Cellular senescence is an early feature and therapeutic target in amyotrophic lateral sclerosis TDP-43Q331K mice

Jose A Viteri; Nathan R Kerr; Charles D Brennan; Grace R Kick; Meifang Wang; Arsh Ketabforoush; Harper J Snyder; Peter J Moore; Fereshteh B Darvishi; Anna R Dashtmian; Sindhuja N Ayyagari; Kelly Rich; Yi Zhu; Hiroshi Nishimune; W David Arnold

doi:10.1016/j.nbd.2026.107610

. Author manuscript; available in PMC: 2026 Nov 5.

Published in final edited form as: Neurobiol Dis. 2026 Sep 18;229:107610. doi: 10.1016/j.nbd.2026.107610

Cellular senescence is an early feature and therapeutic target in amyotrophic lateral sclerosis TDP-43^Q331K mice

Jose A Viteri ^a,^b,¹, Nathan R Kerr ^a,^b,¹, Charles D Brennan ^a,^b,¹, Grace R Kick ^c, Meifang Wang ^a,^b, Arsh Ketabforoush ^a,^b, Harper J Snyder ^a,^b, Peter J Moore ^a,^b, Fereshteh B Darvishi ^a,^b, Anna R Dashtmian ^a,^b, Sindhuja N Ayyagari ^a,^b, Kelly Rich ^d, Yi Zhu ^e,^f, Hiroshi Nishimune ^a,^b, W David Arnold ^a,^b,^*

PMCID: PMC13733421 NIHMSID: NIHMS2214721 PMID: 42759848

Abstract

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by progressive motor neuron degeneration in the motor cortex and spinal cord. Aging is a key risk factor for ALS, and cellular senescence – a hallmark of aging marked by irreversible cell-cycle arrest and a pro-inflammatory senescence-associated secretory phenotype – has been implicated in neurodegeneration, yet its role in ALS progression remains incompletely understood. Here, we show that molecular markers of cellular senescence emerge in the motor cortex and spinal cord alongside declines in neural and neuromuscular function in TDP-43^Q331K ALS mice, supporting senescence as an early feature of ALS pathology. To test whether reduced senescence ameliorates ALS pathology, we evaluated longitudinal senolytic treatment with dasatinib and quercetin (D&Q) in TDP-43^Q331K mice. D&Q treatment improved motor behavior, neuromuscular function, and reduced axonal damage as measured by plasma neurofilament light chain, accompanied by robust improvements in motor cortex excitability and preservation of layer V neuron counts. At the cellular level, cortical microglia were implicated as a potential mediator of senolytic benefits based on reduced microglial TDP-43 burden and senescence markers. Together, these findings identify cellular senescence as an early, disease-relevant, and modifiable feature of ALS pathology.

Keywords: ALS, Aging, Senescence, Senolytics, Motor cortex, Neuromuscular

1. Introduction

Amyotrophic lateral sclerosis (ALS) is a fatal age-related neurodegenerative disorder characterized by the progressive degeneration of motor neurons in the primary motor cortex and spinal cord ventral horn (Masrori and Van Damme, 2020). In both genetic and sporadic forms, ALS symptoms typically begin with focal muscle weakness that spreads regionally, leading to generalized muscle atrophy, paralysis, and death, with a median survival of three years after clinical diagnosis (Masrori and Van Damme, 2020). The average onset of ALS is in the sixth decade of life (Dashtmian et al., 2024), emphasizing that aging is a key factor in disease development and progression.

Accordingly, in healthy individuals, biological aging generally progresses in parallel with chronological aging (Elliott et al., 2021), driving cellular alterations such as DNA damage, epigenetic modifications, mitochondrial dysfunction, and chronic inflammation (Cuollo et al., 2020; Das and Svendsen, 2015; Dashtmian et al., 2024). Mounting evidence suggests that ALS is associated with accelerated biological aging, and recent postmortem human tissue studies indicate that this effect may be particularly evident in the brain (Fang et al., 2026a). Critically, accumulation of biological aging can promote the development of cellular senescence (Dashtmian et al., 2024; Maximova et al., 2021; Mitra et al., 2025). This hallmark of aging is marked by irreversible cell-cycle arrest, impaired apoptosis, and the adoption of a senescence-associated secretory phenotype (SASP) - a pro-inflammatory state capable of propagating senescence to surrounding cells (Maximova et al., 2021; Pandya and Patani, 2020; Vazquez-Villaseñor et al., 2020). Cellular senescence has been increasingly implicated across neurodegenerative and neurological conditions, including Alzheimer’s disease (Gonzales et al., 2022), Parkinson’s disease (Chinta et al., 2018), traumatic-brain injury (Wang et al., 2023), and Huntington’s disease (Horvath et al., 2016). Prior work has shown that TDP-43 and SOD1 mouse models of ALS display increased senescence markers in the cortex (Mitra et al., 2025), spinal cord (Torres et al., 2022), and during paralysis progression (Trias et al., 2019). Similarly, post-mortem cortical tissues from ALS patients exhibit increased astrocytic senescence marker expression (Vazquez-Villaseñor et al., 2020), ALS patient microglia derived from induced pluripotent stem cells (iPSC) show increased neuroinflammation (Quek et al., 2022; Vahsen et al., 2023), and elevated senescent lymphocytes in blood are a feature of faster-progressing ALS (Yildiz et al., 2023).

Based on these observations, we hypothesized that cellular senescence contributes to ALS pathology. Consistent with this hypothesis, we show that molecular markers of cellular senescence in TDP-43^Q331K ALS mice emerge in the spinal cord and motor cortex early in disease progression, coinciding with the onset of neural and neuromuscular impairment (Fig. 1), supporting cellular senescence as an early component of ALS pathology rather than merely a downstream consequence of disease progression.

Fig. 1. — Senescence markers emerge in the spinal cord and motor cortex early in disease progression in TDP-43^Q331K mice. (A) Experimental design and timeline. WT-control and TDP-43^Q331K mice underwent longitudinal in-vivo cortical and neuromuscular electrophysiology (green arrows; N = 10 per genotype) and cross-sectional senescence assays by digital PCR (blue arrows; N = 6 per genotype per age) at 4, 7, 10, and 13 weeks of age. (B) Cortical function vs. senescence progression. Senescence markers (*Trp53*, *Cdkn1a*, *Bcl2*) and cranial MEP amplitude are expressed as log2(TDP-43^Q331K/WT-control). *Trp53* and *Bcl2* were significantly elevated compared to WT-control by 7 weeks, six weeks before a significant cranial MEP deficit emerged at 13 weeks; *Cdkn1a* became elevated only at 13 weeks, coinciding with this deficit. (C) Spinal/peripheral function vs. senescence progression. Senescence markers (*Trp53*, *Cdkn1a*, *Bcl2*) and electrophysiological measures (cervical MEP, CMAP, MUNE) are expressed as log2(TDP-43Q331K/WT-control). *Trp53* and *Cdkn1a* were significantly elevated compared to WT-control as early as 4 weeks, the same age at which CMAP was already significantly reduced, so these markers coincided with the earliest neuromuscular deficit; both markers then normalized to WT-control levels by 7 weeks, the same age at which MUNE first became significantly reduced. *Trp53* was elevated again at 13 weeks. CMAP and MUNE remained significantly reduced from 7 through 13 weeks, while cervical MEP did not significantly differ between genotypes at any age.

This provides a strong rationale for reducing senescent cells in the nervous system as a strategy to mitigate ALS-related motor dysfunction (Bussian et al., 2018). In this context, senolytic drugs, which selectively eliminate senescent cells, have shown promise in alleviating aging-related pathologies (Aguado et al., 2023; Islam et al., 2023; Maximova et al., 2021; Xu et al., 2018), with the combination dasatinib and quercetin (D&Q) among the most studied, synergistically suppressing anti-apoptotic pathways and senescence-driven inflammation (Islam et al., 2023; Kirkland and Tchkonia, 2020; Rad and Grillari, 2024; Torres et al., 2022; Zhu et al., 2015), and showing efficacy in preclinical models of Alzheimer’s disease (Bussian et al., 2018; Zhang et al., 2019), traumatic brain injury (Wang et al., 2023), and age-related metabolic dysfunction (Ogrodnik et al., 2019). Despite their potential, senolytics remain underexplored in ALS (Dashtmian et al., 2024; Maximova et al., 2021; Richardson and Richardson, 2024), presenting an opportunity to assess their impact on ALS pathology. To explore this, we utilized the TDP-43^Q331K mouse model of ALS (Arnold et al., 2013; Mitchell et al., 2015; Viteri et al., 2025b; Watkins et al., 2021), to which we administered a senolytic regimen of D&Q over 15 weeks. During treatment, we longitudinally assessed corticomuscular and neuromuscular function, motor performance, and axonal damage, followed by terminal evaluations of TDP-43 pathology and senescence-associated markers in the nervous system. Our results provide evidence that D&Q has therapeutic potential in ALS, with the most prominent effects observed in the cortex, where treatment reduced cellular senescence and TDP-43 pathology, preserved neuronal counts, and improved motor function.

2. Materials and methods

2.1. Animals

All animal experiments were conducted in accordance with ethical protocols approved by the Institutional Animal Care and Use Committee (IACUC) at the University of Missouri–Columbia (protocol #39905) and were performed in accordance with National Institutes of Health Guide for the Care and Use of Laboratory Animals. All procedures were designed to minimize pain and discomfort. This study was designed, conducted, and reported in accordance with the ARRIVE 2.0 guidelines (Animal Research: Reporting of In Vivo Experiments) for preclinical animal research. Wild-type control C57BL/6 J (Jackson Laboratories; RRID:IMSR_JAX:000664) and TDP-43^Q331K (C57BL/6 J background; Jackson Laboratories; RRID:IMSR_JAX:017933) mice were used for all experiments. TDP-43^Q331K mice were genotyped with the human huTDP-43 gene (forward 5′-AGAGGTGTCCGGCTGGTAG-3′, reverse 5′-CCTGCACCATAAGAACTTCTCC-3′) by PCR following standard procedures (Viteri et al., 2025b; Watkins et al., 2021).

2.1.1. Experiment 1: Longitudinal and cross-sectional characterization of TDP-43^Q331K mice

For experiments shown in Fig. 1, a separate cohort of mice was used (50% female; N = 10 WT-controls, N = 10 TDP-43^Q331K) for longitudinal assessment of physiological function. No behavioral assessments were performed in this cohort. Longitudinal electrophysiological recordings were obtained beginning at 4 weeks of age and repeated every three weeks through 13 weeks of age (Fig. 1A). Molecular markers of senescence were assessed in additional cross-sectional cohorts at 4, 7, and 13 weeks of age (N = 6 per group, 50% female).

2.1.2. Experiment 2: Senolytic treatment

For experiments involving senolytic treatment, mice ranged in age from 1.2 to 3.2 months, with an average age of ~2.3 months (Fig. 2A). Variation in age was due to the availability of TDP-43^Q331K mice from Jackson Laboratories. TDP-43^Q331K mice were randomized to two groups: TDP-43-vehicle (TDP-43^Q331K, N = 14–20), and TDP-43-senolytics (TDP-43^Q331K, N = 15–20). We also included a wild-type vehicle-control (C57BL/6 J, N = 20). All groups were initially balanced for sex (50% female) and age at baseline (Fig. 2A).

Sample sizes for both TDP-43 groups changed over the experimental timeline due to mortality following ketamine (100 mg/kg) and xylazine (7.5 mg/kg) administration for anesthesia during baselines assessments. At the mid-time point, the TDP-43-vehicle group was reduced from N = 20 to N = 14 and this sample size continued into the final time point (male N = 6, female N = 8). At the mid-time point, the TDP-43-senolytics group was reduced from N = 20 to N = 15 and this sample size continued into the final time point (male N = 7, female N = 8).

2.2. Delivery of Senolytic treatment and cadence of assessments

Fig. 2A summarizes the experimental timeline and cadence of senolytic treatment in TDP-43^Q331K mice. Mice treated with senolytics received dasatinib (5 mg/kg; Sigma-Aldrich, St. Louis, MO, USA) and quercetin (50 mg/kg; Thermo Fisher, Waltham, MA, USA) in a solution of 10% ethanol, 30% polyethylene glycol 400, and 60% Phosal 50 PG (Sigma-Aldrich). Vehicle-treated mice received an equal volume of the vehicle solution. Dosing began after baseline assessments of behavior and in-vivo electrophysiology (Fig. 2A) and occurred every 14 days in three-day cycles for a total of six cycles, starting at ~2.3 months of age. Individuals administering senolytics or vehicle treatment doses were unblinded to genotype and group but were not involved in data collection.

For animals included in the senolytic intervention experiments (Fig. 2), motor behavior was assessed at baseline, at intermediate time points following three treatment cycles (vehicle or senolytic), and at the final time point following six treatment cycles. Electrophysiological assessments were performed at baseline and at the final time point only. For plasma NfL assessments (N = 6 per group, approximately 50% female), plasma was collected at baseline, intermediate, and final time points. Terminal molecular assessments of senescence markers using digital PCR (N = 7 per group, approximately 50% female) and immunofluorescence analyses (N = 4 per group, 50% female) were performed at the study endpoint.

2.3. Behavioral assessments

2.3.1. All-limb grip strength

For this and all subsequent described outcome measures, experimenters were blinded to group. All-limb grip strength was assessed using a grip force transducer (Bioseb Model GT3, Pinellas Park, FL, USA) (Owendoff et al., 2023). Mice were gently grasped by the tail and placed on a metal grid, ensuring all four limbs made contact. A steady horizontal tug on the tail was applied, and the force exerted in grams was recorded. Each mouse underwent three trials, and the average grip strength was normalized to body weight (grams/g of body weight) and recorded as the final value.

2.3.2. Motor coordination

Motor coordination was assessed using the rotarod test (BX-ROD, Bioseb, Pinellas Park, FL, USA) as previously described for this model (Viteri et al., 2025b; Watkins et al., 2021). Mice were placed on a rotating rod and allowed to acclimate for 30 s while the rod rotated at 4 rpm. The test protocol consisted of a ramp increase in speed from 4 to 40 rpm over 300 s (Viteri et al., 2025b; Watkins et al., 2021). The latency to fall was recorded as the time taken for the mouse to fall from the rod, and the test was repeated for a second trial. The highest latency time from the two trials was normalized to body weight (time/g) and recorded as the final value.

2.4. In-vivo electrophysiology

Electrophysiological assessments were measured following protocols as previously described (Arnold et al., 2015; Kerr et al., 2025; Viteri et al., 2025b). Fig. 2 shows representative illustrations depicting setup for these recordings. Mice were deeply anesthetized with an intraperitoneal injection of ketamine (100 mg/kg) and xylazine (7.5 mg/kg), placed on a 37 °C heating pad, and positioned prone with the right hindlimb secured with medical tape at a 90° angle relative to the tail. Eye gel was applied to prevent dryness. Two ring electrodes (MFI Medical, San Diego, CA, USA) with conductive gel were positioned around the gastrocnemius (Electrode 1) and calcaneus (Electrode 2). Stimulating needle electrodes (anode and cathode) were placed subcutaneously near the sciatic nerve in the thigh, and a ground electrode was taped to the tail. Electrophysiological recordings were performed using a Sierra Summit system (Cadwell, Kennewick, WA, USA).

2.4.1. Compound muscle action potential (CMAP)

CMAP amplitudes, representing a summated response of muscle excitation and an indicator of neuromuscular excitability, were recorded by applying a supramaximal stimulus to the sciatic nerve. CMAP amplitudes were quantified using peak-to-peak amplitude. Recording sensitivity was set at 10 mV/division, with a time sensitivity of 1 ms / division. Single motor unit potentials (SMUP) were recorded as described previously (Arnold et al., 2015; Kerr et al., 2025; Viteri et al., 2025b) to assess average single motor unit size. A gradually increasing stimulus was applied at 1 Hz to elicit 10 incremental all-or-none responses. SMUP values were calculated as the peak-to-peak amplitude of the 10th SMUP response divided by the number of responses (10). Sensitivity was set at 200 μV/division and 1 ms / division.

2.4.2. Motor unit number estimation (MUNE)

MUNE was calculated using CMAP and SMUP values as previously described (MUNE = CMAP/SMUP) (Kerr et al., 2025; Viteri et al., 2025b). The percentage decrement was calculated as [(Amplitude of 10th response – Amplitude of 1st response)/Amplitude of 1st response] × 100%, using the responses at 50 Hz.

2.4.3. Motor-evoked potentials (MEP)

MEPs were recorded similarly to Kerr et al. and Viteri et al., 2025 (Kerr et al., 2025; Viteri et al., 2025b). Similar to CMAPs, MEP amplitudes reflect the summation of action potentials elicited from the muscle, but are a function of cranial or cervical stimulation, providing insights into the excitability and connectivity of the muscle to the primary motor cortex or corticospinal tracts (Castoldi et al., 2022; Kerr et al., 2025; Viteri et al., 2025b). The setup for MEP recordings (Figs. 1 and 2) was similar to that of CMAPs, with the primary difference being the placement of stimulating electrodes.

For cranial MEPs, stimulating electrodes (MFI Medical, San Diego, CA, USA) were placed subcutaneously on opposite sides of the cranium, 3–4 mm left and right of the bregma, to generate an electric field around the motor cortex (Castoldi et al., 2022; Viteri et al., 2025b). For cervical MEPs, electrodes were placed subcutaneously on opposite sides of the vertebral column near the C2–C3 vertebrae, generating an electric field around the corticospinal tracts (Kerr et al., 2025; Steward et al., 2021; Viteri et al., 2025b). A supramaximal stimulus was applied to evoke maximal MEPs from the gastrocnemius muscle, with amplitudes recorded as the peak-to-peak values that were both maximal and stable. Cranial and cervical MEPs were confirmed by latency, with cranial MEPs averaging 15–17 ms and cervical MEPs 5–10 ms (Kerr et al., 2025; Viteri et al., 2025b). Amplitude recording sensitivity was set at 500 μV/division, and time sensitivity at 5 ms/division.

Final MEP values were normalized as the MEP amplitude (mV) divided by the CMAP amplitude (mV) (Kerr et al., 2025). This normalization was performed to remove the contribution of neuromuscular excitability loss, isolating the excitability of the motor cortex or corticospinal tracts.

2.5. Plantar flexion contractility torque

Plantar flexion contractility torque was measured following previously published protocols (Sheth et al., 2018; Viteri et al., 2025b; Wier et al., 2019). This method assessed torque production as a readout of neuromuscular and muscle contractile function following peripheral nerve stimulation. Fig. 2 shows representative illustrations depicting setup for these recordings. After completing CMAP and MEP measurements, the right hindlimb foot was affixed to a force transducing pedal using medical tape, with the tibia aligned at a 90° angle. The femoral condyles were secured with a clamp to ensure rotation occurred only at the ankle. Subcutaneous needle electrodes (MFI Medical, San Diego, CA, USA) were placed adjacent to the tibial branch of the sciatic nerve. Torque recordings were conducted using a 1305 A whole animal system (Aurora Scientific Inc., Canada). Twitch contractility torque was measured using a single 0.20 ms supramaximal stimulus, while tetanic torque was measured with a 1 s stimulus train at 125 Hz. Final contractility values were recorded in mN-m and normalized to body weight.

