Estimating the Prevalence of Alzheimer's Disease Pathology Using Plasma Biomarkers in COMPASS‐ND
Bibliographic record
Abstract
BACKGROUND: The Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS-ND) study is a national Canadian observational study of participants clinically diagnosed with various forms of dementia and cognitive complaints. Here, we utilize plasma biomarkers including amyloid beta (Aβ42/40), phosphorylated tau-181 (p-tau-181), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP), to estimate the prevalence of Alzheimer's disease (AD) pathology in COMPASS-ND. This enables us to assess concordance between clinical presentation and underlying pathogenesis in participants. METHOD: Biomarkers were analysed in COMPASS-ND plasma samples (n = 936) using the Quanterix Simoa HD-X analyzer with Neurology 4-plex E and p-tau-181 assays. A sub-cohort (n = 150) of participants with cerebrospinal fluid (CSF) Aβ42, p-tau-181 and total tau (Roche Elecsys assays) were utilized to determine plasma biomarker cut-offs. Area under the receiver operating curve (AUROC) analysis was conducted. Cut-offs, determined at the Youden's index, were then applied to the remaining COMPASS-ND participants to estimate the percentage of biomarker positive individuals in each clinically determined diagnostic group. RESULT: Of the COMPASS-ND participants with CSF, 80% (n = 120) were on the AD continuum. AUROC analysis revealed an area of 0.768 for Aβ42/40, 0.638 for p-tau-181, 0.559 for NfL, and 0.689 for GFAP. Cut-offs for plasma biomarkers to be considered on the AD continuum were Aβ42/40 <0.068 pg/mL, p-tau-181 >2.7 pg/mL, NfL >18.6 pg/mL, and GFAP >134.9 pg/mL. A multi-biomarker cut-off based on having positive results for 2 out of 3 from Aβ42/40, p-tau-181, and GFAP, yielded a sensitivity of 64% and specificity of 83%. In the remaining n = 786 COMPASS-ND participants, the multi-marker panel estimated that AD pathology would be present in 30% (n = 28/93) of cognitively normal, 25% (n = 27/106) of subjective cognitive impairment, 52% (n = 167/321) of mild cognitive impairment, 83% (n = 96/116) of AD, 73% (n = 16/22) of Lewy body dementia, 45% (n = 13/29) of frontal temporal dementia, and 34% (n = 34/99) of Parkinson's disease participants. CONCLUSION: The plasma biomarkers assays tested have high specificity for detecting AD pathology, enabling their use to estimate AD pathology in a larger cohort. Based on the low sensitivity of the plasma biomarkers tested, we assume that these results underestimate the prevalence of AD pathology in the COMPASS-ND cohort.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.000 |
| 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".