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WHAT IS ALREADY KNOWN ON THIS TOPIC Asialoglycoprotein receptor 1 (ASGR1) promotes hepatic steatosis, elevates blood lipid levels, and enhances systemic insulin resistance in high-fat diet-fed mice.WHAT THIS STUDY ADDS Soluble ASGR1 (sASGR1) levels are elevated in the serum of metabolic dysfunction-associated steatotic liver disease (MASLD) patients.sASGR1 may be an independent risk factor for the occurrence of MASLD.sASGR1 can effectively predict the occurrence of MASLD.HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY This study identified sASGR1 as a potential serum molecular biomarker for diagnosing MASLD patients.It further supports the fact that sASGR1 is associated with glycolipid metabolism and may exert its effects by regulating adiponectin.Introduction Metabolic dysfunction-associated steatotic liver disease (MASLD) is one of the most common chronic diseases globally. Disorders of lipid metabolism, especially excessive lipid accumulation (with more than 5% of hepatocytes undergoing fatty change), are well-known characteristics for MASLD, which is triggered by nutritional surplus and insulin resistance (IR). 1 2 The pathological process of MASLD encompasses metabolic dysfunction-associated hepatic steatosis, metabolic dysfunction-associated steatohepatitis (MASH), as well as related liver fibrosis and cirrhosis.3 Research indicates that MASLD promotes the occurrence of atherosclerotic cardiovascular disease (CVD), chronic kidney disease, liver decompensation, and malignant tumors such as hepatocellular carcinoma.4–6 With the continuous increase in the global number of MASLD patients7–9, MASLD has already become an increasingly serious public health challenge.10 11 Liver biopsy is the gold standard for diagnosing MASLD,12 but its invasive nature and associated risks limit its application. Although abdominal ultrasound is currently the most commonly used imaging diagnostic method, it exhibits low sensitivity and insufficient specificity for mild fatty liver.13 The quantitative technique for measuring proton density fat fraction using MRI is accurate, but its widespread clinical application has been limited due to the availability and cost of the necessary equipment. Given this situation, searching for highly sensitive novel serum biomarkers has become an important strategy for the early diagnosis and identification of MASLD.The asialoglycoprotein receptor 1 (ASGR1), a highly specific endocytic receptor on the membrane of liver cells, is primarily expressed in hepatocytes. It serves as the core functional subunit of the ASGR complex.14 In recent years, an increasing number of preclinical studies have revealed the role of ASGR1 in MASLD. The knockdown of mouse ASGR1 has been observed to decrease cholesterol and triglyceride levels in the liver, while serum lipid levels also decline significantly.15 This suggests that ASGR1 may be involved in the occurrence of MASLD by affecting lipid metabolism. It also improves systemic IR in high-fat diet mice, suggesting that ASGR1 could exacerbate hepatic IR to promote MASLD.16 Moreover, knocking down ASGR1 in mice inhibits the differentiation of monocytes into macrophages, reduces the infiltration of inflammatory cells, and decreases the release of inflammatory factors. Overall, these findings suggest that ASGR1 is possibly associated with liver inflammation.17Serum soluble ASGR1 (sASGR1) is a splicing variant of the liver ASGR1 protein, which is secreted into the bloodstream after some processing. However, its physiological functions remain unclear, and current research on sASGR1 is very limited. Existing clinical studies indicate that sASGR1 levels are elevated in the serum of patients with coronary heart disease.18 Meanwhile, no studies on sASGR1 in the MASLD population have been reported.Previous studies have identified several serum biomarkers closely associated with MASLD, such as fibroblast growth factor 21 (FGF21) and adiponectin. FGF21 is primarily secreted by the liver and adipose tissue and serves as an important