Predicting rapid progression in knee osteoarthritis: a novel and interpretable automated machine learning approach, with specific focus on young patients and early disease.

OBJECTIVES: To facilitate the stratification of patients with osteoarthritis (OA) for new treatment development and clinical trial recruitment, we created an automated machine learning (autoML) tool predicting the rapid progression of knee OA over a 2-year period. METHODS: We developed autoML models integrating clinical, biochemical, X-ray and MRI data. Using two data sets within the OA Initiative-the Foundation for the National Institutes of Health OA Biomarker Consortium for training and hold-out validation, and the Pivotal Osteoarthritis Initiative MRI Analyses study for external validation-we employed two distinct definitions of clinical outcomes: Multiclass (categorising OA progression into pain and/or radiographic) and binary. Key predictors of progression were identified through advanced interpretability techniques, and subgroup analyses were conducted by age, sex and ethnicity with a focus on early-stage disease. RESULTS: Although the most reliable models incorporated all available features, simpler models including only clinical variables achieved robust external validation performance, with area under the precision-recall curve (AUC-PRC) 0.727 (95% CI: 0.726 to 0.728) for multiclass predictions; and AUC-PRC 0.764 (95% CI: 0.762 to 0.766) for binary predictions. Multiclass models performed best in patients with early-stage OA (AUC-PRC 0.724-0.806) whereas binary models were more reliable in patients younger than 60 (AUC-PRC 0.617-0.693). Patient-reported outcomes and MRI features emerged as key predictors of progression, though subgroup differences were noted. Finally, we developed web-based applications to visualise our personalised predictions. CONCLUSIONS: Our novel tool's transparency and reliability in predicting rapid knee OA progression distinguish it from conventional 'black-box' methods and are more likely to facilitate its acceptance by clinicians and patients, enabling effective implementation in clinical practice.

Viscosupplementation Is Effective for the Treatment of Osteoarthritis in the Hip: A Systematic Review.

PURPOSE: To assess the efficacy of intra-articular viscosupplementation as a therapeutic intervention for hip osteoarthritis (OA), as well as to assess the duration of efficacy, effect of dose, composition and number of injections of the viscosupplement, and the incidence of adverse effects. METHODS: We performed a systematic review using the literature search from the following databases: Embase, Medline, PubMed, Web of Science, and Scopus. Quality assessment of the included studies was performed using the Modified Newcastle-Ottawa Quality Assessment Scale. Random-effects meta-analysis and mixed-effects subgroup analysis were carried out, but due to the high heterogeneity, low level of evidence, and high risk of bias of the included studies after analyzing the data, weighted means and pooled estimates have not been provided. Instead, we have provided a subjective synthesis of the results. RESULTS: Forty studies were included in the analysis from an initial search of 3,265 studies, with data from a total of 3,350 patients. The level of available evidence was low with an overall high risk of bias. Nearly all studies showed a reduction in mean pain at 1 month, 3 months, and 6 months of follow-up, as well as at the end point, and an improvement in mean patient-reported function was also seen at these time points. However, heterogeneity was extremely high at all time points and remained despite attempts at removing outliers. Subgroup analyses looking at the effects of dose, volume, composition of viscosupplement, and number of injections were carried out, but substantial heterogeneity still remained. There were no lasting adverse effects. CONCLUSIONS: Weak evidence suggests that viscosupplementation improves patient-reported pain and function at end point compared to baseline, regardless of dose, volume, composition, and number of injections. However, due to the high heterogeneity, low level of evidence, and high risk of bias in the current available literature, the strength of our conclusions is limited. LEVEL OF EVIDENCE: Level IV, systematic review of level I to IV studies.

The Effects of Chronological Age on the Chondrogenic Potential of Mesenchymal Stromal Cells: A Systematic Review.

