Cardiometabolic Polygenic Risk Scores and Osteoarthritis Outcomes: A Mendelian Randomization Study Using Data From the Malmö Diet and Cancer Study and the UK Biobank

Body mass index and meniscal tears: Evidence from meta-analysis of observational studies and Mendelian randomization

Obesity is a potential risk factor for meniscal tear (MT). We utilized meta-analysis of observational studies and Mendelian randomization (MR) analyses to elucidate the association between body mass index (BMI) and MT. In meta-analysis, a search was performed on June 27, 2022, using PubMed and Embase databases. Odds ratios and 95% confidence intervals were extracted from included studies. In MR analyses, the research utilized summary-level data on BMI and MT obtained from Genetic Investigation of Anthropometric Traits and the FinnGen Consortium, respectively. In meta-analysis, four studies comprising 826,383 participants were included. The pooled odds ratio of MT in the high BMI group was 1.32 (95% confidence interval, 0.83-2.09), compared with the nonhigh BMI group. The pooled odds ratio in the under 30 group was 1.76 (95% confidence interval, 0.61-5.03). In MR analyses, one standard deviation increase in genetically predicted BMI was associated with meniscus derangement as a chronic subtype of MT (odds ratio, 1.36; 95% confidential interval, 1.17-1.59). We found that a high BMI was not associated with an increased likelihood of MT based on meta-analysis of observational studies; however, by complementing MR analyses, we elucidated the causality of BMI increase on meniscus derangement as a chronic subtype of MT.

Causal Factors for Osteoarthritis: A Scoping Review of Mendelian Randomization Studies

OBJECTIVE

Mendelian randomization (MR) has increasingly been utilized as a tool for establishing causal relations between modifiable exposures and osteoarthritis (OA). The goal of this review was to summarize available MR studies of OA that evaluate the causal role of modifiable risk factors on OA.

METHODS

This review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Extension for Scoping Reviews model. We performed a literature search for relevant studies published before December 2021 across multiple databases using the search terms "osteoarthritis" and ("Mendelian randomization" or "polygenic risk score"). We reported the MR estimates of causal associations between exposures and OA and then assessed methodologic quality of abstracted studies according to their efforts to validate the three key MR assumptions.

RESULTS

Our search identified 45 studies reporting on 141 exposure-association analyses. All studies performed a formal instrumental variable analysis to estimate the causal effect of exposure on OA. Causal associations (P < 0.05) were reported in 60 of these analyses representing 36 unique publications, and MR-Egger sensitivity analyses were performed in 45 of these analyses. MR studies provided support for causal associations of OA with increased levels of adiposity, coffee consumption, bone mineral density, and sleep disturbance, and decreased levels of serum calcium and low-density lipoprotein cholesterol.

CONCLUSION

These results highlight the potential benefits of weight reduction and improvement of sleep quality to reduce the risk of OA and call for a better understanding of the relations of coffee consumption and serum calcium to OA risk.

Cross-Sectional and Longitudinal Associations of Comorbidities with Knee Symptoms and Radiographic Abnormalities of Osteoarthritis

INTRODUCTION

This study aimed to investigate the associations of comorbidities with knee symptoms and radiographic abnormalities of osteoarthritis (OA).

METHODS

Participants were from the Osteoarthritis Initiative. Comorbidities were identified at baseline using the modified Charlson Comorbidity Index. For both knees, symptoms were assessed annually from baseline to 48 months using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain and function scores (rescaled range 0-100), and radiographic abnormalities using the Kellgren-Lawrence (KL, 0-4) grades. The presence of significant pain and functional disability was defined as a WOMAC score of ≥ 25 and ≥ 22, respectively, and radiographic OA (ROA) as KL ≥ 2. An increase of ≥ 9 in WOMAC scores and ≥ 1 in KL grades were defined as symptomatic and radiographic progression, respectively.

RESULTS

Of 3337 participants, 28% and 9% had one and ≥ 2 comorbidities, respectively. The number of comorbidities was associated with the presence of significant functional disability (odds ratios [ORs] 1.15; 1.46) and predicted the progression of both knee pain and functional disability (ORs 1.11; 1.51). For the type of comorbidities, non-OA musculoskeletal diseases were associated with the presence of ROA and significant functional disability (ORs 1.63; 1.82) and showed a trend to predict incident ROA (OR 1.84, 95% confidence interval 1.00-3.38 p = 0.051). Diabetes and kidney diseases were associated with symptomatic progression of OA (ORs 1.38; 2.72).

CONCLUSIONS

Having more comorbidities, especially diabetes and kidney diseases, is associated with symptomatic progression of knee OA. Moreover, non-OA musculoskeletal diseases may be associated with the presence and onset of ROA.

The association between lipid biomarkers and osteoarthritis based on the National Health and Nutrition Examination Survey and Mendelian randomization study

To explore the association between lipid markers and osteoarthritis (OA). First, the National Health and Nutrition Examination Survey (NHANES) database was used to screen participants with lipid markers, OA and relevant covariates, and logistic regression was used to analyze the association between lipid markers and OA; Then, under the theoretical framework of Mendelian randomization (MR), two-sample MR was performed using GWAS data of lipid markers and OA to explore the causal association between the two, which was analyzed by inverse variance weighting (IVW) method. Heterogeneity test, sensitivity analysis and pleiotropy analysis were also performed. The NHANES database screened a total of 3706 participants, of whom 836 had OA and 2870 did not have OA. When lipid markers were used as continuous variables, multivariate logistic results showed an association between HDL, LDL and OA (HDL, OR (95%):1.01 (1.00, 1.01); LDL, OR (95%):1.00 (0.99, 1.00)). When lipid markers were used as categorical variables, multivariate logistic results showed the fourth quartile result of 0.713 (0.513, 0.992) for LDL relative to the first quartile. In MR study, the results of the IVW method for TG, TL, HDL and LDL showed OR (95% CI) of 1.06 (0.97-1.16), 0.95 (0.85-1.06), 0.94 (0.86-1.02) and 0.89 (0.80-0.998) with P-values of 0.21, 0.37. 013, 0.046. The heterogeneity tests and multiplicity analyses showed P-values greater than 0.05, and sensitivity analyses showed no abnormal single nucleotide polymorphisms. Through NHANES database and MR analyses, LDL was found to be a protective factor for OA, while HDL still needs further study. Our results provide new biomarkers for preventive and therapeutic strategies for OA.

