) subdomain (dorsal and versal DN) as seeds, the present study investigated resting state functional connectivity (FC) alternations of the seeds with the whole brain and their associations with clinical responses in schizophrenia patients with AVH receiving 1 Hz rTMS treatment. The results showed that the rTMS treatment improved the psychiatric symptoms (e.g., AVH and positive symptoms) and certain neurocognitive functions (e.g., visual learning and verbal learning) in the patients. In addition, the patients at baseline showed increased FC between the DN subdomains and temporal lobes (e.g., right superior temporal gyrus and right middle temporal gyrus) and decreased FC between the DN subdomains and the left superior frontal gyrus, right postcentral gyrus, left supramarginal gyrus and regional cerebellum (e.g., lobule 4-5) compared to controls. Furthermore, these abnormal DN subdomain connectivity patterns did not persist and decreased FC of DN subdomains with cerebellum lobule 4-5 were reversed in patients after rTMS treatment. Linear regression analysis showed that the FC difference values of DN subdomains with the temporal lobes, supramarginal gyrus and cerebellum 4-5 between the patients at baseline and posttreatment were associated with clinical improvements (e.g., AVH and verbal learning) after rTMS treatment. The results suggested that rTMS treatment may modulate the neural circuits of the DN subdomains and hint to underlying neural mechanisms for low-frequency rTMS treating schizophrenia with AVH.

sTREM-1 promotes the phagocytic function of microglia to induce hippocampus damage via the PI3K-AKT signaling pathway

Soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) is a soluble form of TREM-1 released during inflammation. Elevated sTREM-1 levels have been found in neuropsychiatric systemic lupus erythematosus (NPSLE) patients; yet, the exact mechanisms remain unclear. This study investigated the role of sTREM-1 in brain damage and its underlying mechanism. The sTREM-1 recombinant protein (2.5 μg/3 μL) was injected into the lateral ventricle of C57BL/6 female mice. After intracerebroventricular (ICV) injection, the damage in hippocampal neurons increased, and the loss of neuronal synapses and activation of microglia increased compared to the control mice (treated with saline). In vitro. after sTREM-1 stimulation, the apoptosis of BV2 cells decreased, the polarization of BV2 cells shifted to the M1 phenotype, the phagocytic function of BV2 cells significantly improved, while the PI3K-AKT signal pathway was activated in vivo and in vitro. PI3K-AKT pathway inhibitor LY294002 reversed the excessive activation and phagocytosis of microglia caused by sTREM-1 in vivo and in vitro, which in turn improved the hippocampus damage. These results indicated that sTREM-1 activated the microglial by the PI3K-AKT signal pathway, and promoted its excessive phagocytosis of the neuronal synapse, thus inducing hippocampal damage. sTREM-1 might be a potential target for inducing brain lesions.

The correlation between dynamic functional architecture and response to electroconvulsive therapy combined with antipsychotics in schizophrenia

Attempts to determine why some patients respond to electroconvulsive therapy (ECT) are valuable in schizophrenia. Schizophrenia is associated with aberrant dynamic functional architecture, which might impact the efficacy of ECT. We aimed to explore the relationship between pre-treatment temporal variability and ECT acute efficacy. Forty-eight patients with schizophrenia and thirty healthy controls underwent functional magnetic resonance imaging to examine whether patterns of temporary variability of functional architecture differ between high responders (HR) and low responders (LR) at baseline. Compared with LR, HR exhibited significantly abnormal temporal variability in right inferior front gyrus (IFGtriang.R), left temporal pole (TPOsup.L) and right middle temporal gyrus (MTG.R). In the pooled patient group, ∆PANSS was correlated with the temporal variability of these regions. Patients with schizophrenia with a distinct dynamic functional architecture appear to reveal differential response to ECT. Our findings provide not only an understanding of the neural functional architecture patterns that are found in schizophrenia but also the possibility of using these measures as moderators for ECT selection.

Heritable anisotropy associated with cognitive impairments among patients with schizophrenia and their non-psychotic relatives in multiplex families

BACKGROUND

To test the functional implications of impaired white matter (WM) connectivity among patients with schizophrenia and their relatives, we examined the heritability of fractional anisotropy (FA) measured on diffusion tensor imaging data acquired in Pittsburgh and Philadelphia, and its association with cognitive performance in a unique sample of 175 multigenerational non-psychotic relatives of 23 multiplex schizophrenia families and 240 unrelated controls (total = 438).

METHODS

We examined polygenic inheritance (h2r) of FA in 24 WM tracts bilaterally, and also pleiotropy to test whether heritability of FA in multiple WM tracts is secondary to genetic correlation among tracts using the Sequential Oligogenic Linkage Analysis Routines. Partial correlation tests examined the correlation of FA with performance on eight cognitive domains on the Penn Computerized Neurocognitive Battery, controlling for age, sex, site and mother's education, followed by multiple comparison corrections.

