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# Current Understanding of Biomarkers in Post Traumatic Stress Disorder and Mild Traumatic Brain Injury: A Systematic Review and Implications for Research and Treatment

Written By

Jamie L. Scholl, Eric T. Graack, Michaela S. Ahrenholtz, Taylor J. Bosch and Lee A. Baugh

Submitted: December 4th, 2021 Reviewed: January 19th, 2022 Published: February 25th, 2022

DOI: 10.5772/intechopen.102766

From the Edited Volume

## Stress Related Disorders [Working Title]

Prof. Emilio Ovuga

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## Abstract

For nearly 100 years, it was erroneously believed that the loss of consciousness and/or the altered mental status associated with a mild traumatic brain injury (mTBI) offered protection from the development of posttraumatic stress disorder (PTSD). However, it is now accepted that it is possible for PTSD to result from mTBI, and that the co-occurrence of these two conditions creates a more difficult condition to treat and worsens prognosis. In addition, it is known that the symptomology associated with PTSD and mTBI have a great deal of overlap, complicating diagnoses. The objective of this chapter is to review the current state of biomarkers aimed at diagnosing comorbid mTBI and PTSD that are useful on a single-patient basis and are not reliant on self-report or arduous interviews. Further, implications for future research and treatment are discussed.

### Keywords

• posttraumatic stress disorder
• mild traumatic brain injury
• biomarker
• treatment

## 1. Introduction

Highlighted by recent world-conflicts, such as the wars in Afghanistan and Iraq, it has become evident that a better and more comprehensive understanding of the relationship between stress-related psychological disorders and traumatic brain injury is much-needed, in both military and civilian populations. For the purposes of this chapter, we will focus on posttraumatic stress disorder (PTSD) and mild traumatic brain injury (mTBI); however, this is not to underplay the crucial need to better understand the wide range of stress-related psychological conditions and brain injury. The prevalence rates of PTSD and mTBI in American military personnel returning from Operation Enduring Freedom (OEF) and Operation Iraqi Freedom (OIF) has been reportedly as high as approximately 14 and 20%, respectively [1]. Despite both PTSD and mTBI conditions being “invisible injuries” (injuries not outwardly observable), they are both capable of creating significant disruptions in normal living for individuals. Further, what little we know about the co-occurrence of these conditions suggests that, when combined, they are more difficult to treat and often result in poorer prognoses [2, 3, 4]. This understanding is a significant advancement, as it was once thought that the loss of consciousness or altered mental status that is often observed with brain injury offered protection from the development of stress disorders [5]. Although it is recent military engagements that have highlighted the need for a better understanding of concomitant PTSD and mTBI, these conditions are prevalent in both military and civilian contexts and are therefore issues of broad public health on a global scale.

Approximately 3.5–7.0% of adults within the United States develop PTSD every year. When examining military personnel, this number increases to anywhere between 33 and 65% [6]. On the global scale, approximately 25% of the world’s population has been affected by PTSD, making it the most prevalent psychiatric disorder [7]. Traumatic brain injuries are also very commonplace, and well over one-million people within the U.S. seek care annually for brain injury [8], with the majority of these being classified as mild [9, 10]. Worldwide, up to 50-million people annually seek treatment [6]. However, this number is likely an underestimation as many individuals who suffer an mTBI do not seek medical care. Furthermore, those that do seek medical attention oftentimes are misdiagnosed or underdiagnosed, especially if symptoms are mild or transient and loss of consciousness is limited to a short period of time [11]. When examining PTSD comorbid with mTBI, it becomes clear that many of those that have been affected by trauma have also experienced mTBI. Within civilian populations, PTSD following accidents such as falls or automotive collisions in which an mTBI occurs, range from approximately 20–36% [12]. Within a military context, this number increases to roughly 34–44% [13, 14]. However, like the reporting of each condition in isolation, the potential for misdiagnosis or underdiagnosis is large.

The prevalence and impact of both mTBI and PTSD (whether it be together or in isolation) result in a high cost of treatment, increased suicide rates, and lost work, all of which place a substantial burden on healthcare systems. Although the true costs are difficult to quantify, estimates for the health services cost associated with an mTBI alone range from $10,000USD to$100,000+ per patient depending on severity, length of hospital stay, and costs of rehabilitation [15, 16, 17, 18, 19], with a mean cost of \$96,000USD [20]. The numbers are equally startling for the treatment costs associated with PTSD, with annual costs in excess of 200 million USD in US military personnel alone [21], and civilian costs estimated at even greater levels [22, 23, 24]. This estimate does not include the loss of productivity associated with this condition, which easily exceeds billions of dollars at a national level [25]. Although both PTSD and mTBI have substantial costs of care in isolation, when combined, healthcare costs are certainly increased, largely due to the complexity of treating comorbid conditions.

Posttraumatic stress disorder and mild traumatic brain injury have overlapping symptomology yet require different therapeutic approaches. In classical diagnoses, detailed information is collected about the onset and progression of symptoms to arrive at a probable diagnosis, which is then further refined. When dealing with an individual that may meet diagnostic criteria for both conditions, this process becomes much more difficult. In theory, a pattern of symptom overlap and divergence could help differentiate etiologies when dealing with comorbid PTSD and mTBI, however, recent evidence suggests this is not the case. In a 2009 study, eight symptoms that are related to both PTSD and mTBI (fatigue, irritability, concentration problems, memory problems, depression, anxiety, insomnia, and dizziness) were examined and compared between patients who had experienced a recent mTBI or PTSD, revealing substantial overlap between both clinical groups. Although it was found that patients with PTSD had greater overall symptom severity, the degree of overlap prevented differential diagnoses based on the pattern of symptoms reported [26]. A meta-analysis conducted the same year [27] provided some evidence that there are symptoms unique to each when occurring in isolation (PTSD—shame, guilt, re-experiencing symptoms; mTBI—headache, sensitivity to light, dizziness, memory deficits), however, this information does not assist in the diagnosis of those that experience both mTBI and PTSD. Therefore, it remains unclear which aspects of these disorders play significant roles in disease onset following event exposure (whether it be set individual traits, epigenetic changes, alterations to specific brain area structure and function, or a combination of these and other factors), and ultimately which set of symptoms will manifest that are linked to the genuine presence of PTSD, mTBI, or both.

The objective of this chapter is to review our current understanding of comorbid mTBI and PTSD, with an emphasis on reviewing the current state of biomarkers used to diagnose comorbid mTBI and PTSD that offer promise on a single-patient basis. To best accomplish these goals, we will begin with providing definitions of what is meant by the terms PTSD and mTBI. Following, we will review the current understanding of the neurological underpinnings of each condition, with a focus on areas of overlap, and examine currently accepted methods of diagnosis and treatment options. Lastly, we will provide an account of the current researchers utilizing biomarkers for either diagnosis or prognosis of PTSD and mTBI, as well as discuss implications for future research and treatment.

## 2. Definitions

The lack of consistent definitions and assessments of mTBI and PTSD complicates the ability to capture accurate statistics for each condition. We focus on mild traumatic brain injury, as this is both the most common traumatic brain injury in civilian [28] and military populations [29], and is also the most likely to co-occur with PTSD [30]. Additionally, as mTBI is often the hardest to diagnose, the pursuit of biomarkers with clinical utility is of great importance. However, when it comes to describing what constitutes an mTBI, a large amount of ambiguity becomes apparent. What is clear is that for a diagnosis of mTBI, two things need to occur: (1) An external force must be exerted to the head; and (2) there must be a temporary change of mental status and/or other evidence of brain injury. Of course, for a traumatic brain injury to be classified as mild, there also needs to be an upper limit for the severity. This includes: (1) a loss of consciousness that does not exceed 30 minutes; and (2) posttraumatic amnesia that does not exceed 24 hrs. These criteria are largely accepted on a global scale [31, 32, 33] and will be used for this chapter as well.

Formal methods for the diagnosis of PTSD currently exist, making the definitions regarding the psychiatric condition somewhat consistent. In general, PTSD is characterized by four symptom clusters that develop in response to a traumatic event. The traumatic event must involve exposure to actual or perceived death, serious injury, or sexual violation. Furthermore, the event must be directly experienced or witnessed by the individual, or indirectly experienced by subsequently learning about the event after it happened to a close family member or friend. Specific clinical criteria include: (1) intrusive symptoms related to re-experiencing the trauma; (2) avoidance of the traumatic memory or cues; (3) negative mood and thoughts including emotional numbing and anhedonia; and (4) altered arousal including hypervigilance, irritability, aggression, and sleep disturbances [7, 34]. Additionally, symptoms result in significant social, personal, and vocational impairment [7]. PTSD is commonly comorbid with other anxiety or mood disorders, further complicating diagnosis, and is also associated with increased risk for numerous negative behavioral and health conditions, including substance use disorder, type II diabetes, and Alzheimer’s disease [35, 36, 37, 38], significantly expanding the costs of treatment. Although the criteria for diagnosing PTSD are rather straightforward, this does not mean that PTSD is a static phenomenon without gradation. It is known that PTSD symptoms appear on a continuum and can fluctuate in terms of their functional impact and presence across time. Furthermore, although the precipitating traumatic event is a critical component of PTSD, it is how an individual responds to that trauma that is essential in the diagnosis. An identical traumatic event for one individual may result in PTSD, whereas another person experiencing an identical event may not. Therefore, it is as much about the symptoms and functional impairment as it is about the event itself.

