Analysis of cognitive status of Alzheimer’s disease’s subjects and its association with biomarkers (amyloid beta and tau proteins) using NACC data
Bibliographic record
Abstract
Despite extensive research on amyloid-beta ( $$A\beta$$ ) and tau protein aggregation, the precise role of biomarkers in Alzheimer’s disease (AD) remains ambiguous. We use data provided by National Alzheimer’s Coordinating Center (NACC) to understand the relation between key biomarkers phosphorylated Tau (Ptau $$_{181}$$ ), Amyloid-beta ( $$A\beta _{1-42}$$ ), Total tau (Ttau), their ratios and the cognitive status of subjects. We use both Cerebrospinal Fluid (CSF) biomarkers, analyzed Positron Emission Tomographi (PET) outcomes and presence of hippocampal atrophy. This study analyzes biomarkers such as phosphorylated Tau (Ptau $$_{181}$$ ), Amyloid-beta $$A\beta _{1-42}$$ ), Total Tau (Ttau), their ratio, as well as clinical data from individuals diagnosed with Alzheimer’s and controls, compiled by the NACC. Total of 1821 rows data collected from 1347 unique subjects with CSF biomarkers were analyzed. These subjects are further categorized in different Phases and Changes of cognitive impairments. We utilized statistical techniques (ANOVA, Seive Plot, Logistic Regression) and visualization methods (Boxplot, Barplot, Violin Plot) to understand the relationships. A significant correlation was identified between severe cognitive impairment and the phosphorylated ( $$Ptau_{181}$$ ) to $$A\beta _{1-42}$$ ratio and total Tau (Ttau) to $$A\beta$$ ratio, which was negatively correlated in subjects with normal cognitive status. In both case the p-value were $$<0.005$$ .Low mean of $$A\beta$$ were found in the subjects with worst cognitive status, whereas higher mean of Ptau and Ttau were observed, which is the known characteristics of AD pathology. Likewise, higher variability in CSF Ptau, CSF Ttau, and CSF $$A\beta _{1-42}$$ biomarkers were found in subjects with worsened cognitive status. Additionally, there was a higher presence of hippocampal-atrophy and tau protein evidence in AD. Biomarkers such as $$A\beta _{1-42}$$ , $$Ptau_{181}$$ , Ttau and their ratio seems to exhibit significant variability and correlation with cognitive decline in AD. Targeting these biomarkers at specific disease stages may improve the efficacy of treatments. We further evaluated this by segregating subjects into multiple phases of the disease and different changes category. But this study assumes independence of these biomarkers and does not consider the confounders such as age, ethnicity, time of onset, diagnosis, underlying clinical pathologies which may be affecting the underlying process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".