Skip to main content
NCBI home page
International Dental Journal logoLink to International Dental Journal
. 2024 Mar 7;74(4):696–704. doi: 10.1016/j.identj.2024.02.007

Genetic Connectivity of Gut Microbiota and Oral Ulcers: A Mendelian Randomization Study

Bilun Jin a,b,c,#, Pengfei Wang d,#, Peiqi Liu a,b,c, Yijie Wang a,b,c, Yi Guo a,b,c, Chenxu Wang a,b,c, Yue Jia a,b,c, Rui Zou a,b,c, Lin Niu a,b,c,⁎
PMCID: PMC11287153  PMID: 38458846

Abstract

Objectives

The aim of this study was to reveal the relationship, if any, between gut microbiota and oral ulcers.

Methods

We performed a 2-sample Mendelian randomization (MR) study to estimate the roles of gut microbiota in mouth ulcers. The summary datasets of gut microbiota were from the largest genome-wide association study (GWAS) conducted by MiBioGen, and data of mouth ulcers were obtained from UK Biobank. Random effect inverse variance-weighted, weighted median, MR Egger, simple mode and weighted mode were used to estimate the relationship. Sensitivity analyses were conducted to assess the heterogeneity and pleiotropy of instrumental variables. MR Steiger filtering was also applied to orient the causal direction.

Results

Three gut microbiota taxa were positively associated with mouth ulcers: Holdemania (odds ratio [OR] = 1.005, 95% confidence interval [CI]: 1.001-1.009, P = .019), Oxalobacter (OR = 1.004, 95% CI: 1.000-1.007, P = .032), and Ruminococcaceae UCG011 (OR = 1.006, 95% CI: 1.001-1.011, P = .029), while 4 gut microbiota taxa were negatively associated with mouth ulcers: Actinobacteria (OR = 0.992, 95% CI: 0.985-1.000, P = .042), Lactobacillales (OR = 0.995, 95% CI: 0.990-1.000, P = .034), Oscillospira (OR = 0.990, 95% CI: 0.984-0.997, P = .007) and Phascolarctobacterium (OR = 0.992, 95% CI: 0.986-0.997, P = .003). Sensitivity analyses validated the robustness of the association in between.

Conclusions

This MR study identified a strong association between the quality of gut microbiota and oral ulcers. The findings are likely to expand the therapeutic targets for mouth ulcers.

Key words: Microbiome, Oral-gut axis, Mucosal lesions, Probiotics, Mendelian randomization

Introduction

Mouth ulcers are mucosal lesions with persistent defects in the epithelium and connective tissue.1,2 This oral disease occurs frequently in the global population with a prevalence of up to 66%.3 In many cases, mouth ulcers heal on their own, but their presence can cause intolerable pain and negatively affect the oral functions.4 The aetiology of mouth ulcers varies from genetics, diet, lifestyle, medications and even systemic diseases.5 So far, the complicated causations of mouth ulcers have not been determinate. As a result, there is no effective treatment available.6

The gut microbiome refers to trillions of bacteria settled in the intestinal tract of mammals. Targeting the gut microbiota has been a promising strategy to prevent and treat inflammatory diseases.7 Some studies have indicated the pivotal role of gut microbiota in treating mouth ulcers. An animal experiment showed that antibiotic-induced microbiota depletion altered the composition of gut microbiota and reduced the size of tongue ulcers in rats that had been treated with radiation.8 Gavage of live and heat-killed J-12 bacteria regulated the abundance of gut microbiota and alleviated the formation of oral ulcers in LVG golden Syrian hamsters.9 Probiotics were also proposed as a direct therapy for inflammatory bowel diseases and as an indirect therapy for aphthous-like ulcers in the oral cavity.10 However, some limitations remained in those studies. Firstly, it is difficult to draw unified conclusions because of the high heterogeneity among different studies. Secondly, small sample sizes, due to cost saving, result in less convincing results. Finally, confounding factors make it hard to identify the real association.

Mendelian randomization (MR) relies on the principle that genotypes are randomly assigned at gamete formation. Genotypes are generally independent of confounders and disease processes.11 MR selects single nucleotide polymorphisms (SNPs) as instrumental variables (IVs) and simulates randomized controlled trials.12 MR analysis has been performed to search the causal effects between gut microbiota and preeclampsia-eclampsia,13 cancers,14 autoimmune diseases15 and so on. It is a rational method to assess the association between gut microbiota and mouth ulcers.

Given the unclear connection between gut microbiota and mouth ulcers, we conducted a 2-sample MR analysis utilizing the genome-wide association study (GWAS) from the MiBioGen as the exposure and datasets from UK Biobank (UKB) as the outcome. The MiBioGen consortium created a large dataset based on the analysis of genome-wide genotype and 16S faecal microbiome data. The dataset included a total of 18,340 individuals participating in 24 different cohorts, mainly European (16 cohorts, N = 13,266).16 UKB is a large prospective study that includes 500,000 volunteers aged 40 to 69 years in England, Wales and Scotland, and is an important resource for public health research.17 To enhance the credibility of our findings, sensitivity analyses were also applied. The aim of this study was to illuminate the relationship between gut microbiota and mouth ulcers, and to identify the role of specific microbiota taxa in mouth ulcers. Our results uncovered novel gut microbiota taxa associated with mouth ulcers, providing a potential new perspective on the clinical management of the common oral lesions.

