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Introduction

Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease worldwide. It affects up to 30% of adults in Western countries and 15% in Asian countries and also an increasing number of children (1). NAFLD is a clinical syndrome characterized by the accumulation of excess fat in the liver. It spans a spectrum of disease from pathological accumulation of triglyceride (TG), steatosis, to an inflammatory response, non-alcoholic steatohepatitis (NASH) (2). NASH may progress to cirrhosis, cirrhosis complications, liver failure and an increased risk of liver cancer (3). NAFLD is the third cause of liver transplantation in the United States (4).

NAFLD is becoming a major health issue worldwide, not only for its prevalence, but also for its metabolic complications. The underlying insulin resistance is associated with hypertension, hyperlipidemia, cardiovascular disease, type 2 diabetes mellitus (T2DM), chronic kidney disease and recently with carotid atherosclerosis (5–7). Therapeutic options are limited, there is no pharmacological therapy and managing NAFLD focuses on the treatment of risk factors.

The polyphenol resveratrol (RSV) is a potential therapeutic candidate. RSV is a stilbenoid and a phytoalexin produced by several plants in response to injury or when the plant is under attack by pathogens such as bacteria or fungi (8). It is found mainly in Japanese knotweed, red grapes and in other plants, in low concentrations (8). During the last decades, the potential of RSV has been explored. It has pleiotropic effects in various tissues. RSV is an activator of adenosine monophosphate-activated kinase (AMPK) and silent information regulation 2 homolog 1 (SIRT1). The two proteins have a critical role in aiding fat breakdown and removal from the liver, associated with liver diseases such as fibrosis and cirrhosis (9). Through the activation of AMPK and SIRT1 in hepatic cells and anti-oxidant and anti-inflammatory actions, RSV may prevent liver damage and may inhibit the progression of NAFLD (10,11).

Through clinical practice, it has been found that, in patients who suffer from arterial hypertension and elevated hepatic enzymes, treated with anti-hypertensive drugs and a strong antioxidant, such as micronized trans-resveratrol, hepatic enzymes were significantly improved. Thus, it was decided to start a clinical trial regarding the effect of micronized trans-resveratrol in patients with Non-alcoholic fatty liver disease (NAFLD).

In the present study, 50 or 200 mg RSV (Evelor and Evelor H, a food supplement manufactured by Agetis Supplements Ltd., Cyprus) was added to the standard treatment of patients with NAFLD daily for a period of 6 months and the therapeutic efficacy of RSV was investigated.

Materials and methods

Patient characteristics

The study was approved by the Ethics Committee of Cyprus (file no. ΕΕΒΚ/ΕΠ/2010/12, date 06/06/2013). All the patients who participated were volunteers and they were asked to fill out a written consent form.

The patients were selected after they had initially been diagnosed with non-alcoholic fatty liver disease. The primary inclusion criterion was evidence of fatty liver on ultrasonography (US), which is the most commonly used imaging technique with remarkable sensitivity.

The US findings in non-alcoholic fatty liver disease are: i) Diffuse enhancement of near field echo in the hepatic region (stronger than in the kidney and in the spleen region) and gradual attenuation of the far field echo, ii) unclear display of intra-hepatic lacuna structure, iii) mild to moderate hepatomegaly with a round and blunt border, and iv) unclear display of right liver lobe and diaphragm (12).

The study excluded patients with one or more of the following features: i) Any known causes of steatosis, ii) cirrhosis, ii) malignant tumor or any other diseases which significantly decrease the patient's lifespan, iii) symptoms of heart failure or acute coronary syndrome, iv) chronic kidney disease, v) psychiatric disorders, vi) participating in other similar studies or participating in other studies that were completed in the last 6 months, and vii) using food supplements, they should stop the supplement and wait for two weeks before participating in the study.

Equipment used

A GE LogIQ5 expert Ultrasound Machine (General Electric, CA, USA), equipped with Ultrasound Transducer Probe (GE 3.5C model 2050357) was used. The equipment can measure the Echo Level (EL) at specific areas and depths. EL measures the mean intensity of pixels within a user-defined area (region of interest). Raw data provide the average sum (intensity per pixel)/pixels. The ultrasound depicts on screen the area (in cm2), mean (intensity dB) and standard deviation (dispersion). Phantom Model 040GSE (CIRS-Multi Purpose, Multi Tissue u/s Phantom) was used to calibrate the LogIQ5 machine. The specific phantom simulates the human liver and kidney organs and serves for calibration.

