Altered glutamine metabolism of cultured fibroblasts predicts severity of cardiac dysfunction in the dilated cardiomyopathy with ataxia syndrome (DCMA), a mitochondrial cardiomyopathy
Bibliographic record
Abstract
Abstract Dilated cardiomyopathy with ataxia (DCMA) syndrome is a rare mitochondrial disorder caused by mutations in the poorly understood DNAJC19 gene. The clinical presentation of DCMA is very diverse with symptoms ranging from mild cardiac dysfunction to intractable heart failure leading to death in early childhood. Although several lines of evidence indicate that DCMA symptoms are linked to mitochondrial function, the molecular underpinnings of this disease are unclear and there is no way to predict which patients are at risk for developing life-threatening symptoms. To address this we developed a metabolic flux assay for assessing the metabolic function of mitochondria in dermal fibroblasts derived from DCMA patients. Using this approach we discovered that fibroblasts from patients with DCMA showed elevated glutamine uptake, increased glutamate and ammonium secretion, and elevated lactate production when compared to controls. Moreover, the magnitude of these metabolic perturbations was closely correlated with patient cardiac dysfunction. This clinical/metabolic correlation was confirmed in a second blinded cohort of DCMA fibroblasts. Moreover, our metabolic flux diagnostic strategy correctly differentiated severe from mild DCMA cases with only one incorrect patient classification (positive predictive value 1.0 and negative predictive value 0.83). These findings suggest that glutamine catabolism is abnormal in DCMA and may serve as an early biomarker for predicting clinical progression. One Sentence Summary Alterations in glutamine and lactate metabolism in patient-derived dermal fibroblasts are associated with the severity of cardiomyopathy in DCMA.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".