Modeling the trajectory of tau deposition in autosomal‐dominant Alzheimer’s disease using the high‐affinity tau tracer [<sup>18</sup>F]MK6240
Bibliographic record
Abstract
Abstract Background Evidence suggests that Alzheimer’s disease (AD) pathology may appear many years prior to the manifestation of clinical symptoms. While autosomal‐dominant AD (ADAD) only accounts for approximately 1% of AD cases, evidence shows it has similar pathophysiological features to sporadic AD. ADAD provides a unique and powerful means to model the pathophysiological cascade of events leading to clinical dementia during this asymptomatic stage, due to the complete penetrance of ADAD genetic mutations and the consistency of age at symptom onset between generations. Objective: To investigate tau deposition in vivo across the course of ADAD in mutation carriers (MC) and noncarriers (NC) using the high‐affinity tau PET tracer [18F]MK6240. Method Cross‐sectional data was acquired for 12 MC, 6 of whom were symptomatic, and 11 asymptomatic NC. The majority of participants (91%) were from families with PSEN1 mutations. Estimated years from symptom onset (EYO) was obtained by subtracting the age at symptom onset of a parent or sibling from the participant’s age at assessment. [18F]MK6240 standardized uptake value ratio (SUVR) was calculated 90‐110 minutes post‐injection using inferior cerebellar grey matter as the reference region. Statistical analyses performed included ROI‐based and voxel‐based regressions to examine the association between tau load and EYO in MC and NC. Result ROI‐based analyses of [18F]MK6240 SUVR as a function of EYO in mutation carriers revealed strong positive correlations for Braak I‐II, III‐IV, and V‐VI. None of the associations between [18F]MK6240 SUVR and EYO were significant in NC. Voxel‐based analyses showed significant correlation between [18F]MK6240 retention and EYO bilaterally in the entorhinal cortex and in the right posterior cingulate and precuneus in MC, while no associations survived correction for multiple comparisons in NC. Conclusion Our results support a common pathophysiological cascade between ADAD and sporadic AD, as tau aggregation appears to follow Braak stages in both cases. Our study suggests that tau pathology appears up to 10 years before the onset of clinical symptoms. The identification of affected individuals using biomarkers early in the course of disease is crucial for better clinical outcomes. These results support the applications of disease‐modifying therapeutic interventions in the preclinical stage of AD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 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".