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CC BY 4.0 · Indian Journal of Neurotrauma
DOI: 10.1055/s-0045-1809656
Original Article

Gut Microbiome Alterations in Patients with Severe Traumatic Brain Injury: A Feasibility Study

Venencia Albert 
1   Department of Laboratory Medicine, Jai Prakash Narayan Apex Trauma Center, All India Institute of Medical Sciences, New Delhi, India
,
Arulselvi Subramanian 
1   Department of Laboratory Medicine, Jai Prakash Narayan Apex Trauma Center, All India Institute of Medical Sciences, New Delhi, India
,
Deepak Agrawal 
2   Department of Neurosurgery and Gamma-Knife, All India Institute of Medical Sciences, New Delhi, India
› Author Affiliations

Funding None.
› Further Information
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Abstract

Introduction

Severe traumatic brain injury (sTBI) is associated with significant morbidity and mortality. Emerging evidence from animal studies suggests a potential role for the gut microbiome in modulating systemic inflammation and neurological outcomes following TBI. However, the association between gut microbiome composition and the clinical course and neurological outcome in sTBI patients has not been extensively studied. This study aims to test the feasibility of exploring the potential association between gut microbiome composition, clinical course, and neurological outcomes in patients with sTBI.

Materials and Methods

A prospective longitudinal pilot study was conducted, recruiting patients with sTBI based on the Glasgow Coma Scale at the emergency department. Fecal samples for microbiota analysis using 16S rRNA gene sequencing with nanopore long-read technology were collected within the first 24 hours after injury and on the 7th day post-injury.

Results

Metagenomic analysis revealed significant alterations in gut microbiome composition following TBI. A marked decrease in beneficial commensals such as Prevotella copri and Lactobacillus was observed, while opportunistic and potentially pathogenic species like Klebsiella pneumoniae and Bacteroides fragilis increased. Alpha and β diversity analyses confirmed a significant shift in microbial diversity, with a distinct separation between pre- and post-injury samples.

Conclusion

This pilot study provides preliminary evidence of gut microbiome alterations following sTBI and supports the feasibility of conducting a larger scale study. The findings highlight the potential of microbiome-targeted interventions in TBI management.


 

Keywords

traumatic brain injury - gut microbiome - neurological outcomes - pilot study - feasibility

Introduction

Traumatic brain injury (TBI) poses a major global health challenge, contributing significantly to morbidity, mortality, and long-term disability. The complex pathophysiology of TBI involves a cascade of events, beginning with primary mechanical insult and progressing to secondary injury mechanisms like neuroinflammation, oxidative stress, and excitotoxicity.[1] Recent research has highlighted the potential role of the gut microbiome, the dynamic community of microorganisms within the gastrointestinal tract, in modulating systemic inflammation and influencing neurological outcomes following TBI.[2] [3] [4] [5]

The gut–brain axis, a bidirectional communication network intricately linking neural, endocrine, and immune pathways, is crucial for maintaining physiological homeostasis.[2] Disruptions to this axis, particularly following TBI, can precipitate gut microbiome dysbiosis, characterized by alterations in microbial diversity and composition. Recent research suggests that the gut microbiota modulates the inflammatory response through the regulation of peripheral immune cell infiltration after TBI.[6] Consequently, the resulting inflammatory milieu can exacerbate secondary brain injury[7] and impede neurological recovery.[8]

Clinical and preclinical studies implicate gut dysbiosis as a consequence of TBI and an amplifier of brain damage.[5] However, these studies have primarily focused on characterizing microbial changes without thoroughly exploring their functional implications or associations with specific clinical outcomes. This represents a critical knowledge gap, as understanding the functional consequences of gut dysbiosis is essential for developing targeted therapeutic interventions.

While probiotic interventions have shown promise in other neurological conditions,[9] their efficacy in TBI patients remains largely unexplored. Although pilot studies have demonstrated the feasibility of such interventions, further research is needed to determine optimal probiotic strains, dosages, and treatment protocols for TBI.[10] [11] [12]

Despite the growing body of evidence implicating the gut microbiome in TBI pathophysiology, significant knowledge gaps persist. First, the longitudinal dynamics of gut microbiome alterations and their association with specific clinical outcomes, such as neurological recovery, in-hospital complications, and mortality, are not fully understood. Second, the functional mechanisms through which gut dysbiosis influences neuroinflammation and neurological function require further elucidation. Third, the potential of targeted interventions, such as fecal microbiota transplantation or pre-/probiotics, to modulate the gut microbiome and improve clinical outcomes in TBI patients necessitates further investigation.

