Cortical β-amyloid burden, neuropsychiatric symptoms, and cognitive status: the Mayo Clinic Study of Aging
Bibliographic record
Abstract
Abstract Neuropsychiatric symptoms (NPS) are a risk factor for cognitive impairment and are associated with cortical β-amyloid (Aβ) deposition. We conducted a cross-sectional study derived from the ongoing population-based Mayo Clinic Study of Aging to examine the frequency of NPS among cognitively unimpaired (CU) and mild cognitive impairment (MCI) participants who either have normal (A−) or abnormal (A+) Aβ deposition. We also investigated whether combined presence of MCI and amyloid positivity (MCI/A+) is associated with greater odds of having NPS as compared to CU/A− (defined as reference group). Participants were 1627 CU and MCI individuals aged ≥ 50 years (54% males; median age 73 years). All participants underwent NPS assessment (Neuropsychiatric Inventory Questionnaire (NPI-Q); Beck Depression Inventory II (BDI-II); Beck Anxiety Inventory (BAI)) and 11C-PiB-PET. Participants with an SUVR > 1.42 were classified as A+. We conducted multivariable logistic regression analyses adjusted for age, sex, education, and APOE ε4 genotype status. The sample included 997 CU/A−, 446 CU/A+, 78 MCI/A−, and 106 MCI/A+ persons. For most NPS, the highest frequency of NPS was found in MCI/A+ and the lowest in CU/A−. The odds ratios of having NPS, depression (BDI ≥ 13), or anxiety (BAI ≥ 8, ≥ 10) were consistently highest for MCI/A+ participants. In conclusion, MCI with Aβ burden of the brain is associated with an increased risk of having NPS as compared to MCI without Aβ burden. This implies that the underlying Alzheimer’s disease biology (i.e., cerebral Aβ amyloidosis) may drive both cognitive and psychiatric symptoms.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".