TRAF6-Mediated Ubiquitin Signaling Drives Long-Term Neurodegeneration in a Mouse Model of Chronic Traumatic Encephalopathy

TRAF6-Mediated Ubiquitin Signaling Drives Long-Term Neurodegeneration in a Mouse Model of Chronic Traumatic Encephalopathy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article TRAF6-Mediated Ubiquitin Signaling Drives Long-Term Neurodegeneration in a Mouse Model of Chronic Traumatic Encephalopathy Jong-Il Choi, Dain Lee, In-Hyung Lee, Minseop Kim, Sieun Choi, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6652049/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Chronic traumatic encephalopathy (CTE) is a progressive neurodegenerative disease leading to cerebral complications. It is triggered by single or repetitive traumatic brain injury during contact sports or combat activities. Due to diagnostic limitations, i.e., being restricted to postmortem analysis, understanding of CTE remains incomplete. While acute CTE mechanisms have been studied, the long-term effects remain inadequately explored. We investigated long-term CTE mechanisms using mouse models with 3- and 6-month progression. The 6-month model showed increased neurodegeneration and upregulation of ubiquitin signaling pathway genes, identifying TRAF6 as the central node. Accordingly, TRAF6 suppression using AAV9-delivered shRNA after brain injury protected against damage and behavioral deficits. However, TRAF6 knockdown in uninjured animals induced CTE-like changes, suggesting trauma activates compensatory mechanisms. Circulating microRNAs from blood serum reflect these brain changes, offering potential for non-invasive diagnostic approaches. Our findings indicate TRAF6 mediated signaling regulate long-term CTE pathology and present targets for therapeutic development. Biological sciences/Neuroscience/Blood–brain barrier Biological sciences/Neuroscience/Molecular neuroscience Biological sciences/Molecular biology/Proteolysis/Ubiquitylation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Traumatic brain injury (TBI) is brain damage from external forces like contusions, falls, traffic accidents, and sports impacts. TBI is classified as acute or chronic and by severity as mild, moderate, or severe. Mild TBI is typically referred to as a concussion, whereas moderate-to-severe TBI is often associated with loss of consciousness and lasting neurological deficits. 1 – 3 When TBI is sufficiently forceful or repetitive, it can lead to chronic traumatic encephalopathy (CTE), a progressive neurodegenerative condition that persists long after the initial injury. The progression from TBI to CTE is driven by the initial insult and secondary injury mechanisms, including oxidative stress and chronic inflammation. 4 – 6 CTE is most frequently observed in athletes and military personnel, who are regularly exposed to repetitive head trauma during high-intensity physical activity. 7 – 9 Currently, there is no established diagnostic method for CTE. The first CTE case in a military veteran was reported in 2011, and defining its diagnostic criteria only began a decade ago at the NINDS/NIBIB consensus meeting. 5 , 10 , 11 This meeting established hyperphosphorylated tau accumulation as a central pathological feature of CTE. Although evidence suggests that CTE progresses into a chronic neurodegenerative process characterized by inflammation, misfolded proteins, synaptic dysfunction, neuronal loss, and neural network disruption, its pathophysiological mechanisms remain poorly understood, with diagnosis still confined to postmortem histopathological examination and no effective treatment established, highlighting a significant gap driven by multiple contributing factors. 4 , 9 , 12 , 13 First, mechanistic studies rely on animal models examining only short-term effects within weeks of injury, while models capturing long-term TBI-related neurodegeneration are lacking. 14 – 18 Secondly, while tau pathology has been the focus of CTE studies, additional molecular pathways beyond phospho-tau are involved. The behavioral phenotypes of CTE differ from classical tau-driven dementias like Alzheimer's disease, suggesting distinct mechanisms. 15 , 19 – 24 Third, because CTE arises from acquired injuries rather than genetic mutations, establishing animal models without physical trauma remains difficult. Given CTE's recent recognition as a public health concern, understanding of its pathophysiology remains early. CTE symptoms develop gradually and may mimic other neurological disorders, leading to delayed diagnosis until irreversible damage occurs. Therefore, improving early detection and understanding long-term injury mechanisms are priorities. Accordingly, our goal is to establish a reliable CTE model, identify central nodes with therapeutic potential, and assess whether brain alterations are reflected in circulating biomarkers to inform future diagnostic strategies. In this study, we developed a chronic TBI model to investigate long-term CTE mechanisms. We compared brain changes at 3- and 6-month post-injury and selected the 6-month model based on pathogenic pathway gene expression. This revealed TRAF6's strong implication in CTE progression. Using AAV9-delivered shRNA, we examined TRAF6 suppression effects and assessed systemic changes through serum microRNA profiling. Results Pathological characterization indicates that the chronic CTE-6m model is better suited for long-term CTE studies We established a CTE mouse model using a repetitive closed-head impact protocol in C57BL/6 mice. Mice received five impacts over two weeks by releasing a 50‑g weight onto the skull (Fig. 1 A,B). Animals were maintained for three (CTE‑3m) or six (CTE‑6m) months for chronic pathological development. Behavioral assessments were conducted two weeks prior to euthanasia. Behavioral phenotype was first evaluated using the open-field (OF) test, where mice were placed in an arena to record time spent in central versus peripheral zones (Fig. 1 C). Uninjured controls (CTRL) and CTE‑3m mice spent minimal center time, reflecting normal anxiety behavior. CTE‑6m mice (n = 10) showed increased center‑zone time compared to CTRL (n = 10; one-way ANOVA; Tukey's post hoc; p = 0.0497) and CTE‑3m (n = 10; p = 0.0325) groups. No difference was found between CTRL and CTE‑3m groups (p = 0.9796). Immobile time also increased only in CTE-6m mice (n = 8) compared to CTRL (n = 8; one-way ANOVA; Tukey's post hoc test; p < 0.0001) and CTE-3m (n = 8; p < 0.0001) groups. No difference was found between CTRL and CTE‑3m groups (p = 0.4406). Second, animals were assessed with the Y‑maze test (Fig. 1 D). While alternation rates, exploring arms sequentially, did not differ between groups (n = 10 for all; one-way ANOVA; Tukey's post hoc; p = 0.0702), total arm entries decreased in CTE‑6m (n = 10) mice versus CTRL (n = 10; one-way ANOVA; Tukey's post hoc; p = 0.0359) and CTE‑3m (n = 10; p = 0.0038). No difference existed between CTRL and CTE‑3m groups (p = 0.6242). Taken together, increased immobility in the center zone of the OF test and decreased exploratory activity in the Y-maze test indicate apathy-like behavior in CTE-6m mice. Based on the behavioral phenotypes, we conducted immunohistochemical analysis. We examined three key parameters: BBB disruption, neuronal cell death in cortex and hippocampus (Fig. 1 E). Prussian blue staining showed minimal ferric iron deposits in CTE‑3m mice brain tissue (Fig. 1 F). Contrastingly, CTE‑6m mice displayed pronounced ferric iron deposition in the cortex, particularly the cingulum bundle, indicating severe BBB disruption. H&E staining assessed cellular morphology and apoptosis (Fig. 1 G,H). One-way ANOVA with Dunnett's post-hoc test showed significant increases in pyknotic cells in the cortex of CTE‑3m (n = 6; p = 0.0075) and CTE‑6m (n = 6; p < 0.0001) groups versus controls (n = 6). The corpus callosum (CC) showed significant narrowing in CTE‑6m (n = 6; Kruskal-Wallis test; Dunn's post hoc; p = 0.0347) and CTE‑3m (n = 6; p = 0.0257) mice compared to controls (n = 6). A similar pattern was observed in the striatum, which is a critical component of the basal ganglia involved in dopaminergic signaling and regulation of goal-directed behavior. 25 One-way ANOVA with Dunnett’s post hoc analysis revealed that the striatum was significantly impaired in both the CTE‑3m (n = 6; p = 0.0118) and CTE‑6m (n = 6; p = 0.0011) groups compared to controls (n = 6). The hippocampus, a region central to learning and memory, showed increased cell death in the CTE‑6m group (n = 6) compared to controls (n = 6; one-way ANOVA; Dunnett's post hoc test; p = 0.0006). No differences were found between control and CTE‑3m groups (n = 6; p = 0.0529). High-magnification images of CA1 and CA3 revealed neurodegeneration in CTE‑6m mice hippocampus. We also evaluated phospho‑Tau (pTau Ser202, Thr 205; AT8) alongside microglial activation (IBA1), reactive oxygen species (ROS), and phosphorylated TDP‑43 (pTDP43). Analysis was performed using immunofluorescence (IF) microscopy for ROS in cortical regions, while western blotting and PCR quantified protein and gene expression across the brain (Fig. 2 A). Results showed CTE severity correlated with increases in AT8, IBA1, and ROS levels, while pTDP43 decreased with cognitive decline and BBB deterioration shown in previous findings (Fig. 2 B). Whole‑brain western blot analyses showed AT8 levels were elevated in CTE‑6m (n = 6) compared to controls (n = 6; one-way ANOVA; Tukey's post hoc; p = 0.0036) and CTE‑3m (n = 6; p = 0.0032) (Fig. 2 C, D). No differences in AT8 expression were found between control and CTE‑3m (p = 0.9977). To investigate cortical tau pathology, we differentiated between neuronal and glial AT8 immunoreactivity. Neuronal AT8 was significantly elevated in CTE‑3m (n = 9; one-way ANOVA; Tukey's post hoc; p = 0.0492) and CTE‑6m (n = 10; p = 0.0016) compared to control (n = 9), with greater accumulation at 6 months, though not statistically significant between CTE groups (p = 03599). Glial AT8 increased significantly only in CTE‑6m (n = 9; one-way ANOVA; Tukey's post hoc) versus control (n = 8; p = 0.0244) and CTE‑3m (n = 9; p = 0.0258), with no difference between control and CTE-3m (p = 0.9934) (Fig. 2 E–H). Cortical pTDP43 showed significant reduction in CTE‑6m (n = 8; Kruskal-Wallis; Dunn's post hoc) compared to control (n = 9; p 0.9999) (Fig. 2 I). Cortical IBA1 immunoreactivity showed enhanced microglial activation in CTE‑3m (n = 7; one-way ANOVA; Tukey's post-hoc test; p = 0.0061) and CTE‑6m (n = 8; p = 0.0112) versus controls (n = 7) (Fig. 2 J). Cortical ROS accumulation, quantified via relative fluorescence, was significantly elevated in the CTE‑6m group (n = 9; Kruskal-Wallis; Dunn's post hoc) compared to control (n = 9; p = 0.0054) and CTE‑3m (n = 7; p = 0.0059) groups, with no difference between control and CTE‑3m (p > 0.9999) (Fig. 2 K). Finally, whole-brain gene expression analyses targeting Mapt, Aif1, Tardbp , and Gfap were performed (Fig. 2 L). Mapt expression increased significantly in CTE‑6m (n = 8; one-way ANOVA; Tukey's post hoc) versus control (n = 8; p = 0.0012) and CTE‑3m (n = 8; p = 0.0015), with no difference between control and CTE‑3m (p = 0.9931). Aif1 fold change increased in CTE-6m (n = 7; one-way ANOVA; Tukey's post hoc) versus control (n = 7; p = 0.0235) and CTE‑3m (n = 7; p = 0.0164) without difference between control and CTE-3m (p = 0.9843). Tardbp expression decreased in CTE‑6m (n = 8; Kruskal-Wallis; Dunn's post hoc test) compared to control (n = 7; p = 0.0002) and CTE‑3m (n = 7; p = 0.0213) groups, with no difference between control and CTE-3m (p = 0.4410). Gfap expression increased in CTE‑3m (n = 8; one-way ANOVA' Tukey's post hoc) versus control (n = 8; p = 0.0005) but reduced in CTE‑6m (n = 8; p = 0.0045 vs control; p = < 0.0001 vs CTE-3m), implying glial cell loss in CTE-6m. Collectively, these data underscore the robust neuropathological features of the CTE‑6m model, supporting its superior suitability for long-term CTE studies. Gene profiling indicates that TRAF6 plays a critical role in long-term CTE development Following confirmation of severe neurodamage features in the brain, bulk RNA-seq was performed to evaluate gene expression and identify key pathways associated with CTE‑6m model severity. Heatmap analysis showed different gene expression patterns between CTE and control groups and principal component analysis (PCA) revealed distinct gene expression profiles among CTE‑6m, CTE‑3m, and control groups (Fig. 3 A,B). Genes meeting p-value criteria were analyzed using STRING for protein network interactions. Top 10 clusters (DBSCAN Clustering; ε parameter = 2) showed the highest gene count in the signaling by receptor tyrosine kinases in cluster 1 (Fig. 3 C). The protein interaction map of Cluster 1 was presented in Fig. 3 D. Nodes represent proteins, while edges denote protein interactions, with edge colors indicating interaction types. Further analysis of nodes with the highest average combined scores, evaluating edge interactions between nodes, revealed that the top-ranked nodes are involved in ubiquitin signaling, with TRAF6 emerging as a principal mediator of the network, demonstrating the highest combined score supported by coexpression data, experimentally validated interactions, and automated text-mining analytics (Fig. 3 E). 26 – 28 The Cluster 1 gene set was reconfirmed in the bulk RNA-seq data, displaying significant upregulation in the CTE-6m group compared to the control (Fig. 3 F). The average fold change of Cluster 1 genes was markedly elevated in the CTE-6m group (n = 42; p < 0.0001; Kruskal-Wallis test with Dunn's post hoc) compared to CTRL (n = 42), and similarly significant upregulation was observed in the CTE-3m group (n = 32; p < 0.0001) versus CTRL (Fig. 3 G). To finally confirm the significance of Traf6 , the gene expression levels were quantified by whole-brain PCR analysis (n = 8 for all; one-way ANOVA with Dunnett’s post hoc test) (Fig. 3 H). An upregulated fold change was observed for Traf6 (p < 0.0001), Tlr4 (p = 0.0010), and Nfkb1 (p = 0.0023) in the CTE‑6m group compared to controls, while no significant changes were detected in the CTE-3m group (p = 0.9951 for Traf6 ; p = 0.7950 for Tlr4 ; p = 0.9638 for Nfkb1 ). Second, TRAF6 immunoreactivity was examined by IF microscopy (Fig. 3 I). Kruskal-Wallis testing revealed no significant difference in cortical TRAF6 expression between the CTE‑3m (n = 9) and CTE‑6m (n = 8; p > 0.9999) groups; however, both groups significantly differed from controls (n = 8; p = 0.0131 versus CTE-3m; p = 0.0016 versus CTE-6m) (Fig. 3 J). Conversely, whole-brain western blot analysis using one‑way ANOVA with Tukey's post hoc test (n = 6 for all) revealed a significant increase in TRAF6 in the CTE‑6m group compared to both control (p = 0.0211) and CTE‑3m (p = 0.0235), while no difference was observed between control and CTE‑3m (p = 0.9984) (Fig. 3 K,L). These findings indicate that TRAF6 accumulation is not confined to cortical regions but is distributed broadly across the brain, suggesting a widespread involvement in CTE pathology. Collectively, the observed elevation of TRAF6 expression, particularly in the 6-month CTE model, implies that TLR4 signaling mediated by TRAF6 and NFκB activation may serve as a central mechanism driving the chronic neuroinflammatory processes characteristic of advanced CTE stages. To delineate the mechanistic contribution of TRAF6 to CTE progression, subsequent investigations employed a TRAF6 knockdown (KD) mouse model, with a focused examination of the 6-month CTE cohort to elucidate the specific role of TRAF6 in modulating disease pathology. TRAF6 knockdown to investigate its role in long-term CTE progression Based on its significance, a TRAF6 KD model was established using TRAF6‑shRNA-AAV9 for neuronal transduction via intracerebroventricular (ICV) injection (Fig. 4 A, B). A non-targeting scrambled shRNA-GFP virus served as the sham control. One week post-injection, animals from both groups underwent CTE induction through five TBI episodes over two weeks, as previously described. Six months post-injection, all mice were euthanized, and blood serum and brain tissues were collected for analysis. Consequently, four experimental groups were defined: sham, TRAF6 KD (KD), TBI (transduced with scrambled virus), and TRAF6 KD with TBI induction (KD TBI). Several animals were euthanized 2 weeks after injection to verify appropriate viral transduction in the brain. Immunohistochemical analysis confirmed shRNA virus expression in sham and TRAF6 KD groups (Fig. 4 C). qPCR (n = 3 for all; unpaired t-test) showed