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Open AccessJournal ArticleDOI

Sustained Drug Treatment Alters the Gut Microbiota in Rheumatoid Arthritis.

TLDR
Huang et al. as mentioned in this paper tracked the longitudinal changes in gut bacteria in 22 rheumatoid arthritis patients who were randomized into two groups and treated with Huayu-Qiangshen-Tongbi formula (HQT) plus methotrexate (MTX) or leflunomide (LEF) plus MTX.
Abstract
Several studies have investigated the causative role of the microbiome in the development of rheumatoid arthritis (RA), but changes in the gut microbiome in RA patients during drug treatment have been less well studied. Here, we tracked the longitudinal changes in gut bacteria in 22 RA patients who were randomized into two groups and treated with Huayu-Qiangshen-Tongbi formula (HQT) plus methotrexate (MTX) or leflunomide (LEF) plus MTX. There were differences in the gut microbiome between untreated (at baseline) RA patients and healthy controls, with 37 species being more abundant in the RA patients and 21 species (including Clostridium celatum) being less abundant. Regarding the functional analysis, vitamin K2 biosynthesis was associated with RA-enriched bacteria. Additionally, in RA patients, alterations in gut microbial species appeared to be associated with RA-related clinical indicators through changing various gut microbiome functional pathways. The clinical efficacy of the two treatments was further observed to be similar, but the response trends of RA-related clinical indices in the two treatment groups differed. For example, HQT treatment affected the erythrocyte sedimentation rate (ESR), while LEF treatment affected the C-reactive protein (CRP) level. Further, 11 species and 9 metabolic pathways significantly changed over time in the HQT group (including C. celatum, which increased), while only 4 species and 2 metabolic pathways significantly changed over time in the LEF group. In summary, we studied the alterations in the gut microbiome of RA patients being treated with HQT or LEF. The results provide useful information on the role of the gut microbiota in the pathogenesis of RA, and they also provide potentially effective directions for developing new RA treatments.

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Journal ArticleDOI

Gut microbiota and rheumatoid arthritis: From pathogenesis to novel therapeutic opportunities

TL;DR: The impact of gut dysbiosis in the pathogenesis of RA, the selection of gut microbiota-related biomarkers for diagnosing RA, and examples of cross-modulation between the gut microbiota and some drugs commonly used to treat RA are discussed.
Journal ArticleDOI

Gut Dysbiosis and Fecal Microbiota Transplantation in Autoimmune Diseases

TL;DR: This review aims to summarize the current knowledge about gut microbiota dysbiosis and the potential of FMT in studying the pathogeneses and therapies of autoimmune diseases and discusses the extraintestinal autoimmune pathologies with at least one published or ongoing FMT study in human or animal models.
Journal ArticleDOI

Intestinal microbiome–rheumatoid arthritis crosstalk: The therapeutic role of probiotics

TL;DR: Although strain-specific, probiotic supplementation as adjuvant therapy for the management of RA is very promising and warrants more research.
Journal ArticleDOI

Deleterious Effect of Air Pollution on Human Microbial Community and Bacterial Flora: A Short Review

TL;DR: In this paper , the authors have summarized and discussed recent studies' outcomes related to air pollution-driven microbiotas' dysbiosis (including oral, nasal, respiratory, gut, skin, and thyroid) and its potential multi-organ health risks.
Journal ArticleDOI

Effects of Metabolic Disorders in Immune Cells and Synoviocytes on the Development of Rheumatoid Arthritis

TL;DR: The connection between metabolism and inflammation in the context of rheumatoid arthritis is described and in detail the changes in metabolic processes and their subsequent immunomodulatory effects are considered.
References
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Journal ArticleDOI

Uncovering transcriptional regulation of metabolism by using metabolic network topology.

TL;DR: An algorithm that is based on hypothesis-driven data analysis to uncover the transcriptional regulatory architecture of metabolic networks is developed and finds that cells respond to perturbations by changing the expression pattern of several genes involved in the specific part of the metabolism in which a perturbation is introduced.
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