Ageing and inflammation - A central role for mitochondria in brain health and disease.

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Contents lists available at ScienceDirect

Ageing Research Reviews journal homepage: www.elsevier.com/locate/arr

Review

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Ageing and inflammation – A central role for mitochondria in brain health and disease

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Antonio Currais ∗ The Salk Institute for Biological Studies, 10010 N. Torrey Pines Rd, La Jolla, CA 92037, USA

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a r t i c l e

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Article history: Received 9 November 2014 Received in revised form 29 January 2015 Accepted 2 February 2015 Available online xxx

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Keywords: Differentiation Inflammation Metabolism Neurodegenerative diseases

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Contents

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To develop successful therapies that prevent or treat neurodegenerative diseases requires an understanding of the upstream events. Ageing is by far the greatest risk factor for most of these diseases, and to clarify their causes will require an understanding of the process of ageing itself. Starting with the question Why do we age as individual organisms, but the line of pluripotent embryonic stem cells and germ cells carried by individuals and transmitted to descendants is immortal? This review discusses how the process of cellular differentiation leads to the accumulation of biological imperfections with ageing, and how these imperfections may be the cause of chronic inflammatory responses to stress that undermine cellular function. Both differentiation and inflammation involve drastic metabolic changes associated with alterations in mitochondrial dynamics that shift the balance between aerobic glycolysis and oxidative phosphorylation. With ageing, mitochondrial dysfunction can be both the cause and consequence of inflammatory processes and elicit metabolic adaptations that might be either protective or become progressively detrimental. It is argued here that an understanding of the relationship between metabolism, differentiation and inflammation is essential to understand the pathological mechanisms governing brain health and disease during ageing. © 2015 Published by Elsevier B.V.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Differentiation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Acquiring identity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Differentiation and ageing, the price to pay for identity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Inflammation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. A response to stress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Functio laesa – lost identity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1. Metabolically programming identity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2. Metabolic shifts and the homeostasis of the organism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The brain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1. Bioenergetics of identity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2. From cellular identity to inflammation – endpoint disease (focus on AD) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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∗ Tel.: +1 858 453 4100x1480; fax: +1 858 535 9062. E-mail address: [email protected] http://dx.doi.org/10.1016/j.arr.2015.02.001 1568-1637/© 2015 Published by Elsevier B.V.

Please cite this article in press as: Currais, A., Ageing and inflammation – A central role for mitochondria in brain health and disease. Ageing Res. Rev. (2015), http://dx.doi.org/10.1016/j.arr.2015.02.001

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1. Introduction

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Ageing is the greatest risk factor for the majority of neurodegenerative diseases (Lin and Beal, 2006). Given the demographic challenge that ageing currently poses to societies and the lack of therapies that prevent or treat age-associated brain degeneration, neurodegenerative diseases are becoming the epicentre of concern for national health care systems. The need to develop successful therapies that tackle these diseases is turning the attention of scientists to the upstream events that cause the pathology. However, to identify those events requires an understanding of the process of ageing itself. This review will discuss some of the current ideas on ageing and disease, starting with a single fundamental question: Why do we age as individual organisms, but the line of pluripotent embryonic stem cells and germ cells carried by individuals and transmitted to descendants is immortal? In other words, human embryonic stem cell and/or germ cell lines must possess certain characteristics that maintain immortality and protect themselves from ageing so that our species is propagated and thus perpetuated. Somehow, for most cells in complex multicellular organisms, these characteristics change or are lost when the process of cellular differentiation takes place. Evolutionarily, the acquisition of mitochondria played a key energetic role in the establishment of biological complexity, expanding life from unicellular to multicellular (Lane and Martin, 2010). In fact, mitochondria are determinant to cellular differentiation by mediating numerous aspects of metabolism (Agathocleous and Harris, 2013; Folmes et al., 2012; Ito and Suda, 2014; Xu et al., 2013). Therefore, organismal complexity arises from the interaction and cooperation of individual cells with diverse and specialized functions that rely upon crucial metabolic adaptations. With age, changes in mitochondrial homeostasis and the metabolic balance that is essential to support cell function can also lead to disease. Importantly, it is becoming increasingly appreciated that inflammatory processes are associated with alterations in mitochondrial function and cellular metabolism, and are heterogeneous with respect to the cell types and molecular mediators that are involved, constituting a spectrum of responses that go beyond infection to include responses to tissue stress or malfunction (Chovatiya and Medzhitov, 2014; Medzhitov, 2008; Okin and Medzhitov, 2012). Chronic, low-grade inflammation positively correlates with age and is associated with most degenerative diseases of the elderly (Chung et al., 2009; Franceschi et al., 2007; Howcroft et al., 2013; Pawelec et al., 2014). In addition, strong inflammatory responses are a common denominator of all major diseases in humans, including diabetes, cardiovascular disease, neurodegenerative disease and cancer (Medzhitov, 2010; Okin and Medzhitov, 2012). For these reasons, addressing the processes of cellular differentiation and inflammation in the context of ageing may provide significant insight into age-associated disease. This review will discuss how these two processes – differentiation and inflammation – are intimately related to determine heath or disease, with mitochondria playing a central role (Fig. 1). It will be argued that (1) metabolism is the core language that cells use to process the different intracellular and extracellular signals; (2) differentiation is an interpretation of that language, an acquisition of specialized functions towards complexity; and (3) inflammation is a reaction to stress that alters metabolism, meant for adaptation and recovery from adversity, but that, if continued or exacerbated, can lead to disease by compromising cell function. This review will first address the implications of differentiation, inflammation and metabolism for cellular function in the context of ageing, and later examine the practical interpretation of this conceptual interplay in the specific context of the brain.

Fig. 1. The relationship between metabolism, differentiation and inflammation determines health and disease during ageing. When differentiating, cells acquire identity (specialized functions). The transition from pluripotent stem cells to differentiated somatic cells is characterized by a metabolic shift from glycolysis towards an increase in oxidative phosphorylation (OXPHOS). This shift is accompanied by changes in mitochondrial morphology and composition (mitochondrial maturation), to ensure an adequate supply of energy necessary to support specialized functions. With differentiation, cells also commit themselves to accumulate biological imperfections with ageing. As a response to the stress caused by the accumulation of these imperfections, cells can mount inflammatory responses that affect mitochondrial function. With age-associated inflammation, OXPHOS is reduced and cells may increase aerobic glycolysis. This metabolic response can, in part, confer protection but will become detrimental to cell function if persistent and uncontrolled.

2. Differentiation

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2.1. Acquiring identity

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While shifting from stemness to differentiation, cells lose their immortality status in order to gain identity, where identity is defined as the acquisition of specialized functions that altogether sustain the complexity of the organism. The processes that mediate the amplification of a single fertilized cell into the maturity of a complex multicellular organism are complex and require restricted programmes meant to ensure both fidelity and functionality. Every time a cell divides, new components are synthesized and the whole physical structure is re-organized. This can pose a challenge to function and cellular interactions, and the dynamics of cellular division could thus conflict with that of differentiation. To slow down and halt proliferation may have allowed cells to integrate specific functions and to establish complex interactions with each other, building upon complexity. As such, most of the cells of the human body are in a functional non-proliferative G0 phase (Alberts et al., 2007). The reversibility of this state varies with different cell types. For instance, while neurons are terminally differentiated, many other cell types may only transiently withdraw from the cell cycle when necessary (Alberts et al., 2007). Complex multicellular organisms appear to have evolved in such a way that most of their cells do not have a descendent lineage, but instead, ensure that the success of the organism, as a species, is reflected in the transmission of its germ line. In this context, to understand why embryonic stem cells and/or germ cells may represent an immortal line as opposed to somatic cells is to understand how the process of ageing may be related to that of differentiation. Ageing in humans, as in other eukaryotes, might well be interpreted in light of the complexity acquired with the evolution of highly developed multicellular systems. Simple prokaryotic life does not form highly complex relationships, as found in eukaryotes.


