BackgroundTo date, there is no systematic overview of glutamate in the dorsolateral prefrontal cortex (DLPFC) of patients with schizophrenia. Here, we meta-analyzed case-control studies of high-field proton magnetic resonance spectroscopy (1H-MRS) investigating glutamate in DLPFC. Additionally, we estimated variance ratios to investigate homo/heterogeneity. MethodsPreregistration of the study was performed on September 20, 2019. The predefined literature search on PubMed comprised articles with search terms (magnetic resonance spectroscopy OR MRS) AND (glutamate OR glut∗ OR GLX) AND (schizophrenia OR psychosis OR schizophren∗). Meta-analyses with a fixed- and random-effects model with inverse variance method, DerSimonian-Laird estimator for τ2, and Cohen's d were calculated. For differences in variability, we calculated a random-effects model for measures of variance ratios. The primary study outcome was the difference in glutamate in the DLPFC in cases versus controls. Secondary outcomes were differences in variability. ResultsThe quantitative analysis comprised 429 cases and 365 controls. Overall, we found no group difference (d = 0.03 [95% confidence interval (CI), −0.20 to 0.26], z = 0.28, p = .78). Sensitivity analysis revealed an effect for medication status (Q = 8.35, p = .039), i.e., increased glutamate in antipsychotic-naïve patients (d = 0.46 [95% CI, 0.08 to 0.84], z = 2.37, p = .018). Concerning variance ratios, we found an effect of medication status (Q = 16.95, p < .001) due to lower coefficient of variation ratio (CVR) in medication-naïve patients (logCVR = −0.49 [95% CI, −0.78 to −0.20], z = −3.33, p < .001). In studies with medicated patients, we found higher CVR (logCVR = 0.22 [95% CI, 0.06 to 0.39], z = 2.67; p = .008). ConclusionsWe carefully interpret the higher levels and lower variability in cortical glutamate in antipsychotic-naïve patients as a possible key factor resulting from a putative allostatic mechanism. We conclude that care has to be taken when evaluating metabolite levels in clinical samples in which medication might confound findings.