Reduced mineralization potential of osteoblasts in adolescent idiopathic scoliosis: intrinsic dysfunction and crosstalk with TLR-activated chondrocytes

Reduced mineralization potential of osteoblasts in adolescent idiopathic scoliosis: intrinsic dysfunction and crosstalk with TLR-activated chondrocytes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Reduced mineralization potential of osteoblasts in adolescent idiopathic scoliosis: intrinsic dysfunction and crosstalk with TLR-activated chondrocytes Kai Sheng, Daniel G Bisson, Christopher A Coluni, Paolo Brigato, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7602845/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Patients with Adolescent Idiopathic Scoliosis (AIS) present with facet joint osteoarthritis, which may contribute to curve progression. While inflammatory mediators from degenerative cartilage are known to influence osteoclast activity, their effects on osteoblast function in AIS remain unclear. Methods Primary facet joint osteoblasts were isolated from AIS patients undergoing spinal fusion surgery and age-matched non-scoliotic (NSC) individuals from organ donors. Transcriptomic profiles were generated by RNA sequencing, and key regulatory pathways were identified through bioinformatic analysis. Selected genes of interest were validated in an expanded cohort by qPCR. Functional capacity was assessed by comparing mineralization between AIS and NSC osteoblasts in a hydroxyapatite–collagen (HA–Col) three-dimensional culture system. The influence of Toll-Like Receptor (TLR) 2- or 4-pre-activated chondrocytes on osteoblast function was evaluated through qPCR analysis of bone-associated genes and mineralization assays. Results AIS osteoblasts displayed 1,357 differentially expressed genes (635 upregulated, 722 downregulated) with enrichment of inflammatory pathways in Gene Ontology analysis and negative enrichment of bone-related gene sets in gene set enrichment analysis. Key osteogenic markers, including SP7, ALP, and COL1A1, were downregulated by RNA sequencing and confirmed by qPCR. Mineralization capacity was significantly impaired in AIS osteoblasts. Conditioned media from TLR2- or TLR4-pre-activated chondrocytes induced IL-6 expression, reduced osteocalcin levels, and further decreased osteoblast mineralization capacity. Conclusions AIS facet joint osteoblasts exhibit intrinsic mineralization deficits, which are exacerbated by inflammatory mediators released from TLR-activated chondrocytes. These findings identify TLR-mediated cartilage–bone signalling as a potential therapeutic target to preserve facet joint integrity and maintain subchondral bone remodelling in AIS. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Adolescent idiopathic scoliosis (AIS) is a complex spinal deformity characterized by lateral spinal curvature accompanied by vertebral rotation and, in many cases, a disruption of the normal sagittal alignment, thus manifesting as a true three-dimensional skeletal abnormality [ 1 ]. Despite its unknown etiology, AIS commonly appears during rapid adolescent growth spurts in previously healthy individuals, suggesting an intrinsic disturbance in skeletal development. Indeed, recent genetic studies have identified abnormalities in pathways critical to skeletal formation in AIS patients, highlighting variants in genes related to bone formation [ 2 – 4 ], extracellular matrix production [ 5 , 6 ], and melatonin signalling [ 7 , 8 ]. Clinically, AIS is also frequently associated with systemic osteopenia [ 9 ], reduced bone mineral density [ 9 , 10 ], and elevated bone turnover [ 11 ], risk factors that may collectively contribute to curve progression. The facet (zygapophyseal) joints, which articulate the posterior elements of vertebrae, play a critical role in guiding spinal motion and limiting excessive axial rotation [ 12 , 13 ]. In severe AIS, facetectomy is often performed at the curve apex and nearby segments to relieve tension and aid pedicle screw placement during spinal fusion. Our previous studies identified facet joint osteoarthritis (OA) in AIS patients [ 14 ], especially within segments exhibiting significant intervertebral axial rotation above and below the apex [ 15 ]. Moreover, the severity of facet cartilage degeneration inversely correlates with the quality of the underlying subchondral bone [ 15 ] and appears asymmetric between the two facets at the same spinal level. The reciprocal interaction between cartilage and bone is thought to contribute to the acceleration of joint deterioration, compromising the structural integrity and biomechanical function of facet joints [ 16 , 17 ]. Consequently, as facet joints become less effective at limiting axial rotation, the spine’s resistance to progressive deformity in AIS is compromised. Studies of adult OA and rheumatoid arthritis (RA) have demonstrated that the inflammatory joint microenvironment disrupts normal bone remodelling, largely by altering the balanced activities of osteoclasts (bone-resorbing cells) and osteoblasts (bone-forming cells) [ 17 , 18 ]. This disruption is believed to occur, at least in part, through inflammatory mediators secreted from osteoarthritic chondrocytes that penetrate microscopic pores within the subchondral bone plate [ 19 ]. Our recent research has implicated a Toll-Like Receptor (TLR)-mediated mechanism, whereby TLR activation in chondrocytes induces the production of macrophage colony-stimulating factor (M-CSF), a crucial cytokine driving osteoclast proliferation and differentiation [ 16 ]. TLR activation in AIS chondrocytes triggers the release of a broad spectrum of cytokines and chemokines [ 16 ], many of which have roles in the inhibition of osteoblast differentiation, as previously demonstrated in adult OA studies [ 20 – 22 ]. Whether osteoblast modulation is similarly activated within the facet joints of AIS patients has yet to be explored. In the current study, we hypothesize that inflammatory mediators released from degenerative facet joint cartilage from AIS patients adversely affect osteoblast function, impairing osteoblast mineralization capacity. Materials and methods Collection of clinical specimens : Facet joints were collected from 53 consenting AIS patients undergoing spinal fusion surgery at the Shriners Hospital for Children. Non-scoliotic control (NSC) facet joints were retrieved from 19 organ donors through a collaboration with Transplant Quebec Organ Donation Program. The average age was 27.6±8.5 for the non-scoliotic individuals and 15.3±1.6 for the AIS patients. Demographics, including age, sex, Cobb angle, and Lenke classification, along with detailed information on the experiments conducted with the specific facet joint samples, can be found in Table 1. The spinal level from which AIS facet joints are resected depends on the curve type and surgical need and includes both lumbar and thoracic levels. Facet joints from organ donors were also from both thoracic and lumbar levels to ensure a similar distribution and prevent variability due to the spinal level. AIS is more frequent in females, and 84.6% of the patients included in this study were female. The study was approved by the McGill University institutional review board in Montreal, Canada (IRB # Tissue Biobank 2019-4896 and A03-M10-23A/23-02-009). Written informed consent was received before participation in the study. Primary chondrocyte and osteoblast isolation: Facet joint chondrocytes were isolated as previously described by Bisson et al. [23] and Sheng et al. [16]. Briefly, cartilage was removed from subchondral bone, cut into small pieces, and digested with Collagenase Type II (Thermo Gibco™ 17101015). All chondrocyte cell culture experiments were conducted within passages 0-2. The facet joint bone, free of cartilage and ligaments, was processed for osteoblast isolation. Subchondral bone was broken into small pieces using a rongeur, and cortical bone was collected. After a thorough PBS wash to remove marrow cells, bone chips were digested with Collagenase Type II for 16 hours to eliminate residual soft tissue. The digested chips were then placed in T75 flasks with complete Dulbecco's DMEM (Sigma Aldrich D5648; 4.5 g/L glucose, 10% FBS, 25 μg/mL gentamycin, and 2 mmol/L Glutamax). The media was refreshed every two days. Osteoblasts typically emerged and formed colonies within 4 weeks. These cells were then trypsinized, and 1 million cells were seeded/ T75 flask. Full confluence was reached within 2 weeks. For RNA sequencing and baseline gene expression analysis, osteoblasts from medium-sized colonies were directly lysed in TRIzol (Thermo Invitrogen™ 15596026). In all other experiments, osteoblasts were used within passage 1-2. Deep RNA sequencing and analysis: Total RNA was extracted, and 25 million paired-end reads (PE100) per sample were collected on the NovaSeq 6000 platform (Illumina, Inc.). The bioinformatics analysis was performed as described by Sheng et al. (2025). Briefly, raw reads were evaluated by FASTQC (Galaxy Version 0.74+galaxy0) followed by trimming to remove adapter sequences (Trimmomatic (Galaxy Version 0.39+galaxy0)). Cleaned reads were aligned to the reference genome using HISAT2 (Galaxy Version 2.2.1+galaxy1) with gh38 reference genome. FeatureCounts (Galaxy Version 2.0.3+galaxy2) quantified expression levels from aligned reads. Differential expression analysis was evaluated with the Limma package (Galaxy Version 3.50.1+galaxy0). Sex-specific genes, 93 Y-linked and 52 X-linked genes, were omitted from the DEG. Normalized counts (CPM) was obtained and Limma DEG analysis was employed to conduct GSEA on various gene set from MSigDB. Functional annotation of significant DEGs was achieved through Gene Ontology (GO) analysis using the ShinyGO platform (Version 0.77). The STRING database was used to identify protein-protein interaction (PPI) networks. PPI’s were visualized and analyzed in Cytoscape (3.10.1), where MCODE was used for clustering analysis and CytoHubba for topological evaluations (Figure 1A). Metabolic activity assay: The AlamarBlue assay (Thermo DAL1025) was employed to measure metabolic activity (a proxy for total cell number) of AIS and NSC osteoblasts cultured in HA-Col1 constructs under the experimental conditions (CTRL CM vs. TLR2A or TLR4A CM) at day 0, day 7 and day 14. Briefly, AlamarBlue reagent was added at a final concentration of 10%, and fluorescence intensity was measured after a 4-hour incubation at excitation/emission wavelengths of 560/590 nm. In vitro mineralization assay: For monolayer culture, 50,000 osteoblasts were seeded in 24-well plates. Cells reached confluence in approximately 2 days, after which osteogenic medium was added (α-MEM medium supplemented with 50 mg/mL ascorbic acid (Sigma-Aldrich A4544), 10 mM β-glycerophosphate (Sigma-Aldrich G9422), and 10 nM dexamethasone (Sigma-Aldrich D4902)). The media was changed every other 2 days. Alizarin Red staining was performed at week 5 