1. Introduction
Eosinophilic esophagitis (EoE) is a chronic inflammatory disease characterized by esophageal dysfunction and eosinophilic inflammation of the esophageal mucosa [1,2,3,4,5]. The incidence and prevalence of EoE have increased dramatically over the past 20 years. When EoE was first reported in 1977 [6], the incidence was only approximately 0.4 cases per 100,000 people per year [7]. Now, the incidence rate has increased to approximately 10 cases per 100,000 people per year, with the estimated prevalence rate ranging between 50 and 100 cases per 100,000 people [8]. The increased incidence and prevalence of EoE have been observed worldwide, with prevalence tending to be higher in Western countries than in Asian countries. In particular, the prevalence of EoE in North America and Europe is significantly higher than that in Asia. However, the incidence of EoE is also increasing in Asian countries, requiring further investigation into the relevant factors. This increase is more pronounced in high-income countries, with a higher incidence and prevalence in males, especially in boys.
The etiology and pathogenesis of EoE have not yet been fully understood, but several hypotheses have been proposed based on current findings. EoE often runs in families, suggesting a genetic predisposition [9]. Specific genes may increase the risk of EoE [10,11]; however, the specific genes and their mechanisms remain unclear. Furthermore, EoE is associated with abnormal immune responses to foods and environmental allergens [12]. The function of the esophageal epithelial barrier is impaired in patients with EoE [13,14]. Dysfunction of the esophageal epithelial barrier could facilitate the penetration of allergens and microorganisms into the esophageal mucosa, causing inflammation. In particular, the overproduction of Th2 cytokines (such as IL-4, IL-5, and IL-13) may play an important role in eosinophil infiltration and esophageal inflammation [15]. In EoE, the amount of bacteria and specific Toll-like receptors are overexpressed compared with controls. Furthermore, since they normalize with a diet-elimination method, microbial involvement may be strongly related to disease pathogenesis [16].
Oral bacterial flora is a highly complex living environment in the body that regulates the host’s immune system and may contribute not only to oral diseases but also systemic diseases [17]. The relationship between salivary microbiome and EoE has recently attracted attention [18,19]. The oral cavity is an important entry point for triggering allergens, which may subsequently interact and mix with saliva components (including the saliva microbiome) to trigger an immune response that results in eosinophil-dominant esophageal inflammation. Several studies have reported altered salivary microbiome composition in patients with EoE, which may be associated with inflammation. Furthermore, although the mechanisms are yet to be proven, bacteria in saliva may migrate to the esophagus and alter the esophageal microbiome.
A diverse bacterial flora also develops in the esophageal mucosa. Recent research has focused on changes in the bacterial flora caused by esophageal diseases such as reflux esophagitis and esophageal cancer (adenocarcinoma and squamous cell carcinoma) [20]. Changes in the esophageal microbiome can also influence EoE development and pathogenesis [9,21]. Changes in the composition and diversity of esophageal bacterial flora have been reported in patients with EoE, with increases or decreases in specific bacteria, such as Haemophilus and Streptococcus [9,22]. These changes in the bacterial flora may alter the immune response of the esophageal mucosa, inducing the production of Th2 cytokines and chemokines [3]. Furthermore, esophageal microbiome alterations may also affect the function of the esophageal epithelial barrier. However, many aspects remain unknown, such as the relationship between changes in esophageal mucosal flora and the severity of EoE as well as the relationship between cytokines.
In this study, we investigated the bacterial flora in saliva and esophageal mucus in patients with EoE and examined the relationship between EoE disease activity and mucosal cytokine expression.
2. Results
2.1. Patient Characteristics
The demographic and clinical characteristics of the entire study population are presented in Table 1. Of the 59 patients enrolled, 25 were EoE patients (8 patients of I-EoE and 17 patients of A-EoE), and 28 were non-EoE controls. The groups were comparable for age (EoE patients’ mean age: 51, interquartile range (IQR): 40–57 years’ vs. non-EoE patients’ mean age: 49, IQR: 29–62 years; p = 0.13). Dysphagia (41%) and abdominal pain (26%) were two of the most common indications for esophago-gastroduodenoscopy (EGD). A significantly higher proportion of patients with active EoE presented with dysphagia compared with non-EoE controls (76% vs. 14%; p < 0.01). Food or drug allergies (35%) and allergic rhinitis (33%) were the most common allergic comorbidities. Moreover, 11 (44%) EoE patients were taking proton pump inhibitors (PPIs), 4 (16%) EoE patients were taking topical steroids, and 13 (52%) patients were taking antiallergic medicines such as fexofenadine. A significantly higher proportion of patients with I-EoE took PPIs compared with A-EoE (88% vs. 24%; p = 0.01) (Supplemental Figure S2). ERFES scores with A-EoE were significantly higher compared with I-EoE (mean: 2, IQR: 4–4 vs. mean: 2, IQR 0–2). Further, six (21%) non-EoE patients were taking PPIs for gastroesophageal reflex disease (GERD) or abdominal pain.
2.2. Comparative Analyses of the Alpha Diversity Indices Among the Three Groups Using Saliva and Esophageal Mucus
There were no differences in Shannon, Chao1, or observed feature indices for the alpha diversity of saliva (Figure 1A–C). On the other hand, the Shannon index was significantly lower in the esophageal mucosa in the non-EoE patients (Figure 1D). However, no significant difference was observed in the other index, Chao1, or observed features in the esophageal mucosa (Figure 1E,F).
2.3. Comparative Analyses of Saliva Taxonomic Composition
Figure 2 shows a bar plot of the top 10 genera in the bacterial flora of saliva (Figure 2A) and the esophagus (Figure 2B). Major genera such as Streptococcus, Prevotella, Veillonella, and Haemophilus were found in both the oral cavity and the esophagus. Streptococcus was found more frequently in the esophagus than in the oral cavity, which is consistent with previous reports. In saliva, in a comparison of the two groups, the EoE group had significantly more Prevotella and Anaeroglobus than the control group, while Neisseria and Haemophilus were significantly less common (Supplemental Figure S1A). In the esophageal mucosa, in a comparison of the two groups (control group and EoE group), the EoE group had significantly more Prevotella than the control group and, conversely, significantly less Streptococcus.
In saliva, a comparison among the three groups revealed a significant difference in Prevotella spp. and Neisseria spp. (Figure 3A,B). The number of Prevotella spp. was significantly lower in the control and I-EoE groups than in the A-EoE group (p < 0.05, d < 0.5; control group 0.18 ± 0.07 [0.15–0.21], I-EoE 0.25 ± 0.03 [0.23–0.28], A-EoE 0.24 ± 0.07 [0.20–0.28]). Neisseria spp. counts were significantly lower in the A-EoE group than in the control and I-EoE groups (p < 0.05, d < 0.5; control group 0.07 ± 0.05 [0.05–0.09], I-EoE 0.03 ± 0.02 [0.01–0.05], A-EoE 0.04 ± 0.03 [0.02–0.05]).
