(625d) Modeling of the Interaction Between the Serotonin Regulation Pathway and the Stress Response, Mediated by the Hypothalamic-Pituitary-Adrenal Axis, Using a Boolean Approximation: a Novel Study for Depression
AIChE Annual Meeting
2011
2011 Annual Meeting
Food, Pharmaceutical & Bioengineering Division
Poster Session: Engineering Fundamentals In Life Science
Wednesday, October 19, 2011 - 6:00pm to 8:00pm
Modeling
of the Interaction between the Serotonin Regulation Pathway and the Stress
Response, mediated by the Hypothalamic-Pituitary-Adrenal Axis, using a Boolean
Approximation: a Novel Study for Depression.
Oscar Moreno-Ramos1,2, Mar'a Claudia Lattig1,
Andr?s Fernando Gonz?lez2
1. Laboratorio de
Gen?tica Humana, Departamento de Microbiolog'a, Universidad de los Andes
2. Grupo de Dise?o de Productos y Procesos, Departamento de
Ingenier'a Qu'mica, Universidad de los Andes
Depression is a disease with a high incidence in world
population and who suffer it, tend to bear different symptoms that can disable
them to have a normal life. According to different studies performed into
twins, the heritability of it is about 40%. Beside of this fact, the
heritability gets higher if another member of the family suffers this disease
or another neurological disorder. Thus, it has been hypothesized that
depression has a strong genetic background because different genetic
polymorphisms, of the serotonin metabolic pathway, have been found to be
associated. Same, it has been found an association to have the disease if the
patient suffered different stressor events in his childhood so; it shows that
depression is highly related to stress and its response pathways as well. According
to the interaction between the stress response and the serotonin metabolism,
the principal aim of this work was to model the interaction between the
serotoninergic pathway and the stress response pathway mediated by the hypothalamic-pituitary-adrenal
axis using a Boolean approximation; in order to observe how is the interaction
between both paths and examine if the system is stable. Also, we wanted to study
which genes, when are mutated in-silico,
causes the highest impact on the model stability. In this model, we also
simulate the impact that anti-depressive drugs have on the biological pathway. The
results obtained show that the network is stable with or without stress, but
that stability is reached faster when the pathway is run without stress than
when it is taking into account. Also we observed that the biological model
generated predicts steady states (attractors) for each of the different runes
done. Those attractors change in shape, especially when anti-depressive drugs
were also included in the simulation. We also found that when the patient is
depressive and is stressed too, anti-depressive drugs do not have the expected
effect.