following the manufacturer’s instructions (Sigma TMS-008). For each AIS patient or NSC individual, RNA was collected using TRIzol at day 0 and weeks 1, 2, 4, and 6 from parallel wells for time-course gene expression analysis. For 3D culture, osteoblasts (2 million cells/mL) were gently mixed with 0.5 mg/mL HA (Sigma 900193)–Col I gel (PureCol #5005) [24]. A 300 µL aliquot of the mixture was placed into a 48-well plate, creating a gel approximately 2-3 mm in height. Ten minutes after gelation, osteogenic medium was carefully added. Media was replaced every 2 days for 2 weeks. The constructs were then fixed in 4% paraformaldehyde, embedded in OCT compound, and cryosectioned at 8 µm thickness. Alizarin Red staining was performed on the cyro-sections [25]. Chondrocyte-osteoblast cross-talk experiment For short-term effects, primary chondrocytes were encapsulated in 1.25% alginate at a density of 2 × 10⁶ cells/mL. The mixture was expelled through a 20-gauge needle into a 102 mM CaCl₂ crosslinking solution (~0.013 g per bead) [26]. Beads were randomly distributed into three groups: untreated control, TLR2 pre-activated using Pam2CSK4 (InvivoGen, tlrl-pm2s-1), and TLR4 pre-activated using CRX-527 (InvivoGen, tlrl-crx527), both at 100 ng/mL in complete DMEM for 48 hours. After TLR-pre-activation, chondrocyte beads were washed and then transferred into Transwell inserts (12-well plate format) and cultured together with the osteoblasts in osteogenic medium for 24 hours. Osteoblast RNA was extracted 24 hours post-culture and stored at –80°C for subsequent qPCR analysis. For long-term effects, after 48 hours of TLR stimulation, chondrocyte beads were washed and cultured in fresh medium without agonists for an additional 4 days. Conditioned media (with or without prior TLR pre-activation) were collected and mixed at a 1:1 ratio with fresh osteogenic medium while maintaining the concentration of ascorbic acid, β-glycerophosphate, and dexamethasone the same as for each condition, and applied to osteoblasts in HA-Col1-coated 48 wells. After 2 weeks of culture, mineralization was assessed on cryosections with Alizarin Red staining. Gene expression analysis: Total RNA was extracted and reverse transcribed from 1 μg of input RNA per sample, following the manufacturer’s instructions. Real-time qPCR was performed using TaqMan™ Gene Expression Assays (Applied Biosystems) with 15 ng of cDNA per 20 μL reaction, including TaqMan™ Gene Expression Master Mix and gene-specific probe/primer sets (The list of TaqMan probes used is provided in Table 2). Reactions were on a QuantStudio™ system under cycling parameters recommended by the manufacturer. Gene expression was normalized to the geometric mean of two housekeeping genes, ß-actin and 18S rRNA, and relative expression was calculated using the 2 –ΔΔCt method. Statistical analysis: Due to the lack of prior studies on gene expression in facet joint osteoblasts to guide power analysis, p-values from RNA-seq data were used to estimate Cohen’s d, which infers the effect size, following the method described by Sheng et al[16] . A subset of genes of interest for this analysis, including IL1A, CXCL1, CXCL6, EREG, GSTM1, CD99, HOXD10, RUNX2, SP7, and COL1A1. The resulting Cohen’s d values ranged from 0.69 to 2.79, reflecting small to very large effect sizes. A medium effect size (conventional standard: 0.3) was selected as input for the a priori power analysis. (Free Statistics Calculators v4.0) It was determined that a minimum of 10 samples per group would be required to achieve 80% statistical power at a two-tailed alpha level of 0.05. The Shapiro-Wilk test was performed to assess the normality of all datasets. When comparing two groups, parametric data were analyzed using a two-tailed unpaired t-test, while nonparametric data were analyzed using a two-tailed unpaired Mann-Whitney test. For multiple comparisons involving more than two groups, one-way ANOVA with Dunnett's T3 multiple comparisons test was used for parametric data, and the Kruskal-Wallis test was applied for nonparametric data. All statistical analyses were calculated using GraphPad Prism 10. Significance defined by *P < .05, **P < .01, ***P < .001, ****P<0.0001. Results Differentially expressed genes in AIS facet joint osteoblasts To investigate the differentially expressed genes in facet joints, deep RNA sequencing was performed using primary osteoblasts from AIS patients and age-matched NSC individuals, as schematically depicted in Figure 1A. Deep RNA sequencing identified 21,123 genes; 722 were significantly downregulated, and 635 were significantly upregulated in AIS facet joint osteoblasts, while the remaining 19,766 genes showed no statistical difference between AIS and NSC facet joint osteoblasts (Figure 1B). Unsupervised hierarchical clustering of differentially expressed genes (DEGs) demonstrated a clear segregation between osteoblasts from AIS and NSC facet joints, reflecting distinct transcriptomic profiles (Figure 1C). The volcano plot highlighted significantly upregulated genes, including CXCL1, CXCL3, CXCL6, CXCL10, IL1A, GSTM1, EREG, and EGR1, which are associated with inflammatory responses, pain and detoxification. Genes related to a dysregulation of osteoblast differentiation and bone formation, such as CD99, HOXC10, and HOXC11, were significantly downregulated (Figure 1D). Functional annotation of differentially expressed genes Functional enrichment analysis was conducted to gain insights into the biological relevance of DEGs in AIS facet joint osteoblasts. For KEGG pathways, upregulated DEGs were enriched in processes involved in inflammation, including cytokine-cytokine receptor interaction, TNF signalling, IL-17 signalling, NF-kappa B signalling pathways, and chemokine signalling pathways, similar to what we previously observed in AIS facet joint chondrocytes [16] (Figure 2A). However, no significant KEGG pathway enrichment was observed for downregulated DEGs. A protein-protein interaction (PPI) network was constructed to explore interaction patterns among protein-coding DEGs in AIS osteoblasts. Unfiltered genes are displayed in (Supplementary Figure 1). MCODE was applied to identify densely connected modules within the PPI network and CytoHubba was then used to rank genes based on topological features (Maximum Neighbourhood Component) (Figure 2B). Subsequent GO enrichment analysis of the top two clusters highlighted their divergent biological roles: Cluster 1 was mainly associated with cell cycle regulation and cytoskeletal organization, while Cluster 2 was enriched in inflammatory signalling, cytokine activity, and immune response pathways (Figure 2C, D). Bone-specific gene set enrichment analysis and qPCR validation of bone marker genes GO analysis did not reveal significant enrichment of bone-related terms, likely due to its limitation of only analyzing DEGs that pass the p-value and fold change threshold. To gain a more comprehensive understanding of bone-associated biological processes, we performed GSEA, which accounts for all detected genes and their cumulative impact on biological processes. GSEA results show a mild negative enrichment in pathways such as bone growth (ES=-0.34 FDR=0.544), bone mineralization (ES=-0.29 FDR=0.437), bone morphogenesis (ES=-0.38 FDR=0.046), bone remodelling (ES=-0.39 FDR=0.077), bone trabecular formation (ES=-0.36 FDR=0.779), osteoblast differentiation (ES=-0.24 FDR=0.766), runx2 regulates bone development (ES=-0.37 FDR=0.428). (Figure 3A). A closer examination of genes enriched within these bone-related gene sets revealed that the osteoblast master transcription factor SP7 (FC=-1.33, p=0.256) and the osteoblast differentiation marker DLX3 (FC=-1.35, p=0.075), along with CD99 (FC=-4.55, p=0.002), HOXC11 (FC=-3.91, p<0.001) genes, HOXC10 (FC=-0.91, p<0.001) genes, were downregulated from RNAseq results. Additionally, other well-established bone markers, including ALP (FC=-1.91, p=0.051), osteocalcin (FC=-1.35, p=0.329), osteopontin (FC=-1.71, p<0.001), and BSP (FC=-1.73, p=0.009) also showed downregulation. In contrast, genes associated with mechanical stress FOSB (FC=2.70, p=0.224) and apoptosis c-FOS (FC=3.17, p=0.075) were upregulated (Figure 3B). Despite observing trends in RNA-seq data, many of these genes did not reach statistical significance, likely due to the limitations of the sample size. We therefore performed qPCR validation in a larger AIS cohort to validate these findings with greater statistical power. The qPCR results confirmed a downregulation of SP7 (FC = -5.48, p<0.001), ALP (FC = -4.72, p=0.006), and COL1A1 (FC=-2.58, p<0.001), RUNX2 (FC=-1.25, p=0.093), Osteocalcin (FC=-3.56, p=0.011), CD99 (FC=-3.33, p<0.001), HOXD10 (FC=-1.72, p<0.0001) in AIS osteoblast (Figure 3 C). For the same set of cDNA samples, we also measured TRLs, including (TLR1,2,4,6,7) pro-inflammatory genes, including IL1A, IL1B, IL6, CXCL6, and CXCL12. Except for IL1A (FC=2.4, p=0.010), the other genes did not show a statistically significant difference between AIS and NSC osteoblasts (Supplementary Figure 2). Comparative assessment of osteoblast mineralization capacity between AIS and NSC Bioinformatic analyses suggested altered mineralization potential in AIS osteoblasts. To validate this, mineralization capacity was assessed using a 3D HA-Col1 scaffold with Alizarin Red S staining as a readout at 2 weeks. AIS osteoblasts showed a significant 46.9% lower mineralization capacity compared to NSC (p=0.0061) (Figure 4 A, B). There was no significant difference in cell proliferation between the two groups that could explain the difference (Supplementary Figure 3A). We also performed 2D culture, which allows us to obtain high-quality RNA for investigating underlying molecular differences. The 2D cultures similarly showed reduced mineralization capacity in AIS (Supplementary Figure 3B). Gene expression changes of key osteogenic genes (RUNX2, ALP, SP7, COL1A1) were evaluated between baseline (day 0) and weeks 1 and 2 after the introduction of mineralization simulating culture medium. At week 1, RUNX2 and ALP showed a higher induction in NSCs, while SP7 and COL1A1 remained similar. At week 2, RUNX2 was still higher in NSC; but ALP levels were similar between AIS and NSC. However, AIS osteoblasts showed significantly lower SP7 expression and slightly higher COL1A1 expression (Figure 4 C). These temporal shifts imply both impaired early activation of osteogenic programs and prolonged extracellular matrix turnover in AIS osteoblasts. Osteoblast mineralization under the influence of TLR-activated chondrocytes Previous work from our group demonstrated that AIS facet joint chondrocytes exhibit elevated TLR2 expression and that activation leads to the production of a broad range of cytokines and chemokines known to regulate bone remodelling and promote osteoclast precursor proliferation and differentiation [16]. Here, we investigated whether the chondrocyte-derived secretory mediators also