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Chronic traumatic encephalopathy: Diagnostic updates and advances

  • Chronic traumatic encephalopathy (CTE) is a progressive neurodegenerative disease that occurs secondary to repetitive mild traumatic brain injury. Current clinical diagnosis relies on symptomatology and structural imaging findings which often vary widely among those with the disease. The gold standard of diagnosis is post-mortem pathological examination. In this review article, we provide a brief introduction to CTE, current diagnostic workup and the promising research on imaging and fluid biomarker diagnostic techniques. For imaging, we discuss quantitative structural analyses, DTI, fMRI, MRS, SWI and PET CT. For fluid biomarkers, we discuss p-tau, TREM2, CCL11, NfL and GFAP.

    Citation: Kevin Pierre, Vanessa Molina, Shil Shukla, Anthony Avila, Nicholas Fong, Jessica Nguyen, Brandon Lucke-Wold. Chronic traumatic encephalopathy: Diagnostic updates and advances[J]. AIMS Neuroscience, 2022, 9(4): 519-535. doi: 10.3934/Neuroscience.2022030

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  • Chronic traumatic encephalopathy (CTE) is a progressive neurodegenerative disease that occurs secondary to repetitive mild traumatic brain injury. Current clinical diagnosis relies on symptomatology and structural imaging findings which often vary widely among those with the disease. The gold standard of diagnosis is post-mortem pathological examination. In this review article, we provide a brief introduction to CTE, current diagnostic workup and the promising research on imaging and fluid biomarker diagnostic techniques. For imaging, we discuss quantitative structural analyses, DTI, fMRI, MRS, SWI and PET CT. For fluid biomarkers, we discuss p-tau, TREM2, CCL11, NfL and GFAP.



    Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease secondary to repetitive mild traumatic brain injury (mTBI), including concussions and sub-concussive impacts, resulting in long-term issues with cognition, behavior and mood [1][7]. CTE was initially recognized in boxers who developed symptoms like ataxia, memory loss and personality change, and it was coined as the “punch drunk” syndrome or “dementia pugilistica” [1],[3],[4],[8][10]. Over time, it became evident that CTE also affected military personnel, domestic violence victims and those participating in contact sports like football, ice hockey, professional wrestling, rugby, soccer and boxing [1][4],[8].

    Neurodegeneration and symptoms in CTE progress even in the absence of further traumatic insults [2],[6],[11],[12]. mTBI is thought to trigger an inflammatory cascade and lead to blood brain barrier permeability, axonal injury and micro-hemorrhages [13][16]. As a result, there is deposition of pathogenic proteins, including the pathogenic cis-isoform of p-tau, which, through the process termed cistauosis, catalyzes conversion of normal into pathogenic tau [2],[17][21]. As such, CTE develops in pathological stages with worsening depositions of p-tau, neurofibrillary tangles and brain atrophy in similar but distinct fashions as other neurodegenerative diseases like Alzheimer's disease [2].

    The current gold standard diagnosis for CTE is post-mortem pathological examination. Trauma encephalopathy syndrome was proposed to help diagnose patients with CTE. This criterion consists of a history of repetitive brain injury, persistent symptoms over a year and an absence of comorbidities that may also account for the symptoms. Also present should be a cognitive, behavioral or mood impairment in the presence of progressive decline over more than a year, impulsivity or headaches [2],[22][24]. However, patients with CTE present differently and there is no consensus on a single, best set of clinical or research diagnostic criteria [2],[5],[6],[25]. Therefore, there is increasing investigation of adjunctive non-invasive diagnostic modalities. In this paper, we review the recent advances in the use of neuroimaging and fluid biomarkers for early CTE detection.

    Magnetic resonance imaging (MRI) produces images by analyzing tissue characteristics using magnetic fields and radio waves. It is the current imaging modality of choice due to its improved soft tissue differentiation, ability to detect diffuse axonal injury and lack of ionizing radiation compared to computed tomography (CT). The gross, macroscopic structural changes with CTE include cerebral atrophy that is most severe in the frontotemporal lobes, vermis, thalamus, mamillary bodies and hypothalamus. There is also ventricular enlargement, thinning of the corpus callosum and depigmentation of the substantia nigra and locus coeruleus. Though it is not a consistent feature of CTE, neuropathologic change (CTE-NC), i.e., the presence of cavum septum pellucidum in imaging, is associated with CTE. Microhemorrhages representing diffuse axonal injury may also be present [26][30]. These structural findings are not specific to CTE, however [30]. Therefore, there has been increasing research on the use of alternative, more advanced imaging methods as tools to identify and understand the progression of CTE in vivo.

    Methods of quantitative brain volume analyses, like assessing cortical thickness in other neurodegenerative diseases, have provided useful for diagnosis and prognosis [31][34]. A study showed that hippocampal volume in football athletes was inversely correlated with the presence of concussions and amount of football played [35]. These findings, however, may not be specific to CTE considering the volume loss seen in other neurodegenerative diseases [36]. Furthermore, the inclusion criteria consisted of sport participation within the last year in those aged between 18–26. Therefore, it did not necessarily include or correlate with the presence of neuropsychiatric symptoms associated with CTE [16].

    Diffusion tensor imaging (DTI) is an MRI technique that examines the longitudinal diffusion of water through axons to evaluate the orientation and integrity of white matter tracts. A fractional anisotropy (FA) close to 1 means that diffusion occurs along one axis and is otherwise restricted. Axial diffusivity (AD) and radial diffusivity (RD) are similar measures that reflect the magnitude of diffusion running parallel and perpendicular to white matter tracts, respectively [37],[38]. As such, decreased FA, decreased AD and increased RA would be expected in CTE due to decreased white matter integrity. These findings have been demonstrated in mTBI, and even had prognostic value [39][47]. A post-mortem tissue DTI analysis of patients with confirmed CTE-NC by Holleran et al. demonstrated associations between decreased FA and reduced white matter integrity [38]. A DTI analysis by Herweh et al. that evaluated male amateur boxers demonstrated associations between decreased FA and neuropsychological outcomes [48]. A study by Kraus et al. showed that study subjects who were included on the basis of having a history of mTBI (22 subjects) or moderate to severe TBI (17 subjects) had decreased FA and RD. The study also suggested that DTI can help to determine the relationship between TBI and cognitive differences and distinguish the spectrum and severity of TBI [49]. Another study showed decreased FA and no changes in the RD and FA in patients who were football players with sub-concussive impacts, with return to baseline after they abstained from play. Further studies are needed to assess the utility of RD and AD in patients specifically with CTE [50].

    Functional MRI (fMRI) is also known as blood oxygen level-dependent MRI. Neuronal activation in specific brain areas results in an increased oxyhemoglobin-to-deoxyhemoglobin ratio secondary to increased local blood flow, resulting in changes in magnetic susceptibility that are detected by fMRI when a specific task is performed [51]. This method is heavily used in behavioral and physiologic research, as it correlates well with neuronal activity. A theoretical limitation is that the results may be confounded in patients with CTE who already have reduced and altered cerebral blood flow. This modality is yet to be investigated in CTE. A few studies have, however, demonstrated altered brain activation patterns in the fMRI results of living patients with acute and repetitive mTBI [52][62]. The correlation between fMRI and altered brain activation patterns in those with mTBI may overwhelm the theoretical limitation. Furthermore, arterial spin imaging MRI, a type of fMRI, has shown to represent aberrant cerebral blood flow in those with mTBI [63].