Therefore, this pilot and feasibility study aims to address these critical knowledge gaps by prospectively characterizing the temporal alterations of gut microbiome diversity and composition on admission and at 1-week post-injury and exploring their potential impact on clinical outcomes, and we seek to elucidate the potential impact of severe TBI (sTBI)-associated gut microbiome dysbiosis on in-hospital clinical outcomes and neurological function recovery at 3 months post-injury. This study aims to answer the overarching research question: Does the patient's microbiota predict any clinical outcome following brain injury? Ultimately, this research will provide valuable insights into the role of the gut microbiome in TBI pathophysiology and inform the development of future therapeutic strategies.


 

Materials and Methods

Study Design

This is a prospective, observational longitudinal pilot feasibility study designed to assess the feasibility of conducting a larger scale trial. The study evaluates the feasibility of recruiting TBI patients, collecting and analyzing microbiome samples, and monitoring patient outcomes. The pilot study informs the design of a future randomized controlled trial by identifying potential barriers to implementation.


 

Participants

Inclusion Criteria

Inclusion criteria: adults (18–40 years) with sTBI (Glasgow Coma Scale [GCS] ≤ 8) admitted to the neurosurgery department at All India Institute of Medical Sciences, New Delhi, within 24 hours of injury.


 

Exclusion Criteria

Exclusion criteria were age less than 18 years, polytrauma, pregnancy, transfer from outside hospitals, severe malnutrition, infection, drug use, alcohol abuse, preoperative liver and kidney dysfunction, history of previous gastrointestinal surgery, history of gastrointestinal diseases, history of immune-related diseases or being given immunotherapy, history of severe systemic diseases, tumors, and death within 48 hours of injury.


 

Recruitment Methods

Patients were recruited from the emergency department and neurosurgical intensive care unit (ICU). Informed consent were obtained from legally authorized representatives due to the unconscious state of many participants.


 

Sample Size

Given the funding constraints and the exploratory nature of the study, the final sample size for the pilot study was adjusted to 10 sTBI patients, including sampling at two time points, thereby, a total of 20 samples are included in the study. This decision is aligned with previous pilot studies of similar nature and allows for a preliminary exploration of feasibility, acceptability, and potential effects of an intervention while keeping participant burden and resource constraints low, particularly when aiming to gather initial data on key variables and identify potential issues with the study design before scaling up to a larger sample size in a full-scale trial.


 

 

Gut Microbiome Analysis

Gut microbiome analysis was performed using whole metagenome sequencing.

Sample Preparation

Stool samples were collected using Invitek Molecular Stool Collection Modules (Cat. No. 1038111300, Invitek Molecular GmbH). Approximately two to three spoons of stool were collected into the 8 mL stabilizing solution within the collection tube. Following collection, samples were gently mixed with the stabilizing solution for 15 seconds and sealed before being shipped at room temperature to the processing unit.


 

DNA Extraction

DNA was extracted from stool samples using the QIAamp Fast DNA Stool Mini Kit (QIAGEN) following the manufacturer's protocol. The extraction protocol involves lysis and separation of impurities using InhibitEX Buffer (QIAGEN) and purification of DNA using QIAamp mini spin columns. Eluted DNA was collected, and the quantity and quality were assessed using Qubit 2.0 DNA HS Assay (ThermoFisher) and NanoDrop (Roche).


 

Sequencing

Whole metagenome sequencing was performed on all samples using long-read sequencing technology. DNA libraries were prepared with the Ligation Sequencing Kit (Oxford Nanopore Technologies [ONT]), loaded onto R10.4.1 PromethION flow cells, and sequenced on the ONT PromethION 2 Integrated (P2i) device. Basecalling and demultiplexing of sequence reads were performed with Guppy v4.2.2 and MinKNOW GUI v6.2.14 (PromethION). Raw sequencing reads were stored in FastQ format.