Regarding the parameters ‘liver/kidney value’ and ‘liver/kidney depth’, we used the same methodology used by Xia et al (13). The procedure was as follows: An experienced radiologist, who was unaware of the patient's clinical details and laboratory findings, performed ultrasound studies. All the instrument settings, including gain and depth were fixed for each measurement. For assessment of the ultrasound Hepatic/Renal echo value, ultrasound images with both liver and right kidney clearly visualized were obtained in the sagittal liver/right kidney view in the lateral position. A region of interest (ROI) was carefully selected excluding blood vessels, bile ducts and other focal hypoechoic or hyperechoic regions. Another ROI was identified in the right renal cortex with no large vessels, renal sinus or medulla. To avoid the interference of depth-dependent echo-intensity attenuation and the borderline echo distorting effects, the boundary between liver and right kidney area was placed near the center of the image, and the liver and right kidney ROIs were selected at the same depth of the ultrasound images. The gray scale mean value of the pixels within the two ROIs was used as measurement of echo intensity, followed by subtraction of the average hepatic gray scale by the average renal cortex gray scale to calculate the US hepatic/renal value.

Standardization of ultrasound quantitative parameters was performed using an abdominal phantom.

Method of calculation

Attenuation measurements were taken at 2 depths, at the ROI xxcm (liver) and yycm (kidney). Attenuation was calculated by subtracting the EL (liver)-EL (kidney)=Hepato-Renal Index Difference. EL was measured in dB and was linear to the intensity; thus, linear regression was employed to compute normalized values (14).

US hepatic/renal echo value

In sagittal liver/right kidney view, an ROI of 1.5×1.5 cm (1,296 pixels) in the liver parenchyma was selected. The ROI had to be as uniform as possible, excluding blood vessels, bile ducts, and other focal hypo/hyper echogenicity. Another ROI of 0.5×0.5 cm (144 pixels) was identified in the right renal cortex with no large vessels, renal sinus or medulla. To avoid the interference of depth-dependent echo-intensity attenuation and the borderline echo distorting effects, the boundary between liver and right kidney area was placed near the center of the image, and the liver and right kidney ROIs were selected at the same depth of the ultrasound images. The gray scale mean value of the pixels within the two ROIs was used as measurement of echo intensity. Then we subtracted the average hepatic gray scale from the average renal cortex gray scale to calculate the US hepatic/renal value.

US hepatic echo-intensity attenuation rate

In the right intercostal view at the anterior axilla line, a tangent line of the sector ultrasound image was drawn and the ultrasound wave transmission line was determined, starting from the point of tangency and perpendicular to the tangent line. Two ROIs of 1.5×1.5 cm (1,296 pixels) were selected in liver homogeneous regions along the ultrasound transmission line near the liver anterior margin (depth, 4–6 cm) and the liver posterior margin, respectively. The linear distance between the two ROIs was also measured. The echo intensity of the ultrasound wave was attenuated exponentially, as shown in the equation:

where A0 and Ad are the ultrasound echo intensity at the sound source and the liver parenchyma at a specific depth, respectively; a is the attenuation coefficient of the liver parenchyma; f is the frequency of the ultrasound detector; d is the depth of ROI.

The ratio of the average echo intensity in the liver near-field ROI to liver far-field ROI was then calculated based on the equation 1:

where An and Af are average ultrasound echo intensity in the near-field ROI and the far-field ROI, respectively; a and f have been defined in equation 1; dn and df are the depth of liver near-field and far-field ROIs.

Then the formula for ultrasound hepatic echo-intensity attenuation rate was deduced from the equation 2:

where Δd is the distance between the near-field and far-field ROIs, and other parameters are defined in equation 2.

Standardization of ultrasound quantitative parameters

To standardize the measured values of US H/R value and hepatic echo-intensity attenuation rate among different ultrasound machines, a 3D abdominal phantom, containing mimic abdominal organs, was used for standardization in this research.

