Many people living with diabetes also have nonalcoholic fatty liver disease (NAFLD). Interleukin-6 (IL-6) is involved in both diseases, interacting with both membrane-bound (classical) and circulating (trans-signaling) soluble receptors. We investigated whether secretion of IL-6 trans-signaling coreceptors are altered in NAFLD by diabetes and whether this might associate with the severity of fatty liver disease. Secretion patterns were investigated with use of human hepatocyte, stellate, and monocyte cell lines. Associations with liver pathology were investigated in two patient cohorts: 1) biopsy-confirmed steatohepatitis and 2) class 3 obesity. We found that exposure of stellate cells to high glucose and palmitate increased IL-6 and soluble gp130 (sgp130) secretion. In line with this, plasma sgp130 in both patient cohorts positively correlated with HbA1c, and subjects with diabetes had higher circulating levels of IL-6 and trans-signaling coreceptors. Plasma sgp130 strongly correlated with liver stiffness and was significantly increased in subjects with F4 fibrosis stage. Monocyte activation was associated with reduced sIL-6R secretion. These data suggest that hyperglycemia and hyperlipidemia can directly impact IL-6 trans-signaling and that this may be linked to enhanced severity of NAFLD in patients with concomitant diabetes.

Article Highlights

  • IL-6 and its circulating coreceptor sgp130 are increased in people with fatty liver disease and steatohepatitis.

  • High glucose and lipids stimulated IL-6 and sgp130 secretion from hepatic stellate cells.

  • sgp130 levels correlated with HbA1c, and diabetes concurrent with steatohepatitis further increased circulating levels of all IL-6 trans-signaling mediators.

  • Circulating sgp130 positively correlated with liver stiffness and hepatic fibrosis.

  • Metabolic stress to liver associated with fatty liver disease might shift the balance of IL-6 classical versus trans-signaling, promoting liver fibrosis that is accelerated by diabetes.

Nonalcoholic fatty liver disease (NAFLD) is a multistep, progressive disorder beginning with simple steatosis that can evolve to nonalcoholic steatohepatitis (NASH), characterized by hepatocellular ballooning, lobular inflammation, and fibrosis. NAFLD prevalence is rapidly increasing worldwide, currently affecting 25% of the population (1). The biological and physiological signals corresponding to and mediating the transition from simple steatosis to the more advanced and pathogenic stages of NASH are not well understood. NAFLD is closely associated with obesity and diets high in fat and sugar (2). NAFLD stemming from metabolic disease, recently reclassified as metabolically associated steatotic liver disease (MASLD) (3), is often diagnosed in conjunction with diabetes. Upward of 70–80% of people with diabetes also have MASLD, and conversely, MASLD increases one’s risk of developing diabetes by two- to threefold (4). Whether or how one disease impacts the other is unclear.

Liver inflammation plays a key role in the transition of simple steatosis to steatohepatitis. Interleukin-6 (IL-6) is an inflammatory cytokine closely associated with metabolic disease (5,6), has both pro- and anti-inflammatory properties, and may play a role in the progression of NAFLD to NASH (7,8). IL-6 signaling involves activation of either a membrane-bound receptor (classical) or formation of a signaling complex with a soluble (s)IL-6 receptor found in circulation (trans-signaling). Both types of signaling require the ligand/receptor complex to bind a coreceptor, glycoprotein 130 (gp130), on the surface of cells. Circulating IL-6R (sIL-6R), shed from receptor-expressing cells, can dock gp130 on distant cells, allowing IL-6 trans-signaling in tissues that do not express the IL-6R. A soluble, secreted form of the coreceptor (sgp130) also circulates and can inhibit trans-signaling by sequestering the IL-6/sIL-6R complex (9). Based on expression patterns, hepatocytes and hepatic stellate cells may be a rich source of sIL-6R and sgp130, respectively, suggesting the liver as a potential major player in IL-6 trans-signaling (10,11). There is evidence linking increased IL-6 trans-signaling to other metabolic diseases including diabetes (1214), as well as to alcohol- and infection-induced chronic liver disease (11).

While classical IL-6 signaling is known to have close links to NAFLD and metabolic disease, associations between IL-6 trans-signaling and NAFLD/NASH have not been evaluated. In this study, we investigated whether the liver could be a significant source of these circulating coreceptors and whether their levels relate to liver pathology associated with diabetes in two human cohorts with NAFLD. We also investigated whether metabolic stress influences the secretion of IL-6 trans-signaling mediators from liver cell types.

Human Cell Lines

HepG2 cells were cultured in DMEM (1.0 g/L glucose) with 10% FBS, streptomycin/penicillin, and 1% nonessential amino acids. LX-2 cells were cultured in DMEM (4.5 g/L glucose) with 5% FBS, streptomycin/penicillin, and 1 mmol/L sodium pyruvate. THP-1 cells were cultured in RPMI medium (2.0 g/L glucose) with 10% FBS, streptomycin/penicillin, and 1 mmol/L sodium pyruvate. Cell lines were plated at 250,000 cells/mL. LX-2 cells were activated with 5 ng/mL transforming growth factor-β for 48 h (0.5% FBS) followed by 24 h recovery (5% FBS). THP-1 cells were activated with 100 nmol/L propidium monoazide (PMA) for 48 h. For glucolipotoxic challenge, cells were starved overnight in media with 0.5% FBS prior to treatment in similar media with control (BSA vehicle) or additional 25 mmol/L d-glucose and 250 μmol/L sodium palmitate (conjugated to BSA, 1:6) for 18 h.

Conditioned media were collected and cells harvested for mRNA (Trizol) or protein (radioimmunoprecipitation assay [RIPA]). For inhibitor studies, LX-2 cells were treated with vehicle (DMSO), 3 μmol/L GI254023X (GI) (no. AOB3611, ADAM10 inhibitor; AOBIOUS), or 3 µmol/L GW280264X (GW) (AOB3632, ADAM10/17 inhibitor; AOBIOUS) 30 min before glucose/palmitate challenge. For ADAM10 Western blot, RIPA buffer was supplemented with 5 μmol/L GI254023X for prevention of autocatalytic degradation.

Quantification of Media and Serum Cytokines

IL-6, sIL-6R, and sgp130 were measured in conditioned media or plasma with ELISA, according to instructions (D6050, DR600, and DGP00, Human Quantikine ELISA kits; R&D Systems). Levels of secreted proteins were normalized to total cellular protein.

RNA and Protein Quantification

DNAse-treated RNA (1 µg) was reversed transcribed (High-Capacity cDNA Reverse Transcription Kit; Applied Biosystems) and RT-qPCR performed (G892, BlasTaq qPCR MasterMix; Applied Biological Materials) with use of primers: GP130 (forward, 5′-GCAACATTCTTACATTCGGACAG-3′; reverse, 5′-CTCGTTCACAATGCAACTCAAA-3′), IL-6R (forward, 5′-CCTCTGCATTGCCATTGTTC-3′; reverse, 5′-ATGCTTGTCTTGCCTTCCT-3′), IL-6 (forward, 5′-CCCTGACCCAACCACAAA-3′; reverse, 5′-GGACTGCAGGAACTCCTTAAA-3′), ADAM10 (forward, 5′-CCAACAAGGACATGAATT-3′; reverse, 5′-TGTTCCCAGTGCTGGTTTAG-3′), ADAM17 (forward, 5′-CGTGGTGGTGGATGGTAAA-3′; reverse, 5′-ATGTGGGCTAGAACCCTAGA-3′), and RPLP0 (forward, 5′-CGAAATGTTTCATTGTGGGAG-3′; reverse, 5′-CATTCCCCCGGATATGAGGCAGCA-3′). Relative mRNA expressed as 2−ΔCt were normalized to RPLP0.

Proteins solubilized in RIPA were resolved with SDS-PAGE, transferred to nitrocellulose, and probed with anti-ADAM10 (14194; Cell Signaling Technology) or anti–β-ACTIN (A5441; Sigma-Aldrich). ChemiDoc (Bio-Rad Laboratories) and Image Lab software were used to capture and quantify signals.

Patients With NASH

Plasma samples, histological liver scoring, and MRI/magnetic resonance elastography (MRE) data were obtained from 50 patients with NASH (28 women, 22 men) previously recruited from a registry of patients with NASH (study initiated in 2016 with ethics approval at Centre hospitalier de l’Université de Montréal, institutional review board no. 15.147). All selected participants in the current study (institutional review board no. 17.031) provided written informed consent allowing preservation and use of their plasma samples and data.

