Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Differences among patients with and without nonalcoholic fatty liver disease having elevated alanine aminotransferase levels at various stages of metabolic syndrome

  • Masahiro Sogabe ,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Supervision, Validation, Writing – original draft, Writing – review & editing

    tokushimakenananshi@yahoo.co.jp

    Affiliations Department of Gastroenterology and Oncology, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan, Department of Internal Medicine, Shikoku Central Hospital of the Mutual aid Association of Public School Teachers, Shikokuchuo, Japan

  • Toshiya Okahisa,

    Roles Project administration, Supervision

    Affiliations Department of Gastroenterology and Oncology, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan, Department of Internal Medicine, Shikoku Central Hospital of the Mutual aid Association of Public School Teachers, Shikokuchuo, Japan

  • Takeshi Kurihara,

    Roles Data curation

    Affiliation Department of Internal Medicine, Shikoku Central Hospital of the Mutual aid Association of Public School Teachers, Shikokuchuo, Japan

  • Masanori Takehara,

    Roles Data curation

    Affiliation Department of Gastroenterology and Oncology, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan

  • Kaizo Kagemoto,

    Roles Data curation

    Affiliation Department of Gastroenterology and Oncology, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan

  • Jun Okazaki,

    Roles Data curation

    Affiliation Department of Gastroenterology and Oncology, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan

  • Yoshifumi Kida,

    Roles Formal analysis

    Affiliation Department of Gastroenterology and Oncology, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan

  • Akihiro Hirao,

    Roles Formal analysis

    Affiliation Department of Gastroenterology and Oncology, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan

  • Hironori Tanaka,

    Roles Formal analysis

    Affiliation Department of Gastroenterology and Oncology, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan

  • Tetsu Tomonari,

    Roles Investigation

    Affiliation Department of Gastroenterology and Oncology, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan

  • Tatsuya Taniguchi,

    Roles Investigation

    Affiliation Department of Gastroenterology and Oncology, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan

  • Koichi Okamoto,

    Roles Visualization

    Affiliation Department of Gastroenterology and Oncology, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan

  • Masahiko Nakasono,

    Roles Conceptualization, Methodology

    Affiliation Department of Internal Medicine, Tsurugi Municipal Handa Hospital, Tsurugi, Japan

  • Tetsuji Takayama

    Roles Supervision, Writing – review & editing

    Affiliation Department of Gastroenterology and Oncology, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan

Abstract

Background

The prevalence of nonalcoholic fatty liver disease (NAFLD) in the non-obese population has increased and NAFLD is not always recognized in individuals with metabolic syndrome (MS). The risk of cirrhosis is higher in patients having NAFLD with elevated alanine aminotransferase (ALT) levels than in those having NAFLD with normal ALT levels.

Objective

To measure the differences in clinical factors associated with NAFLD having elevation of ALT among subjects with Non-MS, Pre-MS, and MS, and to measure differences in metabolites between MS subjects with and without NAFLD having elevation of ALT.

Methods

Among 7,054 persons undergoing health check-ups, we included 3,025 subjects who met the selection criteria. We measured differences in clinical factors for NAFLD having elevation of ALT among subjects with Non-MS, Pre-MS, and MS, and compared metabolites between subjects with and without NAFLD having elevation of ALT in 32 subjects with MS.

Results

The prevalence of NAFLD and NAFLD having elevation of ALT was significantly progressively greater in subjects with Non-MS, Pre-MS, and MS (p <0.001, respectively). In the Non-MS group, there were significant differences between subjects with and without NAFLD having elevation of ALT with respect to body mass index (BMI), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol, hemoglobin A1c, uric acid, aspartate aminotransferase (AST); In the Pre-MS group, there were significant differences in BMI, hypertension, AST, and gamma-glutamyl transpeptidase (GGT); In the MS group, there were significant differences in HDL-C, impaired glucose tolerance, AST, and GGT. There were significant differences in levels of metabolites of nicotinamide, inosine, and acetyl-L-carnitine between MS subjects with and without NAFLD having elevation of ALT (all p <0.05).

Conclusions

Although NAFLD having elevation of ALT is important for development of NAFLD, differences in factors associated with NAFLD having elevation of ALT at various stages of MS should be considered. Additionally, several metabolites may play roles in the identification of risk for NAFLD in individuals with MS.

