Table 1 Included studies examining the association between smoking and the oral microbiome
Author, year | Oral sample site | Aim | Population studied | Sequencing | Region if 16S | Citation |
|---|---|---|---|---|---|---|
Cigarette smokers | ||||||
Al-Zyoud et al., 2019 | Saliva | Investigate the shift in the salivary microbiota between smokers and non-smokers in Jordan | Nonsmoking subjects (n = 51), subjects who smoke (n = 49), total sample (n = 100) | 16S | V3–V4 | [37] |
Beghini et al., 2019 | Oral rinse | To evaluate the effect of tobacco exposure on the oral microbiome from oral rinse samples in the 2013–14 New York City Health and Nutrition Examination Study | Total sample (n = 259) | 16S | V4 | [43] |
Coretti et al., 2017 | Subgingival | Assess the subgingival microbiota in smoker patients with chronic periodontitis, non‑smoker patients with chronic periodontitis and healthy controls | Subjects with chronic periodontitis who smoke (n = 6), non‑smoker patients with chronic periodontitis (n = 6), nonsmoking subjects without periodontitis (n = 8), total sample (n = 20) | 16S | V3–V4 | [42] |
Duan et al., 2017 | Saliva | Studied the impact of smoking on the salivary microbiome and its further influence on marginal bone loss around an implant during a 3-month bone-healing period | Smokers (n = 10) and non-smokers (n = 10) presenting for single-tooth replacement, total sample (n = 20) | 16S | V4 | [39] |
Gaetti-Jardim, 2018 | Supra- and sub-gingival plaque | Aimed to evaluate the effects of conventional radiotherapy on the prevalence and populations of oral microorganisms in head and neck cancer patients who did not receive adequate preventive dental care | Subjects with head and neck cancer (n = 28) | Culture dependent | N/A | [56] |
Ganesan et al., 2017 | Subgingival plaque | Analyzed 16S sequences from non-smoking normoglycemic individuals (controls), smokers, diabetics and diabetic smokers with periodontitis, as well as periodontally healthy controls, smokers and diabetics to assess subgingival bacterial biodiversity and co-occurrence patterns | Normoglycemic non-smokers with periodontitis (n = 14), hyperglycemic non-smokers with periodontitis (n = 9), normoglycemic smokers with periodontitis (n = 16), and hyperglycemic smokers with periodontitis (n = 8), normoglycemic non-smokers without periodontitis (n = 14), hyperglycemic non-smokers without periodontitis (n = 12), normoglycemic smokers without periodontitis (n = 12), total sample (n = 175) | 16S | V1–V3; V7–V9 | [58] |
Gopinath et al., 2022 | Buccal swab | Investigate the compositional and functional attributes of the oral bacteriome of smokeless tobacco users and smokers relative to controls by 16S rRNA metagenomic sequencing in an Indian population | Smokers (n = 17), smokeless tobacco users (n = 14), age-matched non-smokers (n = 13), total sample (n = 44) | 16S | V3–V4 | [35] |
Hsiao et al., 2018 | Saliva | Investigated the association between oral bacterial profile and oral squamous cell carcinoma risk in a case–control study | Subjects with oral squamous cell carcinoma (n = 138), controls (n = 151), total sample (n = 289) | 16S | V3–V5 | [54] |
Jia et al., 2021 | Saliva | Improve our understanding of the impact of cigarette smoking on the oral microbiota in the Chinese population | Subjects from Guangdong Providence (n = 150), subjects from Yangquan city (n = 81), subjects from Mishan city (n = 85), total sample (n = 316) | 16S | V4 | [36] |
Karabudak et al., 2019 | Buccal swab | Investigate the effect of smoking on the buccal microbiome and to analyze the descriptive ability of each of the seven hypervariable regions in their 16S rRNA genes | Smokers (n = 20), non-smokers (n = 20), total sample (n = 40) | 16S | V2, V3, V4, V6–7, V8, V9 | [44] |
Karasneh et al., 2017 | Subgingival plaque | Investigate the impact of smoking on the subgingival bacterial profile in both healthy adults and chronic periodontitis patients | Subjects with chronic periodontitis (n = 37 non-smokers and n = 18 smokers), subjects without periodontitis (37 non-smokers and 18 smokers), total sample (n = 94) | 16S | V1–V9 | [59] |
Lin et al., 2019 | Saliva | Leveraged next generation sequencing for microbiome and functional neuroimaging to enable the delineation of microbiome-brain network links as well as their relationship to cigarette smoking | Smokers (n = 30), non-smokers (n = 30), total sample (n = 60) | 16S | V4 | [52] |
Mukherjee et al., 2018 | Oral rinse | Assessed the relationship of microbial dysbiosis with smoking and markers of human immunodeficiency virus disease | HIV-infected smokers (n = 48), HIV-infected non-smokers (n = 24), HIV-uninfected smokers (n = 24), total sample (n = 96) | 16S | V4 | [50] |
Murugesan et al., 2020 | Saliva | Characterize the salivary microbiome composition in the Qatari population, and to explore specific microbial signatures that can be associated with various lifestyles and different oral conditions | Total sample (n = 997) | 16S | V1–V3 | [40] |
