Adiponectin is a Mediator of the Association of Adiposity with Radiographic Damage in Rheumatoid Arthritis

Abstract

Objectives

Recent reports have suggested that increasing adiposity may protect against radiographic damage in rheumatoid arthritis. We explored the role of serum adipokines (adiponectin, resistin, leptin) in mediating this association.

Methods

RA patients underwent total-body dual-energy absorptiometry for measurement of total and regional body fat and lean mass, abdominal computed tomography for measurement of visceral fat area, and radiographs of the hands and feet scored according to the Sharp-van der Heijde method. Serum levels of adipokines were measured and cross-sectional associations with radiographic damage were explored, adjusting for pertinent confounders. The associations of measures of adiposity with radiographic damage were explored with the introduction of adipokines into multivariable modeling as potential mediators.

Results

Among the 197 patients studied, adiponectin demonstrated a strong association with radiographic damage, with the log Sharp score increasing 0.40 units for each log unit increase in adiponectin (p=0.001) after adjusting for pertinent predictors of radiographic damage. Adiponectin independently accounted for 6.1% of the explainable variability in Sharp score, a proportion comparable to rheumatoid factor and greater than HLA-DRB1 shared epitope alleles or C-reactive protein. Resistin and leptin were not associated with radiographic damage in adjusted models. An inverse association between visceral fat area and radiographic damage was attenuated when adiponectin was modeled as a mediator. The association of adiponectin with radiographic damage was stronger in patients with longer disease duration.

Conclusions

Adiponectin may represent a mechanistic link between low adiposity and increased radiographic damage in RA. Adiponectin modulation may represent a novel strategy for attenuating articular damage.

INTRODUCTION

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disorder characterized by synovitis and progressive damage to articular cartilage and subchondral bone in a majority of affected individuals (1). Accumulated joint damage leads to deformity and contributes to dysfunction and disability (2), which in turn are major contributors to reduced quality of life. Several disease-related factors are useful for predicting those with more rapid progression of erosive disease. Among these, early erosions, ongoing synovial and systemic inflammation, and the presence of rheumatoid factor (RF), anti-cyclic citrullinated peptide (CCP) antibodies, and HLA-DRB1 shared epitope alleles are well established (3,4). However, even when these factors are considered there remains considerable variability in radiographic progression, suggesting that other unaccounted factors may contribute to articular damage. In this regard, an association of low body mass index (BMI) with an increased risk of progression of joint damage in RA has been reported (5–7), with the risk of radiographic progression declining as BMI increased in two studies (6,7). While rheumatoid cachexia, a surrogate for highly active RA, could potentially explain the association at the lowest end of the BMI spectrum, it fails to explain why the trend in protection against radiographic progression continues to increase with increasing adiposity, even into the overweight and obese categories.

Adipose tissue expresses proteins with hormonal properties (i.e. “adipokines”) that participate in energy homeostasis and metabolism and, more recently, have been shown to participate in inflammatory and immune regulation. Levels of one adipokine, resistin, were elevated in the serum and synovial fluid of RA patients and were shown to induce de novo arthritis when injected into mice (8). Similarly, serum levels of the adipokine leptin were elevated in RA patients (9) and were shown to induce IL-8 production in RA synoviocytes via the JAK/STAT pathway (10). Another adipokine, adiponectin, which shares sequence homology with complement C1q and TNF-α (11), has potent anti-inflammatory activity in vascular endothelium (12), and has been shown to be protective against atherosclerosis (13,14). However, levels of this same adipokine are elevated in the serum (15) and synovial fluid (16) of RA patients and function to increase the production of IL-6 by synovial fibroblasts via the NF-κB signaling pathway, suggesting pro-inflammatory activity in the joint (17). In contrast to an increase in circulating levels of resistin and leptin with increasing adiposity, adiponectin levels decrease as fat mass increases. This observation, coupled with its pro-inflammatory properties in the joint, make adiponectin the most attractive candidate among the adipokines for mediating, in whole or part, the association of decreasing BMI with increasing radiographic progression.

In this study, we explored the associations of serum adipokine concentrations with radiographic damage in a cross-sectional analysis of baseline data from an ongoing prospective observational study of RA patients, controlling for other pertinent predictors of radiographic damage. We hypothesized that adiponectin would be a mediator of the association between adiposity and radiographic damage.

