Faculty of pharmacy department of human pharmacology and toxicology

HPA axis




Figure : This figure shows the pathways that are related to obesity development. The underlying pathways of obesity include the increase of cytokines, leptin and resistin and the decrease of adiponectin, the increase of cortisol, C-reactive protein and insulin causing dysregulation of HPA axis.

In underlying mechanisms of mood disorders immune-inflammatory and endocrine regulation hold a prominent position as HPA axis and glucocorticoids participate in the physiological response to acute stress. Its purpose is to redintegrate energy homeostasis through actions in the glucose and insulin regulation, adipose tissue and appetite. However HPA dysregulation is reported on obese people and a positive association between abnormal activation of HPA and abdominal adiposity has been found. This association is accompanied by lower or higher responses to stress (Pasquali, 2012; Kubera et al., 2012; Jones et al., 2012; Mujica-Parodi, Renelique & Taylor 2009).

Hyperactivation of the hypothalamic– pituitary–adrenal (HPA) axis is induced by stress, which triggers the hypothalamic corticotropin-releasing hormone (CRH) secretion. That prompts the release of adrenocorticotropin hormone (ACTH) by the anterior pituitary ,which causes the adrenal secretion of cortisol (Gragnoli , 2014).

People who are exposed to excessive cortisol (i.e. to chonic stress) represent an increment in visceral adipose tissue, while HPA dysregulation have been present in mood disorders aetiology. Cervantes et al (2001) pointed out that patients with bipolar disease demonstrate hypersecretion of cortisol (in euthymia, depression and mania) and Daban et al (2005) found the existence of blunted cortisol response to stress. Several studies (Lamers et al., 2013; Gold & Chrousos, 2002; Wong et al., 2000) have found and overactivation of HPA to depressive patients that is correlated to melancholic features.

Many clinical indications confirm the participation of HPA axis in depression, as in approximately 50% of depressed patients an increase of cortisol is observed. Probably the increased secretion of CRH in hypothalamus is involved resulting in an increase of ACTH and cortisol (Ahlberg et al., 2002).

The dysfunction of adrenergic systems and the 5-HT system combination with hyperactivity of neurons that use the CRF agent are considered as the basic cause of depressive and anxiety symptoms. The precipitating agent release CRF corticotropin has been found in high prices in patients with depression (Plotsky, Owens & Nemeroff, 1998).

A 75% of patients with major depression shows hyperactivity in HPA axis and is characterized by hypercortisolism. The disturbance in the functioning of HPA axis is observed in generalized anxiety disorder, as it is disclosed by testing dexamethasone ( Manthey et al., 2011;Tiller et al.,1988).

Young et al, showed that depressed patients represent impairment on HPA axis during a test in which patients subjected to intense stress, with a consequent increase in cortisol. Several studies have investigate the effect of the HPA axis in the CNS and evidence shows that clinical forms of Cushing's syndrome are present in some patients with major depressive disorder although cortisol levels are lower in depression than in Cushing syndrome (Brown, Varghese & McEwen, 2004).

Exogenous or endogenous cortisol increase (Cushing's syndrome) is often associated with insulin resistance and obesity, hypertension, hypercholesterolemia and hypertriglyceridemia. Glucocorticoids can reduce the vasodilation induced by insulin and they may also increase the lipolysis and the release of fatty acids, causing inhibition of protein lipase. Elevated fatty acids contribute to impaired glucose transport. Glucocorticoids also reduce insulin secretion from pancreatic beta-cells and inhibit or disrupt the connection with receptors. In the case of hypercortisolism causing insulin resistance in depressed patients, a study reports a significant correlation between insulin resistance and the evening-night cortisol levels of depressive patient's plasma (Andrews & Walker, 1999).

Vicennat et al (2009) have found that intense stress reactivity could predict metabolic syndrome development while there is an association between glucocorticoids and metabolic syndrome (Pasquali et al., 2006).

A well-described aetiology of mood disorders is dysfunction of HPA axis and depression pathogenesis is underlying on to a breakdown in glucocorticoid-receptor-mediated negative feedback mechanisms within the HPA axis (hypercortisolaemia) (Young, 2004).

