Biomarkers in the Brain Oxygen Optimization in Severe Traumatic Brain Injury Trial (BioBOOST)
Conditions: TBI (Traumatic Brain Injury)
Sponsor: University of Pennsylvania

 Protocol Version 1 
 
Version Date:  June 30, 2020 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Study Protocol 
 
 
Biomarkers in the Brain Oxygen Optimization in Severe Traumatic Brain Injury Trial (Bio-
BOOST). 
A multicenter, observational study of the effect of derangements in brain physiologic parameters 
on brain injury biomarker levels in patients with severe traumatic brain injury. 
 
 
Principal Investigators: 
Ramon Diaz-Arrastia, MD, PhD and Frederick Korley, MD, PhD 
 
 
Supported by: 
The Department of Defense, U.S. Army Medical Research and      
Materiel Command (USAMRMC) 
 
ClinicalTrials.gov ID: 
Not Yet Assigned 
 
Version: 
 
 
Version 1 
 
IRB approval: 
 
February 25, 2020 
 
 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 
2 
 
Table of Contents 
PRECIS 
4 
1 
6 
1.1 Primary Objective 
6 
1.2 Secondary Objectives 
6 
2 BACKGROUND 
7 
2.1 Rationale 
7 
2.2 Supporting Data 
9 
3 STUDY DESIGN 
12 
4 SELECTION AND ENROLLMENT OF SUBJECTS 
13 
4.1  Inclusion Criteria 
13 
4.2  Exclusion Criteria 
13 
4.3 
14 
4.3.1  Identification and screening process 
14 
4.3.2. 
14 
4.3.3. 
14 
4.3.3. 
14 
5 
14 
5.1  Biospecimen Collection 
14 
5.2  Biospecimen Processing and Storage 
16 
5.3  Biomarker Assays 
16 
6 
17 
6.1 
17 
6.2 
17 
7 
18 
7.1 Analytic Plan for Primary Objective 
18 
7.2 Analytic Plan for Secondary Objectives 
18 
7.3 Sample Size Justification 
19 
8   DATA MANAGEMENT AND QUALITY ASSURANCE 
20 
9 HUMAN SUBJECT PROTECTION 
22 
9.1 Informed Consent Process 
22 
9.2 Withdrawal from Participation 
22 
9.3  Confidentiality 
22 

 
 
 
 
 
 
 
3 
 
10 RESOURCE SHARING 
22 
11 PUBLICATION OF RESEARCH FINDINGS 
24 
12 REFERENCES 
25 
 
 
 
 

 
 
 
 
 
 
 
4 
 
PRECIS 
 
Study Title:  Biomarkers in the Brain Oxygen Optimization in Severe Traumatic Brain Injury Trial 
(Bio-BOOST) 
 
Objectives 
Bio-BOOST is a multicenter, observational study of the effect of derangements in brain 
physiologic parameters on brain injury biomarker levels in patients with severe traumatic brain 
injury. 
 
Primary Objective: To quantify the effect of total brain tissue hypoxia exposure on brain injury 
using biofluid-based biomarkers of brain injury. 
 
Secondary Objectives:  
● To determine the effect of total cerebral hypoperfusion exposure (defined as the depth 
and duration of cerebral perfusion pressure<60 mmHg within 48 hours of randomization, 
quantified using the AUC methodology) on peak levels of GFAP, UCH-L1, Total Tau and 
NFL. 
● To determine whether treatment informed by PbtO2 monitoring results in a decrease in 
blood and CSF levels of GFAP, UCH-L1, Total Tau and NFL.  
● To determine whether the initial CSF and blood levels of brain injury biomarkers (GFAP, 
UCH-L1, Total Tau and NFL) are associated with unfavorable functional outcome as 
measured by the Glasgow Outcome Scale Extended (GOSE) 6 months after severe TBI. 
● To determine whether the rate of increase in brain injury biomarker levels during the first 
24 hours after randomization are associated with 6-month functional outcome as 
measured by the GOSE.  
● To determine the time-point at which GFAP, UCH-L1, Total Tau and NFL levels provide 
the best discriminative ability for functional outcome as measured by the GOSE. 
● To create a biorepository of longitudinal serum, plasma, CSF, mRNA and DNA samples 
of severe TBI patients for validating novel brain injury biomarkers.  
 
Study Procedures 
This study is a prospective observational, multi-center study of subjects enrolled in the Brain 
Oxygen Optimization in Severe Traumatic Brain Injury—Phase 3 (BOOST-3) trial. BOOST-3 is a 
multicenter, randomized, blinded-endpoint, comparative effectiveness study of goal-directed 
critical care based upon monitoring of brain tissue oxygen and intracranial pressure versus 
monitoring of intracranial pressure alone in patients with severe traumatic brain injury.  
We will obtain an initial set of biospecimens (serum, plasma, CSF, DNA and RNA) shortly after 
randomization into BOOST-3 and within 24 hours of injury. Subsequent biospecimens will be 
obtained every 8 hours for the first 24 hours post-enrollment. This will allow the characterization 
of acute changes in biomarker levels. On study days 2 through 5, biospecimens will be obtained 
twice a day to allow characterization of sub-acute changes in biomarker levels, without 
overburdening study teams or taking too much blood from individual subjects. On study days 7 
and 14 and at 6-months post-enrollment, one set of biospecimen will be obtained, preferably in 
the morning. Biospecimens collected at each time point will consist of 6 ml of whole blood for 
serum extraction, 6 ml of whole blood for plasma extraction, 2.5 ml of whole blood for mRNA 
extraction (a total of 14.5 ml [one tablespoon] of blood) and 5 ml of cerebrospinal fluid (CSF). 
Serum and plasma will be apportioned into aliquots and stored in a -80ºC freezer at enrolling 
sites within 2 hours of collection. During the separation of plasma samples from whole blood, 
the buffy coat suspension (a concentrated leukocyte suspension) will be extracted and stored 

 
 
 
 
 
 
 
5 
 
for DNA analysis to avoid wasting this valuable biospecimens. mRNA and CSF samples will 
also be collected, processed and stored. Periodically (once or twice a year), all biospecimens 
stored at enrolling sites will be shipped on dry ice to a biorepository at the University of 
Pittsburgh. Biospecimens will be collected, processed, stored and shipped according to the 
NINDS common data elements protocol for TBI biospecimen collection.1 
 
Study Duration 
Participants will be enrolled over a period of 2.5 years; however, each participant will remain in 
the study for 6 months. 
 
Sample Size and Population 
We plan to enroll a maximum of 300 male and female subjects among multiple clinical sites.  
 
 
 

 
 
 
 
 
 
 
6 
 
1 STUDY OBJECTIVES  
 
To study the effect of derangements in brain physiologic parameters on brain injury biomarker 
levels in patients with severe traumatic brain injury. 
1.1 Primary Objective 
To quantify the effect of total brain tissue hypoxia exposure on brain injury using biofluid-based 
biomarkers of brain injury. 
1.2 Secondary Objectives 
● 
To determine the effect of total cerebral hypoperfusion exposure on peak levels of 
GFAP, UCH-L1, Total Tau and NFL. 
● 
To determine whether treatment informed by PbtO2 monitoring results in a decrease 
in blood and CSF levels of GFAP, UCH-L1, Total Tau and NFL.  
● 
To determine whether the initial CSF and blood levels of brain injury biomarkers 
(GFAP, UCH-L1, Total Tau and NFL) are associated with unfavorable functional 
outcome as measured by the Glasgow Outcome Scale Extended (GOSE) 6 months 
after severe TBI. 
● 
To determine whether the rate of increase in brain injury biomarker levels during the 
first 24 hours after randomization are associated with 6-month functional outcome 
measured by the GOSE. 
● 
To determine the time-point at which GFAP, UCH-L1, Total Tau and NFL levels 
provide the best discriminative ability for functional outcome measured by the GOSE. 
● 
To create a biorepository of longitudinal serum, plasma, CSF, mRNA and DNA 
samples of severe TBI patients for validating novel brain injury biomarkers. 
 
