Old age alters inflammation and autophagy signaling in the brain, leading to exacerbated neurological outcomes after spinal cord injury in male mice

Abstract

Older patients with spinal cord injury (SCI) have different features with regard to neurological characteristics after injury. Recent large-scale longitudinal population-based studies showed that individuals with SCI are at a higher risk of developing dementia than non-SCI patients, indicating that SCI is a potential risk factor for dementia. Aging is known to potentiate inflammation and neurodegeneration at the injured site leading to impaired recovery from SCI. However, no research has been aimed at studying the mechanisms of SCI-mediated cognitive impairment in the elderly. The present study examined neurobehavioral and molecular changes in the brain and the underlying mechanisms associated with brain dysfunction in aged C57BL/6 male mice using a contusion SCI model. At 2 months post-injury, aged mice displayed worse performance in locomotor, cognitive and depressive-like behavioral tests compared to young adult animals. Histopathology in injured spinal cord tissue was exacerbated in aged SCI mice. In the brain, transcriptomic analysis with NanoString neuropathology panel identified activated microglia and dysregulated autophagy as the most significantly altered pathways by both age and injury. These findings were further validated by flow cytometry, which demonstrated increased myeloid and lymphocytes infiltration at both the injured site and brain of aged mice. Moreover, SCI in aged mice altered microglial function and dysregulated autophagy in microglia, resulting in worsened neurodegeneration. Taken together, our data indicate that old age exacerbates neuropathological changes in both the injured spinal cord and remote brain regions leading to poorer functional outcomes, at least in part, through altered inflammation and autophagy function.

1. Introduction

The incidence of traumatic spinal cord injury (SCI) in the elderly has grown rapidly, with over 20% cases occurring in those over 65 years of age (Ikpeze and Mesfin, 2017). Although aging is a key risk factor for dementia, clinical evidence, including large-scale longitudinal population-based studies (Craig et al., 2017; Huang et al., 2017; Mahmoudi et al., 2021; Yeh et al., 2018), shows a higher incidence of cognitive decline, neurodegenerative disorders, and psychological/somatic comorbidities after SCI (Chiaravalloti et al., 2020; Craig et al., 2017; Sachdeva et al., 2018; Sakakibara et al., 2009). Clinical magnetic resonance imaging studies reveal neuropathological changes in the brain following SCI (Li et al., 2020a). Chronic neuroinflammation, decreased hippocampal neurogenesis, and increased neuronal endoplasmic reticulum (ER) stress have been reported after SCI in the brains of young adult mice and rats (Allison et al., 2016; Jure et al., 2017; Knerlich-Lukoschus et al., 2011; Li et al., 2022b; Luedtke et al., 2014; Maldonado-Bouchard et al., 2016; Wu et al., 2014a; Wu et al., 2016; Wu et al., 2014b; Zhao et al., 2007). These were associated with posttraumatic hyperesthesia, impaired cognition, and depression-like behavior. However, few studies have examined mechanistically how SCI affects the brain in young adult versus aged subjects. Such information is needed for the design of targeted interventions to limit the risk of cognitive decline or depression after SCI.

Clinical trials report that targeting inflammation improves mood and pain after SCI (Allison and Ditor, 2015; Allison et al., 2016). We and others have shown that neuropsychological impairment after SCI is caused, at least in part, by microglial-mediated chronic inflammation in the brain (Li et al., 2020a). Aging microglia show altered physiology, with evidence of cellular senescence and immune dysfunction (Ritzel and Wu, 2023). We recently reported that a subpopulation of microglia in older mice adopted a unique dysfunctional phenotype defined by changes in phagocytosis, oxidative stress, lysosomal content and autophagy, lipid and iron accumulation, metabolic alterations, pro-inflammatory cytokine production, and senescent-like features (Ritzel et al., 2023; Ritzel et al., 2022). However, whether age-related alterations in microglial and immune function are exacerbated in the brain after SCI is unknown.

The autophagy-lysosomal pathway is essential for intracellular lipid, protein, and organelle degradation and quality control (Mizushima et al., 2008). We have previously shown that autophagy is dysregulated in injured central nervous system (CNS) following trauma (Wu and Lipinski, 2019). More recently, we demonstrated in both SCI and traumatic brain injury (TBI) models that perturbation of autophagy alters inflammatory responses: high levels of autophagy flux are associated with anti-inflammatory responses, whereas low levels promote pro-inflammatory phenotypes (Hegdekar et al., 2023; Li et al., 2022a). Thus, inhibition of autophagy-lysosomal function could contribute to both neuronal cell damage and neuroinflammation observed in aging brain. Recent data (Carmona-Gutierrez et al., 2016; Lipinski et al., 2010; Lu et al., 2004) demonstrate an age-dependent decline in expression of autophagy genes and decreased lysosomal function. Although autophagic mechanisms have been found to decrease with age in many experimental models (Loeffler, 2019), how they are altered in the aging brain after SCI is unknown.

In the present study, we assessed the behavioral phenotypes of locomotion and cognition as well as the histochemistry outcomes of injured tissue from both young and aged mice after SCI. Moreover, we analyzed the post-injury transcriptomic changes in the somatosensory cortex and hippocampus, which was further validated by flow cytometry. Given that chronic inflammation potentiation and autophagy impairment are two ubiquitous features of the aging CNS (Aman et al., 2021), here, we examine the hypothesis that age-related inflammation and defects in autophagic function can exacerbate neurodegeneration in the brain, and long-term neurological functional recovery in old mice following SCI.

2. Materials and Methods

2.1. Mouse spinal cord contusion model

All animal experiments and surgical procedures were approved by the Institutional Animal Care and Use Committee (IACUC) at the University of Maryland School of Medicine. Young adult (10–12 weeks, 2.5–3.0-month-old) and aged (18-month-old) male C57BL/6 mice were obtained from Charles River Laboratories via NIA and housed on a 12 hours (h) light/dark cycle with food and water ad libitum. Moderate spinal cord contusion injury was conducted using the Infinite Horizon spinal cord impactor (Precision Systems and Instrumentation) as previously described (Li et al., 2022b; Wu et al., 2016). Briefly, mouse thoracic spinal cord was exposed by laminectomy under anesthetization with isoflurane. The spinal column was stabilized with bilateral steel clamps and a midline spinal contusion at T10 level with a force of 60 kilodyne (kdyn) was conducted. Following surgeries, the bladders of injured mice were manually voided 2–3 times daily until a reflex bladder was established. Sham mice underwent the same procedure except for contusion. After surgeries, mice were randomly assigned to groups based on their age. To minimize stress and fatigue, each behavioral test was performed on a different day.