metabolic regulatory factor.19–21 Clinical studies have observed that endogenous FGF21 serum concentrations can increase between ten and twenty-fold in patients with MASLD.22–24 Adiponectin, primarily secreted by adipose tissue, plays an important role in the progression of MASLD through mechanisms that regulate energy homeostasis, glucose and lipid metabolism, insulin sensitivity, as well as anti-inflammatory and antifibrotic processes.25 Research has found that circulating adiponectin levels in MASLD patients are significantly lower than in healthy individuals, and low adiponectin levels may independently predict the progression of MASLD.26 27 This study preliminarily explored the changes in sASGR1 levels in the MASLD population and their association with serum levels of FGF21 and adiponectin. These findings provide new indicators for predicting MASLD.Materials and methods Study population Based on a case-control study design, we included 148 patients (76 males and 72 females) who visited the outpatient department of the First Affiliated Hospital of University of South China from December 2021 to July 2024. We also incorporated a general population group consisting of 98 individuals (47 males and 51 females) from the health examination center of the First Affiliated Hospital of the University of South China, who were matched by age and gender.Participants were eligible for inclusion if, at the time of enrollment, they (1) were between the ages of 18 years and 75 years, (2) had complete baseline, clinical, and laboratory examination data, (3) participated in a comprehensive physical examination and collection of clinical history, including name, gender, history of alcohol abuse, smoking history, history of diabetes, history of infectious diseases, history of liver disease, history of hypertension, family history of CVD, and history of medication use, (4) conducted routine blood biochemistry tests and abdominal color Doppler ultrasound examinations, (5) voluntarily signed written informed consent forms after being informed of the purpose, nature, procedures, and potential adverse reactions of this trial.Participants were excluded if they (1) had specific diseases that can lead to fatty liver disease including viral hepatitis, drug-induced liver disease, total parenteral nutrition, Wilson’s disease, and autoimmune liver disease, (2) had severe heart, liver, kidney disease, or history of neoplastic disease, (3) were currently in the period of pregnancy or breastfeeding, and (4) used medications affecting liver metabolism or lipid metabolism, such as statins, fibrates, or corticosteroids within the past 3 months.Sample size calculation We performed sample size calculations using the Power Analysis and Sample Size software to assess the association between sASGR1 levels and MASLD. We set the bilateral α=0.05 and power=0.9. The sample size ratio of the MASLD group to the control group is 1.51:1. Based on preliminary findings, we established the mean and SD of ASGR1 levels for both groups. Sample size calculations indicated that selecting 50 MASLD patients and 33 non-MASLD patients would achieve a mean difference of µ1−µ2 =2.60–1.83=0.74, with an SD of 1.11 for the MASLD group and 1.55 for the non-MASLD group. Under this design, the power to reject the null hypothesis of equal means was 90.75%. Finally, a sample consisting of 148 MALSD patients and 98 non-MALSD patients was formed.Clinical characteristics and laboratory measurements General information was collected through standardized interviews, including gender, age, smoking habits, alcohol consumption, medical history (eg, liver disease, diabetes, hypertension, and CVDs), and recent use of medications related to glucose and lipid metabolism. Standardized measurements of physical parameters such as height, weight, and blood pressure are taken.Participants must maintain a fasting state of at least 8 hours before blood collection. They should avoid high-fat, high-sugar, and high-protein diets the day prior and refrain from alcohol consumption. Blood samples of 3–4 mL will