Background. Previously, the Coonrad-Morrey elbow system has typically been performed using linked-type total elbow arthroplasty (TEA) implants. However, this implant have been reported to be associated with some problems, such as wearing down, loosening, the complexity of the necessary surgical techniques and inappropriate implant size for Asian people. The Discovery elbow system (Biomet Inc., Warsaw, US) has recently been developed and it has many advantages when compared to Coonrad-Morrey implant, but the treatment outcome for this system is unclear in patients with rheumatoid arthritis (RA). Objectives. The aim of this study was to clarify the outcome of TEA using the Discovery elbow system. Methods. Eleven RA patients (13 elbows) who underwent TEA using the Discovery elbow system were investigated in this study. Two patients (3 elbows) were males, and 9 patients (10 elbows) were females. Ten were right elbows, and 3 were left elbows. Two elbows has Larsen grade “disease, 7 had grade” disease and 4 elbows underwent revision surgery. The surgical approach used for all cases was Campbell's posterior approach. The Discovery elbow system was installed using cemented fixation. Two weeks after the operation, ROM exercise was started. The elbow ROM, Mayo elbow performance score (MEPS), and any complications observed at baseline, 6 months and 24 months after surgery were assessed. Results. The preoperative elbow ROM (mean±SD) was −33.4±4.4° in extension, 133.5±3.4° in flexion, 48.5±8.4° pronation and 67.7±5.7° in supination. The postoperative elbow ROM (mean±SD) was −18.5±6.2° in extension, 112.7±6.1° in flexion, 70.0±3.4° in pronation and 73.7±1.6° in supination. As a result, a significant improvement was observed in extension, flexion and pronation. The MEPS improved significantly at 6 months and 24 months after surgery. In addition, no implant loosening was found or revision surgery was required at 24 months after surgery. Conclusions. In this study, the elbow function was observed to significantly improve by TEA using the Discovery elbow system based on the short-time outcome. However, further study is still needed to clarify the long-term outcome of this implant in RA patients

Background. The quest for the perfectly designed elbow prosthesis continues as instability and loosening remain the foremost reasons for the failure of total elbow replacement (TER). The Discovery® Elbow System (Biomet, UK) (Figure 1), which has been used in UK since 2003, is one of the latest generations of linked prosthesis. This system was designed to decrease polyethylene-bushing wear, improve anatomic stem design, restore elbow joint biomechanics, and produce a hinge that could be easily revised. This report describes the short term outcome of TER using the Discovery® Elbow System. Patients and Methods. A total of 60 TERs including 48 primary and 12 revisions were performed between 2003 and 2008. Patients included 21 males (37%) and 36 females (63%) with a mean age of 63 years. The indications for primary TER were advanced rheumatoid arthritis (n=19), osteoarthritis (n=16), post traumatic osteoarthritis (n=9), acute fractures (n=3), and haemophilic arthropathy (n=1). The outcome was assessed using pain score, Liverpool Elbow Score (LES), and range of movement during a mean follow-up of 26 months. Associated complications were documented. Radiological assessment included evaluation for loosening, instability and periprosthetic fractures. Results. The mean LES was significantly (p<0.001) improved from 3.8 (±1) pre-operatively to 6.9 (±2) at the final follow- up. Significant improvements were noted in elbow flexion from 100° (±22) to 120° (±15), supination from 41° (±28) to 65° (±20) and pronation from 52° (±22) to 72° (±18). There was no significant change in elbow extension. Mean improvement in flexion-extension and pronation-supination arc was 22° and 44°, respectively. 46 cases (77%) were completely pain-free at the final follow-up. The main complications included deep infection (4 cases – treated with staged revision TER), postoperative ulnar neuropathy (3 cases–treated with decompression), intra-operative fractures of medial condyle (3 cases – treated non-operatively with brace), and elbow haemarthrosis (1 case). Discussion. TER with Discovery® Elbow System resulted in either no pain or mild pain in 87% of cases. Patients undergoing Acclaim, Souter-Strathclyde, GSB III, and Coonrad-Morrey TER have been reported to have no/mild pain in 64%, 67%, 50–92% and 60–100% of cases, respectively. A 22° improvement in flexion-extension arc is comparable to that of Acclaim (23°), Souter-Strathclyde (15°), GSB III (19–33°), and Coonrad-Morrey (17–26°) TER. An improvement of 44° in pronation-supination arc in our series is also comparable to that of 31–67° reported for GSB III and higher than the Coonrad-Morrey prosthesis (21–28°). In terms of complications, an infection rate of 6.7% is consistent with those reported for GSB III TER (7–11%) and Coonrad-Morrey (6–8%). The incidence of persistent ulnar neuropathy was lower compared to GSB III TER (11–14%), Coonrad-Morrey (12–26%), and Acclaim (8%). While the survival of Discovery TER was 93%, the survival of GSB III (5–6 years) and Coonrad-Morrey (5 years) has been reported as 71–85% and 72–90%. The results indicate that Discovery® Elbow System is an effective device for total elbow arthroplasty in terms of functional improvement, pain relief and range of motion at short-term follow-up

