[Identification of Osteoarthritis Inflamm-Aging Biomarkers by Integrating Bioinformatic Analysis and Machine Learning Strategies and the Clinical Validation]. / ç”Ÿç‰©ä¿¡æ¯å­¦å’Œæœºå™¨å­¦ä¹ ç­–ç•¥è¯†åˆ«éª¨å ³èŠ‚ç‚Žç‚Žæ€§è¡°è€ç”Ÿç‰©æ ‡å¿—ç‰©ä¸Žä¸´åºŠéªŒè¯.

Objective: To identify inflamm-aging related biomarkers in osteoarthritis (OA). Methods: Microarray gene profiles of young and aging OA patients were obtained from the Gene Expression Omnibus (GEO) database and aging-related genes (ARGs) were obtained from the Human Aging Genome Resource (HAGR) database. The differentially expressed genes of young OA and older OA patients were screened and then intersected with ARGs to obtain the aging-related genes of OA. Enrichment analysis was performed to reveal the potential mechanisms of aging-related markers in OA. Three machine learning methods were used to identify core senescence markers of OA and the receiver operating characteristic (ROC) curve was used to assess their diagnostic performance. Peripheral blood mononuclear cells were collected from clinical OA patients to verify the expression of senescence-associated secretory phenotype (SASP) factors and senescence markers. Results: A total of 45 senescence-related markers were obtained, which were mainly involved in the regulation of cellular senescence, the cell cycle, inflammatory response, etc. Through the screening with the three machine learning methods, 5 core senescence biomarkers, including FOXO3, MCL1, SIRT3, STAG1, and S100A13, were obtained. A total of 20 cases of normal controls and 40 cases of OA patients, including 20 cases in the young patient group and 20 in the elderly patient group, were enrolled. Compared with those of the young patient group, C-reactive protein (CRP), interleukin (IL)-6, and IL-1ß levels increased and IL-4 levels decreased in the elderly OA patient group (P<0.01); FOXO3, MCL1, and SIRT3 mRNA expression decreased and STAG1 and S100A13 mRNA expression increased (P<0.01). Pearson correlation analysis demonstrated that the selected markers were associated with some indicators, including erythrocyte sedimentation rate (ESR), IL-1ß, IL-4, CRP, and IL-6. The area under the ROC curve of the 5 core aging genes was always greater than 0.8 and the C-index of the calibration curve in the nomogram prediction model was 0.755, which suggested the good calibration ability of the model. Conclusion: FOXO3, MCL1, SIRT3, STAG1, and S100A13 may serve as novel diagnostic biomolecular markers and potential therapeutic targets for OA inflamm-aging.

Identification of clinical characteristics biomarkers for rheumatoid arthritis through targeted DNA methylation sequencing.

OBJECTIVES: Rheumatoid arthritis (RA) is a complex disease with a challenging diagnosis, especially in seronegative patients. The aim of this study is to investigate whether the methylation sites associated with the overall immune response in RA can assist in clinical diagnosis, using targeted methylation sequencing technology on peripheral venous blood samples. METHODS: The study enrolled 241 RA patients, 30 osteoarthritis patients (OA), and 30 healthy volunteers control (HC). Fifty significant cytosine guanine (CG) sites between undifferentiated arthritis and RA were selected and analyzed using targeted DNA methylation sequencing. Logistic regression models were used to establish diagnostic models for different clinical features of RA, and six machine learning methods (logit model, random forest, support vector machine, adaboost, naive bayes, and learning vector quantization) were used to construct clinical diagnostic models for different subtypes of RA. Least absolute shrinkage and selection operator regression and detrended correspondence analysis were utilized to screen for important CGs. Spearman correlation was used to calculate the correlation coefficient. RESULTS: The study identified 16 important CG sites, including tumor necrosis factort receptor associated factor 5 (TRAF5) (chr1:211500151), mothers against decapentaplegic homolog 3 (SMAD3) (chr15:67357339), tumor endothelial marker 1 (CD248) (chr11:66083766), lysosomal trafficking regulator (LYST) (chr1:235998714), PR domain zinc finger protein 16 (PRDM16) (chr1:3307069), A-kinase anchoring protein 10 (AKAP10) (chr17:19850460), G protein subunit gamma 7 (GNG7) (chr19:2546620), yes1 associated transcriptional regulator (YAP1) (chr11:101980632), PRDM16 (chr1:3163969), histone deacetylase complex subunit sin3a (SIN3A) (chr15:75747445), prenylated rab acceptor protein 2 (ARL6IP5) (chr3:69134502), mitogen-activated protein kinase kinase kinase 4 (MAP3K4) (chr6:161412392), wnt family member 7A (WNT7A) (chr3:13895991), inhibin subunit beta B (INHBB) (chr2:121107018), deoxyribonucleic acid replication helicase/nuclease 2 (DNA2) (chr10:70231628) and chromosome 14 open reading frame 180 (C14orf180) (chr14:105055171). Seven CG sites showed abnormal changes between the three groups (P < 0.05), and 16 CG sites were significantly correlated with common clinical indicators (P < 0.05). Diagnostic models constructed using different CG sites had an area under the receiver operating characteristic curve (AUC) range of 0.64-0.78 for high-level clinical indicators of high clinical value, with specificity ranging from 0.42 to 0.77 and sensitivity ranging from 0.57 to 0.88. The AUC range for low-level clinical indicators of high clinical value was 0.63-0.72, with specificity ranging from 0.48 to 0.74 and sensitivity ranging from 0.72 to 0.88. Diagnostic models constructed using different CG sites showed good overall diagnostic accuracy for the four subtypes of RA, with an accuracy range of 0.61-0.96, a balanced accuracy range of 0.46-0.94, and an AUC range of 0.46-0.94. CONCLUSIONS: This study identified potential clinical diagnostic biomarkers for RA and provided novel insights into the diagnosis and subtyping of RA. The use of targeted deoxyribonucleic acid (DNA) methylation sequencing and machine learning methods for establishing diagnostic models for different clinical features and subtypes of RA is innovative and can improve the accuracy and efficiency of RA diagnosis.

