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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.
Afiliación
  • Abbas-Egbariya H; Sheba Medical Center, Tel-HaShomer, affiliated with the Tel-Aviv University, Tel Aviv, Israel.
  • Haberman Y; Sheba Medical Center, Tel-HaShomer, affiliated with the Tel-Aviv University, Tel Aviv, Israel. Yael.Haberman@sheba.health.gov.il.
  • Braun T; Cincinnati Children's Hospital Medical Center and the University of Cincinnati College of Medicine, Cincinnati, OH, USA. Yael.Haberman@sheba.health.gov.il.
  • Hadar R; Sheba Medical Center, Tel-HaShomer, affiliated with the Tel-Aviv University, Tel Aviv, Israel.
  • Denson L; Sheba Medical Center, Tel-HaShomer, affiliated with the Tel-Aviv University, Tel Aviv, Israel.
  • Gal-Mor O; Cincinnati Children's Hospital Medical Center and the University of Cincinnati College of Medicine, Cincinnati, OH, USA.
  • Amir A; The Infectious Diseases Research Laboratory, Sheba Medical Center, Tel-Hashomer, and the Department of Clinical Microbiology and Immunology, Tel Aviv University, Tel Aviv, Israel.
Genome Biol ; 23(1): 61, 2022 02 23.
Article en En | MEDLINE | ID: mdl-35197084
ABSTRACT

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.
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Texto completo: 1 Colección: 01-internacional Asunto principal: Enfermedades Inflamatorias del Intestino / Colitis Ulcerosa / Enfermedad de Crohn / Microbioma Gastrointestinal Tipo de estudio: Systematic_reviews Límite: Humans Idioma: En Revista: Genome Biol Asunto de la revista: BIOLOGIA MOLECULAR / GENETICA Año: 2022 Tipo del documento: Article País de afiliación: Israel

Texto completo: 1 Colección: 01-internacional Asunto principal: Enfermedades Inflamatorias del Intestino / Colitis Ulcerosa / Enfermedad de Crohn / Microbioma Gastrointestinal Tipo de estudio: Systematic_reviews Límite: Humans Idioma: En Revista: Genome Biol Asunto de la revista: BIOLOGIA MOLECULAR / GENETICA Año: 2022 Tipo del documento: Article País de afiliación: Israel