Aging is a multifactorial process that results in increased risk of a myriad of chronic diseases. Being elderly is the greatest risk factor, by orders of magnitude, for cancer, osteoporosis, cardiovascular disease, dementia and most other degenerative diseases (Kirkwood, 2005). While no single mechanism or pathway fully accounts for age-associated functional decline, one prevailing theory is that macromolecular damage, accumulating over time, plays a causal role in driving aging. Most macromolecules in the cell when damaged are simply degraded and replaced. In contrast, the nuclear genome, which is the blueprint for all cellular functions, has dedicated and energetically costly repair mechanisms to rapidly correct DNA damage. This intimates that DNA damage is a particularly hazardous type of macromolecular damage and therefore likely to be deleterious to cellular homeostasis.

Maintaining genome stability is a continuous process. Deoxyribonucleic acids are chemically unstable under physiological conditions (aqueous, oxygen-rich, and pH 7.4) (Lindahl, 1993). DNA is also vulnerable to chemical attack by electrophiles and free radicals. While exogenous sources of genotoxic stress can be quite potent, endogenous threats are constant and relentless (Table 1). The most common DNA lesion is hydrolytic cleavage of the glycosidic bond between the DNA base and sugar phosphate group, leading to abasic sites. Hydrolytic deamination of the DNA bases is also common. Products of normal cellular metabolism can cause oxidation, nitrosylation, and alkylation of the DNA bases (De Bont and van Larebeke, 2004). Breaks in the phosphate deoxyribose backbone arise as a consequence of high energy radiation or during DNA metabolism (replication, decatenation). Spontaneous DNA damage occurs on the order of 10⁴–10⁵ events per cell per day (Lindahl, 1993; De Bont and van Larebeke, 2004).

DNA is also susceptible to damage by environmental factors such as ultraviolet (UV), ionizing radiation, and alkylating agents used to treat proliferative disorders like cancer (Table 1). Notably, even when exogenous genotoxin exposure is instigated with the purpose of driving cell death (e.g., in cancer therapy) adduct burdens are well below the incidence of endogenous damage (Jackson and Loeb, 2001). Fortunately, all organisms have robust mechanisms to sense all types of DNA damage, delay genome replication (if needed), signal for repair, and correct or tolerate the large number of genomic insults that occur on a daily basis (Hoeijmakers, 2009). DNA damage that is not repaired in a timely manner or is too egregious to be repaired induces signaling events that lead to one of many cell fates, one of which, senescence, plays a causal role in aging.

Why? and how? organisms age remain challenging questions. Why one ages interrogates the reasons. How one ages interrogates the method. The antagonistic pleiotropic theory of aging provides a genetic solution to why we age, posing that genes that provide an advantage during reproductive life are disadvantageous post reproduction, yet these genes cannot be selected against (Kirkwood, 2005). As an example of antagonistic pleiotropy, activation of the DNA damage response (DDR) is critical for preventing cancer; however, chronic activation of the DDR is thought to drive the accumulation of senescent cells and chronic sterile inflammation in old age, as described in more detail below. The pillars of aging (Kennedy et al., 2014) describe the method by which (or how) we age: loss of or impaired, mitochondrial integrity and function, metabolism, stem cell function, proteostasis, nutrient sensing, adaptation to stress, autophagic flux, epigenetic control, and an accumulation of damaged cellular macromolecules. This includes damage to the nuclear and mitochondrial genomes. Nevertheless, it has proven challenging to establish the pillars of aging as true causes of aging rather than merely consequences of aging.

If DNA damage drives aging, mechanistically how does it do so? Through activating signaling responses (d'Adda di Fagagna et al., 2003), blocking transcription (Vermeij et al., 2016) and other DNA metabolism, altering the epigenome (Oberdoerffer et al., 2008), mutagenesis (Vijg, 2014), triggering cells senescence or apoptosis? DNA damage occurs stochastically but the amount and types of DNA damage one experiences is influenced by the expression of genes encoding antioxidant enzymes, genes linked to energetics and mitochondrial function, and a myriad of other factors such as histones, methylases, sirtuins, transcription, and replication factors. Every aspect of how DNA damage might drive aging is also genetically determined via the cellular response to DNA damage. The somewhat surprising finding is that DNA damage has far-reaching effects on many aspects of cellular metabolism tied to aging, the so-called pillars of aging (Kennedy et al., 2014). This suggests that aging might be driven by many types of cellular damage yet does not occur until one reaches a state where multiple aspects of cell biology are perturbed, for example, genome integrity, proteostasis, and mitochondrial function.

Once DNA damage is recognized in the nuclear genome, bulky adducts, small miscoding lesions, single-strand breaks, or non-complex double-strand breaks (DSBs) can be directly repaired by nucleotide excision repair (NER), base excision repair (BER), and non-homologous end-joining (NHEJ), respectively. If replication forks or transcription complexes encounter polymerase-blocking lesions (Vermeij et al., 2016), this can lead to the formation of a DSB or R-loop (Tresini et al., 2015), which potently activate signaling events that halt cell cycle progression and promote repair. If the damage signals persist, then the cell selects a fate that avoids replicating a damaged genome and mutagenesis at all cost, by activating events that lead to cell death (apoptosis) or irreversible cell cycle arrest (senescence) (Figure 1). DNA damage signaling begins with the MRE11-RAD50-NBS1 (MRN) complex activating the phosphatidylinositol 3-kinase-like kinases (PIKKs) ataxia-telangiectasia mutated (ATM), ATM-related kinase (ATR) and/or related PIKK (Thompson, 2012). ATM is activated primarily by DNA DSBs while ATR is primarily involved in the response to stalled replication forks, although overlap occurs. Initially ATM and ATR work with checkpoint mediator proteins like MDC1, 53BP1 and BRCA1, TOPBP1, which are sensor proteins that bind to lesions and recruit other DDR factors. Damage recognition is followed by phosphorylation (and activation) of transducer kinases like checkpoint kinase 2 (CHK2) or checkpoint kinase 1 (CHK1), which amplify the ATM-ATR signal. CHK2 activation leads to activation of p53, a master regulator of the cellular response to genotoxic stress (Senturk and Manfredi, 2013). Sustained activation of these transducer proteins leads to phosphorylation of several DNA repair and cell cycle checkpoint proteins (Thompson, 2012; Cheng and Chen, 2010). p53 can also be activated independently of ATM. p14/ARF inhibits MDM2–p53 interaction, resulting in the stabilization of p53 (Senturk and Manfredi, 2013; Meek and Anderson, 2009). p53 can mount a bimodal response to stress where it functions to activate apoptosis via various transcriptional targets like Bax, Puma, and Noxa, or promote transient or prolonged cell cycle arrest through transcriptional activation of the cyclin-dependent kinase inhibitor p21^CIP1 (Reinhardt and Schumacher, 2012). A myriad of factors determines the extent of p53 activation in response to genotoxic stress, and more factors likely will be discovered.

Figure 1

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A variety of types of stress can activate the INK4a/ARF locus in cells. The gene products of the locus—p16^INK4a and ARF—arrest cell progression by acting on the retinoblastoma protein and p53 (Senturk and Manfredi, 2013). p16^INK4a inhibits CDK4 from binding to cyclin D, thereby preventing phosphorylation of RB. Hypo-phosphorylated retinoblastoma (RB) protein represses E2F-dependent gene expression, blocking G1/S cell cycle progression. Free E2F activates many genes involved in mitosis. While sensing DNA damage and responding to it is a positive attribute, persistent DNA damage signaling can have quite deleterious effects. It can lead to chronic activation of p53 and other response pathways (stress response, pro- and anti-apoptotic, pro-inflammatory, etc.), which impact many aspects of cellular function and impact cell fate. Definitive knowledge about which factors determine the selection of cell fate selection remains elusive. However, it seems likely that these factors may vary with the cell type, the level, and the duration of genotoxic stress.

Leonard Hayflick and Paul Moorhead defined cellular senescence as the proliferative arrest that occurs in normal cells after a number of cell divisions (Hayflick and Moorhead, 1961; Hayflick, 1965). The first molecular explanation for senescence was the progressive telomere shorting that occurs with every cell division termed telomere-initiated cellular senescence (Harley et al., 1990). Many cells undergo senescence independently of telomere shorting due to replicative, mitochondrial, oxidative, metabolic, or genotoxic stress (Parrinello et al., 2003; Christoffersen et al., 2010; Correia-Melo et al., 2016; Nair et al., 2015). Senescent cells actively repress cell cycle progression preventing the replication of a damaged genome. Senescent cells have altered metabolism, morphology, and secretory profile called the senescence-associated secretory phenotype (SASP). The SASP includes pro-inflammatory cytokines, chemokines, and proteases (Coppé et al., 2008) and is heterogenous depending on the cell type and the inducer of senescence (Basisty et al., 2020). The SASP is thought to instigate immune clearance of the damaged/stressed cells (Tasdemir et al., 2016), but the immediate negative consequence is the potential to drive local tissue damage and systemic chronic sterile inflammation (Franceschi and Campisi, 2014).

One of the challenges of studying senescence is the absence of a specific marker to identify senescent cells. Therefore, multiple endpoints must be measured simultaneously to identify them (Gorgoulis et al., 2019; Sharpless and Sherr, 2015). The most widely used marker is measurement of senescence-associated β-galactosidase (SA-β-gal) activity (Itahana et al., 2007). Other markers associated with cellular senescence include absence of proliferation markers (e.g., Ki-67), increased expression of the cyclin-dependent kinase inhibitors p16^INK4a and p21^CIP1, persistent activation of the DDR (such as p53, ATM, ATR, ɣH2AX, telomere dysfunction-induced foci [TIF], senescence-associated heterochromatin foci [SAHF], and DNA segments with chromatin alterations reinforcing senescence [DNA-SCARS]), reduced lamin B1 expression, increased HMGB1 and SASP factors (such as IL-1β, IL-6, IL-10, MCP-1, and TNFα) (Coppé et al., 2010; Lawless et al., 2010; Serrano et al., 1997; Takai et al., 2003; Matjusaitis et al., 2016; Rodier et al., 2011).

Cellular senescence plays a critical role in preventing tumorigenesis, tissue repair, and wound healing, promoting insulin secretion and mammalian development (Kuilman et al., 2008; Krizhanovsky et al., 2008; Demaria et al., 2014; Storer et al., 2013; Helman et al., 2016). However, time-dependent accumulation of senescent cells, likely through decreased immunoclearance, occurs in virtually all vertebrates (Jeyapalan et al., 2007; Liu et al., 2009) and has been definitively shown to drive aging (Baker et al., 2016), rather than simply occur with aging. Senescent cells also contribute to age-related diseases such as atherosclerosis (Roos et al., 2016), osteoporosis (Chandra et al., 2020), nonalcoholic fatty liver disease (Ogrodnik et al., 2017), cancer (Alimirah et al., 2020), neurodegenerative diseases (Chinta et al., 2018; Zhang et al., 2019), and numerous other age-related conditions (Kirkland and Tchkonia, 2020). Interestingly, NF-κB is the transcription factor that is most activated with aging (Adler et al., 2007). NF-κB signaling is the major signaling pathway that stimulates SASP (Tilstra et al., 2011). DNA damage activates NF-κB signaling via an ATM-NEMO-dependent regulation of an upstream kinase (Miyamoto, 2011; Figure 1). DNA damage can also lead to NF-κB activation via stabilization of GATA4 (Kang et al., 2015). Thus, genotoxic stress is a potent inducer of senescence and SASP, key drivers of aging and age-related disease.

