The association of gut microbiota with responsiveness to initial high-dose intravenous immunoglobulin therapy in Kawasaki disease

The association of gut microbiota with responsiveness to initial high-dose intravenous immunoglobulin therapy in Kawasaki disease | 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 Article The association of gut microbiota with responsiveness to initial high-dose intravenous immunoglobulin therapy in Kawasaki disease Masato Ogawa, Takayuki Hoshina, Daisuke Shimizu, Masahiro Ishii, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6989625/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Variations in gut microbiota may contribute to the pathogenesis and treatment response in Kawasaki disease (KD), but their role remains unclear. We analyzed fecal samples from 25 children with acute-phase KD and 9 age-matched healthy controls, none of whom had received antibiotics or steroids within two months of sampling. The gut microbiota was examined using 16S rRNA amplicon sequencing. Among the KD patients, 8 were refractory to initial intravenous immunoglobulin (IVIG) therapy. Although α-diversity tended to be lower in KD patients compared to healthy controls, no significant difference was observed. Similarly, α-diversity did not differ significantly between IVIG responders and non-responders. However, comparison of bacterial composition within the KD group revealed that Peptostreptococcaceae was significantly more abundant in IVIG non-responders ( P = 0.02). At the genus level, Peptostreptococcus and Intestinibacter were also more prevalent in the non-responder group. These findings suggest that specific gut microbiota, rather than overall diversity, may be associated with IVIG treatment resistance in KD. Peptostreptococcaceae was relatively abundant in KD patients who did not respond to initial IVIG therapy. Responsiveness to IVIG therapy in KD may be associated with variations in the gut microbiota. Health sciences/Diseases Biological sciences/Immunology Health sciences/Medical research Biological sciences/Microbiology dysbiosis gut microbiota intravenous immunoglobulin Kawasaki disease Peptostreptococcaceae Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Kawasaki disease (KD) is a self-limiting systemic vasculitis of unknown etiology that mainly develops during childhood. [ 1 ] Coronary artery abnormalities (CAAs) occur in 20–25% of untreated patients. [ 2 ] The administration of high-dose intravenous immunoglobulin (IVIG) and oral aspirin resolves the symptoms of the acute phase of KD and reduces the occurrence of CAAs. [ 3 ] However, approximately 20% of patients are resistant to the initial IVIG therapy. [ 4 ] Although some previous studies suggested that genetic factors are associated with susceptibility to the development of CAAs or resistance to IVIG therapy, [ 5 ] [ 6 ] the exact causes for the different responsiveness to IVIG therapy in patients with KD are unknown. In addition to genetic factors, microbes and environmental factors have also been reported to be associated with the development of KD and responsiveness to therapy. [ 7 ] [ 8 ] [ 9 ] [ 10 ] A recent review suggested that variations in the gut microbiota may be involved in the development of KD. [ 11 ] The gut microbiota, containing over 1,000 bacterial species and 22 million genes, plays a crucial role in regulating the internal human environment. [ 12 ] Dysbiosis of the gut microbiota is associated with various childhood diseases, such as necrotizing enterocolitis, food allergy, autism, metabolic syndrome, and inflammatory bowel syndrome. [ 13 ] [ 14 ] [ 15 ] [ 16 ] However, few studies have investigated the relationship between responsiveness to IVIG therapy in KD and variations in the gut microbiota. In this study, we investigated the association of the gut microbiota with the development of KD and responsiveness to treatment using next-generation sequencing-based 16S rRNA amplicon sequencing. RESULTS The characteristics of eligible children The median ages of the KD patients and HCs were 17 (range, 5-57) months and 15 (range 5-59) months, respectively (Table 1). Eight of the 25 KD patients did not respond to the initial therapy. The clinical and demographic characteristics of KD with patients with and without a response to the initial IVIG therapy are shown in Table 2. The median age of the patients who did not respond to initial IVIG therapy (12 months) was younger than that of the patients who responded to the therapy (26 months), although the difference was not statistically significant. The median duration (in days) of illness at the time of initial IVIG therapy was significantly earlier in patients who did not respond to the initial IVIG therapy (3 days) than in those who responded to the therapy (5 days) ( P = 0.03). Comparison of gut microbiota between KD patients and healthy children In a comparison of α-diversity, the diversity in the gut microbiota in the KD group tended to be lower than that in the HC group, although there were no significant differences (Figure 1a, b). No significant differences were observed in the comparison of β-diversity using a weighted UniFrac analysis (data not shown). Furthermore, there was no consistent trend in the taxonomy of the top 10 bacteria detected at the genus level in the KD group (Figure 1c). Comparison of gut microbiota between KD patients with and without a response to the initial IVIG therapy In the comparison of α-diversity, there were no significant differences in the gut microbiota between KD patients with and without a response to the initial IVIG therapy (Figure 2a, b). Furthermore, there was no consistent trend in the taxonomy of the top 10 bacteria detected at the genus level in each KD group (Figure 2c). Relative abundance of bacteria in KD patients without a response to the initial IVIG therapy At the family level, Peptostreptococcaceae was significantly more abundant in KD patients who did not respond to the initial IVIG therapy than in those who responded to the initial IVIG therapy ( P = 0.02) (Figure 3a, b). The same tendency was confirmed even in the regression analysis, although there was no statistical significance ( P = 0.122). In the family Peptostreptococcaceae , at the genus level, Peptostreptococcus and Intestinibacter were more abundant in the group of KD patients without a response to the initial IVIG therapy, although the difference was not statistically significant (Figure 3c). DISCUSSION In this study, the diversity in the gut microbiota of patients with KD tended to be lower than that in age-matched healthy children, although the differences were not statistically significant. This tendency has also been reported in previous studies. [ 17 ] [ 18 ] [ 19 ] [ 20 ] [ 21 ] However, in many previous studies, fecal samples from patients with KD collected after antimicrobial therapy were not excluded, [ 17 ] [ 19 ] [ 21 ] indicating that it was difficult to distinguish whether the lower diversity of gut microbiota was due to KD itself or the effects of prior antimicrobial therapy. Thus, our study population was limited to children who had not been treated with antimicrobial agents within 2 months before sample collection in order to minimize the effect of the use of antimicrobial agents on changes in the gut microbiota. In addition to the tendency for lower diversity in the gut microbiota in KD patients, we found that Peptostreptococcaceae was more abundant in KD patients who did not respond to the initial IVIG therapy than in those who responded to the initial IVIG therapy. Although all patients were also initially treated with aspirin, which might affect the variation of gut microbiota, we believe that the administration of aspirin has no effect on the differences in the microbiota between patients with and without response to initial IVIG therapy because all patients received aspirin continuously. This result suggested that variations in the gut microbiota might be associated with responsiveness to initial IVIG therapy in KD. To the best of our knowledge, no study has investigated the relationship between variations in the gut microbiota and responsiveness to IVIG therapy in children with KD who had not received prior antimicrobial agents. In this study, we found that Peptostreptococcaceae was more abundant in the group of KD patients who did not respond to the initial IVIG therapy than in those who responded to the initial IVIG therapy. At the genus level, Peptostreptococcus and Intestinibacter were more abundant in the former group. In the analysis performed by the culture-based method, Lactobacillus was rarely isolated from fecal samples collected from patients with KD during the acute phase, whereas Peptostreptococcus and Eubacterium were highly isolated. [ 