be collected via antecubital venipuncture in the morning while the participants are still fasting in the morning. After standing at room temperature for 30 min, the blood sample should be centrifuged at 3000 rpm for 10 min at 4°C, and it should then be stored at −80°C for subsequent parameter measurements.The detection of liver function, lipid metabolism, glucose metabolism-related parameters, and inflammatory markers is achieved through a fully automated biochemical analyzer. Relevant metabolic indicator testing includes: fasting plasma glucose (FPG), fasting insulin (FIns), glycosylated hemoglobin (HbA1c), alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (GGT), total bilirubin (TBIL), direct bilirubin (DBIL), triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), high-sensitivity C reactive protein (hs-CRP) and calculated the IR index (homeostasis model assessment for IR, HOMA-IR) = FIns (uU/mL) × FPG (mmol/L) / 22.5 based on the HOMA formula. A fully automated chemiluminescence immunoassay analyzer is used to analyze serum markers for liver fibrosis and inflammation. Several indicators have been detected, which include type III procollagen (PCIII), collagen type IV (CIV), laminin (LN), hyaluronic acid (HA), tumor necrosis factor α (TNF-α), and interleukin-6 (IL-6).Assessment of MASLD All diagnoses of MASLD are based on the standards set forth in the 2024 Edition of the Guidelines for Prevention and Treatment of Metabolic-Associated (non-alcoholic) Fatty Liver Disease. The criteria are as follows: (1) no history of alcohol consumption or a weekly alcohol intake equivalent to <210 g ethanol for males, and <140 g ethanol for females; (2) exclusion of specific diseases that can cause fatty liver such as viral hepatitis, drug-induced liver disease, total parenteral nutrition, Wilson’s disease, etc; (3) abdominal ultrasound indicates diffuse enhancement with near-field echoes from the liver being stronger than those from the kidneys; unclear intrahepatic duct structures; gradually attenuated far-field echoes from the liver (at least two of these criteria must be satisfied); (4) presence of at least one metabolic CVD risk factor: body mass index (BMI) ≥24.0 kg/m², or waist circumference ≥90 cm (males), or ≥85 cm (females), or excessive body fat content/percentage; fasting blood glucose level ≥6.1 mmol/L, or postload blood glucose after 2 hours ≥7.8 mmol/L, or HbA1c ≥5.7%, or a history of type II diabetes mellitus, or steady-state index IR score ≥2.5; or fasting serum triglycerides ≥1.70 mmol/L, or serum HDL ≤1.0 mmol /L (males) and ≤1.3 mol/L (females); blood pressure ≥ to 130/85 mm Hg. 28ELISA for determining the sASGR1 concentration The serum sASGR1 concentration was measured using a sandwich ELISA kit (NBP3-8669; Novus Biologicals, Colorado, USA). The serum FGF21 concentration was measured using a sandwich ELISA kit (RE1042H; ReedBiotech, Wuhan), and the serum adiponectin concentration was determined using a sandwich ELISA kit (RE2837H; ReedBiotech, Wuhan). Each sample is measured twice to reduce random variation. The coefficient of variation both within and between plates is less than 10%, indicating that the detection has good repeatability. The minimum detection concentration of serum sASGR1 is 0.09 ng/mL (1:100 dilution). The minimum detection concentration of serum FGF-21 and adiponectin is 18.75 pg/mL (1:100 dilution).Statistical analyses Data analysis was conducted using SPSS Statistics V.28.0 software, and the graphical representation was created with GraphPad Prism V.10.0, setting p<0.05 as the statistical significance level. Due to the potential for multiple comparisons leading to type I errors, the results should be interpreted as exploratory analyses.The Kolmogorov-Smirnov test was used to assess the normality of continuous variables. Normally distributed variables are described using mean±SD, while non-normally distributed data are represented by median (IQR). The independent samples t-test was conducted for group comparisons on normally distributed continuous variables; the Mann-Whitney U test was