Subjects were aged 18 years and older, diagnosed with NASH (biopsy confirmed), and able to undergo MRI without contrast agent. Subjects were excluded on the basis of alcohol consumption (>10 drinks/week for women and >15 for men) or if they had liver disease other than NASH, were taking medications associated with steatosis (e.g., amiodarone, valproate, tamoxifen, methotrexate, or corticosteroids), were physically unable to fit in the MRI, had contraindications to MRI, or were pregnant or wished to be pregnant during that year. One patient without steatosis and 10 with previous history of hepatocellular carcinoma were excluded. Proton density fat fraction, liver volume (voxels, cm3), and liver stiffness (Pa) were measured as quantitative predictors of liver fat, volume, and fibrosis, respectively. Average proton density fat fraction values for the entire liver volume were obtained with use of the LiverLab package (version VE11C, MAGNETOM Aera; Siemens Healthineers). Liver stiffness by MRE was measured as previously described (15). Repeatability, reproducibility, and accuracy of MRE in NAFLD were previously reported (16,17). Fasting plasma samples were collected on the day of the MRI/MRE and stored at −80°C. Fibrosis stages, activity scores, and steatosis grades were determined by a pathologist according to the NASH Clinical Research Network histological scoring system (18) on liver biopsies taken 6–12 months prior to MRI/MRE.

Patients With Class 3 Obesity

Plasma samples and matching liver biopsies were obtained from Institut universitaire de cardiologie et de pneumologie de Québec (IUCPQ) Biobank, Université Laval, in compliance with IRB-approved management policies initiated in 2002 and still ongoing. Liver biopsy samples were collected at the time of bariatric surgery with ethics approval (IRB no. 1142). Adult men and women (18 years and older) were selected from the registry of 4,781 patients. Exclusion criteria were alcohol consumption (>10 drinks/week for women and >15 for men) or liver disease other than NASH (e.g., autoimmune hepatitis, Wilson disease, hemochromatosis, hepatitis B virus, hepatitis C virus, human immunodeficiency viruses). Our retrospective analysis included a subpopulation of 245 subjects who had both blood samples and histological scoring data available. Group selection prioritized equal representation of sex (123 men, 122 women) and fibrosis stage (F0–F4).

Random blood samples were collected on the night before surgery and stored at −80°C until analysis. Sampling procedure and position were standardized among surgeons. Liver samples were obtained by incisional biopsy of the left lobe and not cauterized. Grading and staging of histological liver sections were performed according to the methodology of Brunt (19) by pathologists blinded to study objectives. The algorithm of Bedossa et al. (20) was used to diagnose NASH, with use of liver biopsy scores for hepatocellular ballooning stage (0–2), lobular inflammation (0–2), steatosis grade (G0–G3), activity score (A0–A4), and fibrosis stage (F0–F4). Since participants in both cohorts were diagnosed prior to 2023 guidelines for MASLD, not all precisely fit this new designation. Thus, we have chosen to use the older classifications of NAFLD and NASH herein for accuracy.

Statistics

Data are presented as mean ± SD for continuous variables and number of subjects (n) and percentage (%) for categorical variables. Normality was evaluated with Kolmogrov-Smirnov test. When normality failed, data were log transformed (log10). Outliers and influencers were identified with SPSS. One subject (NASH cohort) was a strong influencer for plasma IL-6 and sIL-6R and excluded from all analyses. Data were analyzed with unpaired t test, one-way ANOVA, and Pearson correlation as indicated. Sensitivity analysis was performed with Mann-Whitney U test for intergroup differences. For categorical variables, χ2 test was used for count >5; otherwise, Fisher exact test was used. Since the number of these covariates should not be >10% of patient number, stepwise forward regression analysis (liver fat fraction, volume, and stiffness) and univariate analysis (steatosis grade, activity score, fibrosis stage) for the NASH cohort were adjusted with two models (model 1, age, sex, BMI, and diabetes; model 2, age, sex, BMI, and metformin). Diabetes and metformin were classified in different models due to their strong association (P < 0.001). For the morbid obesity cohort, univariate analysis (steatosis grade, activity score, hepatocellular ballooning, lobular, portal inflammation, and fibrosis stage) was adjusted with age, sex, BMI, diabetes, and metformin in one model. Data were analyzed with IBM SPSS (version 27) and GraphPad Prism (version 8), and significance was set at P < 0.05.

Data and Resource Availability

Data, analytical methods, and study materials are available on request.

Hepatic Stellate Cells Express and Secrete sgp130 in Response to Glucolipotoxic Stress

As NASH progresses, the proportion of hepatocytes in liver decreases, whereas hepatic stellate cells and macrophages increase with each fibrosis stage (21). Since inflammation is an important component of the simple steatosis–to–NASH transition, we hypothesized that IL-6 trans-signaling may be active in liver and altered following exposure to glucolipotoxic (high glucose and lipid) conditions. To test this, we first measured mRNA expression of IL-6 trans-signaling components in human hepatocyte (HepG2), quiescent or activated hepatic stellate (LX-2), and unactivated or activated macrophage (THP-1) cell lines to determine the source(s) of these proteins. Although all cell types expressed transcripts for IL-6, IL-6Rα, and GP130, LX-2 stellate cells expressed significantly higher IL-6 (Supplementary Fig. 1A) and GP130 mRNA (Supplementary Fig. 1C) compared with other cell types. Only HepG2 hepatocytes and THP-1 macrophage cells expressed appreciable levels of IL-6 receptor (IL-6R) transcripts (Supplementary Fig. 1B).

Although all cell lines expressed IL-6 mRNA, only LX-2 stellate cells secreted IL-6 (Fig. 1A). In line with our expression data, only HepG2 hepatocytes and THP-1 immune cells secreted the soluble sIL-6R (Fig. 1E and H), confirming observations by Lemmers et al. (11). We also found that HepG2 and LX-2 cells secreted 10-fold more sgp130 than THP-1 cells (Fig. 1C, F, and I). Activation of the stellate cell line with transforming growth factor-β did not impact IL-6 or sgp130 secretion (Fig. 1A and C), while activation of THP-1 monocytes with PMA decreased sIL-6R and sgp130 secretion (Fig. 1H and I). Wolf et al. (22), also reported decreased sgp130, but not sIL-6R secretion, following macrophage activation. These results show that the liver can be a source of IL-6 trans-signaling mediators; however, a coordinated response from multiple hepatic cell types is required for secretion of all components of the soluble complex.

Figure 1

Secretion of IL-6 signaling mediators is influenced in hepatic stellate cells by glucolipotoxicity. Levels of IL-6 (A, D, and G), sIL-6R (B, E, and H), and sgp130 (C, F, and I) in conditioned media from quiescent and activated LX-2 and HepG2 cells, and unactivated and activated THP-1 cells. Cells were treated with high glucose and palmitate (G/P) or BSA vehicle (control [Ctl]) for 18 h, and secreted protein levels normalized to total cell protein. Analyses were performed with one-way ANOVA with multiple comparisons. Data shown are a representative experiment of three independent biological replicates, with three technical replicates for each.

Figure 1

Secretion of IL-6 signaling mediators is influenced in hepatic stellate cells by glucolipotoxicity. Levels of IL-6 (A, D, and G), sIL-6R (B, E, and H), and sgp130 (C, F, and I) in conditioned media from quiescent and activated LX-2 and HepG2 cells, and unactivated and activated THP-1 cells. Cells were treated with high glucose and palmitate (G/P) or BSA vehicle (control [Ctl]) for 18 h, and secreted protein levels normalized to total cell protein. Analyses were performed with one-way ANOVA with multiple comparisons. Data shown are a representative experiment of three independent biological replicates, with three technical replicates for each.

Close modal

NAFLD is related to and influenced by metabolic disorders associated with hyperglycemia and hyperlipidemia, including diabetes, obesity, and cardiovascular disease (23). For exploration of whether glucolipotoxicity influences secretion of IL-6 trans-signaling mediators, cell lines were exposed to high glucose and lipid. LX-2 stellate cells secreted more sgp130 when cultured in glucolipotoxic conditions (regardless of state), while significant increases in IL-6 secretion did not occur unless cells were activated (Fig. 1A and C). High glucose and palmitate did not change secretion patterns from HepG2 or THP-1 cells (Fig. 1D–I). These results suggest that glucolipotoxicity may impact secretion of IL-6 trans-signaling mediators from hepatic stellate cells.

sgp130 levels can be regulated by expression or proteolytic cleavage of gp130 on the plasma membrane (22). For determination of how glucolipotoxicity leads to increased spg130 secretion, LX-2 cells were treated with GI (ADAM10 inhibitor) or GW (ADAM10/17 inhibitor) prior to and during glucolipotoxic challenge. GI and GW similarly inhibited high glucose– and lipid-induced sgp130 secretion (Fig. 2A), suggesting ADAM10 as a potential protease implicated in cleavage of gp130. Consistent with proteolysis underlying sgp130 secretion, the mature, activated form of ADAM10 (mADAM10) was increased in response to high glucose and lipids (Fig. 2B) and this was inhibited by GI and GW without any changes in ADAM10 mRNA (Supplementary Fig. 1D) or total proenzyme levels (proADAM10) (Fig. 2B). These results suggest that glucolipotoxicity activates ADAM10, which promotes secretion of sgp130 from stellate cells.

