Altered Dynamic Functional Connectivity of Cuneus in Schizophrenia Patients: A Resting-State fMRI Study

Diagnosis of Schizophrenia and Its Subtypes Using MRI and Machine Learning

PURPOSE

The neurobiological heterogeneity present in schizophrenia remains poorly understood. This likely contributes to the limited success of existing treatments and the observed variability in treatment responses. Our objective was to employ magnetic resonance imaging (MRI) and machine learning (ML) algorithms to improve the classification of schizophrenia and its subtypes.

METHOD

We utilized a public dataset provided by the UCLA (University of California, Los Angeles) Consortium for Neuropsychiatric Research, containing structural MRI and resting-state fMRI (rsfMRI) data. We integrated all individuals within the dataset diagnosed with schizophrenia (N = 50), along with age- and gender-matched healthy individuals (N = 50). We extracted volumetrics of 66 subcortical and thickness of 72 cortical regions. Additionally, we obtained four graph-based measures for 116 intracranial regions from rsfMRI data, including degree, betweenness centrality, participation coefficient, and local efficiency. Employing conventional ML methods, we sought to distinguish the patients with schizophrenia from healthy individuals. Furthermore, we applied the methods for discriminating subtypes of schizophrenia. To streamline the feature set, various feature selection techniques were applied. Moreover, a validation phase involved employing the model on a dataset domestically acquired using the same imaging assessments (N = 13). Finally, we explored the correlation between neuroimaging features and behavioral assessments.

FINDING

The classification accuracy reached as high as 79% in distinguishing schizophrenia patients from healthy in the UCLA dataset. This result was achieved by the k-nearest neighbor algorithm, utilizing 12 brain neuroimaging features, selected by the feature selection method of minimum redundancy maximum relevance (MRMR). The model demonstrated effectiveness (72% accuracy) in estimating the patient's label for a new dataset acquired domestically. Using a linear support vector machine (SVM) on 62 features obtained from MRMR, patients with schizophrenic subtypes were classified with an accuracy of 64%. The highest Spearman correlation coefficient between the neuroimaging features and behavioral assessments was observed between the degree of the postcentral gyrus and mean reaction time in the verbal capacity task (r = 0.49, p = 0.001).

CONCLUSION

The findings of this study underscore the utility of MRI and ML algorithms in enhancing the diagnostic process for schizophrenia. Furthermore, these methods hold promise for detecting both brain-related abnormalities and cognitive impairments associated with this disorder.

Addressing brain metabolic connectivity in treatment-resistant schizophrenia: a novel graph theory-driven application of 18F-FDG-PET with antipsychotic dose correction

Few studies using Positron Emission Tomography with 18F-fluorodeoxyglucose (18F-FDG-PET) have examined the neurobiological basis of antipsychotic resistance in schizophrenia, primarily focusing on metabolic activity, with none investigating connectivity patterns. Here, we aimed to explore differential patterns of glucose metabolism between patients and controls (CTRL) through a graph theory-based approach and network comparison tests. PET scans with 18F-FDG were obtained by 70 subjects, 26 with treatment-resistant schizophrenia (TRS), 28 patients responsive to antipsychotics (nTRS), and 16 CTRL. Relative brain glucose metabolism maps were processed in the automated anatomical labeling (AAL)-Merged atlas template. Inter-subject connectivity matrices were derived using Gaussian Graphical Models and group networks were compared through permutation testing. A logistic model based on machine-learning was employed to estimate the association between the metabolic signals of brain regions and treatment resistance. To account for the potential influence of antipsychotic medication, we incorporated chlorpromazine equivalents as a covariate in the network analysis during partial correlation calculations. Additionally, the machine-learning analysis employed medication dose-stratified folds. Global reduced connectivity was detected in the nTRS (p-value = 0.008) and TRS groups (p-value = 0.001) compared to CTRL, with prominent alterations localized in the frontal lobe, Default Mode Network, and dorsal dopamine pathway. Disruptions in frontotemporal and striatal-cortical connectivity were detected in TRS but not nTRS patients. After adjusting for antipsychotic doses, alterations in the anterior cingulate, frontal and temporal gyri, hippocampus, and precuneus also emerged. The machine-learning approach demonstrated an accuracy ranging from 0.72 to 0.8 in detecting the TRS condition.

Alterations in amygdala subregions-Default mode network connectivity after treatment in patients with schizophrenia

Disrupted connectivity in the default mode network (DMN) during resting-state functional MRI (rs-fMRI) is well-documented in schizophrenia (SCZ). The amygdala, a key component in the neurobiology of SCZ, comprises distinct subregions that may exert varying effects on the disorder. This study aimed to investigate variations in functional connectivity (FC) between distinct amygdala subregions and the DMN in SCZ individuals and explore the effects of treatment on these connections. Fifty-six SCZ patients and 51 healthy controls underwent FC analysis and questionnaire surveys during resting state. The amygdala was selected as the region of interest (ROI) and subdivided into four parts. Changes in FC were examined, and correlations between questionnaire scores and brain activity were explored. Pre-treatment, SCZ patients exhibited reduced FC between the amygdala and DMN compared to HCs. After treatment, significant differences persisted in the right medial amygdala, while other regions did not differ significantly from controls. In addition, PANSS scores positively correlated with FC between the Right Medial Amygdala and the left SMFC (r = .347, p = .009), while RBANS5A scores showed a positive correlation with FC between the Left Lateral Amygdala and the right MTG (rho = -.347, p = .009). The rsFC between the amygdala and the DMN plays a crucial role in the treatment mechanisms of SCZ. This could provide a promising predictive indicator for understanding the neural mechanisms behind treatment and symptomatic improvement.

