The gut microbiota and metabolite profiles are altered in patients with spinal cord injury
-
Quality control
- Retracted paper
- Contamination issues suspected
- Batch effect issues suspected
- Uncontrolled confounding suspected
- Results are suspect (various reasons)
- Tags applied
Background Metabolites secreted by the gut microbiota may play an essential role in microbiota–gut–central nervous system crosstalk. In this study, we explored the changes occurring in the gut microbiota and their metabolites in patients with spinal cord injury (SCI) and analyzed the correlations among them.
Methods The structure and composition of the gut microbiota derived from fecal samples collected from patients with SCI (n=11) and matched control individuals (n=10) were evaluated using 16S rRNA gene sequencing. Additionally, an untargeted metabolomics approach was used to compare the serum metabolite profles of both groups. Meanwhile, the association among serum metabolites, the gut microbiota, and clinical parameters (including injury duration and neurological grade) was also analyzed. Finally, metabolites with the potential for use in the treatment of SCI were identifed based on the diferential metabolite abundance analysis.
Results The composition of the gut microbiota was diferent between patients with SCI and healthy controls. At the genus level, compared with the control group, the abundance of UBA1819, Anaerostignum, Eggerthella, and Enterococcus was signifcantly increased in the SCI group, whereas that of Faecalibacterium, Blautia, Escherichia–Shigella, Agathobacter, Collinsella, Dorea, Ruminococcus, Fusicatenibacter, and Eubacterium was decreased. Forty-one named metabolites displayed signifcant diferential abundance between SCI patients and healthy controls, including 18 that were upregulated and 23 that were downregulated. Correlation analysis further indicated that the variation in gut microbiota abundance was associated with changes in serum metabolite levels, suggesting that gut dysbiosis is an important cause of metabolic disorders in SCI. Finally, gut dysbiosis and serum metabolite dysregulation was found to be associated with injury duration and severity of motor dysfunction after SCI.
Conclusions We present a comprehensive landscape of the gut microbiota and metabolite profles in patients with SCI and provide evidence that their interaction plays a role in the pathogenesis of SCI. Furthermore, our fndings suggested that uridine, hypoxanthine, PC(18:2/0:0), and kojic acid may be important therapeutic targets for the treatment of this condition.
Experiment 1
Subjects
- Location of subjects
- China
- Host species Species from which microbiome was sampled. Contact us to have more species added.
- Homo sapiens
- Group 0 name Corresponds to the control (unexposed) group for case-control studies
- typically healthy control group
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- spinal cord injury patient
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- Spinal cord injury (SCI) is an insult to the spinal cord resulting in a change, either temporary or permanent, in the cord's normal motor, sensory, or autonomic function
- Group 0 sample size Number of subjects in the control (unexposed) group
- 10
- Group 1 sample size Number of subjects in the case (exposed) group
- 11
Lab analysis
- Sequencing type
- 16S
- 16S variable region One or more hypervariable region(s) of the bacterial 16S gene
- V3-V4
- Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
- DNA-DNA Hybridization
Statistical Analysis
- Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).
- relative abundances
- Significance threshold p-value or FDR threshold used for differential abundance testing (if any)
- 0.05
- MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?
- No
- LDA Score above Threshold for the linear discriminant analysis (LDA) score for studies using the popular LEfSe tool
- 3
- Confounders controlled for Confounding factors that have been accounted for by stratification or model adjustment
- age, Confounders controlled for: "gender" is not in the list (abnormal glucose tolerance, acetaldehyde, acute graft vs. host disease, acute lymphoblastic leukemia, acute myeloid leukemia, adenoma, age, AIDS, alcohol consumption measurement, alcohol drinking, ...) of allowed values.gender, Confounders controlled for: "injury duration" is not in the list (abnormal glucose tolerance, acetaldehyde, acute graft vs. host disease, acute lymphoblastic leukemia, acute myeloid leukemia, adenoma, age, AIDS, alcohol consumption measurement, alcohol drinking, ...) of allowed values.injury duration, Confounders controlled for: "injury site" is not in the list (abnormal glucose tolerance, acetaldehyde, acute graft vs. host disease, acute lymphoblastic leukemia, acute myeloid leukemia, adenoma, age, AIDS, alcohol consumption measurement, alcohol drinking, ...) of allowed values.injury site
Signature 1
Source: Figure 3
Description: Alterations in the gut microbiota at the phylum and genus levels between the two groups.
Abundance in Group 1: increased abundance in spinal cord injury patient
| NCBI | Quality Control | Links |
|---|---|---|
| Synergistota | ||
| UBA1819UBA1819 | ||
| Eggerthella |
Revision editor(s): Omojokunoluwatomisin
Signature 2
Curated date: 2024/03/12
Curator: Omojokunoluwatomisin
Revision editor(s): Omojokunoluwatomisin, Ayibatari
Source: Figure 3
Description: Alterations in the gut microbiota at the phylum and genus levels between the two groups.
Abundance in Group 1: decreased abundance in spinal cord injury patient
Revision editor(s): Omojokunoluwatomisin, Ayibatari
