Serum asprosin levels in patients with rheumatoid arthritis

Abstract

Rheumatoid arthritis (RA) is a chronic systemic inflammatory disease associated with increased cardiometabolic risk. Adipokines are implicated in inflammation and metabolic dysregulation in RA; however, clinical data on serum asprosin, a novel glucogenic adipokine, remain limited. This study aimed to evaluate serum asprosin levels in patients with RA and to assess their relationship with disease activity. In this single-center, cross-sectional observational study conducted between June and August 2025, 42 patients with RA and 40 control participants were included. Serum asprosin levels were measured using enzyme-linked immunosorbent assay (ELISA). Disease activity was assessed using the Disease Activity Score in 28 joints, based on the erythrocyte sedimentation rate (DAS28-ESR). Associations between asprosin levels and clinical, laboratory, and serological parameters were analyzed. Serum asprosin levels differed significantly between patients with RA and control participants, with median (interquartile range) values of 12.43 (9.98) and 9.96 (3.47) ng/mL, respectively (P = .025); however, this association was no longer statistically significant after adjustment for age, sex, BMI, smoking status, and comorbidity in a multivariable regression model (adjusted P = .986). No significant correlations were observed between asprosin and DAS28-ESR, CRP, ESR, RF, or anti-CCP. ROC analysis demonstrated limited discriminatory performance (AUC = 0.643; 95% CI: 0.52–0.767; P = .02). Serum asprosin levels differed between patients with RA and control participants in unadjusted analysis; however, this difference was not retained after adjustment for potential confounders, and no significant association with disease activity or inflammatory markers was identified. These findings suggest that serum asprosin may have limited clinical utility as a standalone biomarker in RA. Further prospective studies with larger sample sizes are needed to clarify the potential role of asprosin in RA pathophysiology.

1. Introduction

Rheumatoid arthritis (RA) is a chronic inflammatory joint disease that causes damage to cartilage and bone, and which may also involve extra-articular organs. RA has a prevalence rate of between 0.5% and 1%.^[1] Joint damage begins in the early stages of the disease as a result of active inflammation, which can lead to progressive and irreversible disability. Accurate measurement of disease activity is necessary to evaluate the efficacy of specific treatments.^[2] Successful treatment depends on patients achieving low disease activity or remission. In recent years, a better understanding of the mechanisms underlying RA has facilitated diagnosis and treatment. Rheumatoid factor (RF) and anti-cyclic citrullinated peptide (anti-CCP) antibodies are well-established serological biomarkers that contribute to the classification, diagnostic assessment, and prognostic evaluation of RA.^[3]

In clinical practice, biomarkers in RA are primarily used for diagnosis, prognostication, and disease monitoring. Although rheumatoid factor (RF) and anti-cyclic citrullinated peptide (anti-CCP) antibodies are well-established diagnostic markers, and acute-phase reactants such as C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) are widely used in follow-up, these parameters do not fully capture the clinical and biological heterogeneity of RA. Therefore, there remains an unmet need for additional biomarkers that can complement existing clinical and laboratory assessments and improve patient stratification.^[1,3]

The pathogenesis of RA is driven by chronic synovial inflammation, sustained by a complex network of proinflammatory cytokines, including TNF-α, IL-6, IL-1, and IL-17, released from immune cells such as T cells, B cells, and macrophages. This inflammatory milieu promotes synovial hyperplasia and pannus formation, which subsequently invades cartilage and subchondral bone, leading to progressive joint destruction^.[4,5]

Adipose tissue is now recognized not only as an energy storage organ but also as an active endocrine organ that secretes a variety of bioactive molecules. Adipokines are biologically active peptides involved in inflammatory and metabolic pathways.^[6] Several adipokines, including leptin, visfatin, adiponectin, and resistin, have been reported to be dysregulated in RA and may contribute to synovial inflammation and joint damage.^[7,8] Asprosin is a recently identified glucogenic adipokine secreted from white adipose tissue during fasting and is involved in glucose homeostasis.^[9] Experimental studies have suggested that asprosin may exert pro-inflammatory effects through increased cytokine production.^[10] In addition, recent experimental evidence has indicated that asprosin may contribute to synovial inflammation through PPAR-γ-dependent mechanisms.^[11] However, clinical data regarding serum asprosin levels in patients with RA remain limited.

