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PERSPECTIVE article

Front. Immunol., 07 October 2025

Sec. Multiple Sclerosis and Neuroimmunology

Volume 16 - 2025 | https://doi.org/10.3389/fimmu.2025.1681724

Targeting senescent microglia in progressive multiple sclerosis: a geroscience-informed approach

  • 1Department of Neurology, The Ohio State University College of Medicine, Wexner Medical Center, Columbus, OH, United States
  • 2The Neuroscience Research Institute, The Ohio State University Wexner Medical Centers, Columbus, OH, United States
  • 3Neuroscience Graduate Program, The Ohio State University, Columbus, OH, United States
  • 4Department of Neuroscience, The Ohio State University Wexner Medical Center, Columbus, OH, United States
  • 5Chronic Brain Injury Program, The Ohio State University, Columbus, OH, United States

Multiple sclerosis (MS) is a neuroinflammatory and neurodegenerative disorder of the central nervous system (CNS). Age is the strongest predictor of disease phenotype, with the majority of older adults transitioning to a progressive form marked by irreversible neurological decline. This clinical progression is associated with smoldering, CNS-compartmentalized inflammation and neurodegeneration, for which there are currently no effective disease-modifying therapies. Cellular senescence, characterized by the secretion of pro-inflammatory mediators collectively known as the senescence-associated secretory phenotype (SASP), increases with age and contributes to tissue injury. In MS, neuroinflammation can further promote cellular senescence, creating a self-reinforcing cycle of damage. Senescent microglia have been identified within MS lesions, where their SASP may impair remyelination and exacerbate neurodegeneration. Senolytic agents selectively target and eliminate senescent cells by disrupting anti-apoptotic pathways. In experimental autoimmune encephalomyelitis (EAE), a widely used model of MS, senolytic treatment reduces senescent microglia burden and attenuates disease severity in an age- and drug-dependent manner. Specifically, here we show that middle-aged mice (40–44 weeks) with EAE exhibit improved clinical outcomes and survival following treatment with either dasatinib plus quercetin (D+Q) or navitoclax. Early-phase clinical trials of senolytics in age-related diseases have demonstrated functional benefits, including improved gait speed in idiopathic pulmonary fibrosis and CNS penetrance in Alzheimer’s disease. Translating senolytic therapy to MS will require careful selection of CNS-penetrant and well-tolerated agents, identification of appropriate patient populations, and deployment of responsive biomarkers. Senolytic therapy represents a promising geroscience-based strategy to meet the urgent therapeutic need in progressive MS.

Introduction

Multiple sclerosis (MS) is a relapsing or chronic progressive multifocal inflammatory and neurodegenerative disorder of the central nervous system (CNS), which afflicts approximately one million people in the United States (1). Age is the strongest predictor of MS clinical course (25). The disease typically presents during young adulthood as relapsing-remitting MS (RRMS), characterized by self-limited episodes separated by clinically quiescent periods. These relapses are associated with acute inflammatory demyelinating white matter lesions, driven by focal blood-brain-barrier breakdown and infiltration of peripheral leukocytes into the perivascular space and parenchyma. As people with RRMS age, up to 90% transition to a progressive form of the disease, defined by the gradual accrual of irreversible neurological disability (6, 7). Progressive MS is pathologically distinguished by smoldering, CNS-compartmentalized inflammation behind an intact blood–brain barrier, slowly expanding lesions, widespread microglial activation, and structured meningeal inflammation (8). Currently, more than 20 FDA-approved disease-modifying therapies (DMTs) are available for RRMS, primarily targeting the peripheral immune system to prevent relapses and new lesion formation (9). However, these therapies are largely ineffective in halting or reversing disability progression in progressive MS (10). This highlights an urgent unmet need for novel therapeutic strategies that specifically address the pathophysiology of progressive MS. One promising approach is the application of geroscience-based therapies that address age-related mechanisms of CNS dysfunction. We summarize emerging evidence of senescent cells, in particular senescent microglia, contributing to neurodegeneration in progressive MS and the effects of their clearance in animal models of MS. We describe translational considerations of using senolytics in people with MS based on lessons learned and challenges observed in early phase senolytic trials in other age-related conditions.

Senescent microglia as a driver of MS progression

Cellular senescence is a hallmark of aging, characterized by the permanent exit of cells from the cell cycle and accompanied by distinct morphological and functional changes in response to cellular damage and stress (11). Senescent cells remain metabolically active and secrete a panel of pro-inflammatory mediators collectively known as the senescence-associated secretory phenotype (SASP), which drives chronic low-grade systemic inflammation (12, 13), and contributes to impaired tissue regeneration and the onset of age-related diseases (14). Premature accumulation of senescent cells is a feature of neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease, with emerging evidence suggesting a similar phenomenon in progressive MS (1518).

