Next Article in Journal
Parathyroid Hormone (PTH) Increases Skeletal Tumour Growth and Alters Tumour Distribution in an In Vivo Model of Breast Cancer
Next Article in Special Issue
Ageing, Cellular Senescence and Neurodegenerative Disease
Previous Article in Journal
Blood Pressure Profile and N-Terminal-proBNP Dynamics in Response to Intravenous Methylprednisolone Pulse Therapy of Severe Graves’ Orbitopathy
Previous Article in Special Issue
Ubiquitylation at the Fork: Making and Breaking Chains to Complete DNA Replication
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:

G Protein-Coupled Receptor Systems as Crucial Regulators of DNA Damage Response Processes

Department of Biomedical Sciences, University of Antwerp, 2610 Antwerp, Belgium
Translational Neurobiology Group, Center of Molecular Neurology, VIB, 2610 Antwerp, Belgium
Institute of Biophysics, Humboldt-Universität zu Berlin, 10115 Berlin, Germany
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2018, 19(10), 2919;
Original submission received: 22 August 2018 / Revised: 14 September 2018 / Accepted: 15 September 2018 / Published: 26 September 2018
(This article belongs to the Special Issue DNA Replication Stress)


G protein-coupled receptors (GPCRs) and their associated proteins represent one of the most diverse cellular signaling systems involved in both physiological and pathophysiological processes. Aging represents perhaps the most complex biological process in humans and involves a progressive degradation of systemic integrity and physiological resilience. This is in part mediated by age-related aberrations in energy metabolism, mitochondrial function, protein folding and sorting, inflammatory activity and genomic stability. Indeed, an increased rate of unrepaired DNA damage is considered to be one of the ‘hallmarks’ of aging. Over the last two decades our appreciation of the complexity of GPCR signaling systems has expanded their functional signaling repertoire. One such example of this is the incipient role of GPCRs and GPCR-interacting proteins in DNA damage and repair mechanisms. Emerging data now suggest that GPCRs could function as stress sensors for intracellular damage, e.g., oxidative stress. Given this role of GPCRs in the DNA damage response process, coupled to the effective history of drug targeting of these receptors, this suggests that one important future activity of GPCR therapeutics is the rational control of DNA damage repair systems.

Graphical Abstract

1. Introduction

With the knowledge gained about mechanisms underlying health and disease, as well as improved living standards and sanitization, there has been a major increase in the global average lifespan [1]. The world health organization reported in 2015 that an estimated 900 million people were aged 60 or older. By 2050, this number is expected to increase to about two billion people [2]. Despite this positive result of improved healthcare, a major complication incurred with this increase in the size of the worldwide elderly population is the burgeoning prevalence of aging-related diseases including neurodegenerative disorders, cardiovascular diseases and diabetes mellitus [3]. Indeed, this has been borne out through multiple studies connecting age-related molecular pathologies and the incidence of these disorders [4,5,6]. These studies suggest that the aging process is an underlying cause for multiple diseases; however, aging itself is not considered a disorder, but a normal physiological process [3]. Pathological aging can be defined as a progressive deterioration of physiological functions, which will eventually lead to systemic dysfunction and death [3]. These alterations include metabolic dysfunction, genome instability, telomere attrition and oxidative stress [7,8]. A greater understanding of these processes should improve our capacity to prevent or treat age-related diseases [9].
Transmembrane heptahelical GPCRs represent perhaps the most studied and effective drug targets to date. Their near ubiquitous role in physiological processes, coupled to their capacity to recognize a wide diversity of impinging molecules, makes them ideal targets for pharmacotherapeutic design [10,11]. As a testament to the functional efficacy of targeting GPCRs in disease, 475 drugs (~34% of all drugs approved by the FDA, acting on over 108 unique GPCR targets) are currently clinically employed [11]. While currently dominating the realm of therapeutics, there is still a strong impetus for future GPCR-based drug design. There are over 300 new experimental drugs that are currently in clinical trials, of which ~20% target 66 previously unexploited GPCR systems. The major disease indications for GPCR modulators have shown a trend towards diabetes, obesity and Alzheimer disease (AD), all of which are strongly age-dependent disorders. While the majority of the worldwide drug design effort has been made using the concept of exploiting and controlling the G protein-dependent signaling modality of GPCRs, there is now a growing field of more ‘engineered efficacy’ therapeutics that can utilize alternative modes of non-G protein-mediated GPCR signaling [12,13,14]. The emergence of these new and diverse GPCR signaling modes expands our concepts of the types of signaling systems that can be controlled through GPCR modulation. In this review, we will investigate one of these new target systems that may hold the key to the future treatment of multiple age-related disorders [15,16,17,18], i.e., the DNA damage-response (DDR) system.
As life proceeds through the individual’s aging process, both endogenous (e.g., reactive oxygen species (ROS)) and environmental (e.g., ionizing radiation) stressors are constantly attacking DNA, causing structural damage [9]. Unrepaired DNA damage negatively affects genome replication and transcription, causing wide-scale chromosomal aberrations that disrupt critical cell functions such as energy metabolism and protein folding/management [19,20,21]. Given the importance of DNA-protective activity as an anti-aging strategy, coupled to the feasibility of GPCR druggability, the generation of GPCR-based DDR controlling agents holds considerable promise for improved treatments for both disorders of genomic aging such as Werner syndrome or ataxia-telangiectasia, as well as age-related disorders such as metabolic syndrome or Parkinson’s disease.

2. Aging, Metabolic Functionality, DNA Stability, Damage and Repair

2.1. Metabolic Dysfunction, Oxidative Damage and Aging

Systemic aging in humans is strongly associated with the accumulation of deleterious molecular perturbations that negatively affect the functionality of almost all cells, tissues and organs. This progressive and stochastic accumulation of molecular perturbations induces significant cellular signaling dysfunctions that affect multiple processes related to energy metabolism, cell survival, genomic instability (via sub-optimal damage responsivity and repair efficiency) and aberrant cellular replication.
The molecular control of the aging process has long been associated with the highly-conserved insulinotropic receptor signaling system. This metabolic system controls the effective uptake and metabolism of glucose as the primary energy source in the majority of higher organisms. The crucial role of this signaling system in aging has been evidenced by the demonstration of lifespan extension, in species ranging from nematodes to mice, by mutations affecting insulin receptor signaling [22,23,24,25,26]. These mutations affect several cellular functions that are negatively regulated by the insulin receptor and therefore typically observed under fasting conditions where little caloric intake was extant and a likelihood of insulin resistance was low. Concomitant with this, lifespan as well as ‘healthspan’ (i.e., period of life in which no overt pathophysiology is extant) extensions have also been induced by caloric restriction and intermittent fasting interventions [6,27,28]. Considering this evidence, the insulinotropic system represents perhaps the most critical system in organismal development and survival. This primacy is due to this system’s ability to generate the optimal adenosine triphosphate (ATP) yield from catabolized dietary carbohydrate sources. As with all biological systems, the perfect repetition of its function is subject to incremental failure and reduction of sensitivity over time, i.e., the age-dependent inevitability of ‘insulin resistance’ and ‘metabolic syndrome’ receptor systems [29,30]. Therefore, with increasing age, there is a prevalent system-wide reduction in the ability of the body to cope with stress, in part, due to a degradation of the efficiency of energy-generating (e.g., ATP) metabolic systems [29,31,32]. Disruption of the primary energy-synthesizing system, i.e., mitochondrial oxidative phosphorylation, leads to both ATP depletion (thus affecting electrical cellular excitability, proteolytic activities, transmembrane transport processes and kinase activity), as well as an increase in the deleterious effects of unregulated hyperglycemia, e.g., systemic inflammation, enhanced ROS generation, arterial stenosis, impaired tissue healing, neuronal damage and renal failure [33,34]. Hence, many characteristic factors of the aging process are linked to effective energy management, i.e., the generation of insulin resistance, disruptions to oxidative phosphorylation of glucose and changes in body fat composition [29].

2.2. Oxidative Aging and DNA Damage Responses

The inexorable generation of systemic metabolic dysfunction (linked to insulinotropic system aberration) induces a global imbalance between ROS and endogenous antioxidant pathways. This systemic perturbation results in an increased susceptibility of lipids, proteins and nucleic acids to oxidative radical attack and the creation of sustained oxidative damage [35]. The Harman free radical/oxidative stress theory stipulates that physiological iron and other metals in the body would cause ROS accumulation in cells as a by-product of normal redox reactions. ROS are natural signaling entities, generated as a by-product of a variety of pathways involved in aerobic metabolism [36]. ROS-mediated oxidative stress in turn causes DNA and cellular damage in aged cells and organisms, which could trigger cellular apoptosis [35,36,37]. Depending on the source of damage, DNA can be altered in different ways, including nucleotide alterations (mutation, substitution, deletion and insertion) and the creation of bulky adducts, single-strand breaks (SSBs) and double-strand breaks (DSBs) [38]. To guide accurate repair of these lesions, cells activate a highly nuanced signaling network (i.e., the DDR pathway) that: (i) detects the presence of DNA damage sites; (ii) transmits the detection of damage to coordinating signal transducers; (iii) stimulates the activation of cell-cycle checkpoint and DNA damage repair mechanisms [39,40,41]. There are currently four elucidated DDR mechanisms characterized in mammalian cells: base excision repair (BER); nucleotide excision repair (NER); homologous recombination (HR); and non-homologous end-joining (NHEJ) [9,42]. BER mainly corrects single lesions or small alterations of bases caused by ROS [42,43]. This pathway involves multiple steps, starting with recognition of the damaged DNA by a DNA glycosylase [44], followed by the activation of a pathway common to SSB repair, involving an apurinic/apyrimidinic (AP) endonuclease to generate the DNA 3′OH terminus [45]. The final repair steps involve a synthesis stage with a DNA polymerase, followed by sealing the DNA lesion via DNA ligase activity [45]. NER is a more complex process for removing bulky DNA lesions formed by exposure to radiation, chemicals or through protein-DNA adduct formation [42,44]. DSB repair is performed by either HR or NHEJ [42]. DSBs caused by exogenous stressors can be repaired by either of these pathways [46]. Damage produced by a malfunction of DNA replication forks is primarily, or even exclusively, repaired by HR [47]. HR-dependent DSB repair is initiated by forming 3′OH overhangs, which associate with Rad52 and subsequently with polymerized Rad51 [48]. NHEJ is initiated by the recognition and binding of the Ku heterodimer (Ku70 and Ku80) to the DSB [49,50]. This then serves as a scaffold to recruit other NHEJ factors to the damaged site, such as the DNA-dependent protein kinase (DNA-PKs) [50].
Stress-induced DNA damage is a routine process in cells; this damage can occur at the level of whole chromosome structures, as well as to exposed single- or double-strand entities. Chromosomal DNA stability is provided by nucleoprotein-DNA structures termed telomeres [51]. Mammalian telomeres are repetitive DNA sequences, which form a lariat-like structure by associating with the multimeric Shelterin protein complex (also known as the telosome) to shield the exposed ends of chromosomal DNA from damage [51,52,53]. Telomeres shorten progressively with each cell replication cycle [54], thus imposing a functional limit on the number of times a cell can safely divide. Significantly shortened telomeres trigger cellular senescence in normal cells, or genomic instability in pre-malignant cells, which contribute to numerous degenerative and aging-related diseases [55]. Multiple lines of research, from human, murine and in cellulo studies, have shown that oxidative stress is associated with accelerated telomere shortening and dysfunction [56,57,58,59,60,61,62,63]. Several mechanistic models have been proposed to explain how oxidative stress accelerates telomere shortening. One possibility is that oxidative stress triggers cell death and/or senescence, and as a compensation, the extant cells then undergo further recuperative divisions, leading to increased telomere shortening [55]. Another widely-appreciated model hypothesizes that ROS induce SSBs at telomeres directly, or as intermediates in lesion repair, leading to replication fork collapse and telomere loss [64].
Furthering the associations between metabolic dysfunction, aberrant DDR and advanced aging phenotypes, several classical DDR-associated diseases (Hutchinson-Gilford progeria, Werner and Cockayne syndromes and ataxia-telangiectasia) are linked to dysglycemic states and insulin resistance [65,66,67,68,69,70]. Given the strong linkage between insulinotropic decline, oxidative stress, DNA damage and advanced aging, it is clear that molecular interventions that are able to manipulate this signaling convergence beneficially may represent important future treatments for age-related diseases.

2.3. Metabolic-Clock Process Linked with DDR

It has recently been demonstrated that the cellular clock and circadian rhythm are disrupted in the aging process [71]. Circadian clock rhythms, present both within the whole-organism and at the single-cell level, underpin the everyday fluctuations in biochemical, behavioral and physiological functions of organisms [72,73,74]. These circadian signaling systems allow the organism to reliably repeat daily patterns of activity throughout its lifespan [75]. The daily rhythm of mammalian energy metabolism is also subject to the circadian clock system. So-called ‘clock genes’ (factors that constitute biological clock regulation) have been revealed not only to constitute the molecular clock of cells, but also to function as facilitators that regulate and interconnect circadian and metabolic functions. As circadian signals generated by clock genes regulate metabolic rhythms, it is therefore unsurprising that clock gene function is tightly coupled to glucose and lipid metabolism. Clock gene dysfunction has thus also been strongly associated with metabolic disorders including diabetes and obesity [76,77,78,79]. Changes in energy balance, in turn, conversely affect circadian clock functionality [80,81,82]. Recent research has demonstrated that the application of high-fat diets to mice increases the circadian period of their locomotor activity under constant dark conditions, suggesting molecular disruption to their suprachiasmatic nucleus clock that controls global somatic time measurement [83]. In addition, high-fat diet supplementation has been shown to disrupt the rhythmic expression of clock genes in peripheral tissues [84]. Alterations in temporal feeding patterns have also been shown to affect circadian clock gene activity in energy-regulatory peripheral tissues [85]. As we have described previously (Section 2.1), dysfunctional metabolic activity may be one of the prime triggers of the pathological aging process that is then associated with telomeric instability and DNA damage. To this end, it is unsurprising that clock gene factors can control and integrate metabolic sensation, day-to-day age assessment and DNA stability. Thus, components of circadian clock, such as Aryl hydrocarbon receptor nuclear translocator-like protein 1 (BMAL1-CLOCK), period circadian protein homolog 1 (PER1), period circadian protein homolog 2 (PER2), period circadian protein homolog 3 (PER3) and inactive tyrosine-protein kinase transmembrane receptor ROR (ROR1), are suggested to be involved in cellular response to genotoxic stress [72,86,87,88,89]. As cellular clocks not only regulate chronological aging, but also the rate/extent of metabolic dysfunction, telomere stability and DNA damage [90,91,92], it is unsurprising that clock functionality is now linked to many age-related disorders, e.g., dementia [93,94], glycemic/adiposity disorders [95] and premature aging diseases associated with attenuated DDR [65,66,67,68,69,70,96,97]. Therapies targeting clock regulation mechanisms have thus demonstrated promising effects on the treatment of aging-related diseases including metabolic syndrome and psycho-affective disorders [98,99,100].
In these initial sections (1 and 2), we have outlined how the seemingly impenetrably complex process of aging, with its strong association with DDR events, may be more effectively understood using signaling network-based concepts. Forming the first level of synergy between the GPCR and DDR systems, we have also detailed how the currently expanding range of GPCR signaling modalities also seems to operate at a network level. At the second level of GPCR-DDR synergy, we have also demonstrated that both of these systems interconnect via the observed metabolic dysfunctions in the aging process. At a third synergistic level, both GPCR and DDR systems, via the alteration of energy metabolism, conspire to accelerate aging pathologies via accumulated oxidative damage. In the final fourth level of GPCR-DDR synergy, we have shown that these two systems converge via their common roles in both circadian clock and metabolic regulation to create a coherent and pervasive role of GPCR-DDR functionality in the aging process. In the following sections, we shall further refine these observations and illustrate them with specific exemplary findings.

3. G Protein-Coupled Receptor Systems: Intersections with DNA Damage and Repair Processes

3.1. GPCR Signaling Diversity

The GPCR superfamily represents perhaps the most diverse group of transmembrane proteins in the human proteome [101]. GPCRs have evolved to provide cells with an incredibly nuanced sensory system for entities ranging from photons, small metabolites, chemical neurotransmitters, to complex glycoprotein hormones and exogenous animal toxins [102]. This unparalleled molecular diversity of GPCR sensitivity has allowed molecular pharmacologists to exploit these complex signaling systems rationally to combat a plethora of diseases.
GPCRs provide a simple, but highly flexible, mechanism to facilitate the signal transfer of the ‘message’ of the extracellular stimulator (i.e., the receptor ‘ligand’ in biomedical terms) to the intracellular milieu. Hence, the stimulated receptor entrains characteristic cell signaling cascade responses to generate a productive cellular response to the external input [103]. These versatile heptahelical receptors essentially function as ligand-activated guanine nucleotide exchange factors (GEFs) for heterotrimeric G proteins. G protein activation is initiated through ligand-driven changes in the tertiary structure of the heptahelical core that are then transmitted to the intracellular transmembrane loops and carboxyl terminus of the receptor. These conformational changes alter the ability of the receptor to interact with intracellular G proteins and catalyze the exchange of GDP for GTP on the heterotrimeric G protein α subunit. This nucleotide exchange promotes dissociation of the G protein αβγ subunit heterotrimer, releasing the GTP-bound α subunit and the free βγ subunit. The GTP-bound α subunit stimulates its cognate downstream effectors, e.g., adenylate cyclase or phospholipase C, conveying information about the presence of an extracellular stimulus to the intracellular environment. In addition to the Gα subunit, free βγ subunits also possess effector stimulatory activity, e.g., promotion of G protein-coupled receptor kinase binding to the receptor. This classical ‘G protein-centric’ view of GPCR function still holds true, yet data accumulated over the last decade have suggested that G protein signaling is not the only physiologically-relevant signaling pathway employed by these receptors [104,105,106,107,108]. The discovery of alternative therapeutically-tractable GPCR signaling pathways, such as the β-arrestin signaling pathway, suggests that additional drug design avenues may be fruitful. Luttrell et al. first demonstrated that β-arrestins interact with Src family kinases and couple beta adrenergic receptors to extracellular signal-regulated kinase 1/2 (ERK1/2) pathways [12]. β-arrestin molecules were primarily associated with GPCR internalization and degradation [12,109]. However, in addition to mediating endocytosis of GPCRs, β-arrestins have been demonstrated to scaffold a wide variety of signaling complexes associated with GPCR signaling cascades that can occur in parallel, or subsequent to, G protein turnover [104]. β-arrestins have subsequently been demonstrated to bind a wide variety of kinases, e.g., E3 ubiquitin ligases, phosphodiesterases and transcription factors [110]. More recently, it has been shown that activation of β-arrestin, through the β2-adrenergic receptor (β2AR), leads to increased DNA damage, p53 degradation and the promotion of apoptosis [111,112]. These data suggest that if the activation of β2AR could be biased to signal through a more ‘non-β-arrestin’ signaling mode, DNA damage repair could be promoted. Implicit with the additional complexity of GPCR signaling repertoires, it has been demonstrated that these additional GPCR transduction mechanisms are facilitated and specified by the creation of stable multiprotein complexes with the receptor [103,107]. These large multi-protein complexes likely represent highly stable, due to the need to regulate multiple protein-protein interactions, sub-structures that are often termed ‘receptorsomes’. Given the likely presence of both G protein and non-G protein GPCR signaling, it is likely that cellular responses to stimulatory ligands will comprise a range of signaling outcomes dictated by both G protein activity and the expression profile of additional proteins that help create stable receptorsome complexes.
In addition to the recent introduction of non-G protein signaling to the functional repertoire of GPCR activity, new theories associated with the enlarged variety and cellular spatial nature of receptor activity are redefining our future concepts of therapeutic development. From their initial discovery, GPCRs were classically considered to be only ligand responsive when expressed on the cell surface plasma membrane. In contrast to this plasma membrane expression, a large majority of the total cellular amount of receptor protein was thought to be held in a cytosolic ‘reserve’ as nascent GPCRs ready to replenish the ‘actively signaling’ plasma membrane forms. This classical view of receptor pharmacology is still valid, especially for rapid extracellular stimulator-based G protein activation. There is now considerable evidence however demonstrating that GPCRs can also signal from intracellular membranes such as endosomes, mitochondria, endoplasmic reticulum, Golgi apparatus and the nucleus [113,114]. This additional signaling capacity suggests that GPCRs also act as intracellular signal transducers for stimulatory factors generated inside the cell. With this concept in mind, it is thus feasible to propose that GPCRs can also act as sensors, at the molecular level, for agents that can directly or indirectly induce oxidative stress and/or DNA damage.