Human mesenchymal stem cells are considered the golden standard for clinical application in regenerative medicine for their multilineage differentiation potential, best candidates to treat diseases such as osteoarthritis and osteogenesis imperfecta. In the past few years several molecules have been described to induce the hMSCs differentiation into osteo cell progenitors, mainly discovered by screening of single metabolites bioactivity. However, hMSCs osteogenic differentiation potential is still poor, and the discovery of differentiation inducers with high efficiency is needed. Thanks to automated processes, High Throughput Screening (HTS) strategies shorten the metabolites bioactivity investigation timeline, allowing testing of many molecules simultaneously. In this work, reliable assays for natural products bioactivity investigation detection were developed using HTS methodologies and validated by testing 15 purified compounds derived by marine fungi and sponges. The HTS cytotoxicity investigation using HepG2 cells allowed to test in a single experiment, 15 metabolites in 4 concentrations ranging from 1 to 20µM. Low cytotoxicity was detected for metabolites concentrations from 1 to 10µM and so set as treatment concentrations to be tested in further assays. Anti-inflammatory bioactivity was tested on THP1 cells triggered by LPS. Five out of 15 metabolites showed to prevent the LPS induced THP1 inflammatory activation by lowering the TNF-α production. The metabolites pro-osteogenic potential was investigated using hMSCs: their differentiation was evaluated by calcium mineralization after 10 days differentiation. Pro-osteogenic molecules were not detected in this screening, but the method validation represents a powerful tool for future natural product and synthetic molecules libraries screenings

Medium-term results of the Discovery elbow replacement are presented. We reviewed 51 consecutive primary Discovery total elbow replacements (TERs) implanted in 48 patients. The mean age of the patients was 69.2 years (49 to 92), there were 19 males and 32 females (37%:63%) The mean follow-up was 40.6 months (24 to 69). A total of six patients were lost to follow-up. Statistically significant improvements in range movement and Oxford Elbow Score were found (p < 0.001). Radiolucent lines were much more common in, and aseptic loosening was exclusive to, the humeral component. Kaplan–Meier survivorship at five years was 92.2% (95% CI 74.5% to 96.4%) for aseptic loosening. In four TERs, periprosthetic infection occurred resulting in failure. A statistically significant association between infection and increased BMI was found (p = 0.0268). Triceps failure was more frequent after the Mayo surgical approach and TER performed after previous trauma surgery. No failures of the implant were noted. . Our comparison shows that the Discovery has early clinical results that are similar to other semi-constrained TERs. We found continued radiological surveillance with particular focus on humeral lucency is warranted and has not previously been reported. Despite advances in the design of total elbow replacement prostheses, rates of complication remain high. Cite this article: Bone Joint J 2014;96-B:1359–65

Aims. Osteoporosis (OP) is a metabolic bone disease, characterized by a decrease in bone mineral density (BMD). However, the research of regulatory variants has been limited for BMD. In this study, we aimed to explore novel regulatory genetic variants associated with BMD. Methods. We conducted an integrative analysis of BMD genome-wide association study (GWAS) and regulatory single nucleotide polymorphism (rSNP) annotation information. Firstly, the discovery GWAS dataset and replication GWAS dataset were integrated with rSNP annotation database to obtain BMD associated SNP regulatory elements and SNP regulatory element-target gene (E-G) pairs, respectively. Then, the common genes were further subjected to HumanNet v2 to explore the biological effects. Results. Through discovery and replication integrative analysis for BMD GWAS and rSNP annotation database, we identified 36 common BMD-associated genes for BMD irrespective of regulatory elements, such as FAM3C (p. discovery GWAS. = 1.21 × 10. -25. , p. replication GWAS. = 1.80 × 10. -12. ), CCDC170 (p. discovery GWAS. = 1.23 × 10. -11. , p. replication GWAS. = 3.22 × 10. -9. ), and SOX6 (p. discovery GWAS. = 4.41 × 10. -15. , p. replication GWAS. = 6.57 × 10. -14. ). Then, for the 36 common target genes, multiple gene ontology (GO) terms were detected for BMD such as positive regulation of cartilage development (p = 9.27 × 10. -3. ) and positive regulation of chondrocyte differentiation (p = 9.27 × 10. -3. ). Conclusion. We explored the potential roles of rSNP in the genetic mechanisms of BMD and identified multiple candidate genes. Our study results support the implication of regulatory genetic variants in the development of OP. Cite this article: Bone Joint Res 2023;12(2):147–154

