International journal of rheumatic diseases · 2024
Combined analysis of metabolomics and 16S rRNA sequencing for ankylosing spondylitis patients before and after secukinumab therapy.
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Sun Chao, Chao Yuyan, Xu Haojie, Yang Xinmeng, Pei Lijia, Xu Guixia, Wang Fei, Fan Xiaoyun, Tang Lin, Xie Changhao, Su Yin, Wang Xin
Аннотация
OBJECTIVE: Alterations in gut microbiota have been implicated in the pathogenesis of ankylosing spondylitis (AS), but the underlying mechanisms remain elusive. This study aims to investigate changes in gut microbiota and metabolites in individuals with AS before and after treatment with secukinumab, to identify the biological characteristics specific to AS patients and investigate the potential biomarkers, for optimizing therapeutic strategies more effectively.
METHODS: Fecal microbiome data were collected from 30 AS patients before and after secukinumab therapy and compared with data from 40 healthy controls (HC). Additionally, we analyzed the metabolic profile of both groups from plasma.
RESULTS: Findings indicated that the treatment-induced changes in the composition of several crucial bacterial groups, including Megamonas, Prevotella_9, Faecalibacterium, Roseburia, Bacteroides, and Agathobacter. Post-treatment, these groups exhibited a distribution more akin to that of the healthy populations compared with their pretreatment status. We identified three gut microbial taxa, namely Prevotellaceae_bacterium_Marseille_P2831, Prevotella_buccae, and Elusimicrobiota, as potential biomarkers for diagnosing individuals at a higher risk of developing AS and assessing disease outcomes. Plasma metabolomics analysis revealed 479 distinct metabolites and highlighted three disrupted metabolic pathways. Integration of microbiome and metabolomics datasets demonstrated a significant degree of correlation, underscoring the impact of the microbiome on metabolic activity.
CONCLUSION: Secukinumab can restore the balance of the gut microbiome and metabolites in AS patients, rendering them more similar to those found in the healthy population. The analysis of microbiome and metabolomics data have unveiled some candidate biomarkers capable of evaluating treatment efficacy.
METHODS: Fecal microbiome data were collected from 30 AS patients before and after secukinumab therapy and compared with data from 40 healthy controls (HC). Additionally, we analyzed the metabolic profile of both groups from plasma.
RESULTS: Findings indicated that the treatment-induced changes in the composition of several crucial bacterial groups, including Megamonas, Prevotella_9, Faecalibacterium, Roseburia, Bacteroides, and Agathobacter. Post-treatment, these groups exhibited a distribution more akin to that of the healthy populations compared with their pretreatment status. We identified three gut microbial taxa, namely Prevotellaceae_bacterium_Marseille_P2831, Prevotella_buccae, and Elusimicrobiota, as potential biomarkers for diagnosing individuals at a higher risk of developing AS and assessing disease outcomes. Plasma metabolomics analysis revealed 479 distinct metabolites and highlighted three disrupted metabolic pathways. Integration of microbiome and metabolomics datasets demonstrated a significant degree of correlation, underscoring the impact of the microbiome on metabolic activity.
CONCLUSION: Secukinumab can restore the balance of the gut microbiome and metabolites in AS patients, rendering them more similar to those found in the healthy population. The analysis of microbiome and metabolomics data have unveiled some candidate biomarkers capable of evaluating treatment efficacy.