Neuropsychiatric symptoms are early indicators of an upcoming metabolic decline in Alzheimer’s disease
Bibliographic record
Abstract
Abstract Background Neuropsychiatric symptoms (NPS) are increasingly recognized as early non-cognitive manifestations in the Alzheimer’s disease (AD) continuum. However, the role of NPS as an early marker of pathophysiological progression in AD remains unclear. Dominantly inherited AD (DIAD) mutation carriers are young individuals who are destined to develop AD in future due to the full penetrance of the genetic mutation. Hence, the study of DIAD mutation carriers enables the evaluation of the associations between pure AD pathophysiology and metabolic correlates of NPS without the confounding effects of co-existing pathologies. In this longitudinal study, we aim to identify regional brain metabolic dysfunctions associated with NPS in cognitively intact DIAD mutation carriers. Methods We stratified 221 cognitively intact participants from the Dominantly Inherited Alzheimer’s Network according to their mutation carrier status. Regression mixed effect models with family-level random effects evaluated the interactions of NPS measured by the Neuropsychiatric Inventory-Questionnaire (NPI-Q), age and estimated years of onset (EYO) as a function of metabolism measured by [ 18 F]flurodeoxyglucose ([ 18 F]FDG) positron emission tomography in DIAD mutation and non-mutation carriers. An exploratory factor analysis was performed to identify the neuropsychiatric subsyndromes in DIAD mutation carriers using the NPI-Q sub-components. Regression mixed effect models then evaluated the interactions of specific neuropsychiatric subsyndromes with EYO on metabolism.Results 119 mutation and 102 non-mutation carriers were studied. The interaction of higher NPI-Q and shorter EYO was associated with more rapid global and regional [ 18 F]FDG uptake decline in the posterior cingulate and ventromedial prefrontal cortices, bilateral parietal lobes and right insula in DIAD mutation carriers. The neuropsychiatric subsyndrome of agitation, disinhibition, irritability and depression interacted with EYO to drive [ 18 F]FDG uptake decline in the DIAD mutation carriers. The interaction of NPI and EYO was not associated with [ 18 F]FDG uptake in DIAD non-mutation carriers. Conclusions NPS in cognitively intact DIAD mutation carriers may be clinical indicators of subsequent metabolic decline in brain networks vulnerable to AD, which support the emerging conceptual framework that NPS represent early manifestations of neuronal injury in AD. Further studies using different methodological approaches to identify NPS in preclinical AD are needed to validate our findings.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".