Constructing a cross-tissue human knee single-cell atlas identified osteoarthritis reduces regenerative tissue stem cells while increasing inflammatory pain macrophages

Constructing a cross-tissue human knee single-cell atlas identified osteoarthritis reduces regenerative tissue stem cells while increasing inflammatory pain macrophages | 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 Article Constructing a cross-tissue human knee single-cell atlas identified osteoarthritis reduces regenerative tissue stem cells while increasing inflammatory pain macrophages Rajnikant Raut, Amit Chakraborty, Tuhina Neogi, Michael Albro, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6247502/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Aug, 2025 Read the published version in Communications Biology → Version 1 posted You are reading this latest preprint version Abstract Osteoarthritis (OA) affects the entire knee joint; however, cross-tissue molecular mechanisms are poorly understood due to a lack of comprehensive, integrated analysis. We constructed the first comprehensive single-cell RNA sequencing knee OA atlas from articular cartilage, meniscus, synovium, and subchondral bone which showed active communication between them. Healthy synovium and meniscus contain the largest populations of tissue stem cells (TSCs) and immune cells that are altered in OA. The regenerative TSCs expressing SDF1, SOX9, CD146, PDGFRB, and CD105 decrease during OA, whereas osteogenic TSCs expressing osteogenic differentiation-related factor NT5E (CD73) are increased. In OA, the balance between regenerative and osteogenic TSCs shifts in the OA state with an increased number of osteogenic TSCs. We also report an increased level of quadruple-positive inflammatory (IL1B-IL6-NOS2-TNF) and pain marker (P2RX7) specific macrophages in OA. Fibroblasts are enriched in OA-synovium and may contribute to fibrosis. Importantly, OA cartilage contains unique MMP13-producing detrimental chondrocytes along with RUNX2-producing chondrocytes that worsen OA pathophysiology. This atlas provides a novel avenue for potential therapeutic applications in human knee OA and other musculoskeletal diseases and injuries, targeting synovium and meniscus to intervene in OA-specific molecular and cellular alterations. Health sciences/Rheumatology/Musculoskeletal system/Cartilage Health sciences/Rheumatology/Osteoimmunology Health sciences/Rheumatology/Rheumatic diseases/Osteoarthritis Knee OA atlas tissue stem cells macrophage pain SDF1 MMP13 Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Osteoarthritis (OA) vexes over 520 million adults worldwide, manifesting clinically as pain, swelling and decreased joint mobility with associated treatment costs (direct and indirect) approaching $ 486.4 billion annually. Osteoarthritis (OA) is a prevalent and debilitating joint disease characterized by the progressive degeneration of cartilage, synovium, bone, and meniscus, leading to chronic pain and impaired mobility. The pathophysiology of OA has been related to various biochemical 1 – 4 , biomechanical 5 – 7 , metabolic 8 , and gene-regulated 9 mechanisms occurring over an extended timeline. Despite its widespread impact, the cellular and molecular mechanisms underlying human clinical OA remain incompletely understood due to the lack of cross-tissue OA atlas. Thus, we constructed the first comprehensive single-cell atlas of the human knee affected by osteoarthritis. By analyzing cartilage, synovium, subchondral bone, and meniscus tissues, we aim to elucidate the distinct cellular populations and their roles in OA pathogenesis. Our investigation includes stem cells, macrophages, and other immune cells, highlighting their contributions to inflammation and tissue remodeling. Dysregulated balance of tissue degeneration and regeneration in the joint leads to OA pathology, which are governed by tissue stem cells (TSCs). TSCs perform specific functions, and various types of TSCs are enriched in the synovium, meniscus, and cartilage. Studies have identified numerous chondroprogenitor and stem cell markers expressed in TSCs 10 – 12 . Stem cells differentiate into chondrocytes during OA 13 and have the potential for cartilage repair 14 . The distinction between various TSCs can help to evaluate the balance of a specific pool. TSCs expressing regenerative factors can be categorized as regenerative TSCs. TSCs expressing factors related to osteogenic differentiation, inflammation, and OA are osteogenic TSCs. TSC pool could be dysregulated with OA, injury and inflammation. Mechanical overloading or biomechanical changes 15 that propagate to structural tissue failure (fissuring/fibrillation 16 ), tissue swelling 17 , compositional loss of GAG 18 , and derangement of the COLII network 19 . Mechanical injury also incites an inflammatory response and elevated cytokines in OA synovial fluid (e.g., IL-1B, TNF-a). 20 , 21 . Depletion of cartilage GAG diminishes its rheological and tribological properties 22 , independently contributing to the propagation of OA pathophysiology 23 , 24 . Joint kinematic dysfunction due to trauma, obesity, or life-long use is one of the main risk factors for OA 25 . The resulting increased mechanical stress causes injury to the principal load-bearing tissues of the knee joint, meniscus, and cartilage 26 as well as to the synovium and subchondral bone. Damage to even one of these tissues leads to a cascade of alterations in the other tissues, emphasizing the interrelated nature of joint tissue degeneration in OA. All knee joint tissues, including the cartilage, menisci, synovium, and subchondral bone, are affected by OA 27 . Despite this inter-tissue dependence, studies have typically focused on individual tissue types such as cartilage 28 , cartilage and meniscus 29 , synovium and infrapatellar fat pad 30 , and subchondral bone 31 , mainly omitting the underlying cross-tissue mechanisms. Recent developments in single-cell RNA sequencing (scRNA-seq) analysis and genomic technologies have provided insights into the crosstalk between cells in tissues or nearby tissues. As OA is an entire joint disease, analysis of knee joint tissues, including cartilage, meniscus, synovium, and subchondral bone, and their interaction at the single-cell level is of interest and may provide a mechanistic understanding of knee OA development. In this study, we constructed an atlas of human knee single-cell transcriptomic profiles and identified changes in specific stem cells, macrophages and detrimental chondrocytes. We present a scRNA-seq atlas of 53 human knee joint samples to evaluate the trajectory of cartilage, meniscus, synovium, and subchondral bone cells. Integrated analysis identified OA-specific cell-type clusters as well as inter-relationships between different tissues. The analysis included: 1) The effect and balance of TSCs during healthy and OA conditions; 2) Enrichment of MMP13 or catabolic factor expressing chondrocytes, proinflammatory macrophages expressing quadruple positive markers (IL1B-IL6-NOS2-TNF+), and pain markers such as P2RX7; and 3) identification of co-relative mechanisms for future translation. This knee joint scRNA-seq atlas provides a comprehensive analysis of tissue-specific factors, recognizing crosstalk between the various cells in adjacent synovial tissues that could be targets for therapeutic interventions to mitigate OA. Through this atlas, we identify key cellular subsets and molecular pathways involved in OA, offering potential targets for therapeutic intervention. This work represents a significant step forward in understanding the complex cellular landscape of OA and paves the way for future research and treatment strategies. Material and methods Human healthy and OA knee specimens. With prior consent from the patients, samples of healthy and OA patients for cartilage, meniscus, synovium, infrapatellar fat pad (SynoFP), and subchondral bone (SCB) were collected from the NCBI Gene Expression Omnibus (GEO) database (please also see Methods and Fig. 1 a). The sample description and corresponding accession IDs show specific characteristics that include the entire knee joint tissue. Here, GEO Series (GSE) identifies individual accession ID under which the raw sequencing data files are publicly available (Fig. 1 a). The samples with accession ID GSE220243: Healthy Samples : Matching healthy cartilage (n = 6) and meniscus (n = 7) samples were obtained from the same knee, and only knees with grades 0 or 1 were considered (Graded macroscopically using Outerbridge System). The cartilage samples in their study were collected from the weight-bearing medial femoral condyle, whereas the whole meniscus was collected. OA samples : Corresponding OA samples for cartilage samples (n = 6; grade 4) were collected from medial femoral osteochondral slabs, and meniscus samples (n = 6) were also collected, excluding the ones with large calcium deposits 29 . The samples with accession ID GSE169454: Non-Arthritic Samples : non-arthritic femoral condyle cartilage specimens (n = 3) were collected from fresh osteochondral allografts discarded during donor plug harvesting during surgical implantation 32 . OA Cartilage Samples : OA cartilage samples (n = 4) were extracted from human patients undergoing total knee joint replacement surgery for OA with prior consent from patients, The samples with accession ID GSE255460: Non-OA Controls : Samples were collected from three non-OA controls who underwent amputation with no prior history of joint injury or disease. OA Cartilage Samples : Cartilage samples were collected from eight patients with OA who underwent knee arthroplasty surgery 33 . The samples with accession ID GSE216651: OA SynoFP : Three OA SynoFP samples were obtained from individuals with end-stage knee OA who underwent total knee replacement surgery. Non-OA SynoFP : Non-OA SynoFP biopsies were obtained from patients who underwent excision of bone tumors surrounding the knee joint or from organ transplant donors 30 . The samples with accession ID GSE196678 were SCB samples isolated from the medial and lateral tibial plateaus of two patients with OA undergoing knee replacement surgery. These samples were divided into two groups: control (n = 2) from the lateral tibial plateau and OA (n = 2) from the medial side 31 . Briefly, all healthy samples from the cartilage, meniscus, SynoFP, and SCB were processed individually for quality control and doublets and integrated using the harmony integration method in Seurat. Similarly, all OA samples were processed and subjected to CellChat 34 and pseudotime trajectory analysis (Fig. 1 b, c). Finally, to perform comparative analysis, both preprocessed healthy and OA samples were integrated and subjected to clustering, cell identity, and cell type proportion analysis (Fig. 1 d). This was followed by the extraction of macrophages and TSCs for downstream analyses. As shown in Fig. 1 b and 1 c, 130012 cells from healthy and 195742 cells from OA were retained after quality control and preprocessing. The total number of cells retained from individual tissue types and analyzed were included (Fig. 1 b, c). Quality control and preprocessing. Individual files of Healthy and OA patients single-cell RNA sequencing (scRNA-seq) for knee joint cartilage, meniscus, synovium, infrapatellar fat pad (SynoFP), and subchondral bone were downloaded from the NCBI GEO and processed independently. The zipped files contained a count matrix, features (genes), and barcode files, which were imported into R studio and converted to a Seurat object using the CreateSeuratObject function in the Seurat R package (v5.1.0) 35 with no initial cutoffs. Further details about the sample characterization and categorization are described above. To filter out low-quality cells, we eliminated cells with less than 3,000 RNA counts, 400 genes (features) detected, and more than 10% reads coming from mitochondrial genes. The retained high-quality cells were further normalized using the default LogNormalize method and a scale factor of 10,000 within NormalizeData function of Seurat. Clustering was performed with 20 Principal Components (PCs) at a resolution of 0.5, using 2,000 variable features found using FindVariableFeatures with the "vst" selection method. The criteria for selecting PCs were defined using elbow plots. Next, DoubletFinder R package (v2.0.4) was used to eliminate doublet cells 36 . After quality control and preprocessing 130012 cells from healthy and 195742 cells from OA cells were retained. Data Integration and cluster identification. All individually processed files were then combined into a single Seurat object. Combined files were subjected to data integration using HarmonyIntegration 37 method within IntegrateLayers function of Seurat 38 . For downstream processing, 20 PCs were used for harmony clustering at a 0.5 resolution. Healthy samples were combined to understand their cellular and molecular landscapes. The OA samples were combined to understand the cellular and molecular landscapes. Both Healthy and OA samples were integrated to identify common and unique mechanisms. Differential marker analysis and cell type identification. The JoinLayers function was used to merge all integrated layers. We performed differential expression analysis using FindAllMarkers function to identify the differentially expressed marker genes in each harmony cluster. The Wilcoxon rank-sum test (Wilcox) was used to perform the analysis with logfc.threshold of 0.25, singleR (v2.8.0) and celldex (v1.16.0) R packages were used to identify cell types. HumanPrimaryCellAtlasData from celldex was considered for this study because it includes almost all types of cells, including stem cells and immune cells 39 , 40 . TSCs and Macrophages were extracted using a subset function of base R for downstream analyses. CellChat analysis. CellChat (v2.1.2) was run on the RNA data slot and separately on the healthy and OA samples. 