Evaluation of periodontal status in gastritis patients with clinical and microbiological parameters

Evaluation of periodontal status in gastritis patients with clinical and microbiological parameters | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Evaluation of periodontal status in gastritis patients with clinical and microbiological parameters Ece Erdem Altınyürek, Veli Özgen Öztürk This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8849413/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 14 You are reading this latest preprint version Abstract Background Gastritis is characterized by alterations in the gastric microbiota. This dysbiosis in the stomach may affect immune system regulation as well as influence the oral microbiota. Periodontal disease results from dysbiosis of subgingival microbial communities that cause inflammatory responses in periodontal tissues. The aim of our study is to examine the oral flora profile and dysbiosis status of gastritis patients along with their periodontal status. Methods A total of 30 patients were included in our study, divided into two groups 15 patients diagnosed with gastritis and 15 systemically healthy individuals. Subsequently, the patients were subdivided into subgroups as periodontally healthy, gingivitis, and stage 1 periodontitis based on their periodontal status. Clinical periodontal parameters and saliva samples were collected. The microbial flora was analyzed using metagenomic analysis through next-generation sequencing methods. Clinical and microbiological parameters were evaluated using non-parametric statistical methods. Results While no differences were observed in any metric in beta diversity analysis across gender groups, study groups, and subgroups, bacterial diversity was found to be higher in women in the Simpson, Shannon and Chao1 metrics in alpha diversity analysis, In the subgroups, a significant increase was observed in the stage 1 periodontitis-gastritis group in the Chao1 metric. Bacterial taxa that showed statistically significant differences between the groups and subgroups were identified using LEfSe analysis. Conclusion Our study underscore dysbiosis in the oral flora in the context of gastritis while also taking into account the periodontal status. Gastritis with periodontitis may enhance the microbial diversity and density. Future research studies are needed to unravel systemic interaction between periodontitits and gastritis. Trial Registration: This clinical trial was registered at ClinicTrials.gov (NCT07378540) Registeration Date: 29/01/2026. Periodontitis gastritis dysbiosis next generation sequencing metagenomic microbiome Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Backgroud Gastritis typically begins in childhood as a simple inflammatory condition accompanied by varying degrees of acute neutrophilic inflammation (1). The earliest recognized histological alteration is active chronic inflammation, which may persist as non-atrophic chronic gastritis without glandular loss or may progress to multifocal atrophic gastritis, the first true step in the precancerous cascade (2). Globally, Helicobacter pylori is regarded as the principal etiological factor for chronic gastritis and, over time, can lead to the progressive destruction of gastric glands characteristic of multifocal atrophic gastritis (3,4). Periodontal diseases and conditions comprise a spectrum of disorders that affect the tissues supporting the teeth. Bacteria are essential for the development of destructive periodontal diseases (5). Dysbiosis is defined as a disruption that leads to an imbalance in the microbiota, resulting in alterations in the functional composition and metabolic activities of the microbial community or shifts in its local distribution. Dysbiosis has been implicated in a wide range of diseases in both human and animal models, including inflammatory bowel disease (IBD), obesity, allergic disorders, type 1 diabetes mellitus, autism, and colorectal cancer (6,7). Periodontal disease arises from dysbiosis of subgingival microbial communities that adversely affect the host immune system, generating and sustaining unabated inflammation within the gingival and periodontal tissues, thereby inhibiting immune resolution and preventing tissue repair. Numerous studies have demonstrated that the predominant microorganisms within dental plaque changes across depending on periodontal health, gingivitis and periodontitis (8). However, limited research has founded on the spesific relationship between oral microbiota and gastritis in terms of dysbiotic era. In our study, we aimed to examine the oral microbiota of patients with gastritis in relation to periodontal parameters. The purpose of this study is to evaluate the levels of microorganisms in the salivary flora of patients with gastritis, their clinical periodontal parameters, and the relationships between these variables. Methods Patient Selection This study was designed as a prospective, observational, case-control study. Participants in our study were selected in order of admission from among patients who presented to the Faculty of Dentistry at Aydın Adnan Menderes University for periodontal treatment between 1 November 2023 and 15 January 2024. A total of 30 patients were included, comprising 15 individuals with no systemic diseases and 15 individuals diagnosed with gastritis via endoscopic examination who had no additional systemic conditions. Patients who were non-smokers, over 18 years of age, had at least 20 teeth, were not undergoing orthodontic treatment, and were not using medications regularly for gastritis or any other condition were included in the study. Patients who were pregnant or in the lactation period, those who had used medications that could affect periodontal status or microbial flora (such as antibiotics or corticosteroids) within the three months preceding sample collection, and those who had received periodontal treatment within the past six months were excluded from the study. Intraoral examinations of all patients included in our study were first performed, and their periodontal parameters were recorded immediately. One week later, saliva samples were collected for microbiological analysis. Patients were further classified into subgroups according to their periodontal status: periodontally healthy (PH-Gas, PH-Cont), gingivitis (Gin-Gas, Gin-Cont) and stage 1 periodontitis (Stage 1P-Gas, Stage 1P-Cont), the schematic distribution is presented in Fig. 1 . Classification of patients into subgroups was based on the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions (9,10). Following the establishment of the study protocol, ethical approval was obtained from the Clinical Research Ethics Committee of the Faculty of Dentistry, Aydın Adnan Menderes University, in accordance with the ethical principles of the 2013 Declaration of Helsinki (approval date: 25.10.2023; protocol number: AADÜDHF 2023/27) and registered at ClinicTrials.gov (NCT07378540) with registeration date 29/01/2026. All patients were provided with detailed information regarding the purpose and content of the study following their admission, and informed consent was obtained through a signed voluntary participation form. Periodontal parameters For each patient, full-mouth probing depth (PD), clinical attachment loss (CAL), dichotomous scoring of bleeding on probing (BOP), and plaque index (PI) scores (Silness and Löe, 1967) were recorded at six sites per tooth by single investigator (E.E.A.). Saliva collection As a standard protocol (11), individuals included in the study were asked to refrain from consuming any food for at least one hour prior to sample collection and to present to the clinic without performing any oral hygiene procedures after the night before. Unstimulated saliva samples were collected from all patients in the morning, at approximately the same time, into sterile saliva containers and then transferred into sterile Eppendorf tubes (Axygen Snaplock Microcentrifuge Tubes 1.5 mL, USA) using a sterile syringe. The saliva samples were stored in the existing Eppendorf tubes at − 80°C in the deep freezer located in the Department of Periodontology, Faculty of Dentistry, Aydın Adnan Menderes University, until the day of transport. DNA Extraction Oral samples were collected in 1.5 mL of DiaRex® RNALater Stabilization Solution (DiaGen, Turkey). The samples were stored at − 80°C until DNA extraction. Immediately prior to extraction, the samples were thawed and diluted with 9 mL of phosphate-buffered saline (PBS). Before removal of the swabs, the tubes were gently agitated in a circular motion. The sample suspensions were centrifuged at 400 × g for 10 minutes. Following centrifugation, the supernatant was discarded and the extraction was continued using the pellet. DNA extraction from the pellet was performed using the QuickGene DNA Tissue Kit S (DT-S, Japan). The pellet was treated with 250 µL of MDT and 25 µL of EDT (Proteinase K) solution and incubated at 56°C for 60 minutes. After the addition of 180 µL of LDT solution, the tubes were vortexed for 15 seconds and incubated at 70°C for 10 minutes. Subsequently, 240 µL of ice-cold 99% ethanol was added, and the samples were vortexed for 15 seconds. Immediately thereafter, the entire volume in the microcentrifuge tube was transferred to QuickGene (Kurabo) columns and washed three times with 750 µL of WDT solution. Finally, 50–60 ng of genomic DNA was eluted by adding 200 µL of CDT solution to the QuickGene (Kurabo) columns and collected into a new sterile 1.5 mL microcentrifuge tube. The extracted DNA was amplified using 16S rRNA gene V3–V4 primer sets. Library preparation was performed using the Nextera XT DNA Library Preparation Kit and index adapters (Illumina). The pooled library was purified with size selection according to the manufacturer’s protocol using AMPure XP beads (Beckman Coulter). Following library preparation, sequencing was carried out on the MiSeq platform (Illumina). Bioinformatic and statistic Paired-end (2 × 250) Illumina reads were imported into the QIIME 2 pipeline (12). In the initial assessment, all samples were found to reach a sequencing depth exceeding approximately 50×, with a comparable distribution across samples. No samples were excluded from the analysis. Data quality was filtered within QIIME 2 using the DADA2 algorithm, and regions with a quality score below 30 were removed to generate amplicon sequence variants (ASVs) (13). After quality filtering, a total of 1,824,084 reads were retained for downstream analysis, and 2,096 ASVs were identified. The resulting ASVs were assigned taxonomy using the SILVA 138 reference database to generate taxonomic tables (14). Files generated by QIIME 2 were processed using the R programming language and RStudio for data visualization and biostatistical analyses. Alpha diversity was assessed using the Chao1, Shannon, and Simpson indices, and statistical comparisons between groups were performed using the Kruskal–Wallis test. Beta diversity was evaluated based on Jaccard, Bray–Curtis, weighted UniFrac, and unweighted UniFrac distance metrics, and group differences were tested using PERMANOVA, which was performed using the Adonis. The most prominent differences between groups were identified using LEfSe analysis, and taxa with p value < 0.05 and LDA score greater than 2 were reported. Results Clinical Data The socio-demographic data of the patients included in our study are given in Table 1 ; the groups were found to be statistically similar in terms of age and gender (p = 0,16). No statistically