Monocyte Activation Drives Atrial Fibrillation in Hypertension

Monocyte Activation Drives Atrial Fibrillation in Hypertension | 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 Monocyte Activation Drives Atrial Fibrillation in Hypertension Qian-wan Deng, Zi-qi Xu, Wei Zhang, Yuan-yuan Kang, Wu-wei Rong, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7748595/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Mar, 2026 Read the published version in Cardiovascular Drugs and Therapy → Version 1 posted 5 You are reading this latest preprint version Abstract BACKGROUND: Atrial fibrillation (AF) is the most common cardiac arrhythmia, with hypertension as its primary risk factor. While immune dysfunction is known to play a crucial role in hypertension, its specific impact on AF in the hypertensive setting remains underexplored. This study aims to elucidate the immune landscape of AF in the context of hypertension and explore the potential mechanisms. METHODS: Single-cell RNA transcriptomic analysis was employed to profile peripheral blood mononuclear cells (PBMCs) in hypertensive patients with AF, using hypertensive patients without AF as controls. Flow cytometry, serum cytokine analysis, and cohort studies were used for validation. RESULTS: Monocytes were identified as the most significantly affected cell type in hypertensive patients with AF, showing heightened disruption of cholesterol homeostasis and immune-inflammatory responses. Interestingly, a unique cluster of monocyte–platelet aggregates (MPAs) were identified to exhibit the most active intercellular interactions. Flow cytometry confirmed elevated proportions of CD14 + monocytes and MPAs in hypertensive patients with AF. Serum analysis of a larger cohort revealed significantly higher levels of monocyte chemoattractant protein-1 (MCP-1) and interleukin-6 (IL-6). Integration of single-cell data from blood and cardiac tissue confirmed enhanced monocyte recruitment and differentiation in hypertensive patients with AF. Cohort studies further supported that the increased number of circulating monocytes was associated with a higher incidence of AF in hypertensive patients. CONCLUSIONS: Our study demonstrated that monocyte activation-mediated inflammatory response may play an important role in the pathogenesis of AF in hypertension. These findings offer new insights into potential therapeutic targets for managing AF in hypertensive patients. Atrial fibrillation Hypertension Monocytes Single-cell RNA sequencing Inflammation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 BACKGROUND Atrial fibrillation (AF) is a predominant cardiac arrhythmia and associated with detrimental clinical outcomes. 1 – 3 Hypertension is the leading contributor to AF, accounting for the highest population-attributable fraction among all studied risk factors. 4 Despite the well-established connection between hypertension and AF, the specific mechanisms underlying the development of AF in hypertensive patients remain elusive. In patients with hypertension, atrial remodeling and activation of the renin-angiotensin system (RAAS) are considered the two primary mechanisms driving the development of AF. 5 Treatments designed to mitigate the effects of RAAS or the sympathetic nervous system (SNS) on blood pressure are notably ineffective in about 40% of cases. 6 – 8 An increasing body of evidence suggests that atrial fibrillation in hypertensive patients may represent a biologically distinct subtype. 9 These findings highlight the critical need for a deeper understanding of the precise mechanisms of AF in hypertension. Inflammation is a major contributor to cardiovascular risk, with growing evidence highlighting its significance in hypertension and AF. 10 The current understanding suggests that inflammatory cells initiate chronic inflammation, disrupting blood pressure regulation and leading to hypertension and its complications. 11 , 12 Inflammation in AF pathophysiology is supported by the presence of monocytes/ macrophages and proteins that drive inflammatory responses in cardiac tissue and circulation. 13 Moreover, inflammation in the heart or systemic circulation is a predictor of AF onset and recurrence, both in the general population and in patients after cardiac surgery, cardioversion, and catheter ablation. 13 , 14 Understanding the complex pathophysiological processes and dynamic changes of hypertension-related inflammation may aid in identifying specific anti-inflammatory strategies for preventing AF in hypertensive patients. Recent breakthroughs in single-cell RNA sequencing (scRNA-seq) have transformed our understanding of inflammatory cells in cardiovascular diseases, powered by its capacity for multidimensional, unbiased data collection from individual cells. 10 , 15 – 17 These innovations have expanded our grasp of the functional diversity within inflammatory responses. Yet, the role of circulating cells in atrial fibrillation (AF) remains insufficiently explored, underscoring the need for more targeted investigations. In this study, we applied single-cell RNA sequencing to investigate the peripheral blood mononuclear cells (PBMCs) landscape in hypertensive patients with atrial fibrillation (AF). We discovered significant cholesterol homeostasis changes in monocytes and identified a novel monocyte–platelet aggregates (MPAs) subpopulations, accompanied by monocyte chemoattractant protein-1 (MCP-1) and interleukin-6 (IL-6) expression. Increased number of circulating monocytes was associated with a higher incidence of AF in hypertensive patients. These findings emphasize the reinforced role of monocyte activation in the development of AF in hypertension and suggest new potential therapeutic targets. METHODS Data Availability Raw and processed human PBMC scRNA-seq data are available at the NCBI Gene Expression Omnibus (GEO) database under accession no. GSE285199. Processed human cardiac scRNA-seq data used for comparison are available under accession no. GSE224959. 16 The data that support the findings of this study are available from the corresponding author upon reasonable request. All details of experimental methods are described in the Supplemental Methods. Statistical Analysis The statistical analysis of the experimental data was conducted using GraphPad Prism version 9 (La Jolla, CA, USA). The normality of the data was assessed using the Shapiro-Wilk test to determine if it followed a normal distribution. Results are presented as means ± SD. Comparisons between two groups (e.g., flow cytometry and ELISA data) were performed using unpaired two-tailed Student’s t-tests. A significance level of P < 0.05 was used for all statistical tests. RESULTS 1. Immune Cell Function, Differentiation, and Intercellular Communication in Hypertensive Patients with Atrial Fibrillation We performed single-cell RNA sequencing on immune cells from blood samples of 6 individuals, including 4 hypertensive patients with AF and 2 hypertensive patients. To minimize intra-group variability and better control for single variables, we selected elderly male patients aged 65–75 with primary hypertension, excluding those with secondary causes such as aldosteronism, renal artery stenosis, or coronary heart disease, including coronary artery atherosclerosis (Supplementary Table). Morning blood samples were collected for single-cell RNA sequencing using the 10X Genomics platform to characterize the overall cellular landscape, identify key populations, and perform subpopulation analyses with validation in patient cohorts (Fig. 1 A). After quality control and merging, a total of 47,264 cells were included for further analysis. To explore the cellular landscape, we performed clustering analysis using the Seurat package. At the optimal resolution, 16 distinct clusters were identified and annotated based on markers reported in recent high-quality single-cell studies (Fig. 1 B, C). 18–20 The PBMC composition was categorized into T and NK cells, myeloid cells (monocytes and dendritic cells), and B cells/plasmablasts. T cells were further divided into subclusters, including CD4 + naïve cells (CCR7 + IL7R + ), central memory T cells (CD44 + IL7R + CCR7 + ), Tregs (FOXP3 + ), GZMK + CD8 + T cells, and cytotoxic T cells (NKG7 + CD8A + ). 21 NK cells were characterized by KLRF1, NKG7, and FGCR3A expression, with a subgroup expressing high levels of PTGDS, suggesting possible senescence. 22 Within the myeloid compartment, we identified CD14⁺ and CD16⁺ monocytes, as well as a subset of CD14⁺CD41⁺ monocyte–platelet aggregates (MPAs) and a distinct population of CD14^dim S100A8⁺ inflammatory monocytes, characterized by high S100A8 expression and molecular features consistent with pro-inflammatory functions. 23 – 28 Both cDCs and pDCs were identified, along with a small group of ASDCs (AXL + SIGLEC6 + ). 29 B cells and plasmablasts constituted a minor part of the PBMCs (Fig. 1 B, C). 30,31 To further characterize the functional profiles of each cell type, we performed gene enrichment analysis. Monocytes were enriched for myeloid leukocyte activation and differentiation processes, and dendritic cells were associated with antigen processing and presentation pathways. NK cells were enriched for cytotoxicity-related processes, including natural killer cell–mediated cytotoxicity and viral response pathways. T cell subsets were associated with pathways related to T cell differentiation and receptor signaling, whereas B cells were primarily associated with B cell activation and B cell receptor signaling (Fig. 1 D). Velocyto analysis revealed differentiation primarily within each lineage, with monocytes showing the highest transcriptional activity and the most reliable trajectories, as indicated by velocity length and confidence scores, while other cell types also displayed consistent but lower activity (Fig. 1 E). Cell-cell communication analysis using the CellChat package revealed that myeloid cells exhibited the most active interactions with other populations, with four distinct functional signaling patterns identified, among which pattern 1—dominated by myeloid cells—showed the highest signaling activity (Fig. 1 F, G). Notably, the hypertension with AF group showed both a higher overall number and stronger intensity of cellular interactions than the hypertension-only group, with myeloid cells—including monocytes and dendritic cells—engaging in the most interactions among immune populations (Supplementary Figure. 1A, B). In summary, the PBMCs exhibited pronounced inflammatory features, with monocytes showing particularly high transcriptional activity and signaling interactions, highlighting the heterogeneity between the hypertension with AF and hypertension-only groups and warranting further subpopulation-level investigation. 