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. Author manuscript; available in PMC: 2024 Apr 1.
Published in final edited form as: Shock. 2023 Jan 17;59(4):621–626. doi: 10.1097/SHK.0000000000002082

Traumatic Brain Injury Induced Inflammation and GI Motility Dysfunction

Abigail R Cannon 1,2,3, Lillian J Anderson 1,3, Kevin Galicia 1,3, Mary Grace Murray 1,2,3, Aadil S Kamran 1,3, Xiaoling Li 1,3, Richard P Gonzalez 1,2,3, Mashkoor A Choudhry 1,2,3,4
PMCID: PMC10065904  NIHMSID: NIHMS1864405  PMID: 36645886

Abstract

Background:

Traumatic Brain Injury (TBI) is a significant cause of morbidity and mortality in the United States, with an annual cost of 60 billion dollars. There is evidence suggesting that in the post-TBI period, the gastrointestinal (GI) tract plays a central role in driving organ and immune dysfunction and may be the source of increased circulating pro-inflammatory mediators. In this study, we examined systemic inflammation and bacterial dysbiosis in patients who sustained a TBI with or without poly trauma. Utilizing a mouse model of TBI, we further show how neuroinflammation following TBI is potentially linked to disruptions in gut homeostasis such as intestinal transit and inflammation.

Methods:

During a study of trauma patients performed from 9/1/18–9/1/19 at a single, level 1 trauma center TBI patients, aged 21–95, were enrolled. Patients were categorized as TBI based upon evidence of acute abnormal findings on head computed tomographic (CT) scan, which was a combination of isolated TBI and TBI with polytrauma. Blood and stool samples were collected between 24 hrs and 3 days post admission. Twelve plasma samples and ten fecal samples were used for this study. Healthy control samples were obtained from a healthy control biobank. We examined systemic inflammation and bacterial changes in patients who sustained a TBI. In addition, TBI was induced in 9–10 week old male mice, we assessed neuroinflammation, and intestine transit (motility) and bacterial changes 24 hrs post TBI.

Results:

When compared to healthy controls, TBI patients had increased systemic inflammation as evidenced by increased levels of IFN-γ and MCP-1 and a trend toward an increase of IL-6 and IL-8, p=0.0551 and p=0.0549, respectively. The anti-inflammatory cytokine, IL-4, was also decreased in TBI patients. While there was a trend of an increase in copy number of Enterobacteriaceae and a decrease in copy number of Lactobacillus in both patients and mice post TBI, these trends were not found to be significantly different. However TBI significantly increased the copy number of another potential pathogenic bacteria Bilopihlia wadsworthia in TBI patients compared to Healthy Controls. Following a moderate TBI, mice had increased expression of TNFα, IL-6, and IL-1β, CXCL1, s100a9, and Ly6G and decreased IL-10 in the brain lesion post TBI. This accompanied decreased transit and increased TNFα in the small intestine of mice following TBI.

Conclusions:

Our findings suggest that TBI increases systemic inflammation, intestinal dysfunction, and neuroinflammation. More studies are needed to confirm whether changes in intestinal motility play a role in post TBI neuroinflammation and cognitive deficit.

Keywords: Traumatic Brain Injury (TBI), Neuroinflammation, Gut Function, Gut Bacteria

Introduction

Traumatic brain injury (TBI) is a major cause of morbidity and mortality in the United States with approximately 1.7 million new cases per year. There are over 2.8 million TBI-related emergency department (ED) visits, hospitalizations, and mortalities each year, with an associated annual cost approaching $60 billion1–3. Chronic traumatic encephalopathy due to sports-related head injury and military blast injury has increased scrutiny given to TBI, and more specifically, the long-lasting sequelae of neurotrauma4. There are two phases of TBI, primary and secondary injury. Primary injury is the direct, physical damage to the brain sustained during the traumatic event. Secondary injury refers to pathophysiological changes that occur in the brain in the hours to days following the trauma that lead to a persistent state of neuroinflammation and dysregulation5. This secondary injury contributes to progressive neuronal loss/dysfunction, disability, and death6–8, and therefore, what health care providers attempt to mitigate through various interventions but often results in death and disability.