22 ] The decrease of Lactobacillus in the gut microbiota is speculated to lead to the increased production of proinflammatory cytokines such as tumor necrosis factor (TNF)-α, interleukin (IL)-1, or IL-6, and decreased subsets of regulatory T cells. [ 23 ] Although the significance of the high isolation rate of Peptostreptococcus from feces is unclear, it may reflect dysbiosis in the gut microbiota. Given the results of this study, dysbiosis in the gut microbiota may be pronounced in patients with KD who do not respond to the initial IVIG therapy. Intestinibacter is abundant in the gut microbiota of patients with various diseases (e.g., IgA vasculitis, inflammatory bowel disease, allergic diseases, and lung cancer). [ 19 ] [ 24 ] [ 25 ] [ 26 ] I. bartlettii can degrade fucose, suggesting its indirect involvement in mucus degradation. [ 27 ] As with Peptostreptococcus , although the direct impact of Intestinibacter on the development and responsiveness to the treatment of various diseases is uncertain, an increase in this bacterium may compromise the barrier mechanism in the intestinal mucosa, allowing pathogenic bacteria and toxins to infiltrate the bloodstream and trigger an excessive immune response. In KD patients who did not respond to the initial IVIG therapy, serum levels of proinflammatory cytokines, such as TNF-α, IL-1 and IL-6, were markedly elevated, compared with those who responded to the initial IVIG therapy. [ 28 ] Variations in the gut microbiota may be associated with excessive inflammation in KD and determine responsiveness to the initial IVIG therapy. However, the association between variations in the gut microbiota and responsiveness to the treatment in KD has not proven in vitro and in vivo experiments. Further basic studies, such as those using animal model, are desired to clarify this association. Two previous studies focusing only on children with KD without prior antimicrobial agents suggested that variations in the gut microbiome may be involved in the development of KD. [ 18 ] [ 20 ] One study indicated that KD patients exhibited a significant reduction in fecal microbial diversity in the acute phase relative to healthy children, and that Enterococcus , Acinetobacter , Helicobacter , Lactococcus , Staphylococcus and Butyricimonas were significantly enriched in patients with acute KD in comparison to healthy children. [ 18 ] Another study indicated that children with a history of KD have characteristic gut microbiota with complexity and that the Ruminococcus gnavus group was more abundant in the gut microbiota, while genus Blautia was less abundant in children with a history of KD. [ 20 ] Although variations in the gut microbiota of patients with KD have been observed in many studies, including our own, the predominant and non-predominant bacterial species differ in all studies. The etiology of KD remains uncertain and various environmental factors are speculated to be involved. The results of our study also suggest that patients with KD can be divided into two groups: those with reduced diversity of gut microbiota in comparison to healthy children and those with the opposite (Fig. 1 a). Given this result, dysbiosis of the gut microbiota may not be involved in the development of KD in all patients. The relationship between the gut microbiota and the development of KD may require further investigation in a larger population. The present study was associated with several limitations. First, the study population was relatively small, which could have affected the accuracy of the statistical analysis. Second, the age distribution of KD patients with and without a response to initial IVIG therapy was different, although the difference was not statistically significant. The differences in the gut microbiota between the two groups may be affected by age. However, as Peptostreptococcaceae is not isolated predominantly in infants, [ 29 ] we believe that age has little effect. Finally, we confirmed that the eligible children had not received antimicrobial or steroid therapy within 2 months before sample collection; however, their history of these therapies over 2 months prior to it was not confirmed. As antimicrobial and steroid therapies can cause long-term changes in the gut microbiota, [ 30 ] [ 31 ] the results of this study may have been affected by such therapies, if any. In conclusion, Peptostreptococcaceae was relatively abundant in KD patients who did not respond to initial IVIG therapy. Responsiveness to IVIG therapy in KD may be associated with variations in the gut microbiota. As the direct effect of Peptostreptococcaceae on the treatment response in KD is uncertain, further studies are needed to perform a detailed analysis of the family Peptostreptococcaceae . MATERIALS and METHODS Study population This prospective study included 25 patients with KD who were admitted to the Department of Pediatrics at the Hospital of the University of Occupational and Environmental Health, Japan and Kitakyushu General Hospital from October 2019 to December 2023 and who were initially treated with high-dose IVIG (2 g/kg) and oral aspirin (30 mg/kg/day). The Diagnostic Guidelines for Kawasaki Disease (6th version) were used as the diagnostic criteria for KD. [32] No patients were diagnosed with incomplete KD. Patient clinical information was collected using a standardized case report form. IVIG was administered for 12–24 hours in all patients. Patients whose body temperature was ≥37.5°C for ≥24 h after the initial IVIG therapy or who showed recurrent KD symptoms after initial defervescence were judged as resistant to the initial IVIG therapy. [32] CAA was defined as an internal lumen diameter of ≥4 mm or local dilation (≤4 mm internal diameter in children <5 years of age and <1.5-fold that of an adjacent segment in children ≥5 years of age). [33] Nine age-matched healthy children served as healthy controls (HC). None of the eligible children were treated with antimicrobial agents or corticosteroids within 2 months of sample collection. Sample collection and DNA extraction Fecal samples were collected from the subjects to analyze the gut microbiota. Stools excreted by children or rectal swabs obtained by the insertion of a swab were collected. In patients with KD, samples were collected before initial treatment. The collected samples were stored at –20°C for bacterial gene analysis. DNA was extracted from fecal samples by vigorous shaking together with sodium dodecyl sulfate solution (final concentration, 3.0%) and glass beads as previously reported. [34] Preparation of bacterial 16S rRNA gene library, its sequencing, and statistical analysis The bacterial 16S rRNA gene were amplified by PCR with the v3–v4 hypervariable region primers (Forward: TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG, Reverse: GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC), and sequenced using a MiSeq System. (Illumina, San Diego, CA). The obtained raw sequence data were analyzed using QIIME2 (version 2021.4.0), [35] and then the amplicon sequence variants (ASV) were characterized by DADA2, [36] following the removal of singletons and rare ASV (< 0.001%). Taxonomy was assigned to ASV using the q2-feature-classifier based on SILVA 138.1. [37] The statistical analysis was performed according to the method described in a previous report. [38] Briefly, the Kruskal–Wallis test was applied to compare the differences in the α-diversity of microorganisms. Differences in the relative presence of the microbiome were determined using a linear discriminant analysis (LDA) effect size (LEfSe). [39] Regression analysis was conducted using Python (version 3.10.6) with the statsmodels library (version 0.14.4). The explanatory variables were standardized using the StandardScaler from sklearn.preprocessing (version 1.6.1). Logistic regression was then performed to fit the model, and standardized partial regression coefficients as well as adjusted P -values were calculated. P -value <0.05 were considered to be statistically significant. Ethical approval This study was approved by the Institutional Review Board of the University of Occupational and Environmental Health, Japan (UOEHCRB21-062), Kitakyushu General Hospital (H30-21), and H.U Group Holdings, Inc. (19-048). Informed consent was obtained from the parents of all patients. This study was conducted in accordance with the Declaration of Helsinki. Declarations Acknowledgements We appreciate the help of Dr. Brian Quinn (Japanese Medical Communication, Fukuoka, Japan) for editing the manuscript. Author contribution Masato Ogawa, Daisuke Shimizu, Masahiro Ishii and Masumi Kojiro conceptualized the study, carried out the initial analysis of data for work, drafted the initial manuscript, approved the final version to be published and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Takayuki Hoshina designed the study, carried out the acquisition, analysis of data for the work, revised the work critically for important intellectual content, approved the final version to be published and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Takeru Nakabayashi, Kosei Tanaka and Masahiro Kamita carried out the acquisition and analysis of data for the work, revised the work critically for important intellectual content, approved the final version to be published and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Koichi Kusuhara designed the study, carried out the analysis and interpretation of data for the work, revised the work critically for important intellectual content, approved the final version to be published and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Data Availability Statement The data presented in the study are deposited in the Sequence Read Archive (SRA) repository, accession number PRJNA1224998. Conflict of Interest We declare that this research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Funding Our study was supported by JSPS KAKENHI grant number JP23K07324. References Burns, J.C., Glodé, M.P. Kawasaki syndrome. Lancet. 