Skip to main content
Download PDF

Gender difference in the association between serum uric acid and metabolic dysfunction-associated steatotic liver disease in patients with newly diagnosed type 2 diabetes

BMC Gastroenterology volume 25, Article number: 322 (2025) Cite this article

Abstract

Purpose

To investigate the relationship between serum uric acid (SUA) levels and metabolic dysfunction-associated steatotic liver disease (MASLD) in newly diagnosed type 2 diabetic patients.

Methods

We performed this retrospective research among 1087 inpatients with new-onset type 2 diabetes millitus (T2DM). Data were analyzed according to gender. Then, the populations were stratified according to their body mass index (BMI) levels in men and women, respectively. The physical and biochemical indicators were measured and recorded. The relationship between SUA and MASLD was estimated using logistic regression analysis, and the unadjusted and adjusted odds ratios (ORs) were calculated.

Results

After adjusting for age, BMI, and other components of the metabolic syndrome, SUA was independently associated with MASLD only in men, but not in women. In addition, for men, the SUA levels were independently associated with MASLD in both non-overweight/obesity and overweight/obesity group. However, for women, the SUA levels were independently related to MASLD in non-overweight/obesity group. There was no association between SUA and MASLD in women with overweight/obesity.

Conclusion

In newly diagnosed type 2 diabetic patients, elevated SUA is an independent predictor for the risk of MASLD in males. In females, the relationship between SUA and MASLD may depend on BMI, with significance only in non-overweight/obese individuals.

Peer Review reports

Introduction

Nonalcoholic fatty liver disease (NAFLD) is characterized by abnormal lipid deposition in hepatic cells [1]. It is an exclusion diagnosis after excluding excessive drinking, drugs, and other causes of chronic liver disease, such as viral hepatitis [1]. Recently, the more inclusive term metabolic dysfunction-associated steatotic liver disease (MASLD) was recommended to replace the term NAFLD [2]. Compared with the NAFLD definition, MASLD places more emphasis on the positive role of metabolic dysregulation, regardless of alcohol intake and other liver diseases [3]. MASLD represents the hepatic manifestation of a multisystem metabolic disease, encompassing a wide spectrum of hepatic injuries, from simple steatosis to nonalcoholic steatohepatitis, liver fibrosis, cirrhosis, and even hepatocellular carcinoma [4]. MASLD can also elevate the risk of extrahepatic diseases, such as chronic kidney diseases and cardiovascular disease [5, 6]. In recent years, MASLD has become the most common cause of chronic liver disease, affecting more than one-third of the global population [7] and 29%−46% of the Chinese population [8]. MASLD aggravates the medical and economic burden worldwide and has become an important public health issue.

A strong bidirectional relationship between MASLD and T2DM has been demonstrated by several studies [9, 10]. On the one hand, T2DM is one of the main risk factors for MASLD [8]. The global prevalence of MASLD in people with T2DM reaches 60–75%, which is significantly higher than that in those without T2DM [11]. Patients with T2DM are more likely to develop advanced forms of MASLD including metabolic dysfunction-associated steatohepatitis (MASH), fibrosis, cirrhosis, and hepatocellular carcinoma [12, 13]. On the other hand, MASLD increases not only the risk of developing T2DM, but also the risks of diabetic complications such as cardiovascular diseases, diabetic retinopathy and diabetic nephropathy, compared to those without MASLD [14,15,16]. Therefore, early diagnosis and identification of risk factors for MASLD in type 2 diabetic patients are of great importance.

Serum uric acid (SUA) is the terminal product of endogenous and dietary purine metabolism. Elevated SUA levels have been reported to reflect high insulin resistance and are associated with the components of metabolic syndrome, including obesity, type 2 diabetes, abnormal lipid metabolism, and hypertension [17, 18]. Numerous studies have shown that SUA levels are significantly higher in NAFLD patients than in controls and are positively associated with NAFLD prevalence, even after adjusting for metabolic syndrome [19, 20]. Cohort studies have also found that higher baseline SUA levels significantly increase the risk of new-onset NAFLD, suggesting that SUA may be an independent risk factor for NAFLD development [21, 22]. Additionally, SUA concentrations have been demonstrated to correlate independently with the severity and long-term mortality of NAFLD [23, 24]. However, inconsistent results about the association between SUA and NAFLD have also been reported. The relationship between SUA and NAFLD appears to differ by sex, with some studies finding that the association is stronger in males than in females [25], whereas others show a stronger link in females [26].

Given the distinct diagnostic criteria between MASLD and NAFLD, the SUA-MASLD relationship has gained attention to assess whether uric acid can serve as a potential sixth cardiometabolic standard for defining MASLD [27]. Elevated SUA levels and SUA trajectories have been shown to be independently associated with the development of MASLD [28, 29]. Yang et al. [30] conducted cross-sectional and longitudinal studies, revealing a bidirectional relationship between hyperuricemia and MASLD, which suggests that these two factors form a vicious cycle that exacerbates metabolic deterioration. However, one study found that SUA levels were not an independent predictive marker for MASLD development in participants with a BMI > 25 kg/m2 [31]. Despite these findings, it remains unclear whether there is an independent association between SUA and MASLD in males or females with T2DM. Therefore, we explored the link between SUA and MASLD in patients with T2DM by gender.