While neurotrauma results in a myriad of changes to the brain, it is not just the central nervous system (CNS) that is affected. TBI is well-known to impact peripheral systems. Gastrointestinal (GI) dysfunction is especially common following TBI, including increased intestinal epithelial barrier permeability, mucosal damage, and dysbiosis9–11. Neurotrauma studies have demonstrated significant changes to gut permeability and gut microbiota composition within a short time following injury10,12,13. These changes in the GI system result in what is referred to as “leaky gut”, during which bacteria and bacterial products, including endotoxins, may cross the leaky intestinal barrier to reach systemic circulation where they impact the inflammatory processes14,15. While the mechanism underlying gut barrier disruption following TBI remains to be determined, inflammation, gut barrier dysfunction, and bacterial dysbiosis following TBI are increasingly connected to neurodegenerative disorders and worsening the long-term morbidity and mortality in TBI patients15.

In this study, we examined systemic inflammation and bacterial dysbiosis in patients who sustained a TBI. Next, we utilized a mouse model of TBI to elucidate further how neuroinflammation following TBI is potentially linked to disruptions in gut homeostasis such as intestinal transit/motility and inflammation.

Methods

Ethics Approval for TBI Patient:

This study was reviewed and approved by the Loyola University Chicago Health Sciences Campus Institutional Review Board, IRB #210065. Written informed consent was obtained from all participants.

Study participants and sample collection:

This cross-sectional analysis included trauma patients aged 21 to 95 years from the general population who were admitted to Loyola’s trauma center from September 2018 to September 2019. Male and female trauma patients were recruited into the study after arrival to our emergency department (ED). TBI categorization was based upon CT scan results with the TBI group having evidence of head injury on CT scan. Exclusion criteria for both groups included: autoimmune disorders, pre-existing clinical infection or antibiotic use prior to injury, pre-existing clinical or historical evidence of GI illness (e.g. ulcerative colitis or Crohn’s disease) or GI infection (e.g. Clostridium difficile or CMV colitis), presence of perforated hollow viscus or peritonitis, any form of ostomy, previous transplantation, HIV positive status or other known immunodeficiency, and current immunosuppressive therapy. Consent was obtained by the patient or surrogate, depending on the patient’s GCS (Glasgow Coma Scale) as well as level of alertness and orientation to time, person, and place. Patients consented for themselves if their GCS was 14 to 15. Anything under a GCS of 13 required surrogate consent. Those initially consented by surrogate were observed daily for decisional competence and consented for continuance in the study when deemed competent.

Of the trauma patients that were consented, 12 were categorized as TBI based on CT scan. This was a combination of 7 isolated TBI’s and 5 polytrauma with TBI. We obtained 12 plasma samples and 10 fecal samples as not every patient had a bowel movement nor could a DRE produce a usable sample for this study. Of the 10 fecal samples collected 8 were isolated TBI and 2 were TBI with polytrauma. Polytrauma included sustaining injury to the face, chest, or pelvic girdle. Six patients were included in the analysis of both plasma inflammation and fecal bacterial changes. Patient demographics for plasma and fecal samples collected (i.e. gender, age, race/ethnicity, and GCS score) are summarized in Table 1 and 2, respectively.

Table 1.

Patient Demographics for Plasma Samples from Patients with Isolated TBI and TBI with Polytrauma

Isolated TBI (n=7) TBI with polytrauma (n=5)
Gender Male (n=5, 71.4%) Male (n=4, 80%)
Age > 65 years (n=5, 71.4%) > 65 years (n=2, 40%)
Race/Ethnicity
Asian n=1 (14.3%) none
Caucasian n=4 (57.14%) n=2 (40%)
Other Race n=2 (28.6%) n=3 (60%)
BAC Positive n=2 (28.6%) Positive n=3 (60%)
GCS ≤ 8 none n=3 (60%)
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*

Healthy controls were purchased from an independent biobank (Discover Life Sciences; Los Osos, CA)

Table 2.