364 , 533-4 (2004). Kato, H., Koike, S., Yamamoto, M., Ito, Y., Yano, E. Coronary aneurysms in infants and young children with acute febrile mucocutaneous lymph node syndrome. J Pediatr. 86, 892-8. (1975). McCrindle, B.W., et al. Diagnosis, treatment, and long-term management of Kawasaki Disease: a scientific statement for health professionals from the American Heart Association. Circulation. 135 , e927-99. (2017). Uehara, R., et al. Analysis of potential risk factors associated with nonresponse to initial intravenous immunoglobulin treatment among Kawasaki disease patients in Japan. Pediatr Infect Dis J . 27 , 155-60. (2008). Onouchi, Y., et al. ITPKC and CASP3 polymorphisms and risks for IVIG unresponsiveness and coronary artery lesion formation in Kawasaki disease. Pharmacogenomics J. 13 , 52-9. (2013). Shimizu, C., et al. Genetic variation in the SLC8A1 calcium signaling pathway is associated with susceptibility to Kawasaki Disease and coronary artery abnormalities. Circ Cardiovasc Genet. 9, 559-68. (2016). Shimizu, D., et al. Seasonality in clinical courses of Kawasaki disease. Arch Dis Child. 104, 694-6. (2019). Shimizu, D., et al. The possible association between epidemics of hand-foot-and-mouth disease and responsiveness to immunoglobulin therapy in Kawasaki disease. Front Pediatr. 10 , 968857. (2022). Fujii, F., Egami, N., Inoue, M., Koga, H. Weather condition, air pollutants, and epidemics as factors that potentially influence the development of Kawasaki disease. Sci Total Environ. 741, 140469. (2020). Marutani, K., et al. Respiratory viral infections and Kawasaki disease: A molecular epidemiological analysis. J Microbiol Immunol Infect. 57, 691-9 (2024). Kaneko, K., Akagawa, S., Akagawa, Y., Kimata, T., Tsuji, S. Our evolving understanding of Kawasaki disease pathogenesis: Role of the gut microbiota. Front Immunol. 11, 1616. (2020). Li, J., et al. An integrated catalog of reference genes in the human gut microbiome. Nat Biotechnol. 32 , 834-41. (2014). Mangiola, F., Ianiro, G., Franceschi, F., Fagiuoli, S., Gasbarrini, G., Gasbarrini, A. Gut microbiota in autism and mood disorders. World J Gastroenterol. 22, 361-8. (2016). Wang, P.X., Deng, X.R., Zhang, C.H., Yuan, H.J. Gut microbiota and metabolic syndrome. Chin Med J. (Engl) 133, 808-16. (2020). Qiu, P., Ishimoto, T., Fu, L., Zhang, J., Zhang, Z., Liu, Y. The Gut Microbiota in Inflammatory Bowel Disease. Front Cell Infect Microbiol. 12, 733992. (2022). Duess, J.W., et al. Necrotizing enterocolitis, gut microbes, and sepsis. Gut Microbes . 15, 222147. (2023) Kinumaki, A., Sekizuka, T., Hamada, H., Kato, K., Yamashita, A., Kuroda, M. Characterization of the gut microbiota of Kawasaki disease patients by metagenomic analysis. Front Microbiol. 6, 824. (2015). Chen, J., et al. Altered gut microbiota correlated with systemic inflammation in children with Kawasaki disease. Sci Rep. 10, 14525. (2020). Hu, X., et al. Landscape of intestinal microbiota in patients with IgA nephropathy, IgA vasculitis and Kawasaki disease. Front Cell Infect Microbiol. 12, 1061629. (2022). Teramoto, Y., Akagawa, S., Hori, S.I., Tsuji, S., Higasa, K., Kaneko, K. Dysbiosis of the gut microbiota as a susceptibility factor for Kawasaki disease. Front Immunol. 14, 1268453. (2023). Han, L., Liu, X., Lan, Y., Hua, Y., Fan, Z., Li, Y. Metagenomic analysis demonstrates distinct changes in the gut microbiome of Kawasaki diseases children. Front Immunol. 15, 1416185. (2024). Takeshita, S., Kobayashi, I., Kawamura, Y., Tokutomi, T., Sekine, I. Characteristic role of intestinal microflora in Kawasaki disease. Acta Paediatr . 91, 783-8. (2001). Reading, N.C., Kasper, D.L. The starting lineup: key microbial players in intestinal immunity and homeostasis. Front Microbiol. 2, 148. (2011). Forbes, J.D., et al. A comparative study of the gut microbiota in immune-mediated inflammatory diseases—does a common dysbiosis exist? Microbiome. 6, 221. (2018). Wang, Y., et al. Association between gut microbiota and pan-dermatological diseases: a bidirectional Mendelian randomization research. Front Cell Infect Microbiol. 14, 1327083. (2024). Yang, W., Fan, X., Li, W., Chen, Y. Causal influence of gut microbiota on small cell lung cancer: a Mendelian randomization study. Clin Respir J. 18, e13764. (2024). Song, Y.L., Liu, C.X., McTeague, M., Summanen, P., Finegold, S.M. Clostridium bartlettii sp. nov., isolated from human faeces. Anaerobe . 10, 179-84. (2004). Wang, Y., et al. Do cytokines correlate with refractory Kawasaki disease in children? Clin Chim Acta. 506, 222-7. (2020). Bäckhed, F., et al. Dynamics and stabilization of the human gut microbiome during the first year of life. Cell Host Microbe. 17, 690-703. (2015). Wurm, J., Curtis, N., Zimmermann, P. The effect of antibiotics on the intestinal microbiota in children—a systematic review. Front Allergy. 5, 1458688. (2024). Okafuji, H., et al. Oral corticosteroids impair mucin production and alter the posttransplantation microbiota in the gut. Digestion. 103, 269-86. (2022). Kobayashi, T., et al. Revision of diagnostic guidelines for Kawasaki disease (6th revised edition). Pediatr Int. 62, 1135–8. (2020). Fukazawa, R., et al. Japanese Circulation Society Joint Working Group. JCS/JSCS 2020 Guideline on Diagnosis and Management of Cardiovascular Sequelae in Kawasaki Disease. Circ J. 22, 84: 1348-1407. (2020). Ogawa, M., Hoshina, T., Abushawish, A., Kusuhara K. Evaluation of the usefulness of culture of induced sputum and the optimal timing for the collection of a good-quality sputum sample to identify causative pathogen of community-acquired pneumonia in young children: A prospective observational study. J Microbiol Immunol Infect. 56, 1036-44. (2023). Bolyen, E., et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 37, 852-7. (2019). Callahan, B.J., McMurdie, P.J., Rosen, M.J., Han, A.W., Johnson, A.J., Holmes, S.P. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods. 13, 581-3. (2016). Quast, C., et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590-6. (2013). Hashimoto, Y., Okada, S., Yasuda, K., Kawagoe, M., Kajiya, M., Tsuga, K. Microbial differences between active and remission peri-implantitis. Sci Rep. 12, 5284. (2022). Segata, N., et al. Metagenomic biomarker discovery and explanation. Genome Biol. 12, R60. (2011). Tables Table 1. The demographic and clinical characteristics of eligible children KD patients n = 25 Healthy children n = 9 P -value Age, months, median (range) 17 (5-57) 15 (5-59) 0.77 Gender, n, (% male) 15 (60) 3 (33) 0.17 Incomplete KD, n, (%) 0 (0) Initial treatments for KD IVIG, n, (%) 25 (100) Oral aspirin, n (%) 25 (100) Patients without response to initial IVIG therapy, n, (%) 8 (32) Coronary artery legions, n, (%) 0 (0) KD: Kawasaki disease, IVIG: intravenous immunoglobulin Table 2. The comparison between patients with Kawasaki disease with and without response to initial IVIG therapy IVIG responders n = 17 IVIG non-responders *1, 2 n = 8 P -value Age, months, median (range) 26 (5-57) 12 (5-50) 0.07 Gender, n, (% male) 9 (53) 6 (75) 0.30 Day of illness at initial IVIG therapy, median (range) 5 (3-10) 3 (3-4) 0.03 Patients with coronary artery abnormalities, n, (%) 0 (0) 0 (0) 1.00 *1 This category includes patients with resistance to the initial IVIG therapy that was defined with reference to the previous study (17). *2 Five and three patients were treated with two doses of IVIG and two doses of IVIG and infliximab, respectively. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-6989625","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":501300757,"identity":"2cfcc94c-a5ee-43dc-86eb-8714a43f7bc8","order_by":0,"name":"Masato Ogawa","email":"","orcid":"","institution":"University of Occupational and Environmental Health","correspondingAuthor":false,"prefix":"","firstName":"Masato","middleName":"","lastName":"Ogawa","suffix":""},{"id":501300759,"identity":"ce9ff08d-d1b2-430c-87a9-25ed593fc977","order_by":1,"name":"Takayuki Hoshina","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIiWNgGAWjYBACAwYGNoYEBgY5CJsBxAYDNoJajEnUAgSJDWhacANz9vZnDx7usEtf2968gZmnwiaPQSKB8cMPBr48XFose86YGySeSc7dduZYATPPmbRioBZmyR4GtmKcDruRwyaR2Macu+1GjgEzb9vhxP03Ehikgc4FORWHlvRnQC316Wb334C0/E9sANryG7+WBDOglsMJZjd4QFoOgLSw4bflzBmQluOG286kFRyccyY5sYHnYZtljwEevxxvfyb5s61a3uz44Y0P3lTYJTawJx++8aPiGM4QQwEHIBQj0EkGxxKI0oIMakjXMgpGwSgYBcMVAAA/QFZv1RjVWwAAAABJRU5ErkJggg==","orcid":"","institution":"University of Occupational and Environmental Health","correspondingAuthor":true,"prefix":"","firstName":"Takayuki","middleName":"","lastName":"Hoshina","suffix":""},{"id":501300760,"identity":"ca39c0ac-8e22-45f1-8f92-e82d58ecf321","order_by":2,"name":"Daisuke Shimizu","email":"","orcid":"","institution":"University of Occupational and Environmental Health","correspondingAuthor":false,"prefix":"","firstName":"Daisuke","middleName":"","lastName":"Shimizu","suffix":""},{"id":501300761,"identity":"650d9cf2-bd4c-48b9-af70-f1c2b0633705","order_by":3,"name":"Masahiro Ishii","email":"","orcid":"","institution":"Kitakyūshū General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Masahiro","middleName":"","lastName":"Ishii","suffix":""},{"id":501300765,"identity":"64a050b3-89c9-4d91-8726-3c4f85f8b48f","order_by":4,"name":"Masumi Kojiro","email":"","orcid":"","institution":"Kitakyūshū General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Masumi","middleName":"","lastName":"Kojiro","suffix":""},{"id":501300767,"identity":"671ffcd3-bafd-4ee8-80b1-22bb8e0b7330","order_by":5,"name":"Takeru Nakabayashi","email":"","orcid":"","institution":"H.U. Group Research Institute G.K.","correspondingAuthor":false,"prefix":"","firstName":"Takeru","middleName":"","lastName":"Nakabayashi","suffix":""},{"id":501300771,"identity":"4145ecfd-99e0-46c8-a7a1-8d9f9a6a7681","order_by":6,"name":"Kosei Tanaka","email":"","orcid":"","institution":"H.U. Group Research Institute G.K.","correspondingAuthor":false,"prefix":"","firstName":"Kosei","middleName":"","lastName":"Tanaka","suffix":""},{"id":501300773,"identity":"6925f111-1854-4415-8195-fbd21e22a8e4","order_by":7,"name":"Masahiro Kamita","email":"","orcid":"","institution":"H.U. Group Research Institute G.K.","correspondingAuthor":false,"prefix":"","firstName":"Masahiro","middleName":"","lastName":"Kamita","suffix":""},{"id":501300774,"identity":"83db5134-f9aa-477d-bfe2-b76e20e119bd","order_by":8,"name":"Koichi Kusuhara","email":"","orcid":"","institution":"University of Occupational and Environmental Health","correspondingAuthor":false,"prefix":"","firstName":"Koichi","middleName":"","lastName":"Kusuhara","suffix":""}],"badges":[],"createdAt":"2025-06-27 08:38:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6989625/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6989625/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89272478,"identity":"fc8781ca-59b0-40e0-8666-8e63ffdb603b","added_by":"auto","created_at":"2025-08-18 09:06:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1412562,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of gut microbiota between children with Kawasaki disease (KD) and healthy children (HC). (a), (b) Comparison of α-diversity between KD and HC groups. (c) Taxonomy of the top 10 bacteria detected in genus level in KD and HC. Control: healthy children, KD: children with Kawasaki disease\u003c/p\u003e","description":"","filename":"figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6989625/v1/56afa34478b0d95480038182.png"},{"id":89272480,"identity":"b4e90ebf-7734-4b8b-ab79-f001cc158d80","added_by":"auto","created_at":"2025-08-18 09:06:00","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1515799,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of gut microbiota between patients with Kawasaki disease (KD) with and without response to initial intravenous immunoglobulin (IVIG) therapy. (a), (b) Comparison of α diversity between the groups of KD patients with and without response to initial IVIG therapy. (c) Taxonomy of the top 10 bacteria detected in genus level in KD patients with and without response to initial IVIG therapy. Responder: KD patients with response to initial IVIG therapy, non-responder (nonRes): KD patients without response to initial IVIG therapy\u003c/p\u003e","description":"","filename":"figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6989625/v1/e6e2201113e6d6e1bdecff6e.png"},{"id":89274090,"identity":"068ca29d-e176-4101-84ec-91992f13679a","added_by":"auto","created_at":"2025-08-18 09:14:00","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1242579,"visible":true,"origin":"","legend":"\u003cp\u003eThe relative abundance of bacteria in patients with Kawasaki disease (KD) without response to the initial intravenous immunoglobulin (IVIG) therapy. (a) Cladogram and linear discriminant analysis (LDA) score in KD patients with and without response to initial IVIG therapy. (b) Comparison of relative abundance of \u003cem\u003ePeptostreptococcaceae\u003c/em\u003e between KD patients with and without response to initial IVIG therapy. (c) Comparison of relative abundance of the genus level (\u003cem\u003ePeptostreptococcus\u003c/em\u003e, \u003cem\u003eIntestinibactor\u003c/em\u003e, \u003cem\u003eClostridioides\u003c/em\u003e, \u003cem\u003eRomboutsia\u003c/em\u003e and \u003cem\u003eTerrisporobacter\u003c/em\u003e) in the family \u003cem\u003ePeptostreptococcaceae\u003c/em\u003ebetween KD patients with and without response to initial IVIG therapy. Responder: KD patients with response to initial IVIG therapy, non-responder (nonRes): KD patients without response to initial IVIG therapy.\u003c/p\u003e","description":"","filename":"figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6989625/v1/79beebf7b8cef8ea03a9ffd0.png"},{"id":89343862,"identity":"697485f5-fab9-45d0-93bb-51b9347851de","added_by":"auto","created_at":"2025-08-19 04:08:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4046628,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6989625/v1/0a45b93a-83ba-4ec0-a313-daedb151eceb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The association of gut microbiota with responsiveness to initial high-dose intravenous immunoglobulin therapy in Kawasaki disease","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eKawasaki disease (KD) is a self-limiting systemic vasculitis of unknown etiology that mainly develops during childhood. [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] Coronary artery abnormalities (CAAs) occur in 20\u0026ndash;25% of untreated patients. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] The administration of high-dose intravenous immunoglobulin (IVIG) and oral aspirin resolves the symptoms of the acute phase of KD and reduces the occurrence of CAAs. [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] However, approximately 20% of patients are resistant to the initial IVIG therapy. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] Although some previous studies suggested that genetic factors are associated with susceptibility to the development of CAAs or resistance to IVIG therapy, [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] the exact causes for the different responsiveness to IVIG therapy in patients with KD are unknown.\u003c/p\u003e\u003cp\u003eIn addition to genetic factors, microbes and environmental factors have also been reported to be associated with the development of KD and responsiveness to therapy. [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] A recent review suggested that variations in the gut microbiota may be involved in the development of KD. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] The gut microbiota, containing over 1,000 bacterial species and 22\u0026nbsp;million genes, plays a crucial role in regulating the internal human environment. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] Dysbiosis of the gut microbiota is associated with various childhood diseases, such as necrotizing enterocolitis, food allergy, autism, metabolic syndrome, and inflammatory bowel syndrome. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] However, few studies have investigated the relationship between responsiveness to IVIG therapy in KD and variations in the gut microbiota.