2.2. Assessment of neurological function and data analysis

Locomotor function:

Basso mouse scale (BMS) and the BMS subscore were recorded on day 1, day 3, and weekly thereafter for up to 49 days post-injury. The testing mouse was placed in a rectangular plastic open field (62 × 42 cm dimensions) with flat and smooth floor for 4-minute continuous observation by two trained researchers blinded to its group information. Animals were rated in a scale of 0 to 9 based on the standards as described previously (Basso et al., 2006).

Y-maze test:

This test was performed 1 day before SCI (baseline) and on day 49 post-injury. The Y-maze instrument (Stoelting, Wood Dale, IL) consisted of three identical arms (35 cm long, 5 cm wide, and 10 cm high) at an angle of 120° with respect to each other (Ritzel et al., 2022). The distal 30 cm of each arm was defined as arm A, B, C. The rest was defined as the center. The mouse was placed at the end of a randomly picked arm facing the center and allowed to explore the maze freely for 6 minutes. An arm entry was defined as all four paws of the mouse entered the arm, and an alternation was designated when the mouse entered the three arms consecutively. The percentage of alternation was calculated as follows: total alternations x 100 / (total arm entries - 2). An arm return was defined as the mouse return to the same arm after entry to a different one. Its calculation is the same as the percentage of alternation. All the tests were videorecorded and analyzed by self-made software.

Novel object recognition (NOR) test:

The NOR, social recognition (SR), and novelty suppressed feeding (NSF) tests were conducted consecutively during 50 to 54 days post-injury. A Plexiglas open field with a 40 cm x 40 cm square gray floor and four of 35 cm high black walls were placed in a dark room with red light on (Ritzel et al., 2022). Mice were placed in the center and allowed to move freely for 5-minute habituation on the first day. Next day, two identical objects were placed on the diagonal line symmetrical to the center, which were at a distance of 12–13 cm from the close walls. One of the familiar objects were randomly replaced with a novel object on the third day for each testing mouse. The time mice spent with two objects was recorded using ANY-maze software (Stoelting) until a sum total of 30 s exploration time was reached.

Social recognition (SR) test:

The SR test was performed using a three-chambered rectangular apparatus (60 × 40 × 23 cm) made of transparent Plexiglas (Ritzel et al., 2023). It was divided into three equal chambers by two walls that each had a semicircular hole of 5 cm diameter in the bottom for free access to each chamber. Two identical wire mesh cylinder cups were placed in the corners of two side chambers separately for every single session. Each mouse was singly housed overnight then placed in the middle chamber for 3 minutes with the holes blocked by transparent partitions, which was followed by 10-minute free exploring with the partitions removed. Next day, a stranger mouse was introduced and randomly placed inside one of the empty cups. The testing mouse started from the middle chamber with the holes blocked and then freely explore all three chambers for 10 minutes with the partitions removed. Then, the testing mouse was led back to the middle chamber and the holes were blocked. A second novel stranger mouse was placed inside the other empty cup. After partitions removal, the testing mouse was once again allowed to freely explore all three chambers for another 10 minutes. All behaviors of the subject mice in the chambers were recorded and analyzed using ANY-maze software (Stoelting).

Novelty suppressed feeding (NSF) test:

All mice were weighed and singly housed, then underwent food deprivation for 24 hours before the test. A Plexiglas open field with a 40 cm x 40 cm square gray floor and four 35 cm high transparent walls was placed in a bright room (Li et al., 2022b). A petri dish filled with food pellets was fixed at the center of the open field floor. The testing animal was weighed again, then placed in a corner of the apparatus facing the wall and allowed to move freely. The latency from mouse entry to its first bite of food was recorded with a maximum of 10 minutes. The mouse was then returned to its home cage with food supply and the food-taking latency was recorded.

Multivariate data analysis of the behavior omics:

We used multivariate data analysis to gain a comprehensive understanding of all the behavior tests adopted in current study. The behavior omics data included BMS, BMS subscore, alteration percentage (Y-maze), arm return percentage (Y-maze), total arm entry (Y-maze), total distance (Y-maze), novelty preference (NOR), social preference (SI), social novelty preference (SI), latency in home cage (NSF), and latency in novel open field (NSF). The partial least squares discriminant Analysis (PLS-DA) was conducted to classify mice behaviors based on the group effect of age or injury using self-coded R language in RStudio based on the ropls and mixOmics (version 6.20.0) packages (Rohart et al., 2017). Moreover, the Mantel test was performed to reveal the relationship between mice’s locomotion and cognition behaviors. The related figure was made through the linkET (version 0.03) R package (Huang, 2021).

2.3. Tissue processing and histopathology

At 60 days post-injury, mice were intracardiac perfused with 4ºC saline followed by 4% paraformaldehyde. 10-mm long spinal cord segments centered at the lesion area were dissected out, embedded, and cut into 20-μm-thick sections placed serially on a set of precleaned microscope slides. Luxol fast blue (LFB, Cat# S3382, Sigma-Aldrich) staining was performed to visualize the spared white matter (SWM) (Li et al., 2022a). The section of the least amount of SWM was defined as the lesion epicenter. 200 μm and 400 μm rostral and caudal sections to the lesion epicenter were imaged at ×2.5 magnification. The total LFB-positive area of each section was calculated for assessment of SWM by ImageJ software (RRID:SCR_003070). For assessment of lesion volume, 5 mm rostral to 5 mm caudal sections spaced 1 mm apart around the lesion epicenter were stained with GFAP (1:1000; Cat# Z0334, Dako) and DAB (Cat# PK-6100, Vector Labs), then imaged in the same way. Quantification was conducted through the Cavalieri method in Stereo Investigator Software (MBF Biosciences) as previously described (Li et al., 2022a).

