Neuroimaging in Schizophrenia

Case report and systematic review of cerebellar vermis alterations in psychosis

INTRODUCTION

Cerebellar alterations, including both volumetric changes in the cerebellar vermis and dysfunctions of the corticocerebellar connections, have been documented in psychotic disorders. Starting from the clinical observation of a bipolar patient with cerebellar hypoplasia, the purpose of this review is to summarize the data in the literature about the association between hypoplasia of the cerebellar vermis and psychotic disorders [schizophrenia (SCZ) and bipolar disorder (BD)].

METHODS

A bibliographic search on PubMed has been conducted, and 18 articles were finally included in the review: five used patients with BD, 12 patients with SCZ and one subject at psychotic risk.

RESULTS

For SCZ patients and subjects at psychotic risk, the results of most of the reviewed studies seem to suggest a gray matter volume reduction coupled with an increase in white matter volumes in the cerebellar vermis, compared to healthy controls. Instead, the results of the studies on BD patients are more heterogeneous with evidence showing a reduction, no difference or even an increase in cerebellar vermis volume compared to healthy controls.

CONCLUSIONS

From the results of the reviewed studies, a possible correlation emerged between cerebellar vermis hypoplasia and psychotic disorders, especially SCZ, ultimately supporting the hypothesis of psychotic disorders as neurodevelopmental disorders.

Unveiling Promising Neuroimaging Biomarkers for Schizophrenia Through Clinical and Genetic Perspectives

Schizophrenia is a complex and serious brain disorder. Neuroscientists have become increasingly interested in using magnetic resonance-based brain imaging-derived phenotypes (IDPs) to investigate the etiology of psychiatric disorders. IDPs capture valuable clinical advantages and hold biological significance in identifying brain abnormalities. In this review, we aim to discuss current and prospective approaches to identify potential biomarkers for schizophrenia using clinical multimodal neuroimaging and imaging genetics. We first described IDPs through their phenotypic classification and neuroimaging genomics. Secondly, we discussed the applications of multimodal neuroimaging by clinical evidence in observational studies and randomized controlled trials. Thirdly, considering the genetic evidence of IDPs, we discussed how can utilize neuroimaging data as an intermediate phenotype to make association inferences by polygenic risk scores and Mendelian randomization. Finally, we discussed machine learning as an optimum approach for validating biomarkers. Together, future research efforts focused on neuroimaging biomarkers aim to enhance our understanding of schizophrenia.

Neurofilament light-chain (NfL) and 18 kDa translocator protein in early psychosis and its putative high-risk

Evidence of elevated peripheral Neurofilament light-chain (NfL) as a biomarker of neuronal injury can be utilized to reveal nonspecific axonal damage, which could reflect altered neuroimmune function. To date, only a few studies have investigated NfL as a fluid biomarker in schizophrenia primarily, though none in its putative prodrome (Clinical High-Risk, CHR) or in untreated first-episode psychosis (FEP). Further, it is unknown whether peripheral NfL is associated with 18 kDa translocator protein (TSPO), a validated neuroimmune marker. In this secondary study, we investigated for the first time (1) serum NfL in early stages of psychosis including CHR and FEP as compared to healthy controls, and (2) examined its association with brain TSPO, using [18F]FEPPA positron emission tomography (PET). Further, in the exploratory analyses, we aimed to assess associations between serum NfL and symptom severity in patient group and cognitive impairment in the combined cohort. A large cohort of 84 participants including 27 FEP (24 antipsychotic-naive), 41 CHR (34 antipsychotic-naive) and 16 healthy controls underwent structural brain MRI and [18F]FEPPA PET scan and their blood samples were obtained and assessed for serum NfL concentrations. We found no significant differences in serum NfL levels across clinical groups, controlling for age. We also found no significant association between NfL levels and brain TSPO in the entire cohort. We observed a negative association between serum NfL and negative symptom severity in CHR. Our findings suggest that neither active neuroaxonal deterioration as measured with NfL nor associated neuroimmune activation (TSPO) is clearly identifiable in an early mostly untreated psychosis sample including its putative high-risk.

Investigating amplitude of low-frequency fluctuation and possible links with cognitive impairment in childhood and adolescence onset schizophrenia: a correlation study

Background

Cognitive impairment (CI) is a distinctive characteristic of schizophrenia, with evidence suggesting that childhood and adolescence onset schizophrenia (CAOS), representing severe but rare forms of schizophrenia, share continuity with adult-onset conditions. While relationships between altered brain function and CI have been identified in adults with schizophrenia, the extent of brain function abnormalities in CAOS remains largely unknown. In this study, we employed resting-state functional magnetic resonance imaging (rs-fMRI) to investigate functional alterations in brain areas among patients with CAOS. To assess CI across multiple cognitive domains, we utilized the Stroop Color and Word Tests (SCWT) and MATRICS Consensus Cognitive Battery (MCCB) tests. Our objective was to explore the associations between functional CI and the amplitude of low-frequency fluctuation (ALFF) levels in these patients.

Methods

We enrolled 50 patients diagnosed with CAOS and 33 healthy controls (HCs) matched for sex and age. Cognitive functions were assessed using the MCCB and SCWT methods. Rs-fMRI data were acquired using gradient-echo echo-planar imaging sequences. Voxel-based ALFF group maps were compared through two-sample t-tests in SPM8. Subsequently, correlation analyses were conducted to identify associations between ALFF levels and cognitive scores.

Results

In comparison to HCs, patients exhibited significantly increased ALFF levels in the right fusiform gyrus, frontal lobe, and caudate, as well as the left frontal lobe and caudate. Conversely, reduced ALFF levels were observed in the temporal and left medial frontal lobes. Significant differences were identified between HCs and patients in terms of total cognitive scores, ALFF levels, and domain scores. All test scores were decreased, except for TMA. Correlation analyses between ALFF levels and cognitive functions in patients with CAOS differed from those in HCs. Pearson correlation analyses revealed positive associations between Brief Visuospatial Memory Test - Revised (BVMT-R) scores and ALFF levels in the left medial frontal gyrus. Digital Span Test (DST) scores were negatively correlated with ALFF levels in the right caudate, and Maze Test values were negatively correlated with levels in the left caudate. However, Pearson correlation analyses in HCs indicated that color and Hopkins Verbal Learning Test (HVLT-R) scores positively correlated with ALFF levels in the left frontal lobe, while color-word and symbol coding scores negatively correlated with levels in the right caudate.

Conclusions

Altered ALFF levels in the brain may be linked to cognitive impairment (CI) in patients with CAOS. We highlighted the pathophysiology of schizophrenia and provide imaging evidence that could potentially aid in the diagnosis of CAOS.

Advances in the understanding of the pathophysiology of schizophrenia and bipolar disorder through induced pluripotent stem cell models

The pathophysiology of schizophrenia and bipolar disorder involves a complex interaction between genetic and environmental factors that begins in the early stages of neurodevelopment. Recent advancements in the field of induced pluripotent stem cells (iPSCs) offer a promising tool for understanding the neurobiological alterations involved in these disorders and, potentially, for developing new treatment options. In this review, we summarize the results of iPSC-based research on schizophrenia and bipolar disorder, showing disturbances in neurodevelopmental processes, imbalance in glutamatergic-GABAergic transmission and neuromorphological alterations. The limitations of the reviewed literature are also highlighted, particularly the methodological heterogeneity of the studies, the limited number of studies developing iPSC models of both diseases simultaneously, and the lack of in-depth clinical characterization of the included samples. Further studies are needed to advance knowledge on the common and disease-specific pathophysiological features of schizophrenia and bipolar disorder and to promote the development of new treatment options.

Losing the chain of thought: A meta-analysis of functional neuroimaging studies using verbal tasks in schizophrenia

BACKGROUND

Disorganization symptoms are a main feature of schizophrenia, which include illogical and incoherent thinking, circumstantiality, tangentiality and loose associations. As these symptoms entail language deficits, several functional neuroimaging studies have been performed in schizophrenia using verbal tasks, producing somewhat heterogenous results. Hence, we performed a meta-analysis seeking to identify the most reliable neural alterations observed in schizophrenia patients during such tasks.

