Multimodal MRI assessment for first episode psychosis: A major change in the thalamus and an efficient stratification of a subgroup

A whole-brain neuromark resting-state fMRI analysis of first-episode and early psychosis: Evidence of aberrant cortical-subcortical-cerebellar functional circuitry

Psychosis (including symptoms of delusions, hallucinations, and disorganized conduct/speech) is a main feature of schizophrenia and is frequently present in other major psychiatric illnesses. Studies in individuals with first-episode (FEP) and early psychosis (EP) have the potential to interpret aberrant connectivity associated with psychosis during a period with minimal influence from medication and other confounds. The current study uses a data-driven whole-brain approach to examine patterns of aberrant functional network connectivity (FNC) in a multi-site dataset comprising resting-state functional magnetic resonance images (rs-fMRI) from 117 individuals with FEP or EP and 130 individuals without a psychiatric disorder, as controls. Accounting for age, sex, race, head motion, and multiple imaging sites, differences in FNC were identified between psychosis and control participants in cortical (namely the inferior frontal gyrus, superior medial frontal gyrus, postcentral gyrus, supplementary motor area, posterior cingulate cortex, and superior and middle temporal gyri), subcortical (the caudate, thalamus, subthalamus, and hippocampus), and cerebellar regions. The prominent pattern of reduced cerebellar connectivity in psychosis is especially noteworthy, as most studies focus on cortical and subcortical regions, neglecting the cerebellum. The dysconnectivity reported here may indicate disruptions in cortical-subcortical-cerebellar circuitry involved in rudimentary cognitive functions which may serve as reliable correlates of psychosis.

Cortical Network Disruption Is Minimal in Early Stages of Psychosis

Background and Hypothesis

Schizophrenia is associated with white matter disruption and topological reorganization of cortical connectivity but the trajectory of these changes, from the first psychotic episode to established illness, is poorly understood. Current studies in first-episode psychosis (FEP) patients using diffusion magnetic resonance imaging (dMRI) suggest such disruption may be detectable at the onset of psychosis, but specific results vary widely, and few reports have contextualized their findings with direct comparison to young adults with established illness.

Study Design

Diffusion and T1-weighted 7T MR scans were obtained from N = 112 individuals (58 with untreated FEP, 17 with established schizophrenia, 37 healthy controls) recruited from London, Ontario. Voxel- and network-based analyses were used to detect changes in diffusion microstructural parameters. Graph theory metrics were used to probe changes in the cortical network hierarchy and to assess the vulnerability of hub regions to disruption. The analysis was replicated with N = 111 (57 patients, 54 controls) from the Human Connectome Project-Early Psychosis (HCP-EP) dataset.

Study Results

Widespread microstructural changes were found in people with established illness, but changes in FEP patients were minimal. Unlike the established illness group, no appreciable topological changes in the cortical network were observed in FEP patients. These results were replicated in the early psychosis patients of the HCP-EP datasets, which were indistinguishable from controls in most metrics.

Conclusions

The white matter structural changes observed in established schizophrenia are not a prominent feature in the early stages of this illness.

Neuroimaging alterations and relapse in early-stage psychosis

BACKGROUND

Recent reports have indicated that symptom exacerbation after a period of improvement, referred to as relapse, in early-stage psychosis could result in brain changes and poor disease outcomes. We hypothesized that substantial neuroimaging alterations may exist among patients who experience relapse in early-stage psychosis.

METHODS

We studied patients with psychosis within 2 years after the first psychotic event and healthy controls. We divided patients into 2 groups, namely those who did not experience relapse between disease onset and the magnetic resonance imaging (MRI) scan (no-relapse group) and those who did experience relapse between these 2 timings (relapse group). We analyzed 3003 functional connectivity estimates between 78 regions of interest (ROIs) derived from resting-state functional MRI data by adjusting for demographic and clinical confounding factors.

RESULTS

We studied 85 patients, incuding 54 in the relapse group and 31 in the no-relapse group, along with 94 healthy controls. We observed significant differences in 47 functional connectivity estimates between the relapse and control groups after multiple comparison corrections, whereas no differences were found between the no-relapse and control groups. Most of these pathological signatures (64%) involved the thalamus. The Jonckheere-Terpstra test indicated that all 47 functional connectivity changes had a significant cross-group progression from controls to patients in the no-relapse group to patients in the relapse group.

