Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium.

Subcortical structures, which include the basal ganglia and parts of the limbic system, have key roles in learning, motor control and emotion, but also contribute to higher-order executive functions. Prior studies have reported volumetric alterations in subcortical regions in schizophrenia. Reported results have sometimes been heterogeneous, and few large-scale investigations have been conducted. Moreover, few large-scale studies have assessed asymmetries of subcortical volumes in schizophrenia. Here, as a work completely independent of a study performed by the ENIGMA consortium, we conducted a large-scale multisite study of subcortical volumetric differences between patients with schizophrenia and controls. We also explored the laterality of subcortical regions to identify characteristic similarities and differences between them. T1-weighted images from 1680 healthy individuals and 884 patients with schizophrenia, obtained with 15 imaging protocols at 11 sites, were processed with FreeSurfer. Group differences were calculated for each protocol and meta-analyzed. Compared with controls, patients with schizophrenia demonstrated smaller bilateral hippocampus, amygdala, thalamus and accumbens volumes as well as intracranial volume, but larger bilateral caudate, putamen, pallidum and lateral ventricle volumes. We replicated the rank order of effect sizes for subcortical volumetric changes in schizophrenia reported by the ENIGMA consortium. Further, we revealed leftward asymmetry for thalamus, lateral ventricle, caudate and putamen volumes, and rightward asymmetry for amygdala and hippocampal volumes in both controls and patients with schizophrenia. Also, we demonstrated a schizophrenia-specific leftward asymmetry for pallidum volume. These findings suggest the possibility of aberrant laterality in neural pathways and connectivity patterns related to the pallidum in schizophrenia.

Conditional False Discovery Rate Analysis Of Genome-Wide Association Studies Uncovers Genetic LOCI Shared Between Schizophrenia And Volumes Of Hippocampus, Putamen And Intracranial Volume

Reduced hippocampal volume is a consistently described structural abnormality in schizophrenia but its cause and timing are not known. To examine the relationship of duration of schizophrenic illness and treatment effects with hippocampal volumes. Quantitative 1.5 T magnetic resonance imaging brain scans of young male patients in the early stage of schizophrenic illness were compared with those of chronically ill older patients. Scans were also acquired for controls matched to both patient groups for age and handedness. Duration of illness was recorded and severity of symptoms assessed with the Positive and Negative Syndrome Scale. The patients with schizophrenia had smaller hippocampal volumes than the controls. The volume reduction was larger in older patients than in young, compared with age-matched controls. In the early illness group atypical antipsychotics rather than haloperidol were associated with larger hippocampal volumes even after controlling for differences in illness severity. The greater reduction of hippocampal volume in people with chronic v. early illness, after controlling for illness severity and age, supports the hypothesis of progressive hippocampal reduction in males with schizophrenia. Atypical antipsychotics early in illness may protect against this.

Early‐onset psychosis disorders are serious mental disorders arising before the age of 18 years. Here, we investigate the largest neuroimaging dataset, to date, of patients with early‐onset psychosis and healthy controls for differences in intracranial and subcortical brain volumes. The sample included 263 patients with early‐onset psychosis (mean age: 16.4 ± 1.4 years, mean illness duration: 1.5 ± 1.4 years, 39.2% female) and 359 healthy controls (mean age: 15.9 ± 1.7 years, 45.4% female) with magnetic resonance imaging data, pooled from 11 clinical cohorts. Patients were diagnosed with early‐onset schizophrenia (n = 183), affective psychosis (n = 39), or other psychotic disorders (n = 41). We used linear mixed‐effects models to investigate differences in intracranial and subcortical volumes across the patient sample, diagnostic subgroup and antipsychotic medication, relative to controls. We observed significantly lower intracranial (Cohen's d = −0.39) and hippocampal (d = −0.25) volumes, and higher caudate (d = 0.25) and pallidum (d = 0.24) volumes in patients relative to controls. Intracranial volume was lower in both early‐onset schizophrenia (d = −0.34) and affective psychosis (d = −0.42), and early‐onset schizophrenia showed lower hippocampal (d = −0.24) and higher pallidum (d = 0.29) volumes. Patients who were currently treated with antipsychotic medication (n = 193) had significantly lower intracranial volume (d = −0.42). The findings demonstrate a similar pattern of brain alterations in early‐onset psychosis as previously reported in adult psychosis, but with notably low intracranial volume. The low intracranial volume suggests disrupted neurodevelopment in adolescent early‐onset psychosis.

163. Third ventricle enlargement and developmental delay in first episode schizophrenia

Specific brain structural abnormalities in first-episode schizophrenia.: A comparative study with patients with schizophreniform disorder, non-schizophrenic non-affective psychoses and healthy volunteers.