34 , 41 . Overexpressed genes were identified using default parameters of identifyOverExpressedGenes function. Communication probabilities were computed using trim = 0.1, type = triMean, and other default parameters of computeCommunProb function. Communications were filtered to include those with at least 100 cells. The two cell-chat objects were merged to compare their interaction occurrences and strengths. ComputeCommunProbPathway function detected actively communicating signaling pathways. Data were visualized in a chord diagram, heatmaps, and scatter plots using the corresponding functional commands of the CellChat package. Pseudotime trajectory analysis. Pseudo-trajectories of chondrocytes and TSCs were constructed using Monocle3 42 . The Seurat object was converted to the monocle3 cell_data_set object using as.cell_data_set function and preprocessed, and 20 PCs were retained using the PCA method. Dimensionality reduction was performed using the UMAP method and was clustered using the cluster_ cell function. The learn_graph function was used to learn and build the trajectory. O rder_cells and pseudotime functions were used to order the cells at the pseudotime. Root nodes were selected from the TSCs cluster, considering chondroprogenitor cells as part of the TSCs. Data Visualization Uniform Manifold Approximation and Projection (UMAP) was used to visualize single-cell data. Violine plots, heatmaps, feature plots, and bar plots were generated using vlnplot (Seurat), netAnalysis_signalingRole_heatmap (CellChat), Featureplot (Seurat), and ggplot2 functions, respectively. Results Cellular and molecular landscape of healthy human knee at single-cell resolution. To delineate the cellular and molecular landscapes of the human knee joint and understand the contribution of different tissues to normal function, scRNA-seq samples were integrated. Healthy cartilage, meniscus, SynoFP, and SCB were harmony-integrated, clustered, and subjected to cell identity analysis using the H umanPrimaryCellAtlas database in c elldex using SingleR R packages (Fig. 2 a; Fig. S1 a, b). UMAP shows all the identified cell types, and Table S1 shows the proportion of each cell type (Fig. 2 a). Indeed, the chondrocyte population was dominant and contributed ~ 99.6% of the healthy cartilage samples, whereas the TSCs population contributed only ~ 0.4% of the total cell population (Fig. 2 b; Fig. S1 b). The chondrocyte population was also enriched in the meniscus, contributing ~ 85.3%, along with ~ 9.5% of TSCs and a small proportion of endothelial cells (EC) (~ 2.7%), smooth muscle cells (SMC) (~ 1.3%), fibroblasts (~ 0.5%), and immune cells (including ~ 0.7% macrophages). However, the proportion of chondrocytes was low in the SynoFP group (approximately 15%) and nearly absent in the SCB group (0.3%). Interestingly, the TSCs pool was significantly higher in SynoFP, contributing to approximately 42.2% of the total cell population, along with ~ 15.7% ECs, ~ 13.1% macrophages, ~ 5% monocytes, ~ 5.4% SMCs, ~ 1.5% synovial fibroblasts, and a relatively small proportion of other immune cell populations. In SCB, T cells (~ 48.9%) and natural killer (NK) cells (~ 36.1%) together contribute nearly 85% of the total cell population, along with a small proportion of macrophages (2.8%), monocytes (2.7%), TSCs (1.7%), and other immune cell populations. Overall, this data suggests that chondrocytes are predominant in the cartilage and meniscus, TSCs largely reside in SynoFP and the meniscus, and SynoFP and SCB are major reservoirs for the immune cells in healthy human knees. To identify signaling and communication, CellChat analysis was performed which showed the active communication between all four tissues. The cartilage was a major sender and receiver of signals, followed by the meniscus and SynoFP. SCB was mainly a receiver of signals from the remaining three tissues (Fig. 2 c). Analysis of cell types showed MSCs, fibroblasts, SMCs, chondrocytes, and TSCs were the major senders of the signals, whereas MSCs, macrophages, monocytes, dendritic cells (DCs), and T-cells were the major receivers of the signals (Fig. 2 d, e). Approximately 85 signaling pathways actively send and receive signals. The most active top 10 signaling pathways are COLLAGEN, MIF, MHC-I, MHC-II, FN1, CD99, LAMININ, APP, CypA, and CXCL (Fig. 2 f, Fig. S1 d). Pseudotime trajectory analysis which determines the origin and terminal differentiation state of chondrocytes 26 , was performed by extracting TSCs and chondrocytes from the total cell population (Fig. 2 g). Using TSCs clusters as a root node, we performed the analysis and visualized on the UMAP (Fig. 2 h). All four tissues contributed to TSCs and chondrocyte populations; however, the contribution of SCB was negligible (Fig. S1 e). Cluster 8 had the lowest Pseudotime since it mostly consists of TSCs and is considered a root node, whereas Cluster 5 and Cluster 0 had the highest Pseudotime, suggesting the terminally differentiated chondrocyte population, primarily residing in the cartilage (Fig. 2 i; Fig. S1 b, e). Cellular and molecular landscape of the human knee during OA at single-cell resolution. To evaluate the changes in cellular homeostasis during OA, samples were subjected to clustering and cell type identification (Fig. 3 a; Fig. S2 a, b). Table S2 lists the proportion of each cell type. OA-cartilage has more than ~ 99% chondrocytes population, ~ 0.1% TSCs, 0.4% macrophages and 0.1% monocytes (Fig. 3 b; Fig. S2 c). In the OA-meniscus, the population was ~ 82.6% chondrocytes, ~ 6.8% TSCs, ~ 3.9% macrophages, ~ 2.8% ECs, ~ 1.2% SMCs, ~ 0.8% monocytes, and 0.3% fibroblasts. OA-synovium had ~ 37.5% chondrocytes and ~ 16.4% TSCs. Interestingly, synovium had a higher number of macrophages (~ 13.7%), fibroblasts (~ 7.7%) and monocytes (~ 1.8%), suggesting increased fibrosis and inflammation in knee OA. In SCB, NK cells (~ 32.6%) and T cells (~ 50.6%) contributed to ~ 83.2% of the total cell population, along with a small proportion of TSCs (~ 2%), macrophages (~ 1.3%), monocytes (~ 3.3%), chondrocytes (~ 1%), and other immune cell populations. Overall, chondrocyte population significantly increased in OA-synovium. In contrast, the TSCs were reduced in OA synovium and meniscus. Macrophage infiltration was increased in the meniscus and synovium. Monocyte infiltration was elevated whereas ECs were reduced in synovium. CellChat analysis showed OA-cartilage was a major sender and receiver of signals, followed by the meniscus and synovium, whereas SCB was mainly a receiver of signals from the remaining three tissues (Fig. 3 c). Unlike healthy tissues, the number of interactions increased between cartilage and SynoFP, and meniscus and synoFP, suggesting active immune signaling during OA. Strong intercellular interactions were observed between cell types (Fig. 3 d; Fig. S2 d). MSCs, fibroblasts, SMCs, chondrocytes, TSCs, neurons, fibroblasts, and macrophages were the major senders of the signals, whereas MSCs, macrophages, neurons, and TSCs were the major receivers (Fig. 3 e). OA promotes intricate processes, such as cartilage degradation, inflammation, and pain, which are influenced by specific signaling pathways 43 – 48 . The top 10 most active signaling pathways in OA were COLLAGEN, FN1, MIF, LAMININ, APP, MHC-II, CD99, CypA, MHC-I, and CXCL (Fig. 3 f). Additional pathways, such as prostaglandins, MK, VISFATIN, ANGPTL, and THBS, were highly active in OA (Fig. 3 f; Fig. S2 d). Pseudotime trajectory analysis identified the terminally differentiated chondrocytes increased in cartilage as well as meniscus since both these tissues contributed to the highest Pseudotime clusters 1 and 3 (Fig. 3 g-i; Fig. S2 e). Thus, the reduced TSCs population in the meniscus and synovium OA compared to the healthy knee joint shows a transition to terminally differentiated chondrocytes, which contributes to fibrosis or osteogenic transition in OA. MMP13 producing detrimental chondrocytes and synovial fibroblasts were expanded in OA To detect unique cellular and molecular OA-specific variations, healthy and OA knee scRNA-seq samples were integrated and subjected to harmony integration following standard Seurat processing (Fig. S3 a). Cell type detection using singleR revealed variability in the population of major cell types, such as chondrocytes, TSCs, macrophages, and most importantly, expansion of synovial fibroblasts in OA (Fig. 4 a, Fig. S3 b, c). To correlate with the individual analyses described above, a stacked bar plot was generated and compared the cell proportion in both the sample types (Fig. S3 d). Clustering was performed at a resolution of 0.5 and generated nearly 27 cell clusters with clusters 3, 10, 18, 19, and 21 expanded, whereas major cluster 1 was depleted in the OA samples (Fig. 4 b). All marker analyses were performed to determine the molecular identity of these clusters (Table S1 ). OA-depleted Cluster 1 expressed genes, such as CYTL1, CLEC3A, S100B, and FRZB, which are effector chondrocyte (EC) markers 49 (Table S1 ). These EC also produce WISP3 50 , CTGF 51 , CYR61 51 , GREM1 52 , and WIF1 53 , which play roles in chondrocyte protection, angiogenesis, and ECM remodeling (Table S3 ). The OA-specific chondrocyte cluster, Cluster 3 (Fig. 4 b), which is absent in healthy samples, contains specific Detrimental Chondrocytes (DCs) that promote cartilage/ECM degeneration, chondrocyte-to-osteoblast transition, and inflammation-related factors. DCs were enriched with MMP13 54 , TNFRSF11B (osteoprotegerin) 55 , LCN2 56,57 , MMP1 58 , MMP3 59 , ELF3 60,61 , WNT7B 53 , and NOS2 62 (Fig. 4 c) and are referred to as MMP13 producing DCs (MDCs). Next, we confirmed that MDCs primarily produced OA-specific markers (Fig. 4 d; Fig. S3 e, f). MDCs specifically produce CCL20 and LAMB3, which are important factors in inflammatory pain and cartilage damage, respectively 63 , 64 (Fig. 4 e). Cluster 18 was exclusively present in OA samples and was molecularly aligned with the previously described pathogenic chondrocyte subpopulation owing to the higher expression of POSTN and ZEB1 29 . It highly expressed genes, such as NELL1 65,66 , LRRC15 67 , and COL3A1 68 , which play a role in OA progression via osteogenesis, fibrosis, and ECM degeneration (Table S1 ). In addition, cluster 18 also expressed RUNX2, ASPN, and OGN, which are known to promote mineralization and osteoblasts (Fig. 4 f). Cluster 18 expressing genes showed negligible expression in the MDCs. Thus, cluster 18 and MDCs may contribute to worsening disease pathology in human knee OA. Cluster 10 showed slightly elevated levels of OA-expressing CHI3L1, CHI3L2, MT1G, MT1H, and MT1E regulatory chondrocyte markers (RegC) 29 . Cluster 19 comprised chondrocytes highly expressing IL10 69 , TM4SF1 70 , CHADL 71 , MIA 72 , MT1G 73 , and COL2A1, which are associated with cartilage protection, matrix–proteoglycan synthesis, and reverse calcification and degeneration. Therefore, clusters 10 and 19 appear to expand because of a compensatory response to protect the knee joint from the degenerative effects of OA. Overall, MMP13 expressing DCs and cluster 18 expressing factors could play a role in specific pathologies and mechanisms in the development of OA, whereas restoring cluster 1 and 19 factors could reverse OA. In addition, expansion of the fibroblast population may result in fibrosis in the synovial region, adding a layer to the pathophysiology of OA. 74 Synovium and meniscus are the primary residences for TSCs that are depleted in OA. The TSC population was significantly reduced in the SynoFP and menisci. In the meniscus, the TSCs proportion decreased from ~ 9.5% to ~ 6.8%, and SynoFP from ~ 42.2% to ~ 16.4%, which can also be correlated with the expansion of the differentiated chondrocyte population in SynoFP (from ~ 15% to ~ 37.5%) during OA (Fig. 5 a). For further analysis, we extracted TSCs from the total cell clusters and generated UMAP to visualize reduced regenerative (Chondrogenic factors producing) and increased osteogenic TSCs in OA (Fig. 5 b). As TSCs primarily reside in the meniscus and SynoFP, we generated UMAP to observe the different TSCs contributing to the different TSC subtypes (Fig. 5 c). TSCs decreased by 36.45% in the meniscus and 37.77% in SynoFP compared with their respective healthy controls (Fig. 5 d). We observed a reduction in the number of regenerative TSCs that produced CXCL12 (SDF1), SOX9, ACAN, MCAM (CD146), PDGFRB, BMPR1B, ENG (CD105/Endoglin), and NGFR (Fig. 5 e, Fig. S4 a, b). Previously identified chondroprogenitor and stem cell markers that express TSCs have also been affected 10 – 12 . These TSCs were SDF1 + 12 , CD146 + 75 , CD105 + 76,77 , 77,78 (Fig. 5 