Aims. Impaired fracture repair in patients with type 2 diabetes mellitus (T2DM) is not fully understood. In this study, we aimed to characterize the local changes in gene expression (GE) associated with diabetic fracture. We used an unbiased approach to compare GE in the fracture callus of Zucker diabetic fatty (ZDF) rats relative to wild-type (WT) littermates at three weeks following femoral osteotomy. Methods. Zucker rats, WT and homozygous for leptin receptor mutation (ZDF), were fed a moderately high-fat diet to induce T2DM only in the ZDF animals. At ten weeks of age, open femoral fractures were simulated using a unilateral osteotomy stabilized with an external fixator. At three weeks post-surgery, the fractured femur from each animal was retrieved for analysis. Callus formation and the extent of healing were assessed by radiograph and histology. Bone tissue was processed for total RNA extraction and messenger RNA (mRNA) sequencing (mRNA-Seq). Results. Radiographs and histology demonstrated impaired fracture healing in ZDF rats with incomplete bony bridge formation and an influx of intramedullary inflammatory tissue. In comparison, near-complete bridging between cortices was observed in Sham WT animals. Of 13,160 genes, mRNA-Seq analysis identified 13 that were differentially expressed in ZDF rat callus, using a false discovery rate (FDR) threshold of 10%. Seven genes were upregulated with high confidence (FDR = 0.05) in ZDF fracture callus, most with known roles in inflammation. Conclusion. These findings suggest that elevated or prolonged inflammation contributes to delayed fracture healing in T2DM. The identified genes may be used as biomarkers to monitor and treat delayed fracture healing in diabetic patients. Cite this article: Bone Joint Res 2023;12(10):657–666

Aims. Current diagnostic tools are not always able to effectively identify periprosthetic joint infections (PJIs). Recent studies suggest that circulating microRNAs (miRNAs) undergo changes under pathological conditions such as infection. The aim of this study was to analyze miRNA expression in hip arthroplasty PJI patients. Methods. This was a prospective pilot study, including 24 patients divided into three groups, with eight patients each undergoing revision of their hip arthroplasty due to aseptic reasons, and low- and high-grade PJI, respectively. The number of intraoperative samples and the incidence of positive cultures were recorded for each patient. Additionally, venous blood samples and periarticular tissue samples were collected from each patient to determine miRNA expressions between the groups. MiRNA screening was performed by small RNA-sequencing using the miRNA next generation sequencing (NGS) discovery (miND) pipeline. Results. Overall, several miRNAs in plasma and tissue were identified to be progressively deregulated according to ongoing PJI. When comparing the plasma samples, patients with a high-grade infection showed significantly higher expression levels for hsa-miR-21-3p, hsa-miR-1290, and hsa-miR-4488, and lower expression levels for hsa-miR-130a-3p and hsa-miR-451a compared to the aseptic group. Furthermore, the high-grade group showed a significantly higher regulated expression level of hsa-miR-1260a and lower expression levels for hsa-miR-26a-5p, hsa-miR-26b-5p, hsa-miR-148b-5p, hsa-miR-301a-3p, hsa-miR-451a, and hsa-miR-454-3p compared to the low-grade group. No significant differences were found between the low-grade and aseptic groups. When comparing the tissue samples, the high-grade group showed significantly higher expression levels for 23 different miRNAs and lower expression levels for hsa-miR-2110 and hsa-miR-3200-3p compared to the aseptic group. No significant differences were found in miRNA expression between the high- and low-grade groups, as well as between the low-grade and aseptic groups. Conclusion. With this prospective pilot study, we were able to identify a circulating miRNA signature correlating with high-grade PJI compared to aseptic patients undergoing hip arthroplasty revision. Our data contribute to establishing miRNA signatures as potential novel diagnostic and prognostic biomarkers for PJI. Cite this article: Bone Jt Open 2024;5(6):479–488