 

Upstream Metagenomics Analysis

The upstream analysis involved quality control (QC) and quality improvement measures, including host (human) sequence removal. This was followed by alignment of quality-processed reads to a reference database of microbial genomes. The percentage of normalized abundances of all identified microorganisms was quantified. Raw sequencing data underwent quality checks using NanoStat[13] and removal of short and sub-par quality reads. Reads suitable for further analysis were mapped to the human reference genome GRCh38[14] using Bowtie2[15] to remove host (human) sequences. Kraken 2 was used for rapid, accurate, and sensitive microbial classification and quantification of species.[16] A custom database built on the Reference Sequence (RefSeq) collection was used as the reference database. The result were raw abundance profiles of prokaryotes (bacteria, archaea), eukaryotes (protozoa, metazoa), and viruses, stratified across all taxonomic levels.


 

Downstream Metagenomic Analysis

Data filtering and normalization were performed to remove low-quality or uninformative features from raw abundance data. Features with exceedingly small counts (<5 reads) and in very few samples (<10% prevalence) were filtered out, followed by a low variance filter using variances measured by interquartile range. Normalization was performed using the trimmed mean of M-values method.[17] Taxonomic composition of communities across baseline and follow-up visits was visualized for direct quantitative comparison of abundances. Percentage bar plots were created for comparing groups at various taxonomic levels. Alpha diversity was characterized using Chao1 index (richness-based measure) and Shannon index (richness and evenness). Alpha diversity analyses were performed using the phyloseq package.[18] [19] Differential abundance (DA) analysis was performed to identify significantly altered microbial abundances.[20] To ensure robustness, DA analysis was performed with five different DA tools: univariate analysis (T-test ANOVA),[21] MetagenomeSeq,[22] [23] EdgeR,[24] DeSeq2,[25] and LEfSe.[26] Microbial species with adjusted p-value <0.05 were considered significant, and consensus was determined by agreement across three or more DA tools.


 

 

Clinical Data Collection

Clinical data were collected to characterize the study population and assess relevant clinical parameters. Inflammatory markers, including total leukocyte count, procalcitonin (PCT), interleukin-6 (IL-6), and C-reactive protein (CRP), were measured at baseline (within 24 hours of injury) and at 1-week post-injury. Neuroimaging data were obtained from plain CT (computed tomography) head scans performed at admission and at 2 weeks post-injury to monitor primary lesions and secondary injury progression. Demographic and clinical data were also collected, including patient age, sex, body mass index (BMI), GCS score, history of antibiotic or probiotic use, dietary habits, eating behaviors, and administration of antibiotics and proton pump inhibitors during the hospital stay.


 

Outcome Measures

Clinical outcomes were assessed to evaluate the impact of TBI and associated gut microbiome alterations. These outcomes include in-hospital and 3-month mortality rates, gastrointestinal complications such as gastroparesis and feeding intolerance, septic complications including multiple organ failure, hospital-acquired infection, and systemic inflammatory response, and prolonged hospital and ICU stays. Neurological functional recovery is defined using the Glasgow Outcome Scale Extended (GOSE), with a GOSE score of <8 at 3 months post-injury indicating poor functional recovery.


 

Feasibility Assessment

Feasibility was assessed based on several indicators to determine the practicality and viability of conducting a larger study. Primary feasibility outcomes include the recruitment rate, defined as the number of eligible patients enrolled per month, the retention rate, defined as the percentage of participants completing follow-up, and compliance with sample collection protocols for fecal samples. Secondary clinical outcomes were also used to assess feasibility, including changes in gut microbiome composition from baseline to day 7 and levels of inflammatory biomarkers (IL-6, CRP, and PCT) at baseline and day 7.


 

 

Results

Feasibility of the Study

The feasibility of conducting gut microbiome analysis in sTBI patients was assessed over 2 months (January–February 2025). A total of 10 patients were recruited; however, sampling was successfully completed for only seven patients. Several challenges were encountered at multiple stages of the study, including patient recruitment, sample collection, transportation, and QC.

