Dapagliflozin | Deubiquitinase

Evaluation of the effects of dapagliflozin, an SGLT2 inhibitor, on hepatic steatosis and fibrosis by transient elastography in patients with type 2 diabetes and non-alcoholic fatty
liver disease

Running title: Effects of dapagliflozin on hepatic steatosis and fibrosis in T2DM with NAFLD

Masanori Shimizu1§, Kunihiro Suzuki 2§, Kanako Kato1, Teruo Jojima1, Toshie Iijima1, Toshimitsu Murohisa3, Makoto Iijima3, Hidehiro Takekawa4, Isao Usui1, Hideyuki Hiraishi3,
and Yoshimasa Aso1*

1Department of Endocrinology and Metabolism, Dokkyo Medical University, Mibu, Tochigi, Japan
2 Oyama East Clinic, Oyama, Tochigi, Japan

3Department of Gastroenterology, Dokkyo Medical University, Mibu, Tochigi, Japan 4Center of Medical Ultrasonics, Dokkyo Medical University, Mibu, Tochigi, Japan

§Both authors contributed equally to this work.

*Corresponding author: Prof. Y. Aso, Department of Endocrinology and Metabolism,

Dokkyo Medical University, Mibu, Tochigi 321-0293, Japan

Key words: non-alcoholic fatty liver disease, dapagliflozin, transient elastography, liver fibrosis, liver steatosis

Objective

This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/dom.13520

To investigate the effects of dapagliflozin on liver steatosis and fibrosis evaluated in patients with type 2 diabetes and non-alcoholic fatty liver disease (NAFLD).

Research design and methods

In a randomized, active-controlled, open-label trial, 57 patients with type 2 diabetes and NAFLD were randomized to a dapagliflozin (5 mg/day) group (n=33) or to the control group (n=24) and were treated for 24 weeks. Hepatic steatosis and fibrosis were assessed by using a transient elastography (FibroScan) to measure the controlled attenuation parameter (CAP) and liver stiffness measurement (LSM), respectively.
Results

Baseline LSM was positively correlated with several markers and scoring systems for liver fibrosis. In week 24, CAP showed a significant decrease from 31461 to 29073 dB/m (P=0.0424) in the dapagliflozin group, while there was no significant change in the control group. In addition, LSM tended to decrease from 9.496.05 kPa to 8.015.78 kPa in the dapagliflozin group. In 14 patients from this group with LS values 8.0 kPa, indicating significant liver fibrosis, LSM decreased significantly from 14.75.7 to 11.07.3 kPa (P=0.0158). Furthermore, serum alanine aminotransferase and γ-glutamyltranspeptidase levels decreased in the dapagliflozin group, but not in the control group, and visceral fat mass was significantly reduced in the dapagliflozin group.
Conclusions

Based on these findings, the SGLT2 inhibitor dapagliflozin improves liver steatosis in patients with type 2 diabetes and NAFLD, and attenuates liver fibrosis in only patients with significant liver fibrosis, although it cannot denied that weight reduction or VAT by dapagliflozin may be associated with a decrease of liver steatosis or fibrosis.

Key words: non-alcoholic fatty liver disease, dapagliflozin, liver fibrosis, transient elastography, type 2 diabetes

Introduction

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease, affecting 17–46% of the population worldwide (1). Approximately 20–30% of patients with NAFLD also have non-alcoholic steatohepatitis (NASH), which can cause liver fibrosis and progresses to cirrhosis with a risk of hepatocellular carcinoma in 10–20% of patients (2-3). Type 2 diabetes is a major risk factor for NAFLD and/or NASH, since the prevalence of NAFLD is as high as 40– 50% among these patients (4). Early detection of severe steatosis and significant fibrosis would be useful to identify patients who may have aggressive NAFLD and therefore need further evaluation. Since a high proportion of NAFLD patients are asymptomatic for a long period and have normal or only slightly abnormal liver function tests, non-invasive methods for early identification of severe steatosis and advanced fibrosis/cirrhosis are needed (5) to allow early treatment of NAFLD in high-risk patients with type 2 diabetes.
Sodium-glucose co-transporter-2 (SGLT2) inhibitors are a new class of oral antidiabetic drugs that reduce hyperglycemia independently of insulin secretion by promoting the urinary excretion of glucose (6). In patients with diabetes who received treatment with the SGLT2 inhibitor dapagliflozin, the majority of weight loss was accounted for by fat loss, with significantly greater reduction in the volume of both abdominal visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) by dapagliflozin versus placebo (7). There have been some recent reports that SGLT2 inhibitors can suppress the development of NAFLD and/or NASH in rodent models (8-11), and SGLT2 inhibitors have also been shown to improve histological hepatic steatosis or steatohepatitis in obese mice or rats with type 2 diabetes (8-11). However, only two prospective clinical studies have investigated the influence of SGLT2