Background. FORECAST is a prospective longitudinal cohort study exploring mechanism-based prognostic factors for pain persistence in sciatica. Here, we share an update on this largest deeply-phenotyped primary care sciatica cohort. Methods/results. Our cohort includes 180 people with sciatica (score >4 on Stynes’ Sum Score), aged 18–85, within 3 months of symptom onset. Psychosocial factors, self-reported sensory profiling, clinical examination, quantitative sensory testing (QST), biological samples (blood and skin samples), and Magnetic Resonance Neurography of lumbar nerve roots were collected at baseline. Pain persistence was determined at three and twelve months with the Sciatica Bothersomeness Index (SBI) and a numeric pain rating scale (NRS) as primary outcomes. Recruitment nears completion, with 160 participants enrolled to date. 127 and 96 participants have completed 3 and 12 months follow-up respectively. Overall, 56% of our cohort are female, with a mean age (SD) of 54.14yrs (16.57). Ethnicity data approximates local populations. SBI at baseline was (median [IQR]) 13[10-17], and interim longitudinal data shows stepwise improvement at 3 and 12 months. Baseline ‘average’ pain intensity was 5.56 (2.15) for leg pain, and 4.14(2.82) for low back pain (LBP). Overall, pain scores decreased at 3 and 12 months, with greater reductions in leg pain than LBP at 12 months. However, around 55–80% and 40–65% of people reported persistent pain at 3 and 12 months respectively. Conclusion. Leg pain severity was moderate and higher than LBP at baseline. All primary outcome measures demonstrate improvement over time, however 40–65% of patients report persistent pain at 12 months. Conflicts of interest. LR: Paid facilitation of post-graduate courses internationally. SK, MT, FP, KM, WS, CP, CR, SC: No conflicts of interest. GC: Editor in Chief of Health Psychology Review. Director of board of directors, MentalCHealth Care setting NoordWestVlaanderen. JF: Copyright holder of ODI (Oswestry Disability Index). Served on a data monitoring committee for a clinical trial of 2 different surgical approaches to cervical disc herniation (FORVAD). Member of HTA Prioritisation Committee B: Inside hospital Care from 2015-February 2019. Member of HTA Interventional Procedures Panel from 2010–2015. Trustee and board member of 3 spine related charities – Back to Back; British Scoliosis Research Foundation and BackCare. Expert instructed by both claimant and defendant solicitors in negligence and person injury cases. GB: Paid consultancy (RNA-seq) with Ivy Farm and Coding.bio. ABS: Paid post-graduate lecturing internationally. Co-chair NeupSig sciatica working group (unpaid). Sources of funding. This project is funded by UKRI and Versus Arthritis as part of the UKRI Strategic Priorities Fund (SPF) Advanced Pain Discovery Platform (APDP), a co-funded initiative by UKRI (MRC, BBSRC, ESRC), Versus Arthritis, the Medical Research Foundation and Eli Lilly and Company Ltd (Grant MR/W027003/1). Additional funding has been received from the back to back charity to expand longitudinal components of the study. LR has received support with PhD fees from the CSP charitable trust. ABS is supported by a Wellcome Trust Clinical Career Development Fellowship. (222101/Z/20/Z). WS is partly funded through the National Institute for Health and Care Research (NIHR) Biomedical Research Centre at the South London and Maudsley NHS Foundation Trust and King's College London. FP is funded by a Dorothy Hodgkin Career Development Fellowship in Chemistry in association with Somerville College. GB is supported by the Wellcome Trust (223149/Z/21/Z) and Diabetes UK (19/0005984). GC and KRM are partly funded by UKRI and Versus Arthritis as part of the Advanced Pain Discovery Platform (APDP) PAINSTORM (MR/W002388/1). The UKRI and Versus Arhthritis (APDP) are the major funders of FORECAST. All other funders provided either some people support, or funded projects with legacy data that we reuse

Aims. To assess the alterations in cell-specific DNA methylation associated with chondroitin sulphate response using peripheral blood collected from Kashin-Beck disease (KBD) patients before initiation of chondroitin sulphate treatment. Methods. Peripheral blood samples were collected from KBD patients at baseline of chondroitin sulphate treatment. Methylation profiles were generated using reduced representation bisulphite sequencing (RRBS) from peripheral blood. Differentially methylated regions (DMRs) were identified using MethylKit, while DMR-related genes were defined as those annotated to the gene body or 2.2-kilobase upstream regions of DMRs. Selected DMR-related genes were further validated by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) to assess expression levels. Tensor composition analysis was performed to identify cell-specific differential DNA methylation from bulk tissue. Results. This study revealed 21,060 hypermethylated and 44,472 hypomethylated DMRs, and 13,194 hypermethylated and 22,448 hypomethylated CpG islands for differential global methylation for chondroitin sulphate treatment response. A total of 12,666 DMR-related genes containing DMRs were identified in their promoter regions, such as CHL1 (false discovery rate (FDR) = 2.11 × 10. -11. ), RIC8A (FDR = 7.05 × 10. -4. ), and SOX12 (FDR = 1.43 × 10. -3. ). Additionally, RIC8A and CHL1 were hypermethylated in responders, while SOX12 was hypomethylated in responders, all showing decreased gene expression. The patterns of cell-specific differential global methylation associated with chondroitin sulphate response were observed. Specifically, we found that DMRs located in TESPA1 and ATP11A exhibited differential DNA methylation between responders and non-responders in granulocytes, monocytes, and B cells. Conclusion. Our study identified cell-specific changes in DNA methylation associated with chondroitin sulphate response in KBD patients. Cite this article: Bone Joint Res 2024;13(5):237–246

Osteoarthritis (OA) is a chronic degenerative joint disease characterized by progressive cartilage degradation, synovial membrane inflammation, osteophyte formation, and subchondral bone sclerosis. Pathological changes in cartilage and subchondral bone are the main processes in OA. In recent decades, many studies have demonstrated that activin-like kinase 3 (ALK3), a bone morphogenetic protein receptor, is essential for cartilage formation, osteogenesis, and postnatal skeletal development. Although the role of bone morphogenetic protein (BMP) signalling in articular cartilage and bone has been extensively studied, many new discoveries have been made in recent years around ALK3 targets in articular cartilage, subchondral bone, and the interaction between the two, broadening the original knowledge of the relationship between ALK3 and OA. In this review, we focus on the roles of ALK3 in OA, including cartilage and subchondral bone and related cells. It may be helpful to seek more efficient drugs or treatments for OA based on ALK3 signalling in future

