Association of Decrease in Body Mass Index With Reduced Incidence and Progression of the Structural Defects of Knee Osteoarthritis: A Prospective Multi-Cohort Study

Association of MRI-based knee osteoarthritis structural phenotypes with short-term structural progression and subsequent total knee replacement

BACKGROUND

The failure of disease-modifying osteoarthritis drugs (DMOADs) trials lies mainly in the heterogeneity of the disease, which calls for a more precise population with specific progression and outcomes. This study aimed to determine whether and which MRI-based structural phenotype of knee osteoarthritis (KOA) is associated with short-term structural progression and subsequent total knee replacement (TKR).

METHODS

A longitudinal study was conducted among participants with baseline Kellgren-Lawrence grade (KLG) ≥ 2 from the Osteoarthritis Initiative (OAI). The structural phenotypes at baseline were defined as subchondral bone, meniscus/cartilage and inflammatory phenotypes according to the MRI Osteoarthritis Knee Score (MOAKS). The primary outcome was the progression of structural abnormalities within 24 months and multivariable logistic regressions were applied to evaluate the associations. The secondary outcome was the incidence of TKR during 108 months. Cox regressions and Kaplan-Meier survival curves were used for the analysis.

RESULTS

A total of 733 participants with KOA were finally included in our study, with 493 (67.3%) having the three main structural phenotypes. For the primary outcome, the subchondral bone phenotype (OR [95% CI]:1.71 [1.02, 2.83], 1.52 [1.06, 2.18], 1.65 [1.11, 2.42], respectively) and the inflammatory phenotype (OR [95% CI]: 1.69 [1.05, 2.74], 1.82 [1.31, 2.52], 2.15 [1.48, 3.14], respectively) were both associated with the short-term progression of joint space narrowing, osteophytes and sclerosis in 24 months, whereas the meniscus/cartilage phenotype was only associated with the progression of osteophytes and sclerosis. For the secondary outcome, the subchondral bone phenotype (HR [95% CI]: 1.71 [1.06-2.78]) and inflammatory phenotype (HR [95%CI]: 2.00 [1.02-2.67]) were associated with shorter time to subsequent TKR, but not the meniscus/cartilage phenotype. Besides, the cumulative effect when the structural phenotype overlapped was confirmed in both outcomes.

CONCLUSIONS

The subchondral bone phenotype and inflammatory phenotype were associated with the progression of joint space narrowing, osteophytes and sclerosis in 24 months, along with subsequent TKR in 108 months. Besides, additive effects of overlapped phenotypes were further determined. These phenotypes could serve as valuable screening tools for future clinical trials and provide guidance for risk evaluation.

The association between accelerated biological aging and the risk of osteoarthritis: a cross-sectional study

Background

Biological age (BA) offers an effective assessment of true aging state. The progression of Osteoarthritis (OA) is closely associated with an increase in chronological age, the correlation between BA and OA has not been fully elucidated.

Methods

This study analyzed data from the National Health and Nutrition Examination Survey (NHANES) 2005-2018. Thirteen commonly used clinical traits were employed to calculate two measures of BA: the Klemera-Doubal method age (KDM-Age) and phenotypic age (Pheno-Age). The residuals of the regression of these ages based on chronological age were calculated as KDM-Age or Pheno-Age acceleration, respectively. OA was determined through self-reported prior diagnoses. The prevalence of OA across different quartiles of BA was compared using weighted chi-square tests and linear trend tests. The association between BA and OA was assessed using weighted multivariate logistic regression models.

Results

A total of 30,547 participants aged ≥20 years were included in this study, 3,922 (14%) were diagnosed with OA. Participants with OA exhibited higher chronological age, KDM-Age, Pheno-Age, KDM-Age advance, and Pheno-Age advance compared to those without OA (p < 0.001). The prevalence of OA significantly increased with higher quartiles of KDM-Age advance and Pheno-Age advance (P for trend < 0.001). In the fully adjusted model, compared to the lowest quartile (Q1) of KDM-Age advance, the highest quartile (Q4) was associated with a 36.3% increased risk of OA (OR = 1.363; 95% CI = 1.213 to 1.532, p < 0.001). The highest quartile of Pheno-Age advance (Q4) was associated with a 24.3% increased risk of OA compared to Q1 (OR = 1.243; 95% CI = 1.113 to 1.389, p < 0.001). In males and young people, no statistical differences were found in OA risk between the highest and the lowest quartiles of KDM-Age advance (p = 0.151) and Pheno-Age advance (p = 0.057), respectively.

