Quantification of tau phosphorylated at threonine 217 using a novel ultrasensitive immunoassay distinguishes Alzheimer’s disease from healthy controls
Bibliographic record
Abstract
Abstract Background One of the major neuropathological hallmarks of a brain affected by Alzheimer’s disease (AD) is neurofibrillary tangles (NFTs), which are composed of aggregated, and sometimes truncated, hyperphosphorylated tau protein. Clinical diagnosis of AD is often aided by the use of biomarkers. One of the three core cerebrospinal fluid (CSF) biomarkers for AD, tau phosphorylated at amino acid 181 (p‐tauT181), shows quite a high sensitivity and specificity for AD but there is also a relatively large overlap between AD non‐demented subjects. Recently, tau species phosphorylated at amino acid 217 (p‐tauT217) quantified by mass spectrometry was shown to correlate with amyloid and tau lesions in the brain and clinical disease progression, and thus seem to be a new potential AD biomarker. Here, we present a novel immunoassay used to quantify p‐tauT217 in CSF and show that it outperforms the classical AD biomarkers. Method CSF samples from AD, healthy controls (Co) (cohort1 [Lund University] and cohort2 [TRIAD cohort, McGill University]), frontotemporal dementia (FTD) and mild cognitive impairment (MCI) (cohort2) were analysed by a novel ultrasensitive immunoassay on the Single molecule array (Simoa) platform. The Simoa assay was based on two in‐house generated monoclonal antibodies. Result CSF levels of p‐tauT217 were significantly increased in AD compared with Co in both cohort1 (p<0.0001, 4.3‐fold increase) and cohort2 (p=0.0003, 3.5‐fold increase). In cohort2, p‐tauT217 was also increased in AD compared with FTD (p=0.0059) and amyloid PET‐negative MCI (p=0.0203, 4.8‐fold increase), and in amyloid PET‐positive MCI compared with Co (p<0.0001, 3.9‐fold increase), amyloid PET‐negative MCI (p=0.0035, 5.2‐fold increase) and FTD (p=0.0011). Conclusion We present performance data on a novel ultrasensitive immunoassay capable of quantifying p‐tauT217 in CSF. There was much less overlap between AD patients and healthy controls, as well as between amyloid PET‐positive and ‐negative MCI when using p‐tauT217 compared with p‐tauT181 in both cohorts, thus indicating that p‐tauT217 reflects the presence of AD pathology better. In conclusion, p‐tauT217 is a very promising new biomarker for AD, which potentially could be used to aid clinical diagnosis, even at pre‐dementia stages of the disease.
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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) | 0.001 | 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 | 0.001 | 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".