affect osteoblast mineralization. Although chondrocytes from OA joints release elevated levels of inflammatory mediators in vivo , their expression diminishes during 2D culture. To mimic the pathological status, we activated TLR2 or TLR4 signalling in primary chondrocytes using a previously validated approach [16,23]. We then assessed their effect on osteoblasts in both short- and long-term co-culture settings. For the short-term interaction, alginate-embedded chondrocytes (with or without TLR pre-activation) were co-cultured with osteoblasts using a transwell insert for 24 hours (Figure 5A). We observed that exposure of osteoblasts to inflammatory cues from chondrocytes resulted in significant upregulation of IL-6 expression following both TLR2A (FC=4.0, p= 0.043) and TLR4A (FC=4.5, p=0.025) pre-activation, while OCN expression was downregulated under the same conditions (TLR2A: FC=-2.17, p=0.004; TLR4A: FC =-1.67, p=0.07) (Figure 5B). For long-term exposure, conditioned media (CM) from pre-activated chondrocytes was collected, and osteoblasts seeded in an HA-collagen matrix were exposed to the conditioned media (CM) for 14 days (Figure 5 C). Osteoblasts exposed to the CM exhibited a marked reduction in mineralization capacity; a 61% decrease was detected following exposure to TLR2A-CM (p = 0.0035) and a 67% reduction following exposure to TLR4A-CM (p=0.0051) (Figure 5D and E). Importantly, this impairment occurred without significant alterations in cellular metabolic activity during the experiment (Supplementary Figure 3C). Discussion Although decreased osteoblast function has been previously associated with specific gene alterations in AIS [ 27 – 29 ] the broader transcriptomic profile of facet joint osteoblasts remains poorly defined. Using deep RNA sequencing, we reveal that AIS osteoblasts exhibit enrichment of inflammatory signalling pathways, similar to those observed in AIS chondrocytes. Simultaneously, genes associated with osteogenesis were broadly downregulated in AIS osteoblasts compared to non-scoliotic controls. These molecular alterations translated into a functional deficit in mineralization, which was exacerbated following exposure to conditioned media of TLR-pre-activated chondrocytes. Facet joint OA is notably present in AIS patients at a young age [ 14 , 15 ]. Our previous research also identified a robust correlation between cartilage degeneration and subchondral bone deterioration in AIS facet joints, a characteristic typically seen at an early stage in adults with knee and hip OA [ 15 ]. Existing transcriptomic analyses of subchondral bone from OA joints have predominantly focused on adult cohorts with late-stage hip or knee OA. After reviewing four recent OA subchondral bone transcriptomic analyses: two utilizing microarrays[ 30 , 31 ] and two employing RNA-seq [ 32 , 33 ], we found a notable lack of consistency in the top-ranked DEG lists. To our surprise, no single top-ranked DEG from the previous studies appeared in our own top-ranked DEG list. Genes such as IL11, OGN, POSTN, ASPN, MMP25, CNTNAP2, GPR158, MT1G, STMN2 and SLC14A1, appeared in at least two prior datasets. Our data revealed similar expression trends for these genes, except ASPN and STMN2, which exhibited the opposite direction. However, none reached statistical significance in our samples and were absent from the top-ranked DEGs. This observation suggests a distinct transcriptomic signature of AIS facet joint osteoblasts, highlighting how variations in joint anatomical site, patient age, and disease stage collectively shape OA pathogenesis. Our top-ranking up-DEG (upregulated DEGs) included several chemokines and cytokines, such as CXCL1, CXCL3, CXCL6, CXCL10, and IL1A, which contributed to the GO enrichment of inflammation-related pathways. This is aligned with previous observations from microarray analysis in Kuttapitiya et al., who highlighted chemokine and cytokine-mediated signalling enrichment in OA subchondral bone [ 30 ]. These inflammatory mediators are known to disrupt the osteoblast-osteoclast balance, promoting aberrant remodelling and enhancing pathological cartilage-bone crosstalk [ 34 , 35 ]. Another top-ranking up-DEG in our dataset, EGR1, is a transcription factor that interacts with RUNX2 to repress RUNX2 expression during osteogenesis [ 36 ]. EGR1 has also been shown to accelerate cartilage and intervertebral disc catabolism and is implicated in osteoporosis [ 37 , 38 ]. However, the impact of its upregulation in osteoblasts remains unexplored in the context of OA. It is worth noting that EGR1 is frequently induced under oxidative stress [ 38 ]. Interestingly, GSTM1, a detoxifying enzyme responsible for eliminating reactive oxygen species (ROS) [ 39 ] also emerged as a top-ranking DEG. The concurrent upregulation of EGR1 and GSTM1 suggests the presence of a ROS-enriched microenvironment, potentially driven by mechanical stress. Lastly, EREG emerged as the most prominently upregulated secretory protein-coding gene within our up-DEG dataset. Although its role in osteoblast differentiation remains controversial [ 40 – 42 ], EREG is well-established as a mediator of nociceptive signalling in the dorsal root ganglion, and it is released from intervertebral disc cells, potentially serving as a contributing factor to low back pain [ 43 , 44 ]. This raises the intriguing possibility that elevated EREG expression in the facet joint could contribute directly to pain sensitization observed in many AIS patients [ 45 ]. For top-ranking down-DEGs, we identified several homeobox (HOX) genes, including HOXD10 and HOXC11. HOX genes are master regulators of skeletal development [ 46 , 47 ]; for example, Wellik et al have shown in a mouse model that in the absence of Hox10, no lumbar vertebrae are formed [ 48 ]. Reduced expression of these developmental regulators might reflect a deviation in the normal osteogenic program of subchondral bone cells. We also found CD99 among the top-ranking down-DEGs. CD99 is a cell surface protein expressed on osteoblasts and mesenchymal cells, and it has been linked to osteoblast maturation, where activation of CD99 can enhance osteoblast differentiation and activity [ 49 , 50 ]. Lower CD99 levels in our samples might indicate impaired osteoblastic differentiation in the facet joint bone of AIS patients. Besides the top-ranking down-DEGs, our RNAseq also showed a widespread downregulation of osteogenic genes, including key transcription factors RUNX2, SP7, and prominent bone formation markers such as ALP, COL1, BSP and osteocalcin, all of which were subsequently validated via qPCR using an expanded sample size. In contrast to what has been observed in the subchondral bone of adult OA patients [ 31 , 51 ], a reduced expression of RUNX2 has been reported from total RNA extracted from AIS cancellous bone, as compared to non-scoliotic controls [ 52 ]. Moreover, Wang et al. reported a further reduced RUNX2 expression in AIS patients with low bone mineral density (BMD) compared to patients with a normal BMD, further emphasizing a potential link between RUNX2 and compromised bone integrity [ 53 ]. The reduction of other bone markers, including SP7, ALP, COL1, and osteocalcin, are all implicated in osteoporosis but has not previously been described in AIS facet joint osteoblasts. The downregulation of osteogenic genes ultimately contributes to reduced mineralization capacity, a finding consistent with previous work by He et al., who performed a 2D in vitro mineralization assay utilizing AIS facet joint osteoblasts [ 29 ]. The advantage in our study is that we used a 3D osteoblast culture system that more closely mimics the in vivo conditions and included osteoblasts from three times more AIS patients and non-scoliotic individuals than the previous study by He et al. Notably, we also observed that the mineralization impairment varied greatly among AIS patients, reflecting the heterogeneous expression patterns of osteoblast-related genes, as we observed by qPCR. This variability is supported by the fact that osteopenia, while recognized as a significant risk factor for AIS progression, is present in only 27% to 59% of patients [ 54 , 55 ]. Activation of TLR signalling pathways has previously been reported in osteoarthritic facet joint chondrocytes from AIS patients [ 23 ]. Activation drives the production of pro-inflammatory mediators capable of diffusing through subchondral pores and altering bone remodelling processes [ 16 ]. Our earlier work demonstrated that conditioned media derived from chondrocytes pre-activated with either TLR2 or TLR4 agonists significantly enhanced osteoclast precursor proliferation and increased mature osteoclast formation, effects mediated at least partially via macrophage colony-stimulating factor (M-CSF) [ 16 ]. However, the impact of these inflammatory mediators on osteoblast function remained unclear. Here, we show that transferring TLR2- or TLR4-pre-activated chondrocytes embedded in alginate beads in co-culture with osteoblasts induced an elevated production of IL-6 in osteoblasts. This was accompanied by a decreased osteocalcin expression, an essential positive regulator of bone formation. Elevated IL-6 expression is known to negatively impact osteoblast differentiation through the SHP2-mediated MEK2 and Akt2 signalling pathways and further promotes bone resorption associated with osteoporosis [ 20 ]. Gong et al. identified elevated IL-6 expression within a distinctive osteoblast subpopulation isolated from relatively young osteoarthritic and osteopenic patients undergoing hip replacement [ 56 ]. Building on these findings, we conducted long-term cultures in which chondrocyte-conditioned media was added to osteoblasts throughout the mineralization phase. This approach aimed to eliminate nutrient competition and avoid potential interactions between the mineralization medium and chondrocytes. We observed a marked inhibition of osteoblast mineralization following exposure to conditioned media from TLR-pre-activated chondrocytes, likely driven by chondrocyte-derived inflammatory mediators such as IL-6 and its further induction in osteoblasts. In the context of AIS, osteoblast dysfunction may serve as an initiating factor for the development of spine deformity in patients. Coupled with our previous research, the current findings suggest a mechanistic link between facet joint cartilage degeneration and subchondral bone deterioration [ 15 ][ 57 , 58 ]. We propose that inflammatory mediators produced by OA chondrocytes with an elevated TLR activation disrupt the bone formation and resorption balance, resulting in net bone loss at the site where cartilage is more degenerate. Deterioration of the subchondral bone may lead to an upward shift of the tidemark, accompanied by cartilage damage and weakened joint stability. This structural vulnerability of facet joints may result in a susceptibility to vertebral rotation, thereby contributing to the progression of