2. Subpopulation Analysis Reveals Limited Involvement of T and NK Cells in Hypertensive Atrial Fibrillation T cells and NK cells constitute the largest proportion of peripheral blood immune cells. Secondary clustering of these groups revealed masked details, including CD4 + T naïve cells (CD4 + CCR7 + ), Tregs (CD4 + FOXP3 + ), cytotoxic T cells (CD8 + GNLY + GZMB + ), and NK cells (CD8 − GNLY + GZMB + ). Other subgroups included Monolike CD4 + T, CD8 + effector-memory T cells (CD8 + TEM, CD8 + CCL5 + ), mucosal-associated invariant T (MAIT) cells (CD8 + effector memory phenotype, CD161 + ), rare γδT cells (CD3 + CD4 − CD8 − NCAM1 + ), and proliferative T cells (PCNA + ) (Supplementary Figure. 2A, B). Velocity analysis showed continuous trajectories for naïve T cells, Tregs, MAIT, and CD8 + TEM cells, while cytotoxic T cells shared a trajectory with NK cells, indicating a close relationship (Supplementary Figure. 2C). Differential gene expression (DEG) analysis between hypertensive patients with and without AF revealed significant DEGs in NK cells, cytotoxic T cells, and CD4 + naïve cells, with less significant DEGs in other clusters (Supplementary Figure. 2D). Further examination of DEGs showed that HLA-DQA2 was significantly up-regulated in both cytotoxic T cells and CD16 + NK cells, which share a differentiation trajectory and express cytotoxic genes (Supplementary Figure. 2E). HLA-DQA2, part of the HLA-II molecule, is crucial for antigen presentation and immune response, with its polymorphisms linked to autoimmune diseases. 32 Enrichment analysis revealed significant activation of autophagy-related processes. KEGG pathways were enriched for autophagy, nucleocytoplasmic transport, and T cell–related pathways, including Th1, Th2, and Th17 cell differentiation and T cell receptor signaling. GO analysis highlighted vesicle transport and protein localization to organelles, along with nucleocytoplasmic and nuclear transport, suggesting enhanced cellular activity and secretion (Supplementary Figure. 2F, G). These findings suggest that T/NK cells may play a less prominent or secondary role in the pathogenesis of atrial fibrillation in hypertensive patients. 3. Elevated Cholesterol Pathway and Cell Interactions in Distinct Myeloid Subpopulations Linked to Atrial Fibrillation We identified 12 myeloid subpopulations in our dataset, including classical (CD14⁺CD16⁻), intermediate monocytes (CD14⁺CD16⁺), non-classical (CD16⁺) monocytes, IL7R⁺ monocytes (CD14⁺IL7R⁺), MPAs (CD14⁺PF4⁺), pDCs, and CD1C⁺ mDCs, along with several very rare clusters that were not further characterized (Fig. 2 A, C). Differential expression analysis between the two groups revealed that classical monocytes, non-classical monocytes, IL1Bhi monocytes, MPAs, IL7R⁺hi monocytes, and intermediate monocytes exhibited more dynamic transcriptional changes, with a greater number of significant DEGs compared to other subsets (Fig. 2 D). To explore which immune populations were associated with atrial fibrillation (AF), we analyzed gene sets related to AF from the Molecular Signatures Database (MSigDB) across all PBMC clusters. Among all cell types, monocytes—particularly CD14⁺ classical monocytes and MPAs—showed the strongest enrichment for AF-related genes (Fig. 2 B). This pattern was further supported by the heatmap of signature genes across all clusters, highlighting the predominant contribution of myeloid subpopulations to AF-associated transcriptional programs (Fig. 2 E). To investigate pathway-specific alterations in myeloid cells, we examined the results of CellChat analysis of intercellular signaling alongside GSEA-based enrichment. The results revealed markedly increased intercellular communication within the cholesterol signaling pathway in myeloid cells (Supplementary Fig. 3). To further validate and characterize this finding, we examined cholesterol-related gene sets from the GSEA database. Enrichment analysis showed that pathways related to cholesterol import, metabolism, and efflux were significantly represented in myeloid cells (Fig. 2 H). Analysis of the average expression of genes within these sets across hypertensive patients with and without atrial fibrillation further revealed that several key cholesterol-related genes were upregulated in the AF group, with ABCA1 showing the most pronounced increase, alongside LRPAP1, FDPS, and LIPA (Fig. 2 F, G), suggesting enhanced cholesterol-associated activity in myeloid cells during AF. 33–35 It is reported that cholesterol crosstalk between the monocyte-macrophage system and T cells may trigger CD8 + T cell exhaustion and induce metabolic reprogramming in diffuse large B cell lymphoma, but its specific role in atrial fibrillation and hypertension requires further investigation. 36 In summary, monocyte subpopulations were the principal contributors to AF-associated transcriptional signatures, with integrated analyses revealing enhanced cholesterol-related signaling and gene expression in the AF group. These findings suggest that dysregulated cholesterol metabolism in monocytes may play a key role in shaping immune responses in hypertension with AF. 4. The Role of MPAs in Immune Interactions Linked to Atrial Fibrillation in Hypertensive Patients In our previous analyses, we demonstrated the highly active role of myeloid cells, within which we identified a distinct population termed MPAs (monocyte-platelet aggregates), characterized by the co-expression of monocyte and platelet markers. This subset was characterized by the coexpression of monocyte marker CD14 and platelet markers PPBP (pro-platelet basic protein) and PF4 (platelet factor 4). CellPhoneDB analysis showed that MPAs had the highest number of cell–cell interactions (Figure. 3A). Differential expression analysis further revealed significant transcriptional changes between the two groups (Figure. 2D). These findings suggest that MPAs are functionally active and undergo significant alterations, particularly in the context of atrial fibrillation. PF4 expression was mainly observed in MPAs, with additional localized expression in subsets of IL7R⁺hi and intermediate monocytes (Figure. 3C). Trajectory analysis showed that the subset of MPAs with relatively low PF4 expression followed a differentiation path similar to CD14⁺ classical monocytes, whereas the subset with high PF4 expression shifted toward a trajectory resembling intermediate and IL7R⁺hi monocytes. Along this continuum, PF4 expression was also detected in subsets of intermediate and IL7R⁺hi monocytes (Figure. 3D). Consistent with reports of MPAs as an intermediate state in monocyte differentiation, these results indicate that PF4⁺ MPAs may represent a transitional population potentially contributing to monocyte inflammatory activation during the development of atrial fibrillation in hypertension. 24 Enrichment analysis showed that PF4-expressing MPAs were associated with coagulation and immune activation pathways, while IL7R⁺hi and intermediate monocytes were linked to ribosome biogenesis and lymphocyte-related signaling (Figure. 3B). These findings suggest functional heterogeneity of PF4⁺ monocytes, with potential roles in coagulation and inflammatory responses in hypertension-related atrial fibrillation. We next examined the pseudotime-dependent transcriptional dynamics of IL7R⁺hiMono, Intermediate-Mono, and MPA using scVelo. Heatmaps of the top velocity-associated genes revealed distinct yet partially overlapping expression programs across the three subpopulations. In MPAs, sequential activation of C5AR1, FTH1, CREB5, PRKX, ID2, and TLR2 was observed, forming a diagonal expression stripe along pseudotime, suggestive of a coordinated inflammatory and signaling response. 37 , 38 Intermediate-Mono and IL7R⁺hiMono displayed enriched expression of immune-regulatory and signaling genes. Notably, genes such as RNF144B, HLA-DRB1, ITGAM, and ANKRD55 were shared across multiple groups, supporting a continuous developmental trajectory rather than completely discrete clusters, in line with the trajectory analysis showing that PF4⁺ MPAs occupy an intermediate state between classical, intermediate, and IL7R⁺hi monocytes. 39 , 40 To further support these observations, we analyzed PBMCs from hypertensive patients with or without atrial fibrillation by flow cytometry. We identified CD14⁺, CD16⁺, and CD41⁺ populations, as well as CD14⁺CD41⁺ double-positive cells (Supplementary Figure. 4). The proportions of CD14⁺, CD41⁺, and CD14⁺CD41⁺ cells were significantly increased in patients with atrial fibrillation, whereas CD16⁺ cells showed no evident difference between groups (Figure. 3F). These results further support the involvement of PF4⁺ monocyte subsets in coagulation and inflammatory activation during hypertension-related atrial fibrillation. 5. Elevated Inflammatory Factors IL-6 and CCL2 in Hypertensive Patients with Atrial Fibrillation Previous studies have indicated that chronic inflammation plays a role in the pathogenesis of AF. 14 Building on our prior finding that myeloid cells, including monocytes and MPAs, are pivotal in AF among hypertensive patients, and in light of previous reports showing that the proportion of MPAs correlates positively with plasma levels of key inflammatory mediators IL-1β and TNF-α in patients with Kawasaki disease, 24 we sought to determine whether the serum concentration of inflammatory factors is altered in this context. After excluding patients with confounding diseases, we collected serum from 39 primary hypertension patients and 41 hypertensive patients with AF. We analyzed a panel of cytokines related to AF, including IL-1β, IL-2, IL-4, IL-6, IL-10, IL-12, IL-17A, IL-23, IFNγ, TNFα, G-CSF, and MCP-1 (Fig. 4 ). 41 Our results revealed that IL-6 and MCP-1 levels were significantly elevated in the AF group, whereas the other cytokines did not exhibit significant changes. MCP-1, also known as CCL2, is a well-established chemokine critical for monocyte recruitment, activation, and macrophage differentiation. 42 , 43 Recent research suggests that atrial macrophages are predominantly derived from circulating monocytes, with CCR2-dependent macrophage recruitment facilitating AF. 16 Our findings imply that elevated CCL2, in addition to CCR2, may contribute to the recruitment of monocytes and macrophages, thereby promoting AF. 44 IL-6 is a key mediator of immune regulation and has been reported to induce CCL2 expression, thereby promoting monocyte recruitment to sites of inflammation. 45 In summary, the increased expression of inflammatory factors, particularly IL-6 and CCL2, is a key factor in the development of atrial fibrillation in hypertensive patients. 6. Interaction and Differentiation of Peripheral and Cardiac Tissue Cells in Atrial Fibrillation On the basis of previous discovery that recruitment of CD14 + monocytes and MPAs increased, we performed a combined analysis of our peripheral data with recently released cardiac tissue single-cell data (GSE224959) of AF to investigate the interaction and differentiation of peripheral cells and cardiac tissue. 