## 3. Neurobiological underpinnings

Research has shown that both mTBI and PTSD are correlated with both structural and functional changes in the brain, as evidenced by advanced neuroimaging. As can be seen in Figure 1, there are many regions of the brain that are known to be particularly susceptible to both mTBI and PTSD.

Within PTSD, structural and functional imaging studies have shown a wide range of brain regions that are affected. These regions include the amygdala, hippocampus, dorsolateral and dorsomedial prefrontal cortex, and the orbitofrontal cortex. As should be apparent, many of these regions have functional implications for the onset and maintenance of PTSD symptomology [39, 40]. When examining brain structure, many studies (including two large meta-analyses) have shown reduced volume in the hippocampus, a brain area that is known to mediate declarative memories [41, 42]. Similarly, reduced volume within the anterior cingulate cortex and insula have also been shown to be related to PTSD onset [43]. When examining the functional neuroimaging data related to PTSD, exposure to stimuli related to an individual’s trauma is associated with increased PTSD symptoms in concert with decreased activity within the medial prefrontal cortex and anterior cingulate [44, 45, 46]. Additional areas of decreased function during exposure to trauma-related stimuli include the inferior frontal gyrus, parietal cortex, visual association cortex, and hippocampus [44, 47, 48]. In contrast, areas of increased activity relative to controls include the amygdala [49, 50], parahippocampal gyrus [44, 51], and posterior cingulate [44, 45, 51]. Taken together, the existing literature provides strong evidence of dysfunction within a network of brain regions that are highly related to PTSD symptoms including the hippocampus and amygdala, cingulate cortex, and medial prefrontal cortex [52].

When examining the neurological correlates of mTBI, brain regions are most often damaged if the shearing forces that the brain undergoes during an mTBI are of sufficient magnitude to deform neural cells beyond normal tolerance levels [53]. If this deformation is of sufficient force to cause axonal tearing, the effects of the mTBI are likely to consist of longer-lasting neurological sequelae resulting from alterations to functional connectivity or difficulty with neuronal processing of information [54]. In comparison, if such forces are of a lesser magnitude, the neurological, cognitive, and behavioral symptoms are more likely to be short lived. In general, these forces particularly affect the longer white-matter tracts of the brain including the hypothalamic-pituitary–adrenal (HPA) axis, frontal, temporal, and limbic areas [55]. Specifically, these include the dorsolateral prefrontal cortex, the temporal pole, cerebellum, and frontal white matter tracts connecting the amygdala and medial prefrontal cortex [39, 40, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67]—all aforementioned areas that are also implicated in PTSD.

Although the role each of these regions play in the formation of cognition is beyond the scope of this chapter, it is apparent that many of these regions are involved in both emotional regulation and executive function, especially those that are affected in both PTSD and mTBI, including the prefrontal cortex and hippocampus [58, 68]. Perhaps not surprisingly, with the large amount of overlap in the neural substrates that are affected by both PTSD and mTBI, there is a fair degree of overlapping symptomology that has a significant impact on optimal methods for both diagnosing and treating PTSD concurrent with mTBI.

## 4. Current methods of diagnosis and treatment options

As stated previously, due to the overlap of symptoms in both PTSD and mTBI (Table 1), it is more difficult to both diagnose and treat PTSD when comorbid with mTBI. For example, in a recent study of 630,000+ veterans diagnosed with PTSD, only 30% had PTSD alone, with most suffering from concurrent psychiatric conditions, of which mTBI was a prominent co-condition [69].

PTSDmTBIPTSD/mTBI
Behavioral symptomsAggression
Agitation
Avoidance of cues
Hostility
Hypervigilance
Irritability
Self-Destructive
Behavior
Aggression
Impulsivity
Irritability
Aggression
Impulsivity/Self
Destructive Behaviors
Irritability
Physical/cognitive symptomsInability to concentrate or focus on tasks Insomnia
Nightmares
Sensitivity to sound
Coordination problems/loss of balance Amnesia
Disorientation
Dizziness
Fatigue
Inability to concentrate or focus on tasks
Insomnia
Sensitivity to sound
Inability to concentrate or focus on tasks
Insomnia
Sensitivity to sound
Psychological SymptomsAnhedonia/loss of
interest Anxiety
Depression
Intrusive thoughts/Unwanted thoughts
Reexperiencing the event/Flashbacks
Shame/Guilt
Social
Isolation/Loneliness
Anxiety
Apathy
Depression
Anhedonia/Apathy
Anxiety
Depression

### Table 1.

Symptomologies of PTSD and mTBI.

Diagnosis of PTSD usually consists of a combination of self-report measures and structured and/or semi-structured interview procedures. These procedures are often based on soliciting the information required to determine whether DSM-5 criteria [34] (or alternatives such as the ICD-10 [70]) have been met and include components of the trauma, symptoms/symptom clusters, and subtypes of the disorder. Common structured interviews, such as the Clinician-Administered PTSD Scale (CAPS), are considered both reliable and valid, however, they are time intensive [71]. Furthermore, due to upwards of 93% of PTSD cases co-reporting another psychiatric disorder, it can become difficult to differentiate between disorders with overlapping symptoms [6].

Unlike the diagnosis of TBI, where CT and MRI structural images readily demonstrate contusions or bleeds verifying their presence, there is a lack of interdisciplinary consensus as to what constitutes an mTBI. Although some criteria have been generally accepted (such as those described within the introduction of this chapter), there are diagnostic criteria available from the American Congress of Rehabilitation Medicine (ACRM), the US Centers for Disease Control and Prevention (CDC), and the World Health Organization (WHO) [72]. Therefore, the utility of a consistent and universally accepted measure of mTBI presence would be of great benefit when diagnosing a mTBI in isolation, and especially when attempting to diagnose in the presence of the overlapping symptoms commonly reported in PTSD.

As should be apparent from this cursory examination, the current process of diagnosing both PTSD and mTBI is largely reliant on often erroneous self-report techniques and arduous clinical interviews that have an inherent lack of consensus, necessitating improvements in both speed of diagnosis and consistency to best offer care and interventions to patients with PTSD and mTBI. One such avenue of providing this information may be found through the discovery of diagnostic biomarkers, which will be the primary focus of discussion for the remainder of this chapter. Before such a discussion takes place, it is important to further highlight the need for improved methods of diagnosing comorbid mTBI and PTSD by examining the implications such discoveries may have on treatment of each condition.

Although there are recognized “gold-standard” treatments for PTSD, there is still much room for improvement. For PTSD, Cognitive Behavioral Therapy (CBT) [73] and psychopharmacological treatment with selective serotonin reuptake inhibitors (SSRIs) and/or serotonin noradrenaline reuptake inhibitors (SNRIs) are often used for treatment. Similarly, both psychological and pharmacological treatments are recommended for the treatment of mTBI, such as CBT [74] in conjunction with pharmacological treatment of the sequalae associated with mTBI [75]. However, in a recent study of the evaluations of 41 guidelines related to the treatment of mTBI, only three were founded in what was determined to be an evidenced-based fashion [76], highlighting the need for more rigorous and evidence-based treatment regimens. There is even less evidence-based guidance when it comes to the treatment of comorbid mTBI and PTSD, making research on how to best identify multimorbidity in PTSD patients critical to developing effective treatment strategies.

## 5. Current biomarker research

As should be evident from the previous sections from this chapter, both the ability to diagnose PTSD comorbid with mTBI and the ability to effectively monitor treatment of the concurrent conditions would benefit from the identification of biomarkers. For this discussion we adapt the definition of a biomarker using a conceptual framework that is useful for clinical research and treatment purposes. This may include any information that can be used as an objective indication of a relevant medical state observed from outside the patient. Importantly, these signs must be able to be measured accurately and have high levels of replicability. This is captured in the WHO’s definition of a biomarker as “any substance, structure, or process that can be measured in the body or its products and influence or predict the incidence of outcome or disease” [77] and can be expanded to “… almost any measurement reflecting an interaction between a biological system and a potential hazard…[and] may be functional and physiological, biochemical at the cellular level, or a molecular interaction.” [78]. In alignment with these requirements, our discussion will focus on the relevance and validity of the suggested biomarkers, allowing for it to be used as a surrogate endpoint [79]. There are a wide range of biomarkers and targets currently being researched for roles in both mTBI and PTSD. A summary of biomarkers currently undergoing research that meet the criteria previously discussed can be seen in Table 2, with in-depth discussion of each following.

