Metabolic syndrome, hypertension, and hyperglycemia were positively associated with knee osteoarthritis, while dyslipidemia showed no association with knee osteoarthritis

Identification of biomarkers for knee osteoarthritis through clinical data and machine learning models

Knee osteoarthritis (KOA) represents a progressive degenerative disorder characterized by the gradual erosion of articular cartilage. This study aimed to develop and validate biomarker-based predictive models for KOA diagnosis using machine learning techniques. Clinical data from 2594 samples were obtained and stratified into training and validation datasets in a 7:3 ratio. Key clinical features were identified through differential analysis between KOA and control groups, combined with least absolute shrinkage and selection operator (LASSO) regression. The SHapley Additive Planning (SHAP) method was employed to rank feature importance quantitatively. Based on these rankings, predictive models were constructed using Logistic Regression (LR), Random Forest (RF), eXtreme Gradient Boosting (xGBoost), Naive Bayes (NB), Support Vector Machine (SVM), and Decision Tree (DT) algorithms. Models were developed for subsets of variables, including the top 5, top 10, top 15, and all identified features. Receiver operating characteristic (ROC) curves were applied to compare diagnostic performance across models. Additionally, a risk stratification framework for KOA prediction was designed using recursive partitioning analysis (RPA). Using difference analysis and LASSO, 44 critical clinical features were identified. Among these, age, plasma prothrombin time, gender, body mass index (BMI), and prothrombin time and international normalized ratio (PTINR) emerged as the top five features, with SHAP values of 0.1990, 0.0981, 0.0471, 0.0433, and 0.0422, respectively. Machine learning analysis demonstrated that these variables provided robust diagnostic performance for KOA. In the training set, area under the curve (AUC) values for LR, RF, xGBoost, NB, SVM, and DT models were 0.947, 0.961, 0.892, 0.952, 0.885, and 0.779, respectively. Similarly, in the validation dataset, these models achieved AUC values of 0.961, 0.943, 0.789, 0.957, 0.824, and 0.76. Among them, RF consistently exhibited superior diagnostic accuracy for KOA. Additionally, RPA analysis indicated a higher prevalence of KOA among individuals aged 54 years and older. The integration of the top five clinical variables significantly enhanced the diagnostic accuracy for KOA, particularly when employing the RF model. Moreover, the RPA model offered valuable insights to assist clinicians in refining prognostic assessments and optimizing clinical decision-making processes.

Obesity and hyperlipidemia were associated with more severe synovitis and structural abnormalities as well as inferior functional outcomes in knee osteoarthritis: a retrospective comparative study

BACKGROUND

Considering that the respective effects of obesity and hyperlipidemia on knee osteoarthritis (OA) have not been fully investigated, the purpose of this study was to determine the relationship of obesity or hyperlipidemia with the synovitis and structural abnormalities of knee OA, and the effect of obesity and hyperlipidemia on functional outcomes of total knee arthroplasty.

METHODS

There were 99 OA patients without obesity and hyperlipidemia in Group 1, 100 OA patients only with obesity in Group 2, 98 OA patients only with hyperlipidemia in Group 3, and 97 OA patients with both obesity and hyperlipidemia in Group 4. Semi-quantitative synovial inflammatory markers were measured including effusion-synovitis, size and intensity of infrapatellar fat pad abnormality, and synovial proliferation score. The structural abnormalities of knee OA were evaluated using Whole-Organ Magnetic Resonance Imaging Score (WORMS). Functional outcomes were evaluated before surgery and at 2 years follow-up.

RESULTS

There were significantly higher effusion-synovitis, size and intensity of infrapatellar fat pad abnormality, and synovial proliferation score, as well as higher cartilage, bone marrow edema, meniscus, and total WORMS scores in Group 2, Group 3, and Group 4 (P < 0.05), but with no significant difference between Group 2 and Group 3 (P > 0.05). Group 2, Group 3, Group 4 had significantly worse Western Ontario and McMaster Universities Osteoarthritis Index, Forgotten Joint Score, Oxford Knee Score, Knee Society Score at baseline and 2 years follow-up (P < 0.05), but with no significant difference between Group 2 and Group 3 (P > 0.05). There were significant associations of obesity or hyperlipidemia with all synovial inflammatory markers and cartilage, bone marrow edema, meniscus, and total WORMS scores as well as functional outcomes (P < 0.05).

CONCLUSIONS

Obesity and hyperlipidemia were associated with more severe synovitis and structural abnormalities of knee OA, as well as inferior preoperative and postoperative functional outcomes. The negative effects of obesity and hyperlipidemia on knee OA could be mutually enhanced. The findings emphasized the negative effects of obesity and hyperlipidemia on the symptoms and outcomes of knee OA, and highlighted the association of obesity and hyperlipidemia with synovitis.