LIMITATIONS

Longitudinal studies are needed to further validate the involvement and pathological importance of the thalamus in relapse.

CONCLUSION

We observed pathological differences in neuronal connectivity associated with relapse in early-stage psychosis, which are more specifically associated with the thalamus. Our study implies the importance of considering neurobiological mechanisms associated with relapse in the trajectory of psychotic disorders.

Classification of First-Episode Psychosis with EEG Signals: ciSSA and Machine Learning Approach

First-episode psychosis (FEP) typically marks the onset of severe psychiatric disorders and represents a critical period in the field of mental health. The early diagnosis of this condition is essential for timely intervention and improved clinical outcomes. In this study, the classification of FEP was investigated using the analysis of electroencephalography (EEG) signals and circulant spectrum analysis (ciSSA) sub-band signals. FEP poses a significant diagnostic challenge in the realm of mental health, and it is aimed at introducing a novel and effective approach for early diagnosis. To achieve this, the LASSO method was utilized to select the most significant features derived from entropy, frequency, and statistical-based characteristics obtained from ciSSA sub-band signals, as well as their hybrid combinations. Subsequently, a high-performance classification model has been developed using machine learning techniques, including ensemble, support vector machine (SVM), and artificial neural network (ANN) methods. The results of this study demonstrated that the hybrid features extracted from EEG signals' ciSSA sub-bands, in combination with the SVM method, achieved a high level of performance, with an area under curve (AUC) of 0.9893, an accuracy of 96.23%, a sensitivity of 0.966, a specificity of 0.956, a precision of 0.9667, and an F1 score of 0.9666. This has revealed the effectiveness of the ciSSA-based method for classifying FEP from EEG signals.

A meta-analysis and systematic review of single vs. multimodal neuroimaging techniques in the classification of psychosis

BACKGROUND

Psychotic disorders are characterized by structural and functional abnormalities in brain networks. Neuroimaging techniques map and characterize such abnormalities using unique features (e.g., structural integrity, coactivation). However, it is unclear if a specific method, or a combination of modalities, is particularly effective in identifying differences in brain networks of someone with a psychotic disorder.

METHODS

A systematic meta-analysis evaluated machine learning classification of schizophrenia spectrum disorders in comparison to healthy control participants using various neuroimaging modalities (i.e., T1-weighted imaging (T1), diffusion tensor imaging (DTI), resting state functional connectivity (rs-FC), or some combination (multimodal)). Criteria for manuscript inclusion included whole-brain analyses and cross-validation to provide a complete picture regarding the predictive ability of large-scale brain systems in psychosis. For this meta-analysis, we searched Ovid MEDLINE, PubMed, PsychInfo, Google Scholar, and Web of Science published between inception and March 13th 2023. Prediction results were averaged for studies using the same dataset, but parallel analyses were run that included studies with pooled sample across many datasets. We assessed bias through funnel plot asymmetry. A bivariate regression model determined whether differences in imaging modality, demographics, and preprocessing methods moderated classification. Separate models were run for studies with internal prediction (via cross-validation) and external prediction.

RESULTS

93 studies were identified for quantitative review (30 T1, 9 DTI, 40 rs-FC, and 14 multimodal). As a whole, all modalities reliably differentiated those with schizophrenia spectrum disorders from controls (OR = 2.64 (95%CI = 2.33 to 2.95)). However, classification was relatively similar across modalities: no differences were seen across modalities in the classification of independent internal data, and a small advantage was seen for rs-FC studies relative to T1 studies in classification in external datasets. We found large amounts of heterogeneity across results resulting in significant signs of bias in funnel plots and Egger's tests. Results remained similar, however, when studies were restricted to those with less heterogeneity, with continued small advantages for rs-FC relative to structural measures. Notably, in all cases, no significant differences were seen between multimodal and unimodal approaches, with rs-FC and unimodal studies reporting largely overlapping classification performance. Differences in demographics and analysis or denoising were not associated with changes in classification scores.

