Glia inflammation and cell death pathways drive disease progression in preclinical and early AD
Bibliographic record
Abstract
Accumulation of amyloid-β (Aβ) and neurofibrillary tangles (NFTs) are followed by the activation of glia cells and infiltration of peripheral immune cells that collectively accelerate neurodegeneration in preclinical AD models. Yet, the role of neuroinflammation for neuronal injury and disease progression in preclinical and early symptomatic AD remains elusive. Here, we combined multiplexed immunoassays and SomaScan proteomics of the cerebrospinal fluid (CSF) with MRI and PET brain imaging of people across the AD continuum to identify pathways that are associated with AD progression. Unbiased clustering revealed that glia-mediated inflammation, activation of cell death pathways (CDPs) and synaptic pathologies were among the earliest Aβ-induced changes, and were associated with disease progression in preclinical AD. Mediation analysis revealed that activation of CDPs were decisive drivers of inflammation in early symptomatic AD. The cycle of glia-mediated neuroinflammation and neuronal injury characterizes preclinical AD and has implications for novel treatment approaches.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".