The theory of bipolar disorder as an illness of accelerated aging: Implications for clinical care and research

Neuroscience and Biobehavioral Reviews 42 (2014) 157–169

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Review

The theory of bipolar disorder as an illness of accelerated aging: Implications for clinical care and research Lucas Bortolotto Rizzo a,b , Leonardo Gazzi Costa a,b , Rodrigo B. Mansur a,b,c , Walter Swardfager d , Síntia Iole Belangero b,e , Rodrigo Grassi-Oliveira f , Roger S. McIntyre c,d , Moisés E. Bauer f , Elisa Brietzke a,b,∗ a Program for Recognition and Intervention in Individuals in At-Risk Mental States (PRISMA), Department of Psychiatry, Federal University of São Paulo, São Paulo, Brazil b Interdisciplinary Laboratory of Clinical Neuroscience (LINC), Department of Psychiatry, Federal University of São Paulo, São Paulo, Brazil c Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, Ontario, Canada d Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada e Department of Morphology and Genetics, Federal University of São Paulo, São Paulo, Brazil f Institute of Biomedical Research and Faculty of Biosciences, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil

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Article history: Received 29 August 2013 Received in revised form 17 December 2013 Accepted 5 February 2014 Keywords: Bipolar disorder Aging Biomarkers Neuroprogression Telomeres Inflammation Immunosenescence BDNF Oxidative stress Amyloid Cognition Molecular imaging

a b s t r a c t Bipolar Disorder (BD) has been conceptualized as both a cyclic and a progressive disorder. Mechanisms involved in neuroprogression in BD remain largely unknown although several non-mutually exclusive models have been proposed as explanatory frameworks. In the present paper, we propose that the pathophysiological changes observed in BD (e.g. brain structural alterations, cognitive deficits, oxidative stress imbalance, amyloid metabolism, immunological deregulation, immunosenescence, neurotrophic deficiencies and telomere shortening) converge on a model of accelerated aging (AA). Aging can be understood as a multidimensional process involving physical, neuropsychological, and social changes, which can be highly variable between individuals. Determinants of successful aging (e.g environmental and genetic factors), may also confer differential vulnerability to components of BD pathophysiology and contribute to the clinical presentation of BD. Herein we discuss how the understanding of aging and senescence can contribute to the search for new and promising molecular targets to explain and ameliorate neuroprogression in BD. We also present the strengths and limitations of this concept. © 2014 Elsevier Ltd. All rights reserved.

Contents 1. 2.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Neurobiological similarities between neuroprogression in BD and aging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Changes at the structural level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Changes at the functional levels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3. Changes at the molecular level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.1. Increased oxidative stress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.2. Disturbances in amyloid metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4. Changes at the cellular level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.1. Immunosenescence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.2. Reduction in neurotrophins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.3. Short telomeres . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

∗ Corresponding author at: R. Pedro de Toledo, 669, 3◦ andar Vila Clementino, CEP: 04039-032 São Paulo, Brazil. E-mail address: [email protected] (E. Brietzke). http://dx.doi.org/10.1016/j.neubiorev.2014.02.004 0149-7634/© 2014 Elsevier Ltd. All rights reserved.

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Implications for research directed to clinical care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Pharmacological strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.1. Current pharmacology modulating aging related mechanisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.2. Sirtuins as possible new target . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Non-pharmacological strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1. Physical activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conflict of interest statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1. Introduction Bipolar Disorder (BD) is a prevalent and often severe mood disorder where individuals experience disruptive episodes of mania or hypomania and depression (Anderson et al., 2012). Causes of BD remain largely unknown but probably involve a set of genetic and environmental factors, which interact during neurodevelopment to determine vulnerability to the disease (Brietzke et al., 2012a). Genetic studies have implicated many chromosomal regions and candidate genes, but results have been inconsistent and often not replicable (Sullivan et al., 2012). Genome-wide Associantion Studies (GWAS) studies indicate that genetic susceptibility is determined by a high number of genes, each with a small effect size (Sullivan et al., 2012). Although BD has been understood classically as a cyclic disease, in the last 10 years evidence has accumulated supporting progressive features of BD (Berk et al., 2010; Fries et al., 2012; Mansur et al., 2013), reconceptualizing BD as both a cyclic and progressive disorder. The starting point for this hypothesis was the clinical evidence that individuals in early and late stages of BD present substantial differences in the severity of clinical presentation and response to treatment (Berk et al., 2011). There are robust data suggesting that a greater number of episodes, especially those of manic polarity, are associated with a decrease in the length of the euthymic interval between episodes, worsening of neurocognitive performance, increasing risk of suicide, and poorer response to both pharmacological and psychosocial treatments (Berk et al., 2010; Magalhaes et al., 2012). Nonetheless, evidence has been mixed and progressive models of mental illness are not universally accepted (Zipursky et al., 2013). At present, operationalization of the concept of neuroprogression in clinical practice manifests mainly in the “staging” of severe mental disorders, including BD (for a detailed review, please see Kapczinski et al., 2009). Mechanisms involved in neuroprogression remain largely unknown and only few explanatory models exist that could justify a neuroprogressive disease course. Among these, one of the most accepted is the concept of Allostatic Load (AL). AL implicates chronic stress in overactivating homeostatic mechanisms that are collectively beyond the capability of the organism, leading to progression of clinical and neurobiological parameters (Brietzke et al., 2011; Goldstein et al., 2009b; Grande et al., 2012; Kapczinski et al., 2008). However, it has been difficult to quantify the impact of stress biology on neuroprogression, in part due to mechanisms of resistance and resilience that can modulate the impact of stress (Brietzke et al., 2012b). Another nascent theoretical framework is the concept of BD as a disorder of accelerated aging (AA) (Simon et al., 2006; Sodhi et al., 2012). Aging in humans refers to a persistent decline in the age-specific fitness components of an organism due to internal physiological degeneration (Rose, 1991). Aging can also be understood as a multidimensional process of physical, neuropsychological, and social changes. With respect to neuropsychological changes, the effect of aging is non-uniform