CONCLUSIONS

The results of this study suggest that neuroimaging approaches have promise in the classification of psychosis. Interestingly, at present most modalities perform similarly in the classification of psychosis, with slight advantages for rs-FC relative to structural modalities in some specific cases. Notably, results differed substantially across studies, with suggestions of biased effect sizes, particularly highlighting the need for more studies using external prediction and large sample sizes. Adopting more rigorous and systematized standards will add significant value toward understanding and treating this critical population.

Relation between white matter integrity, perfusion, and processing speed in early-stage schizophrenia

OBJECTIVE

Cerebral blood flow (CBF) plays a critical role in the maintenance of neuronal integrity, and CBF alterations have been linked to deleterious white matter changes. Several studies report CBF and white matter structural alterations individually. However, whether and how these pathological changes relate to each other remains elusive. By using our cohort of individuals with early-stage schizophrenia, we investigated the relationship between CBF and white matter structure.

METHOD

We studied 51 early-stage schizophrenia patients and age- and sex-matched healthy controls. We investigated the relationship among tissue structure (assessed with diffusion weighted imaging), perfusion (accessed by pseudo-continuous arterial labeling imaging), and neuropsychological indices (focusing on processing speed). We focused on the corpus callosum, due to its major role in associative functions and directness on revealing the architecture of a major white matter bundle. We performed mediation analysis to identify the possible mechanism underlay the relationship among cognition and white matter integrity and perfusion.

RESULTS

The CBF and the fractional anisotropy (FA) were inversely correlated in the corpus callosum of early-stage schizophrenia patients. While CBF negatively correlated with processing speed, FA correlated positively with this cognitive measure. These results were not observed in controls. Mediation analysis revealed that the effect of FA on processing speed was mediated via the CBF.

CONCLUSIONS

We provide evidence of a relationship between brain perfusion and white matter integrity in the corpus callosum in early-stage schizophrenia. These findings may shed the light on underlying metabolic support for structural changes with cognitive impact in schizophrenia.

Brain regions associated with olfactory dysfunction in first episode psychosis patients

OBJECTIVES

Olfactory dysfunction is reproducibly reported in psychotic disorders, particularly in association with negative symptoms. The superior frontal gyrus (SFG) has been frequently studied in patients with psychotic disorders, in particular with their associations with negative symptoms. The relationship between olfactory functions and brain structure has been studied in healthy controls (HCs). Nevertheless, the studies with patients with psychotic disorders are limited. Here we report the olfactory-brain relationship in a first episode psychosis (FEP) cohort through both hypothesis-driven (centred on the SFG) and data-driven approaches.

METHODS

Using data from 88 HCs and 76 FEP patients, we evaluated the correlation between olfactory functions and structural/resting-state functional magnetic resonance imaging (MRI) data.

RESULTS

We found a significant correlation between the left SFG volume and odour discrimination in FEP patients, but not in HCs. We also observed a significant correlation between rs-fMRI connectivity involving the left SFG and odour discrimination in FEP patients, but not in HCs. The data-driven approach didn't observe any significant correlations, possibly due to insufficient statistical power.

CONCLUSION

The left SFG may be a promising brain region in the context of olfactory dysfunction and negative symptoms in FEP.

Neuroimaging in schizophrenia: A review article

In this review article we have consolidated the imaging literature of patients with schizophrenia across the full spectrum of modalities in radiology including computed tomography (CT), morphologic magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), magnetic resonance spectroscopy (MRS), positron emission tomography (PET), and magnetoencephalography (MEG). We look at the impact of various subtypes of schizophrenia on imaging findings and the changes that occur with medical and transcranial magnetic stimulation (TMS) therapy. Our goal was a comprehensive multimodality summary of the findings of state-of-the-art imaging in untreated and treated patients with schizophrenia. Clinical imaging in schizophrenia is used to exclude structural lesions which may produce symptoms that may mimic those of patients with schizophrenia. Nonetheless one finds global volume loss in the brains of patients with schizophrenia with associated increased cerebrospinal fluid (CSF) volume and decreased gray matter volume. These features may be influenced by the duration of disease and or medication use. For functional studies, be they fluorodeoxyglucose positron emission tomography (FDG PET), rs-fMRI, task-based fMRI, diffusion tensor imaging (DTI) or MEG there generally is hypoactivation and disconnection between brain regions. However, these findings may vary depending upon the negative or positive symptomatology manifested in the patients. MR spectroscopy generally shows low N-acetylaspartate from neuronal loss and low glutamine (a neuroexcitatory marker) but glutathione may be elevated, particularly in non-treatment responders. The literature in schizophrenia is difficult to evaluate because age, gender, symptomatology, comorbidities, therapy use, disease duration, substance abuse, and coexisting other psychiatric disorders have not been adequately controlled for, even in large studies and meta-analyses.

