Metagenomic analysis of gut microbiome and spondyloarthropathy: A systematic review

Table 1 Study characteristics of the selected studies of Ankylosing Spondylitis

Ref.	Sudy design	Microbia	Method	Cohorts	Results	Conclusion
Zhou et al[26], 2020	Cohort study	AS-enriched species including Parabacteroides distasonis, Acidaminococcus fermentans Bacteroides coprophilus, Eubacterium siraeum, and Prevotella copri	Metagenomic shotgun sequencing of feceal matter. A microbial peptide's molecular mimicry was also proven using the ELISpot assay	85 AS subjects and 62 healthy controls	The study identified several bacterial species including Parabacteroides distasonis, Acidaminococcus fermentans Bacteroides coprophilus, Eubacterium siraeum, and Prevotella copri in AS patients. Pathway study showed that the gut microbiota of AS had higher levels of oxidative phosphorylation, LPS production, and glycosaminoglycan breakdown. The random forest model's selection of the AS gut's microbial signatures demonstrated great discrimination efficiency. Autoimmune indicators such as Bacteroides fragilis and type III secretion system were identified. In vitro research showed that a bacterial peptide from an AS-enriched species that mimics type II collagen boosted the number of IFNα production	The results show that untreated AS patients had altered gut microbiota with diagnostic possibility, and few AS-enriched species may act as molecular mimics to cause autoimmunity. Furthermore, several forms of inflammatory arthritis had a few similar microbiological fingerprints
Huang et al[33], 2020	Cohort study	Flavonifractor plautii, Oscillibacter, Parabacteroides distasonis and Bacteroides nordii	Illumina HiSeq 4000	113 patients and 37 controls	AS patients had enriched Flavonifractor plautii, Oscillibacter, Parabacteroides distasonis and Bacteroides nordii. F. plautii significantly enhanced in AS untreated patients. AS patients had more bacterial species in their faeces that were involved in glycan production and carbohydrate metabolism. Additionally, their bacterial profiles were less capable of degrading xenobiotics or producing and transporting vitamins	The therapy had an impact on the variation in the gut flora between the AS patients and HCs. The results obtained provide knowledge that may help with AS treatment advancements
Yin et al[31], 2020	Cohort study		Shotgun metagenomic sequencing of stools. All patients and healthy controls were genotyped using the Illumina CoreExome SNP microarray	127 AS patients and 123 healthy controls	The gut dysbiosis in AS previously reported was validated, and several significant types of bacteria and functional categories were substantially prevalent. The disturbed microbiome seen in untreated AS cases was restored to that of healthy controls after TNFi therapy. In the faeces of patients with AS, there was an enrichment of bacterial peptides that were identical to the epitopes that are presented by HLA-B27, indicating that either HLA-B27 Lacks to clear them or that they are responsible for the immunological responses. TNFi treatment restored the disturbed microbiome identified in untreated AS subjects indicating the efficacy of the treatment	These results highlight the critical function of the gut microbiota in the aetiology of AS and point to possible therapeutic and preventive approaches
Li et al[32], 2023	cohort study	Quimbyviridae, Gratiaviridae, Schitoviridae and Drexlerviridae	Metagenomic analysis of fecal matter	113 patients with AS and 37 healthy controls	The intestinal viral richness and overall viral structure of AS patients were significantly altered and decreased. Gratiaviridae and Quimbyviridae were more prevalent in AS patients than Schitoviridae and Drexlerviridae. 1004 viral operational taxonomic units that differed between patients and controls, including Myoviridae viruses in AS and Siphoviridae viruses in controls were identified. A clear distinction between virus infected host were identified between AS and controls. Furthermore, the frequency of some viral functional orthologs varied noticeably between the AS and controls, pointing to the functional significance of these viruses linked to AS. With an ideal AUC of 0.936, classification models were developed using gut viral profiles to differentiate AS patients from healthy controls, indicating the possible clinical utility of the gut virus in AS diagnosis	On metagenomic analysis, the study identified few virus signatures to differentiate AS patients. Predictive models show virus signatures can play significant role in clinical diagnosis of AS
Wen et al[34], 2017	cohort study	Increased abundance of Prevotella melaninogenica, Prevotella copri, Prevotella sp. C561, and decreased abundance of Bacteroides spp.; enrichment of Bifidobacterium, commonly used in probiotics	Metagenomic sequencing of gut microbial DNA from 211 Chinese individuals, with analysis of 23709 genes and 12 metagenomic species differentially abundant in AS patients	73 AS patients and 83 healthy controls in discovery cohort; 24 AS patients and 31 healthy controls in validation cohort	AS patients exhibited pronounced gut microbial dysbiosis compared to inflammatory bowel disease cases. Diagnostic algorithms were developed using gut microbial biomarkers	Gut microbiome alterations are associated with AS development, suggesting potential biomarkers for diagnosis and treatment strategies

AS: Ankylosing spondylitis; HLA: Human leucocyte antigen; SNP: Single nucleotide polymorphism; TNF: Tumor necrosis factor; LPS: Lipopolysaccharide; INF: Interferon.

Table 2 Risk of bias analysis of the selected studies

Ref.	Risk of bias
	Selection				Comparability	Outcome
	Is the exposed cohort truly representative of the population?	Was the nonexposed cohort chosen from the same group of people as the exposed cohort?	Did the determination of exposure originate from secure records?	Was the desired outcome missing at the beginning of the study?	Was comparability of cohorts done on the basis of the design or analysis?	Was the evaluation of the outcome based on a record linkage or an independent blind assessment?	Was the follow-up period long enough for results to materialise?	Was the cohort follow-up sufficient (subjects lost to follow-up < 20%)?
Zhou et al[26] 2020	+	+	+	-	+	+	+	+
Huang et al[33] 2020	+	+	-	+	+	+	+	+
Yin et al[31] 2020	+	+	+	-	+	+	+	+
Li et al[32], 2023	+	+	-	+	-	+	-	+
Wen et al[34], 2017	+	+	+	-	+	+	+	+

“+” indicates studies satisfying the domain item analysed; “-“ indicates studies lacking the domain item analysed.