Materials and methods

Research design and participants

A retrospective analysis was performed on patients with T2DM hospitalized in the Endocrine Department of Qilu Hospital of Shandong University Dezhou Hospital between 2013 and 2023. The inclusion criteria were newly diagnosed T2DM (defined as a recent diagnosis without prior pharmacological treatment, including but not limited to metformin, sulfonylureas, alpha-glucosidase inhibitors, or insulin). The patients had not been treated with drugs affecting SUA metabolism (such as febuxostat, benbromarone, diuretics, aspirin, cytotoxic drugs, captopril, pyrazinamide, ethambutol, beta blocker, losartan, irbesartan, nifedipine, fenofibrate, atorvastatin etc.) before the SUA measurement. The exclusion criteria were 1) type 1 diabetes, gestational diabetes, transient hyperglycemia or stress hyperglycemia; 2) acute complications of diabetes such as ketoacidosis and hyperosmolar coma; 3) trauma, acute infectious diseases, or serious heart, liver or kidney injuries. A total of 1087 participants were evaluated in the final analysis.

The diagnosis of type 2 diabetes was primarily based on comprehensive judgment of the patient's phenotypic characteristics according to previous study [32]: 1) the patients met the criteria for diabetes (including a random plasma glucose concentration ≥ 11.1 mmol/L, a fasting plasma glucose concentration ≥ 7.0 mmol/L or a 2-h plasma glucose (2-h PG) concentration ≥ 11.1 mmol/L following a 75 g oral glucose tolerance test; 2) selected patients were over 16 years of age, without a tendency for ketoacidosis, without absolute insulin deficiency, without special medication histories (such as glucocorticoids) and without a family history of diabetes in three generations or more; they also did not exhibit specific body types or appearances (such as moon face, buffalo hump, short stature, acromegaly, lipodystrophy, etc.); all patients underwent testing for the diabetes associated autoantibodies including antiglutamic acid decarboxylase autoantibodies (GADA), insulin autoantibodies (IAA) and islet cell antibodies (ICA), with negative results. 3) patients with unclear subtype diagnosis requiring further observation were excluded.

MASLD was diagnosed based on imaging evidence of hepatic steatosis in patients who were overweight/obese, had T2DM, or exhibited at least two metabolic risk abnormalities [33]. The subjects of our research were patients with T2DM. Thus, MASLD could be diagnosed in adults with hepatic steatosis detected by imaging techniques, blood biomarkers, or liver histology. Liver ultrasonography examination remains the primary technique to diagnose hepatic steatosis [34].

The ultrasound diagnostic criteria of hepatic steatosis were 1) near-field diffuse punctate hyperecho in the liver region, stronger than the spleen and kidney; 2) the far-field echo gradually decayed and the light spots were sparse; 3) the intrahepatic duct structure was not clearly displayed; 4) the liver was mildly to moderately enlarged, and the edges were round and blunt. The presence of item #1 plus at least one among items #2, #3, and #4 was considered fatty liver [35].

Physical and laboratory examinations

The data including age, sex, and medications were carefully recorded. The physical indexes such as systolic blood pressure (SBP), diastolic blood pressure (DBP), height, and weight were measured using standard methods. Overnight intravenous blood (more than 8 h of fasting) was obtained to detect serology variables. The parameters routinely included alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (γ-GGT), triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), fasting blood glucose (FBG), SUA, creatinine (Cr), and blood urea nitrogen (BUN), which were measured using a biochemical autoanalyzer (Type 7600, Hitachi, Tokyo, Japan). A liver ultrasound was conducted by a trained technician in the ultrasound department. The BMI was obtained by dividing weight (kg) by height squared (m2).

Statistical analysis

Data were generally analyzed by sex. The patients were stratified according to the median of SUA levels in men and women respectively (low SUA group: SUA < 335 µmol/L for men and SUA < 280 µmol/L for women; high SUA group: SUA ≥ 335 µmol/L for men and SUA ≥ 280 µmol/L for women). All data management and statistical analyses were conducted with SPSS 21.0 (IBM, Armonk, NY, USA). The quantitative data were presented as means ± standard deviations or medians (quartile ranges). Qualitative data were reported as percentages (%). Skewness-kurtosis tests were conducted to evaluate the normality of the continuous variables, and non-normally distributed data were logarithmically transformed before analysis. Differences between groups were compared using independent sample T test for continuous variables and the chi-square test for the categorical variables. Logistic regression analysis was used to evaluate the association of MASLD with SUA, and unadjusted odds ratio (OR), as well as multivariable-adjusted OR, were calculated. Then, the males and females were divided into the non-overweight/obesity group (BMI < 25 kg/m2) and the overweight/obesity group (BMI ≥ 25 kg/m2), respectively. Chi-square test and logistic regression analysis were performed to assess the relationship between SUA and MASLD in each group. P < 0.05 (Two-sided) was recognized to indicate statistical significance.

Results

General characteristics of the patients

The physical and biochemical indicators of the patients by sex are presented in Table 1. There were 1087 patients diagnosed with T2DM, including 656 males and 431 females. In males, the patients in high SUA group had increased levels of BMI, SBP, DBP, ALT, AST, γ-GGT, TC, TG, LDL, Cr and reduced levels of age compared with those in low SUA group, while in females, the individuals in high SUA group had increased levels of BMI, SBP, DBP, ALT, AST, γ-GGT, TC, TG, Cr and reduced levels of age than those in low SUA group (Table 1). In addition, the prevalence of MASLD was significantly increased in the high SUA group as compared with the low SUA group, for both men and women (Table 1).

