Association of LILRB3 variants with kidney transplant failure in African Americans

Abstract

African American kidney transplant recipients exhibit a higher risk of graft failure than other racial and ethnic groups even after accounting for HLA mismatches and socioeconomic status, which suggests a role for other risk factors. Now, researchers have identified a cluster of four consecutive missense single-nucleotide polymorphisms (SNPs) within leukocyte immunoglobulin-like receptor B3 (LILRB3) that is enriched among African American individuals and represents a risk factor for death-censored graft loss and immune-related diseases.

Using this approach, the researchers uncovered a cluster of four linked missense SNPs in LILRB3 (termed LILRB3-4SNPs) that was predominantly detected in African American individuals and associated with poor graft outcomes. Further evaluation in other transplantation cohorts and biobank data revealed that LILRB3-4SNPs correlates with a heightened risk of graft loss and progression to kidney failure. These analyses also identified an association between LILRB3-4SNPs and immune-related pathologies, in line with the known role of LILRB3 as a negative regulator of immune responses. Multiomics analyses also demonstrated that transplant recipients with LILRB3-4SNPs demonstrate increased inflammation characterized by persistent activation of T cell and B cell signalling pathways, and monocyte ferroptosis, whereas functional studies in a macrophage cell line demonstrated that the pathogenic effects of LILRB3-4SNPs expression could be reversed by a ferroptosis inhibitor. “This work bridges genetic discovery with translational medicine, offering a pathway to address disparities in transplantation outcomes through precision therapies,” says Zhang. The researchers are now planning further studies to establish the LILRB3-4SNPs cluster as a genetic biomarker for the stratification of graft failure risk in African American transplant recipients and evaluate the efficacy of ferroptosis inhibitors in preclinical models.