mTOR signalling mediates the spinal osteoblast pathotype at the curve apex in adolescent idiopathic scoliosis

mTOR signalling mediates the spinal osteoblast pathotype at the curve apex in adolescent idiopathic scoliosis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article mTOR signalling mediates the spinal osteoblast pathotype at the curve apex in adolescent idiopathic scoliosis Ellie H. Northall, Thomas A. Nicholson, Jon Hazeldine, Liam M. Grover, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8911774/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Adolescent idiopathic scoliosis (AIS) is associated with dysregulated bone remodelling, yet the molecular underpinnings remain unclear. To investigate site-specific osteoblast phenotypes at the spinal curve apex, we performed bulk RNA sequencing on primary matched osteoblasts isolated from the convex, concave, and non-curved regions of AIS patients. Principal component analysis revealed distinct transcriptional clustering by spinal site, independent of patient-specific factors. Differential expression analysis identified region-specific molecular profiles in convex and concave osteoblasts compared to non-curve controls, with the mTOR pathway being highlighted as one of the most dysregulated. Rapamycin, an mTOR inhibitor, reduced Alkaline phosphatase (ALP) activity, Osteoprotegerin (OPG) secretion, and mineralization, while modulating osteogenic gene expression, including sustained upregulation of RUNX2 and COL1A1 . In AIS patient-derived osteoblasts, rapamycin elicited pronounced inhibition of mTOR signalling and osteogenic activity in convex cells compared to control. Convex osteoblasts also showed elevated mTOR expression but reduced downstream translation-related signalling, suggesting dysregulated or uncoupled mTOR activity. Notably, mTOR expression level correlated with curve severity, reinforcing the link between mTOR dysregulation and AIS pathology. These findings identify mTOR signalling as a key regulatory pathway in AIS osteoblast dysfunction and highlight rapamycin as a potential, though complex, therapeutic candidate. Biological sciences/Cell biology Health sciences/Diseases Biological sciences/Molecular biology Scoliosis bone osteoblasts mTOR spine rapamycin Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Adolescent idiopathic scoliosis (AIS) is one of the most common forms of paediatric spinal deformities [ 1 ]. Defined as abnormal lateral curvature of the spine, it occurs during the adolescent growth spurt, usually between the ages of 10 and 18 and requires a lateral vertebral rotation (Cobb angle) of greater than 10° to meet the clinical definition [ 2 ]. It is estimated to affect 2–4% of this population [ 3 ] and accounts for approximately 90% of idiopathic scoliosis in adolescents. AIS is a complex, multifaceted condition with a poorly understood pathophysiology; however, growing evidence suggests that intrinsic factors, particularly genetic influences, play a significant underlying role. Individuals who have a first degree relative affected by AIS have an increased risk of developing the condition [ 4 ], and people who inherit single nucleotide polymorphisms (SNPs) in the POC5 [ 5 – 8 ] and/or TTLL11 [ 9 ] genes also have an increased risk. As scoliosis is widely reported to be more prevalent [ 10 – 13 ] and more severe in females than in males [ 14 – 18 ], the role of hormones such has oestrogen has been investigated. To this end, it has been reported that female AIS patients exhibit lower blood oestradiol level than age-matched control females [ 19 ], suggesting a potential hormonal contribution to the condition’s genetic susceptibility. Increasing evidence suggests that abnormalities in spinal bone development and remodelling are a central driver of AIS pathology. Notably, AIS patients exhibit altered bone structural parameters, including lower bone mineral density (BMD) [ 20 ] and asymmetric vertebral growth compared to age-matched healthy controls - features that may contribute directly to curve initiation and progression. Despite these observations, investigations into the underlying cellular and molecular mechanisms for these findings are limited, largely due to the ethical and logistical access challenges of obtaining spinal tissue samples from paediatric patients. Consequently, much of the current understanding is derived from animal models such as zebrafish or chickens, which although useful, do not fully replicate the human condition in terms of biomechanical environment or developmental timing. Human studies have instead focused on surrogate tissues, such as blood, or cells derived from muscle [ 21 ] or cartilage [ 22 ], which offer indirect insights into spinal pathology. However, a growing number of studies are now beginning to directly assess spinal osteoblasts, the drivers of bone formation, in AIS patients [ 23 , 24 ], offering a more targeted approach to understanding the skeletal abnormalities that underlie this complex disorder. Critically, we recently reported that spinal osteoblasts at the curve apex in AIS patients exhibit intrinsic functional impairment, with greater metabolic and proliferative capacity observed in osteoblasts isolated from the convex site of the curve apex, compared to concave or non-curve osteoblasts from the same patients [ 25 ]. Therefore, we hypothesised that dysregulated signalling in spinal osteoblasts at the curve apex plays a central underlying role in the development of AIS. The aim of this study was therefore to determine the cellular mediators of these dysfunctional curve apex AIS osteoblasts, such that candidate pathways and targets can be identified for subsequent therapeutic modulation. Results 1. Spinal AIS osteoblasts at the curve apex exhibit a differential transcriptomic phenotype Initially, we investigated whether AIS patient osteoblasts at the curve apex exhibit an intrinsic differential transcriptomic phenotype, compared to osteoblasts from a non-curved site. Osteoblasts were isolated from either side of the curve apex (convex and concave) and osteoblast from non-curve spinal facet tissue ( Figure 1A ) of n=6 AIS patients (see Table 1 for clinical details) and subjected to bulk RNA sequencing. Principal component analysis (PCA) of the RNA sequencing data revealed distinct clustering by spinal site (i.e. concave, convex or non-curve), independent of patient ( Figure 1B ). This strikingly demonstrates that spinal site was a greater factor in the overall osteoblast gene expression phenotype than patient-specific characteristics including sex or age. Notably, convex and concave osteoblasts formed separate clusters, indicating that each side of the curve apex is associated with a distinct transcriptional identity rather than representing a uniform “curved” phenotype. Two datasets of differentially expressed genes (DEGs) (p1.5 fold-change) were generated from this analysis: (1) Comparison of patient-matched convex curve osteoblasts with non-curve osteoblasts; (2) Comparison of patient-matched concave curve osteoblasts with non-curve osteoblasts. Interestingly, both DEG datasets showed similar proportions of gene types including mRNAs as well as non-coding RNAs such as microRNAs, lncRNA and pseudogenes ( Figure 1C ), suggesting that broad transcriptional regulation, rather than selective gene class effects, underlies the observed differences. In total, 647 upregulated DEGs were identified in the convex vs non-curve comparison, whilst 768 upregulated DEGs identified between concave vs non-curve, of which 168 genes (representing 26%) were common to both comparisons ( Figure 1D ). Correspondingly, 369 DEGs were downregulated in the convex vs non-curve dataset, whilst 535 DEGs were downregulated between concave vs non-curve, of which 136 DEGS (representing 37%) were common to both comparisons. This partial overlap indicates the presence of both shared curve apex–associated transcriptional changes and region-specific molecular signatures unique to the convex or concave side. In the concave vs non-curve comparison, the most significant DEG by p-value was the transcription factor kruppel-like factor 6 (KLF6) (p-value 0.00000407, q-value 0.23707534) followed by transcription factor JUNB (p-value 0.00000791, q-value 0.23707534), while the DEG with the largest fold change was long intergenic non-protein coding RNA 1004 (LINC01004) (FC +16.0985641) ( Figure 1E ). In the convex vs non-curve comparison, the most significant DEG by p-value was NOP14 Antisense RNA 1 (NOP14-AS1) (p-value 0.000000136, q-value 0.00825825) followed by the transcription factor hairy and enhancer of split-1 (HES1) (p-value 0.00000156, q-value 0.04734841), while the DEG with the largest fold change was long intergenic non-protein coding RNA 472 (LINC00472) (+16.77462044 FC) ( Figure 1F ). Together, these data demonstrate that osteoblasts at the AIS curve apex possess an intrinsic, spatially defined transcriptomic phenotype characterised by both shared and region-specific gene expression changes. To determine the biological significance of these transcriptional differences, we then interrogated dysregulated signalling pathways and upstream regulatory mechanisms associated with each curve region. 2. Dysregulated canonical signalling pathways in curve apex osteoblasts reveals candidate upstream regulators Next, we used ingenuity pathway analysis (IPA, Qiagen, UK) software to identify the dysregulated canonical signalling pathways related to each of the two DEG datasets i.e., convex curve vs non-curve, and concave curve vs non-curve. The most significant pathway identified for each comparison was different; the convex vs non-curve comparison revelated eukaryotic initiation factor 2 (EIF2) signalling as the most dysregulated pathway (-log(p-value) 11.7), ( Figure 2A ), with the network summary ( Figure 2B ) highlighting dysregulated cell division and proliferation including activation of DNA promoters, transcription of RNA and entry into cell cycle phases. In contrast, the concave vs non-curve comparison revealed integrin linked kinase (ILK) signalling as the most dysregulated pathway (-log(p-value) 7), ( Figure 2C ), with the network summary ( Figure 2D ) predominantly highlighting processes of bone and osteoblast differentiation, and fibrogenesis. These findings suggest that convex and concave osteoblasts may be influenced by distinct biological pressures, potentially reflecting differences in mechanical loading or microenvironmental cues across the curve apex. Notably, pathway analysis revealed that both comparisons (i.e. concave vs non-curve; convex vs non-curve) shared several dysregulated pathways, namely, pro-inflammatory cytokine signalling pathways including IL-6, IL-8 and IL-17A. This convergence suggests a common inflammatory component within the curve apex that may act alongside region-specific signalling changes in AIS pathophysiology. To further interrogate potential drivers of these transcriptional changes, we performed upstream regulator analysis to identify genes and drugs whose predicted activity states could explain the observed DEG patterns. Upstream regulator analysis of the convex vs non-curve DEGs predicted the dimer PDGF-BB (composed of two Platelet-derived growth factor subunit B) to be the most inhibited, with the growth factors EGF and HGF and transcriptional regulators (CREB1, RELA, LARP1) also predicted to be significant inhibited upstream regulators ( Figure 2E ). Of the predicted activated upstream regulators, the PI3K inhibitor LY294002 was predicted to be the most activated, with other chemical inhibitors (U0126, PD98059) and transcription regulators (MLXIPL, MYCN, ZFP36) also highlighted as significant activators ( Figure 2E ). In contrast, upstream regulator analysis of the concave vs non-curve comparison ( Figure 2F ), revealed TGFB1 as the most highly inhibited regulator, with the TGF-β family as a whole, and the transcription regulator SMAD3 also predicted to be significant inhibited regulators. Of the predicted activated upstream regulators identified, the JNK inhibitor SP600125 was the most highly activated, with LY294002 again predicted along with microRNAs (miR-30c-5p, miR-338-3p, miR-29b-3p) to be significant activated upstream regulators ( Figure 2F ). Finally, predicted biological functions relevant to bone were filtered from the convex vs non-curve comparison, with most predicted to be downregulated by Z-Score, with the most significant by p-value being growth of connective tissue ( Figure 2G ). For the concave vs non-curve comparison, most functions were again predicted to be downregulated with differentiation of connective tissue cells being the most significant by p-value ( Figure 2H ). These results highlight region-specific regulatory and upstream mechanisms that are distinct to each curve site. These results indicate that distinct upstream regulatory networks operate at each side of the curve apex, and with the identification of multiple chemical inhibitors as upstream regulators, prompted us to functionally test whether pharmacological modulation could alter osteoblast behaviour. 