Lessons in clinical reasoning - pitfalls, myths, and pearls: a woman brought to a halt.

OBJECTIVES: Limitations in human cognition commonly result in clinical reasoning failures that can lead to diagnostic errors. A metacognitive structured reflection on what clinical findings fit and/or do not fit with a diagnosis, as well as how discordance of data can help advance the reasoning process, may reduce such errors. CASE PRESENTATION: A 60-year-old woman with Hashimoto thyroiditis, diabetes, and generalized anxiety disorder presented with diffuse arthralgias and myalgias. She had been evaluated by physicians of various specialties and undergone multiple modalities of imaging, as well as a electromyography/nerve conduction study (EMG/NCS), leading to diagnoses of fibromyalgia, osteoarthritis, and lumbosacral plexopathy. Despite treatment for these conditions, she experienced persistent functional decline. The only definitive alleviation of her symptoms identified was in the few days following intra-articular steroid injections for osteoarthritis. On presentation to our institution, she appeared fit with a normal BMI. She was a long-time athlete and had been training consistently until her symptoms began. Prediabetes had been diagnosed the year prior and her A1c progressed despite lifestyle modifications and 10 pounds of intentional weight loss. She reported fatigue, intermittent nausea without emesis, and reduced appetite. Examination revealed intact strength and range of motion in both the shoulders and hips, though testing elicited pain. She had symmetric hyperreflexia as well as a slowed, rigid gait. Autoantibody testing revealed strongly positive serum GAD-65 antibodies which were confirmed in the CSF. A diagnosis of stiff-person syndrome was made. She had an incomplete response to first-line therapy with high-dose benzodiazepines. IVIg was initiated with excellent response and symptom resolution. CONCLUSIONS: Through integrated commentary on the diagnostic reasoning process from clinical reasoning experts, this case underscores the importance of frequent assessment of fit along with explicit explanation of dissonant features in order to avoid misdiagnosis and halt diagnostic inertia. A fishbone diagram is provided to visually demonstrate the major factors that contributed to the diagnostic error. The case discussant demonstrates the power of iterative reasoning, case progression without commitment to a single diagnosis, and the dangers of both explicit and implicit bias. Finally, this case provides clinical teaching points in addition to a pitfall, myth, and pearl specific to overcoming diagnostic inertia.

Comparative study of 1H-NMR metabolomic profile of canine synovial fluid in patients affected by four progressive stages of spontaneous osteoarthritis.

The study aimed to assess the metabolomic profile of the synovial fluid (SF) of dogs affected by spontaneous osteoarthritis (OA) and compare any differences based on disease progression. Sixty client-owned dogs affected by spontaneous OA underwent clinical, radiographic, and cytologic evaluations to confirm the diagnosis. The affected joints were divided into four study groups based on the Kallgreen-Lawrence classification: OA1 (mild), OA2 (moderate), OA3 (severe), and OA4 (extremely severe/deforming). The osteoarthritic joint's SF was subjected to cytologic examination and 1H-NMR analysis. The metabolomic profiles of the study groups' SF samples were statistically compared using one-way ANOVA. Sixty osteoarthritic joints (45 stifles, 10 shoulders and 5 elbows) were included in the study. Fourteen, 28, and 18 joints were included in the OA1, OA2, and OA3 groups, respectively (0 joints in the OA4 group). Metabolomic analysis identified 48 metabolites, five of which were significantly different between study groups: Mannose and betaine were elevated in the OA1 group compared with the OA2 group, and the 2-hydroxyisobutyrate concentration decreased with OA progression; in contrast, isoleucine was less concentrated in mild vs. moderate OA, and lactate increased in severe OA. This study identified different 1H-NMR metabolomic profiles of canine SF in patients with progressive degrees of spontaneous OA, suggesting 1H-NMR metabolomic analysis as a potential alternative method for monitoring OA progression. In addition, the results suggest the therapeutic potentials of the metabolomic pathways that involve mannose, betaine, 2-hydroxyisobutyrate, isoleucine, and lactate.