The Application of Genetic Risk Scores in Rheumatic Diseases: A Perspective

Modest effect sizes have limited the clinical applicability of genetic associations with rheumatic diseases. Genetic risk scores (GRSs) have emerged as a promising solution to translate genetics into useful tools. In this review, we provide an overview of the recent literature on GRSs in rheumatic diseases. We describe six categories for which GRSs are used: (a) disease (outcome) prediction, (b) genetic commonalities between diseases, (c) disease differentiation, (d) interplay between genetics and environmental factors, (e) heritability and transferability, and (f) detecting causal relationships between traits. In our review of the literature, we identified current lacunas and opportunities for future work. First, the shortage of non-European genetic data restricts the application of many GRSs to European populations. Next, many GRSs are tested in settings enriched for cases that limit the transferability to real life. If intended for clinical application, GRSs are ideally tested in the relevant setting. Finally, there is much to elucidate regarding the co-occurrence of clinical traits to identify shared causal paths and elucidate relationships between the diseases. GRSs are useful instruments for this. Overall, the ever-continuing research on GRSs gives a hopeful outlook into the future of GRSs and indicates significant progress in their potential applications.

Improved genetic prediction of the risk of knee osteoarthritis using the risk factor-based polygenic score

BACKGROUND

Polygenic risk score (PRS) analysis is used to predict disease risk. Although PRS has been shown to have great potential in improving clinical care, PRS accuracy assessment has been mainly focused on European ancestry. This study aimed to develop an accurate genetic risk score for knee osteoarthritis (OA) using a multi-population PRS and leveraging a multi-trait PRS in the Japanese population.

METHODS

We calculated PRS using PRS-CS-auto, derived from genome-wide association study (GWAS) summary statistics for knee OA in the Japanese population (same ancestry) and multi-population. We further identified risk factor traits for which PRS could predict knee OA and subsequently developed an integrated PRS based on multi-trait analysis of GWAS (MTAG), including genetically correlated risk traits. PRS performance was evaluated in participants of the Nagahama cohort study who underwent radiographic evaluation of the knees (n = 3,279). PRSs were incorporated into knee OA integrated risk models along with clinical risk factors.

RESULTS

A total of 2,852 genotyped individuals were included in the PRS analysis. The PRS based on Japanese knee OA GWAS was not associated with knee OA (p = 0.228). In contrast, PRS based on multi-population knee OA GWAS showed a significant association with knee OA (p = 6.7 × 10^-5, odds ratio (OR) per standard deviation = 1.19), whereas PRS based on MTAG of multi-population knee OA, along with risk factor traits such as body mass index GWAS, displayed an even stronger association with knee OA (p = 5.4 × 10^-7, OR = 1.24). Incorporating this PRS into traditional risk factors improved the predictive ability of knee OA (area under the curve, 74.4% to 74.7%; p = 0.029).

CONCLUSIONS

This study showed that multi-trait PRS based on MTAG, combined with traditional risk factors, and using large sample size multi-population GWAS, significantly improved predictive accuracy for knee OA in the Japanese population, even when the sample size of GWAS of the same ancestry was small. To the best of our knowledge, this is the first study to show a statistically significant association between the PRS and knee OA in a non-European population.

TRIAL REGISTRATION

No. C278.

The burden of osteoarthritis: Is it a rising problem?

The objective of this review is to provide an overview of the current status of osteoarthritis (OA) as one of the most common joint disorders worldwide. Despite being the 11th cause of disability globally, there has been an increase in the prevalence, annual incidence, and years lived with disability of OA, particularly in developed and developing countries. Erosive hand OA, which affects approximately 10% of the general population, has been associated with a higher clinical burden compared to non-erosive hand OA. Patients with knee and hip OA, but not hand OA, are also at an increased risk of cardiovascular disease and all-cause mortality. Furthermore, OA has a significant contribution to healthcare costs in most countries. The recent COVID-19 pandemic has further exacerbated the disease burden of OA patients due to limited access to medical and surgical treatment. With increasing life expectancy and the aging of the global population, the burden of OA is expected to worsen. Therefore, this review highlights the importance of improving population and policymaker awareness of risk factors, such as obesity and injury, as well as early intervention and management of OA to control the future burden of the disease.

Association Between Metabolically Different Adiposity Subtypes and Osteoarthritis: A Mendelian Randomization Study

OBJECTIVE

In this Mendelian randomization (MR) study, the objective was to investigate the causal effect of metabolically different adiposity subtypes on osteoarthritis.

METHODS

We performed 2-sample MR using summary-level data for osteoarthritis (10,083 cases and 40,425 controls) from a genome-wide association using the UK Biobank, and for site-specific osteoarthritis from the Arthritis Research UK Osteoarthritis Genetics consortium. We used 3 classes of genetic instruments, which all increase body mass index but are associated with different metabolic profiles (unfavorable, neutral, and favorable). Primary analysis was performed using inverse variance weight (IVW), with additional sensitivity analysis from different MR methods. We further applied a nonlinear MR using UK Biobank data to understand the nature of the adiposity-osteoarthritis relationship.

RESULTS

Greater metabolically unfavorable and metabolically neutral adiposity were associated with higher odds of osteoarthritis (IVW odds ratio [OR] 1.56 [95% confidence interval (95% CI) 1.31, 1.85] and OR 1.60 [95% CI 1.15, 2.23], respectively). The estimate for the association between metabolically favorable adiposity and osteoarthritis was similar, although with notable imprecision (OR 1.55 [95% CI 0.70, 3.41]). Using site-specific osteoarthritis, metabolically unfavorable, neutral, and favorable adiposity were all associated with higher odds of knee osteoarthritis (OR 1.44 [95% CI 1.04, 1.98], OR 2.28 [95% CI 1.04, 4.99], and OR 6.80 [95% CI 2.08, 22.19], respectively). We found generally consistent estimates with a wider confidence interval crossing the null from other MR methods. The nonlinear MR analyses suggested a nonlinear relationship between metabolically unfavorable adiposity and osteoarthritis (Pnonlinear  = 0.003).