significant differences were observed in probing depth (PD), clinical attachment level (CAL), bleeding on probing (BP), and plaque index (PI) among the study groups and subgroups. Clinical periodontal parameters in the groups and subgroups are presented in Tables 1 and 3 , while the p-values are provided in Tables 2 and 4 . Table 1 Demographic features and clinical parameter of study groups Clinical parameters Gastritis (n = 15) Healty (n = 15) Age Min-Max 21–59 20–55 Median 35 27 Gender Female 9 9 Male 6 6 Probing Depth(mm) Min-Max 1,26 − 3,2 1,42 − 2,26 Median 1,78 1,7 Standard deviation 0,49 0,232 Clinical Attachment Level (mm) Min-Max 0,01–3,4 0,26 − 2,32 Median 1,6 1,5 Standard deviation 0,92 0,66 Bleeding on Probing (-/+) Min-Max 2–75 2–83 Median 42 34 Standard deviation 24,7 28,3 Plaque İndex Min-Max 0,5 − 1,78 0,47 − 2 Median 1,13 1,23 Standard deviation 0,4 0,477 Table 2 Statistical analysis of clinical periodontal parameters in gastritis and control group patients PD CAL BOP PI p value (Mann Whitney U) 0,95 0,66 0,93 0,87 Table 3 Clinical periodontal parameters of subgroups Clinical parameters Control- PH Control-Gin Control-Stage 1 P Gastritis-PH Gastritis-Gin Gastritis-Stage 1 P PD (mm) Min-Max 1,42 − 1,66 1,55 − 1,92 1,82 − 2,26 1,26 − 1,59 1,37 − 1,99 2–3,2 Median 1,51 1,7 2 1,42 1,78 2,26 Standard deviation 0,1 0,136 0,188 0,134 0,215 14,15 CAL (mm) Min-Max 0,26 − 0,66 1,35 − 1,72 1,98 − 2,32 0,01 − 0,64 1,27 − 1,79 2,21 − 3,04 Median 0,43 1,5 2,11 0,25 1,6 2,65 Standard deviation 0,179 0,136 0,154 0,264 0,19 0,383 BOP (%) Min-Max 2–7 12–79 17–83 2–10 14–75 42–70 Median 3,5 45 46 7 44 54 Standard deviation 2,38 22,76 28,15 3,41 21,4 14,58 PI Min-Max 0,47 − 0,72 1,16 − 2 0,68 − 1,77 0,5 − 0,96 0,9 − 1,78 0,97 − 1,64 Median 0,62 1,44 1,26 1,14 1,54 Standard deviation 0,121 0,279 0,513 0,19 0,318 0,31 Table 4 Mann Whitney U analysis p-values ​​of clinical periodontal parameters of subgroups PD Gastritis PH- Control PH Gastritis Gin- Control Gin Gastritis Stage 1- Control Stage 1 0,4 0,8 0,25 CAL 0,37 0,37 0,066 BOP 0,5 0,82 0,82 PI 0,99 0,52 0,99 Microbiological Analysis Microbiological evaluations were performed on both gastritis and control group patients, including subgroups. In total, bacterial examinations were conducted at the level of 15 phyla, 27 classes, 60 orders, 100 families, 199 genera, and 207 species. The distribution of bacteria across groups and subgroups is presented in Fig. 2 . Microbial Diversity Alpha Diversity Alpha analysis showed that women had higher microbial diversity and density than men, according to the Simpson (p = 0.0014) and Shannon (p = 0.00981) metrics. Alpha analysis showed no difference in bacterial diversity and density between the gastritis and control groups in the Simpson (p = 0.983), Shannon (p = 0,755), and chao1 (p = 0,35) metrics. However, in the subgroups, the Stage 1P-Gas group had a significantly higher chao1 index than the other groups (p = 0.032). The graphs of the alpha analysis in groups are shown in Fig. 3 . Beta Diversity Beta diversity was assessed using principal component analysis (PCA) and “principal coordinates analysis (PCoA) analyses. PCoA of beta diversity was performed using Bray–Curtis, Jaccard, weighted UniFrac, and unweighted UniFrac distance metrics. No significant differences were found in any metric across study groups, gender groups, and subgroups (all p > 0.05). (Fig. 4 ) Taxonomic Difference Krona analysis was used to determine the most common bacterial species and their proportions in the groups and bacterial distribution diagram of gastritis and control groups given in Fig. 5 . In the gastritis group, the most abundant bacteria at the phylum level are Firmicutes (38%), Bacteroidota (34%), and Proteobacteria (14%); at the genus level, Prevotella (28%), Veillonella (23%), and Neisseria (8%); and at the species level, Prevotella melaninogenica (27.32%), Prevotella pallens (5.38%), and Megasphaera micronuciformis (5.14%). In the control group, the most abundant bacteria were Firmicutes (38%), Bacteroidota (31%), and Proteobacteria (18%) at the phylum level; Prevotella (24%), Veillonella (23%), and Neisseria (10%) at the genus level; and Prevotella melaninogenica (29.9%), Megasphaera micronuciformis (6.13%), and Prevotella pallens (6.11%) at the species level. According to LEfSe analysis, in the gastritis group, Verrucomicrobiota at the phylum level, Lactobacillacea, Bacteriodaceae, Bifidobactericaea, Ruminococcaea and Akkermansiaceae at the family level, Desulfovibrionales, Bifidobacteriales, Oscillospirales and Verrucomicrobiales at the order level, Lactobacillus, Bacteroides, Faecalibacterium, Akkermansia, Gardnerella and Bulleidia at the genus level, and Prevotella multisaccharivorax, Lactobacillus spp, Leptotrichia shahii, Dialister pneumosintes, Akkermansia muciniphila, Faecalibacterium spp, Gardnerella spp, Prevotella bacterium and Bulleidia extructa at the species level were found to be statistically significantly higher. In the healthy control group, Alysiella at the genus level, and Rothia spp, Treponema pedis and Alysella spp at the species level were found to be statistically significantly higher. (Fig. 6 ) When evaluated at the subgroup level using LEfSe analysis, at the species level, Campylobacter showae was significantly enriched in the PH-Cont group. The PH-Gas group showed significant enrichment of Prevotella oulorum and Selenomonas flueggei . In the Gin-Gas group, significant enrichment was observed at the family level for Lactobacillaceae and at the genus level for Lactobacillus . The Gin-ConT group exhibited a higher abundance of Prevotella dentalis and Prevotella enoeca at the species level. In the Stage 1P-Gas group, significant enrichment was detected at the order level Oscillospirales , Enterobacterales , and Izemoplasmotales , family level Desulfomicrobiaceae , Enterobacteriaceae , and Izemoplasmotales , genus level Eubacterium saphenum group, Desulfomicrobium , Faecalibacterium , Escherichia–Shigella , and Izemoplasmotales , and species level Eubacterium saphenum . (Fig. 6 ) According to the Lefse analysis, the p-values ​​and LDA scores of bacteria that differed in groups and subgroups are given in Table S1 and S2. Discussion Recent advancements in sequencing techniques for next-generation processes, which analyze DNA and RNA regions, allow for comprehensive analysis of bacterial diversity from complex environmental samples and to examine the composition and variety of microbial communities. 16S rRNA gene sequences have become by far the most widely used genetic marker due to their presence in almost all bacteria, usually as a multigene family or operon, the invariance of their gene function over time, and their sufficiently large size (1,500 bp) for computational purposes (15). Our study included 18 female and 12 male patients. According to alpha diversity analysis, bacterial diversity and density were found to be statistically significantly higher in women. There are few studies in the literature that show differences in salivary microbiomes between women and men and the differences found in these studies have been attributed to hormonal changes and personal hygiene habits (16,17). In addition, there are numerous studies showing that the salivary microbiomes of women and men are not different (18–21). The fact that the number of female patients was 50% higher than the number of male patients in our study may have resulted in a higher diversity and density of microorganisms in women. In a study by Chen et al (21), saliva samples from gastritis patients and healthy patients were analyzed using 16S rRNA gene amplicon sequencing, and no significant difference was found according to alpha and beta diversity analysis. The results of this study regarding diversity and intensity are consistent with our study, but this study did not examine the periodontal status of the patients. Therefore, the effect of the periodontal condition on the microbiota cannot be assessed. In a study by Cui et al. (22), tongue swabs were taken from gastritis and control group patients and analyzed by 16S rRNA gene applicon sequencing. Alpha and beta analysis revealed statistically significantly less diversity among patient groups in the gastritis group. However, this study also included patients diagnosed with intestinal metaplasia via endoscopic methods in addition to gastritis patients, and tongue swab samples were used. The difference in sampling method and sample location between this study and our study may have resulted in differences in microbial content and density. In the study by Chen et al. (21), according to LEfSe analysis, the bacteria that were enriched in the gastritis group were Ruminococcaceae, Sutterella, Lactobacillaceae at the phylum level, and Sutterella and Lactobacillus at the genus level, while in the control group they were Mitochondria and Corynebacterium-1 , and these findings are largely consistent with our study. Based on these results, we can say that in cases of gastritis, the oral flora shifts towards dysbiosis with an increase in Ruminococcaceae and Lactobacillaceae bacteria at the family level. In the study conducted by Cui et al. (22), the bacteria that were enriched in the gastritis group according to LEfSe analysis were identified as Streptococcus infantis , Treponema vincentii, Leptotrichia unclassified, Campylobacter rectus, Campylobacter showae, Capnocytophaga gingivalis, Leptotrichia buccalis, Campylobacter concisus, Selenomonas flueggei and Leptotrichia hofstadii at the species level. The results of this study do not appear to be consistent with the results of our study; however, in the study conducted by Cui et al., patients diagnosed with intestinal metaplasia, an advanced stage of gastritis, were also included in the gastritis group, and tongue swab samples were used instead of saliva samples. Due to differences in the study group and the microbial diversity in the salivary and tongue regions within the mouth, it is thought that the results obtained are not consistent with the results of our study. When the LEfSe analysis was evaluated at the subgroup level, Campylobacter showae was found to be statistically significantly higher at the species level in the PH-Cont group, Prevotella oulorum and Selenomonas flueggei at the species level in the PH-Gas group, Lactobacillus at the genus level in the Gin-Gas group, Prevotella dentalis and Prevotella enoeca at the species level in the Gin-Cont group, and Eubacterium saphenum (group) , Desulfumicrobium, Faecalibacterium, Escherichia-Shigella and Izemoplasmotales at the genus level, and Eubacterium saphenum at the species level in the Stage 1P-Gas group. A significant finding here is that the number of bacterial species enriched in the group with periodontal disease accompanying gastritis is higher compared to other groups. Furthermore, according to alpha diversity analysis in our study, a statistically significant difference in bacterial diversity and density was found in the Stage 1P-Gas group. In the literature, when 16S rRNA-based studies are evaluated according to periodontal conditions, it has been observed in many studies that Actynomyces, Rothia, Streptococcus , and Carynebacterium species are found in healthy periodontal patients, Selenomonas and Prevotella species increase in patients with gingivitis, and microbial diversity and load increase significantly in periodontal disease patients (5,23,24). These results are largely consistent with the results of our study. The significant difference in diversity and intensity observed in the Stage 1P-Gas