Novel insights into the role of metabolic disorder in osteoarthritis

Osteoarthritis (OA) is a prevalent condition that affects individuals worldwide and is one of the leading causes of disability. Nevertheless, the underlying pathological mechanisms of OA remain inadequately understood. Current treatments for OA include non-drug therapies, pharmacological interventions, and surgical procedures. These treatments are mainly focused on alleviating clinical manifestations and improving patients' quality of life, but are not effective in limiting the progression of OA. The detailed understanding of the pathogenesis of OA is extremely significant for the development of OA treatment. Metabolic syndrome has become a great challenge for medicine and public health, In recent years, several studies have demonstrated that the metabolic syndrome and its individual components play a crucial role in OA. Consequently, this review summarizes the mechanisms and research progress on how metabolic syndrome and its components affect OA. The aim is to gain a deeper understanding of the pathogenesis of OA and explore effective treatment strategies.

Causal relationship between modifiable risk factors and knee osteoarthritis: a Mendelian randomization study

Background

While several risk factors for knee osteoarthritis (KOA) have been recognized, the pathogenesis of KOA and the causal relationship between modifiable risk factors and KOA in genetic epidemiology remain unclear. This study aimed to determine the causal relationship between KOA and its risk factors.

Methods

Data were obtained from published Genome-Wide Association study (GWAS) databases. A two-sample Mendelian randomization (MR) analysis was performed with genetic variants associated with risk factors as instrumental variables and KOA as outcome. First, inverse variance weighting was used as the main MR analysis method, and then a series of sensitivity analyses were conducted to comprehensively evaluate the causal relationship between them.

Results

Univariate forward MR analysis revealed that genetically predicted hypothyroidism, hyperthyroidism/thyrotoxicosis, educational level, income level, metabolic syndrome (MS), essential hypertension, height, hot drink temperature, diet (abstaining from sugar-sweetened or wheat products), and psychological and psychiatric disorders (stress, depression, and anxiety) were causally associated with KOA. Reverse MR exhibits a causal association between KOA and educational attainment. Multivariate MR analysis adjusted for the inclusion of potential mediators, such as body mass index (BMI), smoking, alcohol consumption, and sex, exhibited some variation in causal effects. However, hyperthyroidism/thyrotoxicosis had a significant causal effect on KOA, and there was good evidence that height, hypothyroidism, educational level, psychological and psychiatric disorders (stress, depression, and anxiety), and abstaining from wheat products had an independent causal relationship. The mediating effect of BMI as a mediator was also identified.

Conclusion

This study used MR to validate the causal relationship between KOA and its risk factors, providing new insights for preventing and treating KOA in clinical practice and for developing public health policies.

Non-pharmacological and non-surgical interventions to manage patients with knee osteoarthritis: An umbrella review 5-year update

Objective

This umbrella review aimed to summarize (and update) the effectiveness of non-pharmacological and non-surgical interventions for patients with knee osteoarthritis.

Methods

The study followed the PRISMA guidelines. Manual and electronic databases were searched, to identify systematic reviews, following the P (knee osteoarthritis) I (non-pharmacological and non-surgical treatments) C (pharmacological, surgical, placebo, no intervention, or other non-pharmacological/non-surgical conservative treatments) O (pain, function, quality of life, and other knee-specific measures) model. The quality of evidence was assessed using the R-AMSTAR checklist and GRADE principles.

Results

The search yielded 4086 records, of which 61 met the eligibility criteria. After evaluation with R-AMSTAR, four systematic reviews were excluded, resulting in 57 included systematic reviews, with an overall score of 29.6. The systematic reviews were published between 2018 and 2022 (29.8% in 2022), conducted in 19 countries (52.6% in China), and explored 24 distinct interventions. The systematic reviews encompassed 714 trials (mean of 13 ​± ​7.7 studies per systematic review), and 59,343 participants (mean 1041 ​± ​1002 per systematic review, and 82 ​± ​59.2 per study). The majority of participants were older obese women (61.6 ​± ​4.2 years, 30.2 ​± ​3.6 ​kg/m2, 70%, respectively).

Conclusions

Based on the systematic reviews findings, Diet Therapy, Patient Education, and Resistance Training are strongly supported as core interventions for managing patients with knee osteoarthritis. Aquatic Therapy, Balance Training, Balneology, Dietary Supplements, Extracorporeal Shockwave Therapy, and Tai Ji show moderate support. For other interventions, the evidence quality was low, results were mixed or inconclusive, or there was not sufficient efficacy to support their use.