A connectome-wide association study of altered functional connectivity in schizophrenia based on resting-state fMRI

BACKGROUND

Aberrant resting-state functional connectivity is a neuropathological feature of schizophrenia (SCZ). Prior investigations into functional connectivity abnormalities have primarily employed seed-based connectivity analysis, necessitating predefined seed locations. To address this limitation, a data-driven multivariate method known as connectome-wide association study (CWAS) has been proposed for exploring whole-brain functional connectivity.

METHODS

We conducted a CWAS analysis involving 46 patients with SCZ and 40 age- and sex-matched healthy controls. Multivariate distance matrix regression (MDMR) was utilized to identify key nodes in the brain. Subsequently, we conducted a follow-up seed-based connectivity analysis to elucidate specific connectivity patterns between regions of interest (ROIs). Additionally, we explored the spatial correlation between changes in functional connectivity and underlying molecular architectures by examining correlations between neurotransmitter/transporter distribution densities and functional connectivity.

RESULTS

MDMR revealed the right medial frontal gyrus and the left calcarine sulcus as two key nodes. Follow-up analysis unveiled hypoconnectivity between the right medial frontal superior gyrus and the right fusiform gyrus, as well as hypoconnectivity between the left calcarine sulcus and the right lingual gyrus in SCZ. Notably, a significant association between functional connectivity strength and positive symptom severity was identified. Furthermore, altered functional connectivity patterns suggested potential dysfunctions in the dopamine, serotonin, and gamma-aminobutyric acid systems.

CONCLUSIONS

This study elucidated reduced functional connectivity both within and between the medial frontal regions and the occipital cortex in patients with SCZ. Moreover, it indicated potential alterations in molecular architecture, thereby expanding current knowledge regarding neurobiological changes associated with SCZ.

Intrinsic network abnormalities in children with autism spectrum disorder: an independent component analysis

Aberrant intrinsic brain networks are consistently observed in individuals with autism spectrum disorder. However, studies examining the strength of functional connectivity across brain regions have yielded conflicting results. Therefore, this study aimed to investigate the functional connectivity of the resting brain in children with low-functioning autism, including during the early developmental stages. We explored the functional connectivity of 43 children with autism spectrum disorder and 54 children with typical development aged 2 to 12 years using resting-state functional magnetic resonance imaging data. We used independent component analysis to classify the brain regions into six intrinsic networks and analyzed the functional connectivity within each network. Moreover, we analyzed the relationship between functional connectivity and clinical scores. In children with autism, the under-connectivities were observed within several brain networks, including the cognitive control, default mode, visual, and somatomotor networks. In contrast, we found over-connectivities between the subcortical, visual, and somatomotor networks in children with autism compared with children with typical development. Moderate effect sizes were observed in entire networks (Cohen's d = 0.43-0.77). These network alterations were significantly correlated with clinical scores such as the communication sub-score (r = - 0.442, p = 0.045) and the calibrated severity score (r = - 0.435, p = 0.049) of the Autism Diagnostic Observation Schedule. These opposing results observed based on the brain areas suggest that aberrant neurodevelopment proceeds in various ways depending on the functional brain regions in individuals with autism spectrum disorder.

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.

Bilateral anterior corona radiata microstructure organisation relates to impaired social cognition in schizophrenia

OBJECTIVE

The Corona Radiata (CR) is a large white matter tract in the brain comprising of the anterior CR (aCR), superior CR (sCR), and posterior CR (pCR), which have associations with cognition, self-regulation, and, in schizophrenia, positive symptom severity. This study tested the hypothesis that the microstructural organisation of the aCR, as measured by Fractional Anisotropy (FA) using Diffusion Tensor Imaging (DTI), would relate to poorer social cognitive outcomes and higher positive symptom severity for people with schizophrenia, when compared to healthy participants. We further hypothesised that increased positive symptoms would relate to poorer social cognitive outcomes.

METHODS

Data were derived from n = 178 healthy participants (41 % females; 36.11 ± 12.36 years) and 58 people with schizophrenia (30 % females; 42.4 ± 11.1 years). The Positive and Negative Symptom Severity Scale measured clinical symptom severity. Social Cognition was measured using the Reading the Mind in the Eyes Test (RMET) Total Score, as well as the Positive, Neutral, and Negative stimuli valence. The ENIGMA-DTI protocol tract-based spatial statistics (TBSS) was used.

