Сенсорность клеток в глиальных клетках: последствия для множественного склероза.

Abbreviations

8‐Hydroxy‐2′‐deoxyguanosine

B‐cell leukemia/lymphoma 2

C‐C motif chemokine ligand

cluster of differentiation 4

cyclin‐dependent kinase

cyclin‐dependent kinase inhibitor

central nervous system

cellular senescence

C‐X‐C motif chemokine ligand

disease associated microglia

experimental autoimmune/allergic encephalomyelitis

glial fibrillary acidic protein

high mobility group box 1

IκB kinase

interleukin

Janus kinase/signal transducer and activator of transcription

mitogen‐activated protein kinase

myelin basic protein

myelin oligodendrocyte glycoprotein

multiple sclerosis

mammalian target of rapamycin

nuclear factor kappa B

oligodendrocyte progenitor cell

proteolipid protein

primary progressive multiple sclerosis

reactive oxygen species

relapse remitting multiple sclerosis

senescence associated secretory pathway

senescence associated beta galactosidase

sex determining region Y‐box 2

secondary progressive multiple sclerosis

transforming growth factor

theiler's murine encephalomyelitis virus

Introduction

Multiple Sclerosis (MS) is a chronic neurodegenerative disease characterized by demyelination, or loss of myelin, within the central nervous system (CNS) that affects approximately 2.9 million people worldwide (Walton et al.  2020 ). Physical symptoms of MS include but are not limited to, numbness and tingling sensation, muscle weakness, cramping, difficulty walking, tremors, and blurred vision. Importantly, MS patients also frequently experience psychiatric ailments such as depression and anxiety. As of 2017 about 74% of cases in the United States are in women (Walton et al.  2020 ). Causes of MS remain unclear, and the disease displays itself differently among patients. The majority of patients (80%–85%) are first diagnosed with relapsing‐remitting MS (RRMS), which is characterized by periods of disability with stable recovery between relapses. In some of these patients, the disease evolves into secondary progressive MS (SPMS), or a state of gradual neurological deterioration without recovery. A minority of patients (10%–15%) present with primary progressive MS (PPMS)—a disease course characterized by an increase in disability without any periods of recovery. The average age of onset for MS is 20 to 40 years old, and younger age usually corresponds with an RRMS diagnosis (Rovaris et al.  2006 ; Tremlett, Zhao, and Devonshire  2008 ). Typically, progression into SPMS occurs around 40–50 years old, which is about 10–25 years post diagnosis of RRMS (Tremlett and Zhao  2017 ). Patients diagnosed with PPMS tend to be in their 40–50s, similar to the age of progression to SPMS (Koch et al. 2009 ). Available treatments for these more progressive forms remain sparse, emphasizing the critical need to understand the biology underlying progressive MS.

The most common risk factor for disease progression in MS patients is aging, and for this reason, an interest in how aging affects MS has become a topic of high interest. Most MS patients typically transition to SPMS by their fifth decade of life (Zeydan and Kantarci  2020 ; Tutuncu et al.  2013 ) and those diagnosed later in life tend to develop SPMS more quickly (Koch et al.  2007 ). This indicates that age may pose a greater risk factor for disease progression than time since disease onset. Aging is a broad term used to describe the passage of time for an organism and presents in a variety of different phenotypes. Biological age and chronological age do not always overlap, as a vast number of factors affect biological aging, including environment, diet, lifestyle, and genetics. Unfortunately, there is little consensus on how to measure biological aging (Levine  2013 ; Jia, Zhang, and Chen  2017 ; Jylhävä, Pedersen, and Hägg  2017 ), which makes it difficult to assess if MS patients experience premature or accelerated aging. Identifying reliable biomarkers of aging could significantly deepen our understanding of the relationship between aging and neurodegenerative disease (Rutledge, Oh, and Wyss‐Coray  2022 ).

One key feature of aging is cellular senescence (CS), an irreversible state of cell cycle arrest. The accumulation of senescent cells within an organism is thought to be a primary indicator of biological aging. While senescence was first shown as an artifact of cell culture in 1961 (Hayflick and Moorhead  1961 ), the discovery of senescent cells in organisms has catapulted research towards understanding the cellular process of aging. This includes significant interest in understanding how CS affects or interacts with neurodegenerative disease. Alzheimer's disease, specifically, has been a major focus of research efforts analyzing CS in the nervous system. More recently, this interest has expanded to MS, highlighted by several review articles that discuss the potential impacts of aging and CS on MS (Graves et al.  2023 ; Koutsoudaki et al.  2020 ; Kritsilis et al.  2018 ; Papadopoulos et al.  2020 ). Here, we present an updated overview of the evidence of CS within the CNS of MS patients and different MS animal models, noting the significant gaps in knowledge that still remain. We also discuss the known properties of different senescent glial cell populations, largely identified from studies of aging and Alzheimer's disease, and extrapolate how these properties may also play a role in MS. Finally, we speculate how drugs that target senescent cells, termed senolytics, may hold promise for MS patients.