2.6. Digital PCR

We used primer/probe pairs purchased from Thermo Fisher Scientific (pre-designed and pre-validated by Thermo Fisher Scientific; Waltham, Massachusetts, USA) in digital PCR (dPCR) reactions to quantify the mRNA expression of various markers in the mouse cortex and lumbar spinal cord of a subset of mice.

Senescence and cell-cycle regulation: Cdkn2a (Cyclin-Dependent Kinase Inhibitor 2 A / p16^INK4a; Assay ID Mm00494449_m1), Trp53 (Tumor Protein p53; Assay ID Mm01731290_g1), Cdkn1a (Cyclin-Dependent Kinase Inhibitor 1 A / p21; Assay ID Mm04205640_g1), and Ccnd1 (Cyclin D1; Assay ID Mm00432359_m1).

Apoptosis and cell survival:

Bcl2 (B-Cell Lymphoma 2; Assay ID Mm00477631_m1), Bcl2l1 (BCL-XL / BCL2-Like 1; Assay ID Mm00437783_m1), and Bcl2l2 (BCL-W / BCL2-Like 2; Assay ID Mm00432054_m1).

SASP and inflammatory cytokines:

Il1b (Interleukin-1β; Assay ID Mm00434228_m1), Il6 (Interleukin-6; Assay ID Mm00446190_m1), Cxcl8 (C-X-C Motif Chemokine Ligand 8 / IL-8; Assay ID Mm01337546_g1), Il15 (Interleukin-15; Assay ID Mm00434210_m1), Csf2 (Granulocyte-Macrophage Colony-Stimulating Factor / GM-CSF; Assay ID Mm01290062_m1), Ifng (Interferon-γ; Assay ID Mm01168134_m1), and Tgfb1 (Transforming Growth Factor-β1; Assay ID Mm01178820_m1).

ALS-related pathology markers:

Tardbp (TAR DNA-Binding Protein 43; Assay ID Hs00606522_m1) and Prnp (Prion Protein; Assay ID Mm07296968_m1).

Housekeeping genes:

Hprt1 (Hypoxanthine Phosphoribosyltransferase 1; Assay ID Mm03024075_m1), Ywhaz (Tyrosine 3-Monooxygenase/Tryptophan 5-Monooxygenase Activation Protein Zeta; Assay ID Mm03950126_s1), and Polr2j (RNA Polymerase II Subunit J; Assay ID Mm00448649_m1).

Tissue harvesting and dPCR were done similarly as Viteri et al., 2025 (Viteri et al., 2025b). Mice were deeply anesthetized and decapitated. The cortex and lumbar spinal cord were then harvested, wrapped in aluminum foil, flash frozen in liquid nitrogen, and stored at −80 °C. Total RNA was isolated first by mixing each tissue with 400 μL Trizol (Thermo Fisher Scientific, Waltham, Massachusetts, USA), 80 μL chloroform, homogenizing beads, and then homogenized and centrifuged at 12000 xg. The separated clear aqueous phase was then carefully removed and pipetted into a column extraction kit per the manufacturer’s instructions (Quick-RNA MicroPrep Kit, Zymo Research). From the elution volume, we took the necessary amount to achieve a 1 μg amount of total RNA. We then used this volume to synthesize cDNA from tissue using the SuperScript IV VILO RT in a 20 μL reaction per the manufacturer’s instructions (Thermo Fisher Scientific, Waltham, Massachusetts, USA). The resulting 20 μL reaction was then diluted to a total of 310 μL with water to achieve an 8 μg / μL concentration of cDNA. We used this final volume as the cDNA template for dPCR reactions. cDNA was stored at −20 °C.

To multiplex assays in each dPCR reaction, assays were custom-validated by the manufacturer (Thermo Fisher Scientific, Waltham, Massachusetts, USA) to prevent interaction between fluorescent probes. dPCR reactions were performed in a QuantStudio Absolute Q Digital PCR System (Thermo Fisher Scientific, Waltham, Massachusetts, USA; RRID:SCR_025737). dPCR reactions consisted of a 5× Applied Bio-systems Absolute Q DNA Digital PCR Master Mix (2 μL) (Thermo Fisher Scientific, Waltham, Massachusetts, USA), 0.5× of each primer/probe mix (0.5 μL), 1 μL of cDNA sample, and nuclease free water for a total reaction volume of 10 μL. The assays were conducted on a MAP16 plate (Thermo Fisher Scientific, Waltham, Massachusetts, USA) and we ran the assays with the following thermal cycling protocol: an initial enzyme activation step at 96 °C for 10 min, followed by 40 cycles consisting of denaturing at 96 °C for 5 s, and a combined annealing / extension step at 60 °C for 15 s. After reactions were completed, analysis for final dPCR copies was done on QuantStudio Absolute Q Software version 6.3 (Thermo Fisher Scientific, Waltham, Massachusetts, USA; RRID: SCR_025738). For each sample, the copy number per μL of each assessed gene was normalized to the arithmetic mean of the housekeeping genes, Hprt1 (a purine salvage enzyme with stable expression in neural tissues) (Bonefeld et al., 2008), Ywhaz (a signaling adapter protein abundantly expressed in the nervous system) (Bonefeld et al., 2008; Penna et al., 2011), and Polr2j (an RNA polymerase II subunit for transcriptional normalization) (Červenák et al., 2022), ensuring robust normalization across diverse cellular processes and relevance to neural tissue analysis. Neither the individual genes nor the mean of the three normalizers combined showed changes across conditions, confirming their suitability for normalization (Fig. S4).

2.7. Plasma NfL

For plasma NfL, a biomarker of axonal damage, blood was drawn from the saphenous vein with a hypodermic needle, with a maximum of 100 μL collected per sample. To prevent coagulation, 1 μL of heparin was added per 100 μL of blood. Samples were centrifuged at 2000 ×g for 20 min to separate the plasma, which was then flash frozen in liquid nitrogen and stored at −80 °C. Plasma samples were shipped overnight to RayBiotech (Peachtree Corners, GA, USA) for SIMOA analysis per the manufacturer’s protocol, with NfL levels reported in pg / mL.

2.8. Immunofluorescence

Immunofluorescence assessments were performed similarly to Viteri et al., 2025 (Viteri et al., 2025b). Mice underwent cardiac perfusion with normal saline. Brains and spinal cords were then harvested and post-fixed in 4% paraformaldehyde (PFA) in 1× PBS for 24 h and transferred to 30% sucrose in 1× PBS until equilibrated at 4 °C. Brains were frozen on dry ice, embedded in OCT, and sectioned at 30 μm using a Leica CM1860 cryostat (RRID:SCR_025772) to obtain coronal sections spanning the primary motor cortex (+1.0 mm to −1.5 mm from bregma). The lumbar spinal cord enlargement (L3 to L5 segments), which contains motor neurons innervating the gastrocnemius muscle, was similarly frozen, embedded in OCT, and sectioned transversely at 30 μm. All sections were stored in 1× PBS at 4 °C.

We then performed free floating immunofluorescence for harvested tissue. Every sixth section was selected to ensure stereological analysis across the extent of the tissue while minimizing oversampling of adjacent sections, yielding a total of six sections per animal (Golub et al., 2015; Viteri et al., 2025b; West, 2012; Zhao and van Praag, 2020). One additional section per animal was designated as a negative control, in which the primary antibody was omitted and only the secondary antibody was applied, which yielded no detectable signal.

Sections were washed three times in 1× PBS (10 min each), blocked for 1.5 h in 10% Normal Donkey Serum (NDS) with 0.3% Triton-PBS, and then washed again three times in 1× PBS. Sections were incubated overnight at 4 °C with primary antibodies diluted in 1% NDS and 0.3% Triton-PBS. We used the following primary antibodies: rabbit anti-CTIP2 (1:700; Abcam, ab240636), mouse anti-TDP-43 (1:2000; Thermo Fisher Scientific, MA5–47420; RRID:AB_2942402), goat anti-p53 (1:3000; R&D Systems, AF1355; RRID:AB_354749), rabbit anti-p21 (1:3000; Proteintech, 10355–1-AP; RRID:AB_2077682), mouse anti-p21 (1:1500; Proteintech, 67362–1-Ig; RRID:AB_2882614), mouse anti-BCL2 (1:3000; Proteintech, 68103–1-Ig; RRID:AB_2923635), goat anti-IBA1 (1:1000; abcam, ab289874; RRID:AB_2942069), rabbit anti-ChAT (1:1000; Thermo Fisher Scientific, 20747–1-AP; RRID:AB _10898169), goat anti-ChAT (1:1000; Thermo Fisher Scientific, PA1–9027; RRID:AB_2079590), mouse anti-Phospho-histone H2A.X (Ser139) (1:200; Thermo Fisher Scientific, MA1–2022; RRID: AB_559491), goat anti-NeuN (1:500; Thermo Fisher Scientific, PA5–143586; RRID:AB_2942815), and rabbit anti-Phospho-TDP43 (Ser409/Ser410) (1:200; Thermo Fisher Scientific, PA5–114661; RRID:AB_2899297).

After incubation, sections were washed three times in 1× PBS (10 min each) and then incubated for 1.5 h in the dark with secondary antibodies diluted 1:500 in 1% NDS and 0.3% Triton-PBS. Secondary antibodies included Donkey-anti-Rabbit IgG 647 (A-31573; RRID: AB_2536183), Donkey-anti-Mouse IgG 488 (A-21202; RRID: AB_141607), Donkey-anti-Goat IgG 405 (A48259; RRID:AB_2890272), Donkey-anti-Goat IgG 546 (A-11056; RRID:AB_142628), and Donkey-anti-Goat IgG 488 (A-21131; RRID:AB_141618) (all from Thermo Fisher Scientific). Sections were washed again (three 10-min washes in PBS in the dark), mounted onto gelatin-coated slides and coverslipped using ProLong Gold Antifade (Thermo Fisher Scientific, P36930), with rectangular glass coverslips (No. 1.5; 22 × 40 mm; Corning, CLS2980224) used for mounting tissue sections, and sealed with nail polish. Slides were stored at 4 °C in the dark.

All immunofluorescence images were acquired using consistent imaging settings for each antibody. Images were collected using an inverted IX83 Evident/Olympus widefield fluorescence microscope equipped with a Hamamatsu ORCA-Flash4.0LT3 digital camera (model# C11440) with 20× (LUCPlanFL N, numerical aperture 0.45) and 40× (LUCPlanFL N, numerical aperture 0.60) objective lenses and processed using Olympus cellSens software (RRID:SCR_014551). Exposure times were kept the same within each experiment for a given antibody and applied uniformly across animals and experimental groups. Control sections processed without primary antibody (secondary antibody only) were included and mounted separately to assess background signal and yielded no detectable signal. For each animal, 6 sections were mounted per slide for fluorescent imaging and signal intensity measurements were taken from each cortical hemisphere and each ventral horn of the spinal cord, yielding 10–12 images per animal per marker. For statistical analysis, values from all images belonging to a given animal were averaged to yield a single value per animal per marker, and this animal-level average was treated as the unit of biological replication (N = 4 per group).

Images were acquired from layer V of the primary motor cortex from both hemispheres (Viteri et al., 2024; 2025) (Viteri et al., 2025a; Viteri et al., 2025b). The primary motor cortex was identified using stereotaxic coordinates with reference to the Allen Mouse Brain Atlas and Paxinos and Franklin’s The Mouse Brain in Stereotaxic Coordinates (4th edition, 2013). Sections were selected from coronal levels spanning approximately +1.0 mm to −1.5 mm relative to bregma, and regions of interest were restricted to cortex located ~1.0–2.0 mm lateral to the midline, corresponding to primary motor cortex (Muñoz-Castañeda et al., 2021; Weiler et al., 2008). Regions lateral to this zone, corresponding to secondary motor cortex, were excluded.

Within the primary motor cortex, layer V was identified based on cortical depth from the pial surface and anatomical landmarks visible under brightfield and fluorescence microscopy. In 30 μm coronal sections, layer V was defined as the band located approximately 500–900 μm below the pial surface (Grimsley et al., 2013), with layer V bounded superficially by the densely packed neurons of layers II/III and the thinner, more cell-dense layer IV (Weiler et al., 2008). Thus, the transition from layer IV to layer V was defined by a reduction in cell packing density.

For cortical assessments, the anatomical criteria described above (stereotaxic location, cortical depth from the pial surface, and laminar boundaries defined by layers II/III, IV, VI, and underlying white matter) were applied consistently across all figures. For Figs. 4 and 6, CTIP2 immunofluorescence was used as an additional confirmation of layer V identity, based on the higher density of CTIP2-positive neurons in layer V compared with layer IV (Cánovas et al., 2015). For Fig. S3, NeuN immunofluorescence was used to identify neuronal profiles within the same layer V region defined by these anatomical criteria, with NeuN-positive neurons identified based on nuclear labeling and soma size consistent with cortical neurons (approximately 10–20 μm in diameter (Das and Ramanan, 2023)).

Fig. 4. — Senolytic treatment preferentially reduced ALS pathology in the cortex of TDP-43^Q331K mice. (A) CTIP2+ neuron counts in layer V of the motor cortex were reduced in TDP-43-vehicle mice compared to WT-controls, while counts in senolytic-treated mice were similar to WT-controls and higher than TDP-43-vehicle mice. (B) TDP-43 MFI measured inside CTIP2+ neurons was higher in TDP-43-vehicle mice compared to WT-controls; TDP-43 MFI in senolytic-treated mice was lower than TDP-43-vehicle mice and did not differ from WT-controls. (C) Representative images from layer V of the motor cortex (CTIP2, TDP-43, merge) for WT-control, TDP-43-vehicle, and TDP-43-senolytic mice. For each group, the top row shows a lower-magnification view (scale bar = 100 μm) and the bottom row a higher-magnification view (scale bar = 15 μm). (D) ChAT+ neuron counts in the ventral horn of the spinal cord were reduced in both TDP-43-vehicle and TDP-43-senolytic mice relative to WT-controls, with no difference between the two TDP-43^Q331K groups. (E) TDP-43 MFI measured inside ChAT+ motor neurons was higher in both TDP-43^Q331K groups relative to WT-controls and did not differ between them. (F) Representative images from the spinal cord ventral horn (ChAT, TDP-43, merge) for WT-control, TDP-43-vehicle, and TDP-43-senolytic mice, shown at the same lower and higher magnifications as in (C). Significance: *P < 0.05, **P < 0.01, ***P < 0.001, ns = not significant. Data are presented as individual values with group means ± SD.

Fig. 6. — (A) H2AX signal (DNA damage marker) inside CTIP2+ neurons in primary motor cortex layer V, and the percentage of CTIP2+ neurons positive for H2AX, did not differ between groups. Representative images (CTIP2, H2AX, merge) for WT-control, TDP-43-vehicle, and TDP-43-senolytic mice. (B) P21 signal inside CTIP2+ neurons in layer V, and the percentage of CTIP2+ neurons positive for P21, was higher in TDP-43-vehicle mice compared to WT-controls, with no difference between senolytic-treated and TDP-43-vehicle mice. Representative images (CTIP2, P21, merge). (C) H2AX signal inside ChAT+ motor neurons in the spinal cord ventral horn, and the percentage of ChAT+ neurons positive for H2AX, were higher in bothTDP-43^Q331K groups compared to WT-controls, with no difference between senolytic-treated and TDP-43-vehicle mice. Representative images (ChAT, H2AX, merge). (D) P21 signal inside ChAT+ motor neurons in the ventral horn, and the percentage of ChAT+ neurons positive for P21, were higher in both TDP-43^Q331K groups compared to WT-controls, with no difference between senolytic-treated and TDP-43-vehicle mice. Representative images (ChAT, P21, merge); scale bar = 20 μm. Significance: *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, ns = not significant. Data are presented as individual values with group means ± SD.

For spinal cord sections, imaging was conducted bilaterally in the ventral horn of the lumbar enlargement (L3–L5 segments). Motor neurons were identified based on their large soma size (typically 25–40 μm in diameter in adult mice (Liu et al., 2020; Maxwell et al., 2018)). For Figs. 4 and 6, ChAT immunofluorescence was used to identify motor neurons in the ventral horn, with ChAT-positive cells detected based on somatic labeling and size-based criteria appropriate for motor neuron cell bodies. For Fig. S3, NeuN immunofluorescence was used to identify ventral horn neurons, with NeuN-positive cells detected based on somatic labeling and size-based criteria appropriate for motor neuron cell bodies.

Analysis of antibody signal was performed in ImageJ (1.54 g; RRID: SCR_003070) (Schneider et al., 2012) to quantify mean fluorescence intensity, cell counts, and morphological measures using automated, mask-based analysis.

Neuronal identification and cell counts.

For CTIP2-positive nuclei in layer V of the primary motor cortex, images were converted to grayscale and thresholded. The threshold value was selected based on representative images to capture CTIP2-labeled nuclei while minimizing background signal. Then, a fixed threshold value was applied to all images uniformly within the analysis. The thresholded images were converted to binary masks, and CTIP2-positive nuclei were identified using automated particle detection based on size and shape criteria. Nuclear masks were restricted to objects with an area between approximately 50–300 μm² (Das and Ramanan, 2023) and a circularity between 0.5 and 1.0 (Das and Ramanan, 2023), consistent with the expected size and morphology of cortical neuronal nuclei in adult mice, which typically have nuclear diameters of ~8–20 μm (Das and Ramanan, 2023). Objects outside these criteria were excluded to eliminate debris, fragmented signal, and non-nuclear labeling. All thresholding, size, and shape parameters were held constant across sections, animals, and experimental groups. Quantification was restricted to layer V of the primary motor cortex.

For ChAT-positive motor neurons in the spinal cord, images were converted to grayscale and thresholded. The threshold value was selected once based on representative images to robustly identify ChAT-labeled motor neuron somata while minimizing background signal. Thresholded images were converted to binary masks, and ChAT-positive objects were identified using automated particle detection based on size-based criteria. Masks were restricted to a minimum area of approximately 250 μm² (Maxwell et al., 2018) to selectively capture large motor neuron somata, which typically range from 25 to 40 μm (Liu et al., 2020; Maxwell et al., 2018) in diameter in adult mice. Circularity constraints were not applied due to the irregular morphology of motor neuron cell bodies. These masks were used to quantify marker intensity within identified motor neurons.

Measurement of TDP-43 signal within CTIP2- and ChAT-positive neurons.

For layer V of the primary motor cortex and ventral horn of the spinal cord, TDP-43 signal within CTIP2-positive neurons was quantified using a cell-specific, mask-based approach. CTIP2-positive nuclei were first identified as described. These CTIP2-defined nuclear masks were then applied to the TDP-43 channel, and mean TDP-43 fluorescence intensity was measured only within the identified CTIP2-positive nuclei. No additional thresholding was applied to the TDP-43 channel during intensity measurements. Because measurements were performed on a mean fluorescence intensity per-cell basis and averaged per image, values are inherently normalized to nuclear size and cell number.

For the ventral horn of the spinal cord, TDP-43 signal within ChAT-positive motor neurons was quantified using a separate cell-specific mask-based approach. ChAT-positive motor neurons were first identified as described. ChAT-defined somatic masks were then applied to the TDP-43 channel, and mean TDP-43 fluorescence intensity was measured only within these masks. No additional thresholding was applied to the TDP-43 channel during intensity measurements. Because measurements were performed on a mean fluorescence intensity per-cell basis and averaged per image, values are inherently normalized to neuronal size and cell number.

Measurement of pTDP-43 signal within NeuN-positive neurons (see Fig. S3).

