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In schizophrenia, neurocognitive subtypes can be distinguished based on cognitive performance and they are associated with neuroanatomical alterations. We investigated the existence of cognitive subtypes in shortly medicated recent onset psychosis patients, their underlying gray matter volume patterns and clinical characteristics. We used a K-means algorithm to cluster 108 psychosis patients from the multi-site EU PRONIA (Prognostic tools for early psychosis management) study based on cognitive performance and validated the solution independently (N = 53). Cognitive subgroups and healthy controls (HC; n = 195) were classified based on gray matter volume (GMV) using Support Vector Machine classification. A cognitively spared (N = 67) and impaired (N = 41) subgroup were revealed and partially independently validated (Nspared = 40, Nimpaired = 13). Impaired patients showed significantly increased negative symptomatology (pfdr = 0.003), reduced cognitive performance (pfdr < 0.001) and general functioning (pfdr < 0.035) in comparison to spared patients. Neurocognitive deficits of the impaired subgroup persist in both discovery and validation sample across several domains, including verbal memory and processing speed. A GMV pattern (balanced accuracy = 60.1%, p = 0.01) separating impaired patients from HC revealed increases and decreases across several fronto-temporal-parietal brain areas, including basal ganglia and cerebellum. Cognitive and functional disturbances alongside brain morphological changes in the impaired subgroup are consistent with a neurodevelopmental origin of psychosis. Our findings emphasize the relevance of tailored intervention early in the course of psychosis for patients suffering from the likely stronger neurodevelopmental character of the disease.

Abstract 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.

Abstract The recent renaissance of psychedelic science has reignited interest in the similarity of drug-induced experiences to those more commonly observed in psychiatric contexts such as the schizophrenia-spectrum. This report from a multidisciplinary working group of the International Consortium on Hallucinations Research (ICHR) addresses this issue, putting special emphasis on hallucinatory experiences. We review evidence collected at different scales of understanding, from pharmacology to brain-imaging, phenomenology and anthropology, highlighting similarities and differences between hallucinations under psychedelics and in the schizophrenia-spectrum disorders. Finally, we attempt to integrate these findings using computational approaches and conclude with recommendations for future research.

Background and Hypothesis Early prediction of treatment response to antipsychotics in schizophrenia remains a challenge in clinical practice. This study aimed to investigate if brain morphometries including gray matter volume and cortical thickness could serve as potential predictive biomarkers in first-episode schizophrenia. Study Design Sixty-eight drug-naïve first-episode patients underwent baseline structural MRI scans and were subsequently randomized to receive a single antipsychotic throughout the first 12 weeks. Assessments for symptoms and social functioning were conducted by eight “core symptoms” selected from the Positive and Negative Syndrome Scale (PANSS-8) and the Personal and Social performance scale (PSP) multiple times during follow-ups. Treatment outcome was evaluated as subject-specific slope coefficients for PANSS-8 and PSP scores using linear mixed model. LASSO regression model were conducted to examine the performance of baseline gray matter volume and cortical thickness in prediction of individualized treatment outcome. Study Results The study showed that individual brain morphometries at baseline, especially the orbitofrontal, temporal and parietal cortex, pallidum and amygdala, significantly predicted 12-week treatment outcome of PANSS-8 (r[predicted vs observed] = 0.49, P = .001) and PSP (r[predicted vs observed] = 0.40, P = .003) in first-episode schizophrenia. Moreover, the gray matter volume performed better than cortical thickness in the prediction the symptom changes (P = .034), while cortical thickness outperformed gray matter volume in the prediction of outcome of social functioning (P = .029). Conclusions These findings provide initial evidence that brain morphometry have potential to be used as prognostic predictors for antipsychotic response in patients, encouraging the future investigation of the translational value of these measures in precision psychiatry.

The experience of auditory verbal hallucinations in schizophrenia is associated with changes in brain network function. In particular, studies indicate altered functional coupling between nodes of the language and default mode networks. Neurofeedback based on real-time functional magnetic resonance imaging (rtfMRI) can be used to modulate such aberrant network connectivity. We investigated resting-state connectivity changes after neurofeedback (NF) in 21 patients with schizophrenia and 35 healthy individuals. All participants underwent two days of neurofeedback training of important nodes of the left-hemispheric language network including the inferior frontal gyrus (IFG) and posterior superior temporal gyrus (pSTG). In a double-blind randomized cross-over design, participants learned to down- and up-regulate their brain activation in the designated target regions based on NF. Prior to and after each training day, a resting state measurement took place. Coupling between nodes of the language and the default mode network (DMN) selectively increased after down-as compared to up-regulation NF. Network analyses revealed more pronounced increases in functional connectivity between nodes of the language network and the DMN in patients compared to healthy individuals. In particular, down-regulation NF led to increased coupling between nodes of the language network and bilateral inferior parietal lobe (IPL) as well as posterior cingulate cortex (PCC)/precuneus in patients. Up-regulation strengthened connectivity with the medial prefrontal cortex (mPFC). Improved well-being four weeks after the training predicted increased functional coupling between the left IFG and left IPL. Modulatory effects emerged as increased internetwork communication, indicating that down-regulation NF selectively enhances coupling between language and DM network nodes in patients with AVH. RtfMRI NF may thus be used to modulate brain network function that is relevant to the phenomenology of AVH. Specific effects of self-regulation on symptom improvement have to be explored in therapeutic interventions.

