Disease-associated mutations in C-terminus of HSP70 interacting protein (CHIP) impair its ability to negatively regulate mitophagy
Bibliographic record
Abstract
C-terminus of HSP70 interacting protein (CHIP) is an E3 ubiquitin ligase and HSP70 cochaperone. Mutations in the CHIP encoding gene are the cause of two neurodegenerative conditions: spinocerebellar ataxia autosomal dominant type 48 (SCA48) and autosomal recessive type 16 (SCAR16). The mechanisms underlying CHIP-associated diseases are currently unknown. Mitochondrial dysfunction, specifically dysfunction in mitochondrial autophagy (mitophagy), is increasingly implicated in neurodegenerative diseases and loss of CHIP has been demonstrated to result in mitochondrial dysfunction in multiple animal models, although how CHIP is involved in mitophagy regulation has been previously unknown. Here, we demonstrate that CHIP acts as a negative regulator of the PTEN-induced kinase 1 (PINK1)/Parkin-mediated mitophagy pathway, promoting the degradation of PINK1, impairing Parkin translocation to the mitochondria, and suppressing mitophagy in response to mitochondrial stress. We also show that loss of CHIP enhances neuronal mitophagy in a PINK1 and Parkin dependent manner in Caenorhabditis elegans. Furthermore, we find that multiple disease-associated mutations in CHIP dysregulate mitophagy both in vitro and in vivo in C. elegans neurons, a finding which could implicate mitophagy dysregulation in CHIP-associated diseases.
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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 | 0.000 | 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) | 0.002 | 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".