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Liu Y, Méric G, Havulinna AS, Teo SM, Åberg F, Ruuskanen M, Sanders J, Zhu Q, Tripathi A, Verspoor K, Cheng S, Jain M, Jousilahti P, Vázquez-Baeza Y, Loomba R, Lahti L, Niiranen T, Salomaa V, Knight R, Inouye M. Early prediction of incident liver disease using conventional risk factors and gut-microbiome-augmented gradient boosting. Cell Metab 2022; 34:719-730.e4. [PMID: 35354069 PMCID: PMC9097589 DOI: 10.1016/j.cmet.2022.03.002] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 01/06/2022] [Accepted: 03/08/2022] [Indexed: 02/08/2023]
Abstract
The gut microbiome has shown promise as a predictive biomarker for various diseases. However, the potential of gut microbiota for prospective risk prediction of liver disease has not been assessed. Here, we utilized shallow shotgun metagenomic sequencing of a large population-based cohort (N > 7,000) with ∼15 years of follow-up in combination with machine learning to investigate the predictive capacity of gut microbial predictors individually and in conjunction with conventional risk factors for incident liver disease. Separately, conventional and microbial factors showed comparable predictive capacity. However, microbiome augmentation of conventional risk factors using machine learning significantly improved the performance. Similarly, disease-free survival analysis showed significantly improved stratification using microbiome-augmented models. Investigation of predictive microbial signatures revealed previously unknown taxa for liver disease, as well as those previously associated with hepatic function and disease. This study supports the potential clinical validity of gut metagenomic sequencing to complement conventional risk factors for prediction of liver diseases.
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Affiliation(s)
- Yang Liu
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia; Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, Australia.
| | - Guillaume Méric
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia; Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, Australia; Baker Department of Cardiometabolic Health, The University of Melbourne, Melbourne, VIC, Australia; Department of Infectious Diseases, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Aki S Havulinna
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland; Institute of Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Shu Mei Teo
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia; Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Fredrik Åberg
- Transplantation and Liver Surgery Clinic, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
| | - Matti Ruuskanen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland; Department of Internal Medicine, University of Turku, Turku, Finland
| | - Jon Sanders
- Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Qiyun Zhu
- Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Anupriya Tripathi
- Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA, USA; Division of Biological Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Karin Verspoor
- School of Computing and Information Systems, University of Melbourne, Melbourne, VIC, Australia; School of Computing Technologies, RMIT University, Melbourne, VIC, Australia
| | - Susan Cheng
- Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Mohit Jain
- Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA, USA; Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA
| | - Pekka Jousilahti
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Yoshiki Vázquez-Baeza
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA; Department of Computer Science & Engineering, Jacobs School of Engineering, University of California, San Diego, La Jolla, CA, USA
| | - Rohit Loomba
- NAFLD Research Center, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Leo Lahti
- Department of Computing, University of Turku, Turku, Finland
| | - Teemu Niiranen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland; Department of Internal Medicine, University of Turku, Turku, Finland; Division of Medicine, Turku University Hospital, Turku, Finland
| | - Veikko Salomaa
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Rob Knight
- Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA, USA; Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA; Department of Computer Science & Engineering, Jacobs School of Engineering, University of California, San Diego, La Jolla, CA, USA
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia; Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, Australia; Baker Department of Cardiometabolic Health, The University of Melbourne, Melbourne, VIC, Australia; Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK; Health Data Research UK Cambridge, Wellcome Genome Campus, University of Cambridge, Cambridge, UK; British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK; British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK; The Alan Turing Institute, London, UK.