Co-development and testing of an extended community pharmacy model of service delivery for managing osteoarthritis: protocol for a sequential, multi-methods study (PharmOA).

BACKGROUND: Osteoarthritis is a common, painful and disabling long-term condition. Delivery of high-quality guideline-informed osteoarthritis care that successfully promotes and maintains supported self-management is imperative. However, osteoarthritis care remains inconsistent, including under use of core non-pharmacological approaches of education, exercise and weight loss. Community pharmacies are an accessible healthcare provider. United Kingdom government initiatives are promoting their involvement in a range of long-term conditions, including musculoskeletal conditions. It is not known what an enhanced community pharmacy role for osteoarthritis care should include, what support is needed to deliver such a role, and whether it would be feasible and acceptable to community pharmacy teams. In this (PharmOA) study, we aim to address these gaps, and co-design and test an evidence-based extended community pharmacy model of service delivery for managing osteoarthritis. METHODS: Informed by the Theoretical Domains Framework, Normalisation Process Theory, and the Medical Research Council (MRC) framework for developing complex interventions, we will undertake a multi-methods study involving five phases: 1. Systematic review to summarise currently available evidence on community pharmacy roles in supporting adults with osteoarthritis and other chronic (non-cancer) pain. 2. Cross-sectional surveys and one-to-one qualitative interviews with patients, healthcare professionals and pharmacy staff to explore experiences of current, and potential extended community pharmacy roles, in delivering osteoarthritis care. 3. Stakeholder co-design to: a) agree on the extended role of community pharmacies in osteoarthritis care; b) develop a model of osteoarthritis care within which the extended roles could be delivered (PharmOA model of service delivery); and c) refine existing tools to support community pharmacies to deliver extended osteoarthritis care roles (PharmOA tools). 4. Feasibility study to explore the acceptability and feasibility of the PharmOA model of service delivery and PharmOA tools to community pharmacy teams. 5. Final stakeholder workshop to: a) finalise the PharmOA model of service delivery and PharmOA tools, and b) if applicable, prioritise recommendations for its wider future implementation. DISCUSSION: This novel study paves the way to improving access to and availability of high-quality guideline-informed, consistent care for people with osteoarthritis from within community pharmacies.

Exploring m6A-linked aging genes in osteoarthritis and broad cancer spectrum: Prospects for diagnostic and therapeutic advancements.

Osteoarthritis (OA) is a prevalent degenerative joint disease that significantly impacts individuals and healthcare systems worldwide. However, the exploration of N6-methyladenosine (m6A)-related aging genes in OA pathogenesis remains largely underexplored. This study aimed to elucidate the role of m6A-related aging genes in OA and to develop a robust diagnostic model based on their expression profiles. Leveraging publicly available gene expression datasets, we conducted consensus clustering to categorize OA into distinct subtypes, guided by the expression patterns of m6A-related aging genes. Utilizing XGBoost, a cutting-edge machine learning approach, we identified key diagnostic genes and constructed a predictive model. Our investigation extended to the immune functions of these genes, shedding light on potential therapeutic targets and underlying regulatory mechanisms. Our analysis unveiled specific OA subtypes, each marked by unique expression profiles of m6A-related aging genes. We pinpointed a set of pivotal diagnostic genes, offering potential therapeutic avenues. The developed diagnostic model exhibited exceptional capability in distinguishing OA patients from healthy controls. To corroborate our computational findings, we performed quantitative real-time polymerase chain reaction analyses on two cell lines: HC-OA (representing adult osteoarthritis cells) and C-28/I2 (representative of normal human chondrocytes). The gene expression patterns observed were consistent with our bioinformatics predictions, further validating our initial results. In conclusion, this study underscores the significance of m6A-related aging genes as promising biomarkers for diagnosis and prognosis, as well as potential therapeutic targets in OA. Although these findings are encouraging, further validation and functional analyses are crucial for their clinical application.

Is it possible to predict which patients are most likely to benefit from intra-articular corticosteroid injections? A systematic review.