Figure 2

Inhibition of the ADAM10 protease blocks glucolipotoxicity-induced sgp130 secretion. Cells were treated with either GI or GW inhibitor 30 min prior to high glucose and palmitate (G/P) or BSA vehicle (control [Ctl]) for 18 h. A: Sgp130 secretion was assessed and normalized to total protein content. B: proADAM10 and mADAM10 protein levels were visualized with Western blot using β-ACTIN as loading control. Analyses were performed with one-way ANOVA with multiple comparisons. Data shown is one representative experiment of three independent biological replicates, each with two to three technical replicates.

Figure 2

Inhibition of the ADAM10 protease blocks glucolipotoxicity-induced sgp130 secretion. Cells were treated with either GI or GW inhibitor 30 min prior to high glucose and palmitate (G/P) or BSA vehicle (control [Ctl]) for 18 h. A: Sgp130 secretion was assessed and normalized to total protein content. B: proADAM10 and mADAM10 protein levels were visualized with Western blot using β-ACTIN as loading control. Analyses were performed with one-way ANOVA with multiple comparisons. Data shown is one representative experiment of three independent biological replicates, each with two to three technical replicates.

Close modal

Circulating IL-6 Trans-Signaling Mediators Are Increased in Diabetes and Associated With Blood Glucose in Subjects With NAFLD and NASH

Since glucolipotoxicity altered secretion of IL-6 and sgp130 from hepatic stellate cells, we investigated whether circulating levels of IL-6 trans-signaling proteins are altered in NAFLD and whether this is impacted by diabetes. To this end, we measured plasma levels from subjects with biopsy-confirmed NAFLD or NASH from two patient biobanks. The first cohort was comprised of subjects with NASH with MRI/MRE assessment of liver disease concurrent with blood sampling (n = 38) (Table 1). Among this population, 100% had NASH, 44.7% subjects had diabetes, 47.4% had obesity, 31.6% had hyperlipidemia, and 36.8% were taking metformin. The second cohort was comprised of subjects with class 3 obesity, for whom blood and liver tissue were collected at the time of bariatric surgery (Table 2). In this population, 100% were obese, 81.9% had NAFLD, 16.5% had NASH based on Bedossa scoring (20), 40.4% had diabetes, and 15.1% were taking metformin. Consistent with diabetes being a risk factor for advanced liver disease, people with NAFLD/NASH and diabetes had higher steatosis grade, activity score, and fibrosis stage than those without diabetes (Supplementary Fig. 2AF).

Table 1

Anthropometric, metabolic, and clinical characteristics of patients with NASH

Total (n = 38)Women (n = 24)Men (n = 14)P
Baseline characteristics     
 Age (years) 50.8 ± 13.1 51.4 ± 12.6 49.7 ± 14.4 0.712 
 Weight (kg) 91.1 ± 21.9 89.1 ± 23.0 94.5 ± 20.2 0.472 
 Height (cm) 169.5 ± 9.2 166.7 ± 9.3 174.3 ± 7.1 0.012 
 BMI (kg/m231.4 ± 5.6 31.8 ± 6.2 30.8 ± 4.5 0.695 
Clinical parameters, n (%)     
 Diabetes 17 (44.7) 12 (50.0) 5 (35.7) 0.393 
 Obesity 18 (47.4) 10 (41.7) 8 (57.1) 0.357 
 Hyperlipidemia 12 (31.6) 8 (33.3) 4 (28.6) 0.528 
 Hypertension 15 (39.5) 10 (41.7) 5 (35.7) 0.717 
Medications, n (%)     
 Metformin 14 (36.8) 11 (45.8) 3 (21.4) 0.132 
 Statins 10 (26.3) 7 (29.2) 3 (21.4) 0.451 
 Corticosteroids 1 (2.6) 1 (4.2) 0 (0.0) 0.632 
 Nifedipine 1 (2.6) 1 (4.2) 0 (0.0) 0.632 
MRI/MRE data     
 Liver fat fraction (%) 14.2 ± 9.0 13.0 ± 9.3 16.3 ± 8.4 0.283 
 Liver stiffness (Pa) 2,894.8 ± 1,297.4 2,714.6 ± 1,262.1 3,203.7 ± 1,345.4 0.113 
 Liver volume (cm32,084.0 ± 721.6 2,031.8 ± 754.1 2,173.4 ± 679.7 0.361 
Fasting plasma parameters     
 Hemoglobin (mg/dL)a 141.6 ± 12.9 138.4 ± 14.0 147.3 ± 8.2 0.045 
 Globulin (g/dL)a 6.7 ± 2.3 6.9 ± 2.4 6.2 ± 2.1 0.369 
 INR-PTb 0.9 ± 0.1 0.9 ± 0.1 0.9 ± 0.1 0.125 
 Platelet count (*109/L)a 218.2 ± 69.5 231.3 ± 77.2 195.0 ± 47.6 0.134 
 AST (U/L)a 33.0 ± 17.4 29.3 ± 13.9 39.6 ± 21.3 0.120 
 ALT (IU/L)a 55.1 ± 42.0 44.4 ± 22.2 73.8 ± 60.4 0.392 
 ALP (IU/L)a 70.3 ± 25.7 73.1 ± 26.7 65.2 ± 24.2 0.292 
 Total bilirubin (µmol/L)a 11.5 ± 6.1 11.1 ± 6.8 12.2 ± 4.7 0.066 
 GGT (units/L)a 56.6 ± 62.1 43.0 ± 44.0 80.7 ± 81.8 0.066 
 Albumin (g/L)a 44.5 ± 2.5 43.6 ± 2.2 46.2 ± 2.1 0.002 
 Glycemia (mmol/L)b 6.8 ± 3.0 6.9 ± 2.8 6.6 ± 3.4 0.607 
 HbA1c (%)b 6.1 ± 1.1 6.1 ± 1.0 6.2 ± 1.4 0.781 
 Cholesterol (mmol/L)b 4.4 ± 1.1 4.7 ± 1.0 4.0 ± 1.0 0.059 
 HDL-c (mmol/L)b 1.1 ± 0.2 1.2 ± 0.3 1.0 ± 0.2 0.102 
 LDL-c (mmol/L)c 2.5 ± 0.9 2.8 ± 0.9 2.1 ± 0.8 0.037 
 Triglyceride (mmol/L)b 2.0 ± 1.3 1.8 ± 0.9 2.2 ± 1.7 0.443 
 CK-18 (units/L) 302.9 ± 255.3 246.5 ± 165.9 399.5 ± 347.7 0.341 
Plasma components of the IL-6 pathway     
 IL-6 (pg/mL) 6.1 ± 7.1 7.4 ± 8.4 3.9 ± 3.3 0.055 
 sIL-6R (ng/mL) 37.7 ± 11.2 38.5 ± 10.5 36.2 ± 12.8 0.397 
 sgp130 (ng/mL) 313.8 ± 56.8 313.1 ± 58.7 315.0 ± 55.6 0.864 
Total (n = 38)Women (n = 24)Men (n = 14)P
Baseline characteristics     
 Age (years) 50.8 ± 13.1 51.4 ± 12.6 49.7 ± 14.4 0.712 
 Weight (kg) 91.1 ± 21.9 89.1 ± 23.0 94.5 ± 20.2 0.472 
 Height (cm) 169.5 ± 9.2 166.7 ± 9.3 174.3 ± 7.1 0.012 
 BMI (kg/m231.4 ± 5.6 31.8 ± 6.2 30.8 ± 4.5 0.695 
Clinical parameters, n (%)     
 Diabetes 17 (44.7) 12 (50.0) 5 (35.7) 0.393 
 Obesity 18 (47.4) 10 (41.7) 8 (57.1) 0.357 
 Hyperlipidemia 12 (31.6) 8 (33.3) 4 (28.6) 0.528 
 Hypertension 15 (39.5) 10 (41.7) 5 (35.7) 0.717 
Medications, n (%)     
 Metformin 14 (36.8) 11 (45.8) 3 (21.4) 0.132 
 Statins 10 (26.3) 7 (29.2) 3 (21.4) 0.451 
 Corticosteroids 1 (2.6) 1 (4.2) 0 (0.0) 0.632 
 Nifedipine 1 (2.6) 1 (4.2) 0 (0.0) 0.632 
MRI/MRE data     
 Liver fat fraction (%) 14.2 ± 9.0 13.0 ± 9.3 16.3 ± 8.4 0.283 
 Liver stiffness (Pa) 2,894.8 ± 1,297.4 2,714.6 ± 1,262.1 3,203.7 ± 1,345.4 0.113 
 Liver volume (cm32,084.0 ± 721.6 2,031.8 ± 754.1 2,173.4 ± 679.7 0.361 
Fasting plasma parameters     
 Hemoglobin (mg/dL)a 141.6 ± 12.9 138.4 ± 14.0 147.3 ± 8.2 0.045 
 Globulin (g/dL)a 6.7 ± 2.3 6.9 ± 2.4 6.2 ± 2.1 0.369 
 INR-PTb 0.9 ± 0.1 0.9 ± 0.1 0.9 ± 0.1 0.125 
 Platelet count (*109/L)a 218.2 ± 69.5 231.3 ± 77.2 195.0 ± 47.6 0.134 
 AST (U/L)a 33.0 ± 17.4 29.3 ± 13.9 39.6 ± 21.3 0.120 
 ALT (IU/L)a 55.1 ± 42.0 44.4 ± 22.2 73.8 ± 60.4 0.392 
 ALP (IU/L)a 70.3 ± 25.7 73.1 ± 26.7 65.2 ± 24.2 0.292 
 Total bilirubin (µmol/L)a 11.5 ± 6.1 11.1 ± 6.8 12.2 ± 4.7 0.066 
 GGT (units/L)a 56.6 ± 62.1 43.0 ± 44.0 80.7 ± 81.8 0.066 
 Albumin (g/L)a 44.5 ± 2.5 43.6 ± 2.2 46.2 ± 2.1 0.002 
 Glycemia (mmol/L)b 6.8 ± 3.0 6.9 ± 2.8 6.6 ± 3.4 0.607 
 HbA1c (%)b 6.1 ± 1.1 6.1 ± 1.0 6.2 ± 1.4 0.781 
 Cholesterol (mmol/L)b 4.4 ± 1.1 4.7 ± 1.0 4.0 ± 1.0 0.059 
 HDL-c (mmol/L)b 1.1 ± 0.2 1.2 ± 0.3 1.0 ± 0.2 0.102 
 LDL-c (mmol/L)c 2.5 ± 0.9 2.8 ± 0.9 2.1 ± 0.8 0.037 
 Triglyceride (mmol/L)b 2.0 ± 1.3 1.8 ± 0.9 2.2 ± 1.7 0.443 
 CK-18 (units/L) 302.9 ± 255.3 246.5 ± 165.9 399.5 ± 347.7 0.341 
Plasma components of the IL-6 pathway     
 IL-6 (pg/mL) 6.1 ± 7.1 7.4 ± 8.4 3.9 ± 3.3 0.055 
 sIL-6R (ng/mL) 37.7 ± 11.2 38.5 ± 10.5 36.2 ± 12.8 0.397 
 sgp130 (ng/mL) 313.8 ± 56.8 313.1 ± 58.7 315.0 ± 55.6 0.864 