CONCLUSION

Metabolic abnormalities did not explain the association between greater adiposity and the risk of osteoarthritis, which might suggest that the association is largely due to a mechanical effect on the joints.

Osteoarthritis and risk of cardiovascular diseases: A Mendelian randomization study

BACKGROUND

Observational studies have suggested that osteoarthritis may increase the risk of cardiovascular diseases. However, there is still no high-quality evidence to explain this causal relationship. We conducted a two-sample Mendelian randomization (MR) study to assess the associations of hip arthritis and knee arthritis with 14 types of cardiovascular diseases in the general population.

METHOD

Genome-wide association studies for hip arthritis and knee arthritis were obtained from the UK Biobank. Genome-wide association studies of the 14 types of cardiovascular diseases we studied were extracted from the genetic consortia and the FinnGen consortium. Inverse variance weighted (IVW), maximum likelihood, weighted medium, penalized weighted median, and IVW (fixed effects) of MR were applied to a two-sample MR analysis. The mean pleiotropy of genetic variation and sensitivity analysis were used to evaluate the reliability of the results, and the MR-Egger test and leave-one-out method are the core evaluation methods.

RESULT

Genetically predicted knee arthritis was causally associated with vein thromboembolism (IVW Odds Ratio (OR): 1.005, 95% Confidence Interval (CI): 0.842-1.199, P = 0.020) and pulmonary embolism (IVW OR: 1.003, 95% CI: 0.841-1.197, P = 0.025). Furthermore, hip arthritis also has a significant impact on cardiovascular diseases and is positively correlated with ischemic stroke (IVW OR: 1.086, 95% CI: 0.910-1.295, P = 0.024), atrial fibrillation (IVW OR: 1.093, 95% CI: 0.917-1.304, P = 0.019), and coronary artery disease (IVW OR: 1.061, 95% CI: 0.890-1.266, P = 0. 0.002).

CONCLUSION

Our study suggested that osteoarthritis may increase the risk of vein thromboembolism, pulmonary embolism, ischemic stroke, atrial fibrillation, and coronary artery disease. However, the findings provided no evidence to support that osteoarthritis has a large effect on the risk of cardiovascular diseases that we studied. Further research is needed to clarify the results.

A sex- and site-specific relationship between body mass index and osteoarthritis: evidence from observational and genetic analyses

OBJECTIVE

We primarily aimed to investigate whether there are phenotypic and genetic links underlying body mass index (BMI) and overall osteoarthritis (OA). We then intended to explore whether the relationships differ across sexes and sites.

METHOD

We first evaluated the phenotypic association between BMI and overall OA using data from the UK Biobank. We then investigated the genetic relationship leveraging summary statistics of the hitherto largest genome-wide association studies performed for BMI and overall OA. Finally, we repeated all analyses in a sex- (female, male) and site- (knee, hip, spine) specific manner.

RESULTS

Observational analysis suggested an increased hazard of diagnosed OA per 5 kg/m² increment in BMI (hazard ratio = 1.38, 95% confidence interval (CI) = 1.37-1.39). A positive overall genetic correlation was observed for BMI and OA (r_g = 0.43, P = 4.72 × 10^-133), corroborated by 11 significant local signals. Cross-trait meta-analysis identified 34 pleiotropic loci shared between BMI and OA, of which seven were novel. Transcriptome-wide association study revealed 29 shared gene-tissue pairs, targeting nervous, digestive, and exo/endocrine systems. Mendelian randomization demonstrated a robust BMI-OA causal relationship (odds ratio = 1.47, 95% CI = 1.42-1.52). A similar pattern of effects was observed in sex- and site-specific analyses, with BMI affecting OA comparably in both sexes and most strongly in the knee.

CONCLUSION

Our work demonstrates an intrinsic relationship underlying BMI and overall OA, reflected by a pronounced phenotypic association, significant biological pleiotropy, and a putative causal link. Stratified analysis further reveals that the effects are distinct across sites and comparable across sexes.

Determination of the relationship of visphatin and homocysteine levels with indicators of glucose metabolism and lipid metabolism in peri- and postmenopause women with type 2 diabetes mellitus and osteoarthritis

Type 2 diabetes mellitus (T2DM), among other modern diseases, certainly occupies a leading position today. Moreover, the comorbid combination of T2DM and osteoarthritis (OA) is a common example of the development of complications, disability and mortality these days. As you know, T2DM develops against the background of obesity and overweight. A significant group of patients prone to these pathologies are peri- and postmenopausal women. Estrogen deficiency during this period worsens the course of these interdependent conditions. Therefore, searching for ways of early diagnosis of OA in women with T2DM is an urgent task of internal medicine. Purpose. To determine the interdependencies of indicators of glucose metabolism and lipid metabolism with levels of visfatin (VF) and homocysteine (HC) in women with T2DM and OA in peri- and postmenopause. Methods. For the study, 120 thematic women in peri- and postmenopause were selected and were divided into three groups: 1st (n=20) - women with a mono-course of T2DM; 2nd (n=20) – with a mono-course of OA; 3rd (n=64) – with the comorbid course of T2DM and OA. The control group (CG) consisted of 16 relatively healthy women of the appropriate age. Diagnoses of T2DM and OA were established in accordance with the current Orders of the Ministry of Health of Ukraine. Laboratory diagnostic methods were performed according to standard methods. The results. According to the obtained results, the presence of interdependencies of all indicators of lipid metabolism and glucose-insulin metabolism was reliably determined, which indicated direct correlations (mostly of moderate strength) with the levels of HC and VF in the blood of the examinees, most pronounced in the comorbid combination of T2DM and OA in peri- and postmenopause. Conclusions. In work, an analysis of the correlations of indicators of glucose metabolism and lipid metabolism with disturbances in the metabolism of VF and HC in women with T2DM and OA in pre- and postmenopause was carried out, and their interdependent relationships were determined. The highest levels of VF and HC were recorded in the group of women with comorbid pathology of T2DM and OA.

