Identification of a Novel Heart–Liver Axis: Matrix Metalloproteinase‐2 Negatively Regulates Cardiac Secreted Phospholipase A <sub>2</sub> to Modulate Lipid Metabolism and Inflammation in the Liver
Bibliographic record
Abstract
BACKGROUND: Endocrine functions of the heart have been well established. We investigated the hypothesis that cardiac secretion of a unique phospholipase A2 recently identified by our laboratory (cardiac secreted phospholipase A2 [sPLA2]) establishes a heart-liver endocrine axis that is negatively regulated by matrix metalloproteinase-2 (MMP-2). METHODS AND RESULTS: In Mmp2(-/-) mice, cardiac (but not hepatic) sPLA2 was elevated, leading to hepatic inflammation, immune cell infiltration, dysregulation of the sterol regulatory element binding protein-2 and liver X receptor-α pathways, abnormal transcriptional responses to dietary cholesterol, and elevated triglycerides in very low-density lipoprotein and in the liver. Expression of monocyte chemoattractant protein-3, a known MMP-2 substrate, was elevated at both mRNA and protein levels in the heart. Functional studies including in vivo antibody neutralization identified cardiac monocyte chemoattractant protein 3 as a possible agonist of cardiac sPLA2 secretion. Conversely, systemic sPLA2 inhibition almost fully normalized the cardiohepatic phenotype without affecting monocyte chemoattractant protein-3. Finally, wild-type mice that received high-performance liquid chromatography-isolated cardiac sPLA2 from Mmp2(-/-) donors developed a cardiohepatic gene expression profile similar to that of Mmp2(-/-) mice. CONCLUSIONS: These findings identified the novel MMP-2/cardiac sPLA2 pathway that endows the heart with important endocrine functions, including regulation of inflammation and lipid metabolism in the liver. Our findings could also help explain how MMP2 deficiency leads to cardiac problems, inflammation, and metabolic dysregulation in 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".