RESULTS

Significant total additive genetic heritability of FA was observed in all three-categories of WM tracts (association, commissural and projection fibers), in total 33/48 tracts. There were significant genetic correlations in 40% of tracts. Diagnostic group main effects were observed only in tracts with significantly heritable FA. Correlation of FA with neurocognitive impairments was observed mainly in heritable tracts.

CONCLUSIONS

Our data show significant heritability of all three-types of tracts among relatives of schizophrenia. Significant heritability of FA of multiple tracts was not entirely due to genetic correlations among the tracts. Diagnostic group main effect and correlation with neurocognitive performance were mainly restricted to tracts with heritable FA suggesting shared genetic effects on these traits.

Different patterns of white matter microstructural alterations between psychotic and non-psychotic bipolar disorder

This study aimed to investigate alterations in white matter (WM) microstructure in patients with psychotic and non-psychotic bipolar disorder (PBD and NPBD, respectively). We used 3T-magnetic resonance imaging to examine 29 PBD, 23 NPBD, and 65 healthy control (HC) subjects. Using tract-based spatial statistics for diffusion tensor imaging data, we compared fractional anisotropy (FA) and mean diffusion (MD) pairwise among the PBD, NPBD, and HC groups. We found several WM areas of decreased FA or increased MD in the PBD and NPBD groups compared to HC. PBD showed widespread FA decreases in the corpus callosum as well as the bilateral internal capsule and fornix. However, NPBD showed local FA decreases in a part of the corpus callosum body as well as in limited regions within the left cerebral hemisphere, including the anterior and posterior corona radiata and the cingulum. In addition, both PBD and NPBD shared widespread MD increases across the posterior corona radiata, cingulum, and sagittal stratum. These findings suggest that widespread WM microstructural alterations might be a common neuroanatomical characteristic of bipolar disorder, regardless of being psychotic or non-psychotic. Particularly, PBD might involve extensive inter-and intra-hemispheric WM connectivity disruptions.

Structural connectivity associated with familial risk for mental illness: A meta‐analysis of diffusion tensor imaging studies in relatives of patients with severe mental disorders

Schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD) are heritable conditions with overlapping genetic liability. Transdiagnostic and disorder‐specific brain changes associated with familial risk for developing these disorders remain poorly understood. We carried out a meta‐analysis of diffusion tensor imaging (DTI) studies to investigate white matter microstructure abnormalities in relatives that might correspond to shared and discrete biomarkers of familial risk for psychotic or mood disorders. A systematic search of PubMed and Embase was performed to identify DTI studies in relatives of SCZ, BD, and MDD patients. Seed‐based d Mapping software was used to investigate global differences in fractional anisotropy (FA) between overall and disorder‐specific relatives and healthy controls (HC). Our search identified 25 studies that met full inclusion criteria. A total of 1,144 relatives and 1,238 HC were included in the meta‐analysis. The overall relatives exhibited decreased FA in the genu and splenium of corpus callosum (CC) compared with HC. This finding was found highly replicable in jack‐knife analysis and subgroup analyses. In disorder‐specific analysis, compared to HC, relatives of SCZ patients exhibited the same changes while those of BD showed reduced FA in the left inferior longitudinal fasciculus (ILF). The present study showed decreased FA in the genu and splenium of CC in relatives of SCZ, BD, and MDD patients, which might represent a shared familial vulnerability marker of severe mental illness. The white matter abnormalities in the left ILF might represent a specific familial risk for bipolar disorder.

Cortical thickness abnormalities in patients with bipolar disorder: A systematic review and meta-analysis

BACKGROUND

An increasing number of neuroimaging studies report alterations of cortical thickness (CT) related to the neuropathology of bipolar disorder (BD). We provide here a whole-brain vertex-wise meta-analysis, which may help improve the spatial precision of these identifications.

METHODS

A comprehensive meta-analysis was performed to investigate the differences in CT between patients with BD and healthy controls (HCs) by using a newly developed mask for CT analysis in seed-based d mapping (SDM) meta-analytic software. We used meta-regression to explore the effects of demographics and clinical characteristics on CT. This meta-review was conducted in accordance with PRISMA guideline.

RESULTS

We identified 21 studies meeting criteria for the systematic review, of which 11 were eligible for meta-analysis. The meta-analysis comprising 649 BD patients and 818 HCs showed significant cortical thinning in the left insula extending to left Rolandic operculum and Heschl gyrus, the orbital part of left inferior frontal gyrus (IFG), the medial part of left superior frontal gyrus (SFG) as well as bilateral anterior cingulate cortex (ACC) in BD. In meta-regression analyses, mean patient age was negatively correlated with reduced CT in the left insula.

LIMITATIONS

All enrolled studies were cross-sectional; we could not explore the potential effects of medication and mood states due to the limited data.

CONCLUSIONS

Our results suggest that BD patients have significantly thinner frontoinsular cortex than HCs, and the results may be helpful in revealing specific neuroimaging biomarkers of BD patients.