Treatment method

Participants underwent clinical examination, electrocardiogram and abdominal ultrasound. Blood tests were carried out and the following parameters were measured: Serum glutamic pyruvic transaminase (SGPT), serum glutamic oxaloacetic transaminase (SGOT), alkaline phosphatase (ALP), gamma-glutamyl transpeptidase (g-GT), glucose, total cholesterol levels, high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglycerides (TG), insulin, insulin resistance, liver value, liver depth, kidney value, kidney depth and difference liver-kidney values.

Then, the patients were divided into two groups (randomly assigned) according to the treatment administered: 22 patients were given treatment A (Evelor, 50 mg RSV) and 22 patients were given treatment B (Evelor H, 200 mg RSV). The observation period lasted for 6 months. There was a clinical examination, blood tests and an abdominal ultrasound at the beginning of the study (time 1) and in 6 months (time 2). All the patients were on low fat diet and were followed up by a nutritionist.

The results obtained by the study were used to examine the following parameters: i) The count of hepatic enzymes, ii) insulin resistance, and iii) liver fat.

Statistical analysis

Two-way ANOVA and Bonferroni post-hoc test, with interaction (time and group) was used to determine whether there were differences among dose levels, time levels and a possible interaction among them. However, we did not discover any significant interactions and we used standard two-way ANOVA without interactions. Moreover, an independent t-test was conducted to examine whether there were any differences between the values of physiological parameters at the beginning and the end of the study. P<0.001 was considered to indicate a strongly statistically significant difference. The statistical program used for statistical analysis was R3.2.1.

Results

Subjects

A total of 44 patients participated in the study; 28 men and 16 women from the ages of 29 to 70 with a mean weight of 84.6 kg. The patients were divided into two groups of 22 individuals each, according to the treatment administered: Group A was treated with micronized trans-Resveratrol 50 mg (Evelor), and Group B was treated with micronized trans-Resveratrol 200 mg (Evelor H). Measurements were made at the beginning (time 1) and after 6 months (time 2) to compare results between the two different dose groups as well as within the group itself. Tables I and II contain summary statistics for all the participants in the study with a focus on the main patient demographics including age, weight and height.

Table I. Main demographic variables.

Table I.

Main demographic variables.

Variables	Mean	SD	Median	Minimum	Maximum
Age (years)	54.16	9.92	55	29	70
Weight (kg) at time 1	84.55	11.42	83.30	58	105
Weight (kg) at time 2	82.33	11.73	80	57	103
Height (cm)	170	7	170	155	183
BMI (kg/cm2) at time 1	27.01	3.02	28	20	31
BMI (kg/cm2) at time 2	27.93	3.35	28.50	21	35

[i] BMI, body mass index.

Table II. Classification of the participants by sex and treatment.

Table II.

Classification of the participants by sex and treatment.

Sex/Dose	50 mg RSV	200 mg RSV
Male	12	16
Female	10	6

[i] RSV, resveratrol.

Table III shows the mean values of all the variables in the beginning (time 1) and after 6 months (time 2) of the study and the results of comparisons among different time-points for those participants in the 50 mg group. We obtained the following conclusions: i) There were strongly significant differences among liver values that were initially at 55.20. In fact, the liver values decreased (time 2) resulting in a P-value of <0.001. ii) There were strongly significant differences among kidney values that were initially at 32.49. In fact, the kidney values decreased (time 2) resulting in a P-value of <0.001. iii) There were significant differences among insulin resistance that were initially at 1405.81. In fact the insulin resistance values decreased (time 2) resulting in a P-value of 0.135.

Table III. Statistical comparisons based only on 50 mg (Evelor) dose across time.

Table III.

Statistical comparisons based only on 50 mg (Evelor) dose across time.