    Magnetic resonance spectroscopy measures concentrations of metabolites within the brain based on the chemical shift of their protons, which is determined by the proton's chemical environment. This modality is useful for CTE when considering the pathological changes, including neuroinflammation, in the acute and chronic stages of the disease. In fact, a study investigating male USA National Football League (NFL) players between 40–69 with self-reported neuropsychiatric symptoms were found to have decreased cellular energy metabolism, as evidenced by lower creatinine in the parietal white matter. Neuro-inflammatory metabolites like glutamate, glutathione and myo-inositol also correlated with their behavioral and mood symptoms [64]. Several other studies have demonstrated metabolite abnormalities in patients with a history of repeated head impacts, including decreases in NAA, NAA/Cho and NAA/Cr, as well as increases in Cho, ml, glutamine, choline, fucose and phenylalanine [65][70].

    Susceptibility weighted imaging (SWI) takes advantage of different responses, or susceptibilities, to molecules within a magnetic field. These susceptibilities are measured as phase shifts and superimposed on an MRI, highlighting local susceptibility changes. In the setting of TBI, it can be used to reveal hemorrhagic contusions or diffuse axonal injury. SWI abnormalities, including microhemorrhages, have been demonstrated in contact sport participants, active duty military members and those with concussive-like symptoms and a history of repetitive mTBI [71][74]. Considering that it has shown utility in predicting neuropsychiatric outcomes for those with acute mTBI, its use should be considered in predicting the likelihood of the development of CTE [75],[76]. Neurodegenerative disorders often have characteristic features and positions of cerebral microbleeds [77],[78]. Research investigating the distribution and features of cerebral microbleeds in CTE to make a specific diagnosis would be beneficial.

    Position emission tomography (PET) CT, which employs the use of radioisotopic biomarkers, has been garnering interest for elucidating elevated tau, beta-amyloid, neurofibrillary tangles and other neuroinflammatory proteins [79]. For example, FDDNP binds to the neurofibrillary tangles and proteins that are associated with CTE. As such, it has been employed in the diagnosis of CTE [79],[80]. However, FDDNP has also been shown to bind to beta-amyloid and hyperphosphorylated tau and is therefore limited in specificity when discriminating against other neurological degenerative diseases, such as Alzheimer's disease [79].

    The development of biomarkers specific for the hyperphosphorylated tau proteins associated with CTE, such as [18F]AV-1451 (flortaucipir), are of interest and have been recently studied. [18F]AV-1451 binds to the paired helical tau deposition associated with Alzheimer's disease, and studies are being conducted to investigate its utility for visualizing tau deposition patterns that are associated with CTE, such as those in the medial temporal lobe, brain stem and diencephalon [81]. One such study involved [18F]AV-1451-PET scans from 26 former NFL players aged between 40–69 with reported neuropsychiatric symptoms; the researchers observed a statistically significant increase in the mean standard reuptake of [18F]AV-1451 in the bilateral superior frontal, bilateral medial temporal and left parietal regions as compared to the controls [82]. Another study followed a retired NFL player who underwent an MRI and [18F]AV-1451 PET scan, which revealed uptake in the bilateral medial temporal lobes and parietal regions 4 years before a post-mortem diagnosis of stage-4 CTE [83]. These studies, which are confined to small sample sizes and the single case report, illustrate the need for further investigation to validate [18F]AV-1451 as an optimal radiotracer for in vivo PET scans to diagnose CTE. Other developing PET tracers of interest that bind to tau proteins include [11C]PBB3[84], THK-5105[85], THK-5117[86], THK-5351[87] and T807[88]. [18F]florbetapir and [11C]PiB PET measure amyloid beta plaques [89],[90]. The characteristics of selected biomarkers are reviewed in Table 1. Studies have also investigated the use of [11C]flumazenil and [18F]flumazenil, which bind to the GABAA system in patients with a history of repeated head injury [91]. Lastly, the translocator protein (TSPO) and copper have also been targeted with several radiotracers to assess inflammation [91]. Several studies have also investigated the use of [18F]FDG for patients with a history of mTBI, generally showing decreased brain glucose metabolism in the cerebellum, vermis, pons, temporal lobe, prefrontal cortex and limbic system [91]. Though cortical uptake regions vary, studies have generally consistently demonstrated uptake in the temporal lobes, limbic system, midbrain, hippocampi and amygdalae [2],[79],[91]. The need for further research into PET biomarkers for hyperphosphorylated tau proteins specifically associated with CTE and tasked with reducing off-target binding is warranted.

    Table 1.  PET CT biomarkers.
    Biomarker Specificity
    FDDNP Affinity for intracellular neurofibrillary tangles but has been found to be “non-selective” due to its binding with extracellular β-amyloid and tau, which is a feature of Alzheimer's disease and not necessarily CTE [17],[79],[91]
    [18F]AV-1451 (flortaucipir) Affinity for hyperphosphorylated tau proteins. However, there is a possibility of false negatives, as there is also high binding affinity for paired helical tau filaments in Alzheimer's disease and not CTE [91],[92].
    [11C]PBB3 Affinity for Alzheimer's disease tau pathology but has mixed reviews over its ability to identify paired helical tau filaments in CTE [93],[94]
    THK-5105 High binding affinity to tau protein aggregates and tau-rich Alzheimer disease, but it has reported to have a high background signal in PET images, which could affect its utility. Also, it has not been investigated for tau proteins seen in CTE-related pathology [86],[95].
    THK-5117 Affinity for Alzheimer's disease-related tau protein in the medial temporal lobe in port-mortem patients, but not yet investigated for the CTE-related tau deposits [96].
    THK-5351 Showed affinity with increased t-tau levels in the parahippocampal gyrus, but not investigated for CTE-associated tau patterns to date [97].

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    CTE is characterized by an accumulation of differentiated cis p-tau proteins in the vasculature of sulcal depths with large groups of astrocytic tangles, neurofibrillary tangles and neurites [17]. These abnormal, non-functional p-tau clusters develop within axons [17],[98]. High values of p-tau are also found in single-event TBI and other neurodegenerative diseases, and therefore cannot serve as the sole means of diagnosis of CTE [99],[100]. However, it can serve as a biomarker when considered in the overall clinical setting with accompanying imaging findings from developing diagnostic tools, like PET.

    A promising biomarker that is not as widely employed for tau is the inflammatory marker triggering receptor expressed on myeloid cells 2 (TREM2), a triggering receptor found in several myeloid lineage cells such as peripheral macrophages, dendritic cells and microglial cells in the central nervous system (CNS) [101]. TREM2 is also expressed in the microglia of the brain, regulating microglial activation and playing a multi-faceted role in its immune response [102],[103]. Animal studies have shown that TREM2 is upregulated in the early stages following injury, making it a potential biomarker for TBI and other head injuries [104]. When microglia in the brain are activated, following injury, cleavage of TREM2 by proteases follows. These proteases release soluble TREM2 (sTREM2), indicating that injury has occurred. A study highlighted the relationship between sTREM2 levels in cerebrospinal fluid (CSF) and t-tau concentrations in 68 former NFL players aged 40–69 with self-reported neuropsychiatric symptoms (compared to healthy controls), ultimately finding a positive correlation between the two [102]. The presence of TREM2 variants increases the likelihood of developing Alzheimer's disease by 2–4 times [105],[106]. Therefore, elevated levels of sTREM2 are non-specific. Because upregulation of TREM2 begins early and persists over time [104], it could prove to be a key inflammatory marker used for the diagnosis of CTE in the appropriate clinical context.

