Modeling of the hypothalamic-pituitary-adrenal axis-mediated interaction between the serotonin regulation pathway and the stress response using a Boolean approximation: a novel study of depression

Abstract

Major depressive disorder (MDD) is a multifactorial disorder known to be influenced by both genetic and environmental factors. MDD presents a heritability of 37%, and a genetic contribution has also been observed in studies of family members of individuals with MDD that imply that the probability of suffering the disorder is approximately three times higher if a first-degree family member is affected. Childhood maltreatment and stressful life events (SLEs) have been established as critical environmental factors that profoundly influence the onset of MDD. The serotonin pathway has been a strong candidate for genetic studies, but it only explains a small proportion of the heritability of the disorder, which implies the involvement of other pathways. The serotonin (5-HT) pathway interacts with the stress response pathway in a manner mediated by the hypothalamic-pituitary-adrenal (HPA) axis. To analyze the interaction between the pathways, we propose the use of a synchronous Boolean network (SBN) approximation. The principal aim of this work was to model the interaction between these pathways, taking into consideration the presence of selective serotonin reuptake inhibitors (SSRIs), in order to observe how the pathways interact and to examine if the system is stable. Additionally, we wanted to study which genes or metabolites have the greatest impact on model stability when knocked out in silico. We observed that the biological model generated predicts steady states (attractors) for each of the different runs performed, thereby proving that the system is stable. These attractors changed in shape, especially when anti-depressive drugs were also included in the simulation. This work also predicted that the genes with the greatest impact on model stability were those involved in the neurotrophin pathway, such as CREB, BDNF (which has been associated with major depressive disorder in a variety of studies) and TRkB, followed by genes and metabolites related to 5-HT synthesis.

Figure 1

A flow chart illustrating the methodology used to model the network. For more information, refer to the Methods section.

Figure 2

The genetic pathway predicted to regulate the interaction between 5-HT synthesis, transport and degradation and the stress response mediated by the HPA axis. This figure was generated using the computational program CellDesigner 4.1. * Nodes located in the dorsal Raphe nucleus (DRN) cells.

Figure 3

A simplified model of the regulatory interactions between the serotonin and stress response pathways mediated by the HPA axis. AND/NOT operators are included to show the Boolean logic used. When no operator is shown between the nodes, the activation state is given by any of the nodes upstream. * Nodes located in the dorsal Raphe nucleus (DRN) cells.

Figure 4

Results obtained for all the runs performed with the model generated by a Boolean approximation using Synchronous Boolean Networks (SBNs). Nodes related to G-protein signaling are not shown. An input vector of ones was used for all nodes except the SSRI and stress nodes, which were activated or deactivated to generate 4 possible simulations. A. The pattern obtained when stress and SSRI were both in the ‘off’ state (basal system) and the other nodes were ‘on’. B. The effect of SSRI activity on the serotonin regulation pathway under unstressed conditions is shown. Notice that the antidepressant activity blocks 5-HTT and 5-HT_1A^*, causing 5-HT synthesis, degradation and transport pathways to remain active. C. The pattern generated when the stress node is ‘on’ and SSRI is ‘off’. In this case, a cyclical pattern was observed for nodes related to 5-HT synthesis, transportation and degradation. This figure also shows that while the stress response is well regulated, a persistent stressed state activates the HPA axis over time. D. SSRI clearly regulates the cyclical pattern shown in C, but it does not cause the same pattern shown in B. This is in line with expectation and demonstrates that SSRIs do not have any effect when the patient is stressed.

Figure 5

The effects of knocking out key nodes in the model. The importance of individual nodes was determined based on the mean Hamming distance calculated from 100 discrete runs following node knockout in the model. The nodes corresponding to CREB, BDNF and TRkB had the greatest negative effect on network stability when knocked out, while those related to 5-HT synthesis had the next greatest negative effect.

Figure 6

Results obtained by the application of the bootstrapping method to calculate the deviation error (only shown for the 100th time step because the system has reached stability). These results show strong similarity to those obtained by calculation of the mean Hamming distance (Figure 5).