Risk Of Knee Osteoarthritis Research Articles

Causal associations of anthropometric measurements with osteoarthritis: A Mendelian randomization study.

We believe that there is a causal relationship between waist circumference and knee osteoarthritis. To confirm the hypothesis, we have conducted this study. Genetic variants associated with the five anthropometric variables were obtained from previous large-scale genomewide association studies. Summary-level data on osteoarthritis were obtained from the UK Biobank. The univariable and multivariable MR framework were used to evaluate the associations. The two-sided p value was considered to be statistically significant at 0.01 (where p = 0.05/5) after Bonferroni correction for the five exposure variables. In the univariable MR, there was evidence of a detrimental effect of height, weight, BMI, waist circumference, and hip circumference on osteoarthritis risk in the main IVW analyses (height: OR 1.115, 95% CI 1.054-1.180; weight: OR 1.765, 95% CI 1.650-1.889; BMI: OR 1.952, 95%CI 1.841-2.068; waist circumference: OR 2.140, 95% CI 1.994-2.296; hip circumference: OR 1.719, 95% CI 1.600-1.846). And the analyses on knee osteoarthritis and hip osteoarthritis yielded similar results. However, the multivariable MR showed that only waist circumference was causally associated with osteoarthritis, after adjusting for the confounding exposure effects (waist circumference: OR 1.877, 95% CI 1.286-2.739). Such association was also repeated in the analyses on knee osteoarthritis but not hip osteoarthritis. Our study highlighted the causal associations between waist circumference and knee osteoarthritis risk.

Comment on: Whole grain consumption and risk of radiographic knee osteoarthritis: a prospective study from the Osteoarthritis Initiative.

Dear Editor, We read the recent publication by Liu et al. with great interest [1]. They provided a possible dietary intervention for the prevention of radiographic OA of the knee for people at risk for OA. The researchers showed an inverse association between the risk of developing radiographic knee OA and whole grain consumption in their prospective cohort study. Evidence contributing to the prevention of OA has great value, because it is difficult to manage symptoms related to clinical OA, especially since the prevalence of OA is increasing and more and more people struggle with OA due to increasing obesity and prolonged life expectancy [2]. Even though we appreciate the work of Liu et al. in the prevention of OA, two main questions regarding their methods remain. First, we wonder whether the researchers also considered looking into the development of clinical OA or knee pain in their participants. The results published in the study only focus on the development of radiographic OA. In our opinion, increasing the scope of the study and also looking at clinical symptoms of OA would be a valuable addition, because the presence of radiographic OA is a poor predictor of knee pain in patients [3]. The burden of OA comes from the symptoms a patient experiences, such as pain, stiffness or functional loss. Investigating whether whole grain consumption has an association with the development of OA symptoms would make the results of the study more applicable for clinical practice.

Potential surrogate outcomes in individuals at high risk for incident knee osteoarthritis

To study potential surrogate outcomes for osteoarthritis (OA) incidence by evaluating the association of short-term changes in clinical and imaging biomarkers with long-term clinical knee OA incidence. Middle-aged women with overweight/obesity, but free of knee symptoms were recruited through their general practitioners. At baseline, after 2.5 years, and after 6.5 years, questionnaires, physical examination, radiographs, and Magnetic resonance imaging (MRI) scans were obtained. The percentage of knees with a minimal clinically important difference for knee pain severity, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain/stiffness/function, and joint space narrowing, and of those with progression/regression of medial knee alignment, chronic knee pain, radiographic osteophytes, and cartilage defects, bone marrow lesions, osteophytes, and effusion/synovitis on MRI were determined. For each of these potential surrogate outcomes with ≥10% improvement or progression in the population over 2.5 years, the association with incident clinical knee OA, defined using the combined ACR-criteria, after 6.5 years was determined. Most pre-defined potential surrogate outcomes showed ≥10% change in the population over 2.5 years, but only worsening of TF cartilage defects, worsening of TF osteophytes on MRI, and an increase in pain severity were significantly associated with greater clinical knee OA incidence after 6.5 years. These potential surrogate outcomes had high specificity and negative predictive value (89-91%) and low sensitivity and positive predictive value (20-28%) CONCLUSIONS: Worsening of TF cartilage defects and TF osteophytes on MRI, and increased pain severity could be seen as surrogate outcomes for long-term OA incidence. However, higher positive predictive values seem warranted for the applicability of these factors in future preventive trials.

