Clinical and biomarker trajectories in sporadic Alzheimer's disease: A longitudinal study
Bibliographic record
Abstract
Abstract Background It has been documented that β‐amyloid (Aβ) deposition, tau pathology and neuronal degeneration precedes clinical symptoms in autosomal dominant Alzheimer's disease (AD). Since the divergence on pathogenesis between sporadic and familial AD limits the extension of these findings to sporadic AD, where and magnitude of pathologic processes in sporadic AD are of significant importance to clinical management. Method In this longitudinal study, we analyzed data from 982 ADNI participants with abnormal amyloid accumulations who underwent cerebrospinal fluid (CSF) test, brain imaging and cognitive assessments. We compared the levels of clinical outcomes and biomarkers at baseline and the rates of change in follow‐up between different stages of AD. The slope of the regression model over years was applied to estimate rates of change for Aβ deposition, tau alteration, hypometabolism, brain atrophy, and cognitive decline. Result In total 167 healthy controls, 133 patients with preclinical AD, 451 patients with MCI due to AD, and 231 patients with dementia due to AD were studied. The levels of clinical and biomarkers at baseline and their change rates at follow‐up significantly differed among the four groups. In terms of average years, Aβ deposition was observed over a range of 45·6 years for CSF Aβ, and 31·1 years with amyloid imaging, although Aβ markers began to be abnormal at 27·8 years for CSF Aβ and 26·3 years for neuroimaging. When Aβ markers exceeded the threshold, CSF tau and other non‐ Aβ markers started to change, and patients were estimated to take 29·1 years (CSF tau),12·7 years (memory), 12·2 years (hippocampus atrophy), 10·1years (hypometabolism) to transition from clinically normal to dementia. Finally, CSF p‐tau significantly increased as dementia onset approached. Conclusion Our results reveal the trajectory of biomarkers in sporadic Alzheimer's disease is led by Aβ accumulation, followed by CSF tau change, memory deficits, brain atrophy, hypometabolism, cognitive decline, and lastly CSF p‐tau increase.
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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 | 0.000 |
| 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) | 0.001 | 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".