3.2. GPCR Functionality in the Context of Molecular Gerontology

A considerable proportion of the global mechanistic process of aging is driven by a degradation of metabolic function resulting in elevated oxidative stress and DNA damage. In recent years, it has been demonstrated that there is a complex neuroendocrine control network of inter-connected GPCR systems that regulate ‘neurometabolic’ activity. This convergence of GPCR-based systems bridges the functional domains of endocrine and neuronal systems in health and disease [115,116,117,118,119,120]. Here, we also posit that in addition to controlling the aging process via regulation of global metabolism, GPCR systems can also exert a trophic effect on DDR during normal and pathological aging.
Metabolically-driven aging is characterized by the accumulation of adverse changes in cells over time that attenuates global homeostatic energy control and augments the risk of developing nearly all diseases [121]. In addition to cellular/tissue damage caused by accumulated protein/DNA damage, molecular aging ‘programs’ (i.e., coherent and repeated pathological patterns of protein expression leading to stress-related damage) can also generate age-related increases in cellular senescence. Cell growth arrest and hyporesponsiveness to extrinsic stimuli via cell surface receptors, such as GPCRs, are hallmarks of senescent cells [122,123,124,125]. Cell senescence describes the process in which cells cease dividing, but do not enter an apoptotic state. These senescent cells possess distinct functional phenotypes, compared to normal cells, with respect to chromatin remodeling and protein secretory behavior [126,127,128]. The discovery of this ‘cell stasis’ process has been attributed to Hayflick and Moorhead [129] after they observed the phenomenon of the irreversible growth arrest of human diploid cell strains induced by extensive serial passaging in culture. This ‘replicative senescence’ is linked with telomeric degradation following each cell cycle. As we have discussed previously, this telomere attenuation [129,130] is strongly associated with DNA frailty. Rather than representing a functional ‘dead end’ of cell physiology, evidence gathered over recent years has demonstrated the importance of senescence-related signaling in processes such as embryonic development [131], wound healing/repair [132,133] and, most importantly, aging [134,135].
In addition to telomeric degradation, additional stressors have been shown to engender cellular senescence, e.g., certain DNA lesions and ROS attack [136,137], both of which are linked through the DDR signaling pathway. It is thought that senescence can be regulated via ATM or ATR (ataxia Telangiectasia Rad3 related) kinases that effectively block cell-cycle progression through the stabilization of p53 and transcriptional activation of the cyclin-dependent kinase (Cdk) inhibitor p21 [138]. Along with cell cycle arrest, the alteration of the functional cellular ‘secretome’ (i.e., the range of secreted proteins from a specific cell type) of the specific cell entering a senescent state is one of the characteristic features of this aging-associated state [139]. Profound chromatin remodeling represents one of the first steps in age-related senescence; this event causes a coherent cellular response involving elevation of transcript levels for pro-inflammatory cytokines, chemokines, cell-remodeling growth factors and proteases [140,141]. This modulatory secretory phenotype has now been codified as the senescence-associated secretory phenotype (SASP) [139,142,143]. SASP responses, like cell cycle arrest events, can also be dependent on protracted DNA damage signaling [143], caused by the feed-forward loops that can be generated between DDR signaling and ROS attack [144]. Interestingly, it has been demonstrated that SASP-associated activity is also strongly linked to modifications in GPCR functionality [145,146].

3.3. GPCR Signaling Systems and DNA Damage Repair

While the aging process and the accumulation of age-related damage seem inevitable facts of metabolic life, the strong involvement of GPCR-associated signaling cascades at many levels of this process provides a potentially important and effective drug-based mechanism for amelioration and/or retardation of this process [106,147,148,149]. Aging, as a molecular process, is clearly a slowly developing entity, coordinated by the interaction of multiple signaling systems across almost all somatic tissues over decades. This complexity makes it a troublesome process to target using conventional ‘monolithic target’ therapies, e.g., the failure of anti-amyloid therapies targeting age-related dementia [150]. In contrast, complex mechanistic disease systems may be more effectively targeted by therapeutics that possess multidimensional pharmacological efficacy profiles [151,152,153,154,155]. The discovery and development of the concept that GPCR systems can effectively target and regulate complex transcriptomic/proteomic responses via receptorsome-based non-G protein-dependent signaling [103] provides a feasible platform upon which multidimensional therapeutic interventions for aging can be created [13,14,106]. In their elegant manuscript, Watts and Strogatz [156] demonstrated that an optimal level of communication between entities, within any specific complex system, is facilitated by a level of organization where some nodes within the network possess a greater degree of regulatory connectivity compared to other nodes. In the case of molecular signaling networks in the aging process, it is likely therefore that some proteins possess more profound network-regulating functions than others [8]. These network-controlling factors have been termed ‘keystones’ or ‘hubs’ and are thought to provide a mechanism of dimensional condensation for highly complex cellular signaling systems. This network organization facilitates the rapid transfer of coherent biological/pathological perturbations across a complex series of nodes by making so-called ‘short cuts’ across the network. As such, the super-complex aging process networks can be controlled at a trophic keystone/hub level rather than by individual sensation/regulation at the individual node (protein or gene) level [157,158]. These keystones therefore likely connect and coordinate multiple discrete signaling cascades that synergize to regulate multifactorial somatic processes. Demonstrating the efficiency of organizing networks in this manner, it has been shown that even networks containing thousands of nodes require only the presence of surprisingly few (5–10) keystones to facilitate rapid transfer across large systems [156]. Targeting these trophic-level proteins, potentially via the recently discovered GPCR-based transcriptomic efficacy role, facilitates regulation of such complex disorders in a rational manner as opposed to the unfeasible proposal of therapeutic aging control at every molecular point in the network. In the next section, we will identify key components of complex GPCR signaling systems that possess strong functional roles in the aging-DDR process; by doing so, we hope to illuminate the potential for effective molecular interventions for neurometabolic aging pathologies.

3.3.1. Heptahelical GPCRs and DNA Damage

Lysophosphatidic Acid Receptor

The GPCR heptahelical core still remains the primary target of therapeutic drug development, but it is clear from considerable research that the functionality of this core transmembrane protein is heavily modulated by accessory protein interactions in addition to the standard G protein associations. These accessory protein interactions have been shown to control receptor dimerization, linkage to non-receptor signaling adaptors and associations with other complex receptor systems [110,159,160,161]. The involvement of GPCR signaling systems in DDR pathways has received interest from multiple research groups recently. For example, LPA2 (lysophosphatidic acid G protein coupled receptor subtype 2) receptor stimulation has been shown to activate MAPK/ERK, PI3K/AKT and NF-κβ signaling, which leads to enhanced cells survival and repair of radiation injuries [162,163,164]. The activation of an NF-κβ-dependent, ATM-based signaling cascade in turn then controls the expression of the LPA2 receptor itself [165]. It has furthermore been shown that the activation of this receptor leads to the resolution of radiation-induced γH2AX lesions [166] and enhanced long-term survival of acutely-irradiated cells [167].

Dopamine D2 Receptor

Protein arginine methylation regulates diverse functions in eukaryotic cells, including gene expression, the DDR and circadian rhythms. Protein arginine methyltransferase 5 (PRMT5) has been shown to interact directly with and effect the methylation of the dopamine D2 receptor (D2R). This would therefore represent a potential new signaling pathway with which novel pharmacological agents could modulate GPCR signaling by changing the methylation status of key cell signaling associated with DDR responses [168]. In addition to this link between D2Rs and pro-aging mechanisms, therapeutic targeting of D2R-associated DNA damage effects may also yield the creation of novel anti-neoplastic agents [169]. The selective DR2 blocker thioridazine has been shown to induce apoptosis and autophagy in ovarian cancer cell lines, which may be attributed to an increased level of ROS with associated DNA damage. Thioridazine treatment also resulted in the augmented expression of various proteins associated with oxidative stress, including nuclear factor E2-related factor 2 (NFE2L2), a pivotal transcriptional factor involved in cellular responses to oxidative stress. Conversely, thioridazine treatment has been shown to reduce expression of heme oxygenase 1, NAPDH quinone dehydrogenase 1, hypoxia inducible factor-1α and phosphorylated protein kinase B (Akt-1), factors that together represent a concerted pro-DNA damage molecular phenotype.

CXCR4 Receptor

The chemokine receptor, CXCR4, has been strongly associated with the modulation of DDR-related activity and cell cycle control in the context of oncology. Small peptide antagonists, potentially acting via non-G protein-dependent signaling pathways, have been shown to possess anti-neoplastic activity via the activation of ‘mitotic catastrophe’, an event associated with a premature or inappropriate cellular entry into mitosis [170]. The experimental peptide antagonist (CTCE-9908) has been shown to induce multinucleation, cell cycle arrest and abnormal mitosis through the deregulation of DNA damage and spindle assembly checkpoint proteins. The chemokine receptor CXCR4 and its ligand, CXCL12, are critical factors supporting quiescence and bone marrow retention of hematopoietic stem cells (HSCs) during the aging process. Engineered disruption of CXCR4 receptor expression in mice has been demonstrated to induce an increase in the production of ROS in bone marrow. This elevated ROS activity was subsequently shown to induce apoptosis via enhanced p38 MAPK activation, increase DNA DSBs and apoptosis, leading to a marked reduction in HSC repopulating potential. Taken together, these multiple signaling activities result in an increased rate of bone aging [171].

Hydroxycarboxylic Acid (Lactate) Receptor

The primary metabolite lactate was originally considered to be a biomedical waste product of metabolism. Lactate has however been shown to possess important positive signaling roles, especially in the central nervous system (CNS). In the CNS, lactate is released by astrocytes in response to neuronal activation, after which it is taken up by neurons, oxidized to pyruvate and used for synthesizing acetyl-CoA to feed oxidative phosphorylation [172]. The discovery of a cognate GPCR for lactate (hydroxycarboxylic acid) receptor 1 (HCAR1) [173] further reinforced the importance of the lactate system in linking cellular metabolism with cognitive function and neuroprotective activity. The lactate GPCR system has subsequently been demonstrated to mediate in part the beneficial neurocognitive aspects of anti-aging interventions such as exercise [174,175]. HCAR1 activity has been implicated in lactate-related enhancement of DNA repair mechanisms in cells, via regulation of LIG4 (DNA ligase 4), NBS1 (Nijmegen breakage syndrome 1), APTX (aprataxin) and BRCA1 (BRCA1, DNA repair associated) expression, as well as an increase in DNA-PKcs activity [176,177]. In addition to controlling DDR mechanisms, the HCAR1 also appears to control the generation of chemoresistance to the DNA damaging agent doxorubicin, via a reflexive ABCB1 (ATP binding cassette subfamily B member 1) transporter upregulation in HeLa cells [178].

Melanocortin 1 Receptor

While a considerable degree of DNA damage can be induced during the aging process via ROS attack, the long-term exposure to solar ultraviolet radiation can also contribute to age-related genomic frailty. Recent research has shown that both melanocortin 1 (MC1R), as well as endothelin B (ENDBR) receptors play important roles in the constitutive regulation of melanocytes and their response to solar ultraviolet radiation [179]. Ligand-mediated activation of the MC1R has been shown to (i) effectively attenuate the extent of damage induced by oxidative stress events and (ii) augment the activity of DNA repair pathways. Specifically, α-MSH (alpha-melanocyte stimulating hormone)-mediated stimulation of MC1R results in the phosphorylation and activation of the DNA damage sensors ATM, ATR and DNA-PK [179,180]. Treatment with α-MSH has also been shown to increase the levels of Chk1 and Chk2 (checkpoint kinase 1 and 2), the immediate downstream targets of ATR and ATM, as well as the transcription factor p53 and γ-H2AX, the phosphorylated form of histone 2AX [179].

Angiotensin II Receptor

Emerging data have demonstrated the importance of maintaining effective aortic vascular compliance during the metabolic aging process [181]. The therapeutic attenuation of both vascular stiffening and hypertension in the elderly represent a potentially effective pro-longevity intervention strategy [182]. As advanced aging is commensurate with increased degrees of DNA damage, it is therefore unsurprising that GPCR-associated factors that have strong hemodynamic functions, such as angiotensin II (Ang II), are also important regulators of the DDR process. Activation of the Ang II-associated renin-angiotensin-aldosterone system leads to the formation of ROS. Ang II-mediated stimulation of renal cell lines can induce DNA damage via activation of the Ang II type 1 receptor (AT1R) [183]. AT1R-mediared activation of NADPH oxidase (Nox4 subunit-containing isoform) causes the production of ROS, resulting in the formation of DNA strand breaks and micronuclei induction. In addition to DNA-damaging effects on renal cell systems, Ang II also has been shown to induce oxidative DNA damage and to accelerate the onset of cellular senescence in vascular smooth muscle cells (VSMCs). This pro-aging activity was ultimately shown to occur via telomere-dependent and independent mechanisms [184].

3.3.2. β-Arrestin Family Proteins

Human β-arrestins comprise a small family of cytosolic proteins originally studied for their role in the desensitization and intracellular trafficking of GPCRs. Despite this humble beginning, the β-arrestins (β-arrestin1 (ARRB1) and β-arrestin2 (ARRB2)) have emerged as key regulators of multiple signaling pathways involved in aging. By acting as cellular scaffolding proteins that link vital signaling pathway entities to GPCRs, β-arrestins can exert homeostatic and ligand-responsive allostatic control of intermediary cell metabolic events and long-term cellular functionality [185]. As mentioned previously, Luttrell et al. [12] first demonstrated that β-arrestin interacts with Src family kinases and couples the receptor to MAPK ERK1/2 pathways that are associated with the regulation of both oxidative DNA damage [186] and DNA damage-associated cellular senescence [187]. β-arrestins have subsequently been demonstrated to bind a wide variety of kinases, E3 ubiquitin ligases, phosphodiesterases and transcription factors [110,185]. This ability of β-arrestins to connect GPCRs with these diverse signaling factors has greatly expanded the functional repertoire of these receptors. With respect to a direct association with β-arrestin-mediated signaling and DNA damage/repair pathways, early work indicated that stimulation of beta2-adrenergic receptors (β2ARs) promoted dephosphorylation of β-arrestin2 and its suppression of NF-kappaB (NF-κB) activation. NF-κB activation in response to UV-induced DNA damage is vital to maintain an effective DDR response [112]. Subsequent research into this intersection between β-arrestin-mediated signaling and DNA damage demonstrated that in both murine/human cell lines, β-arrestin1, after association with the active β2AR, induces an Akt-1-mediated activation of the E3 ubiquitin ligase, MDM2. This β-arrestin-dependent activation of MDM2 promotes the direct binding of this ligase to p53, thus promoting its degradation resulting in a detrimental effect upon the integrity of DDR systems, finally leading to increases in nuclear γ-H2AX adducts [188]. The apparent ability of circulating catecholamine stimulants of the β2AR, e.g., epinephrine and norepinephrine, to trigger GPCR-β-arrestin-mediated pro-DNA damage effects led to subsequent testing of these findings in murine models of stress, in which an elevated catecholamine drive would be present. Using an underwater trauma model of stress, Sood et al. [189] found that there was a steady-state increase in the physical association of the β2AR, β-arrestin1 and p53 with MDM2, thus creating a pro-DNA damage state in the CNS. Reinforcing this finding, Hara et al. [111] demonstrated that pharmacological blockade of this β-arrestin1-dependent p53-MDM2 signaling system was effective in reducing the extent of DNA damage induced by an applied behavioral stress to mice. As β-arrestin1 interacts with nearly all GPCR family proteins, this DNA damage cascade is unlikely to be specific to the β2AR system; for example, a simple pro-DNA damage β-arrestin1-p53-MDM2 signaling paradigm has been demonstrated for the previously mentioned MC1R [190]. These data therefore potentially suggest that if the activation of β2AR could be biased to signal exclusively through a non-β-arrestin mediated signaling paradigm, a reparative DDR response could be promoted. While these data evidently link the β-arrestin1 signaling pathway to the generation of DNA damage, in cases where induction of DNA damage may be desired (i.e., in oncology chemotherapy), the specific drug manipulation of β-arrestin1 activity may be beneficial to enhance chemosensitivity to co-administered anti-neoplastic agents [191].