2.4. NanoString transcriptomic analysis

Following intracardiac perfusion with ice cold normal saline, the mouse brain was harvested. Bilateral somatosensory cortex and hippocampus were dissected out and fast-frozen in dry ice. Total RNA was extracted using RNeasy mini kit (Cat# 74104, Qiagen) with concentration measured and sent to the Institute for Genome Sciences at University of Maryland School of Medicine for NanoString Neuropathology panel. The transcriptomic raw data of mRNA read counts was introduced to “Advanced Analysis” in NanoString nSolver software (version 4.0), including normalization, pathway score assessment, gene differential expression analysis, and cell type profiling. Samples distributed outside the boundary of score distance in Orthogonal Partial Least Squares (OPLS) (R, ropls package, 1.22.0) were taken as outliers and excluded for further analysis. In-depth analyses were carried out with self-coded R language in RStudio. Heatmaps were generated based on the ComplexHeatmap package (version 2.13.2) (Gu et al., 2016). PCA and PLSDA graphs were produced using mixOmics package (http://mixomics.org/). Volcano graphs were created via the EnhancedVolcano package (version 1.11.3) (Blighe, 2018). Venn graphs were plotted by VennDiagram package (version 1.73).

2.5. Flow cytometry

Bilateral hemispheres of mice brains were isolated after sacrifice as described (Ritzel et al., 2023; Ritzel et al., 2022). The sample was mechanically ground into mince and passed through a 70 μm filter in complete Roswell Park Memorial Institute (RPMI) 1640 (Cat# 22400105, Invitrogen) medium. Then enzymic digestion was carried out by collagenase (Cat# 10269638001, 1 mg/mL; Roche Diagnostics), papain (Cat# LS003119, 5 U/mL; Worthington Biochemical), DNAse I (Cat# 10104159001, 10 mg/mL; Roche Diagnostics) with 0.5 M EDTA (Cat# 15575020, 1:1000; Invitrogen) at 37 °C on a shaking incubator (200 rpm) for 1 hour. The cell suspension was processed and transferred into FACS tubes, then incubated with Fc Block (Cat# 101320, Clone: 93; Biolegend) for 10 min on ice and stained for the following surface antigens: CD45-eF450 (Cat# 48–0451-82, Clone: 30-F11; eBioscience), CD11b-APC/Fire™750 (Cat# 101262, Clone: M1/70; Biolegend), and Ly6C-APC (Cat# 128016, Clone: HK1.4, Biolegend). Cells were then washed in FACS buffer, fixed in 2% paraformaldehyde for 10 min, and washed once more prior to adding 500 uL FACS buffer. Intracellular staining for Lamp1-PerCPCy5.5 (Cat# 121626, Clone: 1D4B; Biolegend), Thy1-AF700 (Cat# 105320, Clone: 30-H12; Biolegend), NeuN-PE (Cat# FCMAB317PE, Clone: A60; END Millipore), PE/Cyanine7 anti-mouse CD200 (OX2) (Cat# 123818, Clone: OX-90, Biolegend), Myelin CNPase-AF647 (Cat# 836408, Clone: SMI91; Biolegend), Synaptophysin-AF488 (Cat# MAB5258A4, Clone: Sy38; END Millipore), ATG7-AF700 (Cat# FAB6608N, Clone: 683906; R&D Systems) and P62/sqstm1-AF647 (Cat# 42822AF647, Novus Biologicals) was performed after fixation/permeabilization. Cyto-ID Autophagy Detection Kit (Cat# ENZ-51031-K200, Enzo Life Sciences) was used according to the manufacturer’s instructions. Data were acquired on a BD LSRFortessa cytometer using FACSDiva 6.0 (BD Biosciences) and analyzed using FlowJo (Treestar Inc.). Countbright™ Absolute Counting Beads (Invitrogen) were used to estimate cell counts per the manufacturer’s instructions. Data were expressed as cells/mg tissue weight. Leukocytes were first gated using a splenocyte reference (SSC-A vs FSC-A). Singlets were gated (FSC-H vs FSC-W), and live cells were gated based on Zombie Aqua exclusion (SSC-A vs Zombie Aqua-Bv510) (Ritzel et al., 2020; Ritzel et al., 2022).

2.6. Statistical analysis

All data are presented as mean ± SEM from the indicated number of independent experiments. All behavioral, histological, and ex vivo studies were performed by investigators blinded to group designations. Statistical analysis was performed using GraphPad Prism 8.4.2 (GraphPad Software, LLC) for most bar graphs, or SigmaPlot 12.0 (Jandel Scientific, San Jose, CA, USA) for BMS score and subscore, or R for transcriptomic data. Normal distribution of data was assessed with the Shapiro-Wilk test. For multiple comparisons, one-way or two-way ANOVA were performed followed by Tukey’s multiple comparisons post-hoc test for parametric (normality and equal variance passed) data. Nonparametric data were analyzed by Mann-Whitney test. BMS scores and subscores were analyzed with two-way ANOVA for repeated measurements followed by Sidak’s multiple comparisons post-hoc test. Significance was set at p ≤ 0.05 and detailed in figure legends.

3. Results

3.1. Old age exacerbates neurological dysfunction after SCI

To determine whether old age impacts neurobehavioral outcomes after SCI, we assessed young adult and aged male C57BL/6 mice using a battery of behavioral tests as illustrated in Fig. S1A. The body weight of animals was monitored before and after injury (Fig. S1B). Our data showed that the body weights of 18-month-old mice were significantly higher than those of 10–12 weeks old mice (2.5–3.0 months old). However, SCI-induced weight loss was evident at 49d post-injury in both young and the older groups. Actual injury force and displacement were detailed in Fig. S1C. Statistical details are listed in Table S1. Although no significant differences between groups in the actual force were observed, the resulting displacements of the heavier aged mice were significantly lower than those generated from young animals, suggesting that the composition of the spinal cord has changed with age - perhaps the extracellular matrix in the spinal cord is harder with age, causing reduced displacement.

