A Three-Gene Peripheral Blood Potential Diagnosis Signature for Acute Rejection in Renal Transplantation.

ABSTRACT: Background: Acute rejection (AR) remains a major issue that negatively impacts long-term allograft survival in renal transplantation. The current study aims to apply machine learning methods to develop a non-invasive diagnostic test for AR based on gene signature in peripheral blood. Methods: We collected blood gene expression profiles of 251 renal transplant patients with biopsy-proven renal status from three independent cohorts in the Gene Expression Omnibus database. After differential expression analysis and machine learning algorithms, selected biomarkers were applied to the least absolute shrinkage and selection operator (LASSO) logistic regression to construct a diagnostic model in the training cohort. The diagnostic ability of the model was further tested in validatio

SUBMITTER: Wang Y 

PROVIDER: S-EPMC8129004 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature