Abstract
Background
With the continuing global obesity epidemic, fatty pancreas disease (FPD) has become one of the most prevalent chronic pancreatic conditions. The objective of this study was to identify potential risk factors contributing to FPD among individuals who are overweight and obese.
Methods
This cross-sectional study enrolled a total of 205 participants (101 female, 104 male) who were overweight or obese. Data were collected from December 2019 to November 2023. Each participant underwent a comprehensive assessment, including clinical history documentation, physical evaluation, laboratory analysis, and magnetic resonance imaging (MRI). Based on a pancreatic fat fraction cut-off value of 10.4% measured through MRI, the participants were categorized into FPD and non-FPD groups. Differences between groups were analyzed based on sex and the presence or absence of FPD. A binary logistic regression model was constructed and used to identify risk factors for FPD. Subsequently, the diagnostic performance of the identified independent risk factors for diagnosing FPD was assessed using receiver operating characteristic curve analysis.
Results
Among men, no significant correlation was observed between serum uric acid (SUA) levels and FPD. However, among women, SUA levels were significantly elevated in individuals with FPD compared with those without FPD. Multivariate logistic regression analysis confirmed SUA as an independent predictor of FPD in women. The optimal SUA threshold for predicting FPD in women who were overweight and obese was 6.29 mg/dL.
Conclusion
Elevated SUA levels are a risk factor for FPD in women who are overweight or obese. Therefore, clinicians should monitor pancreatic fat accumulation in women with SUA levels exceeding 6.29 mg/dL.
Trial registration
Chinese Clinical Trial Registry ChiCTR1900022948; Registered 4 May 2019.
Keywords: Obesity, Overweight, Fatty pancreas disease, Serum uric acid, Risk factors
Background
The concept of pancreatic fat accumulation was introduced by Ogilvie nearly a century ago [1]. The absence of standardized diagnostic criteria has considerably hindered research on the prevalence of fatty pancreas disease (FPD) in the general population. FPD is an independent risk factor for both exocrine and endocrine pancreatic disorders, including type 2 diabetes mellitus (T2DM), acute and chronic pancreatitis, pancreatic fistulas, and pancreatic cancer [2–4]. Additionally, FPD is associated with metabolic syndrome, subclinical atherosclerosis, and β-cell dysfunction [5–9]. The mechanisms underlying FPD remain incompletely understood but may involve inflammation, oxidative stress, and dysregulation of the gut microbiota [6, 10, 11]. Currently, there are no reliable serum markers for screening FPD.
Research suggests that men generally exhibit a higher pancreatic fat fraction (PFF) than women [12, 13]. In women, FPD is strongly associated with visceral fat and subcutaneous fat accumulation, whereas in men it is strongly associated with hepatic steatosis [14]. These differences may be due to the effects of sex hormones on pancreatic fat deposition through the regulation of fat distribution [13, 15]. Therefore, investigating sex differences in pancreatic fat accumulation and performing sex-stratified analyses of the associated risk factors is essential.
Although the occurrence of FPD is closely related to obesity [10], previous studies have shown that not all individuals who are obese develop FPD [9]. FPD can also result from pancreatic fat replacement due to acinar cells loss or transdifferentiation into adipocytes [16]. The present study aimed to delineate significant risk factor for FPD development among individuals with a high body mass index (BMI), to inform clinical screening protocols and therapeutic interventions for this metabolic disorder.
Methods
Study population
This study employed baseline data from patients who were overweight or obese attending the weight-loss clinic at the affiliated Wuxi People’s Hospital of Nanjing Medical University for individualized multidisciplinary weight management (ChiCTR1900022948; registered May 4, 2019). The study protocol was approved by the Ethics Committee of Wuxi People’s Hospital (approval number: KS2019020) and conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all the participants.