The mammalian genome encodes over 150 proteins directly responsible for safeguarding its integrity (Friedberg, 2006; Wood et al., 2005). These gene products constantly monitor the quality and repair the nuclear genome (Sancar et al., 2004). Distinct DNA repair pathways cope with different types of DNA lesions: BER for small covalent additions to DNA bases, NER for bulky adducts that disrupt the DNA helix, interstrand crosslink (ICL) repair to remove covalent links between the two strands of DNA, NHEJ to ligate broken DNA ends, mismatch repair to correct replication errors, homologous recombination to manage replication stress and DSBs not readily ligated. Inherited defects in each of the DNA repair pathways are linked to distinct genome instability syndromes (Table 2). Broadly, the syndromes are characterized by developmental defects, increased incidence of cancer and features of accelerated aging (Cleaver, 1968; Menck and Munford, 2014; Wood, 2018). Progeroid syndromes are diseases of dramatically accelerated aging and include Hutchinson-Gilford, Werner, and Cockayne syndromes (CS), as well as XFE progeroid syndrome, all of which are linked to genome instability (de Magalhães, 2005; Martin and Oshima, 2000; Burla et al., 2018). The syndromes provide an elegant yet tragic glimpse into the impact that DNA damage can have on human health. Most syndromes were described well before DNA had been discovered or mechanisms of repair described.

Children with Hutchinson-Gilford progeroid syndrome (HGPS) develop many features of premature aging in the first decade of life including alopecia, atherosclerosis, osteolysis, and lipodystrophy among others (Hennekam, 2006). The genetic cause for HGPS are mutations in the LMNA gene, which encodes critical components of the nuclear lamina (Eriksson et al., 2003; De Sandre-Giovannoli et al., 2003) causing pernicious alterations in nuclear architecture resulting in genome instability (Kudlow et al., 2007). Nestor-Guillermo progeroid syndrome, caused by mutations in the nuclear lamina gene BANF1, has characteristics of accelerated aging due to impaired chromatin organization (Cabanillas et al., 2011; Loi et al., 2016).

Mutations in DNA helicases are linked to multiple diseases of accelerated aging. Mutations in three of the RECQ family of helicases (BLM, RECQL4, and WRN) cause progeroid syndromes (Uchiumi et al., 2015). Mutations in WRN, a gene that encodes a helicase responsible for managing replication stress and telomere stability, cause Werner syndrome (WS) (Kudlow et al., 2007). WS patients experience growth retardation, premature hair graying, lipodystrophy, as well as premature onset of multiple age-related diseases including arteriosclerosis, cancer, type 2 diabetes mellitus, and osteoporosis (Sugimoto, 2014). Rothmund-Thomson syndrome (RTS) is caused by mutations in RECQL4, encoding a helicase that participates in DNA replication and repair. RTS patients experience juvenile cataracts, epidermal atrophy, and increased cancer incidence (Croteau et al., 2012; Ghosh et al., 2012). Bloom syndrome (BS) is caused by mutations in BLM, which encodes a RecQ helicase critical for suppressing recombination and thereby genome instability (Nguyen et al., 2014; Hanada and Hickson, 2007). The mean lifespan of BS patients is 26 years and they have premature onset of numerous age-related diseases, including cancer, diabetes, and chronic obstructive pulmonary disease (de Renty and Ellis, 2017).

NER detects and removes DNA adducts that distort the helical structure of DNA such as adducts resulting from exposure to UV light, environmental mutagens, and certain classes of cancer chemotherapeutics (Schärer, 2013). Endogenous DNA adducts repaired by NER are cyclopurines; oxidative DNA lesions believed to contribute to neurodegeneration (Brooks, 2008). NER consists of two sub-pathways that are responsible for repair of the entire nuclear genome (global genome NER) or focused on transcribed genes (transcription-coupled NER). Defects in the former cause xeroderma pigmentosum (XP) linked to mutations in seven genes XPA-G (Cleaver, 1968; Lehmann et al., 2011). XP is characterized by accelerated photoaging of the skin and a 10,000-fold increased risk of skin cancer. XP patients also frequently have accelerated onset of peripheral neuropathy, sensorineural deficits, cerebral atrophy, and neurodegeneration (Kraemer and DiGiovanna, 2015). Defects in transcription-coupled NER cause CS or trichothiodystrophy (TTD). CS patients have progressive growth retardation, neurodegeneration, cataracts, osteoporosis, and metabolic dysfunction similar to old age (Nance and Berry, 1992; Wilson et al., 2016). TTD patients present with CS-like features plus brittle hair and ichthyosis (Faghri et al., 2008). XFE progeroid syndrome results from mutations in ERCC4/FANCQ causing reduced expression of XPF-ERCC1, a heterodimeric DNA repair endonuclease required for NER, DNA ICL repair, and the repair of some DNA DSBs (Niedernhofer et al., 2006; Ahmad et al., 2008; Bhagwat et al., 2009). The sentinel XFE patient, who presented with exceptional photosensitivity and exhibited clear signs of premature aging of virtually all organ systems, lived to only 16 years of age (Niedernhofer et al., 2006).

DNA ICLs are incredibly genotoxic lesions that impair transcription and replication by compromising DNA strand separation (Clauson et al., 2013). ICLs can be caused by endogenous metabolites (e.g., by-products of lipid peroxidation) or environmental exposures (e.g., bifunctional cancer chemotherapeutics such as cisplatin). ICLs are recognized by the Fanconi anemia (FA) repair pathway in replicating cells and by NER in non-dividing cells and are removed by endonucleases in these pathways (Ceccaldi et al., 2016). Defects in ICL repair cause FA, a rare disease in which patients exhibit accelerated bone marrow failure, increased risk of, congenital defects, endocrine dysfunction and other aging features (Nalepa and Clapp, 2018).

Mutations in the ATM, which encodes a serine/threonine kinase activated in response to DNA damage, cause ataxia telangiectasia (AT) (Thompson, 2012; Valentin-Vega et al., 2012). AT patients develop dysphagia, dysphonia, loss of motor control, diabetes as adolescents, premature aging of the hair and skin, consistent with accelerated aging (Rothblum-Oviatt et al., 2016). Mutations in POLD1 and SPRTN cause two Werner-like progeroid syndromes: mandibular hypoplasia, deafness, progeroid features, lipodystrophy syndrome, and Ruijs-Aalfs syndrome, respectively (Weedon et al., 2013; Lessel et al., 2014). Alpers-Huttenlocher syndrome, marked by progressive neurodegeneration and liver failure, is caused by mutation in the mitochondrial DNA polymerase pol ɣ (Nguyen et al., 2006). Clinically, these syndromes are distinct. The distinctions likely arise from how critical a particular DNA repair mechanism is for protecting the integrity of a specific cell type or tissue. Yet there are also tremendous commonalities in the pathophysiology of the distinct syndromes, and the commonalties largely align with changes associated with normal aging. It is humbling to recognize that the vast majority of symptoms seen in these genome instability disorders is driven by endogenous DNA damage.

It is important to note that while the focus here is on human repair-deficiency phenotypes, DNA repair and response genes are for the most part highly conserved. Murine models of these genome instability disorders largely recapitulate the human disorders and have been extremely valuable for discerning genotype:phenotype correlations (Friedberg and Meira, 2006). Studies in patient cells, yeast, and even bacteria were all essential for establishing the mechanisms of DNA repair as well signaling mechanisms in response to unrepaired DNA damage, which contributes more potently to driving aging than the damage itself.

The number of cancer survivors is increasing dramatically as a consequence of improved therapeutics (Bluethmann et al., 2016). Unfortunately, so is the awareness that those treated with genotoxic agents are aging rapidly (Hurria et al., 2016). Radiation and genotoxic chemotherapy are used to kill rapidly dividing cells, like tumor cells. However, they are not specific for cancer cells. All cells in the body experience genotoxic stress during therapy and this triggers signaling events and cell fate decisions that appear to accelerate aging. Cancer survivors display premature onset of frailty and multi-morbidities associated with old age, often decades earlier than expected (Killock, 2014). For example, 20% of childhood cancer survivors have ischemic heart disease or stroke by 50 years of age compared to 1% incidence for their siblings (Armenian et al., 2018). Whether DNA damage is increased by exposure to genotoxins or by genetic depletion of repair mechanisms, the consequence is the same: accelerated aging. This supports the notion that DNA damage, regardless of whether the source is endogenous or environmental, can be both the why and how aging occurs.

It is now well documented that chemotherapy with anthracycline, a DNA intercalating agent used for treating breast cancer, causes a significant increase in the expression of p16^INK4a in peripheral T cells, a recognized measure of aging (Liu et al., 2009; Sanoff et al., 2014). This increased p16^INK4a expression persists for nearly a year after treatment and equates to the rise in p16^INK4a expression that occurs with 15 years of chronological aging (Sanoff et al., 2014). Pediatric cancer survivors have a >2.5-fold increased incidence of disabling age-related diseases compared to their siblings by 50 years of age (Armstrong et al., 2014). This includes arthritis, cardiovascular disease, kidney, and pulmonary disease. Platinum-based therapy (causing intra- and interstrand DNA crosslinks) causes a significantly increased risk of cardiovascular disease and pre-diabetes (Baker, 2013). A central tenet of aging is frailty, which is defined as disability, reduced endurance, risk of falls, and hospitalization due to chronic diseases that typically occur at the end of life (Vetrano, 2018). Ten percent of individuals ≥65 years old are frail. Remarkably this is indistinguishable from the incidence of frailty in childhood cancer survivors in their thirties (Ness et al., 2015). Performance on physical function tests (walking and grip strength) is the same for individuals >65 years of age and survivors of pediatric cancers who are decades younger (Henderson et al., 2014). The accelerated senescence and aging observed in cancer survivors specifically treated with genotoxic agents strongly supports the view that DNA damage drives aging.

Genotoxic stress is a potent driver of cellular senescence and senescent cells play a causal role in driving aging and age-related disease. What is truly remarkable is looking within cells harboring genotoxic stress and finding how profoundly cellular homeostasis is perturb (Figure 2). For example, in tissues of DNA repair-deficient mice (caused by reduced expression of XPF-ERCC1 due to genetic depletion of Ercc1), spontaneous oxidative DNA damage accumulates rapidly, albeit not to a greater extent than what occurs with aging in repair-proficient mice (Wang et al., 2012). As a consequence of this genotoxic stress, mitochondrial and metabolic dysfunction, and increased reactive oxygen species arise, identical to changes seen with normal aging (Robinson et al., 2018). Interestingly, in the same Ercc1 mutant mice, which model XFE progeroid syndrome, senescent cells accumulate in the same organs as occurs with normal aging in mice and to roughly the same extent (Yousefzadeh et al., 2020). The profound similarities between DNA repair-deficient mice and aged mice support the notion that DNA damage drives aging. But more importantly, the cellular perturbations downstream of DNA damage reinforces ‘how’ DNA damage drives aging: by perturbing every aspect of cell biology. The consistency and uniformity with which these cellular responses to genotoxic stress occur argues that the changes are driven via signaling not as a consequence of random mutation or loss of transcription of key genes. Much remains to be elucidated about these signaling mechanisms. It is also interesting to note that the increased ROS observed in tissues of ERCC1-XPF mice is pathological and causes more DNA damage (Robinson et al., 2018), raising the point that endogenous DNA damage, if not repaired, becomes amplified.