applied for analysis of non-normally distributed variables. The categorical variables are presented using frequency and composition ratio, with the χ2 test employed to compare differences between these categorical variables. Spearman correlation analysis was used to explore the relationship between ASGR1 and other indicators. Multifactor linear regression analysis was used to identify independent influencing factors of serum sASGR1, and a binary logistic regression model was used to assess the OR of ASGR1 in relation to the occurrence of MASLD, adjusting for potential confounding factors including age, gender, liver function, lipid metabolism, and glucose metabolism indicators. Testing for mediating effects using SPSS Amos V.26.0 software, validating the model via the Bootstrap method with a sample size of 5000. The diagnostic efficacy of serum sASGR1 for MASLD was evaluated using the receiver operating characteristic (ROC) curve analysis.Result Baseline characteristics This study included a total of 246 participants. According to table 1, BMI, systolic blood pressure, and diastolic blood pressurewere greater in the MASLD group (p<0.05). The MASLD group also had significantly higher levels of serum FPG, Fins, HbA1c, HOMA-IR, TG, TC, LDL-C, ALT, AST, GGT, PCIII, HA, and sASGR1 than did the non-MASLD group (p<0.05). In addition, MASLD patients had higher levels of FGF21 and inflammatory markers such as hs-CRP, TNF-ɑ, and IL-6 in their serum (p<0.05). However, serum HDL-C and adiponectin levels significantly decreased in the MASLD group (p<0.05). The two groups of participants showed no significant differences in age, gender, bilirubin levels, and other liver fibrosis parameters.Table 1Baseline characteristics of the study participantsVariablesNon-MASLD (n=98)MASLD (n=148)P valueAge (years)46 (32–56)42 (32–57)0.927Sex (male, %)47 (47.96%)76 (51.35%)0.602BMI (kg/m²)21.40 (20.51–22.71)28.30 (24.82–29.52)<0.001SBP(mmHg)122 (110–136)130 (121–143)<0.001DBP(mmHg)73 (65–82)82 (75–89)<0.001FPG (mmol/L)4.92 (4.58-5.36)6.06 (5.20-8.93)<0.001Fins (mlU/L)6.43 (4.87-8.44)14.19 (8.66- 20.00)<0.001HbA1c (%)5.35 (5.12–5.70)6.32 (5.68–9.80)<0.001HOMA-IR1.39 (1.09–2.01)3.95 (2.71–6.90)<0.001ALT (U/L)15.20 (10.63–21.53)31.35 (22.05–47.50)<0.001AST (U/L)18.25 (14.78–22.48)23.30 (18.33–31.78)<0.001DBIL (μmol/L)4.15 (3.40–4.90)4.15 (3.40–5.28)0.402TBIL (μmol/L)9.25±2.389.88±3.380.222GGT (U/L)24.00 (16.40–36.33)35.70 (23.70–49.20)<0.001TG (mmol/L)1.20 (0.89–1.57)1.88 (1.32–2.56)<0.001TC (mmol/L)4.40±0.904.68±1.030.012LDL-C (mmol/L)2.60±0.843.03±0.90<0.001HDL-C (mmol/L)1.40 (1.19–1.71)1.11 (0.89–1.29)<0.001hs-CRP (mg/L)1.90 (0.70–3.06)2.44 (1.34–3.61)0.003HA (ng/mL)69.40 (61.75–77.10)80.70 (79.30–82.63)<0.001CIV (ng/mL)16.42 (13.50–19.23)17.44 (14.70–19.80)0.128LN (ng/mL)33.75 (31.40–37.53)36.60 (29.35–43.38)0.165PCIII (ng/mL)21.45 (19.63–23.00)28.40 (23.60–32.18)<0.001IL-6 (pg/mL)4.48 (3.85–5.06)5.08 (3.45–7.32)0.011TNF-α (pg/mL)4.58±1.8710.29±3.60<0.001FGF21 (pg/mL)1043.96 (768.23–1277.63)1290.16 (1043.11–1492.72)<0.001Adiponectin (pg/mL)1359.27±140.641047.17±185.15<0.001sASGR1 (ng/mL)1.49 (1.00–2.17)2.44 (1.91–3.17)<0.001Continuous variables are expressed as the mean±SD or median (IQR); categorical variables are presented as numbers (percentages).ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; CIV, collagen type IV; DBIL, direct bilirubin; DBP, Diastolic Blood Pressure; FGF21, fibroblast growth factor 21; FGF21, fibroblast growth factor 21; FIns, fasting insulin; FPG, fasting plasma glucose; GGT, gamma glutamyl transferase; HA, hyaluronic acid; HAblc, glycosylated hemoglobin; HDL-C, high-density lipoprotein cholesterol; HOMA-IR, homeostatic mode assessment of insulin resistance; Hs-CRP, high-sensitivity C-reactive protein; IL-6, Interleukin-6; LDL-C, low-density lipoprotein cholesterol; LN, laminin; MASLD, metabolic dysfunction-associated steatotic liver disease; PCIII, procollagen type III; sASGR1, soluble asialoglycoprotein receptor 1; SBP, Systolic Blood Pressure; TBIL, total bilirubin; TC, total cholesterol; TG, triglyceride; TNF-α, tumor