A total of 205 patients who met the inclusion criteria were enrolled between December 2019 and November 2023. Inclusion criteria were as follows: (1) age 18–65 years, (2) BMI ≥ 28.0 kg/m2 or ≥ 24.0 kg/m2, with stable weight in the past 3 months. According to the Working Group on Obesity in China, the diagnostic thresholds are defined as follows: ≥24.0 kg/m2 for overweight and ≥ 28.0 kg/m2 for obesity. The exclusion criteria were as follows: (1) secondary obesity (2) daily alcohol intake > 10 g in women and > 20 g in men; (3) any form of pancreatic disease, including tumors, inflammation, or autoimmune disorders; (4) a medical history of malignancy, cardiovascular disease, or severe liver or kidney dysfunction; (5) MRI contraindications (metallic implants, and claustrophobia); (6) pregnancy.
Anthropometric and laboratory data collection
All clinical assessments were performed by certified medical personnel following standardized operating procedures to ensure methodological consistency. Body weight and height were measured using a calibrated scale (HNH-318; Omron, Japan). BMI was calculated as weight (kg)/height squared (m2). Waist circumference (WC) was measured at the midpoint between the lowest rib and superior border of the iliac crest using a standard tape. After a 15-min seated rest, systolic and diastolic blood pressures (SBP and DBP, respectively) were measured twice using a mercury gravity manometer.
After a 10-h overnight fast, venous blood samples were obtained to measure serum uric acid (SUA), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), alanine aminotransferase (ALT), and aspartate aminotransferase (AST), and fasting blood glucose (FBG) using photometric assays (Chemistry Immunoanalyzer AU5800, Beckman Coulter, USA). Glycated hemoglobin (HbA1c) was measured using high-performance liquid chromatography (VARIANT II Hemoglobin Testing System, BIORAD, USA).
FPD assessment
Pancreatic fat content was measured using the six-point Dixon technique on a 3T MRI system (SIEMENS 3.0T MAGNETOM Prisma) equipped with an 18-channel body array coil. Detailed equipment parameters are described in our previous study [9]. The imaging parameters were as follows: TE1, 2.38 ms; TE2, 4.76 ms; TE3, 7.15 ms; TE4, 9.53 ms; TE5, 11.91 ms; TE6, 14.29 ms; TR, 15.60 ms; flip angle, 4°; FOV, 420 mm × 420 mm, and a 3.5-mm slice thickness. The Philips IntelliSpace Portal software was used with MRI workstations for post-processing of the mDixon sequence images. The PDFF (proton density fat fraction) maps were imported into the Syngo software via the MRI workstation, and the pancreas was manually segmented on all layers of the PDFF maps. The pancreas was segmented according to the specialized and standardized anatomical landmarks, avoiding visible pancreatic ducts, vessels, and adjacent visceral fat. The average PFF was then calculated. The participants were categorized into two groups based on PFF, using the cut-off value of 10.4% [17]. Individuals with a PFF < 10.4% were classified as non-FPD, whereas those with a PFF ≥ 10.4% were considered to have FPD.
Statistical analysis
All descriptive data are presented as means ± standard deviations or medians (first quartile, third quartile). Continuous variables were compared using Student’s t-test or the Mann–Whitney U test. Categorical variables are expressed as numbers (%) and were compared using the Chi-square test. A binary logistic regression analysis model was constructed to identify risk factors for FPD. Odds ratios (OR) and 95% confidence intervals (CI) were calculated to assess the effects of these factors. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive value of the independent risk factors for FPD. A p-value < 0.05 was considered statistically significant. All statistical analyses were performed using SPSS software (version 27.0; Armonk, NY: IBM Corp).