 
 

 
 
 
 
 
 
 
7 
 
2 BACKGROUND 
2.1 Rationale 
The societal burden of traumatic brain injury (TBI). TBI is a major cause of death and 
disability in modern industrialized societies. The most recent estimates from the Centers for 
Disease Control and Prevention (CDC) indicate that in the United States 3.5 million individuals 
experience a TBI annually, of which 300,000 are hospitalized and discharged alive, and 52,000 
died as a consequence of the TBI.1;2 Among the 300,000 hospitalized survivors, over 40% 
experience long-term disability,3 which limits their activities of daily living, such as grooming, 
eating, or walking. Because TBI often affects young people who survive for many years with 
serious functional limitations, the prevalence of TBI related disability is high, and it is estimated 
that 3.3 million people, or 1% of the US population, is living with long-term disabilities from TBI.4 
The annual cost to society resulting from TBI has been estimated to range from $83 billion5 to 
$244 billion6 (in 2014 dollars). The magnitude of this problem has led to numerous clinical trials 
aimed at improving survival or functional outcome after TBI, yet no effective therapies have 
been identified to date.  
This proposal focuses on the most severely injured victims of TBI, those with prolonged 
unresponsiveness and extensive intracranial pathology, such as contusions, hemorrhages, 
edema, and diffuse axonal injury.  Since surveillance databases do not typically include data 
elements commonly used to assess severity,7 epidemiologic studies specific to severe TBI are 
sparse. One detailed studied in Aquitaine, France, which included reviews of hospital records of 
all patients admitted to one of 5 trauma centers over one calendar year concluded that the 
incidence of severe TBI was 17.3/100,000 population,8 and the incidence of traumatic coma 
(severe TBI which resulted in coma lasting longer than 24 hours) was 8.5/100,000.9 
Extrapolating the latter number to the US population, a reasonable estimate of the annual 
number of cases of traumatic coma in the US is 27,000. These patients experience high 
mortality and morbidity rates, and less than 20% make a good recovery.9 They require 
sophisticated care in intensive care units (ICUs), and the burden to society in direct and indirect 
costs is very high. Average lifetime costs per TBI survivor in the US has been estimated to be 
$533,000 in 2014 dollars,6 but since this estimate is not specific to those with prolonged 
traumatic coma, the per patient costs for patients who are the target of this proposed study is 
likely to be significantly higher. Thus, the potential payoff to society from improved care of these 
most severely injured TBI patients is potentially very high.  
TBI is a heterogeneous condition that lacks adequate tools to assist in management. TBI 
is a heterogeneous disorder that is usually classified by physical examination (the Glasgow 
Coma Scale, GCS), mechanism of injury (blunt versus penetrating) and neuroimaging.10 The 
primary diagnostic tool for evaluating TBI is the brain CT scan. While CT is often life-saving by 
identifying patients who need emergent neurosurgical interventions, it is insensitive to 
pathologies that account for a substantial fraction of disability after severe TBI, such as diffuse 
axonal injury (DAI), diffuse vascular injury, and cytotoxic edema.11  Further, neuroimaging 
requires transfer from the neurological ICU to the scanning suite, which is cumbersome and 
potentially dangerous for critically ill patients, and is thus poorly suited to evaluate hour-by-hour 
changes in neurological status.  Accordingly, novel strategies are needed to improve the 
management of critically ill patients with TBI.   
Management of severe TBI currently relies on invasive neuromonitoring. Invasive 
neuromonitoring, using devices implanted into brain parenchyma to measure intracranial 
pressure (ICP) and brain tissue oxygen (PbtO2), is widely used in neurological ICUs to identify 
risk factors for secondary neural injury while they are still preventable.  Invasive 
neuromonitoring is the focus of the recently funded BOOST-3 (Brain Oxygen Optimization in 

 
 
 
 
 
 
 
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Severe TBI—Phase 3) Study (NIH/NINDS U01 NS099046).12  This study offers a unique 
opportunity to accelerate our understanding of the pathophysiology of severe TBI and promote 
the development of effective interventions.  BOOST-3 will be carried out through the SIREN 
(Strategies to Innovate Emergency Clinical Care Trials Network).  This study will enroll 1094 
participants with severe TBI from 2019 – 2023, across approximately 45 clinical sites in the US 
and Canada  and represents a $32.5 M federal investment. The primary hypothesis of BOOST-
3 is that a treatment based on PbtO2 and ICP monitoring improves neurologic outcome 
measured by the Glasgow Outcome Scale-Extended (GOS-E) 6 months after injury compared 
to treatment based on ICP monitoring only.   
Although invasive neuromonitoring is the clinical standard of care for severe TBI, it has several 
important limitations which need to be addressed by carefully assessing the relationship 
between intracranial hypertension, brain tissue hypoxia, and molecular biomarkers of neural 
injury.  First, although it is clear that high ICP and low PbtO2 are associated with poor outcomes 
after TBI, the thresholds for ICP and PbtO2 beyond which brain cellular death occurs remain 
controversial, and empirical evidence of cellular death, assessed by measuring brain injury 
biomarkers, is critically needed.  Second, PbtO2 is measured within a small area (7.1 – 15 mm2) 
of brain tissue (usually in area not visibly injured)13;14 and may not accurately represent global 
risk for ischemia.  Brain injury biomarkers provide important data on this issue, as they reflect 
the global burden of brain injury. Third, invasive neuromonitoring is justifiably used only in 
patients who are in coma (GCS < 8) in whom the neurologic exam cannot be reliably followed.  
However, secondary neural injury also occurs in patients with milder injuries, and since the 
neurological evaluation, based on the GCS, has limited sensitivity and dynamic range, 
noninvasive tools to measure secondary neural injury in patients who do not require intracranial 
monitors are desperately needed.  Measuring molecular biomarkers serially is an attractive 
strategy for identifying secondary harmful events which may guide changes in therapy.15  
Finally, there are no available tools for monitoring individual patient responses to novel 
treatment strategies, hindering the development of novel therapies. In summary, there is an 
unmet clinical need for brain injury biomarkers to complement the information obtained from 
neuroimaging, invasive neuromonitoring, and other clinical assessments to optimally inform the 
management of patients with TBI.  
Capitalizing on the infrastructure and the rich study population for BOOST-3, we propose 
conducting an ancillary biomarker study, Bio-BOOST. Bio-BOOST will profile longitudinal 
changes in well-validated molecular biomarkers measured in blood and cerebrospinal fluid 
(CSF) to identify molecular signatures that classify severe TBI with improved precision. BOOST-
3 will study severe TBI only; therefore, Bio-BOOST will fill an important gap in the field, since 
ongoing biomarker collections efforts through the Transforming Research and Clinical 
Knowledge in TBI (TRACK-TBI) and TBI Endpoints Development (TED) efforts are primarily 
focused on mild TBI.      
Biomarkers provide a minimally invasive approach for diagnosing and monitoring TBI. 
Blood and cerebrospinal fluid (CSF) levels of structural protein components of brain cells that 
are released in the aftermath of brain injury are a promising adjunct for detecting and monitoring 
secondary brain injury, including in the neurological ICU setting.15-22 The proposed study will 
examine the diagnostic and prognostic value of four TBI biomarkers which have been widely 
studied in severe15 as well as mild TBI23: Glial Fibrillary Acidic Protein (GFAP), Ubiquitin C-
terminal hydrolase 1 (UCH-L1), total Tau, and Neurofilament light chain (NF-L).  While we 
believe these are currently the most promising biomarkers for TBI, which justifies their inclusion 
in this proposal, we are convinced that other promising biomarkers will be discovered over the 
next several years.  Thus, an important goal of Bio-BOOST, in addition to measuring the four 

