Hippocampal subfield and amygdala nuclei volumes in schizophrenia patients with a history of violence

Selective disrupted gray matter volume covariance of amygdala subregions in schizophrenia

Objective

Although extensive structural and functional abnormalities have been reported in schizophrenia, the gray matter volume (GMV) covariance of the amygdala remain unknown. The amygdala contains several subregions with different connection patterns and functions, but it is unclear whether the GMV covariance of these subregions are selectively affected in schizophrenia.

Methods

To address this issue, we compared the GMV covariance of each amygdala subregion between 807 schizophrenia patients and 845 healthy controls from 11 centers. The amygdala was segmented into nine subregions using FreeSurfer (v7.1.1), including the lateral (La), basal (Ba), accessory-basal (AB), anterior-amygdaloid-area (AAA), central (Ce), medial (Me), cortical (Co), corticoamygdaloid-transition (CAT), and paralaminar (PL) nucleus. We developed an operational combat harmonization model for 11 centers, subsequently employing a voxel-wise general linear model to investigate the differences in GMV covariance between schizophrenia patients and healthy controls across these subregions and the entire brain, while adjusting for age, sex and TIV.

Results

Our findings revealed that five amygdala subregions of schizophrenia patients, including bilateral AAA, CAT, and right Ba, demonstrated significantly increased GMV covariance with the hippocampus, striatum, orbitofrontal cortex, and so on (permutation test, P< 0.05, corrected). These findings could be replicated in most centers. Rigorous correlation analysis failed to identify relationships between the altered GMV covariance with positive and negative symptom scale, duration of illness, and antipsychotic medication measure.

Conclusion

Our research is the first to discover selectively impaired GMV covariance patterns of amygdala subregion in a large multicenter sample size of patients with schizophrenia.

Brain structural alterations associated with impulsiveness in male violent patients with schizophrenia

BACKGROUND

Violence in schizophrenia (SCZ) is a phenomenon associated with neurobiological factors. However, the neural mechanisms of violence in patients with SCZ are not yet sufficiently understood. Thus, this study aimed to explore the structural changes associated with the high risk of violence and its association with impulsiveness in patients with SCZ to reveal the possible neurobiological basis.

METHOD

The voxel-based morphometry approach and whole-brain analyses were used to measure the alteration of gray matter volume (GMV) for 45 schizophrenia patients with violence (VSC), 45 schizophrenia patients without violence (NSC), and 53 healthy controls (HC). Correlation analyses were used to examine the association of impulsiveness and brain regions associated with violence.

RESULTS

The results demonstrated reduced GMV in the right insula within the VSC group compared with the NSC group, and decreased GMV in the right temporal pole and left orbital part of superior frontal gyrus only in the VSC group compared to the HC group. Spearman correlation analyses further revealed a positive correlation between impulsiveness and GMV of the left superior temporal gyrus, bilateral insula and left medial orbital part of the superior frontal gyrus in the VSC group.

CONCLUSION

Our findings have provided further evidence for structural alterations in patients with SCZ who had engaged in severe violence, as well as the relationship between the specific brain alterations and impulsiveness. This work provides neural biomarkers and improves our insight into the neural underpinnings of violence in patients with SCZ.

Genetic architecture of hippocampus subfields volumes in Alzheimer's disease

BACKGROUND

The hippocampus is a heterogeneous structure, comprising histologically and functionally distinguishable hippocampal subfields. The volume reductions in hippocampal subfields have been demonstrated to be linked with Alzheimer's disease (AD). The aim of our study is to investigate the hippocampal subfields' genetic architecture based on the Alzheimer's Disease Neuroimaging Initiative (ADNI) data set.

METHODS

After preprocessing the downloaded genetic variants and imaging data from the ADNI database, a co-sparse reduced rank regression model was applied to analyze the genetic architecture of hippocampal subfields volumes. Homology modeling, docking, molecular dynamics simulations, and Co-IP experiments for protein-protein interactions were used to verify the function of target protein on hippocampal subfields successively. After that, the association analysis between the candidated genes on the hippocampal subfields volume and clinical scales were performed.

RESULTS

The results of the association analysis revealed five unique genetic variants (e.g., ubiquitin-specific protease 10 [USP10]) changed in nine hippocampal subfields (e.g., the granule cell and molecular layer of the dentate gyrus [GC-ML-DG]). Among five genetic variants, USP10 had the strongest interaction effect with BACE1, which affected hippocampal subfields verified by MD and Co-IP experiments. The results of association analysis between the candidated genes on the hippocampal subfields volume and clinical scales showed that candidated genes influenced the volume and function of hippocampal subfields.

CONCLUSIONS

Current evidence suggests that hippocampal subfields have partly distinct genetic architecture and may improve the sensitivity of the detection of AD.

The Hippocampal Subfield Volume Reduction and Plasma Biomarker Changes in Mild Cognitive Impairment and Alzheimer's Disease

Background

The hippocampus consists of histologically and functionally distinct subfields, which shows differential vulnerabilities to Alzheimer's disease (AD)-associated pathological changes.

