Abstract Kawasaki disease (KD) is a severe acute febrile illness and systemic vasculitis that causes coronary artery aneurysms in young children. Platelet hyperreactivity and an aberrant immune response are key indicators of KD; however, the mechanism by which hyperactive platelets contribute to inflammation and vasculopathy in KD remains unclear. A cytokine‐mediated positive feedback loop between KD platelets and monocytes is identified. KD platelet–monocyte aggregates (MPAs) are mediated by an initial interaction of P‐selectin (cluster of differentiation 62P, CD62p) and its glycoprotein ligand 1 (PSGL‐1). This is followed by a coordinated interaction of platelet glycoprotein (GP)Ibα with monocyte CD11b. Monocyte‐activated platelets initiate transforming growth factor (TGF)β1 release, which results in nuclear localization of nuclear factor kappaB in monocytes, therefore, driving the phenotypic conversion of classical monocytes (CD14^+CD16^−) into proinflammatory monocytes (CD14^+CD16^+). The platelet‐activated monocytes release interleukin‐1 and tissue necrotic factor‐α, which promote further platelet activation. KD‐induced inflammation and vasculopathy are prevented by inhibiting the components of this positive feedback loop. Notably, mice deficient in platelet TGFβ1 show less MPA and CD14^+CD16^+ monocytes, along with reduced inflammation and vasculopathy. These findings reveal that platelet–monocyte interactive proteins (CD62p/PSGL‐1 and (GP)Ibα/CD11b) and cytokine mediators (platelet TGFβ1) are potential biomarkers and therapeutic targets for KD vasculopathy. Keywords: inflammation, Kawasaki disease, monocyte, platelet, vasculopathy __________________________________________________________________ The formation of monocyte–platelet aggregate (MPA) induces the phenotypic conversion of monocytes into proinflammatory monocytes via the platelet release of transforming growth factor (TGF)β1, resulting in inflammation (interleukin‐1β, tissue necrotic factor‐α) and vasculopathy in Kawasaki disease (KD). Blocking MPA formation or reducing platelet TGFβ1 may provide potential biomarkers and therapeutic targets for KD vasculopathy. graphic file with name ADVS-12-2406282-g003.jpg 1. Introduction Kawasaki disease (KD) is a systemic vasculitis that predominantly affects children <5 years old.^[ [62]^1 ^] Conventionally, it affects medium‐sized arteries, particularly coronary arteries.^[ [63]^2 ^] Notably, platelet hyperreactivity^[ [64]^3 ^] and inflammation^[ [65]^4 ^] are the key indicators of KD, and standard treatment requires combining oral aspirin and high‐dose intravenous immunoglobulin (IVIG).^[ [66]^4 ^] However, some children with KD develop coronary artery aneurysm (CAA), and young adults experience adverse cardiac events even after receiving the standard therapy,^[ [67]^5 ^] which lead to significant morbidity and mortality. Therefore, there is an urgent need to understand the mechanism of KD‐induced vasculopathy and develop precise mechanism‐based therapies. Notably, monocytes and their derived macrophages are important innate effectors in the pathogenesis of various inflammatory diseases. Human monocytes comprise three main subsets based on the expression of cluster of differentiation 14 (CD14), the lipopolysaccharide (LPS) coreceptor) and CD16 (Fc gamma receptor III, FcγRIII). These subsets include the classical (CD14^+CD16^−), the intermediate (CD14^+CD16^+), and the nonclassical (CD14^lowCD16^+) monocytes.^[ [68]^6 ^] The intermediate monocyte is a recently identified subtype that has the capacity to produce proinflammatory cytokines such as tissue necrotic factor (TNF)‐α, interleukin (IL)‐1β, and IL‐6.^[ [69]^7 ^] Furthermore, expansion of intermediate monocytes has been reported in atherosclerosis,^[ [70]^8 ^] ischemic reperfusion injury,^[ [71]^9 ^] rheumatoid arthritis,^[ [72]^10 ^] and Crohn's disease.^[ [73]^11 ^] Additionally, the ratio of intermediate monocytes in circulation and its correlation with disease severity has been identified.^[ [74]^12 ^] However, the factors leading to conversion to intermediate monocytes remain unclear. Moreover, platelets are immune effector cells that function spanning from acute inflammatory response to adaptive immunity.^[ [75]^13 ^] Their immune response includes the release of adhesion molecules, chemokines, and cytokines, which are essential for recruiting neutrophils and monocytes. The recruited immune cells respond critically in acute inflammation.^[ [76]^14 ^] Furthermore, platelets interact with leukocytes via toll‐like receptors, complement receptors, and integrins, which leads to platelet–leucocyte aggregate formation.