Single-cell transcriptomic analysis identifies an immune erythroid in paroxysmal nocturnal hemoglobinuria

Single-cell transcriptomic analysis identifies an immune erythroid in paroxysmal nocturnal hemoglobinuria | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Single-cell transcriptomic analysis identifies an immune erythroid in paroxysmal nocturnal hemoglobinuria Liyan Li, Junshu Wu, Hui Liu, Wei Wang, Chaomeng Wang, Zhaoyun Liu, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7363120/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Introduction: PNH is complement mediated intravascular hemolysis, the mechanism of intrinsic immune-like transcriptional programs within erythroid remains unclear. Methods Bone marrow samples were collected from patients with PNH and healthy controls. CD59-/+ cells were isolated for single-cell sequencing analysis, based on differential gene markers, erythroid cells were classified into six groups. Results Functional analysis revealed that groups C0, C1, C4, and C5 were primarily enriched in co-translational proteins that target the membrane, RNA catabolic processes, ribonucleoprotein complex biogenesis, and ATP metabolic process pathways. Groups C3 and C6 were associated with T-cell activation and antigen processing. Further investigation of groups C3 and C6 revealed that upregulated genes in the positive cells of PNH are enriched in immune-related pathways. Subsequent cross-enrichment analysis using immune and GEO databases identified five genes, namely AHNAK, CCL5, IL32, CD3E, and IL2RG, that may play a role in this process. Our analysis revealed a correlation between mRNA levels of IL32, IL2RG, CD3E, and CCL5 in the CD235a-positive cells of patients and their immunological markers. Conclusion A subset of erythroid cells with immune functions was identified in PNH, and gene upregulation was predominantly observed in CD59 + cells. We examined five genes which may play a role in this process and may offer novel insights for future investigations. Paroxysmal nocturnal hemoglobinuria erythroid cells immune scRNA-seq Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Paroxysmal nocturnal hemoglobinuria (PNH) is a clonal hematopoietic stem cell disorder characterized by hemolytic anemia, thrombosis, and bone marrow failure. 1 , 2 , 3 Affected cells become extremely susceptible to the impact of C3, C5, and the terminal pathway of the complement cascade due to the crucial role of CD55 in regulating the alternative pathway and C3 convertases. 4 – 6 Moreover, the formation of the membrane attack complex (MAC) is inhibited by CD59, further exacerbating the vulnerability of these cells. 1 , 7 CD55 and CD59 deficiency renders PNH erythrocytes susceptible to complement-mediated intravascular hemolysis 3 , 8 . Erythrocytes are simultaneously targeted by the complement system, resulting in the release and accumulation of free hemoglobin and iron in plasma. Subsequently, nitric oxide (NO) depletion and upregulation of pro-inflammatory cytokines occur. 5 , 9 , 10 Therefore, the role of erythrocytes in PNH remains crucial. Erythrocytes traditionally transport oxygen. 11 Recent studies have indicated that immature CD71 + erythroid cells exhibit immunomodulatory functions under various physiological and pathological conditions, thus expanding our understanding of erythrocytes. 11 , 12 Elahi 13 suggested that the diminished protective immune response in neonates could be attributed to the unique immunosuppressive properties of CD71 + erythrocytes, whereas immature CD71 + erythrocytes exhibit distinctive immune regulatory characteristics that play a role in immune development. Some studies have also reported that erythroid progenitor cells (EPCs) can be induced by tumors to exert immunosuppressive functions in the tumor microenvironment (TME), and EPCs can also secrete artemin in the spleen to promote tumor progression. 14 In recent years, the immunological functions of erythrocytes have garnered increasing attention. However, the precise mechanisms underlying the immune role of erythrocytes in diseases such as intrinsic immune-like transcriptional programs within erythroid remains unclear. Whole transcriptome sequencing identifying CXCR2 expression in PNH granulocytes 15 and transcriptomic analyses of T cells 16 have already been reported. Our study focuses on erythroid cells, we collected clonal bone marrow cells from patients with PNH and normal bone marrow cells to perform single-cell analyses and investigate erythroid development in patients with PNH. We identified a subset of erythroid cells exhibiting abnormal activity in the CD59 + cell compartment in patients with PNH, further elucidating the developmental stage characteristics of these immune erythroid cells and investigating their regulatory genes and immunoregulatory functions. 2. Methods 2.1 Patients and clinical samples This study was approved by the Ethics Committee of General Hospital of Tianjin Medical University. This study included four patients with classic PNH and four young healthy donors who were admitted to the Department of Hematology of Tianjin Medical University General Hospital between February 2023 and November 2024. Informed consent was obtained from all study participants and their families.The clinical characteristics of the 4 PNH patients are detailed in Table 1 . Table 1 Clinical characteristics of 4 PNH patients Characteristics Patients Total no. of patients 4 Gender M/F 2/2 Age Median (range) 38(21–55) Clinical classification n(%) classical PNH 4 PNH-AA 0 subclinical-PNH 0 Parameters at baseline HGB (g/L) 66.9(14.92) Ret (%) 12.18(6.74) WBC (*10 9 /L) 5.49(3.51) PLT (*10 9 /L) 125.00(64.53) TBIL (umol/L) 54.79(27.10) LDH (U/L) 1439(989.80) Granulocyte CD59 − (%) 88.24(19.30) Flaer-/CD14-(%) 87.30(26.28) Flaer-/CD24-(%) 64.85(21.42) n: number; PNH: Paroxysmal nocturnal hemoglobinuria; RET: Reticulocyte ratio; RBC: red blood cell; WBC: white blood cell; HGB: hemoglobin; PLT: Platelet; TBIL: total bilirubin; DBIL: direct bilirubin. LDH: lactate dehydrogenase. 2.2 Cell culture and sorting Bone marrow samples were collected from patients and controls, separated using density gradient centrifugation for 20 min, isolated from the mononuclear cell layer in the middle, washed, and then incubated with FITC CD59 (BD Biosciences) for 15 min at room temperature. CD59+/CD59- BM monocytes from patients were processed using an Aria II instrument (BD Biosciences). Followed the same procedure to collect patient bone marrow mononuclear cells, incubate with CD235a beads at 4 degrees in the dark for 20 minutes, separate positive and negative cells using a magnetic column.The purity of the sorted cells can reach 95%. 2.3 Single-Cell RNA Sequencing (scRNA-seq) Analysis Single-cell sequencing was conducted using the 10× Genomics platform. CellRanger software (version 5.0.1) facilitated the alignment of raw sequencing data to the human reference genome GRCh38 (2020) and extraction of the count matrix following default parameters. After eliminating low-quality cells, data normalization was performed, and the top 2000 variably expressed genes were identified using the FindVariableFeatures function within Seurat. Principal component analysis (PCA) was used to reduce the dimensionality of the scRNA-seq dataset. Cell clusters were defined by implementing the FindClusters function in Seurat, with the resolution parameter set to 0.3. Visualization of these clusters was executed via uniform manifold approximation and projection (UMAP) plots. To delve deeper into the alterations within erythroid lineage cells, the specific cell subset identified as erythroid lineage cells was extracted using the subset function within the Seurat software, followed by subsequent reclustering. This process entailed segregating the population of erythroid lineage cells from the primary dataset and subjecting it to a more detailed clustering analysis using the recluster feature in Seurat. We employed the Harmony package (version 1.0) for batch correction, thereby ensuring reliable comparative assessments spanning multiple datasets. 2.4 RNA extraction and real-time quantitative polymerase chain reaction (PCR) Total RNA was extracted from clinical samples. The FastKing RT kit (ABclonal; RK20433) was used to synthesize samples from total RNA. SuperReal PreMix Plus (SYBR Green) (YEASEN; 11184) was used for real-time quantitative PCR. Table 2 shows the PCR primers for AHNAK, CCL5, Interleukin 32 (IL32), CD3E, IL2RG, and GADPH genes. Melting and amplification curves were examined using Bio-Rad CFX 3.1. Table 2 The PCR primers for the genes Name Sequence (5′–3′) AHNAK Forward: TACCCTTCCTAAGGCTGACATT Reverse: TTGGACCCTTGAGTTTTGCAT CCL5 Forward: CCAGCAGTCGTCTTTGTCAC Reverse: CTCTGGGTTGGCACACACTT IL32 Forward: TGGCGGCTTATTATGAGGAGC Reverse: CTCGGCACCGTAATCCATCTC CD3E Forward: CCTCTTATCAGTTGGCGTTTGG Reverse: TTCAGTGACAGGTGATCCTCA IL2RG Forward: GTGCAGCCACTATCTATTCTCTG Reverse: GTGAAGTGTTAGGTTCTCTGGAG Gapdh Forward:CTGGGCTACACTGAGCACC Reverse:AAGTGGTCGTTGAGGGCAATG 2.5 Statistical analysis Statistical analyses were conducted using the GraphPad Prism software (version 9.0; GraphPad Software). Group comparisons were performed using the Student’s t-test and analysis of variance (ANOVA), with subsequent multiple comparisons using Tukey’s honest significant difference post-ANOVA. Two-way ANOVA with Sidak ’ s multiple comparison test was used to analyze comparisons among multiple groups. P values of less than 0.05 were considered statistically significant. 3. Results 3.1 An immune-responsive erythroid subgroup in PNH is recognized using scRNA-seq analysis. We conducted scRNA-seq of cells harvested from normal bone marrow mononuclear cells (CD59 + cells, P group) with PNH clones (CD59- cells, N group) in patients with PNH (n = 4), as compared to healthy controls (C group, n = 4) using the 10x Genomics platform. After completing data preprocessing and quality control procedures, a total of 129,925 cells were obtained. Dimensionality reduction and unsupervised clustering of the erythroid precursors yielded six major clusters (C0–C6) (Fig. 1 A). We identified specific markers associated with each cluster, including GYPA, MKI67, BNIP3L, IFIT1B, CD74, LYZ, S100A8, MIF, and FAM178B (Fig. 1 B, C; Supplementary Fig. 1). We found that the proportion of erythroid cells changed in various lineages in patients with PNH (Fig. 2 A). Significant differences primarily manifested in clusters 1, 3, 5, and 6. In cluster 3, the proportion in Group P was lower than that in the control group (p = 0.032), whereas no significant difference was noted between Group N and the control group (p = 0.426). In Cluster 6, the P group showed a significant increase compared to both the control and N groups (p = 0.0024 and p = 0.0029, respectively). To investigate the biological relevance of these clusters, we conducted a GO enrichment analysis using the signature genes of each cluster (Fig. 2 B). C0 was associated with co-translational proteins targeting the membrane and SRP-dependent co-translational proteins targeting the membrane and translational initiation (Fig. 2 C; Supplementary Fig. 2). C1 related mRNA catabolism, RNA catabolism(Fig. 2 C; Supplementary Fig. 3). C3 related neutrophil activation involved in T cell activation, immune response-activating cell (Fig. 2 C). C4 related ribonucleoprotein complex biogenesis and mitochondrial translational termination (Fig. 2 C; Supplementary Fig. 4). C5 was involved in oxidative phosphorylation and ATP metabolic processes (Fig. 2 C; Supplementary Fig. 5). C6 related antigen processing and leukocyte-mediated cytotoxicity (Fig. 2 C). Subsequently, we conducted KEGG analyses for each cluster. The C0 cluster pathway was mainly involved in the cell cycle, ferroptosis, apoptosis (Fig. 2 D). The C1 cluster pathway was mainly involved in protein processing in the endoplasmic reticulum(Fig. 2 D). The C3 cluster pathway was mainly involved in leukocyte transendothelial migration, chemokine signaling, IL17 signaling, and NF-kappa B signaling (Fig. 2 D). The C4 cluster pathway was mainly involved in nucleotide excision repair (Fig. 2 D). The C5 cluster pathway was mainly involved in ATP-dependent chromatin remodeling, nucleotide metabolism(Fig. 2 D). The C6 cluster pathway was mainly involved in allograft rejection, antigen processing and presentation (Fig. 2 D). These findings indicate that the cells in C5 exhibited higher maturation than those in C0, C1, and C4. C3 and C6 were uniquely enriched in terms related to immune activity, such as immune response, chemokine signaling pathway, cytokine-cytokine receptor interaction, and antigen processing and presentation (for example, LYZ , CD3D and CD74 ). Thus, C3 and C6 of erythroids were characterized by the expression of immune-related genes. 