Tissue engineering and cell therapy for regenerative medicine have great potential to treat chronic disorders. In musculoskeletal disorders, mesenchymal stromal cells (MSCs) have been identified as a relevant cell type in cell and regenerative strategies due to their multi-lineage potential, although this is likely to be a result of their trophic and immunomodulatory effects on other cells. This PRISMA systematic review aims to assess whether the age of the patient influences the chondrogenic potential of MSCs in regenerative therapy. We identified a total of 3027 studies after performing a search of four databases, including Cochrane, Web of Science, Medline, and PubMed. After applying inclusion and exclusion criteria, a total of 14 papers were identified that were reviewed, assessed, and reported. Cell surface characterization and proliferation, as well as the osteogenic, adipogenic, and chondrogenic differentiation, were investigated as part of the analysis of these studies. Most included studies suggest a clear link between aged donor MSCs and diminished clonogenic and proliferative potential. Our study reveals a heterogeneous and conflicting range of outcomes concerning the chondrogenic, osteogenic, and adipogenic potential of MSCs in relation to age. Further investigations on the in vitro effects of chronological age on the chondrogenic potential of MSCs should follow the outcomes of this systematic review, shedding more light on this complex relationship.

Linking chondrocyte and synovial transcriptional profile to clinical phenotype in osteoarthritis.

OBJECTIVES: To determine how gene expression profiles in osteoarthritis joint tissues relate to patient phenotypes and whether molecular subtypes can be reproducibly captured by a molecular classification algorithm. METHODS: We analysed RNA sequencing data from cartilage and synovium in 113 osteoarthritis patients, applying unsupervised clustering and Multi-Omics Factor Analysis to characterise transcriptional profiles. We tested the association of the molecularly defined patient subgroups with clinical characteristics from electronic health records. RESULTS: We detected two patient subgroups in low-grade cartilage (showing no/minimal degeneration, cartilage normal/softening only), with differences associated with inflammation, extracellular matrix-related and cell adhesion pathways. The high-inflammation subgroup was associated with female sex (OR 4.12, p=0.0024) and prescription of proton pump inhibitors (OR 4.21, p=0.0040). We identified two independent patient subgroupings in osteoarthritis synovium: one related to inflammation and the other to extracellular matrix and cell adhesion processes. A seven-gene classifier including MMP13, APOD, MMP2, MMP1, CYTL1, IL6 and C15orf48 recapitulated the main axis of molecular heterogeneity in low-grade knee osteoarthritis cartilage (correlation ρ=-0.88, p<10-10) and was reproducible in an independent patient cohort (ρ=-0.85, p<10-10). CONCLUSIONS: These data support the reproducible stratification of osteoarthritis patients by molecular subtype and the exploration of new avenues for tailored treatments.

Dynamic contrast-enhanced MRI of synovitis in knee osteoarthritis: repeatability, discrimination and sensitivity to change in a prospective experimental study.

OBJECTIVES: Evaluate test-retest repeatability, ability to discriminate between osteoarthritic and healthy participants, and sensitivity to change over 6 months, of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) biomarkers in knee OA. METHODS: Fourteen individuals aged 40-60 with mild-moderate knee OA and 6 age-matched healthy volunteers (HV) underwent DCE-MRI at 3 T at baseline, 1 month and 6 months. Voxelwise pharmacokinetic modelling of dynamic data was used to calculate DCE-MRI biomarkers including Ktrans and IAUC60. Median DCE-MRI biomarker values were extracted for each participant at each study visit. Synovial segmentation was performed using both manual and semiautomatic methods with calculation of an additional biomarker, the volume of enhancing pannus (VEP). Test-retest repeatability was assessed using intraclass correlation coefficients (ICC). Smallest detectable differences (SDDs) were calculated from test-retest data. Discrimination between OA and HV was assessed via calculation of between-group standardised mean differences (SMD). Responsiveness was assessed via the number of OA participants with changes greater than the SDD at 6 months. RESULTS: Ktrans demonstrated the best test-retest repeatability (Ktrans/IAUC60/VEP ICCs 0.90/0.84/0.40, SDDs as % of OA mean 33/71/76%), discrimination between OA and HV (SMDs 0.94/0.54/0.50) and responsiveness (5/1/1 out of 12 OA participants with 6-month change > SDD) when compared to IAUC60 and VEP. Biomarkers derived from semiautomatic segmentation outperformed those derived from manual segmentation across all domains. CONCLUSIONS: Ktrans demonstrated the best repeatability, discrimination and sensitivity to change suggesting that it is the optimal DCE-MRI biomarker for use in experimental medicine studies. KEY POINTS: • Dynamic contrast-enhanced MRI (DCE-MRI) provides quantitative measures of synovitis in knee osteoarthritis which may permit early assessment of efficacy in experimental medicine studies. • This prospective observational study compared DCE-MRI biomarkers across domains relevant to experimental medicine: test-retest repeatability, discriminative validity and sensitivity to change. • The DCE-MRI biomarker Ktrans demonstrated the best performance across all three domains, suggesting that it is the optimal biomarker for use in future interventional studies.