^[ [77]^14 ^] Reportedly, platelet–monocyte aggregate (MPA) is increased in patients with KD^[ [78]^15 ^] and in mice injected with Lactobacillus casei cell wall extract (LCWE),^[ [79]^16 ^] which is a well‐established murine model of KD. However, the role of MPA in KD vasculopathy remains unclear. In this study, using KD patient samples and murine model, we found that MPA instigates inflammation and vasculopathy during acute KD, targeting the monocyte–platelet aggregation restores monocyte homeostasis, and improves the vasculopathy in LCWE‐induced KD murine model, suggesting a novel therapeutic target in KD vasculopathy. 2. Results 2.1. The Formation of Platelet–Monocyte Aggregate Is Associated with Coronary Pathology and Serves as a Biomarker for Coronary Artery Aneurysm In our prospective cohort involving children, we collected peripheral blood mononuclear cells (PBMCs) from 174 individuals with KD (acute KD, n = 88; recovered KD, n = 86) and 127 healthy subjects (HSs). The samples collected were used for flow cytometry analysis, single‐cell sequencing, in vitro experiments, and assessment for potential biomarkers for CAA development (Figure [80]1A and Table [81]1 ). The MPA subset, defined as CD14^+CD41^+ monocytes, was determined using flow cytometry analysis, as shown in the density plot (Figure [82]1B). Additionally, the proportion (%) of MPA was measured relative to Lin^− (CD3, CD19, CD20, CD56) CD11b^+ cells. Furthermore, acute KD showed a significant increase in MPA (24.00 ± 12.15%, p = 8.65 × 10^−6) when compared with the HS (7.685 ± 4.664%). However, the increase was attenuated in recovered KD (11.67 ± 4.258%, p = 0.029) (Figure [83]1B). The CD14^+CD16^+ monocytes showed a similar trend (9.169 ± 3.991% in acute KD vs 5.083 ± 2.777% in HS, p = 0.0018; vs 5.444 ± 3.045% in recovered KD, p = 0.0047) (Figure [84]1C). In addition, MPA (%) was positively correlated with plasma levels of IL‐1β (p = 0.0209) (Figure [85]1D) and TNF‐α (p = 0.0016) (Figure [86]1E), with both suggested as requirements for inducing KD vasculopathy.^[ [87]^17 ^] In our second cohort involving randomly enrolled participants, MPA levels were measured at hospital admission before classifying CAA or non‐CAA (NCAA) to assess the potential of MPA for predicting CAA development. The results showed that the percentage of MPA was significantly higher in patients with acute KD (Figure [88]1F) with a median interquartile range (IQR) level of 23.65 [15.71–37.40], than in those with recovered KD (10.65 [6.723–14.98]) and HS (10.00 [7.010–11.93]), respectively. Furthermore, the proportion of MPA in patients with CAA was significantly higher than in those with NCAA during acute KD (p = 4.5 × 10^−8) (Figure [89]1G). MPA may serve as a potential marker for predicting CAA development with an area under the curve of 0.9883 [95% confidence interval (CI) 0.9605–1.000] (Figure [90]1H). Figure 1. Figure 1 [91]Open in a new tab MPA is associated with coronary pathology and serves as a biomarker for coronary artery aneurysm. A) Flowchart depicting the overall experimental design of this study. B) Gating strategy for MPA (CD14^+CD41^+) and box plots showing the cell proportion of MPA (CD14^+CD41^+) in PBMC from participants. Lineage‐APC indicates anti‐human Lineage Cocktail (CD3, CD19, CD20, CD56). Kruskal–Wallis test and Dunn's multiple comparisons test. C) Gating strategy for CD14^+CD16^+ monocytes and box plots showing the cell proportion of CD14^+CD16^+ monocytes in PBMC from participants. Lineage‐APC indicates anti‐human Lineage Cocktail (CD3, CD19, CD20, CD56). One‐way ANOVA and Tukey's multiple comparisons test. D,E) Correlation of MPA ratio to (D) IL‐1β (n = 18), (E) TNF‐ɑ (n = 18) in individuals with Acute KD. F) The proportion (%) of MPA in HS (n = 60), Acute KD (n = 32), and Recovered KD (n = 60) in the diagnostic cohort was measured relative to Lin^− (CD3, CD19, CD20, CD56) CD11b^+ cells. Kruskal–Wallis test and Dunn's multiple comparisons test. G) The proportion (%) of MPA in patients with NCAA (n = 16) and CAA (n = 16) during Acute KD was measured relative to Lin^− (CD3, CD19, CD20, CD56) CD11b^+ cells. Unpaired t test. H) A receiver operating characteristic (ROC) analysis was performed to evaluate the ability of the MPA ratio during the acute phase to distinguish KD patients with NCAA from CAA. HS, healthy subject; KD, Kawasaki disease; MPA, platelet–monocyte aggregate; NCAA, noncoronary artery aneurysm; CAA, coronary artery aneurysm; ANOVA, analysis of variance. Table 1. Demographics, characteristics of participants recruited in our study. p‐value