Annual income, age, marital status, and smoking influence healthcare access among American minorities and Caucasians with knee osteoarthritis

ABSTRACT This study examined the associations between annual income, age, marital status, smoking status, and healthcare access in American minority and Caucasian populations with or at high risk for knee osteoarthritis (KOA). The Osteoarthritis Initiative provided data on 4674 Americans aged between 45 and 79 years with or at increased risk for KOA. We categorized the participants into American minorities (such as African Americans, Asians, or other non-whites) and Caucasians based on racial and ethnic backgrounds. A multinomial regression analysis revealed that American minorities having an annual income of <$50,000 and who were single, divorced, or widowed were 3.82- and 2.19-times more likely not to have healthcare access, respectively. For Caucasians, age ≥65, annual household income <$50,000, and present or past smoking habit were 2.34-, 1.93-, and 1.50-times more likely not to access healthcare, respectively. American minorities and Caucasians who either had KOA or were at high risk for developing it and had lower annual income had a greater likelihood of not accessing healthcare. Age ≥65 years and smoking history impacted healthcare access in Caucasians, whereas American minorities were more affected by being single, divorced, or widowed.

The causal association between bone mineral density and risk of osteoarthritis: A Mendelian randomization study.

The causal direction and magnitude of the association between total body bone mineral density (TB-BMD) and osteoarthritis (OA) risk is uncertain owing to the susceptibility of observational studies to confounding and reverse causation. The study aimed to explore the relationships between TB-BMD concentration and OA using Mendelian randomization (MR). In this study, we used two-sample MR to obtain unconfounded estimates of the effect of TB-BMD on hip and knee OA. Single nucleotide polymorphisms (SNPs) strongly associated with TB-BMD in a large genome-wide association study (GWAS) were identified and selected as instrumental variables (IVs). In addition to the main analysis using inverse-variance weighted (IVW) method, we applied 2 additional methods to control for pleiotropy(MR-Egger regression, weighted median estimator) and compared the respective MR estimates. MR analyses suggested that genetically predicted higher TB-BMD is associated with risks of hip OA (For IVW: OR=1.199, 95%CI: 1.02-1.42, P=0.032; for WM: OR=1.257, 95%CI: 1.09-1.45, P=0.002). There was no evidence that the observed causal effect between TB-BMD and the risk of hip OA was affected by genetic pleiotropy(P=0.618). Additionally, our study didn't support causal effects of a genetically increased TB-BMD risk on knee OA risk(OR=1.121, 95%CI: 0.99-1.28, P=0.084 using IVW; OR=1.132, 95%CI: 0.99-1.29, P=0.068 using WM; OR=1.274, 95%CI: 0.88-1.85, P=0.217 using MR-Egger). Our findings support a causal effect that a genetic predisposition to systematically higher TB-BMD was associated with the risk of OA. And, TB-BMD likely exerts an effect on the risk of hip OA not knee OA.

Passive stiffness of the quadriceps predicts the incidence of clinical knee osteoarthritis in twelve months.

