Pretreatment gut microbiome predicts chemotherapy-related bloodstream infection View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-04-28

AUTHORS

Emmanuel Montassier, Gabriel A. Al-Ghalith, Tonya Ward, Stephane Corvec, Thomas Gastinne, Gilles Potel, Phillipe Moreau, Marie France de la Cochetiere, Eric Batard, Dan Knights

ABSTRACT

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. More... »

PAGES

49

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s13073-016-0301-4

DOI

http://dx.doi.org/10.1186/s13073-016-0301-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1012949666

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/27121964


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37 schema:description 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.
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44 schema:keywords BSI incidence
45 BSI risk index
46 Barnesiellaceae
47 Christensenella
48 Coriobacteriaceae
49 DNA sequencing
50 Dehalobacterium
51 Desulfovibrio
52 Faecalibacterium
53 Hodgkin
54 Pretreatment gut microbiome
55 RNA genes
56 Sutterella
57 abundance
58 abundance of taxa
59 administration
60 administration of chemotherapy
61 allo-HSCT
62 allogeneic hematopoietic stem cell transplantation
63 approach
64 bacteremia
65 bacterial taxa
66 biomarkers
67 bloodstream infections
68 cancer
69 cause
70 cell transplantation
71 certain types
72 chemotherapy
73 chemotherapy-related bloodstream infection
74 death
75 development
76 direction
77 disease
78 diversity
79 domination
80 fecal microbiome
81 future research
82 genes
83 gut microbiome
84 gut microbiota
85 hematopoietic stem cell transplantation
86 high-risk patients
87 high-throughput DNA sequencing
88 impact
89 incidence
90 index
91 infection
92 initiation
93 intestinal domination
94 intestinal microbiome
95 leading cause
96 machine
97 machine-learning methods
98 manipulation
99 method
100 microbes
101 microbial biomarkers
102 microbiome
103 microbiota
104 model
105 objective
106 occupation
107 overall diversity
108 patients
109 pretreatment fecal microbiome
110 prevention
111 prevention of BSI
112 previous studies
113 prognostic model
114 research
115 results
116 ribosomal RNA genes
117 risk
118 risk index
119 risk of BSI
120 sensitivity
121 sequencing
122 single bacterial taxon
123 specificity
124 stem cell transplantation
125 study
126 subsequent bloodstream infection
127 taxa
128 technique
129 transplantation
130 treatment
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