Results and lessons learned from the sbv IMPROVER metagenomics diagnostics for inflammatory bowel disease challenge

A growing body of evidence links gut microbiota changes with inflammatory bowel disease (IBD), raising the potential benefit of exploiting metagenomics data for non-invasive IBD diagnostics. The sbv IMPROVER metagenomics diagnosis for inflammatory bowel disease challenge investigated computational m...

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Vydané v:Scientific reports Ročník 13; číslo 1; s. 6303 - 19
Hlavní autori: Khachatryan, Lusine, Xiang, Yang, Ivanov, Artem, Glaab, Enrico, Graham, Garrett, Granata, Ilaria, Giordano, Maurizio, Maddalena, Lucia, Piccirillo, Marina, Manipur, Ichcha, Baruzzo, Giacomo, Cappellato, Marco, Avot, Batiste, Stan, Adrian, Battey, James, Lo Sasso, Giuseppe, Boue, Stephanie, Ivanov, Nikolai V., Peitsch, Manuel C., Hoeng, Julia, Falquet, Laurent, Di Camillo, Barbara, Guarracino, Mario R., Ulyantsev, Vladimir, Sierro, Nicolas, Poussin, Carine
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London Nature Publishing Group UK 18.04.2023
Nature Publishing Group
Nature Portfolio
Predmet:
631/326/2565/107
631/326/2565/2134
631/326/2565/2142
639/705/117
692/699/1503/257
692/699/1503/257/1389
692/699/1503/257/1402
Classification
Colitis, Ulcerative - diagnosis
Computer applications
Crohn Disease - diagnosis
Crohn Disease - genetics
Crohn's disease
Gastrointestinal Microbiome - genetics
Humanities and Social Sciences
Humans
Inflammatory bowel disease
Inflammatory bowel diseases
Inflammatory Bowel Diseases - diagnosis
Inflammatory Bowel Diseases - genetics
Intestinal microflora
Intestine
Metagenomics
multidisciplinary
Predictions
Science
Science (multidisciplinary)
Ulcerative colitis
ISSN:2045-2322, 2045-2322
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Popis
Shrnutí:A growing body of evidence links gut microbiota changes with inflammatory bowel disease (IBD), raising the potential benefit of exploiting metagenomics data for non-invasive IBD diagnostics. The sbv IMPROVER metagenomics diagnosis for inflammatory bowel disease challenge investigated computational metagenomics methods for discriminating IBD and nonIBD subjects. Participants in this challenge were given independent training and test metagenomics data from IBD and nonIBD subjects, which could be wither either raw read data (sub-challenge 1, SC1) or processed Taxonomy- and Function-based profiles (sub-challenge 2, SC2). A total of 81 anonymized submissions were received between September 2019 and March 2020. Most participants’ predictions performed better than random predictions in classifying IBD versus nonIBD, Ulcerative Colitis (UC) versus nonIBD, and Crohn’s Disease (CD) versus nonIBD. However, discrimination between UC and CD remains challenging, with the classification quality similar to the set of random predictions. We analyzed the class prediction accuracy, the metagenomics features by the teams, and computational methods used. These results will be openly shared with the scientific community to help advance IBD research and illustrate the application of a range of computational methodologies for effective metagenomic classification.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-023-33050-0