Three-Dimensional Surface-Based Analysis of Cartilage MRI Data in Knee Osteoarthritis: Validation and Initial Clinical Application.

BACKGROUND: Traditional quantitative analysis of cartilage with MRI averages measurements (eg, thickness) across regions-of-interest (ROIs) which may reduce responsiveness. PURPOSE: To validate and describe clinical application of a semiautomated surface-based method for analyzing cartilage relaxation times ("composition") and morphology on MRI, 3D cartilage surface mapping (3D-CaSM). STUDY TYPE: Validation study in cadaveric knees and prospective observational (cohort) study in human participants. POPULATION: Four cadaveric knees and 14 participants aged 40-60 with mild-moderate knee osteoarthritis (OA) and 6 age-matched healthy volunteers, imaged at baseline, 1, and 6 months. FIELD STRENGTH/SEQUENCE: 3D spoiled gradient echo, T1 rho/T2 magnetization-prepared 3D fast spin echo for mapping of T1 rho/T2 relaxation times and delayed gadolinium enhanced MRI of cartilage (dGEMRIC) using variable flip angle T1 relaxation time mapping at 3T. ASSESSMENT: 3D-CaSM was validated against high-resolution peripheral quantitative computed tomography (HRpQCT) in cadaveric knees, with comparison to expert manual segmentation. The clinical study assessed test-retest repeatability and sensitivity to change over 6 months for cartilage thickness and relaxation times. STATISTICAL TESTS: Bland-Altman analysis was performed for the validation study and evaluation of test-retest repeatability. Six-month changes were assessed via calculation of the percentage of each cartilage surface affected by areas of significant change (%SC), defined using thresholds based on area and smallest detectable difference (SDD). RESULTS: Bias and precision (0.06 ± 0.25 mm) of 3D-CaSM against reference HRpQCT data were comparable to expert manual segmentation (-0.13 ± 0.26 mm). 3D-CaSM demonstrated significant (>SDD) 6-month changes in cartilage thickness and relaxation times in both OA participants and healthy controls. The parameter demonstrating the greatest 6-month change was T2 relaxation time (OA median %SC [IQR] = 8.8% [5.5 to 12.6]). DATA CONCLUSION: This study demonstrates the construct validity and potential clinical utility of 3D-CaSM, which may offer advantages to conventional ROI-based methods. LEVEL OF EVIDENCE: 2. TECHNICAL EFFICACY STAGE: 2. J. Magn. Reson. Imaging 2020;52:1139-1151.

Evaluation of shared genetic aetiology between osteoarthritis and bone mineral density identifies SMAD3 as a novel osteoarthritis risk locus.

