18F-MK-6240 tau-PET in genetic frontotemporal dementia
Bibliographic record
Abstract
Tau is one of several proteins associated with frontotemporal dementia. While knowing which protein is causing a patient's disease is crucial, no biomarker currently exists for identifying tau in vivo in frontotemporal dementia. The objective of this study was to investigate the potential for the promising 18F-MK-6240 PET tracer to bind to tau in vivo in genetic frontotemporal dementia. We enrolled subjects with genetic frontotemporal dementia, who constitute an ideal population for testing because their pathology is already known based on their mutation. Ten participants (three with symptomatic P301L and R406W MAPT mutations expected to show tau binding, three with presymptomatic MAPT mutations and four with non-tau mutations who acted as disease controls) underwent clinical characterization, tau-PET scanning with 18F-MK-6240, amyloid-PET imaging with 18F-NAV-4694 to rule out confounding Alzheimer's pathology, and high-resolution structural MRI. Tau-PET scans of all three symptomatic MAPT carriers demonstrated at least mild 18F-MK-6240 binding in expected regions, with particularly strong binding in a subject with an R406W MAPT mutation (known to be associated with Alzheimer's like neurofibrillary tangles). Two asymptomatic MAPT carriers estimated to be 5 years from disease onset both showed modest 18F-MK-6240 binding, while one ∼30 years from disease onset did not exhibit any binding. Additionally, four individuals with symptomatic frontotemporal dementia caused by a non-tau mutation were scanned (two C9orf72; one GRN; one VCP): 18F-MK-6240 scans were negative for three subjects, while one advanced C9orf72 case showed minimal regionally non-specific binding. All 10 amyloid-PET scans were negative. Furthermore, a general linear model contrasting genetic frontotemporal dementia subjects to a set of 83 age-matched controls showed significant binding only in the MAPT carriers in selected frontal, temporal and subcortical regions. In summary, our findings demonstrate mild but significant binding of MK-6240 in amyloid-negative P301L and R406W MAPT mutation subjects, with higher standardized uptake value ratio in the R406W mutation associated with the presence of NFTs, and little non-specific binding. These results highlight that a positive 18F-MK-6240 tau-PET does not necessarily imply a diagnosis of Alzheimer's disease and point towards a potential use for 18F-MK-6240 as a biomarker in certain tauopathies beyond Alzheimer's, although further patient recruitment and autopsy studies will be necessary to determine clinical applicability.
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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) | 0.001 | 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 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".