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across domains. For instance, psychomotor processing speed and verbal memory performance decline with age, while knowledge and wisdom can continue to expand. The rates of change in these domains differ between individuals and they can be modified by many intervening genetic and environmental factors. A complementary concept is the idea of senescence. The phenomenon of cellular senescence was first described by Leonard Hayflick in 1961, referring to the limited capacity of isolated cells to proliferate in culture (the Hayflick Limit) (Hayflick and Moorhead, 1961), but the concept can also be applied to whole organisms. For example, after a period of near perfect renewal (in humans, between 20 and 35 years of age), organismal senescence is characterized by the declining ability to respond to stress, increasing homeostatic imbalance and risk of disease. Preliminary data suggest that individuals with BD present early senescent features consistent with AA. One of the most clinically conspicuous corollaries is the high prevalence and earlier age on onset of age related medical conditions e.g. cardiovascular conditions, hypertension, metabolic imbalances, autoimmunity and cancer (Crump et al., 2013; Czepielewski et al., 2013; Fagiolini et al., 2008; Goldstein et al., 2009a; McIntyre et al., 2005, 2006; Osby et al., 2001; Padmos et al., 2004; Rege and Hodgkinson, 2013; Soreca et al., 2008). In addition, the association between mood disorders and dementia has been well recognized. Most studies include individuals with Major Depressive Disorder (MDD), but a recent meta-analysis suggested that the association between BD and dementia might be stronger than that of MDD (da Silva et al., 2013). Although the degree of neurobiological overlap between the two conditions remains a matter of debate, there is evidence that inflammation, neurotrophic and amyloid cascades are altered in both conditions (Aprahamian et al., 2013; Modabbernia et al., 2013). Here we discuss how aging and senescence may contribute to the search for new and promising molecular targets to better understand neuroprogressive features of BD. Although some findings are preliminary, we postulate they can be integrated in a new theoretical framework to better explain some elements of BD pathophysiology. 2. Neurobiological similarities between neuroprogression in BD and aging Although there are few studies exploring aging in BD, there is a surprisingly high overlap between neurobiological mechanisms in the two conditions, including progressive changes at the molecular and cellular levels, and in the structure and function of the central nervous system (CNS) (Fig. 1). 2.1. Changes at the structural level Normal aging is associated with alterations in brain structures. Post mortem and structural neuroimaging studies indicate that the human brain shrinks with age, with selective and differential

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Fig. 1. Biological findings linking bipolar disorder and aging. White matter hyperintensities (WMH), T regulatory cells (Treg), cytomegalovirus (CMV), nitric Oxide (NO), thiobarbituric acid reactive substances, (TBARS), superoxide dismutase (SOD), catalase (CAT).

changes that are not uniform or random. CNS volume atrophy is indicated by reduced brain weight and volume, ventriculomegaly and sulcal expansion. Microscopic studies documented myelin pallor, loss of neuronal bodies in the neocortex, the hippocampus and the cerebellum, loss of myelinated fibers across the subcortical cerebrum, shrinkage and dysmorphology of neurons, accumulation of lipofuscin, rarefication of cerebral vasculature, reduction in synaptic density, deafferentation and loss of dendritic spines (Raz and Rodrigue, 2006). The main findings of magnetic resonance imaging studies include brain atrophy (total brain volume: 0.4–0.5% brain tissue loss per year); hippocampal volume loss (1.6% per year in normal individuals); white matter lesions as punctiform or early confluent lesions in periventricular or subcortical distribution and cerebral microbleeds (prevalence more than 20% in persons older than 60 years) (Allen et al., 2005; DeCarli et al., 2005; Enzinger et al., 2005; Fotenos et al., 2005; Ikram et al., 2008; Jernigan et al., 2001; van der Lijn et al., 2008; Vernooij and Smits, 2012). BD is also associated with alterations in brain structures evidenced by previous imaging studies that reported findings of enlargement of the third and lateral ventricles; a reduction in the gray matter volumes of the orbital and medial prefrontal cortex, ventral striatum and mesotemporal cortex and an increase in the size of the amygdala (Hallahan et al., 2011; Konarski et al., 2008; Lisy et al., 2011; Martinez-Aran et al., 2002). These neuroanatomical changes tend to be more pronounced in patients with repeated episodes (Lisy et al., 2011; Strakowski et al., 2002). Furthermore, one of the most consistently reported abnormalities in BD is an increased number and/or severity of white matter hyperintensities (WMH) (Mahon et al., 2010; Mahon et al., 2009). The main findings of neuropathogical studies suggest deficits in neuroplasticity, particularly in cell resilience and connectivity (Connor et al., 2009; Harrison, 2002; Martinez-Aran

et al., 2002; Rajkowska, 2002) as well as data showing fewer oligodendrocytes in prefrontal white matter (Vostrikov et al., 2007). 2.2. Changes at the functional levels The tertiary association cortices, the neostriatum, and the cerebellum are profoundly affected by aging throughout the adult lifespan. Regional volumetric decline has been linked with domainspecific declines in cognitive performance. For example, poorer performance on executive function tasks has been associated with smaller volume of the prefrontal cortex and increased white matter hyperintensity burden. Skill acquisition performance is enhanced in those individuals who show larger volumes of the striatum, prefrontal cortex and cerebellum. Spatial memory performance has been linked to hippocampal volume and the concentration of Nacetyl aspartate therein. In addition, entorhinal cortex shrinkage has been found to predict memory decline, even in healthy individuals (Raz and Rodrigue, 2006). BD is associated with cognitive impairment during acute phases of illness and euthymia, with greater abnormalities reported as function of more frequent episodes (Martinez-Aran et al., 2005; Martinez-Aran et al., 2004; Robinson et al., 2006). The most severe impairments are seen in verbal working memory, response inhibition, sustained attention, psychomotor speed, abstraction and set-shifting (Martinez-Aran et al., 2007). These deficits in executive function and verbal memory have been associated with poorer functional outcomes (Torrent et al., 2006; Ustun, 1999) and burden of illness associated with BD (Rosa et al., 2008). It is similar of individuals with mild cognitive impairment and early dementia who frequently report impairments in functioning such as poor performance in household management activities and in more advanced functions