A Guide for Understanding and Designing Mendelian Randomization Studies in the Musculoskeletal Field

Mendelian randomization (MR) is an increasingly popular component of an epidemiologist's toolkit, used to provide evidence of a causal effect of one trait (an exposure, eg, body mass index [BMI]) on an outcome trait or disease (eg, osteoarthritis). Identifying these effects is important for understanding disease etiology and potentially identifying targets for therapeutic intervention. MR uses genetic variants as instrumental variables for the exposure, which should not be influenced by the outcome or confounding variables, overcoming key limitations of traditional epidemiological analyses. For MR to generate a valid estimate of effect, key assumptions must be met. In recent years, there has been a rapid rise in MR methods that aim to test, or are robust to violations of, these assumptions. In this review, we provide an overview of MR for a non-expert audience, including an explanation of these key assumptions and how they are often tested, to aid a better reading and understanding of the MR literature. We highlight some of these new methods and how they can be useful for specific methodological challenges in the musculoskeletal field, including for conditions or traits that share underlying biological pathways, such as bone and joint disease. © 2022 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

The Polygenic Risk Score Knowledge Base offers a centralized online repository for calculating and contextualizing polygenic risk scores

The process of identifying suitable genome-wide association (GWA) studies and formatting the data to calculate multiple polygenic risk scores on a single genome can be laborious. Here, we present a centralized polygenic risk score calculator currently containing over 250,000 genetic variant associations from the NHGRI-EBI GWAS Catalog for users to easily calculate sample-specific polygenic risk scores with comparable results to other available tools. Polygenic risk scores are calculated either online through the Polygenic Risk Score Knowledge Base (PRSKB; https://prs.byu.edu ) or via a command-line interface. We report study-specific polygenic risk scores across the UK Biobank, 1000 Genomes, and the Alzheimer's Disease Neuroimaging Initiative (ADNI), contextualize computed scores, and identify potentially confounding genetic risk factors in ADNI. We introduce a streamlined analysis tool and web interface to calculate and contextualize polygenic risk scores across various studies, which we anticipate will facilitate a wider adaptation of polygenic risk scores in future disease research.

Celastrol ameliorates osteoarthritis via regulating TLR2/NF-κB signaling pathway

Objectives: Osteoarthritis (OA) is a joint disease characterized by degeneration of joint cartilage and is a significant cause of severe joint pain, physical disability, and impaired quality of life in the aging population. Celastrol, a Chinese herbal medicine, has attracted wide interests because of its anti-inflammatory effects on a variety of diseases. This study aimed to investigate the effect of celastrol on OA as well as the mechanisms in vivo and in vitro.

Methods: A rat knee OA model was established using “medial collateral ligament transection (MCLT) + partial meniscectomy (pMMT)”. Eight weeks after surgery, the OA rats started to receive intra-articular injection of celastrol (1 mg/kg) once a week. Safranin O-fast green (S&F) and hematoxylin and eosin (H&E) staining were used to estimate histopathological changes. Micro-CT was used to evaluate bone volume of the subchondral bone of the knee joint. Chondrocytes were isolated from the knee cartilage of rats and OA patients. Enzyme linked immunosorbent assay (ELISA), Western Blot (WB), Polymerase Chain Reaction (PCR), and Immunohistochemistry (IHC) were used to detect the expression of inflammatory factors and stromal proteins, respectively.

Results: We found that celastrol treatment significantly delayed the progression of cartilage damage with a significant reduction in osteophyte formation and bone resorption in OA rat model. In IL-1β-stimulated rat chondrocytes, celastrol significantly suppressed the production of inflammatory factors such as cyclooxygenase-2 (COX2), interleukin-6 (IL-6), and prostaglandin E2 (PEG2), and reduced IL-1β-induced matrix degradation by down-regulating the expression of matrix metalloproteinase 13 (MMP13). In addition, we found that toll-like receptor 2 (TLR2) was up-regulated in OA patients and rat knee OA models, while celastrol inhibited TLR2 signal and its downstream nuclear factor-kappa B (NF-κB) phosphorylation.

Conclusion: In summary, celastrol may improve OA by inhibiting the TLR2/NF-κB signaling pathway, which provides innovative strategies for the treatment of OA.

Osteoarthritis - Insights From Recent Research

Osteoarthritis (OA) is the most common form of arthritis and is a growing public health concern in the aging society. In rapidly aging societies such as in Korea, the increasing prevalence of OA may present serious new health issues. There is no treatment for OA that can either prevent or slow the progression of joint damage. For the development of effective therapeutics, precise understating of its pathogenesis is important. In this review, the current evidence of etiopathogenesis of OA is discussed. First, while epidemiologic study of OA are still dominated by reports from Western countries, findings from Korean epidemiologic studies are highlighted. Then, recent progresses in genetics, especially in the field of genome wide association study and mendelian randomization studies, are reviewed with focus on Asian population. Lastly, sex difference in pain etopathogenesis is reviewed. Studies of OA pathogenesis including epidemiology, genetics, animal model and pain signaling will aid in progress towards treatment of OA.