METHODS

Web of Sciences, PubMed, and EMBASE were searched for functional neuroimaging studies during verbal tasks (e.g. verbal fluency and semantic processing) in schizophrenia. Out of 795 screened articles, 33 were eligible for this meta-analysis. A coordinated-based meta-analysis was performed with the activation likelihood estimation (ALE) approach, using the cluster-level family-wise error (FWE) correction set at p < 0.05.

RESULTS

In schizophrenia, hyperactivations were observed in the left inferior frontal gyrus (IFG) and middle frontal gyrus (MFG) and hypoactivations were observed in the right IFG, the precentral gyrus and the left caudate nucleus. Another analysis pooling hyper- and hypoactivations revealed altered activations, firstly, in the left IFG and MFG, secondly, in the left precentral gyrus, IFG and insula, and, thirdly, in the left angular gyrus and precuneus. In the light of these results, not only classic language-related regions are abnormally activated during verbal tasks in schizophrenia, but also brain regions involved in executive functions, autobiographical memory and, unexpectedly, in motor functions. Further functional neuroimaging studies are needed to investigate the role of the striatum in linguistic sequencing in schizophrenia.

ROI-based analysis of diffusion indices in healthy subjects and subjects with deficit or non-deficit syndrome schizophrenia

We analyzed DTI data involving 22 healthy subjects (HC), 15 patients with deficit syndrome schizophrenia (DSZ), and 25 patients with non-deficit syndrome schizophrenia (NDSZ). We used a 1.5-T MRI scanner to collect diffusion-weighted images and T1 images, which were employed to correct distortions and deformations within the diffusion-weighted images. For 156 regions of interest (ROI), we calculated the average fractional anisotropy (FA), mean diffusion (MD), and radial diffusion (RD). Each ROI underwent a group-wise comparison using permutation F-test, followed by post hoc pairwise comparisons with Bonferroni correction. In general, we observed lower FA in both schizophrenia groups compared to HC (i.e., HC>(DSZ=NDSZ)), while MD and RD showed the opposite pattern. Notably, specific ROIs with reduced FA in schizophrenia patients included bilateral nucleus accumbens, left fusiform area, brain stem, anterior corpus callosum, left rostral and caudal anterior cingulate, right posterior cingulate, left thalamus, left hippocampus, left inferior temporal cortex, right superior temporal cortex, left pars triangularis and right lingual gyrus. Significantly, the right cuneus exhibited lower FA in the DSZ group compared to other groups ((HC=NDSZ)>DSZ), without affecting MD and RD. These results indicate that compromised neural integrity in the cuneus may contribute to the pathophysiological distinctions between DSZ and NDSZ.

A novel diagnosis method for schizophrenia based on globus pallidus data

This research aims to diagnose schizophrenia with machine learning-based algorithms. Bayesian neural network, logistic regression, decision tree, k-nearest neighbor, and gaussian kernel classification techniques are investigated to diagnose schizophrenia with data from 125 persons. This study showed that left lateral ventricles and left globus pallidus volumes and their percentages in the brain were significantly lower than HCs in FEP patients. Using brain volumes, we were able to diagnose FEP with an accuracy of 73.6 % via logistic regression and with an accuracy of 86.4 % using the SVM kernel classifier method. Therefore, brain volumes can be used to diagnose FEP with the SVM kernel classifier method.

Psychomotor slowing in schizophrenia is associated with cortical thinning of primary motor cortex: A three cohort structural magnetic resonance imaging study

Psychomotor slowing (PS) is characterized by slowed movements and lower activity levels. PS is frequently observed in schizophrenia (SZ) and distressing because it impairs performance of everyday tasks and social activities. Studying brain topography contributing to PS in SZ can help to understand the underlying neurobiological mechanisms as well as help to develop more effective treatments that specifically target affected brain areas. Here, we conducted structural magnetic resonance imaging (sMRI) of three independent cohorts of right-handed SZ patients (SZ#1: n = 72, SZ#2: n = 37, SZ#3: n = 25) and age, gender and education matched healthy controls (HC) (HC#1: n = 40, HC#2: n = 37, HC#3: n = 38). PS severity in the three SZ cohorts was determined using the Positive and Negative Syndrome Scale (PANSS) item #G7 (motor retardation) and Trail-Making-Test B (TMT-B). FreeSurfer v7.2 was used for automated parcellation and segmentation of cortical and subcortical regions. SZ#1 patients showed reduced cortical thickness in right precentral gyrus (M1; p = 0.04; Benjamini-Hochberg [BH] corr.). In SZ#1, cortical thinning in right M1 was associated with PANSS item #G7 (p = 0.04; BH corr.) and TMT-B performance (p = 0.002; BH corr.). In SZ#1, we found a significant correlation between PANSS item #G7 and TMT-B (p = 0.005, ρ=0.326). In conclusion, PANSS G#7 and TMT-B might have a surrogate value for predicting PS in SZ. Cortical thinning of M1 rather than alterations of subcortical structures may point towards cortical pathomechanism underlying PS in SZ.

Revisiting Functional Dysconnectivity: a Review of Three Model Frameworks in Schizophrenia

PURPOSE OF REVIEW

Over the last decade, evidence suggests that a combination of behavioral and neuroimaging findings can help illuminate changes in functional dysconnectivity in schizophrenia. We review the recent connectivity literature considering several vital models, considering connectivity findings, and relationships with clinical symptoms. We reviewed resting state fMRI studies from 2017 to 2023. We summarized the role of two sets of brain networks (cerebello-thalamo-cortical (CTCC) and the triple network set) across three hypothesized models of schizophrenia etiology (neurodevelopmental, vulnerability-stress, and neurotransmitter hypotheses).

RECENT FINDINGS

The neurotransmitter and neurodevelopmental models best explained CTCC-subcortical dysfunction, which was consistently connected to symptom severity and motor symptoms. Triple network dysconnectivity was linked to deficits in executive functioning, and the salience network (SN)-default mode network dysconnectivity was tied to disordered thought and attentional deficits. This paper links behavioral symptoms of schizophrenia (symptom severity, motor, executive functioning, and attentional deficits) to various hypothesized mechanisms.

Modeling psychotic disorders: Environment x environment interaction

Schizophrenia is a major psychotic disorder with multifactorial etiology that includes interactions between genetic vulnerability and environmental risk factors. In addition, interplay of multiple environmental adversities affects neurodevelopment and may increase the individual risk of developing schizophrenia. Consistent with the two-hit hypothesis of schizophrenia, we review rodent models that combine maternal immune activation as the first hit with other adverse environmental exposures as the second hit. We discuss the strengths and pitfalls of the current animal models of environment x environment interplay and propose some future directions to advance the field.

The future of diagnosis in clinical neurosciences: Comparing multiple sclerosis and schizophrenia

The ongoing developments of psychiatric classification systems have largely improved reliability of diagnosis, including that of schizophrenia. However, with an unknown pathophysiology and lacking biomarkers, its validity still remains low, requiring further advancements. Research has helped establish multiple sclerosis (MS) as the central nervous system (CNS) disorder with an established pathophysiology, defined biomarkers and therefore good validity and significantly improved treatment options. Before proposing next steps in research that aim to improve the diagnostic process of schizophrenia, it is imperative to recognize its clinical heterogeneity. Indeed, individuals with schizophrenia show high interindividual variability in terms of symptomatic manifestation, response to treatment, course of illness and functional outcomes. There is also a multiplicity of risk factors that contribute to the development of schizophrenia. Moreover, accumulating evidence indicates that several dimensions of psychopathology and risk factors cross current diagnostic categorizations. Schizophrenia shares a number of similarities with MS, which is a demyelinating disease of the CNS. These similarities appear in the context of age of onset, geographical distribution, involvement of immune-inflammatory processes, neurocognitive impairment and various trajectories of illness course. This article provides a critical appraisal of diagnostic process in schizophrenia, taking into consideration advancements that have been made in the diagnosis and management of MS. Based on the comparison between the two disorders, key directions for studies that aim to improve diagnostic process in schizophrenia are formulated. All of them converge on the necessity to deconstruct the psychosis spectrum and adopt dimensional approaches with deep phenotyping to refine current diagnostic boundaries.