Objective

To investigate the atrophy patterns of the main hippocampal subfields in patients with mild cognitive impairment (MCI) and AD and the relationships among the hippocampal subfield volumes, plasma biomarkers and cognitive performance.

Methods

This cross-sectional study included 119 patients stratified into three categories: normal cognition (CN; N = 40), MCI (N = 39), and AD (N = 40). AD-related plasma biomarkers were measured, including amyloid-β (Aβ)42, Aβ40, Aβ42/Aβ40 ratio, p-tau181, and p-tau217, and the hippocampal subfield volumes were calculated using automated segmentation and volumetric procedures implemented in FreeSurfer.

Results

The subiculum body, cornu ammonis (CA) 1-head, CA1-body, CA4-body, molecular_layer_HP-head, molecular_layer_HP-body, and GC-ML-DG-body volumes were smaller in the MCI group than in the CN group. The subiculum body and CA1-body volumes accurately distinguished MCI from CN (area under the curve [AUC] = 0.647-0.657). The subiculum-body, GC-ML-DG-body, CA4-body, and molecular_layer_HP-body volumes accurately distinguished AD from MCI (AUC = 0.822-0.833) and AD from CN (AUC = 0.903-0.905). The p-tau 217 level served as the best plasma indicator of AD and correlated with broader hippocampal subfield volumes. Moreover, mediation analysis demonstrated that the subiculum-body volume mediated the associations between the p-tau217 and p-tau181 levels, and the Montreal Cognitive Assessment and Auditory Verbal Learning Test recognition scores.

Conclusions

Hippocampal subfields with distinctive atrophy patterns may mediate the effects of tau pathology on cognitive function. The subiculum-body may be the most clinically meaningful hippocampal subfield, which could be an effective target region for assessing disease progression.

Dose-Dependent Atrophy in Bilateral Amygdalae and Nuclei After Brain Radiation Therapy and Its Association With Mood and Memory Outcomes on a Longitudinal Clinical Trial

PURPOSE

Amygdalae are bilateral, almond-shaped structures located anterior to the hippocampi, critical to limbic system functions of emotional processing and memory consolidation. The amygdalae are heterogeneous, composed of multiple nuclei with distinct structural and functional properties. We prospectively assessed associations between longitudinal changes in amygdala morphometry, including component nuclei, and functional outcomes in patients with primary brain tumors receiving radiation therapy (RT).

METHODS AND MATERIALS

On a prospective longitudinal trial, 63 patients underwent high-resolution volumetric brain magnetic resonance imaging and testing for mood (Beck Depression Inventory and Beck Anxiety Inventory), memory (Brief Visuospatial Memory Test-Revised [BVMT] Total Recall and Delayed Recall; Hopkins Verbal Learning Test-Revised [HVLT] Total Recall and Delayed Recall), and health-related quality-of-life outcomes (Functional Assessment of Cancer Therapy-Brain Social/Family Well-Being and Emotional Well-Being) at baseline and 3, 6, and 12 months after RT. Amygdalae, including 8 nuclei, were autosegmented bilaterally using validated techniques. Linear mixed-effects models assessed longitudinal change in amygdalae and nuclei volumes and associations with dose and outcomes. Wilcoxon rank sum tests compared amygdala volume change between patient groups with worse and more stable outcomes at each time point.

RESULTS

Atrophy was found in the right amygdala at 6 months (P = .001) and the left amygdala at 12 months (P = .046). A higher dose was associated with atrophy of the left amygdala (P = .013) at 12 months. The right amygdala showed dose-dependent atrophy at 6 months (P = .016) and 12 months (P = .001). Worse BVMT-Total, HVLT-Total, and HVLT-Delayed performance was associated with smaller left lateral (P = .014, P = .004, and P = .007, respectively) and left basal (P = .034, P = .016, and P = .026, respectively) nuclei volumes. Increased anxiety at 6 months was associated with greater combined (P = .031) and right (P = .007) amygdala atrophy. Greater left amygdala atrophy (P = .038) was noted in patients with decreased emotional well-being at 12 months.

CONCLUSIONS

Bilateral amygdalae and nuclei undergo time- and dose-dependent atrophy after brain RT. Atrophy in amygdalae and specific nuclei was associated with poorer memory, mood, and emotional well-being. Amygdalae-sparing treatment planning may preserve neurocognitive and neuropsychiatric outcomes in this population.

Differential alterations of amygdala nuclei volumes in acutely ill patients with anorexia nervosa and their associations with leptin levels

BACKGROUND

The amygdala is a subcortical limbic structure consisting of histologically and functionally distinct subregions. New automated structural magnetic resonance imaging (MRI) segmentation tools facilitate the in vivo study of individual amygdala nuclei in clinical populations such as patients with anorexia nervosa (AN) who show symptoms indicative of limbic dysregulation. This study is the first to investigate amygdala nuclei volumes in AN, their relationships with leptin, a key indicator of AN-related neuroendocrine alterations, and further clinical measures.