Application of Mass Multivariate Analysis on Neuroimaging Data Sets for Precision Diagnostics of Depression

We used the Mass Multivariate Method on structural, resting-state, and task-related fMRI data from two groups of patients with schizophrenia and depression in order to define several regions of significant relevance to the differential diagnosis of those conditions. The regions included the left planum polare (PP), the left opercular part of the inferior frontal gyrus (OpIFG), the medial orbital gyrus (MOrG), the posterior insula (PIns), and the parahippocampal gyrus (PHG). This study delivered evidence that a multimodal neuroimaging approach can potentially enhance the validity of psychiatric diagnoses. Structural, resting-state, or task-related functional MRI modalities cannot provide independent biomarkers. Further studies need to consider and implement a model of incremental validity combining clinical measures with different neuroimaging modalities to discriminate depressive disorders from schizophrenia. Biological signatures of disease on the level of neuroimaging are more likely to underpin broader nosological entities in psychiatry.

Cognitive Implications of Correlated Structural Network Changes in Schizophrenia

Background

Schizophrenia is a brain disorder characterized by diffuse, diverse, and wide-spread changes in gray matter volume (GM) and white matter structure (fractional anisotropy, FA), as well as cognitive impairments that greatly impact an individual’s quality of life. While the relationship of each of these image modalities and their links to schizophrenia status and cognitive impairment has been investigated separately, a multimodal fusion via parallel independent component analysis (pICA) affords the opportunity to explore the relationships between the changes in GM and FA, and the implications these network changes have on cognitive performance.

Methods

Images from 73 subjects with schizophrenia (SZ) and 82 healthy controls (HC) were drawn from an existing dataset. We investigated 12 components from each feature (FA and GM). Loading coefficients from the images were used to identify pairs of features that were significantly correlated and showed significant group differences between HC and SZ. MANCOVA analysis uncovered the relationships the identified spatial maps had with age, gender, and a global cognitive performance score.

Results

Three component pairs showed significant group differences (HC > SZ) in both gray and white matter measurements. Two of the component pairs identified networks of gray matter that drove significant relationships with cognition (HC > SZ) after accounting for age and gender. The gray and white matter structural networks identified in these three component pairs pull broadly from many regions, including the right and left thalamus, lateral occipital cortex, multiple regions of the middle temporal gyrus, precuneus cortex, postcentral gyrus, cingulate gyrus/cingulum, lingual gyrus, and brain stem.

Conclusion

The results of this multimodal analysis adds to our understanding of how the relationship between GM, FA, and cognition differs between HC and SZ by highlighting the correlated intermodal covariance of these structural networks and their differential relationships with cognitive performance. Previous unimodal research has found similar areas of GM and FA differences between these groups, and the cognitive deficits associated with SZ have been well documented. This study allowed us to evaluate the intercorrelated covariance of these structural networks and how these networks are involved the differences in cognitive performance between HC and SZ.

Meta-analysis of structural and functional brain abnormalities in schizophrenia with persistent negative symptoms using activation likelihood estimation

BACKGROUND

Persistent negative symptoms (PNS) include both primary and secondary negative symptoms that persist after adequate treatment, and represent an unmet therapeutic need. Published magnetic resonance imaging (MRI) evidence of structural and resting-state functional brain abnormalities in schizophrenia with PNS has been inconsistent. Thus, the purpose of this meta-analysis is to identify abnormalities in structural and functional brain regions in patients with PNS compared to healthy controls.

METHODS

We systematically searched PubMed, Web of Science, and Embase for structural and functional imaging studies based on five research methods, including voxel-based morphometry (VBM), diffusion tensor imaging (DTI), functional connectivity (FC), the amplitude of low-frequency fluctuation or fractional amplitude of low-frequency fluctuation (ALFF/fALFF), and regional homogeneity (ReHo). Afterward, we conducted a coordinate-based meta-analysis by using the activation likelihood estimation algorithm.

RESULTS

Twenty-five structural MRI studies and thirty-two functional MRI studies were included in the meta-analyses. Our analysis revealed the presence of structural alterations in patients with PNS in some brain regions including the bilateral insula, medial frontal gyrus, anterior cingulate gyrus, left amygdala, superior temporal gyrus, inferior frontal gyrus, cingulate gyrus and middle temporal gyrus, as well as functional differences in some brain regions including the bilateral precuneus, thalamus, left lentiform nucleus, posterior cingulate gyrus, medial frontal gyrus, and superior frontal gyrus.

CONCLUSION

Our study suggests that structural brain abnormalities are consistently located in the prefrontal, temporal, limbic and subcortical regions, and functional alterations are concentrated in the thalamo-cortical circuits and the default mode network (DMN). This study provides new insights for targeted treatment and intervention to delay further progression of negative symptoms.

SYSTEMATIC REVIEW REGISTRATION

[https://www.crd.york.ac.uk/prospero/], identifier [CRD42022338669].