Osteoarthritis (OA) is a common complex disease with high public health burden and no curative therapy. High bone mineral density (BMD) is associated with an increased risk of developing OA, suggesting a shared underlying biology. Here, we performed the first systematic overlap analysis of OA and BMD on a genome wide scale. We used summary statistics from the GEFOS consortium for lumbar spine (n = 31,800) and femoral neck (n = 32,961) BMD, and from the arcOGEN consortium for three OA phenotypes (hip, ncases=3,498; knee, ncases=3,266; hip and/or knee, ncases=7,410; ncontrols=11,009). Performing LD score regression we found a significant genetic correlation between the combined OA phenotype (hip and/or knee) and lumbar spine BMD (rg=0.18, P = 2.23 × 10-2), which may be driven by the presence of spinal osteophytes. We identified 143 variants with evidence for cross-phenotype association which we took forward for replication in independent large-scale OA datasets, and subsequent meta-analysis with arcOGEN for a total sample size of up to 23,425 cases and 236,814 controls. We found robustly replicating evidence for association with OA at rs12901071 (OR 1.08 95% CI 1.05-1.11, Pmeta=3.12 × 10-10), an intronic variant in the SMAD3 gene, which is known to play a role in bone remodeling and cartilage maintenance. We were able to confirm expression of SMAD3 in intact and degraded cartilage of the knee and hip. Our findings provide the first systematic evaluation of pleiotropy between OA and BMD, highlight genes with biological relevance to both traits, and establish a robust new OA genetic risk locus at SMAD3.

Widespread epigenomic, transcriptomic and proteomic differences between hip osteophytic and articular chondrocytes in osteoarthritis.

Objectives: To identify molecular differences between chondrocytes from osteophytic and articular cartilage tissue from OA patients. Methods: We investigated genes and pathways by combining genome-wide DNA methylation, RNA sequencing and quantitative proteomics in isolated primary chondrocytes from the cartilaginous layer of osteophytes and matched areas of low- and high-grade articular cartilage across nine patients with OA undergoing hip replacement surgery. Results: Chondrocytes from osteophytic cartilage showed widespread differences to low-grade articular cartilage chondrocytes. These differences were similar to, but more pronounced than, differences between chondrocytes from osteophytic and high-grade articular cartilage, and more pronounced than differences between high- and low-grade articular cartilage. We identified 56 genes with significant differences between osteophytic chondrocytes and low-grade articular cartilage chondrocytes on all three omics levels. Several of these genes have known roles in OA, including ALDH1A2 and cartilage oligomeric matrix protein, which have functional genetic variants associated with OA from genome-wide association studies. An integrative gene ontology enrichment analysis showed that differences between osteophytic and low-grade articular cartilage chondrocytes are associated with extracellular matrix organization, skeletal system development, platelet aggregation and regulation of ERK1 and ERK2 cascade. Conclusion: We present a first comprehensive view of the molecular landscape of chondrocytes from osteophytic cartilage as compared with articular cartilage chondrocytes from the same joints in OA. We found robust changes at genes relevant to chondrocyte function, providing insight into biological processes involved in osteophyte development and thus OA progression.

Association of subchondral bone texture on magnetic resonance imaging with radiographic knee osteoarthritis progression: data from the Osteoarthritis Initiative Bone Ancillary Study.

OBJECTIVES: To assess whether initial or 12-18-month change in magnetic resonance imaging (MRI) subchondral bone texture is predictive of radiographic knee osteoarthritis (OA) progression over 36 months. METHODS: This was a nested case-control study including 122 knees/122 participants in the Osteoarthritis Initiative (OAI) Bone Ancillary Study, who underwent MRI optimised for subchondral bone assessment at either the 30- or 36-month and 48-month OAI visits. Case knees (n = 61) had radiographic OA progression between the 36- and 72-month OAI visits, defined as ≥ 0.7 mm minimum medial tibiofemoral radiographic joint space (minJSW) loss. Control knees (n = 61) without radiographic OA progression were matched (1:1) to cases for age, sex, body mass index and initial medial minJSW. Texture analysis was performed on the medial femoral and tibial subchondral bone. We assessed the association of texture features with radiographic progression by creating a composite texture score using penalised logistic regression and calculating odds ratios. We evaluated the predictive performance of texture features for predicting radiographic progression using c-statistics. RESULTS: Initial (odds ratio [95% confidence interval] = 2.13 [1.41-3.40]) and 12- 18-month change (3.76 [2.04-7.82]) texture scores were significantly associated with radiographic OA progression. Combinations of texture features were significant predictors of radiographic progression using initial (c-statistic [95% confidence interval] = 0.65 [0.64-0.65], p = 0.003) and 12-18-month change (0.68 [0.68-0.68], p < 0.001) data. CONCLUSIONS: Initial and 12-18-month changes in MRI subchondral bone texture score were significantly associated with radiographic progression at 36 months, with better predictive performance for 12-18-month change in texture. These results suggest that texture analysis may be a useful biomarker of subchondral bone in OA. KEY POINTS: • Subchondral bone MRI texture analysis is a promising knee osteoarthritis imaging biomarker. • In this study, subchondral bone texture was associated with knee osteoarthritis progression. • This demonstrates predictive and concurrent validity of MRI subchondral bone texture analysis. • This method may be useful in clinical trials with interventions targeting bone.