Table 1 Clinical and biochemical characteristics of study subjects and the differences of factors between patients with high and low SUA levels by gender
Full size table

Relationship between SUA and risk of MASLD by sex

SUA was observed to be positively associated with the risk of MASLD with an unadjusted odds ratio (OR) of 1.017 (95% CI: 1.013–1.02, p < 0.001) for males (Table 2) and of 1.006 (95% CI: 1.003–1.009, p < 0.001) for females (Table 2) in the univariable logistic regression models. A multivariable regression analysis was further conducted to evaluate the independent association between SUA and MASLD after adjusting for confounding variables and showed that in males, after adjusting for age, SBP, DBP, ALT, AST, γ-GGT, FBG, TC, TG, LDL, HDL, BUN, and Cr, the OR of SUA for MASLD was 1.012 (95% CI: 1.008–1.016, p < 0.001) (Table 2), and after further adjusting for BMI, SUA was still significantly associated with an enhanced risk of MASLD with an OR of 1.011 (95% CI: 1.007–1.015, p < 0.001) (Table 2). In females, after adjustment for age, SBP, DBP, ALT, AST, γ-GGT, FBG, TC, TG, LDL, HDL, BUN, and Cr, the OR of SUA for MASLD was 1.004 (95% CI: 1.001–1.008, p = 0.024) (Table 2). However, after adding BMI to the regression equation, SUA had no relevance to the risk of MASLD (OR: 1.003, 95% CI: 0.999–1.007, p = 0.123) (Table 2).

Table 2 Logistic regression analysis of the correlation between SUA and MASLD by gender
Full size table

Association between SUA and MASLD stratified by BMI levels

For males, the prevalence of MASLD was increased from the low SUA group to the high SUA group in both populations with overweight/obesity and non-overweight/obesity (Table 3). SUA levels were positively correlated with MASLD, and the association still existed after adjustment for confounding elements, including age, BMI, SBP, DBP, ALT, AST, γ-GGT, FBG, TC, TG, LDL, HDL, BUN, and Cr by logistic regression analysis in both non-overweight/obesity group and overweight/obesity group. The unadjusted and adjusted ORs were 1.012 (95% CI: 1.007–1.018, p < 0.001) and 1.011 (95% CI: 1.004–1.016, p = 0.002) in non-overweight/obesity group, and were 1.017 (95% CI: 1.012–1.022, p < 0.001) and 1.013 (95% CI: 1.006–1.019, p < 0.001) in overweight/obesity group respectively (Table 4, Fig. 1).

Table 3 Differences of the prevalence rate of MASLD between high and low SUA groups based on stratified analysis according to BMI levels by gender
Full size table
Table 4 Logistic regression analysis of the correlation between SUA and MASLD based on stratified analysis according to BMI levels by gender
Full size table
Fig. 1
figure 1

Forest plot of the logistic regression analysis of the correlation between SUA and MASLD based on stratified analysis according to BMI levels in males. (A) Non-overweight/obesity group (BMI < 25 kg/m2); (B) Overweight/obesity group (BMI ≥ 25 kg/m2). Model 1: unadjusted analyses; Model 2: adjustment for BMI, age, SBP, DBP, ALT, AST, γ-GGT, FBG, TC, TG, LDL, HDL, SUN and Cr

Full size image

For females, the prevalence of MASLD was elevated in the high SUA group as compared with the low SUA group in patients with non-overweight/obesity (Table 3). However, in the overweight/obesity group, there was no significant difference in MASLD prevalence between high and low SUA group (Table 3). SUA levels were positively correlated with the MASLD, and the association still existed after adjustment for confounding elements, including age, BMI, SBP, DBP, ALT, AST, γ-GGT, FBG, TC, TG, LDL, HDL, BUN, and Cr by logistic regression analysis in the non-overweight/obesity group. The unadjusted OR was 1.011 (95% CI: 1.005–1.016, p < 0.001), and the adjusted OR was 1.009 (95% CI: 1.002–1.016, p = 0.015) (Table 4, Fig. 2). However, no relationship between SUA and MASLD was observed in the overweight/obesity group. The unadjusted OR was 0.998 (95% CI: 0.994–1.002, p = 0.248), and the adjusted OR was 0.999 (95% CI: 0.994–1.004, p = 0.792) (Table 4, Fig. 2).

Fig. 2
figure 2

Forest plot of the logistic regression analysis of the correlation between SUA and MASLD based on stratified analysis according to BMI levels in females. (A) Non-overweight/obesity group (BMI < 25 kg/m2); (B) Overweight/obesity group (BMI ≥ 25 kg/m2). Model 1: unadjusted analyses; Model 2: adjustment for BMI, age, SBP, DBP, ALT, AST, γ-GGT, FBG, TC, TG, LDL, HDL, SUN and Cr

Full size image

Discussion

An important finding of this study of subjects with newly diagnosed T2DM was that SUA was independently associated with the prevalence of MASLD only in men, not in women. Moreover, we discovered that the relationship between SUA and MASLD was significantly modified by BMI in the female patients with T2DM, and SUA was positively associated with MASLD only in non-overweight/obese female patients. To our knowledge, this is the first report of the gender specific association between SUA and MASLD in patients with newly diagnosed T2DM.

