Alterations in the Gut Microbiome of Young Children with Airway Allergic Disease Revealed by Next-Generation Sequencing
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Study information
-
Quality control
- Retracted paper
- Contamination issues suspected
- Batch effect issues suspected
- Uncontrolled confounding suspected
- Results are suspect (various reasons)
- Tags applied
study design
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
URI
Authors
Wan J, Song J, Lv Q, Zhang H, Xiang Q, Dai H, Zheng H, Lin X, Zhang W
Journal
Journal of asthma and allergy
Year
2023
Keywords:
allergic asthma, allergic rhinitis, childhood, gut microbiome, metagenomic sequencing
PURPOSE: Recent studies had shown that gut microbiota played a significant role in the development of the immune system and may affect the course of airway allergic disease. We conducted this study to determine unique gut microbial associated with allergic disease in children by shotgun gene sequencing. METHODS: We collected fecal samples from children with allergic asthma (n = 23) and allergic rhinitis (n = 18), and healthy control (n = 19). The gut microbiota of specimens was analyzed by high-throughput metagenomic shotgun gene sequencing. RESULTS: The intestinal microbiota of children with allergic asthma and allergic rhinitis was characterized by increased microbial richness and diversity. Simpson and Shannon were significantly elevated in children with allergic asthma. Principal coordinates analysis (PCoA) showed that the gut microbial communities cluster patterns of children with asthma or rhinitis were significantly different from those of healthy controls. However, no significant difference was found between asthma group and rhinitis group At the phylum level, higher relative abundance of Firmicutes was found in the allergic rhinitis group and allergic asthma group, while the level of Bacteroidetes was significantly lower. At the genus level, Corynebacterium, Streptococcus, Dorea, Actinomyces, Bifidobacterium, Blautia, and Rothia were significantly enriched in the allergic asthma group. Finally, a random forest classifier model selected 16 general signatures to discriminate the allergic asthma group from the healthy control group. CONCLUSION: In conclusion, children in the allergic rhinitis group and allergic asthma group had altered gut microbiomes in comparison with the healthy control group. Compared to healthy children, the gut microbiome in children with allergic diseases has higher pro-inflammatory potential and increased production of pro-inflammatory molecules.
Experiment 1
Reviewed Marked as Reviewed by Svetlana up on 2024-6-10
Subjects
- Location of subjects
- China
- 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
- Allergic asthma allergic form of asthma,atopic asthma,extrinsic asthma with acute exacerbation,extrinsic asthma with status asthmaticus,Allergic asthma,allergic asthma
- Group 0 name Corresponds to the control (unexposed) group for case-control studies
- Healthy control
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- Allergic asthma
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- Children with allergic asthma
- Group 0 sample size Number of subjects in the control (unexposed) group
- 19
- Group 1 sample size Number of subjects in the case (exposed) group
- 23
- Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any)
- 2 months
Lab analysis
- Sequencing type
- WMS
- 16S variable region One or more hypervariable region(s) of the bacterial 16S gene
- Not specified
- 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
- 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
- 3.0
- Matched on Factors on which subjects have been matched on in a case-control study
- age, body mass index, sex
Alpha Diversity
- Shannon Estimator of species richness and species evenness: more weight on species richness
- increased
- Simpson Estimator of species richness and species evenness: more weight on species evenness
- increased
Signature 1
Reviewed Marked as Reviewed by Svetlana up on 2024-6-10
Source: FIG 4A, 4B
Description: Linear discriminant analysis (LDA) scores for crucial bacteria classification with different abundances in allergic asthma versus healthy groups
Abundance in Group 1: increased abundance in Allergic asthma
Revision editor(s): Rahila, Scholastica
Signature 2
Reviewed Marked as Reviewed by Svetlana up on 2024-6-10
Source: FIG 4A, 4B
Description: Linear discriminant analysis (LDA) scores for crucial bacteria classification with different abundances in allergic asthma versus healthy groups
Abundance in Group 1: decreased abundance in Allergic asthma
Revision editor(s): Scholastica
Experiment 2
Reviewed Marked as Reviewed by Svetlana up on 2024-6-10
Differences from previous experiment shown
Subjects
- Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology
- Allergic rhinitis allergic form of rhinitis,allergic rhinitis,Alrh,atopic rhinitis,non-seasonal allergic rhinitis,Perenial allergic rhinitis,perennial allergic rhinitis,pollenosis,seasonal allergic rhinitis,Allergic rhinitis
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- Allergic rhinitis
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- Children with allergic rhinitis
- Group 1 sample size Number of subjects in the case (exposed) group
- 18
Lab analysis
Statistical Analysis
Alpha Diversity
- Shannon Estimator of species richness and species evenness: more weight on species richness
- increased
- Simpson Estimator of species richness and species evenness: more weight on species evenness
- increased
Signature 1
Reviewed Marked as Reviewed by Svetlana up on 2024-6-10
Source: FIG 4A, 4C
Description: Linear discriminant analysis (LDA) scores for crucial bacteria classification with different abundances in allergic rhinitis versus healthy groups
Abundance in Group 1: increased abundance in Allergic rhinitis
Revision editor(s): Rahila, Scholastica
Signature 2
Reviewed Marked as Reviewed by Svetlana up on 2024-6-10
Source: FIG 4A, 4C
Description: Linear discriminant analysis (LDA) scores for crucial bacteria classification with different abundances in allergic rhinitis versus healthy groups
Abundance in Group 1: decreased abundance in Allergic rhinitis
Revision editor(s): Scholastica
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