3.3.3. G Protein-Coupled Receptor Kinases and Associated Proteins

As we have discussed, stressful stimulation of GPCR systems, e.g., via circulating norepinephrine, can lead to pro-DNA damaging events. Therefore, the molecular mechanisms that control the sensitivity/activity of GPCRs may also be an important nexus for controlling age-related DNA damage. In response to ligand stimulation, the vast majority of GPCRs are reflexively ‘cut-off’ from generating further G protein-dependent signals via a ‘desensitization’ of the receptor. This tachyphylactic response is typically mediated by the phosphorylation of the receptor by heterologous desensitization (via second messenger-dependent protein kinases such as protein kinase A) and/or homologous desensitization (via a selective phosphorylation through a G protein-coupled receptor kinase (GRK)). Within seconds of receptor stimulation, these kinases phosphorylate serine and threonine residues within the intracellular domains of GPCRs, thereby uncoupling the receptors from heterotrimeric G proteins [192,193,194]. In addition to mediating this reflexive phosphorylation of activated GPCRs, GRKs also control phosphorylation independent cellular responses via their ability to interact with a broad spectrum of proteins involved in signaling and trafficking, e.g., PI3K (phosphoinositide 3-kinase), clathrin, caveolin, RKIP (Raf kinase inhibitor protein), MEK (mitogen-activated protein kinase kinase), Akt (protein kinase B) and GIT (GRK-interacting transcript) proteins [195,196,197,198]. This scaffolding function of GRKs allows them to act as potential structural regulators that may control the organization of GPCR-based receptorsomes.
GRKs belong to a coherent family of associated proteins that all share at least a similar kinase activity. The GRK superfamily of related proteins can be subdivided into three main groups based on sequence homology: (i) rhodopsin kinase or visual GRK subfamily (GRK1 and GRK7); (ii) the β-adrenergic receptor kinases subfamily (GRK2/GRK3); (iii) the GRK4 subfamily (GRK4, GRK5 and GRK6). These kinases share certain characteristics, but are distinct enzymes with specific regulatory properties. GRK2, 3, 5 and 6 are ubiquitously expressed in mammalian tissues, whereas GRK1/7 (retina) and 4 (cerebellum, kidney, gonads) demonstrate more tissue-specific expression patterns [199,200,201]. With respect to a potential role of GRKs in the DDR realm, it was first noted that genomic reduction of GRK5 expression in osteosarcoma cells inhibited DNA damage-induced apoptosis via a p53-mediated mechanism [202]. It was subsequently demonstrated that p53 was a high-affinity substrate of GRK5 and its phosphorylation by this kinase led to its degradation and subsequent inhibition of the p53-dependent apoptotic response to genotoxic damage. This association of GRK5 with the DDR pathway was shown to be highly selective, as neither GRK2 nor GRK6 could mediate this p53 phosphorylation. Demonstrating the importance of this pathway, it has been shown that GRK5-deficient mice possess an elevated p53 expression level, leading to an elevated irradiation-induced apoptotic sensitivity. Commensurate with this functional role in DDR processes and cell damage, it has been demonstrated that GRK5 deficiency predisposes model organisms to age-related neurodegeneration, cognitive dysfunction and loss of synaptic plasticity [203,204,205]. In the cardiovascular setting, however, age-related pathologies have also been associated with elevated GRK5 expression [206].
As previously mentioned, many GRK-interacting proteins mediate other significant signaling functions. One of these proteins that possesses an important role in controlling DDR is the GRK-interacting transcript 2 (GIT2). GIT2 is a widely-expressed ADP-ribosylation factor GTPase-activating protein (Arf-GAP) [8,207,208,209]. GIT2 was identified as an important protein linked to several aspects of the complex neurometabolic aging process through latent semantic indexing (LSI)-based interrogation of high-dimensionality hypothalamic proteomic datasets gathered from longitudinal analysis of aging rats [8]. It was further demonstrated that an age-dependent elevation of the expression of GIT2 in the hypothalamus (as well as other brain regions) was found in non-human primates, as well as humans [8]. These findings were also supported by the demonstration of elevated expression levels of GIT2 in human neuronal cells exposed to increasing oxidative stress levels [37]. Additional investigations revealed that GIT2 interacts with many proteins involved in multiple signaling pathways linked to aging such as ATM, p53 and BRCA1. All of these proteins are involved in stress-responsive cascades and play important roles in cell cycle/DDR control, circadian clock regulation [157,210,211] and generation of SASP phenotypes in immune tissues [211]. Ectopic elevation of GIT2 expression in neuronal and non-neuronal tissues is able to attenuate the extent of DNA DSB damage induced by both ionizing radiation and chemotherapeutic DNA-damaging agents (cisplatin) [210]. Further reinforcing this permissive role of GIT2 in the aging process, it was shown that genomic deletion of GIT2 resulted in an accelerated rate of γ-H2AX lesion inclusion in central nervous cortex tissue in experimental mice [210]. In addition to the damage caused to brain tissues in GIT2 knockout (GIT2KO) mice, it was recently demonstrated that genomic deletion of GIT2 led to a significant co-reduction of multiple circadian clock-related mRNA transcripts in a broad range of immunological tissues including spleen, thymus and multiple lymph nodes [211]. This downregulation of GIT2 with associated clock-related proteins has been associated with premature aging (evidenced by accelerated thymic involution), the creation of a SASP-like phenotype and DDR functions [211]. These data together suggest that GIT2 may act as a functional connector between cellular senescence, clock regulation and DNA damage repair and as such could possess the capacity to alter the accumulation of age-related cellular damage. Therefore, GIT2 might represent a crucial therapeutic target to attenuate age-related metabolic decline. Classical therapeutic targets however are usually receptors, ion channels, kinases and phosphatases; hence, as GIT2 is a scaffolding protein, it does not represent a typical therapeutic target [212]. The demonstration that, in addition to regulating intermediary cell metabolism events, GPCRs can also effectively regulate the expression profiles of multiple signaling proteins via non-G protein-dependent functions [13,14,213] facilitates an important expanded capacity for drug development. Hence, it is likely that in the future, GPCRs can be employed to control the expression profile of specific non-canonical signaling proteins, e.g., GIT2 [13,107]. In this scenario, the GPCR target would be chosen for its capacity to control the expression of network-controlling regulators (e.g., GIT2) and their associated factors rather than just modulating a single protein target. Therefore, in order to target and control GIT2, it is imperative to find a GPCR that can modulate the function and expression of this scaffolding protein. To identify a GPCR strongly associated with GIT2, GIT2KO mice were used recently to investigate expression relationships across multiple tissues [212]. In GIT2KO mice, a consistently downregulated GPCR, the Relaxin 3 family peptide receptor (RXFP3), was found in the murine CNS, pancreas and liver [212]. The therapeutic control of this GPCR therefore may represent a facile system with which to control the expression profile of GIT2 in tissues and therefore regulate aging-related cellular damage in a trophic manner.

3.3.4. Regulator of G Protein Signaling Proteins

The regulation of GPCR activity is highly complex and well controlled, with multiple layers of interconnected signaling pathways activated upon receptor stimulation that feedback to modulate receptor signaling. The most studied GPCR signal ‘conditioning’ mechanisms are mediated by GRKs and β-arrestins; however, an extra level of control is common to many GPCRs, as well, i.e., that exerted by the regulator of G protein-signaling (RGS) proteins [214]. RGS proteins control the activity of GPCRs via their ability to control heterotrimeric G protein signaling negatively by accelerating the Gα subunit GTP hydrolytic activity, thus helping to determine the magnitude and duration of the cellular response to GPCR stimulation [215]. It is interesting to note, however, given our current knowledge of non-G protein-dependent GPCR signaling, that indeed RGS proteins may conversely represent themselves as positive stimulators of these recently identified pathways.
Presently, there are thought to be at least twenty canonical RGS protein versions found in mammals [214]. These members of the RGS superfamily are divided into four subfamilies based on sequence homology and the presence and nature of additional non-RGS domains. With respect to the involvement of RGS proteins in the dynamics of DDR responses, early research indicated that disruptions to RGS protein (RGS16, RGSL1/RGSL2 (RGS-like proteins 1/2)) expression/functions were mediated in human breast carcinomas through DNA fragility within the HPC1 region in chromosome 1 [216]. As with many GPCR-system interactions with the DDR process, the cell cycle regulator p53 clearly exerts a trophic functional role, e.g., within immune cells, the cellular expression profile of RGS13 was demonstrated to be suppressed by prevailing p53 activity [217]. Reinforcing the importance of p53-mediated signaling associated with RGS protein functionality, Huang et al. [218] demonstrated that the anti-neoplastic agent doxorubicin activates ATM and p53 through an RGS6- and ROS-dependent signaling process. Interestingly, this ROS/RGS6-dependent ATM-activating mechanism was found to be functionally independent of actual physical DNA damage [218]. This RGS6-dependent ATM/p53 mechanism has also been shown to be relevant in myocardial apoptosis; this finding therefore introduces the potential to reduce the harmful cardiotoxic effects of human doxorubicin oncological treatment regimens in the future [219]. Further research investigating the role of RGS6 in ATM activation found that mammary epithelial cells (MECs), isolated from RGS6-null mice, demonstrated a deficit in ATM/p53 activation, ROS generation and apoptosis in response to the DNA damaging agent DMBA (7,12-dimethylbenza[α]anthracene), confirming that RGS6 was required for effective activation of the DDR in these cells [220]. These data suggested that RGS6 might be a potent natural inhibitor of breast cancer initiation and progress, thereby presenting a new capacity for future breast cancer treatment. An unexpected intersection between the RGS system and DDR responses was recently found by Sjögren et al. [221] during an unbiased genomic siRNA screening approach to uncover mechanisms that control proteasomal degradation pathways for RGS2. This research team was able to identify a novel E3 ligase complex containing cullin 4B (CUL4B), DNA damage binding protein 1 (DDB1) and F-box protein 44 (FBXO44) that mediates RGS2 protein degradation. DDB1 is a multifunctional DDR-associated factor initially isolated as a subunit of a heterodimeric complex that recognizes ultraviolet radiation-induced DNA lesions in the NER pathway [222]. Therefore, within this screen, it was clear that a functional link with the DDR system was evidenced by the presence of DDB1 in the RGS2-controlling interactome.

3.3.5. Non-Canonical GPCR-Interacting Proteins

It is evident from the growing body of literature concerning the functional and effective intersections between the GPCR and DDR systems that future research into this paradigm will hopefully yield actionable therapeutic strategies to mitigate age-associated DNA damage and the age-related disorders this damage triggers. So far, we have shown that GPCRs themselves, β-arrestins, GRKs and their interacting proteins, as well as RGS proteins can play important regulatory roles in DNA-management processes. As we have stated before, however, the true functional spectrum of GPCR-system associated proteins, including ones likely to affect the stoichiometry of GPCR receptorsome structures, has yet to be conclusively mapped. Therefore, in this final section, we shall discuss the role(s) of other non-canonical GPCR-interacting factors that also control the functional intersection of GPCR and DDR signaling systems.

Regulated in Development and DNA Damage Responses

The availability of cellular nutrients and prevalent metabolic energy levels are functionally detected by signaling mechanisms that involve the mTORC1 (mammalian target of rapamycin complex 1) kinase. In response to the presence or absence of these stimuli, mTORC1 can control cell growth and viability. The cellular ability to maintain energy homeostasis is tightly linked to a cells’ capacity to maintain DNA integrity and stability. To this end, the catalytic activity of mTORC1 can be inhibited by the absence of sufficient nutrients or via the sensation of cellular stressors through the responsive overexpression of REDD1 (regulated in development and DNA damage responses) [223]. REDD1 was initially identified as a crucial developmentally-regulated factor that connects p53 signaling to the cellular regulation of ROS-sensitivity, thus suggesting its role in DDR activities [224]. Researchers have recently shown that this mTORC1-regulatory protein demonstrates a strong functional link to GPCR-systems. Michel and co-workers [225] employed a quantitative BRET (bioluminescent resonance energy transfer)-based plasma membrane localization assay to screen for the ability of a panel of endogenously-expressed calcium-mobilizing GPCRs to induce plasma membrane translocation of REDD1. This research team demonstrated that REDD1 and its mTORC1-inhibitory motif participate in the GPCR-evoked dynamic interaction of REDD1 with the plasma membrane, thus identifying this novel DDR-associated protein as a new effector in GPCR signaling. Translocation to the plasma membrane appears to be an inactivation mechanism of REDD1 by GPCRs. This GPCR-mediated inactivation process is most likely via the resultant sequestration of REDD1’s functional mTORC1-inhibitory motif.

Fanconi Anemia A Protein

Fanconi anemia (FA) is a rare genetic disease resulting in impaired responses to DNA damage. Among FA patients, the majority develop cancer, most often acute myelogenous leukemia, and 90% develop bone marrow failure (the inability to produce blood cells) by the age of 40. Over two-thirds of FA patients present with congenital defects including: short stature; abnormalities of the skin, arms, head, eyes, kidneys, ears, developmental disabilities and infertility [226]. FA is the result of a genetic defect in a cluster of proteins responsible for DNA damage repair via homologous recombination and is considered to be a classical ‘genome instability’ disorder. FA is therefore formally defined as an acquired state that allows for an increased rate of spontaneous genetic mutations throughout each replicative cell cycle [227,228]. To date, 17 different Fanconi anemia proteins (FANC A, B, C, D1, D2, E, F, G, I, J, L, M, N, P, S and RAD51C, XPF) are currently known to exist; disruption of these can lead to the genomic instability characteristic of FA [228]. The FANCA protein is found to be responsible for approximately 64% of FA cases [229,230], suggesting that this specific FA protein holds a singular position in the maintenance of genome integrity. In addition to its role in genomic stability, FANCA has been shown to also be a key regulator of GPCR activity. Larder and co-workers [231] demonstrated that the expression levels of FANCA, in pituitary gonadotrope cell lines, were controlled by gonadotropin-releasing hormone (GnRH)-mediated stimulation of its cognate GPCR. Upon GnRH-induced expression of FANCA, it was shown to adopt an intracellular nucleocytoplasmic distribution pattern constitutively. Protracted GnRH receptor stimulation was shown to induce a nuclear accumulation of FANCA before eventually trafficking back to the cytoplasm via the nuclear export receptor CRM1 (chromosome region maintenance 1 protein homolog). FANCA was subsequently demonstrated to be vital in allowing GnRH to control the expression of the gonadotropin hormones, i.e., luteinizing and follicle-stimulating hormones. Regulating the transcriptional control of these two hormones offers a convincing explanation of the infertility issues found in FA patients. It was concluded from this study that FANCA could be considered as a novel signal transducer of the GnRH receptor.

Poly(ADP-ribose) Polymerase 1 Protein

The poly(ADP-ribose) polymerase (PARP1) protein is directly involved in the BER DDR pathway. PARP1 catalyzes the poly(ADP-ribosyl)ation of a number of acceptor proteins involved in the regulation of chromatin architecture, as well as DNA metabolism. This poly(ADP-ribosyl)ation tracks DNA damages and represents a crucial step in the sensory signaling pathway leading to the repair of DNA strand breaks [232,233,234,235]. Demonstrating the tight functional links between DDR and the aging process, it has been shown that the prevailing PARP1 activity, measured in the permeabilized mononuclear leukocytes of thirteen mammalian species (rat, guinea pig, rabbit, marmoset, sheep, pig, cattle, pygmy chimpanzee, horse, donkey, gorilla elephant and man), predictably correlates with the maximum lifespan of these species [236]. In recent years, the scope of functionality of DDR proteins, e.g., BRCA1, has expanded to include effective roles in age-related disorders of cognition such as AD [237]. Recent studies have also indicated that PARP1 may be a new nuclear target in AD-related signal transduction pathways [238]. Further studies into the PARP1 connection with AD have found that muscarinic acetylcholine (mAChR) GPCR stimulation can fully activate hippocampal PARP1 through a calcium mobilization-dependent and ROS independent process [239]. This cholinergic GPCR-dependent PARP1 activation was abolished by the administration of a pro-AD amyloidogenic peptide (Amyloid beta 25–35) to experimental mice. This toxic pathological peptide itself significantly stimulated PARP1 activity by inducing ROS-mediated DNA damage. These data suggest that toxic amyloid beta peptides can affect mAChR-dependent signal transduction to PARP1, probably via ROS interdiction and inhibition of ligand-induced calcium mobilization. PARP1 therefore effectively serves as a downstream effector of the mAChRs that form the prime functional target of current AD therapeutics such as the cholinesterase inhibitor Aricept®.
Further to the role of PARP1 in receptor-mediated protection of CNS DNA, it has been shown in human neuronal cells that the aging keystone GIT2 forms active complexes with both PARP1 and PARP2 in response to DNA-damaging stress caused by cisplatin treatment or ionizing radiation. The interaction of GIT2 served to enhance the signaling activity of PARP1 in these cells and likely contributed to the DNA-protecting activity of the GIT2 protein [210].

Angiotensin II Type 2 Receptor-Interacting Protein

We have previously indicated that with respect to age-related cardiovascular pathophysiologies, the Ang II ligand-receptor system is an important player in this paradigm (Section 3.3.1). However, in addition to the role of angiotensin receptors in DDR processes, recent research has demonstrated that additional GPCR interacting proteins can also condition the output of this receptor system. Ang II can functionally interact in a selective manner with two major cell surface GPCRs, angiotensin type 1 receptor (AT1R) and angiotensin type 2 receptor (AT2R). As discussed previously, Ang II is closely associated with vascular diseases and vascular remodeling. Since vascular senescence plays a critical role in vascular aging and age-related vascular diseases, this pro-aging process can be functionally enhanced by AT1R stimulation [240,241]. Conversely, AT2R stimulation generates the opposite signaling output and can functionally antagonize AT1R-mediated vascular senescence [242]. It has been demonstrated that multiple non-G protein interacting partners synergize with the Ang II GPCRs to regulate this complex interplay with respect to cellular senescence control. For example, the AT1R–interacting protein (ATRAP) attenuates the ability of the AT1R to induce vascular senescence [243,244]. A direct binding partner of the AT2R, i.e., the AT2R-interacting protein (ATIP) [245], has been shown to control vascular senescence behavior, as well [246]. ATIP interaction with the AT2R appears to play an important role in AT2R control of the senescent process. Hence, Min and co-workers [246] investigated the functional mechanisms of this system in a transgenic murine system. Transgenic mice were created overexpressing the ATIP protein and were employed to derive primary VSMC cultures. Chronic Ang II stimulation of VSMCs from wild-type mice resulted in the increase of the DNA damage marker, 8-OHdG. This damaging effect of Ang II was significantly attenuated in the VSMCs of ATIP transgenic mice after similar treatment with Ang II. VSMCs of ATIP transgenic mice, in response to chronic Ang II stimulation, showed a greater elevation of the DNA repair factor methyl methanesulfonate-sensitive 2 (MMS2) levels compared to wild-type controls. Significantly less aortic 8-OHdG expression was found, along with a more potent elevation in MMS2 levels in the ATIP transgenic mice compared to controls following whole-body irradiation of wild-type and ATIP transgenic mice. Thus, the ATIP GPCR interacting protein was shown to possess the capacity to attenuate the extent of DNA damage while augmenting the degree of damage repair.

