Nicotinamide-N-methyltransferase controls behavior, neurodegeneration and lifespan by regulating neuronal autophagy
Bibliographic record
Abstract
Nicotinamide N-methyl-transferase (NNMT) is an essential contributor to various metabolic and epigenetic processes, including the regulating of aging, cellular stress response, and body weight gain. Epidemiological studies show that NNMT is a risk factor for psychiatric diseases like schizophrenia and neurodegeneration, especially Parkinson's disease (PD), but its neuronal mechanisms of action remain obscure. Here, we describe the role of neuronal NNMT using C. elegans. We discovered that ANMT-1, the nematode NNMT ortholog, competes with the methyltransferase LCMT-1 for methyl groups from S-adenosyl methionine. Thereby, it regulates the catalytic capacities of LCMT-1, targeting NPRL-2, a regulator of autophagy. Autophagy is a core cellular, catabolic process for degrading cytoplasmic material, but very little is known about the regulation of autophagy during aging. We report an important role for NNMT in regulation of autophagy during aging, where high neuronal ANMT-1 activity induces autophagy via NPRL-2, which maintains neuronal function in old wild type animals and various disease models, also affecting longevity. In younger animals, however, ANMT-1 activity disturbs neuronal homeostasis and dopamine signaling, causing abnormal behavior. In summary, we provide fundamental insights into neuronal NNMT/ANMT-1 as pivotal regulator of behavior, neurodegeneration, and lifespan by controlling neuronal autophagy, potentially influencing PD and schizophrenia risk in humans.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".