Horm Metab Res 2019; 51(09): 618-622
DOI: 10.1055/a-0975-9268
Hypothesis
© Georg Thieme Verlag KG Stuttgart · New York

Post-Traumatic Stress Disorder Chronification via Monoaminooxidase and Cortisol Metabolism

Vadim Tseilikman
1   School of Medical Biology, South Ural State University, Chelyabinsk, Russia
,
Eliyahu Dremencov
1   School of Medical Biology, South Ural State University, Chelyabinsk, Russia
2   Institute of Molecular Physiology and Genetics, Centre for Biosciences, Slovak Academy of Sciences, Bratislava, Slovak Republic
12   Institute of Experimental Endocrinology, Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovak Republic
,
Ekaterina Maslennikova
1   School of Medical Biology, South Ural State University, Chelyabinsk, Russia
,
Alla Ishmatova
1   School of Medical Biology, South Ural State University, Chelyabinsk, Russia
,
Eugenia Manukhina
1   School of Medical Biology, South Ural State University, Chelyabinsk, Russia
3   Laboratory for Regulatory Mechanisms of Stress and Adaptation, Institute of General Pathology and Pathophysiology, Moscow, Russia
4   Department of Physiology and Anatomy, University of North Texas Health Science Center, Fort Worth, Texas, USA
,
H. Fred Downey
1   School of Medical Biology, South Ural State University, Chelyabinsk, Russia
4   Department of Physiology and Anatomy, University of North Texas Health Science Center, Fort Worth, Texas, USA
,
Igor Klebanov
1   School of Medical Biology, South Ural State University, Chelyabinsk, Russia
,
Olga Tseilikman
1   School of Medical Biology, South Ural State University, Chelyabinsk, Russia
,
Mariya Komelkova
1   School of Medical Biology, South Ural State University, Chelyabinsk, Russia
,
Maxim S. Lapshin
1   School of Medical Biology, South Ural State University, Chelyabinsk, Russia
,
Mariya V. Vasilyeva
1   School of Medical Biology, South Ural State University, Chelyabinsk, Russia
,
Stefan R. Bornstein
5   Department of Medicine, Technical University of Dresden, Dresden, Germany
6   Rayne Institute, Division of Diabetes & Nutritional Sciences, Endocrinology and Diabetes, Faculty of Life Sciences & Medicine, Kings College London, London, UK
,
Seth W. Perry
7   College of Medicine, SUNY Upstate Medical University, Syracuse, NY, USA
,
Ma-Li Wong
7   College of Medicine, SUNY Upstate Medical University, Syracuse, NY, USA
10   Department of Psychiatry, Flinders University School of Medicine, Bedford Park, SA, Australia
11   Department of Psychiatry, University of Adelaide School of Medicine, Bedford Park, SA, Australia
,
Julio Licinio
7   College of Medicine, SUNY Upstate Medical University, Syracuse, NY, USA
10   Department of Psychiatry, Flinders University School of Medicine, Bedford Park, SA, Australia
11   Department of Psychiatry, University of Adelaide School of Medicine, Bedford Park, SA, Australia
,
Rachel Yehuda
8   ICAHN School of Medicine at Mount Sinai, New York, NY, USA
,
Enrico Ullmann
1   School of Medical Biology, South Ural State University, Chelyabinsk, Russia
5   Department of Medicine, Technical University of Dresden, Dresden, Germany
9   Department of Child and Adolescent Psychiatry, Psychotherapy, and Psychosomatics, University of Leipzig, Leipzig, Germany
› Author Affiliations
Further Information

Publication History

received 28 April 2019

accepted 11 July 2019

Publication Date:
10 September 2019 (online)

Preview

Introduction

Post-traumatic stress disorder (PTSD) is a severe psychiatric illness which may develop in individuals exposed to trauma [1], including exposure to military combat, interpersonal violence, and childhood maltreatment. The disorder is characterized by an alternating pattern of re-experiencing symptoms, avoidance of traumatic stimuli, changes in mood and cognition, numbing of general responsiveness, and increased arousal (DSM 5).

