The experimental data from various studies indicate that tau pathology may be associated with cellular senescence. This complex stress response induces a near permanent cell cycle arrest, adaptations to maintain survival, cellular remodeling, metabolic dysfunction, and disruption of surrounding tissue due to the secretion of toxic molecules (Childs et al., 2016 ). While many of these features have been described in AD brains and transgenic animal models throughout the literature (e.g., aberrant cell cycle activity, p16 INK4A co‐localization with NFTs (Arendt, Rodel, Gartner, & Holzer, 1996 ), decreased lamin B1, and heterochromatin relaxation (Frost, Bardai, & Feany, 2016 ); a role for cellular senescence in AD‐associated neurodegeneration has not been investigated. We hypothesized that tau accumulation may activate this stress response and thereby initiate a chronic degenerative process culminating in neuron loss and brain dysfunction. To test this hypothesis, we examined human brain tissue with NFT pathology and utilized AD transgenic mouse models that develop tau‐associated pathologies. Also, we employed methods to genetically reduce NFTs and pharmacologically clear senescent cells. Our results indicate that NFTs induce cellular senescence in transgenic mice and postmortem human brain tissue. We also found that senolytics decreased cortical NFT burden, brain atrophy, and neuron loss in an advanced age (20 months old) transgenic mouse model of tau‐associated neurodegeneration.

The underlying processes driving chronic neurodegeneration in Alzheimer’s disease (AD) and related neurodegenerative disorders are largely unknown, and disease‐modifying treatments remain elusive. The accumulation of tau protein is the most common pathology among these diseases making tau an appealing molecular target for intervention (Orr, Sullivan, & Frost, 2017 ). Tau‐containing neurofibrillary tangles (NFTs) closely track with disease severity in human AD (Arriagada, Growdon, Hedley‐Whyte, & Hyman, 1992 ); however, NFT‐containing neurons are long‐lived and do not induce immediate cell death (de Calignon, Spires‐Jones, Pitstick, Carlson, & Hyman, 2009 ). In silico modeling predicts that NFT‐containing neurons may survive decades (Morsch, Simon, & Coleman, 1999 ), which suggests that non‐cell autonomous mechanisms may contribute to NFT‐associated toxicity.

2 RESULTS

2.1 NFT‐bearing neurons from postmortem AD brain tissue displayed a senescence‐like transcriptomic profile We queried the publicly available GEO Profiles database (Barrett et al., 2013) for gene sets specific to NFTs. We evaluated laser capture‐microdissected cortical neurons containing NFTs from AD brains (GEO accession GDS2795) and compared them to adjacent histopathologically normal neurons for a within‐subject study design (Dunckley et al., 2006). NFT‐containing neurons upregulated genes involved in cell survival and viability, inflammation, cell cycle progression and molecular transport and downregulated apoptosis, necrosis, and cell death pathways (Figure 1a). NFκB, a pro‐survival master transcriptional regulator of inflammation, was the highest predicted upstream regulator of the NFT gene expression profile. In agreement with inflammatory activation, other predicted upstream regulators included IFNG, TNF, TLR4, IL1B, and CXCL1 (Figure 1b). Collectively, the molecular pathways identified in the NFT analyses resembled cellular senescence. Figure 1 Open in figure viewer PowerPoint Neurofibrillary tangles were associated with cellular senescence‐associated gene pathways in human Alzheimer’s disease neurons and tau transgenic mouse brains. (a) Pathways and predicted upstream regulators identified by ingenuity pathway analyses (IPA, QIAGEN) as significantly enriched in Alzheimer’s disease patient‐derived neurons with neurofibrillary tangles compared to non‐tangle‐containing neurons; z‐score plotted on x‐axis and (p‐value) indicated in bar graph. Cellular functions and (b) predicted upstream regulators employed by neurofibrillary tangle‐containing neurons derived from Alzheimer’s disease patient are shown. (c) Predicted upstream regulators of gene transcription in tau NFT mice after the onset of neurofibrillary tangles (~6 months old vs. ~2 months old); z‐score plotted on x‐axis and (p‐value) indicated in bar graph. (d‐e) Representative immunoblot generated by capillary electrophoresis on chromatin‐bound fractions from mouse forebrain homogenate probed with anti‐γ‐H2ax antibody. (e) Densitometric normalization of γ‐H2ax to total protein content (CTL: n = 3; tau WT n = 4; tau NFT : n = 5; ANOVA, p = 0.0056. Mice aged 16 to 18 months old). (f–g) Quantitative gene expression on RNA isolated from CTL (open bar, n = 3), tau WT (closed bar, n = 3), and tau NFT (red bar, n = 4) mouse forebrain targeting (f): Cdkn2a, p = 0.0066, and (g) Cdkn1a, p = 0.0207. Gene expression was analyzed by one‐way ANOVA Tukey’s multiple comparison post hoc. Data are graphically represented as mean ± SEM