\u003c/p\u003e\u003cp\u003eIn this study, we investigated the association of the gut microbiota with the development of KD and responsiveness to treatment using next-generation sequencing-based 16S rRNA amplicon sequencing.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cstrong\u003eThe characteristics of eligible children\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe median ages of the KD patients and HCs were 17 (range, 5-57) months and 15 (range 5-59) months, respectively (Table 1). Eight of the 25 KD patients did not respond to the initial therapy. The clinical and demographic characteristics of KD with patients with and without a response to the initial IVIG therapy are shown in Table 2. The median age of the patients who did not respond to initial IVIG therapy (12 months) was younger than that of the patients who responded to the therapy (26 months), although the difference was not statistically significant. The median duration (in days) of illness at the time of initial IVIG therapy was significantly earlier in patients who did not respond to the initial IVIG therapy (3 days) than in those who responded to the therapy (5 days) (\u003cem\u003eP\u003c/em\u003e = 0.03).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison of gut microbiota between KD patients and healthy children\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn a comparison of \u0026alpha;-diversity, the diversity in the gut microbiota in the KD group tended to be lower than that in the HC group, although there were no significant differences (Figure 1a, b). No significant differences were observed in the comparison of \u0026beta;-diversity using\u0026nbsp;a weighted UniFrac analysis (data not shown). Furthermore, there was no consistent trend in the taxonomy of the top 10 bacteria detected at the genus level in the KD group (Figure 1c).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison of gut microbiota between KD patients with and without a response to the initial IVIG therapy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the comparison of \u0026alpha;-diversity, there were no significant differences in the gut microbiota between KD patients with and without a response to the initial IVIG therapy (Figure 2a, b). Furthermore, there was no consistent trend in the taxonomy of the top 10 bacteria detected at the genus level in each KD group (Figure 2c).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRelative abundance of bacteria in KD patients without a response to the initial IVIG therapy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAt the family level,\u0026nbsp;\u003cem\u003ePeptostreptococcaceae\u003c/em\u003e was significantly more abundant in KD patients who did not respond to the initial IVIG therapy than in those who responded to the initial IVIG therapy (\u003cem\u003eP\u003c/em\u003e = 0.02) (Figure 3a, b). The same tendency was confirmed even in the regression analysis, although there was no statistical significance (\u003cem\u003eP\u003c/em\u003e = 0.122). In the family \u003cem\u003ePeptostreptococcaceae\u003c/em\u003e, at the genus level, \u003cem\u003ePeptostreptococcus\u003c/em\u003e and \u003cem\u003eIntestinibacter\u003c/em\u003e were more abundant in the group of KD patients without a response to the initial IVIG therapy, although the difference was not statistically significant (Figure 3c).\u0026nbsp;\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn this study, the diversity in the gut microbiota of patients with KD tended to be lower than that in age-matched healthy children, although the differences were not statistically significant. This tendency has also been reported in previous studies. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] However, in many previous studies, fecal samples from patients with KD collected after antimicrobial therapy were not excluded, [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] indicating that it was difficult to distinguish whether the lower diversity of gut microbiota was due to KD itself or the effects of prior antimicrobial therapy. Thus, our study population was limited to children who had not been treated with antimicrobial agents within 2 months before sample collection in order to minimize the effect of the use of antimicrobial agents on changes in the gut microbiota. In addition to the tendency for lower diversity in the gut microbiota in KD patients, we found that \u003cem\u003ePeptostreptococcaceae\u003c/em\u003e was more abundant in KD patients who did not respond to the initial IVIG therapy than in those who responded to the initial IVIG therapy. Although all patients were also initially treated with aspirin, which might affect the variation of gut microbiota, we believe that the administration of aspirin has no effect on the differences in the microbiota between patients with and without response to initial IVIG therapy because all patients received aspirin continuously. This result suggested that variations in the gut microbiota might be associated with responsiveness to initial IVIG therapy in KD.\u003c/p\u003e\u003cp\u003eTo the best of our knowledge, no study has investigated the relationship between variations in the gut microbiota and responsiveness to IVIG therapy in children with KD who had not received prior antimicrobial agents. In this study, we found that \u003cem\u003ePeptostreptococcaceae\u003c/em\u003e was more abundant in the group of KD patients who did not respond to the initial IVIG therapy than in those who responded to the initial IVIG therapy. At the genus level, \u003cem\u003ePeptostreptococcus\u003c/em\u003e and \u003cem\u003eIntestinibacter\u003c/em\u003e were more abundant in the former group. In the analysis performed by the culture-based method, \u003cem\u003eLactobacillus\u003c/em\u003e was rarely isolated from fecal samples collected from patients with KD during the acute phase, whereas \u003cem\u003ePeptostreptococcus\u003c/em\u003e and \u003cem\u003eEubacterium\u003c/em\u003e were highly isolated. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] The decrease of \u003cem\u003eLactobacillus\u003c/em\u003e in the gut microbiota is speculated to lead to the increased production of proinflammatory cytokines such as tumor necrosis factor (TNF)-α, interleukin (IL)-1, or IL-6, and decreased subsets of regulatory T cells. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] Although the significance of the high isolation rate of \u003cem\u003ePeptostreptococcus\u003c/em\u003e from feces is unclear, it may reflect dysbiosis in the gut microbiota. Given the results of this study, dysbiosis in the gut microbiota may be pronounced in patients with KD who do not respond to the initial IVIG therapy. \u003cem\u003eIntestinibacter\u003c/em\u003e is abundant in the gut microbiota of patients with various diseases (e.g., IgA vasculitis, inflammatory bowel disease, allergic diseases, and lung cancer). [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] \u003cem\u003eI. bartlettii\u003c/em\u003e can degrade fucose, suggesting its indirect involvement in mucus degradation. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] As with \u003cem\u003ePeptostreptococcus\u003c/em\u003e, although the direct impact of \u003cem\u003eIntestinibacter\u003c/em\u003e on the development and responsiveness to the treatment of various diseases is uncertain, an increase in this bacterium may compromise the barrier mechanism in the intestinal mucosa, allowing pathogenic bacteria and toxins to infiltrate the bloodstream and trigger an excessive immune response. In KD patients who did not respond to the initial IVIG therapy, serum levels of proinflammatory cytokines, such as TNF-α, IL-1 and IL-6, were markedly elevated, compared with those who responded to the initial IVIG therapy. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] Variations in the gut microbiota may be associated with excessive inflammation in KD and determine responsiveness to the initial IVIG therapy. However, the association between variations in the gut microbiota and responsiveness to the treatment in KD has not proven in vitro and in vivo experiments. Further basic studies, such as those using animal model, are desired to clarify this association.\u003c/p\u003e\u003cp\u003eTwo previous studies focusing only on children with KD without prior antimicrobial agents suggested that variations in the gut microbiome may be involved in the development of KD. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] One study indicated that KD patients exhibited a significant reduction in fecal microbial diversity in the acute phase relative to healthy children, and that \u003cem\u003eEnterococcus\u003c/em\u003e, \u003cem\u003eAcinetobacter\u003c/em\u003e, \u003cem\u003eHelicobacter\u003c/em\u003e, \u003cem\u003eLactococcus\u003c/em\u003e, \u003cem\u003eStaphylococcus\u003c/em\u003e and \u003cem\u003eButyricimonas\u003c/em\u003e were significantly enriched in patients with acute KD in comparison to healthy children. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] Another study indicated that children with a history of KD have characteristic gut microbiota with complexity and that the \u003cem\u003eRuminococcus gnavus\u003c/em\u003e group was more abundant in the gut microbiota, while genus \u003cem\u003eBlautia\u003c/em\u003e was less abundant in children with a history of KD. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] Although variations in the gut microbiota of patients with KD have been observed in many studies, including our own, the predominant and non-predominant bacterial species differ in all studies. The etiology of KD remains uncertain and various environmental factors are speculated to be involved. The results of our study also suggest that patients with KD can be divided into two groups: those with reduced diversity of gut microbiota in comparison to healthy children and those with the opposite (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). Given this result, dysbiosis of the gut microbiota may not be involved in the development of KD in all patients. The relationship between the gut microbiota and the development of KD may require further investigation in a larger population.\u003c/p\u003e\u003cp\u003eThe present study was associated with several limitations. First, the study population was relatively small, which could have affected the accuracy of the statistical analysis. Second, the age distribution of KD patients with and without a response to initial IVIG therapy was different, although the difference was not statistically significant. The differences in the gut microbiota between the two groups may be affected by age. However, as \u003cem\u003ePeptostreptococcaceae\u003c/em\u003e is not isolated predominantly in infants, [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] we believe that age has little effect. Finally, we confirmed that the eligible children had not received antimicrobial or steroid therapy within 2 months before sample collection; however, their history of these therapies over 2 months prior to it was not confirmed. As antimicrobial and steroid therapies can cause long-term changes in the gut microbiota, [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] the results of this study may have been affected by such therapies, if any.\u003c/p\u003e\u003cp\u003eIn conclusion, \u003cem\u003ePeptostreptococcaceae\u003c/em\u003e was relatively abundant in KD patients who did not respond to initial IVIG therapy. Responsiveness to IVIG therapy in KD may be associated with variations in the gut microbiota. As the direct effect of \u003cem\u003ePeptostreptococcaceae\u003c/em\u003e on the treatment response in KD is uncertain, further studies are needed to perform a detailed analysis of the family \u003cem\u003ePeptostreptococcaceae\u003c/em\u003e.\u003c/p\u003e"},{"header":"MATERIALS and METHODS","content":"\u003cp\u003e\u003cstrong\u003eStudy population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis prospective study included 25 patients with KD who were admitted to the Department of Pediatrics at the Hospital of the University of Occupational and Environmental Health, Japan and Kitakyushu General Hospital from October 2019 to December 2023 and who were initially treated with high-dose IVIG (2 g/kg) and oral aspirin (30 mg/kg/day). The Diagnostic Guidelines for Kawasaki Disease (6th version) were used as the diagnostic criteria for KD. [32] No patients were diagnosed with incomplete KD. Patient clinical information was collected using a standardized case report form. IVIG was administered for 12\u0026ndash;24 hours in all patients. Patients whose body temperature was \u0026ge;37.5\u0026deg;C for \u0026ge;24 h after the initial IVIG therapy or who showed recurrent KD symptoms after initial defervescence were judged as resistant to the initial IVIG therapy. [32]\u003csup\u003e\u0026nbsp;\u003c/sup\u003eCAA was defined as an internal lumen diameter of \u0026ge;4 mm or local dilation (\u0026le;4 mm internal diameter in children \u0026lt;5 years of age and \u0026lt;1.5-fold that of an adjacent segment in children \u0026ge;5 years of age). [33] Nine age-matched healthy children served as healthy controls (HC). None of the eligible children were treated with antimicrobial agents or corticosteroids within 2 months of sample collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample collection and DNA extraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFecal samples were collected from the subjects to analyze the gut microbiota. Stools excreted by children or rectal swabs obtained by the insertion of a swab were collected. In patients with KD, samples were collected before initial treatment. The collected samples were stored at \u0026ndash;20\u0026deg;C\u0026nbsp;for bacterial gene analysis. DNA was extracted from fecal samples by vigorous shaking together with sodium dodecyl sulfate solution (final concentration, 3.0%) and glass beads as previously reported. [34]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePreparation of bacterial 16S rRNA gene library, its sequencing, and statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe bacterial 16S rRNA gene were amplified by PCR with the v3\u0026ndash;v4 hypervariable region primers (Forward: TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG, Reverse: GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC), and sequenced using a MiSeq System.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;(Illumina, San Diego, CA). The obtained raw sequence data were analyzed using QIIME2 (version 2021.4.0), [35] and then the amplicon sequence variants (ASV) were characterized by DADA2, [36]\u003csup\u003e\u0026nbsp;\u003c/sup\u003efollowing the removal of singletons and rare ASV (\u0026lt; 0.001%). Taxonomy was assigned to ASV using the q2-feature-classifier based on SILVA 138.1. [37] The statistical analysis was performed according to the method described in a previous report. [38] Briefly, the Kruskal\u0026ndash;Wallis test was applied to compare the differences in the \u0026alpha;-diversity of microorganisms. Differences in the relative presence of the microbiome were determined using a linear discriminant analysis (LDA) effect size (LEfSe). [39]\u0026nbsp;Regression analysis was conducted using Python (version 3.10.6) with the statsmodels library (version 0.14.4). The explanatory variables were standardized using the StandardScaler from sklearn.preprocessing (version 1.6.1). Logistic regression was then performed to fit the model, and standardized partial regression coefficients as well as adjusted\u0026nbsp;\u003cem\u003eP\u003c/em\u003e-values were calculated.\u0026nbsp;\u003cem\u003eP\u003c/em\u003e-value \u0026lt;0.05 were considered to be statistically significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Institutional Review Board of the University of Occupational and Environmental Health, Japan (UOEHCRB21-062), Kitakyushu General Hospital (H30-21), and H.U Group Holdings, Inc. (19-048). Informed consent was obtained from the parents of all patients. This study was conducted in accordance with the Declaration of Helsinki.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe appreciate the help of Dr. Brian Quinn (Japanese Medical Communication, Fukuoka, Japan) for editing the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMasato Ogawa, Daisuke Shimizu, Masahiro Ishii and Masumi Kojiro conceptualized the study, carried out the initial analysis of data for work, drafted the initial manuscript, approved the final version to be published and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Takayuki Hoshina designed the study, carried out the acquisition, analysis of data for the work, revised the work critically for important intellectual content, approved the final version to be published and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Takeru Nakabayashi, Kosei Tanaka and Masahiro Kamita carried out the acquisition and analysis of data for the work, revised the work critically for important intellectual content, approved the final version to be published and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Koichi Kusuhara designed the study, carried out the analysis and interpretation of data for the work, revised the work critically for important intellectual content, approved the final version to be published and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data presented in the study are deposited in the Sequence Read Archive (SRA) repository, accession number PRJNA1224998.