Figure 3: This figure describes the mechanisms which are involved in glucocorticoids release visceral adipose tissue accumulation and the pathogenesis of metabolic syndrome. Cortisol is excreted as a responder to stressful events under HPA axis control and affects adipocytes promoting the visceral obesity. These conditions lead to the manifestation of metabolic syndrome (Paredes & Ribeiro, 2014).
Proinflammatory signals

Stetler & Miller (2001) stated that depressive patients show a raise in cortisol levels while Munkholm, Vinberg, & Vedel Kessing (2013) highlighted the existence of higher levels of pro- inflammatory markers such as IL-6, sIL-2R and TNF-a in bipolar disorder and major mood disorder patients. Thus, the contribution of immune-inflammatory dysregulation and mood disorders is emphasized by studies results (Dowlati et al., 2010; Howren, Lamkin, & Suls, 2009).

The adipose tissue constitutes a significant origin of cytokines and it has been stated that the inflammatory imbalances are present in mood disorders. The adiposity contributes as an immune-inflammatory dysregulation moderator as Choi, Joseph & Pilote (2013) highlighted and it has been found that obesity is related to a low-grade pro-inflammatory state with elevated levels of C-reactive protein.

At the same time, Hickman, Khambaty & Stewart (2014) compared individuals with atypical major depressive disorder, non-atypical major depressive disorder and with no major depressive disorder regarding to their serum C-reactive protein levels. The researchers found that participants with atypical features (compared to those with melancholic features) demonstrated higher levels of pro-inflammatory markers (TNF-a, CRP and IL-6).

Both metabolic abnormalities and mood disorders present an association with adipose-derived hormones in accordance to Wilhelm et al (2013). Barbosa et al (2012) have found that obesity is linked to lower levels of adiponectin while bipolar disorder and major depressive disorder to altered levels of adiponectin. Leptin, as it has mentioned before, is also associated with both obesity and mood disorders and it has been observed that high levels of waist circumference and leptin increase the risk of depression development (Milaneschi et al., 2012).

Adipose derived hormones

Τhe adipokines consist of polypeptides such as other non-protein products that are metabolically active molecules belonging to different categories, like immunization (additional agents, haptoglobin), endocrine function (leptin, steroid sex various growth factors) metabolic function (fatty acids, adiponectin, resistin) and cardiovascular functions (angiotensin, PAI-1) (Scherer, 2006).

The increase of adipose tissue is accompanied by changes in the distribution and morphology of fat cells, which differ between individuals because there is a genetic and an influence by lifestyle. The presence of large fat cells is accompanied by functional changes of which the most important are:

a) the increased production of adipocytes, the pro-inflammatory cytokines and reactive oxygen species (ROS),

b) the decreased storage of lipids capacity leading to ectopic deposition of fat,

That malfunction of adipose tissue causes activation against sympathetic nervous system (Scherer, 2006).

The research data that associates major depression disorder and adipokines is focused on leptin which is produced initially by differentiated adipocytes stimulating energy expenditure and repressing food intake (Munzberg, 2010). Primary leptin was identified as an antiobesity hormone as it was suggested to act as a negative feedback adiposity signal to control energy homeostasis by interacting with its receptors in the hypothalamus (Elmquist et al., 1998). Increased leptin levels are linked to obesity caused by leptin resistance (Munzberg & Myers, 2005).

Leptin and leptin receptors may be regarded as candidate genes for the development of obesity. Several polymorphisms in the coding region and the region 5 and 3 appear to be related to body weight, weight loss and BMI. The level of leptin used as a measure of obesity and polymorphism in leptin receptor (Gln223Arg) is associated with the fat mass and body composition in many populations (Morris & Rui, 2009; Speakman, 2004).

The majority of research data highlights the importance of leptin in determining body weight. Leptin is a protein, such as insulin, produced in adipocytes from the gene «ob» (obesity gene) and acts through specific receptors in the hypothalamus (control center of appetite), achieving the adjustment of the sense of hunger or saturation. Leptin levels are an indicator of energy reserves in the adipose tissue. High levels of leptin lead to reduced food intake and increase of energy consumption (Morris & Rui, 2009; Speakman, 2004).

