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Thanks to shotgun metagenomic sequencing of gut microbiota, physicians are on track to more easily distinguish inflammatory bowel disease (IBD) from irritable bowel syndrome (IBS), according to an analysis of stool samples from patients with the two common gastrointestinal diseases.
“The integration of these datasets allowed us to pinpoint key species as targets for functional studies in IBD and IBS and to connect knowledge of the etiology and pathogenesis of IBD and IBS with the gut microbiome to provide potential new targets for treatment,” wrote Arnau Vich Vila, of the University of Groningen, the Netherlands, and his coauthors. The report is in Science Translational Medicine.
Stool samples from 1,792 participants were analyzed: 355 from patients with IBD, 412 from patients with IBS, and 1,025 from the control group. The researchers found 24 bacterial taxa associated with both IBD and IBS and specific species that accompanied specific diseases, such as an abundance of Bacteroides in patients with IBD and Firmicutes in patients with IBS. In addition, their predictive model to distinguish IBD from IBS via gut microbial composition data [area under the curve (AUC) mean = 0.91 (0.81 to 0.99)] proved more accurate than did current fecal biomarker calprotectin [AUC mean = 0.80 (0.71 to 0.88); P = .002].
The authors acknowledged additional evidence that will be needed before these results can be translated to clinical practice, including supporting their described microbial pathways with metatranscriptomics and metabolomics data as well as functional experiments. They also observed that their predictive model will need to be validated through replication of their findings in patients with other gastrointestinal disorders or prediagnostic groups. They noted that their analysis benefited from being able to correct for confounding factors such as medication use, which is “essential for identifying disease-associated microbial features and avoiding false-positive associations due to changes in GI acidity or bowel mobility.”
One author reported receiving speaker fees from AbbVie and was a shareholder of the health care IT company Aceso BV and of Floris Medical Holding BV. Another author declared unrestricted research grants from AbbVie, Takeda, and Ferring Pharmaceuticals, is on the advisory boards for Mundipharma and Pharmacosmos, and has received speaker fees from Takeda and Janssen Pharmaceuticals. A third author declared consulting work for Takeda. The others reported no conflicts of interest.
SOURCE: Vich Vila A et al. Sci Transl Med. 2018 Dec 19. doi: 10.1126/scitranslmed.aap8914.
Thanks to shotgun metagenomic sequencing of gut microbiota, physicians are on track to more easily distinguish inflammatory bowel disease (IBD) from irritable bowel syndrome (IBS), according to an analysis of stool samples from patients with the two common gastrointestinal diseases.
“The integration of these datasets allowed us to pinpoint key species as targets for functional studies in IBD and IBS and to connect knowledge of the etiology and pathogenesis of IBD and IBS with the gut microbiome to provide potential new targets for treatment,” wrote Arnau Vich Vila, of the University of Groningen, the Netherlands, and his coauthors. The report is in Science Translational Medicine.
Stool samples from 1,792 participants were analyzed: 355 from patients with IBD, 412 from patients with IBS, and 1,025 from the control group. The researchers found 24 bacterial taxa associated with both IBD and IBS and specific species that accompanied specific diseases, such as an abundance of Bacteroides in patients with IBD and Firmicutes in patients with IBS. In addition, their predictive model to distinguish IBD from IBS via gut microbial composition data [area under the curve (AUC) mean = 0.91 (0.81 to 0.99)] proved more accurate than did current fecal biomarker calprotectin [AUC mean = 0.80 (0.71 to 0.88); P = .002].
The authors acknowledged additional evidence that will be needed before these results can be translated to clinical practice, including supporting their described microbial pathways with metatranscriptomics and metabolomics data as well as functional experiments. They also observed that their predictive model will need to be validated through replication of their findings in patients with other gastrointestinal disorders or prediagnostic groups. They noted that their analysis benefited from being able to correct for confounding factors such as medication use, which is “essential for identifying disease-associated microbial features and avoiding false-positive associations due to changes in GI acidity or bowel mobility.”