3. The mTOR pathway inhibitor rapamycin alters osteogenic functional activity in a human osteoblast cell line In order to identify and test candidate drugs that could modulate the phenotype of AIS osteoblasts at the curve apex, we filtered the upstream regulators identified from pathway analysis to include only commercially available small molecule inhibitors/activators. This provided a list of 12 candidate drugs ( Supplementary Table S2 ), which were screened to assess acute (24 h) and chronic (21 day) effects on multiple parameters of osteoblast function (including mineralisation, alkaline phosphatase activity (ALP), osteoprotegerin (OPG) secretion and gene expression of modulators of osteoblast function) using the human foetal osteoblast cell line hFOb 1.19 ( Figure 3A ). For all screen parameters, 30,000 cells were seeded per well, then cultured in osteogenic media for 3 days before treatment given, also in osteogenic media. Across these multiple parameters of osteoblast function, the mTOR inhibitor rapamycin was found to elicit the most pronounced and consistent effects, as summarised by the heatmap ( Figure 3B; Supplementary Figure 1-5 ). Acute (24hr) treatment with rapamycin (1 nM) significantly reduced both ALP enzymatic activity ( Figure 3C ) and OPG secretion ( Figure 3D ) compared to vehicle control. Furthermore, chronic treatment with rapamycin showed a significant reduction in the ability of the osteoblasts to form and deposit mineral in their matrix, assessed by alizarin red quantification ( Figure 3E ). To investigate whether these functional changes are a result of rapamycin differentially affecting key genes associated with osteoblast differentiation and maturation, cells were dosed (1 nM) every three days for 21 days and RNA extracted after 7-, 14- and 21-day timepoints. For osteogenic markers ( Figure 3F ), 7 days of rapamycin treatment resulted in no significant effect on ALPL (tissue non-specific alkaline phosphatase) expression, a significant increase in RUNX2 (runt-related transcription factor 2) expression, which was also increased at 21 days and a significant increase in COL1A1 (alpha-1 type I collagen) expression at 14 and 21 days. SP7 (osterix) expression was highly variable, and statistically significant differences were not detected between rapamycin treatment and vehicle control at any timepoint. Notably, by day 21, SP7 expression was undetectable in either rapamycin treated or control cells. For markers associated with mineralisation initiation ( Figure 3G ), BMP2 (bone morphogenetic protein 2) was significantly higher at 14 days of rapamycin treatment compared to vehicle control, whereas SPP1 (osteopontin) showed no significant differences between rapamycin or control cells at any time point, and expression was markedly reduced from day 7 onwards in both control and rapamycin treated cells. Secreted type-1 collagen (COL1A1), also a key functional indicator of osteoblast activity, was also significantly increased at week three with rapamycin treatment ( Figure 3H ) compared to vehicle control. These results collectively suggest that rapamycin is capable of modulating both the function and differentiation of osteoblasts, prompting further investigation of mTOR signalling in primary AIS osteoblasts. 4. mTOR signalling dysregulation in curve apex osteoblasts and its association with curve severity Given our finding that rapamycin elicits functional responses in osteoblasts, we next mapped the transcriptomic dataset from the convex v non-curve comparison onto the mTOR signalling pathway to interrogate which pathway components were dysregulated ( Figure 4A ). Much of the pathway was predicted to be activated, including both mTOR complexes (mTORC1 and 2), although translation subunits were predicted to be inhibited ( Figure 4A ). Bolstering the connection between dysregulated mTOR signalling in osteoblasts at the curve apex and AIS pathology, we also found that mTOR pathway components correlated significantly with curve severity at the convex site ( Figure 4B ). AKT1 gene expression negatively correlated with curve severity, whilst IR protein expression, and mTOR gene and protein expression positively correlated with curve severity Finally, we profiled mTOR pathway protein ( Figure 4C ) and phosphorylation ( Figure 4D ) levels, both upstream and downstream of mTOR itself, in patient matched convex and non-curve osteoblasts. For markers upstream of mTOR, we found significant decreases in insulin receptor levels (IGF1R and IR) in osteoblasts isolated from convex regions compared to patient-matched non-curve cells, as well as a significant increase in PTEN expression. mTOR itself was found to be expressed significantly higher in the convex cells, with no difference in downstream pathway component expression. Interestingly, no upstream markers of mTOR, nor mTOR itself, were found to be significantly different at the phosphorylation level between convex and non-curve cells. For markers downstream of mTOR, RPS6 had significantly lower phosphorylation levels in the convex cells. Together, these findings suggest that osteoblasts at the curve apex show a dysregulated mTOR signalling state characterised by altered signal integration and reduced translational output rather than canonical mTOR activation. 5. The mTOR inhibitor rapamycin modulates the function and phenotype of AIS spinal osteoblasts Next, the ability of rapamycin to modulate the phenotype of primary osteoblasts from the curve apex (convex) and from outside the curve (non-curve) in AIS patients was assessed. We examined the functional effect of rapamycin treatment on the cells from the different spinal sites. Similar to that observed using the hFOb cell line, short term treatment of rapamycin (1 nM) significantly reduced ALP activity in primary AIS patient osteoblasts compared to vehicle control ( Figure 5A ). Notably, the greatest effect was observed in convex curve osteoblasts (average 27% reduction) compared to an average 19% reduction in non-curve cells. OPG secretion was also reduced in convex cells with treatment (average 21.5% reduction) but had the greatest effect in non-curve cells (average 29% reduction). Mineralisation of both convex and non-curve cells was reduced at similar rate after chronic treatment ( Figure 5B ). Next, we profiled the effect of rapamycin on the expression and their phosphorylation status of other mediators within the mTOR pathway on convex osteoblasts. Rapamycin significantly increased IGF1R, PTEN and p70S6K protein expression in convex cells ( Figure 5C ). Conversely, rapamycin significantly reduced expression of mTOR itself. Additionally, rapamycin increased phosphorylation of TSC2, whilst decreasing phosphorylation of p70S6K ( Figure 5D ). Discussion Dysregulated bone remodelling is a driving factor in numerous musculoskeletal diseases across the lifespan. Here, we have demonstrated for the first time that the mTOR signalling pathway is altered in AIS osteoblasts at the curve apex and provide evidence that pharmacological inhibition of mTOR signalling may, in part, reverse this pathotype. Importantly, our data further demonstrate that these alterations are highly spatially dependent, with osteoblasts from convex and concave regions of the curve apex exhibiting distinct molecular and functional phenotypes compared to non-curved spinal sites. Patient-matched convex and concave spinal tissue in AIS are known to display different tissue parameters including BMD and trabecular thickness [ 25 ], which supports the concept that different intrinsic pathological drivers are responsible for mediating the osteoblast pathotype at each side of the curve apex. Pathway analysis of differentially expressed gene datasets of spinal osteoblast cells derived from the apex of the curve revealed distinct and shared dysregulated biological pathways between curved (concave and convex) and osteoblasts from non-curved sites. Consistent with this, principal component analysis of osteoblast transcriptomes revealed clustering by spinal site rather than by patient-specific variables such as age or sex, indicating that local microenvironmental cues dominate osteoblast identity in AIS. Pathway analysis of differentially expressed gene datasets of spinal osteoblast cells derived from the apex of the curve revealed distinct and shared dysregulated biological pathways between curved (concave and convex) and osteoblasts from non-curved sites. In the convex vs non-curve comparison, EIF2 signalling was the most dysregulated, with enriched pathways related to cell proliferation and division, and PDGF-BB identified as the most inhibited upstream regulator. In contrast, the concave vs non-curve comparison showed ILK signalling as the most dysregulated, with pathways associated with bone and osteoblast differentiation, and TGFB1 as the most inhibited upstream regulator. These findings suggest that convex osteoblasts may exist in a state of altered translational control and cellular stress, whereas concave osteoblasts display changes more closely aligned with matrix interaction and differentiation processes. Despite these differences, both comparisons shared dysregulation of key pro-inflammatory cytokine signalling pathways, including IL-6, IL-8, and IL-17A, and featured common upstream regulators such as the PI3K inhibitor LY294002, potentially indicating increased inflammatory responses in spinal tissue at either side of the curve apex. This convergence on inflammatory signalling supports emerging evidence that low-grade inflammation contributes to abnormal bone remodelling in AIS and may act synergistically with mechanical and metabolic stressors. Screening a panel of identified pharmacological upstream regulators as candidate drugs that could mediate the phenotype of osteoblasts at the curve apex revealed that rapamycin, an mTOR inhibitor, the most effective candidate. The mammalian/mechanistic target of rapamycin (mTOR) is well known as a central regulator of cell growth and metabolism. mTOR is known for roles in bone remodelling [ 26 ] and mTORC1 specifically was shown to facilitate bone healing in a mouse model [ 27 ]. The mTOR pathway has also previously been implicated in scoliosis, albeit in animal models, including rat [ 28 ], and zebrafish [ 29 ] systems, underscoring its relevance to spinal development and deformity. mTOR exists as two complexes: mTORC1 and mTORC2. mTORC1 activation is required for preosteoblast proliferation, but overactivation can impair differentiation and maturation, thought to be through Notch pathway activation [ 30 ]. However, when mTORC1 is disrupted, there is decreased matrix synthesis and mineralization, suggesting that it can promote the transition to mature osteoblasts [ 31 ]. Interestingly, inhibition of mTOR was found to supress osteogenic gene expression whilst under strain [ 32 ]. Rapamycin selectively inhibits mTORC1, which is responsible for promoting protein synthesis, cell growth and metabolism. These findings collectively highlight the highly context- and stage-dependent role of mTOR signalling in osteoblast biology. Rapamycin has shown promise for treating several bone diseases, including those involving aging or inflammation such as osteoporosis [ 33 ] and osteoarthritis [ 34 ], and those involving abnormal bone remodelling: heterotopic ossification [ 35 ], osteolytic disease [ 36 ]. However, the potential of rapamycin as a therapeutic has been evaluated in predominantly older populations. Preclinical studies assessing its skeletal effects have produced mixed results, with reports of reduced bone density following prolonged treatment [ 37 ], contrasted by minimal effects on bone microarchitecture or strength with short term, low dose treatment [ 38 ]. In our study we found that rapamycin supressed functional human osteoblast markers (ALP, OPG) and mineralization capacity in both a human osteoblast cell line and in AIS patient primary spinal osteoblasts from the curve apex. Furthermore, Rapamycin, increased the expression of key osteogenic genes RUNX2 , COL1A1 , as well as increased collagen production. The continued higher expression of RUNX2 , typically considered an early osteoblast marker [ 39 ], suggests that rapamycin may have not only anti-proliferative effects but may also disrupt osteoblast differentiation, consistent with a block in late-stage maturation. Notably, the persistence of BGLAP expression and the absence of detectable SP7 expression at later timepoints suggest that mTOR inhibition may uncouple early differentiation from terminal maturation rather than fully abrogating osteogenesis. The downregulation of SPP1 at later timepoints may reflect the loss of SP7 , which along with RUNX2 , is required for its expression [ 40 – 42 ]. Further evidence for the role of dysregulated mTOR signalling in AIS pathogenesis was garnered upon finding that the expression of several mediators of mTOR signalling were not only differentially expressed in curve apex spinal osteoblasts but that their expression correlated with curve severity. However, of note, although mTOR expression was increased in convex curve apex osteoblasts and the pathway appears broadly activated, translation-related outputs (e.g., RPS6 phosphorylation) were reduced, suggesting a dysregulated or uncoupled mTOR response. Specifically, upstream mTOR signalling was dampened, evidenced by reduced insulin receptor expression and increased PTEN, while downstream translational activity was suppressed despite elevated mTOR levels. This decoupling suggests that altered mTOR signalling in AIS osteoblasts is not driven by canonical phosphorylation-based activation but may instead reflect impaired signal integration and translational control. The reduced expression of IGF1R and IR in convex cells may reflect crosstalk with other spinal tissues or systemic metabolic influences and may contribute to altered autophagy regulation rather than increased protein synthesis. This interpretation is supported by the identification of EIF2 signalling as the most dysregulated pathway in the convex vs non-curve comparison, a pathway closely linked to cellular stress responses and the unfolded protein response (UPR). Together, these features may underpin both the altered functional phenotype of convex osteoblasts and their association with curve severity in AIS. There are several limitations to this study. First, the relatively small patient cohort reflects the challenges of obtaining spinal tissue during corrective surgery in adolescents. As a result, sex-specific analyses were not feasible, despite the known influence of sex hormones on bone metabolism and insulin/mTOR signalling [ 43 ]. Second, while we identified strong associations between osteoblast phenotypes, mTOR pathway components and curve severity, causality cannot be inferred. Longitudinal sampling of spinal tissue is not ethically feasible, highlighting the need for future studies to identify circulating biomarkers reflective of curve apex osteoblast phenotypes. Such biomarkers could enable longitudinal monitoring of disease progression and treatment response. Additionally, limited tissue availability constrained architectural and mechanistic analyses, and in vitro studies were inherently limited by the proliferative capacity of primary osteoblasts. In conclusion, we demonstrate that AIS is associated with intrinsic, spatially defined osteoblast dysfunction at the curve apex, characterised by dysregulated mTOR signalling. Rapamycin partially modulated this phenotype, revealing mTOR as a key mechanistic node linking inflammatory, metabolic and stress-related pathways in AIS. While systemic mTOR inhibition is unlikely to be clinically viable in adolescents, our findings provide a strong rationale for exploring targeted modulation of mTOR-related pathways as a strategy to correct asymmetric bone remodelling in AIS and potentially other disorders of abnormal skeletal growth. Materials and methods 1. Patient recruitment and collection of spinal tissues Facet spinal tissue was collected perioperatively from AIS patients undergoing surgery at the Royal Orthopaedic Hospital, Birmingham, UK, with prior informed patient (and/or parent/carer) consent and research ethics committee approval (19/WM/0083). The study was conducted in compliance with the Declaration of Helsinki; clinical data are summarised in Table 1 . 