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Article

The Association of Statin Therapy with Liver and Pancreatic Fat Fraction in Type 2 Diabetes Mellitus

by
Mehmet Akif Parlar
1,*,
Hakan Mutlu
1,
Betül Doğantekin
1,
İsmail Serhat Musaoğlu
1,
Nisa Demirboşnak Albayrakoğlu
1,
Mustafa Lütfi Yavuz
2,
Zehra Buşra Özbolat
3 and
Mustafa Kaplan
1
1
Department of Internal Medicine, Sultan 2. Abdülhamid Han Training and Research Hospital, University of Health Sciences, Selimiye Neighborhood, Tıbbiye Street, 34668 Istanbul, Turkey
2
Department of Cardiology, Istanbul University Faculty of Medicine, 34093 Istanbul, Turkey
3
Deparment of Chest Diseases, Çerkezköy State Hospital, Tekirdağ Provincial Health Directorate, 59100 Tekirdağ, Turkey
*
Author to whom correspondence should be addressed.
Diagnostics 2025, 15(4), 426; https://doi.org/10.3390/diagnostics15040426
Submission received: 26 December 2024 / Revised: 2 February 2025 / Accepted: 7 February 2025 / Published: 10 February 2025
(This article belongs to the Section Medical Imaging and Theranostics)
Browse Figures
Versions Notes

Abstract

:
Background/Objectives: It has been shown that the use of statins in patients with type 2 diabetes mellitus (T2DM) worsens hyperglycemia and hemoglobin A1c levels but may help in the preservation of pancreatic β-cell function. The potential role of a high pancreatic fat fraction (PFF) in this process has not yet been clarified. This study aimed to investigate whether the liver fat fraction (LFF) and PFF in T2DM patients is affected by statin therapy. Methods: This cross-sectional study involved a total of 140 T2DM patients, including both those who were receiving (n = 70) and those who were not receiving (n = 70) statin therapy. The mapping of the LFF and PFF utilizing the IDEAL-IQ sequence was conducted in magnetic resonance imaging. Results: In T2DM patients who used statins, the median PFF was higher compared to those who did not use statins (8.4 vs. 6.2%, p = 0.021), while the median LFF was found to be similar (8.4 vs. 8.9, p = 0.572). Variations in PFF were associated with the use of various statins (non-statin group: 6.2 vs. atovastatin: 8.7 vs. rosuvastatin: 3.2 vs. pitavastatin: 9.2, p = 0.004). The multivariable regression analysis indicated that insulin usage decreased log(LFF) by a factor of 0.16-fold (ꞵ ± SE = −0.16 ± 0.05, p = 0.010), and rosuvastatin usage reduced log(PFF) by 0.16-fold (ꞵ ± SE = −0.16 ± 0.07, p = 0.025), irrespective of other risk factors. Furthermore, the use of atorvastatin (ꞵ ± SE = 0.17 ± 0.06, p = 0.011) and pitavastatin (ꞵ ± SE = 0.19 ± 0.07, p = 0.008) were independently associated with an increase in log(PFF). Conclusions: In patients with T2DM, statin use did not show a significant effect on the liver fat fraction, but it caused differences in the pancreatic fat fraction. The observation of a lower pancreatic fat fraction in patients taking a rosuvastatin and atorvastatin dose of 40 mg/day suggests that different types and doses of statins may have varying effects on pancreatic fat accumulation.

1. Introduction

Diabetes has a global prevalence exceeding 10%, and it is expected to rise to 12.2% by 2045. Among all diabetes cases, type 2 diabetes mellitus (T2DM) constitutes the majority [1]. Patients with T2DM are at an elevated risk for complications such as cardiovascular disease, kidney damage, neuropathy, and retinopathy, which impose a significant burden on healthcare systems [2]. Notably, recent evidence suggests that even in individuals without diabetes, subclinical glycemic fluctuations leading to increased glycated hemoglobin (HbA1c) levels are associated with subclinical cardiovascular dysfunction [3]. This heightened risk is largely attributed to the presence of metabolic syndrome (MetS), a cluster of interrelated metabolic abnormalities that includes central obesity, insulin resistance, dyslipidemia, and hypertension [4]. While obesity is a well-known risk factor for T2DM, visceral fat has been identified as a stronger determinant of metabolic dysfunction than subcutaneous fat [5,6]. One of the most prominent manifestations of MetS is metabolic dysfunction-associated fatty liver disease (MAFLD), formerly known as non-alcoholic fatty liver disease (NAFLD) [7,8,9]. MAFLD is now recognized as a distinct clinical entity defined by hepatic fat accumulation in the presence of metabolic dysfunction, irrespective of other etiologies such as alcohol consumption [9]. The prevalence of MAFLD is particularly high among individuals with T2DM, and it has been strongly linked to both hepatic and systemic insulin resistance, contributing to the progression of diabetes [10].
In healthy individuals, fatty acids are primarily stored as triacylglycerol in adipose tissue. However, when the storage capacity of adipose tissue is exceeded, fat accumulates in non-adipose tissues, such as the pancreas, liver, and heart [11,12]. This ectopic fat deposition can lead to cellular dysfunction, impair pancreatic β-cell function, contribute to insulin resistance, and ultimately result in elevated blood glucose levels [13]. Moreover, ectopic fat depots are metabolically active and secrete pro-inflammatory cytokines, which further exacerbate insulin resistance and β-cell dysfunction through chronic low-grade inflammation [14]. Increasing evidence suggests a strong association between pancreatic fat accumulation and the onset of both prediabetes and diabetes [15,16]. Since the pancreas and liver play central roles in glucose metabolism, fat deposition in these organs is believed to be a key factor in the pathophysiology of T2DM, particularly through mechanisms related to β-cell dysfunction and insulin resistance [17]. Several studies have shown that patients with T2DM exhibit increased pancreatic fat content and a smaller pancreatic volume compared to healthy individuals [18]. Furthermore, pancreatic fat accumulation has been inversely associated with insulin secretion, indicating its potential role in the progression of diabetes [19,20]. Similarly, hepatic fat accumulation has been strongly linked to insulin resistance during gluconeogenesis and is recognized as a major contributor to the progression of T2DM [21]. A key mechanism underlying β-cell dysfunction in T2DM is glucolipotoxicity, which refers to the combined detrimental effects of chronic hyperglycemia and elevated free fatty acids on pancreatic β-cells. This phenomenon leads to impaired insulin secretion and β-cell apoptosis, thereby exacerbating hyperglycemia and contributing to the progression of diabetes [22,23].
Despite these findings, the association between elevated pancreatic fat content and lipid accumulation or dyslipidemia in diabetic patients remains controversial. While some studies have reported an independent association between fatty pancreas and diabetes without a clear link to dyslipidemia [24,25,26], others have suggested that prediabetic or diabetic patients with a pancreatic fat accumulation are more susceptible to a disrupted lipid metabolism [26,27,28]. Additionally, a positive relationship has been identified between fatty pancreas and elevated lipid levels [29]. Statins, commonly prescribed for diabetic patients with MetS and at cardiovascular risk, are known for their lipid-lowering effects [30]. Evidence from both experimental and clinical studies indicates that statins possess a direct anti-inflammatory effect on adipose tissue [31,32,33]. It has been demonstrated that statins significantly contribute to the improvement of fatty pancreas in rats stimulated with a diet rich in fructose and cholesterol [34]. Although there is limited evidence in the literature specifically addressing the effects of statin therapy on pancreatic or hepatic fat accumulation, studies on other forms of ectopic fat deposition provide supporting insights. A study conducted in patients with aortic stenosis identified a strong correlation between statin therapy and a decreased accumulation of epicardial adipose tissue. Additionally, atorvastatin was reported to exhibit an in vitro anti-inflammatory effect on cultured epicardial adipose tissue adipocytes [33]. Furthermore, another study demonstrated that statins reduced epicardial adipose tissue attenuation on computed tomography, independent of their lipid-lowering effects. This suggests that statins may decrease the metabolic activity of epicardial fat through mechanisms involving reduced cellularity, vascularity, or inflammation [35]. These findings highlight the broader pleiotropic effects of statins on ectopic fat depots, warranting further investigation into their potential impact on pancreatic fat accumulation and metabolism.
Given the established significance of ectopic fat accumulation in metabolic dysregulation, whether statin therapy could favorably influence pancreatic fat in humans with T2DM remains unclear. While preclinical models suggest that statins can ameliorate fatty pancreas [34], and clinical studies demonstrate the beneficial effects of statins on other ectopic fat depots such as epicardial adipose tissue [33,35], there is a distinct lack of direct human data examining statin use and the pancreatic fat fraction in T2DM. This gap is especially pertinent given the central role of pancreatic β-cell function in diabetes pathophysiology and the potential for targeted interventions to improve clinical outcomes. Moreover, given the observed effects of statins on epicardial adipose tissue, it is plausible that similar mechanisms could extend to pancreatic and hepatic fat depots.
We hypothesized that statin therapy may be associated with a lower pancreatic fat fraction in patients with T2DM, potentially through mechanisms involving reduced inflammation and adipose tissue remodeling. Therefore, this study aimed to investigate whether the pancreatic fat fraction in patients with T2DM is affected by statin therapy. By addressing this research gap, our study aims to provide new insights into the metabolic effects of statins beyond their conventional lipid-lowering role.