Altered thalamic subregion functional networks in patients with treatment-resistant schizophrenia

BACKGROUND

The thalamus plays a key role in filtering information and has extensive interconnectivity with other brain regions. A large body of evidence points to impaired functional connectivity (FC) of the thalamocortical pathway in schizophrenia. However, the functional network of the thalamic subregions has not been investigated in patients with treatment-resistant schizophrenia (TRS).

AIM

To identify the neural mechanisms underlying TRS, we investigated FC of thalamic sub-regions with cortical networks and voxels, and the associations of this FC with clinical symptoms. We hypothesized that the FC of thalamic sub-regions with cortical networks and voxels would differ between TRS patients and HCs.

METHODS

In total, 50 patients with TRS and 61 healthy controls (HCs) matched for age, sex, and education underwent resting-state functional magnetic resonance imaging (rs-fMRI) and clinical evaluation. Based on the rs-fMRI data, we conducted a FC analysis between thalamic subregions and cortical functional networks and voxels, and within thalamic subregions and cortical functional networks, in the patients with TRS. A functional parcellation atlas was used to segment the thalamus into nine subregions. Correlations between altered FC and TRS symptoms were explored.

RESULTS

We found differences in FC within thalamic subregions and cortical functional networks between patients with TRS and HCs. In addition, increased FC was observed between thalamic subregions and the sensorimotor cortex, frontal medial cortex, and lingual gyrus. These abnormalities were associated with the pathophysiology of TRS.

CONCLUSION

Our findings suggest that disrupted FC within thalamic subregions and cortical functional networks, and within the thalamocortical pathway, has potential as a marker for TRS. Our findings also improve our understanding of the relationship between the thalamocortical pathway and TRS symptoms.

Sex-specific involvement of the Notch-JAG pathway in social recognition

Under the hypothesis that olfactory neural epithelium gene expression profiles may be useful to look for disease-relevant neuronal signatures, we examined microarray gene expression in olfactory neuronal cells and underscored Notch-JAG pathway molecules in association with schizophrenia (SZ). The microarray profiling study underscored JAG1 as the most promising candidate. Combined with further validation with real-time PCR, downregulation of NOTCH1 was statistically significant. Accordingly, we reverse-translated the significant finding from a surrogate tissue for neurons, and studied the behavioral profile of Notch1+/- mice. We found a specific impairment in social novelty recognition, whereas other behaviors, such as sociability, novel object recognition and olfaction of social odors, were normal. This social novelty recognition deficit was male-specific and was rescued by rapamycin treatment. Based on the results from the animal model, we next tested whether patients with psychosis might have male-specific alterations in social cognition in association with the expression of NOTCH1 or JAG1. In our first episode psychosis cohort, we observed a specific correlation between the expression of JAG1 and a face processing measure only in male patients. The expression of JAG1 was not correlated with any other cognitive and symptomatic scales in all subjects. Together, although we acknowledge the pioneering and exploratory nature, the present work that combines both human and animal studies in a reciprocal manner suggests a novel role for the Notch-JAG pathway in a behavioral dimension(s) related to social cognition in psychotic disorders in a male-specific manner.