METHODS

Study Subjects

Study subjects were participants in ESCAPE RA (Evaluation of Subclinical Cardiovascular disease And Predictors of Events in Rheumatoid Arthritis), a cohort study investigating the prevalence, progression, and risk factors for subclinical cardiovascular disease in RA. All met American College of Rheumatology (formerly American Rheumatism Association) 1987 classification criteria for RA (18), were 45 to 84 years of age, and did not report any prior pre-specified cardiovascular events or procedures, as previously described (19). Subjects weighing over 300 pounds were excluded due to limitations of the imaging equipment used in the study.

The study was approved by the Institutional Review Board of the Johns Hopkins Hospital with all subjects providing written informed consent prior to enrollment. Enrollment began in October 2004 and concluded in May 2006.

Assessments

Outcome

Single view, anterior-posterior radiographs of the hands and feet were obtained and scored using the van der Heijde modification of the Sharp method (20) by a single trained radiologist blinded to patient characteristics (WMS). The score is a quantitative assessment of the presence and degree of marginal erosion and joint space narrowing for selected joints in the hands, wrists, and feet. The van der Heijde modified total Sharp score ranges from 0 – 398 and is the sum of the erosion score (0 – 230) and the joint space narrowing score (0 – 168). Five subjects had incomplete radiographic assessments (three had hand but not feet radiographs; two had feet but not hand radiographs). For these subjects, the missing score (hand or foot) was imputed from the available hands and feet based on a regression equation relating the predicted hand or foot erosion and joint space narrowing scores derived from the remaining subjects in the cohort.

Independent Variables

Body Composition Assessments

Subjects underwent total body DXA scanning on a Lunar Prodigy DXA scanner (GE/Lunar Radiation Corp., Madison WI). Prodigy software (version 05.60.003) was utilized to analyze and measure fat, lean, and bone mass for the total body (minus the head) and per body region (arms, legs, and trunk). All subjects were scanned on the same DXA scanner. Quality control and calibration procedures were performed daily using standard procedures provided by the manufacturer.

A single cross-sectional image of the abdomen was obtained using computed tomography (CT) at the level of the interspace between the fourth and fifth lumbar vertebrae on a Toshiba Aquilon scanner. A single trained reader (MA), blinded to the clinical characteristics of the participants, quantified visceral fat area for all of the scans using the National Institutes on Aging Musculoskeletal Analysis Program (MAP). Briefly, the reader manually traces the borders of the subcutaneous and visceral abdominal cavities on the CT scan. Based on the attenuation of a selected area of fat from the subcutaneous compartment, tissue with similar fat attenuation in the visceral cavity is identified and quantified in square centimeters.

Measures of height were obtained using a wall-mounted stadiometer. Weight was measured with subjects wearing light indoor clothing and no shoes with a Detecto™ platform. Body mass index (BMI) was calculated as body weight (kg) divided by height (meters²).

Demographic and Lifestyle Characteristics

Age, gender, race, and highest level of education were assessed by self-report. Physical activity was assessed using the 7-Day Physical Activity Recall questionnaire (7-Day PAR) (21). Current smokers were those reporting current smoking with >100 lifetime cigarettes smoked. Diabetes was defined as a fasting serum glucose ≥ 126 mg/dL or the use of diabetes medication.

RA Disease Characteristics

RA disease duration was assessed by self-report from the date of diagnosis. Joint counts were performed by a single trained assessor. RA disease activity was calculated using the Disease Activity Score for 28 joints with CRP (DAS28-CRP) (22). The 21-item Stanford Health Assessment Questionnaire (HAQ) (23) was used to assess self-reported disability. Current and past use of glucocorticoids, biologic and non-biologic disease modifying anti-rheumatic drugs (DMARDs) was queried by detailed examiner-administered questionnaires.

