Multiomics Analysis Reveals the Impact of Microbiota on Host Metabolism in Hepatic Steatosis

• Published in: Advanced science Vol. 9; no. 11; pp. e2104373 - n/a
• Main Authors: Zeybel, Mujdat, Arif, Muhammad, Li, Xiangyu, Altay, Ozlem, Yang, Hong, Shi, Mengnan, Akyildiz, Murat, Saglam, Burcin, Gonenli, Mehmet Gokhan, Yigit, Buket, Ulukan, Burge, Ural, Dilek, Shoaie, Saeed, Turkez, Hasan, Nielsen, Jens, Zhang, Cheng, Uhlén, Mathias, Borén, Jan, Mardinoglu, Adil
• Format: Journal Article
• Language: English
• Published: Germany John Wiley & Sons, Inc 01.04.2022; John Wiley and Sons Inc; Wiley
• Subjects: Body mass index; Clinical Medicine; Datasets; Diabetes; Diseases; dysbiosis; Dysbiosis - genetics; fatty liver; Fatty Liver - genetics; Fatty liver disease; Gastrointestinal Microbiome; Gastrointestinal Microbiome - genetics; genetics; Gut and oral metagenomic; gut and oral metagenomics; Hepatic steatosis; human; Humans; intestine flora; Klinisk medicin; Liver diseases; Magnetic resonance imaging; metabolic dysfunction-associated fatty liver disease; Metabolic syndrome; Metabolism; metabolomics; Metagenomics; Microbiome; Microbiota; Microbiota - genetics; microflora; Molecular biology; Multiomic analyse; multiomics analysis; Obesity; Pathogenesis; Plasma; Proteomics; Regression analysis; Statistical analysis; System medicine; systems biology; systems medicine; systems biology; metabolic dysfunction-associated fatty liver disease; proteomics; metabolomics; systems medicine; gut and oral metagenomics; multiomics analysis
• ISSN: 2198-3844; 2198-3844
• DOI: 10.1002/advs.202104373

Metabolic dysfunction‐associated fatty liver disease (MAFLD) is a complex disease involving alterations in multiple biological processes regulated by the interactions between obesity, genetic background, and environmental factors including the microbiome. To decipher hepatic steatosis (HS) pathogenesis by excluding critical confounding factors including genetic variants and diabetes, 56 heterogenous MAFLD patients are characterized by generating multiomics data including oral and gut metagenomics as well as plasma metabolomics and inflammatory proteomics data. The dysbiosis in the oral and gut microbiome is explored and the host–microbiome interactions based on global metabolic and inflammatory processes are revealed. These multiomics data are integrated using the biological network and HS's key features are identified using multiomics data. HS is finally predicted using these key features and findings are validated in a follow‐up cohort, where 22 subjects with varying degree of HS are characterized. A comprehensive study to decipher hepatic steatosis (HS) by generating multiomics data including oral and gut metagenomics as well as plasma metabolomics and inflammatory proteomics data in a well‐characterized metabolic dysfunction‐associated fatty liver disease (MAFLD) cohort.