Causal Associations of Circulating Lipids with Osteoarthritis: A Bidirectional Mendelian Randomization Study

Osteoarthritis (OA) imposes an increasing social burden due to global activity limitations, especially among the aged. Links between circulating lipids and OA have been reported; however, confounding data from observational studies have hindered causal conclusions. We used Mendelian randomization (MR) approach to evaluate the genetic causal effects of circulating apolipoproteins and lipoprotein lipids on OA risk. Genetic instruments at the genome-wide significance level (p < 5 × 10−8) were selected from genome-wide association studies (n = 393,193−441,016 individuals). Summary-level OA data were obtained from the UK Biobank (39,427 cases, 378,169 controls). Bidirectional two-sample Mendelian randomization (MR) analyses used MR-Egger, weighted median, and MR-PRESSO for sensitivity analysis. Genetic predisposition to 1-SD increments of Apolipoprotein B (APOB), and low-density lipoprotein (LDL) was associated with a decreased risk of knee or hip OA (KHOA) (odds ratio (OR) = 0.925, 95% confidence interval (95% CI): 0.881−0.972, p = 0.002; OR = 0.898, 95% CI: 0.843−0.957, p = 0.001) and hip OA (HOA) (OR = 0.894; 95% CI: 0.832−0.961, p = 0.002; OR = 0.870 95% CI: 0.797−0.949, p = 0.002). Genetically predicted APOB showed an association with knee OA (KOA) (OR per SD increase, 0.930, 95% CI: 0.876−0.987, p = 0.016). The OR of KOA was 0.899 (95% CI: 0.835−0.968, p = 0.005) for a 1-SD increase in LDL. Apolipoprotein A1, high-density lipoprotein, and triglycerides showed no association. Inverse MR showed no causal effect of KOA, HOA, or KHOA on these serum lipids. Distinct protective genetic-influence patterns were observed for APOB and LDL on OA, offering new insights into relationships between lipids and OA risk and a better understanding of OA etiology.

Validation of knee osteoarthritis case identification algorithms in a large electronic health record database

Purpose:

To facilitate studies of knee osteoarthritis (OA) in large databases, case finding algorithms with high levels of diagnostic performance are needed.

Methods:

From a UK general practitioner (GP) practice derived database, we selected adults ages 40–90 years meeting algorithms that included various combinations of codes for knee OA or knee pain and imaging. The GP for each patient was mailed a questionnaire to assess the cause of knee pain and provide knee x-ray and/or MRI findings. We considered knee pain with x-ray and/or MRI findings consistent with OA the gold standard. We calculated positive predictive values (PPV) and sensitivity for case identification algorithms.

Results:

Of 100 questionnaires sent, 93 were returned; we excluded 8 subjects who had other rheumatic disorders or total knee replacements. Among those with one code for OA, the PPV was 64% (95% CI = 49%–79%) and it increased to 92% (95% CI = 76%–100%) when two or more OA codes over six months were required. The increase in PPV was accompanied by a drop in sensitivity from 44% (95% CI = 31%–57%) to 19% (95% CI = 9%–30%). Use of one pain code yielded similar results to use of one OA code. Requiring two or more knee pain codes over six months yielded a PPV of 68% (95% CI = 49%–88%) and sensitivity of 26% (95% CI = 15%–38%).

Discussion:

A case identification algorithm requiring two or more knee OA codes yielded the highest PPV at the cost of reduced sensitivity. Tradeoffs between PPV and sensitivity will need to be weighed alongside study goals when selecting a case identification algorithm.

Epidemiology of osteoarthritis

OBJECTIVE

To summarize the current state of the evidence regarding osteoarthritis (OA) prevalence, incidence and risk factors at the person-level and joint-level.

DESIGN

This was a narrative review that took a comprehensive approach regarding inclusion of potential risk factors. The review complements prior reviews of OA epidemiology, with a focus on new research and emerging topics since 2017, as well as seminal studies.

RESULTS

Studies continue to illustrate the high prevalence of OA worldwide, with a greater burden among older individuals, women, some racial and ethnic groups, and individuals with lower socioeconomic status. Modifiable risk factors for OA with the strongest evidence are obesity and joint injury. Topics of high interest or emerging evidence for a potential association with OA risk or progression include specific vitamins and diets, high blood pressure, genetic factors, metformin use, bone mineral density, abnormal joint shape and malalignment, and lower muscle strength/quality. Studies also continue to highlight the heterogenous nature of OA, with strong interest in understanding and defining OA phenotypes.

CONCLUSIONS

OA is an increasingly prevalent condition with worldwide impacts on many health outcomes. The strong evidence for obesity and joint injury as OA risk factors calls for heightened efforts to mitigate these risks at clinical and public health levels. There is also a need for continued research regarding how potential person- and joint-level risk factors may interact to influence the development and progression of OA.

Causal Relationship of Genetically Predicted Serum Micronutrients Levels With Sarcopenia: A Mendelian Randomization Study

Objectives

Previous observational studies have suggested associations between concentrations of several circulating micronutrients and sarcopenia. However, the causality inferred from those studies was subjected to residual confounding and reverse causation. Therefore, we aimed to examine the causal effects of the levels of genetically predicted serum micronutrients on sarcopenia.

Methods

Single nucleotide polymorphisms (SNPs) were chosen from large-scale genome-wide association studies of participants only with European descent and were used as genetic instruments for the levels of 10 serum micronutrients (calcium, magnesium, selenium, copper, iron, zinc, Vitamin A, Vitamin B12, Vitamin D, and Vitamin E). Sarcopenia was defined by referencing to the 2019 definition given by the European Working Group on Sarcopenia in Older People (EWGSOP). A two-sample Mendelian randomization (MR) analysis was carried out to examine the associations between the levels of genetically predicted serum micronutrients and the risk of sarcopenia. Then, sensitivity analyses (including weighted median, MR-Egger and leave-one-out sensitivity analyses) were performed to evaluate the robustness of study findings. The estimates were presented as odds ratio (OR) with their 95% confidence intervals (CIs) per one standard deviation (SD) increase in the exposures.

Results

A total of 378,635 UK Biobank participants, including 572 participants who were identified with sarcopenia, were included in this study. The iron status was shown to have a clear effect on the risk of sarcopenia based on MR analyses. The per one SD increment in the genetically-determined serum iron level corresponded to a 53% increase in the risk of sarcopenia (OR = 1.53, 95% CI: 1.31-1.78, P = 0.001). The exclusion of SNPs of the circulating iron level (i.e., rs1799945 SNP, rs1800562 SNP or rs855791 SNP) did not attenuate the magnitude of the signal in MR analysis. There was little evidence supporting the associations between other remaining micronutrients and sarcopenia.

Conclusions

An increased risk of sarcopenia was observed with a genetically higher concentration of iron, suggesting that iron may play a role in the occurrence or development of sarcopenia.