 HPA axis dysregulation Cortisol Adrenal glucocorticoid hormone that modulates the HPA axis PTSD Monoamine Dysfunction Norepinephrine (NE) Endogenous neurotransmitter and stress hormone PTSD Serotonin (5-HT) Monoamine neurotransmitter PTSD Inflammatory and immune function Interleukin-1ß (IL-1ß)Interleukin-2 (IL-2)Interleukin-6 (IL-6)Interleukin-8 (IL-8)Interleukin-10 (IL-10) Cytokine protein involved in inflammationCytokine protein involved in immune function regulationCytokine protein with pro- and antiinflammatory actionsCytokine protein involved in inflammationCytokine protein with anti-inflammatory actions PTSDPTSDPTSD and mTBI mTBI mTBI C-reactive protein (CRP) Circulating protein released in response to inflammation PTSD Tumor Necrosis Factor alpha subunit (TNF-α) Cytokine protein with pro-inflammatory actions PTSD Interferon gamma (IFN-γ) Cytokine protein involved in immune function regulation PTSD Marinobufagenin (MBG) Endogenous steroid related to myocardial infarction, heart failure, and kidney failure mTBI Genetic variation FKBP Prolyl Isomerase 5 (FKBP5)Serotonin transporter gene linked polymorphic region(5-HTTLPR) Protein coding gene regulating neuroendocrine stressGene promotor region on the serotonintransporter gene linked to neuropsychiatric disorders PTSDPTSD Nuclear receptor subfamily3 group C, member 1(NR3C-1) Promotor region of the glucocorticoid receptor gene related to metabolism and immune response PTSD Apolipoprotein E (APOE) Protein coding gene that regulates fat metabolism mTBI brain-derived neurotrophic factor (BDNF) Protein coding gene that promotes neuronal survival PTSD and mTBI Functional and structural neuroimaging AmygdalaMedial Prefrontal CortexRostral Anterior CingulateCortexHippocampus Involved in emotional processing, and conditioned fearInvolved in inhibition and goal-directed behaviorsCortical structure involved in mediating emotion and cognitive functionInvolved in memory and cognition PTSDPTSDPTSDPTSD Diffusion weighted imaging (DWI) Noninvasive technique using a specific form of Magnetic Resonance Imaging (MRI) to view water diffusion in images mTBI Magnetic resonance spectroscopy (MRS) Noninvasive technique to analyze metabolic changes in tissue mTBI Neuronal and axonal injury Tau ProteinUbiquitin C-terminal hydrolase isozyme L1 (UCHL1)Neuron-specific enolase(NSE) Protein expressed primarily in neurons, involved in stabilizing microtubulesEnzyme involved in axonal transport and integrityEnzyme involved in glycolytic metabolism in the brain mTBImTBImTBI Neutrophil gelatinaseassociated lipocalin (NGAL) Polypeptide released in response to systemic inflammation mTBI Blood BrainBarrierDisturbances CSF/serum albumin ratioAstrocyte-specific SNS protein S100B Measure of cerebrospinal fluid components in the periphery following injuryBinding protein produced by astrocytes involved in intracellular functions mTBImTBI PrPc-cellular prion protein Glycoprotein typically anchored to plasma membranes, proposed to be involved in neurodegenerative prion disease mTBI CerebralBlood FlowChanges Vasoreactivity MRI measurable changes that could impair smooth muscle and affect cognition mTBI

### Table 2.

Summary of current biomarker research.

### 5.1 PTSD

Most of the promising biomarkers for the presence of PTSD are related to either dysfunction of the HPA axis, monoamine systems, heightened inflammation, genetic and epigenetic changes thought to be a result of methylation brought about through exposure to prolonged stress, or functional and structural neuroimaging. There has also been growing interest and research in the examination of psychophysical biomarkers of PTSD, such as indicators of hyperarousal (heart rate, blood pressure, skin conductance, etc.). However, examination of these forms of hyperactivity through psychological testing is beyond the scope of this chapter.

HPA Axis Dysregulation.Cortisol, a circulating adrenal glucocorticoid hormone that modulates the HPA axis is known to be involved in anxiety responses and sleep regulation [80]. Research has shown that within a PTSD population, lower salivary cortisol levels were found when compared to control participants, especially when measurements were taken in the morning [80]. Typically, there is a diurnal cycle of salivary cortisol with peak concentration observed shortly after waking, and then drops across the waking hours. In addition to a lower morning level of cortisol, PTSD patients have also demonstrated a blunted cortisol response throughout the day [81]. This blunted cortisol reactivity in response to exposure to acute stress may offer more promise as it removes confounds associated with the measurement of baseline cortisol, such as sex differences and time of day effects. Therefore, although not specific to the presence of PTSD, measurements of circulating cortisol levels may form part of a panel of assays designed to detect the presence of PTSD in a clinical population due to its non-invasive status when measured from a saliva sample.

Monoamine Dysfunction.As PTSD includes increased sympathetic nervous system tone, it is not surprising that levels of norepinephrine (NE) are also heightened [82]. In a prospective study of motor vehicle accident survivors, urinary levels of NE were positively correlated with the likelihood of development of PTSD in the month following trauma, but only in males [83]. Changes in the serotonergic (5-HT) system have also been observed in PTSD. Specifically, 5-HT transporter binding within the amygdala is reduced in PTSD and correlated with both anxiety and depression within PTSD patients [84].

Inflammatory and Immune Function.Stemming from the high comorbidity between PTSD and general physical illnesses [85], there has been extensive examination of the potential role of markers of inflammation as a proxy for PTSD and PTSD symptomology. In all instances examined, there is a positive correlation between inflammatory markers and PTSD symptomology. This includes interleukin (IL) -6 [86], IL-2 [87], IL-1β [88]. Additionally, increased C-reactive protein (CRP) levels are shown to be elevated in individuals with PTSD [89, 90, 91], but also has been shown to be predictive of post-deployment PTSD when examined in a prospective study [92]. Continuing this trend, PTSD is also positively correlated with higher levels of TNF-α and IFN-γ when compared to healthy controls, likely as a result of the persistent stress experienced [93]. In general, data concerning the relationship between inflammatory responses and PTSD confirm that PTSD is likely associated with chronic inflammation. Although this may lead to inflammation as a viable therapeutic target to alleviate at least some of the symptoms associated with PTSD, they do not serve well as a general biomarker of PTSD presence or prognosis due to its status as a hallmark finding in many other diseased states, including those that are often comorbid with PTSD [85, 94, 95, 96, 97].

Genetic Variation.Most genetic and epigenetic findings have clustered around modulators of HPA axis function either before or following trauma. Perhaps the most cited modulator is FKBP5, a protein encoding gene involved in immunoregulation [98]. Polymorphisms on FKBP5, specifically Val66Met, have been associated PTSD [99]. Met-allele carriers are also reported to have greater severity in PTSD symptoms amongst veterans compared to Val/Val genotypes [100]. However, FKBP5 is also associated with depression [101], a condition known to often co-occur with PTSD therefore making its use as a solitary differential marker of PTSD unlikely. The serotonin transporter gene linked polymorphic region (5-HTTLPR short and long) has also been linked to trauma exposure and depression. Individuals with the LL genotype exhibit lower intrusion and avoidance symptoms compared to those with the S-allele, though no differences were found in other PTSD symptoms [102]. Increased methylation levels at 4 promotor sites on BDNF were found in PTSD patients that experienced high combat exposure compared to those without PTSD [103]. Reduced glucocorticoid receptor NR3C1-1F promotor methylation was found in combat veterans that developed PTSD when compared to those that did not [104]. Hypermethylation at NR3C1 gene promoters were associated with lower risk of PTSD in male genocide survivors, but not female [105].

As has become apparent, many (if not all) of these genetic regions have been associated with other psychiatric conditions and may therefore be a better marker of stress-induced psychopathology in general rather than PTSD specifically, and there has yet to be a single genetic or epigenetic factor that reliably predicts the presence or severity of PTSD in isolation of other psychiatric conditions.

Functional and Structural Neuroimaging.One of the most consistent findings regarding neuroimaging of PTSD is the presence of increased amygdala activation when compared to controls when patients have been exposed to fear inducing stimuli [106]. For example, there have now been a number of studies that demonstrate hyperactivity of the amygdala when PTSD participants have been exposed to trauma-relevant words when compared to amygdala activity of control participants [107, 108, 109, 110]. Further studies have shown that this increased activity may be a result of weakened inhibitory control of the amygdala by the medial prefrontal cortex [106, 108, 110]. Furthering these findings, a recent meta-analysis of imaging studies during emotional tasks for individuals with PTSD, anxiety, and phobia revealed that only the PTSD patients demonstrated decreased activity within the rostral anterior cingulate cortex, offering a potential mechanism to distinguish between aberrant functional activity observed in PTSD and not in other anxiety disorders [111].

In addition to functional studies, a number of structural examinations of PTSD have taken place using neuroimaging techniques. Early studies examining structural differences between PTSD and non-PTSD patients demonstrated that smaller hippocampal volume may be associated with an increased risk of developing PTSD [112], though this finding has more recently been questioned with hippocampal volume reductions being acquired with trauma exposure [113]. When examining specific regions of the hippocampus using structural MRI, it appears as though reductions in specific subregions can be associated with PTSD symptoms. Specifically, reductions within the cornu ammonis 3 (CA3) layer of the hippocampus and the dentate gyrus are related to PTSD symptomology [114].