RESULTS

There was a significant difference in FA for the CR, in individuals with schizophrenia compared to healthy participants. On stratification, both the aCR and pCR were significantly different between groups, with patients showing reduced white matter tract microstructural organisation. Significant negative correlations were observed between positive symptomatology and reduced microstructural organisation of the aCR. Performance for RMET negative valence items was significantly correlated bilaterally with the aCR, but not the sCR or pCR, and no relationship to positive symptoms was observed.

CONCLUSIONS

These data highlight specific and significant microstructural white-matter differences for people with schizophrenia, which relates to positive clinical symptomology and poorer performance on social cognition stimuli. While reduced FA is associated with higher positive symptomatology in schizophrenia, this study shows the specific associated with anterior frontal white matter tracts and reduced social cognitive performance. The aCR may have a specific role to play in frontal-disconnection syndromes, psychosis, and social cognitive profile within schizophrenia, though further research requires more sensitive, specific, and detailed consideration of social cognition outcomes.

Differential responses from the left postcentral gyrus, right middle frontal gyrus, and precuneus to meal ingestion in patients with functional dyspepsia

Background

Functional dyspepsia (FD) is most often a meal-induced syndrome. Studies using resting-state functional magnetic resonance imaging (rs-fMRI) reported abnormal connectivity in areas related to pain processing in FD. However, only a few studies have attempted to determine how meal ingestion affects the brain's working patterns. Through rs-fMRI, this study observed how meal ingestion affected brain regions related to visceral hypersensitivity and emotional response networks in FD patients.

Methods

A total of 30 FD patients and 32 healthy controls (HC) were enrolled and underwent clinical investigations. Rs-fMRI was performed twice after a 4-h fast and 50 min after a meal. The mean functional connectivity strength (FCS) values were extracted from brain regions with significant differences to show the trend of changes related to meal ingestion after FCS analyses.

Results

Depression, anxiety, sleep disturbances, and weight loss were more common in FD patients (P ≤ 0.001). Compared with HCs (corrected cluster P-value < 0.05), FD patients had significantly higher FCS in the right middle frontal gyrus before meals and higher meal-induced FCS in the left postcentral gyrus. HCs had greater meal-induced activation in the right precuneus and anterior cingulate cortex. FD patients had a decreasing trend in the right inferior frontal gyrus compared to the increasing trend in HCs. We only found anxiety to be negatively correlated with FCS in the right inferior frontal gyrus in FD (r = -0.459, p = 0.048, uncorrected).

Conclusions

In this study, we discovered that FD patients have different perceptual and emotional responses to food intake in defined brain areas, providing promising impetus for understanding pathogenic brain mechanisms in FD.

Unraveling the pathophysiology of schizophrenia: insights from structural magnetic resonance imaging studies

Background

Schizophrenia affects about 1% of the global population. In addition to the complex etiology, linking this illness to genetic, environmental, and neurobiological factors, the dynamic experiences associated with this disease, such as experiences of delusions, hallucinations, disorganized thinking, and abnormal behaviors, limit neurological consensuses regarding mechanisms underlying this disease.

Methods

In this study, we recruited 72 patients with schizophrenia and 74 healthy individuals matched by age and sex to investigate the structural brain changes that may serve as prognostic biomarkers, indicating evidence of neural dysfunction underlying schizophrenia and subsequent cognitive and behavioral deficits. We used voxel-based morphometry (VBM) to determine these changes in the three tissue structures: the gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). For both image processing and statistical analysis, we used statistical parametric mapping (SPM).

Results

Our results show that patients with schizophrenia exhibited a significant volume reduction in both GM and WM. In particular, GM volume reductions were more evident in the frontal, temporal, limbic, and parietal lobe, similarly the WM volume reductions were predominantly in the frontal, temporal, and limbic lobe. In addition, patients with schizophrenia demonstrated a significant increase in the CSF volume in the left third and lateral ventricle regions.

Conclusion

This VBM study supports existing research showing that schizophrenia is associated with alterations in brain structure, including gray and white matter, and cerebrospinal fluid volume. These findings provide insights into the neurobiology of schizophrenia and may inform the development of more effective diagnostic and therapeutic approaches.

The Tryptophan-Kynurenine Metabolic System Is Suppressed in Cuprizone-Induced Model of Demyelination Simulating Progressive Multiple Sclerosis

Progressive multiple sclerosis (MS) is a chronic disease with a unique pattern, which is histologically classified into the subpial type 3 lesions in the autopsy. The lesion is also homologous to that of cuprizone (CPZ) toxin-induced animal models of demyelination. Aberration of the tryptophan (TRP)-kynurenine (KYN) metabolic system has been observed in patients with MS; nevertheless, the KYN metabolite profile of progressive MS remains inconclusive. In this study, C57Bl/6J male mice were treated with 0.2% CPZ toxin for 5 weeks and then underwent 4 weeks of recovery. We measured the levels of serotonin, TRP, and KYN metabolites in the plasma and the brain samples of mice at weeks 1, 3, and 5 of demyelination, and at weeks 7 and 9 of remyelination periods by ultra-high-performance liquid chromatography with tandem mass spectrometry (UHPLC-MS/MS) after body weight measurement and immunohistochemical analysis to confirm the development of demyelination. The UHPLC-MS/MS measurements demonstrated a significant reduction of kynurenic acid, 3-hydoxykynurenine (3-HK), and xanthurenic acid in the plasma and a significant reduction of 3-HK, and anthranilic acid in the brain samples at week 5. Here, we show the profile of KYN metabolites in the CPZ-induced mouse model of demyelination. Thus, the KYN metabolite profile potentially serves as a biomarker of progressive MS and thus opens a new path toward planning personalized treatment, which is frequently obscured with immunologic components in MS deterioration.