Effect of blood lipids and lipid-lowering therapies on osteoarthritis risk: A Mendelian randomization study

Background

We aimed to investigate the effects of blood lipids and lipid-lowering agents on osteoarthritis (OA) risk.

Materials and methods

We performed Mendelian randomization (MR) analyses to estimate the causal effect of blood low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) levels on knee and hip OA. Single nucleotide polymorphisms (SNPs) were selected from large genome-wide association studies (GWASs) of individuals of European ancestry as genetic instruments for blood lipid levels. The associations of selected genetic instruments with knee and hip OA were estimated in a recent GWAS of the UK Biobank and arcOGEN datasets. Univariate and multivariate MR analyses were performed to detect and adjust for potential pleiotropy. Furthermore, genetic instruments in HMGCR, NPC1L1, and PCSK9 regions were used to mimic LDL-C-lowering effects of statin, ezetimibe, and evolocumab, respectively.

Results

Genetically determined LDL-C increments led to reduced risks of both knee OA (OR = 0.91 per 1-SD increment, 95% CI: 0.86-0.95, P = 6.3 × 10^-5) and hip OA (OR = 0.92, 95% CI: 0.85-0.99, P = 0.027). Multivariate MR analysis proved that the effect was independent of HDL-C, TG, and body mass index. TG increment was associated with reduced risks of hip OA in the univariate MR analysis; however, this was not supported by the multivariate MR analysis. Genetically proxied LDL-C-lowering effects of statins are related to increased risks of knee OA but not hip OA.

Conclusions

The findings suggested that LDL-C increments have independent protective effects on both knee and hip OA. LDL-C-lowering effects of statins may increase the risk of knee OA.

Causal role of high body mass index in multiple chronic diseases: a systematic review and meta-analysis of Mendelian randomization studies

BACKGROUND

Obesity is a worldwide epidemic that has been associated with a plurality of diseases in observational studies. The aim of this study was to summarize the evidence from Mendelian randomization (MR) studies of the association between body mass index (BMI) and chronic diseases.

METHODS

PubMed and Embase were searched for MR studies on adult BMI in relation to major chronic diseases, including diabetes mellitus; diseases of the circulatory, respiratory, digestive, musculoskeletal, and nervous systems; and neoplasms. A meta-analysis was performed for each disease by using results from published MR studies and corresponding de novo analyses based on summary-level genetic data from the FinnGen consortium (n = 218,792 individuals).

RESULTS

In a meta-analysis of results from published MR studies and de novo analyses of the FinnGen consortium, genetically predicted higher BMI was associated with increased risk of type 2 diabetes mellitus, 14 circulatory disease outcomes, asthma, chronic obstructive pulmonary disease, five digestive system diseases, three musculoskeletal system diseases, and multiple sclerosis as well as cancers of the digestive system (six cancer sites), uterus, kidney, and bladder. In contrast, genetically predicted higher adult BMI was associated with a decreased risk of Dupuytren's disease, osteoporosis, and breast, prostate, and non-melanoma cancer, and not associated with Alzheimer's disease, amyotrophic lateral sclerosis, or Parkinson's disease.

CONCLUSIONS

The totality of the evidence from MR studies supports a causal role of excess adiposity in a plurality of chronic diseases. Hence, continued efforts to reduce the prevalence of overweight and obesity are a major public health goal.

The Causal Relationship Between Body Mass Index and the Risk of Osteoarthritis

Objective

The study aimed to explore the causal effect of body mass index (BMI) on osteoarthritis.

Methods

The genome-wide association data of BMI and osteoarthritis were obtained via the Mendelian randomization (MR)-base platform. Single nucleotide polymorphisms (SNPs) significantly associated with BMI were identified and used as instrumental variables, and the causal relationship between BMI and osteoarthritis was examined using the two-sample MR research method. Three statistical methods including inverse-variance weighted (IVW) method, weighted median estimator, and MR-Egger regression were employed.

Results

A total of 79 SNPs significantly associated with BMI were identified in the study (P<5×10⁻⁸; linkage disequilibrium r² <0.1). Consistent association between BMI and osteoarthritis was observed when evaluated by different methods (IVW: odds ratio (OR) 1.028, 95% confidence interval (CI) 1.021–1.036; weighted median estimator: OR 1.028, 95% CI 1.019–1.037; MR-Egger regression: OR 1.028, 95% CI 1.009–1.046), which suggests that BMI is positively associated with increased risk of osteoarthritis. There was no evidence that the observed causal effect between BMI and the risk of osteoarthritis was affected by genetic pleiotropy (MR-Egger intercept 1.3×10⁻⁵, P=0.959).

Conclusion

The MR analysis provided the strong evidence to indicate that BMI might be causally associated with the risk of osteoarthritis.

Association Between Environmental Factors and Asthma Using Mendelian Randomization: Increased Effect of Body Mass Index on Adult-Onset Moderate-to-Severe Asthma Subtypes

Although asthma is one of the most common chronic diseases throughout all age groups, its etiology remains unknown, primarily due to its heterogeneous characteristics. We examined the causal effects of various environmental factors on asthma using Mendelian randomization and determined whether the susceptibility to asthma due to the causal effect of a risk factor differs between asthma subtypes, based on age of onset, severity of asthma, and sex. We performed Mendelian randomization analyses (inverse variance weighted, weighted median, and generalized summary-data-based Mendelian randomization) using UK Biobank data to estimate the causal effects of 69 environmental factors on asthma. Additional sensitivity analyses (MR-Egger regression, Cochran’s Q test, clumping, and reverse Mendelian randomization) were performed to ensure minimal or no pleiotropy. For confirmation, two-sample setting analyses were replicated using BMI SNPs that had been reported by a meta-genome-wide association study in Japanese and European (GIANT) populations and a genome-wide association study in control individuals from the UK Biobank. We found that BMI causally affects the development of asthma and that the adult-onset moderate-to-severe asthma subtype is the most susceptible to causal inference by BMI. Further, it is likely that the female subtype is more susceptible to BMI than males among adult asthma cases. Our findings provide evidence that obesity is a considerable risk factor in asthma patients, particularly in adult-onset moderate-to-severe asthma cases, and that weight loss is beneficial for reducing the burden of asthma.