Early diagnosis and accurate assessment of disease activity are essential for the optimal clinical management of RA. However, both diagnosis and monitoring of disease activity remain challenging in clinical practice. Coexisting pain syndromes such as fibromyalgia may lead to an overestimation of disease activity scores, while acute-phase reactants such as C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) may remain within normal ranges in a substantial proportion of patients. Furthermore, seronegative RA, characterized by the absence of RF and anti-CCP antibodies, poses additional diagnostic and monitoring difficulties.^[12–14] These limitations highlight the need for novel biomarkers that can improve both disease assessment and patient stratification in RA.

This study aimed to evaluate serum asprosin levels in patients with RA and to investigate their relationship with clinical, laboratory, and serological parameters, including disease activity assessed by DAS28-ESR.

2. Materials and methods

2.1. Study design and participants

This single-center, observational, cross-sectional study was conducted to compare serum asprosin levels in patients with rheumatoid arthritis (RA) and control participants. The study was carried out between June and August 2025, during which consecutive eligible participants with complete clinical and laboratory data were included. Patients diagnosed according to the 2010 American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) classification criteria for RA, as well as control participants, were enrolled in the study.^[15] Inclusion criteria were age ≥ 18 years and provision of informed consent. Exclusion criteria included pregnancy, breastfeeding, acute infection, chronic liver or kidney disease, malignancy, morbid obesity, and diabetes mellitus. Diabetes mellitus was excluded based on medical history, current medication use, and available fasting blood glucose measurements in hospital records.

2.2. Ethical approval

Ethical approval was obtained from the İnönü University Scientific Research and Publication Ethics Committee (No. 2025/7797). Written informed consent was obtained from all participants. The study was conducted in accordance with the principles of the Declaration of Helsinki.

2.3. Clinical and laboratory assessment

Blood samples were obtained from RA patients attending the outpatient clinic for the measurement of serum asprosin levels. Samples from control participants were collected in the same manner. Blood samples for asprosin measurement were collected during the morning hours; however, a standardized fasting period was not required. Disease activity in RA patients was assessed using the Disease Activity Score in 28 joints based on the erythrocyte sedimentation rate (DAS28-ESR), which incorporates the number of tender and swollen joints, patient global assessment, and ESR. DAS28-ESR scores were categorized as remission (<2.6), low disease activity (2.6–3.2), moderate disease activity (>3.2–5.1), and high disease activity (>5.1). Disease duration was defined as the time from RA diagnosis to serum sampling and was expressed in months.

The following data were recorded for all participants: age, sex, body mass index (BMI), smoking and alcohol use, comorbidities, ESR, CRP, complete blood count parameters, and levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), and creatinine. Rheumatoid factor (RF) and anti-cyclic citrullinated peptide (anti-CCP) antibody results were also recorded.

2.4. Measurement of serum asprosin

Blood samples collected for asprosin measurement were centrifuged at 3000 rpm (approximately 1000–1500 × g) for 5 minutes to separate the serum. Approximately 3 mL of serum was aliquoted into Eppendorf tubes and stored at − 40°C until analysis.

Serum asprosin concentrations were quantified using a commercial enzyme-linked immunosorbent assay (ELISA) kit (Cat. No. E4095HU, BT Lab, Shanghai, China) following the manufacturer’s protocol. Although the manufacturer-reported nominal assay range is 0.5–100 ng/mL (sensitivity: 0.23 ng/mL), the working standard curve for the assay batch was established up to 128 ng/mL via serial dilutions (128, 64, 16, 8, 4, 2, and 0 ng/mL), fully encompassing all measured serum concentrations (min: 1.5 ng/mL; max: 106 ng/mL) without extrapolation. All study samples were analyzed on a single plate, with RA patient and control samples interspersed randomly. Standard curve calibrators were run in duplicate, whereas study samples were tested in singlicate. The manufacturer-reported intra-assay and inter-assay coefficients of variation were 4.4% and 7.3%, respectively, and internal quality controls fell within acceptable limits. Laboratory personnel were blinded to participant clinical status.

