Analysis of the Genetic Relationship between Atherosclerosis and Non-Alcoholic Fatty Liver Disease through Biological Interaction Networks

Abstract

Non-alcoholic fatty liver disease (NAFLD) seems to have some molecular links with atherosclerosis (ATH); however, the molecular pathways which connect both pathologies remain unexplored to date. The identification of common factors is of great interest to explore some therapeutic strategies to improve the outcomes for those affected patients. Differentially expressed genes (DEGs) for NAFLD and ATH were extracted from the GSE89632 and GSE100927 datasets, and common up- and downregulated DEGs were identified. Subsequently, a protein–protein interaction (PPI) network based on the common DEGs was performed. Functional modules were identified, and the hub genes were extracted. Then, a Gene Ontology (GO) and pathway analysis of common DEGs was performed. DEGs analysis in NAFLD and ATH showed 21 genes that were regulated similarly in both pathologies. The common DEGs with high centrality scores were ADAMTS1 and CEBPA which appeared to be down- and up-regulated in both disorders, respectively. For the analysis of functional modules, two modules were identified. The first one was oriented to post-translational protein modification, where ADAMTS1 and ADAMTS4 were identified, and the second one mainly related to the immune response, where CSF3 was identified. These factors could be key proteins with an important role in the NAFLD/ATH axis.

Bioinformatics-based identification and validation of hub genes associated with aging in patients with coronary artery disease

“…Together with PPARγ, CEBPA regulates the adipogenesis process and is involved in the sequence expression of adipocytespecific proteins [30][31][32][33][34][35][36]. CEBPA is upregulated in unstable plaques, and overexpression of CEBPA may contribute to the occurrence and development of atherosclerosis [37,38]. However, Bristol et al [39] observed that CEBPA and CEBPB bind the TNFR1 promoter, increase its expression through a positive feedback mechanism, and induce an increase in TNF expression.…”

High-Carbohydrate Diet Consumption Poses a More Severe Liver Cholesterol Deposition than a High-Fat and High-Calorie Diet in Mice

“…Il-1β and Il-6 are two important pro-inflammatory cytokines that amplify inflammation and sensitize hepatocytes to TNF-induced liver damage [43]. ADAMTS1, a metalloproteinase belonging to the ADAMS family, is involved in extracellular matrix (ECM) remodeling [44]. Several studies suggest a link between ADAMTS1 not only with the development of atherosclerotic plaques and ATH [45] but also with the ability to activate hepatic fibrotic TGF-b [46].…”

Linking Metallic Micronutrients and Toxic Xenobiotics to Atherosclerosis and Fatty Liver Disease—Postmortem ICP-MS Analysis of Selected Human Tissues

“…Pie charts were used to compare the proportions of elements, and to visualise their percentages (Figure 2). Elements such as 44 Ca, potassium ( 39 K), sodium ( 23 Na), 31 P, magnesium ( 24 Mg), zinc ( 66 Zn), and 56 Fe, which were present in the highest concentration, were removed from the graph to show the proportions of trace elements in the tissues examined. The series for both organs was split at 140 ppb.…”

“…A key role in the initiation of ATH is played by damage to the arterial endothelial cells by reactive oxygen and nitrogen species (ROS and RNS). These are generated by mitochondrial dysfunction in fatty hepatocytes and the vascular smooth muscle cell (VSMC) proliferation, induced by an overexpression of the coagulation factors angiotensin II [44,45], FII, FX, and FXII [46][47][48], and the production of pro-inflammatory IL-1β and TNF-α, under the influence of ox-LDL, as a consequence of atherogenic dyslipidaemia. Smaller, denser particles, sdLDLs, formed from very low-density lipoproteins (VLDLs), are also involved in the formation of atherogenic plaques.…”

“…In 2023, four genes common to NAFLD and ATH were selected, namely ADAMTS1, ADAMTS4, CEBPA, and CSF3 [44]. In this study, the association between cardiovascular disease and liver disease was analysed using bioinformatics tools, based on genetic data.…”