4. The GPCR-DDR Signaling Intersection and Its Potential Therapeutic Exploitation

In recent years, ever stronger connections have been observed between the functional realms of GPCR and DDR systems. Both signaling systems comprise a highly important and organized set of interacting proteins that together connect and coordinate physiological responses to multiple stressors experienced during an organism’s lifespan. To illustrate this important functional intersection in an unbiased manner, we employed latent semantic analysis [247,248] of biomedical text corpora (extracted from all available public texts at PubMed Central) using interrogator text terms associated with GPCR or DDR signaling systems (Table S1). This biomedical text interrogation yields protein lists with a measurable extent of scientific text association (cosine similarity score: ranging from 0.1 for the lowest to 1.0 for the strongest associations: [249]) between the interrogator terms and the identified proteins. To refine these GPCR- or DDR-associated proteins, we extracted the 95% percentile most strongly associated proteins (Table S2, GPCR; Table S3, DDR). To investigate the functional crossovers between these unbiased protein lists, we cross-interrogated the GPCR-associated protein list (Table S2) with the DDR interrogator terms (Table S1); this generated the protein list detailed in Table S4. In addition, we also cross-interrogated the DDR-associated protein list (Table S3) with the GPCR interrogator terms (Table S1), generating the protein list detailed in Table S5. This protocol therefore generated a list of proteins, identified using unbiased informatic text analysis, linking both GPCR and DDR systems (Figure 1A). For illustrative purposes, we created a wordcloud using 20 proteins from the DDR term interrogation of the GPCR list (Table S4, blue text) and 20 proteins from the GPCR term interrogation of the DDR list (Table S5, red text). In the resulting wordcloud (Figure 1B), the protein term size is proportional to the cumulative cosine similarity score (indicative of strength of GPCR/DDR association) for this protein. Within this cloud, many of the factors discussed in this review are evident (e.g., RXFP3, HCAR1, PARP, FANCA, etc.); details of the protein descriptions of these GPCR-DDR intersection factors are outlined in Table S6 (GPCR list, blue) and S7 (DDR list, red). In addition to this unbiased interaction between GPCR and DDR systems, we also employed canonical signaling pathway analysis (ingenuity pathway analysis (IPA)) of the combined protein lists from Tables S4 and S5. From this pathway-based annotation, a list of significantly regulated signaling cascades was generated (Table S8). Plotting the intersection (Figure 1C) between pathways that share the same proteins (>2 common factors) revealed that multiple connections were present between DDR-associated signaling (red) and GPCR-associated signaling (blue) systems. Therefore, using entirely unbiased semantic analysis of publicly-available biomedical texts, the viability of our posit that these two crucial signaling systems are functionally interconnected has been shown.
With a more advanced understanding of the therapeutically-tractable points of intersection between these two systems, it might be possible to create a novel series of drug-based strategies rationally to regulate genomic stability and the aging process. These multifunctional GPCR-DDR controllers may likely demonstrate the capacity to retard the onset of major debilitating age-associated diseases. It has been demonstrated over several decades that perhaps the most effective mechanism of drug development lies in the exploitation of GPCR signaling systems. Research into the nuances of GPCR signaling have revealed the potential for new avenues of therapeutic discovery based on the selective regulation of GPCR signaling. Historically, some of the earliest theories of GPCR signaling considered that the receptor exists in a simple two-state equilibrium between “on” or “off” states distinguished by their ability to trigger downstream responses [250]. Further advancement of this concept, via the creation of constitutively active mutant receptors, led to the widely accepted ternary and extended ternary complex models of GPCR activation [251,252]. Within these models, the mechanisms by which complex ligand signaling behaves could be better appreciated, i.e., stimulating GPCR ligands could alter this equilibrium in different ways and hence were classified as agonists, partial agonists, inverse agonists and antagonists [103,253]. Agonists provoke a maximal response of the GPCR, whereas partial agonists generate a submaximal response at saturating ligand concentrations. Classical antagonists were considered to simply lack all receptor efficacy, yet among these agents, many were found to possess inverse agonist activity, i.e., the ability to attenuate basal G protein activation status. Such simple ligand/drug classification has largely been relegated to historical interest since the advent of the demonstration of multiple signaling system coupling, ligand bias/agonist trafficking and non-G protein-dependent GPCR signaling [12,103,107,253]. Therefore, it is clear that with respect to GPCR signaling classification, there is likely to be a broad spectrum of multiple ‘on’ states at all times. It is our proposal that after protein translation and membrane insertion, that a single GPCR is never ‘off’ or inactive. In this paradigm, depending on the nature and type of GPCR receptorsomes present in the cell, ligands/drugs will possess an ability to stabilize/de-stabilize a percentage of these multiple ‘on’ states to mediate their cellular activity [106]. In addition to possessing this ‘spectrum’ functionality of signaling, the subcellular localization aspect of GPCR signaling has a profound impact upon future drug design, especially with respect to the molecular intersection between GPCR and DDR realms. Much of our knowledge of GPCR signaling is concerned with the analysis of ligand-dependent signals that emanate from stimulated cell surface receptors [254]; here, the activated receptors (stimulated via ligand stimulation or constitutive basal activation) can elicit a broad range of cellular responses depending on receptorsome formation and eventual subcellular trafficking or desensitization. This plasma membrane-focused signaling paradigm we can describe as ‘Model 1′ signaling. However, considerable emerging data suggest that actively signaling GPCRs are not solely associated with the plasma membrane. Instead, GPCR signaling can also emanate from various intracellular membrane structures and can display distinct signaling features such as diverse receptorsome structures, altered lipid environments or differential ‘stimulator’ sensitivities [113,121,255,256,257]. While the classical perspective that GPCRs can be activated at the plasma membrane and subsequently be transported to the intracellular membranes (Model 1) still holds true, it is now evident that GPCRs can be activated at intracellular membranes through intracellularly-synthesized stimulators, as well as membrane-permeable or even endocytosed receptor ligands [256]. To allow this intracellular signaling, it might be necessary that GPCRs are atypically inserted in the intracellular membranes [255] to allow cytoplasmic ligand/stimulator interactions [255]. In this case, GPCRs may be able to function as intracellular stress sensors, e.g., for ROS or lactate, and signal from inside the cell to the outside or to other cellular compartments; this differential signaling behavior we have codified as ‘Model 2′ signaling. It is interesting to note that the majority of our receptor activation theories (as well as drug design strategies) have been entirely based upon the Model 1 concept. In addition, our molecular and structural appreciation of GPCR activation has also been driven from a Model 1-biased standpoint. One widely investigated aspect of Model 1 signaling is the well-characterized rhodopsin-like receptor transmembrane helix 3 Asp-Arg-Tyr (DRY) motif [258] that is thought to control agonist-induced conformational changes in the receptor. Naturally occurring receptor mutations in the DRY-motif are considered to disrupt normal G protein-dependent signaling in rhodopsin-like GPCRs and increase the amount of intracellularly-retained receptor [259]. Does this specific combination of events then pre-dispose such mutated receptor forms to adopt a propensity for Model 2 signaling? If so, then perhaps a re-adjustment of our concepts of receptor activation and ligand sensitivity will be important to potentially exploit the presence of these intracellular Model 2 receptors. A more thorough study of such Model 2 receptors may represent an important resource to identify potential GPCR sensors of damage that can then synergize productively with the DDR machinery to reduce age/metabolism-dependent DNA damage.

5. Conclusions

Taken together, our aggregated findings suggest that multiple components of the GPCR signaling system can modulate the activity of signaling proteins directly or indirectly involved in DNA damage and/or repair. As such, GPCR signaling systems may represent multifunctional sensors for DNA damaging insults, and their rational exploitation via novel drug design may facilitate our ability to augment DNA repair processes therapeutically. Thus, GPCR systems may have long evolved side-by-side with emerging DDR systems to act as sensors, and ameliorative effectors, for intracellular DNA damage and age-related stresses.

Supplementary Materials

Supplementary materials can be found at

Author Contributions

Writing-Reviewing & Editing, H.L., J.v.G., J.O.H., P.S.-O., B.M. and S.M.; Visualization, S.M.; Supervision, S.M.; Project Administration, S.M.; Funding Acquisition, J.v.G., J.O.H. and S.M.


This research was funded by the FWO-OP/Odysseus program #42/FA010100/32/6484, the University of Antwerp GOA (Geconcerteerde onderzoeksacties) Program #33931, the FWO Travelling Fellowship Program #V4.161.17N and the EU Erasmus+ training program.