Four-modality imaging of unmedicated subjects with schizophrenia: 18F-fluorodeoxyglucose and 18F-fallypride PET, diffusion tensor imaging, and MRI

Diminished prefrontal function, dopaminergic abnormalities in the striatum and thalamus, reductions in white matter integrity and frontotemporal gray matter deficits are the most replicated findings in schizophrenia. We used four imaging modalities (¹⁸F-fluorodeoxyglucose and ¹⁸F-fallypride PET, diffusion tensor imaging, structural MRI) in 19 healthy and 25 schizophrenia subjects to assess the relationship between functional (dopamine D₂/D₃ receptor binding potential, glucose metabolic rate) and structural (fractional anisotropy, MRI) correlates of schizophrenia and their additive diagnostic prediction potential. Multivariate ANOVA was used to compare structural and functional image sets for identification of schizophrenia. Integration of data from all four modalities yielded better predictive power than less inclusive combinations, specifically in the thalamus, left dorsolateral prefrontal and temporal regions. Among the modalities, fractional anisotropy showed highest discrimination in white matter whereas ¹⁸F-fallypride binding showed highest discrimination in gray matter. Structural and functional modalities displayed comparable discriminative power but different topography, with higher sensitivity of structural modalities in the left prefrontal region. Combination of functional and structural imaging modalities with inclusion of both gray and white matter appears most effective in diagnostic discrimination. The highest sensitivity of ¹⁸F-fallypride PET to gray matter changes in schizophrenia supports the primacy of dopaminergic abnormalities in its pathophysiology.

Limbic links to paranoia: increased resting-state functional connectivity between amygdala, hippocampus and orbitofrontal cortex in schizophrenia patients with paranoia

Paranoia is a frequent and highly distressing experience in psychosis. Models of paranoia suggest limbic circuit pathology. Here, we tested whether resting-state functional connectivity (rs-fc) in the limbic circuit was altered in schizophrenia patients with current paranoia. We collected MRI scans in 165 subjects including 89 patients with schizophrenia spectrum disorders (schizophrenia, schizoaffective disorder, brief psychotic disorder, schizophreniform disorder) and 76 healthy controls. Paranoia was assessed using a Positive And Negative Syndrome Scale composite score. We tested rs-fc between bilateral nucleus accumbens, hippocampus, amygdala and orbitofrontal cortex between groups and as a function of paranoia severity. Patients with paranoia had increased connectivity between hippocampus and amygdala compared to patients without paranoia. Likewise, paranoia severity was linked to increased connectivity between hippocampus and amygdala. Furthermore, paranoia was associated with increased connectivity between orbitofrontal and medial prefrontal cortex. In addition, patients with paranoia had increased functional connectivity within the frontal hubs of the default mode network compared to healthy controls. These results demonstrate that current paranoia is linked to aberrant connectivity within the core limbic circuit and prefrontal cortex reflecting amplified threat processing and impaired emotion regulation. Future studies will need to explore the association between limbic hyperactivity, paranoid ideation and perceived stress.

Thalamic connectivity system across psychiatric disorders: Current status and clinical implications

The thalamic connectivity system, with the thalamus as the central node, enables transmission of the brain’s neural computations via extensive connections to cortical, subcortical, and cerebellar regions. Emerging reports suggest deficits in this system across multiple psychiatric disorders, making it a unique network of high translational and transdiagnostic utility in mapping neural alterations that potentially contribute to symptoms and disturbances in psychiatric patients. However, despite considerable research effort, it is still debated how this system contributes to psychiatric disorders. This review characterizes current knowledge regarding thalamic connectivity system deficits in psychiatric disorders, including schizophrenia, bipolar disorder, major depressive disorder, and autism spectrum disorder, across multiple levels of the system. We identify the presence of common and distinct patterns of deficits in the thalamic connectivity system in major psychiatric disorders and assess their nature and characteristics. Specifically, this review assembles evidence for the hypotheses of 1) thalamic microstructure, particularly in the mediodorsal nucleus, as a state marker of psychosis; 2) thalamo-prefrontal connectivity as a trait marker of psychosis; and 3) thalamo-somatosensory/parietal connectivity as a possible marker of general psychiatric illness. Furthermore, possible mechanisms contributing to thalamocortical dysconnectivity are explored. We discuss current views on the contributions of cerebellar-thalamic connectivity to the thalamic connectivity system and propose future studies to examine its effects at multiple levels, from the molecular (e.g., glutamatergic) to the behavioral (e.g., cognition), to gain a deeper understanding of the mechanisms that underlie the disturbances observed in psychiatric disorders.