Leveraging Human Microbiome Features to Diagnose and Stratify Children with Irritable Bowel Syndrome.

TitleLeveraging Human Microbiome Features to Diagnose and Stratify Children with Irritable Bowel Syndrome.
Publication TypeJournal Article
Year of Publication2019
AuthorsHollister, EB, Oezguen, N, Chumpitazi, BP, Luna, RAnn, Weidler, EM, Rubio-Gonzales, M, Dahdouli, M, Cope, JL, Mistretta, T-A, Raza, S, Metcalf, GA, Muzny, DM, Gibbs, RA, Petrosino, JF, Heitkemper, M, Savidge, TC, Shulman, RJ, Versalovic, J
JournalJ Mol Diagn
Date Published2019 May
KeywordsAbdominal Pain, Bacteria, Case-Control Studies, Child, Feces, Female, Gastrointestinal Tract, Genomics, Humans, Irritable Bowel Syndrome, Male, Metabolome, Microbiota, Multivariate Analysis, Principal Component Analysis, Statistics, Nonparametric

Accurate diagnosis and stratification of children with irritable bowel syndrome (IBS) remain challenging. Given the central role of recurrent abdominal pain in IBS, we evaluated the relationships of pediatric IBS and abdominal pain with intestinal microbes and fecal metabolites using a comprehensive clinical characterization and multiomics strategy. Using rigorous clinical phenotyping, we identified preadolescent children (aged 7 to 12 years) with Rome III IBS (n = 23) and healthy controls (n = 22) and characterized their fecal microbial communities using whole-genome shotgun metagenomics and global unbiased fecal metabolomic profiling. Correlation-based approaches and machine learning algorithms identified associations between microbes, metabolites, and abdominal pain. IBS cases differed from controls with respect to key bacterial taxa (eg, Flavonifractor plautii and Lachnospiraceae bacterium 7_1_58FAA), metagenomic functions (eg, carbohydrate metabolism and amino acid metabolism), and higher-order metabolites (eg, secondary bile acids, sterols, and steroid-like compounds). Significant associations between abdominal pain frequency and severity and intestinal microbial features were identified. A random forest classifier built on metagenomic and metabolic markers successfully distinguished IBS cases from controls (area under the curve, 0.93). Leveraging multiple lines of evidence, intestinal microbes, genes/pathways, and metabolites were associated with IBS, and these features were capable of distinguishing children with IBS from healthy children. These multi-omics features, and their links to childhood IBS coupled with nutritional interventions, may lead to new microbiome-guided diagnostic and therapeutic strategies.

Alternate JournalJ Mol Diagn
PubMed ID31005411
PubMed Central IDPMC6504675
Grant ListK23 DK101688 / DK / NIDDK NIH HHS / United States
R01 NR005337 / NR / NINR NIH HHS / United States
R03 DK117219 / DK / NIDDK NIH HHS / United States
U01 AI124290 / AI / NIAID NIH HHS / United States

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