Association between lipopolysaccharide, immune biomarkers and cerebral amyloid‐beta deposition in older adults with mild cognitive impairment & major depressive disorder
Bibliographic record
Abstract
Abstract Background Inflammatory activation and increased immune response to lipopolysaccharide (LPS, a cell wall component of gut bacteria) is observed in both depression and cognitive decline. Depression is associated with accelerated cognitive decline, and persistent inflammatory activation may link depression and cognitive decline in later life. We determined if LPS is associated with inflammatory activation and cerebral deposition of amyloid‐beta (Abeta) in older adults with Mild Cognitive Impairment (MCI) and/or remitted Major Depressive Disorder (rMDD). Method Serum samples of LPS, LPS‐binding protein (LBP, which enhances the inflammatory response to LPS), and inflammatory markers (Interleukin 6 [Il‐6], C‐reactive protein [CRP], Monocyte Chemoattractant Protein 1 [MCP‐1]) were measured using ELISA. Abeta deposition was measured using PET neuroimaging using [11C]‐PIB radiotracer. Global amyloid burden was calculated using a composite Standardized Uptake Value Ratio (SUVR) score with the cerebellar cortex as the reference region. Multivariable linear regression analyses, adjusting for significant demographic and genetic variables, were conducted to determine if LPS, LBP, inflammatory biomarkers, MCI and rMDD were independently associated with global cerebral deposition of Abeta. Result Among 155 study participants (79 with MCI only, 54 with both MCI and rMDD, 22 with rMDD only) we found a median Abeta SUVR of 1.41 (IQR 0.57). There was no significant association between LPS (beta ‐1.28, 95% CI ‐11.69, 9.13, p = 0.8) or LBP (beta ‐0.02, 95% CI ‐0.05, 0.006, p = 0.12) and global deposition of Abeta, following adjustment for age, sex, and APOE genotype. LBP was positively correlated with inflammatory biomarkers: CRP (r = 0.49, p < 0.001) and IL‐6 (r = 0.21, p = 0.01) but no inflammatory biomarker was significantly associated with Abeta deposition. Having a history of rMDD (beta ‐0.09, 95% CI ‐0.26, 0.08, p = 0.28) or MCI alone (beta ‐0.11, 95% CI ‐0.47, 0.049, p = 0.11) was not associated with deposition of Abeta. Conclusion In this cross‐sectional analysis, we did not find an association between LPS/LBP, immune biomarkers, remitted MDD and global deposition of Abeta. Future analyses should examine the longitudinal relationships between peripheral and central biomarkers of immune activation with cerebral Abeta deposition in patients and controls.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".