Exploring Perturbations in Peripheral B Cell Memory Subpopulations Early after Kidney Transplantation Using Unsupervised Machine Learning.

Abstract

B cells have a significant role in transplantation. We examined the distribution of memory subpopulations (MBCs) and naïve B cell (NBCs) phenotypes in patients soon after kidney transplantation. Unsupervised machine learning cluster analysis is used to determine the association between the cellular phenotypes and renal function. MBC subpopulations and NBCs from 47 stable renal transplant recipients were characterized by flow cytometry just before (T0) and 6 months after (T6) transplantation. T0 and T6 measurements were compared, and clusters of patients with similar cellular phenotypic profiles at T6 were identified. Two clusters, clusters 1 and 2, were formed, and the glomerular filtration rate was estimated (eGFR) for these clusters. A significant increase in NBC frequency was observed between T0 and T6, with no statistically significant differences in the MBC subpopulations. Cluster 1 was characterized by a predominance of the NBC phenotype with a lower frequency of MBCs, whereas cluster 2 was characterized by a high frequency of MBCs and a lower frequency of NBCs. With regard to eGFR, cluster 1 showed a higher value compared to cluster 2. Transplanted kidney patients can be stratified into clusters based on the combination of heterogeneity of MBC phenotype, NBCs and eGFR using unsupervised machine learning.