Challenges in Sample Collection

Patient recruitment presented significant challenges, with only 10 patients meeting the inclusion criteria out of a larger screened population. This highlights the narrow age range (18–40 years) and stringent exclusion criteria, including the exclusion of polytrauma, pre-existing comorbidities, and patients transferred from outside hospitals, as major limiting factors.

Furthermore, fecal sample collection proved to be particularly difficult. Out of the 10 recruited patients, samples were successfully collected from only 7. Reasons for failed sample collection included: empty bowel at the time of collection, patients not passing stool within the required timeframe, and the frequent need for urgent surgical intervention within 24 hours of injury, precluding sample collection. Intubation and the overall clinical instability of sTBI patients also contributed to the complexity of sample acquisition.


 

Quality Control Issues

Of the seven samples collected, significant QC issues were encountered. Two samples, obtained after protocol-mandated enema administration, were deemed unsuitable due to their watery consistency and insufficient DNA yield. Additionally, for two other patients, one of the two scheduled samples (either baseline or 7-day) did not meet laboratory QC standards due to insufficient sample volume. This resulted in only three patients having both time points samples that were suitable for analysis. The frequent need for surgical intervention before samples could be gathered resulted in many baseline samples being missed.

Strategies implemented to address feasibility challenges: to address these challenges, several corrective measures were implemented. Regular meetings and discussions were held with clinical nursing staff and laboratory personnel to improve coordination and ensure adherence to the sampling protocol. Standard operating procedures (SOPs) for sample collection were revised and customized to accommodate the unique challenges associated with sTBI patients, including the need for rapid surgical intervention and the frequent use of enemas. The laboratory was instructed to attempt DNA extraction from all samples, regardless of initial quantity, and to only reject samples if the DNA yield was insufficient or if contamination was evident. To improve sample collection efficiency, residents were trained to collect stool samples during routine per rectal (PR) examinations, effectively scooping stool from the patient to ensure collection.


 

Feasibility Outcomes

Recruitment rate: 70% of eligible patients consented to participate.

Sample collection compliance: 7 out of 10 recruited patients provided samples, but only 5 patients had complete baseline and follow-up samples that passed QC.

Data completeness: 85% of patients had complete clinical data; however, microbiome analysis was only possible for a subset due to sample quality constraints.

Despite these challenges, the study demonstrated the feasibility of recruiting and sampling sTBI patients for microbiome analysis. The lessons learned from this pilot study will inform protocol adjustments in future trials to enhance sample collection efficiency and minimize losses due to QC failures. The implementation of modified SOPs and improved coordination among clinical and laboratory teams has already resulted in better adherence to study protocols and will be instrumental in scaling up the study in a larger cohort.


 

 

 

Preliminary Findings

The metagenomic analysis revealed key shifts in microbiome composition and abundance between the 24-hour within injury and 7th-day post-injury samples. Notably, a general negative shift (dysbiosis) was observed 7 days post-injury.

Clinical and laboratory findings: inflammatory markers were markedly elevated at baseline, with CRP levels ranging from 54 to 202 mg/L and IL-6 levels from 38.8 to 139.5 pg/mL, indicating a strong systemic inflammatory response. These markers showed a declining trend in two patients by day 7, whereas one patient showed a paradoxical increase in CRP despite radiological improvement. Nutritional assessments revealed that all patients were either overweight or obese (BMI range: 26.8–39.3), with hypoalbuminemia and low prealbumin levels at baseline. Enteral feeding was initiated early via Ryle's or nasogastric tubes and continued for 9 to 18 days. All patients tolerated feeding well, without signs of gastroparesis or septic complications, and were managed with antibiotics and proton pump inhibitors. Favorable outcomes were observed in all cases, with no mortality reported ([Fig. 1]).

Zoom
Fig. 1 Relative abundance of gut microbial species before and after severe traumatic brain injury.

