Cross‐Sectional and Longitudinal Associations of Mild Behavioural Impairment‐Apathy and Alzheimer’s Disease‐Related Biomarkers
Bibliographic record
Abstract
Abstract Background Apathy, characterized by decreased interest, initiative, and emotional reactivity, is amongst the most common neuropsychiatric symptoms in Alzheimer’s Disease (AD) dementia, but it can also manifest in prodromal, and even preclinical disease stages. Apathy in individuals who are cognitively normal and who have mild cognitive impairment (MCI), is associated with accelerated progression to AD, and apathy in AD has been associated with greater disability, lower quality of life, poorer health, greater caregiver distress and burden, as well as higher morbidity and mortality. The multitude of negative outcomes associated with apathy highlight the importance of research whose primary goal is to identify mild behavioural impairment(MBI)‐apathy in non‐dementia samples and combine this behavioural syndrome with well‐established AD‐biomarkers, such as beta‐amyloid (Aβ), phosphorylated tau (p‐tau), and total tau (t‐tau), to better predict AD dementia risk. Method Dementia‐free participants in the Alzheimer’s Disease Neuroimaging Initiative were stratified as MBI‐apathy and no neuropsychiatric symptoms (no‐NPS) based on Neuropsychiatric Inventory (NPI) and NPI‐Questionnaire (NPI‐Q) scores at two consecutive visits. Covariates of interest included age, sex, apolipoprotein ε4 carriership, years of education, Mini Mental State Examination scores, and the questionnaire NPS status was derived from. Linear regressions assessed the association of MBI‐apathy (predictor) with Aβ40, Aβ42, p‐tau181, t‐tau, Aβ40/Aβ42, p‐tau181/Aβ42, and t‐tau/Aβ42 (outcome variables). We also used linear mixed effect models for repeated measures to investigate change in our outcome variables across a two‐year period. Results Of the 253 participants (127 CN); 51 had MBI‐apathy. MBI‐apathy was found to be significantly associated with baseline p‐tau181/Aβ42 (p<0.05) and t‐tau/Aβ42 (p<0.05) ratios. MBI‐apathy was also found to be significantly associated with changes in Aβ42 (p = 0.001), Aβ40/Aβ42 (p<0.01), p‐tau181/Aβ42 (p = 0.001), and t‐tau/Aβ42 (p = 0.001) levels and ratios over a two‐year period. Conclusion To our knowledge, this is the first study examining the relationship between MBI‐apathy and AD‐related biomarkers. Results suggest that MBI‐apathy is significantly associated with several AD‐related biomarkers both cross‐sectionally and longitudinally. Combining the presence of persistent and emergent apathy with these biomarkers might serve as a prognostically useful approach for predicting AD dementia at a time when there is opportunity for intervention.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".