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(Albert et al., 1999). Furthermore, impairments psychosocial functioning can take a progressive course (Rosa et al., 2012; Rosa et al., 2011) and can be present during euthymia (Swann et al., 1999). Some authors have proposed that individuals with BD present an acceleration in age-related cognitive decline, when compared with healthy controls (Gualtieri and Johnson, 2008), although there are some contrary data (Samame et al., 2013). Individuals with MDD, especially those who present the disorder in late life, carry a well-documented risk of dementia (Aprahamian et al., 2013; Osorio et al., 2013). The increased risk of dementia associated with mood disorders in epidemiological studies may be due to common neuropathological changes shared by these disorders. The investigation of aging and senescence processes might lead to an improved understanding of these associations (Gualtieri and Johnson, 2008). 2.3. Changes at the molecular level 2.3.1. Increased oxidative stress Increased generation of reactive oxygen species (ROS) or dysregulation of anti-oxidant mechanisms can lead to the damage of cellular components such as DNA, proteins and lipids (Andreazza et al., 2009). Possible sources of ROS include changes in energy generation and ATP production, for instance free radicals can be generated during mitochondrial electron transport (Steckert et al., 2010). Other cell process can also generate ROS, including excessive dopaminergic transmission (due reductive potential of this neurotransmitter and its metabolites) and increases in levels of glutamate leading to increases in levels of intracellular calcium and cytotoxicity (Berk et al., 2011). Under physiological conditions, the harmful potential of ROS is kept under control by enzymatic and non-enzymatic antioxidant defense systems (Steckert et al., 2010). As oxidative stress has been considered a major source of molecular and cellular damage, and aging can be understood as a lifelong process of cell damage, these two phenomena are presumably linked. Key pathophysiological elements of several diseases related to aging cause end-organ damage through oxidative mechanisms, including chronic obstructive pulmonary disease (Ito et al., 2012), cancer (Ito et al., 2012), type II diabetes (Stadler, 2012), cardiovascular disease (Penna et al., 2013), Parkinson’s disease (Torrao et al., 2012), and Alzheimer’s disease (Torrao et al., 2012). These data initially lead to “the free radical theory of aging” supported extensively by numerous in vivo and in vitro studies (Harman, 2009). Cumulative oxidative stress causes DNA damage, reduces mechanisms of DNA repair, stimulates inflammatory activation and modulates redox-sensitive transcriptional factors, such as activator protein (AP)-1 and nuclear factor-kappa B (NF-␬B), which alter the transcription of numerous genes, both adaptive and maladaptive, consequently disrupting homeostasis. Increased oxidative stress and its cellular and molecular consequences have been found extensively in BD. In animal models of mania, increases in oxidative mediators such as thiobarbituric acid reactive substances (TBARS) are well documented (Ghedim et al., 2012). Studies that focused on individuals in manic episodes observed increases in nitric oxide (NO) and TBARS, as well as decreases in antioxidant enzymes, including superoxide dismutase (SOD) and catalase (CAT) (Gergerlioglu et al., 2007; Machado-Vieira et al., 2007; Savas et al., 2002). Acute treatment with lithium appears to have an antioxidant effect, as it was shown to affect TBARS, SOD and CAT levels (Machado-Vieira et al., 2007). The only study that evaluated BD individuals in depressive episodes reported higher levels of NO and lower levels of SOD, which were also responsive to pharmacological treatment (Selek et al., 2008). While imbalances in oxidative stress can be detected in early stages of disease, they tend to be more pronounced with increasing duration of illness or number of episodes, suggesting that oxidative stress might be a mechanism of neuroprogression and a source of

plasma biomarkers to monitor the course of the disease (Andreazza et al., 2009; Berk et al., 2011; Magalhaes et al., 2012). 2.3.2. Disturbances in amyloid metabolism Amyloid ␤ (A␤) peptides of 40 or 42 amino acids are formed after sequential cleavage of the amyloid precursor protein (APP), a trans membrane glycoprotein of undetermined function, by successive action of the ␤ and ␥ secretases (Zhang et al., 2011). Alzheimer’s disease (AD) is characterized, from a neuropathological standpoint, by the extracellular deposition of the A␤ and by the intraneuronal generation of neurofibrillary tangles, neuropil threads, and abnormal material in dystrophic nerve cell processes of neuritic plaques. These changes are also found in a large number of nondemented elderly people post-mortem. One difference between demented AD patients and nondemented elderly with AD-related pathology is reflected by the distribution pattern of neurofibrillary tangles and A␤ deposits. The AD patients who manifest clinical symptoms of dementia present a pattern of widespread lesions occurring in many areas of the brain (all areas affected in nondemented patients plus in the brain stem and cerebellum) whereas nondemented elderly people showed neurofibrillary tangles and A␤ deposits restricted to distinct predilection sites (neocortex, allocortex, basal ganglia, and diencephalic nuclei) (Thal et al., 2004). Alterations of A␤ peptides concentration in plasma from AD patients (i.e. reduced A␤ 42 and an increased A␤ 40/A␤ 42 ratio) are common findings in recent studies, and this alteration was also found in patients suffering from MDD (Kita et al., 2009; Qiu et al., 2007; Sun et al., 2007). The risk for dementia and for cognitive decline seems to be greater in patients with mood disorders than in the general population (Geerlings et al., 2008; Gualtieri and Johnson, 2008). In BD, the number of affective episodes (Geerlings et al., 2008; Kessing and Andersen, 2004) and the presence of psychotic symptoms (Kessing and Andersen, 2004; Robinson et al., 2006; Torres et al., 2007) have been implicated as additional risk factor. Another study on bipolar depressed patients, found a significant negative correlation between A␤ 42 plasma levels and the duration of the illness, whereas a positive correlation was detected between the A␤ 40/A␤ 42 ratio and the number of affective episodes (Piccinni et al., 2012). Direct cytotoxic effects of A␤, negative effects on monoaminergic transmission, and functional antagonism between brainderived neurotrophic factor (BDNF) and A␤, suggest the potential involvement of A␤ in the pathophysiology of BD and cellular aging. Studies suggest that A␤ may exhibit functional interference with BDNF actions, because BDNF stimulates glutamatergic transmission and long-term potentiation (LTP) (Korte et al., 1995; Levine et al., 1998; Lue et al., 1999) whereas A␤ inhibits these phenomena (Snyder et al., 2005). Furthermore, A␤ can block the phosphorylation of the transcription factor cAMP response element-binding (CREB) (Tong et al., 2001) and its nuclear translocation, inhibiting the synthesis of BDNF (Arancio and Chao, 2007; Arvanitis et al., 2007). The hypothesized increase in glutamatergic transmission during mood episodes (Kugaya and Sanacora, 2005; MachadoVieira et al., 2009; Yildiz-Yesiloglu and Ankerst, 2006) may play a role in the A␤-mediated neurotoxicity, explaining the relationship between cognitive decline and the severity of the clinical course of mood disorders, and the greater risk of developing dementia reported in mood disorders (Geerlings et al., 2008; Gualtieri and Johnson, 2008; Kessing and Andersen, 2004; Robinson et al., 2006; Torres et al., 2007). It has been suggested that some presentations may represent a prodromal manifestation of AD, or a subtype of amyloid-associate mood disorder characterized by cognitive impairment and risk of dementia (Sun et al., 2007). More generally, individuals who present with considerable Alzheimer’s pathology but who do not develop clinical dementia may be less susceptible to dementia due to greater “cognitive reserve” (i.e. greater

