Skeletal muscle expression of the genes associated with glycoprotein 130 signaling in relation to obesity and insulin sensitivity

Abstract

Purpose

Glycoprotein 130 (gp130) is a critical signal transducer in the interleukin-6 (IL-6) receptor family, regulates immune response, inflammation, and metabolic processes. In obesity, elevated levels of proinflammatory cytokines like IL-6 can lead to chronic activation of gp130, disrupting normal signaling in tissues such as skeletal muscle. The aim of the study was to investigate the expression of IL-6–related and JAK/STAT pathway genes in human skeletal muscle and to explore their association with insulin sensitivity, as well as to evaluate the role of serum soluble gp130 (sgp130) in the development of overweight and obesity.

Methods

The study included 57 participants, 25 with normal body weight (control group), 17 with overweight and 15 with obesity. Hyperinsulinemic-euglycemic clamp and muscle biopsy were conducted. Muscle mRNA expression was analysed by qPCR.

Results

Individuals with overweight exhibited significantly lower IL6R expression in skeletal muscle, while those with obesity showed reduced IL6ST expression. The expression levels of IL6R (r = 0.28, p = 0.036), IL6ST (r = 0.46, p < 0.001), JAK2 (r = 0.32, p = 0.015), and STAT3 (r = 0.44, p < 0.001) and PRKAA2 (r = 0.26, p = 0.049) in skeletal muscle were positively correlated with insulin sensitivity. Additionally, individuals with overweight and obesity had significantly higher serum sgp130 levels. Serum sgp130 was positively correlated with BMI (r = 0.43, P < 0.01) and inversely associated with insulin sensitivity (r = -0.44, P < 0.01).

Conclusion

Gp130 is associated with insulin sensitivity in skeletal muscle in obesity, revealing a novel mechanism linking gp130 to metabolic regulation.

Introduction

Glycoprotein 130 (gp130) is a signal-transducing receptor widely expressed across tissues and serves as a key mediator for the interleukin-6 (IL-6) family of cytokines, including IL-6, IL-11, Leukemia Inhibitory Factor (LIF), Ciliary Neurotrophic Factor (CNTF), and Oncostatin M (OSM) [1]. Gp130 does not directly bind cytokine ligands. Rather, cytokines initially engage their cognate α-receptors (such as IL-6Rα), which subsequently facilitates the recruitment of gp130 to form a high-affinity receptor complex capable of initiating intracellular signaling [2]. Upon activation, gp130 undergoes conformational changes that enable Janus kinases (JAKs) to phosphorylate intracellular tyrosine residues, creating docking sites for STAT transcription factors (mainly STAT3) [3, 4]. In addition to JAK/STAT signaling, gp130 can activate the mitogen-activated protein kinase/extracellular signal regulated kinase (MAPK/ERK) and phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) pathways, giving it broad influence over cell survival, proliferation, metabolism, and differentiation [1, 5, 6]. Gp130 is expressed ubiquitously, but it has particularly important roles in the immune system, heart, liver, nervous system, and skeletal muscle.

In skeletal muscle, gp130 is widely expressed across muscle, stromal, and immune cells, enabling many cell types to respond to IL-6. However, the membrane-bound IL-6 receptor (IL-6Rα) is limited mainly to certain immune cells, such as macrophages and T cells, allowing them to signal via classical IL-6 signaling. Other cells lacking IL-6Rα can still respond through IL-6 trans-signaling, where IL-6 binds soluble IL-6R (sIL-6R) to activate gp130. This enables IL-6 to influence diverse processes in muscle, including inflammation, repair, and adaptation [5, 7, 8]. During exercise or metabolic stress, AMP-activated protein kinase (AMPK) activation enhances glucose uptake by promoting glucose transporter 4 (GLUT4) translocation to the plasma membrane, independent of insulin, and increases lipid oxidation by phosphorylating and inhibiting acetyl-CoA carboxylase (ACC), which lowers malonyl-CoA levels and facilitates fatty acid entry into mitochondria for β-oxidation. IL-6/gp130 signaling can activate STAT3, PI3K/AKT, and AMPK, linking cytokine signaling to metabolic adaptation by improving glucose utilization and enhancing lipid metabolism. These pathways also converge on peroxisome proliferator-activated receptor-gamma coactivator-1-alpha (PGC-1α), a master regulator of mitochondrial biogenesis, which drives transcription of genes involved in oxidative phosphorylation and energy production [7–12]. Beyond metabolism, IL-6/gp130-mediated activation of STAT3 and MAPK/ERK pathways supports muscle repair by stimulating satellite cell proliferation and differentiation, modulating immune cell infiltration, and coordinating extracellular matrix remodeling. Collectively, these signaling mechanisms ensure that skeletal muscle efficiently adapts to energetic demands while maintaining regenerative capacity after injury [13–15].

