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Meta-analysis defines predominant shared microbial responses in various diseases and a specific inflammatory bowel disease signal

BACKGROUND: Gut microbial alteration is implicated in inflammatory bowel disease but is noted in other diseases. Systematic comparison to define similarities and specificities is hampered since most studies focus on a single disease. RESULTS: We develop a pipeline to compare between disease cohorts...

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Autores principales: Abbas-Egbariya, Haya, Haberman, Yael, Braun, Tzipi, Hadar, Rotem, Denson, Lee, Gal-Mor, Ohad, Amir, Amnon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8867743/
https://www.ncbi.nlm.nih.gov/pubmed/35197084
http://dx.doi.org/10.1186/s13059-022-02637-7
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author Abbas-Egbariya, Haya
Haberman, Yael
Braun, Tzipi
Hadar, Rotem
Denson, Lee
Gal-Mor, Ohad
Amir, Amnon
author_facet Abbas-Egbariya, Haya
Haberman, Yael
Braun, Tzipi
Hadar, Rotem
Denson, Lee
Gal-Mor, Ohad
Amir, Amnon
author_sort Abbas-Egbariya, Haya
collection PubMed
description BACKGROUND: Gut microbial alteration is implicated in inflammatory bowel disease but is noted in other diseases. Systematic comparison to define similarities and specificities is hampered since most studies focus on a single disease. RESULTS: We develop a pipeline to compare between disease cohorts starting from the raw V4 16S amplicon sequence variants. Including 12,838 subjects, from 59 disease cohorts, we demonstrate a predominant shared signature across diseases, indicating a common bacterial response to different diseases. We show that classifiers trained on one disease cohort predict relatively well other diseases due to this shared signal, and hence, caution should be taken when using such classifiers in real-world scenarios, where diseases are intermixed. Based on this common signature across a large array of diseases, we develop a universal dysbiosis index that successfully differentiates between cases and controls across various diseases and can be used for prioritizing fecal donors and samples with lower disease probability. Finally, we identify a set of IBD-specific bacteria, which can direct mechanistic studies and design of IBD-specific microbial interventions. CONCLUSIONS: A robust non-specific general response of the gut microbiome is detected in a large array of diseases. Disease classifiers may confuse between different diseases due to this shared microbial response. Our universal dysbiosis index can be used as a tool to prioritize fecal samples and donors. Finally, the IBD-specific taxa may indicate a more direct association to gut inflammation and disease pathogenesis, and those can be further used as biomarkers and as future targets for interventions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-022-02637-7.
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spelling pubmed-88677432022-02-25 Meta-analysis defines predominant shared microbial responses in various diseases and a specific inflammatory bowel disease signal Abbas-Egbariya, Haya Haberman, Yael Braun, Tzipi Hadar, Rotem Denson, Lee Gal-Mor, Ohad Amir, Amnon Genome Biol Research BACKGROUND: Gut microbial alteration is implicated in inflammatory bowel disease but is noted in other diseases. Systematic comparison to define similarities and specificities is hampered since most studies focus on a single disease. RESULTS: We develop a pipeline to compare between disease cohorts starting from the raw V4 16S amplicon sequence variants. Including 12,838 subjects, from 59 disease cohorts, we demonstrate a predominant shared signature across diseases, indicating a common bacterial response to different diseases. We show that classifiers trained on one disease cohort predict relatively well other diseases due to this shared signal, and hence, caution should be taken when using such classifiers in real-world scenarios, where diseases are intermixed. Based on this common signature across a large array of diseases, we develop a universal dysbiosis index that successfully differentiates between cases and controls across various diseases and can be used for prioritizing fecal donors and samples with lower disease probability. Finally, we identify a set of IBD-specific bacteria, which can direct mechanistic studies and design of IBD-specific microbial interventions. CONCLUSIONS: A robust non-specific general response of the gut microbiome is detected in a large array of diseases. Disease classifiers may confuse between different diseases due to this shared microbial response. Our universal dysbiosis index can be used as a tool to prioritize fecal samples and donors. Finally, the IBD-specific taxa may indicate a more direct association to gut inflammation and disease pathogenesis, and those can be further used as biomarkers and as future targets for interventions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-022-02637-7. BioMed Central 2022-02-23 /pmc/articles/PMC8867743/ /pubmed/35197084 http://dx.doi.org/10.1186/s13059-022-02637-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Abbas-Egbariya, Haya
Haberman, Yael
Braun, Tzipi
Hadar, Rotem
Denson, Lee
Gal-Mor, Ohad
Amir, Amnon
Meta-analysis defines predominant shared microbial responses in various diseases and a specific inflammatory bowel disease signal
title Meta-analysis defines predominant shared microbial responses in various diseases and a specific inflammatory bowel disease signal
title_full Meta-analysis defines predominant shared microbial responses in various diseases and a specific inflammatory bowel disease signal
title_fullStr Meta-analysis defines predominant shared microbial responses in various diseases and a specific inflammatory bowel disease signal
title_full_unstemmed Meta-analysis defines predominant shared microbial responses in various diseases and a specific inflammatory bowel disease signal
title_short Meta-analysis defines predominant shared microbial responses in various diseases and a specific inflammatory bowel disease signal
title_sort meta-analysis defines predominant shared microbial responses in various diseases and a specific inflammatory bowel disease signal
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8867743/
https://www.ncbi.nlm.nih.gov/pubmed/35197084
http://dx.doi.org/10.1186/s13059-022-02637-7
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