2.2 NFTs were associated with a senescence‐associated transcriptomic profile in tau transgenic mice We used the rTg(tauP301L)4510 transgenic mouse line, hereon referred to as “tau NFT ” to investigate a link between NFT formation and a senescence‐like phenomenon in neurodegeneration. These mice develop well‐characterized, aggressive, tau pathology in forebrain regions concomitant with neurodegeneration and cognitive deficits (Santacruz et al., 2005; pathology illustrated in Supporting Information Figure S1). Mice that overexpress wild‐type human tau, “tau WT ,” express the same level of transgenic human tau protein as tau NFT , but acquire age‐dependent tau pathogenesis at a much slower rate and are used to identify effects of elevated pre‐pathogenic tau (Hoover et al., 2010; Supporting Information Figures S1 and S2); age‐matched tau NFT littermate mice without human tau overexpression serve as wild‐type controls, “CTL”. To determine whether NFT‐containing neurons in mice induced a gene expression profile resembling cellular senescence, we assessed hippocampal gene expression patterns in tau NFT mice before (~2 months old) and after (~6 months old) NFT formation (GSE56772). Consistent with NFTs from human AD, mouse NFTs also caused significant activation scores for IFNG, TNF, and IL‐1B, as well as enrichment in other senescence‐associated JAK, STAT, CDKN2A, and BCL2 predicted upstream regulators (Figure 1c) indicating translational relevance for using tau NFT mice to explore our hypothesis.

2.3 Evidence of DNA damage, SASP, and NFκB activation were associated with NFTs Senescence‐inducing stressors often inflict DNA damage that drives production of the SASP (Rodier et al., 2009). Tau NFT mouse brains displayed significantly elevated histone γ‐H2ax, a sensitive marker of both double‐stranded DNA breaks and cellular senescence (Sedelnikova et al., 2004; p = 0.0056; Figure 1d–e). The cell cycle protein p21, encoded by Cdkn1a, is upregulated in many senescent cell types and has been associated with DNA damage during neuronal aging (Jurk et al., 2012). Similarly, elevated expression of the cyclin‐dependent kinase inhibitor 2a, Cdkn2a, is one of the most robust markers of cellular senescence, and its protein product, p16INK4A, colocalizes with NFTs in human AD (Arendt et al., 1996). Because anti‐p21 and anti‐p16INK4A antibodies are notoriously poor in mouse tissue, we exclusively measured Cdkn1a and Cdkn2a gene expression. Tau NFT brains expressed three‐fold higher Cdkn1a than control mice (p = 0.0178, Figure 1f), which was replicated in a separate mouse cohort (p = 0.0086, Supporting Information Figure S2f). Moreover, Cdkn2a was expressed at levels 2.7‐ and 2.6‐fold higher in tau NFT than CTL and tau WT , respectively (p = 0.0303 and p = 0.0352, respectively; Figure 1g); this effect was replicated in an independent mouse cohort (p = 0.0016, Supporting Information Figure S2g). Senescent cells exert chronic tissue degeneration through secretion of toxic SASP (Coppe et al., 2010). Consistent with the transcriptomic profile in human NFT‐bearing neurons and mouse brain tissue (Figure 1a‐c), SASP genes were found to be upregulated in tau NFT brains, that is, Il1b was four‐ and twofold higher than CTL and tau WT , respectively; and Cxcl1 was fourfold higher than both control genotypes; Tnfa was 13‐ and eightfold higher than CTL and tau WT , respectively; Tlr4 was threefold higher than both control genotypes (Figure 2a‐d). Further gene expression analyses allowed us to define an array specific to tau pathology in tau NFT brains (Supporting Information Figure S2e). NFκB regulates the pro‐survival, pro‐inflammatory SASP gene expression profile characteristic of cellular senescence (Salminen & Kaarniranta, 2011). Consistent with NFκB pathway activation and the SASP profile, nuclear‐localized NFκB p65 was significantly increased in tau NFT brains (Figure 2e‐f). In all measures, tau WT mice were not significantly different from CTL. These results suggest that insoluble tau and/or post‐translational modifications associated with insoluble tau, but not general tau overexpression, were responsible for the senescence‐associated profile (i.e., DNA damage, NFκB activation, and upregulated SASP; Figures 1, 2 and Supporting Information Figure S2). Figure 2 Open in figure viewer PowerPoint Neurofibrillary tangles were associated with upregulation of SASP gene expression and NFκB activation. (a) Quantitative gene expression on RNA isolated from CTL (open bar, n = 3), tau WT (closed bar, n = 3), and tau NFT (red bar, n = 4) mouse forebrain targeting SASP‐associated genes Il1b, p = 0.0025; (b) Cxcl1, p = 0.0040; (c) Tnfa, p = 0.0114; and (d) Tlr4, p = 0.0144. (d) Immunoblot generated by capillary electrophoresis on subcellular fractionated mouse forebrain homogenate probed with anti‐NFκB p65 antibody. Total cellular p65 (top blot) and nuclear‐localized p65 protein levels (bottom blot) were (e) normalized to total protein content. Total p65, p = 0.0758; nuclear p65, p = 0.0223. CTL: open bar, n = 3; tau WT : closed bar, n = 4; tau NFT : red bar, n = 5. In all experiments, mice were aged 16–18 months old; both males and females were included. Significance was determined by one‐way ANOVA Tukey’s multiple comparison post hoc. Data are graphically represented as mean ± SEM