Buildup of senescent cells in the CNS creates oxidative stress that hinders the remyelinating capacity of oligodendrocyte progenitor cells and promotes neurodegeneration (16, 19). In progressive MS, senescent cells exhibiting the SASP accumulate in actively demyelinating gray and white matter lesions and is associated with faster disability progression and higher mortality (20). SASP components can mediate axonal damage and impede myelin repair (19). Senescent cells express high levels of the tumor suppressor gene p16INK4a (21, 22), and postmortem analysis of MS lesions has revealed a greater density of p16INK4a-positive cells compared to normal white matter (23). In p16INK4a-luciferase reporter mice, bioluminescence signal from aged brains correlated with elevated p16INK4a mRNA and protein expression in white matter regions (24). Single-cell RNA sequencing identified microglia as the primary cell type expressing p16INK4a in the aged brains. Isolated microglia from aged brains corroborated increased p16INK4a mRNA and protein expression. Moreover, these senescent microglia showed reduced proliferative potential, as evidenced by diminished 5-ethynyl-2’-deoxyuridine (EdU) incorporation compared to p16INK4a-negative microglia. In experimental autoimmune encephalomyelitis (EAE), a widely used animal model of MS, p16INK4a-positive microglia accumulate in the spinal cord at the peak of clinical disease severity. Notably, p16INK4a-deficient mice exhibited reduced CNS infiltration by T cells, less demyelination and attenuated clinical disability (24). Collectively these findings indicate that microglia are the predominant senescent cell in CNS white matter during aging and EAE.

Recent studies have investigated the relationships between cellular senescence, microglial proliferation and remyelination in the EAE model. Compared to young adult mice, aged mice with EAE exhibited a more severe clinical course, increased neurodegeneration, and impaired remyelination (25). Spatial gene expression profiling of spinal cord lesions revealed an expansion of macrophages and microglia, reduced oligodendrocyte density, and upregulation of senescence-associated gene signatures—changes that were especially pronounced in aged mice (26). The accumulation of senescent cells within lesions was accompanied by a marked reduction in oligodendrocyte precursor cell (OPC) differentiation and mature oligodendrocyte formation. Senescent cells could, potentially, modulate oligodendroglial cells through the production of soluble factors. Proteomic analysis of CNS homogenates has demonstrated that CCL11/Eotaxin-1, a chemokine involved in myeloid cell recruitment and a component of the SASP, is elevated in the spinal cords of aged mice with EAE. Plasma CCL11 levels are elevated in progressive MS and correlate with disease severity (27). It readily crosses the blood–brain barrier and has been shown to suppress myelin basic protein (MBP) expression in maturing oligodendrocytes (26, 28).

The hyperproliferation of certain microglial subsets may lead to replication stress and the induction of senescence programs (29). When coupled with age-related impairments in the clearance of senescent cells, this results in the accumulation of dysfunctional, senescent microglia within the CNS. Collectively, these findings support a model in which microglial senescence contributes to remyelination failure and neurodegeneration, thereby accelerating disease progression in progressive MS.

Senolytics remove senescent microglia

Current treatment of progressive MS in older adults focuses on palliative symptom management rather than addressing the underlying mechanisms such as age-related immune dysregulation. The association between cellular senescence and age-related diseases highlights the critical role of aging mechanisms in clinical outcomes of age-related diseases (30). Although chronological age is the greatest risk factor for MS disease progression (25), there is variation in the age at which patients with RRMS convert to SPMS, which may be explained by interindividual variations in biological aging mechanisms (30) (31).

Senescent cells can be selectively eliminated by senolytic drugs, which have been shown to delay age-related decline in animal models and hold promise for improving functional outcomes in human clinical trials (32). The discovery of senolytics was guided by the observation that senescent cells upregulate anti-apoptotic pathways to resist cell death. Proteomic and transcriptomic analyses of senescent cells revealed upregulation of antiapoptotic pathways, and disabling these antiapoptotic pathways selectively depletes these cells while sparing non-senescent cells (32). The first senolytics identified were dasatinib (D), a tyrosine kinase inhibitor, and quercetin (Q), a naturally occurring flavonoid. In combination (D+Q), these agents induce apoptosis in senescent cells across multiple tissues (33). Dasatinib, a FDA-approved cancer treatment, disrupts pro-survival signaling in senescent cells (34, 35), while quercetin impairs DNA damage repair and inhibits the PI3K/AKT pathway, promoting senescent cell death (36, 37). Together, D+Q act synergistically to eliminate a broader range of senescent cells than either agent alone (38), leading to improved lifespan in preclinical studies in mice (39). Notably, clearance of peripheral senescent cells has been linked to improved outcomes in CNS disorders (40). The removal of senescent cells by senolytics underscores their therapeutic potential.

Targeting senescent microglia represents a promising strategy for progressive MS, a disease stage characterized by limited blood-brain barrier disruption and minimal peripheral immune infiltration. A recent study demonstrated accumulation of p21+ senescent-like myeloid cells—including monocyte-derived macrophages and microglia—in the spinal cord and meninges during EAE (41). Treatment of EAE mice with D+Q reduced the frequency of these senescent-like myeloid cells, but did not impact clinical disease severity. A possible explanation for the lack of efficacy may be due to the exclusive use of young female mice in this study, wherein it was previously shown that D+Q displayed sexual dimorphic treatment effects in young adult mice (42). Alternatively, according to the threshold theory of senescence, senescent cell burden in young animals may remain below the threshold necessary to cause clinical pathology (32).

In our own study, using Th17-mediated adoptive transfer EAE, we found that initiating daily D+Q treatment at symptom onset (approximately day 6 following T cell transfer) significantly ameliorated disease in middle-aged (40–44 weeks old) mice compared to vehicle-treated controls (Figure 1A). Treated mice exhibited lower peak clinical scores, reduced cumulative disease severity (AUC), and doubled survival rates. D+Q treatment also led to diminished infiltration of peripheral CD45hi immune cells into the inflamed spinal cord, including neutrophils and encephalitogenic CD45.1+ CD4+ T cells (Figures 1B–E). Prior work from our group strongly implicates microglia as a key driver of age-dependent progressive-like disease (25). Notably, D+Q treatment reduced microglial expression of CD14 and TREM2 (Figure 1F), markers previously associated with a senescent microglial phenotype (43, 44). These data show D+Q may selectively improve clinical outcomes in middle aged rather than young EAE mice.

