When type II diabetes mellitus meets COVID-19-Identification of the shared gene signatures and biological mechanism between the two diseases

BACKGROUND

According to current studies, more than 20% of all patients diagnosed with COVID-19 globally have diabetes. Further, the mortality rate of these patients is 7.3%. Compared with non-diabetic COVID-19 patients, diabetic COVID-19 patients have higher rates of mortality and severe infection, suggesting that diabetes is associated with the severity of COVID-19 infection. This study aimed to analyse the relationship and susceptibility factors between COVID-19 and T2DM.

METHODS

Using bioinformatics methods, potential targets for COVID-19 and T2DM were screened from GeneCards database. Potential targets of COVID-19 and T2DM were mapped to each other to identify overlapping targets, and a PPI network was constructed to extract the core target. The clusterProfiler package in R was used to analyse the function and pathway that core target involved. GO enrichment and KEGG pathway analysis were used to elucidate the correlation between COVID-19 and T2DM.

RESULTS

A total of 277 potential pathogenic targets of COVID-19 were found, 282 potential targets were found for T2DM. Mapping of the potential COVID-19 and T2DM targets revealed 53 overlapping targets, with TNF as the core target. IL-17 signalling pathway was the most significant KEGG pathway involving TNF.

CONCLUSIONS

The inflammatory cytokine, TNF, was identified as a core target between COVID-19 and T2DM, which induces inflammatory response mainly through the IL-17 signalling pathway, leading to aggravation of infection and increased difficulty in blood glucose control. This study provides a reference for further exploring the potential correlation and endogenous mechanisms between two seemingly independent and unrelated diseases-T2DM and COVID-19.

An integrated network pharmacology and RNA-Seq approach for exploring the preventive effect of Lonicerae japonicae flos on LPS-induced acute lung injury

ETHNOPHARMACOLOGICAL RELEVANCE

Lonicerae japonicae flos (LJF, the dried flower bud or newly bloomed flower of Lonicera japonica Thunb.), a typical herbal medicine, targets the lung, heart and stomach meridian with the function of clearing heat and detoxication. It ameliorated inflammatory responses and protected against acute lung inflammation in animal models. Acute lung injury (ALI) is a kind of inflammatory disease in which alveolar cells are damaged. However, a network pharmacology study to thoroughly investigate the mechanisms preventing ALI has not been performed.

AIM OF THE STUDY

In this study, we examined the main active ingredients in LJF and the protective effects of LJF on LPS-induced ALI in rats.

MATERIALS AND METHODS

First, the main active ingredients of LJF were screened in the TCMSP database, and the ALI-associated targets were collected from the GeneCards database. Then, we used compound-target and target-pathway networks to uncover the preventive mechanisms of LJF. Furthermore, we assessed the preventive effects of LJF in an LPS-induced rat model with the RNA-Seq technique to validate the possible molecular mechanisms of the effects of LJF in the treatment of ALI.

RESULTS

The network pharmacology results identified 28 main active compounds in LJF, and eight chemical components highly related to the potential targets, which were potential active compounds in LJF. In all, 94 potential targets were recognized, including IL6, TNF, PTGS2, APP, F2, and GRM5. The pathways revealed that the possible targets of LJF involved in the regulation of the IL-17 signalling pathway. Then, in vivo experiments indicated that LJF decreased the levels of proinflammatory cytokines (TNF-, IL-1, and IL-6) in serum and bronchoalveolar lavage fluid, decreased the levels of oxidative stress factors (MDA and MPO) and increased the activities of SOD and GSH-Px in lung tissue. The RNA-Seq results revealed that 7811, 775 and 3654 differentially expressed genes (DEGs) in Ctrl (control group), ALI-LJF (Lonicerae japonicae flos group) and ALI-DXSM (dexamethasone group), respectively. KEGG pathway analysis showed that the DEGs associated with immune response and inflammation signalling pathways and the IL-17 signalling pathway were significantly enriched in LJF. Compared with those in ALI, the expression of CXCL2, CXCL1, CXCL6, NFKBIA, IFNG, IL6, IL17A, IL17F, IL17C, MMP9 and TNFAIP3, which are involved in the IL-17 signalling pathway, were significantly decreased in the LJF group according to the qRT-PCR analyses.

CONCLUSIONS

In view of the network pharmacology and RNA-Seq results, the study identified the main active ingredient and potential targets of LJF involved in protecting against ALI, which suggests directions for further research on LJF.