Prediction of peripheral blood lymphocyte subpopulations after renal transplantation.

Abstract

Immune monitoring is essential for maintaining immune homeostasis after renal transplantation (RT). Peripheral blood lymphocyte subpopulations (PBLSs) are widely used biomarkers for immune monitoring, yet there is no established standard reference for PBLSs during immune reconstitution post-RT. PBLS data from stable recipients at various time points post-RT were collected. Binary and multiple linear regressions, along with a mixed-effect linear model, were used to analyze the correlations between PBLSs and clinical parameters. Predictive models for PBLS reference values were developed using Gradient Boosting Regressor, and the models' performance was also evaluated in infected recipients. A total of 1,736 tests from 494 stable recipients and 98 tests from 82 infected recipients were included. Age, transplant time, induction therapy, dialysis duration, serum creatinine, albumin, hemoglobin, and immunosuppressant drug concentration were identified as major factors influencing PBLSs. CD4⁺ and CD8⁺ T cells and NK cells increased rapidly, stabilizing within three months post-RT. In contrast, B cells peaked at around two weeks and gradually plateaued after four months. Both static and dynamic predictive models provided accurate reference values for PBLSs at any time post-RT, with the static model showing superior performance in distinguishing stable, infected and sepsis patients. Key factors influencing PBLS reconstitution after RT were identified. The predictive models accurately reflected PBLS reconstitution patterns and provided practical, personalized reference values for PBLSs, contributing to precision-guided care. The study was registered on Chinese Clinical Trial Registry (ChiCTR2300068666).