Knowledge of the PTSD biology continues to expand whereby earlier observations of elevated catecholamines and decreased cortisol in urine of chronic PTSD of combat veterans [2] were criticized for reflecting only downstream or peripheral components of a very complex pathology [3]. Nonetheless, more recent and sophisticated studies have, by in large, supported these early observations and have provided important additional data relevant to the pathomechanism of PTSD [4]. For example, neuroimaging studies identified important neural circuits in the limbic system, including amygdala, hippocampus, and prefrontal cortex (PFC) which are involved in PTSD [5] [6] [7], but did not explain the initial neuroendocrine findings, especially of decreased urinary cortisol. The concept of allostatic load is a useful paradigm to connect PTSD-related neuroendocrine findings to altered neural circuits [8] [9], however, to date, the relationship between glucocorticoid and catecholamine metabolism in PTSD has not been studied, although monoamine oxidase (MAO)-A, the key enzyme of catecholamine metabolism is glucocorticoid-dependent [10]. Here we present a new hypothesis to explain the link between activation of glucocorticoid metabolism and depression of catecholamine metabolism among different allostatic states in PTSD.

Catecholamines and corticosteroids in PTSD

PTSD is characterized by a pattern of alterations that, on the one hand, reflect an increased activity of the sympathetic nervous system (SNS). These include, increased heart rate, elevated catecholamine levels, and heightened alpha2 adrenergic receptor responsiveness [4]. However, concurrent with this hyperadrenergic activation, many patients with PTSD also show evidence of low plasma and urinary basal corticosteroids, reflecting reduced cortisol signaling [11]. The low cortisol levels in PTSD are thought to reflect, or contribute to, an enhanced responsiveness of the hypothalamic-pituitary-adrenal (HPA) axis to glucocorticoids that has been demonstrated by studies examining glucocorticoid responsiveness with in vivo endocrine tests, such as the dexamethasone suppression test (DST) and ex vivo methods, such as examination of enzyme responses to stimulation of cultured blood cells with glucocorticoids [11] [12]. Now there is evidence for altered cortisol metabolism in PTSD, but unfortunately, no evidence that it contributes to a functional disconnection between the SNS and HPA. A first indicator of this direct link could be the connection between disturbed glucocorticoid metabolism and anxiety via the inhibition of 11β-hydroxysteroid dehydrogenase (11β-HSD) with carbenoxolone [13], however, there is a lack of evidence related to PTSD.


MAO metabolism in PTSD

Clinical data revealed the implications of MAO activity to psychotic features in patients with PTSD [14]. MAO-A is one of the key enzymes mediating the turnover of biogenic amines, such as norepinephrine (NE), and is thus to be considered a major candidate molecule in PTSD and potentially, enhanced NE signaling via MAO-A gene hypermethylation, as discussed recently in order to make personalized treatment decisions [15]. Moreover, an activation of MAO-A expression in neurons via higher ability to receptor binding was described for glucocorticoids [10]. Interestingly, low levels of basal corticosterone [16] and low levels of cerebral MAO without distinguishing the isoforms of MAO linked to physical activity were shown in rats, three days after traumatic stress [17]. And, in more physical active offensive rats we found a reduction of anxiety, corticosteroids and glutamate as well as higher concentrations of lactate in the amygdala region compared to the hippocampal region by using our model of chronic and extensive predator stress, indicating a limbic triggered HPA activity with different oxidative processes [18].


Glucocorticoid metabolizers in PTSD

The major enzymes metabolizing glucocorticoids are 11β-hydroxysteroid dehydrogenase-1 (11β-HSD1) and 11β-hydroxysteroid dehydrogenase-2 (11β-HSD2). 11-Dehydrocorticosterone is a mineral corticosteroid. The conversion of inactive 11-ketoglucocorticoids (such as 11-dehydrocorticosterone) into active 11- hydroxyglucocorticoids (such as corticosterone) is catalyzed by 11β-HSD1, which is expressed in many local metabolically tissues such as the liver, kidney, skeletal muscles, and adipose tissue. Corticosterone was inactivated via 11β-HSD2 into 11-dehydrocorticosterone [19]. An elevated activity of 11β-HSD2 in children of Holocaust survivors was demonstrated [20], which could explain decreased cortisol concentrations within this population not only in the 2nd but also in the 3rd generation removed from the Holocaust [21]. Recently, we found increased levels of 11-dehydrocorticosterone in chronic stressed Active Offensive Response (AOR) rats compared to Passive Defensive Response (PDR) rats indicating a higher activity of the 11β-HSD2 or a lower activity of 11β-HSD1 (Tseilikman et al. in preparation). At the systemic (circulating) level, the major metabolizers of glucocorticoids are subtypes of the hepatic-microsomal oxidation enzymes, for example, cytochrome P450 (CYP), CYP3A1, and CYP3A2. The latter metabolizes corticosterone into 6B-corticosterone irreversibly [22]; however, there is a lack of evidence in the literature concerning CYP activity in PTSD. The CYPs are involved in the metabolism of many therapeutic drugs and a relationship between inflammation and CYPs-mediated drug metabolism in critically ill patients is absent, whereas the clearance of many CYP3A drug substrates may be decreased [23] indicating a higher CYP activity in overstressed subjects.


