Using neurolipidomics to identify phospholipid mediators of synaptic (dys)function in Alzheimer's Disease
Bibliographic record
Abstract
Not all of the mysteries of life lie in our genetic code. Some can be found buried in our membranes. These shells of fat, sculpted in the central nervous system into the cellular (and subcellular) boundaries of neurons and glia, are themselves complex systems of information. The diversity of neural phospholipids, coupled with their chameleon-like capacity to transmute into bioactive molecules, provides a vast repertoire of immediate response second messengers. The effects of compositional changes on synaptic function have only begun to be appreciated. Here, we mined 29 neurolipidomic datasets for changes in neuronal membrane phospholipid metabolism in Alzheimer's Disease (AD). Three overarching metabolic disturbances were detected. We found that an increase in the hydrolysis of platelet activating factor precursors and ethanolamine-containing plasmalogens, coupled with a failure to regenerate relatively rare alkyl-acyl and alkenyl-acyl structural phospholipids, correlated with disease severity. Accumulation of specific bioactive metabolites [i.e., PC(O-16:0/2:0) and PE(P-16:0/0:0)] was associated with aggravating tau pathology, enhancing vesicular release, and signaling neuronal loss. Finally, depletion of PI(16:0/20:4), PI(16:0/22:6), and PI(18:0/22:6) was implicated in accelerating Aβ42 biogenesis. Our analysis further suggested that converging disruptions in platelet activating factor, plasmalogen, phosphoinositol, phosphoethanolamine (PE), and docosahexaenoic acid metabolism may contribute mechanistically to catastrophic vesicular depletion, impaired receptor trafficking, and morphological dendritic deformation. Together, this analysis supports an emerging hypothesis that aberrant phospholipid metabolism may be one of multiple critical determinants required for Alzheimer disease conversion.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".