Introduction

Despite the fact that the increase in prevalence of metabolic syndrome (MS) that is strongly associated with nonalcoholic fatty liver disease (NAFLD) has been problematic in gastroenterology, NAFLD is not always recognized in individuals with MS [13]. Persons who are easy to become NAFLD and those who are hard to become NAFLD may exist in individuals who belong to the same MS. Additionally, the prevalence of NAFLD in the non-obese population has gradually increased in Japan, and not low [4, 5]. Generally, NAFLD is diagnosed using the presence of fatty liver regardless of assessment of liver enzymes in the context of medical check-ups and NAFLD having elevation of liver enzyme and NAFLD having standard values of liver enzyme have been treated in the same way; nevertheless, patients with NAFLD and elevation of alanine aminotransferase (ALT) are at higher risk for cirrhosis than those with NAFLD and normal ALT values [6]. However, there is few reports about NAFLD having elevation of ALT levels at various stages of MS. The aim of this study was to measure the differences in clinical factors associated with NAFLD having elevation of ALT among subjects with Non-MS, Pre-MS, and MS, and to measure differences in metabolites between MS subjects with and without NAFLD having elevation of ALT.

Methods

Study design and subjects

This cross-sectional study was conducted among 7,054 subjects residing in the Shikoku region, Japan, and undergoing regular health check-ups at Shikoku Central Hospital of the Mutual Aid Association of Public School Teachers between April 2018 and March 2019. Among 7,054 subjects, 4,029 subjects were excluded for fulfilling any of the following criteria: (1) positivity for markers of hepatitis B virus infection (hepatitis B surface antigen) and/or hepatitis C virus infection (anti-hepatitis C virus antibodies); (2) alcohol consumption of ≥20 g/day in males or alcohol consumption of ≥10 g/day in females; (3) absence of abdominal ultrasonography; (4) history of liver surgery; and (5) current or previous medication for liver disease. Finally, 3,025 subjects were enrolled (Fig 1). The study protocol was approved by the Ethics Committee of Shikoku Central Hospital, and all procedures were performed in accordance with the Declaration of Helsinki. All subjects were informed that their clinical data might be retrospectively analyzed, and informed consent was obtained.

thumbnail
Fig 1. Participant flow of individuals undergoing check-ups.

HBsAg, hepatitis B surface antigen; HCVAb, hepatitis C antibody.

https://doi.org/10.1371/journal.pone.0238388.g001

Diagnosis of MS

The diagnostic criteria for MS adopted by the World Health Organization (WHO) or the adult treatment panel (ATP) III criteria are used worldwide. However, we adopted the MS criteria proposed by the joint committee of eight Japanese medical societies in 2005 because all subjects in our study were Japanese [7]. Component factors of MS criteria are waist circumference (WC) must exceed 85 cm for males or 90 cm for females, and the presence of two or more of the following: (1) dyslipidemia: high-density lipoprotein cholesterol (HDL-C) <40 mg/dl, and/or triglycerides (TG) ≥150 mg/dl, or medication for dyslipidemia; (2) impaired glucose tolerance (IGT): fasting plasma glucose (FPG) ≥110 mg/dl or medication for diabetes; and (3) hypertension: blood pressure ≥ 130/85 mmHg or medication for hypertension.

We designated individuals who fulfilled these criteria as the MS group. Individuals who did not fulfill above MS criteria were divided into two groups as follows: The Non-MS group was defined as individuals having no component of MS; The Pre-MS group was defined as individuals having more than 85 cm of WC for males or 90 cm for females and one component of MS.

Physical examination and serum biochemistry

Body weight (BW) and height were obtained from all subjects. BW was measured to the nearest 0.1 kg, and height was measured to the nearest 0.1 cm. The body mass index (BMI) was calculated as the weight (in kilograms) divided by the square of the height (in meters) expressed in kg/m2. WC was measured at the umbilical level by a laboratory technician. Venous blood samples were taken from all subjects in the morning after 12 hours of overnight fasting. Clinical laboratory tests included aspartate aminotransferase (AST), ALT, gamma-glutamyl transpeptidase (GGT), total cholesterol (T-CHO), HDL-C, TG, low-density lipoprotein cholesterol (LDL-C), uric acid (UA), FPG, and hemoglobin A1c (HbA1c). Ferritin, insulin, and type IV collagen 7S were measured among 34 subjects with MS during 2018 April, and the homeostasis model assessment of insulin resistance (HOMA-IR) and NAFIC score and the Fibrosis (FIB)-4 indexes were assessed [812]. ALT elevation was defined as level more than 30 IU/L.