Materials and methods

Study design

Our study performed a 2-sample MR analysis to reveal the association between gut microbiota and mouth ulcers. The workflow diagram is presented in Figure 1. This MR study was based on 3 key assumptions. Firstly, the IVs must be associated with gut microbiota significantly. Secondly, the IVs should not be associated with confounders. Thirdly, the IVs should only affect mouth ulcers through gut microbiota. The MR analysis was based on publicly available GWAS data, and ethical approval and informed consent were obtained in the original studies.

Fig. 1.

Fig 1

Open in a new tab

Schematic illustration of the relationship between gut microbiota and mouth ulcers through MR analyses. The 196 taxa of gut microbiota served as exposure, and mouth ulcers served as the outcome. Single nucleotide polymorphisms selected from the GWAS of gut microbiota served as instrumental variables (IVs). Tumour, chronic inflammatory gastrointestinal diseases, autoimmune diseases, and deficiencies of B-vitamins or trace elements were identified as confounders in this study. The results showed 7 taxa were identified as taxa associated with mouth ulcers. The MR study should meet 3 assumptions in the illustration: A, The IVs must be associated with gut microbiota significantly. B, The IVs should not be associated with confounders. C, The IVs should only affect mouth ulcers through gut microbiota. Note: MR, Mendelian randomization.

GWAS data of gut microbiota

GWAS data of gut microbiota were obtained from the largest scale study on human gut microbiome composition supported by the MiBioGen consortium.16 The large-scale association analyses have adjusted for sex, age, and genetic principal components. After eliminating 15 unknown taxa, totally 196 taxa of gut microbiota were recognized as the exposure, including 119 genera, 32 families, 20 orders, 16 classes, and 9 phyla.16

GWAS data of mouth ulcers

GWAS data of mouth ulcers were from UKB which covered 47,102 cases and 414,011 control subjects (ID: ukb-b-6458). The questionnaire from UKB identified mouth ulcers based on a question (Do you have any of the following in the past years? Mouth ulcers?). Touchscreen questionnaires were used to capture field 6149 in the UK Biobank Assessment Centre using the ACE system.

Instrumental variables selection

In order to satisfy 3 essential assumptions of MR studies, we set some criteria: Firstly, SNPs should be associated with gut microbiota at the locus-wide significance level (P < 1 × 10−5).13 All candidate SNPs were listed in Supplementary Table S1. Secondly, the linkage disequilibrium (LD) coefficient r2 should be less than 0.001 in a 10,000-kb window. Thirdly, the R2 and F statistics were calculated to avoid bias from weak instruments. SNPs with F <10 or minor allele frequency ≤0.01 should be removed. Fourthly, palindromic SNPs should be excluded. Ultimately, the PhenoScanner tool was used to check whether any of the SNPs was associated with potential confounders at the risk of mouth ulcers. We set genome-wide significance (P < 5 × 10−8) as the threshold. In this study, tumour, chronic inflammatory gastrointestinal diseases, autoimmune diseases, and deficiencies of B-vitamins or trace elements were identified as potential confounders.18,19

Statistical analysis

In this MR study, we used random effect inverse variance-weighted (IVW) as the main analysis. IVW was the most robust MR analysis and had capacity of error-tolerance with heterogeneity. Considering that pleiotropy may contribute to an inflation in estimates and vacillate the true causality, we turned to the weighted median and MR Egger to select relevant gut bacterial taxa.20,21 Subsequently, other 2 robust methods, the simple mode and the weighted mode, were utilized to further validate the association between relative taxa and mouth ulcers.

Sensitivity analyses were performed to identify heterogeneity and pleiotropy in significant results. We used the Cochran's Q test, funnel plots and the leave-one-out sensitivity analysis to evaluate the heterogeneity of IVs.22 The MR Egger intercept and MR-PRESSO global test (Mendelian randomization pleiotropy residual sum and outlier) were conducted to identify potential horizontal pleiotropic effects of IVs.21,23 In addition, we performed the MR Steiger test to orient the causal direction between gut microbiota and mouth ulcers because this MR study aimed to certificate some novel targets among 196 microbiota taxa to treat mouth ulcers.24 A “TRUE” MR Steiger result suggested that the causal association is expected, while a “FALSE” result suggested the reverse causality.

All data were analysed by R (Version 3.1.5), combined with R packages “TwoSampleMR” and “MR-PRESSO.” A value of P < .05 was considered to be statistically significant.