downregulated Traf6 (p = 0.0260) in TRAF6 KD versus SHAM group (Fig. 4 D). After six months, viral expression was confirmed using GFP detection (Fig. 4 E). In the IF analysis performed 6 months post-injection, TRAF6 expression in both the KD TBI (n = 7; one-way ANOVA; Tukey’s post hoc test; p = 0.5578) and KD (n = 7; p = 0.9357) groups remained at levels comparable to those in sham controls (n = 7), suggesting minimal baseline expression (Fig. 4 F,G). Moreover, TRAF6 expression in the KD TBI (p = 0.0002) and KD (p = 0.0012) groups was significantly lower than in the TBI group (n = 7; p = 0.0053 vs. control). TRAF6 knockdown is neuroprotective in TBI, but Induces TBI-like pathogenesis without trauma After confirming TRAF6 KD, further analyses delineated its role in CTE progression. H&E staining showed the KD TBI group restored tissue architecture compared to the TBI group, which had many pyknotic cells (Fig. 5 A). More nuclei were observed in the KD TBI group's cortex. Also, hippocampal structures were more intact in the KD TBI group (Fig. 5 B). The CA1 and CA2 subregions of the KD TBI group maintained structures similar to the SHAM group (Fig. 5 C), while the TRAF6 KD model without TBI showed significant disruption (Fig. 5 A-C). Quantitative analysis based on nuclei counts within selected regions in the cortex, CA1, CA2, and hippocampus supported these findings (Fig. 5 D). In the cortex, one-way ANOVA (n = 8 for all; Tukey's post hoc test) showed the KD TBI group did not differ from SHAM (p = 0.9867) but differed from TBI (p = 0.0443) and KD (p = 0.0284) groups. Significant differences existed between sham and TBI groups (p = 0.0205), and sham and KD groups (p = 0.0128), with no difference between TBI and KD groups (p = 0.9973). For CA1 (n = 7 for all), CA2 (n = 7 for all), and hippocampus (n = 7 for all), the KD TBI group showed no difference from SHAM (p = 0.4090, 0.9996, 0.8955), but differed from TBI group (p = 0.0052, 0.0054, 0.0026). Both TBI (p = 0.0001, 0.0069, 0.0005) and KD groups (p = 0.0006, 0.0105, 0.0039) differed from sham, while TBI and KD showed no significant difference (p = 0.8875, 0.9980, 0.8188). A DHE assay was conducted to assess oxidative stress levels (Fig. 5 E,F). Quantitative analysis by one-way ANOVA with Tukey’s post hoc test (n = 12 for all) revealed that oxidative stress in the KD TBI group was significantly attenuated compared to that in the TBI group (p < 0.0001) and was comparable to that in the SHAM (p = 0.1580). In contrast, the KD group without TBI exhibited oxidative stress levels similar to those of the TBI group (p = 0.8467), differing from both the sham (p < 0.0179) and KD TBI (p < 0.0001) groups. Cognitive performance was evaluated using OF and Y-maze tests. One-way ANOVA with Tukey's post hoc test (n = 9 for all) showed the KD TBI group demonstrated improved cognitive function versus TBI group (p = 0.0003), comparable to SHAM (p = 0.5580) in average time spent in center zone (Fig. 5 G,H). The KD group showed cognitive abilities similar to sham (p = 0.8742) and KD-TBI (p = 0.9418) groups, while TBI group showed impairment (p = 0.0112 versus control). For moved distance (n = 9 for all; one-way ANOVA; Tukey's post hoc), KD TBI differed from TBI (p = 0.0003) but matched SHAM (p = 0.8742), while TBI differed from SHAM (p = 0.0112). The KD group did not differ significantly from the SHAM group (P = 0.8742 vs. control; P = 0.0015 vs. TBI). The center entries showed apathy (n = 9 for all; one-way ANOVA; Tukey's post hoc), with KD TBI showing improvement compared to TBI (p = 0.0021) and SHAM group (p = 0.6234). TBI showed decreased center entries versus control (p = 0.0464) and KD groups (p = 0.0021), with no difference between control and KD groups (P > 0.4630). Y-maze test (n = 9 per group) with one-way ANOVA revealed TBI mice had impaired exploration versus controls, showing reduced distance traveled (p = 0.0378) and fewer arm entries (p = 0.0036) (Fig. 5 I,J). KD TBI mice showed restored exploration compared to TBI mice, with increased distance (p = 0.0203) and entries (p = 0.0179), matching sham controls (distance: p = 0.9952; entries: p = 0.9250). KD mice were similar to SHAM and KD TBI mice but differed from TBI mice (distance: p = 0.0016; entries: p = 0.0041). No differences appeared in correct alternations (p = 0.4548), indicating preserved spatial working memory. These findings show TRAF6 KD provides therapeutic benefits in TBI-induced CTE by preserving tissue integrity, reducing oxidative stress, and maintaining cognitive function, while without TBI, TRAF6 KD causes TBI-like pathogenesis not yet manifesting in cognitive impairment. TRAF6 knockdown shows therapeutic effects in TBI, and K63-linked ubiquitination is key to these pathological changes To assess therapeutic effects in the KD TBI group, three pathological markers of CTE (AT8, IBA1, and SMI312) were evaluated across groups. IF analysis of AT8 (n = 8 for all, one-way ANOVA; Tukey's post hoc test) showed significantly reduced accumulation in the cortex of KD TBI compared to the TBI group (p = 0.0006 vs. KD TBI; p = 0.0138 vs. SHAM) and was comparable to SHAM (p = 0.6355) (Fig. 6 A, B). Mice with KD without trauma showed CTE-like pathology similar to TBI (p = 0.9577) and higher than both sham (p = 0.0447) and KD TBI groups (p = 0.0024). However, the distribution of AT8 differed between groups; whereas AT8 focally accumulated in the nucleus in TBI mice, a broader accumulation across the nuclear area was observed in KD mice. One-way ANOVA with Tukey’s post hoc analysis (n = 7 for all) of Mapt mRNA fold-change expression further corroborated these findings. The KD TBI group showed significant Mapt downregulation comparable to sham controls (p = 0.5026), relative to the TBI group (p = 0.0492 versus KD TBI; p = 0.0018 versus sham controls). KD without trauma showed upregulated Mapt mRNA levels, similar to TBI (p = 0.9854) and higher than sham (p = 0.0007) and KD TBI (p = 0.0230). While both KD and TBI groups showed altered gene expression and tau hyperphosphorylation, KD-TBI reduced these pathological markers. Next, the microglial activation marker, IBA1, was evaluated in all groups (Fig. 6 C, D). One-way ANOVA with Tukey’s post hoc analysis (n = 8 for all) revealed that IBA1 expression in the KD-TBI group was significantly reduced to levels comparable to those in the SHAM group (p = 0.7579), relative to the TBI group (p = 0.0041 versus KD-TBI; p = 0.0443 versus sham controls). KD without trauma showed increased IBA1 expression, similar to TBI (p = 0.1050) and significantly different from sham (p = 0.0001) and KD TBI (p < 0.0001). The gene expression of Aif1 (n = 7 for all; one-way ANOVA: Tukey's post hoc test), encoding IBA1, was altered in KD-TBI to SHAM levels (p = 0.9423), relative to TBI (p = 0.0317 versus KD-TBI; p = 0.0086 versus sham). The KD group showed Aif1 upregulation relative to sham (p = 0.0021) and KD TBI groups (p = 0.0083). To confirm neurofilament integrity, SMI312 immunostaining was performed (Fig. 6 E). One-way ANOVA with Tukey's post hoc analysis (n = 6 for all) showed SMI312 levels in the KD TBI were restored compared to the TBI group (p = 0.0075) and similar to SHAM group (p = 0.0016), indicating neurofilament deterioration in the TBI group (p = 0.0271 versus sham) was mitigated by TRAF6 KD. KD without trauma showed SMI312 loss comparable to the TBI group (p = 0.5914) and different from sham (p = 0.0016) and KD TBI groups (p = 0.0004) (Fig. 6 F). K48-linked polyubiquitination (Ub-K48) quantification (n = 14 for all; one-way ANOVA; Tukey's post hoc test) (Fig. 6 G-H) showed increased immunoreactivity in the TBI group versus SHAM (p = 0.0071), with levels attenuated in KD TBI (p < 0.0001 vs. TBI). No differences were found between KD TBI and SHAM (p = 0.4249). The KD group without trauma differed from SHAM (p = 0.0113) and KD TBI groups (p < 0.0001) but not from the TBI group (0.9984). Brown-Forsythe and Welch ANOVA (n = 8 for all) showed K48-linked polyubiquitination was more concentrated in TBI group nuclei than SHAM (p = 0.0022). KD TBI (p = 0.0272 versus TBI) recovered to SHAM levels (p = 0.9419). The KD group matched the TBI group (p = 0.9406) but differed from sham (p < 0.0001) and KD TBI (p = 0.0349) groups. For K63‑linked polyubiquitination (Ub‑K63) assessment (Fig. 6 I,J), quantitative analysis (n = 10 for all) showed KD‑dependent characteristics, with patterns attenuated in KD TBI showing no difference from the sham (p = 0.8680) and TBI (p = 0.1001) groups. TBI rarely showed Ub‑K63 accumulation (p = 0.3873 versus SHAM), while KD induced intensive Ub-K63 accumulation (p < 0.0001 versus sham and KD TBI; p = 0.0051 versus TBI), suggesting TRAF6-dependent regulation. Nuclear distributions were evaluated given its role in quality control (QC) and DNA repair. 29 , 30 Nuclear Ub-K63, associated with DNA damage response and transcription regulation, was significantly reduced in KD TBI versus TBI group (p = 0.0205). The TBI group showed higher nuclear Ub‑K63 levels than SHAM (p = 0.0313), while KD TBI levels matched sham controls (p = 0.4704). The KD group without trauma had high nuclear K63‑linked polyubiquitination similar to TBI group (p = 0.0653) and significantly different from SHAM (p = 0.0116) and KD TBI groups (p = 0.0014). K63 ubiquitination appears more involved in nuclear protein QC and DNA repair in both TBI and KD conditions, with KD mouse brain mediating Ub-K63 polyubiquitination more actively, though this effect returns to SHAM level when combined with TBI. Overall, TRAF6 KD in CTE exerted significant therapeutic effects by normalizing key pathological markers, including tau hyperphosphorylation, microglial activation, neurofilament degradation, and dysregulated ubiquitination patterns, while also playing a dual role in inducing CTE-like pathogenesis in the absence of trauma. Circulating miRNA expression in blood serum was assessed to determine if neuropathological changes were mirrored in blood, addressing the lack of diagnostic biomarkers for CTE. Brain condition is reflected in miRNA expression in mouse blood serum Mouse blood serum was extracted from each group and subjected to small RNA sequencing (miRNA-seq) (Fig. 7 A). Differential expression analyses identified miRNAs associated with long-term TBI and determined whether cerebral miRNA signatures appeared in peripheral circulation. Because both the KD and TBI groups exhibited CTE-like pathology in the brain, each was first compared with sham controls, and then the patterns were compared between sham and KD TBI. Volcano plot analysis of 396 mature miRNAs revealed that only a small subset met the predefined fold-change and p-value thresholds in each pairwise comparison (See Supplementary Table 1) (Fig. 7 B). Notably, SHAM vs. KD showed predominantly downregulated miRNAs, whereas SHAM vs. TBI showed upregulated miRNAs. The SHAM vs. KD TBI comparison yielded very few differentially expressed miRNAs, mirroring the minimal pathology observed in KD TBI brains. The comparisons of KD TBI vs. KD and KD TBI vs. TBI exhibited similar patterns to those observed in SHAM vs. KD and SHAM vs. TBI, respectively. To identify miRNAs commonly altered in KD and TBI groups versus sham, we filtered for significantly downregulated miRNAs in both comparisons. Two miRNAs—mmu‑miR‑7a‑5p and mmu‑miR‑351‑5p—were consistently downregulated, implicated in PI3K/AKT and NFκB signaling (Fig. 7 C, D). 31 , 32 These miRNAs were also reduced in KD TBI versus sham TBI (Fig. 7 E). Conversely, mmu‑miR‑574‑3p was upregulated in both KD and TBI, with miR-574 regulating Toll-like receptor signaling for proliferation control by arm variant, but showed no difference between the SHAM and KD TBI groups. 33 Given the resemblance between sham and KD TBI brains, we compared KD TBI with KD and TBI individually (Fig. 7 F, G). Three miRNAs—mmu‑miR‑16‑2‑3p, mmu‑miR‑451a, and mmu‑miR‑7687‑3p—were uniquely upregulated in KD TBI; these regulate proliferations via PI3K/AKT and NFκB signaling, though mmu-miR-7687-3p’s role is not well-verified. 34 – 36 Finally, miRNAs dysregulated in both TBI vs sham and TBI vs KD TBI were identified: miR‑122‑5p and miR‑467f were upregulated, while miR‑3535 and miR‑301a‑3p were downregulated (Fig. 7 H). miR‑122‑5p promotes inflammation via PI3K/AKT disruption, while miR-467f regulates TNF in p38 MAPK pathway as an anti-inflammatory modulator. 37 – 39 miR‑3535 is linked to Nrf2 pathway redox regulation, and miR‑301a‑3p affects STAT3/AKT inflammation and behavioral phenotypes. 40 , 41 In summary, miRNA‑seq of blood serum reflects CTE-like brain pathology: minimal changes in KD TBI, marked dysregulation in KD or TBI alone, and identification of PI3K/AKT– and NFκB–related miRNAs as disease mediators. Discussion This study was built upon the need for validated CTE diagnostic criteria and characterization, driven by recent evidence linking repeated TBI to progressive neuropathology. 5 , 8 , 9 , 11 , 42 – 44 Mouse models enable precise control over injury severity, timing, and targeting, yet most studies focus on short-term outcomes, leaving the long-term effects of TBI and its differentiation from other neurodegenerative diseases, especially in aging populations with comorbidities, poorly understood. 9 , 11 To address these gaps, we established two trauma-induced mouse groups maintained for three or six months post-TBI. Notably, only the six-month cohort exhibited anxiety, reduced exploration, prolonged center zone occupancy, and apathy-like behavior, without impairments in spatial memory (Fig. 1 ). 24 , 25 Apathy, a hallmark symptom of CTE distinct from dementia-related disorders, is associated with dysfunction in the neural circuit involving the prefrontal cortex, anterior cingulate cortex, and nucleus accumbens. 19 , 45 Therefore, the reduced exploratory behavior observed in CTE‑6m mice likely indicates progressive disruption of these fronto-striatal motivational networks. Further analyses revealed that six-month CTE mice exhibited significant deterioration in brain structures, including the cortex, corpus callosum, hippocampus, and the BBB (Fig. 1 ). These changes were marked by pathological accumulation of p-Tau, microglial activation, pTDP43, ROS and other pathological markers (Fig. 2 ). While AT8 pathology was present in both three- and six-month groups, widespread tau hyperphosphorylation and associated markers emerged exclusively at six months, indicating that TBI-induced CTE progresses over time, complicating early clinical diagnosis. In the six-month model, RNA-seq and protein network analyses revealed significant upregulation of ubiquitination-related signaling molecules in CTE mice (Fig. 3 ). Among these, TRAF6 was selected for further investigation, and its pathway components were found to be dysregulated in CTE. TRAF6 mediates signaling cascades that activate NFκB and MAPK pathways and functions as a RING-type E3 ubiquitin ligase, catalyzing Lys63-linked ubiquitin chains on itself and its substrates. 46 While TRAF6 has been studied in acute TBI, its direct role in CTE pathology has not yet been explored. 47 , 48 As a first study to directly link TRAF6 to CTE, we generated a TRAF6 KD model to evaluate its contribution to TBI-induced CTE. TRAF6 KD markedly attenuated brain deterioration, exerting protective effects on tissue structure, oxidative stress, tau pathology, inflammation, and cellular morphology after repeated TBIs (Figs. 5 , 6 ). It alters ubiquitin deposition, relevant to DNA repair and nuclear protein QC in the nucleus but not in cytosol. 29 , 30 TRAF6 KD in uninjured mice produced CTE pathologies-like ubiquitin deposition, oxidative stress, and structural damage, while cognitive function remained intact. This suggests TRAF6 suppression can induce CTE unless counterbalanced by trauma-activated compensatory signals. Given the involvement of the PI3K-AKT pathway in TRAF6-mediated signaling, as indicated by serum miRNA profiles, associated with cellular energy homeostasis and inflammatory regulation, our data implicate this cascade in CTE progression. 