Quadriceps weakness is a known risk factor for the onset of knee osteoarthritis (OA). In addition to muscle weakness, increased passive stiffness of the quadriceps may affect knee biomechanics and hence contribute to the pathogenesis of knee OA. However, the association between quadriceps stiffness and the risk of knee OA development has not been prospectively investigated. The aim of this study was to investigate how baseline quadriceps passive stiffness predicts the incidence of clinical knee OA at the 12-month follow-up. Prospective cohort study. University laboratory. Community-dwelling adults aged 60-80 years were recruited. We excluded participants with: 1) knee pain or known arthritis; 2) knee injury; 3) knee or hip joint replacement, 4) cognitive impairment; or 5) neurological conditions. At baseline, passive stiffness of the three superficial quadriceps muscle heads (rectus femoris [RF], vastus lateralis [VL], and vastus medialis oblique [VMO]) was evaluated using shear-wave ultrasound elastography. Knee muscle (quadriceps and hamstrings) strength was tested using a Cybex dynamometer. Knee OA was defined based on clinical criteria 12 months after baseline measurements. Generalized estimating equations were used to examine the associations of quadriceps stiffness and knee muscle strength with the risk of knee OA, controlling for age, sex, Body Mass Index, comorbidities, and activity level. The analyses included 158 knees (58.2% females, age: 65.6±4.1 years). Twenty-eight knees (17.7%) were classified as having clinical OA at 12 months. Compared with the lowest stiffness tertiles, the highest stiffness tertiles of the RF (relative risk =5.31, 95% CI: 1.34-21.0), VMO (4.15, 1.04-16.6), and total superficial quadriceps (6.35, 1.48-27.3) at baseline were significantly associated with a higher risk of knee OA at the follow-up. The highest strength tertile of quadriceps has a trend of association with a lower risk of knee OA than the lowest tertile (0.18, 0.03-1.25, P=0.083). Greater passive stiffness of the quadriceps at baseline was associated with a higher risk of clinical knee OA incidence at the 12-month follow-up. Interventions for reducing the passive stiffness of the quadriceps should be included in preventative training programs for older adults.

Тізе және жамбас буындарының идиопатиялық остеоартрозының дамуының генетикалық бейімділігі: Әдеби шолу

Osteoarthritis is a degenerative joint disease that leads to damage to cartilage tissue and changes in the structure of bones, ligaments and muscles that surround joints. Despite numerous studies of osteoarthritis in our country and abroad, the wide variability in the development of the disease does not give a clear picture of the true cause of osteoarthritis formation. In the available domestic literature, there is still almost no information about genetic factors in the development of osteoarthritis. In this literature review, we discuss some evidence suggesting a genetic association with the risk of knee and hip osteoarthritis and summarize recent advances in this field, with special emphasis on genetically associated studies.

Automated machine learning-based prediction of the progression of knee pain, functional decline, and incidence of knee osteoarthritis in individuals at high risk of knee osteoarthritis: Data from the osteoarthritis initiative study.

This study aimed to examine the performance of machine learning models in predicting the progression of knee pain, functional decline, and incidence of knee osteoarthritis (OA) in high-risk individuals, with automated machine learning (AutoML) being used to automate the prediction process. There were four stages in the process of our AutoML-integrated prediction. Stage 1-Data preparation: The data of 3200 eligible individuals in the Osteoarthritis Initiative (OAI) study who were considered at high risk of knee OA at the baseline visit were extracted and used. Specifically, 1094 variables from the OAI study were used to predict the changes in knee pain, physical function, and incidence of knee OA (i.e. the first occurrence of frequent knee symptoms and definite tibial osteophytes (Kellgren and Lawrence grade ≥2)) over a 9-year period. Stage 2-Model training: The AutoML approach was used to automatically train nine widely used machine learning (ML) models. Stage 3-Model testing: The AutoML approach was used to automatically test the performance of the ML models. Stage 4-Selection of important input variables: The AutoML approach automated the process of computing the importance scores of all input variables and identifying the most important ones, using the technique of permutation feature importance. Using the AutoML approach, the weighted ensemble model and the CatBoost model showed the best performance among all nine ML models. For the prediction of each outcome in each year, the five most important input variables were identified, most of which were obtained from self-reported questionnaire surveys and radiographic imaging reports. The AutoML approach has shown potential in automating the process of using ML models to predict long-term changes in knee OA-related outcomes. Its use could support the deployment of ML solutions, facilitating the provision of personalized interventions to prevent the deterioration of knee health and incident knee OA.