 
 
 
 
 
 
 
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biomarkers listed here, is to create a Biofluids Bank of well-characterized samples that can be 
used in validation studies of future biomarkers of TBI.    
GFAP is an intermediate filament protein that is responsible for maintaining the mechanical 
strength of the cytoskeleton of astrocytes in the central nervous system (CNS).24 GFAP 
released into the CSF post-TBI may be absorbed into peripheral circulation through the sagittal 
sinus. GFAP also gains access to the circulatory system via the glymphatic system.25 Although 
GFAP is predominantly expressed by CNS astrocytes, it can also be expressed in lesser 
quantities by non-myelinated Schwann cells of the peripheral nervous system26 and in glial cells 
found in the gut.27;28 As a consequence of these non-CNS sites of expression, extracranial 
traumatic injuries do cause elevations in blood GFAP levels.29;30 Nonetheless, numerous studies 
have demonstrated that GFAP values obtained on the day of injury are capable of discriminating 
TBI subjects with intracranial hemorrhage from those without.30-35 Furthermore, higher GFAP 
levels are associated with poor functional recovery.35-38   
UCH-L1 is an enzyme that is highly abundant in neuronal cells and accounts for 1-2% of total 
brain protein. It plays a key role in the removal of excessive, oxidized, or misfolded proteins.39 
Similar to GFAP, elevated blood concentrations of UCH-L1 occur following TBI in proportion to 
TBI severity. However, blood UCH-L1 levels peak shortly after injury and decline to near 
baseline levels within 24 hours of injury, whereas GFAP levels peak within 20 hours of injury 
and remain significantly elevated for approximately 72 hours.40;41  
NF-L is an intermediate filament protein abundantly expressed in the long myelinated 
subcortical axons. It is the smallest and most abundant of the three major neurofilament 
subunits (NF-light chain, NF-medium chain, NF-heavy chain) and consequently the most likely 
to be found in circulation after brain injury.42 NF-L has been found to be elevated in the 
cerebrospinal fluid (CSF) of boxers after a bout;43 however until recently measurement of NF-L 
in circulation has been limited by the analytical sensitivity of existing immunoassays.44 The 
single molecule array technology (Simoa HD-1 Analyzer from Quanterix) is capable of 
measuring NF-L with higher analytical sensitivity than existing immunoassays.45 Serum NF-L 
measured by Simoa correlates with CSF NF-L with a correlation coefficient of 0.89.46 Using this 
assay, a small study of American football players (n=20) reported elevated NF-L levels in 
starters compared to non-starters.47 Additionally in another small study, severe TBI patients 
(n=72) had higher NF-L levels than healthy controls (n=35).48  A third study demonstrated that 
serum and CSF NF-L levels are associated with functional recovery.16 NF-L levels remain 
elevated in CSF up to 19 months after severe TBI.49  
Tau proteins are microtubule associated proteins that are found predominantly in neurons and 
play an important role in the assembly of tubulin monomers into microtubules that are important 
in maintaining the cytoskeleton of axons.50 Elevated blood levels of Total tau protein have been 
reported in concussed professional hockey players.51 Furthermore, total tau levels were 
reported to be higher in TBI patients with intracranial hemorrhage on head CT, compared to 
those without intracranial hemorrhage on head CT.   
2.2 Supporting Data 
Use of blood biomarkers in the management of severe TBI in the neuroICU. There are 
limited data on the role of longitudinal measurements of brain injury biomarkers in monitoring 
secondary brain injury. In a cohort of 67 severe TBI patients who were subjected to hypothermia 
and had daily serum GFAP measurements during the first 5 days of injury, GFAP levels 
decreased gradually but increased when rewarming was started on day 4 (Figure 1)36 This 
finding suggests that serial GFAP levels may be useful for monitoring secondary brain injury.  
Furthermore, in a cohort of predominantly severe TBI patients18 (n=250, 70% severe Figure 2), 
subjects with progression in the size of traumatic intracranial lesions found on head CT were 

 
 
 
 
 
 
 
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likely to have a secondary increase in serum levels of S100B (a biomarker of astrocytic injury). 
In this proposal we have selected GFAP as the biomarker of astrocytic injury since S100B lacks 
brain specificity.52   
 
 
Figure 1: GFAP values decreased from days 
1-3 and increased on day 4 when rewarming 
was started 
Figure 2: A secondary peak in serum 
S100B levels occurred in TBI subjects 
with progression of intracranial lesions.  
 
Ultrasensitive immunoassays can be multiplexed to detect GFAP, UCHL-1, NF-L, and Tau 
in blood from TBI patients.  GFAP, UCH-L1, total Tau and NF-L been widely studied in severe 
as well as mild TBI, and currently represent the most promising biomarkers for TBI.  Since each 
biomarker is expressed in different cells or cell regions (GFAP in astrocytes, UCHL-1 in 
neuronal cell bodies, Tau in dendrites and axon terminals, NF-L in axons),23;52 it is likely that 
each provides complementary information about primary and secondary neural injury.  
Additionally, there are differences in the kinetics of release and clearance of each of these 
biomarkers, further supporting the need to obtain multiple biomarker measurements to fully 
assess TBI.  These considerations have led to the development of multiplex assays, which allow 
simultaneous assay of GFAP, UCH-L1, total Tau, and NF-L from small volumes of biological 
fluids.  For the Bio-BOOST study, we propose to use the Neurology 4PLEX A developed by 
Quanterix (Lexington, MA) as it is more cost-effective than running the four assays 
independently and minimizes the consumption of valuable biofluids.   
We have experience using the Neurology 4-PLEX A in samples from humans with TBI.  We 
measured serum levels of the four biomarkers in stored blood samples collected from subjects 
enrolled in the Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot 
(TRACK-TBI Pilot) study (n=107).53 The TRACK-TBI Pilot was a multicenter prospective 
observational study conducted at three Level I trauma centers in the U.S.53 GFAP, UCH-L1, 
Total Tau and NF-L were measured in blood samples collected from consenting subjects within 
24 hours of injury, using the Neurology 4-PLEX A (Quanterix).   
The correlation matrix of all four biomarkers is presented in Figure 3.  Among the four 
biomarkers studied, the strongest correlation was between NF-L and UCH-L1 and the weakest 
correlation was between GFAP and total Tau. In order to assess how each biomarker yielded 
useful information about TBI, we compared biomarker levels from TRACK-TBI patients with 
normal head CTs with those from patients whose head CT showed trauma-related 
abnormalities.  Serum levels of all four biomarkers were higher in subjects with abnormal head 
CT than those with normal head CT (Figure 4). The discriminative ability of GFAP (AUCGFAP) for 
distinguishing between subjects with and without abnormal head CT was 0.88 (95% CI: 0.81 – 
0.95). AUCGFAP was not statistically significantly different from the AUCUCH-L1 (0.86 [95% CI: 0.79 
 

