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Glutamatergic dysfunction is implicated in schizophrenia pathoaetiology, but this may vary in extent between patients. It is unclear whether inter-individual variability in glutamate is greater in schizophrenia than the general population. We conducted meta-analyses to assess (1) variability of glutamate measures in patients relative to controls (log coefficient of variation ratio: CVR); (2) standardised mean differences (SMD) using Hedges g; (3) modal distribution of individual-level glutamate data (Hartigan’s unimodality dip test). MEDLINE and EMBASE databases were searched from inception to September 2022 for proton magnetic resonance spectroscopy (1H-MRS) studies reporting glutamate, glutamine or Glx in schizophrenia. 123 studies reporting on 8256 patients and 7532 controls were included. Compared with controls, patients demonstrated greater variability in glutamatergic metabolites in the medial frontal cortex (MFC, glutamate: CVR = 0.15,p p = 0.003; Glx: CVR = 0.11,p = 0.002), dorsolateral prefrontal cortex (glutamine: CVR = 0.14,p = 0.05; Glx: CVR = 0.25,p p = 0.008; Glx: CVR = 0.19,p = 0.008). Studies in younger, more symptomatic patients were associated with greater variability in the basal ganglia (BG glutamate with age:z = −0.03,p = 0.003, symptoms:z = 0.007,p = 0.02) and temporal lobe (glutamate with age:z = −0.03,p = 0.02), while studies with older, more symptomatic patients associated with greater variability in MFC (glutamate with age:z = 0.01,p = 0.02, glutamine with symptoms:z = 0.01,p = 0.02). For individual patient data, most studies showed a unimodal distribution of glutamatergic metabolites. Meta-analysis of mean differences found lower MFC glutamate (g = −0.15,p = 0.03), higher thalamic glutamine (g = 0.53,p g = 0.28,p z = −0.02,p z = −0.03,p = 0.02) in patients relative to controls. Patient PANSS total score was positively associated with glutamate SMD in BG (z = 0.01,p = 0.01) and temporal lobe (z = 0.05,p = 0.008). Further research into the mechanisms underlying greater glutamatergic metabolite variability in schizophrenia and their clinical consequences may inform the identification of patient subgroups for future treatment strategies.

Background Tetrahydrobiopterin (BH4) plays an important role in the biosynthesis of serotonin, melatonin and catecholamines, all of which are implicated in the pathophysiology of mood disorders (MDs), including major depressive disorder (MDD) and bipolar disorder (BP). Production of BH4 is regulated by GTP cyclohydrolase transcription and activity. Thus, we considered the GTP cyclohydrolase gene ( GCH1 ) to be a good candidate gene in the pathophysiology of MDs and of the serotonin selective reuptake inhibitors (SSRIs) response in MDD, and conducted a case-control study utilizing three SNPs (rs8007267, rs3783641 and rs841) and moderate sample sizes (405 MDD patients, including 262 patients treated by SSRIs, 1022 BP patients and 1805 controls). Method A multiple logistic regression analysis was carried out to compare the frequencies of each SNP genotype for the target phenotype across patients and controls in several genetic models, while adjusting for possible confounding factors. A clinical response was defined as a decrease of more than 50% from the baseline score on the Structured Interview Guide for Hamilton Rating Scale for Depression (SIGH-D) within 8 weeks, and clinical remission as a SIGH-D score of less than 7 at 8 weeks. Result No associations between three SNPs in GCH1 and MDD or BP were observed; however, GCH1 was associated with SSRI therapeutic response in MDD in all the marker’s haplotype analysis (Global P value=0.0379). Conclusions Results suggest that GCH1 may predict response to SSRI in MDD in the Japanese population. Nevertheless, a replication study using larger samples may be required for conclusive results, since our sample size was small.