Pretreatment gut microbiome predicts chemotherapy-related bloodstream infection

Study information

Needs review

study design

prospective cohort

Citation

PMID PubMed identifier for scientific articles.

27121964

DOI Digital object identifier for electronic documents.

10.1186/s13073-016-0301-4

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

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Curated date: 2021/01/10

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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

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): 0.15

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

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Curated date: 2021/01/10

Curator: William Lam

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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 Control	Links
Veillonella
unclassified Erysipelotrichaceae

Revision editor(s): WikiWorks, Aiyshaaaa

Signature 2

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Curator: William Lam

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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 Control	Links
Alcaligenaceae
Barnesiellaceae
Butyricimonas
Dehalobacterium
Dehalococcoidaceae
Desulfovibrionaceae
Faecalibacterium
Odoribacteraceae
Oscillospira
Oxalobacteraceae
Sutterella

Revision editor(s): WikiWorks, Merit