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe declare that this research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur study was supported by JSPS KAKENHI grant number JP23K07324.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBurns, J.C., Glod\u0026eacute;, M.P. Kawasaki syndrome. \u003cem\u003eLancet.\u003c/em\u003e \u003cstrong\u003e364\u003c/strong\u003e, 533-4 (2004).\u003c/li\u003e\n \u003cli\u003eKato, H., Koike, S., Yamamoto, M., Ito, Y., Yano, E. Coronary aneurysms in infants and young children with acute febrile mucocutaneous lymph node syndrome. \u003cem\u003eJ Pediatr.\u003c/em\u003e \u003cstrong\u003e86,\u0026nbsp;\u003c/strong\u003e892-8. (1975).\u003c/li\u003e\n \u003cli\u003eMcCrindle, B.W., et al. Diagnosis, treatment, and long-term management of Kawasaki Disease: a scientific statement for health professionals from the American Heart Association. \u003cem\u003eCirculation.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e135\u003c/strong\u003e, e927-99. (2017).\u003c/li\u003e\n \u003cli\u003eUehara, R., et al. Analysis of potential risk factors associated with nonresponse to initial intravenous immunoglobulin treatment among Kawasaki disease patients in Japan. \u003cem\u003ePediatr Infect Dis J\u003c/em\u003e. \u003cstrong\u003e27\u003c/strong\u003e, 155-60. (2008).\u003c/li\u003e\n \u003cli\u003eOnouchi, Y., et al. ITPKC and CASP3 polymorphisms and risks for IVIG unresponsiveness and coronary artery lesion formation in Kawasaki disease. \u003cem\u003ePharmacogenomics J.\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 52-9. (2013).\u003c/li\u003e\n \u003cli\u003eShimizu, C., et al. Genetic variation in the SLC8A1 calcium signaling pathway is associated with susceptibility to Kawasaki Disease and coronary artery abnormalities. \u003cem\u003eCirc Cardiovasc Genet.\u003c/em\u003e \u003cstrong\u003e9,\u0026nbsp;\u003c/strong\u003e559-68. (2016).\u003c/li\u003e\n \u003cli\u003eShimizu, D., et al. Seasonality in clinical courses of Kawasaki disease.\u003cem\u003e\u0026nbsp;Arch Dis Child.\u003c/em\u003e \u003cstrong\u003e104,\u0026nbsp;\u003c/strong\u003e694-6. (2019).\u003c/li\u003e\n \u003cli\u003eShimizu, D., et al. The possible association between epidemics of hand-foot-and-mouth disease and responsiveness to immunoglobulin therapy in Kawasaki disease. \u003cem\u003eFront Pediatr.\u0026nbsp;\u003c/em\u003e\u003cstrong\u003e10\u003c/strong\u003e, 968857. (2022).\u003c/li\u003e\n \u003cli\u003eFujii, F., Egami, N., Inoue, M., Koga, H. Weather condition, air pollutants, and epidemics as factors that potentially influence the development of Kawasaki disease. \u003cem\u003eSci Total Environ.\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;741,\u003c/strong\u003e 140469. (2020).\u003c/li\u003e\n \u003cli\u003eMarutani, K., et al. Respiratory viral infections and Kawasaki disease: A molecular epidemiological analysis. \u003cem\u003eJ Microbiol Immunol Infect.\u003c/em\u003e \u003cstrong\u003e57,\u003c/strong\u003e 691-9 (2024).\u003c/li\u003e\n \u003cli\u003eKaneko, K., Akagawa, S., Akagawa, Y., Kimata, T., Tsuji, S. Our evolving understanding of Kawasaki disease pathogenesis: Role of the gut microbiota. \u003cem\u003eFront Immunol.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e11,\u003c/strong\u003e 1616. (2020).\u003c/li\u003e\n \u003cli\u003eLi, J., et al. An integrated catalog of reference genes in the human gut microbiome.\u003cem\u003e\u0026nbsp;Nat Biotechnol.\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e, 834-41. (2014).\u003c/li\u003e\n \u003cli\u003eMangiola, F., Ianiro, G., Franceschi, F., Fagiuoli, S., Gasbarrini, G., Gasbarrini, A. Gut microbiota in autism and mood disorders. \u003cem\u003eWorld J Gastroenterol.\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;22,\u0026nbsp;\u003c/strong\u003e361-8. (2016).\u003c/li\u003e\n \u003cli\u003eWang, P.X., Deng, X.R., Zhang, C.H., Yuan, H.J. Gut microbiota and metabolic syndrome. \u003cem\u003eChin Med J.\u003c/em\u003e (Engl)\u003cstrong\u003e\u0026nbsp;133,\u0026nbsp;\u003c/strong\u003e808-16. (2020).\u003c/li\u003e\n \u003cli\u003eQiu, P., Ishimoto, T., Fu, L., Zhang, J., Zhang, Z., Liu, Y. The Gut Microbiota in Inflammatory Bowel Disease. \u003cem\u003eFront Cell Infect Microbiol.\u003c/em\u003e \u003cstrong\u003e12,\u003c/strong\u003e 733992. (2022).\u003c/li\u003e\n \u003cli\u003eDuess, J.W., et al. Necrotizing enterocolitis, gut microbes, and sepsis. \u003cem\u003eGut Microbes\u003c/em\u003e. \u003cstrong\u003e15,\u0026nbsp;\u003c/strong\u003e222147. (2023)\u003c/li\u003e\n \u003cli\u003eKinumaki, A., Sekizuka, T., Hamada, H., Kato, K., Yamashita, A., Kuroda, M. Characterization of the gut microbiota of Kawasaki disease patients by metagenomic analysis. \u003cem\u003eFront Microbiol.\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e6,\u003c/strong\u003e 824. (2015).\u003c/li\u003e\n \u003cli\u003eChen, J., et al. Altered gut microbiota correlated with systemic inflammation in children with Kawasaki disease. \u003cem\u003eSci Rep.\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cstrong\u003e10,\u003c/strong\u003e 14525. (2020).\u003c/li\u003e\n \u003cli\u003eHu, X., et al. Landscape of intestinal microbiota in patients with IgA nephropathy, IgA vasculitis and Kawasaki disease. \u003cem\u003eFront Cell Infect Microbiol.\u003c/em\u003e \u003cstrong\u003e12,\u003c/strong\u003e 1061629. (2022).\u003c/li\u003e\n \u003cli\u003eTeramoto, Y., Akagawa, S., Hori, S.I., Tsuji, S., Higasa, K., Kaneko, K.\u0026nbsp;Dysbiosis of the gut microbiota as a susceptibility factor for Kawasaki disease.\u003cem\u003e\u0026nbsp;Front Immunol.\u003c/em\u003e \u003cstrong\u003e14,\u0026nbsp;\u003c/strong\u003e1268453. (2023).\u003c/li\u003e\n \u003cli\u003eHan, L., Liu, X., Lan, Y., Hua, Y., Fan, Z., Li, Y. Metagenomic analysis demonstrates distinct changes in the gut microbiome of Kawasaki diseases children.\u003cem\u003e\u0026nbsp;Front Immunol.\u0026nbsp;\u003c/em\u003e\u003cstrong\u003e15,\u0026nbsp;\u003c/strong\u003e1416185. (2024).\u003c/li\u003e\n \u003cli\u003eTakeshita, S., Kobayashi, I., Kawamura, Y., Tokutomi, T., Sekine, I. Characteristic role of intestinal microflora in Kawasaki disease. \u003cem\u003eActa Paediatr\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e91,\u0026nbsp;\u003c/strong\u003e783-8. (2001).\u003c/li\u003e\n \u003cli\u003eReading, N.C., Kasper, D.L. The starting lineup: key microbial players in intestinal immunity and homeostasis. \u003cem\u003eFront Microbiol.\u003c/em\u003e \u003cstrong\u003e2,\u0026nbsp;\u003c/strong\u003e148. (2011).\u003c/li\u003e\n \u003cli\u003eForbes, J.D., et al. A comparative study of the gut microbiota in immune-mediated inflammatory diseases\u0026mdash;does a common dysbiosis exist?\u003cem\u003e\u0026nbsp;Microbiome.\u003c/em\u003e \u003cstrong\u003e6,\u0026nbsp;\u003c/strong\u003e221. (2018).\u003c/li\u003e\n \u003cli\u003eWang, Y., et al. Association between gut microbiota and pan-dermatological diseases: a bidirectional Mendelian randomization research. \u003cem\u003eFront Cell Infect Microbiol.\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;14,\u0026nbsp;\u003c/strong\u003e1327083. (2024).\u003c/li\u003e\n \u003cli\u003eYang, W., Fan, X., Li, W., Chen, Y.\u0026nbsp;Causal influence of gut microbiota on small cell lung cancer: a Mendelian randomization study.\u003cem\u003e\u0026nbsp;Clin Respir J.\u003c/em\u003e \u003cstrong\u003e18,\u0026nbsp;\u003c/strong\u003ee13764. (2024).\u003c/li\u003e\n \u003cli\u003eSong, Y.L., Liu, C.X., McTeague, M., Summanen, P., Finegold, S.M. Clostridium bartlettii sp. nov., isolated from human faeces. \u003cem\u003eAnaerobe\u003c/em\u003e\u003cem\u003e.\u0026nbsp;\u003c/em\u003e\u003cstrong\u003e10,\u0026nbsp;\u003c/strong\u003e179-84. (2004).\u003c/li\u003e\n \u003cli\u003eWang, Y., et al. Do cytokines correlate with refractory Kawasaki disease in children?\u003cem\u003e\u0026nbsp;Clin Chim Acta.\u003c/em\u003e \u003cstrong\u003e506,\u003c/strong\u003e 222-7. (2020).\u003c/li\u003e\n \u003cli\u003eB\u0026auml;ckhed, F., et al. Dynamics and stabilization of the human gut microbiome during the first year of life. \u003cem\u003eCell Host Microbe.\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cstrong\u003e17,\u003c/strong\u003e 690-703. (2015).\u003c/li\u003e\n \u003cli\u003eWurm, J., Curtis, N., Zimmermann, P.\u0026nbsp;The effect of antibiotics on the intestinal microbiota in children\u0026mdash;a systematic review.\u003cem\u003e\u0026nbsp;Front Allergy.\u003c/em\u003e \u003cstrong\u003e5,\u0026nbsp;\u003c/strong\u003e1458688. (2024).\u003c/li\u003e\n \u003cli\u003eOkafuji, H., et al. Oral corticosteroids impair mucin production and alter the posttransplantation microbiota in the gut.\u003cem\u003e\u0026nbsp;Digestion.\u003c/em\u003e \u003cstrong\u003e103,\u0026nbsp;\u003c/strong\u003e269-86. (2022).