Ontology highlight
ABSTRACT: Background
Acute cellular rejection (ACR) remains a major cause of morbidity after heart transplantation despite advances in immunosuppression. Whole genome transcriptomic profiling offers a systems-based, unbiased approach to elucidate the molecular mechanisms underlying ACR. However, noninvasive, longitudinal biomarker assessments capable of capturing the temporal dynamics of rejection biology remain scarce.Methods
RNA sequencing of peripheral blood from heart transplant recipients before, during, and after ACR was compared with nonrejection controls. Pathway analysis was conducted using differentially expressed genes (DEGs), and a machine learning approach was applied to assess gene-based prediction of ACR.Results
A total of 235 rejection-specific significant DEG
SUBMITTER: Ghazal R
PROVIDER: S-EPMC12818864 | biostudies-literature | 2026 Feb
REPOSITORIES: biostudies-literature