2. Isolation of spinal osteoblasts and cell culture Facet bone chips were washed three times in Dulbecco’s Modified Eagles Media (DMEM) (Cat: 41965062; Gibco) containing 100 U/mL penicillin streptomycin (Cat: 15140122; Gibco) and cultured in differentiation media (DMEM, 10% FBS, 100 U/mL penicillin streptomycin, 1% non-essential amino acids (NEAA) (Cat: 11140035; Gibco), 2 mM β-glycerophosphate (Cat: G9422; Sigma-Aldrich), 50 µg/mL L-Ascorbic acid (Cat: A5960; Sigma-Aldrich), 10 nM Dexamethasone (Cat: D4902; Sigma-Aldrich)). Media was changed every three days and bone chips removed upon the appearance of adhered osteoblasts. Primary cells were then used between passages 1 and 3. hFOb 1.19 cells (CRL-3602; ATCC) were cultured in either basal media, composed of DMEM/F-12, no phenol red (Cat:11580546; Gibco) supplemented with 10% FBS and 0.3 mg/mL G418 (Cat: 4727878001; Sigma-Aldrich) or osteogenic media, composed of basal media supplemented with 10 -8 M menadione and 100 µg/mL L-Ascorbic acid (all from Sigma-Aldrich). Unless stated otherwise, cells were seeded then cultured in osteogenic media for 3 days before treatment or assay. hFOb cells were used between passages 10 and 14. 3. Transcriptomic analysis RNA was extracted using a RNeasy Mini Kit (Cat: 74104; Qiagen) according to manufacturer’s instructions. Cells were collected by addition of RLT buffer supplemented with β-mercaptoethanol and incubated on ice for 20 minutes. RNA was quantified using a NanoDrop One (Thermo Scientific). For RNA sequencing, RNA integrity (RIN) was evaluated in P1 primary osteoblasts by bioanalyzer (Agilent) and samples with a RIN >7 were deemed acceptable. Sequencing was performed by Birmingham Genomics using QuantSeq 3’ mRNA-Seq Library Prep Kit FWD for Illumina (Lexogen). Data processing was performed in Qlucore, (Lund, Sweden) and pathway analyses were performed using Ingenuity Pathway Analysis (IPA) (V21.0; Qiagen). Differentially expressed genes (fold change of ± >1.5, p < 0.05) were analysed using the core functional analysis feature to identify significant canonical pathways and cellular processes for each comparison (concave/non-curve, convex/non-curve). For selective gene expression analysis, relative mRNA expression was determined by Quantitative Real-Time Polymerase Chain Reaction (RT-qPCR) in hFOb cells. This was performed using the iTaq™ Universal SYBR® Green One-Step Kit (Cat: 1725151; BIO-RAD), 5 ng total RNA and primers ( Supplementary Table S1 ) (Merck) on a CFX384 C1000 Touch Thermal Cycler (BIO-RAD). After normalisation to housekeeping gene 18S, data are presented as relative expression unless stated otherwise. 4. Alkaline phosphatase activity assay Alkaline phosphatase activity was assessed at 24 hours post treatment. Cells were lysed by addition of RIPA buffer (1X) (Cat: 20-188; Millipore) supplemented with protease and phosphatase inhibitors (Cat: 4693132001, 4906845001; Roche) and placed on ice for 20 minutes with agitation. Cells were harvested using a cell scraper, passed through a 21-gauge needle, and then centrifuged at 20,000 x g for 15 minutes at 4°C. Total protein concentration was determined using BCA Assay (Cat: 23225; Thermo Scientific). Lysates were then added to room temperature alkaline phosphatase yellow (pNPP) liquid substrate (Cat: P7998, Sigma-Aldrich) at a 1:4 ratio in a 96 well plate. The plate was protected from light and incubated at 37°C on a shaker for 45 minutes. The plate was then quantified using a synergy HT plate reader at 405 nm absorbance (with 540 nm as a wavelength control). Data is presented as fold change to vehicle control, after normalisation to total protein unless stated otherwise. 5. Alizarin red staining Alizarin red staining and quantification was performed using an ARed-Q kit (Cat: 8678; Caltag+Medsystems) according to manufacturer’s protocol. Rapamycin (1 nM, Cat: r0161 ; LKT Laboratories) treatment or vehicle control was dosed every 3 days and the cells left to mineralise for 3-4 weeks. Cells were then fixed in 4% paraformaldehyde (PFA) prior to staining with 40 mM Alizarin red solution (ARS) per well. Dye was then extracted using 10% acetic acid, incubated for 30 min at RT. Cells were then transferred to a 1.5 mL Eppendorf tube and vortexed for 30 seconds before boiling at 85°C for 10 min. Tubes were then placed on ice before centrifugation at 20,000 x g for 15 min. 10% ammonium hydroxide was then added to 500 μL of supernatant to neutralise the acid. Standards were prepared according to manufacturer’s instructions and both standards and samples were loaded onto a 96-well opaque-walled transparent bottomed plate and read at 405 nm using a Synergy HT plate reader (Biotek). Data are presented in mM after standard curve quantification. 6. Luminex and ELISAs mTOR pathway signalling was assessed using the Total Akt/mTOR 11-plex (Cat: 48-612MAG; Merck-Millipore) and Phosphoprotein kits (Cat: 48-611MAG; Merck-Millipore) according to manufacturer’s instructions. In brief, 1 mg total protein for each sample was loaded in triplicate and the samples incubated overnight at 4°C in the dark with agitation. The next day, samples were analysed on a Luminex® 200™ system running settings recommended by the manufacturer. Total protein is presented as median fluorescence intensity (MFI), and phosphoprotein results were normalised to the respective total protein. For the quantification of OPG (human osteoprotegerin/TNFRSF11B) and COL1A1 (human pro-collagen 1 α1), ELISAs (Cat: DY805 and DY6220-05; R&D Systems) were performed on cell supernatants according to manufacturer’s instructions. Data was analysed using a 4-parameter logistic curve and plotted as concentrations. 7. Statistical analysis All statistical analysis was performed in Graphpad Prism v10.5.0. All data are mean ± standard error of mean (SEM) unless stated otherwise. Normality tests on all data were performed first using both Shapiro-Wilk and Kolmogorov-Smirnov tests, with Shapiro-Wilk being used solely on datasets with too small an n for Kolmogorov-Smirnov. Significance levels were set at P<0.05, with individual figure legends indicating which specific statistical test were used. Declarations Authors contribution S.W.J and M.NE conceived the idea. M.NE acquired clinical data and patient samples. E.H.N, T.A.N and J.H developed the methods, carried out the experiments and contributed to data interpretation and analysis. E.H.N drafted the manuscript. H.M.M, L.G, A.J.N and S.W.J supervised the project. All authors reviewed and approved the final manuscript. Funders statement E.H.N was funded by the University of Birmingham. S.W.J received grants from UKRI Medical Research council (reference MR/W026961/1) and Arthritis UK (reference 21812). Acknowledgements The authors acknowledge all study participants, research staff at the Royal Orthopaedic Hospital NHS Foundation Trust for obtaining consents and screening. The authors would like to acknowledge the Birmingham Genomics facility at the University of Birmingham for support of bulk RNA sequencing experiments. This study has been delivered through the National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre (BRC). Data availability Bulk RNA-sequencing data will be made available. Additional information The author(s) declare no competing interests. References Konieczny, M.R., H. Senyurt, and R. Krauspe, Epidemiology of adolescent idiopathic scoliosis. J Child Orthop, 2013. 7 (1): p. 3-9. Weinstein, S.L., et al., Adolescent idiopathic scoliosis. Lancet, 2008. 371 (9623): p. 1527-37. Negrini, S., De Mauroy, J.C., Grivas, T.B., Knott, P., Maruyama, T., O'Brien, J.P., Rigo, M., Zaina, F., Actual evidence in the medical approach to adolescents with idiopathic scoliosis. Eur J Phys Rehabil Med, 2014. 50 (1): p. 87-92. Ogilvie, J.W., et al., The search for idiopathic scoliosis genes. Spine (Phila Pa 1976), 2006. 31 (6): p. 679-681. Patten, S.A., et al., Functional variants of POC5 identified in patients with idiopathic scoliosis. J Clin Invest, 2015. 125 (3): p. 1124-8. Xu, L., et al., Common variant of POC5 is associated with the susceptibility of adolescent idiopathic scoliosis. Spine (Phila Pa 1976), 2017. 43 (12): p. E683-E688. Hassan, A., et al., Adolescent idiopathic scoliosis associated POC5 mutation impairs cell cycle, cilia length and centrosome protein interactions. 2019, 2019. 14 (3). Mathieu, H., et al., Prevalence of POC5 Coding Variants in French-Canadian and British AIS Cohort. Genes 2021, 12(7), 1032; https://doi.org/, 2021. 12 (7). Mathieu, H., et al., Genetic variant of TTLL11 gene and subsequent ciliary defects are associated with idiopathic scoliosis in a 5-generation UK family. Sci Rep, 2021. 11 . Kamtsiuris, P., et al., Prevalence of somatic diseases in German children and adolescents. Results of the German Health Interview and Examination Survey for Children and Adolescents (KiGGS) Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz, 2007. 50 (5-6): p. 686-700. Daruwalla, J.S., et al., Idiopathic scoliosis. Prevalence and ethnic distribution in Singapore schoolchildren. J Bone Joint Surg Br., 1985. 67 (2): p. 182-184. Cilli, K., et al., School screening for scoliosis in Sivas, Turkey. Acta Orthop Traumatol Turc, 2009. 43 (5): p. 426-430. Nery, L.S., et al., Prevalence of scoliosis among school students in a town in southern Brazil. Sao Paulo Med J, 2010. 128 (2): p. 69-73. Soucacos, P.N., et al., School-screening for scoliosis. A prospective epidemiological study in northwestern and central Greece. J Bone Joint Surg Am, 1997. 79 (10): p. 1498-1503. Raggio, C.L., Sexual dimorphism in adolescent idiopathic scoliosis. Orthop Clin North Am, 2006. 37 (4): p. 555-558. Luk, K.D., et al., Clinical effectiveness of school screening for adolescent idiopathic scoliosis: a large population-based retrospective cohort study. Spine (Phila Pa 1976), 2010. 35 (17): p. 1607-1614. Ueno, M., et al., A 5-year epidemiological study on the prevalence rate of idiopathic scoliosis in Tokyo: school screening of more than 250,000 children. J Orthop Sci, 2011. 16 (1): p. 1-6. Richards, B.S., et al., Treatment of adolescent idiopathic scoliosis using Texas Scottish Rite Hospital instrumentation. Spine (Phila Pa 1976), 1994. 19 (14): p. 1598-1605. Kulis, A., et al., Participation of sex hormones in multifactorial pathogenesis of adolescent idiopathic scoliosis. International orthopaedics, 2015. 39 : p. 1227-1236. Nishida, M., et al., Persistent low bone mineral density in adolescent idiopathic scoliosis: A longitudinal study. J Orthop Sci, 2023. 28 (5): p. 1099-1104. Shao, Z., et al., A targeted antibody-based array reveals a serum protein signature as biomarker for adolescent idiopathic scoliosis patients. BMC Genomics, 2023. 24 (1): p. 522. Sheng, K., Bission, D., Saran, N., Bourdages, J., Coluni, C., Upshaw, K., Tiedemann, K., Komarova, S., Ouellet, J., Haglund, L., The TLR-M-CSF axis is implicated in increased bone turnover and curve progression in adolescent idiopathic scoliosis. Arthritis Research & Therapy, 2025. 27 . Oliazadeh N, G.K., Elbakry M, Moreau A. , Altered mechanotransduction in adolescent idiopathic scoliosis osteoblasts: an exploratory in vitro study. Sci Rep, 2022. 12 (1). He S, L.J., Wang Y, Xiang G, Yang G, Xiao L, Tang M, Zhang H., Phosphorylated heat shock protein 27 improves the bone formation ability of osteoblasts and bone marrow stem cells from patients with adolescent idiopathic scoliosis. JOR Spine, 2023. Pearson, M.J., et al., Evidence of Intrinsic Impairment of Osteoblast Phenotype at the Curve Apex in Girls With Adolescent Idiopathic Scoliosis. Spine Deform, 2019. 7 (4): p. 533-542. Chen, J. and F. Long, mTOR signaling in skeletal development and disease. Bone Res, 2018. 6 : p. 1. Li, D., et al., Dynamic control of mTORC1 facilitates bone healing in mice. Bone, 2025. 190 : p. 117285. Wang, Y., X.D. Yi, and C.D. Li, Suppression of mTOR signaling pathway promotes bone marrow mesenchymal stem cells differentiation into osteoblast in degenerative scoliosis: in vivo and in vitro. Mol Biol Rep, 2017. 44 (1): p. 129-137. Sun, X., et al., Dstyk mutation leads to congenital scoliosis-like vertebral malformations in zebrafish via dysregulated mTORC1/TFEB pathway. Nat Commun, 2020. 11 (1): p. 479. Huang, B., et al., mTORC1 Prevents Preosteoblast Differentiation through the Notch Signaling Pathway. PLoS Genet, 2015. 11 (8): p. e1005426. Chen, J. and F. Long, mTORC1 Signaling Promotes Osteoblast Differentiation from Preosteoblasts. PLoS One, 2015. 