Introduction
Chronic liver diseases and their common consequent pathological characteristics, liver fibrosis and cirrhosis, are global health burdens.1–3 Although numerous studies have yielded promising results regarding the prevention of disease progression by directly targeting viral infections or inhibiting hepatitis,4–10 safe and effective drugs are still needed, as CLD morbidity is growing with the increasing prevalence of nonalcoholic steatohepatitis (NASH) and nonalcoholic fatty liver disease.2,3,11,12
Magnetic resonance imaging (MRI) is used to diagnose liver diseases because of its superior contrast resolution.13,14 MRI provides morphological information and physiologic information to assess liver function,15–18 and various MRI techniques have been used to evaluate novel liver drugs in development from the preclinical to the clinical phases.19–21 Gadolinium ethoxybenzyl diethylenetriaminepentaacetic acid (Gd-EOB-DTPA)-enhanced T1-weighted MRI, proton density fat fraction (PDFF) MRI, and T2*-weighted MRI have all been used to measure liver functionality and pathologies.22–27 Although all techniques are well established and have been used for liver imaging and functional assessment, preclinical liver and liver drug studies with MRI are still lacking compared with clinical liver MRI studies. However, as the importance of reliability between preclinical research and clinical outcomes increases, more preclinical MRI and translational research utilizing various imaging modalities may help the development of novel therapies for liver disease.28–33
Silymarin is a flavonolignan isolated from milk thistle seeds (Silybum marianum) that has been used to treat various liver diseases in preclinical and clinical studies owing to its anti-oxidative, anti-inflammatory, and antifibrotic effects.34–36 Silymarin protects cell membranes from damage caused by reactive oxygen species and inhibits free radical formation. It also exerts anti-inflammatory activity by preventing cellular NF-kB activation, thereby inhibiting the activation of hepatic stellate cells and recruitment of other pro-inflammatory immune cells. Moreover, silymarin has an antifibrotic effect through the inhibition of myofibroblast activities. It prevents the transformation of hepatic stellate cells to a myofibroblast-like phenotype and blocks the generation of the extracellular matrix that induces hepatic fibrosis. However, no studies have evaluated the effects of silymarin on liver function with 8 weeks of follow-up MRIs. Moreover, correlative relation analysis with longitudinal MRI data and other traditional serological and histological biomarkers of liver function have not been done in previous studies. Herein, we investigated the protective effects of silymarin in a thioacetamide (TAA)-induced animal model longitudinally with MRI. In addition, we analyzed the correlations between biomarkers and multiparametric MRI data and assessed the interpretability of biomarkers and MRI values reflecting disease severity.
Methods
TAA-induced fibrosis animal model and silymarin administration
We purchased 6-week-old male Sprague-Dawley (SD) rats from the Orient Animal Laboratory (Seoul, South Korea). The SD-rats were randomly divided into three groups, controls (n=9), TAA-injected (n=13, TAA group), and TAA-injected, silymarin-treated (n=11, TAA-SY group). To induce hepatic fibrosis, 200 mg/kg thioacetamide (TAA, 163678, Sigma-Aldrich, St. Louis, MO, USA) was intraperitoneally injected three times a week for 8 weeks. After 4 weeks, 100 mg/kg of silymarin (SY, S0292, Sigma-Aldrich, St. Louis, MO, USA) was intraperitoneally administered three times a week for four weeks (Fig. 1). The silymarin administration protocol was determined based on previous studies that showed the liver-protective effects of silymarin.37,38 All animal experimental procedures were approved by the Committee on the Ethics of Animal Experiments at Asan Medical Center (IACUC No. 2018-12-115).
Biochemical analysis
Blood samples were collected from the tail vein every 2 weeks. Whole blood samples were collected in BD serum separation tubes (Becton Dickinson, Franklin Lakes, NJ, USA) and blood was allowed to clot for 30 m and centrifuged at 3,000 rpm for 10 m. We measured serum levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), and albumin (ALB) with a Hitachi 7180 Autoanalyzer (Hitachi Ltd., Tokyo, Japan).