f-h). Interestingly, osteogenic TSCs expressing ALCAM, NT5E (CD73), NGF, and BDNF were increased in OA. NT5E (CD73) is known to increase in OA (Fig. 5 e) 79 – 81 . Comparative analysis of knee joint tissue compartments identified that the meniscus and synovium are the primary residences of tissue stem cells, which are significantly depleted during OA, contributing to the worst pathological outcome. Elevated levels of unique IL1B-IL6-NOS2-TNF and pain markers P2RX7-producing macrophages contribute to OA pathophysiology. We hypothesized that OA promotes the infiltration of proinflammatory cells, which initiate a vicious cycle of cytokine production, leading to knee joint inflammation and pain. Integration of healthy and OA samples revealed an expansion of the macrophage population in cluster 13 in OA samples (Fig. 4 a, b). Within this macrophage population, we identified seven different subpopulations of macrophages at a resolution of 0.5 and labeled them as macrophage clusters MC1-MC7 (Fig. 6 a). MC1 and MC2 were the largest clusters, with MC2 being largely expanded during OA, whereas MC3 and MC4 were exclusively present in OA samples (Fig. 6 a). To determine the levels of pro- and anti-inflammatory macrophages under healthy and OA conditions, we analyzed the levels of proinflammatory M1 (CD86 and TNF) and anti-inflammatory M2 (CD163 and MRC1)-type macrophages. We found that CD86 and TNF-producing macrophages were expanded in OA samples, whereas CD163 and MRC1-expressing macrophages were significantly depleted (Fig. 6 b). Feature plot analysis revealed that MC1 mostly expressed M2 macrophage markers, whereas MC2 and MC3 expressed M1 macrophage markers (Fig. S5 a, b). Next, we analyzed the expression of the proinflammatory OA-causing markers IL1B, IL6, TNF, and NOS2 within each macrophage cluster (Fig. 6 c). Interestingly, IL1B and TNF were highly expressed in OA-specific macrophages, MC2 and MC1, suggesting a novel IL1B + TNF + inflammatory macrophage population, irrespective of their M1 and M2 status. These IL1B + and TNF + macrophages may serve as novel prognostic or diagnostic biomarkers of OA pathophysiology. Notably, we discovered that MC3, a unique OA-specific macrophage cluster, is the only cluster that expresses all four proinflammatory genes: IL1B, NOS2, IL6, and TNF (Fig. 6 c, Fig. S5 a, e). Next, we extracted MC3 from the total macrophage clusters and confirmed the significantly upregulated expression of these genes in OA (Fig. 6 d, e). We termed this novel macrophage subpopulation quadruple-positive (IL1B + IL6 + NOS2 + TNF+) inflammatory macrophages that worsen the disease outcome in terms of joint inflammation and pain in patients with OA. Finally, we analyzed the expression of classic pain marker genes in total macrophages to understand the association between OA macrophages and joint pain. As expected, P2RX7, CSF1R, AIF1, and PTGS2 (COX2)-producing macrophages were highly expanded in OA samples (Fig. 6 f). However, two well-studied OA pain markers, PIEZO2 and TACR1, are not expressed in macrophages. Thus, we conclude that clinical knee OA inflammation and pain arise due to the accumulation of unique dual- and quadruple-positive proinflammatory macrophages, which need to be functionally characterized in a large cohort of clinical samples in the future. Discussion An atlas was constructed by integrating single-cell RNA sequencing profiles of the cartilage, meniscus, synovium, and subchondral bone, which showed specific differences in health and OA knee. The analysis of the molecular landscapes of healthy and OA knees found that OA samples have increased cell-cell communications across the tissues, suggesting active TSCs and immune signaling during OA. However, terminally differentiated chondrocytes in OA originated from the Tissue stem cells (TSCs) residing in the synovium and meniscus identified through pseudotime trajectory analysis. Our findings highlight the synovium as a hotspot of degenerative and regenerative changes. TSCs, cross-tissue interaction, and inflammation affect cartilage integrity and indicate OA-specific alterations initiated in synovial tissue. As mentioned, TSCs primarily reside in the synovium. Regenerative TSCs were depleted in OA. This dynamic change reduces regeneration and increases degeneration. Regenerative TSCs 10 – 12 express markers such as CXCL12 (SDF1), SOX9, ACAN, MCAM (CD146), PDGFRB, BMPR1B, ENG (CD105/Endoglin), and NGFR. SDF1-expressing TSCs are explicitly depleted in the meniscus, and studies have shown that SDF1 is required for chondroprogenitor cell migration during post-injury tissue repair in the meniscus 12 . MCAM+ (CD146+) stem cells have previously shown a more significant migration potential towards degenerated intervertebral discs 75 . CD105 promotes chondrogenesis of synovium-derived MSCs 76 , 77 . Osteogenic TSCs, which express ALCAM, NT5E (CD73), NGF, and BDNF, were expanded in OA. ALCAM + cells can differentiate into osteoblasts, adipocytes, chondrocytes, and stromal cells, which support osteoclastogenesis, hematopoiesis, and angiogenesis 82 . NT5E is a marker of resting chondrocytes 81 and is upregulated in OA 79 – 81 . Expanding fibroblasts in synovium may contribute to fibrosis in OA knees. There was a substantial elevation in inflammation- and pain-related macrophages in OA, including unique macrophage subpopulations with dual positive (IL1B and TNF) and quadruple positive (IL1B, TNF, IL6, and NOS2) nature. OA-specific MDCs were enriched with degradative factors such as LCN2 56 , TNFRSF11B 55 , MMP1, MMP3, MMP13, NOS2, WNT7B 53 , and ELF3 60 , 61 , which play significant roles in extracellular matrix destruction, bone remodeling, and cartilage degradation. OA-specific cluster 18 is enriched with RUNX2 66 , ASPN, and OGN, which are markers of mineralization and osteoblast characteristics 55 that contribute to stiffness. OA-specific MDCs were enriched in CCL20 and other markers associated with inflammation and pain. In the presence of CCL20, cartilage released more MMP-1, MMP-13, PGE2, GAG fragments, and IL-6, whereas collagen type II mRNA expression was inhibited 63 . The limitation of this study is that, although we generated a unique scRNA-seq atlas, the inclusion of a large number of samples with various stages of OA will provide the detailed mechanism for OA progression. OA disproportionately affects underserved populations 83 , 84 and females. The detailed temporal and spatial appearance of RNA from the time of an inciting injury through the initiation and progression of OA pathophysiology, its proteomics profile, and actual tissue changes need to be performed. Future studies should involve well-controlled clinical cohorts with age- and sex-matched large cohorts of samples and standardized tissue extraction procedures. In conclusion, the synovium and meniscus are the most damaged compartments, and synovium regeneration could have potential therapeutic opportunities considering highly dysregulated homeostasis. Atala et al. showed that the synovial environment causes cartilage deterioration and regeneration 85 . OA pain may be a consequence of resident TSCs depletion and proinflammatory changes in the synovium and meniscus. Moreover, dual- and quadruple-positive macrophages could serve as prognostic markers to identify OA severity pre-and post-treatment. As there are no FDA-approved drugs, our study shows that future clinical trials should consider the involvement of synovium and meniscus regeneration when designing future OA disease-modifying drugs. Our analysis also emphasizes the heterogeneity within the meniscus and bone compartments, revealing distinct cellular niches that may influence disease outcomes. Understanding the role of these niches in OA pathogenesis could lead to more targeted and effective treatments. This atlas provides a valuable resource for the scientific community, offering new perspectives on cellular and molecular mechanisms and opening up exciting possibilities for developing targeted therapies aimed at halting or reversing disease progression. Future studies should build on these findings to further elucidate the intricate cellular dynamics within the OA joint and translate these insights into clinical applications. Declarations Acknowledgment: This study was supported by an NIH grant R01 DE031413 (MB) and P30 AR072571 (TN). Author Contributions: Rajnikant Dilip Raut performed the experiments and analyzed the data with the help of Amit Kumar Chakraborty and Manish V. Bais. Tuhina Neogi, Brian Snyder, Thomas P. Schaer, Michael Albro, Mark W. Grinstaff, Chao Zhang, and Manish V. Bais helped with the conception, interpretation, and manuscript editing. Manish V. Bais conceived and designed the study. Rajnikant Dilip Raut and Manish V. Bais, with Brian Snyder and Mark W. Grinstaff, interpreted data and wrote the manuscript. Conflicts of interest: The authors declare that they have no conflicts of interest regarding the content of this manuscript. Financial Interests: The authors declare that they have no financial interests regarding the content of this manuscript. Declaration of generative AI in scientific writing: The authors declare that they have not used AI to write or edit this manuscript. Data Availability: The human knee OA single-cell RNA-seq data used in this study are publicly available under the following accession ID: cartilage (GSE220243, GSE169454, and GSE255460); meniscus (GSE220243); synovium and IPFP (GSE216651); and subchondral bone (GSE196678). References Arokoski, J., Kiviranta, I., Jurvelin, J., Tammi, M. & Helminen, H. J. 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Racial-Ethnic Differences in Osteoarthritis Pain and Disability: A Meta-Analysis. J Pain 20 , 629–644 (2019). Bolander, J. et al. The synovial environment steers cartilage deterioration and regeneration. Sci Adv 9 , eade4645 (2023). Additional Declarations There is NO Competing Interest. Supplementary Files AtlasFigureS1.png Supplementary Figure Legends: Fig. S1: UMAP cluster identification and pseudotime trajectory analysis in healthy knee tissues: A) UMAP shows the before integration (Unintegrated) and after harmony integration (Integrated) scRNA seq samples from healthy cartilage, meniscus, subchondral bone, and SynoFP; CartNorm: Healthy cartilage, MenNorm: Healthy meniscus, SCBNorm: Healthy subchondral bone, SynofpNorm: Healthy SynoFP. B) A total of 15 clusters were identified at 0.5 resolution after harmony integration. C) Cell type contribution of individual tissue type in a healthy human knee. D)Highly active signaling pathways in a healthy human knee. E)Contribution of individual tissue type in TSCs and chondrocytes populations for pseudotime trajectory analysis. AtlasFigureS2.png Fig. S2: UMAP cluster identification and pseudotime trajectory analysis in OA knee tissues: A) UMAP shows the before integration (Unintegrated) and after harmony integration (Integrated) scRNA seq samples from OA cartilage, meniscus, subchondral bone, and SynoFP; CartOA: Cartilage of OA patients, MenOA: Meniscus of OA patients, SCBOA: Subchondral bone of OA patients, SynofpOA: SynoFP of OA patients. B) A total of 17 clusters were identified at 0.5 resolution after harmony integration. C) Cell type contribution of individual tissue type in the human knee with OA. D)Highly active OA-specific signaling pathways in the human knee with OA. E)Contribution of individual tissue type in TSCs and chondrocytes populations for pseudotime trajectory analysis. AtlasFigureS3.png Fig. S3: UMAP of total cell types in combined samples of healthy and OA human knee: A) UMAP shows the before-integration (Unintegrated) and after-Harmony integration (Integrated) scRNA seq samples from human healthy and OA samples. B) Contribution of individual tissue type within the Harmony integrated healthy and OA samples. C) UMAP representation of total cell types in combined samples of healthy and OA human knee identified by SingleR. D) The proportion of each cell type in healthy human and OA knees; here, the TSC pool significantly decreased in OA samples, whereas there was an increase in detrimental chondrocytes. E)Feature plot analysis shows the MDCs expressing OA-specific genes; the colored rectangle highlights the cells (MDCs) expressing a particular gene in healthy and OA samples. F) Violin plots show the elevated expressions of cartilage degeneration and inflammatory immune response genes, including MMP13, TNFRSF11B, and NOS2 in OA samples. G) Violin plots show the overexpression of osteogenic transition and mineralization-related genes in human knee OA samples. AtlasFigureS4.png Fig. S4: Tissue stem cells and markers expression: A) Violin plots show TSCs expressing stem cell and chondroprogenitor markers during healthy and OA conditions in human knee. B) Feature plots show TSCs expressing stem cell and chondroprogenitor markers during healthy and OA conditions in human knee; here, blue represents cells expressing a particular gene. AtlasFigureS5.png Fig. S5: Inflammatory and pain macrophages markers: A)Feature plots showing total macrophages expressing key proinflammatory M1 macrophage marker genes (CD86 and TNF) during healthy and OA conditions. B)Feature plots showing total macrophages expressing key M2 macrophage marker genes (CD163 and MRC1) during healthy and OA conditions. C) Bubble plot represents the percent expression of specific M1 marker genes within each cluster of total macrophages in healthy and OA samples; Note: percent expression only represents the cells expressing a particular gene compared to the total cells within that cluster, i.e., if the ball size in healthy is more significant than its OA counterpart does not necessarily represent the overall expression levels, as the number of M1 macrophages are lower in healthy but higher in OA. D) Bubble plot represents the percent expression of specific M2 marker genes within each cluster of total macrophages in healthy and OA samples. E) Feature plots highlighting quadruple positive macrophages (Feature plot for TNF has been shown above in S5A). F) The violin plot shows the total macrophages expressing IL1B, IL6, and NOS2 during healthy and OA conditions. 