group in our study may be due to the microbial aspect of periodontal disease or to dysbiosis caused by gastritis. Although furter studies would be needed to investigate this hypotesis, due to the cross-sectional design of our study limits the ability to infer causality. Our study found no statistically significant differences in bacterial diversity, density, and phylogenetic distribution between the gastritis and control groups. The reason may be due to the small number of periodontitis patients in each group. When subgroups were evaluated, the diversity and density were found to be higher in the Stage 1P-Gas group than in other subgroups, and this can be interpreted as gastritis increasing dysbiosis in the oral flora caused by periodontal disease. This is one of our study limitations; sample size though sufficient to detect key differences, remains relatively small participant limit the applicability of the results. In our study, we analyzed Aggregatibacter actynomycetemcomitans, Capnocytophaga species, Filifactor alocis, Porphyromanas gingivalis, Prevotella intermedia, Prevotella nigrescens, Tannarella forsythia , and Treponema denticola bacteria, which are associated with periodontal disease. No species among these bacteria showed significant differences at the group or subgroup level. In a study by Salazar et al. (25), saliva and plaque samples were taken from patients with gastric precancerous lesions and a healthy patient group, and the levels of perio-pathogenic bacteria were compared. Although an increase in the amount of perio-pathogenic bacteria was observed with the increase in periodontal disease markers (probing depth, bleeding on probing) in both groups, an increase in T. forsythia levels was observed only in the saliva of the precancerous lesion group, and this increase was not observed in plaque. Apart from that, bacterial levels were found to be similar in both groups. The results of our study are consistent with that study. In this study, Eubacterium saphenum was found to be significantly higher in the Stage 1P-Gas group. Studies have shown that this bacterium is associated with increased periods of periodontal disease (26–30), and our study supports this finding, with further research in this area, we believe that this bacteria may also be associated with periodontal disease. In addition, Desulfomicrobium orale (31), a sulfate reductase, has been associated with periodontitis. The increase in sulfate-reducing bacteria in periodontal disease is associated with periodontal disease due to the toxic effect of h 2 s on epithelial cells (32,33). Although this bacterial species did not appear different in our study, the genus-level sulfate reductase family Desulfomicrobiale was found to be elevated in the Stage 1P-Gas group. Further research is needed into the relationship between this bacterium and periodontal disease, and how this mechanism contributes to the progression of periodontal disease. In a study by Contaldo et al. (34), the levels of P. gingivalis and F. nucleatum were examined in saliva samples from chronic gastritis and healthy patient groups using real-time PCR analysis. The levels of P. gingivalis and F. nucleatum were found to be significantly lower in the chronic gastritis group. However, the periodontal status of the patients was not examined in this study. This could be speculated that the association between the severity periodontal status and microbiota. This stregth in our study, patients were divided into subgroups according to their periodontal status, and the number of patients in each group was kept equal. In our study, the company performing the metagenomic analysis uses a standardized analysis kit that allows for the quantification and inclusion of only the bacterial taxa contained within the kit; the addition of optional or custom bacteria is not possible. Consequently, Helicobacter pylori , a major etiological agent of gastritis, could not be analyzed as it was not included in the kit. Future studies could incorporate this bacterium into the analysis and be designed to include only H. pylori –positive patients. Another limitation of our study is the limited number of patients with periodontitis and the absence of individuals with advanced-stage periodontal disease in the study groups. This may be attributed to the fact that gastritis typically manifests at a younger age, whereas periodontal disease tends to develop later in life. As observed in our study, microbial diversity and abundance increase when gastritis and periodontal disease coexist. We believe that more definitive conclusions could be achieved with a larger number of patients with periodontitis or with the inclusion of individuals with advanced-stage periodontitis. Conclusion This study is important in that, while examining the variation of gastritis on the oral flora, it also takes periodontal status and oral hygiene into consideration. The significant difference in diversity and intensity observed in the Stage 1P-Gas group in our study may be due to the microbial aspect of periodontal disease or to dysbiosis caused by gastritis. Abbreviations IBD Inflammatory bowel disease PH-Gas Periodontal healty- Gastritis PH-Cont Periodontal healty- Control Gin-Gas Gingivitis- Gastritis Gin-Cont Gingivitis- Control Stage 1P-Gas Stage 1 Periodontitis- Gastritis Stage 1P-Cont Stage 1 Periodontitis- Control PD Probing depth CAL Clinic attachment level BOP Bleeding on probing PI Plaque index ASV Amplicon sequence variants PBS Phosphate-buffered saline Declarations Acknowlidgements The authors extend their sincere gratitude to all the patients who generously participated in this study. Author Contribution E.E.A. made the patient selection, collect the clinical data and saliva samples. V.Ö.Ö planned and desgined the study, made critical revisions. All authors contributed to manuscript drafting and final approval of the published version. Funding This research has been supported by Aydın Adnan Menderes University Scientific Research Projects Unit. (Project Number: DHF-24004) Data Availability Statement The data that support the findings of this study are available from the corresponding author upon reasonable request. The raw sequencing data have been deposited in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) database under PRJNA1430215. Conflict Of Interest Statement The authors explicitly state that there are no competing interests in connection with this study. Ethics approval and consent to participate Ethical approval was obtained from the Clinical Research Ethics Committee of the Faculty of Dentistry, Aydın Adnan Menderes University, in accordance with the ethical principles of the 2013 Declaration of Helsinki (approval date: 25.10.2023; protocol number: AADÜDHF 2023/27). All patients were provided with detailed information regarding the purpose and content of the study following their admission, and informed consent was obtained through a signed voluntary participation form. Consent for publication Not Applicable. Competing interests The authors declare no competing interests. Author Details Ece Erdem Altınyürek1, Veli Özgen Öztürk1 1 Department of Periodontology, Faculty of Dentistry, Aydın Adnan Menderes University, Aydın, Turkey References Siurala M. The story of gastritis. Scand J Gastroenterol. 1991;26(S186):1–3. Villako K, Kekki M, Maaroos HI, Sipponen P, Tammur R, Tamm A, et al. A 12-Year Follow-up Study of Chronic Gastritis and Helicobacter pylori in a Population-Based Random Sample. Scand J GastroenteroL. 1995;30(10):964–7. Delle Fave G, Kwekkeboom DJ, Van Cutsem E, Rindi G, Kos-Kudla B, Knigge U, et al. ENETS Consensus Guidelines for the management of patients with gastroduodenal neoplasms. Neuroendocrinology. 2012 Feb;95(2):74–87. Annibale B, Esposito G, Lahner E. A current clinical overview of atrophic gastritis. Vol. 14, Expert Review of Gastroenterology and Hepatology. Taylor and Francis Ltd; 2020. p. 93–102. Curtis MA, Diaz PI, Van Dyke TE. The role of the microbiota in periodontal disease. Vol. 83, Periodontology 2000. Blackwell Munksgaard; 2020. p. 14–25. Moos WH, Faller D V., Harpp DN, Kanara I, Pernokas J, Powers WR, et al. Microbiota and Neurological Disorders: A Gut Feeling. Biores Open Access. 2016 May 1;5(1):137–45. Tamboli CP, Neut C, Desreumaux P, Colombel JF. Dysbiosis in inflammatory bowel disease. Gut. 2004;53(1):1-4. doi:10.1136/gut.53.1.1 Hajishengallis G. Periodontitis: from microbial immune subversion to systemic inflammation. Nat Rev Immunol. 2015 Jan 1;15(1):30–44. Chapple ILC, Mealey BL, Van Dyke TE, Bartold PM, Dommisch H, Eickholz P, et al. Periodontal health and gingival diseases and conditions on an intact and a reduced periodontium: Consensus report of workgroup 1 of the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions. J Periodontol. 2018 Jun 1;89:S74–84. Papapanou PN, Sanz M, Buduneli N, Dietrich T, Feres M, Fine DH, et al. Periodontitis: Consensus report of workgroup 2 of the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions. J Periodontol. 2018 Jun 1;89:S173–82. Navazesh M. Methods for collecting saliva. Ann N Y Acad Sci. 1993;694:72-77. doi:10.1111/j.1749-6632.1993.tb18343.x Austin B. The value of cultures to modern microbiology. Antonie Van Leeuwenhoek. 2017 Oct 1;110(10):1247–56. Hayashi H, Sakamoto M, Benno Y. Phylogenetic analysis of the human gut microbiota using 16S rDNA clone libraries and strictly anaerobic culture-based methods. Microbiol Immunol. 2002;46(8):535–48. Ranjan R, Rani A, Metwally A, McGee HS, Perkins DL. Analysis of the microbiome: Advantages of whole genome shotgun versus 16S amplicon sequencing. Biochem Biophys Res Commun. 2016 Jan 22;469(4):967–77. JB P. 16S rRNA gene sequencing for bacterial pathogen identification in the clinical laboratory. Mol Diagn. 2001 Dec;6(4):313–21. Liu X, Tong X, Jie Z, Zhu J, Tian L, Sun Q, et al. Sex differences in the oral microbiome, host traits, and their causal relationships. iScience. 2023 Jan 20;26(1). Umeda M, Chen C, Bakker I, Contreras A, Morrison JL, Slots J. Risk indicators for harboring periodontal pathogens. J Periodontol. 1998 Oct;69(10):1111–8. Slots J, Feik D, Rams TE. Age and sex relationships of superinfecting microorganisms in periodontitis patients. Oral Microbiol Immunol. 1990;5(6):305–8. Schenkein HA, Burmeister JA, Koertge TE, Brooks CN, Best AM, Moore LVH, et al. The influence of race and gender on periodontal microflora. J Periodontol. 1993 Apr;64(4):292–6. Corby PMA, Bretz WA, Hart TC, Melo Filho M, Oliveira B, Vanyukov M. Mutans streptococci in preschool twins. Arch Oral Biol. 2005;50(3):347–51. Chen M, Fan HN, Chen XY, Yi YC, Zhang J, Zhu JS. Alterations in the saliva microbiome in patients with gastritis and small bowel inflammation. Microb Pathog. 2022 Apr 1;165. Cui J, Cui H, Yang M, Du S, Li J, Li Y, et al. Tongue coating microbiome as a potential biomarker for gastritis including precancerous cascade. Protein Cell. 2019 Jul 1;10(7):496–509. Hong BY, Araujo MVF, Strausbaugh LD, Terzi E, Ioannidou E, Diaz PI. Microbiome profiles in periodontitis in relation to host and disease characteristics. PLoS One. 2015 May 18;10(5). Abusleme L, Hoare A, Hong BY, Diaz PI. Microbial signatures of health, gingivitis, and periodontitis. Vol. 86, Periodontology 2000. Blackwell Munksgaard; 2021. p. 57–78. Salazar CR, Sun J, Li Y, Francois F, Corby P. Association between Selected Oral Pathogens and Gastric Precancerous Lesions. PLoS One. 2013;8(1):51604. Abusleme L, Dupuy AK, Dutzan N, Silva N, Burleson JA, Strausbaugh LD, et al. The subgingival microbiome in health and periodontitis and its relationship with community biomass and inflammation. ISME J. 2013 May;7(5):1016–25. Griffen AL, Beall CJ, Campbell JH, Firestone ND, Kumar PS, Yang ZK, et al. Distinct and complex bacterial profiles in human periodontitis and health revealed by 16S pyrosequencing. ISME J. 2012 Jun;6(6):1176–85. Abiko Y, Sato T, Mayanagi G, Takahashi N. Profiling of subgingival plaque biofilm microflora from periodontally healthy subjects and from subjects with periodontitis using quantitative real-time PCR. J Periodontal Res. 2010 Jun;45(3):389–95. Mayanagi G, Sato T, Shimauchi H, Takahashi N. Detection frequency of periodontitis-associated bacteria by polymerase chain reaction in subgingival and supragingival plaque of periodontitis and healthy subjects. Oral Microbiol Immunol. 