16 After quality control and removal of batch effect, we found that all cells could be clearly divided into respective clusters. Cells from peripheral and cardiac tissues are quite distinct from each other, but homogenous cell types from both sources (e.g., T/NK cells, monocytes, and macrophages) are positioned closely. This indicates that dimensionality reduction effectively revealed the similarities between these cells by positioning them together while distinguishing them based on their origins, thereby avoiding any confusion (Figure. 5A). To be specific, using canonical markers, we identified fibroblasts (FIBRO(T)), endothelial cells (ENDO(T)), smooth muscle cells (SMC(T)), T cells (T Cells(T)), NK cells (NK(T)), and two macrophage subtypes (MACRO_1(T) and MACRO_2(T)) in cardiac tissue. In peripheral blood, we identified T cells (CD4 + T(P) and CD8 + T(P)), NK cells (NK(P)), and myeloid cells (CD14 + MONO(P), CD16 + MONO(P), and DC(P)). The signature gene expression profiles validated the robust clustering of each cell type (Figure. 5A, B). To explore cell-cell communication between peripheral immune cells and cardiac tissue cells, we performed CellChat analysis and found that cardiac fibroblasts were the most active cluster, communicating extensively with all other clusters, including cells from peripheral and cardiac tissue (Figure. 5C). PROS signaling, a known regulator of cell survival and proliferation, was elevated in fibroblasts and SMCs, suggesting excessive fibrotic tissue production and atrial remodeling in AF. 46 Conversely, PTN signaling was increased in SMCs but slightly decreased in fibroblasts, potentially reducing extracellular matrix production and altering tissue remodeling. 47 This may indicate a compensatory mechanism, reflecting a complex interplay between disease-induced remodeling and the body's resistance to detrimental changes (Figure. 5D). Given the significant role of monocyte recruitment and differentiation, we conducted trajectory analysis to examine the differential trajectories of monocytes and macrophages. As expected, monocytes and DCs were positioned in the early stages of the trajectory, while macrophages occupied later stages, with MACRO_1 at the most mature end and MACRO_2 slightly earlier. The proportion of cells from the AF group was notably higher at the end of the trajectory, consistent with previous findings that AF involves increased recruitment of monocytes differentiating into macrophages (Figure. 5E). Heatmaps and dot plots along the trajectory further highlighted these features. Monocytes exhibited high expression of calprotectin (S100A8, S100A9, and S100A12), which is involved in the immune response. On the other side of the branch, cells expressed typical macrophage markers (C1QA, C1QB, C1QC), which encode the C1q protein subunits and are integral components of the complement system (Figure. 5F, G). 48,49 In conclusion, our results indicate that the recruitment of inflammatory monocytes and their differentiation into macrophages play a crucial role in atrial fibrillation (AF) in hypertensive patients. 7. Elevated Monocyte number in Hypertension-Related Atrial Fibrillation Next, we conducted a cross-sectional population study among Chinese residents aged 65 and older at a community health center in Shanghai. The mean monocyte count was significantly higher in patients with both hypertension and atrial fibrillation (n = 104) compared to those with hypertension alone (n = 4,356, 0.31 ± 0.06 vs. 0.28 ± 0.05 x 10^9/L, P < 0.0001, Figure. 6A). In a prospective study with a median follow-up of 2.1 years, 18 participants developed atrial fibrillation: 5 in the lower monocyte count group (< 0.35 x 10^9/L) and 13 in the higher monocyte count group (≥ 0.35 x10^9/L). A higher monocyte count was associated with a significant increase in the incidence of atrial fibrillation compared to a lower monocyte count (hazard ratio HR: 3.28; 95% confidence interval 1.14–9.43; P = 0.03) (Figure. 6B). Other clinical features of all candidates could be found in supplementary data. DISCUSSION In recent years, accumulating evidence suggests that inflammation mechanisms play an increasingly pivotal role in the pathogenesis of hypertension and AF. 11,41,50 However, limited studies have investigated the circulating immune landscape in hypertensive patients with AF. By profiling the gene signatures of individual immune cells in PBMCs from hypertensive patients with AF and control hypertensive patients, we identified activation of monocyte populations in those with AF. Specifically, a distinct population of MPAs in peripheral circulation, further supporting the involvement of PF4⁺ monocyte subsets in coagulation and inflammatory activation during hypertension-related atrial fibrillation. Moreover, an increased number of circulating monocytes was associated with a higher incidence of AF in hypertensive patients. These findings offer new insights into potential targets for treating AF in hypertensive patients. Monocytes and macrophages have long been implicated in the development of hypertension, as evidenced by their increased numbers and altered phenotypes in the vasculature, kidneys, heart, and brain across various disease models. 11 In this study, we observed significant gene expression changes across most monocyte subpopulations. Enrichment analysis of atrial fibrillation-related gene sets revealed that many of these genes are predominantly expressed in monocytes, underscoring their crucial role in the development of hypertensive AF. Circulating monocytes from hypertensive patients have been reported to display a pro-inflammatory phenotype, with elevated levels of cytokines such as IL-1β, IL-23, and IL-6. 51,52 Our data corroborate this observation, showing that approximately half of the monocytes exhibiting high levels of IL-1β. However, this pro-inflammatory phenotype was nearly identical between hypertensive patients with and without AF, with no significant differences in serum cytokine levels. Beyond the broader monocyte alterations, we identified a distinct subset of MPAs defined by the co-expression of CD14 and platelet markers. These cells displayed pronounced transcriptional activity with enrichment in coagulation and immune activation pathways, indicating functional engagement rather than passive platelet binding. Similar prothrombotic and inflammatory phenotypes have been described in other conditions such as COVID-19, where platelet–monocyte interactions drive immunothrombosis 23 , 53 . Consistent with this, our trajectory analysis showed that PF4⁺ MPAs occupy an intermediate state between classical and inflammatory monocytes, linking platelet-derived signals with monocyte differentiation 24 . Flow cytometry further confirmed an expansion of CD14⁺CD41⁺ double-positive cells in hypertensive patients with AF, underscoring the clinical relevance of this subset. Collectively, these findings suggest that MPAs represent a transitional population that promotes thromboinflammatory responses and may increase susceptibility to atrial fibrillation in hypertension. Given their distinct phenotype and functional profile, MPAs may serve as potential biomarkers or therapeutic targets in hypertension-related atrial fibrillation. Another important finding is that the cholesterol pathway in monocytes emerged as the most significantly altered in hypertensive patients with AF compared to those without AF. This pathway represents an intricate link between lipid metabolism and immune-inflammatory processes, making it difficult to disentangle the impact of cholesterol homeostasis from inflammatory changes. 54 , 55 In hypertensive patients with AF, the cholesterol efflux pathway is highly expressed and is known to regulate T cell activation. 36 Furthermore, a strong correlation has been observed between intracellular cholesterol homeostasis and CCR2 expression in monocytes. 54 , 56 Cholesterol accumulation leads to increased expression of efflux mediators such as ABCA1, which have a pro-inflammatory effect on circulating monocytes. 57 Our results show that ABCA1 expression is significantly elevated in the hypertension with AF group. The uptake of native LDL (low-density lipoprotein cholesterol) in monocytes elicits increased CCR2 expression and enhances monocyte chemotaxis. 58 Medications targeting cholesterol homeostasis, such as statins and PCSK9 mAbs, have been shown to reduce monocyte recruitment. Emerging evidence suggests that inflammation plays a significant role in AF pathogenesis, as indicated by elevated serum levels of various inflammatory biomarkers in AF patients. 59 An intriguing finding in our study is the notable upregulation of MCP-1 and IL-6 in the serum of hypertensive patients with AF compared to controlsMCP-1 is secreted by infected, stressed or damaged heart tissue and binds to CC chemokine receptor 2 (CCR2), leading to the accumulation of monocytes at sites of inflammation. 51 IL-6 also plays a crucial role in regulating the differentiation and activation of monocytes into macrophages, working alongside MCP-1 to facilitate monocyte recruitment and activation. 45 Despite reports of elevated levels of several inflammatory factors, such as IL-1β, in AF and hypertension independently, we did not observe significant increases in these factors in the peripheral blood of hypertensive patients with AF. One possibility is that the changes in these inflammatory factors are subtle and may have been masked by our sample size. Another possibility is that lipid metabolic disturbances in monocytes, particularly in cholesterol homeostasis, contribute to their increased recruitment to the heart, reducing their presence in the peripheral blood. Extensive studies have established the critical role of adaptive immune cells in hypertension, with T cells often considered central to this process. 60 However, in our study comparing hypertensive patients with AF to hypertensive controls, significant differential expression was observed only in CD8 + cytotoxic T cells and NK cells, while other T cell subclusters showed negligible changes. Both CD8 + T cells and NK cells exhibited an activated phenotype in hypertensive patients with AF, characterized by immunosenescence and increased expression of perforin and granzyme B. 60,61 Although the precise mechanism linking perforin and granzyme B to hypertension remains unclear, their pro-apoptotic effects could trigger the release of DAMPs, which are key factors in the onset of atrial fibrillation. 