Data are means ± SD for continuous data and sample size (n) and percent within the population (%) for categorical data. P values are comparisons between men and women, measured with unpaired t test for continuous data and χ2 or Fisher exact test for categorical data. Bolded P values represent statistically significant differences. ALP, alkaline phosphatase; HDL-c, HDL cholesterol; LDL-c, LDL cholesterol; INR-PT, international normalized ratio of prothrombine time.

a

n = 23 for women, 13 for men.

b

n = 22 for women, 13 for men.

c

n = 21 for women, 12 for men.

Table 2

Anthropometric, metabolic, and clinical characteristics of patients with class 3 obesity

Total (n = 245)Women (n = 122)Men (n = 123)P
Baseline characteristics     
 Weight (kg) 135.8 ± 26.4 126.0 ± 22.1 145.5 ± 26.8 <0.0001 
 Height (cm) 168.1 ± 9.3 161.5 ± 6.5 174.6 ± 6.7 <0.0001 
 Age (years) 45.2 ± 11.4 44.0 ± 11.1 46.4 ± 11.6 0.099 
 BMI (kg/m247.9 ± 7.8 48.2 ± 7.5 47.7 ± 8.2 0.234 
Clinical parameters, n (%)     
 Diabetes 99 (40.4) 58 (47.5) 41 (33.3) 0.023 
Bedossa algorithm for NASH, n (%)     
 No NAFLD 4 (1.6) 4 (3.3) 0 (0.0) 0.042 
 NAFLD 199 (81.9) 95 (78.5) 104 (85.2)  
 NASH 40 (16.5) 22 (18.2) 18 (14.8)  
Medications, n (%)     
 Hypertension 111 (45.3) 44.0 (36.1) 67.0 (54.5) 0.004 
 Metformin 37 (15.1) 19.0 (15.6) 18.0 (14.6) 0.837 
 Other medication for diabetes 30 (12.2) 13.0 (10.7) 17.0 (13.8) 0.450 
 Dyslipidemia 54 (22.0) 23.0 (18.9) 31.0 (25.2) 0.231 
Biochemical parameters     
 Glycemia (mmol/L) 6.4 ± 2.0 6.6 ± 2.3 6.2 ± 1.6 0.316 
  HbA1c (%)a 6.0 ± 1.3 6.1 ± 1.1 6.0 ± 1.1 0.625 
 Cholesterol (mmol/L) 4.5 ± 1.0 4.6 ± 0.9 4.5 ± 1.0 0.572 
 HDL (mmol/L) 1.2 ± 0.4 1.3 ± 0.3 1.1 ± 0.5 <0.0001 
 LDL (mmol/L)b 2.6 ± 0.9 2.6 ± 0.8 2.6 ± 0.9 0.992 
 Triglyceride (mmol/L) 1.7 ± 0.8 1.5 ± 0.6 1.9 ± 1.0 0.042 
 ALT (IU/L) 33.9 ± 22.4 33.4 ± 28.6 34.4 ± 14.0 0.002 
Plasma levels of cytokines     
 IL-6 (pg/mL) 8.1 ± 16.5 10.5 ± 22.7 5.8 ± 4.3 <0.0001 
 sIL-6R (ng/mL) 42.0 ± 9.3 42.6 ± 9.3 41.5 ± 9.3 0.335 
 sgp130 (ng/mL) 316.3 ± 54.9 317.1 ± 55.5 315.4 ± 54.6 0.807 
Total (n = 245)Women (n = 122)Men (n = 123)P
Baseline characteristics     
 Weight (kg) 135.8 ± 26.4 126.0 ± 22.1 145.5 ± 26.8 <0.0001 
 Height (cm) 168.1 ± 9.3 161.5 ± 6.5 174.6 ± 6.7 <0.0001 
 Age (years) 45.2 ± 11.4 44.0 ± 11.1 46.4 ± 11.6 0.099 
 BMI (kg/m247.9 ± 7.8 48.2 ± 7.5 47.7 ± 8.2 0.234 
Clinical parameters, n (%)     
 Diabetes 99 (40.4) 58 (47.5) 41 (33.3) 0.023 
Bedossa algorithm for NASH, n (%)     
 No NAFLD 4 (1.6) 4 (3.3) 0 (0.0) 0.042 
 NAFLD 199 (81.9) 95 (78.5) 104 (85.2)  
 NASH 40 (16.5) 22 (18.2) 18 (14.8)  
Medications, n (%)     
 Hypertension 111 (45.3) 44.0 (36.1) 67.0 (54.5) 0.004 
 Metformin 37 (15.1) 19.0 (15.6) 18.0 (14.6) 0.837 
 Other medication for diabetes 30 (12.2) 13.0 (10.7) 17.0 (13.8) 0.450 
 Dyslipidemia 54 (22.0) 23.0 (18.9) 31.0 (25.2) 0.231 
Biochemical parameters     
 Glycemia (mmol/L) 6.4 ± 2.0 6.6 ± 2.3 6.2 ± 1.6 0.316 
  HbA1c (%)a 6.0 ± 1.3 6.1 ± 1.1 6.0 ± 1.1 0.625 
 Cholesterol (mmol/L) 4.5 ± 1.0 4.6 ± 0.9 4.5 ± 1.0 0.572 
 HDL (mmol/L) 1.2 ± 0.4 1.3 ± 0.3 1.1 ± 0.5 <0.0001 
 LDL (mmol/L)b 2.6 ± 0.9 2.6 ± 0.8 2.6 ± 0.9 0.992 
 Triglyceride (mmol/L) 1.7 ± 0.8 1.5 ± 0.6 1.9 ± 1.0 0.042 
 ALT (IU/L) 33.9 ± 22.4 33.4 ± 28.6 34.4 ± 14.0 0.002 
Plasma levels of cytokines     
 IL-6 (pg/mL) 8.1 ± 16.5 10.5 ± 22.7 5.8 ± 4.3 <0.0001 
 sIL-6R (ng/mL) 42.0 ± 9.3 42.6 ± 9.3 41.5 ± 9.3 0.335 
 sgp130 (ng/mL) 316.3 ± 54.9 317.1 ± 55.5 315.4 ± 54.6 0.807 

Data are means ± SD for continuous data and sample size (n) and percent within the population (%) for categorical data. P value shows comparisons between men and women, measured with unpaired t test for continuous data and χ2 or Fisher exact test for categorical data. Bolded P values represent statistically significant differences.

a

n = 122 for women, 120 for men.

b

n = 122 for women, 121 for men.