Patient Demographics for Fecal Samples from Patients with Isolated TBI and TBI with Polytrauma

Isolated TBI (n=8) TBI with polytrauma (n=2)
Gender Male (n=5, 62.5%) Male (n=2, 100%)
Age > 65 years (n=3, 37.5%) > 65 years (n=0, 0%)
Race/Ethnicity
Asian n=1 (12.5%) None
Caucasian n=6 (75%) n=1 (50%)
Other Race n=1 (12.5%) n=1 (50%)
BAC Positive (n=2, 25%) Positive (n=1, 50%)
GCS ≤ 8 n=1 (12.5%) n=2 (100%)
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*

Healthy controls were purchased from an independent biobank (Discover Life Sciences; Los Osos, CA)

Study Design:

Blood samples were collected within 24 hours of arrival/admission and fecal samples were collected within 24 hrs or 3–5 days post-admission. Patients were consented to undergo a digital rectal exam (DRE) in the event a bowel movement did not occur during hospitalization. The study also included stool and plasma samples (individuals aged 22 to 89 years) purchased from an independent biobank (Discover Life Sciences; Los Osos, CA). These samples served as healthy controls.

Plasma sample collection and biochemical analysis:

Blood samples were drawn into EDTA coated collection tubes and transported to our laboratory at room temperature, which is approximately a five-minute walk. Blood was immediately centrifuged at 8000rpm for 10min at 4°C. Plasma supernatant was collected and frozen in the −80°C freezer in order to measure pro- and anti-inflammatory cytokine levels in circulation. At time of measurement, plasma was thawed on ice and cytokine levels in all plasma samples were determined by magnetic bead suspension array using the Bio-Plex Pro Human Cytokine 17-plex panel (Bio-Rad Laboratories, Hercules, CA, USA). Following manufacturer protocol instructions, 100 uL/ well of undiluted plasma was used and run in duplicate. The panel included the cytokines: IL-1β, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12(p70), IL-13, IL-17, G-CSF, GM-CSF, IFN-γ, MCP-1, MIP-1β, TNF-α.

Fecal sample collection and biochemical analysis:

Fecal samples were obtained by either bowel movement or DRE and stored in sterile collection cups on ice for transfer to the lab. Stool samples were stored in −80° C until analysis. Samples were aliquoted into 50 mg amounts for patient samples. Entire luminal content from mouse colon was taken and stored in −80° C until analysis. 50 mg of luminal content per animal was utilized to isolate DNA. Bacterial DNA was isolated from these samples using the QIAamp PowerFecal DNA Kit (QiagenHilden, Germany) according to manufacturer’s guidelines. The optional 5-minute incubation at 2–8°C was not used. Isolated DNA was quantified using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific). Isolated DNA was diluted to 0.7ng/uL and 6uL DNA/well was used to standardize 4.2ng DNA/well in duplicate for PCR.

Primers for bacterial community quantification were as follows:

Enterobacteriaceae- Uni515F (GTGCCAGCAGCCGCGGTAA) Ent826R (GCCTCAAGGGCACAACCTCCAAG), annealing temperature 67°C; Bilophila wadsworthia - B.wads_F (CAACGTCCCCACCATCAAGTTCTCTG) and B.wads_R (TGAATTCGCGGAAGGAGCGAGAGGTC), annealing temperature 67°C, and Lactobacillus- LabF362 (AGCAGTAGGGAATCTTCCA) and LabR677 (CACCGCTACACATGGAG), annealing temperature 56°C. 6 uL of of DNA at 0.7ng/uL was mixed with 2 uL of each forward and reverse primer (ThermoFisher) and 10 uL of iTaq Universal SYBR Green supermix (Bio-Rad) for a total reaction volume of 20 uL. Reactions were performed on a Step One Plus qPCR instrument (Applied Biosystems) and run as follows: 95°C for 3 min, 40 cycles of 95°C for 15s, followed by data collection at the annealing temperature for 1 min. This was followed by a melt-curve analysis. To interpret bacterial DNA relative quantity, Ct values from target bacteria were used for the 2^(−Ct) calculation.

