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ALTERATION OF GUT MICROBIOME AND METABOLITES IN WILSON’S DISEASE

Date
May 18, 2024

Background
Recent studies revealed that patients with wilson’s disease (WD) have an imbalanced gut microbiota. It is still unclear how microbes and metabolites interactively promote the development of WD. This study aimed to provide a comprehensive description of the role of gut microbiome and serum metabolites in WD.
Methods
Fresh fecal and serum samples were collected from 17 healthy volunteers, and 19 WD patients. Metagenomics sequencing was performed following fecal DNA extraction. Non-targeted metabolomics analysis was used to measure serum metabolites. We further explore the correlations among gut microbes and the serum metabolites.
Results
Patients with WD had lower microbial species richness and altered β-diversity than healthy subjects. WD had enriched Escherichia_coli, Streptococcus_equinus compared to healthy subjects at the species level, and significant reductions of Faecalibacterium prausnitzii, Bacteroides uniformis, Akkermansia muciniphila, Bacteroides thetaiotaomicron. The WD patients had higher concentrations of 58 metabolites including 3beta,5beta-ketotriol, epinephrine, hippuric acid, m-cresol, 2-methylserine, 4-hydroxybenzoic acid, (S)-2-propylpiperidine, dihydrothymine, cholesterol than controls. There are 31 metabolites were enriched in controls than in the WD patients, such as L-gulose, L-gluconic acid, O-toluate, shikimic acid, lenticin, octadecanamide, pyridoxine. Subsequent pathway analysis suggested that dysfunction of energy metabolism, and dysregulated lipid metabolism were observed. Moreover, certain gut microbes were associated with serum metabolites.
Conclusions
Dysbiosis of gut microbiota is implicated in the pathogenesis of WD. Understanding the role of the gut microbiome and metabolites in WD may deepen our understanding of the pathogenesis of WD, and may help early identification of WD patients.
Figure 1: Altered gut microbiota diversity and composition in patients with WD and healthy controls. A: Taxonomic profiles of the dominant taxa of each group at the phylum level. Left: WD. Right: healthy controls (CT). B: Genus-level relative abundances of dominant taxa in each group. C: Comparison of the α diversity of gut microbiota between WD patients and healthy controls. <sup>*</sup>showed a significant difference between the two groups. D: Significant differential microbiota biomarkers were identified using the LEfSe algorithm.

Figure 1: Altered gut microbiota diversity and composition in patients with WD and healthy controls. A: Taxonomic profiles of the dominant taxa of each group at the phylum level. Left: WD. Right: healthy controls (CT). B: Genus-level relative abundances of dominant taxa in each group. C: Comparison of the α diversity of gut microbiota between WD patients and healthy controls. *showed a significant difference between the two groups. D: Significant differential microbiota biomarkers were identified using the LEfSe algorithm.

Figure 2: A: Significantly altered metabolites were determined using VIP score from pairwise PLD-DA analysis and Wilcoxon rank-sum test. B: Metabolomic pathway enrichment analysis using the significantly altered metabolites between WD and healthy controls (CT). C: Heatmap of correlation analysis between the gut microbiota and metabolites. <sup>* </sup>displays notable correlations were observed between microbial species and metabolites.

Figure 2: A: Significantly altered metabolites were determined using VIP score from pairwise PLD-DA analysis and Wilcoxon rank-sum test. B: Metabolomic pathway enrichment analysis using the significantly altered metabolites between WD and healthy controls (CT). C: Heatmap of correlation analysis between the gut microbiota and metabolites. * displays notable correlations were observed between microbial species and metabolites.

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