necrosis factor-α.Serum sASGR1 levels in the MASLD and non-MASLD groups As shown in table 1, the serum sASGR1 level was significantly increased in the MASLD group compared with the control group (1.49 ng/mL vs 2.44 ng/mL, p<0.05). No statistically significant differences in serum sASGR1 levels were observed between males and females (figure 1A). However, subgroup analysis (figure 1B,C) showed that the serum sASGR1 levels in the MASLD group were significantly higher than those in the control group for both males and females (p<0.05). The specific distribution characteristics are detailed in figure 1.Figure 1Expression level of serum sASGR1. (A) Comparison of serum sASGR1 levels between the Control and NAFLD groups. (B) Comparison of serum sASGR1 levels between the female and male groups in NAFLD patients. (C) Comparison of male serum sASGR1 levels between the control and NAFLD groups. (D) Comparison of female serum sASGR1 levels between the control and NAFLD groups. ***p<0.001；****p<0.0001. MASLD, metabolic dysfunction-associated steatotic liver disease; NAFLD, non-alcoholic fatty liver disease; sASGR1, soluble asialoglycoprotein receptor 1.Relationships between the serum sASGR1 concentration and MASLD Next, we investigated the correlation between sASGR1 level and MASLD. Spearman analysis indicated that serum sASGR1 levels are not statistically associated with age ( r=0.036, p=0.570) or gender (r=0.015, p=0.820). As MASLD is a multifactorial chronic disease, the related clinical evaluation indicators include glucose metabolism, IR, lipid metabolism, inflammation, fibrosis, liver function, and BMI. We investigated the correlation between sASGR1 levels and these clinical parameters. According to figure 2, the sASGR1 levels were significantly positively correlated with glucose metabolism and insulin-related indicators (FPG, FIns, HOMA-IR, and HbA1c), lipid metabolic indicators (TG, TC, and LDL-C), liver function markers (ALT, AST, and GGT), fibrosis markers (PC III and HA), and inflammatory markers (TNF-α) as well as BMI (p<0.05), while exhibiting a significant negative correlation with HDL-C (p<0.05). However, serum sASGR1 levels were not significantly correlated with serum hs-CRP, IL-6, TBIL, DBIL, CIV, or LN.Figure 2The relationship between sASGR1 levels and the severity of MASLD. (A) Correlation analysis between serum sASGR1 and glucose metabolism indicators. (B) Correlation analysis between serum sASGR1 and lipid metabolism indicators. (C) Correlation analysis between serum sASGR1 and inflammation indicators. (D) Correlation analysis between serum sASGR1 and fibrosis indicators. (E) Correlation analysis of serum sASGR1 and liver function. (F) Correlation analysis of serum sASGR1 and BMI. ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; CIV, collagen type IV; FPG, fasting plasma glucose; Fins, fasting insulin; GGT, gamma glutamyl transferase; HA, hyaluronic acid; HbA1c, glycosylated hemoglobin; HDL-C, high-density lipoprotein cholesterol; HOMA-IR, homeostatic mode assessment of insulin resistance; Hs-CRP, high-sensitivity C-reactive protein; IL-6, Interleukin-6; LN, laminin; LDL-C, low-density lipoprotein cholesterol; MASLD, metabolic dysfunction-associated steatotic liver disease; PC III, procollagen type III; TG, triglyceride; sASGR1, soluble asialoglycoprotein receptor 1; TC, total cholesterol; TNF-α, Tumor necrosis factor-α.;We employed a multiple linear regression model to further explore the relationship between ASGR1 and the aforementioned clinical parameters. The independent variables were included based on the results of univariate analysis, clinical significance, sample size, and multicollinearity. Table 2 showed that ASGR1 levels were positively associated with increased LDL-C, TG, TC, GGT, and IL-6 levels (p<0.05), after adjusting for confounding factors such as BMI, FPG, HbA1c, ALT, AST, TC, HDL-C, PCIII, and TNF-α.Table 2Univariate and multivariate regression analysis of serum sASGR1VariablesULRMLRβP valueβP