INTRODUCTION
Biomarkers can be defined as molecules (genetic sequences, proteins or small molecules found in blood, urine, saliva, cerebrospinal fluid [CSF]) or as specific patterns of activation in anatomical structures (e.g. functional magnetic resonance imaging of brain regions) associated with a disease state. Therefore, biomarkers can be classified into three primary categories: protein-based, imaging-linked, and genetic. All these have a great potential for improving care of psychiatric patients. In particular three areas of application can be identified: i. enhanced diagnostic accuracy (in a field in which diagnoses are generally symptom-based), ii. prognostic information about the natural course of an individual’s illness, iii. prediction of response to treatment (Singh and Rose, 2009).
Candidate biomarkers should be chosen according to established knowledge about mechanisms of diseases. Afterwards, biomarkers studies require peer review of findings and independent replication taking into account that desirable characteristics of biomarkers in psychiatry should be: i. test reliability and accuracy, ii. timely and clinically usefulness of the information provided, iii. methodology well tolerated by target patient population and integrable into clinical care patterns (Cook, 2008).
In the last decades the identification of biomarkers relevant to mental disorders has been slow probably because of the lack in etiological models of diagnoses for psychiatric disorders. In fact, it is very challenging to identify biomarkers which meet such important issues. However, the research in this field continues to be primary because these approaches could greatly expand general knowledge about psychiatric disorders neurobiology. So, even if to date most investigated proteins have found limited application in daily clinical practices, they could still be useful as research tools.
Easily accessible bodily fluids like blood, urine and CSF are potential sources for the identification of protein-based biomarkers in psychiatry. Among all, CSF is probably the most relevant source because proteins secreted by neurons can be found there. However, the same proteins can be eventually measured in the blood due to a dynamic exchange with CSF. The poor invasiveness of a blood sample collection and test makes the blood a source much more suitable than CSF for a clinical diagnostic assay (van Beveren and Hoogendijk, 2011).
The aim of this dissertation is to investigate about blood biomarkers related to the recent neurotrophic and neurodegenerative hypotheses for mood disorders.
Over the past 10 years, molecular and cellular studies about stress, depression, and antidepressants have moved the field of mood disorder research beyond the monoamine hypothesis of depression. These studies demonstrated that stress and antidepressant treatment exert opposite actions on the expression of specific neurotrophic factors in brain regions involved in the regulations of mood and cognition. According to the neurotrophic hypothesis, depression is the clinical manifestation of a prolonged neuronal distress biologically associated with a neurotrophin deficit causing a decrease in synaptic connections, receptors expression, and neuronal survival (Duman et al., 1997). Different studies demonstrated that stress and depression can lead to neuronal atrophy and cell loss in key limbic areas implicated in depression (including the amygdala, prefrontal cortex, and hippocampus) and that antidepressant treatment can block or reverse these effects (Sapolsky, 2001; Sheline et al., 2003; Banasr et al., 2011). Most notable are studies on brain-derived neurotrophic factor (BDNF) which is involved in differentiation, survival of peripheral and central neurons and modulation of synaptic plasticity (Poo, 2001; Popoli et al., 2002). Many different types of acute or chronic stress paradigms in animal models decrease the expression of BDNF in the hippocampus while BDNF produces antidepressant effects in behavioural models of depression (Duman and Monteggia, 2006; Siuciak et al., 1997; Shirayama et al., 2002).
Moreover, chronic specific antidepressant treatment but also other treatments that are known to have antidepressant efficacy (NMDA antagonists, electroconvulsion and transcranial magnetic stimulation) produce BDNF up-regulation in the brain (Nibuja et al., 1995; Tardito et al., 2006;
Duman and Monteggia, 2006). In humans, some recent meta-analyses demonstrated that blood BDNF behaves as a state marker of mood episodes: during a depressive or manic episode patients exhibit lower plasma and/or serum BDNF levels than those of healthy subjects.
BDNF levels increase up to controls’ levels after specific treatments and remission of symptoms (Sen et al., 2008; Lin, 2009; Fernandes et al., 2011; Polyakova et al., 2015).
