The cardiac molecular setting of metabolic syndrome in pigs reveals disease susceptibility and suggests mechanisms that exacerbate COVID-19 outcomes in patients

Autor: Kostadin Todorov, Denitsa Radeva, Nivedita Sriram, Simon C. Robson, Jun Feng, Olivia Ziegler, Boian S. Alexandrov, Anny Usheva, Frank W. Sellke, Vladimir Gelev, Makoto Hiromura
Rok vydání: 2021
Předmět:
Zdroj: Scientific Reports
Scientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
ISSN: 2045-2322
Popis: Although metabolic syndrome (MetS) is linked to an elevated risk of cardiovascular disease (CVD), the cardiac-specific risk mechanism is unknown. Obesity, hypertension, and diabetes (all MetS components) are the most common form of CVD and represent risk factors for worse COVID-19 outcomes compared to their non MetS peers. Here, we use obese Yorkshire pigs as a highly relevant animal model of human MetS, where pigs develop the hallmarks of human MetS and reproducibly mimics the myocardial pathophysiology in patients. Myocardium-specific mass spectroscopy-derived metabolomics, proteomics, and transcriptomics enabled the identity and quality of proteins and metabolites to be investigated in the myocardium to greater depth. Myocardium-specific deregulation of pro-inflammatory markers, propensity for arterial thrombosis, and platelet aggregation was revealed by computational analysis of differentially enriched pathways between MetS and control animals. While key components of the complement pathway and the immune response to viruses are under expressed, key N6-methyladenosin RNA methylation enzymes are largely overexpressed in MetS. Blood tests do not capture the entirety of metabolic changes that the myocardium undergoes, making this analysis of greater value than blood component analysis alone. Our findings create data associations to further characterize the MetS myocardium and disease vulnerability, emphasize the need for a multimodal therapeutic approach, and suggests a mechanism for observed worse outcomes in MetS patients with COVID-19 comorbidity.
Databáze: OpenAIRE
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