The connection between gp130 signaling and insulin resistance lies primarily in the induction of Suppressor of Cytokine Signaling 3 (SOCS3). Chronic activation of gp130 by cytokines such as IL-6 leads to sustained JAK/STAT3 signaling and consequent upregulation of SOCS3 [16–18]. SOCS3 interferes with insulin signaling by binding to the insulin receptor and insulin receptor substarte-1 (IRS-1), blocking their phosphorylation and downstream activation of the PI3K/AKT pathway. This disruption reduces GLUT4 translocation and glucose uptake in skeletal muscle [12, 17, 19]. While gp130 activation during exercise can improve glucose metabolism through AMPK and transient STAT3 activation, sustained stimulation contributes to insulin resistance, particularly in obesity, type 2 diabetes, and chronic inflammation [18, 20, 21]. Most of the current data derives from rodent models and cell culture, with limited direct confirmation in humans.

Gp130 also exists in a soluble form (sgp130), which acts as a selective antagonist of IL-6 trans-signaling. It binds the IL-6/sIL-6R complex, preventing its interaction with membrane-bound gp130 and thereby blocking trans-signaling without affecting classical IL-6 signaling. This helps regulate IL-6 activity and limits excessive inflammation while preserving its regenerative functions [5]. Zuliani et al. [22] suggest that elevated sgp130 levels may be linked to the presence of insulin resistance, whereas Kraakman et al. [23] report that sgp130 does not improve insulin resistance. The precise role of sgp130 and their impact on insulin metabolism remain poorly understood.

Therefore, the present study aimed to analyze the expression of IL-6–related genes (IL6R, IL6ST – gene encoding gp130) and JAK/STAT pathway components in individuals with overweight and obesity, compared with normal-weight individuals, and to examine their association with insulin sensitivity. It also evaluated the role of serum sgp130, a key regulator of IL-6 signaling, in individuals with overweight and obesity.

Materials and methods

Study group

The study group consisted of 57 individuals (16 women and 41 men), including 25 with normal body weight (BMI < 25 kg/m²), 17 with overweight (BMI ≥ 25 kg/m² and ≤ 30 kg/m²) and 15 with obesity (BMI > 30 kg/m²). All individuals were sedentary, i.e. performing no structured regular exercise > 20 min twice weekly. Physical activity was assessed with a questionnaire, and active metabolic rate (AMR) was calculated. All participants had maintained a stable body weight for at least three months prior to the study. Each volunteer was a non-smoker, free from significant illnesses, not using any medications and showed no clinical or inflammatory indicators of disease. Clinical evaluations, anthropometric measurements, and laboratory analyses were conducted following established procedures [24]. The Ethics Committee of the Medical University of Bialystok approved the study, and written informed consent was obtained from all volunteers before participation.