In healthy subjects, normal plasma levels of IL-6 are <3 pg/mL (24,25) and average plasma concentrations of sIL-6R and sgp130 are 35 ng/mL and 217 ng/mL, respectively (25,26). In our NASH cohort, average plasma IL-6 and sgp130 levels were above normal at 6.1 pg/mL and 313.8 ng/mL, respectively, while average levels of sIL-6R were within normal range (37.7 ng/mL) (Table 1). In the class 3 obesity cohort, average plasma IL-6, sIL-6R, and sgp130 were all above levels in healthy subjects (25,26) (8.1 pg/mL, 42.0 ng/mL, and 316.3 ng/mL, respectively) (Table 2). We also noted that circulating IL-6 was higher in women, sIL-6R and sgp130 were influenced by age, and there was a significant positive correlation between BMI and circulating IL-6 or sIL-6R (Supplementary Figs. 3 and 4), in line with previously published findings (27,28).

Given the close relationship between glucotoxicity and NAFLD severity (29), we first investigated whether IL-6 trans-signaling mediators varied with blood lipids or glycated hemoglobin (HbA1c). We found no consistent relationships between plasma cholesterol or triglycerides with any component of the circulating IL-6 trans-signaling complex (Supplementary Fig. 5). However, in the NASH cohort we observed clear correlations between HbA1c and sIL-6R or sgp130 (Fig. 3B and C) and HbA1c with sgp130 in the class 3 obesity cohort (Fig. 4C). Consistently, plasma IL-6 and sIL-6R in the NASH cohort (Fig. 3D and E), and all three trans-signaling components in the obese population, were significantly higher in subjects with NASH and concurrent diabetes (Fig. 4D–F). Metformin can reduce inflammatory signaling (30); yet, IL-6 and sIL-6R were higher in individuals with NASH taking metformin (Fig. 3G and H) and sgp130 was higher in individuals with obesity taking metformin (Fig. 4I). Interestingly, the relationship between sIL-6R and HbA1c was not seen in the obesity cohort (Fig. 4B). This may be explained by sex differences, as we found significant associations between sIL-6R and HbA1c in women of both cohorts (NASH, r = 0.39, P = 0.02; class 3 obesity, r = 0.17, P = 0.06) but not men (NASH, r = 0.01, P = 0.97; class 3 obesity, r = 0.04, P = 0.70). Taken together with in vitro data, our data suggest a strong association between circulating regulators of IL-6 trans-signaling and diabetes that may be associated with increased secretion within a setting of hyperglycemia.

Figure 3

IL-6 trans-signaling correlates with HbA1c, diabetes, and metformin use in NASH. Pearson correlations between plasma IL-6 (A), sIL-6R (B), and sgp130 (C) with plasma HbA1c in patients with NASH. n = 22 women and n = 13 men. Plasma concentrations of IL-6, sIL-6R, and sgp130 in patients with NASH compared among patients with diabetes (DF) and metformin use (GI). Analysis was conducted with t test; n = 24 women, n = 14 men.

Figure 3

IL-6 trans-signaling correlates with HbA1c, diabetes, and metformin use in NASH. Pearson correlations between plasma IL-6 (A), sIL-6R (B), and sgp130 (C) with plasma HbA1c in patients with NASH. n = 22 women and n = 13 men. Plasma concentrations of IL-6, sIL-6R, and sgp130 in patients with NASH compared among patients with diabetes (DF) and metformin use (GI). Analysis was conducted with t test; n = 24 women, n = 14 men.

Close modal
Figure 4

IL-6 trans-signaling correlates with HbA1c, diabetes, and metformin use in class 3 obesity. Pearson correlations between plasma IL-6 (A), sIL-6R (B), and sgp130 (C) and plasma HbA1c in patients with class 3 obesity. n = 122 women, n = 120 men. Plasma concentrations of IL-6, sIL-6R, and sgp130 in patients with class 3 obesity compared among patients with diabetes (DF) and metformin use (GI). Analysis was conducted with t test; n = 122 women, n = 123 men.

Figure 4

IL-6 trans-signaling correlates with HbA1c, diabetes, and metformin use in class 3 obesity. Pearson correlations between plasma IL-6 (A), sIL-6R (B), and sgp130 (C) and plasma HbA1c in patients with class 3 obesity. n = 122 women, n = 120 men. Plasma concentrations of IL-6, sIL-6R, and sgp130 in patients with class 3 obesity compared among patients with diabetes (DF) and metformin use (GI). Analysis was conducted with t test; n = 122 women, n = 123 men.

Close modal

Circulating IL-6 Signaling Mediators Correlate With NAFLD Pathology

We next sought to determine whether circulating levels of IL-6 trans-signaling mediators were associated with pathological features of fatty liver disease, including hepatic lipid content, inflammation, and/or fibrosis. In both human cohorts, liver disease severity was determined with biopsy samples, while in the NASH cohort we also had access to data from MRI/MRE scans. Liver volume and stiffness measured with MRI/MRE have good prognostic value to predict liver disease severity (3134), with much greater surface area covered than with biopsy alone.

Plasma sIL-6R positively correlated with liver fat fraction (Fig. 5B) and liver volume (Fig. 5E) in the NASH cohort. However, stepwise forward regression analysis adjusted with model 1 (Supplementary Table 1) or 2 (Supplementary Table 2) demonstrated that these correlations may be influenced by BMI or metformin. Given strong relationships between BMI and liver fat/volume (35) and BMI and sIL-6R (Supplementary Fig. 3), it is impossible to delineate the contribution of liver fat versus whole-body adiposity. However, we did not observe a significant relationship between steatosis grade in biopsies and any circulating proteins in either cohort (Fig. 5J–L). Overall, data suggest that sIL-6R correlates with adiposity, but further exploration is needed to determine whether this is directly related to hepatic fat.

Figure 5

Plasma sIL-6R correlates with hepatic fat content and volume by imaging but not steatosis grade. Pearson correlations between plasma IL-6 (A and D), sIL-6R (B and E), and sgp130 (C and F) and MRE/MRI measures of liver fat fraction and liver volume in patients with NASH. n = 24 women and n = 14 men. Plasma concentrations of IL-6 (G and J), sIL-6R (H and K), and sgp130 (I and L) in patients with NASH and class 3 obesity compared among liver biopsy measures of steatosis grade. Data presented for subjects with NASH with steatosis grade G1 (n = 9) and G2 (n = 29) and class 3 obesity grade G0 (n = 5), G1 (n = 168), G2 (n = 47), and G3 (n = 25). Analysis was conducted with one-way ANOVA with multiple comparisons with adjustment for age, sex, BMI, and diabetes or metformin use.

Figure 5

Plasma sIL-6R correlates with hepatic fat content and volume by imaging but not steatosis grade. Pearson correlations between plasma IL-6 (A and D), sIL-6R (B and E), and sgp130 (C and F) and MRE/MRI measures of liver fat fraction and liver volume in patients with NASH. n = 24 women and n = 14 men. Plasma concentrations of IL-6 (G and J), sIL-6R (H and K), and sgp130 (I and L) in patients with NASH and class 3 obesity compared among liver biopsy measures of steatosis grade. Data presented for subjects with NASH with steatosis grade G1 (n = 9) and G2 (n = 29) and class 3 obesity grade G0 (n = 5), G1 (n = 168), G2 (n = 47), and G3 (n = 25). Analysis was conducted with one-way ANOVA with multiple comparisons with adjustment for age, sex, BMI, and diabetes or metformin use.

Close modal

Plasma sgp130 Correlates With Advanced Liver Disease in NASH and Class 3 Obesity

Given our observation that high glucose and lipids stimulated sgp130 secretion from stellate cells, we next evaluated relationships between circulating IL-6 trans-signaling components and liver fibrosis. Both plasma IL-6 and plasma sgp130 positively correlated with liver stiffness (Fig. 6A and C) in the NASH cohort, with plasma sgp130 showing a particularly strong linear association (r = 0.69, P < 0.0001). When adjustment with model 1 or model 2, our results show that plasma sgp130 level correlated with liver stiffness independent of all covariates (Supplementary Tables 1 and 2). We also noted a trend toward higher sIL-6R and sgp130 in NASH patients with advanced fibrosis stage versus F0–F1 (Fig. 6E and F) (sIL-6R, adjustment with model 1, P = 0.07, and model 2, P = 0.05; sgp130, adjustment with model 1, P = 0.11, and model 2, P = 0.12), while only plasma sgp130 was significantly higher in obese subjects with F4 fibrosis compared with all other stages (Fig. 6I) (adjustment with age, sex, BMI, diabetes, and metformin; P < 0.001). Taken together, data from both cohorts suggest that increased circulating sgp130 can indicate liver fibrosis in NAFLD.

Figure 6

sgp130 correlations with liver stiffness and fibrosis in people with NAFLD/NASH. Pearson correlations between plasma IL-6 (A), sIL-6R (B), and sgp130 (C) and MRE/MRI measures of liver stiffness in patients with NASH. n = 24 women and n = 14 men. Plasma concentrations of IL-6 (D and G), sIL-6R (E and H), and sgp130 (F and I) in patients with NASH and class 3 obesity compared among liver biopsy measures of fibrosis stage. Data presented for subjects with NASH with fibrosis stage F0 (n = 1, pooled with F1), F1 (n = 12), F2 (n = 21), F3 (n = 3), and F4 (n = 1, pooled with F3) and class 3 obesity stage F0 (n = 73), F1 (n = 73), F2 (n = 48), F3 (n = 41), and F4 (n = 10). Analysis was conducted with one-way ANOVA with multiple comparisons with adjustment for age, sex, BMI, and diabetes and metformin use.