3.2 The unique signatures of C3 erythroid lineage cells. We further investigate the immune alterations in the erythroid lineage cells of PNH, differential gene enrichment analysis was initially conducted on C3 cells from normal bone marrow mononuclear cells (CD59 + cells, P group) with PNH clones (CD59- cells, N group) and normal controls (C group) (Fig. 3 A, B, C). In the comparison between the N and C groups, a total of 3,304 differentially expressed genes were identified, with upregulated genes including HBG1 and HBD and downregulated genes mainly consisting of IGLC2 and IGHG3. And comparing the N and P groups, 15 genes exhibited statistically significant differences, with DEFA3 and HIST1H1E being upregulated, and CCL4 and IGHA1 being downregulated. Comparing the P group to the C group, 17 genes showed statistically significant differences, with IL32 and GNLY being upregulated and DEFA3 and LRRC75A being downregulated. KEGG analyses (Fig. 3 D) of differentially expressed genes (DEGs) revealed that compared to group P, group N exhibited upregulation of pathways mainly enriched in the cell cycle and p53 signaling pathways, whereas downregulated pathways were predominantly enriched in ribosome biogenesis in eukaryotes, steroid hormone biosynthesis, cytosolic DNA-sensing pathway, and N-glycan biosynthesis. When comparing group P to group C, the upregulated pathways were primarily enriched in ribosome biogenesis and glycosyltransferases, whereas the downregulated pathways were predominantly enriched in neutrophil extracellular trap formation, transcriptional dysregulation in cancer, cytoskeleton proteins, and the NOD-like receptor signaling pathway. GO enrichment analyses of differentially expressed genes (DEGs) (Fig. 3 E, F) revealed that the upregulated processes in group N compared to those in group C were associated with cofactor catabolic processes, protein heterooligomerization, and antibiotic metabolic processes, whereas the downregulated processes were primarily linked to organ- or tissue-specific immune responses and tumor necrosis factor superfamily cytokine production. 3.3 The unique signatures of C6 erythroid lineage cells. Differential gene enrichment analyses were initially conducted on C6 cells (Fig. 4 A, B, C). A total of 820 differentially expressed genes were identified between the N and C groups, with upregulated genes including GNLY and HBG2, and downregulated genes mainly consisting of RPS29 and DEFA3. When comparing the N and P groups, 203 genes exhibited statistically significant differences, with BLVRB and HIST1H4C being upregulated, and TMSB4X and GZMK being downregulated. When comparing the P group to the C group, 417 genes showed statistical differences, with ARL4A and HBG1 being upregulated and RPS4Y1 and AZU1 being downregulated. Gene ontology (GO) and KEGG enrichment analyses of differentially expressed genes indicated that compared to group C, the upregulated genes in group N were mainly enriched in DNA methylation, DNA damage/telomere stress-induced senescence, pre-NOTCH transcription and translation, HDACs deacetylation histones, and PRC2 methylation of histones and DNA. In contrast, the upregulated genes in group C were predominantly enriched in the L13a-mediated translational silencing of ceruloplasmin expression, Formation of ATP by chemiosmotic coupling, and cell-extracellular matrix interactions (Fig. 4 D). In a comparison between groups N and P, the upregulated genes in group N were mainly enriched in oxidative phosphorylation, DNA replication, G2/M checkpoints, and ubiquitin-dependent degradation of cyclin D1, whereas the upregulated genes in group P were significantly enriched in hematopoietic cell lineage, T cell receptor signaling pathway, antigen processing and presentation, Th1 and Th2 cell differentiation, NF-kappa B signaling pathway, and cytokine signaling in immune system (Fig. 4 E). Furthermore, when comparing groups P and C, the upregulated genes in group P were predominantly enriched in allograft rejection, natural killer cell mediated cytotoxicity, antigen processing and presentation, and Th17 cell differentiation, whereas the upregulated genes in group C were mainly enriched in retrograde endocannabinoid signaling and DNA replication (Fig. 4 F). Therefore, it can be inferred that CD59 + cells of patients with PNH exhibit stronger immune activity in the C6 cell population. 3.4 There is a correlation between the screening of C6 cluster-specific genes and immunological markers in patients with PNH. To further investigate the immune erythroid cells in patients with PNH, we conducted a cross-enrichment analysis by comparing the upregulated genes in the P group of C6 using ImmPort Portal and identified 9 relevant genes: AHNAK, CCL5, CD3E, HLA-A, HLA-E, IL2RG, IL32, PTPRC, and TRIM22 (Fig. 5 A). In single-cell sequencing of the C6 group, the expression level trend of AHNAK was P > C > N (Fig. 5 B [1]). The expression levels of CCL5 of C6 group following the trend P > C > N (Fig. 5 B [2]), CD3E showing a trend of P > C > N (Fig. 5 B [3]), HLA-A trending towards P > N > C (Fig. 5 B [4]), HLA-E following the trend P > N > C (Fig. 5 B [5]), IL2RG showing a trend of P > C > N (Fig. 5 B [6]), IL32 trending in the order P > C > N (Fig. 5 B [7]), PTPRC following the trend P > N > C (Fig. 5 B [8]), and the expression levels of TRIM22 showing a trend of P > C > N (Fig. 5 B [9]). Subsequently, a comparative analysis was conducted using the GEO database GSE80062 on the RNA expression levels of the eight genes; no relevant data for HLA-E was present, leading to the selection of five genes for further investigation (Supplementary Fig. 6). These genes are identified as AHNAK, CCL5, IL32, CD3E, and IL2RG. We detected the expression of these gene in CD235a-positive cells of patients using PCR and statistical analyses with immune-related indicators (Supplementary Fig. 7). We found that the mRNA levels of IL32 and IL2RG were positively correlated with CD3 + CD4+/T cells; the mRNA content of CD3E was positively correlated with class-switched memory B cells/B cell%, and the mRNA content of CCL5 was positively correlated with CD19+%, CD19/Lym%, and Treg/CD3 + CD4 + cells (Fig. 5 C, p < 0.05). 4. Discussion In this study, we conducted a multi-omics analysis of CD59+/CD59- erythroid cells from the bone marrow of patients with PNH and normal control erythroid cells. We identified an immunological red cell subset involved in the development of PNH and identified key genes that potentially play a crucial role. This study provides valuable information to understand the mechanisms underlying erythroid abnormalities in PNH. In recent years, in addition to their role in oxygen transport, red blood cells (RBCs) have gained attention for their immunomodulatory functions. 17 The immunomodulatory role of RBCs was first discovered in 1953 when Nelson RA et al. 18 found that RBCs exhibit immune adhesion to microorganisms, triggering immune-specific reactions and enhancing phagocytosis. Subsequently, nucleated RBCs in the spleen mediate immune suppression. 19 , 20 Studies have shown that nucleated RBCs can inhibit first and second antibody-mediated reactions in the body. 13 Furthermore, a type of nucleated RBCs has been shown to suppress B cell proliferation in humoral immune responses. 21 Several studies have indicated that erythroid cells can impair innate and adaptive immune responses 22 against bacterial species including L. monocytogenes 23 and Bordetella pertussis. 24 , 25 Depletion of CD71 + erythroid cells in neonatal mice restored their immune response against various pathogens and reduced bacterial loads 26 . Decreased CD71 + nucleated RBCs in neonates enhanced the activation of immune cells and the production of TNF-a, IL17, and IFN-g. 23 – 25 Furthermore, studies have shown that the removal of CD71 + erythroid cells from the neonatal splenic cell population in mice eliminates their inhibitory effects on the development of immune responses. 23 CD71 + erythroid cells have been reported to play a role in tumor immunity. 27 Studies have indicated that CD71 + erythroid cells effectively inhibit antitumor immunity. The excessive presence of CD71 + cells leads to accelerated tumor growth, whereas anti-EPO or anti-CD71 antibodies can exert an anti-tumor effect, delaying tumor progression. 28 Additionally, erythroid cells can suppress the proliferation and differentiation of CD4 + T cells as well as inhibit the proliferation and cytotoxicity of CD8 + T cells. 29 In tumor-bearing mice, the absence of CD71 + erythroid cells can delay tumor growth and restore immune responses to levels comparable to those of tumor-free mice; 28 conversely, overexpression of CD71 + erythroid cells reduces T cell proliferation, as well as the production of TNF-a and IFN-g. 29 Therefore, we conducted an enrichment analysis of differentially expressed genes in each cell group. The analysis revealed that in addition to erythroid cells with functions in transcription, translation, and oxygen transport, there were two other groups of erythroid cells associated with T cell activation and antigen presentation. These findings were consistent with those of previous studies. PNH is characterized by dysregulation of the complement system. 30 Owing to the deficiency in CD55 and CD59, RBCs in PNH are unable to regulate the activation of complements on their surfaces, ultimately leading to complement-mediated intravascular hemolysis. 31 CD55 (DAF) and CD59 (MIRL) act as natural inhibitors of the complement system. Their deficiency in RBCs results in uncontrolled activation of the complement system, leading to chronic hemolysis, platelet activation, thrombosis, and various systemic manifestations. 32 In cases of PNH, the deficiency CD59 in RBCs causes unregulated MAC formation, instigating a complement-dependent process of intravascular hemolysis. 33 , 34 Therefore, we posit that aberrations in the complement and immune systems in PNH have a profound impact on erythrocytes. Consequently, we conducted an in-depth analysis of the differences between PNH CD59+/CD59- cells and normal controls in the C3 and C6 erythroid clusters associated with immunity. Discrepancies among the three groups in the C3 cluster primarily focused on cell cycle and transcription, leading us to concentrate on the C6 group. In our investigation, we observed that in the C6 cluster, the upregulated genes in the positive group, compared with those in the negative and control groups, were predominantly enriched in immune-related pathways. Hence, we contend that positive cells in the C6 group of erythrocytes in PNH play a dominant role in erythroid cell immunity. To further explore the underlying causes of this phenomenon, we conducted a comparative analysis using the immune and PNH databases and identified five genes, AHNAK, CCL5, IL32, CD3E, and IL2RG, which may play crucial roles in this process. AHNAK was initially identified as a large tumor-associated nuclear protein in the neuroblastoma cell type. 44 Over the past decade, increasing evidence has shown its involvement in muscle regeneration, tumor suppression, cellular structure, and calcium homeostasis. 35 , 36 CCL5/CCR5 are well-recognized for their roles in promoting inflammatory responses and facilitating the adhesion and migration of different T cell subsets during immune reactions. Furthermore, recent studies have implicated the interaction between CCL5 and CCR5 in various pathological processes, including inflammation, chronic diseases, cancer, and COVID-19 infection. 