Mouse model of TBI:

All experiments were performed on male C57BL/6 mice (9–10 weeks old; ~25g body weight) obtained from Charles River Laboratory (Raleigh, NC), and all animal procedures were performed in compliance with the Guide for the Care and Use of Laboratory Animals (National Institutes of Health, Bethesda, MD, US) procedures were in compliance with regulations of the Loyola University Chicago Health Sciences Division Institutional Animal Care and Use Committee, IACUC #2019031. TBI was induced via controlled cortical impact (CCI). Briefly, mice were randomly divided into two groups: Sham Injury or TBI. Mice in the TBI group were anesthetized by injecting Ketamine hydrochloride (60–80mg/kg) and Xylazine (~2.5mg/Kg) intraperitoneally. Once anesthetized, mice were shaved at the surgical site and placed in a stereotactic frame in a prone position, with anesthesia delivered via nosecone. The mice were frequently checked for adequate depth of sedation by absent response to toe-pinch. Throughout the procedure, core body temperature was monitored by a rectal thermistor probe and maintained at 36–38°C on a thermopad. A midline incision was made, the cranium exposed, and a 4mm diameter craniotomy was performed directly over the forelimb sensorimotor cortex centered at a position of 0.5 mm anterior and 3 mm lateral to Bregma using a circular surgical tool. The traumatic brain injury was delivered by a controlled cortical impact injury device (Leica Biosystems, Richmond, IL). The impactor tip struck the brain at 4.0 m/sec at a depth of 1.7 mm below the cortical surface. After impact, the scalp was closed with 5–0 monofilament nylon suture. Similarly, mice in the Sham Injury group were anesthetized, shaved at the surgical site, and placed in a stereotaxic frame. A midline incision was made, the cranium exposed, and a 4mm diameter craniotomy performed. However, mice did not receive CCI, but instead their scalp was closed with 5–0 monofilament nylon suture. Post-operatively, analgesia was administered with sustained release Buprenorphine (0.1–0.5mg/kg), providing 72 hours of pain relief. After recovery from anesthesia, mice were returned to their cages and allowed food and water ad libitum.

Measurement of Intestinal Transit:

As described previously16, one day after TBI, mice were gavaged with 0.4 ml of 22mg/ml FITC-dextran4D (Sigma-Aldrich, St. Louis, MO) in phosphate buffer saline. Three hours post gavage with FITC-dextran, mice were sacrificed. Entire luminal contents of stomach, the upper small intestinal section #1, the middle small intestine section #2, the distal small intestine section #3, and large intestine were collected. Luminal contents were weighed and suspended in PBS (weight mg X 5uL PBS ) and sonicated (XL-2000 Misonix) until the solution was homogenous. Homogenates were centrifuged at 8000rpm for 10min at 4°C, supernatants were collected, and read spectrophotometrically at 480nm excitation and 520nm emission wavelengths to determine FITC-dextran concentration and were used for analysis of intestinal transit.

Real-time PCR Gene Analysis:

Transcript levels of cytokines from the brain lesion and small intestine were measured using TaqMan Gene Expression Assay. Briefly, 25 mg of either brain or intestinal tissue was used. RNA was isolated using a Qigaen RNEasy Kit per the manufacturer’s instructions (Qiagen, Hilden, Germany). 337.5ng/20ul of RNA per well was used for reverse transcription into cDNA using a High Capacity Reverse Transcription Kit (Applied Biosystems), and real-time PCR using 3.75ng RNA was performed per manufacturer’s instructions. Primers for TNFα, IL-6, IL-1β, CXCL1, s100a9, Ly6G, and GAPDH were obtained from ThermoFisher.

