Hippocampal Subfield Volumes and Cognitive Function in Schizophrenia and Mood Disorders.

INTRODUCTION: The hippocampus is relevant to cognitive function in schizophrenia (SCZ) and mood disorder patients. Although not anatomically uniform, it is clearly divided into subfields. This study aimed to elucidate the relationship between hippocampal subfield volume and cognitive function in patients with SCZ, bipolar disorder (BP), and major depressive disorder (MDD). METHODS: The study included 21 patients with SCZ, 22 with BP, and 21 with MDD and 25 healthy controls (HCs). Neurocognitive function was assessed using the Brief Assessment of Cognition in Schizophrenia. We obtained hippocampal subfield volumes using FreeSurfer 6.0. We compared the volumes of the hippocampal subfield between the 4 groups and ascertained correlation between the cognitive composite score and hippocampal subfield volume in each group. RESULTS: The SCZ group had significantly lower cognitive composite score than the BP, MDD, and HC groups. In the SCZ group, the left and right hippocampus-amygdala transition area and right subiculum and right presubiculum volumes were significantly reduced compared to those in the HC group. The left presubiculum volumes in the SCZ group were significantly reduced compared to those in the MDD group. Subfield volumes did not significantly differ between the BP, MDD, and HC groups. Interestingly, in the SCZ group, volumes of the right CA1, right molecular layer of the hippocampus, and right granule cell and molecular layer of the dentate gyrus were significantly correlated with the cognitive composite score. CONCLUSION: Patients with SCZ had poorer cognitive function, which is related to their hippocampal pathology, than those with mood disorders.

Aberrant brain dynamics of large-scale functional networks across schizophrenia and mood disorder.

INTRODUCTION: The dynamics of large-scale networks, which are known as distributed sets of functionally synchronized brain regions and include the visual network (VIN), somatomotor network (SMN), dorsal attention network (DAN), salience network (SAN), limbic network (LIN), frontoparietal network (FPN), and default mode network (DMN), play important roles in emotional and cognitive processes in humans. Although disruptions in these large-scale networks are considered critical for the pathophysiological mechanisms of psychiatric disorders, their role in psychiatric disorders remains unknown. We aimed to elucidate the aberrant dynamics across large-scale networks in patients with schizophrenia (SZ) and mood disorders. METHODS: We performed energy-landscape analysis to investigate the aberrant brain dynamics of seven large-scale networks across 50 healthy controls (HCs), 36 patients with SZ, and 42 patients with major depressive disorder (MDD) recruited at Wakayama Medical University. We identified major patterns of brain activity using energy-landscape analysis and estimated their duration, occurrence, and ease of transition. RESULTS: We identified four major brain activity patterns that were characterized by the activation patterns of the DMN and VIN (state 1, DMN (-) VIN (-); state 2, DMN (+) VIN (+); state 3, DMN (-) VIN (+); and state 4, DMN (+) VIN (-)). The duration of state 1 and the occurrence of states 1 and 2 were shorter in the SZ group than in HCs and the MDD group, and the duration of state 3 was longer in the SZ group. The ease of transition between states 3 and 4 was larger in the SZ group than in the HCs and the MDD group. The ease of transition from state 3 to state 4 was negatively associated with verbal fluency in patients with SZ. The current study showed that the brain dynamics was more disrupted in SZ than in MDD. CONCLUSIONS: Energy-landscape analysis revealed aberrant brain dynamics across large-scale networks between SZ and MDD and their associations with cognitive abilities in SZ, which cannot be captured by conventional functional connectivity analyses. These results provide new insights into the pathophysiological mechanisms underlying SZ and mood disorders.

Female sex and age-based advantage of simulated electric field in TMS to the prefrontal cortex in schizophrenia and mood disorders.

This study investigates computational models of electric field strength for transcranial magnetic stimulation (TMS) of the left dorsolateral prefrontal cortex (DLPFC) based on individual MRI data of patients with schizophrenia (SZ), major depressive disorder (MDD), bipolar disorder (BP), and healthy controls (HC). In addition, it explores the association of electric field intensities with age, gender and intracranial volume. The subjects were 23 SZ (12 male, mean age = 45.30), 24 MDD (16 male, mean age = 43.57), 23 BP (16 male, mean age = 39.29), 23 HC (13 male, mean age = 40.91). Based on individual MRI sequences, electric fields were computationally modeled by two independent investigators using SimNIBS ver. 2.1.1. There was no significant difference in electric field strength between the groups (HC vs SZ, HC vs MDD, HC vs BP, SZ vs MDD, SZ vs BP, MDD vs BP). Female subjects showed higher electric field intensities in widespread areas than males, and age was positively significantly associated with electric field strength in the left parahippocampal area as observed. Our results suggest differences in electric field strength of left DLPFC TMS for gender and age. It may open future avenues for individually modeling TMS based on structural MRI data.

Structural connectivity between the hippocampus and cortical/subcortical area relates to cognitive impairment in schizophrenia but not in mood disorders.

