Progressive brain structural changes after the first year of treatment in first-episode treatment-naive patients with deficit or nondeficit schizophrenia

Topological Perturbations in the Functional Connectome Support the Deficit/Non-deficit Distinction in Antipsychotic Medication-Naïve First Episode Psychosis Patients

BACKGROUND

Heterogeneity in the etiology, pathophysiology, and clinical features of schizophrenia challenges clinicians and researchers. A helpful approach could be stratifying patients according to the presence or absence of clinical features of the deficit syndrome (DS). DS is characterized by enduring and primary negative symptoms, a clinically less heterogeneous subtype of the illness, and patients with features of DS are thought to present abnormal brain network characteristics, however, this idea has received limited attention. We investigated functional brain network topology in patients displaying deficit features and those who do not.

DESIGN

We applied graph theory analytics to resting-state functional magnetic resonance imaging data of 61 antipsychotic medication-naïve first episode psychosis patients, 18 DS and 43 non-deficit schizophrenia (NDS), and 72 healthy controls (HC). We quantified small-worldness, global and nodal efficiency measures, shortest path length, nodal local efficiency, and synchronization and contrasted them among the 3 groups.

RESULTS

DS presented decreased network integration and segregation compared to HC and NDS. DS showed lower global efficiency, longer global path lengths, and lower global local efficiency. Nodal efficiency was lower and the shortest path length was longer in DS in default mode, ventral attention, dorsal attention, frontoparietal, limbic, somatomotor, and visual networks compared to HC. Compared to NDS, DS showed lower efficiency and longer shortest path length in default mode, limbic, somatomotor, and visual networks.

CONCLUSIONS

Our data supports increasing evidence, based on topological perturbations of the functional connectome, that deficit syndrome may be a distinct form of the illness.

Profiling gut microbiota signatures associated with the deficit subtype of schizophrenia: Findings from a case-control study

BACKGROUND

Previous studies have reported a variety of gut microbiota alterations in patients with schizophrenia. However, none of these studies has investigated gut microbiota in patients with the deficit subtype of schizophrenia (D-SCZ) that can be characterized by primary and enduring negative symptoms. Therefore, in this study we aimed to profile gut microbiota of individuals with D-SCZ, compared to those with non-deficit schizophrenia (ND-SCZ) and healthy controls (HCs).

METHODS

A total of 115 outpatients (44 individuals with D-SCZ and 71 individuals with ND-SCZ) during remission of positive and disorganization symptoms as well as 120 HCs were enrolled. Gut microbiota was analyzed using the 16 rRNA amplicon sequencing. Additionally, the levels of C-reactive protein (CRP), glucose and lipid metabolism markers were determined in the peripheral blood samples.

RESULTS

Altogether 14 genera showed differential abundance in patients with D-SCZ compared to ND-SCZ and HCs, including Candidatus Soleaferrea, Eubacterium, Fusobacterium, Lachnospiraceae UCG-002, Lachnospiraceae UCG-004, Lachnospiraceae UCG-010, Libanicoccus, Limosilactobacillus, Mogibacterium, Peptococcus, Prevotella, Prevotellaceae NK3B31 group, Rikenellaceae RC9 gut group, and Slackia after adjustment for potential confounding factors. Observed alterations were significantly associated with cognitive performance in both groups of patients. Moreover, several significant correlations of differentially abundant genera with the levels of CRP, lipid profile parameters, glucose and insulin were found across all subgroups of participants.

CONCLUSION

Findings from the present study indicate that individuals with D-SCZ show a distinct profile of gut microbiota alterations that is associated with cognitive performance, metabolic parameters and subclinical inflammation.

Altered brain functional networks in schizophrenia with persistent negative symptoms: an activation likelihood estimation meta-analysis

Objective

To investigate brain structural and functional characteristics of three brain functional networks including default mode network (DMN), central executive network (CEN), and salience network (SN) in persistent negative symptoms (PNS) patients.

Methods

We performed an activation likelihood estimation (ALE) meta-analysis of functional connectivity (FC) studies and voxel-based morphometry (VBM) studies to detect specific structural and functional alterations of brain networks between PNS patients and healthy controls.