inhibitors on hepatic steatosis in patients with type 2 diabetes and NAFLD (12, 13), and the anti-fibrotic effect of SGLT2 inhibitors has not been examined in these patients.
Transient elastography is an ultrasound-based method of elastography (14), which allows simultaneous evaluation of hepatic steatosis by measuring the controlled attenuation parameter (CAP) and liver fibrosis by measuring liver stiffness (LS), which is strongly correlated with the stage of liver fibrosis assessed by concurrent liver biopsy (15). Thus, measurement of CAP and LS by transient elastography might be an appropriate screening tool for liver fibrosis and steatosis in patients with diabetes (16, 17), and may be more accurate than biomarkers or scoring systems for detection of significant fibrosis and cirrhosis (18).
Accordingly, we employed transient elastography to determine the effects of dapagliflozin, an SGLT2 inhibitor, on hepatic fibrosis and steatosis in patients with type 2 diabetes and NAFLD.

Research design and methods

We studied 63 patients with type 2 diabetes and NAFLD who were referred to the diabetes outpatient clinic of Dokkyo Medical University Hospital. Patients were eligible for enrollment if they had type 2 diabetes combined with NAFLD, were at least 20 years old, and had a glycated hemoglobin (HbA1c) level of 6.0–12.0% on stable therapy with one to three oral antidiabetic agents with or without insulin for at least 3 months.
This study was performed according to a prospective, randomized, open-label, blinded endpoint design. Patients were randomly allocated at a 1:1 ratio to receive either dapagliflozin or the standard treatment without SGLT2 inhibitors. Randomization was stratified according to sex, age and BMI using the minimization method described by Pocock and Simon. Each patient

was followed for 24 weeks and was reviewed every month. The dose of dapagliflozin was fixed at 5 mg/day, which is the standard dose for treatment of type 2 diabetes in Japan. Throughout
the study, all patients receive standard-of-care treatment for type 2 diabetes and the investigators were encouraged to manage their patients according to local guidelines in order to achieve optimal glycemic control. The control group received standard treatment for type 2 diabetes,
and if the HbA1C target (less than 7.0%) is not achieved after approximately 3 months, up-titration treatment was done with anti-diabetic drugs excluding SGLT2 inhibitors. As
additional anti-diabetic drugs in the control group, 3 patient were newly started with DPP-4 inhibitors, 2 patient with alpha glucosidase inhibitors, 1 patient with glinides, and 1 patient with basal insulin during the study period.
The diagnosis of NAFLD was made on the basis of liver dysfunction (persistent elevation of ALT  the upper limit for our laboratory), the presence of fatty liver on ultrasonography, low daily alcohol intake (less than 30 g for men and less than 20 g for women), and exclusion of other liver diseases such as chronic hepatitis B and C, autoimmune hepatitis, primary biliary cirrhosis, hemochromatosis, and Wilson’s disease. All of the subjects gave informed consent to this study and it was approved by the Institutional Review Board of
Dokkyo Medical University. This study was registered with University Hospital Medical Information Network (UMIN) Clinical Trials Registry (UMIN000022155).

Methods

Transient elastography (TE) was performed using a FibroScan with the standard 3.5 MHz M probe (Echosen, Paris, France) to measure CAP and LS simultaneously in the same cylinder of liver parenchyma (14 cm). CAP is a measure of ultrasonic attenuation at 3.5 MHz on the

FibroScan signal that is used to assess the severity of liver steatosis and is expressed in dB/m (19). FibroScan simultaneously assesses LS by measuring the propagation of an elastic shear wave through the liver parenchyma (20), and it is expressed in kPa with higher values
indicating greater stiffness (13, 19). LS ≥8.0 kPa was shown to indicate significant liver fibrosis in a study of the general French population (15), and this value was used to indicate the existence of liver fibrosis in the present study. The median value of ten measurements represented LS. The intra-assay and inter-assay coefficients of variation (CV) of LS were3.2% and 3.3%, respectively. A scan failure was defined as the inability to obtain 10 valid measurements in a single patient. Fortunately, none of subjects became a scan failure in the present study.
VAT was measured by dual bioelectrical impedance (BIA) analysis using a Dual Scan® (Omron Healthcare Company, Limited, Kyoto, Japan). This instrument calculates the cross-sectional area of intra-abdominal fat (VAT and SAT) at the umbilicus based on
measurement of electrical potentials after application of small electrical currents to two different body spaces (21). VAT measured by the Dual BIA is equal to that measured by abdominal computed tomography, which is the gold standard for determination of VAT (22). The
intra-assay and inter-assay coefficients of variation (CV) of VAT were 6.3% and 6.8%, respectively.
The serum level of HMW adiponectin was measured with our sandwich ELISA employing a monoclonal antibody for human HMW adiponectin, as described previously (23). Serum leptin and type 4 collagen 7S levels were determined by using radioimmunoassay kits (Human leptin RIA kit, Millipore Corporation, St. Louis, MO; type 4 collagen 7S kit, SCETI MEDICAL LABO, Tokyo, Japan). The serum ferritin concentration was measured by an