10 (6): p. e0130627. Wang, D., et al., The interactions between mTOR and NF-kappaB: A novel mechanism mediating mechanical stretch-stimulated osteoblast differentiation. J Cell Physiol, 2020. Luo, D., et al., Rapamycin reduces severity of senile osteoporosis by activating osteocyte autophagy. Osteoporos Int, 2016. 27 (3): p. 1093-1101. Dhanabalan, K.M., et al., Intra-articular injection of rapamycin microparticles prevent senescence and effectively treat osteoarthritis. Bioeng Transl Med, 2023. 8 (1): p. e10298. Hu, Y. and Z. Wang, Rapamycin prevents heterotopic ossification by inhibiting the mTOR pathway and oxidative stress. Biochem Biophys Res Commun, 2021. 573 : p. 171-178. Hussein, O., et al., Rapamycin inhibits osteolysis and improves survival in a model of experimental bone metastases. Cancer Lett, 2012. 314 (2): p. 176-84. Martin, S.A., et al., Rapamycin impairs bone accrual in young adult mice independent of Nrf2. Exp Gerontol, 2021. 154 : p. 111516. Devine, C.C., et al., Rapamycin does not alter bone microarchitecture or material properties quality in young-adult and aged female C57BL/6 mice. JBMR Plus, 2024. 8 (2): p. ziae001. Komori, T., Regulation of osteoblast differentiation by Runx2. Adv Exp Med Biol, 2010. 658 : p. 43-9. Tu, Q., P. Valverde, and J. Chen, Osterix enhances proliferation and osteogenic potential of bone marrow stromal cells. Biochem Biophys Res Commun, 2006. 341 (4): p. 1257-65. Kim, Y.J., et al., The bone-related Zn finger transcription factor Osterix promotes proliferation of mesenchymal cells. Gene, 2006. 366 (1): p. 145-51. Cao, Z., et al., Osterix controls cementoblast differentiation through downregulation of Wnt-signaling via enhancing DKK1 expression. Int J Biol Sci, 2015. 11 (3): p. 335-44. Khosla, S., M.J. Oursler, and D.G. Monroe, Estrogen and the skeleton. Trends in Endocrinology and Metabolism, 2012. 23 (11): p. 576-81. Table Table 1. Demographic information for AIS patient tissue donors used in this study . ID Age (years) Sex Height (cm) Weight (kg) BMI Waist circ. (cm) Hip circ. (cm) Waist : Hip (ratio) Cobb angle (°) 1* 18 M 170 54.6 18.9 74 76 0.97 54.5 2 16 F 160 71.7 28.0 97 106 0.92 50.6 3* 18 F 160 71.7 28.0 78 87 0.90 52.2 4* 18 F 162 66 25.1 86 106 0.81 43.2 5* 16 F 157 43.6 17.7 62.5 74.5 0.84 74.5 6 17 F 152 42.8 18.5 76 89 0.85 52.8 7* 17 F 171 60.2 20.6 78 95 0.82 76.2 8* 16 F 155 59.9 24.9 96 98 0.98 64.6 9 16 M 174 64.8 21.4 94 96 0.98 65.5 10 16 F 159 45.6 18.0 72 86 0.84 42.1 11 16 F 163 60 22.6 - - - 43.6 12 17 F 162 54 20.6 84 87 0.97 48.2 13 16 F 156 45.5 18.7 63 83 0.76 61.1 14 - - - - - - - - - 15 16 F 158 45.7 18.3 73 79 0.92 - 16 18 F 158 52.7 21.1 66 84 0.79 47.2 17 17 M 177 57.6 18.4 69 80 0.86 58.5 18 16 M 169 59.2 20.7 74 93 0.80 41.9 19 17 F 166 65.3 23.7 75 95 0.79 57.2 20 16 M 168 48.4 17.1 68 83 0.82 44.8 21 18 M 194 91.4 24.3 87 100 0.87 59.3 22 16 F 160 55.6 21.7 69 90 0.77 46.4 All details are anonymised data that were available to researchers from patients at the time of surgery. Matching tissue from each patient was collected from three sites for use in experimental analyses. A dash (-) denotes no clinical data available for the indicated variable. A star (*) denotes the subgroup of samples from which RNA sequencing was performed. Additional Declarations No competing interests reported. Supplementary Files Papersupplementaryfigures.pdf SupplementaryTables.pdf Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 21 Feb, 2026 Editor assigned by journal 20 Feb, 2026 Submission checks completed at journal 20 Feb, 2026 First submitted to journal 18 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8911774","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":593762846,"identity":"3f181a45-a9fd-4659-916c-2a5b277bd3f7","order_by":0,"name":"Ellie H. Northall","email":"","orcid":"","institution":"University of Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Ellie","middleName":"H.","lastName":"Northall","suffix":""},{"id":593762847,"identity":"40c684bb-5812-4fbb-9eb5-4bb376a19945","order_by":1,"name":"Thomas A. Nicholson","email":"","orcid":"","institution":"University of Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Thomas","middleName":"A.","lastName":"Nicholson","suffix":""},{"id":593762848,"identity":"8ef59eae-c6ef-4dbb-9ebb-fbf219106905","order_by":2,"name":"Jon Hazeldine","email":"","orcid":"","institution":"University of Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Jon","middleName":"","lastName":"Hazeldine","suffix":""},{"id":593762850,"identity":"f0db08a9-bb50-4098-b81f-1abc44d6bff7","order_by":3,"name":"Liam M. Grover","email":"","orcid":"","institution":"University of Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Liam","middleName":"M.","lastName":"Grover","suffix":""},{"id":593762852,"identity":"866c16c9-00f5-4056-9dea-404acdfda258","order_by":4,"name":"Helen M. McGettrick","email":"","orcid":"","institution":"University of Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Helen","middleName":"M.","lastName":"McGettrick","suffix":""},{"id":593762854,"identity":"0aeeee00-b96b-4afe-9e8d-e373ef01aa09","order_by":5,"name":"Matthew Newton Ede","email":"","orcid":"","institution":"The Royal Orthopaedic Hospital","correspondingAuthor":false,"prefix":"","firstName":"Matthew","middleName":"Newton","lastName":"Ede","suffix":""},{"id":593762859,"identity":"4b44864f-c97f-4f0d-96ab-bf760c0dacac","order_by":6,"name":"Amy J. Naylor","email":"","orcid":"","institution":"University of Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Amy","middleName":"J.","lastName":"Naylor","suffix":""},{"id":593762861,"identity":"6d889028-7003-458a-829f-7f6318aa6c86","order_by":7,"name":"Simon W. Jones","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYLACCRDB3sMG4zMTqYXnDClaIPpyiNQi38BjwGBRcUdOfubbYw9+5jDI8zfwGBvg02JwAKhF4swzY4PbeemGvdsYDGcc4DFOwKuFgXcDg2Tb4cQN0jlmErzbGBg3MPAYH8DvMIiW+vkzz5hJ/t3GYE9QC8MBiJYEhhs8ZtJAWxJBWvA77DD/hwMSZw4bbjiTlyYtu00iecZhtmK83pdvb0t8LFFxWF6+/ewxybfbbGz725s3S+B1GDAODiOpkCAuIhk/EKFoFIyCUTAKRjAAALwQQNd5TjxyAAAAAElFTkSuQmCC","orcid":"","institution":"University of Birmingham","correspondingAuthor":true,"prefix":"","firstName":"Simon","middleName":"W.","lastName":"Jones","suffix":""}],"badges":[],"createdAt":"2026-02-18 18:53:57","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8911774/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8911774/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103179404,"identity":"fcdfbaa3-462b-491b-a4da-6019b1791c6e","added_by":"auto","created_at":"2026-02-22 17:10:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":651414,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRNAseq analysis reveals distinct transcriptomic profiles between non-curve and curve apex site AIS patient spinal osteoblasts. \u003c/strong\u003e\u0026nbsp;(\u003cstrong\u003eA\u003c/strong\u003e) Schematic showing tissue collection sites at the curve apex (convex – grey arrow, concave – black arrow) and non-curve control (white arrow) (made in BioRender). (\u003cstrong\u003eB\u003c/strong\u003e) Principal component analysis of RNAseq data of n = 6 patients showing clustering by spinal site. (\u003cstrong\u003eC\u003c/strong\u003e) Percentages of gene transcript type identified by RNA sequencing in Convex (CV) vs Non-curve (NC) and in Concave (CC) vs Non-curve (NC). (\u003cstrong\u003eD\u003c/strong\u003e) Venn diagram showing the number of upregulated and downregulated differentially expressed genes (DEGs; p ≤ 0.05, FC ≥ ±1.5) between Convex and Non-curve, and between Convex and Non-curve, and those shared between the 2 comparisons. (\u003cstrong\u003eE\u003c/strong\u003e) Top DEGs by p-value and fold-change (FC) for the concave vs non-curve comparison and (\u003cstrong\u003eF\u003c/strong\u003e) for the convex vs non-curve comparison.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8911774/v1/74d832fdddc0e9555f82b698.png"},{"id":103504790,"identity":"f283f4a0-5fa1-4dba-93c7-b78ba9a8103b","added_by":"auto","created_at":"2026-02-26 13:21:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":411911,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePathway analysis highlights dysregulated signalling pathways, biological processes and upstream regulators between AIS spinal osteoblasts at the curve apex compared to non-curve. \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Top canonical pathways of the convex vs non-curve DEGs as determined using IPA, sorted by p-value with the number of genes involved in the pathway shown, with (\u003cstrong\u003eB\u003c/strong\u003e) graphical summary where blue=predicted inhibition and orange=predicted activation. (\u003cstrong\u003eC\u003c/strong\u003e) Top canonical pathways of the concave vs non-curve DEGs, sorted by p-value with the number of genes involved in the pathway shown, with (\u003cstrong\u003eD\u003c/strong\u003e) graphical summary where blue=predicted inhibition and orange=predicted activation. (\u003cstrong\u003eE\u003c/strong\u003e) Top upstream regulators (USRs) of the convex vs non-curve DEGs that are predicted to be either activated or inhibited. Yellow denotes a gene USR, blue demotes a small molecule chemical USR. (\u003cstrong\u003eF\u003c/strong\u003e) Top upstream regulators (USRs) of the concave vs non-curve DEGs that are predicted to be either activated or inhibited. Yellow denotes a gene USR, blue demotes a small molecule chemical USR. (\u003cstrong\u003eG\u003c/strong\u003e) Top predicted relevant biological functions of the convex vs non-curve dataset and (\u003cstrong\u003eH\u003c/strong\u003e) of the concave vs non-curve dataset.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8911774/v1/f29d74b68194164eff32f880.png"},{"id":103179408,"identity":"953527bf-edb3-418c-9bee-fc46c4ccd74c","added_by":"auto","created_at":"2026-02-22 17:10:38","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":266789,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRapamycin is a functional modulator of human osteoblasts. \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Workflow schematic of the approach for the identification and screening of Upstream regulators (USRs), with functional testing in the human fFOB osteoblast cells and then in primary AIS patient osteoblasts. (\u003cstrong\u003eB\u003c/strong\u003e) Summary heat maps (by Z-score) of primary functional screening assays of USR for short term (top) and long term (bottom) functional outputs. (\u003cstrong\u003eC\u003c/strong\u003e) Effects of short-term (24 hr) Rapamycin treatment (1 nM) on Alkaline phosphatase activity and (\u003cstrong\u003eD\u003c/strong\u003e) Osteoprotegerin secretion in hFOB cells, compared to vehicle control (DMSO). (\u003cstrong\u003eE\u003c/strong\u003e) Effect of long-term (21 day) Rapamycin treatment on mineralisation ability in hFOB cells comparted to vehicle control (DMSO), assessed by Alizarin Red. (\u003cstrong\u003eF\u003c/strong\u003e) Gene expression changes following rapamycin treatment of hFOB cells for osteoblast differentiation markers and (\u003cstrong\u003eG\u003c/strong\u003e) mineralisation initiation markers after 1-, 2- and 3-weeks of treatment. (\u003cstrong\u003eH\u003c/strong\u003e) Effects of rapamycin treatment on collagen production in hFOB cells over 3 weeks compared to vehicle control. Statistical significance was determined by two-tailed T-test (B, C, D) or 2-way ANOVA with Bonferroni’s correction (E, F, G), where p\u0026lt;0.05=*, p\u0026lt;0.01=** and p\u0026lt;0.001=***.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8911774/v1/99ee453ec4ff47f146c5d7e9.png"},{"id":103179409,"identity":"0201b628-6334-48ce-b1c5-464b947fe038","added_by":"auto","created_at":"2026-02-22 17:10:39","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":363443,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDysregulated mTOR signalling in curve apex convex osteoblasts correlates with curve severity. \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Overlaid gene expression changes in the mTOR pathway from bulk RNA-seq using IPA (Qiagen); orange = predicted activation, blue = predicted inhibition. (\u003cstrong\u003eB\u003c/strong\u003e) Correlation between the expression of mTOR signalling in convex curve apex cells and curve severity. Gene (n=6) and protein (n=8) expression of mTOR pathway components AKT1/AKT, INSR/IR and MTOR/mTOR were measured in convex cells by qPCR and Western Blot respectively. Curve severity was measured by Cobb angle (°) (95% confidence bands shown). Statistical significance was determined by Pearson’s correlation following linear regression (B) where p\u0026lt;0.05=*, p\u0026lt;0.01=** and p\u0026lt;0.001=***. (\u003cstrong\u003eC\u003c/strong\u003e) Protein expression of mTOR signalling components, including mTOR, between matched non-curve and convex AIS spinal osteoblasts. (\u003cstrong\u003eD\u003c/strong\u003e) Phosphorylated protein expression of mTOR signalling components, including mTOR, between matched non-curve and Convex AIS spinal osteoblasts. Statistical significance was determined by paired T-test (A-F) where p\u0026lt;0.05=*, p\u0026lt;0.01=** and p\u0026lt;0.001=***.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8911774/v1/6043b1668a96f5e3d07808e5.png"},{"id":103505144,"identity":"11f9f2b4-11fc-4bb9-ac36-43f94b9d3cf5","added_by":"auto","created_at":"2026-02-26 13:25:14","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":164658,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRapamycin modulates the function and phenotype of AIS spinal osteoblasts. \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Effects of short-term Rapamycin treatment on alkaline phosphatase activity and osteoprotegerin secretion in matched convex and non-curve osteoblasts. (\u003cstrong\u003eB\u003c/strong\u003e) Effects of long-term rapamycin treatment on mineralisation in matched convex and non-curve osteoblasts. (\u003cstrong\u003eC\u003c/strong\u003e) Effects of rapamycin on total protein and (\u003cstrong\u003eD\u003c/strong\u003e) protein phosphorylation levels in convex osteoblasts, compared to vehicle control DMSO (VC). Statistical significance was determined 2-way ANOVA with Bonferroni’s correction (A-B), or by two-tailed T-test (C-D) where p\u0026lt;0.05=*, p\u0026lt;0.01=** and p\u0026lt;0.001=***.