Conclusion

Adults with accelerated biological aging have an increased risk of OA, particularly among females and older adults.

The Relationship Between Central Obesity and Osteoarthritis in US Adults: The Mediating Role of Biological Aging Acceleration

OBJECTIVE

This study aims to investigate the association between central obesity and the risk of osteoarthritis, and the mediating role of biological age and biological aging advance in this relationship.

METHODS

The study is based on data from the National Health and Nutrition Examination Survey (NHANES) for the years 2005-2018. Thirteen commonly used clinical traits were used to calculate the Klemera-Doubal method age (KDM-Age) and phenotypic age (Pheno-Age) as two measures of biological aging. Additionally, KDM-Age advance and Pheno-Age advance were calculated as two measures of biological aging advance. Weighted multivariable logistic regression was used to analyze the association between central obesity and the risk of osteoarthritis (OA). Mediation analysis was then applied to elucidate the role of biological aging and biological aging advance in this relationship.

RESULTS

A total of 31,162 subjects aged ≥20 years were included in this study, of which 3,964 subjects reported having OA (14%). Compared to the Non-OA group, the OA group showed significantly higher proportions of central obesity, KDM-Age, KDM-Age advance, PhenoAge, and PhenoAge advance. Compared to the Non-central obesity group, the central obesity group had higher KDM-Age, KDM-Age advance, PhenoAge, PhenoAge advance, and a higher risk of OA (p < 0.05). Additionally, higher KDM-Age, KDM-Age advance, PhenoAge, and PhenoAge advance were positively correlated with the risk of OA (p < 0.05). Mediation analysis revealed that part of the association between central obesity and the risk of OA was mediated by KDM-Age, KDM-Age advance, PhenoAge, and PhenoAge advance (p < 0.05).

CONCLUSION

Central obesity increases the risk of OA, with part of this association being mediated by biological aging and biological aging advance.

Relationship between systemic immune-inflammation index and osteoarthritis: a cross-sectional study from the NHANES 2005-2018

Objective

The study aimed to explore the relationship between systemic inflammatory response index (SIRI) levels and osteoarthritis (OA) using cross-sectional data from the National Health and Nutrition Examination Survey (NHANES) database from 2005 to 2018.

Methods

Using cross-sectional data from the NHANES database from 2005 to 2018, we included 11,381 study participants divided into OA (n = 1,437) and non-OA (n = 9,944) groups. Weighted multivariable regression models and subgroup analyses were employed to investigate the relationship between SIRI and OA. Additionally, restricted cubic spline models were used to explore nonlinear relationships.

Results

This study enrolled 11,381 participants aged ≥20 years, including 1,437 (14%) with OA. Weighted multivariable regression analysis in the fully adjusted Model 3 indicated a correlation between higher levels of SIRI (log2-transformed) and an increased OA risk (odds ratio: 1.150; 95% confidence interval: 1.000-1.323, p < 0.05). Interaction tests showed that the variables did not significantly affect this correlation (p for interaction all >0.05). Additionally, a restricted cubic spline model revealed a nonlinear relationship between log2(SIRI) and OA risk, with a threshold effect showing 4.757 as the critical value of SIRI. SIRI <4.757 showed almost unchanged OA risk, whereas SIRI >4.757 showed rapidly increasing OA risk.

Conclusion

The positive correlation between SIRI and OA risk, with a critical value of 4.757, holds clinical value in practical applications. Additionally, our study indicates that SIRI is a novel, clinically valuable, and convenient inflammatory biomarker that can be used to predict OA risk in adults.

Association of Weight Loss and Weight Gain With Structural Defects and Pain in Hand Osteoarthritis: Data From the Osteoarthritis Initiative

OBJECTIVE

Our aim was to define the association of weight change (weight loss or weight gain) with the incidence and progression of hand osteoarthritis (OA), assessed either by radiography or by pain, using data from the Osteoarthritis Initiative.

METHODS

Among the 4,796 participants, we selected 4,598 participants, excluding those with cancer or rheumatoid arthritis or a body mass index under 18.5 kg/m2. We investigated the association of weight change with incidence and progression of radiographic hand OA and the development and resolution of hand pain. Using multivariable logistic regression, we investigated the association of weight change from baseline to the 4-year follow-up with the incidence and progression of radiographic hand OA at the 4-year follow-up. Additionally, multivariable repeated-measure mixed-effects logistic regression analyzed the association of weight change with the development and resolution of hand pain across 2-year, 4-year, 6-year, and 8-year follow-ups.

