Chronic urticaria (CU) is a common chronic inflammatory disease characterized by recurrent mast cell activation with unclear pathogenesis. Associations with microorganisms such as Helicobacter pylori and hepatitis virus have been reported [1]. Otherwise, the gut microbiome is closely linked to immunity and implicated in various diseases including skin, neurologic, and metabolic disorders [2-5]. Mast cells play a key role in such interactions [2, 3]. CU and gut microbiota share common traits, both strongly influenced by diet and lifestyle. This study explores their relationship. A total of 84 CU patients and 30 healthy controls were enrolled (Table S1). The mean CU duration was 2.0 ± 3.1 years and the median (interquartile range) UAS-15 and UCT scores were 8 (6–10) and 12 (10–15), respectively. We used 16S rRNA gene sequencing to examine gut microbiome profiles in fecal samples. CU patients exhibited significant gut microbiome changes (β-diversity) with increased Firmicutes and decreased Bacteroidetes abundance (p = 0.017) (Figure 1A,B and Figure S1). These alterations correlated with CU severity and urticaria activity scores (Figure 1C,D and Figure S2); the relative abundance of Bacteroidaceae was negatively related to UAS-15 (coefficient = −0.331, p = 0.014), whereas that of Firmicutes showed a positive correlation (coefficient = 0.104, p = 0.044). The differences in relative functional gene enrichment between the CU and healthy controls were also more pronounced in severe CU (Figure S3). Increases in the Firmicutes/Bacteroidetes (F/B) ratio are also widely reported in pathological conditions, including obesity, diabetes, and inflammatory bowel disease [4]. This microbial shift in obesity leads to increased intestinal permeability resulting in lipopolysaccharide (LPS)-mediated metabolic endotoxemia and subsequent systemic low-grade inflammation [5]. We also assessed the plasma levels of LPS, immunoglobulins (Ig), and LL-37 (Figure 2A). Plasma LPS levels were higher in CU patients (Figure 2B) and also correlated with CU severity (Figure 2C). IgE levels were increased in CU patients compared to controls, as previously reported, while IgM levels were lower. Total IgM levels are known to be influenced by the gut microbiome, and significantly lower levels have been reported in treatment-resistant CU patients. The plasma cathelicidin peptide, LL-37, was also increased in CU patients and showed correlations with altered enterotype (Figure S4). LL-37 forms the first layer of defense against bacteria in epithelial cells of the intestine, airway, and skin. LL-37 from the colon is also involved in maintaining colon mucosal barrier integrity and has been reported to affect the gut microbiome composition [6]. LL-37 directly stimulates mast cells via MRGPRX2 and acts as a strong mast cell chemoattractant. Inflammatory bowel disease, which shows a similar enterotype, increased F/B ratio [4], is characterized by gut mast cell activation associated with intestinal motor abnormalities and barrier dysfunction [3]. In this study, fecal water content was significantly higher in the CU group than in controls (78.97% ± 6.71% vs. 74.73% ± 5.96%, p = 0.003; Figure S5), and might be caused by mast cell activation via LL-37 and IgE, increasing bowel transit and intestinal permeability, represented by elevated plasma LPS levels. This study has limitations, including inadequately controlling important confounders such as diet and medication. Moreover, it demonstrates correlation rather than causation, highlighting the need for mechanistic research to establish causal relationships. Furthermore, the gut microbiome and CU may interact bidirectionally, potentially creating a vicious cycle. This study revealed that CU is associated with distinct gut microbiome alterations that show a potential link with disease severity and plasma levels of LPS, immunoglobulins, and LL-37, all related to mast cell activation. Hopefully, future research will guide dietary interventions or probiotics for CU treatment and relapse prevention. Conception and design: Han-Ki Park and Jae-Woo Kwon. Acquisition of data and analysis: Han-Ki Park, Young Her, and Jae-Woo Kwon. Development of methodology, and analysis and interpretation of data: Han-Ki Park, Doo Young Choi, and Tansol Park. Drafting of the manuscript, review, and/or revision of the manuscript: Han-Ki Park, Young Her, Doo Young Choi, Tansol Park, and Jae-Woo Kwon. Study supervision: Han-Ki Park, Doo Young Choi, and Jae-Woo Kwon. All authors jointly discussed, reviewed, and amended the manuscript. This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-RS-2023-00279953). The biospecimens and data used for this study were provided by the Biobank of Kangwon University Hospital, a member of the Korea Biobank Network. The authors declare no conflicts of interest. The data that support the findings of this study are available from the corresponding author upon reasonable request. Figure S1. Data S1. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.