Leptin has been found to reduce appetite, increases energy consumption, stimulates the gonadotropins and is an important regulator of the body's insulin sensitivity and the metabolic rate of the body (Morris & Rui, 2009; Speakman, 2004).

However, the mechanism of leptin appears to be broken in obese people and despite the fact that they have increased production and concentration of leptin in their blood they are unable to control their body weight due to the resistance to leptin. A new term is the "leptin resistance" and it is believed to be the reason by which the high levels of leptin in obesity are unable to suppress appetite and result in weight loss. Various mechanisms have been discovered to act to this resistance; recently an unsaturation carrier has been discovered which appears to prevent the passage of leptin across the blood brain barrier, where concentrations exceeding the normal, thus reducing the availability of the hypothalamus. Also, studies indicate that the signal transduction pathway inhibitors of leptin such as protein tyrosine phosphatase 1B (PTP-1B), SH-contained protein tyrosine phosphatase (SH-2) and the signaling cytokines inhibitor 3 (SOCS- 3) contribute to leptin resistance. The fact that insulin can increase the inhibitor SOCS-3 leptin appearing to act competitively in leptin is quite interesting (Dotsch, Rascher & Meissner, 2005).

Generally, the problems related to leptin are mainly the following three: the leptinopenia wherein fat cells do not produce normal amounts of leptin; the absence of leptin receptors in the brain and leptin-resistance, i.e. the desensitization mechanism of leptin recognition from the brain or the abnormal reaction of the brain to the stimulus that causes leptin when contacted with leptin receptors (Morris & Rui, 2009).

Stubbs et al (2016) study suggested that leptin has a significant role in the pathophysiology of schizophrenia and performed a systematic review and meta-analysis in order to compare leptin levels on control groups and schizophrenic patients. They collected scientific 27 articles which represented 2.033 control group individuals and 1.674 schizophrenic individuals. The follow figure shows the summary of the included studies.

Their analysis found that when one outlier was removed leptin levels maybe marginally higher in schizophrenia. Moreover, leptin levels were higher in females and multi-episode schizophrenia.

4. Factors involved in the correlation between metabolic abnormalities and Mood Disorders
The systematic review of longitudinal studies of Luppino et al (2010) have reported the bidirectional association between depression and obesity and more specifically they found out that obese people are at 55% increased risk of developing depression while depressed people are on at 58% increased risk of becoming obese. Gariepy, Nitka & Schmitz (2010) meta-analysis confirmed the association between anxiety disorders and obesity.
Obese women and men experience greater odds (OR from 1.21 to 2.08) of any mood and anxiety disorder (Petry et al., 2008) while Scott et al (2008) mentioned that obesity is associated with anxiety disorder (OR = 1.46), major depressive disorder (OR = 1.27) and mood disorder (OR = 1.23).
Obesity influences several biological pathways associated with psychiatric disorders including immuno-inflammatory processes, oxidative stress, neuroprogression, mitochondrial disturbances, HPA axis imbalances, and neurotransmitter imbalances. A bi-directional relationship likely exists (represented by the bidirectional arrow) between obesity and psychiatric disorders, as obesity increases the risk of psychiatric disorders, and suffering from a psychiatric disorder increases the likelihood of obesity. Suffering from both these conditions is likely to have an additive influence on these pathways. While psychiatric disorders share many commonalities in dysregulated pathways, genetic, environmental, lifestyle, and psychological factors will determine the specific disorder(s) suffered [C - reactive protein (CRP), interleukin-6 (IL-6), tumour necrosis factor-α (TNF-α), indoleamine 2, 3 3-dioxygenase (IDO)].



Figure 4: Stubbs et al (2015) representation of association between neuropsychological and metabolic phenotypes aspects.

The authors suggests that this phenotypical congruity is moderated by shared pathophysiological pathways which are underlied by environmental and genetic risk factors as it will be analyzed later in the this chapter. The existence of specific environmental and, epigenetic, and genetic factors, such as genetic vulnerabilities, stress, the inadequate or excessive food intake, or the childhood trauma, could lead to the negative impact on neural systems and peripheral homoeostatic systems. This impact could be translated transferred into the damage on brain structures damage and functioning connectivity dysfunction. , on bBrain energy metabolism, and BDNF, and endocannabinoid system are affected caused by dysregulation of HPA axis, the existence of inflammation and adipocytes derived hormones are present. These alterations may lead on to phenotypical expression of metabolic phenotype and behavioral/emotional phenotype, which whose combination constitutes forms the metabolic-mood syndrome.

