Gut microbiota composition can reflect immune responses of latent tuberculosis infection in patients with poorly controlled diabetes

Study information

Needs review

study design

case-control

Citation

PMID PubMed identifier for scientific articles.

36631857

DOI Digital object identifier for electronic documents.

10.1186/s12931-023-02312-w

URI Uniform resource identifier for web resources.

Authors

Huang HL, Luo YC, Lu PL, Huang CH, Lin KD, Lee MR, Cheng MH, Yeh YT, Kao CY, Wang JY, Yang JM, Chong IW

Journal

Respiratory research

Year

2023

Keywords:

Diabetic mellitus, Gut microbiota, Immunity, Latent tuberculosis infection

BACKGROUND: Diabetes mellitus (DM) is a major risk factor for tuberculosis (TB). Evidence has linked the DM-related dysbiosis of gut microbiota to modifiable host immunity to Mycobacterium tuberculosis infection. However, the crosslinks between gut microbiota composition and immunological effects on the development of latent TB infection (LTBI) in DM patients remain uncertain. METHODS: We prospectively obtained stool, blood samples, and medical records from 130 patients with poorly-controlled DM (pDM), defined as ever having an HbA1c > 9.0% within previous 1 year. Among them, 43 had LTBI, as determined by QuantiFERON-TB Gold in-Tube assay. The differences in the taxonomic diversity of gut microbiota between LTBI and non-LTBI groups were investigated using 16S ribosomal RNA sequencing, and a predictive algorithm was established using a random forest model. Serum cytokine levels were measured to determine their correlations with gut microbiota. RESULTS: Compared with non-LTBI group, the microbiota in LTBI group displayed a similar alpha-diversity but different beta-diversity, featuring decrease of Prevotella_9, Streptococcus, and Actinomyces and increase of Bacteroides, Alistipes, and Blautia at the genus level. The accuracy was 0.872 for the LTBI prediction model using the aforementioned 6 microbiome-based biomarkers. Compared with the non-LTBI group, the LTBI group had a significantly lower serum levels of IL-17F (p = 0.025) and TNF-α (p = 0.038), which were correlated with the abundance of the aforementioned 6 taxa. CONCLUSIONS: The study results suggest that gut microbiome composition maybe associated with host immunity relevant to TB status, and gut microbial signature might be helpful for the diagnosis of LTBI.

Experiment 1

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Curated date: 2025/07/23

Curator: Nuerteye

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Subjects

Location of subjects: Taiwan

Host species Species from which microbiome was sampled. Contact us to have more species added.: Homo sapiens

Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology: Feces Cow dung,Cow pat,Droppings,Dung,Excrement,Excreta,Faeces,Fecal material,Fecal matter,Fewmet,Frass,Guano,Matières fécales@fr,Merde@fr,Ordure,Partie de la merde@fr,Piece of shit,Porción de mierda@es,Portion of dung,Portion of excrement,Portion of faeces,Portion of fecal material,Portion of fecal matter,Portion of feces,Portion of guano,Portion of scat,Portionem cacas,Scat,Spoor,Spraint,Stool,Teil der fäkalien@de,Feces,feces

Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology: Tuberculosis , Diabetes mellitus active tuberculosis,Kochs disease,TB,tuberculosis,tuberculosis disease,Tuberculosis,Diabetes,diabetes,diabetes mellitus,diabetes mellitus (disease),Diabetes mellitus (disorder),Diabetes mellitus, NOS,Diabetes NOS,DM,DM - Diabetes mellitus,Diabetes mellitus

Group 0 name Corresponds to the control (unexposed) group for case-control studies: poorly-controlled diabetes mellitus (pDM) without latent tuberculosis infection (LTBI)

Group 1 name Corresponds to the case (exposed) group for case-control studies: poorly-controlled diabetes mellitus with latent tuberculosis infection (pDM + LTBI)

Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group: poorly-controlled diabetes mellitus with latent tuberculosis infection (pDM + LTBI)

Group 0 sample size Number of subjects in the control (unexposed) group: 87

Group 1 sample size Number of subjects in the case (exposed) group: 43

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: Illumina

Statistical Analysis

Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).: relative abundances

Statistical test: LEfSe

Significance threshold p-value or FDR threshold used for differential abundance testing (if any): 0.05

LDA Score above Threshold for the linear discriminant analysis (LDA) score for studies using the popular LEfSe tool: 2

Matched on Factors on which subjects have been matched on in a case-control study: age, sex

Alpha Diversity

Shannon Estimator of species richness and species evenness: more weight on species richness: unchanged

Richness Number of species: unchanged

Faith Phylogenetic diversity, takes into account phylogenetic distance of all taxa identified in a sample: unchanged

Signature 1

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Curated date: 2025/07/23

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Source: Fig. 3A and B

Description: Differential abundance analysis and identification of representative genera as predictive signatures through linear discriminant analysis (LDA) with effect size measurements (LEfSe) analysis and a random forest model to discriminate between patients with poorly controlled diabetes with and without latent tuberculosis infection (LTBI). (A) Significantly different taxa in the cladogram according to a LDA score of ≥ 2 (each circle represents phylogenetic levels from phylum to genus [inside to outside], and each diameter is proportional to the taxon’s abundance). (B) Significantly different genera in terms of relative abundance (LDA score of ≥ 2) between LTBI and non-LTBI groups.

Abundance in Group 1: increased abundance in poorly-controlled diabetes mellitus with latent tuberculosis infection (pDM + LTBI)

NCBI	Quality Control	Links
Eisenbergiella
Ruminococcaceae bacterium UCG-013Ruminococcaceae bacterium UCG-013
Anaerotruncus
Eubacterium xylanophilum
Butyrivibrio
Hydrogenoanaerobacterium
Butyricicoccus
Flavonifractor
Candidatus Soleaferrea sp.
uncultured Muribaculaceae bacterium
uncultured Clostridiales Family XIIIuncultured Clostridiales Family XIII
ProteusProteus
uncultured Rhodospirillalesuncultured Rhodospirillales
Lachnoclostridium
Ruminiclostridium sp.
Blautia
Alistipes
Bacteroides

Revision editor(s): Nuerteye

Signature 2

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Source: Figure 3A and B

Description: Differential abundance analysis and identification of representative genera as predictive signatures through linear discriminant analysis (LDA) with effect size measurements (LEfSe) analysis and a random forest model to discriminate between patients with poorly controlled diabetes with and without latent tuberculosis infection (LTBI). A) Significantly different taxa in the cladogram according to a LDA score of ≥ 2 (each circle represents phylogenetic levels from phylum to genus [inside to outside], and each diameter is proportional to the taxon’s abundance). B) Significantly different genera in terms of relative abundance (LDA score of ≥ 2) between LTBI and non-LTBI groups.

Abundance in Group 1: decreased abundance in poorly-controlled diabetes mellitus with latent tuberculosis infection (pDM + LTBI)

NCBI	Quality Control	Links
Prevotella 9Prevotella 9
Streptococcus
Actinomyces
Haemophilus
RothiaRothia
Intestinimonas
Acidaminococcus
Muribaculaceae metagenomeMuribaculaceae metagenome

Revision editor(s): Nuerteye