Machine learning analysis of serum cholesterol's impact on knee osteoarthritis progression

The controversy surrounding whether serum total cholesterol is a risk factor for the graded progression of knee osteoarthritis (KOA) has prompted this study to develop an authentic prediction model using a machine learning (ML) algorithm. The objective was to investigate whether serum total cholesterol plays a significant role in the progression of KOA. This cross-sectional study utilized data from the public database DRYAD. LASSO regression was employed to identify risk factors associated with the graded progression of KOA. Additionally, six ML algorithms were utilized in conjunction with clinical features and relevant variables to construct a prediction model. The significance and ranking of variables were carefully analyzed. The variables incorporated in the model include JBS3, Diabetes, Hypertension, HDL, TC, BMI, SES, and AGE. Serum total cholesterol emerged as a significant risk factor for the graded progression of KOA in all six ML algorithms used for importance ranking. XGBoost algorithm was based on the combined best performance of the training and validation sets. The ML algorithm enables predictive modeling of risk factors for the progression of the KOA K-L classification and confirms that serum total cholesterol is an important risk factor for the progression of KOA.

Metabolic syndrome and arthritis among Mexican American older adults: findings from a 23-year follow-up

PURPOSE

To examine the sex differences in the relationship of metabolic syndrome (MetS) criteria with arthritis and symptomatic arthritis among Mexican American older adults aged ≥ 65 without self-reported arthritis at baseline over 23-years of follow-up.

METHODS

Participants (N = 1447) were from the Hispanic Established Population for the Epidemiologic Study of the Elderly (1993/94-2016). Measures included MetS criteria, arthritis defined as self-reported physician-diagnosed arthritis, socio-demographics, morbidities, depressive symptoms, pain on weight-bearing, cognitive and physical function, handgrip strength, mobility, and activities of daily living (ADLs) limitations. Symptomatic arthritis was defined as self-reported arthritis and having ≥ 1 of the following: pain, mobility limitation, or limited ADLs.

RESULTS

At baseline, the mean age was 72.6 years and 730 (50.5%) of our participants were females. Female participants with 2 and 3 MetS criteria had greater odds of arthritis [odds ratio (OR) = 1.77, 95% Confidence Interval (Cl) = 1.28-2.45 and OR = 2.68, 95% CI = 1.69-4.27, respectively) and symptomatic arthritis (OR = 1.74, 95% Cl = 1.24-2.44 and OR = 3.27, 95% CI = 2.04-5.26, respectively) after controlling for covariates. Male participants with 2 and 3 MetS criteria had greater odds of arthritis (OR = 1.65, 95% Cl = 1.14-2.39 and OR = 2.52, 95% CI = 1.51-4.19, respectively) and symptomatic arthritis (OR = 1.93, 95% Cl = 1.30-2.86 and OR = 2.98, 95% CI = 1.62-5.47, respectively) after controlling for covariates. Both females and males with pain on weight-bearing had greater odds of arthritis than those without pain.

CONCLUSIONS

At 23-years of follow-up, Mexican American older adults with MetS have an increased risk of arthritis and symptomatic arthritis. Early MetS screening and management may reduce arthritis in this population at high risk of disability.

Blood pressure is associated with knee pain severity in middle-aged and elderly individuals with or at risks for osteoarthritis: data from the Osteoarthritis Initiative

BACKGROUND

Hypertension is a common comorbidity of osteoarthritis (OA). Joint pain is the main clinical manifestation of OA. Knowledge about the relationship between hypertension and OA pain is limited. This study aimed to investigate whether blood pressure parameters are associated with knee pain severity in individuals with or at risks for OA.

METHODS

Our sample consisted of 2598 subjects (60.7% female, aged 45-79 years) collected from the Osteoarthritis Initiative. Blood pressure parameters included blood pressure stage, systolic blood pressure (SBP), diastolic blood pressure (DBP) and pulse pressure (PP). Radiographic evaluation using Kellgren-Lawrence system and pain severity evaluation using Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Knee Injury and Osteoarthritis Outcome Score (KOOS), and Numeric Rating Scale (NRS) were performed for right knee. Linear regression was used to examine the relationship between blood pressure parameters and knee pain severity.

RESULTS

For the overall sample, blood pressure stage, SBP, and PP were positively correlated with WOMAC and NRS pain scores when adjusting for age, sex, and body mass index (BMI) (p ≤ 0.024) and were inversely correlated with KOOS score (p ≤ 0.004). After further adjusting for all covariates, PP remained a positive correlation with WOMAC score (p = 0.037) while other associations between blood pressure parameters and pain scores did not reach the statistical significance. In female, higher blood pressure stage, SBP, and PP were significantly associated with increased WOMAC and NRS scores and decreased KOOS score after adjustments of age and BMI (p ≤ 0.018). When adjusting for all covariates, the correlations of PP with WOMAC, KOOS and NRS scores remained significant (p = 0.008-0.049). In male sample, SBP was positively correlated with WOMAC score when adjusting for age and BMI (p = 0.050), but other associations between blood pressure parameters and pain scores were not statistically significant. No significant correlation was observed in male when further adjusting for other covariates.

