Magnetic resonance spectroscopy biomarkers in premanifest and early Huntington disease
Bibliographic record
Abstract
OBJECTIVES: To evaluate in vivo brain metabolite differences in control subjects, individuals with premanifest Huntington disease (pre-HD), and individuals with early HD using ¹H magnetic resonance spectroscopy (MRS) and to assess their relationship with motor performance. METHODS: Eighty-five participants (30 controls, 25 pre-HD, and 30 early HD) were recruited as part of the TRACK-HD study. Eighty-four were scanned at 3 T with single-voxel spectroscopy in the left putamen. Disease burden score was >220 among pre-HD individuals. Subjects underwent TRACK-HD motor assessment including Unified Huntington's Disease Rating Scale (UHDRS) motor scoring and a novel quantitative motor battery. Statistical analyses included linear regression and one-way analysis of variance. RESULTS: Total N-acetylaspartate (tNAA), a neuronal integrity marker, was lower in early HD (∼15%) vs controls (p < 0.001). N-acetylaspartate (NAA), a constituent of tNAA, was lower in pre-HD (∼8%) and early HD (∼17%) vs controls (p < 0.05). The glial cell marker, myo-inositol (mI), was 50% higher in early HD vs pre-HD (p < 0.01). In early HD, mI correlated with UHDRS motor score (R² = 0.23, p < 0.05). Across pre-HD and early HD, tNAA correlated with performance on a tongue pressure task (R² = 0.30, p < 0.0001) and with disease burden score (R² = 0.17, p < 0.005). CONCLUSIONS: We demonstrate lower putaminal tNAA in early HD compared to controls in a cross-section of subjects. A novel biomarker role for mI in early HD was also identified. These findings resolve disagreement in the literature about the role of MRS as an HD biomarker. We conclude that putaminal MRS measurements of NAA and mI are promising potential biomarkers of HD onset and progression.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".