Histological analysis
Liver tissue samples were fixed in 4% paraformaldehyde, paraffin-embedded, sectioned at 4 µm and stained with hematoxylin and eosin (H&E) or Masson’s trichrome (MT) following standard procedures. Stained slides were scanned with a Vectra imaging system (PerkinElmer, Waltham, MA, USA). Lobular inflammation (0–3), ballooning (0–2), and fibrosis (0–4) were graded. Lobular inflammation was scored as no foci (score 0), <2 foci/200× (score 1), 2–4 foci/200× (score 2), and >4 foci/200× (score 3). Hepatocyte ballooning was scored as none (score 0), few ballooned cells (score 1), or many ballooned cells (score 2). Fibrosis stage was graded as described by Brunt et al.39 as none (stage 0), portal fibrosis (stage 1), portal fibrosis with few septa (stage 2), septal or bridging fibrosis (stage 3), or cirrhosis (stage 4). Prussian blue staining was carried out with a staining kit (ab150674, Abcam, Cambridge, MA, USA) following the manufacturer’s protocol. Iron quantification was performed by measuring Prussian blue-positive regions in photographs using ImageJ software (National Institutes of Health, Bethesda, MD, USA).
Western blotting
Liver tissue was homogenized in RIPA lysis buffer (Thermo Fisher Scientific, Rockford, IL, USA) supplemented with protease and phosphatase inhibitors. Western blots reacted with primary antibodies against ferritin (3998S, Cell Signaling Technology, Beverly, MA, USA), hepcidin (M01347, Boster Biological Technology, Pleasanton, CA, USA) and GAPDH (ab8245, Abcam, USA), followed by HRP-conjugated secondary antibodies. The results were read with an image analyzer (Image lab 3.0, Bio-Rad, Hercules, CA, USA) and blots were quantified with ImageJ.
MRI
MRI was performed every 2 weeks using a 9.4-T magnet (Agilent, Inc., Santa Clara, CA, USA) with a 64 mm transmit/receive volume coil. Animals were anesthetized with a 1.5–2% isoflurane/air mixture during the imaging session, body temperature was maintained at 37.5 ± 0.5°C with an air heater system, and the respiratory rate was monitored to adjust the anesthetic concentration. T1-weighted dynamic contrast-enhanced (DCE)-MRI were obtained after the administration of 25 µmol/kg Gd-EOB-DTPA (Primovist, Bayer Healthcare, Leverkusen, Germany) by intravenous injection after 120 s. The MRI parameters were: (1) T1-weighted DCE-MRIs with TR/TE=70/2.34 ms, flip angle=35°, averages=1, matrix size=96×96, field-of-view (FOV)=50×50 mm2 (resolution: 0.52 mm), total scan time=44 min 48 s, and the number of images=400; and (2) T2* maps with TR/TE=800/2.56 ms, echo=6, flip angle=30°, averages=4, matrix size 128×128, and FOV=50×50 mm2 (resolution: 0.39 mm).
MRI analysis
The MRI data (AUCtmax and T2*) were analyzed with ImageJ. Two regions of interest (ROIs) were randomly placed in the liver and were measured, avoiding visible blood vessels. The relative enhancement rate (RER) was calculated using the equation RER(t)=[{SI(t) − SI(0)} / SI(0)] × 100 (%),33 where SI(t) is the signal intensity of the liver at time t and SI(0) is the average of SI before Gd-EOB-DTPA injection. The area under the curve to maximum time (AUCtmax) was calculated by the integration of areas from 0–6 m. The time to peak (Tmax) was calculated using Analysis of Functional NeuroImages Software (http://afni.nimh.nih.gov/afni ).
Statistical analysis
Statistical analysis was performed with IBM SPSS for Windows version 21.0 (IBM Corp., Armonk, NY, USA). To evaluate the changes in parameters over time, we performed a comparison using repeated measures analysis of variance. One-way analysis of variance, and independent t-tests were performed to compare mean values, and p<0.05 was considered statistically significant.
