Association between metabolic syndrome and knee structural change on MRI

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.

The Impact of Metabolic Syndrome on Quality of Life Among Individuals With Knee Osteoarthritis Living in Egypt

Background:

Several studies have linked metabolic syndrome (MetS) to osteoarthritis (OA), but they have not looked into how MetS can affect the health-related quality of life (HRQOL) of OA individuals.

Objectives:

We aimed to assess the association of MetS and its components, including obesity, hypertension, hyperglycemia, and dyslipidemia, with HRQOL among Egyptians with knee OA.

Methods:

This cross-sectional study comprised 116 adult Egyptian participants with knee OA. They were divided into 2 groups based on whether or not they had the MetS. All participants were subjected to a thorough medical history taking and a detailed medical examination. The Kellgren and Lawrence (K/L) scale evaluated OA in all individuals using anteroposterior knee radiographs. The Health Assessment Questionnaire-Disability Index (HAQ-DI) and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) were used to assess participants’ HRQOL; their higher scores indicate more disability. Spearman rank and Pearson’s correlation analyses were used to assess the association between variables.

Results:

Diabetes, hypertension, dyslipidemia, and obesity were significantly associated with the OA + MetS group with a prevalence of 77.6%, 82.8%, 77.6%, and 50.0%, respectively. According to the K/L scale, 70.7% of the OA + MetS group had grade IV knee affection. The HAQ-DI and WOMAC scores were significantly (P < .001) higher among the OA + MetS individuals compared with the OA individuals. Interleukin (IL)-6 serum levels were also significantly higher in the OA + MetS group (P = .036) and increased significantly with the more serious radiological damage and functional disability. We found significant positive correlations between HAQ-DI and WOMAC with waist circumference (P = .004, .001), as well as triglycerides (P = .006, .008), cholesterol (P = .041, .048), fasting blood sugar (P < .001, < .001) and significant negative correlations with high-density lipoprotein levels (P = .628, .002).

Conclusions:

Individuals with knee OA with MetS showed more significant radiological damage, severe functional disability, and poor HRQOL. They also had higher levels of IL-6, which correlated significantly with the degree of disability, promoting it as a significant therapeutic target.

Adiponectin, May Be a Potential Protective Factor for Obesity-Related Osteoarthritis

Osteoarthritis (OA) is the most common joint disease in elderly individuals and seriously affects quality of life. OA has often been thought to be caused by body weight load, but studies have increasingly shown that OA is an inflammation-mediated metabolic disease. The current existing evidence suggests that OA is associated with obesity-related chronic inflammation as well as abnormal lipid metabolism in obesity, such as fatty acids (FA) and triglycerides. Adiponectin, a cytokine secreted by adipose tissue, can affect the progression of OA by regulating obesity-related inflammatory factors. However, the specific molecular mechanism has not been fully elucidated. According to previous research, adiponectin can promote the metabolism of FA and triglycerides, which indicates that it is a potential protective factor for OA through many mechanisms. This article aims to review the mechanisms of chronic inflammation, FA and triglycerides in OA, as well as the potential mechanisms of adiponectin in regulating chronic inflammation and promoting FA and triglyceride metabolism. Therefore, adiponectin may have a protective effect on obesity-related OA, which could provide new insight into adiponectin and the related mechanisms in OA.

Investigating the Association of Metabolic Biomarkers With Knee Cartilage Composition and Structural Abnormalities Using MRI: A Pilot Study

OBJECTIVE

The goal of this study was to explore the metabolic syndrome-associated phenotype of osteoarthritis by investigating the cross-sectional associations of glycemic markers and serum lipids with knee cartilage composition and structural abnormalities in middle-aged adults.

DESIGN

Twenty participants between 40 to 70 years of age with Kellgren-Lawrence score 0-1 in at least one knee were recruited at a single center. Knee cartilage composition was assessed using 3.0 T cartilage T₂ and T_1ρ mapping. Evaluation of structural knee abnormalities was performed using the modified Whole-Organ Magnetic Resonance Imaging Score (WORMS). Linear regression was used to assess the associations of standardized fasting glucose (FG), hemoglobin A1c (HbA1c), insulin, total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), non-HDL cholesterol, and triglycerides with cartilage T₂ and T_1ρ as well as WORMS subscores, adjusting for body mass index.

RESULTS

Higher FG and higher HbA1c were associated with higher WORMS meniscus sum (beta coefficient 1.31 [95% confidence interval (CI): 0.57, 2.05], P = 0.002 per standard deviation [SD] increase in FG; beta coefficient 0.90 [95% CI: 0.07, 1.73], P = 0.035 per SD increase in HbA1c). Also, higher total cholesterol and higher non-HDL cholesterol were associated with higher WORMS cartilage sum (beta coefficient 0.94 [95% CI: 0.01, 1.86], P = 0.048 per SD increase in total cholesterol; beta coefficient 1.05 [95% CI: 0.14, 1.96], P = 0.03 per SD increase in non-HDL cholesterol).

CONCLUSIONS

Higher FG and HbA1c were associated with increased meniscal degeneration while higher total and non-HDL cholesterol were associated with increased cartilage degeneration.