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B) Anatomy of the healthy human knee and the number of cells retained post-QC using standard Seurat and doubletFinder. C) Anatomy of OA knee and the number of cells retained post-QC. D) Overview of healthy and OA sample integration followed by downstream analyses.\u003c/p\u003e","description":"","filename":"AtlasFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6247502/v1/e13b5ae6c5c9f34bd4ccf7aa.png"},{"id":82007371,"identity":"f1f7e41e-5d8b-4b01-b5cd-2fbe71d2852a","added_by":"auto","created_at":"2025-05-05 23:33:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3502960,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCellular and molecular landscape of a healthy human knee.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA) UMAP representation of total cell types in healthy human knee identified by SingleR. B) Proportion of each cell type in a healthy human knee; here, the chondrocytes predominantly resided in cartilage and meniscus, TSCs in SynoFP and meniscus, and immune cells in SynoFP, subchondral bone, and meniscus. C) Chord diagram showing communication between all four tissue types. D) Chord diagram showing communications between different cell types. E) Scatter plot showing outgoing and incoming interaction strength for different cell types; cell types with molecularly significant differences are shown in the broad letter. F) Heatmap representation of active signaling pathways in the healthy human knee with outgoing and incoming signaling patterns; here, the top signaling pathways are highlighted in the red rectangle. G) UMAP highlighted the location of chondrocytes and TSCs for pseudotime trajectory analysis. H) UMAP visualization of pseudotime trajectory analysis; the root node was selected from the TSCs cluster. I) Horizontal box plot showing pseudotime for individual harmony clusters.\u003c/p\u003e","description":"","filename":"AtlasFigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6247502/v1/e140299948143a78df897acf.png"},{"id":82007372,"identity":"b67f8a71-74c2-4765-80b1-52d7d5b47a7b","added_by":"auto","created_at":"2025-05-05 23:33:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3743947,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCellular and molecular landscape during human knee OA.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA) UMAP representation of total cell types during OA condition identified by SingleR. B) Proportion of each cell type in the human knee with OA; here, the chondrocytes predominantly resided in cartilage and meniscus, TSCs in SynoFP and meniscus, and immune cells in SynoFP, subchondral bone and meniscus. C) Chord diagram showing communication between all four tissue types. D) Chord diagram showing communications between different cell types. E) Scatter plot showing outgoing and incoming interaction strength for different cell types; cell types with molecularly significant differences are shown in the broad letter. F) Heatmap representation of active signaling pathways in the healthy human knee with outgoing and incoming signaling pattern; the top signaling pathways are highlighted in the red rectangle, whereas OA-specific active signaling pathways are highlighted with the blue rectangle. G) UMAP highlighted the location of chondrocytes and TSCs for pseudotime trajectory analysis. H) UMAP visualization of pseudotime trajectory analysis; here, the root node was selected from the TSCs cluster. I) Horizontal box plot showing pseudotime for individual harmony clusters.\u003c/p\u003e","description":"","filename":"AtlasFigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6247502/v1/b4e9009e42ec007684df88e5.png"},{"id":82007108,"identity":"6aa8a381-53c7-458a-b591-a8fa2dcbc100","added_by":"auto","created_at":"2025-05-05 23:17:08","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":4045960,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIntegration of healthy and OA samples identified an OA-specific degenerative chondrocyte cluster.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA) UMAP representation of cell identity in Harmony integrated healthy and OA samples; rectangles show predominant cell types. B) Total cell clusters (n=27) across healthy and OA samples at 0.5 resolution; red boxes highlight the clusters variably present in OA samples. C) Feature plots showing the total expression of top markers of Cluster 3 (MDCs) in both healthy and OA samples; red boxes highlight their expression levels (blue) in Cluster 3. D) Violine plots showing upregulation of chondrocytes expressing OA-specific genes. E) Feature plots showing the expression of CCL20 and LAMB3 in Cluster 3 (MDCs) of OA samples; red boxes highlight their expression levels (blue). F) Violine plots showing chondrocytes expressing mineralization and osteogenic transition-related genes in Cluster 18.\u003c/p\u003e","description":"","filename":"AtlasFigure4.png","url":"https://assets-eu.researchsquare.com/files/rs-6247502/v1/c1889c49e604fb61aad95e20.png"},{"id":82007376,"identity":"ad8b1dbb-6ecc-4875-8618-ee5ce302f9c2","added_by":"auto","created_at":"2025-05-05 23:33:08","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":4190766,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSynovium and meniscus are primary residences for tissue stem cells depleted due to OA.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA) Stacked bar plots show comparative cell type proportion in each tissue type during healthy and OA conditions; TSCs are shown in brown color and highlighted in a rectangle. B) UMAP shows the drastic depletion of the TSCs pool in OA compared to the healthy samples. C) Extraction and UMAP visualization of TSCs pool in meniscus and SynoFP during healthy and OA conditions. D) Bar plots show levels of total TSCs in all four tissue types: CartNorm: Healthy cartilage, CartOA: OA cartilage, MenNorm: Healthy meniscus, MenOA: OA meniscus, SCBNorm: Healthy subchondral bone, SCBOA: OA subchondral bone, SynofpNorm: Healthy synovium \u0026amp; infrapatellar fat pad, SynofpOA: OA synovium \u0026amp; infrapatellar fat pad; (Blue: Healthy samples, Red: OA samples). E) Violine plots show TSCs expressing chondroprogenitor and stem cell markers in healthy and OA conditions. F-H) CXCL12 (SDF1), MCAM (CD146), and ENG (CD105, Endoglin) expressing TSCs from meniscus and SynoFP in healthy and OA conditions.\u003c/p\u003e","description":"","filename":"AtlasFigure5.png","url":"https://assets-eu.researchsquare.com/files/rs-6247502/v1/4161b675de806134ad681268.png"},{"id":82007523,"identity":"e42056e9-1eee-41fa-85f5-dc0f59d211f8","added_by":"auto","created_at":"2025-05-05 23:41:08","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":4093297,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIncreased levels of novel quadruple positive inflammation and pain-associated macrophages in OA.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA) Extraction and UMAP visualization of the total macrophages in healthy and OA samples. Red boxes highlight the macrophage subtypes enriched in OA samples: MC2, MC3, and MC4 (MC: Macrophage Cluster). B) Visualization of M1 and M2 macrophages in healthy and OA samples, where we used CD86 and TNF as classical M1 macrophage markers and CD163 and MRC1 as classical M2 macrophage markers. C) Violine plots showing significant inflammatory markers expressing MCs, where MC3 stands out as a unique cluster expressing all four inflammatory markers (IL1B, IL6, TNF, and NOS2) (quadruple markers). D-E) Feature plots and violin plots show MC3 expressing quadruple markers. F) Violine plots showing higher enrichment of macrophages expressing classical pain markers in knee OA.\u003c/p\u003e","description":"","filename":"AtlasFigure6.png","url":"https://assets-eu.researchsquare.com/files/rs-6247502/v1/d0feb55531074b7a00f0b0dd.png"},{"id":88148954,"identity":"dddc8def-5084-4c55-8815-c19e716e8512","added_by":"auto","created_at":"2025-08-02 07:10:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":23645370,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6247502/v1/af3da054-6091-4d8d-b924-d04ea5ddb8f8.pdf"},{"id":82007298,"identity":"3fcd18ff-4622-481b-af7b-2d75a0ebc086","added_by":"auto","created_at":"2025-05-05 23:25:08","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1495977,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure Legends:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S1: UMAP cluster identification and pseudotime trajectory analysis in healthy knee tissues: A)\u003c/strong\u003e UMAP shows the before integration (Unintegrated) and after harmony integration (Integrated) scRNA seq samples from healthy cartilage, meniscus, subchondral bone, and SynoFP; CartNorm: Healthy cartilage, MenNorm: Healthy meniscus, SCBNorm: Healthy subchondral bone, SynofpNorm: Healthy SynoFP. \u003cstrong\u003eB)\u003c/strong\u003e A total of 15 clusters were identified at 0.5 resolution after harmony integration.\u003cstrong\u003e C)\u003c/strong\u003e Cell type contribution of individual tissue type in a healthy human knee. \u003cstrong\u003eD)\u003c/strong\u003eHighly active signaling pathways in a healthy human knee.\u003cstrong\u003e E)\u003c/strong\u003eContribution of individual tissue type in TSCs and chondrocytes populations for pseudotime trajectory analysis.\u003c/p\u003e","description":"","filename":"AtlasFigureS1.png","url":"https://assets-eu.researchsquare.com/files/rs-6247502/v1/69a6248dbdb64b5526e1e754.png"},{"id":82007118,"identity":"ae8cb030-f60f-4d30-b7ac-d15431bf9c31","added_by":"auto","created_at":"2025-05-05 23:17:08","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1702882,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig. S2: UMAP cluster identification and pseudotime trajectory analysis in OA knee tissues: A)\u003c/strong\u003e UMAP shows the before integration (Unintegrated) and after harmony integration (Integrated) scRNA seq samples from OA cartilage, meniscus, subchondral bone, and SynoFP; CartOA: Cartilage of OA patients, MenOA: Meniscus of OA patients, SCBOA: Subchondral bone of OA patients, SynofpOA: SynoFP of OA patients. \u003cstrong\u003eB)\u003c/strong\u003e A total of 17 clusters were identified at 0.5 resolution after harmony integration. \u003cstrong\u003eC)\u003c/strong\u003e Cell type contribution of individual tissue type in the human knee with OA. \u003cstrong\u003eD)\u003c/strong\u003eHighly active OA-specific signaling pathways in the human knee with OA. \u003cstrong\u003eE)\u003c/strong\u003eContribution of individual tissue type in TSCs and chondrocytes populations for pseudotime trajectory analysis.\u003c/p\u003e","description":"","filename":"AtlasFigureS2.png","url":"https://assets-eu.researchsquare.com/files/rs-6247502/v1/c7a72facdd7d688221e8c193.png"},{"id":82007312,"identity":"69c5023b-797d-470b-a493-7b9eec79d4c6","added_by":"auto","created_at":"2025-05-05 23:25:08","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":2431043,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig. S3:\u003c/strong\u003e \u003cstrong\u003eUMAP of total cell types in combined samples of healthy and OA human knee:\u003c/strong\u003e \u003cstrong\u003eA)\u003c/strong\u003e UMAP shows the before-integration (Unintegrated) and after-Harmony integration (Integrated) scRNA seq samples from human healthy and OA samples. \u003cstrong\u003eB)\u003c/strong\u003e Contribution of individual tissue type within the Harmony integrated healthy and OA samples. \u003cstrong\u003eC)\u003c/strong\u003e UMAP representation of total cell types in combined samples of healthy and OA human knee identified by SingleR. \u003cstrong\u003eD)\u003c/strong\u003e The proportion of each cell type in healthy human and OA knees; here, the TSC pool significantly decreased in OA samples, whereas there was an increase in detrimental chondrocytes.\u003cstrong\u003e E)\u003c/strong\u003eFeature plot analysis shows the MDCs expressing OA-specific genes; the colored rectangle highlights the cells (MDCs) expressing a particular gene in healthy and OA samples. \u003cstrong\u003eF)\u003c/strong\u003e Violin plots show the elevated expressions of cartilage degeneration and inflammatory immune response genes, including MMP13, TNFRSF11B, and NOS2 in OA samples. \u003cstrong\u003eG)\u003c/strong\u003e Violin plots show the overexpression of osteogenic transition and mineralization-related genes in human knee OA samples.