Genetic

Generally, the genes affect the body weight to the extent that encodes molecular components of the normal setup system. The detection of rare mutations has raised new ground in detecting pathways involved in the regulation of body weight. The volatilities at the gene sequence adrenergic receptors of uncoupling proteins have the greatest scientific interest nuclear, also the PPAs receptors and the leptin receptor. The results of studies analysis of the genome shows that the key genes are located mainly in the genes chromosomes 2p, 3q, 5p, 6p, 7q, 10p, 11q, 17, and 20q (Loos & Bouchard, 2003).

Proopiomelanocortin (POMC) is a precursor of many neuropeptides and hormones of the hypothalamic - pituitary - adrenal axis and neuropeptides and participates in the regulation of energy consumption and food intake. The mutations of the gene encoding the synthesis of proopiomelanocortin affectinhibit the synthesis of alpha-MSH, a neuropeptide that inhibits appetite in the hypothalamus, leading to severe obesity (Krubde et al., 1998).

Bell, Walley & Froguel (2005) have mentioned that obesity is heritable for ranging from 50 to 90% and Kendler et al (2006) and Smoller & Finn (2003) have stated that major depressive disorder is hereditary about 30-50%, while bipolar disorder is heritable about 50-70%. Kerner (2014) reports that obesity and mood disorders present a polygenic mode of inheritance as multiple genes are conduced to their deploymentinvolved in their pathophysiology.

Farmer et al (2008) have mentioned a relationship between increased BMI and depression, as their regression analyses have showed shown that metabolic syndrome was widely accounted for BMI. Newly studies indicate the potential shared aetiological factors (containing genetic factors) between obesity and unipolar depression (Rivera et al., 2012; Patten et al., 2005).

Barry, Pietrzak & Petry (2008) and Scott et al (2008) studies have investigated the FTO on BMI in a large sample of depressed patients to report the association with obesity and psychiatric disorders. Rivera et al (2012) investigated the genetic influence of polymorphisms in FTO in relation to BMI to in control group (Radiant Study) and group with major depressive disorder. 88 polymorphisms have been analyzed and 8 of the top 10 single-nucleotide polymorphisms, showing the strongest associations with BMI, were followed-up in a population-based cohort. The results have shown a significant interaction between genotype and affected status in relation to BMI for seven SNPs in radiant indicating an association between mood disorders and obesity.

Several studies have reported that fat mass and obesity associated gene, FTO on chromosome 16q contribute to obesity (Loos & Bouchard, 2008; Dina et al., 2007; Frayling et al., 2007; Scuteri et al., 2007).

Rivera et al (2012) have suggested that the association between FTO and obesity was mitigated by the attendance presence of depressive symptoms. A differentiation in gene TCF7L2 has been associated with protection to bipolar disease, but as BMI increases this outcome becomes weaker. Gene TCF7L2 encodes a transcription factor involved in the Wnt signaling pathway (Winham & Biernacka, 2013).

Developmental aspects

It has been suggested that obesity and mood disorders are sharingshare developmental pathways (Wu et al., 2012). Several studies have associated pediatric and adolescent obesity with adulthood depression in adults (Reeves, Postolache & Snitker, 2008; Anderson et al., 2007).

Reeves, Postolache & Snitker (2008) concluded that the investigation of childhood factors that influence the onset of adulthood depression and obesity in adults and obesity is needed.

Early child-hood malnutrition and low birth-weight have been linked to higher odds of developing depression during adulthood (or adolescence) (Wojcik et al., 2013; Sanchez-Villegas et al., 2012).

Grigoriadis et al (2013) have noted that mothers' depression due to pregnancy increases the risk of depression development in puberty, a fact that have been confirmed by Pearson et al (2013) and Raisanen et al (2014).

