CHCHD2 mutant mice link mitochondrial deficits to PD pathophysiology
Bibliographic record
Abstract
Mitochondrial dysfunction is a hallmark of Parkinson’s disease (PD), but the mechanisms by which it drives autosomal dominant and idiopathic forms of PD remain unclear. To investigate this, we generated and performed a comprehensive phenotypic analysis of a knock-in mouse model carrying the T61I mutation in the mitochondrial protein CHCHD2 (coiled-coil–helix–coiled-coil–helix domain–containing 2), which causes late-onset symptoms indistinguishable from idiopathic PD. We observed pronounced mitochondrial disruption in substantia nigra dopaminergic neurons, including distorted ultrastructure and CHCHD2 aggregation, as well as disrupted mitochondrial protein-protein interactions in brain lysates. These abnormalities were associated with a whole-body metabolic shift toward glycolysis, elevated mitochondrial reactive oxygen species (ROS), and progressive accumulation of aggregated α-synuclein. In idiopathic PD, CHCHD2 gene expression also correlated with α-synuclein levels in vulnerable dopaminergic neurons, and CHCHD2 protein accumulated in early Lewy aggregates. These findings delineate a pathogenic cascade in which CHCHD2 accumulation impairs mitochondrial respiration and increases ROS production, driving α-synuclein aggregation and neurodegeneration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".