Peripheral mononuclear blood cell apheresis in a preclinical ovine model.

BACKGROUND: Recent research has demonstrated that circulating peripheral blood mononuclear fractions (PBMC) containing haematopoietic stem (HSC)/progenitor cells have the potential to play a crucial role in regenerative medicine strategies. Work in our laboratory has shown that a peripheral blood mononuclear cell fraction (PBMC) enhances cartilage repair in an osteochondral defect model in sheep and has a significant effect on cells in the joint niche. In order to obtain PBMC rich blood containing HSCs for further studies, we have performed, for the first time, apheresis on adult sheep. RESULTS: Subcutaneous granulocyte-colony stimulating factor (G-CSF) was used to mobilise white blood cells and continual flow apheresis was performed on 8 sheep under general anaesthetic. There were no observable side effects, although a marked tendency for blood clotting during the procedure was noted. The administration of G-CSF for 3 days increased the white blood cell (WBC) count in the peripheral blood from to 6.7 ± 2.1 × 106/ml to 16.1 ± 5.0 × 106/ml. Following apheresis, the WBC numbers in the apheretic product increased to 38.5 ± 27.6 × 106/ml, comprised of a significant increase in neutrophils and PBMC (from 5.25 ± 1.8 × 106/ml following G-CSF stimulation to 27.5 5 ± 27.6 × 106/ml). There was a mean of 2.1% CD34 + ve cells and 95.5% CD45 + ve cells in the apheretic product. CONCLUSIONS: This study describes the administration of G-CSF and subsequent apheresis in adult sheep. The technique is safe when performed as described with no observable side effects. The technique permits collection of an increased WBC fraction containing neutrophils and PBMC in adult sheep. This apheretic product contains CD34 + ve cells, representing an HSC/progenitor population for use in in vivo and in vitro experiments.

Novel bioglasses for bone tissue repair and regeneration: Effect of glass design on sintering ability, ion release and biocompatibility.

Eight novel silicate, phosphate and borate glass compositions (coded as NCLx, where x = 1 to 8), containing different oxides (i.e. MgO, MnO2, Al2O3, CaF2, Fe2O3, ZnO, CuO, Cr2O3) were designed and evaluated alongside apatite-wollastonite (used as comparison material), as potential biomaterials for bone tissue repair and regeneration. Glass frits of all the formulations were processed to have particle sizes under 53 µm, with their morphology and dimensions subsequently investigated by scanning electron microscopy (SEM). In order to establish the nature of the raw glass powders, X-ray diffraction (XRD) analysis was also performed. The sintering ability of the novel materials was determined by using hot stage microscopy (HSM). Ionic release potential was assessed by inductively coupled plasma optical emission spectroscopy (ICP-OES). Finally, the cytotoxic effect of the novel glass powders was evaluated for different glass concentrations via a colorimetric assay, on which basis three formulations are considered promising biomaterials.

A variant in MCF2L is associated with osteoarthritis.