Currently implemented accuracy metrics in open-source libraries for segmentation by supervised machine learning are typically one-dimensional scores [1]. While extremely relevant to evaluate applicability in clinics, anatomical location of segmentation errors is often neglected. This study aims to include the three-dimensional (3D) spatial information in the development of a novel framework for segmentation accuracy evaluation and comparison between different methods. Predicted and ground truth (manually segmented) segmentation masks are meshed into 3D surfaces. A template mesh of the same anatomical structure is then registered to all ground truth 3D surfaces. This ensures all surface points on the ground truth meshes to be in the same anatomically homologous order. Next, point-wise surface deviations between the registered ground truth mesh and the meshed segmentation prediction are calculated and allow for color plotting of point-wise descriptive statistics. Statistical parametric mapping includes point-wise false discovery rate (FDR) adjusted p-values (also referred to as q-values). The framework reads volumetric image data containing the segmentation masks of both ground truth and segmentation prediction. 3D color plots containing descriptive statistics (mean absolute value, maximal value,…) on point-wise segmentation errors are rendered. As an example, we compared segmentation results of nnUNet [2], UNet++ [3] and UNETR [4] by visualizing the mean absolute error (surface deviation from ground truth) as a color plot on the 3D model of bone and cartilage of the mean distal femur. A novel framework to evaluate segmentation accuracy is presented. Output includes anatomical information on the segmentation errors, as well as point-wise comparative statistics on different segmentation algorithms. Clearly, this allows for a better informed decision-making process when selecting the best algorithm for a specific clinical application

Osteosarcoma (OSA) is a rare, but disproportionately lethal cancer that predominantly affects children. Sadly, discovery of new therapies for OSA has largely been unsuccessful in the past 30 years; there is an urgent need to identify new treatments for OSA. Pet dogs with naturally-occurring OSA represent a unique comparative “model” to discover new treatments for OSA. Unlike humans, in which fewer than 1,000 cases of OSA occur each year, there are nearly 50,000 new cases each year of OSA in dogs. In addition, dogs have an intact immune system, a shared environment with humans, and more rapid progression of disease. Together these factors make dogs an important comparative model for new therapies for OSA. The purpose of this study was: 1) to validate this mouse-dog-human pipeline for drug discovery and 2) to validate CRM1 as a novel target for ostesoarcoma treatment. We developed patient-derived cell lines and xenografts of OSA from both dogs and humans and applied these models to identify new therapies for OSA using high-throughput drug screens in vitro followed by in vivo validation. Whole exome sequencing was performed on the patient-derived models and original tumors to identify potential driver mutations. A high-throughput screen in both dog and human OSA identified CRM1 inhibitors as effective at killing dog and human OSA patient-derived cell lines in vitro. In vivo, CRM1 inhibition led to significant tumor growth inhibition in patient-derived xenografts from dogs and humans. Western blotting demonstrated increased levels of CRM1 protein expression across nine different dog and human OSA cell lines compared to non-transformed human osteoblasts. CRM1 upregulation in OSA cells was further verified by immunofluorescence staining. Increased CRM1 expression was prognostic for poorer metastasis-free survival and poorer overall survival. Our cross-species personalized medicine pipeline identified CRM1 as a potential therapeutic target to treat OSA in both dogs and humans. Future studies are focused on testing CRM1 inhibitors in canine clinical trials

Precision health aims to develop personalised and proactive strategies for predicting, preventing, and treating complex diseases such as osteoarthritis (OA). Due to OA heterogeneity, which makes developing effective treatments challenging, identifying patients at risk for accelerated disease progression is essential for efficient clinical trial design and new treatment target discovery and development. To create a reliable and interpretable precision health tool that predicts rapid knee OA progression over a 2-year period from baseline patient characteristics using an advanced automated machine learning (autoML) framework, “Autoprognosis 2.0”. All available 2-year follow-up periods of 600 patients from the FNIH OA Biomarker Consortium were analysed using “Autoprognosis 2.0” in two separate approaches, with distinct definitions of clinical outcomes: multi-class predictions (categorising disease progression into pain and/or radiographic progression) and binary predictions. Models were developed using a training set of 1352 instances and all available variables (including clinical, X-ray, MRI, and biochemical features), and validated through both stratified 10-fold cross-validation and hold-out validation on a testing set of 339 instances. Model performance was assessed using multiple evaluation metrics. Interpretability analyses were carried out to identify important predictors of progression. Our final models yielded higher accuracy scores for multi-class predictions (AUC-ROC: 0.858, 95% CI: 0.856-0.860) compared to binary predictions (AUC-ROC: 0.717, 95% CI: 0.712-0.722). Important predictors of rapid disease progression included WOMAC scores and MRI features. Additionally, accurate ML models were developed for predicting OA progression in a subgroup of patients aged 65 or younger. This study presents a reliable and interpretable precision health tool for predicting rapid knee OA progression. Our models provide accurate predictions and, importantly, allow specific predictors of rapid disease progression to be identified. Furthermore, the transparency and explainability of our methods may facilitate their acceptance by clinicians and patients, enabling effective translation to clinical practice