The exposure of fetus to maternal depression has been characterized as a risk factor of for childhood obesity development (Ruttle et al., 2014), while epigenetic processes such as DNA methylations causing changes in gene expression have been suggested as underlying developmental mechanisms. More specifically, Teh et al (2014) have found a link between mother's' depression and obesity with epigenetic modifications.

Anderson et al (2007) have found that women who had experienced early childhood depression have had higher weight gain and BMI z scores in contrast to the women without depression.

A potential link between obesity and depression could be include altered stress system and increased inflammation, as obesity is regarded as a pro-inflammatory state. Both human and animal investigations have mentioned that obesity increases adipose tissue expression and the secretion of pro-inflammatory cytokines.

Also it has been reported that treatment options that reduce obesity or insulin resistance have a moderating effect of on reducing inflammation (Ferrante AW Jr, 2007). In obese children the levels of the pro-inflammatory cytokine IL-6 and the C-reactive protein have been shown to be higher in comparison as levels of C-reactive protein to overweight and non-overweight youths (McMurray et al., 2007; Cindik et al., 2005).

Additionally, there is evidence that depression is linked to dysregulation of inflammatory system, where patients suffering major depressive disorder have higher levels of pro-inflammatory cytokines IL-6 and tumor necrosis factor alpha (Kim et al., 2007).

Those levels were also higher in patients with treatment treatment-refractory depression, as well as and in as euthymic individuals who were previously treatment-t refractory in accordance to O'Brien et al (2007).

Charmandari et al (2003) based on Gold & Chrousos (2002) centering on the hypothalamic-pituitary-adrenal (HPA) axis argued that early childhood stress effects onleads to the dysregulation of the stress system. This dysregulation causes hyperreactivity of the stress system and impaired glucocorticoid negative feedback showing a link between depression states and obesity.

The treatment used for pediatric depression (serotonin selective reuptake inhibitors - SSRI's) could play a role in the association of obesity and depression. It has been shown that serotonin affects appetite through food intake/preferences and mood states.

Wurtman & Wurtman (1995) have argued that underlying decreases serotonin decrease during mood episodes in seasonal depression could be an explanation factor explaining forthe preference for carbohydrates since they which increases the serotonin levels.

Gotlib et al (2008) assumed that it there could be a potentialn association between serotonin and HPA axis stress response through the investigation of discrepancies found in the promoter region of the serotonin transporter gene.

Environmental

Mood disorders and obesity share have some common environmental risk factors of for their development such as the chronic psychosocial stress (Horesh & Iancu, 2010; Kyrou et al., 2006). One of the greatest risk factors for mood disorders is childhood trauma (i.e. physical, emotional and sexual abuse) (Watson et al., 2013; Carr et al., 2013; Nanni, Uher & Danese, 2012) while and recent evidence shows an impact on metabolic health causing the increase of BMI and the risk of metabolic syndrome development in adulthood (Lee, Tsenkova & Carr, 2014a; Midei et al., 2013; Pervanidou & Chrousos, 2012; Midei, Matthews & Bromberger, 2010).

The scarcity of physical activity/exercise and the insufficient diet play a significant role oin obesity onset while studies (Lai et al., 2014; Sanhueza, Ryan & Foxcroft, 2013; Lopresti Hood & Drummond, 2013a; Vancampfort et al., 2013) have argued that play a role oin the onset of bipolar disorder and major depression disorder too.

Regarding to the socioeconomic risk factors, several epidemiological studies have found a positive association between obesity and mood disorders and unpropitious socioeconomic status. More specifically, poverty, isolation, low education level, and scarcity of support affect the onset of both obesity and mood disorders (Devaux & Sassi, 2013; Sassi, Devaux, & Church, 2009; Everson et al., 2002).

Brain substrates

Functional connectivity problems and changes in brain structure are connected to mood disorders. Studies using neuroimaging have reported irregular probity in the neural tracts which connect the temporal and parietal cortices with the frontal cortex and sub-cortical regions in major depressive disorder in bipolar disorder (Liao et al., 2013; Vederine et al., 2011) while it has been shown that there is a decreased connectivity between limbic brain structures and ventral prefrontal networks (Vargas, Lopez-Jaramillo & Vieta, 2013; Strakowski et al., 2012). These networks may be involved in the formation of emotional control and cognition.