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8911774/v1/7b8145c3fbc5f24c12283b49.png"},{"id":103509530,"identity":"d8cec69e-323f-4ed2-9d24-df8361a1f3a9","added_by":"auto","created_at":"2026-02-26 13:59:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3301978,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8911774/v1/093ef402-1e01-4f2a-9643-11a3f3d77b66.pdf"},{"id":103179407,"identity":"98b93a6a-9333-4755-91e3-4f929b117447","added_by":"auto","created_at":"2026-02-22 17:10:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":331137,"visible":true,"origin":"","legend":"","description":"","filename":"Papersupplementaryfigures.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8911774/v1/6a6522cea9163e00fba77f02.pdf"},{"id":103179405,"identity":"423f44cc-a314-46be-b69e-510356aa1737","added_by":"auto","created_at":"2026-02-22 17:10:38","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":65139,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8911774/v1/1108b5a325e3a4dafe40161a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"mTOR signalling mediates the spinal osteoblast pathotype at the curve apex in adolescent idiopathic scoliosis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAdolescent idiopathic scoliosis (AIS) is one of the most common forms of paediatric spinal deformities [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Defined as abnormal lateral curvature of the spine, it occurs during the adolescent growth spurt, usually between the ages of 10 and 18 and requires a lateral vertebral rotation (Cobb angle) of greater than 10\u0026deg; to meet the clinical definition [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. It is estimated to affect 2\u0026ndash;4% of this population [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] and accounts for approximately 90% of idiopathic scoliosis in adolescents. AIS is a complex, multifaceted condition with a poorly understood pathophysiology; however, growing evidence suggests that intrinsic factors, particularly genetic influences, play a significant underlying role.\u003c/p\u003e \u003cp\u003eIndividuals who have a first degree relative affected by AIS have an increased risk of developing the condition [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], and people who inherit single nucleotide polymorphisms (SNPs) in the POC5 [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and/or TTLL11 [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] genes also have an increased risk. As scoliosis is widely reported to be more prevalent [\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and more severe in females than in males [\u003cspan additionalcitationids=\"CR15 CR16 CR17\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], the role of hormones such has oestrogen has been investigated. To this end, it has been reported that female AIS patients exhibit lower blood oestradiol level than age-matched control females [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], suggesting a potential hormonal contribution to the condition\u0026rsquo;s genetic susceptibility.\u003c/p\u003e \u003cp\u003eIncreasing evidence suggests that abnormalities in spinal bone development and remodelling are a central driver of AIS pathology. Notably, AIS patients exhibit altered bone structural parameters, including lower bone mineral density (BMD) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] and asymmetric vertebral growth compared to age-matched healthy controls - features that may contribute directly to curve initiation and progression. Despite these observations, investigations into the underlying cellular and molecular mechanisms for these findings are limited, largely due to the ethical and logistical access challenges of obtaining spinal tissue samples from paediatric patients. Consequently, much of the current understanding is derived from animal models such as zebrafish or chickens, which although useful, do not fully replicate the human condition in terms of biomechanical environment or developmental timing. Human studies have instead focused on surrogate tissues, such as blood, or cells derived from muscle [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] or cartilage [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], which offer indirect insights into spinal pathology. However, a growing number of studies are now beginning to directly assess spinal osteoblasts, the drivers of bone formation, in AIS patients [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], offering a more targeted approach to understanding the skeletal abnormalities that underlie this complex disorder.\u003c/p\u003e \u003cp\u003eCritically, we recently reported that spinal osteoblasts at the curve apex in AIS patients exhibit intrinsic functional impairment, with greater metabolic and proliferative capacity observed in osteoblasts isolated from the convex site of the curve apex, compared to concave or non-curve osteoblasts from the same patients [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Therefore, we hypothesised that dysregulated signalling in spinal osteoblasts at the curve apex plays a central underlying role in the development of AIS. The aim of this study was therefore to determine the cellular mediators of these dysfunctional curve apex AIS osteoblasts, such that candidate pathways and targets can be identified for subsequent therapeutic modulation.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003e1.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eSpinal AIS osteoblasts at the curve apex exhibit a differential transcriptomic phenotype\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInitially, we investigated whether AIS patient osteoblasts at the curve apex exhibit an intrinsic differential transcriptomic phenotype, compared to osteoblasts from a non-curved site. Osteoblasts were isolated from either side of the curve apex (convex and concave) and osteoblast from non-curve spinal facet tissue (\u003cstrong\u003eFigure 1A\u003c/strong\u003e) of n=6 AIS patients (see \u003cstrong\u003eTable 1\u003c/strong\u003e for clinical details) and subjected to bulk RNA sequencing. Principal component analysis (PCA) of the RNA sequencing data revealed distinct clustering by spinal site (i.e. concave, convex or non-curve), independent of patient (\u003cstrong\u003eFigure 1B\u003c/strong\u003e). This strikingly demonstrates that spinal site was a greater factor in the overall osteoblast gene expression phenotype than patient-specific characteristics including sex or age. Notably, convex and concave osteoblasts formed separate clusters, indicating that each side of the curve apex is associated with a distinct transcriptional identity rather than representing a uniform \u0026ldquo;curved\u0026rdquo; phenotype.\u003c/p\u003e\n\u003cp\u003eTwo datasets of differentially expressed genes (DEGs) (p\u0026lt;0.05; \u0026gt;1.5 fold-change) were generated from this analysis: (1) Comparison of patient-matched convex curve osteoblasts with non-curve osteoblasts; (2) Comparison of patient-matched concave curve osteoblasts with non-curve osteoblasts. Interestingly, both DEG datasets showed similar proportions of gene types including mRNAs as well as non-coding RNAs such as microRNAs, lncRNA and pseudogenes (\u003cstrong\u003eFigure 1C\u003c/strong\u003e), suggesting that broad transcriptional regulation, rather than selective gene class effects, underlies the observed differences. \u0026nbsp;In total, 647 upregulated DEGs were identified in the convex vs non-curve comparison, whilst 768 upregulated DEGs identified between concave vs non-curve, of which 168 genes (representing 26%) were common to both comparisons (\u003cstrong\u003eFigure 1D\u003c/strong\u003e). Correspondingly, 369 DEGs were downregulated in the convex vs non-curve dataset, whilst 535 DEGs were downregulated between concave vs non-curve, of which 136 DEGS (representing 37%) were common to both comparisons. This partial overlap indicates the presence of both shared curve apex\u0026ndash;associated transcriptional changes and region-specific molecular signatures unique to the convex or concave side.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the concave vs non-curve comparison, the most significant DEG by p-value was the transcription factor kruppel-like factor 6 (KLF6) (p-value 0.00000407, q-value 0.23707534) followed by transcription factor JUNB (p-value 0.00000791, q-value 0.23707534), while the DEG with the largest fold change was long intergenic non-protein coding RNA 1004 (LINC01004) (FC +16.0985641) (\u003cstrong\u003eFigure 1E\u003c/strong\u003e). In the convex vs non-curve comparison, the most significant DEG by p-value was NOP14 Antisense RNA 1 (NOP14-AS1) (p-value 0.000000136, q-value 0.00825825) followed by the transcription factor hairy and enhancer of split-1 (HES1) (p-value 0.00000156, q-value 0.04734841), while the DEG with the largest fold change was long intergenic non-protein coding RNA 472 (LINC00472) (+16.77462044 FC) (\u003cstrong\u003eFigure 1F\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eTogether, these data demonstrate that osteoblasts at the AIS curve apex possess an intrinsic, spatially defined transcriptomic phenotype characterised by both shared and region-specific gene expression changes. To determine the biological significance of these transcriptional differences, we then interrogated dysregulated signalling pathways and upstream regulatory mechanisms associated with each curve region.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2. Dysregulated canonical signalling pathways in curve apex osteoblasts reveals candidate upstream regulators\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNext, we used ingenuity pathway analysis (IPA, Qiagen, UK) software to identify the dysregulated canonical signalling pathways related to each of the two DEG datasets i.e., convex curve vs non-curve, and concave curve vs non-curve. The most significant pathway identified for each comparison was different; the convex vs non-curve comparison revelated eukaryotic initiation factor 2 (EIF2) signalling as the most dysregulated pathway (-log(p-value) 11.7), (\u003cstrong\u003eFigure 2A\u003c/strong\u003e), with the network summary (\u003cstrong\u003eFigure 2B\u003c/strong\u003e) \u0026nbsp;highlighting \u0026nbsp;dysregulated cell division and proliferation including activation of DNA promoters, transcription of RNA and entry into cell cycle phases. In contrast, the concave vs non-curve comparison revealed integrin linked kinase (ILK) signalling as the most dysregulated pathway (-log(p-value) 7), (\u003cstrong\u003eFigure 2C\u003c/strong\u003e), with the network summary (\u003cstrong\u003eFigure 2D\u003c/strong\u003e) predominantly highlighting processes of bone and osteoblast differentiation, and fibrogenesis. These findings suggest that convex and concave osteoblasts may be influenced by distinct biological pressures, potentially reflecting differences in mechanical loading or microenvironmental cues across the curve apex. Notably, pathway analysis revealed that both comparisons (i.e. concave vs non-curve; convex vs non-curve) shared several dysregulated pathways, namely, pro-inflammatory cytokine signalling pathways including IL-6, IL-8 and IL-17A. This convergence suggests a common inflammatory component within the curve apex that may act alongside region-specific signalling changes in AIS pathophysiology.\u003c/p\u003e\n\u003cp\u003eTo further interrogate potential drivers of these transcriptional changes, we performed upstream regulator analysis to identify genes and drugs whose predicted activity states could explain the observed DEG patterns. Upstream regulator analysis of the convex vs non-curve DEGs predicted the dimer PDGF-BB (composed of two Platelet-derived growth factor subunit B) to be the most inhibited, with the growth factors EGF and HGF and transcriptional regulators (CREB1, RELA, LARP1) also predicted to be significant inhibited upstream regulators (\u003cstrong\u003eFigure 2E\u003c/strong\u003e). Of the predicted activated upstream regulators, the PI3K inhibitor LY294002 was predicted to be the most activated, with other chemical inhibitors (U0126, PD98059) and transcription regulators (MLXIPL, MYCN, ZFP36) also highlighted as significant activators (\u003cstrong\u003eFigure 2E\u003c/strong\u003e). In contrast, upstream regulator analysis of the concave vs non-curve comparison (\u003cstrong\u003eFigure 2F\u003c/strong\u003e), revealed TGFB1 as the most highly inhibited regulator, with the TGF-\u0026beta; family as a whole, and the transcription regulator SMAD3 also predicted to be significant inhibited regulators. Of the predicted activated upstream regulators identified, the JNK inhibitor SP600125 was the most highly activated, with LY294002 again predicted along with microRNAs (miR-30c-5p, miR-338-3p, miR-29b-3p) to be significant activated upstream regulators (\u003cstrong\u003eFigure 2F\u003c/strong\u003e). Finally, predicted biological functions relevant to bone were filtered from the convex vs non-curve comparison, with most predicted to be downregulated by Z-Score, with the most significant by p-value being growth of connective tissue (\u003cstrong\u003eFigure 2G\u003c/strong\u003e). For the concave vs non-curve comparison, most functions were again predicted to be downregulated with differentiation of connective tissue cells being the most significant by p-value (\u003cstrong\u003eFigure 2H\u003c/strong\u003e). These results highlight region-specific regulatory and upstream mechanisms that are distinct to each curve site. These results indicate that distinct upstream regulatory networks operate at each side of the curve apex, and with the identification of multiple chemical inhibitors as upstream regulators, prompted us to functionally test whether pharmacological modulation could alter osteoblast behaviour.