14 , 41 A limitation of our study is its focus on peripheral blood monocytes, which may not fully capture the complexity of immune interactions occurring within cardiac tissue. Additionally, the sample size may limit the detection of subtle changes in inflammatory markers. Further research, including more extensive in vivo studies and tissue-specific analyses, is needed to confirm our findings and explore the precise mechanisms linking hypertension, lipid metabolism, and inflammation to atrial fibrillation. In conclusion, our study highlights the crucial role of monocytes in hypertension contributes to the development of atrial fibrillation.The elevated expression of cholesterol efflux mediators, alongside increased MPAs and inflammatory factors expression in peripheral bloodsuggests a synergistic interplay between lipid dysregulation and inflammation in promoting AF. These findings underscore the importance of targeting monocyte-driven inflammation in developing therapeutic strategies for AF in hypertensive patients. Declarations Author Declarations Funding This study received financial support from the National Natural Science Foundation of China (82030006, 82370426, 82270250, 82070435) and the National Key Research and Development Program (2022YFA1104200). Competing interests The authors declare that they have no competing interests. Availability of data and materials The dataset(s) supporting the conclusions of this article are available in the NCBI Gene Expression Omnibus (GEO) repository, accession numbers GSE285199 (raw and processed human PBMC scRNA-seq data, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE285199) and GSE224959 (processed human cardiac scRNA-seq data used for comparison, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE224959). Code availability The custom code used in this study is available from the corresponding author upon reasonable request. Authors’ contributions QWD analyzed the data, performed the experiments, and drafted the manuscript. ZQX performed the experiments. WZ performed the experiments and provided clinical samples. YYK, WWR, and JHX assisted with data analysis. PJG provided overall guidance. XDL and JGW supervised the study design and critically revised the manuscript. All authors read and approved the final manuscript. Ethics approval The study was approved by the Ethics Committee of Ruijin Hospital, Shanghai Jiao Tong University School of Medicine. All animal experiments were performed in accordance with institutional guidelines. Consent to participate All human participants provided written informed consent before sample collection. Consent for publication Not applicable. References Joglar, J. A. et al. 2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation 149 , e1-e156 (2024). https://doi.org/10.1161/cir.0000000000001193 Guo, Y., Imberti, J. F., Kotalczyk, A., Wang, Y. & Lip, G. Y. H. Atrial Fibrillation Better Care Pathway Adherent Care Improves Outcomes in Chinese Patients With Atrial Fibrillation. JACC Asia 2 , 422-429 (2022). https://doi.org/10.1016/j.jacasi.2022.01.007 Bilfinger, T. V., Almassi, G. H. & Shroyer, A. L. W. 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08:54:37","extension":"html","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":151246,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7748595/v1/71e01be07af427e634b2e1c1.html"},{"id":93569790,"identity":"9f37148b-db4e-4da3-8ae1-1c9e8ecd8255","added_by":"auto","created_at":"2025-10-15 08:54:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1557892,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComprehensive Analysis of PBMCs in Hypertensive Patients with and without Atrial Fibrillation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Single-cell RNA sequencing (scRNA-seq) was performed on peripheral blood mononuclear cells (PBMCs) from hypertensive patients with and without AF. The workflow included global analysis, subcluster analysis, and clinical validation.\u003c/p\u003e\n\u003cp\u003e(B) UMAP plot of all PBMCs, with clusters colored according to their identity.\u003c/p\u003e\n\u003cp\u003e(C) Dot plot showing the expression of signature genes across major cell types.\u003c/p\u003e\n\u003cp\u003e(D) Bar plot illustrating the results of Gene Ontology (GO) term analysis for the top 50 marker genes in each major cell type.\u003c/p\u003e\n\u003cp\u003e(E) RNA velocity stream plot showing dynamic transitions between major cell types, with velocity length indicating transcriptional activity and velocity confidence reflecting the local reliability of transition direction.\u003c/p\u003e\n\u003cp\u003e(F) Heatmap displaying the interaction counts among different major cell types.\u003c/p\u003e\n\u003cp\u003e(G) Alluvial plot visualizing the outgoing signaling patterns of secreting cells, showing the relationships between inferred latent patterns, cell groups, and signaling pathways. The flow's thickness reflects the contribution of each cell group or signaling pathway to the latent patterns, with the height of each pattern proportional to the number of associated cell groups or signaling pathways.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7748595/v1/ae63bae847773f1c3ee9a695.png"},{"id":93569800,"identity":"9e6d2f9b-3761-423c-a298-ff84f9a3912d","added_by":"auto","created_at":"2025-10-15 08:54:44","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1047092,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAlterations in Myeloid Cells in Hypertensive Patients with Atrial Fibrillation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) UMAP plot showing the subclusters of myeloid cells.\u003c/p\u003e\n\u003cp\u003e(B) Box plot displaying the scores of gene modules associated with atrial fibrillation in each cluster, as calculated by AddModuleScore.\u003c/p\u003e\n\u003cp\u003e(C) Dot plot representing the expression of signature genes across major myeloid cell types.\u003c/p\u003e\n\u003cp\u003e(D) Volcano plot illustrating differentially expressed genes (Bonferroni adjusted p-value \u0026lt; 0.01 and avg_log2FC \u0026gt; 0.5, shown in red) between hypertensive patients with and without AF.\u003c/p\u003e\n\u003cp\u003e(E) Heatmaps comparing the expression levels of genes within each module associated with atrial fibrillation between hypertensive patients without AF and those with AF.\u003c/p\u003e\n\u003cp\u003e(F) CellChat circle plot showing cholesterol pathway alterations between AFHTN and HTN groups.\u003c/p\u003e\n\u003cp\u003e(G) Heatmaps showing the expression of cholesterol homeostasis-related genes between the two groups, between hypertensive patients without AF (left) and those with AF (right).\u003c/p\u003e\n\u003cp\u003e(H) Box plot displaying the scores of cholesterol-related gene modules in each cluster, as calculated by AddModuleScore.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7748595/v1/f8b4b57442179f97bbea3036.png"},{"id":93569798,"identity":"b10d6295-ec4c-451c-af9e-b4379239c2dd","added_by":"auto","created_at":"2025-10-15 08:54:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2533410,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eInteraction Analysis and Differentiation Trajectories of Myeloid Cells in Hypertensive Patients with Atrial Fibrillation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Heatmap displaying the sum of significant interactions between all clusters, calculated by CellPhoneDB.\u003c/p\u003e\n\u003cp\u003e(B) Bar plot illustrating the GO term analysis results for the top 50 marker genes in PF4 expression clusters.\u003c/p\u003e\n\u003cp\u003e(C) Feature plot showing the localization of PF4 expression within myeloid cells.\u003c/p\u003e\n\u003cp\u003e(D) RNA velocity stream plot depicting the dynamic transitions within myeloid cells.\u003c/p\u003e\n\u003cp\u003e(E) Pseudotime heatmap of IL7R⁺hiMono, Intermediate-Mono, and MPA subpopulations showing top velocity-associated genes.\u003c/p\u003e\n\u003cp\u003e(F) Representative dot plots comparing the proportions of CD14+ cells, CD16+ cells, CD41+ cells, and CD14+CD41+ cells between hypertensive patients with and without AF, as well as their percentages among total PBMCs.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7748595/v1/d442f41e58698e182c71db96.png"},{"id":93569797,"identity":"d14f7e0c-3b43-482f-9e41-a98b4a377b2e","added_by":"auto","created_at":"2025-10-15 08:54:42","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":32345,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eQuantification of Inflammatory Biomarkers in Peripheral Blood of Hypertensive Patients with and without Atrial Fibrillation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePeripheral blood was collected from 39 patients with primary hypertension and 41 patients with both hypertension and AF. Inflammatory biomarkers (including G-CSF, IL-10, IL-13, IFNγ, IL-2, TNFα, IL-17A, IL-12p70, IL-4, IL-1β, MCP-1, IL-23p19, and IL-6) were quantified. Sample size varies per measurement due to exclusion of zero values. Initial sample sizes: hypertension without AF (n=39), hypertension with AF (n=41). *P\u0026lt;0.05; unpaired Student t test.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7748595/v1/ccad934a84d60e7b0cd60667.png"},{"id":93569757,"identity":"848fc83a-83e0-4ef8-b844-34523b70bfd5","added_by":"auto","created_at":"2025-10-15 08:54:33","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1175012,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIntegration and Analysis of PBMCs and Cardiac Tissue in Hypertension with Atrial Fibrillation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) UMAP plot showing the integration of PBMCs (P) and cardiac tissue cells (T).\u003c/p\u003e\n\u003cp\u003e(B) Dot plot depicting the expression of signature genes across major cell types.\u003c/p\u003e\n\u003cp\u003e(C) Heatmap illustrating the interaction counts within each major cell type.\u003c/p\u003e\n\u003cp\u003e(D) Circle plot displaying changes in signaling pathways between hypertension and hypertension with atrial fibrillation (AF).\u003c/p\u003e\n\u003cp\u003e(E) Pseudotime analysis revealing the differentiation trajectories of monocytes, dendritic cells (DCs), and macrophages, with bar plots showing the proportions of these cells in hypertension with and without AF.\u003c/p\u003e\n\u003cp\u003e(F) (G) Heatmap and dot plot presenting genes differentially expressed across pseudotime trajectory.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7748595/v1/c9af374c7583183984d8f5cb.png"},{"id":93569792,"identity":"3e3e18bf-280b-41ed-8b05-84843117cf38","added_by":"auto","created_at":"2025-10-15 08:54:39","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":93918,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eElevated monocytes count in relation to atrial fibrillation and hypertension in cross-sectional and prospective studies.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A): Bars indicate mean monocyte, neutrophiles, eosinophiles, and lymphocyte count in patients with both hypertension and atrial fibrillation (red) and hypertension alone (black). (B): Cumulative incidence of atrial fibrillation according to monocyte count. Shown is the cumulative incidence of atrial fibrillation in the lower (\u0026lt;0.35 x 10^9/L) and higher monocyte count group (≥0.35 x 10^9/L) with the use of a modified Kaplan-Meier approach.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-7748595/v1/217fa231885fa520a4e0c9c1.png"},{"id":105223587,"identity":"7234ab2f-8331-40f9-891e-8d06f8b4a201","added_by":"auto","created_at":"2026-03-23 16:08:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7719573,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7748595/v1/5eea05e6-4a1b-4fe9-a149-0c2c01390eb3.pdf"},{"id":93569803,"identity":"fa8799ac-6861-4747-a988-2d324d0f0956","added_by":"auto","created_at":"2025-10-15 08:54:45","extension":"docx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":2339236,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile.docx","url":"https://assets-eu.researchsquare.com/files/rs-7748595/v1/09af96d5f6f21aeba8f82149.docx"}],"financialInterests":"","formattedTitle":"Monocyte Activation Drives Atrial Fibrillation in Hypertension","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eAtrial fibrillation (AF) is a predominant cardiac arrhythmia and associated with detrimental clinical outcomes.