An inherited mitochondrial DNA mutation remodels inflammatory cytokine responses in macrophages and in vivo in mice
Bibliographic record
Abstract
Abstract Impaired mitochondrial bioenergetics in macrophages promotes hyperinflammatory cytokine responses, but whether inherited mtDNA mutations drive similar phenotypes is unknown. Here, we profiled macrophages harbouring a heteroplasmic mitochondrial tRNA Ala mutation ( m.5019A > G ) to address this question. These macrophages exhibit combined respiratory chain defects, reduced oxidative phosphorylation, disrupted cristae architecture, and compensatory metabolic adaptations in central carbon metabolism. Upon inflammatory activation, m.5019A > G macrophages produce elevated type I interferon (IFN), while exhibiting reduced pro-inflammatory cytokines and oxylipins. Mechanistically, suppression of pro-IL-1β and COX2 requires autocrine IFN-β signalling. IFN-β induction is biphasic: an early TLR4-IRF3 driven phase, and a later response involving mitochondrial nucleic acids and the cGAS-STING pathway. In vivo, lipopolysaccharide (LPS) challenge of m.5019A > G mice results in elevated type I IFN signalling and exacerbated sickness behaviour. These findings reveal that a pathogenic mtDNA mutation promotes an imbalanced innate immune response, which has potential implications for the progression of pathology in mtDNA disease patients.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".