Immune phase transition under steroid treatment

Abstract

The steroid hormone, Glucocorticoid (GC) is a well-known immunosuppressant that controls T cellmediated adaptive immune response. In this work, we have developed a minimal kinetic network model of T-cell regulation connecting relevant experimental and clinical studies to quantitatively understand the long-term effects of GC on pro-inflammatory T-cell (Tpro) and anti-inflammatory Tcell (Tanti) dynamics. Due to the antagonistic relation between these two types of T-cells, their longterm steady-state population ratio helps us to characterize three classified immune-regulations:), and (iii) moderate ([Tpro] ~ [Tanti]); holding the characteristic bistability). In addition to the differences in their long-term steady-state outcome, each immune-regulation shows distinct dynamical phases. In the pre-steady, a characteristic intermediate stationary phase is observed to develop only in the moderate regulation regime. In the medicinal field, the resting time in this stationary phase is distinguished as a clinical latent period. GC dose-dependent steady-state analysis shows an optimal level of GC to drive a phase-transition from the weak/autoimmune prone to the moderate regulation regime. Subsequently, the pre-steady state clinical latent period tends to diverge near that optimal GC level where [Tpro]: [Tanti] is highly balanced. The GCoptimized elongated stationary phase explains the rationale behind the requirement of long-term immune diagnostics, especially when long-term GC-based chemotherapeutics and other immunosuppressive drugs are administrated. Moreover, our study reveals GC sensitivity of clinical latent period which might serve as an early warning signal in the diagnosis of different immune phases and determining immune phase-wise steroid treatment.

Effects of immunosuppressants on T-cell dynamics: Understanding from a generic coarse-grained immune network model

“…In the T-cell-mediated immune system context, such theoretical concepts help characterize different immunoregulatory states and their modulation under different environmental situations (Roy et al . 2014 ; Roy and Bagchi 2020 ; Nayak and Roy 2021 ). T-cell-mediated immune regulations are often classified into weak, strong, and moderate regulation regimes based on the ratio and relative concentration of pro-inflammatory T-cells and anti-inflammatory T-cells.…”

“…Among these CD4+ T-cells, it has been observed that some act as pro-inflammatory cells (Th1, Th2, Th17, Th9, Th22, and Tfh cells), and others work as anti-inflammatory cells (Th 3 and Treg cells) (Lei et al . 2021 ; Nayak and Roy 2021 ).…”

“…The immune system can transit from a weak regulation regime to a moderate regulation regime and then to a strong regulation regime and vice versa depending on the concentration and composition of pro-inflammatory T-cells (T pro ) and anti-inflammatory T-cells (T anti ) (refer to Roy et al . 2014 ; Roy and Bagchi 2020 ; Nayak and Roy 2021 for more details). …”

“…The saturation function presents a one-time external dose (GC) intake mode. Nayak and Roy ( 2021 ) have also developed a kinetic network-based model to understand the direct and indirect effects of GCs on the immune system and anti-inflammatory immune response. In the model of Yakimchuk ( 2020 ), the saturation function leads the system to saturate towards a constant dose value.…”

“…After recognizing the microbial trespasser in the body, phagocytes are the specialized cells that quickly engulf the microbe through phagocytosis (Perelson 1989 ; Chaplin 2010 ; Brodin and Davis 2017 ; Mayassi et al . 2021 ; Nayak and Roy 2021 ).…”