\u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Hypertension is the leading contributor to AF, accounting for the highest population-attributable fraction among all studied risk factors.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Despite the well-established connection between hypertension and AF, the specific mechanisms underlying the development of AF in hypertensive patients remain elusive. In patients with hypertension, atrial remodeling and activation of the renin-angiotensin system (RAAS) are considered the two primary mechanisms driving the development of AF.\u003csup\u003e5\u003c/sup\u003e Treatments designed to mitigate the effects of RAAS or the sympathetic nervous system (SNS) on blood pressure are notably ineffective in about 40% of cases.\u003csup\u003e\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e An increasing body of evidence suggests that atrial fibrillation in hypertensive patients may represent a biologically distinct subtype.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e These findings highlight the critical need for a deeper understanding of the precise mechanisms of AF in hypertension.\u003c/p\u003e\u003cp\u003eInflammation is a major contributor to cardiovascular risk, with growing evidence highlighting its significance in hypertension and AF.\u003csup\u003e10\u003c/sup\u003e The current understanding suggests that inflammatory cells initiate chronic inflammation, disrupting blood pressure regulation and leading to hypertension and its complications.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Inflammation in AF pathophysiology is supported by the presence of monocytes/ macrophages and proteins that drive inflammatory responses in cardiac tissue and circulation.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e Moreover, inflammation in the heart or systemic circulation is a predictor of AF onset and recurrence, both in the general population and in patients after cardiac surgery, cardioversion, and catheter ablation.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e Understanding the complex pathophysiological processes and dynamic changes of hypertension-related inflammation may aid in identifying specific anti-inflammatory strategies for preventing AF in hypertensive patients.\u003c/p\u003e\u003cp\u003eRecent breakthroughs in single-cell RNA sequencing (scRNA-seq) have transformed our understanding of inflammatory cells in cardiovascular diseases, powered by its capacity for multidimensional, unbiased data collection from individual cells.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e These innovations have expanded our grasp of the functional diversity within inflammatory responses. Yet, the role of circulating cells in atrial fibrillation (AF) remains insufficiently explored, underscoring the need for more targeted investigations. In this study, we applied single-cell RNA sequencing to investigate the peripheral blood mononuclear cells (PBMCs) landscape in hypertensive patients with atrial fibrillation (AF). We discovered significant cholesterol homeostasis changes in monocytes and identified a novel monocyte\u0026ndash;platelet aggregates (MPAs) subpopulations, accompanied by monocyte chemoattractant protein-1 (MCP-1) and interleukin-6 (IL-6) expression. Increased number of circulating monocytes was associated with a higher incidence of AF in hypertensive patients. These findings emphasize the reinforced role of monocyte activation in the development of AF in hypertension and suggest new potential therapeutic targets.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eRaw and processed human PBMC scRNA-seq data are available at the NCBI Gene Expression Omnibus (GEO) database under accession no. GSE285199. Processed human cardiac scRNA-seq data used for comparison are available under accession no. GSE224959.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e The data that support the findings of this study are available from the corresponding author upon reasonable request. All details of experimental methods are described in the Supplemental Methods.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eThe statistical analysis of the experimental data was conducted using GraphPad Prism version 9 (La Jolla, CA, USA). The normality of the data was assessed using the Shapiro-Wilk test to determine if it followed a normal distribution. Results are presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Comparisons between two groups (e.g., flow cytometry and ELISA data) were performed using unpaired two-tailed Student\u0026rsquo;s t-tests. A significance level of P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was used for all statistical tests.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cb\u003e1. Immune Cell Function, Differentiation, and Intercellular Communication in Hypertensive Patients with Atrial Fibrillation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe performed single-cell RNA sequencing on immune cells from blood samples of 6 individuals, including 4 hypertensive patients with AF and 2 hypertensive patients. To minimize intra-group variability and better control for single variables, we selected elderly male patients aged 65\u0026ndash;75 with primary hypertension, excluding those with secondary causes such as aldosteronism, renal artery stenosis, or coronary heart disease, including coronary artery atherosclerosis (Supplementary Table). Morning blood samples were collected for single-cell RNA sequencing using the 10X Genomics platform to characterize the overall cellular landscape, identify key populations, and perform subpopulation analyses with validation in patient cohorts (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). After quality control and merging, a total of 47,264 cells were included for further analysis. To explore the cellular landscape, we performed clustering analysis using the Seurat package. At the optimal resolution, 16 distinct clusters were identified and annotated based on markers reported in recent high-quality single-cell studies (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB, C).\u003csup\u003e18\u0026ndash;20\u003c/sup\u003e The PBMC composition was categorized into T and NK cells, myeloid cells (monocytes and dendritic cells), and B cells/plasmablasts. T cells were further divided into subclusters, including CD4\u003csup\u003e+\u003c/sup\u003e na\u0026iuml;ve cells (CCR7\u003csup\u003e+\u003c/sup\u003eIL7R\u003csup\u003e+\u003c/sup\u003e), central memory T cells (CD44\u003csup\u003e+\u003c/sup\u003eIL7R\u003csup\u003e+\u003c/sup\u003eCCR7\u003csup\u003e+\u003c/sup\u003e), Tregs (FOXP3\u003csup\u003e+\u003c/sup\u003e), GZMK\u003csup\u003e+\u003c/sup\u003eCD8\u003csup\u003e+\u003c/sup\u003e T cells, and cytotoxic T cells (NKG7\u003csup\u003e+\u003c/sup\u003eCD8A\u003csup\u003e+\u003c/sup\u003e).\u003csup\u003e21\u003c/sup\u003e NK cells were characterized by KLRF1, NKG7, and FGCR3A expression, with a subgroup expressing high levels of PTGDS, suggesting possible senescence.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e Within the myeloid compartment, we identified CD14⁺ and CD16⁺ monocytes, as well as a subset of CD14⁺CD41⁺ monocyte\u0026ndash;platelet aggregates (MPAs) and a distinct population of CD14^dim S100A8⁺ inflammatory monocytes, characterized by high S100A8 expression and molecular features consistent with pro-inflammatory functions.\u003csup\u003e\u003cspan additionalcitationids=\"CR24 CR25 CR26 CR27\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e Both cDCs and pDCs were identified, along with a small group of ASDCs (AXL\u003csup\u003e+\u003c/sup\u003eSIGLEC6\u003csup\u003e+\u003c/sup\u003e).\u003csup\u003e29\u003c/sup\u003e B cells and plasmablasts constituted a minor part of the PBMCs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB, C).\u003csup\u003e30,31\u003c/sup\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo further characterize the functional profiles of each cell type, we performed gene enrichment analysis. Monocytes were enriched for myeloid leukocyte activation and differentiation processes, and dendritic cells were associated with antigen processing and presentation pathways. NK cells were enriched for cytotoxicity-related processes, including natural killer cell\u0026ndash;mediated cytotoxicity and viral response pathways. T cell subsets were associated with pathways related to T cell differentiation and receptor signaling, whereas B cells were primarily associated with B cell activation and B cell receptor signaling (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). Velocyto analysis revealed differentiation primarily within each lineage, with monocytes showing the highest transcriptional activity and the most reliable trajectories, as indicated by velocity length and confidence scores, while other cell types also displayed consistent but lower activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). Cell-cell communication analysis using the CellChat package revealed that myeloid cells exhibited the most active interactions with other populations, with four distinct functional signaling patterns identified, among which pattern 1\u0026mdash;dominated by myeloid cells\u0026mdash;showed the highest signaling activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF, G). Notably, the hypertension with AF group showed both a higher overall number and stronger intensity of cellular interactions than the hypertension-only group, with myeloid cells\u0026mdash;including monocytes and dendritic cells\u0026mdash;engaging in the most interactions among immune populations (Supplementary Figure. 1A, B). In summary, the PBMCs exhibited pronounced inflammatory features, with monocytes showing particularly high transcriptional activity and signaling interactions, highlighting the heterogeneity between the hypertension with AF and hypertension-only groups and warranting further subpopulation-level investigation.