electrochemiluminescence assay (ECLlusys ferritin, Roche-Diagnostics, Tokyo, Japan), while serum hyaluronic acid was determined by the latex agglutination method (LPIA-ACE HA, LSI Medience, Tokyo, Japan).
The NAFLD fibrosis risk score predicts the severity of hepatic fibrosis based on 6 variables according to the following formula: score = 1.675+0.037  age (years) + 0.094BMI (kg/m2) + 1.13 IFG/diabetes (yes = 1, no= 0) +0.99 AST/ALT ratio 0.013 platelet count (109/l) 0.66 albumin (g/dl). The NAFIC score was also calculated as the sum of the following three clinical variables: serum ferritin ≥200 ng/mL [female] or ≥300 ng/mL [male] =
1 point; serum fasting insulin ≥10 μU/mL = 1 point; and serum type IV collagen 7 s ≥5.0 ng/mL = 2 points. Furthermore, the FIB-4 index was calculated with the following formula: [age ×
AST (units/L)] /platelet count [×109/L] × [ALT (units/L)] 1/2.

Outcomes

The primary endpoint was the change in CAP from baseline to 24 weeks of treatment. The key secondary endpoint was the change in LS from baseline to 24 weeks of treatment, while other secondary endpoints were the change in HbA1c, VAT, liver enzymes (AST, ALT, and GGT), and various markers and scores for hepatic fibrosis.

Statistical analysis

Data are expressed as the mean  SD or as the median with interquartile range. Differences between groups were analyzed by Student’s paired t-test or the unpaired t-test, while between-group differences in non-parametric data were analyzed by Wilcoxon’s matched-pairs test or the Mann-Whitney U test. Correlations were determined by linear

regression analysis or Spearman rank correlation test. Statistical analyses were carried out by using GraphPad Prism 7 software (GraphPad Software, Inc., La Jolla, CA), and P < 0.05 was accepted as indicating statistical significance.
We calculated that a sample of 61 patients were required for 90% power at a significance level of 0.05 to detect a difference in the mean of CAP of 25 on the assumptive SD of 30 (24).

Results

A total of 63 patients were screened and underwent randomization to receive dapagliflozin (n=35) or the standard treatment (n=28; Figure 1). In the dapagliflozin group, 33/35 patients completed the trial, while 24/28 patients completed it in the standard treatment group.
At baseline, the two groups were well balanced with respect to demographic characteristics and laboratory data (Table1).
In the 57 patients who completed the study, baseline CAP was positively correlated with the baseline body weight, BMI, VAT, SCT, HOMA-IR, AST, ALT, and NAFIC score, while CAP showed a negative correlation with the serum level of HMW adiponectin (Supple Table 1). On the other hand, baseline LSM was positively correlated with baseline VAT, AST, ALT, GGT, type 4 collagen 7S, hyaluronic acid, and Mac-2 binding protein. Moreover, LS was closely associated with the three liver fibrosis scores (the FIB-4 index, NAFLD score, and NAFIC score). There was a significant positive correlation between CAP and LSM in all 57 patients (r=0.4199, P=0.0016).
In the dapagliflozin group, VAT, SCT, and body weight all showed a significant decrease at the end of the treatment period, while no changes in these parameters were found in

the standard treatment group (Table 2). HbA1c decreased significantly from 8.37±1.48% at baseline to 7.36±1.22% after 24 weeks of dapagliflozin treatment. HbA1c also decreased in the standard treatment group, but the change was not significant. HOMA-IR showed a significant decrease after 24 weeks in the dapagliflozin group, but not in the standard treatment group. Changes of BMI, VAT, and HbA1c in the control or the dapaglifloizn group were 0.0 (-0.55, 0.50) vs. -0.8 (-1.25, -0.07), -2.0 (-13.0, 6.0) vs. -10.0 (-17.0, 0.5) cm2, and -0.3 (-0.5, 0.5) vs.
-0.8 (-1.3, -0.5)%, respectively.