CONCLUSIONS

Increased PP is a risk factor for knee pain and mainly affects females, which suggested that controlling PP may be beneficial in preventing or reducing knee pain in females with or at risks for OA.

[Relationship between hypercholesterolemia and osteoarthritis (preliminary results)]

AIM

To evaluate the relationship of hypercholesterolemia (HCE) with clinical, instrumental, and laboratory parameters in osteoarthritis (OA) in a multicenter, cross-sectional study.

MATERIALS AND METHODS

The study included 183 patients aged 40-75 years, with a confirmed diagnosis of stage I-III OA (ACR) of the knee joints, who signed an informed consent. The mean age was 55.6±10.7 years (40 to 75), body mass index was 29.3±6.3 kg/m2, and disease duration was 5 [1; 10] years. For each patient, a case record form was filled out, including anthropometric indicators, medical history, clinical examination data, an assessment of knee joint pain according to VAS, WOMAC, KOOS and comorbidities. All patients underwent standard radiography and ultrasound examination of the knee joints and laboratory tests.

RESULTS

HCE was detected in 59% of patients. Depending on its presence or absence, patients were divided into two groups. Patients were comparable in body mass index, waist and hip measurement, and disease duration but differed significantly in age. Individuals with elevated total cholesterol levels had higher VAS pain scores, total WOMAC and its components, an overall assessment of the patient's health, a worse KOOS index, and ultrasound findings (reduced cartilage tissue). HCE patients showed high levels of cholesterol, low-density lipoproteins, triglycerides, STX-II, and COMP (p<0.05). However, after stratification by age, many initial intergroup differences became insignificant, and differences in the WOMAC pain score persisted.

CONCLUSION

The results of the study confirmed the high prevalence of HCE in OA patients (59%). Patients with OA and increased total cholesterol have more intense pain in the knee joints.

Identification of biomarkers and immune infiltration characterization of lipid metabolism-associated genes in osteoarthritis based on machine learning algorithms

Osteoarthritis (OA) is a prevalent degenerative condition commonly observed in the elderly, leading to consequential disability. Despite notable advancements made in clinical strategies for OA, its pathogenesis remains uncertain. The intricate association between OA and metabolic processes has yet to receive comprehensive exploration. In our investigation, we leveraged public databases and applied machine learning algorithms, including WGCNA, LASSO, RF, immune infiltration analysis, and pathway enrichment analysis, to scrutinize the role of lipid metabolism-associated genes (LAGs) in the OA. Our findings identified three distinct biomarkers, and evaluated their expression to assess their diagnostic value in the OA patients. The exploration of immune infiltration in these patients revealed an intricate relationship between immune cells and the identified biomarkers. In addition, in vitro experiments, including qRT-PCR, Western blot, chondrocyte lipid droplets detection and mitochondrial fatty acid oxidation measurement, further verified abnormal expressions of selected LAGs in OA cartilage and confirmed the correlation between lipid metabolism and OA.

Phenome-wide causal associations between osteoarthritis and other complex traits through the latent causal variable analysis

BACKGROUND

Individuals with osteoarthritis present with comorbidities, and the potential causal associations remain incompletely elucidated. The present study undertook a large-scale investigation about the causality between osteoarthritis and variable traits, using the summary-level data of genome-wide association studies (GWAS).

METHODS

The present study included the summary-level GWS data of knee osteoarthritis, hip osteoarthritis, hip or knee osteoarthritis, hand osteoarthritis, and other 1355 traits. Genetic correlation analysis was conducted between osteoarthritis and other traits through cross-trait bivariate linkage disequilibrium score regression. Subsequently, latent causal variable analysis was performed to explore the causal association when there was a significant genetic correlation. Genetic correlation and latent causal variable analysis were conducted on the Complex Traits Genomics Virtual Lab platform ( https://vl.genoma.io/ ).

RESULTS

We found 133 unique phenotypes showing causal relationships with osteoarthritis. Our results confirmed several well-established risk factors of osteoarthritis, such as obesity, weight, BMI, and meniscus derangement. Additionally, our findings suggested putative causal links between osteoarthritis and multiple factors. Socioeconomic determinants such as occupational exposure to dust and diesel exhaust, extended work hours exceeding 40 per week, and unemployment status were implicated. Furthermore, our analysis revealed causal associations with cardiovascular and metabolic disorders, including heart failure, deep venous thrombosis, type 2 diabetes mellitus, and elevated cholesterol levels. Soft tissue and musculoskeletal disorders, such as hallux valgus, internal derangement of the knee, and spondylitis, were also identified to be causally related to osteoarthritis. The study also identified the putative causal associations of osteoarthritis with digestive and respiratory diseases, such as Barrett's esophagus, esophagitis, and asthma, as well as psychiatric conditions including panic attacks and manic or hyperactive episodes. Additionally, we observed osteoarthritis causally related to pharmacological treatments, such as the use of antihypertensive medications, anti-asthmatic drugs, and antidepressants.