Prediction Models for Knee Osteoarthritis: Review of Current Models and Future Directions.

Knee osteoarthritis (OA) is a prevalent joint disease. Clinical prediction models consider a wide range of risk factors for knee OA. This review aimed to evaluate published prediction models for knee OA and identify opportunities for future model development. We searched Scopus, PubMed, and Google Scholar using the terms knee osteoarthritis, prediction model, deep learning, and machine learning. All the identified articles were reviewed by one of the researchers and we recorded information on methodological characteristics and findings. We only included articles that were published after 2000 and reported a knee OA incidence or progression prediction model. We identified 26 models of which 16 employed traditional regression-based models and 10 machine learning (ML) models. Four traditional and five ML models relied on data from the Osteoarthritis Initiative. There was significant variation in the number and type of risk factors. The median sample size for traditional and ML models was 780 and 295, respectively. The reported Area Under the Curve (AUC) ranged between 0.6 and 1.0. Regarding external validation, 6 of the 16 traditional models and only 1 of the 10 ML models validated their results in an external data set. Diverse use of knee OA risk factors, small, non-representative cohorts, and use of magnetic resonance imaging which is not a routine evaluation tool of knee OA in daily clinical practice are some of the main limitations of current knee OA prediction models.

Cartilage Acidic Protein 1 in Plasma Associates With Prevalent Osteoarthritis and Predicts Future Risk as Well as Progression to Joint Replacements: Results From the UK Biobank Resource.

The level of cartilage acidic protein 1 (CRTAC1) in plasma was recently discovered to be associated with osteoarthritis (OA) risk and progression to joint replacement in Iceland. This study was undertaken to validate these findings in an independent population. In this study, 1,462 plasma proteins were measured in 54,265 participants from the UK Biobank on the Olink Explore platform. We analyzed the association of plasma proteins with prevalent OA, incident OA, and progression to joint replacement. We assessed the specificity of OA association through comparison of associations with inflammatory joint diseases and with previous joint replacement. The CRTAC1 protein showed the strongest association with prevalent knee OA (odds ratio [OR] 1.34 [95% confidence interval (95% CI) 1.27, 1.41]) and was associated with hip OA (OR 1.19 [95% CI 1.11, 1.28]). It predicted incident diagnosis of OA in the knee (hazard ratio [HR] 1.40 [95% CI 1.35, 1.46]) and hip (HR 1.25 [95% CI 1.19, 1.31]), as well as progression to joint replacement (HR 1.20 [95% CI 1.08, 1.33] for the knee and HR 1.22 [95% CI 1.08, 1.38] for the hip), while no association was found with inflammatory joint diseases. Individuals in the highest quintile of risk based on CRTAC1 level, age, sex, and body mass index had a 10-fold risk of knee or hip OA within 5 years compared to those in the lowest quintile. Adding aggrecan core protein (ACAN) and neurocan core protein (NCAN) to the model improved the prediction of OA but not joint replacement. Furthermore, we replicated the association of CUB domain-containing protein 1 with prior joint replacement. Plasma CRTAC1 is a specific biomarker for OA and a predictor of OA risk and progression to joint replacement. Adding ACAN and NCAN protein levels to the CRTAC1 model improved the prediction of OA.