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Why is that? The answer appears to rely on the mitochondria. Nick Lane and William Martin addressed this question from an energetic point of view (Lane and Martin, 2010). They proposed that the endosymbiosis that gave rise to mitochondria was the key for the development of complex multicellular life. Mitochondria and, in particular, the tight arrangement of their genome in relation to their bioenergetic membrane, offered an efficient extra source of energy. This was crucial for complexity and allowed for a 200,000fold rise in genome size compared to bacteria. The end result was an impressive new repertoire of potential functions for cells to explore that is sustained by mitochondrial power (Lane and Martin, 2010). Given the role of mitochondria in the evolution of complex multicellular organisms, one would expect a link between mitochondria and differentiation. As discussed further below, this is indeed the case, and mitochondrial respiration is upregulated in order to meet the energetic demands of differentiated cells (Agathocleous and Harris, 2013; Folmes et al., 2012; Ito and Suda, 2014; Xu et al., 2013). Thus, it should come as no surprise that mitochondria also play a central role in human disease when their function is impaired (Chan, 2006; Harris et al., 2012; HernandezAguilera et al., 2013; Lin and Beal, 2006; Navarro and Boveris, 2010; Vafai and Mootha, 2012; Wallace, 2005; Wallace and Fan, 2010). Therefore, with the energy supplied by mitochondria, cells could then expand not only a broader range of functions but also evolve high energy-consuming functions. In addition, given the proper structural stability, with a slow down/halt of cellular division, those functions could be made more consistent and permanent. The balance of energy and stability might be crucial to sustain cellular identity in complex multicellular organisms. However, as addressed next, the attainment of such identity might also be the commitment of cells and organisms to age.

2.2. Differentiation and ageing, the price to pay for identity In 2013, Carlos López-Otín et al. published The Hallmarks of Aging (Lopez-Otin et al., 2013), which enumerated nine common denominators of ageing: genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion and altered intercellular communication. This review on the major features of ageing purposely resembles the work of Douglas Hanahan and Robert Weinberg in The Hallmarks of Cancer first published in 2000 (Hanahan and Weinberg, 2000) and recently revisited in Hallmarks of Cancer: The Next Generation (Hanahan and Weinberg, 2011). As Carlos López-Otín and colleagues note, cancer is of surprising relevance to the study of ageing. However, although each of the identified hallmarks of ageing may contribute to the slow degeneration of the different functions in a given organism, they require a unifying context. In an attempt to provide a comprehensive perspective on ageing, Vadim Gladyshev presented the imperfectness-driven, nonrandom damage model of the origin of ageing (Gladyshev, 2013). In my opinion, Gladyshev’s model represents one of the current best models to understand ageing. This model might also explain the different hallmarks of ageing defined by Carlos López-Otín and colleagues because progressive, accumulating damage can lead to any of those changes. Gladyshev proposed two major ideas. The first is that cellular life involves the generation of damage as an inevitable consequence of metabolism, which by its nature is imperfect. The second is that while the more severe types of damage will provide a substrate for natural selection, low-abundance, slightly deleterious, milder forms of damage can be removed (by processes such as autophagy) or diluted when cells divide and renew. The nature of the balance between these two processes determines ageing, and this strategy has been operating since the beginning of life.

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Gladyshev’s ideas fit well with what is known about simpler organisms. Ageing in bacteria has been described, and asymmetrical division hypothesized to be an efficient way of improving the fitness in bacteria with a lower amount of damage (Gomez, 2010; Rang et al., 2011). This means that through the process of cell division bacteria dilute damage that could potentially become deleterious if cells did not divide. Of relevance to answer the question Why do we age as individual organisms, but the line of pluripotent embryonic stem cells and germ cells carried by individuals and transmitted to descendants is immortal? Gladyshev comments that immortality of organisms would be achieved if an equilibrium in cumulative damage and cell division is achieved. However, this cannot occur in post-mitotic, non-renewable cells and therefore they have a finite lifespan. Nondividing or slow-dividing cells would eventually reach the stage of damage overload and die (Gladyshev, 2013). Given that germ cells do not seem to exist in a condition of diapause or metabolic arrest (Rando and Chang, 2012) and ageing of both male (Paul and Robaire, 2013) and female (Tilly and Sinclair, 2013) germ lines has been documented, it could be that the key to avoiding the accumulation of age-related, deleterious damage lies in the process of embryogenesis. Indeed, the ageing clock is reset with every fertilization event (Rando and Chang, 2012). Otherwise, the germ line and eventually the members of the species would age with each generation and life on Earth would fail (Rando and Chang, 2012). It has been suggested that the process of rejuvenation that follows fertilization is associated with intense epigenetic reprogramming that confers dedifferentiation and pluripotency prior to any differentiation (Rando and Chang, 2012). As such, the reprogramming resets and clears epigenetic modifications linked to ageing that can be detrimental (Rando and Chang, 2012). A broader perspective, and an extension of Gladyshev’s ideas, could be that the rejuvenation that takes place during embryogenesis is precisely a consequence of the extraordinarily high rate of cellular proliferation, which eventually dilutes all ageing factors and likely the age-related epigenome. As discussed above, the progressive accumulation of biological imperfections that becomes evident when cells differentiate and age may thus generate stress and threaten cell function. Importantly, chronic low-grade inflammation positively correlates with age and is closely associated with all major degenerative diseases of the elderly (Chung et al., 2009; Franceschi et al., 2007; Howcroft et al., 2013; Pawelec et al., 2014). Next, inflammation will be addressed as a response to stress generated during ageing that expands beyond the context of infection and alters cell identity. As such, although only slightly addressed in the Hallmarks of Aging, inflammation should perhaps be considered a hallmark of ageing itself.

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The survival of cells depends on their ability to appropriately respond to exogenous or endogenous stresses. If a toxic stimulus is not removed, cells must adapt or they will die (Fulda et al., 2010). The cellular stress response (CSR) is an evolutionarily conserved mechanism of defense to an environmental stress that usually results in damage to lipids, proteins and DNA (Fulda et al., 2010; Kultz, 2005). There are forty-four proteins involved in key aspects of the CSR that are conserved in all organisms and are referred as the minimal stress proteome (Kultz, 2005). These proteins are induced/activated in response to deformation and/or damage of macromolecules and can be grouped into functional categories that include redox regulation, fatty acid/lipid metabolism, molecular


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chaperones, protein degradation, DNA damage sensing/repair and energy metabolism (Kultz, 2005). Most cellular stresses are intrinsically associated with the generation of ROS and reactive nitrogen species (RNS), which act as second messengers during CSR signalling (Kultz, 2005). Damage to the lipid membranes is associated with changes in membrane tension/stretch, permeability, lipid and protein arrangement, transmembrane electrochemical potential and the formation of lipid peroxides and adducts. Protein damage is mostly oxidative or structural (unfolding), often leading to aggregation, and it can be either repaired by enzymes or removed by proteolysis. DNA damage includes DNA double-strand breaks, DNA nucleotide adduct formation and base modification, DNA basepairing mismatches, and DNA single-strand breaks (Kultz, 2005). Some well-characterized examples of CSRs include the heat shock response, the unfolded protein response (UPR), the DNA damage response and the response to oxidative stress (Fulda et al., 2010; Muralidharan and Mandrekar, 2013). Although traditionally regarded as an immediate protective response to infection and injury, inflammation is also induced by tissue stress or malfunction (Chovatiya and Medzhitov, 2014; Medzhitov, 2008). An inflammatory response can be organized into four components: stress inducers (endogenous or exogenous), sensors (detect stress and induce production of pro-inflammatory mediators), mediators (act on target tissues), and effectors (the target cells and tissues) (Medzhitov, 2008). Exogenous inducers can be microbial (pathogen-associated molecular patterns (PAMPS) and virulence factors) or non-microbial (allergens, irritants, foreign bodies and toxic compounds). Endogenous inducers are produced when a tissue is injured or stressed. They include the release of molecules and breakdown products of the extracellular matrix as a consequence of tissue damage or malfunction (damage-associated molecular patterns (DAMPs)). Importantly, some other endogenous inducers of chronic inflammatory conditions include crystals of monosodium urate and calcium pyrophosphate dihydrate, advanced glycation end products (AGEs) and oxidized lipoproteins (Medzhitov, 2008). Inflammatory mediators can be produced by immune cells such as leukocytes (namely tissue-resident macrophages and mast cells), but also by non immune cells present in the tissue. They can be classified into seven groups: vasoactive amines (histamine and serotonin), vasoactive peptides (substance P, kinins, fibrinopeptide A, fibrinopeptide B, and fibrin degradation products), fragments of complement components (anaphylatoxins C3a, C4a, and C5a), lipid mediators (eicosanoids and platelet-activating factors), cytokines (TNF-␣, IL-1, IL-6, among many others), chemokines, and proteolytic enzymes (elastin, cathepsins, and matrix metalloproteinases) (Medzhitov, 2008). In essence, and similar to the CSRs, inflammation is an adaptive response meant to restore homeostasis (Medzhitov, 2010). When directly comparing important components of the different innate immune systems of different species, it is not possible to distinguish a common evolutionary origin from convergent evolution (Ausubel, 2005; Nurnberger et al., 2004). However, there are still striking similarities between the different innate immune systems and between those and some CSRs. These include the activation of mitogen-associated protein kinase (MAPK) cascades, changes in Ca2+ levels, the production of ROS and RNS, metabolic changes, activation of transcription factors and the inducible expression of immune effectors (Ausubel, 2005; Chovatiya and Medzhitov, 2014; Kultz, 2005; Nurnberger et al., 2004). Although it is not clear whether inflammation should be defined as a classical CSR itself (Medzhitov, 2010), Ruslan Medzhitov and colleagues have been addressing this question (Chovatiya and Medzhitov, 2014; Medzhitov, 2008, 2010; Okin and Medzhitov, 2012) and have proposed that perhaps both inflammation and stress responses could