    A biomarker with potential for pre-mortem CTE diagnosis is the chemokine C-C motif chemokine ligand 11 (CCL11). Chemokines are proteins that play a central role and facilitate biochemical and cellular events in the immune response. They upregulate leukocytes and act as secondary pro-inflammatory mediators [107],[108]. CCL11 is a chemoattractant of eosinophils in the peripheral immune system and has recently been shown to also penetrate the blood brain barrier [107]. A study showed that the brain of mice secreted CCL11 as a response to the inflammation of astrocytes, pericytes and microglia [109]. A key study showed an increase in the plasma blood levels of CCL11 to correlate with a decrease in learning, memory and neurogenesis in the brains of mice [110]. It has been proposed that the main reason for CCL11's involvement in neurological decline is its ability to increase the microglial production of reactive oxygen species and promote excitotoxic neuronal death [111]. A study indicated that CCL11 is released in the CSF from the choroid plexus in the brain, suggesting direct effects on the brain [112]. This is also associated with an increase in the ratio of cytokine interleukin (IL)-4 and interferon (IFN)-γ in the choroid plexus and CSF. Prior research has shown the physiological importance of CCL11 to neurological function, but it may be a useful biomarker for CTE considering its ability to distinguish it among other neurodegenerative diseases. A collection of studies showed that plasma CCL11 increased in patients with Alzheimer's disease and Huntington's disease, while it decreased in amyotrophic lateral sclerosis and secondary progressive multiple sclerosis [113][115]. Using ELISA, a post-mortem study of 23 former football players with neuropathologically diagnosed CTE and 50 subjects with neuropathologically diagnosed Alzheimer's disease showed a statistically significant increase in the CCL11 levels in the dorsolateral frontal cortex of CTE subjects compared to the Alzheimer's disease and control subjects [116]. Another study with subjects aged 25–33 showed significant increases in CCL11 in the CSF of retired football players relative to swimmers with no TBI history and a sedentary control group. Analysis of the IL-4-to-IFN-γ ratio also showed significant increase in the football players compared to the others in the study. Lastly, CCL11 levels showed a strong positive correlation with the number of years of football played [107]. There is a lot of promise that CCL11 can provide CTE diagnosis for patients pre-mortem. More comprehensive research can be done to analyze the relationship of CCL11 levels with the IL-4-to-IFN-γ ratio found in the CSF of different types of neurodegenerative diseases in pre- and post-mortem brains to build a more accurate predictive model for diagnosis.

    Another biomarker widely employed in TBI is neurofilament-L (NfL). NfL comes from the intermediate filament protein family and is part of the neuronal cytoskeleton [117]. It can serve as an indicator of CNS axonal damage. NfL is released into the CSF [117]. A meta-analysis with a sample size of 1118 patients showed that NfL CSF, serum and plasma levels were significantly higher in patients with TBI compared to the control patients without prior TBI [117]. Another study showed that patients with Alzheimer's disease, Guillain-Barré-syndrome and amyotrophic lateral sclerosis had increased levels of serum NfL compared to a control without CNS damage [118]. These studies suggest that NfL could be used to also conduct future research toward CTE diagnosis.

    Glial fibrillary acidic protein (GFAP) is a cytoskeletal monomeric filament protein located in the astroglial cells of gray and white matter [119]. A study showed that levels of GFAP, tau and NfL were all higher in the group of 277 patients suspected with mTBI, with GFAP yielding high discriminatory power in differentiating these patients from the 49 healthy controls, with an area under the curve (AUC) of 0.93 [120]. In the same study, GFAP similarly served as a strong predictor of mTBI when examining MRI abnormalities, with an AUC of 0.83 [120]. Another study of GFAP's ability to predict CT abnormalities showed an AUC of 0.88 when examining 215 patients (83% with mTBI; mean age 42.5 ± 18.0) [121]. Further analysis could be done using pre-mortem CTE subjects and comparing GFAP levels in those patients to a control to assess whether this translates to specifically diagnosing CTE over other diseases as a result of a TBI. The characteristics of the biomarkers are summarized in Table 2.

    Table 2.  Blood biomarkers for the diagnosis of CTE.
    Biomarker Description Significance Advantages Limitations
    p-tau Hyperphosphorylated tau protein found in the cortical vasculature within the sulcal depths [17]. -Repetitive head injury causes the conversion of typical tau protein to p-tau [2].
    -P-tau is indicative of axonal functional decline and will deposit in predictable patterns and high concentrations following brain injury [17],[122],[123].
    -Consistent and sensitive results considering large concentrations following injury [123].
    -A blood sample is less invasive than lumbar puncture [124].
    Other neurodegenerative diseases also express high concentrations of p-tau [123].
    TREM2 Triggering receptor found in myeloid lineage cells that regulates CNS microglial activation [101]. -Cleavage of TREM2 by proteases following head injury produces sTREM2
    -Increased sTREM2 levels in the CSF are indicative of increased protease activity, likely due to trauma [102].
    Early upregulation of TREM2 following head injury may eventually lead to its diagnostic use in potential CTE cases in vivo [102],[104]. -Invasive sample collection with lumbar puncture [102].
    -TREM2 variants can impair the function of receptors due to poor signaling, ultimately leading to decreased sTREM levels [125].
    CCL11 -Chemokine that serves as a mediator in inflammatory cascades [107],[108].
    -Penetrates the blood brain barrier [107].
    -Secreted into CSF by choroid plexus in the brain [112].
    -Increases microglial production of reactive oxygen species and promotes excitotoxic neuronal death [111].
    -Reflective of neuroinflammatory processes [111].
    -Potential ability to differentiate between CTE and other neurodegenerative diseases [116].
    -Possible correlation with number of repeated head impacts [107].
    -Its main role in the CNS is unclear, as it is a chemoattractant of eosinophils in the peripheral immune system [112].
    NfL Part of the Intermediate filament protein family and of the neuronal cytoskeleton [117]. -Can be measured, as axonal damage induces its release into the CSF [117]. -Released in a delayed fashion and may be correlated with cognitive decline in patients with chronic TBI [126].
    -Specific to CTE [116].
    -Conflicting data regarding its validity in accurately diagnosing CTE [117].
    GFAP Cytoskeletal monomeric filament protein in the brain's astroglial cells [119]. -Reflective of astroglial injury and released acutely following TBI [116]. -Better predictor of mTBI than NfL and p-tau [120]. -Utility in CTE specifically unknown [120],[121].

