Dynamic co-expression modular network analysis in nonalcoholic fatty liver disease

Background Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease affecting people’s health worldwide. Exploring the potential biomarkers and dynamic networks during NAFLD progression is urgently important. Material and methods Differentially expressed genes (DEGs) in obesity, NAFL and NASH were screened from GSE126848 and GSE130970, respectively. Gene set enrichment analysis of DEGs was conducted to reveal the Gene Ontology (GO) biological process in each period. Dynamic molecular networks were constructed by DyNet to illustrate the common and distinct progression of health- or obesity-derived NAFLD. The dynamic co-expression modular analysis was carried out by CEMiTool to elucidate the key modulators, networks, and enriched pathways during NAFLD. Results A total of 453 DEGs were filtered from obesity, NAFL and NASH periods. Function annotation showed that health-NAFLD sequence was mainly associated with dysfunction of metabolic syndrome pathways, while obesity-NAFLD sequence exhibited dysregulation of Cell cycle and Cellular senescence pathways. Nine nodes including COL3A1, CXCL9, CYCS, CXCL10, THY1, COL1A2, SAA1, CDKN1A, and JUN in the dynamic networks were commonly identified in health- and obesity-derived NAFLD. Moreover, CYCS, whose role is unknown in NAFLD, possessed the highest correlation with NAFLD activity score, lobular inflammation grade, and the cytological ballooning grade. Dynamic co-expression modular analysis showed that module 4 was activated in NAFL and NASH, while module 3 was inhibited at NAFLD stages. Module 3 was negatively correlated with CXCL10, and module 4 was positively correlated with COL1A2 and THY1. Conclusion Dynamic network analysis and dynamic gene co-expression modular analysis identified a nine-gene signature as the potential key regulator in NAFLD progression, which provided comprehensive regulatory mechanisms underlying NAFLD progression.