2.5. Statistical analysis

Sample size estimation was performed using G*Power version 3.1.7 for a two-group comparison, assuming a two-sided type I error rate (α) of 0.05 and a statistical power (1 − β) of 0.80. Because no previous study directly comparing serum asprosin levels between patients with RA and control participants was available at the time of study design, the anticipated effect size was informed by a previous study by Hong et al evaluating serum asprosin concentrations in individuals with and without metabolic syndrome.^[16] Based on the reported means and standard deviations in that study, the standardized effect size was estimated to be approximately Cohen’s d = 0.76. To adopt a more conservative assumption, an effect size of d = 0.70 was used for the sample size calculation. Accordingly, a minimum total sample size of 68 participants (34 participants per group) was required to achieve 80% power at a two-sided α level of 0.05.^[16,17]

The normality of data distribution was assessed using the Shapiro–Wilk test, supported by visual inspection of histograms and Q-Q plots. Continuous variables were compared using the independent samples t-test or Mann–Whitney U test, as appropriate. Categorical variables were compared using the Pearson chi-square test or Fisher’s exact test, as appropriate. Serum asprosin concentrations across the four DAS28-ESR disease activity categories were compared using the Kruskal–Wallis test. For the primary between-group comparison of serum asprosin, the Mann–Whitney U effect size (r) was reported with a 95% confidence interval estimated using bootstrap resampling. Continuous variables are presented as mean ± standard deviation or median (interquartile range), while categorical variables are expressed as number and percentage.

Correlations between serum asprosin levels and clinical, laboratory, and serological parameters – including binary categorical variables (RF, anti-CCP, and seropositivity status) – were evaluated using Spearman’s rank correlation coefficient within the RA group only (n = 42), for methodological consistency with the nonparametric approach used for between-group comparisons and because DAS28-ESR and seropositivity status are not applicable to control participants. 95% confidence intervals for correlation coefficients were calculated using Fisher’s z-transformation.

To assess whether the association between RA status and serum asprosin concentration was independent of potential confounding factors, a multivariable linear regression analysis was performed. Because serum asprosin concentrations were markedly right-skewed, serum asprosin values were natural log-transformed before regression analysis. Group status (RA vs control) was entered as the main independent variable, with age, sex, BMI, smoking status, and comorbidity status included as covariates. Regression coefficients (B) with 95% confidence intervals and corresponding p-values were reported. A P-value < .05 was considered statistically significant. All reported p-values are nominal; no adjustment for multiple comparisons was applied. Statistical analyses were performed using IBM SPSS Statistics version 27.

3. Results

A total of 82 participants were included in the study: 42 patients with RA and 40 control participants. The mean age of the RA group was 48 ± 17 years, compared to 44 ± 11 years for the control group. There was no significant difference in age between the 2 groups (P = .175).

The proportion of women in the RA group was significantly higher than in the control group (78.6% vs 57.5%; P = .04). No difference was found between the groups in terms of BMI (P = .926). Examination of laboratory parameters revealed that the white blood cell (WBC) level was higher in the RA group than in the control group (8.2 ± 2.3 vs 7.2 ± 1.7 × 10³/µL; P = .027). Hemoglobin levels were significantly lower in RA patients (13.0 ± 1.7 vs 14.3 ± 1.8 g/dL; P < .001). Although the platelet count was higher in the RA group, this difference was not statistically significant (P = .059). CRP and ESR levels were significantly higher in the RA group (P = .001 and P < .001, respectively). No significant differences were found in ALT, AST, and creatinine levels.

Serological examination revealed RF positivity in 33.3% of RA patients and anti-CCP positivity in 30.9%. The seropositivity rate was 40.5% in the RA group. No significant differences were observed between the groups in terms of smoking or alcohol consumption. However, comorbidities were significantly more frequent in the RA group than in the control group (31% vs 10.0%, P = .019). In the RA group, hypertension was present in 9 patients and hypothyroidism in 5 patients, with one patient having concomitant hypertension, hypothyroidism, and coronary artery disease. In the control group, 2 participants had hypertension and two had hypothyroidism. Serum asprosin levels were non-normally distributed in both groups (Shapiro–Wilk test: W = 0.754, df = 42, P < .001 for the RA group; W = 0.464, df = 40, P < .001 for the control group). The median serum asprosin level was 12.43 ng/mL (IQR, 9.98) in the RA group and 9.96 ng/mL (IQR, 3.47) in the control group, with a statistically significant between-group difference (P = .025, Mann–Whitney U test). The difference between the arithmetic means and medians, together with the wide dispersion of values, particularly in the control group, reflects substantial inter-individual variability. The distribution of serum asprosin concentrations in the RA and control groups is shown in Figure 1. The demographic, clinical, and laboratory characteristics of the study groups are summarized in Table 1. Treatment exposure data for the RA group are presented in Table S1, Supplemental Digital Content 1.