Osteoarthritis (OA) is a prevalent, heritable degenerative joint disease with a substantial public health impact. We used a 1000-Genomes-Project-based imputation in a genome-wide association scan for osteoarthritis (3177 OA cases and 4894 controls) to detect a previously unidentified risk locus. We discovered a small disease-associated set of variants on chromosome 13. Through large-scale replication, we establish a robust association with SNPs in MCF2L (rs11842874, combined odds ratio [95% confidence interval] 1.17 [1.11-1.23], p = 2.1 × 10(-8)) across a total of 19,041 OA cases and 24,504 controls of European descent. This risk locus represents the third established signal for OA overall. MCF2L regulates a nerve growth factor (NGF), and treatment with a humanized monoclonal antibody against NGF is associated with reduction in pain and improvement in function for knee OA patients.

A meta-analysis of genome-wide association studies identifies novel variants associated with osteoarthritis of the hip.

OBJECTIVES: Osteoarthritis (OA) is the most common form of arthritis with a clear genetic component. To identify novel loci associated with hip OA we performed a meta-analysis of genome-wide association studies (GWAS) on European subjects. METHODS: We performed a two-stage meta-analysis on more than 78,000 participants. In stage 1, we synthesised data from eight GWAS whereas data from 10 centres were used for 'in silico' or 'de novo' replication. Besides the main analysis, a stratified by sex analysis was performed to detect possible sex-specific signals. Meta-analysis was performed using inverse-variance fixed effects models. A random effects approach was also used. RESULTS: We accumulated 11,277 cases of radiographic and symptomatic hip OA. We prioritised eight single nucleotide polymorphism (SNPs) for follow-up in the discovery stage (4349 OA cases); five from the combined analysis, two male specific and one female specific. One locus, at 20q13, represented by rs6094710 (minor allele frequency (MAF) 4%) near the NCOA3 (nuclear receptor coactivator 3) gene, reached genome-wide significance level with p=7.9×10(-9) and OR=1.28 (95% CI 1.18 to 1.39) in the combined analysis of discovery (p=5.6×10(-8)) and follow-up studies (p=7.3×10(-4)). We showed that this gene is expressed in articular cartilage and its expression was significantly reduced in OA-affected cartilage. Moreover, two loci remained suggestive associated; rs5009270 at 7q31 (MAF 30%, p=9.9×10(-7), OR=1.10) and rs3757837 at 7p13 (MAF 6%, p=2.2×10(-6), OR=1.27 in male specific analysis). CONCLUSIONS: Novel genetic loci for hip OA were found in this meta-analysis of GWAS.

A mixed-methods approach exploring acceptability and feasibility of trials designed to test drugs targeting prevention of post-traumatic osteoarthritis after knee injury.

Aims: To explore key stakeholder views around feasibility and acceptability of trials seeking to prevent post-traumatic osteoarthritis (PTOA) following knee injury, and provide guidance for next steps in PTOA trial design. Methods: Healthcare professionals, clinicians, and/or researchers (HCP/Rs) were surveyed, and the data were presented at a congress workshop. A second and related survey was then developed for people with joint damage caused by knee injury and/or osteoarthritis (PJDs), who were approached by a UK Charity newsletter or Oxford involvement registry. Anonymized data were collected and analyzed in Qualtrics. Results: Survey responses (n = 19 HCP/Rs, 39 PJDs) supported studies testing pharmacological agents preventing PTOA. All HCP/Rs and 30/31 (97%) PJDs supported the development of new treatments that improved or delayed knee symptoms and damage to knee structure. PJDs thought that improving structural knee damage was more important than knee symptoms. Both groups found studies more acceptable as expected future benefit and risk of PTOA increased. All drug delivery routes were acceptable. Workshop participants (around n = 60) reflected survey views. Discussions suggested that stratifying using molecular testing for likely drug response appeared to be more acceptable than using characteristics such as sex, age, and BMI. Conclusion: Our findings supported PTOA drug intervention studies, including situations where there is low risk of disease, no expected benefit of treatment, and frequent treatment administration. PJDs appeared less risk-averse than HCP/Rs. This work reinforces the benefits of consensus and involvement work in the co-creation of PTOA drug trial design. Involvement of key stakeholders, such as PJDs with different risks of OA and regulatory representatives, are critical for trial design success.