Longitudinal hind limb motor function was evaluated using the BMS on day 1 and day 3 after injury and weekly thereafter for up to 7 weeks (Fig. 1A, Statistical details in Table S2). Both aged and young sham mice had full scores of 9. After moderate SCI, all injured mice showed rapid increase of BMS score in the first two weeks, indicating a spontaneous recovery, and reached a plateau after 4 weeks post-injury. By day 7 after injury, aged mice had significantly reduced BMS scores compared with young animals. Significant differences between groups remained through 49 d after injury. Beginning 21 d post-injury, BMS sub-scores of Aged SCI group were significantly lower than Young SCI group. This reduction remained through 49 d after injury. Together these data show that old age worsens locomotor functional deficits after SCI.

Figure 1. Aged male mice exhibit exacerbated motor functional deficits and neurological dysfunction at 2 months after SCI.

(A) Old age worsened locomotor functional deficits after SCI. Locomotor function was measured by BMS score and BMS subscore in both young adult and aged mice at multiple post-injury time points. N=18 (Young SCI) and 15 (Aged SCI). Two-way ANOVA with repeated measurement following by Sidak’s multiple comparisons test was performed combined with Young Sham (n=16) and Aged Sham (n=15). (B-C) SCI in aged mice aggravated cognitive functions assessed in Y-maze test as alteration and arm return (B) and novelty preference in novel object recognition (NOR) test (C). (D) Reduced social novelty preference was observed in aged SCI mice assessed in social recognition (SR) test. (E) Depressive-like behavior was evaluated as latency in novel arena in novelty suppressed feeding (NSF) test. Both age and injury significantly increased food-taking latencies in novel arena. n=16 mice (Young Sham group), 18 mice (Young SCI group), 15 mice (Aged Sham group), and 14 mice (Aged SCI group). Two-way ANOVA with Tukey’s post hoc test was performed for (B-E). *, #, $: p<0.05; **, ##: p<0.01; ***: p<0.001.

Cognitive function was measured using the Y-maze for hippocampus-dependent spatial working memory and novel object recognition (NOR) test for recognition memory. In the Y-maze test, the percentage of spontaneous alteration and alternate arm return were adopted to access the short-term memory of the four groups. Aged mice had comparable baseline level of alternation but higher one of arm return compared to young mice before SCI (Fig. S1D, Statistical details in Table S1). After the injury, both aged and young mice showed significantly lower spontaneous alteration and higher arm return versus sham animals (Fig. 1B). On the other hand, aged mice showed significantly lower total arm entries and total distance compared to young mice in the baseline (Fig. S1E) and post-injury phase (Fig. S1F–G). Statistical analysis indicated significant group effects of age and injury for these parameters, which suggested that Aged SCI group had more severe working memory impairments and decreased locomotion activities. In the NOR test, all mice took comparable time exploring the two identical objects in the open field during sample phase, indicating no object bias (Fig. S1H). In choice phase, however, the time for exploring the newly-introduced object of Aged SCI group was further reduced versus Young SCI group, resulting in significantly lower novelty preference (Fig. 1C). Statistical analysis indicated significant group effects of age and injury as well as their interaction, which implied that learning and memory in aged mice was further impaired after SCI compared to the young group.

To assess depression-like phenotype, we subjected mice to three-chamber social recognition (SR) test and novelty suppressed feeding (NSF) test. With an unbiased preference to the chambers (Fig. S1I), the four groups showed comparable social preference to a stranger mouse than an empty cup. When another new mouse was introduced, only Aged SCI group showed significantly lower social novelty preference compared to other groups (Fig. 1D, Statistical details in Table S2). The results suggest potential functional deficits in olfaction, memory or social interest mediated by SCI in aged mice. In NSF test, the four groups showed no difference of food-taking latency in home cages with significant age effect (Fig. S1J). While in the novel arena, significant group effects of age and injury and their interaction were observed based on the difference between sham groups and the increases of food-taking latencies after SCI (Fig. 1E). These data suggest that the aged mice are more vulnerable to stimuli that elicit stress, anxiety, and depression-like states.

To depict the total behavioral profiles of the animals from different groups, all the behavioral data were applied for Partial Least Squares Discriminant Analysis (PLS-DA) after data normalization in RStudio. Fig. S1K displays the sample plot of the four groups based on the first two components, which indicates they clustered by group along the first component with 48.9% variations and the second component with 8.6% variations. Then, we combined Pearson’s correlation coefficient with Mantel Test to estimate the correlations between the two behavioral sets, locomotion and cognition based on the data clustered by age or injury (Fig. S2), which demonstrated the relationship between motor functional deficits and cognitive impairments following SCI. The correlation in Pearson’s correlation coefficient is the linear correlation ranging from −1 to 1 reflecting the strength and direction of the relationship between any two animals’ score sets from motor or cognitive tests. The correlations in Mantel’s test reflect if the distances between two samples in different coordinate systems defined by the parameters of a data set (locomotion, cognition, or a single behavior test) are significantly correlated. In young mice, either Locomotion or Cognition exhibited significant Mantel’s correlation coefficient with any test included. Specifically, in Pearson’s correlation coefficient, Alteration and Arm return in Y-maze, along with Novelty preference in NOR, were significantly correlated with BMS and BMS subscore, Total arm entry and Total distance in Y-maze respectively (Fig. S2A). These correlation statistics increased with higher significance in aged mice (Fig. S2B). However, Locomotion in aged animals demonstrated weakened correlations with most Cognition parameters in Mantel’s test and vice versa, implying potential differences from the young mice. For SCI only behavior data, Alteration and Arm return in Y-maze had significant correlations with the four locomotion parameters. However, neither Locomotion nor Cognition showed significant Mantel’s correlation with the behavioral parameters in the other category (Fig. S2C). Meanwhile, Sham only data did not show noticeable significant correlations (Fig. S2D). These results suggest that the fundamental differences caused by age and injury are highly correlated with their behaviors of locomotion and cognition.

