Multi-Tissue Metabolomics Reveal mtDNA- and Diet-Specific Metabolite Profiles in a Mouse Model of Cardiometabolic Disease
Bibliographic record
Abstract
Abstract Rationale Excess consumption of sugar- and fat-rich foods has heightened the prevalence of cardiometabolic disease, which remains a driver of cardiovascular disease- and type II diabetes-related mortality globally. Skeletal muscle insulin resistance is an early feature of cardiometabolic disease and is a precursor to diabetes. Insulin resistance risk varies with self-reported race, whereby, African-Americans have a greater risk of diabetes development relative to their White counterparts. Self-reported race is strongly associated with mitochondrial DNA (mtDNA) haplogroups, and previous reports have noted marked differences in bioenergetic and metabolic parameters in cells belonging to distinct mtDNA haplogroups, but the mechanism of these associations remains unknown. Additionally, distinguishing nuclear DNA (nDNA) and mtDNA contributions to cardiometabolic disease remains challenging in humans. The Mitochondrial-Nuclear eXchange (MNX) mouse model enables in vivo preclinical investigation of the role of mtDNA in cardiometabolic disease development, and has been implemented in studies of insulin resistance, fatty liver disease, and obesity in previous reports. Methods Six-week-old male C57 nDNA :C57 mtDNA and C3H nDNA :C3H mtDNA wild-type mice, and C57 nDNA :C3H mtDNA and C3H nDNA :C57 mtDNA MNX mice, were fed sucrose-matched high-fat (45% kcal fat) or control diet (10% kcal fat) until 12 weeks of age (n = 5/group). Mice were weighed weekly and total body fat was collected at euthanasia. Gastrocnemius skeletal muscle and plasma metabolomes were characterized using untargeted dual-chromatography mass spectrometry; both hydrophilic interaction liquid chromatography (HILIC) and C18 columns were used, in positive- and negative-ion modes, respectively. Results Comparative analyses between nDNA-matched wild-type and MNX strains demonstrated significantly increased body fat percentage in mice possessing C57 mtDNA regardless of nDNA background. High-fat diet in mice possessing C57 mtDNA was associated with differential abundance of phosphatidylcholines, lysophosphatidylcholines, phosphatidylethanolamines, and glucose. Conversely, high-fat diet in mice possessing C3H mtDNA was associated with differential abundance of phosphatidylcholines, cardiolipins, and alanine. Glycerophospholipid metabolism and beta-alanine signaling pathways were enriched in skeletal muscle and plasma, indicating mtDNA-directed priming of mitochondria towards oxidative stress and increased fatty acid oxidation in C57 nDNA :C57 mtDNA wild-type and C3H nDNA :C57 mtDNA MNX mice, relative to their nDNA-matched counterparts. In mtDNA-matched mice, C57 mtDNA was associated with metabolite co-expression related to the pentose phosphate pathway and sugar-related metabolism; C3H mtDNA was associated with branched chain amino acid metabolite co-expression. Conclusions These results reveal novel nDNA-mtDNA interactions that drive significant changes in metabolite levels. Alterations to key metabolites involved in mitochondrial bioenergetic dysfunction and electron transport chain activity are implicated in elevated beta-oxidation during high-fat diet feeding; abnormally elevated rates of beta-oxidation may be a key driver of insulin resistance. The results reported here support the hypothesis that mtDNA influences cardiometabolic disease-susceptibility by modulating mitochondrial function and metabolic pathways.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".