Portal hypertension as an independent risk factor for cirrhotic cardiomyopathy: An investigation on its mechanism based on bioinformatics analysis

Abstract Aims Despite being commonly found in patients with various etiologies of liver cirrhosis, cirrhotic cardiomyopathy (CCM) is often overlooked, and its mechanism remains unknown. This study aimed to illuminate the epidemiological data and risk factors of CCM and to explore its potential mechanisms through a bioinformatics analysis. Methods Clinical data were collected from January 2008 to December 2022 retrospectively, and patients were divided into the CCM and non‐CCM groups based on the criteria proposed by the 2005 World Congress of Gastroenterology. Independent risk factors for CCM were identified through a multivariate logistic regression analysis. CCM‐related genes were explored using the GeneCards database, and enrichment analysis was performed. Protein–protein interaction analysis was conducted using the Search Tool for the Retrieval of Interacting Genes (STRING) database, and hub genes were identified using Cytoscape software. The Transcriptional Regulatory Relationships Unraveled by Sentence‐based Text Mining (TRRUST) database was utilized to explore transcription factors (TFs), and a network regulatory diagram of TF‐gene pathways was constructed. Finally, potential drugs were predicted using the Drug Gene Interaction Database. Results A total of 965 patients with liver cirrhosis were included, among whom 563 (58.3%) were diagnosed with CCM. Portal hypertension (PHT) was identified as the only independent risk factor for CCM. The hub genes included IL6 , TNF, TGFB1 , IL1B , MMP9 , and IL10 . Enrichment analysis revealed that Forkhead box O (FoxO), mitogen‐activated protein kinase (MAPK), hypoxia‐inducible factor (HIF‐1), phosphoinositide 3‐kinase‐protein kinase B (PI3K‐AKT), interleukin (IL)‐17, tumor necrosis factor (TNF), vascular endothelial growth factor (VEGF), mammalian target of rapamycin (mTOR), Janus kinase/signal transducers and activators of transcription (JAK‐STAT), and transforming growth factor (TGF)‐beta pathways were enriched. TFs such as CEBPB , NFKB1 , STAT1 , STAT3 , and SP1 were also implicated. Potential drugs included pravastatin and atorvastatin. Conclusions The morbidity associated with CCM was high, and PHT was the only independent risk factor. The mechanism may be related to inflammation, and statins may hold therapeutic promise.