be viewed as distinct but overlapping components in a spectrum of deviation states from homeostasis (Chovatiya and Medzhitov, 2014). These states would range from the stress response when homeostasis fails; to para-inflammation, a tissue-level response that has only some of the characteristics of inflammation; and finally inflammation at the end of the spectrum (Chovatiya and Medzhitov, 2014). Depending on the trigger, inflammation can have both a stress response and/or a defense response component. While the defense response component can be induced by agents such as pathogens, toxins and allergens, extreme deviations in cellular and tissue homeostasis will trigger the stress response component (Chovatiya and Medzhitov, 2014). Unlike in infection and injury, the specific inflammatory signals and respective molecular sensors involved during the response to tissue stress are poorly known (Medzhitov, 2008). It has been suggested that, due to the heterogeneity of responses and the cell populations involved, inflammation is not a cell-autonomous response but rather a non-cell-autonomous response at the level of tissues and organism (Medzhitov, 2010). However, even though innate immune cells present the strongest pro-inflammatory response, all cells, although to a lesser degree than immune cells, are responsive to stress and are active players in the inflammatory response. The extent to which non-immune cells are capable of mounting responses to stress that share mechanisms with a canonical inflammatory innate immune response is not only poorly understood but it has also been underappreciated. There is now evidence for activation of inflammatory pathways induced by disease-associated stress in a wide range of non-immune cells, including adipocytes (Berg and Scherer, 2005; Calabro et al., 2009), cardiomyocytes (Aoyagi and Matsui, 2011; Marchant et al., 2012), chondrocytes (Goldring and Otero, 2011; Houard et al., 2013), fibroblasts (Enzerink and Vaheri, 2011; Flavell et al., 2008), hepatocytes (He and Karin, 2011), neurons (Hanzel et al., 2014; Lafon et al., 2006; Rubio-Perez and Morillas-Ruiz, 2012), and vascular endothelial cells (Alom-Ruiz et al., 2008; Grammas, 2011). Understanding the exact nature of the inflammatory response in different cell types, its heterogeneity, as well as its physiological causes and consequences remains a challenge in the field, but it is paramount to understanding the cell-autonomous versus noncell-autonomous character of inflammation in cells, tissues and organisms during ageing and disease. As addressed below, these responses may be associated with detrimental changes in cell function. 3.2. Functio laesa – lost identity Inflammation occurs at the expense of normal tissue function – functio laesa – and this phenomenon underlies the pathological potential of the inflammatory response (Medzhitov, 2010; Okin and Medzhitov, 2012). The current interpretation suggests that although the initial inflammatory response is meant for protection, it may become detrimental if dysregulated and excessive in magnitude or duration (Okin and Medzhitov, 2012). There is now strong evidence for inflammation as a common denominator to all major diseases in humans – diabetes, cardiovascular disease, neurodegenerative disease and cancer (Medzhitov, 2010; Okin and Medzhitov, 2012). Importantly, the trigger of inflammation in these conditions does not appear to involve infection (Medzhitov, 2010). Given that age is also a risk factor for all of these diseases and that ageing is positively associated with chronic low-grade inflammation (Chung et al., 2009; Franceschi et al., 2007; Howcroft et al., 2013; Pawelec et al., 2014), one can argue that understanding inflammation in the context of ageing might shed light onto the mechanisms governing age-associated diseases. It is not clear what specifically causes the chronic low-grade inflammation that occurs during ageing. Ageing is associated with


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a reduced ability of both the innate and adaptative immune systems to mount efficient responses (Shaw et al., 2013; Solana et al., 2006). In both immune and non-immune cells, elevated age-associated inflammation could be partly explained by pattern recognition receptor (PRR) ligands, such as DAMPs, which increase with ageing (Shaw et al., 2013). Another important contributor to age-associated inflammation in non-immune cells may be cellular senescence that, in turn, can promote ageing via the senescence-associated secretory phenotype (SASP). The SASP consists of inflammatory cytokines, chemokines, matrix metalloproteinases and growth factors, which have a profound effect on cell function (Campisi and d’Adda di Fagagna, 2007; Coppe et al., 2010). These factors are angiogenic and they can stimulate the proliferation, migration and invasion of pre-malignant and malignant cells, and, importantly, they can alter the differentiation status of nearby cells (Coppe et al., 2010). The fact that the growth of senescent cells is arrested (typically in a G1 phase) is thought to represent a potent tumour-suppressor mechanism (Campisi and d’Adda di Fagagna, 2007; Coppe et al., 2010). However, senescent cells are metabolically active and, surprisingly, acquire resistance to apoptotic signals as well as to growth-factor deprivation and oxidative stress (Campisi and d’Adda di Fagagna, 2007). In turn, senescence-inducing stimuli include telomere attrition, DNA damage and chromatin disruption, expression of certain oncogenes, mitochondrial deterioration and oxidative stress (Campisi and d’Adda di Fagagna, 2007; Coppe et al., 2010). Therefore, both cellular senescence and inflammation do not necessarily require an extracellular stimulus. For example, the intracellular accumulation of non-degraded proteins, as happens with age, could not only decrease lifespan and increase oxidative stress (Simonsen et al., 2008) but also perhaps trigger inflammatory responses. The gradual increase in inflammation during ageing further puts at risk tissue function generating more stress and thereby creating a vicious cycle that eventually evolves into disease (Okin and Medzhitov, 2012). Importantly, mitochondria power cells to determine function and identity, which is disrupted by inflammation (Lopez-Armada et al., 2013). Not surprisingly, mitochondrial dysfunction is a trait of a vast array of human diseases and ageing (Chan, 2006; Lin and Beal, 2006; Vafai and Mootha, 2012; Wallace, 2005) and is associated with changes in the expression of nuclear genes involved in metabolism, growth, differentiation and apoptosis (Minocherhomji et al., 2012). This could take place in part because mitochondrial respiration and glycolysis define a bioenergetic balance of high-energy substrates that can regulate the epigenome, such as ATP, acetyl-CoA, s-adenosyl-l-methionine (SAM), NADH/NAD+ ratio, flavin adenine dinucleotide (FAD), and ␣ketoglutarate (Minocherhomji et al., 2012; Wallace and Fan, 2010). In this scenario, cellular function could be affected not only by impaired energy production caused by mitochondrial dysfunction but also associated epigenomic changes. Therefore, the progressive alterations in cell and tissue composition that take place with ageing may eventually converge into changes in physiological functions resulting in inflammatory responses. The extent to which these responses reflect a metabolic adaptive response to deal with age-associated stress remains to be clarified. As discussed next, profound metabolic changes take place during cellular differentiation that are essential to support cell identity, but that are also altered with inflammation.

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4.1. Metabolically programming identity

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glycolytic metabolism to enhanced oxidative phosphorylation, which is a requirement to acquire specialized functions (Agathocleous and Harris, 2013; Folmes et al., 2012; Ito and Suda, 2014; Xu et al., 2013). While pluripotent stem cells (PSCs) mainly use glycolysis for energy, in somatic cells most energy is derived from oxidative phosphorylation, concurrent with changes in mitochondrial morphology and composition (mitochondrial maturation), to fulfil their bioenergetic demands (Xu et al., 2013). The balance between the two types of metabolism affects the epigenome (Minocherhomji et al., 2012; Wallace and Fan, 2010) and could be partly responsible for epigenomic changes that take place during differentiation. Importantly, stimulation of glycolysis as well as inhibition of mitochondrial respiration promote pluripotency and take place right before induction of pluripotency during reprogramming. In turn, inhibition of glycolysis or activation of mitochondrial function abrogate stemness and reprogramming (Xu et al., 2013). During re-reprogramming, the metabolic shift resembles that of the Warburg effect in cancer cells (Agathocleous and Harris, 2013; Folmes et al., 2012; Ito and Suda, 2014; Xu et al., 2013) as it underlies the basic process of cellular division (Aguilar and Fajas, 2010). Up-regulation of glycolysis and secondary pathways, such as the pentose phosphate shunt, serves to meet the biosynthetic demands of proliferation (nucleotides, carbohydrates and lipids). Although the exact mechanisms responsible for this shift remain unclear, the coordinated interaction of several pathways such as PI3K/AKT/mTOR, Ras, Hedgehog, Myc, p53, AMPK and the sirtuins appear to be involved (Agathocleous and Harris, 2013). The crosstalk between metabolic and cell cycle regulators has only recently begun to be addressed (Aguilar and Fajas, 2010; Buchakjian and Kornbluth, 2010; Duan and Pagano, 2011). While most of the research has been conducted in cancer models, it has relevance to other systems. Both glucose and glutamine metabolism are synchronized with the cell cycle (Duan and Pagano, 2011). In addition, not only can metabolic intermediates control phases of the cell cycle, such as G1 and S, but cell cycle regulators involved in the G1 to S transition can also feedback to metabolic pathways increasing glycolysis and lowering oxidative phosphorylation in the mitochondria (Aguilar and Fajas, 2010; Buchakjian and Kornbluth, 2010). A possible direct role of mitochondria in the cell cycle has been less well investigated. A ROS rheostat has been proposed to directly modulate cell fate (Maryanovich and Gross, 2013) and ROS production can regulate the cell cycle in a number of different ways (Verbon et al., 2012). Mitochondria represent a potential major source of intracellular ROS which, together with other metabolites that regulate the epigenome (Minocherhomji et al., 2012; Wallace and Fan, 2010), could have a more important role in cell cycle regulation than is currently known. In light of what was discussed above, metabolism may be looked at as a language that determines cell survival in response to intraand extra-cellular cues while interacting with the specific molecular effectors that regulate the cell cycle and determine cellular function. The tight association between metabolism and differentiation strongly hints at the relevance of this relationship in balancing health and disease. Next, it will be addressed how inflammation is associated with metabolic alterations and mitochondrial dysfunction, and how these may impair the cellular identity. 4.2. Metabolic shifts and the homeostasis of the organism

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Expressing identity has an energetic cost. It is currently thought that the switch to differentiation is achieved via a shift from

There is evidence for a link between stress-related inflammation, metabolism and function that may be relevant to studying age-associated diseases. Not only is activation of inflammatory pathways required for efficient nuclear reprogramming during the induction of pluripotency (Lee et al., 2012), but activation of innate


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immune cells is also accompanied by metabolic reprogramming from oxidative respiration to aerobic glycolysis, which is necessary for the expression of pro-inflammatory cytokines and chemokines (Cloonan and Choi, 2012; Lartigue and Faustin, 2013; Wen et al., 2012). Other metabolic systems are also integrated with immune responses (Hotamisligil and Erbay, 2008). Importantly, mitochondria could play a central role in this metabolic shift. The numerous recent reviews on mitochondria and innate immunity (Arnoult et al., 2011; Cloonan and Choi, 2012; Galluzzi et al., 2012a; Green et al., 2011; Hernandez-Aguilera et al., 2013; Koshiba et al., 2011; Lartigue and Faustin, 2013; Lopez-Armada et al., 2013; Tschopp, 2011; West et al., 2011) reflect a growing awareness of the importance of this topic. Mitochondria are emerging as central regulators of the innate immune system in response to stresses or pathogens that often lead to chronic inflammation and disease. Not only do mitochondria play a role in modulating the inflammatory response in innate immune cells, their function is also the target of inflammatory mediators. Mitochondria can modulate innate immunity in response to viruses, bacteria or cellular stress/damage in a number of ways that often culminates in the activation of several transcription factors, such as NF-␬B, that control the expression of pro-inflammatory mediators. Examples include: the mitochondrial antiviral signalling protein (MAVS); mitochondrial fission/fusion/mitophagy dynamics; mitochondrial uncoupling; activation of the NLRP3 inflammasome; and generation of mitochondrial DAMPs (such as mitochondrial DNA). For some of these cases, the generation of ROS is both a trigger and a signalling entity; and pharmacological inhibition of ROS can attenuate the inflammatory response (Arnoult et al., 2011; Cloonan and Choi, 2012; Galluzzi et al., 2012a; Green et al., 2011; Hernandez-Aguilera et al., 2013; Koshiba et al., 2011; Lartigue and Faustin, 2013; Lopez-Armada et al., 2013; Tschopp, 2011; West et al., 2011). In addition, it has been shown that succinate, an intermediary of the mitochondrial tricarboxylic acid cycle (TCA), can work as a pro-inflammatory signal to induce IL-1␤ via HIF-1␣ (Wen et al., 2012). Succinate increases along with glycolysis and other TCA cycle intermediates during inflammation, and this could be a consequence of increased levels of ROS (Tannahill et al., 2013). In turn, the production of pro-inflammatory mediators, such as RNS and the cytokines TNF␣ and IL-1␤, impairs mitochondrial function by increasing ROS production and decreasing the activity of respiratory complexes, therefore decreasing ATP production and mitochondrial membrane potential (Lopez-Armada et al., 2013). Mitochondrial function is severely affected in age-associated diseases (Chan, 2006; Lin and Beal, 2006; Wallace, 2005). Given the central role of mitochondria in cellular differentiation, the association observed between inflammation and all major degenerative diseases of the elderly (Chung et al., 2009; Franceschi et al., 2007; Howcroft et al., 2013; Pawelec et al., 2014) could reflect, at least in part, important metabolic alterations linked to mitochondrial dysfunction that undermine cellular function. Historically, inflammation has been best studied in the context of infection. Its potential relevance for the homeostasis of any given cell is thus poorly understood, and the nature and extent to which associated metabolic alterations apply, in particular during ageing, remains unclear. A transient and controlled inflammatory response to stress could be beneficial to cells, tissues and organisms. However, a prolonged inflammatory response would put at risk mitochondrial function and could lead to changes that would eventually disrupt cellular function. The outcome could depend on the type of cell and its degree of differentiation. The following section will investigate the practical interpretation of the conceptual interplay described above in the specific context of cells and ageassociated diseases of the brain, with a focus on Alzheimer’s disease (AD).