2.4 SA β‐gal activity did not correlate with NFTs or brain atrophy In regenerative tissues and in vitro cultures, senescent cells may exhibit SA β‐gal activity, which is a measure of lysosomal galactosidase activity at pH 6.0 and indicative of altered/expanded lysosomal compartments (Severino, Allen, Balin, Balin, & Cristofalo, 2000). The examination of the gene that codes for the hydrolase enzyme, galactosidase beta (β) 1 (Glb1), revealed that tau NFT mice expressed higher Glb1 gene expression than controls (Supporting Information Figure S3). However, staining for β‐gal hydrolase activity at pH 6.0 revealed fewer positive cells than controls. Furthermore, SA β‐gal‐reactive cells were observed even in very young mice (1 month old) and the number of SA β‐gal‐reactive cells was positively correlated with brain mass (R2 = 0.4852, p = 0.0039 Supporting Information Figure S3). While our results indicate that SA β‐gal reactivity did not correlate with other senescence markers or brain atrophy, the observed increase in Glb1 gene expression along with a decrease in lysosomal activity at pH 6.0, compared to controls, is suggestive of tau‐associated lysosomal defects, which have been reported by others (Caballero et al., 2018; Wang, Martinez‐Vicente, et al., 2009).

2.5 NFT‐containing brain tissue displayed aberrant cellular bioenergetics Mitochondrial dysfunction is obligatory for SASP production and cellular senescence (Correia‐Melo et al., 2016; Hutter et al., 2004). To examine mitochondrial bioenergetics, we performed high‐resolution respirometry to yield accurate quantitative measurements of oxidative phosphorylation in response to specific substrates for complex I, complex II, fat oxidation, and electron‐transfer system (ETS) capacity. Across genotypes, we compared cortex, hippocampus, and cerebellum. This allowed for the evaluation of specific differences in oxygen consumption due to elevated transgenic tau (comparing CTL with tau wt and tau NFT ), pathogenic tau‐specific effects (comparing tau wt to tau NFT ), as well as the interaction among brains regions and tau expression (e.g., cortex and hippocampus express transgenic tau and develop NFTs, but cerebellum does not). We found a significant genotype main effect for oxygen flux in both cortex and hippocampus, indicating that global respiratory capacity was impaired in NFT‐containing brain regions (p < 0.0001; Figure 3), an effect primarily driven by CI + CII respiration coupled to ATP production (cortex: p = 0.0034; hippocampus: p = 0.0215; Figure 3g,h, respectively), and uncoupled or maximum respiratory capacity (cortex: p = 0.0248; hippocampus: p = 0.0261; Figure 3g,h, respectively). These changes were different between tau NFT and each of the control mouse lines, CTL, and tau WT mice. Because tau WT and tau NFT mice express comparable total tau levels, alterations to respiratory capacity cannot be attributed to tau overexpression. Citrate synthase activity is a surrogate marker of total mitochondrial content/mass and was similar across genotypes and brain regions (Figure 3i) suggesting that the defects in cellular respiration were due to altered mitochondrial quality and not content/mass. Moreover, tau NFT cerebellum did not show deficits in cellular respiration or Cdkn2a upregulation (Figure 3j,k), indicating that senescence‐associated mitochondrial dysfunction was present only in brain regions with persistent pathogenic tau expression. Figure 3 Open in figure viewer PowerPoint Brain regions with neurofibrillary tangles displayed altered cellular respiration. (a–c) Representative respirometric traces from cortical and (d–f) hippocampal tissues using the SUIT protocol to measure oxygen consumption (top gray traces: CTL; black middle traces: tau WT ; bottom red traces: tau NFT ). (g) Tissue mass‐specific respiration analyses in cortical and (h) hippocampal tissue. Two‐way ANOVA Tukey’s multiple comparison post hoc: **p < 0.005. (i) Biochemical analyses of citrate synthase (CS) activity to assess total mitochondrial content in the cortex and hippocampus (n = 5/group). Experimental mice were aged 16–18 months old with n = 6/group; both males and females were included. (j) Total oxygen consumption and (k) Cdkn2a gene expression were measured in the cerebellum, a brain region devoid of NFTs. n = 3/group. Data are graphically represented as mean ± SEM. ETF_L (fat oxidation in the absence of ADP [state 2]), ETF_P (fat oxidation coupled to ATP production), CI_P (complex I activity linked to ATP production [state 3]), CI + CII_P (complex I and complex II linked respiration [state 3]), CI + CII_E (complex I and complex II linked respiration uncoupled [maximum respiration]), and CII_E (complex II activity uncoupled). Data are graphically represented as mean ± SEM