Hallmarks of Cellular Senescence

CS is most typically represented as an irreversible halt in the cell cycle, triggered by various biological factors. For mitotic cells, the cumulative effect of cellular replication over time, as seen in the aging process, is believed to be the main driver of senescence. However, post‐mitotic cells have recently been found to also enter senescence via cellular stress and damage responses (Toussaint, Medrano, and von Zglinicki  2000 ; Serrano et al.  1997 ). Therefore, CS can be classified as either replicative or stress‐induced premature senescence (Toussaint, Medrano, and von Zglinicki  2000 ; von Zglinicki, Wan, and Miwa  2021 ). Because the majority of cells within the adult CNS are post mitotic, cellular stress may be the main driver of CS in the brain and spinal cord. However, proliferative microglia and endogenous progenitor cells (i.e., neural stem cells and oligodendrocyte progenitor cells or OPC) may enter a senescent state due to replicative exhaustion caused by repair attempts (Nicaise et al.  2019 ; Guan et al.  2024 ). Common inducers of CS include oxidative stress, telomere shortening, DNA damage, and chromatin disruption (Muñoz‐Espín and Serrano  2014 ). As organisms age, they continue to collect these hallmarks of senescence, which in turn play a role in age‐related diseases. Senescence does have an important biological function, eliminating potentially hazardous cells, such as cancer cells, in a manner similar to apoptosis (Calcinotto et al.  2019 ). Interestingly, CS was also shown to play a beneficial role in tissue remodeling during embryonic development (Muñoz‐Espín et al.  2013 ; Storer et al.  2013 ) and wound healing (Demaria et al.  2014 ; Li et al.  2010 ). However, problems arise when the accumulation of senescent cells becomes a burden, particularly through the release of proinflammatory factors that can be damaging to nearby tissue. While this can be beneficial within a tumor, tissue experiencing high numbers of senesced cells due to aging may become damaged by the same mechanism meant to protect (Zhang et al.  2022 ).

Knowledge of the molecular pathways of CS and its cellular profile has taken shape over the past several decades. While many factors can initiate the senescent pathway, most of them result in some form of DNA damage, either through telomere shortening via cell division, or external sources damaging non‐telomeric DNA (d'Adda di Fagagna  2008 ; Schumacher et al.  2021 ). Mitochondrial stress can produce reactive oxygen species which are also capable of DNA damage (Herranz and Gil  2016 ). Long term exposure to ionizing radiation causes DNA breaks and mutations. Weakening or mis‐regulation of the nuclear envelope can release chromatin into the cytoplasm (Rodriguez‐Muñoz, Anglada, and Genescà  2022 ), signaling that DNA damage has occurred. Multiple signaling pathways can be activated in response to DNA damage, which ultimately lead to halting of the cell cycle and CS. These pathways have been extensively reviewed elsewhere (d'Adda di Fagagna  2008 ; Stagni et al.  2021 ; Ben‐Porath and Weinberg  2005 ); therefore, we will only briefly highlight those that have been frequently studied in the context of MS and demyelination. Most notably, cell cycle regulators such as the p16INK4A/ CDKN2A ‐pRb axis (Liu et al. 2019 ; Rayess et al. 2012 ), and the p53‐p21/ CDKN1A axis, which both function as tumor suppressors, are activated in response to CS. The p16INK4A pathway induces downstream inhibition of cyclin‐dependent kinases CDK4/6 and CDK2, which eventually halt cell cycle progression through activation of pRb. Transcription of p21 is activated by p53 which halts other genes responsible for cell cycle progression. These protein pathways are commonly used as indicators of CS, both in vivo and in vitro, along with senescence‐associated beta‐galactosidase (SA‐β‐gal). In senescent cells, β‐gal is active at a more neutral pH than healthy cells, thus termed the SA‐β‐gal (Dimri et al.  1995 ). This change in enzymatic activity is then used to produce staining of senescent cells under senescence associated acidity levels. It is important to note that there are difficulties with assessing senescence in cells and tissue, as there are technical challenges associated with these described markers, as well as variability in senescent phenotypes across different cell types. Currently, the preferred method is the use of SA‐β‐gal in combination with other markers, such as p16INK4A or p21. Several additional markers used to indicate senescence are the following: senescent secreted factors (HMGB1, CCL11, and IL's), p38γMAPK (Freund, Patil, and Campisi  2011 ), LaminB1 (Matias et al.  2022 ), indicators of proliferation, DNA damage (γ‐H2A.X (Bernadotte, Mikhelson, and Spivak  2016 )), and oxidative stress (Davalli et al.  2016 ) (8‐OhdG). While this list is not all inclusive, these markers are some of the more common and well‐established indicators of CS.

More recently, with the advances of single cell sequencing, efforts have focused on identifying transcriptomic profiles of senescent cells. The Mayo clinic developed a profile of genes used to characterize senescent cells at the single cell level for both humans and mice, termed SenMayo (Saul et al.  2022 ). The list of genes is expansive, including growth factors, chemokines, cytokines, transmembrane signal responders, protease inhibitors, and metalloproteases. While the SenMayo list has proven very useful for analyzing transcriptomic datasets for senescent cell populations, there are several caveats. First, it remains unclear what percentage of these genes must be expressed for a cell to be determined as “senescent.” Second, while the gene set was shown to apply to different tissue types, it does not consider the variability in gene expression across different senescent cell types. More recently, a research group at the University of Illinois has developed a Python program (SenePy) that establishes distinct senescent signatures (75 for mouse and 65 for human) to account for differences in senescent phenotype between cell types (Sanborn et al.  2023 ). These profiles were verified by applying them to a multitude of different cell types such as lung, heart, liver, neuronal, tongue, and blood cells between mouse and human data sets (Sanborn et al.  2023 ). Further development of these single cell techniques and bioinformatic analysis tools will hopefully allow for more accurate assessment of CS.