Laboratory Assessments

Fasting serum and plasma samples were collected on the day of body composition analysis and stored at −70 degrees C. Serum adipokines (adiponectin, resistin, leptin) were measured by ELISA at the Laboratory for Clinical Biochemistry Research (University of Vermont, Burlington, VT). C-reactive protein (CRP) was measured by nephelometry (Dade Behring Inc., Deerfield, IL). Rheumatoid factor (RF) was assessed by ELISA, with seropositivity defined at or above a level of 40 units. Anti-CCP antibody was assessed by ELISA, with seropositivity defined at or above a level of 60 units. PAD4 antibodies were measured by immunoprecipitation using ³⁵S methionine–labeled in vitro transcribed/translated (IVTT) products as previously described (24). Autoradiograms were scanned and assigned a semiquantitative score based on densitometry, with 3+ immunoprecipitation defined as the level of seropositivity.

Genomic DNA was extracted from peripheral blood leukocytes and exon 2 of HLA-DR B1 sequenced for shared epitope alleles and identified according to accepted classification criteria (25).

Statistical Analysis

The distributions of all variables were examined. Means and standard deviations were calculated for all normally distributed continuous variables and medians and interquartile ranges were calculated for continuous variables that were not normally distributed. For categorical variables, counts and percentages were calculated. Logarithmic transformation of variables was used for highly skewed variables (i.e. adipokine concentrations, visceral fat area, Sharp scores, and CRP) when needed to satisfy the requirements of regression modeling.

The associations of sociodemographic, body composition, and RA disease and treatment variables with adipokine concentrations were explored using linear regression, first in simple (unadjusted) models and then in multivariate models retaining variables with associations in univariate modeling with significance at the p=0.20 level or below. Simpler models were constructed by comparing Akaike’s Information Criteria (AIC) values for complex vs. simple models. The Shapiro-Wilk test was used to examine normality of the modeled outcome variables across the extent of independent variables. Variance Inflation Factors were calculated to ensure that variables with excessive collinearity were not co-modeled. Next, the associations of sociodemographic, body composition, RA disease and treatment variables, and adipokines with Sharp scores were explored using the strategy outlined above. For the final model, the independent contributions of included variables to the total explainable variability of the model were calculated by dividing the change in the adjusted coefficient of determination (R²) for each variable when excluded from the full model by the adjusted R² for the full model. Potential heterogeneities in the associations of adipokine concentrations with Sharp scores across strata of patient characteristics were modeled in statistical interaction models and tested using Analysis of Covariance (ANCOVA).

Statistical calculations were performed using Intercooled Stata 9 (StataCorp, College Station, TX). In all tests, a two-tailed α of 0.05 was defined as the level of statistical significance.

RESULTS

Characteristics of the 197 study patients are summarized in Table 1. While all 197 patients underwent anthropometric assessment, radiographs, and adipokine measurements, a subgroup of 131 patients (66.3%) underwent abdominal CT scanning for measurement of visceral fat area. Patient characterisitics for the subgroup with visceral fat measurements were not different from the entire cohort (Table 1). On average, the cohort was older (mean age 59 years) with a median RA disease duration of 9 years. Almost all patients (99%) had evidence of joint damage (total modified Sharp score > 0) on radiographs. The median modified total Sharp score was 44 units; however, there was broad variability in the extent of radiographic damage among patients (absolute range 0 – 364 units; interquartile range 16 – 121 units).

Table 1.

