Poor Diet, Stress, and Inactivity Converge to Form a “Perfect Storm” That Drives Alzheimer’s Disease Pathogenesis
Bibliographic record
Abstract
North American incidence of Alzheimer's disease (AD) is expected to more than double over the coming generation. Although genetic factors surrounding the production and clearance of amyloid-β and phosphorylated tau proteins are known to be responsible for a subset of early-onset AD cases, they do not explain the pathogenesis of the far more prevalent sporadic late-onset variant of the disease. It is thus likely that lifestyle and environmental factors contribute to neurodegenerative processes implicated in the pathogenesis of AD. Herein, we review evidence that (1) excess sucrose consumption induces AD-associated liver pathologies and brain insulin resistance, (2) chronic stress overdrives activity of locus coeruleus neurons, leading to loss of function (a common event in neurodegeneration), (3) high-sugar diets and stress promote the loss of neuroprotective sex hormones in men and women, and (4) Western dietary trends set the stage for a lithium-deficient state. We propose that these factors may intersect as part of a "perfect storm" to contribute to the widespread prevalence of neurodegeneration and AD. In addition, we put forth the argument that exercise and supplementation with trace lithium can counteract many of the deleterious consequences associated with excessive caloric intake and perpetual stress. We conclude that lifestyle and environmental factors likely contribute to AD pathogenesis and that simple lifestyle and dietary changes can help counteract their effects.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".