scoliosis. Therefore, targeting the TLR-mediated inflammatory crosstalk via specific inhibitors may represent a potential therapeutic strategy to slow AIS progression. Declarations Ethics approval and consent to participate This study was reviewed and approved by the McGill University Institutional Review Board in Montreal, Canada (IRB # Tissue Biobank 2019-4896 and A03-M10-23A/23-02-009). The research was conducted in accordance with the International Council for Harmonization Good Clinical Practice guidelines (ICH-GCP) for clinical research involving human participants and adhered to the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans (TCPS 2). Written informed consent was obtained from all participants prior to study participation. Consent for publication The authors confirm that all participants involved in the study have provided written informed consent for publication of the results and any accompanying data/images in this manuscript. Competing interests The authors report no conflicts of interest. Funding sources This study was funded by the Shriner’s Hospital for Children (72002-CAN-23) and the Canadian Institutes of Health Research (PJT-183867). KS received a studentship from Fonds de recherche du Québec Santé (FRQS). Acknowledgements The authors kindly acknowledge the help from staff and surgeons at the Shriner’s Hospital for Children. Contributions LH and KS were responsible for the conception and design of the study. KS, DB acquired the experiment data. KS performed the analysis and interpretation of the data and drafted the initial manuscript. KS, DB and CC processed cell isolation from the facet joint sample. PB, NS, KU, and JO, as orthopedic surgeons, were responsible for performing AIS surgeries and harvesting tissues from organ donors. All authors participated in revising and submitting the final manuscript. Declaration of generative AI and AI-assisted technologies in the writing process The authors used Grammarly to check spelling and to revise the sentences. The content was then reviewed and edited as needed, and the authors assume full responsibility for the content of the publication. Abbreviations AIS (Adolescent Idiopathic Scoliosis) CM (Conditioned Media) CXCLs (Chemokine (C-X-C motif) Ligands) DEG (Differentially Expressed Gene) GSEA (Gene Set Enrichment Analysis) GO (Gene Ontology) FC (Fold Change) ILs (Interleukins) M-CSF (Macrophage Colony-Stimulating Factor) Maximum Neighborhood Component (MNC) NSC (Non-Scoliotic Control) OA (Osteoarthritis) OPG (Osteoprotegerin) OCN (osteocalcin/BGLAP) OCT (Optimal Cutting Temperature) POSTN (Periostin) OGN (Osteoglycin) PPI-network (Protein-Protein Interaction Network) RNAseq (RNA Sequencing) ROS (Reactive Oxygen Species) RUNX2 (RUNX family transcription factor 2) SHP2 (Src homology 2 domain-containing phosphatase 2) SLC14A1 (Solute carrier family 14 member 1) SP7 (Osterix) STMN2 (Stathmin 2) TLR2 (Toll-Like Receptor 2) TLR2A (Toll-Like Receptor 2 Agonist) TLR4 (Toll-Like Receptor 4) TLR4A (Toll-Like Receptor 4 Agonist) TNF-α (Tumor Necrosis Factor-Alpha) TRAP (Tartrate-Resistant Acid Phosphatase) References Cheng JC, Castelein RM, Chu WC, Danielsson AJ, Dobbs MB, Grivas TB, et al. 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Human Myeloma Cell Lines Induce Osteoblast Downregulation of CD99 Which Is Involved in Osteoblast Formation and Activity. J Immunol Res. 2015;2015:156787. Rice SJ, Aubourg G, Sorial AK, Almarza D, Tselepi M, Deehan DJ, et al. Identification of a novel, methylation-dependent, RUNX2 regulatory region associated with osteoarthritis risk. Hum Mol Genet. 2018;27:3464–74. Zhang H, Wang L, Liu S, Li J, Xiao L, Yang G. Adiponectin regulates bone mass in AIS osteopenia via RANKL/OPG and IL6 pathway. J Transl Med. 2019;17:64. Wang W, Sun C, Liu Z, Sun X, Zhu F, Zhu Z, et al. Transcription Factor Runx2 in the Low Bone Mineral Density of Girls with Adolescent Idiopathic Scoliosis. Orthop Surg. 2014;6:8–14. Cheng JCY, Tang SP, Guo X, Chan CW, Qin L. Osteopenia in Adolescent Idiopathic Scoliosis. Spine. 2001;26:C1–5. Hung VWY, Qin L, Cheung CSK, Lam TP, Ng BKW, Tse YK, et al. Osteopenia: a new prognostic factor of curve progression in adolescent idiopathic scoliosis. J Bone Jt Surg Am Volume. 2005;87:2709–16. Gong Y, Yang J, Li X, Zhou C, Chen Y, Wang Z, et al. A systematic dissection of human primary osteoblasts in vivo at single-cell resolution. Aging (Albany NY). 2021;13:20629–50. Schlager B, Krump F, Boettinger J, Niemeyer F, Ruf M, Kleiner S, et al. Characteristic morphological patterns within adolescent idiopathic scoliosis may be explained by mechanical loading. Eur Spine J. 2018;27:2184–91. Yahara Y, Seki S, Makino H, Futakawa H, Kamei K, Kawaguchi Y. Asymmetric Load Transmission Induces Facet Joint Subchondral Sclerosis and Hypertrophy in Patients with Idiopathic Adolescent Scoliosis: Evaluation Using Finite Element Model and Surgical Specimen. JBMR Plus. 2023;7:e10812. Tables Tables 1 and 2 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1QTHandAISdemographicsfinal.xlsx Table 1.Patient Information and Applications. This table summarizes the key details of the AIS patients and NSC organ donors. The table lists each sample applied in specific experiments, as indicated with a checkmark (✓). E1 RNA-seq; E2 Validation of RNA-seq DEGs by qPCR (Baseline, Untreated); E3 Mineralization comparasion (NSC vs AIS); E4 Expression of bone marker genes by qPCR (Post-Mineralization Stimulation); E5 Osteoblasts (Co-culture); E6 Osteoblasts (CM treatment) Table2TaqmanPrimerCatlog.xlsx Table 2. List of Primer catalog number used in This Study. SupplementaryFigures.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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1","display":"","copyAsset":false,"role":"figure","size":262009,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferentially expressed genes in AIS facet joint osteoblasts \u003c/strong\u003e(A) Schematic representation of the RNA sequencing workflow, from sample processing to bioinformatics analysis (AIS n=3, age=15±1.2; NSC n=3, age=18.3±1.7).\u003cstrong\u003e \u003c/strong\u003e(B) Venn diagram illustrating the distribution of DEGs in AIS compared to NSC: upregulated (pink), downregulated (blue), and commonly expressed genes (overlap).\u003cstrong\u003e \u003c/strong\u003e(C) Heatmap of DEGs showing distinct clustering of AIS and NSC osteoblasts. Red indicates higher expression, while blue represents lower expression levels. (D) Volcano plot depicting DEGs with P \u0026lt; 0.05 and |Log2FC| \u0026gt; 1. Upregulated genes are shown in red, downregulated genes in blue, and non-significant genes in grey.\u003cstrong\u003e \u003c/strong\u003eThe figure layout was designed using the BioRender.com platform.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7602845/v1/9e7dcb37a5ec21778047027c.jpg"},{"id":93341950,"identity":"4e739d20-b670-4dcc-9ab3-cc947c0b7600","added_by":"auto","created_at":"2025-10-12 14:41:08","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":294487,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFunctional annotation of differentially expressed genes \u003c/strong\u003e(A) KEGG pathway enrichment analysis of upregulated DEGs. (B) The top 2 clusters identified using the MCODE plugin in Cytoscape, colour-coded based on Maximum Neighbourhood Component (MNC) ranking by the CytoHubba plug-in. The top hub genes are highlighted from red to orange, blue dots represent their first-degree connected genes. (C, D) Show GO term enrichment (BP, CC, MF categories) for all genes in clusters 1 and 2.\u003c/p\u003e\n\u003cp\u003eFigure created using BioRender.com.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7602845/v1/352f003cb2fd98891ab742e8.jpg"},{"id":93341949,"identity":"d214b42b-7a48-44dc-8a29-2732379ebc04","added_by":"auto","created_at":"2025-10-12 14:41:08","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":175221,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBone-specific gene set enrichment analysis and qPCR validation of bone marker genes \u003c/strong\u003e(A) Multi-GSEA plot of bone-related pathways. (B) Fold change of selected osteoblast transcription factors and bone markers in AIS relative to NSC, based on RNA-seq data. (C) qPCR validation of bone-related genes in a larger cohort (NSC n=14, AIS n =32-36). Data was analyzed using a two-tailed Mann–Whitney U test. Significance defined by *P\u0026lt;0.05, **P\u0026lt;0.01, ***P\u0026lt;0.001\u003cstrong\u003e \u003c/strong\u003eFigure layout was designed using the BioRender.com platform.\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7602845/v1/d95485cfdbe85967f05996d9.jpg"},{"id":93341958,"identity":"044154bc-5918-43d5-a380-9eef438780d4","added_by":"auto","created_at":"2025-10-12 14:41:08","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":159923,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparative assessment of AIS and NSC osteoblast mineralization capacity \u003c/strong\u003e(A) Representative image of Alizarin Red staining of HA-Col constructs (B) Densitometric quantification of Alizarin Red staining intensity, normalized percentage relative to NSC. (C) Gene expression of key osteogenic markers measured by qPCR at weeks 1 and 2 following induction of mineralization, normalized to Day 0. Statistical analysis performed using Kruskal-Wallis ANOVA; significance indicated as by *P\u0026lt;0.05, **P\u0026lt;0.01, ***P\u0026lt;0.001\u003cstrong\u003e. \u003c/strong\u003eFigure layout created with BioRender.com\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7602845/v1/d3bf7f86d929598cccbd2f27.jpg"},{"id":93343162,"identity":"59d98766-4bf2-4744-8656-1117bfc39dbe","added_by":"auto","created_at":"2025-10-12 14:49:08","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":260954,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOsteoblast mineralization under the influence of TLR-pre-activated chondrocytes \u003c/strong\u003e(A) Schematic representation of osteoblast and chondrocyte co-culture experiment (B) Gene expression of osteoblast markers and pro-inflammatory markers was measured by qPCR after 24 hours of exposure, normalized to fold change relative to time 0. Statistical analysis was performed using Kruskal-Wallis ANOVA; significance is indicated as *P\u0026lt;0.05, **P\u0026lt;0.01, ***P\u0026lt;0.001. (C) Timeline of long-term monitoring of TLR-activated chondrocyte effects on osteoblast mineralization. Chondrocyte-conditioned media (CM) was collected after TLR pre-activation. Osteoblasts seeded in an HA-COL1 scaffold were exposed to the CM for 14 days. (D) Representative image of Alizarin Red staining of a HA-Col construct section (E). Densitometric quantification of Alizarin Red staining intensity, normalized percentage relative to CTRL CM.