One author reported receiving speaker fees from AbbVie and was a shareholder of the health care IT company Aceso BV and of Floris Medical Holding BV. Another author declared unrestricted research grants from AbbVie, Takeda, and Ferring Pharmaceuticals, is on the advisory boards for Mundipharma and Pharmacosmos, and has received speaker fees from Takeda and Janssen Pharmaceuticals. A third author declared consulting work for Takeda. The others reported no conflicts of interest.
SOURCE: Vich Vila A et al. Sci Transl Med. 2018 Dec 19. doi: 10.1126/scitranslmed.aap8914.
Thanks to shotgun metagenomic sequencing of gut microbiota, physicians are on track to more easily distinguish inflammatory bowel disease (IBD) from irritable bowel syndrome (IBS), according to an analysis of stool samples from patients with the two common gastrointestinal diseases.
“The integration of these datasets allowed us to pinpoint key species as targets for functional studies in IBD and IBS and to connect knowledge of the etiology and pathogenesis of IBD and IBS with the gut microbiome to provide potential new targets for treatment,” wrote Arnau Vich Vila, of the University of Groningen, the Netherlands, and his coauthors. The report is in Science Translational Medicine.
Stool samples from 1,792 participants were analyzed: 355 from patients with IBD, 412 from patients with IBS, and 1,025 from the control group. The researchers found 24 bacterial taxa associated with both IBD and IBS and specific species that accompanied specific diseases, such as an abundance of Bacteroides in patients with IBD and Firmicutes in patients with IBS. In addition, their predictive model to distinguish IBD from IBS via gut microbial composition data [area under the curve (AUC) mean = 0.91 (0.81 to 0.99)] proved more accurate than did current fecal biomarker calprotectin [AUC mean = 0.80 (0.71 to 0.88); P = .002].
The authors acknowledged additional evidence that will be needed before these results can be translated to clinical practice, including supporting their described microbial pathways with metatranscriptomics and metabolomics data as well as functional experiments. They also observed that their predictive model will need to be validated through replication of their findings in patients with other gastrointestinal disorders or prediagnostic groups. They noted that their analysis benefited from being able to correct for confounding factors such as medication use, which is “essential for identifying disease-associated microbial features and avoiding false-positive associations due to changes in GI acidity or bowel mobility.”
One author reported receiving speaker fees from AbbVie and was a shareholder of the health care IT company Aceso BV and of Floris Medical Holding BV. Another author declared unrestricted research grants from AbbVie, Takeda, and Ferring Pharmaceuticals, is on the advisory boards for Mundipharma and Pharmacosmos, and has received speaker fees from Takeda and Janssen Pharmaceuticals. A third author declared consulting work for Takeda. The others reported no conflicts of interest.
SOURCE: Vich Vila A et al. Sci Transl Med. 2018 Dec 19. doi: 10.1126/scitranslmed.aap8914.
FROM SCIENCE TRANSLATIONAL MEDICINE
Key clinical point: Shotgun metagenomic sequencing data revealed key differences in gut microbiome composition between patients with inflammatory bowel disease and patients with irritable bowel syndrome.
Major finding: A predictive model to distinguish IBD from IBS based on gut microbial composition data [area under the curve (AUC) mean = 0.91 (0.81-0.99)] proved more accurate than did fecal biomarker calprotectin [AUC mean = 0.80 (0.71-0.88); P = .002].
Study details: A case-control analysis using shotgun metagenomic sequencing of stool samples from 1,792 individuals with IBD, IBS, or neither.
Disclosures: One author reported receiving speaker fees from AbbVie and was a shareholder of the health care IT company Aceso BV and of Floris Medical Holding BV. Another author declared unrestricted research grants from AbbVie, Takeda, and Ferring Pharmaceuticals, is on the advisory boards for Mundipharma and Pharmacosmos, and has received speaker fees from Takeda and Janssen Pharmaceuticals. A third author declared consulting work for Takeda. The others reported no conflicts of interest.
Source: Vich Vila A et al. Sci Transl Med. 2018 Dec 19. doi: 10.1126/scitranslmed.aap8914.