 
 
 
 
 
 
 
11 
 
– 0.93], p=0.62) or the AUCNF-L (0.84 [95% CI: 0.77 – 0.92], p=0.44); however it was higher than 
the AUCTau (0.77 [95% CI: 0.67 – 0.86], p=0.04). For each biomarker studied, there was a 
statistically significant linear association between biomarker value and probability of having an 
abnormal head CT. Higher biomarker values were associated with a higher probability of having 
an abnormal head CT.  
Pre-clinical studies indicate that GFAP and NF-L may be useful as pharmacodynamic 
biomarkers of neuroprotective therapies. To date, the majority of the literature on TBI 
biomarkers has focused on the diagnostic and prognostic value of these biomarkers. 
Development of novel therapies for TBI will also require validated pharmacodynamic 
biomarkers.  However, little is known on how TBI therapeutics modify blood levels of brain injury 
biomarkers. Our collaborators recently reported that in swine subjected to TBI and hemorrhagic 
shock only and to TBI, hemorrhagic shock and polytrauma, high dose valproic acid (VPA) 
treatment is safe, decreases brain lesion size and results in faster neurologic recovery when 
compared to resuscitation with normal saline alone. We subsequently conducted a post-hoc 
analysis of blood samples stored from these 
pigs to: 1) examine longitudinal changes in 
serum GFAP and NF-L levels post-TBI; 2) 
elucidate the effect of polytrauma on blood 
levels of GFAP and NF-L; 3) examine the 
treatment effect of VPA on serum levels of 
GFAP and NF-L.   We studied a total of 15 
Yorkshire Swine who were subjected to: 
controlled cortical impact (CCI) TBI + 
hemorrhagic shock + polytrauma and treated 
with normal saline (n=5); CCI TBI + hemorrhagic shock + polytrauma and treated with VPA 
(n=5); and CCI TBI + hemorrhagic shock only and treated with VPA (n=5). Blood samples were 
collected at baseline (prior to injury) and at 2, 4, 8, 24, 72 and 240 hours after injury. 
Neurocognitive testing was performed daily and consisted of complex integration of various long 
term memory processing and recall, integration of spatial memory, prioritization, and processing 
of color vision. Time to normalization of behavior was determined based on performance on 
neurocognitive testing. T2-weighted MRIs were completed under anesthesia on day 3 to 
determine lesion size.  Serum GFAP and NF-L were measured in duplicates by blinded 
technicians from Quanterix using a digital immunoassay based on a single molecule array 
technology (Simoa).  
 
  

 
 
 
 
 
 
 
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Table 1: The Effects of Valproic Acid Treatment on Biomarker Levels: median biomarker 
values and their corresponding interquartile ranges in TBI + polytrauma swine models  
Time   
NF-L  
GFAP  
 
Saline   
VPA   
p-value  Saline  
VPA  
p-value  
Baseline  
 10.6 (9.0-12.9)  
   4.6 (3.8-5.2)  
<0.01  
 10.1 (6.6-16.7)   
   5.4 (3.5-10.2)  
0.17  
2 hours  
 28.4 (18.3-31.2)  
 14.7 (11.6-17.6)  
 0.03  
252.0 (126.2-810.1)  129.4 (75.7-286.3)  0.17  
4 hours  
 15.2 (14.3-18.8)  
 11.0 (9.2-13.8)  
<0.01  
152.1 (137.0-303.3)  
 78.4 (58.4-224.7)  0.25  
8 hours  
 22.6 (17.2-31.1)  
 15.8 (14.1-16.1)  
<0.01  
207.9 (165.9-470.1)  125.0 (52.6-288.8)  0.17  
1 day  
153.0 (133.2-208.7)  101.2 (80.9-129.3)   0.02  
586.7 (292.2-1657.4)    79.7 (27.8-102.8)   0.02  
3 days  
270.2 (190.9-568.3)  169.7 (75.1-272.6)   0.17  
 83.1 (34.6-639.9)   
   6.5 (2.7-31.7)  
0.03  
10 days  
143.4 (121.5-444.5)  114.8 (48.9-162.5)   0.22  
    8.7 (4.0-12.1)   
   2.9 (.4-15.6)   
0.33  
  
We found that TBI + polytrauma swine treated with 
VPA had GFAP values pre-injury, 2, 4 and 8 hours 
post-injury that were similar to those treated with 
normal saline, however, median GFAP values at 1 
and 3 days were significantly lower in the VPA 
group than in the normal saline group (see Figure 
5A and 5B and Table 1). Each set of curves in 
Figure 5 represents a different animal.  GFAP 
values in both groups returned to pre-injury levels 
at 10 days post-injury.  Similarly, compared to 
swine treated with normal saline, swine treated with 
VPA had lower NF-L values at all time points, with 
the exception of at 3 and 10 days when the 
difference in NF-L between the two groups was not 
significantly different (Figure 5C and 1D and Table 
1).  Compared to GFAP values obtained at other 
time points, GFAP values obtained at 24 hours 
post-injury and the peak GFAP values (which are 
the same in most but not all cases) have the 
strongest correlation with time to normalization of 
behavior and lesion size detected by MRI (Table 2). Relative to peak GFAP values, the area 
under the biomarker concentration versus time curve during the first 10 days (AUC0-10days) was 
weakly correlated with lesion size and behavioral outcome. Similarly, NF-L values obtained at 
24 hours post-injury and peak NF-L had the strongest correlation with time to normalization of 
behavior and lesion size. Irrespective of time point NF-L outperformed GFAP with regards to 
correlation with both lesion size and normalization of behavior.  These findings support the 
potential of these proteins as pharmacodynamic biomarkers of neuroprotective therapies.  
3 STUDY DESIGN 
Bio-BOOST is a prospective observational study that will collect biospecimen during a 6-month 
period of observation, from subjects enrolled in the BOOST-3 trial.  
4 SELECTION AND ENROLLMENT OF SUBJECTS 
 

 
 
 
 
 
 
 
13 
 
4.1  Inclusion Criteria 
Criteria 
Rationale 
Metric 
Enrolled in BOOST-3 
This is an ancillary study to the BOOST-
3 trial 
Randomization to a 
BOOST-3 study 
arm. 
BOOST-3 participant is 
enrolled at a Bio-BOOST site 
Subjects can only be enrolled at BOOST-
3 sites that have been approved to enroll 
in Bio-BOOST 
Bio-BOOST site 
activation letter.  
Able to obtain initial blood 
sample within 24 hours of 
injury 
Time between injury and blood draw 
influences blood levels of some 
biomarkers 
Study coordinators 
assessment 
Provide proxy informed 
consent 
Informed consent is required prior to 
enrollment in Bio-BOOST 
Signed informed 
consent document 
  
  
4.2  Exclusion Criteria 
Criteria 
Rationale 
Metric 
Profoundly anemic 
Subjects who are profoundly anemic 
require blood transfusion. 
Hemoglobin < 8 
mg/dl 
Age less than 18 years 
These subjects will constitute a small 
subset of the parent BOOST-3  trial and 
therefore we may not be sufficiently 
powered to make scientifically sound 
inferences.  
Age less than 18 
years 
 
 
 

 
 
 
 
 
 
 
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4.3 Study Enrollment Procedures 
 
4.3.1  Identification and screening process   
 
Subjects will be recruited from BOOST-3 participants enrolled at a Bio-BOOST site. Each site 
will have a system for identification and early notification of potential participants who qualify for 
this ancillary study. The early notification system will result in timely arrival of the study 
coordinator or other trained study personnel, who will evaluate participant eligibility. Once 
notified, study personnel will review the potential participant’s information and screen the patient 
according to the inclusion and exclusion criteria. 
 
4.3.2. Recruitment and informed consent 
 
This protocol and the informed consent document and any subsequent modifications will be 
reviewed and approved by the Central IRB and the Department of Defense’s Human Research 
Protection Office (HRPO). A signed consent form will be obtained for every subject. Since 
subjects in this trial cannot consent for themselves, a LAR, or person with power of attorney, 
must sign the consent form. The consent form will describe the purpose of the study, the 
procedures to be followed, and the risks and benefits of participation. Every attempt will be 
made to contact the subject’s family as soon as possible after the subject’s admission, and in 
accordance with the individual hospital’s protocol. To the extent possible, consent discussions 
should be carried out in a private setting without distraction.  No coercion will be applied.  The 
LAR and other family members will be provided a verbal description of this ancillary study and 
all the items described in the consent form will be reviewed and explained.  The LAR will be 
given an opportunity to read the informed consent document, ask and have answered any 
questions they may have about the study.  
4.3.3. Consent/assent and Other Informational Documents Provided to participants 
A copy of the consent form will be given to the LAR, and this fact will be documented in the 
subject’s record. 
4.3.3. Consent Procedures and Documentation 
Consent is obtained by either the clinical site PI or by individuals to whom the clinical site PI has 
delegated authority to obtain informed consent. The delegation of authority is documented and 
maintained in WebDCUTM. As with most clinical trial responsibilities delegated by the clinical site 
PI, it is his/her responsibility to ensure that the delegation is made only to those individuals who 
are qualified to undertake the delegated tasks, and that there is adherence to all applicable 
regulatory requirements and Good Clinical Practices (GCP) Guidelines. Additionally, it is the 
investigator’s responsibility to ensure that the subject’s legally authorized representative (LAR) 
has been given an adequate explanation of the purpose, methods, risks, potential benefits and 
subject responsibilities of the study.  
  
5 BIOSPECIMEN 
5.1  Biospecimen Collection 
 
The initial set of biospecimens (serum, plasma, CSF, DNA and RNA) will be obtained as soon 
as feasible after randomization to a BOOST-3 study arm, but no later than 24 hours from injury. 
Given the logistical challenges of timely identification of an LAR, we will obtain the initial set of 
biospecimen as soon as it is logistically feasible; however, we will only utilize biospecimens for 

 
 
 
 
 
 
 
15 
 
research purposes after informed consent has been obtained. For subjects in whom the initial 
set of biospecimens is obtained before informed consent, the study team will have up to 24 
hours after blood draw to obtain informed consent. If informed consent cannot be obtained, 
biospecimens will be discarded and will not be utilized in Bio-BOOST. Once informed consent is 
obtained, subsequent biospecimens will be obtained every 8 hours (+/- 1 hour) for the first 24 
hours post-enrollment. This will allow the characterization of acute changes in biomarker levels. 
Our preliminary data from pig experiments (Figure 5 and Table 2) suggests that peak GFAP and 
NF-L values have the strongest correlation with neurological outcome post-TBI, compared to 
GFAP and NF-L values obtained at other time points. On study days 2 through 5, biospecimens 
will be obtained every 12 hours (+/- 2 hours) to allow characterization of sub-acute changes in 
biomarker levels, while minimizing the amount of blood collected from individual subjects. On 
study days 7 (+/-1 day), 14 (+/- 1 day) and at 6 months (+/- 30 days) post-enrollment, a set of 
biospecimen will be obtained. These samples will also allow the characterization of subacute 
and long-term changes in biomarker levels. On study Days 7 and 14 samples will be obtained 
only if the subject remains hospitalized during those days. In addition, during days 2 – 5, a one-
time additional set of biospecimens will be obtained 2 hours after the start of a sustained 
hypoxic event in subjects randomized to PbtO2 guided treatment. A sustained hypoxic event is 
defined as a period of brain tissue hypoxia (PbtO2 < 20 mmHg) that lasts 30 minutes or greater. 
In subjects randomized to ICP guided treatment only, a one-time additional set of biospecimens 
will be obtained 2 hours after the start of a sustained cerebral hypoperfusion event. A sustained 
cerebral hypoperfusion event is defined as a period of CPP<55mmHg that lasts 30 minutes or 
greater.  
It has been suggested that brain injury biomarkers are transported to the blood via the 
glymphatic system, and sleep deprivation manipulates glymphatic activity.19 Accordingly, it is 
possible that biomarker values are affected by circadian rhythm. For this reason, on days 2 
through 5, biospecimens will be collected at 8 am (+/- 2 hours) and 8 pm (+/- 2 hours). On days 
7, and 14 after injury, biospecimens will be obtained at 8 am local time if feasible. The 6-month 
sample will be drawn in conjunction with their follow-up visit. If the 6-month visit for the parent 
BOOST-3 study is conducted remotely, then no 6-month blood sample will be collected. Table 3 
presents a tabulation of the sequence of biospecimen collection.    
Biospecimens collected at each time point will consist of 6 ml of whole blood for serum 
extraction, 6 ml of whole blood for plasma extraction, 2.5 ml of whole blood for RNA extraction, 
collected in a PaxGENE tube (a total of 14.5 ml [one tablespoon] of blood) and 5 ml of 
cerebrospinal fluid (CSF). Since subjects are unlikely to have an EVD after the first week post-
injury, CSF samples will be collected only for as long as the EVD is in place. During the 
separation of plasma samples from whole blood, the buffy coat suspension (a concentrated 
leukocyte suspension) will be extracted and stored for DNA analysis. This will be done each 
time plasma is extracted from whole blood, in order to increase the DNA yield.   
Research coordinators participating in Bio-BOOST will participate in a training session 
performed by the biorepository staff at the University of Pittsburgh. This session will occur via a 
webinar (or site visit depending on the availability of funds) and will teach appropriate blood 
draw technique and storage techniques.  
Table 3: Sequence of biospecimen collection  
  
Day 1  
Days 2 - 5  
Day 7  
Day 14  
6 month  
Frequency  ASAP after 
randomization 
and 16 and 24 
Every 12 hours and 
once post-sustained 
ischemic event  
Once  
Once  
Once  

 
 
 
 
 
 
 
16 
 
hours post-
injury  
Timing  
See above 
Q8am and Q8pm (+/- 
2 hours) and once 
post-sustained 
ischemic event  
Q8 am  
Q8am  
During 
follow-up 
visit  
Specimen 
Type  
Serum, 
Plasma,  
CSF, DNA, 
RNA  
Serum, Plasma, CSF, 
DNA, RNA  
Serum,  
Plasma, 
CSF,  
DNA, RNA  
Serum, 
Plasma, 
DNA, RNA  
Serum, 
Plasma, 
DNA, RNA  
 
Timing of Sample Collection.   
Day 1 is defined as the remainder of the calendar day after randomization.  The first set of Day 
1 samples should be collected at the time of enrollment into Bio-BOOST (and no later than 24 
hours post-injury).  The second sample should be collected 16 hours after injury, and the 3rd 
sample collected 24 hours after injury. 
We require that at least one sample should be obtained within 24 hours of injury.  
For Days 2 - 5, the timing of blood collection should switch to a twice daily schedule, generally 8 
AM and 8 PM.  If sample #3 (24 hours after injury) is collected between 4 PM and 4 AM, sample 
#4 should be collected at 8 AM.  If sample #3 is collected between 4 AM and 4 PM, sample #4 
should be collected at 8 PM.  Thus, the time between sample #3 and #4 will be variable and 
could be as short as 4 hours and as long as 16 hours.  Time of sample collection will be 
documented in Case Report Forms.   
While this introduces some variability into the scientific analysis, the excessive burden on 
research staff of maintaining a blood sample collection clock tied to the highly variable time of 
injury carries excessive risk of protocol deviations, which will impact the scientific integrity of the 
analysis to an even greater degree.      
 