Figure 3C–E show a comparison of salivary samples between the two groups. In the comparison between the control and I-EoE groups, Prevotella was significantly more abundant in the I-EoE group than in the control group (C). In the comparison between the control and A-EoE groups, Prevotella was significantly more common in the I-EoE group than in the control group, whereas Neiseria and Hemophilia were significantly less common (D). In the comparison between the I-EoE and A-EoE groups, the abundance of Bacteroides was significantly more common in the I-EoE group than in the A-EoE group (E).
2.4. Comparative Taxonomic Analysis of the Esophageal Mucosa
In the esophagus mucus, a comparison among the three groups revealed significant differences in Streptococcus spp. and Prevotella spp. (Figure 2B and Figure 4A,B). Streptococcus spp., the most common genus in the esophagus, were significantly less common in the active EoE group compared to the inactive EoE and non-EoE groups (p < 0.05, d < 0.5; control 0.41 ± 0.18 [0.32–0.49], I-EoE 0.33 ± 0.11 [0.23–0.42], A-EoE 0.21 ± 0.10 [0.16–0.26]). Prevotella spp. were significantly more common in the active EoE group compared to the inactive EoE group (p < 0.05, d < 0.5; control 0.18 ± 0.07 [0.06–0.15], I-EoE 0.26 ± 0.03 [0.14–0.21], A-EoE 0.24 ± 0.07 [0.14–0.22]).
Figure 4C–E show the comparison of esophageal samples between the two groups. In the comparison between the control and I-EoE groups, Prevotella was significantly more abundant in the I-EoE group than in the control group (C). In the comparison between the control and A-EoE groups, Prevotella was significantly more common in the I-EoE group than in the control group, whereas Streptococcus was significantly less common (D). In the comparison between the I-EoE and A-EoE groups, Streptococcus was significantly more common in the I-EoE group than in the A-EoE group (E).
2.5. Correlation Between Salivary and Esophageal Flora
As a result of examining the correlation between the bacterial flora of saliva and esophageal mucosa, no correlation was found for Streptococcus (Figure 5A), but a correlation was found for all of the other top bacterial species: Prevotella (Figure 5B), Haemophilus, Veillonella, Gemella, Alloprevotella, Fusobacterium, Pauijensenia, Porphyromonas, Neisseria, and Rothis. In particular, Prevotella was strongly correlated.
We examined differences in bacterial abundance for each ERFFS item (box-and-whisker diagram, Figure 6C). The lower the ERFFS score, the greater the amount of Streptococcus present, and a significant difference was observed in particular for edema, rings, and furrows.
3. Discussion
This study investigated the microbiome of saliva and esophageal mucus in patients with EoE. Compared with the control group, significantly more Prevotella spp. were observed in the saliva and esophageal mucosa of patients with active EoE. Conversely, we found significantly fewer Neisseria in the saliva and Streptococcus in the esophageal mucosa of patients with active EoE. The endoscopic findings of EoE and the abundance of Streptococcus were inversely correlated, indicating a specific association with edema and longitudinal furrow.
Prevotella are commonly found in the gut and mouth, and their presence varies according to dietary habits and the living environment. In this study, Prevotella in the saliva and esophageal mucosa were significantly abundant in active EoE. The increased abundance of Prevotella spp. may be involved in the onset and progression of autoimmune diseases such as rheumatoid arthritis, systemic lupus erythematosus, and multiple sclerosis [17,23,24]. The abundance of Prevotella spp., specifically Prevotella salivae, in the saliva of patients with IBD was higher than that in healthy controls [25]. Prevotella activates the immune system and specifically promotes the secretion of inflammatory cytokines (e.g., IL-17 and IL-23) via Th17 cells. The Prevotella-Th17/IL-23 axis has a significant role in chronic inflammatory diseases [26]. Certain Prevotella strains, such as P. histicola, exhibit anti-inflammatory properties [27], whereas other strains, including P. copri and P. nigrescens, induce inflammation via IL-23-mediated activation of Th17 cells [28,29,30]. Although the Th17/IL-23 axis and eosinophilic inflammation (eosinophilic inflammation, EI) belong to different immune pathways, their interaction is attracting attention. IL-23 may be involved not only in the activation of Th17 cells but also in the activation of eosinophils and tissue infiltration, and in some diseases, where Th17 and Th17 and Th2 coexist (asthma, eosinophilic chronic rhinosinusitis (ECRS), atopic dermatitis, inflammatory bowel disease (IBD), etc.), inflammation tends to worsen, and steroid resistance may occur [31,32,33,34]. Prevotella produces lipopolysaccharide and other metabolites that may cause systemic inflammation and tissue damage [17,35]. In EoE, allergen-present naive T cells differentiate into Th17 cells, which secrete inflammatory cytokines and induce humoral and cellular factors. Therefore, an increase in the abundance of Prevotella spp. may contribute to the pathogenesis of EoE [36]. They may also play an important role in EoE, but further research is needed to elucidate their pathogenesis and the associated mechanisms. Further research will be required to examine more closely the association between these factors in eosinophilic gastrointestinal disorders.
The genus Streptococcus is an important commensal bacterial genus in the human oral and pharyngeal cavities and includes species that are pathogenic under certain conditions. Some Streptococcus spp. form biofilms and evade host defense mechanisms to proliferate infection. In both the present and previous studies, Streptococcus spp. were significantly decreased in the esophageal mucosa. The study by Zhang et al. found that some bacterial species in the esophageal microbiome, particularly Streptococcus spp., decreased in patients with EoE compared with healthy individuals [21]. Interestingly, some streptococci have been considered as potential probiotics. The Lactobacillales, to which Streptococcus belongs, may have antiallergic and anti-inflammatory effects. Supplementation with lactic acid bacteria attenuated pathogenicity and reduced esophageal eosinophilia in an EoE mouse model [37]. Streptococcus salivarius K12 is a probiotic that helps prevent upper respiratory tract infections. This bacterium produces antimicrobial peptides (bacteriocins) that may suppress harmful bacteria in the mouth and throat by competitive exclusion [38]. S. salivarius can also help prevent tooth decay and periodontal disease and demonstrates a high degree of oral adhesion [39]. It has been used in oral care products (lozenges and mouthwashes) and may help reduce the risk of tooth decay. Bacteria of the Streptococcus genus, and in particular Streptococcus salivarius, have attracted attention in recent years for their potential as probiotics. They have been reported to have anti-inflammatory effects against periodontal disease [40] and to be effective against periodic fever, aphthous stomatitis, pharyngitis, and cervical adenitis (PFAPA) syndrome [41]. In the present study, the number of Streptococcus spp. was significantly lower in the active EoE group and negatively correlated with the EREFS score, which may thus reflect the severity of EoE. Streptococci may be effective probiotics for EoE and should be further investigated.