Results

An overview of IVs in taxa

Through screening the significance threshold (P < 1 × 10−5), LD test, harmonizing, MR-PRESSO test and verifying F statistics and MAF, each of 196 bacterial taxa got multiple SNPs as corresponding IVs. IVs and details of significant associated taxa were listed in Supplementary Table S2.

Associations of gut bacterial taxa with mouth ulcers

As shown in Figure 2 and Table 1, 7 gut microbiota taxa had strong association with mouth ulcers. We found that 3 gut microbiota taxa were positively associated with mouth ulcers: the genus Holdemania (OR = 1.005, 95% CI: 1.001-1.009, P = .019), the genus Oxalobacter (OR = 1.004, 95% CI: 1.000-1.007, P = .032), and the genus Ruminococcaceae UCG011 (OR = 1.006, 95% CI: 1.001-1.011, P = .029). The associations remained directionally consistent in other MR methods, although with wider confidence intervals (Figure 3).

Fig. 2.

Fig 2

Open in a new tab

Preliminary MR analyses for the associations between gut microbiota and mouth ulcers. Note: MR, Mendelian randomization; IVW, inverse variance-weighted.

Table 1.

MR estimates for the association between gut microbiota and mouth ulcers.

Taxa MR method SNP OR 95% CI P-value F-statistic
class.Actinobacteria Inverse variance weighted 18 0.992 (0.985, 1.000) .042 28.579
class.Actinobacteria MR Egger 18 0.969 (0.949, 0.988) .007
class.Actinobacteria Weighted median 18 0.995 (0.986, 1.003) .223
class.Actinobacteria Simple mode 18 1.001 (0.984, 1.018) .915
class.Actinobacteria Weighted mode 18 1.000 (0.980, 1.020) .978
order.Lactobacillales Inverse variance weighted 19 0.995 (0.990, 1.000) .034 26.982
order.Lactobacillales MR Egger 19 0.993 (0.981, 1.005) .276
order.Lactobacillales Weighted median 19 0.994 (0.987, 1.001) .119
order.Lactobacillales Simple mode 19 0.994 (0.980, 1.007) .364
order.Lactobacillales Weighted mode 19 0.991 (0.980, 1.003) .164
genus.Holdemania Inverse variance weighted 18 1.005 (1.001, 1.009) .019 24.502
genus.Holdemania MR Egger 18 1.001 (0.989, 1.014) .816
genus.Holdemania Weighted median 18 1.005 (0.999, 1.011) .076
genus.Holdemania Simple mode 18 1.002 (0.991, 1.013) .766
genus.Holdemania Weighted mode 18 1.002 (0.992, 1.012) .727
genus.Oscillospira Inverse variance weighted 9 0.990 (0.984, 0.997) .007 21.445
genus.Oscillospira MR Egger 9 0.995 (0.964, 1.027) .762
genus.Oscillospira Weighted median 9 0.991 (0.981, 0.999) .038
genus.Oscillospira Simple mode 9 0.983 (0.968, 0.999) .071
genus.Oscillospira Weighted mode 9 0.986 (0.972, 1.001) .102
genus.Oxalobacter Inverse variance weighted 12 1.004 (1.000, 1.007) .032 26.887
genus.Oxalobacter MR Egger 12 1.001 (0.986, 1.016) .924
genus.Oxalobacter Weighted median 12 1.003 (0.998, 1.007) .276
genus.Oxalobacter Simple mode 12 1.000 (0.991, 1.009) .982
genus.Oxalobacter Weighted mode 12 1.000 (0.992, 1.009) .913
genus.Phascolarctobacterium Inverse variance weighted 12 0.992 (0.986, 0.997) .003 23.836
genus.Phascolarctobacterium MR Egger 12 0.988 (0.967, 1.009) .270
genus.Phascolarctobacterium Weighted median 12 0.992 (0.985, 0.999) .020
genus.Phascolarctobacterium Simple mode 12 0.991 (0.979, 1.003) .170
genus.Phascolarctobacterium Weighted mode 12 0.991 (0.980, 1.002) .135
genus.Ruminococcaceae UCG011 Inverse variance weighted 8 1.006 (1.001, 1.011) .029 23.340
genus.Ruminococcaceae UCG011 MR Egger 8 1.012 (0.985, 1.040) .434
genus.Ruminococcaceae UCG011 Weighted median 8 1.004 (0.999, 1.010) .133
genus.Ruminococcaceae UCG011 Simple mode 8 1.011 (1.000, 1.023) .094
genus.Ruminococcaceae UCG011 Weighted mode 8 0.999 (0.989, 1.010) .901
Open in a new tab

Fig. 3.

Fig 3

Open in a new tab

Forest plot of Mendelian randomization estimates between gut microbiota and mouth ulcers via IVW. Note: CI, confidence interval; OR, odds ratio; SNP, the single nucleotide polymorphism.

