Current issue
Archive
Manuscripts accepted
About the Journal
Editorial office
Editorial board
Section Editors
Abstracting and indexing
Subscription
Contact
Ethical standards and procedures
Most read articles
Instructions for authors
Article Processing Charge (APC)
Regulations of paying article processing charge (APC)
PEDIATRICS / CLINICAL RESEARCH
Evaluation of microbiome composition combined with serum untargeted metabolomic profiling in newly diagnosed children with inflammatory bowel disease
1
Department of Pediatrics, Gastroenterology, Hepatology, Nutrition, Allergology and Pulmonology, Medical University of Bialystok, Poland
2
Metabolomics Laboratory, Clinical Research Centre, Medical University of Bialystok, Poland
3
Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, Poland
4
Department of Gastroenterology and Internal Medicine, Medical University of Bialystok, Poland
Submission date: 2024-04-24
Final revision date: 2024-06-17
Acceptance date: 2024-06-29
Online publication date: 2024-07-25
Corresponding author
Katarzyna Zdanowicz
Department of Pediatrics, Gastroenterology, Hepatology, Nutrition, Allergology and Pulmonology, Medical University of Bialystok, Poland
Department of Pediatrics, Gastroenterology, Hepatology, Nutrition, Allergology and Pulmonology, Medical University of Bialystok, Poland
KEYWORDS
TOPICS
ABSTRACT
Introduction:
The relationship between the intestinal microbiota, metabolites, and development of inflammatory bowel disease (IBD) is still being investigated. We aimed to assess whether the gut microbiome and serum metabolic profile are consistent with a diagnosis of Crohn’s disease (CD) or ulcerative colitis (UC) in children with newly diagnosed disease.
Material and methods:
Bacterial abundance in fecal samples was evaluated using a 16S rRNA DNA-based test in treatment-naive children with IBD (n = 18) and healthy controls (n = 10). Metabolic fingerprinting of serum samples of the same individuals was estimated using liquid chromatography coupled with mass spectrometry.
Results:
It was not possible to discriminate between CD and UC patients based on the gut microbiota profiles, but surprisingly, in the principal component analysis (PCA) model we observed a spontaneous separation of IBD patients into two groups, independently of IBD type. Then, serum metabolic profiles of these two microbiota-based groups of IBD patients were compared using orthogonal partial least squares discriminant analysis (OPLS-DA) modelling. Good quality models were obtained based on serum metabolomics data collected in positive and negative ion mode. In total, 12 metabolites significantly discriminating these groups were identified.
Conclusions:
Based on microbiota profiling, a grouping of IBD patients, unrelated to the IBD type, was noted. These two groups also have specific serum metabolic profiles. Further studies are needed to assess whether IBD patients, depending on their gut microbiota and serum metabolite composition, require different treatments and whether that impacts disease outcomes.
The relationship between the intestinal microbiota, metabolites, and development of inflammatory bowel disease (IBD) is still being investigated. We aimed to assess whether the gut microbiome and serum metabolic profile are consistent with a diagnosis of Crohn’s disease (CD) or ulcerative colitis (UC) in children with newly diagnosed disease.
Material and methods:
Bacterial abundance in fecal samples was evaluated using a 16S rRNA DNA-based test in treatment-naive children with IBD (n = 18) and healthy controls (n = 10). Metabolic fingerprinting of serum samples of the same individuals was estimated using liquid chromatography coupled with mass spectrometry.
Results:
It was not possible to discriminate between CD and UC patients based on the gut microbiota profiles, but surprisingly, in the principal component analysis (PCA) model we observed a spontaneous separation of IBD patients into two groups, independently of IBD type. Then, serum metabolic profiles of these two microbiota-based groups of IBD patients were compared using orthogonal partial least squares discriminant analysis (OPLS-DA) modelling. Good quality models were obtained based on serum metabolomics data collected in positive and negative ion mode. In total, 12 metabolites significantly discriminating these groups were identified.
Conclusions:
Based on microbiota profiling, a grouping of IBD patients, unrelated to the IBD type, was noted. These two groups also have specific serum metabolic profiles. Further studies are needed to assess whether IBD patients, depending on their gut microbiota and serum metabolite composition, require different treatments and whether that impacts disease outcomes.
REFERENCES (42)
1.
Sýkora J, Pomahačová R, Kreslová M, Cvalínová D, Štych P, Schwarz J. Current global trends in the incidence of pediatric-onset inflammatory bowel disease. World J Gastroenterol 2018; 24: 2741-63.
2.
