The CCL2 rs4586 SNP Is Associated with Slower Amyloid-β Deposition and Faster Tau Accumulation of Alzheimer’s Disease
Bibliographic record
Abstract
BACKGROUND: CC-chemokine ligand 2 (CCL2), the key immunomodulatory chemokine for microglial activation, has been implicated in the pathogenesis of Alzheimer's disease (AD). Whether the association of CCL2 single nucleotide polymorphisms (SNPs) and the risk of AD is still controversial. OBJECTIVE: We aimed to investigate whether CCL2 rs4586 SNP is associated with the pathological changes and cognitive decline of AD. METHODS: A total of 486 participants with longitudinal cerebrospinal fluid (CSF) amyloid-β (Aβ) and phospho-tau (P-tau) biomarkers, 18F-Florbetapir and 18F-flortaucipir-positron emission tomography (PET), and cognitive assessments from the Alzheimer's disease Neuroimaging Initiative were included in the study. The effects of CCL2 rs4586 SNP on the pathological changes and cognitive decline of AD were assessed with linear mixed-effects models and evaluated according to the Aβ-status so as to identify whether the effects were independent of Aβ status. RESULTS: CCL2 rs4586-CC carriers exhibited a slower global Aβ-PET accumulation, particularly within stage I and stage II. However, they exhibited a faster accumulation of CSF P-tau and global tau-PET standard uptake value ratios, especially in Braak I and Braak III/IV and the inferior temporal gyrus. The congruent effects of CCL2 rs4586 on tau accumulation existed only in the Aβ-group, as is shown in global tau-PET and Braak I. However, CCL2 rs4586 was not associated with the cognitive decline. CONCLUSION: Our findings showed that the CCL2 rs4586-CC (versus TT/TC) genotype was associated with slower Aβ deposition and faster tau accumulation, and the latter of which was independent of Aβ status.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".