Figure 1
Graphs and flow cytometry plots display the effects of vehicle versus D+Q treatment. Panel A includes a line graph showing clinical scores over time, bar graphs of AUC and peak score, and a survival plot. Panels B, C, and D provide flow cytometry plots showing CD45 vs. CD11b and CD45 vs. CD4 cell distributions, with percentages noted. Panel E shows a histogram of CD45.1 expression levels. Panel F includes histograms of CD14 and TREM2 expressions. The treatment group shows decreased scores and different cell population distributions compared to the vehicle group.

Figure 1. Dasatinib and quercetin (D+Q) treatment ameliorates EAE and reduces senescent microglial phenotypes in middle-aged mice. (A) Clinical course of EAE in middle-aged mice treated with vehicle (black, n = 5) or D+Q (blue, n = 5), starting at symptom onset. Dasatinib (5 mg/kg; HY-10181, MedChemExpress) and Quercetin (50 mg/kg; HY-18085, MedChemExpress) suspended in a 10% DMSO/30% PEG300/10% Tween80/50% water solution, or vehicle solution alone, was administered i.v. into the tail vein. Left: daily mean clinical scores; Middle left: area under the clinical score curve (AUC); Middle right: mean peak clinical scores; Right: survival over time. (B–E) Flow cytometric analysis of immune cells harvested from the spinal cords of vehicle-treated (black) and D+Q-treated (blue) EAE mice on day 18 post-transfer. (B–D) Representative contour plots of infiltrating peripheral immune cells (CD45hi) and microglia (CD11b+ CD45int), gated on all viable CD45+ cells, (B) Ly6G+ neutrophils, gated on CD45hi CD11b+ infiltrating peripheral myeloid cells, (C), and CD4+ T cells, gated on CD45+ CD11b- cells (D). (E) Representative histograms showing CD45.1 expression gated on total CD4+ T cells. The percentage of CD45.1+ donor encephalitogenic T cells is shown. (F) Representative histograms showing expression of CD14 (left) and TREM2 (right) on microglia, gated as in (B) All experiments were performed with female C57BL/6 mice purchased from Charles River. Statistical significance was determined using unpaired 2-tailed Student’s t test. (A) Curves in the left panel were compared using a 2-way ANOVA. Error bars indicate mean ± SEM. *p < 0.05, or as indicated.

A separate study demonstrated the efficacy of the senolytic navitoclax in attenuating EAE severity. Single-cell RNA sequencing at peak disease revealed a microglial population with transcriptional signatures of inflammation, neurodegeneration, and senescence (45). Among these, anti-apoptotic BCL2-family genes, including of BCL2L1, were differentially expressed in EAE microglia compared to control counterparts, but not in other CNS cell types. Notably, BCL2L1+ microglia exhibited higher expression of proinflammatory genes compared to BCL2L1 microglia. Similar patterns were observed in human MS tissue, where microglia within chronic active lesions showed features of senescence and enrichment for BCL2L1 transcripts.

Treatment of EAE mice with navitoclax, a BCL2 family inhibitor, selectively depleted senescent microglia and macrophages in the spinal cord without altering the proportions of other cell types (45). Treated animals exhibited sustained improvements in motor function beginning two days post-treatment, along with preserved visual acuity. Histological analysis of optic nerves revealed reduced inflammation and gliosis, accompanied by increased survival of retinal ganglion cells.

Our group has extended these findings to middle-aged mice, where navitoclax treatment similarly reduced overall disease severity, peak clinical scores, and mortality (Figure 2A). These clinical improvements were associated with decreased expression of senescence-associated markers in spinal cord microglia (Figure 2B), mirroring the effects observed with D+Q treatment. Together, these data highlight the therapeutic potential of senolytic agents in EAE—particularly in the aged CNS—through selective elimination of senescent microglia.

Figure 2
Graphs show the effects of Navitoclax and vehicle treatments. Panel A depicts: a line graph of clinical scores over time, bar graphs comparing AUC and peak scores, and a survival percentage graph, all indicating Navitoclax's significant impact. Panel B shows flow cytometry histograms and bar graphs for CD14 and TREM2 expressions, highlighting reduced geometric mean fluorescence intensity with Navitoclax. Statistically significant differences are marked by asterisks.

Figure 2. Navitoclax treatment ameliorates EAE and reduces senescent microglial phenotypes in middle-aged mice. (A) Clinical course of EAE in middle-aged mice treated with vehicle (black, n = 12) or navitoclax (red, n = 5), starting at symptom onset. Navitoclax (5 mg/kg; HY-10087, MedChemExpress) suspended in a 10% DMSO/30% PEG300/10% Tween80/50%water solution, or vehicle solution alone, was administered i.v. into the tail vein. (A) Clinical score curve for middle-aged mice treated with either vehicle (black, n=12) or navitoclax (red, n=5) beginning at the time of clinical disease onset. Left: daily mean clinical scores; Middle left: area under the clinical score curve (AUC); Middle right: mean peak clinical scores; Right: survival over time. (B) Histograms and corresponding geometric mean fluorescent intensity (gMFI) showing the expression of CD14 (left) and TREM2 (right), gated on CD45int CD11b+ microglia. Data are representative of 2 individual experiments. All experiments were performed with female C57BL/6 mice purchased from Charles River. Statistical significance was determined using unpaired 2-tailed Student’s t test. Curves in the left panel of A were compared using a mixed effects model. Error bars indicate mean ± SEM. *p < 0.05, **p < 0.01.

