# Integrating 1H MRS with 2H-Labeled Glucose to Characterize Dynamic Glutamate Metabolism in Major Depressive Disorder > **NIH NIH R21** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2024 · $201,875 ## Abstract PROJECT SUMMARY/ABSTRACT Major depressive disorder (MDD) is a brain-based disorder that affects nearly 300 million people worldwide. Recent theoretical models and empirical studies have highlighted glutamate (Glu) as a key neurotransmitter in the pathophysiology of MDD that may be an important target for novel antidepressants. Using proton magnetic spectroscopy (1H MRS), several studies have identified lower concentrations of Glu and other related metabolites (e.g., glutamine, Gln) in depressed patients in anterior cingulate cortex (ACC). However, given the dynamic nature of the Glu–Gln cycle (Glu can be metabolized in neurons as part of the tricarboxylic acid [TCA] cycle or synthesized into Gln, which is a precursor to both GABA and Glu, in astrocytes), it is critical to generate novel imaging methods that will clarify which aspects of Glu metabolism underlie MDD. Doing so will advance our understanding of MDD and elucidate the mechanisms underlying fast-acting antidepressants targeting glutamatergic neurotransmission (e.g., ketamine). In this context, carbon-13 (13C) MRS with 13C-labeled substrates has been the only method to evaluate the Glu–Gln cycle, but this method has limited clinical applications due to significant technical challenges. Deuterium (2H) metabolic imaging has also been recently presented as a tool for detecting Glx (Glu+Gln) following oral administration of deuterated glucose (2H-glucose), as this method contains higher overall sensitivity compared to 13C MRS but is unable to resolve Glu from Gln. Thus, the goal of the present proposal is to develop an interleaved 1H/2H MRS acquisition combined with 2H- glucose on a 7T scanner to establish the reliable detection of Glu metabolism in patients with MDD. In Aim 1, we will develop the dynamic imaging protocol to obtain reliable measures of Glu metabolism following oral 2H- glucose intake. Our benchmarks for determining the optimal dynamic acquisition protocol will be based on maximizing signal-to-noise ratios of 1H Glu, 1H Gln, and 2H Glx and temporal resolution (time per block of 1H or 2H MRS) and determining the time course when kinetic curves for label exchange reaches steady-state. We will validate our optimized protocol in an independent sample of patients with MDD and age- and sex-matched healthy controls and hypothesize that both groups will exhibit comparable test-retest reliability (repeatability coefficient > 0.95). In Aim 2, we will develop methods to fit a simplified kinetic metabolic model to estimate the rates of TCA and Glu–Gln cycling, and will test the hypothesis that MDD is characterized lower baseline (as measured during the pre-glucose acquisition) levels of Glu and Gln, and slower Glu metabolism (as measured by the metabolic cycling rates) in ACC. The novel imaging protocol and the metabolic metrics we develop will stimulate innovative research on elucidating the mechanisms of fast-acting antidepressants targeting glutamatergic neurotransmission (e.g., ketam... ## Key facts - **NIH application ID:** 10795901 - **Project number:** 5R21MH130817-02 - **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO - **Principal Investigator:** TIFFANY CHEING HO - **Activity code:** R21 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $201,875 - **Award type:** 5 - **Project period:** 2023-03-01 → 2026-02-28 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10795901 ## Citation > US National Institutes of Health, RePORTER application 10795901, Integrating 1H MRS with 2H-Labeled Glucose to Characterize Dynamic Glutamate Metabolism in Major Depressive Disorder (5R21MH130817-02). Retrieved via AI Analytics 2026-06-12 from https://api.ai-analytics.org/grant/nih/10795901. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*