Characteristics of RA Patients

Characteristic	All Patients n = 197	Visceral Fat Subgroup n = 131
Age, years	59.4 ± 8.7	60.5 ± 8.9
Male gender, n (%)	79 (40.1)	51 (38.9)
Caucasian, n (%)	169 (85.8)	113 (86.3)
Any college, n (%)	148 (75.5)	99 (75.6)
Current Smoking, n (%)	23 (11.7)	12 (9.2)
Diabetes, n (%)	12 (6.1)	10 (7.6)
Exercise, kMET-min/wk; median (IQR)	0.91 (0 – 2.24)	0.93 (0 – 2.55)
BMI	28.4 ± 5.3	28.5 ± 5.5
Total fat, kg	29.9 ± 10.7	29.5 ± 10.8
Total lean, kg	46.4 ± 11.5	46.3 ± 11.7
Truncal fat, kg	16.2 ± 6.2	16.0 ± 6.1
Visceral fat area, cm2	n/a	119 ± 72
Adiponectin (mg/L); median (IQR)	30.5 (19.1 – 40.3)	32.0 (18.9 – 40.5)
Resistin (ng/mL); median (IQR)	16.0 (12.2 – 21.6)	16.2 (12.3 – 22.4)
Leptin (ng/mL); median (IQR)	13.7 (6.5 – 26.4)	14.4 (6.5 – 25.5)
RA duration, years; median (IQR)	9 (4 – 17)	9 (5 – 17)
RF seropositivity, n (%)	129 (65.5)	90 (68.7)
anti-CCP seropositivity, n (%)	139 (70.9)	91 (70.0)
Any shared epitope alleles present, n (%)	136 (69.7)	92 (70.8)
PAD4 antibodies, n (%)	35 (17.9)	23 (17.7)
DAS28-CRP, units; median (IQR)	3.6 (2.9 – 4.4)	3.6 (2.8 – 4.5)
Swollen joints (0–42); median (IQR)	7 (3 – 10)	6 (3 – 10)
Tender joints (0–44); median (IQR)	6 (2 – 13)	6 (2 – 12)
CRP (mg/L); median (IQR)	2.6 (1.1 – 7.2)	3.0 (1.1 – 7.8)
HAQ, units; median (IQR)	0.63 (0.13 – 1.25)	0.63 (0.13 – 1.25)
Any radiographic damage	195 (99.0)	129 (98.5)
Total modified Sharp score; median (IQR)	44 (16 – 121)	47 (20 – 114)
Current prednisone, n (%)	76 (38.6)	49 (37.4)
Cumulative prednisone, grams; median (IQR)	3.1 (0 – 9.1)	2.8 (0 – 8.7)
Current non-biologic DMARDs, n (%)	165 (84.2)	110 (84.0)
Current methotrexate, n (%)	125 (63.4)	80 (61.1)
Current biologic DMARDs, n (%)	89 (45.4)	54 (41.2)
Etanercept, n (%)	36 (18.4)	22 (16.8)
Infliximab, n (%)	22 (11.2)	12 (9.2)
Adalimumab, n (%)	27 (13.8)	18 (13.7)
Rituximab, n (%)	4 (2.0)	2 (1.5)

values are mean ± standard deviation unless otherwise noted

Cross-Sectional Predictors of Radiographic Damage in RA Patients

We considered patient characteristics, including serum adipokines, in a prediction model of the logarithmically transformed total modified Sharp score (Table 2). Significant univariate predictors included the log of the serum adiponectin and resistin concentrations, age, any college education, body lean mass, RA duration, RF seropositivity, presence of any shared epitope alleles, PAD4 antibodies, swollen joint count, log CRP, current and cumulative prednisone, and current use of biologic DMARDs (Table 2, univariate model). Leptin was not associated with Sharp scores in either univariate or multivariable modeling. Simultaneous inclusion of univariate predictors into a multivariate model resulted in a final parsimonious model with 8 significant predictors: log adiponectin, age, RA duration, RF seropositivity, any shared epitope alleles, 3+ PAD4 antibodies, log CRP, and current use of biologic DMARDs (Table 2, multivariate model 2). Within this model, the log modified Sharp score increased 0.40 units for each increase in log adiponectin (p=0.001). Resistin was no longer significantly associated with Sharp scores in the final adjusted model. Together, these predictors accounted for 50% of the variability in total modified Sharp score (i.e. the adjusted R² was 0.501 for the final adjusted model).

Table 2.

Crude and Adjusted Associations of Patient Characteristics with log Total Modified Sharp Score

