Immune cell mitochondrial phenotypes are largely preserved in mitochondrial diseases and do not reflect disease severity
Bibliographic record
Abstract
ABSTRACT Objective To profile immune cell mitochondrial phenotypes in mitochondrial diseases (MitoD) and evaluate how those phenotypes relate to disease manifestations or biomarkers. Methods We profiled mitochondrial content and oxidative phosphorylation (OxPhos) enzymatic activities in isolated monocytes, lymphocytes, neutrophils, platelets, and mixed peripheral blood mononuclear cells (PBMCs) from 37 individuals with MitoD (m.3243A>G, n=23; single, large-scale mitochondrial DNA (mtDNA) deletions, n=14) and 68 healthy women and men from the Mitochondrial Stress, Brain Imaging, and Epigenetics (MiSBIE) study. Results We first confirm and quantify robust cell type differences in mitochondrial content, activities of OxPhos complexes I, II, and IV, and the mitochondrial respiratory capacity (MRC) index. In relation to MitoD, neither mitochondrial content nor OxPhos capacity were consistently affected, other than a mild monocyte-specific reduction in complex I (partially mtDNA encoded) relative to complex II (entirely nDNA encoded), consistent with the mtDNA defects examined. Relative to the large differences in cell type-specific mitochondrial phenotypes, differences in MitoD relative to controls were generally small (<25%) across mitochondrial measures. The MitoD biomarkers GDF15 and FGF21, as well as clinical disease severity measures, were most strongly related to mitochondrial abnormalities in platelets, and most weakly related to mitochondrial OxPhos capacity in lymphocytes, which are known to eliminate mtDNA defects. Finally, comparing PBMCs collected in the morning/fasted state to the afternoon/fed state following a stressful experience, we report significant time-dependent changes in mitochondrial biology over the time scale of hours. Conclusions Overall, these results demonstrate that the dynamic and cell-type specific mitochondrial phenotypes are preserved in mitochondrial diseases and are generally unrelated to the severity of MitoD symptoms.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".