Chrome Extension
WeChat Mini Program
Use on ChatGLM

Transcriptomic Analysis Identifies Novel Candidates in Cardiorenal Pathology Mediated by Chronic Peritoneal Dialysis

Scientific reports(2023)

Cited 0|Views0
No score
Abstract
Peritoneal dialysis (PD) is associated with increased cardiovascular (CV) risk. Studies of PD-related CV pathology in animal models are lacking despite the clinical importance. Here we introduce the phenotypic evaluation of a rat model of cardiorenal syndrome in response to chronic PD, complemented by a rich transcriptomic dataset detailing chronic PD-induced changes in left ventricle (LV) and kidney tissues. This study aims to determine how PD alters CV parameters and risk factors while identifying pathways for potential therapeutic targets. Sprague Dawley rats underwent Sham or 5/6 nephrectomy (5/6Nx) at 10 weeks of age. Six weeks later an abdominal dialysis catheter was placed in all rats before random assignment to Control or PD (3 daily 1-h exchanges) groups for 8 days. Renal and LV pathology and transcriptomic analysis was performed. The PD regimen reduced circulating levels of BUN in 5/6Nx, indicating dialysis efficacy. PD did not alter blood pressure or cardiovascular function in Sham or 5/6Nx rats, though it attenuated cardiac hypertrophy. Importantly PD increased serum triglycerides in 5/6Nx rats. Furthermore, transcriptomic analysis revealed that PD induced numerous changed transcripts involved with inflammatory pathways, including neutrophil activation and atherosclerosis signaling. We have adapted a uremic rat model of chronic PD. Chronic PD induced transcriptomic changes related to inflammatory signaling that occur independent of 5/6Nx and augmented circulating triglycerides and predicted atherosclerosis signaling in 5/6Nx LV tissues. The changes are indicative of increased CV risk due to PD and highlight several pathways for potential therapeutic targets.
More
Translated text
Key words
Kidney diseases,Renal replacement therapy,Transcriptomics,Science,Humanities and Social Sciences,multidisciplinary
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined