Trajectories of neurodegeneration and seed amplification biomarkers prior to disease onset in individuals at risk of prion disease
Bibliographic record
Abstract
Abstract Human prion diseases are remarkable for long incubation times followed by typically rapid clinical decline. Seed amplification assays and neurodegeneration biofluid biomarkers are remarkably useful in the clinical phase, but their potential to predict clinical onset in healthy people remains unclear. This is relevant not only to the design of preventive strategies in those at-risk of prion diseases, but more broadly, because prion-like mechanisms are thought to underpin many neurodegenerative disorders. Here we report the accrual of a longitudinal biofluid resource in patients, controls and healthy people at-risk of prion diseases, to which ultrasensitive techniques such as real-time quaking-induced conversion (RT-QuIC), and single molecule array (Simoa) digital immunoassays were applied for preclinical biomarker discovery. We studied a total of 648 CSF and plasma samples, including importantly, 16 people who had samples taken when healthy but later developed inherited prion disease (IPD) (“converters,” range from 9.9 prior to, and 7.4 years after onset). A second generation (IQ-CSF) RT-QuIC assay was used to screen symptomatic IPD samples, followed by optimisation for other IPDs, before the entire collection of at-risk samples was screened using the most sensitive assay. Glial fibrillary acidic protein (GFAP), neurofilament light (NfL), tau and ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) levels were measured in plasma and CSF. IQ-CSF RT-QuIC proved 100% sensitive and specific for sporadic Creutzfeldt-Jakob disease (sCJD), iatrogenic (iCJD) and familial CJD phenotypes, and subsequently detected seeding activity in four CSF samples from three PRNP E200K carriers in the presymptomatic phase, one of whom converted shortly after but the other two remain asymptomatic after two and three years of follow up. A bespoke HuPrP P102L RT-QuIC showed partial sensitivity for P102L disease and was positive in a CSF sample from an individual at risk of P102L IPD. No compatible RT-QuIC assay iterations were discovered for classical 6-OPRI, A117V and D178N, and these at-risk samples tested negative with bank vole RT-QuIC. Plasma GFAP and NfL, and CSF NfL levels emerged as proximity markers of neurodegeneration in slowly progressive forms of IPDs, with highly statistically significant differences in mean values segregating normal control (together with IPD > 2 years to onset) from IPD < 2 years to onset and symptomatic IPD cohorts. The trajectories of biomarker change appeared to correspond to expected fast and slow clinical phenotypes of progression in IPD with plasma GFAP changes preceding NfL changes. We propose patterns of preclinical biomarker changes in prion diseases based on the presence of clinical, seeding and neurodegeneration features.
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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 | 0.001 | 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".