Efficacy of Serotonin and Dopamine Activity Modulators in the Treatment of Negative Symptoms in Schizophrenia: A Rapid Review

Schizophrenia is among the fifteen most disabling diseases worldwide. Negative symptoms (NS) are highly prevalent in schizophrenia, negatively affect the functional outcome of the disorder, and their treatment is difficult and rarely specifically investigated. Serotonin-dopamine activity modulators (SDAMs), of which aripiprazole, cariprazine, brexpiprazole, and lumateperone were approved for schizophrenia treatment, represent a possible therapy to reduce NS. The aim of this rapid review is to summarize the evidence on this topic to make it readily available for psychiatrists treating NS and for further research. We searched the PubMed database for original studies using SDAM, aripiprazole, cariprazine, brexpiprazole, lumateperone, schizophrenia, and NS as keywords. We included four mega-analyses, eight meta-analyses, two post hoc analyses, and 20 clinical trials. Aripiprazole, cariprazine, and brexpiprazole were more effective than placebo in reducing NS. Only six studies compared SDAMs with other classes of antipsychotics, demonstrating a superiority in the treatment of NS mainly for cariprazine. The lack of specific research and various methodological issues, related to the study population and the assessment of NS, may have led to these partial results. Here, we highlight the need to conduct new methodologically robust investigations with head-to-head treatment comparisons and long-term observational studies on homogeneous groups of patients evaluating persistent NS with first- and second-generation scales, namely the Brief Negative Symptom Scale and the Clinical Assessment Interview for Negative Symptoms. This rapid review can expand research on NS therapeutic strategies in schizophrenia, which is fundamental for the long-term improvement of patients’ quality of life.

Mismatch negativity as an early biomarker of cognitive impairment in schizophrenia

Background

Due to its disturbance in schizophrenic patients, mismatch negativity (MMN) generation is believed to be a potential biomarker for recognizing primary impairments in auditory sensory processing during the course of the disease. However, great controversy exists regarding the type and onset of MMN-related impairments, with the deficits to frequency deviants is more debatable. This cross-sectional, case–control study was conducted to assess the cognitive functions among 33 eligible Egyptian schizophrenics (15 early and 18 chronic), and 30 matched healthy controls by assessing their psychometric tests and correlating them to the coexisting frequency deviant MMN responses (using both tone and speech stimuli).

Results

Deficits in frequency MMN and neuropsychological tests were evident among early and chronic schizophrenics compared to their matched control counterparts, and also between early versus chronic schizophrenia in favor of the later. MMN deficits to speech stimuli were more elicited than tone stimuli among schizophrenics. Moreover, significant correlations were identified between MMN parameters and the results of psychiatric cognitive scales.

Conclusions

We demonstrated that frequency-deviant MMN deficits are evident feature among the enrolled Egyptian schizophrenics. The cognitive functions as indexed by MMN seem affected early, with the striking decrease of MMN amplitude and delay of latency point towards the progression of the illness. The normal lateralization of MMN was absent in chronic schizophrenia. These findings could be helpful in using the MMN as an additional objective tool for confirming cognitive impairments among schizophrenics and to differentiate between early- and chronic-schizophrenic patients for medico-legal purposes and clinical implication for medications.

Clozapine Suppresses the Gene Expression and the Production of Cytokines and Up-Regulates Cyclooxygenase 2 mRNA in Human Astroglial Cells

Schizophrenia (SCZ) is a chronic neurodevelopmental psychotic disorder. The immune system and neuroinflammation seem to play a central role in the pathophysiology of SCZ. Clozapine is an effective atypical antipsychotic used for treatment-resistant SCZ. Life-threatening side effects, such as myocarditis, limit its use. We investigated the immunomodulatory effects of clozapine in an astroglial model of neuroinflammation. We thus assessed the effect of clozapine on the production of inflammatory mediators in human-derived astroglial (A172) cells, stimulated with a cytokine mix (TNFα, IL-1β, IFNγ). RT-PCR and ELISA analyses demonstrated that clozapine suppressed gene expression and production of TNFα, IL-1β and IL-8 and increased COX2 mRNA 24 h after stimulation. Clozapine inhibited Akt phosphorylation induced by the cytokine mix at 10 min and 40 min, as assessed by Western blot analysis with anti-pT308Akt antibody. Pretreatment with the Akt inhibitor MK-2206 increased COX2 gene expression in cytokine-stimulated cells, suggesting that Akt inhibition may be involved in COX2 gene expression upregulation. Clozapine may possess dual beneficial effects: inhibiting astroglial production of proinflammatory cytokines, thus attenuating neuroinflammation, and upregulating COX2 expression that may be relevant to improvement of neural functioning while accounting for some of its detrimental effects. Patients with TRS and neuroinflammatory markers may benefit particularly from clozapine treatment.