2. Materials and Methods

This cross-sectional study was conducted on T2DM patients under outpatient follow-up at the Internal Medicine Clinic of Sultan Abdülhamid Han Training and Research Hospital, between December 2021 and December 2022. The study was approved by the local ethics committee (date: 9 February 2022, decision No: 101412) and was carried out in accordance with the relevant ethical guidelines and the Helsinki Declaration (2013 Brazil revision). All study participants provided written informed consent.
An a priori power analysis was conducted to determine the required sample size for the study, based on pilot data collected from 10 patients in each group. The primary outcome was the difference in pancreatic fat fraction between T2DM patients using statins (10.2 ± 5.7) and those not using statins (7.5 ± 5.1). The effect size for the pancreatic fat ratio was determined to be 0.50 using Cohen’s formula, indicating a moderate effect size. Using the G*Power (version 3.1.9) program, the sample size was determined to be 70 patients per group, with a 90% power and a 5% margin of error.

2.1. Study Population

A total of 140 patients with T2DM (77 female [55.0%], 63 male [45.0%]) who had received upper abdominal magnetic resonance imaging (MRI) for different indications (abdominal pain, fatty liver monitoring, etc.) were evaluated. Patients were consecutively recruited from internal medicine clinics. The inclusion criteria required patients to be aged 18–70, diagnosed with T2DM, and to have either been using statin therapy for at least one year prior to the abdominal MRI or to have never used statins, and to have consented to participate in the study. All patients were enrolled from the same clinical environment, where a Mediterranean-style diet is routinely recommended as part of standard diabetes management, and adherence to this diet was included as one of the inclusion criteria. Patients with a history of systemic inflammatory or autoimmune diseases, heart failure, active rheumatologic conditions, malignancy, and pregnancy were excluded from the study. The study analyzed 70 patients with T2DM who were on statin therapy and met the eligibility criteria, along with 70 T2DM patients not on statins, matched for age and gender.
At the time of the patients’ outpatient clinic visits, their demographic information, laboratory results, and prescribed medications were documented. Anthropometric parameters, including height, weight, and waist circumference, were measured by trained healthcare staff in the outpatient clinic using standardized equipment. Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared (kg/m2). Alcohol consumption was assessed as drinking alcohol weekly or more frequently over a minimum period of one year. The patients’ pancreas and liver fat fraction were assessed by an expert radiologist with at least five years of experience, based on abdominal MRI images taken within the last year.

2.2. Laboratory Measurements

After a fasting period of 8–10 h, venous blood samples from all patients were obtained and evaluated using the Beckman Coulter LH 780 device (Mervue, Galway, Ireland) and the Hitachi Modular P800 autoanalyzer (Roche Diagnostics Corp., Indianapolis, IN, USA). Levels of hemoglobin (photometric method), leukocytes (impedance method), C-reactive protein (CRP) (immunoturbidimetric method), albumin (bromocresol green method), fasting blood glucose (FBG) (enzymatic colorimetry), glycated hemoglobin (HbA1c) (high-performance liquid chromatography), urea (urease/glutamate dehydrogenase method), creatinine (enzymatic colorimetry, Jaffe method), alanine aminotransferase (ALT) and aspartate aminotransferase (AST) (kinetic UV method), alkaline phosphatase (ALP) (p-Nitrophenyl phosphate method), gamma-glutamyl transferase (GGT) (γ-glutamyl-3-carboxy-4-nitroanilide method), and amylase and lipase (enzymatic colorimetry) were determined. Total cholesterol, high-density lipoprotein cholesterol (HDL-C), and triglyceride levels were measured using enzymatic colorimetry. The Friedewald formula was used to determine low-density lipoprotein cholesterol (LDL-C) [36].

2.3. MRI Measurements

Pancreatic MRI imaging was carried out using a 1.5 Tesla scanner (General Electric, 1.5 T GE Signa Artist, Milwaukee, WI, USA), which includes an eight-channel body phase array extremity coil. The MRI protocol comprised conventional 2-plane (coronal and axial) T2-weighted, fat-suppressed axial T2-weighted, diffusion weighted imaging (DWI) and apparent diffusion coefficient (ADC) mapping, a dual-echo T1 in phase and out of phase, and iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL-IQ) sequences.
In the MR spectrum, water molecules exhibit a single peak, whereas fat molecules display multiple peaks. The IDEAL-IQ technique includes acquiring images at various and asymmetric echo times to address these multiple fat peaks, enabling T2* corrections based on multiple chemical shifts, independent of T1. In the IDEAL-IQ sequences, the parameters were TR = 35.3 ms, FOV = 36–42 cm, matrix = 128 × 128, bandwidth = 125 kHz, and a slice thickness of 8 mm, with an approximate total of 72–112 slices covering all upper abdominal structures, including the pancreas. The analysis of IDEAL-IQ images was carried out on an imaging workstation (Advantage Workstation VolumeShare7; GE Healthcare, General Electric Company, Milwaukee, WI, USA) by a single experienced radiologist with over five years of expertise in abdominal imaging. For the liver fat percentage analysis, images were captured from eight different segments, carefully excluding major vascular formations. In the pancreas, while excluding the pancreatic duct, two elliptical Regions of Interest (ROIs), each of 15 mm2, were placed in the head, body, and tail areas (Figure 1). All calculations have been automatically corrected using homogeneity maps.

2.4. Hepatobiliary USG

All patients’ hepatobiliary ultrasound images, taken after a minimum of 8–10 h of fasting, were performed on a Samsung RS85 device (Samsung Medison, Seoul, Republic of Korea), equipped with a Samsung CA1-7A convex probe with a bandwidth of 1–7 MHz. As echogenicity increases in the liver parenchyma due to rising fat levels, the penetration of ultrasound waves diminishes with an increased fat accumulation, making it harder to visualize deeper parts of the parenchyma (such as near the subhepatic–diaphragm area and hepatic vein). Accordingly, the liver steatosis was classified as follows: (1) liver with normal parenchyma; (2) mild hepatosteatosis (Grade I), where the borders of vascular structures can be discerned, with the liver parenchyma appearing the same or more echogenic compared to the spleen parenchyma; (3) moderate hepatosteatosis (Grade II), characterized by increased echogenicity, where the borders of vascular structures cannot be discerned; and (4) severe hepatosteatosis (Grade III), where the borders of vascular structures are indiscernible, there is a marked increase in echogenicity, and deep parenchymal areas like that adjacent to the diaphragm cannot be visualized [37,38,39]. The assessment of patients was stratified according to the presence or absence of hepatic steatosis. The ultrasound evaluations were conducted by a single radiologist with at least five years of experience in hepatobiliary imaging. The evaluation of the pancreas was conducted by describing its echogenicity in comparison to the spleen parenchyma, without making any judgment related to steatosis.