\u003c/p\u003e","description":"","filename":"Picture5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7602845/v1/f59397150a01e2a73b1abd7a.jpg"},{"id":95818665,"identity":"73dbe23f-c5be-4b73-bf0e-1d8ea1075d44","added_by":"auto","created_at":"2025-11-13 10:27:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2143838,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7602845/v1/8d8a1075-6112-40d3-8b2b-216b144b9d24.pdf"},{"id":93341966,"identity":"607227d3-6db8-49a0-aa64-1dc23174c5a1","added_by":"auto","created_at":"2025-10-12 14:41:08","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":14235,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003ePatient Information and Applications. This table summarizes the key details of the AIS patients and NSC organ donors. The table lists each sample applied in specific experiments, as indicated with a checkmark (✓). E1 RNA-seq; E2 Validation of RNA-seq DEGs by qPCR (Baseline, Untreated); E3 Mineralization comparasion (NSC vs AIS); E4 Expression of bone marker genes by qPCR (Post-Mineralization Stimulation); E5 Osteoblasts (Co-culture); E6 Osteoblasts (CM treatment)\u003c/p\u003e","description":"","filename":"Table1QTHandAISdemographicsfinal.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7602845/v1/148fc7336f6ab1dc0718dee8.xlsx"},{"id":93343923,"identity":"9ec9a5e8-bb77-429a-969e-3a2933626abd","added_by":"auto","created_at":"2025-10-12 14:57:08","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":8788,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e List of Primer catalog number used in This Study.\u003c/p\u003e","description":"","filename":"Table2TaqmanPrimerCatlog.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7602845/v1/032be417ee46f5c461a8f77b.xlsx"},{"id":93343158,"identity":"e38bdbad-8cdb-4820-b234-c66c2f1492ba","added_by":"auto","created_at":"2025-10-12 14:49:08","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":811443,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigures.docx","url":"https://assets-eu.researchsquare.com/files/rs-7602845/v1/55767844749c914acab6a1e6.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Reduced mineralization potential of osteoblasts in adolescent idiopathic scoliosis: intrinsic dysfunction and crosstalk with TLR-activated chondrocytes","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAdolescent idiopathic scoliosis (AIS) is a complex spinal deformity characterized by lateral spinal curvature accompanied by vertebral rotation and, in many cases, a disruption of the normal sagittal alignment, thus manifesting as a true three-dimensional skeletal abnormality [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Despite its unknown etiology, AIS commonly appears during rapid adolescent growth spurts in previously healthy individuals, suggesting an intrinsic disturbance in skeletal development. Indeed, recent genetic studies have identified abnormalities in pathways critical to skeletal formation in AIS patients, highlighting variants in genes related to bone formation [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], extracellular matrix production [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], and melatonin signalling [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Clinically, AIS is also frequently associated with systemic osteopenia [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], reduced bone mineral density [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], and elevated bone turnover [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], risk factors that may collectively contribute to curve progression.\u003c/p\u003e\u003cp\u003eThe facet (zygapophyseal) joints, which articulate the posterior elements of vertebrae, play a critical role in guiding spinal motion and limiting excessive axial rotation [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In severe AIS, facetectomy is often performed at the curve apex and nearby segments to relieve tension and aid pedicle screw placement during spinal fusion. Our previous studies identified facet joint osteoarthritis (OA) in AIS patients [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], especially within segments exhibiting significant intervertebral axial rotation above and below the apex [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Moreover, the severity of facet cartilage degeneration inversely correlates with the quality of the underlying subchondral bone [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and appears asymmetric between the two facets at the same spinal level. The reciprocal interaction between cartilage and bone is thought to contribute to the acceleration of joint deterioration, compromising the structural integrity and biomechanical function of facet joints [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Consequently, as facet joints become less effective at limiting axial rotation, the spine\u0026rsquo;s resistance to progressive deformity in AIS is compromised.\u003c/p\u003e\u003cp\u003eStudies of adult OA and rheumatoid arthritis (RA) have demonstrated that the inflammatory joint microenvironment disrupts normal bone remodelling, largely by altering the balanced activities of osteoclasts (bone-resorbing cells) and osteoblasts (bone-forming cells) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. This disruption is believed to occur, at least in part, through inflammatory mediators secreted from osteoarthritic chondrocytes that penetrate microscopic pores within the subchondral bone plate [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Our recent research has implicated a Toll-Like Receptor (TLR)-mediated mechanism, whereby TLR activation in chondrocytes induces the production of macrophage colony-stimulating factor (M-CSF), a crucial cytokine driving osteoclast proliferation and differentiation [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. TLR activation in AIS chondrocytes triggers the release of a broad spectrum of cytokines and chemokines [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], many of which have roles in the inhibition of osteoblast differentiation, as previously demonstrated in adult OA studies [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Whether osteoblast modulation is similarly activated within the facet joints of AIS patients has yet to be explored. In the current study, we hypothesize that inflammatory mediators released from degenerative facet joint cartilage from AIS patients adversely affect osteoblast function, impairing osteoblast mineralization capacity.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003eCollection of clinical specimens\u003c/strong\u003e: Facet joints were collected from 53 consenting AIS patients undergoing spinal fusion surgery at the Shriners Hospital for Children. \u0026nbsp;Non-scoliotic control (NSC) facet joints were retrieved from 19 organ donors through a collaboration with Transplant Quebec Organ Donation Program. The average age was 27.6±8.5 for the non-scoliotic individuals and 15.3±1.6 for the AIS patients. Demographics, including age, sex, Cobb angle, and Lenke classification, along with detailed information on the experiments conducted with the specific facet joint samples, can be found in Table 1. The spinal level from which AIS facet joints are resected depends on the curve type and surgical need and includes both lumbar and thoracic levels. Facet joints from organ donors were also from both thoracic and lumbar levels to ensure a similar distribution and prevent variability due to the spinal level. AIS is more frequent in females, and 84.6% of the patients included in this study were female. The study was approved by the McGill University institutional review board in Montreal, Canada (IRB # Tissue Biobank 2019-4896 and A03-M10-23A/23-02-009). Written informed consent was received before participation in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrimary chondrocyte and osteoblast isolation:\u003c/strong\u003e Facet joint chondrocytes were isolated as previously described by Bisson et al. [23] and Sheng et al. [16]. Briefly, cartilage was removed from subchondral bone, cut into small pieces, and digested with Collagenase Type II (Thermo Gibco™ 17101015). All chondrocyte cell culture experiments were conducted within passages 0-2. The facet joint bone, free of cartilage and ligaments, was processed for osteoblast isolation. Subchondral bone was broken into small pieces using a rongeur, and cortical bone was collected. After a thorough PBS wash to remove marrow cells, bone chips were digested with Collagenase Type II for 16 hours to eliminate residual soft tissue. The digested chips were then placed in T75 flasks with complete Dulbecco's DMEM (Sigma Aldrich D5648; 4.5 g/L glucose, 10% FBS, 25 μg/mL gentamycin, and 2 mmol/L Glutamax). The media was refreshed every two days. Osteoblasts typically emerged and formed colonies within 4 weeks. These cells were then trypsinized, and 1 million cells were seeded/ T75 flask. Full confluence was reached within 2 weeks. For RNA sequencing and baseline gene expression analysis, osteoblasts from medium-sized colonies were directly lysed in TRIzol (Thermo Invitrogen™ 15596026). In all other experiments, osteoblasts were used within passage 1-2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeep RNA sequencing and analysis:\u003c/strong\u003e Total RNA was extracted, and 25 million paired-end reads (PE100) per sample were collected on the NovaSeq 6000 platform (Illumina, Inc.). The bioinformatics analysis was performed as described by Sheng et al. (2025). Briefly, raw reads were evaluated by FASTQC (Galaxy Version 0.74+galaxy0) followed by trimming to remove adapter sequences (Trimmomatic (Galaxy Version 0.39+galaxy0)). Cleaned reads were aligned to the reference genome using HISAT2 (Galaxy Version 2.2.1+galaxy1) with gh38 reference genome. FeatureCounts (Galaxy Version 2.0.3+galaxy2) quantified expression levels from aligned reads. Differential expression analysis was evaluated with the Limma package (Galaxy Version 3.50.1+galaxy0). Sex-specific genes, 93 Y-linked and 52 X-linked genes, were omitted from the DEG. Normalized counts (CPM) was obtained and Limma DEG analysis was employed to conduct GSEA on various gene set from MSigDB. Functional annotation of significant DEGs was achieved through Gene Ontology (GO) analysis using the ShinyGO platform (Version 0.77). The STRING database was used to identify protein-protein interaction (PPI) networks. PPI’s were visualized and analyzed in Cytoscape (3.10.1), where MCODE was used for clustering analysis and CytoHubba for topological evaluations (Figure 1A).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMetabolic activity assay:\u0026nbsp;\u003c/strong\u003eThe AlamarBlue assay (Thermo DAL1025) was employed to measure metabolic activity (a proxy for total cell number) of AIS and NSC osteoblasts cultured in HA-Col1 constructs under the experimental conditions (CTRL CM vs. TLR2A or TLR4A CM) at day 0, day 7 and day 14. Briefly, AlamarBlue reagent was added at a final concentration of 10%, and fluorescence intensity was measured after a 4-hour incubation at excitation/emission wavelengths of 560/590 nm.