Statistical Analysis:

Comparison of two groups was performed using unpaired student’s t-tests. Statistical Analysis was performed using GraphPad Prism version 8.4 for Windows (GraphPad Software, San Diego, CA). Grubbs’s outlier test (GraphPad Software, San Diego, CA) was performed in order to determine significant outliers with a confidence level of p<0.05. Significant outliers were removed from analysis. If no detectable levels were observed in the assay performed, these were also removed from analysis. A confidence level of p < 0.05 was considered statistically significant. Significance is represented throughout the manuscript as follows: * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001.

Results

We examined levels of pro- and anti-inflammatory cytokines in the circulation of patients who had suffered a TBI (Table 1) compared to Healthy Control patients. Of the 17 cytokines profiled, plasma levels of the pro-inflammatory cytokines IFN-γ and MCP-1 in TBI patients were significantly increased compared to Healthy Controls. IL-6 (p=0.0551) and IL-8 (p=0.0549) trended toward an increase following TBI, Figure 1. While the level of IL-1β was significantly decreased, no changes were noted G-CSF, MIP-1β, or TNFα. Levels of the anti-inflammatory cytokine, IL-4, was significantly reduced in TBI patients compare to Healthy Controls. Interestingly, the anti-inflammatory IL-10 trended toward an increase in TBI patient plasma, which could be a compensatory anti-inflammatory response that was simply not high enough to mitigate the systemic inflammation post TBI we observed.

Figure 1.

Figure 1.

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Cytokine levels in the plasma of patients with TBI vs plasma of Healthy Control. A. IL-6 B. IL-8 C. IL-4 D. G-CSF E. MIP-1β, F. MCP-1 G. IL-1β. H. IL-10 I. IFN-γ J. TNF-α. *p<0.05, **p<0.01, ***p<0.001 TBI vs. Healthy Control via student t-test. Values are mean ± SEM; n = 8–12 TBI. Where Healthy Control number is less than n=8, no detectable levels of cytokine were observed.

To assess intestinal bacterial changes, DNA was isolated from patient fecal samples outlined in Table 2 and followed by qPCR to detect levels of target bacteria. Firstly, we analyzed Enterobacteriaceae as it is a known family of pathogenic bacteria that can penetrate the mucus layer of intestines and express pro-inflammatory endotoxin. While there was a trend towards increased copy #’s of Enterobacteriaceae post TBI compared to Healthy Controls, this was not found to be significantly different (Figure 2A). Bilophilia wadsworthia is a sulfite-reducing and hydrogen sulfide-producing microbe17. Hydrogen sulfide can directly trigger inflammation, exert cytotoxic effects on epithelial cells, impair the gut barrier, and influence progression of neurological disorders18,19. Figure 2B shows that TBI significantly increased of Bilopihlia wadsworthia compared to Healthy Controls. Lastly, we assessed Lactobacillus, a group of beneficial bacteria known to promote intestinal health and check the growth of Enterobacteriaceae. As can be seen in Figure 2C, the copy #’s of Lactobacillus were also not found to be significantly different in the feces of TBI patients compared to that obtained from Healthy Control.

Figure 2.

Figure 2.

