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Seneviratne CJ, Balan P, Suriyanarayanan T, Lakshmanan M, Lee DY, Rho M, Jakubovics N, Brandt B, Crielaard W, Zaura E. Oral microbiome-systemic link studies: perspectives on current limitations and future artificial intelligence-based approaches. Crit Rev Microbiol 2020; 46:288-299. [PMID: 32434436 DOI: 10.1080/1040841x.2020.1766414] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
In the past decade, there has been a tremendous increase in studies on the link between oral microbiome and systemic diseases. However, variations in study design and confounding variables across studies often lead to inconsistent observations. In this narrative review, we have discussed the potential influence of study design and confounding variables on the current sequencing-based oral microbiome-systemic disease link studies. The current limitations of oral microbiome-systemic link studies on type 2 diabetes mellitus, rheumatoid arthritis, pregnancy, atherosclerosis, and pancreatic cancer are discussed in this review, followed by our perspective on how artificial intelligence (AI), particularly machine learning and deep learning approaches, can be employed for predicting systemic disease and host metadata from the oral microbiome. The application of AI for predicting systemic disease as well as host metadata requires the establishment of a global database repository with microbiome sequences and annotated host metadata. However, this task requires collective efforts from researchers working in the field of oral microbiome to establish more comprehensive datasets with appropriate host metadata. Development of AI-based models by incorporating consistent host metadata will allow prediction of systemic diseases with higher accuracies, bringing considerable clinical benefits.
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Affiliation(s)
- Chaminda Jayampath Seneviratne
- Singapore Oral Microbiomics Initiative (SOMI), National Dental Research Institute Singapore, National Dental Centre Singapore, Duke NUS Medical School, Singapore, Singapore
| | - Preethi Balan
- Singapore Oral Microbiomics Initiative (SOMI), National Dental Research Institute Singapore, National Dental Centre Singapore, Duke NUS Medical School, Singapore, Singapore
| | - Tanujaa Suriyanarayanan
- Singapore Oral Microbiomics Initiative (SOMI), National Dental Research Institute Singapore, National Dental Centre Singapore, Duke NUS Medical School, Singapore, Singapore
| | - Meiyappan Lakshmanan
- Bioprocessing Technology Institute (BTI), ASTAR - Agency for Science, Technology and Research, Singapore, Singapore
| | - Dong-Yup Lee
- Bioprocessing Technology Institute (BTI), ASTAR - Agency for Science, Technology and Research, Singapore, Singapore.,School of Chemical Engineering, Sungkyunkwan University, Jongno-gu, Republic of Korea
| | - Mina Rho
- Departments of Computer Science and Engineering & Biomedical Informatics, Hanyang University, Seoul, Korea
| | - Nicholas Jakubovics
- Oral Biology, School of Dental Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Bernd Brandt
- Department of Preventive Dentistry, Academic Centre for Dentistry Amsterdam, University of Amsterdam and Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Wim Crielaard
- Department of Preventive Dentistry, Academic Centre for Dentistry Amsterdam, University of Amsterdam and Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Egija Zaura
- Department of Preventive Dentistry, Academic Centre for Dentistry Amsterdam, University of Amsterdam and Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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Ramadugu K, Blostein F, Bhaumik D, Jiang W, Davis E, Salzman E, Srinivasan U, Marrs CF, Neiswanger K, McNeil DW, Marazita ML, Foxman B. Co-occurrence of yeast, streptococci, dental decay, and gingivitis in the post-partum period: results of a longitudinal study. J Oral Microbiol 2020; 12:1746494. [PMID: 32363007 PMCID: PMC7178893 DOI: 10.1080/20002297.2020.1746494] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Revised: 03/10/2020] [Accepted: 03/16/2020] [Indexed: 12/30/2022] Open
Abstract
Objective: The interactions between yeast and streptococci species that lead to dental decay and gingivitis are poorly understood. Our study describes these associations among a cohort of 101 post-partum women enrolled in the Center for Oral Health Research in Appalachia, 2012–2013. Methods: All eligible women without dental caries were included (n = 21) and the remainder were randomly sampled to represent the total number of decayed, missing, and filled teeth (DMFT) at enrollment. We used amplicon sequencing and qPCR of saliva from 2, 6, 12 and 24 visits to determine microbiome composition. Results: Active decay and generalized gingivitis were strongly predictive of each other. Using adjusted marginal models, Candida albicans and Streptococcus mutans combined were associated with active decay (OR = 3.13; 95% CI 1.26, 7.75). However, C. albicans alone (OR = 2.33; 95% CI: 0.81, 6.75) was associated with generalized gingivitis, but S. mutans alone was not (OR = 0.55; 95% CI: 0.21, 1.44). Models including microbiome community state types (CSTs) showed CSTs positively associated with active decay were negatively associated with generalized gingivitis. Discussion: C. albicans is associated with active decay and generalized gingivitis, but whether one or both are present depends on the structure of the co-existing microbial community.