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously named non-alcoholic fatty liver disease (NAFLD), is a systemic metabolic disorder attracting increasing attention [36]. MASLD affects 30% of the adult population and the prevalence of MASLD increases yearly [37]. Hepatic steatohepatitis and fibrosis are the more severe forms of MASLD and may progress to cirrhosis and even hepatocellular carcinoma [38]. Those pathological manifestations significantly increase the risk of liver-related mortality, with the risk increasing exponentially with fibrosis stage [39]. MASLD is an independent risk factor for atherosclerotic cardiovascular disease (CVD), meanwhile CVD is the leading cause of death in patients with MASLD [40]. The overlapping of MASLD and T2DM, another important metabolic disease, has been noticed by rising evidencesss [41]. A recent meta-analysis indicated that in the eastern and western countries, the estimated global prevalence of MASLD in subjects with T2DM was 58.84% and 72.65%, respectively [42]. Undoubtedly, T2DM and MASLD can affect each other due to shared pathogenic mechanisms. The co-existence of the two diseases increases the risk of liver-related adverse outcomes [43], imposes serious glucose metabolic disorders and insulin resistance [16]. MASLD was also confirmed to induce the occurrence of macrovascular and microvascular complications in type 2 diabetic patients [15]. There is a growing need for a cost-effective laboratory measurement for predicting MASLD in patients with T2DM.

The present study found that among patients with newly diagnosed T2DM, those with higher SUA levels had increased levels of BMI, SBP, DBP, TC, TG, LDL, Cr, ALT, AST and γ-GGT than those with lower SUA levels. Hyperuricemia is an important element of metabolic syndrome which has been confirmed to be associated with various metabolic diseases [44]. We confirmed that elevated SUA levels represented more serious metabolic disorders and higher liver enzyme levels which were also present in patients with MASLD [16]. Our study further showed that SUA was positively associated with the prevalence of MASLD in men and women, suggesting that MASLD was more likely to be present in individuals with increased SUA levels than in those with lower SUA. However, we indicated that after adjustment for potential confounding parameters such as age, BMI, blood pressure, glucose, lipids, liver enzymes, BUN, and Cr, SUA was positively associated with the risk of MASLD only in males. There were no independent associations between SUA and MASLD in females. Our research suggested for the first time that the relationship between SUA and MASLD in patients with newly diagnosed T2DM was sex-specific. SUA can be considered an independent risk factor for MASLD only in men. Furthermore, we found that, in females, SUA was positively correlated with the risk of MASLD independent of other metabolic factors in subjects with non-overweight/obesity. There were no associations between SUA and MASLD in females with overweight/obesity. These results indicated that the correlation between SUA and MASLD in women with T2DM might rely on BMI. This hypothesis has also not been suggested by previous studies.

Several mechanisms have been proposed to explain how elevated SUA levels increase MASLD risk. First, SUA induces insulin resistance, enhancing hepatic lipogenesis [45]. Second, SUA triggers mitochondrial oxidative stress, inhibiting citric acid metabolism, and further upregulating adipogenic genes [46]. Third, SUA promotes hepatocyte triglyceride accumulation by increasing endoplasmic reticulum (ER) stress via sterol regulatory element-binding protein-1 (SREBP-1c) activation [47]. Fourth, elevated SUA stimulates the activity of NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome, which accelerates de novo lipogenesis [48]. Finally, excessive uric acid directly causes hepatic steatosis by activating ROS/JNK/AP-1 signaling and suppressing AMP-activated protein kinase (AMPK) activity [49, 50]. Notably, while these mechanisms explain SUA-mediated hepatic fat accumulation, their potential sex-specific variations remain unexplored. We hypothesize that the SUA-MASLD association in women may be modulated by sex hormones. Estrogen reduces SUA levels in women by inhibiting the production of uric acid and promoting its excretion [51]. Additionally, estrogen is a well-known protective factor of MASLD. It can activate hepatic estrogen receptors, inhibiting TEA domain transcription factor 1 (TEAD1) and activating AMPK signaling to reduce hepatocyte lipid content and promote fatty acid oxidation [52, 53]. Estrogen can also attenuate liver X receptor (LXR) induced SREBP-1 expression, decreasing hepatic lipogenesis and triglyceride accumulation [54]. Conversely, excess androgens in women exacerbates hepatic insulin resistance by downregulating insulin-stimulated hepatic Akt phosphorylation [55], which can elevate both SUA levels and the risk of hepatic steatosis [56]. Overweight/obese women often exhibit imbalances of sex hormones, characterized by increased androgen and reduced estrogen levels, due to altered hormone secretion, metabolism, transport, and action [57]. These changes contribute to visceral adiposity and metabolic derangements, including hyperuricemia and MASLD [58], which may underlie the BMI-dependent SUA-MASLD association observed in women. As sex hormone levels were not measured in our study, this hypothesis requires validation. Future research should investigate molecular pathways underlying sex-specific SUA-MASLD associations.

This study highlights the clinical importance of sex- and BMI-stratified approaches for SUA monitoring in T2DM management. For male patients, routine SUA assessment could facilitate earlier identification of MASLD risk. Proactive screening for MASLD when SUA levels exceed population-specific cutoffs (e.g., median values)—even before hyperuricemia develops—may improve clinical outcomes. Implementing BMI-specific SUA thresholds (overweight/obese vs. non-obese) could further enhance MASLD detection accuracy. For female T2DM patients, SUA can serve as a cost-effective screening marker for MASLD in non-overweight/obese subjects. Establishing appropriate SUA cutoffs, such as the median levels, would be clinical valuable for identifying MASLD in this population. However, in overweight/obese subjects with T2DM, SUA appears unsuitable as an indicator for assessing MASLD.

