[P1–452]: COMBINED GLOBAL AND REGIONAL AMYLOID EFFECT ON THE DEFAULT MODE NETWORK LEADS TO COGNITIVE DECLINE
Bibliographic record
Abstract
The association between amyloid-β aggregates, default mode network (DMN) dysfunction, and dementia symptoms remains unclear in Alzheimer's disease (AD). Although individuals presenting both abnormal amyloid-β and hypometabolism in posterior DMN are especially vulnerable to disease progression, the lack of a strong association between regional amyloid-β burden and metabolic or cognitive dysfunction has puzzled researchers. The present study was designed to test the hypothesis that the widespread global amyloid-β aggregation determines the metabolic dysfunction of the brain's posterior DMN, whereas a synergistic interaction between the regional toxic effects of amyloid-β aggregates and the levels of local network dysfunction determines the subsequent clinical progression to AD dementia. We performed a longitudinal study using a computational framework developed to perform voxel-wise multimodal statistics in human or animal brain image (Fig.1). We studied 347 mild cognitive impairment (MCI) ADNI participants and 20 transgenic McGill-R-Thy1-APP rats overexpressing amyloid-β precursor protein with mild cognitive symptoms with T1-weighted magnetic resonance imaging, [F]fluorodeoxyglucose and amyloid-β positron emission tomography (PET) at baseline, as well as cognition at baseline and follow-up. Voxel-wise regression analyses taking into consideration global and voxel standardized uptake values tested the associations between Aβ deposition, glucose metabolism, and cognition (MCIs, all available follow-ups up to 5.6 years; rats, 8-month follow-up). Analysis of covariance was used to further compare the models. We found that global brain amyloid-β burden determined regional metabolic hypometabolism in the functional hubs of the brain's posterior DMN at baseline (P < 0.001). Furthermore, we found that the regional, rather than the global, levels of amyloid-β aggregates in posterior DMN synergistically interact with the regional levels of network dysfunction to determine subsequent clinical progression to dementia. Notably, the same results in the posterior DMN of the transgenic amyloid-β rats, which do not form neurofibrillary tangles, supported this model as an independent mechanism of cognitive deterioration (Fig.2). These findings highlight a model where a widespread amyloid-β aggregation determines the vulnerability of the well conserved – in mammals – DMN, whereas the synergism between this vulnerability and the regional concentrations of amyloid-β aggregates determines dementia symptoms.
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 | 0.000 | 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) | 0.004 | 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".