Characterizing hub biomarkers for post-transplant renal fibrosis and unveiling their immunological functions through RNA sequencing and advanced machine learning techniques.

ABSTRACT:

Background

Kidney transplantation stands out as the most effective renal replacement therapy for patients grappling with end-stage renal disease. However, post-transplant renal fibrosis is a prevalent and irreversible consequence, imposing a substantial clinical burden. Unfortunately, the clinical landscape remains devoid of reliable biological markers for diagnosing post-transplant renal interstitial fibrosis.

Methods

We obtained transcriptome and single-cell sequencing datasets of patients with renal fibrosis from NCBI Gene Expression Omnibus (GEO). Subsequently, we employed Weighted Gene Co-Expression Network Analysis (WGCNA) to identify potential genes by integrating core modules and differential genes. Functional enrichment analysis was conducted to unveil the involveme

SUBMITTER: Niu X 

PROVIDER: S-EPMC10880303 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature