The role of Phospholipids in Neurodegeneration
Bibliographic record
Abstract
Introduction: Disturbances in phospholipid metabolism have been linked to the risk of dementia. However, data on how phospholipoid disturbances change across the different dementias and their relationships to brain function and structural changes are lacking. This study aimed to elucidate the role of plasma phospholipids in neurodegenerative disorders associated with dementia in the Ontario Neurodegenerative Research Initiative (ONDRI) cohort. Methods: Plasma phospholipid species were quantified using LC-MS/MS in 520 individuals diagnosed with Mild Cognitive Impairment (MCI), Alzheimers Disease (AD), Vascular Dementia (VD), Parkinsons Disease (PD), or Frontotemporal Dementia (FTD), and compared to controls. Cognitive function was assessed, and structural brain changes were evaluated via 3.0T MRI. Adjusted linear regression models analyzed phospholipid differences among groups and their corresponding clinical characteristics. Results: Significantly lower phospholipids and higher lysophospholipds were found in individuals diagnosed with MCI, AD, VD, PD and FTD, compared to controls. Significant positive associations were found between Lysophospholipids and phospholipids and brain atrophy, as well as hippocampal volume, in individuals with MCI and dementia. Conclusions: This study identifies novel phospholipid signatures specific to different forms of neurodegeneration, highlighting distinct underlying pathophysiological processes. These signatures may serve as potential biomarkers for early diagnosis and improve diagnostic accuracy for neurodegenerative diseases.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".