Figure 2

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Additional evidence to support the notion that genotoxic stress profoundly perturbs cellular homeostasis includes the following. Cells from patients with XP, CS, and AT have altered energy homeostasis, impaired mitophagy, and an increased mitochondrial membrane potential, implying accumulation of dysfunctional mitochondria and increased ATP and oxygen consumption (Valentin-Vega et al., 2012; Scheibye-Knudsen et al., 2012; Fang et al., 2014). Poly(ADP-ribose) polymerase 1 (PARP1) is critical for the detection and repair of strand breaks. Persistent activation of PARP1 depletes cellular reserves of nicotinamide adenine dinucleotide (NAD⁺) (Finkel et al., 2009), a critical co-factor for many enzymes including sirtuins, which are a family of protein deacetylases and ADP-ribosyltransferases that broadly regulate gene expression and protein stability. SIRT1 also regulates mitochondrial biogenesis by deacetylating PGC-1α (peroxisome proliferator-activated receptor γ coactivator 1 α) (Finkel et al., 2009). SIRT1 activity is dramatically reduced in animal models of XP and CS due to persistent activation of PARP1 (Scheibye-Knudsen et al., 2012; Fang et al., 2014). Inhibition of PARP1 or supplementation with NAD⁺ precursors restore SIRT1 activity and improve mitochondrial homeostasis and cellular metabolism (Scheibye-Knudsen et al., 2014; Fang et al., 2016).

The gold standard for establishing a causal relationship between two events (DNA damage and aging) is to demonstrate that impaired repair accelerates aging, while improved repair slows aging. This is tricky with DNA repair as there are no drugs that stimulate DNA repair, nor is it easy to improve DNA repair genetically. DNA repair mechanisms require the coordinated action of numerous proteins. Overexpression of just one protein does not always improve repair and, in fact, can be detrimental (Shaposhnikov et al., 2015). Nevertheless, there are some hints that longevity correlates with improved responses to genotoxic stress. In the nematode Caenorhabditis elegans, 40 single gene mutations have been described that increase lifespan by at least 20% and in all cases these mutations confer resistance to UV irradiation (Johnson et al., 2002). Overexpression of human MTH1, which prevents 8-oxoG accumulation, in mice protects against neurodegeneration (De Luca et al., 2008) and extends lifespan (De Luca et al., 2013). Enhancing ATM activity in a murine model of HGPS reduces progeroid features and extends lifespan (Qian et al., 2018). Interspecies comparisons have not definitively identified a correlation between DNA repair capacity and lifespan (Austad, 2010; Cortopassi and Wang, 1996; Hart and Setlow, 1974), with a couple of exceptions. BER (but not NER) capacity is greater in cells from longer-lived rodents and non-human primates, than in shorter-lived species (Austad, 2010). Naked mole rats (lifespan 30+ years) have improved NER and BER efficiency relative to mice (lifespan 3 years) (Evdokimov et al., 2018). Many longer-lived species have increased expression or sequence optimization of key regulators of genome stability (Keane et al., 2015; Tian et al., 2017) leading to improved DSB repair in longer-lived mammals (Tian et al., 2019). Cells of centenarians have improved DNA repair activity and antioxidant capacity compared to non-centenarians (Chevanne et al., 2003; Franzke et al., 2015a). Calorie restriction (CR) is the most successful intervention to extend lifespan and/or health span in organisms ranging from yeast to mammals, including non-human primates. CR has been demonstrated to decrease the abundance of DNA damaging reactive oxygen species (reviewed in Pamplona and Barja, 2006), thereby reducing oxidative DNA damage (reviewed in Heydari et al., 2007). Consistent with this is the observation that CR reduces transcriptional stress in DNA repair defective mice (Vermeij et al., 2016). However, there is also evidence that CR might improve DNA repair, including BER, NER, and NHEJ (studies in rodents thoroughly reviewed in Heydari et al., 2007). In humans, there is evidence that CR (Matt et al., 2016), dietary micronutrients (Ames, 2010), chronic exercise, and improved socialization of the elderly (Franzke et al., 2015b) can enhance genome stability, which is ascribed to improved DNA repair capacity. However, more studies using robust measures of DNA repair capacity are needed. Collectively, there is abundant evidence that more DNA repair at least correlates with improved healthspan and lifespan.

There is now sufficient and diverse evidence to support a cogent argument that DNA damage plays a causal role in aging. This includes environmental/iatrogenic sources of genotoxic stress as well as spontaneous/endogenous genotoxic stress. DNA damage contributes to aging via cell autonomous events such as causing apoptosis, which depletes functional cells such as neurons, and via cell non-autonomous mechanisms such as triggering senescence, which can negatively impact the function of neighboring, undamaged cells through their SASP. Downstream consequences of DNA damage impinge upon all of the other pillars of aging resulting in a state of self-perpetuating damage, which likely is the ultimate cause of aging. Despite these broad consequences of genotoxic stress, there is also evidence that these consequences can be modulated through approaches aimed at slowing aging, including caloric restriction, NAD+ supplementation, or ablating senescent cells. The field is still lacking tools to measure DNA lesions and DNA repair capacity that are accessible to the broader research community. Building such a tool kit would enable more precise determination of when (under what circumstances) and where (in what organs) DNA damage truly drives aging. It also might open new opportunities in precision medicine, enabling fine tuning of DNA damage and repair to, for example, improve tumor ablation, slow the loss of irreplaceable cells, or optimize metabolism to promote repair.

1. 1. Adler AS
   2. Sinha S
   3. Kawahara TL
   4. Zhang JY
   5. Segal E
   6. Chang HY

   (2007) Motif module map reveals enforcement of aging by continual NF-kappaB activity

   Genes & Development 21:3244–3257.

   https://doi.org/10.1101/gad.1588507

   • PubMed
   • Google Scholar
2. 1. Ahmad A
   2. Robinson AR
   3. Duensing A
   4. van Drunen E
   5. Beverloo HB
   6. Weisberg DB
   7. Hasty P
   8. Hoeijmakers JH
   9. Niedernhofer LJ

   (2008) ERCC1-XPF endonuclease facilitates DNA double-strand break repair

   Molecular and Cellular Biology 28:5082–5092.

   https://doi.org/10.1128/MCB.00293-08

   • PubMed
   • Google Scholar
3. 1. Alimirah F
   2. Pulido T
   3. Valdovinos A
   4. Alptekin S
   5. Chang E
   6. Jones E
   7. Diaz DA
   8. Flores J
   9. Velarde MC
   10. Demaria M
   11. Davalos AR
   12. Wiley CD
   13. Limbad C
   14. Desprez PY
   15. Campisi J

   (2020) Cellular senescence promotes skin carcinogenesis through p38MAPK and p44/42MAPK signaling

   Cancer Research 80:3606–3619.

   https://doi.org/10.1158/0008-5472.CAN-20-0108

   • PubMed
   • Google Scholar
4. 1. Ames BN

   (2010) Prevention of mutation, Cancer, and other Age-Associated diseases by optimizing micronutrient intake

   Journal of Nucleic Acids 2010:1–11.

   https://doi.org/10.4061/2010/725071

   • Google Scholar
5. 1. Armenian SH
   2. Armstrong GT
   3. Aune G
   4. Chow EJ
   5. Ehrhardt MJ
   6. Ky B
   7. Moslehi J
   8. Mulrooney DA
   9. Nathan PC
   10. Ryan TD
   11. van der Pal HJ
   12. van Dalen EC
   13. Kremer LCM

   (2018) Cardiovascular disease in survivors of childhood Cancer: insights into epidemiology, pathophysiology, and prevention

   Journal of Clinical Oncology 36:2135–2144.

   https://doi.org/10.1200/JCO.2017.76.3920

   • PubMed
   • Google Scholar
6. 1. Armstrong GT
   2. Kawashima T
   3. Leisenring W
   4. Stratton K
   5. Stovall M
   6. Hudson MM
   7. Sklar CA
   8. Robison LL
   9. Oeffinger KC

   (2014) Aging and risk of severe, disabling, life-threatening, and fatal events in the childhood Cancer survivor study

   Journal of Clinical Oncology 32:1218–1227.

   https://doi.org/10.1200/JCO.2013.51.1055

   • PubMed
   • Google Scholar
7. 1. Austad SN

   (2010) Methusaleh's Zoo: How Nature provides us with Clues for Extending Human Health Span

   Journal of Comparative Pathology 142:S10–S21.

   https://doi.org/10.1016/j.jcpa.2009.10.024

   • Google Scholar
8. 1. Baker KS

   (2013) Impact of treatment exposures on cardiovascular risk and insulin resistance in childhood Cancer survivors , biomarkers & prevention: a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology

   Cancer Epidemiology 22:1954–1963.

   https://doi.org/10.1158/1055-9965.EPI-13-0610

   • Google Scholar
9. 1. Baker DJ
   2. Childs BG
   3. Durik M
   4. Wijers ME
   5. Sieben CJ
   6. Zhong J
   7. Saltness RA
   8. Jeganathan KB
   9. Verzosa GC
   10. Pezeshki A
   11. Khazaie K
   12. Miller JD
   13. van Deursen JM

   (2016) Naturally occurring p16(Ink4a)-positive cells shorten healthy lifespan

   Nature 530:184–189.

   https://doi.org/10.1038/nature16932

   • PubMed
   • Google Scholar
10. 1. Basisty N
    2. Kale A
    3. Patel S
    4. Campisi J
    5. Schilling B

    (2020) The power of proteomics to monitor senescence-associated secretory phenotypes and beyond: toward clinical applications

    Expert Review of Proteomics 17:297–308.

    https://doi.org/10.1080/14789450.2020.1766976

    • PubMed
    • Google Scholar
11. 1. Bhagwat N
    2. Olsen AL
    3. Wang AT
    4. Hanada K
    5. Stuckert P
    6. Kanaar R
    7. D'Andrea A
    8. Niedernhofer LJ
    9. McHugh PJ

    (2009) XPF-ERCC1 participates in the fanconi Anemia pathway of cross-link repair

    Molecular and Cellular Biology 29:6427–6437.

    https://doi.org/10.1128/MCB.00086-09

    • PubMed
    • Google Scholar
12. 1. Bluethmann SM
    2. Mariotto AB
    3. Rowland JH

    (2016) Anticipating the "Silver Tsunami": Prevalence Trajectories and Comorbidity Burden among Older Cancer Survivors in the United States