Obesity has also been considered to be subserved by abnormal brain networks (Mansur, Brietzke & McIntyre, 2015). In accordance to Garcia-Garcia et al (2012) obesity is considered to be linked to disturbed connectivity in neurocircuits which are involved in reward and motivation regulation including fronto-occipital and fronto-amygdala networks. These abnormalities, both at resting-state and in response to food and non-food rewarding stimuli, point out the extension beyond appetite regulation.

Bond et al (2011) found the increased BMI in bipolar disorder patients has been shown to mediate the decrease of brain white-matter volume and temporal lobe volume while Cole et al (2013) mentioned that in major depressive disorder patients, the reductions in subcortical and white matter areas were associated with increased BMI.

Serotonin, dopamine and opioids seems to be involved in mood regulation and brain reward circuitry. These neurotransmitters are also involved in homeostatic regulation of food intake (Russo & Nestler, 2013). Van de Giessen et al (2014) suggested that the abnormal dopamine signaling (low dopamine receptor availability) which is proportional to patient's BMI increased the sensitivity to conditioned stimuli and decreased sensitivity to rewarding effects.

Also, abnormities in cellular bioenergetics (focused on mitochondrial function) seem to be tangled in mood disorders aetiology (Manji et al., 2012) and in pathopsysiological mechanisms of obesity (Thrush et al., 2013).

Additionally, brain-derived neurotrophic factor (BDNF) is found to be a moderator of neuroplasticity and seems to be implicated in energy metabolism (Zagrebelsky & Korte, 2014; Marosi & Mattson, 2014). As Markham et al (2012)note, other functions that BDNF in part of are modulating neuronal glucose transport and mitochondrial function, energy homeostasis regulation, cellular bioenergetics, while the decrease of BDNF expression seems to be associated to obesity and hyperphagia in mouse model. BDNF expression in the hypothalamus was found to be inhibited by dietary restriction and enhanced by energy availability (Unger et al., 2007). Moreover, BMI has been associated with single nucleotide polymorphism Val66Met of BDNF gene (Shugart et al., 2009). Val66Met is a single nucleotide polymorphism which present a non-synonymous amino acid substitution of methionine (Met) for valine (Val) at position 66 of the BDNF protein (Bonaccorso et al., 2015).

Also, the endocannabinoid system (ECS) is suggested to be implicated in the regulation of energy metabolism and could be a factor in bipolar disorder and major depressive disorder pathophysiology (Ashton & Moore, 2011). ECS interacts with systems which are involved in the regulation of weight and food intake and also with energy-related hormones (such as leptin) (Bermudez-Silva et al., 2012). In the case of ECS dysregulation a development of obesity could be triggered, as were found to be altered in adipose tissue and in the plasma and saliva of obese people (Matias et al., 2012).

The chronic antagonism of the CB1 receptor reduced body weight con-comitant improvements of metabolic parameters (Christopoulou & Kiortsis, 2011). eCB signaling has been characterized as a crucial modulator of the stress response through modulatory effects in HPA axis activation and behavioral reactions (Hill & Tasker, 2012). A CB1 antagonist impairs the antidepressant effects of eCBs and is connected to molecular pathways mediating both mood and metabolism (Moreira et al., 2008).

A potential aetiology of obesity and depression is the dysregulation of the hypothalamic-pituitary-adrenocortical system which is present on both health situations (Collins & Bentz, 2009; Scott et al., 2008; McIntyre et al., 2006; Carr & Friedman, 2005; Faith, Matz & Jorge, 2002).

Gold & Chrousos (2002) based on hypothalamic-pituitary-adrenal (HPA) axis created a concise model that presumes 2 subtypes of depression, melancholic and atypical of the stress system by changes in the HPA axis and sympathetic arousal. The depressed patients show decrease of sympathetic activity and HPA axis a fact that cause the increase of appetite which is triggered by sympathetic stimulation and corticotrophin releasing hormone mediated glucocorticoid secretion. These metabolic effects of HPA down regulation cause the increase of fat mass and the decrease of insulin sensitivity and dyslipidemia. Insulin resistance could be an aetiology factor of the association of obesity and depression.