Gut microbiota in children with juvenile idiopathic arthritis: characteristics, biomarker identification, and usefulness in clinical prediction

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Background

Recent studies have suggested that the gut microbiota is altered in children with juvenile idiopathic arthritis (JIA). However, age, sex, and body mass index (BMI) were not matched in the previous studies, and the results are inconsistent. We conducted an age-, sex-, and BMI-matched cross-sectional study to characterize the gut microbiota in children with JIA, and evaluate its potential in clinical prediction.

Methods

A total of 40 patients with JIA and 42 healthy controls, ranging from 1 to 16 years, were enrolled in this study. Fecal samples were collected for 16S rDNA sequencing. The data were analyzed using QIIME software and R packages. Specifically, the random forest model was used to identify biomarkers, and the receiver operating characteristic curve and the decision curve analysis were used to evaluate model performance.

Results

A total of 39 fecal samples from patients with JIA, and 42 fecal samples from healthy controls were sequenced successfully. The Chao 1 and Shannon–Wiener index in the JIA group were significantly lower than those in the control group, and the Bray-Curtis dissimilarity also differed significantly between the two groups. The relative abundance of 4 genera, Anaerostipes, Dialister, Lachnospira, and Roseburia, decreased significantly in the JIA group compared to those in the control group. The 4 genera included microbes that produce short-chain fatty acids (SCFAs) and were negatively correlated with some rheumatic indices. Moreover, 12 genera were identified as potential biomarkers by using the nested cross-validation function of the random forest. A random forest model constructed using these genera was able to differentiate the patients with JIA from the healthy controls, and the area under the receiver operating characteristic curve was 0.7975. The decision curve analysis indicated that the model had usefulness in clinical practice.

Conclusions

The gut microbiota in patients with JIA is altered and characterized by a decreased abundance of 4 SCFA-producing genera. The decreases in the 4 genera correlated with more serious clinical indices. Twelve genera could be used as biomarkers and predictors in clinical practice.

Trial registration

The study is registered online at the Chinese Clinical Trial Registry on 11 May 2018 (registration number: ChiCTR1800016110).

Related collections

Most cited references 42

Record: found
Abstract: found
Article: not found

Reporting and Interpreting Decision Curve Analysis: A Guide for Investigators

Ben Van Calster, Laure Wynants, Jan F.M. Verbeek … (2018)

Context: Urologists regularly develop clinical risk prediction models to support clinical decisions. In contrast to traditional performance measures, decision curve analysis (DCA) can assess the utility of models for decision making. DCA plots net benefit (NB) at a range of clinically reasonable risk thresholds. Objective: To provide recommendations on interpreting and reporting DCA when evaluating prediction models. Evidence acquisition: We informally reviewed the urological literature to determine investigators’ understanding of DCA. To illustrate, we use data from 3616 patients to develop risk models for high-grade prostate cancer ( n = 313, 9%) to decide who should undergo a biopsy. The baseline model includes prostate-specific antigen and digital rectal examination; the extended model adds two predictors based on transrectal ultrasound (TRUS). Evidence synthesis: We explain risk thresholds, NB, default strategies (treat all, treat no one), and test tradeoff. To use DCA, first determine whether a model is superior to all other strategies across the range of reasonable risk thresholds. If so, that model appears to improve decisions irrespective of threshold. Second, consider if there are important extra costs to using the model. If so, obtain the test tradeoff to check whether the increase in NB versus the best other strategy is worth the additional cost. In our case study, addition of TRUS improved NB by 0.0114, equivalent to 1.1 more detected high-grade prostate cancers per 100 patients. Hence, adding TRUS would be worthwhile if we accept subjecting 88 patients to TRUS to find one additional high-grade prostate cancer or, alternatively, subjecting 10 patients to TRUS to avoid one unnecessary biopsy. Conclusions: The proposed guidelines can help researchers understand DCA and improve application and reporting. Patient summary: Decision curve analysis can identify risk models that can help us make better clinical decisions. We illustrate appropriate reporting and interpretation of decision curve analysis.

0 comments Cited 359 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

The short-chain fatty acid pentanoate suppresses autoimmunity by modulating the metabolic-epigenetic crosstalk in lymphocytes

Maik Luu, Sabine Pautz, Vanessa Kohl … (2019)

Short-chain fatty acids (SCFAs) have immunomodulatory effects, but the underlying mechanisms are not well understood. Here we show that pentanoate, a physiologically abundant SCFA, is a potent regulator of immunometabolism. Pentanoate induces IL-10 production in lymphocytes by reprogramming their metabolic activity towards elevated glucose oxidation. Mechanistically, this reprogramming is mediated by supplying additional pentanoate-originated acetyl-CoA for histone acetyltransferases, and by pentanoate-triggered enhancement of mTOR activity. In experimental mouse models of colitis and multiple sclerosis, pentanoate-induced regulatory B cells mediate protection from autoimmune pathology. Additionally, pentanoate shows a potent histone deacetylase-inhibitory activity in CD4+ T cells, thereby reducing their IL-17A production. In germ-free mice mono-colonized with segmented filamentous bacteria (SFB), pentanoate inhibits the generation of small-intestinal Th17 cells and ameliorates SFB-promoted inflammation in the central nervous system. Taken together, by enhancing IL-10 production and suppressing Th17 cells, the SCFA pentanoate might be of therapeutic relevance for inflammatory and autoimmune diseases.