    Cancer Epidemiology Biomarkers & Prevention 25:1029–1036.

    https://doi.org/10.1158/1055-9965.EPI-16-0133

    • PubMed
    • Google Scholar
13. 1. Brooks PJ

    (2008) The 8,5'-cyclopurine-2'-deoxynucleosides: candidate neurodegenerative DNA lesions in Xeroderma Pigmentosum, and unique probes of transcription and nucleotide excision repair

    DNA Repair 7:1168–1179.

    https://doi.org/10.1016/j.dnarep.2008.03.016

    • PubMed
    • Google Scholar
14. 1. Burla R
    2. La Torre M
    3. Merigliano C
    4. Vernì F
    5. Saggio I

    (2018) Genomic instability and DNA replication defects in progeroid syndromes

    Nucleus 9:368–379.

    https://doi.org/10.1080/19491034.2018.1476793

    • PubMed
    • Google Scholar
15. 1. Cabanillas R
    2. Cadiñanos J
    3. Villameytide JA
    4. Pérez M
    5. Longo J
    6. Richard JM
    7. Alvarez R
    8. Durán NS
    9. Illán R
    10. González DJ
    11. López-Otín C

    (2011) Néstor-Guillermo progeria syndrome: a novel premature aging condition with early onset and chronic development caused by BANF1 mutations

    American Journal of Medical Genetics Part A 155A:2617–2625.

    https://doi.org/10.1002/ajmg.a.34249

    • PubMed
    • Google Scholar
16. 1. Ceccaldi R
    2. Sarangi P
    3. D'Andrea AD

    (2016) The fanconi anaemia pathway: new players and new functions

    Nature Reviews Molecular Cell Biology 17:337–349.

    https://doi.org/10.1038/nrm.2016.48

    • PubMed
    • Google Scholar
17. 1. Chandra A
    2. Lagnado AB
    3. Farr JN
    4. Monroe DG
    5. Park S
    6. Hachfeld C
    7. Tchkonia T
    8. Kirkland JL
    9. Khosla S
    10. Passos JF
    11. Pignolo RJ

    (2020) Targeted reduction of senescent cell burden alleviates focal Radiotherapy-Related bone loss

    Journal of Bone and Mineral Research 35:1119–1131.

    https://doi.org/10.1002/jbmr.3978

    • PubMed
    • Google Scholar
18. 1. Cheng Q
    2. Chen J

    (2010) Mechanism of p53 stabilization by ATM after DNA damage

    Cell Cycle 9:472–478.

    https://doi.org/10.4161/cc.9.3.10556

    • PubMed
    • Google Scholar
19. 1. Chevanne M
    2. Caldini R
    3. Tombaccini D
    4. Mocali A
    5. Gori G
    6. Paoletti F

    (2003) Comparative levels of DNA breaks and sensitivity to oxidative stress in aged and senescent human fibroblasts: a distinctive pattern for centenarians

    Biogerontology 4:97–104.

    https://doi.org/10.1023/a:1023399820770

    • PubMed
    • Google Scholar
20. 1. Chinta SJ
    2. Woods G
    3. Demaria M
    4. Rane A
    5. Zou Y
    6. McQuade A
    7. Rajagopalan S
    8. Limbad C
    9. Madden DT
    10. Campisi J
    11. Andersen JK

    (2018) Cellular senescence is induced by the environmental neurotoxin paraquat and contributes to neuropathology linked to Parkinson's Disease

    Cell Reports 22:930–940.

    https://doi.org/10.1016/j.celrep.2017.12.092

    • PubMed
    • Google Scholar
21. 1. Christoffersen NR
    2. Shalgi R
    3. Frankel LB
    4. Leucci E
    5. Lees M
    6. Klausen M
    7. Pilpel Y
    8. Nielsen FC
    9. Oren M
    10. Lund AH

    (2010) p53-independent upregulation of miR-34a during oncogene-induced senescence represses MYC

    Cell Death & Differentiation 17:236–245.

    https://doi.org/10.1038/cdd.2009.109

    • PubMed
    • Google Scholar
22. 1. Clauson C
    2. Schärer OD
    3. Niedernhofer L

    (2013) Advances in understanding the complex mechanisms of DNA interstrand cross-link repair

    Cold Spring Harbor Perspectives in Biology 5:a012732.

    https://doi.org/10.1101/cshperspect.a012732

    • PubMed
    • Google Scholar
23. 1. Cleaver JE

    (1968) Defective repair replication of DNA in xeroderma pigmentosum

    Nature 218:652–656.

    https://doi.org/10.1038/218652a0

    • PubMed
    • Google Scholar
24. 1. Coppé J-P
    2. Patil CK
    3. Rodier F
    4. Sun Y
    5. Muñoz DP
    6. Goldstein J
    7. Nelson PS
    8. Desprez P-Y
    9. Campisi J

    (2008) Senescence-Associated secretory phenotypes reveal Cell-Nonautonomous functions of oncogenic RAS and the p53 tumor suppressor

    PLOS Biology 6:e301.

    https://doi.org/10.1371/journal.pbio.0060301

    • Google Scholar
25. 1. Coppé JP
    2. Desprez PY
    3. Krtolica A
    4. Campisi J

    (2010) The senescence-associated secretory phenotype: the dark side of tumor suppression

    Annual Review of Pathology: Mechanisms of Disease 5:99–118.

    https://doi.org/10.1146/annurev-pathol-121808-102144

    • PubMed
    • Google Scholar
26. 1. Correia-Melo C
    2. Marques FD
    3. Anderson R
    4. Hewitt G
    5. Hewitt R
    6. Cole J
    7. Carroll BM
    8. Miwa S
    9. Birch J
    10. Merz A
    11. Rushton MD
    12. Charles M
    13. Jurk D
    14. Tait SW
    15. Czapiewski R
    16. Greaves L
    17. Nelson G
    18. Bohlooly-Y M
    19. Rodriguez-Cuenca S
    20. Vidal-Puig A
    21. Mann D
    22. Saretzki G
    23. Quarato G
    24. Green DR
    25. Adams PD
    26. von Zglinicki T
    27. Korolchuk VI
    28. Passos JF

    (2016) Mitochondria are required for pro-ageing features of the senescent phenotype

    The EMBO Journal 35:724–742.

    https://doi.org/10.15252/embj.201592862

    • PubMed
    • Google Scholar
27. 1. Cortopassi GA
    2. Wang E

    (1996) There is substantial agreement among interspecies estimates of DNA repair activity

    Mechanisms of Ageing and Development 91:211–218.

    https://doi.org/10.1016/S0047-6374(96)01788-5

    • PubMed
    • Google Scholar
28. 1. Croteau DL
    2. Singh DK
    3. Hoh Ferrarelli L
    4. Lu H
    5. Bohr VA

    (2012) RECQL4 in genomic instability and aging

    Trends in Genetics 28:624–631.

    https://doi.org/10.1016/j.tig.2012.08.003

    • PubMed
    • Google Scholar
29. 1. d'Adda di Fagagna F
    2. Reaper PM
    3. Clay-Farrace L
    4. Fiegler H
    5. Carr P
    6. Von Zglinicki T
    7. Saretzki G
    8. Carter NP
    9. Jackson SP

    (2003) A DNA damage checkpoint response in telomere-initiated senescence

    Nature 426:194–198.

    https://doi.org/10.1038/nature02118

    • PubMed
    • Google Scholar
30. 1. de Boer J
    2. Andressoo JO
    3. de Wit J
    4. Huijmans J
    5. Beems RB
    6. van Steeg H
    7. Weeda G
    8. van der Horst GT
    9. van Leeuwen W
    10. Themmen AP
    11. Meradji M
    12. Hoeijmakers JH

    (2002) Premature aging in mice deficient in DNA repair and transcription

    Science 296:1276–1279.

    https://doi.org/10.1126/science.1070174

    • PubMed
    • Google Scholar
31. 1. De Bont R
    2. van Larebeke N

    (2004) Endogenous DNA damage in humans: a review of quantitative data

    Mutagenesis 19:169–185.

    https://doi.org/10.1093/mutage/geh025

    • PubMed
    • Google Scholar
32. 1. De Luca G
    2. Russo MT
    3. Degan P
    4. Tiveron C
    5. Zijno A
    6. Meccia E
    7. Ventura I
    8. Mattei E
    9. Nakabeppu Y
    10. Crescenzi M
    11. Pepponi R
    12. Pèzzola A
    13. Popoli P
    14. Bignami M

    (2008) A role for oxidized DNA precursors in Huntington's disease-like striatal neurodegeneration

    PLOS Genetics 4:e1000266.

    https://doi.org/10.1371/journal.pgen.1000266

    • PubMed
    • Google Scholar
33. 1. De Luca G
    2. Ventura I
    3. Sanghez V
    4. Russo MT
    5. Ajmone-Cat MA
    6. Cacci E
    7. Martire A
    8. Popoli P
    9. Falcone G
    10. Michelini F
    11. Crescenzi M
    12. Degan P
    13. Minghetti L
    14. Bignami M
    15. Calamandrei G

    (2013) Prolonged lifespan with enhanced exploratory behavior in mice overexpressing the oxidized nucleoside triphosphatase hMTH1

    Aging Cell 12:695–705.

    https://doi.org/10.1111/acel.12094

    • PubMed
    • Google Scholar
34. 1. de Magalhães JP

    (2005) Open-minded scepticism: inferring the causal mechanisms of human ageing from genetic perturbations

    Ageing Research Reviews 4:1–22.

    https://doi.org/10.1016/j.arr.2004.05.003

    • PubMed
    • Google Scholar
35. 1. de Renty C
    2. Ellis NA

    (2017) Bloom's syndrome: Why not premature aging?: A comparison of the BLM and WRN helicases

    Ageing Research Reviews 33:36–51.

    https://doi.org/10.1016/j.arr.2016.05.010

    • PubMed
    • Google Scholar
36. 1. De Sandre-Giovannoli A
    2. Bernard R
    3. Cau P
    4. Navarro C
    5. Amiel J
    6. Boccaccio I
    7. Lyonnet S
    8. Stewart CL
    9. Munnich A
    10. Le Merrer M
    11. Lévy N

    (2003) Lamin a truncation in Hutchinson-Gilford progeria

    Science 300:2055.

    https://doi.org/10.1126/science.1084125

    • PubMed
    • Google Scholar
37. 1. Demaria M
    2. Ohtani N
    3. Youssef SA
    4. Rodier F
    5. Toussaint W
    6. Mitchell JR
    7. Laberge RM
    8. Vijg J
    9. Van Steeg H
    10. Dollé ME
    11. Hoeijmakers JH
    12. de Bruin A
    13. Hara E
    14. Campisi J

    (2014) An essential role for senescent cells in optimal wound healing through secretion of PDGF-AA

    Developmental Cell 31:722–733.

    https://doi.org/10.1016/j.devcel.2014.11.012

    • PubMed
    • Google Scholar
38. 1. Eriksson M
    2. Brown WT
    3. Gordon LB
    4. Glynn MW
    5. Singer J
    6. Scott L
    7. Erdos MR
    8. Robbins CM
    9. Moses TY
    10. Berglund P
    11. Dutra A
    12. Pak E
    13. Durkin S
    14. Csoka AB
    15. Boehnke M
    16. Glover TW
    17. Collins FS

