[P4–077]: ALZHEIMER's BIOMARKERS INTERACT DYNAMICALLY TO PREDICT COGNITIVE TRAJECTORIES DIFFERENTIALLY FOR COGNITIVELY EXCEPTIONAL, NORMAL, AND IMPAIRED GROUPS
Bibliographic record
Abstract
Alzheimer's disease (AD) risk-related biomarkers may be quantitatively modeled for independent or interactive effects on preclinical trajectories of cognitive change. Biomarkers may alter cognitive trajectories (a) independently as risk-reducing or risk-increasing and (b) interactively as risk-intensifying or protection-enhancing. Both modifiable (e.g., vascular health) and non-modifiable (e.g., genetic) biomarkers may exert effects differentially according to important selection classifications (e.g., sex, cognitive status). We examine a series of dynamic AD biomarker interactions (i.e., insulin degrading enzyme [IDE], pulse pressure [PP]) that predict non-demented cognitive performance and longitudinal change differentially for three cognitive status groups. The participants from the Victoria Longitudinal Study (n=623; 53–95 years, M=70.6) were objectively classified in three cognitive status groups: Cognitively Exceptional (CE, n=79), Cognitively Normal (CN, n=394), and Cognitively Impaired (CI, n=150). All participants contributed executive function (EF) performance (6 tests, one latent variable) on up to three waves across 9 years. Latent growth modeling (Mplus) was used for statistical evaluation. First, for the full sample, overall 40-year EF decrements were moderated by PP. Specifically, higher PP (worse vascular health) was associated with worse EF performance and steeper decline; establishing a benchmark dynamic biomarker fan effect. Second, further moderation by IDE showed a dynamic fan effect similar to the benchmark, although homozygote carriers of the risk-increasing allele (AA) had lower performance and steeper decline. Third, markedly differential biomarker interaction effects were observed for each cognitive status group. For the CE group, the dynamic fan effect was evident but at elevated levels and sustained slopes for all IDE x PP combinations. For the CN group, the pattern mirrored that of the overall benchmark with the AA genotype exhibiting steeper decline at all levels of PP. For the CI group, the dynamic fan effect exhibited lower performance, as well as consolidated and steeper decline. The beneficial effects of better vascular health are evident in genetically low risk and cognitively intact adults. However, once cognitive impairment is established vascular health plays an apparent but not significant role in aging decline. Dementia biomarkers from different modalities interact in distinct patterns across non-demented exceptional, normal, and impaired aging groups.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.076 | 0.014 |
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".