\u003c/p\u003e","description":"","filename":"AtlasFigureS3.png","url":"https://assets-eu.researchsquare.com/files/rs-6247502/v1/b5296266199e1b55be831bc9.png"},{"id":82007522,"identity":"e2586d68-10ab-46eb-a527-fc38fbf4f70c","added_by":"auto","created_at":"2025-05-05 23:41:08","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":680549,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig. S4:\u003c/strong\u003e \u003cstrong\u003eTissue stem cells and markers expression:\u003c/strong\u003e \u003cstrong\u003eA)\u003c/strong\u003e Violin plots show TSCs expressing stem cell and chondroprogenitor markers during healthy and OA conditions in human knee. \u003cstrong\u003eB)\u003c/strong\u003e Feature plots show TSCs expressing stem cell and chondroprogenitor markers during healthy and OA conditions in human knee; here, blue represents cells expressing a particular gene.\u003c/p\u003e","description":"","filename":"AtlasFigureS4.png","url":"https://assets-eu.researchsquare.com/files/rs-6247502/v1/f039f0d026996170fb00c229.png"},{"id":82007308,"identity":"9f804bb6-d12f-46ba-948f-6c4f5a5f6135","added_by":"auto","created_at":"2025-05-05 23:25:08","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":1365749,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig. S5: Inflammatory and pain macrophages markers:\u003c/strong\u003e \u003cstrong\u003eA)\u003c/strong\u003eFeature plots showing total macrophages expressing key proinflammatory M1 macrophage marker genes (CD86 and TNF) during healthy and OA conditions. \u003cstrong\u003eB)\u003c/strong\u003eFeature plots showing total macrophages expressing key M2 macrophage marker genes (CD163 and MRC1) during healthy and OA conditions. \u003cstrong\u003eC)\u003c/strong\u003e Bubble plot represents the percent expression of specific M1 marker genes within each cluster of total macrophages in healthy and OA samples; Note: percent expression only represents the cells expressing a particular gene compared to the total cells within that cluster, i.e., if the ball size in healthy is more significant than its OA counterpart does not necessarily represent the overall expression levels, as the number of M1 macrophages are lower in healthy but higher in OA. \u003cstrong\u003eD)\u003c/strong\u003e Bubble plot represents the percent expression of specific M2 marker genes within each cluster of total macrophages in healthy and OA samples. \u003cstrong\u003eE)\u003c/strong\u003e Feature plots highlighting quadruple positive macrophages (Feature plot for TNF has been shown above in S5A). \u003cstrong\u003eF)\u003c/strong\u003e The violin plot shows the total macrophages expressing IL1B, IL6, and NOS2 during healthy and OA conditions.\u003c/p\u003e","description":"","filename":"AtlasFigureS5.png","url":"https://assets-eu.researchsquare.com/files/rs-6247502/v1/5d5855ff26dcfc75592e1dda.png"},{"id":82007135,"identity":"ad5d9661-3d97-4085-b0e8-66d1867f3791","added_by":"auto","created_at":"2025-05-05 23:17:08","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":3585190,"visible":true,"origin":"","legend":"Table","description":"","filename":"SupplementaryTables.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6247502/v1/8f530a103583e4113587ed63.xlsx"},{"id":82007374,"identity":"3957ef0e-091d-4deb-96c1-379758f55d7d","added_by":"auto","created_at":"2025-05-05 23:33:08","extension":"png","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":1011298,"visible":true,"origin":"","legend":"Graphical abstract","description":"","filename":"GraphicalAbstractKneescRNAAtlas.png","url":"https://assets-eu.researchsquare.com/files/rs-6247502/v1/922b0e9b68dc749993d03839.png"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Constructing a cross-tissue human knee single-cell atlas identified osteoarthritis reduces regenerative tissue stem cells while increasing inflammatory pain macrophages","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOsteoarthritis (OA) vexes over 520\u0026nbsp;million adults worldwide, manifesting clinically as pain, swelling and decreased joint mobility with associated treatment costs (direct and indirect) approaching \u003cspan\u003e$\u003c/span\u003e486.4\u0026nbsp;billion annually. Osteoarthritis (OA) is a prevalent and debilitating joint disease characterized by the progressive degeneration of cartilage, synovium, bone, and meniscus, leading to chronic pain and impaired mobility. The pathophysiology of OA has been related to various biochemical\u003csup\u003e \u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e \u003c/sup\u003e, biomechanical\u003csup\u003e \u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e \u003c/sup\u003e, metabolic\u003csup\u003e \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e \u003c/sup\u003e, and gene-regulated\u003csup\u003e \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e \u003c/sup\u003e mechanisms occurring over an extended timeline. Despite its widespread impact, the cellular and molecular mechanisms underlying human clinical OA remain incompletely understood due to the lack of cross-tissue OA atlas. Thus, we constructed the first comprehensive single-cell atlas of the human knee affected by osteoarthritis. By analyzing cartilage, synovium, subchondral bone, and meniscus tissues, we aim to elucidate the distinct cellular populations and their roles in OA pathogenesis. Our investigation includes stem cells, macrophages, and other immune cells, highlighting their contributions to inflammation and tissue remodeling.\u003c/p\u003e \u003cp\u003eDysregulated balance of tissue degeneration and regeneration in the joint leads to OA pathology, which are governed by tissue stem cells (TSCs). TSCs perform specific functions, and various types of TSCs are enriched in the synovium, meniscus, and cartilage. Studies have identified numerous chondroprogenitor and stem cell markers expressed in TSCs\u003csup\u003e\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Stem cells differentiate into chondrocytes during OA\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e and have the potential for cartilage repair\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. The distinction between various TSCs can help to evaluate the balance of a specific pool. TSCs expressing regenerative factors can be categorized as regenerative TSCs. TSCs expressing factors related to osteogenic differentiation, inflammation, and OA are osteogenic TSCs. TSC pool could be dysregulated with OA, injury and inflammation.\u003c/p\u003e \u003cp\u003eMechanical overloading or biomechanical changes\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e that propagate to structural tissue failure (fissuring/fibrillation\u003csup\u003e16\u003c/sup\u003e), tissue swelling\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, compositional loss of GAG\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, and derangement of the COLII network\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Mechanical injury also incites an inflammatory response and elevated cytokines in OA synovial fluid (e.g., IL-1B, TNF-a).\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Depletion of cartilage GAG diminishes its rheological and tribological properties\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, independently contributing to the propagation of OA pathophysiology\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Joint kinematic dysfunction due to trauma, obesity, or life-long use is one of the main risk factors for OA\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. The resulting increased mechanical stress causes injury to the principal load-bearing tissues of the knee joint, meniscus, and cartilage\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e as well as to the synovium and subchondral bone. Damage to even one of these tissues leads to a cascade of alterations in the other tissues, emphasizing the interrelated nature of joint tissue degeneration in OA. All knee joint tissues, including the cartilage, menisci, synovium, and subchondral bone, are affected by OA\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Despite this inter-tissue dependence, studies have typically focused on individual tissue types such as cartilage\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, cartilage and meniscus\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, synovium and infrapatellar fat pad\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e, and subchondral bone\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, mainly omitting the underlying cross-tissue mechanisms. Recent developments in single-cell RNA sequencing (scRNA-seq) analysis and genomic technologies have provided insights into the crosstalk between cells in tissues or nearby tissues. As OA is an entire joint disease, analysis of knee joint tissues, including cartilage, meniscus, synovium, and subchondral bone, and their interaction at the single-cell level is of interest and may provide a mechanistic understanding of knee OA development.\u003c/p\u003e \u003cp\u003eIn this study, we constructed an atlas of human knee single-cell transcriptomic profiles and identified changes in specific stem cells, macrophages and detrimental chondrocytes. We present a scRNA-seq atlas of 53 human knee joint samples to evaluate the trajectory of cartilage, meniscus, synovium, and subchondral bone cells. Integrated analysis identified OA-specific cell-type clusters as well as inter-relationships between different tissues. The analysis included: 1) The effect and balance of TSCs during healthy and OA conditions; 2) Enrichment of MMP13 or catabolic factor expressing chondrocytes, proinflammatory macrophages expressing quadruple positive markers (IL1B-IL6-NOS2-TNF+), and pain markers such as P2RX7; and 3) identification of co-relative mechanisms for future translation. This knee joint scRNA-seq atlas provides a comprehensive analysis of tissue-specific factors, recognizing crosstalk between the various cells in adjacent synovial tissues that could be targets for therapeutic interventions to mitigate OA. Through this atlas, we identify key cellular subsets and molecular pathways involved in OA, offering potential targets for therapeutic intervention. This work represents a significant step forward in understanding the complex cellular landscape of OA and paves the way for future research and treatment strategies.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cp\u003e \u003cb\u003eHuman healthy and OA knee specimens.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWith prior consent from the patients, samples of healthy and OA patients for cartilage, meniscus, synovium, infrapatellar fat pad (SynoFP), and subchondral bone (SCB) were collected from the NCBI Gene Expression Omnibus (GEO) database (please also see Methods and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). The sample description and corresponding accession IDs show specific characteristics that include the entire knee joint tissue. Here, GEO Series (GSE) identifies individual accession ID under which the raw sequencing data files are publicly available (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe samples with accession ID GSE220243: \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eHealthy Samples\u003c/span\u003e: Matching healthy cartilage (n\u0026thinsp;=\u0026thinsp;6) and meniscus (n\u0026thinsp;=\u0026thinsp;7) samples were obtained from the same knee, and only knees with grades 0 or 1 were considered (Graded macroscopically using Outerbridge System). The cartilage samples in their study were collected from the weight-bearing medial femoral condyle, whereas the whole meniscus was collected. \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eOA samples\u003c/span\u003e: Corresponding OA samples for cartilage samples (n\u0026thinsp;=\u0026thinsp;6; grade 4) were collected from medial femoral osteochondral slabs, and meniscus samples (n\u0026thinsp;=\u0026thinsp;6) were also collected, excluding the ones with large calcium deposits\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe samples with accession ID GSE169454: \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eNon-Arthritic Samples\u003c/span\u003e: non-arthritic femoral condyle cartilage specimens (n\u0026thinsp;=\u0026thinsp;3) were collected from fresh osteochondral allografts discarded during donor plug harvesting during surgical implantation\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eOA Cartilage Samples\u003c/span\u003e: OA cartilage samples (n\u0026thinsp;=\u0026thinsp;4) were extracted from human patients undergoing total knee joint replacement surgery for OA with prior consent from patients,\u003c/p\u003e \u003cp\u003eThe samples with accession ID GSE255460: \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eNon-OA Controls\u003c/span\u003e: Samples were collected from three non-OA controls who underwent amputation with no prior history of joint injury or disease.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eOA Cartilage Samples\u003c/span\u003e: Cartilage samples were collected from eight patients with OA who underwent knee arthroplasty surgery\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe samples with accession ID GSE216651: \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eOA SynoFP\u003c/span\u003e: Three OA SynoFP samples were obtained from individuals with end-stage knee OA who underwent total knee replacement surgery.