Obesity has become a global health issue due to its association with numerous comorbidities, including type 2 diabetes, metabolic dysfunction-associated steatotic liver disease, cardiovascular diseases, and certain cancers (Fall et al., 2017). The prevalence of obesity is increasing, prompting considerable interest in understanding its underlying mechanisms and contributing factors (Afshin et al., 2017).

Obesity is a complex multifactorial disease with diverse etiologies, including genetics, lifestyle, and socioeconomic, and environmental risk factors (Ghosh and Bouchard, 2017). Among these risk factors, the role of gut microbiota in the pathogenesis of obesity has gained substantial attention through various studies (Ley et al., 2005; Turnbaugh et al., 2006; Maruvada et al., 2017). Alterations in gut microbial composition, known as dysbiosis, have been implicated in metabolic disturbances that exacerbate obesity-related conditions​. Specifically, obesity has been associated with a decrease in the relative abundance of beneficial bacterial species, such as Bacteroidota (formerly known as Bacteroidetes) and an increase in Bacillota (formerly known as Firmicutes) (Ley et al., 2005; Turnbaugh et al., 2006). Studies using next-generation sequencing techniques, such as 16S rRNA sequencing have revealed that these microbial changes affect energy harvesting, lipid metabolism, and systemic inflammation, thereby contributing to obesity.

While most research has focused on the intestinal microbiota, other regions of the gastrointestinal tract, such as the stomach, also harbor distinct microbial communities that may influence metabolic health (Engstrand and Graham, 2020). Helicobacter pylori has been suggested to be associated not only with various gastrointestinal diseases but also with obesity and metabolic disorders (Azami et al., 2021; Baryshnikova et al., 2024). However, the gastric microbiota, except H. pylori infection, remain understudied in relation to obesity. A previous study in mice reported that high-fat diets induced dysbiosis not only in the intestinal microbiota but also in the gastric microbiota, potentially affecting the development and progression of metabolic diseases (He et al., 2018). This study aimed to investigate the gastric microbiota composition according to body mass index (BMI) categories and their potential associations with metabolic indices in humans. By analyzing gastric mucosal samples using 16S rRNA sequencing and functional profiling, this study seeks to bridge the gap in understanding the relationship between gastric microbiota (except H. pylori) and obesity beyond the established roles of intestinal microbiota.

This study demonstrates significant differences in the composition and functional profiles of the gastric microbiota between BMI categories, suggesting gastric microbial communities, like their intestinal counterparts, may play a role in obesity-related metabolic alterations (Ley et al., 2005; Turnbaugh et al., 2009; Denou et al., 2016; Yun et al., 2017; Kim et al., 2020; Duan et al., 2021).

In this study, among the four indices related to alpha diversity, only the Gini–Simpson index for evenness significantly decreased in overweight and obese individuals. This aligns with previous studies on the intestinal microbiota, where dysbiosis and decreased microbial diversity were strongly associated with obesity and metabolic disorders (Turnbaugh et al., 2009; Denou et al., 2016; Yun et al., 2017; Kim et al., 2020; Duan et al., 2021). This reduced diversity may impair the microbiota functional capacity, including energy homeostasis and anti-inflammatory processes, as shown in other regions of the gastrointestinal tract.

Although some studies have reported no significant differences, obesity has generally been associated with changes in the composition of the gut microbiota, including an increased relative abundance of Bacillota at the phylum level and a higher Bacillota/Bacteroidota ratio compared to individuals with normal weight (Ley et al., 2005; Andoh et al., 2016; Koliada et al., 2017; Murga-Garrido et al., 2022). In this study, there was no significant difference in the gastric microbiota at the phylum level among normal weight, overweight, and obese groups. Seventeen bacterial species showed significant differences between the normal weight and overweight/obese groups. M. gordoncarteri, T. bilis, and D. dubosii were notably reduced in the overweight/obese group and are linked to lipid and carbohydrate metabolism (Lagkouvardos et al., 2019; Chung et al., 2020; Zhu et al., 2024), whereas H. parainfluenzae and V. atypica were more abundant and may contribute to metabolic dysregulation via pro-inflammatory pathways. A meta-analysis identified Pseudomonadota (formerly Proteobacteria) as the phylum most consistently associated with obesity (Xu et al., 2022). Several species belonging to Pseudomonadota, such as Proteus mirabilis and E. coli, promote gastrointestinal inflammation, contributing to insulin resistance and metabolic diseases (Longstreth, 2007; Zhang et al., 2021). In this study, H. parainfluenzae, N. perflava, B. australiense, and C. concisus—all within this phylum—were more abundant in the overweight/obese group.