AIM: Intra-articular corticosteroid injections (IACIs) can reduce osteoarthritis-related pain, with differing levels of response across patient groups. This systematic review investigates what is known about the positive and negative predictors of outcomes in patients with osteoarthritis who undergo IACIs. METHODS: We systematically searched the Medline, Embase, and Cochrane databases to May 2023 for studies that evaluated patients undergoing IACIs for osteoarthritis and reported on predictors of outcomes in these patients. RESULTS: Eight studies were included. Two were placebo-controlled trials, six were observational studies. Due to the heterogeneity of outcomes and variables between the studies, it was not possible to pool the results for formal meta-analysis. Higher baseline pain, older age, higher BMI, lower range of movement, higher Kellgren-Lawrence radiographic score, joint effusion, and aspiration were shown to be predictors of a positive response to IACIs in some of the included studies. However, other studies showed no difference in response with these variables, or a negative correlation with response. Sex, smoking, mental health status, hypertension/ischaemic heart disease, diabetes mellitus, duration of symptoms, and socioeconomic status did not demonstrate any correlation with the prediction of positive or negative outcomes after IACIs. CONCLUSION: Several patient features have been identified as positive predictors of outcomes following IACIs. However, this systematic review has identified inconsistent and variable findings across the existing literature. Further research with standardization of IACI administration and outcome measures is required to facilitate further analysis of the reliability and significance of predictive factors for response to IACIs.

A novel biomarker of MMP-cleaved cartilage intermediate layer protein-1 is elevated in patients with rheumatoid arthritis, ankylosing spondylitis and osteoarthritis.

Rheumatic joints have an altered cartilage turnover. Cartilage intermediate layer protein 1 (CILP-1) is secreted from articular chondrocytes and deposited into the cartilage extracellular matrix. We developed an immunoassay targeting a Matrix Metalloproteinase (MMP)-generated neo-epitope of CILP-1, named CILP-M. Human articular cartilage was cleaved with proteolytic enzymes and CILP-M levels were measured. We also quantified CILP-M in two studies from patients with rheumatoid arthritis (RA), ankylosing spondylitis (AS) and osteoarthritis (OA) and explored the monitoring and prognostic potential of CILP-M in TNF-α inhibitory treatment and modified Stoke AS Spine Score (mSASSS) progression. CILP-M was generated by MMP-1, -8 and -12. In the discovery study, CILP-M was significantly higher in patients with RA, AS and OA than healthy donors (p < 0.01, p < 0.001, p < 0.05) with an area under the curve (AUC) between the diseased groups and healthy donors > 0.95 (p < 0.001). In the validation study, patients with RA and AS had significantly higher CILP-M levels than healthy controls (p < 0.001) and AUC > 0.90 (p < 0.001). Patients with AS treated with TNF- α inhibitory treatment in the validation study had significantly lower CILP-M levels after treatment (p = 0.004). CILP-M may provide useful insights into cartilage degradation processes in rheumatic diseases.

[German Translation and Validation of the Patient-Oriented Questionnaire "Thumb Disability Examination" (TDX) for Specific Diagnosis and Follow-Up of Thumb Carpometacarpal Joint Osteoarthritis]. / Deutsche Übersetzung und Validierung des patienten-orientierten Fragebogens "Thumb Disability Examination" (TDX) zur spezifischen Diagnostik und Verlaufskontrolle bei Rhizarthrose.

BACKGROUND: Patient-reported outcome measures (PROMs) are becoming increasingly important in today's patient care. Unfortunately, the most common PROMs in hand surgery are very time-consuming and usually do not cover the actual, diagnosis-specific complaints of the patients. For diagnosis and follow-up of thumb carpometacarpal joint osteoarthritis, Noback et al. developed and validated the Thumb Disability Examination (TDX) questionnaire. This 20-item questionnaire specifically assesses daily living limitations and pain as well as patient-reported satisfaction of thumb function. The aim of this study is to validate the German translation of the TDX, the Thumb Disability Examination - German (TDX-G), and to compare it with the German-language versions of the MHQ and qDASH, which are currently used as gold standard. MATERIAL UND METHODS: Translation and back-translation were performed in accordance with accepted guidelines. For statistical validation of the TDX-G, 30 consecutive patients with thumb carpometacarpal joint osteoarthritis were interviewed under standardised conditions. Internal consistency was calculated using Cronbach's alpha. Test-retest reliability was determined in 10 patients who completed the TDX-G twice at an interval of 2 weeks. The validity of the TDX-G was determined by calculating the correlation coefficients of the TDX-G with the MHQ and qDASH, subjective pain sensation (NRS), and hand strength levels (coarse and pinch strength). In addition, the time to collect each questionnaire was compared. RESULTS: The TDX-G has high internal consistency (Cronbach's alpha 0.932) and test-retest reliability (intraclass correlation coefficient 0.963 [0.850-0.991]). There is a significant correlation between TDX-G and MHQ (- 0.782; p<0.001) and qDASH (0.833; p<0.001). All questionnaires correlate significantly with pain on exertion and pinch force, with the TDX-G having the highest correlation in each case. Significantly less time is needed to record the TDX-G (110±28 s) than to record the MHQ (413±98 s). CONCLUSION: The TDX-G is a reliable tool for diagnosing and monitoring the progression of thumb carpometacarpal joint osteoarthritis. It can be used in both patient care and clinical research and accurately mirrors the symptoms.

Integrating multiple microarray datasets to explore the significance of ferroptosis regulators in the diagnosis and subtype classification of osteoarthritis.