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Affiliation(s)
- Kirtana Ramadugu
- Center for Molecular and Clinical Epidemiology of Infectious Diseases, University of Michigan School of Public Health Department of Epidemiology, Ann Arbor, MI, USA
| | - Freida Blostein
- Center for Molecular and Clinical Epidemiology of Infectious Diseases, University of Michigan School of Public Health Department of Epidemiology, Ann Arbor, MI, USA
| | - Deesha Bhaumik
- Center for Molecular and Clinical Epidemiology of Infectious Diseases, University of Michigan School of Public Health Department of Epidemiology, Ann Arbor, MI, USA
| | - Wenwen Jiang
- Center for Molecular and Clinical Epidemiology of Infectious Diseases, University of Michigan School of Public Health Department of Epidemiology, Ann Arbor, MI, USA
| | - Elyse Davis
- Center for Molecular and Clinical Epidemiology of Infectious Diseases, University of Michigan School of Public Health Department of Epidemiology, Ann Arbor, MI, USA
| | - Elizabeth Salzman
- Center for Molecular and Clinical Epidemiology of Infectious Diseases, University of Michigan School of Public Health Department of Epidemiology, Ann Arbor, MI, USA
| | - Usha Srinivasan
- Center for Molecular and Clinical Epidemiology of Infectious Diseases, University of Michigan School of Public Health Department of Epidemiology, Ann Arbor, MI, USA
| | - Carl F Marrs
- Center for Molecular and Clinical Epidemiology of Infectious Diseases, University of Michigan School of Public Health Department of Epidemiology, Ann Arbor, MI, USA
| | - Katherine Neiswanger
- Center for Craniofacial and Dental Genetics, Department of Oral Biology, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, USA.,Center for Oral Health Research in Appalachia, University of Pittsburgh, Pittsburgh, Pennsylvania, USA, and West Virginia University, Morgantown, West Virginia, USA
| | - Daniel W McNeil
- Center for Oral Health Research in Appalachia, University of Pittsburgh, Pittsburgh, Pennsylvania, USA, and West Virginia University, Morgantown, West Virginia, USA.,Departments of Psychology and Dental Practice & Rural Health, West Virginia University, Morgantown, WV, USA
| | - Mary L Marazita
- Center for Craniofacial and Dental Genetics, Department of Oral Biology, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, USA.,Center for Oral Health Research in Appalachia, University of Pittsburgh, Pittsburgh, Pennsylvania, USA, and West Virginia University, Morgantown, West Virginia, USA.,Department of Human Genetics, Graduate School of Public Health; and Clinical and Translational Sciences Institute, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Betsy Foxman
- Center for Molecular and Clinical Epidemiology of Infectious Diseases, University of Michigan School of Public Health Department of Epidemiology, Ann Arbor, MI, USA.,Center for Oral Health Research in Appalachia, University of Pittsburgh, Pittsburgh, Pennsylvania, USA, and West Virginia University, Morgantown, West Virginia, USA.,Departments of Psychology and Dental Practice & Rural Health, West Virginia University, Morgantown, WV, USA
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53
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The Sex-Gender Effects in the Road to Tailored Botanicals. Nutrients 2019; 11:nu11071637. [PMID: 31319627 PMCID: PMC6682902 DOI: 10.3390/nu11071637] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2019] [Revised: 07/10/2019] [Accepted: 07/10/2019] [Indexed: 12/17/2022] Open
Abstract
Phenols are a wide family of phytochemicals that are characterized by large chemical diversity and are considered to bioactive molecules of foods, beverages, and botanicals. Although they have a multitude of biological actions, their beneficial effects are rarely evidenced in clinical research with high scientific rigor. This may occur due to the presence of numerous confounders, such as the modulation of phenol bioavailability, which can be regulated by microbiota, age, sex-gender. Sex-gender is an important determinant of health and well-being, and has an impact on environmental and occupational risks, access to health care, disease prevalence, and treatment outcomes. In addition, xenobiotic responses may be strongly influenced by sex-gender. This review describes how sex–gender differentially influences the activities of phenols also in some critical periods of women life such as pregnancy and lactation, considering also the sex of fetuses and infants. Thus, sex–gender is a variable that must be carefully considered and should be used to propose directions for future research on the road to tailored medicine and nutrition.
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