    (2003) Recurrent de novo point mutations in lamin A cause Hutchinson-Gilford progeria syndrome

    Nature 423:293–298.

    https://doi.org/10.1038/nature01629

    • PubMed
    • Google Scholar
39. 1. Evdokimov A
    2. Kutuzov M
    3. Petruseva I
    4. Lukjanchikova N
    5. Kashina E
    6. Kolova E
    7. Zemerova T
    8. Romanenko S
    9. Perelman P
    10. Prokopov D
    11. Seluanov A
    12. Gorbunova V
    13. Graphodatsky A
    14. Trifonov V
    15. Khodyreva S
    16. Lavrik O

    (2018) Naked mole rat cells display more efficient excision repair than mouse cells

    Aging 10:1454–1473.

    https://doi.org/10.18632/aging.101482

    • PubMed
    • Google Scholar
40. 1. Faghri S
    2. Tamura D
    3. Kraemer KH
    4. Digiovanna JJ

    (2008) Trichothiodystrophy: a systematic review of 112 published cases characterises a wide spectrum of clinical manifestations

    Journal of Medical Genetics 45:609–621.

    https://doi.org/10.1136/jmg.2008.058743

    • PubMed
    • Google Scholar
41. 1. Fang EF
    2. Scheibye-Knudsen M
    3. Brace LE
    4. Kassahun H
    5. SenGupta T
    6. Nilsen H
    7. Mitchell JR
    8. Croteau DL
    9. Bohr VA

    (2014) Defective mitophagy in XPA via PARP-1 hyperactivation and NAD(+)/SIRT1 reduction

    Cell 157:882–896.

    https://doi.org/10.1016/j.cell.2014.03.026

    • PubMed
    • Google Scholar
42. 1. Fang EF
    2. Kassahun H
    3. Croteau DL
    4. Scheibye-Knudsen M
    5. Marosi K
    6. Lu H
    7. Shamanna RA
    8. Kalyanasundaram S
    9. Bollineni RC
    10. Wilson MA
    11. Iser WB
    12. Wollman BN
    13. Morevati M
    14. Li J
    15. Kerr JS
    16. Lu Q
    17. Waltz TB
    18. Tian J
    19. Sinclair DA
    20. Mattson MP
    21. Nilsen H
    22. Bohr VA

    (2016) NAD⁺replenishment improves lifespan and healthspan in ataxia telangiectasia models via mitophagy and DNA repair

    Cell Metabolism 24:566–581.

    https://doi.org/10.1016/j.cmet.2016.09.004

    • PubMed
    • Google Scholar
43. 1. Finkel T
    2. Deng CX
    3. Mostoslavsky R

    (2009) Recent progress in the biology and physiology of sirtuins

    Nature 460:587–591.

    https://doi.org/10.1038/nature08197

    • PubMed
    • Google Scholar
44. 1. Franceschi C
    2. Campisi J

    (2014) Chronic inflammation (inflammaging) and its potential contribution to age-associated diseases

    The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 69 Suppl 1:S4–S9.

    https://doi.org/10.1093/gerona/glu057

    • PubMed
    • Google Scholar
45. 1. Franzke B
    2. Neubauer O
    3. Wagner K-H

    (2015a) Super DNAging—New insights into DNA integrity, genome stability and telomeres in the oldest old

    Mutation Research/Reviews in Mutation Research 766:48–57.

    https://doi.org/10.1016/j.mrrev.2015.08.001

    • Google Scholar
46. 1. Franzke B
    2. Halper B
    3. Hofmann M
    4. Oesen S
    5. Pierson B
    6. Cremer A
    7. Bacher E
    8. Fuchs B
    9. Baierl A
    10. Tosevska A
    11. Strasser EM
    12. Wessner B
    13. Wagner KH
    14. Vienna Active Ageing Study Group (VAAS)

    (2015b) The effect of six months of elastic band resistance training, nutritional supplementation or cognitive training on chromosomal damage in institutionalized elderly

    Experimental Gerontology 65:16–22.

    https://doi.org/10.1016/j.exger.2015.03.001

    • PubMed
    • Google Scholar
47. Book

    1. Friedberg EC

    (2006) DNA Repair and Mutagenesis

    Wiley.

    https://doi.org/10.1128/9781555816704

    • Google Scholar
48. 1. Friedberg EC
    2. Meira LB

    (2006) Database of mouse strains carrying targeted mutations in genes affecting biological responses to DNA damage version 7

    DNA Repair 5:189–209.

    https://doi.org/10.1016/j.dnarep.2005.09.009

    • PubMed
    • Google Scholar
49. 1. Ghosh AK
    2. Rossi ML
    3. Singh DK
    4. Dunn C
    5. Ramamoorthy M
    6. Croteau DL
    7. Liu Y
    8. Bohr VA

    (2012) RECQL4, the protein mutated in Rothmund-Thomson syndrome, functions in telomere maintenance

    Journal of Biological Chemistry 287:196–209.

    https://doi.org/10.1074/jbc.M111.295063

    • PubMed
    • Google Scholar
50. 1. Gorgoulis V
    2. Adams PD
    3. Alimonti A
    4. Bennett DC
    5. Bischof O
    6. Bishop C
    7. Campisi J
    8. Collado M
    9. Evangelou K
    10. Ferbeyre G
    11. Gil J
    12. Hara E
    13. Krizhanovsky V
    14. Jurk D
    15. Maier AB
    16. Narita M
    17. Niedernhofer L
    18. Passos JF
    19. Robbins PD
    20. Schmitt CA
    21. Sedivy J
    22. Vougas K
    23. von Zglinicki T
    24. Zhou D
    25. Serrano M
    26. Demaria M

    (2019) Cellular senescence: defining a path forward

    Cell 179:813–827.

    https://doi.org/10.1016/j.cell.2019.10.005

    • PubMed
    • Google Scholar
51. 1. Hanada K
    2. Hickson ID

    (2007) Molecular genetics of RecQ helicase disorders

    Cellular and Molecular Life Sciences 64:2306–2322.

    https://doi.org/10.1007/s00018-007-7121-z

    • PubMed
    • Google Scholar
52. 1. Harley CB
    2. Futcher AB
    3. Greider CW

    (1990) Telomeres shorten during ageing of human fibroblasts

    Nature 345:458–460.

    https://doi.org/10.1038/345458a0

    • PubMed
    • Google Scholar
53. 1. Hart RW
    2. Setlow RB

    (1974) Correlation between deoxyribonucleic acid excision-repair and life-span in a number of mammalian species

    PNAS 71:2169–2173.

    https://doi.org/10.1073/pnas.71.6.2169

    • PubMed
    • Google Scholar
54. 1. Hayflick L

    (1965) The limited in vitro lifetime of human diploid cell strains

    Experimental Cell Research 37:614–636.

    https://doi.org/10.1016/0014-4827(65)90211-9

    • Google Scholar
55. 1. Hayflick L
    2. Moorhead PS

    (1961) The serial cultivation of human diploid cell strains

    Experimental Cell Research 25:585–621.

    https://doi.org/10.1016/0014-4827(61)90192-6

    • PubMed
    • Google Scholar
56. 1. Helman A
    2. Klochendler A
    3. Azazmeh N
    4. Gabai Y
    5. Horwitz E
    6. Anzi S
    7. Swisa A
    8. Condiotti R
    9. Granit RZ
    10. Nevo Y
    11. Fixler Y
    12. Shreibman D
    13. Zamir A
    14. Tornovsky-Babeay S
    15. Dai C
    16. Glaser B
    17. Powers AC
    18. Shapiro AM
    19. Magnuson MA
    20. Dor Y
    21. Ben-Porath I

    (2016) p16(Ink4a)-induced senescence of pancreatic beta cells enhances insulin secretion

    Nature Medicine 22:412–420.

    https://doi.org/10.1038/nm.4054

    • PubMed
    • Google Scholar
57. 1. Henderson TO
    2. Ness KK
    3. Cohen HJ

    (2014) Accelerated aging among Cancer survivors: from pediatrics to geriatrics

    American Society of Clinical Oncology Educational Book 1:e423–e430.

    https://doi.org/10.14694/EdBook_AM.2014.34.e423

    • Google Scholar
58. 1. Hennekam RC

    (2006) Hutchinson-Gilford progeria syndrome: review of the phenotype

    American Journal of Medical Genetics Part A 140:2603–2624.

    https://doi.org/10.1002/ajmg.a.31346

    • PubMed
    • Google Scholar
59. 1. Heydari AR
    2. Unnikrishnan A
    3. Lucente LV
    4. Richardson A

    (2007) Caloric restriction and genomic stability

    Nucleic Acids Research 35:7485–7496.

    https://doi.org/10.1093/nar/gkm860

    • PubMed
    • Google Scholar
60. 1. Hoeijmakers JHJ

    (2009) DNA damage, aging, and Cancer

    New England Journal of Medicine 361:1475–1485.

    https://doi.org/10.1056/NEJMra0804615

    • Google Scholar
61. Conference

    1. Hurria A
    2. Jones L
    3. Muss HB

    (2016)

    Cancer treatment as an accelerated aging process: assessment, biomarkers, and interventions

    American Society of Clinical Oncology Educational Book. American Society of Clinical Oncology. Annual Meeting. pp. e516–e522.

    • Google Scholar
62. 1. Itahana K
    2. Campisi J
    3. Dimri GP

    (2007) Methods to detect biomarkers of cellular senescence: the senescence-associated beta-galactosidase assay

    Methods in Molecular Biology 371:21–31.

    https://doi.org/10.1007/978-1-59745-361-5_3

    • PubMed
    • Google Scholar
63. 1. Jackson AL
    2. Loeb LA

    (2001) The contribution of endogenous sources of DNA damage to the multiple mutations in Cancer

    Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis 477:7–21.

    https://doi.org/10.1016/S0027-5107(01)00091-4

    • PubMed
    • Google Scholar
64. 1. Jeyapalan JC
    2. Ferreira M
    3. Sedivy JM
    4. Herbig U

    (2007) Accumulation of senescent cells in Mitotic tissue of aging primates

    Mechanisms of Ageing and Development 128:36–44.

    https://doi.org/10.1016/j.mad.2006.11.008

    • PubMed
    • Google Scholar
65. 1. Johnson TE
    2. Henderson S
    3. Murakami S
    4. de Castro E
    5. de Castro SH
    6. Cypser J
    7. Rikke B
    8. Tedesco P
    9. Link C

    (2002) Longevity genes in the nematode Caenorhabditis elegans also mediate increased resistance to stress and prevent disease

    Journal of Inherited Metabolic Disease 25:197–206.

    https://doi.org/10.1023/a:1015677828407

    • PubMed
    • Google Scholar
66. 1. Kang C
    2. Xu Q
    3. Martin TD
    4. Li MZ
    5. Demaria M
    6. Aron L
    7. Lu T
    8. Yankner BA
    9. Campisi J
    10. Elledge SJ