The obesity-related microbes identified in previous studies using fecal samples, such as H. parainfluenzae, V. atypica, and R. mucilaginosa were also found in this study in gastric mucosal samples. This suggests that changes in these microbes may originate in the stomach, leading to their increase or decrease throughout the gastrointestinal tract, ultimately affecting the colon and fecal microbiota. Notably, the altered abundance of D. dubosii, B. polymerisocia, and R. palustris (decreased), and N. perflava, B. australiense, C. concisus, S. rubneri (increased) in the overweight/obese group has not been previously reported in studies using intestinal or fecal microbiota. These shifts may reflect unique gastric environmental factors rather than obesity per se. Given that H. pylori infection alters gastric microbial diversity during progression to atrophic gastritis and intestinal metaplasia (Noto and Peek, 2017), we excluded individuals with such conditions to minimize confounding by inflammation. Therefore, the observed changes likely reflect gastric-specific rather than inflammation-driven microbiota alterations.

The gut microbiota contribute to obesity via pathways involving energy harvest, inflammation, and lipid and bile acid metabolism (Kim, 2023; Zhuang et al., 2023). Gut microbiota play a crucial role in the host’s energy harvest, as demonstrated in germ-free mouse models where mice harboring gut microbiota exhibited greater weight gain and higher energy absorption despite consuming the same diet (Lupp et al., 2012; Rooks and Garrett, 2016). In this study, PICRUSt2 analysis revealed BMI-related differences in fatty acid, amino acid, and vitamin metabolism. The increased activity of fatty acid biosynthesis pathways in obesity aligns with prior findings linking this shift to enhanced energy extraction and adipogenesis​​ (Turnbaugh et al., 2006; Kim et al., 2020; Duan et al., 2021). Furthermore, the diminished activity of amino acid degradation pathways in obese individuals may suggest alterations in protein metabolism. Although short-chain fatty acids (SCFAs) support lipid metabolism and intestinal health, their role in obesity remains debated due to variable effects (Turnbaugh et al., 2006; Chambers et al., 2015). In addition, gut microbes modulate bile acid deconjugation, which influences hepatic cholesterol and lipid metabolism (Kalaany and Mangelsdorf, 2006; Watanabe et al., 2006; Wahlström et al., 2016). While we identified alterations in predicted pathways related to amino acid metabolism (e.g., degradation) and SAM biosynthesis using PICRUSt2, our study did not include untargeted metabolomics or direct quantification of SAM/S-adenosylhomocysteine levels. Although microbial functions can be inferred using PICRUSt2, the lack of supporting data such as serum metabolite measurements or untargeted metabolomics prevents confirmation of the metabolic relevance of the gastric microbiota in this study.

Among the species significantly associated with BMI, there is limited research on the association between M. gordoncarteri and metabolic diseases. However, the Muribaculum genus plays a key role in carbohydrate metabolism, particularly glycolysis and gluconeogenesis (Chung et al., 2020; Zhu et al., 2024), which are central to energy regulation and may influence obesity. Muribaculum also contributes to SCFA production from dietary fiber, supporting energy balance, lipid metabolism, and anti-inflammatory effects beneficial in metabolic disorders like obesity and type 2 diabetes. Additionally, through bile salt hydrolase activity, Muribaculum affects bile acid metabolism. Its depletion has been associated with reduced levels of hyodeoxycholic and ursodeoxycholic acid, bile acids that activate the intestinal farnesoid X receptor (FXR), thereby influencing lipid absorption and bile acid synthesis via the FXR– fibroblast growth factor 19 axis (Xu et al., 2023). Therefore, reduced Muribaculum abundance may contribute to lipid dysregulation through impaired bile acid signaling.

Although D. dubosii has not been directly linked to obesity or metabolic diseases in humans or animal models, it belongs to the Muribaculaceae family, known for its role in carbohydrate metabolism and SCFA production—key processes in energy and lipid regulation (Lagkouvardos et al., 2019; Chung et al., 2020). Given its reduced abundance in obese individuals, further research is warranted to clarify its potential involvement in metabolic dysregulation via impaired carbohydrate metabolism and SCFA-associated protective functions.

Studies suggest that Turicibacter genus, including T. bilis, may affect host lipid metabolism and be associated with obesity-related changes in body weight (Fung et al., 2019; Lynch et al., 2023). A systematic review also reported lower levels of Turicibacter-related taxa in obese individuals compared to lean controls, indicating a potential protective role against metabolic dysfunction (Xu et al., 2022).