Senescence Associated Secretory Phenotype ( SASP )

Senescent cells secrete a unique inflammatory profile coined the senescence associated secretory phenotype (SASP). Characterized by the secretion of cytokines and chemokines, this mechanism is believed to be at least partly responsible for senescent cell clearance by the immune system. Work has been done that suggests SASP could potentially be “pro‐senescence” and induce senescence in neighboring cells (Acosta et al.  2013 ; Lujambio et al.  2013 ; da Silva et al.  2019 ). Therefore, SASP may potentially expedite degeneration and worsen symptoms in neurodegenerative disease. While the composition of SASP varies cell to cell, it is initially composed primarily of immunosuppressive factors (TGF‐β1 and TGF‐β3) and progresses to proinflammatory cytokines (e.g., IL‐6, IL‐8) and chemokines (e.g., CXCL1, CXCL2) (Basisty et al.  2020 ; Lopes‐Paciencia et al.  2019 ). The phenomenon of immunosenescence, or the gradual deterioration of the immune system with age, has also been proposed to impact MS patients (Adamczyk‐Sowa et al.  2022 ; Dema et al.  2021 ; Thakolwiboon et al.  2023 ). As organisms age, they tend to express higher levels of pro‐inflammatory molecules, aptly named inflammaging. The adaptive immune system suffers the most from this phenomenon with disturbance of T‐cells, while the innate immune system becomes dysfunctional and induces prolonged production of inflammatory cytokines (Lee et al.  2022 ; Wang et al.  2022 ). This in turn causes premature senescence, both in the immune system and surrounding tissue. While the CNS is mostly removed from the adaptive immune system, immune cells such as microglia and perivascular macrophages may suffer from immunosenescence. This has important implications for MS, in which both the adaptive (Hemmer, Kerschensteiner, and Korn  2015 ) and innate (Hernández‐Pedro et al.  2013 ; Gandhi, Laroni, and Weiner  2010 ) immune systems play roles in disease phenotype and progression.

Do MS Patients Display Altered Cellular Senescence?

It is now well established that senescence occurs in the aged CNS of otherwise healthy organisms, including mice and humans. Multiple review articles summarize recent findings of CS in astrocytes (Bhat et al.  2012 ; Cohen and Torres  2019 ; Csipo et al.  2020 ; Han et al.  2020 ), microglia (Ng, McNeely, and Baker  2023 ; Angelova and Brown  2019 ; Streit  2006 ), oligodendrocytes (Sams  2021 ), neurons (Chou et al.  2023 ), as well as the brain as a whole (Sikora et al.  2021 ; Baker and Petersen  2018 ). Increased CS has also been widely observed in neurodegenerative diseases such as Alzheimer's (Han et al.  2020 ; Guerrero, Strooper, and Arancibia‐Cárcamo  2021 ; Saez‐Atienzar and Masliah  2020 ) and Parkinson's disease (Miller et al.  2022 ; Chinta et al.  2013 ). Therefore, it is reasonable to hypothesize that CS also plays a role in MS disease progression.

MS is characterized by immune system attacks on the fatty myelin sheaths of oligodendrocytes, inducing demyelination that eventually leads to axonal damage and neuronal loss. Approved treatments for MS suppress this autoimmune response, in hopes of delaying and preventing demyelination events. Without these treatments, about 50% of patients with RRMS progress to SPMS within 10 years of diagnosis (Barzegar et al. 2021 ). It is possible that many of these therapies delay immunosenescence. However, despite the efficacy of these treatments, many MS patients eventually transition into a more progressive stage of the disease, where remyelination or myelin regeneration fails. A significant area of research focuses on strategies to induce or enhance remyelination as a neuroprotective mechanism, and an outstanding question in the MS field is whether aging impacts remyelination and disease progression due to increased CS.

Currently, there are few published studies showing direct evidence of CS in the CNS of MS patients. Oxidative stress (marked by 8‐OhdG), a hallmark of CS, was found elevated in oligodendrocytes, astrocytes, microglia/macrophages, and T‐cells in the white matter of patients with PPMS (Haider et al.  2011 ). In a separate study, OPCs within chronic active lesions in MS tissue were found to express p38γMAPK, which is required for SASP secretion (Marziali et al.  2024 ). Additional analysis of chronic lesions in MS tissue identified increased numbers of p16INK4A‐positive cells within the lesion core when compared to other locations (Absinta et al.  2021 ). These p16INK4A‐positive cells co‐localized with the microglial marker IBA1 and the astrocyte marker GFAP (Absinta et al.  2021 ). P16INK4a‐positive cells were also identified within demyelinated lesions of PPMS patients in a separate study; however, these cells expressed the progenitor marker SOX2. Therefore, there is evidence of senescent microglia, astrocytes, OPCs, and neural progenitor cells within lesions of MS tissue. This has important implications for how remyelination may be blocked in MS patients. However, it is interesting that different senescent cell populations were identified in each of these studies. This may indicate a general increase in CS across all cell types in MS tissue or may simply reflect the wide heterogeneity seen across MS patients. Additional analysis of other senescent markers is required to firmly establish the level of CS in the CNS of MS patients. At the transcriptional level, single nuclei RNAseq analysis of lesions from post‐mortem MS brain tissue identified subsets of cells that express stressed phenotypes (Absinta et al.  2021 ). These stressed microglia and oligodendrocytes share similar gene expression with “disease‐associated” subtypes observed in datasets of Alzheimer's disease (Absinta et al.  2021 ; Olah et al.  2020 ; Prater et al.  2023 ), but whether they correspond functionally to senescent cells remains unclear (Ng, McNeely, and Baker  2023 ). Overall, while these studies provide some evidence of CS in MS, there is a critical need for additional work that thoroughly characterizes the many different hallmarks of CS across different MS samples, using both transcriptomics and histological analysis. Furthermore, it will be important to determine whether patients with progressive MS contain increased numbers of senescent cells compared to RRMS patients. Better understanding of the correlation between CS abundance and MS disease state will lead to new avenues for therapies.

