Pretreatment gut microbiome predicts chemotherapy-related bloodstream infection

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Needs review
study design
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
URI
Authors
Montassier E, Al-Ghalith GA, Ward T, Corvec S, Gastinne T, Potel G, Moreau P, de la Cochetiere MF, Batard E, Knights D
Journal
Genome medicine
Year
2016
Keywords:
Bloodstream infection, Chemotherapy, Intestinal microbiome, Prediction
BACKGROUND: Bacteremia, or bloodstream infection (BSI), is a leading cause of death among patients with certain types of cancer. A previous study reported that intestinal domination, defined as occupation of at least 30 % of the microbiota by a single bacterial taxon, is associated with BSI in patients undergoing allo-HSCT. However, the impact of the intestinal microbiome before treatment initiation on the risk of subsequent BSI remains unclear. Our objective was to characterize the fecal microbiome collected before treatment to identify microbes that predict the risk of BSI. METHODS: We sampled 28 patients with non-Hodgkin lymphoma undergoing allogeneic hematopoietic stem cell transplantation (HSCT) prior to administration of chemotherapy and characterized 16S ribosomal RNA genes using high-throughput DNA sequencing. We quantified bacterial taxa and used techniques from machine learning to identify microbial biomarkers that predicted subsequent BSI. RESULTS: We found that patients who developed subsequent BSI exhibited decreased overall diversity and decreased abundance of taxa including Barnesiellaceae, Coriobacteriaceae, Faecalibacterium, Christensenella, Dehalobacterium, Desulfovibrio, and Sutterella. Using machine-learning methods, we developed a BSI risk index capable of predicting BSI incidence with a sensitivity of 90 % at a specificity of 90 % based only on the pretreatment fecal microbiome. CONCLUSIONS: These results suggest that the gut microbiota can identify high-risk patients before HSCT and that manipulation of the gut microbiota for prevention of BSI in high-risk patients may be a useful direction for future research. This approach may inspire the development of similar microbiome-based diagnostic and prognostic models in other diseases.

Experiment 1


Needs review

Curated date: 2021/01/10

Curator: WikiWorks

Revision editor(s): WikiWorks

Subjects

Location of subjects
France
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
Non-Hodgkins lymphoma NHL,non-Hodgkin lymphoma,non-Hodgkin's lymphoma,non-Hodgkin's lymphoma (NHL),non-Hodgkins lymphoma,Non-Hodgkins lymphoma
Group 0 name Corresponds to the control (unexposed) group for case-control studies
non-bloodstream infection
Group 1 name Corresponds to the case (exposed) group for case-control studies
bloodstream infection
Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
participants had blood stream infection, diagnosis with non-Hodgkins lymphoma (NHL), undergone hematopoeitic stem cell transplant and chemotherapy that did not had a history of inflammatory bowel disease, no exposure to probiotics, prebiotics or broad-soectrium antibiotics, no administered nasal-tube feeding or parenteral nutrition in a month prior to initiation of the study
Group 0 sample size Number of subjects in the control (unexposed) group
17
Group 1 sample size Number of subjects in the case (exposed) group
11

Lab analysis

Sequencing type
16S
16S variable region One or more hypervariable region(s) of the bacterial 16S gene
V5-V6
Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
Roche454

Statistical Analysis

Statistical test
Mann-Whitney (Wilcoxon)
Significance threshold p-value or FDR threshold used for differential abundance testing (if any)
0.15
MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?
Yes

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

Needs review

Curated date: 2021/01/10

Curator: William Lam

Revision editor(s): WikiWorks, Aiyshaaaa

Source: Figure 2, 3, aditional file 5a and b, 7

Description: Relative abundance of the differentiated taxa in samples collected prior to treatment in patients who developed subsequent Blood Stream Infections and patients who did not develop Blood Stream Infections

Abundance in Group 1: increased abundance in bloodstream infection

NCBI Quality ControlLinks
Veillonella
unclassified Erysipelotrichaceae

Revision editor(s): WikiWorks, Aiyshaaaa

Signature 2

Needs review

Curated date: 2021/01/10

Curator: William Lam

Revision editor(s): WikiWorks, Merit

Source: Figure 2, 3, aditional file 5a and b, 7

Description: Relative abundance of the differentiated taxa in samples collected prior to treatment in patients who developed subsequent Blood Stream Infections and patients who did not develop Blood Stream Infections

Abundance in Group 1: decreased abundance in bloodstream infection

NCBI Quality ControlLinks
Alcaligenaceae
Barnesiellaceae
Butyricimonas
Dehalobacterium
Dehalococcoidaceae
Desulfovibrionaceae
Faecalibacterium
Odoribacteraceae
Oscillospira
Oxalobacteraceae
Sutterella

Revision editor(s): WikiWorks, Merit