Disease Progression Patterns of Brain Morphology in Schizophrenia: More Progressed Stages in Treatment Resistance.

BACKGROUND AND HYPOTHESIS: Given the heterogeneity and possible disease progression in schizophrenia, identifying the neurobiological subtypes and progression patterns in each patient may lead to novel biomarkers. Here, we adopted data-driven machine-learning techniques to identify the progression patterns of brain morphological changes in schizophrenia and investigate the association with treatment resistance. STUDY DESIGN: In this cross-sectional multicenter study, we included 177 patients with schizophrenia, characterized by treatment response or resistance, with 3D T1-weighted magnetic resonance imaging. Cortical thickness and subcortical volumes calculated by FreeSurfer were converted into z scores using 73 healthy controls data. The Subtype and Stage Inference (SuStaIn) algorithm was used for unsupervised machine-learning analysis. STUDY RESULTS: SuStaIn identified 3 different subtypes: (1) subcortical volume reduction (SC) type (73 patients), in which volume reduction of subcortical structures occurs first and moderate cortical thinning follows, (2) globus pallidus hypertrophy and cortical thinning (GP-CX) type (42 patients), in which globus pallidus hypertrophy initially occurs followed by progressive cortical thinning, and (3) cortical thinning (pure CX) type (39 patients), in which thinning of the insular and lateral temporal lobe cortices primarily happens. The remaining 23 patients were assigned to baseline stage of progression (no change). SuStaIn also found 84 stages of progression, and treatment-resistant schizophrenia showed significantly more progressed stages than treatment-responsive cases (P = .001). The GP-CX type presented earlier stages than the pure CX type (P = .009). CONCLUSIONS: The brain morphological progressions in schizophrenia can be classified into 3 subtypes, and treatment resistance was associated with more progressed stages, which may suggest a novel biomarker.

Glutamatergic neurometabolite levels in the caudate are associated with the ability of rhythm production.

Introduction: Glutamatergic neurometabolites play important roles in the basal ganglia, a hub of the brain networks involved in musical rhythm processing. We aimed to investigate the relationship between rhythm processing abilities and glutamatergic neurometabolites in the caudate. Methods: We aquired Glutamatergic function in healthy individuals employing proton magnetic resonance spectroscopy. We targeted the right caudate and the dorsal anterior cingulate cortex (dACC) as a control region. Rhythm processing ability was assessed by the Harvard Beat Assessment Test (H-BAT). Results: We found negative correlations between the production part of the Beat Saliency Test in the H-BAT and glutamate and glutamine levels in the caudate (r = -0.693, p = 0.002) whereas there was no such association in the dACC. Conclusion: These results suggest that higher glutamatergic neurometabolite levels in the caudate may contribute to rhythm processing, especially the ability to produce meter in music precisely.

Glutamatergic and GABAergic metabolite levels in schizophrenia-spectrum disorders: a meta-analysis of 1H-magnetic resonance spectroscopy studies.

BACKGROUND: The glutamate (Glu) and gamma aminobutyric acid (GABA) hypotheses of schizophrenia were proposed in the 1980s. However, current findings on those metabolite levels in schizophrenia have been inconsistent, and the relationship between their abnormalities and the pathophysiology of schizophrenia remains unclear. To summarize the nature of the alterations of glutamatergic and GABAergic systems in schizophrenia, we conducted meta-analyses of proton magnetic resonance spectroscopy (1H-MRS) studies examining these metabolite levels. METHODS: A systematic literature search was conducted using Embase, Medline, PsycINFO, and PubMed. Original studies that compared four metabolite levels (Glu, glutamine [Gln], Glx [Glu+Gln], and GABA), as measured by 1H-MRS, between individuals at high risk for psychosis, patients with first-episode psychosis, or patients with schizophrenia and healthy controls (HC) were included. A random-effects model was used to calculate the effect sizes for group differences in these metabolite levels of 18 regions of interest between the whole group or schizophrenia group and HC. Subgroup analysis and meta-regression were performed based on the status of antipsychotic treatment, illness stage, treatment resistance, and magnetic field strength. RESULTS: One-hundred-thirty-four studies met the eligibility criteria, totaling 7993 participants with SZ-spectrum disorders and 8744 HC. 14 out of 18 ROIs had enough numbers of studies to examine the group difference in the metabolite levels. In the whole group, Glx levels in the basal ganglia (g = 0.32; 95% CIs: 0.18-0.45) were elevated. Subgroup analyses showed elevated Glx levels in the hippocampus (g = 0.47; 95% CIs: 0.21-0.73) and dorsolateral prefrontal cortex (g = 0.25; 95% CIs: 0.05-0.44) in unmedicated patients than HC. GABA levels in the MCC were decreased in the first-episode psychosis group compared with HC (g = -0.40; 95% CIs: -0.62 to -0.17). Treatment-resistant schizophrenia (TRS) group had elevated Glx and Glu levels in the MCC (Glx: g = 0.7; 95% CIs: 0.38-1.01; Glu: g = 0.63; 95% CIs: 0.31-0.94) while MCC Glu levels were decreased in the patient group except TRS (g = -0.17; 95% CIs: -0.33 to -0.01). CONCLUSIONS: Increased glutamatergic metabolite levels and reduced GABA levels indicate that the disruption of excitatory/inhibitory balance may be related to the pathophysiology of schizophrenia-spectrum disorders.