Potential of Gut Microbe-Derived Extracellular Vesicles to Differentiate Inflammatory Bowel Disease Patients from Healthy Controls
1
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
Background/Aims: This study aimed to evaluate the potential of the stool microbiome and gut microbe-derived extracellular vesicles (EVs) to differentiate between patients with inflammatory bowel disease (IBD) and healthy controls, and to predict relapse in patients with IBD. Methods: Metagenomic profiling of the microbiome and bacterial EVs in stool samples of controls (n=110) and patients with IBD (n=110) was performed using 16S rRNA sequencing and then compared. Patients with IBD were divided into two enterotypes based on their microbiome, and the cumulative risk of relapse was evaluated. Results: There was a significant difference in the composition of the stool microbiome and gut microbe-derived EVs between patients with IBD and controls. The alpha diversity of the microbiome in patients with IBD was significantly lower than that in controls, while the beta diversity also differed significantly between the two groups. These findings were more prominent in gut microbe-derived EVs than in the stool microbiome. The survival curve tended to be different for enterotypes based on the gut microbe-derived EVs; however, this difference was not statistically significant (log-rank test, p=0.166). In the multivariable analysis, elevated fecal calprotectin (>250 mg/kg) was the only significant risk factor associated with relapse (adjusted hazard ratio, 3.147; 95% confidence interval, 1.545 to 6.408; p=0.002). Conclusions: Analysis of gut microbe-derived EVs is better at differentiating patients with IBD from healthy controls than stool microbiome analysis.
Abstract
Background/Aims: This study aimed to evaluate the potential of the stool microbiome and gut microbe-derived extracellular vesicles (EVs) to differentiate between patients with inflammatory bowel disease (IBD) and healthy controls, and to predict relapse in patients with IBD. Methods: Metagenomic profiling of the microbiome and bacterial EVs in stool samples of controls (n=110) and patients with IBD (n=110) was performed using 16S rRNA sequencing and then compared. Patients with IBD were divided into two enterotypes based on their microbiome, and the cumulative risk of relapse was evaluated. Results: There was a significant difference in the composition of the stool microbiome and gut microbe-derived EVs between patients with IBD and controls. The alpha diversity of the microbiome in patients with IBD was significantly lower than that in controls, while the beta diversity also differed significantly between the two groups. These findings were more prominent in gut microbe-derived EVs than in the stool microbiome. The survival curve tended to be different for enterotypes based on the gut microbe-derived EVs; however, this difference was not statistically significant (log-rank test, p=0.166). In the multivariable analysis, elevated fecal calprotectin (>250 mg/kg) was the only significant risk factor associated with relapse (adjusted hazard ratio, 3.147; 95% confidence interval, 1.545 to 6.408; p=0.002). Conclusions: Analysis of gut microbe-derived EVs is better at differentiating patients with IBD from healthy controls than stool microbiome analysis.
참고문헌 (41)
- 박상형, "Update on the epidemiology of inflammatory bowel disease in Asia: where are we now?", Intestinal research, 20(2), pp.159~164 (2022), 대한장연구학회[DOI]
- Ronald Keller, "Quality of life in inflammatory bowel diseases: it is not all about the bowel", Intestinal research, 19(1), pp.45~52 (2021), 대한장연구학회[DOI]
- Emiko Mizoguchi, "Recent updates on the basic mechanisms and pathogenesis of inflammatory bowel diseases in experimental animal models", Intestinal research, 18(2), pp.151~167 (2020), 대한장연구학회[DOI]
- Katsuhiro Arai, "Phenotypic characteristics of pediatric inflammatory bowel disease in Japan: results from a multicenter registry", Intestinal research, 18(4), pp.412~420 (2020), 대한장연구학회[DOI]
- 신승용, "Compositional changes in fecal microbiota associated with clinical phenotypes and prognosis in Korean patients with inflammatory bowel disease", Intestinal research, 21(1), pp.148~160 (2023), 대한장연구학회[DOI]
- Matsuoka K, "The gut microbiota and inflammatory bowel disease", Semin Immunopathol, 37, pp.47~55 (2015)
- Berry D, "Intestinal microbiota : a source of novel biomarkers in inflammatory bowel diseases?", Best Pract Res Clin Gastroenterol, 27, pp.47~58 (2013)
- Choi DS, "Proteomics of extracellular vesicles : exosomes and ectosomes", Mass Spectrom Rev, 34, pp.474~490 (2015)