Evidence of Senescence Across Different Animal Models of MS

Due to the difficulty in assessing MS disease progression solely using post‐mortem tissue, animal models of MS are critical to our understanding of mechanisms of demyelination and repair. MS is characterized by both demyelinated lesions of the CNS and inflammation due to an upregulated immune response; therefore, most animal models of MS aim to recapitulate these pathologies. The gold standard animal model for MS is the experimental autoimmune/allergic encephalomyelitis (EAE) model that mimics the autoimmune response in MS patients against myelin proteins (Constantinescu et al.  2011 ). However, while this model is incredibly useful for investigating the immune aspect of MS, it is difficult to observe reproducible remyelination in these animals, especially within the brain. Therefore, toxicity models are favored for modeling the molecular and cellular mechanisms of remyelination. The most used toxicity models are focal demyelination induced by injection of lysolecithin (Hall  1988 ) or ethidium bromide (Kuypers et al.  2013 ) into white matter regions of the CNS, and global demyelination through cuprizone feeding (Kipp et al.  2009 ). Viral infections of the CNS such as Theiler's murine encephalomyelitis virus (TMEV) have also been used to induce demyelination, which causes encephalomyelitis (Tsunoda and Fujinami  2010 ). However, not all mouse strains are susceptible to TMEV, including C57BL/6, which limits research capabilities. A more recent model system has also been developed, coined the adoptive transfer model, which involves the transfer of myelin reactive CD4+ T cells into the CNS (Ben‐Nun, Wekerle, and Cohen  1981 ). This model allows for increased severity of lesions and allows for the use of most mouse strains as opposed to the TMEV model. For this review, we will focus on EAE and the toxicity models of demyelination, as those have been the most widely used in the field. Specifically, we will highlight evidence of CS and the impacts of aging on remyelination within these models, highlighting gaps that remain to be filled. While most studies use young mice (6–10 weeks old, which is approximately equivalent to the human age of 10–20 years old) for investigating remyelination, there is increased interest and focus on moving these models into aged mice to more accurately model patients with progressive forms of MS (Wang et al.  2020 ; Dutta and Sengupta  2016 ). However, experiments with aged mice are both expensive and time‐consuming, which can be inhibitory for many research labs. Therefore, a better understanding of the extent of CS within these existing animal models, both young and aged, will allow researchers to tackle the question of how CS impacts remyelination.

EAE Model of MS

In the EAE model, mice are immunized with myelin‐derived antigens or T‐cells. These antigens target specific oligodendrocyte proteins such as myelin oligodendrocyte glycoprotein (MOG), myelin basic protein (MBP), or proteolipid protein (PLP) (Stromnes and Goverman  2006 ). Interestingly, different strains of mice can present symptoms in a heterogenous manner, similar to the human disease. For example, SJL/J mice immunized with PLP antigens present with a relapsing phenotype (Meeson et al.  1994 ; Vanderlugt et al.  2000 ), while C57BL6/J mice immunized with an immunodominant MOG antigen present a more chronic phenotype (Meeson et al.  1994 ; Bittner et al.  2014 ). Importantly, all the EAE models largely affect the spinal cord, whereas MS patients typically have higher numbers of lesions in the brain. Several studies have examined the hallmarks of aging and senescence in these models. Adoptive transfer EAE in middle‐aged mice (40–44 weeks) results in an accelerated and more severe disease course, with higher mortality rates, compared to young adult mice (8–12 weeks) (Atkinson et al.  2022 ). Interestingly, the age of radiation‐resistant, nonhematopoietic cells (including CNS‐resident cells) was found to be the dominant factor in determining the severity of EAE, as chimeric middle‐aged mice reconstituted with bone marrow from young mice displayed similar results to nonchimeric middle‐aged mice upon EAE induction (Atkinson et al.  2022 ). While CS was not analyzed in this study, microglia from the aged EAE mice were found to upregulate proinflammatory and interferon response genes more highly than young EAE mice, highlighting the impact of aging on microglia (Atkinson et al.  2022 ). A separate study in 2023 observed that p16INK4a‐positive microglia accumulated in the spinal cord at the peak of the acute phase of EAE (day 22; Matsudaira et al.  2023 ). Importantly, p16 knockout mice displayed reduced CD4+ T cell infiltration during the EAE acute phase, and demyelination progression was significantly reduced, along with paralysis (Matsudaira et al.  2023 ). These results were repeated, but to a lesser extent, in microglia/macrophage‐specific p16INK4a knockout mice. Together, these results indicate that the EAE phenotype is attenuated by inhibiting microglial CS. However, it will be important to determine whether removal of senescent microglia after induction of EAE and in aged mice also provides similar beneficial effects. A recent study also reports evidence of senescent‐like microglia in the EAE model, focusing on upregulation of anti‐apoptotic Bcl2 family genes (Drake et al.  2024 ). Analysis of single cell RNAseq data revealed that Bcl2‐positive microglia in EAE mice have enriched gene expression for CS, using the SenMayo gene list (Drake et al.  2024 ). Interestingly, treatment of EAE mice with a small molecule inhibitor of BCL2 (ABT‐263) at the onset of symptoms reduced the number of microglia in the optic nerve and increased optomotor function (Drake et al.  2024 ). These are promising results, but many questions remain. Is this functional recovery due specifically to a reduction of senescent microglia, or are other cells affected? While it seems that microglia constitute the largest senescent population in the EAE model, does this change with age? Also, does removal of senescent microglia after EAE disease onset improve remyelination, both within the optic nerve and in other brain or spinal cord areas? If so, this may open up senolytics, a category of drugs that eliminate senescent cells, as viable new treatment options for MS patients.