Results

Seventeen VBM studies and twenty FC studies were included. In the DMN, PNS patients showed decreased gray matter in the bilateral medial frontal gyrus and left anterior cingulate gyrus and a significant reduction of FC in the right precuneus. Also, PNS patients had a decrease of gray matter in the left inferior parietal lobules and medial frontal gyrus, and a significant reduction of FC in the bilateral superior frontal gyrus in the CEN. In comparison with healthy controls, PNS patients exhibited reduced gray matter in the bilateral insula, anterior cingulate gyrus, left precentral gyrus and right claustrum and lower FC in these brain areas in the SN, including the left insula, claustrum, inferior frontal gyrus and extra-nuclear.

Conclusion

This meta-analysis reveals brain structural and functional imaging alterations in the three networks and the interaction among these networks in PNS patients, which provides neuroscientific evidence for more personalized treatment.Systematic Review RegistrationThe PROSPERO (https://www.crd.york.ac.uk/PROSPERO/, registration number: CRD42022335962).

Brain Hemispheric Asymmetry in Schizophrenia and Bipolar Disorder

BACKGROUND

This study aimed to compare brain asymmetry in patients with schizophrenia (SCZ), bipolar disorder (BPD), and healthy controls to test whether asymmetry patterns could discriminate and set boundaries between two partially overlapping severe mental disorders.

METHODS

We applied a fully automated voxel-based morphometry (VBM) approach to assess structural brain hemispheric asymmetry in magnetic resonance imaging (MRI) anatomical scans in 60 participants (SCZ = 20; BP = 20; healthy controls = 20), all right-handed and matched for gender, age, and education.

RESULTS

Significant differences in gray matter asymmetry were found between patients with SCZ and BPD, between SCZ patients and healthy controls (HC), and between BPD patients and HC. We found a higher asymmetry index (AI) in BPD patients when compared to SCZ in Brodmann areas 6, 11, and 37 and anterior cingulate cortex and an AI higher in SCZ patients when compared to BPD in the cerebellum.

CONCLUSION

Our study found significant differences in brain asymmetry between patients with SCZ and BPD. These promising results could be translated to clinical practice, given that structural brain changes detected by MRI are good candidates for exploration as biological markers for differential diagnosis, besides helping to understand disease-specific abnormalities.

The effect of initial antipsychotic treatment on hippocampal and amygdalar volume in first-episode schizophrenia is influenced by age

BACKGROUND

Antipsychotic treatment has been shown to yield hippocampal and amygdalar volumetric changes in first-episode schizophrenia (FES). However, whether antipsychotic induced volumetric changes interact with age remains unclear.

METHODS

The current study includes data from 120 medication naïve FES patients and 110 matched healthy controls (HC). Patients underwent MRI scans before (T1) and after (T2) antipsychotic treatment. HCs underwent MRI scans at baseline only. The hippocampus and amygdala were segmented via Freesurfer 7. General linear models were conducted to investigate the effect of age by diagnosis interaction on baseline volume. Linear mixed models (LMM) were used to detect the effect of age on volumetric changes from pre to post treatment in FES.

RESULTS

GLM revealed a trending effect (F = 3.758, p = 0.054) of age by diagnosis interaction on the baseline volume of the left (whole) hippocampus, with older FES patients showing smaller hippocampal volumes, relative to HC, when controlled sex, education years, and ICV. LMM showed a significant age by time-point interaction effect (F = 4.194, estimate effect = -1.964, p = 0.043) on left hippocampal volume in all FES and significant time effect(F = 6.608,T1-T2(estimate effect) = 62.486, p = 0.011), whereby younger patients showed greater hippocampal volumetric decreases following treatment. At the subfield level, a significant time effect emerged in left molecular_layer_HP (F = 4.509,T1-T2(estimate effect) = 12.424, p = 0.032, FDR corrected) and left cornu ammonis(CA)4 (F = 4.800,T1-T2(estimate effect) = 7.527, p = 0.046, FDR corrected), implying volumetric reduction after treatment in these subfields.

CONCLUSIONS

Our findings suggest that age plays an important role in the neuroplastic mechanisms of initial antipsychotics on the hippocampus and amygdala of schizophrenia.

Using support vector machine to explore the difference of function connection between deficit and non-deficit schizophrenia based on gray matter volume

Objective

Schizophrenia can be divided into deficient schizophrenia (DS) and non-deficient schizophrenia (NDS) according to the presence of primary and persistent negative symptoms. So far, there are few studies that have explored the differences in functional connectivity (FC) between the different subtypes based on the region of interest (ROI) from GMV (Gray matter volume), especially since the characteristics of brain networks are still unknown. This study aimed to investigate the alterations of functional connectivity between DS and NDS based on the ROI obtained by machine learning algorithms and differential GMV. Then, the relationships between the alterations and the clinical symptoms were analyzed. In addition, the thalamic functional connection imbalance in the two groups was further explored.