3.2. SCI in aged mice causes larger tissue damage

To determine if the observed behavioral exacerbation in aged mice may relate to decreased remyelination of spared axons, spinal cord sections from injured mice perfused at 8 weeks were stained with Luxol fast blue (LFB) and spared white matter (SWM) area was quantified at 2-mm intervals rostral and caudal to the injury epicenter. Representative LFB stained sections at 2 mm rostral or caudal to the epicenter of each subject illustrate the differences in myelinated WM area between young and aged animals (Fig. 2A). Statistical analysis indicated that aged mice had significantly reduced SWM at the epicenter after SCI compared to the young animals (Fig. 2B). Furthermore, SCI-induced lesion volume/cavity formation was measured with GFAP/DAB staining at 8 weeks after SCI and analyzed by unbiased stereological techniques (Fig. 2C–D). The average lesion volume assessed for the aged mice was significantly enlarged compared to young animals. This expansion occurred in both white and gray matter, with an overall increase in cavity formation and tissue loss. Thus, these results suggest that SCI causes aggravated tissue damage in older mice.

Figure 2. Old age exacerbates tissue damage at 2 months after SCI.

(A) Representative Luxol fast blue (LFB) stained sections at 2 mm rostral or caudal to the epicenter of each subject illustrate the differences in myelinated spared white matter (SWM) area between young and aged animals. (B) Aged SCI mice showed significantly reduced SWM area at the injury epicenter compared to young injured animals. SWM area was quantified at 2-mm intervals rostral and caudal to the injury epicenter. Unpaired t test was performed for two injured groups at different sites. (C) Representative GFAP-DAB staining images of spinal cord sections showed the lesion area at the epicenter of young or aged mouse. (D) The average lesion volume was significantly enlarged in old SCI mice vs. young group. Scale bar=200 μm. n=7 mice/group, *p<0.05; **p<0.01. Unpaired t-test was performed.

3.3. SCI in young and aged mice lead to distinct RNA transcriptome profiles in the brain

To address age-related differences in the transcriptional response to SCI, somatosensory cortical (Fig. 3) and hippocampal tissues (Fig. 4) were sampled from young and old mice at 2 months post-injury. Using the NanoString Neuropathology panel, we examined transcriptional changes for 760 genes within six fundamental themes of neurodegeneration: neurotransmission, neuron-glia interaction, neuroplasticity, cell structure integrity, neuroinflammation, and metabolism. The mRNA reading counts of all the genes were scaled by individual mouse and clustered into two blocks by K-means method based on Aged SCI group (Fig. 3A–4A). In the somatosensory cortex, block 1 contains downregulated genes and block 2 includes upregulated ones for Aged SCI group. While in the hippocampus, compared to the baseline in Young Sham mice, most genes were universally upregulated in other groups. Principal Components Analysis (PCA) of the same datasets demonstrated the in-group similarities as well as between-group differences in both brain regions (Fig. 3B–4B). For the somatosensory cortex, PC1 was the major principal component with a contribution of 33.9% gene variations separating injury groups from sham groups, which may represent injury effects. PC2 contained 14.1% gene variations and separated aged mice from young groups, which may represent age effects. For the hippocampus, Young Sham group is vastly far from other groups. Age or injury effects shift 57.9% gene variations along PC1 in the same direction. While 7% gene variations along PC2 drive young or aged groups towards opposite directions after SCI.

Figure 3. SCI leads to distinct RNA transcriptome profiles in the somatosensory cortex between aged mice and young adult animals.

(A) The genes in NanoString Neuropathology panel exhibited different expression profiles by group visualized in the heatmaps of z-scores. The heatmap was labeled with top 10 genes from the 1st and 2nd principal components (PC) in PCA analysis. (B) The four groups clustered into separated pools in PC1 × PC2 dimensions based on the PCA analysis of mouse cortical transcriptomic data. (C) Pathway scoring showed up/downregulation of gene expression enriched in different pathways of Aged SCI mice compared to other groups. (D) Gene differential expression analysis between Aged SCI and Young SCI was visualized as volcano graph. (E-F) Pathway enrichment analysis indicated specifically upregulations of activated microglia and autophagy in Aged SCI mice, showing typical genes with expression variations relating to inflammation (g) and autophagy (h). (G-H) Box plots exhibited dysregulation of typical genes in the two corresponding cortical pathways in Aged SCI mice. n=4-6 mice/group.

Figure 4. Old age and SCI lead to distinct RNA transcriptome profiles in mouse hippocampus.

(A-B) The heatmap of gene expression z-scores in mouse hippocampus formed different clusters by group labeled with top 10 genes from PCA analysis. (C) Pathway scoring showed major aging effect in the upregulations of most pathways in aged groups. (D) Gene differential expression analysis between Aged SCI and Young SCI was visualized as volcano graph. (E-H) Box plots of pathway enrichment analysis of activated microglia (E-F) and autophagy (G-H) indicated that gene variations relating to inflammation and autophagy were upregulated by aging with SCI. n=4–6 mice/group.

Through heatmap hierarchy clustering of the average z-scores for each group, along with the two-way ANOVA statistical analysis results followed by age, injury, and their interaction (Table S3–6), we identified “Activated Microglia” and “Autophagy” as the top two upregulated pathways in the cortex between young and aged SCI mice (Fig. 3C). To reveal the gene variations relating to these pathways, we performed differential expression (DE) analysis between Aged SCI and Young SCI groups, which showed that 172 out of 671 genes in the cortex (Fig. 3D) and 238 out of 668 genes in the hippocampus (Fig. 4D) changed significantly at mRNA level. Furthermore, based on the cortical transcriptomics, the pathway scores of “Activated Microglia” and “Autophagy” were calculated and displayed as box plots, next to which showing the differentially expressed genes (DEGs) involved in the corresponding pathways as z-score heatmaps of the four groups (Fig. 3E–F). The data demonstrates robust differences of Aged SCI group compared to others. Based on the statistical analysis of relevant gene sets (Table S3), mRNA levels of typical individual genes were displayed in Fig. 3G for “Activated Microglia” pathway, and in Fig. 3H for “Autophagy” pathway. Aged SCI mice exhibited high levels of Cd68, Trem2, Csf1, and Cd33 following SCI with significant group effects of age, injury, or the interaction (Table S4), indicating upregulated activities of macrophage lineage cells. The increase of Psmb8, an immunoproteasomal subunit, implied active inflammation with involvement of lymphocytes infiltrations. Reduction of the neuroprotective transcription factor Npas4 gene was also observed in the brain from aged SCI mice. Sqstm1, a key gene for autophagosome formation, along with Lamp1, Gusb, Galc, and Gaa that reflect lysosome activities, were highly upregulated with significant group effects of age and injury. However, Gga1, a gene mediating cargo transport from the trans-Golgi network to endosomes and lysosomes, was downregulated. Moreover, Optn, a key gene involved in autophagy processes and inflammatory responses, surged in Aged SCI group. These results suggest that both inflammation and autophagy pathways were dysregulated in the aged cortex following SCI.