37 , 38 IL32 is a cytokine involved in inflammation and cancer development. It is selectively expressed by activated T and NK cells. Early studies indicated that IL32 plays a role in regulating cell growth, metabolism, and immune modulation, thus contributing to pathophysiological regulation or protection against inflammatory diseases. 39 , 40 CD3E is a component of the TCR-CD3 complex found on the surface of T lymphocytes and plays a crucial role in adaptive immune responses17. Upon antigen presentation, T-cell receptor (TCR) activation triggers the signaling mediated by CD3D, CD3E, CD3G, and CD3Z across the cell membrane 41 . IL2RG is a common subunit of various IL receptors. IL15RA may play a role in stimulating the phagocytic activity of neutrophils via IL15. 42 , 43 In this study, we found that the mRNA levels of IL32 and IL2RG were positively correlated with CD3 + CD4+/T cells, whereas the mRNA content of CD3E was positively correlated with class-switched memory B cells/B cell%; The mRNA content of CCL5 was positively correlated with CD19+%, CD19/Lym%, and Treg/CD3 + CD4 + cells (Fig. 5 C). Therefore, we speculated that these genes may play a role in the immunity of PNH erythroid cells, providing new insights for future research. PNH is a rare disease, according to statistics, the global incidence rate is 1–2/1 million people/year, and the prevalence rate is 10–20/1 million. Therefore, our research includes a limited number of PNH patients. At present, our research team is trying to expand the research queue to ensure the robustness and repeatability of the research results, 5. Conclusion In conclusion, through single-cell sequencing analysis of red cell fractions in the bone marrow mononuclear cells of patients with PNH with CD59+/CD59- or normal controls, we identified a subset of red cells with immune functions. Furthermore, we observed enhanced immune functions in CD59 + cells in patients with PNH within this subset. By examining the potentially involved genes, our study offers a novel direction and perspective on the immune mechanisms of the erythroid lineage in PNH. Declarations Ethics approval and consent to participate All patients provided written informed consent before enrollment. This study protocol was reviewed and approved by the Ethics Committee of General Hospital of Tianjin Medical University, approval number ZYY-IRB-SOP-016(F)-002-04. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Funding Statement This work was supported by the National Natural Science Foundation Project (grant no.82270142), Tianjin Municipal Natural Science Foundation (grant no. 24ZGSSSS00050), Tianjin Science and Technology Planning Project (grant no. 24ZXGZSY00090), and Tianjin Municipal Health Commission Project (grant no. TJWJ2023XK003). Author contributions Liyan Li and Junshu Wu performed the research and wrote the paper, Hui Liu, Wei Wang, Chaomeng Wang, Zhaoyun Liu, Yingying Chen and Honglei Wang contributed essential reagents and help analysed the data, Rong Fu designed the research study. Data availability statement All data generated or analyzed during this study are included in this article, but these research data are not publicly available on ethical grounds. Further enquiries can be directed to the corresponding author. References Hill A, DeZern AE, Kinoshita T, Brodsky RA. Paroxysmal nocturnal haemoglobinuria. Nat Rev Dis Primers. 2017;3:17028. Kinoshita T, Fujita M. Thematic Review Series: Glycosylphosphatidylinositol (GPI) Anchors: Biochemistry and Cell Biology Biosynthesis of GPI-anchored proteins: special emphasis on GPI lipid remodeling. J Lipid Res. 2016;57(1):6–24. Luzzatto L. PNH phenotypes and their genesis. Br J Haematol. 2020;189(5):802–5. Navenot JM, Muller JY, Blanchard D. Investigation of the survival of paroxysmal nocturnal hemoglobinuria red cells through the immunophenotyping of reticulocytes. Transfusion. 1998;38(4):337–42. Rosse WF. The Life-span of Complement-sensitive and -insensitive Red Cells in Paroxysmal Nocturnal Hemoglobinuria. Blood. 1971;37(5):556–62. Ferreira VP, Pangburn MK. Factor H–mediated cell surface protection from complement is critical for the survival of PNH erythrocytes. Blood. 2007;110(6):2190–2. Jalink M, de Boer ECW, Evers D, Havinga MQ, Vos JMI, Zeerlede S, et al. Halting targeted and collateral damage to red blood cells by the complement system. Semin Immunopathol. 2021;43(6):799–816. Brodsky RA. How I treat paroxysmal nocturnal hemoglobinuria.Blood. 2021;137(10):1304–9. Freitas Leal JK, Preijers F, Brock R, Adjobo-Hermans M, Bosman G. Red Blood Cell Homeostasis and Altered Vesicle Formation in Patients With Paroxysmal Nocturnal Hemoglobinuria. Front Physiol. 2019;10. Styliani K, Gavriilaki E, Miari A, Anthi, Travlou4, Kyriakou E, et al. Renal involvement in paroxysmal nocturnal hemoglobinuria: an update on clinical features, pathophysiology and treatment. Hematology. 2018;23(8):558–66. Xu C, He J, Wang H, Zhang Y, Wu J, Zhao L, et al. Single-cell transcriptomic analysis identifies an immune-prone population in erythroid precursors during human ontogenesis. Nat Immunol. 2022;23(7):1109–20. Elahi S. Neglected Cells: Immunomodulatory Roles of CD71 + Erythroid Cells. Trends Immunol. 2019;40(3):181–5. Elahi S. New insight into an old concept: role of immature erythroid cells in immune pathogenesis of neonatal infection. Front Immunol. 2014;5:376. Mo WT, Huang CF, Sun ZJ. Erythroid progenitor cell modulates cancer immunity: Insights and implications. Biochimica et Biophysica Acta (BBA) - Reviews on Cancer. 2024;1879(6):189209. Kohei Hosokawa S, Kajigaya K, Keyvanfar W, Qiao Y, Xie A, Biancotto, et al. Whole transcriptome sequencing identifies increased CXCR2 expression in PNH granulocytes. Br J Haematol. 2017;177(1):136–41. Kohei Hosokawa S, Kajigaya K, Keyvanfar W, Qiao Y, Xie, Danielle M, Townsley, et al. T Cell Transcriptomes from Paroxysmal Nocturnal Hemoglobinuria Patients Reveal Novel Signaling Pathways. J Immunol. 2017;199(2):477–88. Niu C, Zhang J. Immunoregulation role of the erythroid cells. Front Immunol. 2024;15:1466669. NELSON RA Jr.. The immune-adherence phenomenon; an immunologically specific reaction between microorganisms and erythrocytes leading to enhanced phagocytosis. Science. 1953;118(3077):733–7. Pavia CS, Stites DP. Immunosuppressive activity of murine newborn spleen cells. I. Selective inhibition of in vitro lymphocyte activation. Cell Immunol. 1979;42(1):48–60. de Macario E, Macario AJ. Immunosuppression associated with erythropoiesis in genetic low responder mice. Ann Immunol (Paris). 1980;131C(3):397–404. Tsyrlova IG. Erythroid immunosuppressor cells (Er suppressors) and their role in the regulation of immunity. Vestn Akad Med Nauk SSSR. 1991;(12):34–9. Grzywa TM, Nowis D, Golab J. The role of CD71 + erythroid cells in the regulation of the immune response. Pharmacol Ther. 2021;228:107927. Elahi S, Ertelt JM, Kinder JM, Jiang TT, Zhang X, Xin L, et al. Immunosuppressive CD71 + erythroid cells compromise neonatal host defence against infection. Nature. 2013;504(7478):158–62. Dunsmore G, Bozorgmehr N, Delyea C, Koleva P, Namdar A, Elahi S. Erythroid Suppressor Cells Compromise Neonatal Immune Response against Bordetella pertussis. J Immunol. 2017;199(6):2081–95. Namdar A, Koleva P, Shahbaz S, Strom S, Gerdts V, Elahi S. CD71 + erythroid suppressor cells impair adaptive immunity against Bordetella pertussis. Sci Rep. 2017;7(1):7728. Elahi S, Mashhouri S. Immunological consequences of extramedullary erythropoiesis: immunoregulatory functions of CD71 + erythroid cells. Haematologica. 2020;105(6):1478–83. Zhao L, He R, Guo HLB, Jia Q, Qin D, et al. Late-stage tumors induce anemia and immunosuppressive extramedullary erythroid progenitor cells. Nat Med. 2018;24(10):1536–44. Yasuyo Sano T, Yoshida M-K, Choo Y, Jiménez-Andrade KR, Hill K, Georgopoulos, et al. Multiorgan Signaling Mobilizes Tumor-Associated Erythroid Cells Expressing Immune Checkpoint Molecules. Mol Cancer Res. 2021;19(3):507–15. Chen J, Qiao Y-D, Li X, Xu J-L, Ye Q-J, Jiang N, et al. Intratumoral CD45 + CD71 + erythroid cells induce immune tolerance and predict tumor recurrence in hepatocellular carcinoma. Cancer Lett. 2021;499:85–98. de Peffault R, Risitano AM. Complement inhibition in medicine: Hematology and beyond; complement inhibition in hematology: PNH and beyond. Am J Hematol. 2023;98(S4):S3–4. Risitano AM, Frieri C, Urciuoli E, Marano L. The complement alternative pathway in paroxysmal nocturnal hemoglobinuria: From a pathogenic mechanism to a therapeutic target. Immunol Rev. 2023;313(1):262–78. Nicholson-Weller A, March JP, Rosenfeld SI, Austen KF. Affected erythrocytes of patients with paroxysmal nocturnal hemoglobinuria are deficient in the complement regulatory protein, decay accelerating factor. Proc Natl Acad Sci U S A. 1983;80(16):5066–70. Holguin MH, Fredrick LR, Bernshaw NJ, Wilcox LA, Parker CJ. Isolation and characterization of a membrane protein from normal human erythrocytes that inhibits reactive lysis of the erythrocytes of paroxysmal nocturnal hemoglobinuria. J Clin Invest. 1989;84(1):7–17. Lehto T, Meri S. Interactions of soluble CD59 with the terminal complement complexes. CD59 and C9 compete for a nascent epitope on C8. J Immunol. 1993;151(9):4941–9. Shtivelman E, Cohen FE, Bishop JM. A human gene (AHNAK) encoding an unusually large protein with a 1.2-microns polyionic rod structure. Proc Natl Acad Sci U S A. 1992;89(12):5472–6. Davis TA, Loos B, Engelbrecht AM. AHNAK: The giant jack of all trades. Cell Signal. 2014;26(12):2683–93. Zeng Z, Lan T, Wei Y, Wei X. CCL5/CCR5 axis in human diseases and related treatments. Genes Dis. 2022;9(1):12–27. Aldinucci D, Borghese C, Casagrande N. The CCL5/CCR5 Axis in Cancer Progression. Cancers (Basel). 2020;12(7):1765. Hong JT, Son DJ, Lee CK, Yoon DY, Lee DH, Park MH. Interleukin 32, inflammation and cancer. Pharmacol Ther. 2017;174:127–37. de Albuquerque R, Komsi E, Starskaia I, Ullah U, Lahesmaa R. The role of Interleukin-32 in autoimmunity. Scand J Immunol. 2021;93(2):e13012. Barber EK, Dasgupta JD, Schlossman SF, Trevillyan JM, Rudd CE. The CD4 and CD8 antigens are coupled to a protein-tyrosine kinase (p56lck) that phosphorylates the CD3 complex. Proc Natl Acad Sci U S A. 1989;86(9):3277–81. Ratthé C, Girard D. Interleukin-15 enhances human neutrophil phagocytosis by a Syk-dependent mechanism: importance of the IL-15Ralpha chain. J Leukoc Biol. 2004;76(1):162–8. Lisa Kalman ML, Lindegren L, Kobrynski R, Vogt H, Hannon JT, Howard, et al. Mutations in genes required for T-cell development: IL7R, CD45, IL2RG, JAK3, RAG1, RAG2, ARTEMIS, and ADA and severe combined immunodeficiency: HuGE review. Genet Med. 2004;6(1):16–26. Supplementary Files SupplementFigure.doc Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 24 Sep, 2025 Editor invited by journal 15 Sep, 2025 Editor assigned by journal 14 Aug, 2025 First submitted to journal 13 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7363120","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":519754572,"identity":"8189411c-afe2-43b0-b3ec-14c75065406b","order_by":0,"name":"Liyan Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIiWNgGAWjYDACZijNxt584MCHCgYeErTwHEs8OOMMMVrgQCLH+DBnGxEKDY4zP3zMU3PHno/njMFhxnl1MubsBxg/fMzBrUWymc3YmOfYM2Y29raCw4XbDvNY9iQwS87chlsLPzODmTQP22E2Np7DGw7P3HaAx+BAAhszLx4tbMzs36R5/h3mYZNIMDjMO6eOx+D8A/xa+Jl5zKR52w5LsEmkALU0MPMY3CBgi2QzT7Hh3L7DBsBATjg449hhoJaHzXj9YnD++MYHb74dtpdvbz784UNNnb3B+eSDHz7i0QICTGjRx9iAXz1IyQ+CSkbBKBgFo2BEAwC7bE/a30Fv9gAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-2732-3646","institution":"Tianjin Medical University General Hospital","correspondingAuthor":true,"prefix":"","firstName":"Liyan","middleName":"","lastName":"Li","suffix":""},{"id":519754573,"identity":"d4ad2eac-df2a-494d-9cf9-1fb006f74c03","order_by":1,"name":"Junshu Wu","email":"","orcid":"","institution":"Tianjin Medical University General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Junshu","middleName":"","lastName":"Wu","suffix":""},{"id":519754574,"identity":"b658bc45-5901-424a-98c9-11e8ca1f17a2","order_by":2,"name":"Hui Liu","email":"","orcid":"","institution":"Tianjin Medical University