After 24 weeks, there was a significant decrease in AST, ALT, and GGT in the dapagliflozin group, while there were no changes in liver enzymes in the standard treatment group (Table 2 ). In agreement with previous studies, dagagliflozin trreatment reduced the uric acid level and increased the hematocrit at 24 weeks. HMW adiponectin showed a significant increase at 24 weeks in the dapagliflozin group, but not in the standard treatment group. Serum ferritin was decreased at 24 weeks in the dapagliflozin group,but not in the placebo group. CAP was significantly decreased after 24 weeks in the dapagliflozin group (Fig. 2A), while there was no change in CAP in the standard treatment group, and the percent reduction in CAP from baseline to 24 weeks was significantly larger in the dapagliflozin group than in the standard treatment group (92.418.7 vs. 102.213.2%, P=0.0429) (Fig. 2B). LSM was also decreased after 24 weeks in the dapagliflozin group (9.496.05 kPa to 8.015.78 kPa), but the change was not significant (P=0.0539). We divided the 33 patients who completed dapagliflozin treatment into subgroups with or without significant liver fibrosis, which were stratified according to a baseline LSM 8.0 or <8.0 kPa. As shown in the supplementary Table 2, AST, ALT, and GGT were significantly higher in the patients with significant fibrosis than in those without fibrosis. Serum markers of liver fibrosis and fibrosis scores were also significantly higher in the patients

with significant fibrosis. In the 14 patients with a baseline LSM 8.0kPa, dapagliflozin treatment significantly decreased LSM from 14.75.7 kPa at baseline to 11.07.3 kPa after 24 weeks (P=0.0158; Fig. 2C). Furthermore, the magnitude of percent reduction in LS from baseline to 24 weeks was significantly larger in the dapagliflozin group (14 patients with a baseline LSM8.0kPa) than in the control group (77.9 [55.8, 112] vs. 95.3 [74.5, 135] %, P=0.0479) (Fig. 2D).
Next, we investigated the relations between changes in CAP or LS and those in clinical variables in the dapagliflozin group. We found no significant correlations between changes in CAP and those in body weight, BMI, or VAT in the dapagliflozin group (supple Table 3). There was a significant positive correlation between changes in CAP and those in HbA1c (r=0.4288, P=0.0203). Like CAP, no significant correlations between changes in LSM and those in body weight, BMI, VAT, or HbA1c in the dapagliflozin group (supple Table 3). To identify independent determinants of changes in CAP or LS after treatment with dapagliflozin in
patients with type 2 diabetes and NAFLD, we performed stepwise regression analysis with forward selection that included changes in body weight, VAT, HbA1c, LDL-cholesterol, HDL cholesterol, and ALT. Changes in HbA1c (=0.530, P=0.004) and LDL-C (=0.411, P=0.033) were independent determinants of changes in CAP, while only change in HDL cholesterol was an independent determinant of changes in LSM (=0.417, P=0.030)

Conclusions

This was the first investigation into the effects of the SGLT2 inhibitor dapagliflozin on hepatic steatosis and fibrosis, as evaluated by transient elastography with the FibroScan, in patients with type 2 diabetes and NAFLD. We demonstrated significant improvement in CAP (an indicator of

hepatic steatosis) in the dapagliflozin group after 24 weeks of treatment, while there was no improvement in the control group, and the percent reduction in CAP from baseline to 24 weeks was significantly larger in the dapagliflozin group than in the control group. There has only been one previous prospective investigation into the effect of SGLT2 inhibitors on hepatic steatosis that employed imaging modalities such as ultrasonography and computed tomography (12). In the present study, we investigated the effect of dapagliflozin by measuring CAP, a new quantitative index of hepatic steatosis (19). Recent studies have shown that CAP is significantly correlated with both the percentage of steatosis and the grade of steatosis evaluated by liver biopsy (19, 25). Fat attenuates the propagation of ultrasound, and CAP is determined by quantitation of ultrasonic attenuation at the central frequency of the FibroScan M probe (3.5 MHz) (26). A large-scale prospective study demonstrated the accuracy of CAP for diagnosis of NAFLD (19). In this study, we found a significant correlation of baseline CAP with baseline VAT and with liver function tests (ALT, AST, and GGT), confirming that CAP is a marker of hepatic steatosis. Ito et al. previously reported that treatment with ipragliflozin, another SGLT2 inhibitor, reduced hepatic steatosis, which they evaluated from the liver-to-spleen attenuation ratio on computed tomography (12). Very recently, Kuchay et al. also have demonstrated that empagliflozin reduced liver fat content evaluated by MRI-derived proton density fat fraction (MRI-PDFF) in patients with type 2 diabetes and NAFLD (13). MR elastography or
MRI-PDFF has a better diagnostic accuracy for assessing significant fibrosis that TE, although this technique remains expensive and time-consuming for their implementation in clinical practice for screening liver fibrosis (27). Their results agree with our finding that SGLT2 inhibitor therapy can reduce hepatic steatosis in patients with type 2 diabetes and NAFLD, but the mechanisms underlying improvement of hepatic steatosis (the hepatic triglyceride content)