CONCLUSION

Our study uncovered a wide range of traits causally associated with osteoarthritis. Further studies are needed to validate and illustrate the detailed mechanism of those causal associations.

The effect of ellagic acid on the metabolic syndrome: A review article

Objective

(s): Metabolic syndrome is a collection of metabolic abnormalities that includes hyperglycemia, dyslipidemia, hypertension, and obesity. Ellagic acid is found in various fruits and vegetables. It has been reported to have several pharmacological properties, such as antibacterial, antifungal, antiviral, anti-inflammatory, hepatoprotective, cardioprotective, chemopreventive, neuroprotective, gastroprotective, and antidiabetic. Our current study aims to shed light on the probable efficiency of ellagic acid in managing metabolic syndrome and its complications.

Materials and methods

To prepare the present review, the databases or search engines utilized included Scopus, PubMed, Science Direct, and Google Scholar, and relevant articles have been gathered with no time limit until March 2023.

Results

Several investigations indicated that ellagic acid could be a potent compound for the treatment of many disorders such as diabetes, hypertension, and hyperlipidemia by various mechanisms, including increasing insulin secretion, insulin receptor substrate protein 1 expression, regulating glucose transporter 4, triglyceride, total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), attenuating tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), reactive oxygen species (ROS), malondialdehyde (MDA), and oxidative stress in related tissues. Furthermore, ellagic acid ameliorates mitochondrial function, upregulates uncoupling protein 1 (found in brown and white adipose tissues), and regulates blood levels of nitrate/nitrite and vascular relaxations in response to acetylcholine and sodium nitroprusside.

Conclusion

Ellagic acid can treat or manage metabolic syndrome and associated complications, according to earlier studies. To validate the beneficial effects of ellagic acid on metabolic syndrome, additional preclinical and clinical research is necessary.

Leptin and interleukin-1β levels associated with osteoarthritis in Vietnamese patients: a cross-sectional analysis

Leptin and interleukin-1 beta (IL-1β) are two extensively studied biomarkers associated with metabolic syndrome (MetS) and osteoarthritis (OA). Previous studies have mostly focused on either MetS or OA alone, with no available data on Vietnamese patients. This study aimed to investigate the levels of leptin and IL-1β in this patient population and explore their association with clinical parameters of MetS and OA. The study included 164 patients with primary knee OA, who were classified into two categories based on the presence of MetS, and 78 healthy controls. The plasma leptin and IL-1β levels were quantified by ELISA and correlated with clinical parameters. Leptin levels were higher in patients with OA (11.50±10.04 ng/mL) than in healthy controls (0.54±0.37 ng/mL) and increased in patients with MetS compared to those without MetS. IL-1β levels were also significantly higher in OA patients (14.63±15.87 pg/mL) than in controls (7.79±5.11 pg/mL), but were not significantly different between the MetS and non-MetS groups. Leptin levels were positively correlated with body mass index, waist-to-hip ratio, visual analogue scale scores, HbA1c and insulin levels, and HOMA-IR index, whereas IL-1β levels were only correlated with insulin levels and HOMA-IR index. ROC curve analysis revealed that leptin and IL-1β levels could distinguish individuals with and without OA (AUC=0.96; 0.88, respectively), and individuals with and without MetS (AUC=0.82; 0.71, respectively). Our findings suggested that both leptin and IL-1β levels were associated with both MetS and OA and may play a critical role in the pathogenesis of MetS-related OA.

Comorbidity in incident osteoarthritis cases and matched controls using electronic health record data

BACKGROUND

Comorbidities are common in patients with osteoarthritis (OA). This study aimed to determine the association of a wide range of previously diagnosed comorbidities in adults with newly diagnosed OA compared with matched controls without OA.

METHODS

A case-control study was conducted. The data were derived from an electronic health record database that contains the medical records of patients from general practices throughout the Netherlands. Incident OA cases were defined as patients with one or more diagnostic codes recorded in their medical records that correspond to knee, hip, or other/peripheral OA. Additionally, the first OA code had to be recorded between January 1, 2006, and December 31, 2019. The date of cases' first OA diagnosis was defined as the index date. Cases were matched (by age, sex, and general practice) to up to 4 controls without a recorded OA diagnosis. Odds ratios were derived for each 58 comorbidities separately by dividing the comorbidity prevalence of cases by that of their matched controls at the index date.

