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DOI: 10.1055/s-0045-1809656
Gut Microbiome Alterations in Patients with Severe Traumatic Brain Injury: A Feasibility Study
Funding None.

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 - feasibilityEthical 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.
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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References
- 1 Freire MAM, Rocha GS, Bittencourt LO, Falcao D, Lima RR, Cavalcanti JRLP. Cellular and molecular pathophysiology of traumatic brain injury: what have we learned so far?. Biology (Basel) 2023; 12 (08) 1139
- 2 O'Riordan KJ, Moloney GM, Keane L, Clarke G, Cryan JF. The gut microbiota-immune-brain axis: therapeutic implications. Cell Rep Med 2025; 6 (03) 101982
- 3 Albert V, Kedia S, Subramanian A. A comprehensive review of the brain–gut microbiota system in traumatic brain injury: mechanisms, outcomes, and emerging interventions. Indian J Neurosurg (ahead of publication)
- 4 Mahajan C, Khurana S, Kapoor I. et al. Characteristics of gut microbiome after traumatic brain injury. J Neurosurg Anesthesiol 2023; 35 (01) 86-90
- 5 Albert V, Subramanian A, Agrawal D. Role of the gut-brain axis in severe traumatic brain injury: insights from experimental models and clinical studies. Indian J Neurosurg (ahead of publication)
- 6 You X, Niu L, Fu J. et al. Bidirectional regulation of the brain-gut-microbiota axis following traumatic brain injury. Neural Regen Res 2025; 20 (08) 2153-2168
- 7 Khatri N, Sumadhura B, Kumar S, Kaundal RK, Sharma S, Datusalia AK. The complexity of secondary cascade consequent to traumatic brain injury: pathobiology and potential treatments. Curr Neuropharmacol 2021; 19 (11) 1984-2011
- 8 Taraskina A, Ignatyeva O, Lisovaya D. et al. Effects of traumatic brain injury on the gut microbiota composition and serum amino acid profile in rats. Cells 2022; 11 (09) 1409
- 9 Ma YY, Li X, Yu JT, Wang YJ. Therapeutics for neurodegenerative diseases by targeting the gut microbiome: from bench to bedside. Transl Neurodegener 2024; 13 (01) 12
- 10 Ma Y, Liu T, Fu J. et al. Lactobacillus acidophilus exerts neuroprotective effects in mice with traumatic brain injury. J Nutr 2019; 149 (09) 1543-1552
- 11 Gu N, Yan J, Tang W. et al. Prevotella copri transplantation promotes neurorehabilitation in a mouse model of traumatic brain injury. J Neuroinflammation 2024; 21 (01) 147
- 12 Pasam T, Padhy HP, Dandekar MP. Lactobacillus helveticus improves controlled cortical impact injury-generated neurological aberrations by remodeling of gut-brain axis mediators. Neurochem Res 2024; 50 (01) 3
- 13 De Coster W, D'Hert S, Schultz DT, Cruts M, Van Broeckhoven C. NanoPack: visualizing and processing long-read sequencing data. Bioinformatics 2018; 34 (15) 2666-2669
- 14 Nurk S, Koren S, Rhie A. et al. The complete sequence of a human genome. Science 2022; 376 (6588) 44-53
- 15 Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods 2012; 9 (04) 357-359
- 16 Wood DE, Lu J, Langmead B. Improved metagenomic analysis with Kraken 2. Genome Biol 2019; 20 (01) 257
- 17 Pereira MB, Wallroth M, Jonsson V, Kristiansson E. Comparison of normalization methods for the analysis of metagenomic gene abundance data. BMC Genomics 2018; 19 (01) 274
- 18 McMurdie PJ, Holmes S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One 2013; 8 (04) e61217
- 19 McMurdie PJ, Holmes S. Shiny-phyloseq: Web application for interactive microbiome analysis with provenance tracking. Bioinformatics 2015; 31 (02) 282-283
- 20 Nearing JT, Douglas GM, Hayes MG. et al. Author Correction: Microbiome differential abundance methods produce different results across 38 datasets. Nat Commun 2022; 13 (01) 777
- 21 Calle ML. Statistical analysis of metagenomics data. Genomics Inform 2019; 17 (01) e6
- 22 Paulson JN, Olson ND, Braccia DJ. et al. metagenomeSeq: Statistical analysis for sparse high-throughput sequencing. Bioconductor. Version 1.32.0. Accessed April 15, 2025 at: https://github.com/nosson/metagenomeSeq/
- 23 Paulson JN, Stine OC, Bravo HC, Pop M. Differential abundance analysis for microbial marker-gene surveys. Nat Methods 2013; 10 (12) 1200-1202
- 24 Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 2010; 26 (01) 139-140
- 25 Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 2014; 15 (12) 550
- 26 Segata N, Izard J, Waldron L. et al. Metagenomic biomarker discovery and explanation. Genome Biol 2011; 12 (06) R60
- 27 Howard BM, Kornblith LZ, Christie SA. et al. Characterizing the gut microbiome in trauma: significant changes in microbial diversity occur early after severe injury. Trauma Surg Acute Care Open 2017; 2 (01) e000108
- 28 Burmeister DM, Johnson TR, Lai Z. et al. The gut microbiome distinguishes mortality in trauma patients upon admission to the emergency department. J Trauma Acute Care Surg 2020; 88 (05) 579-587
- 29 Pyles RB, Miller AL, Urban RJ. et al. The altered TBI fecal microbiome is stable and functionally distinct. Front Mol Neurosci 2024; 17: 1341808
- 30 Urban RJ, Pyles RB, Stewart CJ. et al. Altered fecal microbiome years after traumatic brain injury. J Neurotrauma 2020; 37 (08) 1037-1051
- 31 Armstrong PA, Venugopal N, Wright TJ. et al. Traumatic brain injury, abnormal growth hormone secretion, and gut dysbiosis. Best Pract Res Clin Endocrinol Metab 2023; 37 (06) 101841