Variables	Mean at Time 1	Mean at Time 2	t-test (P-value)
SGPT	36.09	37.24	0.871
SGOT	24.95	26.33	0.603
ALP	63.63	59.23	0.593
g-GT	30.95	27.00	0.770
GLU	105.95	96.57	0.122
CH	194.50	185.67	0.656
HDL	48.60	47.67	0.905
LDL	119.45	116.19	0.932
TG	132.50	109.76	0.301
Insulin	13.58	12.69	0.206
Insulin resistance	1405.81	1226.04	0.135
Liver value	55.20	45.42	<0.001
Liver depth	5.60	5.79	0.034
Kidney value	32.49	28.42	<0.001
Kidney depth	7.06	7.30	0.008
Difference L-K value	22.71	17.00	0.170

[i] SGPT, serum glutamate pyruvic transaminase; SGOT, serum glutamic oxaloacetic transaminase; ALP, alkaline phosphatase; g-GT, gamma-glutamyl transpeptidase; GLU, glucose; HDL, high-density lipoprotein; LDL, low-density lipoprotein; TG, triglycerides.

Table IV contains the mean values of all the variables in the beginning (time 1), and after six months (time 2) of the study, the results of comparisons among different time-points for those participants in the 200 mg group. We obtained the following conclusions: i) There were strongly significant differences among liver values that were initially at 58.77. In fact, the liver values decreased (time 2) resulting in a P-value of <0.001. ii) There were strongly significant differences among kidney values that were initially at 32.30. In fact, the kidney values decrease (time 2) resulting in a P-value of <0.001. iii) There were significant differences among insulin resistance that were initially at 1541.04. In fact the insulin resistance values decrease (time 2) resulting in a P-value of 0.151.

Table IV. Statistical comparisons based only on 200 mg (Evelor H) dose across time.

Table IV.

Statistical comparisons based only on 200 mg (Evelor H) dose across time.

Variables	Mean at Time 1	Mean at Time 2	t-test (P-value)
SGPT	47.05	41.70	0.631
SGOT	32.81	30.90	0.887
ALP	74.50	71.20	0.804
g-GT	29.20	25.35	0.434
GLU	121.18	112.50	0.786
CH	194.27	181.15	0.258
HDL	41.14	41.70	0.832
LDL	118.75	105.95	0.408
TG	205.13	167.80	0.465
Insulin	12.62	13.01	0.091
Insulin resistance	1541.04	1489.52	0.151
Liver value	58.77	43.33	<0.001
Liver depth	5.20	5.63	0.792
Kidney value	32.30	25.21	<0.001
Kidney depth	7.04	7.26	0.795
Difference L-K value	26.46	18.115	0.795

[i] SGPT, serum glutamate pyruvic transaminase; SGOT, serum glutamic oxaloacetic transaminase; ALP, alkaline phosphatase; g-GT, gamma-glutamyl transpeptidase; GLU, glucose; HDL, high-density lipoprotein; LDL, low-density lipoprotein; TG, triglycerides.

Table V contains the comparisons among groups and different time points for all participants in the study. We used a two-way ANOVA model with interaction to test whether there are differences among dose levels, time levels and possible interaction among them. We obtained the following conclusions: i) There are strongly significant differences between liver values and kidney values across the time, interaction between time and dose (p-value) 0.383 for liver value and 0.778 for kidney value. Both of these measurements decreased (time 2). ii) The difference between liver and kidney values decreased as time progressed. iii) There were statistically significant differences between the two dose levels for ALP and TG (P<0.05). iv) There were significant differences between the dose levels for SGOT, glucose and HDL.

Table V. Statistical comparisons based on different doses and across time.

Table V.

Statistical comparisons based on different doses and across time.

Variables	Time effect (P-value)	Dose effect (P-value)	Interaction between time and dose (P-value)
SGPT	0.842	0.052	0.576
SGOT	0.991	0.022	0.686
ALP	0.563	<0.001	0.883
g-GT	0.567	0.377	0.798
GLU	0.336	0.005	0.963
CH	0.215	0.563	0.863
HDL	0.983	0.004	0.764
LDL	0.479	0.190	0.697
TG	0.183	<0.001	0.898
Insulin	0.027	0.782	0.887
Insulin resistance	0.021	0.179	0.914
Liver value	<0.001	0.621	0.383
Liver depth	0.136	0.821	0.376
Kidney value	<0.001	0.287	0.778
Kidney depth	0.051	0.330	0.350
Difference L-K value	0.001	0.681	0.424

[i] SGPT, serum glutamate pyruvic transaminase; SGOT, serum glutamic oxaloacetic transaminase; ALP, alkaline phosphatase; g-GT, gamma-glutamyl transpeptidase; GLU, glucose; HDL, high-density lipoprotein; LDL, low-density lipoprotein; TG, triglycerides.