The composition of the salivary microbiome is altered in patients with EoE. Nonpathogenic species, such as Neisseria cinerea and Neisseria sicca, which are known commensals of the oral cavity and upper respiratory tract, are part of the healthy oral microbiome. They help maintain oral and respiratory health by contributing to the production of antioxidants to mitigate oxidative stress and inhibit the growth of other pathogenic bacteria [42,43]. Furthermore, the present study found significantly fewer Neisseria spp. in the saliva of patients with A-EoE. A decrease in Neisseria spp. was also reported in the mouths of patients with recurrent aphthous stomatitis. This change in the Neisseria subpopulation was associated with the local inflammatory milieu, indicating the involvement of Neisseria spp. in the regulation of inflammation.
The relationship between oral and esophageal microbiomes has been investigated in the context of various diseases. Bacteria in saliva may migrate to the esophagus through the swallowing mechanism and subsequently induce changes in the esophageal microbiome. Changes in the esophageal microbiome may cause an immune response in the esophageal mucosa, which may promote inflammation in EoE [9]. In patients with EoE, inflammation may also occur in the mouth, which in turn may affect the composition of the salivary microbiome. EoE may also be a systemic immune disorder. In the present study, the Prevotella subpopulation was significantly increased in both the saliva and esophageal mucosa. Interestingly, the Prevotella subpopulation is also increased in the mouths and intestines of patients with inflammatory bowel disease (IBD), which can also develop when oral bacteria from human patients with IBD are transplanted into mice [26,44]. In other words, Prevotella in the mouth may influence the development of inflammation throughout the digestive tract and the whole body. However, the mechanism is not yet well understood. Further research is required to elucidate these details.
It has been posited that the salivary microbiota may serve as a noninvasive biomarker for eosinophilic esophagitis (EoE) [19]. A comparative analysis of the salivary microbiota composition between children with EoE and non-EoE has revealed alterations in the former group compared with the latter. Specifically, children diagnosed with EoE exhibited lower relative abundances of Streptococcus, Lactobacillus, Leptotrichiaceae (unclassified), and Actinomyces compared with children in the non-EoE control group. In contrast, the relative abundance of Streptococcus was significantly higher in the control group. Children with active EoE exhibited lower relative abundances of Actinomyces, Lactobacillus, Leptotrichiaceae (unclassified), and Streptococcus than non-EoE subjects. In the control group, the relative abundance of Neisseriaceae (unclassified) in non-EoE subjects was significantly higher. These findings also suggest that bacterial flora may discriminate between patients. In this study, the composition of the salivary microflora was similar between the EoE and non-EoE groups. Similar results were shown in this study for Streptococcus and Neisseriaceae. However, it is necessary to further investigate whether changes in the salivary microbiome can be used to help diagnose EoE, determine responsiveness to treatment, and predict prognosis.
Streptococcus in the esophageal mucosa was found to be correlated with EoE endoscopic scores, particularly in patients with edema, longitudinal ulcers, and furrows. This study is the first to detail the relationship between the EoE endoscopic scores and bacterial flora. Streptococcus is involved in the intestinal barrier and has been indicated as a potential probiotic; thus, the results of this study are confirmatory. However, in children with active EoE, the relative abundance of Haemophilus was significantly higher, and the relative bacterial abundance was significantly correlated with the abnormal esophageal mucosa and histopathological severity as indicated by the EoE histological score [19]. The study subjects’ young age may be the reason for the varying results. Many studies on the differences between the EoE and normal intestinal flora have mostly involved pediatric patients. The intestinal flora changes with age; thus, differences in intestinal flora between children and adults should also be assessed.
It has been posited that alterations in the esophageal microbiota of patients may exert an influence on specific metabolic pathways associated with EoE [45]. These alterations may contribute to the onset and progression of the disease by affecting sulfur compounds, 4-aminobutyric acid, and ornithine–arginine metabolism. An increase in EoE has been observed, and Gram-negative bacteria samples have been described as possibly affecting the inflammatory process [46]. The cell wall components of Gram-negative bacteria have been identified as stimulants of host immune receptors (e.g., Toll-like receptors) and inducers of inflammatory responses. It has been proposed that may play a role in the pathway mediated by Toll-like receptor (TLR) activation of inflammatory responses in EoE [21]. It has been proposed that alterations in the microbiota, achieved through the modulation of TLR-mediated immune responses, may exert an influence on the pathophysiology of EoE. Unfortunately, this study did not assess functional microbiota changes, including metagenomic or metabolomic changes. This necessitates further study.
This study has several limitations. First, the number of patients was small. The small sample size limits the generalizability of the results and increases the risk of type II errors. Second, the study was single-center, which reduces external validity. In the future, multicenter validation studies should be considered. Third, the study characterized bacterial composition but did not assess functional microbiota changes, such as metabolic activity or microbial interactions with the host immune system. Therefore, future studies should involve combined investigations into microbial communities and metabolomics for verification. The esophageal biopsies were taken only from the lower esophagus; however, different sampling sites may produce conflicting results. Sampling only the distal esophagus may miss regional microbial variations. Furthermore, several factors could influence microbiome composition, including dietary habits, antibiotic use, proton pump inhibitor (PPI) use, and genetic predisposition. The study did not control for these confounders, making it difficult to determine whether the observed microbiota differences were causative or incidental. In order to control for these confounding factors, it will be necessary to establish more rigorous selection criteria, conduct stratified analyses based on the use or non-use of PPIs used in treatment, and conduct longitudinal studies of the same participants’ microbiomes before and after treatment. By integrating these approaches, we must persist in our endeavors to comprehend the impact of confounding factors such as diet, antibiotic utilization, PPI use, and genetic predisposition on the outcomes of esophageal microbiome research in EoE, thereby facilitating the attainment of more reliable conclusions.
In this study, we clarified the characteristics of the bacterial flora in the saliva and esophageal mucosa of patients with EoE. However, further research is needed to determine whether these changes in bacterial flora are the cause or effect of EoE. Furthermore, their utility in diagnosis and treatment should also be evaluated.
4. Materials and Methods
4.1. Ethics
Ethics approval was obtained from the Kawasaki Medical School Ethics and Medical Research Committee (approval no. 5436-01). Written informed consent was obtained from all study participants before enrollment. All patients were treated at the Division of Gastroenterology of Kawasaki Medical School Hospital.