Methods

A total of 16 DS, 31 NDS, and 38 health controls (HC) underwent resting-state fMRI scans, patient group will further be evaluated by clinical scales including the Brief Psychiatric Rating Scale (BPRS), the Scale for the Assessment of Negative Symptoms (SANS), and the Scale for the Assessment of Positive Symptoms (SAPS). Based on GMV image data, a support vector machine (SVM) is used to classify DS and NDS. Brain regions with high weight in the classification were used as seed points in whole-brain FC analysis and thalamic FC imbalance analysis. Finally, partial correlation analysis explored the relationships between altered FC and clinical scale in the two subtypes.

Results

The relatively high classification accuracy is obtained based on the SVM. Compared to HC, the FC increased between the right inferior parietal lobule (IPL.R) bilateral thalamus, and lingual gyrus, and between the right inferior temporal gyrus (ITG.R) and the Salience Network (SN) in NDS. The FC between the right thalamus (THA.R) and Visual network (VN), between ITG.R and right superior occipital gyrus in the DS group was higher than that in HC. Furthermore, compared with NDS, the FC between the ITG.R and the left superior and middle frontal gyrus decreased in the DS group. The thalamic FC imbalance, which is characterized by frontotemporal-THA.R hypoconnectivity and sensory motor network (SMN)-THA.R hyperconnectivity was found in both subtypes. The FC value of THA.R and SMN was negatively correlated with the SANS score in the DS group but positively correlated with the SAPS score in the NDS group.

Conclusion

Using an SVM classification method and based on an ROI from GMV, we highlighted the difference in functional connectivity between DS and NDS from the local to the brain network, which provides new information for exploring the neural physiopathology of the two subtypes of schizophrenic.

Meta-analysis of structural and functional brain abnormalities in schizophrenia with persistent negative symptoms using activation likelihood estimation

BACKGROUND

Persistent negative symptoms (PNS) include both primary and secondary negative symptoms that persist after adequate treatment, and represent an unmet therapeutic need. Published magnetic resonance imaging (MRI) evidence of structural and resting-state functional brain abnormalities in schizophrenia with PNS has been inconsistent. Thus, the purpose of this meta-analysis is to identify abnormalities in structural and functional brain regions in patients with PNS compared to healthy controls.

METHODS

We systematically searched PubMed, Web of Science, and Embase for structural and functional imaging studies based on five research methods, including voxel-based morphometry (VBM), diffusion tensor imaging (DTI), functional connectivity (FC), the amplitude of low-frequency fluctuation or fractional amplitude of low-frequency fluctuation (ALFF/fALFF), and regional homogeneity (ReHo). Afterward, we conducted a coordinate-based meta-analysis by using the activation likelihood estimation algorithm.

RESULTS

Twenty-five structural MRI studies and thirty-two functional MRI studies were included in the meta-analyses. Our analysis revealed the presence of structural alterations in patients with PNS in some brain regions including the bilateral insula, medial frontal gyrus, anterior cingulate gyrus, left amygdala, superior temporal gyrus, inferior frontal gyrus, cingulate gyrus and middle temporal gyrus, as well as functional differences in some brain regions including the bilateral precuneus, thalamus, left lentiform nucleus, posterior cingulate gyrus, medial frontal gyrus, and superior frontal gyrus.

CONCLUSION

Our study suggests that structural brain abnormalities are consistently located in the prefrontal, temporal, limbic and subcortical regions, and functional alterations are concentrated in the thalamo-cortical circuits and the default mode network (DMN). This study provides new insights for targeted treatment and intervention to delay further progression of negative symptoms.

SYSTEMATIC REVIEW REGISTRATION

[https://www.crd.york.ac.uk/prospero/], identifier [CRD42022338669].