2.5. Statistical Analysis

All data were analyzed with IBM SPSS Statistics for Windows 20.0 (IBM Corp., Armonk, NY, USA). Numerical data determined to be normally distributed based on the results of Kolmogorov–Smirnov tests are given as the mean ± standard deviation, while non-normally distributed variables are given as the median (25th–75th quartile). For comparisons between groups, the Student t-test or Mann–Whitney U test and ANOVA test or Kruskall–Wallis H test were used in line with the normality of the considered distribution. Categorical variables are given as numbers and percentages, and inter-group comparisons were conducted with Chi-square and Fisher exact tests. Spearman correlation analyses were applied to evaluate the relationships between numerical variables. A multivariable Cox regression analysis with the backward Wald method was subsequently performed to identify any possible independent predictors of the fat fraction of the liver and pancreas. Significance was accepted at p < 0.05 (*) for all statistical analyses.

3. Results

The study population included 140 patients with T2DM, of which 70 were statin users (mean age: 57.4 ± 7.5 years) and 70 were non-users of statins (mean age: 55.7 ± 8.7 years). Among the patients using statins, 75.7% (n = 53) were on atorvastatin, 11.4% (n = 8) on rosuvastatin, and 12.9% (n = 9) on pitavastatin. Of those taking atorvastatin, 47.1% (n = 33) were on a dose of 10 mg/day, 34.3% (n = 24) were taking 20 mg/day, and 18.5% (n = 13) were on 40 mg/day. The median duration of statin use was 2 years (IQR range = 1–5 years). The demographic and clinical characteristics of the T2DM patients are shown in Table 1 in detail.
In T2DM patients who used statins, the median duration of T2DM, as well as the rates of hypertension and hyperlipidemia, were higher compared to those who did not use statins. Other demographic characteristics did not show significant differences between the groups. In T2DM patients who used statins, the median pancreatic fat fraction level was higher compared to those who did not use statins (8.4 vs. 6.2%, p = 0.021) (Figure 2A), while the median liver fat fraction level was found to be similar (8.4 vs. 8.9, p = 0.572) (Figure 2A) (Table 1).
Among the statin subgroups that shared similar demographic features (Supplementary Table S1), the rosuvastatin group exhibited a lower pancreatic fat fraction compared to both the group not using statins and other groups receiving statin treatment. Meanwhile, the atorvastatin and pitavastatin groups showed a comparable pancreatic fat fraction, which was elevated when compared to the non-statin user group (non-statin group: 6.2 vs. atorvastatin: 8.7 vs. rosuvastatin: 3.2 vs. pitavastatin: 9.2, p = 0.004) (Table 2).
No correlation was found between liver fat fraction and pancreatic fat fraction in the all population (r = 0.035, p = 0.705). Similarly, the use of statins showed no variation in this relationship (non-statin group, r = −0.032, p = 0.792; statin group, r = 0.113, p = 0.351) (Figure 2B). While a positive correlation existed between BMI and waist circumference and liver fat fraction, they did not show any correlation with the pancreatic fat fraction. No relationship was found between comorbid conditions and either liver fat fraction or pancreatic fat fraction (Table 2). In patients using only insulin, the median liver fat fraction was lower than in those receiving other types of anti-diabetic therapies. Similarly, in the group receiving a combined treatment, the liver fat fraction was lower compared to those taking only OADs (only OADs: 10.5 vs. only insulin: 4.8 vs. combined therapy: 7.4, p = 0.032). There were no significant variations in the median pancreatic fat fraction levels among different antidiabetic treatment groups (Table 2).
There was a positive correlation between liver fat fraction and levels of ALT (r = 0.348, p < 0.001) and triglycerides (r = 0.458, p < 0.001), while a positive correlation existed between pancreatic fat fraction and ALP level (r = 0.484, p < 0.001). Other laboratory parameters did not show a correlation with either liver or pancreatic fat fractions (Table 3).
Potential risk factors associated with the liver and pancreatic fat fraction were shown in a univariable linear regression analysis. The multivariable regression analysis indicated that insulin usage decreased the log(liver fat fraction) by a factor of 0.16-fold (ꞵ ± SE = −0.16 ± 0.05, p = 0.010), and rosuvastatin usage reduced the log(pancreatic fat fraction) by 0.16-fold (ꞵ ± SE = −0.16 ± 0.07, p = 0.025), irrespective of other risk factors. Furthermore, the use of atorvastatin (ꞵ ± SE = 0.17 ± 0.06, p = 0.011) and pitavastatin (ꞵ ± SE = 0.19 ± 0.07, p = 0.008) were independently associated with an increase in log(pancreatic fat fraction) (Table 4).

4. Discussion

To the best of our knowledge, this is the first study investigating the relationship between the pancreatic fat fraction and statin use in patients with T2DM. The main findings of this study were as follows: (1) In statin users, there was an increased pancreatic fat fraction compared to those not using statins, but the liver fat fraction did not exhibit any significant difference. (2) Variations in the pancreatic fat fraction were associated with the use of various statins. (3) There was no correlation between the liver fat fraction and the pancreatic fat fraction.
Growing evidence indicates that the accumulation of fat in the pancreas impacts the metabolism of glucose and lipids [24,25,26,27,28]. Lifestyle changes like diet, weight loss, or insulin resistance management, along with bariatric surgery, can reduce pancreatic fat levels [40]. Innovative approaches such as the microbiota and fecal microbiota transplantation are emerging as promising therapeutic options for pancreatic and liver disease [41,42]. Nevertheless, the majority of studies investigating the impact of drugs on fatty pancreas have been carried out using in vitro methods or mouse models [43]. A study assessing the impact of telmisartan, sitagliptin, or their combination on the ultrastructural alterations in the pancreases of mice fed a high-fat diet found that both the monotherapy and the combined treatment effectively reversed pancreatic steatosis [44]. A study investigating the effect of glucagon-like peptide-1 analogs on ectopic fat accumulation in obese patients with T2DM showed that exenatide effectively reduces liver fat and epicardial fat levels [45]. Another study on patients with T2DM and non-alcoholic fatty liver disease (NAFLD) revealed that 24 weeks of dapagliflozin treatment led to a notable decrease in both liver and pancreatic fat content [46]. Contrary to these findings, there are studies reporting that in prediabetes or T2DM patients, treatment with metformin or empagliflozin had no effect on pancreatic fat content [47,48]. In this study, antidiabetic drugs were not associated with the pancreatic fat fraction, but insulin use was linked to a reduction in the liver fat fraction. These variations among studies might be due to factors like the criteria for choosing patients, the size of the sample groups, and ethnic origins [49].
It has been shown that statins may potentially lead to a decrease in the metabolic activity of adipose tissue [35]. However, research in this area predominantly targets NAFLD and non-alcoholic steatohepatitis (NASH), showing that statins effectively lower liver enzymes and positively influence liver histology in these conditions [50,51,52]. Interestingly, this study showed that in T2DM patients using statins, the pancreatic fat fraction was higher compared to the control group, but it did not cause a significant difference in the liver fat fraction. This condition could be associated with the simultaneous progression of lipid buildup and β-cell dysfunction in the pancreas. A study conducted in rats has shown that lipid accumulation in pancreatic tissue parallels the development of β-cell insufficiency, both in terms of timing and magnitude [53]. Statins inhibit the synthesis of cholesterol through the HMG-CoA reductase pathway, leading to the enhanced entry and buildup of cholesterol in pancreatic β-cells. This process disrupts β-cell functionality through the alteration in glucose-induced Ca2+ signaling pathways [54]. Contrary to these findings, a study assessing pancreatic fat content in subjects with prediabetes, diabetes, and the general population without cardiovascular disease, using magnetic resonance imaging, demonstrated that lipid-lowering drugs had a protective effect in a univariate analysis. However, this significance was lost in a multivariate regression analysis [15]. However, these relationships may be strongly associated with the type and dosage of statins [55].
Glucolipotoxicity, a key mechanism in β-cell dysfunction, refers to the synergistic toxic effects of chronic hyperglycemia and elevated free fatty acids on pancreatic β-cells, ultimately leading to impaired insulin secretion and β-cell apoptosis [22,23]. Recent findings indicate that glucolipotoxicity induces lipid partitioning imbalances, mitochondrial dysfunction, and the accumulation of reactive oxygen species, cholesterol, and ceramides, all of which contribute to β-cell failure [56]. A previous study indicated that lipophilic statins could influence insulin secretion via HMG-CoA inhibition or cytotoxicity, while hydrophilic statins did not have this effect [57]. Subclasses of statins differ in function in terms of oral absorption, bioavailability, hepatic extraction, protein binding, and HMG-CoA reductase activity. Simvastatin, atorvastatin, fluvastatin, and lovastatin, being hydrophobic, undergo metabolism through the cytochrome P450 enzyme system. Conversely, pravastatin and pitavastatin, being hydrophilic, are minimally metabolized in the liver, with rosuvastatin exhibiting a moderately distinct behavior [58]. The research indicates that statins with hydrophobic properties achieve greater concentrations in the liver than hydrophilic statins [59]. Patients with T2DM who used atorvastatin and rosuvastatin showed a tendency towards lower liver fat fractions. However, the pancreatic fat fraction was significantly lower only in the rosuvastatin group compared to the atorvastatin and pitavastatin ones. There are studies indicating that pitavastatin has neutral effects on adipocytes and insulin resistance [60,61]. Moreover, rosuvastatin, which is associated with a lower pancreatic fat fraction, may exhibit a pleiotropic effect by altering the fat distribution from internal organs to subcutaneous fat depots [62]. On the other hand, in patients using a 40 mg dose of atorvastatin, both the liver and pancreatic fat fractions were observed to be lower. An experimental study in obese mice indicated that treatment with atorvastatin (30 mg/kg/day) maintained the functionality of pancreatic β-cells, linked to enhanced pancreatic regeneration and the alleviation of pancreatic ER stress [63]. The current findings support the pleiotropic effect of rosuvastatin on adipose tissues, as well as the dose-dependent effect of atorvastatin. However, contrary findings have also been reported. In another experimental study conducted on Zucker rats, the effect of 6-week treatments with various statins (simvastatin, pravastatin, rosuvastatin, atorvastatin, lovastatin, and fluvastatin) on body and liver fat accumulation was investigated. It was reported that all statins, except simvastatin, worsened insulin resistance. Additionally, significant increases in adipose tissue were observed in rats treated with rosuvastatin, atorvastatin, fluvastatin, and lovastatin [64]. The variations in the existing literature underscore the requirement for additional prospective, randomized controlled trials.
Our study has several strengths. It provides novel insights into the potential impact of statin therapy on pancreatic fat accumulation in patients with T2DM, an area that has not been extensively studied. Additionally, our study utilized magnetic resonance imaging (MRI)-based fat quantification, which is considered one of the most reliable non-invasive methods for assessing pancreatic and hepatic fat content. The inclusion of a well-characterized cohort of T2DM patients with detailed clinical and biochemical assessments further strengthens our findings. Moreover, the use of multivariable regression models to adjust for potential confounders enhances the robustness of our results, allowing for a more nuanced evaluation of the independent associations between statin use and ectopic fat accumulation.
Our study also has several limitations. Firstly, this study was single-centered and had a relatively small sample size, which significantly affected the sample size in the statin subgroups. Secondly, temporal changes in the patients’ lipid profiles and liver and pancreatic fat fractions were not examined. Thirdly, fatty pancreas, a relatively new clinical entity, has not yet had its significance and diagnostic methodologies comprehensively defined, with diagnosis primarily based on an histopathological evaluation. Finally, no evaluation was conducted on additional data related to the patients’ diets or on anthropometric measurements, including muscle and fat assessments.