Assessment of ultrasonography

Standard abdominal ultrasonography was performed by trained technicians in the morning with the subjects fasting. The HI-VISION Avius® and ALOKA ARIETTA 850 (Hitachi Ltd., Tokyo, Japan) platforms with 6-MHz convex-array probes were used for ultrasonography. The diagnostic criteria for fatty liver on ultrasonography were as follows: echo contrast between the liver and the renal cortex, liver brightness, blurring of liver vessels, and/or deep attenuation [13, 14]. In our study, fatty liver with alcohol consumption of less than 20 g/day in males or alcohol consumption of less than 10 g/day in females and without chronic liver diseases such as hepatitis B, hepatitis C, and liver disease related with autoimmune was defined as NAFLD.

Metabolomics and sulfur metabolomics

Sera from 34 subjects with MS during 2018 April were obtained by centrifugation of blood samples for 10 min at 1500× g at 4°C, and was stored at –80°C until use. Metabolomics following the primary metabolism method was performed using liquid chromatography coupled to a tandem mass spectrometry (LC-MS/MS) (Nexera UHPLC system with on-line LC-MS 8040, Shimadzu Corporation, Kyoto, Japan). Briefly, 10 μL of serum was added to 110 μL methanol containing internal standards at 0°C to inactivate native enzymes. After centrifugation, the upper aqueous layer of the separated solution was desiccated using a centrifugal evaporator. Thereafter, 60 μL of water was added, and the solution was centrifuged. We used 10 μL from the upper aqueous layer as the metabolomics sample. Sulfur metabolomics was performed by the Sulfur Index service in Japan (http://www.euglena.jp/sulfurindex/; Euglena Co. Ltd., Tokyo, Japan). The sulfur index uses a technology where metabolites are detected as S-bimanyl derivatives by LC-MS/MS (Shimadzu (Nexera UHPLC system with on-line LC-MS 8040, Shimadzu, Corporation, Kyoto, Japan) as described previously [15, 16]. Briefly, the sulfur-containing compounds in the samples were extracted by adding methanol and converting to fluorescent derivatives with monobromobimane. The levels of the target metabolites were determined from the peak area in the mass chromatography, monitoring each mass-to-charge ratio of the individual target, and represented as relative amounts (relative areas) after normalization based on the peak area of the internal standard (D-camphor-10-sulfonic acid). We measured 101 primary metabolites such as amino acids, organic acids, and the like, and a total of 52 metabolites were obtained from subjects with MS. We measured 90 sulfur metabolites and found a total of 17 sulfur metabolites in subjects with MS.

Statistical analysis

Quantitative data, including subject baseline characteristics, were expressed as the mean ± standard deviation (SD). P-values of less than 0.05 were considered statistically significant. The χ2-test or Mann–Whitney U-test was used for comparisons between the two groups. The m × n χ2-test or Kruskal–Wallis test was used to analyze differences among three groups. If the Kruskal–Wallis test revealed differences between the groups, then post-hoc pairwise comparisons were performed using the Mann–Whitney U test with Bonferroni correction. Correlations between variables were assessed by calculating Spearman rank correlation coefficients. Factors with significant influence on the prevalence of NAFLD having elevation of ALT were determined using univariate analysis. All parameters that had P-values of less than 0.05 by univariate analysis were assessed using stepwise multivariate logistic regression analysis adjusted for age and gender. The odds ratio (OR) and 95% confidence interval (CI) were analyzed for each variable. All statistical analyses were performed using MedCalc Statistical Software for Windows (MedCalc Software; Ostend, Belgium).

