Abstract
Recent work has highlighted the importance of confounder control in microbiome association studies1,2. For instance, multiple pathologies previously linked to gut ecosystem dysbiosis display concomitant changes in stool consistency3,4,5,6, a major covariate of microbiome variation2,7. In those cases, observed microbiota alterations could largely reflect variation in faecal water content. Moreover, stool moisture variation has been linked to fluctuations in faecal microbial load, inducing artefacts in relative abundance profile analyses8,9. Hence, the identification of associations between the gut microbiota and specific disease manifestations in pathologies with complex aetiologies requires a deconfounded, quantitative assessment of microbiome variation. Here, we revisit a disease association microbiome data set comprising 106 patients with primary sclerosing cholangitis (PSC) and/or inflammatory bowel disease10. Assessing quantitative taxon abundances9, we study microbiome alterations beyond symptomatic stool moisture variation. We observe an increased prevalence of a low cell count Bacteroides 2 enterotype across the pathologies studied, with microbial loads correlating inversely with intestinal and systemic inflammation markers. Quantitative analyses allow us to differentiate between taxa associated with either intestinal inflammation severity (Fusobacterium) or cholangitis/biliary obstruction (Enterococcus) among previously suggested PSC marker genera. We identify and validate a near-exclusion pattern between the inflammation-associated Fusobacterium and Veillonella genera, with Fusobacterium detection being restricted to Crohn’s disease and patients with PSC–Crohn’s disease. Overall, through absolute quantification and confounder control, we single out clear-cut microbiome markers associated with pathophysiological manifestations and disease diagnosis.
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Data availability
Raw amplicon sequencing data that support the findings of this study have been deposited at the European Genome-phenome Archive (EGA), with accession no. EGAS00001003600. The genus-level QMP matrix can be downloaded at http://raeslab.org/software/QMP2/.
Code availability
The R code used to compute QMPs can be found at https://github.com/raeslab/QMP/.
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Acknowledgements
We thank all study participants for their valuable contribution. We thank K. Verbeke for facilitating moisture content determinations. The development of QMP analysis was funded by a KU Leuven CREA grant. S.V.-S., G.K. and M.V.-C. were supported by a (post-)doctoral fellowship from the Research Foundation Flanders (FWO Vlaanderen). S.V. and S.v.d.M. are Senior Clinical Researchers of the FWO Vlaanderen. This work was co-funded by VIB, the Rega Institute for Medical Research, KU Leuven, the FWO EOS program (30770923), FP7 METACARDIS (305312) and H2020 SYSCID (733100).
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This study was conceived by J.S., S.V. and J.R. Experiments were designed by J.S., G.F. and J.R. Sampling of the different cohorts was set up and carried out by J.S., S.v.d.M., S.V.-S., C.C. and G.F. Experiments were performed by J.S. (calprotectin measurements), G.K. (flow cytometry analysis and moisture content) and C.C. (QMP analysis of the validation cohort). Statistical analyses were planned and executed by J.S., S.V.-S., M.V.-C., I.C. and G.F. S.V.-S., G.F., S.V. and J.R. drafted the manuscript. All authors revised the article and approved the final version for publication.
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J.R., S.V., S.V.-S., J.S., M.V.-C., G.F. and G.K. are inventors on the patent application PCT/EP2018/084920 in the name of VIB VZW, Katholieke Universiteit Leuven, KU Leuven R&D and Vrije Universiteit Brussel covering the microbiome features associated with inflammation described in this article.
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Vieira-Silva, S., Sabino, J., Valles-Colomer, M. et al. Quantitative microbiome profiling disentangles inflammation- and bile duct obstruction-associated microbiota alterations across PSC/IBD diagnoses. Nat Microbiol 4, 1826–1831 (2019). https://doi.org/10.1038/s41564-019-0483-9
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DOI: https://doi.org/10.1038/s41564-019-0483-9