Presenilin mutations disrupt iron homeostasis to promote ferroptosis mediated neurodegeneration in Caenorhabditis elegans
Bibliographic record
Abstract
Iron is a vital trace element involved in numerous physiological processes, but it becomes toxic when present in excess. Disruption of iron balance in the brain has been linked to the development of neurodegenerative diseases such as Alzheimer's disease (AD), though the underlying mechanisms remain poorly understood. Familial forms of AD are primarily caused by mutations in presenilin, which are known to disturb cellular calcium homeostasis. However, the role of iron in presenilin-related neurodegeneration has not been fully explored. Using C. elegans as a model organism, we investigated the function of SEL-12, the worm ortholog of presenilin, and found that loss of SEL-12 leads to elevated iron levels and increased expression of FTN-2/ferritin, an iron-sequestering protein. Notably, reducing mitochondrial calcium in sel-12 mutants prevented this iron accumulation, indicating that elevated mitochondrial calcium drives increased cellular iron levels. This iron overload depends on mitochondrial superoxide production, which occurs alongside heightened mitochondrial calcium, suggesting that oxidative stress contributes to iron dysregulation. The resulting iron imbalance causes mitochondrial and lysosomal dysfunction, ultimately impairing neuronal and behavioral function. Supporting the involvement of iron, sel-12 mutants exhibit elevated lipid peroxidation, and inhibition of ferroptosis restores neuronal function. Together, these findings reveal a novel role for presenilin in regulating iron homeostasis and identify a mechanism linking calcium signaling disruption to iron dyshomeostasis and neurodegeneration.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".