RESULTS

80,099 incident OA patients were identified of whom 79,937 (99.8%) were successfully matched with 318,206 controls. OA cases had higher odds for 42 of the 58 studied comorbidities compared with matched controls. Musculoskeletal diseases and obesity showed large associations with incident OA.

CONCLUSIONS

Most of the comorbidities under study had higher odds in patients with incident OA at the index date. While previously known associations were confirmed in this study, some associations were not described earlier.

Beyond mechanical loading: The metabolic contribution of obesity in osteoarthritis unveils novel therapeutic targets

Osteoarthritis (OA) is a prevalent progressive disease that frequently coexists with obesity. For several decades, OA was thought to be the result of ageing and mechanical stress on cartilage. Researchers' perspective has been greatly transformed when cumulative findings emphasized the role of adipose tissue in the diseases. Nowadays, the metabolic effect of obesity on cartilage tissue has become an integral part of obesity research; hoping to discover a disease-modifying drug for OA. Recently, several adipokines have been reported to be associated with OA. Particularly, metrnl (meteorin-like) and retinol-binding protein 4 (RBP4) have been recognized as emerging adipokines that can mediate OA pathogenesis. Accordingly, in this review, we will summarize the latest findings concerned with the metabolic contribution of obesity in OA pathogenesis, with particular emphasis on dyslipidemia, insulin resistance and adipokines. Additionally, we will discuss the most recent adipokines that have been reported to play a role in this context. Careful consideration of these molecular mechanisms interrelated with obesity and OA will undoubtedly unveil new avenues for OA treatment.

An Integrated View of Stressors as Causative Agents in OA Pathogenesis

Cells in the body are exposed to dynamic external and internal environments, many of which cause cell damage. The cell's response to this damage, broadly called the stress response, is meant to promote survival and repair or remove damage. However, not all damage can be repaired, and sometimes, even worse, the stress response can overtax the system itself, further aggravating homeostasis and leading to its loss. Aging phenotypes are considered a manifestation of accumulated cellular damage and defective repair. This is particularly apparent in the primary cell type of the articular joint, the articular chondrocytes. Articular chondrocytes are constantly facing the challenge of stressors, including mechanical overloading, oxidation, DNA damage, proteostatic stress, and metabolic imbalance. The consequence of the accumulation of stress on articular chondrocytes is aberrant mitogenesis and differentiation, defective extracellular matrix production and turnover, cellular senescence, and cell death. The most severe form of stress-induced chondrocyte dysfunction in the joints is osteoarthritis (OA). Here, we summarize studies on the cellular effects of stressors on articular chondrocytes and demonstrate that the molecular effectors of the stress pathways connect to amplify articular joint dysfunction and OA development.

Pathogenetic features of cardiovascular pathology in patients with osteoarthritis

Cardiovascular pathology occupies a leading place among all causes of death and permanent disability of the population. In recent years, there has been an increase in the number of cardiovascular comorbidity cases, which leads to a significant deterioration in the quality of life, difficulties in the selection of therapy and a worse prognosis. Cardiorheumatology is an actual and actively discussed direction in this area. One of the most common rheumatic pathologies is osteoarthritis. Researchers identify a number of factors aggravating the course of cardiovascular pathology in the presence of osteoarthritis: regular intake of non-steroidal antiinflammatory drugs, chronic pain syndrome, decreased mobility. The review provides current data on the problem under discussion, in particular, the current understanding of pathogenetic relationships. The issues of safety of non-steroidal anti-inflammatory drugs in cardiovascular patients are highlighted. The potential of using modern immunological cytokines in this group of patients are described using the example of galectin-3 as a marker of prognosis.

Osteoarthritis year in review 2022: epidemiology & therapy

This 'Year in Review' provides a synopsis of key research themes and individual studies from the clinical osteoarthritis (OA) field, focused on epidemiology and therapy. The electronic database search for the review was adapted from the 2021 year in review search, to increase search specificity for relevant study designs, and was conducted in Medline, Embase and medRxiv (31^st March 2021 to 4^th March 2022). Following screening for eligibility, studies were grouped according to their key research design, including reviews, cohorts and randomised trials. 11 key themes emerged, including the importance of several comorbidities in predicting OA incidence and prevalence, surgical approaches that can reduce the risk of post-traumatic OA, the heterogenous but nevertheless relatively stable nature of OA subgroup trajectories, the paucity of robust studies particularly of surgery for OA and the very modest benefit of many therapies under evaluation in trials. A particular interest of the authors was to consider whether new studies are helping determine how to better ensure the right patient with OA is matched to the right treatment at the right time. There are several new studies developing improved predictive models through big data analytics and machine learning which show promise, need validation, and may support new approaches to stratified care.