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resilience to neuropathological processes by virtue of greater neural substrate, higher premorbid IQ, extensive education, exercise, other lifestyle factors, etc.), which may be eroded by BD pathology resulting in greater susceptibility to dementia in the presence of the same neuropathological burden. 2.4. Changes at the cellular level 2.4.1. Immunosenescence Immunosenescence refers to the decline of immunological function that occurs with aging. During aging, sustained low-grade inflammatory activity gradually evolves and this is sometimes referred to as “inflammaging” (Franceschi et al., 2007). In this context, healthy aging and longevity are likely result not only from a lower propensity to mount inflammatory responses but also maintenance of efficient anti-inflammatory networks (Franceschi et al., 2007). During aging, regulatory processes may fail to counteract the inflammatory responses consequent to exposure to damaging agents or to the lifelong acquired antigenic burden. Intriguing data from a large multi-ethnic cohort study suggests that cumulative pathogen exposure, particularly viral pathogens such as cytomegalovirus (CMV) and other herpes virus, can lead to increased risks of vascular aging, and cognitive decline in laterlife (Elkind et al., 2010; Katan et al., 2013; Swardfager and Black, 2013). Further investigation is needed, but it is possible that these infections, overwhelm the diminishing capacity for immunoregulation/immunotolerace that occurs with age, resulting in increased tissue damage. In animal models, the inflammatory response to experimental infection resolves more slowly in aged mice than in adult mice, which is associated with prolonged depressive-like behavior in aged mice (Kelley et al., 2013). According to this perspective, one key to successful physical, psychological and cognitive aging is decreased inflammatory activity without compromising an effective acute response to new pathogens (Franceschi et al., 2007). The paradigm of inflammaging has been largely accepted to explain why age is an important risk factor for diseases such as type-2 diabetes, cardiovascular diseases and some types of cancer (Macaulay et al., 2013). In addition, inflammaging has been postulated as an explanation for some neurobiological characteristics of Alzheimer’s disease. Patients with Alzheimer’s disease show increased inflammatory activity compared to controls (Swardfager et al., 2010b) as do patients in the clinical mild cognitive impairment prodromal phase of the illness (Fuchs et al., 2013). There is evidence that IFN-␥ and other pro-inflammatory cytokines interact with processing and production of A␤ peptide, suggesting that the increased inflammatory activity that accompanies aging could precipitate, accelerate or exacerbate AD pathology (Giunta, 2008). Some treatments that counteract inflammaging have been proposed to prevent or treat AD, including celecoxib, naproxen, trifusal and indomethacin although limitations in trial design or uncertainty in these results limit their readiness for clinical application (de Jong et al., 2008; Gomez-Isla et al., 2008). There is a consistent body of evidence suggesting that BD is associated with a persistent and low intensity pro-inflammatory states, which are more intense during mood episodes, especially manic episodes, and less intense in depressive episodes (Brietzke et al., 2009b; Modabbernia et al., 2013). Even euthymia has been associated with detectable peripheral pro-inflammatory activity (Brietzke et al., 2009a). In the context of aging, blood cytokine concentrations have been correlated with immune-stimulated catabolism of tryptophan and tyrosine, necessary precursors in the synthesis of serotonin and dopamine, and this has been associated with affective and neurovegetative symptoms, respectively (Capuron et al., 2011). This mechanism may apply to BD patients earlier in life. For instance, the enzymes and final products of the kynurenine pathway, which catabolizes tryptophan, are increased

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in the cingulate cortex in BD (Miller et al., 2006, 2008). This has been associated with cognitive symptoms in mood disorders patients and proposed as a modifiable target for therapy (Wonodi and Schwarcz, 2010). BD patients exhibit other immunological alterations common in elderly people; for instance higher proportions of circulating CD8+ CD28− cells (do Prado et al., 2013; Wieck et al., 2013), and lower proportions of regulatory T cells (do Prado et al., 2013; Wieck et al., 2013) and increased cytomegalovirus (CMV) infection (Rizzo et al., 2013). CD8+ CD28− cells have lost the expression of the CD28 protein, which is necessary for their complete stimulation and clonal expansion. They have short telomeres, impaired cytotoxic function, and they are resistant to apoptosis (Derhovanessian et al., 2009; Weng et al., 2009). The proportion of CD8+ CD28− cells increases with aging and a high frequency of CD28− cells in the elderly correlates with a less effective response to influenza virus vaccination (Goronzy et al., 2001) and with a higher risk of mortality (Olsson et al., 2000; Wikby et al., 2002). The main cause for the expansion of these senescent cells is related to infectious burden, particularly CMV infection. After infection with CMV, the body is not able to promote virus clearance, leading to chronic albeit asymptomatic infection. The long course of the infection promotes chronic immunological stimulation of specific cells for CMV epitopes, and consequently restriction of the immunological repertoire (Almanzar et al., 2005; Ouyang et al., 2003). Intriguingly, this effect is less pronounced other chronic infections (Pawelec and Derhovanessian, 2011). The motive is until now not completely understood, but it is possible that CMV has a closer relation with the immunological system compared to other infections, since dendritic and endothelial cells function as viral reservoirs (Benedict et al., 2008; Bentz et al., 2006; Tabata et al., 2008). 2.4.2. Reduction in neurotrophins Impaired capacity for neuroplasticity has been proposed as a core-underlying feature of mood disorders, which may be related to both affective and cognitive symptoms as they affect the integrity of nodal brain structures and connectivity between them. Neuroplasticity can be impaired by pro-inflammatory cytokines (Das and Basu, 2008; Goshen et al., 2008), normal aging (Kuhn et al., 1996) and activation of the stress-response systems (Joca et al., 2007; Karten et al., 2005). On the other hand, physical activity (van Praag et al., 1999) and mood stabilizers such as lithium can promote neurogenesis (Chen et al., 2000). Many treatment benefits are thought to depend on the release of neurotrophic factors. Neurotrophins, notably BDNF, have been considered one of the most important mediators of synaptic plasticity and apoptosis control in mood disorders. Individuals with BD, when compared with healthy controls, have lower peripheral levels of BDNF in mania and in depressive episodes, as described by a systematic review, with a meta-regression analysis (Fernandes et al., 2011). In that study, BDNF levels in euthymia were unaltered, although they were influenced by age and length of illness. A separate study reported that BDNF levels were decreased in euthymic individuals, but only in the latter stages of illness (Kauer-Sant’Anna et al., 2009). Therefore, BDNF has been considered both a marker of clinical symptoms and a mechanism underlying neuroprogression (Berk, 2009; Berk et al., 2010). Interestingly, reduced BDNF levels have also been found in aging (Perovic et al., 2013). In non-demented elderly individuals, lower BDNF plasma levels have been correlated with white-matter atrophy (Driscoll et al., 2012). The age-related decline in BDNF is probably due to epigenetic changes. In one rodent study, hippocampal BDNF mRNA was lower in 12-month-old compared with 6 months old animals. In addition, there was a decrease in the expression of TrkB, the BDNF receptor mediating neuroprotection and structural plasticity, which was accompanied by lower levels

