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Original Research

Fecal microbiota profiles in treatment-naïve pediatric inflammatory bowel disease – associations with disease phenotype, treatment, and outcome

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Pages 37-49 | Published online: 31 Jan 2019

Figures & data

Table 1 Disease extent and behavior at diagnosis according to the Paris classification and treatments in pediatric IBD patients

Table 2 Demographics and laboratory tests of IBD, non-IBD patients, and healthy controls at baseline

Figure 1 Faecalibacterium prausnitzii abundance in IBD patients according to whether they had received antibiotics prior to the diagnosis (measured in fluorescence signal strength in 1,000 units).

Abbreviation: IBD, inflammatory bowel disease.
Figure 1 Faecalibacterium prausnitzii abundance in IBD patients according to whether they had received antibiotics prior to the diagnosis (measured in fluorescence signal strength in 1,000 units).

Figure 2 Boxplot illustrating the differences in the total fluorescence signal strength measured in 1,000 units between IBD, non-IBD symptomatic patients, and healthy controls.

Abbreviations: IBD, inflammatory bowel disease; CD, Crohn’s disease; UC, ulcerative colitis; IBDU, inflammatory bowel disease unclassified; ns, not significant.
Figure 2 Boxplot illustrating the differences in the total fluorescence signal strength measured in 1,000 units between IBD, non-IBD symptomatic patients, and healthy controls.

Figure 3 Principal component analysis, illustrating the difference in microbiota abundance of all 54 bacterial probes between IBD, non-IBD symptomatic patients, and healthy controls.

Notes: Each dot represents one individual. The units represent the total item loadings on each of the extracted factors.
Abbreviations: IBD, inflammatory bowel disease; PCA, principal component analysis.
Figure 3 Principal component analysis, illustrating the difference in microbiota abundance of all 54 bacterial probes between IBD, non-IBD symptomatic patients, and healthy controls.

Figure 4 Sensitivity and specificity of Proteobacteria, Enterobacteriaceae, and Shigella/Escherichia abundance in differentiating Crohn’s disease phenotypes (stricturing/penetrating vs inflammatory disease behavior) using the area under the receiver operating characteristics curve analysis.

Abbreviations: CD, Crohn’s disease; AUC, area under the curve.
Figure 4 Sensitivity and specificity of Proteobacteria, Enterobacteriaceae, and Shigella/Escherichia abundance in differentiating Crohn’s disease phenotypes (stricturing/penetrating vs inflammatory disease behavior) using the area under the receiver operating characteristics curve analysis.

Figure 5 Sensitivity and specificity of Firmicutes and Mycoplasma hominis abundance in differentiating conventional- vs biologic therapy-treated IBD patients using the area under the receiver operating characteristics curve analysis.

Abbreviations: IBD, inflammatory bowel disease; CD, Crohn’s disease; AUC, area under the curve.
Figure 5 Sensitivity and specificity of Firmicutes and Mycoplasma hominis abundance in differentiating conventional- vs biologic therapy-treated IBD patients using the area under the receiver operating characteristics curve analysis.

Figure 6 Proteobacteria abundance in IBD patients according to whether they needed surgery or not (measured in fluorescence signal strength in 1,000 units).

Abbreviation: IBD, inflammatory bowel disease.
Figure 6 Proteobacteria abundance in IBD patients according to whether they needed surgery or not (measured in fluorescence signal strength in 1,000 units).

Table S1 List of phyla and bacterial names of the GA-Map technology markers