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    In conclusion, the current clinical diagnosis of CTE relies on clinical symptomatology and structural imaging findings. While there is extensive research on imaging and fluid biomarkers in relation to TBI, there is comparatively limited research on CTE. Particularly, the referenced studies are often small and investigate mTBI, TBI or repetitive head injury and do not study CTE directly. Investigating CTE directly is especially difficult considering the lack of consensus on pre-mortem diagnostic criteria. The studies also frequently include patients based on a history of sport participation alone, self-reported history of TBI or self-reported neuropsychiatric symptoms. The studied biomarkers are also often elevated in other neurodegenerative disorders, and there is relatively limited research on the use of biomarkers to differentiate CTE from other neurodegenerative disorders. Lastly, many of the fluid biomarkers are also elevated following a single TBI event, and there is not an imaging or fluid biomarker approved solely for CTE. We look forward to further research on the early promising imaging modalities and fluid biomarkers to potentially assist in the diagnosis of CTE and in differentiation of it from other neurodegenerative diseases.



    Conflict of interest



    The authors declare no conflict of interest.

    [1] McKee AC, Abdolmohammadi B, Stein TD (2018) The neuropathology of chronic traumatic encephalopathy. Handb Clin Neurol 158: 297-307. https://doi.org/10.1016/B978-0-444-63954-7.00028-8
    [2] Pierre K, Dyson K, Dagra A, et al. (2021) Chronic Traumatic Encephalopathy: Update on Current Clinical Diagnosis and Management. Biomedicines 9: 415. https://doi.org/10.3390/biomedicines9040415
    [3] Castellani RJ, Perry G (2017) Dementia Pugilistica Revisited. J Alzheimers Dis 60: 1209-1221. https://doi.org/10.3233/JAD-170669
    [4] Alosco ML, Mariani ML, Adler CH, et al. (2021) Developing methods to detect and diagnose chronic traumatic encephalopathy during life: rationale, design, and methodology for the DIAGNOSE CTE Research Project. Alzheimers Res Ther 13: 136. https://doi.org/10.1186/s13195-021-00872-x
    [5] Baugh CM, Robbins CA, Stern RA, et al. (2014) Current understanding of chronic traumatic encephalopathy. Curr Treat Options Neurol 16: 306. https://doi.org/10.1007/s11940-014-0306-5
    [6] Gavett BE, Stern RA, McKee AC (2011) Chronic traumatic encephalopathy: a potential late effect of sport-related concussive and subconcussive head trauma. Clin Sports Med 30: 179-88, xi. https://doi.org/10.1016/j.csm.2010.09.007
    [7] Gavett BE, Cantu RC, Shenton M, et al. (2011) Clinical appraisal of chronic traumatic encephalopathy: current perspectives and future directions. Curr Opin Neurol 24: 525-531. https://doi.org/10.1097/WCO.0b013e32834cd477
    [8] Martland HS (1928) PUNCH DRUNK. J Am Med Assoc 91: 1103-1107. https://doi.org/10.1001/jama.1928.02700150029009
    [9] Hay J, Johnson VE, Smith DH, et al. (2016) Chronic Traumatic Encephalopathy: The Neuropathological Legacy of Traumatic Brain Injury. Annu Rev Pathol 11: 21-45. https://doi.org/10.1146/annurev-pathol-012615-044116
    [10] Lampert PW, Hardman JM (1984) Morphological Changes in Brains of Boxers. JAMA 251: 2676-2679. https://doi.org/10.1001/jama.1984.03340440034023
    [11] Saulle M, Greenwald BD (2012) Chronic traumatic encephalopathy: a review. Rehabil Res Pract 2012: 816069. https://doi.org/10.1155/2012/816069
    [12] Omalu B (2014) Chronic traumatic encephalopathy. Prog Neurol Surg 28: 38-49. https://doi.org/10.1159/000358761
    [13] Doherty CP, O'Keefe E, Wallace E, et al. (2016) Blood-Brain Barrier Dysfunction as a Hallmark Pathology in Chronic Traumatic Encephalopathy. J Neuropathol Exp Neurol 75: 656-662. https://doi.org/10.1093/jnen/nlw036
    [14] Johnson VE, Weber MT, Xiao R, et al. (2018) Mechanical disruption of the blood-brain barrier following experimental concussion. Acta Neuropathol 135: 711-726. https://doi.org/10.1007/s00401-018-1824-0
    [15] Ogino Y, Bernas T, Greer JE, et al. (2022) Axonal injury following mild traumatic brain injury is exacerbated by repetitive insult and is linked to the delayed attenuation of NeuN expression without concomitant neuronal death in the mouse. Brain Pathol 32: e13034. https://doi.org/10.1111/bpa.13034
    [16] Toth L, Czigler A, Horvath P, et al. (2021) The Effect of Mild Traumatic Brain Injury on Cerebral Microbleeds in Aging. Front Aging Neurosci 13: 717391. https://doi.org/10.3389/fnagi.2021.717391
    [17] McKee AC, Stein TD, Kiernan PT, et al. (2015) The neuropathology of chronic traumatic encephalopathy. Brain Pathol 25: 350-364. https://doi.org/10.1111/bpa.12248
    [18] McKee AC, Stern RA, Nowinski CJ, et al. (2013) The spectrum of disease in chronic traumatic encephalopathy. Brain 136: 43-64. https://doi.org/10.1093/brain/aws307
    [19] Huber BR, Alosco ML, Stein TD, et al. (2016) Potential Long-Term Consequences of Concussive and Subconcussive Injury. Phys Med Rehabil Clin N Am 27: 503-511. https://doi.org/10.1016/j.pmr.2015.12.007
    [20] McKee AC, Alosco ML, Huber BR (2016) Repetitive Head Impacts and Chronic Traumatic Encephalopathy. Neurosurg Clin N Am 27: 529-535. https://doi.org/10.1016/j.nec.2016.05.009
    [21] VanItallie TB (2019) Traumatic brain injury (TBI) in collision sports: Possible mechanisms of transformation into chronic traumatic encephalopathy (CTE). Metabolism 100s: 153943. https://doi.org/10.1016/j.metabol.2019.07.007
    [22] Reams N, Eckner JT, Almeida AA, et al. (2016) A Clinical Approach to the Diagnosis of Traumatic Encephalopathy Syndrome: A Review. JAMA Neurol 73: 743-749. https://doi.org/10.1001/jamaneurol.2015.5015
    [23] Katz DI, Bernick C, Dodick DW, et al. (2021) National Institute of Neurological Disorders and Stroke Consensus Diagnostic Criteria for Traumatic Encephalopathy Syndrome. Neurology 96: 848-863. https://doi.org/10.1212/WNL.0000000000011850
    [24] Montenigro PH, Baugh CM, Daneshvar DH, et al. (2014) Clinical subtypes of chronic traumatic encephalopathy: literature review and proposed research diagnostic criteria for traumatic encephalopathy syndrome. Alzheimers Res Ther 6: 68. https://doi.org/10.1186/s13195-014-0068-z
