#1779 Assessment of inflammation score in immune cells of atypical hemolytic uremic syndrome using single-cell sequencing analysis
Authors: Chen I-Ru , Chang Jan-gowth , Tu Siang-jyun , Chang Ya-Sian , Lai Ping-Chin , Huang Chiu-Ching 
Published: May 2024

Background and Aims

Atypical hemolytic uremic syndrome (aHUS) is a rare and life-threatening form of thrombotic microangiopathy (TMA) characterized by a complex interplay of genetic and immunological factors. Historically, research into aHUS has primarily focused on genes associated with complement activation and coagulation pathways. Our previous studies, employing single cell sequencing analysis, have revealed a significant association between aHUS and various immune cell types [1]. The clinical manifestation of aHUS is often initiated by infections, autoimmune diseases, or pregnancy, with many instances not reverting to a stable state even after the elimination of these triggering factors. Additionally, a significant portion of patients, despite lacking identifiable anomalies in complement or coagulation genes, respond positively to anti-complement therapy. This observation suggests a potential role for inflammation-related genes in the pathogenesis of aHUS. Given the extensive array of genes linked to inflammation, our study is designed to quantitatively assess inflammation gene expression, converting these measures into an inflammation score for each immune cell type in aHUS patients, their nuclear families, and healthy controls. This approach allows for a detailed comparison of disease activity variations within aHUS cases, aiming to deepen our understanding of aHUS and explore new avenues for therapeutic intervention.

Method

This study enrolled 13 aHUS patients, 3 nuclear families without aHUS, and 4 healthy subjects from Taiwan. Peripheral blood samples were collected for single-cell RNA sequencing analysis. aHUS patients were categorized into stable and unstable groups. The definition of stable disease activity is characterized by consistent TMA-related organ involvement and normal markers of hemolysis. Single-cell RNA sequencing data was processed using CellRanger and analyzed using the Seurat package in R. We obtained inflammatory genes from the Molecular Signatures Database, and we used the AddModuleScore function in Seurat to calculate inflammation score (IS).

Results

Our analysis demonstrated that non-switch memory B cells, classical monocytes, intermediate monocytes, non-classical monocytes, low-density basophils, naïve CD8 T cells, central memory CD8 T cells, terminal effector CD4 T cells, Th1 cells, Th17 cells, Th1/Th17 cells, and follicular helper T cells had the highest IS in aHUS patients, followed by aHUS patients' nuclear family members without aHUS and healthy control subjects. Furthermore, we observed that the IS of classical monocytes, non-switch memory B cells (Fig. 1), intermediate monocytes, non-classical monocytes, naïve CD8 T cells, central memory CD8 T cells, non-vd2 gd T cells, terminal effector CD4 T cells, Th17 cells, and follicular helper T cells were highest in aHUS patients with unstable disease activity, followed by aHUS patients with stable disease activity, aHUS patients' nuclear family members without aHUS, and healthy control subjects.

Conclusion

Our study underscores a pivotal link between elevated inflammation scores and aHUS severity aHUS. This finding not only emphasizes the critical role of inflammation in disease progression but also opens new avenues for therapeutic intervention, particularly in cases of unstable aHUS. By highlighting inflammation as a key factor in aHUS pathophysiology, our research offers fresh insights for disease management and future investigations. Moreover, exploring anti-inflammatory pathways presents promising therapeutic possibilities, potentially leading to improved patient outcomes and enhanced management strategies for aHUS.