- Chang X, "Extracellular vesicles with possible roles in gut intestinal tract homeostasis and IBD", Mediators Inflamm, 2020, pp.1945832~ (2020)
- Park J, "Fecal microbiota and gut microbe-derived extracellular vesicles in colorectal cancer", Front Oncol, 11, pp.650026~ (2021)
- Kim DJ, "Colorectal cancer diagnostic model utilizing metagenomic and metabolomic data of stool microbial extracellular vesicles", Sci Rep, 10, pp.2860~ (2020)
- Shin CM, "Validity and safety of IDJPL934in lower gastrointestinal symptom improvement", Sci Rep, 11, pp.13046~ (2021)
- Martin M, "Cutadapt removes adapter sequences from highthroughput sequencing reads", EMBnet J, 17, pp.10~12 (2011)
- Bokulich NA, "Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing", Nat Methods, 10, pp.57~59 (2013)
- Kwon S, "CASPER : context-aware scheme for paired-end reads from high-throughput amplicon sequencing", BMC Bioinformatics, 15(Suppl 9), pp.S10~ (2014)
- Quast C, "The SILVA ribosomal RNA gene database project : improved data processing and web-based tools", Nucleic Acids Res, 41, pp.D590~D596 (2013)
- Rognes T, "VSEARCH : a versatile open source tool for metagenomics", PeerJ, 4, pp.e2584~ (2016)
- Caporaso JG, "QIIME allows analysis of high-throughput community sequencing data", Nat Methods, 7, pp.335~336 (2010)
- Yoon SH, "Introducing EzBioCloud : a taxonomically united database of 16S rRNA gene sequences and whole-genome assemblies", Int J Syst Evol Microbiol, 67, pp.1613~1617 (2017)
- Kim KJ, "Phylogenetic tree-based microbiome association test", Bioinformatics, 36, pp.1000~1006 (2020)
- Koh H, "A powerful microbiome-based association test and a microbial taxa discovery framework for comprehensive association mapping", Microbiome, 5, pp.45~ (2017)
- Holmes I, "Dirichlet multinomial mixtures : generative models for microbial metagenomics", PLoS One, 7, pp.e30126~ (2012)
- Lo Presti A, "Fecal and mucosal microbiota profiling in irritable bowel syndrome and inflammatory bowel disease", Front Microbiol, 10, pp.1655~ (2019)
- Valter M, "Extracellular vesicles in inflammatory bowel disease : small particles, big players", J Crohns Colitis, 15, pp.499~510 (2021)
- Hiippala K, "The potential of gut commensals in reinforcing intestinal barrier function and alleviating inflammation", Nutrients, 10, pp.988~ (2018)
- Takeshita K, "A single species of clostridium subcluster XIVa decreased in ulcerative colitis patients", Inflamm Bowel Dis, 22, pp.2802~2810 (2016)
- Richard ML, "Mucosa-associated microbiota dysbiosis in colitis associated cancer", Gut Microbes, 9, pp.131~142 (2018)
- Sila S, "Altered gut microbiota is present in newly diagnosed pediatric patients with inflammatory bowel disease", J Pediatr Gastroenterol Nutr, 70, pp.497~502 (2020)
- Rajilić-Stojanović M, "Phylogenetic analysis of dysbiosis in ulcerative colitis during remission", Inflamm Bowel Dis, 19, pp.481~488 (2013)
- Hold GL, "Role of the gut microbiota in inflammatory bowel disease pathogenesis : what have we learnt in the past 10 years?", World J Gastroenterol, 20, pp.1192~1210 (2014)
- Guo X, "Gut microbiota is a potential biomarker in inflammatory bowel disease", Front Nutr, 8, pp.818902~ (2022)
- Braun T, "Individualized dynamics in the gut microbiota precede Crohn's disease flares", Am J Gastroenterol, 114, pp.1142~1151 (2019)
- Arumugam M, "Enterotypes of the human gut microbiome", Nature, 473, pp.174~180 (2011)
- Wu GD, "Linking long-term dietary patterns with gut microbial enterotypes", Science, 334, pp.105~108 (2011)
- Lewis JD, "A randomized trial comparing the specific carbohydrate diet to a Mediterranean diet in adults with Crohn’s disease", Gastroenterology, 161, pp.837~852 (2021)
- Precup G, "Gut Prevotella as a possible biomarker of diet and its eubiotic versus dysbiotic roles : a comprehensive literature review", Br J Nutr, 122, pp.131~140 (2019)
- Prosberg M, "The association between the gut microbiota and the inflammatory bowel disease activity : a systematic review and metaanalysis", Scand J Gastroenterol, 51, pp.1407~1415 (2016)
- Machiels K, "A decrease of the butyrate-producing species Roseburia hominis and Faecalibacterium prausnitzii defines dysbiosis in patients with ulcerative colitis", Gut, 63, pp.1275~1283 (2014)
- Galazzo G, "Faecal microbiota dynamics and their relation to disease course in Crohn's disease", J Crohns Colitis, 13, pp.1273~1282 (2019)
- Öhman L, "Fecal microbiota dynamics during disease activity and remission in newly diagnosed and established ulcerative colitis", Sci Rep, 11, pp.8641~ (2021)
- Jang SC, "In vivo kinetic biodistribution of nano-sized outer membrane vesicles derived from bacteria", Small, 11, pp.456~461 (2015)