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIn vitro mineralization assay:\u0026nbsp;\u003c/strong\u003eFor monolayer culture, 50,000 osteoblasts were seeded in 24-well plates. Cells reached confluence in approximately 2 days, after which osteogenic medium was added (α-MEM medium supplemented with 50 mg/mL ascorbic acid (Sigma-Aldrich A4544), 10 mM β-glycerophosphate (Sigma-Aldrich G9422), and 10 nM dexamethasone (Sigma-Aldrich D4902)). The media was changed every other 2 days. Alizarin Red staining was performed at week 5 following the manufacturer’s instructions (Sigma TMS-008). For each AIS patient or NSC individual, RNA was collected using TRIzol at day 0 and weeks 1, 2, 4, and 6 from parallel wells for time-course gene expression analysis. For 3D culture, osteoblasts (2 million cells/mL) were gently mixed with 0.5 mg/mL HA (Sigma 900193)–Col I gel (PureCol #5005) [24]. A 300 µL aliquot of the mixture was placed into a 48-well plate, creating a gel approximately 2-3 mm in height. Ten minutes after gelation, osteogenic medium was carefully added. Media was replaced every 2 days for 2 weeks. The constructs were then fixed in 4% paraformaldehyde, embedded in OCT compound, and cryosectioned at 8 µm thickness. Alizarin Red staining was performed on the cyro-sections [25].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChondrocyte-osteoblast cross-talk experiment\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor short-term effects, primary chondrocytes were encapsulated in 1.25% alginate at a density of 2 × 10⁶ cells/mL. The mixture was expelled through a 20-gauge needle into a 102 mM CaCl₂\u0026nbsp;crosslinking solution (~0.013 g per bead) [26]. Beads were randomly distributed into three groups: untreated control, TLR2 pre-activated using Pam2CSK4 (InvivoGen, tlrl-pm2s-1), and TLR4 pre-activated using CRX-527 (InvivoGen, tlrl-crx527), both at 100 ng/mL in complete DMEM for 48 hours. After TLR-pre-activation, chondrocyte beads were washed and then transferred into Transwell inserts (12-well plate format) and cultured together with the osteoblasts in osteogenic medium for 24 hours. Osteoblast RNA was extracted 24 hours post-culture and stored at –80°C for subsequent qPCR analysis. For long-term effects, after 48 hours of TLR stimulation, chondrocyte beads were washed and cultured in fresh medium without agonists for an additional 4 days. Conditioned media (with or without prior TLR pre-activation) were collected and mixed at a 1:1 ratio with fresh osteogenic medium while maintaining the concentration of ascorbic acid, β-glycerophosphate, and dexamethasone the same as for each condition, and applied to osteoblasts in HA-Col1-coated 48 wells. After 2 weeks of culture, mineralization was assessed on cryosections with Alizarin Red staining.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGene expression analysis:\u003c/strong\u003e Total RNA was extracted and reverse transcribed from 1 μg of input RNA per sample, following the manufacturer’s instructions. Real-time qPCR was performed using TaqMan™ Gene Expression Assays (Applied Biosystems) with 15 ng of cDNA per 20 μL reaction, including TaqMan™ Gene Expression Master Mix and gene-specific probe/primer sets (The list of TaqMan probes used is provided in Table 2). Reactions were on a QuantStudio™ system under cycling parameters recommended by the manufacturer. Gene expression was normalized to the geometric mean of two housekeeping genes, ß-actin and 18S rRNA, and relative expression was calculated using the 2\u003csup\u003e–ΔΔCt\u003c/sup\u003e method.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis:\u003c/strong\u003e Due to the lack of prior studies on gene expression in facet joint osteoblasts to guide power analysis, p-values from RNA-seq data were used to estimate Cohen’s d, which infers the effect size, following the method described by Sheng et al[16] . A subset of genes of interest for this analysis, including IL1A, CXCL1, CXCL6, EREG, GSTM1, CD99, HOXD10, RUNX2, SP7, and COL1A1. The resulting Cohen’s d values ranged from 0.69 to 2.79, reflecting small to very large effect sizes. A medium effect size (conventional standard: 0.3) was selected as input for the a priori power analysis. (Free Statistics Calculators v4.0) It was determined that a minimum of 10 samples per group would be required to achieve 80% statistical power at a two-tailed alpha level of 0.05.\u003c/p\u003e\n\u003cp\u003eThe Shapiro-Wilk test was performed to assess the normality of all datasets. When comparing two groups, parametric data were analyzed using a two-tailed unpaired t-test, while nonparametric data were analyzed using a two-tailed unpaired Mann-Whitney test. For multiple comparisons involving more than two groups, one-way ANOVA with Dunnett's T3 multiple comparisons test was used for parametric data, and the Kruskal-Wallis test was applied for nonparametric data. All statistical analyses were calculated using GraphPad Prism 10. Significance defined by *P \u0026lt; .05, **P \u0026lt; .01, ***P \u0026lt; .001, ****P\u0026lt;0.0001.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eDifferentially expressed genes in AIS facet joint osteoblasts\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate the differentially expressed genes in facet joints, deep RNA sequencing was performed using primary osteoblasts from AIS patients and age-matched NSC individuals, as schematically depicted in Figure 1A. Deep RNA sequencing identified 21,123 genes; 722 were significantly downregulated, and 635 were significantly upregulated in AIS facet joint osteoblasts, while the remaining 19,766 genes showed no statistical difference between AIS and NSC facet joint osteoblasts (Figure 1B). Unsupervised hierarchical clustering of differentially expressed genes (DEGs) demonstrated a clear segregation between osteoblasts from AIS and NSC facet joints, reflecting distinct transcriptomic profiles (Figure 1C). The volcano plot highlighted significantly upregulated genes, including CXCL1, CXCL3, CXCL6, CXCL10, IL1A, GSTM1, EREG, and EGR1, which are associated with inflammatory responses, pain and detoxification. Genes related to a dysregulation of osteoblast differentiation and bone formation, such as CD99, HOXC10, and HOXC11, were significantly downregulated (Figure 1D).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunctional annotation of differentially expressed genes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunctional enrichment analysis was conducted to gain insights into the biological relevance of DEGs in AIS facet joint osteoblasts. For KEGG pathways, upregulated DEGs were enriched in processes involved in inflammation, including cytokine-cytokine receptor interaction, TNF signalling, IL-17 signalling, NF-kappa B signalling pathways, and chemokine signalling pathways, similar to what we previously observed in AIS facet joint chondrocytes [16] (Figure 2A). \u0026nbsp;However, no significant KEGG pathway enrichment was observed for downregulated DEGs. A protein-protein interaction (PPI) network was constructed to explore interaction patterns among protein-coding DEGs in AIS osteoblasts. \u0026nbsp;Unfiltered genes are displayed in (Supplementary Figure 1). \u0026nbsp;MCODE was applied to identify densely connected modules within the PPI network and CytoHubba was then used to rank genes based on topological features (Maximum Neighbourhood Component) (Figure 2B). Subsequent GO enrichment analysis of the top two clusters highlighted their divergent biological roles: Cluster 1 was mainly associated with cell cycle regulation and cytoskeletal organization, while Cluster 2 was enriched in inflammatory signalling, cytokine activity, and immune response pathways (Figure 2C, D).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBone-specific gene set enrichment analysis and qPCR validation of bone marker genes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGO analysis did not reveal significant enrichment of bone-related terms, likely due to its limitation of only analyzing DEGs that pass the p-value and fold change threshold. To gain a more comprehensive understanding of bone-associated biological processes, we performed GSEA, which accounts for all detected genes and their cumulative impact on biological processes. GSEA results show a mild negative enrichment in pathways such as bone growth (ES=-0.34 FDR=0.544), bone mineralization (ES=-0.29 FDR=0.437), bone morphogenesis (ES=-0.38 FDR=0.046), bone remodelling (ES=-0.39 FDR=0.077), bone trabecular formation (ES=-0.36 FDR=0.779), osteoblast differentiation (ES=-0.24 FDR=0.766), runx2 regulates bone development (ES=-0.37 FDR=0.428). (Figure 3A).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA closer examination of genes enriched within these bone-related gene sets revealed that the osteoblast master transcription factor SP7 (FC=-1.33, p=0.256) and the osteoblast differentiation marker DLX3 (FC=-1.35, p=0.075), along with CD99 (FC=-4.55, p=0.002), HOXC11 (FC=-3.91, p\u0026lt;0.001) genes, HOXC10 (FC=-0.91, p\u0026lt;0.001) genes, were downregulated from RNAseq results. Additionally, other well-established bone markers, including ALP (FC=-1.91, p=0.051), osteocalcin (FC=-1.35, p=0.329), osteopontin (FC=-1.71, p\u0026lt;0.001), and BSP (FC=-1.73, p=0.009) also showed downregulation. In contrast, genes associated with mechanical stress FOSB (FC=2.70, p=0.224) and apoptosis c-FOS (FC=3.17, p=0.075) were upregulated (Figure 3B). Despite observing trends in RNA-seq data, many of these genes did not reach statistical significance, likely due to the limitations of the sample size. We therefore performed qPCR validation in a larger AIS cohort to validate these findings with greater statistical power. The qPCR results confirmed a downregulation of SP7 (FC = -5.48, p\u0026lt;0.001), ALP (FC = -4.72, p=0.006), and COL1A1 (FC=-2.58, p\u0026lt;0.001), RUNX2 (FC=-1.25, p=0.093), Osteocalcin (FC=-3.56, p=0.011), CD99 (FC=-3.33, p\u0026lt;0.001), HOXD10 (FC=-1.72, p\u0026lt;0.0001) in AIS osteoblast (Figure 3 C). \u0026nbsp;For the same set of cDNA samples, we also measured TRLs, including (TLR1,2,4,6,7) pro-inflammatory genes, including IL1A, IL1B, IL6, CXCL6, and CXCL12. Except for IL1A (FC=2.4, p=0.010), the other genes did not show a statistically significant difference between AIS and NSC osteoblasts (Supplementary Figure 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparative assessment of osteoblast mineralization capacity between AIS and NSC\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBioinformatic analyses suggested altered mineralization potential in AIS osteoblasts. To validate this, mineralization capacity was assessed using a 3D HA-Col1 scaffold with Alizarin Red S staining as a readout at 2 weeks. AIS osteoblasts showed a significant 46.9% lower mineralization capacity compared to NSC (p=0.0061) (Figure 4 A, B). There was no significant difference in cell proliferation between the two groups that could explain the difference (Supplementary Figure 3A). We also performed 2D culture, which allows us to obtain high-quality RNA for investigating underlying molecular differences. The 2D cultures similarly showed reduced mineralization capacity in AIS (Supplementary Figure 3B). Gene expression changes of key osteogenic genes (RUNX2, ALP, SP7, COL1A1) were evaluated between baseline (day 0) and weeks 1 and 2 after the introduction of mineralization simulating culture medium. At week 1, RUNX2 and ALP showed a higher induction in NSCs, while SP7 and COL1A1 remained similar. At week 2, RUNX2 was still higher in NSC; but ALP levels were similar between AIS and NSC. However, AIS osteoblasts showed significantly lower SP7 expression and slightly higher COL1A1 expression (Figure 4 C). These temporal shifts imply both impaired early activation of osteogenic programs and prolonged extracellular matrix turnover in AIS osteoblasts.