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eNon-OA SynoFP\u003c/span\u003e: Non-OA SynoFP biopsies were obtained from patients who underwent excision of bone tumors surrounding the knee joint or from organ transplant donors\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe samples with accession ID GSE196678 were SCB samples isolated from the medial and lateral tibial plateaus of two patients with OA undergoing knee replacement surgery. These samples were divided into two groups: control (n\u0026thinsp;=\u0026thinsp;2) from the lateral tibial plateau and OA (n\u0026thinsp;=\u0026thinsp;2) from the medial side\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBriefly, all healthy samples from the cartilage, meniscus, SynoFP, and SCB were processed individually for quality control and doublets and integrated using the harmony integration method in Seurat. Similarly, all OA samples were processed and subjected to CellChat\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e and pseudotime trajectory analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb, c). Finally, to perform comparative analysis, both preprocessed healthy and OA samples were integrated and subjected to clustering, cell identity, and cell type proportion analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed). This was followed by the extraction of macrophages and TSCs for downstream analyses. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec, 130012 cells from healthy and 195742 cells from OA were retained after quality control and preprocessing. The total number of cells retained from individual tissue types and analyzed were included (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb, c).\u003c/p\u003e \u003cp\u003e \u003cb\u003eQuality control and preprocessing.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIndividual files of Healthy and OA patients single-cell RNA sequencing (scRNA-seq) for knee joint cartilage, meniscus, synovium, infrapatellar fat pad (SynoFP), and subchondral bone were downloaded from the NCBI GEO and processed independently. The zipped files contained a count matrix, features (genes), and barcode files, which were imported into R studio and converted to a Seurat object using the \u003cem\u003eCreateSeuratObject\u003c/em\u003e function in the Seurat R package (v5.1.0)\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e with no initial cutoffs. Further details about the sample characterization and categorization are described above.\u003c/p\u003e \u003cp\u003eTo filter out low-quality cells, we eliminated cells with less than 3,000 RNA counts, 400 genes (features) detected, and more than 10% reads coming from mitochondrial genes. The retained high-quality cells were further normalized using the default \u003cem\u003eLogNormalize\u003c/em\u003e method and a scale factor of 10,000 within \u003cem\u003eNormalizeData\u003c/em\u003e function of Seurat. Clustering was performed with 20 Principal Components (PCs) at a resolution of 0.5, using 2,000 variable features found using \u003cem\u003eFindVariableFeatures\u003c/em\u003e with the \"vst\" selection method. The criteria for selecting PCs were defined using elbow plots. Next, \u003cem\u003eDoubletFinder\u003c/em\u003e R package (v2.0.4) was used to eliminate doublet cells\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. After quality control and preprocessing 130012 cells from healthy and 195742 cells from OA cells were retained.\u003c/p\u003e \u003cp\u003e \u003cb\u003eData Integration and cluster identification.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAll individually processed files were then combined into a single Seurat object. Combined files were subjected to data integration using \u003cem\u003eHarmonyIntegration\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e method within \u003cem\u003eIntegrateLayers\u003c/em\u003e function of Seurat\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. For downstream processing, 20 PCs were used for harmony clustering at a 0.5 resolution. Healthy samples were combined to understand their cellular and molecular landscapes. The OA samples were combined to understand the cellular and molecular landscapes. Both Healthy and OA samples were integrated to identify common and unique mechanisms.\u003c/p\u003e \u003cp\u003e \u003cb\u003eDifferential marker analysis and cell type identification.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe \u003cem\u003eJoinLayers\u003c/em\u003e function was used to merge all integrated layers. We performed differential expression analysis using \u003cem\u003eFindAllMarkers\u003c/em\u003e function to identify the differentially expressed marker genes in each harmony cluster. The Wilcoxon rank-sum test (Wilcox) was used to perform the analysis with \u003cem\u003elogfc.threshold\u003c/em\u003e of 0.25, singleR (v2.8.0) and celldex (v1.16.0) R packages were used to identify cell types. \u003cem\u003eHumanPrimaryCellAtlasData\u003c/em\u003e from celldex was considered for this study because it includes almost all types of cells, including stem cells and immune cells\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. TSCs and Macrophages were extracted using \u003cem\u003ea subset\u003c/em\u003e function of base R for downstream analyses.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCellChat analysis.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eCellChat (v2.1.2) was run on the RNA data slot and separately on the healthy and OA samples.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Overexpressed genes were identified using default parameters of \u003cem\u003eidentifyOverExpressedGenes\u003c/em\u003e function. Communication probabilities were computed using trim\u0026thinsp;=\u0026thinsp;0.1, type\u0026thinsp;=\u0026thinsp;triMean, and other default parameters of \u003cem\u003ecomputeCommunProb\u003c/em\u003e function. Communications were filtered to include those with at least 100 cells. The two cell-chat objects were merged to compare their interaction occurrences and strengths. \u003cem\u003eComputeCommunProbPathway\u003c/em\u003e function detected actively communicating signaling pathways. Data were visualized in a chord diagram, heatmaps, and scatter plots using the corresponding functional commands of the CellChat package.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePseudotime trajectory analysis.\u003c/b\u003e \u003c/p\u003e \u003cp\u003ePseudo-trajectories of chondrocytes and TSCs were constructed using Monocle3\u003csup\u003e42\u003c/sup\u003e. The Seurat object was converted to the monocle3 cell_data_set object using \u003cem\u003eas.cell_data_set\u003c/em\u003e function and preprocessed, and 20 PCs were retained using the PCA method. Dimensionality reduction was performed using the UMAP method and was clustered using the cluster_ cell function. The \u003cem\u003elearn_graph\u003c/em\u003e function was used to learn and build the trajectory. O\u003cem\u003erder_cells\u003c/em\u003e and \u003cem\u003epseudotime\u003c/em\u003e functions were used to order the cells at the pseudotime. Root nodes were selected from the TSCs cluster, considering chondroprogenitor cells as part of the TSCs.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Visualization\u003c/h2\u003e \u003cp\u003eUniform Manifold Approximation and Projection (UMAP) was used to visualize single-cell data. Violine plots, heatmaps, feature plots, and bar plots were generated using \u003cem\u003evlnplot\u003c/em\u003e (Seurat), \u003cem\u003enetAnalysis_signalingRole_heatmap\u003c/em\u003e (CellChat), \u003cem\u003eFeatureplot\u003c/em\u003e (Seurat), and \u003cem\u003eggplot2\u003c/em\u003e functions, respectively.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eCellular and molecular landscape of healthy human knee at single-cell resolution.\u003c/span\u003e \u003c/p\u003e \u003cp\u003eTo delineate the cellular and molecular landscapes of the human knee joint and understand the contribution of different tissues to normal function, scRNA-seq samples were integrated. Healthy cartilage, meniscus, SynoFP, and SCB were harmony-integrated, clustered, and subjected to cell identity analysis using the H\u003cem\u003eumanPrimaryCellAtlas\u003c/em\u003e database in c\u003cem\u003eelldex\u003c/em\u003e using \u003cem\u003eSingleR\u003c/em\u003e R packages (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea; Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003ea, b). UMAP shows all the identified cell types, and Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e shows the proportion of each cell type (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). Indeed, the chondrocyte population was dominant and contributed\u0026thinsp;~\u0026thinsp;99.6% of the healthy cartilage samples, whereas the TSCs population contributed only\u0026thinsp;~\u0026thinsp;0.4% of the total cell population (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb; Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eb). The chondrocyte population was also enriched in the meniscus, contributing\u0026thinsp;~\u0026thinsp;85.3%, along with ~\u0026thinsp;9.5% of TSCs and a small proportion of endothelial cells (EC) (~\u0026thinsp;2.7%), smooth muscle cells (SMC) (~\u0026thinsp;1.3%), fibroblasts (~\u0026thinsp;0.5%), and immune cells (including\u0026thinsp;~\u0026thinsp;0.7% macrophages). However, the proportion of chondrocytes was low in the SynoFP group (approximately 15%) and nearly absent in the SCB group (0.3%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eInterestingly, the TSCs pool was significantly higher in SynoFP, contributing to approximately 42.2% of the total cell population, along with ~\u0026thinsp;15.7% ECs, ~\u0026thinsp;13.1% macrophages, ~\u0026thinsp;5% monocytes, ~\u0026thinsp;5.4% SMCs, ~\u0026thinsp;1.5% synovial fibroblasts, and a relatively small proportion of other immune cell populations. In SCB, T cells (~\u0026thinsp;48.9%) and natural killer (NK) cells (~\u0026thinsp;36.1%) together contribute nearly 85% of the total cell population, along with a small proportion of macrophages (2.8%), monocytes (2.7%), TSCs (1.7%), and other immune cell populations. Overall, this data suggests that chondrocytes are predominant in the cartilage and meniscus, TSCs largely reside in SynoFP and the meniscus, and SynoFP and SCB are major reservoirs for the immune cells in healthy human knees.\u003c/p\u003e \u003cp\u003eTo identify signaling and communication, CellChat analysis was performed which showed the active communication between all four tissues. The cartilage was a major sender and receiver of signals, followed by the meniscus and SynoFP. SCB was mainly a receiver of signals from the remaining three tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). Analysis of cell types showed MSCs, fibroblasts, SMCs, chondrocytes, and TSCs were the major senders of the signals, whereas MSCs, macrophages, monocytes, dendritic cells (DCs), and T-cells were the major receivers of the signals (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed, e). Approximately 85 signaling pathways actively send and receive signals. The most active top 10 signaling pathways are COLLAGEN, MIF, MHC-I, MHC-II, FN1, CD99, LAMININ, APP, CypA, and CXCL (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef, Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003ed).\u003c/p\u003e \u003cp\u003ePseudotime trajectory analysis which determines the origin and terminal differentiation state of chondrocytes \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, was performed by extracting TSCs and chondrocytes from the total cell population (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg). Using TSCs clusters as a root node, we performed the analysis and visualized on the UMAP (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eh). All four tissues contributed to TSCs and chondrocyte populations; however, the contribution of SCB was negligible (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003ee). Cluster 8 had the lowest Pseudotime since it mostly consists of TSCs and is considered a root node, whereas Cluster 5 and Cluster 0 had the highest Pseudotime, suggesting the terminally differentiated chondrocyte population, primarily residing in the cartilage (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ei; Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eb, e).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eCellular and molecular landscape of the human knee during OA at single-cell resolution.\u003c/span\u003e \u003c/p\u003e \u003cp\u003eTo evaluate the changes in cellular homeostasis during OA, samples were subjected to clustering and cell type identification (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003ea; Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003ea, b). Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e lists the proportion of each cell type. OA-cartilage has more than ~\u0026thinsp;99% chondrocytes population, ~\u0026thinsp;0.1% TSCs, 0.4% macrophages and 0.1% monocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eb; Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003ec). In the OA-meniscus, the population was ~\u0026thinsp;82.6% chondrocytes, ~\u0026thinsp;6.8% TSCs, ~\u0026thinsp;3.9% macrophages, ~\u0026thinsp;2.8% ECs, ~\u0026thinsp;1.2% SMCs, ~\u0026thinsp;0.8% monocytes, and 0.3% fibroblasts. OA-synovium had\u0026thinsp;~\u0026thinsp;37.5% chondrocytes and ~\u0026thinsp;16.4% TSCs. Interestingly, synovium had a higher number of macrophages (~\u0026thinsp;13.7%), fibroblasts (~\u0026thinsp;7.7%) and monocytes (~\u0026thinsp;1.8%), suggesting increased fibrosis and inflammation in knee OA. In SCB, NK cells (~\u0026thinsp;32.6%) and T cells (~\u0026thinsp;50.6%) contributed to ~\u0026thinsp;83.2% of the total cell population, along with a small proportion of TSCs (~\u0026thinsp;2%), macrophages (~\u0026thinsp;1.3%), monocytes (~\u0026thinsp;3.3%), chondrocytes (~\u0026thinsp;1%), and other immune cell populations. Overall, chondrocyte population significantly increased in OA-synovium. In contrast, the TSCs were reduced in OA synovium and meniscus. Macrophage infiltration was increased in the meniscus and synovium. Monocyte infiltration was elevated whereas ECs were reduced in synovium.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCellChat analysis showed OA-cartilage was a major sender and receiver of signals, followed by the meniscus and synovium, whereas SCB was mainly a receiver of signals from the remaining three tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). Unlike healthy tissues, the number of interactions increased between cartilage and SynoFP, and meniscus and synoFP, suggesting active immune signaling during OA. Strong intercellular interactions were observed between cell types (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003ed; Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003ed). MSCs, fibroblasts, SMCs, chondrocytes, TSCs, neurons, fibroblasts, and macrophages were the major senders of the signals, whereas MSCs, macrophages, neurons, and TSCs were the major receivers (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003ee). OA promotes intricate processes, such as cartilage degradation, inflammation, and pain, which are influenced by specific signaling pathways\u003csup\u003e\u003cspan additionalcitationids=\"CR44 CR45 CR46 CR47\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. The top 10 most active signaling pathways in OA were COLLAGEN, FN1, MIF, LAMININ, APP, MHC-II, CD99, CypA, MHC-I, and CXCL (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003ef). Additional pathways, such as prostaglandins, MK, VISFATIN, ANGPTL, and THBS, were highly active in OA (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003ef; Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003ed).\u003c/p\u003e \u003cp\u003ePseudotime trajectory analysis identified the terminally differentiated chondrocytes increased in cartilage as well as meniscus since both these tissues contributed to the highest Pseudotime clusters 1 and 3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eg-i; Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003ee). Thus, the reduced TSCs population in the meniscus and synovium OA compared to the healthy knee joint shows a transition to terminally differentiated chondrocytes, which contributes to fibrosis or osteogenic transition in OA.\u003c/p\u003e\n\u003ch3\u003eMMP13 producing detrimental chondrocytes and synovial fibroblasts were expanded in OA\u003c/h3\u003e\n\u003cp\u003eTo detect unique cellular and molecular OA-specific variations, healthy and OA knee scRNA-seq samples were integrated and subjected to harmony integration following standard Seurat processing (Fig. \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003ea). Cell type detection using singleR revealed variability in the population of major cell types, such as chondrocytes, TSCs, macrophages, and most importantly, expansion of synovial fibroblasts in OA (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, Fig. \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003eb, c). To correlate with the individual analyses described above, a stacked bar plot was generated and compared the cell proportion in both the sample types (Fig. \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003ed). Clustering was performed at a resolution of 0.5 and generated nearly 27 cell clusters with clusters 3, 10, 18, 19, and 21 expanded, whereas major cluster 1 was depleted in the OA samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). All marker analyses were performed to determine the molecular identity of these clusters (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOA-depleted Cluster 1 expressed genes, such as CYTL1, CLEC3A, S100B, and FRZB, which are effector chondrocyte (EC) markers\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). These EC also produce WISP3\u003csup\u003e50\u003c/sup\u003e, CTGF\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e, CYR61\u003csup\u003e51\u003c/sup\u003e, GREM1\u003csup\u003e52\u003c/sup\u003e, and WIF1\u003csup\u003e53\u003c/sup\u003e, which play roles in chondrocyte protection, angiogenesis, and ECM remodeling (Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe OA-specific chondrocyte cluster, Cluster 3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003eb), which is absent in healthy samples, contains specific Detrimental Chondrocytes (DCs) that promote cartilage/ECM degeneration, chondrocyte-to-osteoblast transition, and inflammation-related factors. DCs were enriched with MMP13\u003csup\u003e54\u003c/sup\u003e, TNFRSF11B (osteoprotegerin)\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e, LCN2\u003csup\u003e56,57\u003c/sup\u003e, MMP1\u003csup\u003e58\u003c/sup\u003e, MMP3\u003csup\u003e59\u003c/sup\u003e, ELF3\u003csup\u003e60,61\u003c/sup\u003e, WNT7B\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e, and NOS2\u003csup\u003e62\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003ec) and are referred to as MMP13 producing DCs (MDCs). Next, we confirmed that MDCs primarily produced OA-specific markers (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003ed; Fig. \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003ee, f). MDCs specifically produce CCL20 and LAMB3, which are important factors in inflammatory pain and cartilage damage, respectively\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e,\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003ee).\u003c/p\u003e \u003cp\u003eCluster 18 was exclusively present in OA samples and was molecularly aligned with the previously described pathogenic chondrocyte subpopulation owing to the higher expression of POSTN and ZEB1\u003csup\u003e29\u003c/sup\u003e. It highly expressed genes, such as NELL1\u003csup\u003e65,66\u003c/sup\u003e, LRRC15\u003csup\u003e67\u003c/sup\u003e, and COL3A1\u003csup\u003e68\u003c/sup\u003e, which play a role in OA progression via osteogenesis, fibrosis, and ECM degeneration (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). In addition, cluster 18 also expressed RUNX2, ASPN, and OGN, which are known to promote mineralization and osteoblasts (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003ef). Cluster 18 expressing genes showed negligible expression in the MDCs. Thus, cluster 18 and MDCs may contribute to worsening disease pathology in human knee OA.\u003c/p\u003e \u003cp\u003eCluster 10 showed slightly elevated levels of OA-expressing CHI3L1, CHI3L2, MT1G, MT1H, and MT1E regulatory chondrocyte markers (RegC)\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Cluster 19 comprised chondrocytes highly expressing IL10\u003csup\u003e69\u003c/sup\u003e, TM4SF1\u003csup\u003e70\u003c/sup\u003e, CHADL\u003csup\u003e\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e, MIA\u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e, MT1G\u003csup\u003e\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e, and COL2A1, which are associated with cartilage protection, matrix\u0026ndash;proteoglycan synthesis, and reverse calcification and degeneration. Therefore, clusters 10 and 19 appear to expand because of a compensatory response to protect the knee joint from the degenerative effects of OA.\u003c/p\u003e \u003cp\u003eOverall, MMP13 expressing DCs and cluster 18 expressing factors could play a role in specific pathologies and mechanisms in the development of OA, whereas restoring cluster 1 and 19 factors could reverse OA. In addition, expansion of the fibroblast population may result in fibrosis in the synovial region, adding a layer to the pathophysiology of OA.\u003csup\u003e\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eSynovium and meniscus are the primary residences for TSCs that are depleted in OA.\u003c/span\u003e \u003c/p\u003e \u003cp\u003eThe TSC population was significantly reduced in the SynoFP and menisci. In the meniscus, the TSCs proportion decreased from ~\u0026thinsp;9.5% to ~\u0026thinsp;6.8%, and SynoFP from ~\u0026thinsp;42.2% to ~\u0026thinsp;16.4%, which can also be correlated with the expansion of the differentiated chondrocyte population in SynoFP (from ~\u0026thinsp;15% to ~\u0026thinsp;37.5%) during OA (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). For further analysis, we extracted TSCs from the total cell clusters and generated UMAP to visualize reduced regenerative (Chondrogenic factors producing) and increased osteogenic TSCs in OA (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). As TSCs primarily reside in the meniscus and SynoFP, we generated UMAP to observe the different TSCs contributing to the different TSC subtypes (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). TSCs decreased by 36.45% in the meniscus and 37.77% in SynoFP compared with their respective healthy controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003ed). We observed a reduction in the number of regenerative TSCs that produced CXCL12 (SDF1), SOX9, ACAN, MCAM (CD146), PDGFRB, BMPR1B, ENG (CD105/Endoglin), and NGFR (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003ee, Fig. \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003ea, b). Previously identified chondroprogenitor and stem cell markers that express TSCs have also been affected\u003csup\u003e\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. These TSCs were SDF1\u0026thinsp;+\u0026thinsp;\u003csup\u003e12\u003c/sup\u003e, CD146\u0026thinsp;+\u0026thinsp;\u003csup\u003e75\u003c/sup\u003e, CD105\u0026thinsp;+\u0026thinsp;\u003csup\u003e76,77\u003c/sup\u003e,\u003csup\u003e77,78\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003ef-h).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eInterestingly, osteogenic TSCs expressing ALCAM, NT5E (CD73), NGF, and BDNF were increased in OA. NT5E (CD73) is known to increase in OA (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003ee) \u003csup\u003e\u003cspan additionalcitationids=\"CR80\" citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e. Comparative analysis of knee joint tissue compartments identified that the meniscus and synovium are the primary residences of tissue stem cells, which are significantly depleted during OA, contributing to the worst pathological outcome.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eElevated levels of unique IL1B-IL6-NOS2-TNF and pain markers P2RX7-producing macrophages contribute to OA pathophysiology.\u003c/span\u003e \u003c/p\u003e \u003cp\u003eWe hypothesized that OA promotes the infiltration of proinflammatory cells, which initiate a vicious cycle of cytokine production, leading to knee joint inflammation and pain. Integration of healthy and OA samples revealed an expansion of the macrophage population in cluster 13 in OA samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, b). Within this macrophage population, we identified seven different subpopulations of macrophages at a resolution of 0.5 and labeled them as macrophage clusters MC1-MC7 (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003ea). MC1 and MC2 were the largest clusters, with MC2 being largely expanded during OA, whereas MC3 and MC4 were exclusively present in OA samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo determine the levels of pro- and anti-inflammatory macrophages under healthy and OA conditions, we analyzed the levels of proinflammatory M1 (CD86 and TNF) and anti-inflammatory M2 (CD163 and MRC1)-type macrophages. We found that CD86 and TNF-producing macrophages were expanded in OA samples, whereas CD163 and MRC1-expressing macrophages were significantly depleted (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003eb). Feature plot analysis revealed that MC1 mostly expressed M2 macrophage markers, whereas MC2 and MC3 expressed M1 macrophage markers (Fig. \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003ea, b). Next, we analyzed the expression of the proinflammatory OA-causing markers IL1B, IL6, TNF, and NOS2 within each macrophage cluster (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003ec). Interestingly, IL1B and TNF were highly expressed in OA-specific macrophages, MC2 and MC1, suggesting a novel IL1B\u0026thinsp;+\u0026thinsp;TNF\u0026thinsp;+\u0026thinsp;inflammatory macrophage population, irrespective of their M1 and M2 status. These IL1B\u0026thinsp;+\u0026thinsp;and TNF\u0026thinsp;+\u0026thinsp;macrophages may serve as novel prognostic or diagnostic biomarkers of OA pathophysiology.