Neuroinflammation imposes vulnerability to tau propagation
Bibliographic record
Abstract
Abstract Background Translocator protein (TSPO) is an 18 kDa protein has been considered a target for neuroinflammation. Using multiparametric acquisitions, we tested in a large‐scale cohort the hypothetical framework proposing that neuroinflammation imposes vulnerability to neurofibrillary tangles (NFT) formation and propagation. Methods We studied cognitive unimpaired and impaired individuals from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort who had a complete baseline clinical and cognitive assessments, structural MRIs, [11C]PBR28, [18F]MK6240 and [18F]AZD4694 (PET proxies for TSPO, NFT and Αβ, respectively). The PET outcome measure was the SUVR. A fraction of these individuals also had CSF cytokines analysed using the Olink Platform. We conducted ROI path analysis and voxel‐based analysis to establish the associations between [11C]PBR28, [18F]MK6240 and [18F]AZD4694. Results A total of 138 (CN=90; MCI=30=; AD=18) individuals were included in this analysis. We found that brain [11C]PBR28 uptake was correlated with CSF biomarkers of neuroinflammation. We also found an age‐related increase of [11C]PBR28 uptake. [11C]PBR28 was increased brain in AD related areas across the its clinical spectrum. [11C]PBR28 was associated with cognitive deficits in these individuals. In regards to tau aggregates, we found that [18F]MK6240 uptake in the mesial temporal structures derives from local interactions between [18F]AZD4694 and [11C]PBR28. Importantly, path analysis revealed that [11C]PBR28 and [18F]AZD4694 uptake potentiated the propagation of [18F]MK6240 from early to late Braak stages (Figure 1). Conclusions Our results reveal that TSPO upregulation is part of the repertoire of biomarker alterations in patients within the entire AD clinical spectrum. TSPO is critical for the early and late tangle formation on medial temporal structures as well in advanced Braak stages. Neuroinflammation imaging agents such as [11C]PBR28 provide critical information regarding inflammatory tissue responses amenable of pharmacological interventions.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".