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Bacterial copy number in the feces of patients with TBI vs. feces of Healthy Control. A. Enterobacteriaceae B. Bilophilia wadsworthia C. Lactobacillus. Values are mean ± SEM; n = 7–10 samples. *p<0.05 TBI vs. Healthy Control via student t-test

In order to expand on the systemic inflammation and bacterial changes we observed in TBI patients, we utilized a murine model of moderate TBI to further understand the link between neuroinflammation and gut barrier dysfunction post TBI. Following a moderate TBI, mice have significantly increased expression of the pro-inflammatory cytokines TNFα, IL-6, and IL-1β, Figure 3A, B, and C, and decreased anti-inflammatory IL-10, Figure 3D, in the brain lesion post TBI. Interestingly, the neutrophil chemokine CXCL1 was also increased following TBI Figure 4A. As we saw increases in the neutrophil attractant CXCL1, we assessed expression of neutrophil markers in the brain lesion and found both s100a9 and Ly6G were significantly increased in TBI mice compared to Sham mice, Figure 4B, and C.

Figure 3.

Figure 3.

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Increased neuro pro- and anti-inflammatory cytokines 24 hours post moderate TBI. A. TNFα B. IL-6 C. IL-1β D. IL-10. Values are mean ± SEM; n = 3–4 mice per group **p<0.01, ***p<0.001, ****p<0.0001 TBI vs. Sham via student t-test.

Figure 4.

Figure 4.

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Increased neutrophil chemokines and markers in the brain lesion 24 hours post moderate TBI. A. CXCL1 B. s100a9 C. Ly6G. Values are mean ± SEM; n = 3–4 mice per group *p<0.05, **p<0.01, ****p<0.0001 TBI vs. Sham via student t-test.

GI dysfunction is one of the most prevalent co-morbidities associated with TBI. Hence, we performed a FITC-dextran transit assay to assess intestinal peristalsis. Mice were gavaged with FITC-dextran one day after TBI. Three hours later luminal contents of the stomach, small intestine sections #1, #2, and #3, and large intestine were collected and analyzed for the presence of FITC spectrophotometrically. We found a significant decrease in normal intestinal transit in TBI mice as evidenced by an accumulation of FITC-dextran in the distal part of the small intestine, section #3, Figure 5A.

Figure 5.

Figure 5.

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Intestinal dysfunction 24 hours post moderate TBI. A. Decreased intestinal transit Values are mean ± SEM; n = 6–10 mice per group **p<0.01 Sham vs TBI in small intestine #3, ***p<0.001 Sham vs TBI large intestine by student’s t-test. B. Increased pathogenic Enterobacteriaceae and decreased beneficial Lactobacillus bacteria Values are mean ± SEM; n = 3–6 mice per group. C. Increased intestinal inflammation, TNFα. Values are mean ± SEM; n = 3–6 mice per group *p<0.05 Sham vs TBI by student’s t-test.

As intestinal transit was halted in the small intestine following TBI, we assessed whether this contributed to changes in the small intestine microbiome of mice that were given a TBI. Copy #’s of the pathogenic family of Enterobacteriaceae trended toward an increase (p=0.23), while beneficial probiotic Lactobacillus copy #’s trended towards a decrease (p=0.26) in the small intestine feces TBI mice compared to Sham, Figure 5B. Finally, in Figure 5C, we saw significantly increased expression of the pro-inflammatory cytokine TNFα in the small intestine homogenates of TBI mice compared to Sham.

Discussion

Here, we have described a potential impact of TBI on systemic inflammation and GI dysfunction/microbial changes and their potential relationship to the progression of co-morbidities following initial injury. We observed elevated pro-inflammatory cytokine levels and decreased levels anti-inflammatory cytokines in the circulation of TBI patients. We saw an increase in Bilophila wadsworthia, a common pathogen reported in patients presenting with Inflammatory Bowel Disease17–19. Furthermore, our study shows an upward trend in another potentially pathogenic bacterial family, Enterobacteriaceae, and a downward trend in beneficial Lactobacillus copy numbers following TBI in both patients and in our murine model of TBI. However, the changes in Enterobacteriaceae, and Lactobacillus remain non-significant, and, thus, more studies with a large number of human fecal samples are needed to establish the significance of these bacterial changes in post TBI pathology.