Lysolecithin and Ethidium Bromide Models of Demyelination

Remyelination has been widely investigated in focal demyelination animal models, which allow for highly reproducible lesions in known regions of the CNS. While the majority of studies use lysolecithin to induce demyelination, other toxins (ethidium bromide, carbon tetrachloride, and lysophosphatidic acid) have also been used. When discussing these studies, it is important to differentiate the models, as they may induce CS to differing levels or via different molecular mechanisms. A paper published in 2019 analyzed the impact of fasting on remyelination in 18‐month‐old mice after injection of ethidium bromide into the spinal cord (Neumann et al.  2019 ). Fasting has been used as an approach for reducing senescent cells, as it encourages less cellular turn over, and therefore restricts replicative senescence (Erlangga et al.  2023 ; Tagliafico, Nencioni, and Monacelli  2023 ). Fasting significantly increased differentiation of OPCs and remyelination (Neumann et al. 2019 ). These results were recapitulated with the drug Metformin (Neumann et al.  2019 ), which has been shown to reduce signs of aging in animals and is currently in clinical trials for multiple age‐related chronic diseases, including dementia. Therefore, this study suggests that decreasing CS in aged animals prior to myelin injury improves remyelination. However, CS was not directly examined in the remyelination experiments, and both fasting and Metformin are systemic treatments with global effects on metabolism and physiology. Metformin likely decreases both replicative‐CS and stress‐induced CS, as it reduces autophagy and modulates the AMPK/mTOR pathway, thereby disrupting key processes that sustain senescent cells (Sorrenti et al.  2022 ; Zhang et al.  2021 ). Recently, a new study established evidence of CS in microglia following lysolecithin‐induced demyelination of the spinal cord white matter of both young and aged mice (Gross et al.  2024 ). In both 3‐month and 18‐month‐old mice, demyelination resulted in a significant increase of senescent microglia as shown by p16INK4A and SA‐β‐gal staining (Gross et al.  2024 ). Interestingly, in young mice, senescent cells were effectively cleared during remyelination, whereas in aged mice, these cells persisted. In young mice, the immune system clears senescent cells by recognizing specific signals released as part of the SASP, which attract natural killer cells to eliminate them (Muñoz‐Espín and Serrano  2014 ; Sagiv and Krizhanovsky  2013 ). This suggests that age‐related defects in immune surveillance and senescent cell clearance may inhibit remyelination in older individuals. To test this, the authors then ablated senescent cells either genetically with the transgenic INK‐ATTAC mouse model, which ablates p16INK4A‐expressing cells, or pharmacologically with the senolytics Dasatinib and Quercetin (Gross et al.  2024 ). In both approaches, removal of senescent cells increased MBP levels and the number of mature oligodendrocytes in the younger mice but had no effect in aged mice (Gross et al.  2024 ). Proteomic analysis revealed that CCL11, a common SASP component, was elevated in the demyelinated lesions of aged mice (Gross et al.  2024 ). Delivery of a neutralizing antibody against CCL11 following demyelination increased MBP levels in young mice, indicating CCL11 may inhibit efficient oligodendrocyte maturation (Gross et al.  2024 ). This is the first study to clearly indicate that focal demyelination induces CS in the CNS, regardless of age. Importantly, this study extensively characterized CS within these lesions using multiple parameters, including histology, transcriptomics, and proteomics. Whether microglia are also the primary senescent cell population in aged mice or more chronic demyelination models remains to be seen. It is interesting that removal of senescent cells did not restore myelination in the older animals, suggesting other inhibitory cues may still prevent oligodendrocyte differentiation in lesions. An important next step will be to test if inhibition of CCL11 in aged mice following demyelination is sufficient to overcome these barriers. Another potential inhibitory signal is extracellular HMGB1, which has been associated with both senescence and MS patients (Bucova et al.  2020 ). Exogenous HMBG1 blocked OPC differentiation in 3‐month‐old mice following lysolecithin‐induced demyelination, whereas inhibition of HMGB1 receptors restored OPC differentiation (Rouillard et al.  2022 ). Further analysis of the effects of different SASP signaling proteins on OPC proliferation, differentiation, and remyelination are required to better understand how CS may impact endogenous repair mechanisms in both animal models and human patients. In addition, it remains unknown how lysolecithin induces CS, as well as how microglial functions are altered upon induction of CS in these demyelination models. Conditional deletion of only senescent microglia would indicate whether they are the primary factor affecting remyelination.

