Integrative multi-omics and multi-trait analysis prioritizes regulatory mechanisms and genes for metabolic dysfunction-associated steatotic liver disease
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Updated: Nov 1, 2026
Optimized Analysis of In Vivo and In Vitro Hepatic Steatosis
Published on: March 11, 2017
Zhaode Feng1, Fangjun Chen1, Jiajia Xiao1
1Center for Mitochondrial Biology and Medicine, The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, 28 West Xianning Road, Xi'an 710049, China.
Background:
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a prevalent condition that progresses from simple steatosis to advanced fibrosis, significantly affecting liver function and systemic health. Despite its widespread impact, therapeutic options remain limited, highlighting the urgent need for comprehensive exploration to identify potential therapeutic targets.
Methods:
We developed an analysis pipeline anchored on liver gene expression, integrating differential meta-analysis of transcriptomic data across three MASLD stages, transcriptome-wide Mendelian randomization (MR), and transcriptome-wide association studies (TWAS) to identify candidate genes potentially involved in MASLD progression. We further prioritized these genes using a scoring system that incorporated gene expression-clinical phenotype correlation meta-analysis, proteome-wide association studies (PWAS), and external genetic data from the GWAS Catalog and ExPheWAS. In addition, single-nucleus RNA sequencing (snRNA-seq) analysis was performed to characterize the expression patterns of prioritized genes across liver cell types and disease stages.
Results:
By integrating transcriptomic, genetic, and phenotypic evidence, we prioritized 39 candidate regulators of MASLD. snRNA-seq analysis of liver cells from healthy to cirrhotic stages revealed stage- and cell-type-specific expression patterns of these genes. Through experimental validation in a lipid overload hepatocyte model, we confirmed a role for MLIP in lipid metabolism. To facilitate community access and data exploration, these data were organized and deposited into a publicly accessible interactive web portal (www.masldportal.net).
Conclusions:
Our integrative, liver expression-anchored multi-omics framework prioritized 39 candidate regulators of MASLD and highlighted MLIP as a functional modulator of hepatocellular lipid accumulation. These results provide a systematic foundation for understanding MASLD biology and for guiding future mechanistic and therapeutic studies.