Integrating Armchair, Bench, and Bedside Research for Behavioral Neurology and Neuropsychiatry: Editorial

"To learning much inclined, who went to see the Elephant (though all of them were blind) that each by observation might satisfy the mind" [...].

NGFR Gene and Single Nucleotide Polymorphisms, rs2072446 and rs11466162, Playing Roles in Psychiatric Disorders

Psychiatric disorders are a class of complex disorders characterized by brain dysfunction with varying degrees of impairment in cognition, emotion, consciousness and behavior, which has become a serious public health issue. The NGFR gene encodes the p75 neurotrophin receptor, which regulates neuronal growth, survival and plasticity, and was reported to be associated with depression, schizophrenia and antidepressant efficacy in human patient and animal studies. In this study, we investigated its association with schizophrenia and major depression and its role in the behavioral phenotype of adult mice. Four NGFR SNPs were detected based on a study among 1010 schizophrenia patients, 610 patients with major depressive disorders (MDD) and 1034 normal controls, respectively. We then knocked down the expression of NGFR protein in the hippocampal dentate gyrus of the mouse brain by injection of shRNA lentivirus to further investigate its behavioral effect in mice. We found significant associations of s2072446 and rs11466162 for schizophrenia. Ngfr knockdown mice showed social and behavioral abnormalities, suggesting that it is linked to the etiology of neuropsychiatric disorders. We found significant associations between NGFR and schizophrenia and that Ngfr may contribute to the social behavior of adult mice in the functional study, which provided meaningful clues to the pathogenesis of psychiatric disorders.

Corpus Callosum Microstructural Tract Integrity Relates to Longer Emotion Recognition Reaction Time in People with Schizophrenia

Objective: Schizophrenia is a complex functionally debilitating neurodevelopmental disorder, with associated social cognitive impairment. Corpus Callosum (CC) white matter tracts deficits are reported for people with schizophrenia; however, few studies focus on interhemispheric processing relative to social cognition tasks. This study aimed to determine if a relationship between the CC and social cognition exists. Method: In this cross-section study, a sample of n = 178 typical controls and n = 58 people with schizophrenia completed measures of mentalising (Reading the Mind in the Eyes), emotion recognition outcome and reaction time (Emotion Recognition Test), and clinical symptoms (Positive and Negative Symptom Scale), alongside diffusion-based tract imaging. The CC and its subregions, i.e., the genu, body, and splenium were the regions of interest (ROI). Results: Reduced white matter tract integrity was observed in the CC for patients when compared to controls. Patients performed slower, and less accurately on emotion recognition tasks, which significantly and negatively correlated to the structural integrity of the CC genu. Tract integrity further significantly and negatively related to clinical symptomatology. Conclusions: People with schizophrenia have altered white matter integrity in the genu of the CC, compared to controls, which relates to cognitive deficits associated with recognising emotional stimuli accurately and quickly, and severity of clinical symptoms.

Mitochondrial Impairment: A Common Motif in Neuropsychiatric Presentation? The Link to the Tryptophan-Kynurenine Metabolic System

Nearly half a century has passed since the discovery of cytoplasmic inheritance of human chloramphenicol resistance. The inheritance was then revealed to take place maternally by mitochondrial DNA (mtDNA). Later, a number of mutations in mtDNA were identified as a cause of severe inheritable metabolic diseases with neurological manifestation, and the impairment of mitochondrial functions has been probed in the pathogenesis of a wide range of illnesses including neurodegenerative diseases. Recently, a growing number of preclinical studies have revealed that animal behaviors are influenced by the impairment of mitochondrial functions and possibly by the loss of mitochondrial stress resilience. Indeed, as high as 54% of patients with one of the most common primary mitochondrial diseases, mitochondrial encephalomyopathy with lactic acidosis and stroke-like episodes (MELAS) syndrome, present psychiatric symptoms including cognitive impairment, mood disorder, anxiety, and psychosis. Mitochondria are multifunctional organelles which produce cellular energy and play a major role in other cellular functions including homeostasis, cellular signaling, and gene expression, among others. Mitochondrial functions are observed to be compromised and to become less resilient under continuous stress. Meanwhile, stress and inflammation have been linked to the activation of the tryptophan (Trp)-kynurenine (KYN) metabolic system, which observably contributes to the development of pathological conditions including neurological and psychiatric disorders. This review discusses the functions of mitochondria and the Trp-KYN system, the interaction of the Trp-KYN system with mitochondria, and the current understanding of the involvement of mitochondria and the Trp-KYN system in preclinical and clinical studies of major neurological and psychiatric diseases.