Figure 1.

Box-and-whisker plot of serum asprosin concentrations in patients with rheumatoid arthritis (RA) and control participants. Boxes represent the interquartile range (IQR), with the median indicated by the horizontal line and whiskers extending to values within 1.5 × IQR from the quartiles. Individual serum asprosin measurements are overlaid as points to illustrate the distribution and between-group overlap.

Table 1.

Comparison of demographic, clinical and laboratory parameters between rheumatoid arthritis patients and the control group.

Variable		Control (n = 40) Median (IQR)	RA (n = 42) Median (IQR)	Hodges–Lehmann 95% CI (RA − control)	Effect size (r or Cramér’s V)	P
Age (years)		46.0 (12.0)	48.5 (28.0)	−2.00 to 12.00	0.17	.175*
Gender (n, %)	Female	23 (57.5%)	33 (78.6%)		0.23	.04†
	Male	17 (42.5%)	9 (21.4%)
BMI (kg/m2)		26.9 (4.2)	26.1 (6.9)	−1.70 to 1.80	0.01	.926*
WBC (×103/µL)		6.7 (2.8)	8.1 (3.1)	0.05–1.86	0.27	.027*
Hb (g/dL)		14.6 (2.4)	12.8 (2.4)	−2.20 to −0.70	0.43	<.001*
PLT (×103/µL)		259.5 (98.0)	294.5 (107.0)	−1.00 to 67.00	0.24	.059*
ALT (U/L)		20 (12)	18 (12)	−5.00 to 2.00	0.10	.427*
AST (U/L)		20 (8)	22 (10)	−2.00 to 4.00	0.08	.524*
Creatinine (mg/dL)		0.8 (0.3)	0.8 (0.3)	−0.10 to 0.10	0.04	.449*
CRP (mg/dL)		0.3 (0.0)	0.4 (0.7)	0.00–0.40	0.37	.001*
ESR (mm/h)		5.0 (9.0)	14.5 (21.0)	3.00 to 14.00	0.48	<.001*
RF	Negative	40 (100.0%)	28 (66.7%)		0.44	<.001†
	Positive	0 (0.0%)	14 (33.3%)
Anti-CCP	Negative	40 (100.0%)	29 (69.0%)		0.42	<.001†
	Positive	0 (0.0%)	13 (31.0%)
Seropositivity	Negative	40 (100.0%)	25 (59.5%)		0.50	<.001†
	Positive	0 (0.0%)	17 (40.5%)
Smoking (n, %)	No	27 (67.5%)	34 (81.0%)		0.15	.163†
	Yes	13 (32.5%)	8 (19.0%)
Alcohol (n, %)	No	39 (97.5%)	42 (100.0%)		0.11	.488‡
	Yes	1 (2.5%)	0 (0.0%)
Comorbidity (n, %)	No	36 (90.0%)	29 (69.0%)		0.26	0.019†
	Yes	4 (10.0%)	13 (31.0%)
Asprosin (ng/mL)		10.0 (3.4)	12.4 (9.9)	0.23–3.42	0.29 (95% CI: 0.04–0.53)	.025*
DAS28-ESR		N/A	3.16 (1.67)
Disease duration, months		N/A	49.0 (107.0)

Continuous variables are expressed as median (interquartile range), and categorical variables as n (%), unless otherwise specified.

ALT = alanine aminotransferase, anti-CCP = anti-cyclic citrullinated peptide antibody, AST = aspartate aminotransferase, BMI = body mass index, CRP = C-reactive protein, ESR = erythrocyte sedimentation rate, Hb = hemoglobin, PLT = platelet count, RF = rheumatoid factor, seropositivity = RF and/or anti-CCP positivity, WBC = white blood cell count.

