Cerebrospinal Fluid sTREM2 in Alzheimer’s Disease Is Associated with Both Amyloid and Tau Pathologies but not with Cognitive Status
Bibliographic record
Abstract
BACKGROUND: Cerebrospinal fluid (CSF) soluble triggering receptor expressed on myeloid cells 2 (sTREM2) is considered a biomarker of microglial activation. The relationships between CSF sTREM2 levels and Alzheimer's disease (AD) CSF core biomarkers, cognitive status, and neurodegeneration remain unclear. OBJECTIVE: To assess the association between CSF sTREM2 levels and AD progression and other AD hallmarks. METHODS: Using the Alzheimer's Disease Neuroimaging Initiative database, we investigated 1,035 participants, including 310 cognitively normal controls, 527 patients with mild cognitive impairment, and 198 patients with dementia. They were grouped according to CSF pathology (A/T profile) severity. CSF sTREM2 levels were compared between the groups, and linear regression analysis was performed to evaluate the factors affecting sTREM2 levels. The predictive effectiveness of sTREM2 levels was tested, and the correlation with other indicators was explored. The increase rate was assessed using linear mixed-effects models. RESULTS: Higher CSF sTREM2 levels were associated with older age as well as higher CSF p-tau or t-tau and amyloid-β levels (all p < 0.001), but not with cognitive status. sTREM2 levels were not correlated with the baseline or longitudinal scale and neuroimaging result changes, and could not predict clinical conversion, but were correlated with multiple non-amyloid-β and non-tau CSF cytokines related to inflammation and neurodegeneration (p < 0.0001). The increased sTREM2 expression rate did not change among groups. CONCLUSION: CSF sTREM2 levels were jointly determined by age, amyloid-β, and tau pathologies, leading to complex AD cognitive continuum changes. Although sTREM2 levels could not predict cognitive deterioration and neurodegeneration, they could reflect the microglial state as a non-specific biomarker.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".