Different allostatic set points in different PTSD-levels

Generally, the stressed body can adapt to reach a homeostatic equilibrium via both autonomic (ANS) and central nervous system (CNS) mechanisms. The stages of adaptation and exhaustion are also known as allostasis and allostatic overload; they involve both activation of the HPA axis and its downstream effector pathways and immune, metabolic, and behavioral responses [24]. An allostatic state is defined by chronic deviation of regulatory systems away from their normal state of operation, to establish a new set point [25]. We showed that there are different set points of allostasis between less anxious AOR rats with an allostatic flight/fight response mechanism compared to PDR rats with an allostatic freezing/passive response mechanism with “lower” levels of physical activity and oxidative stress. AOR rats showed lower levels of basal corticosterone and glutamate as well as higher levels of lactate as described above indicating an inhibited amygdala activity in AOR rats [18].

These data are consistent with depressed amygdala activity in PTSD-resistant subjects [26]. The mechanism of amygdala inhibition is not completely clear. It was suggested that the prefrontal cortex restricts the activity of amygdala to ameliorate the development of PTSD [5] whereas Geuze et al. (2012) demonstrated that peripheral GR number is associated with amygdala functioning and predicts the increase in amygdala activity following military deployment in healthy individuals who did not develop PTSD [27]. It is uncertain how this relationship is mediated mechanistically, but future studies should examine the relation of GR and amygdala activity to determine whether this is a part of a common pathway leading to increased vulnerability to stress-related disorders.

We suggest to include, into the biological model of PTSD, activities of PFC and amygdala along with the MAO-A dependent metabolism of noradrenaline and other monoamine neurotransmitters in relation with glucocorticoid concentration and tissue metabolism.


Empiric-based hypothesis

Thus we propose the following working hypothesis represented also in [Fig. 1]:

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Fig. 1 Extended biological model of PTSD.
  • i) In PTSD, the activity of 11β-HSD2 and CYP3A is increased and the activity of 11β-HSD1 will be decreased leading to higher levels of 11-dehydrocorticosterone and lower levels of basal glucocorticoids.

  • ii) Low glucocorticoid levels stimulate the progression of PTSD via suppression of MAO-A activity since a low level of MAO-A expression and activity in the PFC occurs after traumatization leading to NE accumulation with consequent loss of the inhibitory activity of the PFC via amygdala activity. In turn, reduced MAO-A activity in various brain regions, including PFC, is directly linked to increased glucocorticoid metabolism.

Based on our hypothesis about the key role of reduced MAO-A activity as well as metabolizers of glucocorticoids in the progression of PTSD, we have constructed a phenomenological mathematical model to describe this process. The model is a system of first-order ordinary differential equations:

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C (t) is the concentration of the corticosterone, N (t) is the concentration of NE in the prefrontal cortex. E (t) is the activity of enzymes; E1 (t) is the CYP3A1/CYP3A2 activity in the liver, E2 (t) is the 11β-HSD2 activity in tissues, E3 (t) is the activity of 11β-HSD1 in the tissues, E4 (t) is the activity of MAO-A in the brain. a1, a2; k1, k2, k3; q1, q2, q3; p1, p2; C0 , N0 are phenomenological constants.

This model shows, how the concentration of NE in the prefrontal cortex, the concentration of corticosterone in the blood, and the activity of the MAO in the PFC, change at the same time interval. We took into account the mutual influence of enzymes and corticosterone, as well as the presence of self-regulation of the concentration of corticosterone and norepinephrine. In case of significant discrepancies with the experimental data, the model will be expanded by adding additional variables characterizing corticosterone production in the adrenal glands and the production of NE in locus coeruleous. For clarity of this model we performed an example calculation as illustrated in [Fig. 2].

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Fig. 2 a Phenomenological model of time-dependent changes of the plasma corticosterone-concentration in PTSD dynamic. b Phenomenological model of time-dependent changes of norepinephrine in PFC in PTSD dynamic. c Phenomenological model of time-dependent changes of MAO-A activity (E4) in PFC in PTSD dynamic. All units are dimensionless and conditional. The initial conditions correspond to the moment of cessation of stressor exposures values of phenomenological constants k1=k2=0.9, k3=1, p1=p2=q1=q2=10, q3=0.1, a1=a2=1, С0=10, N0=10.