\u003c/li\u003e\n \u003cli\u003eKobayashi, T., et al. Revision of diagnostic guidelines for Kawasaki disease (6th revised edition). \u003cem\u003ePediatr Int.\u003c/em\u003e \u003cstrong\u003e62,\u003c/strong\u003e 1135\u0026ndash;8. (2020).\u003c/li\u003e\n \u003cli\u003eFukazawa, R., et al. Japanese Circulation Society Joint Working Group. JCS/JSCS 2020 Guideline on Diagnosis and Management of Cardiovascular Sequelae in Kawasaki Disease. \u003cem\u003eCirc J.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e22,\u0026nbsp;\u003c/strong\u003e84: 1348-1407. (2020).\u003c/li\u003e\n \u003cli\u003eOgawa, M., Hoshina, T., Abushawish, A., Kusuhara K. \u0026nbsp;Evaluation of the usefulness of culture of induced sputum and the optimal timing for the collection of a good-quality sputum sample to identify causative pathogen of community-acquired pneumonia in young children: A prospective observational study.\u003cem\u003e\u0026nbsp;J Microbiol Immunol Infect.\u003c/em\u003e \u003cstrong\u003e56,\u0026nbsp;\u003c/strong\u003e1036-44. (2023).\u003c/li\u003e\n \u003cli\u003eBolyen, E., et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. \u003cem\u003eNat Biotechnol.\u0026nbsp;\u003c/em\u003e\u003cstrong\u003e37,\u0026nbsp;\u003c/strong\u003e852-7. (2019).\u003c/li\u003e\n \u003cli\u003eCallahan, B.J., McMurdie, P.J., Rosen, M.J., Han, A.W., Johnson, A.J., Holmes, S.P. DADA2: High-resolution sample inference from Illumina amplicon data. \u003cem\u003eNat Methods.\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;13,\u003c/strong\u003e 581-3. (2016).\u003c/li\u003e\n \u003cli\u003eQuast, C., et al.\u0026nbsp;The SILVA ribosomal RNA gene database project: improved data processing and web-based tools.\u003cem\u003e\u0026nbsp;Nucleic Acids Res.\u003c/em\u003e \u003cstrong\u003e41,\u0026nbsp;\u003c/strong\u003eD590-6. (2013).\u003c/li\u003e\n \u003cli\u003eHashimoto, Y., Okada, S., Yasuda, K., Kawagoe, M., Kajiya, M., Tsuga, K. Microbial differences between active and remission peri-implantitis. \u003cem\u003eSci Rep.\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e12,\u0026nbsp;\u003c/strong\u003e5284. (2022).\u003c/li\u003e\n \u003cli\u003eSegata, N., et al. Metagenomic biomarker discovery and explanation. \u003cem\u003eGenome Biol.\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cstrong\u003e12,\u003c/strong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003eR60. (2011).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. The demographic and clinical characteristics of eligible children\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"879\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 425px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003eKD patients\u003c/p\u003e\n \u003cp\u003en = 25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003eHealthy children\u003c/p\u003e\n \u003cp\u003en = 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 425px;\"\u003e\n \u003cp\u003eAge, months, median (range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e17 (5-57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e15 (5-59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 425px;\"\u003e\n \u003cp\u003eGender, n, (% male)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e15 (60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e3 (33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 425px;\"\u003e\n \u003cp\u003eIncomplete KD, n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 425px;\"\u003e\n \u003cp\u003eInitial treatments for KD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 425px;\"\u003e\n \u003cp\u003e\u0026nbsp;IVIG, n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e25 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 425px;\"\u003e\n \u003cp\u003e\u0026nbsp;Oral aspirin, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e25 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 425px;\"\u003e\n \u003cp\u003ePatients without response to initial IVIG therapy, n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e8 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 425px;\"\u003e\n \u003cp\u003eCoronary artery legions, n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eKD: Kawasaki disease, IVIG: intravenous immunoglobulin\u003c/p\u003e\n\u003cp\u003eTable 2. The comparison between patients with Kawasaki disease with and without response to initial IVIG therapy\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"879\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 454px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eIVIG responders\u003c/p\u003e\n \u003cp\u003en = 17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eIVIG non-responders\u003csup\u003e*1, 2\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;n = 8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 454px;\"\u003e\n \u003cp\u003eAge, months, median (range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e26 (5-57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e12 (5-50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 454px;\"\u003e\n \u003cp\u003eGender, n, (% male)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e9 (53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e6 (75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 454px;\"\u003e\n \u003cp\u003eDay of illness\u0026nbsp;at initial IVIG therapy, median (range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e5 (3-10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e3 (3-4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 454px;\"\u003e\n \u003cp\u003ePatients with coronary artery abnormalities, n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e*1\u003c/sup\u003e This category includes patients with resistance to the initial IVIG therapy that was defined with reference to the previous study (17).\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e*2\u003c/sup\u003e Five and three patients were treated with two doses of IVIG and two doses of IVIG and infliximab, respectively.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"dysbiosis, gut microbiota, intravenous immunoglobulin, Kawasaki disease, Peptostreptococcaceae","lastPublishedDoi":"10.21203/rs.3.rs-6989625/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6989625/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eVariations in gut microbiota may contribute to the pathogenesis and treatment response in Kawasaki disease (KD), but their role remains unclear. We analyzed fecal samples from 25 children with acute-phase KD and 9 age-matched healthy controls, none of whom had received antibiotics or steroids within two months of sampling. The gut microbiota was examined using 16S rRNA amplicon sequencing. Among the KD patients, 8 were refractory to initial intravenous immunoglobulin (IVIG) therapy. Although α-diversity tended to be lower in KD patients compared to healthy controls, no significant difference was observed. Similarly, α-diversity did not differ significantly between IVIG responders and non-responders. However, comparison of bacterial composition within the KD group revealed that \u003cem\u003ePeptostreptococcaceae\u003c/em\u003e was significantly more abundant in IVIG non-responders (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02). At the genus level, \u003cem\u003ePeptostreptococcus\u003c/em\u003e and \u003cem\u003eIntestinibacter\u003c/em\u003e were also more prevalent in the non-responder group. These findings suggest that specific gut microbiota, rather than overall diversity, may be associated with IVIG treatment resistance in KD. \u003cem\u003ePeptostreptococcaceae\u003c/em\u003e was relatively abundant in KD patients who did not respond to initial IVIG therapy. Responsiveness to IVIG therapy in KD may be associated with variations in the gut microbiota.\u003c/p\u003e","manuscriptTitle":"The association of gut microbiota with responsiveness to initial high-dose intravenous immunoglobulin therapy in Kawasaki disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-18 09:05:56","doi":"10.21203/rs.3.rs-6989625/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"57847d4f-1c5a-449e-a7d1-798350454cec","owner":[],"postedDate":"August 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":53249012,"name":"Health sciences/Diseases"},{"id":53249013,"name":"Biological sciences/Immunology"},{"id":53249014,"name":"Health sciences/Medical research"},{"id":53249015,"name":"Biological sciences/Microbiology"}],"tags":[],"updatedAt":"2025-08-19T04:08:15+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-18 09:05:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6989625","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6989625","identity":"rs-6989625","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}