Metabolic syndrome linked to higher osteoarthritis risk, UK Biobank study finds

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In a recent article published in BMC Public Healthresearchers investigated the association between metabolic syndrome (MetS), its components, namely, obesity, hyperglycemia, hypertension, and hyperlipidemia [elevated triglycerides (TG) and reduced high-density lipoprotein (HDL)] and the risk of osteoarthritis (OA) using data from the United Kingdom (UK) Biobank.

Study: Metabolic syndrome increases osteoarthritis risk: findings from the UK Biobank prospective cohort study. Image Credit: Dragana Gordic/Shutterstock.comStudy: Metabolic syndrome increases osteoarthritis risk: findings from the UK Biobank prospective cohort study. Image Credit: Dragana Gordic/Shutterstock.com

Background

OA is a chronic degenerative joint disorder with over 250 million patients worldwide. Given its enormous per capita disease management cost of approximately $700-$15,600, all its phenotypes are now receiving attention, including metabolic syndrome-associated osteoarthritis.

Researchers are pursuing evidence of all or any factor(s) contributing to the development and progression of OA.

Examples include the effects of aging, chronic low-grade inflammation, obesity, and unhealthy lifestyles, to name a few. Since MetS is an ensemble of several such clinical risk factors, it is reasonable to evaluate its association with OA risk.

Previous studies have investigated the potential relationship between OA risk and MetS but made contradictory findings.

For instance, a study by Jansen et al. found a correlation between HDL cholesterol, waist circumference, and OA progression, even after adjustment for body mass index (BMI) at baseline; however, Niu et al. found that except for hypertension, adjusting for MetS components, especially BMI, made its association with incident OA nonsignificant.

Moreover, studies have not established the association between MetS and OA risk in low-grade inflammatory states.

Thus, C-reactive protein (CRP) is one of the most common inflammatory markers; however, evidence of its association with MetS is conflicting.

About the study

In the present study, researchers investigated linear and nonlinear associations between MetS and its components and OA risk and whether this association remains significant during inflammation using CRP as its biomarker. 

They defined MetS and its components according to the International Diabetes Federation (IDF) standards, which diagnoses MetS when an individual has central obesity with two or more other components.

Likewise, they identified OA cases for hand, hip, knee, and polyarthrosis till 2021 in the UK Biobank database using the International Classification of Diseases, Tenth Revision (ICD-10) codes.

The team also enquired about the participant's diet, lifestyle, medical history, medications, socio-demographic traits, and physical activity levels using a questionnaire with adapted questions from the International Physical Activity Questionnaire (IPAQ). 

The researchers used Cox proportional risk models to estimate the hazard ratio (HR) and confidence interval (CI) of MetS and its components on OA risk. These models accounted for an individual's lifestyle, age, gender, BMI, and inflammatory markers.

While they used Kaplan-Meier curves to estimate the number of MetS components and the cumulative incidence of OA, a restricted cubic spline was used to identify potential nonlinear associations between MetS components and OA risk.

Finally, the researchers performed sensitivity analyses to check the robustness of the study results.

Results

This study cohort included 370,311 participants with a median age of 58 years, of which 195,700 were females. The prevalence of OA was 12.31% in over 12 years of study follow-up.

The effect of MetS on OA development was higher in those under 65 than those aged ≥65, corroborating evidence from previous studies.

Moreover, the higher the number of MetS components, the higher the OA risk; it was also independent of the genetic risk of OA. Another intriguing observation was that CRP was associated with higher OA risk, and MetS strengthened this association. 

Regarding different MetS components, even though they could not establish a causal relationship, the authors observed a significant link between central obesity and OA risk via multivariable regression analysis.

Obesity likely increases mechanical stress on the joints and alters the metabolism of serum cholesterol, triglycerides (TG), and inflammatory factors to exert these effects.

Further, restricted cubic spline analysis confirmed that high-density lipoprotein (HDL) and TG were nonlinearly associated with OA risk. While elevated HDL decreased the OA risk, increased serum TG levels increased its risk.

Studies have suggested that synovial inflammation and macrophage infiltration due to lipid metabolism disturbances might be causing OA.

Furthermore, the authors observed a marked positive association between diabetes mellitus/hyperglycemia and higher OA risk, even after adjusting for the individual's age, obesity, and gender with HR = 1.13 and 95%CI. 

Finally, the authors noted that ≥3 mg/L of serum CRP levels were associated with an increased OA risk, which increased further by 35% in conjunction with MetS (HR = 1.35, 95% CI), suggesting that even low-grade inflammation strengthened this association.

Conclusions

The present epidemiological study showed robust evidence that obesity, hyperglycemia, and elevated triglycerides, three core MetS components, were positively associated with OA risk (independently). 

MetS increased the OA risk by 15%, with HR = 1.15, 95%CI and its components, central obesity, and hyperglycemia, were associated with a 58% and 13% increased risk of OA, with HRs equal to 1.58 and 1.13: 95%CI, respectively.

Dyslipidemia, specifically in TG and HDL, was also slightly associated with OA risk, with HRs of 1.07 and 1.05, 95%CI, respectively. 

Future studies should investigate the specific mechanisms governing these associations to help develop better OA prevention strategies.

Journal reference:
Neha Mathur

Written by

Neha Mathur

Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.

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