Levels of Soluble Interleukin 6 Receptor and Asp358Ala Are Associated With Cognitive Performance and Alzheimer Disease Biomarkers
Bibliographic record
Abstract
Background and Objectives Alzheimer disease (AD) is a neurodegenerative disease process manifesting clinically with cognitive impairment and dementia. AD pathology is complex, and in addition to plaques and tangles, neuroinflammation is a consistent feature. Interleukin (IL) 6 is a multifaceted cytokine involved in a plethora of cellular mechanisms including both anti-inflammatory and inflammatory processes. IL6 can signal classically through the membrane-bound receptor or by IL6 trans-signaling forming a complex with the soluble IL6 receptor (sIL6R) and activating membrane-bound glycoprotein 130 on cells not expressing IL6R. IL6 trans-signaling has been demonstrated as the primary mechanism of IL6-mediated events in neurodegenerative processes. In this study, we performed a cross-sectional analysis to investigate whether inheritance of a genetic variation in the IL6R gene and associated elevated sIL6R levels in plasma and CSF were associated with cognitive performance. Methods We genotyped the IL6R rs2228145 nonsynonymous variant (Asp358Ala) and assayed IL6 and sIL6R concentrations in paired samples of plasma and CSF obtained from 120 participants with normal cognition, mild cognitive impairment, or probable AD enrolled in the Wake Forest Alzheimer9s Disease Research Center9s Clinical Core. IL6 rs2228145 genotype and measures of plasma IL6 and sIL6R were assessed for relationships with cognitive status and clinical data, including the Montreal Cognitive Assessment (MoCA), modified Preclinical Alzheimer9s Cognitive Composite (mPACC), cognitive domain scores obtained from the Uniform Data Set, and CSF concentrations of phosphoTauT181 (pTau181), β-amyloid (Aβ) Aβ40 and Aβ42 concentrations. Results We found that inheritance of the IL6R Ala358 variant and elevated sIL6R levels in plasma and CSF were correlated with lower mPACC, MoCA and memory domain scores, increases in CSF pTau181, and decreases in the CSF Aβ42/40 ratio in both unadjusted and covariate-adjusted statistical models. Discussion These data suggest that IL6 trans-signaling and the inheritance of the IL6R Ala358 variant are related to reduced cognition and greater levels of biomarkers for AD disease pathology. Follow-up prospective studies are necessary, as patients who inherit IL6R Ala358 may be identified as ideally responsive to IL6 receptor–blocking therapies.
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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 | 0.000 |
| 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 | 0.000 |
| 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".