On the other hand, 4 gut microbiota taxa were negatively associated with mouth ulcers: the class Actinobacteria (OR = 0.992, 95% CI: 0.985-1.000, P = .042), the order Lactobacillales (OR = 0.995, 95% CI: 0.990-1.000, P = .034), the genus Oscillospira (OR = 0.990, 95% CI: 0.984-0.997, P = .007) and the genus Phascolarctobacterium (OR = 0.992, 95% CI: 0.986-0.997, P = .003). The associations remained consistent in most supplementary analyses except some divergent results in the class Actinobacteria, which indicated a bias of genetic pleiotropy (Table 1, Figure 3 and Supplementary Figure S1).

Sensitivity analyses

The analysis for the class Actinobacteria (P Cochran's Q = 0.006) revealed heterogeneity. The results of MR Egger and MR-PRESSO global test also indicated the horizontal pleiotropic effect in the class Actinobacteria (P intercept = 0.025 and P MR-PRESSO global test = 0.007). No heterogeneity or horizontal pleiotropic was suggested in other taxa (Table 2). Thus, the estimates from MR Egger for the class Actinobacteria would be preferred (OR = 0.969, 95% CI: 0.949-0.988, P = .007).25

Table 2.

Sensitivity analyses for the pleiotropy and heterogeneity.

Taxa Heterogeneity
 Pleiotropy MR-PRESSO global test
P-value for Cochran's Q Cochran's Q statistic P-value for MR-Egger intercept
class.Actinobacteria .006 35.244 .025 0.007
order.Lactobacillales .643 15.278 .772 0.661
genus.Holdemania .355 18.554 .565 0.360
genus.Oscillospira .246 10.284 .780 0.611
genus.Oxalobacter .586 9.385 .689 0.611
genus.Phascolarctobacterium .990 3.085 .700 0.992
genus.Ruminococcaceae UCG011 .134 11.119 .065 0.171
Open in a new tab

The leave-one-out sensitivity showed no obvious difference in estimated effect after removing individual SNP and repeating the MR analysis (Supplementary Figure S2). SNPs distributed symmetrically in funnel plots, which indicated the estimates were unlikely to be influenced by biases (Supplementary Figure S3).

Discussion

In this study, a 2-sample MR analysis was performed to explore the roles of gut microbiota in oral ulcers. The summary statistics of gut microbiota were extracted from the largest GWAS conducted by the MiBioGen consortium, and the datasets of mouth ulcers were extracted from UK Biobank. The results showed that the class Actinobacteria, the order Lactobacillales, the genus Oscillospira and the genus Phascolarctobacterium were negatively associated with oral ulcers, while the genus Holdemania, the genus Oxalobacter, and the genus Ruminococcaceae UCG011 were positively associated with oral ulcers. To the best of our knowledge, this study is the first to reinforce the association between gut microbiota and oral ulcers via an MR analysis.

We revealed that Holdemania, Oxalobacter, and Ruminococcaceae UCG011 were positively associated with oral ulcers. Ruminococcaceae UCG011 appeared to be key pathogenic bacteria of oral ulcers. A previous study collected stool samples from patients who had been diagnosed with head and neck cancer and treated with radiotherapy or combined therapies. Enrichment of Ruminococcus was observed in patients with mouth ulcers severely interfering with oral intake.26 Holdemania and Oxalobacter are the first 2 genera reported to be positively associated with oral ulcers. They have been observed to increase in several inflammatory responses. Upregulation of Holdemania was observed in faeces of mice with colitis caused by dextran sulfate sodium.27 Patients with chronic alcohol overconsumption had a higher abundance of Holdemania in gut microbiota.28 Lipopolysaccharide could increase the expression of proinflammatory cytokines and the abundance of Oxalobacter in cecal contents of piglets.29 The findings of the current study provide some suggestive evidence that Holdemania, Oxalobacter, and Ruminococcaceae UCG011 may be considered as targets for the treatment of oral ulcers. Nevertheless, further research is needed to understand the biological pathways.

Actinobacteria, Lactobacillales, Oscillospira, and Phascolarctobacterium were found to be negatively associated with a risk of oral ulcers. Our study suggested a potential protective effect of probiotics against oral ulcers, which was consistent with previous findings. Lactobacillus, as an active immunomodulator, has been one of the most promising probiotics.30 A metagenome-wide association study found that the abundance of Lactobacillus was significantly lower in the faecal samples from recurrent aphthous ulcer patients than in healthy people. Thalidomide could upregulate the abundance of Lactobacillus and ameliorate recurrent aphthous ulcers.31 Symbiotic treatment containing fructooligosaccharide, Lactobacillus, and Bifidobacterium was able to reduce pain in recurrent aphthous stomatitis patients.32 Besides, Oscillospira and Phascolarctobacterium are also recognized as probiotics. Healthy people have a higher number of Phascolarctobacterium in the gut compared to patients with Behcet's disease, who have a 97% to 100% risk of mouth ulcers.33, 34, 35 Oscillospira is also a well-known probiotic, and has been observed to be significantly reduced in the gut of patients with metabolic diseases or chronic inflammation related to obesity.36 The mechanisms involved in the protective effect of probiotics against mouth ulcers would be multifaceted. Probiotics modulate the systemic immune response by regulating immune cells such as dendritic cells and Treg lymphocytes.37 Probiotics can also decrease the serum levels of certain inflammatory factors (such as TNF-alpha, IL-6), and raise the levels of anti-inflammatory cytokines (such as IL-10).10,38,39 Furthermore, probiotics reduce the production of toxic metabolites from harmful gut microbiota, such as D-lactic acid and ethanol, by producing nontoxic L-lactic acid.40