2004 Dec;19(6):379–85. Kumar PS, Griffen AL, Barton JA, Paster BJ, Moeschberger ML, Leys EJ. New bacterial species associated with chronic periodontitis. J Dent Res. 2003;82(5):338–44. Langendijk PS, Kulik EM, Sandmeier H, Meyer J, van der Hoeven JS. Isolation of Desulfomicrobium orale sp. nov. and Desulfovibrio strain NY682, oral sulfate-reducing bacteria involved in human periodontal disease. Int J Syst Evol Microbiol. 2001;51(3):1035–44. Shu W, Du B, Wu G. Strategies for enriching targeted sulfate-reducing bacteria and revealing their microbial interactions in anaerobic digestion ecosystems. Water Res. 2025 Feb 15;270:122842. Kushkevych I, Coufalová M, Vítězová M, Rittmann SKMR. Sulfate-Reducing Bacteria of the Oral Cavity and Their Relation with Periodontitis—Recent Advances. Journal of Clinical Medicine 2020, Vol 9, Page 2347. 2020 Jul 23;9(8):2347. Contaldo M, Fusco A, Stiuso P, Lama S, Gravina AG, Itro A, et al. Oral microbiota and salivary levels of oral pathogens in gastro‐intestinal diseases: Current knowledge and exploratory study. Vol. 9, Microorganisms. MDPI AG; 2021. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8849413","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":626105312,"identity":"0fe1d608-e0aa-46f5-8724-bb67935511e5","order_by":0,"name":"Ece Erdem Altınyürek","email":"","orcid":"","institution":"Aydın Adnan Menderes University","correspondingAuthor":false,"prefix":"","firstName":"Ece","middleName":"Erdem","lastName":"Altınyürek","suffix":""},{"id":626105313,"identity":"37bba3ba-7f5a-444c-a5cd-8ace18759715","order_by":1,"name":"Veli Özgen Öztürk","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8klEQVRIiWNgGAWjYJADZoYPQAwEBsSp5wFqYZwB15JApBZmHmK08PMfv/i4gMHG3l4i97GxTY11YgN78zYJxh/3cGqRbDhTbDyDIY2ZRyLdODnnWHpiA8+xMgmGhGKcWgwO9qRJ8zAcZuORSGM+nMN2OLFBIscMqAW3ywwO86T/BmrhAWux+AfUIv+GgJZj7MeAvj4sAdKSzNgGsoUHvxbJHh5maR6DNAOeM8+YDXv70o3beNKKLRLScGsBhtjDzzwVNvbs7WnMEj++Wcv2sx/eeOODDW4twAgxQI1uNhCBTwMDA/sDvNKjYBSMglEwChgAhOFD14OXbsUAAAAASUVORK5CYII=","orcid":"","institution":"Aydın Adnan Menderes University","correspondingAuthor":true,"prefix":"","firstName":"Veli","middleName":"Özgen","lastName":"Öztürk","suffix":""}],"badges":[],"createdAt":"2026-02-11 08:56:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8849413/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8849413/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107705993,"identity":"3e1fa593-e763-4ba4-a4d4-b23e559bc1c9","added_by":"auto","created_at":"2026-04-24 09:17:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":53443,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic representation of patient distribution\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8849413/v1/c1c7511ca5e8ca58b4f2f968.png"},{"id":107500346,"identity":"77e290c5-0bca-4d7a-a129-c7c5bd41249f","added_by":"auto","created_at":"2026-04-22 05:46:17","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":262160,"visible":true,"origin":"","legend":"\u003cp\u003eThe distribution of bacterial species across groups (A) and subgroups (B).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8849413/v1/2801eb81eaed834f841a5a21.png"},{"id":107705378,"identity":"5f24b740-b3f6-4c5b-8c13-b4c3c7e076d4","added_by":"auto","created_at":"2026-04-24 09:12:05","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":50739,"visible":true,"origin":"","legend":"\u003cp\u003eAlpha diversity and density graphs. Study groups according to simpson (A), shannon (B) and chao1 (C) metrics and subgroups graphs according to simpson (D) and chao1 (E) metrics.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8849413/v1/db1a86d460061f47a808602e.png"},{"id":107705598,"identity":"b210b38e-e2da-406d-9da0-6c6cc8d0d0c5","added_by":"auto","created_at":"2026-04-24 09:13:46","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":89781,"visible":true,"origin":"","legend":"\u003cp\u003eBeta diversity graphs\u003cstrong\u003e.\u003c/strong\u003e In the study groups, PCoA analysis was performed using Bray–Curtis (A), Jaccard (B), weighted UniFrac (C), and unweighted UniFrac (D) metrics. PCA analysis was conducted at the group (E) and subgroup (F) levels.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8849413/v1/8451ffe18bd687c830818372.png"},{"id":107705186,"identity":"a80aea0d-e6c6-4407-a944-10f4fc9a895c","added_by":"auto","created_at":"2026-04-24 09:09:11","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":187294,"visible":true,"origin":"","legend":"\u003cp\u003eDiagrams illustrating bacterial distribution of study groups. (A) Schematic diagram of bacterial distribution of gastritis group. (B) Schematic diagram of bacterial distribution of healty control group\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8849413/v1/36e91e387eb4ae1c38cde4aa.png"},{"id":107705116,"identity":"cc2b9657-8a84-4168-a53a-25f90210ef15","added_by":"auto","created_at":"2026-04-24 09:08:21","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":120102,"visible":true,"origin":"","legend":"\u003cp\u003eGraphs showing the relative abundent bacteria of lefse analysis in groups (A) and subgroups (B).\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8849413/v1/218629f4233b6a52bdc2e785.png"},{"id":107709009,"identity":"b719d536-017e-4975-b04d-af99bf83c6f4","added_by":"auto","created_at":"2026-04-24 09:34:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":993104,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8849413/v1/96321024-8f5a-4057-9d10-f2063ca4cd41.pdf"},{"id":107705583,"identity":"fc2c310c-1cf1-4eb7-8b12-37a9d6a47278","added_by":"auto","created_at":"2026-04-24 09:13:40","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":21852,"visible":true,"origin":"","legend":"","description":"","filename":"suppelementaryfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8849413/v1/727f269f182463eb9822e7dc.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluation of periodontal status in gastritis patients with clinical and microbiological parameters","fulltext":[{"header":"Backgroud","content":"\u003cp\u003eGastritis typically begins in childhood as a simple inflammatory condition accompanied by varying degrees of acute neutrophilic inflammation (1). The earliest recognized histological alteration is active chronic inflammation, which may persist as non-atrophic chronic gastritis without glandular loss or may progress to multifocal atrophic gastritis, the first true step in the precancerous cascade (2). Globally, \u003cem\u003eHelicobacter pylori\u003c/em\u003e is regarded as the principal etiological factor for chronic gastritis and, over time, can lead to the progressive destruction of gastric glands characteristic of multifocal atrophic gastritis (3,4).\u003c/p\u003e \u003cp\u003ePeriodontal diseases and conditions comprise a spectrum of disorders that affect the tissues supporting the teeth. Bacteria are essential for the development of destructive periodontal diseases (5). Dysbiosis is defined as a disruption that leads to an imbalance in the microbiota, resulting in alterations in the functional composition and metabolic activities of the microbial community or shifts in its local distribution. Dysbiosis has been implicated in a wide range of diseases in both human and animal models, including inflammatory bowel disease (IBD), obesity, allergic disorders, type 1 diabetes mellitus, autism, and colorectal cancer (6,7). Periodontal disease arises from dysbiosis of subgingival microbial communities that adversely affect the host immune system, generating and sustaining unabated inflammation within the gingival and periodontal tissues, thereby inhibiting immune resolution and preventing tissue repair. Numerous studies have demonstrated that the predominant microorganisms within dental plaque changes across depending on periodontal health, gingivitis and periodontitis (8).\u003c/p\u003e \u003cp\u003eHowever, limited research has founded on the spesific relationship between oral microbiota and gastritis in terms of dysbiotic era. In our study, we aimed to examine the oral microbiota of patients with gastritis in relation to periodontal parameters. The purpose of this study is to evaluate the levels of microorganisms in the salivary flora of patients with gastritis, their clinical periodontal parameters, and the relationships between these variables.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatient Selection\u003c/h2\u003e \u003cp\u003eThis study was designed as a prospective, observational, case-control study. Participants in our study were selected in order of admission from among patients who presented to the Faculty of Dentistry at Aydın Adnan Menderes University for periodontal treatment between 1 November 2023 and 15 January 2024. A total of 30 patients were included, comprising 15 individuals with no systemic diseases and 15 individuals diagnosed with gastritis via endoscopic examination who had no additional systemic conditions. Patients who were non-smokers, over 18 years of age, had at least 20 teeth, were not undergoing orthodontic treatment, and were not using medications regularly for gastritis or any other condition were included in the study. Patients who were pregnant or in the lactation period, those who had used medications that could affect periodontal status or microbial flora (such as antibiotics or corticosteroids) within the three months preceding sample collection, and those who had received periodontal treatment within the past six months were excluded from the study.\u003c/p\u003e \u003cp\u003eIntraoral examinations of all patients included in our study were first performed, and their periodontal parameters were recorded immediately. One week later, saliva samples were collected for microbiological analysis. Patients were further classified into subgroups according to their periodontal status: periodontally healthy (PH-Gas, PH-Cont), gingivitis (Gin-Gas, Gin-Cont) and stage 1 periodontitis (Stage 1P-Gas, Stage 1P-Cont), the schematic distribution is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Classification of patients into subgroups was based on the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions (9,10).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e Following the establishment of the study protocol, ethical approval was obtained from the Clinical Research Ethics Committee of the Faculty of Dentistry, Aydın Adnan Menderes University, in accordance with the ethical principles of the 2013 Declaration of Helsinki (approval date: 25.10.2023; protocol number: AAD\u0026Uuml;DHF 2023/27) and registered at ClinicTrials.gov (NCT07378540) with registeration date 29/01/2026. All patients were provided with detailed information regarding the purpose and content of the study following their admission, and informed consent was obtained through a signed voluntary participation form.