A Pathway-Specific Polygenic Risk Score Is Associated with Tau Pathology and Cognitive Decline
Bibliographic record
Abstract
BACKGROUND: Tauopathy is a primary neuropathological hallmark of Alzheimer's disease with a strong relationship to cognitive impairment. In the brain, tau aggregation is associated with the regulation of tau kinases and the binding ability of tau to microtubules. OBJECTIVE: To explore the potential for using specific polygenic risk scores (PRSs), combining the genetic influences involved in tau-protein kinases and the tau-protein binding pathway, as predictors of tau pathology and cognitive decline in non-demented individuals. METHODS: We computed a pathway-specific PRS using summary statistics from previous large-scale genome-wide association studies of dementia. We examined whether PRS is related to tau uptake in positron emission tomography (PET), tau levels, and the rate of tau level changes in cerebrospinal fluid (CSF). We further assessed whether PRS is associated with memory impairment mediated by CSF tau levels. RESULTS: A higher PRS was related to elevated CSF tau levels and tau-PET uptake at baseline, as well as greater rates of change in CSF tau levels. Moreover, PRS was associated with memory impairment, mediated by increased CSF tau levels. The association between PRS and tau pathology was significant when APOE was excluded, even among females. However, the effect of PRS on cognitive decline appeared to be driven by the inclusion of APOE. CONCLUSION: The influence of genetic risk in a specific tau-related biological pathway may make an individual more susceptible to tau pathology, resulting in cognitive dysfunction in an early preclinical phase 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".