Results
Demographic and clinical characteristics of study participants
Table 1 presents the baseline characteristics of the study participants, stratified by sex. A total of 205 patients were included in the analysis, with a mean age of 33 ± 8 years. Of these, 104 patients (50.7%) were men, and 50 (24.4%) had T2DM. Among male patients, the prevalence of FPD was 87.5%, whereas among female patients, it was 58.4%. Compared with women, men were more likely to have hypertension and a history of smoking. Moreover, men exhibited significantly higher WC, SBP, DBP; ALT, AST, TG, LDL-C, HbA1c, creatinine (Cr), blood urea nitrogen, and SUA levels; and PFF than women (P < 0.05). Further analysis was stratified by FPD status in only women, as the small number of non-FPD cases in men (n = 13) limited meaningful subgroup comparisons. As shown in Table 2, female participants with FPD had a higher incidence of T2DM and significantly higher BMI, WC, and HbA1c levels than those without FPD (P < 0.05). Additionally, SUA levels were significantly higher in women with FPD than in those without FPD (6.82 ± 1.71 vs. 5.62 ± 1.71 mg/dL; P < 0.001). No significant differences were observed between the FPD and non-FPD groups in terms of age, prevalence of hypertension (HP), blood pressure (SBP and DBP), lipid levels (TG, TC, LDL-C, and HDL-C), and FBG levels. Among women, SUA levels were significantly higher in those with either HP or FPD than in those without these conditions (Fig. 1B, C). No significant differences in SUA levels were observed in women with and without T2DM, or in men stratified by T2DM, HP, or FPD (Fig. 1A–C).
Table 1.
Demographic and clinical characteristics of enrolled participants
| Variables | All participants (n = 205) | Women (n = 101) | Men (n = 104) |
|---|---|---|---|
| Age (years) | 33 ± 8 | 32 ± 7 | 32 ± 8 |
| BMI (kg/m2) | 33.37 ± 5.07 | 32.77 ± 4.68 | 33.96 ± 5.38 |
| WC (cm) | 104.32 ± 12.96 | 99.43 ± 11.63 | 109.08 ± 12.45 ∗ |
| T2DM (n, %) | 50 (24.4%) | 21 (20.8%) | 29 (27.9%) |
| HP (n, %) | 67 (32.7%) | 24 (23.8%) | 43 (41.3%) ∗ |
| Smoker (n, %) | 39 (19.0%) | 1 (0.9%) | 38 (36.5%) ∗ |
| SBP (mmHg) | 133 ± 19 | 126 ± 16 | 139 ± 20 |
| DBP (mmHg) | 79 ± 12 | 75 ± 9 | 82 ± 13 |
| ALT (U/L) | 38.00 (21.50,62.25) | 26.00 (17.00,46.25) | 50.00 (33.78,83.65) ∗ |
| AST(U/L) | 26.00 (18.50,39.00) | 20.06 (17.00,29.00) | 31.00 (23.00,48.00) ∗ |
| TG (mmol/L) | 1.84 (1.29,2.53) | 1.60 (1.07,2.19) | 2.10 (1.57,3.06) ∗ |
| TC (mmol/L) | 5.14 (4.58,5.86) | 5.11 (4.66,5.76) | 5.16 (4.38,5.99) |
| LDL-C (mmol/L) | 3.11 (2.55,3.60) | 3.09 (2.59,3.49) | 3.13 (2.52,3.64) ∗ |
| HDL-C (mmol/L) | 1.04 (0.94,1.20) | 1.15 (1.01,1.30) | 0.98 (0.87,1.07) |
| HbA1c (%) | 5.60 (5.29,6.24) | 5.50 (5.22,6.15) | 5.70 (5.40,6.58) ∗ |
| FBG (mmol/L) | 5.48 (4.99, 6.48) | 5.41 (5.02,6.16) | 5.49 (4.94,6.75) |
| Cr (umol/L) | 63.20 (54.35,74.95) | 55.70 (50.90,62.20) | 74.05 (65.65,83.78) ∗ |
| BUN (mmol/L) | 4.97 ± 1.25 | 4.61 ± 1.09 | 5.32 ± 1.30 ∗ |
| SUA (mg/dL) | 7.05 ± 1.79 | 6.32 ± 1.80 | 7.70 ± 1.47 ∗ |
| PFF (%) | 13.59 (10.20,17.31) | 11.58 (8.51,15.94) | 14.73 (12.10,18.78) ∗ |
| FPD (n, %) | 150 (73.2%) | 59 (58.4%) | 91 (87.5%) |
∗P < 0.05 vs. women
Abbreviations: BMI, body mass index; WC, waist circumference; DM, diabetes mellitus; HP, hypertension; SBP, systolic blood pressure; DBP, diastolic blood pressure; ALT, alanine aminotransferase; AST, aspartate aminotransferase; TG, triacylglycerol; TC, total cholesterol; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; HbA1c, glycated hemoglobin; FBG, fasting blood glucose; Cr, creatinine; BUN, blood urea nitrogen; SUA, serum uric acid; PFF, pancreatic fat fraction; FPD, fatty pancreas disease
Table 2.
