Article
Compositional clusters in the nasal microbiome as predictors of SARS-CoV-2 infection – results from the German National Cohort (NAKO) study
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Authors
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Sven Kleine Bardenhorst
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
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Julia Six-Merker
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
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Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany; Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, München, Germany
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Lilian Krist
- Institute of Social Medicine, Epidemiology and Health Economics, Charité – Universitätsmedizin Berlin, Berlin, Germany
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Thomas Keil
- Institute of Social Medicine, Epidemiology and Health Economics, Charité – Universitätsmedizin Berlin, Berlin, Germany; Institute for Clinical Epidemiology and Biometry, University of Würzburg, Würzburg, Germany; State Institute of Health, Bavarian Health and Food Safety Authority, Erlangen, Germany
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Katharina Nimptsch
- Max Delbrück Center for Molecular Medicine (MDC), Berlin, Germany
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Tobias Pischon
- Max Delbrück Center for Molecular Medicine (MDC), Berlin, Germany; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
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Sylvia Gastell
- German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
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Matthias B. Schulze
- German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany; Institute of Nutritional Science, University of Potsdam, Potsdam, Germany
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Maike Wolters
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
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Kathrin Günther
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
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Tamara Schikowski
- IUF - Leibniz Institute for Environmental Medicine, Düsseldorf, Germany
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Börge Schmidt
- Institute for Medical Informatics, Biometry and Epidemiology (IMIBE), University Hospital of Essen (AöR), Essen, Germany
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Andreas Stang
- Institute for Medical Informatics, Biometry and Epidemiology (IMIBE), University Hospital of Essen (AöR), Essen, Germany
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Karin B. Michels
- Institute for Prevention and Cancer Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
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Bianca Klee
- Interdisciplinary Center for Health Sciences, Institute for Medical Epidemiology, Biometrics and Informatics (IMEBI), Medical School of the Martin-Luther University Halle-Wittenberg, Halle (Saale), Germany
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Rafael Mikolajczyk
- Interdisciplinary Center for Health Sciences, Institute for Medical Epidemiology, Biometrics and Informatics (IMEBI), Medical School of the Martin-Luther University Halle-Wittenberg, Halle (Saale), Germany
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Volker Harth
- Institute for Occupational and Maritime Medicine (ZfAM), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
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Nadia Obi
- Institute for Occupational and Maritime Medicine (ZfAM), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
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Berit Lange
- Department for Epidemiology, Helmholtz Centre for Infection Research, Braunschweig, Germany
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Carolina J. Klett-Tammen
- Department for Epidemiology, Helmholtz Centre for Infection Research, Braunschweig, Germany
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Wolfgang Lieb
- Institute of Epidemiology, Christian-Albrechts-University Kiel, Kiel, Germany
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Heiko Becher
- Institute of Global Health, University Hospital Heidelberg, Heidelberg, Germany
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Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
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André Karch
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
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Klaus Berger
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
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Matthias Nauck
- Institute for Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
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Muhammad N. K. Khattak
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
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Hansjörg Baurecht
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
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Michael Leitzmann
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
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Bernd Holleczek
- Krebsregister Saarland, Saarbrücken, Germany
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Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
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Yvonne Kemmling
- Department for Epidemiology, Helmholtz Centre for Infection Research, Braunschweig, Germany
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Leo Panreck
- NAKO e.V., Heidelberg, Germany
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Marius Vital
- Institute for Medical Microbiology and Hospital Epidemiology, Hannover Medical School, Hannover, Germany
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Nicole Rübsamen
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| Published: | September 6, 2024 |
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Outline
Text
Introduction: The microbiome of the anterior nares can interact with viruses and might modify the risk of respiratory infections. Using pre-pandemic samples, we derived clusters that shape this microbial landscape and assessed their association with the risk of SARS-CoV-2 infection.
Methods: Between 2014 and 2019, the German National Cohort (NAKO) recruited 205,415 randomly selected persons aged 19–74 years for the baseline examination at 18 study centres. The NAKO conducted a COVID-19 survey among all participants about the distribution, course, and effects of COVID-19 in Germany in May 2020, i.e., during the first wave of the pandemic. Almost 162,000 NAKO participants completed the survey; among those, 492 participants reported an infection with SARS-CoV-2 confirmed by PCR testing [1]. We randomly selected nasal swabs from the baseline examination of 309 reportedly PCR-positive participants (150 women) and of 1,763 participants (948 women) who had not reported an infection with SARS-CoV-2 (of note, 95% stated that they had not been tested). Alpha and beta diversity were assessed using several complementary indices. Differential abundance was assessed using a triangulation approach by three methods: ANCOM-BC [2], LinDA [3], and ZicoSeq [4]. To determine compositional microbiome clusters, we used Latent Dirichlet Allocation, which is commonly used for topic modelling in text analysis, but has recently been translated to the area of microbiome analysis [5].
Results: There were no systematic differences in alpha diversity at baseline associated with later SARS-CoV-2 infection. Further, beta diversity did not depict discernible patterns and principal coordinate axes did not explain any variation related to SARS-CoV-2 infection. Differential abundance as analysed by a triangulation approach of three methods did not detect any differentially abundant genera. Latent Dirichlet Allocation identified seven discernible sub-communities that shape the nasal microbial composition, with the three most dominant communities being characterized by high shares of the genera Corynebacterium, Staphylococcus and Cutibacterium, respectively. There were no structural differences in relative topic abundances related to SARS-CoV-2 infection.
Conclusion: Investigations of the baseline nasal microbiome revealed neither systematic differences in diversity nor in the abundance of individual genera that are directly associated with later SARS-CoV-2 infection. Probability of exposition was low during the first wave of the COVID-19 pandemic so that any possible differential susceptibility could only have a minimal effect. However, topic analysis revealed discernible sub-communities of co-abundant genera, which are characterized by known prevalent genera in the nasal cavity. Although the relative topic abundances showed no association with later SARS-CoV-2 infection, future investigation will focus on relating patterns in sub-communities to known risk factors of SARS-CoV-2 infection.
Acknowledgements: This project was conducted with data from the German National Cohort (NAKO). The NAKO is funded by BMBF [project funding reference numbers: 01ER1301A/B/C, 01ER1511D and 01ER1801A/B/C/D], federal states of Germany and the Helmholtz Association, the participating universities, and the institutes of the Leibniz Association. We thank all participants who took part in the NAKO study and the staff of this research initiative. SKB and NR were supported by the fund IMF (University of Münster Medical School, RÜ122010).
The authors declare that they have no competing interests.
The authors declare that a positive ethics committee vote has been obtained.
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