5. Conclusions

In patients with T2DM, statin use did not show a significant effect on the liver fat fraction, but it caused differences in the pancreatic fat fraction. The observation of a lower pancreatic fat fraction in patients taking a rosuvastatin and atorvastatin dose of 40 mg/day suggests that different types and doses of statins may have varying effects on pancreatic fat accumulation. In the management of T2DM, specific statins may guide personalized treatment strategies by modulating pancreatic lipid metabolism.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/diagnostics15040426/s1, Table S1: Distribution of demographic and clinical characteristics among type 2 diabetes mellitus patients according to types of statin used.

Author Contributions

Conceptualization, M.A.P.; data curation, M.A.P., H.M., B.D., İ.S.M., N.D.A., M.L.Y., Z.B.Ö. and M.K.; formal analysis, M.A.P., M.K., H.M., B.D., İ.S.M., N.D.A., M.L.Y., Z.B.Ö. and M.K.; project administration, M.K.; visualization, M.A.P. and M.K.; writing—original draft preparation, M.A.P.; writing—review and editing, H.M., B.D., İ.S.M., N.D.A., M.L.Y., Z.B.Ö. and M.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This study was performed in accordance with the Declaration of Helsinki and approved by the Health Sciences University Hamidiye Clinical Research Ethics Committee (date: 9 February 2022, decision No: 101412).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Sun, H.; Saeedi, P.; Karuranga, S.; Pinkepank, M.; Ogurtsova, K.; Duncan, B.B.; Stein, C.; Basit, A.; Chan, J.C.N.; Mbanya, J.C.; et al. IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diabetes Res. Clin. Pract. 2022, 183, 109119. [Google Scholar] [CrossRef] [PubMed]
  2. Yapislar, H.; Gurler, E.B. Management of Microcomplications of Diabetes Mellitus: Challenges, Current Trends, and Future Perspectives in Treatment. Biomedicines 2024, 12, 1958. [Google Scholar] [CrossRef]
  3. Jakubiak, G.K.; Chwalba, A.; Basek, A.; Cieslar, G.; Pawlas, N. Glycated Hemoglobin and Cardiovascular Disease in Patients Without Diabetes. J. Clin. Med. 2024, 14, 53. [Google Scholar] [CrossRef]
  4. Huang, P.L. A comprehensive definition for metabolic syndrome. Dis. Model. Mech. 2009, 2, 231–237. [Google Scholar] [CrossRef] [PubMed]
  5. Dhokte, S.; Czaja, K. Visceral Adipose Tissue: The Hidden Culprit for Type 2 Diabetes. Nutrients 2024, 16, 1015. [Google Scholar] [CrossRef]
  6. Oh, Y.H.; Moon, J.H.; Kim, H.J.; Kong, M.H. Visceral-to-subcutaneous fat ratio as a predictor of the multiple metabolic risk factors for subjects with normal waist circumference in Korea. Diabetes Metab. Syndr. Obes. 2017, 10, 505–511. [Google Scholar] [CrossRef]
  7. Eskridge, W.; Cryer, D.R.; Schattenberg, J.M.; Gastaldelli, A.; Malhi, H.; Allen, A.M.; Noureddin, M.; Sanyal, A.J. Metabolic dysfunction-associated steatotic liver disease and metabolic dysfunction-associated steatohepatitis: The patient and physician perspective. J. Clin. Med. 2023, 12, 6216. [Google Scholar] [CrossRef] [PubMed]
  8. Eslam, M.; Newsome, P.N.; Sarin, S.K.; Anstee, Q.M.; Targher, G.; Romero-Gomez, M.; Zelber-Sagi, S.; Wong, V.W.-S.; Dufour, J.-F.; Schattenberg, J.M. A new definition for metabolic dysfunction-associated fatty liver disease: An international expert consensus statement. J. Hepatol. 2020, 73, 202–209. [Google Scholar] [CrossRef]
  9. Canivet, C.M.; Boursier, J.; Loomba, R. New Nomenclature for Nonalcoholic Fatty Liver Disease: Understanding Metabolic Dysfunction-Associated Steatotic Liver Disease, Metabolic Dysfunction-and Alcohol-Associated Liver Disease, and Their Implications in Clinical Practice. Semin. Liver Dis. 2024, 44, 35–42. [Google Scholar] [CrossRef]
  10. Dharmalingam, M.; Yamasandhi, P.G. Nonalcoholic Fatty Liver Disease and Type 2 Diabetes Mellitus. Indian. J. Endocrinol. Metab. 2018, 22, 421–428. [Google Scholar] [CrossRef]
  11. Mika, A.; Macaluso, F.; Barone, R.; Di Felice, V.; Sledzinski, T. Effect of Exercise on Fatty Acid Metabolism and Adipokine Secretion in Adipose Tissue. Front. Physiol. 2019, 10, 26. [Google Scholar] [CrossRef]
  12. Kozawa, J.; Shimomura, I. Ectopic Fat Accumulation in Pancreas and Heart. J. Clin. Med. 2021, 10, 1326. [Google Scholar] [CrossRef]
  13. Imai, Y.; Cousins, R.S.; Liu, S.; Phelps, B.M.; Promes, J.A. Connecting pancreatic islet lipid metabolism with insulin secretion and the development of type 2 diabetes. Ann. N. Y. Acad. Sci. 2020, 1461, 53–72. [Google Scholar] [CrossRef]
  14. Zatterale, F.; Longo, M.; Naderi, J.; Raciti, G.A.; Desiderio, A.; Miele, C.; Beguinot, F. Chronic Adipose Tissue Inflammation Linking Obesity to Insulin Resistance and Type 2 Diabetes. Front. Physiol. 2019, 10, 1607. [Google Scholar] [CrossRef]
  15. Heber, S.D.; Hetterich, H.; Lorbeer, R.; Bayerl, C.; Machann, J.; Auweter, S.; Storz, C.; Schlett, C.L.; Nikolaou, K.; Reiser, M.; et al. Pancreatic fat content by magnetic resonance imaging in subjects with prediabetes, diabetes, and controls from a general population without cardiovascular disease. PLoS ONE 2017, 12, e0177154. [Google Scholar] [CrossRef]
  16. Ahbab, S.; Unsal, A.; Ataoglu, H.E.; Can, T.S.; Kayas, D.; Savas, Y. Prediabetes and Type 2 Diabetes are Independent Risk Factors for Computed Tomography-Estimated Nonalcoholic Fatty Pancreas Disease. Clinics 2019, 74, e1337. [Google Scholar] [CrossRef] [PubMed]
  17. Cerf, M.E. Beta cell dysfunction and insulin resistance. Front. Endocrinol. 2013, 4, 37. [Google Scholar] [CrossRef] [PubMed]
  18. Macauley, M.; Percival, K.; Thelwall, P.E.; Hollingsworth, K.G.; Taylor, R. Altered volume, morphology and composition of the pancreas in type 2 diabetes. PLoS ONE 2015, 10, e0126825. [Google Scholar] [CrossRef] [PubMed]
  19. Steven, S.; Hollingsworth, K.G.; Small, P.K.; Woodcock, S.A.; Pucci, A.; Aribisala, B.; Al-Mrabeh, A.; Daly, A.K.; Batterham, R.L.; Taylor, R. Weight Loss Decreases Excess Pancreatic Triacylglycerol Specifically in Type 2 Diabetes. Diabetes Care 2016, 39, 158–165. [Google Scholar] [CrossRef]
  20. Heni, M.; Machann, J.; Staiger, H.; Schwenzer, N.F.; Peter, A.; Schick, F.; Claussen, C.D.; Stefan, N.; Haring, H.U.; Fritsche, A. Pancreatic fat is negatively associated with insulin secretion in individuals with impaired fasting glucose and/or impaired glucose tolerance: A nuclear magnetic resonance study. Diabetes Metab. Res. Rev. 2010, 26, 200–205. [Google Scholar] [CrossRef]
  21. Fabbrini, E.; Magkos, F.; Mohammed, B.S.; Pietka, T.; Abumrad, N.A.; Patterson, B.W.; Okunade, A.; Klein, S. Intrahepatic fat, not visceral fat, is linked with metabolic complications of obesity. Proc. Natl. Acad. Sci. USA 2009, 106, 15430–15435. [Google Scholar] [CrossRef]