Conflicts of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


  1. Van Dijk, G.; van Heijningen, S.; Reijne, A.C.; Nyakas, C.; van der Zee, E.A.; Eisel, U.L. Integrative neurobiology of metabolic diseases, neuroinflammation, and neurodegeneration. Front. Neurosci. 2015, 9, 1–19. [Google Scholar] [CrossRef] [PubMed]
  2. World Report on Ageing and Health. Available online: (accessed on 30 September 2015).
  3. Nkuipou-Kenfack, E.; Koeck, T.; Mischak, H.; Pich, A.; Schanstra, J.P.; Zürbig, P.; Schumacher, B. Proteome analysis in the assessment of ageing. Ageing Res. Rev. 2014, 18, 74–85. [Google Scholar] [CrossRef] [PubMed]
  4. Redman, L.M.; Smith, S.R.; Burton, J.H.; Martin, C.K.; Il’yasova, D.; Ravussin, E. Metabolic Slowing and Reduced Oxidative Damage with Sustained Caloric Restriction Support the Rate of Living and Oxidative Damage Theories of Aging. Cell Metab. 2018, 27, 805–815. [Google Scholar] [CrossRef] [PubMed]
  5. Colman, R.J.; Beasley, T.M.; Kemnitz, J.W.; Johnson, S.C.; Weindruch, R.; Anderson, R.M. Caloric restriction reduces age-related and all-cause mortality in rhesus monkeys. Nat. Commun. 2014, 5, 3557. [Google Scholar] [CrossRef] [PubMed]
  6. Colman, R.J.; Anderson, R.M.; Johnson, S.C.; Kastman, E.K.; Kosmatka, K.J.; Beasley, T.M.; Allison, D.B.; Cruzen, C.; Simmons, H.A.; Kemnitz, J.W.; et al. Caloric restriction delays disease onset and mortality in rhesus monkeys. Science 2009, 325, 201–204. [Google Scholar] [CrossRef] [PubMed]
  7. López-Otín, C.; Blasco, M.A.; Partridge, L.; Serrano, M.; Kroemer, G. The hallmarks of aging. Cell 2013, 153, 1194–1217. [Google Scholar] [CrossRef] [PubMed]
  8. Chadwick, W.; Martin, B.; Chapter, M.C.; Park, S.-S.; Wang, L.; Daimon, C.M.; Brenneman, R.; Maudsley, S. GIT2 Acts as a Potential Keystone Protein in Functional Hypothalamic Networks Associated with Age-Related Phenotypic Changes in Rats. PLoS ONE 2012, 7, e36975. [Google Scholar] [CrossRef] [PubMed]
  9. Pan, M.-R.; Li, K.; Lin, S.Y.; Hung, W.C. Connecting the Dots: From DNA Damage and Repair to Aging. Int. J. Mol. Sci. 2016, 17, 685. [Google Scholar] [CrossRef] [PubMed]
  10. Overington, J.P.; Al-Lazikani, B.; Hopkins, A.L. How many drug targets are there? Nat. Rev. Drug Discov. 2006, 5, 993–996. [Google Scholar] [CrossRef] [PubMed]
  11. Hauser, A.S.; Attwood, M.M.; Rask-Andersen, M.; Schiöth, H.B.; Gloriam, D.E. Trends in GPCR drug discovery: New agents, targets and indications. Nat. Rev. Drug Discov. 2017, 16, 829–842. [Google Scholar] [CrossRef] [PubMed]
  12. Luttrell, L.M.; Ferguson, S.S.; Daaka, Y.; Miller, W.E.; Maudsley, S.; Della Rocca, G.J.; Lin, F.; Kawakatsu, H.; Owada, K.; Luttrell, D.K.; et al. Beta-arrestin-dependent formation of beta2 adrenergic receptor-Src protein kinase complexes. Science 1999, 283, 655–661. [Google Scholar] [CrossRef] [PubMed]
  13. Maudsley, S.; Martin, B.; Janssens, J.; Etienne, H.; Jushaj, A.; van Gastel, J.; Willemsen, A.; Chen, H.; Gesty-Palmer, D.; Luttrell, L.M. Informatic deconvolution of biased GPCR signaling mechanisms from in vivo pharmacological experimentation. Methods 2016, 92, 51–63. [Google Scholar] [CrossRef] [PubMed][Green Version]
  14. Maudsley, S.; Martin, B.; Gesty-Palmer, D.; Cheung, H.; Johnson, C.; Patel, S.; Becker, K.G.; Wood, W.H., 3rd; Zhang, Y.; Lehrmann, E.; et al. Delineation of a Conserved Arrestin-Biased Signaling Repertoire In Vivo. Mol. Pharmacol. 2015, 87, 706–717. [Google Scholar] [CrossRef] [PubMed][Green Version]
  15. Madabhushi, R.; Pan, L.; Tsai, L.H. DNA damage and its links to neurodegeneration. Neuron 2014, 83, 266–282. [Google Scholar] [CrossRef] [PubMed]
  16. Chow, H.M.; Herrup, K. Genomic integrity and the ageing brain. Nat. Rev. Neurosci. 2015, 16, 672–684. [Google Scholar] [CrossRef] [PubMed]
  17. Ishida, T.; Ishida, M.; Tashiro, S.; Yoshizumi, M.; Kihara, Y. Role of DNA damage in cardiovascular disease. Circ. J. 2014, 8, 42–50. [Google Scholar] [CrossRef]
  18. Dobbelstein, M.; Sorensen, C.S. Exploiting replicative stress to treat cancer. Nat. Rev. Drug Discov. 2015, 14, 405–423. [Google Scholar] [CrossRef] [PubMed]
  19. De, I.; Dogra, N.; Singh, S. The Mitochondrial Unfolded Protein Response: Role in Cellular Homeostasis and Disease. Curr. Mol. Med. 2017, 17, 587–597. [Google Scholar] [CrossRef] [PubMed]
  20. Chung, J.H. The role of DNA-PK in aging and energy metabolism. FEBS J. 2018, 285, 1959–1972. [Google Scholar] [CrossRef] [PubMed]
  21. Awate, S.; Brosh, R.M., Jr. Interactive Roles of DNA Helicases and Translocases with the Single-Stranded DNA Binding Protein RPA in Nucleic Acid Metabolism. Int. J. Mol. Sci. 2017, 18, 1233. [Google Scholar] [CrossRef] [PubMed]
  22. Honda, Y.; Honda, S. The daf-2 gene network for longevity regulates oxidative stress resistance and Mn-superoxide dismutase gene expression in Caenorhabditis elegans. FASEB J. 1999, 13, 1385–1393. [Google Scholar] [CrossRef] [PubMed]
  23. Orr, W.C.; Sohal, R.S. Extension of lifespan by overexpression of superoxide dismutase and catalase in Drosophila melanogaster. Science 1994, 263, 1128–1130. [Google Scholar] [CrossRef] [PubMed]
  24. Lin, Y.J.; Seroude, L.; Benzer, S. Extended life-span and stress resistance in the drosophila mutant methuselah. Science 1998, 282, 943–946. [Google Scholar] [CrossRef] [PubMed]
  25. Lee, C.K.; Klopp, R.G.; Weindruch, R.; Prolla, T.A. Gene expression profile of aging and its retardation by caloric restriction. Science 1999, 285, 1390–1393. [Google Scholar] [CrossRef] [PubMed]
  26. Holzenberger, M.; Dupont, J.; Ducos, B.; Leneuve, P.; Géloën, A.; Even, P.C.; Cervera, P.; Le Bouc, Y. IGF-1 receptor regulates lifespan and resistance to oxidative stress in mice. Nature 2003, 421, 182–187. [Google Scholar] [CrossRef] [PubMed]
  27. Johnson, J.B.; Summer, W.; Cutler, R.G.; Martin, B.; Hyun, D.H.; Dixit, V.D.; Pearson, M.; Nassar, M.; Telljohann, R.; Maudsley, S.; et al. Alternate day calorie restriction improves clinical findings and reduces markers of oxidative stress and inflammation in overweight adults with moderate asthma. Free Radic. Biol. Med. 2007, 42, 665–674. [Google Scholar] [CrossRef] [PubMed][Green Version]
  28. Carlson, O.; Martin, B.; Stote, K.S.; Golden, E.; Maudsley, S.; Najjar, S.S.; Ferrucci, L.; Ingram, D.K.; Longo, D.L.; Rumpler, W.V.; et al. Impact of reduced meal frequency without caloric restriction on glucose regulation in healthy, normal-weight middle-aged men and women. Metabolism 2007, 56, 1729–1734. [Google Scholar] [CrossRef] [PubMed][Green Version]
  29. Barzilai, N.; Huffman, D.M.; Muzumdar, R.H.; Bartke, A. The critical role of metabolic pathways in aging. Diabetes 2012, 61, 1315–1322. [Google Scholar] [CrossRef] [PubMed]
  30. Tangvarasittichai, S. Oxidative stress, insulin resistance, dyslipidemia and type 2 diabetes mellitus. World J. Diabetes 2015, 6, 456–480. [Google Scholar] [CrossRef] [PubMed]
  31. Terman, A. Catabolic insufficiency and aging. Ann. N. Y. Acad. Sci. 2006, 1067, 27–36. [Google Scholar] [CrossRef] [PubMed]
  32. Daum, B.; Walter, A.; Horst, A.; Osiewacz, H.D.; Kühlbrandt, W. Age-dependent dissociation of ATP synthase dimers and loss of inner-membrane cristae in mitochondria. Proc. Natl. Acad. Sci. USA 2013, 110, 15301–15306. [Google Scholar] [CrossRef] [PubMed][Green Version]
  33. Brownlee, M. The pathobiology of diabetic complications: A unifying mechanism. Diabetes 2005, 54, 1615–1625. [Google Scholar] [CrossRef] [PubMed]
  34. Giacco, F.; Brownlee, M. Oxidative stress and diabetic complications. Circ. Res. 2107, 2010, 1058–1070. [Google Scholar] [CrossRef] [PubMed]
  35. Niccoli, T.; Partridge, L. Ageing as a risk factor for disease. Curr. Biol. 2012, 22, R741–R752. [Google Scholar] [CrossRef] [PubMed]
  36. Viña, J.; Borras, C.; Abdelaziz, K.M.; Garcia-Valles, R.; Gomez-Cabrera, M.C. The free radical theory of aging revisited: The cell signaling disruption theory of aging. Antioxid. Redox Signal 2013, 19, 779–787. [Google Scholar] [CrossRef] [PubMed]
  37. Chadwick, W.; Zhou, Y.; Park, S.S.; Wang, L.; Mitchell, N.; Stone, M.D.; Becker, K.G.; Martin, B.; Maudsley, S. Minimal Peroxide Exposure of Neuronal Cells Induces Multifaceted Adaptive Responses. PLoS ONE 2010, 5, e14352. [Google Scholar] [CrossRef] [PubMed]
  38. Rodriguez-Rocha, H.; Garcia-Garcia, A.; Panayiotidis, M.I.; Franco, R. DNA damage and autophagy. Mutat. Res. 2011, 711, 158–166. [Google Scholar] [CrossRef] [PubMed][Green Version]
  39. Zhou, B.B.; Elledge, S.J. The DNA damage response: Putting checkpoints in perspective. Nature 2000, 408, 433–439. [Google Scholar] [CrossRef] [PubMed]
  40. Seviour, E.G.; Lin, S.Y. The DNA damage response: Balancing the scale between cancer and ageing. Aging 2010, 2, 900–907. [Google Scholar] [CrossRef] [PubMed][Green Version]
  41. Ciccia, A.; Elledge, S.J. The DNA damage response: Making it safe to play with knives. Mol. Cell 2010, 40, 179–204. [Google Scholar] [CrossRef] [PubMed]
  42. Ambekar, S.S.; Hattur, S.S.; Bule, P.B. DNA: Damage and Repair Mechanisms in Humans. Glob. J. Pharm. Pharm. Sci. 2017, 3, 555613. [Google Scholar]
  43. David, S.S.; O’Shea, V.L.; Kundu, S. Base-excision repair of oxidative DNA damage. Nature 2007, 447, 941–950. [Google Scholar] [CrossRef] [PubMed][Green Version]
  44. Sancar, A.; Lindsey-Boltz, L.A.; Ünsal-Kaçmaz, K.; Linn, S. Molecular Mechanisms of Mammalian DNA Repair and the DNA Damage Checkpoints. Annu. Rev. Biochem. 2004, 73, 39–85. [Google Scholar] [CrossRef] [PubMed]
  45. Hegde, M.L.; Hazra, T.K.; Mitra, S. Early steps in the DNA base excision/single-strand interruption repair pathway in mammalian cells. Cell Res. 2008, 18, 27–47. [Google Scholar] [CrossRef] [PubMed][Green Version]
  46. Shrivastav, M.; De Haro, L.P.; Nickoloff, J.A. Regulation of DNA double-strand break repair pathway choice. Cell Res. 2008, 18, 134–147. [Google Scholar] [CrossRef] [PubMed]
  47. Shen, Z.; Nickoloff, J.A. DNA Repair, Genetic Instability, and Cancer; World Scientific: River Edge, NJ, USA, 2007; pp. 119–156. [Google Scholar] [CrossRef]
  48. Jasin, M.; Rothstein, R. Repair of strand breaks by homologous recombination. Cold Spring Harb. Perspect. Biol. 2013, 5, a012740. [Google Scholar] [CrossRef] [PubMed]
  49. Mari, P.-O.; Florea, B.I.; Persengiev, S.P.; Verkaik, N.S.; Brüggenwirth, H.T.; Modesti, M.; Giglia-Mari, G.; Bezstarosti, K.; Demmers, J.A.; Luider, T.M.; et al. Dynamic assembly of end-joining complexes requires interaction between Ku70/80 and XRCC4. Proc. Natl. Acad. Sci. USA 2006, 103, 18597–18602. [Google Scholar] [CrossRef] [PubMed][Green Version]
  50. Davis, A.J.; Chen, D.J. DNA double strand break repair via non-homologous end-joining. Transl. Cancer Res. 2013, 2, 130–143. [Google Scholar] [PubMed]
  51. Aubert, G.; Lansdorp, P.M. Telomeres and Aging. Physiol. Rev. 2008, 88, 557–579. [Google Scholar] [CrossRef] [PubMed]
  52. Greider, C.W. Telomeres. Curr. Opin. Cell Biol. 1991, 3, 444–451. [Google Scholar] [CrossRef]
  53. De Lange, T. Shelterin: The protein complex that shapes and safeguards human telomeres. Genes Dev. 2005, 19, 2100–2110. [Google Scholar] [CrossRef] [PubMed]
  54. Harley, C.B.; Futcher, A.B.; Greider, C.W. Telomeres shorten during ageing of human fibroblasts. Nature 1990, 345, 458–460. [Google Scholar] [CrossRef] [PubMed]
  55. Barnes, R.P.; Fouquerel, E.; Opresko, P.L. The impact of oxidative DNA damage and stress on telomere homeostasis. Mech. Ageing Dev. 2018. pii:S0047-6374(18)30052-6. [Google Scholar] [CrossRef] [PubMed]
  56. Reichert, S.; Stier, A. Does oxidative stress shorten telomeres in vivo? A review. Biol. Lett. 2017, 13, 20170463. [Google Scholar] [CrossRef] [PubMed]
  57. Kliment, C.R.; Oury, T.D. Oxidative stress, extracellular matrix targets, and idiopathic pulmonary fibrosis. Free Radic. Biol. Med. 2010, 49, 707–717. [Google Scholar] [CrossRef] [PubMed]
  58. Graham, M.K.; Meeker, A. Telomeres and telomerase in prostate cancer development and therapy. Nat. Rev. Urol. 2017, 14, 607–619. [Google Scholar] [CrossRef] [PubMed][Green Version]
  59. Jurk, D.; Wilson, C.; Passos, J.F.; Oakley, F.; Correia-Melo, C.; Greaves, L.; Saretzki, G.; Fox, C.; Lawless, C.; Anderson, R.; et al. Chronic inflammation induces telomere dysfunction and accelerates ageing in mice. Nat. Commun. 2014, 2, 4172. [Google Scholar] [CrossRef] [PubMed]
  60. Cattan, V.; Mercier, N.; Gardner, J.P.; Regnault, V.; Labat, C.; Maki-Jouppila, J.; Nzietchueng, R.; Benetos, A.; Kimura, M.; et al. Chronic oxidative stress induces a tissue-specific reduction in telomere length in CAST/Ei mice. Free Radic. Biol. Med. 2008, 44, 1592–1598. [Google Scholar] [CrossRef] [PubMed]
  61. Kaul, Z.; Cesare, A.J.; Huschtscha, L.I.; Neumann, A.A.; Reddel, R.R. Five dysfunctional telomeres predict onset of senescence in human cells. EMBO Rep. 2012, 13, 52–59. [Google Scholar] [CrossRef] [PubMed]
  62. Shay, J.W. Role of Telomeres and Telomerase in Aging and Cancer. Cancer Discov. 2016, 6, 584–593. [Google Scholar] [CrossRef] [PubMed][Green Version]
  63. Lidzbarsky, G.; Gutman, D.; Shekhidem, H.A.; Sharvit, L.; Atzmon, G. Genomic Instabilities, Cellular Senescence, and Aging: In Vitro, In Vivo and Aging-Like Human Syndromes. Front. Med. 2018, 5, 104. [Google Scholar] [CrossRef] [PubMed]
  64. Von Zglinicki, T. Oxidative stress shortens telomeres. Trends Biochem. Sci. 2002, 27, 339–344. [Google Scholar] [CrossRef]
  65. Caux, F.; Dubosclard, E.; Lascols, O.; Buendia, B.; Chazouilleres, O.; Cohen, A.; Courvalin, J.C.; Laroche, L.; Capeau, J.; Vigouroux, C.; et al. A new clinical condition linked to a novel mutation in lamins A and C with generalized lipoatrophy, insulin-resistant diabetes, disseminated leukomelanodermic papules, liver steatosis, and cardiomyopathy. J. Clin. Endocrinol. Metab. 2003, 88, 1006–1013. [Google Scholar] [CrossRef] [PubMed]
  66. Nishioka, M.; Kamei, S.; Kinoshita, T.; Sanada, J.; Fushimi, Y.; Irie, S.; Hirata, Y.; Tanabe, A.; Hirukawa, H.; Kimura, T.; et al. Werner Syndrome and Diabetes Mellitus Accompanied by Adrenal Cortex Cancer. Intern. Med. 2017, 56, 1987–1992. [Google Scholar] [CrossRef] [PubMed][Green Version]
  67. Okamoto, M.; Okamoto, M.; Yamada, K.; Yoshimasa, Y.; Kosaki, A.; Kono, S.; Inoue, G.; Maeda, I.; Kubota, M.; Hayashi, T.; et al. Insulin resistance in Werner’s syndrome. Mech. Ageing Dev. 1992, 63, 11–25. [Google Scholar] [CrossRef]
  68. Hayashi, A.; Takemoto, M.; Shoji, M.; Hattori, A.; Sugita, K.; Yokote, K. Pioglitazone improves fat tissue distribution and hyperglycemia in a case of cockayne syndrome with diabetes. Diabetes Care 2015, 38, e76. [Google Scholar] [CrossRef] [PubMed]
  69. Schalch, D.S.; McFarlin, D.E.; Barlow, M.H. An unusual form of diabetes mellitus in ataxia telangiectasia. N. Engl. J. Med. 1970, 282, 1396–1402. [Google Scholar] [CrossRef] [PubMed]
  70. Bar, R.S.; Levis, W.R.; Rechler, M.M.; Harrison, L.C.; Siebert, C.; Podskalny, J.; Roth, J.; Muggeo, M. Extreme insulin resistance in ataxia telangiectasia: Defect in affinity of insulin receptors. N. Engl. J. Med. 1978, 298, 1164–1171. [Google Scholar] [CrossRef] [PubMed]
  71. Arellanes-Licea, E.; Caldelas, I.; De Ita-Pérez, D.; Díaz-Muñoz, M. The circadian timing system: A recent addition in the physiological mechanisms underlying pathological and aging processes. Aging Dis. 2014, 5, 406–418. [Google Scholar] [PubMed]
  72. Kang, T.-H.; Reardon, J.T.; Kemp, M.; Sancar, A. Circadian oscillation of nucleotide excision repair in mammalian brain. Proc. Natl. Acad. Sci. USA 2009, 106, 2864–2867. [Google Scholar] [CrossRef] [PubMed][Green Version]
  73. Reppert, S.M.; Weaver, D.R. Coordination of circadian timing in mammals. Nature 2002, 418, 935–941. [Google Scholar] [CrossRef] [PubMed]
  74. Panda, S.; Hogenesch, J.B.; Kay, S.A. Circadian rhythms from flies to human. Nature 2002, 417, 329–335. [Google Scholar] [CrossRef] [PubMed]
  75. Uchida, Y.; Hirayama, J.; Nishina, H. A Common Origin: Signaling Similarities in the Regulation of the Circadian Clock and DNA Damage Responses. Biol. Pharm. Bull. 2010, 33, 535–544. [Google Scholar] [CrossRef] [PubMed][Green Version]
  76. Ohta, Y.; Taguchi, A.; Matsumura, T.; Nakabayashi, H.; Akiyama, M.; Yamamoto, K.; Fujimoto, R.; Suetomi, R.; Yanai, A.; Shinoda, K.; et al. Clock Gene Dysregulation Induced by Chronic ER Stress Disrupts β-cell Function. EBioMedicine 2017, 18, 146–156. [Google Scholar] [CrossRef] [PubMed]
