Mixed Pathologies in a Subject with a Novel PSEN1 G206R Mutation
Bibliographic record
Abstract
BACKGROUND: There are more than 300 presenilin-1 (PSEN1) mutations identified but a thorough postmortem neuropathological assessment of the mutation carriers is seldom performed. OBJECTIVE: To assess neuropathological changes (NC) in a 73-year-old subject with the novel PSEN1 G206R mutation suffering from cognitive decline in over 20 years. To compare these findings with an age- and gender-matched subject with sporadic Alzheimer's disease (sAD). METHODS: The brains were assessed macro- and microscopically and the proteinopathies were staged according to current recommendations. RESULTS: The AD neuropathological change (ADNC) was more extensive in the mutation carrier, although both individuals reached a high level of ADNC. The transactive DNA binding protein 43 pathology was at the end-stage in the index subject, a finding not previously described in familial AD. This pathology was moderate in the sAD subject. The PSEN1 G206R subject displayed full-blown alpha-synuclein pathology, while this proteinopathy was absent in the sAD case. Additionally, the mutation carrier displayed pronounced neuroinflammation, not previously described in association with PSEN1 mutations. CONCLUSION: Our findings are exceptional, as the PSEN1 G206R subject displayed an end-stage pathology of every common proteinopathy. It is unclear whether the observed alterations are caused by the mutation or are related to a cross-seeding mechanisms. The pronounced neuroinflammation in the index patient can be reactive to the extensive NC or a contributing factor to the proteinopathies. Thorough postmortem neuropathological and genetic assessment of subjects with familial AD is warranted, for further understanding of a dementing illness.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".