by dapagliflozin remain to be elucidated. According to a meta-analysis, ≥5% weight loss improved hepatic steatosis and ≥7% weight loss also improved histological findings of NAFLD, although fibrosis was unchanged (28). The present study showed no significant correlation between the change in CAP and the changes in body weight or VAT from baseline to 24 weeks of dapagliflozin treatment, suggesting that dapagliflozin improved liver dysfunction and steatosis by a mechanism unrelated to reduction of VAT or body weight. One possible explanation is that dapagliflozin inhibited de novo lipogenesis in the liver, since our previous study using a mouse model of NASH with diabetes demonstrated significantly lower expression of fatty acid synthase and acetyl-CoA carboxylase 1, two genes involved in de novo lipogenesis (29), in mice treated with empagliflozin than in mice receiving the vehicle or linagliptin (8). Fatty acid synthase is a key enzyme in the hepatic biosynthesis of fatty acids and is believed to determine the maximal liver capacity for producing fatty acids by de novo lipogenesis, because it catalyzes the last step in the fatty acid biosynthetic pathway (29). Thus, dapagliflozin may contribute to improvement of hepatic steatosis in patients with type 2 diabetes and NAFLD by inhibiting fatty acid production through promotion of urinary glucose excretion. However, a
very recent study has investigated the impact of bariatric surgery-induced weight loss on NAFLD by FibroScan in morbidly obese subjects, showing a significant improvement in CAP and LS (30). It therefore cannot be denied that CAP or LS reduction by dapagliflozin may be associated with a reduction in body weight or VAT. On the other hand, since we found a significant positive correlation between changes in CAP and those in HbA1c in the dapagliflozin group, the reduction in CAP may be due to an improvement in glycemic control. A previous study also demonstrated that changes in FPG and HbA1c after treatment with

ipragliflozin were correlated positively with those in fatty liver index in Japanese patients with type 2 diabetes (31).
The present study provided the first evidence that an SGLT2 inhibitor can prevent progression of hepatic fibrosis in patients with type 2 diabetes and NAFLD who have
pre-existing significant liver fibrosis, defined as LSM >8.0 kPa (15). Measurement of LSM by transient elastography was reported to be an easy non-invasive method for reliably estimating the severity of liver fibrosis in patients with type 2 diabetes and NAFLD (17). In addition, LSM was found to be an accurate and reproducible parameter for detecting advanced liver fibrosis in patients with NAFLD that was comparable with liver biopsy (32). In the present study, baseline LSM showed a strong positive correlation with several laboratory markers and scoring systems for liver fibrosis, including type 4 collagen, the FIB-4 index, and the NAFLD fibrosis score. LS ≥8.0 kPa is used as the threshold for excessive stiffness, which indicates clinically important liver disease (15), based on a large-scale study of the general population in France that showed this value was an accurate predictor of liver fibrosis on biopsy (17). Another large
population-based study (the Rotterdam study) showed that 5.6% of the subjects had an LSM

8.0 kPa and that elevation of LSM was strongly associated with diabetes and hepatic steatosis (33). In the present study, LSM decreased in all 33 patients treated with dapagliflozin, although the change was not significant. However, there was significant reduction of LS in the 14
patients with a baseline LSM value ≥8.0 kPa. This suggests that dapagliflozin may attenuate the development of significant liver fibrosis in patients with type 2 diabetes who have significant fibrosis.
The mechanisms leading to improvement of the hepatic fibrosis by dapagliflozin remain unclear. We previously obtained histological evidence that empagliflozin treatment

improved hepatic steatosis and inflammation, as well as fibrosis, in a mouse model of NASH and diabetes (8). These findings suggest that SGLT2 inhibitor therapy may prevent the progression of hepatic fibrosis by reducing inflammation in the liver (8). In fact, serum ferritin was decreased significantly by treatment with dapagliflozin in the present study, and we found a significant positive correlation between the changes in ALT and serum ferritin (r=0.5632, P=0.0010) in the dapagliflozin group. It has been reported that serum ferritin is an independent predictor of histological severity and advanced fibrosis in patients with NAFLD (34),
suggesting that the serum ferritin level may reflect liver inflammation and fibrosis in NAFLD/NASH. Taken together, these results suggest that dapagliflozin may attenuate the development of significant liver fibrosis in high-risk patients with type 2 diabetes and NAFLD.
We acknowledged that the present study has several limitations. A major limitation is that our control group is not a placebo, which may have multiple variations of treatment including varying levels of medication intensification. Second limitation is that we did not perform liver biopsy to confirm liver fibrosis. Although liver biopsy is the gold standard to assess liver fibrosis, there are accumulating evidence that TE by FibroScan is strongly correlated with the stage of liver fibrosis assessed by concurrent liver biopsy (15). Third limitation is the definition of significant liver fibrosis (an LSM ≥8.0 kPa), based on a previous study in the French general population (15), which is probably not representative of Japanese people with type 2 diabetes. Fourth limitation is a potential impact of abdominal obesity on the readings of LSM. In fact, high rate of a scan failure with FibroScan is found in obese subjects, because the thick subcutaneous fat between the probe and liver attenuates the propagation of
shear wave. Fortunately, none of subjects became a scan failure in our study. Fifth limitation is a short period (24 weeks) of our study to see a reduction in liver fibrosis.