  77. Ingenwerth, M.; Reinbeck, A.L.; Stahr, A.; Partke, H.J.; Roden, M.; Burkart, V.; von Gall, C. Perturbation of the molecular clockwork in the SCN of non-obese diabetic mice prior to diabetes onset. Chronobiol. Int. 2016, 33, 1369–1375. [Google Scholar] [CrossRef] [PubMed]
  78. Saini, C.; Petrenko, V.; Pulimeno, P.; Giovannoni, L.; Berney, T.; Hebrok, M.; Howald, C.; Dermitzakis, E.T.; Dibner, C. A functional circadian clock is required for proper insulin secretion by human pancreatic islet cells. Diabetes Obes. Metab. 2016, 18, 355–365. [Google Scholar] [CrossRef] [PubMed]
  79. Sato, F.; Kohsaka, A.; Bhawal, U.K.; Muragaki, Y. Potential Roles of Dec and Bmal1 Genes in Interconnecting Circadian Clock and Energy Metabolism. Int. J. Mol. Sci. 2018, 19, 781. [Google Scholar] [CrossRef] [PubMed]
  80. Krishnaiah, S.Y.; Wu, G.; Altman, B.J.; Growe, J.; Rhoades, S.D.; Coldren, F.; Venkataraman, A.; Olarerin-George, A.O.; Francey, L.J.; Mukherjee, S.; et al. Clock Regulation of Metabolites Reveals Coupling between Transcription and Metabolism. Cell Metab. 2017, 25, 961–974. [Google Scholar] [CrossRef] [PubMed]
  81. Liu, F.; Chang, H.C. Physiological links of circadian clock and biological clock of aging. Protein Cell 2017, 8, 477–488. [Google Scholar] [CrossRef] [PubMed][Green Version]
  82. Tevy, M.F.; Giebultowicz, J.; Pincus, Z.; Mazzoccoli, G.; Vinciguerra, M. Aging signaling pathways and circadian clock-dependent metabolic derangements. Trends Endocrinol. Metab. 2013, 24, 229–237. [Google Scholar] [CrossRef] [PubMed][Green Version]
  83. Kohsaka, A.; Laposky, A.D.; Ramsey, K.M.; Estrada, C.; Joshu, C.; Kobayashi, Y.; Turek, F.W.; Bass, J. High-Fat Diet Disrupts Behavioral and Molecular Circadian Rhythms in Mice. Cell Metab. 2007, 6, 414–421. [Google Scholar] [CrossRef] [PubMed][Green Version]
  84. Ando, H.; Yanagihara, H.; Hayashi, Y.; Obi, Y.; Tsuruoka, S.; Takamura, T.; Kaneko, S.; Fujimura, A. Rhythmic messenger ribonucleic acid expression of clock genes and adipocytokines in mouse visceral adipose tissue. Endocrinology 2005, 146, 5631–5636. [Google Scholar] [CrossRef] [PubMed]
  85. Chang, H.C.; Guarente, L. SIRT1 mediates central circadian control in the SCN by a mechanism that decays with aging. Cell 2013, 153, 1448–1460. [Google Scholar] [CrossRef] [PubMed]
  86. Bee, L.; Marini, S.; Pontarin, G.; Ferraro, P.; Costa, R.; Albrecht, U.; Celotti, L. Nucleotide excision repair efficiency in quiescent human fibroblasts is modulated by circadian clock. Nucleic Acids Res. 2015, 43, 2126–2137. [Google Scholar] [CrossRef] [PubMed][Green Version]
  87. Im, J.-S.; Jung, B.-H.; Kim, S.-E.; Lee, K.-H.; Lee, J.-K. Per3, a circadian gene, is required for Chk2 activation in human cells. FEBS Lett. 2010, 584, 4731–4734. [Google Scholar] [CrossRef] [PubMed][Green Version]
  88. Kim, H.; Lee, J.M.; Lee, G.; Bhin, J.; Oh, S.K.; Kim, K.; Pyo, K.E.; Lee, J.S.; Yim, H.Y.; Kim, K.I.; et al. DNA Damage-Induced RORα Is Crucial for p53 Stabilization and Increased Apoptosis. Mol. Cell 2011, 44, 797–810. [Google Scholar] [CrossRef] [PubMed]
  89. Geyfman, M.; Kumar, V.; Liu, Q.; Ruiz, R.; Gordon, W.; Espitia, F.; Cam, E.; Millar, S.E.; Smyth, P.; Ihler, A. Brain and muscle Arnt-like protein-1 (BMAL1) controls circadian cell proliferation and susceptibility to UVB-induced DNA damage in the epidermis. Proc. Natl. Acad. Sci. USA 2012, 109, 11758–11763. [Google Scholar] [CrossRef] [PubMed][Green Version]
  90. Collis, S.J.; Boulton, S.J. Emerging links between the biological clock and the DNA damage response. Chromosoma 2007, 116, 331–339. [Google Scholar] [CrossRef] [PubMed]
  91. Kagawa, Y. From clock genes to telomeres in the regulation of the healthspan. Nutr. Rev. 2012, 70, 459–471. [Google Scholar] [CrossRef] [PubMed]
  92. Khapre, R.V.; Samsa, W.E.; Kondratov, R.V. Circadian regulation of cell cycle: Molecular connections between aging and the circadian clock. Ann. Med. 2010, 42, 404–415. [Google Scholar] [CrossRef] [PubMed]
  93. Musiek, E.S.; Lim, M.M.; Yang, G.; Bauer, A.Q.; Qi, L.; Lee, Y.; Roh, J.H.; Ortiz-Gonzalez, X.; Dearborn, J.T.; Culver, J.P.; et al. Circadian clock proteins regulate neuronal redox homeostasis and neurodegeneration. J. Clin. Investig. 2013, 123, 5389–5400. [Google Scholar] [CrossRef] [PubMed][Green Version]
  94. Hood, S.; Amir, S. Neurodegeneration and the Circadian Clock. Front. Aging Neurosci. 2017, 9, 170. [Google Scholar] [CrossRef] [PubMed]
  95. Pagano, E.S.; Spinedi, E.; Gagliardino, J.J. At the Cutting Edge White Adipose Tissue and Circadian Rhythm Dysfunctions in Obesity: Pathogenesis and Available Therapies. Neuroendocrinology 2017, 104, 347–363. [Google Scholar] [CrossRef] [PubMed]
  96. Kowalska, E.; Ripperger, J.A.; Hoegger, D.C.; Bruegger, P.; Buch, T.; Birchler, T.; Mueller, A.; Albrecht, U.; Contaldo, C.; Brown, S.A. NONO couples the circadian clock to the cell cycle. Proc. Natl. Acad. Sci. USA 2013, 110, 1592–1599. [Google Scholar] [CrossRef] [PubMed]
  97. Vaziri, H.; West, M.D.; Allsopp, R.C.; Davison, T.S.; Wu, Y.S.; Arrowsmith, C.H.; Poirier, G.G.; Benchimol, S. ATM-dependent telomere loss in aging human diploid fibroblasts and DNA damage lead to the post-translational activation of p53 protein involving poly(ADP-ribose) polymerase. EMBO J. 1997, 16, 6018–6033. [Google Scholar] [CrossRef] [PubMed][Green Version]
  98. Chaudhari, A.; Gupta, R.; Makwana, K.; Kondratov, R. Circadian clocks, diets and aging. Nutr. Heal. Aging 2017, 4, 101–112. [Google Scholar] [CrossRef] [PubMed][Green Version]
  99. He, B.; Nohara, K.; Park, N.; Park, Y.S.; Guillory, B.; Zhao, Z.; Garcia, J.M.; Koike, N.; Lee, C.C.; Takahashi, J.S. The Small Molecule Nobiletin Targets the Molecular Oscillator to Enhance Circadian Rhythms and Protect against Metabolic Syndrome. Cell Metab. 2016, 23, 610–621. [Google Scholar] [CrossRef] [PubMed]
  100. Gloston, G.F.; Yoo, S.-H.; Chen, Z.J. Clock-Enhancing Small Molecules and Potential Applications in Chronic Diseases and Aging Front. Neurol. 2017, 8, 100. [Google Scholar]
  101. Vass, M.; Kooistra, A.J.; Yang, D.; Stevens, R.C.; Wang, M.W.; de Graaf, C. Chemical Diversity in the G Protein-Coupled Receptor Superfamily. Trends Pharmacol. Sci. 2018, 39, 494–512. [Google Scholar] [CrossRef] [PubMed]
  102. Rosenbaum, D.M.; Rasmussen, S.G.; Kobilka, B.K. The structure and function of G-protein-coupled receptors. Nature 2009, 459, 356–363. [Google Scholar] [CrossRef] [PubMed][Green Version]
  103. Maudsley, S.; Martin, B.; Luttrell, L.M. The origins of diversity and specificity in g protein-coupled receptor signaling. J. Pharmacol. Exp. Ther. 2005, 314, 485–494. [Google Scholar] [CrossRef] [PubMed]
  104. Luttrell, L.M.; Gesty-Palmer, D. Beyond desensitization: Physiological relevance of arrestin-dependent signaling. Pharmacol. Rev. 2010, 62, 305–330. [Google Scholar] [CrossRef] [PubMed]
  105. Luttrell, L.M.; Kenakin, T.P. Refining efficacy: Allosterism and bias in G protein-coupled receptor signaling. Methods Mol. Biol. 2011, 756, 3–35. [Google Scholar] [PubMed]
  106. Maudsley, S.; Patel, S.A.; Park, S.S.; Luttrell, L.M.; Martin, B. Functional signaling biases in G protein-coupled receptors: Game Theory and receptor dynamics. Mini. Rev. Med. Chem. 2012, 12, 831–840. [Google Scholar] [CrossRef] [PubMed]
  107. Luttrell, L.M.; Maudsley, S.; Gesty-Palmer, D. Translating in vitro ligand bias into in vivo efficacy. Cell Signal 2018, 41, 46–55. [Google Scholar] [CrossRef] [PubMed]
  108. Liu, Y.; Yang, Y.; Ward, R.; An, S.; Guo, X.X.; Li, W.; Xu, T.R. Biased signalling: The instinctive skill of the cell in the selection of appropriate signalling pathways. Biochem. J. 2015, 470, 155–167. [Google Scholar] [CrossRef] [PubMed]
  109. Maudsley, S.; Gent, J.P.; Findlay, J.B.; Donnelly, D. The relationship between the agonist-induced activation and desensitization of the human tachykinin NK2 receptor expressed in Xenopus oocytes. Br. J. Pharmacol. 1998, 124, 675–684. [Google Scholar] [CrossRef] [PubMed]
  110. Magalhaes, A.C.; Dunn, H.; Ferguson, S.S. Regulation of GPCR activity, trafficking and localization by GPCR-interacting proteins. Br. J. Pharmacol. 2012, 165, 1717–1736. [Google Scholar] [CrossRef] [PubMed][Green Version]
  111. Hara, M.R.; Sachs, B.D.; Caron, M.G.; Lefkowitz, R.J. Pharmacological blockade of a β(2)AR-β-arrestin-1 signaling cascade prevents the accumulation of DNA damage in a behavioral stress model. Cell Cycle 2013, 12, 219–224. [Google Scholar] [CrossRef] [PubMed]
  112. Luan, B.; Zhang, Z.; Wu, Y.; Kang, J.; Pei, G. Beta-arrestin2 functions as a phosphorylation-regulated suppressor of UV-induced NF-kappaB activation. EMBO J. 2005, 24, 4237–4246. [Google Scholar] [CrossRef] [PubMed]
  113. Stäubert, C.; Schöneberg, T. GPCR Signaling From Intracellular Membranes—A Novel Concept. BioEssays 2017, 39, 1700200. [Google Scholar] [CrossRef] [PubMed]
  114. Ellisdon, A.M.; Halls, M.L. Compartmentalization of GPCR signalling controls unique cellular responses. Biochem. Soc. Trans. 2016, 44, 562–567. [Google Scholar] [CrossRef] [PubMed]
  115. Pi, M.; Nishimoto, S.K.; Quarles, L.D. GPRC6A: Jack of all metabolism (or master of none). Mol. Metab. 2016, 6, 185–193. [Google Scholar] [CrossRef] [PubMed]
  116. Reimann, F.; Gribble, F.M. G protein-coupled receptors as new therapeutic targets for type 2 diabetes. Diabetologia 2016, 59, 229–233. [Google Scholar] [CrossRef] [PubMed]
  117. Amisten, S.; Neville, M.; Hawkes, R.; Persaud, S.J.; Karpe, F.; Salehi, A. An atlas of G-protein coupled receptor expression and function in human subcutaneous adipose tissue. Pharmacol. Ther. 2015, 146, 61–93. [Google Scholar] [CrossRef] [PubMed]
  118. Hudson, B.D.; Ulven, T.; Milligan, G. The therapeutic potential of allosteric ligands for free fatty acid sensitive GPCRs. Curr. Top. Med. Chem. 2013, 13, 14–25. [Google Scholar] [CrossRef] [PubMed]
  119. Van Gastel, J.; Janssens, J.; Etienne, H.; Azmi, A.; Maudsley, S. The synergistic GIT2-RXFP3 system in the brain and its importance in age-related disorders. Front. Aging Neurosci. 2016. [Google Scholar] [CrossRef]
  120. Janssens, J.; Etienne, H.; Idriss, S.; Azmi, A.; Martin, B.; Maudsley, S. Systems-Level G Protein-Coupled Receptor Therapy Across a Neurodegenerative Continuum by the GLP-1 Receptor System. Front. Endocrinol. 2014, 5, 142. [Google Scholar] [CrossRef] [PubMed]
  121. Alemany, R.; Perona, J.S.; Sánchez-Dominguez, J.M.; Montero, E.; Cañizares, J.; Bressani, R.; Escribá, P.V.; Ruiz-Gutierrez, V. G protein-coupled receptor systems and their lipid environment in health disorders during aging. Biochim. Biophys. Acta 2007, 1768, 964–975. [Google Scholar] [CrossRef] [PubMed][Green Version]
  122. Yeo, E.J.; Jang, I.S.; Lim, H.K.; Ha, K.S.; Park, S.C. Agonist-specific differential changes of cellular signal transduction pathways in senescent human diploid fibroblasts. Exp. Gerontol. 2002, 37, 871–883. [Google Scholar] [CrossRef]
  123. Yeo, E.J.; Park, S.C. Age-dependent agonist-specific dysregulation of membrane-mediated signal transduction: Emergence of the gate theory of aging. Mech. Ageing Dev. 2002, 123, 1563–1578. [Google Scholar] [CrossRef]
  124. Hakim, M.A.; Buchholz, J.N.; Behringer, E.J. Electrical dynamics of isolated cerebral and skeletal muscle endothelial tubes: Differential roles of G-protein-coupled receptors and K+ channels. Pharmacol. Res. Perspect. 2018, 6, e00391. [Google Scholar] [CrossRef] [PubMed]
  125. Xiao, P.; Huang, X.; Huang, L.; Yang, J.; Li, A.; Shen, K.; Wedegaertner, P.B.; Jiang, X. G protein-coupled receptor kinase 4-induced cellular senescence and its senescence-associated gene expression profiling. Exp. Cell Res. 2017, 360, 273–280. [Google Scholar] [CrossRef] [PubMed]
  126. Kuilman, T.; Michaloglou, C.; Mooi, W.J.; Peeper, D.S. The essence of senescence. Genes Dev. 2010, 24, 2463–2479. [Google Scholar] [CrossRef] [PubMed][Green Version]
  127. Adams, P.D. Healing and hurting: Molecular mechanisms, functions, and pathologies of cellular senescence. Mol. Cell 2009, 36, 2–14. [Google Scholar] [CrossRef] [PubMed]
  128. Tchkonia, T.; Zhu, Y.; van Deursen, J.; Campisi, J.; Kirkland, J.L. Cellular senescence and the senescent secretory phenotype: Therapeutic opportunities. J. Clin. Investig. 2013, 123, 966–972. [Google Scholar] [CrossRef] [PubMed]
  129. Hayflick, L.; Moorhead, P.S. The serial cultivation of human diploid cell strains. Exp. Cell Res. 1961, 25, 585–621. [Google Scholar] [CrossRef]
  130. Bodnar, A.G.; Ouellette, M.; Frolkis, M.; Holt, S.E.; Chiu, C.P.; Morin, G.B.; Harley, C.B.; Shay, J.W.; Lichtsteiner, S.; Wright, W.E. Extension of life-span by introduction of telomerase into normal human cells. Science 1998, 279, 349–352. [Google Scholar] [CrossRef] [PubMed]
  131. Muñoz-Espin, D.; Cañamero, M.; Maraver, A.; Gómez-López, G.; Contreras, J.; Murillo-Cuesta, S.; Rodríguez-Baeza, A.; Varela-Nieto, I.; Ruberte, J.; Collado, M.; et al. Programmed cell senescence during mammalian embryonic development. Cell 2013, 155, 1104–1118. [Google Scholar] [CrossRef] [PubMed]
  132. Jun, J.I.; Lau, L.F. The matricellular protein CCN1 induces fibroblast senescence and restricts fibrosis in cutaneous wound healing. Nat. Cell Biol. 2010, 12, 676–685. [Google Scholar] [CrossRef] [PubMed][Green Version]
  133. Krizhanovsky, V.; Yon, M.; Dickins, R.A.; Hearn, S.; Simon, J.; Miething, C.; Yee, H.; Zender, L.; Lowe, S.W. Senescence of activated stellate cells limits liver fibrosis. Cell 2008, 134, 657–667. [Google Scholar] [CrossRef] [PubMed]
  134. Baker, D.J.; Perez-Terzic, C.; Jin, F.; Pitel, K.S.; Niederländer, N.J.; Jeganathan, K.; Yamada, S.; Reyes, S.; Rowe, L.; Hiddinga, H.J.; et al. Opposing roles for p16Ink4a and p19Arf in senescence and ageing caused by BubR1 insufficiency. Nat. Cell Biol. 2008, 10, 825–836. [Google Scholar] [CrossRef] [PubMed][Green Version]
  135. Baker, D.J.; Wijshake, T.; Tchkonia, T.; LeBrasseur, N.K.; Childs, B.G.; van de Sluis, B.; Kirkland, J.L.; van Deursen, J.M. Clearance of p16Ink4a-positive senescent cells delays ageing-associated disorders. Nature 2011, 479, 232–236. [Google Scholar] [CrossRef] [PubMed][Green Version]
  136. Nardella, C.; Clohessy, J.G.; Alimonti, A.; Pandolfi, P.P. Pro-senescence therapy for cancer treatment. Nat. Rev. Cancer 2011, 11, 503–511. [Google Scholar] [CrossRef] [PubMed]
  137. Sedelnikova, O.A.; Horikawa, I.; Zimonjic, D.B.; Popescu, N.C.; Bonner, W.M.; Barrett, J.C. Senescing human cells and ageing mice accumulate DNA lesions with unrepairable double-strand breaks. Nat. Cell Biol. 2004, 6, 168–170. [Google Scholar] [CrossRef] [PubMed]
  138. Van Deursen, J.M. The role of senescent cells in ageing. Nature 2014, 509, 439–446. [Google Scholar] [CrossRef] [PubMed][Green Version]
  139. Coppé, J.P.; Patil, C.K.; Rodier, F.; Sun, Y.; Muñoz, D.P.; Goldstein, J.; Nelson, P.S.; Desprez, P.Y.; Campisi, J. Senescence-associated secretory phenotypes reveal cell-nonautonomous functions of oncogenic RAS and the p53 tumor suppressor. PLoS Biol. 2008, 6, e301. [Google Scholar] [CrossRef] [PubMed]
  140. Shah, P.P.; Donahue, G.; Otte, G.L.; Capell, B.C.; Nelson, D.M.; Cao, K.; Aggarwala, V.; Cruickshanks, H.A.; Rai, T.S.; McBryan, T.; et al. Lamin B1depletion in senescent cells triggers large-scale changes in gene expression and the chromatin landscape. Genes Dev. 2013, 27, 1787–1799. [Google Scholar] [CrossRef] [PubMed]
  141. Zhang, H.; Pan, K.H.; Cohen, S.N. Senescence-specific gene expression fingerprints reveal cell-type-dependent physical clustering of up-regulated chromosomal loci. Proc. Natl. Acad. Sci. USA 2003, 100, 3251–3256. [Google Scholar] [CrossRef] [PubMed]
  142. Rodier, F.; Coppé, J.P.; Patil, C.K.; Hoeijmakers, W.A.; Muñoz, D.P.; Raza, S.R.; Freund, A.; Campeau, E.; Davalos, A.R.; Campisi, J. Persistent DNA damage signalling triggers senescence-associated inflammatory cytokine secretion. Nat. Cell Biol. 2009, 11, 973–979. [Google Scholar] [CrossRef] [PubMed][Green Version]
  143. Kuilman, T.; Peeper, D.S. Senescence-messaging secretome: SMS-ing cellular stress. Nat. Rev. Cancer 2009, 9, 81–94. [Google Scholar] [CrossRef] [PubMed]
