Ferritin Levels and Their Association With Regional Brain Volumes in Tourette’s Syndrome
Bibliographic record
Abstract
Objective: A previous small study showed lower serum ferritin levels in subjects with Tourette’s syndrome than in healthy subjects. The authors measured peripheral iron indices in a large group of Tourette’s syndrome and comparison subjects and explored associations of ferritin levels with regional brain volumes. Method: Ferritin was measured in 107 children and adults (63 Tourette’s syndrome, 44 comparison); serum iron was measured in 73 (41 Tourette’s syndrome, 32 comparison). Magnetic resonance imaging scans were used to measure volumes of the basal ganglia and cortical gray matter. Results: Ferritin and serum iron were significantly lower in the Tourette’s syndrome subjects, although still within the normal range. No association was found between tic severity and either iron index. In the Tourette’s syndrome subjects, ferritin did not correlate significantly with caudate volume but did correlate positively with putamen volume. In the comparison subjects, ferritin correlated inversely with caudate volume but did not correlate significantly with putamen volume. Irrespective of diagnosis, ferritin correlated positively with volumes of the sensorimotor, midtemporal, and subgenual cortices. Conclusions: The lower peripheral ferritin and iron levels in persons with Tourette’s syndrome are consistent with findings in other movement disorders and suggest that lower iron availability may have a causal role in the pathophysiology of tic disorders. Lower iron stores may contribute to hypoplasia of the caudate and putamen, increasing vulnerability to developing tics or to having more severe tics. Lower iron stores may also contribute to smaller cortical volumes and consequently to reduced inhibitory control of tics.
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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 | 0.000 | 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) | 0.001 | 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".