Understanding the role of machine learning in predicting progression of osteoarthritis.

Aims: Machine learning (ML), a branch of artificial intelligence that uses algorithms to learn from data and make predictions, offers a pathway towards more personalized and tailored surgical treatments. This approach is particularly relevant to prevalent joint diseases such as osteoarthritis (OA). In contrast to end-stage disease, where joint arthroplasty provides excellent results, early stages of OA currently lack effective therapies to halt or reverse progression. Accurate prediction of OA progression is crucial if timely interventions are to be developed, to enhance patient care and optimize the design of clinical trials. Methods: A systematic review was conducted in accordance with PRISMA guidelines. We searched MEDLINE and Embase on 5 May 2024 for studies utilizing ML to predict OA progression. Titles and abstracts were independently screened, followed by full-text reviews for studies that met the eligibility criteria. Key information was extracted and synthesized for analysis, including types of data (such as clinical, radiological, or biochemical), definitions of OA progression, ML algorithms, validation methods, and outcome measures. Results: Out of 1,160 studies initially identified, 39 were included. Most studies (85%) were published between 2020 and 2024, with 82% using publicly available datasets, primarily the Osteoarthritis Initiative. ML methods were predominantly supervised, with significant variability in the definitions of OA progression: most studies focused on structural changes (59%), while fewer addressed pain progression or both. Deep learning was used in 44% of studies, while automated ML was used in 5%. There was a lack of standardization in evaluation metrics and limited external validation. Interpretability was explored in 54% of studies, primarily using SHapley Additive exPlanations. Conclusion: Our systematic review demonstrates the feasibility of ML models in predicting OA progression, but also uncovers critical limitations that currently restrict their clinical applicability. Future priorities should include diversifying data sources, standardizing outcome measures, enforcing rigorous validation, and integrating more sophisticated algorithms. This paradigm shift from predictive modelling to actionable clinical tools has the potential to transform patient care and disease management in orthopaedic practice.

Time- and cell-specific activation of BMP signaling restrains chondrocyte hypertrophy.

Stem cell therapies for degenerative cartilage disease are limited by an incomplete understanding of hyaline cartilage formation and maintenance. Human bone marrow stromal cells/skeletal stem cells (hBMSCs/SSCs) produce stable hyaline cartilage when attached to hyaluronic acid-coated fibrin microbeads (HyA-FMBs), yet the mechanism remains unclear. In vitro, hBMSC/SSC/HyA-FMB organoids exhibited reduced BMP signaling early in chondrogenic differentiation, followed by restoration of BMP signaling in chondrogenic IGFBP5 + /MGP + cells. Subsequently, human-induced pluripotent stem cell (hiPSC)-derived sclerotome cells were established (BMP inhibition) and then treated with transforming growth factor ß (TGF-ß) -/+ BMP2 and growth differentiation factor 5 (GDF5) (BMP signaling activation). TGF-ß alone elicited a weak chondrogenic response, but TGF-ß/BMP2/GDF5 led to delamination of SOX9 + aggregates (chondrospheroids) with high expression of COL2A1, ACAN, and PRG4 and minimal expression of COL10A1 and ALP in vitro. While transplanted hBMSCs/SSCs/HyA-FMBs did not heal articular cartilage defects in immunocompromised rodents, chondrospheroid-derived cells/HyA-FMBs formed non-hypertrophic cartilage that persisted until at least 5 months in vivo.

No evidence of an association between mitochondrial DNA variants and osteoarthritis in 7393 cases and 5122 controls.

OBJECTIVES: Osteoarthritis (OA) has a complex aetiology with a strong genetic component. Genome-wide association studies implicate several nuclear genes in the aetiology, but a major component of the heritability has yet to be defined at the molecular level. Initial studies implicate maternally inherited variants of mitochondrial DNA (mtDNA) in subgroups of patients with OA based on gender and specific joint involvement, but these findings have not been replicated. METHODS: The authors studied 138 maternally inherited mtDNA variants genotyped in a two cohort genetic association study across a total of 7393 OA cases from the arcOGEN consortium and 5122 controls genotyped in the Wellcome Trust Case Control consortium 2 study. RESULTS: Following data quality control we examined 48 mtDNA variants that were common in cohort 1 and cohort 2, and found no association with OA. None of the phenotypic subgroups previously associated with mtDNA haplogroups were associated in this study. CONCLUSIONS: We were not able to replicate previously published findings in the largest mtDNA association study to date. The evidence linking OA to mtDNA is not compelling at present.