Alterations in oral microbes may be another mechanism by which gut probiotics decrease the risk of mouth ulcers. Actinobacillus appears to be another beneficial gut flora for oral ulcers in our current study. Although limited research demonstrated that Actinobacillus is more abundant in the gut of normal people than mouth ulcer patients, Actinobacillus in oral mucosa has been observed to be less abundant in aphthous ulcer patients than normal population (P = .014, normal group 1.71%-3.35% and ulcer group 0.84%-1.75% at 95% CI).41 Indeed, oral microbes and gut microbiota were tightly linked through the “oral-gut” axis.42 Porphyromanus gingivalis was found to induce the specific Th17 cells in the gut. Then Th17 cells migrated to the oral cavity, disrupted oral microbes and exacerbated periodontitis.43 Oral microbiota dysbiosis is also an important reason for oral ulcers according to some.44 We presumed a similar mechanism by which gut microbiota influenced oral ulcers. Probiotics might activate immune cells in the gut. Subsequently, these immune cells could migrate to the site of the lesions, modulate the dysbiosis of oral microbiota and promote ulcer healing.

Oral ulcers can be caused by localized trauma, or systemic factors such as genetics, vitamin or trace element deficiencies, microbial factors, systemic diseases, lifestyle factors, radiotherapy and chemotherapy.45,46 Because of the complex aetiology of mouth ulcers, the current treatment of this disease is correspondingly divided into topical therapies and systemic therapies. Traditional topical treatments like mouthwash and gel only temporarily alleviate the pain as palliative. Nanofiber films have been recognized as an ideal choice to treat the lesions. However, its role in preventing relapse has not been fully evaluated.45 Systemic treatments could not only reduce symptoms but also delay the next recurrence. However, drugs used for systemic therapy inevitably produced some side effects, such as teratogenic defects and severe adverse effects of metabolic and endocrine.47 The novel findings in this study might expand the therapeutic targets for mouth ulcers. Some commercial products have been applied to reduce the risk of various diseases, such as diarrhea,48 gynaecological diseases49 and even cancer.50 In the future, faecal microbiota transplant and probiotic agents in lyophilized pills and foods might be optional methods in the prevention and treatment of oral ulcers.51,52

There are a number of strengths of study. Above all, MR analysis not only excluded spurious effects from confounders or reverse causality, but also drew a powerful conclusion without an expensive process based on large-scale genetic datasets. Then, MR Egger regression and the global test in MR-PRESSO were applied as sensitive methods to detect horizontal pleiotropy. In addition, MR Steiger filtering was implemented to verify the causal direction between gut microbiota and oral ulcers. However, some limitations should also be noted. Firstly, this MR study focused on the relationship between gut microbiota and mouth ulcers mainly in European populations. The findings may not be appropriate for other non-European groups. Secondly, genetic variants are sectional affecting factors of the gut microbiome. Some environmental factors such as diet, lifestyle, and medication use might affect the gut microbiota. These factors reduced the efficacy of MR estimates in this study. Thus, actual relationship between should be deduced prudently.53,54 Thirdly, there are various subtypes of mouth ulcers. But the questionnaire from UK Biobank identified mouth ulcers only based on a simple question if participants have mouth ulcers in the past years. It is difficult to distinguish detailed types of mouth ulcers. Finally, some gut microbiota taxa associated with mouth ulcers were never reported before. The potential mechanisms have been unclarified and need more experimental evidences.

Conclusions

To summarize, this MR study demonstrated the association between the quality of gut microbiota and oral ulcers in European populations. Specifically, Actinobacteria, Lactobacillales, Oscillospira, Phascolarctobacterium, Holdemania, Oxalobacter and Ruminococcaceae UCG011 were identified as taxa associated with oral ulcers. The findings are likely to expand the therapeutic targets for mouth ulcers.

Conflict of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

Acknowledgements

We thank UK Biobank and MRC-IEU for making the summary data publicly available. We are thankful to the investigators and participants contributed to those studies.

Author contributions

Bilun Jin: Conceptualization, Writing-Original draft. Pengfei Wang contributed equally to this work. Peiqi Liu: Validation, Data curation. Yijie Wang: Data curation, Resources. Yi Guo: Visualization, Software. Chenxu Wang: Investigation, Validation. Yue Jia: Validation, Investigation. Rui Zou: Data curation, Resources. Lin Niu: Writing-Review and Editing, Supervision.

