Integrative analysis of gut microbiota and fecal metabolites in metabolic associated fatty liver disease patients - Yang, Lidan; Dai, Yuzhao; He, He; Liu, Zhi; Liao, Shenling; Zhang, Yu; Liao, Ga; An, Zhenmei (Frontiers in Microbiology, 2022)
Objective Metabolic associated fatty liver disease (MAFLD) affects nearly a quarter of the world's population. Our study aimed to characterize the gut microbiome and overall changes in the fecal and serum metabolomes in MAFLD patients. Methods Thirty-two patients diagnosed with MAFLD and 30 healthy individuals （control group, CG）were included in this study, the basic clinical characteristics and laboratory test results including routine biochemistry, etc. were recorded for all, and their serum and fecal samples were collected. A portion of the fecal samples was subjected to 16S rDNA sequencing, and the other portion of the fecal samples and serum samples were subjected to non-targeted metabolomic detection based on liquid chromatography-mass spectrometry (LC-MS). Statistical analysis of clinical data was performed using SPSS software package version 25.0 (SPSS Inc., Chicago, IL). The analysis of 16S rDNA sequencing results was mainly performed by R software (V. 2.15.3), and the metabolomics data analysis was mainly performed by CD 3.1 software. Two-tailed P value < 0.05 was considered statistically significant. Results The 16S sequencing data suggested that the species richness and diversity of MAFLD patients were reduced compared with controls. At the phylum level, the relative abundance of Bacteroidota, Proteobacteria, and Fusobacteriota increased and Firmicutes decreased in MAFLD patients. At the genus level, the relative abundances of Prevotella, Bacteroides, Escherichia-Shigella, etc. increased. 2770 metabolites were detected in stool samples and 1245 metabolites were detected in serum samples. The proportion of differential lipid metabolites in serum (49%) was higher than that in feces (21%). There were 22 differential metabolites shared in feces and serum. And the association analysis indicated that LPC 18:0 was positively correlated with Christensenellaceae_R-7_group, Oscillospiraceae_UCG-002; neohesperidin was also positively correlated with Peptoniphilus, Phycicoccus, and Stomatobaculum. Conclusions Microbial sequencing data suggested decreased species richness and diversity and altered β-diversity in feces. Metabolomic analysis identified overall changes in fecal and serum metabolites dominated by lipid molecules. And the association analysis with gut microbes provided potentially pivotal gut microbiota-metabolite combinations in MAFLD patients, which might provide new clues for further research on the disease mechanism and the development of new diagnostic markers and treatments.