METHODS

T1-weighted MRI scans were subsegmented and multi-stage quality controlled using FreeSurfer. Left/right hemispheric amygdala nuclei volumes were cross-sectionally compared between females with AN (n = 168, 12-29 years) and age-matched healthy females (n = 168) applying general linear models. Associations with plasma leptin, body mass index (BMI), illness duration, and psychiatric symptoms were analyzed via robust linear regression.

RESULTS

Globally, most amygdala nuclei volumes in both hemispheres were reduced in AN v. healthy control participants. Importantly, four specific nuclei (accessory basal, cortical, medial nuclei, corticoamygdaloid transition in the rostral-medial amygdala) showed greater volumetric reduction even relative to reductions of whole amygdala and total subcortical gray matter volumes, whereas basal, lateral, and paralaminar nuclei were less reduced. All rostral-medially clustered nuclei were positively associated with leptin in AN independent of BMI. Amygdala nuclei volumes were not associated with illness duration or psychiatric symptom severity in AN.

CONCLUSIONS

In AN, amygdala nuclei are altered to different degrees. Severe volume loss in rostral-medially clustered nuclei, collectively involved in olfactory/food-related reward processing, may represent a structural correlate of AN-related symptoms. Hypoleptinemia might be linked to rostral-medial amygdala alterations.

Aberrant brain structure in patients with schizophrenia and violence: A meta-analysis

Previous studies have indicated that schizophrenia is associated with an increased risk of violence, which may constitute a public health concern, leading to poor treatment outcomes and stigmatization of patients. Investigating brain structural features of violence in schizophrenia could help us understand its specific pathogenesis and find effective biomarkers. Our study aimed at identifying reliable brain structural changes associated with violence in patients with schizophrenia by conducting a meta-analysis and meta-regression of magnetic resonance imaging studies. Specific brain changes in patients with schizophrenia and violence (VSZ) were studied, compared with patients with schizophrenia and violence (VSZ), patients with non-violent schizophrenia (NVSZ), and individuals with a history of violence only and health controls. Primary outcomes revealed that there was no significant difference of gray matter volume between patients with VSZ and patient with NVSZ. Compared with controls, patients with VSZ exhibited decreased gray matter volume in the insula, the superior temporal gyrus (STG), the left inferior frontal gyrus, the left parahippocampus, and the right putamen. Compared with individuals with a history of violence only, patients with VSZ exhibited decreased volume in the right insula and the right STG. Meta-regression analysis revealed a negative correlation between the duration of schizophrenia and the volume of the right insula in patients with VSZ. These findings may suggest a shared neurobiological basis for both violence and psychiatric symptoms. The impaired frontotemporal-limbic network may serve as a neurobiological basis for higher prevalence of violent behaviour in patients with schizophrenia. However, it is important to note that these changes are not unique to patients with VSZ. Further investigation is needed to explore the neural mechanism that drive the interaction between violent behaviour and specific aggression-related dimensions of schizophrenia.

Volume alterations of the hippocampus and amygdala in patients with schizophrenia and persistent auditory hallucinations

INTRODUCTION

Auditory hallucinations (AH) are one of the most prevalent symptoms of schizophrenia. They might cause several brain alterations, especially changes in the volumes of hippocampus and amygdala, regions related to the relay and processing of auditory cues and emotional memories.

MATERIAL AND METHODS

We have recruited 41 patients with schizophrenia and persistent AH, 35 patients without AH, and 55 healthy controls. Using their MRIs, we have performed semiautomatic segmentations of the hippocampus and amygdala using Freesurfer. We have also performed bilateral correlations between the total PSYRATS score and the volumes of affected subregions and nuclei.

RESULTS

In the hippocampus, we found bilateral increases in the volume of its hippocampal fissure and decreases in the right fimbria in patients with and without AH. The volume of the right hippocampal tail and left head of the granule cell layer from the dentate gyrus were decreased in patients with AH. In the amygdala, we found its left total volume was shrunk, and there was a decrease of its left accessory basal nucleus in patients with AH.

CONCLUSIONS

We have detected volume alterations of different limbic structures likely due to the presence of AH. The volumes of the right hippocampal tail and left head of the granule cell layer from the dentate gyrus, and total volume of the amygdala and its accessory basal nucleus, were only affected in patients with AH. Bilateral volume alterations in the hippocampal fissure and right fimbria seem inherent of schizophrenia and due to traits not contemplated in our research.

Volume of hippocampus-amygdala transition area predicts outcomes of electroconvulsive therapy in major depressive disorder: high accuracy validated in two independent cohorts

BACKGROUND

Although many previous studies reported structural plasticity of the hippocampus and amygdala induced by electroconvulsive therapy (ECT) in major depressive disorder (MDD), yet the exact roles of both areas for antidepressant effects are still controversial.