Cuprizone Model of Demyelination

For global CNS demyelination, the copper chelator cuprizone is mixed into normal mouse chow and fed ad libitum . An acute injury is typically caused by a cuprizone diet lasting 4–6 weeks, and removal of cuprizone results in rapid remyelination seen as early as two weeks after removal of cuprizone (de Castillo‐Rodriguez et al.  2022 ; Palavra et al.  2022 ). A chronic demyelination injury can be observed when mice are fed for longer durations, typically 12 weeks (Kipp et al.  2011 ). Remyelination occurs much later in a chronic injury, usually at least 4 weeks post removal of cuprizone, and capacity for restoration is much slower. While several studies using cuprizone have reported indicators of CS, it remains underexplored compared to other animal models. Acute cuprizone was found to increase HMGB1 protein levels, an indicator of CS (Ammar et al.  2022 ). At the transcriptional level, chronic cuprizone increased expression of tgfβ‐r, il‐6, p16INK4A , and p53 , which have all been implicated in CS (Parandavar et al.  2024 ). Interestingly, SA‐β‐gal positive cells were also identified in chronic cuprizone brain tissue, and they co‐localized with the OPC marker O4 (Parandavar et al.  2024 ). Whether other cells, such as microglia or astrocytes, also exhibit hallmarks of senescence will be important to determine in this model. Importantly, the structural changes in myelin and upregulation of CS markers in the chronic cuprizone model were all comparable to aged (18‐month‐old) animals (Parandavar et al.  2024 ), indicating a relationship between chronic cuprizone demyelination and aging. This may be partly due to cuprizone's induction of mitochondrial dysfunction (Acs et al.  2013 ; Praet et al.  2014 ), which has also been shown to occur in CS and aging (Miwa et al.  2022 ; Martini and Passos  2023 ; Chistiakov et al.  2014 ). While acute cuprizone may induce these symptoms to some degree, chronic cuprizone may allow for more accumulation of senescent cells, resulting in increased SASP and reduced clearance by microglia. Although evidence of CS in cuprizone studies is limited, insights from traumatic brain injury research suggest a potential link between microglial phagocytic burden and premature aging. In the cuprizone model, microglia are heavily engaged in clearing myelin debris, which imposes a significant phagocytic burden. A study on traumatic brain injury demonstrated that such a burden can drive premature aging in microglia, characterized by increased production of ROS, upregulation of p16INK4a, and heightened expression of pro‐inflammatory cytokines like IL‐1β (Ritzel et al.  2023 ). This raises intriguing parallels and possible mechanistic overlap between these conditions. Future studies that comprehensively analyze CS across different cell populations in the chronic cuprizone model will be critical for using this model to dissect the impact of CS on remyelination.

Overall, these studies highlight several important conclusions. First, as senescent microglia were observed across multiple models, they likely play an important role in MS disease progression. Better understanding of how senescent microglia impact other cells within the lesion environment, either via SASP or other factors, is greatly needed. Second, removal of senescent cells appears to have some beneficial effects on remyelination. Whether this can be attributed solely to removal of senescent microglia remains unclear. Third, there are still relatively few studies comprehensively analyzing CS in the context of MS and myelin pathology. This is particularly true for the cuprizone model of demyelination. With recent advances in the understanding of white matter aging in Alzheimer's disease, the myelin field is poised to examine similar questions in the context of MS, glial biology, and neuroinflammation. In the next section, we briefly discuss known effects of senescence on different glial cells, and speculate how such changes may impact MS.

Characteristics of Senescent Glial Cells

Microglia

Microglia act as the brain's immune system, responsible for the cleanup of the CNS through phagocytosis of debris and dying cells. With their highly migratory behavior, as well as a complex secretome, CS in microglia may pose a more substantial threat to surrounding tissue as opposed to other CNS cell types. In addition, unlike most cells of the adult CNS, microglia are proliferative, which puts them more at risk of telomere shortening (Hecker et al.  2021 ). Because of this, microglia have been a major focus of CS research in the CNS. Microglia acquire a senescence associated phenotype in Alzheimer's disease (Hu et al.  2021 ) and upon stimulation with the pro‐inflammatory molecule lipopolysaccharide (Yu et al.  2012 ). Aged microglia both in cell culture and in mice exhibit a decrease in migratory and phagocytic behavior, as well as an increase in released cytokines (Rawji et al.  2020 ; Njie et al.  2012 ). Senescent microglia drive neuroinflammation (Matsudaira et al.  2023 ; Njie et al.  2012 ; Damani et al.  2011 ), have slower migration and motility (Damani et al.  2011 ), and defective phagocytosis (Rawji et al.  2020 ; Njie et al.  2012 ; Damani et al.  2011 ). Interestingly, p16INK4a‐positive microglia in aged mice also highly express known disease‐associated microglia (DAM) markers, such as Lgals3 (Matsudaira et al.  2023 ). DAMs secrete a pro‐inflammatory profile similar to the SASP, which makes it difficult to differentiate beneficial versus inhibitory subpopulations. However, recent works have attempted to establish a difference between these profiles (Matsudaira et al.  2023 ; Hu et al.  2021 ). In MS, the senescent state of microglia likely plays out as a chicken and egg situation. Less motile microglia may be unable to respond as quickly to damaged oligodendrocytes, and decreased phagocytosis likely results in decreased myelin clearance. Prolonged release of proinflammatory cytokines and chemokines may evolve into an SASP, potentially producing a positive feedback loop that induces senescence in surrounding cells (Matsudaira et al.  2023 ; Hu et al.  2021 ). This may create an environment unsuitable for remyelination, either by the signaling factors of SASP themselves or by the induction of senescence onto neighboring progenitor cells.