0 comments Cited 166 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Evidence for Immune Relevance of Prevotella copri, a Gut Microbe, in Patients with Rheumatoid Arthritis.

Annalisa Pianta, Sheila Arvikar, Klemen Strle … (2017)

Prevotella copri, an intestinal microbe, may over-expand in stool samples of patients with new-onset rheumatoid arthritis (NORA), but it is not yet clear whether the organism has immune relevance in RA pathogenesis.

0 comments Cited 153 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Xianning Zhang: zhangxianning@zju.edu.cn

Meiping Lu:

ORCID: http://orcid.org/0000-0002-4930-9493

meipinglu@zju.edu.cn

Journal

Journal ID (nlm-ta): BMC Genomics

Journal ID (iso-abbrev): BMC Genomics

Title: BMC Genomics

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2164

Publication date (Electronic): 7 April 2020

Publication date PMC-release: 7 April 2020

Publication date Collection: 2020

Volume: 21

Electronic Location Identifier: 286

Affiliations

[1 ]ISNI 0000 0004 1759 700X, GRID grid.13402.34, Department of Rheumatology Immunology and Allergy, Children’s Hospital, , Zhejiang University School of Medicine, ; Hangzhou, Zhejiang Province China

[2 ]ISNI 0000 0004 0596 2989, GRID grid.418558.5, State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, ; Beijing, China

[3 ]Department of Scientific Research Management and Medical Education, Jinhua Hospital of Traditional Chinese Medicine, Jinhua, Zhejiang Province China

[4 ]ISNI 0000 0004 1764 2632, GRID grid.417384.d, Department of Paediatric Rheumatology, , The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, ; Wenzhou, Zhejiang Province China

[5 ]Nursing Department, Jiangnan Community Healthcare Center, Jinhua, Zhejiang Province China

[6 ]Department of Pediatrics, Wenling Maternal and Child Healthcare Hospital, Wenling, Zhejiang Province China

[7 ]ISNI 0000 0004 1759 700X, GRID grid.13402.34, Department of Pediatrics, Shaoxing People’s Hospital, Shaoxing Hospital, , Zhejiang University School of Medicine, ; Shaoxing, Zhejiang Province China

[8 ]Department of Rheumatology Immunology, Jinhua Municipal People’s Hospital, Jinhua, Zhejiang Province China

[9 ]ISNI 0000 0004 1759 700X, GRID grid.13402.34, Department of Genetics, Institute of Genetics, Institute of Cell Biology, , Zhejiang University School of Medicine, ; Hangzhou, Zhejiang Province China

Author information

Meiping Lu http://orcid.org/0000-0002-4930-9493

Article

Publisher ID: 6703

DOI: 10.1186/s12864-020-6703-0

PMC ID: 7137182

PubMed ID: 32264859

SO-VID: 09f0a9e1-8df3-425c-8c10-81bf0c14c42e

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 23 January 2020

Date accepted : 25 March 2020

Funding

Funded by: 1

Award ID: The Project of Young Talent in Medical Field in Zhejiang Province (2015-70)

Funded by: 2

Award ID: Zhejiang Provincial Natural Science Foundation (LGF19H100002)

Award Recipient : Meiping Lu

Custom metadata

ScienceOpen disciplines: Genetics

Keywords: juvenile idiopathic arthritis,microbiota,short-chain fatty acids,butyrate,propionate,biomarker,machine learning,random forest model,decision curve analysis

Data availability:

ScienceOpen disciplines: Genetics

Keywords: juvenile idiopathic arthritis, microbiota, short-chain fatty acids, butyrate, propionate, biomarker, machine learning, random forest model, decision curve analysis

Gut microbiota in children with juvenile idiopathic arthritis: characteristics, biomarker identification, and usefulness in clinical prediction

Read this article at

Abstract

Background

Methods

Results

Conclusions

Trial registration

Related collections

European Journal of Microbiology and Immunology

Most cited references 42

Reporting and Interpreting Decision Curve Analysis: A Guide for Investigators

The short-chain fatty acid pentanoate suppresses autoimmunity by modulating the metabolic-epigenetic crosstalk in lymphocytes

Evidence for Immune Relevance of Prevotella copri, a Gut Microbe, in Patients with Rheumatoid Arthritis.

Author and article information

Contributors

Journal

Affiliations

Author information

Article

History

Funding

Categories

Custom metadata

Comments

Comment on this article

Similar content 185

Cited by 24

Most referenced authors 1,935