Multiomics Analysis Reveals the Impact of Microbiota on Host Metabolism in Hepatic Steatosis.
Mujdat ZeybelMuhammad ArifXiangyu LiOzlem AltayHong YangMengnan ShiMurat AkyildizBurcin SaglamMehmet Gokhan GonenliBuket YigitBurge UlukanDilek UralSaeed ShoaieHasan TurkezJens NielsenCheng ZhangMathias UhlénJan BorénAdil MardingluPublished in: Advanced science (Weinheim, Baden-Wurttemberg, Germany) (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.
Keyphrases
- electronic health record
- big data
- type diabetes
- end stage renal disease
- oxidative stress
- mass spectrometry
- cardiovascular disease
- metabolic syndrome
- chronic kidney disease
- newly diagnosed
- ejection fraction
- insulin resistance
- prognostic factors
- data analysis
- physical activity
- weight gain
- peritoneal dialysis
- high fat diet induced