“I feel I'm leading the charge.” Experiences of a virtual physiotherapist-guided knee health program for persons at-risk of osteoarthritis after a sport-related knee injury

ObjectiveDescribe participants’ perspectives about the feasibility of a virtual, physiotherapist-guided knee health program for people at risk of post-traumatic osteoarthritis after a sport-related knee injury. DesignQualitative description study nested within a quasi-experimental study evaluating the feasibility of the Stop OsteoARthritis (SOAR) with persons with sport-related knee injuries. SOAR includes: 1) one-time Knee Camp (group education, 1:1 exercise/activity goal-setting); 2) weekly home-based exercise/activity program with tracking, and; 3) weekly 1:1 physiotherapy-guided action-planning. Upon program completion, semi-structured 1:1 interviews were conducted with participants identified by convenience and maximum variation sampling (age, gender, program satisfaction). Open-ended questions elicited participants’ experiences with the program. Content analysis was conducted. Results12 women and 4 men [median (min-max) age; 30 (19–46) years] were interviewed. Four categories depicted participants' experiences: 1) ‘SOAR satisfies an unmet need’ portrayed the perceived relevance and need for a program that promotes knowledge about knee health and self-efficacy for independent exercise behaviour, 2) ‘Regaining control of knee health’ described how SOAR empowered participants and fostered a sense of ‘leading the charge’ to their own knee health, 3) ‘Social support encourages exercise participation’ highlighted that weekly physiotherapy interactions provided accountability for achieving exercise goals, and that relating to other participants was inspirational, 4) ‘Program refinements and barriers’ suggested enhancements to meet the needs of future participants. ConclusionsParticipants report the SOAR program to be acceptable, relevant, and empowering. Improved knowledge about one's knee health, self-efficacy, autonomy, and social support may encourage exercise adherence and self-management of future knee OA risk.

Association of hormone replacement therapy and the risk of knee osteoarthritis: A meta-analysis.

The relationship between hormone replacement therapy (HRT) and osteoarthritis is controversial in epidemiological studies. With the aim of better understanding the effect of HRT use, this first meta-analysis was implemented to explore the association of HRT and knee OA. A series of data is retrieved from Web of Science, PubMed, and Embase databases to observe the association of HRT and knee osteoarthritis up to December 2021. Two separated reviewers chose the research, extracted the data, and evaluated the study quality. Pooled estimates of 95% CI and HRs were acquired through a random-effects model. Finally, there existed 13 pieces of research, containing one case-control research, four cross-sectional pieces of research, as well as eight cohort pieces of research, involving 2573,164 participants. The overall results showed that the use of HRT was related to a raised risk of knee OA (HR = 1.24, 95% CI 1.07-1.45). And the pooled analysis showed a statistically significant raised risk of knee joint replacement (HR = 1.30, 95% CI 1.09-1.54) when using HRT. In addition, the outcome exhibits the raised knee OA risk for the present users of HRT (HR = 1.40, 95% CI 1.16-1.68) according to HRT status. In the past users of HRT, the augment of knee OA risk was not statistically evident (HR = 1.16, 95% CI 0.94-1.42). We observed that HRT use was related to a raised knee OA risk. Furthermore, future studies might focus on relevant mechanistic to verify our observed associations.

Causal Effect of Higher Glycated Hemoglobin (HbA1c) Levels on Knee Osteoarthritis Risk: A Mendelian Randomization Study.

The association between diabetes mellitus (DM) and risk of osteoarthritis (OA) is inconsistent based on published observational studies. This study aimed to conduct a two-sample Mendelian randomization (MR) analysis to explore the causal link between glycated hemoglobin (HbA1c) level and OA risk. Genome-wide association studies (GWAS) summary statistics were obtained from the publicly available Integrative Epidemiology Unit (IEU) OpenGWAS database. A series of screening processes were performed to select qualified instrumental single-nucleotide polymorphisms (SNPs) strongly related to exposure. The inverse-variance-weighted method, weighted-median method, and MR-Egger method were performed to ensure robust and reliable results. The MR-Egger intercept test, Cochran's Q test, and the leave-one-out sensitivity analysis were utilized to assess the horizontal pleiotropy, heterogeneities, and stability of these genetic variants for OA. Odds ratio (OR) and 95% confidence interval (CI) were calculated. MR analyses found a robust causal association of genetically determined HbA1c with knee OA (OR = 1.561; 95% CI 1.110-2.197; P = 0.011), but not with hip OA (OR = 1.073; 95% CI 0.674-1.710; P = 0.766) or overall OA (OR = 1.141; 95% CI 0.904-1.441; P = 0.804). Sensitivity analyses showed that there was a strong association between SNPs and HbA1c (F = 21.138), no evidence of heterogeneity (Q = 150.625, P = 0.402), and no potential SNPs affecting the causal link. Our MR study supported a causal effect of genetically increased HbA1c on knee OA risk.