\u003c/p\u003e\u003cp\u003e\u003cb\u003e2. Subpopulation Analysis Reveals Limited Involvement of T and NK Cells in Hypertensive Atrial Fibrillation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eT cells and NK cells constitute the largest proportion of peripheral blood immune cells. Secondary clustering of these groups revealed masked details, including CD4\u003csup\u003e+\u003c/sup\u003e T na\u0026iuml;ve cells (CD4\u003csup\u003e+\u003c/sup\u003eCCR7\u003csup\u003e+\u003c/sup\u003e), Tregs (CD4\u003csup\u003e+\u003c/sup\u003eFOXP3\u003csup\u003e+\u003c/sup\u003e), cytotoxic T cells (CD8\u003csup\u003e+\u003c/sup\u003eGNLY\u003csup\u003e+\u003c/sup\u003eGZMB\u003csup\u003e+\u003c/sup\u003e), and NK cells (CD8\u003csup\u003e\u0026minus;\u003c/sup\u003eGNLY\u003csup\u003e+\u003c/sup\u003eGZMB\u003csup\u003e+\u003c/sup\u003e). Other subgroups included Monolike CD4\u003csup\u003e+\u003c/sup\u003eT, CD8\u003csup\u003e+\u003c/sup\u003e effector-memory T cells (CD8\u003csup\u003e+\u003c/sup\u003eTEM, CD8\u003csup\u003e+\u003c/sup\u003eCCL5\u003csup\u003e+\u003c/sup\u003e), mucosal-associated invariant T (MAIT) cells (CD8\u003csup\u003e+\u003c/sup\u003e effector memory phenotype, CD161\u003csup\u003e+\u003c/sup\u003e), rare γδT cells (CD3\u003csup\u003e+\u003c/sup\u003eCD4\u003csup\u003e\u0026minus;\u003c/sup\u003eCD8\u003csup\u003e\u0026minus;\u003c/sup\u003eNCAM1\u003csup\u003e+\u003c/sup\u003e), and proliferative T cells (PCNA\u003csup\u003e+\u003c/sup\u003e) (Supplementary Figure. 2A, B). Velocity analysis showed continuous trajectories for na\u0026iuml;ve T cells, Tregs, MAIT, and CD8\u003csup\u003e+\u003c/sup\u003e TEM cells, while cytotoxic T cells shared a trajectory with NK cells, indicating a close relationship (Supplementary Figure. 2C). Differential gene expression (DEG) analysis between hypertensive patients with and without AF revealed significant DEGs in NK cells, cytotoxic T cells, and CD4\u003csup\u003e+\u003c/sup\u003e na\u0026iuml;ve cells, with less significant DEGs in other clusters (Supplementary Figure. 2D). Further examination of DEGs showed that HLA-DQA2 was significantly up-regulated in both cytotoxic T cells and CD16\u003csup\u003e+\u003c/sup\u003e NK cells, which share a differentiation trajectory and express cytotoxic genes (Supplementary Figure. 2E). HLA-DQA2, part of the HLA-II molecule, is crucial for antigen presentation and immune response, with its polymorphisms linked to autoimmune diseases.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e Enrichment analysis revealed significant activation of autophagy-related processes. KEGG pathways were enriched for autophagy, nucleocytoplasmic transport, and T cell\u0026ndash;related pathways, including Th1, Th2, and Th17 cell differentiation and T cell receptor signaling. GO analysis highlighted vesicle transport and protein localization to organelles, along with nucleocytoplasmic and nuclear transport, suggesting enhanced cellular activity and secretion (Supplementary Figure. 2F, G). These findings suggest that T/NK cells may play a less prominent or secondary role in the pathogenesis of atrial fibrillation in hypertensive patients.\u003c/p\u003e\u003cp\u003e\u003cb\u003e3. Elevated Cholesterol Pathway and Cell Interactions in Distinct Myeloid Subpopulations Linked to Atrial Fibrillation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe identified 12 myeloid subpopulations in our dataset, including classical (CD14⁺CD16⁻), intermediate monocytes (CD14⁺CD16⁺), non-classical (CD16⁺) monocytes, IL7R⁺ monocytes (CD14⁺IL7R⁺), MPAs (CD14⁺PF4⁺), pDCs, and CD1C⁺ mDCs, along with several very rare clusters that were not further characterized (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, C). Differential expression analysis between the two groups revealed that classical monocytes, non-classical monocytes, IL1Bhi monocytes, MPAs, IL7R⁺hi monocytes, and intermediate monocytes exhibited more dynamic transcriptional changes, with a greater number of significant DEGs compared to other subsets (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). To explore which immune populations were associated with atrial fibrillation (AF), we analyzed gene sets related to AF from the Molecular Signatures Database (MSigDB) across all PBMC clusters. Among all cell types, monocytes\u0026mdash;particularly CD14⁺ classical monocytes and MPAs\u0026mdash;showed the strongest enrichment for AF-related genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). This pattern was further supported by the heatmap of signature genes across all clusters, highlighting the predominant contribution of myeloid subpopulations to AF-associated transcriptional programs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). To investigate pathway-specific alterations in myeloid cells, we examined the results of CellChat analysis of intercellular signaling alongside GSEA-based enrichment. The results revealed markedly increased intercellular communication within the cholesterol signaling pathway in myeloid cells (Supplementary Fig.\u0026nbsp;3). To further validate and characterize this finding, we examined cholesterol-related gene sets from the GSEA database. Enrichment analysis showed that pathways related to cholesterol import, metabolism, and efflux were significantly represented in myeloid cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH). Analysis of the average expression of genes within these sets across hypertensive patients with and without atrial fibrillation further revealed that several key cholesterol-related genes were upregulated in the AF group, with ABCA1 showing the most pronounced increase, alongside LRPAP1, FDPS, and LIPA (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF, G), suggesting enhanced cholesterol-associated activity in myeloid cells during AF.\u003csup\u003e33\u0026ndash;35\u003c/sup\u003e It is reported that cholesterol crosstalk between the monocyte-macrophage system and T cells may trigger CD8\u003csup\u003e+\u003c/sup\u003e T cell exhaustion and induce metabolic reprogramming in diffuse large B cell lymphoma, but its specific role in atrial fibrillation and hypertension requires further investigation.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e In summary, monocyte subpopulations were the principal contributors to AF-associated transcriptional signatures, with integrated analyses revealing enhanced cholesterol-related signaling and gene expression in the AF group. These findings suggest that dysregulated cholesterol metabolism in monocytes may play a key role in shaping immune responses in hypertension with AF.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e4. The Role of MPAs in Immune Interactions Linked to Atrial Fibrillation in Hypertensive Patients\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn our previous analyses, we demonstrated the highly active role of myeloid cells, within which we identified a distinct population termed MPAs (monocyte-platelet aggregates), characterized by the co-expression of monocyte and platelet markers. This subset was characterized by the coexpression of monocyte marker CD14 and platelet markers PPBP (pro-platelet basic protein) and PF4 (platelet factor 4). CellPhoneDB analysis showed that MPAs had the highest number of cell\u0026ndash;cell interactions (Figure. 3A). Differential expression analysis further revealed significant transcriptional changes between the two groups (Figure. 2D). These findings suggest that MPAs are functionally active and undergo significant alterations, particularly in the context of atrial fibrillation. PF4 expression was mainly observed in MPAs, with additional localized expression in subsets of IL7R⁺hi and intermediate monocytes (Figure. 3C). Trajectory analysis showed that the subset of MPAs with relatively low PF4 expression followed a differentiation path similar to CD14⁺ classical monocytes, whereas the subset with high PF4 expression shifted toward a trajectory resembling intermediate and IL7R⁺hi monocytes. Along this continuum, PF4 expression was also detected in subsets of intermediate and IL7R⁺hi monocytes (Figure. 3D). Consistent with reports of MPAs as an intermediate state in monocyte differentiation, these results indicate that PF4⁺ MPAs may represent a transitional population potentially contributing to monocyte inflammatory activation during the development of atrial fibrillation in hypertension.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eEnrichment analysis showed that PF4-expressing MPAs were associated with coagulation and immune activation pathways, while IL7R⁺hi and intermediate monocytes were linked to ribosome biogenesis and lymphocyte-related signaling (Figure. 3B). These findings suggest functional heterogeneity of PF4⁺ monocytes, with potential roles in coagulation and inflammatory responses in hypertension-related atrial fibrillation. We next examined the pseudotime-dependent transcriptional dynamics of IL7R⁺hiMono, Intermediate-Mono, and MPA using scVelo. Heatmaps of the top velocity-associated genes revealed distinct yet partially overlapping expression programs across the three subpopulations. In MPAs, sequential activation of C5AR1, FTH1, CREB5, PRKX, ID2, and TLR2 was observed, forming a diagonal expression stripe along pseudotime, suggestive of a coordinated inflammatory and signaling response.\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e Intermediate-Mono and IL7R⁺hiMono displayed enriched expression of immune-regulatory and signaling genes. Notably, genes such as RNF144B, HLA-DRB1, ITGAM, and ANKRD55 were shared across multiple groups, supporting a continuous developmental trajectory rather than completely discrete clusters, in line with the trajectory analysis showing that PF4⁺ MPAs occupy an intermediate state between classical, intermediate, and IL7R⁺hi monocytes.\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eTo further support these observations, we analyzed PBMCs from hypertensive patients with or without atrial fibrillation by flow cytometry. We identified CD14⁺, CD16⁺, and CD41⁺ populations, as well as CD14⁺CD41⁺ double-positive cells (Supplementary Figure. 4). The proportions of CD14⁺, CD41⁺, and CD14⁺CD41⁺ cells were significantly increased in patients with atrial fibrillation, whereas CD16⁺ cells showed no evident difference between groups (Figure. 3F). These results further support the involvement of PF4⁺ monocyte subsets in coagulation and inflammatory activation during hypertension-related atrial fibrillation.\u003c/p\u003e\u003cp\u003e\u003cb\u003e5. Elevated Inflammatory Factors IL-6 and CCL2 in Hypertensive Patients with Atrial Fibrillation\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePrevious studies have indicated that chronic inflammation plays a role in the pathogenesis of AF.\u003csup\u003e14\u003c/sup\u003e Building on our prior finding that myeloid cells, including monocytes and MPAs, are pivotal in AF among hypertensive patients, and in light of previous reports showing that the proportion of MPAs correlates positively with plasma levels of key inflammatory mediators IL-1β and TNF-α in patients with Kawasaki disease,\u003csup\u003e24\u003c/sup\u003e we sought to determine whether the serum concentration of inflammatory factors is altered in this context. After excluding patients with confounding diseases, we collected serum from 39 primary hypertension patients and 41 hypertensive patients with AF. We analyzed a panel of cytokines related to AF, including IL-1β, IL-2, IL-4, IL-6, IL-10, IL-12, IL-17A, IL-23, IFNγ, TNFα, G-CSF, and MCP-1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e Our results revealed that IL-6 and MCP-1 levels were significantly elevated in the AF group, whereas the other cytokines did not exhibit significant changes. MCP-1, also known as CCL2, is a well-established chemokine critical for monocyte recruitment, activation, and macrophage differentiation.