METHODS

In the current study, segmentation of amygdala and hippocampal sub-regions was used to investigate the longitudinal changes of volume, the relationship between volume and antidepressant effects, and prediction performances for ECT in MDD patients before and after ECT using two independent datasets.

RESULTS

As a result, MDD patients showed selectively and consistently increased volume in the left lateral nucleus, right accessory basal nucleus, bilateral basal nucleus, bilateral corticoamygdaloid transition (CAT), bilateral paralaminar nucleus of the amygdala, and bilateral hippocampus-amygdala transition area (HATA) after ECT in both datasets, whereas marginally significant increase of volume in bilateral granule cell molecular layer of the head of dentate gyrus, the bilateral head of cornu ammonis (CA) 4, and left head of CA 3. Correlation analyses revealed that increased volume of left HATA was significantly associated with antidepressant effects after ECT. Moreover, volumes of HATA in the MDD patients before ECT could be served as potential biomarkers to predict ECT remission with the highest accuracy of 86.95% and 82.92% in two datasets (The predictive models were trained on Dataset 2 and the sensitivity, specificity and accuracy of Dataset 2 were obtained from leave-one-out-cross-validation. Thus, they were not independent and very likely to be inflated).

CONCLUSIONS

These results not only suggested that ECT could selectively induce structural plasticity of the amygdala and hippocampal sub-regions associated with antidepressant effects of ECT in MDD patients, but also provided potential biomarkers (especially HATA) for effectively and timely interventions for ECT in clinical applications.

Machine Learning Prediction of Estimated Risk for Bipolar Disorders Using Hippocampal Subfield and Amygdala Nuclei Volumes

The pathophysiology of bipolar disorder (BD) remains mostly unclear. Yet, a valid biomarker is necessary to improve upon the early detection of this serious disorder. Patients with manifest BD display reduced volumes of the hippocampal subfields and amygdala nuclei. In this pre-registered analysis, we used structural MRI (n = 271, 7 sites) to compare volumes of hippocampus, amygdala and their subfields/nuclei between help-seeking subjects divided into risk groups for BD as estimated by BPSS-P, BARS and EPIbipolar. We performed between-group comparisons using linear mixed effects models for all three risk assessment tools. Additionally, we aimed to differentiate the risk groups using a linear support vector machine. We found no significant volume differences between the risk groups for all limbic structures during the main analysis. However, the SVM could still classify subjects at risk according to BPSS-P criteria with a balanced accuracy of 66.90% (95% CI 59.2-74.6) for 10-fold cross-validation and 61.9% (95% CI 52.0-71.9) for leave-one-site-out. Structural alterations of the hippocampus and amygdala may not be as pronounced in young people at risk; nonetheless, machine learning can predict the estimated risk for BD above chance. This suggests that neural changes may not merely be a consequence of BD and may have prognostic clinical value.

A significant, functional and replicable risk KTN1 variant block for schizophrenia

Cortical and subcortical structural alteration has been extensively reported in schizophrenia, including the unusual expansion of gray matter volumes (GMVs) of basal ganglia (BG), especially putamen. Previous genome-wide association studies pinpointed kinectin 1 gene (KTN1) as the most significant gene regulating the GMV of putamen. In this study, the role of KTN1 variants in risk and pathogenesis of schizophrenia was explored. A dense set of SNPs (n = 849) covering entire KTN1 was analyzed in three independent European- or African-American samples (n = 6704) and one mixed European and Asian Psychiatric Genomics Consortium sample (n = 56,418 cases vs. 78,818 controls), to identify replicable SNP-schizophrenia associations. The regulatory effects of schizophrenia-associated variants on the KTN1 mRNA expression in 16 cortical or subcortical regions in two European cohorts (n = 138 and 210, respectively), the total intracranial volume (ICV) in 46 European cohorts (n = 18,713), the GMVs of seven subcortical structures in 50 European cohorts (n = 38,258), and the surface areas (SA) and thickness (TH) of whole cortex and 34 cortical regions in 50 European cohorts (n = 33,992) and eight non-European cohorts (n = 2944) were carefully explored. We found that across entire KTN1, only 26 SNPs within the same block (r2 > 0.85) were associated with schizophrenia across ≥ 2 independent samples (7.5 × 10-5 ≤ p ≤ 0.048). The schizophrenia-risk alleles, which increased significantly risk for schizophrenia in Europeans (q < 0.05), were all minor alleles (f < 0.5), consistently increased (1) the KTN1 mRNA expression in 12 brain regions significantly (5.9 × 10-12 ≤ p ≤ 0.050; q < 0.05), (2) the ICV significantly (6.1 × 10-4 ≤ p ≤ 0.008; q < 0.05), (3) the SA of whole (9.6 × 10-3 ≤ p ≤ 0.047) and two regional cortices potentially (2.5 × 10-3 ≤ p ≤ 0.042; q > 0.05), and (4) the TH of eight regional cortices potentially (0.006 ≤ p ≤ 0.050; q > 0.05), and consistently decreased (1) the BG GMVs significantly (1.8 × 10-19 ≤ p ≤ 0.050; q < 0.05), especially putamen GMV (1.8 × 10-19 ≤ p ≤ 1.0 × 10-4; q < 0.05, (2) the SA of four regional cortices potentially (0.010 ≤ p ≤ 0.048), and (3) the TH of four regional cortices potentially (0.015 ≤ p ≤ 0.049) in Europeans. We concluded that we identified a significant, functional, and robust risk variant block covering entire KTN1 that might play a critical role in the risk and pathogenesis of schizophrenia.