    (2015) The DNA damage response induces inflammation and senescence by inhibiting autophagy of GATA4

    Science 349:aaa5612.

    https://doi.org/10.1126/science.aaa5612

    • PubMed
    • Google Scholar
67. 1. Keane M
    2. Semeiks J
    3. Webb AE
    4. Li YI
    5. Quesada V
    6. Craig T
    7. Madsen LB
    8. van Dam S
    9. Brawand D
    10. Marques PI
    11. Michalak P
    12. Kang L
    13. Bhak J
    14. Yim HS
    15. Grishin NV
    16. Nielsen NH
    17. Heide-Jørgensen MP
    18. Oziolor EM
    19. Matson CW
    20. Church GM
    21. Stuart GW
    22. Patton JC
    23. George JC
    24. Suydam R
    25. Larsen K
    26. López-Otín C
    27. O'Connell MJ
    28. Bickham JW
    29. Thomsen B
    30. de Magalhães JP

    (2015) Insights into the evolution of longevity from the bowhead whale genome

    Cell Reports 10:112–122.

    https://doi.org/10.1016/j.celrep.2014.12.008

    • PubMed
    • Google Scholar
68. 1. Kennedy BK
    2. Berger SL
    3. Brunet A
    4. Campisi J
    5. Cuervo AM
    6. Epel ES
    7. Franceschi C
    8. Lithgow GJ
    9. Morimoto RI
    10. Pessin JE
    11. Rando TA
    12. Richardson A
    13. Schadt EE
    14. Wyss-Coray T
    15. Sierra F

    (2014) Geroscience: linking aging to chronic disease

    Cell 159:709–713.

    https://doi.org/10.1016/j.cell.2014.10.039

    • PubMed
    • Google Scholar
69. 1. Killock D

    (2014) Chemotherapy: life gained, years lost?

    Nature Reviews. Clinical Oncology 11:303.

    https://doi.org/10.1038/nrclinonc.2014.67

    • PubMed
    • Google Scholar
70. 1. Kirkland JL
    2. Tchkonia T

    (2020) Senolytic drugs: from discovery to translation

    Journal of Internal Medicine 288:518–536.

    https://doi.org/10.1111/joim.13141

    • PubMed
    • Google Scholar
71. 1. Kirkwood TB

    (2005) Understanding the odd science of aging

    Cell 120:437–447.

    https://doi.org/10.1016/j.cell.2005.01.027

    • PubMed
    • Google Scholar
72. 1. Kraemer KH
    2. DiGiovanna JJ

    (2015) Forty years of research on xeroderma pigmentosum at the US national institutes of health

    Photochemistry and Photobiology 91:452–459.

    https://doi.org/10.1111/php.12345

    • PubMed
    • Google Scholar
73. 1. Krizhanovsky V
    2. Yon M
    3. Dickins RA
    4. Hearn S
    5. Simon J
    6. Miething C
    7. Yee H
    8. Zender L
    9. Lowe SW

    (2008) Senescence of activated stellate cells limits liver fibrosis

    Cell 134:657–667.

    https://doi.org/10.1016/j.cell.2008.06.049

    • PubMed
    • Google Scholar
74. 1. Kudlow BA
    2. Kennedy BK
    3. Monnat RJ

    (2007) Werner and Hutchinson-Gilford progeria syndromes: mechanistic basis of human progeroid diseases

    Nature Reviews Molecular Cell Biology 8:394–404.

    https://doi.org/10.1038/nrm2161

    • PubMed
    • Google Scholar
75. 1. Kuilman T
    2. Michaloglou C
    3. Vredeveld LC
    4. Douma S
    5. van Doorn R
    6. Desmet CJ
    7. Aarden LA
    8. Mooi WJ
    9. Peeper DS

    (2008) Oncogene-induced senescence relayed by an interleukin-dependent inflammatory network

    Cell 133:1019–1031.

    https://doi.org/10.1016/j.cell.2008.03.039

    • PubMed
    • Google Scholar
76. 1. Lawless C
    2. Wang C
    3. Jurk D
    4. Merz A
    5. Zglinicki T
    6. Passos JF

    (2010) Quantitative assessment of markers for cell senescence

    Experimental Gerontology 45:772–778.

    https://doi.org/10.1016/j.exger.2010.01.018

    • PubMed
    • Google Scholar
77. 1. Lehmann AR
    2. McGibbon D
    3. Stefanini M

    (2011) Xeroderma pigmentosum

    Orphanet Journal of Rare Diseases 6:70.

    https://doi.org/10.1186/1750-1172-6-70

    • PubMed
    • Google Scholar
78. 1. Lessel D
    2. Vaz B
    3. Halder S
    4. Lockhart PJ
    5. Marinovic-Terzic I
    6. Lopez-Mosqueda J
    7. Philipp M
    8. Sim JC
    9. Smith KR
    10. Oehler J
    11. Cabrera E
    12. Freire R
    13. Pope K
    14. Nahid A
    15. Norris F
    16. Leventer RJ
    17. Delatycki MB
    18. Barbi G
    19. von Ameln S
    20. Högel J
    21. Degoricija M
    22. Fertig R
    23. Burkhalter MD
    24. Hofmann K
    25. Thiele H
    26. Altmüller J
    27. Nürnberg G
    28. Nürnberg P
    29. Bahlo M
    30. Martin GM
    31. Aalfs CM
    32. Oshima J
    33. Terzic J
    34. Amor DJ
    35. Dikic I
    36. Ramadan K
    37. Kubisch C

    (2014) Mutations in SPRTN cause early onset hepatocellular carcinoma, genomic instability and progeroid features

    Nature Genetics 46:1239–1244.

    https://doi.org/10.1038/ng.3103

    • PubMed
    • Google Scholar
79. 1. Lindahl T

    (1993) Instability and decay of the primary structure of DNA

    Nature 362:709–715.

    https://doi.org/10.1038/362709a0

    • PubMed
    • Google Scholar
80. 1. Liu B
    2. Wang J
    3. Chan KM
    4. Tjia WM
    5. Deng W
    6. Guan X
    7. Huang JD
    8. Li KM
    9. Chau PY
    10. Chen DJ
    11. Pei D
    12. Pendas AM
    13. Cadiñanos J
    14. López-Otín C
    15. Tse HF
    16. Hutchison C
    17. Chen J
    18. Cao Y
    19. Cheah KS
    20. Tryggvason K
    21. Zhou Z

    (2005) Genomic instability in laminopathy-based premature aging

    Nature Medicine 11:780–785.

    https://doi.org/10.1038/nm1266

    • PubMed
    • Google Scholar
81. 1. Liu Y
    2. Sanoff HK
    3. Cho H
    4. Burd CE
    5. Torrice C
    6. Ibrahim JG
    7. Thomas NE
    8. Sharpless NE

    (2009) Expression of p16(INK4a) in peripheral blood T-cells is a biomarker of human aging

    Aging Cell 8:439–448.

    https://doi.org/10.1111/j.1474-9726.2009.00489.x

    • PubMed
    • Google Scholar
82. 1. Loi M
    2. Cenni V
    3. Duchi S
    4. Squarzoni S
    5. Lopez-Otin C
    6. Foisner R
    7. Lattanzi G
    8. Capanni C

    (2016) Barrier-to-Autointegration factor (BAF) involvement in prelamin A-related chromatin organization changes

    Oncotarget 7:15662–15677.

    https://doi.org/10.18632/oncotarget.6697

    • Google Scholar
83. 1. Martin GM
    2. Oshima J

    (2000) Lessons from human progeroid syndromes

    Nature 408:263–266.

    https://doi.org/10.1038/35041705

    • PubMed
    • Google Scholar
84. 1. Matjusaitis M
    2. Chin G
    3. Sarnoski EA
    4. Stolzing A

    (2016) Biomarkers to identify and isolate senescent cells

    Ageing Research Reviews 29:1–12.

    https://doi.org/10.1016/j.arr.2016.05.003

    • PubMed
    • Google Scholar
85. 1. Matt K
    2. Burger K
    3. Gebhard D
    4. Bergemann J

    (2016) Influence of calorie reduction on DNA repair capacity of human peripheral blood mononuclear cells

    Mechanisms of Ageing and Development 154:24–29.

    https://doi.org/10.1016/j.mad.2016.02.008

    • PubMed
    • Google Scholar
86. 1. Meek DW
    2. Anderson CW

    (2009) Posttranslational modification of p53: cooperative integrators of function

    Cold Spring Harbor Perspectives in Biology 1:a000950.

    https://doi.org/10.1101/cshperspect.a000950

    • PubMed
    • Google Scholar
87. 1. Menck CF
    2. Munford V

    (2014) DNA repair diseases: what do they tell us about Cancer and aging?

    Genetics and Molecular Biology 37:220–233.

    https://doi.org/10.1590/S1415-47572014000200008

    • PubMed
    • Google Scholar
88. 1. Miyamoto S

    (2011) Nuclear initiated NF-κB signaling: nemo and ATM take center stage

    Cell Research 21:116–130.

    https://doi.org/10.1038/cr.2010.179

    • PubMed
    • Google Scholar
89. 1. Mouret S
    2. Baudouin C
    3. Charveron M
    4. Favier A
    5. Cadet J
    6. Douki T

    (2006) Cyclobutane pyrimidine dimers are predominant DNA lesions in whole human skin exposed to UVA radiation

    PNAS 103:13765–13770.

    https://doi.org/10.1073/pnas.0604213103

    • PubMed
    • Google Scholar
90. 1. Nair RR
    2. Bagheri M
    3. Saini DK

    (2015) Temporally distinct roles of ATM and ROS in genotoxic-stress-dependent induction and maintenance of cellular senescence

    Journal of Cell Science 128:342–353.

    https://doi.org/10.1242/jcs.159517

    • PubMed
    • Google Scholar
91. 1. Nalepa G
    2. Clapp DW

    (2018) Fanconi anaemia and Cancer: an intricate relationship

    Nature Reviews Cancer 18:168–185.

    https://doi.org/10.1038/nrc.2017.116

    • PubMed
    • Google Scholar
92. 1. Nance MA
    2. Berry SA

    (1992) Cockayne syndrome: review of 140 cases

    American Journal of Medical Genetics 42:68–84.

    https://doi.org/10.1002/ajmg.1320420115

    • PubMed
    • Google Scholar
93. 1. Ness KK
    2. Armstrong GT
    3. Kundu M
    4. Wilson CL
    5. Tchkonia T
    6. Kirkland JL

    (2015) Frailty in childhood Cancer survivors

    Cancer 121:1540–1547.

    https://doi.org/10.1002/cncr.29211

    • PubMed
    • Google Scholar
94. 1. Nguyen KV
    2. Sharief FS
    3. Chan SS
    4. Copeland WC
    5. Naviaux RK

    (2006) Molecular diagnosis of alpers syndrome

    Journal of Hepatology 45:108–116.

    https://doi.org/10.1016/j.jhep.2005.12.026

    • PubMed
    • Google Scholar
95. 1. Nguyen GH
    2. Tang W
    3. Robles AI
    4. Beyer RP
    5. Gray LT
    6. Welsh JA
    7. Schetter AJ
    8. Kumamoto K
    9. Wang XW
    10. Hickson ID
    11. Maizels N
    12. Monnat RJ
    13. Harris CC