5. The brain

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Metabolically, the human brain is a unique organ. It consumes about 20–25% of the body’s total energy, yet it represents only 2% of its mass (Belanger et al., 2011a; Brooks et al., 2007; Schubert, 2005). The brain comprises a multitude of cell types that use metabolic intermediates to communicate with each other. These include resident innate immune cells, the microglia, as well as other glial cells of support, such as astrocytes and oligodendrocytes, and highly differentiated cells, the neurons. The brain is also one of the organs with more restricted access and studies addressing human brain metabolism are scarce and limited to non-invasive imaging techniques. This is additionally complicated by the heterogeneity of the cells that, due to their diverse functions and degrees of differentiation, are characterized by different metabolic dynamics. Post-mitotic neurons are thought to be permanently arrested in a G0 phase characterized by a decrease in the gene expression and activity of proteins involved in the biosynthesis of products necessary for cell proliferation. For instance, high activity of the anaphase-promoting complex/cyclosome APC/C-Cdh1 complex and low levels of 6-phosphofructo-2-kinase/fructose-2,6biphosphatase-3 (PFKFB3) were hypothesized to maintain control over glycolytic flux and prevent cell cycle progression, while partly shifting the metabolic intermediate glucose 6-phosphate (G6P) to the pentose phosphate pathway (PPP) (Herrero-Mendez et al., 2009) (Fig. 2). The oxidative branch of the PPP produces a major reducing molecule in cells, NADPH, which is necessary to prevent the detrimental accumulation of mitochondrial-derived ROS (Schubert, 2005) and maintain the cellular redox status in neurons (Belanger et al., 2011a; Rodriguez-Rodriguez et al., 2013). To fulfil the energetic demands of neurotransmission, which account for the majority of the energy consumed in the brain (mostly at the level of ATP-dependent ion-pumps), neurons rely on mitochondria (Attwell and Laughlin, 2001; Harris et al., 2012). The main substrate for energy production in neurons may be one of the most debated questions in the field of brain bioenergetics. The debate arises from the fact that, due to their high energy requirements but also to their tightly regulated glycolysis, neurons must rely on a variety of substrates for their energy needs. Neurons have transporters for glucose (mostly GLUT3), but they can also use other energy substrates, such as ketone bodies, lactate, pyruvate, glutamate and glutamine (Belanger et al., 2011a; Schubert, 2005). One line of thought proposes that lactate reuptake and recycling back into the TCA cycle in neurons represents a primary source of fuel. Astrocytes, which are more glycolytic, would be the major suppliers of lactate, released when they take up glutamate produced during neurotransmission (the astrocyte-neuron lactate shuttle hypothesis) (Pellerin and Magistretti, 2012). This hypothesis has found opposition (Chih et al., 2001; Dienel, 2012a; Schubert, 2005) and it is still not clear what the main source of energy is for neurons. In mouse brain hippocampal slices, neurons and astrocytes are capable of using both glycolysis and oxidative phosphorylation during network activation (Ivanov et al., 2014). In addition, GLUT3 transporters are more abundant in synaptic membranes (Leino et al., 1997) and are increased at the cell surface during neuronal activation (Ferreira et al., 2011). In vivo, there is an increase in glucose uptake during brain activation (Bauernfeind et al., 2014; Dienel, 2012b; Gjedde and Marrett, 2001). Therefore, it is likely that glucose is a major fuel to support neuronal function under physiological conditions (Chih et al., 2001; Dienel, 2012a), in particular in providing substrate for the PPP to generate vital reducing potential (Schubert, 2005). This might have to take place under certain metabolic constraints, given that upregulation of PFKFB3 directly (Herrero-Mendez et al., 2009), or in conjunction with


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Fig. 2. Schematic representation of glucose metabolism, including the cytoplasmic glycolysis and pentose phosphate pathway (PPP) and the mitochondrial tricarboxylic acid (TCA) cycle and electron transport chain (ETC). Abbreviations: Glucose 6-P, glucose 6-phosphate; fructose 6-P, fructose 6-phosphate; fructose 1,6-BP, fructose 1,6-biphosphate; glyceraldehyde 3-P, glyceraldehyde 3-phosphate; 1,3-BPG, 1,3-biphosphoglycerate; 3-PG, 3-phosphoglycerate; 2-PG, 2-phosphoglycerate; PEP, phosphoenolpyruvate; dihydroxyacetone P, dihydroxyacetone phosphate; MG, methylglyoxal; AGEs, advanced glycation end products; PPP, pentose phosphate pathway; G6PDH, glucose-6-phosphate dehydrogenase; 6-PGL, 6-phosphogluconolactone; 6-PG, 6-phosphogluconate; 3K 6PG, 3-keto 6-phosphogluconate; ribulose 5-P, ribulose 5-phosphate; NADPH, nicotinamide adenine dinucleotide phosphate; TCA, tricarboxylic acid cycle; NADH, nicotinamide adenine dinucleotide; FADH2 , flavin adenine dinucleotide reduced; ETC, electron transport chain; ATP, adenosine triphosphate; APC/C, anaphase-promoting complex; PFKFB3, 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase-3; fructose 2,6-BP; fructose 2,6-biphosphate.

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glutamate excitotoxicity (Rodriguez-Rodriguez et al., 2012), shifts the metabolism of glucose from the PPP back to the glycolytic pathway, leading to oxidative stress and death. It is important to note that the substrates of the PPP may cycle back to glycolysis via fructose 6-phosphate and glyceraldehyde 3-phosphate (Fig. 2). Fructose 6-phosphate can re-enter the PPP via glucose 6-phosphate further contributing to the generation of reducing potential (Rodriguez-Rodriguez et al., 2013). However, glyceraldehyde 3-phosphate is downstream of the glycolytic step regulated by PFKFB3 and part of the glucose taken up by neurons and used in the PPP will eventually provide substrates to the TCA cycle. Therefore, it might not be correct to conclude that glycolysis is greatly reduced in neurons, but instead to understand how it is differentially regulated. Oligodendrocytic metabolism is the least well studied of all the brain cells and has only recently been gaining attention. Oligodendrocytes insulate axons for efficient neurotransmission but, just like astrocytes, they might also exchange metabolic intermediates with neurons (Amaral et al., 2013). Regarding microglia, they are tissue-resident macrophages and their function and metabolism have been mostly investigated in the context of disease, as addressed next. Overall, the data indicate that there is an intricate relationship between the cells of the brain that modulates function and relies on the specific metabolism of each cell type. The metabolic differences could reflect, in part, the importance of mitochondria for the overall function. As such, the delicate balance between glycolysis and respiration in cells might have a central role in ageing, inflammation and disease, as addressed below in the case of AD. 5.2. From cellular identity to inflammation – endpoint disease (focus on AD) Studies aimed at understanding how metabolism is affected in the brain during ageing and in disease have not produced a clear picture. The confusion arises from the evidence for a significant decrease in brain glucose uptake (hypometabolism) with age

and in cases of neurodegenerative disease (Cunnane et al., 2011; Heiss et al., 1991; Mielke et al., 1998; Mosconi et al., 2008). It is not clear why the hypometabolism develops, but it could be due to alterations in glucose transport through the blood brain barrier (BBB), glycolysis or mitochondrial function (Cunnane et al., 2011). Some authors have proposed that, to compensate for a diminished efficiency of energy production due to age-related metabolic dysregulation, mitochondrial oxidative phosphorylation is up-regulated – the “Inverse Warburg hypothesis” (Demetrius and Simon, 2012, 2013) (not to be confused with the “Reverse Warburg effect”). The inverse Warburg effect would explain the increased production of ROS with age, which becomes progressively detrimental, as well as the inverse correlation between the incidence of cancer and the incidence of AD (Demetrius and Simon, 2012, 2013). Not only is AD related to a reduced risk of cancer, the occurrence of cancer is associated with a reduced risk of AD (Demetrius and Simon, 2012, 2013; Driver et al., 2012; Musicco et al., 2013; Plun-Favreau et al., 2010). The following argues that this hypothesis is misleading because it attempts to explain observations that fit better with an aerobic glycolytic response to inflammatory stress associated with respiratory failure (Fig. 3). First, there is abundant evidence supporting a decline in mitochondrial function, including oxidative phosphorylation, with age and in neurodegenerative diseases, such as AD, Parkinson’s disease, Huntington’s disease and Amyotrophic lateral sclerosis (Boumezbeur et al., 2010; Boveris and Navarro, 2008; Chan, 2006; Harris et al., 2012; Lesnefsky and Hoppel, 2006; Lin and Beal, 2006; Navarro and Boveris, 2010; Sorbi et al., 1983; Wallace, 2005). This decline is associated with oxidative damage to the mitochondria and its DNA, which is particularly vulnerable to ROS (Chan, 2006; Lin and Beal, 2006; Wallace, 2005). An increase in ROS production does not exclusively imply an increase in respiration. ROS can also be generated by mitochondria as a consequence of inhibition/dysregulation of certain electron transport chain (ETC) complexes, as with age-associated mutations in mtDNA and inflammation.


