P-1844. T cell Subtypes and DNA Methylome Dynamics Predict Infection after Kidney Transplantation
Authors: Hsu Fei-Man , Pickering Harry , Cappelletti Monica , Reed Elaine , Pellegrini Matteo , Schaenman Joanna M 
Published: January 2025

Abstract

Background
Infectious complications continue to cause significant morbidity and mortality after kidney transplantation (KTx), especially in older patients where immune senescence increases impact of immunosuppression. Given the importance of T cell function and of epigenetic regulation in infection vulnerability, we sought to evaluate whether the DNA methylome and T cell phenotypes could predict development of infection after KTx.

Principal component analysis (PCA) of CD4 and CD8 subsets associated with PBMC collected pre (green) compared with post (blue) transplantation, as well as T cell subsets associated with development of infection (red) versus freedom from infection (orange).

Methods
We evaluated PBMC from 91 KTx patients with samples collected before and then 3 months after transplantation. Deep flow cytometry was performed to delineate naïve, central memory (CM) effector memory (EM), and senescence subtypes including TIM3 and TIGIT in CD4 and CD8 T cells. Targeted bisulfite sequencing (TBS-seq) was applied to PBMC, utilizing probes directed at regions important for T cell maturation, activation, and control of viral infections.

Multivariate multiple linear regression model. A Spearman correlation matrix of actual-prediction traits. B Distribution of predicted values of ATG (left) and infection risk (right). C ROC curves of ATG (left) and infection risk (right).

Results
Transplantation had significant impact on T cell phenotypes, with increase in CD4 memory T cell subtypes CM TIM3+ (p&lt; 0.001) and EM CD127+ (p=0.001) and decrease in CD4 naïve T cells, especially after receipt of antithymocyte globulin (ATG) induction (p=0.008). CD4 T cell subtypes measured pre-transplant were also significantly associated with infection after KTx, including CM (p=0.014) and EM TIGIT (p&lt; 0.001). PCA analysis incorporating multiple maturation subtypes demonstrated ability to separate patients by transplant status and development of infection (Figure 1). Differential DNA methylation similarly demonstrated ability to predict infection: Multivariate linear regression identified significant association with infection post KTx with correction for age, sex, CMV serostatus, and ATG induction (Figure 2A). An integrated epigenetic risk score was associated with ATG induction and development of infection (Figure 2B), with AUC of 0.90 and 0.79, respectively (Figure 2C).

Conclusion
Immune markers based on T cell phenotype and differential methylation demonstrate the ability to predict infection after KTx. Pre- and post-transplant immune monitoring has the potential for patient risk stratification and individualization of immunosuppression to improve clinical outcomes by decreasing infection risk after transplantation.

Disclosures
Joanna M. Schaenman, MD, PhD, FAST, Eurofins Viracor: Honoraria|F2G: Grant/Research Support|MedCure: Advisor/Consultant|Moderna: Clinical trial support to institution|OneLegacy: Advisor/Consultant