Hippocampal subfield alterations in schizophrenia and major depressive disorder: a systematic review and network meta-analysis of anatomic MRI studies

BACKGROUND

Hippocampal disturbances are important in the pathophysiology of both schizophrenia and major depressive disorder (MDD). Imaging studies have shown selective volume deficits across hippocampal subfields in both disorders. We aimed to investigate whether these volumetric alterations in hippocampal subfields are shared or divergent across disorders.

METHODS

We searched PubMed and Embase from database inception to May 8, 2021. We identified MRI studies in patients with schizophrenia, MDD or both, in which hippocampal subfield volumes were measured. We excluded nonoriginal, animal or postmortem studies, and studies that used other imaging modalities or overlapping data. We conducted a network meta-analysis to estimate and contrast alterations in subfield volumes in the 2 disorders.

RESULTS

We identified 45 studies that met the initial criteria for systematic review, of which 15 were eligible for network metaanalysis. Compared to healthy controls, patients with schizophrenia had reduced volumes in the bilateral cornu ammonis (CA) 1, granule cell layer of the dentate gyrus, subiculum, parasubiculum, molecular layer, hippocampal tail and hippocampus-amygdala transition area (HATA); in the left CA4 and presubiculum; and in the right fimbria. Patients with MDD had decreased volumes in the left CA3 and CA4 and increased volumes in the right HATA compared to healthy controls. The bilateral parasubiculum and right HATA were smaller in patients with schizophrenia than in patients with MDD.

LIMITATIONS

We did not investigate medication effects because of limited information. Study heterogeneity was noteworthy in direct comparisons between patients with MDD and healthy controls.

CONCLUSION

The volumes of multiple hippocampal subfields are selectively altered in patients with schizophrenia and MDD, with overlap and differentiation in subfield alterations across disorders. Rigorous head-to-head studies are needed to validate our findings.

Smaller amygdala subnuclei volume in schizophrenia patients with violent behaviors

To investigate the association between the volume of amygdala subnuclei and violent behaviors in patients with schizophrenia (SCZ). In the present study, we recruited 40 SCZ patients with violent behaviors (VS), 26 SCZ patients without violent behaviors (NVS), and 28 matched healthy controls (HC) who completed T1-weighted magnetic resonance imaging. Both the total amygdala and amygdala subnuclei volumes were estimated with FreeSurfer. When comparing the SCZ patients with HC, SCZ patients had a smaller volume of the left basal nucleus (P < 0.05, uncorrected). Further, the VS patients had a smaller volume of the left amygdala central nucleus than the NVS group (P < 0.05, Bonferroni corrected). Our study suggests that a smaller volume of the left amygdala basal nucleus may be a biomarker for SCZ and that a smaller volume of the left central nucleus may be relevant to violence risk in patients with schizophrenia.

Anatomical and molecular features of the amygdalohippocampal transition area and its role in social and emotional behavior processes

The amygdalohippocampal transition area (AHi) has emerged as a critical nucleus of sociosexual behaviors such as mating, parenting, and aggression. The AHi has been overlooked in rodent and human amygdala studies until recently. The AHi is hypothesized to play a role in metabolic and cognitive functions as well as social behaviors based on its connectivity and molecular composition. The AHi is small nucleus rich in neuropeptide and hormone receptors and is contiguous with the ventral subiculum of the hippocampus-hence its designation as a "transition area". Literature focused on the AHi can be difficult to interpret because of changing nomenclature and conflation with neighboring nuclei. Here we summarize what is currently known about AHi structure and development, connections throughout the brain, molecular composition, and functional significance. We aim to delineate current knowledge regarding the AHi, identify potential functions with supporting evidence, and ultimately make clear the importance of the AHi in sociosexual function.