A novel computer-assisted diagnosis method of knee osteoarthritis based on multivariate information and deep learning model

Knee Osteoarthritis (KOA) is a chronic joint disease characterized by degeneration of knee's articular cartilage. Comparing with the imaging diagnostic method, the vibroarthrographic (VAG) may be emerged as a new candidate for diagnosis of KOA in clinics. However, it is challenging for doctors to evaluate patients' condition by visually detecting VAGs due to the limited understanding about contained information. Besides, the basic physiological signals are also closely correlated with a greater risk of KOA. Based on this, we focus on studying computer-assisted diagnosis method of KOA (KOA-CAD) using multivariate information (i.e. VAGs and basic physiological signals) based on an improved deep learning model (DLM). Firstly, a new Laplace distribution-based strategy (LD-S) for classification in DLM is designed. Secondly, an aggregated multiscale dilated convolution network (AMD-CNN) is constructed to learn features from multivariate information of KOA patients. Then, a new KOA-CAD method is proposed by integrating the AMD-CNN with the LD-S to realize three CAD objectives, including the automatic KOA detection, the KOA early detection, and the KOA grading detection. Finally, the multivariate information collected clinically is applied to verify the proposed method, where the automatic detection accuracy, early detection accuracy and grading detection accuracy are 93.6%, 92.1%, and 84.2% respectively.

Effusion detected by ultrasonography and overweight may predict the risk of knee osteoarthritis in females with early knee osteoarthritis: a retrospective analysis of Iwaki cohort data

BackgroundKnee osteoarthritis (OA) has enormous medical and socioeconomic burdens, which early diagnosis and intervention can reduce. We investigated the influence of knee effusion on the progression of knee OA in patients with early knee OA.MethodsA total of 404 participants without radiographic knee OA were assessed from a 3-year longitudinal analysis. Participants were classified into non-OA and early knee OA groups. The effusion area (mm2) was quantified using ultrasonography. Receiver operating characteristic and logistic regression analyses were performed.ResultsAt the 3-year follow-up, 114 of 349 knees (32%) had progressed from non-OA and 32 of 55 knees (58%) had progressed from early knee OA to radiographic knee OA. Logistic regression analysis showed that female sex (odds ratio [OR] 3.36, 95% confidence interval [CIs] 2.98–5.42), early knee OA (OR 2.02, 95% CI 1.08–3.75), body mass index (OR 1.11, 95% CI 1.02–1.19), and effusion area (OR 1.01, 95% CI 1.01–1.02) were significantly correlated with knee OA progression. Women who were overweight (body mass index ≥ 25 kg/m2) with more severe effusion had a higher risk of OA progression (area under the curve = 0.691, OR = 6.00) compared to those not overweight (area under the curve = 0.568, OR = 1.91).ConclusionKnee effusion may be an indicator of the progression of early-stage knee OA.

Causal effects of B vitamins and homocysteine on obesity and musculoskeletal diseases: A Mendelian randomization study.