DHDIP: An interpretable model for hypertension and hyperlipidemia prediction based on EMR data

BACKGROUND AND OBJECTIVE

Traditional hypertension and hyperlipidemia prediction models suffer from uneven modeling data sources, small sample sizes, and a lack of uniform standards for the index system, resulting in the model failing to fulfill clinical applications. To address this issue, this work will offer DHDIP, an interpretable hypertension and hyperlipidemia prediction model based on EMR data.

METHODS

First, we will select massive high-dimensional, unstructured EMR data as a unified modeling data source, and propose a pre-processing algorithm for EMR data to solve the problem that EMR data cannot be directly processed by machine learning algorithms. Second, a variety of mainstream models such as XGBoost, CatBoost, and RandomForest are selected for modeling, and the best adaptation algorithms are identified by performance comparison. Finally, the SHAP framework was introduced into the DHDIP model, thus identifying the main factors contributing to hypertension and hyperlipidemia, effectively enhancing the interpretability of the model.

RESULTS

The DHDIP model's MSE value is 0.0285, and its LOSS value is 0.0054, both of which are better than previous studies.

CONCLUSION

The model balances performance and interpretability. Multi-objective learning allows for a more thorough analysis and prediction of the condition, which not only lowers the cost of disease prediction but also aids physicians in clinical diagnosis. In addition, the datasets and source code are available from this link: https://github.com/Xiaoyao-Jia/DHDIP.

Association Between History of Gestational Diabetes Mellitus and the Risk of Arthritis in Women

Objective

The association between gestational diabetes mellitus (GDM) and the risk of arthritis has not been reported. GDM increases the risk of long-term complications including diabetes and metabolic syndrome that are positively associated with the risk of arthritis. This study aimed to explore the association between GDM and the risk of arthritis.

Methods

Women (age ≥ 20 years) who had delivered at least one live birth were included from the 2007 to 2018 National Health and Nutrition Examination Survey cohort (N = 11,997). Patients who had a history of GDM and arthritis were identified by in-home interview. Subgroup analyses were conducted by arthritis types and status of obesity, current diabetes, metabolic syndrome, smoking, alcohol drinking, and physical activity.

Results

GDM was associated with increased odds of arthritis [multivariable-adjusted odds ratio (95% confidence interval): 1.31 (1.06–1.62)], and the result was similar in sensitivity analysis with further adjustment for metabolic syndrome [1.30 (1.05–1.60)]. In subgroup analyses, GDM was associated with increased odds of osteoarthritis [1.47 (1.05–2.06)], while no association was observed with rheumatoid arthritis [1.04 (0.69–1.57)] and other types [1.26 (0.94–1.68)]. GDM was associated with increased odds of arthritis in women without metabolic syndrome [1.34 (1.00–1.78)] and diabetes [1.35 (1.03–1.76)], in obese individuals [1.64 (1.24–2.16)], current/former smokers [1.43 (1.05–1.95)], and current drinkers [1.76 (1.00–3.14)], and in individuals engaging in higher levels of physical activity [1.53 (1.06–2.20)].

Conclusions

GDM was associated with increased odds of arthritis, and the association was independent of type 2 diabetes and metabolic syndrome.

Promoting Sports Practice in Persons with Hemophilia: A Survey of Clinicians' Perspective

Historically, people with hemophilia have been warned to avoid physical activities as a possible cause of bleeding; however, currently, sport is considered necessary, especially in the developmental age, for providing a good quality of life. A survey was proposed to a group of hematologists and sports physicians working in Puglia, Italy, to explore their approach to physical activities for their patients with hemophilia and to obtain suggestions about possible interventions to promote the access of patients to sports. The survey was answered by 6 hematologists and 15 sports physicians. In total, 71% (about six patients/year/physician) of patients with hemophilia seen by sports physicians asked for counseling about sports, and 67% (about five patients/year/physician) actually practiced sports. On the other hand, only 31% (about 16 patients/year/hematologist) of patients asked hematologists questions on sports, and only 16% (about seven patients/year/hematologist) of patients with hemophilia and that were followed-up by hematologists practiced sports. The sports most often recommended to patients with hemophilia by physicians included swimming, athletics, tennis, running and gymnastics. According to hematologists, physical activity was very efficient in improving the quality of life of patients; stability of joints; their psychological, social and musculoskeletal wellbeing; and in reducing the risk of bleedings. On the other hand, physical activity was considered less important in all these areas by sport physicians. In conclusion, answers to this survey suggested that sports could be promoted among hemophilic patients by increasing the sports physicians' knowledge about hemophilia and their special role in this area. In addition, interviewed clinicians were of the opinion that increased awareness of specific guidelines and clinical practice protocols among both hematologists and sports physicians could be beneficial. Finally, answers suggested that access to fitness certification should be facilitated.