Anxiety in children and youth with autism spectrum disorder and the association with amygdala subnuclei structure

Autism spectrum disorder (ASD) is clinically characterized by social and communication difficulties as well as repetitive behaviors. Many children with ASD also suffer from anxiety, which has been associated with alterations in amygdala structure. In this work, the association between amygdala subnuclei volumes and anxiety was assessed in a cohort of 234 participants (mean age = 11.0 years, SD = 3.9, 95 children with ASD, 139 children were non-autistic). Children underwent magnetic resonance imaging. Amygdala subnuclei volumes were extracted automatically. Anxiety was assessed using the Screen for Child Anxiety Related Disorders, the Child Behavior Checklist, and the Strength and Difficulties Questionnaire. Children with ASD had higher anxiety scores relative to non-autistic children on all anxiety measures (all, p < 0.05). Anxiety levels were significantly predicted in children with ASD by right basal (right: B = 0.235, p = 0.002) and paralaminar (PL) (B = −0.99, p = 0.009) volumes. Basal nuclei receive multisensory information from cortical and subcortical areas and have extensive projections within the limbic system while the PL nuclei are involved in emotional processing. Alterations in basal and PL nuclei in children with ASD and the association with anxiety may reflect morphological changes related to in the neurocircuitry of anxiety in ASD.

Lay abstract

Autism spectrum disorder (ASD) is clinically characterized by social communication difficulties as well as restricted and repetitive patterns of behavior. In addition, children with ASD are more likely to experience anxiety compared with their peers who do not have ASD. Recent studies suggest that atypical amygdala structure, a brain region involved in emotions, may be related to anxiety in children with ASD. However, the amygdala is a complex structure composed of heterogeneous subnuclei, and few studies to date have focused on how amygdala subnuclei relate to in anxiety in this population. The current sample consisted of 95 children with ASD and 139 non-autistic children, who underwent magnetic resonance imaging (MRI) and assessments for anxiety. The amygdala volumes were automatically segmented. Results indicated that children with ASD had elevated anxiety scores relative to peers without ASD. Larger basal volumes predicted greater anxiety in children with ASD, and this association was not seen in non-autistic children. Findings converge with previous literature suggesting ASD children suffer from higher levels of anxiety than non-autistic children, which may have important implications in treatment and interventions. Our results suggest that volumetric estimation of amygdala’s subregions in MRI may reveal specific anxiety-related associations in children with ASD.

Influencing factors of multiple adverse outcomes among schizophrenia patients using count regression models: a cross-sectional study

BACKGROUND

Schizophrenia patients have increased risks of adverse outcomes, including violent crime, aggressiveness, and suicide. However, studies of different adverse outcomes in schizophrenia patients are limited and the influencing factors for these outcomes need clarification by appropriate models. This study aimed to identify influencing factors of these adverse outcomes by examining and comparing different count regression models.

METHODS

This study included schizophrenia patients who had at least one follow-up record in the Guangdong Mental Health Center Network Medical System during 2020. Three types of adverse outcomes were included: a) aggressiveness with police dispatch or violent crime, b) aggressiveness without police dispatch, and c) self-harm or suicide attempts. The incidence density of these adverse outcomes was investigated using the Poisson, negative binomial (NB), zero-inflated Poisson (ZIP), and zero-inflated negative binomial (ZINB) models, accordingly. The best model was chosen based on goodness-of-fit tests. We further analyzed associations between the number of occurrences of adverse outcomes and sociodemographic, clinical factors with the best model.

RESULTS

A total of 130,474 schizophrenia patients were enrolled. Adverse outcomes rates were reported to be less than 1% for schizophrenia patients in 2020, in Guangdong. The NB model performed the best in terms of goodness-of-fit and interpretation when fitting for the number of occurrences of aggressiveness without police dispatch, whereas the ZINB models performed better for the other two outcomes. Age, sex, and history of adverse outcomes were influencing factors shared across these adverse outcomes. Higher education and employment were protective factors for aggressive and violent behaviors. Disease onset aged ≥ 18 years served as a significant risk factor for aggressiveness without police dispatch, and self-harm or suicide attempts. Family history of mental diseases was a risk factor for self-harm or suicide attempts individually.

CONCLUSIONS

NB and ZINB models were selected for fitting the number of occurrences of adverse outcomes among schizophrenia patients in our studies. Influencing factors for the incidence density of adverse outcomes included both those shared across different types and those individual to specific types. Therefore, comprehensive and customized tools in risk assessment and intervention might be necessary.

Intestinal Microbes in Patients With Schizophrenia Undergoing Short-Term Treatment: Core Species Identification Based on Co-Occurrence Networks and Regression Analysis

Schizophrenia, a common mental disorder, has a tremendous impact on the health and economy of people worldwide. Evidence suggests that the microbial-gut-brain axis is an important pathway for the interaction between the gut microbiome and the development of schizophrenia. What is not clear is how changes in the gut microbiota composition and structure during antipsychotic treatment improve the symptoms of schizophrenia. In this study, 25 patients with schizophrenia were recruited. Their fecal samples were collected before and after hospital treatment for 14–19 days. The composition and structure of the intestinal microbiota were evaluated by 16S rRNA sequencing analysis, and the results showed significant differences in fecal microbiota before and after treatment. Firmicutes (relative abundances of 82.60 and 86.64%) and Gemminger (relative abundances of 14.17 and 13.57%) were the first dominant species at the phylum and genus levels, respectively. The random forest algorithm and co-occurrence network analysis demonstrated that intestinal flora (especially the core species ASV57) could be used as biomarkers to distinguish different clinical states and match treatment regimens accordingly. In addition, after fecal microbiota transplantation, antibiotic-treated recipient mice showed multiple behavioral improvements. These included decreased psychomotor hyperactivity, increased social interaction, and memory. In conclusion, this study suggests that differences in the composition and structure of gut microbiota after treatment are associated with the development and severity of schizophrenia. Results may provide a potential target for the treatment of this disorder.