An fNIRS investigation of novel expressed emotion stimulations in schizophrenia

Living in high expressed emotion (EE) environments tends to increase the relapse rate in schizophrenia (SZ). At present, the neural substrates responsible for high EE in SZ remain poorly understood. Functional near-infrared spectroscopy (fNIRS) may be of great use to quantitatively assess cortical hemodynamics and elucidate the pathophysiology of psychiatric disorders. In this study, we designed novel low- (positivity and warmth) and high-EE (criticism, negative emotion, and hostility) stimulations, in the form of audio, to investigate cortical hemodynamics. We used fNIRS to measure hemodynamic signals while participants listened to the recorded audio. Healthy controls (HCs, [Formula: see text]) showed increased hemodynamic activation in the major language centers across EE stimulations, with stronger activation in Wernicke's area during the processing of negative emotional language. Compared to HCs, people with SZ ([Formula: see text]) exhibited smaller hemodynamic activation in the major language centers across EE stimulations. In addition, people with SZ showed weaker or insignificant hemodynamic deactivation in the medial prefrontal cortex. Notably, hemodynamic activation in SZ was found to be negatively correlated with the negative syndrome scale score at high EE. Our findings suggest that the neural mechanisms in SZ are altered and disrupted, especially during negative emotional language processing. This supports the feasibility of using the designed EE stimulations to assess people who are vulnerable to high-EE environments, such as SZ. Furthermore, our findings provide preliminary evidence for future research on functional neuroimaging biomarkers for people with psychiatric disorders.

Nicotine's effect on cognition, a friend or foe?

Tobacco smoking is a preventable cause of morbidity and mortality throughout the world. Smoking comes in form of absorption of many compounds, among which nicotine is the main psychoactive component of tobacco and its positive and negative reinforcement effects are proposed to be the key mechanism for the initiation and maintenance of smoking. Growing evidence suggests that the cognitive enhancement effects of nicotine may also contribute to the difficulty of quitting smoking, especially in individuals with psychiatric disorders. In this review, we first introduce the beneficial effect of nicotine on cognition including attention, short-term memory and long-term memory. We next summarize the beneficial effect of nicotine on cognition under pathological conditions, including Alzheimer's disease, Parkinson's disease, Schizophrenia, Stress-induced Anxiety, Depression, and drug-induced memory impairment. The possible mechanism underlying nicotine's effect is also explored. Finally, nicotine's detrimental effect on cognition is discussed, including in the prenatal and adolescent periods, and high-dose nicotine- and withdrawal-induced memory impairment is emphasized. Therefore, nicotine serves as both a friend and foe. Nicotine-derived compounds could be a promising strategy to alleviate neurological disease-associated cognitive deficit, however, due to nicotine's detrimental effect, continued educational programs and public awareness campaigns are needed to reduce tobacco use among pregnant women and smoking should be quitted even if it is e-cigarette, especially for the adolescents.

Inhibition of glycolysis prevents behavioural changes in mice with MK801-induced SCZ model by alleviating lactate accumulation and lactylation

Schizophrenia (SCZ) is a debilitating neuropsychiatric disorder with a complex aetiology. Cognitive symptoms and hippocampal changes have been implicated in the pathophysiology of SCZ. Changes in metabolites level and up-regulated glycolysis have been reported in previous studies, which may be related to the hippocampal dysfunction in SCZ. However, the pathological mechanism of glycolysis involved in the pathogenesis of SCZ remains unclear. Therefore, the change of glycolysis level and the involvement in SCZ need to be further studied. In our study, MK801 was used to induce an SCZ mouse model and cell model in vivo and in vitro. Western blotting was performed to evaluate the levels of glycolysis, metabolites, and lactylation in hippocampal tissue of mice with SCZ or cell models. The level of high mobility group protein 1 (HMGB1) in the medium of MK801-treated primary hippocampal neurons was examined. Apoptosis was evaluated in HMGB1-treated hippocampal neurons by flow cytometry. The glycolysis inhibitor 2-DG prevented behavioural changes in the MK801-induced SCZ mouse model. The lactate accumulation and level of lactylation were alleviated in the hippocampal tissue of MK801-treated mice. Glycolysis was enhanced, and lactate accumulated in MK-801-treated primary hippocampal neurons. In addition, the level of HMGB1 increased in the medium and induced apoptosis in primary hippocampal neurons. Together, the data showed that glycolysis and lactylation increased in the MK801-induced SCZ model in vivo and in vitro, and this effect could be prevented by 2-DG (a glycolysis inhibitor). Glycolytic related HMGB1 upregulation may induce apoptosis in hippocampal neurons downstream.

Distinctive effects of NMDA receptor modulators on cerebral microcirculation in a schizophrenia mouse model

Substantial evidence demonstrates that schizophrenia patients have altered cerebral microcirculation. However, little is known regarding how cerebral microcirculatory blood flow (microCBF) changes in schizophrenia. Here, using time-lapse two-photon imaging of individual capillaries, we demonstrated a substantial decrease in cerebral microcirculation in a mouse model of schizophrenia. The involvement of NMDA receptor (NMDAR) functions was investigated to understand further the mechanism of microcirculation reduction in this animal model. Administration of D-serine, a selective full agonist at the glycine site of NMDAR, significantly increased the microCBF in the schizophrenia mouse. Interestingly, administration of GNE-8324, a GluN2A-selective positive allosteric modulator that selectively enhances NMDAR-mediated synaptic responses in inhibitory but not excitatory neurons, had no effect on the microCBF of the schizophrenia mice. Together, these data indicated that NMDAR participated in the regulation of microcirculation in schizophrenia using a mechanism dependent on the tonic NMDAR signaling and the selective modulation of inhibitory neuron activity. Further studies are warranted to establish NMDAR's role in modulating microcirculation in schizophrenia.

Cognitive Processes and Resting-State Functional Neuroimaging Findings in High Schizotypal Individuals and Schizotypal Personality Disorder Patients: A Systematic Review

Ample research findings indicate that there is altered brain functioning in the schizophrenia spectrum. Nevertheless, functional neuroimaging findings remain ambiguous for healthy individuals expressing high schizotypal traits and patients with schizotypal personality disorder (SPD). The purpose of this systematic review was to identify patterns of task-related and resting-state neural abnormalities across these conditions. MEDLINE-PubMed and PsycINFO were systematically searched and forty-eight studies were selected. Forty studies assessed healthy individuals with high schizotypal traits and eight studies examined SPD patients with functional neuroimaging techniques (fNIRS; fMRI; Resting-state fMRI). Functional alterations in striatal, frontal and temporal regions were found in healthy individuals with high schizotypal traits. Schizotypal personality disorder was associated with default mode network abnormalities but further research is required in order to better conceive its neural correlates. There was also evidence for functional compensatory mechanisms associated with both conditions. To conclude, the findings suggest that brain dysfunctions are evident in individuals who lie along the subclinical part of the spectrum, further supporting the continuum model for schizophrenia susceptibility. Additional research is required in order to delineate the counterbalancing processes implicated in the schizophrenia spectrum, as this approach will provide promising insights for both conversion and protection from conversion into schizophrenia.

