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

Study information

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

study design

case-control

Citation

PMID PubMed identifier for scientific articles.

27338587

DOI Digital object identifier for electronic documents.

10.1186/s40168-016-0171-4

URI Uniform resource identifier for web resources.

Authors

Giloteaux L, Goodrich JK, Walters WA, Levine SM, Ley RE, Hanson MR

Journal

Microbiome

Year

2016

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

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

Curated date: 2021/01/10

Curator: WikiWorks743

Revision editor(s): WikiWorks753, WikiWorks743

Subjects

Location of subjects: United States of America

Host species Species from which microbiome was sampled (if applicable): 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

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

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

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