4.2. Patients and Sample Collection
We recruited patients with EoE or with symptoms of esophageal dysfunction who underwent esophagogastroduodenoscopy (EGD) at our center between April 2021 and May 2024. The exclusion criteria were inflammatory bowel disease, including non-EoE EGD; a history of esophageal surgery, varices, or esophageal cancer; or use of or exposure to antibiotics within the previous 4 weeks (Table 2).
Cases consisted of patients with active and inactive EoE (A-EoE and I-EoE). A-EoE was defined as a peak eosinophil count > 15/high-power field (hpf), as recommended by the 2025 consensus guidelines [47], whereas inactive disease was defined as a peak eosinophil count < 15/hpf. Biopsies of at least two samples were taken from the distal esophagus. The control group consisted of patients with non-EoE with symptoms suggestive of esophageal dysfunction but normal esophageal histology. We collected brush samples from the distal esophagus mucosa using an endoscopic microbiology brush (COOK, Bloomington, IN, USA) to prevent contamination. The brush method was selected as the specimen sampling method based on its reportedly higher bacterial DNA recovery rate than that by biopsy [48]. Saliva samples were collected from patients before the endoscopic examination.
The EoE endoscopic reference score (EREFS) is an indicator for evaluating the degree of inflammation in the esophagus [47,49,50]. The EREFS is based on five endoscopic findings, namely exudates, rings, edema, furrows, and strictures, and it is useful for evaluating EoE severity (Figure 7).
4.3. RNA Extraction
Esophageal tissue samples were collected from the distal esophagus simultaneously with the brush samples. The tissue biopsies were frozen at −80 °C until analysis. Total RNA was extracted from the esophagus using a NucleoSpin RNA kit and reverse-transcribed using the SuperScript™ IV First-Strand Synthesis System, according to the manufacturer’s instructions.
4.4. Reverse Transcription Quantitative Polymerase Chain Reaction
Reverse transcription quantitative polymerase chain reaction (RT-qPCR) was performed using PowerUpTM SYBRTM Green Master Mix (Thermo Fisher Scientific, Waltham, MA, USA). Human actin-beta expression was evaluated as an internal control. The primers used for the RT-qPCR experiments are listed in Table 1. The PCR conditions were as follows: initial denaturing at 95 °C for 2 min; 40 cycles at 95 °C for 15 s; 60 °C for 1 min; and melting curve analysis (95 °C for 15 s, 60 °C for 1 min, and 95 °C for 15 s). The primers used are listed in Table 2.
4.5. DNA Extraction, PCR Amplification, Library Preparation, and 16S rRNA Sequencing
The 16SrRNA gene amplicon library was prepared and sequenced using previously reported methods for DNA extraction, amplicon generation, and sequencing [51]. A library of amplicons encoding the 16S rRNA gene was prepared, and sequencing was conducted as previously described [52]. The samples were profiled using high-throughput amplicon sequencing with dual-index barcoding using the Illumina MiSeq platform (Illumina, San Diego, CA, USA). The V3–V4 regions of the 16S rDNA, which span 460 base pairs, were amplified using tailed PCR [53]. PCR amplicons were purified using SPRI select beads (Beckman Colter, Brea, CA, USA). The DNA concentration of the purified amplicons was measured using a Quantus Fluorometer and the QuantiFluor® dsDNA System (Promega, Madison, WI, USA), and an approximately equal amount of their DNA was pooled. The pooled sample was sequenced using a MiSeq Reagent Kit V3 (600 cycles; Illumina, San Diego, CA, USA) on the MiSeq system according to the manufacturer’s instructions.
4.6. Bioinformatics Analysis
Sequence data processing, consisting of quality filtering, chimera checking, and amplicon sequence variant (ASV) definition, was accomplished using the QIIME 2. ver 2024.5 (
4.7. Alpha Diversity
The observed features, Shannon entropy, and Chao1 diversity indices were calculated using the phyloseq package of R software (version 4.4.1). The data were visualized by principal coordinate analysis and statistically analyzed using permutational multivariate analysis of variance (PERMANOVA), which was performed using the vegan package (version 2.6-2).
4.8. Statistical Analysis
The differences in families among the lines were analyzed using the Statistical Analysis of Metagenomic Profiles software (version 2.1.3) [54]. The diversity and relative abundance of bacterial genera indices were compared among the three groups by the Kruskal–Wallis analysis and compared between the two groups by the Mann–Whitney U test. The category data were analyzed using the chi-square test. The correlation between saliva and esophageal bacterial flora and the correlation between bacterial flora and the ERFES score were evaluated using Spearman’s correlation coefficient and Pearson’s correlation coefficient. Statistical analyses were performed using SPSS (version 25 for Windows, IBM Japan, Ltd., Tokyo, Japan). Statistical significance was set at a p-value of <0.05.
Conceptualization, H.M. and A.S.; methodology, T.T.G., R.I. and S.Y.; validation, T.T.G., M.O. and O.H.; formal analysis, T.T.G., R.I. and M.S.; investigation, H.M.; resources, T.T.G.; data curation, T.T.G., S.M., T.N., R.I. and M.O.; writing—original draft preparation, H.M.; writing—review and editing, A.S. and E.U.; supervision, A.S.; project administration, H.M.; funding acquisition, H.M. All authors have read and agreed to the published version of the manuscript.
The study was conducted in accordance with the Declaration of Helsinki and approved by the Kawasaki Medical School Ethics and Medical Research Committee (approval no. 5436-01).
Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the patient(s) to publish this paper.
The raw data supporting the conclusions of this article will be made available by the authors upon request. The data were restricted for privacy reasons.
During the preparation of this work, Hiroshi Matsumoto used Grammarly [free version; data of use: 31 January 2024] in order to check the English language quality. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.
The authors declare no conflicts of interest.
The following abbreviations are used in this manuscript:
| EoE | Eosinophilic esophagitis |
| A-EoE | Active eosinophilic esophagitis |
| I-EoE | Inactive eosinophilic esophagitis |
| EREFS | Eosinophilic esophagitis endoscopic reference score |
| IL | Interleukin |
| EGD | Esophago-gastroduodenoscopy |
| PPI | Proton pump inhibitor |
| GERD | Gastroesophageal reflex disease |
| hpf | high-power field |
| IBD | inflammatory bowel disease |
| TSLP | Thymic stromal lymphopoietin |
| CCL | CC chemokine ligand |
| CXCL | CXC motif chemokine ligand |
Footnotes
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Enlarge this image.Figure 1. Alpha diversity indices: (A) Shannon index, (B) Chao1 index, and (C) observed feature using saliva; (D) Shannon index, (E) Chao1 index, and (F) observed feature using esophageal mucus.