    (2014) Regulation of gene expression by the BLM helicase correlates with the presence of G-quadruplex DNA motifs

    PNAS 111:9905–9910.

    https://doi.org/10.1073/pnas.1404807111

    • PubMed
    • Google Scholar
96. 1. Niedernhofer LJ
    2. Garinis GA
    3. Raams A
    4. Lalai AS
    5. Robinson AR
    6. Appeldoorn E
    7. Odijk H
    8. Oostendorp R
    9. Ahmad A
    10. van Leeuwen W
    11. Theil AF
    12. Vermeulen W
    13. van der Horst GT
    14. Meinecke P
    15. Kleijer WJ
    16. Vijg J
    17. Jaspers NG
    18. Hoeijmakers JH

    (2006) A new progeroid syndrome reveals that genotoxic stress suppresses the somatotroph Axis

    Nature 444:1038–1043.

    https://doi.org/10.1038/nature05456

    • PubMed
    • Google Scholar
97. 1. Oberdoerffer P
    2. Michan S
    3. McVay M
    4. Mostoslavsky R
    5. Vann J
    6. Park SK
    7. Hartlerode A
    8. Stegmuller J
    9. Hafner A
    10. Loerch P
    11. Wright SM
    12. Mills KD
    13. Bonni A
    14. Yankner BA
    15. Scully R
    16. Prolla TA
    17. Alt FW
    18. Sinclair DA

    (2008) SIRT1 redistribution on chromatin promotes genomic stability but alters gene expression during aging

    Cell 135:907–918.

    https://doi.org/10.1016/j.cell.2008.10.025

    • PubMed
    • Google Scholar
98. 1. Ogrodnik M
    2. Miwa S
    3. Tchkonia T
    4. Tiniakos D
    5. Wilson CL
    6. Lahat A
    7. Day CP
    8. Burt A
    9. Palmer A
    10. Anstee QM
    11. Grellscheid SN
    12. Hoeijmakers JHJ
    13. Barnhoorn S
    14. Mann DA
    15. Bird TG
    16. Vermeij WP
    17. Kirkland JL
    18. Passos JF
    19. von Zglinicki T
    20. Jurk D

    (2017) Cellular senescence drives age-dependent hepatic steatosis

    Nature Communications 8:15691.

    https://doi.org/10.1038/ncomms15691

    • PubMed
    • Google Scholar
99. 1. Pamplona R
    2. Barja G

    (2006) Mitochondrial oxidative stress, aging and caloric restriction: the protein and methionine connection

    Biochimica Et Biophysica Acta (BBA) - Bioenergetics 1757:496–508.

    https://doi.org/10.1016/j.bbabio.2006.01.009

    • Google Scholar
100. 1. Parrinello S
     2. Samper E
     3. Krtolica A
     4. Goldstein J
     5. Melov S
     6. Campisi J

     (2003) Oxygen sensitivity severely limits the replicative lifespan of murine fibroblasts

     Nature Cell Biology 5:741–747.

     https://doi.org/10.1038/ncb1024

     • PubMed
     • Google Scholar
101. 1. Qian M
     2. Liu Z
     3. Peng L
     4. Tang X
     5. Meng F
     6. Ao Y
     7. Zhou M
     8. Wang M
     9. Cao X
     10. Qin B
     11. Wang Z
     12. Zhou Z
     13. Wang G
     14. Gao Z
     15. Xu J
     16. Liu B

     (2018) Boosting ATM activity alleviates aging and extends lifespan in a mouse model of progeria

     eLife 7:e34836.

     https://doi.org/10.7554/eLife.34836

     • PubMed
     • Google Scholar
102. 1. Reinhardt HC
     2. Schumacher B

     (2012) The p53 network: cellular and systemic DNA damage responses in aging and Cancer

     Trends in Genetics 28:128–136.

     https://doi.org/10.1016/j.tig.2011.12.002

     • PubMed
     • Google Scholar
103. 1. Robinson AR
     2. Yousefzadeh MJ
     3. Rozgaja TA
     4. Wang J
     5. Li X
     6. Tilstra JS
     7. Feldman CH
     8. Gregg SQ
     9. Johnson CH
     10. Skoda EM
     11. Frantz MC
     12. Bell-Temin H
     13. Pope-Varsalona H
     14. Gurkar AU
     15. Nasto LA
     16. Robinson RAS
     17. Fuhrmann-Stroissnigg H
     18. Czerwinska J
     19. McGowan SJ
     20. Cantu-Medellin N
     21. Harris JB
     22. Maniar S
     23. Ross MA
     24. Trussoni CE
     25. LaRusso NF
     26. Cifuentes-Pagano E
     27. Pagano PJ
     28. Tudek B
     29. Vo NV
     30. Rigatti LH
     31. Opresko PL
     32. Stolz DB
     33. Watkins SC
     34. Burd CE
     35. Croix CMS
     36. Siuzdak G
     37. Yates NA
     38. Robbins PD
     39. Wang Y
     40. Wipf P
     41. Kelley EE
     42. Niedernhofer LJ

     (2018) Spontaneous DNA damage to the nuclear genome promotes senescence, redox imbalance and aging

     Redox Biology 17:259–273.

     https://doi.org/10.1016/j.redox.2018.04.007

     • PubMed
     • Google Scholar
104. 1. Rodier F
     2. Muñoz DP
     3. Teachenor R
     4. Chu V
     5. Le O
     6. Bhaumik D
     7. Coppé JP
     8. Campeau E
     9. Beauséjour CM
     10. Kim SH
     11. Davalos AR
     12. Campisi J

     (2011) DNA-SCARS: distinct nuclear structures that sustain damage-induced senescence growth arrest and inflammatory cytokine secretion

     Journal of Cell Science 124:68–81.

     https://doi.org/10.1242/jcs.071340

     • PubMed
     • Google Scholar
105. 1. Roos CM
     2. Zhang B
     3. Palmer AK
     4. Ogrodnik MB
     5. Pirtskhalava T
     6. Thalji NM
     7. Hagler M
     8. Jurk D
     9. Smith LA
     10. Casaclang-Verzosa G
     11. Zhu Y
     12. Schafer MJ
     13. Tchkonia T
     14. Kirkland JL
     15. Miller JD

     (2016) Chronic senolytic treatment alleviates established vasomotor dysfunction in aged or atherosclerotic mice

     Aging Cell 15:973–977.

     https://doi.org/10.1111/acel.12458

     • PubMed
     • Google Scholar
106. 1. Rothblum-Oviatt C
     2. Wright J
     3. Lefton-Greif MA
     4. McGrath-Morrow SA
     5. Crawford TO
     6. Lederman HM

     (2016) Ataxia telangiectasia: a review

     Orphanet Journal of Rare Diseases 11:159.

     https://doi.org/10.1186/s13023-016-0543-7

     • PubMed
     • Google Scholar
107. 1. Sancar A
     2. Lindsey-Boltz LA
     3. Unsal-Kaçmaz K
     4. Linn S

     (2004) Molecular mechanisms of mammalian DNA repair and the DNA damage checkpoints

     Annual Review of Biochemistry 73:39–85.

     https://doi.org/10.1146/annurev.biochem.73.011303.073723

     • PubMed
     • Google Scholar
108. 1. Sander M
     2. Cadet J
     3. Casciano DA
     4. Galloway SM
     5. Marnett LJ
     6. Novak RF
     7. Pettit SD
     8. Preston RJ
     9. Skare JA
     10. Williams GM
     11. Van Houten B
     12. Gollapudi BB

     (2005) Proceedings of a workshop on DNA adducts: biological significance and applications to risk assessment Washington, DC, April 13-14, 2004

     Toxicology and Applied Pharmacology 208:1–20.

     https://doi.org/10.1016/j.taap.2004.12.012

     • PubMed
     • Google Scholar
109. 1. Sanoff HK
     2. Deal AM
     3. Krishnamurthy J
     4. Torrice C
     5. Dillon P
     6. Sorrentino J
     7. Ibrahim JG
     8. Jolly TA
     9. Williams G
     10. Carey LA
     11. Drobish A
     12. Gordon B-B
     13. Alston S
     14. Hurria A
     15. Kleinhans K
     16. Rudolph KL
     17. Sharpless NE
     18. Muss HB

     (2014) Effect of cytotoxic chemotherapy on markers of molecular age in patients with breast Cancer

     JNCI: Journal of the National Cancer Institute 106:dju057.

     https://doi.org/10.1093/jnci/dju057

     • Google Scholar
110. 1. Schärer OD

     (2013) Nucleotide excision repair in eukaryotes

     Cold Spring Harbor Perspectives in Biology 5:a012609.

     https://doi.org/10.1101/cshperspect.a012609

     • PubMed
     • Google Scholar
111. 1. Scheibye-Knudsen M
     2. Ramamoorthy M
     3. Sykora P
     4. Maynard S
     5. Lin P-C
     6. Minor RK
     7. Wilson DM
     8. Cooper M
     9. Spencer R
     10. de Cabo R
     11. Croteau DL
     12. Bohr VA

     (2012) Cockayne syndrome group B protein prevents the accumulation of damaged mitochondria by promoting mitochondrial autophagy

     Journal of Experimental Medicine 209:855–869.

     https://doi.org/10.1084/jem.20111721

     • Google Scholar
112. 1. Scheibye-Knudsen M
     2. Mitchell SJ
     3. Fang EF
     4. Iyama T
     5. Ward T
     6. Wang J
     7. Dunn CA
     8. Singh N
     9. Veith S
     10. Hasan-Olive MM
     11. Mangerich A
     12. Wilson MA
     13. Mattson MP
     14. Bergersen LH
     15. Cogger VC
     16. Warren A
     17. Le Couteur DG
     18. Moaddel R
     19. Wilson DM
     20. Croteau DL
     21. de Cabo R
     22. Bohr VA

     (2014) A high-fat diet and NAD(+) activate Sirt1 to rescue premature aging in cockayne syndrome

     Cell Metabolism 20:840–855.

     https://doi.org/10.1016/j.cmet.2014.10.005

     • PubMed
     • Google Scholar
113. 1. Sears CR
     2. Turchi JJ

     (2012) Complex Cisplatin-Double Strand Break (DSB) Lesions Directly Impair Cellular Non-Homologous End-Joining (NHEJ) Independent of Downstream Damage Response (DDR) Pathways*

     Journal of Biological Chemistry 287:24263–24272.

     https://doi.org/10.1074/jbc.M112.344911

     • Google Scholar
114. 1. Senturk E
     2. Manfredi JJ

     (2013) p53 and cell cycle effects after DNA damage

     Methods in Molecular Biology 962:49–61.

     https://doi.org/10.1007/978-1-62703-236-0_4

     • PubMed
     • Google Scholar
115. 1. Serrano M
     2. Lin AW
     3. McCurrach ME
     4. Beach D
     5. Lowe SW

     (1997) Oncogenic ras provokes premature cell senescence associated with accumulation of p53 and p16INK4a