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePeriodontal parameters\u003c/h3\u003e\n\u003cp\u003eFor each patient, full-mouth probing depth (PD), clinical attachment loss (CAL), dichotomous scoring of bleeding on probing (BOP), and plaque index (PI) scores (Silness and L\u0026ouml;e, 1967) were recorded at six sites per tooth by single investigator (E.E.A.).\u003c/p\u003e\n\u003ch3\u003eSaliva collection\u003c/h3\u003e\n\u003cp\u003e As a standard protocol (11), individuals included in the study were asked to refrain from consuming any food for at least one hour prior to sample collection and to present to the clinic without performing any oral hygiene procedures after the night before. Unstimulated saliva samples were collected from all patients in the morning, at approximately the same time, into sterile saliva containers and then transferred into sterile Eppendorf tubes (Axygen Snaplock Microcentrifuge Tubes 1.5 mL, USA) using a sterile syringe. The saliva samples were stored in the existing Eppendorf tubes at \u0026minus;\u0026thinsp;80\u0026deg;C in the deep freezer located in the Department of Periodontology, Faculty of Dentistry, Aydın Adnan Menderes University, until the day of transport.\u003c/p\u003e\n\u003ch3\u003eDNA Extraction\u003c/h3\u003e\n\u003cp\u003eOral samples were collected in 1.5 mL of DiaRex\u0026reg; RNALater Stabilization Solution (DiaGen, Turkey). The samples were stored at \u0026minus;\u0026thinsp;80\u0026deg;C until DNA extraction. Immediately prior to extraction, the samples were thawed and diluted with 9 mL of phosphate-buffered saline (PBS). Before removal of the swabs, the tubes were gently agitated in a circular motion. The sample suspensions were centrifuged at 400 \u0026times; g for 10 minutes. Following centrifugation, the supernatant was discarded and the extraction was continued using the pellet. DNA extraction from the pellet was performed using the QuickGene DNA Tissue Kit S (DT-S, Japan). The pellet was treated with 250 \u0026micro;L of MDT and 25 \u0026micro;L of EDT (Proteinase K) solution and incubated at 56\u0026deg;C for 60 minutes. After the addition of 180 \u0026micro;L of LDT solution, the tubes were vortexed for 15 seconds and incubated at 70\u0026deg;C for 10 minutes. Subsequently, 240 \u0026micro;L of ice-cold 99% ethanol was added, and the samples were vortexed for 15 seconds. Immediately thereafter, the entire volume in the microcentrifuge tube was transferred to QuickGene (Kurabo) columns and washed three times with 750 \u0026micro;L of WDT solution. Finally, 50\u0026ndash;60 ng of genomic DNA was eluted by adding 200 \u0026micro;L of CDT solution to the QuickGene (Kurabo) columns and collected into a new sterile 1.5 mL microcentrifuge tube.\u003c/p\u003e \u003cp\u003eThe extracted DNA was amplified using 16S rRNA gene V3\u0026ndash;V4 primer sets. Library preparation was performed using the Nextera XT DNA Library Preparation Kit and index adapters (Illumina). The pooled library was purified with size selection according to the manufacturer\u0026rsquo;s protocol using AMPure XP beads (Beckman Coulter). Following library preparation, sequencing was carried out on the MiSeq platform (Illumina).\u003c/p\u003e\n\u003ch3\u003eBioinformatic and statistic\u003c/h3\u003e\n\u003cp\u003ePaired-end (2 \u0026times; 250) Illumina reads were imported into the QIIME 2 pipeline (12). In the initial assessment, all samples were found to reach a sequencing depth exceeding approximately 50\u0026times;, with a comparable distribution across samples. No samples were excluded from the analysis. Data quality was filtered within QIIME 2 using the DADA2 algorithm, and regions with a quality score below 30 were removed to generate amplicon sequence variants (ASVs) (13). After quality filtering, a total of 1,824,084 reads were retained for downstream analysis, and 2,096 ASVs were identified. The resulting ASVs were assigned taxonomy using the SILVA 138 reference database to generate taxonomic tables (14). Files generated by QIIME 2 were processed using the R programming language and RStudio for data visualization and biostatistical analyses. Alpha diversity was assessed using the Chao1, Shannon, and Simpson indices, and statistical comparisons between groups were performed using the Kruskal\u0026ndash;Wallis test. Beta diversity was evaluated based on Jaccard, Bray\u0026ndash;Curtis, weighted UniFrac, and unweighted UniFrac distance metrics, and group differences were tested using PERMANOVA, which was performed using the Adonis. The most prominent differences between groups were identified using LEfSe analysis, and taxa with p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and LDA score greater than 2 were reported.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eClinical Data\u003c/h2\u003e \u003cp\u003eThe socio-demographic data of the patients included in our study are given in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; the groups were found to be statistically similar in terms of age and gender (p\u0026thinsp;=\u0026thinsp;0,16).\u003c/p\u003e \u003cp\u003eNo statistically significant differences were observed in probing depth (PD), clinical attachment level (CAL), bleeding on probing (BP), and plaque index (PI) among the study groups and subgroups. Clinical periodontal parameters in the groups and subgroups are presented in Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, while the p-values are provided in Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic features and clinical parameter of study groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eClinical parameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGastritis\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHealty\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMin-Max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u0026ndash;55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eProbing Depth(mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMin-Max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,26\u0026thinsp;\u0026minus;\u0026thinsp;3,2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,42\u0026thinsp;\u0026minus;\u0026thinsp;2,26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eClinical Attachment Level (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMin-Max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,01\u0026ndash;3,4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,26\u0026thinsp;\u0026minus;\u0026thinsp;2,32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eBleeding on Probing (-/+)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMin-Max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u0026ndash;75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u0026ndash;83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24,7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePlaque İndex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMin-Max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,5\u0026thinsp;\u0026minus;\u0026thinsp;1,78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,47\u0026thinsp;\u0026minus;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,477\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStatistical analysis of clinical periodontal parameters in gastritis and control group patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBOP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePI\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep value (Mann Whitney U)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinical periodontal parameters of subgroups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eClinical parameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl- PH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl-Gin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eControl-Stage 1 P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGastritis-PH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGastritis-Gin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eGastritis-Stage 1 P\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePD (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMin-Max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,42\u0026thinsp;\u0026minus;\u0026thinsp;1,66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,55\u0026thinsp;\u0026minus;\u0026thinsp;1,92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,82\u0026thinsp;\u0026minus;\u0026thinsp;2,26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,26\u0026thinsp;\u0026minus;\u0026thinsp;1,59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,37\u0026thinsp;\u0026minus;\u0026thinsp;1,99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u0026ndash;3,2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2,26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14,15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCAL (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMin-Max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,26\u0026thinsp;\u0026minus;\u0026thinsp;0,66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,35\u0026thinsp;\u0026minus;\u0026thinsp;1,72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,98\u0026thinsp;\u0026minus;\u0026thinsp;2,32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,01\u0026thinsp;\u0026minus;\u0026thinsp;0,64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,27\u0026thinsp;\u0026minus;\u0026thinsp;1,79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2,21\u0026thinsp;\u0026minus;\u0026thinsp;3,04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2,65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0,383\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eBOP (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMin-Max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u0026ndash;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17\u0026ndash;83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u0026ndash;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14\u0026ndash;75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e42\u0026ndash;70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22,76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28,15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21,4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14,58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMin-Max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,47\u0026thinsp;\u0026minus;\u0026thinsp;0,72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,16\u0026thinsp;\u0026minus;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,68\u0026thinsp;\u0026minus;\u0026thinsp;1,77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,5\u0026thinsp;\u0026minus;\u0026thinsp;0,96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,9\u0026thinsp;\u0026minus;\u0026thinsp;1,78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0,97\u0026thinsp;\u0026minus;\u0026thinsp;1,64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1,54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,513\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0,31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMann Whitney U analysis p-values ​​of clinical periodontal parameters of subgroups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGastritis PH-\u003c/p\u003e \u003cp\u003eControl PH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGastritis Gin-\u003c/p\u003e \u003cp\u003eControl Gin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGastritis Stage 1-\u003c/p\u003e \u003cp\u003eControl Stage 1\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,8\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,25\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0,37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0,37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,066\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBOP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0,82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0,99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0,52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMicrobiological Analysis\u003c/h3\u003e\n\u003cp\u003eMicrobiological evaluations were performed on both gastritis and control group patients, including subgroups. In total, bacterial examinations were conducted at the level of 15 phyla, 27 classes, 60 orders, 100 families, 199 genera, and 207 species. The distribution of bacteria across groups and subgroups is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eMicrobial Diversity\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003eAlpha Diversity\u003c/h2\u003e \u003cp\u003eAlpha analysis showed that women had higher microbial diversity and density than men, according to the Simpson (p\u0026thinsp;=\u0026thinsp;0.0014) and Shannon (p\u0026thinsp;=\u0026thinsp;0.00981) metrics.