Enlarge this image.Figure 2. Taxonomic composition of saliva (A) and esophageal mucus (B): top 10 genera in the bacterial flora.
Enlarge this image.Figure 3. (A,B) Comparison of the esophageal mucus microbiota among the control, inactive (I)-EoE, and active (A)-EoE groups in saliva: (A) Prevotella and (B) Neisseria. (C–E) Comparison between the two groups in the salvia microbiota: (C) control vs. I-EoE, (D) control vs. A-EoE, and (E) I-EoE vs. A-EoE.
Enlarge this image.Figure 3. (A,B) Comparison of the esophageal mucus microbiota among the control, inactive (I)-EoE, and active (A)-EoE groups in saliva: (A) Prevotella and (B) Neisseria. (C–E) Comparison between the two groups in the salvia microbiota: (C) control vs. I-EoE, (D) control vs. A-EoE, and (E) I-EoE vs. A-EoE.
Enlarge this image.Figure 4. (A,B) Comparison among the control, inactive (I)-EoE, and active (A)-EoE groups of the esophageal mucus microbiota: (A) Streptococcus and (B) Prevotella spp. (C–E) Comparison of the esophageal microbiota between the two groups: (C) control vs. I-EoE, (D) control vs. A-EoE, and (E) I-EoE vs. A-EoE.
Enlarge this image.Figure 5. Correlation between salivary and esophageal microbiota: (A) Streptococcus and (B) Prevotella.
Enlarge this image.Figure 6. Correlation of esophageal bacteria flora and eosinophilic esophagitis endoscopic reference score (EREFS): (A) Streptococcus and (B) Prevotella. (C) Correlation of streptococcus and each item of EREFS.
Enlarge this image.Figure 7. Study design: Three groups: control, inactive EoE (I-EoE), and active EoE(A-EoE).
Patients characteristics.
| Control (n = 28) | EoE | p-Value | p-Value | ||
|---|---|---|---|---|---|
| Inactive (n = 8) | Active (n = 17) | 2 Groups | |||
| Gender (M) | 11 (39%) | 5 (62%) | 10 (59%) | 0.3 | 0.52 |
| Age (mean ± SD; yr) | 49 [29–62] | 52 [37–66] | 50 [42–57] | 0.9 | 0.23 |
| Allergic comorbidities (n, %) | |||||
| Asthma | 0 | 3 (38%) | 5 (29%) | 0.04 | <0.01 |
| Eczema | 1 (0%) | 6 (75%) | 3 (18%) | <0.01 | <0.01 |
| Allergic rhinitis | 6 (21%) | 2 (25%) | 12 (71%) | 0.01 | 0.05 |
| Food allergies | 6 (21%) | 4 (40%) | 11 (65%) | 0.02 | <0.01 |
| Clinical symptoms (n, %) | |||||
| Dysphagia | 4 (14%) | 6 (75%) | 13 (76%) | <0.01 | <0.01 |
| Abdominal pain | 9 (32%) | 2 (25%) | 3 (18%) | 0.32 | 0.2 |
| Nausea, vomiting | 1 (0%) | 0 | 5 (29%) | 0.05 | 0.08 |
| Endoscopy findings (n, %) | |||||
| Edema | - | 0 [0–0] | 1 [1–1] | <0.01 | |
| Rings | - | 0 [0–1] | 1 [1–2] | <0.01 | |
| Furrows | - | 0 [0–1] | 1 [1–1] | <0.01 | |
| Exudates | - | 0 [0–1] | 1 [1–1] | <0.01 | |
| Structure | - | 0 [0–0] | 0 [0–0] | 0.28 | |
| EREFS | - | 2 [2–0] | 4 [4–4] | 0.02 | |
| The number of eosinophilic infiltration (median IQR: eos/hpf) | - | 0 [0–20] | 65 [24–85] | <0.01 | |
| Medication (n, %) | |||||
| Proton pump inhibitors | 6 (21%) | 7 (88%) | 4 (24%) | 0.59 | 0.27 |
| Topical steroids | 0 (0%) | 2 (25%) | 2 (12%) | <0.01 | 0.04 |
| Antiallergic medicine | 0 (0%) | 6 (75%) | 7 (41%) | <0.01 | <0.01 |
| H. pylori infection (uninfected/ | 22/5/1 | 5/3/0 | 14/3/0 | 0.85 | 0.6 |
| Cytokines expression in esophageal mucosa | |||||
| IL-4 | 12.5 (2.3–111.3) | 240.2 (159.4–333.7) | 8.4 (5.6–12.4) | 0.03 | 0.53 |
| IL-13 | 1.0 (0.53–17.1) | 19.6 (7.9–29.4) | 1.5 (0.74–2.4) | 0.02 | 0.26 |
| IL-33 | 1.7 (1.0–12.6) | 26.4 (4.8–84.9) | 3.2 (2.9–3.3) | 0.02 | 0.25 |
| TGF-beta1 | 2.0 (1.1–6.1) | 3.5 (2.0–5.2) | 4.0 (2.4–9.7) | 0.65 | 0.19 |
| TSLP | 2.9 (1.8–13.5) | 8.9 (5.5–15.5) | 3.4 (2.3–4.6) | 0.58 | 0.80 |
| CCL26 | 1.4 (0.97–6.7) | 42.0 (21.2–113.4) | 0.38 (0.11–0.49) | 0.01 | 0.11 |
| CXCL16 | 1.0 (0.72–1.9) | 6.0 (2.5–25.2) | 1.2 (0.69–2.4) | 0.03 | 0.76 |
Three groups: control, I-EoE, and A-EoE; two groups: control vs. EoE (I-EoE + A-EoE). EREFS: eosinophilic esophagitis endoscopic reference score
PCR primer sequences.
