Brain cell densities are associated with hypometabolism and Aβ burden in Alzheimer’s disease
Bibliographic record
Abstract
BACKGROUND: Neurons and glial cells, such as astrocytes, microglia, and oligodendrocytes, compose and orchestrate the synaptic process. The pathogenesis of Alzheimer's Disease (AD), which includes amyloid-beta (Aβ) accumulation, can disrupt these cell functions leading to brain glucose hypometabolism, which is generally interpreted as a signal of neurodegeneration. Therefore, it is crucial to understand the potential relationship between neuronal and glial cell densities with AD progression. Here, we investigated how brain cellular densities associate with FDG- and Aβ-PET imaging across regions implicated in AD. METHOD: We obtained FDG- and Aβ-PET images from 619 cognitively unimpaired (CU) and impaired (CI) individuals from ADNI. Brain cellular abundance maps were sourced from the Neuropm-Lab's GitHub repository. Pearson correlations were conducted between cellular densities and the mean FDG or Aβ SUVr across AD vulnerable and non-vulnerable brain regions (p <0.05). RESULT: Neuronal density positively correlates with FDG-PET in non-vulnerable regions, despite amyloid or cognitive status. However, the delta FDG SUVr (difference between CI and CU) was negatively associated with neuronal density in both non-vulnerable and vulnerable regions for FDG in A+ individuals. Alternatively, a positive correlation was observed between astrocyte density and delta FDG-PET SUVr in vulnerable regions. Oligodendrocytes showed a positive correlation in FDG-vulnerable regions regardless of amyloid or cognitive status (Figure 1A). For Aβ-PET, astrocyte density presented a negative correlation in CU A- individuals in non-vulnerable regions, while neuronal density presented negative correlations despite amyloid or cognitive status. However, in vulnerable regions astrocytes exhibited positive correlations in all groups including the delta Aβ-PET SUVr group (Figure 1B). CONCLUSION: Our findings reveal that higher astrocyte densities are linked to reduced differences in delta FDG SUVr in AD-vulnerable regions, whereas neuronal densities show an inverse correlation. Conversely, oligodendrocytes display positive correlations with FDG-PET. This suggests a compensatory glial metabolism aimed at preserving neuronal homeostasis, supported by the higher proportion of these cells compared to neurons across all brain regions (Figure 1C and D). Additionally, analysis of Aβ-PET data reveals that regions with a higher astrocyte density are linked to a lower amyloid burden in vulnerable areas, further emphasizing the role of glia on amyloid pathology.
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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 | 0.002 | 0.001 |
| 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) | 0.003 | 0.001 |
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".