49 , 50 Besides, the miRNA-seq results show serum miRNA profiles reflect brain pathology (Fig. 7 ). Nearly identical expression patterns in sham and KD TBI groups revealed circulating miRNAs as minimally invasive biomarkers. We propose miR‑122‑5p, miR‑467f, miR‑3535, and miR‑301a‑3p as blood‑based diagnostics due to their dysregulation in TBI models versus control (SHAM) and therapeutic model (KD TBI). In summary, our six-month CTE mouse model recapitulates key features of chronic neuropathology following repetitive TBI, establishing a platform for mechanistic exploration. TRAF6 emerges as a critical driver of neurodegeneration post-trauma, while its knockdown paradoxically induces CTE-like pathology in uninjured mice, suggesting compensatory mechanisms mitigate TRAF6-dependent damage. Transcriptomic analyses identify a circulating miRNA signature that reflects brain pathology and distinguishes resilient (KD TBI) from vulnerable (TBI or KD-only) states, highlighting novel biomarkers and therapeutic targets. Future studies should further elucidate TRAF6-related ubiquitination signaling and validate miRNA signatures in human cohorts for targeted CTE interventions. Materials and Methods Mouse Housing and TBI Modeling This study was approved by the Institutional Animal Care and Use Committee (IACUC) of the Korea University Medical Center (approval no. KOREA-2022-0040). We conducted a study using male 25–30 g 12-week-old C57BL/6 mice (DBL, Eumseong, Republic of Korea). Animals were group-housed with no more than 4 animals per cage and acclimatized to standard laboratory conditions on a 12 h light/dark cycle. Food and water were provided ad libitum. Anesthesia was induced in mice by inhalation of 5% isoflurane in 1 L of oxygen using an animal anesthesia machine (cat no. L-PAS-01D; LMS Korea, Pyeongtaek, Korea). Full anesthesia was achieved within 3 min. During the surgical procedure, anesthesia was maintained using 3% isoflurane in 600 mL of oxygen. For TBI modeling, the mice were subjected to a repetitive closed-head impact model of CTE using the Portable Stereotaxic Instrument for Mouse (cat no. 68806, RWD Life Science Co., Shenzhen, China). Animals were anesthetized with 3% isoflurane in oxygen and placed on a heating pad to maintain core temperature at 37 ± 0.5°C. A 50 g weight was released from a height of 15 cm through a vertical guide tube onto the intact midline skull (between the bregma and lambda) to deliver a reproducible impact. Five impacts were administered over a two‑week period (one impact every 2–3 days). Following the final injury, animals were returned to their home cages and housed under standard conditions for either three months (CTE‑3m) or six months (CTE‑6m) to permit chronic pathology to develop. Two weeks before the planned sacrifice, the mice underwent behavioral tests. Continuous monitoring confirmed full recovery from anesthesia between impacts and no gross motor deficits that would confound long-term behavioral outcomes. Virus Injection This study was approved by the Institutional Biosafety Committee of Korea University Medical Center (approval no. KUIBC-2022-0017). ICV injection of AAV9-m-Traf6-shRNA (cat no. shAAV-277724, VECTOR BIOLABS, Philadelphia, PA, USA) or scrambled shRNA (cat no. 1122, VECTOR BIOLABS) was performed in C57BL/6 male mice (11 weeks old, 25–30 g). The mice were anesthetized with 3% isoflurane and placed in a stereotaxic frame. A small incision was made to expose the skull, and a hole was drilled at the following coordinates: caudal − 0.58 mm, lateral 1.25 mm, and ventral − 1.77 mm. A total of 1 µL (3.04 × 10¹² GC/mL) of AAV9-m-Traf6-shRNA was injected at a rate of 1 µL/min using a stereotaxic infusion pump (cat no. 68528, Stereotaxic Instrument, RWD Life Science Co.; cat no. 70-4507, Pump 11 Elite Nanomite Infusion, Harvard Apparatus, MA, USA). After injection, the syringe was held in place for 1 min and slowly removed. The incision was closed using 6 − 0 silk sutures. After recovery from anesthesia, the animals were monitored for abnormalities. Upon completion of the experiment, tissue samples, including brain and blood, were collected and stored at -80°C for further analysis. OF Test The mice were moved to the test room 30 min before the open-field test. The illuminance of the test room was maintained in a dim-lit. The mouse was placed in the center of a white chamber (50x50x30cm), and the recording began 10 s after the mouse was transferred to the chamber. Each mouse was allowed to move freely inside the chamber for 5 min, after which it was transferred to its home cage. Animal’s cognitive behavior was analyzed by using ANY-maze™ (Stoelting Co., Wood Dale, IL, USA) software. Y Maze Test The mice were moved to the test room 30 min before the open-field test. The illuminance of the test room was maintained in a dim-lit. The mouse was placed in the center of the Y-shaped maze, and the recording began 10 s after the translocation of the mouse to the chamber. Each mouse was allowed to move freely inside the chamber for 5 min, after which it was transferred to its home cage. Animal’s cognitive behavior was analyzed by using ANY-maze™ software. Prussian Blue Staining For Prussian blue staining, a VitroView Prussian Blue Stain Kit (cat no. VB-3009, VitroVivo Biotech, Rockville, MD, USA) was purchased. Mouse brain tissue was fixed by 4% Paraformaldehyde (PFA) incubation 48 h at 4°C. After the serial incubation in Sucrose buffer from 30-50-70% overnight for each, the samples were immersed into the Tissue-Tek® O.C.T. Compound (cat no. HIO-0051, Sakura Finetek, Torrance, USA), and frozen at -80°C. Cryosectioned and slide-attached 10 µm tissue slices were incubated for 5 min in freshly prepared working solution (1:1 mix of potassium ferrocyanide and HCl, pre‑equilibrated 30 min at room temperature), followed by a distilled water rinse, counterstaining with Nuclear Fast Red for 5 min, a tap‑water rinse, dehydration through 95% and 100% ethanol (2 min each), clearing in xylene (3×5 min), and mounting with Eukitt® Quick-hardening mounting medium (cat no. 03989, Sigma-Aldrich, Steinheim, Germany). Hemosiderin deposits were visualized in blue, nuclei red, and background pink. H&E Staining Cryosections of mouse brains were air-dried and then immersed in xylene for 5 min three times each to remove residual OCT. Slides were rinsed in distilled water for 1 min, hydrated using graded ethanol (100%, 90%, 80%, and 70%; 30 s each), and rinsed again in distilled water for 1 min. Sections were stained with Mayer’s hematoxylin (cat. no. 30002, MUTO PURE CHEMICALS Co., Ltd., Tokyo, Japan) for 5 min, washed under running tap water for 5 min, and briefly rinsed with PBS for 1 min. Eosin Y solution (cat. no. 32002, MUTO PURE CHEMICALS CO., LTD., Tokyo, Japan) staining was performed for 5 min, followed by a 5 min distilled‑water wash, dehydration in 70%, 80%, 90%, and 100% ethanol (30 s each), and clearing in xylene (cat. no. 214736, Sigma‑Aldrich, St. Louis, MO, USA) for 5 min each for three times and mounted with Eukitt® Quick-hardening mounting medium (cat no. 03989, Sigma-Aldrich, Steinheim, Germany). Whole-slide imaging was performed using the Panoramic Scan II digital scanner (3DHISTECH, Budapest, Hungary). Western Blotting Mouse brain tissue was homogenized in ice-cold RIPA buffer (cat no. R0278, Sigma-Aldrich) containing 1% protease and phosphatase inhibitors (cat no. 78446, Thermo Fisher Scientific, Sunnyvale, CA, USA) using a Dounce homogenizer for 30 min at 4°C. The lysate was centrifuged at 16,000 × g for 30 min at 4°C, and the supernatant was collected. Protein concentration was determined using the Pierce™ Bradford Plus Protein Assay Reagent (cat no. 23238, Thermo Fisher Scientific). Equal amounts of protein (5 µg) were separated on–4–15% Mini-Protean TGX Stain-Free Precast Gels (cat no. BR4568086, Bio-Rad Laboratories, Hercules, CA, USA) at 160V for 30 min and then transferred onto a PVDF membrane using preassembled transfer packs (cat no. 1704156, Bio-Rad Laboratories) in a Trans-Blot Turbo Transfer System (cat no. 1704150, Bio-Rad Laboratories). The membrane was blocked with 5% BSA (cat no. 05470, Sigma-Aldrich) in TBS for 30 min at room temperature, followed by incubation overnight at 4°C with the primary antibody (1:100-1:1000 dilution in TBS-T (0.2% Tween-20) supplied with 2.5% BSA, see Supplementary Table 2). After three 5-min washes in TBS-T, the membrane was incubated with an HRP-conjugated secondary antibody (1:3000, Supplementary Table 2) for 1 h at room temperature and washed again in TBS-T. Chemiluminescence detection was performed using Clarity Western ECL Substrate (cat no. 1705061, Bio-Rad Laboratories), and protein bands were visualized using a gel imager (ChemiDoc MP, Bio-Rad Laboratories) and analyzed using ImageJ software. IF Staining The sections were permeabilized with 0.4% Triton X-100 in TBS for 15 min at room temperature, blocked with 5% BSA in TBS for 30 min at room temperature, and then incubated overnight at 4°C with primary antibodies in TBST supplemented with 2.5% BSA (see Supplementary Table 3). Following three consecutive TBST washes (5 min each), the slides were incubated with fluorophore-conjugated secondary antibodies in TBST supplemented with 2.5% BSA for 1 h at room temperature and then washed again in TBS (three times, 5 min each). Finally, the slides were mounted using the Vectashield Antifade Mounting Medium containing DAPI (cat no. H-1200-10, Vector laboratories Ltd., Peterborough, UK) and imaged using fluorescence microscopy (Carl Zeiss™ Axio Vert.A1 Inverted Microscope, Carl Zeiss AG, Oberkochen, Germany) to visualize protein expression. DHE Assay Cryosectioned mouse brain tissues (10 µm thickness) were prepared for Dihydroethidium (DHE, cat no: D7008, Sigma-Aldrich, St. Louis, MO, USA) staining to detect reactive oxygen species (ROS). The sections were incubated with a 10 µM solution of DHE in PBS for 1 h at room temperature in a dark. Following incubation, the sections were washed thrice with PBS to remove excess dye. Slides were mounted using the Vectashield mounting medium. Fluorescence microscopy was performed to visualize and quantify ROS production. PCR Analysis Total RNA was isolated from tissue samples using the TRIzol reagent (cat no. 15596026, Invitrogen, NY, USA) following the manufacturer’s protocol. First‑strand cDNA synthesis was carried out with the High‑Capacity RNA‑to‑cDNA Kit (cat no. 4387406, Applied Biosystems). Quantitative PCR was performed using SYBR Green PCR Master Mix (cat no. 4309155, Applied Biosystems) on QuantStudio 5 Real-Time PCR System (A34322, Applied Biosystems) and relative expression levels were determined by normalization to GAPDH via the 2 –ΔΔCt method. The primer sequences are listed in Supplementary Table 3. Bulk RNA Sequencing Total RNA concentration was calculated using Quant-IT RiboGreen (cat no. R11490, Invitrogen). To assess the integrity of the total RNA, samples were run on a TapeStation RNA screentape (cat no. 5067–5576, Agilent Technologies, Waldbronn, Germany). Only high-quality RNA preparations (RIN greater than 7.0) were used for the RNA library construction. A library was independently prepared with 1ug of total RNA for each sample by Illumina TruSeq Stranded mRNA Sample Prep Kit (cat no. 20020595, Illumina, Inc., San Diego, CA, USA). The first step in the workflow involves purifying the poly-A containing mRNA molecules using poly‐T‐attached magnetic beads. Following purification, mRNA was fragmented into small pieces using divalent cations at elevated temperatures. The cleaved RNA fragments were copied into first-strand cDNA using SuperScript II reverse transcriptase (cat no. 18064014; Invitrogen) and random primers. This was followed by synthesis of second-strand cDNA using DNA Polymerase I, RNase H, and dUTP. These cDNA fragments then go through an end repair process, the addition of a single ‘A’ base, and then ligation of the adapters. The products were purified and enriched using PCR to create a final cDNA library. The libraries were quantified using KAPA Library Quantification kits for Illumina Sequencing platforms, according to the qPCR Quantification Protocol Guide (cat no. KK4854, Kapa Biosystems, Woburn, MA, USA) and qualified using a TapeStation D1000 ScreenTape (cat no. 5067–5582, Agilent Technologies). Indexed libraries were then submitted to an Illumina NovaSeq6000 (Illumina, Inc., San Diego, CA, USA) and paired-end (2×100 bp) sequencing was performed by Macrogen, Inc.. STRING Network Analysis Significantly upregulated mRNAs (2,777 genes; p < 0.05) identified by bulk RNA-seq were analyzed using the STRING module in Cytoscape v.2.2.0 (Institute for System Biology; WA; USA). A cluster network was constructed using the MCL algorithm with a granularity parameter of 4, followed by filtering nodes with mcl.cluster > 10. The resulting 1,848 nodes were processed through STRING v12.0 (Swiss Institute of Bioinformatics; Lausanne; Switzerland) to generate a protein–protein interaction (PPI) network, incorporating evidence from text mining, genomic neighborhood, experimental data, curated databases, co-expression, gene fusion, and co-occurrence, with a minimum confidence score threshold of 0.40. Network modules were defined using the DBSCAN clustering algorithm with an ε parameter of 2. Cluster 1, representing the largest gene set (101 genes), was further analyzed by sorting the top 20 nodes with the highest node degree, resulting in a network comprising 101 nodes and 756 edges. Global network metrics indicated an average node degree of 15, a local clustering coefficient of 0.600, and a PPI enrichment p-value of < 1 × 10⁻¹⁶. The average values of coexpression, experimentally determined interactions, automated text mining, and combined scores were calculated. Immunohistochemistry For GFP detection, 4 µm paraffin sections of mouse brain tissue were prepared and mounted on Superfrost glass slides (Thermo Fisher Scientific). The tissues were deparaffinized with xylene and rehydrated using a graded ethanol series. Antigen retrieval was performed by immersing the sections in 0.01 M citric acid buffer and heating them in a pressure cooker to reach full pressure, followed by 10 min of high-pressure treatment. Endogenous peroxidase activity was blocked by incubating sections with 3% hydrogen peroxide for 15 min. Nonspecific binding was minimized by incubating the tissue with a blocking reagent (Vector Laboratories, USA). The primary antibody, anti-GFP rabbit antibody (Cat. no. Ab290, Abcam, Cambridge, MA, USA), was diluted 1:500 in PBS and incubated overnight at 4°C. After three washes with PBS, the sections were incubated with a secondary HRP-conjugated anti-rabbit IgG antibody for 1 h. The antibody complex was visualized using diaminobenzidine (DAB) chromogen, and the reaction was monitored under a microscope to ensure optimal staining. The slides were scanned using a Digital Slide Scanner (EasyScan Pro, Motic, USA) to obtain whole-slide images for analysis. Small RNA Sequencing RNA isolated from each sample was used to construct sequencing libraries using the SMARTer smRNA-Seq Kit for Illumina following the manufacturer's protocol. Briefly, the Input RNA was polyadenylated to provide a priming sequence for the oligo-(dT) primer. cDNA synthesis is primed by the 3’ smRNA dT Primer, which incorporates an adapter sequence at the 5’ end of each first-strand cDNA molecule. When the MMLV-derived PrimeScript™ Reverse Transcriptase (RT, cat no: 2680. Takara Bio, Otsu, Japan) reaches the 5’ end of each RNA template, it adds nontemplated nucleotides which are bound by the SMART smRNA Oligo-enhanced with locked nucleic acid (LNA) technology for greater sensitivity. In the template-switching step, PrimeScript RT uses the SMART smRNA Oligo as a template for the addition of a second adapter sequence to the 3’ end of each first-strand cDNA molecule. In the next step, full-length Illumina adapters (including index sequences for sample multiplexing) are added during PCR amplification. The Forward PCR Primer binds to the sequence added by the SMART smRNA Oligo, while the Reverse PCR Primer binds to the sequence added by the 3’ smRNA dT Primer. The resulting cDNA library included the sequences required for clustering in an Illumina flow cell. Libraries were validated by checking their size, purity, and concentration using an Agilent Bioanalyzer. The libraries were pooled in equimolar amounts and sequenced using an Illumina NovaSeq instrument. Image decomposition and quality value calculations were performed using Illumina pipeline modules. Statistics All experimental measurements were performed on at least three independent biological replicates, and the mean values were used for statistical analysis. Data are displayed with error bars indicating mean ± SEM, and where appropriate, a two-sided Student’s t-test or one-way ANOVA was applied based on assessments of normality and variance (p < 0.05, considered significant). Post-hoc multiple comparisons (e.g., Tukey’s or Dunnett’s tests) were conducted following ANOVA when significant. Statistical analyses were performed using GraphPad Prism, version 10 (GraphPad Software, San Diego, CA, USA). Declarations Data availability Data are available upon request. Competing interests The authors declare no competing interests. Author contributions D.L. developed the concept, methodology, validation, formal analysis, and investigation; administered the project; and wrote the original draft. I.H.L. participated in investigation and methodology. M.K., S.C., and H.B. participated in investigation. S.C. participated in visualization and review of original draft. J.I.C. developed the conceptualization and methodology, supervised the project, reviewed and edited the original draft, and secured funding. Acknowledgements This work was supported by a Korea University Ansan Hospital research grant (O2411971), the Korea University Research Fund (K2508441), the National Research Foundation of Korea (RS-2022-NR071661), and Jonggeundang Co., Ltd. References Mayer, A. R., Quinn, D. K. & Master, C. L. The spectrum of mild traumatic brain injury. Neurology 89, 623–632 (2017). Majerus, S., Gill-Thwaites, H., Andrews, K. & Laureys, S. 