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e3. The mTOR pathway inhibitor rapamycin alters osteogenic functional activity in a human osteoblast cell line\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn order to identify and test candidate drugs that could modulate the phenotype of AIS osteoblasts at the curve apex, we filtered the upstream regulators identified from pathway analysis to include only commercially available small molecule inhibitors/activators. This provided a list of 12 candidate drugs (\u003cstrong\u003eSupplementary\u003c/strong\u003e \u003cstrong\u003eTable S2\u003c/strong\u003e), which were screened to assess acute (24 h) and chronic (21 day) effects on multiple parameters of osteoblast function (including mineralisation, alkaline phosphatase activity (ALP), osteoprotegerin (OPG) secretion and gene expression of modulators of osteoblast function) using the human foetal osteoblast cell line hFOb 1.19 (\u003cstrong\u003eFigure 3A\u003c/strong\u003e). For all screen parameters, 30,000 cells were seeded per well, then cultured in osteogenic media for 3 days before treatment given, also in osteogenic media. Across these multiple parameters of osteoblast function, the mTOR inhibitor rapamycin was found to elicit the most pronounced and consistent effects, as summarised by the heatmap (\u003cstrong\u003eFigure 3B; Supplementary Figure 1-5\u003c/strong\u003e). Acute (24hr) treatment with rapamycin (1 nM) significantly reduced both ALP enzymatic activity (\u003cstrong\u003eFigure 3C\u003c/strong\u003e) and OPG secretion (\u003cstrong\u003eFigure 3D\u003c/strong\u003e) compared to vehicle control. Furthermore, chronic treatment with rapamycin showed a significant reduction in the ability of the osteoblasts to form and deposit mineral in their matrix, assessed by alizarin red quantification (\u003cstrong\u003eFigure 3E\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo investigate whether these functional changes are a result of rapamycin differentially affecting key genes associated with osteoblast differentiation and maturation, cells were dosed (1 nM) every three days for 21 days and RNA extracted after 7-, 14- and 21-day timepoints. For osteogenic markers (\u003cstrong\u003eFigure 3F\u003c/strong\u003e), 7 days of rapamycin treatment resulted in no significant effect on \u003cem\u003eALPL\u003c/em\u003e (tissue non-specific alkaline phosphatase) expression, a significant increase in \u003cem\u003eRUNX2\u003c/em\u003e (runt-related transcription factor 2) expression, which was also increased at 21 days and a significant increase in \u003cem\u003eCOL1A1\u003c/em\u003e (alpha-1 type I collagen) expression at 14 and 21 days. \u003cem\u003eSP7\u003c/em\u003e (osterix) expression was highly variable, and statistically significant differences were not detected between rapamycin treatment and vehicle control at any timepoint. Notably, by day 21, \u003cem\u003eSP7\u003c/em\u003e expression was undetectable in either rapamycin treated or control cells.\u003c/p\u003e\n\u003cp\u003eFor markers associated with mineralisation initiation (\u003cstrong\u003eFigure 3G\u003c/strong\u003e), \u003cem\u003eBMP2\u003c/em\u003e (bone morphogenetic protein 2) was \u0026nbsp; significantly higher at 14 days of rapamycin treatment compared to vehicle control, whereas \u003cem\u003eSPP1\u003c/em\u003e (osteopontin) showed no significant differences between rapamycin or control cells at any time point, and expression was markedly reduced from day 7 onwards in both control and rapamycin treated cells. Secreted type-1 collagen (COL1A1), also a key functional indicator of osteoblast activity, was also significantly increased at week three with rapamycin treatment (\u003cstrong\u003eFigure 3H\u003c/strong\u003e) compared to vehicle control. These results collectively suggest that rapamycin is capable of modulating both the function and differentiation of osteoblasts, prompting further investigation of mTOR signalling in primary AIS osteoblasts.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e4. mTOR signalling dysregulation in curve apex osteoblasts and its association with curve severity\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGiven our finding that rapamycin elicits functional responses in osteoblasts, we next mapped the transcriptomic dataset from the convex v non-curve comparison onto the mTOR signalling pathway to interrogate which pathway components were dysregulated (\u003cstrong\u003eFigure 4A\u003c/strong\u003e). Much of the pathway was predicted to be activated, including both mTOR complexes (mTORC1 and 2), although translation subunits were predicted to be inhibited (\u003cstrong\u003eFigure 4A\u003c/strong\u003e). Bolstering the connection between dysregulated mTOR signalling in osteoblasts at the curve apex and AIS pathology, we also found that mTOR pathway components correlated significantly with curve severity at the convex site (\u003cstrong\u003eFigure 4B\u003c/strong\u003e). AKT1 gene expression negatively correlated with curve severity, whilst IR protein expression, and mTOR gene and protein expression positively correlated with curve severity\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFinally, we profiled mTOR pathway protein (\u003cstrong\u003eFigure 4C\u003c/strong\u003e) and phosphorylation (\u003cstrong\u003eFigure 4D\u003c/strong\u003e) levels, both upstream and downstream of mTOR itself, in patient matched convex and non-curve osteoblasts. For markers upstream of mTOR, we found significant decreases in insulin receptor levels (IGF1R and IR) in osteoblasts isolated from convex regions compared to patient-matched non-curve cells, as well as a significant increase in PTEN expression. mTOR itself was found to be expressed significantly higher in the convex cells, with no difference in downstream pathway component expression. Interestingly, no upstream markers of mTOR, nor mTOR itself, were found to be significantly different at the phosphorylation level between convex and non-curve cells. For markers downstream of mTOR, RPS6 had significantly lower phosphorylation levels in the convex cells. Together, these findings suggest that osteoblasts at the curve apex show a dysregulated mTOR signalling state characterised by altered signal integration and reduced translational output rather than canonical mTOR activation.\u003cbr\u003e\u0026nbsp;\u003cstrong\u003e\u003cem\u003e5. The mTOR inhibitor rapamycin modulates the function and phenotype of AIS spinal osteoblasts\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNext, the ability of rapamycin to modulate the phenotype of primary osteoblasts from the curve apex (convex) and from outside the curve (non-curve) in AIS patients was assessed.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eWe examined the functional effect of rapamycin treatment on the cells from the different spinal sites. Similar to that observed using the hFOb cell line, short term treatment of rapamycin (1 nM) significantly reduced ALP activity in primary AIS patient osteoblasts compared to vehicle control (\u003cstrong\u003eFigure 5A\u003c/strong\u003e). Notably, the greatest effect was observed in convex curve osteoblasts (average 27% reduction) compared to an average 19% reduction in non-curve cells. OPG secretion was also reduced in convex cells with treatment (average 21.5% reduction) but had the greatest effect in non-curve cells (average 29% reduction). Mineralisation of both convex and non-curve cells was reduced at similar rate after chronic treatment (\u003cstrong\u003eFigure 5B\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eNext, we profiled the effect of rapamycin on the expression and their phosphorylation status of other mediators within the mTOR pathway on convex osteoblasts. Rapamycin significantly increased IGF1R, PTEN and p70S6K protein expression in convex cells (\u003cstrong\u003eFigure 5C\u003c/strong\u003e). Conversely, rapamycin significantly reduced expression of mTOR itself. Additionally, rapamycin increased phosphorylation of TSC2, whilst decreasing phosphorylation of p70S6K (\u003cstrong\u003eFigure 5D\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eDysregulated bone remodelling is a driving factor in numerous musculoskeletal diseases across the lifespan. Here, we have demonstrated for the first time that the mTOR signalling pathway is altered in AIS osteoblasts at the curve apex and provide evidence that pharmacological inhibition of mTOR signalling may, in part, reverse this pathotype. Importantly, our data further demonstrate that these alterations are highly spatially dependent, with osteoblasts from convex and concave regions of the curve apex exhibiting distinct molecular and functional phenotypes compared to non-curved spinal sites.\u003c/p\u003e \u003cp\u003ePatient-matched convex and concave spinal tissue in AIS are known to display different tissue parameters including BMD and trabecular thickness [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], which supports the concept that different intrinsic pathological drivers are responsible for mediating the osteoblast pathotype at each side of the curve apex. Pathway analysis of differentially expressed gene datasets of spinal osteoblast cells derived from the apex of the curve revealed distinct and shared dysregulated biological pathways between curved (concave and convex) and osteoblasts from non-curved sites. Consistent with this, principal component analysis of osteoblast transcriptomes revealed clustering by spinal site rather than by patient-specific variables such as age or sex, indicating that local microenvironmental cues dominate osteoblast identity in AIS. Pathway analysis of differentially expressed gene datasets of spinal osteoblast cells derived from the apex of the curve revealed distinct and shared dysregulated biological pathways between curved (concave and convex) and osteoblasts from non-curved sites.\u003c/p\u003e \u003cp\u003eIn the convex vs non-curve comparison, EIF2 signalling was the most dysregulated, with enriched pathways related to cell proliferation and division, and PDGF-BB identified as the most inhibited upstream regulator. In contrast, the concave vs non-curve comparison showed ILK signalling as the most dysregulated, with pathways associated with bone and osteoblast differentiation, and TGFB1 as the most inhibited upstream regulator. These findings suggest that convex osteoblasts may exist in a state of altered translational control and cellular stress, whereas concave osteoblasts display changes more closely aligned with matrix interaction and differentiation processes. Despite these differences, both comparisons shared dysregulation of key pro-inflammatory cytokine signalling pathways, including IL-6, IL-8, and IL-17A, and featured common upstream regulators such as the PI3K inhibitor LY294002, potentially indicating increased inflammatory responses in spinal tissue at either side of the curve apex. This convergence on inflammatory signalling supports emerging evidence that low-grade inflammation contributes to abnormal bone remodelling in AIS and may act synergistically with mechanical and metabolic stressors.\u003c/p\u003e \u003cp\u003eScreening a panel of identified pharmacological upstream regulators as candidate drugs that could mediate the phenotype of osteoblasts at the curve apex revealed that rapamycin, an mTOR inhibitor, the most effective candidate. The mammalian/mechanistic target of rapamycin (mTOR) is well known as a central regulator of cell growth and metabolism. mTOR is known for roles in bone remodelling [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] and mTORC1 specifically was shown to facilitate bone healing in a mouse model [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The mTOR pathway has also previously been implicated in scoliosis, albeit in animal models, including rat [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], and zebrafish [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] systems, underscoring its relevance to spinal development and deformity.\u003c/p\u003e \u003cp\u003emTOR exists as two complexes: mTORC1 and mTORC2. mTORC1 activation is required for preosteoblast proliferation, but overactivation can impair differentiation and maturation, thought to be through Notch pathway activation [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. However, when mTORC1 is disrupted, there is decreased matrix synthesis and mineralization, suggesting that it can promote the transition to mature osteoblasts [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Interestingly, inhibition of mTOR was found to supress osteogenic gene expression whilst under strain [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Rapamycin selectively inhibits mTORC1, which is responsible for promoting protein synthesis, cell growth and metabolism. These findings collectively highlight the highly context- and stage-dependent role of mTOR signalling in osteoblast biology.