Comparison of clinical characteristics in female participants with and without FPD
| Variables | Non-FPD (n = 42) | FPD (n = 59) | P |
|---|---|---|---|
| Age (years) | 30.99 ± 6.69 | 33.46 ± 7.46 | 0.09 |
| BMI (kg/m2) | 30.80 ± 3.96 | 34.15 ± 4.68 | < 0.001 |
| WC (cm) | 94.16 ± 9.77 | 103.09 ± 11.48 | < 0.001 |
| T2DM (n, %) | 4 (9.5%) | 17 (28.8%) | 0.019 |
| HP (n, %) | 11 (26.2%) | 13 (22.0%) | 0.629 |
| SBP (mmHg) | 126.07 ± 15.36 | 125.89 ± 15.89 | 0.956 |
| DBP (mmHg) | 72.37 ± 8.34 | 76.00 ± 9.69 | 0.052 |
| ALT(U/L) | 21.45 (16.38,39.75) | 26.80 (17.00,42.20) | 0.074 |
| AST(U/L) | 20.30 (16.75,26.25) | 21.00 (17.00,42.20) | 0.256 |
| TG (mmol/L) | 1.49 (0.94,2.41) | 1.64 (1.21,2.18) | 0.240 |
| TC (mmol/L) | 5.04 (4.64,5.79) | 5.15 (4.67,5.74) | 0.839 |
| LDL-C (mmol/L) | 3.06 (2.52,3.48) | 3.14 (2.59,3.55) | 0.723 |
| HDL-C (mmol/L) | 1.19 (0.99,1.32) | 1.14 (1.03,1.28) | 0.741 |
| HbA1c (%) | 5.34 (5.15,5.70) | 5.54 (5.30,6.20) | < 0.01 |
| FBG (mmol/L) | 5.38 (5.03,5.86) | 5.53 (5.01,6.36) | 0.335 |
| Cr (umol/L) | 58.70 (52.77,62.90) | 54.40 (49.60,54.40) | 0.057 |
| BUN (mmol/L) | 4.75 ± 1.33 | 4.51 ± 0.88 | 0.279 |
| SUA (mg/dL) | 5.62 ± 1.71 | 6.82 ± 1.71 | < 0.001 |
Abbreviations: FPD, fatty pancreas disease; BMI, body mass index; WC, waist circumference; T2DM, type 2 diabetes mellitus; HP, hypertension; SBP, systolic blood pressure; DBP, diastolic blood pressure; ALT, alanine aminotransferase; AST, aspartate aminotransferase; TG, triacylglycerol; TC, total cholesterol; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; HbA1c, glycated hemoglobin; FBG, fasting blood glucose; Cr, creatinine ; BUN, blood urea nitrogen; SUA, serum uric acid
Fig. 1.
Impacts of having T2DM (A), HP (B), FPD (C) on SUA levels in each sex. Abbreviations: T2DM, type 2 diabetes mellitus; HP, hypertension; FPD, fatty pancreas disease; SUA, serum uric acid
Risk factors for FPD
In the female group, univariate logistic regression analysis revealed that FPD was positively correlated with BMI, WC, T2DM, and SUA levels and negatively correlated with Cr levels (Table 3). Multivariate logistic regression analysis showed that SUA levels were the only independent risk factor for FPD (OR = 1.474; 95% CI = 1.089–1.9931, P = 0.012) (Table 4).
