Quantification of mutant huntingtin protein in cerebrospinal fluid from Huntington’s disease patients
Bibliographic record
Abstract
BACKGROUND: Quantification of disease-associated proteins in the cerebrospinal fluid (CSF) has been critical for the study and treatment of several neurodegenerative disorders; however, mutant huntingtin protein (mHTT), the cause of Huntington's disease (HD), is at very low levels in CSF and, to our knowledge, has never been measured previously. METHODS: We developed an ultrasensitive single-molecule counting (SMC) mHTT immunoassay that was used to quantify mHTT levels in CSF samples from individuals bearing the HD mutation and from control individuals in 2 independent cohorts. RESULTS: This SMC mHTT immunoassay demonstrated high specificity for mHTT, high sensitivity with a femtomolar detection threshold, and a broad dynamic range. Analysis of the CSF samples showed that mHTT was undetectable in CSF from all controls but quantifiable in nearly all mutation carriers. The mHTT concentration in CSF was approximately 3-fold higher in patients with manifest HD than in premanifest mutation carriers. Moreover, mHTT levels increased as the disease progressed and were associated with 5-year onset probability. The mHTT concentration independently predicted cognitive and motor dysfunction. Furthermore, the level of mHTT was associated with the concentrations of tau and neurofilament light chain in the CSF, suggesting a neuronal origin for the detected mHTT. CONCLUSIONS: We have demonstrated that mHTT can be quantified in CSF from HD patients using the described SMC mHTT immunoassay. Moreover, the level of mHTT detected is associated with proximity to disease onset and diminished cognitive and motor function. The ability to quantify CSF mHTT will facilitate the study of HD, and mHTT quantification could potentially serve as a biomarker for the development and testing of experimental mHTT-lowering therapies for HD. TRIAL REGISTRATION: Not applicable. FUNDING: CHDI Foundation Inc.; Medical Research Council (MRC) UK; National Institutes for Health Research (NIHR); Rosetrees Trust; Swedish Research Council; and Knut and Alice Wallenberg Foundation.
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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) | 0.000 | 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".