2.6 Cdkn2a upregulation occurred with NFT onset and correlated with NFT density We pursued multiple genetic approaches to determine whether senescence was mechanistically linked to NFT density, NFT onset, or merely protein accumulation. Reducing NFT load in age‐matched animals is not feasible; once NFTs form, they cannot be therapeutically eliminated. However, genetically ablating endogenous mouse tau (microtubule‐associated protein tau, Mapt) reduces NFT pathology and neurodegeneration in tau NFT mice (tau NFT ‐Mapt0/0; Wegmann et al., 2015). The reduced tau pathology corresponded with 60% lower Cdkn2a expression (p = 0.0041, Figure 4a), decreased SASP (Supporting Information Figure S4), and decreased brain atrophy (tau NFT ‐Mapt0/0: 0.4058 ± 0.009 vs. age‐matched tau NFT ‐Maptwt/wt: 0.3451 ± 0.0116; 17.5% difference, p = 0.0143, Figure 4b). Tau NFT mice develop aggressive tauopathy with NFT formation in early life and show a senescence‐associated transcriptomic profile with NFT onset (Figure 1c). To detect subtle cellular changes associated with different stages of age‐associated NFT development and progression, we focused on tau WT mice between 16 and 28 months old. Cdkn2a gene expression increased significantly during this age interval, and at 28 months of age, tau WT Cdkn2a expression was similar to that of 16‐month‐old tau NFT mice (Figure 4c). Concomitantly, at this age, tau WT mice developed NFTs as visualized by Bielschowsky silver staining and immunofluorescence analyses (Figure 4d). These results provide additional evidence for the association between NFT formation and senescence‐associated Cdkn2a upregulation. Figure 4 Open in figure viewer PowerPoint Senescence‐associated Cdkn2a was significantly upregulated in mouse and human brains with neurofibrillary tangles and tracked with total tangle deposition and brain atrophy. (a) Genetically ablating endogenous mouse tau to significantly reduce neurofibrillary tangle load resulted in a concomitant 60% reduction in Cdk2na expression (two‐tailed t test: p = 0.0041; n = 3/group) and (b) significant reduction in brain atrophy (two‐tailed t test, p = 0.0143; n = 3/group). (c) Tracking Cdkn2a expression in tau WT mice revealed a significant age‐dependent increase (one‐way ANOVA: p = 0.0043; n = 3/group for tau WT and n = 4 tau P301L ). In contrast to significantly lower expression than tau NFT mice at 16 months old (p = 0.0075), Dunnett's multiple comparison test indicated that at 22 months of age, tau WT mouse Cdkn2a expression was no longer statistically lower than tau NFT mice (p = 0.0577) and by 28–30 months they were are statistically the same (p = 0.999). (d) Immunofluorescence and Bielschowsky silver staining revealed neurofibrillary tangles in 18‐month‐old tau WT mouse hippocampal CA1 (NeuN, neuron, green; PHF1: phosphorylated tau, red; DAPI, blue, nuclei). (e) qPCR analyses of RNA extracted from 3xTgAD mice with Aβ plaques were compared to tau NFT set at y = 1. 3xTgAD Cdkn2a expression was no different than age‐matched C57BL/6 mice (two‐tailed t test, p = 0.1081; n = 3 WT, n = 6 3xTgAD; n = 4 tau NFT ). Both mouse cohorts expressed significantly less Cdkn2a than tau NFT mice (one‐way ANOVA: p < 0.0001). (f) Cdkn2a expression level was significantly correlated with brain atrophy (R2 = 0.5615, p < 0.0001; n = 43). (g) qPCR analyses of RNA extracted from brains from control older adult humans (n = 10; ave. age = 85.70 years) and age‐matched progressive supranuclear palsy (n = 14; ave. age = 83.86 years) indicated a 57% upregulation of CDKN2A with progressive supranuclear palsy diagnosis (unpaired t test, p = 0.0415) that (h) positively correlated with neurofibrillary tangle deposition in the parietal lobe (ANOVA, p = 0.0008; Kendall’s Tau rank correlation p = 0.059). (i) Immunoblot generated by capillary electrophoresis on cortical brain homogenate from control and progressive supranuclear palsy human brains probed with total tau antibody, HT7. The individual with the highest CDKN2A expression (panel g) displayed high molecular weight tau, lane 9*. Data are graphically represented as error bars, mean ± SEM