\u003c/p\u003e \u003cp\u003eAlpha analysis showed no difference in bacterial diversity and density between the gastritis and control groups in the Simpson (p\u0026thinsp;=\u0026thinsp;0.983), Shannon (p\u0026thinsp;=\u0026thinsp;0,755), and chao1 (p\u0026thinsp;=\u0026thinsp;0,35) metrics. However, in the subgroups, the Stage 1P-Gas group had a significantly higher chao1 index than the other groups (p\u0026thinsp;=\u0026thinsp;0.032). The graphs of the alpha analysis in groups are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eBeta Diversity\u003c/h2\u003e \u003cp\u003eBeta diversity was assessed using principal component analysis (PCA) and \u0026ldquo;principal coordinates analysis (PCoA) analyses. PCoA of beta diversity was performed using Bray\u0026ndash;Curtis, Jaccard, weighted UniFrac, and unweighted UniFrac distance metrics. No significant differences were found in any metric across study groups, gender groups, and subgroups (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eTaxonomic Difference\u003c/h2\u003e \u003cp\u003eKrona analysis was used to determine the most common bacterial species and their proportions in the groups and bacterial distribution diagram of gastritis and control groups given in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. In the gastritis group, the most abundant bacteria at the phylum level are \u003cem\u003eFirmicutes\u003c/em\u003e (38%), \u003cem\u003eBacteroidota\u003c/em\u003e (34%), and \u003cem\u003eProteobacteria\u003c/em\u003e (14%); at the genus level, Prevotella (28%), \u003cem\u003eVeillonella\u003c/em\u003e (23%), and \u003cem\u003eNeisseria\u003c/em\u003e (8%); and at the species level, \u003cem\u003ePrevotella melaninogenica\u003c/em\u003e (27.32%), \u003cem\u003ePrevotella pallens\u003c/em\u003e (5.38%), and \u003cem\u003eMegasphaera micronuciformis\u003c/em\u003e (5.14%).\u003c/p\u003e \u003cp\u003eIn the control group, the most abundant bacteria were \u003cem\u003eFirmicutes\u003c/em\u003e (38%), \u003cem\u003eBacteroidota\u003c/em\u003e (31%), and \u003cem\u003eProteobacteria\u003c/em\u003e (18%) at the phylum level; \u003cem\u003ePrevotella\u003c/em\u003e (24%), \u003cem\u003eVeillonella\u003c/em\u003e (23%), and \u003cem\u003eNeisseria\u003c/em\u003e (10%) at the genus level; and \u003cem\u003ePrevotella melaninogenica\u003c/em\u003e (29.9%), \u003cem\u003eMegasphaera micronuciformis\u003c/em\u003e (6.13%), and \u003cem\u003ePrevotella pallens\u003c/em\u003e (6.11%) at the species level.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAccording to LEfSe analysis, in the gastritis group, \u003cem\u003eVerrucomicrobiota\u003c/em\u003e at the phylum level, \u003cem\u003eLactobacillacea, Bacteriodaceae, Bifidobactericaea, Ruminococcaea\u003c/em\u003e and \u003cem\u003eAkkermansiaceae\u003c/em\u003e at the family level, \u003cem\u003eDesulfovibrionales, Bifidobacteriales, Oscillospirales\u003c/em\u003e and \u003cem\u003eVerrucomicrobiales\u003c/em\u003e at the order level, \u003cem\u003eLactobacillus, Bacteroides, Faecalibacterium, Akkermansia, Gardnerella\u003c/em\u003e and \u003cem\u003eBulleidia\u003c/em\u003e at the genus level, and \u003cem\u003ePrevotella multisaccharivorax, Lactobacillus spp, Leptotrichia shahii, Dialister pneumosintes, Akkermansia muciniphila, Faecalibacterium spp, Gardnerella spp, Prevotella bacterium\u003c/em\u003e and \u003cem\u003eBulleidia extructa\u003c/em\u003e at the species level were found to be statistically significantly higher. In the healthy control group, \u003cem\u003eAlysiella\u003c/em\u003e at the genus level, and \u003cem\u003eRothia spp, Treponema pedis\u003c/em\u003e and \u003cem\u003eAlysella spp\u003c/em\u003e at the species level were found to be statistically significantly higher. (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eWhen evaluated at the subgroup level using LEfSe analysis, at the species level, \u003cem\u003eCampylobacter showae\u003c/em\u003e was significantly enriched in the PH-Cont group. The PH-Gas group showed significant enrichment of \u003cem\u003ePrevotella oulorum\u003c/em\u003e and \u003cem\u003eSelenomonas flueggei\u003c/em\u003e. In the Gin-Gas group, significant enrichment was observed at the family level for \u003cem\u003eLactobacillaceae\u003c/em\u003e and at the genus level for \u003cem\u003eLactobacillus\u003c/em\u003e. The Gin-ConT group exhibited a higher abundance of \u003cem\u003ePrevotella dentalis\u003c/em\u003e and \u003cem\u003ePrevotella enoeca\u003c/em\u003e at the species level. In the Stage 1P-Gas group, significant enrichment was detected at the order level \u003cem\u003eOscillospirales\u003c/em\u003e, \u003cem\u003eEnterobacterales\u003c/em\u003e, and \u003cem\u003eIzemoplasmotales\u003c/em\u003e, family level \u003cem\u003eDesulfomicrobiaceae\u003c/em\u003e, \u003cem\u003eEnterobacteriaceae\u003c/em\u003e, and \u003cem\u003eIzemoplasmotales\u003c/em\u003e, genus level \u003cem\u003eEubacterium saphenum\u003c/em\u003e group, \u003cem\u003eDesulfomicrobium\u003c/em\u003e, \u003cem\u003eFaecalibacterium\u003c/em\u003e, \u003cem\u003eEscherichia\u0026ndash;Shigella\u003c/em\u003e, and \u003cem\u003eIzemoplasmotales\u003c/em\u003e, and species level \u003cem\u003eEubacterium saphenum\u003c/em\u003e. (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) According to the Lefse analysis, the p-values ​​and LDA scores of bacteria that differed in groups and subgroups are given in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e and S2.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eRecent advancements in sequencing techniques for next-generation processes, which analyze DNA and RNA regions, allow for comprehensive analysis of bacterial diversity from complex environmental samples and to examine the composition and variety of microbial communities. 16S rRNA gene sequences have become by far the most widely used genetic marker due to their presence in almost all bacteria, usually as a multigene family or operon, the invariance of their gene function over time, and their sufficiently large size (1,500 bp) for computational purposes (15).\u003c/p\u003e \u003cp\u003eOur study included 18 female and 12 male patients. According to alpha diversity analysis, bacterial diversity and density were found to be statistically significantly higher in women. There are few studies in the literature that show differences in salivary microbiomes between women and men and the differences found in these studies have been attributed to hormonal changes and personal hygiene habits (16,17). In addition, there are numerous studies showing that the salivary microbiomes of women and men are not different (18\u0026ndash;21). The fact that the number of female patients was 50% higher than the number of male patients in our study may have resulted in a higher diversity and density of microorganisms in women.\u003c/p\u003e \u003cp\u003eIn a study by Chen et al (21), saliva samples from gastritis patients and healthy patients were analyzed using 16S rRNA gene amplicon sequencing, and no significant difference was found according to alpha and beta diversity analysis. The results of this study regarding diversity and intensity are consistent with our study, but this study did not examine the periodontal status of the patients. Therefore, the effect of the periodontal condition on the microbiota cannot be assessed.\u003c/p\u003e \u003cp\u003eIn a study by Cui et al. (22), tongue swabs were taken from gastritis and control group patients and analyzed by 16S rRNA gene applicon sequencing. Alpha and beta analysis revealed statistically significantly less diversity among patient groups in the gastritis group. However, this study also included patients diagnosed with intestinal metaplasia via endoscopic methods in addition to gastritis patients, and tongue swab samples were used. The difference in sampling method and sample location between this study and our study may have resulted in differences in microbial content and density.\u003c/p\u003e \u003cp\u003eIn the study by Chen et al. (21), according to LEfSe analysis, the bacteria that were enriched in the gastritis group were \u003cem\u003eRuminococcaceae, Sutterella, Lactobacillaceae\u003c/em\u003e at the phylum level, and \u003cem\u003eSutterella\u003c/em\u003e and \u003cem\u003eLactobacillus\u003c/em\u003e at the genus level, while in the control group they were \u003cem\u003eMitochondria\u003c/em\u003e and \u003cem\u003eCorynebacterium-1\u003c/em\u003e, and these findings are largely consistent with our study. Based on these results, we can say that in cases of gastritis, the oral flora shifts towards dysbiosis with an increase in \u003cem\u003eRuminococcaceae\u003c/em\u003e and \u003cem\u003eLactobacillaceae\u003c/em\u003e bacteria at the family level.\u003c/p\u003e \u003cp\u003eIn the study conducted by Cui et al. (22), the bacteria that were enriched in the gastritis group according to LEfSe analysis were identified as \u003cem\u003eStreptococcus infantis\u003c/em\u003e, \u003cem\u003eTreponema vincentii, Leptotrichia unclassified, Campylobacter rectus, Campylobacter showae, Capnocytophaga gingivalis, Leptotrichia buccalis, Campylobacter concisus, Selenomonas flueggei\u003c/em\u003e and \u003cem\u003eLeptotrichia hofstadii\u003c/em\u003e at the species level. The results of this study do not appear to be consistent with the results of our study; however, in the study conducted by Cui et al., patients diagnosed with intestinal metaplasia, an advanced stage of gastritis, were also included in the gastritis group, and tongue swab samples were used instead of saliva samples. Due to differences in the study group and the microbial diversity in the salivary and tongue regions within the mouth, it is thought that the results obtained are not consistent with the results of our study.