Auditory hallucinations (AHs) are debilitating and often treatment‐resistant symptoms of schizophrenia (SZ). Real‐time functional magnetic resonance imaging (fMRI) neurofeedback (NFB) is emerging as a flexible brain circuit‐based tool for targeting AH via self‐modulation of brain activity. A better understanding of what baseline characteristics predict NFB success will enhance its clinical utility. Previous work suggests that AH symptomology implicates measures across multiple modalities, including T1 structural MRI (sMRI), diffusion‐weighted MRI (dMRI), and resting‐state fMRI (rsfMRI). Specifically, AH severity and treatment response are associated with thinner superior temporal gyrus (STG), thinner dorsolateral prefrontal cortex (DLPFC), reduced white matter integrity in tracts connecting brain regions implicated in SZ symptomatology, increased within‐default mode network (DMN) connectivity, and reduced DMN–DLPFC anticorrelation. In this study, we tested the individual and combined contributions of multimodal brain features for the prediction of AH change after NFB in adults ( N = 25, 36.1 ± 10.0 years, 24% females) with SZ spectrum disorders (SZ or schizoaffective disorder) and frequent medication‐resistant AH. Participants underwent a baseline MRI scan (including sMRI, dMRI, and rsfMRI) and were randomly assigned to receive NFB from their STG ( n = 12, real condition) or NFB from their motor cortex (MC) ( n = 13, sham condition). NFB success was operationalized as the improvement in AH severity after NFB. We found that higher baseline AH severity, greater STG thickness, decreased dorsal cingulum integrity, increased within‐DMN resting‐state functional connectivity, and increased DMN–DLPFC anticorrelation were each individually correlated with reduction in AH severity. However, in a combined regression model, DMN–DLPFC connectivity emerged as the only independent variable that explained the unique variance in AH change. These results suggest that a specific rsfMRI measure, namely DMN–DLPFC connectivity, may be a promising predictor of NFB success in reducing AH and support the precision medicine approach. Trial Registration: ClinicalTrials.gov identifier: NCT03504579

Cognitive impairment is a core feature of schizophrenia, which is aggravated by antipsychotics-induced metabolic disturbance and lacks effective pharmacologic treatments in clinical practice. Our previous study demonstrated the efficiency of metformin in alleviating metabolic disturbance following antipsychotic administration. Here we report that metformin could ameliorate cognitive impairment and improve functional connectivity (FC) in prefrontal regions. This is an open-labeled, evaluator-blinded study. Clinically stable patients with schizophrenia were randomly assigned to receive antipsychotics plus metformin (N = 48) or antipsychotics alone (N = 24) for 24 weeks. The improvement in cognition was assessed by the MATRICS Consensus Cognitive Battery (MCCB). Its association with metabolic measurements, and voxel-wise whole-brain FC with dorsolateral prefrontal cortex (DLPFC) subregions as seeds were evaluated. When compared to the antipsychotics alone group, the addition of metformin resulted in significantly greater improvements in the MCCB composite score, speed of processing, working memory, verbal learning, and visual learning. A significant time × group interaction effect of increased FC between DLPFC and the anterior cingulate cortex (ACC)/middle cingulate cortex (MCC), and between DLPFC subregions were observed after metformin treatment, which was positively correlated with MCCB cognitive performance. Furthermore, the FC between left DLPFC A9/46d to right ACC/MCC significantly mediated metformin-induced speed of processing improvement; the FC between left A46 to right ACC significantly mediated metformin-induced verbal learning improvement. Collectively, these findings demonstrate that metformin can improve cognitive impairments in schizophrenia patients and is partly related to the FC changes in the DLPFC. Trial Registration: The trial was registered with ClinicalTrials.gov (NCT03271866). The full trial protocol is provided in Supplementary Material.

