557. GLUTAMATE, GLUTAMINE, AND GABA LEVELS IN ADULTS WITH AUTISM SPECTRUM DISORDER: A 7T MRS STUDY
Bibliographic record
Abstract
Abstract Background Alterations in excitatory and inhibitory neuronal tones are implicated in the pathophysiology of autism spectrum disorder (ASD). Excitatory neurotransmission is primarily mediated by glutamate (Glu) and its precursor, glutamine (Gln), whereas inhibitory neurotransmission is mediated by GABA. Magnetic resonance spectroscopy (MRS) at 7T MR enables the in vivo assessments of neurometabolites, including Glu, Gln, and GABA, with increased sensitivity. Aims & Objectives We aimed to investigate the status of Glu, Gln, and GABA in the brain of adults with ASD, using MRS with a 7T MR device. Method Thirty-three adults with ASD (mean age = 31.1 years) and 52 neurotypical control adults were included in this study. MRS scans of all participants were conducted using the semi-adiabatic short TE spin-echo full-intensity-acquired localized single voxel spectroscopy (sSPECIAL) sequence. The volumes of interest (VOIs) were localized at the anterior cingulate cortex (ACC), the bilateral thalamus, and the right temporo-parietal junction (TPJ). MRS quantification was conducted with LCModel, and quality control of the data was performed. Analysis of covariance (ANCOVA) was conducted to examine the effects of diagnosis on Glu, Gln, and GABA levels in each VOI, controlling for age and sex. Statistical significance thresholds were set at p < 0.05, with Bonferroni correction for the three VOIs. Results ANCOVA demonstrated significant effects of diagnosis on Gln for the thalamus (p = 0.012) and the right TPJ (p = 0.006), and a trend for the ACC (p = 0.04), indicating that Gln levels in these regions are higher in the ASD group. No significant effects of diagnosis were found on either Glu or GABA. Discussion & Conclusions The current results indicate that alterations in the regulation of excitatory neurotransmission, presumably increased cycling of the Gln-Glu circuit, may underlie the pathophysiology of ASD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 0.000 |
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".