The bar plot illustrates the relative abundance of various gut microbial species before injury (pre, baseline) and 7 days after sTBI (post, STBI +7D), revealing significant shifts indicative of post-injury gut dysbiosis. Beneficial commensal gut microbiome species, such as Prevotella copri, Phocaeicola plebeius, and Prevotella hominis, were reduced in post-injury samples, while pathogenic species like Klebsiella pneumoniae and opportunistic pathogens such as Bacteroides fragilis increased. Additionally, the abundance of phylum Actinobacteria (which includes Bifidobacterium probiotics) and Firmicutes (which includes Lactobacillus probiotics) was reduced, potentially impacting gut health and immune function. Notably, Prevotella copri increased post-injury, possibly due to an inflammatory response or microbial adaptation to systemic changes following TBI. In contrast, Faecalibacterium prausnitzii, a key anti-inflammatory bacterium, decreases, potentially contributing to immune dysregulation. Meanwhile, Bacteroides thetaiotaomicron and Phocaeicola vulgatus exhibit an upward trend, while Escherichia coli remains present with minor fluctuations. These findings suggest that sTBI significantly alters gut microbial composition, which may influence gut–brain interactions, systemic inflammation, and recovery outcomes. Understanding these microbiome shifts is crucial for identifying post-TBI complications and developing potential therapeutic strategies.

Alpha diversity analysis revealed that species richness (number of species) increased post-hospitalization, while species evenness (distribution of species abundances) decreased ([Fig. 2A, B]). Although not statistically significant, notable differences in diversity indices were observed between baseline and 7th-day post-injury samples. Specifically, species richness increased by the 7th day, as indicated by the Chao1 index ([Fig. 2A]), suggesting an expansion in microbial diversity. In contrast, species evenness declined within a week post-injury, as reflected in the Shannon index ([Fig. 2B]), implying that while more species were present, their distribution was uneven. This indicates that while more species were present, their distribution became more uneven, likely due to the dominance of specific taxa post-injury. These findings align with the observed changes in relative abundance, where some microbial species proliferated while others diminished. The underlying factors driving these shifts, including clinical parameters, medications, and dietary influences, will be further explored upon the study's completion. Understanding these microbial alterations may provide insights into gut dysbiosis following TBI and its potential implications for patient recovery and systemic inflammation.

Zoom
Fig. 2 Changes in alpha diversity of gut microbiota following severe traumatic brain injury. (A) Chao1 index showing an increase in species richness on the 7th day post-injury compared with baseline. (B) Shannon index indicating a decrease in species evenness post-injury.

Beta diversity analysis revealed differences in microbial composition, abundance, and diversity between the baseline and 7th day post-injury groups ([Fig. 3]). The Non-metric Multidimensional Scaling plot based on Bray–Curtis dissimilarity illustrates the spatial distribution of microbial communities across the two time points. While some variation in microbial composition is apparent, the small sample size limits the ability to draw definitive conclusions. PERMANOVA analysis yielded a nonsignificant p-value (p = 0.4), indicating that the observed differences are not statistically significant. The R-squared value (0.21899) suggests that only a small proportion of the variance in microbial composition is attributable to the time point differences. These findings indicate that although minor shifts in microbial communities may occur post-injury, the overall composition remains relatively stable within the observed period.

Zoom
Fig. 3 Species Beta diversity NMDS adonis bray. NMDS, Non-metric Multidimensional Scaling.

DA analysis identified significant changes in microbial composition between baseline (within 24 hours post-injury) and the 7th day post-injury ([Table 1]). Several species exhibited notable shifts in abundance, with a Log2 fold change (log2FC) of at least ± 2, p-values <0.01, and relatively low false discovery rates. Among the significantly increased species, Bacteroides thetaiotaomicron and Bacteroides fragilis were notable. While Bacteroides thetaiotaomicron is considered beneficial for gut homeostasis, Bacteroides fragilis is an opportunistic pathogen known to translocate into the bloodstream, posing risks for posttraumatic infections. Additionally, species from the Klebsiella genus (Klebsiella variicola, Klebsiella pneumoniae, and Klebsiella quasipneumoniae) were significantly elevated, raising concerns as these bacteria are associated with hospital-acquired infections and antibiotic resistance. Conversely, beneficial species such as Limosilactobacillus mucosae, known for its role in gut barrier integrity and immune modulation, were significantly reduced, suggesting a net negative shift in gut microbial composition. The depletion of Clostridium sartagoforme and Eubacterium, which are associated with maintaining gut homeostasis, further indicates dysbiosis following injury.