Associations between amygdala nuclei volumes, psychosis, psychopathy, and violent offending

The amygdala is involved in fear perception and aggression regulation, and smaller volumes have been associated with psychotic and non-psychotic violence. We explored the relationship between amygdala nuclei volumes in violent offenders with and without psychosis, and the association to psychopathy traits. 3T MRI scans (n = 204, males, 18-66 years) were obtained from psychotic violent offenders (PSY-V, n = 29), non-psychotic violent offenders (NPV, n = 19), non-violent psychosis patients (PSY-NV, n = 67), and healthy controls (HC, n = 89). Total amygdala and 9 amygdala nuclei volumes were obtained with FreeSurfer. Psychopathy traits were measured with the Psychopathy Checklist-revised (PCL-R). Multivariate analyses explored diagnostic differences in amygdala nuclei volumes and associations to psychosis, violence, and psychopathy traits. PSY-V had a smaller basal nucleus, anterior amygdaloid area, and cortical amygdalar transition area (CATA), whereas PSY-NV had a smaller CATA than HC. Volumes in NPV did not differ from HC, and there were no associations between PCL-R total or factor scores and any of the nuclei or whole amygdala volumes. The lower volumes of amygdala nuclei involved in fear modulation, stress responses, and social interpretation may point towards some mechanisms of relevance to violence in psychosis, but the results warrant replication in larger subject samples.

Structural Deficits in the Frontotemporal Network Associated With Psychopathic Traits in Violent Offenders With Schizophrenia

People with schizophrenia (SZ) are at increased risk of violence compared to the general population. However, the neural mechanisms of violent behavior in patients with SZ are still unclear due to the heterogeneity of the diseased population. In this study, we aimed to examine the neural correlates of violent behavior in SZ and to determine whether the structural deficits were related to psychopathic traits. A total of 113 participants, including 31 SZ patients with violent behavior (vSZ), 39 SZ patients without violent behavior (nvSZ), and 43 healthy controls (HC), completed the T1-weighted magnetic resonance imaging (MRI) scan and were analyzed using voxel-based morphometry approach. The psychopathic traits were assessed using the Psychopathy Checklist: Screening Version (PCL:SV). The results showed decreased gray matter volume (GMV) in the vSZ group in the right temporal lobe and bilateral inferior frontal gyri compared to HCs; while reduced GMV in the inferior parietal lobe, parahippocampal and orbital frontal gyri was found in the nvSZ group compared with HCs. Correlation analyses showed that psychopathic traits were negatively associated with the GMV in the right superior temporal and left fusiform gyri in the vSZ group, indicating that psychopathic traits, as reflected by the score of antisocial factor, might be related to structural deficits in the temporal lobe, which led to a propensity to violent behavior in patients with SZ. Our findings suggest that violent behavior in patients with SZ might have a personality background associated with the frontotemporal network aberrance. In future studies, we need to take a closer look at psychopathic traits for better understanding of the mechanism of interpersonal violence in patients with SZ and to explore whether the imaging findings from this study can serve as a biomarker to predict future violent behaviors and community living.

Identification of violent patients with schizophrenia using a hybrid machine learning approach at the individual level

Despite numerous risk factors associated with violence in patients with schizophrenia, predicting and preventing violent behavior is still a challenge. At present, machine learning (ML) has become a promising strategy for guiding individualized assessment. To build an effective model to predict the risk of violence in patients with schizophrenia, we proposed a hybrid ML method to improve the prediction capability in 42 violent offenders with schizophrenia and 33 non-violent patients with schizophrenia. The results revealed that the final model, which combined multimodal data, achieved the highest prediction performance with an accuracy of 90.67%. Specifically, the model, which fused three modalities of neuroimaging data, achieved a better accuracy than other fused models. In addition, the msot discriminative neuroimaging features involved in the prefrontal-temporal cognitive circuit and striatum reward system, indicating that dysfunction in cortical-subcortical circuits might be associated with high risk of violence in patients with schizophrenia. This study provides the first evidence supporting that the combination of specific multimodal neuroimaging and clinical data in ML analysis can effectively identify violent patients with schizophrenia. Furthermore, this work is crucial for the development of neuro-prediction models that could facilitate individualized treatment and interventions for violent behaviors in patients with schizophrenia.