^*Mann–Whitney U test; † chi-square test; ‡ Fisher’s exact test.

Effect size was expressed as r for Mann–Whitney U tests and Cramér’s V for categorical comparisons. For the primary serum asprosin comparison, the 95% confidence interval for the effect size was estimated using bootstrap resampling. The 95% confidence intervals reported for continuous variables represent the Hodges–Lehmann estimate of the between-group location shift (RA − control), consistent with the Mann–Whitney U test used for these comparisons.

Within the RA group, no significant correlation was found between serum asprosin levels and DAS28-ESR (ρ = 0.168, 95% CI − 0.14–0.45, P = .286), CRP (ρ = 0.174, 95% CI − 0.14–0.45, P = .271), or ESR (ρ = −0.093, 95% CI − 0.39–0.22, P = .557). Similarly, asprosin levels were not significantly correlated with RF (ρ = −0.038, P = .814), anti-CCP (ρ = 0.049, P = .759), or seropositivity status (ρ = 0.014, P = .930). All confidence intervals were wide and crossed zero, indicating limited precision. The correlations between serum asprosin levels and clinical and laboratory parameters are presented in Table 2.

Table 2.

Correlations between serum asprosin levels and clinical, laboratory, and serological parameters in patients with rheumatoid arthritis (n = 42).

Variable 1	Variable 2	Spearman’s ρ	95% CI	P-value
Asprosin	CRP	0.174	−0.14, 0.45	.271
	DAS28-ESR	0.168	−0.14, 0.45	.286
	ESR	−0.093	−0.39, 0.22	.557
	RF	−0.038	−0.34, 0.27	.814
	Anti-CCP	0.049	−0.26, 0.35	.759
	Seropositivity	0.014	−0.29, 0.32	.930

anti-CCP = anti-cyclic citrullinated peptide antibody, CI = confidence interval, CRP = C-reactive protein, DAS28-ESR = Disease Activity Score in 28 joints based on the erythrocyte sedimentation rate, ESR = erythrocyte sedimentation rate, RF = rheumatoid factor.

Correlations were calculated using Spearman’s rank correlation coefficient within the RA group only (n = 42), including for binary variables (RF, anti-CCP, seropositivity), for methodological consistency with the nonparametric approach used for between-group comparisons. 95% confidence intervals were calculated using Fisher’s z-transformation.

To account for potential confounding by baseline demographic and clinical characteristics, an adjusted analysis was performed using multivariable linear regression, with natural log-transformed serum asprosin level as the dependent variable and group (RA vs control), age, sex, BMI, comorbidity status, and smoking status as covariates (Table 3). In this adjusted model, the association between group status and serum asprosin level was substantially attenuated and no longer statistically significant (B = 0.003, 95% CI − 0.296–0.301, P = .986). Body mass index was independently and significantly associated with asprosin levels (B = −0.055, 95% CI − 0.095 to − 0.016, P = .007), whereas age, sex, comorbidity status, and smoking status were not significant independent predictors.

Table 3.

Multivariable regression predicting natural log-transformed serum asprosin levels (n = 82).

Variable	B	SE	t	P	95% CI (lower)	95% CI (upper)
Intercept	3.654	0.516	7.080	<.001	2.626	4.682
Group (RA vs control)	0.003	0.150	0.017	.986	−0.296	0.301
Age	0.011	0.006	1.842	.070	−0.001	0.022
Sex	−0.008	0.169	−0.049	.961	−0.345	0.328
BMI	−0.055	0.020	−2.780	.007	−0.095	−0.016
Comorbidity	−0.280	0.201	−1.389	.169	−0.681	0.121
Smoking	−0.306	0.172	−1.777	.080	−0.649	0.037

Model summary: R² = 0.156, Adjusted R² = 0.089, n = 82, df = 75.

Dependent variable: natural log-transformed serum asprosin level. B: unstandardized regression coefficient.

SE = standard error; CI = confidence interval. Group status was coded as RA = 1, control = 0 (reference); sex was coded as male = 1, female = 0 (reference). Comorbidity and smoking status were coded as binary (present/absent).