Cognitive impairment in schizophrenia and other psychiatric disorders is a challenge to be overcome in order to maintain patients' quality of life and social function. The neurological pathogenesis of cognitive impairment requires further elucidation. In general, the hippocampus interacts between the cortical and subcortical areas for information processing and consolidation and has an important role in memory. We examined the relationship between structural connectivity of the hippocampus and cortical/subcortical areas and cognitive impairment in schizophrenia, major depressive disorder and bipolar disorder. Subjects comprised 21 healthy controls, 19 patients with schizophrenia, 20 patients with bipolar disorder and 18 patients with major depressive disorder. Diffusion-weighted tensor images data were processed using ProbtrackX2 to calculate the structural connectivity between the hippocampus and cortical/subcortical areas. Cognitive function was assessed using the Brief Assessment of Cognition in schizophrenia composite score. Hippocampal structural connectivity index was significantly correlated with composite score in the schizophrenia group but not in the healthy control, major depressive disorder or bipolar disorder groups. There were no statistically significant differences in hippocampal structural connectivity index between the four groups. Structural connectivity between the hippocampus and cortical/subcortical areas is suggested to be a pathophysiological mechanism of comprehensive cognitive impairment in schizophrenia.

Impact of individual factors and personality trait on psychological problems of family members living with staff of a COVID-19 frontline hospital: A cross-sectional self-administered anonymous questionnaire survey.

Aim: This study aims to evaluate the association between individual factors/personality traits and depression and anxiety in family members living with staff working on the frontline of COVID-19 care. Methods: The subjects were family members over the age of 15 years living with staff members of a COVID-19 frontline hospital. Between March 27 and April 11, 2021, 204 self-administered anonymous questionnaires were distributed, and 149 responses were received. Symptoms of depression and anxiety were assessed using the Hospital Anxiety and Depression Scale (HADS). Personality trait was assessed using the Big Five personality traits, and fear of COVID-19 was assessed using the Fear of COVID-19 Scale. We examined associations between HADS depression or anxiety scores with individual background factors, scores of Big Five personality traits, and Fear of COVID-19 Scale. Results: The participants with anxiety had significantly higher scores for neuroticism and for the Fear of COVID-19 Scale. The participants with depression had significantly lower scores for extraversion and higher scores for the Fear of COVID-19 Scale. No individual background factors were significantly associated with HADS depression or anxiety scores. Conclusion: Among family members of staff of a COVID-19 frontline hospital, lower extraversion, higher neuroticism, and fear of COVID-19 were associated with anxiety and depression. This questionnaire survey was conducted before wide-spread rollout of COVID-19 vaccination, so the findings of this study are expected to be applicable to other future novel infectious outbreaks.

Schizophrenia after remission of anti-NMDA receptor encephalitis.

N-methyl-D-aspartate receptor (NMDAR) dysfunction is an attractive hypothesis regarding the etiology of schizophrenia. We present the unprecedented case of a woman diagnosed with schizophrenia without anti-NMDAR antibodies after history of NMDAR encephalitis. A first episode of psychosis was antibody-positive and was improved with steroid and immunoglobulin treatment. Second and third episodes were antibody-negative, each about three months postpartum (different pregnancies) and were improved with antipsychotics. Without NMDAR encephalitis-related findings, we diagnosed schizophrenia. After anti-NMDAR encephalitis, NMDAR dysfunction may decrease the threshold for the onset of psychosis. This case provides insight into NMDAR dysfunction on etiology of schizophrenia.

Computational modeling of electric fields for prefrontal tDCS across patients with schizophrenia and mood disorders.

This cross-diagnostic study aims to computationally model electric field (efield) for prefrontal transcranial direct current stimulation in mood disorders and schizophrenia. Enrolled were patients with major depressive disorder (n = 23), bipolar disorder (n = 24), schizophrenia (n = 23), and healthy controls (n = 23). The efield was simulated using SimNIBS software (ver.2.1.1). Electrodes were placed at the left and right prefrontal areas and the current intensity was set to 2 mA intensity. Schizophrenia and major depressive disorder groups showed significantly lower 99.5th percentile efield strength than healthy controls. In voxel-wise analysis, patients with schizophrenia showed a significant reduction of simulated efield strength in the bilateral frontal lobe, cerebellum and brain stem compared with healthy controls. Among the patients with schizophrenia, reduction of simulated efield strength was not significantly correlated with psychiatric symptoms or global functioning. The patients with bipolar disorder showed no significant difference in simulated efield strength compared with healthy controls, and there was no significant difference between the clinical groups. Our results suggest attenuated electrophysiological response to transcranial direct current stimulation to the prefrontal cortex in patients with schizophrenia, and to some extent in patients with major depressive disorder.

A case of autoimmune autonomic ganglionopathy with prolonged delirium.

Autoimmune autonomic ganglionopathy (AAG) is a rare acquired immune-mediated disorder that leads to autonomic failure. It is sometimes complicated by mental and behavioral symptoms. We report a case of 72-year-old male with AAG who was admitted to the psychiatric department for prolonged severe delirium. Repeated loss of consciousness attributed to severe orthostatic hypotension disturbed recovery from delirium. In addition, intracerebral hemorrhage occurred during hospitalization, and this cerebrovascular event may have been substantially affected by unstable blood pressure due to AAG. This case suggests importance of differential diagnosis of AAG in patients with mental and behavioral symptoms accompanying severe autonomic failure.