Childhood trauma is associated with altered white matter microstructural organization in schizophrenia

It has been reported that childhood trauma (CT) is associated with reductions in fractional anisotropy (FA) in individuals with schizophrenia (SZ). Here, we hypothesized that SZ with high levels of CT will show the greatest reductions in FA in frontolimbic and frontoparietal regions compared to healthy controls (HC) with high trauma levels and participants with no/low levels of CT. Thirty-seven SZ and 129 HC with CT experience were dichotomized into groups of 'none/low' or 'high' levels. Participants underwent diffusion-weighted MRI, and Tract-based spatial statistics were employed to assess the main effect of diagnosis, main effect of CT severity irrespective of diagnosis, and interaction between diagnosis and CT severity. SZ showed FA reductions in the corpus callosum and corona radiata compared to HC. Irrespective of a diagnosis, high CT levels (n = 48) were related to FA reductions in frontolimbic and frontoparietal regions compared to those with none/low levels of CT (n = 118). However, no significant interaction between diagnosis and high levels of CT was found (n = 13). Across all participants, we observed effects of CT on late developing frontolimbic and frontoparietal regions, suggesting that the effects of CT severity on white matter organization may be independent of schizophrenia.

The Hypothalamic-Pituitary-Gonadal Axis in Men with Schizophrenia

Schizophrenia is a severe mental disorder with a chronic, progressive course. The etiology of this condition is linked to the interactions of multiple genes and environmental factors. The earlier age of onset of schizophrenia, the higher frequency of negative symptoms in the clinical presentation, and the poorer response to antipsychotic treatment in men compared to women suggests the involvement of sex hormones in these processes. This article aims to draw attention to the possible relationship between testosterone and some clinical features in male schizophrenic patients and discuss the complex nature of these phenomena based on data from the literature. PubMed, Web of Science, and Google Scholar databases were searched to select the papers without limiting the time of the publications. Hormone levels in the body are regulated by many organs and systems, and take place through the neuroendocrine, hormonal, neural, and metabolic pathways. Sex hormones play an important role in the development and function of the organism. Besides their impact on secondary sex characteristics, they influence brain development and function, mood, and cognition. In men with schizophrenia, altered testosterone levels were noted. In many cases, evidence from available single studies gave contradictory results. However, it seems that the testosterone level in men affected by schizophrenia may differ depending on the phase of the disease, types of clinical symptoms, and administered therapy. The etiology of testosterone level disturbances may be very complex. Besides the impact of the illness (schizophrenia), stress, and antipsychotic drug-induced hyperprolactinemia, testosterone levels may be influenced by, i.a., obesity, substances of abuse (e.g., ethanol), or liver damage.

Discriminative analysis of schizophrenia patients using graph convolutional networks: A combined multimodal MRI and connectomics analysis

Introduction

Recent studies in human brain connectomics with multimodal magnetic resonance imaging (MRI) data have widely reported abnormalities in brain structure, function and connectivity associated with schizophrenia (SZ). However, most previous discriminative studies of SZ patients were based on MRI features of brain regions, ignoring the complex relationships within brain networks.

Methods

We applied a graph convolutional network (GCN) to discriminating SZ patients using the features of brain region and connectivity derived from a combined multimodal MRI and connectomics analysis. Structural magnetic resonance imaging (sMRI) and resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from 140 SZ patients and 205 normal controls. Eighteen types of brain graphs were constructed for each subject using 3 types of node features, 3 types of edge features, and 2 brain atlases. We investigated the performance of 18 brain graphs and used the TopK pooling layers to highlight salient brain regions (nodes in the graph).

Results

The GCN model, which used functional connectivity as edge features and multimodal features (sMRI + fMRI) of brain regions as node features, obtained the highest average accuracy of 95.8%, and outperformed other existing classification studies in SZ patients. In the explainability analysis, we reported that the top 10 salient brain regions, predominantly distributed in the prefrontal and occipital cortices, were mainly involved in the systems of emotion and visual processing.

Discussion

Our findings demonstrated that GCN with a combined multimodal MRI and connectomics analysis can effectively improve the classification of SZ at an individual level, indicating a promising direction for the diagnosis of SZ patients. The code is available at https://github.com/CXY-scut/GCN-SZ.git.

Retinal layers and symptoms and inflammation in schizophrenia

Schizophrenia is a neurodevelopmental disorder that affects brain structure and function. The retina, as well as the brain, consists of neuronal and glial cells packed in layers. Cortical volume and brain thickness are associated with inflammatory biomarkers, however, no study has been performed associating inflammatory biomarkers and retina in schizophrenia. our study aims to compare the retinal macular thickness and volume and peripapillary thickness in patients with schizophrenia and controls, and associate it to symptoms of schizophrenia, to interleukin-6 (IL-6) and C Reactive Protein (CRP) levels. Optical coherence tomography was performed to assess retinal layer thickness and volume, and CRP and IL-6 levels were measured in patients with schizophrenia and controls. Positive, negative, and general symptoms of schizophrenia were measured with the Positive and Negative Syndrome Scale (PANSS). A linear regression controlling for confounding factors was performed. 70 subjects were included, 35 patients, and 35 controls matched for sex and age. Patients with schizophrenia presented a significantly lower macular volume (p < 0.05) and thickness (< 0.05) than controls. PANSS positive, general and total scores were associated with retinal nerve fiber layer (RNFL) thickness (p < 0.05). There was no association between inflammatory markers (CRP and IL-6) levels and the retinal layer. A reduction in macular volume and thickness was found in patients with schizophrenia. The severity of schizophrenia symptoms was associated with RNFL thickness. CRP and IL-6 are not associated with retinal thickness/volume in schizophrenia or controls.

The challenging quest of neuroimaging: From clinical to molecular-based subtyping of Parkinson disease and atypical parkinsonisms

The current framework of Parkinson disease (PD) focuses on phenotypic classification despite its considerable heterogeneity. We argue that this method of classification has restricted therapeutic advances and therefore limited our ability to develop disease-modifying interventions in PD. Advances in neuroimaging have identified several molecular mechanisms relevant to PD, variation within and between clinical phenotypes, and potential compensatory mechanisms with disease progression. Magnetic resonance imaging (MRI) techniques can detect microstructural changes, disruptions in neural pathways, and metabolic and blood flow alterations. Positron emission tomography (PET) and single-photon emission computed tomography (SPECT) imaging have informed the neurotransmitter, metabolic, and inflammatory dysfunctions that could potentially distinguish disease phenotypes and predict response to therapy and clinical outcomes. However, rapid advancements in imaging techniques make it challenging to assess the significance of newer studies in the context of new theoretical frameworks. As such, there needs to not only be a standardization of practice criteria in molecular imaging but also a rethinking of target approaches. In order to harness precision medicine, a coordinated shift is needed toward divergent rather than convergent diagnostic approaches that account for interindividual differences rather than similarities within an affected population, and focus on predictive patterns rather than already lost neural activity.

P50 inhibition defects, psychopathology and gray matter volume in patients with first-episode drug-naive schizophrenia

BACKGROUND

Sensory gating deficits and gray matter volume (GMV) abnormalities have been found to be associated with the pathogenesis and psychopathology of patients with schizophrenia (SCZ). However, no studies have investigated their interrelationship in first-episode treatment-naive (FETN) SCZ patients.

METHODS

We recruited 52 FETN SCZ patients and 57 healthy controls. The Positive and Negative Syndrome Scale (PANSS) was used to measure the psychopathology of the patients. We collected magnetic resonance imaging and P50 inhibition data from all participants.

RESULTS

Compared to healthy controls, patients had shorter S1 and S2 latencies but larger S2 amplitudes and P50 ratio (Bonferroni adjusted all p < 0.01). In patients, S2 latency was independently associated with PANSS total score, negative symptoms and general psychopathology (t = 2.26-2.58, both P < 0.05), whereas S1 (t = 2.44, P < 0.05) and S2 latencies (t = 2.13, P < 0.05) were associated with PANSS cognitive factor. Moreover, GMV in the left inferior temporal gyrus, left lingual gyrus and right superior occipital gyrus, and bilateral dorsolateral superior frontal gyrus were each associated with the P50 components (all p < 0.05). In addition, GMV associated with S2 latency was negatively correlated with PANSS general psychopathology (t = -2.46, p < 0.05) and total score (t = -2.34, p < 0.05).