General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"Liu","suffix":""},{"id":519754575,"identity":"1119cb16-b14a-416d-ac8f-90464bef32ce","order_by":3,"name":"Wei Wang","email":"","orcid":"","institution":"ShanghaiTech University","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Wang","suffix":""},{"id":519754576,"identity":"dd01806d-297b-4e64-8f74-df6d3884fcca","order_by":4,"name":"Chaomeng Wang","email":"","orcid":"","institution":"Tianjin Medical University General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chaomeng","middleName":"","lastName":"Wang","suffix":""},{"id":519754577,"identity":"3aa9cacd-3d4e-4efd-bd89-211cad2097ad","order_by":5,"name":"Zhaoyun Liu","email":"","orcid":"","institution":"Tianjin Medical University General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Zhaoyun","middleName":"","lastName":"Liu","suffix":""},{"id":519754578,"identity":"6e598c5d-2517-4d86-9b59-1bea3270c219","order_by":6,"name":"Yingying Chen","email":"","orcid":"","institution":"Tianjin Medical University General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yingying","middleName":"","lastName":"Chen","suffix":""},{"id":519754579,"identity":"50b7a8ba-8b6a-40d5-b94f-4f239ee269cc","order_by":7,"name":"Honglei Wang","email":"","orcid":"","institution":"Tianjin Medical University General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Honglei","middleName":"","lastName":"Wang","suffix":""},{"id":519754580,"identity":"49a5dcd1-f933-4862-8a0d-63e4e9b8a20f","order_by":8,"name":"Rong Fu","email":"","orcid":"https://orcid.org/0000-0002-9928-9224","institution":"Tianjin Medical University General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Rong","middleName":"","lastName":"Fu","suffix":""}],"badges":[],"createdAt":"2025-08-13 09:16:54","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7363120/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7363120/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":93009051,"identity":"393eb79c-8d53-4efe-b091-0c33272e5021","added_by":"auto","created_at":"2025-10-08 07:06:58","extension":"doc","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":40448,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.doc","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/ae0ebf069b0016029507ee84.doc"},{"id":93012483,"identity":"ec873e09-4709-4c18-8975-2704449ee11f","added_by":"auto","created_at":"2025-10-08 07:22:58","extension":"xml","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":13258,"visible":true,"origin":"","legend":"","description":"","filename":"ojrdOJRDD2501210.xml","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/5162599cd217237f6194cea6.xml"},{"id":93010526,"identity":"1bfa9419-cf1f-4def-bcdd-9eee69a044cf","added_by":"auto","created_at":"2025-10-08 07:14:58","extension":"xml","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1204,"visible":true,"origin":"","legend":"","description":"","filename":"OJRDD250121025804.go.xml","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/c3585e84c81da8c0924c22c4.xml"},{"id":93009054,"identity":"da8e7da7-8f17-4334-be10-a842fc0818cf","added_by":"auto","created_at":"2025-10-08 07:06:58","extension":"xml","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":829,"visible":true,"origin":"","legend":"","description":"","filename":"OJRDD2501210Import.xml","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/0686bcfe7b471fafdd223845.xml"},{"id":93009063,"identity":"b5da91ce-8fc9-4039-b14a-263d66d1c2e1","added_by":"auto","created_at":"2025-10-08 07:06:58","extension":"xml","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":103187,"visible":true,"origin":"","legend":"","description":"","filename":"OJRDD25012100enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/8780221105b3a13a9607070f.xml"},{"id":93009059,"identity":"5a0f2460-25bd-4122-b846-f847279e4487","added_by":"auto","created_at":"2025-10-08 07:06:58","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2878301,"visible":true,"origin":"","legend":"","description":"","filename":"FIGURE1.png","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/a85a34f04f252eabacf2aa0e.png"},{"id":93009068,"identity":"d9cca289-0172-4ed4-911e-281bba37a178","added_by":"auto","created_at":"2025-10-08 07:06:59","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1425588,"visible":true,"origin":"","legend":"","description":"","filename":"FIGURE2.png","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/adc72a46e2dcc136b094f40b.png"},{"id":93009057,"identity":"f8ea05e4-b3ce-4ee5-89cd-abeb50f68941","added_by":"auto","created_at":"2025-10-08 07:06:58","extension":"png","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":804762,"visible":true,"origin":"","legend":"","description":"","filename":"FIGURE3.png","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/728e7cfa0b95a68d45d8764e.png"},{"id":93012485,"identity":"cf669695-06ef-4f9b-9c83-6466149fc583","added_by":"auto","created_at":"2025-10-08 07:22:59","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":951812,"visible":true,"origin":"","legend":"","description":"","filename":"FIGURE4.png","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/7357ea3522ddc911217ae909.png"},{"id":93009072,"identity":"e5895160-fb39-470e-8bd5-56ad396ca17a","added_by":"auto","created_at":"2025-10-08 07:06:59","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1522478,"visible":true,"origin":"","legend":"","description":"","filename":"FIGURE5.png","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/293ca6d3620c39e952f7dbc3.png"},{"id":93009064,"identity":"6677dec7-71bd-4318-92f3-4cf0edee9d78","added_by":"auto","created_at":"2025-10-08 07:06:58","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":420139,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFIGURE1.png","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/054cae2de4577a7892861478.png"},{"id":93010531,"identity":"4681a636-da30-4644-81d2-79f547ed2b59","added_by":"auto","created_at":"2025-10-08 07:14:59","extension":"png","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":199031,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFIGURE2.png","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/f1e012c79845c40b367f1637.png"},{"id":93009073,"identity":"fbedf736-0e65-46e8-9b50-61980d30b7ca","added_by":"auto","created_at":"2025-10-08 07:06:59","extension":"png","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":141585,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFIGURE3.png","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/1c7be757523371864abdb213.png"},{"id":93009067,"identity":"330a5ec0-ac8d-44e1-9cce-344db61e4508","added_by":"auto","created_at":"2025-10-08 07:06:58","extension":"png","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":165835,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFIGURE4.png","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/9e25e0988c171a85285b1ab1.png"},{"id":93009070,"identity":"50177f06-24bd-42ae-accd-33deecff05d0","added_by":"auto","created_at":"2025-10-08 07:06:59","extension":"png","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":225173,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFIGURE5.png","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/cdd63c317e96a61a3743b875.png"},{"id":93010532,"identity":"016e7f44-f309-4c43-a7e1-50dcc256954d","added_by":"auto","created_at":"2025-10-08 07:14:59","extension":"xml","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":101684,"visible":true,"origin":"","legend":"","description":"","filename":"OJRDD25012100structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/16f06a71de0aa896ecd56a19.xml"},{"id":93010529,"identity":"bb03cfb3-9479-463d-b212-aa41a3d745ca","added_by":"auto","created_at":"2025-10-08 07:14:58","extension":"html","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":108256,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/7168182a8105cd0d0df0666a.html"},{"id":93009062,"identity":"0d60ebde-04ce-4c87-b5f1-40e24048b4d9","added_by":"auto","created_at":"2025-10-08 07:06:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2878301,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResults of multiomics analysis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. t-SNE representing erythrocytes from 6 types of peripheral blood. B. Dot plot of cell-specific markers. The size of the dot represents the percentage of cells expressing the markers, and the colour encodes the average scaled expression values.C.(1)-(9) Illustration of cell-specific markers.\u003c/p\u003e","description":"","filename":"FIGURE1.png","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/858692536f048e2e5ec63276.png"},{"id":93010527,"identity":"1aaf8bf0-c652-4745-a7e5-e43db4d04a06","added_by":"auto","created_at":"2025-10-08 07:14:58","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1425588,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAn immune-responsive erythroid subgroup in PNH is recognized through single-cell RNA sequencing analysis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. The ratio of each observed cell type in the CD59+leukocyte of PNH patients(P)、CD59- leukocyte of PNH patients(N) and normal controls（C). B. Volcano Plot displaying the Mrna expression level of DEPs of Clusters based on significance and log FC values. C. GO enrichment analysis of differential genes in each cluster. D. KEGG enrichment of differential genes in each cluster.**P \u0026lt; 0.01 ,***P \u0026lt; 0.001, ****P \u0026lt; 0.0001\u003c/p\u003e","description":"","filename":"FIGURE2.png","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/bfc596d3a1b90dcb6f4a09a7.png"},{"id":93010525,"identity":"786a4f0d-8ad2-41c2-8eca-801e06208367","added_by":"auto","created_at":"2025-10-08 07:14:58","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":804762,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe unique signatures of C3 erythroid lineage cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Heatmap displaying the mRNA expression level of DEPs of Cluster 3 in the three groups based on significance and log FC values. B. Volcano plot showing differentially expressed genes (DEGs) of Cluster 3 in the three groups. C. Venn diagram showing the summary of DEGs in Cluster 3 detected by pair-wise comparison at three groups. D. KEGG enrichment of differential genes in Cluster 3 at three groups. E. Upregulated GO Enrichment in Cluster 3 at three groups. F. Downregulated GO Enrichment in Cluster 3 at three groups.\u003c/p\u003e","description":"","filename":"FIGURE3.png","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/f0df4f76fe801b7d09385718.png"},{"id":93009053,"identity":"6ef76774-4d3c-41d7-999f-08d5cc4675c4","added_by":"auto","created_at":"2025-10-08 07:06:58","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":951812,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe unique signatures of C6 erythroid lineage cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Heatmap displaying the mRNA expression level of DEPs of Cluster 6 in the three groups based on significance and log FC values. B. Volcano plot showing differentially expressed genes (DEGs) of Cluster 6 in the three groups. C. Venn diagram showing the summary of DEGs in Cluster 6 detected by pair-wise comparison at three groups. D. Upregulated pathways in N and C groups. E. Upregulated pathways in N and P groups. F. Upregulated pathways in P and C.\u003c/p\u003e","description":"","filename":"FIGURE4.png","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/fc64cec522499e1562b4343d.png"},{"id":93009056,"identity":"6637fc60-f634-4a91-ac3e-7e2cfca57497","added_by":"auto","created_at":"2025-10-08 07:06:58","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1522478,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThere is a correlation between the screening of C6 cluster-specific genes and immunological markers in PNH patients.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. The Venn diagram illustrates the results of cross-referencing the upregulated genes from three groups within cluster 6 with immune databases. B.