For layer V of the primary motor cortex and ventral horn of the spinal cord, phosphorylated TDP-43 (pTDP-43) signal within NeuN-positive neurons was quantified using a cell-specific, mask-based approach. NeuN-positive neurons were first identified as described above by converting images to grayscale and applying a fixed intensity threshold. The threshold value was selected once based on representative images to capture NeuN-labeled neurons while minimizing background signal, and no image-by-image or adaptive thresholding was used. NeuN-defined masks were restricted to objects with an area of approximately 150–600 μm² for cortical neurons and 200–800 μm² for spinal neurons [57], selected to capture neuronal nuclei plus somatic labeling while excluding small non-neuronal nuclei and background signal (Mullen et al., 1992). For layer V, circularity constraints of approximately 0.3–1.0 were applied to exclude highly elongated or fragmented objects while allowing for variability in neuronal soma shape. Circularity constraints were not applied to ventral horn neurons. These NeuN-defined masks were then applied to the pTDP-43 channel, and mean pTDP-43 fluorescence intensity was measured only within identified NeuN-positive neurons. No additional thresholding was applied to the pTDP-43 channel during intensity measurements, and fluorescence values were extracted directly from the pTDP-43 signal within the NeuN-defined masks. Because measurements were performed on a mean fluorescence intensity per-cell basis and averaged per image, values are inherently normalized to neuronal size and cell number.

Measurement of pTDP-43/TDP-43 ratio within NeuN-positive neurons (see Fig. S3).

For layer V of the primary motor cortex and ventral horn of the spinal cord, the ratio of phosphorylated TDP-43 to total TDP-43 within NeuN-positive neurons was quantified using the same NeuN-defined, soma-inclusive masks described above for pTDP-43 measurements. NeuN-positive neurons were identified as described above and TDP-43 and pTDP-43 were measured for each mask as described above. Mean fluorescence intensity for total TDP-43 and pTDP-43 was measured separately within each NeuN-defined neuronal mask, without applying additional thresholding to either channel. For each neuron, the pTDP-43 to total TDP-43 ratio was calculated. Because measurements were averaged on a per-cell basis, values are inherently normalized to neuronal size and cell number.

Cytosolic pTDP-43 within NeuN-positive neurons (see Fig. S3).

For layer V of the primary motor cortex and the ventral horn of the spinal cord, cytosolic phosphorylated TDP-43 signal within NeuN-positive neurons was quantified using a cell-specific, mask-based approach. NeuN-positive neurons were first identified as described above by converting images to grayscale and applying a fixed intensity threshold determined empirically for the NeuN antibody and then applied uniformly across all images within the analysis. The threshold value was selected once based on representative images to capture NeuN-labeled neurons while minimizing background signal, and no image-by-image or adaptive thresholding was used. Thresholded images were converted to binary masks, and NeuN-positive neurons were identified using automated particle detection based on size and shape criteria appropriate for NeuN labeling in adult mouse cortex and ventral horn, which includes neuronal nuclei together with the surrounding soma. NeuN-defined masks were restricted to objects with an area of approximately 150–600 μm² for layer V neurons and 200–800 μm² for ventral horn neurons, selected to capture cortical and spinal neuronal nuclei plus somatic labeling while excluding small non-neuronal nuclei and background signal. For layer V, circularity constraints of approximately 0.3–1.0 were applied to exclude highly elongated or fragmented objects while allowing for variability in neuronal soma shape. No constraints were applied for the ventral horn.

To isolate cytosolic signal, a nuclear region was identified within each NeuN-defined neuron using the NeuN fluorescence channel (Kelley and Paschal, 2019; Zhou et al., 2025). Because NeuN is predominantly localized to the neuronal nucleus and is widely used as a nuclear neuronal marker (Mullen et al., 1992), the NeuN channel was used to delineate the nuclear compartment. Within each NeuN-defined soma, the NeuN channel was converted to grayscale and a fixed high-intensity threshold was applied to capture the brightest NeuN signal, corresponding to the nucleus. This threshold was determined once for the NeuN antibody based on representative images and then held constant across all images; no adaptive or image-by-image thresholding was used. The resulting binary mask defined the nuclear region. The NeuN-defined nuclear mask was then subtracted from the corresponding NeuN-defined somatic mask to generate a cytosolic region of interest for each neuron. Mean pTDP-43 fluorescence intensity was measured exclusively within this cytosolic region. Because measurements were performed on a mean fluorescence intensity per-cell basis and averaged per image, values are inherently normalized to neuronal size and cell number.

Senescence marker expression (see Fig. S5).

For layer V of the primary motor cortex and the VH of the spinal cord, P21, BCL-2, and P53 mean fluorescence intensity was quantified from immunofluorescence images using a threshold-based, region-level approach restricted to nuclear-sized signal. For each marker, the channel was converted to grayscale, and a single fixed intensity threshold was selected once based on representative images to capture nuclear-localized signal for each channel while minimizing background fluorescence; no image-by-image or adaptive thresholding was used. Thresholded images were converted to binary images, and P21, BCL-2, and P53 positive nuclear-sized objects were identified using automated particle detection with size and shape constraints consistent with cortical and spinal neuronal nuclei. Total mean fluorescence intensity for each marker was then measured for all nuclear-sized objects within layer V or the VH. Measurements therefore reflect bulk fluorescence for each marker across all cells within layer V or VH.

Neuronal senescence markers within CTIP2- and ChAT-positive cells.

For layer V of the primary motor cortex and ventral horn of the spinal cord, phosphorylated histone H2A.X and P21 were quantified within identified CTIP2-positive and ChAT-positive neurons in a similar manner as described above for Measurement of TDP-43 signal within CTIP2- and ChAT-positive neurons.

Microglial number and morphology.

For microglia in layer V of the primary motor cortex and the ventral horn of the spinal cord (Leyh et al., 2021; Zanier et al., 2015), IBA1-positive cells were converted to grayscale and thresholded. The threshold value was selected based on representative images to capture IBA1-labeled cells while minimizing background signal. Then, a fixed threshold value was applied to all images uniformly within the analysis. The thresholded images were converted to binary masks, and IBA1-positive cells were identified using automated particle detection approach (Leyh et al., 2021; Stetzik et al., 2022; Young and Morrison, 2018; Zanier et al., 2015) based on size and shape criteria. Masks were restricted to objects with an area between approximately 20–200 μm², selected to capture microglial somata together with immediately adjacent proximal processes while excluding small debris, fragmented signal, and larger non-microglial cells such as neurons (Young and Morrison, 2018; Zanier et al., 2015). Circularity constraints of approximately 0.2–1.0 were applied to accommodate the wide range of cortical and ventral horn microglial morphologies, from highly ramified to more amoeboid states, while excluding elongated non-cellular artifacts (Leyh et al., 2021; Young and Morrison, 2018; Zanier et al., 2015). All thresholding, size, and shape parameters were held constant across sections, animals, and experimental groups. Microglial number was quantified as the total number of IBA1-positive masks per region, and morphological metrics including circularity were extracted from each individually identified microglial mask and averaged per image.

Senescence-associated markers within IBA1-positive microglia.

For both layer V of the primary motor cortex and the ventral horn of the spinal cord, senescence-associated markers within IBA1-positive microglia were quantified using the same pipeline as described above in Measurement of TDP-43 signal within CTIP2- and ChAT-positive neurons.

2.9. Statistical analysis

All statistical analyses were performed using GraphPad Prism 10 (GraphPad Version 10.1.1 (270) Software, San Diego, CA, USA; RRID: SCR_002798). Data that included two factors (animal group and time point) and that involved repeat measures such as weight measurements, electrophysiological assessments, behavioral assessments, and plasma NfL quantification were analyzed using a two-way mixed-effects ANOVA with repeated measures. dPCR data were analyzed using a one-way ANOVA to assess differences between groups. Immunohistochemical assessments (mean fluorescence intensity, cell counts, morphological assessments) were quantified from multiple images per animal, which were then averaged to yield a single animal-level value per marker. These animal-level values were used as the unit of biological replication (N = 4 per group) and analyzed using a one-way ANOVA to assess differences between groups.

Post-hoc statistical analyses for all multiple comparisons were done using Tukey’s Honestly Significant Difference (HSD) test. Data normality was assessed using the Shapiro-Wilk test. All group data are expressed as means ± standard deviation (SD), and statistical significance was determined using p < 0.05. All means, SD, and statistical information that accompanies all figures (Figs. 1–7) and supplementary figures (Fig. S1–7) can be found as tables in supplementary document S2.

Fig. 7. — (A) Representative IBA1 images from primary motor cortex layer V for WT-control, TDP-43-vehicle, and TDP-43-senolytic mice; white arrows indicate microglia with enlarged somas and thickened processes; scale bar = 100 μm. (B) Microglia number (IBA1+ cells) was higher in TDP-43-vehicle mice compared to WT-controls and lower in senolytic-treated mice compared to TDP-43-vehicle mice, with no difference between senolytic-treated mice and WT-controls. Circularity was lower in TDP-43-vehicle mice compared to WT-controls and higher in senolytic-treated mice compared to TDP-43-vehicle mice, with no difference between senolytic-treated mice and WT-controls. (C) Representative images (IBA1, TDP-43, P21, merge) of individual microglia; scale bar = 20 μm. Solid circles indicate microglia with TDP-43 and P21 signal comparable to WT-controls; dashed circles indicate microglia with elevated TDP-43 and P21 signal in TDP-43-vehicle mice. (D) TDP-43 signal inside IBA1+ microglia was higher in TDP-43-vehicle mice compared to WT-controls and lower in senolytic-treated mice compared to TDP-43-vehicle mice. P21 signal inside IBA1+ microglia was higher in TDP-43-vehicle mice compared to WT-controls and lower in senolytic-treated mice compared to TDP-43-vehicle mice. Significance: *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, ns = not significant. Data are presented as individual values with group means ± SD.

For reference, the longitudinal outcomes from Fig. 1 and the outcomes from the senolytic intervention experiment (Figs. 2–3) were stratified by sex and analyzed using the same statistical approach described above, run separately for each sex, with results shown in the corresponding figures in Supplementary Document 3 and corresponding statistics also provided in that document.

Fig. 3. — Senolytic treatment reduced plasma neurofilament light chain elevation in TDP-43^Q331K mice. Plasma NfL concentration was measured longitudinally in WT-control, TDP-43-vehicle, and TDP-43-senolytic mice at baseline, mid-time point, and final time point. NfL did not differ between groups at baseline. At the mid-time point, NfL was higher in both TDP-43-vehicle and senolytic-treated mice compared to WT-controls, with no difference between the two TDP-43^Q331K groups. At the final time point, NfL was lower in senolytic-treated mice compared to TDP-43-vehicle mice, while both TDP-43^Q331K groups remained elevated relative to WT-controls. Pink arrows denote the point at which senolytic or vehicle dosing was initiated in TDP-43 mice. Significance: *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. Data are presented as individual values with group means ± SD.

All figures were made using a combination of GraphPad Prism 10, R Studio (2025.5.1.513), and BioRender (RRID:SCR_018361).

3. Results

3.1. Senescence markers emerged in the spinal cord and motor cortex early in disease progression in TDP-43^Q331K mice

To define the temporal relationship between cellular senescence and functional decline, we combined longitudinal in vivo electrophysiology and muscle contractile function with cross-sectional profiling of senescence-associated markers in the cortex and spinal cord of TDP-43^Q331K and WT-control mice at 4, 7, 10, and 13 weeks of age (Fig. 1A). Fig. 1B–C summarizes trajectories of select senescence markers (Trp53, Cdkn1a, Bcl2; full panel in Fig. S1) and measures of corticomuscular function (cranial MEP) and spinal/peripheral motor function (cervical MEP, CMAP, and MUNE; full electrophysiological dataset in Fig. S1). To facilitate comparison of molecular and functional changes over time, values are expressed as log2(TDP-43^Q331K /WT-control).

In both the cortex and spinal cord, senescence-associated molecular changes emerged early in the TDP-43^Q331K disease course (Fig. 1B–C).

In the cortex, Trp53 and Bcl2 were significantly elevated compared to WT-control by 7 weeks, while cranial MEP deficits showed a significant reduction at 13 weeks. Cdkn1a became elevated at 13 weeks, coinciding with the onset of reduced cranial MEP (Fig. 1B; full statistics in Fig. S1).

In the spinal cord (Fig. 1C), Trp53 and Cdkn1a were significantly elevated at 4 weeks compared to WT-controls, coinciding with a significant reduction in CMAP at that age. Both markers then normalized to WT-control levels by 7 weeks, when MUNE first became significantly reduced. CMAP and MUNE remained significantly reduced from 7 through 13 weeks, the age at which Bcl2 significantly increased an when Trp53 was elevated again. Cervical MEP did not differ between genotypes at any age (Fig. 1C; full statistics in Fig. S1).

Together, these findings position senescence-associated changes as an early feature of TDP-43^Q331K pathology, emerging alongside detectable corticomuscular and neuromuscular deficits.

3.2. Senolytic treatment improved corticomuscular and neuromuscular function, as well as motor behavior in TDP-43^Q331K mice

Based on prior evidence linking cellular senescence to neurodegeneration and ALS-related pathology, we tested whether longitudinal D&Q treatment could improve motor, neuromuscular, and corticomuscular outcomes in TDP-43^Q331K mice; our temporal characterization further supported this approach by showing that senescence-associated markers emerged alongside functional decline in this model (Fig. 1). Mouse body weights were similar across groups until week 10 (Fig. S2A). From week 11 onward, both TDP-43^Q331K groups gained more weight than WT-controls, with no differences between TDP-43-vehicle and senolytic-treated mice, consistent with prior reports (Watkins et al., 2021).

At baseline, before senolytic dosing began, both TDP-43^Q331K groups exhibited functional impairments consistent with ALS phenotype relative to WT-controls, with no differences between the two TDP-43^Q331K groups. Compared to WT-Controls, cranial MEP amplitude was reduced in both TDP-43^Q331K groups (Fig. 2B), while cervical MEP did not differ between groups (Fig. 2C). CMAP and MUNE were also reduced in both TDP-43^Q331K groups (Fig. 2D). SMUP was elevated in TDP-43-vehicle mice compared to WT-controls, while TDP-43-senolytic mice did not differ from WT-controls (Fig. S2B). Tetanic torque was reduced in both TDP-43^Q331K groups (Fig. 2E), while twitch torque did not differ between groups (Fig. S2C). Grip strength and rotarod performance were reduced in both TDP-43^Q331K groups compared to WT-controls (Fig. 2F).

Mid-time point measurements were limited to motor behavior (see Methods). Senolytic treatment improved rotarod performance compared to TDP-43-vehicle mice, and grip strength in senolytic-treated mice was no longer different from WT-controls (Fig. 2F).

At the final time point, senolytic treatment increased cranial MEP amplitude compared to TDP-43-vehicle mice, to levels comparable to WT-controls (Fig. 2B), but cervical MEP remained similar between groups (Fig. 2C). Senolytic treatment resulted in increased CMAP and MUNE compared to TDP-43-vehicle mice. SMUP was higher in TDP-43-senolytic mice than in both WT-controls and TDP-43-vehicle mice (Fig. S2B). Senolytic treatment also increased tetanic and twitch contractility torque compared to TDP-43-vehicle mice (Fig. 2E and Fig. S2C). Rotarod performance was higher in senolytic-treated mice than TDP-43-vehicle mice at the final time point, reaching WT-control levels (Fig. 2F). Grip strength no longer differed between senolytic-treated and TDP-43-vehicle mice at this time point (Fig. 2F).

Together, these results demonstrate that senolytic treatment improved motor behavior and both corticomuscular and neuromuscular function in TDP-43^Q331K mice compared to vehicle-treated mice.

3.3. Senolytic treatment reduced plasma neurofilament light chain elevation in TDP-43^Q331K mice

Plasma NfL, a biomarker of axonal damage, did not differ between groups at baseline. At the mid-time point, NfL was higher in both TDP-43-vehicle and senolytic-treated mice compared to WT-controls, with no difference between the two TDP-43^Q331K groups. At the final time point, NfL was lower in senolytic-treated mice compared to TDP-43-vehicle mice, though NfL in both TDP-43^Q331K groups remained elevated relative to WT-controls (Fig. 3). Together, these data indicate that senolytic treatment attenuated the rise in plasma NfL.

3.4. Senolytic treatment preferentially reduced ALS pathology in the cortex of TDP-43^Q331K mice

Compared to WT-controls, TDP-43-vehicle mice exhibited a reduced number of CTIP2+ neurons and higher TDP-43 mean fluorescence intensity (MFI) within these neurons in layer V of the motor cortex (Fig. 4A–C). In contrast, senolytic-treated mice showed similar number of CTIP2+ neurons as WT-controls, with lower TDP-43 MFI inside CTIP2+ neurons relative to TDP-43-vehicle mice. However, ChAT+ motor neuron counts in the spinal cord ventral horn were reduced in both TDP-43^Q331K groups compared to WT-controls, with TDP-43 MFI inside ChAT+ motor neurons also elevated in both TDP-43^Q331K groups (Fig. 4D–F).

We then assessed pathological TDP-43 accumulation, and measured TDP-43 phosphorylation, linked to aggregation, nuclear mislocalization, and ALS pathology (Fig. S3) (Hasegawa et al., 2008; Mitchell et al., 2015; Mitra et al., 2025). We quantified total pTDP-43 MFI, the pTDP-43/total TDP-43 ratio (reflecting relative phosphorylation), and cytosolic pTDP-43 MFI (indicating cytoplasmic mislocalization) inside NeuN+ neurons in layer V of the motor cortex and in the ventral horn of the spinal cord. In motor cortex layer V and in the spinal cord ventral horn, pTDP-43 MFI inside NeuN+ neurons was higher in TDP-43-vehicle mice compared to WT-controls. Senolytic-treated mice showed lower pTDP-43 MFI inside NeuN+ neurons relative to TDP-43-vehicle mice. In contrast, the pTDP-43/total TDP-43 ratio and cytosolic pTDP-43 measured inside NeuN+ neurons were higher in both TDP-43^Q331K groups compared to WT-controls and did not differ with senolytic treatment. Interestingly, mouse Tardbp transcripts were increased in the cortex and spinal cord following senolytic treatment (Fig. S4). This effect is unlikely to reflect altered transgene TDP-43^Q331K expression, as it is driven by the Prnp promoter (Arnold et al., 2013), which also remained unchanged across groups (Fig. S4). This increase may instead reflect a transcriptional response to reduced TDP-43 protein levels, though the biological significance remains unclear.

Together, these data indicate that in the motor cortex, senolytic treatment preserved CTIP2+ neuron number and reduced total TDP-43 and pTDP-43 accumulation within neurons, though it did not reduce the degree of TDP-43 phosphorylation or cytosolic mislocalization. In the spinal cord, senolytic treatment did not prevent ChAT+ motor neuron loss, reduce total TDP-43, or alter the degree of TDP-43 phosphorylation or cytosolic mislocalization.