Based on the fact that there was no interaction between dose and time for all variable considered, we also implemented a two-way ANOVA model but without interaction. Table VI contains the comparisons among groups and different time points for all the participants in the study.

Table VI. Statistical comparisons based on different doses and across time.

Table VI.

Statistical comparisons based on different doses and across time.

Variables	Time effect (P-value)	Dose effect (P-value)
SGPT	0.841	0.051
SGOT	0.991	0.022
ALP	0.556	<0.001
g-GT	0.563	0.374
GLU	0.330	0.004
CH	0.211	0.460
HDL	0.983	0.004
LDL	0.475	0.187
TG	0.179	<0.001
Insulin	0.025	0.781
Insulin resistance	0.020	0.176
Liver value	<0.001	0.621
Liver depth	0.136	0.821
Kidney value	<0.001	0.284
Kidney depth	0.051	0.331
Difference L-K value	0.001	0.681

[i] SGPT, serum glutamate pyruvic transaminase; SGOT, serum glutamic oxaloacetic transaminase; ALP, alkaline phosphatase; g-GT, gamma-glutamyl transpeptidase; GLU, glucose; HDL, high-density lipoprotein; LDL, low-density lipoprotein; TG, triglycerides.

The results show the same conclusions as in the case of a model that includes interactions: i) There were strongly statistically significant differences between Liver value and Kidney value across time. Both of these measurements, liver value and kidney value decreased (time 2). ii) The difference liver-kidney decreased as time progressed. iii) There were statistically significant differences between the two dose levels for ALP and TG. iv) There are significant differences between the dose levels for SGOT, glucose and HDL.

Discussion

Liver is an important organ because of its unique metabolism. Its main function is to take up nutrients, to store and/or provide them to the other organs. At the same time, it is a clearance and recycling organ. That means it is also a frequent target for a number of toxicants. The resulting hepatic injury is characterized by leakage of cellular enzymes into the blood stream. Elevation of SGPT, SGOT, g-GT in the blood often reflects hepatocellular damage (15,16).

Normal ranges of SGOT/SGPT in blood are 5–40 or 7–56 U/l and these are sensitive indicators of liver damage from different types of diseases. SGPT is primarily located in the liver and represents more specifically an injury to the organ as compared to SGOT, which is found in decreasing order of concentration in liver, cardiac muscle, skeletal muscle, kidneys, lungs, and brain.

Gamma-GT normal range in blood is 5–55 U/l. It is primarily present in kidney, liver, and pancreatic cells. Small amounts are present in other tissues. Even though renal tissue has the highest level of g-GT, the enzyme present in the serum appears to originate primarily from the hepatobiliary system, and g-GT activity is elevated in any and all forms of liver disease. It is currently the most sensitive enzymatic indicator of liver disease (17).

The common causes of elevated SGPT, SGOT, g-GT are alcohol abuse, drugs, chronic hepatitis B and C, autoimmune hepatitis, congenital metabolic disorders and fatty liver disease. In the United States, the majority of unexplained cases of elevated transaminases are strongly associated with non-alcoholic fatty liver disease (NAFLD) (18).

NAFLD is the most common form of chronic liver disease and a major health burden in developed countries with a prevalence of up to 30% (19). Two thirds of the patients are asymptomatic. It is characterized by the accumulation of triglycerides in the liver and spans a histological spectrum of liver disease, ranging from simple steatosis to steatohepatitis, fibrosis and rarely to cirrhosis or even hepatocellular carcinoma (20). It was considered to be a benign condition, but is now recognized as an important cause of liver-related morbidity and mortality (20).