There are several limitations in this study. First, it was a cross-sectional study conducted in a single center. Therefore, we could not determine the causal relationship between SUA and MASLD, and the single center design may affect the generalizability of our findings. In future studies, we plan to conduct prospective cohort studies in both male and female populations. This longitudinal approach will enable us to better establish the causal relationship between SUA and MASLD, and systematically investigate the dynamic changes of gender differences in this association over time. Additionally, future studies should adopt a multi-center design, incorporating diverse populations, to ensure broader sample representativeness and enhance the generalizability of the findings regarding SUA-MASLD association. Second, we relied solely on ultrasonography for the diagnosis of MASLD. Ultrasound has inherent limitations in detecting mild steatosis (e.g., < 20% hepatic fat) and distinguishing between simple steatosis, steatohepatitis, and fibrosis. As a consequence, it becomes difficult to assess the association between SUA and lower degrees of steatosis, as well as the association between SUA and the liver steatosis progression. Despite these limitations, ultrasonography remains the first-line screening modality for hepatic steatosis recommended by major guidelines in clinical practice [59]. It has high sensitivity (84.8%) and specificity (93.6%) for detecting moderate-to-severe steatosis (≥ 20% fat), and is feasible, cost-effective, and safe in a large-scale cohort [60]. Thus, ultrasound is widely used in clinical studies and provides valuable insights into MASLD prevalence and risk factors [61,62,63,64]. We recognize that advanced techniques like transient elastography, MRI proton density fat fraction (PDFF), and liver biopsy offer higher accuracy, and we plan to incorporate them in future follow-up studies to enhance diagnostic accuracy and validate our findings. Third, due to the retrospective design of our study, we were unable to collect standardized data on some important confounders such as diet, physical activity, waist circumference, insulin resistance, sex hormones, alcohol intake and menopausal status. These factors are known to be closely associated with both SUA and MASLD. Future studies should incorporate a more comprehensive adjustment for additional confounders, including waist circumference, insulin resistance indices (e.g., HOMA-IR), sex hormone levels (e.g., testosterone and estradiol), lifestyle factors (e.g., diet, physical activity, and alcohol consumption), and menstrual status parameters, to better assess the SUA-MASLD association while minimizing residual confounding. Finally, as most patients had not sought medical care for high blood glucose levels prior to diagnosis, we co+uld not determine the exact duration of hyperglycemia, which may affect the development of hepatic steatosis. Future studies should aim to collect this information to better understand its impact on the relationship between uric acid and fatty liver.

Conclusion

This study demonstrated that in patients with newly diagnosed T2DM, the relationship between SUA and MASLD was sex-specific. SUA might serve as an independent biomarker of MASLD only in male patients. In females, BMI might be a crucial factor influencing the relationship between SUA and MASLD, and this relationship might depend upon non-overweight/obesity.

Data availability

The datasets generated and/or analysed during the current study are not publicly available but are available from the corresponding author on reasonable request.

Abbreviations

SUA:

Serum uric acid

MASLD:

Metabolic dysfunction-associated steatotic liver disease

NAFLD:

Nonalcoholic fatty liver disease

T2DM:

Type 2 diabetes mellitus

BMI:

Body mass index

SBP:

Systolic blood pressure

DBP:

Diastolic blood pressure

ALT:

Alanine aminotransferase

AST:

Aspartate aminotransferase

γ-GGT:

γ-Glutaryl transferase

TC:

Total cholesterol

TG:

Triglycerides

HDL:

High-density lipoprotein cholesterol

LDL:

Low-density lipoprotein cholesterol

FBG:

Fasting blood glucose

Cr:

Creatinine

BUN:

Blood urea nitrogen

References

  1. Review T, LaBrecque DR, Abbas Z, et al. World Gastroenterology Organisation global guidelines: Nonalcoholic fatty liver disease and nonalcoholic steatohepatitis. J Clin Gastroenterol. 2014;48:467–73.

    Article  Google Scholar 

  2. 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(1):202–9.

    Article  PubMed  Google Scholar 

  3. Li Y, Yang P, Ye J, et al. Updated mechanisms of MASLD pathogenesis. Lipids Health Dis. 2024;23(1):117.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Eslam M, Sarin SK, Wong VW, et al. The Asian Pacifc Association for the Study of the Liver clinical practice guidelines for the diagnosis and management of metabolic associated fatty liver disease. Hepatol Int. 2020;14(6):889–919.

    Article  PubMed  Google Scholar 

  5. Wang TY, Wang RF, Bu ZY, et al. Association of metabolic dysfunction-associated fatty liver disease with kidney disease. Nat Rev Nephrol. 2022;18(4):259–68.

    Article  PubMed  Google Scholar 

  6. Lee H, Lee YH, Kim SU, et al. Metabolic Dysfunction-Associated Fatty Liver Disease and Incident Cardiovascular Disease Risk: A Nationwide Cohort Study. Clin Gastroenterol Hepatol. 2021;19(10):2138–47.