Extracellular vesicles as novel approaches for the treatment of osteoarthritis: a narrative review on potential mechanisms

Osteoarthritis (OA) is a progressive degeneration of articular cartilage with involvement of synovial membrane, and subchondral bone. Current treatment approaches have focused on controlling the OA symptoms, pain, and inflammation. Recently, cell-based therapies, including the application of stem cells such as mesenchymal stem cells (MSCs), have been introduced for restoration of the articular cartilage. Despite promising outcomes, there are some limitations in the application of MSCs for OA treatment. It has been demonstrated that the regenerative potential of stem cells is related to the production of paracrine factors. Extracellular vehicles (EVs), the main component of cell secretome, are membrane-bounded structures that deliver biologically active agents. The delivery of molecules (e.g., nucleic acids, proteins, and lipids) leads to cell-to-cell communication and the alteration of cell functions. In this review, general characteristics of EVs, as well as their potential mechanisms in the prevention and treatment of OA were considered. Based on in vitro and in vivo studies, EVs have shown to contribute to cartilage regeneration via suppression of degenerative factors and regulation of chondrocyte function in the synthesis of extracellular matrix components. Also, they inhibit the progression of OA or protect the cartilage from degradation via their impact on inflammatory cytokines. The different signaling pathways of EVs against the pathologic features of OA were summarized in this review. According to the results obtained from several investigations, more investigations should be design to prove the safety and effectiveness of EVs in the treatment and prevention of OA progression.

Hypertension meets osteoarthritis - revisiting the vascular aetiology hypothesis

Osteoarthritis (OA) is a whole-joint disease characterized by subchondral bone perfusion abnormalities and neovascular invasion into the synovium and articular cartilage. In addition to local vascular disturbance, mounting evidence suggests a pivotal role for systemic vascular pathology in the aetiology of OA. This Review outlines the current understanding of the close relationship between high blood pressure (hypertension) and OA at the crossroads of epidemiology and molecular biology. As one of the most common comorbidities in patients with OA, hypertension can disrupt joint homeostasis both biophysically and biochemically. High blood pressure can increase intraosseous pressure and cause hypoxia, which in turn triggers subchondral bone and osteochondral junction remodelling. Furthermore, systemic activation of the renin-angiotensin and endothelin systems can affect the Wnt-β-catenin signalling pathway locally to govern joint disease. The intimate relationship between hypertension and OA indicates that endothelium-targeted strategies, including re-purposed FDA-approved antihypertensive drugs, could be useful in the treatment of OA.

Polycystic ovary syndrome and (pre)osteoarthritis: assessing the link between hyperandrogenism in young women and cartilage oligomeric matrix protein as a marker of cartilage breakdown

INTRODUCTION

OBJECTIVES: Our aim was to analyze the link between hyperandrogenism and early clinical manifestations of osteoarthritis (OA), knee cartilage thickness, and serum cartilage oligomeric matrix protein (sCOMP) levels in patients with polycystic ovary syndrome (PCOS) and to compare them with healthy volunteers.

METHODS

Fifty-four PCOS patients who met the Rotterdam criteria with phenotypes A, B, and C were included. They were compared with 26 age- and body mass index (BMI)-matched controls. Detailed anthropometric measurements and clinical evaluation for hyperandrogenism were performed for all participants who also filled in the Knee Injury and Osteoarthritis Outcome Score (KOOS) questionnaire. Furthermore, laboratory tests including sCOMP and hormone quantification were performed in a fasting stage. Finally, an ultrasound assessment was carried out in randomly selected 56 study participants.

RESULTS

PCOS women reported more prominent knee-related symptoms (p = 0.035) and more impaired activities of daily living (ADL) (p = 0.001) than controls. Cartilage thickness of the left and right medial condyle and left lateral condyle was significantly greater in PCOS group (n = 41) than in control group (n = 15) (p = 0.05, p = 0.006, and p = 0.036, respectively). COMP correlated significantly and negatively with testosterone levels (p = 0.029, r =  - 0.297) in women with PCOS and the correlation remained significant after controlling for BMI.

CONCLUSIONS

Women with PCOS may experience knee-related symptoms and impaired ADL. They had greater knee femoral cartilage thickness. Although sCOMP levels did not significantly differ between the groups, lower levels of sCOMP may be inherent to PCOS patients with higher testosterone levels. Key Points • Although PCOS patients may experience more prominent knee related symptoms, their femoral cartilage of the knee joint is found thicker than controls. • PCOS patients did not have significantly elevated levels of sCOMP. • Lower sCOMP levels were related to higher testosterone levels.