A meta-analysis of deep brain structural shape and asymmetry abnormalities in 2,833 individuals with schizophrenia compared with 3,929 healthy volunteers via the ENIGMA Consortium

Schizophrenia is associated with widespread alterations in subcortical brain structure. While analytic methods have enabled more detailed morphometric characterization, findings are often equivocal. In this meta-analysis, we employed the harmonized ENIGMA shape analysis protocols to collaboratively investigate subcortical brain structure shape differences between individuals with schizophrenia and healthy control participants. The study analyzed data from 2,833 individuals with schizophrenia and 3,929 healthy control participants contributed by 21 worldwide research groups participating in the ENIGMA Schizophrenia Working Group. Harmonized shape analysis protocols were applied to each site's data independently for bilateral hippocampus, amygdala, caudate, accumbens, putamen, pallidum, and thalamus obtained from T1-weighted structural MRI scans. Mass univariate meta-analyses revealed more-concave-than-convex shape differences in the hippocampus, amygdala, accumbens, and thalamus in individuals with schizophrenia compared with control participants, more-convex-than-concave shape differences in the putamen and pallidum, and both concave and convex shape differences in the caudate. Patterns of exaggerated asymmetry were observed across the hippocampus, amygdala, and thalamus in individuals with schizophrenia compared to control participants, while diminished asymmetry encompassed ventral striatum and ventral and dorsal thalamus. Our analyses also revealed that higher chlorpromazine dose equivalents and increased positive symptom levels were associated with patterns of contiguous convex shape differences across multiple subcortical structures. Findings from our shape meta-analysis suggest that common neurobiological mechanisms may contribute to gray matter reduction across multiple subcortical regions, thus enhancing our understanding of the nature of network disorganization in schizophrenia.

Grey matter connectome abnormalities and age-related effects in antipsychotic-naive schizophrenia

Background

Convergent evidence is increasing to indicate progressive brain abnormalities in schizophrenia. Knowing the brain network features over the illness course in schizophrenia, independent of effects of antipsychotic medications, would extend our sight on this question.

Methods

We recruited 237 antipsychotic-naive patients with schizophrenia range from 16 to 73 years old, and 254 healthy controls. High-resolution T1 weighted images were obtained with a 3.0T MR scanner. Grey matter networks were constructed individually based on the similarities of regional grey matter measurements. Network metrics were compared between patient groups and healthy controls, and regression analyses with age were conducted to determine potential differential rate of age-related changes between them.

Findings

Nodal centrality abnormalities were observed in patients with untreated schizophrenia, particularly in the central executive, default mode and salience networks. Accelerated age-related declines and illness duration-related declines were observed in global assortativity, and in nodal metrics of left superior temporal pole in schizophrenia patients. Although no significant intergroup differences in age-related regression were observed, the pattern of network metric alternation of left thalamus indicated higher nodal properties in early course patients, which decreased in long-term ill patients.

Interpretations

Global and nodal alterations in the grey matter connectome related to age and duration of illness in antipsychotic-naive patients, indicating potentially progressive network organizations mainly involving temporal regions and thalamus in schizophrenia independent from medication effects.

Funding

The National Natural Science Foundation of China, Sichuan Science and Technology Program, the Fundamental Research Funds for the Central Universities, Post-Doctor Research Project, West China Hospital, Sichuan University , the Science and Technology Project of the Health Planning Committee of Sichuan, Postdoctoral Interdisciplinary Research Project of Sichuan University and 1.3.5 Project for Disciplines of Excellence, West China Hospital, Sichuan University.

New concepts in the development of schizophrenia, autism spectrum disorders, and degenerative brain diseases based on chronic inflammation: A working hypothesis from continued advances in neuroscience research

This paper was written prompted by a poignant film about adolescent girl with schizophrenia who babysits for a younger girl in an isolated cabin. Schizophrenia is an illness that both authors are fascinated with and that they continue to study and investigate. There is now compelling evidence that schizophrenia is a very complex syndrome that involves numerous neural pathways in the brain, far more than just dopaminergic and serotonergic systems. One of the more popular theories in recent literature is that it represents a hypo glutaminergic deficiency of certain pathways, including thalamic ones. After much review of research and study in this area, we have concluded that most such theories contain a number of shortcomings. Most are based on clinical responses to certain drugs, particularly antipsychotic drugs affecting the dopaminergic neurotransmitters; thus, assuming dopamine release was the central cause of the psychotic symptoms of schizophrenia. The theory was limited in that dopamine excess could only explain the positive symptoms of the disorder. Antipsychotic medications have minimal effectiveness for the negative and cognitive symptoms associated with schizophrenia. It has been estimated that 20–30% of patients show either a partial or no response to antipsychotic medications. In addition, the dopamine hypothesis does not explain the neuroanatomic findings in schizophrenia.