Astrocytes

Astrocytes perform a variety of metabolic and neuroprotective tasks, including regulating the blood–brain barrier, promoting synapse formation, and clearing excess neurotransmitters. Following CNS infection or injury, astrocytes are also critical for repair by forming protective borders around lesions. The effect of CS on these functions remains unclear. In culture, inducing oxidative stress, proteasome inhibition, or exhausting replication in astrocytes altered expression of p16INK4A, p21, and SA‐β‐gal (Bitto et al.  2010 ). When aged in culture, astrocytes show a reduced capacity to support neurons (Pertusa et al.  2007 ; Limbad et al.  2020 ) and neural progenitor cell proliferation (Miranda et al.  2012 ). Patients with Alzheimer's disease have significantly higher numbers of p16INK4A positive astrocytes (Dimri et al.  1995 ), as well as increased γ‐H2A.X labeling (Rouillard et al.  2022 ), which indicates double stranded‐DNA breaks (Chinta et al.  2018 ). Senescent astrocytes have also been identified in animal models of Alzheimer's disease and Parkinson's disease. Removal of p16+ senescent astrocytes in a mouse model of Parkinson's disease protected against the toxicity induced neuropathy (Chinta et al.  2018 ). Overall, these studies suggest that senescent astrocytes display reduced neuroprotective function (Thadathil et al.  2021 ). Astrocytes respond to demyelination in humans (Brosnan and Raine  2013 ; Ludwin et al.  2016 ) and mice (Brambilla et al.  2014 ; Skripuletz et al.  2013 ; Hibbits et al.  2012 ), where they both promote and possibly inhibit remyelination via reactive gliosis. Much like microglia, reactive astrocytes secrete factors similar to the SASP of senescent cells (Bhat et al.  2012 ; Clarke et al.  2018 ). Reactive astrocytes, characterized by release of chemokines, cytokines, and growth factors, are found in many neurodegenerative diseases and the aged brain, and may also present a secretome similar to the SASP (Sofroniew  2020 ; Zamanian et al.  2012 ; Liddelow et al.  2017 ). While attempts to differentiate these different subpopulations has occurred, further understanding remains to be seen (López‐Teros et al.  2022 ; Lazic et al.  2022 ). Evidence of astrocyte senescence in MS and demyelination models remains limited, but findings from other neurodegenerative diseases suggest that senescent astrocytes may contribute to impaired remyelination in MS. Senescent astrocytes are known to secrete the SASP, which could create a hostile environment for remyelination by promoting inflammation, disrupting signaling pathways essential for repair, and impairing the function of oligodendrocytes and their precursors. Much like microglia, the senescence of astrocytes could exacerbate neurodegenerative processes by shifting from supportive to pathological roles within the CNS. In progressive MS, persistent astrocyte activation—similar to the sustained activation seen in microglia—may reflect a senescence‐associated phenotype. This prolonged dysregulation could exacerbate neuroinflammation and demyelination, while simultaneously reducing neuroprotective functions such as maintaining blood‐brain barrier integrity. Understanding these dynamics requires further investigation, as targeting senescent astrocytes could present a novel therapeutic approach for mitigating neurodegeneration and promoting remyelination in MS.

Oligodendrocytes

Despite oligodendrocyte loss being one of the hallmarks of MS, relatively little work has been done examining senescence in these cells. Human oligodendrocytes express less MBP with age, along with increased expression of CDKN1A and CDKN2A (Windener et al.  2024 ). This suggests that as senescent hallmarks accumulate in oligodendrocytes, their capacity for myelination diminishes. There is ongoing debate regarding the role of surviving oligodendrocytes in remyelination. Some studies suggest that surviving oligodendrocytes are capable of contributing to myelin repair in demyelinated lesions (Yeung et al.  2019 ; Cui et al.  2017 ), while others argue that they are not the primary source of new myelin (Neely et al.  2022 ). If senescent oligodendrocytes are present, they may further complicate this process by either impairing the remyelination capacity of surviving oligodendrocytes or contributing to remyelination failure in other ways. OPCs, on the other hand, may be more adversely affected by CS than oligodendrocytes. In patients with Alzheimer's disease, OPCs associated with amyloid beta plaques exhibit CS as indicated by upregulation of CDKN1A , CDKN2A , and SA‐β‐gal (Zhang et al.  2019 ). Aged mouse OPCs express several markers of senescence and fail to respond to differentiation signals (Neumann et al.  2019 ). Similar to other senescent progenitor cells (Nicaise et al.  2019 ; Tropepe et al.  1997 ), senescent OPCs would likely exhibit decreased proliferation, migration, and differentiation to oligodendrocytes, which are all critical steps for remyelination. As inhibition of OPC differentiation is suggested to be one of the main mechanisms underlying remyelination failure in MS patients (Graves et al.  2023 ; Koutsoudaki et al.  2020 ; Papadopoulos et al.  2020 ), it is critical to determine to what extent this is due to OPC senescence or secreted SASP factors from neighboring senescent cells.

In summary, senescence within the major glial cells of the CNS may significantly impact MS progression and remyelination, emphasizing the need to better understand how senescence uniquely alters the properties of each cell population. In addition to glia, it is important to note that CS has been described in other CNS cell types. Aged neurons, which are post‐mitotic cells, accumulate markers of CS, such as DNA damage, dysfunctional mitochondria, SASP, and SA‐B‐gal staining (Stahon et al.  2016 ; Lodato et al.  2018 ; Bender et al.  2006 ; Bigagli et al.  2016 ; Barral et al.  2014 ; Jurk et al.  2012 ). During aging, endothelial cells of the blood–brain barrier can become senescent and disruptive, allowing for the influx of proinflammatory factors that could be interpreted as SASP (Zlokovic  2008 ). Additionally, lymphocytes, which infiltrate the CNS in MS and the EAE model, have also been shown to become senescent (Kaer et al.  2019 ; Gao et al.  2024 ; Tomas‐Ojer et al.  2022 ). These senescent T‐cells contribute greatly to inflammation, which has been linked to neuronal damage (Gao et al.  2024 ; Tomas‐Ojer et al.  2022 ). The combined effects of these different cell types and how they present senescence may all influence MS disease progression. Unfortunately, most work analyzing CS has been performed in primary cell culture, which does not fully recapitulate the complexity of neural tissue or the inflammatory environment. In addition, there are still technical issues in properly assessing senescence in vivo, especially in post‐mortem human tissue, which make this a challenge. While hypotheses can be extrapolated from other neurodegenerative diseases, it is important to verify these findings in MS tissue.