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of the two main downstream effector kinases, pAkt and protein kinase C (Perovic et al., 2013). Recently, a post-mortem study showed an age-related decrease in BDNF transcripts in amygdala of both healthy and MDD individuals as well as in BDNF-dependent gene expression. Interestingly, most genes that are age-dependent in control subjects display greater age effects in MDD subjects (Douillard-Guilloux et al., 2013). A second neurotrophin likely to be of importance to mood disorders, and particularly in senescence processes, is insulin-like growth factor 1 (IGF-1). In mouse behavioral studies, experimental IGF-1 deficiency induces depressive-like symptoms (Mitschelen et al., 2011), and in an inflammatory depression model, IGF-1 reduced depression-like behavior (Park et al., 2011). Polymorphisms in the IGF-1 gene have been associated with BD, suggesting that genomic variants may increase susceptibility (Pereira et al., 2011). Insulin-like growth factor-1 (IGF-1) can increase neural stem cell proliferation in the dentate gyrus of the hippocampus and increase CA1 pyramidal neuron dendritic spine density (Glasper et al., 2010). IGF-1 activates anti-apoptotic signaling, protecting neurons against oxidative stress (Floratou et al., 2012; Wang et al., 2010). Moreover, a recent study found that BD patients who respond to lithium express greater amounts of IGF-1 (Squassina et al., 2013) compared to non-responders. The IGF-1 system is a well-known regulator of aging; however, the relationship may be complex and the overall effect on lifespan may depend on the period of reduced IGF-1 signaling (Kenyon, 2010). In animals, the IGF-1 receptor determines lifespan based on a neuroendocrine mechanism during normal development that increases metabolic function and reduces longevity (Holzenberger et al., 2003). In humans, mutations that decrease the function of the IGF-1 receptor or of signaling molecules downstream of the IGF-1 receptor are associated with longevity (Kenyon, 2010). However, plasma IGF-1 concentrations decline with age and they are negatively associated with cardiometabolic risk factors such as BMI, insulin resistance and blood pressure, suggesting that concentrations of IGF-1 may be a marker of metabolic disease rendering patients with BD more susceptible to neural insult and impaired resilience (Sesti et al., 2005). In later-life and in mood disorders, increases in oxidative stress, apoptosis, inflammation, and declining endothelial function may be ameliorated by IGF-1 (Higashi et al., 2012). Further investigation into the relationships between BD, aging and the IGF-1 system are warranted.

2.4.3. Short telomeres In humans and other animals, cellular senescence has been attributed mainly to the shortening of telomeres. Telomeres are specialized structures present at the end of chromosomes composed by DNA tandem repeats of (TTAGGG/CCCTAA)n ranging 5–15 kbp (Aubert and Lansdorp, 2008) and proteins such as TRFs, POT, TIN2, which stabilize the region (Amiard et al., 2007; Teixeira et al., 2004). Telomeres are believed to have evolved to “cap” chromosomal termini and prevent end-to-end recombination and thus serve a critical role in the maintenance of chromosomal integrity (Blackburn, 2001; Blackburn et al., 2000; Simon et al., 2006). Since telomerase levels are insufficient in normal human cells, in each cell division telomeres get shorter due to the “end replication problem”. When telomeres become too short, the cell ceases to proliferate and enters a state known as “replicative senescence”. Thus, metered loss of telomeres can serve as a cellular “mitotic clock” that ultimately limits the number of cell divisions and cellular life span. For instance, telomere length declines in stem cells, affecting their functionality and capability to generate new cells (Vaziri et al., 1994). Interestingly, shorter telomeres have been associated with higher risk of mortality due to cardiovascular and infection-related diseases (Cawthon et al., 2003). Although the replicative problem

play a role in telomere shortening, other mechanisms are involved like oxidative stress (von Zglinicki, 2000). A preliminary study conducted by Simon and collaborators found reduction of telomere length from peripheral leukocytes in individuals with mood disorders (MDD and BD) compared with healthy controls (Simon et al., 2006). Hartman et al. also found shorter mean telomere length in leukocytes of individuals with MDD compared to healthy controls, although the duration of illness and depression severity were not associated with telomere length (Hartmann et al., 2010). On the other hand, the number of previous depressive episodes was an important determinant of telomere shortening in another study (Wolkowitz et al., 2011). In addition, pre-treatment telomerase activity was significantly elevated in depressed individuals compared with healthy controls and telomerase activity was correlated with depression severity and predicticting response to antidepressant treatment (Wolkowitz et al., 2012). Telomere shortening is less investigated in BD than in MDD. In a group of individuals with BD type 2, short telomeres were more common among the affected group that among healthy control subjects (15.04% vs. 13.48%; p = 0.04). Mean telomere length in the patient group was 552 base pairs (bp) shorter than in the control group; however, the difference did not reach statistical significance (Elvsashagen et al., 2011). The effect of lithium in telomere length of individuals with BD was also investigated. Lithium-treated BD patients had 35% longer telomeres compared with healthy controls. In this study, telomere length correlated positively with lithium treatment duration of >30 months and was negatively associated with increasing number of depressive episodes. Thus, response to lithium in BD patients may also be associated with longer telomeres (Martinsson et al., 2013). Possible causes for shortening of telomeres have been investigated. One study assessing telomere length in the cerebellar gray matter of patients diagnosed with MDD, BD and schizophrenia found no difference in mean telomere length between the three groups and controls. Since mean telomere length has been reported to be a heritable quantitative trait, the authors also carried out genome-wide mapping of genetic factors for telomere length and no association survived correction of multiple comparisons for the number of SNPs studied. This suggests that genetic predisposition to shorter telomere length could be determined by multiple loci with small effect sizes (Zhang et al., 2010). Although a cause-effect relationship cannot be definitively established, stress and its impact in the organism have been postulated as an important factor. In subjects with MDD, telomere length was inversely correlated with oxidative stress and with inflammation in depressed individuals (Wolkowitz et al., 2011). In addition, stress is implicated as a crucial causal mechanism for mood disorders, as well as for aging. In one study of individuals with MDD, short telomere length was associated with Perceived Stress Questionnaire scores, and with a hypocortisolemic state, which was especially prevalent among patients with a high familial loading of affective disorders and high levels of C-reactive protein levels (Wikgren et al., 2012). A possible limitation of current research investigating telomeres in mood disorders is the possibility of tissue-specific changes. It is possible that premature senescence may occur particularly in rapidly dividing tissues such as leukocytes, sparing others such as the cerebellar gray matter, as suggested by Zhang and collaborators. Analyses that include other brain regions, particularly the subgranular zone of the dentate gyrus or the subventrical zone where neurogenesis continues into adulthood may be more appropriate. Additionally, analyses that seek to identify correlations between other peripheral senescence-related biomarkers with telomere length and clinical symptoms or staging in BD are also warranted.