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Fig. 3. The effects of inflammation on brain metabolism and health during ageing. The accumulation of biological imperfections in the ageing brain may trigger the activation of inflammatory responses in different cell types (endothelial cells, microglia, astrocytes, oligodendrocytes and neurons). Inflammation impairs mitochondrial function, further worsening the inflammatory response itself. As a consequence, cells may increase their aerobic glycolysis as well as the pentose phosphate pathway (PPP). The PPP generates NADPH, a reducing molecule fundamental to preventing the detrimental accumulation of ROS. Therefore, inflammation may have a protective component. The specific effect of the inflammatory response on cell function will depend on the type of cell and its degree of differentiation. An inflamed brain vascular endothelium, accompanied by a disrupted blood-brain barrier (BBB), and increased gliosis (microglia, astrocytes and oligodendrocytes) are commonly observed with ageing and in neurodegenerative diseases. In neurons, persistent activation of inflammation may lead to mitochondrial failure along with synaptic deterioration, which could partially explain the reduced rates of glucose uptake (mostly used for neurotransmission). In extreme cases, neurons may be “pushed” to re-enter the cell cycle, a characteristic of several neurodegenerative diseases, such as Alzheimer’s disease. Although aerobic glycolysis may increase in certain conditions and cell types with age-associated mitochondrial failure and confer protection, a continuous state of inflammation will create non-physiological conditions that eventually will lead to neuronal dysfunction and loss.

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Second, published data support the idea that several cell types in the brain may upregulate glucose uptake in response to stress and inflammation. This “activated” (or “reactive”) phenotype is commonly associated with the production and secretion of pro-inflammatory mediators, further exacerbating the vicious inflammatory cycle. Inflammation positively correlates with ageing (Chung et al., 2009; Franceschi et al., 2007; Howcroft et al., 2013; Pawelec et al., 2014) and is a hallmark of neurodegenerative diseases including AD (Glass et al., 2010; Howcroft et al., 2013; Wyss-Coray, 2006; Wyss-Coray and Rogers, 2012). Activation of astrocytes in these conditions is accompanied by an increase in the levels of glial fibrillary acidic protein (GFAP) and a display of pro-inflammatory SASP biomarkers (Salminen et al., 2011). The neurosupportive functions of astrocytes are compromised (Steele and Robinson, 2012), as well as the physical properties of their mitochondria and their respiratory capacity (Motori et al., 2013). Not only is astrocyte respiration disrupted but also glycolysis is upregulated in response to inflammatory stimuli (Almeida et al., 2001, 2004; Bal-Price and Brown, 2001; Belanger et al., 2011b; Brown et al., 1995; Motori et al., 2013). Microglia are the brainresident macrophages. As such, their activation could resemble that of a classical inflammatory response described in macrophages. They are more prone to produce an inflammatory response than any other cell type in the brain and may thus represent a central contributor to neurodegeneration (Perry et al., 2010). Microglia cell lines become pro-inflammatory and upregulate glycolysis in response to lipopolysaccharide (LPS) (Voloboueva et al., 2013), and primary microglia produce a pro-inflammatory phenotype when in high-glucose media (Graeber, 2010; Quan et al., 2011). Given that microglia also participate in important physiological functions, such as synaptic pruning/remodelling and in learning and memory

(Prinz and Priller, 2014), it will be critical to address how those relate to inflammatory and metabolic alterations. Finally, vascular inflammation impairs BBB homeostasis and may compromise brain function during ageing and predispose the individual to disease (Grammas, 2011; Marques et al., 2013). Activated brain endothelial cells in conditions of stress can express pro-inflammatory cytokines directly promoting inflammation (Alom-Ruiz et al., 2008) and affecting the integrity of the BBB (Grammas, 2011). Endothelial cells synthesize ATP primarily via glycolysis, even in the presence of blood oxygen (Harjes et al., 2012). The metabolic changes underlying endothelial activation have not yet been clarified. Endothelial cells can respond to LPS (Alom-Ruiz et al., 2008), which leads to an increase in glucose uptake (Spolarics and Spitzer, 1993) and is further enhanced in the presence of high levels of glucose (Liu et al., 2013). Third, several studies have reported metabolic abnormalities with ageing and in AD suggestive of increased glycolytic metabolism. Levels of lactate are elevated in the cerebrospinal fluid (CSF) of AD patients (Liguori et al., 2014; Redjems-Bennani et al., 1998) while levels of the TCA cycle intermediates succinate and fumarate are lower (Redjems-Bennani et al., 1998). High CSF levels of lactate are also found with ageing (Yesavage et al., 1982a,b) and prematurely ageing mtDNA mutator mice develop high levels of lactate associated with mitochondrial failure due to a metabolic shift from respiration to glycolysis (Ross et al., 2010). Although a few studies have reported decreased activities of some glycolytic enzymes with age and in AD (Iwangoff et al., 1980), the majority of studies are consistent with increases in the activity of these enzymes in the AD brain (Bigl et al., 1996, 1999; Schubert, 2005; Soucek et al., 2003). Importantly, it has been shown by positron emission tomography (PET) imaging that there is a spatial


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correlation between aerobic glycolysis and A␤ deposition in the brains of patients with sporadic AD (Vlassenko et al., 2010). This finding suggests that measuring aerobic glycolysis, as defined by the amount of glucose use apart from that entering oxidative phosphorylation, might provide more insight regarding metabolic changes than simply measuring glucose uptake, which is decreased in AD (Cunnane et al., 2011; Heiss et al., 1991; Mielke et al., 1998; Mosconi et al., 2008). Fourth, the notion of neuronal cell cycle re-entry as a mechanism of neurodegeneration has been established. Neuronal re-expression of cell cycle proteins and oncogenic signalling has been thoroughly documented in several neurodegenerative diseases, in particular AD (Bonda et al., 2010; Currais et al., 2009; Herrup and Yang, 2007). In culture, post-mitotic neurons activate the expression of cell cycle intermediates (only markers of G1, S and G2 phases have been documented) before dying when exposed to a diversity of stresses. Blocking the cell cycle prevents neuronal death. The underlying metabolic alterations as well as the expression of pro-inflammatory signals in such conditions have been poorly investigated. But given the tight relationship between glycolysis and the cell cycle, as discussed above, it could be that expression of cell cycle markers in neurons reflects an attempt to activate the glycolytic pathway. In vitro, A␤ induces differentiated neurons to express cell cycle markers (Malik et al., 2008; Seward et al., 2013) and it also increases glycolytic flux (Soucek et al., 2003). In addition, it has been shown that neurons can mount pro-inflammatory responses characterized by the expression and release of cytokines and chemokines (Lafon et al., 2006; RubioPerez and Morillas-Ruiz, 2012), which has been recently confirmed in a mouse model of AD (Hanzel et al., 2014). In silico modelling of neuronal metabolism in a condition of accumulation of intracellular aggregates and associated mitochondrial dysfunction, as occurs with ageing, predicts that neurons would progressively rely more on glycolysis (Vazquez, 2013). Even though in vivo the situation is certainly more complex, given that glycolysis is tightly regulated in order to maintain neurons in a non-proliferative state, the modelling might offer some insight. A shift to aerobic glycolysis, in particular with increases in the PPP, could be protective in neurons (Schubert, 2005) as long as it takes place under certain constraints, as explained above. Nerve cell lines selected for their resistance to A␤ toxicity display upregulated aerobic glycolysis that feeds the PPP and protects against oxidative stress-mediated insults (Behl et al., 1994; Cumming et al., 2007; Dargusch and Schubert, 2002; Newington et al., 2011; Sagara et al., 1996; Schubert, 2005; Soucek et al., 2003). What determines the plasticity of neurons to upregulate glucose uptake and the PPP while simultaneously avoiding the activation of cell death cascades remains to be clarified. How to reconcile the evidence presented above with the brain imaging studies reporting a decrease in glucose uptake with ageing and in AD? One possible scenario is that, given the progressive synaptic deterioration (and eventually neuronal cell loss) seen with ageing and in AD, less glucose would be required for neurotransmission. Since mitochondrial function and physical properties can affect cognition by directly shaping synaptic structure (Picard and McEwen, 2014; Sheng and Cai, 2012), fewer functional synapses caused by age-related mitochondrial dysfunction would require less energy. This is compatible with a scenario of inflammation with activated glycolytic astrocytes and microglia with ageing. Given that most of the energy in the brain is used in neurotransmission, glycolytic glia could easily be underestimated when looking at total brain activity and glucose uptake. Also, as mentioned above, measuring aerobic glycolysis instead of just glucose uptake might provide more valuable information. Another possibility is that a disruption of the BBB could compromise glucose transport into the brain thereby decreasing its availability. In addition, glucose uptake could be inhibited by a progressive imbalance in metabolic as well