Table 3.
Univariate logistic regression analysis of potential risk factors for FPD in females
| Variables | Odds ratio (95% confidence interval) | P |
|---|---|---|
| Age (years) | 1.05 (0.99,1.12) | 0.094 |
| BMI (kg/m2) | 1.20 (1.08,1.33) | < 0.001 |
| WC (cm) | 1.08 (1.04,1.126) | < 0.001 |
| T2DM (n, %) | 3.85 (1.19,12.44) | 0.025 |
| HP (n, %) | 1.26 (0.50,3.16) | 0.629 |
| SBP (mmHg) | 0.99 (0.97,1.03) | 0.956 |
| DBP (mmHg) | 1.05 (0.99,1.09) | 0.055 |
| ALT (U/L) | 1.005 (0.99,1.02) | 0.368 |
| AST (U/L) | 1.01 (0.99,1.03) | 0.211 |
| TG (mmol/L) | 1.19 (0.76,1.89) | 0.444 |
| TC (mmol/L) | 1.09 (0.68,1.76) | 0.702 |
| LDL-C (mmol/L) | 1.12 (0.60,2.04) | 0.744 |
| HDL-C (mmol/L) | 0.67 (0.09,4.57) | 0.679 |
| HbA1c (%) | 1.64 (0.98,2.75) | 0.060 |
| FBG (mmol/L) | 1.21 (0.94,1.57) | 0.142 |
| Cr (umol/L) | 0.95 (0.90,0.99) | 0.042 |
| BUN (mmol/L) | 0.82 (0.56,1.18) | 0.282 |
| SUA (mg/dL) | 1.57 (1.17,2.11) | 0.003 |
Abbreviations: FPD, fatty pancreas disease; BMI, body mass index; WC, waist circumference; T2DM, type 2 diabetes mellitus; HP, hypertension; SBP, systolic blood pressure; DBP, diastolic blood pressure; ALT, alanine aminotransferase; AST, aspartate aminotransferase; TG, triacylglycerol; TC, total cholesterol; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; HbA1c, glycated hemoglobin; FBG, fasting blood glucose; Cr, creatinine ; BUN, blood urea nitrogen; SUA, serum uric acid
Table 4.
Multivariate logistic regression models for FPD in females
| Variables | Odds ratio (95% confidence interval) | P |
|---|---|---|
| BMI (kg/m2) | 1.091 (0.884,1.347) | 0.415 |
| WC (cm) | 1.022 (0.937,1.113) | 0.625 |
| T2DM (n, %) | 2.527 (0.672,9.507) | 0.170 |
| Cr (umol/L) | 0.951 (0.896,1.010) | 0.102 |
| SUA (mg/dL) | 1.474 (1.089,1.993) | 0.012 |
Abbreviations: FPD, fatty pancreas disease; BMI, body mass index; WC, waist circumference; T2DM, type 2 diabetes mellitus; Cr, creatinine; SUA, serum uric acid
Accuracy of SUA in predicting FPD
Based on ROC curve analysis (Fig. 2), the SUA cut-off value was 6.29 mg/dL, with an area under the curve of 0.702. The sensitivity and specificity of SUA levels for predicting FPD were 61.0% and 71.4%, respectively (P < 0.05).
Fig. 2.
