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.

High-fidelity discrete modeling of the HPA axis: a study of regulatory plasticity in biology

“…CORT has broad effects across the body where it binds to glucocorticoid receptors (R) and in a negative feedback suppresses ACTH secretion [ 4 ]. Previously, models of the HPA axis have been formulated as sets of Ordinary Differential Equations (ODE) [ 5 , 6 ], delay differential equations (DDEs) [ 7 , 8 ] or as discrete Boolean (BN) networks [ 9 ]. Early work by our group extended the BN formalism to a fixed 3-state logic to provide additional detail [ 10 ].…”

An in silico target identification using Boolean network attractors: Avoiding pathological phenotypes

“…The goal of this work is to propose a computational methodology implemented in an algorithm for in silico therapeutic target discovery using Boolean network attractors. It assumes that Boolean network attractors correspond to phenotypes produced by the modeled biological network, an assumption successfully applied in several works [41][42][43][44][45][46][47][48][49][50][51][52][53][54][55][56][57]. Assuming that a phenotype is an observable state, and thus relatively stable, of a biological system and assuming that the state of a biological system results from its dynamics, a phenotype is likely to correspond to an attractor.…”

Whole-Exome Sequencing in a South American Cohort Links ALDH1A3, FOXN1 and Retinoic Acid Regulation Pathways to Autism Spectrum Disorders

“…Our results are in concordance with previous studies demonstrating that transcription factors play significant roles in ASD [ 8 , 10 – 13 , 16 ]. A previous study of our group reported that genes involved in transcription regulation are essential to serotoninergic pathway stability in depression [ 65 ]. Moreover, even though ASD is highly heritable, a multitude of environmental influences play a fundamental role on ASD incidence [ 4 ], which might interact with the proband’s genetic variants causing the disorder.…”