Osteoarthritis (OA) is a chronic joint disease that reduces quality of life for patients. Ferroptosis plays a significant role in OA. However, its underlying mechanism remains unclear. In this study, we integrated 7 OA synovial datasets from the GEO database to screen for significant ferroptosis-related genes. The top 5 ferroptosis regulators were used to construct nomogram models to predict OA prevalence. Consensus clustering was applied to classify OA patients into different ferroptosis patterns based on significant ferroptosis-related genes. Subsequently, an immune cell infiltration study was performed to investigate the relationship between the significant ferroptosis regulators and immune cells. As a result, we screened 11 ferroptosis-related genes in OA patients. Five candidate ferroptosis regulators (SLC7A11, ALOX5, SLC1A5, GOT1, and GSS) were used to predict OA risk. The nomogram model based on these 5 genes is important for assessing the occurrence of OA. Consensus clustering analysis showed that OA patients could be classified into 2 ferroptosis patterns (Clusters A and B). Immune cell infiltration levels were higher in Cluster B than in Cluster A. Two subtypes, gene Clusters A and B, were classified according to the expression of ferroptosis-related DEGs among the ferroptosis patterns. Cluster A and gene Cluster A had higher ferroptosis scores than Cluster B or gene Cluster B, whereas the expression levels of the proinflammatory cytokines interleukin (IL)-1ß, tumor necrosis factor, IL-6, IL-18, and IL-10 were higher in Cluster B or gene Cluster B than those in Cluster A or gene Cluster A. Different subtypes of ferroptosis play critical roles in OA. Furthermore, immunotherapy strategies for OA treatment may be guided by our study on ferroptosis patterns.

Evaluation of the serum tRNA-derived fragment tRF-5022B as a potential biomarker for the diagnosis of osteoarthritis.

Osteoarthritis (OA) is a degenerative disease. It is common in middle-aged and elderly people and is one of the main causes of disability. Currently, the etiology of OA is unclear, and no specific biomarkers for the diagnosis of OA have been identified. Therefore, finding a highly sensitive biomarker is essential for a proper diagnosis.TRNA-derived fragments (tRFs) and tRNA-derived stress-induced RNAs (tiRNAs) are newly discovered classes of noncoding RNAs. tRF has been proven in several studies to have significant associations with tumor diagnosis, making it a promising biomarker in cancer research. However, the diagnostic utility of tRF in OA patients and the correlation between OA progression and trf differential expression have yet to be elaborated. The purpose of this research was to identify tRFs with differential expression in OA to assess their potential as OA biomarkers. To determine the tRF-5022B expression level in this research, real-time fluorescence quantitative PCR has been employed. Agarose gel electrophoresis, Sanger sequencing, and other investigations have been employed for evaluating tRF-5022B's molecular properties. Receiver operating characteristic curve analysis has been utilized for assessing the diagnostic effectiveness of the tRF-5022B. The findings demonstrated that tRF-5022B expression was considerably lower in OA serum. The Kellgren-Lawrence grading scale was shown to correspond with serum expression levels. The ROC curve confirmed that tRF-5022B serum expression levels might differentiate OA cases from healthy individuals and RA patients. According to the aforementioned findings, tRF-5022B may be employed as a novel biomarker for OA diagnosis due to its excellent diagnostic value.

Ferroptosis-related genes LPCAT3 and PGD are potential diagnostic biomarkers for osteoarthritis.

BACKGROUND: Osteoarthritis (OA) is the most common chronic joint disease and how ferroptosis contributes to OA has garnered much attention recently. Bioinformatics promoted the discovery of ferroptosis-related biomarkers for OA. But since OA is a whole-joint disease, sensitive biomarkers for OA are still limited. We herein focused on subchondral bone, a joint component often-ignored by existing bioinformatic reports, to identify ferroptosis-related diagnostic biomarkers for OA. METHOD: Microarray datasets GSE51588 and GSE55457 were downloaded from Gene Expression Omnibus database. Ferroptosis-related differential expression genes (Ferr-DEGs) between OA and normal samples were identified and their functional enrichment was analyzed. Common genes for OA diagnosis were selected from Ferr-DEGs using the combination of SVM-RFE, LASSO regression, and RandomForest machine learning algorithms. Common genes' diagnostic value was verified by receiver operating characteristic (ROC) curve and their association with immune infiltration was analyzed by CIBERSORT. Finally, candidate gene's expression was verified in chondrocytes from OA patients and in an in vitro IL-1ß-induced OA model, by RT-PCR. RESULTS: Two ferroptosis-related genes, LPCAT3 and PGD, were identified as OA diagnostic biomarkers and confirmed by ROC diagnostic test. The association of LPCAT3 and PGD with the infiltration of several types of immune cells was identified. The decreased expression of LPCAT3 and PGD was both confirmed in OA chondrocytes and IL-1ß-induced OA condition. CONCLUSIONS: We identified ferroptosis-related genes LPCAT3 and PGD as potential diagnostic biomarkers for OA, which may offer insight into the role of ferroptosis in OA and provides useful information for the diagnosis and treatment of OA.