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Fig. 2. The relation between Allostatic Load (AL) and Accelerated Aging (AA) hypotheses. Both hypotheses are complementary, the higher the allostatic load experienced by BD patients, the higher will the demand of mechanisms to recover homeostasis. This leads to an exhaustion of the entire system and promotes the accelerated aging. The AA paradigm expands the AL hypothesis to its long term consequences, but also offers new insights into the etiopathology of BD, putting in perspective some of the current knowledge and indicating new areas for further research. AA hypothesis also opens the field on thinking BD as not just a neuroprogressive, but a somatoprogressive disorder.

3. Implications for research directed to clinical care Bipolar disorder is a complex disease, accumulating evidence points to the involvement of a myriad of pathophysiological pathways that are dynamic and interact with each other and with the environment. Notwithstanding these foraging observations, a unitary disease model is still unavailable, necessitating further advancement of our understanding of this multifaceted mental disorder, and the development and refinement of comprehensive theoretical frameworks. One integrative hypothesis for neuroprogression in BD is the Allostatic Load (AL) which says that BD patients are under stressful conditions (cyclic mood episodes, drug addiction and other comorbidities) and struggle to restore homeostasis by allostatic mechanisms. In the same way, aging can be thought as a loss in the capability to reattain homeostasis (O’Neill, 1997). In this concept, the AA and AL hypotheses are complementary (Fig. 2), the burden of BD promotes exhaustion of allostatic mechanisms that promote homeostasis. The AA paradigm expands the AL hypothesis to its long term consequences, but also offer new insights into the etiopathology of BD, putting in perspective some of the current knowledge and indicating new areas for further research. AA hypothesis also opens the field on thinking BD as not just a neuroprogressive, but a somatoprogressive disorder. Although the most explored models for progression of BD are related to stress, it is intuitive that, even organisms that are not submitted to chronic stress will age. In addition to environmental agents, there is also a strong genetic component in aging. One interesting insight about genetic component in aging can be obtained from diseases marked by a highly accelerated aging, such as Hutchinson-Gilford Progeria (HGP) and Werner syndrome (WS) (Hegele, 2003; Heyn et al., 2013). As naturally aged individuals, HGP and WS patients present hair graying, skin thinning, atherosclerosis and osteopenia. Genetically, the disease could be traced back to mutations in lamin A (LMNA) (De Sandre-Giovannoli et al., 2003; Eriksson et al., 2003; Worman and Bonne, 2007) and the Werner syndrome RecQ helicase like (WRN) (Yu et al., 1996) genes. Although similarities between these conditions and BD were never explored, schizophrenia was conceptualized by some authors as a segmental Progeria, due to similarities in genetic and epigenetic control of CNS senescence between the disorders (Papanastasiou et al., 2011).

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From a clinical point of view, based on the evidence of the progressive nature of BD, some authors propose that the notion of clinical staging can be applied to BD (Kapczinski et al., 2009; Scott et al., 2013). The main benefits are allowing better prognosis and more personalized treatments. The use of biomarkers, including neurotrophins, inflammatory markers and oxidative stress markers have been proposed as auxiliary tools to refine the description of the stages (Kapczinski et al., 2009). In this sense, age-related features, such as the presence of medical comorbidities, cognitive impairment and shortened telomere length could be useful in the characterization of clinical stages. Also, investigation of the progression of these features along the course of the disease may allow early interventions aimed at better management and prognoses for patients. Finally, the recognition of aging processes as part of the BD puzzle leads to the possibility of treatments targeting specifically these pathways the so-called “anti-aging” strategies, including nutritional approaches and pharmacological and non-pharmacological interventions 3.1. Pharmacological strategies 3.1.1. Current pharmacology modulating aging related mechanisms The mechanisms of action of drugs currently used to treat BD is not completely understood, but there are some data showing their capability to modulate pathways related to aging. Patients in treatment with lithium show reduced neuronal loss and higher level of N-acetyl-aspartate (NAA) (marker of neuronal viability) (Bearden et al., 2007; Moore et al., 2000), suggesting a neuroprotectional effect by lithium which is already known to be partially mediated by several mechanisms, its capability to reduce glutamate-induced excitotoxicity by NMDA receptors (Hashimoto et al., 2002), direct and indirect inhibittion of the pro-apoptotic protein Glycogen synthase kinase 3 (GSK-3) (Chiu and Chuang, 2011; Stambolic et al., 1996), induction the antiapoptotic protein B-cell lymphoma 2 (Bcl2) (Chen and Chuang, 1999) and induction of the growth factors BDNF (Fukumoto et al., 2001) and vascular endothelial growth factor (VEGF) (Guo et al., 2009). Over the last years, GSK-3 was also identified as a regulator of many components of the immune system. GSK-3 plays an important role in the signal transmission to promote production of the pro-inflammatory cytokines IL-6, IL-1␤, IL-12p40, IFN␥ and TNF-␣ and inhibition of the anti-inflammatory cytokine IL-10 and IL1-RA (Beurel et al., 2010). The inhibition of GSK-3 by lithium and its consequent impact in the immune system may be one of the therapeutic mechanisms of lithium. Recently, the recognition that BD patients that were lithium intakers had longer telomeres raised the question by which means lithium could promote telomere extension. It seems to be also related to the inhibition of GSK-3 and consequently promoting the transcription hTERT the catalytic subunit bearing the enzymatic activity of telomerase (Martinsson et al., 2013). Lithium also seems to plays a role in the reduction of oxidative stress, since lithium treated patients present lower peripheral levels of oxidative stress makers like TBARS, SOD and CAT compared to unmedicated patients (Machado-Vieira et al., 2007). Also, lithium pré-treatment was able to protect human neuroblastoma (SH-SY5Y) cell line from rotenone and H2 O2 -induced cytotoxicity (Lai et al., 2006). The mechanism by which the medication mediates oxidative protection is not yet completely understood, but it is partly due to induction of antioxidant proteins like CAT and SOD, and interaction with GSK-3 and Bcl-2 (Lai et al., 2006). Valproic acid (VPA) also inhibits GSK-3 activity, although it is now clear yet if it shares the same direct effect as lithium or other mechanism are involved (Chen et al., 1999; Rosenberg,