\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e Recent research suggests that atrial macrophages are predominantly derived from circulating monocytes, with CCR2-dependent macrophage recruitment facilitating AF.\u003csup\u003e16\u003c/sup\u003e Our findings imply that elevated CCL2, in addition to CCR2, may contribute to the recruitment of monocytes and macrophages, thereby promoting AF.\u003csup\u003e44\u003c/sup\u003e IL-6 is a key mediator of immune regulation and has been reported to induce CCL2 expression, thereby promoting monocyte recruitment to sites of inflammation.\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e In summary, the increased expression of inflammatory factors, particularly IL-6 and CCL2, is a key factor in the development of atrial fibrillation in hypertensive patients.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e6. Interaction and Differentiation of Peripheral and Cardiac Tissue Cells in Atrial Fibrillation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOn the basis of previous discovery that recruitment of CD14\u003csup\u003e+\u003c/sup\u003e monocytes and MPAs increased, we performed a combined analysis of our peripheral data with recently released cardiac tissue single-cell data (GSE224959) of AF to investigate the interaction and differentiation of peripheral cells and cardiac tissue.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e After quality control and removal of batch effect, we found that all cells could be clearly divided into respective clusters. Cells from peripheral and cardiac tissues are quite distinct from each other, but homogenous cell types from both sources (e.g., T/NK cells, monocytes, and macrophages) are positioned closely. This indicates that dimensionality reduction effectively revealed the similarities between these cells by positioning them together while distinguishing them based on their origins, thereby avoiding any confusion (Figure. 5A). To be specific, using canonical markers, we identified fibroblasts (FIBRO(T)), endothelial cells (ENDO(T)), smooth muscle cells (SMC(T)), T cells (T Cells(T)), NK cells (NK(T)), and two macrophage subtypes (MACRO_1(T) and MACRO_2(T)) in cardiac tissue. In peripheral blood, we identified T cells (CD4\u003csup\u003e+\u003c/sup\u003eT(P) and CD8\u003csup\u003e+\u003c/sup\u003eT(P)), NK cells (NK(P)), and myeloid cells (CD14\u003csup\u003e+\u003c/sup\u003eMONO(P), CD16\u003csup\u003e+\u003c/sup\u003eMONO(P), and DC(P)). The signature gene expression profiles validated the robust clustering of each cell type (Figure. 5A, B). To explore cell-cell communication between peripheral immune cells and cardiac tissue cells, we performed CellChat analysis and found that cardiac fibroblasts were the most active cluster, communicating extensively with all other clusters, including cells from peripheral and cardiac tissue (Figure. 5C). PROS signaling, a known regulator of cell survival and proliferation, was elevated in fibroblasts and SMCs, suggesting excessive fibrotic tissue production and atrial remodeling in AF.\u003csup\u003e46\u003c/sup\u003e Conversely, PTN signaling was increased in SMCs but slightly decreased in fibroblasts, potentially reducing extracellular matrix production and altering tissue remodeling.\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e This may indicate a compensatory mechanism, reflecting a complex interplay between disease-induced remodeling and the body's resistance to detrimental changes (Figure. 5D).\u003c/p\u003e\u003cp\u003eGiven the significant role of monocyte recruitment and differentiation, we conducted trajectory analysis to examine the differential trajectories of monocytes and macrophages. As expected, monocytes and DCs were positioned in the early stages of the trajectory, while macrophages occupied later stages, with MACRO_1 at the most mature end and MACRO_2 slightly earlier. The proportion of cells from the AF group was notably higher at the end of the trajectory, consistent with previous findings that AF involves increased recruitment of monocytes differentiating into macrophages (Figure. 5E). Heatmaps and dot plots along the trajectory further highlighted these features. Monocytes exhibited high expression of calprotectin (S100A8, S100A9, and S100A12), which is involved in the immune response. On the other side of the branch, cells expressed typical macrophage markers (C1QA, C1QB, C1QC), which encode the C1q protein subunits and are integral components of the complement system (Figure. 5F, G).\u003csup\u003e48,49\u003c/sup\u003e In conclusion, our results indicate that the recruitment of inflammatory monocytes and their differentiation into macrophages play a crucial role in atrial fibrillation (AF) in hypertensive patients.\u003c/p\u003e\u003cp\u003e\u003cb\u003e7. Elevated Monocyte number in Hypertension-Related Atrial Fibrillation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eNext, we conducted a cross-sectional population study among Chinese residents aged 65 and older at a community health center in Shanghai. The mean monocyte count was significantly higher in patients with both hypertension and atrial fibrillation (n\u0026thinsp;=\u0026thinsp;104) compared to those with hypertension alone (n\u0026thinsp;=\u0026thinsp;4,356, 0.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 vs. 0.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05 x 10^9/L, P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, Figure. 6A). In a prospective study with a median follow-up of 2.1 years, 18 participants developed atrial fibrillation: 5 in the lower monocyte count group (\u0026lt;\u0026thinsp;0.35 x 10^9/L) and 13 in the higher monocyte count group (\u0026ge;\u0026thinsp;0.35 x10^9/L). A higher monocyte count was associated with a significant increase in the incidence of atrial fibrillation compared to a lower monocyte count (hazard ratio HR: 3.28; 95% confidence interval 1.14\u0026ndash;9.43; P\u0026thinsp;=\u0026thinsp;0.03) (Figure. 6B). Other clinical features of all candidates could be found in supplementary data.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn recent years, accumulating evidence suggests that inflammation mechanisms play an increasingly pivotal role in the pathogenesis of hypertension and AF.\u003csup\u003e11,41,50\u003c/sup\u003e However, limited studies have investigated the circulating immune landscape in hypertensive patients with AF. By profiling the gene signatures of individual immune cells in PBMCs from hypertensive patients with AF and control hypertensive patients, we identified activation of monocyte populations in those with AF. Specifically, a distinct population of MPAs in peripheral circulation, further supporting the involvement of PF4⁺ monocyte subsets in coagulation and inflammatory activation during hypertension-related atrial fibrillation. Moreover, an increased number of circulating monocytes was associated with a higher incidence of AF in hypertensive patients. These findings offer new insights into potential targets for treating AF in hypertensive patients.\u003c/p\u003e\u003cp\u003eMonocytes and macrophages have long been implicated in the development of hypertension, as evidenced by their increased numbers and altered phenotypes in the vasculature, kidneys, heart, and brain across various disease models.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e In this study, we observed significant gene expression changes across most monocyte subpopulations. Enrichment analysis of atrial fibrillation-related gene sets revealed that many of these genes are predominantly expressed in monocytes, underscoring their crucial role in the development of hypertensive AF. Circulating monocytes from hypertensive patients have been reported to display a pro-inflammatory phenotype, with elevated levels of cytokines such as IL-1β, IL-23, and IL-6.\u003csup\u003e51,52\u003c/sup\u003e Our data corroborate this observation, showing that approximately half of the monocytes exhibiting high levels of IL-1β. However, this pro-inflammatory phenotype was nearly identical between hypertensive patients with and without AF, with no significant differences in serum cytokine levels.\u003c/p\u003e\u003cp\u003eBeyond the broader monocyte alterations, we identified a distinct subset of MPAs defined by the co-expression of CD14 and platelet markers. These cells displayed pronounced transcriptional activity with enrichment in coagulation and immune activation pathways, indicating functional engagement rather than passive platelet binding. Similar prothrombotic and inflammatory phenotypes have been described in other conditions such as COVID-19, where platelet\u0026ndash;monocyte interactions drive immunothrombosis\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. Consistent with this, our trajectory analysis showed that PF4⁺ MPAs occupy an intermediate state between classical and inflammatory monocytes, linking platelet-derived signals with monocyte differentiation\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Flow cytometry further confirmed an expansion of CD14⁺CD41⁺ double-positive cells in hypertensive patients with AF, underscoring the clinical relevance of this subset. Collectively, these findings suggest that MPAs represent a transitional population that promotes thromboinflammatory responses and may increase susceptibility to atrial fibrillation in hypertension. Given their distinct phenotype and functional profile, MPAs may serve as potential biomarkers or therapeutic targets in hypertension-related atrial fibrillation.\u003c/p\u003e\u003cp\u003eAnother important finding is that the cholesterol pathway in monocytes emerged as the most significantly altered in hypertensive patients with AF compared to those without AF. This pathway represents an intricate link between lipid metabolism and immune-inflammatory processes, making it difficult to disentangle the impact of cholesterol homeostasis from inflammatory changes.\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e54\u003c/span\u003e,\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e In hypertensive patients with AF, the cholesterol efflux pathway is highly expressed and is known to regulate T cell activation.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e Furthermore, a strong correlation has been observed between intracellular cholesterol homeostasis and CCR2 expression in monocytes.\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e54\u003c/span\u003e,\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e Cholesterol accumulation leads to increased expression of efflux mediators such as ABCA1, which have a pro-inflammatory effect on circulating monocytes.