Figure 6

sgp130 correlations with liver stiffness and fibrosis in people with NAFLD/NASH. Pearson correlations between plasma IL-6 (A), sIL-6R (B), and sgp130 (C) and MRE/MRI measures of liver stiffness in patients with NASH. n = 24 women and n = 14 men. Plasma concentrations of IL-6 (D and G), sIL-6R (E and H), and sgp130 (F and I) in patients with NASH and class 3 obesity compared among liver biopsy measures of fibrosis stage. Data presented for subjects with NASH with fibrosis stage F0 (n = 1, pooled with F1), F1 (n = 12), F2 (n = 21), F3 (n = 3), and F4 (n = 1, pooled with F3) and class 3 obesity stage F0 (n = 73), F1 (n = 73), F2 (n = 48), F3 (n = 41), and F4 (n = 10). Analysis was conducted with one-way ANOVA with multiple comparisons with adjustment for age, sex, BMI, and diabetes and metformin use.

Close modal

Liver stiffness (measured with MRI/MRE) is highly related to fibrosis but also influenced by inflammation and steatosis (36). Activity score is a composite value of indices given for histological evidence of inflammation (lobular and/or portal) and hepatocyte ballooning (an indication of hepatocyte damage). Plasma IL-6, sIL-6, and sgp130 did not correspond with activity score in either cohort (Supplementary Fig. 6AF). Hepatocyte ballooning trended higher with increased plasma IL-6, and portal inflammation trended higher with increased plasma sIL-6R (Supplementary Fig. 6G and L). No associations were noted with lobular inflammation. Since metabolic inflammation is intimately linked to diabetes, we investigated whether diabetes influenced these associations. Interestingly, when considering only subjects with both NAFLD and diabetes, all IL-6 trans-signaling components were associated with hepatocyte ballooning (Fig. 7A–C) and sgp130 was significantly associated with increased portal inflammation and fibrosis (Fig. 7E and F). Thus, diabetes accentuated associations of IL-6 and sgp130 with liver pathology in NAFLD, suggesting that enhanced IL-6 trans-signaling in diabetes may exacerbate NASH.

Figure 7

Increased IL-6 trans-signaling is associated with histological markers of liver inflammation in obese patients with NAFLD and concurrent diabetes. Plasma concentrations of IL-6, sIL-6R, or sgp130 in patients with class 3 obesity and diabetes compared with measures of hepatocellular ballooning stage (AC) and liver portal inflammation (D and E) and fibrosis (F) stage determined with histology. Data presented for subjects with hepatocellular ballooning stage S0 (n = 69) and S1 (n = 28); subjects with portal inflammation stage S0 (n = 20), S1 (n = 64), S2 (n = 11), and S3 (n = 2, pooled with S2); and subjects with fibrosis stage S0 (n = 17), S1 (n = 29), S2 (n = 24), S3 (n = 21), and S4 (n = 8). Analysis was conducted with one-way ANOVA with multiple comparisons with adjustment for age, sex, BMI, and diabetes and metformin use.

Figure 7

Increased IL-6 trans-signaling is associated with histological markers of liver inflammation in obese patients with NAFLD and concurrent diabetes. Plasma concentrations of IL-6, sIL-6R, or sgp130 in patients with class 3 obesity and diabetes compared with measures of hepatocellular ballooning stage (AC) and liver portal inflammation (D and E) and fibrosis (F) stage determined with histology. Data presented for subjects with hepatocellular ballooning stage S0 (n = 69) and S1 (n = 28); subjects with portal inflammation stage S0 (n = 20), S1 (n = 64), S2 (n = 11), and S3 (n = 2, pooled with S2); and subjects with fibrosis stage S0 (n = 17), S1 (n = 29), S2 (n = 24), S3 (n = 21), and S4 (n = 8). Analysis was conducted with one-way ANOVA with multiple comparisons with adjustment for age, sex, BMI, and diabetes and metformin use.

Close modal

In this study we explored relationships among three components of the IL-6 signaling pathway (IL-6, sIL-6R, and sgp130), diabetes, and steatotic liver disease. We provide novel data showing that in people with NAFLD, diabetes and hyperglycemia are associated with higher plasma concentrations of IL-6 trans-signaling mediators. Our data in cell lines suggest that high blood glucose and lipids promote ADAM10 activation and proteolytic cleavage of gp130, potentiating sgp130 secretion from hepatic stellate cells along with IL-6 (Fig. 8). In line with IL-6 trans-signaling playing a role in NAFLD pathobiology, higher plasma sgp130 strongly correlated with liver stiffness and was associated with histological evidence of liver fibrosis. IL-6 trans-signaling was also associated with liver inflammation in people with concurrent diabetes.

Figure 8

IL-6 trans-signaling mediator secretion is controlled by different liver cell types in their microenvironment. Hepatocytes and monocytes secrete sIL-6R basally, which can induce IL-6 trans-signaling in quiescent hepatic stellate cells. In return, hepatic stellate cells secrete sgp130, blunting IL-6 trans-signaling and facilitating classical signaling in hepatocytes and monocytes. Progression of NAFLD, which promotes monocyte infiltration in liver and activation into macrophages, could result in lower levels of sIL-6R from macrophages and higher amounts of sgp130 from stellate cells. In this context, inhibition of IL-6 trans-signaling in liver might be linked to steatotic hepatocytes, hepatic stellate cell activation and fibrosis, and chronic liver inflammation. In diabetes, the secretion of IL-6, sIL-6R, and sgp130 is significantly increased, which could exacerbate this pathway to accelerate the disease. The scheme was created with BioRender (biorender.com).

Figure 8

IL-6 trans-signaling mediator secretion is controlled by different liver cell types in their microenvironment. Hepatocytes and monocytes secrete sIL-6R basally, which can induce IL-6 trans-signaling in quiescent hepatic stellate cells. In return, hepatic stellate cells secrete sgp130, blunting IL-6 trans-signaling and facilitating classical signaling in hepatocytes and monocytes. Progression of NAFLD, which promotes monocyte infiltration in liver and activation into macrophages, could result in lower levels of sIL-6R from macrophages and higher amounts of sgp130 from stellate cells. In this context, inhibition of IL-6 trans-signaling in liver might be linked to steatotic hepatocytes, hepatic stellate cell activation and fibrosis, and chronic liver inflammation. In diabetes, the secretion of IL-6, sIL-6R, and sgp130 is significantly increased, which could exacerbate this pathway to accelerate the disease. The scheme was created with BioRender (biorender.com).

Close modal

Higher IL-6 is often observed in metabolic disease (5,1214,3739), but much less is known about its circulating coreceptors or how their secretion is regulated. Our data support the liver as a possible source for the circulating components of IL-6 trans-signaling in NAFLD (sIL-6R and sgp130). Most notably, all three circulating IL-6 trans-signaling components were further increased in concomitant diabetes. We show that different liver cell types secrete components of the complex and their secretion is influenced by high glucose and lipids, and we report higher circulating IL-6 and sgp130 in NAFLD/NASH aligning with increases seen in alcoholic steatotic liver disease (11). Circulating sIL-6R in both our cohorts were within normal ranges (25), while in a previous study investigators found increased plasma sIL-6R in NASH (40). However, we did not include healthy subjects for direct comparison.

There are close relationships between hyperglycemia and chronic liver disease. High blood glucose positively correlates with hepatic insulin resistance, which can result in excessive fat accumulation. Elevated blood glucose can also amplify oxidative stress and trigger secretion of inflammatory cytokines, creating a state of low but constitutive inflammation that damages liver cells and plays a critical role in development of liver fibrosis (41). Our data showing a relationship between circulating IL-6 coreceptors and HbA1c, together with in vitro data linking increased sgp130 secretion from stellate cells in response to glucolipotoxicity, lead us to propose that IL-6 trans-signaling plays a direct role in the unique pathogenesis of NAFLD associated with diabetes.

The physiological role of IL-6 trans-signaling within liver is controversial. Total ablation of hepatic IL-6 signaling in mice causes steatosis and fibrosis (40), but this does not discriminate between classical- and trans-signaling. Activation of both classical and trans IL-6 signaling is associated with increased cellular proliferation via STAT3, but trans-signaling seems to prolong activation (42). Blockade of IL-6 trans-signaling with sgp130 decreases liver regeneration following partial hepatectomy (43), while activation of IL-6 trans-signaling promotes regeneration (44,45) and aggravates liver cancer in mice (46,47). In our study, the strong correlation between sgp130 and liver stiffness/fibrosis suggests that increased IL-6 trans-signaling (IL-6 and sIL-6R) might promote repair in response to liver damage or inflammation. Since sgp130 acts as a natural inhibitor for IL-6 trans-signaling, higher secretion (i.e., by glucolipotoxicity) could inhibit repair and promote NASH progression. However, our ability to draw mechanistic links is limited by the correlative nature of human data; thus, further investigation is needed to determine whether decreased local IL-6 trans-signaling could be responsible for worsening inflammation and/or fibrosis in NAFLD.