Funding

This research work was supported by the National Natural Science Foundation of China (No.81970981), the Key Research and Development Project of Shaanxi Province (No.2023-YBSF-389).

Ethical approval

Ethical approval had been obtained in all original studies. All data generated during this study are included in this article and supplement materials.

Footnotes

Supplementary material associated with this article can be found in the online version at doi:10.1016/j.identj.2024.02.007.

Appendix. Supplementary materials

mmc1.docx (1.1MB, docx)
mmc2.xlsx (1.6MB, xlsx)

REFERENCES

  • 1.Zeng X, Jin X, Zhong L, et al. Difficult and complicated oral ulceration: an expert consensus guideline for diagnosis. Int J Oral Sci. 2022;14:28. doi: 10.1038/s41368-022-00178-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Siu A, Landon K, Ramos DM. Differential diagnosis and management of oral ulcers. Semin Cutan Med Surg. 2015;34:171–177. doi: 10.12788/j.sder.2015.0170. [DOI] [PubMed] [Google Scholar]
  • 3.Saikaly SK, Saikaly TS, Saikaly LE. Recurrent aphthous ulceration: a review of potential causes and novel treatments. J Dermatolog Treat. 2018;29:542–552. doi: 10.1080/09546634.2017.1422079. [DOI] [PubMed] [Google Scholar]
  • 4.Fitzpatrick SG, Cohen DM, Clark AN. Ulcerated lesions of the oral mucosa: clinical and histologic review. Head Neck Pathol. 2019;13:91–102. doi: 10.1007/s12105-018-0981-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Natah SS, Konttinen YT, Enattah NS, Ashammakhi N, Sharkey KA, Häyrinen-Immonen R. Recurrent aphthous ulcers today: a review of the growing knowledge. Int J Oral Maxillofac Surg. 2004;33:221–234. doi: 10.1006/ijom.2002.0446. [DOI] [PubMed] [Google Scholar]
  • 6.Gu Y, Huang Y, Qiu Z, et al. Vitamin B(2) functionalized iron oxide nanozymes for mouth ulcer healing. Sci China Life Sci. 2020;63:68–79. doi: 10.1007/s11427-019-9590-6. [DOI] [PubMed] [Google Scholar]
  • 7.Pickard JM, Zeng MY, Caruso R, Núñez G. Gut microbiota: role in pathogen colonization, immune responses, and inflammatory disease. Immunol Rev. 2017;279:70–89. doi: 10.1111/imr.12567. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Al-Qadami G, Verma G, Van Sebille Y, et al. Antibiotic-induced gut microbiota depletion accelerates the recovery of radiation-induced oral mucositis in rats. Int J Radiat Oncol Biol Phys. 2022;113:845–858. doi: 10.1016/j.ijrobp.2022.03.036. [DOI] [PubMed] [Google Scholar]
  • 9.Jing N, Liu F, Wang R, et al. Both live and heat-killed Bifidobacterium animalis J-12 alleviated oral ulcers in LVG golden Syrian hamsters by gavage by directly intervening in the intestinal flora structure. Food Funct. 2023;14:2045–2058. doi: 10.1039/d2fo03751c. [DOI] [PubMed] [Google Scholar]
  • 10.Cappello F, Rappa F, Canepa F, et al. Probiotics can cure oral aphthous-like ulcers in inflammatory bowel disease patients: a review of the literature and a working hypothesis. Int J Mol Sci. 2019;20:5026. doi: 10.3390/ijms20205026. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Davey Smith G, Hemani G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Hum Mol Genet. 2014;23:R89–R98. doi: 10.1093/hmg/ddu328. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Zheng J, Baird D, Borges MC, et al. Recent developments in Mendelian randomization studies. Curr Epidemiol Rep. 2017;4:330–345. doi: 10.1007/s40471-017-0128-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Li P, Wang H, Guo L, et al. Association between gut microbiota and preeclampsia-eclampsia: a two-sample Mendelian randomization study. BMC Med. 2022;20:443. doi: 10.1186/s12916-022-02657-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Long Y, Tang L, Zhou Y, Zhao S, Zhu H. Causal relationship between gut microbiota and cancers: a two-sample Mendelian randomisation study. BMC Med. 2023;21:66. doi: 10.1186/s12916-023-02761-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Xu Q, Ni JJ, Han BX, et al. Causal relationship between gut microbiota and autoimmune diseases: a two-sample mendelian randomization study. Front Immunol. 2021;12 doi: 10.3389/fimmu.2021.746998. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Kurilshikov A, Medina-Gomez C, Bacigalupe R, et al. Large-scale association analyses identify host factors influencing human gut microbiome composition. Nat Genet. 2021;53:156–165. doi: 10.1038/s41588-020-00763-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Conroy MC, Lacey B, Bešević J, et al. UK Biobank: a globally important resource for cancer research. Br J Cancer. 2023;128:519–527. doi: 10.1038/s41416-022-02053-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Taleb R, Hafez B, El Kassir N, El Achkar H, Mourad M. Role of vitamin B12 in treating recurrent aphthous stomatitis: a review. Int J Vitam Nutr Res. 2022;92:423–430. doi: 10.1024/0300-9831/a000684. [DOI] [PubMed] [Google Scholar]