\u003c/p\u003e \u003cp\u003eRapamycin has shown promise for treating several bone diseases, including those involving aging or inflammation such as osteoporosis [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] and osteoarthritis [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], and those involving abnormal bone remodelling: heterotopic ossification [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], osteolytic disease [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. However, the potential of rapamycin as a therapeutic has been evaluated in predominantly older populations. Preclinical studies assessing its skeletal effects have produced mixed results, with reports of reduced bone density following prolonged treatment [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], contrasted by minimal effects on bone microarchitecture or strength with short term, low dose treatment [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn our study we found that rapamycin supressed functional human osteoblast markers (ALP, OPG) and mineralization capacity in both a human osteoblast cell line and in AIS patient primary spinal osteoblasts from the curve apex. Furthermore, Rapamycin, increased the expression of key osteogenic genes \u003cem\u003eRUNX2\u003c/em\u003e, \u003cem\u003eCOL1A1\u003c/em\u003e, as well as increased collagen production. The continued higher expression of \u003cem\u003eRUNX2\u003c/em\u003e, typically considered an early osteoblast marker [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], suggests that rapamycin may have not only anti-proliferative effects but may also disrupt osteoblast differentiation, consistent with a block in late-stage maturation. Notably, the persistence of \u003cem\u003eBGLAP\u003c/em\u003e expression and the absence of detectable \u003cem\u003eSP7\u003c/em\u003e expression at later timepoints suggest that mTOR inhibition may uncouple early differentiation from terminal maturation rather than fully abrogating osteogenesis. The downregulation of \u003cem\u003eSPP1\u003c/em\u003e at later timepoints may reflect the loss of \u003cem\u003eSP7\u003c/em\u003e, which along with \u003cem\u003eRUNX2\u003c/em\u003e, is required for its expression [\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurther evidence for the role of dysregulated mTOR signalling in AIS pathogenesis was garnered upon finding that the expression of several mediators of mTOR signalling were not only differentially expressed in curve apex spinal osteoblasts but that their expression correlated with curve severity. However, of note, although mTOR expression was increased in convex curve apex osteoblasts and the pathway appears broadly activated, translation-related outputs (e.g., RPS6 phosphorylation) were reduced, suggesting a dysregulated or uncoupled mTOR response. Specifically, upstream mTOR signalling was dampened, evidenced by reduced insulin receptor expression and increased PTEN, while downstream translational activity was suppressed despite elevated mTOR levels. This decoupling suggests that altered mTOR signalling in AIS osteoblasts is not driven by canonical phosphorylation-based activation but may instead reflect impaired signal integration and translational control. The reduced expression of IGF1R and IR in convex cells may reflect crosstalk with other spinal tissues or systemic metabolic influences and may contribute to altered autophagy regulation rather than increased protein synthesis. This interpretation is supported by the identification of EIF2 signalling as the most dysregulated pathway in the convex vs non-curve comparison, a pathway closely linked to cellular stress responses and the unfolded protein response (UPR). Together, these features may underpin both the altered functional phenotype of convex osteoblasts and their association with curve severity in AIS.\u003c/p\u003e \u003cp\u003eThere are several limitations to this study. First, the relatively small patient cohort reflects the challenges of obtaining spinal tissue during corrective surgery in adolescents. As a result, sex-specific analyses were not feasible, despite the known influence of sex hormones on bone metabolism and insulin/mTOR signalling [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Second, while we identified strong associations between osteoblast phenotypes, mTOR pathway components and curve severity, causality cannot be inferred. Longitudinal sampling of spinal tissue is not ethically feasible, highlighting the need for future studies to identify circulating biomarkers reflective of curve apex osteoblast phenotypes. Such biomarkers could enable longitudinal monitoring of disease progression and treatment response. Additionally, limited tissue availability constrained architectural and mechanistic analyses, and in vitro studies were inherently limited by the proliferative capacity of primary osteoblasts.\u003c/p\u003e \u003cp\u003eIn conclusion, we demonstrate that AIS is associated with intrinsic, spatially defined osteoblast dysfunction at the curve apex, characterised by dysregulated mTOR signalling. Rapamycin partially modulated this phenotype, revealing mTOR as a key mechanistic node linking inflammatory, metabolic and stress-related pathways in AIS. While systemic mTOR inhibition is unlikely to be clinically viable in adolescents, our findings provide a strong rationale for exploring targeted modulation of mTOR-related pathways as a strategy to correct asymmetric bone remodelling in AIS and potentially other disorders of abnormal skeletal growth.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003e1. Patient recruitment and collection of spinal tissues\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFacet spinal tissue was collected perioperatively from AIS patients undergoing surgery at the Royal Orthopaedic Hospital, Birmingham, UK, with prior informed patient (and/or parent/carer) consent and research ethics committee approval (19/WM/0083). The study was conducted in compliance with the Declaration of Helsinki; clinical data are summarised in \u003cstrong\u003eTable 1\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2. Isolation of spinal osteoblasts and cell culture\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFacet bone chips were washed three times in Dulbecco\u0026rsquo;s Modified Eagles Media (DMEM) (Cat: 41965062; Gibco) containing 100 U/mL penicillin streptomycin (Cat: 15140122; Gibco) and cultured in differentiation media (DMEM, 10% FBS, 100 U/mL penicillin streptomycin, 1% non-essential amino acids (NEAA) (Cat: 11140035; Gibco), 2 mM \u0026beta;-glycerophosphate (Cat: G9422; Sigma-Aldrich), 50 \u0026micro;g/mL L-Ascorbic acid (Cat: A5960; Sigma-Aldrich), 10 nM Dexamethasone (Cat: D4902; Sigma-Aldrich)). Media was changed every three days and bone chips removed upon the appearance of adhered osteoblasts. Primary cells were then used between passages 1 and 3.\u003c/p\u003e\n\u003cp\u003ehFOb 1.19 cells (CRL-3602; ATCC) were cultured in either basal media, composed of DMEM/F-12, no phenol red (Cat:11580546; Gibco) supplemented with 10% FBS and 0.3 mg/mL G418 (Cat: 4727878001; Sigma-Aldrich) or osteogenic media, composed of basal media supplemented with 10\u003csup\u003e-8\u003c/sup\u003e M menadione and 100 \u0026micro;g/mL L-Ascorbic acid (all from Sigma-Aldrich). Unless stated otherwise, cells were seeded then cultured in osteogenic media for 3 days before treatment or assay. hFOb cells were used between passages 10 and 14.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e3. Transcriptomic analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRNA was extracted using a RNeasy Mini Kit (Cat: 74104; Qiagen) according to manufacturer\u0026rsquo;s instructions. Cells were collected by addition of RLT buffer supplemented with \u0026beta;-mercaptoethanol and incubated on ice for 20 minutes. RNA was quantified using a NanoDrop One (Thermo Scientific).\u003c/p\u003e\n\u003cp\u003eFor RNA sequencing, RNA integrity (RIN) was evaluated in P1 primary osteoblasts by bioanalyzer (Agilent) and samples with a RIN \u0026gt;7 were deemed acceptable. Sequencing was performed by Birmingham Genomics using QuantSeq 3\u0026rsquo; mRNA-Seq Library Prep Kit FWD for Illumina (Lexogen). Data processing was performed in Qlucore, (Lund, Sweden)\u0026nbsp;and pathway analyses were performed using Ingenuity Pathway Analysis (IPA) (V21.0; Qiagen). Differentially expressed genes (fold change of \u0026plusmn; \u0026gt;1.5, p \u0026lt; 0.05) were analysed using the core functional analysis feature to identify significant canonical pathways and cellular processes for each comparison (concave/non-curve, convex/non-curve).\u003c/p\u003e\n\u003cp\u003eFor selective gene expression analysis, relative mRNA expression was determined by Quantitative Real-Time Polymerase Chain Reaction (RT-qPCR) in hFOb cells. This was performed using the iTaq\u0026trade; Universal SYBR\u0026reg; Green One-Step Kit (Cat:\u0026nbsp;1725151; BIO-RAD), 5 ng total RNA and primers (\u003cstrong\u003eSupplementary Table S1\u003c/strong\u003e) (Merck) on a CFX384 C1000 Touch Thermal Cycler (BIO-RAD). After normalisation to housekeeping gene 18S, data are presented as relative expression unless stated otherwise.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e4. Alkaline phosphatase activity assay\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAlkaline phosphatase activity was assessed at 24 hours post treatment. Cells were lysed by addition of RIPA buffer (1X) (Cat: 20-188; Millipore) supplemented with protease and phosphatase inhibitors (Cat: 4693132001, 4906845001; Roche) and placed on ice for 20 minutes with agitation. Cells were harvested using a cell scraper, passed through a 21-gauge needle, and then centrifuged at 20,000 x g for 15 minutes at 4\u0026deg;C. Total protein concentration was determined using BCA Assay (Cat: 23225; Thermo Scientific). Lysates were then added to room temperature alkaline phosphatase yellow (pNPP) liquid substrate (Cat: P7998, Sigma-Aldrich) at a 1:4 ratio in a 96 well plate. The plate was protected from light and incubated at 37\u0026deg;C on a shaker for 45 minutes. The plate was then quantified using a synergy HT plate reader at 405 nm absorbance (with 540 nm as a wavelength control). Data is presented as fold change to vehicle control, after normalisation to total protein unless stated otherwise.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e5. Alizarin red staining\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAlizarin red staining and quantification was performed using an ARed-Q kit (Cat: 8678; Caltag+Medsystems) according to manufacturer\u0026rsquo;s protocol. Rapamycin (1 nM, Cat: r0161 ; LKT Laboratories) treatment or vehicle control was dosed every 3 days and the cells left to mineralise for 3-4 weeks. Cells were then fixed in 4% paraformaldehyde (PFA) prior to staining with 40 mM Alizarin red solution (ARS) per well. Dye was then extracted using 10% acetic acid, incubated for 30 min at RT. Cells were then transferred to a 1.5 mL Eppendorf tube and vortexed for 30 seconds before boiling at 85\u0026deg;C for 10 min. Tubes were then placed on ice before centrifugation at 20,000 x g for 15 min. 10% ammonium hydroxide was then added to 500 \u0026mu;L of supernatant to neutralise the acid. Standards were prepared according to manufacturer\u0026rsquo;s instructions and both standards and samples were loaded onto a 96-well opaque-walled transparent bottomed plate and read at 405 nm using a Synergy HT plate reader (Biotek). Data are presented in mM after standard curve quantification.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e6. Luminex and ELISAs\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003emTOR pathway signalling was assessed using the Total Akt/mTOR 11-plex (Cat: 48-612MAG; Merck-Millipore) and Phosphoprotein kits (Cat: 48-611MAG; Merck-Millipore) according to manufacturer\u0026rsquo;s instructions. In brief, 1 mg total protein for each sample was loaded in triplicate and the samples incubated overnight at 4\u0026deg;C in the dark with agitation. The next day, samples were analysed on a Luminex\u0026reg; 200\u0026trade; system running settings recommended by the manufacturer. Total protein is presented as median fluorescence intensity (MFI), and phosphoprotein results were normalised to the respective total protein.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor the quantification of OPG (human osteoprotegerin/TNFRSF11B) and COL1A1 (human pro-collagen 1 \u0026alpha;1), ELISAs (Cat: DY805 and DY6220-05; R\u0026amp;D Systems) were performed on cell supernatants according to manufacturer\u0026rsquo;s instructions. Data was analysed using a 4-parameter logistic curve and plotted as concentrations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e7. Statistical analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll statistical analysis was performed in Graphpad Prism v10.5.0. All data are mean \u0026plusmn; standard error of mean (SEM) unless stated otherwise. Normality tests on all data were performed first using both Shapiro-Wilk and Kolmogorov-Smirnov tests, with Shapiro-Wilk being used solely on datasets with too small an n for Kolmogorov-Smirnov. Significance levels were set at P\u0026lt;0.05, with individual figure legends indicating which specific statistical test were used.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eS.W.J and M.NE conceived the idea. M.NE acquired clinical data and patient samples. E.H.N, T.A.N and J.H developed the methods, carried out the experiments and contributed to data interpretation and analysis. E.H.N drafted the manuscript. H.M.M, L.G, A.J.N and S.W.J supervised the project. All authors reviewed and approved the final manuscript. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunders statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eE.H.N was funded by the University of Birmingham. S.W.J received grants from UKRI Medical Research council (reference MR/W026961/1) and Arthritis UK (reference 21812).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge all study participants, research staff at the Royal Orthopaedic Hospital NHS Foundation Trust for obtaining consents and screening. The authors would like to acknowledge the Birmingham Genomics facility at the University of Birmingham for support of bulk RNA sequencing experiments. This study has been delivered through the National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre (BRC).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBulk RNA-sequencing data will be made available.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKonieczny, M.R., H. Senyurt, and R. 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Long, \u003cem\u003emTORC1 Signaling Promotes Osteoblast Differentiation from Preosteoblasts.\u003c/em\u003e PLoS One, 2015. \u003cstrong\u003e10\u003c/strong\u003e(6): p. e0130627.