| Target Gene | Sequence | |
|---|---|---|
| IL-4 | FP | ACATCTTTGCTGCCTCCAA |
| RP | AGGCAGCGAGTGTCCTTCT | |
| IL-13 | FP | GATTCTGCCCGCACAAGGT |
| RP | CGATTTTGGTGTCTCGGACAT | |
| IL-33 | FP | GGCTGAGAATTACCATACAAGG |
| RP | AGTGTTTTTCAGATGGGATGA | |
| TGFβ1 | FP | CGCGTGCTAATGGTGGAAA |
| RP | TGTGTGTACTCTGCTTGAACTTG | |
| CCL26 | FP | TCCCTCCTGAGTCTCCACCTT |
| RP | CTGTATTGGAAGCAGCAGGTCTT | |
| CXCL16 | FP | CCTATGTGCTGTGCAAGAGGAG |
| RP | CTGGGCAACATAGAGTCCGTCT |
Supplementary Materials
The following supporting information can be downloaded at:
References
1. Barchi, B.; Vespa, E.; Passaretti, S.; Dell’Anna, G.; Fasulo, E.; Yacoub, M.; Albarello, L.; Sinagra, E.; Massimino, L.; Ungaro, F. et al. The Dual Lens of Endoscopy and Histology in the Diagnosis and Management of Eosinophilic Gastrointestinal Disorders-A Comprehensive Review. Diagnostics; 2024; 22, 858. [DOI: https://dx.doi.org/10.3390/diagnostics14080858]
2. Furuta, G.T.; Katzka, D.A. Eosinophilic Esophagitis. N. Engl. J. Med.; 2015; 373, pp. 1640-1648. [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/26488694]
3. Dellon, E.S.; Liacouras, C.A.; Molina-Infante, J.; Furuta, G.T.; Spergel, J.M.; Zevit, N.; Spechler, S.J.; Attwood, S.E.; Straumann, A.; Aceves, S.S. et al. Updated International Consensus Diagnostic Criteria for Eosinophilic Esophagitis: Proceedings of the AGREE Conference. Gastroenterology; 2018; 155, pp. 1022-1033.e10.
4. Lucendo, A.J.; Molina-Infante, J.; Arias, Á.; von Arnim, U.; Bredenoord, A.J.; Bussmann, C.; Amil Dias, J.; Bove, M.; González-Cervera, J.; Larsson, H. et al. Guidelines on Eosinophilic Esophagitis: Evidence-Based Statements and Recommendations for Diagnosis and Management in Children and Adults. United Eur. Gastroenterol. J.; 2017; 5, pp. 335-358.
5. Hirano, I.; Chan, E.S.; Rank, M.A.; Sharaf, R.N.; Stollman, N.H.; Stukus, D.R.; Wang, K.; Greenhawt, M.; Falck-Ytter, Y.T. AGA Institute Clinical Guidelines Committeeet al. AGA Institute and the Joint Task Force on Allergy-Immunology Practice Parameters Clinical Guidelines for the Management of Eosinophilic Esophagitis. Gastroenterology; 2020; 158, pp. 1776-1786.
6. Dobbins, J.W.; Sheahan, D.G.; Behar, J. Eosinophilic Gastroenteritis with Esophageal Involvement. Gastroenterology; 1977; 72, pp. 1312-1316.
7. Jensen, E.T.; Kuhl, J.T.; Martin, L.J.; Langefeld, C.D.; Dellon, E.S.; Rothenberg, M.E. Early-Life Environmental Exposures Interact with Genetic Susceptibility Variants in Pediatric Patients with Eosinophilic Esophagitis. J. Allergy Clin. Immunol.; 2018; 141, pp. 632-637.e5. [DOI: https://dx.doi.org/10.1016/j.jaci.2017.07.010] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/29029802]
8. Hahn, J.W.; Kim, S.; Yon, D.K. Global Incidence and Prevalence of Eosinophilic Esophagitis, 1976–2022, and Projections to 2037: A Post-Hoc Analysis. Clin. Gastroenterol. Hepatol.; 2023; 21, pp. S1542-S3565.
9. Angerami Almeida, K.; de Queiroz Andrade, E.; Burns, G.; Hoedt, E.C.; Mattes, J.; Keely, S.; Collison, A. The Microbiota in Eosinophilic Esophagitis: A Systematic Review. J. Gastroenterol. Hepatol.; 2022; 37, pp. 1673-1684.
10. Kottyan, L.C.; Rothenberg, M.E. Genetics of Eosinophilic Esophagitis. Mucosal Immunol.; 2017; 10, pp. 580-588. [DOI: https://dx.doi.org/10.1038/mi.2017.4]
11. Sherrill, J.D.; Blanchard, C. Genetics of Eosinophilic Esophagitis. Dig. Dis.; 2014; 32, pp. 22-29. [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/24603376]
12. Simon, D.; Cianferoni, A.; Spergel, J.M.; Aceves, S.; Holbreich, M.; Venter, C.; Rothenberg, M.E.; Terreehorst, I.; Muraro, A.; Lucendo, A.J. et al. Eosinophilic Esophagitis Is Characterized by a Non-IgE-Mediated Food Hypersensitivity. Allergy; 2016; 71, pp. 611-620. [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/26799684]
13. Rochman, M.; Travers, J.; Miracle, C.E.; Bedard, M.C.; Wen, T.; Azouz, N.P.; Caldwell, J.M.; Kc, K.; Sherrill, J.D.; Davis, B.P. et al. Profound Loss of Esophageal Tissue Differentiation in Patients with Eosinophilic Esophagitis. J. Allergy Clin. Immunol.; 2017; 140, pp. 738-749.e3.
14. McGowan, E.C.; Singh, R.; Katzka, D.A. Barrier Dysfunction in Eosinophilic Esophagitis. Curr. Gastroenterol. Rep.; 2023; 25, pp. 380-389.
15. Odiase, E.; Zhang, X.; Chang, Y.; Nelson, M.; Balaji, U.; Gu, J.; Zhang, Q.; Pan, Z.; Spechler, S.J.; Souza, R.F. In Esophageal Squamous Cells from Eosinophilic Esophagitis Patients, Th2 Cytokines Increase Eotaxin-3 Secretion through Effects on Intracellular Calcium and a Non-Gastric Proton Pump. Gastroenterology; 2021; 160, pp. 2072-2088.e6. [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33581123]
16. Arias, Á.; Vicario, M.; Bernardo, D.; Olalla, J.M.; Fortea, M.; Montalban-Arques, A.; Martínez-Fernández, P.; González-Castro, A.M.; Mota-Huertas, T.; Arias-González, L. et al. Toll-like Receptors-Mediated Pathways Activate Inflammatory Responses in the Esophageal Mucosa of Adult Eosinophilic Esophagitis. Clin. Transl. Gastroenterol.; 2018; 9, 147.
17. Graves, D.T.; Corrêa, J.D.; Silva, T.A. The Oral Microbiota Is Modified by Systemic Diseases. J. Dent. Res.; 2019; 98, pp. 148-156.
18. Facchin, S.; Calgaro, M.; Pandolfo, M.; Caldart, F.; Ghisa, M.; Greco, E.; Sattin, E.; Valle, G.; Dellon, E.S.; Vitulo, N. et al. Salivary Microbiota Composition May Discriminate between Patients with Eosinophilic Oesophagitis (EoE) and Non-EoE Subjects. Aliment. Pharmacol. Ther.; 2022; 56, pp. 450-462. [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/35715947]
19. Hiremath, G.; Shilts, M.H.; Boone, H.H.; Correa, H.; Acra, S.; Tovchigrechko, A.; Rajagopala, S.V.; Das, S.R. The Salivary Microbiome Is Altered in Children with Eosinophilic Esophagitis and Correlates with Disease Activity. Clin. Transl. Gastroenterol.; 2019; 10, e00039.
