Zinc Status Alters Alzheimer's Disease Progression through NLRP3-Dependent Inflammation
Bibliographic record
Abstract
Alzheimer's disease is a devastating neurodegenerative disease with a dramatically increasing prevalence and no disease-modifying treatment. Inflammatory lifestyle factors increase the risk of developing Alzheimer's disease. Zinc deficiency is the most prevalent malnutrition in the world and may be a risk factor for Alzheimer's disease potentially through enhanced inflammation, although evidence for this is limited. Here we provide epidemiological evidence suggesting that zinc supplementation was associated with reduced risk and slower cognitive decline, in people with Alzheimer's disease and mild cognitive impairment. Using the APP/PS1 mouse model of Alzheimer's disease fed a control (35 mg/kg zinc) or diet deficient in zinc (3 mg/kg zinc), we determined that zinc deficiency accelerated Alzheimer's-like memory deficits without modifying amyloid β plaque burden in the brains of male mice. The NLRP3-inflammasome complex is one of the most important regulators of inflammation, and we show here that zinc deficiency in immune cells, including microglia, potentiated NLRP3 responses to inflammatory stimuli in vitro , including amyloid oligomers, while zinc supplementation inhibited NLRP3 activation. APP/PS1 mice deficient in NLRP3 were protected against the accelerated cognitive decline with zinc deficiency. Collectively, this research suggests that zinc status is linked to inflammatory reactivity and may be modified in people to reduce the risk and slow the progression of Alzheimer's disease. SIGNIFICANCE STATEMENT Alzheimer's disease is a common condition mostly affecting the elderly. Zinc deficiency is also a global problem, especially in the elderly and also in people with Alzheimer's disease. Zinc deficiency contributes to many clinical disorders, including immune dysfunction. Inflammation is known to contribute to the risk and progression of Alzheimer's disease; thus, we hypothesized that zinc status would affect Alzheimer's disease progression. Here we show that zinc supplementation reduced the prevalence and symptomatic decline in people with Alzheimer's disease. In an animal model of Alzheimer's disease, zinc deficiency worsened cognitive decline because of an enhancement in NLRP3-driven inflammation. Overall, our data suggest that zinc status affects Alzheimer's disease progression, and that zinc supplementation could slow the rate of cognitive decline.
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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 | 0.000 |
| 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) | 0.001 | 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".