Towards clinical trials of senolytics in MS

Currently, there are no effective treatments that reliably halt, yet alone slow, disability accumulation in progressive MS. Traditional approaches to understanding MS pathophysiology and therapy have largely overlooked the influence of aging, which may critically shape disease mechanisms and treatment responses. Although several recent publications have proposed targeting cellular senescence in MS using senolytic agents (1518), no clinical trials of senolytics for MS have been published.

Clinical trials of senolytics have been conducted in other age-related diseases. In the first-in-human senolytic trial, 14 patients with idiopathic pulmonary fibrosis were treated and showed improved gait speed and increased chair-stand repetitions, indicating enhanced physical function (46). A phase 1 study of D+Q in people with Alzheimer’s disease demonstrated that dasatinib crosses the blood–brain barrier. Although therapeutic efficacy was not demonstrated, the study showed that the combination therapy is safe and well-tolerated, supporting advancement to placebo-controlled efficacy trials (47), which are currently underway (NCT04685590; NCT04785300). As a repurposed drug, D+Q has demonstrated acceptable safety profiles and enables faster track to clinical trials. The combination of D+Q targets more anti-apoptotic pathways than either drug alone, resulting in removal of more senescent cells from different tissues (38). Removal of senescent cells in the periphery of individuals with CNS disorders has been linked to clinical improvement (40). A phase 2 study of D+Q in postmenopausal women demonstrated that individuals with higher baseline senescent cell burden—measured by p16INK4a expression in T cells—exhibited a greater therapeutic response to D+Q, resulting in increased bone mineral density (48). Although other senolytics have been tested in preclinical models, D+Q remain the most commonly used senolytics in clinical trials due to acceptable safety and tolerability (49).

Because senescent cells are non-proliferative and require weeks to reaccumulate and reestablish the SASP, they do not require continuous inhibition of pro-survival pathways for sustained therapeutic benefit (38, 50, 51). A short course of D+Q treatment in people with diabetic kidney disease reduced senescent cell burden and maintained the effect for at least 11 days (52), showing senolytics can be dosed every 2 weeks while maintaining efficacy. The short half-life (<11 hours) of D+Q coupled with the intermittent dosing in a “hit and run” approach minimizes drug exposure and lowers the risk of off-target and side effects (46).

There are challenges in the design of clinical trials of senolytics for MS. Most notably, there are no standards for identifying and monitoring of senescent cells, and standardized biomarkers of senescent cell accumulation and removal are still in development. Some biomarkers may be helpful. For example, the treatment effects of D+Q can be measured using the senescence biomarker p16INK4a, a tumor suppressor marker that is a key trigger of cellular senescence (53, 54). Senescent cells express high levels of the tumor suppressor gene p16INK4a (21, 22), and higher levels have corresponded to increased treatment effect with senolytics (48). Nevertheless, p16INK4a expression is not exclusive to senescent cells as it is upregulated in other terminally differentiated immune cells (55, 56), limiting its usefulness as a selective marker of senescent cells. SASP factor panels and composite biomarker scores are also likely to be helpful in defining response to senolytic treatment. In progressive MS, it is possible that senescence of other immune cell types besides microglia contribute to disease progression. Aging in MS is associated with premature immune exhaustion, marked by an accumulation of effector memory CD4+ and CD8+ T cells and disrupted regulation of immunoregulatory and costimulatory pathways. Compared to age- and sex-matched controls, individuals with MS exhibit a higher frequency of effector memory T cells and a reduced frequency of naïve T cells in both CD4+ and CD8+ circulating compartments (57). Furthermore, unlike individuals without MS, those with MS exhibit a reduced frequency of CTLA-4+ memory T cells, which play a key role in regulating immune activation and have been implicated as contributors to progressive MS (57). Senescence has also been observed in neural progenitor cells (NPCs) derived from induced pluripotent stem cells of patients with primary progressive MS (19). These NPCs expressed markers of cellular senescence and failed to support oligodendrocyte progenitor cell maturation, in contrast to NPCs derived from age-matched control lines. Treatment with rapamycin restored the ability of senescent NPCs to support oligodendrocyte maturation in vitro. Ultimately, the design and conduct of senolytic trials in people with MS require unique cross-disciplinary expertise in neurology, geriatric medicine, and aging biology to integrate aging biomarkers and principles of senolytic treatment with immune response and clinical outcomes in MS (58, 59).

Conclusion

Evidence implicating cellular senescence—particularly in microglia—as a driver of disease in older individuals with progressive MS has led to the plausible therapeutic strategy of using senolytics to slow disease progression. Preclinical evidence has highlighted the role of senescent microglia in hindering remyelination in the setting of autoimmune neuroinflammation. Senolytics have demonstrated effective clearance of senescent cells; however, their efficacy likely depends on factors such as the specific agent used, as well as the age, sex, and underlying characteristics of the individual. Clinical trials of senolytics in people with MS are currently in development, informed by insights from ongoing and completed studies in other age-related diseases. Targeting cellular senescence is a promising therapeutic approach to address the urgent unmet need for effective treatments in the aging progressive MS population.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The animal study was approved by The Ohio State University Institutional Animal Care and Use Committee. The study was conducted in accordance with the local legislation and institutional requirements.