20. Yano, Y.; Etemadi, A.; Abnet, C.C. Microbiome and Cancers of the Esophagus: A Review. Microorganisms; 2021; 9, 1764. [DOI: https://dx.doi.org/10.3390/microorganisms9081764]
21. Zhang, X.; Zhang, N.; Wang, Z. Eosinophilic Esophagitis and Esophageal Microbiota. Front. Cell Infect. Microbiol.; 2023; 13, 1206343. [DOI: https://dx.doi.org/10.3389/fcimb.2023.1206343] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/37600943]
22. Harris, J.K.; Fang, R.; Wagner, B.D.; Choe, H.N.; Kelly, C.J.; Schroeder, S.; Moore, W.; Stevens, M.J.; Yeckes, A.; Amsden, K. et al. Esophageal Microbiome in Eosinophilic Esophagitis. PLoS ONE; 2015; 10, e0128346. [DOI: https://dx.doi.org/10.1371/journal.pone.0128346] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/26020633]
23. Maeda, Y.; Takeda, K. Host-Microbiota Interactions in Rheumatoid Arthritis. Exp. Mol. Med.; 2019; 51, pp. 1-6. [DOI: https://dx.doi.org/10.1038/s12276-019-0283-6]
24. Mangalam, A.K.; Murray, J. Microbial Monotherapy with Prevotella Histicola for Patients with Multiple Sclerosis. Expert Rev. Neurother.; 2019; 19, pp. 45-53. [DOI: https://dx.doi.org/10.1080/14737175.2019.1555473] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/30513004]
25. Abdelbary, M.M.H.; Hatting, M.; Bott, A.; Dahlhausen, A.; Keller, D.; Trautwein, C.; Conrads, G. The Oral-Gut Axis: Salivary and Fecal Microbiome Dysbiosis in Patients with Inflammatory Bowel Disease. Front. Cell. Infect. Microbiol.; 2022; 12, 1010853. [DOI: https://dx.doi.org/10.3389/fcimb.2022.1010853]
26. Larsen, J.M. The Immune Response to Prevotella Bacteria in Chronic Inflammatory Disease. Immunology; 2017; 151, pp. 363-374. [DOI: https://dx.doi.org/10.1111/imm.12760]
27. Blais, L.L.; Montgomery, T.L.; Amiel, E.; Deming, P.B.; Krementsov, D.N. Probiotic and commensal gut microbial therapies in multiple sclerosis and its animal models: Comprehensive review. Gut Microbes; 2021; 13, 194289. [DOI: https://dx.doi.org/10.1080/19490976.2021.1943289]
28. Cani, P.D. Human gut microbiome: Hope, threats and promises. Gut; 2018; 67, pp. 1716-1725. [DOI: https://dx.doi.org/10.1136/gutjnl-2018-316723]
29. Gao, Y.; Nanan, R.; Micia, L.; Tan, J.; Sominsky, L.; Quinn, T.P.; O’Hely, M.; Ponsonby, A.; Tang, M.L.K.; Collier, F. et al. The maternal gut microbiome during pregnancy and offspring allergy and asthma. J. Allergy Clin. Immunol.; 2021; 148, pp. 669-678. [DOI: https://dx.doi.org/10.1016/j.jaci.2021.07.011]
30. Ahmed, H.S. The impact of Prevotella on Neurobiology in Aging: Deciphering Dendritic Cell Activity and Inflammatory Dynamics. Mol. Neurobiol.; 2024; 61, pp. 9240-9251. [DOI: https://dx.doi.org/10.1007/s12035-024-04156-x]
31. Nabe, T. Steroid-Resistant Asthema and Neutrophils. Biol. Pharm. Bull.; 2020; 43, pp. 31-35.
32. Luo, W.; Hu, J.; Xu, W.; Dong, J. Distinct spatial and temporal for Th1, Th2, and Th17 cells in asthema. Front. Immunol.; 2022; 12, 974066.
33. Baring, C.; Bezema, T.; Calder, P.C.; Charloux, A.; Frossard, N.; Garssen, J.; Haworth, O.; Dilevskaya, K.; Levi-Schaffer, F.; Lonsdorfer, E. et al. Activation of Resolution Pathways to Prevent and Fight Chronic Inflammation: Lessons from Asthma and Inflammatory Bowel Disease. Front. Immunol.; 2019; 23, 1699.
34. Li, H.; Zhang, Z.; Zhang, H.; Guo, Y.; Yao, Z. Update on the Pathogenesis and Therapy of Atopic Dermatitis. Clin. Rev. Allergy Immunol.; 2021; 61, pp. 324-338. [DOI: https://dx.doi.org/10.1007/s12016-021-08880-3]
35. Sharma, G.; Garg, N.; Hasan, S.; Saffarini, D.; Shirodkar, S. Fumarate and Nitrite Reduction by Prevotella Nigrescens and Prevotella Buccae Isolated from Chronic Periodontitis Patients. Microb. Pathog.; 2023; 176, 106022. [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/36739100]
36. Lianto, P.; Zhang, Y.; Che, H. Signals from the Various Immune Cells in Promoting Food Allergy-Induced Eosinophilic Esophagitis like Disease. Asia Pac. Allergy; 2019; 9, e28.
37. Holvoet, S.; Doucet-Ladevèze, R.; Perrot, M.; Barretto, C.; Nutten, S.; Blanchard, C. Beneficial Effect of Lactococcus Lactis NCC 2287 in a Murine Model of Eosinophilic Esophagitis. Allergy; 2016; 71, pp. 1753-1761.
38. Tagg, J.R. Prevention of Streptococcal Pharyngitis by Anti-Streptococcus Pyogenes Bacteriocin-like Inhibitory Substances (BLIS) Produced by Streptococcus Salivarius. Indian J. Med. Res.; 2004; 119, pp. 13-16.
39. Wescombe, P.A.; Dyet, K.H.; Dierksen, K.P.; Power, D.A.; Jack, R.W.; Burton, J.P.; Inglis, M.A.; Wescombe, A.L.; Tagg, J.R. Salivaricin G32, a Homolog of the Prototype Streptococcus Pyogenes Nisin-like Lantibiotic SA-FF22, Produced by the Commensal Species Streptococcus Salivarius. Int. J. Microbiol.; 2012; 2012, 738503. [DOI: https://dx.doi.org/10.1155/2012/738503]
40. Beak, D.; Lee, S. Anti-inflammatory efficacy of human-derived Streptococcus salivarius on Peridontopathogen-induced inflammation. J. Microbiol. Biotechnol.; 2023; 33, pp. 998-1005.
