Quantitative Lipidomic Analysis of Serum Phospholipids Reveals Dissociable Markers of Alzheimer’s Disease and Subcortical Cerebrovascular Disease
Bibliographic record
Abstract
BACKGROUND: Circulating phospholipid species have been shown to predict Alzheimer's disease (AD) prognosis but the link between phospholipid disturbances and subcortical small vessel cerebrovascular disease (CeVD) common in AD patients is not known. OBJECTIVE: Mass-spectrometry lipidomics was applied to quantify serum diacyl, alkenyl (ether), alkyl, and lyso phospholipid species in individuals with extensive CeVD (n = 29), AD with minimal CeVD (n = 16), and AD with extensive CeVD (n = 14), and compared them to age-matched controls (n = 27). Memory was assessed using the California Verbal Learning Test. 3.0T MRI was used to assess hippocampal volume, atrophy, and white matter hyperintensity (WMH) volumes as manifestations of CeVD. RESULTS: AD was associated with significantly higher concentrations of choline plasmalogen 18:0_18:1 and alkyl-phosphocholine 18:1. CeVD was associated with significantly lower lysophospholipids containing 16:0. Phospholipids containing arachidonic acid (AA) were associated with poorer memory in controls, whereas docosahexaenoic acid (DHA)-containing phospholipids were associated with better memory in individuals with AD+CeVD. In controls, DHA-containing phospholipids were associated with more atrophy, and phospholipids containing linoleic acid and AA were associated with less atrophy. Lysophospholipids containing 16:0, 18:0, and 18:1 were correlated with less atrophy in controls, and of these, alkyl-phosphocholine 18:1 was correlated with smaller WMH volumes. Conversely, 16:0_18:1 choline plasmalogen was correlated with greater WMH volumes in controls. CONCLUSION: This study demonstrates discernable differences in circulating phospholipids in individuals with AD and CeVD, as well as new associations between phospholipid species with memory and brain structure that were specific to contexts of commonly comorbid vascular and neurodegenerative pathologies.
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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 | 0.000 | 0.001 |
| 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".