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Hsiao YC, Lee YH, Ho CM, Tseng CH, Wang JH. Clinical Characteristics of Actinomyces viscosus Bacteremia. ACTA ACUST UNITED AC 2021; 57:medicina57101064. [PMID: 34684101 PMCID: PMC8537041 DOI: 10.3390/medicina57101064] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 09/21/2021] [Accepted: 09/27/2021] [Indexed: 11/16/2022]
Abstract
Background and Objectives: Actinomyces species are part of the normal flora of humans and rarely cause disease. It is an uncommon cause of disease in humans. The clinical features of actinomycosis have been described, and various anatomical sites (such as face, bones and joints, respiratory tract, genitourinary tract, digestive tract, central nervous system, skin, and soft tissue structures) can be affected. It is not easy to identify actinomycosis because it sometimes mimics cancer due to under-recognition. As new diagnostic methods have been applied, Actinomyces can now more easily be identified at the species level. Recent studies have also highlighted differences among Actinomyces species. We report a case of Actinomyces viscosus bacteremia with cutaneous actinomycosis. Materials and Methods: A 66 years old male developed fever for a day with progressive right lower-leg erythematous swelling. Blood culture isolates yielded Actinomyces species, which was identified as Actinomyces viscosus by sequencing of the 16S rRNA gene. In addition, we searched for the term Actinomyces or actinomycosis cross-referenced with bacteremia or "blood culture" or "blood stream" from January 2010 to July 2020. The infectious diseases caused by species of A. viscosus from January 1977 to July 2020 were also reviewed. Results: The patient recovered well after intravenous ampicillin treatment. Poor oral hygiene was confirmed by dental examination. There were no disease relapses during the following period. Most cases of actinomycosis can be treated with penicillin. However, clinical alertness, risk factor evaluation, and identification of Actinomyces species can prevent inappropriate antibiotic or intervention. We also compiled a total of 18 cases of Actinomyces bacteremia after conducting an online database search. Conclusions: In summary, we describe a case of fever and progressive cellulitis. Actinomyces species was isolated from blood culture, which was further identified as Actinomyces viscosus by 16S rRNA sequencing. The cellulitis improved after pathogen-directed antibiotics. Evaluation of risk factors in patients with Actinomyces bacteremia and further identification of the Actinomyces species are recommended for successful treatment.
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Affiliation(s)
- Yi-Chun Hsiao
- Department of Internal Medicine, Division of Infectious Diseases, Taichung Veterans General Hospital, Taichung 40705, Taiwan; (Y.-C.H.); (C.-M.H.); (C.-H.T.)
| | - Yi-Hsuan Lee
- Department of Post-Baccalaureate Veterinary Medicine, Asia University, Taichung 41354, Taiwan;
| | - Chun-Mei Ho
- Department of Internal Medicine, Division of Infectious Diseases, Taichung Veterans General Hospital, Taichung 40705, Taiwan; (Y.-C.H.); (C.-M.H.); (C.-H.T.)
| | - Chien-Hao Tseng
- Department of Internal Medicine, Division of Infectious Diseases, Taichung Veterans General Hospital, Taichung 40705, Taiwan; (Y.-C.H.); (C.-M.H.); (C.-H.T.)
| | - Jui-Hsing Wang
- Department of Internal Medicine, Division of Infectious Disease, Taichung Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Taichung 40705, Taiwan
- Department of Internal Medicine, School of Medicine, Buddhist Tzu Chi Medical Foundation Taichung Tzu Chi Hospital, Taichung 427213, Taiwan
- Correspondence:
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Evaluation of the Andromas matrix-assisted laser desorption ionization-time of flight mass spectrometry system for identification of aerobically growing Gram-positive bacilli. J Clin Microbiol 2012; 50:2702-7. [PMID: 22692743 DOI: 10.1128/jcm.00368-12] [Citation(s) in RCA: 99] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023] Open
Abstract
Matrix-associated laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is a rapid and simple microbial identification method. Previous reports using the Biotyper system suggested that this technique requires a preliminary extraction step to identify Gram-positive rods (GPRs), a technical issue that may limit the routine use of this technique to identify pathogenic GPRs in the clinical setting. We tested the accuracy of the MALDI-TOF MS Andromas strategy to identify a set of 659 GPR isolates representing 16 bacterial genera and 72 species by the direct colony method. This bacterial collection included 40 C. diphtheriae, 13 C. pseudotuberculosis, 19 C. ulcerans, and 270 other Corynebacterium isolates, 32 L. monocytogenes and 24 other Listeria isolates, 46 Nocardia, 75 Actinomyces, 18 Actinobaculum, 11 Propionibacterium acnes, 18 Propionibacterium avidum, 30 Lactobacillus, 21 Bacillus, 2 Rhodococcus equi, 2 Erysipelothrix rhusiopathiae, and 38 other GPR isolates, all identified by reference techniques. Totals of 98.5% and 1.2% of non-Listeria GPR isolates were identified to the species or genus level, respectively. Except for L. grayi isolates that were identified to the species level, all other Listeria isolates were identified to the genus level because of highly similar spectra. These data demonstrate that rapid identification of pathogenic GPRs can be obtained without an extraction step by MALDI-TOF mass spectrometry.
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