BackgroundIndividuals with schizophrenia show significant brain morphological abnormalities. The ENIGMA consortium identified that patients with schizophrenia had smaller hippocampus, amygdala, thalamus, accumbens and intracranial volumes.1 Reduced hippocampal volume is one of the most consistent findings in schizophrenia research.2–4 Also, Previous research has reported differences in hippocampal volume and white matter integrity in young adolescents who report psychotic experiences.5,6 However there has been little longitudinal research to investigate the developmental trajectory of these regions in adolescence with an increased susceptibility to psychotic disorders.Aimsto investigate two-year longitudinal changes in hippocampal volume in a sample of adolescents who reported psychotic experiences relative to their peers. To investigate the role of presence of co-morbid DSM IV mental disorders and stressful life events in influencing hippocampal volume and study the differences in hippocampus volume between adolescents who were having persistent symptoms versus adolescents with remitting symptoms.MethodsA longitudinal case-control study of 50 community-based adolescents aged 13–16 years (25 with psychotic experiences and a matched sample of 25 without psychotic experiences), compared hippocampal volume. All participants were assessed at baseline and two years follow up. T1 weighted anatomical high-resolution imaging and high angular resolution diffusion imaging data were used to conduct quantitative anatomical volumetric evaluations of global hippocampal volume. Clinical interviews also provided information on psychotic experiences, co-morbid disorders and adverse life events.ResultsThere were significant differences in the Right and Left Whole hippocampus between PE and Control group at baseline and 2-year follow up (p≤ 0.05). There were significant differences between PE persist and Control group in the left and right whole hippocampus (p≤ 0.05).DiscussionThe differences identified in our study suggest that early hippocampal reductions, may play a role in increasing vulnerability to psychosis.

A multi-scanner study of subcortical brain volume abnormalities in schizophrenia

Structural abnormality in schizophrenia versus bipolar disorder: A whole brain cortical thickness, surface area, volume and gyrification analyses.

Pediatric hydrocephalus requires evaluation while accounting for growth of the intracranial structures, but information on choroid plexus growth in children is lacking. This study aimed to create normal growth curves for intracranial volume, choroid plexus volume, and lateral ventricles volume. Additionally, the authors aimed to objectively assess the degree of hydrocephalus caused by choroid plexus hyperplasia (CPH) and to examine the impact of surgical procedures. This retrospective study analyzed the head CT scans of pediatric patients with minor head trauma treated at Osaka Women's and Children's Hospital between March 2006 and May 2023. The study segmented and calculated intracranial, choroid plexus, and lateral ventricles volumes. The study also calculated the correlation coefficients among these 3 parameters. Patients aged 0 to 10 years were divided into 15 age-related clusters, and mean ± SD values were calculated for each cluster. Growth curves were created by plotting mean values sequentially. Volume obtained from patients with CPH were z-normalized using mean and SD values and compared. A total of 229 CT scans (94 from females) were analyzed, and positive correlations were observed among intracranial volume, choroid plexus volume, and lateral ventricles volume, with the strongest correlation between the choroid plexus and lateral ventricles volumes. The growth rate of intracranial volume was rapid until approximately 20 months of age, while those of choroid plexus volume and lateral ventricles volume increased rapidly until approximately 1 year of age. Subsequently, choroid plexus volume and lateral ventricles volume plateaued at 1.5 ml and 10 ml, respectively. Three patients with CPH were enrolled and quantitatively evaluated on the basis of the z-normalized volume. Notable abnormal volumes of the choroid plexus (range z-normalized values 24.11-51.17) and lateral ventricles (46.78-122.36) were observed. In 2 patients, improvements in the z-normalized values of intracranial volume and lateral ventricles volume were observed after surgical interventions. Additionally, in 1 patient, choroid plexus volume was reduced by approximately 24% (range z-normalized values 51.17-38.93) after bilateral endoscopic plexus coagulation. This study provides normal growth curves for intracranial volume, choroid plexus volume, and lateral ventricles volume. Knowledge of these normal values holds the potential for objective assessment of abnormal values associated with hydrocephalus and choroid plexus diseases such as CPH.

Psychiatric disorders as well as subcortical brain volumes are highly heritable. Large-scale genome-wide association studies (GWASs) for these traits have been performed. We investigated the genetic correlations between five psychiatric disorders and the seven subcortical brain volumes and the intracranial volume from large-scale GWASs by linkage disequilibrium score regression. We revealed weak overlaps between the genetic variants associated with psychiatric disorders and subcortical brain and intracranial volumes, such as in schizophrenia and the hippocampus and bipolar disorder and the accumbens. We confirmed shared aetiology and polygenic architecture across the psychiatric disorders and the specific subcortical brain and intracranial volume.