  22. van Raalte, D.H.; Diamant, M. Glucolipotoxicity and beta cells in type 2 diabetes mellitus: Target for durable therapy? Diabetes Res. Clin. Pract. 2011, 93 (Suppl. S1), S37–S46. [Google Scholar] [CrossRef] [PubMed]
  23. Cnop, M. Fatty acids and glucolipotoxicity in the pathogenesis of Type 2 diabetes. Biochem. Soc. Trans. 2008, 36, 348–352. [Google Scholar] [CrossRef] [PubMed]
  24. Chan, T.T.; Tse, Y.K.; Lui, R.N.; Wong, G.L.; Chim, A.M.; Kong, A.P.; Woo, J.; Yeung, D.K.; Abrigo, J.M.; Chu, W.C.; et al. Fatty Pancreas Is Independently Associated With Subsequent Diabetes Mellitus Development: A 10-Year Prospective Cohort Study. Clin. Gastroenterol. Hepatol. 2022, 20, 2014–2022.e2014. [Google Scholar] [CrossRef]
  25. Skudder-Hill, L.; Coffey, S.; Sequeira-Bisson, I.R.; Ko, J.; Poppitt, S.D.; Petrov, M.S. Comprehensive analysis of dyslipidemia states associated with fat in the pancreas. Diabetes Metab. Syndr. 2023, 17, 102881. [Google Scholar] [CrossRef]
  26. Yu, T.Y.; Wang, C.Y. Impact of non-alcoholic fatty pancreas disease on glucose metabolism. J. Diabetes Investig. 2017, 8, 735–747. [Google Scholar] [CrossRef] [PubMed]
  27. Ou, H.Y.; Wang, C.Y.; Yang, Y.C.; Chen, M.F.; Chang, C.J. The association between nonalcoholic fatty pancreas disease and diabetes. PLoS ONE 2013, 8, e62561. [Google Scholar] [CrossRef] [PubMed]
  28. Tushuizen, M.E.; Bunck, M.C.; Pouwels, P.J.; Bontemps, S.; van Waesberghe, J.H.; Schindhelm, R.K.; Mari, A.; Heine, R.J.; Diamant, M. Pancreatic fat content and beta-cell function in men with and without type 2 diabetes. Diabetes Care 2007, 30, 2916–2921. [Google Scholar] [CrossRef]
  29. Yu, X.; Wang, D.; Xiao, W.; Shi, X.; She, Q.; Sun, H.; Qi, T.; Xu, R.; Li, G.; Liu, X.; et al. Relationship between fatty pancreas and hypertriglyceridemic waist phenotype: A cross-sectional study. Sci. Rep. 2020, 10, 21937. [Google Scholar] [CrossRef] [PubMed]
  30. Elnaem, M.H.; Mohamed, M.H.N.; Huri, H.Z.; Azarisman, S.M.; Elkalmi, R.M. Statin Therapy Prescribing for Patients with Type 2 Diabetes Mellitus: A Review of Current Evidence and Challenges. J. Pharm. Bioallied Sci. 2017, 9, 80–87. [Google Scholar] [CrossRef] [PubMed]
  31. Abe, M.; Matsuda, M.; Kobayashi, H.; Miyata, Y.; Nakayama, Y.; Komuro, R.; Fukuhara, A.; Shimomura, I. Effects of statins on adipose tissue inflammation: Their inhibitory effect on MyD88-independent IRF3/IFN-beta pathway in macrophages. Arterioscler. Thromb. Vasc. Biol. 2008, 28, 871–877. [Google Scholar] [CrossRef]
  32. Yamada, Y.; Takeuchi, S.; Yoneda, M.; Ito, S.; Sano, Y.; Nagasawa, K.; Matsuura, N.; Uchinaka, A.; Murohara, T.; Nagata, K. Atorvastatin reduces cardiac and adipose tissue inflammation in rats with metabolic syndrome. Int. J. Cardiol. 2017, 240, 332–338. [Google Scholar] [CrossRef]
  33. Parisi, V.; Petraglia, L.; D’Esposito, V.; Cabaro, S.; Rengo, G.; Caruso, A.; Grimaldi, M.G.; Baldascino, F.; De Bellis, A.; Vitale, D.; et al. Statin therapy modulates thickness and inflammatory profile of human epicardial adipose tissue. Int. J. Cardiol. 2019, 274, 326–330. [Google Scholar] [CrossRef]
  34. Krisnamurti, D.G.B.; Farida, S.; Putri, R.C.; Fachri, W.; Purwaningsih, E.H. The effect of simvastatin-Acalypha indica Linn. combination on the improvement of fatty pancreas in rats induced with a high fructose and cholesterol diet. J. Adv. Vet. Anim. Res. 2022, 9, 346–350. [Google Scholar] [CrossRef] [PubMed]
  35. Raggi, P.; Gadiyaram, V.; Zhang, C.; Chen, Z.; Lopaschuk, G.; Stillman, A.E. Statins Reduce Epicardial Adipose Tissue Attenuation Independent of Lipid Lowering: A Potential Pleiotropic Effect. J. Am. Heart Assoc. 2019, 8, e013104. [Google Scholar] [CrossRef]
  36. Friedewald, W.T.; Levy, R.I.; Fredrickson, D.S. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin. Chem. 1972, 18, 499–502. [Google Scholar] [CrossRef]
  37. Kim, S.H.; Lee, J.M.; Kim, J.H.; Kim, K.G.; Han, J.K.; Lee, K.H.; Park, S.H.; Yi, N.J.; Suh, K.S.; An, S.K.; et al. Appropriateness of a donor liver with respect to macrosteatosis: Application of artificial neural networks to US images—Initial experience. Radiology 2005, 234, 793–803. [Google Scholar] [CrossRef]
  38. Hernaez, R.; Lazo, M.; Bonekamp, S.; Kamel, I.; Brancati, F.L.; Guallar, E.; Clark, J.M. Diagnostic accuracy and reliability of ultrasonography for the detection of fatty liver: A meta-analysis. Hepatology 2011, 54, 1082–1090. [Google Scholar] [CrossRef] [PubMed]
  39. Dasarathy, S.; Dasarathy, J.; Khiyami, A.; Joseph, R.; Lopez, R.; McCullough, A.J. Validity of real time ultrasound in the diagnosis of hepatic steatosis: A prospective study. J. Hepatol. 2009, 51, 1061–1067. [Google Scholar] [CrossRef] [PubMed]
  40. Leiu, K.H.; Poppitt, S.D.; Miles-Chan, J.L.; Sequeira, I.R. Fatty Pancreas and Cardiometabolic Risk: Response of Ectopic Fat to Lifestyle and Surgical Interventions. Nutrients 2022, 14, 4873. [Google Scholar] [CrossRef] [PubMed]
  41. Boicean, A.; Ichim, C.; Todor, S.B.; Anderco, P.; Popa, M.L. The Importance of Microbiota and Fecal Microbiota Transplantation in Pancreatic Disorders. Diagnostics 2024, 14, 861. [Google Scholar] [CrossRef]
  42. Boicean, A.; Birlutiu, V.; Ichim, C.; Brusnic, O.; Onisor, D.M. Fecal Microbiota Transplantation in Liver Cirrhosis. Biomedicines 2023, 11, 2930. [Google Scholar] [CrossRef]
  43. Mahyoub, M.A.; Elhoumed, M.; Maqul, A.H.; Almezgagi, M.; Abbas, M.; Jiao, Y.; Wang, J.; Alnaggar, M.; Zhao, P.; He, S. Fatty infiltration of the pancreas: A systematic concept analysis. Front. Med. 2023, 10, 1227188. [Google Scholar] [CrossRef] [PubMed]
  44. Souza-Mello, V.; Gregorio, B.M.; Relvas-Lucas, B.; da Silva Faria, T.; Aguila, M.B.; Mandarim-de-Lacerda, C.A. Pancreatic ultrastructural enhancement due to telmisartan plus sitagliptin treatment in diet-induced obese C57BL/6 mice. Pancreas 2011, 40, 715–722. [Google Scholar] [CrossRef] [PubMed]
  45. Dutour, A.; Abdesselam, I.; Ancel, P.; Kober, F.; Mrad, G.; Darmon, P.; Ronsin, O.; Pradel, V.; Lesavre, N.; Martin, J.C.; et al. Exenatide decreases liver fat content and epicardial adipose tissue in patients with obesity and type 2 diabetes: A prospective randomized clinical trial using magnetic resonance imaging and spectroscopy. Diabetes Obes. Metab. 2016, 18, 882–891. [Google Scholar] [CrossRef]
  46. Shi, M.; Zhang, H.; Wang, W.; Zhang, X.; Liu, J.; Wang, Q.; Wang, Y.; Zhang, C.; Guo, X.; Qiao, Q.; et al. Effect of dapagliflozin on liver and pancreatic fat in patients with type 2 diabetes and non-alcoholic fatty liver disease. J. Diabetes Complicat. 2023, 37, 108610. [Google Scholar] [CrossRef]