    [25] Shively SB, Edgerton SL, Iacono D, et al. (2017) Localized cortical chronic traumatic encephalopathy pathology after single, severe axonal injury in human brain. Acta Neuropathol 133: 353-366. https://doi.org/10.1007/s00401-016-1649-7
    [26] Shetty T, Raince A, Tsiouris AJ, et al. (2015) Imaging in Chronic Traumatic Encephalopathy and Traumatic Brain Injury. Sports Health 8: 26-36. https://doi.org/10.1177/1941738115588745
    [27] Dallmeier JD, Meysami S, Merrill DA, et al. (2019) Emerging advances of in vivo detection of chronic traumatic encephalopathy and traumatic brain injury. Br J Radiol 92: 20180925. https://doi.org/10.1259/bjr.20180925
    [28] Baugh CM, Stamm JM, Riley DO, et al. (2012) Chronic traumatic encephalopathy: neurodegeneration following repetitive concussive and subconcussive brain trauma. Brain Imaging Behav 6: 244-254. https://doi.org/10.1007/s11682-012-9164-5
    [29] Tharmaratnam T, Iskandar MA, Tabobondung TC, et al. (2018) Chronic Traumatic Encephalopathy in Professional American Football Players: Where Are We Now?. Front Neurol 9: 445. https://doi.org/10.3389/fneur.2018.00445
    [30] Gandy S, Ikonomovic MD, Mitsis E, et al. (2014) Chronic traumatic encephalopathy: clinical-biomarker correlations and current concepts in pathogenesis. Mol Neurodegener 9: 37. https://doi.org/10.1186/1750-1326-9-37
    [31] Park H, Yang J-j, Seo J, et al. (2013) Dimensionality reduced cortical features and their use in predicting longitudinal changes in Alzheimer's disease. Neurosci Lett 550: 17-22. https://doi.org/10.1016/j.neulet.2013.06.042
    [32] Seo SW, Ahn J, Yoon U, et al. (2010) Cortical thinning in vascular mild cognitive impairment and vascular dementia of subcortical type. J Neuroimaging 20: 37-45. https://doi.org/10.1111/j.1552-6569.2008.00293.x
    [33] Jubault T, Gagnon J-F, Karama S, et al. (2011) Patterns of cortical thickness and surface area in early Parkinson's disease. Neuroimage 55: 462-467. https://doi.org/10.1016/j.neuroimage.2010.12.043
    [34] Singh V, Chertkow H, Lerch JP, et al. (2006) Spatial patterns of cortical thinning in mild cognitive impairment and Alzheimer's disease. Brain 129: 2885-2893. https://doi.org/10.1093/brain/awl256
    [35] Meier TB, España LY, Kirk AJ, et al. (2021) Association of Previous Concussion with Hippocampal Volume and Symptoms in Collegiate-Aged Athletes. J Neurotrauma 38: 1358-1367. https://doi.org/10.1089/neu.2020.7143
    [36] Schuff N, Woerner N, Boreta L, et al. (2009) MRI of hippocampal volume loss in early Alzheimer's disease in relation to ApoE genotype and biomarkers. Brain 132: 1067-1077. https://doi.org/10.1093/brain/awp007
    [37] Winklewski PJ, Sabisz A, Naumczyk P, et al. (2018) Understanding the Physiopathology Behind Axial and Radial Diffusivity Changes-What Do We Know?. Front Neurol 9: 92. https://doi.org/10.3389/fneur.2018.00092
    [38] Holleran L, Kim JH, Gangolli M, et al. (2017) Axonal disruption in white matter underlying cortical sulcus tau pathology in chronic traumatic encephalopathy. Acta Neuropathol 133: 367-380. https://doi.org/10.1007/s00401-017-1686-x
    [39] Veeramuthu V, Narayanan V, Kuo TL, et al. (2015) Diffusion Tensor Imaging Parameters in Mild Traumatic Brain Injury and Its Correlation with Early Neuropsychological Impairment: A Longitudinal Study. J Neurotrauma 32: 1497-1509. https://doi.org/10.1089/neu.2014.3750
    [40] Bouix S, Pasternak O, Rathi Y, et al. (2013) Increased gray matter diffusion anisotropy in patients with persistent post-concussive symptoms following mild traumatic brain injury. PLoS One 8: e66205. https://doi.org/10.1371/journal.pone.0066205
    [41] Wada T, Asano Y, Shinoda J (2012) Decreased fractional anisotropy evaluated using tract-based spatial statistics and correlated with cognitive dysfunction in patients with mild traumatic brain injury in the chronic stage. AJNR Am J Neuroradiol 33: 2117-2122. https://doi.org/10.3174/ajnr.A3141
    [42] Asano Y, SHINODA J, OKUMURA A, et al. (2012) Utility of fractional anisotropy imaging analyzed by statistical parametric mapping for detecting minute brain lesions in chronic-stage patients who had mild or moderate traumatic brain injury. Neurol Med Chir (Tokyo) 52: 31-40. https://doi.org/10.2176/nmc.52.31
    [43] Yin B, Li D-D, Huang H, et al. (2019) Longitudinal Changes in Diffusion Tensor Imaging Following Mild Traumatic Brain Injury and Correlation With Outcome. Front Neural Circuits 13: 28. https://doi.org/10.3389/fncir.2019.00028
    [44] Mahan MY, Rafter DJ, Truwit CL, et al. (2021) Evaluation of diffusion measurements reveals radial diffusivity indicative of microstructural damage following acute, mild traumatic brain injury. Magn Reson Imaging 77: 137-147. https://doi.org/10.1016/j.mri.2020.12.012
    [45] Yeh P-H, Lippa SM, Brickell TA, et al. (2022) Longitudinal changes of white matter microstructure following traumatic brain injury in U.S. military service members. Brain Communications 4: fcac132. https://doi.org/10.1093/braincomms/fcac132
    [46] Mayer AR, Ling J, Mannell MV, et al. (2010) A prospective diffusion tensor imaging study in mild traumatic brain injury. Neurology 74: 643-650. https://doi.org/10.1212/WNL.0b013e3181d0ccdd
    [47] Palacios EM, Yuh EL, Mac Donald CL, et al. (2022) Diffusion Tensor Imaging Reveals Elevated Diffusivity of White Matter Microstructure that Is Independently Associated with Long-Term Outcome after Mild Traumatic Brain Injury: A TRACK-TBI Study. J Neurotrauma 39: 1318-1328. https://doi.org/10.1089/neu.2021.0408
    [48] Herweh C, Hess K, Meyding-Lamadé U, et al. (2016) Reduced white matter integrity in amateur boxers. Neuroradiology 58: 911-920. https://doi.org/10.1007/s00234-016-1705-y
    [49] Kraus MF, Susmaras T, Caughlin BP, et al. (2007) White matter integrity and cognition in chronic traumatic brain injury: a diffusion tensor imaging study. Brain 130: 2508-2519. https://doi.org/10.1093/brain/awm216
