Elevated brain glutamine levels in adults with autism spectrum disorder: A 7T MRS study
Bibliographic record
Abstract
Alterations in excitatory neurotransmitters, involving the glutamate (Glu) and glutamine (Gln) cycle, as well as inhibitory neurotransmission, GABA, are implicated in the pathophysiology of autism spectrum disorder (ASD). Although magnetic resonance spectroscopy (MRS) holds promise for assessing these metabolites, conventional 3 T MRI does not robustly measure them, leaving the neurochemical pathophysiology of ASD insufficiently understood. 7 T MRI enables reliable assessments of these neurometabolites by enhancing the signal-to-noise ratio and improving the spectral resolution, particularly in distinguishing neuroactive Glu from its metabolic precursor, Gln. The current 7 T MRS study has two primary objectives: first, to investigate neurometabolite levels in adults with ASD to elucidate its neurochemical pathophysiology, and second, to examine their association with symptoms of ASD. Thirty-three adults with ASD (mean age = 31 years) and 52 age-matched control adults were included. The neurometabolite levels of Glu, Gln, and GABA were assessed in the anterior cingulate cortex (ACC), thalamus, and right temporo-parietal junction (TPJ), with most quantifications passing quality checks. Analysis of covariance revealed significant effects of diagnosis on Gln in the thalamus (p = 0.008) and right TPJ (p = 0.006), indicating elevated Gln levels in these regions in the ASD group. Among social communication and restricted and repetitive behaviors, significant negative correlations were observed in the ASD group between Gln levels and sensory symptoms. These findings suggest that alterations in the excitatory neurotransmission regulation, 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 | 0.001 | 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".