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Implications of Phosphoinositide 3-Kinase-Akt (PI3K-Akt) Pathway in the Pathogenesis of Alzheimer’s Disease. Mol Neurobiol 59, 354–385 (2022). Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryTable1.xlsx Supplementary Table 1. Upregulated and downregulated miRNAs in the heat-map SupplementaryTable2.xlsx Supplementary Table 2. Antibodies SupplementaryTable3.xlsx Supplementary Table 3. Primer Sequences Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6652049","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":460512580,"identity":"e412dbea-8f2c-44e5-8879-5ac832da373f","order_by":0,"name":"Jong-Il Choi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxklEQVRIiWNgGAWjYDACCeYGZgY2GwOEACEdPBKMjc0MbGmkazlMghZ76cb2xwVl5435pQ8f/MBQY8cgOfsAAVtkDjY2zzh320yyLy1ZguFYMoM0XwIhhyU2NvO23bYxOMNjIMHAdoBBjoegX8BazgG18H/+wfCPeC0HzIC2sEkwth1gkCao5UZi42yec8nGkj1sZhaJfck8kj0EtLDPSD7wmafMzrCfh/nxjQ/f7OQkzhDQggoSgNaSpGEUjIJRMApGAXYAADirOXJZRHK6AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-5272-0905","institution":"Deparment of Neurosurgery, Korea University Ansan Hospital, Korea University","correspondingAuthor":true,"prefix":"","firstName":"Jong-Il","middleName":"","lastName":"Choi","suffix":""},{"id":460512581,"identity":"9fe29f57-bfff-4cff-b2f5-1c005d84ed51","order_by":1,"name":"Dain Lee","email":"","orcid":"","institution":"KU-KIST Graduate School of Converging Science and Technology, Korea Univresity","correspondingAuthor":false,"prefix":"","firstName":"Dain","middleName":"","lastName":"Lee","suffix":""},{"id":460512582,"identity":"673a7520-45dd-4948-aae4-0adca02d3b1d","order_by":2,"name":"In-Hyung Lee","email":"","orcid":"","institution":"Deparment of Neurosurgery, Korea University Ansan Hospital, Korea University","correspondingAuthor":false,"prefix":"","firstName":"In-Hyung","middleName":"","lastName":"Lee","suffix":""},{"id":460512583,"identity":"4d2cdfbd-1a01-44d6-94d0-f08c05b290cf","order_by":3,"name":"Minseop Kim","email":"","orcid":"","institution":"KU-KIST Graduate School of Converging Science and Technology, Korea Univresity","correspondingAuthor":false,"prefix":"","firstName":"Minseop","middleName":"","lastName":"Kim","suffix":""},{"id":460512584,"identity":"39b06287-aa16-4bf5-bee1-a052a0079e40","order_by":4,"name":"Sieun Choi","email":"","orcid":"https://orcid.org/0000-0003-1708-5672","institution":"KU-KIST Graduate School of Converging Science and Technology, Korea Univresity","correspondingAuthor":false,"prefix":"","firstName":"Sieun","middleName":"","lastName":"Choi","suffix":""},{"id":460512585,"identity":"83ffe0df-881f-44b0-8389-e4f59bcd9e44","order_by":5,"name":"Hyunjun Bae","email":"","orcid":"","institution":"School of Mechanical Engineering, Korea University","correspondingAuthor":false,"prefix":"","firstName":"Hyunjun","middleName":"","lastName":"Bae","suffix":""},{"id":460512586,"identity":"3889c404-5d62-4da5-b293-6858fce0deda","order_by":6,"name":"Seok Chung","email":"","orcid":"https://orcid.org/0000-0002-1735-8338","institution":"Korea University","correspondingAuthor":false,"prefix":"","firstName":"Seok","middleName":"","lastName":"Chung","suffix":""}],"badges":[],"createdAt":"2025-05-13 06:30:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6652049/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6652049/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83428419,"identity":"a341aa7a-b9c1-4eee-9317-abaedeae6643","added_by":"auto","created_at":"2025-05-26 06:05:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":9485571,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEstablishment of the animal model, behavioral assessment, and histo\u003c/strong\u003epathological changes observed at 3 and 6 months in the controlled cortical impact–induced TBI animal model\u003cstrong\u003e.\u003c/strong\u003e \u003cstrong\u003e(A)\u003c/strong\u003e Experimental timeline for generating controlled cortical impact (CCI)–induced traumatic brain injury (TBI). Animals received five CCI procedures at 2–3‑day intervals during weeks 1–2. Behavioral testing was performed at week 10, followed by euthanasia at week 12 (3‑month model, CTE‑3m). A second cohort underwent behavioral testing at week 22 and was euthanized at week 24 (6‑month model, CTE‑6m). \u003cstrong\u003e(B)\u003c/strong\u003eSchematic of the CCI procedure. Mice were anesthetized with 5% isoflurane, maintained at 3% during surgery, and secured in a stereotaxic frame. A 50‑g weight was dropped from a height of 15 cm onto the skull to induce TBI. \u003cstrong\u003e(C)\u003c/strong\u003e Open‑field (OF) test apparatus (left). In the 6‑month model, animals spent significantly more time in the central zone (middle) and exhibited increased immobility (right), indicative of dysfunctional anxiety and apathy-like behavior. *p \u0026lt; 0.05;\u003cstrong\u003e \u003c/strong\u003e****p \u0026lt; 0.0001; ns, not significant.\u003cstrong\u003e (D)\u003c/strong\u003eY‑maze configuration showing three arms labeled a, b, and c (left). Right panels show percentage alternation and total number of arm entries, reflecting working memory and exploratory activity. *p \u0026lt; 0.05; **p \u0026lt; 0.01; ns, not significant. (E) Schematic overview of secondary injury–associated pathology following traumatic brain injury, illustrating disruption of the blood‑brain barrier (BBB), and neuronal cell death in the cortex and hippocampus. (F) Representative Prussian blue staining of brain sections from 3‑month (CTE‑3m) and 6‑month (CTE‑6m) animals, demonstrating progressive BBB disruption in hemisphere, cortex, corpus callosum (CC) and cingulum bundle (CB). (G) Hematoxylin \u0026amp; eosin (H\u0026amp;E)–stained sections showing histopathological alterations in cortical, CC, striatal, and hippocampal (Hipp) regions at 3 and 6 months post‑injury. (H) Quantification of histological damage across the indicated brain regions. *p \u0026lt; 0.05; **p \u0026lt; 0.01; ***p \u0026lt; 0.001; ****p \u0026lt; 0.0001; ns, not significant. \u003cstrong\u003eData are presented as mean ± SEM.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-6652049/v1/6761a2a5115701db17e45822.png"},{"id":83428880,"identity":"1c9e87b3-f6fe-428f-aa69-bf42c267da41","added_by":"auto","created_at":"2025-05-26 06:13:39","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":4131483,"visible":true,"origin":"","legend":"\u003cp\u003eVerification of biomarker accumulation in the brain following TBI. (A) A schematic illustrates that cortical tissue was reserved for histological staining and reactive oxygen species (ROS) detection, whereas whole‑brain homogenates were used for protein immunoblotting and gene expression analyses. (B) Chronic traumatic encephalopathy progression after TBI is depicted by increasing levels of AT8, IBA1, ROS, and cell death, alongside deteriorating BBB integrity, cognitive function, and pTDP43. (C) Representative immunoblot membranes for AT8 accumulation in whole‑brain lysates are shown, with (D) corresponding quantitative analyses. (E,F) Cortical images demonstrate neuronal and astrocytic accumulation of AT8, (G,H) with quantification presented. (I,J,K) Additional panels display cortical pTDP43, IBA1, and ROS accumulation with their respective quantifications. (L) Finally, mRNA expression levels of \u003cem\u003eMapt, Aif1, Tardbp, and Gfap\u003c/em\u003e are quantified. *p \u0026lt; 0.05; **p \u0026lt; 0.01; ***p \u0026lt; 0.001; ns, not significant. Data are presented as mean ± SEM\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-6652049/v1/1ef6947e714cf4fb8d8bdf6e.png"},{"id":83428426,"identity":"2ef0a14e-6071-4067-9aa7-924a3f502d51","added_by":"auto","created_at":"2025-05-26 06:05:39","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":6124465,"visible":true,"origin":"","legend":"\u003cp\u003eDynamic transcriptomic alterations from acute to chronic stages in the TBI model revealing TRAF6 pathway involvement in long-term CTE. (A) A heatmap depicts gene expression changes at 3 and 6 months post-injury. (B) A principal component analysis (PCA) plot illustrates the genetic similarity among individual animals. (C, D) STRING network clustering analysis identifies the top 10 clusters using DBSCAN clustering (ε=2) and visualizes the map of Cluster 1 (Gene count = 101). (E) The corresponding analysis highlights the top 5 nodes with the highest average combined scores, with TRAF6 prominently marked for its leading average combined score (F) Cluster 1 gene set analysis was performed using bulk RNA-seq, visualizing the list of upregulated genes (*p\u0026lt;0.05). (G) The average fold change of Cluster 1 genes (n=42 for all) was quantified, ***p \u0026lt; 0.001; ****p \u0026lt; 0.0001. (H) qPCR analysis of TRAF6‑related pathway genes showing statistically significant upregulation in CTE‑6m versus control. \u0026nbsp;**p \u0026lt; 0.01; ****p \u0026lt; 0.0001; ns, not significant. (I) Representative IF image showing TRAF6 expression in the cerebral cortex, with (J) corresponding quantitative analysis. (K) Western blot of whole‑brain lysates demonstrating increased TRAF6 protein levels in CTE‑6m, (L) with quantification. * p \u0026lt; 0.05. Data are presented as mean ± SEM.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-6652049/v1/2f8027b48afb1cfe394d3aee.png"},{"id":83428422,"identity":"75c06add-1115-4888-b6ad-6900b81cfdf2","added_by":"auto","created_at":"2025-05-26 06:05:39","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":6098273,"visible":true,"origin":"","legend":"\u003cp\u003eInduction of TRAF6 gene knockdown (KD) via intracerebroventricular (ICV) viral delivery. A schematic (A) depicts the ICV injection of control virus (V1; SHAM) or TRAF6 KD virus (V2; KD) and the 6 month experimental timeline. (B) Photograph of the surgical procedure showing scalp incision and ICV injection. (C) Representative immunohistochemical staining of GFP (brown) in cortical sections two weeks post injection, confirming viral transduction. (D) Quantitative RT-PCR analysis of whole brain tissue two weeks after injection shows reduced \u003cem\u003eTraf6\u003c/em\u003e mRNA expression in KD animals. *p \u0026lt; 0.05 (E) GFP expression at 6 months post TBI confirms sustained viral presence in each group. (F) Representative immunoblots demonstrate decreased TRAF6 protein levels in KD animals at 6 months post injury, with corresponding quantification in (G). **p \u0026lt; 0.01, ***p \u0026lt; 0.001. Data are mean ± SEM.\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-6652049/v1/03fbfc7dec725e9e14a5f9ee.png"},{"id":83428424,"identity":"a52427b8-50c5-4715-ae1f-f83faf78e9f0","added_by":"auto","created_at":"2025-05-26 06:05:39","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":12615407,"visible":true,"origin":"","legend":"\u003cp\u003eCognitive behavioral performance and pathological outcomes following TRAF6 knockdown and traumatic brain injury (A-C) Representative histological images showing neuronal cell death in the cortex and hippocampus across experimental groups, with (D) corresponding quantitative analysis. (E) Representative images of ROS accumulation (DHE staining) in the cortex, with (F) corresponding quantification. Data are presented as mean ± SEM; *p \u0026lt; 0.05; **p \u0026lt; 0.01; ***p \u0026lt; 0.001; ****p \u0026lt; 0.0001. (G) Representative tracking maps from the open field test. (H) Quantification of total distance traveled, center entries, and time spent in the center zone. (I) Representative tracking maps from the Y maze. *p \u0026lt; 0.05; **p \u0026lt; 0.01; ***p \u0026lt; 0.001. (J) Quantitative measures of total distance traveled, number of arm entries, and percent spontaneous alternation. Data are presented as mean ± SEM; *p \u0026lt; 0.05; **p \u0026lt; 0.01; ns, not significant.\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-6652049/v1/31f2dfcfd65a4f0841ce56f2.png"},{"id":83428882,"identity":"42cc8ad5-59df-4bcd-98a3-3d64ccb1b61c","added_by":"auto","created_at":"2025-05-26 06:13:39","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":7566495,"visible":true,"origin":"","legend":"\u003cp\u003eIF image analysis illustrating the pathological outcomes following TRAF6 knockdown and TBI with reference to known CTE pathology and key ubiquitination factors. Panels (A,C, and E) show representative IF images of AT8, IBA1, and SMI312 distributions in the cortex across the experimental groups, with the corresponding quantitative analyses in (B,D, and F) combined with qPCR analysis. Panels (G,H) present representative images and quantification of UB-k48 in the cortex, including total accumulation (normalized to DAPI intensity) and subcellular distribution. Panels (I and J) similarly display representative images and quantification of UB-k63. *p \u0026lt; 0.05; **p \u0026lt; 0.01; ***p \u0026lt; 0.001; ****p \u0026lt; 0.0001. Data are presented as mean ± SEM\u003c/p\u003e","description":"","filename":"Fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-6652049/v1/64742c37c03d89d7e7cfe1b3.png"},{"id":83428881,"identity":"f2dbc04c-4899-4614-9e71-1fed9a319446","added_by":"auto","created_at":"2025-05-26 06:13:39","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":928592,"visible":true,"origin":"","legend":"\u003cp\u003eMouse blood serum miRNA profiling demonstrating the impact of TRAF6-related pathology on circulating miRNAs and their potential as biomarkers. (A) Schematic description of blood serum collection from mice. (B) Volcano plots to show the miRNA expression patterns in comparisons. (C–E) Comparisons of miRNA profiles in each group versus the sham control, with commonly upregulated miRNAs in SHAM highlighted in yellow and commonly downregulated miRNAs in SHAM highlighted in cyan. (F–G) Comparisons of miRNA profiles in each group versus the KD TBI group, with commonly upregulated miRNAs in KD TBI (relative to KD and TBI) highlighted in green. (H) Commonly upregulated or downregulated miRNAs in the TBI group identified\u003c/p\u003e","description":"","filename":"Fig7.png","url":"https://assets-eu.researchsquare.com/files/rs-6652049/v1/af0d12c2fd012ea0ec48cd8e.png"},{"id":104780239,"identity":"f8f50228-6912-4945-943b-94f729591e8d","added_by":"auto","created_at":"2026-03-17 07:51:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":46362879,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6652049/v1/6b1431d2-9bb0-47e3-8b49-8df9790d04d7.pdf"},{"id":83428411,"identity":"f4f5ffb7-f21f-4862-854b-34afcf00a8bc","added_by":"auto","created_at":"2025-05-26 06:05:39","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16001,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 1. Upregulated and downregulated miRNAs in the heat-map\u003c/p\u003e","description":"","filename":"SupplementaryTable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6652049/v1/d5c4b4a5d93102c2b5e15293.xlsx"},{"id":83428417,"identity":"a43bf13f-614a-42b9-8535-860863634d45","added_by":"auto","created_at":"2025-05-26 06:05:39","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":10815,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 2. Antibodies\u003c/p\u003e","description":"","filename":"SupplementaryTable2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6652049/v1/d74fbcfbd4e83d4a1cfc46b6.xlsx"},{"id":83428416,"identity":"4571ae9a-018b-4be8-b7bf-1f08bb8d92c1","added_by":"auto","created_at":"2025-05-26 06:05:39","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":10489,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 3. Primer Sequences\u003c/p\u003e","description":"","filename":"SupplementaryTable3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6652049/v1/216b477d4138989d33fb34f8.xlsx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"TRAF6-Mediated Ubiquitin Signaling Drives Long-Term Neurodegeneration in a Mouse Model of Chronic Traumatic Encephalopathy","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTraumatic brain injury (TBI) is brain damage from external forces like contusions, falls, traffic accidents, and sports impacts. TBI is classified as acute or chronic and by severity as mild, moderate, or severe. Mild TBI is typically referred to as a concussion, whereas moderate-to-severe TBI is often associated with loss of consciousness and lasting neurological deficits.