    Article  PubMed  Google Scholar 

  7. Chan KE, Koh TJL, Tang ASP, et al. Global Prevalence and Clinical Charac teristics of Metabolic-associated Fatty Liver Disease: A Meta-Analysis and Systematic Review of 10739607 Individuals. J Clin Endocrinol Metab. 2022;107(9):2691–700.

    Article  PubMed  Google Scholar 

  8. Fan J, Luo S, Ye Y, et al. Prevalence and risk factors of metabolic associated fatty liver disease in the contemporary South China population. Nutr Metab (Lond). 2021;18(1):82.

    Article  CAS  PubMed  Google Scholar 

  9. Lonardo A, Lugari S, Ballestri S, et al. A round trip from nonalcoholic fatty liver disease to diabetes: molecular targets to the rescue? Acta Diabetol. 2019;56:385–96.

    Article  PubMed  Google Scholar 

  10. Targher G, Corey KE, Byrne CD, et al. The complex link between NAFLD and type 2 diabetes mellitus - mechanisms and treatments. Nat Rev Gastroenterol Hepatol. 2021;18:599–612.

    Article  PubMed  Google Scholar 

  11. Ciardullo S, Vergani M, Perseghin G. Nonalcoholic Fatty Liver Disease in Patients with Type 2 Diabetes: Screening, Diagnosis, and Treatment. J Clin Med. 2023;12(17):5597.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Zhang X, Yip TC, Tse YK, et al. Duration of type 2 diabetes and liver-related events in nonalcoholic fatty liver disease: A landmark analysis. Hepatology. 2023;78(6):1816–27.

    Article  PubMed  Google Scholar 

  13. Lomonaco R, Godinez Leiva E, Bril F, et al. Advanced Liver Fibrosis Is Common in Patients With Type 2 Diabetes Followed in the Outpatient Setting: The Need for Systematic Screening. Diabetes Care. 2021;44(2):399–406.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Mantovani A, Petracca G, Beatrice G, et al. Non-alcoholic fatty liver disease and risk of incident diabetes mellitus: an updated meta-analysis of 501022 adult individuals. Gut. 2021;70(5):962–9.

    Article  CAS  PubMed  Google Scholar 

  15. Mantovani A, Dalbeni A, Beatrice G, et al. Non-Alcoholic Fatty Liver Disease and Risk of Macro- and Microvascular Complications in Patients with Type 2 Diabetes. J Clin Med. 2022;11(4):968.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Targher G, Bertolini L, Rodella S, et al. Nonalcoholic fatty liver disease is independently associated with an increased incidence of cardiovascular events in type 2 diabetic patients. Diabetes Care. 2007;30:2119–21.

    Article  CAS  PubMed  Google Scholar 

  17. Borghi C, Rodriguez-Artalejo F, De Backer G, et al. Serum uric acid levels are associated with cardiovascular risk score: A post hoc analysis of the EURIKA study. Int J Cardiol. 2018;253:167–73.

    Article  PubMed  Google Scholar 

  18. Buzas R, Tautu OF, Dorobantu M, et al. Serum uric acid and arterial hypertension-Data from Sephar III survey. PLoS ONE. 2018;13: e0199865.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Liu CQ, He CM, Chen N, et al. Serum uric acid is independently and linearly associated with risk of nonalcoholic fatty liver disease in obese Chinese adults. Sci Rep. 2016;6:38605.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Zheng X, Gong L, Luo R, et al. Serum uric acid and non-alcoholic fatty liver disease in non-obesity Chinese adults. Lipids Health Dis. 2017;16(1):202.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Wei F, Li J, Chen C, et al. Higher Serum Uric Acid Level Predicts Nonalcoholic Fatty Liver Disease: A 4-Year Prospective Cohort Study. Front Endocrinol (Lausanne). 2020;11:179.

    Article  PubMed  Google Scholar 

  22. Jensen T, Niwa K, Hisatome I, et al. Increased Serum Uric Acid over five years is a Risk Factor for Developing Fatty Liver. Sci Rep. 2018;8(1):11735.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Petta S, Cammà C, Cabibi D, Di Marco V, Craxì A. Hyperuricemia is associated with histological liver damage in patients with non-alcoholic fatty liver disease. Aliment Pharmacol Ther. 2011;34(7):757–66.

    Article  CAS  PubMed  Google Scholar 

  24. Yang S, Ye Z, Liu M, et al. Association of serum uric acid with all-cause and cardiovascular mortality among adults with nonalcoholic fatty liver disease. Clin Endocrinol (Oxf). 2023;98(1):49–58.

    Article  CAS  PubMed  Google Scholar 

  25. Yu XL, Shu L, Shen XM, et al. Gender difference on the relationship between hyperuricemia and nonalcoholic fatty liver disease among Chinese: An observational study. Medicine (Baltimore). 2017;96(39): e8164.

    Article  PubMed  Google Scholar 

  26. Wu SJ, Zhu GQ, Ye BZ, et al. Association between sex-specific serum uric acid and non-alcoholic fatty liver disease in Chinese adults: a large population-based study. Medicine (Baltimore). 2015;94(17): e802.

    Article  CAS  PubMed  Google Scholar 

  27. He L, Qiu K, Zheng W, et al. Uric acid may serve as the sixth cardiometabolic criterion for defining MASLD. J Hepatol. 2024;80(4):e152–3.

