Microbiota-based markers predictive of development of Clostridioides difficile infection

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作者
Matilda Berkell
Mohamed Mysara
Basil Britto Xavier
Cornelis H. van Werkhoven
Pieter Monsieurs
Christine Lammens
Annie Ducher
Maria J. G. T. Vehreschild
Herman Goossens
Jean de Gunzburg
Marc J. M. Bonten
Surbhi Malhotra-Kumar
机构
[1] University of Antwerp,Laboratory of Medical Microbiology, Vaccine & Infectious Disease Institute
[2] SCK–CEN,Microbiology Unit, Interdisciplinary Biosciences, Belgian Nuclear Research Centre
[3] Utrecht University,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht
[4] Da Volterra,Department of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf
[5] University of Cologne,Department of Internal Medicine, Infectious Diseases, University Hospital Frankfurt
[6] German Centre for Infection Research (DZIF),Department of Medical Microbiology, University Medical Center Utrecht
[7] partner site Bonn-Cologne,Department of Biomedical Sciences
[8] Goethe University Frankfurt,Department of Internal Medicine
[9] Utrecht University,Institute for Medical Microbiology, Immunology and Hygiene
[10] Institute of Tropical Medicine,Hospital Universitari de Bellvitge, Universitat de Barcelona
[11] University Medical Center Utrecht,undefined
[12] University of Cologne,undefined
[13] INSERM,undefined
[14] Paris Diderot University,undefined
[15] IAME,undefined
[16] Universitätsklinikum Heidelberg,undefined
[17] Universitätsklinikum Jena,undefined
[18] Universitätsklinikum Schleswig-Holstein,undefined
[19] Klinikum der Universität München,undefined
[20] Universitätsklinikum Leipzig,undefined
[21] Universitätsklinikum Aachen,undefined
[22] Universitätsklinikum Essen,undefined
[23] University Hospital of Heraklion,undefined
[24] Laiko General Hospital,undefined
[25] University General Hospital ATTIKON,undefined
[26] Evangelismos General Hospital,undefined
[27] Ippokratio Hospital,undefined
[28] IDIBELL,undefined
[29] Hospital Universitario 12 de Octubre,undefined
[30] Hospital Universitario Gregorio Marañón,undefined
[31] Hospital Universitario Ramón y Cajal,undefined
[32] Hospital Universitario Virgen Macarena,undefined
[33] Hospital Universitari Vall d’Hebrón,undefined
[34] IMIBIC-Hospital Universitario Reina Sofia,undefined
[35] UCO,undefined
[36] Infectious and Tropical Diseases Hospital Dr. Victor Babes,undefined
[37] Clinical Hospital of Infectious Diseases of Iasi,undefined
[38] The National Institute of Infectious Diseases Matei Bals,undefined
[39] Cluj Napoca Infectious disease Clinical Hospital,undefined
[40] Oncology Institute Prof. Dr. I Chiricuta,undefined
[41] Centre hospitalier universitaire Dupuytren,undefined
[42] Hôpital St Louis,undefined
[43] APHP Beaujon,undefined
[44] Centre Hospitalier Départemental Vendée,undefined
[45] CH de Cornouaille,undefined
[46] APHP Bichat,undefined
[47] Centre hospitalo-universitaire de Tours,undefined
[48] APHP Hôpital Cochin,undefined
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摘要
Antibiotic-induced modulation of the intestinal microbiota can lead to Clostridioides difficile infection (CDI), which is associated with considerable morbidity, mortality, and healthcare-costs globally. Therefore, identification of markers predictive of CDI could substantially contribute to guiding therapy and decreasing the infection burden. Here, we analyze the intestinal microbiota of hospitalized patients at increased CDI risk in a prospective, 90-day cohort-study before and after antibiotic treatment and at diarrhea onset. We show that patients developing CDI already exhibit significantly lower diversity before antibiotic treatment and a distinct microbiota enriched in Enterococcus and depleted of Ruminococcus, Blautia, Prevotella and Bifidobacterium compared to non-CDI patients. We find that antibiotic treatment-induced dysbiosis is class-specific with beta-lactams further increasing enterococcal abundance. Our findings, validated in an independent prospective patient cohort developing CDI, can be exploited to enrich for high-risk patients in prospective clinical trials, and to develop predictive microbiota-based diagnostics for management of patients at risk for CDI.
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