Recent studies have shown an association between NAFLD and metabolic syndrome, as it seems to have a common pathogenic factor, insulin resistance (IR) (21). Major expressions of NAFLD are diabetes mellitus type II and obesity. NAFLD has also been associated with acute starvation, total parenteral nutrition, abdominal surgery, use of several drugs and chemicals, and rare metabolic disorders (19). Depending on the pathogenesis, NAFLD is classified as, primary NAFLD associated with insulin resistance and secondary NAFLD associated with other conditions (22).

Although clinical studies have tried several pharmacological treatments, there is currently no satisfactory therapy for NAFLD. Therefore, investigators focus on the management of metabolic syndrome (22). Previous findings demonstrated that, weight loss by calorie restriction (CR), improves insulin resistance and fatty acid metabolism (23,24) and it is the only effective treatment for NAFLD. However, the long-term adherence to lifestyle modifications is hard. Alternative treatments are therefore required.

Natural polyphenols are a potential therapeutic option for NAFLD. They have been proposed for the treatment of different metabolic disorders, because of their anti-inflammatory and anti-oxidative properties. Additionally, they have an effect on glucose and lipid metabolism (24).

The polyphenol resveratrol (RSV3,5,4′-trihydroxystilbene) is a stilbenoid produced by several plants in response to injury or when the plant is under attack by pathogens. RSV has multiple biochemical and physiological actions. One of the most important is that RSV mimics a condition of caloric restriction (CR) (25) and this could be beneficial for the treatment of NAFLD. Previous findings have indicated that RSV improves insulin sensitivity, reduces insulin-like growth factor 1 (IGF-I) levels and activates key regulators of metabolism, such as adenosine monophosphate-activated kinase (AMPK) and silent information regulator 1 (SIRT1) (26).

AMPK is a protein consisting of three subunits, one catalytic and two non-catalytic. AMPK is activated, by phosphorylation, as a response to changes in the cellular AMP/ATP ratio (27). Findings have shown that RSV promoted the phosphorylation of AMPK. Once activated, AMPK regulates the lipid and glucose metabolism. AMPK suppresses anabolic processes and promotes catabolic processes. It reduces the activities of lipogenesis-associated genes, such as sterol regulatory element-binding protein-1c (SREBP-1c) and fatty acid synthase (FAS), leading to reduced lipogenesis and lipid accumulation (28). It also inactivates acetyl-CoA carboxylase (ACC) and promotes the activity of carnitine palmitoyltransferase-1 (CPT-1) and this leads to a decrease of liver fat accumulation (29). AMPK is a key molecule in the pathogenesis of NAFLD. Its other metabolic effect is that it promotes glucose metabolism, as it inhibits gluconeogenesis and enhances glucose uptake in the skeletal muscle.

RSV is also an activator of SIRT1, which is a NAD+ (oxidized nicotinamide adenine dinucleotide)-dependent protein deacetylase. SIRT1 plays a key role in lipid and glucose homeostasis and in insulin secretion sensitivity via CR. Furthermore, SIRT1 is an inhibitor of inflammation, reduces oxidative stress and improves endothelial function (30). In the liver, deacetylates activate certain proteins resulting in increased fatty acid β-oxidation (31). A number of studies have confirmed that activation of SIRT1 affects the pathogenetic molecular cascade of NAFLD (30,32,33).

In this study, the results indicated that trans-resveratrol in micronized formulation supplementation prevents and improves liver damage. The mechanism that RSV mimics CR is not fully understood yet, but the activation of AMPK and SIRT1 has a key role. The reduction of TG accumulation and the improvement of IR serve to protect the liver from NAFLD. Therefore, our data suggest that trans-resveratrol in micronized formulation is a hepatoprotective agent in humans, and a new therapeutic option for NAFLD.

Acknowledgements

Not applicable

Funding

This study was financially supported by the ‘Program Sustainable Development and Competitiveness’.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Authors' contributions

MT designed and performed the study. AC, AA and AM were responsible for the collection and analysis of the data. KF, DM and RK performed data analysis and interpretation. JD and ES participated in analysing the data and revised the manuscript. All authors read and approved the final manuscript.

Ethics approval and consent to participate

All patients provided written informed consent for the use of their data. The study protocol was approved by the Cyprus National Bioethics Committee.

Patient consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

References