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Diabetic Covid-19 severity: Impaired glucose tolerance and pathologic bone loss

ABSTRACT: Diabetes mellitus (DM), hypertension, and cardiovascular diseases (CVDs) are the leading chronic comorbidities that enhance the severity and mortality of COVID-19 cases. However, SARS-CoV-2 mediated deregulation of diabetes pathophysiology and comorbidity that links the skeletal bone loss remain unclear. We used both streptozocin-induced type 2 diabetes (T2DM) mouse and hACE2 transgenic mouse to enable SARS-CoV-2-receptor binding domain (RBD) mediated abnormal glucose metabolism and bone loss phenotype in mice. The data demonstrate that SARS-CoV-2-RBD treatment in pre-existing diabetes conditions in hACE2 (T2DM + RBD) mice results in the aggravated osteoblast inflammation and downregulation of Glucose transporter 4 (Glut4) expression via upregulation of miR-294–3p expression. The data also found increased fasting blood glucose and reduced insulin sensitivity in the T2DM + RBD condition compared to the T2DM condition. Femoral trabecular bone mass loss and bone mechanical quality were further reduced in T2DM + RBD mice. Mechanistically, silencing of miR-294 function improved Glut4 expression, glucose metabolism, and bone formation in T2DM + RBD + anti-miR-294 mice. These data uncover the previously undefined role of SARS-CoV-2-RBD treatment mediated complex pathological symptoms of diabetic COVID-19 mice with abnormal bone metabolism via a miRNA-294/Glut4 axis. Therefore, this work would provide a better understanding of the interplay between diabetes and SARS-CoV-2 infection. Graphical abstract Image 1

SUBMITTER: Behera J

PROVIDER: S-EPMC9213044 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Using RNA-seq and high-resolution mass spectrometry we performed a comprehensive systems analysis on 128 plasma and leukocyte samples from hospitalized patients with or without COVID-19 (n=102 and 26 respectively) and with differing degrees of disease severity. We generated abundance measurements for over 17,000 transcripts, proteins, metabolites, and lipids and compiled them with clinical data into a curated relational database. This resource offers the unique opportunity to perform systems analysis and cross-ome correlations to both molecules and patient outcomes. In total 219 molecular features were mapped with high significance to COVID-19 status and severity, including those involved in processes such as complement system activation, dysregulated lipid transport, and B cell activation. In one example, we detected a trio of covarying molecules – citrate, plasmenyl-phosphatidylcholines, and gelsolin (GSN) – that offer both pathophysiological insight and potential novel therapeutic targets. Further, our data revealed in some cases, and supported in others, that several biological processes were dysregulated in COVID-19 patients including vessel damage, platelet activation and degranulation, blood coagulation, and acute phase response. For example, we observed that the coagulation-related protein, cellular fibronectin (cFN), was highly increased within COVID-19 patients and provide new evidence that the upregulated proteoform stems from endothelial cells, consistent with endothelial injury as a major activator of the coagulation cascade. The abundance of prothrombin, which is cleaved to form thrombin during clotting, was significantly reduced and correlated with severity and might help to explain the hyper coagulative environment of SARS-CoV-2 infection. From transcriptomic analysis of leukocytes, we concluded that COVID-19 patients with acute respiratory distress syndrome (ARDS) demonstrated a phenotype that overlapped with, but was distinct from, that found in patients with non-COVID-19-ARDS. To aid in the global efforts toward elucidation of disease pathophysiology and therapeutic development, we created a web-based tool with interactive visualizations allowing for easy navigation of this systems-level compendium of biomolecule abundance in relation to COVID-19 status and severity. Finally, we leveraged these multi-omic data to predict COVID-19 patient outcomes with machine learning, which highlighted the predictive power of these expansive molecular measurements beyond the standardized clinical estimate of 10-year survival Charlson score.

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Diabetic Covid-19 severity: Impaired glucose tolerance and pathologic bone loss

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