The alterations of brain functional connectivity networks in major depressive disorder detected by machine learning through multisite rs-fMRI data

BACKGROUND

The current diagnosis of major depressive disorder (MDD) is mainly based on the patient's self-report and clinical symptoms. Machine learning methods are used to identify MDD using resting-state functional magnetic resonance imaging (rs-fMRI) data. However, due to large site differences in multisite rs-fMRI data and the difficulty of sample collection, most of the current machine learning studies use small sample sizes of rs-fMRI datasets to detect the alterations of functional connectivity (FC) or network attribute (NA), which may affect the reliability of the experimental results.

METHODS

Multisite rs-fMRI data were used to increase the size of the sample, and then we extracted the functional connectivity (FC) and network attribute (NA) features from 1611 rs-fMRI data (832 patients with MDD (MDDs) and 779 healthy controls (HCs)). ComBat algorithm was used to harmonize the data variances caused by the multisite effect, and multivariate linear regression was used to remove age and sex covariates. Two-sample t-test and wrapper-based feature selection methods (support vector machine recursive feature elimination with cross-validation (SVM-RFECV) and LightGBM's "feature_importances_" function) were used to select important features. The Shapley additive explanations (SHAP) method was used to assign the contribution of features to the best classification effect model.

RESULTS

The best result was obtained from the LinearSVM model trained with the 136 important features selected by SVMRFE-CV. In the nested five-fold cross-validation (consisting of an outer and an inner loop of five-fold cross-validation) of 1611 data, the model achieved the accuracy, sensitivity, and specificity of 68.90 %, 71.75 %, and 65.84 %, respectively. The 136 important features were tested in a small dataset and obtained excellent classification results after balancing the ratio between patients with depression and HCs.

CONCLUSIONS

The combined use of FC and NA features is effective for classifying MDDs and HCs. The important FC and NA features extracted from the large sample dataset have some generalization performance and may be used as a reference for the altered brain functional connectivity networks in MDD.

Transfer Learning from Healthy to Unhealthy Patients for the Automated Classification of Functional Brain Networks in fMRI

Functional Magnetic Resonance Imaging (fMRI) is an essential tool for the pre-surgical planning of brain tumor removal, which allows the identification of functional brain networks to preserve the patient’s neurological functions. One fMRI technique used to identify the functional brain network is the resting-state-fMRI (rs-fMRI). This technique is not routinely available because of the necessity to have an expert reviewer who can manually identify each functional network. The lack of sufficient unhealthy data has so far hindered a data-driven approach based on machine learning tools for full automation of this clinical task. In this article, we investigate the possibility of such an approach via the transfer learning method from healthy control data to unhealthy patient data to boost the detection of functional brain networks in rs-fMRI data. The end-to-end deep learning model implemented in this article distinguishes seven principal functional brain networks using fMRI images. The best performance of a 75% correct recognition rate is obtained from the proposed deep learning architecture, which shows its superiority over other machine learning algorithms that were equally tested for this classification task. Based on this best reference model, we demonstrate the possibility of boosting the results of our algorithm with transfer learning from healthy patients to unhealthy patients. This application of the transfer learning technique opens interesting possibilities because healthy control subjects can be easily enrolled for fMRI data acquisition since it is non-invasive. Consequently, this process helps to compensate for the usual small cohort of unhealthy patient data. This transfer learning approach could be extended to other medical imaging modalities and pathology.

The Interplay between Vitamin D, Exposure of Anticholinergic Antipsychotics and Cognition in Schizophrenia

Vitamin D deficiency is a frequent finding in schizophrenia and may contribute to neurocognitive dysfunction, a core element of the disease. However, there is limited knowledge about the neuropsychological profile of vitamin D deficiency-related cognitive deficits and their underlying molecular mechanisms. As an inductor of cytochrome P450 3A4, a lack of vitamin D might aggravate cognitive deficits by increased exposure to anticholinergic antipsychotics. This cross-sectional study aims to assess the relationship between 25-OH-vitamin D-serum concentrations, anticholinergic drug exposure and neurocognitive functioning (Brief Assessment of Cognition in Schizophrenia, BACS, and Trail Making Test, TMT) in 141 patients with schizophrenia. The anticholinergic drug exposure was estimated by adjusting the concentration of each drug for its individual muscarinic receptor affinity. Using regression analysis, we observed a positive relationship between vitamin D levels and processing speed (TMT-A and BACS Symbol Coding) as well as executive functioning (TMT-B and BACS Tower of London). Moreover, a negative impact of vitamin D on anticholinergic drug exposure emerged, but the latter did not significantly affect cognition. When other cognitive items were included as regressors, the impact of vitamin D remained only significant for the TMT-A. Among the different cognitive impairments in schizophrenia, vitamin D deficiency may most directly affect processing speed, which in turn may aggravate deficits in executive functioning. This finding is not explained by a cytochrome P450-mediated increased exposure to anticholinergic antipsychotics.