### 5.2 mTBI

Currently, mTBI is typically diagnosed based solely on clinical presentation, in comparison to TBI which has prominent and objective neuroimaging findings. This has several implications as to the utility of biomarkers of mTBI. Perhaps of primary concern is the fact that any biomarker that would offer clinical benefits must be correlated with clinical symptom presentation. For example, a marker that elevates with impacts to the head without observable changes in clinical presentation in the patient would be of little clinical use. Potential biomarkers for mTBI are most often related to, or spawned, by the axonal injury that occurs following the much smaller forces related to a mTBI. These can be broadly categorized as those that are related to neuronal and axonal injury, blood brain barrier disturbances, neuroinflammation, cerebral blood flow changes, and genetic variation.

Neuronal and Axonal Injury. Disturbances of the cellular environment often occur following the shearing forces that often accompany mTBI [115], and while this usually is not to the extend to the point of axonal disconnection, it can indirectly affect membrane homeostasis which ultimately results in cell damage [53, 116]. There are several potential biomarkers associated with neuronal damage. Tau protein is known to be changed in response to injury [117] including mTBI, at least in animal models [118]. In one of the larger human studies (196 patients), the ratio of phosphorylated-tau to total tau had both a good diagnostic and prognostic marker for acute TBI, including those with a mild severity [119]. Other biomarkers of neuronal and axonal injury that have been explored as potentials include ubiquitin carboxyl-terminal hydrolase isozyme L1 (UCHL1), [120, 121, 122], neuron-specific enolase (NSE) [123, 124, 125], and neutrophil gelatinase-associated lipocalin (NGAL) [126]. However, current research into their utility has not demonstrated sufficient levels of specificity and/or replicability to be discussed in detail, but likely warrant further examination.

Blood Brain Barrier Disturbances.Although it has been well demonstrated that blood brain barrier (BBB) disruptions are associated with TBI [127], there is growing evidence that there are BBB disruptions following mTBI during both the chronic and the acute phase [128]. There are a number of non-invasive indirect measures of BBB dysfunction that rely on the detection of cerebrospinal fluid (CSF) components within peripheral serum, however, there has been little convincing evidence that suggests it will be a suitable biomarker of mTBI if used in isolation. The CSF/serum albumin ratio is the standard biomarker for BBB integrity [129] but is not sensitive enough to detect the presence of BBB disruption as a result of mTBI [130]. Perhaps the most studied is the astrocyte-specific SNS protein S100B. Research has shown that the detection of this marker approaches the same levels of sensitivity as the CSF/serum albumin ratio [127], and has been used to rule out mTBI in emergency medicine already, where S100B levels have a high (99 + %) predictive value [131]. However, there is relative non-specificity of elevated S100B (as there are extracerebral sources of S100B in peripheral blood), and it has also shown to be elevated in clinical cases without head trauma [132]. Further dampening enthusiasm, there is still conflicting evidence as to whether S100B levels are positively correlated with mTBI [133]. A less explored, though perhaps more promising marker is the glycoprotein PrPc—cellular prion protein. Since this plasma-soluble prion protein is located within the plasma membrane, is has been suggested that it may be released following an mTBI as a result of BBB dysfunction [134], with animal models showing increased serum levels following blast exposure induced mTBI [135, 136]. Within humans, a small (N = 6) study amongst athletes demonstrated PrPc levels increased and remained elevated following mTBI [134]. More recently, a slightly larger study conducted within a hospital setting (N = 20) confirmed this effect with elevated PrPc levels following TBI, with 8 of the 20 being classified as mild injuries. However, PrPc did levels did not correlate with severity of trauma [137]. A third study confirmed the ability for PrPc levels to differentiate TBI with cognitive symptoms versus TBI in which no cognitive symptoms were present [138]. Although additional study is required, these specific features of PrPc make it a particularly attractive candidate biomarker for mTBI. Specifically, its relative specificity with regard to cognitive dysfunction, and ability to be detected years following trauma, are likely of great utility.

Neuroinflammation.Following TBI, including mTBI, there is a cascade of events that ultimately results in the presence of inflammation [139, 140, 141, 142], offering an opportunity to examine markers of the neuroinflammatory response as a marker of brain injury. Two promising classes of markers of neuroinflammation are the inflammatory interleukin proteins and the cardiotonic steroid marinobufagenin. There have been many studies demonstrating elevated levels of interleukins including IL-6, IL-8 and IL-10 following brain injury [143, 144, 145, 146, 147, 148], as well as studies showing these levels are related to clinical outcome in mTBI [149, 150]. In a small (N = 6) study, marinobufagenin (MBG) levels were initially increased following mTBI, along with symptomology [151]. As MBG levels decreased, symptom scores also decreased, suggesting there may be a relationship between symptoms and MBG. A larger study (N = 110) found MBG levels were elevated following mTBI, and were also correlated with reported symptoms [151] adding further evidence for the potential utility of MBG.

A further drawback to most biofluid based biomarkers of mTBI is the timescale at which they can be detected, necessitating their examination within the acute stage of the injury as they return to baseline levels rather quickly (though PrPc is an exception to this). As an alternative, potentially longer-lasting biomarker, advanced neuroimaging techniques such as diffusion weighted imagery (DWI) and magnetic resonance spectroscopy (MRS) for diagnosing the presence of an mTBI at a timescale that extends beyond the acute stage. Genetic information may offer additional information not available through the other methods discussed, such as the susceptibility to mTBI following head trauma, reflected in the likelihood of developing symptoms based on genetic variation.

Cerebral Blood Flow Changes.Recent research has shown that following mTBI, there are changes in vasoreactivity that impair smooth muscle response [152], ultimately affecting cerebral blood flow that animal models have shown can persist up to a year after initial damage [153]. Due to the extended period of blood flow changes, this may be an ideal candidate for evaluating whether long-term changes in cognition are a result of a previously acquired mTBI [154]. These changes in blood flow can be detected using modern magnetic resonance imaging techniques as hypoperfusion in many of the anatomical regions previously described as particularly susceptible to mTBI injury including the prefrontal, frontal, and temporal regions of the brain [118].

Genetic Variation.The two leading genetic candidates are the genetic mutations in the genes encoding for apolipoprotein E (APOE) and brain-derived neurotrophic factor (BDNF). It is important to note that both of these genes are already being explored as they pertain to the risk of generating various types of neurodegeneration disorders, such as Alzheimer’s disease [155]. This finding is not all that unexpected considering the building link between mTBI and subsequent neurodegenerative conditions [156, 157, 158, 159]. The APOE ε4 allele has been shown to be a significant risk factor for the development of Alzheimer’s disease, but systematic review [160] has shown it is unrelated to mTBI diagnosis. Interestingly, this same allele confers increased risk to some of the cognitive impairment associated with the longer-term symptoms of mTBI [161]. When it comes to studies examining the role of BDNF, a small sample (at least on the scale of genetic studies; N = 110) showed a link between carriers of the minor allele of rs115769 and the memory impairments often associated with mTBI [162], as well as the BDNF Val66Met allele being linked to a higher risk of experiencing an mTBI [163], and increased experience of emotional symptoms following the occurrence of an mTBI [164]. Further, it was been shown that mutations of BDNF rs6265 Val66Met polymorphisms affect neurocognitive performance in patients following mTBI, offering the potential for predicting which patients will go on to develop neurocognitive symptoms following mTBI [165].

## 6. Summary and conclusions

Biomarkers for PTSD.At this time, there are a number of biomarkers that are associated with PTSD risk, symptoms, and symptom progression. Despite this association, due to the common comorbidity with both other psychiatric conditions and general health status, there is currently little chance of using any single marker as a diagnostic characterization. Future studies must do a more thorough examination of biological and psychological states within PTSD to be able to characterize a combination of biomarkers that may cluster around symptoms and symptom progression in a meaningful way. One way that this may be accomplished is through the use of biomarkers to identify features associated with PTSD, rather than with markers that are consistent with the DSM criteria [166]. For example, it may be that reduced hippocampal volume is associated both with PTSD and comorbid depressive state and can serve as a biomarker of the cluster of symptoms associated with both. This approach would necessitate a panel of biomarkers to increase the specificity, sensitivity, and replicability of any proposed tool. In fact, such an approach utilizing signals from multiple biological domains totaling in excess of one million unique markers was used to define 343 candidate biomarkers via a combination of data-driven and hypothesis driven approaches. These features were further reduced to 28 based on performance and ability to track phenotype, resulting in a final panel which obtained impressive levels of accuracy, sensitivity, and specificity (81, 85, and 77%, respectively) [167].

Biomarkers for mTBI.Currently, there is insufficient evidence to support a relationship between biomarkers of mTBI and clinical outcomes, though many offer promise of acting in this capacity. For this relationship to be drawn, it is imperative that future research includes clinical outcome measures and that a standardized study design is utilized. From the non-exhaustive work cited here, it is clear that differences in methodology, especially related to the timing of sample collection, the length of follow-up, the clinical measurements performed, and the clinical population studied all could be leading to the sometimes-conflicting results reported and the relatively small, unconvincing effect sizes. Further, it is also apparent that although many of the reported biomarkers are sensitive to the presence of head impact, unless the candidate biomarker scales with symptoms reported, it will be of little clinical utility. In fact, there is often little disagreement as to whether an impact to the head has occurred, but rather, the intent of the biomarker is to assess whether that impact is going to result (or is the cause) of symptoms being reported.