Searching for Imaging Biomarkers of Psychotic Dysconnectivity

BACKGROUND

Progress in precision psychiatry is predicated on identifying reliable individual-level diagnostic biomarkers. For psychosis, measures of structural and functional connectivity could be promising biomarkers given consistent reports of dysconnectivity across psychotic disorders using magnetic resonance imaging.

METHODS

We leveraged data from four independent cohorts of patients with psychosis and control subjects with observations from approximately 800 individuals. We used group-level analyses and two supervised machine learning algorithms (support vector machines and ridge regression) to test within-, between-, and across-sample classification performance of white matter and resting-state connectivity metrics.

RESULTS

Although we replicated group-level differences in brain connectivity, individual-level classification was suboptimal. Classification performance within samples was variable across folds (highest area under the curve [AUC] range = 0.30) and across datasets (average support vector machine AUC range = 0.50; average ridge regression AUC range = 0.18). Classification performance between samples was similarly variable or resulted in AUC values of approximately 0.65, indicating a lack of model generalizability. Furthermore, collapsing across samples (resting-state functional magnetic resonance imaging, N = 888; diffusion tensor imaging, N = 860) did not improve model performance (maximal AUC = 0.67). Ridge regression models generally outperformed support vector machine models, although classification performance was still suboptimal in terms of clinical relevance. Adjusting for demographic covariates did not greatly affect results.

CONCLUSIONS

Connectivity measures were not suitable as diagnostic biomarkers for psychosis as assessed in this study. Our results do not negate that other approaches may be more successful, although it is clear that a systematic approach to individual-level classification with large independent validation samples is necessary to properly vet neuroimaging features as diagnostic biomarkers.

Spatially Covarying Patterns of Gray Matter Volume and Concentration Highlight Distinct Regions in Schizophrenia

Introduction: Individuals with schizophrenia have consistent gray matter reduction throughout the cortex when compared to healthy individuals. However, the reduction patterns vary based on the quantity (concentration or volume) utilized by study. The objective of this study was to identify commonalities between gray matter concentration and gray matter volume effects in schizophrenia.

Methods: We performed both univariate and multivariate analyses of case/control effects on 145 gray matter images from 66 participants with schizophrenia and 79 healthy controls, and processed to compare the concentration and volume estimates.

Results: Diagnosis effects in the univariate analysis showed similar areas of volume and concentration reductions in the insula, occipitotemporal gyrus, temporopolar area, and fusiform gyrus. In the multivariate analysis, healthy controls had greater gray matter volume and concentration additionally in the superior temporal gyrus, prefrontal cortex, cerebellum, calcarine, and thalamus. In the univariate analyses there was moderate overlap between gray matter concentration and volume across the entire cortex (r = 0.56, p = 0.02). The multivariate analyses revealed only low overlap across most brain patterns, with the largest correlation (r = 0.37) found in the cerebellum and vermis.

Conclusions: Individuals with schizophrenia showed reduced gray matter volume and concentration in previously identified areas of the prefrontal cortex, cerebellum, and thalamus. However, there were only moderate correlations across the cortex when examining the different gray matter quantities. Although these two quantities are related, concentration and volume do not show identical results, and therefore, should not be used interchangeably in the literature.

Global fractional anisotropy predicts transition to psychosis after 12 months in individuals at ultra-high risk for psychosis

OBJECTIVE

Psychosis spectrum disorders are associated with cerebral changes, but the prognostic value and clinical utility of these findings are unclear. Here, we applied a multivariate statistical model to examine the predictive accuracy of global white matter fractional anisotropy (FA) for transition to psychosis in individuals at ultra-high risk for psychosis (UHR).

METHODS

110 UHR individuals underwent 3 Tesla diffusion-weighted imaging and clinical assessments at baseline, and after 6 and 12 months. Using logistic regression, we examined the reliability of global FA at baseline as a predictor for psychosis transition after 12 months. We tested the predictive accuracy, sensitivity and specificity of global FA in a multivariate prediction model accounting for potential confounders to FA (head motion in scanner, age, gender, antipsychotic medication, parental socioeconomic status and activity level). In secondary analyses, we tested FA as a predictor of clinical symptoms and functional level using multivariate linear regression.

RESULTS

Ten UHR individuals had transitioned to psychosis after 12 months (9%). The model reliably predicted transition at 12 months (χ²  = 17.595, p = 0.040), accounted for 15-33% of the variance in transition outcome with a sensitivity of 0.70, a specificity of 0.88 and AUC of 0.87. Global FA predicted level of UHR symptoms (R²  = 0.055, F = 6.084, p = 0.016) and functional level (R²  = 0.040, F = 4.57, p = 0.036) at 6 months, but not at 12 months.

CONCLUSION

Global FA provided prognostic information on clinical outcome and symptom course of UHR individuals. Our findings suggest that the application of prediction models including neuroimaging data can inform clinical management on risk for psychosis transition.