Although homocysteine (Hcy) increases the risk of cardiovascular diseases, its effects on obesity and musculoskeletal diseases remain unclear. We performed a Mendelian randomization study to estimate the associations between Hcy and B vitamin concentrations and their effects on obesity and musculoskeletal-relevant diseases in the general population. We selected independent single nucleotide polymorphisms of Hcy (n = 44,147), vitamin B12 (n = 45,576), vitamin B6 (n = 1864), and folate (n = 37,465) at the genome-wide significance level as instruments and applied them to the studies of summary-level data for fat and musculoskeletal phenotypes from the UK Biobank study (n = 331,117), the FinnGen consortium (n = 218,792), and other consortia. Two-sample Mendelian randomization (MR) approaches were utilized in this study. The inverse variance weighting (IVW) was adopted as the main analysis. MR-PRESSO, MR-Egger, the weighted median estimate, bidirectional MR, and multivariable MR were performed as sensitivity methods. Higher Hcy concentrations were robustly associated with an increased risk of knee osteoarthritis [odds ratio (OR) 1.119; 95% confidence interval (CI) 1.032-1.214; P = 0.007], hospital-diagnosed osteoarthritis (OR 1.178; 95% CI 1.012-1.37; P = 0.034), osteoporosis with pathological fracture (OR 1.597; 95% CI 1.036-2.46; P = 0.034), and soft tissue disorder (OR 1.069; 95% CI 1.001-1.141; P = 0.045) via an inverse variance weighting method and other MR approaches. Higher vitamin B12 levels were robustly associated with decreased body fat percentage and its subtypes (all P < 0.05). Bidirectional analyses showed no reverse causation. Multivariable MR analyses and other sensitivity analyses showed directionally similar results. There exist significant causal effects of vitamin B12 in the serum and Hcy in the blood on fat and musculoskeletal diseases, respectively. These findings may have an important insight into the pathogenesis of obesity and musculoskeletal diseases and other possible future therapies.

Knee osteoarthritis, joint laxity and PROMs following conservative management versus surgical reconstruction for ACL rupture: a meta-analysis.

Patients whose rupture of the anterior cruciate ligament (ACL) can be managed conservatively or undergo reconstruction surgery. Current scientific literature published in Web of Science, PubMed and Scopus. Several studies published by July 2022 compare surgical and conservative management following ACL rupture. The latest evidence suggests that surgical management may expose patients to an increased risk of early-onset knee osteoarthritis (OA). The state of art does not recommend a systematic ACL reconstruction to all patients who tore their ACL. After the initial trauma, surgical reconstruction may produce even greater damage to the intra-articular structures compared to conservative management. The state of art does not recommend systematic surgical reconstruction to all patients who tore their ACL. The present study compared surgical reconstruction versus conservative management for primary ACL ruptures in terms of joint laxity, patient reported outcome measures (PROMs) and rate of osteoarthritis. ACL reconstruction provides significant improvement in joint laxity compared to conservative management, but is associated with a significantly greater rate of knee osteoarthritis, despite similar results at PROM assessment.

Osteoarthritis and cardiovascular disease: A Mendelian randomization study.

This Mendelian randomization (MR) study aimed to investigate the causal relationship between osteoarthritis (OA) and cardiovascular disease (CVD). From a genome-wide association study of European ancestry, we selected single nucleotide polymorphisms for two types of OA, knee osteoarthritis (KOA) and hip osteoarthritis (HOA), as instrumental variables. We evaluated three types of CVD: coronary heart disease (CHD), heart failure (HF), and stroke. We used the traditional inverse variance weighting (IVW) method and other methods to estimate causality. Heterogeneity and sensitivity tests were also applied. Finally, we conducted a MR analysis in the opposite direction to investigate reverse causality. IVW analysis showed that HOA significantly affected the incidence of HF [odds ratio (OR): 1.0675; 95% confidence interval (CI): 0.0182-0.1125, P = 0.0066]. HOA significantly affected the incidence of stroke (OR: 1.1368; 95% CI: 1.0739-1.2033, P = 9.9488e-06). CHD could dramatically affect the incidence of KOA (OR: 0.9011; 95% CI: 0.8442-0.9619, P = 0.0018). The rest of the results were negative. Our results revealed a potential causal relationship between HOA and risk of HF, and a potential causal relationship between HOA and risk of stroke. Our findings also suggested that CHD has a significant causal relationship with the risk of KOA. This paper may provide new ideas for the treatment of OA and CVD.