## 7. Summary of differential features

Differential features of biomarkers specific to PTSD

• HPA Axis Dysregulation (cortisol)

• Monoamine Dysfunction (norepinephrine and serotonin)

• Inflammatory and Immune Function (interleukins 2 and 1ß, C-reactive protein)

• Genetic Variation (polymorphisms and methylation on genes FKBP5, 5-HTTLPR, and NR3C1)

• Functional and Structural Neuroimaging (differential activation in amygdala, prefrontal cortex, hippocampus and rostral anterior cingulate cortex)

Differential features of biomarkers specific to mTBI

• Neuronal and Axonal Injury (Tau protein, ubiquitin carboxyl-terminal hydrolase, neuron-specific enolase, neutrophil gelatinase-associated lipocalin)

• Blood Brain Barrier Disturbances (CSF/serum albumin ratio, S100B, PrPC levels)

• Neuroinflammation (interleukins 8 and 10, marinobufagenin)

• Cerebral Blood Flow Changes (magnetic resonance imaging techniques to detect hypoperfusion)

Biomarkers for PTSD comorbid with mTBI.It should be apparent from the lack of conclusive biomarkers for PTSD and mTBI when occurring in isolation that there is currently little prospect for a single biomarker that will be able to diagnose PTSD concurrent with mTBI versus detecting the presence of each condition in isolation. Part of this difficulty directly stems from the current method of diagnoses for each of these conditions. As previously discussed, although mTBI is most certainly a neurological event, it is diagnosed in a manner consistent with a psychiatric condition—based on the collection of symptoms reported. With the overlap of symptoms between both mTBI and PTSD, many of the identified biomarker candidates would be expected to be present in both PTSD and mTBI, ultimately hindering a differential diagnosis. In essence, the same conditions that necessitate the identification of a biomarker of these conditions also prevents its discovery. In addition to the necessity for larger and better designed studies, it is clear that examining the potential of any biomarker in isolation is ultimately a futile event. What may be possible in the near future is the union of several different biomarkers that are selected based on their specificity and replicability in differentially identifying PTSD and mTBI. This will require larger scale studies that collect a wide range of neuropsychological and biological samples, as well as neuroimaging, and combine them to truly accomplish these goals. In recent years there has been some progress in this regard [168, 169], at least signifying that within the field there is a recognized need and attempt to combine biomarkers not only from separate conditions, but indeed separate disciplines to discover ways to diagnose PTSD concurrent with mTBI in a more rigorous and efficient manner. This use of a collective intelligence approach, common in other fields such as finance [170], would allow for domain area expertise to identify successful candidates from what is a current, and continually growing, set of candidate biomarkers.

In summary, posttraumatic stress disorder and mTBI are both significant problems that lead to reduced quality of life for a wide range of people. Due to the nature of symptoms, diagnosis and treatment is inefficient and often delayed, resulting in additional complications in patient outcomes. Determining consistent and accurate biomarkers to improve diagnostic measures of both PTSD and mTBI as well as to differentiate between the two would improve outcomes for both disorders. In the near future, the combination of a selection of the individual biomarkers discussed could be used to design a comprehensive screening tool for individuals following a traumatic event. Additionally, identification of biomarkers involved in the transition post-injury to long-term post-concussive symptoms could allow for early intervention and prevent development of PTSD following trauma. Further, the monitoring and classification of individual responses to screening arrays could dictate the best treatment options, and inform recommendations of medication, therapies, neuromodulation techniques and various combinations from those currently available. Ultimately, this could allow patients and physicians to better direct treatment and response measures based on the individual’s biological makeup.