  144. Passos, J.F.; Nelson, G.; Wang, C.; Richter, T.; Simillion, C.; Proctor, C.J.; Miwa, S.; Olijslagers, S.; Hallinan, J.; Wipat, A.; et al. Feedback between p21 and reactive oxygen production is necessary for cell senescence. Mol. Syst. Biol. 2010, 6, 347. [Google Scholar] [CrossRef] [PubMed]
  145. Guo, H.; Liu, Z.; Xu, B.; Hu, H.; Wei, Z.; Liu, Q.; Zhang, X.; Ding, X.; Wang, Y.; Zhao, M.; et al. Chemokine receptor CXCR2 is transactivated by p53 and induces p38-mediated cellular senescence in response to DNA damage. Aging Cell 2013, 12, 1110–1121. [Google Scholar] [CrossRef] [PubMed][Green Version]
  146. Jin, H.J.; Lee, H.J.; Heo, J.; Lim, J.; Kim, M.; Kim, M.K.; Nam, H.Y.; Hong, G.H.; Cho, Y.S.; Choi, S.J.; et al. Senescence-Associated MCP-1 Secretion Is Dependent on a Decline in BMI1 in Human Mesenchymal Stromal Cells. Antioxid Redox Signal 2016, 24, 471–485. [Google Scholar] [CrossRef] [PubMed][Green Version]
  147. Garcia-Martinez, I.; Shaker, M.E.; Mehal, W.Z. Therapeutic Opportunities in Damage-Associated Molecular Pattern-Driven Metabolic Diseases. Antioxid Redox Signal 2015, 23, 1305–1315. [Google Scholar] [CrossRef] [PubMed][Green Version]
  148. Pearl, L.H.; Schierz, A.C.; Ward, S.E.; Al-Lazikani, B.; Pearl, F.M. Therapeutic opportunities within the DNA damage response. Nat. Rev. Cancer 2015, 15, 166–180. [Google Scholar] [CrossRef] [PubMed][Green Version]
  149. Williams, D.T.; Staples, C.J. Approaches for Identifying Novel Targets in Precision Medicine: Lessons from DNA Repair. Adv. Exp. Med. Biol. 2017, 1007, 1–16. [Google Scholar] [PubMed]
  150. Gold, M. Phase II clinical trials of anti-amyloid β antibodies: When is enough, enough? Alzheimers Dement. (NY). 2017, 3, 402–409. [Google Scholar] [CrossRef] [PubMed]
  151. Janssens, J.; Lu, D.; Ni, B.; Chadwick, W.; Siddiqui, S.; Azmi, A.; Etienne, H.; Jushaj, A.; van Gastel, J.; Martin, B. Development of Precision Small-Molecule Proneurotrophic Therapies for Neurodegenerative Diseases. Vitam. Horm. 2017, 104, 263–311. [Google Scholar] [PubMed]
  152. Chadwick, W.; Mitchell, N.; Martin, B.; Maudsley, S. Therapeutic targeting of the endoplasmic reticulum in Alzheimer’s disease. Curr. Alzheimer Res. 2012, 9, 110–119. [Google Scholar] [CrossRef] [PubMed]
  153. Jacobson, K.A. New paradigms in GPCR drug discovery. Biochem. Pharmacol. 2015, 98, 541–555. [Google Scholar] [CrossRef] [PubMed][Green Version]
  154. De Pascali, F.; Reiter, E. β-arrestins and biased signalling in gonadotropin receptors. Minerva Ginecol. 2018. [Google Scholar] [CrossRef]
  155. Luttrell, L.M. Minireview: More than just a hammer: Ligand “bias” and pharmaceutical discovery. Mol. Endocrinol. 2014, 28, 281–294. [Google Scholar] [CrossRef] [PubMed]
  156. Watts, D.J.; Strogatz, S.H. Collective dynamics of ‘small-world’ networks. Nature 1998, 393, 440–442. [Google Scholar] [CrossRef] [PubMed]
  157. Martin, B.; Chadwick, W.; Janssens, J.; Premont, R.T.; Schmalzigaug, R.; Becker, K.G.; Lehrmann, E.; Wood, W.H.; Zhang, Y.; Siddiqui, S.; et al. GIT2 Acts as a Systems-Level Coordinator of Neurometabolic Activity and Pathophysiological Aging. Front. Endocrinol. 2015, 6, 191. [Google Scholar] [CrossRef] [PubMed]
  158. Han, J.D.; Bertin, N.; Hao, T.; Goldberg, D.S.; Berriz, G.F.; Zhang, L.V.; Dupuy, D.; Walhout, A.J.; Cusick, M.E.; Roth, F.P.; et al. Evidence for dynamically organized modularity in the yeast protein–protein interaction network. Nature 2004, 430, 88–93. [Google Scholar] [CrossRef] [PubMed]
  159. Walther, C.; Ferguson, S.S. Minireview: Role of intracellular scaffolding proteins in the regulation of endocrine G protein-coupled receptor signaling. Mol. Endocrinol. 2015, 29, 814–830. [Google Scholar] [CrossRef] [PubMed]
  160. Maudsley, S.; Zamah, A.M.; Rahman, N.; Blitzer, J.T.; Luttrell, L.M.; Lefkowitz, R.J.; Hall, R.A. Platelet-derived growth factor receptor association with Na(+)/H(+) exchanger regulatory factor potentiates receptor activity. Mol. Cell Biol. 2000, 20, 8352–8363. [Google Scholar] [CrossRef] [PubMed]
  161. Wang, W.; Qiao, Y.; Li, Z. New Insights into Modes of GPCR Activation. Trends Pharmacol. Sci. 2018, 39, 367–386. [Google Scholar] [CrossRef] [PubMed]
  162. Deng, W.; Wang, D.A.; Gosmanova, E.; Johnson, L.R.; Tigyi, G. LPA protects intestinal epithelial cells from apoptosis by inhibiting the mitochondrial pathway. Am. J. Physiol. Liver Physiol. 2003, 284, G821–G829. [Google Scholar] [CrossRef] [PubMed]
  163. Lin, M.E.; Herr, D.R.; Chun, J. Lysophosphatidic acid (LPA) receptors: Signaling properties and disease relevance. Prostaglandins Other Lipid Mediat. 2010, 91, 130–138. [Google Scholar] [CrossRef] [PubMed][Green Version]
  164. Deng, W.; Poppleton, H.; Yasuda, S.; Makarova, N.; Shinozuka, Y.; Wang, D.A.; Johnson, L.R.; Patel, T.B.; Tigyi, G. Optimal lysophosphatidic acid-induced DNA synthesis and cell migration but not survival require intact autophosphorylation sites of the epidermal growth factor receptor. J. Biol. Chem. 2004, 279, 47871–47880. [Google Scholar] [CrossRef] [PubMed]
  165. Chen, B.P.C.; Li, M.; Asaithamby, A. New insights into the roles of ATM and DNA-PKcs in the cellular response to oxidative stress. Cancer Lett. 2012, 327, 103–110. [Google Scholar] [CrossRef] [PubMed]
  166. Balogh, A.; Shimizu, Y.; Lee, S.C.; Norman, D.D.; Gangwar, R.; Bavaria, M.; Moon, C.; Shukla, P.; Rao, R.; Ray, R. The autotaxin-LPA2 GPCR axis is modulated by γ-irradiation and facilitates DNA damage repair. Cell Signal 2015, 27, 1751–1762. [Google Scholar] [CrossRef] [PubMed]
  167. Patil, R.; Szabó, E.; Fells, J.I.; Balogh, A.; Lim, K.G.; Fujiwara, Y.; Norman, D.D.; Lee, S.C.; Balazs, L.; Thomas, F.; et al. Combined mitigation of the gastrointestinal and hematopoietic acute radiation syndromes by an LPA2 receptor-specific nonlipid agonist. Chem. Biol. 2015, 22, 206–216. [Google Scholar] [CrossRef] [PubMed]
  168. Likhite, N.; Jackson, C.A.; Liang, M.S.; Krzyzanowski, M.C.; Lei, P.; Wood, J.F.; Birkaya, B.; Michaels, K.L.; Andreadis, S.T.; Clark, S.D.; et al. The protein arginine methyltransferase PRMT5 promotes D2-like dopamine receptor signaling. Sci. Signal 2015, 8, ra115. [Google Scholar] [CrossRef] [PubMed]
  169. Yong, M.; Yu, T.; Tian, S.; Liu, S.; Xu, J.; Hu, J.; Hu, L. DR2 blocker thioridazine: A promising drug for ovarian cancer therapy. Oncol. Lett. 2017, 14, 8171–8177. [Google Scholar] [CrossRef] [PubMed][Green Version]
  170. Kwong, J.; Kulbe, H.; Wong, D.; Chakravarty, P.; Balkwill, F. An antagonist of the chemokine receptor CXCR4 induces mitotic catastrophe in ovarian cancer cells. Mol. Cancer Ther. 2009, 8, 1893–1905. [Google Scholar] [CrossRef] [PubMed][Green Version]
  171. Zhang, Y.; Dépond, M.; He, L.; Foudi, A.; Kwarteng, E.O.; Lauret, E.; Plo, I.; Desterke, C.; Dessen, P.; Fujii, N.; et al. CXCR4/CXCL12 axis counteracts hematopoietic stem cell exhaustion through selective protection against oxidative stress. Sci. Rep. 2016, 6, 37827. [Google Scholar] [CrossRef] [PubMed][Green Version]
  172. Proia, P.; Di Liegro, C.M.; Schiera, G.; Fricano, A.; Di Liegro, I. Lactate as a Metabolite and a Regulator in the Central Nervous System. Int. J. Mol Sci. 2016, 17, 1450. [Google Scholar] [CrossRef] [PubMed][Green Version]
  173. Lee, D.K.; Nguyen, T.; Lynch, K.R.; Cheng, R.; Vanti, W.B.; Arkhitko, O.; Lewis, T.; Evans, J.F.; George, S.R.; O’Dowd, B.F. Discovery and mapping of ten novel G protein-coupled receptor genes. Gene 2001, 275, 83–91. [Google Scholar] [CrossRef]
  174. Stranahan, A.M.; Lee, K.; Martin, B.; Maudsley, S.; Golden, E.; Cutler, R.G.; Mattson, M.P. Voluntary exercise and caloric restriction enhance hippocampal dendritic spine density and BDNF levels in diabetic mice. Hippocampus 2009, 19, 951–961. [Google Scholar] [CrossRef] [PubMed][Green Version]
  175. Li, Z.; Peng, X.; Xiang, W.; Han, J.; Li, K. The effect of resistance training on cognitive function in the older adults: A systematic review of randomized clinical trials. Aging Clin. Exp. Res. 2018. [Google Scholar] [CrossRef] [PubMed]
  176. Wagner, W.; Ciszewski, W.M.; Kania, K.D. L- and D-lactate enhance DNA repair and modulate the resistance of cervical carcinoma cells to anticancer drugs via histone deacetylase inhibition and hydroxycarboxylic acid receptor 1 activation. Cell Commun. Signal 2015, 13, 36. [Google Scholar] [CrossRef] [PubMed][Green Version]
  177. Wagner, W.; Kania, K.D.; Ciszewski, W.M. Stimulation of lactate receptor (HCAR1) affects cellular DNA repair capacity. DNA Repair 2017, 52, 49–58. [Google Scholar] [CrossRef] [PubMed]
  178. Wagner, W.; Kania, K.D.; Blauz, A.; Ciszewski, W.M. The lactate receptor (HCAR1/GPR81) contributes to doxorubicin chemoresistance via ABCB1 transporter up-regulation in human cervical cancer HeLa cells. J. Physiol. Pharmacol. 2017, 68, 555–564. [Google Scholar] [PubMed]
  179. Swope, V.B.; Abdel-Malek, Z.A. Significance of the Melanocortin 1 and Endothelin B Receptors in Melanocyte Homeostasis and Prevention of Sun-Induced Genotoxicity. Front Genet. 2016, 7, 146. [Google Scholar] [CrossRef] [PubMed]
  180. Kadekaro, A.L.; Chen, J.; Yang, J.; Chen, S.; Jameson, J.; Swope, V.B.; Cheng, T.; Kadakia, M.; Abdel-Malek, Z. Alpha-melanocyte-stimulating hormone suppresses oxidative stress through a p53-mediated signaling pathway in human melanocytes. Mol. Cancer Res. 2012, 10, 778–786. [Google Scholar] [CrossRef] [PubMed]
  181. Mattison, J.A.; Wang, M.; Bernier, M.; Zhang, J.; Park, S.S.; Maudsley, S.; An, S.S.; Santhanam, L.; Martin, B.; Faulkner, S.; et al. Resveratrol prevents high fat/sucrose diet-induced central arterial wall inflammation and stiffening in nonhuman primates. Cell Metab. 2014, 20, 183–190. [Google Scholar] [CrossRef] [PubMed]
  182. Hughes, T.M.; Kuller, L.H.; Barinas-Mitchell, E.J.; McDade, E.M.; Klunk, W.E.; Cohen, A.D.; Mathis, C.A.; Dekosky, S.T.; Price, J.C.; Lopez, O.L. Arterial stiffness and β-amyloid progression in nondemented elderly adults. JAMA Neurol. 2014, 71, 562–568. [Google Scholar] [CrossRef] [PubMed]
  183. Fazeli, G.; Stopper, H.; Schinzel, R.; Ni, C.W.; Jo, H.; Schupp, N. Angiotensin II induces DNA damage via AT1 receptor and NADPH oxidase isoform Nox4. Mutagenesis 2012, 27, 673–681. [Google Scholar] [CrossRef] [PubMed][Green Version]
  184. Herbert, K.E.; Mistry, Y.; Hastings, R.; Poolman, T.; Niklason, L.; Williams, B. Angiotensin II-mediated oxidative DNA damage accelerates cellular senescence in cultured human vascular smooth muscle cells via telomere-dependent and independent pathways. Circ. Res. 2008, 102, 201–208. [Google Scholar] [CrossRef] [PubMed]
  185. Yuri, K.; Peterson, Y.K.; Luttrell, L.M. The Diverse Roles of Arrestin Scaffolds in G Protein–Coupled Receptor Signaling. Pharmacol. Rev. 2017, 69, 256–297. [Google Scholar]
  186. Fan, Y.; Huang, Z.; Long, C.; Ning, J.; Zhang, H.; Kuang, X.; Zhang, Q.; Shen, H. ID2 protects retinal pigment epithelium cells from oxidative damage through p-ERK1/2/ID2/NRF2. Arch. Biochem. Biophys. 2018, 15, 1–13. [Google Scholar] [CrossRef] [PubMed]
  187. Sun, X.; Shi, B.; Zheng, H.; Min, L.; Yang, J.; Li, X.; Liao, X.; Huang, W.; Zhang, M.; Xu, S. Senescence-associated secretory factors induced by cisplatin in melanoma cells promote non-senescent melanoma cell growth through activation of the ERK1/2-RSK1 pathway. Cell Death Dis. 2018, 9, 260. [Google Scholar] [CrossRef] [PubMed][Green Version]
  188. Hara, M.R.; Kovacs, J.J.; Whalen, E.J.; Rajagopal, S.; Strachan, R.T.; Grant, W.; Towers, A.J.; Williams, B.; Lam, C.M.; Xiao, K.; et al. A stress response pathway regulates DNA damage through β2-adrenoreceptors and β-arrestin-1. Nature 2011, 477, 349–353. [Google Scholar] [CrossRef] [PubMed][Green Version]
  189. Sood, R.; Ritov, G.; Richter-Levin, G.; Barki-Harrington, L. Selective increase in the association of the β2 adrenergic receptor, β Arrestin-1 and p53 with Mdm2 in the ventral hippocampus one month after underwater trauma. Behav. Brain Res. 2013, 240, 26–28. [Google Scholar] [CrossRef] [PubMed]
  190. Herraiz, C.; Garcia-Borron, J.C.; Jiménez-Cervantes, C.; Olivares, C. MC1R signaling. Intracellular partners and pathophysiological implications. Biochim. Biophys. Acta 2017, 1863, 2448–2461. [Google Scholar] [CrossRef] [PubMed]
  191. Shen, H.; Wang, L.; Zhang, J.; Dong, W.; Zhang, T.; Ni, Y.; Cao, H.; Wang, K.; Li, Y.; Wang, Y.; et al. ARRB1 enhances the chemosensitivity of lung cancer through the mediation of DNA damageresponse. Oncol. Rep. 2017, 37, 761–767. [Google Scholar] [CrossRef] [PubMed]
  192. Ferguson, S.S.; Barak, L.S.; Zhang, J.; Caron, M.G. G-protein-coupled receptor regulation: Role of G-protein-coupled receptor kinases and arrestins. Can. J. Physiol. Pharmacol. 1996, 74, 1095–1110. [Google Scholar] [CrossRef] [PubMed]
  193. Premont, R.T.; Inglese, J.; Lefkowitz, R.J. Protein kinases that phosphorylate activated G protein-coupled receptors. FASEB J. 1995, 9, 175–182. [Google Scholar] [CrossRef] [PubMed]
  194. Krupnick, J.G.; Benovic, J.L. The role of receptor kinases and arrestins in G protein-coupled receptor regulation. Annu. Rev. Pharmacol. Toxicol. 1998, 38, 289–319. [Google Scholar] [CrossRef] [PubMed]
  195. Penela, P.; Ribas, C.; Mayor, F. Jr. Mechanisms of regulation of the expression and function of G protein-coupled receptor kinases. Cell Signal 2003, 15, 973–981. [Google Scholar] [CrossRef]
  196. Lorenz, K.; Lohse, M.J.; Quitterer, U. Protein kinase C switches the Raf kinase inhibitor from Raf-1 to GRK-2. Nature 2003, 426, 574–579. [Google Scholar] [CrossRef] [PubMed]
  197. Jimenez-Sainz, M.C.; Murga, C.; Kavelaars, A.; Jurado-Pueyo, M.; Krakstad, B.F.; Heijnen, C.J.; Mayor, F. Jr.; Aragay, A.M. G protein-coupled receptor kinase 2 negatively regulates chemokine signaling at a level downstream from G. protein subunits. Mol. Biol. Cell 2006, 17, 25–31. [Google Scholar] [CrossRef] [PubMed]
  198. Liu, S.; Premont, R.T.; Kontos, C.D.; Zhu, S.; Rockey, D.C. A crucial role for GRK2 in regulation of endothelial cell nitric oxide synthase function in portal hypertension. Nat. Med. 2005, 11, 952–958. [Google Scholar] [CrossRef] [PubMed]
  199. Sallese, M.; Mariggio, S.; Collodel, G.; Moretti, E.; Piomboni, P.; Baccetti, B.; De Blasi, A. G protein-coupled receptor kinase GRK4. Molecular analysis of the four isoforms and ultrastructural localization in spermatozoa and germinal cells. J. Biol. Chem. 1997, 272, 10188–10195. [Google Scholar] [CrossRef] [PubMed]
  200. Virlon, B.; Firsov, D.; Cheval, L.; Reiter, E.; Troispoux, C.; Guillou, F.; Elalouf, J.M. Rat G protein-coupled receptor kinase GRK4: Identification, functional expression, and differential tissue distribution of two splice variants. Endocrinology 1998, 139, 2784–2795. [Google Scholar] [CrossRef] [PubMed]
  201. Sallese, M.; Salvatore, L.; D’Urbano, E.; Sala, G.; Storto, M.; Launey, T.; Nicoletti, F.; Knopfel, T.; De Blasi, A. The G-protein-coupled receptor kinase GRK4 mediates homologous desensitization of metabotropic glutamate receptor 1. FASEB J. 2000, 14, 2569–2580. [Google Scholar] [CrossRef] [PubMed]
  202. Chen, X.; Zhu, H.; Yuan, M.; Fu, J.; Zhou, Y.; Ma, L. G-protein-coupled receptor kinase 5 phosphorylates p53 and inhibits DNA damage-induced apoptosis. J. Biol. Chem. 2010, 285, 12823–12830. [Google Scholar] [CrossRef] [PubMed]
  203. Suo, Z.; Cox, A.A.; Bartelli, N.; Rasul, I.; Festoff, B.W.; Premont, R.T.; Arendash, G.W. GRK5 deficiency leads to early Alzheimer-like pathology and working memory impairment. Neurobiol. Aging 2007, 28, 1873–1888. [Google Scholar] [CrossRef] [PubMed]
  204. Li, L.; Rasul, I.; Liu, J.; Zhao, B.; Tang, R.; Premont, R.T.; Suo, W.Z. Augmented axonal defects and synaptic degenerative changes in female GRK5 deficient mice. Brain Res. Bull. 2009, 78, 145–151. [Google Scholar] [CrossRef] [PubMed]
  205. Singh, P.; Peng, W.; Zhang, Q.; Ding, X.; Suo, W.Z. GRK5 deficiency leads to susceptibility to intermittent hypoxia-induced cognitive impairment. Behav. Brain Res. 2016, 302, 29–34. [Google Scholar] [CrossRef] [PubMed][Green Version]
  206. Takagi, C.; Urasawa, K.; Yoshida, I.; Takagi, Y.; Kaneta, S.; Nakano, N.; Onozuka, H.; Kitabatake, A. Enhanced GRK5 expression in the hearts of cardiomyopathic hamsters, J2N-k. Biochem. Biophys. Res. Commun. 1999, 262, 206–210. [Google Scholar] [CrossRef] [PubMed]