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2007). VPA also impacts in the immunological system promoting anti-inflammatory effects in different models as ischemia and experimental auto-immune neuritis reducing pro-inflammatory cytokines IFN-␥, TNF-␣, IL-1, IL-6 and IL-17, and also elevating levels of Treg cell (Zhang et al., 2008; Zhang et al., 2012). Mechanisms by which VPA promotes the anti-inflammatory effect needs to be clarified, but it seems to be partly mediated by inhibition of GSK3 and histone deacetylase inhibition (Beurel et al., 2010; Grabiec et al., 2011). The relation between GSK-3 inhibition by VPA and induction of hTERT transcription still needs to be investigated. VPA and atypical antipsychotics also seems to promote effect on cell survival by elevating levels BDNF and fibroblast growth factor 1 (FGF1)(Bai et al., 2003; Kao et al., 2013; Yasuda et al., 2009) and upregulating Bcl-2 (Bai et al., 2004).

3.1.2. Sirtuins as possible new target The sirtuins are a family of ribosyltransferase or deacylase enzymes that influence a plethora of processes involved in aging, including apoptosis, DNA repair, the inflammatory response and resistance to stress. The mammalian sirtuin homologues, SIRTs 1–7, are also involved in energy metabolism, with a particular role in metabolic efficiency and maintenance of function during low energy situations. The sirtuin genes can be upregulated by calorie restriction, with longevity promoting effects (Kanfi et al., 2012). For example, SIRT6 is expressed in the nucleus where it is involved in DNA repair, regulating cell metabolism, and regulating the secretion of TNF. In male mice, over-expression of Sirt6 increases lifespan and alters IGF-1 signaling, consistent with a role of IGF-1 in determining longevity (Kanfi et al., 2012). On the other hand, SIRT6 deficiency leads to enhanced NF-␬B dependent signaling, apoptosis and accelerated cell senescence (Kawahara et al., 2009). Recently, decreased expression of SIRT1, SIRT2 and SIRT6 was found in white blood cells collected from BD patients in states of acute depression compared to controls. In contrast, SIRT mRNA levels in euthymic BD patients were different from those of controls (Abe et al., 2011), suggesting that sirtuin genes may be deficiently expressed in BD, and that sirtuin expression may be a state marker of illness. Previously, differences have been described in the response of white blood cells to glucose deprivation between BD subjects and controls – whereas healthy controls showed upregulated transcripts related to mitochondrial energy metabolism, these transcripts were down-regulated in BD (Naydenov et al., 2007). Sirtuin expression would seem to be a compensatory protective measure, and this resilience pathway may be defective in BD. These observations suggest the possibility for novel pharmacological interventions. For instance, in animal models, resveratrol can activate SIRT1, prolonging the lifespan in obese animals and reversing age-related cardiovascular dysfunction (Alcain and Villalba, 2009; Barger et al., 2008). More potent pharmacological activators of SIRT1 are under development. These agents can more dramatically increase mitochondrial activity (Alcain and Villalba, 2009). Interestingly, sirtuin activity is inhibited by nictotinamide, a final product of the kynurenine pathway and an important component of NAD and NADPH involved in the mitochondrial electron transport chain. It has been suggested that blocking nicotinamide binding to its cognate receptors could enhance sirtuin activity and prevent tissue damage caused by age-related degenerative diseases such as diabetes, Alzheimers and atherosclerosis (David Adams and Lori, 2007; Milne et al., 2007). These pharmacological strategies might be useful to mitigate the cellular damage that occurs during depressive episodes, and prevent the associated neuroprogression.

3.2. Non-pharmacological strategies 3.2.1. Physical activity Physical activity and cardiopulmonary fitness are welldocumented neuroprotective strategies that can increase brain volumes (Colcombe et al., 2006; Colcombe et al., 2006) and preserve cognitive function later in life (Barnes et al., 2003) even in groups of patients with concomitant cardiovascular morbidity (Swardfager et al., 2010a) or clinical mild cognitive impairment (Baker et al., 2010). It has been suggested that these effects may be mediated, in part by augmentation of neurotrophin concentrations (e.g. BDNF and IGF-1) (Erickson et al., 2011; Llorens-Martin et al., 2010; Swardfager et al., 2011) but improvements in other aspects of physiological function may also ameliorate neurocognitive decline, including improvements in vascular endothelial function (Bank et al., 1998; Fuchsjager-Mayrl et al., 2002; Xiang et al., 2009). Vascular endothelial dysfunction is related to increased generation of oxidative species, which can irreversibly damage intracellular components of the cerebral neurovascular unit and compromise regulation of cerebral blood flow and thus brain function. Vascular endothelial cell senescence and changes in vascular endothelial function occur with aging, favoring pro-inflammatory and prooxidant processes that may contribute substantially to age-related neurological decline (Yildiz, 2007), particularly since these processes are exacerbated by age-related cognitive risk factors such as diabetes and hypertension. Physical activity is also known to increase telomerase activity both in human and animal models (Ludlow et al., 2012; Werner et al., 2008; Wolf et al., 2011). Telomerase has not yet been evaluated in BD, but there are reports of decreased activity in major depression and schizophrenia (Porton et al., 2008; Wolkowitz et al., 2012). These data suggest that BD may follow the same direction, and other mechanism by which patients could be benefited by exercise. The extant literature suggests that BD, and manic or hypomanic symptoms in particular, may be associated with premature increases in vascular endothelial dysfunction (Fiedorowicz et al., 2012; Rybakowski et al., 2006). Physical activity as a means to promote vascular endothelial health or telomere length in BD has not yet been assessed; however, poorer physical fitness can confer an increased risk of affective disorders including BD (Aberg et al., 2012) and exercise has been suggested as a strategy to improve cognition in BD (Ng et al., 2007). Prospective controlled studies are needed, and related mechanisms require further investigation (Kucyi et al., 2010).