Author contributions

JA: Conceptualization, Data curation, Formal Analysis, Investigation, Methodology, Resources, Visualization, Writing – original draft, Writing – review & editing. AD: Data curation, Investigation, Methodology, Writing – review & editing. HG: Data curation, Investigation, Methodology, Writing – review & editing. JG: Conceptualization, Writing – review & editing. BS: Data curation, Resources, Supervision, Writing – review & editing. YZ: Conceptualization, Funding acquisition, Project administration, Supervision, Writing – original draft, Writing – review & editing.

Funding

The author(s) declare financial support was received for the research and/or publication of this article. The manuscript is supported by funding awarded to Yinan Zhang from the National Institute on Aging (K23AG084848) and by a Career Transition Fellowship awarded to JA from the National Multiple Sclerosis Society (TA-2305-41248).

Conflict of interest

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

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References

1. Wallin MT, Culpepper WJ, Campbell JD, Nelson LM, Langer-Gould A, Marrie RA, et al. The prevalence of MS in the United States: A population-based estimate using health claims data. Neurology. (2019) 92:e1029–40. doi: 10.1212/WNL.0000000000007035

PubMed Abstract | Crossref Full Text | Google Scholar

2. Trojano M, Liguori M, Bosco Zimatore G, Bugarini R, Avolio C, Paolicelli D, et al. Age-related disability in multiple sclerosis. Ann Neurol. (2002) 51:475–80. doi: 10.1002/ana.10147

PubMed Abstract | Crossref Full Text | Google Scholar

3. Confavreux C and Vukusic S. Age at disability milestones in multiple sclerosis. Brain. (2006) 129:595–605. doi: 10.1093/brain/awh714

PubMed Abstract | Crossref Full Text | Google Scholar

4. Scalfari A, Neuhaus A, Daumer M, Ebers GC, and Muraro PA. Age and disability accumulation in multiple sclerosis. Neurology. (2011) 77:1246–52. doi: 10.1212/WNL.0b013e318230a17d

PubMed Abstract | Crossref Full Text | Google Scholar

5. Scalfari A, Lederer C, Daumer M, Nicholas R, Ebers GC, and Muraro PA. The relationship of age with the clinical phenotype in multiple sclerosis. Mult Scler. (2016) 22:1750–8. doi: 10.1177/1352458516630396

PubMed Abstract | Crossref Full Text | Google Scholar

6. Zhang Y, Salter A, Jin S, Culpepper WJ 2nd, Cutter GR, Wallin M, et al. Disease-modifying therapy prescription patterns in people with multiple sclerosis by age. Ther Adv Neurol Disord. (2021) 14:17562864211006499. doi: 10.1177/17562864211006499

PubMed Abstract | Crossref Full Text | Google Scholar

7. Weinshenker BG, Bass B, Rice GP, Noseworthy J, Carriere W, Baskerville J, et al. The natural history of multiple sclerosis: a geographically based study. I. Clinical course and disability. Brain. (1989) 112:133–46. doi: 10.1093/brain/112.1.133

PubMed Abstract | Crossref Full Text | Google Scholar

8. Lassmann H, van Horssen J, and Mahad D. Progressive multiple sclerosis: pathology and pathogenesis. Nat Rev Neurol. (2012) 8:647–56. doi: 10.1038/nrneurol.2012.168

PubMed Abstract | Crossref Full Text | Google Scholar

9. Chataway J, Williams T, Li V, Marrie RA, Ontaneda D, and Fox RJ. Clinical trials for progressive multiple sclerosis: progress, new lessons learned, and remaining challenges. Lancet Neurol. (2024) 23:277–301. doi: 10.1016/S1474-4422(24)00027-9

PubMed Abstract | Crossref Full Text | Google Scholar

10. Manouchehri N, Salinas VH, Rabi Yeganeh N, Pitt D, Hussain RZ, and Stuve O. Efficacy of disease modifying therapies in progressive MS and how immune senescence may explain their failure. Front Neurol. (2022) 13:854390. doi: 10.3389/fneur.2022.854390

PubMed Abstract | Crossref Full Text | Google Scholar

11. Di Micco R, Krizhanovsky V, Baker D, and d’Adda di Fagagna F. Cellular senescence in ageing: from mechanisms to therapeutic opportunities. Nat Rev Mol Cell Biol. (2021) 22:75–95. doi: 10.1038/s41580-020-00314-w

PubMed Abstract | Crossref Full Text | Google Scholar

12. Acosta JC, Banito A, Wuestefeld T, Georgilis A, Janich P, Morton JP, et al. A complex secretory program orchestrated by the inflammasome controls paracrine senescence. Nat Cell Biol. (2013) 15:978–90. doi: 10.1038/ncb2784

PubMed Abstract | Crossref Full Text | Google Scholar

13. Munoz-Espin D and Serrano M. Cellular senescence: from physiology to pathology. Nat Rev Mol Cell Biol. (2014) 15:482–96. doi: 10.1038/nrm3823

PubMed Abstract | Crossref Full Text | Google Scholar

14. Witham MD, Granic A, Miwa S, Passos JF, Richardson GD, and Sayer AA. New Horizons in cellular senescence for clinicians. Age Ageing. (2023) 52:1–9. doi: 10.1093/ageing/afad127