Characteristic*	Univariate			Multivariate (Complex)		Multivariate** (Simplified)
	β	p	R2	β	p	β	p
log adiponectin (mg/L), per unit	0.618	<0.001	0.070	0.392	0.004	0.401	0.001
log resistin (ng/mL), per unit	1.074	<0.001	0.094	0.078	0.70
log leptin (ng/mL) per unit	0.121	0.23
Age, per year	0.047	<0.001	0.085	0.022	0.019	0.020	0.019
Any college	−0.470	0.038	0.017	−0.152	0.39
Total lean, per kg	−0.021	0.015	0.025	0.001	0.93
RA duration, per year	0.073	<0.001	0.314	0.051	<0.001	0.055	<0.001
RF seropositivity	0.775	<0.001	0.068	0.648	0.001	0.539	0.001
anti-CCP antibody seropositivity	0.374	0.087	0.010	−0.330	0.090
Any shared epitope alleles present	0.639	0.003	0.041	0.379	0.025	0.382	0.017
PAD4 antibodies	1.254	<0.001	0.118	0.604	0.004	0.540	0.006
DAS28-CRP†	0.215	0.018	0.024
Swollen joints, per joint	0.035	0.072	0.012	0.020	0.174
Tender joints, per joint	0.007	0.50
log CRP, per log mg/L	0.264	<0.001	0.063	0.156	0.010	0.154	0.007
Current prednisone	0.549	0.006	0.034	0.034	0.85
Cumulative prednisone	0.033	0.001	0.049	0.010	0.25
Current biologic DMARDs	0.354	0.073	0.012	0.398	0.009	0.457	0.002
R2				0.497		0.501

^*Univariate models include only the covariate of interest. Multivariate models include all the covariates with β coefficients in the column. Potential predictors of radiographic damage scores tested but not found to contribute to model fit in either univariate or multivariate models included gender, race, smoking, diabetes, habitual exercise, BMI, total or truncal fat mass, and current non-biologic DMARD use

^**AIC for the complex multivariable model minus the simpler multivariable model was 542.0 – 534.4 = 7.6 (p = 0.40), indicating that the fit of the simpler model was not significantly different from that of the more complex model.

^†For multivariable modeling, only the components of the DAS28-CRP (swollen and tender joint count, and CRP) were considered.

RA=rheumatoid arthritis; RF=rheumatoid factor; CCP=cyclic citrullinated peptide; PAD4=peptidyl argenine deiminase 4; DAS=disease activity score; CRP=C-reactive protein; DMARD=disease modifying anti-rheumatic drug; R²=coefficient of determination

Within the context of this adjusted model, the greatest contributor to explainable variability was RA duration, which independently accounted for 68% (Table 3). Outside of RA duration, adiponectin independently accounted for 6.1% of the explainable variability of the model, a proportion similar in magnitude to that of RF (6.3%) and current use of biologics (6.8%) and greater than that of age (2.6%), presence of any SE alleles (2.0%), PAD4 antibodies (4.1%), or CRP (3.8%). Based on the AIC, inclusion of adiponectin into the model significantly improved model fit (p = 0.0008).

Table 3.

Contributions to the Explainable Variability and Model Fit for Predictors of log Total Modified Sharp Score

Predictor	Total* Association	Independent* Association	AIC**	Difference†	p
Adiponectin	14.0%	6.1%	547.65	10.29	0.0008
Age	17.0%	2.6%	541.58	4.22	0.016
RA duration	62.3%	68.0%	589.37	52.01	<0.0001
RF seropositivity	13.6%	6.3%	548.52	11.16	0.0004
Presence of any SE alleles	8.2%	2.0%	545.12	7.76	0.014
PAD4 antibodies	23.6%	4.1%	545.81	8.45	0.005
log CRP	12.6%	3.8%	543.36	6.00	0.006
Use of biologic DMARDs	2.4%	6.8%	552.00	14.64	0.0013

^*Total association is the proportion of the total explainable variability (coefficient of determination: R²) contributed by the predictor in the univariate model expressed as a proportion of the total variability explained by all the predictors from the final model (R²=0.501). Independent association is the proportion of the total explainable variability contributed by the predictor in the final adjusted model. The sum of the total associations is greater than 100% due to overlapping associations of the predictors in the unadjusted models. The sum of the independent associations is equal to 100%.

^**Values indicate the change in Akaike’s Information Criterion (AIC) for the nested model that includes all of the predictors in the table excluding the indicated covariate. AIC for the full model = 537.36. Higher AIC values for the model when the predictor is excluded indicate better fit for the model that includes the predictor.

^†Values are the difference in the AIC between the simpler model excluding the predictor of interest and the full model including the predictor of interest. Higher values for the difference indicate a greater independent contribution to the full model

Higher adjusted Sharp scores for both erosions and joint space narrowing were observed with increasing adiponectin concentration (Figure). Trends for the incremental increase in the log erosion and log joint space narrowing scores per log unit increase in adiponectin were similar (0.373 (p=0.003) and 0.346 (p=0.014), respectively).