41. Torre, F.; Sota, J.; Insalaco, A.; Conti, G.; Giudice, E.; Lubrano, R.; Breda, L.; Maggio, M.C.; Civino, A.; Mastrorilli, V. et al. Preliminary data revealing efficacy of Sterptococcus salivarius (SSK12) in Periodic Fever, Apthous stomatitis, Pharygitis, and cervical Adenitis (PFAPA) syndrome: A multicenter study from the AIDA Network PFAPA syndrome registry. Front. Med.; 2023; 10, 1105605. [DOI: https://dx.doi.org/10.3389/fmed.2023.1105605] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/36873863]
42. Yuan, H.; Qiu, J.; Zhang, T.; Wu, X.; Zhou, J.; Park, S. Quantitative Changes of Veillonella, Streptococcus, and Neisseria in the Oral Cavity of Patients with Recurrent Aphthous Stomatitis: A Systematic Review and Meta-Analysis. Arch. Oral Biol.; 2021; 129, 105198. [DOI: https://dx.doi.org/10.1016/j.archoralbio.2021.105198] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/34167010]
43. Di Spirito, F.; Pisano, M.; Di Palo, M.P.; Franci, G.; Rupe, A.; Fiorino, A.; Rengo, C. Peri-Implantitis-Associated Microbiota before and after Peri-Implantitis Treatment, the Biofilm “Competitive Balancing” Effect: A Systematic Review of Randomized Controlled Trials. Microorganisms; 2024; 12, 1965. [DOI: https://dx.doi.org/10.3390/microorganisms12101965]
44. Han, Y.; Wang, B.; Gao, H.; He, C.; Hua, R.; Liang, C.; Xin, S.; Wang, Y.; Xu, J. Insight into the Relationship between Oral Microbiota and the Inflammatory Bowel Disease. Microorganisms; 2022; 10, 1868. [DOI: https://dx.doi.org/10.3390/microorganisms10091868] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/36144470]
45. Laserna-Mendieta, E.J.; FitzGerald, J.A.; Arias-Gonzalez, L.; Ollala, J.M.; Bernardo, D.; Claesson, M.J.; Lucendo, A.J. Esophageal microbiome in active eosinophilic esophagitis and changes induced by different therapies. Sci. Rep.; 2021; 11, 7113. [DOI: https://dx.doi.org/10.1038/s41598-021-86464-z]
46. Furuta, G.T.; Fillon, S.A.; Williamson, K.M.; Robertson, C.E.; Stevens, M.J.; Aceves, S.S.; Arva, N.C.; Chehade, M.; Collins, M.H.; Davis, C.M. et al. Mucosal microbiota associated with eosinophilic esophagitis and eosinophilic gastritis. J. Pediatr. Gastroenterol. Nutr.; 2023; 76, pp. 347-354.
47. Hirano, I.; Moy, N.; Heckman, M.G.; Thomas, C.S.; Gonsalves, N.; Achem, S.R. Endoscopic Assessment of the Oesophageal Features of Eosinophilic Oesophagitis: Validation of a Novel Classification and Grading System. Gut; 2013; 62, pp. 489-495. [DOI: https://dx.doi.org/10.1136/gutjnl-2011-301817]
48. Dellon, E.S.; Muir, A.B.; Katzka, D.A.; Shah, S.C.; Sauer, B.G.; Aceves, S.S.; Furuta, G.T.; Gonsalves, N.; Hirano, I. ACG Clinical Guideline: Diagnosis and Management of Eosinophilic Esophagitis. Am. J. Gastroenterol.; 2025; 120, pp. 31-59. [DOI: https://dx.doi.org/10.14309/ajg.0000000000003194]
49. Gall, A.; Fero, J.; McCoy, C.; Claywell, B.C.; Sanchez, C.A.; Blount, P.L.; Li, X.; Vaughan, T.L.; Matsen, F.A.; Reid, B.J. et al. Bacterial Composition of the Human Upper Gastrointestinal Tract Microbiome Is Dynamic and Associated with Genomic Instability in a Barrett’s Esophagus Cohort. PLoS ONE; 2015; 10, e0129055. [DOI: https://dx.doi.org/10.1371/journal.pone.0129055]
50. Dellon, E.S.; Cotton, C.C.; Gebhart, J.H.; Higgins, L.L.; Beitia, R.; Woosley, J.T.; Shaheen, N.J. Accuracy of the Eosinophilic Esophagitis Endoscopic Reference Score in Diagnosis and Determining Response to Treatment. Clin. Gastroenterol. Hepatol.; 2016; 14, pp. 31-39. [DOI: https://dx.doi.org/10.1016/j.cgh.2015.08.040]
51. Juge, N. Relationship between Mucosa-Associated Gut Microbiota and Human Diseases. Biochem. Soc. Trans.; 2022; 50, pp. 1225-1236. [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/36214382]
52. Shimizu, H.; Arai, K.; Tang, J.; Hosoi, K.; Funayama, R. 5-Aminosalicylate Intolerance Causing Exacerbation in Pediatric Ulcerative Colitis. Pediatr. Int.; 2017; 59, pp. 583-587. [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28063246]
53. Hayashi, A.; Mikami, Y.; Miyamoto, K.; Kamada, N.; Sato, T.; Mizuno, S.; Naganuma, M.; Teratani, T.; Aoki, R.; Fukuda, S. et al. Intestinal Dysbiosis and Biotin Deprivation Induce Alopecia Through Overgrowth of Lactobacillus Murinus in Mice. Cell Rep.; 2017; 20, pp. 1513-1524. [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28813664]
54. Klindworth, A.; Pruesse, E.; Schweer, T.; Peplies, J.; Quast, C.; Horn, M.; Glöckner, F.O. Evaluation of General 16S Ribosomal RNA Gene PCR Primers for Classical and Next-Generation Sequencing-Based Diversity Studies. Nucleic Acids Res.; 2013; 41, e1.
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Details
; Tei Tei Go 1
; Shogen Yo 1 ; Monden, Shuzo 1 ; Ninomiya, Takahirao 1 ; Oosawa, Motoyasu 1 ; Handa, Osamu 1
; Umegaki, Eiji 1
; Inoue, Ryo 2
; Shiotani, Akiko 1
1 Department of Gastroenterology, Kawasaki Medical School, Okayama 701-0192, Japan;
2 Faculty of Agriculture, Setsunan University, Hirakata-City 573-0101, Japan;