Pushalkar et al., 2020* | Saliva | Evaluate the effects of e-cigarette aerosol and its influence on human salivary microbiome and immune health. Additionally, the authors evaluate the influence of e-cigarette aerosols on infection efficiency of oral pathogens in pre-cancerous and cancer cell lines using a novel e-cigarette aerosol-generating machine and pro-inflammatory immune mediators | Smokers (n = 40), never smokers (n = 39), e-cigarette users (n = 40), total sample (n = 119) | 16S | V3–V4 | [46] |
Renson et al., 2019 | Oral rinse | Describe sociodemographic variation of oral microbiomes in a subsample of the 2013–14 population-based New York City Health and Nutrition Examination Study | Total sample (n = 282) | 16S | V4 | [47] |
Rodríguez- Rabassa et al., 2018 | Saliva | Investigated the effects of cigarette smoking on bacterial diversity and host responses compared to non-smokers | Non-smokers (n = 16), current smokers (n = 18), total sample (n = 34) | 16S | V3–V4 | [51] |
Sato et al., 2020a | Tongue dorsum | Investigated the bacterial species composition in the tongue microbiome, as well as single-nucleotide variant profiles and gene content of these species, in never and current smokers by utilizing metagenomic sequences | Never smokers (n = 234), current smokers (n = 52), total sample (n = 286) | Shotgun metagenomic sequencing | N/A | [55] |
Sato et al., 2020b | Tongue dorsum | Used 16S rRNA amplicon sequencing of tongue-coating samples obtained from East Asian subjects who were current, former, or never smokers to identify differences in their tongue microbiomes and related metagenomic functions | Never smokers (n = 384), former smokers (n = 129), current smokers (n = 144), total sample (n = 657) | 16S | V3–V4 | [41] |
Shay et al., 2020 | Oral rinse | Characterize the bacteriome, mycobiome and mycobiome-bacteriome interactions of oral wash samples in head and neck squamous cell carcinoma patients and to determine if they are distinct from those of the oral wash of matched non-head and neck squamous cell carcinoma patients | Subjects with head and neck squamous cell carcinoma (n = 46), subjects without cancer (n = 46), total sample (n = 92) | 16S | V1–V2 | [49] |
Suzuki et al., 2022 | Saliva and tongue dorsum | Investigated the differences in the microbial composition of the tongue directly exposed to cigarette smoke in smokers with that of nonsmokers | Saliva (n = 47) and tongue dorsum (n = 50) samples of healthy volunteers, total sample (n = 50) | 16S | V3–V4 | [45] |
Thomas et al., 2014 | Oral biofilm/whole mouth swab | Investigate the effects of the chronic use of alcohol and tobacco over the oral microbiome, in terms of diversity and composition, using 16S rRNA gene sequencing | Subjects with no alcohol or tobacco consumption (n = 9); subjects with heavy alcohol and tobacco consumption (n = 7), subjects who smoke but do not consume alcohol (n = 6), total sample (n = 22) | 16S | V1 | [38] |
Vallès et al., 2018 | Oral rinse | Compared the effects of cigarette, dokha and shisha use on community composition of the oral microbiome by high-throughput sequencing of the bacterial 16S rRNA gene in 330 participants from the “UAE Healthy Future” pilot study | Subjects who smoke (n = 105), subjects who do not smoke (n = 225), total sample (n = 330) | 16S | V4 | [34] |
Wolff et al., 2019 | Supragingival plaque | Study patterns in pathogenic biofilm composition to characterize the oral microbiome present in tooth surfaces with and without caries. Smoking and socio-economic status were studied as exploratory variables | Total sample (n = 56) | 16S | V4 | [57] |
Yeo et al., 2019 | Saliva | Address the gap in knowledge by reporting on the anthropometrics and cardiometabolic health of a resettled Temiar community and investigated their saliva microbiome in association with their health | Total sample (n = 72) | 16S | V3–V4 | [53] |
Yeoh et al., 2019 | Oral rinse | Collected oral rinse samples from patients showing symptoms of acute tonsillitis and compared their oral cavity microbial community composition to healthy individuals without oral disease | Healthy (n = 165), tonsillitis (n = 43), total sample (n = 208) | 16S | V3–V4 | [48] |
E-cigarette smokers | ||||||
Ganesan et al., 2020 | Subgingival plaque | Investigate the effects of e-cigarettes on the subgingival microbiome using complementary approaches to achieve comprehensive insights into community assembly, dynamics, and function, as well as the impact of this community on the host’s immunoinflammatory response | Smokers (n = 25), non-smokers (n = 25), e-cigarette users (n = 20), former smokers currently using e-cigarettes (n = 25), concomitant cigarette and e-cigarette users (n = 28), total sample (n = 123) | Shotgun metagenomic sequencing | N/A | [15] |
Pushalkar, 2020* | Saliva | Study the in vivo effects of e-cigarette aerosol and its influence Additionally, the authors evaluated the influence of e-cigarette aerosols on infection efficiency of oral pathogens in pre-cancerous and cancer cell lines using a novel e-cigarette aerosol-generating machine and pro-inflammatory immune mediators | Smokers (n = 40), never smokers (n = 39), e-cigarette users (n = 40), total sample (n = 119) | 16S | V3–V4 | [46] |