PubMed Abstract | Crossref Full Text | Google Scholar

15. Graves JS, Krysko KM, Hua LH, Absinta M, and Franklin RJM and Segal BM. Ageing and multiple sclerosis. Lancet Neurol. (2023) 22:66–77. doi: 10.1016/S1474-4422(22)00184-3

PubMed Abstract | Crossref Full Text | Google Scholar

16. Koutsoudaki PN, Papadopoulos D, Passias PG, Koutsoudaki P, and Gorgoulis VG. Cellular senescence and failure of myelin repair in multiple sclerosis. Mech Ageing Dev. (2020) 192:111366. doi: 10.1016/j.mad.2020.111366

PubMed Abstract | Crossref Full Text | Google Scholar

17. Kritsilis M, VR S, Koutsoudaki PN, Evangelou K, Gorgoulis VG, and Papadopoulos D. Ageing, cellular senescence and neurodegenerative disease. Int J Mol Sci. (2018) 19:1–37. doi: 10.3390/ijms19102937

PubMed Abstract | Crossref Full Text | Google Scholar

18. Papadopoulos D, Magliozzi R, Mitsikostas DD, Gorgoulis VG, and Nicholas RS. Aging, cellular senescence, and progressive multiple sclerosis. Front Cell Neurosci. (2020) 14:178. doi: 10.3389/fncel.2020.00178

PubMed Abstract | Crossref Full Text | Google Scholar

19. Nicaise AM, Wagstaff LJ, Willis CM, Paisie C, Chandok H, Robson P, et al. Cellular senescence in progenitor cells contributes to diminished remyelination potential in progressive multiple sclerosis. Proc Natl Acad Sci U S A. (2019) 116:9030–9. doi: 10.1073/pnas.1818348116

PubMed Abstract | Crossref Full Text | Google Scholar

20. Papadopoulos D, Magliozzi R, Bandiera S, Cimignolo I, Barusolo E, Probert L, et al. Accelerated cellular senescence in progressive multiple sclerosis: A histopathological study. Ann Neurol. (2025) 97:1074–87. doi: 10.1002/ana.27195

PubMed Abstract | Crossref Full Text | Google Scholar

21. LaPak KM and Burd CE. The molecular balancing act of p16(INK4a) in cancer and aging. Mol Cancer Res. (2014) 12:167–83. doi: 10.1158/1541-7786.MCR-13-0350

PubMed Abstract | Crossref Full Text | Google Scholar

22. Liu Y, Sanoff HK, Cho H, Burd CE, Torrice C, Ibrahim JG, et al. Expression of p16(INK4a) in peripheral blood T-cells is a biomarker of human aging. Aging Cell. (2009) 8:439–48. doi: 10.1111/j.1474-9726.2009.00489.x

PubMed Abstract | Crossref Full Text | Google Scholar

23. Absinta M, Maric D, Gharagozloo M, Garton T, Smith MD, Jin J, et al. A lymphocyte-microglia-astrocyte axis in chronic active multiple sclerosis. Nature. (2021) 597:709–14. doi: 10.1038/s41586-021-03892-7

PubMed Abstract | Crossref Full Text | Google Scholar

24. Matsudaira T, Nakano S, Konishi Y, Kawamoto S, Uemura K, Kondo T, et al. Cellular senescence in white matter microglia is induced during ageing in mice and exacerbates the neuroinflammatory phenotype. Commun Biol. (2023) 6:665. doi: 10.1038/s42003-023-05027-2

PubMed Abstract | Crossref Full Text | Google Scholar

25. Atkinson JR, Jerome AD, Sas AR, Munie A, Wang C, Ma A, et al. Biological aging of CNS-resident cells alters the clinical course and immunopathology of autoimmune demyelinating disease. JCI Insight. (2022) 7:1–17. doi: 10.1172/jci.insight.158153

PubMed Abstract | Crossref Full Text | Google Scholar

26. Gross PS, Duran-Laforet V, Ho LT, Melchor GS, Zia S, Manavi Z, et al. Senescent-like microglia limit remyelination through the senescence associated secretory phenotype. Nat Commun. (2025) 16:2283. doi: 10.1038/s41467-025-57632-w

PubMed Abstract | Crossref Full Text | Google Scholar

27. Huber AK, Giles DA, Segal BM, and Irani DN. An emerging role for eotaxins in neurodegenerative disease. Clin Immunol. (2018) 189:29–33. doi: 10.1016/j.clim.2016.09.010

PubMed Abstract | Crossref Full Text | Google Scholar

28. Erickson MA, Morofuji Y, Owen JB, and Banks WA. Rapid transport of CCL11 across the blood-brain barrier: regional variation and importance of blood cells. J Pharmacol Exp Ther. (2014) 349:497–507. doi: 10.1124/jpet.114.213074

PubMed Abstract | Crossref Full Text | Google Scholar

29. Herr LM, Schaffer ED, Fuchs KF, Datta A, and Brosh RM Jr. Replication stress as a driver of cellular senescence and aging. Commun Biol. (2024) 7:616. doi: 10.1038/s42003-024-06263-w

PubMed Abstract | Crossref Full Text | Google Scholar

30. Ferrucci L, Gonzalez-Freire M, Fabbri E, Simonsick E, Tanaka T, Moore Z, et al. Measuring biological aging in humans: A quest. Aging Cell. (2020) 19:e13080. doi: 10.1111/acel.13080