\u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e When TBI is sufficiently forceful or repetitive, it can lead to chronic traumatic encephalopathy (CTE), a progressive neurodegenerative condition that persists long after the initial injury. The progression from TBI to CTE is driven by the initial insult and secondary injury mechanisms, including oxidative stress and chronic inflammation.\u003csup\u003e\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e CTE is most frequently observed in athletes and military personnel, who are regularly exposed to repetitive head trauma during high-intensity physical activity.\u003csup\u003e\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eCurrently, there is no established diagnostic method for CTE. The first CTE case in a military veteran was reported in 2011, and defining its diagnostic criteria only began a decade ago at the NINDS/NIBIB consensus meeting.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e This meeting established hyperphosphorylated tau accumulation as a central pathological feature of CTE. Although evidence suggests that CTE progresses into a chronic neurodegenerative process characterized by inflammation, misfolded proteins, synaptic dysfunction, neuronal loss, and neural network disruption, its pathophysiological mechanisms remain poorly understood, with diagnosis still confined to postmortem histopathological examination and no effective treatment established, highlighting a significant gap driven by multiple contributing factors. \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFirst, mechanistic studies rely on animal models examining only short-term effects within weeks of injury, while models capturing long-term TBI-related neurodegeneration are lacking.\u003csup\u003e\u003cspan additionalcitationids=\"CR15 CR16 CR17\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e Secondly, while tau pathology has been the focus of CTE studies, additional molecular pathways beyond phospho-tau are involved. The behavioral phenotypes of CTE differ from classical tau-driven dementias like Alzheimer's disease, suggesting distinct mechanisms.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan additionalcitationids=\"CR20 CR21 CR22 CR23\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e Third, because CTE arises from acquired injuries rather than genetic mutations, establishing animal models without physical trauma remains difficult. Given CTE's recent recognition as a public health concern, understanding of its pathophysiology remains early. CTE symptoms develop gradually and may mimic other neurological disorders, leading to delayed diagnosis until irreversible damage occurs. Therefore, improving early detection and understanding long-term injury mechanisms are priorities.\u003c/p\u003e \u003cp\u003eAccordingly, our goal is to establish a reliable CTE model, identify central nodes with therapeutic potential, and assess whether brain alterations are reflected in circulating biomarkers to inform future diagnostic strategies. In this study, we developed a chronic TBI model to investigate long-term CTE mechanisms. We compared brain changes at 3- and 6-month post-injury and selected the 6-month model based on pathogenic pathway gene expression. This revealed TRAF6's strong implication in CTE progression. Using AAV9-delivered shRNA, we examined TRAF6 suppression effects and assessed systemic changes through serum microRNA profiling.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePathological characterization indicates that the chronic CTE-6m model is better suited for long-term CTE studies\u003c/h2\u003e \u003cp\u003eWe established a CTE mouse model using a repetitive closed-head impact protocol in C57BL/6 mice. Mice received five impacts over two weeks by releasing a 50‑g weight onto the skull (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA,B). Animals were maintained for three (CTE‑3m) or six (CTE‑6m) months for chronic pathological development. Behavioral assessments were conducted two weeks prior to euthanasia.\u003c/p\u003e \u003cp\u003eBehavioral phenotype was first evaluated using the open-field (OF) test, where mice were placed in an arena to record time spent in central versus peripheral zones (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Uninjured controls (CTRL) and CTE‑3m mice spent minimal center time, reflecting normal anxiety behavior. CTE‑6m mice (n\u0026thinsp;=\u0026thinsp;10) showed increased center‑zone time compared to CTRL (n\u0026thinsp;=\u0026thinsp;10; one-way ANOVA; Tukey's post hoc; p\u0026thinsp;=\u0026thinsp;0.0497) and CTE‑3m (n\u0026thinsp;=\u0026thinsp;10; p\u0026thinsp;=\u0026thinsp;0.0325) groups. No difference was found between CTRL and CTE‑3m groups (p\u0026thinsp;=\u0026thinsp;0.9796). Immobile time also increased only in CTE-6m mice (n\u0026thinsp;=\u0026thinsp;8) compared to CTRL (n\u0026thinsp;=\u0026thinsp;8; one-way ANOVA; Tukey's post hoc test; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and CTE-3m (n\u0026thinsp;=\u0026thinsp;8; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) groups. No difference was found between CTRL and CTE‑3m groups (p\u0026thinsp;=\u0026thinsp;0.4406).\u003c/p\u003e \u003cp\u003eSecond, animals were assessed with the Y‑maze test (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). While alternation rates, exploring arms sequentially, did not differ between groups (n\u0026thinsp;=\u0026thinsp;10 for all; one-way ANOVA; Tukey's post hoc; p\u0026thinsp;=\u0026thinsp;0.0702), total arm entries decreased in CTE‑6m (n\u0026thinsp;=\u0026thinsp;10) mice versus CTRL (n\u0026thinsp;=\u0026thinsp;10; one-way ANOVA; Tukey's post hoc; p\u0026thinsp;=\u0026thinsp;0.0359) and CTE‑3m (n\u0026thinsp;=\u0026thinsp;10; p\u0026thinsp;=\u0026thinsp;0.0038). No difference existed between CTRL and CTE‑3m groups (p\u0026thinsp;=\u0026thinsp;0.6242).\u003c/p\u003e \u003cp\u003eTaken together, increased immobility in the center zone of the OF test and decreased exploratory activity in the Y-maze test indicate apathy-like behavior in CTE-6m mice.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBased on the behavioral phenotypes, we conducted immunohistochemical analysis. We examined three key parameters: BBB disruption, neuronal cell death in cortex and hippocampus (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE).\u003c/p\u003e \u003cp\u003ePrussian blue staining showed minimal ferric iron deposits in CTE‑3m mice brain tissue (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). Contrastingly, CTE‑6m mice displayed pronounced ferric iron deposition in the cortex, particularly the cingulum bundle, indicating severe BBB disruption.\u003c/p\u003e \u003cp\u003eH\u0026amp;E staining assessed cellular morphology and apoptosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG,H). One-way ANOVA with Dunnett's post-hoc test showed significant increases in pyknotic cells in the cortex of CTE‑3m (n\u0026thinsp;=\u0026thinsp;6; p\u0026thinsp;=\u0026thinsp;0.0075) and CTE‑6m (n\u0026thinsp;=\u0026thinsp;6; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) groups versus controls (n\u0026thinsp;=\u0026thinsp;6). The corpus callosum (CC) showed significant narrowing in CTE‑6m (n\u0026thinsp;=\u0026thinsp;6; Kruskal-Wallis test; Dunn's post hoc; p\u0026thinsp;=\u0026thinsp;0.0347) and CTE‑3m (n\u0026thinsp;=\u0026thinsp;6; p\u0026thinsp;=\u0026thinsp;0.0257) mice compared to controls (n\u0026thinsp;=\u0026thinsp;6).\u003c/p\u003e \u003cp\u003eA similar pattern was observed in the striatum, which is a critical component of the basal ganglia involved in dopaminergic signaling and regulation of goal-directed behavior.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e One-way ANOVA with Dunnett\u0026rsquo;s post hoc analysis revealed that the striatum was significantly impaired in both the CTE‑3m (n\u0026thinsp;=\u0026thinsp;6; p\u0026thinsp;=\u0026thinsp;0.0118) and CTE‑6m (n\u0026thinsp;=\u0026thinsp;6; p\u0026thinsp;=\u0026thinsp;0.0011) groups compared to controls (n\u0026thinsp;=\u0026thinsp;6).\u003c/p\u003e \u003cp\u003eThe hippocampus, a region central to learning and memory, showed increased cell death in the CTE‑6m group (n\u0026thinsp;=\u0026thinsp;6) compared to controls (n\u0026thinsp;=\u0026thinsp;6; one-way ANOVA; Dunnett's post hoc test; p\u0026thinsp;=\u0026thinsp;0.0006). No differences were found between control and CTE‑3m groups (n\u0026thinsp;=\u0026thinsp;6; p\u0026thinsp;=\u0026thinsp;0.0529). High-magnification images of CA1 and CA3 revealed neurodegeneration in CTE‑6m mice hippocampus.\u003c/p\u003e \u003cp\u003eWe also evaluated phospho‑Tau (pTau Ser202, Thr 205; AT8) alongside microglial activation (IBA1), reactive oxygen species (ROS), and phosphorylated TDP‑43 (pTDP43). Analysis was performed using immunofluorescence (IF) microscopy for ROS in cortical regions, while western blotting and PCR quantified protein and gene expression across the brain (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Results showed CTE severity correlated with increases in AT8, IBA1, and ROS levels, while pTDP43 decreased with cognitive decline and BBB deterioration shown in previous findings (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eWhole‑brain western blot analyses showed AT8 levels were elevated in CTE‑6m (n\u0026thinsp;=\u0026thinsp;6) compared to controls (n\u0026thinsp;=\u0026thinsp;6; one-way ANOVA; Tukey's post hoc; p\u0026thinsp;=\u0026thinsp;0.0036) and CTE‑3m (n\u0026thinsp;=\u0026thinsp;6; p\u0026thinsp;=\u0026thinsp;0.0032) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC, D). No differences in AT8 expression were found between control and CTE‑3m (p\u0026thinsp;=\u0026thinsp;0.9977).\u003c/p\u003e \u003cp\u003eTo investigate cortical tau pathology, we differentiated between neuronal and glial AT8 immunoreactivity. Neuronal AT8 was significantly elevated in CTE‑3m (n\u0026thinsp;=\u0026thinsp;9; one-way ANOVA; Tukey's post hoc; p\u0026thinsp;=\u0026thinsp;0.0492) and CTE‑6m (n\u0026thinsp;=\u0026thinsp;10; p\u0026thinsp;=\u0026thinsp;0.0016) compared to control (n\u0026thinsp;=\u0026thinsp;9), with greater accumulation at 6 months, though not statistically significant between CTE groups (p\u0026thinsp;=\u0026thinsp;03599). Glial AT8 increased significantly only in CTE‑6m (n\u0026thinsp;=\u0026thinsp;9; one-way ANOVA; Tukey's post hoc) versus control (n\u0026thinsp;=\u0026thinsp;8; p\u0026thinsp;=\u0026thinsp;0.0244) and CTE‑3m (n\u0026thinsp;=\u0026thinsp;9; p\u0026thinsp;=\u0026thinsp;0.0258), with no difference between control and CTE-3m (p\u0026thinsp;=\u0026thinsp;0.9934) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE\u0026ndash;H).\u003c/p\u003e \u003cp\u003eCortical pTDP43 showed significant reduction in CTE‑6m (n\u0026thinsp;=\u0026thinsp;8; Kruskal-Wallis; Dunn's post hoc) compared to control (n\u0026thinsp;=\u0026thinsp;9; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0012) and CTE‑3m (n\u0026thinsp;=\u0026thinsp;9; p\u0026thinsp;=\u0026thinsp;0.0017), with no difference between control and CTE‑3m (p\u0026thinsp;\u0026gt;\u0026thinsp;0.9999) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eI). Cortical IBA1 immunoreactivity showed enhanced microglial activation in CTE‑3m (n\u0026thinsp;=\u0026thinsp;7; one-way ANOVA; Tukey's post-hoc test; p\u0026thinsp;=\u0026thinsp;0.0061) and CTE‑6m (n\u0026thinsp;=\u0026thinsp;8; p\u0026thinsp;=\u0026thinsp;0.0112) versus controls (n\u0026thinsp;=\u0026thinsp;7) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eJ).\u003c/p\u003e \u003cp\u003eCortical ROS accumulation, quantified via relative fluorescence, was significantly elevated in the CTE‑6m group (n\u0026thinsp;=\u0026thinsp;9; Kruskal-Wallis; Dunn's post hoc) compared to control (n\u0026thinsp;=\u0026thinsp;9; p\u0026thinsp;=\u0026thinsp;0.0054) and CTE‑3m (n\u0026thinsp;=\u0026thinsp;7; p\u0026thinsp;=\u0026thinsp;0.0059) groups, with no difference between control and CTE‑3m (p\u0026thinsp;\u0026gt;\u0026thinsp;0.9999) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eK).\u003c/p\u003e \u003cp\u003eFinally, whole-brain gene expression analyses targeting \u003cem\u003eMapt, Aif1, Tardbp\u003c/em\u003e, and \u003cem\u003eGfap\u003c/em\u003e were performed (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eL). \u003cem\u003eMapt\u003c/em\u003e expression increased significantly in CTE‑6m (n\u0026thinsp;=\u0026thinsp;8; one-way ANOVA; Tukey's post hoc) versus control (n\u0026thinsp;=\u0026thinsp;8; p\u0026thinsp;=\u0026thinsp;0.0012) and CTE‑3m (n\u0026thinsp;=\u0026thinsp;8; p\u0026thinsp;=\u0026thinsp;0.0015), with no difference between control and CTE‑3m (p\u0026thinsp;=\u0026thinsp;0.9931). \u003cem\u003eAif1\u003c/em\u003e fold change increased in CTE-6m (n\u0026thinsp;=\u0026thinsp;7; one-way ANOVA; Tukey's post hoc) versus control (n\u0026thinsp;=\u0026thinsp;7; p\u0026thinsp;=\u0026thinsp;0.0235) and CTE‑3m (n\u0026thinsp;=\u0026thinsp;7; p\u0026thinsp;=\u0026thinsp;0.0164) without difference between control and CTE-3m (p\u0026thinsp;=\u0026thinsp;0.9843). \u003cem\u003eTardbp\u003c/em\u003e expression decreased in CTE‑6m (n\u0026thinsp;=\u0026thinsp;8; Kruskal-Wallis; Dunn's post hoc test) compared to control (n\u0026thinsp;=\u0026thinsp;7; p\u0026thinsp;=\u0026thinsp;0.0002) and CTE‑3m (n\u0026thinsp;=\u0026thinsp;7; p\u0026thinsp;=\u0026thinsp;0.0213) groups, with no difference between control and CTE-3m (p\u0026thinsp;=\u0026thinsp;0.4410). \u003cem\u003eGfap\u003c/em\u003e expression increased in CTE‑3m (n\u0026thinsp;=\u0026thinsp;8; one-way ANOVA' Tukey's post hoc) versus control (n\u0026thinsp;=\u0026thinsp;8; p\u0026thinsp;=\u0026thinsp;0.0005) but reduced in CTE‑6m (n\u0026thinsp;=\u0026thinsp;8; p\u0026thinsp;=\u0026thinsp;0.0045 vs control; p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 vs CTE-3m), implying glial cell loss in CTE-6m.\u003c/p\u003e \u003cp\u003eCollectively, these data underscore the robust neuropathological features of the CTE‑6m model, supporting its superior suitability for long-term CTE studies.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGene profiling indicates that TRAF6 plays a critical role in long-term CTE development\u003c/h3\u003e\n\u003cp\u003eFollowing confirmation of severe neurodamage features in the brain, bulk RNA-seq was performed to evaluate gene expression and identify key pathways associated with CTE‑6m model severity.\u003c/p\u003e \u003cp\u003eHeatmap analysis showed different gene expression patterns between CTE and control groups and principal component analysis (PCA) revealed distinct gene expression profiles among CTE‑6m, CTE‑3m, and control groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA,B).\u003c/p\u003e \u003cp\u003eGenes meeting p-value criteria were analyzed using STRING for protein network interactions. Top 10 clusters (DBSCAN Clustering; ε parameter\u0026thinsp;=\u0026thinsp;2) showed the highest gene count in the signaling by receptor tyrosine kinases in cluster 1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). The protein interaction map of Cluster 1 was presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD. Nodes represent proteins, while edges denote protein interactions, with edge colors indicating interaction types. Further analysis of nodes with the highest average combined scores, evaluating edge interactions between nodes, revealed that the top-ranked nodes are involved in ubiquitin signaling, with TRAF6 emerging as a principal mediator of the network, demonstrating the highest combined score supported by coexpression data, experimentally validated interactions, and automated text-mining analytics (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE).\u003csup\u003e\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe Cluster 1 gene set was reconfirmed in the bulk RNA-seq data, displaying significant upregulation in the CTE-6m group compared to the control (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF). The average fold change of Cluster 1 genes was markedly elevated in the CTE-6m group (n\u0026thinsp;=\u0026thinsp;42; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; Kruskal-Wallis test with Dunn's post hoc) compared to CTRL (n\u0026thinsp;=\u0026thinsp;42), and similarly significant upregulation was observed in the CTE-3m group (n\u0026thinsp;=\u0026thinsp;32; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) versus CTRL (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG).\u003c/p\u003e \u003cp\u003eTo finally confirm the significance of \u003cem\u003eTraf6\u003c/em\u003e, the gene expression levels were quantified by whole-brain PCR analysis (n\u0026thinsp;=\u0026thinsp;8 for all; one-way ANOVA with Dunnett\u0026rsquo;s post hoc test) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eH). An upregulated fold change was observed for \u003cem\u003eTraf6\u003c/em\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), \u003cem\u003eTlr4\u003c/em\u003e (p\u0026thinsp;=\u0026thinsp;0.0010), and \u003cem\u003eNfkb1\u003c/em\u003e (p\u0026thinsp;=\u0026thinsp;0.0023) in the CTE‑6m group compared to controls, while no significant changes were detected in the CTE-3m group (p\u0026thinsp;=\u0026thinsp;0.9951 for \u003cem\u003eTraf6\u003c/em\u003e; p\u0026thinsp;=\u0026thinsp;0.7950 for \u003cem\u003eTlr4\u003c/em\u003e; p\u0026thinsp;=\u0026thinsp;0.9638 for \u003cem\u003eNfkb1\u003c/em\u003e).\u003c/p\u003e \u003cp\u003eSecond, TRAF6 immunoreactivity was examined by IF microscopy (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eI). Kruskal-Wallis testing revealed no significant difference in cortical TRAF6 expression between the CTE‑3m (n\u0026thinsp;=\u0026thinsp;9) and CTE‑6m (n\u0026thinsp;=\u0026thinsp;8; p\u0026thinsp;\u0026gt;\u0026thinsp;0.9999) groups; however, both groups significantly differed from controls (n\u0026thinsp;=\u0026thinsp;8; p\u0026thinsp;=\u0026thinsp;0.0131 versus CTE-3m; p\u0026thinsp;=\u0026thinsp;0.0016 versus CTE-6m) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eJ). Conversely, whole-brain western blot analysis using one‑way ANOVA with Tukey's post hoc test (n\u0026thinsp;=\u0026thinsp;6 for all) revealed a significant increase in TRAF6 in the CTE‑6m group compared to both control (p\u0026thinsp;=\u0026thinsp;0.0211) and CTE‑3m (p\u0026thinsp;=\u0026thinsp;0.0235), while no difference was observed between control and CTE‑3m (p\u0026thinsp;=\u0026thinsp;0.9984) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eK,L). These findings indicate that TRAF6 accumulation is not confined to cortical regions but is distributed broadly across the brain, suggesting a widespread involvement in CTE pathology.\u003c/p\u003e \u003cp\u003eCollectively, the observed elevation of TRAF6 expression, particularly in the 6-month CTE model, implies that TLR4 signaling mediated by TRAF6 and NFκB activation may serve as a central mechanism driving the chronic neuroinflammatory processes characteristic of advanced CTE stages. To delineate the mechanistic contribution of TRAF6 to CTE progression, subsequent investigations employed a TRAF6 knockdown (KD) mouse model, with a focused examination of the 6-month CTE cohort to elucidate the specific role of TRAF6 in modulating disease pathology.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eTRAF6 knockdown to investigate its role in long-term CTE progression\u003c/h3\u003e\n\u003cp\u003eBased on its significance, a TRAF6 KD model was established using TRAF6‑shRNA-AAV9 for neuronal transduction via intracerebroventricular (ICV) injection (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, B). A non-targeting scrambled shRNA-GFP virus served as the sham control. One week post-injection, animals from both groups underwent CTE induction through five TBI episodes over two weeks, as previously described. Six months post-injection, all mice were euthanized, and blood serum and brain tissues were collected for analysis. Consequently, four experimental groups were defined: sham, TRAF6 KD (KD), TBI (transduced with scrambled virus), and TRAF6 KD with TBI induction (KD TBI).\u003c/p\u003e \u003cp\u003eSeveral animals were euthanized 2 weeks after injection to verify appropriate viral transduction in the brain. Immunohistochemical analysis confirmed shRNA virus expression in sham and TRAF6 KD groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). qPCR (n\u0026thinsp;=\u0026thinsp;3 for all; unpaired t-test) showed downregulated \u003cem\u003eTraf6\u003c/em\u003e (p\u0026thinsp;=\u0026thinsp;0.0260) in TRAF6 KD versus SHAM group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). After six months, viral expression was confirmed using GFP detection (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE). In the IF analysis performed 6 months post-injection, TRAF6 expression in both the KD TBI (n\u0026thinsp;=\u0026thinsp;7; one-way ANOVA; Tukey\u0026rsquo;s post hoc test; p\u0026thinsp;=\u0026thinsp;0.5578) and KD (n\u0026thinsp;=\u0026thinsp;7; p\u0026thinsp;=\u0026thinsp;0.9357) groups remained at levels comparable to those in sham controls (n\u0026thinsp;=\u0026thinsp;7), suggesting minimal baseline expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF,G). Moreover, TRAF6 expression in the KD TBI (p\u0026thinsp;=\u0026thinsp;0.0002) and KD (p\u0026thinsp;=\u0026thinsp;0.0012) groups was significantly lower than in the TBI group (n\u0026thinsp;=\u0026thinsp;7; p\u0026thinsp;=\u0026thinsp;0.0053 vs. control).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eTRAF6 knockdown is neuroprotective in TBI, but Induces TBI-like pathogenesis without trauma\u003c/h3\u003e\n\u003cp\u003eAfter confirming TRAF6 KD, further analyses delineated its role in CTE progression. H\u0026amp;E staining showed the KD TBI group restored tissue architecture compared to the TBI group, which had many pyknotic cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). More nuclei were observed in the KD TBI group's cortex. Also, hippocampal structures were more intact in the KD TBI group (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). The CA1 and CA2 subregions of the KD TBI group maintained structures similar to the SHAM group (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC), while the TRAF6 KD model without TBI showed significant disruption (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-C).\u003c/p\u003e \u003cp\u003eQuantitative analysis based on nuclei counts within selected regions in the cortex, CA1, CA2, and hippocampus supported these findings (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). In the cortex, one-way ANOVA (n\u0026thinsp;=\u0026thinsp;8 for all; Tukey's post hoc test) showed the KD TBI group did not differ from SHAM (p\u0026thinsp;=\u0026thinsp;0.9867) but differed from TBI (p\u0026thinsp;=\u0026thinsp;0.0443) and KD (p\u0026thinsp;=\u0026thinsp;0.0284) groups. Significant differences existed between sham and TBI groups (p\u0026thinsp;=\u0026thinsp;0.0205), and sham and KD groups (p\u0026thinsp;=\u0026thinsp;0.0128), with no difference between TBI and KD groups (p\u0026thinsp;=\u0026thinsp;0.9973).\u003c/p\u003e \u003cp\u003eFor CA1 (n\u0026thinsp;=\u0026thinsp;7 for all), CA2 (n\u0026thinsp;=\u0026thinsp;7 for all), and hippocampus (n\u0026thinsp;=\u0026thinsp;7 for all), the KD TBI group showed no difference from SHAM (p\u0026thinsp;=\u0026thinsp;0.4090, 0.9996, 0.8955), but differed from TBI group (p\u0026thinsp;=\u0026thinsp;0.0052, 0.0054, 0.0026). Both TBI (p\u0026thinsp;=\u0026thinsp;0.0001, 0.0069, 0.0005) and KD groups (p\u0026thinsp;=\u0026thinsp;0.0006, 0.0105, 0.0039) differed from sham, while TBI and KD showed no significant difference (p\u0026thinsp;=\u0026thinsp;0.8875, 0.9980, 0.8188).\u003c/p\u003e \u003cp\u003eA DHE assay was conducted to assess oxidative stress levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE,F). Quantitative analysis by one-way ANOVA with Tukey\u0026rsquo;s post hoc test (n\u0026thinsp;=\u0026thinsp;12 for all) revealed that oxidative stress in the KD TBI group was significantly attenuated compared to that in the TBI group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and was comparable to that in the SHAM (p\u0026thinsp;=\u0026thinsp;0.1580). In contrast, the KD group without TBI exhibited oxidative stress levels similar to those of the TBI group (p\u0026thinsp;=\u0026thinsp;0.8467), differing from both the sham (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0179) and KD TBI (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) groups.\u003c/p\u003e \u003cp\u003eCognitive performance was evaluated using OF and Y-maze tests. One-way ANOVA with Tukey's post hoc test (n\u0026thinsp;=\u0026thinsp;9 for all) showed the KD TBI group demonstrated improved cognitive function versus TBI group (p\u0026thinsp;=\u0026thinsp;0.0003), comparable to SHAM (p\u0026thinsp;=\u0026thinsp;0.5580) in average time spent in center zone (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG,H). The KD group showed cognitive abilities similar to sham (p\u0026thinsp;=\u0026thinsp;0.8742) and KD-TBI (p\u0026thinsp;=\u0026thinsp;0.9418) groups, while TBI group showed impairment (p\u0026thinsp;=\u0026thinsp;0.0112 versus control). For moved distance (n\u0026thinsp;=\u0026thinsp;9 for all; one-way ANOVA; Tukey's post hoc), KD TBI differed from TBI (p\u0026thinsp;=\u0026thinsp;0.0003) but matched SHAM (p\u0026thinsp;=\u0026thinsp;0.8742), while TBI differed from SHAM (p\u0026thinsp;=\u0026thinsp;0.0112). The KD group did not differ significantly from the SHAM group (P\u0026thinsp;=\u0026thinsp;0.8742 vs. control; P\u0026thinsp;=\u0026thinsp;0.0015 vs. TBI). The center entries showed apathy (n\u0026thinsp;=\u0026thinsp;9 for all; one-way ANOVA; Tukey's post hoc), with KD TBI showing improvement compared to TBI (p\u0026thinsp;=\u0026thinsp;0.0021) and SHAM group (p\u0026thinsp;=\u0026thinsp;0.6234). TBI showed decreased center entries versus control (p\u0026thinsp;=\u0026thinsp;0.0464) and KD groups (p\u0026thinsp;=\u0026thinsp;0.0021), with no difference between control and KD groups (P\u0026thinsp;\u0026gt;\u0026thinsp;0.4630).\u003c/p\u003e \u003cp\u003eY-maze test (n\u0026thinsp;=\u0026thinsp;9 per group) with one-way ANOVA revealed TBI mice had impaired exploration versus controls, showing reduced distance traveled (p\u0026thinsp;=\u0026thinsp;0.0378) and fewer arm entries (p\u0026thinsp;=\u0026thinsp;0.0036) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eI,J). KD TBI mice showed restored exploration compared to TBI mice, with increased distance (p\u0026thinsp;=\u0026thinsp;0.0203) and entries (p\u0026thinsp;=\u0026thinsp;0.0179), matching sham controls (distance: p\u0026thinsp;=\u0026thinsp;0.9952; entries: p\u0026thinsp;=\u0026thinsp;0.9250). KD mice were similar to SHAM and KD TBI mice but differed from TBI mice (distance: p\u0026thinsp;=\u0026thinsp;0.0016; entries: p\u0026thinsp;=\u0026thinsp;0.0041). No differences appeared in correct alternations (p\u0026thinsp;=\u0026thinsp;0.4548), indicating preserved spatial working memory.\u003c/p\u003e \u003cp\u003eThese findings show TRAF6 KD provides therapeutic benefits in TBI-induced CTE by preserving tissue integrity, reducing oxidative stress, and maintaining cognitive function, while without TBI, TRAF6 KD causes TBI-like pathogenesis not yet manifesting in cognitive impairment.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eTRAF6 knockdown shows therapeutic effects in TBI, and K63-linked ubiquitination is key to these pathological changes\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo assess therapeutic effects in the KD TBI group, three pathological markers of CTE (AT8, IBA1, and SMI312) were evaluated across groups. IF analysis of AT8 (n\u0026thinsp;=\u0026thinsp;8 for all, one-way ANOVA; Tukey's post hoc test) showed significantly reduced accumulation in the cortex of KD TBI compared to the TBI group (p\u0026thinsp;=\u0026thinsp;0.0006 vs. KD TBI; p\u0026thinsp;=\u0026thinsp;0.0138 vs. SHAM) and was comparable to SHAM (p\u0026thinsp;=\u0026thinsp;0.6355) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA, B). Mice with KD without trauma showed CTE-like pathology similar to TBI (p\u0026thinsp;=\u0026thinsp;0.9577) and higher than both sham (p\u0026thinsp;=\u0026thinsp;0.0447) and KD TBI groups (p\u0026thinsp;=\u0026thinsp;0.0024). However, the distribution of AT8 differed between groups; whereas AT8 focally accumulated in the nucleus in TBI mice, a broader accumulation across the nuclear area was observed in KD mice.\u003c/p\u003e \u003cp\u003eOne-way ANOVA with Tukey\u0026rsquo;s post hoc analysis (n\u0026thinsp;=\u0026thinsp;7 for all) of \u003cem\u003eMapt\u003c/em\u003e mRNA fold-change expression further corroborated these findings. The KD TBI group showed significant \u003cem\u003eMapt\u003c/em\u003e downregulation comparable to sham controls (p\u0026thinsp;=\u0026thinsp;0.5026), relative to the TBI group (p\u0026thinsp;=\u0026thinsp;0.0492 versus KD TBI; p\u0026thinsp;=\u0026thinsp;0.0018 versus sham controls). KD without trauma showed upregulated \u003cem\u003eMapt\u003c/em\u003e mRNA levels, similar to TBI (p\u0026thinsp;=\u0026thinsp;0.9854) and higher than sham (p\u0026thinsp;=\u0026thinsp;0.0007) and KD TBI (p\u0026thinsp;=\u0026thinsp;0.0230). While both KD and TBI groups showed altered gene expression and tau hyperphosphorylation, KD-TBI reduced these pathological markers.\u003c/p\u003e \u003cp\u003eNext, the microglial activation marker, IBA1, was evaluated in all groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC, D). One-way ANOVA with Tukey\u0026rsquo;s post hoc analysis (n\u0026thinsp;=\u0026thinsp;8 for all) revealed that IBA1 expression in the KD-TBI group was significantly reduced to levels comparable to those in the SHAM group (p\u0026thinsp;=\u0026thinsp;0.7579), relative to the TBI group (p\u0026thinsp;=\u0026thinsp;0.0041 versus KD-TBI; p\u0026thinsp;=\u0026thinsp;0.0443 versus sham controls). KD without trauma showed increased IBA1 expression, similar to TBI (p\u0026thinsp;=\u0026thinsp;0.1050) and significantly different from sham (p\u0026thinsp;=\u0026thinsp;0.0001) and KD TBI (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). The gene expression of \u003cem\u003eAif1\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;7 for all; one-way ANOVA: Tukey's post hoc test), encoding IBA1, was altered in KD-TBI to SHAM levels (p\u0026thinsp;=\u0026thinsp;0.9423), relative to TBI (p\u0026thinsp;=\u0026thinsp;0.0317 versus KD-TBI; p\u0026thinsp;=\u0026thinsp;0.0086 versus sham). The KD group showed \u003cem\u003eAif1\u003c/em\u003e upregulation relative to sham (p\u0026thinsp;=\u0026thinsp;0.0021) and KD TBI groups (p\u0026thinsp;=\u0026thinsp;0.0083).\u003c/p\u003e \u003cp\u003eTo confirm neurofilament integrity, SMI312 immunostaining was performed (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE). One-way ANOVA with Tukey's post hoc analysis (n\u0026thinsp;=\u0026thinsp;6 for all) showed SMI312 levels in the KD TBI were restored compared to the TBI group (p\u0026thinsp;=\u0026thinsp;0.0075) and similar to SHAM group (p\u0026thinsp;=\u0026thinsp;0.0016), indicating neurofilament deterioration in the TBI group (p\u0026thinsp;=\u0026thinsp;0.0271 versus sham) was mitigated by TRAF6 KD. KD without trauma showed SMI312 loss comparable to the TBI group (p\u0026thinsp;=\u0026thinsp;0.5914) and different from sham (p\u0026thinsp;=\u0026thinsp;0.0016) and KD TBI groups (p\u0026thinsp;=\u0026thinsp;0.0004) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF).\u003c/p\u003e \u003cp\u003eK48-linked polyubiquitination (Ub-K48) quantification (n\u0026thinsp;=\u0026thinsp;14 for all; one-way ANOVA; Tukey's post hoc test) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eG-H) showed increased immunoreactivity in the TBI group versus SHAM (p\u0026thinsp;=\u0026thinsp;0.0071), with levels attenuated in KD TBI (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 vs. TBI). No differences were found between KD TBI and SHAM (p\u0026thinsp;=\u0026thinsp;0.4249). The KD group without trauma differed from SHAM (p\u0026thinsp;=\u0026thinsp;0.0113) and KD TBI groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) but not from the TBI group (0.9984).\u003c/p\u003e \u003cp\u003eBrown-Forsythe and Welch ANOVA (n\u0026thinsp;=\u0026thinsp;8 for all) showed K48-linked polyubiquitination was more concentrated in TBI group nuclei than SHAM (p\u0026thinsp;=\u0026thinsp;0.0022). KD TBI (p\u0026thinsp;=\u0026thinsp;0.0272 versus TBI) recovered to SHAM levels (p\u0026thinsp;=\u0026thinsp;0.9419). The KD group matched the TBI group (p\u0026thinsp;=\u0026thinsp;0.9406) but differed from sham (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and KD TBI (p\u0026thinsp;=\u0026thinsp;0.0349) groups.