    [50] Mayinger MC, Merchant-Borna K, Hufschmidt J, et al. (2018) White matter alterations in college football players: a longitudinal diffusion tensor imaging study. Brain Imaging Behav 12: 44-53. https://doi.org/10.1007/s11682-017-9672-4
    [51] Basser PJ, Mattiello J, LeBihan D (1994) MR diffusion tensor spectroscopy and imaging. Biophys J 66: 259-267. https://doi.org/10.1016/S0006-3495(94)80775-1
    [52] Terry DP, Adams TE, Ferrara MS, et al. (2015) FMRI hypoactivation during verbal learning and memory in former high school football players with multiple concussions. Arch Clin Neuropsychol 30: 341-355. https://doi.org/10.1093/arclin/acv020
    [53] Scheibel RS, Newsome MR, Troyanskaya M, et al. (2012) Altered brain activation in military personnel with one or more traumatic brain injuries following blast. J Int Neuropsychol Soc 18: 89-100. https://doi.org/10.1017/S1355617711001433
    [54] Talavage TM, Nauman EA, Breedlove EL, et al. (2014) Functionally-detected cognitive impairment in high school football players without clinically-diagnosed concussion. J Neurotrauma 31: 327-338. https://doi.org/10.1089/neu.2010.1512
    [55] Ford JH, Giovanello KS, Guskiewicz KM (2013) Episodic memory in former professional football players with a history of concussion: an event-related functional neuroimaging study. J Neurotrauma 30: 1683-1701. https://doi.org/10.1089/neu.2012.2535
    [56] Keightley ML, Saluja RS, Chen J-K, et al. (2014) A functional magnetic resonance imaging study of working memory in youth after sports-related concussion: is it still working?. J Neurotrauma 31: 437-451. https://doi.org/10.1089/neu.2013.3052
    [57] Monti JM, Voss MW, Pence A, et al. (2013) History of mild traumatic brain injury is associated with deficits in relational memory, reduced hippocampal volume, and less neural activity later in life. Front Aging Neurosci 5: 41. https://doi.org/10.3389/fnagi.2013.00041
    [58] Clark MD, Varangis EML, Champagne AA, et al. (2018) Effects of Career Duration, Concussion History, and Playing Position on White Matter Microstructure and Functional Neural Recruitment in Former College and Professional Football Athletes. Radiology 286: 967-977. https://doi.org/10.1148/radiol.2017170539
    [59] Hampshire A, MacDonald A, Owen AM (2013) Hypoconnectivity and hyperfrontality in retired American football players. Sci Rep 3: 2972. https://doi.org/10.1038/srep02972
    [60] Goswami R, Dufort P, Tartaglia MC, et al. (2016) Frontotemporal correlates of impulsivity and machine learning in retired professional athletes with a history of multiple concussions. Brain Struct Funct 221: 1911-1925. https://doi.org/10.1007/s00429-015-1012-0
    [61] Rajesh A, Cooke GE, Monti JM, et al. (2017) Differences in Brain Architecture in Remote Mild Traumatic Brain Injury. J Neurotrauma 34: 3280-3287. https://doi.org/10.1089/neu.2017.5047
    [62] Rowland JA, Stapleton-Kotloski JR, Dobbins DL, et al. (2018) Increased Small-World Network Topology Following Deployment-Acquired Traumatic Brain Injury Associated with the Development of Post-Traumatic Stress Disorder. Brain Connect 8: 205-211. https://doi.org/10.1089/brain.2017.0556
    [63] Wang Y, Bartels HM, Nelson LD (2020) A Systematic Review of ASL Perfusion MRI in Mild TBI. Neuropsychol Rev . https://doi.org/10.1007/s11065-020-09451-7
    [64] Alosco ML, Tripodis Y, Rowland B, et al. (2020) A magnetic resonance spectroscopy investigation in symptomatic former NFL players. Brain Imaging Behav 14: 1419-1429. https://doi.org/10.1007/s11682-019-00060-4
    [65] Davie CA, Pirtosek Z, Barker GJ, et al. (1995) Magnetic resonance spectroscopic study of parkinsonism related to boxing. J Neurol Neurosurg Psychiatry 58: 688-691. https://doi.org/10.1136/jnnp.58.6.688
    [66] Hetherington HP, Hamid H, Kulas J, et al. (2014) MRSI of the medial temporal lobe at 7 T in explosive blast mild traumatic brain injury. Magn Reson Med 71: 1358-1367. https://doi.org/10.1002/mrm.24814
    [67] Koerte IK, Lin AP, Muehlmann M, et al. (2015) Altered Neurochemistry in Former Professional Soccer Players without a History of Concussion. J Neurotrauma 32: 1287-1293. https://doi.org/10.1089/neu.2014.3715
    [68] Lin AP, Ramadan S, Stern RA, et al. (2015) Changes in the neurochemistry of athletes with repetitive brain trauma: preliminary results using localized correlated spectroscopy. Alzheimer's Research Therapy 7: 13. https://doi.org/10.1186/s13195-015-0094-5
    [69] Tremblay S, De Beaumont L, Henry LC, et al. (2013) Sports concussions and aging: a neuroimaging investigation. Cereb Cortex 23: 1159-1166. https://doi.org/10.1093/cercor/bhs102
    [70] Lin AP, Ramadan S, Stern RA, et al. (2015) Changes in the neurochemistry of athletes with repetitive brain trauma: preliminary results using localized correlated spectroscopy. Alzheimers Res Ther 7: 13. https://doi.org/10.1186/s13195-015-0094-5
    [71] Helmer KG, Pasternak O, Fredman E, et al. (2014) Hockey Concussion Education Project, Part 1. Susceptibility-weighted imaging study in male and female ice hockey players over a single season. J Neurosurg 120: 864-872. https://doi.org/10.3171/2013.12.JNS132093
    [72] Hasiloglu ZI, Albayram S, Selcuk H, et al. (2011) Cerebral microhemorrhages detected by susceptibility-weighted imaging in amateur boxers. AJNR Am J Neuroradiol 32: 99-102. https://doi.org/10.3174/ajnr.A2250
    [73] Viola-Saltzman M, Musleh C (2016) Traumatic brain injury-induced sleep disorders. Neuropsychiatr Dis Treat 12: 339-348. https://doi.org/10.2147/NDT.S69105
    [74] Eldeş T, Çeliker FB, Bilir Ö, et al. (2020) How important is susceptibility-weighted imaging in mild traumatic brain injury?. Ulus Travma Acil Cerrahi Derg 26: 574-579. https://doi.org/10.14744/tjtes.2019.35485
    [75] Huang Y-L, Kuo Y-S, Tseng Y-C, et al. (2015) Susceptibility-weighted MRI in mild traumatic brain injury. Neurology 84: 580. https://doi.org/10.1212/WNL.0000000000001237
    [76] Tate DF, Gusman M, Kini J, et al. (2017) Susceptibility Weighted Imaging and White Matter Abnormality Findings in Service Members With Persistent Cognitive Symptoms Following Mild Traumatic Brain Injury. Mil Med 182: e1651-e1658. https://doi.org/10.7205/MILMED-D-16-00132