In conclusion, this was the first study to investigate the effects of dapagliflozin on hepatic steatosis and fibrosis by in patients with type 2 diabetes and NAFLD. We demonstrated here that dapagliflozin improves both liver steatosis and fibrosis in these patients. It is necessary to keep in mind that weight reduction or VAT by dapagliflozin may be associated with a decrease of liver steatosis or fibrosis. Transient elastography allows identification of patients with type 2 diabetes who are at risk of developing aggressive NAFLD by early detection of severe steatosis and significant fibrosis. It may be possible to prevent the development of liver cirrhosis and/or HCC in these high-risk patients by administration of SGLT2 inhibitors such as dapagliflozin.

Acknowledgments

The authors thank Drs. T. Minaguchi and T. Arisaka, Department of Gastroenterology, Dokkyo Medical University, for their technical assistance.
Conflict of Interest

Y.A. has received speaker fee from AstraZeneca and Ono.

Author Contributions: M.S. and K.S. contributed to the study design, data collection, and drafting the manuscript. K.K. and K.M. helped with data collection. T.J., T.I., M.I., and H.T. contributed to the discussion and reviewed the manuscript. I.U. reviewed/edited the manuscript. Y.A. researched data and wrote and reviewed/edited the manuscript.

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Figure legends Fig. 1
Study design. A total of 57 patients completed the study (33 in the dapagliflozin group and 24 in the control group).

Fig. 2

A.Change in the controlled attenuation parameter (CAP) after treatment with dapagliflozin 5 (mg/day) in patients with type 2 diabetes and NAFLD
B.The magnitude of percent change in the controlled attenuation parameter (CAP) from baseline to 24 weeks of treatment with dapagliflozin (5 mg/day) or the control (standard treatment) in patients with type 2 diabetes and non-alcoholic fatty liver disease (NAFLD). Data are expressed as the meanSD.
C.Change in liver stiffness (LS) after treatment with dapagliflozin 5 (mg/day) in patients with type 2 diabetes and NAFLD who had significant baseline liver fibrosis measurement (LSM 8.0 kPa).
D.The magnitude of percent change in t liver stiffness (LS) from baseline to 24 weeks of treatment with dapagliflozin (5 mg/day) in patients with type 2 diabetes and non-alcoholic fatty liver disease (NAFLD) who had significant baseline liver fibrosis (LSM 8.0 kPa) or the control (standard treatment).

Fig. 1

63 patients with type 2 diabetes and NAFLD enrolled and randomized

Aggressive non-SGLT2i treatment (control) n = 28 Additional treatment with SGLT2i (dapagliflozin) n = 35

Newly added treatment as follows;
All patients: Intensifying diet and exercise 3 patients received DPP-4 inhibitors
2 patients received  glucosidase inhibitors 1 patient received basal insulin
1 patient received glinides
Added 5mg dapagliflozin to preceding therapy

4 patients not completed
•1 patient due to congestive heart failure
•1 patient due to surgery for Charcot joint
•1 patient no longer met study criteria
•1 patient lost to follow-up

24 patients completed the trial

2 patients not completed
•1 patient no longer met study criteria
•1 patient lost to follow-up

33 patients completed the trial

Fig. 2
A B
P = 0 . 0424
P = 0 . 0429

40 0 3 5 0 3 0 0 2 5 0 2 0 0 1 5 0 1 0 0
50
0
1 5 0

10 0

5 0

B e fo re A fte r D a p a g liflo z in C o n tro l

D a p a g liflo z in 5 m g /d a y

C
D

P = 0 .0 1 5 8 P = 0 . 0479

1 5

0
20 0

1 5 0

1 0 0

5 0

D a p a g lifliz in 5 m g /d a y
D a p a g liflo z in
C o n tro l

Table 1. Baseline demographic, clinical, and laboratory data for patients with type 2 diabetes and NAFLD treated with dapagliflozin (5mg/day) or standard therapy (control)
Dapagliflozin Control P value