\u003c/li\u003e\n\u003cli\u003eWang, D., et al., \u003cem\u003eThe interactions between mTOR and NF-kappaB: A novel mechanism mediating mechanical stretch-stimulated osteoblast differentiation.\u003c/em\u003e J Cell Physiol, 2020.\u003c/li\u003e\n\u003cli\u003eLuo, D., et al., \u003cem\u003eRapamycin reduces severity of senile osteoporosis by activating osteocyte autophagy.\u003c/em\u003e Osteoporos Int, 2016. \u003cstrong\u003e27\u003c/strong\u003e(3): p. 1093-1101.\u003c/li\u003e\n\u003cli\u003eDhanabalan, K.M., et al., \u003cem\u003eIntra-articular injection of rapamycin microparticles prevent senescence and effectively treat osteoarthritis.\u003c/em\u003e Bioeng Transl Med, 2023. \u003cstrong\u003e8\u003c/strong\u003e(1): p. e10298.\u003c/li\u003e\n\u003cli\u003eHu, Y. and Z. 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Valverde, and J. Chen, \u003cem\u003eOsterix enhances proliferation and osteogenic potential of bone marrow stromal cells.\u003c/em\u003e Biochem Biophys Res Commun, 2006. \u003cstrong\u003e341\u003c/strong\u003e(4): p. 1257-65.\u003c/li\u003e\n\u003cli\u003eKim, Y.J., et al., \u003cem\u003eThe bone-related Zn finger transcription factor Osterix promotes proliferation of mesenchymal cells.\u003c/em\u003e Gene, 2006. \u003cstrong\u003e366\u003c/strong\u003e(1): p. 145-51.\u003c/li\u003e\n\u003cli\u003eCao, Z., et al., \u003cem\u003eOsterix controls cementoblast differentiation through downregulation of Wnt-signaling via enhancing DKK1 expression.\u003c/em\u003e Int J Biol Sci, 2015. \u003cstrong\u003e11\u003c/strong\u003e(3): p. 335-44.\u003c/li\u003e\n\u003cli\u003eKhosla, S., M.J. Oursler, and D.G. Monroe, \u003cem\u003eEstrogen and the skeleton.\u003c/em\u003e Trends in Endocrinology and Metabolism, 2012. \u003cstrong\u003e23\u003c/strong\u003e(11): p. 576-81.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Demographic information for AIS patient tissue donors used in this study\u003c/strong\u003e.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eID\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.16667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeight (cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeight (kg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.5%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWaist circ. (cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHip circ. (cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWaist : Hip (ratio)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCobb angle (\u0026deg;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.16667%;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e54.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.5%;\"\u003e\n \u003cp\u003e18.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5%;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8333%;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e54.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.16667%;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e71.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.5%;\"\u003e\n \u003cp\u003e28.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5%;\"\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8333%;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e50.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.16667%;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e71.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.5%;\"\u003e\n \u003cp\u003e28.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5%;\"\u003e\n \u003cp\u003e87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8333%;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e52.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.16667%;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.5%;\"\u003e\n \u003cp\u003e25.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5%;\"\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8333%;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e43.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.16667%;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e43.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.5%;\"\u003e\n \u003cp\u003e17.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e62.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5%;\"\u003e\n \u003cp\u003e74.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8333%;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e74.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.16667%;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e42.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.5%;\"\u003e\n \u003cp\u003e18.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5%;\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8333%;\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e52.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.16667%;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e60.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.5%;\"\u003e\n \u003cp\u003e20.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5%;\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8333%;\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e76.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e8*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.16667%;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e59.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.5%;\"\u003e\n \u003cp\u003e24.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5%;\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8333%;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e64.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.16667%;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e64.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.5%;\"\u003e\n \u003cp\u003e21.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5%;\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8333%;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e65.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.16667%;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e45.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.5%;\"\u003e\n \u003cp\u003e18.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5%;\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8333%;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e42.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.16667%;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.5%;\"\u003e\n \u003cp\u003e22.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8333%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e43.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.16667%;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.5%;\"\u003e\n \u003cp\u003e20.6\u003c/p\u003e\n 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style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e45.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.5%;\"\u003e\n \u003cp\u003e18.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5%;\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8333%;\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e61.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e14\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.16667%;\"\u003e\n 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valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.16667%;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e45.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.5%;\"\u003e\n \u003cp\u003e18.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5%;\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8333%;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e16\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.16667%;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e52.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.5%;\"\u003e\n \u003cp\u003e21.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5%;\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8333%;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e47.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e17\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.16667%;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e57.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.5%;\"\u003e\n \u003cp\u003e18.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5%;\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8333%;\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e58.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.16667%;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e59.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.5%;\"\u003e\n \u003cp\u003e20.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5%;\"\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8333%;\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e41.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e19\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.16667%;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e65.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.5%;\"\u003e\n \u003cp\u003e23.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5%;\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8333%;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e57.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e20\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.16667%;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e48.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.5%;\"\u003e\n \u003cp\u003e17.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5%;\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8333%;\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e44.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.16667%;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e91.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.5%;\"\u003e\n \u003cp\u003e24.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8333%;\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e59.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e22\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.16667%;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1667%;\"\u003e\n \u003cp\u003e55.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.5%;\"\u003e\n \u003cp\u003e21.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5%;\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8333%;\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.33333%;\"\u003e\n \u003cp\u003e46.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAll details are anonymised data that were available to researchers from patients at the time of surgery. Matching tissue from each patient was collected from three sites for use in experimental analyses. A dash (-) denotes no clinical data available for the indicated variable. A star (*) denotes the subgroup of samples from which RNA sequencing was performed. \u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Scoliosis, bone, osteoblasts, mTOR, spine, rapamycin","lastPublishedDoi":"10.21203/rs.3.rs-8911774/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8911774/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAdolescent idiopathic scoliosis (AIS) is associated with dysregulated bone remodelling, yet the molecular underpinnings remain unclear. To investigate site-specific osteoblast phenotypes at the spinal curve apex, we performed bulk RNA sequencing on primary matched osteoblasts isolated from the convex, concave, and non-curved regions of AIS patients. Principal component analysis revealed distinct transcriptional clustering by spinal site, independent of patient-specific factors. Differential expression analysis identified region-specific molecular profiles in convex and concave osteoblasts compared to non-curve controls, with the mTOR pathway being highlighted as one of the most dysregulated.\u003c/p\u003e \u003cp\u003eRapamycin, an mTOR inhibitor, reduced Alkaline phosphatase (ALP) activity, Osteoprotegerin (OPG) secretion, and mineralization, while modulating osteogenic gene expression, including sustained upregulation of \u003cem\u003eRUNX2\u003c/em\u003e and \u003cem\u003eCOL1A1\u003c/em\u003e. In AIS patient-derived osteoblasts, rapamycin elicited pronounced inhibition of mTOR signalling and osteogenic activity in convex cells compared to control. Convex osteoblasts also showed elevated mTOR expression but reduced downstream translation-related signalling, suggesting dysregulated or uncoupled mTOR activity. Notably, mTOR expression level correlated with curve severity, reinforcing the link between mTOR dysregulation and AIS pathology.\u003c/p\u003e \u003cp\u003eThese findings identify mTOR signalling as a key regulatory pathway in AIS osteoblast dysfunction and highlight rapamycin as a potential, though complex, therapeutic candidate.\u003c/p\u003e","manuscriptTitle":"mTOR signalling mediates the spinal osteoblast pathotype at the curve apex in adolescent idiopathic scoliosis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-22 17:10:30","doi":"10.21203/rs.3.rs-8911774/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-21T09:23:39+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-20T07:42:06+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-20T07:40:16+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-02-18T18:38:01+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"39cd7c2e-b46f-46e8-9636-59c32855c5a5","owner":[],"postedDate":"February 22nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":63184008,"name":"Biological sciences/Cell biology"},{"id":63184009,"name":"Health sciences/Diseases"},{"id":63184010,"name":"Biological sciences/Molecular biology"}],"tags":[],"updatedAt":"2026-05-15T08:53:03+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-22 17:10:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8911774","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8911774","identity":"rs-8911774","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}