CONCLUSIONS

Our findings indicate that FETN SCZ patients exhibit deficits in P50 inhibition and GMV of brain regions associated with these deficits may be associated with their psychopathological symptoms, suggesting that brain structures associated with P50 components may be important biomarkers of SCZ psychopathology. Future studies could use a prospective longitudinal design to investigate the potential causal relationship of brain structures associated with P50 components in the psychopathological symptoms of SCZ patients.

Biological hypotheses, risk factors, and biomarkers of schizophrenia

Both the discovery of biomarkers of schizophrenia and the verification of biological hypotheses of schizophrenia are an essential part of the process of understanding the etiology of this mental disorder. Schizophrenia has long been considered a neurodevelopmental disease whose symptoms are caused by impaired synaptic signal transduction and brain neuroplasticity. Both the onset and chronic course of schizophrenia are associated with risk factors-induced disruption of brain function and the establishment of a new homeostatic setpoint characterized by biomarkers. Different risk factors and biomarkers can converge to the same symptoms of schizophrenia, suggesting that the primary cause of the disease can be highly individual. Schizophrenia-related biomarkers include measurable biochemical changes induced by stress (elevated allostatic load), mitochondrial dysfunction, neuroinflammation, oxidative and nitrosative stress, and circadian rhythm disturbances. Here is a summary of selected valid biological hypotheses of schizophrenia formulated based on risk factors and biomarkers, neurodevelopment, neuroplasticity, brain chemistry, and antipsychotic medication. The integrative neurodevelopmental-vulnerability-neurochemical model is based on current knowledge of the neurobiology of the onset and progression of the disease and the effects of antipsychotics and psychotomimetics and reflects the complex and multifactorial nature of schizophrenia.

Gray matter volume drives the brain age gap in schizophrenia: a SHAP study

Neuroimaging-based brain age is a biomarker that is generated by machine learning (ML) predictions. The brain age gap (BAG) is typically defined as the difference between the predicted brain age and chronological age. Studies have consistently reported a positive BAG in individuals with schizophrenia (SCZ). However, there is little understanding of which specific factors drive the ML-based brain age predictions, leading to limited biological interpretations of the BAG. We gathered data from three publicly available databases - COBRE, MCIC, and UCLA - and an additional dataset (TOPSY) of early-stage schizophrenia (82.5% untreated first-episode sample) and calculated brain age with pre-trained gradient-boosted trees. Then, we applied SHapley Additive Explanations (SHAP) to identify which brain features influence brain age predictions. We investigated the interaction between the SHAP score for each feature and group as a function of the BAG. These analyses identified total gray matter volume (group × SHAP interaction term β = 1.71 [0.53; 3.23]; p_corr < 0.03) as the feature that influences the BAG observed in SCZ among the brain features that are most predictive of brain age. Other brain features also presented differences in SHAP values between SCZ and HC, but they were not significantly associated with the BAG. We compared the findings with a non-psychotic depression dataset (CAN-BIND), where the interaction was not significant. This study has important implications for the understanding of brain age prediction models and the BAG in SCZ and, potentially, in other psychiatric disorders.

The Difficult Path to the Discovery of Novel Treatments in Psychiatric Disorders

CNS diseases, including psychiatric disorders, represent a significant opportunity for the discovery and development of new drugs and therapeutic treatments with the potential to have a significant impact on human health. CNS diseases, however, present particular challenges to therapeutic discovery efforts, and psychiatric diseases/disorders may be among the most difficult. With specific exceptions such as psychostimulants for ADHD, a large number of psychiatric patients are resistant to existing treatments. In addition, clinicians have no way of knowing which psychiatric patients will respond to which drugs. By definition, psychiatric diagnoses are syndromal in nature; determinations of efficacy are often self-reported, and drug discovery is largely model-based. While such models of psychiatric disease are amenable to screening for new drugs, whether cellular or whole-animal based, they have only modest face validity and, more importantly, predictive validity. Multiple academic, pharmaceutical industry, and government agencies are dedicated to the translation of new findings about the neurobiology of major psychiatric disorders into the discovery and advancement of novel therapies. The collaboration of these agencies provide a pathway for developing new therapeutics. These efforts will be greatly helped by recent advances in understanding the genetic bases of psychiatric disorders, the ongoing search for diagnostic and therapy-responsive biomarkers, and the validation of new animal models.

Schizophrenia: One Name, Many Different Manifestations

Schizophrenia is a disabling condition impacting approximately 1% of the worldwide population. Symptoms include positive symptoms (eg, hallucinations, delusions), negative symptoms (eg, avolition, anhedonia), and cognitive impairment. There are likely many different environmental and pathophysiologic etiologies involving distinct neurotransmitters and neurocircuits. Pharmacologic treatment at present consists of dopamine receptor antagonists, which are reasonably effective at treating positive symptoms, but less effective at treating cognitive and negative symptoms. Nondopaminergic medications targeting alternative receptors are under investigation. Supportive psychosocial treatments can work in tandem with antipsychotic medications and optimize patient care.

Longitudinal alterations of modular functional-metabolic coupling in first-episode schizophrenia

Altered network organization and aberrant neurometabolic levels have been associated with schizophrenia. However, modular alterations of functional-neurometabolic coupling in various stages of schizophrenia remain unclear. This longitudinal study enrolled 34 drug-naïve first-episode schizophrenia (FES) patients and 30 healthy controls (HC). The FES patients underwent resting-state functional magnetic resonance imaging (rs-fMRI) and proton magnetic resonance spectroscopy (¹H-MRS) at baseline, 2 months, and 6 months of treatment. For ¹H-MRS, the concentrations of γ-aminobutyric acid (GABA), N-acetylaspartate (NAA) and glutamate + glutamine in the ventromedial prefrontal cortex region were measured. A graph theoretical approach was applied for functional connectivity-based modular parcellation. We found that intra-default mode network (DMN) connectivity, inter-modular connectivity between the DMN and the hippocampus, and inter-modular connectivity between the DMN and the frontoparietal module were significantly different across 6-month treatment in the FES patients. The inter-module connectivity of the DMN and hippocampus correlated positively with NAA concentration in the HC group, while this correlation was absent in FES patients. This exploratory study suggests an altered modular connectivity in association with neurometabolite concentrations in FES patients and provides insights into multimodal neuroimaging biomarkers in schizophrenia. Future studies with larger sample sizes are needed to consolidate our findings.

Neuroanatomical subtypes of schizophrenia and relationship with illness duration and deficit status

BACKGROUND

The heterogeneity of schizophrenia (SCZ) regarding psychopathology, illness trajectory and their inter-relationships with underlying neural substrates remain incompletely understood. In a bid to reduce illness heterogeneity using neural substrates, our study aimed to replicate the findings of an earlier study by Chand et al. (2020). We employed brain structural measures for subtyping SCZ patients, and evaluate each subtype's relationship with clinical features such as illness duration, psychotic psychopathology, and additionally deficit status.

METHODS

Overall, 240 subjects (160 SCZ patients, 80 healthy controls) were recruited for this study. The participants underwent brain structural magnetic resonance imaging scans and clinical rating using the Positive and Negative Syndrome Scale. Neuroanatomical subtypes of SCZ were identified using "Heterogeneity through discriminative analysis" (HYDRA), a clustering technique which accounted for relevant covariates and the inter-group normalized percentage changes in brain volume were also calculated.

RESULTS

As replicated, two neuroanatomical subtypes (SG-1 and SG-2) were found amongst our patients with SCZ. The subtype SG-1 was associated with enlargements in the third and lateral ventricles, volume increase in the basal ganglia (putamen, caudate, pallidum), longer illness duration, and deficit status. The subtype SG-2 was associated with reductions of cortical and subcortical structures (hippocampus, thalamus, basal ganglia).