2.7 Cdkn2a upregulation was specific to NFT tau pathology and correlated with brain atrophy To determine whether Cdkn2a expression was driven specifically by NFTs, or whether AD‐associated Aβ protein deposition also increased Cdkn2a, we utilized 3xTgAD mice that acquire both AD‐associated pathologies with Aβ deposition and NFT onset at 6 and 18 months of age, respectively (Oddo et al., 2003). In 15‐month‐old mice with heavy Aβ deposition and phosphorylated tau, but lacking NFT pathology (Orr, Salinas, Buffenstein, & Oddo, 2014), Cdkn2a expression was not elevated (Figure 4e). These data indicate that Cdkn2a expression was neither a response to general protein accumulation, nor to pre‐NFT tau pathology, but instead required the presence of NFTs. Further, when plotted against brain weight, Cdkn2a expression was a strong predictor of brain atrophy across mouse lines (p < 0.0001, R2 = 0.5615; Figure 4f).

2.8 CDKN2A was upregulated in NFT‐containing brains from patients with progressive supranuclear palsy Tau pathology is common among >20 brain diseases. To investigate whether the findings in human AD neurons and transgenic mice translated to human brains with pure tauopathy (i.e., NFT pathology without other protein aggregates such as Aβ), we acquired human brain tissue with histopathologically confirmed progressive supranuclear palsy (PSP; Table 1 for patient characteristics). PSP is an age‐associated tauopathy that clinically manifests as parkinsonism with additional motor abnormalities and cognitive dysfunction (Orr et al., 2017) and is neuropathologically defined by the accumulation of four‐repeat (4R) tau, NFTs, gliosis, and neurodegeneration (Flament, Delacourte, Verny, Hauw, & Javoy‐Agid, 1991). Consistent with the results from transgenic mice, CDKN2A was upregulated in PSP brains (p = 0.0415, Figure 4g) and expression correlated with NFT deposition, specifically in the parietal lobe (ANOVA, p = 0.0008; Kendall's Tau rank correlation, p = 0.059, Figure 4h). Moreover, one individual with the worst cognitive performance, Mini–Mental State Examination (MMSE) score of 12, displayed the highest level of CDKN2A expression, and high molecular weight tau (Figure 4i). Collectively, these findings led us to conclude that NFTs were directly linked to senescence‐associated Cdkn2a upregulation, which in turn was a strong predictor of neurodegeneration and cognitive decline. Table 1. Human postmortem brain characteristics Control (n = 10) PSP (n = 14) p‐Value Age at death (years) 85.70 ± 2.81 83.86 ± 3.08 0.6765 Sex (M/F) 6/4 9/5 N/A Last MMSE score 27.67 ± 0.87 (n = 9) 21.00 ± 2.02 0.0194 Brain mass (g) 1,169 ± 17.83 1,139 ± 43.21 0.5800 Total tangles 4.03 ± 0.77 7.64 ± 0.66 0.0017