The ability to edit DNA at the nucleotide level using clustered regularly interspaced short palindromic repeats (CRISPR) systems is a relatively new investigative tool that is revolutionizing the analysis of many aspects of human health and disease, including orthopaedic disease. CRISPR, adapted for mammalian cell genome editing from a bacterial defence system, has been shown to be a flexible, programmable, scalable, and easy-to-use gene editing tool. Recent improvements increase the functionality of CRISPR through the engineering of specific elements of CRISPR systems, the discovery of new, naturally occurring CRISPR molecules, and modifications that take CRISPR beyond gene editing to the regulation of gene transcription and the manipulation of RNA. Here, the basics of CRISPR genome editing will be reviewed, including a description of how it has transformed some aspects of molecular musculoskeletal research, and will conclude by speculating what the future holds for the use of CRISPR-related treatments and therapies in clinical orthopaedic practice. Cite this article: Bone Joint Res 2020;9(7):351–359

Background. Involving research users in setting priorities for research is essential to ensure research outcomes are patient-centred and to maximise research value and impact. The Musculoskeletal (MSK) Disorders Research Advisory Group Versus Arthritis led a research priority setting exercise across MSK disorders. Methods. The Child Health and Nutrition Research Initiative (CHRNI) method of setting research priorities with a range of stakeholders were utilised. The MSKD RAG identified, through consensus, four research Domains: Mechanisms of Disease; Diagnosis and Impact; Living Well with MSK disorders and Successful Translation. Following ethical approval, the research priority exercise involved four stages and two surveys, to: 1) gather research uncertainties; 2) consolidate these; 3) score uncertainties using agreed criteria of importance and impact on a score of 1–10; and 4) analyse scoring, for prioritisation. Results. The first survey had 209 respondents, who described 1290 research uncertainties, which were refined into 68 research questions. 285 people responded to the second survey. The largest group of respondents represented patients and carers, followed by researchers and healthcare professionals. A ranked list was produced, with scores ranging between 12 and 18. Key priorities included developing and testing new treatments, better targeting of treatments, early diagnosis, prevention and better understanding and management of pain, with an emphasis on understanding underpinning mechanisms. Conclusions. For the first time, we have summarised priorities for research across MSKD, from discovery science to applied clinical and health research, including translation. We present a call to action to researchers and funders to target these priorities. Conflict of Interest: None. Sources of funding: We thank the funder, Versus Arthritis for their support of the research advisory groups and this activity

Abstract. Objectives. A promising therapy for early osteoarthritis (OA) is the transplantation of human umbilical cord-derived mesenchymal stromal cells (hUC-MSCs). The synovial fluid (SF) from a pre-clinical ovine model treated with hUC-MSCs has been profiled using proteomics and bioinformatics to elucidate potential mechanisms of therapeutic effect. Methods. Four weeks after a medial meniscus transection surgery, sheep were injected with 10. 7. hUC-MSCs in Phosphate Buffered Saline (PBS) or PBS only (n=7) and sacrificed at 12 weeks. SF was normalised for protein abundance (ProteoMiner. TM. ) and analysed using label-free quantitation proteomics. Bioinformatics analyses (Ingenuity Pathway Analysis (IPA) and STRING) were used to assess differentially regulated functions from the proteomic data. Human orthologues were identified for the ovine proteins using UniProt and DAVID resources and proteins that were ≥±1.3 fold differentially abundant between treatment groups, were included in the bioinformatics analyses. Results. hUC-MSC treated animals demonstrated significantly less joint space narrowing. Nineteen SF proteins were differentially abundant in treated cf. control sheep (FC±2.0; p<0.05). Biglycan (a small leucine-rich proteoglycan of the cartilage extracellular matrix) abundance was increased by 2.1 fold in treated compared to untreated sheep (p=0.024). IPA indicated that lipid synthesis (z-score=1.772; p=0.00267) and immune cell migration pathways (cell movement of mononuclear leukocytes: z-score=1.761; p=0.00259), amongst others, were likely to be activated in the treated sheep. Conversely, tissue damage (z-score=−2; p=0.00019), senescence (z-score=−1.981; p=0.00007) and necrosis (z-score=−1.728; p=0.00829) associated pathways as well as inflammation (z-score=−1.718; p=0.00057) and vascular permeability (z-score=−1.698; p=0.00002) were likely to be inhibited in treated cf. untreated sheep. Conclusions. hUC-MSC treatment prevented/delayed OA progression, demonstrated via a reduction in joint space narrowing. SF proteome bioinformatics revealed potential mechanisms of therapeutic action related to immunomodulation and the inhibition of multiple cell death, and tissue damage associated pathways. Further, a potential predicted upregulation in lipid synthesis in treated sheep represents a novel mechanism warranting further investigation. Additional work is required to validate these discovery phase proteomic findings in studies which specifically target and manipulate the proposed mechanisms highlighted. Declaration of Interest. (b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project