An ROC curve analysis was performed to evaluate the discriminatory performance of serum asprosin levels between patients with RA and control participants. The area under the curve (AUC) for asprosin was found to be 0.643 (95% confidence interval (CI): 0.52–0.767; P = .02). The Youden index was 0.296, corresponding to a Youden index-derived threshold of 11.514 ng/mL. Using serum asprosin levels > 11.514 ng/mL as test-positive for RA, the sensitivity was 57.1% and the specificity was 72.5% (24 true positives and 18 false negatives among RA patients; 29 true negatives and 11 false positives among control participants). The ROC curve is shown in Figure 2.

Figure 2.

Receiver operating characteristic (ROC) curve of serum asprosin levels for discriminating patients with rheumatoid arthritis from control participants. The area under the curve (AUC) was 0.643 (95% confidence interval (CI): 0.52–0.767; P = .02), indicating modest discriminatory performance. A Youden index-derived threshold of 11.514 ng/mL (Youden index = 0.296) yielded a sensitivity of 57.1% and a specificity of 72.5% for distinguishing patients with RA from control participants.

The mean DAS28-ESR score in the RA group was 3.09 ± 1.33 (median 3.16, IQR 1.67), and the median disease duration was 49 months (IQR, 107). Patients were distributed across disease activity categories as follows: remission, 11 (26.2%); low disease activity, 11 (26.2%); moderate disease activity, 18 (42.9%); and high disease activity, 2 (4.8%). A Kruskal-Wallis test comparing serum asprosin levels across these 4 categories showed no statistically significant difference (H = 3.73, P = .292).

In subgroup analyses, there was no statistically significant difference in asprosin levels between patients in remission and those in the active group (P = .100). Similarly, there was no significant difference in asprosin levels between seropositive and seronegative patients with RA (P = .929). Given the small size of several subgroups (e.g., remission, n = 11; high disease activity, n = 2), these comparisons were underpowered, and the absence of statistically significant differences should not be interpreted as evidence against a true association.

4. Discussion

In this study, we investigated the relationship between serum asprosin levels and clinical and laboratory parameters in patients with rheumatoid arthritis. Our findings demonstrated that inflammatory markers such as CRP and ESR were significantly elevated, while hemoglobin levels were lower in the RA group compared with controls. Serum asprosin levels differed significantly between the 2 groups in the unadjusted analysis; however, this association was not retained after adjustment for age, sex, BMI, smoking status, and comorbidity. No significant associations were observed between asprosin levels and disease activity as assessed by DAS28-ESR, inflammatory markers (CRP and ESR), or serological parameters, including RF and anti-CCP. Furthermore, ROC analysis indicated only modest discriminatory performance, suggesting that the clinical utility of serum asprosin as a standalone biomarker in RA may be limited.

Asprosin is a recently identified adipokine implicated in energy metabolism and inflammatory processes.^[18] Beyond its metabolic functions, experimental and translational studies have suggested that asprosin may exert pro-inflammatory effects and contribute to RA-related synovial inflammation.^[11] These observations provide a biological rationale for investigating circulating asprosin in RA and its potential relationship with clinical disease activity.

Xu et al recently reported higher circulating asprosin levels in patients with RA and provided mechanistic evidence suggesting a role for asprosin in synovial inflammation through PPAR-γ-dependent pathways.^[11] In our cohort, serum asprosin levels also differed significantly between patients with RA and control participants, with a higher median value in the RA group; however, substantial inter-individual variability and overlap between the groups were observed. Importantly, serum asprosin was not significantly associated with DAS28-ESR, CRP, ESR, RF, anti-CCP, or overall seropositivity. Our study extends the available clinical evidence by specifically evaluating the relationship between circulating asprosin and disease activity using a validated composite index. Taken together, these findings suggest that although circulating asprosin may differ between patients with RA and control participants, its relationship with clinical disease activity remains uncertain. Differences in clinical characteristics, metabolic factors, and treatment exposure may contribute to variability across studies and should be considered when interpreting these findings.