Cardiometabolic traits mediating the effect of education on osteoarthritis risk: a Mendelian randomization study

OBJECTIVE

To investigate which cardiometabolic factors underlie clustering of osteoarthritis (OA) with cardiovascular disease, and the extent to which these mediate an effect of education.

DESIGN

Genome-wide association study (GWAS) of OA was performed in UK Biobank (60,800 cases and 328,251 controls) to obtain genetic association estimates for OA risk. Genetic instruments and association estimates for body mass index (BMI), low-density lipoprotein cholesterol (LDL-C), systolic blood pressure (SBP), smoking and education were obtained from existing GWAS summary data (sample sizes 188,577-866,834 individuals). Two-sample Mendelian randomization (MR) analyses were performed to investigate the effects of exposure traits on OA risk. MR mediation analyses were undertaken to investigate whether the cardiometabolic traits mediate any effect of education on OA risk.

RESULTS

MR analyses identified protective effects of higher genetically predicted education (main MR analysis odds ratio (OR) per standard deviation increase 0.59, 95% confidence interval (CI) 0.54-0.64) and LDL-C levels (OR 0.94, 95%CI 0.91-0.98) on OA risk, and unfavourable effects of higher genetically predicted BMI (OR 1.82, 95%CI 1.73-1.92) and smoking (OR 2.23, 95%CI 1.85-2.68). There was no strong evidence of an effect of genetically predicted SBP on OA risk (OR 0.98, 95% CI 0.90-1.06). The proportion of the effect of genetically predicted education mediated through genetically predicted BMI and smoking was 35% (95%CI 13-57%).

CONCLUSIONS

These findings highlight education, obesity and smoking as common mechanisms underlying OA and cardiovascular disease. These risk factors represent clinical and public health targets for reducing multi-morbidity related to the burden these common conditions.

Metabolic osteoarthritis - relation of diabetes and cardiovascular disease with knee osteoarthritis

OBJECTIVE

There is an interest in identifying a metabolic OA phenotype. We therefore assessed the relation of diabetes and cardiovascular disease to prevalent and incident radiographic (ROA) and symptomatic knee osteoarthritis (SxOA).

DESIGN

In two large cohort studies of individuals with or at risk for knee OA, the Multicenter Osteoarthritis Study (MOST) and Osteoarthritis Initiative (OAI), participants self-reported diabetes and cardiovascular disease (CVD) at baseline. We assessed the relation of baseline diabetes and CVD (exposures) to ROA and SxOA cross-sectionally and after 60 (MOST) or 48 (OAI) months of follow-up using logistic regression with GEE to account for 2 knees within an individual, adjusting for potential confounders.

RESULTS

In MOST, 6,020 knees of 3,021 participants (60.1% female, mean ± SD age 62.5 ± 8.1, mean BMI 30.7 ± 6.0, 83.3% Caucasian) were included in the analyses. In OAI, 8,645 knees of 4,339 participants (58.2% female, mean ± SD age 61.1 ± 9.2, mean BMI 28.6 ± 4.8, 80.3% Caucasian) were included. We found no significant associations between prevalent diabetes or CVD and prevalent or incident ROA or SxOA. Effect estimates for prevalent ROA and SxOA ranged from 0.80 (95% CI 0.63-1.03) to 1.17 (0.91-1.51). Effect estimates for incident ROA ranged from 0.80 (0.58-1.11) to 0.88 (0.60-1.29) in MOST and from 0.75 (0.50-1.14) to 1.19 (0.81-1.74) in OAI, and for incident SxOA from 0.93 (0.65-1.31) to 1.22 (0.89-1.67) in MOST and from 0.82 (0.59-1.16) to 1.19 (0.85-1.66) in OAI).

CONCLUSIONS

Diabetes and CVD were not associated with prevalent or incident knee OA.

Osteoarthritis year in review: genetics, genomics, epigenetics

OBJECTIVE

In this review, we have highlighted advances in genetics, genomics and epigenetics in the field of osteoarthritis (OA) over the past year.

METHODS

A literature search was performed using PubMed and the criteria: "osteoarthritis" and one of the following terms "genetic(s), genomic(s), epigenetic(s), epigenomic(s), noncoding RNA, microRNA, long noncoding RNA, lncRNA, circular RNA, RNA sequencing, single cell sequencing, or DNA methylation between April 1, 2019 and April 30, 2020.

RESULTS

We identified 653 unique publications, many studies spanned multiple search terms. We summarized advances relating to evolutionary genetics, pain, ethnicity specific risk factors, functional studies of gene variants, and interactions between coding and non-coding RNAs in OA pathogenesis.

CONCLUSIONS

Studies have identified variants contributing to OA susceptibility, candidate biomarkers for diagnosis and prognosis, as well as promising therapeutic candidates. Validation in multiple cohorts, multi-omics strategies, and machine learning aided computational analyses have all contributed to the strength of published literature. Open access data-sets, greater sample sizes to capture broader populations and understanding disease mechanisms by investigating the interactions between multiple tissue types will further aid in progress towards understanding and curing OA.

Osteoarthritis year in review 2020: epidemiology & therapy

This personal choice of research themes and highlights from within the past year (1 May 2019 to 14 April 2020) spans descriptive, analytical-observational, and intervention studies. Descriptive estimates of the burden of osteoarthritis continue to underscore its position as a leading cause of disability worldwide, but whose burden is often felt greatest among disadvantaged and marginalised communities. Many of the major drivers of that burden are known but epidemiological studies continue the important work of elaborating on their timing, dose, specificity, and reversibility and placing them within an appropriate multi-level framework. A similar process of elaboration is seen also in studies (re-)estimating the relative benefits and risks of existing interventions, in some cases helping to identify low-value care, unwarranted variation, and initiating processes of deprescribing and decommissioning. Such research need not engender therapeutic nihilism. Our review closes by highlighting some emerging evidence on the efficacy and safety of novel therapeutic interventions and with a selective roll-call of methodological and meta-research in OA illustrating the continued commitment to improving research quality.

