Common Transcriptional Program of Liver Fibrosis in Mouse Genetic Models and Humans.
Kaja Blagotinšek CokanŽiga UrlepMiha MoškonMiha MrazXiang Yi KongWinnie EskildDamjana RozmanPeter JuvanTadeja ReženPublished in: International journal of molecular sciences (2021)
Multifactorial metabolic diseases, such as non-alcoholic fatty liver disease, are a major burden to modern societies, and frequently present with no clearly defined molecular biomarkers. Herein we used system medicine approaches to decipher signatures of liver fibrosis in mouse models with malfunction in genes from unrelated biological pathways: cholesterol synthesis-Cyp51, notch signaling-Rbpj, nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling-Ikbkg, and unknown lysosomal pathway-Glmp. Enrichment analyses of Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome and TRANScription FACtor (TRANSFAC) databases complemented with genome-scale metabolic modeling revealed fibrotic signatures highly similar to liver pathologies in humans. The diverse genetic models of liver fibrosis exposed a common transcriptional program with activated estrogen receptor alpha (ERα) signaling, and a network of interactions between regulators of lipid metabolism and transcription factors from cancer pathways and the immune system. The novel hallmarks of fibrosis are downregulated lipid pathways, including fatty acid, bile acid, and steroid hormone metabolism. Moreover, distinct metabolic subtypes of liver fibrosis were proposed, supported by unique enrichment of transcription factors based on the type of insult, disease stage, or potentially, also sex. The discovered novel features of multifactorial liver fibrotic pathologies could aid also in improved stratification of other fibrosis related pathologies.
Keyphrases
- liver fibrosis
- transcription factor
- nuclear factor
- genome wide
- estrogen receptor
- genome wide identification
- toll like receptor
- fatty acid
- dna methylation
- dna binding
- copy number
- systemic sclerosis
- idiopathic pulmonary fibrosis
- quality improvement
- signaling pathway
- papillary thyroid
- squamous cell carcinoma
- gene expression
- bioinformatics analysis
- inflammatory response
- big data
- squamous cell
- artificial intelligence
- single cell
- machine learning
- single molecule
- breast cancer cells
- pi k akt
- cell proliferation