valueVIFSex0.0360.576Age0.0410.526BMI0.227<0.0010.0060.9462.043FPG0.1290.043−0.0880.2771.888FIns0.275<0.001HbA1c0.1770.0050.0870.2731.838HOMA-IR0.249<0.001ALT0.2100.001−0.0160.8762.883AST0.1690.0080.0680.4692.547DBIL−0.0720.26TBIL−0.0780.223TG0.287<0.0010.2380.0031.786TC0.1750.006−0.0600.4752.031LDL-C0.260<0.0010.284<0.0011.697HDL-C−0.1930.002−0.0350.6321.524CRP0.0440.488GGT0.221<0.0010.1320.0471.272HA0.0860.176CIV−0.0290.647LN0.0810.206PCIII0.1780.0050.0530.4511.420IL-60.1320.0380.1240.0481.133TNF-α0.1800.005−0.0240.7581.753FGF210.0780.224Adiponectin−0.289<0.001sASGR1 is an independent influencing factor for the occurrence of MASLD A binary logistic regression model was used to identify the role of ASGR1 in MASLD. First, the OR of serum sASGR1 levels associated with the risk of MASLD was 2.201 (95% CI 1.619 to 2.993, p<0.001), without adjusting for confounding factors.Based on the results in table 2, we further constructed several stepwise regression models to further validate ASGR1 as an independent risk factor for MASLD. Included confounding factors were determined based on clinical significance, multiple linear regression analysis, and collinearity testing. Table 3 showed that after adjusting for TG and LDL, the OR decreased to 1.533 (95% CI 1.121 to 2.096, p=0.007). And after further adjusting for IL-6 and GGT, the OR decreased to 1.383 (95% CI 1.006 to 1.901, p=0.046). In summary, it suggests that the increased risk of sASGR1 is associated with an elevated risk of MASLD.Table 3Association of sASGR1 with MASLD incidence according to the different modelsOR95% CIP valueCrude model2.201(1.619 to 2.993)<0.001Model 11.533(1.121 to 2.096)0.007Model 21.383(1.006 to 1.901)0.046The multivariate regression stepwise models are shown. Model I was adjusted for TG, TC and LDL-C, model II was adjusted for model I plus IL-6 and GGT.GGT, gamma-glutamyl transferase; IL-6, interleukin-6; LDL-C, low-density lipoprotein cholesterol; MASLD, metabolic dysfunction-associated steatotic liver disease; sASGR1, soluble asialoglycoprotein receptor 1; TC, total cholesterol; TG, triglycerides.Relationships between the serum sASGR1 and FGF21, adiponectin Existing studies have found that plasma levels of FGF21 are elevated in both rodents and humans with MASLD, and the level of FGF21 is associated with the severity of fibrosis. 29–31 In various rodent models of MASLD, FGF21 has been shown to reduce liver lipid content and reverse hepatocellular injury.32 At the same time, FGF21 analogs have shown significant efficacy in reducing hepatic lipids and fibrosis severity in clinical trials for MASLD and MASH patients.33 34 So, we hypothesize that there may be a correlation between sASGR1 and FGF21. The results showed that there was no significant correlation between the levels of sASGR1 and FGF21 (figure 3A, p>0.05), indicating that suggesting that the promotive effect of sASGR1 during the process of MASLD may be independent of FGF21.Figure 3The relationship between sASGR1 levels and the molecular markers of MASLD. (A) Correlation analysis between serum sASGR1 and FGF21. (B) Correlation analysis between serum sASGR1 and adiponectin. FGF21, fibroblast growth factor 21; MASLD, metabolic dysfunction-associated steatotic liver disease; sASGR1, soluble asialoglycoprotein receptor 1.Adiponectin has long been proven to have various beneficial effects on MASLD35 36 and is recognized as a molecular biomarker associated with MASLD.37 38 We also investigated the correlation between sASGR1 levels and adiponectin levels. The results show that the level of sASGR1 is significantly negatively correlated with adiponectin levels (figure 3B, r=−0.3989, p<0.05). Given the significant negative correlation between adiponectin and ASGR1, we further investigated whether adiponectin mediates the effect of ASGR1 on MASLD. Figure 4 revealed that adiponectin mediated 55.49% (p<0.001) of the effect on ASGR1. As a supplement, we also investigated the possibility of ASGR1 acting as a mediator of adiponectin’s effects on MASLD. However, ASGR1 mediated only 7.15% (p=0.002) of the effect on adiponectin (figure 4B). This suggests that ASGR1 may influence the occurrence and progression of MASLD by regulating adiponectin levels.Figure 4The influence path of ASGR1 or adiponectin on MASLD. (A) Adiponectin mediates the effects of ASGR1 on MASLD (B) ASGR1 mediates the effects of adiponectin on MASLD. ASGR1, asialoglycoprotein receptor 1; MASLD, metabolic dysfunction-associated steatotic liver disease.Diagnostic value of sASGR1 and traditional biomarkers for MASLD patients We used the ROC curve to evaluate the diagnostic capability of serum sASGR1 levels for MASLD. 