Modulation of motor cortical excitability by continuous theta-burst stimulation in adults with autism spectrum disorder: The roles of BDNF and APOE polymorphisms
Bibliographic record
Abstract
Objective. To assess the utility of the modulation of motor cortex (M1) excitability by continuous theta-burst stimulation (cTBS) as a physiologic biomarker for adults with autism spectrum disorder (ASD), and to evaluate the influences of brain-derived neurotrophic factor (BDNF) and apolipoprotein E (APOE) polymorphisms on cTBS aftereffects. Methods. 44 neurotypical individuals (NT; age 21-65, 34 males) and 19 age-matched adults with high-functioning ASD (age 21-58, 17 males) underwent M1 cTBS. Cortico-motor reactivity was assessed before cTBS and thereafter every 5-10 minutes for 60 minutes (T5-T60). Results. Logistic regressions found cTBS-induced change in amplitude of motor evoked potentials (ΔMEP) at T15 was a significant predictor of ASD diagnosis (p=0.04). ΔMEP at T15 remained a significant predictor of diagnosis among BDNF Met+ subjects and APOEε4- subjects (p-values < 0.05) but not BDNF Met- subjects. ΔMEP at T30 was the best predictor of diagnosis among APOEε4+ subjects (p = 0.08). Conclusions. We confirm previous findings on the utility of cTBS measures of plasticity for adults with ASD, and we find the diagnostic utility of cTBS is modulated by BDNF and APOE SNPs. Significance. It is important to control for BDNF and APOE polymorphisms when comparing TBS aftereffects in ASD and NT individuals.
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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 | 0.000 | 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) | 0.001 | 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".