Identifying strategies that support equitable person-centred osteoarthritis care for diverse women: content analysis of guidelines.

INTRODUCTION: Women are disproportionately impacted by osteoarthritis (OA) but less likely than men to access early diagnosis and management, or experience OA care tailored through person-centred approaches to their needs and preferences, particularly racialized women. One way to support clinicians in optimizing OA care is through clinical guidelines. We aimed to examine the content of OA guidelines for guidance on providing equitable, person-centred care to disadvantaged groups including women. METHODS: We searched indexed databases and websites for English-language OA-relevant guidelines published in 2000 or later by non-profit organizations. We used manifest content analysis to extract data, and summary statistics and text to describe guideline characteristics, person-centred care (PCC) using a six-domain PCC framework, OA prevalence or barriers by intersectional factors, and strategies to improve equitable access to OA care. RESULTS: We included 36 OA guidelines published from 2003 to 2021 in 8 regions or countries. Few (39%) development panels included patients. While most (81%) guidelines included at least one PCC domain, guidance was often brief or vague, few addressed exchange information, respond to emotions and manage uncertainty, and none referred to fostering a healing relationship. Few (39%) guidelines acknowledged or described greater prevalence of OA among particular groups; only 3 (8%) noted that socioeconomic status was a barrier to OA care, and only 2 (6%) offered guidance to clinicians on how to improve equitable access to OA care: assess acceptability, availability, accessibility, and affordability of self-management interventions; and employ risk assessment tools to identify patients without means to cope well at home after surgery. CONCLUSIONS: This study revealed that OA guidelines do not support clinicians in caring for diverse persons with OA who face disadvantages due to intersectional factors that influence access to and quality of care. Developers could strengthen OA guidelines by incorporating guidance for PCC and for equity that could be drawn from existing frameworks and tools, and by including diverse persons with OA on guideline development panels. Future research is needed to identify multi-level (patient, clinician, system) strategies that could be implemented via guidelines or in other ways to improve equitable, person-centred OA care. PATIENT OR PUBLIC CONTRIBUTION: This study was informed by a team of researchers, collaborators, and thirteen diverse women with lived experience, who contributed to planning, and data collection, analysis and interpretation by reviewing study materials and providing verbal (during meetings) and written (via email) feedback.

Investigation of a family affected by early-onset osteoarthritis - proposal of a clinical pathway and bioinformatics pipeline for the investigation of cases of familial OA.

BACKGROUND: Familial cases of early-onset osteoarthritis (OA) are rare although the exact prevalence is unknown. Early recognition of underlying OA-associated disorders is vital for targeted treatment, when available, and genetic counselling, in case of skeletal dysplasias. Currently, there is no clear guidance on how best to investigate families affected by early-onset OA. METHODS: We investigated a family with multiple members affected by early-onset OA (age at onset ≤ 40 years). Clinical and demographic characteristics were collected, followed by laboratory investigations screening for a range of potential OA-associated disorders, and whole genome sequencing in selected individuals. RESULTS: Seventeen members of the family were included (7 affected and 10 non-affected). There was an even split between the two sexes and two participants were under 18 years old. No pattern of abnormality was seen in the laboratory investigation that could explain the OA phenotype in the family. Whole-genome sequencing was perfomed in one participant and analysed for likely pathogenic variants in genes known to be associated with skeletal dysplasias. A heterozygous variant in the COL2A1 gene was identified (p.Arg519Cys). Confirmatory tests were performed in five additional participants (four affected and one unaffected). CONCLUSION: The methodology used in this study, including the clinical pathway and bioinformatics pipeline, could be applied to other families affected by early-onset OA.

Identification of aging-related biomarkers and immune infiltration characteristics in osteoarthritis based on bioinformatics analysis and machine learning.