## References

1. 1. Tanielian T et al. Invisible Wounds: Mental Health and Cognitive Care Needs of America’s Returning Veterans. Santa Monica, CA: Rand Corporation; 2008
2. 2. Tanev KS et al. PTSD and TBI co-morbidity: Scope, clinical presentation and treatment options. Brain Injury. 2014;28(3):261-270
3. 3. Otis JD et al. Complicating factors associated with mild traumatic brain injury: Impact on pain and posttraumatic stress disorder treatment. Journal of Clinical Psychology in Medical Settings. 2011;18(2):145-154
4. 4. McAllister TW. Psychopharmacological Issues in the Treatment of TBI and PTSD. The Clinical Neuropsychologist. 2009;23(8):1338-1367
5. 5. Adler A. Neuropsychiatric complications in victims of Boston’s cocoanut grove disaster. Journal of the American Medical Association. 1943;123(17):1098-1101
6. 6. Van Praag DLG et al. Post-traumatic stress disorder after civilian traumatic brain injury: A systematic review and meta-analysis of prevalence rates. Journal of Neurotrauma. 2019;36(23):3220-3232
7. 7. Jorge RE. Posttraumatic stress disorder. Continuum: Lifelong Learning in Neurology. 2015;21(3):789-805
8. 8. Faul M. et al. Traumatic Brain Injury in the United States; Emergency Department Visits, Hospitalizations, and Deaths, 2002-2006. Atlanta (GA): Centers for Disease Control and Prevention, National Center for Injury Prevention and Control; 2010
9. 9. Vos PE et al. EFNS guideline on mild traumatic brain injury: Report of an EFNS task force. European Journal of Neurology. 2002;9(3):207-219
10. 10. Corrigan JD, Selassie AW, Orman JAL. The epidemiology of traumatic brain injury. The Journal of Head Trauma Rehabilitation. 2010;25(2):72-80
11. 11. Carroll LJ et al. Systematic review of the prognosis after mild traumatic brain injury in adults: Cognitive, psychiatric, and mortality outcomes: Results of the international collaboration on mild traumatic brain injury prognosis. Archives of Physical Medicine and Rehabilitation. 2014;95(3):S152-S173
12. 12. Craig A et al. Psychological impact of injuries sustained in motor vehicle crashes: Systematic review and meta-analysis. BMJ Open. 2016;6(9):e011993-e011993
13. 13. Hoge CW et al. Mild traumatic brain injury in US soldiers returning from Iraq. New England Journal of Medicine. 2008;358(5):453-463
14. 14. Lew HL et al. Prevalence of chronic pain, posttraumatic stress disorder, and persistent postconcussive symptoms in OIF/OEF veterans: Polytrauma clinical triad. Journal of Rehabilitation Research & Development. 2009;46(6):697-702
15. 15. Borg J et al. Non-surgical intervention and cost for mild traumatic brain injury: Results of the WHO collaborating centre task force on mild traumatic brain injury. Journal of Rehabilitation Medicine. 2004;36(0):76-83
16. 16. Hu J et al. Trend and geographic analysis for traumatic brain injury mortality and cost based on MarketScan database. Journal of Neurotrauma. 2013;30(20):1755-1761
17. 17. Davis KL et al. The direct economic burden of blunt and penetrating trauma in a managed care population. Journal of Trauma and Acute Care Surgery. 2007;62(3):622-630
18. 18. McGarry LJ et al. Outcomes and costs of acute treatment of traumatic brain injury. Journal of Trauma and Acute Care Surgery. 2002;53(6):1152-1159
19. 19. Kreutzer JS et al. Charges and lengths of stay for acute and inpatient rehabilitation treatment of traumatic brain injury 1990-1996. Brain Injury. 2001;15(9):763-774
20. 20. Thompson K, Antony A, Holtzman A. The costs of traumatic brain injury. North Carolina Medical Journal. 2001;62(6):376-379
21. 21. Harrison JP, Satterwhite LF, Ruday W. The financial impact of post traumatic stress disorder on returning US military personnel. Journal of Health Care Finance. 2010;36(4):65-74
22. 22. Ferry FR et al. The economic burden of PTSD in Northern Ireland. Journal of Traumatic Stress. 2015;28(3):191-197
23. 23. Konnopka A, König H. Economic burden of anxiety disorders: A systematic review and meta-analysis. PharmacoEconomics. 2020;38(1):25-37
24. 24. Greenberg PE et al. The economic burden of anxiety disorders in the 1990s. Journal of Clinical Psychiatry. 1999;60(7):427-435
25. 25. Wilson S, Guliani H, Boichev G. On the economics of post-traumatic stress disorder among first responders in Canada. Journal of Community Safety and Well-Being. 2016;1(2):26-31
26. 26. Vanderploeg RD, Belanger HG, Curtiss G. Mild traumatic brain injury and posttraumatic stress disorder and their associations with health symptoms. Archives of Physical Medicine and Rehabilitation. 2009;90(7):1084-1093
27. 27. Stein MB, McAllister TW. Exploring the convergence of posttraumatic stress disorder and mild traumatic brain injury. American Journal of Psychiatry. 2009;166(7):768-776
28. 28. Silverberg ND, Duhaime A-C, Iaccarino MA. Mild traumatic brain injury in 2019-2020. JAMA. 2020;323(2):177-178
29. 29. Cameron KL et al. Trends in the incidence of physician-diagnosed mild traumatic brain injury among active duty US military personnel between 1997 and 2007. Journal of Neurotrauma. 2012;29(7):1313-1321
30. 30. Zatzick DF et al. Multisite investigation of traumatic brain injuries, posttraumatic stress disorder, and self-reported health and cognitive impairments. Archives of General Psychiatry. 2010;67(12):1291-1300
31. 31. Menon DK et al. Position statement: Definition of traumatic brain injury. Archives of Physical Medicine and Rehabilitation. 2010;91(11):1637-1640
32. 32. Prevention, N.C.f.I. and Control, Report to Congress on mild traumatic brain injury in the United States: Steps to prevent a serious public health problem. 2003: Centers for Disease Control and Prevention
33. 33. Ruff RM et al. Recommendations for diagnosing a mild traumatic brain injury: A National Academy of Neuropsychology education paper. Archives of Clinical Neuropsychology. 2009;24(1):3-10
34. 34. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders: DSM-5. Arlington, VA: American Psychiatric Association; 2013
35. 35. Gaher RM et al. An experience sampling study of PTSD and alcohol-related problems. Psychology of Addictive Behaviors. 2014;28(4):1013
36. 36. Sareen J. Posttraumatic stress disorder in adults: Impact, comorbidity, risk factors, and treatment. The Canadian Journal of Psychiatry. 2014;59(9):460-467
37. 37. Weiner MW et al. Effects of traumatic brain injury and posttraumatic stress disorder on Alzheimer’s disease in veterans, using the Alzheimer’s disease neuroimaging initiative. Alzheimer’s & Dementia. 2014;10:S226-S235
38. 38. Roberts AL et al. Posttraumatic stress disorder and incidence of type 2 diabetes mellitus in a sample of women: A 22-year longitudinal study. JAMA Psychiatry. 2015;72(3):203-210
39. 39. Jovanovic T, Ressler KJ. How the neurocircuitry and genetics of fear inhibition may inform our understanding of PTSD. American Journal of Psychiatry. 2010;167(6):648-662
40. 40. Lanius RA et al. Emotion modulation in PTSD: Clinical and neurobiological evidence for a dissociative subtype. American Journal of Psychiatry. 2010;167(6):640-647
41. 41. Kitayama N et al. Magnetic resonance imaging (MRI) measurement of hippocampal volume in posttraumatic stress disorder: A meta-analysis. Journal of Affective Disorders. 2005;88(1):79-86
42. 42. Smith ME. Bilateral hippocampal volume reduction in adults with post-traumatic stress disorder: A meta-analysis of structural MRI studies. Hippocampus. 2005;15(6):798-807
43. 43. Kasai K et al. Evidence for acquired pregenual anterior cingulate gray matter loss from a twin study of combat-related posttraumatic stress disorder. Biological Psychiatry. 2008;63(6):550-556
44. 44. Bremner JD et al. Neural correlates of memories of childhood sexual abuse in women with and without posttraumatic stress disorder. American Journal of Psychiatry. 1999;156(11):1787-1795
45. 45. Lanius RA et al. Recall of emotional states in posttraumatic stress disorder: An fMRI investigation. Biological Psychiatry. 2003;53(3):204-210
46. 46. Lanius RA et al. Neural correlates of traumatic memories in posttraumatic stress disorder: A functional MRI investigation. American Journal of Psychiatry. 2001;158(11):1920-1922
47. 47. Shin LM et al. Regional cerebral blood flow during script-driven imagery in childhood sexual abuse-related PTSD: A PET investigation. American Journal of Psychiatry. 1999;156(4):575-584
48. 48. Shin LM et al. Visual imagery and perception in posttraumatic stress disorder: A positron emission tomographic investigation. Archives of General Psychiatry. 1997;54(3):233-241
49. 49. Rauch SL et al. A symptom provocation study of posttraumatic stress disorder using positron emission tomography and script-driven imagery. Archives of General Psychiatry. 1996;53(5):380-387
50. 50. Shin LM et al. Regional cerebral blood flow in the amygdala and medial prefrontalcortex during traumatic imagery in male and female vietnam veterans with ptsd. Archives of General Psychiatry. 2004;61(2):168-176
51. 51. Bremner JD et al. Neural correlates of exposure to traumatic pictures and sound in Vietnam combat veterans with and without posttraumatic stress disorder: A positron emission tomography study. Biological Psychiatry. 1999;45(7):806-816
52. 52. Bremner JD. Neuroimaging studies in post-traumatic stress disorder. Current Psychiatry Reports. 2002;4(4):254-263
53. 53. Büki A, Povlishock J. All roads lead to disconnection?–Traumatic axonal injury revisited. Acta Neurochirurgica. 2006;148(2):181-194
54. 54. Biasca N, Maxwell WL. Minor traumatic brain injury in sports: A review in order to prevent neurological sequelae. Progress in Brain Research. 2007;161:263-291
55. 55. Hamberger A et al. Concussion in professional football: Morphology of brain injuries in the NFL concussion model—part 16. Neurosurgery. 2009;64(6):1174-1182
56. 56. Yehuda R. Post-traumatic stress disorder. New England Journal of Medicine. 2002;346(2):108-114
57. 57. McAllister TW, Stein MB. Effects of psychological and biomechanical trauma on brain and behavior. Annals of the New York Academy of Sciences. 2010;1208(1):46-57
58. 58. Thurmond VA et al. Advancing integrated research in psychological health and traumatic brain injury: Common data elements. Archives of Physical Medicine and Rehabilitation. 2010;91(11):1633-1636