These theoretical foundations supported the first study of this dissertation which aimed to assess plasma BDNF levels in a sample of patients with mixed episode and compare them with the values of depressed patients and healthy subjects. Our study derived from the observation that the current literature was lacking regarding BDNF levels during the mixed episode of BD patients. It is part of an important strand of our research group that previously had given other contributions to the study of BDNF role as potential biomarker of mood disorders. Our previous studies have demonstrated lower plasma BDNF levels in depressed patients compared to healthy controls with subsequent recovery during antidepressant treatment and one year clinical follow-up (Piccinni et al., 2008). Moreover, we found electroconvulsive therapy (ECT)
effectiveness in producing an increase of plasma BDNF values up to those of healthy controls in drug-resistant depressed patients who responded to treatment (Piccinni et al., 2009). Finally, another study showed that plasma BDNF levels in depressed patients were negatively correlated with the number of episodes, with the severity of symptoms and, in particular, with the severity of the most representative symptoms of HPA (hypothalamic-pituitary-adrenal) axis dysfunctions such as sleep disturbances and psychomotor retardation (Dell’Osso et al., 2010).
The second and the third presented studies investigated about beta-amyloid (Aβ) plasma levels in a sample of bipolar depressed patients and in a sample of drug-resistant bipolar depressed patients treated with ECT. These last projects derived from some clinical and preclinical observations. Firstly, patients suffering from mood disorders show high risk for cognitive decline and dementia. The impairment in attention, memory and executive functions characterizes both the depressive and manic phases but cognitive deficits have been described also during the euthimic periods of bipolar patients (for review see: Goodwin et al., 2008).
Both cognitive impairment and risk for dementia correlate with the severity of illness course in terms of number of episodes and early-onset (Kessing and Andersen, 2004; Robinson et al., 2006; Geerlings et al., 2008; Dotson et al., 2010). Strakowsky et al. (2005) observed that some brain regions (cerebellar vermis, lateral ventricles, inferior prefrontal regions) degenerate during the course of bipolar disorder: they speculated that this atrophy represents the effect of the illness progression. This hypothesis is supported by a four-year follow-up study. The severity of illness course correlates with reduction in memory function and atrophy of the medial-temporal cortex in bipolar patients (Moorhead et al., 2007).
Beta-amyloid is the main component of extracellular plaques in Alzheimer’s Disease (AD) and its soluble oligomers are known to exhibit important neurotoxicity through the inhibition of long term potentiation (LTP; Walsh et al., 2002, 2005; Chen et al., 2002) and BDNF expression (Arvanitis et al., 2007; Arancio and Chao, 2007). Another recent study showed that a single intracerebroventricular (i.c.v.) injection of soluble Aβ in rats induces a significant reduction of BDNF protein and mRNA in prefrontal cortex (Colaianna et al., 2010). Aβ-treated rats showed a significant reduction in explorating the environment and a motivational deficit.
Moreover, a marked increase in time of immobility was noted in the forced swimming test which is a behavioural paradigm for depression (Colaianna et al., 2010). The same authors described a marked reduction of 5-hydroxytryptamine (5-HT) and dopamine (DA) levels in the prefrontal cortex of Aβ-treated rats. These preclinical findings led to investigate about the role of Aβ in the pathophysiology of mood disorders. Studies on blood samples have reported in
depressed patients dysregulation of Aβ peptides (with respect to controls: lower levels of Aβ42, matching levels of Aβ40 and a higher Aβ40/42 ratio) similarly to that described in patients suffering from AD and mild cognitive impairment (MCI) (Qiu et al., 2007; Sun et al., 2007, 2008). Sun et al. (2008) hypothesized the existence in the elderly of a so-called
“amyloid-associated depression” characterized by severe cognitive deficits and considered as a prodromal manifestation of dementia. However, such changes in different Aβ peptides have recently been described also in young depressed patients, suggesting that also an early-onset depression may be associated with a greater risk for AD (Kita et al., 2009; Baba et al., 2012).
In conclusion, the aim of the two last presented studied was to measure plasma Aβ peptides levels in a sample of bipolar depressed patients and healthy subjects and to explore the possible relationship between plasma Aβ levels, the clinical course of affective illness and the ECT response.
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