3.5. Senolytics exerted a stronger effect on senescence in the cortex than in the spinal cord of TDP-43^Q331K mice

At the final time point, we used dPCR to assess whether senolytic treatment altered the mRNA expression level of genes related to senescence. These included senescence and cell-cycle regulation (Trp53 [P53] – induces senescence/apoptosis; Cdkn1a [P21] – enforces cell-cycle arrest; Ccnd1 [BCL1] – promotes G1/S progression), apoptosis and cell survival (Bcl2 [BCL2] – inhibits apoptosis; Bcl2l1 [BCL-XL] – prevents mitochondrial membrane permeabilization; Bcl2l2 [BCL-W] – supports neuronal survival), and Senescence Associated Secretory Phenotype (SASP)/cytokine signaling (Il1b [IL-1β] – SASP cytokine; Il6 [IL6] – inflammatory cytokine; Cxcl8 [IL8] – chemokine; Il15 [IL15] – promotes lymphocyte survival; Csf2 [GM-CSF] – activates myeloid cells; Ifng [IFN-γ] – stimulates macrophages; Tgfb1 [TGF-β1] – promotes fibrosis/remodeling), expressed as log2 fold change (log2FC) relative to WT-controls (Fig. 5).

Fig. 5. — Senolytics normalized senescence marker expression in the cortex and spinal cord of TDP-43^Q331K mice. (A) summary matrix of mRNA expression (log2FC relative to WT-controls) of senescence-related genes in the cortex at final time point. Circled in pink: *Trp53*, *Cdkn1a* (senescence and cell-cycle regulation), *Bcl2* (apoptosis and cell survival), and *Csf2* (Senescence associated secretory phenotype and inflammatory cytokines) are each higher in TDP-43-vehicle mice compared to WT-controls, lower in senolytic-treated mice compared to TDP-43-vehicle mice, and not different from WT-controls in senolytic-treated mice. All remaining genes are reported in Fig. S4A–E. (B) summary matrix of mRNA expression (log2FC relative to WT-controls) of senescence-related genes in the spinal cord. Circled in pink: *Cdkn1a* (senescence and cell-cycle regulation), *Bcl2, Bcl2l2* (apoptosis and cell survival), and *Cxcl8* (Senescence associated secretory phenotype and inflammatory cytokines) are each higher in TDP-43-vehicle mice compared to WT-controls, lower in senolytic-treated mice compared to TDP-43-vehicle mice, and not different from WT-controls in senolytic-treated mice. All remaining genes are reported in Fig. S4F–J. Significance: *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, ns = not significant.

In the cortex, the senescence and cell-cycle regulation genes Cdkn1a and Trp53, along with the apoptosis and cell survival gene Bcl2 and the SASP/inflammatory cytokine gene Csf2 (circled in pink oval, Fig. 5A), were all increased in TDP-43-vehicle mice relative to WT-controls, lower in TDP-43-senolytic mice compared to TDP-43-vehicle mice, and not different from WT-controls in TDP-43-senolytic mice. Of the remaining genes assessed in the cortex (Fig. 5A and Fig. S4A–E) Bcl2l1, Bcl2l2, Cxcl8, Ifng, and Il6 did not differ across any comparison; Ccnd1 did not differ between TDP-43-vehicle and WT-controls or between TDP-43-senolytic and TDP-43-vehicle mice, but was higher in TDP-43-senolytic mice compared to WT-controls; Il15 was higher in TDP-43-vehicle mice compared to WT-controls only; Il1b did not differ between TDP-43-vehicle mice and WT-controls but was higher in TDP-43-senolytic mice compared to both; and Tgfb1 was higher in both TDP-43^Q331K groups compared to WT-controls, with no effect of senolytic treatment.

In the spinal cord, the senescence and cell-cycle regulation gene Cdkn1a, the apoptosis and cell survival genes Bcl2 and Bcl2l2, and the SASP/inflammatory cytokine gene Cxcl8 (circled in pink oval, Fig. 5B) were increased in TDP-43-vehicle mice relative to WT-controls, lower in TDP-43-senolytic mice compared to TDP-43-vehicle mice, and not different from WT-controls in TDP-43-senolytic mice. Of the remaining genes assessed in the spinal cord (Fig. 5B and Fig. S4F–J), Bcl2l1, Ifng, and Il6 did not differ across any comparison; Ccnd1, Trp53, Csf2, Il15, and Tgfb1 were higher in both TDP-43^Q331K groups compared to WT-controls, with no effect of senolytic treatment; and Il1b did not differ between TDP-43-vehicle mice and WT-controls but was higher in TDP-43-senolytic mice compared to both.

Immunofluorescence confirmed transcript-level changes at the protein level (Fig. S5). In layer V of the motor cortex, P21, BCL2, and P53 signal intensity were each higher in TDP-43-vehicle mice compared to WT-controls and lower in senolytic-treated mice compared to TDP-43-vehicle mice; P21 and BCL2 were normalized to WT-control levels, while P53 remained above WT-controls. In the spinal cord ventral horn, all three markers were higher in TDP-43-vehicle mice compared to WT-controls, but senolytic treatment reduced only P21, which remained above WT-control levels; BCL2 and P53 were unaffected by treatment.

Together, these data indicate that senolytic treatment normalized several senescence-related genes in both the cortex and spinal cord, but full normalization at the protein level was seen only in the cortex, specifically for P21 and BCL2, indicating a more specific effect of senolytic treatment on senescence in the cortex compared to the spinal cord.

3.6. Senolytics reduce senescent microglia TDP-43^Q331K mice

Having shown that senolytic treatment reduced senescence-related transcripts and proteins in the cortex and spinal cord, we next asked whether this reduction reflected clearance of senescence within neurons themselves, given evidence that post-mitotic neurons can express markers of senescence (Herdy et al., 2022; Jurk et al., 2012; Vazquez-Villaseñor et al., 2020). In primary motor cortex layer V (Fig. 6A–B), H2AX, a marker of DNA damage, showed no group differences in signal intensity inside layer V neurons labeled with CTIP2. The percentage of CTIP2+ neurons positive for H2AX also did not differ between groups. P21 signal intensity within CTIP2+ layer V neurons was elevated in TDP-43-vehicle mice compared to WT-controls and remained high in the TDP-43-senolytic treatment group. The percentage of CTIP2+ neurons positive for P21 was similarly higher in both TDP-43^Q331K groups compared to WT-controls, with no effect of senolytic treatment. In the spinal cord ventral horn (Fig. 6C–D), H2AX signal intensity within ChAT+ neurons was elevated in both TDP-43^Q331K groups compared to WT-controls and unaffected by treatment. The percentage of ChAT+ neurons positive for H2AX was also elevated in both TDP-43^Q331K groups compared to WT-controls, with no effect of treatment. P21 signal intensity within ChAT+ motor neurons was elevated in both TDP-43^Q331K groups compared to WT-controls. The percentage of ChAT+ neurons positive for P21 was similarly elevated in both TDP-43^Q331K groups compared to WT-controls, with no effect of senolytic treatment.

Next, we examined the impact of senolytic treatment on microglia, given their role in ALS progression and sensitivity to senolytics (Drake et al., 2024; Quek et al., 2022; Trias et al., 2019; Vahsen et al., 2023; Wang et al., 2023). In motor cortex layer V (Fig. 7A–B), microglial number (IBA1+ cells) was elevated in TDP-43-vehicle mice compared to WT-controls but reduced to WT-control levels with senolytic treatment. In addition, circularity, a measure of microglial activation (Green et al., 2022; Leyh et al., 2021; Migliarini et al., 2021), was reduced in TDP-43-vehicle mice compared to WT-controls, with senolytic-treated mice comparable to WT-controls. Signal intensities for TDP-43 and P21 were elevated in TDP-43-vehicle mice compared to WT-controls, and both were significantly reduced by senolytics (Fig. 7C–D).

In the spinal cord ventral horn, microglial counts were increased in TDP-43-vehicle mice compared to WT-controls and reduced by senolytics to levels comparable to WT-controls (Fig. S6A–B). However, circularity was unchanged across all groups. Signal intensities for TDP-43 and P21 were elevated in TDP-43-vehicle mice compared to WT-controls, with no difference after senolytic treatment (Fig. S6C–D).

Together, these data show that senolytics did not affect neuronal senescence markers but reduced microglial number and activation, with TDP-43 and P21 signal reduced more strongly in cortex than spinal cord.

4. Discussion

In this study we identified cellular senescence in the nervous system as an early disease-associated process that emerged with, and may contribute to, progressive motor decline in the TDP-43^Q331K mouse model of ALS. Specifically, cortical senescence markers emerged alongside impairments in electrophysiological measures of corticomuscular excitability and persisted throughout the disease course (Fig. 1), whereas spinal cord senescence also coincided with overt neuromuscular deficits but became less detectable at advanced stages. Because senescent cells can persist and promote dysfunction in surrounding cells through the SASP (Dashtmian et al., 2024; Maximova et al., 2021; Pandya and Patani, 2020; Vazquez-Villaseñor et al., 2020), we hypothesized that reducing senescent burden could represent a potential strategy to improve the cellular environment supporting vulnerable neurons. Accordingly, we targeted cellular senescence with D&Q, a senolytic combination that targets survival pathways used by senescent cells and that has shown beneficial effects in other neurodegenerative disease models (Kirkland and Tchkonia, 2020). We show that senolytic treatment improved motor behavior and neuromuscular excitability in TDP-43^Q331K mice (Fig. 2), with the most pronounced effects observed in the cortex, including improved corticomuscular excitability alongside cortical reductions in neuronal (Fig. 4) and microglial TDP-43 burden (Fig. 7), and selective decreases in cortical, but not spinal, senescent microglia (Fig. 7 and Fig. S6). Collectively, these findings establish cellular senescence as a disease-relevant feature of this ALS model, that when targeted, can mitigate motor dysfunction.

D&Q-treated TDP-43^Q331K mice exhibited motor behavior improvements, with transient maintenance in grip strength and sustained improvements in motor performance measured by rotarod (Fig. 2). These divergent outcomes may reflect the selective vulnerability of motor neuron subtypes in ALS (Wier et al., 2019), whereby fast-twitch motor units, which contribute disproportionately to grip strength (Sadaki et al., 2023), tend to degenerate earlier and more severely than slow-twitch units (Nijssen et al., 2017), and may therefore be less amenable to senolytic rescue. Additionally, neuromuscular excitability, motor unit numbers, and muscle contractility all showed improvements following senolytic treatment. Critically, these gains were accompanied by stabilization of plasma NfL levels (Fig. 3), a clinically validated biomarker of ALS and therapeutic efficacy (Meyer et al., 2024; Meyer et al., 2023; Miller et al., 2025; Wiesenfarth et al., 2024), suggesting reduced axonal damage following treatment. Notably, improvements in CMAP and MUNE occurred despite ChAT+ motor neuron counts remaining reduced in both TDP-43^Q331K groups compared to WT-controls (Fig. 4D), suggesting that senolytics improved the function of surviving motor units rather than rescuing motor neuron cell bodies. Further, SMUP was elevated in senolytic-treated mice (Fig. S2B), consistent with enlargement of surviving motor units through collateral reinnervation of denervated muscle fibers, a compensatory process well described in ALS (Dantes and McComas, 1991; Schaefer et al., 2005). Reduced axonal injury, reflected by lower plasma NfL in senolytic-treated mice, may support this capacity for reinnervation and improved function of surviving motor units. A limitation of the present study is that NMJ morphology was not directly assessed. While senolytic-treated TDP-43^Q331K mice exhibited improvements in CMAP and MUNE (Fig. 2) and increased SMUP (Fig. S2B), consistent with improved motor unit connectivity and collateral reinnervation (Dantes and McComas, 1991; Schaefer et al., 2005), these electrophysiological measures cannot determine whether treatment reduced NMJ denervation or restored NMJ structure. Future studies combining longitudinal electrophysiology with direct assessment of NMJ innervation and morphology will be important to define the structural basis of these functional improvements.

Our results also suggest that D&Q has preferential cortical effects, aligning with growing evidence that the cortex is an early site of ALS pathogenesis, where deficits often precede spinal and neuromuscular impairments (Dyer et al., 2021; Haidar et al., 2025; Menon et al., 2020; Menon et al., 2015; Reale et al., 2023). We show that cortical impairments represented the most severe deficit in TDP-43^Q331K mice, reflected by marked reductions in corticomuscular excitability and layer V CTIP2+ neuron number (Figs. 2 and 4) (Viteri et al., 2025b). While therapeutic strategies targeting cortical dysfunction in ALS are limited, with treatments such as riluzole producing only modest improvements (Vucic et al., 2013), D&Q-treated mice exhibited a robust improvement of cortical excitability, maintenance of CTIP2+ neuron numbers, and reductions in TDP-43 pathology. Consistent with these cortical effects, senolytics also had a greater effect on cortical senescence, with several transcripts normalized toward control levels (Fig. 5) and some markers showing reduced signal intensity for cell-cycle arrest and anti-apoptotic markers in layer V (Fig. S5). A SASP cytokine linked to ALS progression (Meissner et al., 2010), Il1b (Italiani et al., 2014), increased following treatment in both cortex and spinal cord - a context-dependent effect previously reported with senolytics (Bogdanova et al., 2024) that likely does not reflect global inflammation worsening, given concurrent reductions in other senescence markers. Importantly, a limitation of the present study is that a WT-senolytic group was not included, as the intervention experiment was designed to test the effects of D&Q in TDP-43^Q331K mice rather than as a full genotype × treatment factorial study. Accordingly, we cannot determine whether the molecular changes observed following D&Q, particularly in the dPCR analyses, are specific to the disease state or also occur in WT mice. Future studies incorporating WT-senolytic controls will be important for distinguishing disease-specific therapeutic effects from baseline pharmacological effects of D&Q.

After senolytic treatment, cortical microglia also showed reduced P21 and TDP-43 signal intensity, decreased cell number, and a shift away from an activated, amoeboid-like morphology (Fig. 7) (Davis et al., 2017; Green et al., 2022; Migliarini et al., 2021; Quek et al., 2022; Spiller et al., 2018). Combined with evidence implicating microglia senescence in ALS and neurodegeneration (Fang et al., 2026a; Quek et al., 2022; Trias et al., 2019; Vahsen et al., 2023), our findings support a cortical, microglial-mediated model in which senolytics reduce senescent microglia, limit their spread of senescence and TDP-43 pathology (Jo et al., 2020), and improve downstream motor neuron health and motor system function. This preferential cortical effect may also relate to baseline regional differences in microglial activation: human postmortem studies show substantially greater microglial activation in the spinal cord than the motor cortex in ALS (Ashford et al., 2025). This is consistent with evidence that microglia differ by CNS region in baseline gene expression and in how their activation state changes with age (Grabert et al., 2016). Thus, considering these regional differences and that senolytics act through specific survival pathways that can vary across senescent cell populations (Zhu et al., 2016a; Zhu et al., 2015), we speculate that differences in microglial activation and molecular state may contribute to differential sensitivity to D&Q, potentially explaining the stronger normalization of senescence markers observed in the cortex than in the spinal cord. However, this remains speculative, and future studies will be needed to directly compare senescence-associated and pro-survival pathways in cortical and spinal microglia in ALS and determine whether these regional molecular differences influence responsiveness to senolytic treatment.

Importantly, senolytics do not indiscriminately eliminate all cells expressing senescence-associated markers. Rather, senolytic drugs can act on specific survival pathways that senescent cells depend on, and these pathways can vary by cell type (Zhu et al., 2016b; Zhu et al., 2015). Thus, two findings support microglia, rather than neurons, as the primary mediators of this effect. First, senescence-associated features (elevated P21 and H2AX signal intensity, as well as the percentage of P21+ and H2AX+ cells) remained elevated in layer V and ventral horn neurons despite treatment (Fig. 6) indicating that D&Q did not reduce these senescence-associated features in neurons, despite its effects on the surrounding microglial environment. In support of this, we observed preserved CTIP2+ neuron counts in the senolytic-treated group (Fig. 4A), suggesting that CTIP2+ neuron counts were preserved without clearing the neurons’ own senescent state. Thus, a given senolytic drug may be clearing one senescent cell type, such as microglia, while sparing another, such as CTIP2+ neurons. Second, although pTDP-43, the phosphorylated and pathologically aggregated form of TDP-43 (Neumann et al., 2009; Suk and Rousseaux, 2020), was reduced in cortical and spinal neurons after treatment (Fig. S3), the pTDP-43-to-total-TDP-43 ratio and cytosolic pTDP-43 remained elevated in both regions relative to WT-controls, indicating persistent phosphorylation and mislocalization consistent with ongoing gain-of-toxicity. This dissociation suggests that senolytics may have not directly acted on neurons or TDP-43 pathology itself, but rather that reduced TDP-43 burden in neurons was a downstream consequence of clearing senescent, TDP-43-laden microglia.

Other studies have also attempted to reduce cellular senescence in ALS models with limited effects. In the hSOD1-G93A ALS mouse model, NKG2D CAR-T cells reduced senescence burden and suppressed SASP in the brain and spinal cord after symptom onset. However, the treatment did not significantly rescue motor function, though a trend toward improvement was observed, potentially due to the small sample size of the study (Fang et al., 2026b). In another study, navitoclax, which directly targets Bcl-2 (Zhu et al., 2016b), failed to reduce senescence markers in vivo and in vitro or alter disease course in the hSOD1-G93A ALS mouse model, whereas D&Q reduced senescence markers in vitro (Torres et al., 2022), indicating that senolytic efficacy in ALS may be drug-specific. Meanwhile, D&Q has been shown to cause demyelination of the sub-domain of the corpus callosum in both young and aged wild-type mice (Lombardo et al., 2026). To test whether this occurred in our TDP-43^Q331K mice, we analyzed cranial and cervical MEP latencies, which would be expected to be prolonged in the context of demyelination (Pukos et al., 2023). These latencies did not differ between senolytic-treated and TDP-43-vehicle mice (Fig. S7), suggesting that D&Q did not cause demyelination in the motor pathways of TDP-43^Q331K mice.

In summary, we have identified cellular senescence as a disease-relevant and modifiable feature of ALS in the TDP-43^Q331K mouse model, with its emergence coinciding with cortico- and neuromuscular deficits, supporting the view that biological aging processes intersect with ALS pathophysiology in ways that shape disease course rather than merely reflecting advancing pathology. Senolytic intervention with D&Q reduced key senescence markers and senescent cell burden, likely of microglial origin, coinciding with improved motor function particularly within cortical circuits. Given the growing evidence of senolytic efficacy in human studies of other age-related diseases (Dashtmian et al., 2024; Gonzales et al., 2023; Gonzales et al., 2022; Hickson et al., 2019; Justice et al., 2019), these findings provide rationale for further evaluation of senolytic strategies in ALS.

Supplementary Material

NIHMS2214721-supplement-1.docx^{(4.9MB, docx)}

NIHMS2214721-supplement-2.docx^{(121.3KB, docx)}

NIHMS2214721-supplement-3.docx^{(1.5MB, docx)}

Sources of funding

JAV was supported by the University of Missouri Spinal Cord Injuries/Disease Research Program (2024) and the American Academy of Neurology 2025 Clinical Research Training Scholarship in ALS. WDA was supported by NIA/NIH R01AG078129 and R01AG067758. YZ was supported by R01AG087387, R21AG087361, and HF-GRO-23–1,199,262.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.nbd.2026.107610.

Footnotes

Declaration of competing interest

The authors declare no conflicts of interest.

Declaration of generative AI and AI-assisted technologies in the manuscript preparation process

During the preparation of this work, the author(s) used Claude Sonnet 5 (Anthropic) to assist in generating ImageJ macros for immunofluorescence image analysis, under continuous author supervision, and to assist in generating the code used to produce the trajectory plot in Fig. 1 and the senescence heatmap matrix in Fig. 5. The author(s) reviewed and edited the output as needed and take full responsibility for the content of the published article.

