Decoding the Microbiome’s Influence on Rheumatoid Arthritis
Abstract
:1. Introduction
2. Relevant Sections
2.1. Identification of the Literature
2.2. Study Characteristics
2.3. Relative Abundance
2.4. Quality Appraisal
3. Discussion
4. Conclusions and Future Directions
Author Contributions
Funding
Conflicts of Interest
References
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Author | Study Design | Study Subjects | Biospecimen | Microbiological Analysis | Findings |
---|---|---|---|---|---|
Chen et al. (2016) [21] | Cross-sectional | n = 40 RA n = 32 HCs | Fecal samples | 16S rDNA sequencing | Decrease in Faecalibacterium and expansion of Eggerthellales and Collinsella. |
Scher et al. 2013 [59] | Cross-sectional | n = 44 new onset RA n = 26 chronic RA n = 16 PsA n = 28 HCs | Fecal samples | 16S rDNA sequencing | Prevotella copri strongly correlated with disease in new onset RA patients. Increases in Prevotella abundance correlated with a reduction in Bacteroides and a loss of reportedly beneficial microbes in new onset RA subjects. |
Pianta et al. (2018) [60] | Observational | n = 127 RA | Fecal samples | 16S rDNA sequencing | Prevotella copri antibody responses were rarely found in patients with other rheumatic diseases or in HCs. |
Yu et al. (2021) [61] | Cross-sectional | n = 26 RA n = 26 HCs | Fecal samples | 16S rDNA sequencing | Klebsiella, Escherichia, Eisenbergiella, and Flavobacterium were more abundant in the RA patients, while Fusicatenibacter, Megamonas, and Enterococcus were more abundant in the HCs. |
Kishikawa et al. (2020) [62] | Cross-sectional | n = 82 RA n = 42 HCs | Fecal samples | 16S rDNA sequencing | Multiple species belonging to the Prevotella genus increased in the RA gut metagenome. |
Alpizar-Rodriguez et al. (2019) [63] | Cross-sectional | n = 50 HCs n = 83 pre-clinical RA | Fecal samples | Culture-independent microbiota analyses | The microbiota of individuals in “pre-clinical RA stages” was significantly altered compared with FDR controls. A significant enrichment of the bacterial family Prevotellaceae, particularly Prevotella spp., in the “pre-clinical RA” group (p = 0.04) was observed. |
Chen et al. (2021) [64] | Cross-sectional | n = 29 RA n = 30 HCs | Fecal samples | 16s rRNA sequencing | At the genus level, Bacteroides, Faecalibacterium, and some probiotics decreased in the RA group, while 97 genera, including Lactobacillus, Streptococcus, and Akkermansia, increased in the RA group. |
Diamanti et al. (2020) [65] | Cross-sectional | n = 30 RA with high adherence to Mediterranean diet, n = 30 RA with low adherence to Mediterranean diet | Fecal samples | 16s rRNA sequencing | A healthier gut microbiota composition was observed in the high adherence to the Mediterranean diet group, with a significant decrease in Lactobacillaceae and an almost complete absence of Prevotella copri with respect to the low/moderate adherence group. |
Sun et al. (2022) [66] | Cross-sectional | n = 42 RA n = 39 HCs | Fecal samples | MiSeq sequencing | The gut microbiota of RA patients was characterized by a decreased abundance of Pholiota, Scedosporium, and Trichosporon. |
Kitamura et al. (2022) [37] | Observational | n = 87 RA | Fecal samples | 16s rRNA sequencing | Total bacteria counts were correlated with endotoxin neutralizing capacity (p < 0.001) and inversely correlated with serum lipopolysaccharide (p < 0.001) and anti-Pg-LPS IgA antibody levels (p < 0.001). |
Reference | Methodological Quality | Directness of Evidence | Heterogeneity | Precision of Effect Estimates | Publication Bias | Level of Evidence | Recommendation for Use |
---|---|---|---|---|---|---|---|
Chen et al. (2016) [21] | Moderate | High | |||||
Scher et al. 2013 [59] | Moderate | High | |||||
Pianta et al. (2018) [60] | Moderate | Low+ | |||||
Yu et al. (2021) [61] | Moderate | High | |||||
Kishikawa et al. (2020) [62] | Moderate | High | |||||
Alpizar-Rodriguez et al. (2019) [63] | Moderate | Low+ | |||||
Chen et al. (2021) [64] | Moderate | High | |||||
Diamanti et al. (2020) [65] | Moderate | High | |||||
Sun et al. (2022) [66] | Moderate | Low+ | |||||
Kitamura et al. (2022) [37] | Moderate | Low+ |
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Coradduzza, D.; Bo, M.; Congiargiu, A.; Azara, E.; De Miglio, M.R.; Erre, G.L.; Carru, C. Decoding the Microbiome’s Influence on Rheumatoid Arthritis. Microorganisms 2023, 11, 2170. https://doi.org/10.3390/microorganisms11092170
Coradduzza D, Bo M, Congiargiu A, Azara E, De Miglio MR, Erre GL, Carru C. Decoding the Microbiome’s Influence on Rheumatoid Arthritis. Microorganisms. 2023; 11(9):2170. https://doi.org/10.3390/microorganisms11092170
Chicago/Turabian StyleCoradduzza, Donatella, Marco Bo, Antonella Congiargiu, Emanuela Azara, Maria Rosaria De Miglio, Gian Luca Erre, and Ciriaco Carru. 2023. "Decoding the Microbiome’s Influence on Rheumatoid Arthritis" Microorganisms 11, no. 9: 2170. https://doi.org/10.3390/microorganisms11092170
APA StyleCoradduzza, D., Bo, M., Congiargiu, A., Azara, E., De Miglio, M. R., Erre, G. L., & Carru, C. (2023). Decoding the Microbiome’s Influence on Rheumatoid Arthritis. Microorganisms, 11(9), 2170. https://doi.org/10.3390/microorganisms11092170