39 40 As described in table 4, the AUC of sASGR1 is 0.761 (95% CI 0.698 to 0.824, p<0.001). The critical value for predicting the occurrence of MASLD with sASGR1 is 1.800 ng/mL, achieving a diagnostic sensitivity of 79.1% and specificity of 66.3%. Its overall diagnostic utility surpasses that of traditional lipid metabolic markers. The utility is higher than TG (AUC 0.737, 95% CI 0.68 to 0.80, p<0.001), TC (AUC 0.594, 95% CI 0.52 to 0.67, p=0.012) and LDL-C (AUC 0.639, 95% CI 0.57 to 0.71, p<0.001), and is similar to HDL-C (AUC 0.773, 95% CI 0.71 to 0.83 p <0.001). It has a similar diagnostic value to that of traditional liver function indicators, such as AST/ALT (AUC 0.829, 95% CI 0.78 to 0.88, p<0.001).Table 4ROC curve analysis for the predictive value of serum sASGR1 and traditional biomarkers in the presence of MASLDVariablesArea95% CIP valueSensitivitySpecificityLower limitUpper limitsASGR10.7610.6980.824<0.010.7910.663TG (mmol/L)0.7370.6750.799<0.0010.5470.816TC (mmol/L)0.5940.5220.6660.0120.7090.480LDL-C (mmol/L)0.6390.5690.709<0.0010.5950.633FGF21 (pg/mL)0.7200.6560.785<0.0010.6890.663ALT/AST0.8290.7760.882<0.0010.7840.816HDL-C0.7730.7140.832<0.0010.6280.786Adiponectin0.9360.9040.968<0.0010.9190.836ASGR1+ALT+AST0.8630.8130.913<0.0010.8110.847ALT, alanine aminotransferase; ASGR1, asialoglycoprotein receptor 1; AST, aspartate aminotransferase; FGF21, fibroblast growth factor 21; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; MASLD, metabolic dysfunction-associated steatotic liver disease; ROC, receiver operating characteristic; sASGR1, soluble ASGR1; TC, total cholesterol; TG, triglycerides.We continued to explore whether sASGR1 has further auxiliary diagnostic value. The results showed that the diagnostic value combining sASGR1 with AST/ALT achieved an AUC of 0.863 (95% CI 0.81 to 0.91, p<0.001), and the DeLong test indicated that this combined diagnosis was significantly superior to the individual diagnoses of either sASGR1 or AST/ALT alone (p<0.05).Discussion According to our research, the levels of sASGR1 were significantly elevated in MASLD patients compared with the control group. We also observed a significant positive correlation between ASGR1 and metabolic indicators, liver injury markers, and inflammatory factors, as well as liver fibrosis indicators. This finding is consistent with previous reports regarding the involvement of ASGR1 in regulating glucose and lipid metabolism, as well as liver pathological processes. Further analysis using multiple linear regression revealed an independent correlation between LDL-C and sASGR1 levels, which is consistent with earlier studies. 41 sASGR1 may be an independent risk factor for the occurrence of MASLD, even after adjusting for potential confounding factors. Notably, ASGR1 has a predictive effectiveness of 87% for MASLD when combined with AST and ALT. sASGR1 could therefore serve as a non-invasive diagnostic marker for MASLD.Wang et al found that after 16 weeks on a Western diet, plasma cholesterol and triglyceride levels were significantly reduced in ASGR1 gene knockout ApoE-mice.42 Xu et al also found that ASGR1 deletion regulates lipid homeostasis by upregulating insulin-induced genes and inhibiting the activation of sterol regulatory element-binding proteins.43 In addition, studies show that inhibiting ASGR1 reduces the hepatic breakdown of glycogen and gluconeogenesis induced by a high-fat diet in mice, thereby improving systemic IR.16 This study found that sASGR1 correlates with metabolic indicators including BMI, HOMA-IR, TG, TC, and LDL-C. Multiple linear regression