Abstract. Introduction. Precision health aims to develop personalised and proactive strategies for predicting, preventing, and treating complex diseases such as osteoarthritis (OA), a degenerative joint disease affecting over 300 million people worldwide. Due to OA heterogeneity, which makes developing effective treatments challenging, identifying patients at risk for accelerated disease progression is essential for efficient clinical trial design and new treatment target discovery and development. Objectives. This study aims to create a trustworthy and interpretable precision health tool that predicts rapid knee OA progression based on baseline patient characteristics using an advanced automated machine learning (autoML) framework, “Autoprognosis 2.0”. Methods. All available 2-year follow-up periods of 600 patients from the FNIH OA Biomarker Consortium were analysed using “Autoprognosis 2.0” in two separate approaches, with distinct definitions of clinical outcomes: multi-class predictions (categorising patients into non-progressors, pain-only progressors, radiographic-only progressors, and both pain and radiographic progressors) and binary predictions (categorising patients into non-progressors and progressors). Models were developed using a training set of 1352 instances and all available variables (including clinical, X-ray, MRI, and biochemical features), and validated through both stratified 10-fold cross-validation and hold-out validation on a testing set of 339 instances. Model performance was assessed using multiple evaluation metrics, such as AUC-ROC, AUC-PRC, F1-score, precision, and recall. Additionally, interpretability analyses were carried out to identify important predictors of rapid disease progression. Results. Our final models yielded high accuracy scores for both multi-class predictions (AUC-ROC: 0.858, 95% CI: 0.856–0.860; AUC-PRC: 0.675, 95% CI: 0.671–0.679; F1-score: 0.560, 95% CI: 0.554–0.566) and binary predictions (AUC-ROC: 0.717, 95% CI: 0.712–0.722; AUC-PRC: 0.620, 95% CI: 0.616–0.624; F1-score: 0.676, 95% CI: 0.673–0679). Important predictors of rapid disease progression included the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores and MRI features. Our models were further successfully validated using a hold-out dataset, which was previously omitted from model development and training (AUC-ROC: 0.877 for multi-class predictions; AUC-ROC: 0.746 for binary predictions). Additionally, accurate ML models were developed for predicting OA progression in a subgroup of patients aged 65 or younger (AUC-ROC: 0.862, 95% CI: 0.861–0.863 for multi-class predictions; AUC-ROC: 0.736, 95% CI: 0.734–0.738 for binary predictions). Conclusions. This study presents a reliable and interpretable precision health tool for predicting rapid knee OA progression using “Autoprognosis 2.0”. Our models provide accurate predictions and offer insights into important predictors of rapid disease progression. Furthermore, the transparency and interpretability of our methods may facilitate their acceptance by clinicians and patients, enabling effective utilisation in clinical practice. Future work should focus on refining these models by increasing the sample size, integrating additional features, and using independent datasets for external validation. Declaration of Interest. (b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project

Abstract. OBJECTIVE. Knee varus malalignment increases medial knee compartment loading and is associated with knee osteoarthritis (OA) progression and severity. 1. Altered biomechanical loading and dysregulation of joint tissue biology drive OA progression, but mechanistic links between these factors are lacking. Subchondral bone structural changes are biomechanically driven, involve bone resorption, immune cell influx, angiogenesis, and sensory nerve invasion, and contribute to joint destruction and pain. 2. We have investigated mechanisms underlying this involving RANKL and alkaline phosphatase (ALP), which reflect bone resorption and mineralisation respectively. 3. and the axonal guidance factor Sema3A. Sema3A is osteotropic, expressed by mechanically sensitive osteocytes, and an inhibitor of sensory nerve, blood vessel and immune cell invasion. 4. Sema3A is also differentially expressed in human OA bone. 5. HYPOTHESIS: Medial knee compartment overloading in varus knee malalignment patients causes dysregulation of bone derived Sema3A signalling directly linking joint biomechanics to pathology and pain. METHODS. Synovial fluid obtained from 30 subjects with medial knee OA (KL grade II-IV) undergoing high tibial osteotomy surgery (HTO) was analysed by mesoscale discovery and ELISA analysis for inflammatory, neural and bone turnover markers. 11 of these patients had been previously analysed in a published patient-specific musculoskeletal model. 6. of gait estimating joint contact location, pressure, forces, and medial-lateral condyle load distribution in a published data set included in analyses. Data analysis was performed using Pearson's correlation matrices and principal component analyses. Principal Components (PCs) with eigenvalues greater than 1 were analysed. RESULTS. PC1 (32.94% of variation) and PC2 (25.79% of variation) from PCA analysis and correlation matrices separated patients according to correlated clusters of established inflammatory markers of OA pain and progression (IL6/IL8, r=0.754, p<0.001) and anti-inflammatory mediators (IL4/IL10, r=0.469, p=0.005). Bone turnover marker ALP was positively associated with KL grade (r=0.815, p=0.002) and negatively associated with IL10 (r=−0.402, p=0.018) and first peak knee loading pressures (r=−0.688, p=0.019). RANKL was positively associated with IL4 (r=0.489, p=0.003). Synovial fluid Sema3A concentrations showed separate clustering from all OA progression markers and was inversely correlated with TNF-α (r=−0.423, p=0.022) in HTO patients. Sema3A was significantly inversely correlated with total predicted force in the medial joint compartment (r=−0.621, p=0.041), mean (r=−0.63, p=0.038) and maximum (r=−0.613, p=0.045) calculated medial compartment joint pressures during the first phase and mean (r=−0.618, p=0.043) and maximum (r=−0.641, p=0.034) medial compartment joint pressures during midstance outputs of patient-specific musculoskeletal model. CONCLUSIONS. This study shows joint inflammatory status and mechanical overloading influence subchondral bone-remodelling. Synovial Sema3A concentrations are inversely correlated to patient-specific musculoskeletal model estimations of pathological medial overloading. This study reveals Sema3A as a biological mediator with capacity to induce OA pain and disease progression that is directly regulated by gait mechanical loading. Declaration of Interest. (b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project

