Diagnostic accuracy of cerebrospinal fluid biomarkers in genetic prion diseases
Bibliographic record
Abstract
Genetic prion diseases are a rare and diverse group of fatal neurodegenerative disorders caused by pathogenic sequence variations in the prion protein gene, PRNP. Data on CSF biomarkers in patients with genetic prion diseases are limited and conflicting results have been reported for unclear reasons. Here, we aimed to analyse the diagnostic accuracy of CSF biomarkers currently used in prion clinical diagnosis in 302 symptomatic genetic prion disease cases from 11 prion diagnostic centres, encompassing a total of 36 different pathogenic sequence variations within the open reading frame of PRNP. CSF samples were assessed for the surrogate markers of neurodegeneration, 14-3-3 protein (14-3-3), total-tau protein (t-tau) and α-synuclein and for prion seeding activity through the real-time quaking-induced conversion assay. Biomarker results were compared with those obtained in healthy and neurological controls. For the most prevalent PRNP pathogenic sequence variations, biomarker accuracy and associations between biomarkers, demographic and genetic determinants were assessed. Additionally, the prognostic value of biomarkers for predicting total disease duration from symptom onset to death was investigated. High sensitivity of the four biomarkers was detected for genetic Creutzfeldt-Jakob disease associated with the E200K and V210I mutations, but low sensitivity was observed for mutations associated with Gerstmann-Sträussler-Scheinker syndrome and fatal familial insomnia. All biomarkers showed good to excellent specificity using the standard cut-offs often used for sporadic Creutzfeldt-Jakob disease. In genetic prion diseases related to octapeptide repeat insertions, the biomarker sensitivity correlated with the number of repeats. New genetic prion disease-specific cut-offs for 14-3-3, t-tau and α-synuclein were calculated. Disease duration in genetic Creutzfeldt-Jakob disease-E200K, Gerstmann-Sträussler-Scheinker-P102L and fatal familial insomnia was highly dependent on PRNP codon 129 MV polymorphism and was significantly associated with biomarker levels. In a large cohort of genetic prion diseases, the simultaneous analysis of CSF prion disease biomarkers allowed the determination of new mutation-specific cut-offs improving the discrimination of genetic prion disease cases and unveiled genetic prion disease-specific associations with disease duration.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".