Early Markers in Resistant Schizophrenia: Effect of the First Antipsychotic Drug

Background: Schizophrenia is a mental illness with a multifactorial etiology and clinical presentation. Treatment is mainly with antipsychotic drugs. Despite the increasing number of antipsychotic drugs, there has been no significant change in the percentage of resistant cases. These data gave us reason to look for a link between the effect of the first individually selected antipsychotic drug and the established resistance to therapy. Method: An assessment has been made of 105 patients with chronic schizophrenia with consecutive psychotic episodes. The choice of antipsychotic has been made on the basis of clinical features, history of efficacy of previously used neuroleptics, anthropometric features, as well as somatic comorbidities. Accidental use of benzodiazepines in anxiety conditions as well as correctors in indications for extrapyramidal problems have been reported. Assessment was made based on clinical observation as well as on changes in PANSS score. Results: Of the 105 observed patients, the effectiveness of the first antipsychotic effect was found in 46.7% of patients. Follow-up of patients for a period of 12 weeks revealed that 45 (42.8%) of them had resistant schizophrenia, while the remaining 60 (57.2%) achieved clinical remission and initial functional recovery. The effect of the first antipsychotic drug was established in 9 (20%) of the patients with resistant schizophrenia and in 40 (66.57%) of the patients in clinical remission. Conclusion: The evaluation of the first antipsychotic medication is significant for the prognosis of patients with schizophrenia. Its lack of effectiveness indicates a high probability of resistance and can be a good indicator of earlier change and a possible search for more “aggressive” measures to prevent future resistance and possible disability.

Gray matter, white matter and cerebrospinal fluid abnormalities in Parkinson's disease: A voxel-based morphometry study

BACKGROUND

Parkinson's disease (PD) is a chronic neurodegenerative disorder characterized by bradykinesia, tremor, and rigidity among other symptoms. With a 70% cumulative prevalence of dementia in PD, cognitive impairment and neuropsychiatric symptoms are frequent.

MATERIALS AND METHODS

In this study, we looked at anatomical brain differences between groups of patients and controls. A total of 138 people with PD were compared to 64 age-matched healthy people using voxel-based morphometry (VBM). VBM is a fully automated technique that allows for the identification of regional differences in gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) allowing for an objective comparison of brains of different groups of people. We used statistical parametric mapping for image processing and statistical analysis.

RESULTS

In comparison to controls, PD patients had lower GM volumes in the left middle cingulate, left lingual gyrus, right calcarine and left fusiform gyrus, also PD patients indicated lower WM volumes in the right middle cingulate, left lingual gyrus, right calcarine, and left inferior occipital gyrus. Moreover, PD patients group demonstrated higher CSF in the left caudate compared to the controls.

CONCLUSION

Physical fragility and cognitive impairments in PD may be detected more easily if anatomical abnormalities to the cingulate gyrus, occipital lobe and the level of CSF in the caudate are identified. Thus, our findings shed light on the role of the brain in PD and may aid in a better understanding of the events that occur in PD patients.

Comparative Analysis of Lateral Preferences in Patients With Resistant Schizophrenia

BACKGROUND

Schizophrenia is a chronic brain disorder of diverse etiology and clinical presentation. Despite the expansion of treatment methods, between 30 and 50% of cases remain resistant to treatment. In patients with schizophrenia, specifics in the dominant lateralization in the brain function have been discovered. This gave a reason to seek the relation between functional lateralization and the effect of treatment.

METHODS

Of the 105 people observed with schizophrenia, 45 (42.9%) were treatment resistant, and 60 (57.1%) were considered responders. We compared functional lateralization (hand, foot, and eye) between the two groups. Handedness was ascertained by using the Edinburgh Handedness Inventory. The assessment was made at 12 weeks of treatment.

RESULTS

Of all patients with schizophrenia, 41.89% have mixed lateralization, 53.34% are right winged, and 4.76% of the patients are left winged. Resistance of the symptoms shows that 26 (57.78%) are cross-dominated, 18 (40%) are right winged, and 1 (2.22%) is left winged. In patients with clinical remission, 18 (30%) are of mixed dominance, 38 (63.33%) are right winged, and 4 (6.66%) are left winged. From the results for the separate lateralization of the hand, foot, and eye, we found a significant difference only in terms of the dominance of the eye. In 44 (41.9%) of the patients, we found dominance of the left eye. In patients with resistance, the percentage established by us is higher-at 26 (57.8%). These results indicate that the increased percentage of mixed dominance in patients with schizophrenia is mainly due to left-sided lateralization of the eye, especially in those with resistance to treatment.

CONCLUSION

We find an increased number of patients with cross-dominance left eye dominance in patients with schizophrenia. Cross-dominance and left eye dominance are associated with a higher probability of symptom resistance than other forms of lateralization (left-handed or right-handed). The high percentage of cross-dominance is due to the high percentage of left-sided dominance of the eye.

Altered striatal functional connectivity and structural dysconnectivity in individuals with bipolar disorder: A resting state magnetic resonance imaging study

OBJECTIVE

Bipolar disorder (BD) is a mood swing illness characterized by episodes ranging from depressive lows to manic highs. Although the specific origin of BD is unknown, genetics, environment, and changes in brain structure and chemistry may all have a role. Through magnetic resonance imaging (MRI) evaluations, this study looked into functional abnormalities involving the striatum between BD group and healthy controls (HC), compared the whole-brain gray matter (GM) morphological patterns between the groups and see whether functional connectivity has its underlying structural basis.