Numerous studies have investigated the role of adipokines in RA.^[19,20] Adipokines such as leptin, adiponectin, and resistin have been linked to inflammatory responses, with leptin and resistin levels positively correlating with inflammatory markers, whereas adiponectin may exhibit an inverse relationship.^[20] In addition, visfatin has been shown to enhance the production of IL-6, IL-8, and MMP-3 in synovial fibroblasts, thereby promoting pro-inflammatory activity and joint damage.^[21] In contrast, omentin-1 appears to exert anti-inflammatory effects through macrophage modulation.^[22] Within this adipokine network, our findings indicate that although serum asprosin levels differed between RA patients and control participants, they were not significantly associated with disease activity or conventional inflammatory markers. This observation may partly be explained by the clinical characteristics of our cohort, in which many patients were receiving treatment and approximately half were in remission or had low disease activity. Recent experimental studies have suggested that asprosin may exert pro-inflammatory effects through increased cytokine production and synovial inflammatory pathways.^[11] However, the clinical implications of these findings in RA remain unclear.

ROC analysis in our study demonstrated a modest discriminatory performance of asprosin in distinguishing RA from control participants (AUC = 0.64), with a sensitivity of 57.1% and a specificity of 72.5%. These findings suggest that asprosin alone may have limited utility as a standalone biomarker for distinguishing patients with RA from control participants. Previous studies evaluating asprosin in different clinical conditions have also reported variable discriminatory performance. For example, serum asprosin levels were shown to increase during Familial Mediterranean Fever attacks, with higher discriminatory performance in ROC analyses.^[23] Similarly, in patients undergoing hemodialysis, asprosin has been associated with metabolic syndrome, with an AUC of 0.725.^[24] In contrast, the more modest discriminatory performance observed in RA suggests that serum asprosin may have limited clinical utility when used alone and should be interpreted cautiously.

When interpreted within the broader biomarker landscape of RA, the discriminatory performance of asprosin in our cohort (AUC = 0.64) appears modest compared with established biomarkers such as anti-CCP/ACPA and emerging markers like 14–3-3η, which have demonstrated higher sensitivity and specificity in previous studies.^[25,26] Consistent with our findings, recent studies have reported comparable discriminatory performance for asprosin, with area under the curve values in the moderate range.^[11] These findings suggest that although asprosin may have limited standalone discriminatory utility, further studies are needed to determine whether it may provide additional clinical information when interpreted alongside established biomarkers.

The present study has several strengths. First, it provides an independent clinical evaluation of circulating asprosin in RA and extends the emerging literature by specifically examining its relationship with disease activity assessed using the validated DAS28-ESR composite index. In addition, serum asprosin was evaluated together with a broad range of clinical, inflammatory, and serological parameters, allowing a more comprehensive assessment of its potential clinical relevance in RA. The inclusion of a control group enabled direct comparison of circulating asprosin concentrations between patients with RA and control participants, while laboratory personnel performing the ELISA measurements were blinded to participants’ clinical status, reducing the potential for measurement-related bias. Taken together, these features provide additional clinically oriented data on circulating asprosin in RA and complement the recent mechanistic and clinical findings reported by Xu et al.

However, several limitations should be acknowledged. Due to the cross-sectional design, longitudinal changes in serum asprosin levels and treatment-related dynamics at the individual patient level could not be assessed. In addition, the relatively small sample size and single-center nature of the study may limit statistical power and generalizability and may have contributed to the observed inter-individual variability in asprosin levels. Furthermore, the sample size calculation was powered for the primary between-group comparison rather than for the correlation analyses; the correlation analyses should therefore be regarded as exploratory. The wide 95% confidence intervals observed for several correlation coefficients (Table 2) indicate limited precision and raise the possibility of type II error, meaning that clinically relevant associations between asprosin and disease activity or serological markers cannot be excluded on the basis of this sample size. All reported p-values are nominal, and no formal correction for multiple comparisons was applied across the six correlation analyses performed (asprosin vs DAS28-ESR, CRP, ESR, RF, anti-CCP, and seropositivity). A Bonferroni-corrected threshold for these six tests would require P < .008; none of the observed correlations (P = .271–.930) would have met this threshold, so the overall conclusion of no significant association is unaffected by this adjustment. The subgroup analyses were also underpowered because of the small numbers within individual disease activity and serological subgroups; therefore, the absence of significant subgroup differences should be interpreted cautiously. In addition, the majority of patients were receiving treatment and were in remission or had low disease activity (52.4%, 22/42), which may have reduced the variability necessary to detect associations between serum asprosin levels and disease activity. The potential effects of treatment-related immunomodulation on serum asprosin levels cannot be fully excluded. In our cohort, 88.1% of RA patients were receiving conventional synthetic DMARDs, 16.7% biologic DMARDs, and 69.0% were receiving glucocorticoids (median prednisolone-equivalent dose 5.0 mg/day across the overall RA cohort, with non-users coded as 0; Table S1, Supplemental Digital Content 1), and detailed statistical adjustment for individual treatment classes was not performed given the sample size.