was calculated by Kruskal–Wallis test followed by Dunn's multiple comparisons test for continuous variables. Mann–Whitney U test was used to analyze differences between NCAA and CAA. Variables HS Acute KD Recovered KD p‐value n = 127 n = 88 n = 86 Age [months] (IQR) 31 (17–43) 23 (13–50) 34.5 (14–48) NS Male, n [%] 93 (73.2) 60 (68.2) 63 (73.3) NS Coronary artery aneurysm, n [%] SCAA NA 11 (12.5) 8 (9.3) MCAA NA 4 (4.5) 9 (10.5) GCAA NA 1 (1.1) 6 (7) Normal 127 (100) 72 (81.8) 63 (73.3) Fever time [days] NA 5 (4–7) 5 (4–6) NS Laboratory data, median (IQR) PLT [10^9 L^−1] 323 (281–377) 371 (314–441)*** 348 (291.5–404.3) 0.00067 MPV [fL] 9.6 (9.15–10.25) 9.5 (9.1–10.3) 9.2 (8.9–9.8)** 0.004 PDW [%] 10 (9.1–11.4) 9.8 (9.0–11.1) 9.5 (8.8–10.6)* 0.038 WBC [10^9 L^−1] 8.1 (6.6–9.5) 13.3 (9.8–17.6)**** 7.3 (6.7–8.6)^#### <0.0001 <0.0001 Mono [10^9 L^−1] 0.42 (0.35–0.52) 0.99 (0.61–1.29)**** 0.52 (0.39–0.64)*^#### <0.0001 0.0185 Mono [%] 5.1 (4.9–6.0) 7.1 (5.0–9.0)**** 6.7 (5.7–8.5)**** <0.0001 <0.0001 HGB [g L^−1] 122 (116–128) 109 (101–114)**** 123 (115–127)^#### <0.0001 <0.0001 CRP [mg L^−1] NA 61.6 (33.1–95.9) 0.65 (0.5–1.2)^#### <0.0001 ESR [mm h^−1] NA 54 (31.3–71.8) 10 (8–15.8)^#### <0.0001 [92]Open in a new tab Abbreviations: HS, healthy subject; KD, Kawasaki disease; coronary artery aneurysm is determined by the score of coronary angiography, expressed as Z‐worst, which is the inner diameter of the proximal coronary artery segment/body surface area. A normal coronary artery dimension was defined as a Z‐worst <2.5. Small coronary artery aneurysm (SCAA) with a Z‐worst ≥2.5 to <5; medium coronary artery aneurysm (MCAA): ≥5 to <10, with absolute dimension <8 mm; large or giant coronary artery aneurysm (GCAA): ≥10, or absolute dimension ≥8 mm; PLT, platelet; ESR, erythrocyte sedimentation rate; CRP: C‐reactive protein; HGB, hemoglobin; MPV, mean platelet volume; PDW, platelet distribution width; WBC, white blood cell; NA, not applicable; NS, not significant. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 versus HS; ^#### p < 0.0001 versus Acute KD. 2.2. Hyperactive Kawasaki Disease Platelets Are Prone to Interact with Monocytes We performed single‐cell RNA sequencing (scRNA‐Seq with 10× Genomics) on PBMCs from acute KD (n = 7), recovered KD (n = 6), and HS (n = 7) to characterize the populations of monocytes and their crosstalk with platelets in peripheral blood. Following standard data processing and quality control procedures, an average of 7524 cells per sample were sequenced (minimum of 5543 cells and <20% mitochondria reads per cell). Next, using uniform manifold approximation and projection (UMAP), seven major cell types were defined in the PBMCs, including B cells (CD79A, MS4A1 (membrane spanning 4‐domainsA1), CD19), plasma cells (JCHAIN (immunoglobulin J chain), MZB1 (margunal zone B and B1 cell specific protein 1), CD79A, CD19), monocytes (VCAN (versican), FCN1 (ficolin 1)), dendritic cells (DCs) (CD1C, CLEC10A (C‐type lectin domain family 10A), plasmacytoid dendritic cells (pDCs) (JCHAIN, CLEC4C, LILRA4 (leukocyte immunoglobulin like receptor A4)), nature killer (NK) cells (NCAM1 (neural cell adhesion molecule 1), CD3D, KLRC1 (killer cell lectin like receptor C1)), and T cells (CD3D, CD3E, CD3G) (Figures [93]2A and [94]S1A (Supporting Information)). The acute KD group exhibited an expansion of monocytes when compared with those of the HS group. However, this expansion was attenuated in recovered KD (Figure [95]S1B, Supporting Information). Figure 2. Figure 2 [96]Open in a new tab MPA contributes higher risk to cytokine storm during acute KD. A) UMAP plot visualization of peripheral blood immune cells colored by annotated cell types. Each point represents a single cell, and the cell types were annotated and colored based on 3′ gene expression. B) Dot plot showing the expression of KD‐associated risk genes in each major cell type. The color is scaled by log[2]FC of acute KD versus HS, log[2]FC > 0 label as red, log[2]FC < 0 label as blue. The dot size is proportional to the mean expression of genes associated with KD identified in recent GWAS studies. C) UMAP plot of total cells colored by inflammatory score. The gene set termed “HALLMARK_INFLAMMATORY_RESPONSE” from MsigDB. Box plots showing the inflammatory score of cell subtypes (left panel), and heatmap depicting the average normalized expression of genes significantly upregulated in monocytes (right panel). D) UMAP plot of total cells colored by cytokine score. The cytokine genes were collected based on the references of Kawasaki disease (Table [97]S3, Supporting Information).