N (M/F) 33 (19/14) 24 (15/9) 0.7883

Age (years) 56.211.5 57.113.8 0.7823

Body weight (Kg) 73.916.1 76.413.9 0.5521

BMI (Kg/m2) 27.64.7 28.33.5 0.3166

VAT (cm2) 108.742.9 125.738.2 0.1334

SCT (cm2) 249.582.5 226.789.9 0.3501

Body water (kg) 37.39.1 36.86.7 0.8374

Skeletal muscle mass (Kg) 27.87.5 27.15.4 0.7001

FPG (mg/dl) 137.854.0 136.541.2 0.9257

HbA1c (%) 8.371.48 7.701.24 0.0748

HOMA-IR 3.58 (2.41, 6.10) 3.92 (1.96, 5.47) 0.7106

LDL cholesterol (mg/dl) 108.129.5 102.423.6 0.4354

Triglyceride (mg/dl) 120.5 (90.3, 168.3) 108.0 (90.5, 176.8) 0.9052

HDL-cholesterol (mg/dl) 49.712.8 46.112.2 0.2934

AST (U/L) 28.0 (20.5, 49.8) 26.0 (20.3, 32.0) 0.4652

ALT (U/L) 38.0 (21.5, 61.0) 33.0 (24.5, 46.5) 0.5187

GGT (U/L) 47.0 (28.0, 88.3) 37.5 (20.0, 62.3) 0.1799

Uric acid (mg/dl) 4.831.24 5.161.33 0.3072

Albumin (g/dl) 4.320.42 4.320.34 0.9921

Hematocrit (%) 44.33.9 44.23.7 0.9415

Platelets (109/mL) 24.16.4 27.88.1 0.0609

eGFR (ml/min/1.73m2) 79.415.8 76.919.0 0.5881

Leptin (ng/mL) 9.75 (6.20, 17.4) 13.0 (8.33, 25.5) 0.2240

HMW adiponectin (g/ml) 1.08 (0.56, 4.11) 1.31 (0.44, 2.53) 0.4959

Ferritin (ng/ml) 82.1 (33.1, 177.5) 69.8 (30.0, 157.8) 0.6705

Type 4 collagen 7S (ng/ml) 4.401.30 3.710.91 0.0316

Hyaluronic acid (ng/ml) 31.4 (20.9, 60.4) 28.2 (18.6, 51.) 0.3938

Mac-2 binding protein 0.71 (0.41, 1.10) 0.59 (0.45, 0.81) 0.2643

Fib-4 index 1.32 (0.74, 2.10) 0.98 (0.62, 1.33) 0.0860

NAFLD fibrosis score -0.66 (-1.91, -0.05) -1.43 (-2.56, -0.45) 0.1719

NAFIC score 1.00 (0.00, 2.00) 1.00 (0.00, 1.00) 0.2338

CAP (dB/m) 314.161.0 306.034.3 0.5659

LSM (kPa) 7.20 (5.22, 13.6) 6.10 (4.83, 9.43) 0.2102

Metformin/DPP-4i/SU/Ins 31/16/12/10 21/14/11/4 0.6413

Data are the meanSD or the median and inter-quartile ranges.

γ-glutamyltranspeptidase; eGFR, estimated glomerular filtration; HMW, high-molecular weight; CAP, controlled attenuation parameter; LSM, liver stiffness measurement; DPP-4i , dipeptidyl peptidase-4 inhibitors; SU, sulfonylurea; Ins, insulin..

Table 2. Changes in clinical parameters, hepatic steatosis and fibrosis, and mean differences between groups in type 2 diabetic and NAFLD patients

treated with dapagliflozin (the dapagliflozin groups) or those with standard treatment (the control group).

Dapagliflozin Control Difference b/w groups

baseline Week 24 P value baseline Week 24 P values P-value

N 33 33  24 24 

Body weight (Kg) 73.6 (61.9, 80.8) 70.7 (60.0, 79.2) 0.0004 76.413.8 75.812.8 0.4911 0.0375