\u003c/p\u003e \u003cp\u003eWhen the LEfSe analysis was evaluated at the subgroup level, \u003cem\u003eCampylobacter showae\u003c/em\u003e was found to be statistically significantly higher at the species level in the PH-Cont group, \u003cem\u003ePrevotella oulorum\u003c/em\u003e and \u003cem\u003eSelenomonas flueggei\u003c/em\u003e at the species level in the PH-Gas group, \u003cem\u003eLactobacillus\u003c/em\u003e at the genus level in the Gin-Gas group, \u003cem\u003ePrevotella dentalis\u003c/em\u003e and \u003cem\u003ePrevotella enoeca\u003c/em\u003e at the species level in the Gin-Cont group, and \u003cem\u003eEubacterium saphenum (group)\u003c/em\u003e, \u003cem\u003eDesulfumicrobium, Faecalibacterium, Escherichia-Shigella\u003c/em\u003e and \u003cem\u003eIzemoplasmotales\u003c/em\u003e at the genus level, and \u003cem\u003eEubacterium saphenum\u003c/em\u003e at the species level in the Stage 1P-Gas group.\u003c/p\u003e \u003cp\u003eA significant finding here is that the number of bacterial species enriched in the group with periodontal disease accompanying gastritis is higher compared to other groups. Furthermore, according to alpha diversity analysis in our study, a statistically significant difference in bacterial diversity and density was found in the Stage 1P-Gas group. In the literature, when 16S rRNA-based studies are evaluated according to periodontal conditions, it has been observed in many studies that \u003cem\u003eActynomyces, Rothia, Streptococcus\u003c/em\u003e, and \u003cem\u003eCarynebacterium\u003c/em\u003e species are found in healthy periodontal patients, \u003cem\u003eSelenomonas\u003c/em\u003e and \u003cem\u003ePrevotella\u003c/em\u003e species increase in patients with gingivitis, and microbial diversity and load increase significantly in periodontal disease patients (5,23,24). These results are largely consistent with the results of our study. The significant difference in diversity and intensity observed in the Stage 1P-Gas group in our study may be due to the microbial aspect of periodontal disease or to dysbiosis caused by gastritis. Although furter studies would be needed to investigate this hypotesis, due to the cross-sectional design of our study limits the ability to infer causality.\u003c/p\u003e \u003cp\u003eOur study found no statistically significant differences in bacterial diversity, density, and phylogenetic distribution between the gastritis and control groups. The reason may be due to the small number of periodontitis patients in each group. When subgroups were evaluated, the diversity and density were found to be higher in the Stage 1P-Gas group than in other subgroups, and this can be interpreted as gastritis increasing dysbiosis in the oral flora caused by periodontal disease. This is one of our study limitations; sample size though sufficient to detect key differences, remains relatively small participant limit the applicability of the results.\u003c/p\u003e \u003cp\u003eIn our study, we analyzed \u003cem\u003eAggregatibacter actynomycetemcomitans, Capnocytophaga species, Filifactor alocis, Porphyromanas gingivalis, Prevotella intermedia, Prevotella nigrescens, Tannarella forsythia\u003c/em\u003e, and \u003cem\u003eTreponema denticola\u003c/em\u003e bacteria, which are associated with periodontal disease. No species among these bacteria showed significant differences at the group or subgroup level. In a study by Salazar et al. (25), saliva and plaque samples were taken from patients with gastric precancerous lesions and a healthy patient group, and the levels of perio-pathogenic bacteria were compared. Although an increase in the amount of perio-pathogenic bacteria was observed with the increase in periodontal disease markers (probing depth, bleeding on probing) in both groups, an increase in \u003cem\u003eT. forsythia\u003c/em\u003e levels was observed only in the saliva of the precancerous lesion group, and this increase was not observed in plaque. Apart from that, bacterial levels were found to be similar in both groups. The results of our study are consistent with that study.\u003c/p\u003e \u003cp\u003eIn this study, \u003cem\u003eEubacterium saphenum\u003c/em\u003e was found to be significantly higher in the Stage 1P-Gas group. Studies have shown that this bacterium is associated with increased periods of periodontal disease (26\u0026ndash;30), and our study supports this finding, with further research in this area, we believe that this bacteria may also be associated with periodontal disease. In addition, \u003cem\u003eDesulfomicrobium orale\u003c/em\u003e (31), a sulfate reductase, has been associated with periodontitis. The increase in sulfate-reducing bacteria in periodontal disease is associated with periodontal disease due to the toxic effect of h\u003csup\u003e2\u003c/sup\u003es on epithelial cells (32,33). Although this bacterial species did not appear different in our study, the genus-level sulfate reductase family \u003cem\u003eDesulfomicrobiale\u003c/em\u003e was found to be elevated in the Stage 1P-Gas group. Further research is needed into the relationship between this bacterium and periodontal disease, and how this mechanism contributes to the progression of periodontal disease.\u003c/p\u003e \u003cp\u003eIn a study by Contaldo et al. (34), the levels of \u003cem\u003eP. gingivalis\u003c/em\u003e and \u003cem\u003eF. nucleatum\u003c/em\u003e were examined in saliva samples from chronic gastritis and healthy patient groups using real-time PCR analysis. The levels of \u003cem\u003eP. gingivalis\u003c/em\u003e and \u003cem\u003eF. nucleatum\u003c/em\u003e were found to be significantly lower in the chronic gastritis group. However, the periodontal status of the patients was not examined in this study. This could be speculated that the association between the severity periodontal status and microbiota. This stregth in our study, patients were divided into subgroups according to their periodontal status, and the number of patients in each group was kept equal.\u003c/p\u003e \u003cp\u003eIn our study, the company performing the metagenomic analysis uses a standardized analysis kit that allows for the quantification and inclusion of only the bacterial taxa contained within the kit; the addition of optional or custom bacteria is not possible. Consequently, \u003cem\u003eHelicobacter pylori\u003c/em\u003e, a major etiological agent of gastritis, could not be analyzed as it was not included in the kit. Future studies could incorporate this bacterium into the analysis and be designed to include only \u003cem\u003eH. pylori\u003c/em\u003e\u0026ndash;positive patients. Another limitation of our study is the limited number of patients with periodontitis and the absence of individuals with advanced-stage periodontal disease in the study groups. This may be attributed to the fact that gastritis typically manifests at a younger age, whereas periodontal disease tends to develop later in life. As observed in our study, microbial diversity and abundance increase when gastritis and periodontal disease coexist. We believe that more definitive conclusions could be achieved with a larger number of patients with periodontitis or with the inclusion of individuals with advanced-stage periodontitis.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study is important in that, while examining the variation of gastritis on the oral flora, it also takes periodontal status and oral hygiene into consideration. The significant difference in diversity and intensity observed in the Stage 1P-Gas group in our study may be due to the microbial aspect of periodontal disease or to dysbiosis caused by gastritis.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIBD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInflammatory bowel disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePH-Gas\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePeriodontal healty- Gastritis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePH-Cont\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePeriodontal healty- Control\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGin-Gas\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGingivitis- Gastritis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGin-Cont\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGingivitis- Control\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eStage 1P-Gas\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStage 1 Periodontitis- Gastritis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eStage 1P-Cont\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStage 1 Periodontitis- Control\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProbing depth\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCAL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eClinic attachment level\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBOP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBleeding on probing\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePlaque index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eASV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAmplicon sequence variants\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePBS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePhosphate-buffered saline\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowlidgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors extend their sincere gratitude to all the patients who generously participated in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eE.E.A. made the patient selection, collect the clinical data and saliva samples. V.\u0026Ouml;.\u0026Ouml; planned and desgined the study, made critical revisions. All authors contributed to manuscript drafting and final approval of the published version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research has been supported by Aydın Adnan Menderes University Scientific Research Projects Unit. (Project Number: DHF-24004)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request. The raw sequencing data have been deposited in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) database under PRJNA1430215.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict Of Interest Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors explicitly state that there are no competing interests in connection with this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the Clinical Research Ethics Committee of the Faculty of Dentistry, Aydın Adnan Menderes University, in accordance with the ethical principles of the 2013 Declaration of Helsinki (approval date: 25.10.2023; protocol number: AAD\u0026Uuml;DHF 2023/27). All patients were provided with detailed information regarding the purpose and content of the study following their admission, and informed consent was obtained through a signed voluntary participation form.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEce Erdem Altıny\u0026uuml;rek1, Veli \u0026Ouml;zgen \u0026Ouml;zt\u0026uuml;rk1\u003c/p\u003e\n\u003cp\u003e1 Department of Periodontology, Faculty of Dentistry, Aydın Adnan Menderes University, Aydın, Turkey\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSiurala M. The story of gastritis. Scand J Gastroenterol. 1991;26(S186):1\u0026ndash;3. \u003c/li\u003e\n\u003cli\u003eVillako K, Kekki M, Maaroos HI, Sipponen P, Tammur R, Tamm A, et al. A 12-Year Follow-up Study of Chronic Gastritis and Helicobacter pylori in a Population-Based Random Sample. Scand J GastroenteroL. 1995;30(10):964\u0026ndash;7. \u003c/li\u003e\n\u003cli\u003eDelle Fave G, Kwekkeboom DJ, Van Cutsem E, Rindi G, Kos-Kudla B, Knigge U, et al. ENETS Consensus Guidelines for the management of patients with gastroduodenal neoplasms. Neuroendocrinology. 2012 Feb;95(2):74\u0026ndash;87.