     Cell 88:593–602.

     https://doi.org/10.1016/S0092-8674(00)81902-9

     • PubMed
     • Google Scholar
116. 1. Shaposhnikov M
     2. Proshkina E
     3. Shilova L
     4. Zhavoronkov A
     5. Moskalev A

     (2015) Lifespan and stress resistance in Drosophila with overexpressed DNA repair genes

     Scientific Reports 5:srep15299.

     https://doi.org/10.1038/srep15299

     • Google Scholar
117. 1. Sharpless NE
     2. Sherr CJ

     (2015) Forging a signature of in vivo senescence

     Nature Reviews Cancer 15:397–408.

     https://doi.org/10.1038/nrc3960

     • PubMed
     • Google Scholar
118. 1. Storer M
     2. Mas A
     3. Robert-Moreno A
     4. Pecoraro M
     5. Ortells MC
     6. Di Giacomo V
     7. Yosef R
     8. Pilpel N
     9. Krizhanovsky V
     10. Sharpe J
     11. Keyes WM

     (2013) Senescence is a developmental mechanism that contributes to embryonic growth and patterning

     Cell 155:1119–1130.

     https://doi.org/10.1016/j.cell.2013.10.041

     • PubMed
     • Google Scholar
119. 1. Sugimoto M

     (2014) A cascade leading to premature aging phenotypes including abnormal tumor profiles in werner syndrome (review)

     International Journal of Molecular Medicine 33:247–253.

     https://doi.org/10.3892/ijmm.2013.1592

     • PubMed
     • Google Scholar
120. 1. Takai H
     2. Smogorzewska A
     3. de Lange T

     (2003) DNA damage foci at dysfunctional telomeres

     Current Biology 13:1549–1556.

     https://doi.org/10.1016/S0960-9822(03)00542-6

     • PubMed
     • Google Scholar
121. 1. Tasdemir N
     2. Banito A
     3. Roe JS
     4. Alonso-Curbelo D
     5. Camiolo M
     6. Tschaharganeh DF
     7. Huang CH
     8. Aksoy O
     9. Bolden JE
     10. Chen CC
     11. Fennell M
     12. Thapar V
     13. Chicas A
     14. Vakoc CR
     15. Lowe SW

     (2016) BRD4 connects enhancer remodeling to senescence immune surveillance

     Cancer Discovery 6:612–629.

     https://doi.org/10.1158/2159-8290.CD-16-0217

     • PubMed
     • Google Scholar
122. 1. Thompson LH

     (2012) Recognition, signaling, and repair of DNA double-strand breaks produced by ionizing radiation in mammalian cells: the molecular choreography

     Mutation Research/Reviews in Mutation Research 751:158–246.

     https://doi.org/10.1016/j.mrrev.2012.06.002

     • PubMed
     • Google Scholar
123. 1. Tian X
     2. Seluanov A
     3. Gorbunova V

     (2017) Molecular mechanisms determining lifespan in short- and Long-Lived species

     Trends in Endocrinology & Metabolism 28:722–734.

     https://doi.org/10.1016/j.tem.2017.07.004

     • PubMed
     • Google Scholar
124. 1. Tian X
     2. Firsanov D
     3. Zhang Z
     4. Cheng Y
     5. Luo L
     6. Tombline G
     7. Tan R
     8. Simon M
     9. Henderson S
     10. Steffan J
     11. Goldfarb A
     12. Tam J
     13. Zheng K
     14. Cornwell A
     15. Johnson A
     16. Yang JN
     17. Mao Z
     18. Manta B
     19. Dang W
     20. Zhang Z
     21. Vijg J
     22. Wolfe A
     23. Moody K
     24. Kennedy BK
     25. Bohmann D
     26. Gladyshev VN
     27. Seluanov A
     28. Gorbunova V

     (2019) SIRT6 is responsible for more efficient DNA Double-Strand break repair in Long-Lived species

     Cell 177:622–638.

     https://doi.org/10.1016/j.cell.2019.03.043

     • PubMed
     • Google Scholar
125. 1. Tilstra JS
     2. Clauson CL
     3. Niedernhofer LJ
     4. Robbins PD

     (2011)

     NF-kappaB in aging and disease

     Aging and Disease 2:449–465.

     • PubMed
     • Google Scholar
126. 1. Tresini M
     2. Warmerdam DO
     3. Kolovos P
     4. Snijder L
     5. Vrouwe MG
     6. Demmers JA
     7. van IJcken WF
     8. Grosveld FG
     9. Medema RH
     10. Hoeijmakers JH
     11. Mullenders LH
     12. Vermeulen W
     13. Marteijn JA

     (2015) The core spliceosome as target and effector of non-canonical ATM signalling

     Nature 523:53–58.

     https://doi.org/10.1038/nature14512

     • PubMed
     • Google Scholar
127. 1. Uchiumi F
     2. Seki M
     3. Furuichi Y

     (2015) Helicases and human diseases

     Frontiers in Genetics 6:39.

     https://doi.org/10.3389/fgene.2015.00039

     • PubMed
     • Google Scholar
128. 1. Valentin-Vega YA
     2. Maclean KH
     3. Tait-Mulder J
     4. Milasta S
     5. Steeves M
     6. Dorsey FC
     7. Cleveland JL
     8. Green DR
     9. Kastan MB

     (2012) Mitochondrial dysfunction in ataxia-telangiectasia

     Blood 119:1490–1500.

     https://doi.org/10.1182/blood-2011-08-373639

     • PubMed
     • Google Scholar
129. 1. Vermeij WP
     2. Dollé ME
     3. Reiling E
     4. Jaarsma D
     5. Payan-Gomez C
     6. Bombardieri CR
     7. Wu H
     8. Roks AJ
     9. Botter SM
     10. van der Eerden BC
     11. Youssef SA
     12. Kuiper RV
     13. Nagarajah B
     14. van Oostrom CT
     15. Brandt RM
     16. Barnhoorn S
     17. Imholz S
     18. Pennings JL
     19. de Bruin A
     20. Gyenis Á
     21. Pothof J
     22. Vijg J
     23. van Steeg H
     24. Hoeijmakers JH

     (2016) Restricted diet delays accelerated ageing and genomic stress in DNA-repair-deficient mice

     Nature 537:427–431.

     https://doi.org/10.1038/nature19329

     • PubMed
     • Google Scholar
130. 1. Vetrano DL

     (2018) Frailty and multimorbidity: a systematic review and meta-analysis

     The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences 23:659–666.

     https://doi.org/10.1093/gerona/gly110

     • Google Scholar
131. 1. Vijg J

     (2014) Somatic mutations, genome mosaicism, Cancer and aging

     Current Opinion in Genetics & Development 26:141–149.

     https://doi.org/10.1016/j.gde.2014.04.002

     • PubMed
     • Google Scholar
132. 1. Wang J
     2. Clauson CL
     3. Robbins PD
     4. Niedernhofer LJ
     5. Wang Y

     (2012) The oxidative DNA lesions 8,5′-cyclopurines accumulate with aging in a tissue-specific manner

     Aging Cell 11:714–716.

     https://doi.org/10.1111/j.1474-9726.2012.00828.x

     • Google Scholar
133. 1. Weedon MN
     2. Ellard S
     3. Prindle MJ
     4. Caswell R
     5. Lango Allen H
     6. Oram R
     7. Godbole K
     8. Yajnik CS
     9. Sbraccia P
     10. Novelli G
     11. Turnpenny P
     12. McCann E
     13. Goh KJ
     14. Wang Y
     15. Fulford J
     16. McCulloch LJ
     17. Savage DB
     18. O'Rahilly S
     19. Kos K
     20. Loeb LA
     21. Semple RK
     22. Hattersley AT

     (2013) An in-frame deletion at the polymerase active site of POLD1 causes a multisystem disorder with lipodystrophy

     Nature Genetics 45:947–950.

     https://doi.org/10.1038/ng.2670

     • PubMed
     • Google Scholar
134. 1. Wilson BT
     2. Stark Z
     3. Sutton RE
     4. Danda S
     5. Ekbote AV
     6. Elsayed SM
     7. Gibson L
     8. Goodship JA
     9. Jackson AP
     10. Keng WT
     11. King MD
     12. McCann E
     13. Motojima T
     14. Murray JE
     15. Omata T
     16. Pilz D
     17. Pope K
     18. Sugita K
     19. White SM
     20. Wilson IJ

     (2016) The cockayne syndrome natural history (CoSyNH) study: clinical findings in 102 individuals and recommendations for care

     Genetics in Medicine 18:483–493.

     https://doi.org/10.1038/gim.2015.110

     • PubMed
     • Google Scholar
135. 1. Wood RD
     2. Mitchell M
     3. Lindahl T

     (2005) Human DNA repair genes, 2005

     Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis 577:275–283.

     https://doi.org/10.1016/j.mrfmmm.2005.03.007

     • PubMed
     • Google Scholar
136. 1. Wood RD

     (2018) Fifty years since DNA repair was linked to Cancer

     Nature 557:648–649.

     https://doi.org/10.1038/d41586-018-05255-1

     • PubMed
     • Google Scholar
137. 1. Yousefzadeh MJ
     2. Zhao J
     3. Bukata C
     4. Wade EA
     5. McGowan SJ
     6. Angelini LA
     7. Bank MP
     8. Gurkar AU
     9. McGuckian CA
     10. Calubag MF
     11. Kato JI
     12. Burd CE
     13. Robbins PD
     14. Niedernhofer LJ

     (2020) Tissue specificity of senescent cell accumulation during physiologic and accelerated aging of mice

     Aging Cell 19:e13094.

     https://doi.org/10.1111/acel.13094

     • PubMed
     • Google Scholar
138. 1. Zhang P
     2. Kishimoto Y
     3. Grammatikakis I
     4. Gottimukkala K
     5. Cutler RG
     6. Zhang S
     7. Abdelmohsen K
     8. Bohr VA
     9. Misra Sen J
     10. Gorospe M
     11. Mattson MP

     (2019) Senolytic therapy alleviates Aβ-associated oligodendrocyte progenitor cell senescence and cognitive deficits in an alzheimer's disease model

     Nature Neuroscience 22:719–728.

     https://doi.org/10.1038/s41593-019-0372-9

     • PubMed
     • Google Scholar

Author details

1. Matt Yousefzadeh

   Institute on the Biology of Aging and Metabolism Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, United States

   Contributed equally with

   Chathurika Henpita

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-2869-1029

2. Chathurika Henpita

   Institute on the Biology of Aging and Metabolism Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, United States

   Contributed equally with

   Matt Yousefzadeh

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-7610-1380

3. Rajesh Vyas

   Institute on the Biology of Aging and Metabolism Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, United States

   Competing interests

   No competing interests declared

4. Carolina Soto-Palma

   Institute on the Biology of Aging and Metabolism Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, United States

   Competing interests

   No competing interests declared

5. Paul Robbins

   Institute on the Biology of Aging and Metabolism Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, United States

   Competing interests

   No competing interests declared

6. Laura Niedernhofer

   Institute on the Biology of Aging and Metabolism Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, United States

   For correspondence

   lniedern@umn.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-1074-1385

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