PubMed Abstract | Crossref Full Text | Google Scholar

31. Tutuncu M, Tang J, Zeid NA, Kale N, Crusan DJ, Atkinson EJ, et al. Onset of progressive phase is an age-dependent clinical milestone in multiple sclerosis. Mult Scler. (2013) 19:188–98. doi: 10.1177/1352458512451510

PubMed Abstract | Crossref Full Text | Google Scholar

32. Chaib S, Tchkonia T, and Kirkland JL. Cellular senescence and senolytics: the path to the clinic. Nat Med. (2022) 28:1556–68. doi: 10.1038/s41591-022-01923-y

PubMed Abstract | Crossref Full Text | Google Scholar

33. Tchkonia T and Kirkland JL. Aging, cell senescence, and chronic disease: emerging therapeutic strategies. JAMA. (2018) 320:1319–20. doi: 10.1001/jama.2018.12440

PubMed Abstract | Crossref Full Text | Google Scholar

34. Olivieri A and Manzione L. Dasatinib: a new step in molecular target therapy. Ann Oncol. (2007) 18 Suppl 6:vi42–6. doi: 10.1093/annonc/mdm223

PubMed Abstract | Crossref Full Text | Google Scholar

35. Lindauer M and Hochhaus A. Dasatinib. Recent Results Cancer Res. (2014) 201:27–65. doi: 10.1007/978-3-642-54490-3_2

PubMed Abstract | Crossref Full Text | Google Scholar

36. Zhou B, Yang Y, Pang X, Shi J, Jiang T, and Zheng X. Quercetin inhibits DNA damage responses to induce apoptosis via SIRT5/PI3K/AKT pathway in non-small cell lung cancer. BioMed Pharmacother. (2023) 165:115071. doi: 10.1016/j.biopha.2023.115071

PubMed Abstract | Crossref Full Text | Google Scholar

37. Kim SG, Sung JY, Kim JR, and Choi HC. Quercetin-induced apoptosis ameliorates vascular smooth muscle cell senescence through AMP-activated protein kinase signaling pathway. Korean J Physiol Pharmacol. (2020) 24:69–79. doi: 10.4196/kjpp.2020.24.1.69

PubMed Abstract | Crossref Full Text | Google Scholar

38. Zhu Y, Tchkonia T, Pirtskhalava T, Gower AC, Ding H, Giorgadze N, et al. The Achilles’ heel of senescent cells: from transcriptome to senolytic drugs. Aging Cell. (2015) 14:644–58. doi: 10.1111/acel.12344

PubMed Abstract | Crossref Full Text | Google Scholar

39. Baker DJ, Childs BG, Durik M, Wijers ME, Sieben CJ, Zhong J, et al. Naturally occurring p16(Ink4a)-positive cells shorten healthy lifespan. Nature. (2016) 530:184–9. doi: 10.1038/nature16932

PubMed Abstract | Crossref Full Text | Google Scholar

40. Ogrodnik M, Zhu Y, Langhi LGP, Tchkonia T, Kruger P, Fielder E, et al. Obesity-induced cellular senescence drives anxiety and impairs neurogenesis. Cell Metab. (2019) 29:1233. doi: 10.1016/j.cmet.2019.01.013

PubMed Abstract | Crossref Full Text | Google Scholar

41. Manavi Z, Melchor GS, Bullard MR, Gross PS, Ray S, Gaur P, et al. Senescent cell reduction does not improve recovery in mice under experimental autoimmune encephalomyelitis (EAE) induced demyelination. J Neuroinflammation. (2025) 22:101. doi: 10.1186/s12974-025-03425-3

PubMed Abstract | Crossref Full Text | Google Scholar

42. Fang Y, Medina D, Stockwell R, McFadden S, Quinn K, Peck MR, et al. Sexual dimorphic metabolic and cognitive responses of C57BL/6 mice to Fisetin or Dasatinib and quercetin cocktail oral treatment. Geroscience. (2023) 45:2835–50. doi: 10.1007/s11357-023-00843-0

Crossref Full Text | Google Scholar

43. Mrdjen D, Pavlovic A, Hartmann FJ, Schreiner B, Utz SG, Leung BP, et al. High-dimensional single-cell mapping of central nervous system immune cells reveals distinct myeloid subsets in health, aging, and disease. Immunity. (2018) 48:599. doi: 10.1016/j.immuni.2018.02.014

PubMed Abstract | Crossref Full Text | Google Scholar

44. Rachmian N, Medina S, Cherqui U, Akiva H, Deitch D, Edilbi D, et al. Identification of senescent, TREM2-expressing microglia in aging and Alzheimer’s disease model mouse brain. Nat Neurosci. (2024) 27:1116–24. doi: 10.1038/s41593-024-01620-8

PubMed Abstract | Crossref Full Text | Google Scholar

45. Drake SS, Zaman A, Gianfelice C, Hua EM, Heale K, Afanasiev E, et al. Senolytic treatment diminishes microglia and decreases severity of experimental autoimmune encephalomyelitis. J Neuroinflammation. (2024) 21:283. doi: 10.1186/s12974-024-03278-2

PubMed Abstract | Crossref Full Text | Google Scholar

46. Justice JN, Nambiar AM, Tchkonia T, LeBrasseur NK, Pascual R, Hashmi SK, et al. Senolytics in idiopathic pulmonary fibrosis: Results from a first-in-human, open-label, pilot study. EBioMedicine. (2019) 40:554–63. doi: 10.1016/j.ebiom.2018.12.052