5.2  Biospecimen Processing and Storage 
Whole blood and CSF samples will be centrifuged, aliquoted and stored in a -70 or 80 degree 
Celsius freezer within 2 hours of phlebotomy. They will then be shipped periodically (once or 
twice a year) from Bio-BOOST sites to a Biorepository housed at the University of Pittsburgh for 
long-term storage. This biorepository stores biospecimens collected in other ongoing TBI 
studies such as the Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) study. 
Specimen collection and storage kits will be shipped from the biorepository to study sites.    
See Bio-BOOST manual of procedures for detailed instructions on sample collection, 
processing and storage.  
5.3 Biomarker Assays 
Serum/plasma and CSF samples will be analysed for simultaneous measurement of GFAP, 
UCH-L1, tau, and NF-L. These procedures will be carried out in Dr. Diaz-Arrastia’s laboratory at 
the University of Pennsylvania, by a research scientist blinded to the clinical and physiologic 
data. There will be no difference in the distribution of samples by BOOST-3 treatment group. 
Other novel brain injury biomarkers will be assayed when they become available. 

 
 
 
 
 
 
 
17 
 
Blood samples collected in the study may be used for both TBI research and the study of other 
medical conditions.  
6 BOOST-3 DATA 
6.1 Demographic and Clinical Data 
Bio-BOOST will utilize data collected in the BOOST-3 trial. This data includes: demographic 
data and clinical data such as injury characteristics, vital signs, head CT findings, laboratory 
data and data on physiologic parameters such as intracranial pressure (ICP), partial pressure of 
brain tissue oxygen (PbtO2), mean arterial pressure (MAP), and cerebral perfusion pressure 
(CPP), among others.  
6.2  Outcome Data 
Bio-BOOST will also utilize outcome assessment data collected from BOOST-3 participants at 6 
months after injury (180 Days ± 30 days). Trained study personnel who are blinded to the 
treatment arm will administer the outcome assessments, which will include the measures listed 
below. The battery includes measures of functional status (GOSE), cognition, and emotional 
health.  The 6-month follow-up interview will be done in person whenever possible.  It may be 
done by telephone or video conference with participants where an in-person interview is not 
possible. 
Table 4.  Outcome Assessments 
Functional Status 
Formal Measures of Cognition 
Emotional Health Measures 
● 
Glasgow Outcome Scale-
Extended (GOSE) 
● 
Structured Interview 
● 
Rey Auditory Verbal Learning Test 
● 
Trail Making Test Part A+B 
● 
WAIS IV Processing Speed Index 
● 
Rivermead Post-Concussion 
Symptom Questionnaire 
● 
Brief Symptom Inventory 18 
● 
Satisfaction with Life Scale 
For explanations, citations, and expected testing durations of each component of the battery please refer to the BOOST-3 
study protocol. 
 
 

 
 
 
 
 
 
 
18 
 
7 STATISTICAL ANALYSIS PLAN        
7.1 Analytic Plan for Primary Objective  
Our primary objective is to quantify the effect of total brain tissue hypoxia exposure on brain 
injury using fluid-based biomarkers of brain injury.   
Hypothesis 1:  We hypothesize that brain tissue hypoxia is associated with higher peak levels 
of biomarkers of astrocytic (GFAP) and axonal (UCH-L1, total Tau and NF-L) injury.  This 
hypothesis will be tested via linear regression model, with peak biomarker level as the response 
variable and hypoxia exposure as the predictor of interest.  Hypoxia exposure will be defined as 
the depth and duration of PbtO2 < 20 mmHg during the first 48 hours of injury, quantified using 
AUC methodology.  Model assumptions of normality and constant variance will be assessed.  If 
the validity of the model assumptions is questioned, even after appropriate transformation of the 
response variable, nonparametric methods may be considered.  As an exploratory analysis 
related to this objective, alternative definitions of hypoxia (including PbtO2 < 15 mmHg and 
PbtO2 < 10 mmHg) will also be considered.    
Additional analyses will be detailed in the Statistical Analysis Plan.     
7.3 Sample Size Justification  
The primary analysis will evaluate the effect of total brain tissue hypoxia exposure on brain 
injury biomarker levels.  Because the primary analysis considers each of the blood-based 
biomarkers independently, a conservative Bonferroni correction was assumed in order to 
maintain the overall family-wise error rate at 0.05.  We assume the standard deviation of the 
hypoxia exposure is 291 hour x mmHg,12 as observed in BOOST-2.  The power of the planned 
linear regression model thus depends on the assumed slope under the alternative hypothesis 
and the standard deviation of the model residuals.  The relevant variables do not currently exist 
in the same data set, so there is little information on which to base these assumptions.  Instead, 
the power of the regression model is shown in Figure 6 for varying scenarios.  
  
Figure 6.  Power estimates 
based on different scenarios for 
slope   
Figure 7 provides a visual representation, using simulated data, of the scenario where the slope 
is 0.004 with a residual standard deviation of 6.       

 
 
 
 
 
 
 
19 
 
 
Figure 7.  Simulation of 
relationship between GFAP and 
hypoxia exposure, based on slope 
of 0.004 and standard deviation of 
residual 6.  
 
8   DATA MANAGEMENT AND QUALITY ASSURANCE 
Data management will be handled by the BOOST-3 DCC, which is housed in the Data 
Coordination Unit (DCU) of the Department of Public Health Sciences at the Medical University 
of South Carolina. All study activities will be conducted in coordination with the study co-PIs, the 
hubs/spokes, and the CCC and DCC, and will use an electronic data acquisition method where 
all clinical data on enrolled subjects will be entered by site personnel. The latest version of each 
CRF will be available as a PDF file in the study database for use as worksheets and source 
documents by study personnel. 
The study data will be managed by the DCC using the WebDCUTM system. This user-friendly 
web-based clinical trial management system, developed by the DCC, will be used for regulatory 
document management, data entry, data validation, project progress monitoring, subject 
tracking, user customizable report generation and secure data transfer.  Upon entry of CRFs 
into the study database, quality control procedures will be applied at each stage of data 
handling in order to ensure compliance with GCP guidelines, integrity of the study data and 
document processing system reliability.   
 