Fitzgerald RS, Sanderson IR, Claesson MJ. Paediatric Inflammatory bowel disease and its relationship with the microbiome. Microb Ecol 2021; 82: 833-44.
3.
Balish E, Warner T. Enterococcus faecalis induces inflammatory bowel disease in interleukin-10 knockout mice. Am J Pathol 2002; 160: 2253-7.
4.
Ogunrinola GA, Oyewale JO, Oshamika OO, Olasehinde GI. The human microbiome and its impacts on health. Int J Microbiol 2020; 2020: 8045646.
5.
Henke MT, Kenny DJ, Cassilly CD, Vlamakis H, Xavier RJ, Clardy J. A member of the human gut microbiome associated with Crohn’s disease, produces an inflammatory polysaccharide. Proc Natl Acad Sci USA 2019; 116: 12672-7.
6.
Kowalska-Duplaga K, Gosiewski T, Kapusta P, et al. Differences in the intestinal microbiome of healthy children and patients with newly diagnosed Crohn’s disease. Sci Rep 2019; 9: 18880.
7.
Wang Y, Gao X, Ghozlane A, et al. Characteristics of faecal microbiota in paediatric Crohn’s disease and their dynamic changes during infliximab therapy. J Crohns Colitis 2018; 12: 337-46.
8.
Lopetuso LR, Petito V, Graziani C, et al. Gut microbiota in health, diverticular disease, irritable bowel syndrome, and inflammatory bowel diseases: time for microbial marker of gastrointestinal disorders. Dig Dis 2018; 36: 56-65.
9.
Khan I, Ullah N, Zha L, et al. Alteration of gut microbiota in inflammatory bowel disease (IBD): cause or consequence? IBD treatment targeting the gut microbiome. Pathogens 2019; 8: 126.
10.
Maukonen J, Kolho KL, Paasela M, et al. Altered fecal microbiota in paediatric inflammatory bowel disease. J Crohns Colitis 2015; 9: 1088-95.
11.
Hall AB, Yassour M, Sauk J, et al. A novel Ruminococcus gnavus clade enriched in inflammatory bowel disease patients. Genome Med 2017; 9: 103.
12.
Hansen R, Russell RK, Reiff C, et al. Microbiota of de-novo pediatric IBD: increased Faecalibacterium prausnitzii and reduced bacterial diversity in Crohn’s but not in ulcerative colitis. Am J Gastroenterol 2012; 107: 1913-22.
13.
Filimoniuk A, Daniluk U, Samczuk P, et al. Metabolomic profiling in children with inflammatory bowel disease. Adv Med Sci 2020; 65: 65-70.
14.
Chen R, Zheng J, Li L, et al. Metabolomics facilitate the personalized management in inflammatory bowel disease. Therap Adv Gastroenterol 2021; 14: 17562848211064489.
15.
Daniluk U, Daniluk J, Kucharski R, et al. Untargeted metabolomics and inflammatory markers profiling in children with Crohn’s disease and ulcerative colitis-a preliminary study. Inflamm Bowel Dis 2019; 25: 1120-8.
16.
Aldars-García L, Gisbert JP, Chaparro M. Metabolomics insights into inflammatory bowel disease: a comprehensive review. Pharmaceuticals (Basel) 2021; 14: 1190.
17.
Xu X, Ocansey DKW, Hang S, et al. The gut metagenomics and metabolomics signature in patients with inflammatory bowel disease. Gut Pathog 2022; 14: 26.
18.
Ning L, Zhou YL, Sun H, et al. Microbiome and metabolome features in inflammatory bowel disease via multi-omics integration analyses across cohorts. Nat Commun 2023; 14: 7135.
19.
Ma Y, Zhang Y, Xiang J, et al. Metagenome analysis of intestinal bacteria in healthy people, patients with inflammatory bowel disease and colorectal cancer. Front Cell Infect Microbiol 2021; 11: 599734.
20.
Iyer N, Corr SC. Gut microbial metabolite-mediated regulation of the intestinal barrier in the pathogenesis of inflammatory bowel disease. Nutrients 2021; 13: 4259.
21.
Lloyd-Price J, Arze C, Ananthakrishnan AN, et al. Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases. Nature 2019; 569: 655-62.
22.
Filimoniuk A, Blachnio-Zabielska A, Imierska M, Lebensztejn DM, Daniluk U. Sphingolipid analysis indicate lactosylceramide as a potential biomarker of inflammatory bowel disease in children. Biomolecules 2020; 10: 1083.
23.