  207. Premont, R.T.; Claing, A.; Vitale, N.; Perry, S.J.; Lefkowitz, R.J. The GIT family of ADP-ribosylation factor GTPase-activating proteins. Functional diversity of GIT2 through alternative splicing. J. Biol. Chem. 2000, 275, 22373–22380. [Google Scholar] [CrossRef] [PubMed]
  208. Perry, S.J.; Schmalzigaug, R.; Roseman, J.T.; Xing, Y.; Claing, A. The GIT/PIX complex: An oligomeric assembly of GIT family ARF GTPase-activating proteins and PIX family Rac1/Cdc42 guanine nucleotide exchange factors. Cell Signal. 2004, 16, 1001–1011. [Google Scholar]
  209. Van Gastel, J.; Jushaj, A.; Boddaert, J.; Premont, R.T.; Luttrell, L.M.; Janssens, J.; Martin, B.; Maudsley, S. GIT2—A keystone in ageing and age-related disease. Ageing Res. Rev. 2018, 43, 46–63. [Google Scholar] [CrossRef] [PubMed]
  210. Lu, D.; Cai, H.; Park, S.S.; Siddiqui, S.; Premont, R.T.; Schmalzigaug, R.; Paramasivam, M.; Seidman, M.; Bodogai, I.; Biragyn, A.; et al. Nuclear GIT2 Is an ATM Substrate and Promotes DNA Repair. Mol. Cell. Biol. 2015, 35, 1081–1096. [Google Scholar] [CrossRef] [PubMed][Green Version]
  211. Siddiqui, S.; Lustig, A.; Carter, A.; Sankar, M.; Daimon, C.M.; Premont, R.T.; Etienne, H.; van Gastel, J.; Azmi, A.; Janssens, J.; et al. Genomic deletion of GIT2 induces a premature age-related thymic dysfunction and systemic immune system disruption. Aging 2017, 9, 706–740. [Google Scholar] [CrossRef] [PubMed][Green Version]
  212. Van Gastel, J.; Hendrickx, J.; Leysen, H.; Luttrell, L.M.; Lee, M.-H.M.; Azmi, A.; Janssens, J.; Maudsley, S. The RXFP3-GIT2 signaling system represents a potential multidimensional therapeutic target in age-related disorders. FASEB J. 2018, 32, 1. [Google Scholar]
  213. Roux, B.T.; Cottrell, G.S. G protein-coupled receptors: What a difference a ‘partner’ makes. Int. J. Mol. Sci. 2014, 15, 1112–1142. [Google Scholar] [CrossRef] [PubMed][Green Version]
  214. Stewart, A.; Fisher, R.A. Introduction: G Protein-coupled Receptors and RGS Proteins. Prog. Mol. Biol. Transl. Sci. 2015, 133, 1–11. [Google Scholar] [PubMed]
  215. Berman, D.M.; Wilkie, T.M.; Gilman, A.G. GAIP and RGS4 are GTPase-activating proteins for the Gi subfamily of G protein alpha subunits. Cell 1996, 86, 445–452. [Google Scholar] [CrossRef]
  216. Wiechec, E.; Overgaard, J.; Hansen, L.L. A fragile site within the HPC1 region at 1q25.3 affecting RGS16, RGSL1, and RGSL2 in human breast carcinomas. Genes Chromosomes Cancer 2008, 47, 766–780. [Google Scholar] [CrossRef] [PubMed]
  217. Iwaki, S.; Lu, Y.; Xie, Z.; Druey, K.M. p53 negatively regulates RGS13 protein expression in immune cells. J. Biol Chem. 2011, 286, 22219–22226. [Google Scholar] [CrossRef] [PubMed]
  218. Huang, J.; Yang, J.; Maity, B.; Mayuzumi, D.; Fisher, R.A. Regulator of G protein signaling 6 mediates doxorubicin-induced ATM and p53 activation by a reactive oxygen species-dependent mechanism. Cancer Res. 2011, 71, 6310–6319. [Google Scholar] [CrossRef] [PubMed]
  219. Yang, J.; Maity, B.; Huang, J.; Gao, Z.; Stewart, A.; Weiss, R.M.; Anderson, M.E.; Fisher, R.A. G-protein inactivator RGS6 mediates myocardial cell apoptosis and cardiomyopathy caused by doxorubicin. Cancer Res. 2013, 73, 1662–1667. [Google Scholar] [CrossRef] [PubMed]
  220. Maity, B.; Stewart, A.; O’Malley, Y.; Askeland, R.W.; Sugg, S.L.; Fisher, R.A. Regulator of G protein signaling 6 is a novel suppressor of breast tumor initiation and progression. Carcinogenesis 2013, 34, 1747–1755. [Google Scholar] [CrossRef] [PubMed][Green Version]
  221. Sjögren, B.; Swaney, S.; Neubig, R.R. FBXO44-Mediated Degradation of RGS2 Protein Uniquely Depends on a Cullin 4B/DDB1 Complex. PLoS ONE 2015, 10, e0123581. [Google Scholar] [CrossRef] [PubMed]
  222. Iovine, B.; Iannella, M.L.; Bevilacqua, M.A. Damage-specific DNA binding protein 1 (DDB1): A protein with a wide range of functions. Int. J. Biochem. Cell Biol. 2011, 43, 1664–1667. [Google Scholar] [CrossRef] [PubMed]
  223. Maiese, K.; Chong, Z.Z.; Shang, Y.C.; Wang, S. mTOR: On target for novel therapeutic strategies in the nervous system. Trends Mol. Med. 2013, 19, 51–60. [Google Scholar] [CrossRef] [PubMed]
  224. Ellisen, L.W.; Ramsayer, K.D.; Johannessen, C.M.; Yang, A.; Beppu, H.; Minda, K.; Oliner, J.D.; McKeon, F.; Haber, D.A. REDD1, a developmentally regulated transcriptional target of p63 and p53, links p63 to regulation of reactive oxygen species. Mol. Cell 2002, 10, 995–1005. [Google Scholar] [CrossRef]
  225. Michel, G.; Matthes, H.W.; Hachet-Haas, M.; El Baghdadi, K.; de Mey, J.; Pepperkok, R.; Simpson, J.C.; Galzi, J.L.; Lecat, S. Plasma membrane translocation of REDD1 governed by GPCRs contributes to mTORC1 activation. J. Cell Sci. 2014, 127, 773–787. [Google Scholar] [CrossRef] [PubMed]
  226. Walden, H.; Deans, A.J. The Fanconi Anemia DNA Repair Pathway: Structural and Functional Insights into a Complex Disorder. Annu. Rev. Biophys. 2014, 43, 257–278. [Google Scholar] [CrossRef] [PubMed]
  227. Pikor, L.; Thu, K.; Vucic, E.; Lam, W. The detection and implication of genome instability in cancer. Cancer Metastasis Rev. 2013, 32, 341–352. [Google Scholar] [CrossRef] [PubMed][Green Version]
  228. Palovcak, A.; Liu, W.; Yuan, F.; Zhang, Y. Maintenance of genome stability by Fanconi anemia proteins. Cell Biosci. 2017, 7, 8. [Google Scholar] [CrossRef] [PubMed]
  229. Auerbach, A.D. Fanconi anemia and its diagnosis. Mutat. Res. 2009, 668, 4–10. [Google Scholar] [CrossRef] [PubMed][Green Version]
  230. Moldovan, G.L.; D’Andrea, A.D. How the fanconi anemia pathway guards the genome. Annu. Rev. Genet. 2009, 43, 223–249. [Google Scholar] [CrossRef] [PubMed]
  231. Larder, R.; Karali, D.; Nelson, N.; Brown, P. Fanconi anemia A is a nucleocytoplasmic shuttling molecule required for gonadotropin-releasing hormone (GnRH) transduction of the GnRH receptor. Endocrinology 2006, 147, 5676–5689. [Google Scholar] [CrossRef] [PubMed]
  232. Maruyama, T.; Nara, K.; Yoshikawa, H.; Suzuki, N. Txk, a member of the non-receptor tyrosine kinase of the Tec family, forms a complex with poly(ADP-ribose) polymerase 1 and elongation factor 1alpha and regulates interferon-gamma gene transcription in Th1 cells. Clin. Exp. Immunol. 2007, 147, 164–175. [Google Scholar] [CrossRef] [PubMed]
  233. Ahel, I.; Ahel, D.; Matsusaka, T.; Clark, A.J.; Pines, J.; Boulton, S.J.; West, S.C. Poly(ADP-ribose)-binding zinc finger motifs in DNA repair/checkpoint proteins. Nature 2008, 451, 81–85. [Google Scholar] [CrossRef] [PubMed]
  234. Reinemund, J.; Seidel, K.; Steckelings, U.M.; Zaade, D.; Klare, S.; Rompe, F.; Katerbaum, M.; Schacherl, J.; Li, Y.; Menk, M. Poly(ADP-ribose) polymerase-1 (PARP-1) transcriptionally regulates angiotensin AT2 receptor (AT2R) and AT2R binding protein (ATBP) genes. Biochem Pharmacol. 2009, 77, 1795–1805. [Google Scholar] [CrossRef] [PubMed][Green Version]
  235. Ahel, D.; Horejsí, Z.; Wiechens, N.; Polo, S.E.; Garcia-Wilson, E.; Ahel, I.; Flynn, H.; Skehel, M.; West, S.C.; Jackson, S.P. Poly(ADP-ribose)-dependent regulation of DNA repair by the chromatin remodeling enzyme ALC1. Science 2009, 325, 1240–1243. [Google Scholar] [CrossRef] [PubMed]
  236. Grube, K.; Bürkle, A. Poly(ADP-ribose) polymerase activity in mononuclear leukocytes of 13 mammalian species correlates with species-specific life span. Proc. Natl. Acad. Sci. USA 1992, 89, 11759–11763. [Google Scholar] [CrossRef] [PubMed]
  237. Suberbielle, E.; Djukic, B.; Evans, M.; Kim, D.H.; Taneja, P.; Wang, X.; Finucane, M.; Knox, J.; Ho, K.; Devidze, N.; et al. DNA repair factor BRCA1 depletion occurs in Alzheimer brains and impairs cognitive function in mice. Nat. Commun. 2015, 6, 8897. [Google Scholar] [CrossRef] [PubMed][Green Version]
  238. Kim, S.; Nho, K.; Risacher, S.L.; Inlow, M.; Swaminathan, S.; Yoder, K.K.; Shen, L.; West, J.D.; McDonald, B.C.; Tallman, E.F.; et al. PARP1 gene variation and microglial activity on [11C]PBR28 PET in older adults at risk for Alzheimer’s disease. Multimodal Brain Image Anal. 2013, 8159, 150–158. [Google Scholar]
  239. Adamczyk, A.; Jeśko, H.; Strosznajder, R.P. Alzheimer’s disease related peptides affected cholinergic receptor mediated poly(ADP-ribose) polymerase activity in the hippocampus. Folia Neuropathol. 2005, 43, 139–142. [Google Scholar] [PubMed]
  240. Kunieda, T.; Minamino, T.; Nishi, J.; Tateno, K.; Oyama, T.; Katsuno, T.; Miyauchi, H.; Orimo, M.; Okada, S.; Takamura, M.; et al. Angiotensin II induces premature senescence of vascular smooth muscle cells and accelerates the development of atherosclerosis via a p21-dependent pathway. Circulation 2006, 114, 953–960. [Google Scholar] [CrossRef] [PubMed]
  241. Min, L.J.; Mogi, M.; Iwanami, J.; Li, J.M.; Sakata, A.; Fujita, T.; Tsukuda, K.; Iwai, M.; Horiuchi, M.; et al. Cross-talk between aldosterone and angiotensin II in vascular smooth muscle cell senescence. Cardiovasc. Res. 2007, 76, 506–516. [Google Scholar] [CrossRef] [PubMed][Green Version]
  242. Min, L.J.; Mogi, M.; Iwanami, J.; Li, J.M.; Sakata, A.; Fujita, T.; Tsukuda, K.; Iwai, M.; Horiuchi, M. Angiotensin II type 2 receptor deletion enhances vascular senescence by methyl methanesulfonate sensitive 2 inhibition. Hypertension 2008, 51, 1339–1344. [Google Scholar] [CrossRef] [PubMed]
  243. Daviet, L.; Lehtonen, J.Y.; Tamura, K.; Griese, D.P.; Horiuchi, M.; Dzau, V.J. Cloning and characterization of ATRAP, a novel protein that interacts with the angiotensin II type 1 receptor. J. Biol. Chem. 1999, 274, 17058–17062. [Google Scholar] [CrossRef] [PubMed]
  244. Min, L.J.; Mogi, M.; Tamura, K.; Iwanami, J.; Sakata, A.; Fujita, T.; Tsukuda, K.; Jing, F.; Iwai, M.; Horiuchi, M. Angiotensin II type 1 receptor-associated protein prevents vascular smooth muscle cell senescence via inactivation of calcineurin/nuclear factor of activated T cells pathway. J. Mol. Cell Cardiol. 2009, 47, 798–809. [Google Scholar] [CrossRef] [PubMed]
  245. Nouet, S.; Amzallag, N.; Li, J.M.; Louis, S.; Seitz, I.; Cui, T.X.; Alleaume, A.M.; Di Benedetto, M.; Boden, C.; Masson, M.; et al. Trans-inactivation of receptor tyrosine kinases by novel angiotensin II AT2 receptor-interacting protein. ATIP J. Biol. Chem. 2004, 279, 28989–38997. [Google Scholar] [CrossRef] [PubMed]
  246. Min, L.J.; Mogi, M.; Iwanami, J.; Jing, F.; Tsukuda, K.; Ohshima, K.; Horiuchi, M. Angiotensin II type 2 receptor-interacting protein prevents vascular senescence. J. Am. Soc. Hypertens. 2012, 6, 179–184. [Google Scholar] [CrossRef] [PubMed]
  247. Maudsley, S.; Devanarayan, V.; Martin, B.; Geerts, H.; Brain Health Modeling Initiative (BHMI). Intelligent and effective informatic deconvolution of “Big Data” and its future impact on the quantitative nature of neurodegenerative disease therapy. Alzheimers Dement. 2018, 14, 961–975. [Google Scholar] [CrossRef] [PubMed]
  248. Chen, H.; Martin, B.; Daimon, C.M.; Maudsley, S. Effective use of latent semantic indexing and computational linguistics in biological and biomedical applications. Front. Physiol. 2013, 4, 8. [Google Scholar] [CrossRef] [PubMed]
  249. Cashion, A.; Stanfill, A.; Thomas, F.; Xu, L.; Sutter, T.; Eason, J.; Ensell, M.; Homayouni, R. Expression levels of obesity-related genes are associated with weight change in kidney transplant recipients. PLoS ONE 2013, 8, e59962. [Google Scholar] [CrossRef] [PubMed]
  250. Leff, P. The two-state model of receptor activation. Trends Pharmacol. Sci. 1995, 16, 89–97. [Google Scholar] [CrossRef]
  251. De Lean, A.; Stadel, J.M.; Lefkowitz, R.J. A ternary complex model explains the agonist-specific binding properties of the adenylate cyclase-coupled beta-adrenergic receptor. J. Biol. Chem. 1980, 255, 7108–7117. [Google Scholar] [PubMed]
  252. Samama, P.; Cotecchia, S.; Costa, T.; Lefkowitz, R.J. A mutation-induced activated state of the beta 2-adrenergic receptor. Extending the ternary complex model. J. Biol. Chem. 1993, 268, 4625–4636. [Google Scholar] [PubMed]
  253. Luttrell, L.M.; Maudsley, S.; Bohn, L.M. Fulfilling the Promise of “Biased” G Protein-Coupled Receptor Agonism. Mol. Pharmacol. 2015, 88, 579–588. [Google Scholar] [CrossRef] [PubMed]
  254. Nair, R.R.; Kiran, A.; Saini, D.K.G. protein Signaling, Journeys Beyond the Plasma Membrane. J. Indian Inst. Sci. 2017, 97, 95–108. [Google Scholar] [CrossRef]
  255. Irannejad, R.; von Zastrow, M. GPCR signaling along the endocytic pathway. Curr. Opin. Cell Biol. 2014, 27, 109–116. [Google Scholar] [CrossRef] [PubMed][Green Version]
  256. Jong, Y.I.; Harmon, S.K.; O’Malley, K.L. GPCR signaling from within the cell. Br. J. Pharmacol. 2017, 1–10. [Google Scholar]
  257. Jong, Y.I.; Harmon, S.K.; O’Malley, K.L. Intracellular GPCRs Play Key Roles in Synaptic Plasticity. ACS Chem. Neurosci. 2018. [Google Scholar] [CrossRef] [PubMed]
  258. Römpler, H.; Yu, H.T.; Arnold, A.; Orth, A.; Schöneberg, T. Functional consequences of naturally occurring DRY motif variants in the mammalian chemoattractant receptor GPR33. Genomics 2006, 87, 724–732. [Google Scholar] [CrossRef] [PubMed][Green Version]
  259. Wilbanks, A.M.; Laporte, S.A.; Bohn, L.M.; Barak, L.S.; Caron, M.G. Apparent Loss-of-Function Mutant GPCRs Revealed as Constitutively Desensitized Receptors. Biochemistry 2002, 41, 11981–11989. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Unbiased informatics appraisal of functional intersection between GPCR and DNA damage-response (DDR) systems. (A) Protein identities, semantically associated with GPCR-related (blue) or DDR-related (red), were generated from whole proteome-wide datasets created from PubMed abstracts. The most strongly GPCR or DDR system-associated protein lists were then cross-interrogated using the opposing interrogator term list. (B) Wordcloud representation (using cosine similarity score values) of both GPCR- (blue text) and DDR-intersectional protein factors. The font size of the protein term is proportional to the cumulative cosine similarity score values across the multiple (17) interrogator terms. (C) Canonical signaling pathway analysis was applied to the combined GPCR or DDR-associated protein lists (Panel A) created using cross-interrogation. Displaying the pathways linked by common signaling proteins reveals the connections between DDR-associated (red) and GPCR-associated (blue) cellular signaling cascades.
Figure 1. Unbiased informatics appraisal of functional intersection between GPCR and DNA damage-response (DDR) systems. (A) Protein identities, semantically associated with GPCR-related (blue) or DDR-related (red), were generated from whole proteome-wide datasets created from PubMed abstracts. The most strongly GPCR or DDR system-associated protein lists were then cross-interrogated using the opposing interrogator term list. (B) Wordcloud representation (using cosine similarity score values) of both GPCR- (blue text) and DDR-intersectional protein factors. The font size of the protein term is proportional to the cumulative cosine similarity score values across the multiple (17) interrogator terms. (C) Canonical signaling pathway analysis was applied to the combined GPCR or DDR-associated protein lists (Panel A) created using cross-interrogation. Displaying the pathways linked by common signaling proteins reveals the connections between DDR-associated (red) and GPCR-associated (blue) cellular signaling cascades.
Ijms 19 02919 g001

Share and Cite

MDPI and ACS Style

Leysen, H.; Van Gastel, J.; Hendrickx, J.O.; Santos-Otte, P.; Martin, B.; Maudsley, S. G Protein-Coupled Receptor Systems as Crucial Regulators of DNA Damage Response Processes. Int. J. Mol. Sci. 2018, 19, 2919.

AMA Style

Leysen H, Van Gastel J, Hendrickx JO, Santos-Otte P, Martin B, Maudsley S. G Protein-Coupled Receptor Systems as Crucial Regulators of DNA Damage Response Processes. International Journal of Molecular Sciences. 2018; 19(10):2919.

Chicago/Turabian Style

Leysen, Hanne, Jaana Van Gastel, Jhana O. Hendrickx, Paula Santos-Otte, Bronwen Martin, and Stuart Maudsley. 2018. "G Protein-Coupled Receptor Systems as Crucial Regulators of DNA Damage Response Processes" International Journal of Molecular Sciences 19, no. 10: 2919.

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop