Oxytocin's anti-inflammatory and proimmune functions in COVID-19: a transcriptomic signature-based approach

Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a worldwide pandemic, infecting over 16 million people worldwide with a significant mortality rate. However, there is no current Food and Drug Administration-approved drug that treats coronavirus disease 2019 (COVID-19). Damage to T lymphocytes along with the cytokine storm are important factors that lead to exacerbation of clinical cases. Here, we are proposing intravenous oxytocin (OXT) as a candidate for adjunctive therapy for COVID-19. OXT has anti-inflammatory and proimmune adaptive functions. Using the Library of Integrated Network-Based Cellular Signatures (LINCS), we used the transcriptomic signature for carbetocin, an OXT agonist, and compared it to gene knockdown signatures of inflammatory (such as interleukin IL-1β and IL-6) and proimmune markers (including T cell and macrophage cell markers like CD40 and ARG1). We found that carbetocin's transcriptomic signature has a pattern of concordance with inflammation and immune marker knockdown signatures that are consistent with reduction of inflammation and promotion and sustaining of immune response. This suggests that carbetocin may have potent effects in modulating inflammation, attenuating T cell inhibition, and enhancing T cell activation. Our results also suggest that carbetocin is more effective at inducing immune cell responses than either lopinavir or hydroxychloroquine, both of which have been explored for the treatment of COVID-19.

Keywords: COVID19; LINCS; immune; oxytocin; transcriptomic signature.

Fig. 1.

A flow chart representation of the workflow. The R Pipeline is available freely in a GitHub repository.

Fig. 2.

In silico analysis of transcriptional profiles of inflammation-related gene knockout (KO) cell lines in comparison with drug-treated cell line signatures. Maximum concordance scores are shown. A: the IL6 KO signature compared across different drug-treated signatures. B: the TNF KO signature compared across different drug-treated signatures. C: heatmap summarizing the concordance scores of TNF, IL6, IL1B, and NFKB KO cell lines with drug-treated cell lines.

Fig. 3.

In silico analysis of transcriptional profiles of immune-related gene knockout (KO) cell lines in comparison with drug-treated cell line signatures. Maximum concordance scores are shown. A: the ARG1 KO signature compared across different drug-treated signatures. B: the CD40 KO signature compared across different drug-treated signatures. C: heatmap summarizing the concordance scores of immune-related genes KO cell lines including ARG1, CD40, TGFB1, TGFBR1, TGFBR2, and TLR9 with drug-treated cell lines.