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOsteoblast mineralization under the influence of TLR-activated chondrocytes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrevious work from our group demonstrated that AIS facet joint chondrocytes exhibit elevated TLR2 expression and that activation leads to the production of a broad range of cytokines and chemokines known to regulate bone remodelling and promote osteoclast precursor proliferation and differentiation [16]. Here, we investigated whether the chondrocyte-derived secretory mediators also affect osteoblast mineralization.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAlthough chondrocytes from OA joints release elevated levels of inflammatory mediators \u003cem\u003ein vivo\u003c/em\u003e, their expression diminishes during 2D culture. To mimic the pathological status, we activated TLR2 or TLR4 signalling in primary chondrocytes using a previously validated approach [16,23]. We then assessed their effect on osteoblasts in both short- and long-term co-culture settings.\u003c/p\u003e\n\u003cp\u003eFor the short-term interaction, alginate-embedded chondrocytes (with or without TLR pre-activation) were co-cultured with osteoblasts using a transwell insert for 24 hours (Figure 5A). We observed that exposure of osteoblasts to inflammatory cues from chondrocytes resulted in significant upregulation of IL-6 expression following both TLR2A (FC=4.0, p= 0.043) and TLR4A (FC=4.5, p=0.025) pre-activation, while OCN expression was downregulated under the same conditions (TLR2A: FC=-2.17, p=0.004; TLR4A: FC =-1.67, p=0.07) (Figure 5B).\u003c/p\u003e\n\u003cp\u003eFor long-term exposure, conditioned media (CM) from pre-activated chondrocytes was collected, and osteoblasts seeded in an HA-collagen matrix were exposed to the conditioned media (CM) for 14 days (Figure 5 C). Osteoblasts exposed to the CM exhibited a marked reduction in mineralization capacity; a 61% decrease was detected following exposure to TLR2A-CM (p = 0.0035) and a 67% reduction following exposure to TLR4A-CM (p=0.0051) (Figure 5D and E). Importantly, this impairment occurred without significant alterations in cellular metabolic activity during the experiment (Supplementary Figure 3C).\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAlthough decreased osteoblast function has been previously associated with specific gene alterations in AIS [\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] the broader transcriptomic profile of facet joint osteoblasts remains poorly defined. Using deep RNA sequencing, we reveal that AIS osteoblasts exhibit enrichment of inflammatory signalling pathways, similar to those observed in AIS chondrocytes. Simultaneously, genes associated with osteogenesis were broadly downregulated in AIS osteoblasts compared to non-scoliotic controls. These molecular alterations translated into a functional deficit in mineralization, which was exacerbated following exposure to conditioned media of TLR-pre-activated chondrocytes.\u003c/p\u003e\u003cp\u003eFacet joint OA is notably present in AIS patients at a young age [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Our previous research also identified a robust correlation between cartilage degeneration and subchondral bone deterioration in AIS facet joints, a characteristic typically seen at an early stage in adults with knee and hip OA [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Existing transcriptomic analyses of subchondral bone from OA joints have predominantly focused on adult cohorts with late-stage hip or knee OA. After reviewing four recent OA subchondral bone transcriptomic analyses: two utilizing microarrays[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] and two employing RNA-seq [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], we found a notable lack of consistency in the top-ranked DEG lists. To our surprise, no single top-ranked DEG from the previous studies appeared in our own top-ranked DEG list. Genes such as IL11, OGN, POSTN, ASPN, MMP25, CNTNAP2, GPR158, MT1G, STMN2 and SLC14A1, appeared in at least two prior datasets. Our data revealed similar expression trends for these genes, except ASPN and STMN2, which exhibited the opposite direction. However, none reached statistical significance in our samples and were absent from the top-ranked DEGs. This observation suggests a distinct transcriptomic signature of AIS facet joint osteoblasts, highlighting how variations in joint anatomical site, patient age, and disease stage collectively shape OA pathogenesis.\u003c/p\u003e\u003cp\u003eOur top-ranking up-DEG (upregulated DEGs) included several chemokines and cytokines, such as CXCL1, CXCL3, CXCL6, CXCL10, and IL1A, which contributed to the GO enrichment of inflammation-related pathways. This is aligned with previous observations from microarray analysis in Kuttapitiya et al., who highlighted chemokine and cytokine-mediated signalling enrichment in OA subchondral bone [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. These inflammatory mediators are known to disrupt the osteoblast-osteoclast balance, promoting aberrant remodelling and enhancing pathological cartilage-bone crosstalk [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Another top-ranking up-DEG in our dataset, EGR1, is a transcription factor that interacts with RUNX2 to repress RUNX2 expression during osteogenesis [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. EGR1 has also been shown to accelerate cartilage and intervertebral disc catabolism and is implicated in osteoporosis [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. However, the impact of its upregulation in osteoblasts remains unexplored in the context of OA. It is worth noting that EGR1 is frequently induced under oxidative stress [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Interestingly, GSTM1, a detoxifying enzyme responsible for eliminating reactive oxygen species (ROS) [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] also emerged as a top-ranking DEG. The concurrent upregulation of EGR1 and GSTM1 suggests the presence of a ROS-enriched microenvironment, potentially driven by mechanical stress. Lastly, EREG emerged as the most prominently upregulated secretory protein-coding gene within our up-DEG dataset. Although its role in osteoblast differentiation remains controversial [\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], EREG is well-established as a mediator of nociceptive signalling in the dorsal root ganglion, and it is released from intervertebral disc cells, potentially serving as a contributing factor to low back pain [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. This raises the intriguing possibility that elevated EREG expression in the facet joint could contribute directly to pain sensitization observed in many AIS patients [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFor top-ranking down-DEGs, we identified several homeobox (HOX) genes, including HOXD10 and HOXC11. HOX genes are master regulators of skeletal development [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]; for example, Wellik et al have shown in a mouse model that in the absence of Hox10, no lumbar vertebrae are formed [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Reduced expression of these developmental regulators might reflect a deviation in the normal osteogenic program of subchondral bone cells. We also found CD99 among the top-ranking down-DEGs. CD99 is a cell surface protein expressed on osteoblasts and mesenchymal cells, and it has been linked to osteoblast maturation, where activation of CD99 can enhance osteoblast differentiation and activity [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Lower CD99 levels in our samples might indicate impaired osteoblastic differentiation in the facet joint bone of AIS patients.\u003c/p\u003e\u003cp\u003eBesides the top-ranking down-DEGs, our RNAseq also showed a widespread downregulation of osteogenic genes, including key transcription factors RUNX2, SP7, and prominent bone formation markers such as ALP, COL1, BSP and osteocalcin, all of which were subsequently validated via qPCR using an expanded sample size. In contrast to what has been observed in the subchondral bone of adult OA patients [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], a reduced expression of RUNX2 has been reported from total RNA extracted from AIS cancellous bone, as compared to non-scoliotic controls [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Moreover, Wang et al. reported a further reduced RUNX2 expression in AIS patients with low bone mineral density (BMD) compared to patients with a normal BMD, further emphasizing a potential link between RUNX2 and compromised bone integrity [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. The reduction of other bone markers, including SP7, ALP, COL1, and osteocalcin, are all implicated in osteoporosis but has not previously been described in AIS facet joint osteoblasts. The downregulation of osteogenic genes ultimately contributes to reduced mineralization capacity, a finding consistent with previous work by He et al., who performed a 2D in vitro mineralization assay utilizing AIS facet joint osteoblasts [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The advantage in our study is that we used a 3D osteoblast culture system that more closely mimics the \u003cem\u003ein vivo\u003c/em\u003e conditions and included osteoblasts from three times more AIS patients and non-scoliotic individuals than the previous study by He et al. Notably, we also observed that the mineralization impairment varied greatly among AIS patients, reflecting the heterogeneous expression patterns of osteoblast-related genes, as we observed by qPCR. This variability is supported by the fact that osteopenia, while recognized as a significant risk factor for AIS progression, is present in only 27% to 59% of