Fatty Acid-Binding Protein 4 (FABP4) Is Associated with Cartilage Thickness in End-Stage Knee Osteoarthritis

BACKGROUND

There is no single blood biomarker for the staging of knee osteoarthritis (KOA). The purpose of this study was to assess the relationship of obesity, serum biomarkers, the hip-knee-ankle angle (HKAA) with sonographic cartilage thickness.

METHODS

We conducted a cross-sectional study of n = 33 patients undergoing knee arthroplasty. Body mass index (BMI) was recorded, and patients were grouped based on BMI. Serum blood samples were collected, and the following biomarkers were measured using the ELISA technique (subgroup of n = 23): oxidized low-density lipoprotein (oxLDL), soluble receptor for advanced glycation end-products (sRAGE), fatty acid-binding protein 4 (FABP4), membrane-bound phospholipase A2 (PLA2G2A). The HKAA was analyzed on full-length limb standing x-ray images. Cartilage thickness was assessed on ultrasound images. Multivariable regression analysis was performed to account for confounding.

RESULTS

After adjusting for age, gender, and HKAA, obese patients had thicker medial femoral cartilage (β = 0.165, P = 0.041). Furthermore, lateral cartilage thickness was negatively correlated with FABP4 level after adjusting for of age, gender, BMI, and HKAA (β = -0.006, P = 0.001). Confirming previous studies, after adjustment, FABP4 level was associated with a higher BMI group (β = 42.99, P < 0.001). None of the other markers (oxLDL, PLA2G2A, and sRAGE) was associated with BMI or cartilage thickness.

DISCUSSION

Our results indicate that BMI has a weak, positive association with cartilage thickness in end-stage KOA patients. FABP4 levels were negatively associated with cartilage thickness. While our study is limited by a small sample size, these results further highlight the role of FABP4 as promising biomarkers of burden of disease in KOA.

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.

Metabolic Syndrome and Its Effects on Cartilage Degeneration vs Regeneration: A Pilot Study Using Osteoarthritis Biomarkers

BACKGROUND

Osteoarthritis (OA) of the knee is one of the leading causes of disability characterized by degeneration of hyaline cartilage combined with reparative processes. Its strong association with metabolic syndrome is postulated to be due to both mechanical and biochemical factors. Our study aims to study differential effect of metabolic risk factors on cartilage degeneration and regeneration at biomarker level.

DESIGN

After screening 281 patients presenting with knee pain, 41 patients who met the selection criteria were included and were divided into metabolic (MetS) OA and non-metabolic (Non-MetS) OA phenotypes using National Cholesterol Education Programme-Adult Treatment Panel-III (NCEP-ATP-III) criteria for metabolic syndrome. Serum Cartilage Oligomeric Matrix Protein (COMP) and Procollagen type IIA N terminal Propeptide (PIIANP) levels were used as tools to assess cartilage degeneration and regeneration, respectively.

RESULTS

22 among 41 patients (53.66%) had metabolic syndrome. Covariates like age, gender, Kellgren Lawrence (KL) grades were comparable in both groups. MetS-OA group showed significant increase in serum COMP levels (p = 0.03) with no significant effect on serum PIIANP levels (p = 0.46). Hypertriglyceridemia showed independent association with both cartilage anabolism (p = 0.03) and catabolism (p = 0.03).

CONCLUSION

Metabolic syndrome, though has no effect on cartilage regeneration tends to shift cartilage homeostasis towards degeneration with hypertriglyceridemia showing significant independent effect on cartilage metabolism.

Serum adipokines/related inflammatory factors and ratios as predictors of infrapatellar fat pad volume in osteoarthritis: Applying comprehensive machine learning approaches

OBJECTIVE

The infrapatellar fat pad (IPFP) has been associated with knee osteoarthritis onset and progression. This study uses machine learning (ML) approaches to predict serum levels of some adipokines/related inflammatory factors and their ratios on knee IPFP volume of osteoarthritis patients.

METHODS

Serum and MRI were from the OAI at baseline. Variables comprised the 3 main osteoarthritis risk factors (age, gender, BMI), 6 adipokines, 3 inflammatory factors, and their 36 ratios. IPFP volume was assessed on MRI with a ML methodology. The best variables and models were identified in Total-cohort (n = 678), High-BMI (n = 341) and Low-BMI (n = 337), using a selection approach based on ML methods.

RESULTS

The best model for each group included three risk factors and adipsin/C-reactive protein combined for Total-cohort, adipsin/chemerin; High-BMI, chemerin/adiponectin HMW; and Low-BMI, interleukin-8. Gender separation improved the prediction (13-16%) compared to the BMI-based models. Reproducibility with osteoarthritis patients from a clinical trial was excellent (R: female 0.83, male 0.95). Pseudocodes based on gender were generated.

CONCLUSION

This study demonstrates for the first time that the combination of the serum levels of adipokines/inflammatory factors and the three main risk factors of osteoarthritis could predict IPFP volume with high reproducibility, with the superior performance of the model accounting for gender separation.