In order to expand on the gut-brain axis connection post TBI, we utilized our mouse model of TBI to assess neuroinflammation and found increased neuroinflammation as measured by TNFα, IL-6, and IL-1β, CXCL1, s100a9, and Ly6G. This coincided with significantly increased expression of the pro-inflammatory cytokine TNFα in the small intestine post TBI. Further, we found intestinal transit halted in the small intestine following TBI. Gastrointestinal motility contributes to the maintenance of a healthy intestinal barrier as it clears luminal debris and, importantly prevents the proliferation of microbiota20. Impaired motility can potentially contribute to bacterial dysbiosis, which may have deleterious effects on gut barrier integrity. As pathogenic bacteria have the potential to cross the mucosal barrier, increases in bacterial growth (i.e., Bilophila wadsworthia and Enterobacteriaceae) in the feces of TBI patients could lead to increased translocation of bacteria or their products contributing to sustained inflammation and secondary injury to the brain of the injured host.

While the findings presented in this manuscript clearly show that TBI can result in GI dysfunction, more studies are needed to establish the translational impact of our findings. It is imperative that more work is needed to delineate whether these changes play a role in the long-term changes in cognition, behavior, and marked organ and immune dysfunction of TBI patients, and, therefore, has become a major focus of future studies in our laboratory. Additionally, more studies are needed to further establish an association between elevated cytokines and secondary complications associated with TBI. The majority of our patients had mild TBI, and left the hospital after 24–48 hours, which hindered the opportunity to collect samples, and made it difficult to assess changes in inflammation and bacteria over time. Two TBI patients received narcotics during admission. Narcotics are well known to affect gut motility21, and therefore could have contributed to the bacterial changes we observed. As our patient sample size was relatively small, we did not separate patients based on narcotic use. However, when gut motility was assessed in our murine model of TBI where TBI mice and Sham mice received the same post-operative analgesia, there was still significantly decreased intestinal transit in TBI mice compared to Shams. Alcohol use is also a well-known contributor to systemic inflammation and GI dysfunction22–24. Two TBI patients had a positive BAC upon admission to the hospital. Due to the relatively small sample size of this report, we were unable to stratify patients into BAC positive vs. BAC negative groups. Age is another potential factor that can contribute to poor outcome in TBI patients. Patient ages ranged from 21–95 years. Due to this wide range, it would have been extremely difficult to age match mice across this extreme, and therefore, we chose to use adult 9–10 week old mice in our study. As our studies are ongoing, we expect to communicate in the future how time, narcotic use, a positive BAC at time of TBI, and age affect these parameters as we continue to enroll more patients.

Concerns may be raised regarding the healthy control samples used in our study as they were purchased from a biobank that collects samples from across the US. We do not have complete demographic data for these samples and do not have the full knowledge of medical history, medications used during sample collection, or behaviors (e.g. alcohol, tobacco, or drug use). Furthermore, geographical location and the volunteers’ comorbidities may also impact the microbiome and other parameters in our study. Therefore, future studies will be carried under our revised protocol, which includes healthy control samples obtained from our local population (i.e. the same communities as our TBI patients). These volunteers will be screened for the same exclusion criteria as the TBI and non-TBI groups, in addition to other criteria as defined by our university’s biobank.

In summary, the continuation of this research on changes in plasma inflammation, neuroinflammation, and intestinal dysbiosis following TBI is critical as restoration of the gut microbiome could alleviate the consequential systemic inflammation we observed post TBI highlighting one possible treatment that may mitigate secondary injury following TBI25,26. By gaining a more thorough understanding of the mediators of the gut-brain axis and how they contribute to secondary injury following TBI, we have the potential to reduce damage due to secondary injury and improve patient outcomes and quality of life.

Funding:

This work is supported by National Institutes of Health (NIH) Grants T32GM008750 and T32AA013527.

Footnotes

Conflicts of Interest and Funding Sources:

The authors have no conflicts of interest to declare.

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