Abstract Background and Hypothesis Schizophrenia manifests with marked heterogeneity in both clinical presentation and underlying biology. Modeling individual differences within clinical cohorts is critical to translate knowledge reliably into clinical practice. We hypothesized that individualized brain atrophy in patients with schizophrenia may explain the heterogeneous outcomes of repetitive transcranial magnetic stimulation (rTMS). Study Design The magnetic resonance imaging (MRI) data of 797 healthy subjects and 91 schizophrenia patients (between January 1, 2015, and December 31, 2020) were retrospectively selected from our hospital database. The healthy subjects were used to establish normative reference ranges for cortical thickness as a function of age and sex. Then, a schizophrenia patient’s personalized atrophy map was computed as vertex-wise deviations from the normative model. Each patient’s atrophy network was mapped using resting-state functional connectivity MRI from a subgroup of healthy subjects (n = 652). In total 52 of the 91 schizophrenia patients received rTMS in a randomized clinical trial (RCT). Their longitudinal symptom changes were adopted to test the clinical utility of the personalized atrophy map. Results The personalized atrophy maps were highly heterogeneous across patients, but functionally converged to a putative schizophrenia network that comprised regions implicated by previous group-level findings. More importantly, retrospective analysis of rTMS-RCT data indicated that functional connectivity of the personalized atrophy maps with rTMS targets was significantly associated with the symptom outcomes of schizophrenia patients. Conclusions Normative modeling can aid in mapping the personalized atrophy network associated with treatment outcomes of patients with schizophrenia.

Rationale Second-generation antipsychotics occupy dopamine D 2 receptors and act as antagonists or partial agonists at these receptors. While these drugs alleviate positive symptoms in patients with schizophrenia, they are less effective for treating cognitive deficits and negative symptoms. Dopamine D 3 receptors are highly expressed in areas of the brain thought to play a role in the regulation of motivation and reward-related behavior. Consequently, the dopamine D 3 receptor has become a target for treating negative symptoms in combination with D 2 antagonism to treat positive symptoms in patients with schizophrenia. Objective The purpose of this study was to determine the cariprazine receptor occupancies in brain for D 2 and D 3 receptors in patients with schizophrenia. Methods Using [ 11 C]-(+)-PHNO as a radioligand, positron emission tomography (PET) scans were performed in eight patients at baseline and postdose on days 1, 4, and 15. Plasma and cerebrospinal fluid (CSF) samples were analyzed for cariprazine concentrations. Results A monotonic dose-occupancy relationship was observed for both receptor types. After 2 weeks of treatment, near complete (∼100 %) occupancies were observed for both receptors at a dose of 12 mg/day. At the lowest cariprazine dose (1 mg/day), mean D 3 and D 2 receptor occupancies were 76 and 45 %, respectively, suggesting selectivity for D 3 over D 2 receptors at low doses. An exposure-response analysis found a ∼3-fold difference in EC 50 (D 3  = 3.84 nM and D 2  = 13.03 nM) in plasma after 2 weeks of dosing. Conclusion This PET imaging study in patients with schizophrenia demonstrated that cariprazine is a D 3 -preferring dual D 3 /D 2 receptor partial agonist.

Hippocampal hyperactivity is a novel pharmacological target in the treatment of schizophrenia. We hypothesized that levetiracetam (LEV), a drug binding to the synaptic vesicle glycoprotein 2 A, normalizes hippocampal activity in persons with schizophrenia and can be measured using neuroimaging methods. Thirty healthy control participants and 30 patients with schizophrenia (28 treated with antipsychotic drugs), were randomly assigned to a double-blind, cross-over trial to receive a single administration of 500 mg oral LEV or placebo during two study visits. At each visit, we assessed hippocampal function using resting state fractional amplitude of low frequency fluctuations (fALFF), cerebral blood flow (CBF) with arterial spin labeling, and hippocampal blood-oxygen-level-dependent (BOLD) signal during a scene processing task. After placebo treatment, we found significant elevations in hippocampal fALFF in patients with schizophrenia, consistent with hippocampal hyperactivity. Additionally, hippocampal fALFF in patients with schizophrenia after LEV treatment did not significantly differ from healthy control participants receiving placebo, suggesting that LEV may normalize hippocampal hyperactivity. In contrast to our fALFF findings, we did not detect significant group differences or an effect of LEV treatment on hippocampal CBF. In the context of no significant group difference in BOLD signal, we found that hippocampal recruitment during scene processing is enhanced by LEV more significantly in schizophrenia. We conclude that pharmacological modulation of hippocampal hyperactivity in schizophrenia can be studied with some neuroimaging methods, but not others. Additional studies in different cohorts, employing alternate neuroimaging methods and study designs, are needed to establish levetiracetam as a treatment for schizophrenia.