Aβ42 mediated activation of the NLRP3 inflammasome predicts cognitive and gait performance in midlife type 2 diabetes mellitus (T2DM)
Bibliographic record
Abstract
Abstract Background Midlife Type 2 Diabetes Mellitus (T2DM) is a potent risk factor for later development of dementia. However, putative mechanisms mediating this risk are poorly understood. The NLRP3 inflammasome receptor, which drives strong pro‐inflammatory responses, has been implicated in both T2DM and Alzheimer’s disease (AD) pathogenesis, and can be activated by Amyloid β1‐42 (Aβ42). Method Peripheral Blood Mononuclear Cells (PBMCs) were isolated from participants with T2DM (N = 39; 52.04 ± 8.01 years) and matched controls (N = 21; 52.16 ± 7.82 years) without any evidence of cognitive impairment. PBMCs were incubated for 18 hours under the following conditions: (i) Lipopolysaccharide (LPS), (ii) Aβ42, (iii) LPS & Aβ42 and (iv) LPS & Nigericin (potent NLRP3 activator). Cytokine production was measured using ELISA and gene expression using qPCR. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA). Gait speed was measured under normal and dual‐task conditions (reciting alternate letters of the alphabet). Wilcoxon rank‐sum tests were used for univariate analysis and Poisson and linear regression models used for multivariate analyses, adjusting for important covariates. Results Treatment of PBMCs under all four conditions resulted in a significant production of the pro‐inflammatory cytokines IL‐1β and IL‐6, which did not differ between T2DM and healthy controls. Greater IL‐1β production (an NLRP3‐dependent cytokine) under both Aβ‐42 (ii) and LPS & Nigericin (iv) conditions was associated with greater likelihood of error on the MoCA (aIRR 1.01, p = 0.010; aIRR 1.01, p = 0.004). Further, greater IL‐1β production under both LPS & Aβ42 (iii) and LPS & Nigericin (iv) conditions was associated with a greater slowing effect (cost) on the dual‐task (adjusted: β = 0.31, 0.04‐0.58, p = 0.023; 0.029, 0.05 – 0.54, p = 0.019). Effects were seen in the cohort overall, regardless of T2DM status, but were stronger in those with T2DM. Conclusions Greater activation of the NLRP3 inflamamsome by Aβ42 was associated with poorer cognitive and gait performance in midlife T2DM. Further work will follow this cohort longitudinally and assess the ability of innate immune NLRP3 activity to predict later cognitive trajectories in those with midlife T2DM.
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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) | 0.001 | 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 | 0.001 | 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".