(1)-(9) The violin plot illustrates the expression of genes associated with three groups in cluster 6. C. Analysis of the correlation between mRNA levels of AHNAK, IL32, CD3E, IL2RG, and CCL5 in CD235a-positive cells of PNH patients and immune parameters. *P \u0026lt; 0.05, **P \u0026lt; 0.01 ,***P \u0026lt; 0.001, ****P \u0026lt; 0.0001\u003c/p\u003e","description":"","filename":"FIGURE5.png","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/956d5832f34c6924c2dbfeae.png"},{"id":93013859,"identity":"47025fed-ec9a-4b17-bd0f-36192ded1910","added_by":"auto","created_at":"2025-10-08 07:31:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8095089,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/7f7db216-2bed-4d3b-9ce7-8e90c93cddbc.pdf"},{"id":93012484,"identity":"7425b08b-d42d-45c8-84f0-2c64ab3fe15f","added_by":"auto","created_at":"2025-10-08 07:22:59","extension":"doc","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":2758656,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementFigure.doc","url":"https://assets-eu.researchsquare.com/files/rs-7363120/v1/abe5a96e4cca9bee163e582c.doc"}],"financialInterests":"","formattedTitle":"Single-cell transcriptomic analysis identifies an immune erythroid in paroxysmal nocturnal hemoglobinuria","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eParoxysmal nocturnal hemoglobinuria (PNH) is a clonal hematopoietic stem cell disorder characterized by hemolytic anemia, thrombosis, and bone marrow failure.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Affected cells become extremely susceptible to the impact of C3, C5, and the terminal pathway of the complement cascade due to the crucial role of CD55 in regulating the alternative pathway and C3 convertases.\u003csup\u003e\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e Moreover, the formation of the membrane attack complex (MAC) is inhibited by CD59, further exacerbating the vulnerability of these cells.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e CD55 and CD59 deficiency renders PNH erythrocytes susceptible to complement-mediated intravascular hemolysis\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Erythrocytes are simultaneously targeted by the complement system, resulting in the release and accumulation of free hemoglobin and iron in plasma. Subsequently, nitric oxide (NO) depletion and upregulation of pro-inflammatory cytokines occur.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e Therefore, the role of erythrocytes in PNH remains crucial.\u003c/p\u003e\u003cp\u003eErythrocytes traditionally transport oxygen.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Recent studies have indicated that immature CD71\u0026thinsp;+\u0026thinsp;erythroid cells exhibit immunomodulatory functions under various physiological and pathological conditions, thus expanding our understanding of erythrocytes.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Elahi\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e suggested that the diminished protective immune response in neonates could be attributed to the unique immunosuppressive properties of CD71\u0026thinsp;+\u0026thinsp;erythrocytes, whereas immature CD71\u0026thinsp;+\u0026thinsp;erythrocytes exhibit distinctive immune regulatory characteristics that play a role in immune development. Some studies have also reported that erythroid progenitor cells (EPCs) can be induced by tumors to exert immunosuppressive functions in the tumor microenvironment (TME), and EPCs can also secrete artemin in the spleen to promote tumor progression.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e In recent years, the immunological functions of erythrocytes have garnered increasing attention. However, the precise mechanisms underlying the immune role of erythrocytes in diseases such as intrinsic immune-like transcriptional programs within erythroid remains unclear.\u003c/p\u003e\u003cp\u003eWhole transcriptome sequencing identifying CXCR2 expression in PNH granulocytes\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e and transcriptomic analyses of T cells\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e have already been reported. Our study focuses on erythroid cells, we collected clonal bone marrow cells from patients with PNH and normal bone marrow cells to perform single-cell analyses and investigate erythroid development in patients with PNH. We identified a subset of erythroid cells exhibiting abnormal activity in the CD59\u0026thinsp;+\u0026thinsp;cell compartment in patients with PNH, further elucidating the developmental stage characteristics of these immune erythroid cells and investigating their regulatory genes and immunoregulatory functions.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Patients and clinical samples\u003c/h2\u003e\u003cp\u003e This study was approved by the Ethics Committee of General Hospital of Tianjin Medical University. This study included four patients with classic PNH and four young healthy donors who were admitted to the Department of Hematology of Tianjin Medical University General Hospital between February 2023 and November 2024. Informed consent was obtained from all study participants and their families.The clinical characteristics of the 4 PNH patients are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClinical characteristics of 4 PNH patients\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePatients\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal no. of patients\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender M/F\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2/2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge Median (range)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e38(21\u0026ndash;55)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical classification n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eclassical PNH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePNH-AA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003esubclinical-PNH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameters at baseline\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHGB (g/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e66.9(14.92)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRet (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.18(6.74)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWBC (*10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.49(3.51)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePLT (*10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e125.00(64.53)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBIL (umol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e54.79(27.10)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLDH (U/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1439(989.80)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGranulocyte CD59\u003csup\u003e\u0026minus;\u003c/sup\u003e (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e88.24(19.30)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFlaer-/CD14-(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e87.30(26.28)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFlaer-/CD24-(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e64.85(21.42)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003en: number; PNH: Paroxysmal nocturnal hemoglobinuria; RET: Reticulocyte ratio; RBC: red blood cell; WBC: white blood cell; HGB: hemoglobin; PLT: Platelet; TBIL: total bilirubin; DBIL: direct bilirubin. LDH: lactate dehydrogenase.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Cell culture and sorting\u003c/h2\u003e\u003cp\u003eBone marrow samples were collected from patients and controls, separated using density gradient centrifugation for 20 min, isolated from the mononuclear cell layer in the middle, washed, and then incubated with FITC CD59 (BD Biosciences) for 15 min at room temperature. CD59+/CD59- BM monocytes from patients were processed using an Aria II instrument (BD Biosciences). Followed the same procedure to collect patient bone marrow mononuclear cells, incubate with CD235a beads at 4 degrees in the dark for 20 minutes, separate positive and negative cells using a magnetic column.The purity of the sorted cells can reach 95%.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Single-Cell RNA Sequencing (scRNA-seq) Analysis\u003c/h2\u003e\u003cp\u003eSingle-cell sequencing was conducted using the 10\u0026times; Genomics platform. CellRanger software (version 5.0.1) facilitated the alignment of raw sequencing data to the human reference genome GRCh38 (2020) and extraction of the count matrix following default parameters. After eliminating low-quality cells, data normalization was performed, and the top 2000 variably expressed genes were identified using the FindVariableFeatures function within Seurat. Principal component analysis (PCA) was used to reduce the dimensionality of the scRNA-seq dataset. Cell clusters were defined by implementing the FindClusters function in Seurat, with the resolution parameter set to 0.3. Visualization of these clusters was executed via uniform manifold approximation and projection (UMAP) plots. To delve deeper into the alterations within erythroid lineage cells, the specific cell subset identified as erythroid lineage cells was extracted using the subset function within the Seurat software, followed by subsequent reclustering. This process entailed segregating the population of erythroid lineage cells from the primary dataset and subjecting it to a more detailed clustering analysis using the recluster feature in Seurat. We employed the Harmony package (version 1.0) for batch correction, thereby ensuring reliable comparative assessments spanning multiple datasets.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 RNA extraction and real-time quantitative polymerase chain reaction (PCR)\u003c/h2\u003e\u003cp\u003eTotal RNA was extracted from clinical samples. The FastKing RT kit (ABclonal; RK20433) was used to synthesize samples from total RNA. SuperReal PreMix Plus (SYBR Green) (YEASEN; 11184) was used for real-time quantitative PCR. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the PCR primers for AHNAK, CCL5, Interleukin 32 (IL32), CD3E, IL2RG, and GADPH genes. Melting and amplification curves were examined using Bio-Rad CFX 3.1.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe PCR primers for the genes\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eName\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSequence (5\u0026prime;\u0026ndash;3\u0026prime;)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAHNAK\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eForward: TACCCTTCCTAAGGCTGACATT\u003c/p\u003e\u003cp\u003eReverse: TTGGACCCTTGAGTTTTGCAT\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eCCL5\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eForward: CCAGCAGTCGTCTTTGTCAC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReverse: CTCTGGGTTGGCACACACTT\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eIL32\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eForward: TGGCGGCTTATTATGAGGAGC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReverse: CTCGGCACCGTAATCCATCTC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eCD3E\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eForward: CCTCTTATCAGTTGGCGTTTGG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReverse: TTCAGTGACAGGTGATCCTCA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eIL2RG\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eForward: GTGCAGCCACTATCTATTCTCTG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReverse: GTGAAGTGTTAGGTTCTCTGGAG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eGapdh\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eForward:CTGGGCTACACTGAGCACC\u003c/p\u003e\u003cp\u003eReverse:AAGTGGTCGTTGAGGGCAATG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Statistical analysis\u003c/h2\u003e\u003cp\u003eStatistical analyses were conducted using the GraphPad Prism software (version 9.0; GraphPad Software). Group comparisons were performed using the Student\u0026rsquo;s t-test and analysis of variance (ANOVA), with subsequent multiple comparisons using Tukey\u0026rsquo;s honest significant difference post-ANOVA. Two-way ANOVA with Sidak\u003csup\u003e\u0026rsquo;\u003c/sup\u003es multiple comparison test was used to analyze comparisons among multiple groups. P values of less than 0.05 were considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1 An immune-responsive erythroid subgroup in PNH is recognized using scRNA-seq analysis.