Measurements of insulin sensitivity, muscle biopsy and biochemical analyses

Participants underwent an overnight fast of at least 10–12 h before the clamp and biopsy procedures. Insulin sensitivity was measured by using the hyperinsulinemic-euglycemic clamp technique as described [25, 26] in all tested groups of volunteers. Briefly, insulin (Actrapid HM; Novo Nordisk) was given as a primed-continuous i.v. infusion at 40 mU m^{− 2} min^{− 1}. Arterialized blood glucose was obtained every 5 min, and 20% dextrose (1.11 mol/L) infusion was adjusted to maintain plasma glucose levels at 5.0 mmol/L. Whole-body glucose uptake (M) was calculated as the mean glucose infusion rate during the last 40 min of the clamp, corrected for the glucose space and normalized to fat-free mass (FFM) [24].

Before clamp, skeletal muscle biopsies were obtained from the vastus lateralis under local anesthesia with 1% lidocaine. A percutaneous biopsy was performed using a 4.5 mm diameter skeletal biopsy needle (Popper & Sons, Inc.), approximately 15 cm above the patella, following a 1 cm skin incision. Tissues were immediately placed in RNAlater solution (Ambion, Thermo Fisher Scientific) to stabilize RNA and subsequently stored at − 80 °C until further analysis [26].

Plasma glucose and serum insulin was measured as described previously [24, 27]. Serum sgp130 was measured with a quantitative sandwich enzyme immunoassay kit (ELISA) (R&D Systems, Minneapolis, MN) with the lowest detectable limit of 0.08 ng/ml and with intra- and interassay CVs below 5.5 and 5.2%, respectively [28]. Serum high-sensitivity IL-6 (sIL-6) and sIL-6R concentrations were determined with ELISA kits (R&D Systems) [28]. The minimum detectable concentration was 0.039 pg/ml for hsIL-6 and 6.5 pg/ml for sIL-6R. Intra- and interassay CVs were, respectively, < 7.8 and 9.6% for hsIL-6 and < 8.6 and 9.6% for sIL-6R.

The expression of Proinflammatory genes in skeletal muscle

RNA purification and gene expression analyses were performed as described [26, 29]. The mRNA was extracted using the RNeasy minikit on a fully automated Qiacube (QIAGEN GmbH). Assessment of RNA quantity and quality were confirmed using an Agilent Technologies 2100 Bioanalyzer and RNA 6000 Nano LabChip kit (Agilent, Mountain View, CA). RNA purity (A260/A280 ratio) was assessed by using a NanoDrop spectrophotometer (NanoDrop 2000, Thermo Scientific Inc., Wilmington, DE). The cDNA was then synthesized with the EvoScript Universal cDNA Master kit (Roche Diagnostics, Rotkreuz, Switzerland) according to the manufacturer’s instructions. The mRNA expression was determined using the real-time PCR method. Samples were quantified using primers and Taqman probes specific for the analyzed genes using QuantStudio 6 Flex System equipment (Applied Biosystems, Waltham, Massachusetts, USA). The following assays were used: IL6R (Hs05412665_s1), IL6ST (Hs00174360_m1), JAK1 (Hs010269883_m1), JAK2 (Hs01078136_m1), STAT3 (Hs00374280_m1), SOCS3 (Hs02330328_s1), PRKAA1 (Hs01562315_m1), PRKAA2 (Hs00178903_m1) and B2M (Hs00187842_m1) (TaqMan Gene Expression Assays; Thermo Fisher Scientific). Each reaction was performed in triplicate using TaqMan™ Universal PCR Master Mix (Applied Biosystems) under standard cycling conditions for 45 cycles. Relative mRNA expression levels were normalized to beta-2-microglobulin (B2M) gene and calculated using the comparative ΔΔCt method in QuantStudioTM Real-Time PCR software 1.3.

Statistical analyses

Statistical analysis was performed using the STATISTICA 13.3 program (Statsoft, Kraków, Poland). Data are presented as mean ± SD. Variables that did not have a normal distribution were log-transformed before analysis. Following the log transformation, the Shapiro–Wilk test indicated that the data were approximately normally distributed (p > 0.05). Absolute values are presented in the Results section. Differences among groups were assessed using one-way ANOVA and post hoc Tukey test. Relationships between variables were examined using Pearson’s product-moment correlation and multiple regression analyses. A significance level of P < 0.05 was considered statistically significant in all analyses.