  47. Hummel, J.; Machann, J.; Dannecker, C.; Kullmann, S.; Birkenfeld, A.L.; Haring, H.U.; Peter, A.; Fritsche, A.; Wagner, R.; Heni, M. Eight weeks of empagliflozin does not affect pancreatic fat content and insulin secretion in people with prediabetes. Diabetes Obes. Metab. 2022, 24, 1661–1666. [Google Scholar] [CrossRef] [PubMed]
  48. Zsori, G.; Illes, D.; Ivany, E.; Kosar, K.; Holzinger, G.; Tajti, M.; Palinkas, E.; Szabovik, G.; Nagy, A.; Palko, A.; et al. In New-Onset Diabetes Mellitus, Metformin Reduces Fat Accumulation in the Liver, But Not in the Pancreas or Pericardium. Metab. Syndr. Relat. Disord. 2019, 17, 289–295. [Google Scholar] [CrossRef]
  49. Szczepaniak, L.S.; Victor, R.G.; Mathur, R.; Nelson, M.D.; Szczepaniak, E.W.; Tyer, N.; Chen, I.; Unger, R.H.; Bergman, R.N.; Lingvay, I. Pancreatic steatosis and its relationship to beta-cell dysfunction in humans: Racial and ethnic variations. Diabetes Care 2012, 35, 2377–2383. [Google Scholar] [CrossRef] [PubMed]
  50. Al Quran, T.M.; Bataineh, Z.A.; Al-Mistarehi, A.H.; Zein Alaabdin, A.M.; Allan, H.; Al Qura’an, A.; Weshah, S.M.; Alanazi, A.A.; Khader, Y.S. Prevalence and Pattern of Dyslipidemia and Its Associated Factors Among Patients with Type 2 Diabetes Mellitus in Jordan: A Cross-Sectional Study. Int. J. Gen. Med. 2022, 15, 7669–7683. [Google Scholar] [CrossRef]
  51. Boutari, C.; Pappas, P.D.; Anastasilakis, D.; Mantzoros, C.S. Statins’ efficacy in non-alcoholic fatty liver disease: A systematic review and meta-analysis. Clin. Nutr. 2022, 41, 2195–2206. [Google Scholar] [CrossRef] [PubMed]
  52. Athyros, V.G.; Boutari, C.; Stavropoulos, K.; Anagnostis, P.; Imprialos, K.P.; Doumas, M.; Karagiannis, A. Statins: An Under-Appreciated Asset for the Prevention and the Treatment of NAFLD or NASH and the Related Cardiovascular Risk. Curr. Vasc. Pharmacol. 2018, 16, 246–253. [Google Scholar] [CrossRef] [PubMed]
  53. Lingvay, I.; Esser, V.; Legendre, J.L.; Price, A.L.; Wertz, K.M.; Adams-Huet, B.; Zhang, S.; Unger, R.H.; Szczepaniak, L.S. Noninvasive quantification of pancreatic fat in humans. J. Clin. Endocrinol. Metab. 2009, 94, 4070–4076. [Google Scholar] [CrossRef]
  54. Laakso, M.; Fernandes Silva, L. Statins and risk of type 2 diabetes: Mechanism and clinical implications. Front. Endocrinol. 2023, 14, 1239335. [Google Scholar] [CrossRef]
  55. Kothari, S.; Dhami-Shah, H.; Shah, S.R. Antidiabetic Drugs and Statins in Nonalcoholic Fatty Liver Disease. J. Clin. Exp. Hepatol. 2019, 9, 723–730. [Google Scholar] [CrossRef] [PubMed]
  56. El-Assaad, W.; Joly, E.; Barbeau, A.; Sladek, R.; Buteau, J.; Maestre, I.; Pepin, E.; Zhao, S.; Iglesias, J.; Roche, E.; et al. Glucolipotoxicity alters lipid partitioning and causes mitochondrial dysfunction, cholesterol, and ceramide deposition and reactive oxygen species production in INS832/13 ss-cells. Endocrinology 2010, 151, 3061–3073. [Google Scholar] [CrossRef]
  57. Ishikawa, M.; Okajima, F.; Inoue, N.; Motomura, K.; Kato, T.; Takahashi, A.; Oikawa, S.; Yamada, N.; Shimano, H. Distinct effects of pravastatin, atorvastatin, and simvastatin on insulin secretion from a beta-cell line, MIN6 cells. J. Atheroscler. Thromb. 2006, 13, 329–335. [Google Scholar] [CrossRef]
  58. Climent, E.; Benaiges, D.; Pedro-Botet, J. Hydrophilic or Lipophilic Statins? Front. Cardiovasc. Med. 2021, 8, 687585. [Google Scholar] [CrossRef] [PubMed]
  59. Pastori, D.; Polimeni, L.; Baratta, F.; Pani, A.; Del Ben, M.; Angelico, F. The efficacy and safety of statins for the treatment of non-alcoholic fatty liver disease. Dig. Liver Dis. 2015, 47, 4–11. [Google Scholar] [CrossRef]
  60. Cho, Y.; Lee, H.; Park, H.K.; Choe, E.Y.; Wang, H.J.; Kim, R.H.; Kim, Y.; Kang, E.S. Differential Diabetogenic Effect of Pitavastatin and Rosuvastatin, in vitro and in vivo. J. Atheroscler. Thromb. 2020, 27, 429–440. [Google Scholar] [CrossRef]
  61. Braun, L.R.; Feldpausch, M.N.; Czerwonka, N.; Weiss, J.; Branch, K.; Lee, H.; Martinez-Salazar, E.L.; Torriani, M.; Sponseller, C.A.; Grinspoon, S.K.; et al. Effects of Pitavastatin on Insulin Sensitivity and Liver Fat: A Randomized Clinical Trial. J. Clin. Endocrinol. Metab. 2018, 103, 4176–4186. [Google Scholar] [CrossRef]
  62. Neto-Ferreira, R.; Rocha, V.N.; Souza-Mello, V.; Mandarim-de-Lacerda, C.A.; de Carvalho, J.J. Pleiotropic effects of rosuvastatin on the glucose metabolism and the subcutaneous and visceral adipose tissue behavior in C57Bl/6 mice. Diabetol. Metab. Syndr. 2013, 5, 32. [Google Scholar] [CrossRef] [PubMed]
  63. Chen, Z.Y.; Liu, S.N.; Li, C.N.; Sun, S.J.; Liu, Q.; Lei, L.; Gao, L.H.; Shen, Z.F. Atorvastatin helps preserve pancreatic beta cell function in obese C57BL/6 J mice and the effect is related to increased pancreas proliferation and amelioration of endoplasmic-reticulum stress. Lipids Health Dis. 2014, 13, 98. [Google Scholar] [CrossRef] [PubMed]
  64. Aguirre, L.; Hijona, E.; Macarulla, M.T.; Gracia, A.; Larrechi, I.; Bujanda, L.; Hijona, L.; Portillo, M.P. Several statins increase body and liver fat accumulation in a model of metabolic syndrome. J. Physiol. Pharmacol. 2013, 64, 281–288. [Google Scholar] [PubMed]
Diagnostics 15 00426 g001
Figure 1. For the use of the IDEAL-IQ fat fraction ratio, the areas are marked in the pancreas. The numbered regions correspond to the tail (1), body (2), and head (3) of the pancreas.
Figure 1. For the use of the IDEAL-IQ fat fraction ratio, the areas are marked in the pancreas. The numbered regions correspond to the tail (1), body (2), and head (3) of the pancreas.
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Diagnostics 15 00426 g002
Figure 2. In type 2 diabetes mellitus patients, the distribution of liver and pancreatic fat fractions based on statin usage (A) and the correlation existing between these fractions (B).
Figure 2. In type 2 diabetes mellitus patients, the distribution of liver and pancreatic fat fractions based on statin usage (A) and the correlation existing between these fractions (B).
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Table 1. Demographic and clinical characteristics of patients with type 2 diabetes mellitus.
Table 1. Demographic and clinical characteristics of patients with type 2 diabetes mellitus.
VariablesAll
Population
n = 140		Statin Usep
NoYes
n = 70n = 70
Female gender, n (%)77 (55.0)40 (57.1)37 (52.9)0.610
Age, years56.5 ± 8.255.7 ± 8.757.4 ± 7.50.225
BMI, kg/m231.1 ± 7.630.9 ± 8.031.2 ± 7.30.776
Waist circumference, cm103.4 ± 12.1102.9 ± 11.4103.9 ± 12.80.637
Alcohol use, n (%)19 (13.6)12 (17.1)7 (10.0)0.324
Duration of diabetes, years7.0 (3.2–13.0)6.0 (2.2–12.0)8.0 (5.0–15.0)0.050 *
Comorbidities, n (%)
  Hypertension65 (46.4)26 (37.1)39 (55.7)0.028 *
  Cardiac disease14 (10.0)5 (7.1)9 (12.9)0.260
  Thyroid diseases16 (11.4)7 (10.0)9 (12.9)0.595
  Hyperlipidemia88 (62.9)22 (31.4)66 (94.3)<0.001 *
Anti-diabetic drugs
  Only OADs92 (65.7)46 (65.7)46 (65.7)0.684