To further analyze the connection between aging, SCI, and the behaviors reflective of cognitive impairment and depression that we observed in tested mice, hippocampal tissue was also analyzed. Interestingly, hippocampal transcriptomics demonstrate different patterns in the two pathways (Fig. 4E–H). Comparison of the total pathway scores indicates higher levels in aged groups without significant injury effects, however, analysis reveals that a big part of the DEGs has significant group effects of age and injury and their interactions (Table S5–6). Typically, Apoe, a gene regulating neuroinflammation in macrophages and microglia, has the most significant interaction effects in the pathway of “Activated Microglia” (Fig. 4E–F & Table S6). Its deficiency could aggravate neuroinflammation and lysosome dysregulation following injury. The gene Cul1, capable of attenuating inflammatory responses by NLRP3-related signaling pathways, was downregulated in aged hippocampus after SCI (Fig. 4F). We observed similar variations in the DEGs of “Autophagy” pathway with top interaction effects of aged and injury, including Atp6v0c, Atp6v0d1, and Atp6v1h (Fig. 4G–H & Table S6). All the three genes encode components of vacuolar ATPase, a multisubunit enzyme that mediates acidification of intracellular organelles, which is crucial for the normal functioning of endosomes, lysosomes etc. Their abnormal downregulations in mouse hippocampus following SCI suggest that the autophagy lysosomal pathway could be greatly tampered. The statistical analysis results of the relevant gene sets were included in Table S5.

Taken together, our results show that SCI leads to distinct transcriptomic profiles and diverse pathway regulations in old age and young adult mice as well as in different brain regions. Upregulation of activated microglia and dysregulation of autophagy-lysosome pathway in aged groups following SCI are pronounced.

3.4. Old age increases infiltration of lymphocytes and exaggerates microglial responses to SCI

Next, we investigated the cellular inflammatory response at 2 months after SCI. Microglia and leukocyte identification and characterization in both lesion area and the brain were performed using flow cytometry. The expression levels of CD45 and CD11b were used to distinguish microglia (CD45^intCD11b+), myeloid (CD45^hiCD11b+), and lymphocyte (CD45^hiCD11b-). At the injury site (Fig. 5A–B), SCI induced significantly increased number of microglia and lymphocytes in both young and aged groups. Greater myeloid infiltration was observed in aged SCI mice compared to aged sham animals, but not in young injury mice at this time-point. Nevertheless, marked microglial accumulation and increased infiltration of myeloid, as well as putative lymphocyte populations, were found in old mice at 2 months post-injury. Statistical data showed that the groups’ effects of age, injury, and their interaction are significant.

Figure 5. Old age increases infiltration of lymphocytes and exaggerates microglial responses to SCI.

Young and aged C57BL/6 mice were subjected to moderate SCI and both lesion area and the brain were extracted at 2 months post-injury for flow cytometry. (A-B) Representative dot plots depict the relative immune cell composition in the lesion area of the spinal cord (A). Cell counts normalized by tissue weight showed increased number of CD45^intCD11b+ microglia, CD45^hiCD11b+ infiltrating myeloid cells, and CD45^hiCD11b- infiltrating lymphocytes in the spinal cord of SCI mice (B). Marked microglial accumulation, increased infiltration of myeloid, and putative lymphocyte populations were found in old mice at 2 months post-injury. (C-D) Representative dot plots depict the relative immune cell composition in the brain (C). Decreased microglia along with increased myeloid and lymphocytes in aged brain showed significant group effect of aging rather than injury or their interaction compared to the young groups (D). Data was represented as mean ± SEM for Aged SCI group (n=6), Young SCI group (n=8), Aged Sham group (n=5), and Young Sham group (n=6). *, #, &: p<0.05; **, ##, &&: p<0.01; ***, ###: p<0.001. Two-way ANOVA with Tukey’s post hoc test was performed.

In the brain, decreased numbers of microglia were found in aged mice compared to young adult group (Fig. 5C–D). Statistical analysis showed an effect of age, but not injury. This is in agreement with the reports previously by our group (Ritzel et al., 2022) and others (Zoller et al., 2018), and may reflect age-related dystrophy and proliferative senescence. Although aged SCI mice showed further elevation of lymphocyte accumulation compared to young SCI mice, increased infiltration, and accumulation of myeloid and lymphocytes were detected in aged brain with significant age effect only.

3.5. Functions of microglia and neurons in the brain after SCI are altered with age

To better understand the effects of age on microglial function in the brain following SCI, flow cytometry was performed to examine phagocytosis and autophagy which were informed largely by our NanoString results indicated age-related, posttraumatic changes in these pathways after injury. Microglial phagocytosis was measured by intracellular detection of neuronal antigens, including Thy1, NeuN, and Synaptophysin. Consistent with our previous reports (Ritzel et al., 2023; Ritzel et al., 2022), microglial cells in aged groups showed higher levels of these neuronal markers with significant group effect of age, confirming increased activities of microglial phagocytosis in aged brain (Fig. 6A–C). These findings suggest that microglial phagocytosis of dead or dying neurons increase in brain with both age and SCI, consistent with our gene expression data.