Han S, Van Treuren W, Fischer CR, et al. A metabolomics pipeline for the mechanistic interrogation of the gut microbiome. Nature 2021; 595: 415-20.
24.
Dunn KA, Moore-Connors J, MacIntyre B, et al. Early changes in microbial community structure are associated with sustained remission after nutritional treatment of pediatric Crohn’s disease. Inflamm Bowel Dis 2016; 22: 2853-62.
25.
Levine A, Koletzko S, Turner D, et al. ESPGHAN revised porto criteria for the diagnosis of inflammatory bowel disease in children and adolescents. J Pediatr Gastroenterol Nutr 2014; 58: 795-806.
26.
Ciborowski M, Teul J, Martin-Ventura JL, Egido J, Barbas C. Metabolomics with LC-QTOF-MS permits the prediction of disease stage in aortic abdominal aneurysm based on plasma metabolic fingerprint. PLoS One 2012; 7: e31982.
27.
Jacobs JP, Goudarzi M, Singh N, et al. A disease-associated microbial and metabolomics state in relatives of pediatric inflammatory bowel disease patients. Cell Mol Gastroenterol Hepatol 2016; 2: 750-66.
28.
Franzosa EA, Sirota-Madi A, Avila-Pacheco J, et al. Gut microbiome structure and metabolic activity in inflammatory bowel disease. Nat Microbiol 2019; 4: 293-305.
29.
Andoh A, Imaeda H, Aomatsu T, et al. Comparison of the fecal microbiota profiles between ulcerative colitis and Crohn’s disease using terminal restriction fragment length polymorphism analysis. J Gastroenterol 2011; 46: 479-86.
30.
Saito Y, Sato T, Nomoto K, Tsuji H. Corrigendum: identification of phenol- and p-cresol-producing intestinal bacteria by using media supplemented with tyrosine and its metabolites. FEMS Microbiol Ecol 2019; 95: fiy125.
31.
Al Hinai EA, Kullamethee P, Rowland IR, Swann J, Walton GE, Commane DM. Modelling the role of microbial p-cresol in colorectal genotoxicity. Gut Microbes 2019; 10: 398-411.
32.
Yu X, Yang G, Jiang H, et al. Patchouli oil ameliorates acute colitis: a targeted metabolite analysis of 2,4,6-trinitrobenzenesulfonic acid-induced rats. Exp Ther Med 2017; 14: 1184-92.
33.
Lucafò M, Curci D, Franzin M, Decorti G, Stocco G. Inflammatory bowel disease and risk of colorectal cancer: an overview from pathophysiology to pharmacological prevention. Front Pharmacol 2021; 12: 772101.
34.
Meiners J, Palmieri V, Klopfleisch R, et al. Intestinal acid sphingomyelinase protects from severe pathogen-driven colitis. Front Immunol 2019; 10: 1386.
35.
Imdad A, Pandit NG, Zaman M, et al. Fecal transplantation for treatment of inflammatory bowel disease. Cochrane Database Syst Rev 2023; 4: CD012774.
36.
Wang Y, Gao X, Zhang X, et al. Microbial and metabolic features associated with outcome of infliximab therapy in pediatric Crohn’s disease. Gut Microbes 2021; 13: 1865708.
37.
Bushman FD, Conrad M, Ren Y, et al. Multi-omic analysis of the interaction between Clostridioides difficile infection and pediatric Inflammatory bowel disease. Cell Host Microbe 2020; 28: 422-33.e7.
38.
Weng YJ, Gan HY, Li X, et al. Correlation of diet, microbiota and metabolite networks in inflammatory bowel disease. J Dig Dis 2019; 20: 447-59.
39.
Ding NS, McDonald JAK, Perdones-Montero A, et al. Metabonomics and the gut microbiome associated with primary response to anti-TNF therapy in Crohn’s disease. J Crohns Colitis 2020; 14: 1090-102.
40.
Amoroso C, Perillo F, Strati F, Fantini MC, Caprioli F, Facciotti F. The role of gut microbiota biomodulators on mucosal immunity and intestinal inflammation. Cells 2020; 9: 1234.
41.
Higashiyama M, Hokaria R. New and emerging treatments for inflammatory bowel disease. Digestion 2023; 104: 74-81.
42.
Jarmakiewicz-Czaja S, Piątek D, Filip R. The impact of selected food additives on the gastrointestinal tract in the example of nonspecific inflammatory bowel diseases. Arch Med Sci 2021; 18: 1286-96.
Share
RELATED ARTICLE
| eISSN: | 1896-9151 |
| ISSN: | 1734-1922 |
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