\u003c/li\u003e\n\u003cli\u003eAnnibale B, Esposito G, Lahner E. A current clinical overview of atrophic gastritis. Vol. 14, Expert Review of Gastroenterology and Hepatology. Taylor and Francis Ltd; 2020. p. 93\u0026ndash;102. \u003c/li\u003e\n\u003cli\u003eCurtis MA, Diaz PI, Van Dyke TE. The role of the microbiota in periodontal disease. Vol. 83, Periodontology 2000. Blackwell Munksgaard; 2020. p. 14\u0026ndash;25. \u003c/li\u003e\n\u003cli\u003eMoos WH, Faller D V., Harpp DN, Kanara I, Pernokas J, Powers WR, et al. Microbiota and Neurological Disorders: A Gut Feeling. Biores Open Access. 2016 May 1;5(1):137\u0026ndash;45. \u003c/li\u003e\n\u003cli\u003eTamboli CP, Neut C, Desreumaux P, Colombel JF. Dysbiosis in inflammatory bowel disease. Gut. 2004;53(1):1-4. doi:10.1136/gut.53.1.1\u003c/li\u003e\n\u003cli\u003eHajishengallis G. Periodontitis: from microbial immune subversion to systemic inflammation. Nat Rev Immunol. 2015 Jan 1;15(1):30\u0026ndash;44.\u003c/li\u003e\n\u003cli\u003eChapple ILC, Mealey BL, Van Dyke TE, Bartold PM, Dommisch H, Eickholz P, et al. Periodontal health and gingival diseases and conditions on an intact and a reduced periodontium: Consensus report of workgroup 1 of the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions. J Periodontol. 2018 Jun 1;89:S74\u0026ndash;84. \u003c/li\u003e\n\u003cli\u003ePapapanou PN, Sanz M, Buduneli N, Dietrich T, Feres M, Fine DH, et al. Periodontitis: Consensus report of workgroup 2 of the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions. J Periodontol. 2018 Jun 1;89:S173\u0026ndash;82. \u003c/li\u003e\n\u003cli\u003eNavazesh M. Methods for collecting saliva. Ann N Y Acad Sci. 1993;694:72-77. doi:10.1111/j.1749-6632.1993.tb18343.x \u003c/li\u003e\n\u003cli\u003eAustin B. The value of cultures to modern microbiology. Antonie Van Leeuwenhoek. 2017 Oct 1;110(10):1247\u0026ndash;56.\u003c/li\u003e\n\u003cli\u003eHayashi H, Sakamoto M, Benno Y. Phylogenetic analysis of the human gut microbiota using 16S rDNA clone libraries and strictly anaerobic culture-based methods. Microbiol Immunol. 2002;46(8):535\u0026ndash;48.\u003c/li\u003e\n\u003cli\u003eRanjan R, Rani A, Metwally A, McGee HS, Perkins DL. Analysis of the microbiome: Advantages of whole genome shotgun versus 16S amplicon sequencing. Biochem Biophys Res Commun. 2016 Jan 22;469(4):967\u0026ndash;77. \u003c/li\u003e\n\u003cli\u003eJB P. 16S rRNA gene sequencing for bacterial pathogen identification in the clinical laboratory. Mol Diagn. 2001 Dec;6(4):313\u0026ndash;21. \u003c/li\u003e\n\u003cli\u003eLiu X, Tong X, Jie Z, Zhu J, Tian L, Sun Q, et al. Sex differences in the oral microbiome, host traits, and their causal relationships. iScience. 2023 Jan 20;26(1). \u003c/li\u003e\n\u003cli\u003eUmeda M, Chen C, Bakker I, Contreras A, Morrison JL, Slots J. Risk indicators for harboring periodontal pathogens. J Periodontol. 1998 Oct;69(10):1111\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eSlots J, Feik D, Rams TE. Age and sex relationships of superinfecting microorganisms in periodontitis patients. Oral Microbiol Immunol. 1990;5(6):305\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eSchenkein HA, Burmeister JA, Koertge TE, Brooks CN, Best AM, Moore LVH, et al. The influence of race and gender on periodontal microflora. J Periodontol. 1993 Apr;64(4):292\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eCorby PMA, Bretz WA, Hart TC, Melo Filho M, Oliveira B, Vanyukov M. Mutans streptococci in preschool twins. Arch Oral Biol. 2005;50(3):347\u0026ndash;51.\u003c/li\u003e\n\u003cli\u003eChen M, Fan HN, Chen XY, Yi YC, Zhang J, Zhu JS. Alterations in the saliva microbiome in patients with gastritis and small bowel inflammation. Microb Pathog. 2022 Apr 1;165. \u003c/li\u003e\n\u003cli\u003eCui J, Cui H, Yang M, Du S, Li J, Li Y, et al. Tongue coating microbiome as a potential biomarker for gastritis including precancerous cascade. Protein Cell. 2019 Jul 1;10(7):496\u0026ndash;509. \u003c/li\u003e\n\u003cli\u003eHong BY, Araujo MVF, Strausbaugh LD, Terzi E, Ioannidou E, Diaz PI. Microbiome profiles in periodontitis in relation to host and disease characteristics. PLoS One. 2015 May 18;10(5). \u003c/li\u003e\n\u003cli\u003eAbusleme L, Hoare A, Hong BY, Diaz PI. Microbial signatures of health, gingivitis, and periodontitis. Vol. 86, Periodontology 2000. Blackwell Munksgaard; 2021. p. 57\u0026ndash;78. \u003c/li\u003e\n\u003cli\u003eSalazar CR, Sun J, Li Y, Francois F, Corby P. Association between Selected Oral Pathogens and Gastric Precancerous Lesions. PLoS One. 2013;8(1):51604. \u003c/li\u003e\n\u003cli\u003eAbusleme L, Dupuy AK, Dutzan N, Silva N, Burleson JA, Strausbaugh LD, et al. The subgingival microbiome in health and periodontitis and its relationship with community biomass and inflammation. ISME J. 2013 May;7(5):1016\u0026ndash;25. \u003c/li\u003e\n\u003cli\u003eGriffen AL, Beall CJ, Campbell JH, Firestone ND, Kumar PS, Yang ZK, et al. Distinct and complex bacterial profiles in human periodontitis and health revealed by 16S pyrosequencing. ISME J. 2012 Jun;6(6):1176\u0026ndash;85. \u003c/li\u003e\n\u003cli\u003eAbiko Y, Sato T, Mayanagi G, Takahashi N. Profiling of subgingival plaque biofilm microflora from periodontally healthy subjects and from subjects with periodontitis using quantitative real-time PCR. J Periodontal Res. 2010 Jun;45(3):389\u0026ndash;95.\u003c/li\u003e\n\u003cli\u003eMayanagi G, Sato T, Shimauchi H, Takahashi N. Detection frequency of periodontitis-associated bacteria by polymerase chain reaction in subgingival and supragingival plaque of periodontitis and healthy subjects. Oral Microbiol Immunol. 2004 Dec;19(6):379\u0026ndash;85. \u003c/li\u003e\n\u003cli\u003eKumar PS, Griffen AL, Barton JA, Paster BJ, Moeschberger ML, Leys EJ. New bacterial species associated with chronic periodontitis. J Dent Res. 2003;82(5):338\u0026ndash;44. \u003c/li\u003e\n\u003cli\u003eLangendijk PS, Kulik EM, Sandmeier H, Meyer J, van der Hoeven JS. Isolation of Desulfomicrobium orale sp. nov. and Desulfovibrio strain NY682, oral sulfate-reducing bacteria involved in human periodontal disease. Int J Syst Evol Microbiol. 2001;51(3):1035\u0026ndash;44. \u003c/li\u003e\n\u003cli\u003eShu W, Du B, Wu G. Strategies for enriching targeted sulfate-reducing bacteria and revealing their microbial interactions in anaerobic digestion ecosystems. Water Res. 2025 Feb 15;270:122842. \u003c/li\u003e\n\u003cli\u003eKushkevych I, Coufalov\u0026aacute; M, V\u0026iacute;tězov\u0026aacute; M, Rittmann SKMR. Sulfate-Reducing Bacteria of the Oral Cavity and Their Relation with Periodontitis\u0026mdash;Recent Advances. Journal of Clinical Medicine 2020, Vol 9, Page 2347. 2020 Jul 23;9(8):2347. \u003c/li\u003e\n\u003cli\u003eContaldo M, Fusco A, Stiuso P, Lama S, Gravina AG, Itro A, et al. Oral microbiota and salivary levels of oral pathogens in gastro‐intestinal diseases: Current knowledge and exploratory study. Vol. 9, Microorganisms. MDPI AG; 2021. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-oral-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ohea","sideBox":"Learn more about [BMC Oral Health](http://bmcoralhealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ohea/default.aspx","title":"BMC Oral Health","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Periodontitis, gastritis, dysbiosis, next generation sequencing, metagenomic, microbiome","lastPublishedDoi":"10.21203/rs.3.rs-8849413/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8849413/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eGastritis is characterized by alterations in the gastric microbiota. This dysbiosis in the stomach may affect immune system regulation as well as influence the oral microbiota. Periodontal disease results from dysbiosis of subgingival microbial communities that cause inflammatory responses in periodontal tissues. The aim of our study is to examine the oral flora profile and dysbiosis status of gastritis patients along with their periodontal status.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA total of 30 patients were included in our study, divided into two groups 15 patients diagnosed with gastritis and 15 systemically healthy individuals. Subsequently, the patients were subdivided into subgroups as periodontally healthy, gingivitis, and stage 1 periodontitis based on their periodontal status. Clinical periodontal parameters and saliva samples were collected. The microbial flora was analyzed using metagenomic analysis through next-generation sequencing methods. Clinical and microbiological parameters were evaluated using non-parametric statistical methods.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWhile no differences were observed in any metric in beta diversity analysis across gender groups, study groups, and subgroups, bacterial diversity was found to be higher in women in the Simpson, Shannon and Chao1 metrics in alpha diversity analysis, In the subgroups, a significant increase was observed in the stage 1 periodontitis-gastritis group in the Chao1 metric. Bacterial taxa that showed statistically significant differences between the groups and subgroups were identified using LEfSe analysis.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOur study underscore dysbiosis in the oral flora in the context of gastritis while also taking into account the periodontal status. Gastritis with periodontitis may enhance the microbial diversity and density. Future research studies are needed to unravel systemic interaction between periodontitits and gastritis.\u003c/p\u003e\u003ch2\u003eTrial Registration:\u003c/h2\u003e \u003cp\u003eThis clinical trial was registered at ClinicTrials.gov (NCT07378540) Registeration Date: 29/01/2026.\u003c/p\u003e","manuscriptTitle":"Evaluation of periodontal status in gastritis patients with clinical and microbiological parameters","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-22 05:46:12","doi":"10.21203/rs.3.rs-8849413/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-23T08:04:36+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-22T23:27:46+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-21T14:16:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-21T11:46:46+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-20T08:15:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"100148844901772963224560656494159237535","date":"2026-04-16T07:31:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"234383393654266066354706061127413247682","date":"2026-04-15T07:20:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"201111189219688770322527205697601441736","date":"2026-04-14T10:18:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"260669573045278257097376510022865972499","date":"2026-04-14T10:15:19+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-14T09:40:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-13T18:21:26+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-04T03:06:42+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-02T22:49:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Oral Health","date":"2026-03-02T14:47:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-oral-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ohea","sideBox":"Learn more about [BMC Oral Health](http://bmcoralhealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ohea/default.aspx","title":"BMC Oral Health","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c76ef3e0-62f2-4fe4-a47c-24fce2abace9","owner":[],"postedDate":"April 22nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-16T08:53:22+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-22 05:46:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8849413","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8849413","identity":"rs-8849413","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}