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eNotably, we discovered that MC3, a unique OA-specific macrophage cluster, is the only cluster that expresses all four proinflammatory genes: IL1B, NOS2, IL6, and TNF (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003ec, Fig. \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003ea, e). Next, we extracted MC3 from the total macrophage clusters and confirmed the significantly upregulated expression of these genes in OA (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003ed, e). We termed this novel macrophage subpopulation quadruple-positive (IL1B\u0026thinsp;+\u0026thinsp;IL6\u0026thinsp;+\u0026thinsp;NOS2\u0026thinsp;+\u0026thinsp;TNF+) inflammatory macrophages that worsen the disease outcome in terms of joint inflammation and pain in patients with OA.\u003c/p\u003e \u003cp\u003eFinally, we analyzed the expression of classic pain marker genes in total macrophages to understand the association between OA macrophages and joint pain. As expected, P2RX7, CSF1R, AIF1, and PTGS2 (COX2)-producing macrophages were highly expanded in OA samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003ef). However, two well-studied OA pain markers, PIEZO2 and TACR1, are not expressed in macrophages. Thus, we conclude that clinical knee OA inflammation and pain arise due to the accumulation of unique dual- and quadruple-positive proinflammatory macrophages, which need to be functionally characterized in a large cohort of clinical samples in the future.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAn atlas was constructed by integrating single-cell RNA sequencing profiles of the cartilage, meniscus, synovium, and subchondral bone, which showed specific differences in health and OA knee. The analysis of the molecular landscapes of healthy and OA knees found that OA samples have increased cell-cell communications across the tissues, suggesting active TSCs and immune signaling during OA. However, terminally differentiated chondrocytes in OA originated from the Tissue stem cells (TSCs) residing in the synovium and meniscus identified through pseudotime trajectory analysis. Our findings highlight the synovium as a hotspot of degenerative and regenerative changes. TSCs, cross-tissue interaction, and inflammation affect cartilage integrity and indicate OA-specific alterations initiated in synovial tissue.\u003c/p\u003e \u003cp\u003eAs mentioned, TSCs primarily reside in the synovium. Regenerative TSCs were depleted in OA. This dynamic change reduces regeneration and increases degeneration. Regenerative TSCs\u003csup\u003e\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e express markers such as CXCL12 (SDF1), SOX9, ACAN, MCAM (CD146), PDGFRB, BMPR1B, ENG (CD105/Endoglin), and NGFR. SDF1-expressing TSCs are explicitly depleted in the meniscus, and studies have shown that SDF1 is required for chondroprogenitor cell migration during post-injury tissue repair in the meniscus\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. MCAM+ (CD146+) stem cells have previously shown a more significant migration potential towards degenerated intervertebral discs\u003csup\u003e\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e. CD105 promotes chondrogenesis of synovium-derived MSCs\u003csup\u003e\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e,\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e. Osteogenic TSCs, which express ALCAM, NT5E (CD73), NGF, and BDNF, were expanded in OA. ALCAM\u0026thinsp;+\u0026thinsp;cells can differentiate into osteoblasts, adipocytes, chondrocytes, and stromal cells, which support osteoclastogenesis, hematopoiesis, and angiogenesis\u003csup\u003e\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e\u003c/sup\u003e. NT5E is a marker of resting chondrocytes\u003csup\u003e\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e and is upregulated in OA\u003csup\u003e\u003cspan additionalcitationids=\"CR80\" citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e. Expanding fibroblasts in synovium may contribute to fibrosis in OA knees. There was a substantial elevation in inflammation- and pain-related macrophages in OA, including unique macrophage subpopulations with dual positive (IL1B and TNF) and quadruple positive (IL1B, TNF, IL6, and NOS2) nature.\u003c/p\u003e \u003cp\u003eOA-specific MDCs were enriched with degradative factors such as LCN2\u003csup\u003e56\u003c/sup\u003e, TNFRSF11B\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e, MMP1, MMP3, MMP13, NOS2, WNT7B\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e, and ELF3\u003csup\u003e60\u003c/sup\u003e,\u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e, which play significant roles in extracellular matrix destruction, bone remodeling, and cartilage degradation. OA-specific cluster 18 is enriched with RUNX2\u003csup\u003e66\u003c/sup\u003e, ASPN, and OGN, which are markers of mineralization and osteoblast characteristics\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e that contribute to stiffness. OA-specific MDCs were enriched in CCL20 and other markers associated with inflammation and pain. In the presence of CCL20, cartilage released more MMP-1, MMP-13, PGE2, GAG fragments, and IL-6, whereas collagen type II mRNA expression was inhibited\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe limitation of this study is that, although we generated a unique scRNA-seq atlas, the inclusion of a large number of samples with various stages of OA will provide the detailed mechanism for OA progression. OA disproportionately affects underserved populations\u003csup\u003e\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e,\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u003c/sup\u003e and females. The detailed temporal and spatial appearance of RNA from the time of an inciting injury through the initiation and progression of OA pathophysiology, its proteomics profile, and actual tissue changes need to be performed. Future studies should involve well-controlled clinical cohorts with age- and sex-matched large cohorts of samples and standardized tissue extraction procedures.\u003c/p\u003e \u003cp\u003eIn conclusion, the synovium and meniscus are the most damaged compartments, and synovium regeneration could have potential therapeutic opportunities considering highly dysregulated homeostasis. Atala et al. showed that the synovial environment causes cartilage deterioration and regeneration\u003csup\u003e\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e\u003c/sup\u003e. OA pain may be a consequence of resident TSCs depletion and proinflammatory changes in the synovium and meniscus. Moreover, dual- and quadruple-positive macrophages could serve as prognostic markers to identify OA severity pre-and post-treatment. As there are no FDA-approved drugs, our study shows that future clinical trials should consider the involvement of synovium and meniscus regeneration when designing future OA disease-modifying drugs. Our analysis also emphasizes the heterogeneity within the meniscus and bone compartments, revealing distinct cellular niches that may influence disease outcomes. Understanding the role of these niches in OA pathogenesis could lead to more targeted and effective treatments. This atlas provides a valuable resource for the scientific community, offering new perspectives on cellular and molecular mechanisms and opening up exciting possibilities for developing targeted therapies aimed at halting or reversing disease progression. Future studies should build on these findings to further elucidate the intricate cellular dynamics within the OA joint and translate these insights into clinical applications.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study was supported by an NIH grant R01 DE031413 (MB) and P30 AR072571 (TN).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAuthor Contributions:\u003c/u\u003e Rajnikant Dilip Raut performed the experiments and analyzed the data with the help of Amit Kumar Chakraborty and Manish V. Bais. Tuhina Neogi, Brian Snyder, Thomas P. Schaer, Michael Albro, Mark W. Grinstaff, Chao Zhang, and Manish V. Bais helped with the conception, interpretation, and manuscript editing. Manish V. Bais conceived and designed the study. Rajnikant Dilip Raut and Manish V. Bais, with Brian Snyder and Mark W. Grinstaff, interpreted data and wrote the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eConflicts of interest:\u003c/u\u003eThe authors declare that they have no conflicts of interest regarding the content of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eFinancial Interests:\u003c/u\u003e\u003c/strong\u003eThe authors declare that they have no financial interests regarding the content of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eDeclaration of generative AI in scientific writing:\u003c/u\u003e The authors declare that they have not used AI to write or edit this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eData Availability:\u0026nbsp;\u003c/u\u003eThe human knee OA single-cell RNA-seq data used in this study are publicly available under the following accession ID: cartilage (GSE220243, GSE169454, and GSE255460); meniscus (GSE220243); synovium and IPFP (GSE216651); and subchondral bone (GSE196678).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eArokoski, J., Kiviranta, I., Jurvelin, J., Tammi, M. \u0026amp; Helminen, H. 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Racial-Ethnic Differences in Osteoarthritis Pain and Disability: A Meta-Analysis. \u003cem\u003eJ Pain\u003c/em\u003e \u003cstrong\u003e20\u003c/strong\u003e, 629\u0026ndash;644 (2019).\u003c/li\u003e\n\u003cli\u003eBolander, J. \u003cem\u003eet al.\u003c/em\u003e The synovial environment steers cartilage deterioration and regeneration. \u003cem\u003eSci Adv\u003c/em\u003e\u003cstrong\u003e9\u003c/strong\u003e, eade4645 (2023).\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":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Knee OA, atlas, tissue stem cells, macrophage, pain, SDF1, MMP13","lastPublishedDoi":"10.21203/rs.3.rs-6247502/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6247502/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOsteoarthritis (OA) affects the entire knee joint; however, cross-tissue molecular mechanisms are poorly understood due to a lack of comprehensive, integrated analysis. We constructed the first comprehensive single-cell RNA sequencing knee OA atlas from articular cartilage, meniscus, synovium, and subchondral bone which showed active communication between them. Healthy synovium and meniscus contain the largest populations of tissue stem cells (TSCs) and immune cells that are altered in OA. The regenerative TSCs expressing SDF1, SOX9, CD146, PDGFRB, and CD105 decrease during OA, whereas osteogenic TSCs expressing osteogenic differentiation-related factor NT5E (CD73) are increased. In OA, the balance between regenerative and osteogenic TSCs shifts in the OA state with an increased number of osteogenic TSCs. We also report an increased level of quadruple-positive inflammatory (IL1B-IL6-NOS2-TNF) and pain marker (P2RX7) specific macrophages in OA. Fibroblasts are enriched in OA-synovium and may contribute to fibrosis. Importantly, OA cartilage contains unique MMP13-producing detrimental chondrocytes along with RUNX2-producing chondrocytes that worsen OA pathophysiology. This atlas provides a novel avenue for potential therapeutic applications in human knee OA and other musculoskeletal diseases and injuries, targeting synovium and meniscus to intervene in OA-specific molecular and cellular alterations.\u003c/p\u003e","manuscriptTitle":"Constructing a cross-tissue human knee single-cell atlas identified osteoarthritis reduces regenerative tissue stem cells while increasing inflammatory pain macrophages","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-05 23:17:03","doi":"10.21203/rs.3.rs-6247502/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"communications-biology","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"commsbio","sideBox":"Learn more about [Communications Biology](http://www.nature.com/commsbio/)","snPcode":"","submissionUrl":"","title":"Communications Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Communications Series","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"1a09b2e5-2be9-4994-85e0-c4cd7bfc7ee5","owner":[],"postedDate":"May 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":46217667,"name":"Health sciences/Rheumatology/Musculoskeletal system/Cartilage"},{"id":46217668,"name":"Health sciences/Rheumatology/Osteoimmunology"},{"id":46217669,"name":"Health sciences/Rheumatology/Rheumatic diseases/Osteoarthritis"}],"tags":[],"updatedAt":"2025-08-02T07:10:45+00:00","versionOfRecord":{"articleIdentity":"rs-6247502","link":"https://doi.org/10.1038/s42003-025-08586-8","journal":{"identity":"communications-biology","isVorOnly":false,"title":"Communications Biology"},"publishedOn":"2025-08-02 04:00:00","publishedOnDateReadable":"August 2nd, 2025"},"versionCreatedAt":"2025-05-05 23:17:03","video":"","vorDoi":"10.1038/s42003-025-08586-8","vorDoiUrl":"https://doi.org/10.1038/s42003-025-08586-8","workflowStages":[]},"version":"v1","identity":"rs-6247502","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6247502","identity":"rs-6247502","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}