Differential involvement of hippocampal subfields in Niemann-Pick type C disease: a case-control study

Hippocampal brain regions are strongly implicated in Niemann Pick type C disease (NPC), but little is known regarding distinct subregions of the hippocampal complex and whether these are equally or differentially affected. To address this gap, we compared volumes of five hippocampal subfields between NPC and healthy individuals using MRI. To this end, 9 adult-onset NPC cases and 9 age- and gender-matched controls underwent a 3 T T1-weighted MRI scan. Gray matter volumes of the cornu ammonis (CA1, CA2 and CA3), dentate gyrus (DG), subiculum, entorhinal cortex and hippocampal-amygdalar transition area were calculated by integrating MRI-based image intensities with microscopically defined cytoarchitectonic probabilities. Compared to healthy controls, NPC patients showed smaller volumes of the CA1-3 and DG regions bilaterally, with the greatest difference localized to the left DG (Cohen's d = 1.993, p = 0.008). No significant associations were shown between hippocampal subfield volumes and key clinical features of NPC, including disease duration, symptom severity and psychosis. The pattern of hippocampal subregional atrophy in NPC differs from those seen in other dementias, which may indicate unique cytoarchitectural vulnerabilities in this earlier-onset disorder. Future MRI studies of hippocampal subfields may clarify its potential as a biomarker of neurodegeneration in NPC.

Is treatment-resistant schizophrenia associated with distinct neurobiological callosal connectivity abnormalities?

BACKGROUND

Resistance to antipsychotic treatment affects up to 30% of patients with schizophrenia. Although the time course of development of treatment-resistant schizophrenia (TRS) varies from patient to patient, the reasons for these variations remain unknown. Growing evidence suggests brain dysconnectivity as a significant feature of schizophrenia. In this study, we compared fractional anisotropy (FA) of brain white matter between TRS and non-treatment-resistant schizophrenia (non-TRS) patients. Our central hypothesis was that TRS is associated with reduced FA values.

METHODS

TRS was defined as the persistence of moderate to severe symptoms after adequate treatment with at least two antipsychotics from different classes. Diffusion-tensor brain MRI obtained images from 34 TRS participants and 51 non-TRS. Whole-brain analysis of FA and axial, radial, and mean diffusivity were performed using Tract-Based Spatial Statistics (TBSS) and FMRIB's Software Library (FSL), yielding a contrast between TRS and non-TRS patients, corrected for multiple comparisons using family-wise error (FWE) < 0.05.

RESULTS

We found a significant reduction in FA in the splenium of corpus callosum (CC) in TRS when compared to non-TRS. The antipsychotic dose did not relate to the splenium CC.

CONCLUSION

Our results suggest that the focal abnormality of CC may be a potential biomarker of TRS.

Function-structure coupling: White matter functional magnetic resonance imaging hyper-activation associates with structural integrity reductions in schizophrenia

White matter (WM) microstructure deficit may be an underlying factor in the brain dysconnectivity hypothesis of schizophrenia using diffusion tensor imaging (DTI). However, WM dysfunction is unclear in schizophrenia. This study aimed to investigate the association between structural deficits and functional disturbances in major WM tracts in schizophrenia. Using functional magnetic resonance imaging (fMRI) and DTI, we developed the skeleton-based WM functional analysis, which could achieve voxel-wise function-structure coupling by projecting the fMRI signals onto a skeleton in WM. We measured the fractional anisotropy (FA) and WM low-frequency oscillation (LFO) and their couplings in 93 schizophrenia patients and 122 healthy controls (HCs). An independent open database (62 schizophrenia patients and 71 HCs) was used to test the reproducibility. Finally, associations between WM LFO and five behaviour assessment categories (cognition, emotion, motor, personality and sensory) were examined. This study revealed a reversed pattern of structure and function in frontotemporal tracts, as follows. (a) WM hyper-LFO was associated with reduced FA in schizophrenia. (b) The function-structure association was positive in HCs but negative in schizophrenia patients. Furthermore, function-structure dissociation was exacerbated by long illness duration and severe negative symptoms. (c) WM activations were significantly related to cognition and emotion. This study indicated function-structure dys-coupling, with higher LFO and reduced structural integration in frontotemporal WM, which may reflect a potential mechanism in WM neuropathologic processing of schizophrenia.

Disrupted Dorsal Mid-Insula Activation During Interoception Across Psychiatric Disorders

OBJECTIVE

Maintenance of bodily homeostasis relies on interoceptive mechanisms in the brain to predict and regulate bodily state. While altered neural activation during interoception in specific psychiatric disorders has been reported in many studies, it is unclear whether a common neural locus underpins transdiagnostic interoceptive differences.

METHODS

The authors conducted a meta-analysis of neuroimaging studies comparing patients with psychiatric disorders with healthy control subjects to identify brain regions exhibiting convergent disrupted activation during interoception. Bibliographic, neuroimaging, and preprint databases through May 2020 were searched. A total of 306 foci from 33 studies were extracted, which included 610 control subjects and 626 patients with schizophrenia, bipolar or unipolar depression, posttraumatic stress disorder, anxiety, eating disorders, or substance use disorders. Data were pooled using a random-effects model implemented by the activation likelihood estimation algorithm. The preregistered primary outcome was the neuroanatomical location of the convergence of peak voxel coordinates.