Conclusion

CS and its role in disease have become an exciting topic of interest over the past 50 years, with an explosion of multi‐directional therapies in the last 20 years. It has been well established that senescence presents itself not only in the aging brain but also as a premature feature of several neurodegenerative diseases. Despite the knowledge that aging is a major risk factor for MS, relatively little work has been done to fully characterize CS in the CNS of MS patients, leaving a major gap in the field. Multiple studies have demonstrated the presence of senescent cells in demyelinated lesions, observed in both animal models and human patients (summarized in Figure  1 ). From work in animal models, demyelination has been shown to induce CS. However, in aged animal models and aging MS patients, CS may precede demyelination, likely exacerbating injury and impairing the repair process. A better understanding of the functional effects of senescence in glial cells is critical for deciphering this relationship and identifying new treatment strategies.

Evidence of senescent cells in the demyelinated CNS. An overview of how chronic demyelination and senescence affect various CNS cells, contributing to the disease pathology of MS. Senescent markers, such as SA‐β‐gal, p16, p21, and SASP, have been found in various cell types, including astrocytes, microglia, oligodendrocytes, endothelial cells of the blood brain barrier, and progenitor cells. Markers are denoted by if they have been observed in rodent models of MS (*), post‐mortem MS tissue (†), or both (bolded text). The expected consequences of senescence on each cell type are listed. NPC = neural progenitor cells. OPC = oligodendrocyte progenitor cells. SASP = senescence associated secretory phenotype. Created in Biorender. Maupin, E (2024). https://BioRender.com/f10l606 .

As we further our understanding of CS in the CNS, new therapies can be developed to effectively address the accumulation of senescent cells. Two new categories of drugs, termed senolytics and senomorphics, have emerged as potential methods of clearing senescent cells from the body. Senolytics are a broad category of drugs that mainly target anti‐apoptotic pathways, such as the BCL‐2 family, p53, p21, AKT, PI3K, and other proteins known to induce apoptosis within senescent cells (Zhang et al.  2023 ). Dasatinib and Quercetin are two of the most commonly used senolytics. Dasatinib is a tyrosine kinase inhibitor that disrupts the pro‐survival networks protecting senescent cells, making them more susceptible to apoptosis (Olivieri and Manzione  2007 ; Lindauer and Hochhaus  2014 ). Quercetin, a flavonoid, inhibits the PI3K/AKT pathway, impairing DNA damage repair and triggering apoptosis in senescent cells (Zhou et al.  2023 ; Kim et al.  2019 ). They are commonly used in combination to induce apoptosis in senescent cells (Zhang et al.  2023 ). Use of combination or single drug therapy has provided promising results in several models of neurodegeneration (Gross et al.  2024 ; Krzystyniak et al.  2022 ; Ota and Kodama  2022 ; Dhawan and Combs  2012 ; Ryu et al.  2019 ). Recently, the combination therapy of Dasatinib/Quercetin has gone through several clinical trials to treat patients with Alzheimer's disease (Sutter et al.  2022 ). Additionally, BCL‐2 inhibitors such as Navitoclax have alleviated symptoms of neurodegeneration in animal models (Greenberg et al.  2024 ; Faakye et al.  2024 ).

In contrast, senomorphics reduce CS by modulating senescent cells rather than inducing apoptosis, targeting proteins such as NF‐κB, p38γMAPK, JAK/STAT, and mTOR (Zhang et al.  2023 ). Rapamycin, which has immunosuppressive and anti‐proliferative properties, suppresses CS and SASP, as well as increases lifespan (Demidenko et al.  2009 ; Wang et al.  2017 ). Metformin, originally approved for treatment of type 2 diabetes, also suppresses CS and SASP in multiple age‐ related disorders by interfering with IKK/NF‐κB activation (Moiseeva et al.  2013 ; Garg et al.  2017 ). Fasting produces similar results to Metformin, as it seems to slow cellular replication, which delays replicative senescence (Neumann et al.  2019 ). Both Metformin and rapamycin have been shown to alleviate symptoms of aging in neurodegeneration models (Neumann et al.  2019 ; Garg et al.  2017 ; Wang et al.  2024 ). However, many senomorphics and senolytics, particularly Metformin, are most effective when administered before symptom/disease onset (Neumann et al.  2019 ). A study performed in 2022 observed the coincidence of MS diagnosis in patients taking anti‐hyperglycemics, such as Metformin, for their type‐2 diabetes (Branigan et al.  2022 ). Patients under 45 taking anti‐hyperglycemics were associated with a reduced risk of developing MS, while patients older than 45 were associated with an increased risk of developing MS, particularly in women (Branigan et al.  2022 ). One interpretation is that anti‐hyperglycemics prevented development of MS in the younger patients, mirroring what is observed in animal models. However, the therapeutic effect of these anti‐hyperglycemics may be reduced in older patients, especially women undergoing menopause. Therefore, the effectiveness of these drugs in PPMS and SPMS patients, when the disease has already progressed, may be reduced. Early disease diagnosis and combinatorial treatment of senolytics/senomorphics with disease modifying therapies and remyelination therapies may serve as the best option for MS patients. However, to successfully test these senolytics and senomorphics as a treatment for MS, CS must be properly represented in animal models of MS and better understood. Therefore, it is critical that information is shared across the fields of aging, glial biology, cancer biology, and neurodegenerative disease to develop better tools for detecting senescent cells and assessing their intrinsic and extrinsic properties.

Author Contributions

Elizabeth A. Maupin: conceptualization, writing – original draft, writing – review and editing. Katrina L. Adams: conceptualization, funding acquisition, supervision, writing – original draft, writing – review and editing.

Conflicts of Interest

The authors declare no conflicts of interest.

Peer Review

The peer review history for this article is available at https://www.webofscience.com/api/gateway/wos/peer‐review/10.1111/jnc.16301 .