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as inflammatory intermediates. For instance, high levels of lactate could have a negative feedback impact on glucose uptake (SoteloHitschfeld et al., 2012). The high lactate could be a result of high glycolytic glia and/or impaired neuronal respiration (less lactate substrate would be required to support mitochondrial respiration). Also, inflammation can trigger insulin resistance in diabetes (Glass and Olefsky, 2012) and it has been shown that the AD brain may develop insulin resistance (Craft, 2012; Talbot et al., 2012), which could contribute to a decrease in glucose demand and uptake. However, it would still be possible to detect an upregulation of glycolytic enzymatic activity in the brain tissue under stronger inflammatory conditions such as in AD, as has been detected in other tissues (Giebelstein et al., 2012; Simoneau and Kelley, 1997), in particular if it is part of an inflammatory response causative of insulin resistance. Importantly, it is not clear how the capacity of cells to mount stress-related inflammatory responses associated with activation of aerobic glycolysis is affected during ageing or continuous inflammation. It is possible that, as happens with the innate and adaptive immune systems, the potential to mount these responses also weakens with time, even with an overall increase in age-associated stress triggers. Regarding the inverse correlation between cancer and AD (Demetrius and Simon, 2013; Plun-Favreau et al., 2010), it has been proposed recently that the mechanistic explanation is linked to modulation of aerobic glycolysis, which is enhanced in cancers and may be compromised with ageing (Harris et al., 2014). In this context, one possible explanation could be that if patients that develop AD present a lower propensity to increase the PPP in order to generate reducing potential, they might be particularly susceptible to neuronal decay. However, given that cancers strongly rely on the PPP for anabolic demands during cell division and also to produce reducing potential (Patra and Hay, 2014), a lower PPP would reduce cancer development.

6. Discussion Over the past 20 years, cellular metabolism, the core engine for survival and identity, has been less well studied than other topics in the field of brain ageing and disease. This review attempts to revive interest in this fundamental property of life by discussing how diverse scientific concepts relate to each other via metabolism. The initial question was Why do we age as individual organisms, but the line of pluripotent embryonic stem cells and germ cells carried by individuals and transmitted to descendants is immortal? It was discussed that: • Ageing is the greatest risk factor for neurodegenerative diseases, and to identify their causes requires an understanding of the process of ageing itself. • Ageing might be best understood in the context of cellular differentiation. In order to exist as complex organisms, our cells differentiate. With differentiation, cells acquire identity but they also commit themselves to accumulate biological imperfections with ageing, which may cause stress and eventually disrupt their function. • Inflammation comprises a range of stress responses meant for protection that can affect mitochondrial function and become detrimental if uncontrolled. Age-associated stress triggers inflammatory responses that may vary according to the cell type but that shift the balance between aerobic glycolysis and oxidative phosphorylation, undermining cell identity. It is necessary to study the physiological causes and consequences of these responses in order to clarify the cell-autonomous versus


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non-cell-autonomous character of inflammation in cells, tissues and organisms. • It is argued here that an understanding of the relationship between metabolism, differentiation and inflammation is essential to understanding the pathological mechanisms governing brain health and disease during ageing (Fig. 1). Despite the significant progress in the specific fields that study these concepts, we still know very little, in particular how they relate to each other. For instance, how does one define “mitochondrial function”? Mitochondria have been well studied in the context of respiration, TCA cycle and ETC, but their function is more complex and includes activities such as heme biosynthesis, steroid metabolism, amino acid metabolism, assembly of Fe/S clusters, gluconeogenesis, fatty acid oxidation and ketogenesis, apoptosis, redox regulation and Ca2+ storage (Galluzzi et al., 2012b; Xu et al., 2013). How do these relate with cellular identity and disease? For instance, it has been suggested that, while respiration provides energy for neurotransmission, aerobic glycolysis supports the biosynthetic requirements of synapse formation and growth in the human brain (Goyal et al., 2014). Do mitochondria play a role in these processes? Importantly, how do tissues with more energy demands, such as brain, heart, muscle, renal and endocrine systems (Wallace and Fan, 2010) react to age and inflammation at the metabolic level? The signals that might involve a coordinated response centralized in the mitochondria during stress are unclear. For example, much has been described regarding the association between mitochondrial depolarization and cell death. However, some studies have also reported an increase in mitochondrial polarization during stress that is associated with an impaired ETC and an increase in ROS production due to a reverse flow of electrons (Heinen et al., 2007; Liu et al., 2002; Liu and Schubert, 2009). The ATP synthase can work in reverse to promote hyperpolarization in neurons with mitochondrial mutations (Abramov et al., 2010). Interestingly, expression of ATPase inhibitor factor 1 (IF1) is increased in iPSCs (Vazquez-Martin et al., 2013) as well as in human tumours, and could be responsible for the metabolic shift underlying the Warburg effect (SanchezCenizo et al., 2010). Overexpression of IF1 in cancer cells inhibits the activity of the mitochondrial ATP synthase, evoking a protective response associated with mitochondrial hyperpolarization and an increase in aerobic glycolysis (Formentini et al., 2012). Importantly, in vivo expression of IF1 in neurons inhibits the activity of oxidative phosphorylation while enhancing aerobic glycolysis, protecting the brain against quinolinic acid-induced excitotoxicity (Formentini et al., 2014). How does ATP synthase function and the ETC relate to the PPP? Since the PPP produces reducing potential essential to major anti-oxidants in the cell (catalase, glutathione and thiredoxin) (Ying, 2008), it would be important to address how the PPP might be linked with mitochondrial respiration. It has been assumed here that identity is related to the functions in the organism other than basic cell maintenance and division. In essence, functions that are dependent on mitochondria and involved in cellular specialization. Although it may simplify the interpretation of the data, it is to some extent a presumptuous assumption. For instance, in the case of activated macrophages, which possess predominantly a glycolytic metabolism, such a reaction upon an infection is their function. Nonetheless, the simple fact that all complex life still retain mitochondria suggests that mitochondria are vital and can play roles beyond oxidative phosphorylation as discussed above. It has been proposed that age-associated inflammation fits the antagonistic pleiotropy theory of ageing (beneficial for survival at early age but detrimental at old post-reproductive age) and that anti-inflammatory approaches could promote healthy ageing (Franceschi et al., 2007). However, as highlighted in this

