bioRxivPathologyPreprint
Metabolic shifts in the heart of hypothyroid mice -- insights from untargeted metabolomics
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Abstract
ABSTRACTSO_ST_ABSIntroductionC_ST_ABSHypothyroidism is a prevalent disorder that affect all systems of body, including the cardiovascular system and control of cardiac function. However, much remains unknown about the metabolic pathways and disorders in the heart induced by hypothyroidism, as well as the metabolic mechanisms involved. ObjectivesThis work aims to investigate the impacts of hypothyroidism on the heart and explore its underlying mechanisms through untargeted metabolomics analysis. MethodsAn experimental model of hypothyroidism was established by giving water containing 0.1% methimazole and 1% potassium perchlorate to 12-week-old C57BL/6J mice for six consecutive weeks. ResultsAfter treatment, hypothyroidism significantly reduced mices heart weight and heart rate. Metabolomics analysis revealed that the different metabolites (DEMs) primarily concentrated in Phospholipids, Lipids or Lipids-like, Carbohydrates and Carbohydrate conjugates. These specific metabolites were mainly enriched in pathways related to lipid metabolism. The hearts of hypothyroid mice exhibited significantly lower levels of lipoyl-carnitine compared to controls, along with markedly higher levels of glycolysis and pentose phosphate pathway (PPP) intermediates. Furthermore, carnitine palmitoyltransferase 1B (CPT1B) and carnitine palmitoyltransferase 2 (CPT2) expressions were significantly decreased in the hypothyroid mouse heart, while lactate dehydrogenase A (LDHA) expressions was significantly increased, according to the immunoblotting assay. ConclusionsResearch indicates that hypothyroidism triggers disruptions in both cardiac energy metabolism and phospholipid metabolism in adult mice, which in turn results in myocardial atrophy. These findings could pave the way for novel therapeutic strategies aimed at treating hypothyroidism-induced myocardial atrophy.
- organism: mouse
- assay: metabolomics
- research focus: metabolism & bioenergetics
- approach: statistical model
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