\u003c/p\u003e \u003cp\u003eFor K63‑linked polyubiquitination (Ub‑K63) assessment (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eI,J), quantitative analysis (n\u0026thinsp;=\u0026thinsp;10 for all) showed KD‑dependent characteristics, with patterns attenuated in KD TBI showing no difference from the sham (p\u0026thinsp;=\u0026thinsp;0.8680) and TBI (p\u0026thinsp;=\u0026thinsp;0.1001) groups. TBI rarely showed Ub‑K63 accumulation (p\u0026thinsp;=\u0026thinsp;0.3873 versus SHAM), while KD induced intensive Ub-K63 accumulation (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 versus sham and KD TBI; p\u0026thinsp;=\u0026thinsp;0.0051 versus TBI), suggesting TRAF6-dependent regulation. Nuclear distributions were evaluated given its role in quality control (QC) and DNA repair.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eNuclear Ub-K63, associated with DNA damage response and transcription regulation, was significantly reduced in KD TBI versus TBI group (p\u0026thinsp;=\u0026thinsp;0.0205). The TBI group showed higher nuclear Ub‑K63 levels than SHAM (p\u0026thinsp;=\u0026thinsp;0.0313), while KD TBI levels matched sham controls (p\u0026thinsp;=\u0026thinsp;0.4704). The KD group without trauma had high nuclear K63‑linked polyubiquitination similar to TBI group (p\u0026thinsp;=\u0026thinsp;0.0653) and significantly different from SHAM (p\u0026thinsp;=\u0026thinsp;0.0116) and KD TBI groups (p\u0026thinsp;=\u0026thinsp;0.0014). K63 ubiquitination appears more involved in nuclear protein QC and DNA repair in both TBI and KD conditions, with KD mouse brain mediating Ub-K63 polyubiquitination more actively, though this effect returns to SHAM level when combined with TBI.\u003c/p\u003e \u003cp\u003eOverall, TRAF6 KD in CTE exerted significant therapeutic effects by normalizing key pathological markers, including tau hyperphosphorylation, microglial activation, neurofilament degradation, and dysregulated ubiquitination patterns, while also playing a dual role in inducing CTE-like pathogenesis in the absence of trauma. Circulating miRNA expression in blood serum was assessed to determine if neuropathological changes were mirrored in blood, addressing the lack of diagnostic biomarkers for CTE.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eBrain condition is reflected in miRNA expression in mouse blood serum\u003c/h3\u003e\n\u003cp\u003eMouse blood serum was extracted from each group and subjected to small RNA sequencing (miRNA-seq) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). Differential expression analyses identified miRNAs associated with long-term TBI and determined whether cerebral miRNA signatures appeared in peripheral circulation. Because both the KD and TBI groups exhibited CTE-like pathology in the brain, each was first compared with sham controls, and then the patterns were compared between sham and KD TBI.\u003c/p\u003e \u003cp\u003eVolcano plot analysis of 396 mature miRNAs revealed that only a small subset met the predefined fold-change and p-value thresholds in each pairwise comparison (See Supplementary Table\u0026nbsp;1) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). Notably, SHAM vs. KD showed predominantly downregulated miRNAs, whereas SHAM vs. TBI showed upregulated miRNAs. The SHAM vs. KD TBI comparison yielded very few differentially expressed miRNAs, mirroring the minimal pathology observed in KD TBI brains. The comparisons of KD TBI vs. KD and KD TBI vs. TBI exhibited similar patterns to those observed in SHAM vs. KD and SHAM vs. TBI, respectively.\u003c/p\u003e \u003cp\u003eTo identify miRNAs commonly altered in KD and TBI groups versus sham, we filtered for significantly downregulated miRNAs in both comparisons. Two miRNAs\u0026mdash;mmu‑miR‑7a‑5p and mmu‑miR‑351‑5p\u0026mdash;were consistently downregulated, implicated in PI3K/AKT and NFκB signaling (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC, D). \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e These miRNAs were also reduced in KD TBI versus sham TBI (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE). Conversely, mmu‑miR‑574‑3p was upregulated in both KD and TBI, with miR-574 regulating Toll-like receptor signaling for proliferation control by arm variant, but showed no difference between the SHAM and KD TBI groups.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eGiven the resemblance between sham and KD TBI brains, we compared KD TBI with KD and TBI individually (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF, G). Three miRNAs\u0026mdash;mmu‑miR‑16‑2‑3p, mmu‑miR‑451a, and mmu‑miR‑7687‑3p\u0026mdash;were uniquely upregulated in KD TBI; these regulate proliferations via PI3K/AKT and NFκB signaling, though mmu-miR-7687-3p\u0026rsquo;s role is not well-verified.\u003csup\u003e\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e Finally, miRNAs dysregulated in both TBI vs sham and TBI vs KD TBI were identified: miR‑122‑5p and miR‑467f were upregulated, while miR‑3535 and miR‑301a‑3p were downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eH). miR‑122‑5p promotes inflammation via PI3K/AKT disruption, while miR-467f regulates TNF in p38 MAPK pathway as an anti-inflammatory modulator.\u003csup\u003e\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e miR‑3535 is linked to Nrf2 pathway redox regulation, and miR‑301a‑3p affects STAT3/AKT inflammation and behavioral phenotypes.\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn summary, miRNA‑seq of blood serum reflects CTE-like brain pathology: minimal changes in KD TBI, marked dysregulation in KD or TBI alone, and identification of PI3K/AKT\u0026ndash; and NFκB\u0026ndash;related miRNAs as disease mediators.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study was built upon the need for validated CTE diagnostic criteria and characterization, driven by recent evidence linking repeated TBI to progressive neuropathology.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan additionalcitationids=\"CR43\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e Mouse models enable precise control over injury severity, timing, and targeting, yet most studies focus on short-term outcomes, leaving the long-term effects of TBI and its differentiation from other neurodegenerative diseases, especially in aging populations with comorbidities, poorly understood.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eTo address these gaps, we established two trauma-induced mouse groups maintained for three or six months post-TBI. Notably, only the six-month cohort exhibited anxiety, reduced exploration, prolonged center zone occupancy, and apathy-like behavior, without impairments in spatial memory (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e Apathy, a hallmark symptom of CTE distinct from dementia-related disorders, is associated with dysfunction in the neural circuit involving the prefrontal cortex, anterior cingulate cortex, and nucleus accumbens.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e Therefore, the reduced exploratory behavior observed in CTE‑6m mice likely indicates progressive disruption of these fronto-striatal motivational networks.\u003c/p\u003e \u003cp\u003eFurther analyses revealed that six-month CTE mice exhibited significant deterioration in brain structures, including the cortex, corpus callosum, hippocampus, and the BBB (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These changes were marked by pathological accumulation of p-Tau, microglial activation, pTDP43, ROS and other pathological markers (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). While AT8 pathology was present in both three- and six-month groups, widespread tau hyperphosphorylation and associated markers emerged exclusively at six months, indicating that TBI-induced CTE progresses over time, complicating early clinical diagnosis.\u003c/p\u003e \u003cp\u003eIn the six-month model, RNA-seq and protein network analyses revealed significant upregulation of ubiquitination-related signaling molecules in CTE mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among these, TRAF6 was selected for further investigation, and its pathway components were found to be dysregulated in CTE. TRAF6 mediates signaling cascades that activate NFκB and MAPK pathways and functions as a RING-type E3 ubiquitin ligase, catalyzing Lys63-linked ubiquitin chains on itself and its substrates.\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e While TRAF6 has been studied in acute TBI, its direct role in CTE pathology has not yet been explored.\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAs a first study to directly link TRAF6 to CTE, we generated a TRAF6 KD model to evaluate its contribution to TBI-induced CTE. TRAF6 KD markedly attenuated brain deterioration, exerting protective effects on tissue structure, oxidative stress, tau pathology, inflammation, and cellular morphology after repeated TBIs (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e,\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). It alters ubiquitin deposition, relevant to DNA repair and nuclear protein QC in the nucleus but not in cytosol.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e TRAF6 KD in uninjured mice produced CTE pathologies-like ubiquitin deposition, oxidative stress, and structural damage, while cognitive function remained intact. This suggests TRAF6 suppression can induce CTE unless counterbalanced by trauma-activated compensatory signals. Given the involvement of the PI3K-AKT pathway in TRAF6-mediated signaling, as indicated by serum miRNA profiles, associated with cellular energy homeostasis and inflammatory regulation, our data implicate this cascade in CTE progression. \u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eBesides, the miRNA-seq results show serum miRNA profiles reflect brain pathology (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). Nearly identical expression patterns in sham and KD TBI groups revealed circulating miRNAs as minimally invasive biomarkers. We propose miR‑122‑5p, miR‑467f, miR‑3535, and miR‑301a‑3p as blood‑based diagnostics due to their dysregulation in TBI models versus control (SHAM) and therapeutic model (KD TBI).\u003c/p\u003e \u003cp\u003eIn summary, our six-month CTE mouse model recapitulates key features of chronic neuropathology following repetitive TBI, establishing a platform for mechanistic exploration. TRAF6 emerges as a critical driver of neurodegeneration post-trauma, while its knockdown paradoxically induces CTE-like pathology in uninjured mice, suggesting compensatory mechanisms mitigate TRAF6-dependent damage. Transcriptomic analyses identify a circulating miRNA signature that reflects brain pathology and distinguishes resilient (KD TBI) from vulnerable (TBI or KD-only) states, highlighting novel biomarkers and therapeutic targets. Future studies should further elucidate TRAF6-related ubiquitination signaling and validate miRNA signatures in human cohorts for targeted CTE interventions.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eMouse Housing and TBI Modeling\u003c/h2\u003e \u003cp\u003e This study was approved by the Institutional Animal Care and Use Committee (IACUC) of the Korea University Medical Center (approval no. KOREA-2022-0040). We conducted a study using male 25\u0026ndash;30 g 12-week-old C57BL/6 mice (DBL, Eumseong, Republic of Korea). Animals were group-housed with no more than 4 animals per cage and acclimatized to standard laboratory conditions on a 12 h light/dark cycle. Food and water were provided ad libitum. Anesthesia was induced in mice by inhalation of 5% isoflurane in 1 L of oxygen using an animal anesthesia machine (cat no. L-PAS-01D; LMS Korea, Pyeongtaek, Korea). Full anesthesia was achieved within 3 min. During the surgical procedure, anesthesia was maintained using 3% isoflurane in 600 mL of oxygen.\u003c/p\u003e \u003cp\u003eFor TBI modeling, the mice were subjected to a repetitive closed-head impact model of CTE using the Portable Stereotaxic Instrument for Mouse (cat no. 68806, RWD Life Science Co., Shenzhen, China). Animals were anesthetized with 3% isoflurane in oxygen and placed on a heating pad to maintain core temperature at 37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u0026deg;C. A 50 g weight was released from a height of 15 cm through a vertical guide tube onto the intact midline skull (between the bregma and lambda) to deliver a reproducible impact. Five impacts were administered over a two‑week period (one impact every 2\u0026ndash;3 days). Following the final injury, animals were returned to their home cages and housed under standard conditions for either three months (CTE‑3m) or six months (CTE‑6m) to permit chronic pathology to develop. Two weeks before the planned sacrifice, the mice underwent behavioral tests. Continuous monitoring confirmed full recovery from anesthesia between impacts and no gross motor deficits that would confound long-term behavioral outcomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eVirus Injection\u003c/h2\u003e \u003cp\u003eThis study was approved by the Institutional Biosafety Committee of Korea University Medical Center (approval no. KUIBC-2022-0017). ICV injection of AAV9-m-Traf6-shRNA (cat no. shAAV-277724, VECTOR BIOLABS, Philadelphia, PA, USA) or scrambled shRNA (cat no. 1122, VECTOR BIOLABS) was performed in C57BL/6 male mice (11 weeks old, 25\u0026ndash;30 g). The mice were anesthetized with 3% isoflurane and placed in a stereotaxic frame. A small incision was made to expose the skull, and a hole was drilled at the following coordinates: caudal \u0026minus;\u0026thinsp;0.58 mm, lateral 1.25 mm, and ventral \u0026minus;\u0026thinsp;1.77 mm. A total of 1 \u0026micro;L (3.04 \u0026times; 10\u0026sup1;\u0026sup2; GC/mL) of AAV9-m-Traf6-shRNA was injected at a rate of 1 \u0026micro;L/min using a stereotaxic infusion pump (cat no. 68528, Stereotaxic Instrument, RWD Life Science Co.; cat no. 70-4507, Pump 11 Elite Nanomite Infusion, Harvard Apparatus, MA, USA). After injection, the syringe was held in place for 1 min and slowly removed. The incision was closed using 6\u0026thinsp;\u0026minus;\u0026thinsp;0 silk sutures. After recovery from anesthesia, the animals were monitored for abnormalities. Upon completion of the experiment, tissue samples, including brain and blood, were collected and stored at -80\u0026deg;C for further analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eOF Test\u003c/h2\u003e \u003cp\u003eThe mice were moved to the test room 30 min before the open-field test. The illuminance of the test room was maintained in a dim-lit. The mouse was placed in the center of a white chamber (50x50x30cm), and the recording began 10 s after the mouse was transferred to the chamber. Each mouse was allowed to move freely inside the chamber for 5 min, after which it was transferred to its home cage. Animal\u0026rsquo;s cognitive behavior was analyzed by using ANY-maze\u0026trade; (Stoelting Co., Wood Dale, IL, USA) software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eY Maze Test\u003c/h2\u003e \u003cp\u003eThe mice were moved to the test room 30 min before the open-field test. The illuminance of the test room was maintained in a dim-lit. The mouse was placed in the center of the Y-shaped maze, and the recording began 10 s after the translocation of the mouse to the chamber. Each mouse was allowed to move freely inside the chamber for 5 min, after which it was transferred to its home cage. Animal\u0026rsquo;s cognitive behavior was analyzed by using ANY-maze\u0026trade; software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003ePrussian Blue Staining\u003c/h2\u003e \u003cp\u003eFor Prussian blue staining, a VitroView Prussian Blue Stain Kit (cat no. VB-3009, VitroVivo Biotech, Rockville, MD, USA) was purchased. Mouse brain tissue was fixed by 4% Paraformaldehyde (PFA) incubation 48 h at 4\u0026deg;C. After the serial incubation in Sucrose buffer from 30-50-70% overnight for each, the samples were immersed into the Tissue-Tek\u0026reg; O.C.T. Compound (cat no. HIO-0051, Sakura Finetek, Torrance, USA), and frozen at -80\u0026deg;C. Cryosectioned and slide-attached 10 \u0026micro;m tissue slices were incubated for 5 min in freshly prepared working solution (1:1 mix of potassium ferrocyanide and HCl, pre‑equilibrated 30 min at room temperature), followed by a distilled water rinse, counterstaining with Nuclear Fast Red for 5 min, a tap‑water rinse, dehydration through 95% and 100% ethanol (2 min each), clearing in xylene (3\u0026times;5 min), and mounting with Eukitt\u0026reg; Quick-hardening mounting medium (cat no. 03989, Sigma-Aldrich, Steinheim, Germany). Hemosiderin deposits were visualized in blue, nuclei red, and background pink.