MATERIALS AND METHODS

We applied sliding windows to functional magnetic resonance imaging (fMRI) data from 49 BD patients and 44 HCs to generate temporal correlations maps to determine strength and variability of the striatum-to-whole-brain-network functional connectivity (FC) in each window whilst also employing voxel-based morphometry (VBM) to high-resolution structural MRI data to uncover structural differences between the groups.

RESULTS

Our analyses revealed increased striatal connectivity in three consecutive windows 69, 70, and 71 (180, 182, and 184 s) in individuals with BD (p < 0.05; Bonferroni corrected) in fMRI images. Moreover, the VBM findings of structural images showed gray matter (GM) deficits in the left precentral gyrus and middle frontal gyrus of the BD patients (p = 0.001, uncorrected) when compared to HCs. Variability of striatal connectivity did not reveal significant differences between the groups.

CONCLUSION

These findings revealed that BD was associated with a weakening of the precentral gyrus and middle frontal gyrus, also implying that bipolar illness may be linked to striatal functional brain alterations.

Dissociative Model in Patients With Resistant Schizophrenia

BACKGROUND

Schizophrenia is a severe mental illness in which, despite the growing number of antipsychotics from 30 to 50% of patients remain resistant to treatment. Many resistance factors have been identified. Dissociation as a clinical phenomenon is associated with a loss of integrity between memories and perceptions of reality. Dissociative symptoms have also been found in patients with schizophrenia of varying severity. The established dispersion of the degree of dissociation in patients with schizophrenia gave us reason to look for the connection between the degree of dissociation and resistance to therapy.

METHODS

The type of study is correlation analysis. 106 patients with schizophrenia were evaluated. Of these, 45 with resistant schizophrenia and 60 with clinical remission. The Positive and Negative Syndrome Scale (PANSS) and Brief Psychiatric Rating Scale (BPRS) scales were used to assess clinical symptoms. The assessment of dissociative symptoms was made with the scale for dissociative experiences (DES). Statistical methods were used to analyze the differences in results between the two groups of patients.

RESULTS

Patients with resistant schizophrenia have a higher level of dissociation than patients in remission. This difference is significant and demonstrative with more than twice the level of dissociation in patients with resistant schizophrenia.The level of dissociation measured in patients with resistant schizophrenia is as high as the points on the DES in dissociative personality disorder.

CONCLUSION

Patients with resistant schizophrenia have a much higher level of dissociation than patients in clinical remission. The established difference between the two groups support to assume that resistance to the administered antipsychotics is associated with the presence of high dissociation in the group of resistant patients. These results give us explanation to think about therapeutic options outside the field of antipsychotic drugs as well as to consider different strategies earlier in the diagnostic process.

Gender-associated role in patients with schizophrenia. Is there a connection with the resistance?

Schizophrenia is a chronic mental illness observed with equal prevalence in different cultures and ethnic groups. The clinical picture relates to behavior and social adaptation. A significant percentage of patients, despite the implementation of various therapeutic interventions, remain resistant to the ongoing treatment. Occupying a certain gender role depends both on biological belonging and on the way of self-perception characteristic of the given person. Self-perception reflects gender identification, which in social aspect is determined by the choice of social activities performed. Changes in behavior and social adaptation in patients with schizophrenia led us to conduct a study to analyze the perceived gender role in patients with schizophrenia, looking for differences between patients with treatment resistance and those in clinical remission.

MATERIALS AND METHODS

A total of 105 patients with schizophrenia were analyzed. Of them, 45 were with resistant symptoms and 60 in clinical remission. The clinical analysis of the patients was carried out using the PANSS and BPRS scales. The evaluation of the choice of social activity related to a particular gender was done with the Bem Sex-Role Inventory (BSRI).

RESULTS

Out of all 105 patients with schizophrenia, in 80/76.19%/we found a higher identification with the female role, 17/16.19%/made an association with the male role and in 8/7.61%/patients we found the same results, i.e., with both the male and female roles. Among the patients with treatment resistant schizophrenia (TRS)-45, 34/75.56%/identified more with the female gender role, 6/13.33/perceived the male gender role as active, and in 5/11.11%/the identification was equal both with the male and with the female roles. Among the patients in clinical remission (CR)-60, 46/76.67%/accepted the female role as active, 11/18.33/identified with the male one, and three/5%/accepted both roles equally. When assessing the relationship between biological sex and perceived gender role, it was found that among men/a total of 39/half identified with the female gender role and half with the male gender role. Among women/a total of 66/, 90% perceived the female gender role, 7%-the male and 3% equally the male and the female gender role. No relationship was found between the choice of a certain gender role and the onset of psychosis and its duration in the observed patients.

CONCLUSION

We found a higher percentage of schizophrenic patients who showed higher identification with the female gender role. Approximately half of the males identified with the female gender role. Resistance had no influence on the choice of sex-associated social activity. Factors related to the course of the schizophrenia process such as age of onset of psychosis and duration of psychosis was not associated with an influence on identification with sex-associated social activity. Our research suggests that identification with a particular sex associative social activity is most likely established earlier in the prodromal period.