Limitations of our study include use of isolated, immortalized cell lines and lack of an in vivo model. It is difficult to target IL-6 alone, differentiate classical versus trans-signaling, or isolate tissue-specific roles using available mouse models. Interestingly, transgenic overexpression of human sgp130 in mice does not exacerbate diet-induced NAFLD (48,49), but chronic increases may promote obesity and fatty liver with age (50), suggesting that decreased trans-signaling could potentiate metabolic disease.

One interesting possibility stemming from our data is that plasma sgp130 (alone or in combination with sIL-6R) might be an effective, noninvasive method to predict the severity of liver disease in NASH. We present this as a hypothesis-generating observation and recognize that a larger sample size and additional analysis are required to test whether IL-6 trans-signaling proteins are biomarkers of NAFLD/NASH. Yet, we found it interesting that while sgp130 correlates very well with liver stiffness by MRI/MRE, its correlation with the stage of histological fibrosis was less pronounced. Liver fibrosis in biopsies is scored based on collagen staining, while MRE-determined liver stiffness is influenced by fibrosis, inflammation, and steatosis (3234). sgp130 is a component of an inflammatory pathway, which could explain its stronger correlation with liver stiffness versus collagen (a late consequence of damage). Our data may also suggest that high sgp130 represents active NASH (i.e., inflammatory state) instead of collagen deposition (fibrosis).

In conclusion, our data support that circulating components of the IL-6 trans-signaling system correlate with NAFLD/NASH pathogenesis and that liver may be a source of these mediators in metabolic disease. Our data also suggest a link between diabetes and/or hyperglycemia and hepatic IL-6 trans-signaling. Strong associations of IL-6, sIL-6R, and sgp130 with liver pathobiology imply that these circulating proteins may be locally involved in NAFLD pathogenesis and suggest further investigation into whether higher plasma levels indicate liver damage, particularly in people with concurrent NAFLD and diabetes.

This article contains supplementary material online at https://doi.org/10.2337/figshare.24114459.

Acknowledgments. The authors acknowledge the invaluable collaboration of the surgery team, bariatric surgeons, and biobank staff of the IUCPQ. The authors also thank Paule Bodson Clermont, Centre de Recherche du Centre Hospitalier de l’Université de Montréal (CRCHUM), Hannah Zhang, Institut de recherches cliniques de Montréal (IRCM), Mélissa Léveillé (IRCM) and Stewart Jeromson (IRCM) for their assistance.

Patients and the public were not involved in the design, conduct, reporting, or dissemination plans of the authors’ research.

Funding and Duality of Interest. This work was supported by unrestricted operating grants from Merck Sharp & Dohme/University of Montreal and the International Development Research Centre (108591-001). J.L.E. and A.T. are supported by Chercheurs-boursiers Senior awards from Fonds de recherche du Québec Santé. The IUCPQ Biobank is supported by the IUCPQ Foundation and Research Center. L.B. receives funding from Johnson & Johnson, Medtronic, Bodynov, and GI Windows for studies on bariatric surgery. A.T. and J.L.E. received a speaking honorarium from Eli Lilly. No other potential conflicts of interest relevant to this article were reported.

Author Contributions. A.T. and J.L.E. designed studies. C.H. and A.B. managed the NASH clinical study. L.Bie. and A.L. designed and carried out the bariatric surgery study. A.G., C.S., L.Bil., C.Ba., and A.T. acquired, analyzed, and interpreted data. M.F. assisted with data analysis. B.N.N. scored histological samples. L.Bil., A.C., E.G., C.Bé., M.B., J.-M.G., M.L., A.T., M.F., and J.L.E. contributed intellectual content toward study design and interpretation. C.Y.C. scored liver histological samples. A.G., C.S., M.F., and J.L.E. wrote the manuscript. All authors reviewed the manuscript. J.L.E. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Prior Presentation. Parts of this study were presented in abstract form at the 2022 Canadian Liver Meeting, Ottawa, Ontario, Canada, 12–15 May 2022; IRCM 2022 Scientific Forum, Orford, Quebec, Canada, 2–3 June 2022; International Liver Congress 2022, London, U.K., 22–26 June 2022; XVIIIth Scientific Day of Molecular Biology Programs, Montreal, QC, Canada, 5 May 2023; and IRCM 2023 Scientific Forum, Carlin, British Columbia, Canada, 8–9 June 2023.