The Effects of Antipsychotic Treatment on the Brain of Patients With First-Episode Schizophrenia: A Selective Review of Longitudinal MRI Studies

A large number of neuroimaging studies have detected brain abnormalities in first-episode schizophrenia both before and after treatment, but it remains unclear how these abnormalities reflect the effects of antipsychotic treatment on the brain. To summarize the findings in this regard and provide potential directions for future work, we reviewed longitudinal structural and functional imaging studies in patients with first-episode schizophrenia before and after antipsychotic treatment. A total of 36 neuroimaging studies was included, involving 21 structural imaging studies and 15 functional imaging studies. Both anatomical and functional brain changes in patients after treatment were consistently observed in the frontal and temporal lobes, basal ganglia, limbic system and several key components within the default mode network (DMN). Alterations in these regions were affected by factors such as antipsychotic type, course of treatment, and duration of untreated psychosis (DUP). Over all we showed that: (a) The striatum and DMN were core target regions of treatment in schizophrenia, and their changes were related to different antipsychotics; (b) The gray matter of frontal and temporal lobes tended to reduce after long-term treatment; and (c) Longer DUP was accompanied with faster hippocampal atrophy after initial treatment, which was also associated with poorer outcome. These findings are in accordance with previous notions but should be interpreted with caution. Future studies are needed to clarify the effects of different antipsychotics in multiple conditions and to identify imaging or other biomarkers that may predict antipsychotic treatment response. With such progress, it may help choose effective pharmacological interventional strategies for individuals experiencing recent-onset schizophrenia.

Anatomic abnormalities of hippocampal subfields in never-treated and antipsychotic-treated patients with long-term schizophrenia

Hippocampal volume deficits have been reported in chronically-treated schizophrenia patients, however, the longer-term effects of antipsychotic medications on hippocampal anatomy are unclear. This case-control study investigated volume differences in hippocampal subfields of never-treated and antipsychotic-treated patients with long-term schizophrenia. High spatial-resolution T1-weighted magnetic resonance images were collected from 29 never-treated and 40 antipsychotic-treated patients with long-term schizophrenia matched for illness duration (all ≥ 5 years), and 40 demographically-matched healthy controls. Hippocampal subfield volumes were measured using FreeSurfer v6.0, compared across groups and between hemispheres, and correlated with clinical features. Volume reductions were found in both patient groups compared to healthy controls in 8 of 26 hippocampal subfields (Cohen's d = 0.46 - 1.17, P = < .001 - .03), and more diffusely and obviously in never-treated than treated patients (Cohen's d = 0.50 - 0.90, P = < .001 - .04). Greater right-than-left volumes were seen in treated patients and healthy controls in 11 of 13 subfields (T = 2.30 - 7.29, P = < .001 - .03), but not in never-treated patients, in whom the volumes were reduced more on the right than on the left. Subfield volumes were negatively correlated with symptom severity and illness duration, and declined with age in never-treated patients. Findings indicate clinically-relevant and age-related volume reductions in hippocampal subfields of never-treated patients with long-term schizophrenia. Broader and greater subfield deficits in never-treated than treated patients, especially in the right hippocampus, suggest that long-term antipsychotic treatment may benefit hippocampal structures over the longer-term course of illness.

Gray Matter Changes in the Insular Cortex During the Course of the Schizophrenia Spectrum

Progressive gray matter reductions in the insular cortex have been reported in the early phases of schizophrenia (Sz); however, the trajectory of these reductions during the course of the illness currently remains unclear. Furthermore, it has not yet been established whether patients with schizotypal (SzTypal) features exhibit progressive changes in the insular cortex. This follow-up magnetic resonance imaging study examined volume changes in the short and long insular cortices (mean inter-scan interval = 2.6 years) of 23 first-episode (FE) and 17 chronic patients with Sz, 14 with SzTypal disorder, and 21 healthy controls. Baseline comparisons revealed smaller insular cortex volumes bilaterally in Sz patients (particularly in the chronic group) than in SzTypal patients and healthy controls. FESz patients showed significantly larger gray matter reductions in the insular cortex over time (left: -3.4%/year; right: -2.9%/year) than those in healthy controls (-0.1%/year for both hemispheres) without the effect of subregion or antipsychotic medication, whereas chronic Sz (left: -1.5%/year; right: -1.6%/year) and SzTypal (left: 0.5%/year; right: -0.6%/year) patients did not. Active atrophy of the right insular cortex during FE correlated with fewer improvements in positive symptoms in the Sz groups, while mild atrophy of the left insular cortex during the chronic phase was associated with the severity of negative symptoms in the follow-up period. The present results support dynamic volumetric changes in the insular cortex being specific to overt Sz among the spectrum disorders examined and their degree and role in symptomatology appear to differ across the illness stages.