patients [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eActivation of TLR signalling pathways has previously been reported in osteoarthritic facet joint chondrocytes from AIS patients [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Activation drives the production of pro-inflammatory mediators capable of diffusing through subchondral pores and altering bone remodelling processes [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Our earlier work demonstrated that conditioned media derived from chondrocytes pre-activated with either TLR2 or TLR4 agonists significantly enhanced osteoclast precursor proliferation and increased mature osteoclast formation, effects mediated at least partially via macrophage colony-stimulating factor (M-CSF) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, the impact of these inflammatory mediators on osteoblast function remained unclear. Here, we show that transferring TLR2- or TLR4-pre-activated chondrocytes embedded in alginate beads in co-culture with osteoblasts induced an elevated production of IL-6 in osteoblasts. This was accompanied by a decreased osteocalcin expression, an essential positive regulator of bone formation. Elevated IL-6 expression is known to negatively impact osteoblast differentiation through the SHP2-mediated MEK2 and Akt2 signalling pathways and further promotes bone resorption associated with osteoporosis [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Gong et al. identified elevated IL-6 expression within a distinctive osteoblast subpopulation isolated from relatively young osteoarthritic and osteopenic patients undergoing hip replacement [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Building on these findings, we conducted long-term cultures in which chondrocyte-conditioned media was added to osteoblasts throughout the mineralization phase. This approach aimed to eliminate nutrient competition and avoid potential interactions between the mineralization medium and chondrocytes. We observed a marked inhibition of osteoblast mineralization following exposure to conditioned media from TLR-pre-activated chondrocytes, likely driven by chondrocyte-derived inflammatory mediators such as IL-6 and its further induction in osteoblasts.\u003c/p\u003e\u003cp\u003eIn the context of AIS, osteoblast dysfunction may serve as an initiating factor for the development of spine deformity in patients. Coupled with our previous research, the current findings suggest a mechanistic link between facet joint cartilage degeneration and subchondral bone deterioration [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e][\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. We propose that inflammatory mediators produced by OA chondrocytes with an elevated TLR activation disrupt the bone formation and resorption balance, resulting in net bone loss at the site where cartilage is more degenerate. Deterioration of the subchondral bone may lead to an upward shift of the tidemark, accompanied by cartilage damage and weakened joint stability. This structural vulnerability of facet joints may result in a susceptibility to vertebral rotation, thereby contributing to the progression of scoliosis. Therefore, targeting the TLR-mediated inflammatory crosstalk via specific inhibitors may represent a potential therapeutic strategy to slow AIS progression.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003eThis study was reviewed and approved by the McGill University Institutional Review Board in Montreal, Canada (IRB # Tissue Biobank 2019-4896 and A03-M10-23A/23-02-009). The research was conducted in accordance with the International Council for Harmonization Good Clinical Practice guidelines (ICH-GCP) for clinical research involving human participants and adhered to the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans (TCPS 2). Written informed consent was obtained from all participants prior to study participation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003eThe authors confirm that all participants involved in the study have provided written informed consent for publication of the results and any accompanying data/images in this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003eThe authors report no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding sources\u0026nbsp;\u003c/strong\u003eThis study was funded by the Shriner\u0026rsquo;s Hospital for Children (72002-CAN-23) and the Canadian Institutes of Health Research (PJT-183867). KS received a studentship from Fonds de recherche du Qu\u0026eacute;bec Sant\u0026eacute; (FRQS).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003eThe authors kindly acknowledge the help from staff and surgeons at the Shriner\u0026rsquo;s Hospital for\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eChildren.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u0026nbsp;\u003c/strong\u003eLH and KS were responsible for the conception and design of the study. KS, DB acquired the experiment data. KS performed the analysis and interpretation of the data and drafted the initial manuscript. KS, DB and CC processed cell isolation from the facet joint sample. PB, NS, KU, and JO, as orthopedic surgeons, were responsible for performing AIS surgeries and harvesting tissues from organ donors. All authors participated in revising and submitting the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of generative AI and AI-assisted technologies in the writing process\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors used Grammarly to check spelling and to revise the sentences. The content was then reviewed and edited as needed, and the authors assume full responsibility for the content of the publication.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAIS (Adolescent Idiopathic Scoliosis)\u003c/p\u003e\n\u003cp\u003eCM (Conditioned Media)\u003c/p\u003e\n\u003cp\u003eCXCLs (Chemokine (C-X-C motif) Ligands)\u003c/p\u003e\n\u003cp\u003eDEG (Differentially Expressed Gene)\u003c/p\u003e\n\u003cp\u003eGSEA (Gene Set Enrichment Analysis)\u003c/p\u003e\n\u003cp\u003eGO (Gene Ontology)\u003c/p\u003e\n\u003cp\u003eFC (Fold Change)\u003c/p\u003e\n\u003cp\u003eILs (Interleukins)\u003c/p\u003e\n\u003cp\u003eM-CSF (Macrophage Colony-Stimulating Factor)\u003c/p\u003e\n\u003cp\u003eMaximum Neighborhood Component (MNC)\u003c/p\u003e\n\u003cp\u003eNSC (Non-Scoliotic Control)\u003c/p\u003e\n\u003cp\u003eOA (Osteoarthritis)\u003c/p\u003e\n\u003cp\u003eOPG (Osteoprotegerin)\u003c/p\u003e\n\u003cp\u003eOCN (osteocalcin/BGLAP)\u003c/p\u003e\n\u003cp\u003eOCT (Optimal Cutting Temperature)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePOSTN (Periostin)\u003c/p\u003e\n\u003cp\u003eOGN (Osteoglycin)\u003c/p\u003e\n\u003cp\u003ePPI-network (Protein-Protein Interaction Network)\u003c/p\u003e\n\u003cp\u003eRNAseq (RNA Sequencing)\u003c/p\u003e\n\u003cp\u003eROS (Reactive Oxygen Species)\u003c/p\u003e\n\u003cp\u003eRUNX2 (RUNX family transcription factor 2)\u003c/p\u003e\n\u003cp\u003eSHP2 (Src homology 2 domain-containing phosphatase 2)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSLC14A1 (Solute carrier family 14 member 1)\u003c/p\u003e\n\u003cp\u003eSP7 (Osterix)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSTMN2 (Stathmin 2)\u003c/p\u003e\n\u003cp\u003eTLR2 (Toll-Like Receptor 2)\u003c/p\u003e\n\u003cp\u003eTLR2A (Toll-Like Receptor 2 Agonist)\u003c/p\u003e\n\u003cp\u003eTLR4 (Toll-Like Receptor 4)\u003c/p\u003e\n\u003cp\u003eTLR4A (Toll-Like Receptor 4 Agonist)\u003c/p\u003e\n\u003cp\u003eTNF-α (Tumor Necrosis Factor-Alpha)\u003c/p\u003e\n\u003cp\u003eTRAP (Tartrate-Resistant Acid Phosphatase)\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCheng JC, Castelein RM, Chu WC, Danielsson AJ, Dobbs MB, Grivas TB, et al. 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JBMR Plus. 2023;7:e10812.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 and 2 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7602845/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7602845/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePatients with Adolescent Idiopathic Scoliosis (AIS) present with facet joint osteoarthritis, which may contribute to curve progression. While inflammatory mediators from degenerative cartilage are known to influence osteoclast activity, their effects on osteoblast function in AIS remain unclear.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePrimary facet joint osteoblasts were isolated from AIS patients undergoing spinal fusion surgery and age-matched non-scoliotic (NSC) individuals from organ donors. Transcriptomic profiles were generated by RNA sequencing, and key regulatory pathways were identified through bioinformatic analysis. Selected genes of interest were validated in an expanded cohort by qPCR. Functional capacity was assessed by comparing mineralization between AIS and NSC osteoblasts in a hydroxyapatite\u0026ndash;collagen (HA\u0026ndash;Col) three-dimensional culture system. The influence of Toll-Like Receptor (TLR) 2- or 4-pre-activated chondrocytes on osteoblast function was evaluated through qPCR analysis of bone-associated genes and mineralization assays.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAIS osteoblasts displayed 1,357 differentially expressed genes (635 upregulated, 722 downregulated) with enrichment of inflammatory pathways in Gene Ontology analysis and negative enrichment of bone-related gene sets in gene set enrichment analysis. Key osteogenic markers, including SP7, ALP, and COL1A1, were downregulated by RNA sequencing and confirmed by qPCR. Mineralization capacity was significantly impaired in AIS osteoblasts. Conditioned media from TLR2- or TLR4-pre-activated chondrocytes induced IL-6 expression, reduced osteocalcin levels, and further decreased osteoblast mineralization capacity.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAIS facet joint osteoblasts exhibit intrinsic mineralization deficits, which are exacerbated by inflammatory mediators released from TLR-activated chondrocytes. These findings identify TLR-mediated cartilage\u0026ndash;bone signalling as a potential therapeutic target to preserve facet joint integrity and maintain subchondral bone remodelling in AIS.\u003c/p\u003e","manuscriptTitle":"Reduced mineralization potential of osteoblasts in adolescent idiopathic scoliosis: intrinsic dysfunction and crosstalk with TLR-activated chondrocytes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-12 14:41:03","doi":"10.21203/rs.3.rs-7602845/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"67e3afb4-809f-4db5-91a5-33804f1f3a46","owner":[],"postedDate":"October 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-11T14:54:01+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-12 14:41:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7602845","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7602845","identity":"rs-7602845","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}