Figure 1. Adjusted* Mean Modified Sharp Scores According to Quartile of Serum Adiponectin.

Markers reflect adjusted means; ranges indicate 95% confidence intervals for the estimates of the mean

* Analyses adjusted for age, disease duration, rheumatoid factor seropositivity, presence of HLA-DRB1 “shared epitope” alleles, PAD4 antibodies, log C-reactive protein, and use of biologic disease modifying anti-rheumatic drugs

Association of Adiposity with Radiographic Damage

We next explored the ability of adiponectin to cross-sectionally mediate the association of adiposity with radiographic damage (Table 4). BMI, total fat, and truncal fat (measured with DXA) were not associated with Sharp scores in univariate or multivariate modeling. After adjusting for confounders of radiographic damage (age, RA duration, RF seropositivity, any shared epitope alleles, 3+ PAD4 antibodies, log CRP, and current use of biologic DMARDs), a strong inverse association between log visceral fat area and log Sharp score was observed, with the log Sharp score decreasing by −0.354 units for each unit increase in log visceral fat area (p=0.008). As expected, serum adiponectin concentration decreased as visceral fat area increased (data not shown). Introducing log adiponectin into the model as a possible mediator (Table 4, Model 3) attenuated the magnitude of the association of visceral fat with Sharp score by almost half, diminishing its level of significance (p=0.17). In this final adjusted model, the log Sharp score increased by 0.409 units for each unit increase in log adiponectin (p=0.017).

Table 4.

Crude and Adjusted Associations of Visceral Fat Area with log Total Modified Sharp Score

Characteristic**	Model 1*		Model 2*		Model 3*
	β	p	β	p	β	p
log Visceral fat area	−0.276	0.089	−0.354	0.008	−0.198	0.17
log Adiponectin					0.409	0.017

^*Model 1: Unadjusted model; includes log visceral fat area as the only covariate

Model 2: Includes adjustment for age, RA disease duration, RF seropositivity, the presence of any SE alleles, 3+ PAD4 antibodies, current use of biologic DMARDs, and log CRP

Model 3: Includes adjustment for all Model 2 confounders with log Adiponectin included as a possible mediator of the association between log visceral fat area and log total Sharp score

^**Analyses include only those patients in the subgroup that underwent abdominal CT scanning for visceral fat assessment (n = 131).

Modification of the Association of Adiponectin with Radiographic Damage by Level of RA Characteristics

Finally, we explored potential differences in the association of log adiponectin with log Sharp score according to strata of other RA characteristics (Table 5). There was no association between log adiponectin and log Sharp score noted in RA subjects with early disease (disease duration < 2 yrs; n = 16) (p = 0.45) in contrast to the strong positive association in patients with longer standing disease (p<0.001). This heterogeneity by strata of RA duration was statistically significant (p=0.034). Otherwise, the association of log adiponectin with log Sharp score was not significantly modified by gender, age group (defined by a median split at 60 years), presence of diabetes, RF, shared epitope, anti-CCP antibody, PAD4 antibody status, biologic DMARD use, or current glucocorticoid use.

Table 5.

Adjusted^* Associations of log Adiponectin with log Sharp Score According to Strata of Select Characteristics

Potential Effect Modifier	Modifier Present		Modifier Absent
	β	p	β	p	p**
Male gender	0.469	0.008	0.311	0.11	0.54
Age ≥ median (60 years)	0.511	0.007	0.305	0.059	0.41
Diabetes	1.065	0.077	0.373	0.003	0.26
Early RA (disease duration < 2 years; n = 16)	−0.286	0.48	0.618	<0.001	0.034
RF present	0.273	0.074	0.604	0.002	0.17
anti-CCP present	0.318	0.028	0.542	0.010	0.37
Any shared epitope alleles	0.442	0.002	0.277	0.24	0.54
Current biologic use	0.570	0.003	0.291	0.061	0.25
Current prednisone use	0.34	0.064	0.44	0.006	0.66

^*Analyses adjusted for age, RA duration, RF seropositivity, the presence of any SE alleles, 3+ PAD4 expression, current use of biologic DMARDs, and log CRP.