Receiver operating characteristic curve of SUA level for diagnosis FPD in females. Abbreviations: FPD, fatty pancreas disease; SUA, serum uric acid
Discussion
Prior studies have associated FPD with age [18] and BMI [19] while being inconclusive for SUA [19, 20]. Here, we identified SUA as an independent risk factor for FPD in overweight and obese women. The results of this study suggest that FPD is highly prevalent (87.5%) in overweight and obese men, possibly due to underlying physiological or multiple risk factors; thus, the significance of risk factor research for prevention is relatively low. In contrast, the incidence rate of FPD in women who are overweight and obese was 58.4%, indicating that FPD is not inevitable. The difference in incidence rates highlights the importance of studying female-specific risk factors. Our study specifically focused on overweight and obese women. The role of SUA as an independent risk factor for FPD further establishes the key position of SUA levels in the pathological process of FPD in women, especially in the group with high BMI. This finding suggests that controlling SUA may become a new target for women with overweight/obesity to prevent or delay FPD progression. It also provides a biochemical basis for explaining the observed sex differences.Biopsy remains the gold standard for diagnosing FPD. However, due to the complex anatomical location of the pancreas and the heterogeneous distribution of pancreatic fat [21], performing invasive biopsy is challenging in routine clinical practice. MRI enables the quantification of pancreatic fat and offers greater accuracy than ultrasound or computed tomography (CT) [22]. In this study, we used MRI to quantitatively assess FPD. Based on the findings from a Hong Kong study [17], we adopted a PFF threshold >10.4% to define FPD. The reported prevalence of FPD among Asian populations ranges from 16% to 35% [17, 23]. A South Korean cross-sectional study with obesity reported a 61.4% prevalence of FPD [24]. In our study, the prevalence of FPD was 58.4% in women who were overweight or obese, further validating the positive relationship between high BMI and greater FPD risk.
Age has been identified as an independent risk factor for FPD [18, 20]. Wong et al. conducted age-stratified analysis demonstrating that compared with that in younger individuals (< 40 years, n = 114), the overall risks of developing FPD were significantly higher in older adults (≥ 60 years, n = 73) and middle-aged individuals (40–59 years, n = 498), with OR values of 4.95 (P = 0.0003) and 3.20 (P = 0.005), respectively [17]. Besides, Koyuncu et al. reported an independent correlation between age and FPD [25]. However, another study showed that pancreatic fat accumulation tends to plateau between the ages of 20 and 60 [26], In our study, age had no significant effect on FPD in univariate regression analysis, possibly due to the relatively small age range of the enrolled study participants.
SUA is a key metabolic byproduct. It plays a significant role in various metabolic disorders, including T2DM, obesity, non-alcoholic fatty liver disease, and metabolic syndrome [27–30]. Elevated SUA levels are associated with worsening metabolic profiles and exhibit a positive correlation with abdominal fat, particularly visceral fat [29, 31]. However, the relationship between SUA levels and FPD remains unclear. A Chinese study involving 1,774 participants used ultrasonography to assess pancreatic fat and evaluate the predictive value of physical and biochemical indicators of FPD [19]. The results showed that weight-related parameters, such as body weight and BMI, were superior to uric acid in predicting FPD.A cross-sectional study by Altinmakas et al. involving 322 patients used CT-based pancreatic fat quantification and identified SUA as an independent predictor of FPD [18]. Similarly, another Chinese study found that uric acid in patients with FPD were significantly higher than those in the control group (P < 0.001); [20] however, multivariate logistic regression analysis failed to establish an independent association between SUA and FPD. The differences in these results may partly stem from the variations in the characteristics of the study population and diagnostic methods for FPD. Previous studies usually included a wide range of populations [18–20] and mainly relied on ultrasound or CT for FPD assessment. The detection ability of ultrasound for pancreatic fat deposition is affected by factors such as the operator’s experience and abdominal fat interference. CT allows only semi-quantitative assessment of pancreatic fat and involves radiation exposure. In contrast, our study focused on a clearly defined high-risk group: overweight and obese women. More importantly, we used MRI for the quantitative determination of pancreatic fat. This study identified SUA as an independent factor for FPD in women with overweight/obesity and established a clinically relevant cut-off of 6.29 mg/dL by ROC analysis. These findings may better reflect the true association between SUA and FPD, owing to improved methodological rigor. The determined SUA cut-off value (6.29 mg/dL) provides a potential biomarker reference for the early identification and risk stratification of FPD in overweight/obese women.
