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Abstract
Background Lupus nephritis (LN) is characterized by considerable variability in its clinical manifestations and histopathological findings. Understanding the cellular and molecular mechanisms underlying this heterogeneity is key for the development of personalized treatments for LN.
Methods Droplet-based single-cell RNA-sequencing was applied to the analysis of dissociated kidney samples, collected from 155 LN patients with active kidney disease and 30 living donor controls as part of the Accelerating Medicines Partnership (AMP) in SLE consortium - a large- scale, multi-center study. 73,440 immune cells passing quality control were identified, spanning 134 cell subsets, representing various populations of tissue-resident and infiltrating leukocytes, as well as the activation states these cells assume as part of their disease-related activation and differentiation (figure 1). Principal component analysis (PCA) was used to characterize the variability in cell subset frequencies across the LN patients. Relationships between the resulting principal components (PCs) and the demographic, clinical and histopathological features of the patients were then assessed.
Results The main source of variability in immune cell subset frequencies, as represented by the first PC (PC1), reflected the balance between lymphocytes and monocytes/macrophages. Subsequent PCs represented the balance between B cells and T cells (PC2); the levels of cytotoxic T lymphocytes and NK cells, as compared to plasma cells (PC3); and the degree of macrophage differentiation to an alternatively activated phagocytic profile (PC4). PC1 was significantly correlated with the Chronicity index, such that patients with a higher percentage of lymphocytes compared to monocytes/macrophages had a higher Chronicity score (rho = -0.422, p-value < 0.001; figure 2A). A high degree of macrophage differentiation, as represented by PC4, was associated with a high Activity score (rho = 0.387, p-value < 0.001; figure 2B), and, in addition, with proliferative or mixed histology class, compared to pure membranous nephritis (p-value = 0.001, Kruskal–Wallis test). The ratio of B cells to T cells, as represented by PC2, demonstrated a positive correlation with the Activity index (rho = 0.311, p-value < 0.001). We further identified a significant correlation of PC1 with age; specifically, older patients had a higher relative frequency of lymphocytes compared to monocytes/macrophages (rho = -0.239, p-value = 0.003). Our analysis indicated that these relations are not driven by demographic, clinical and technical sources of variation in our data, including race, ethnicity, the mixture of different nephritic classes, and the inclusion of both first and later biopsies.
Conclusion Our work identifies distinct leukocyte populations active in different LN patients and, possibly, different stages of disease, and points to potential therapeutic targets, that must be validated in mechanistic studies. This approach may pave the way to personalized treatment of LN.
Single-cell RNA-sequencing was used to profile immune cells isolated from the kidneys of LN patients and healthy controls. Five main lineages of cells were identified, as shown in a Uniform Manifold Approximation and Projection (UMAP) plot: myeloid cells, T/NK cells, B cells, plasma cells and dividing cells. The cells of each lineage were further split into finer subsets of cells (color-coded).
PCA was used to characterize the variability in cell subset frequencies across LN patients. (A) The first PC, representing the balance between lymphoid cells and monocytes/macrophages, was found to be significantly correlated with the Chronicity index. (B) The fourth PC, representing the degree of macrophage differentiation, was found to be significantly correlated with the Activity index. Shown in each case are the Spearman correlation and its associated p-value.
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