^**p-value is for the interaction of the modifier on the association of log adiponectin with the log modified Sharp score. A p-value for interaction > 0.05 indicates that the association of log adiponectin with log Sharp score does not statistically differ according to the two strata of the modifier

DISCUSSION

In this study exploring the associations of adipokines with radiographic damage in RA, we observed a strong cross-sectional association between increasing serum adiponectin concentration and both radiographic erosions and joint space narrowing, even after accounting for recognized predictors of radiographic damage. Significant associations between other adipokines (resistin and leptin) and radiographic damage were not observed. Adiponectin accounted for the variability in radiographic damage scores to an extent equal to that of RF, and greater than that of other well-recognized predictors of radiographic damage (such as shared epitope alleles and CRP) and was shown to be a mediator of the inverse association of visceral fat area with radiographic damage. A recent study (26) identified an association between adiponectin levels and radiographic damage. Our investigation extends this observation by estimating the contribution of adiponectin levels to radiographic damage in relation to other recognized predictors and by exploring the potential for adiponectin to mediate the association of adiposity with joint damage.

Several prior investigations have consistently demonstrated that adiponectin is elevated in the serum (15) and synovial fluid (16) of RA patients. This finding has been somewhat puzzling since adiponectin expression by adipocytes is antagonized by inflammatory cytokines that are typically elevated in RA (i.e. TNF-α and IL-6) (27) and that adiposity has been shown to be increased in RA patients (28). Under these circumstances, adiponectin would be expected to be reduced, rather than increased, in RA.

What are the potential implications of higher adiponectin levels for RA patients? Although adiponectin has been shown to exert potent anti-inflammatory effects on the vasculature and in fat and muscle tissue, antagonizing atherogenesis and improving insulin sensitivity (13), its activity in the joint may be pro-inflammatory, as suggested by several recent in vitro studies. Tang et al (17) demonstrated an increase in IL-6 production in cultured synovial fibroblasts from RA and osteoarthritis patients when stimulated with increasing concentrations of adiponectin. Upregulation of IL-6 was induced by adiponectin stimulated signaling through the NF-κB pathway. In another study, Luo et al (29) demonstrated that stimulation with adiponectin induced RANKL and inhibited osteoprotegerin in cultured human osteoblasts, leading to increased osteoclast formation. Taken together, these studies provide circumstantial evidence that adiponectin may have pro-inflammatory activity in the joint, inducing the terminal mechanisms involved in erosive joint damage. Indeed, the effect may not be specific to RA, as adiponectin levels were higher in patients with erosive vs. non-erosive osteoarthritis of the hands in a recently report (30).

Three prior studies have identified an association between increasing BMI (a surrogate for adiposity) and lower rates of radiographic progression in RA patients (5–7). This association is seemingly paradoxical, as adipose tissue is a potent source of cytokines (31) and was associated with increased systemic inflammation in RA patients (32). Thus, one might hypothesize that increasing adiposity would result in higher, rather than lower, rates of radiographic progression. However, a key feature of adiponectin physiology is that circulating levels diminish as adiposity increases, with highest levels noted in individuals with the lowest fat mass (33). In this light, considering that adiponectin may have detrimental effects on the joint, adiponectin becomes an excellent candidate to mediate the inverse relationship between increasing adiposity and radiographic damage observed in prior RA studies. Two of the studies identified a protective effect of obesity only in patients seropositive for RF (6) or anti-CCP antibodies (7), a heterogeneity not detected in our study. Differences in study design (prospective and enrolling only early RA patients in the prior studies and cross-sectional with early and established patients in our study) may account for the discrepancy in findings.