Results
Biochemical assessment of liver function-related biomarkers
Biochemical assays were performed to evaluate liver function and to analyze the correlation between serum markers and MRI data. In the control group, aspartate aminotransferase (AST), alanine aminotransferase (ALT), and albumin (ALB) levels remained the same from week 1 to week 8 of the study. In the TAA group, AST and ALT gradually increased, but the ALB level remained constant. In the TAA-SY group, AST and ALT increased until week 4, and their levels decreased with the initiation of silymarin (Supplementary Table 1). AST and ALT levels in the TAA group were significantly higher compared with the other groups during the last week of the study (Fig. 2A and Supplementary Table 1). After the animals were euthanized, histological analysis showed inflammatory cell infiltration and fibrous septa in the TAA-treated groups (TAA and TAA-SY). The NAS scores for lobular inflammation (0.00±0.00 vs. 2.29±0.83 vs. 1.55±0.69) and Brunt scores for fibrosis degree (0.22±0.44 vs. 3.29±0.73 vs. 2.36±1.03) in the three study groups were significantly higher in the TAA group than in the other two groups (Fig. 2B and Supplementary Table 2).
Table 1Repeated measures analysis of variance of the AUCtmax in the three groups
| AUCtmax (%)
|
|---|
Control (G1)
| TAA (G2)
| TAA+SY (G3)
| G1 vs. G2
| G1 vs. G3
| G2 vs. G3
|
|---|
| Mean | SD | Mean | SD | Mean | SD | p |
|---|
| Week 0 | 1.00 | 0.14 | 1.00 | 0.25 | 1.00 | 0.21 | n.s | n.s | n.s |
| Week 2 | 0.97 | 0.18 | 0.76 | 0.21 | 0.72 | 0.17 | n.s | n.s | n.s |
| Week 4 | 1.09 | 0.26 | 0.70 | 0.14 | 0.66 | 0.12 | <0.001 | <0.001 | n.s |
| Week 6 | 0.94 | 0.12 | 0.67 | 0.24 | 0.72 | 0.10 | 0.049 | n.s | n.s |
| Week 8 | 1.08 | 0.20 | 0.56 | 0.12 | 0.84 | 0.13 | <0.001 | 0.005 | p0.033 |
| RM-ANOVA | F=1.055 | F=5.781 | F=3.977 | *<0.05, **<0.01, ***<0.001 |
| p=0.395 | p=0.001*** | p=0.013* |
Gd-EOB-DTPA-enhanced T1-weighted MRI for liver function assessment
Parallel to the serological marker assays and histological analysis, we performed T1-weighted MRI of ROIs in the liver parenchyma (Fig. 3A). Comparative analysis found that the TAA group had a lower RER than the control group from week 2 onward and that the TAA-SY group showed recovery from week 6 (Fig. 3B). The AUCtmax values were maintained at similar levels for 8 weeks in the control group (F=1.055, p=0.395). The TAA group showed gradual decreases following TAA injection (F=5.781, ***p=0.001). In the TAA-SY group, AUCtmax showed recovering patterns from the week 6, which was 2 weeks after silymarin injection (F=3.977, *p=0.013). In the group comparison, the AUCtmax levels in the TAA group significantly decreased from week 4 onward compared with the control group. In the TAA-SY group, there was a significant decrease in the AUCtmax compared with the control group at week 4. As the levels of AUCtmax recovered after week. 6, we observed significant differences between the TAA and TAA-SY groups. However, the AUCtmax did not recover to the levels of the control group at week 8 (Fig. 3C and Table 1). A delay of the peak (Tmax) was not observed (Fig. 3D and Supplementary Table 3) in the experiment. We observed negative correlations between AUCtmax and each AST (R=−0.4605, ***p<0.0001) and ALT (R=−0.3608, ***p<0.0001; Fig. 3E).
T2* mapping MRI for liver function assessment
We included T2* mapping MR images in a multiparametric analysis (Fig. 4A). Similar patterns were observed in the T2* values compared with T1-weighted images. Fairly constant levels of T2* values were observed in the control group for 8 weeks (F=1.370, p=0.264) and gradual decreases in the T2* values were observed in the TAA group (F=60.214, ***p<0.001). The values of the TAA-SY group showed a tendency of recovery from week 6 (F=12.325, ***p<0.001). In the group comparison, the T2* values were significantly lower in the TAA group compared with the control group from week 2. Also, the TAA-SY group showed a gradual decrease of T2* values compared with the control group. No significant differences were observed in the T2* values between the TAA group and TAA-SY group. However, the T2* values of the TAA-SY group increased after week 6, eventually becoming significantly higher at week 8 (Fig. 4B and Table 2). Significant negative correlations between the T2* and AST (R=−0.6200, ***p<0.0001) and ALT (R=−0.5617, ***p<0.0001) were observed (Fig. 4C).
