Multiomics Analysis Reveals the Impact of Microbiota on Host Metabolism in Hepatic Steatosis
Journal article, 2022
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.
proteomics
multiomics analysis
gut and oral metagenomics
metabolomics
metabolic dysfunction-associated fatty liver disease
systems medicine
systems biology
Author
Mujdat Zeybel
Koç University
Nottingham University Hospitals NHS Trust
University of Nottingham
Muhammad Arif
NIAAA
Royal Institute of Technology (KTH)
Xiangyu Li
Royal Institute of Technology (KTH)
Ozlem Altay
Royal Institute of Technology (KTH)
Hong Yang
Royal Institute of Technology (KTH)
Mengnan Shi
Royal Institute of Technology (KTH)
Murat Akyildiz
Koç University
Burcin Saglam
Koç University
Mehmet Gokhan Gonenli
Koç University
Buket Yigit
Koç University
Burge Ulukan
Koç University
Dilek Ural
Koç University
Saeed Shoaie
Royal Institute of Technology (KTH)
King's College London
Hasan Turkez
Atatürk University
Jens B Nielsen
Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology
C. Zhang
Zhengzhou University
Royal Institute of Technology (KTH)
Mathias Uhlen
Royal Institute of Technology (KTH)
Jan Borén
Sahlgrenska University Hospital
Adil Mardinoglu
King's College London
Royal Institute of Technology (KTH)
Advanced Science
2198-3844 (ISSN) 21983844 (eISSN)
Vol. 9 11 2104373Subject Categories
Pharmaceutical Sciences
Medical Genetics
Bioinformatics and Systems Biology
DOI
10.1002/advs.202104373
PubMed
35128832