\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e Our results show that ABCA1 expression is significantly elevated in the hypertension with AF group. The uptake of native LDL (low-density lipoprotein cholesterol) in monocytes elicits increased CCR2 expression and enhances monocyte chemotaxis.\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e Medications targeting cholesterol homeostasis, such as statins and PCSK9 mAbs, have been shown to reduce monocyte recruitment.\u003c/p\u003e\u003cp\u003eEmerging evidence suggests that inflammation plays a significant role in AF pathogenesis, as indicated by elevated serum levels of various inflammatory biomarkers in AF patients.\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e An intriguing finding in our study is the notable upregulation of MCP-1 and IL-6 in the serum of hypertensive patients with AF compared to controlsMCP-1 is secreted by infected, stressed or damaged heart tissue and binds to CC chemokine receptor 2 (CCR2), leading to the accumulation of monocytes at sites of inflammation.\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e IL-6 also plays a crucial role in regulating the differentiation and activation of monocytes into macrophages, working alongside MCP-1 to facilitate monocyte recruitment and activation.\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e Despite reports of elevated levels of several inflammatory factors, such as IL-1β, in AF and hypertension independently, we did not observe significant increases in these factors in the peripheral blood of hypertensive patients with AF. One possibility is that the changes in these inflammatory factors are subtle and may have been masked by our sample size. Another possibility is that lipid metabolic disturbances in monocytes, particularly in cholesterol homeostasis, contribute to their increased recruitment to the heart, reducing their presence in the peripheral blood.\u003c/p\u003e\u003cp\u003eExtensive studies have established the critical role of adaptive immune cells in hypertension, with T cells often considered central to this process.\u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e However, in our study comparing hypertensive patients with AF to hypertensive controls, significant differential expression was observed only in CD8\u003csup\u003e+\u003c/sup\u003e cytotoxic T cells and NK cells, while other T cell subclusters showed negligible changes. Both CD8\u003csup\u003e+\u003c/sup\u003e T cells and NK cells exhibited an activated phenotype in hypertensive patients with AF, characterized by immunosenescence and increased expression of perforin and granzyme B.\u003csup\u003e60,61\u003c/sup\u003e Although the precise mechanism linking perforin and granzyme B to hypertension remains unclear, their pro-apoptotic effects could trigger the release of DAMPs, which are key factors in the onset of atrial fibrillation.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eA limitation of our study is its focus on peripheral blood monocytes, which may not fully capture the complexity of immune interactions occurring within cardiac tissue. Additionally, the sample size may limit the detection of subtle changes in inflammatory markers. Further research, including more extensive in vivo studies and tissue-specific analyses, is needed to confirm our findings and explore the precise mechanisms linking hypertension, lipid metabolism, and inflammation to atrial fibrillation.\u003c/p\u003e\u003cp\u003eIn conclusion, our study highlights the crucial role of monocytes in hypertension contributes to the development of atrial fibrillation.The elevated expression of cholesterol efflux mediators, alongside increased MPAs and inflammatory factors expression in peripheral bloodsuggests a synergistic interplay between lipid dysregulation and inflammation in promoting AF. These findings underscore the importance of targeting monocyte-driven inflammation in developing therapeutic strategies for AF in hypertensive patients.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study received financial support from the National Natural Science Foundation of China (82030006, 82370426, 82270250, 82070435) and the National Key Research and Development Program (2022YFA1104200).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset(s) supporting the conclusions of this article are available in the NCBI Gene Expression Omnibus (GEO) repository, accession numbers GSE285199 (raw and processed human PBMC scRNA-seq data, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE285199) and GSE224959 (processed human cardiac scRNA-seq data used for comparison, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE224959).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe custom code used in this study is available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQWD analyzed the data, performed the experiments, and drafted the manuscript. ZQX performed the experiments. WZ performed the experiments and provided clinical samples. YYK, WWR, and JHX assisted with data analysis. PJG provided overall guidance. XDL and JGW supervised the study design and critically revised the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee of Ruijin Hospital, Shanghai Jiao Tong University School of Medicine. All animal experiments were performed in accordance with institutional guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll human participants provided written informed consent before sample collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eJoglar, J. A.\u003cem\u003e et al.\u003c/em\u003e 2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. \u003cem\u003eCirculation\u003c/em\u003e \u003cstrong\u003e149\u003c/strong\u003e, e1-e156 (2024). https://doi.org/10.1161/cir.0000000000001193\u003c/li\u003e\n\u003cli\u003eGuo, Y., Imberti, J. F., Kotalczyk, A., Wang, Y. \u0026amp; Lip, G. 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Immune mechanisms in the pathophysiology of hypertension. \u003cem\u003eNat Rev Nephrol\u003c/em\u003e \u003cstrong\u003e20\u003c/strong\u003e, 530-540 (2024). https://doi.org/10.1038/s41581-024-00838-w\u003c/li\u003e\n\u003cli\u003eGuan, Y.\u003cem\u003e et al.\u003c/em\u003e CD28(null) T cells in aging and diseases: From biology to assessment and intervention. \u003cem\u003eInt Immunopharmacol\u003c/em\u003e \u003cstrong\u003e131\u003c/strong\u003e, 111807 (2024). https://doi.org/10.1016/j.intimp.2024.111807\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cardiovascular-drugs-and-therapy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cdty","sideBox":"Learn more about [Cardiovascular Drugs and Therapy](https://www.springer.com/journal/10557)","snPcode":"10557","submissionUrl":"https://submission.nature.com/new-submission/10557/3","title":"Cardiovascular Drugs and Therapy","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Atrial fibrillation, Hypertension, Monocytes, Single-cell RNA sequencing, Inflammation","lastPublishedDoi":"10.21203/rs.3.rs-7748595/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7748595/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBACKGROUND: \u003c/strong\u003eAtrial fibrillation (AF) is the most common cardiac arrhythmia, with hypertension as its primary risk factor. While immune dysfunction is known to play a crucial role in hypertension, its specific impact on AF in the hypertensive setting remains underexplored. This study aims to elucidate the immune landscape of AF in the context of hypertension and explore the potential mechanisms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMETHODS:\u003c/strong\u003e Single-cell RNA transcriptomic analysis was employed to profile peripheral blood mononuclear cells (PBMCs) in hypertensive patients with AF, using hypertensive patients without AF as controls. Flow cytometry, serum cytokine analysis, and cohort studies were used for validation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRESULTS:\u003c/strong\u003e Monocytes were identified as the most significantly affected cell type in hypertensive patients with AF, showing heightened disruption of\u003cstrong\u003e \u003c/strong\u003echolesterol homeostasis and immune-inflammatory responses. Interestingly, a unique cluster of monocyte–platelet aggregates (MPAs) were identified to exhibit the most active intercellular interactions. Flow cytometry confirmed elevated proportions of CD14\u003csup\u003e+\u003c/sup\u003e monocytes and MPAs in hypertensive patients with AF. Serum analysis of a larger cohort revealed significantly higher levels of monocyte chemoattractant protein-1 (MCP-1) and interleukin-6 (IL-6). Integration of single-cell data from blood and cardiac tissue confirmed enhanced monocyte recruitment and differentiation in hypertensive patients with AF. Cohort studies further supported that the increased number of circulating monocytes was associated with a higher incidence of AF in hypertensive patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCONCLUSIONS:\u003c/strong\u003e Our study demonstrated that monocyte activation-mediated inflammatory response may play an important role in the pathogenesis of AF in hypertension. These findings offer new insights into potential therapeutic targets for managing AF in hypertensive patients.\u003c/p\u003e","manuscriptTitle":"Monocyte Activation Drives Atrial Fibrillation in Hypertension","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-15 08:53:27","doi":"10.21203/rs.3.rs-7748595/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2025-10-06T16:20:37+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-01T15:53:25+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Cardiovascular Drugs and Therapy","date":"2025-10-01T15:47:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-01T07:48:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cardiovascular Drugs and Therapy","date":"2025-10-01T01:46:53+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cardiovascular-drugs-and-therapy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cdty","sideBox":"Learn more about [Cardiovascular Drugs and Therapy](https://www.springer.com/journal/10557)","snPcode":"10557","submissionUrl":"https://submission.nature.com/new-submission/10557/3","title":"Cardiovascular Drugs and Therapy","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"17ab8fe7-0e18-4d6c-be75-5f03f08cfe25","owner":[],"postedDate":"October 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-23T16:05:24+00:00","versionOfRecord":{"articleIdentity":"rs-7748595","link":"https://doi.org/10.1007/s10557-026-07867-6","journal":{"identity":"cardiovascular-drugs-and-therapy","isVorOnly":false,"title":"Cardiovascular Drugs and Therapy"},"publishedOn":"2026-03-21 15:58:58","publishedOnDateReadable":"March 21st, 2026"},"versionCreatedAt":"2025-10-15 08:53:27","video":"","vorDoi":"10.1007/s10557-026-07867-6","vorDoiUrl":"https://doi.org/10.1007/s10557-026-07867-6","workflowStages":[]},"version":"v1","identity":"rs-7748595","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7748595","identity":"rs-7748595","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}