Relapsing Multiple Sclerosis Exhibits Reduced Normal Appearing White Matter Glutamate Levels (P6.132)
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to compare glutamate, and other brain metabolite, concentrations in patients with relapsing multiple sclerosis (RMS) and healthy controls using an advanced magnetic resonance spectroscopy (MRS) analysis technique. BACKGROUND: Glutamate is the major excitatory neurotransmitter in the brain and is also used for communication between axons and myelin. Reduced communication leads to diminished repair mechanisms, which may be related to neurodegeneration in MS. MRS provides an effective tool to non-invasively and quantitatively measure glutamate levels in the brain. DESIGN/METHODS: 26 RMS subjects participating in a Phase III clinical trial of ocrelizumab (OPERA) and 40 age and gender-matched healthy controls were scanned at baseline. A 6.5x4.5x1.8cm^3 white matter voxel was analyzed with MRS and the spectra were fit with LCModel version 6.3. Glutamate, N-acetyl-aspartate (primary role: neuronal integrity), creatine (energy storage), choline (membrane synthesis), and myo-Inositol (glial marker) concentrations were calculated relative to the water peak and corrected for voxel compartmentation and relaxation to obtain institutional mM values. RESULTS: Glutamate was significantly lower in RMS subjects compared to controls. The median glutamate concentration was 7.0 (6.7 - 7.5) mM in RMS and 7.5 (7.1 - 7.9) mM in healthy controls (p=0.009). There were no significant differences between RMS patients and controls for all other metabolites. CONCLUSIONS: Glutamate concentrations were lower in RMS subjects compared to healthy controls. This result could be indicative of reduced axo-myelinic communication in RMS. Our previous finding of declining glutamate and glutamine levels over 2 years in patients with secondary progressive MS is consistent with the results of the present study. Both of these studies suggest that abnormal glutamate homeostasis is a common feature of MS and could be a potential biomarker of neurodegeneration. These brain metabolites will be measured longitudinally in the OPERA Phase III RMS clinical trials.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".