Background: Osteoarthritis (OA) is a degenerative disease closely related to aging. Nevertheless, the role and mechanisms of aging in osteoarthritis remain unclear. This study aims to identify potential aging-related biomarkers in OA and to explore the role and mechanisms of aging-related genes and the immune microenvironment in OA synovial tissue. Methods: Normal and OA synovial gene expression profile microarrays were obtained from the Gene Expression Omnibus (GEO) database and aging-related genes (ARGs) from the Human Aging Genomic Resources database (HAGR). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Disease Ontology (DO), and Gene set variation analysis (GSVA) enrichment analysis were used to uncover the underlying mechanisms. To identify Hub ARDEGs with highly correlated OA features (Hub OA-ARDEGs), Weighted Gene Co-expression Network Analysis (WGCNA) and machine learning methods were used. Furthermore, we created diagnostic nomograms and receiver operating characteristic curves (ROC) to assess Hub OA-ARDEGs' ability to diagnose OA and predict which miRNAs and TFs they might act on. The Single sample gene set enrichment analysis (ssGSEA) algorithm was applied to look at the immune infiltration characteristics of OA and their relationship with Hub OA-ARDEGs. Results: We discovered 87 ARDEGs in normal and OA synovium samples. According to functional enrichment, ARDEGs are primarily associated with inflammatory regulation, cellular stress response, cell cycle regulation, and transcriptional regulation. Hub OA-ARDEGs with excellent OA diagnostic ability were identified as MCL1, SIK1, JUND, NFKBIA, and JUN. Wilcox test showed that Hub OA-ARDEGs were all significantly downregulated in OA and were validated in the validation set and by qRT-PCR. Using the ssGSEA algorithm, we discovered that 15 types of immune cell infiltration and six types of immune cell activation were significantly increased in OA synovial samples and well correlated with Hub OA-ARDEGs. Conclusion: Synovial aging may promote the progression of OA by inducing immune inflammation. MCL1, SIK1, JUND, NFKBIA, and JUN can be used as novel diagnostic biomolecular markers and potential therapeutic targets for OA.

Proteoglycans in Articular Cartilage and Their Contribution to Chondral Injury and Repair Mechanisms.

Proteoglycans are vital components of the extracellular matrix in articular cartilage, providing biomechanical properties crucial for its proper functioning. They are key players in chondral diseases, specifically in the degradation of the extracellular matrix. Evaluating proteoglycan molecules can serve as a biomarker for joint degradation in osteoarthritis patients, as well as assessing the quality of repaired tissue following different treatment strategies for chondral injuries. Despite ongoing research, understanding osteoarthritis and cartilage repair remains unclear, making the identification of key molecules essential for early diagnosis and effective treatment. This review offers an overview of proteoglycans as primary molecules in articular cartilage. It describes the various types of proteoglycans present in both healthy and damaged cartilage, highlighting their roles. Additionally, the review emphasizes the importance of assessing proteoglycans to evaluate the quality of repaired articular tissue. It concludes by providing a visual and narrative description of aggrecan distribution and presence in healthy cartilage. Proteoglycans, such as aggrecan, biglycan, decorin, perlecan, and versican, significantly contribute to maintaining the health of articular cartilage and the cartilage repair process. Therefore, studying these proteoglycans is vital for early diagnosis, evaluating the quality of repaired cartilage, and assessing treatment effectiveness.

Identification of S100A8 as a common diagnostic biomarkers and exploring potential pathogenesis for osteoarthritis and metabolic syndrome.

Background: Osteoarthritis (OA) is the most frequent musculoskeletal disease and the major contributor to disability worldwide. Metabolic syndrome (MetS) has been recognized as being associated with the pathogenesis of osteoarthritis. However, the exact mechanisms and links between the two are not clear. Methods: We downloaded clinical information data and gene expression profiles for OA and MetS from the database of Gene Expression Omnibus (GEO), and immune related gene (IRG) from the database of Immunology Database and Analysis Portal (IMMPORT). After screening OA-DEG and MetS-DEG, we identified the common immune hub gene by screening the overlapping genes between OA-DEG, MetS-DEG and IRG. Then we conducted single-gene analysis of S100A8, assessed the correlation of S100A8 with immune cell infiltration, and verified the diagnostic value of S100A8 in OA and MetS database respectively. Results: 323 OA-DEGs,101 MetS-DEGs and an immune-related hub gene, S100A8, were identified. In single gene analysis of S100A8 in OA samples, GSEA suggested that immune-related biological processes were more significantly enriched. The results of immune cell infiltration analysis showed that the enrichment fraction of M2 macrophages was significantly higher in the high S100A8-expressing group, and the level of S100A8 expression was positively correlated with M2 macrophage infiltration. The results of the dataset validation showed that S100A8 expression levels were significantly upregulated in the OA group and performed well in the diagnosis of OA. In single gene analysis of S100A8 in MetS samples, immune cell infiltration analysis showed that monocyte infiltration was higher in the S100A8 high expression samples and that there was a positive correlation between the two. Dataset validation showed that S100A8 is of high value for the diagnosis of MetS. In the validation of the dataset for the four metabolism-related diseases (obesity, diabetes, hypertension and hyperlipidaemia), S100A8 was expressed at higher levels in the disease group and also had a higher diagnostic value for the four metabolism-related diseases. Conclusion: S100A8 is a common hub gene and diagnostic biomarker for OA and MetS, and the immune regulation involved in S100A8 may play a central role in the pathogenesis of OA and MetS.

The completely patient-reported version of the American Orthopaedic Foot and Ankle Society (AOFAS) score: A valid and reliable measurement for ankle osteoarthritis.