    [77] Ayaz M, Boikov AS, Haacke EM, et al. (2010) Imaging cerebral microbleeds using susceptibility weighted imaging: one step toward detecting vascular dementia. J Magn Reson Imaging 31: 142-148. https://doi.org/10.1002/jmri.22001
    [78] Sparacia G, Agnello F, Sparacia B, et al. (2017) Assessment of cerebral microbleeds by susceptibility-weighted imaging in Alzheimer's disease patients: A neuroimaging biomarker of the disease. Neuroradiol J 30: 330-335. https://doi.org/10.1177/1971400916689483
    [79] Lee BG, Leavitt MJ, Bernick CB, et al. (2018) A Systematic Review of Positron Emission Tomography of Tau, Amyloid Beta, and Neuroinflammation in Chronic Traumatic Encephalopathy: The Evidence To Date. J Neurotrauma 35: 2015-2024. https://doi.org/10.1089/neu.2017.5558
    [80] Chen ST, Siddarth P, Merrill DA, et al. (2018) FDDNP-PET Tau Brain Protein Binding Patterns in Military Personnel with Suspected Chronic Traumatic Encephalopathy1. J Alzheimers Dis 65: 79-88. https://doi.org/10.3233/JAD-171152
    [81] Turk KW, Geada A, Alvarez VE, et al. (2022) A comparison between tau and amyloid-β cerebrospinal fluid biomarkers in chronic traumatic encephalopathy and Alzheimer disease. Alzheimers Res Ther 14: 28. https://doi.org/10.1186/s13195-022-00976-y
    [82] Stern RA, Adler CH, Chen K, et al. (2019) Tau Positron-Emission Tomography in Former National Football League Players. N Engl J Med 380: 1716-1725. https://doi.org/10.1056/NEJMoa1900757
    [83] Mantyh WG, Spina S, Lee A, et al. (2020) Tau Positron Emission Tomographic Findings in a Former US Football Player With Pathologically Confirmed Chronic Traumatic Encephalopathy. JAMA Neurol 77: 517-521. https://doi.org/10.1001/jamaneurol.2019.4509
    [84] Kimura Y, Ichise M, Ito H, et al. (2015) PET Quantification of Tau Pathology in Human Brain with 11C-PBB3. J Nucl Med 56: 1359-1365. https://doi.org/10.2967/jnumed.115.160127
    [85] Okamura N, Furumoto S, Fodero-Tavoletti MT, et al. (2014) Non-invasive assessment of Alzheimer's disease neurofibrillary pathology using 18F-THK5105 PET. Brain 137: 1762-1771. https://doi.org/10.1093/brain/awu064
    [86] Harada R, Okamura N, Furumoto S, et al. (2015) [(18)F]THK-5117 PET for assessing neurofibrillary pathology in Alzheimer's disease. Eur J Nucl Med Mol Imaging 42: 1052-1061. https://doi.org/10.1007/s00259-015-3035-4
    [87] Harada R, Okamura N, Furumoto S, et al. (2016) 18F-THK5351: A Novel PET Radiotracer for Imaging Neurofibrillary Pathology in Alzheimer Disease. J Nucl Med 57: 208-214. https://doi.org/10.2967/jnumed.115.164848
    [88] Dickstein DL, Pullman MY, Fernandez C, et al. (2016) Cerebral [(18) F]T807/AV1451 retention pattern in clinically probable CTE resembles pathognomonic distribution of CTE tauopathy. Transl Psychiatry 6: e900. https://doi.org/10.1038/tp.2016.175
    [89] Clark CM, Schneider JA, Bedell BJ, et al. (2011) Use of florbetapir-PET for imaging beta-amyloid pathology. Jama 305: 275-283. https://doi.org/10.1001/jama.2010.2008
    [90] Rabinovici GD, Furst AJ, O'Neil JP, et al. (2007) 11C-PIB PET imaging in Alzheimer disease and frontotemporal lobar degeneration. Neurology 68: 1205-1212. https://doi.org/10.1212/01.wnl.0000259035.98480.ed
    [91] Huang CX, Li Y-H, Lu W, et al. (2022) Positron emission tomography imaging for the assessment of mild traumatic brain injury and chronic traumatic encephalopathy: recent advances in radiotracers. Neural Regen Res 17: 74-81. https://doi.org/10.4103/1673-5374.314285
    [92] Passamonti L, Rodríguez PV, Hong YT, et al. (2017) 18F-AV-1451 positron emission tomography in Alzheimer's disease and progressive supranuclear palsy. Brain 140: 781-791. https://doi.org/10.1093/brain/aww340
    [93] Kimura Y, Endo H, Ichise M, et al. (2016) A new method to quantify tau pathologies with (11)C-PBB3 PET using reference tissue voxels extracted from brain cortical gray matter. EJNMMI Res 6: 24. https://doi.org/10.1186/s13550-016-0182-y
    [94] Ono M, Sahara N, Kumata K, et al. (2017) Distinct binding of PET ligands PBB3 and AV-1451 to tau fibril strains in neurodegenerative tauopathies. Brain 140: 764-780. https://doi.org/10.1093/brain/aww339
    [95] Tago T, Furumoto S, Okamura N, et al. (2016) Preclinical Evaluation of [(18)F]THK-5105 Enantiomers: Effects of Chirality on Its Effectiveness as a Tau Imaging Radiotracer. Mol Imaging Biol 18: 258-266. https://doi.org/10.1007/s11307-015-0879-8
    [96] Lemoine L, Gillberg P-G, Svedberg M, et al. (2017) Comparative binding properties of the tau PET tracers THK5117, THK5351, PBB3, and T807 in postmortem Alzheimer brains. Alzheimers Res Ther 9: 96. https://doi.org/10.1186/s13195-017-0325-z
    [97] Leuzy A, Chiotis K, Lemoine L, et al. (2019) Tau PET imaging in neurodegenerative tauopathies-still a challenge. Mol Psychiatry 24: 1112-1134. https://doi.org/10.1038/s41380-018-0342-8
    [98] Lucke-Wold BP, Turner RC, Logsdon AF, et al. (2014) Linking traumatic brain injury to chronic traumatic encephalopathy: identification of potential mechanisms leading to neurofibrillary tangle development. J Neurotrauma 31: 1129-1138. https://doi.org/10.1089/neu.2013.3303
    [99] Chen L (2018) What triggers tauopathy in chronic traumatic encephalopathy?. Neural Regen Res 13: 985-986. https://doi.org/10.4103/1673-5374.233439
    [100] Moszczynski AJ, Strong W, Xu K, et al. (2018) Pathologic Thr(175) tau phosphorylation in CTE and CTE with ALS. Neurology 90: e380-e387. https://doi.org/10.1212/WNL.0000000000004899
    [101] Shao F, Wang X, Wu H, et al. (2022) Microglia and Neuroinflammation: Crucial Pathological Mechanisms in Traumatic Brain Injury-Induced Neurodegeneration. Front Aging Neurosci 14: 825086. https://doi.org/10.3389/fnagi.2022.825086
    [102] Alosco ML, Tripodis Y, Fritts NG, et al. (2018) Cerebrospinal fluid tau, Aβ, and sTREM2 in Former National Football League Players: Modeling the relationship between repetitive head impacts, microglial activation, and neurodegeneration. Alzheimers Dement 14: 1159-1170. https://doi.org/10.1016/j.jalz.2018.05.004
    [103] Verboon LN, Patel HC, Greenhalgh AD (2021) The Immune System's Role in the Consequences of Mild Traumatic Brain Injury (Concussion). Front Immunol 12: 620698. https://doi.org/10.3389/fimmu.2021.620698