review, it is important to first understand the potential effects of anti-inflammatory interventions. For example, while they could very likely be protective in cases of exacerbated inflammatory responses, as in neurodegenerative diseases, the situation might differ during healthy brain ageing. Clearly, if there is a protective component to the low-grade chronic inflammation associated with ageing, then it should not be inhibited. Thus, this requires an understanding of inflammation in all its complexity (Wyss-Coray, 2006), how it relates to stress, and how its different components function in the context of metabolism. For instance, an upregulation of the PPP with the generation of NADPH could reduce oxidative stress and protect cells. Therapies that promote aerobic glycolysis and the PPP could be beneficial for promoting redox homeostasis and thereby preserving cell function. It should be noted that the PPP also produces NADPH that is utilized by iNOS and NADPH oxidases during inflammation. A shift from NADPH utilization as an anti-oxidant factor to a pro-inflammatory factor could be detrimental. The concept of hormesis defines the process through which exposure to low levels of a stressor induces mechanisms involved in biological repair (Calabrese et al., 2007). Ageing, as well as dietary, behavioural and pharmacological interventions, can activate adaptive cellular stress responses that have beneficial effects on neuronal function and brain homeostasis (Stranahan and Mattson, 2012). Therefore, perhaps the potential protective components of the inflammatory response in different brain cell types should be investigated from the perspective of hormesis. Although mitochondrial respiration generates potentially toxic by-products, such as ROS, it should be mentioned that the current data remain inconclusive on whether oxidative stress is the primary cause of age-related decline in physiological functions, as presented by the free radical theory of ageing. Several lines of research in the last few years have questioned this theory, in particular evidence that ROS production can elicit survival responses during stress, associated with the activation of compensatory homeostatic responses (Lopez-Otin et al., 2013), in line with hormesis. The involvement of ROS in inflammatory processes could be such an example. In addition, recent articles have proposed that changes in the redox state of cells may underlie the decline in physiological function with age given by the disruption of redox-regulated signalling mechanisms – the redox stress hypothesis (Sohal and Orr, 2012). Glycolysis also has its own adverse side effects. This is the case with methylglyoxal (a derivative of the glycolytic intermediates glyceraldehyde 3-phosphate and dihydroxyacetone phosphate) that generates AGEs. AGEs accumulate with ageing and can promote inflammation via binding to the receptor for AGEs (RAGE) (Currais and Maher, 2013). Whether this increase could be a consequence of upregulated glycolysis and/or a decrease in removal by antioxidant systems is not clear. With time, the accumulation of age-associated imperfections in cells and tissues may trigger specific responses to stress. This review argues that inflammation, with a broad definition that extends to most cells of our organism and the heterogeneous nature of the molecules involved, might represent such a response. In particular, it discusses the available evidence that supports a central role for mitochondria in coordinating the inflammatory processes. With ageing, mitochondrial dysfunction can be both the cause and consequence of those processes and elicit metabolic shifts, such as an upregulation of aerobic glycolysis. It is essential to investigate the protective nature of these shifts at the cell and tissue levels, which can also become detrimental if mitochondrial function is not restored/preserved. Although the intriguing similarities between the metabolic alterations that occur during inflammation and those that operate during the process of cellular re-programming remain to be clarified, they may provide insight into the overlap of


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observations regarding the activation of some regulators of the cell cycle and ageing. This review, with a particular focus on the brain, proposes that understanding the relationship between metabolism, differentiation and inflammation is necessary to shed light onto the mechanisms governing health and disease during ageing. In summary, much more information is required to have a full understanding of the metabolic alterations that determine the fine line between health and disease. Ageing may well be a consequence of the imperfectness of life and the price we have to pay in order to exist. However, as the most restless minds continue to ask the question “Is it possible to uncouple the resetting of the ageing clock from the resetting of the differentiation programme?” (Rando and Chang, 2012), curiosity will steer the boat. Acknowledgements I would like to thank Drs. Pamela Maher, David Schubert, Salvador Soriano, Stephen Hedrick and Ruslan Medzhitov for help with the manuscript editing and valuable scientific discussions. I would also like to thank Jamie T. Simon for help with the preparation of the figures. References Abramov, A.Y., Smulders-Srinivasan, T.K., Kirby, D.M., Acin-Perez, R., Enriquez, J.A., Lightowlers, R.N., Duchen, M.R., Turnbull, D.M., 2010. Mechanism of neurodegeneration of neurons with mitochondrial DNA mutations. Brain 133, 797–807. Agathocleous, M., Harris, W.A., 2013. Metabolism in physiological cell proliferation and differentiation. Trends Cell Biol. 23, 484–492. Aguilar, V., Fajas, L., 2010. Cycling through metabolism. EMBO Mol. Med. 2, 338–348. Alberts, B., Johnson, A., Lewis, J., Raff, M., Roberts, K., Walter, P., 2007. Molecular Biology of the Cell, 5th ed. Garland Science, New York. Almeida, A., Almeida, J., Bolanos, J.P., Moncada, S., 2001. Different responses of astrocytes and neurons to nitric oxide: the role of glycolytically generated ATP in astrocyte protection. Proc. Natl. Acad. Sci. U. S. A. 98, 15294–15299. Almeida, A., Moncada, S., Bolanos, J.P., 2004. Nitric oxide switches on glycolysis through the AMP protein kinase and 6-phosphofructo-2-kinase pathway. Nat. Cell Biol. 6, 45–51. Alom-Ruiz, S.P., Anilkumar, N., Shah, A.M., 2008. Reactive oxygen species and endothelial activation. Antioxid. Redox Signal. 10, 1089–1100. Amaral, A.I., Meisingset, T.W., Kotter, M.R., Sonnewald, U., 2013. Metabolic aspects of neuron-oligodendrocyte–astrocyte interactions. Front. Endocrinol. (Lausanne) 4, 54. Aoyagi, T., Matsui, T., 2011. The cardiomyocyte as a source of cytokines in cardiac injury. J. Cell Sci. Therapy, 2012. Arnoult, D., Soares, F., Tattoli, I., Girardin, S.E., 2011. Mitochondria in innate immunity. EMBO Rep. 12, 901–910. Attwell, D., Laughlin, S.B., 2001. An energy budget for signaling in the grey matter of the brain. J. Cereb. Blood Flow Metab. 21, 1133–1145. Ausubel, F.M., 2005. Are innate immune signaling pathways in plants and animals conserved? Nat. Immunol. 6, 973–979. Bal-Price, A., Brown, G.C., 2001. Inflammatory neurodegeneration mediated by nitric oxide from activated glia-inhibiting neuronal respiration, causing glutamate release and excitotoxicity. J. Neurosci. 21, 6480–6491. Bauernfeind, A.L., Barks, S.K., Duka, T., Grossman, L.I., Hof, P.R., Sherwood, C.C., 2014. Aerobic glycolysis in the primate brain: reconsidering the implications for growth and maintenance. Brain Struct. Funct. 219, 1149–1167. Behl, C., Davis, J.B., Lesley, R., Schubert, D., 1994. Hydrogen peroxide mediates amyloid beta protein toxicity. Cell 77, 817–827. Belanger, M., Allaman, I., Magistretti, P.J., 2011a. Brain energy metabolism: focus on astrocyte-neuron metabolic cooperation. Cell Metab. 14, 724–738. Belanger, M., Allaman, I., Magistretti, P.J., 2011b. Differential effects of pro- and antiinflammatory cytokines alone or in combinations on the metabolic profile of astrocytes. J. Neurochem. 116, 564–576. Berg, A.H., Scherer, P.E., 2005. Adipose tissue, inflammation, and cardiovascular disease. Circ. Res. 96, 939–949. Bigl, M., Bleyl, A.D., Zedlick, D., Arendt, T., Bigl, V., Eschrich, K., 1996. Changes of activity and isozyme pattern of phosphofructokinase in the brains of patients with Alzheimer’s disease. J. Neurochem. 67, 1164–1171. Bigl, M., Bruckner, M.K., Arendt, T., Bigl, V., Eschrich, K., 1999. Activities of key glycolytic enzymes in the brains of patients with Alzheimer’s disease. J. Neural Transm. 106, 499–511. Bonda, D.J., Lee, H.P., Kudo, W., Zhu, X., Smith, M.A., Lee, H.G., 2010. Pathological implications of cell cycle re-entry in Alzheimer disease. Expert Rev. Mol. Med. 12, e19. Boumezbeur, F., Mason, G.F., de Graaf, R.A., Behar, K.L., Cline, G.W., Shulman, G.I., Rothman, D.L., Petersen, K.F., 2010. Altered brain mitochondrial metabolism in

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