\u003c/h2\u003e\u003cp\u003eWe conducted scRNA-seq of cells harvested from normal bone marrow mononuclear cells (CD59\u0026thinsp;+\u0026thinsp;cells, P group) with PNH clones (CD59- cells, N group) in patients with PNH (n\u0026thinsp;=\u0026thinsp;4), as compared to healthy controls (C group, n\u0026thinsp;=\u0026thinsp;4) using the 10x Genomics platform. After completing data preprocessing and quality control procedures, a total of 129,925 cells were obtained. Dimensionality reduction and unsupervised clustering of the erythroid precursors yielded six major clusters (C0\u0026ndash;C6) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). We identified specific markers associated with each cluster, including GYPA, MKI67, BNIP3L, IFIT1B, CD74, LYZ, S100A8, MIF, and FAM178B (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB, C; Supplementary Fig.\u0026nbsp;1).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe found that the proportion of erythroid cells changed in various lineages in patients with PNH (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Significant differences primarily manifested in clusters 1, 3, 5, and 6. In cluster 3, the proportion in Group P was lower than that in the control group (p\u0026thinsp;=\u0026thinsp;0.032), whereas no significant difference was noted between Group N and the control group (p\u0026thinsp;=\u0026thinsp;0.426). In Cluster 6, the P group showed a significant increase compared to both the control and N groups (p\u0026thinsp;=\u0026thinsp;0.0024 and p\u0026thinsp;=\u0026thinsp;0.0029, respectively).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo investigate the biological relevance of these clusters, we conducted a GO enrichment analysis using the signature genes of each cluster (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). C0 was associated with co-translational proteins targeting the membrane and SRP-dependent co-translational proteins targeting the membrane and translational initiation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC; Supplementary Fig.\u0026nbsp;2). C1 related mRNA catabolism, RNA catabolism(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC; Supplementary Fig.\u0026nbsp;3). C3 related neutrophil activation involved in T cell activation, immune response-activating cell (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). C4 related ribonucleoprotein complex biogenesis and mitochondrial translational termination (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC; Supplementary Fig.\u0026nbsp;4). C5 was involved in oxidative phosphorylation and ATP metabolic processes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC; Supplementary Fig.\u0026nbsp;5). C6 related antigen processing and leukocyte-mediated cytotoxicity (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Subsequently, we conducted KEGG analyses for each cluster. The C0 cluster pathway was mainly involved in the cell cycle, ferroptosis, apoptosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). The C1 cluster pathway was mainly involved in protein processing in the endoplasmic reticulum(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). The C3 cluster pathway was mainly involved in leukocyte transendothelial migration, chemokine signaling, IL17 signaling, and NF-kappa B signaling (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). The C4 cluster pathway was mainly involved in nucleotide excision repair (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). The C5 cluster pathway was mainly involved in ATP-dependent chromatin remodeling, nucleotide metabolism(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). The C6 cluster pathway was mainly involved in allograft rejection, antigen processing and presentation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). These findings indicate that the cells in C5 exhibited higher maturation than those in C0, C1, and C4. C3 and C6 were uniquely enriched in terms related to immune activity, such as immune response, chemokine signaling pathway, cytokine-cytokine receptor interaction, and antigen processing and presentation (for example, \u003cem\u003eLYZ\u003c/em\u003e, \u003cem\u003eCD3D\u003c/em\u003e and \u003cem\u003eCD74\u003c/em\u003e). Thus, C3 and C6 of erythroids were characterized by the expression of immune-related genes.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.2 The unique signatures of C3 erythroid lineage cells.\u003c/h2\u003e\u003cp\u003eWe further investigate the immune alterations in the erythroid lineage cells of PNH, differential gene enrichment analysis was initially conducted on C3 cells from normal bone marrow mononuclear cells (CD59\u0026thinsp;+\u0026thinsp;cells, P group) with PNH clones (CD59- cells, N group) and normal controls (C group) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, B, C). In the comparison between the N and C groups, a total of 3,304 differentially expressed genes were identified, with upregulated genes including HBG1 and HBD and downregulated genes mainly consisting of IGLC2 and IGHG3. And comparing the N and P groups, 15 genes exhibited statistically significant differences, with DEFA3 and HIST1H1E being upregulated, and CCL4 and IGHA1 being downregulated. Comparing the P group to the C group, 17 genes showed statistically significant differences, with IL32 and GNLY being upregulated and DEFA3 and LRRC75A being downregulated. KEGG analyses (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD) of differentially expressed genes (DEGs) revealed that compared to group P, group N exhibited upregulation of pathways mainly enriched in the cell cycle and p53 signaling pathways, whereas downregulated pathways were predominantly enriched in ribosome biogenesis in eukaryotes, steroid hormone biosynthesis, cytosolic DNA-sensing pathway, and N-glycan biosynthesis. When comparing group P to group C, the upregulated pathways were primarily enriched in ribosome biogenesis and glycosyltransferases, whereas the downregulated pathways were predominantly enriched in neutrophil extracellular trap formation, transcriptional dysregulation in cancer, cytoskeleton proteins, and the NOD-like receptor signaling pathway. GO enrichment analyses of differentially expressed genes (DEGs) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE, F) revealed that the upregulated processes in group N compared to those in group C were associated with cofactor catabolic processes, protein heterooligomerization, and antibiotic metabolic processes, whereas the downregulated processes were primarily linked to organ- or tissue-specific immune responses and tumor necrosis factor superfamily cytokine production.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.3 The unique signatures of C6 erythroid lineage cells.\u003c/h2\u003e\u003cp\u003eDifferential gene enrichment analyses were initially conducted on C6 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, B, C). A total of 820 differentially expressed genes were identified between the N and C groups, with upregulated genes including GNLY and HBG2, and downregulated genes mainly consisting of RPS29 and DEFA3. When comparing the N and P groups, 203 genes exhibited statistically significant differences, with BLVRB and HIST1H4C being upregulated, and TMSB4X and GZMK being downregulated. When comparing the P group to the C group, 417 genes showed statistical differences, with ARL4A and HBG1 being upregulated and RPS4Y1 and AZU1 being downregulated. Gene ontology (GO) and KEGG enrichment analyses of differentially expressed genes indicated that compared to group C, the upregulated genes in group N were mainly enriched in DNA methylation, DNA damage/telomere stress-induced senescence, pre-NOTCH transcription and translation, HDACs deacetylation histones, and PRC2 methylation of histones and DNA. In contrast, the upregulated genes in group C were predominantly enriched in the L13a-mediated translational silencing of ceruloplasmin expression, Formation of ATP by chemiosmotic coupling, and cell-extracellular matrix interactions (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). In a comparison between groups N and P, the upregulated genes in group N were mainly enriched in oxidative phosphorylation, DNA replication, G2/M checkpoints, and ubiquitin-dependent degradation of cyclin D1, whereas the upregulated genes in group P were significantly enriched in hematopoietic cell lineage, T cell receptor signaling pathway, antigen processing and presentation, Th1 and Th2 cell differentiation, NF-kappa B signaling pathway, and cytokine signaling in immune system (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE). Furthermore, when comparing groups P and C, the upregulated genes in group P were predominantly enriched in allograft rejection, natural killer cell mediated cytotoxicity, antigen processing and presentation, and Th17 cell differentiation, whereas the upregulated genes in group C were mainly enriched in retrograde endocannabinoid signaling and DNA replication (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF). Therefore, it can be inferred that CD59\u0026thinsp;+\u0026thinsp;cells of patients with PNH exhibit stronger immune activity in the C6 cell population.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e3.4 There is a correlation between the screening of C6 cluster-specific genes and immunological markers in patients with PNH.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo further investigate the immune erythroid cells in patients with PNH, we conducted a cross-enrichment analysis by comparing the upregulated genes in the P group of C6 using ImmPort Portal and identified 9 relevant genes: AHNAK, CCL5, CD3E, HLA-A, HLA-E, IL2RG, IL32, PTPRC, and TRIM22 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). In single-cell sequencing of the C6 group, the expression level trend of AHNAK was P\u0026thinsp;\u0026gt;\u0026thinsp;C\u0026thinsp;\u0026gt;\u0026thinsp;N (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB [1]). The expression levels of CCL5 of C6 group following the trend P\u0026thinsp;\u0026gt;\u0026thinsp;C\u0026thinsp;\u0026gt;\u0026thinsp;N (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB [2]), CD3E showing a trend of P\u0026thinsp;\u0026gt;\u0026thinsp;C\u0026thinsp;\u0026gt;\u0026thinsp;N (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB [3]), HLA-A trending towards P\u0026thinsp;\u0026gt;\u0026thinsp;N\u0026thinsp;\u0026gt;\u0026thinsp;C (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB [4]), HLA-E following the trend P\u0026thinsp;\u0026gt;\u0026thinsp;N\u0026thinsp;\u0026gt;\u0026thinsp;C (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB [5]), IL2RG showing a trend of P\u0026thinsp;\u0026gt;\u0026thinsp;C\u0026thinsp;\u0026gt;\u0026thinsp;N (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB [6]), IL32 trending in the order P\u0026thinsp;\u0026gt;\u0026thinsp;C\u0026thinsp;\u0026gt;\u0026thinsp;N (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB [7]), PTPRC following the trend P\u0026thinsp;\u0026gt;\u0026thinsp;N\u0026thinsp;\u0026gt;\u0026thinsp;C (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB [8]), and the expression levels of TRIM22 showing a trend of P\u0026thinsp;\u0026gt;\u0026thinsp;C\u0026thinsp;\u0026gt;\u0026thinsp;N (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB [9]).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eSubsequently, a comparative analysis was conducted using the GEO database GSE80062 on the RNA expression levels of the eight genes; no relevant data for HLA-E was present, leading to the selection of five genes for further investigation (Supplementary Fig.\u0026nbsp;6). These genes are identified as AHNAK, CCL5, IL32, CD3E, and IL2RG. We detected the expression of these gene in CD235a-positive cells of patients using PCR and statistical analyses with immune-related indicators (Supplementary Fig.