BACKGROUND: The American Orthopaedic Foot and Ankle score (AOFAS) is an outcome measure for ankle and hindfoot conditions, which requires scoring from both the patients and the physician. A completely patient-reported version has been developed and used before, but its measurements properties are unknown. Our goal was to determine the measurement properties and the minimally important change (MIC) of a completely patient-reported AOFAS (PR-AOFAS) in patients with ankle osteoarthritis. Additionally, the MIC of both the PR-AOFAS and the AOFAS was estimated, which had not previously been done. MATERIALS AND METHODS: The PR-AOFAS of 112 patients was evaluated for reliability, construct validity (using the AOFAS, Foot and Ankle Outcome Score, Ankle Osteoarthritis Score, Visual Analogue Scale, and Short Form-36), and responsiveness. The MIC was estimated using the optimal cut-off point of the receiver operating characteristic curve. This was a substudy of a randomized clinical trial on the efficacy of platelet-rich plasma injections for ankle osteoarthritis (OA). RESULTS: The PR-AOFAS had sufficient construct validity, internal consistency, test-retest reliability, and responsiveness. The smallest detectable change at group level was 2.34. The MIC was 6.5 points (95% confidence interval: 0.6-14.4). CONCLUSIONS: The measurement properties of the Dutch PR-AOFAS were sufficient in patients with ankle osteoarthritis who are willing to participate in a trial on injection therapy. The minimally important change of the PR-AOFAS is smaller than its smallest detectable change, making it more suitable for use in groups of patients, such as a research setting. LEVEL OF CLINICAL EVIDENCE: 1.

Identification of Novel Diagnostic Biomarkers and Classification Patterns for Osteoarthritis by Analyzing a Specific Set of Genes Related to Inflammation.

Osteoarthritis (OA) is a prevalent joint disease globally. TNFA is recognized as a crucial inflammatory cytokine that plays a significant role in the pathophysiological mechanisms that occur during the progression of OA. However, the TNFA_SIGNALING_VIA_NFKB (TSVN)-related genes (TRGs) during the progression of OA remain unclear. By conducting a combinatory analysis of OA transcriptome data from three datasets, various differentially expressed TRGs were identified. The logistic regression model was used to mine hub TRGs for OA, and a nomogram prediction model was subsequently constructed using these TRGs. To identify new molecular subgroups, we performed consensus clustering. We then conducted functional analyses, including GO, KEGG, GSVA, and GSEA, to elucidate the underlying mechanisms. To determine the immune microenvironment, we applied xCell. The logistic regression analysis identified three hub TRGs (BHLHE40, BTG2, and CCNL1) as potential biomarkers for OA. Based on these TRGs, we constructed an OA predictive model. This model has demonstrated promising results in enhancing the accuracy of OA diagnosis, as evident from the ROC analysis (AUC merged dataset = 0.937, AUC validating dataset = 0.924). We identified two molecular subtypes, C1 and C2, and found that the C1 subtype showed activation of immune- and inflammation-related pathways. The involvement of TSVN in the development and progression of OA has been established. We identified several hub genes, such as BHLHE40, BTG2, and CCNL1, that may have a significant association with the progression of OA. Furthermore, our logistic regression model based on these genes has shown promising results in accurately diagnosing OA patients.

Simultaneous hybrid closed-wedge supramalleolar osteotomy and ankle arthrodesis for post-traumatic varus ankle arthritis with periarticular deformity: A case report.

The treatment of end-stage ankle arthritis associated with extra-articular tibial deformity, especially for ankles deformed by previous traumatic injuries and/or surgical treatment, is extremely challenging but rewarding. Only one previous report describes simultaneous tibial deformity correction and ankle arthrodesis for tibial malalignment and ipsilateral ankle arthritis. Here, we describe a unique case of post-traumatic ankle osteoarthritis concomitant with extra-articular varus deformity in a 77-year-old female. We have combined medial opening-wedge supramalleolar osteotomy (SMO) and lateral closed-wedge SMO in this case, which we termed 'hybrid' closed-wedge SMO, to overcome the limitations of traditional closed-wedge SMO. The patient was successfully treated with simultaneous hybrid closed-wedge SMO and ankle arthrodesis using a single lateral locking plate. To our knowledge, this is the first report describing the successful introduction of a hybrid closed-wedge osteotomy procedure in the distal tibia. Three years after surgery, the patient could walk without assistance and swim normally. The patient experienced no discomfort or pain in the operated ankle and was satisfied with the results. Radiographs confirmed that the pre-existing ankle joint line was parallel to the ground and almost invisible. The hind foot alignment was slightly valgus. No progression of the subtalar joint arthritis was detected. The simultaneous hybrid closed-wedge SMO and ankle arthrodesis was technically difficult but effective. This technique preserves leg length and subtalar joint motion. Additionally, a single lateral incision minimises the risk of impaired blood supply. The one-stage surgical treatment reduces the recovery time, duration of hospitalisation, and surgical costs. Rigid locking fixation with careful postoperative weight-bearing is required for uneventful bone healing.