Plasma Cytokines Profile in Subjects with Alzheimer’s Disease: Interleukin 1 Alpha as a Candidate for Target Therapy
Bibliographic record
Abstract
Background: Alzheimer's disease (AD) is the main cause of the neurodegenerative disorder, which is not detected unless the cognitive deficits are manifested. An early prediagnostic specific biomarker preferably detectable in plasma and hence non-invasive is highly sought-after. Various hypotheses refer to AD, with amyloid-beta (Aβ) being the most studied hypothesis and inflammation being the most recent theory wherein pro-and anti-inflammatory cytokines are the main culprits. Materials and Methods: In this study, the cognitive performance of AD patients (n=39) was assessed using mini-mental state examination (MMSE), AD assessment scale-cognitive subscale (ADAS-cog), and clinical dementia rating (CDR). Their neuropsychiatric symptoms were evaluated through neuropsychiatric inventory-questionnaire (NPI-Q). Moreover, plasma levels of routine biochemical markers, pro-/anti-inflammatory cytokines such as tumor necrosis factor α (TNF-α), interleukin-1 α (IL-1α), IL-1β, IL-2, IL-4, IL-6, IL-8, IL-12p70, IL-10, Interferon-gamma, chemokines, including prostaglandin E2 (PGE-2), monocyte chemoattractant protein-1, interferon gamma-induced protein 10, Aβ peptide species (42, 40) and Transthyretin (TTR) were measured. Results: Our results revealed that Aβ 42/40 ratio and TTR were correlated (r=0.367, P=0.037). IL-1α was directly correlated with ADAS-cog (r=0.386, P=0.017) and Aβ 40 (r=0.379, P=0.019), but was inversely correlated with IL-4 (r=-0.406, P=0.011). Negative correlations were found between MMSE and PGE2 (r=-0.405, P=0.012) and TNF-α/ IL-10 ratio (r=-0.35, P=0.037). CDR was positively correlated with both PGE2 (r=0.358, P=0.027) and TNF-α (r=0.416, P=0.013). There was a positive correlation between NPI-caregiver distress with CDR (r=0.363, P=0.045) and ADAS-cog (r=0.449, P=0.019). Conclusion: Based on the observed correlation between IL-1α, as a clinical moiety, and ADAS-cog, as a clinical manifestation of AD, anti-IL-1α therapy in AD could be suggested.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".