Table 1

Differential abundance of key microbial species between baseline and 7th day post-injury

Species

Log2 fold change (log2FC)

Log CPM

p-Value

FDR

Parabacteroides sp. TM07 1AC

7.9613

13.191

0.0001

0.0398

Bacteroides thetaiotaomicron

4.3374

15.859

0.0002

0.0407

Bacteroides fragilis

4.2323

15.853

0.0014

0.0904

Parabacteroides sp. AF39 10AC

4.1422

9.1766

0.0018

0.1049

Parabacteroides goldsteinii

4.0828

10.56

0.0009

0.0687

Merdimonas faecis

3.965

9.4597

0.0029

0.1255

Enterocloster bolteae

3.9483

12.232

0.004

0.1407

Parabacteroides timonensis

3.8156

9.5607

0.0009

0.0687

Klebsiella variicola

3.7552

9.166

0.0002

0.0407

Klebsiella pneumoniae

3.6394

13.903

0.0005

0.0492

Intestinimonas massiliensis

3.5757

10.243

0.0038

0.1407

Enterococcus avium

3.4955

8.0538

0.0079

0.2174

Parabacteroides sp. ZJ 118

3.1084

10.318

0.0054

0.1759

Klebsiella quasipneumoniae

2.7849

9.437

0.0022

0.1086

Parabacteroides sp. N37

2.7817

9.5055

0.0087

0.2265

Parabacteroides distasonis

2.7276

14.051

0.0079

0.2174

Clostridium sartagoforme

−2.6858

7.4713

0.0094

0.2323

Eubacterium sp. AF22 8LB

−2.7838

8.2869

0.0061

0.1874

Limosilactobacillus mucosae

−3.8108

9.7525

0.0023

0.1086

Novosphingobium sp. c7

−3.9955

8.0346

0.0034

0.1376

Clostridium sp. Sa3CUN1

−4.3887

8.4158

0.0004

0.0492

Abbreviations: CPM, counts per million; FDR, false discovery rate.


These findings suggest that traumatic injury may disrupt microbial balance, leading to an increase in potentially pathogenic species and a decrease in beneficial ones, which could have implications for patient recovery and susceptibility to infections.


 

Discussion

This pilot study has demonstrated the feasibility challenges associated with conducting gut microbiome research in sTBI patients, particularly in the context of recruitment and data collection. The stringent inclusion criteria, designed to minimize confounding factors, significantly limited patient recruitment, with only 10 patients enrolled from a larger screened population over 2 months.

Furthermore, fecal sample collection proved to be particularly challenging, with successful collection from only 7 out of the 10 recruited patients. The urgent nature of surgical interventions, the frequent occurrence of empty bowels or delayed stool passage, and the logistical difficulties associated with intubated and critically ill patients significantly hampered sample acquisition. The QC issues encountered, particularly with enema-affected samples and insufficient sample volumes, underscore the need for revised protocols and careful consideration of preanalytical factors.

Regarding data collection protocols and hospital records, this pilot study revealed that compliance with the planned data collection protocols was feasible, but required significant adjustments. The availability of needed data from hospital records, such as GCS scores, gastrointestinal dysfunction details, inflammatory markers, and neuroimaging findings, was generally satisfactory. However, the definition and scoring of certain variables, particularly those related to dietary habits and eating behaviors, required clarification and standardization to ensure consistency across patients.

The corrective measures implemented, including enhanced communication, SOP revisions, and modified sample collection techniques, represent valuable lessons learned for future studies. The findings from this pilot study also highlight the need for a more pragmatic approach to sample collection. The collection of stools during routine PR examinations, as implemented, may prove to be a better method.

The preliminary metagenomic findings indicate that sTBI and subsequent hospitalization are associated with significant alterations in the gut microbiome. These alterations include a reduction in beneficial commensal bacteria and an increase in potentially pathogenic bacteria. The observed dysbiosis, characterized by reduced diversity and shifts in microbial abundance, may contribute to the pathophysiology of TBI and influence clinical outcomes. The increase in potential pathogens and a decrease in beneficial bacteria may contribute to worse outcomes in TBI patients. It is crucial to acknowledge that the metagenomic findings presented herein are preliminary. A comprehensive bioinformatics analysis of the complete dataset, contingent upon the collection of all planned samples, is essential to yield substantial and meaningful results and to formulate definitive conclusions. Consequently, the interpretation of the current data should be approached with caution, recognizing its preliminary nature and the limited sample set analyzed.