Results

The clinical characteristics and biochemical data of individuals with normal body weight, overweight, and obesity are presented in Table 1. The analysis revealed significantly elevated serum sgp130 concentrations in individuals with overweight and obesity. Clamp-derived insulin sensitivity (M) was also statistically significantly reduced in participants with overweight (p = 0.001) and obesity (p < 0.001). Serum sgp130 was positively correlated with BMI (r = 0.43, P < 0.01) and showed a significant inverse correlation with insulin sensitivity (r = -0.44, P < 0.01). Furthermore, the lipid profile showed marked higher levels of triacylglycerols (p = 0.003), LDL-cholesterol (p = 0.033) levels, along with lower levels of HDL-cholesterol (p = 0.011) in individuals with obesity compared to those with normal body weight.

Table 1.

Clinical characteristics and biochemical data of participants with normal body weight, overweight and obesity

	Normal-weight (n=25)a	Overweight (n=17)a	Obesity (n=15)a
Age (years)	23,48 ± 2,79	23,82 ± 2,65	24,93 ± 4,62
BMI (kg/m 2 ) b	22,34 ± 1,78	27,19 ± 1,69	32,86 ± 2,17
Waist (cm)	80,40 ± 5,54	92,76 ± 7,91	108,13 ± 9,44
Body fat (%)	18,16 ± 6,50	26,29 ± 7,53	33,73 ± 8,14
AMR (kJ/day) c	767,94 ± 381,81	797,87 ± 444,32	585,80 ± 209,07
Fasting plasma glucose (mg/dL)	85,04 ± 8,88	86,84 ± 9,35	87,08 ± 8,22
Fasting serum insulin (µIU/mL)	7,69 ± 2,56	13,72 ± 9,17***	15,04 ± 6,36***
Cholesterol (mg/dL)	163,20 ± 34,22	175,56 ± 34,51	187,01 ± 23,40
Triacylglycerols (mg/dL)	68,70 ± 25,68	91,33 ± 52,61	115,10 ± 45,60**
HDL-cholesterol (mg/dL)	62,31 ± 9,54	58,98 ± 13,93	52,05 ± 6,56*
LDL-cholesterol (mg/dL)	93,58 ± 28,54	101,80 ± 38,55	121,03 ± 31,77*
M (mg/kg FFM /min) d	9,33 ± 2,69	7,47 ± 2,23**	4,99 ± 2,08***
sIL-6	1,12 ± 1,38	0,89 ± 0,41	1,64 ± 2,13
sIL-6R	49416,89 ± 15187,09	52215,60 ± 11834,86	56603,37 ± 19061,94
sgp130 (ng/ml)	291,70 ± 41,98	335,83 ± 58,03*	365,38 ± 56,47***
CRP	0,50 ± 0,59	0,69 ± 0,46*	1,29 ± 0,75***

^a Values are mean ± SD

^b Body mass index

^c AMR, active metabolic rate

^d M, clamp-derived insulin sensitivity

P-values * < 0.05, ** < 0.01, *** < 0.001 vs. the normal-weight group

Correlation analyses revealed no significant association between sgp130 and IL6ST expression in skeletal muscle

Individuals with overweight had lower muscle IL6R gene expression, while those with obesity had lower IL6ST gene expression compared to normal-weight individuals (Fig. 1). The expression of IL6R in individuals with obesity, IL6ST in individuals with overweight, and other genes related to gp130 (JAK2, SOCS3) is also reduced in overweight and obesity, although this reduction is not statistically significant (Fig. 1). The expression of IL6R (r = 0.28, p = 0.036), IL6ST (r = 0.46, p < 0.001), JAK2 (r = 0.32, p = 0.015), STAT3 (r = 0.44, p < 0.001) and PRKAA2 (r = 0.26, p = 0.049) in skeletal muscle showed a positive correlation with insulin sensitivity (Fig. 2), which was independent of BMI (IL6ST β = 0.30, p = 0.008; JAK2 β = 0.25, p = 0.019; STAT3 β = 0.28, p = 0.011), except for IL6R and PRKAA2. There was no significant correlation between the expression of the examined genes and serum CRP levels.

