Tear film microbiome in Sjogren's and non-Sjogren's aqueous deficiency dry eye
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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
Pal S, Vani G, Donthineni PR, Basu S, Arunasri K
Journal
Indian journal of ophthalmology
Year
2023
Keywords:
Dry eye disease, Prevotella, Sjogren's syndrome, non-Sjogren's syndrome, tear film microbiome
PURPOSE: To understand the bacterial microbiome changes associated with Sjogren's syndrome (SS) and non-Sjogren's syndrome (NSS) aqueous-deficient dry eyes compared to healthy eyes. METHODS: Bacterial microbiome was generated from the deoxyribonucleic acid of tear film samples in healthy (n = 33), SS (n = 17), and NSS (n = 28) individuals. Sequencing of the V3-V4 region of the 16S rRNA gene was performed on the Illumina HiSeq2500 platform. Quantitative Insights Into Microbial Ecology (QIIME) pipeline was used to assign taxa to sequences. Statistical analysis was performed in R to assess the alpha diversity and beta diversity indices. Significant changes between the healthy, SS, and NSS cohorts were depicted by principal coordinate analysis (PCoA), differential abundance, and network analysis. RESULTS: Tear microbiome was generated in healthy, SS, and NSS samples. Phyla Actinobacteria, Firmicutes, and Bacteroidetes showed significant changes in SS and NSS compared to healthy. Genera Lactobacillus and Bacillus were predominantly present in all samples. PCoA and heat map analysis showed distinct clusters for SS and NSS from the healthy cohort. Genera Prevotella, Coriobacteriaceae UCG-003, Enterococcus, Streptomyces, Rhodobacter, Ezakiella, and Microbacterium significantly increased in abundance in SS and NSS compared to a healthy cohort. Bacteria-bacteria interaction in SS, NSS, and healthy cohorts was predicted by CoNet network analysis. This analysis predicted a major hub of interaction for the pro-inflammatory bacterium Prevotella in the SS and NSS cohorts. CONCLUSION: The results of the study indicate significant changes in the phyla and genera in SS and NSS compared to healthy. Both discriminative analysis and network analysis indicated a possible association of predominant pro-inflammatory bacteria with SS and NSS.
Experiment 1
Reviewed Marked as Reviewed by Peace Sandy on 2023-12-22
Subjects
- Location of subjects
- India
- 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
- Tear film Precorneal film,Tear film,tear film
- Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology
- Dry eye syndrome dry eye,Dry Eye Syndrome,dry eye syndrome,Dry Eye Syndromes,dry eye(s),eye(s), dry,KCS,Keraconjunctivitis sicca,Keratoconjunctivitis Sicca,Keratoconjunctivitis sicca,keratoconjunctivitis sicca,Keratoconjunctivitis sicca (disorder),sicca, keratoconjunctivitis,Tear film insufficiency,tear film insufficiency,Dry eye syndrome
- Group 0 name Corresponds to the control (unexposed) group for case-control studies
- Healthy Controls
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- Dry Eye Disease patients
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- Both Sjogren's and non-Sjogren's patients with Dry Eye Disease
- Group 0 sample size Number of subjects in the control (unexposed) group
- 18
- Group 1 sample size Number of subjects in the case (exposed) group
- 24
- Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any)
- No medications in the past month
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
- Mann-Whitney (Wilcoxon)
- Significance threshold p-value or FDR threshold used for differential abundance testing (if any)
- 0.05
Alpha Diversity
- Shannon Estimator of species richness and species evenness: more weight on species richness
- decreased
- Simpson Estimator of species richness and species evenness: more weight on species evenness
- decreased
Signature 1
Reviewed Marked as Reviewed by Peace Sandy on 2023-12-22
Source: Table S2A
Description: Table S2A: Discriminative genera in SS and NSS compared to HC
Abundance in Group 1: increased abundance in Dry Eye Disease patients
Revision editor(s): Mary Bearkland
Signature 2
Reviewed Marked as Reviewed by Peace Sandy on 2023-12-22
Source: Table S2A
Description: Table S2A: Discriminative genera in SS and NSS compared to HC
Abundance in Group 1: decreased abundance in Dry Eye Disease patients
Revision editor(s): Mary Bearkland
Experiment 2
Reviewed Marked as Reviewed by Peace Sandy on 2023-12-22
Differences from previous experiment shown
Subjects
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- Sjogren's patients with Dry Eye Disease
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- Sjogren's patients with Dry Eye Disease
- Group 1 sample size Number of subjects in the case (exposed) group
- 9
Lab analysis
Statistical Analysis
Alpha Diversity
- Shannon Estimator of species richness and species evenness: more weight on species richness
- decreased
- Simpson Estimator of species richness and species evenness: more weight on species evenness
- decreased
Signature 1
Reviewed Marked as Reviewed by Peace Sandy on 2023-12-22
Source: Table S2B
Description: Table S2B: Discriminative genera in SS compared to HC
Abundance in Group 1: increased abundance in Sjogren's patients with Dry Eye Disease
Revision editor(s): Mary Bearkland
Signature 2
Reviewed Marked as Reviewed by Peace Sandy on 2023-12-22
Source: Table S2B
Description: Table S2B: Discriminative genera in SS compared to HC
Abundance in Group 1: decreased abundance in Sjogren's patients with Dry Eye Disease
Revision editor(s): Mary Bearkland
Experiment 3
Reviewed Marked as Reviewed by Peace Sandy on 2023-12-22
Differences from previous experiment shown
Subjects
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- Non-Sjogren's Syndrome patients with Dry Eye Disease
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- Non-Sjogren's patients with Dry Eye Disease
- Group 1 sample size Number of subjects in the case (exposed) group
- 15
Lab analysis
Statistical Analysis
Alpha Diversity
- Shannon Estimator of species richness and species evenness: more weight on species richness
- decreased
- Simpson Estimator of species richness and species evenness: more weight on species evenness
- decreased
Signature 1
Reviewed Marked as Reviewed by Peace Sandy on 2023-12-22
Source: Table S2C
Description: Table S2C: Discriminative genera in NSS compared to HC
Abundance in Group 1: increased abundance in Non-Sjogren's Syndrome patients with Dry Eye Disease
Revision editor(s): Mary Bearkland, Muqtadirat
Signature 2
Reviewed Marked as Reviewed by Peace Sandy on 2023-12-22
Source: Table S2C
Description: Table S2C: Discriminative genera in NSS compared to HC
Abundance in Group 1: decreased abundance in Non-Sjogren's Syndrome patients with Dry Eye Disease
Revision editor(s): Mary Bearkland
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