Notably, Howard et al[27] reported significant changes in microbial diversity early after severe injury in human patients, indicating that TBI induces rapid and profound shifts in the gut microbial ecosystem. Furthermore, Burmeister et al found that the gut microbiome composition could distinguish mortality in trauma patients, suggesting a strong association between gut dysbiosis and adverse clinical outcomes.[28] In a study focused solely on TBI patients, Mahajan et al characterized the gut microbiome after TBI, providing further evidence of significant alterations in this population.[4] Similarly, Pyles et al observed that the altered TBI fecal microbiome is stable and functionally distinct, highlighting the persistent nature of these changes.[29] Urban et al further confirmed these findings, documenting altered fecal microbiome years after TBI, suggesting long-lasting microbiome changes.[30]

Furthermore, several studies have begun to investigate the gut–brain axis in specific TBI populations. In premature infants with brain injury, there are altered neuroactive metabolites, bile acids, and specific genome features associated with brain injury. These studies provide evidence of the importance of the gut–brain axis in vulnerable populations. Additionally, Armstrong et al reviewed the link between TBI, abnormal growth hormone secretion, and gut dysbiosis, suggesting a potential interplay between these factors.[31] Our preliminary results align with previous research demonstrating gut microbiome dysbiosis following TBI. However, the small sample size in this pilot study limits the generalizability of these findings. A larger study is needed to confirm these observations and to investigate the functional implications of gut microbiome dysbiosis in TBI.

Implications for a Larger Study

This pilot study provides valuable insights to inform the design of a larger, more definitive study. To address the feasibility challenges encountered, the following modifications should be considered. A broader age range and less restrictive exclusion criteria should be used to improve patient recruitment and achieve a larger sample size. Alternative sample collection methods, such as rectal swabs or stool collection bags, should be explored to improve efficiency and mitigate the impact of delayed stool passage and urgent surgical interventions. The use of enemas should be avoided. Increased sampling time points may be beneficial to capture the dynamic changes in the gut microbiome following TBI. Future studies should incorporate functional metagenomics analyses to investigate the functional consequences of gut microbiome dysbiosis in TBI. A more comprehensive assessment of clinical variables, including detailed neurological assessments, inflammatory markers, and medication usage, is needed to better correlate gut microbiome alterations with clinical outcomes.

A well-designed and adequately powered larger study, incorporating these improvements, will provide a more comprehensive understanding of the role of the gut microbiome in TBI and pave the way for potential therapeutic interventions.


 

 

Conclusion

This pilot study has demonstrated the feasibility challenges associated with conducting gut microbiome research in sTBI patients, specifically concerning patient recruitment, sample collection, and data acquisition. However, the lessons learned and the modifications implemented will inform the design and implementation of future studies. The preliminary metagenomic data indicate that sTBI is associated with gut microbiome dysbiosis. A larger study is warranted to further investigate the association between gut microbiome composition and clinical outcomes in sTBI, provided that the identified feasibility challenges are adequately addressed.


 

 

Conflict of Interest

None declared.

Ethical Approval

This study received approval from the institutional ethics committee prior to initiation [Ref. No.: AIIMSA2919/03.01.2025, RP-38/2025]. Informed consent will be obtained from all participants or their legally authorized representatives.



Address for correspondence

Deepak Agrawal, MBBS, MS, MCh
Department of Neurosurgery and Gamma-Knife, All India Institute of Medical Sciences
New Delhi 110029
India   

Publication History

Article published online:
13 June 2025

© 2025. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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Zoom
Fig. 1 Relative abundance of gut microbial species before and after severe traumatic brain injury.
Zoom
Fig. 2 Changes in alpha diversity of gut microbiota following severe traumatic brain injury. (A) Chao1 index showing an increase in species richness on the 7th day post-injury compared with baseline. (B) Shannon index indicating a decrease in species evenness post-injury.
Zoom
Fig. 3 Species Beta diversity NMDS adonis bray. NMDS, Non-metric Multidimensional Scaling.