Wear patterns in knee OA correlate with native limb geometry.

Background: To date, the amount of cartilage loss is graded by means of discrete scoring systems on artificially divided regions of interest (ROI). However, optimal statistical comparison between and within populations requires anatomically standardized cartilage thickness assessment. Providing anatomical standardization relying on non-rigid registration, we aim to compare morphotypes of a healthy control cohort and virtual reconstructed twins of end-stage knee OA subjects to assess the shape-related knee OA risk and to evaluate possible correlations between phenotype and location of cartilage loss. Methods: Out of an anonymized dataset provided by the Medacta company (Medacta International SA, Castel S. Pietro, CH), 798 end-stage knee OA cases were extracted. Cartilage wear patterns were observed by computing joint space width. The three-dimensional joint space width data was translated into a two-dimensional pixel image, which served as the input for a principal polynomial autoencoder developed for non-linear encoding of wear patterns. Virtual healthy twin reconstruction enabled the investigation of the morphology-related risk for OA requiring joint arthroplasty. Results: The polynomial autoencoder revealed 4 dominant, orthogonal components, accounting for 94% of variance in the latent feature space. This could be interpreted as medial (54.8%), bicompartmental (25.2%) and lateral (9.1%) wear. Medial wear was subdivided into anteromedial (11.3%) and posteromedial (10.4%) wear. Pre-diseased limb geometry had a positive predictive value of 0.80 in the prediction of OA incidence (r 0.58, p < 0.001). Conclusion: An innovative methodological workflow is presented to correlate cartilage wear patterns with knee joint phenotype and to assess the distinct knee OA risk based on pre-diseased lower limb morphology. Confirming previous research, both alignment and joint geometry are of importance in knee OA disease onset and progression.

Using genetic instruments to estimate the causal effect of hormonal reproductive factors on osteoarthritis.

Hormonal reproductive factors have been considered to play an important role in the etiology of osteoarthritis (OA). We performed Mendelian randomization (MR) to examine whether a causal effect existed between them. MR was performed by using publicly released genome-wide association study (GWAS) summary statistics to estimate the causal associations of three relevant exposures, including age at menarche (AAM), age at natural menopause (ANM) and age at first birth (AFB), with the risk of OA. We employed several MR methods, including inverse-variance weighted (IVW), MR-Egger regression, weighted median and weighted mode, to estimate the causality. We performed a sensitivity analysis by manually pruning pleiotropic variants associated with the known confounder body mass index (BMI). The instrumental variables that achieved genome-wide significance, including 349 AAM single nucleotide polymorphisms (SNPs), 121 AAM SNPs, 54 ANM SNPs, and 10 AFB SNPs, were incorporated into the operation. IVW analysis indicated that each additional year in AFB was associated with a decreasing risk of hip and/or knee OA and overall OA (hip and/or knee OA: OR = 0.79, 95% CI: 0.64-0.93, P = 1.33 × 10-3; overall OA: OR = 0.80, 95% CI: 0.68-0.92, P = 1.80 × 10-4). In addition, our results suggested that AAM exerted a causal effect on knee OA in an unfavorable manner (OR = 0.86, 95% CI: 0.76-0.95, P = 1.58 × 10-3). After accounting for the effect of BMI, the causal effect association between AFB and hip and/or knee OA was also examined (IVW: OR = 0.78, 95% CI: 0.66-0.92, P = 3.22 × 10-3). Our findings add a growing body of evidence surrounding the unfavorable effects of early AFB on OA risk, suggesting the essential for relevant health problem management in susceptible populations.