Fig. 1.

Expression of genes related with gp130 in skeletal muscle of individuals with normal body weight, overweight and obesity. ^*P-values * < 0.05 vs. normal-weight group

Fig. 2.

Correlations between insulin sensitivity (M) and skeletal muscle IL6R (A), IL6ST (B), JAK2 (C), STAT3 (D), PRKAA2 (E) gene expression in the entire study group (N = 57)

Significant correlations (Table 2) were identified in the entire group between PRKAA1 expression, which encodes the catalytic α1 subunit of AMPK, and the expression of JAK1 (r = 0.65, p < 0.001), JAK2 (r = 0.34, p = 0.009), and STAT3 (r = 0.46, p < 0.001). In addition, PRKAA2, encoding the α2 subunit of AMPK, was significantly correlated with IL6ST (r = 0.44, p = 0.001), JAK1 (r = 0.59, p < 0.001), JAK2 (r = 0.52, p < 0.001), and STAT3 (r = 0,52, p < 0.001). The associations linking PRKAA1 and PRKAA2 expression with IL-6-related gene expression were independent of BMI.

Table 2.

The correlations between insulin sensitivity (M), IL-6–related genes and JAK/STAT pathway genes, were analyzed in the entire study group (n = 57). Additionally, correlations between PRKAA1 and PRKAA2 expression, IL-6–related genes and JAK/STAT pathway genes were examined in the entire study group (n = 57)

Variable	r
	IL6R	IL6ST	JAK1	JAK2	STAT3	PRKAA2
M	0.28*	0.46***	-	0.32*	0.44***	0.26*
PRKAA1	-	-	0.65***	0.34**	0.46***	-
PRKAA2	-	0.44**	0.59***	0.52***	0.52***	-

P-values * < 0.05, ** < 0.01, *** < 0.001 vs. the normal-weight group

Discussion

This study reveals for the first time that elevated serum sgp130 levels and altered gp130 signaling gene expression in skeletal muscle are associated with reduced insulin sensitivity in individuals with overweight and obesity, independent of BMI and inflammation.

In our study, a positive correlation between sgp130 levels and BMI, suggesting that obesity is associated with an increase in gp130-related signaling. This finding aligns with previous studies, such as Filippo et al. [30], who suggested that insulin resistance in children and adolescents with obesity is linked to elevated IL-6 levels and reduced sIL-6R, which is part of the broader IL-6 signaling pathway that has been implicated in metabolic dysfunction. No significant changes in circulating sIL-6 and sIL-6R levels were observed, which may reflect the early phase of obesity and insulin resistance development in participants. Serum sgp130 is expressed at much lower levels compared with soluble IL-6Rα (sIL-6Rα), a finding that is also supported by previous studies [31, 32]. Furthermore, Nikolajuk et al. [28] demonstrated an increase in serum sgp130 concentration in obesity, underscoring the broader relevance of sgp130 in obesity-related metabolic disturbances. This study did not find a significant relationship between sgp130 levels and CRP levels, suggesting that the effects of sgp130 on insulin sensitivity may be independent of generalized systemic inflammation often seen in obesity [33].

Correlation analysis revealed no significant association between sgp130 and gene encoding gp130 (IL6ST) expression in skeletal muscle, indicating that skeletal muscle is unlikely to be a major source of circulating sgp130. Instead, adipose tissue may contribute more substantially to systemic sgp130 levels. These results align with previous evidence that adipose tissue serves as a primary source of chronically elevated circulating IL-6 in obesity [34]. Although skeletal muscle can also produce IL-6 under inflammatory conditions, as demonstrated by Bouzakri et al. [35], who showed that TNF-α stimulation increases IL-6 secretion from human myotubes.