Table 2Repeated measures analysis of variance of T2* values in the three groups
| T2* (ms)
|
|---|
Control (G1)
| TAA (G2)
| TAA+SY (G3)
| G1 vs. G2
| G1 vs. G3
| G2 vs. G3
|
|---|
| Mean | SD | Mean | SD | Mean | SD | p |
|---|
| Week 0 | 9.84 | 1.32 | 9.68 | 1.12 | 9.38 | 0.75 | n.s | n.s | n.s |
| Week 2 | 9.91 | 1.55 | 8.28 | 1.50 | 7.15 | 0.92 | 0.027 | <0.001 | n.s |
| Week 4 | 9.45 | 1.49 | 7.26 | 0.84 | 7.03 | 1.04 | 0.001 | <0.001 | n.s |
| Week 6 | 9.88 | 1.30 | 5.68 | 0.28 | 6.53 | 1.02 | <0.001 | <0.001 | n.s |
| Week 8 | 9.53 | 1.40 | 5.05 | 0.72 | 6.74 | 1.48 | <0.001 | <0.001 | 0.035 |
| RM-ANOVA | F=1.370 | F=60.214 | F=12.325 | *<0.05, **<0.01, ***<0.001 |
| p=0.264 | p<0.001*** | p<0.001*** |
Iron accumulation in the liver and correlation with T2*
We further analyzed iron accumulation in the liver and its correlation with T2* shortening. We observed iron overload near the portal triad of fibrosis in the liver in both TAA-treated groups (TAA and TAA-SY) with Prussian blue staining (Fig. 5A). We also observed significant iron accumulation in both TAA-treated groups compared with the control group (0.39±0.24 control vs. 6.23±3.30 TAA, ***p<0.001; 0.39±0.24 control vs. 3.23±1.73 TAA-SY; *p=0.03). However, iron accumulation was significantly lower in the TAA-SY than in the TAA group (6.23±3.30 TAA vs. 3.23±1.73 TAA-SY, *p=0.011; Fig. 5B). We measured ferritin and hepcidin levels to assess iron storage and homeostasis. The highest expression level of ferritin, the iron storage protein, was observed in the TAA group compared with the control (*p=0.047) and TAA-SY (*p=0.038) groups. The expression of hepcidin, the negative regulator for iron release, was not significantly altered, but the lowest expression was observed in the TAA group compared with the other two groups (Fig. 5C, D). The T2* values and hepatic iron accumulation (% area) in the control, TAA, and TAA-SY groups at week 8 negatively correlated (R=−0.7010, ***p<0.0001; Fig. 5E).
Discussion
We monitored the liver-protective effects of silymarin with longitudinal MRI follow-up and monitoring of liver function biomarkers. We observed meaningful correlations between MRI-based values and the levels of several biomarkers. Carbon tetrachloride (CCl4) is frequently used to induce liver failure,40–42 but liver function occasionally occurs when CCl4 administration is stopped.42 Conversely, TAA damage persists for more than 2 months after withdrawal, and induces pathological characteristics similar to human chronic liver dysfunction. TAA-induced liver injury models are thus more suitable than CCl4 for longitudinal studies. We did not show the results of more than one concentration of silymarin as we designed our study to avoid the complexities associated with multi-dosages. We observed changes in serological biomarkers that reflected the liver-protective effects of silymarin at 100 mg/kg. We also observed reduced fibrosis and infiltration of inflammatory cells in H&E stained tissue. The results are consistent with previous studies of silymarin treatment in induced liver injury models.34,38 The anti-oxidative, anti-inflammatory, and anti-fibrotic effects of silymarin were evident throughout the study period.
Gadoxetate-enhanced T1-weighted MRI images are used to assess liver function because of their implicative representations of the contrast agent-transporting abilities of hepatocytes. The maximum RER values in the TAA group were reduced after TAA injection. In the TAA-SY group, lowered the RERs; however, silymarin treatment led to a gradual RER recovery to levels similar to those of the control group. The AUCtmax values showed patterns equivalent to those of the level change patterns of RERs. In the latter period of the experiment, the AUCtmax of the TAA group was significantly lower compared to those of the other two groups. Although several studies refer to T1-weighted MRI as an extremely useful tool for liver function assessment,28,43 we analyzed the correlation between the MRI data and serological markers to assess the relationship between MRI and liver function. AUCtmax, AST, and ALT showed significant negative correlations, which confirmed an association between the lowered T1 values and elevated enzyme levels resulting from liver dysfunction. Cumulatively, the results indicate that the contrast agent uptake into the hepatocytes was hindered after TAA injection. The resulting liver dysfunction caused changes of the T1-weighted image data.