CONCLUSIONS

These replicated findings have clinical implications in the early intervention, response monitoring, and prognostication of SCZ. Future studies may adopt a multi-modal neuroimaging approach to enhance insights into the neurobiological composition of relevant subtypes.

Impact of Maternal Immune Activation on Nonhuman Primate Prefrontal Cortex Development: Insights for Schizophrenia

Late adolescence is a period of dynamic change in the brain as humans learn to navigate increasingly complex environments. In particular, prefrontal cortical (PFC) regions undergo extensive remodeling as the brain is fine-tuned to orchestrate cognitive control over attention, reasoning, and emotions. Late adolescence also presents a uniquely vulnerable period as neurodevelopmental illnesses, such as schizophrenia, become evident and worsen into young adulthood. Challenges in early development, including prenatal exposure to infection, may set the stage for a cascade of maladaptive events that ultimately result in aberrant PFC connectivity and function before symptoms emerge. A growing body of research suggests that activation of the mother's immune system during pregnancy may act as a disease primer, in combination with other environmental and genetic factors, contributing to an increased risk of neurodevelopmental disorders, including schizophrenia. Animal models provide an invaluable opportunity to examine the course of brain and behavioral changes in offspring exposed to maternal immune activation (MIA). Although the vast majority of MIA research has been carried out in rodents, here we highlight the translational utility of the nonhuman primate (NHP) as a model species more closely related to humans in PFC structure and function. In this review, we consider the protracted period of brain and behavioral maturation in the NHP, describe emerging findings from MIA NHP offspring in the context of rodent preclinical models, and lastly explore the translational relevance of the NHP MIA model to expand understanding of the etiology and developmental course of PFC pathology in schizophrenia.

Cognitive dysfunction in schizophrenia: An expert group paper on the current state of the art

Cognitive impairment in schizophrenia represents one of the main obstacles to clinical and functional recovery. This expert group paper brings together experts in schizophrenia treatment to discuss scientific progress in the domain of cognitive impairment to address cognitive impairments and their consequences in the most effective way. We report on the onset and course of cognitive deficits, linking them to the alterations in brain function and structure in schizophrenia and discussing their role in predicting the transition to psychosis in people at risk. We then address the assessment tools with reference to functioning and social cognition, examining the role of subjective measures and addressing new methods for measuring functional outcomes including technology based approaches. Finally, we briefly review treatment options for cognitive deficits, focusing on cognitive remediation programs, highlighting their effects on brain activity and conclude with the potential benefit of individualized integrated interventions combing cognitive remediation with other approaches.

Schizophrenia: A Narrative Review of Etiopathogenetic, Diagnostic and Treatment Aspects

Although schizophrenia is currently conceptualized as being characterized as a syndrome that includes a collection of signs and symptoms, there is strong evidence of heterogeneous and complex underpinned etiological, etiopathogenetic, and psychopathological mechanisms, which are still under investigation. Therefore, the present viewpoint review is aimed at providing some insights into the recently investigated schizophrenia research fields in order to discuss the potential future research directions in schizophrenia research. The traditional schizophrenia construct and diagnosis were progressively revised and revisited, based on the recently emerging neurobiological, genetic, and epidemiological research. Moreover, innovative diagnostic and therapeutic approaches are pointed to build a new construct, allowing the development of better clinical and treatment outcomes and characterization for schizophrenic individuals, considering a more patient-centered, personalized, and tailored-based dimensional approach. Further translational studies are needed in order to integrate neurobiological, genetic, and environmental studies into clinical practice and to help clinicians and researchers to understand how to redesign a new schizophrenia construct.

Thalamo-hippocampal dysconnectivity is associated with serum cholesterol level in drug-naïve patients with first-episode schizophrenia

Hippocampal deficits and metabolic dysregulations such as dyslipidemia have been frequently reported in schizophrenia and are suggested to contribute to the pathophysiology of schizophrenia. Hippocampus is particularly susceptible to environmental challenges including metabolism and inflammation. However, evidence linking hippocampal alterations and metabolic dysregulations are quite sparse in drug-naïve schizophrenia. A total of 166 drug-naïve patients with first-episode schizophrenia (FES) and 78 healthy controls (HC) underwent measures for several serum metabolic markers, structural and resting-state functional magnetic resonance imaging (rs-fMRI), as well as diffusion tensor imaging (DTI). Seed-to-voxel functional connectivity (FC) and probabilistic tractography were performed to assess the functional and microstructural connectivity of the bilateral hippocampi. Clinical symptoms were evaluated with Positive and Negative Syndrome Scale (PANSS). Patients with FES showed significantly decreased total cholesterol (Chol) level. Patients showed elevated FC between the left hippocampus and bilateral thalami while showing decreased microstructural connectivity between the left hippocampus and bilateral thalami. Multiple regression analyses showed that FC from the left hippocampus to the right superior frontal gyrus (SFG), bilateral frontal pole (FP), and right thalamus were negatively associated with the Chol level, while no association was observed in the HC group. Our study validated alterations in both functional and microstructural thalamo-hippocampal connectivities, and abnormal cholesterol level in FES. Moreover, decreased cholesterol level is associated with elevated thalamo-hippocampal functional connectivity in patients with FES, suggesting that dyslipidemia may interact with the hippocampal dysfunction in FES.

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.

Advantages and Limitations of Animal Schizophrenia Models

Mental illness modeling is still a major challenge for scientists. Animal models of schizophrenia are essential to gain a better understanding of the disease etiopathology and mechanism of action of currently used antipsychotic drugs and help in the search for new and more effective therapies. We can distinguish among pharmacological, genetic, and neurodevelopmental models offering various neuroanatomical disorders and a different spectrum of symptoms of schizophrenia. Modeling schizophrenia is based on inducing damage or changes in the activity of relevant regions in the rodent brain (mainly the prefrontal cortex and hippocampus). Such artificially induced dysfunctions approximately correspond to the lesions found in patients with schizophrenia. However, notably, animal models of mental illness have numerous limitations and never fully reflect the disease state observed in humans.

Dynamics of intrinsic whole-brain functional connectivity in abstinent males with methamphetamine use disorder

Background

The global prevalence of methamphetamine use disorder (MUD) and the associated economic burden are increasing, but effective pharmacological treatment is lacking. Therefore, understanding the neurological mechanisms underlying MUD is essential to develop clinical strategies and improve patient care. Individuals with MUD can show static brain network abnormalities during the resting state, but their alterations in dynamic functional network connectivity (dFNC) are unclear.

Methods

In this study, we obtained resting-state functional magnetic resonance imaging from 42 males with MUD and 41 healthy controls. Sliding-window and spatial independent component analyses with a k-means clustering algorithm were used to assess the recurring functional connectivity states. The temporal properties of the dFNC, including fraction and dwelling time of each state and the number of transitions between different states, were compared between the two groups. In addition, the relationships between the temporal properties of the dFNC and clinical characteristics of the MUDs, including their anxiety and depressive symptoms, were further explored.

Results

While the two groups shared many similarities in their dFNC, the occurrence of a highly integrated functional network state and a state featuring balanced integration and segregation in the MUDs significantly correlated with the total drug usage (Spearman's rho = 0.47, P = 0.002) and duration of abstinence (Spearman's rho = 0.38, P = 0.013), respectively.

Conclusions

The observed results in our study demonstrate that methamphetamines can affect dFNC, which may reflect the drug's influence on cognitive abilities. Our study justifies further studies into the effects of MUD on dynamic neural mechanisms.

Brain Mechanism of Acupuncture Treatment of Chronic Pain: An Individual-Level Positron Emission Tomography Study

Objective

Acupuncture has been shown to be effective in the treatment of chronic pain. However, their neural mechanism underlying the effective acupuncture response to chronic pain is still unclear. We investigated whether metabolic patterns in the pain matrix network might predict acupuncture therapy responses in patients with primary dysmenorrhea (PDM) using a machine-learning-based multivariate pattern analysis (MVPA) on positron emission tomography data (PET).