Nevertheless, the mechanisms underlying the relationship between SUA levels and FPD remain unclear. Research has shown that elevated SUA levels are significantly associated with insulin resistance, which in turn promotes lipolysis and the release of free fatty acids (FFA), leading to abnormal fat deposition in visceral tissues [32]. An animal study demonstrated that SUA can induce the expression of monocyte chemoattractant protein-1 in vitro, promoting a systematic proinflammatory state [33]. Uric acid may also contribute to de novo lipogenesis and increase circulating FFA levels by inducing mitochondrial oxidative stress [34]. Emerging evidence suggests that excessive visceral fat may be involved in purine and uric acid metabolism through the upregulation of xanthine oxidoreductase expression and enzymatic activity in adipocytes [35]. Therefore, the relationship between SUA level and FPD may be bidirectional and multifactorial.
Our study has certain limitations. First, the study participants were recruited exclusively from weight-loss clinics, which may limit the generalizability of our findings to broader populations, including those from other settings, ethnicities, or community-based cohorts. Second, the cross-sectional design enabled association analysis but could not ascertain causality between FPD and identified risk factors. Third, data on important potential confounders such as dietary purine intake, detailed alcohol consumption, and medication use were not collected. Thus, their residual effects on the observed associations between SUA levels and FPD cannot be excluded. Future large-scale, multicenter studies are necessary to further validate the association between SUA levels and FPD.
Conclusion
Our findings identify SUA as an independent risk factor for FPD and propose a preliminary cut-off (> 6.29 mg/dL) for risk stratification in Asian women with overweight and obesity. These results highlight SUA as a potential biomarker for early detection and prevention of FPD. However, external validation in larger, diverse populations is essential before this threshold is clinically applied.
Acknowledgements
The authors thank Editage (www.editage.cn) for professional English language editing of this manuscript.
Abbreviations
- ALT
alanine aminotransferase
- AST
aspartate aminotransferase
- AUC
area under the curve
- BMI
body mass index
- CI
confidence interval
- Cr
creatinine
- CT
computed tomography
- DBP
diastolic blood pressure
- FBG
fasting blood glucose
- FFA
free fatty acid
- FPD
fatty pancreas disease
- HbA1c
glycated hemoglobin
- HDL-C
high-density lipoprotein cholesterol
- HP
hypertension
- LDL-C
low-density lipoprotein cholesterol
- MRI
magnetic resonance imaging
- OR
odds ratio
- PDFF
proton density fat fraction
- PFF
pancreatic fat fraction
- ROC
receiver operating characteristic
- SBP
systolic blood pressure
- SUA
serum uric acid
- T2DM
type 2 diabetes mellitus
- TC
total cholesterol
- TG
triglycerides
- WC
waist circumference
Author contributions
Xiaolei Chen and Chenxi Li: designed the initial study and drafted the initial script. Haiyan Cheng and Xiaowen Zhu collected and analyzed the data. Mengjiao Cao and Qunfeng Tang: data curation, methodology. Wenjun Wu: project administration, writing-review and editing, supervision. All authors read and approved the final manuscript.
Funding
This work was supported by the Shanghai Six Hospital Medical Group Project (2024-01), and the Cohort and Clinical Research Program of Wuxi Medical Center, Nanjing Medical University (WMCC202322, WMCC202405).
Data availability
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Declarations
Ethics approval and consent to participant
This study was conducted in accordance with the principles of the Declaration of Helsinki. Written, informed consent was obtained from all of the participants, and the study was approved by the Ethics Committee of Wuxi People’s Hospital (ChiCTR1900022948; registered May 4, 2019).
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Xiaolei Chen and Chenxi Li contributed equally to this work and share co-first authorship.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.