  Only insulin4 (2.9)1 (1.4)3 (4.3)
  Combined therapy44 (31.4)23 (32.9)21 (30.0)
Hepatosteatosis, n (%)122 (87.1)64 (91.4)58 (82.9)0.207
Liver fat fraction, %8.5 (4.5–14.7)9.0 (5.1–14.7)8.4 (4.2–14.7)0.572
Pancreatic fat fraction, %7.2 (4.4–11.4)6.2 (4.2–9.3)8.4 (4.7–12.6)0.021 *
Laboratory findings
  Glucose, mg/dL134.5 (107.0–174.5)142.0 (121.0–184.5)130.5 (103.0–161.8)0.060
  Leukocytes, 103/mm37.9 ± 2.27.9 ± 2.57.8 ± 1.90.821
  Platelets, 103/mm3271.5 ± 58.5269.1 ± 58.1273.9 ± 59.20.634
  HbA1-c, %7.5 (6.5–9.0)7.7 (6.6–9.8)7.1 (6.4–8.6)0.073
  Urea, mg/dL30.0 (25.0–34.0)29.0 (25.0–32.0)30.0 (25.0–36.0)0.255
  Creatinine, mg/dL0.8 (0.6–0.9)0.7 (0.6–0.8)0.8 (0.7–0.9)0.035 *
  ALT, U/L18.8 (14.0–25.0)18.1 (14.0–23.0)19.0 (14.5–25.0)0.479
  AST, U/L17.0 (14.0–20.0)16.0 (14.0–18.8)17.0 (15.0–20.7)0.047 *
  ALP, U/L78.0 (65.8–96.0)77.5 (64.0–96.0)79.5 (69.0–95.8)0.298
  GGT, U/L23.0 (16.0–32.0)23.0 (15.2–30.8)24.5 (17.0–35.5)0.216
  Amylase, U/L61.0 (45.5–77.8)54.0 (41.2–82.8)63.0 (54.2–74.0)0.142
  Lipase, U/L30.0 (24.0–41.0)32.5 (23.0–41.5)28.5 (24.4–40.5)0.467
  Cholesterol, mg/dL197.5 ± 58.2221.6 ± 66.5180.4 ± 44.80.002 *
  HDL-C, mg/dL47.7 ± 12.848.4 ± 12.846.9 ± 12.90.495
  LDL-C, mg/dL110.5 (86.0–140.0)119.5 (96.2–142.8)100.0 (78.0–133.8)0.009 *
  Triglycerides, mg/dL142.0 (97.8–195.8)164.0 (101.2–212.2)132.0 (97.2–181.5)0.087
Numerical variables are shown as mean ± standard deviation or median (IQR). Categorical variables are shown as numbers (%). * p < 0.05 shows statistical significance. Abbreviations: ALP, alkaline phosphatase; ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; GGT, gamma-glutamyl transferase, HbA1-c, hemoglobin A1c; OAD, oral anti-diabetic drug; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol.
Table 2. The relationship between demographic characteristics and the fat fractions of the liver and pancreas in patients with type 2 diabetes mellitus.
Table 2. The relationship between demographic characteristics and the fat fractions of the liver and pancreas in patients with type 2 diabetes mellitus.
VariablesLFF (%)PFF (%)
Median (IQR)
or
Correlation Coefficient (r)		pMedian (IQR)
or
Correlation Coefficient (r)		p
Gender
   Female11.3 (6.7–16.7)0.002 *7.0 (4.9–10.3)0.752
   Male6.9 (3.8–11.3)7.4 (3.9–12.5)
Age−0.0030.9750.1670.149
BMI0.310<0.001 *0.0900.292
Waist circumference0.2240.008 *0.1480.082
Alcohol use
   No9.0 (4.4–14.8)0.1917.2 (4.5–11.2)0.966
   Yes6.1 (4.6–11.2)7.5 (3.5–11.6)
Duration of diabetes−0.0450.6010.0740.385
Hypertension
   No7.8 (4.3–13.8)0.2537.1 (4.3–9.7)0.240
   Yes9.8 (5.8–14.7)7.2 (4.5–13.3)
Cardiac disease
   No9.2 (4.6–14.8)0.3707.2 (4.5–10.6)0.367
   Yes8.1 (3.8–10.8)8.3 (4.2–17.3)
Thyroid diseases
   No8.5 (4.7–14.7)0.9587.3 (4.5–11.0)0.888
   Yes10.6 (3.8–15.0)6.6 (4.3–11.5)
Hyperlipidemia
   No10.4 (5.5–14.8)0.5096.7 (4.5–9.2)0.112
   Yes8.4 (4.3–14.5)7.6 (4.4–12.5)
Anti-diabetic drugs
   Only OADs10.5 (6.0–15.3) †0.032 *7.3 (4.3–11.1)0.906
   Only insulin4.8 (3.4–7.1) †7.2 (4.1–9.0)
   Combined therapy7.4 (4.2–13.2) †6.9 (4.5–12.0)
Duration of statin−0.0860.3150.1420.194
Statin use
   No9.0 (5.1–14.7)0.4456.2 (4.2–9.3) †0.004 *
   Atorvastatin8.3 (3.8–13.0)8.7 (5.5–14.9)
   Rosuvastatin8.1 (5.1–16.1)3.2 (2.6–6.6) †
   Pitavastatin14.8 (7.8–20.1)9.2 (3.5–10.2)
Dose of atorvastatin
   10 mg/day8.5 (5.1–13.9)0.009 *8.8 (5.4–15.4)0.042 *
   20 mg/day11.9 (4.4–22.0)9.0 (5.1–13.5)
   40 mg/day4.8 (1.6–8.0) †5.5 (2.8–8.9) †
* p < 0.05 shows statistical significance. † Indicates groups that showed differences in the post hoc analysis. Abbreviations: BMI, body mass index; IQR, interquartile range; LFF, liver fat fraction; PFF, pancreatic fat fraction; OADs, oral anti-diabetic drugs.
Table 3. Relationship between laboratory findings and liver and pancreatic fat fraction in patients with type 2 diabetes mellitus.
Table 3. Relationship between laboratory findings and liver and pancreatic fat fraction in patients with type 2 diabetes mellitus.
VariablesLFFPFF
rprp
Glucose0.1680.1660.0250.836
Leukocytes0.1840.1300.0230.848
Platelets0.1460.232−0.0570.644
HbA1-c0.0160.8990.0130.918
Urea−0.0320.796−0.0250.838
Creatinine−0.1700.161−0.0730.553
ALT0.348<0.001 *0.2280.090
AST0.2200.1020.1490.223
ALP0.2300.0800.484<0.001 *
GGT0.1620.1840.1280.293
Amylase−0.1410.248−0.1660.163
Lipase0.0030.978−0.0670.582
Cholesterol0.1490.222−0.0910.458
HDL-C−0.0460.709−0.1400.252
LDL-C0.0240.844−0.0430.726
Triglycerides0.458<0.001 *−0.0100.933
* p < 0.05 shows statistical significance. Abbreviations: ALP, alkaline phosphatase; ALT, alanine aminotransferase; AST, aspartate aminotransferase; GGT, gamma-glutamyl transferase, HbA1-c, hemoglobin A1c; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; LFF, liver fat fraction; PFF, pancreatic fat fraction; r, correlation coefficient.
Table 4. Independent predictors of liver and pancreatic fat fractions.
Table 4. Independent predictors of liver and pancreatic fat fractions.
VariablesUnivariable RegressionMultivariable Regression
ꞵ ± SE95% CIpꞵ ± SE95% CIp
log(LFF)
   Male gender−0.18 ± 0.06(−0.29)–(−0.06)0.003 *−0.21 ± 0.05(−0.31)–(−0.10)0.007 *
   BMI0.09 ± 0.040.02–0.170.017 *---
   Waist circumference0.06 ± 0.020.01–0.110.009 *0.05 ± 0.020.01–0.090.033 *
   Insulin use−0.17 ± 0.06(−0.29)–(−0.05)0.007 *−0.16 ± 0.05(−0.27)–(−0.06)0.010 *
   log(ALT)0.71 ± 0.150.41–1.01<0.001 *0.67 ± 0.140.40–0.94<0.001 *
   log(Triglyceride)0.50 ± 0.130.24–0.77<0.001 *0.36 ± 0.120.12–0.590.003 *
Adjusted R2 = 0.33, p < 0.001 *
log(PFF)
   Atorvastatin0.19 ± 0.070.05–0.330.001 *0.17 ± 0.060.06–0.280.011 *
   Rosuvastatin−0.18 ± 0.06(−0.30)–(−0.06)0.010 *−0.16 ± 0.07(−0.30)–(−0.02)0.025 *
   Pitavastatin0.21 ± 0.080.05–0.370.008 *0.19 ± 0.070.05–0.330.008 *
   log(ALP)0.44 ± 0.160.11–0.76<0.001 *0.33 ± 0.160.01–0.640.046 *
Adjusted R2 = 0.21, p < 0.001 *
Prior to the regression analysis, logarithmic transformation was applied to numerical variables that did not exhibit a normal distribution. In all multivariable regression models, the effects of age, alcohol use, duration of diabetes, and comorbidities were adjusted. Additionally, in the regression model created for log(PFF), the effects of BMI, waist circumference, and insulin use were adjusted. * p < 0.05 shows statistical significance. Abbreviations: see Table 1, Table 2 and Table 3; ꞵ, regression coefficient; CI, confidence interval; SE, standard error.
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Parlar, M.A.; Mutlu, H.; Doğantekin, B.; Musaoğlu, İ.S.; Albayrakoğlu, N.D.; Yavuz, M.L.; Özbolat, Z.B.; Kaplan, M. The Association of Statin Therapy with Liver and Pancreatic Fat Fraction in Type 2 Diabetes Mellitus. Diagnostics 2025, 15, 426. https://doi.org/10.3390/diagnostics15040426