Animal subject

This study was conducted in accordance with the ARRIVE (Animal Research: Reporting of In Vivo Experiments) guidelines.

This study was approved by the Institutional Animal Care and Use Committee (IACUC) at the University of Missouri–Columbia (Approval No. protocol #39905).

Data availability

Data will be made available on request.

References

Aguado J, Amarilla AA, Taherian Fard A, Albornoz EA, Tyshkovskiy A, Schwabenland M, Chaggar HK, Modhiran N, Gómez-Inclán C, Javed I, Baradar AA, Liang B, Peng L, Dharmaratne M, Pietrogrande G, Padmanabhan P, Freney ME, Parry R, Sng JDJ, Isaacs A, Khromykh AA, Valenzuela Nieto G, Rojas-Fernandez A, Davis TP, Prinz M, Bengsch B, Gladyshev VN, Woodruff TM, Mar JC, Watterson D, Wolvetang EJ, 2023. Senolytic therapy alleviates physiological human brain aging and COVID-19 neuropathology. Nat. Aging 3, 1561–1575. 10.1038/s43587-023-00519-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
Arnold ES, Ling SC, Huelga SC, Lagier-Tourenne C, Polymenidou M, Ditsworth D, Kordasiewicz HB, McAlonis-Downes M, Platoshyn O, Parone PA, Da Cruz S, Clutario KM, Swing D, Tessarollo L, Marsala M, Shaw CE, Yeo GW, Cleveland DW, 2013. ALS-linked TDP-43 mutations produce aberrant RNA splicing and adult-onset motor neuron disease without aggregation or loss of nuclear TDP-43. Proc. Natl. Acad. Sci. U. S. A. 110. 10.1073/pnas.1222809110. [DOI] [PMC free article] [PubMed] [Google Scholar]
Arnold WD, Sheth KA, Wier CG, Kissel JT, Burghes AH, Kolb SJ, 2015. Electrophysiological motor unit number estimation (MUNE) measuring compound muscle action potential (CMAP) in mouse hindlimb muscles. J. Vis. Exp. 1–8. 10.3791/52899. [DOI] [PMC free article] [PubMed] [Google Scholar]
Ashford BA, Simpson JE, Dawson C, Boche D, Cooper-Knock J, Heath PR, Fillingham D, Appleby-Mallinder C, Wei W, Dunning M, Highley JR, 2025. Human amyotrophic lateral sclerosis/motor neuron disease: the disease-associated microglial pathway is upregulated while APOE genotype governs risk and survival. Brain Pathol. 35, 1–21. 10.1111/bpa.70019. [DOI] [PMC free article] [PubMed] [Google Scholar]
Bogdanova DA, Kolosova ED, Pukhalskaia TV, Levchuk KA, Demidov ON, Belotserkovskaya EV, 2024. The differential effect of Senolytics on SASP cytokine secretion and regulation of EMT by CAFs. Int. J. Mol. Sci. 25. 10.3390/ijms25074031. [DOI] [PMC free article] [PubMed] [Google Scholar]
Bonefeld BE, Elfving B, Wegener G, 2008. Reference genes for normalization: a study of rat brain tissue. Synapse 62, 302–309. 10.1002/syn.20496. [DOI] [PubMed] [Google Scholar]
Bussian TJ, Aziz A, Meyer CF, Swenson BL, van Deursen JM, Baker DJ, 2018. Clearance of senescent glial cells prevents tau-dependent pathology and cognitive decline. Nature 562, 578–582. 10.1038/s41586-018-0543-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
Cánovas J, Berndt FA, Sepúlveda H, Aguilar R, Veloso FA, Montecino M, Oliva C, Maass JC, Sierralta J, Kukuljan M, 2015. The specification of cortical subcerebral projection neurons depends on the direct repression of TBR1 by CTIP1/BCL11a. J. Neurosci. 35, 7552–7564. 10.1523/JNEUROSCI.0169-15.2015. [DOI] [PMC free article] [PubMed] [Google Scholar]
Castoldi V, Rossi E, Marenna S, Comi G, Leocani L, 2022. Improving reproducibility of motor evoked potentials in mice. J. Neurosci. Methods 367, 109444. 10.1016/j.jneumeth.2021.109444. [DOI] [PubMed] [Google Scholar]
Červenák Z, Červenák F, Adamičková A, Šalingová B, Gažová A, Kyselovič J, 2022. Normalization strategy for selection of reference genes for RT-qPCR analysis in left ventricles of failing human hearts. BMC Cardiovasc. Disord. 22, 1–12. 10.1186/s12872-022-02614-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
Chinta SJ, Woods G, Demaria M, Rane A, Zou Y, McQuade A, Rajagopalan S, Limbad C, Madden DT, Campisi J, Andersen JK, 2018. Cellular senescence is induced by the environmental neurotoxin paraquat and contributes to neuropathology linked to Parkinson’s disease. Cell Rep. 22, 930–940. 10.1016/j.celrep.2017.12.092. [DOI] [PMC free article] [PubMed] [Google Scholar]
Cuollo L, Antonangeli F, Santoni A, Soriani A, 2020. The senescence-associated secretory phenotype and age-related diseases. Biology (Basel) 9, 1–16. 10.3390/biology9120485. [DOI] [PMC free article] [PubMed] [Google Scholar]
Dantes M, McComas A, 1991. The extent and time course of motoneuron involvement in amyotrophic lateral sclerosis. Muscle Nerve 416–421. 10.1002/mus.880140506. [DOI] [PubMed] [Google Scholar]
Das MM, Svendsen CN, 2015. Astrocytes show reduced support of motor neurons with aging that is accelerated in a rodent model of ALS. Neurobiol. Aging 36, 1130–1139. 10.1016/j.neurobiolaging.2014.09.020. [DOI] [PubMed] [Google Scholar]
Das S, Ramanan N, 2023. Region-specific heterogeneity in neuronal nuclear morphology in young, aged and in Alzheimer’s disease mouse brains. Front. Cell Dev. Biol. 11, 1–12. 10.3389/fcell.2023.1032504. [DOI] [PMC free article] [PubMed] [Google Scholar]
Dashtmian AR, Darvishi FB, Arnold WD, 2024. Chronological and biological aging in amyotrophic lateral sclerosis and the potential of Senolytic therapies. Cells 13. 10.3390/cells13110928. [DOI] [PMC free article] [PubMed] [Google Scholar]
Davis BM, Salinas-Navarro M, Cordeiro MF, Moons L, de Groef L, 2017. Characterizing microglia activation: a spatial statistics approach to maximize information extraction. Sci. Rep. 7, 1–12. 10.1038/s41598-017-01747-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
Drake SS, Zaman A, Gianfelice C, Hua EML, Heale K, Afanasiev E, Klement W, Stratton JA, Prat A, Zandee S, Fournier AE, 2024. Senolytic treatment diminishes microglia and decreases severity of experimental autoimmune encephalomyelitis. J. Neuroinflammation 21. 10.1186/s12974-024-03278-2, 2024.02.05.579017. [DOI] [PMC free article] [PubMed] [Google Scholar]
Dyer MS, Reale LA, Lewis KE, Walker AK, Dickson TC, Woodhouse A, Blizzard CA, 2021. Mislocalisation of TDP-43 to the cytoplasm causes cortical hyperexcitability and reduced excitatory neurotransmission in the motor cortex. J. Neurochem. 157, 1300–1315. 10.1111/jnc.15214. [DOI] [PubMed] [Google Scholar]
Elliott ML, Caspi A, Houts RM, Ambler A, Broadbent JM, Hancox RJ, Harrington HL, Hogan S, Keenan R, Knodt A, Leung JH, Melzer TR, Purdy SC, Ramrakha S, Richmond-Rakerd LS, Righarts A, Sugden K, Thomson WM, Thorne PR, Williams BS, Wilson G, Hariri AR, Poulton R, Moffitt TE, 2021. Disparities in the pace of biological aging among midlife adults of the same chronological age have implications for future frailty risk and policy. Nat. Aging 1, 295–308. 10.1038/s43587-021-00044-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
Fang C, Jin J, Shi W, Xu X, Li H, Duan Q, Yu X, Wu S, Lu T, Hu F, Qin X, Huang J, Sun D, Zhang M, He S, Dang J, He Q, Zhang Q, Gan S, 2026a. Accelerated brain aging in amyotrophic lateral sclerosis and its prognostic associations: a cohort study. BMC Med. 10.1186/s12916-026-04631-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
Fang L, Bai Z, Yang D, Sun B, Zhao X, Deng J, 2026b. Elimination of senescent cells fails to attenuate disease progression in an ALS mouse model. Neurol. Sci. 47, 1–13. 10.1007/s10072-026-09023-2. [DOI] [PubMed] [Google Scholar]
Golub VM, Brewer J, Wu X, Kuruba R, Short J, Manchi M, Swonke M, Younus I, Reddy DS, 2015. Neurostereology protocol for unbiased quantification of neuronal injury and neurodegeneration. Front. Aging Neurosci. 7, 1–14. 10.3389/fnagi.2015.00196. [DOI] [PMC free article] [PubMed] [Google Scholar]
Gonzales MM, Garbarino VR, Pollet E, Palavicini JP, Kellogg DL, Kraig E, Orr ME, 2022. Biological aging processes underlying cognitive decline and neurodegenerative disease. J. Clin. Invest. 132. 10.1172/JCI158453. [DOI] [PMC free article] [PubMed] [Google Scholar]
Gonzales MM, Garbarino VR, Kautz TF, Palavicini JP, Lopez-Cruzan M, Dehkordi SK, Mathews JJ, Zare H, Xu P, Zhang B, Franklin C, Habes M, Craft S, Petersen RC, Tchkonia T, Kirkland JL, Salardini A, Seshadri S, Musi N, Orr ME, 2023. Senolytic therapy in mild Alzheimer’s disease: a phase 1 feasibility trial. Nat. Med. 29, 2481–2488. 10.1038/s41591-023-02543-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
Grabert K, Michoel T, Karavolos MH, Clohisey S, Kenneth Baillie J, Stevens MP, Freeman TC, Summers KM, McColl BW, 2016. Microglial brain regiona ˆ ‘dependent diversity and selective regional sensitivities to aging. Nat. Neurosci. 19, 504–516. 10.1038/nn.4222. [DOI] [PMC free article] [PubMed] [Google Scholar]
Green TRF, Murphy SM, Rowe RK, 2022. Comparisons of quantitative approaches for assessing microglial morphology reveal inconsistencies, ecological fallacy, and a need for standardization. Sci. Rep. 12, 1–13. 10.1038/s41598-022-23091-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
Grimsley CA, Sanchez JT, Sivaramakrishnan S, 2013. Diversity of layer 5 projection neurons in the mouse motor cortex. Front. Neural Circuits 7, 1–18. 10.3389/fncir.2013.00174. [DOI] [Google Scholar]
Haidar M, Viden A, Daniel C, Cuic B, Wang T, Rosier M, Tomas D, Mills SA, Govier-Cole A, Djouma E, Perera ND, Luikinga S, Rytova V, Barton SK, Gonsalvez DG, Palmer LM, McLean C, Kiernan MC, Vucic S, Turner BJ, 2025. Cortical hyperexcitability drives dying forward amyotrophic lateral sclerosis symptoms and pathology in mice. Prog. Neurobiol. 252, 102809. 10.1016/j.pneurobio.2025.102809. [DOI] [PubMed] [Google Scholar]
Hasegawa M, Arai T, Nonaka T, Kametani F, Yoshida M, Hashizume Y, Beach TG, Buratti E, Baralle F, Morita M, Nakano I, Oda T, Tsuchiya K, Akiyama H, 2008. Phosphorylated TDP-43 in frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Ann. Neurol. 64, 60–70. 10.1002/ana.21425. [DOI] [PMC free article] [PubMed] [Google Scholar]
Herdy JR, Traxler L, Agarwal RK, Karbacher L, Schlachetzki JCM, Boehnke L, Zangwill D, Galasko D, Glass CK, Mertens J, Gage FH, 2022. Increased post-mitotic senescence in aged human neurons is a pathological feature of Alzheimer’s disease. Cell Stem Cell 29, 1637–1652.e6. 10.1016/j.stem.2022.11.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
Hickson LTJ, Langhi Prata LGP, Bobart SA, Evans TK, Giorgadze N, Hashmi SK, Herrmann SM, Jensen MD, Jia Q, Jordan KL, Kellogg TA, Khosla S, Koerber DM, Lagnado AB, Lawson DK, LeBrasseur NK, Lerman LO, McDonald KM, McKenzie TJ, Passos JF, Pignolo RJ, Pirtskhalava T, Saadiq IM, Schaefer KK, Textor SC, Victorelli SG, Volkman TL, Xue A, Wentworth MA, Wissler Gerdes EO, Zhu Y, Tchkonia T, Kirkland JL, 2019. Senolytics decrease senescent cells in humans: preliminary report from a clinical trial of Dasatinib plus quercetin in individuals with diabetic kidney disease. EBioMedicine 47, 446–456. 10.1016/j.ebiom.2019.08.069. [DOI] [PMC free article] [PubMed] [Google Scholar]
Horvath S, Langfelder P, Kwak S, Aaronson J, Rosinski J, Vogt TF, Eszes M, Faull RLM, Curtis MA, Waldvogel HJ, Choi OW, Tung S, Vinters HV, Coppola G, Yang XW, 2016. Huntington’s disease accelerates epigenetic aging of human brain and disrupts DNA methylation levels. Aging 8, 1485–1512. 10.18632/aging.101005. [DOI] [PMC free article] [PubMed] [Google Scholar]
Islam MT, Tuday E, Allen S, Kim J, Trott DW, Holland WL, Donato AJ, Lesniewski LA, 2023. Senolytic drugs, dasatinib and quercetin, attenuate adipose tissue inflammation, and ameliorate metabolic function in old age. Aging Cell 22, 1–15. 10.1111/acel.13767. [DOI] [PMC free article] [PubMed] [Google Scholar]
Italiani P, Carlesi C, Giungato P, Puxeddu I, Borroni B, Bossù P, Migliorini P, Siciliano G, Boraschi D, 2014. Evaluating the levels of interleukin-1 family cytokines in sporadic amyotrophic lateral sclerosis. J. Neuroinflammation 11, 1–7. 10.1186/1742-2094-11-94. [DOI] [PMC free article] [PubMed] [Google Scholar]
Jo M, Lee S, Jeon YM, Kim S, Kwon Y, Kim HJ, 2020. The role of TDP-43 propagation in neurodegenerative diseases: integrating insights from clinical and experimental studies. Exp. Mol. Med. 52, 1652–1662. 10.1038/s12276-020-00513-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
Jurk D, Wang C, Miwa S, Maddick M, Korolchuk V, Tsolou A, Gonos ES, Thrasivoulou C, Jill Saffrey M, Cameron K, von Zglinicki T, 2012. Postmitotic neurons develop a p21-dependent senescence-like phenotype driven by a DNA damage response. Aging Cell 11, 996–1004. 10.1111/j.1474-9726.2012.00870.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
Justice JN, Nambiar AM, Tchkonia T, LeBrasseur NK, Pascual R, Hashmi SK, Prata L, Masternak MM, Kritchevsky SB, Musi N, Kirkland JL, 2019. Senolytics in idiopathic pulmonary fibrosis: results from a first-in-human, open-label, pilot study. EBioMedicine 40, 554–563. 10.1016/j.ebiom.2018.12.052. [DOI] [PMC free article] [PubMed] [Google Scholar]
Kelley JB, Paschal BM, 2019. Fluorescence-based quantification of nucleocytoplasmic transport. Methods 157, 106–114. 10.1016/j.ymeth.2018.11.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
Kerr NR, Dashtmian AR, Darvishi FB, Brennan CD, Ayyagari SN, Moore PJ, Viteri JA, Wang M, Rich MM, Clark BC, Arnold WD, 2025. 5-HT2C agonism as a neurotherapeutic for sarcopenia: preclinical proof of concept. Geroscience 47, 4075–4092. 10.1007/s11357-025-01519-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
Kirkland JL, Tchkonia T, 2020. Senolytic drugs: from discovery to translation. J. Intern. Med. 288, 518–536. 10.1111/joim.13141. [DOI] [PMC free article] [PubMed] [Google Scholar]
Leyh J, Paeschke S, Mages B, Michalski D, Nowicki M, Bechmann I, Winter K, 2021. Classification of microglial morphological phenotypes using machine learning. Front. Cell. Neurosci. 15, 1–17. 10.3389/fncel.2021.701673. [DOI] [PMC free article] [PubMed] [Google Scholar]
Liu B, Liu J, Shi JS, 2020. SAMP8 mice as a model of age-related cognition decline with underlying mechanisms in Alzheimer’s disease. J. Alzheimer’s Dis 75, 385–395. 10.3233/JAD-2000063. [DOI] [PubMed] [Google Scholar]
Lombardo ER, Pijewski RS, Lustig JT, Dhari Z, Lahiri A, Papile LE, Lavoie ER, Scanlon VM, Bartley JM, Crocker SJ, 2026. Senolytic treatment induces oligodendrocyte dysfunction and demyelination in the corpus callosum. Proc. Natl. Acad. Sci. U. S. A. 123, 1–10. 10.1073/pnas.2524897123. [DOI] [PMC free article] [PubMed] [Google Scholar]
Masrori P, Van Damme P, 2020. Amyotrophic lateral sclerosis: a clinical review. Eur. J. Neurol. 27, 1918–1929. 10.1111/ene.14393. [DOI] [PMC free article] [PubMed] [Google Scholar]
Maximova A, Werry EL, Kassiou M, 2021. Senolytics: a novel strategy for neuroprotection in als? Int. J. Mol. Sci. 22, 1–15. 10.3390/ijms222112078. [DOI] [PMC free article] [PubMed] [Google Scholar]
Maxwell N, Castro RW, Sutherland NM, Vaughan KL, Szarowicz MD, de Cabo R, Mattison JA, Valdez G, 2018. α-Motor neurons are spared from aging while their synaptic inputs degenerate in monkeys and mice. Aging Cell 17. 10.1111/acel.12726. [DOI] [PMC free article] [PubMed] [Google Scholar]
Meissner F, Molawi K, Zychlinsky A, 2010. Mutant superoxide dismutase 1-induced IL-1β accelerates ALS pathogenesis. Proc. Natl. Acad. Sci. U. S. A. 107, 13046–13050. 10.1073/pnas.1002396107. [DOI] [PMC free article] [PubMed] [Google Scholar]
Menon P, Kiernan MC, Vucic S, 2015. Cortical hyperexcitability precedes lower motor neuron dysfunction in ALS. Clin. Neurophysiol. 126, 803–809. 10.1016/j.clinph.2014.04.023. [DOI] [PubMed] [Google Scholar]
Menon P, Higashihara M, van den Bos M, Geevasinga N, Kiernan MC, Vucic S, 2020. Cortical hyperexcitability evolves with disease progression in ALS. Ann. Clin. Transl. Neurol. 7, 733–741. 10.1002/acn3.51039. [DOI] [PMC free article] [PubMed] [Google Scholar]
Meyer T, Schumann P, Weydt P, Petri S, Koc Y, Spittel S, Bernsen S, Günther R, Weishaupt JH, Dreger M, Kolzarek F, Kettemann D, Norden J, Boentert M, Vidovic M, Meisel C, Münch C, Maier A, Körtvélyessy P, 2023. Neurofilament light-chain response during therapy with antisense oligonucleotide tofersen in SOD1-related ALS: treatment experience in clinical practice. Muscle Nerve 67, 515–521. 10.1002/mus.27818. [DOI] [PubMed] [Google Scholar]