\u0026nbsp;7). We found that the mRNA levels of IL32 and IL2RG were positively correlated with CD3\u0026thinsp;+\u0026thinsp;CD4+/T cells; the mRNA content of CD3E was positively correlated with class-switched memory B cells/B cell%, and the mRNA content of CCL5 was positively correlated with CD19+%, CD19/Lym%, and Treg/CD3\u0026thinsp;+\u0026thinsp;CD4\u0026thinsp;+\u0026thinsp;cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn this study, we conducted a multi-omics analysis of CD59+/CD59- erythroid cells from the bone marrow of patients with PNH and normal control erythroid cells. We identified an immunological red cell subset involved in the development of PNH and identified key genes that potentially play a crucial role. This study provides valuable information to understand the mechanisms underlying erythroid abnormalities in PNH.\u003c/p\u003e\u003cp\u003eIn recent years, in addition to their role in oxygen transport, red blood cells (RBCs) have gained attention for their immunomodulatory functions.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e The immunomodulatory role of RBCs was first discovered in 1953 when Nelson RA et al.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e found that RBCs exhibit immune adhesion to microorganisms, triggering immune-specific reactions and enhancing phagocytosis. Subsequently, nucleated RBCs in the spleen mediate immune suppression.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e Studies have shown that nucleated RBCs can inhibit first and second antibody-mediated reactions in the body.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e Furthermore, a type of nucleated RBCs has been shown to suppress B cell proliferation in humoral immune responses.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e Several studies have indicated that erythroid cells can impair innate and adaptive immune responses\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e against bacterial species including L. monocytogenes\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e and Bordetella pertussis.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e Depletion of CD71\u0026thinsp;+\u0026thinsp;erythroid cells in neonatal mice restored their immune response against various pathogens and reduced bacterial loads\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Decreased CD71\u0026thinsp;+\u0026thinsp;nucleated RBCs in neonates enhanced the activation of immune cells and the production of TNF-a, IL17, and IFN-g.\u003csup\u003e\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e Furthermore, studies have shown that the removal of CD71\u0026thinsp;+\u0026thinsp;erythroid cells from the neonatal splenic cell population in mice eliminates their inhibitory effects on the development of immune responses.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eCD71\u0026thinsp;+\u0026thinsp;erythroid cells have been reported to play a role in tumor immunity.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e Studies have indicated that CD71\u0026thinsp;+\u0026thinsp;erythroid cells effectively inhibit antitumor immunity. The excessive presence of CD71\u0026thinsp;+\u0026thinsp;cells leads to accelerated tumor growth, whereas anti-EPO or anti-CD71 antibodies can exert an anti-tumor effect, delaying tumor progression.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e Additionally, erythroid cells can suppress the proliferation and differentiation of CD4\u0026thinsp;+\u0026thinsp;T cells as well as inhibit the proliferation and cytotoxicity of CD8\u0026thinsp;+\u0026thinsp;T cells.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e In tumor-bearing mice, the absence of CD71\u0026thinsp;+\u0026thinsp;erythroid cells can delay tumor growth and restore immune responses to levels comparable to those of tumor-free mice;\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e conversely, overexpression of CD71\u0026thinsp;+\u0026thinsp;erythroid cells reduces T cell proliferation, as well as the production of TNF-a and IFN-g.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e Therefore, we conducted an enrichment analysis of differentially expressed genes in each cell group. The analysis revealed that in addition to erythroid cells with functions in transcription, translation, and oxygen transport, there were two other groups of erythroid cells associated with T cell activation and antigen presentation. These findings were consistent with those of previous studies.\u003c/p\u003e\u003cp\u003ePNH is characterized by dysregulation of the complement system.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e Owing to the deficiency in CD55 and CD59, RBCs in PNH are unable to regulate the activation of complements on their surfaces, ultimately leading to complement-mediated intravascular hemolysis.\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e CD55 (DAF) and CD59 (MIRL) act as natural inhibitors of the complement system. Their deficiency in RBCs results in uncontrolled activation of the complement system, leading to chronic hemolysis, platelet activation, thrombosis, and various systemic manifestations.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e In cases of PNH, the deficiency CD59 in RBCs causes unregulated MAC formation, instigating a complement-dependent process of intravascular hemolysis.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e Therefore, we posit that aberrations in the complement and immune systems in PNH have a profound impact on erythrocytes. Consequently, we conducted an in-depth analysis of the differences between PNH CD59+/CD59- cells and normal controls in the C3 and C6 erythroid clusters associated with immunity. Discrepancies among the three groups in the C3 cluster primarily focused on cell cycle and transcription, leading us to concentrate on the C6 group. In our investigation, we observed that in the C6 cluster, the upregulated genes in the positive group, compared with those in the negative and control groups, were predominantly enriched in immune-related pathways. Hence, we contend that positive cells in the C6 group of erythrocytes in PNH play a dominant role in erythroid cell immunity.\u003c/p\u003e\u003cp\u003eTo further explore the underlying causes of this phenomenon, we conducted a comparative analysis using the immune and PNH databases and identified five genes, AHNAK, CCL5, IL32, CD3E, and IL2RG, which may play crucial roles in this process. AHNAK was initially identified as a large tumor-associated nuclear protein in the neuroblastoma cell type.\u003csup\u003e44\u003c/sup\u003e Over the past decade, increasing evidence has shown its involvement in muscle regeneration, tumor suppression, cellular structure, and calcium homeostasis.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e CCL5/CCR5 are well-recognized for their roles in promoting inflammatory responses and facilitating the adhesion and migration of different T cell subsets during immune reactions. Furthermore, recent studies have implicated the interaction between CCL5 and CCR5 in various pathological processes, including inflammation, chronic diseases, cancer, and COVID-19 infection.\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e IL32 is a cytokine involved in inflammation and cancer development. It is selectively expressed by activated T and NK cells. Early studies indicated that IL32 plays a role in regulating cell growth, metabolism, and immune modulation, thus contributing to pathophysiological regulation or protection against inflammatory diseases.\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e CD3E is a component of the TCR-CD3 complex found on the surface of T lymphocytes and plays a crucial role in adaptive immune responses17. Upon antigen presentation, T-cell receptor (TCR) activation triggers the signaling mediated by CD3D, CD3E, CD3G, and CD3Z across the cell membrane\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. IL2RG is a common subunit of various IL receptors. IL15RA may play a role in stimulating the phagocytic activity of neutrophils via IL15.\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e In this study, we found that the mRNA levels of IL32 and IL2RG were positively correlated with CD3\u0026thinsp;+\u0026thinsp;CD4+/T cells, whereas the mRNA content of CD3E was positively correlated with class-switched memory B cells/B cell%; The mRNA content of CCL5 was positively correlated with CD19+%, CD19/Lym%, and Treg/CD3\u0026thinsp;+\u0026thinsp;CD4\u0026thinsp;+\u0026thinsp;cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). Therefore, we speculated that these genes may play a role in the immunity of PNH erythroid cells, providing new insights for future research.\u003c/p\u003e\u003cp\u003ePNH is a rare disease, according to statistics, the global incidence rate is 1\u0026ndash;2/1\u0026nbsp;million people/year, and the prevalence rate is 10\u0026ndash;20/1\u0026nbsp;million. Therefore, our research includes a limited number of PNH patients. At present, our research team is trying to expand the research queue to ensure the robustness and repeatability of the research results,\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn conclusion, through single-cell sequencing analysis of red cell fractions in the bone marrow mononuclear cells of patients with PNH with CD59+/CD59- or normal controls, we identified a subset of red cells with immune functions. Furthermore, we observed enhanced immune functions in CD59\u0026thinsp;+\u0026thinsp;cells in patients with PNH within this subset. By examining the potentially involved genes, our study offers a novel direction and perspective on the immune mechanisms of the erythroid lineage in PNH.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\u003cp\u003e All patients provided written informed consent before enrollment. This study protocol was reviewed and approved by the Ethics Committee of General Hospital of Tianjin Medical University, approval number ZYY-IRB-SOP-016(F)-002-04.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding Statement\u003c/h2\u003e\u003cp\u003eThis work was supported by the National Natural Science Foundation Project (grant no.82270142), Tianjin Municipal Natural Science Foundation (grant no. 24ZGSSSS00050), Tianjin Science and Technology Planning Project (grant no. 24ZXGZSY00090), and Tianjin Municipal Health Commission Project (grant no. TJWJ2023XK003).\u003c/p\u003e\u003ch2\u003eAuthor contributions\u003c/h2\u003e\u003cp\u003eLiyan Li and Junshu Wu performed the research and wrote the paper, Hui Liu, Wei Wang, Chaomeng Wang, Zhaoyun Liu, Yingying Chen and Honglei Wang contributed essential reagents and help analysed the data, Rong Fu designed the research study.\u003c/p\u003e\u003ch2\u003eData availability statement\u003c/h2\u003e\u003cp\u003eAll data generated or analyzed during this study are included in this article, but these research data are not publicly available on ethical grounds. Further enquiries can be directed to the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHill A, DeZern AE, Kinoshita T, Brodsky RA. Paroxysmal nocturnal haemoglobinuria. Nat Rev Dis Primers. 2017;3:17028.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKinoshita T, Fujita M. Thematic Review Series: Glycosylphosphatidylinositol (GPI) Anchors: Biochemistry and Cell Biology Biosynthesis of GPI-anchored proteins: special emphasis on GPI lipid remodeling. J Lipid Res. 2016;57(1):6\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLuzzatto L. PNH phenotypes and their genesis. Br J Haematol. 2020;189(5):802\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNavenot JM, Muller JY, Blanchard D. Investigation of the survival of paroxysmal nocturnal hemoglobinuria red cells through the immunophenotyping of reticulocytes. Transfusion. 1998;38(4):337\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRosse WF. The Life-span of Complement-sensitive and -insensitive Red Cells in Paroxysmal Nocturnal Hemoglobinuria. Blood. 1971;37(5):556\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFerreira VP, Pangburn MK. Factor H\u0026ndash;mediated cell surface protection from complement is critical for the survival of PNH erythrocytes. Blood. 2007;110(6):2190\u0026ndash;2.