Aims. The aim of this study was to explore the genetic correlation and causal relationship between blood plasma proteins and rheumatoid arthritis (RA). Methods. Based on the genome-wide association studies (GWAS) summary statistics of RA from European descent and the GWAS summary datasets of 3,622 plasma proteins, we explored the relationship between RA and plasma proteins from three aspects. First, linkage disequilibrium score regression (LD score regression) was applied to detect the genetic correlation between RA and plasma proteins. Mendelian randomization (MR) analysis was then used to evaluate the causal association between RA and plasma proteins. Finally, GEO2R was used to screen the differentially expressed genes (DEGs) between patients with RA and healthy controls. Results. We found that seven kinds of plasma proteins had genetic correlations with RA, such as Soluble Receptor for Advanced Glycation End Products (sRAGE) (correlation coefficient = 0.2582, p = 0.049), vesicle transport protein USE1 (correlation coefficient = 0.1337, p = 0.018), and spermatogenesis-associated protein 20 (correlation coefficient = 0.3706, p = 0.018). There was a significant causal relationship between sRAGE and RA. By comparing the genes encoding seven plasma proteins, we found that only USE1 was a DEG associated with RA. Conclusion. Our study identified a set of candidate plasma proteins that showed signals correlated with RA. Since the results of this study need further experimental verification, they should be interpreted with caution. However, we hope that this paper will provide new insights for the discovery of pathogenic genes and RA pathogenesis in the future. Cite this article: Bone Joint Res 2022;11(2):134–142

Purpose. Back pain is the primary cause of disability worldwide yet surprisingly little is known of the underlying pathobiology. We conducted a genome-wide association study (GWAS) meta-analysis of chronic back pain (CBP). Adults of European ancestry from 15 cohorts in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, and UK Biobank were studied. Methods. CBP cases were defined as reporting back pain present for ≥3–6 months; non-cases were included as comparisons (“controls”). Each cohort conducted genotyping followed by imputation. GWAS used logistic regression with additive genetic effects adjusting for age, sex, study-specific covariates, and population substructure. Suggestive (p<5×10. –7. ) & genome-wide significant (p<5×10. –8. ) variants were carried forward for replication in an independent sample of UK Biobank participants. Discovery sample n = 158,025 individuals, including 29,531 CBP cases. Results. Genome-wide significant association was found for intron variant rs12310519 in SOX5 (OR=1.08, p=7.2×10. −10. ). This was replicated in the independent sample n = 283,752, comprising 50,915 cases (OR 1.06, p=5.3×10. −11. ); in joint meta-analysis OR=1.07, p=4.5×10. −19. exceeding genome-wide significance. We found three other suggestive associations in discovery, two of which exceeded genome-wide significance in joint meta-analysis: an intergenic variant rs7833174 located between CCDC26 and GSDMC (OR 1.05, p=4.4×10. −13. ), and an intron variant, rs4384683, in DCC (OR 0.97, p=2.4×10. −10. ). Conclusion. We have identified and replicated a genetic locus associated with CBP (SOX5). We also identified 2 other loci that reached genome-wide significance in a 2-stage joint meta-analysis (CCDC26/GSDMC and DCC) which will shed light on the pathogenic mechanisms underlying CBP. Conflicts of interest: YA and LK are owners of Maatschap PolyOmica. This study was supported by the European Community's Seventh Framework Programme funded project PainOmics (Grant agreement n. 602736) and conducted using the UK Biobank Resource (project # 18219). CHARGE and other cohort-specific funding sources to be submitted- see below