Associations of GFAP, NfL, Aβ42/40, and pTau231 with global cognition in LEADS
Bibliographic record
Abstract
Abstract Background Historically, Alzheimer’s disease (AD) biomarkers have been used to identify the presence of pathology and have been shown to change well ahead of symptom onset. While previous research has evaluated plasma pTau231 and its associations with cognition, little to none of this research has focused on early‐onset AD (EOAD) populations. Here we investigate how select plasma biomarkers are associated with global cognitive measures in early‐onset cognitive impairment. Method The current sample included 367 Longitudinal Early‐Onset AD Study (LEADS) participants (aged 41 to 65) categorized as amyloid PET‐positive EOAD, amyloid PET‐negative EOnonAD, or cognitively normal (CN). Each participant had baseline global cognitive (Mini‐Mental State Examination [MMSE], Montreal Cognitive Assessment [MoCA], Clinical Dementia Rating Scale sum of boxes [CDR‐SB], and ADAS‐Cog13) and plasma biomarker assessments (Simoa‐HDx N4PE kit: Aβ42/40, phosphorylated Tau [pTau231], Neurofilament light protein [NfL], and glial fibrillary acidic protein [GFAP]). Partial correlations were used to check for associations with cognitive performance controlling for age, sex, and years of education. Fisher r‐to‐z transformations were conducted to compare the performance across diagnostic groups. Result Partial correlations in the pooled sample showed moderate associations between cognition and plasma pTau231, GFAP and NfL (r = .42‐.50, p<.001) and weaker associations with Aβ42/40 (r = .25‐.33, p<.001). When split into diagnostic groups, the NfL and GFAP correlations were significant in both EOAD and EOnonAD, but not CN. The pTau231 correlations were significant only in EOAD. Aβ42/40 correlations were non‐significant within specific diagnostic groups. No differences were observed in the magnitude of the cognitive and biomarker associations between EOAD and EOnonAD samples (ps>.05). Conclusion As expected, the neurodegenerative biomarkers pTau231 and NfL showed stronger association with cognition compared to the marker for brain amyloidosis (Aβ42/40). The nonspecific markers for neurodegeneration (NfL) and brain astrogliosis (GFAP) showed associations in both EOAD and EOnonAD while the markers specific to AD were only significant in EOAD. Plasma biomarkers show great promise for AD diagnosis and monitoring.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".