Testing lipid markers as predictors of all-cause morbidity, cardiac disease, and mortality risk in captive western lowland gorillas (Gorilla gorilla gorilla)

Great apes and humans develop many of the same health conditions, including cardiac disease as a leading cause of death. In humans, lipid markers are strong predictors of morbidity and mortality risk. To determine if they similarly predict risk in gorillas, we measured five serum lipid markers and calculated three lipoprotein ratios from zoo-housed western lowland gorillas (aged 6-52 years, n = 61 , subset with routine immobilizations only: n = 47 ): total cholesterol (TC), triglycerides (TGs), high-density lipoprotein (HDL), low-density lipoprotein (LDL), apolipoprotein A1 (apoA1), TC / HDL , LDL / HDL , and TG / HDL . We examined each in relation to age and sex, then analyzed whether they predicted all-cause morbidity, cardiac disease, and mortality using generalized linear models (GLMs). Older age was significantly associated with higher TG, TC / HDL , LDL / HDL , and TG / HDL , and lower HDL and apoA1. With all ages combined, compared to females, males had significantly lower TG, TC / HDL , LDL / HDL , and TG / HDL , and higher HDL. Using GLMs, age, sex, and lower LDL / HDL were significant predictors of all-cause morbidity; this is consistent with research demonstrating lower LDL in humans with arthritis, which was the second most prevalent condition in this sample. In contrast to humans, lipid markers were not better predictors of cardiac disease and mortality risk in gorillas, with cardiac disease best predicted by age and sex alone, and mortality risk only by age. Similar results were observed when multimodel inference was used as an alternative analysis strategy, suggesting it can be used in place of or in addition to traditional methods for predicting risk.

Reduction in Osteoarthritis Risk After Treatment With Ticagrelor Compared to Clopidogrel: A Propensity Score-Matching Analysis

OBJECTIVE

Osteoarthritis (OA) is a common cause of joint pain and disability, and effective treatments are lacking. Extracellular adenosine has antiinflammatory effects and can prevent and treat OA in animal models. Ticagrelor and clopidogrel are both used in patients with coronary artery disease, but only ticagrelor increases extracellular adenosine levels. This study was undertaken to determine whether treatment with ticagrelor was associated with a lower risk of OA.

METHODS

We conducted a 1:2 propensity score-matching analysis using data from 2011-2017 in the Optum Clinformatics Data Mart. Patients who had received either ticagrelor or clopidogrel for ≥90 days were included in our study, and patients with a prior diagnosis of OA or inflammatory arthritis were excluded. OA was identified using International Classification of Diseases codes. The primary outcome was the time to diagnosis of OA after treatment with ticagrelor versus clopidogrel.

RESULTS

Our propensity score-matched cohort consisted of 7,007 ticagrelor-treated patients and 14,014 clopidogrel-treated patients, with a median number of days receiving treatment of 287 and 284, respectively. For both groups, the mean age was 64 years, and 73% of the patients were male. Multivariate Cox regression analysis estimated a hazard ratio for developing OA of 0.71 (95% confidence interval 0.64-0.79) (P < 0.001) after treatment with ticagrelor compared to clopidogrel.

CONCLUSION

Treatment with ticagrelor was associated with a 29% lower risk of developing OA compared to treatment with clopidogrel over 5 years of follow-up. We hypothesize that the reduction in OA seen in patients who received ticagrelor may in part be due to increased extracellular adenosine levels.

Setting up distinctive outcome measures for each osteoarthritis phenotype

Osteoarthritis (OA) is an evolving chronic joint disease with a huge global impact. Given the intricate nature of the etiopathogenesis and subsequent high heterogeneity in the clinical course of OA, it is crucial to discriminate between etiopathogenic endotypes and clinical phenotypes, especially in the early stages of the disease. In this sense, we propose that an OA phenotype should be properly assessed with a set of outcome measures including those specifically related to the main underlying pathophysiological mechanisms. Thus, each OA phenotype can be related to different and clinically meaningful outcomes. OA phenotyping would lead to an adequate patient stratification in well-designed clinical trials and the discovery of precise therapeutic approaches. A significant effort will be required in this field in light of inconclusive results of clinical trials of tissue-targeting agents for the treatment of OA.

Causal Factors for Knee, Hip, and Hand Osteoarthritis: A Mendelian Randomization Study in the UK Biobank

OBJECTIVE

There is no curative treatment for osteoarthritis (OA), which is the most common form of arthritis. This study was undertaken to identify causal risk factors of knee, hip, and hand OA.

METHODS

Individual-level data from 384,838 unrelated participants in the UK Biobank study were analyzed. Mendelian randomization (MR) analyses were performed to test for causality for body mass index (BMI), bone mineral density (BMD), serum high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglyceride levels, type 2 diabetes, systolic blood pressure (BP), and C-reactive protein (CRP) levels. The primary outcome measure was OA determined using hospital diagnoses (all sites, n = 48,431; knee, n = 19,727; hip, n = 11,875; hand, n = 2,330). Odds ratios (ORs) with 95% confidence intervals (95% CIs) were calculated.

RESULTS

MR analyses demonstrated a robust causal association of genetically determined BMI with all OA (OR per SD increase 1.57 [95% CI 1.44-1.71]), and with knee OA and hip OA, but not with hand OA. Increased genetically determined femoral neck BMD was causally associated with all OA (OR per SD increase 1.14 [95% CI 1.06-1.22]), knee OA, and hip OA. Low systolic BP was causally associated with all OA (OR per SD decrease 1.55 [95% CI 1.29-1.87]), knee OA, and hip OA. There was no evidence of causality for the other tested metabolic factors or CRP level.

CONCLUSION

Our findings indicate that BMI exerts a major causal effect on the risk of OA at weight-bearing joints, but not at the hand. Evidence of causality of all OA, knee OA, and hip OA was also observed for high femoral neck BMD and low systolic BP. However, we found no evidence of causality for other metabolic factors or CRP level.