BMI (kg/m2) 27.6±4.7 26.9±5.0 0.0006 28.7±3.5 28.6±3.6 0.4930 0.0513

VAT (cm2) 108.742.9 101.439.2 0.0068 125.732.2 120.040.1 0.1795 0.3692

SCT (cm2) 226.790.0 215.580.6 0.0354 249.582.5 250.891.3 0.6991 0.6205

Total boy water (Kg) 37.39.1 36.29.5 0.0057 36.86.7 36.56.4 0.9762 0.0286

Skeletal muscle mass (Kg) 27.87.5 26.97.8 0.0580 27.15.4 26.85.0 0.3828 0.0060

FPG (mg/dl) 137.8±54.0 122.5±35.2 0.1057 136.5±41.2 144.3±45.5 0.2218 0.2964

HbA1c (%) 8.37±148 7.36±1.22 <0.0001 7.70±1.24 7.22±1.11 0.1414 0.0949

HOMA-IR 3.58 (2.41, 6.10) 2.66 (1.49, 4.85) 0.0076 3.92 (1.96, 5.47) 3.56 (2.17, 5.78) 0.9240 0.0407

LDL-C (mg/dl) 108.1±29.5 109.4±32.1 0.6398 102.4±23.6 109.3±23.5 0.2842 0.8232

TG (mg/dl) 132.654.7 117.548.2 0.0842 144.892.5 141.784.6 0.3512 0.3821

AST (U/L) 28.0 (20.5, 49.8) 27.5 (17.3, 31.8) 0.0018 29.812.8 27.49.6 0.3353 0.0837

ALT (U/L) 38.0 (21.5, 61.0) 26.5 (16.3, 42.5) <0.0001 33.0 (24.5, 46.5) 32.0 (25.0, 49.3) 0.4493 0.0212

GGT (U/L) 47.0 (28.0, 88.3) 27.0 (20.5, 61.5) 0.0003 37.5 (20.0, 62.3) 32.0 (22.3, 50.0) 0.4584 0.0041

Albumin (g/L) 4.320.42 4.480.35 0.0127 5.161.33 5.121.23 0.7527 0.2829

Uric acid (mg/dl) 4.801.24 4.461.20 0.0236 5.161.33 5.121.23 0.7527 0.1549

Hematocrit (%) 44.33.9 45.64.3 0.0002 44.23.7 44.83.2 0.3864 0.0945

Platelets (109/mL) 24.16.4 24.18.0 0.2278 27.88.1 28.210.0 0.8350 0.4705

eGFR (ml/min/1.73m2) 79.415.8 82.317.1 0.1435 76.919.0 80.824.0 0.1586 0.8900

HMW adiponectin (g/ml) 1.08 (0.56, 4.11) 1.62 (0.91, 4.67) 0.0002 1.31 (0.44, 2.53) 1.79 (0.39, 2.55) 0.3894 0.0045

Leptin (ng/ml) 9.75 (6.20, 17.4) 10.8 (7.73, 15.7) 0.7243 13.0 (8.3, 25.5) 15.2 (9.7, 24.7) 0.2453 0.9772

Ferritin (ng/ml) 79.5 (32.4, 150) 46.5 (22.6, 106) <0.0001 63.0 (30.0, 157.8) 76.7 (36.3, 116.0) 0.7270 0.0037

Type 4 collagen 7S (ng/ml) 4.00 (3.53, 4.90) 4.00 (3.32, 4.78) 0.4707 3.710.91 4.151.06 0.0295 0.0222

Hyaluronic acid (ng/ml) 31.4 (20.9, 60.4) 30.6 (21.3, 78.2) 0.8941 28.2 (18.6, 51.8) 30.7 (20.1, 64.3) 0.5392 0.6274

Mac-2 binding protein 0.71 (0.41, 1.10) 0.68 (0.47, 1.00) 0.3543 0.650.27 0.670.29 0.9335 0.9861

Fib-4 index 1.32 (0.74, 2.10) 1.27 (0.77, 1.91) 0.7207 1.110.64 1.170.70 0.9286 0.9155

NAFLD fibrosis score -0.66 (-1.91, -0.05) -0.78 (-1.66, -0.22) 0.2988 -1.41(-2.50, -0.46) -1.12 (-2.24, -0.40) 0.5226 0.2923

NAFIC score 1.0 (0.0, 2.0) 0.0 (0.0, 1.0) 0.2026 1.0 (1.0, 4.0) 1.0 (1.0, 4.0) 0.7930 0.5301

LSM (kPa) 9.496.05 8.015.78 0.0539 Data are presented as the mean  SD or as the median and interquartile range.
7.403.76 7.854.18 0.8655 0.2217

NAFLD, non-alcoholic fatty liver disease; BMI, body mass index; VAT, visceral adipose tissue; SCT, subcutaneous adipose tissue; FPG, fasting plasma glucose; Hb, hemoglobin; HOMA-IR, homeostasis model assessment of insulin resistance; L ; LDL, low-density lipoprotein; HDL, high-density lipoprotein; AST, aspartate aminotransferase; ALT, alanine transaminase; GGT, γ-glutamyltranspeptidase; eGFR, estimated glomerular filtration; HMW, high-molecular weight; CAP, controlled attenuation parameter; LSM, liver stiffness measurement.