Schizophrenia (SCZ) is associated with differences in subcortical brain volumes and intracranial volume (ICV). However, little is known about the underlying etiology of these brain alterations. Here, we explored whether brain structure volumes and SCZ share genetic risk factors. Using conditional false discovery rate (FDR) analysis, we integrated genome-wide association study (GWAS) data on SCZ (n = 82315) and GWAS data on 7 subcortical brain volumes and ICV (n = 11840). By conditioning the FDR on overlapping associations, this statistical approach increases power to discover genetic loci. To assess the credibility of our approach, we studied the identified loci in larger GWAS samples on ICV (n = 26577) and hippocampal volume (n = 26814). We observed polygenic overlap between SCZ and volumes of hippocampus, putamen, and ICV. Based on conjunctional FDR < 0.05, we identified 2 loci shared between SCZ and ICV implicating genes FOXO3 (rs10457180) and ITIH4 (rs4687658), 2 loci shared between SCZ and hippocampal volume implicating SLC4A10 (rs4664442) and SPATS2L (rs1653290), and 2 loci shared between SCZ and volume of putamen implicating DCC (rs4632195) and DLG2 (rs11233632). The loci shared between SCZ and hippocampal volume or ICV had not reached significance in the primary GWAS on brain phenotypes. Proving our point of increased power, 2 loci did reach genome-wide significance with ICV (rs10457180) and hippocampal volume (rs4664442) in the larger GWAS. Three of the 6 identified loci are novel for SCZ. Altogether, the findings provide new insights into the relationship between SCZ and brain structure volumes, suggesting that their genetic architectures are not independent.

Brain tissue segmentation on structural Magnetic Resonance Imaging (MRI) has received considerable attention. Quantitative analysis of MR images of the brain is of interest in order to study the aging brain in epidemiological studies, to better understand how diseases affect the brain and to support diagnosis in clinical practice. Manual quantitative analysis of brain imaging data is a tedious and time-consuming procedure, prone to observer variability. Therefore, there is a large interest in automatic analysis of MR brain imaging data, especially segmentation of Cerebrospinal Fluid (CSF), Gray Matter (GM) and White Matter (WM). This paper presents a fully automated method for the segmentation of cerebrospinal fluid and internal brain nuclei from T1-weighted MRI head scans. The proposed methodology performs intensity based thresholding to get the boundaries between gray matter, white matter, cerebrospinal fluid and others. Combined with preprocessing techniques and incorporating mathematical morphology, we first perform the extraction of brain cortex. Subsequently, the cerebrospinal fluid is segmented by using orthogonal polynomial transform. Finally, the gray matter and the white matter regions in the MRI are segmented based on the intensity values. Experimental results show that the proposed method achieves reasonably good segmentation. The comparative analysis depicts that the proposed methodology shows better segmentation results with some other existing techniques like FAST, SPM5, k-nearest neighbor (k-NN) classifier, and a conventional k-NN.

Objective: The present study examined whole-brain structural abnormalities in schizophrenia, with a special focus on the anterior and posterior cingulate cortex (ACC, PCC) as this is an understudied issue in schizophrenia. Method: Whole-brain voxel-based morphometry analyses of gray matter (GM) and white matter (WM) were performed to detect volumetric differences between 14 patients with schizophrenia and 14 healthy controls matched for age, sex, educational level and parents' educational level. We examined within-group GM and WM correlations and completed the analysis with measurements of sulci in medial cortical areas. Results: Compared with the healthy controls, the schizophrenic patients showed significant decreases in GM volumes in the ACC and PCC, and in neighboring WM regions such as the corpus callosum and the fimbriae of the fornix. Moreover, the patient group also displayed a negative correlation between volumes of GM and WM in the ACC. Finally, the patients showed significantly reduced volumes in the right cingulate sulci and left inferior frontal sulci. Conclusion: Our results replicate typical brain-structural abnormalities with new findings in the medial prefrontal cortex, suggested to be a key region in this disorder.

Identifying generalizable brain imaging markers from large multi-center datasets remains challenging due to varying statistical aggregation approaches and p-hacking with increasing big data. We hypothesized that effect size (ES) inference surpasses P-value-based inference in reliably identifying core brain damage of schizophrenia, regardless of whether Mega- or Meta-analyses are used. We examined voxel-wise inter-group differences in gray matter volume (GMV) based on individual data from 976 schizophrenia patients and 801 healthy controls across 16 datasets, along with published coordinates data from 103 studies involving 5151 patients and 5438 controls, using Mega-analysis (Mega), Image-Based Meta-analysis (IBMA), and Coordinate-Based Meta-analysis (CBMA) under P-value and ES inference frameworks, respectively. We then compared the performances of different statistical aggregation (Mega, IBMA, and CBMA) and statistical inference (P-value and ES) strategies in revealing brain abnormalities in schizophrenia. P-value Mega identified significant GMV abnormalities in nearly all gray matter voxels (94.85%) with high sensitivity to sample size; in contrast, ES Mega detected core abnormalities in only 24.63% of voxels that had large ES and manifested higher resistance to sample size. ES IBMA and CBMA also demonstrated superior detection performance and were less affected by sample size than P-value ones. Finally, IBMA exhibited comparable performance with the Mega-analysis and superior performance than all types of CBMAs. These results underscore the advantages of using ES inference in multi-center statistical aggregation and highlight the potential of IBMA for enhanced detection of brain structural abnormalities in schizophrenia.