RESULTS

No statistically significant associations were observed between weight change and the investigated outcomes. Specifically, for each 5% weight loss, the odds ratios for the incidence and progression of radiographic hand OA were 0.90 (95% confidence interval [95% CI] 0.67-1.23) and 0.92 (95% CI 0.84-1.00), respectively. Similarly, for each 5% weight loss, the odds ratios for the development and resolution of hand pain at the 8-year follow-up were 1.00 (95% CI 0.92-1.09) and 1.07 (95% CI 0.91-1.25), respectively.

CONCLUSION

Our study found no evidence of an association between weight change and the odds of incidence or progression of radiographic hand OA over 4 years, nor the development or resolution of hand pain over 8 years.

Development of radiographic knee osteoarthritis and the associations to radiographic changes and baseline variables in individuals with knee pain: a 2-year longitudinal study

OBJECTIVES

The aim was to study the development of radiographic knee osteoarthritis (RKOA) in individuals with knee pain over 2 years, and the associations between radiographic changes and baseline variables.

DESIGN

Longitudinal cohort study.

PARTICIPANTS AND SETTING

This study is part of the Halland Osteoarthritis cohort. The included 178 individuals, aged 30-67, had knee pain, without cruciate ligament injury or radiographic findings and 67% were women. The presence of RKOA was defined as Ahlbäck score of ≥1 in ≥1 knee. (Ahlbäck grade 1: joint space narrowing in the tibiofemoral joint <3 mm). Diagnosis of clinical KOA was based on the clinical guideline from the National Institute for Health and Care Excellence (NICE). Knee injury and Osteoarthritis Outcome Score (KOOS), pain intensity, physical function, body mass index (BMI) and visceral fat area (VFA) were measured. Associations to RKOA were analysed with logistic regression (OR).

RESULTS

In all, 13.8% (n=24) developed RKOA in 2 years whereof all had clinical KOA at baseline, as defined by NICE. Deterioration to RKOA was significantly associated with higher BMI, OR 1.119 (95% CI 1.024 to 1.223; p=0.013), and VFA, 1.008 (95% CI 1.000 to 1.016; p=0.049), worse knee pain intensity, 1.238 (95% CI 1.028 to 1.490; p=0.024), worse scores for KOOS Pain, 0.964 (95% CI 0.937 to 0.992; p=0.013) and KOOS Symptoms, 0.967 (95% CI 0.939 to 0.996; p=0.027), KOOS Activities of daily living 0.965 (95% CI 0.935 to 0.996; p=0.026) and KOOS Quality of Life 0.973 (95% CI 0.947 to 0.999; p=0.044), at baseline.

CONCLUSIONS

One out of seven individuals with clinical KOA developed RKOA in only 2 years. Baseline variables associated with RKOA after 2 years may possibly be detected early by using the NICE guideline, assessment of obesity and self-reported data of symptoms to support first-line treatment: education, exercise and weight control.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov (NCT04928170).

Osteoarthritis year in review 2023: Epidemiology & therapy

OBJECTIVE

To highlight some important findings from osteoarthritis (OA) epidemiology and therapy research undertaken over the past year.

METHODS

Search of MEDLINE and EMBASE databases between April 1, 2022 to March 3, 2023 using "exp *Osteoarthritis/" as the preliminary search term. The search was limited to articles published in English and including human subjects. Final inclusions were based on perceived importance and results that may inform improved identification of risk factors or OA treatments, as well as OA subgroups of potential relevance to risk factors or treatment approaches.

RESULTS

3182 studies were screened, leaving 208 eligible for inclusion. This narrative review of thirty-three selected studies was arranged into: a) OA predictors - population-based studies, b) Specific predictors of OA and OA outcome; c) Intra-articular injections, and d) OA phenotypes. There was some suggestion of sex differences in predictors of incidence or outcomes. Body mass index changes appear largely to affect knee OA outcomes. Evidence points to a lack of benefit of viscosupplementation in knee OA; findings were variable for other injectables. Studies of OA phenotypes reveal potentially relevant clinical and pathophysiological differences.