  • 19.Samiraninezhad N, Kazemi H, Rezaee M, Gholami A. Effect of lactobacillus reuteri-derived probiotic nano-formulation on recurrent aphthous stomatitis: a double-blinded randomized clinical trial. BMC Oral Health. 2023;23:1019. doi: 10.1186/s12903-023-03756-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Bowden J, Davey Smith G, Haycock PC, Burgess S. Consistent estimation in Mendelian randomization with some invalid instruments using a weighted median estimator. Genet Epidemiol. 2016;40:304–314. doi: 10.1002/gepi.21965. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through egger regression. Int J Epidemiol. 2015;44:512–525. doi: 10.1093/ije/dyv080. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Hemani G, Zheng J, Elsworth B, et al. The MR-base platform supports systematic causal inference across the human phenome. Elife. 2018;7:e34408. doi: 10.7554/eLife.34408. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Yazdanpanah N, Yazdanpanah M, Wang Y, et al. Clinically relevant circulating protein biomarkers for type 1 diabetes: evidence from a two-sample Mendelian randomization study. Diabetes Care. 2022;45:169–177. doi: 10.2337/dc21-1049. [DOI] [PubMed] [Google Scholar]
  • 24.Hemani G, Tilling K, Davey Smith G. Orienting the causal relationship between imprecisely measured traits using GWAS summary data. PLoS Genet. 2017;13 doi: 10.1371/journal.pgen.1007081. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Sun X, Chen L, He Y, Zheng L. Circulating α-klotho levels in relation to cardiovascular diseases: a Mendelian randomization study. Front Endocrinol (Lausanne) 2022;13 doi: 10.3389/fendo.2022.842846. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Al-Qadami G, Bowen J, Van Sebille Y, et al. Baseline gut microbiota composition is associated with oral mucositis and tumour recurrence in patients with head and neck cancer: a pilot study. Support Care Cancer. 2023;31:98. doi: 10.1007/s00520-022-07559-5. [DOI] [PubMed] [Google Scholar]
  • 27.Yan Y, Li L, Wu K, et al. A combination of baicalin and berberine hydrochloride ameliorates dextran sulfate sodium-induced colitis by modulating colon gut microbiota. J Med Food. 2022;25:853–862. doi: 10.1089/jmf.2021.K.0173. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Bjørkhaug ST, Aanes H, Neupane SP, et al. Characterization of gut microbiota composition and functions in patients with chronic alcohol overconsumption. Gut Microbes. 2019;10:663–675. doi: 10.1080/19490976.2019.1580097. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Xiao X, Cheng Y, Fu J, et al. Gut immunity and microbiota dysbiosis are associated with altered bile acid metabolism in LPS-challenged piglets. Oxid Med Cell Longev. 2021;2021 doi: 10.1155/2021/6634821. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Du T, Lei A, Zhang N, Zhu C. The beneficial role of probiotic lactobacillus in respiratory diseases. Front Immunol. 2022;13 doi: 10.3389/fimmu.2022.908010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Wang X, Xiong K, Huang F, et al. A metagenome-wide association study of the gut microbiota in recurrent aphthous ulcer and regulation by thalidomide. Front Immunol. 2022;13 doi: 10.3389/fimmu.2022.1018567. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Mimura MAM, Borra RC, Hirata CHW, de Oliveira Penido N. Immune response of patients with recurrent aphthous stomatitis challenged with a symbiotic. J Oral Pathol Med. 2017;46:821–828. doi: 10.1111/jop.12621. [DOI] [PubMed] [Google Scholar]
  • 33.Shimizu J, Murayama MA, Miyabe Y, Suzuki N. Immunopathology of Behcet's disease: an overview of the metagenomic approaches. Rheumato. 2022;2:74–86. [Google Scholar]
  • 34.Han G, Kwon D, Jang W, Song JH. Compositional changes of gut microbiota in patients with Behcet's disease: systematic literature review. Investigat Ophthalmol Visual Sci. 2023;64:3581. [Google Scholar]
  • 35.Taylor J, Glenny AM, Walsh T, et al. Interventions for the management of oral ulcers in Behçet's disease. Cochrane Database Syst Rev. 2014 doi: 10.1002/14651858.CD011018.pub2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Yang J, Li Y, Wen Z, Liu W, Meng L, Huang H. Oscillospira: a candidate for the next-generation probiotics. Gut Microbes. 2021;13 doi: 10.1080/19490976.2021.1987783. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Aggour RL, Mahmoud SH, Abdelwhab A. Evaluation of the effect of probiotic lozenges in the treatment of recurrent aphthous stomatitis: a randomized, controlled clinical trial. Clin Oral Investig. 2021;25:2151–2158. doi: 10.1007/s00784-020-03527-7. [DOI] [PubMed] [Google Scholar]
