Abstract
Background: To 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.
Methods: Preregistration 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.
Results: The 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).
Conclusions: We 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.