    Article  CAS  PubMed  Google Scholar 

  28. Liu Z, Wang Q, Huang H, Wang X, Xu C. Association between serum uric acid levels and long-term mortality of metabolic dysfunction-associated fatty liver disease: a nationwide cohort study. Diabetol Metab Syndr. 2023;15(1):27.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Shi D, Tan Q, Zhang Y, et al. Serum uric acid trajectories and risk of metabolic dysfunction-associated steatotic liver disease in China: a 2019–2021 cohort health survey. BMC Public Health. 2025;25(1):653.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Yang C, He Q, Chen Z, et al. A Bidirectional Relationship Between Hyperuricemia and Metabolic Dysfunction-Associated Fatty Liver Disease. Front Endocrinol (Lausanne). 2022;13: 821689.

    Article  PubMed  Google Scholar 

  31. Fukuda T, Akihisa T, Okamoto T, et al. Association of uric acid levels with the development of metabolic dysfunction-associated and metabolic and alcohol-related/associated steatotic liver disease: a study on Japanese participants undergoing health checkups. Endocr J. Published online February 26, 2025.

  32. Ahmad E, Lim S, Lamptey R, et al. Type 2 diabetes. Lancet. 2022;400:1803–20.

    Article  PubMed  Google Scholar 

  33. Chan WK, Chuah KH, Rajaram RB, et al. Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD): A State-of-the-Art Review. J Obes Metab Syndr. 2023;32(3):197–213.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Chan WK, Petta S, Noureddin M, et al. Diagnosis and non-invasive assessment of MASLD in type 2 diabetes and obesity. Aliment Pharmacol Ther. 2024;59(Suppl 1):S23–40.

    PubMed  Google Scholar 

  35. Fan JG, Wei L, Zhuang H, Workshop N, on Fatty L, Alcoholic Liver Disease CSoHCMA, Fatty Liver Disease Expert Committee CMDA. Guidelines of prevention and treatment of nonalcoholic fatty liver disease,. China). J Dig Dis. 2018;2019(20):163–73.

    Google Scholar 

  36. Targher G, Byrne CD, Tilg H. MASLD: a systemic metabolic disorder with cardiovascular and malignant complications. Gut. 2024;73(4):691–702.

    CAS  PubMed  Google Scholar 

  37. Miao L, Targher G, Byrne CD, et al. Current status and future trends of the global burden of MASLD. Trends Endocrinol Metab. 2024;35(8):697–707.

    Article  CAS  PubMed  Google Scholar 

  38. Lekakis V, Papatheodoridis GV. Natural history of metabolic dysfunction-associated steatotic liver disease. Eur J Intern Med. 2024;122:3–10.

    Article  CAS  PubMed  Google Scholar 

  39. Dulai PS, Singh S, et al. Increased risk of mortality by fibrosis stage in nonalcoholic fatty liver disease: systematic review and meta-analysis. Hepatology. 2017;65:1557–65.

    Article  CAS  PubMed  Google Scholar 

  40. Mellemkjær A, Kjær MB, Haldrup D, et al. Management of cardiovascular risk in patients with metabolic dysfunction-associated steatotic liver disease. Eur J Intern Med. 2024;122:28–34.

    Article  PubMed  Google Scholar 

  41. Qi X, Li J, Caussy C, et al. Epidemiology, screening, and co-management of type 2 diabetes mellitus and metabolic dysfunction-associated steatotic liver disease. Hepatology Published online May 8, 2024.

  42. En Li Cho E, Ang CZ, Quek J, et al. Global prevalence of non-alcoholic fatty liver disease in type 2 diabetes mellitus: an updated systematic review and meta-analysis. Gut 2023;72(11):2138–48.

  43. Huang DQ, Wilson LA, Behling C, et al. Fibrosis Progression Rate in Biopsy-Proven Nonalcoholic Fatty Liver Disease Among People With Diabetes Versus People Without Diabetes: A Multicenter Study. Gastroenterology. 2023;165:463–72.

    Article  CAS  PubMed  Google Scholar 

  44. Yadav D, Lee ES, Kim HM, et al. Prospective study of serum uric acid levels and incident metabolic syndrome in a Korean rural cohort. Atherosclerosis. 2015;241:271–7.

    Article  CAS  PubMed  Google Scholar 

  45. Fan J, Wang D. Serum uric acid and nonalcoholic fatty liver disease. Front Endocrinol (Lausanne). 2024;15:1455132.

    Article  PubMed  Google Scholar 

  46. Lanaspa MA, Sanchez-Lozada LG, Choi YJ, et al. Uric acid induces hepatic steatosis by generation of mitochondrial oxidative stress: potential role in fructose-dependent and -independent fatty liver. J Biol Chem. 2012;287:40732–44.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Choi YJ, Shin HS, Choi HS, et al. Uric acid induces fat accumulation via generation of endoplasmic reticulum stress and SREBP-1c activation in hepatocytes. Lab Invest. 2014;94(10):1114–25.

    Article  CAS  PubMed  Google Scholar 

  48. Wan X, Xu C, Lin Y, et al. Uric acid regulates hepatic steatosis and insulin resistance through the NLRP3 inflammasome-dependent mechanism. J Hepatol. 2016;64(4):925–32.

    Article  CAS  PubMed  Google Scholar 

  49. Xie, Zhao H, Lu J, He F, Liu W, Yu W, et al. High uric acid induces liver fat accumulation via ROS/JNK/AP-1 signaling. Am J Physiol Endocrinol Metab. 2021;320(6):E1032–43.