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJalink M, de Boer ECW, Evers D, Havinga MQ, Vos JMI, Zeerlede S, et al. Halting targeted and collateral damage to red blood cells by the complement system. Semin Immunopathol. 2021;43(6):799\u0026ndash;816.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrodsky RA. How I treat paroxysmal nocturnal hemoglobinuria.Blood. 2021;137(10):1304\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFreitas Leal JK, Preijers F, Brock R, Adjobo-Hermans M, Bosman G. Red Blood Cell Homeostasis and Altered Vesicle Formation in Patients With Paroxysmal Nocturnal Hemoglobinuria. Front Physiol. 2019;10.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStyliani K, Gavriilaki E, Miari A, Anthi, Travlou4, Kyriakou E, et al. Renal involvement in paroxysmal nocturnal hemoglobinuria: an update on clinical features, pathophysiology and treatment. Hematology. 2018;23(8):558\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXu C, He J, Wang H, Zhang Y, Wu J, Zhao L, et al. Single-cell transcriptomic analysis identifies an immune-prone population in erythroid precursors during human ontogenesis. Nat Immunol. 2022;23(7):1109\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eElahi S. Neglected Cells: Immunomodulatory Roles of CD71\u0026thinsp;+\u0026thinsp;Erythroid Cells. Trends Immunol. 2019;40(3):181\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eElahi S. New insight into an old concept: role of immature erythroid cells in immune pathogenesis of neonatal infection. Front Immunol. 2014;5:376.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMo WT, Huang CF, Sun ZJ. Erythroid progenitor cell modulates cancer immunity: Insights and implications. Biochimica et Biophysica Acta (BBA) - Reviews on Cancer. 2024;1879(6):189209.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKohei Hosokawa S, Kajigaya K, Keyvanfar W, Qiao Y, Xie A, Biancotto, et al. Whole transcriptome sequencing identifies increased CXCR2 expression in PNH granulocytes. Br J Haematol. 2017;177(1):136\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKohei Hosokawa S, Kajigaya K, Keyvanfar W, Qiao Y, Xie, Danielle M, Townsley, et al. T Cell Transcriptomes from Paroxysmal Nocturnal Hemoglobinuria Patients Reveal Novel Signaling Pathways. J Immunol. 2017;199(2):477\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNiu C, Zhang J. Immunoregulation role of the erythroid cells. Front Immunol. 2024;15:1466669.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNELSON RA Jr.. The immune-adherence phenomenon; an immunologically specific reaction between microorganisms and erythrocytes leading to enhanced phagocytosis. Science. 1953;118(3077):733\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePavia CS, Stites DP. Immunosuppressive activity of murine newborn spleen cells. I. Selective inhibition of in vitro lymphocyte activation. Cell Immunol. 1979;42(1):48\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ede Macario E, Macario AJ. Immunosuppression associated with erythropoiesis in genetic low responder mice. Ann Immunol (Paris). 1980;131C(3):397\u0026ndash;404.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTsyrlova IG. Erythroid immunosuppressor cells (Er suppressors) and their role in the regulation of immunity. Vestn Akad Med Nauk SSSR. 1991;(12):34\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGrzywa TM, Nowis D, Golab J. The role of CD71\u0026thinsp;+\u0026thinsp;erythroid cells in the regulation of the immune response. Pharmacol Ther. 2021;228:107927.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eElahi S, Ertelt JM, Kinder JM, Jiang TT, Zhang X, Xin L, et al. Immunosuppressive CD71\u0026thinsp;+\u0026thinsp;erythroid cells compromise neonatal host defence against infection. Nature. 2013;504(7478):158\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDunsmore G, Bozorgmehr N, Delyea C, Koleva P, Namdar A, Elahi S. Erythroid Suppressor Cells Compromise Neonatal Immune Response against Bordetella pertussis. J Immunol. 2017;199(6):2081\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNamdar A, Koleva P, Shahbaz S, Strom S, Gerdts V, Elahi S. CD71\u0026thinsp;+\u0026thinsp;erythroid suppressor cells impair adaptive immunity against Bordetella pertussis. Sci Rep. 2017;7(1):7728.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eElahi S, Mashhouri S. Immunological consequences of extramedullary erythropoiesis: immunoregulatory functions of CD71\u0026thinsp;+\u0026thinsp;erythroid cells. Haematologica. 2020;105(6):1478\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhao L, He R, Guo HLB, Jia Q, Qin D, et al. Late-stage tumors induce anemia and immunosuppressive extramedullary erythroid progenitor cells. Nat Med. 2018;24(10):1536\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYasuyo Sano T, Yoshida M-K, Choo Y, Jim\u0026eacute;nez-Andrade KR, Hill K, Georgopoulos, et al. Multiorgan Signaling Mobilizes Tumor-Associated Erythroid Cells Expressing Immune Checkpoint Molecules. Mol Cancer Res. 2021;19(3):507\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen J, Qiao Y-D, Li X, Xu J-L, Ye Q-J, Jiang N, et al. Intratumoral CD45\u0026thinsp;+\u0026thinsp;CD71\u0026thinsp;+\u0026thinsp;erythroid cells induce immune tolerance and predict tumor recurrence in hepatocellular carcinoma. Cancer Lett. 2021;499:85\u0026ndash;98.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ede Peffault R, Risitano AM. Complement inhibition in medicine: Hematology and beyond; complement inhibition in hematology: PNH and beyond. Am J Hematol. 2023;98(S4):S3\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRisitano AM, Frieri C, Urciuoli E, Marano L. The complement alternative pathway in paroxysmal nocturnal hemoglobinuria: From a pathogenic mechanism to a therapeutic target. Immunol Rev. 2023;313(1):262\u0026ndash;78.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNicholson-Weller A, March JP, Rosenfeld SI, Austen KF. Affected erythrocytes of patients with paroxysmal nocturnal hemoglobinuria are deficient in the complement regulatory protein, decay accelerating factor. Proc Natl Acad Sci U S A. 1983;80(16):5066\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHolguin MH, Fredrick LR, Bernshaw NJ, Wilcox LA, Parker CJ. Isolation and characterization of a membrane protein from normal human erythrocytes that inhibits reactive lysis of the erythrocytes of paroxysmal nocturnal hemoglobinuria. J Clin Invest. 1989;84(1):7\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLehto T, Meri S. Interactions of soluble CD59 with the terminal complement complexes. CD59 and C9 compete for a nascent epitope on C8. J Immunol. 1993;151(9):4941\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShtivelman E, Cohen FE, Bishop JM. A human gene (AHNAK) encoding an unusually large protein with a 1.2-microns polyionic rod structure. Proc Natl Acad Sci U S A. 1992;89(12):5472\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDavis TA, Loos B, Engelbrecht AM. AHNAK: The giant jack of all trades. Cell Signal. 2014;26(12):2683\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZeng Z, Lan T, Wei Y, Wei X. CCL5/CCR5 axis in human diseases and related treatments. Genes Dis. 2022;9(1):12\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAldinucci D, Borghese C, Casagrande N. The CCL5/CCR5 Axis in Cancer Progression. Cancers (Basel). 2020;12(7):1765.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHong JT, Son DJ, Lee CK, Yoon DY, Lee DH, Park MH. Interleukin 32, inflammation and cancer. Pharmacol Ther. 2017;174:127\u0026ndash;37.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ede Albuquerque R, Komsi E, Starskaia I, Ullah U, Lahesmaa R. The role of Interleukin-32 in autoimmunity. Scand J Immunol. 2021;93(2):e13012.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBarber EK, Dasgupta JD, Schlossman SF, Trevillyan JM, Rudd CE. The CD4 and CD8 antigens are coupled to a protein-tyrosine kinase (p56lck) that phosphorylates the CD3 complex. Proc Natl Acad Sci U S A. 1989;86(9):3277\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRatth\u0026eacute; C, Girard D. Interleukin-15 enhances human neutrophil phagocytosis by a Syk-dependent mechanism: importance of the IL-15Ralpha chain. J Leukoc Biol. 2004;76(1):162\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLisa Kalman ML, Lindegren L, Kobrynski R, Vogt H, Hannon JT, Howard, et al. Mutations in genes required for T-cell development: IL7R, CD45, IL2RG, JAK3, RAG1, RAG2, ARTEMIS, and ADA and severe combined immunodeficiency: HuGE review. Genet Med. 2004;6(1):16\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"orphanet-journal-of-rare-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ojrd","sideBox":"Learn more about [Orphanet Journal of Rare Diseases](http://ojrd.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ojrd/default.aspx","title":"Orphanet Journal of Rare Diseases","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Paroxysmal nocturnal hemoglobinuria, erythroid cells, immune, scRNA-seq","lastPublishedDoi":"10.21203/rs.3.rs-7363120/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7363120/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e\u003cp\u003ePNH is complement mediated intravascular hemolysis, the mechanism of intrinsic immune-like transcriptional programs within erythroid remains unclear.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eBone marrow samples were collected from patients with PNH and healthy controls. CD59-/+ cells were isolated for single-cell sequencing analysis, based on differential gene markers, erythroid cells were classified into six groups.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eFunctional analysis revealed that groups C0, C1, C4, and C5 were primarily enriched in co-translational proteins that target the membrane, RNA catabolic processes, ribonucleoprotein complex biogenesis, and ATP metabolic process pathways. Groups C3 and C6 were associated with T-cell activation and antigen processing. Further investigation of groups C3 and C6 revealed that upregulated genes in the positive cells of PNH are enriched in immune-related pathways. Subsequent cross-enrichment analysis using immune and GEO databases identified five genes, namely AHNAK, CCL5, IL32, CD3E, and IL2RG, that may play a role in this process. Our analysis revealed a correlation between mRNA levels of IL32, IL2RG, CD3E, and CCL5 in the CD235a-positive cells of patients and their immunological markers.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eA subset of erythroid cells with immune functions was identified in PNH, and gene upregulation was predominantly observed in CD59\u0026thinsp;+\u0026thinsp;cells. We examined five genes which may play a role in this process and may offer novel insights for future investigations.\u003c/p\u003e","manuscriptTitle":"Single-cell transcriptomic analysis identifies an immune erythroid in paroxysmal nocturnal hemoglobinuria","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-08 07:06:54","doi":"10.21203/rs.3.rs-7363120/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-09-24T06:07:05+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Orphanet Journal of Rare Diseases","date":"2025-09-15T06:16:35+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-14T05:27:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"Orphanet Journal of Rare Diseases","date":"2025-08-13T05:16:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"orphanet-journal-of-rare-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ojrd","sideBox":"Learn more about [Orphanet Journal of Rare Diseases](http://ojrd.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ojrd/default.aspx","title":"Orphanet Journal of Rare Diseases","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0e52fd77-485a-48dc-b56d-ae6d83e9b626","owner":[],"postedDate":"October 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-10-08T07:06:54+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-08 07:06:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7363120","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7363120","identity":"rs-7363120","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}