Although blood samples were collected during the morning hours, fasting status and the timing of blood sampling in relation to the last meal were not standardized. In addition, detailed metabolic parameters, including fasting glucose, insulin/HOMA-IR, HbA1c, and lipid profiles, were not systematically available for all participants. Given the fasting-responsive and metabolic nature of asprosin, these factors may have contributed to measurement variability and residual confounding and should be considered when interpreting the observed between-group differences. In addition, the relatively short centrifugation period (5 minutes) used for serum separation may have increased the possibility of residual cellular or platelet contamination. This pre-analytical factor may have contributed to the observed variability in serum asprosin measurements and should be considered when interpreting the findings. Serum asprosin concentrations were measured in single wells rather than in duplicate. Although the standard curve was performed in duplicate and internal quality-control results were within acceptable ranges, the absence of technical replicates for individual samples limited the assessment of within-sample analytical variability and may have increased susceptibility to well-specific or pipetting-related measurement error. In addition, although a multivariable regression model was performed to adjust for baseline demographic and clinical covariates, the association between group status and serum asprosin level was markedly attenuated in this adjusted analysis compared with the unadjusted comparison (Mann–Whitney U test, P = .025 vs adjusted P = .986). This attenuation indicates that the unadjusted between-group difference was not independent of the included covariates. Notably, BMI was itself significantly and independently associated with serum asprosin levels in the adjusted model, suggesting that body composition may account for at least part of the unadjusted difference observed between groups. Given the relatively small sample size and the number of covariates included, the adjusted model may also have had limited power to detect an independent group effect, and residual or unmeasured confounding cannot be excluded. These adjusted findings should therefore be interpreted with caution and considered exploratory. Finally, the study was limited to clinical and biochemical assessments and did not include mechanistic or molecular analyses, thereby limiting biological interpretation. Overall, these findings should be considered exploratory and hypothesis-generating and warrant validation in larger, prospective, multicenter studies.

5. Conclusions

Serum asprosin levels differed between patients with RA and control participants in the unadjusted analysis; however, this association was not retained after adjustment for potential confounders. No significant association was identified between serum asprosin levels and disease activity, inflammatory markers, or serological parameters. In addition, serum asprosin demonstrated only modest discriminatory performance, suggesting limited clinical utility as a standalone biomarker in RA. Overall, these findings should be considered exploratory and hypothesis-generating. Further prospective, multicenter studies with larger sample sizes are needed to better clarify the potential role of serum asprosin in RA.

Acknowledgments

The authors would like to thank all participants for their valuable contribution to this study.

Author contributions

Conceptualization: Sezgin Zontul.

Investigation: Sezgin Zontul, Zeynep Kaya, Mesude Seda Aydoğdu, Elif İnanç, Merve Çetin, Servet Yolbaş, Cihat Uçar.

Methodology: Sezgin Zontul, Zeynep Kaya, Elif İnanç, Cihat Uçar.

Project administration: Sezgin Zontul.

Supervision: Sezgin Zontul.

Validation: Sezgin Zontul, Elif İnanç, Servet Yolbaş.

Writing – original draft: Sezgin Zontul, Mesude Seda Aydoğdu, Elif İnanç, Ahmet Kadir Arslan.

Writing – review & editing: Sezgin Zontul, Servet Yolbaş, Ahmet Kadir Arslan.

Visualization: Zeynep Kaya, Merve Çetin.

Data curation: Mesude Seda Aydoğdu, Elif İnanç, Merve Çetin.

Resources: Servet Yolbaş, Cihat Uçar.

Formal analysis: Ahmet Kadir Arslan.