  50. Lanaspa MA, Cicerchi C, Garcia G, et al. Counteracting roles of AMP deaminase and AMP kinase in the development of fatty liver. PLoS ONE. 2012;7(11): e48801.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Hak AE, Choi HK. Menopause, postmenopausal hormone use and serum uric acid levels in US women–the Third National Health and Nutrition Examination Survey. Arthritis Res Ther. 2008;10(5):R116.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Sommerauer C, Gallardo-Dodd CJ, Savva C, et al. Estrogen receptor activation remodels TEAD1 gene expression to alleviate hepatic steatosis. Mol Syst Biol. 2024;20(4):374–402.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Li L, Yao Y, Wang Y, et al. G protein-coupled estrogen receptor 1 ameliorates nonalcoholic steatohepatitis through targeting AMPK-dependent signaling. J Biol Chem. 2024;300(3): 105661.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Han SI, Komatsu Y, Murayama A, et al. Estrogen receptor ligands ameliorate fatty liver through a nonclassical estrogen receptor/Liver X receptor pathway in mice. Hepatology. 2014;59(5):1791–802.

    Article  CAS  PubMed  Google Scholar 

  55. Lu C, Cardoso RC, Puttabyatappa M, Padmanabhan V. Developmental Programming: Prenatal Testosterone Excess and Insulin Signaling Disruptions in Female Sheep. Biol Reprod. 2016;94(5):113.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Hossain IA, Faruque MO, Akter S, et al. Elevated levels of serum uric acid and insulin resistance are associated with nonalcoholic fatty liver disease among prediabetic subjects. Trop Gastroenterol. 2016;37(2):101–11.

    Article  CAS  PubMed  Google Scholar 

  57. Pasquali R, Oriolo C. Obesity and Androgens in Women. Front Horm Res. 2019;53:120–34.

    Article  CAS  PubMed  Google Scholar 

  58. Kim C, Halter JB. Endogenous sex hormones, metabolic syndrome, and diabetes in men and women. Curr Cardiol Rep. 2014;16(4):467.

    Article  PubMed  PubMed Central  Google Scholar 

  59. RinellaME, Neuschwander-TetriBA, SiddiquiMS, et al. AASLD practice guidance on the clinical assessment and management of nonalcoholic fatty liver disease. Hepatology, 2023, 77( 5): 1797- 1835

  60. Hernaez R, Lazo M, Bonekamp S, et al. Diagnostic accuracy and reliability of ultrasonography for the detection of fatty liver: a meta-analysis. Hepatology. 2011;54(3):1082–90.

    Article  PubMed  Google Scholar 

  61. Chen Q, Hu P, Hou X, et al. Association between triglyceride-glucose related indices and mortality among individuals with non-alcoholic fatty liver disease or metabolic dysfunction-associated steatotic liver disease. Cardiovasc Diabetol. 2024;23(1):232.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Yokoyama S, Honda T, Ishizu Y, et al. Risk factors for decreased bone mineral density in patients with metabolic dysfunction-associated steatotic liver disease: A cross-sectional study at a health examination center. Clin Nutr. 2024;43(6):1425–32.

    Article  CAS  PubMed  Google Scholar 

  63. Heo JH, Lee MY, Kim SH, et al. Comparative associations of non-alcoholic fatty liver disease and metabolic dysfunction-associated steatotic liver disease with risk of incident chronic kidney disease: a cohort study. Hepatobiliary Surg Nutr. 2024;13(5):801–13.

    Article  PubMed  PubMed Central  Google Scholar 

  64. De Matteis C, Crudele L, Di Buduo E, et al. Hyperhomocysteinemia is linked to MASLD. Eur J Intern Med. 2025;131:49–57.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

The authors would be grateful for language services by Duoease Scientific Service Center.

Funding

This work was supported by the Natural Science Foundation of Shandong Province [grant numbers ZR2021QH181].

Author information

Authors and Affiliations

  1. Department of Endocrinology, Qilu Hospital of Shandong University Dezhou Hospital, Dezhou, 253000, China

    Yuliang Cui, Zhenzhen Qu & Wenmei Hu

  2. Department of Health Management, Qilu Hospital of Shandong University Dezhou Hospital, Dezhou, 253000, China

    Lingling Li

Authors
  1. Yuliang Cui
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Zhenzhen Qu
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Lingling Li
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Wenmei Hu
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Zhenzhen Qu, and Lingling Li. The Data analysis and first draft preparation of the manuscript were performed by Yuliang Cui. The conceptualization and writing- reviewing were performed by Wenmei Hu and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Wenmei Hu.

Ethics declarations

Ethics approval and consent to participate

The study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki (6 th revision, 2008) as reflected in a priori approval by the ethics committees of Qilu Hospital of Shandong University Dezhou Hospital. Written informed consent was provided by each participant.

Consent for publication

Informed consent for publication was obtained from each participant included in the study.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cui, Y., Qu, Z., Li, L. et al. Gender difference in the association between serum uric acid and metabolic dysfunction-associated steatotic liver disease in patients with newly diagnosed type 2 diabetes. BMC Gastroenterol 25, 322 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12876-025-03917-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12876-025-03917-9

Keywords

BMC Gastroenterology

ISSN: 1471-230X

Contact us