Figure 6. SCI in aged mice alters microglia function and dysregulates microglia autophagy in the brain.

(A) Representative dot plots show Thy+ cells in the microglia (left panel). Increased percentage of Thy+ cells in the microglia was observed in aged SCI mice (right panel). (B) Representative histogram of NeuN in the microglia is indicated and increased MFI of NeuN+ in the microglia was observed in aged SCI group. (C) Representative histogram and MFI of Synaptophysin in the microglia. Aged sham mice showed increased MFI of Synaptophysin+ in the microglia vs young sham group. (D) Representative dot plots and percentage of Cyto-ID Autophagosome Dye+ cells in the microglia. (E-G) Representative histograms and MFI of p62 (E), ATG7 (F), and Lamp1 (G) in the microglia. Old mice elevated MFI of these markers in the microglia. Data was represented as mean ± SEM for Aged SCI group (n=6), Young SCI group (n=8), Aged Sham group (n=5), and Young Sham group (n=6). #, &: p<0.05; ##: p<0.01; ###, &&&: p<0.001. Two-way ANOVA with Tukey’s post hoc test was performed. SSC: side scatter; FMO: fluorescence minus one; MFI: Mean fluorescence intensity.

We recently reported that age-related deficits in autophagy function underlie chronic microglial activation and dysfunction following brain trauma (Ritzel et al., 2022). Therefore, we examined lysosome and autophagosome content in microglia (Fig. 6D–G). Aged mice showed greater formation of LC3-positive autophagosomes and increased expression level of p62 (Sqstm1), ATG7, and Lamp1, compared to young mice. Moreover, the two-way ANOVA multiple comparisons tests showed that several lysosomes and autophagosome components in microglia from aged SCI mice were significantly increased compared to young SCI animals. These data indicate that brain microglial phagocytosis and autophagic function are exacerbated with age and SCI, consistent with our NanoString gene signature.

We have previously shown an approach for identifying neuronal populations in the brain using flow cytometry (Ritzel et al., 2020). Using the same strategy (Fig. 7A), we examined changes in neuronal function of the brain following SCI. Reduced expression levels of synaptophysin and myelin CNPase were detected in neurons of aged groups with significant group effect of age (Fig. 7B–C). These findings indicate reduced neurons in brain with both age and SCI, suggesting increased neurodegeneration.

Figure 7. SCI in aged mice leads to neurodegeneration in the brain.

(A) Gating strategy is indicated for identifying neuronal populations in the brain. Representative dot plots show the identification of living, nucleated cells in single cell suspensions of brain tissue, based on Zombie Aqua and Cytophase violet staining pattern. After confirming the scatter reference gate for living, nucleated cells and validating the neuronal markers, we determined the specificity of our neuronal gating strategy using the neuronal markers CD200 and NeuN. (B-C) Representative histograms and MFI of Synaptophysin (B) and Myelin CNPase (C) in the neurons. Reduced expression levels of synaptophysin and myelin CNPase were detected in neurons of aged groups with significant group effect of age. Data was represented as mean ± SEM for Aged SCI group (n=6), Young SCI group (n=8), Aged Sham group (n=5), and Young Sham group (n=6). ##, &&: p<0.01. Two-way ANOVA with Tukey’s post hoc test was performed. SSC: side scatter; FMO: fluorescence minus one; MFI: Mean fluorescence intensity.

4. Discussion

Despite the increasing incidence of SCI in older individuals, there have been few experimental studies of SCI in aged animals, especially those examining posttraumatic brain changes. Here, we investigated the pathological changes at both the injury site and brain of young and aged mice following SCI, as well as potentially underlying cellular and molecular mechanisms. We showed that Aged SCI mice presented worse neurological function, including motor, cognitive, and depressive-like behaviors. These changes were associated with increased tissue damage in injured spinal cord and exaggerated microglia responses in the brain. Age-related deficits in autophagy were exacerbated in the brain following SCI. Together, our findings suggest that agerelated dysregulation of brain microglial phagocytosis and autophagic function as well as infiltration of lymphocytes contributes to chronic neuroinflammation in the brain, leading to neurodegeneration and poorer functional outcomes following SCI.

In agreement with previous findings (Fenn et al., 2014; Gaudet et al., 2021; Hooshmand et al., 2014; Takano et al., 2017), we observed aggravated locomotor functional deficits in aged male mice subjected to moderate SCI (>20-month-old), which is coincident with exacerbated tissue damage. Prior studies reported that aged spinal cord is more susceptible to traumatic injury in both mice and humans (Ikpeze and Mesfin, 2017; Piekarz et al., 2020). Similar results in rodent SCI models were reported even in 14-month-old female mice (Zhang et al., 2015; Zhang et al., 2019), which are middle-aged animals correspond to humans aged 38–47 years. These findings support the concept that aging alters the trajectory of SCI behavioral responses and pathology in lesion area. As the average age at the time of SCI is significantly increasing, there’s a heightened need for careful consideration of SCI management and therapy in elderly population.

One important observation of the present study is impaired cognition and neurological outcomes in aged male mice after SCI. We and others have previously reported neurological behavioral deficits including cognition, neuropathic pain, and anxiety/depression-like behaviors in young adult mice and rats following SCI (Li et al., 2020a; Li et al., 2022b; Luedtke et al., 2014; Maldonado-Bouchard et al., 2016; Zhao et al., 2007). Recently, Gaudet et al. reported increased spontaneous pain in 20-month-old female mice subjected to T9 contusion SCI (Gaudet et al., 2021). The current work is the first to report age-related cognition deficits after a moderate SCI, evidenced by significantly reduced novelty preference in both novel object recognition (NOR) and social recognition (SR) tests. Although aging declines learning and memory, we observed no difference in these tests between two sham groups, suggesting a critical role of SCI on aged mice. The Y-maze, NOR, and SR tests used in the present study are less dependent on locomotion, reflecting hippocampal and prefrontal-thalamic function. In a SCI injury-severity study, only severe injury mice revealed impairment in the step-down passive avoidance test, which reflects a fearmotivated learning task (Wu et al., 2016). While we acknowledge that motor deficits may be a confounding factor to interpreting cognitive test results, our method of measuring cognition with multiple behavior tests that complement each other adds validity to our observations on the rodent SCI model. In addition, increased neuropathic pain observed in aged SCI mice negatively affects cognition and depression (Gaudet et al., 2021). The novelty-suppressed feeding test (NSF) is often used as a measure of depression-like behaviors (Stedenfeld et al., 2011). Both aged and injury mice showed significantly increased the latency to find food in the novel arena, suggesting depression-like behavior. These findings accentuate the crucial need to consider age as a factor in SCI research in both preclinical and clinical settings.