  • 38.Niscola P, Tendas A, Scaramucci L, Giovannini M, Trinchieri V, De Fabritiis P. Aphthous oral ulceration and its successful management by Lactobacillus brevis CD2 extract in an adult haemophilic patient. Haemophilia. 2012;18:e78–e79. doi: 10.1111/j.1365-2516.2012.02757.x. [DOI] [PubMed] [Google Scholar]
  • 39.Frey-Furtado L, Magalhães I, Azevedo MJ, Sampaio-Maia B. The role of biotics as a therapeutic strategy for oral mucositis: a systematic review. Probiotics Antimicrob Proteins. 2023 doi: 10.1007/s12602-023-10116-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Zhang Q, Zhao Q, Li T, et al. Lactobacillus plantarum-derived indole-3-lactic acid ameliorates colorectal tumorigenesis via epigenetic regulation of CD8(+) T cell immunity. Cell Metab. 2023;35:943–960.e9. doi: 10.1016/j.cmet.2023.04.015. [DOI] [PubMed] [Google Scholar]
  • 41.Yang Z, Cui Q, An R, et al. Comparison of microbiomes in ulcerative and normal mucosa of recurrent aphthous stomatitis (RAS)-affected patients. BMC Oral Health. 2020;20:128. doi: 10.1186/s12903-020-01115-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Schmidt TS, Hayward MR, Coelho LP, et al. Extensive transmission of microbes along the gastrointestinal tract. Elife. 2019;8:e42693. doi: 10.7554/eLife.42693. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Zhou T, Xu W, Wang Q, et al. The effect of the "Oral-Gut" axis on periodontitis in inflammatory bowel disease: a review of microbe and immune mechanism associations. Front Cell Infect Microbiol. 2023;13 doi: 10.3389/fcimb.2023.1132420. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Min Z, Yang L, Hu Y, Huang R. Oral microbiota dysbiosis accelerates the development and onset of mucositis and oral ulcers. Front Microbiol. 2023;14 doi: 10.3389/fmicb.2023.1061032. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Zhou Y, Wang M, Yan C, Liu H, Yu DG. Advances in the application of electrospun drug-loaded nanofibers in the treatment of oral ulcers. Biomolecules. 2022;12:1254. doi: 10.3390/biom12091254. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Panahi Y, Saadat A, Shadboorestan A, Ahmadi A. An updated review of natural products intended to prevent or treat oral mucositis in patients undergoing radio-chemotherapy. Curr Pharm Biotechnol. 2016;17:949–961. doi: 10.2174/1389201017666160808094008. [DOI] [PubMed] [Google Scholar]
  • 47.Lau CB, Smith GP. Recurrent aphthous stomatitis: a comprehensive review and recommendations on therapeutic options. Dermatol Ther. 2022;35:e15500. doi: 10.1111/dth.15500. [DOI] [PubMed] [Google Scholar]
  • 48.Dietrich CG, Kottmann T, Alavi M. Commercially available probiotic drinks containing Lactobacillus casei DN-114001 reduce antibiotic-associated diarrhea. World J Gastroenterol. 2014;20:15837–15844. doi: 10.3748/wjg.v20.i42.15837. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Mei Z, Li D. The role of probiotics in vaginal health. Front Cell Infect Microbiol. 2022;12 doi: 10.3389/fcimb.2022.963868. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Zheng DW, Li RQ, An JX, et al. Prebiotics-encapsulated probiotic spores regulate gut microbiota and suppress colon cancer. Adv Mater. 2020;32 doi: 10.1002/adma.202004529. [DOI] [PubMed] [Google Scholar]
  • 51.Suez J, Zmora N, Segal E, Elinav E. The pros, cons, and many unknowns of probiotics. Nat Med. 2019;25:716–729. doi: 10.1038/s41591-019-0439-x. [DOI] [PubMed] [Google Scholar]
  • 52.Uchiyama K, Naito Y, Takagi T. Intestinal microbiome as a novel therapeutic target for local and systemic inflammation. Pharmacol Ther. 2019;199:164–172. doi: 10.1016/j.pharmthera.2019.03.006. [DOI] [PubMed] [Google Scholar]
  • 53.Wade KH, Hall LJ. Improving causality in microbiome research: can human genetic epidemiology help? Wellcome Open Res. 2019;4:199. doi: 10.12688/wellcomeopenres.15628.3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Jiang L, Li JC, Tang BS, Guo JF. Associations between gut microbiota and Parkinson disease: a bidirectional Mendelian randomization analysis. Eur J Neurol. 2023 doi: 10.1111/ene.15848. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

mmc1.docx (1.1MB, docx)
mmc2.xlsx (1.6MB, xlsx)

Articles from International Dental Journal are provided here courtesy of Elsevier

RESOURCES