4. Conclusions There is considerable overlap between neurobiological characteristics of BD and processes of both normal and pathological aging, which is evident in clinical, physiological, neurostructural, cellular, and molecular studies. The strengths of the AA integrative view of BD progression are that the hypothesis comprises and also expends the neuroprogression and allostatic load view, also expands the field of possible biological mechanisms involved in the pathophysiology of the disease. The AA hypothesis also creates a theoretical framework that encompasses not only neurological but also systemic alterations involved in the pathophysiology of BD. Although AA hypothesis integrates the current knowledge regarding progression of BD, it does not provide direct answers about the mechanisms that generate mood cyclicity. Yet, in our concept, mood cyclicity generates stressful conditions that demand the action of biological mechanisms to reattain homeostasis, the chronicity of this conditions could promote accelerated aging (Fig. 2). Other limitation is that albeit there are compelling

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data supporting AA hypothesis, most studies use cross-sectional methodology which are more susceptible to bias. The present work, creates the basis for new prospective studies focusing on AA framework and consequently bring more understanding about BD etiology and physiology. Although the scope of the present work made an in deep analysis of AA in BD, there are some data suggesting that this concept could be extrapolated for other psychiatric disorders like major depression, schizophrenia and posttraumatic stress disorder (Simon et al., 2006; Wolkowitz et al., 2010). Finally, the exploration of physiological processes involved in aging provides useful insights into the biology of BD, and new potential to suggest new avenues of treatment. Notwithstanding, the associated of controversy and practical challenges, anti-aging interventions could be beneficial in subpopulations of BD warranting further investigation. Conflict of interest statement The authors declare that they have no competing financial interests. Acknowledgements The authors acknowledge support by fellowships from Coordination of Improvement of Higher Education Personnel (CAPES), National Counsel of Technological and Scientific Development (CNPq) and São Paulo Research Foundation (Fapesp). Dr. Swardfager acknowledges support by fellowships from the Heart & Stroke Foundation Centre for Stroke Recovery and the Toronto Rehabilitation Institute. References Abe, N., Uchida, S., Otsuki, K., Hobara, T., Yamagata, H., Higuchi, F., Shibata, T., Watanabe, Y., 2011. Altered sirtuin deacetylase gene expression in patients with a mood disorder. J. Psychiatr. Res. 45, 1106–1112. Aberg, M.A., Waern, M., Nyberg, J., Pedersen, N.L., Bergh, Y., Aberg, N.D., Nilsson, M., Kuhn, H.G., Toren, K., 2012. Cardiovascular fitness in males at age 18 and risk of serious depression in adulthood: Swedish prospective population-based study. Br. J. Psychiatry 201, 352–359. Alcain, F.J., Villalba, J.M., 2009. Sirtuin activators. Expert Opin. Ther. Pat. 19, 403–414. Albert, S.M., Michaels, K., Padilla, M., Pelton, G., Bell, K., Marder, K., Stern, Y., Devanand, D.P., 1999. Functional significance of mild cognitive impairment in elderly patients without a dementia diagnosis. Am. J. Geriatr. Psychiatry 7, 213–220. Allen, J.S., Bruss, J., Brown, C.K., Damasio, H., 2005. Normal neuroanatomical variation due to age: the major lobes and a parcellation of the temporal region. Neurobiol. Aging 26, 1245–1260, discussion 1279-1282. Almanzar, G., Schwaiger, S., Jenewein, B., Keller, M., Herndler-Brandstetter, D., Wurzner, R., Schonitzer, D., Grubeck-Loebenstein, B., 2005. Long-term cytomegalovirus infection leads to significant changes in the composition of the CD8+ T-cell repertoire, which may be the basis for an imbalance in the cytokine production profile in elderly persons. J. Virol. 79, 3675–3683. Amiard, S., Doudeau, M., Pinte, S., Poulet, A., Lenain, C., Faivre-Moskalenko, C., Angelov, D., Hug, N., Vindigni, A., Bouvet, P., Paoletti, J., Gilson, E., Giraud-Panis, M.J., 2007. A topological mechanism for TRF2-enhanced strand invasion. Nat. Struct. Mol. Biol. 14, 147–154. Anderson, I.M., Haddad, P.M., Scott, J., 2012. Bipolar disorder. BMJ 345, e8508. Andreazza, A.C., Kapczinski, F., Kauer-Sant’Anna, M., Walz, J.C., Bond, D.J., Goncalves, C.A., Young, L.T., Yatham, L.N., 2009. 3-Nitrotyrosine and glutathione antioxidant system in patients in the early and late stages of bipolar disorder. J. Psychiatry Neurosci. 34, 263–271. Aprahamian, I., Nunes, P.V., Forlenza, O.V., 2013. Cognitive impairment and dementia in late-life bipolar disorder. Curr. Opin. Psychiatry 26, 120–123. Arancio, O., Chao, M.V., 2007. Neurotrophins, synaptic plasticity and dementia. Curr. Opin. Neurobiol. 17, 325–330. Arvanitis, D.N., Ducatenzeiler, A., Ou, J.N., Grodstein, E., Andrews, S.D., Tendulkar, S.R., Ribeiro-da-Silva, A., Szyf, M., Cuello, A.C., 2007. High intracellular concentrations of amyloid-beta block nuclear translocation of phosphorylated CREB. J. Neurochem. 103, 216–228. Aubert, G., Lansdorp, P.M., 2008. Telomeres and aging. Physiol. Rev. 88, 557–579. Bai, O., Chlan-Fourney, J., Bowen, R., Keegan, D., Li, X.M., 2003. Expression of brainderived neurotrophic factor mRNA in rat hippocampus after treatment with antipsychotic drugs. J. Neurosci. Res. 71, 127–131.

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