 
 
 

 
 
 
 
 
 
 
20 
 
9 HUMAN SUBJECT PROTECTION 
9.1 Informed Consent Process 
Written informed consent will be obtained from legally authorized representatives. See section 
4.3.2. 
9.2 Withdrawal from Participation 
Participation in Bio-BOOST is voluntary. Participants or LARs may refuse to participate in the 
study at any time. Withdrawal from the study will not result in any penalty. If a participant 
withdraws from the study, they may request that any unused sample be destroyed. After the 
study is completed, it will not be possible to remove samples because they may no longer be 
identified with the participant. 
9.3  Confidentiality 
To protect against risks related to loss of confidentiality, clinical information will be kept coded in 
a secure database (WebDCU). Records collected will be confidential, unless required to be 
disclosed to oversight bodies, funders, regulators, or by state or federal law. Subjects will not be 
personally identified in any publications resulting from this project.  Numerous safeguards are 
maintained at all levels of the trial, including standard data management procedures at the 
DCC. 
10 RESOURCE SHARING 
Bio-BOOST will create a highly phenotyped biorepository of longitudinal serum, plasma, CSF, 
RNA and DNA samples from severe traumatic brain injury (TBI) patients. These samples will 
serve as a national resource for validating the diagnostic and prognostic accuracy of novel brain 
injury biomarkers. Investigators across the country will be invited to submit meritorious scientific 
proposals for the use of these samples. The use of these samples will be restricted to rigorous 
clinical validation of biomarkers that have already demonstrated diagnostic/prognostic value in 
preliminary investigations.  
The primary results of this study will be disseminated by publication in the peer reviewed 
medical literature.  In accordance with the Department of Defense’s Public Access Policy, the 
investigators will submit an electronic version of their final, peer-reviewed manuscripts (directly 
or through the publisher) to the National Library of Medicine’s PubMed Central, no later than 12 
months after the official date of publication.  
The study will be registered with http://www.clinicaltrials.gov, and results of Bio-BOOST will be 
reported there within a year of trial completion.  Submission of results to http://www.clinical 
trials.gov will be performed consistent with the requirements for applicable clinical trials per 
FDAAA 801 requirements.  
All manuscripts, abstracts and press releases using the study data must acknowledge BOOST-
3/SIREN investigators and the Department of Defense as the study sponsor with the relevant 
grant numbers. 
 
 
 
 
12 PUBLICATION OF RESEARCH FINDINGS 

 
 
 
 
 
 
 
21 
 
Publication of the results of this trial will be governed by the policies and procedures developed 
by the Executive Committee consistent with the SIREN publication policy. Any presentation, 
abstract, or manuscript will be made available for review by the Executive Committee prior to 
submission for publication.  
 
  
 
 
 

 
 
 
 
 
 
 
22 
 
12 REFERENCES 
 
(1) Coronado VG, McGuire LC, Sarmiento K et al. Trends in Traumatic Brain Injury in the U.S. 
and the public health response: 1995-2009. J Safety Res 2012;43:299-307.  
(2) Taylor CA, Bell JM, Breiding MJ, Xu L. Traumatic brain injury-related Emergency 
Department visits, Hospitalizations, and Deaths--United States, 2007 and 2013. MMWR 
Surveill Summ 2017;66 (No. 9):118.  
(3) Selassie AW, Zaloshnja E, Langlois JA, Miller T, Jones P, Steiner C. Incidence of long-term 
disability following traumatic brain injury hospitalization, United States, 2003. J Head 
Trauma Rehabil 2008;23:123-131.  
(4) Zaloshnja E, Miller T, Langlois JA, Selassie AW. Prevalence of long-term disability from 
traumatic brain injury in the civilian population of the United States, 2005. J Head Trauma 
Rehabil 2008;23:394400.  
(5) Finkelstein E, Corso PS, Miller TR. The incidence and economic burden of injuries in the 
United States. Oxford, New York: Oxford University Press, 2006.  
(6) Faul M, Wald MM, Rutland-Brown W, Sullivent EE, Sattin RW. Using a cost-benefit analysis 
to estimate outcomes of a clinical treatment guideline: testing the Brain Trauma Foundation 
guidelines for the treatment of severe traumatic brain injury. J Trauma 2007;63:1271-1278.  
(7) Peeters W, van den Brande R, Polinder S et al. Epidemiology of traumatic brain injury in 
Europe. Acta Neurochir (Wien ) 2015;157:1683-1696.  
(8) Masson F, Thicoipe M, Aye P et al. Epidemiology of severe brain injuries: a prospective 
populationbased study. J Trauma 2001;51:481-489.  
(9) Masson F, Thicoipe M, Mokni T, Aye P, Erny P, Dabadie P. Epidemiology of traumatic 
comas: a prospective population-based study. Brain Inj 2003;17:279-293.  
(10) Hawryluk GW, Manley GT. Classification of traumatic brain injury: past, present, and 
future. Handb Clin Neurol 2015;127:15-21.  
(11) Amyot F, Arciniegas DB, Brazaitis MP et al. A Review of the Effectiveness of 
Neuroimaging Modalities for the Detection of Traumatic Brain Injury. J Neurotrauma 
2015;32:1693-1721.  
(12) Okonkwo DO, Shutter LA, Moore C et al. Brain Oxygen Optimization in Severe Traumatic 
Brain Injury Phase-II: A Phase II Randomized Trial. Crit Care Med 2017;45:1907-1914.  
(13) Lang EW, Mulvey JM, Mudaliar Y, Dorsch NW. Direct cerebral oxygenation monitoring--a 
systematic review of recent publications. Neurosurg Rev 2007;30:99-106.  
(14) De Georgia MA. Brain Tissue Oxygen Monitoring in Neurocritical Care. J Intensive Care 
Med 2015;30:473-483.  
(15) Thelin EP, Zeiler FA, Ercole A et al. Serial Sampling of Serum Protein Biomarkers for 
Monitoring Human Traumatic Brain Injury Dynamics: A Systematic Review. Front Neurol 
2017;8:300.  
(16) Al NF, Thelin E, Nystrom H et al. Comparative Assessment of the Prognostic Value of 
Biomarkers in Traumatic Brain Injury Reveals an Independent Role for Serum Levels of 
Neurofilament Light. PLoS One 2015;10:e0132177.  
(17) Thelin EP, Johannesson L, Nelson D, Bellander BM. S100B is an important outcome 
predictor in traumatic brain injury. J Neurotrauma 2013;30:519-528.  
(18) Thelin EP, Nelson DW, Bellander BM. Secondary peaks of S100B in serum relate to 
subsequent radiological pathology in traumatic brain injury. Neurocrit Care 2014;20:217-
229.  
(19) Ercole A, Thelin EP, Holst A, Bellander BM, Nelson DW. Kinetic modelling of serum S100b 
after traumatic brain injury. BMC Neurol 2016;16:93.  
(20) Thelin EP, Jeppsson E, Frostell A et al. Utility of neuron-specific enolase in traumatic brain 
injury; relations to S100B levels, outcome, and extracranial injury severity. Crit Care 
2016;20:285.  