RESULTS

Convergent disrupted activation specific to the left dorsal mid-insula was found (Z=4.47, peak coordinates: -36, -2, 14; volume: 928 mm3). Studies directly contributing to the cluster included patients with bipolar disorder, anxiety, major depression, anorexia, and schizophrenia, assessed with task probes including pain, hunger, and interoceptive attention. A series of conjunction analyses against extant meta-analytic data sets revealed that this mid-insula cluster was anatomically distinct from brain regions involved in affective processing and from regions altered by psychological or pharmacological interventions for affective disorders.

CONCLUSIONS

These results reveal transdiagnostic, domain-general differences in interoceptive processing in the left dorsal mid-insula. Disrupted mid-insular activation may represent a neural marker of psychopathology and a putative target for novel interventions.

Differential Effects of a Left Frontal Glioma on the Cortical Thickness and Complexity of Both Hemispheres

Glioma is a type of brain tumor that infiltrates and compresses the brain as it grows. Focal gliomas affect functional connectivity both in the local region of the lesion and the global network of the brain. Any anatomical changes associated with a glioma should thus be clarified. We examined the cortical structures of 15 patients with a glioma in the left lateral frontal cortex and compared them with those of 15 healthy controls by surface-based morphometry. Two regional parameters were measured with 3D-MRI: the cortical thickness (CT) and cortical fractal dimension (FD). The FD serves as an index of the topological complexity of a local cortical surface. Our comparative analyses of these parameters revealed that the left frontal gliomas had global effects on the cortical structures of both hemispheres. The structural changes in the right hemisphere were mainly characterized by a decrease in CT and mild concomitant decrease in FD, whereas those in the peripheral regions of the glioma (left hemisphere) were mainly characterized by a decrease in FD with relative preservation of CT. These differences were found irrespective of tumor volume, location, or grade. These results elucidate the structural effects of gliomas, which extend to the distant contralateral regions.

Strucutural brain imaging at the onset of schizophrenia:What have we learned and what have we missed

Over the past 50 years, the application of structural neuroimaging techniques to schizophrenia research has added relevant information about the pathophysiology of the disorder. Several lines of investigation gave strong evidence that schizophrenia is associated with multiple subtle brain abnormalities that involve both cerebral grey and white matter volumes and structure. The time of onset and longitudinal course of brain morphological abnormalities support the notion that brain pathology of schizophrenia has a neurodevelopmental component and a progressive course, although several confounders of brain changes should be carefully taken into account. Brain anomalies detected before and close to the onset of schizophrenia are likely to be unrelated to confounders of brain changes such as antipsychotic drug treatment, duration of illness or illicit substance abuse, i.e. they related to the pathological process of the disorder per se. Nonetheless, clinically useful diagnostic or prognostic biomarkers have not derived from neuroimaging studies and this is likely related to the neurobiological heterogeneity of the disorder. Thus, there is the compelling need to set new methodological standards for developing innovative hypothesis-driven studies to overcome what we have missed to date in neuroimaging research in schizophrenia.

Motor abnormalities and basal ganglia in first-episode psychosis (FEP)

BACKGROUND

Motor abnormalities (MAs) are the primary manifestations of schizophrenia. However, the extent to which MAs are related to alterations of subcortical structures remains understudied.

METHODS

We aimed to investigate the associations of MAs and basal ganglia abnormalities in first-episode psychosis (FEP) and healthy controls. Magnetic resonance imaging was performed on 48 right-handed FEP and 23 age-, gender-, handedness-, and educational attainment-matched controls, to obtain basal ganglia shape analysis, diffusion tensor imaging techniques (fractional anisotropy and mean diffusivity), and relaxometry (R2*) to estimate iron load. A comprehensive motor battery was applied including the assessment of parkinsonism, catatonic signs, and neurological soft signs (NSS). A fully automated model-based segmentation algorithm on 1.5T MRI anatomical images and accurate corregistration of diffusion and T2* volumes and R2* was used.

RESULTS

FEP patients showed significant local atrophic changes in left globus pallidus nucleus regarding controls. Hypertrophic changes in left-side caudate were associated with higher scores in sensory integration, and in right accumbens with tremor subscale. FEP patients showed lower fractional anisotropy measures than controls but no significant differences regarding mean diffusivity and iron load of basal ganglia. However, iron load in left basal ganglia and right accumbens correlated significantly with higher extrapyramidal and motor coordination signs in FEP patients.

CONCLUSIONS

Taken together, iron load in left basal ganglia may have a role in the emergence of extrapyramidal signs and NSS of FEP patients and in consequence in the pathophysiology of psychosis.

