Association of Blood Redox Markers with Alzheimer Disease Biomarkers and Cognitive Performance
Bibliographic record
Abstract
Abstract Background Oxidative stress has been implicated in the pathogenesis of Alzheimer’s disease (AD). Nevertheless, whether redox perturbations are associated with cognition and AD pathology in the preclinical AD stages, remains unclear. We examined associations of blood redox markers with AD biomarkers and cognitive performance in older adults without clinical dementia. Method In a sample of 141 participants without clinical dementia from a memory clinic‐based cohort, we measured total antioxidant capacity (TAC), reduced glutathione (GSH), thiobarbituric acid reactive substances (TBARS), reducing power (RP), and hydroxyl radical scavenging activity (HRSA), using standard laboratory techniques and absorbance spectrophotometry (Hitachi U‐1500). Cerebrospinal fluid (CSF) AD biomarkers, including Aβ42, pTau, and tTau, were measured using automated assays (Elecsys, Roche Diagnostics). Global and domain‐specific (i.e., memory, executive function, language, attention, and visuospatial abilities) cognitive performance was assessed with a comprehensive neuropsychological test battery. Associations of blood redox markers with AD biomarkers and cognitive performance were examined with logistic and linear regression models, respectively. Models were adjusted for age, sex, education, and APOE ε4 carriership. The false discovery rate for each outcome was controlled at <5% using the Benjamini‐Hochberg procedure. Result Mean (SD) age was 64.2 (9.1) years and 95 (67%) of the participants were women (Table 1). Higher TAC and HRSA values were associated with lower odds for pathologically low CSF Aβ42, whereas higher TBARS values were associated with higher odds for pathologically low CSF Aβ42 (Table 2). Higher TAC values were associated with better memory cognitive domain scores, whereas higher TBARS values were associated with worse memory cognitive domain scores (Table 3). Conclusion Higher blood TAC and HRSA, indicating better blood reactive oxygen species‐buffering capacity, were associated with lower odds for pathological CSF Aβ42, whereas higher TBARS, indicating increased lipid peroxidation, was associated with higher odds for pathological CSF Aβ42. Overall, these findings strongly point towards a link between redox imbalance and subclinical AD‐related neuropathology, and highlight the potential role of blood redox markers in AD risk stratification.
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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 | 0.003 |
| 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".