Candidate symptomatic markers for predicting violence in schizophrenia: A cross-sectional study of 7711 patients in a Chinese population

OBJECTIVE

Violent behaviour is an alarming problem among schizophrenia patients. The effects of historical, clinical, and pathological risk factors for violence have been investigated by multiple studies, but consensus has not been achieved. As psychotic symptoms are more direct and intuitive indicators for violence, identifying robustly associated symptoms is a crucial part of the future prediction and precise management of violent patients in clinics. This study aims to identify the psychotic symptoms correlated with violence among schizophrenia patients in a Chinese population.

METHODS

In this cross-sectional study, the medical records of 7711 schizophrenia patients (4711 in the discovery set and 3000 in the validation set) were collected from 1998 to 2010. Their psychotic symptoms were extracted, and the patients were divided into violent and non-violent groups. Multivariate logistic analysis was applied to identify symptoms associated with violence in the discovery set.

RESULTS

Eight psychotic symptoms were found to be significantly correlated with violence in schizophrenia. "Destruction of property", "verbal aggression" and "insomnia" increased the risk of violence, while "flat affect", "delusion of persecution", "auditory hallucination", "vagueness of thought" and "poverty of thought" decreased the risk of violence. The regression model was evaluated by receiver operating characteristic (ROC) analysis for its discriminatory performance, achieving area under curve (AUC) values of 0.887 in the discovery sample set and 0.824 in the validation sample set.

CONCLUSIONS

The correlated symptoms identified by this study can serve as future candidate predictors for violence in schizophrenia, paving the way for precise management of schizophrenia patients in clinics.

Predicting disease severity in children with combined attention deficit hyperactivity disorder using quantitative features from structural MRI of amygdaloid and hippocampal subfields

OBJECTIVE

Volumetric changes in the amygdaloid and hippocampal subfields have been observed in children with combined attention deficit hyperactivity disorder (ADHD-C). The purpose of this study was to investigate whether volumetric changes in the amygdaloid and hippocampal subfields could be used to predict disease severity in children with ADHD-C.

APPROACH

The data used in this study was from ADHD-200 datasets, a total of 76 ADHD-C patients were included in this study. T1 structural MRI data were used and 64 structural features from the amygdala and hippocampus were extracted. Three ADHD rating scales were used as indicators of ADHD severity. Sequential backward elimination (SBE) algorithm was used for feature selection. A linear support vector regression (SVR) was configured to predict disease severity in children with ADHD-C.

MAIN RESULTS

The three ADHD rating scales could be accurately predicted with the use of SBE-SVR. SBE-SVR achieved the highest accuracy in predicting ADHD index with a correlation of 0.7164 (p < 0.001, tested with 1000-time permutation test). Mean squared error of the SVR was 43.6868, normalized mean squared error was 0.0086, mean absolute error was 3.2893. Several amygdaloid and hippocampal subregions were significantly related to ADHD severity, as revealed by the absolute weight from the SVR model.

SIGNIFICANCE

The proposed SBE-SVR could accurately predict the severity of patients with ADHD-C based on quantitative features extracted from the amygdaloid and hippocampal structures. The results also demonstrated that the two subcortical nuclei could be used as potential biomarkers in the progression and evaluation of ADHD.

In Vivo Amygdala Nuclei Volumes in Schizophrenia and Bipolar Disorders

Abnormalities in amygdala volume are well-established in schizophrenia and commonly reported in bipolar disorders. However, the specificity of volumetric differences in individual amygdala nuclei is largely unknown. Patients with schizophrenia disorders (SCZ, N = 452, mean age 30.7 ± 9.2 [SD] years, females 44.4%), bipolar disorders (BP, N = 316, 33.7 ± 11.4, 58.5%), and healthy controls (N = 753, 34.1 ± 9.1, 40.9%) underwent T1-weighted magnetic resonance imaging. Total amygdala, nuclei, and intracranial volume (ICV) were estimated with Freesurfer (v6.0.0). Analysis of covariance and multiple linear regression models, adjusting for age, age2, ICV, and sex, were fitted to examine diagnostic group and subgroup differences in volume, respectively. Bilateral total amygdala and all nuclei volumes, except the medial and central nuclei, were significantly smaller in patients relative to controls. The largest effect sizes were found for the basal nucleus, accessory basal nucleus, and cortico-amygdaloid transition area (partial η2 > 0.02). The diagnostic subgroup analysis showed that reductions in amygdala nuclei volume were most widespread in schizophrenia, with the lateral, cortical, paralaminar, and central nuclei being solely reduced in this disorder. The right accessory basal nucleus was marginally smaller in SCZ relative to BP (t = 2.32, P = .05). Our study is the first to demonstrate distinct patterns of amygdala nuclei volume reductions in a well-powered sample of patients with schizophrenia and bipolar disorders. Volume differences in the basolateral complex (lateral, basal, and accessory basal nuclei), an integral part of the threat processing circuitry, were most prominent in schizophrenia.