Multiomics Analysis Reveals the Impact of Microbiota on Host Metabolism in Hepatic Steatosis. Issue 11 (7th February 2022)

• Record Type: Journal Article
• 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
• Is Part Of: Advanced science. Volume 9:Issue 11(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-02-07
• Subjects: gut and oral metagenomics -- metabolic dysfunction‐associated fatty liver disease -- metabolomics -- multiomics analysis -- proteomics -- systems biology -- systems medicine; Science -- Periodicals; 505
• DOI: 10.1002/advs.202104373
• Languages: English
• ISSNs: 2198-3844

Abstract

Abstract: 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. Abstract : 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.