59. 59. Daniels JK et al. Switching between executive and default mode networks in posttraumatic stress disorder: Alterations in functional connectivity. Journal of Psychiatry & Neuroscience: JPN. 2010;35(4):258
60. 60. Panenka WJ et al. Neuropsychological outcome and diffusion tensor imaging in complicated versus uncomplicated mild traumatic brain injury. PLoS One. 2015;10(4):e0122746
61. 61. Meier TB et al. Longitudinal assessment of white matter abnormalities following sports-related concussion. Human Brain Mapping. 2016;37(2):833-845
62. 62. Orrison WW Jr et al. Traumatic brain injury: A review and high-field MRI findings in 100 unarmed combatants using a literature-based checklist approach. Journal of Neurotrauma. 2009;26(5):689-701
63. 63. Dretsch MN. Enhancing operational readiness through neuroimaging: Mapping the pathophysiology of mild traumatic brain injury in warfighters. In: The 71F Advantage: Applying army research psychology for health and performance gains. Washington D.C.: National Defense University Press; 2010. pp. 261-282
64. 64. Huisman TA et al. Diffusion tensor imaging as potential biomarker of white matter injury in diffuse axonal injury. American Journal of Neuroradiology. 2004;25(3):370-376
65. 65. Kennis M et al. Treatment outcome-related white matter differences in veterans with posttraumatic stress disorder. Neuropsychopharmacology. 2015;40(10):2434
66. 66. Bierer LM et al. White matter abnormalities in Gulf War veterans with posttraumatic stress disorder: A pilot study. Psychoneuroendocrinology. 2015;51:567-576
67. 67. Sanjuan PM et al. Reduced white matter integrity in the cingulum and anterior corona radiata in posttraumatic stress disorder in male combat veterans: A diffusion tensor imaging study. Psychiatry Research: Neuroimaging. 2013;214(3):260-268
68. 68. Rosenfeld JV, Ford NL. Bomb blast, mild traumatic brain injury and psychiatric morbidity: A review. Injury. 2010;41(5):437-443
69. 69. Hefner K, Rosenheck R. Multimorbidity among veterans diagnosed with PTSD in the veterans health administration nationally. Psychiatric Quarterly. 2019;90(2):275-291
70. 70. World Health Organization. The ICD-10 Classification of Mental and Behavioural Disorders: Clinical Descriptions and Diagnostic Guidelines. Geneva: World Health Organization; 1992
71. 71. Blake DD et al. The development of a clinician-administered PTSD scale. Journal of Traumatic Stress. 1995;8(1):75-90
72. 72. Prince C, Bruhns ME. Evaluation and treatment of mild traumatic brain injury: The role of neuropsychology. Brain Sciences. 2017;7(8):105
73. 73. Kar N. Cognitive behavioral therapy for the treatment of post-traumatic stress disorder: A review. Neuropsychiatric Disease and Treatment. 2011;7:167
74. 74. Cicerone KD et al. Evidence-based cognitive rehabilitation: Updated review of the literature from 2003 through 2008. Archives of Physical Medicine and Rehabilitation. 2011;92(4):519-530
75. 75. Warden DL et al. Guidelines for the pharmacologic treatment of neurobehavioral sequelae of traumatic brain injury. Journal of Neurotrauma. 2006;23(10):1468-1501
76. 76. Borg J, Carroll L. Critical evaluation of the existing guidelines on mild traumatic brain injury. Journal of Rehabilitation Medicine. 2004;43:106-112
77. 77. World Health Organization. International Programme on Chemical Safety. Biomarkers in Risk Assessment: Validity and Validation. Geneva: WHO; 2001. p. 2016
78. 78. World Health Organization. Biomarkers and Risk Assessment: Concepts and Principles-Environmental Health Criteria 155. Geneva: WHO; 1993
79. 79. Strimbu K, Tavel JA. What are biomarkers? Current Opinion in HIV and AIDS. 2010;5(6):463-466
80. 80. Pan X et al. Salivary cortisol in post-traumatic stress disorder: A systematic review and meta-analysis. BMC Psychiatry. 2018;18(1):324-324
81. 81. Speer KE et al. HPA axis function and diurnal cortisol in post-traumatic stress disorder: A systematic review. Neurobiology of Stress. 2019;11:100180-100180
82. 82. Geracioti TD et al. CSF norepinephrine concentrations in posttraumatic stress disorder. American Journal of Psychiatry. 2001;158(8):1227-1230
83. 83. Hawk LW et al. Urinary catecholamines and cortisol in recent-onset posttraumatic stress disorder after motor vehicle accidents. Psychosomatic Medicine. 2000;62(3):423-434
84. 84. Murrough JW et al. Reduced amygdala serotonin transporter binding in posttraumatic stress disorder. Biological Psychiatry. 2011;70(11):1033-1038
85. 85. Boscarino JA. Posttraumatic stress disorder and physical illness: Results from clinical and epidemiologic studies. Annals of the New York Academy of Sciences. 2004;1032(1):141-153
86. 86. Maes M et al. Elevated serum interleukin-6 (IL-6) and IL-6 receptor concentrations in posttraumatic stress disorder following accidental man-made traumatic events. Biological Psychiatry. 1999;45(7):833-839
87. 87. Smith AK et al. Differential immune system DNA methylation and cytokine regulation in post-traumatic stress disorder. American journal of medical genetics. Part B: Neuropsychiatric Genetics : The Official Publication of the International Society of Psychiatric Genetics. 2011;156B(6):700-708
88. 88. Spivak B et al. Elevated levels of serum interleukin-1β in combat-related posttraumatic stress disorder. Biological Psychiatry. 1997;42(5):345-348
89. 89. Michopoulos V et al. Association of CRP genetic variation and CRP level with elevated PTSD symptoms and physiological responses in a civilian population with high levels of trauma. The American Journal of Psychiatry. 2015;172(4):353-362
90. 90. Miller RJ et al. C-reactive protein and interleukin6 receptor in post-traumatic stress disorder: A pilot study. Cytokine. 2001;13(4):253-255
91. 91. Plantinga L et al. Association between posttraumatic stress disorder and inflammation: A twin study. Brain, Behavior, and Immunity. 2013;30:125-132
92. 92. Eraly SA et al. Assessment of plasma C-reactive protein as a biomarker of posttraumatic stress disorder risk. JAMA Psychiatry. 2014;71(4):423-431
93. 93. Passos IC et al. Inflammatory markers in post-traumatic stress disorder: A systematic review, meta-analysis, and meta-regression. The Lancet Psychiatry. 2015;2(11):1002-1012
94. 94. Boscarino JA. Diseases among men 20 years after exposure to severe stress. Psychosomatic Medicine. 1997;59(6):605-614
95. 95. Boscarino JA, Chang J. Electrocardiogram abnormalities among men with stress-related psychiatric disorders: Implications for coronary heart disease and clinical research. Annals of Behavioral Medicine. 1999;21(3):227-234
96. 96. Raison CL, Capuron L, Miller AH. Cytokines sing the blues: Inflammation and the pathogenesis of depression. Trends in Immunology. 2006;27(1):24-31
97. 97. Weiss T et al. Posttraumatic stress disorder is a risk factor for metabolic syndrome in an impoverished urban population. General Hospital Psychiatry. 2011;33(2):135-142
98. 98. Wang Q, Shelton RC, Dwivedi Y. Interaction between early-life stress and FKBP5 gene variants in major depressive disorder and post-traumatic stress disorder: A systematic review and meta-analysis. Journal of Affective Disorders. 2018;225:422-428
99. 99. Zhang L et al. PTSD risk is associated with BDNF Val66Met and BDNF overexpression. Molecular Psychiatry. 2013;19(1):8-10
100. 100. Pitts BL et al. BDNF Val66Met polymorphism and posttraumatic stress symptoms in U.S. military veterans: Protective effect of physical exercise. Psychoneuroendocrinology. 2019;100:198-202
101. 101. Hosang GM et al. Interaction between stress and the BDNF Val66Met polymorphism in depression: A systematic review and meta-analysis. BMC Medicine. 2014;12:7-7
102. 102. Liu L et al. Serotonin transporter 5-HTTLPR genotype is associated with intrusion and avoidance symptoms of DSM-5 posttraumatic stress disorder (PTSD) in Chinese earthquake survivors. Anxiety, Stress, & Coping. 2017;31(3):318-327
103. 103. Kim TY et al. Epigenetic alterations of theBDNFgene in combat-related post-traumatic stress disorder. Acta Psychiatrica Scandinavica. 2016;135(2):170-179
104. 104. Yehuda R et al. Lower methylation of glucocorticoid receptor gene promoter 1F in peripheral blood of veterans with posttraumatic stress disorder. Biological Psychiatry. 2015;77(4):356-364
105. 105. Vukojevic V et al. Epigenetic modification of the glucocorticoid receptor gene is linked to traumatic memory and post-traumatic stress disorder risk in genocide survivors. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience. 2014;34(31):10274-10284
106. 106. Hughes KC, Shin LM. Functional neuroimaging studies of post-traumatic stress disorder. Expert Review of Neurotherapeutics. 2011;11(2):275-285
107. 107. Protopopescu X et al. Differential time courses and specificity of amygdala activity in posttraumatic stress disorder subjects and normal control subjects. Biological Psychiatry. 2005;57(5):464-473
108. 108. Rauch SL et al. Exaggerated amygdala response to masked facial stimuli in posttraumatic stress disorder: A functional MRI study. Biological Psychiatry. 2000;47(9):769-776
109. 109. Shin LM et al. A functional magnetic resonance imaging study of amygdala and medial prefrontal cortex responses to overtly presented fearful faces in posttraumatic stress disorder. Archives of General Psychiatry. 2005;62(3):273
110. 110. Stevens JS et al. Disrupted amygdala-prefrontal functional connectivity in civilian women with posttraumatic stress disorder. Journal of Psychiatric Research. 2013;47(10):1469-1478
111. 111. Etkin A, Wager TD. Functional neuroimaging of anxiety: A meta-analysis of emotional processing in PTSD, social anxiety disorder, and specific phobia. The American Journal of Psychiatry. 2007;164(10):1476-1488
112. 112. Gilbertson MW et al. Smaller hippocampal volume predicts pathologic vulnerability to psychological trauma. Nature Neuroscience. 2002;5(11):1242-1247
113. 113. Admon R, Milad MR, Hendler T. A causal model of post-traumatic stress disorder: Disentangling predisposed from acquired neural abnormalities. Trends in Cognitive Sciences. 2013;17(7):337-347
114. 114. Neylan TC et al. Insomnia severity is associated with a decreased volume of the CA3/dentate gyrus hippocampal subfield. Biological Psychiatry. 2010;68(5):494-496
115. 115. Smith DH, Hicks R, Povlishock JT. Therapy development for diffuse axonal injury. Journal of Neurotrauma. 2013;30(5):307-323