 
 
 
 
 
 
 
23 
 
(21) Thelin EP, Nelson DW, Bellander BM. A review of the clinical utility of serum S100B protein 
levels in the assessment of traumatic brain injury. Acta Neurochir (Wien ) 2017;159:209-
225.  
(22) Bellander BM, Olafsson IH, Ghatan PH et al. Secondary insults following traumatic brain 
injury enhance complement activation in the human brain and release of the tissue damage 
marker S100B. Acta Neurochir (Wien ) 2011;153:90-100.  
(23) Bogoslovsky T, Gill J, Jeromin A, Davis C, Diaz-Arrastia R. Fluid Biomarkers of Traumatic 
Brain Injury and Intended Context of Use. Diagnostics (Basel) 2016;6.  
(24) Hol EM, Pekny M. Glial fibrillary acidic protein (GFAP) and the astrocyte intermediate 
filament system in diseases of the central nervous system. Curr Opin Cell Biol 2015;32:121-
130.  
(25) Plog BA, Dashnaw ML, Hitomi E et al. Biomarkers of traumatic injury are transported from 
brain to blood via the glymphatic system. J Neurosci 2015;35:518-526.  
(26) Mokuno K, Kamholz J, Behrman T et al. Neuronal modulation of Schwann cell glial fibrillary 
acidic protein (GFAP). J Neurosci Res 1989;23:396-405.  
(27) Laranjeira C, Sandgren K, Kessaris N et al. Glial cells in the mouse enteric nervous system 
can undergo neurogenesis in response to injury. J Clin Invest 2011;121:3412-3424.  
(28) Gulbransen BD, Sharkey KA. Novel functional roles for enteric glia in the gastrointestinal 
tract. Nat Rev Gastroenterol Hepatol 2012;9:625-632.  
(29) Pelinka LE, Kroepfl A, Schmidhammer R et al. Glial fibrillary acidic protein in serum after 
traumatic brain injury and multiple trauma. J Trauma 2004;57:1006-1012.  
(30) Papa L, Silvestri S, Brophy GM et al. GFAP out-performs S100beta in detecting traumatic 
intracranial lesions on computed tomography in trauma patients with mild traumatic brain 
injury and those with extracranial lesions. J Neurotrauma 2014;31:1815-1822.  
(31) Diaz-Arrastia R, Wang KK, Papa L et al. Acute biomarkers of traumatic brain injury: 
relationship between plasma levels of ubiquitin C-terminal hydrolase-L1 and glial fibrillary 
acidic protein. J Neurotrauma 2014;31:19-25.  
(32) Papa L, Lewis LM, Falk JL et al. Elevated levels of serum glial fibrillary acidic protein 
breakdown products in mild and moderate traumatic brain injury are associated with 
intracranial lesions and neurosurgical intervention. Ann Emerg Med 2012;59:471-483.  
(33) Papa L, Mittal MK, Ramirez J et al. In Children and Youth with Mild and Moderate 
Traumatic Brain Injury, Glial Fibrillary Acidic Protein Out-Performs S100beta in Detecting 
Traumatic Intracranial Lesions on Computed Tomography. J Neurotrauma 2016;33:58-64.  
(34) Mondello S, Papa L, Buki A et al. Neuronal and glial markers are differently associated 
with computed tomography findings and outcome in patients with severe traumatic brain 
injury: a case control study. Crit Care 2011;15:R156.  
(35) Okonkwo DO, Yue JK, Puccio AM et al. GFAP-BDP as an Acute Diagnostic Marker in 
Traumatic Brain Injury: Results from the prospective TRACK-TBI Study. J Neurotrauma 
2013;30:1490-1497.  
(36) Lei J, Gao G, Feng J et al. Glial fibrillary acidic protein as a biomarker in severe traumatic 
brain injury patients: a prospective cohort study. Crit Care 2015;19:362.  
(37) Takala RS, Posti JP, Runtti H et al. Glial Fibrillary Acidic Protein and Ubiquitin C-Terminal 
HydrolaseL1 as Outcome Predictors in Traumatic Brain Injury. World Neurosurg 2016;87:8-
20.  
(38) Metting Z, Wilczak N, Rodiger LA, Schaaf JM, van der Naalt J. GFAP and S100B in the 
acute phase of mild traumatic brain injury. Neurology 2012;78:1428-1433.  
(39) Yokobori S, Hosein K, Burks S, Sharma I, Gajavelli S, Bullock R. Biomarkers for the clinical 
differential diagnosis in traumatic brain injury--a systematic review. CNS Neurosci Ther 
2013;19:556565.  
(40) Welch RD, Ellis M, Lewis LM et al. Modeling the Kinetics of Serum Glial Fibrillary Acidic 
Protein,  

 
 
 
 
 
 
 
24 
 
Ubiquitin Carboxyl-Terminal Hydrolase-L1, and S100B Concentrations in Patients with Traumatic 
Brain Injury. J Neurotrauma 2017;34:1957-1971.  
(41) Papa L, Brophy GM, Welch RD et al. Time Course and Diagnostic Accuracy of Glial and 
Neuronal Blood Biomarkers GFAP and UCH-L1 in a Large Cohort of Trauma Patients With 
and Without Mild Traumatic Brain Injury. JAMA Neurol 2016;73:551-560.  
(42) Lee MK, Xu Z, Wong PC, Cleveland DW. Neurofilaments are obligate heteropolymers in 
vivo. J Cell Biol 1993;122:1337-1350.  
(43) Zetterberg H, Hietala MA, Jonsson M et al. Neurochemical aftermath of amateur boxing. 
Arch Neurol 2006;63:1277-1280.  
(44) Rohrer JD, Woollacott IO, Dick KM et al. Serum neurofilament light chain protein is a 
measure of disease intensity in frontotemporal dementia. Neurology 2016;87:1329-1336.  
(45) Kuhle J, Barro C, Andreasson U et al. Comparison of three analytical platforms for 
quantification 
of 
the 
neurofilament 
light 
chain 
in 
blood 
samples: 
ELISA, 
electrochemiluminescence immunoassay and Simoa. Clin Chem Lab Med 2016;54:1655-
1661.  
(46) Gisslen M, Price RW, Andreasson U et al. Plasma Concentration of the Neurofilament 
Light Protein (NFL) is a Biomarker of CNS Injury in HIV Infection: A Cross-Sectional Study. 
EBioMedicine 2016;3:135-140.  
(47) Oliver JM, Jones MT, Kirk KM et al. Serum Neurofilament Light in American Football 
Athletes over the Course of a Season. J Neurotrauma 2016;33:1784-1789.  
(48) Shahim P, Gren M, Liman V et al. Serum neurofilament light protein predicts clinical 
outcome in traumatic brain injury. Sci Rep 2016;6:36791.  
(49) Bagnato S, Grimaldi LME, Di RG et al. Prolonged Cerebrospinal Fluid Neurofilament Light 
Chain Increase in Patients with Post-Traumatic Disorders of Consciousness. J 
Neurotrauma 2017;34:24752479.  
(50) Goedert M. Tau protein and the neurofibrillary pathology of Alzheimer's disease. Trends 
Neurosci 1993;16:460-465.  
(51) Shahim P, Tegner Y, Wilson DH et al. Blood biomarkers for brain injury in cocussed 
professional ice hockey players. JAMA Neurol. In press.  
(52) Zetterberg H, Smith DH, Blennow K. Biomarkers of mild traumatic brain injury in 
cerebrospinal fluid and blood. Nat Rev Neurol 2013;9:201-210.  
(53) Yue JK, Vassar MJ, Lingsma HF et al. Transforming research and clinical knowledge in 
traumatic brain injury pilot: multicenter implementation of the common data elements for 
traumatic brain injury. J Neurotrauma 2013;30:1831-1844.  
(54) Steyerberg EW, Mushkudiani N, Perel P et al. Predicting outcome after traumatic brain 
injury: development and international validation of prognostic scores based on admission 
characteristics. PLoS Med 2008;5:e165.  
(55) Henningsen A. Estimating censored regression models in R using the censReg package. 
https://cran rproject org/web/packages/censReg/vignettes/censReg pdf [serial online] 2018; 
Accessed January 17, 2018.