GP73 links SARS-CoV-2 infection with dysglycaemia

Coate, Katie C.

doi:10.1038/s42255-021-00511-7

Cited by 2 publications

(2 citation statements)

References 7 publications

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“…GP73 is involved in many human diseases, such as cancer, HIV, nonalcoholic fatty liver disease, and SARS-CoV-2-induced dysglycemia. [13][14][15][16][17][18] However, the role of GP73 in LPS-induced cardiac dysfunction remains unknown.…”

Section: Introductionmentioning

confidence: 99%

Golgi Protein 73 Promotes LPS-Induced Cardiac Dysfunction via Mediating Myocardial Apoptosis and Autophagy

Xing,

Gao,

Bai

et al. 2024

Journal of Cardiovascular Pharmacology

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Sepsis-induced cardiac dysfunction represents a major cause of high mortality in intensive care units with limited therapeutic options. Golgi protein 73 (GP73) has been implicated in various diseases. However, the role of GP73 in LPS-induced cardiac dysfunction is unclear. Here, we established sepsis-induced cardiac dysfunction model by LPS administration in wild type (WT) and GP73 knockout (GP73 -/- ) mice. We found GP73 was increased in LPS-treated mouse hearts and LPS-cultured neonatal rat cardiomyocytes (NRCMs). Knockout of GP73 alleviated myocardial injury and improved cardiac dysfunction. Moreover, depletion of GP73 in NRCMs relieved LPS-induced cardiomyocyte apoptosis and activated myocardial autophagy. Therefore, GP73 is a negative regulator in LPS-induced cardiac dysfunction by promoting cardiomyocyte apoptosis and inhibiting cardiomyocyte autophagy.

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Section: Introductionmentioning

confidence: 99%

Golgi Protein 73 Promotes LPS-Induced Cardiac Dysfunction via Mediating Myocardial Apoptosis and Autophagy

Xing,

Gao,

Bai

et al. 2024

Journal of Cardiovascular Pharmacology

View full text Add to dashboard Cite

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“…6 More recently, it was discovered that GOLM1 connects SARS-CoV-2 infection with dysglycemia. 7 In order to infer potential causality of risk factor-disease associations, we used the promising approach of Mendelian randomization (MR). 8 This strategy is based on the premise that genetic variations are distributed randomly during meiosis, hence minimizing confounding bias.…”

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confidence: 99%