Adiponectin expression is suppressed to the greatest extent in visceral fat (fat located within the visceral abdominal cavity); under a pathophysiologic mechanism that is not well defined (34). As expected, we observed in our RA patients that adiponectin levels were highest in the patients with the lowest visceral fat area. These patients also demonstrated higher radiographic damage scores, even after accounting for multiple pertinent confounders. When adiponectin and visceral fat were co-modeled, the association of increasing visceral fat area with radiographic damage was subsumed in part by adiponectin, suggesting that adiponectin functions as an intermediate in the pathway between visceral fat and radiographic damage (35). These mediating effects of adiponectin provide further clues to demystifying the apparent paradoxical association between increasing BMI and protection from radiographic progression noted in RA (6, 7). We did not, however, observe significant associations between other measures of adiposity (e.g. BMI, total fat by DXA) and radiographic damage. However, adiponectin tends to be more strongly correlated with visceral fat than BMI or DXA measures of fat. Longitudinal assessments of radiographic damage are underway to explore the ability of measures of adiposity and adipokines to predict radiographic change scores over time.

The origin of the adiponectin implicated in the joint damage observed in our study remains unclear. Adipocytes are abundant in the joint (36) and may express adiponectin that acts locally in a paracrine fashion. Another possibility is that circulating adiponectin produced by remote adipocytes acts in the joint as an endocrine hormone. A prior study in RA patients showed that serum adiponectin concentration was higher than synovial fluid concentration (16), with significant correlation noted in adiponectin levels between the two sources. This finding suggests that the source of articular adiponectin may be peripheral adipose rather than a local source. Inhibition of adiponectin could represent a potential therapeutic target in RA and identifying its source may have relevant therapeutic implications. Given its anti-inflammatory effects on the vasculature and on metabolic pathways, systemic adiponectin inhibition may have undesirable adverse cardiovascular consequences, while intraarticular delivery of an adiponectin inhibitor could theoretically limit its pro-inflammatory effects on the joint.

We also explored whether the association of adiponectin with radiographic damage was modified by levels of RA characteristics. Our finding that adiponectin was more strongly associated with radiographic damage in patients with established disease compared to those with early disease could indicate that there is a physiologic difference in the pathologic activity of adiponectin at different stages of RA. The difference could, however, reflect the relative insensitivity of radiographs in early disease, in which a lag in the emergence of erosions is often noted (37). A more sensitive imaging technique, such as MRI, could assess whether there is a true interaction of RA duration on the association of adiponectin with radiographic damage. We did not detect a statistical difference in the association of adiponectin with radiographic damage between men and women. However, because adiponectin tends to be higher in women (38), this could make women at greater risk for adiponectin-associated radiographic damage. Importantly, we did not see differences in the association of adiponectin with radiographic damage according to autoantibody or shared epitope status. Adiponectin was as strongly associated with radiographic damage in patients receiving biologic DMARDs as those who were not receiving biologics, suggesting that cytokine inhibition may be not be a successful way of limiting potential adiponectin effects on the joint. The current literature is divergent on the effect of biologics on circulating adiponectin, with studies demonstrating increased levels (39–41), no change in levels (42), and even decreased levels (43) after administration of TNF inhibitors. Thus, further study is required to appreciate the role of treatment on the association of adiponectin with articular damage.

Some notable limitations to our study should be acknowledged. The analyses were cross-sectional, and strong claims on causality cannot be made. Additionally, as our cohort was not followed from disease onset, disentangling the effects of other radiographic predictors and treatment effects over time from the association of adiponectin with joint damage is difficult. We did not measure synovial fluid adiponectin levels, nor did we quantify articular fat mass. Knowing these factors proximal to the outcome of radiographic damage could validate and strengthen the associations observed. Finally, we excluded participants exceeding 300 lbs. due to limitations of the imaging equipment used. As these patients would be expected to have higher visceral fat and lower adiponectin, inclusion of this group could have provided additional confirmation of trends in the observed associations.

In conclusion, we identified a robust cross-sectional association between serum adiponectin levels and radiographic damage in RA patients, suggesting that this adipokine may be a pathogenic mediator of the seemingly paradoxical relationship between increasing adiposity and protection from radiographic damage in RA. These findings suggest that targeting adiponectin may be beneficial in preventing articular damage in RA patients. However, recognizing the beneficial effects of adiponectin on cardiovascular risk, any effect on radiographic progression of systemically reducing adiponectin could be accompanied by an increase in cardiovascular disease. Conversely, attempting to improve the elevated cardiovascular risk of RA patients by reducing visceral fat (with diet and exercise, for example) and increasing adiponectin levels could serve to undesirably accelerate joint damage.