    [104] Snyder HM, Carare RO, DeKosky ST, et al. (2018) Military-related risk factors for dementia. Alzheimers Dement 14: 1651-1662. https://doi.org/10.1016/j.jalz.2018.08.011
    [105] Zhou Y, Song WM, Andhey PS, et al. (2020) Human and mouse single-nucleus transcriptomics reveal TREM2-dependent and TREM2-independent cellular responses in Alzheimer's disease. Nat Med 26: 131-142. https://doi.org/10.1038/s41591-019-0695-9
    [106] Silva MC, Haggarty SJ (2020) Tauopathies: Deciphering Disease Mechanisms to Develop Effective Therapies. Int J Mol Sci 21. https://doi.org/10.3390/ijms21238948
    [107] Weissenfels R (2018) CCL11 as a Biomarker for the In Vivo Diagnosis of Chronic Traumatic Encephalopathy.Claremont McKenna College.
    [108] Hughes CE, Nibbs RJB (2018) A guide to chemokines and their receptors. Febs J 285: 2944-2971. https://doi.org/10.1111/febs.14466
    [109] Kovac A, Erickson MA, Banks WA (2011) Brain microvascular pericytes are immunoactive in culture: cytokine, chemokine, nitric oxide, and LRP-1 expression in response to lipopolysaccharide. J Neuroinflamm 8: 139. https://doi.org/10.1186/1742-2094-8-139
    [110] Villeda SA, Luo J, Mosher KI, et al. (2011) The ageing systemic milieu negatively regulates neurogenesis and cognitive function. Nature 477: 90-94. https://doi.org/10.1038/nature10357
    [111] Parajuli B, Horiuchi H, Mizuno T, et al. (2015) CCL11 enhances excitotoxic neuronal death by producing reactive oxygen species in microglia. Glia 63: 2274-2284. https://doi.org/10.1002/glia.22892
    [112] Baruch K, Ron-Harel N, Gal H, et al. (2013) CNS-specific immunity at the choroid plexus shifts toward destructive Th2 inflammation in brain aging. Proc Natl Acad Sci U S A 110: 2264-2269. https://doi.org/10.1073/pnas.1211270110
    [113] Huber AK, Wang L, Han P, et al. (2014) Dysregulation of the IL-23/IL-17 axis and myeloid factors in secondary progressive MS. Neurology 83: 1500-1507. https://doi.org/10.1212/WNL.0000000000000908
    [114] Wild E, Magnusson A, Swales NL, et al. (2011) Abnormal peripheral chemokine profile in Huntington's disease. PLoS Curr 3: Rrn1231. https://doi.org/10.1371/currents.RRN1231
    [115] Leung R, Proitsi P, Simmons A, et al. (2013) Inflammatory proteins in plasma are associated with severity of Alzheimer's disease. PLoS One 8: e64971. https://doi.org/10.1371/journal.pone.0064971
    [116] Cherry JD, Stein TD, Tripodis Y, et al. (2017) CCL11 is increased in the CNS in chronic traumatic encephalopathy but not in Alzheimer's disease. PLoS One 12: e0185541. https://doi.org/10.1371/journal.pone.0185541
    [117] Gao W, Zhang Z, Lv X, et al. (2020) Neurofilament light chain level in traumatic brain injury: A system review and meta-analysis. Medicine (Baltimore) 99: e22363. https://doi.org/10.1097/MD.0000000000022363
    [118] Gaiottino J, Norgren N, Dobson R, et al. (2013) Increased neurofilament light chain blood levels in neurodegenerative neurological diseases. PLoS One 8: e75091. https://doi.org/10.1371/journal.pone.0075091
    [119] Janigro D, Mondello S, Posti JP, et al. (2022) GFAP and S100B: What You Always Wanted to Know and Never Dared to Ask. Front Neurol 13: 835597. https://doi.org/10.3389/fneur.2022.835597
    [120] Gill J, Latour L, Diaz-Arrastia R, et al. (2018) Glial fibrillary acidic protein elevations relate to neuroimaging abnormalities after mild TBI. Neurology 91: e1385-e1389. https://doi.org/10.1212/WNL.0000000000006321
    [121] Okonkwo DO, Yue JK, Puccio AM, et al. (2013) GFAP-BDP as an acute diagnostic marker in traumatic brain injury: results from the prospective transforming research and clinical knowledge in traumatic brain injury study. J Neurotrauma 30: 1490-1497. https://doi.org/10.1089/neu.2013.2883
    [122] Castellani RJ (2015) Chronic traumatic encephalopathy: A paradigm in search of evidence?. Lab Invest 95: 576-584. https://doi.org/10.1038/labinvest.2015.54
    [123] Katsumoto A, Takeuchi H, Tanaka F (2019) Tau Pathology in Chronic Traumatic Encephalopathy and Alzheimer's Disease: Similarities and Differences. Front Neurol 10: 980. https://doi.org/10.3389/fneur.2019.00980
    [124] Stern RA, Tripodis Y, Baugh CM, et al. (2016) Preliminary Study of Plasma Exosomal Tau as a Potential Biomarker for Chronic Traumatic Encephalopathy. J Alzheimers Dis 51: 1099-1109. https://doi.org/10.3233/JAD-151028
    [125] Jay TR, von Saucken VE, Landreth GE (2017) TREM2 in Neurodegenerative Diseases. Mol Neurodegener 12: 56. https://doi.org/10.1186/s13024-017-0197-5
    [126] Wang KK, Yang Z, Zhu T, et al. (2018) An update on diagnostic and prognostic biomarkers for traumatic brain injury. Expert Rev Mol Diagn 18: 165-180. https://doi.org/10.1080/14737159.2018.1428089
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    9. Michal J. Halicki, Karen Hind, Paul L. Chazot, Blood-Based Biomarkers in the Diagnosis of Chronic Traumatic Encephalopathy: Research to Date and Future Directions, 2023, 24, 1422-0067, 12556, 10.3390/ijms241612556
    10. Lan-Wan Wang, Kuan-Hung Cho, Pi-Yu Chao, Li-Wei Kuo, Chia-Wen Chiang, Chien-Ming Chao, Mao-Tsun Lin, Ching-Ping Chang, Hung-Jung Lin, Chung-Ching Chio, White and gray matter integrity evaluated by MRI-DTI can serve as noninvasive and reliable indicators of structural and functional alterations in chronic neurotrauma, 2024, 14, 2045-2322, 10.1038/s41598-024-57706-7
    11. Natalia Surzenko, Johana Bastidas, Robert W. Reid, Julien Curaba, Wei Zhang, Hamed Bostan, Mickey Wilson, Ashley Dominique, Julia Roberson, Glicerio Ignacio, Slavko Komarnytsky, Alexa Sanders, Kevin Lambirth, Cory R. Brouwer, Bassem F. El‐Khodor, Functional recovery following traumatic brain injury in rats is enhanced by oral supplementation with bovine thymus extract, 2024, 38, 0892-6638, 10.1096/fj.202301859R
    12. 2024, 9783437224874, 10, 10.1016/B978-3-437-22487-4.16001-0
    13. Sikandar Khan, Lora Talley, Beyond the Hit: The Hidden Costs of Repetitive Head Trauma, 2025, 20, 2633-1055, 10.1177/26331055251316315
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