1.
Younossi
ZM
,
Koenig
AB
,
Abdelatif
D
,
Fazel
Y
,
Henry
L
,
Wymer
M
.
Global epidemiology of nonalcoholic fatty liver disease-meta-analytic assessment of prevalence, incidence, and outcomes
.
Hepatology
2016
;
64
:
73
84
2.
Huang
DQ
,
El-Serag
HB
,
Loomba
R
.
Global epidemiology of NAFLD-related HCC: trends, predictions, risk factors and prevention
.
Nat Rev Gastroenterol Hepatol
2021
;
18
:
223
238
3.
Rinella
ME
,
Lazarus
JV
,
Ratziu
V
, et al
.
group. A multi-society Delphi consensus statement on new fatty liver disease nomenclature
.
Hepatology
.
24 June 2023 [Epub ahead of print]. DOI: 10.1097/HEP.0000000000000520
4.
Cuthbertson
DJ
,
Koskinen
J
,
Brown
E
, et al
.
Fatty liver index predicts incident risk of prediabetes, type 2 diabetes and non-alcoholic fatty liver disease (NAFLD)
.
Ann Med
2021
;
53
:
1256
1264
5.
Yeste
D
,
Vendrell
J
,
Tomasini
R
, et al
.
Interleukin-6 in obese children and adolescents with and without glucose intolerance
.
Diabetes Care
2007
;
30
:
1892
1894
6.
Charles
BA
,
Doumatey
A
,
Huang
H
, et al
.
The roles of IL-6, IL-10, and IL-1RA in obesity and insulin resistance in African-Americans
.
J Clin Endocrinol Metab
2011
;
96
:
E2018
E2022
7.
Wieckowska
A
,
Papouchado
BG
,
Li
Z
,
Lopez
R
,
Zein
NN
,
Feldstein
AE
.
Increased hepatic and circulating interleukin-6 levels in human nonalcoholic steatohepatitis
.
Am J Gastroenterol
2008
;
103
:
1372
1379
8.
Giraldez
MD
,
Carneros
D
,
Garbers
C
, et al
.
New insights into IL-6 family cytokines in metabolism, hepatology and gastroenterology
.
Nat Rev Gastroenterol Hepatol
2021
;
18
:
787
803
9.
Schmidt-Arras
D
,
Rose-John
S
.
IL-6 pathway in the liver: from physiopathology to therapy
.
J Hepatol
2016
;
64
:
1403
1415
10.
Uhlén
M
,
Fagerberg
L
,
Hallström
BM
, et al
.
Proteomics. Tissue-based map of the human proteome
.
Science
2015
;
347
:
1260419
11.
Lemmers
A
,
Gustot
T
,
Durnez
A
, et al
.
An inhibitor of interleukin-6 trans-signalling, sgp130, contributes to impaired acute phase response in human chronic liver disease
.
Clin Exp Immunol
2009
;
156
:
518
527
12.
Weiss
TW
,
Arnesen
H
,
Seljeflot
I
.
Components of the interleukin-6 transsignalling system are associated with the metabolic syndrome, endothelial dysfunction and arterial stiffness
.
Metabolism
2013
;
62
:
1008
1013
13.
Nikolajuk
A
,
Kowalska
I
,
Karczewska-Kupczewska
M
, et al
.
Serum soluble glycoprotein 130 concentration is inversely related to insulin sensitivity in women with polycystic ovary syndrome
.
Diabetes
2010
;
59
:
1026
1029
14.
Chen
H
,
Zhang
X
,
Liao
N
,
Wen
F
.
Increased levels of IL-6, sIL-6R, and sgp130 in the aqueous humor and serum of patients with diabetic retinopathy
.
Mol Vis
2016
;
22
:
1005
1014
15.
Venkatesh
SK
,
Yin
M
,
Ehman
RL
.
Magnetic resonance elastography of liver: technique, analysis, and clinical applications
.
J Magn Reson Imaging
2013
;
37
:
544
555
16.
Hines
CD
,
Bley
TA
,
Lindstrom
MJ
,
Reeder
SB
.
Repeatability of magnetic resonance elastography for quantification of hepatic stiffness
.
J Magn Reson Imaging
2010
;
31
:
725
731
17.
Tang
A
,
Dzyubak
B
,
Yin
M
, et al
.
MR elastography in nonalcoholic fatty liver disease: inter-center and inter-analysis-method measurement reproducibility and accuracy at 3T
.
Eur Radiol
2022
;
32
:
2937
2948
18.
Kleiner
DE
,
Brunt
EM
,
Van Natta
M
, et al.;
Nonalcoholic Steatohepatitis Clinical Research Network
.
Design and validation of a histological scoring system for nonalcoholic fatty liver disease
.
Hepatology
2005
;
41
:
1313
1321
19.
Brunt
EM
,
Janney
CG
,
Di Bisceglie
AM
,
Neuschwander-Tetri
BA
,
Bacon
BR
.
Nonalcoholic steatohepatitis: a proposal for grading and staging the histological lesions
.
Am J Gastroenterol
1999
;
94
:
2467
2474
20.
Bedossa
P
,
Poitou
C
,
Veyrie
N
, et al
.
Histopathological algorithm and scoring system for evaluation of liver lesions in morbidly obese patients
.
Hepatology
2012
;
56
:
1751
1759
21.
Pantano
L
,
Agyapong
G
,
Shen
Y
, et al
.
Molecular characterization and cell type composition deconvolution of fibrosis in NAFLD
.
Sci Rep
2021
;
11
:
18045
22.
Wolf
J
,
Waetzig
GH
,
Chalaris
A
, et al
.
Different soluble forms of the interleukin-6 family signal transducer gp130 fine-tune the blockade of interleukin-6 trans-signaling
.
J Biol Chem
2016
;
291
:
16186
16196
23.
Eslam
M
,
Newsome
PN
,
Sarin
SK
, et al
.
A new definition for metabolic dysfunction-associated fatty liver disease: an international expert consensus statement
.
J Hepatol
2020
;
73
:
202
209
24.
Reference Values for Biochemical Tests - Centre hospitalier de l’Université de Montréal
.
25.
Nikolaus
S
,
Waetzig
GH
,
Butzin
S
, et al
.
Evaluation of interleukin-6 and its soluble receptor components sIL-6R and sgp130 as markers of inflammation in inflammatory bowel diseases
.
Int J Colorectal Dis
2018
;
33
:
927
936
26.
Padberg
F
,
Feneberg
W
,
Schmidt
S
, et al
.
CSF and serum levels of soluble interleukin-6 receptors (sIL-6R and sgp130), but not of interleukin-6 are altered in multiple sclerosis
.
J Neuroimmunol
1999
;
99
:
218
223
27.
Sindhu
S
,
Thomas
R
,
Shihab
P
, et al
.
Obesity is a positive modulator of IL-6R and IL-6 expression in the subcutaneous adipose tissue: significance for metabolic inflammation
.
PLoS One
2015
;
10
:
e0133494
28.
Kuo
FC
,
Huang
YH
,
Lin
FH
, et al
.
Circulating soluble IL-6 receptor concentration and visceral adipocyte size are related to insulin resistance in Taiwanese adults with morbid obesity
.
Metab Syndr Relat Disord
2017
;
15
:
187
193
29.
Watt
GP
,
De La Cerda
I
,
Pan
JJ
, et al
.
Elevated glycated hemoglobin is associated with liver fibrosis, as assessed by elastography, in a population-based study of Mexican Americans
.
Hepatol Commun
2020
;
4
:
1793
1801
30.
Bharath
LP
,
Nikolajczyk
BS
.
The intersection of metformin and inflammation
.
Am J Physiol Cell Physiol
2021
;
320
:
C873
C879
31.
Tang
A
,
Cloutier
G
,
Szeverenyi
NM
,
Sirlin
CB
.
Ultrasound elastography and MR elastography for assessing liver fibrosis: part 1, principles and techniques
.
AJR Am J Roentgenol
2015
;
205
:
22
32
32.
Costa-Silva
L
,
Ferolla
SM
,
Lima
AS
,
Vidigal
PVT
,
Ferrari
TCA
.
MR elastography is effective for the non-invasive evaluation of fibrosis and necroinflammatory activity in patients with nonalcoholic fatty liver disease
.
Eur J Radiol
2018
;
98
:
82
89
33.
Chen
J
,
Yin
M
,
Talwalkar
JA
, et al
.
Diagnostic performance of MR elastography and vibration-controlled transient elastography in the detection of hepatic fibrosis in patients with severe to morbid obesity
.
Radiology
2017
;
283
:
418
428
34.
Park
CC
,
Nguyen
P
,
Hernandez
C
, et al
.
Magnetic resonance elastography vs transient elastography in detection of fibrosis and noninvasive measurement of steatosis in patients with biopsy-proven nonalcoholic fatty liver disease
.
Gastroenterology
2017
;
152
:
598
607.e2
35.
Loomis
AK
,
Kabadi
S
,
Preiss
D
, et al
.
Body mass index and risk of nonalcoholic fatty liver disease: two electronic health record prospective studies
.
J Clin Endocrinol Metab
2016
;
101
:
945
952
36.
Lefebvre
T
,
Wartelle-Bladou
C
,
Wong
P
, et al
.
Prospective comparison of transient, point shear wave, and magnetic resonance elastography for staging liver fibrosis
.
Eur Radiol
2019
;
29
:
6477
6488
37.
Zuliani
G
,
Galvani
M
,
Maggio
M
, et al
.
Plasma soluble gp130 levels are increased in older subjects with metabolic syndrome. The role of insulin resistance
.
Atherosclerosis
2010
;
213
:
319
324
38.
Bowker
N
,
Shah
RL
,
Sharp
SJ
, et al
.
Meta-analysis investigating the role of interleukin-6 mediated inflammation in type 2 diabetes
.
EBioMedicine
2020
;
61
:
103062
39.
Skuratovskaia
D
,
Komar
A
,
Vulf
M
, et al
.
IL-6 reduces mitochondrial replication, and IL-6 receptors reduce chronic inflammation in NAFLD and type 2 diabetes
.
Int J Mol Sci
2021
;
22
:
1774
40.
Hou
X
,
Yin
S
,
Ren
R
, et al
.
Myeloid-cell-specific IL-6 signaling promotes microRNA-223-enriched exosome production to attenuate NAFLD-associated fibrosis
.
Hepatology
2021
;
74
:
116
132
41.
Targher
G
,
Byrne
CD
.
Clinical review: nonalcoholic fatty liver disease: a novel cardiometabolic risk factor for type 2 diabetes and its complications
.
J Clin Endocrinol Metab
2013
;
98
:
483
495
42.
Reeh
H
,
Rudolph
N
,
Billing
U
, et al
.
Response to IL-6 trans- and IL-6 classic signalling is determined by the ratio of the IL-6 receptor α to gp130 expression: fusing experimental insights and dynamic modelling
.
Cell Commun Signal
2019
;
17
:
46
43.
Fazel Modares
N
,
Polz
R
,
Haghighi
F
, et al
.
IL-6 trans-signaling controls liver regeneration after partial hepatectomy
.
Hepatology
2019
;
70
:
2075
2091
44.
Galun
E
,
Zeira
E
,
Pappo
O
,
Peters
M
,
Rose-John
S
.
Liver regeneration induced by a designer human IL-6/sIL-6R fusion protein reverses severe hepatocellular injury
.
FASEB J
2000
;
14
:
1979
1987
45.
Peters
M
,
Blinn
G
,
Jostock
T
, et al
.
Combined interleukin 6 and soluble interleukin 6 receptor accelerates murine liver regeneration
.
Gastroenterology
2000
;
119
:
1663
1671
46.
Bergmann
J
,
Müller
M
,
Baumann
N
, et al
.
IL-6 trans-signaling is essential for the development of hepatocellular carcinoma in mice
.
Hepatology
2017
;
65
:
89
103
47.
Rosenberg
N
,
Van Haele
M
,
Lanton
T
, et al
.
Combined hepatocellular-cholangiocarcinoma derives from liver progenitor cells and depends on senescence and IL-6 trans-signaling
.
J Hepatol
2022
;
77
:
1631
1641
48.
Kraakman
MJ
,
Kammoun
HL
,
Allen
TL
, et al
.
Blocking IL-6 trans-signaling prevents high-fat diet-induced adipose tissue macrophage recruitment but does not improve insulin resistance
.
Cell Metab
2015
;
21
:
403
416
49.
Kammoun
HL
,
Allen
TL
,
Henstridge
DC
, et al
.
Over-expressing the soluble gp130-Fc does not ameliorate methionine and choline deficient diet-induced non alcoholic steatohepatitis in mice
.
PLoS One
2017
;
12
:
e0179099
50.
Lanton
T
,
Levkovitch-Siany
O
,
Udi
S
, et al
.
Peripheral sgp130-mediated trans-signaling blockade induces obesity and insulin resistance in mice via PPARα suppression
.
24 September 2020 [preprint]. bioRxiv:2020.09.24.309716
Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. More information is available at https://www.diabetesjournals.org/journals/pages/license.