Methods

Forty-two patients with PDM were selected and randomized into two groups: real acupuncture and sham acupuncture (three menstrual cycles). Brain metabolic data from the three special brain networks (the sensorimotor network (SMN), default mode network (DMN), and salience network (SN)) were extracted at the individual level by using PETSurfer in fluorine-18 fluorodeoxyglucose positron emission tomography (18F-FDG-PET) data. MVPA analysis based on metabolic network features was employed to predict the pain relief after treatment in the pooled group and real acupuncture treatment, separately.

Results

Paired t-tests revealed significant alterations in pain intensity after real but not sham acupuncture treatment. Traditional mass-univariate correlations between brain metabolic and alterations in pain intensity were not significant. The MVPA results showed that the brain metabolic pattern in the DMN and SMN did predict the pain relief in the pooled group of patients with PDM (R2 = 0.25, p = 0.005). In addition, the metabolic pattern in the DMN could predict the pain relief after treatment in the real acupuncture treatment group (R2 = 0.40, p = 0.01).

Conclusion

This study indicates that the individual-level metabolic patterns in DMN is associated with real acupuncture treatment response in chronic pain. The present findings advanced the knowledge of the brain mechanism of the acupuncture treatment in chronic pain.

Neuroimaging of psychiatric disorders

Psychiatry remains the only medical specialty where diagnoses are still based on clinical syndromes rather than measurable biological abnormalities. As imaging technology and analytical methods evolve, it is becoming clear that subtle but measurable radiological characteristics exist and can be used to experimentally classify psychiatric disorders, predict response to treatment and, hopefully, develop new, more effective therapies. This review highlights advances in neuroimaging modalities that are now allowing assessment of brain structure, connectivity and neural network function, describes technical aspects of the most promising methods, and summarizes observations made in some frequent psychiatric disorders.

The Limits between Schizophrenia and Bipolar Disorder: What Do Magnetic Resonance Findings Tell Us?

Schizophrenia and bipolar disorder, two of the most severe psychiatric illnesses, have historically been regarded as dichotomous entities but share many features of the premorbid course, clinical profile, genetic factors and treatment approaches. Studies focusing on neuroimaging findings have received considerable attention, as they plead for an improved understanding of the brain regions involved in the pathophysiology of schizophrenia and bipolar disorder. In this review, we summarize the main magnetic resonance imaging findings in both disorders, aiming at exploring the neuroanatomical and functional similarities and differences between the two. The findings show that gray and white matter structural changes and functional dysconnectivity predominate in the frontal and limbic areas and the frontotemporal circuitry of the brain areas involved in the integration of executive, cognitive and affective functions, commonly affected in both disorders. Available evidence points to a considerable overlap in the affected regions between the two conditions, therefore possibly placing them at opposite ends of a psychosis continuum.

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.

Epilepsy in patients with schizophrenia: Pathophysiology and basic treatments

Schizophrenia is a chronic psychiatric disorder that may lead to epilepsy. However, there are limited findings on the issues. This narrative review aimed to provide a practical perspective on epilepsy in patients with schizophrenia using the current treatment systems for epilepsy. While there has been a debate on the relationship between epilepsy and schizophrenia, i.e., antagonism, affinity, and coincidence, recent large cohort studies have revealed a high frequency of epilepsy in patients with schizophrenia (4-5 times higher than that of general population). The high incidence observed is likely to be due to the bidirectionality between epilepsy and schizophrenia and additional schizophrenia-related conditions, e.g., antipsychotic drugs (APD), substance abuse, and head injury. As for symptomatology of epilepsy, only one small-size study showed that seizures of patients with schizophrenia are equivalent to those of patients without schizophrenia. Patients with schizophrenia exhibit the first seizure in their twenties or later, which are mostly focal seizures. Most of seizures in patients with schizophrenia can be controlled with conventional antiepileptic drugs. Few patients with schizophrenia develop treatment-resistant epilepsy. However, since drug interactions can be more complicated due to multiple conditions, such as pre-existing polypharmacy, heavy smoking, irregular eating, and comorbid metabolic disorders, cautious monitoring for clinical symptoms is required. To improve seizure control and adherence, non-pharmacological approaches are also recommended. Thus far, for seizure treatments in patients with schizophrenia, we have to use many empirical findings or substitute certain findings from population without schizophrenia because evidence is insufficient. The accumulation of clinical findings may contribute to the development of efficient treatment systems.

Quantifying Retinal Microvascular Morphology in Schizophrenia Using Swept-Source Optical Coherence Tomography Angiography

BACKGROUND

Retinovascular changes are reported on fundus imaging in schizophrenia (SZ). This is the first study to use swept-source optical coherence tomography angiography (OCT-A) to comprehensively examine retinal microvascular changes in SZ.

METHODS

This study included 30 patients with SZ/schizoaffective disorder (8 early and 15 chronic) and 22 healthy controls (HCs). All assessments were performed at Beth Israel Deaconess Medical Center and Massachusetts Eye and Ear. All participants underwent swept-source OCT-A of right (oculus dextrus [OD]) and left (oculus sinister [OS]) eye, clinical, and cognitive assessments. Macular OCT-A images (6 × 6 mm) were collected with the DRI Topcon Triton for superficial, deep, and choriocapillaris vascular regions. Microvasculature was quantified using vessel density (VD), skeletonized vessel density (SVD), fractal dimension (FD), and vessel diameter index (VDI).

RESULTS

Twenty-one HCs and 26 SZ subjects were included. Compared to HCs, SZ patients demonstrated higher overall OD superficial SVD, OD choriocapillaris VD, and OD choriocapillaris SVD, which were primarily observed in the central, central and outer superior, and central and outer inferior/superior, respectively. Early-course SZ subjects had significantly higher OD superficial VD, OD choriocapillaris SVD, and OD choriocapillaris FD compared to matched HCs. Higher bilateral (OU) superficial VD correlated with lower Positive and Negative Syndrome Scale (PANSS) positive scores, and higher OU deep VDI was associated with higher PANSS negative scores.

CONCLUSIONS AND RELEVANCE

These results suggest the presence of microvascular dysfunction associated with early-stage SZ. Clinical associations with microvascular alterations further implicate this hypothesis, with higher measures being associated with worse symptom severity and functioning in early stages and with lower symptom severity and better functioning in later stages.

Decreased gray matter volume is associated with theory of mind deficit in adolescents with schizophrenia

Schizophrenia patients often suffer from deficit in theory of mind (TOM). Prior neuroimaging studies revealed neuroimaging correlates of TOM deficit in adults with schizophrenia, neuroimaging correlates of TOM in adolescents is less well established. This study aimed to investigate gray matter volume (GMV) abnormalities and TOM deficits in schizophrenic adolescents, and examine the relationship between them. Twenty adolescent schizophrenic patients and 25 age, sex-matched healthy controls underwent T1-weighted magnetic resonance imaging (MRI) scans, and were examined for TOM based on the Reading the Mind in the Eyes test (RMET). Univariate voxel-based morphometry (VBM) and multivariate source-based morphometry (SBM) were employed to examine alterations of two GMV phenotypes in schizophrenic adolescents: voxel-wise GMV and covarying structural brain patterns (SBPs). Compared with controls, our results revealed a significant deficit in RMET performance of the patients, Voxel-wise VBM analysis revealed that patients exhibited decreased GMV in bilateral insula, orbitofrontal cortex, and right rolandic operculum, and GMV of these brain regions were positively correlated with RMET performance. Multivariate SBM analysis identified a significantly different between-group SBP comprising of bilateral insula and inferior frontal cortex, bilateral superior temporal cortex, and bilateral lateral parietal cortex and right rolandic operculum. The loading scores of this SBP was positively correlated with RMET performance. This study revealed impairment of TOM ability in schizophrenic adolescents and revealed an association between TOM deficit and decreased GMV in regions which are crucial for social cognition, thereby provided insight and possible target regions for understanding the neural pathology and normalizing TOM deficit in adolescent schizophrenia patients.

