Multiomics Analysis Reveals the Impact of Microbiota on Host Metabolism in Hepatic Steatosis
Artikel i vetenskaplig tidskrift, 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.

systems biology

metabolomics

metabolic dysfunction-associated fatty liver disease

multiomics analysis

systems medicine

proteomics

gut and oral metagenomics

Författare

Mujdat Zeybel

University of Nottingham

Nottingham University Hospitals NHS Trust

Koç Üniversitesi

Muhammad Arif

Kungliga Tekniska Högskolan (KTH)

National Institute on Alcohol Abuse and Alcoholism

Xiangyu Li

Kungliga Tekniska Högskolan (KTH)

Ozlem Altay

Kungliga Tekniska Högskolan (KTH)

Hong Yang

Kungliga Tekniska Högskolan (KTH)

Mengnan Shi

Kungliga Tekniska Högskolan (KTH)

Murat Akyildiz

Koç Üniversitesi

Burcin Saglam

Koç Üniversitesi

Mehmet Gokhan Gonenli

Koç Üniversitesi

Buket Yigit

Koç Üniversitesi

Burge Ulukan

Koç Üniversitesi

Dilek Ural

Koç Üniversitesi

Saeed Shoaie

Kungliga Tekniska Högskolan (KTH)

King's College London

Hasan Turkez

Atatürk Üniversitesi

Jens B Nielsen

Chalmers, Biologi och bioteknik, Systembiologi

C. Zhang

Zhengzhou University

Kungliga Tekniska Högskolan (KTH)

Mathias Uhlen

Kungliga Tekniska Högskolan (KTH)

Jan Borén

Sahlgrenska universitetssjukhuset

Adil Mardinoglu

King's College London

Kungliga Tekniska Högskolan (KTH)

Advanced Science

2198-3844 (ISSN)

Vol. In Press

Ämneskategorier

Farmaceutisk vetenskap

Medicinsk genetik

Bioinformatik och systembiologi

DOI

10.1002/advs.202104373

Mer information

Senast uppdaterat

2022-02-22