Regarding chronic inflammation, lipopolysaccharides from gram-negative bacteria can cross the intestinal barrier and trigger systemic inflammation via the Toll-like receptor-4 pathway, promoting the production of pro-inflammatory cytokines (such as IL-1, IL-6, and TNF-α) and contributing to insulin resistance (Cani et al., 2009; Lee et al., 2020). The elevated abundance of H. parainfluenzae and V. atypica in obese individuals in our study suggests a possible role of gastric microbiota in systemic inflammation and metabolic disorders. H. parainfluenzae is known to elicit mucosal immune responses in chronic obstructive pulmonary disease (Mitchell and Hill, 2000), while V. atypica, prevalent in dysbiotic oral biofilms, has been linked to altered inflammatory and nutritional status in children (Theodorea et al., 2022).

Several studies have linked H. pylori infection to metabolic dysregulation, including obesity and insulin resistance (Azami et al., 2021; Baryshnikova et al., 2024). For instance, Azami et al. (2021) reported significantly elevated BMI and insulin resistance in H. pylori-positive individuals, while Baryshnikova et al. (2024) suggested that reduced ghrelin levels and chronic inflammation may underlie these metabolic disturbances. To avoid confounding effects of infection-induced microbiota shifts, our study excluded H. pylori-positive subjects, allowing for a more accurate assessment of BMI-associated changes in gastric microbiota among non-infected individuals. Future research directly comparing H. pylori-positive and -negative populations across BMI categories could provide valuable insights into the interactive effects of H. pylori infection and host metabolic status on gastric microbial ecology.

The association between gastric microbiota and BMI highlights the stomach as a potential therapeutic target for modulating obesity. Interventions targeting the gastric microbiota, such as probiotics or dietary modifications, may complement existing treatments aimed at restoring gut microbial balance. Additionally, the distinct microbial profiles observed in this study warrant further research to elucidate the causal relationships between specific bacterial taxa and metabolic pathways.

This study had several limitations. First, the small sample size (n=10 per group) substantially limits the statistical power and generalizability of our findings. In particular, the limited sample size increases the risk of false-positive or -negative results and precludes robust detection of subtle microbial differences. Furthermore, the unequal sex distribution in the normal weight group and the absence of sex-stratified statistical analysis limits our ability to draw definitive conclusions regarding sex-specific microbial patterns. In our study, the proportion of women was higher than that of men in the normal weight group. Subgroup analysis based on sex (Supplementary Figure S5A) revealed that female participants exhibited lower alpha diversity metrics—including the Shannon index, observed ASVs, and Faith’s PD—compared to their male counterparts; however, these differences were not statistically significant (P>0.05). Furthermore, we confirmed that the separation observed between the normal and overweight/obese groups in the beta diversity of PCoA (Figure 2A) may not have been influenced by this sex imbalance (Supplementary Figure S5B). In addition, most participants in this study resided in a specific region of South Korea, which limits the ability to reflect geographic diversity related to dietary habits and lifestyle. Given the homogeneity of the study population, further validation in multi-center and multi-ethnic cohorts is necessary to confirm the findings. Second, this study is a cross-sectional analysis comparing overweight/obese and normal-weight groups using 16S rRNA gene sequencing. Due to the nature of this design, it is difficult to determine whether the observed differences in microbial composition are a cause or consequence of obesity. Third, although we excluded individuals with H. pylori infection to minimize its confounding effect on the gastric microbiota, other potential confounders such as dietary habits, physical activity, medication use, socioeconomic status, and host genetic factors were not systematically assessed and thus could not be adjusted for. In addition, local physiological variables, including gastric pH and mucosal immune markers such as cytokine levels, were not measured. This was due to the limited volume of biopsy tissue obtained from clinical endoscopy. Nonetheless, these factors may be important in shaping the gastric microbial environment. Lastly, we acknowledge that deeper functional validation, such as shotgun metagenomics, metatranscriptomics, or experimental verification of microbial metabolic activity, was not performed. While our findings suggest that taxa such as Muribaculum and Turicibacter are linked to metabolic pathways involving SCFA production and bile acid metabolism, our study did not include direct measurement of host biomarkers such as circulating bile acids, inflammatory cytokines, or fecal SCFA concentrations. These data would be valuable in confirming the functional consequences of microbial shifts. Therefore, future studies with larger, geographically diverse cohorts and balanced sex distributions are necessary to validate these preliminary observations. Moreover, longitudinal studies integrating host metabolic profiles with microbial community data—using multi-omics approaches such as metabolomics, microbial genome analysis, and host genotyping—and accounting for dietary habits, local physiological parameters, and other potential confounding factors, would be valuable to better characterize the functional implications of gastric microbiota alterations in obesity.

In conclusion, our findings highlight significant differences in the composition and functional potential of the gastric microbiota across BMI categories. The identification of specific microbial taxa and metabolic pathways associated with obesity provides a valuable basis for future research into the metabolic roles of the gastric microbiota and its potential as a therapeutic target.