Brain age in mood and psychotic disorders: a systematic review and meta-analysis

OBJECTIVE

To evaluate whether accelerated brain aging occurs in individuals with mood or psychotic disorders.

METHODS

A systematic review following PRISMA guidelines was conducted. A meta-analysis was then performed to assess neuroimaging-derived brain age gap in three independent groups: (1) schizophrenia and first-episode psychosis, (2) major depressive disorder, and (3) bipolar disorder.

RESULTS

A total of 18 papers were included. The random-effects model meta-analysis showed a significantly increased neuroimaging-derived brain age gap relative to age-matched controls for the three major psychiatric disorders, with schizophrenia (3.08; 95%CI [2.32; 3.85]; p < 0.01) presenting the largest effect, followed by bipolar disorder (1.93; [0.53; 3.34]; p < 0.01) and major depressive disorder (1.12; [0.41; 1.83]; p < 0.01). The brain age gap was larger in older compared to younger individuals.

CONCLUSION

Individuals with mood and psychotic disorders may undergo a process of accelerated brain aging reflected in patterns captured by neuroimaging data. The brain age gap tends to be more pronounced in older individuals, indicating a possible cumulative biological effect of illness burden.

Bioinformatics analysis of long non-coding RNA-associated competing endogenous RNA network in schizophrenia

Schizophrenia (SCZ) is a serious psychiatric condition with a 1% lifetime risk. SCZ is one of the top ten global causes of disabilities. Despite numerous attempts to understand the function of genetic factors in SCZ development, genetic components in SCZ pathophysiology remain unknown. The competing endogenous RNA (ceRNA) network has been demonstrated to be involved in the development of many kinds of diseases. The ceRNA hypothesis states that cross-talks between coding and non-coding RNAs, including long non-coding RNAs (lncRNAs), via miRNA complementary sequences known as miRNA response elements, creates a large regulatory network across the transcriptome. In the present study, we developed a lncRNA-related ceRNA network to elucidate molecular regulatory mechanisms involved in SCZ. Microarray datasets associated with brain regions (GSE53987) and lymphoblasts (LBs) derived from peripheral blood (sample set B from GSE73129) of SCZ patients and control subjects containing information about both mRNAs and lncRNAs were downloaded from the Gene Expression Omnibus database. The GSE53987 comprised 48 brain samples taken from SCZ patients (15 HPC: hippocampus, 15 BA46: Brodmann area 46, 18 STR: striatum) and 55 brain samples taken from control subjects (18 HPC, 19 BA46, 18 STR). The sample set B of GSE73129 comprised 30 LB samples (15 patients with SCZ and 15 controls). Differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified using the limma package of the R software. Using DIANA-LncBase, Human MicroRNA Disease Database (HMDD), and miRTarBase, the lncRNA- associated ceRNA network was generated. Pathway enrichment of DEmRNAs was performed using the Enrichr tool. We developed a protein-protein interaction network of DEmRNAs and identified the top five hub genes by the use of STRING and Cytoscape, respectively. Eventually, the hub genes, DElncRNAs, and predictive miRNAs were chosen to reconstruct the subceRNA networks. Our bioinformatics analysis showed that twelve key DEmRNAs, including BDNF, VEGFA, FGF2, FOS, CD44, SOX2, NRAS, SPARC, ZFP36, FGG, ELAVL1, and STARD13, participate in the ceRNA network in SCZ. We also identified DLX6-AS1, NEAT1, MINCR, LINC01094, DLGAP1-AS1, BABAM2-AS1, PAX8-AS1, ZFHX4-AS1, XIST, and MALAT1 as key DElncRNAs regulating the genes mentioned above. Furthermore, expression of 15 DEmRNAs (e.g., ADM and HLA-DRB1) and one DElncRNA (XIST) were changed in both the brain and LB, suggesting that they could be regarded as candidates for future biomarker studies. The study indicated that ceRNAs could be research candidates for investigating SCZ molecular pathways.

Maternal Immune Activation during Pregnancy Alters Postnatal Brain Growth and Cognitive Development in Nonhuman Primate Offspring

Human epidemiological studies implicate exposure to infection during gestation in the etiology of neurodevelopmental disorders. Animal models of maternal immune activation (MIA) have identified the maternal immune response as the critical link between maternal infection and aberrant offspring brain and behavior development. Here we evaluate neurodevelopment of male rhesus monkeys (Macaca mulatta) born to MIA-treated dams (n = 14) injected with a modified form of the viral mimic polyinosinic:polycytidylic acid at the end of the first trimester. Control dams received saline injections at the same gestational time points (n = 10) or were untreated (n = 4). MIA-treated dams exhibited a strong immune response as indexed by transient increases in sickness behavior, temperature, and inflammatory cytokines. Although offspring born to control or MIA-treated dams did not differ on measures of physical growth and early developmental milestones, the MIA-treated animals exhibited subtle changes in cognitive development and deviated from species-typical brain growth trajectories. Longitudinal MRI revealed significant gray matter volume reductions in the prefrontal and frontal cortices of MIA-treated offspring at 6 months that persisted through the final time point at 45 months along with smaller frontal white matter volumes in MIA-treated animals at 36 and 45 months. These findings provide the first evidence of early postnatal changes in brain development in MIA-exposed nonhuman primates and establish a translationally relevant model system to explore the neurodevelopmental trajectory of risk associated with prenatal immune challenge from birth through late adolescence.SIGNIFICANCE STATEMENT Women exposed to infection during pregnancy have an increased risk of giving birth to a child who will later be diagnosed with a neurodevelopmental disorder. Preclinical maternal immune activation (MIA) models have demonstrated that the effects of maternal infection on fetal brain development are mediated by maternal immune response. Since the majority of MIA models are conducted in rodents, the nonhuman primate provides a unique system to evaluate the MIA hypothesis in a species closely related to humans. Here we report the first longitudinal study conducted in a nonhuman primate MIA model. MIA-exposed offspring demonstrate subtle changes in cognitive development paired with marked reductions in frontal gray and white matter, further supporting the association between prenatal immune challenge and alterations in offspring neurodevelopment.

The colors of our brain: an integrated approach for dimensionality reduction and explainability in fMRI through color coding (i-ECO)

Several systematic reviews have highlighted the role of multiple sources in the investigation of psychiatric illness. For what concerns fMRI, the focus of recent literature preferentially lies on three lines of research, namely: functional connectivity, network analysis and spectral analysis. Data was gathered from the UCLA Consortium for Neuropsychiatric Phenomics. The sample was composed by 130 neurotypicals, 50 participants diagnosed with Schizophrenia, 49 with Bipolar disorder and 43 with ADHD. Single fMRI scans were reduced in their dimensionality by a novel method (i-ECO) averaging results per Region of Interest and through an additive color method (RGB): local connectivity values (Regional Homogeneity), network centrality measures (Eigenvector Centrality), spectral dimensions (fractional Amplitude of Low-Frequency Fluctuations). Average images per diagnostic group were plotted and described. The discriminative power of this novel method for visualizing and analyzing fMRI results in an integrative manner was explored through the usage of convolutional neural networks. The new methodology of i-ECO showed between-groups differences that could be easily appreciated by the human eye. The precision-recall Area Under the Curve (PR-AUC) of our models was > 84.5% for each diagnostic group as evaluated on the test-set – 80/20 split. In conclusion, this study provides evidence for an integrative and easy-to-understand approach in the analysis and visualization of fMRI results. A high discriminative power for psychiatric conditions was reached. This proof-of-work study may serve to investigate further developments over more extensive datasets covering a wider range of psychiatric diagnoses.