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eH\u0026amp;E Staining\u003c/h2\u003e \u003cp\u003eCryosections of mouse brains were air-dried and then immersed in xylene for 5 min three times each to remove residual OCT. Slides were rinsed in distilled water for 1 min, hydrated using graded ethanol (100%, 90%, 80%, and 70%; 30 s each), and rinsed again in distilled water for 1 min. Sections were stained with Mayer\u0026rsquo;s hematoxylin (cat. no. 30002, MUTO PURE CHEMICALS Co., Ltd., Tokyo, Japan) for 5 min, washed under running tap water for 5 min, and briefly rinsed with PBS for 1 min. Eosin Y solution (cat. no. 32002, MUTO PURE CHEMICALS CO., LTD., Tokyo, Japan) staining was performed for 5 min, followed by a 5 min distilled‑water wash, dehydration in 70%, 80%, 90%, and 100% ethanol (30 s each), and clearing in xylene (cat. no. 214736, Sigma‑Aldrich, St. Louis, MO, USA) for 5 min each for three times and mounted with Eukitt\u0026reg; Quick-hardening mounting medium (cat no. 03989, Sigma-Aldrich, Steinheim, Germany). Whole-slide imaging was performed using the Panoramic Scan II digital scanner (3DHISTECH, Budapest, Hungary).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eWestern Blotting\u003c/h2\u003e \u003cp\u003eMouse brain tissue was homogenized in ice-cold RIPA buffer (cat no. R0278, Sigma-Aldrich) containing 1% protease and phosphatase inhibitors (cat no. 78446, Thermo Fisher Scientific, Sunnyvale, CA, USA) using a Dounce homogenizer for 30 min at 4\u0026deg;C. The lysate was centrifuged at 16,000 \u0026times; g for 30 min at 4\u0026deg;C, and the supernatant was collected. Protein concentration was determined using the Pierce\u0026trade; Bradford Plus Protein Assay Reagent (cat no. 23238, Thermo Fisher Scientific). Equal amounts of protein (5 \u0026micro;g) were separated on\u0026ndash;4\u0026ndash;15% Mini-Protean TGX Stain-Free Precast Gels (cat no. BR4568086, Bio-Rad Laboratories, Hercules, CA, USA) at 160V for 30 min and then transferred onto a PVDF membrane using preassembled transfer packs (cat no. 1704156, Bio-Rad Laboratories) in a Trans-Blot Turbo Transfer System (cat no. 1704150, Bio-Rad Laboratories). The membrane was blocked with 5% BSA (cat no. 05470, Sigma-Aldrich) in TBS for 30 min at room temperature, followed by incubation overnight at 4\u0026deg;C with the primary antibody (1:100-1:1000 dilution in TBS-T (0.2% Tween-20) supplied with 2.5% BSA, see Supplementary Table\u0026nbsp;2). After three 5-min washes in TBS-T, the membrane was incubated with an HRP-conjugated secondary antibody (1:3000, Supplementary Table\u0026nbsp;2) for 1 h at room temperature and washed again in TBS-T. Chemiluminescence detection was performed using Clarity Western ECL Substrate (cat no. 1705061, Bio-Rad Laboratories), and protein bands were visualized using a gel imager (ChemiDoc MP, Bio-Rad Laboratories) and analyzed using ImageJ software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eIF Staining\u003c/h2\u003e \u003cp\u003eThe sections were permeabilized with 0.4% Triton X-100 in TBS for 15 min at room temperature, blocked with 5% BSA in TBS for 30 min at room temperature, and then incubated overnight at 4\u0026deg;C with primary antibodies in TBST supplemented with 2.5% BSA (see Supplementary Table\u0026nbsp;3). Following three consecutive TBST washes (5 min each), the slides were incubated with fluorophore-conjugated secondary antibodies in TBST supplemented with 2.5% BSA for 1 h at room temperature and then washed again in TBS (three times, 5 min each). Finally, the slides were mounted using the Vectashield Antifade Mounting Medium containing DAPI (cat no. H-1200-10, Vector laboratories Ltd., Peterborough, UK) and imaged using fluorescence microscopy (Carl Zeiss\u0026trade; Axio Vert.A1 Inverted Microscope, Carl Zeiss AG, Oberkochen, Germany) to visualize protein expression.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eDHE Assay\u003c/h2\u003e \u003cp\u003eCryosectioned mouse brain tissues (10 \u0026micro;m thickness) were prepared for Dihydroethidium (DHE, cat no: D7008, Sigma-Aldrich, St. Louis, MO, USA) staining to detect reactive oxygen species (ROS). The sections were incubated with a 10 \u0026micro;M solution of DHE in PBS for 1 h at room temperature in a dark. Following incubation, the sections were washed thrice with PBS to remove excess dye. Slides were mounted using the Vectashield mounting medium. Fluorescence microscopy was performed to visualize and quantify ROS production.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003ePCR Analysis\u003c/h2\u003e \u003cp\u003eTotal RNA was isolated from tissue samples using the TRIzol reagent (cat no. 15596026, Invitrogen, NY, USA) following the manufacturer\u0026rsquo;s protocol. First‑strand cDNA synthesis was carried out with the High‑Capacity RNA‑to‑cDNA Kit (cat no. 4387406, Applied Biosystems). Quantitative PCR was performed using SYBR Green PCR Master Mix (cat no. 4309155, Applied Biosystems) on QuantStudio 5 Real-Time PCR System (A34322, Applied Biosystems) and relative expression levels were determined by normalization to GAPDH via the 2\u003csup\u003e\u0026ndash;ΔΔCt\u003c/sup\u003e method. The primer sequences are listed in Supplementary Table\u0026nbsp;3.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eBulk RNA Sequencing\u003c/h2\u003e \u003cp\u003eTotal RNA concentration was calculated using Quant-IT RiboGreen (cat no. R11490, Invitrogen). To assess the integrity of the total RNA, samples were run on a TapeStation RNA screentape (cat no. 5067\u0026ndash;5576, Agilent Technologies, Waldbronn, Germany). Only high-quality RNA preparations (RIN greater than 7.0) were used for the RNA library construction. A library was independently prepared with 1ug of total RNA for each sample by Illumina TruSeq Stranded mRNA Sample Prep Kit (cat no. 20020595, Illumina, Inc., San Diego, CA, USA). The first step in the workflow involves purifying the poly-A containing mRNA molecules using poly‐T‐attached magnetic beads. Following purification, mRNA was fragmented into small pieces using divalent cations at elevated temperatures. The cleaved RNA fragments were copied into first-strand cDNA using SuperScript II reverse transcriptase (cat no. 18064014; Invitrogen) and random primers. This was followed by synthesis of second-strand cDNA using DNA Polymerase I, RNase H, and dUTP. These cDNA fragments then go through an end repair process, the addition of a single \u0026lsquo;A\u0026rsquo; base, and then ligation of the adapters. The products were purified and enriched using PCR to create a final cDNA library. The libraries were quantified using KAPA Library Quantification kits for Illumina Sequencing platforms, according to the qPCR Quantification Protocol Guide (cat no. KK4854, Kapa Biosystems, Woburn, MA, USA) and qualified using a TapeStation D1000 ScreenTape (cat no. 5067\u0026ndash;5582, Agilent Technologies). Indexed libraries were then submitted to an Illumina NovaSeq6000 (Illumina, Inc., San Diego, CA, USA) and paired-end (2\u0026times;100 bp) sequencing was performed by Macrogen, Inc..\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eSTRING Network Analysis\u003c/h2\u003e \u003cp\u003eSignificantly upregulated mRNAs (2,777 genes; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) identified by bulk RNA-seq were analyzed using the STRING module in Cytoscape v.2.2.0 (Institute for System Biology; WA; USA). A cluster network was constructed using the MCL algorithm with a granularity parameter of 4, followed by filtering nodes with mcl.cluster\u0026thinsp;\u0026gt;\u0026thinsp;10. The resulting 1,848 nodes were processed through STRING v12.0 (Swiss Institute of Bioinformatics; Lausanne; Switzerland) to generate a protein\u0026ndash;protein interaction (PPI) network, incorporating evidence from text mining, genomic neighborhood, experimental data, curated databases, co-expression, gene fusion, and co-occurrence, with a minimum confidence score threshold of 0.40. Network modules were defined using the DBSCAN clustering algorithm with an ε parameter of 2. Cluster 1, representing the largest gene set (101 genes), was further analyzed by sorting the top 20 nodes with the highest node degree, resulting in a network comprising 101 nodes and 756 edges. Global network metrics indicated an average node degree of 15, a local clustering coefficient of 0.600, and a PPI enrichment p-value of \u0026lt;\u0026thinsp;1 \u0026times; 10⁻\u0026sup1;⁶. The average values of coexpression, experimentally determined interactions, automated text mining, and combined scores were calculated.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eImmunohistochemistry\u003c/h2\u003e \u003cp\u003eFor GFP detection, 4 \u0026micro;m paraffin sections of mouse brain tissue were prepared and mounted on Superfrost glass slides (Thermo Fisher Scientific). The tissues were deparaffinized with xylene and rehydrated using a graded ethanol series. Antigen retrieval was performed by immersing the sections in 0.01 M citric acid buffer and heating them in a pressure cooker to reach full pressure, followed by 10 min of high-pressure treatment. Endogenous peroxidase activity was blocked by incubating sections with 3% hydrogen peroxide for 15 min. Nonspecific binding was minimized by incubating the tissue with a blocking reagent (Vector Laboratories, USA). The primary antibody, anti-GFP rabbit antibody (Cat. no. Ab290, Abcam, Cambridge, MA, USA), was diluted 1:500 in PBS and incubated overnight at 4\u0026deg;C. After three washes with PBS, the sections were incubated with a secondary HRP-conjugated anti-rabbit IgG antibody for 1 h. The antibody complex was visualized using diaminobenzidine (DAB) chromogen, and the reaction was monitored under a microscope to ensure optimal staining. The slides were scanned using a Digital Slide Scanner (EasyScan Pro, Motic, USA) to obtain whole-slide images for analysis.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eSmall RNA Sequencing\u003c/h2\u003e \u003cp\u003eRNA isolated from each sample was used to construct sequencing libraries using the SMARTer smRNA-Seq Kit for Illumina following the manufacturer's protocol. Briefly, the Input RNA was polyadenylated to provide a priming sequence for the oligo-(dT) primer. cDNA synthesis is primed by the 3\u0026rsquo; smRNA dT Primer, which incorporates an adapter sequence at the 5\u0026rsquo; end of each first-strand cDNA molecule. When the MMLV-derived PrimeScript\u0026trade; Reverse Transcriptase (RT, cat no: 2680. Takara Bio, Otsu, Japan) reaches the 5\u0026rsquo; end of each RNA template, it adds nontemplated nucleotides which are bound by the SMART smRNA Oligo-enhanced with locked nucleic acid (LNA) technology for greater sensitivity. In the template-switching step, PrimeScript RT uses the SMART smRNA Oligo as a template for the addition of a second adapter sequence to the 3\u0026rsquo; end of each first-strand cDNA molecule. In the next step, full-length Illumina adapters (including index sequences for sample multiplexing) are added during PCR amplification. The Forward PCR Primer binds to the sequence added by the SMART smRNA Oligo, while the Reverse PCR Primer binds to the sequence added by the 3\u0026rsquo; smRNA dT Primer. The resulting cDNA library included the sequences required for clustering in an Illumina flow cell. Libraries were validated by checking their size, purity, and concentration using an Agilent Bioanalyzer. The libraries were pooled in equimolar amounts and sequenced using an Illumina NovaSeq instrument. Image decomposition and quality value calculations were performed using Illumina pipeline modules.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eStatistics\u003c/h2\u003e \u003cp\u003eAll experimental measurements were performed on at least three independent biological replicates, and the mean values were used for statistical analysis. Data are displayed with error bars indicating mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM, and where appropriate, a two-sided Student\u0026rsquo;s t-test or one-way ANOVA was applied based on assessments of normality and variance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, considered significant). Post-hoc multiple comparisons (e.g., Tukey\u0026rsquo;s or Dunnett\u0026rsquo;s tests) were conducted following ANOVA when significant. Statistical analyses were performed using GraphPad Prism, version 10 (GraphPad Software, San Diego, CA, USA).\u003c/p\u003e "},{"header":"Declarations","content":"\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eData availability\u003c/h2\u003e \u003cp\u003eData are available upon request.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor contributions\u003c/h2\u003e \u003cp\u003eD.L. developed the concept, methodology, validation, formal analysis, and investigation; administered the project; and wrote the original draft. I.H.L. participated in investigation and methodology. M.K., S.C., and H.B. participated in investigation. S.C. participated in visualization and review of original draft. J.I.C. developed the conceptualization and methodology, supervised the project, reviewed and edited the original draft, and secured funding.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThis work was supported by a Korea University Ansan Hospital research grant (O2411971), the Korea University Research Fund (K2508441), the National Research Foundation of Korea (RS-2022-NR071661), and Jonggeundang Co., Ltd.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMayer, A. R., Quinn, D. K. \u0026amp; Master, C. L. The spectrum of mild traumatic brain injury. \u003cem\u003eNeurology\u003c/em\u003e 89, 623\u0026ndash;632 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMajerus, S., Gill-Thwaites, H., Andrews, K. \u0026amp; Laureys, S. 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Implications of Phosphoinositide 3-Kinase-Akt (PI3K-Akt) Pathway in the Pathogenesis of Alzheimer\u0026rsquo;s Disease. \u003cem\u003eMol Neurobiol\u003c/em\u003e 59, 354\u0026ndash;385 (2022).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6652049/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6652049/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eChronic traumatic encephalopathy (CTE) is a progressive neurodegenerative disease leading to cerebral complications. It is triggered by single or repetitive traumatic brain injury during contact sports or combat activities. Due to diagnostic limitations, i.e., being restricted to postmortem analysis, understanding of CTE remains incomplete. While acute CTE mechanisms have been studied, the long-term effects remain inadequately explored. We investigated long-term CTE mechanisms using mouse models with 3- and 6-month progression. The 6-month model showed increased neurodegeneration and upregulation of ubiquitin signaling pathway genes, identifying TRAF6 as the central node. Accordingly, TRAF6 suppression using AAV9-delivered shRNA after brain injury protected against damage and behavioral deficits. However, TRAF6 knockdown in uninjured animals induced CTE-like changes, suggesting trauma activates compensatory mechanisms. Circulating microRNAs from blood serum reflect these brain changes, offering potential for non-invasive diagnostic approaches. Our findings indicate TRAF6 mediated signaling regulate long-term CTE pathology and present targets for therapeutic development.\u003c/p\u003e","manuscriptTitle":"TRAF6-Mediated Ubiquitin Signaling Drives Long-Term Neurodegeneration in a Mouse Model of Chronic Traumatic Encephalopathy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-26 06:05:34","doi":"10.21203/rs.3.rs-6652049/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1c0c1fa5-0ae4-4846-abc2-9a54891ce5df","owner":[],"postedDate":"May 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":48917835,"name":"Biological sciences/Neuroscience/Blood\u0026#x2013;brain barrier"},{"id":48917836,"name":"Biological sciences/Neuroscience/Molecular neuroscience"},{"id":48917837,"name":"Biological sciences/Molecular biology/Proteolysis/Ubiquitylation"}],"tags":[],"updatedAt":"2026-03-11T15:42:38+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-26 06:05:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6652049","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6652049","identity":"rs-6652049","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}