Adipose tissue primarily serves as energy storage and an endocrine organ, secreting cytokines (adipokines) like IL-6 to regulate systemic metabolism [36]. In contrast, skeletal muscle is a metabolically active tissue responsible for glucose uptake, energy expenditure, and contraction, and it responds dynamically to exercise, nutrient status, and inflammatory signals [8]. While human obesity is associated with elevated expression of IL6R and IL6ST in adipose tissue [37], our findings show that IL6R expression in skeletal muscle is reduced in overweight, and IL6ST expression is reduced in obesity. Furthermore, expression of IL6ST, JAK2, STAT3 is positively associated with insulin sensitivity, independent of BMI. Human data on IL-6-related insulin resistance in skeletal muscle is limited. Sato [38] demonstrated that gp130 knockdown in mice skeletal muscle cells led to decreased STAT3 phosphorylation, impaired insulin-mediated glucose metabolism signaling and decreased glucose uptake, suggesting that the absence of gp130 disrupts insulin-mediated glucose uptake by impairing glucose metabolism-regulated signaling pathways. Nieto-Velazquez et al. [11, 20] demonstrated that IL-6 can both promote and inhibit insulin sensitivity in mouse skeletal muscle.

Unlike adipose tissue, where IL-6 signaling may primarily influence systemic inflammation, in muscle this pathway integrates metabolic adaptation and inflammatory responses at the cellular level. The BMI independence suggests these correlations are intrinsic to muscle physiology rather than driven by fat mass or systemic inflammation. In our study, expression of PRKAA1 and PRKAA2, encoding the catalytic α1 and α2 subunits of AMPK, was significantly correlated with IL6ST (gp130), JAK1, JAK2, and STAT3, independent of BMI. PRKAA1 and PRKAA2 are central regulators of cellular energy metabolism [39, 40], promoting glucose uptake and fatty acid oxidation, while IL6ST, JAK1, JAK2, and STAT3 mediate IL-6–dependent signaling involved in inflammation and insulin sensitivity. These associations suggest coordinated regulation between AMPK and IL-6/JAK/STAT3 pathways, linking metabolic and inflammatory responses in skeletal muscle. Carey et al. [9] demonstrated that acute IL-6 treatment can enhance glucose uptake and fat oxidation in skeletal muscle, primarily through the activation of AMPK. However, it remains unclear whether functional AMPK signaling is required for mediating the beneficial or adverse metabolic effects of IL-6 [41]. All participants in this study were sedentary, which may have led to reduced AMPK activity [42] and impaired IL-6–mediated signaling in skeletal muscle, thereby contributing to dysregulated metabolic control. Regular physical activity may enhances these pathways, supporting improved insulin sensitivity and metabolic resilience [43].

The inability to assess protein expression due to limited tissue availability is a significant limitation of this study. Additionally, a definitive cause–effect relationship cannot be established.

In conclusion, our findings highlight the potential role of gp130 (IL6ST) in regulating insulin sensitivity in obesity. The observed correlations between IL-6 pathway genes (IL6ST, JAK2, STAT3) and metabolic regulators (PRKAA1 and PRKAA2) suggest an interaction between cytokine signaling and energy-sensing pathways in skeletal muscle. To determine causality, future studies should employ functional approaches, such as muscle-specific knockout or overexpression models of IL6ST or AMPK, to evaluate direct effects on glucose uptake and insulin signaling. Moreover, exercise intervention or AMPK-activating treatments in animal or human studies could clarify how modulation of these pathways influences metabolic outcomes. These investigations would provide mechanistic insight into how IL-6/gp130–AMPK signaling contributes to metabolic regulation, potentially revealing new targets for improving insulin sensitivity in obesity.

Funding

This study was supported by the research fund of the Institute of Animal Reproduction and Food Research, Polish Academy of Sciences, Poland.

Declarations

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

All data generated or analysed during this study are included in this published article.