Several clinical and preclinical studies have reported that iron metabolism is disturbed in chronic hepatic diseases.44–46 Iron accumulation becomes significant with the progression of fibrosis severity, and excessive iron accumulation induces fibrosis-promoting oxidative stress. This iron-dependent cell death loop causes ongoing cellular and tissue damage to the liver. The release of iron from the dead cells and accumulation in the interstitial space of the liver shortens the T2* in the MRI. Consistent with the results of many studies that measure the iron overload with MRI,47,48 we also observed gradual decreases in T2* along the experimental period in the TAA group. A decrease of T2* was also observed in the TAA-SY group; however, the degree of decrease became smaller, and significant differences were noted compared with the values of the TAA group at eight weeks. Negative correlations were observed between the T2* values and the serological biomarkers and between AUCtmax and the serological biomarkers. However, the T2* values in the TAA-SY group did not recover to the levels of the control group at the week 8, although a significant difference existed between the TAA and TAA-SY groups. The Prussian blue staining results indicate that the amount of iron residing in the extracellular matrices explained the lowered T2* values in the TAA-SY group compared with the control group. Moreover, the expression patterns of ferritin and hepcidin supported the iron accumulation status of the three groups, as higher ferritin expression levels imply that cells store more iron. Lower expression of hepcidin implies that the iron release inside the liver was redundant.
Considering the different patterns in AUCtmax and T2* values, silymarin treatment appears to have caused the time differences in the recovery of hepatocyte transporting abilities and in accumulated iron clearance in the interstitial space. To elucidate the precise reason for this phenomenon, further studies are needed.
In line with other studies, we found that silymarin had hepatoprotective effects36,49,50 and that MRI was highly useful for assessing liver function and drug efficacy. Although preclinical studies of new liver disease drugs using MRI are limited, the applications of MRI will increase along with the increasing need for new drugs to combat chronic liver diseases. Further studies are necessary if new MRI techniques develop to assess liver function, and we expect that additional studies will broaden the scope of MRI use in the future.
Supporting information
Supplementary Table 1
Repeated measures analysis of variance of serum markers.
(DOCX)
Supplementary Table 2
Histology scores of hepatic injury in three groups.
(DOCX)
Supplementary Table 3
Repeated measures analysis of variance of Tmax.
(DOCX)
Abbreviations
- ALB:
albumin
- ALT:
alanine aminotransferase
- AST:
aspartate aminotransferase
- AUCtmax:
area under the curve to maximum time
- DCE:
dynamic contrast-enhanced
- GAPDH:
glyceraldehyde 3-phosphate dehydrogenase
- Gd-EOB-DTPA:
gadolinium ethoxybenzyl diethylenetriaminepentaacetic acid
- MRI:
magnetic resonance imaging
- TAA:
thioacetamide
- Tmax:
time to peak
Declarations
Acknowledgement
We thank the core facilities of the Magnetic Resonance Core and the Comparative Pathology Core at the ConveRgence mEDIcine research center (CREDIT), Asan Medical Center for the use of their shared equipment, services and expertise.
Data sharing statement
All data are available upon request.
Funding
This work was supported by grants from the Asan Institute of Life Sciences, Asan Medical Center, Republic of Korea (2020IL0026-1); the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (2018R1A2B2007694); and the Ministry of Education (2020R1I1A1A01058302).
Conflict of interest
The authors have no conflict of interests related to this publication.
Authors’ contributions
Study concept and design (DCW, YC), acquisition of data (YJC, JIK, MYC), analysis and interpretation of data (YJC, HH), manuscript drafting (YC, YJC), magnetic resonance imaging (WCW, STK), critical revision of the manuscript for important intellectual content (HH, YC), and administrative, technical, or material support and study supervision (YSS, KWK, DCW, YC). All authors contributed important intellectual content and approved the submission of this manuscript.