Previous work has shown that injury to the thoracic spinal cord causes profound neuropathological changes in the brain in young adult animals (Li et al., 2020a; Li et al., 2020b; Li et al., 2022b; Wu et al., 2016; Wu et al., 2014b; Zhao et al., 2007). A recent study examining gene expression patterns in the brain after acute and sub-acute SCI, using transcriptome analysis with RNA sequencing, revealed that mitochondria dysfunction occurred at 3h post-injury, followed by increased inflammatory response and ER stress at 2 weeks after injury (Baek et al., 2017). However, the brain changes following SCI in old age are largely unknown. In the present study, by utilizing the NanoString Neuropathology panel directly targeting specific mRNAs, we unequivocally showed that SCI in old and young adult mice induce distinct transcriptomic profiles in the brain at 2 months post-injury. Comparisons between young and aged sham mice indicated genetic heterogeneity between cortex and hippocampus during aging. This is in agreement with a recent report that summarized the cellular and molecular heterogeneity of astrocytes and microglia in different brain regions in relation to aging and neurodegenerative diseases (Lee et al., 2022). Through heatmap clustering of the average z-scores for each group, our findings demonstrate that (1) the “Activated Microglia” and “Autophagy” are the top two upregulated pathways in the somatosensory cortex with aging and injury, but not in the hippocampus, and (2) these pathways become pronounced following SCI in the cortex from aged but not young adult animals. Noticeably, the “Autophagy” pathway is the only one boosted in aged mouse cortex following SCI with significant interaction effects of aging and injury, suggesting its potential key roles in the neuropathological process.

Brain and spinal cord aging lead to increased inflammatory activity, peripheral immune cell infiltration, and decreased autophagy efficiency. Previous work has found that cellular and molecular markers of inflammation in the injured spinal cord are acutely altered after SCI in aged animals (Fenn et al., 2014; Gaudet et al., 2021; Takano et al., 2017; Zhang et al., 2019). We observed similar changes in aged mice during the chronic phase of SCI, using a combination of ex vivo cellular assays and histological approaches. At the cellular level, increased microglial proliferation and infiltrating myeloid cells occurred at the injury site at 2 months in aged mice. Lymphocyte infiltration was also increased in old mice at this time-point. Similar changes have been reported in aged models of brain trauma and experimental stroke (Crapser et al., 2016; Ritzel et al., 2022), suggesting that this may be a conserved age-related response to CNS injury. These aged related cellular changes contribute to greater tissue damage at the injured site. In the brain, older mice showed fewer microglia compared to young adult animals, likely either due cell senescence and/or death, consistently with the previously reports (Ritzel et al., 2022; Zoller et al., 2018). However, myeloid cells and lymphocyte infiltration were prominent in old mice, with increased lymphocyte recruitment after chronic injury. To ascertain whether the changes of microglia and leukocytes in the brain after SCI were affected in old age, we performed an extensive profiling of cellular functions. The most pronounced effects of age were microglial phagocytosis and dysregulated autophagy. In general, older microglia, especially in injured mice, were more likely to engulf neuronal debris or form autophagosome or lysosome than their younger counterparts. Moreover, we demonstrate perturbations in synaptic function of aged neurons. These age-related alterations in inflammatory activity, phagocytosis, and autophagy at the cellular levels are consistent with the results from the NanoString analysis. It is known that brain aging leads to decline in autophagy efficiency, increasing the probability of protein aggregation and contributing to a higher prevalence of neurodegenerative diseases (Nah et al., 2015). Our data indicate that age related decline in autophagy and lysosomal function in microglia in the mouse brain was exacerbated by SCI. This was accompanied by increased brain inflammation and neurodegeneration, suggesting that perturbation of autophagy may provide a mechanistic link between SCI and posttraumatic brain dysfunction.

According to the report from the National SCI Statistical Center, SCI is more common in men (~80%). Despite sex differences have been widely reported in experimental models of SCI (Li et al., 2023; Li et al., 2022b; Stewart et al., 2021; Stewart et al., 2020), only male mice were chosen for the present study to reduce the number of animals and minimize variability of experimental outcomes affected by female hormones. Due to the fact that SCI is more common in older females (Raguindin et al., 2021), including aged female mice is required for future investigation. In addition, only somatosensory cortex and hippocampus were investigated for transcriptomics while the whole brain for flow cytometry, which limited our neuroanatomical understanding of structure-function changes in areas critical for learning and memory such as the amygdala, the cerebellum, and the prefrontal cortex. Future studies can validate the spatial expression profile of these biomarkers via immunohistochemistry in brain sections.

In summary, using a battery of neurological behavioral tests that are less dependent on motor function, we show that SCI in aged mice aggravates tissue damage and neurological dysfunction. Our histological, cellular, and molecular findings provide complementary evidence that SCI in aged mice increases pathophysiological responses involving microglial activation and the autophagy-lysosome pathway in the brain, exacerbating neurodegeneration and neurological dysfunction. Thus, these data provide insight into the mechanisms of SCI-mediated brain dysfunction in aged animals.

Highlights.

• SCI in old mice aggravated tissue damage and neurological dysfunction

• Transcriptomes identified activated microglia and dysregulated autophagy in the brain

• Old age increases infiltration of myeloid and lymphocytes in the brain after SCI

• SCI in aged mice altered microglial function and dysregulated autophagy in microglia

• Old age after SCI exacerbated neurodegeneration in the brain