Evaluation of the genetic overlap between osteoarthritis with body mass index and height using genome-wide association scan data.

OBJECTIVES: Obesity as measured by body mass index (BMI) is one of the major risk factors for osteoarthritis. In addition, genetic overlap has been reported between osteoarthritis and normal adult height variation. We investigated whether this relationship is due to a shared genetic aetiology on a genome-wide scale. METHODS: We compared genetic association summary statistics (effect size, p value) for BMI and height from the GIANT consortium genome-wide association study (GWAS) with genetic association summary statistics from the arcOGEN consortium osteoarthritis GWAS. Significance was evaluated by permutation. Replication of osteoarthritis association of the highlighted signals was investigated in an independent dataset. Phenotypic information of height and BMI was accounted for in a separate analysis using osteoarthritis-free controls. RESULTS: We found significant overlap between osteoarthritis and height (p=3.3×10(-5) for signals with p≤0.05) when the GIANT and arcOGEN GWAS were compared. For signals with p≤0.001 we found 17 shared signals between osteoarthritis and height and four between osteoarthritis and BMI. However, only one of the height or BMI signals that had shown evidence of association with osteoarthritis in the arcOGEN GWAS was also associated with osteoarthritis in the independent dataset: rs12149832, within the FTO gene (combined p=2.3×10(-5)). As expected, this signal was attenuated when we adjusted for BMI. CONCLUSIONS: We found a significant excess of shared signals between both osteoarthritis and height and osteoarthritis and BMI, suggestive of a common genetic aetiology. However, only one signal showed association with osteoarthritis when followed up in a new dataset.

Henry's pelvic deltoid: antiquated concept or important consideration for total hip arthroplasty? An anatomical study.

The relevance of Henry's pelvic deltoid and its contribution to hip abductor strength is often not considered in hip arthroplasty. This small cadaveric study (n = 11) aimed to quantify the relative contributions of the pelvic deltoid muscles to abductor strength and to assess how different surgical approaches(anterolateral, direct lateral and posterior) impact on each of these muscle groups. We inspected the path of each approach and measured the cross-sectional area of the hip abductors, from which the contribution of each muscle to abductor moment was derived. We concluded that the posterior approach has the least impact on the pelvic deltoid and overall abductor moment.

MicroRNA profiling of low concentration extracellular vesicle RNA utilizing NanoString nCounter technology.

Extracellular vesicles (EV) and the microRNAs that they contain are increasingly recognised as a rich source of informative biomarkers, reflecting pathological processes and fundamental biological pathways and responses. Their presence in biofluids makes them particularly attractive for biomarker identification. However, a frequent caveat in relation to clinical studies is low abundance of EV RNA content. In this study, we used NanoString nCounter technology to assess the microRNA profiles of n = 64 EV low concentration RNA samples (180-49125 pg), isolated from serum and cell culture media using precipitation reagent or sequential ultracentrifugation. Data was subjected to robust quality control parameters based on three levels of limit of detection stringency, and differential microRNA expression analysis was performed between biological subgroups. We report that RNA concentrations > 100 times lower than the current NanoString recommendations can be successfully profiled using nCounter microRNA assays, demonstrating acceptable output ranges for imaging parameters, binding density, positive/negative controls, ligation controls and normalisation quality control. Furthermore, despite low levels of input RNA, high-level differential expression analysis between biological subgroups identified microRNAs of biological relevance. Our results demonstrate that NanoString nCounter technology offers a sensitive approach for the detection and profiling of low abundance EV-derived microRNA, and may provide a solution for research studies that focus on limited sample material.