Machine Learning of Schizophrenia Detection with Structural and Functional Neuroimaging

Schizophrenia (SZ) is a severe psychiatric illness, and it affects around 1% of the general population; however, its reliable diagnosis is challenging. Functional MRI (fMRI) and structural MRI (sMRI) are useful techniques for investigating the functional and structural abnormalities of the human brain, and a growing number of studies have reported that multimodal brain data can improve diagnostic accuracy. Machine learning (ML) is widely used in the diagnosis of neuroscience and neuropsychiatry diseases, and it can obtain high accuracy. However, the conventional ML which concatenated the features into a longer feature vector could not be sufficiently effective to combine different features from different modalities. There are considerable controversies over the use of global signal regression (GSR), and few studies have explored the role of GSR in ML in diagnosing neurological diseases. The current study utilized fMRI and sMRI data to implement a new method named multimodal imaging and multilevel characterization with multiclassifier (M3) to classify SZs and healthy controls (HCs) and investigate the influence of GSR in SZ classification. We found that when we used Brainnetome 246 atlas and without performed GSR, our method obtained a classification accuracy of 83.49%, with a sensitivity of 68.69%, a specificity of 93.75%, and an AUC of 0.8491, respectively. We also got great classification performances with different processing methods (with/without GSR and different brain parcellation schemes). We found that the accuracy and specificity of the models without GSR were higher than that of the models with GSR. Our findings indicate that the M3 method is an effective tool to distinguish SZs from HCs, and it can identify discriminative regions to detect SZ to explore the neural mechanisms underlying SZ. The global signal may contain important neuronal information; it can improve the accuracy and specificity of SZ detection.

Reduced GABA/glutamate in the thalamus of individuals at clinical high risk for psychosis

Youth at clinical high risk (CHR) are a unique population enriched for precursors of major psychiatric disorders, especially schizophrenia (SCZ). Recent neuroimaging findings point to abnormalities in the thalamus of patients with SCZ, including chronic and early course patients, as well as in CHR individuals relative to healthy comparison groups, thus suggesting that thalamic dysfunctions are present even before illness onset. Furthermore, modeling data indicate that alteration between excitatory and inhibitory control, as reflected by alteration in GABAergic and glutamatergic balance (i.e., GABA/Glu), may underlie thalamic deficits linked to the risk and development of psychosis. There is, however, a lack of in vivo evidence of GABA/Glu thalamic abnormalities in the CHR state. Magnetic resonance spectroscopic imaging (MRSI) 7 Tesla (7 T) provides enhanced resolution to quantify GABA and Glu levels in the thalamus of CHR individuals. In this study, we performed 7 T MRSI in 15 CHR and 20 healthy control (HC) participants. We found that GABA/Glu was significantly reduced in the right medial anterior and right medial posterior thalamus of CHR relative to HC groups. The GABA/Glu reduction was negatively correlated with general symptoms in the right medial anterior thalamus, as well as with disorganization symptoms in the right medial posterior thalamus. Altogether, these findings indicate that GABA/Glu abnormalities are present in the thalamus before the onset of full-blown psychosis and are associated with symptom severity, thus providing putative molecular and neuronal targets for early interventions in youth at CHR.

Psychopathological Syndromes Across Affective and Psychotic Disorders Correlate With Gray Matter Volumes

INTRODUCTION

More than a century of research on the neurobiological underpinnings of major psychiatric disorders (major depressive disorder [MDD], bipolar disorder [BD], schizophrenia [SZ], and schizoaffective disorder [SZA]) has been unable to identify diagnostic markers. An alternative approach is to study dimensional psychopathological syndromes that cut across categorical diagnoses. The aim of the current study was to identify gray matter volume (GMV) correlates of transdiagnostic symptom dimensions.

METHODS

We tested the association of 5 psychopathological factors with GMV using multiple regression models in a sample of N = 1069 patients meeting Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria for MDD (n = 818), BD (n = 132), and SZ/SZA (n = 119). T1-weighted brain images were acquired with 3-Tesla magnetic resonance imaging and preprocessed with CAT12. Interactions analyses (diagnosis × psychopathological factor) were performed to test whether local GMV associations were driven by DSM-IV diagnosis. We further tested syndrome specific regions of interest (ROIs).

RESULTS

Whole brain analysis showed a significant negative association of the positive formal thought disorder factor with GMV in the right middle frontal gyrus, the paranoid-hallucinatory syndrome in the right fusiform, and the left middle frontal gyri. ROI analyses further showed additional negative associations, including the negative syndrome with bilateral frontal opercula, positive formal thought disorder with the left amygdala-hippocampus complex, and the paranoid-hallucinatory syndrome with the left angular gyrus. None of the GMV associations interacted with DSM-IV diagnosis.

CONCLUSIONS

We found associations between psychopathological syndromes and regional GMV independent of diagnosis. Our findings open a new avenue for neurobiological research across disorders, using syndrome-based approaches rather than categorical diagnoses.