<scp><i>TAF1</i></scp> Transcripts and Neurofilament Light Chain as Biomarkers for X‐linked Dystonia‐Parkinsonism
Bibliographic record
Abstract
BACKGROUND: X-linked dystonia-parkinsonism is a rare neurological disease endemic to the Philippines. Dystonic symptoms appear in males at the mean age of 40 years and progress to parkinsonism with degenerative pathology in the striatum. A retrotransposon inserted in intron 32 of the TAF1 gene leads to alternative splicing in the region and a reduction of the full-length mRNA transcript. OBJECTIVES: The objective of this study was to discover cell-based and biofluid-based biomarkers for X-linked dystonia-parkinsonism. METHODS: RNA from patient-derived neural progenitor cells and their secreted extracellular vesicles were used to screen for dysregulation of TAF1 expression. Droplet-digital polymerase chain reaction was used to quantify the expression of TAF1 mRNA fragments 5' and 3' to the retrotransposon insertion and the disease-specific splice variant TAF1-32i in whole-blood RNA. Plasma levels of neurofilament light chain were measured using single-molecule array. RESULTS: In neural progenitor cells and their extracellular vesicles, we confirmed that the TAF1-3'/5' ratio was lower in patient samples, whereas TAF1-32i expression is higher relative to controls. In whole-blood RNA, both TAF1-3'/5' ratio and TAF1-32i expression can differentiate patient (n = 44) from control samples (n = 18) with high accuracy. Neurofilament light chain plasma levels were significantly elevated in patients (n = 43) compared with both carriers (n = 16) and controls (n = 21), with area under the curve of 0.79. CONCLUSIONS: TAF1 dysregulation in blood serves as a disease-specific biomarker that could be used as a readout for monitoring therapies targeting TAF1 splicing. Neurofilament light chain could be used in monitoring neurodegeneration and disease progression in patients. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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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 | 0.000 |
| 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".