AMA Style

Parlar MA, Mutlu H, Doğantekin B, Musaoğlu İS, Albayrakoğlu ND, Yavuz ML, Özbolat ZB, Kaplan M. The Association of Statin Therapy with Liver and Pancreatic Fat Fraction in Type 2 Diabetes Mellitus. Diagnostics. 2025; 15(4):426. https://doi.org/10.3390/diagnostics15040426

Chicago/Turabian Style

Parlar, Mehmet Akif, Hakan Mutlu, Betül Doğantekin, İsmail Serhat Musaoğlu, Nisa Demirboşnak Albayrakoğlu, Mustafa Lütfi Yavuz, Zehra Buşra Özbolat, and Mustafa Kaplan. 2025. "The Association of Statin Therapy with Liver and Pancreatic Fat Fraction in Type 2 Diabetes Mellitus" Diagnostics 15, no. 4: 426. https://doi.org/10.3390/diagnostics15040426

APA Style

Parlar, M. A., Mutlu, H., Doğantekin, B., Musaoğlu, İ. S., Albayrakoğlu, N. D., Yavuz, M. L., Özbolat, Z. B., & Kaplan, M. (2025). The Association of Statin Therapy with Liver and Pancreatic Fat Fraction in Type 2 Diabetes Mellitus. Diagnostics, 15(4), 426. https://doi.org/10.3390/diagnostics15040426

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