2026 ECNP Congress

PS01-1039

The role of the glutamate system in major depressive disorder with comorbid anxiety: A comprehensive 7 tesla multimodal neuroimaging study

Giuseppe Delvecchio — A.R. Bianchi, F. Goffi, E. Maggioni, M. Tosetti, G. Donatelli, S. Giomi, L. Di Consoli, C. Moltrasio, S.M. Pozzoli, P. Brambilla · University of Milan, Department of Pathophysiology and Transplantation, Milan, Italy

2026 ECNP Congress

Introduction

Major depressive disorder (MDD) and anxiety disorders (AD) are highly prevalent and frequently comorbid conditions, resulting in a significant impact in social and occupational functioning [1]. The common presence of both MDD and AD may be explained by the existence of shared etiological factors, with a common -at least in part- pathophysiological process [2]. Moreover, the pathophysiological and clinical proximity of these conditions extends to treatment as well. Recent research is increasingly focused on pharmacological compounds targeting systems beyond monoamines, with growing evidence implicating glutamate and the glutamatergic system in the pathophysiology of depressive disorders [3]. Notably, neuroimaging studies also offered valuable insights into the still poorly understood mechanisms underlying anxiety and depression and have increasingly investigated the role of the glutamatergic system, particularly within prefronto-limbic circuitry, in their pathophysiology. However, a clear picture regarding the role of glutamate in these disorders has not been reached yet.

Aims

The main objective of the present study is to advance the understanding of the neurobiological underpinnings of MDD in comorbidity with AD by leveraging the excellent ultra-high field (UHF)- Magnetic Resonance Imaging (MRI) resolution via a comprehensive multimodal approach.

Methods

Ten patients with MDD and comorbid AD and ten healthy controls (HC) underwent a multimodal MRI acquisitions at ultra-high (7T) magnetic field. Specifically, structural MRI was used to assess gray matter volume (GMV) and cortical thickness, while resting-state functional MRI was used to evaluate whole-brain functional connectivity. Finally, proton Magnetic Resonance Spectroscopy (1H-MRS) was employed to measured metabolite concentrations in the anterior cingulate cortex (ACC) and dorsolateral prefrontal cortex (DLPFC). Group differences between patients and HC were assessed using a general linear model, with age and sex included as covariates to control for their potential confounding effects. Statistical significance was set at p < 0.05. Given the small sample size, no correction for multiple comparisons was applied; instead, effect sizes (Cohen’s d) were reported for all group comparisons to provide a more robust estimate of the magnitude of group differences.

Results

Patients showed widespread GMV reductions, with the strongest and most consistent differences identified bilaterally in the parahippocampal gyrus, entorhinal cortex, and fusiform gyrus (all p-values<0.01, large effect size), alongside cortical thinning in insular and temporal areas (all p-values < 0.05, moderate to large effect size). Resting-state analyses revealed reduced fronto-frontal and fronto-parietal connectivity, coupled with increased limbic–cerebellar and precuneus connectivity (all p-values < 0.05, moderate to large effect size). Finally, 1H-MRS findings indicated reduced glutathione and myo-inositol in the ACC, and decreased N-acetylaspartate coupled with altered creatine metabolism in the DLPFC, with trends toward increased glutamatergic metabolites (all p-values < 0.05, moderate-large effect sizes).

Discussion

These findings support a model of MDD with comorbid AD characterized by disrupted prefronto-limbic integration, default mode network dysregulation, and altered glutamatergic metabolism. Therefore, the multimodal UHF-MRI approach used in this study provided valuable insights into the mechanisms of glutamatergic circuitry in MDD, revealing distinct, yet overlapping, structural, functional, and metabolic differences between patients and HC.

References

  1. Gunnarsson AB, Hedberg AK, Håkansson C, Hedin K, Wagman P. Occupational performance problems in people with depression and anxiety. Scand J Occup Ther. 2023 Feb;30(2):148-158. doi: 10.1080/11038128.2021.1882562.
  2. Gorwood P. Generalized anxiety disorder and major depressive disorder comorbidity: an example of genetic pleiotropy? Eur Psychiatry. 2004 Feb;19(1):27-33. doi: 10.1016/j.eurpsy.2003.10.002.
  3. Abdallah CG, Jiang L, De Feyter HM, Fasula M, Krystal JH, Rothman DL, Mason GF, Sanacora G. Glutamate metabolism in major depressive disorder. Am J Psychiatry. 2014 Dec 1;171(12):1320-7. doi: 10.1176/appi.ajp.2014.14010067.