Meyer T, Dreger M, Grehl T, Weyen U, Kettemann D, Weydt P, Günther R, Lingor P, Petri S, Koch JC, Großkreutz J, Rödiger A, Baum P, Hermann A, Prudlo J, Boentert M, Weishaupt JH, Löscher WN, Dorst J, Koc Y, Bernsen S, Cordts I, Vidovic M, Steinbach R, Metelmann M, Kleinveld VE, Norden J, Ludolph A, Walter B, Schumann P, Münch C, Körtvélyessy P, Maier A, 2024. Serum neurofilament light chain in distinct phenotypes of amyotrophic lateral sclerosis: a longitudinal, multicenter study. Eur. J. Neurol. 31, 1–13. 10.1111/ene.16379. [DOI] [PMC free article] [PubMed] [Google Scholar]
Migliarini S, Scaricamazza S, Valle C, Ferri A, Pasqualetti M, Ferraro E, 2021. Microglia morphological changes in the motor cortex of hsod1g93a transgenic als mice. Brain Sci. 11. 10.3390/brainsci11060807. [DOI] [PMC free article] [PubMed] [Google Scholar]
Miller TM, Cudkowicz ME, Shaw PJ, Genge A, Sobue G, Bucelli RC, Chiò A, Van Damme P, Ludolph AC, Glass JD, Andrews JA, Babu S, Benatar M, McDermott CJ, Salachas F, Bruneteau G, Al-Chalabi A, Amorin M, Nestorov I, Graham D, Lin L, Sun P, McNeill M, Malek S, Inra J, Garafalo S, Fradette S, 2025. Long-term Tofersen in SOD1 amyotrophic lateral sclerosis. JAMA Neurol. 02142, 1–11. 10.1001/jamaneurol.2025.4946. [DOI] [PMC free article] [PubMed] [Google Scholar]
Mitchell JC, Constable R, So E, Vance C, Scotter E, Glover L, Hortobagyi T, Arnold ES, Ling SC, McAlonis M, Da Cruz S, Polymenidou M, Tessarolo L, Cleveland DW, Shaw CE, 2015. Wild type human TDP-43 potentiates ALS-linked mutant TDP-43 driven progressive motor and cortical neuron degeneration with pathological features of ALS. Acta Neuropathol. Commun. 3, 36. 10.1186/s40478-015-0212-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
Mitra J, Kodavati M, Dharmalingam P, Guerrero EN, Rao KS, Garruto RM, Hegde ML, 2025. Endogenous TDP-43 mislocalization in a novel knock-in mouse model reveals DNA repair impairment, inflammation, and neuronal senescence. Acta Neuropathol. Commun. 13. 10.1186/s40478-025-01962-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
Mullen RJ, Buck CR, Smith AM, 1992. NeuN, a neuronal specific nuclear protein in vertebrates. Development 116, 201–211. 10.1242/dev.116.1.201. [DOI] [PubMed] [Google Scholar]
Muñoz-Castañeda R, Zingg B, Matho KS, Chen X, Wang Q, Foster NN, Li A, Narasimhan A, Hirokawa KE, Huo B, Bannerjee S, Korobkova L, Park CS, Park YG, Bienkowski MS, Chon U, Wheeler DW, Li X, Wang Y, Naeemi M, Xie P, Liu L, Kelly K, An X, Attili SM, Bowman I, Bludova A, Cetin A, Ding L, Drewes R, D’Orazi F, Elowsky C, Fischer S, Galbavy W, Gao L, Gillis J, Groblewski PA, Gou L, Hahn JD, Hatfield JT, Hintiryan H, Huang JJ, Kondo H, Kuang X, Lesnar P, Li X, Li Y, Lin M, Lo D, Mizrachi J, Mok S, Nicovich PR, Palaniswamy R, Palmer J, Qi X, Shen E, Sun YC, Tao HW, Wakemen W, Wang Y, Yao S, Yuan J, Zhan H, Zhu M, Ng L, Zhang LI, Lim BK, Hawrylycz M, Gong H, Gee JC, Kim Y, Chung K, Yang XW, Peng H, Luo Q, Mitra PP, Zador AM, Zeng H, Ascoli GA, Josh Huang Z, Osten P, Harris JA, Dong HW (2021) Cellular anatomy of the mouse primary motor cortex. Nature 598:159–166. doi: 10.1038/s41586-021-03970-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
Neumann M, Kwong LK, Lee EB, Kremmer E, Flatley A, Xu Y, Forman MS, Troost D, Kretzschmar HA, Trojanowski JQ, Lee VMY, 2009. Phosphorylation of S409/410 of TDP-43 is a consistent feature in all sporadic and familial forms of TDP-43 proteinopathies. Acta Neuropathol. 117, 137–149. 10.1007/s00401-008-0477-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
Nijssen J, Comley LH, Hedlund E, 2017. Motor neuron vulnerability and resistance in amyotrophic lateral sclerosis. Acta Neuropathol. 133, 863–885. 10.1007/s00401-017-1708-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
Ogrodnik M, Zhu Y, Langhi LGP, Tchkonia T, Krüger P, Fielder E, Victorelli S, Ruswhandi RA, Giorgadze N, Pirtskhalava T, Podgorni O, Enikolopov G, Johnson KO, Xu M, Inman C, Palmer AK, Schafer M, Weigl M, Ikeno Y, Burns TC, Passos JF, von Zglinicki T, Kirkland JL, Jurk D, 2019. Obesity-induced cellular senescence drives anxiety and impairs neurogenesis. Cell Metab. 29, 1061–1077.e8. 10.1016/j.cmet.2018.12.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
Owendoff G, Ray A, Bobbili P, Clark L, Baumann CW, Clark BC, Arnold WD, 2023. Optimization and construct validity of approaches to preclinical grip strength testing. J. Cachexia. Sarcopenia Muscle 14, 2439–2445. 10.1002/jcsm.13300. [DOI] [PMC free article] [PubMed] [Google Scholar]
Pandya VA, Patani R, 2020. Decoding the relationship between ageing and amyotrophic lateral sclerosis: a cellular perspective. Brain 143, 1057–1072. 10.1093/brain/awz360. [DOI] [PMC free article] [PubMed] [Google Scholar]
Penna I, Vella S, Gigoni A, Russo C, Cancedda R, Pagano A, 2011. Selection of candidate housekeeping genes for normalization in human postmortem brain samples. Int. J. Mol. Sci. 12, 5461–5470. 10.3390/ijms12095461. [DOI] [PMC free article] [PubMed] [Google Scholar]
Pukos N, Marion CM, Arnold WD, Noble BT, Popovich PG, McTigue DM, 2023. Chronic demyelination and myelin repair after spinal cord injury in mice: a potential link for glutamatergic axon activity. Glia 71, 2096–2116. 10.1002/glia.24382. [DOI] [PMC free article] [PubMed] [Google Scholar]
Quek H, Cuní-López C, Stewart R, Colletti T, Notaro A, Nguyen TH, Sun Y, Guo CC, Lupton MK, Roberts TL, Lim YC, Oikari LE, La Bella V, White AR, 2022. ALS monocyte-derived microglia-like cells reveal cytoplasmic TDP-43 accumulation, DNA damage, and cell-specific impairment of phagocytosis associated with disease progression. J. Neuroinflammation 19, 1–21. 10.1186/s12974-022-02421-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
Rad AN, Grillari J, 2024. Current senolytics: mode of action, efficacy and limitations, and their future. Mech. Ageing Dev. 217, 111888. 10.1016/j.mad.2023.111888. [DOI] [PubMed] [Google Scholar]
Reale LA, Dyer MS, Perry SE, Young KM, Dickson TC, Woodhouse A, Blizzard CA, 2023. Pathologically mislocalised TDP-43 in upper motor neurons causes a die-forward spread of ALS-like pathogenic changes throughout the mouse corticomotor system. Prog. Neurobiol. 226, 102449. 10.1016/j.pneurobio.2023.102449. [DOI] [PubMed] [Google Scholar]
Richardson M, Richardson DR, 2024. Pharmacological targeting of senescence with Senolytics as a new therapeutic strategy for neurodegeneration. Mol. Pharmacol. 105, 64–74. 10.1124/molpharm.123.000803. [DOI] [PubMed] [Google Scholar]
Sadaki S, Fujita R, Hayashi T, Nakamura A, Okamura Y, Fuseya S, Hamada M, Warabi E, Kuno A, Ishii A, Muratani M, Okada R, Shiba D, Kudo T, Takeda S, Takahashi S, 2023. Large Maf transcription factor family is a major regulator of fast type IIb myofiber determination. Cell Rep. 42, 112289. 10.1016/j.celrep.2023.112289. [DOI] [PubMed] [Google Scholar]
Schaefer AM, Sanes JR, Lichtman JW, 2005. A compensatory subpopulation of motor neurons in a mouse model of amyotrophic lateral sclerosis. J. Comp. Neurol. 219, 209–219. 10.1002/cne.20620. [DOI] [PubMed] [Google Scholar]
Schneider CA, Rasband WS, Eliceiri KW, 2012. NIH image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675. 10.1038/nmeth.2089. [DOI] [PMC free article] [PubMed] [Google Scholar]
Sheth KA, Iyer CC, Wier CG, Crum AE, Bratasz A, Kolb SJ, Clark BC, Burghes AHM, Arnold WD, 2018. Muscle strength and size are associated with motor unit connectivity in aged mice. Neurobiol. Aging 67, 128–136. 10.1016/j.neurobiolaging.2018.03.016. [DOI] [PMC free article] [PubMed] [Google Scholar]
Spiller KJ, Restrepo CR, Khan T, Dominique MA, Fang TC, Canter RG, Roberts CJ, Miller KR, Ransohoff RM, Trojanowski JQ, Lee VMY, 2018. Microglia-mediated recovery from ALS-relevant motor neuron degeneration in a mouse model of TDP-43 proteinopathy. Nat. Neurosci. 21, 329–340. 10.1038/s41593-018-0083-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
Stetzik L, Mercado G, Smith L, George S, Quansah E, Luda K, Schulz E, Meyerdirk L, Lindquist A, Bergsma A, Jones RG, Brundin L, Henderson MX, Pospisilik JA, Brundin P, 2022. A novel automated morphological analysis of Iba1 + microglia using a deep learning assisted model. Front. Cell. Neurosci. 16, 1–16. 10.3389/fncel.2022.944875. [DOI] [PMC free article] [PubMed] [Google Scholar]
Steward O, Yee KM, Metcalfe M, Willenberg R, Luo J, Azevedo R, Martin-Thompson JH, Gandhi SP, 2021. Rostro-caudal specificity of corticospinal tract projections in mice. Cereb. Cortex 31, 2322–2344. 10.1093/cercor/bhaa338. [DOI] [PMC free article] [PubMed] [Google Scholar]
Suk TR, Rousseaux MWC, 2020. The role of TDP-43 mislocalization in amyotrophic lateral sclerosis. Mol. Neurodegener. 15, 1–16. 10.1186/s13024-020-00397-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
Torres P, Anerillas C, Ramırez-Núñez O, Fernandeź A, Encinas M, Povedano M, Andrés-Benito P, Ferrer I, Ayala V, Pamplona R, Portero-Otın M, 2022. A motor neuron disease mouse model reveals a non-canonical profile of senescence biomarkers. Dis. Model. Mech. 15. 10.1242/DMM.049059. [DOI] [PMC free article] [PubMed] [Google Scholar]
Trias E, Beilby PR, Kovacs M, Ibarburu S, Varela V, Barreto-Núñez R, Bradford SC, Beckman JS, Barbeito L, 2019. Emergence of microglia bearing senescence markers during paralysis progression in a rat model of inherited ALS. Front. Aging Neurosci. 10, 1–14. 10.3389/fnagi.2019.00042. [DOI] [PMC free article] [PubMed] [Google Scholar]
Vahsen BF, Nalluru S, Morgan GR, Farrimond L, Carroll E, Xu Y, Cramb KML, Amein B, Scaber J, Katsikoudi A, Candalija A, Carcolé M, Dafinca R, Isaacs AM, Wade-Martins R, Gray E, Turner MR, Cowley SA, Talbot K, 2023. C9orf72-ALS human iPSC microglia are pro-inflammatory and toxic to co-cultured motor neurons via MMP9. Nat. Commun. 14. 10.1038/s41467-023-41603-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
Vazquez-Villaseñor I, Garwood CJ, Heath PR, Simpson JE, Ince PG, Wharton SB, 2020. Expression of p16 and p21 in the frontal association cortex of ALS/MND brains suggests neuronal cell cycle dysregulation and astrocyte senescence in early stages of the disease. Neuropathol. Appl. Neurobiol. 46, 171–185. 10.1111/nan.12559. [DOI] [PMC free article] [PubMed] [Google Scholar]
Viteri JA, Bueschke N, Santin JM, Arnold WD, 2025a. Age-related increase in the excitability of mouse layer V pyramidal neurons in the primary motor cortex is accompanied by an increased persistent inward current. Geroscience 47, 2199–2222. 10.1007/s11357-024-01405-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
Viteri JA, Kerr NR, Brennan CD, Suleiman LA, Wendt CD, Xu C, An H, Wang M, Nishimune H, Santin JM, Arnold WD, 2025b. Reduced corticomuscular output is associated with intrinsic hypoexcitability and reduced persistent inward currents in motor cortex neurons of TDP-43Q331K ALS mice. Neurobiol. Dis. 218, 107247. 10.1016/j.nbd.2025.107247. [DOI] [PubMed] [Google Scholar]
Vucic S, Lin CSY, Cheah BC, Murray J, Menon P, Krishnan AV, Kiernan MC, 2013. Riluzole exerts central and peripheral modulating effects in amyotrophic lateral sclerosis. Brain 136, 1361–1370. 10.1093/brain/awt085. [DOI] [PubMed] [Google Scholar]
Wang J, Lu Y, Carr C, Dhandapani KM, Brann DW, 2023. Senolytic therapy is neuroprotective and improves functional outcome long-term after traumatic brain injury in mice. Front. Neurosci. 17, 1–15. 10.3389/fnins.2023.1227705. [DOI] [PMC free article] [PubMed] [Google Scholar]
Watkins JA, Alix JJP, Shaw PJ, Mead RJ, 2021. Extensive phenotypic characterisation of a human TDP-43Q331K transgenic mouse model of amyotrophic lateral sclerosis (ALS). Sci. Rep. 11, 1–14. 10.1038/s41598-021-96122-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
Weiler N, Wood L, Yu J, Solla SA, Shepherd GMG, 2008. Top-down laminar organization of the excitatory network in motor cortex. Nat. Neurosci. 11, 360–366. 10.1038/nn2049. [DOI] [PMC free article] [PubMed] [Google Scholar]
West MJ, 2012. Introduction to stereology. Cold Spring Harb. Protoc. 7, 843–851. 10.1101/pdb.top070623. [DOI] [PubMed] [Google Scholar]
Wier CG, Crum AE, Reynolds AB, Iyer CC, Chugh D, Palettas MS, Heilman PL, Kline DM, Arnold WD, Kolb SJ, 2019. Muscle contractility dysfunction precedes loss of motor unit connectivity in SOD1(G93A) mice. Muscle Nerve 59, 254–262. 10.1002/mus.26365. [DOI] [PMC free article] [PubMed] [Google Scholar]
Wiesenfarth M, Dorst J, Brenner D, Elmas Z, Parlak Ö, Uzelac Z, Kandler K, Mayer K, Weiland U, Herrmann C, Schuster J, Freischmidt A, Müller K, Siebert R, Bachhuber F, Simak T, Günther K, Fröhlich E, Knehr A, Regensburger M, German A, Petri S, Grosskreutz J, Klopstock T, Reilich P, Schöberl F, Hagenacker T, Weyen U, Günther R, Vidovic M, Jentsch M, Haarmeier T, Weydt P, Valkadinov I, Hesebeck-Brinckmann J, Conrad J, Weishaupt JH, Schumann P, Körtvélyessy P, Meyer T, Ruf WP, Witzel S, Senel M, Tumani H, Ludolph AC, 2024. Effects of tofersen treatment in patients with SOD1-ALS in a “real-world” setting – a 12-month multicenter cohort study from the German early access program. EClinicalMedicine 69, 102495. 10.1016/j.eclinm.2024.102495. [DOI] [PMC free article] [PubMed] [Google Scholar]
Xu M, Pirtskhalava T, Farr JN, Weigand BM, Palmer AK, Weivoda MM, Inman CL, Ogrodnik MB, Hachfeld CM, Fraser DG, Onken JL, Johnson KO, Verzosa GC, Langhi LGP, Weigl M, Giorgadze N, LeBrasseur NK, Miller JD, Jurk D, Singh RJ, Allison DB, Ejima K, Hubbard GB, Ikeno Y, Cubro H, Garovic VD, Hou X, Weroha SJ, Robbins PD, Niedernhofer LJ, Khosla S, Tchkonia T, Kirkland JL, 2018. Senolytics improve physical function and increase lifespan in old age. Nat. Med. 24, 1246–1256. 10.1038/s41591-018-0092-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
Yildiz O, Schroth J, Tree T, Turner MR, Shaw PJ, Henson SM, Malaspina A, 2023. Senescent-like blood lymphocytes and disease progression in amyotrophic lateral sclerosis. Neurol. Neuroimmunol. Neuroinflamm. 10, 1–13. 10.1212/NXI.0000000000200042. [DOI] [PMC free article] [PubMed] [Google Scholar]
Young K, Morrison H, 2018. Quantifying microglia morphology from photomicrographs of immunohistochemistry prepared tissue using imagej. J. Vis. Exp. 1–9. 10.3791/57648. [DOI] [PMC free article] [PubMed] [Google Scholar]
Zanier ER, Fumagalli S, Perego C, Pischiutta F, De Simoni MG, 2015. Shape descriptors of the “never resting” microglia in three different acute brain injury models in mice. Intensive Care Med. Exp. 3, 1–18. 10.1186/s40635-015-0039-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
Zhang P, Kishimoto Y, Grammatikakis I, Gottimukkala K, Cutler RG, Zhang S, Abdelmohsen K, Bohr VA, Misra Sen J, Gorospe M, Mattson MP, 2019. Senolytic therapy alleviates aβ-associated oligodendrocyte progenitor cell senescence and cognitive deficits in an Alzheimer’s disease model. Nat. Neurosci. 22, 719–728. 10.1038/s41593-019-0372-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
Zhao X, van Praag H, 2020. Steps towards standardized quantification of adult neurogenesis. Nat. Commun. 11, 1–10. 10.1038/s41467-020-18046-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
Zhou C, Hardin EJ, Zimmer TS, Jackvony S, Barnett D, Khobrekar N, Giacomelli E, Studer L, Orr AL, Orr AG, 2025. Neuroimmune signaling mediates astrocytic nucleocytoplasmic disruptions and stress granule formation associated with TDP-43 pathology. Neurobiol. Dis. 211, 106939. 10.1016/j.nbd.2025.106939. [DOI] [PMC free article] [PubMed] [Google Scholar]
Zhu Y, Tchkonia T, Pirtskhalava T, Gower AC, Ding H, Giorgadze N, Palmer AK, Ikeno Y, Hubbard GB, Lenburg M, O’hara SP, Larusso NF, Miller JD, Roos CM, Verzosa GC, Lebrasseur NK, Wren JD, Farr JN, Khosla S, Stout MB, SJ McGowan, Fuhrmann-Stroissnigg H, Gurkar AU, Zhao J, Colangelo D, Dorronsoro A, Ling YY, Barghouthy AS, Navarro DC, Sano T, Robbins PD, Niedernhofer LJ, Kirkland JL, 2015. The achilles’ heel of senescent cells: from transcriptome to senolytic drugs. Aging Cell 14, 644–658. 10.1111/acel.12344. [DOI] [PMC free article] [PubMed] [Google Scholar]
Zhu Y, Tchkonia T, Fuhrmann H, Dai HM, Ling YY, Michael B, Pirtskhalava T, Giorgadze N, Kurt O, Giles CB, Wren JD, Laura J, Robbins PD, Kirkland JL, 2016. Identification of a novel senolytic agent, navitoclax, targeting the Bcl-2 family of anti-apoptotic factors. Aging Cell 428–435. 10.1111/acel.12445. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

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Supplementary Materials

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Data Availability Statement

Data will be made available on request.

[R1] Aguado J, Amarilla AA, Taherian Fard A, Albornoz EA, Tyshkovskiy A, Schwabenland M, Chaggar HK, Modhiran N, Gómez-Inclán C, Javed I, Baradar AA, Liang B, Peng L, Dharmaratne M, Pietrogrande G, Padmanabhan P, Freney ME, Parry R, Sng JDJ, Isaacs A, Khromykh AA, Valenzuela Nieto G, Rojas-Fernandez A, Davis TP, Prinz M, Bengsch B, Gladyshev VN, Woodruff TM, Mar JC, Watterson D, Wolvetang EJ, 2023. Senolytic therapy alleviates physiological human brain aging and COVID-19 neuropathology. Nat. Aging 3, 1561–1575. 10.1038/s43587-023-00519-6. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R2] Arnold ES, Ling SC, Huelga SC, Lagier-Tourenne C, Polymenidou M, Ditsworth D, Kordasiewicz HB, McAlonis-Downes M, Platoshyn O, Parone PA, Da Cruz S, Clutario KM, Swing D, Tessarollo L, Marsala M, Shaw CE, Yeo GW, Cleveland DW, 2013. ALS-linked TDP-43 mutations produce aberrant RNA splicing and adult-onset motor neuron disease without aggregation or loss of nuclear TDP-43. Proc. Natl. Acad. Sci. U. S. A. 110. 10.1073/pnas.1222809110. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R3] Arnold WD, Sheth KA, Wier CG, Kissel JT, Burghes AH, Kolb SJ, 2015. Electrophysiological motor unit number estimation (MUNE) measuring compound muscle action potential (CMAP) in mouse hindlimb muscles. J. Vis. Exp. 1–8. 10.3791/52899. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R4] Ashford BA, Simpson JE, Dawson C, Boche D, Cooper-Knock J, Heath PR, Fillingham D, Appleby-Mallinder C, Wei W, Dunning M, Highley JR, 2025. Human amyotrophic lateral sclerosis/motor neuron disease: the disease-associated microglial pathway is upregulated while APOE genotype governs risk and survival. Brain Pathol. 35, 1–21. 10.1111/bpa.70019. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R5] Bogdanova DA, Kolosova ED, Pukhalskaia TV, Levchuk KA, Demidov ON, Belotserkovskaya EV, 2024. The differential effect of Senolytics on SASP cytokine secretion and regulation of EMT by CAFs. Int. J. Mol. Sci. 25. 10.3390/ijms25074031. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R6] Bonefeld BE, Elfving B, Wegener G, 2008. Reference genes for normalization: a study of rat brain tissue. Synapse 62, 302–309. 10.1002/syn.20496. [DOI] [PubMed] [Google Scholar]

[R7] Bussian TJ, Aziz A, Meyer CF, Swenson BL, van Deursen JM, Baker DJ, 2018. Clearance of senescent glial cells prevents tau-dependent pathology and cognitive decline. Nature 562, 578–582. 10.1038/s41586-018-0543-y. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R8] Cánovas J, Berndt FA, Sepúlveda H, Aguilar R, Veloso FA, Montecino M, Oliva C, Maass JC, Sierralta J, Kukuljan M, 2015. The specification of cortical subcerebral projection neurons depends on the direct repression of TBR1 by CTIP1/BCL11a. J. Neurosci. 35, 7552–7564. 10.1523/JNEUROSCI.0169-15.2015. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R9] Castoldi V, Rossi E, Marenna S, Comi G, Leocani L, 2022. Improving reproducibility of motor evoked potentials in mice. J. Neurosci. Methods 367, 109444. 10.1016/j.jneumeth.2021.109444. [DOI] [PubMed] [Google Scholar]

[R10] Červenák Z, Červenák F, Adamičková A, Šalingová B, Gažová A, Kyselovič J, 2022. Normalization strategy for selection of reference genes for RT-qPCR analysis in left ventricles of failing human hearts. BMC Cardiovasc. Disord. 22, 1–12. 10.1186/s12872-022-02614-9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R11] Chinta SJ, Woods G, Demaria M, Rane A, Zou Y, McQuade A, Rajagopalan S, Limbad C, Madden DT, Campisi J, Andersen JK, 2018. Cellular senescence is induced by the environmental neurotoxin paraquat and contributes to neuropathology linked to Parkinson’s disease. Cell Rep. 22, 930–940. 10.1016/j.celrep.2017.12.092. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R12] Cuollo L, Antonangeli F, Santoni A, Soriani A, 2020. The senescence-associated secretory phenotype and age-related diseases. Biology (Basel) 9, 1–16. 10.3390/biology9120485. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R13] Dantes M, McComas A, 1991. The extent and time course of motoneuron involvement in amyotrophic lateral sclerosis. Muscle Nerve 416–421. 10.1002/mus.880140506. [DOI] [PubMed] [Google Scholar]

[R14] Das MM, Svendsen CN, 2015. Astrocytes show reduced support of motor neurons with aging that is accelerated in a rodent model of ALS. Neurobiol. Aging 36, 1130–1139. 10.1016/j.neurobiolaging.2014.09.020. [DOI] [PubMed] [Google Scholar]

[R15] Das S, Ramanan N, 2023. Region-specific heterogeneity in neuronal nuclear morphology in young, aged and in Alzheimer’s disease mouse brains. Front. Cell Dev. Biol. 11, 1–12. 10.3389/fcell.2023.1032504. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R16] Dashtmian AR, Darvishi FB, Arnold WD, 2024. Chronological and biological aging in amyotrophic lateral sclerosis and the potential of Senolytic therapies. Cells 13. 10.3390/cells13110928. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R17] Davis BM, Salinas-Navarro M, Cordeiro MF, Moons L, de Groef L, 2017. Characterizing microglia activation: a spatial statistics approach to maximize information extraction. Sci. Rep. 7, 1–12. 10.1038/s41598-017-01747-8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R18] Drake SS, Zaman A, Gianfelice C, Hua EML, Heale K, Afanasiev E, Klement W, Stratton JA, Prat A, Zandee S, Fournier AE, 2024. Senolytic treatment diminishes microglia and decreases severity of experimental autoimmune encephalomyelitis. J. Neuroinflammation 21. 10.1186/s12974-024-03278-2, 2024.02.05.579017. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R19] Dyer MS, Reale LA, Lewis KE, Walker AK, Dickson TC, Woodhouse A, Blizzard CA, 2021. Mislocalisation of TDP-43 to the cytoplasm causes cortical hyperexcitability and reduced excitatory neurotransmission in the motor cortex. J. Neurochem. 157, 1300–1315. 10.1111/jnc.15214. [DOI] [PubMed] [Google Scholar]

[R20] Elliott ML, Caspi A, Houts RM, Ambler A, Broadbent JM, Hancox RJ, Harrington HL, Hogan S, Keenan R, Knodt A, Leung JH, Melzer TR, Purdy SC, Ramrakha S, Richmond-Rakerd LS, Righarts A, Sugden K, Thomson WM, Thorne PR, Williams BS, Wilson G, Hariri AR, Poulton R, Moffitt TE, 2021. Disparities in the pace of biological aging among midlife adults of the same chronological age have implications for future frailty risk and policy. Nat. Aging 1, 295–308. 10.1038/s43587-021-00044-4. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R21] Fang C, Jin J, Shi W, Xu X, Li H, Duan Q, Yu X, Wu S, Lu T, Hu F, Qin X, Huang J, Sun D, Zhang M, He S, Dang J, He Q, Zhang Q, Gan S, 2026a. Accelerated brain aging in amyotrophic lateral sclerosis and its prognostic associations: a cohort study. BMC Med. 10.1186/s12916-026-04631-3. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R22] Fang L, Bai Z, Yang D, Sun B, Zhao X, Deng J, 2026b. Elimination of senescent cells fails to attenuate disease progression in an ALS mouse model. Neurol. Sci. 47, 1–13. 10.1007/s10072-026-09023-2. [DOI] [PubMed] [Google Scholar]

[R23] Golub VM, Brewer J, Wu X, Kuruba R, Short J, Manchi M, Swonke M, Younus I, Reddy DS, 2015. Neurostereology protocol for unbiased quantification of neuronal injury and neurodegeneration. Front. Aging Neurosci. 7, 1–14. 10.3389/fnagi.2015.00196. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R24] Gonzales MM, Garbarino VR, Pollet E, Palavicini JP, Kellogg DL, Kraig E, Orr ME, 2022. Biological aging processes underlying cognitive decline and neurodegenerative disease. J. Clin. Invest. 132. 10.1172/JCI158453. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R25] Gonzales MM, Garbarino VR, Kautz TF, Palavicini JP, Lopez-Cruzan M, Dehkordi SK, Mathews JJ, Zare H, Xu P, Zhang B, Franklin C, Habes M, Craft S, Petersen RC, Tchkonia T, Kirkland JL, Salardini A, Seshadri S, Musi N, Orr ME, 2023. Senolytic therapy in mild Alzheimer’s disease: a phase 1 feasibility trial. Nat. Med. 29, 2481–2488. 10.1038/s41591-023-02543-w. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R26] Grabert K, Michoel T, Karavolos MH, Clohisey S, Kenneth Baillie J, Stevens MP, Freeman TC, Summers KM, McColl BW, 2016. Microglial brain regiona ˆ ‘dependent diversity and selective regional sensitivities to aging. Nat. Neurosci. 19, 504–516. 10.1038/nn.4222. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R27] Green TRF, Murphy SM, Rowe RK, 2022. Comparisons of quantitative approaches for assessing microglial morphology reveal inconsistencies, ecological fallacy, and a need for standardization. Sci. Rep. 12, 1–13. 10.1038/s41598-022-23091-2. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R28] Grimsley CA, Sanchez JT, Sivaramakrishnan S, 2013. Diversity of layer 5 projection neurons in the mouse motor cortex. Front. Neural Circuits 7, 1–18. 10.3389/fncir.2013.00174. [DOI] [Google Scholar]

[R29] Haidar M, Viden A, Daniel C, Cuic B, Wang T, Rosier M, Tomas D, Mills SA, Govier-Cole A, Djouma E, Perera ND, Luikinga S, Rytova V, Barton SK, Gonsalvez DG, Palmer LM, McLean C, Kiernan MC, Vucic S, Turner BJ, 2025. Cortical hyperexcitability drives dying forward amyotrophic lateral sclerosis symptoms and pathology in mice. Prog. Neurobiol. 252, 102809. 10.1016/j.pneurobio.2025.102809. [DOI] [PubMed] [Google Scholar]

[R30] Hasegawa M, Arai T, Nonaka T, Kametani F, Yoshida M, Hashizume Y, Beach TG, Buratti E, Baralle F, Morita M, Nakano I, Oda T, Tsuchiya K, Akiyama H, 2008. Phosphorylated TDP-43 in frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Ann. Neurol. 64, 60–70. 10.1002/ana.21425. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R31] Herdy JR, Traxler L, Agarwal RK, Karbacher L, Schlachetzki JCM, Boehnke L, Zangwill D, Galasko D, Glass CK, Mertens J, Gage FH, 2022. Increased post-mitotic senescence in aged human neurons is a pathological feature of Alzheimer’s disease. Cell Stem Cell 29, 1637–1652.e6. 10.1016/j.stem.2022.11.010. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R32] Hickson LTJ, Langhi Prata LGP, Bobart SA, Evans TK, Giorgadze N, Hashmi SK, Herrmann SM, Jensen MD, Jia Q, Jordan KL, Kellogg TA, Khosla S, Koerber DM, Lagnado AB, Lawson DK, LeBrasseur NK, Lerman LO, McDonald KM, McKenzie TJ, Passos JF, Pignolo RJ, Pirtskhalava T, Saadiq IM, Schaefer KK, Textor SC, Victorelli SG, Volkman TL, Xue A, Wentworth MA, Wissler Gerdes EO, Zhu Y, Tchkonia T, Kirkland JL, 2019. Senolytics decrease senescent cells in humans: preliminary report from a clinical trial of Dasatinib plus quercetin in individuals with diabetic kidney disease. EBioMedicine 47, 446–456. 10.1016/j.ebiom.2019.08.069. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R33] Horvath S, Langfelder P, Kwak S, Aaronson J, Rosinski J, Vogt TF, Eszes M, Faull RLM, Curtis MA, Waldvogel HJ, Choi OW, Tung S, Vinters HV, Coppola G, Yang XW, 2016. Huntington’s disease accelerates epigenetic aging of human brain and disrupts DNA methylation levels. Aging 8, 1485–1512. 10.18632/aging.101005. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R34] Islam MT, Tuday E, Allen S, Kim J, Trott DW, Holland WL, Donato AJ, Lesniewski LA, 2023. Senolytic drugs, dasatinib and quercetin, attenuate adipose tissue inflammation, and ameliorate metabolic function in old age. Aging Cell 22, 1–15. 10.1111/acel.13767. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R35] Italiani P, Carlesi C, Giungato P, Puxeddu I, Borroni B, Bossù P, Migliorini P, Siciliano G, Boraschi D, 2014. Evaluating the levels of interleukin-1 family cytokines in sporadic amyotrophic lateral sclerosis. J. Neuroinflammation 11, 1–7. 10.1186/1742-2094-11-94. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R36] Jo M, Lee S, Jeon YM, Kim S, Kwon Y, Kim HJ, 2020. The role of TDP-43 propagation in neurodegenerative diseases: integrating insights from clinical and experimental studies. Exp. Mol. Med. 52, 1652–1662. 10.1038/s12276-020-00513-7. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R37] Jurk D, Wang C, Miwa S, Maddick M, Korolchuk V, Tsolou A, Gonos ES, Thrasivoulou C, Jill Saffrey M, Cameron K, von Zglinicki T, 2012. Postmitotic neurons develop a p21-dependent senescence-like phenotype driven by a DNA damage response. Aging Cell 11, 996–1004. 10.1111/j.1474-9726.2012.00870.x. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R38] Justice JN, Nambiar AM, Tchkonia T, LeBrasseur NK, Pascual R, Hashmi SK, Prata L, Masternak MM, Kritchevsky SB, Musi N, Kirkland JL, 2019. Senolytics in idiopathic pulmonary fibrosis: results from a first-in-human, open-label, pilot study. EBioMedicine 40, 554–563. 10.1016/j.ebiom.2018.12.052. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R39] Kelley JB, Paschal BM, 2019. Fluorescence-based quantification of nucleocytoplasmic transport. Methods 157, 106–114. 10.1016/j.ymeth.2018.11.002. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R40] Kerr NR, Dashtmian AR, Darvishi FB, Brennan CD, Ayyagari SN, Moore PJ, Viteri JA, Wang M, Rich MM, Clark BC, Arnold WD, 2025. 5-HT2C agonism as a neurotherapeutic for sarcopenia: preclinical proof of concept. Geroscience 47, 4075–4092. 10.1007/s11357-025-01519-7. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R41] Kirkland JL, Tchkonia T, 2020. Senolytic drugs: from discovery to translation. J. Intern. Med. 288, 518–536. 10.1111/joim.13141. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R42] Leyh J, Paeschke S, Mages B, Michalski D, Nowicki M, Bechmann I, Winter K, 2021. Classification of microglial morphological phenotypes using machine learning. Front. Cell. Neurosci. 15, 1–17. 10.3389/fncel.2021.701673. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R43] Liu B, Liu J, Shi JS, 2020. SAMP8 mice as a model of age-related cognition decline with underlying mechanisms in Alzheimer’s disease. J. Alzheimer’s Dis 75, 385–395. 10.3233/JAD-2000063. [DOI] [PubMed] [Google Scholar]

[R44] Lombardo ER, Pijewski RS, Lustig JT, Dhari Z, Lahiri A, Papile LE, Lavoie ER, Scanlon VM, Bartley JM, Crocker SJ, 2026. Senolytic treatment induces oligodendrocyte dysfunction and demyelination in the corpus callosum. Proc. Natl. Acad. Sci. U. S. A. 123, 1–10. 10.1073/pnas.2524897123. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R45] Masrori P, Van Damme P, 2020. Amyotrophic lateral sclerosis: a clinical review. Eur. J. Neurol. 27, 1918–1929. 10.1111/ene.14393. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R46] Maximova A, Werry EL, Kassiou M, 2021. Senolytics: a novel strategy for neuroprotection in als? Int. J. Mol. Sci. 22, 1–15. 10.3390/ijms222112078. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R47] Maxwell N, Castro RW, Sutherland NM, Vaughan KL, Szarowicz MD, de Cabo R, Mattison JA, Valdez G, 2018. α-Motor neurons are spared from aging while their synaptic inputs degenerate in monkeys and mice. Aging Cell 17. 10.1111/acel.12726. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R48] Meissner F, Molawi K, Zychlinsky A, 2010. Mutant superoxide dismutase 1-induced IL-1β accelerates ALS pathogenesis. Proc. Natl. Acad. Sci. U. S. A. 107, 13046–13050. 10.1073/pnas.1002396107. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R49] Menon P, Kiernan MC, Vucic S, 2015. Cortical hyperexcitability precedes lower motor neuron dysfunction in ALS. Clin. Neurophysiol. 126, 803–809. 10.1016/j.clinph.2014.04.023. [DOI] [PubMed] [Google Scholar]

[R50] Menon P, Higashihara M, van den Bos M, Geevasinga N, Kiernan MC, Vucic S, 2020. Cortical hyperexcitability evolves with disease progression in ALS. Ann. Clin. Transl. Neurol. 7, 733–741. 10.1002/acn3.51039. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R51] Meyer T, Schumann P, Weydt P, Petri S, Koc Y, Spittel S, Bernsen S, Günther R, Weishaupt JH, Dreger M, Kolzarek F, Kettemann D, Norden J, Boentert M, Vidovic M, Meisel C, Münch C, Maier A, Körtvélyessy P, 2023. Neurofilament light-chain response during therapy with antisense oligonucleotide tofersen in SOD1-related ALS: treatment experience in clinical practice. Muscle Nerve 67, 515–521. 10.1002/mus.27818. [DOI] [PubMed] [Google Scholar]

