Reduced diversity and altered composition of the gut microbiome in individuals with myalgic encephalomyelitis/chronic fatigue syndrome

From BugSigDB
Reviewed Marked as Reviewed by Shaimaa Elsafoury on 2021/02/09
study design
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
URI
Authors
Giloteaux L, Goodrich JK, Walters WA, Levine SM, Ley RE, Hanson MR
Journal
Microbiome
Year
2016
Keywords:
Beta-diversity, Chronic fatigue syndrome, Inflammation, Lipopolysaccharides, Microbial translocation, Microbiome, Myalgic encephalomyelitis
BACKGROUND: Gastrointestinal disturbances are among symptoms commonly reported by individuals diagnosed with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). However, whether ME/CFS is associated with an altered microbiome has remained uncertain. Here, we profiled gut microbial diversity by sequencing 16S ribosomal ribonucleic acid (rRNA) genes from stool as well as inflammatory markers from serum for cases (n = 48) and controls (n = 39). We also examined a set of inflammatory markers in blood: C-reactive protein (CRP), intestinal fatty acid-binding protein (I-FABP), lipopolysaccharide (LPS), LPS-binding protein (LBP), and soluble CD14 (sCD14). RESULTS: We observed elevated levels of some blood markers for microbial translocation in ME/CFS patients; levels of LPS, LBP, and sCD14 were elevated in ME/CFS subjects. Levels of LBP correlated with LPS and sCD14 and LPS levels correlated with sCD14. Through deep sequencing of bacterial rRNA markers, we identified differences between the gut microbiomes of healthy individuals and patients with ME/CFS. We observed that bacterial diversity was decreased in the ME/CFS specimens compared to controls, in particular, a reduction in the relative abundance and diversity of members belonging to the Firmicutes phylum. In the patient cohort, we find less diversity as well as increases in specific species often reported to be pro-inflammatory species and reduction in species frequently described as anti-inflammatory. Using a machine learning approach trained on the data obtained from 16S rRNA and inflammatory markers, individuals were classified correctly as ME/CFS with a cross-validation accuracy of 82.93 %. CONCLUSIONS: Our results indicate dysbiosis of the gut microbiota in this disease and further suggest an increased incidence of microbial translocation, which may play a role in inflammatory symptoms in ME/CFS.

Experiment 1


Reviewed Marked as Reviewed by Shaimaa Elsafoury on 2021/02/09

Curated date: 2021/01/10

Curator: WikiWorks

Revision editor(s): WikiWorks, Victoria

Subjects

Location of subjects
United States of America
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
Chronic fatigue syndrome CFS,chronic fatigue syndrome,myalgic encephalitis,myalgic encephalomeyelitis/chronic fatigue syndrome,Myalgic Encephalomyelitis,myalgic encephalomyelitis,Postviral fatigue syndrome,systemic exertion intolerance disease,Chronic fatigue 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
CFS cases
Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
Subjects with ME/CFS were established patients of a ME/ CFS specialist, Susan Levine, M.D. and fit the Fukuda diag- nostic criteria
Group 0 sample size Number of subjects in the control (unexposed) group
39
Group 1 sample size Number of subjects in the case (exposed) group
48

Lab analysis

Sequencing type
16S
16S variable region One or more hypervariable region(s) of the bacterial 16S gene
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
MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?
Yes
LDA Score above Threshold for the linear discriminant analysis (LDA) score for studies using the popular LEfSe tool
2

Alpha Diversity

Shannon Estimator of species richness and species evenness: more weight on species richness
decreased
Chao1 Abundance-based estimator of species richness
decreased

Signature 1

Reviewed Marked as Reviewed by Shaimaa Elsafoury on 2021/02/09

Curated date: 2021/01/10

Curator: Shaimaa Elsafoury

Revision editor(s): WikiWorks

Source: figure 5

Description: taxonomy of differentially abundant microbiota between ME/CFS and healthy individuals

Abundance in Group 1: increased abundance in CFS cases

NCBI Quality ControlLinks
Oscillospira
Eggerthella
Lactococcus
Anaerotruncus
Coprobacillus

Revision editor(s): WikiWorks

Signature 2

Reviewed Marked as Reviewed by Shaimaa Elsafoury on 2021/02/09

Curated date: 2021/01/10

Curator: Shaimaa Elsafoury

Revision editor(s): WikiWorks

Source: figure 5

Description: taxonomy of differentially abundant microbiota between ME/CFS and healthy individuals

Abundance in Group 1: decreased abundance in CFS cases

NCBI Quality ControlLinks
Peptococcus
Haemophilus
Atopobium
Clostridium
Faecalibacterium
Ruminococcus
Aggregatibacter
Bifidobacterium
Collinsella
Sutterella

Revision editor(s): WikiWorks