PubMed Abstract | Crossref Full Text | Google Scholar

47. Gonzales MM, Garbarino VR, Kautz TF, Palavicini JP, Lopez-Cruzan M, Dehkordi SK, et al. Senolytic therapy in mild Alzheimer’s disease: a phase 1 feasibility trial. Nat Med. (2023) 29:2481–8. doi: 10.1038/s41591-023-02543-w

PubMed Abstract | Crossref Full Text | Google Scholar

48. Farr JN, Atkinson EJ, Achenbach SJ, Volkman TL, Tweed AJ, Vos SJ, et al. Effects of intermittent senolytic therapy on bone metabolism in postmenopausal women: a phase 2 randomized controlled trial. Nat Med. (2024) 30:2605–12. doi: 10.1038/s41591-024-03096-2

PubMed Abstract | Crossref Full Text | Google Scholar

49. Kirkland JL and Tchkonia T. Senolytic drugs: from discovery to translation. J Intern Med. (2020) 288:518–36. doi: 10.1111/joim.13141

PubMed Abstract | Crossref Full Text | Google Scholar

50. Kirkland JL and Tchkonia T. Cellular senescence: A translational perspective. EBioMedicine. (2017) 21:21–8. doi: 10.1016/j.ebiom.2017.04.013

PubMed Abstract | Crossref Full Text | Google Scholar

51. Schafer MJ, White TA, Iijima K, Haak AJ, Ligresti G, Atkinson EJ, et al. Cellular senescence mediates fibrotic pulmonary disease. Nat Commun. (2017) 8:14532. doi: 10.1038/ncomms14532

PubMed Abstract | Crossref Full Text | Google Scholar

52. Hickson LJ, Langhi Prata LGP, Bobart SA, Evans TK, Giorgadze N, Hashmi SK, et al. Senolytics decrease senescent cells in humans: Preliminary report from a clinical trial of dasatinib plus Quercetin in individuals with diabetic kidney disease. EBioMedicine. (2019) 47:446–456. doi: 10.1016/j.ebiom.2019.08.069

PubMed Abstract | Crossref Full Text | Google Scholar

53. Farr JN, Monroe DG, Atkinson EJ, Froemming MN, Ruan M, LeBrasseur NK, et al. Characterization of human senescent cell biomarkers for clinical trials. Aging Cell. (2025) 2025:e14489. doi: 10.1111/acel.14489

PubMed Abstract | Crossref Full Text | Google Scholar

54. Tchkonia T, Zhu Y, van Deursen J, Campisi J, and Kirkland JL. Cellular senescence and the senescent secretory phenotype: therapeutic opportunities. J Clin Invest. (2013) 123:966–72. doi: 10.1172/JCI64098

PubMed Abstract | Crossref Full Text | Google Scholar

55. Suryadevara V, Hudgins AD, Rajesh A, Pappalardo A, Karpova A, Dey AK, et al. SenNet recommendations for detecting senescent cells in different tissues. Nat Rev Mol Cell Biol. (2024) 25:1001–23. doi: 10.1038/s41580-024-00738-8

PubMed Abstract | Crossref Full Text | Google Scholar

56. Hall BM, Balan V, Gleiberman AS, Strom E, Krasnov P, Virtuoso LP, et al. Aging of mice is associated with p16(Ink4a)- and beta-galactosidase-positive macrophage accumulation that can be induced in young mice by senescent cells. Aging (Albany NY). (2016) 8:1294–315. doi: 10.18632/aging.100991

PubMed Abstract | Crossref Full Text | Google Scholar

57. Zuroff L, Rezk A, Shinoda K, Espinoza DA, Elyahu Y, Zhang B, et al. Immune aging in multiple sclerosis is characterized by abnormal CD4 T cell activation and increased frequencies of cytotoxic CD4 T cells with advancing age. EBioMedicine. (2022) 82:104179. doi: 10.1016/j.ebiom.2022.104179

PubMed Abstract | Crossref Full Text | Google Scholar

58. DeKosky ST and Asthana S. The evolution of geriatric neurology. Handb Clin Neurol. (2019) 167:575–84. doi: 10.1016/B978-0-12-804766-8.00032-7

PubMed Abstract | Crossref Full Text | Google Scholar

59. Gill TM. Translational geroscience: challenges and opportunities for geriatric medicine. J Am Geriatr Soc. (2019) 67:1779–81. doi: 10.1111/jgs.16056

PubMed Abstract | Crossref Full Text | Google Scholar

Keywords: multiple sclerosis, senolytic, geroscience, aging, experimental autoimmue encephalomyelitis

Citation: Atkinson J, Dokiburra A, Groover H, Godbout JP, Segal BM and Zhang Y (2025) Targeting senescent microglia in progressive multiple sclerosis: a geroscience-informed approach. Front. Immunol. 16:1681724. doi: 10.3389/fimmu.2025.1681724

Received: 07 August 2025; Accepted: 23 September 2025;
Published: 07 October 2025.

Edited by:

Horea Rus, University of Maryland, United States

Reviewed by:

Jeffrey K Huang, Georgetown University, United States

Copyright © 2025 Atkinson, Dokiburra, Groover, Godbout, Segal and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Yinan Zhang, eWluYW4uemhhbmdAb3N1bWMuZWR1

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.