Contribution of cardiovascular comorbidities to Alzheimer’s Disease (AD) among older adults with low plasma AD biomarker level
Bibliographic record
Abstract
Abstract Background There has been a great advancement in clinical application of blood‐based biomarkers of Alzheimer’s Disease (AD) over the past years. We aimed to examine whether cardiovascular comorbidities may contribute to clinical cognitive impairment in individuals with low level of these biomarkers. Method The current cross‐sectional study included 969 elderly [562 cognitively unimpaired, 407 cognitive impairment (104 amnestic MCI and 303 AD)] participants of the Washington Heights, Hamilton Heights, and Inwood Columbia Aging Project (WHICAP) study. We used Quanterix SIMOA HD‐X platforms to measure phosphorylated Tau‐181 (P‐tau181), total (T‐tau), Amyloid beta (Aβ) 40, Aβ42, Glial Fibrillary Acid Protein (GFAP), and Neurofilament Light Chain. Individuals were characterized as ‘biomarker positive’ or ‘biomarker negative’ based on combined GFAP and P‐tau181/Aβ42 cut scores. Clustering of cardiovascular comorbidities was defined as the total number of conditions including diabetes, hypertension, heart disease, and stroke. The association between the cardiovascular comorbidities and cognitive impairment was examined using logistic regression, adjusted for age, sex, ethnic group, and years of education. Result Among individuals with 0 ‐ 4 cardiovascular comorbidities, 20%, 43%, 42%, 52%, and 70% had cognitive impairment, respectively (p<0.001). Individuals with more cardiovascular conditions were more likely to be Hispanics, but not different in biomarker positivity status, sex, age, or education. Based on GFAP and P‐tau181/Aβ42, 188 (19.4%) were biomarker positive. As expected, being biomarker positive was associated with higher odds (OR=2.0, 95%CI=1.3‐3.2, P=0.002) of having cognitive impairment, after adjusting for age, sex, ethnic group, and years of education, and comorbidities score. Still, 37% of the 781 biomarker negative individuals had cognitive impairment. We further found that among these biomarker negative individuals, having more comorbidities (OR=1.40, 95%CI=1.02‐1.92, P=0.035) was associated with higher odds, while education was associated with lower odds (OR=0.80, 95%CI=0.75‐0.85, P<0.001), of having cognitive impairment. No association of comorbidity and cognitive impairment (OR=1.2, 95%CI=0.68‐2.15, P=0.52) was found in biomarker positive individuals. Conclusion Plasma AD‐related biomarkers were associated with clinical cognitive impairment. Older adults with low level of AD biomarkers may still be at risk of developing cognitive impairment if they have high burden of cardiovascular comorbidities.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".