116. 116. Smith DH et al. High tolerance and delayed elastic response of cultured axons to dynamic stretch injury. Journal of Neuroscience. 1999;19(11):4263-4269
117. 117. Wang Y, Mandelkow E. Tau in physiology and pathology. Nature Reviews Neuroscience. 2016;17(1):22-35
118. 118. Choe MC. The pathophysiology of concussion. Current Pain and Headache Reports. 2016;20(6):42
119. 119. Rubenstein R et al. Comparing plasma phospho tau, total tau, and phospho tau–total tau ratio as acute and chronic traumatic brain injury biomarkers. JAMA Neurology. 2017;74(9):1063-1072
120. 120. Kou Z et al. Combining biochemical and imaging markers to improve diagnosis and characterization of mild traumatic brain injury in the acute setting: Results from a pilot study. PLoS One. 2013;8(11):e80296
121. 121. Papa L et al. Serum levels of Ubiquitin C-terminal Hydrolase (UCH-L1) distinguish mild traumatic brain injury (TBI) from trauma controls and are elevated in mild and moderate TBI patients with intracranial lesions and neurosurgical intervention. The Journal of Trauma and Acute Care Surgery. 2012;72(5):1335
122. 122. Puvenna V et al. Significance of ubiquitin carboxy-terminal hydrolase L1 elevations in athletes after sub-concussive head hits. PLoS One. 2014;9(5):e96296
123. 123. Böhmer AE et al. Neuron-specific enolase, S100B, and glial fibrillary acidic protein levels as outcome predictors in patients with severe traumatic brain injury. Neurosurgery. 2011;68(6):1624-1631
124. 124. Chiaretti A et al. NGF, DCX, and NSE upregulation correlates with severity and outcome of head trauma in children. Neurology. 2009;72(7):609-616
125. 125. Ross S et al. Neuron-specific enolase as an aid to outcome prediction in head injury. British Journal of Neurosurgery. 1996;10(5):471-476
126. 126. Zhao J et al. Early expression of serum neutrophil gelatinase-associated lipocalin (NGAL) is associated with neurological severity immediately after traumatic brain injury. Journal of the Neurological Sciences. 2016;368:392-398
127. 127. Marchi N et al. Consequences of repeated blood-brain barrier disruption in football players. PLoS One. 2013;8(3):e56805
128. 128. Shlosberg D et al. Blood–brain barrier breakdown as a therapeutic target in traumatic brain injury. Nature Reviews Neurology. 2010;6(7):393-403
129. 129. Tibbling G, Link H, Öhman S. Principles of albumin and IgG analyses in neurological disorders. I. Establishment of reference values. Scandinavian Journal of Clinical and Laboratory Investigation. 1977;37(5):385-390
130. 130. Zetterberg H, Blennow K. Fluid biomarkers for mild traumatic brain injury and related conditions. Nature Reviews Neurology. 2016;12(10):563-574
131. 131. Zongo D et al. S100-B protein as a screening tool for the early assessment of minor head injury. Annals of Emergency Medicine. 2012;59(3):209-218
132. 132. Neher MD et al. Serum biomarkers for traumatic brain injury. Southern Medical Journal. 2014;107(4):248-255
133. 133. Metting Z et al. GFAP and S100B in the acute phase of mild traumatic brain injury. Neurology. 2012;78(18):1428-1433
134. 134. Pham N et al. Plasma soluble prion protein, a potential biomarker for sport-related concussions: A pilot study. PLoS One. 2015;10(2):e0117286
135. 135. Kochanek PM et al. Screening of biochemical and molecular mechanisms of secondary injury and repair in the brain after experimental blast-induced traumatic brain injury in rats. Journal of Neurotrauma. 2013;30(11):920-937
136. 136. Pham N et al. Primary blast-induced traumatic brain injury in rats leads to increased prion protein in plasma: A potential biomarker for blast-induced traumatic brain injury. Journal of Neurotrauma. 2015;32(1):58-65
137. 137. Persad A et al. Plasma PrPC and ADAM-10 as novel biomarkers for traumatic brain injury and concussion: A pilot study. Brain Injury. 2021:1-8
138. 138. Goetzl EJ et al. Neuron-derived plasma exosome proteins after remote traumatic brain injury. Journal of Neurotrauma. 2020;37(2):382-388
139. 139. Loane DJ, Byrnes KR. Role of microglia in neurotrauma. Neurotherapeutics : The Journal of the American Society for Experimental NeuroTherapeutics. 2010;7(4):366-377
140. 140. Habgood MD et al. Changes in blood-brain barrier permeability to large and small molecules following traumatic brain injury in mice. European Journal of Neuroscience. 2007;25(1):231-238
141. 141. Shitaka Y et al. Repetitive closed-skull traumatic brain injury in mice causes persistent multifocal axonal injury and microglial reactivity. Journal of Neuropathology and Experimental Neurology. 2011;70(7):551-567
142. 142. Khuman J et al. Tumor necrosis factor alpha and Fas receptor contribute to cognitive deficits independent of cell death after concussive traumatic brain injury in mice. Journal of Cerebral Blood Flow and Metabolism : Official Journal of the International Society of Cerebral Blood Flow and Metabolism. 2011;31(2):778-789
143. 143. Csuka E et al. IL-10 levels in cerebrospinal fluid and serum of patients with severe traumatic brain injury: Relationship to IL-6, TNF-α, TGF-β1 and blood–brain barrier function. Journal of Neuroimmunology. 1999;101(2):211-221
144. 144. Kossmann T et al. Intrathecal and serum interleukin-6 and the acute-phase response in patients with severe traumatic brain injuries. Shock. 1995;4(5):311-317
145. 145. Semple BD et al. Role of CCL2 (MCP-1) in traumatic brain injury (TBI): Evidence from severe TBI patients and CCL2−/− mice. Journal of Cerebral Blood Flow and Metabolism : Official Journal of the International Society of Cerebral Blood Flow and Metabolism. 2010;30(4):769-782
146. 146. Goodman JC et al. Pro-inflammatory and pro-apoptotic elements of the neuroinflammatory response are activated in traumatic brain injury. In: Acta Neurochirurgica Supplements. Vienna: Springer; 2008. pp. 437-439
147. 147. Buttram SDW et al. Multiplex assessment of cytokine and chemokine levels in cerebrospinal fluid following severe pediatric traumatic brain injury: Effects of moderate hypothermia. Journal of Neurotrauma. 2007;24(11):1707-1718
148. 148. Phillips DJ et al. Activin a release into cerebrospinal fluid in a subset of patients with severe traumatic brain injury. Journal of Neurotrauma. 2006;23(9):1283-1294
149. 149. Kumar RG et al. Acute CSF interleukin-6 trajectories after TBI: Associations with neuroinflammation, polytrauma, and outcome. Brain, Behavior, and Immunity. 2015;45:253-262
150. 150. Csajbok LZ et al. In-hospital C-reactive protein predicts outcome after aneurysmal subarachnoid haemorrhage treated by endovascular coiling. Acta Anaesthesiologica Scandinavica. 2015;59(2):255-264
151. 151. Oliver J et al. Comparison of neurocognitive testing and the measurement of marinobufagenin in mild traumatic brain injury: A preliminary report. Journal of Experimental Neuroscience. 2015;9:S27921
152. 152. DeWitt DS, Prough DS. Traumatic cerebral vascular injury: The effects of concussive brain injury on the cerebral vasculature. Journal of Neurotrauma. 2003;20(9):795-825
153. 153. Jünger EC et al. Cerebral autoregulation following minor head injury. Journal of Neurosurgery. 1997;86(3):425-432
154. 154. Xiong Y, Mahmood A, Chopp M. Animal models of traumatic brain injury. Nature Reviews. Neuroscience. 2013;14(2):128-142
155. 155. Liu C-C et al. Apolipoprotein E and Alzheimer disease: Risk, mechanisms and therapy. Nature Reviews. Neurology. 2013;9(2):106-118
156. 156. Brett BL et al. Traumatic brain injury and risk of neurodegenerative disorder. Biological Psychiatry. 2021;91(5):498-507
157. 157. Gardner RC, Yaffe K. Epidemiology of mild traumatic brain injury and neurodegenerative disease. Molecular and Cellular Neuroscience. 2015;66:75-80
158. 158. Graham NS, Sharp DJ. Understanding neurodegeneration after traumatic brain injury: From mechanisms to clinical trials in dementia. Journal of Neurology, Neurosurgery & Psychiatry. 2019;90(11):1221-1233
159. 159. Johnson VE et al. Traumatic brain injury as a trigger of neurodegeneration. Neurodegenerative Diseases. 2017:383-400
160. 160. Lawrence DW et al. The role of apolipoprotein E episilon (ɛ)-4 allele on outcome following traumatic brain injury: A systematic review. Brain Injury. 2015;29(9):1018-1031
161. 161. Yang S-T et al. Accumulation of amyloid in cognitive impairment after mild traumatic brain injury. Journal of the Neurological Sciences. 2015;349(1-2):99-104
162. 162. Hayes JP et al. BDNF genotype is associated with hippocampal volume in mild traumatic brain injury. Genes, Brain, and Behavior. 2018;17(2):107-117
163. 163. Dretsch MN et al. Brain-derived neurotropic factor polymorphisms, traumatic stress, mild traumatic brain injury, and combat exposure contribute to postdeployment traumatic stress. Brain and Behavior. 2015;6(1):e00392-e00392
164. 164. Wang Y-J et al. The association between BDNF Val66Met polymorphism and emotional symptoms after mild traumatic brain injury. BMC Medical Genetics. 2018;19(1):1-7
165. 165. Narayanan V et al. Missense mutation of brain derived neurotrophic factor (BDNF) alters neurocognitive performance in patients with mild traumatic brain injury: A longitudinal study. PLoS One. 2016;11(7):e0158838
166. 166. Michopoulos V, Norrholm SD, Jovanovic T. Diagnostic biomarkers for posttraumatic stress disorder: Promising horizons from translational neuroscience research. Biological Psychiatry. 2015;78(5):344-353
167. 167. Dean KR et al. Multi-omic biomarker identification and validation for diagnosing warzone-related post-traumatic stress disorder. Molecular Psychiatry. 2020;25(12):3337-3349
168. 168. Huang M, Risling M, Baker DG. The role of biomarkers and MEG-based imaging markers in the diagnosis of post-traumatic stress disorder and blast-induced mild traumatic brain injury. Psychoneuroendocrinology. 2016;63:398-409
169. 169. Rangaprakash D et al. Compromised hippocampus-striatum pathway as a potential imaging biomarker of mild-traumatic brain injury and posttraumatic stress disorder. Human Brain Mapping. 2017;38(6):2843-2864
170. 170. Ray R. Prediction markets and the financial “Wisdom of Crowds”. The Journal of Behavioral Finance. 2006;7(1):2-4

Written By

Jamie L. Scholl, Eric T. Graack, Michaela S. Ahrenholtz, Taylor J. Bosch and Lee A. Baugh

Submitted: December 4th, 2021 Reviewed: January 19th, 2022 Published: February 25th, 2022