CONCLUSIONS

Identifying risk factors for the incidence/progression of OA represents an ongoing and important area of OA research. Sex may play a role in this understanding and bears consideration and further study. For knee injectables other than viscosupplementation, additional high-quality trials appear warranted. Continued investigation and application of phenotyping across the OA disease, illness and care spectrum may be key to developing disease-modifying agents and their appropriate selection for individuals.

Investigating the causal relationship between physical activity and incident knee osteoarthritis: a two-sample Mendelian randomization study

There is evidence that physical activity (PA) has a long-term positive impact on disease. Whether PA is a risk factor for knee osteoarthritis (OA) is still controversial. The purpose of this study was to explore whether there is a causal relationship between PA and knee OA. We extracted PA and knee OA data from genome-wide association study (GWAS) databases. We used single-nucleotide polymorphisms (SNPs) as instrumental variables. We performed MR analysis by random-effects inverse-variance weighting (IVW), MR‒Egger, weighted median, simple mode, and weighted mode methods. We evaluated the stability and reliability of the results through sensitivity analysis. There was no significant association between PA and knee OA (p > 0.05). We did not detect any pleiotropy (MR‒Egger intercept test et al.: p > 0.05). The sensitivity analysis confirmed our results (p > 0.05). There is no causal relationship between PA and knee OA.

Effects of osteoarthritis grades on pain, function and quality of life

BACKGROUND

Osteoarthritis (OA) is a pathology that frequently affects the geriatric population.

OBJECTIVE

To investigate the extent to which pain, functionality, and quality of life change over the progression of OA grades.

METHOD

The study included 161 patients with bilateral OA, whose disease stages ranged from 1 to 4 according to the Kellgren-Lawrence radiographic classification system. Pain was assessed using the Visual Analog Scale (VAS), functionality using the two-minute walk test and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) questionnaire, and quality of life using the Nottingham Health Profile (NHP).

RESULTS

There were significant differences between the groups in terms of age, weight, and body mass index. The VAS, two-minute walk test, and WOMAC scores also significantly differed between the groups (p< 0.05). There was a significant difference between the groups in all domains of the NHP, except for energy (p< 0.05). The two-minute walk test score was negatively correlated with all the remaining evaluation parameters (p< 0.05). No correlation was found between the energy domain of the NHP and body mass index, the VAS score, the two-minute walk test distance, or the total WOMAC score (p> 0.05).

CONCLUSION

After grade 1, the functional impacts of OA on patients increased by an average of four times. Pain was one of the most basic symptoms, the severity of which started to increase in grade 2. With the added effect of diminishing walking capacity over time, the reduction in the quality of life of the patients accelerated as the OA grade progressed.

Researchers in rheumatology should avoid categorization of continuous predictor variables

BACKGROUND

Rheumatology researchers often categorize continuous predictor variables. We aimed to show how this practice may alter results from observational studies in rheumatology.

METHODS

We conducted and compared the results of two analyses of the association between our predictor variable (percentage change in body mass index [BMI] from baseline to four years) and two outcome variable domains of structure and pain in knee and hip osteoarthritis. These two outcome variable domains covered 26 different outcomes for knee and hip combined. In the first analysis (categorical analysis), percentage change in BMI was categorized as ≥ 5% decrease in BMI, < 5% change in BMI, and ≥ 5% increase in BMI, while in the second analysis (continuous analysis), it was left as a continuous variable. In both analyses (categorical and continuous), we used generalized estimating equations with a logistic link function to investigate the association between the percentage change in BMI and the outcomes.

RESULTS

For eight of the 26 investigated outcomes (31%), the results from the categorical analyses were different from the results from the continuous analyses. These differences were of three types: 1) for six of these eight outcomes, while the continuous analyses revealed associations in both directions (i.e., a decrease in BMI had one effect, while an increase in BMI had the opposite effect), the categorical analyses showed associations only in one direction of BMI change, not both; 2) for another one of these eight outcomes, the categorical analyses suggested an association with change in BMI, while this association was not shown in the continuous analyses (this is potentially a false positive association); 3) for the last of the eight outcomes, the continuous analyses suggested an association of change in BMI, while this association was not shown in the categorical analyses (this is potentially a false negative association).

CONCLUSIONS

Categorization of continuous predictor variables alters the results of analyses and could lead to different conclusions; therefore, researchers in rheumatology should avoid it.