[R52] Meyer T, Dreger M, Grehl T, Weyen U, Kettemann D, Weydt P, Günther R, Lingor P, Petri S, Koch JC, Großkreutz J, Rödiger A, Baum P, Hermann A, Prudlo J, Boentert M, Weishaupt JH, Löscher WN, Dorst J, Koc Y, Bernsen S, Cordts I, Vidovic M, Steinbach R, Metelmann M, Kleinveld VE, Norden J, Ludolph A, Walter B, Schumann P, Münch C, Körtvélyessy P, Maier A, 2024. Serum neurofilament light chain in distinct phenotypes of amyotrophic lateral sclerosis: a longitudinal, multicenter study. Eur. J. Neurol. 31, 1–13. 10.1111/ene.16379. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R53] Migliarini S, Scaricamazza S, Valle C, Ferri A, Pasqualetti M, Ferraro E, 2021. Microglia morphological changes in the motor cortex of hsod1g93a transgenic als mice. Brain Sci. 11. 10.3390/brainsci11060807. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R54] Miller TM, Cudkowicz ME, Shaw PJ, Genge A, Sobue G, Bucelli RC, Chiò A, Van Damme P, Ludolph AC, Glass JD, Andrews JA, Babu S, Benatar M, McDermott CJ, Salachas F, Bruneteau G, Al-Chalabi A, Amorin M, Nestorov I, Graham D, Lin L, Sun P, McNeill M, Malek S, Inra J, Garafalo S, Fradette S, 2025. Long-term Tofersen in SOD1 amyotrophic lateral sclerosis. JAMA Neurol. 02142, 1–11. 10.1001/jamaneurol.2025.4946. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R55] Mitchell JC, Constable R, So E, Vance C, Scotter E, Glover L, Hortobagyi T, Arnold ES, Ling SC, McAlonis M, Da Cruz S, Polymenidou M, Tessarolo L, Cleveland DW, Shaw CE, 2015. Wild type human TDP-43 potentiates ALS-linked mutant TDP-43 driven progressive motor and cortical neuron degeneration with pathological features of ALS. Acta Neuropathol. Commun. 3, 36. 10.1186/s40478-015-0212-4. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R56] Mitra J, Kodavati M, Dharmalingam P, Guerrero EN, Rao KS, Garruto RM, Hegde ML, 2025. Endogenous TDP-43 mislocalization in a novel knock-in mouse model reveals DNA repair impairment, inflammation, and neuronal senescence. Acta Neuropathol. Commun. 13. 10.1186/s40478-025-01962-9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R57] Mullen RJ, Buck CR, Smith AM, 1992. NeuN, a neuronal specific nuclear protein in vertebrates. Development 116, 201–211. 10.1242/dev.116.1.201. [DOI] [PubMed] [Google Scholar]

[R58] Muñoz-Castañeda R, Zingg B, Matho KS, Chen X, Wang Q, Foster NN, Li A, Narasimhan A, Hirokawa KE, Huo B, Bannerjee S, Korobkova L, Park CS, Park YG, Bienkowski MS, Chon U, Wheeler DW, Li X, Wang Y, Naeemi M, Xie P, Liu L, Kelly K, An X, Attili SM, Bowman I, Bludova A, Cetin A, Ding L, Drewes R, D’Orazi F, Elowsky C, Fischer S, Galbavy W, Gao L, Gillis J, Groblewski PA, Gou L, Hahn JD, Hatfield JT, Hintiryan H, Huang JJ, Kondo H, Kuang X, Lesnar P, Li X, Li Y, Lin M, Lo D, Mizrachi J, Mok S, Nicovich PR, Palaniswamy R, Palmer J, Qi X, Shen E, Sun YC, Tao HW, Wakemen W, Wang Y, Yao S, Yuan J, Zhan H, Zhu M, Ng L, Zhang LI, Lim BK, Hawrylycz M, Gong H, Gee JC, Kim Y, Chung K, Yang XW, Peng H, Luo Q, Mitra PP, Zador AM, Zeng H, Ascoli GA, Josh Huang Z, Osten P, Harris JA, Dong HW (2021) Cellular anatomy of the mouse primary motor cortex. Nature 598:159–166. doi: 10.1038/s41586-021-03970-w. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R59] Neumann M, Kwong LK, Lee EB, Kremmer E, Flatley A, Xu Y, Forman MS, Troost D, Kretzschmar HA, Trojanowski JQ, Lee VMY, 2009. Phosphorylation of S409/410 of TDP-43 is a consistent feature in all sporadic and familial forms of TDP-43 proteinopathies. Acta Neuropathol. 117, 137–149. 10.1007/s00401-008-0477-9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R60] Nijssen J, Comley LH, Hedlund E, 2017. Motor neuron vulnerability and resistance in amyotrophic lateral sclerosis. Acta Neuropathol. 133, 863–885. 10.1007/s00401-017-1708-8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R61] Ogrodnik M, Zhu Y, Langhi LGP, Tchkonia T, Krüger P, Fielder E, Victorelli S, Ruswhandi RA, Giorgadze N, Pirtskhalava T, Podgorni O, Enikolopov G, Johnson KO, Xu M, Inman C, Palmer AK, Schafer M, Weigl M, Ikeno Y, Burns TC, Passos JF, von Zglinicki T, Kirkland JL, Jurk D, 2019. Obesity-induced cellular senescence drives anxiety and impairs neurogenesis. Cell Metab. 29, 1061–1077.e8. 10.1016/j.cmet.2018.12.008. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R62] Owendoff G, Ray A, Bobbili P, Clark L, Baumann CW, Clark BC, Arnold WD, 2023. Optimization and construct validity of approaches to preclinical grip strength testing. J. Cachexia. Sarcopenia Muscle 14, 2439–2445. 10.1002/jcsm.13300. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R63] Pandya VA, Patani R, 2020. Decoding the relationship between ageing and amyotrophic lateral sclerosis: a cellular perspective. Brain 143, 1057–1072. 10.1093/brain/awz360. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R64] Penna I, Vella S, Gigoni A, Russo C, Cancedda R, Pagano A, 2011. Selection of candidate housekeeping genes for normalization in human postmortem brain samples. Int. J. Mol. Sci. 12, 5461–5470. 10.3390/ijms12095461. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R65] Pukos N, Marion CM, Arnold WD, Noble BT, Popovich PG, McTigue DM, 2023. Chronic demyelination and myelin repair after spinal cord injury in mice: a potential link for glutamatergic axon activity. Glia 71, 2096–2116. 10.1002/glia.24382. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R66] Quek H, Cuní-López C, Stewart R, Colletti T, Notaro A, Nguyen TH, Sun Y, Guo CC, Lupton MK, Roberts TL, Lim YC, Oikari LE, La Bella V, White AR, 2022. ALS monocyte-derived microglia-like cells reveal cytoplasmic TDP-43 accumulation, DNA damage, and cell-specific impairment of phagocytosis associated with disease progression. J. Neuroinflammation 19, 1–21. 10.1186/s12974-022-02421-1. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R67] Rad AN, Grillari J, 2024. Current senolytics: mode of action, efficacy and limitations, and their future. Mech. Ageing Dev. 217, 111888. 10.1016/j.mad.2023.111888. [DOI] [PubMed] [Google Scholar]

[R68] Reale LA, Dyer MS, Perry SE, Young KM, Dickson TC, Woodhouse A, Blizzard CA, 2023. Pathologically mislocalised TDP-43 in upper motor neurons causes a die-forward spread of ALS-like pathogenic changes throughout the mouse corticomotor system. Prog. Neurobiol. 226, 102449. 10.1016/j.pneurobio.2023.102449. [DOI] [PubMed] [Google Scholar]

[R69] Richardson M, Richardson DR, 2024. Pharmacological targeting of senescence with Senolytics as a new therapeutic strategy for neurodegeneration. Mol. Pharmacol. 105, 64–74. 10.1124/molpharm.123.000803. [DOI] [PubMed] [Google Scholar]

[R70] Sadaki S, Fujita R, Hayashi T, Nakamura A, Okamura Y, Fuseya S, Hamada M, Warabi E, Kuno A, Ishii A, Muratani M, Okada R, Shiba D, Kudo T, Takeda S, Takahashi S, 2023. Large Maf transcription factor family is a major regulator of fast type IIb myofiber determination. Cell Rep. 42, 112289. 10.1016/j.celrep.2023.112289. [DOI] [PubMed] [Google Scholar]

[R71] Schaefer AM, Sanes JR, Lichtman JW, 2005. A compensatory subpopulation of motor neurons in a mouse model of amyotrophic lateral sclerosis. J. Comp. Neurol. 219, 209–219. 10.1002/cne.20620. [DOI] [PubMed] [Google Scholar]

[R72] Schneider CA, Rasband WS, Eliceiri KW, 2012. NIH image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675. 10.1038/nmeth.2089. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R73] Sheth KA, Iyer CC, Wier CG, Crum AE, Bratasz A, Kolb SJ, Clark BC, Burghes AHM, Arnold WD, 2018. Muscle strength and size are associated with motor unit connectivity in aged mice. Neurobiol. Aging 67, 128–136. 10.1016/j.neurobiolaging.2018.03.016. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R74] Spiller KJ, Restrepo CR, Khan T, Dominique MA, Fang TC, Canter RG, Roberts CJ, Miller KR, Ransohoff RM, Trojanowski JQ, Lee VMY, 2018. Microglia-mediated recovery from ALS-relevant motor neuron degeneration in a mouse model of TDP-43 proteinopathy. Nat. Neurosci. 21, 329–340. 10.1038/s41593-018-0083-7. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R75] Stetzik L, Mercado G, Smith L, George S, Quansah E, Luda K, Schulz E, Meyerdirk L, Lindquist A, Bergsma A, Jones RG, Brundin L, Henderson MX, Pospisilik JA, Brundin P, 2022. A novel automated morphological analysis of Iba1 + microglia using a deep learning assisted model. Front. Cell. Neurosci. 16, 1–16. 10.3389/fncel.2022.944875. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R76] Steward O, Yee KM, Metcalfe M, Willenberg R, Luo J, Azevedo R, Martin-Thompson JH, Gandhi SP, 2021. Rostro-caudal specificity of corticospinal tract projections in mice. Cereb. Cortex 31, 2322–2344. 10.1093/cercor/bhaa338. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R77] Suk TR, Rousseaux MWC, 2020. The role of TDP-43 mislocalization in amyotrophic lateral sclerosis. Mol. Neurodegener. 15, 1–16. 10.1186/s13024-020-00397-1. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R78] Torres P, Anerillas C, Ramırez-Núñez O, Fernandeź A, Encinas M, Povedano M, Andrés-Benito P, Ferrer I, Ayala V, Pamplona R, Portero-Otın M, 2022. A motor neuron disease mouse model reveals a non-canonical profile of senescence biomarkers. Dis. Model. Mech. 15. 10.1242/DMM.049059. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R79] Trias E, Beilby PR, Kovacs M, Ibarburu S, Varela V, Barreto-Núñez R, Bradford SC, Beckman JS, Barbeito L, 2019. Emergence of microglia bearing senescence markers during paralysis progression in a rat model of inherited ALS. Front. Aging Neurosci. 10, 1–14. 10.3389/fnagi.2019.00042. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R80] Vahsen BF, Nalluru S, Morgan GR, Farrimond L, Carroll E, Xu Y, Cramb KML, Amein B, Scaber J, Katsikoudi A, Candalija A, Carcolé M, Dafinca R, Isaacs AM, Wade-Martins R, Gray E, Turner MR, Cowley SA, Talbot K, 2023. C9orf72-ALS human iPSC microglia are pro-inflammatory and toxic to co-cultured motor neurons via MMP9. Nat. Commun. 14. 10.1038/s41467-023-41603-0. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R81] Vazquez-Villaseñor I, Garwood CJ, Heath PR, Simpson JE, Ince PG, Wharton SB, 2020. Expression of p16 and p21 in the frontal association cortex of ALS/MND brains suggests neuronal cell cycle dysregulation and astrocyte senescence in early stages of the disease. Neuropathol. Appl. Neurobiol. 46, 171–185. 10.1111/nan.12559. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R82] Viteri JA, Bueschke N, Santin JM, Arnold WD, 2025a. Age-related increase in the excitability of mouse layer V pyramidal neurons in the primary motor cortex is accompanied by an increased persistent inward current. Geroscience 47, 2199–2222. 10.1007/s11357-024-01405-8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R83] Viteri JA, Kerr NR, Brennan CD, Suleiman LA, Wendt CD, Xu C, An H, Wang M, Nishimune H, Santin JM, Arnold WD, 2025b. Reduced corticomuscular output is associated with intrinsic hypoexcitability and reduced persistent inward currents in motor cortex neurons of TDP-43Q331K ALS mice. Neurobiol. Dis. 218, 107247. 10.1016/j.nbd.2025.107247. [DOI] [PubMed] [Google Scholar]

[R84] Vucic S, Lin CSY, Cheah BC, Murray J, Menon P, Krishnan AV, Kiernan MC, 2013. Riluzole exerts central and peripheral modulating effects in amyotrophic lateral sclerosis. Brain 136, 1361–1370. 10.1093/brain/awt085. [DOI] [PubMed] [Google Scholar]

[R85] Wang J, Lu Y, Carr C, Dhandapani KM, Brann DW, 2023. Senolytic therapy is neuroprotective and improves functional outcome long-term after traumatic brain injury in mice. Front. Neurosci. 17, 1–15. 10.3389/fnins.2023.1227705. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R86] Watkins JA, Alix JJP, Shaw PJ, Mead RJ, 2021. Extensive phenotypic characterisation of a human TDP-43Q331K transgenic mouse model of amyotrophic lateral sclerosis (ALS). Sci. Rep. 11, 1–14. 10.1038/s41598-021-96122-z. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R87] Weiler N, Wood L, Yu J, Solla SA, Shepherd GMG, 2008. Top-down laminar organization of the excitatory network in motor cortex. Nat. Neurosci. 11, 360–366. 10.1038/nn2049. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R88] West MJ, 2012. Introduction to stereology. Cold Spring Harb. Protoc. 7, 843–851. 10.1101/pdb.top070623. [DOI] [PubMed] [Google Scholar]

[R89] Wier CG, Crum AE, Reynolds AB, Iyer CC, Chugh D, Palettas MS, Heilman PL, Kline DM, Arnold WD, Kolb SJ, 2019. Muscle contractility dysfunction precedes loss of motor unit connectivity in SOD1(G93A) mice. Muscle Nerve 59, 254–262. 10.1002/mus.26365. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R90] Wiesenfarth M, Dorst J, Brenner D, Elmas Z, Parlak Ö, Uzelac Z, Kandler K, Mayer K, Weiland U, Herrmann C, Schuster J, Freischmidt A, Müller K, Siebert R, Bachhuber F, Simak T, Günther K, Fröhlich E, Knehr A, Regensburger M, German A, Petri S, Grosskreutz J, Klopstock T, Reilich P, Schöberl F, Hagenacker T, Weyen U, Günther R, Vidovic M, Jentsch M, Haarmeier T, Weydt P, Valkadinov I, Hesebeck-Brinckmann J, Conrad J, Weishaupt JH, Schumann P, Körtvélyessy P, Meyer T, Ruf WP, Witzel S, Senel M, Tumani H, Ludolph AC, 2024. Effects of tofersen treatment in patients with SOD1-ALS in a “real-world” setting – a 12-month multicenter cohort study from the German early access program. EClinicalMedicine 69, 102495. 10.1016/j.eclinm.2024.102495. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R91] Xu M, Pirtskhalava T, Farr JN, Weigand BM, Palmer AK, Weivoda MM, Inman CL, Ogrodnik MB, Hachfeld CM, Fraser DG, Onken JL, Johnson KO, Verzosa GC, Langhi LGP, Weigl M, Giorgadze N, LeBrasseur NK, Miller JD, Jurk D, Singh RJ, Allison DB, Ejima K, Hubbard GB, Ikeno Y, Cubro H, Garovic VD, Hou X, Weroha SJ, Robbins PD, Niedernhofer LJ, Khosla S, Tchkonia T, Kirkland JL, 2018. Senolytics improve physical function and increase lifespan in old age. Nat. Med. 24, 1246–1256. 10.1038/s41591-018-0092-9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R92] Yildiz O, Schroth J, Tree T, Turner MR, Shaw PJ, Henson SM, Malaspina A, 2023. Senescent-like blood lymphocytes and disease progression in amyotrophic lateral sclerosis. Neurol. Neuroimmunol. Neuroinflamm. 10, 1–13. 10.1212/NXI.0000000000200042. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R93] Young K, Morrison H, 2018. Quantifying microglia morphology from photomicrographs of immunohistochemistry prepared tissue using imagej. J. Vis. Exp. 1–9. 10.3791/57648. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R94] Zanier ER, Fumagalli S, Perego C, Pischiutta F, De Simoni MG, 2015. Shape descriptors of the “never resting” microglia in three different acute brain injury models in mice. Intensive Care Med. Exp. 3, 1–18. 10.1186/s40635-015-0039-0. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R95] Zhang P, Kishimoto Y, Grammatikakis I, Gottimukkala K, Cutler RG, Zhang S, Abdelmohsen K, Bohr VA, Misra Sen J, Gorospe M, Mattson MP, 2019. Senolytic therapy alleviates aβ-associated oligodendrocyte progenitor cell senescence and cognitive deficits in an Alzheimer’s disease model. Nat. Neurosci. 22, 719–728. 10.1038/s41593-019-0372-9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R96] Zhao X, van Praag H, 2020. Steps towards standardized quantification of adult neurogenesis. Nat. Commun. 11, 1–10. 10.1038/s41467-020-18046-y. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R97] Zhou C, Hardin EJ, Zimmer TS, Jackvony S, Barnett D, Khobrekar N, Giacomelli E, Studer L, Orr AL, Orr AG, 2025. Neuroimmune signaling mediates astrocytic nucleocytoplasmic disruptions and stress granule formation associated with TDP-43 pathology. Neurobiol. Dis. 211, 106939. 10.1016/j.nbd.2025.106939. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R98] Zhu Y, Tchkonia T, Pirtskhalava T, Gower AC, Ding H, Giorgadze N, Palmer AK, Ikeno Y, Hubbard GB, Lenburg M, O’hara SP, Larusso NF, Miller JD, Roos CM, Verzosa GC, Lebrasseur NK, Wren JD, Farr JN, Khosla S, Stout MB, SJ McGowan, Fuhrmann-Stroissnigg H, Gurkar AU, Zhao J, Colangelo D, Dorronsoro A, Ling YY, Barghouthy AS, Navarro DC, Sano T, Robbins PD, Niedernhofer LJ, Kirkland JL, 2015. The achilles’ heel of senescent cells: from transcriptome to senolytic drugs. Aging Cell 14, 644–658. 10.1111/acel.12344. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R99] Zhu Y, Tchkonia T, Fuhrmann H, Dai HM, Ling YY, Michael B, Pirtskhalava T, Giorgadze N, Kurt O, Giles CB, Wren JD, Laura J, Robbins PD, Kirkland JL, 2016. Identification of a novel senolytic agent, navitoclax, targeting the Bcl-2 family of anti-apoptotic factors. Aging Cell 428–435. 10.1111/acel.12445. [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Cellular senescence is an early feature and therapeutic target in amyotrophic lateral sclerosis TDP-43Q331K mice

Jose A Viteri

Nathan R Kerr

Charles D Brennan

Grace R Kick

Meifang Wang

Arsh Ketabforoush

Harper J Snyder

Peter J Moore

Fereshteh B Darvishi

Anna R Dashtmian

Sindhuja N Ayyagari

Kelly Rich

Yi Zhu

Hiroshi Nishimune

W David Arnold

Roles