further confirmed the potential relationship between ASGR1 and TG, TC, and LDL-C, suggesting ASGR1 may be deeply involved in hepatic lipid metabolism processes. Furthermore, since MASLD originates from abnormal lipid accumulation in the liver, ASGR1’s significant influence on lipid metabolism positions it as a promising early warning indicator for MASLD detection.In patients with MASLD, the inflammatory response of the liver is a crucial step in the progression of the disease. TNF-α, as a key pro-inflammatory cytokine, can activate the intracellular nuclear factor-kappa-B pathway.44 ASGR1 knockdown can inhibit the NF-κB/ATF5 (Activating Transcription Factor 5) pathway and reduce the production of pro-inflammatory cytokines TNF-α, IL-1β, and IL-6 in peripheral blood.17 In this study, IL-6 was found to be significantly elevated in patients with MASLD and is positively correlated with ASGR1. This provides evidence that ASGR1 may play a role in the pathological progression of MASLD by mediating chronic tissue inflammation.Liver fibrosis is a crucial stage in the progression of MASLD, where continuous hepatocyte injury activates hepatic stellate cells, causing them to differentiate into myofibroblasts that secrete large amounts of extracellular matrix, ultimately leading to the development of liver fibrosis.45 Research by Zhang et al confirmed that ASGR1 expression is downregulated in liver tissues from patients with cirrhosis and mice. This study found that liver function indicators (ALT, AST, and GGT) and liver fibrosis markers (HA and PCIII) in MASLD patients were elevated compared with the control group. Furthermore, these indicators showed a positive correlation with ASGR1. Therefore, it is reasonable to speculate that ASGR1 is involved in liver injury and its fibrotic process, which provides direction for subsequent research related to ASGR1 and MASLD.Adiponectin serves as a key regulatory link between IR and mitochondrial dysfunction.46 Previous studies have found that low adiponectin levels lead to reduced activation of Adenosine 5‘-monophosphate-activated protein kinase (AMPK) and increased acetyl-CoA carboxylase.47 Previous studies have also confirmed that inhibiting ASGR1 may enhance AMPK activation and reduce lipid accumulation.48 We found that sASGR1 is significantly and negatively correlated with adiponectin. Moreover, the mediation analysis results indicate that adiponectin exerts a substantial mediating effect on ASGR1 influencing the occurrence of MALSD. Therefore, we hypothesize that ASGR1 may indirectly suppress adiponectin expression by inhibiting AMPK activity, thereby promoting MALSD. This finding provides new perspectives for elucidating the molecular mechanism by which ASGR1 promotes the progression of MASLD.The study has several limitations. First, this is a cross-sectional study, and the causal relationship between sASGR1 concentration, the incidence of MASLD, and its biomarker levels cannot be determined. Second, a relatively small and limited sample size may reduce the generalizability of the conclusions, although the results of our sample size calculation indicate that our sample size is appropriate for the main objectives of the study. These findings need to be confirmed in studies with larger and more diverse samples. Third, the lack of severity grading for MASLD cases hinders a more precise analysis of the relationship between sASGR1 levels and the degree of hepatic steatosis.Conclusions Our study found that serum sASGR1 levels were elevated in patients with MASLD and correlated with indicators of glycometabolism, hepatic inflammation, and fibrosis. After adjusting for age, sex, and various relevant clinical parameters, sASGR1 emerged as an independent risk factor for MASLD development. This research demonstrated a significant negative correlation between sASGR1 and adiponectin levels, leading us to hypothesize that sASGR1 may participate in MASLD progression through the adiponectin pathway. Notably, the combination of sASGR1 and ALT/AST levels demonstrates excellent predictive utility for MASLD.