Results

Baseline characteristics among Non-MS, Pre-MS, and MS groups

The baseline characteristics of 3,025 subjects are shown in Table 1. The prevalence of Non-MS, Pre-MS, and MS groups was 74.3%, 11.9%, and 13.8%, respectively. The proportion of males, age, BMI, and WC were significantly high in order of MS group, Pre-MS group, Non-MS group (p < 0.001, p <0.05, p <0.05, and p <0.05, respectively). The prevalence of smoker and drinker in MS group and Pre-MS group were significantly higher than in Non-MS group (p < 0.001 and p <0.05, respectively). The prevalence of hypertension, SBP, and DBP were significantly high in order of MS group, Pre-MS group, Non-MS group (p < 0.001, p <0.05, and p <0.05, respectively). The prevalence of dyslipidemia, TG, and LDL-C were significantly high in order of MS group, Pre-MS group, Non-MS group (p < 0.001, p <0.05, and p <0.05, respectively), and HDL-C was significantly low in order of MS group, Pre-MS group, Non-MS group (p <0.05). FPG and HbA1c were significantly high in order of MS group, Pre-MS group, Non-MS group (p <0.05 for both). The prevalence of IGT was significantly higher in MS group than in Pre-MS group and Non-MS group (p <0.001). UA was significantly high in order of MS group, Pre-MS group, Non-MS group (p <0.05). ALT, AST, GGT, and the prevalence of NAFLD were significantly high in order of MS group, Pre-MS group, Non-MS group (p < 0.05, p <0.05, p <0.05, and p <0.001, respectively).

thumbnail
Table 1. Baseline characteristics among Non-MS, Pre-MS, and MS groups (n = 3,025).

https://doi.org/10.1371/journal.pone.0238388.t001

Comparison of the prevalence of NAFLD and NAFLD having elevation of ALT among Non-MS, Pre-MS, and MS groups

The comparison of the prevalence of NAFLD among the Non-MS, Pre-MS, and MS groups is shown in Fig 2A. The prevalence of NAFLD in Non-MS group, Pre-MS group, and MS group were 18.6% (417/2,246), 67.0% (242/361), and 82.1% (343/418), respectively. There was a significant difference in the prevalence of NAFLD among the three groups (p < 0.001). The prevalence of NAFLD was higher in the MS group vs. the Pre-MS group and the Non-MS group (p < 0.001 and p < 0.001, respectively), and the prevalence of NAFLD was significantly higher in the Pre-MS group than in the Non-MS group (p <0.001).

thumbnail
Fig 2. Comparison of the prevalence of NAFLD and NAFLD having elevation of ALT among the Non-MS, Pre-MS, and MS groups.

A Comparison of the prevalence of NAFLD among the Non-MS, Pre-MS, and MS groups. B Comparison of the prevalence of NAFLD having elevation of ALT among the Non-MS, Pre-MS, and MS groups. The gray bar indicates the prevalence of NAFLD. The black bar indicates the prevalence of NAFLD having elevation of ALT. ALT, alanine aminotransferase; MS, metabolic syndrome; NAFLD, nonalcoholic fatty liver disease; *P < 0.001.

https://doi.org/10.1371/journal.pone.0238388.g002

A comparison of the prevalence of NAFLD having elevation of ALT among Non-MS, Pre-MS, and MS groups is shown in Fig 2B. The prevalence of NAFLD having elevation of ALT in Non-MS, Pre-MS, and MS groups were 5.1% (115/2,246), 28.8% (104/361), and 44.3% (185/418), respectively. There were significant differences in the prevalence of NAFLD having elevation of ALT among the three groups (p < 0.001). The prevalence of NAFLD having elevation of ALT was higher in the MS group than in the Pre-MS group and Non-MS group (p < 0.001 and p < 0.001, respectively), and the prevalence of NAFLD having elevation of ALT was higher in Pre-MS group than in the Non-MS group (p <0.001).

Factors associated with NAFLD having elevation of ALT among Non-MS, Pre-MS, and MS groups

Results of univariate analysis for factors associated with NAFLD having elevation of ALT among Non-MS group, Pre-MS group, and MS group are shown in Table 2. In the Non-MS group, univariate analysis showed that gender, BMI, WC, SBP, DBP, hypertension, T-CHO, TG, HDL-C, LDL-C, dyslipidemia, FPG, HbA1c, IGT, UA, AST, and GGT were significantly associated with NAFLD having elevation of ALT. In the Pre-MS group, univariate analysis showed that gender, age, BMI, WC, hypertension, HDL-C, dyslipidemia, FPG, HbA1c, UA, AST, and GGT were significantly associated with NAFLD having elevation of ALT. In the MS group, univariate analysis showed that gender, age, BMI, WC, TG, HDL-C, HbA1c, IGT, UA, AST, and GGT were significantly associated with NAFLD having elevation of ALT.

thumbnail
Table 2. Results of univariate analysis for factors associated with NAFLD having elevation of ALT among Non-MS, Pre-MS, and MS groups.

https://doi.org/10.1371/journal.pone.0238388.t002

Independent predictors of NAFLD having elevation of ALT among Non-MS, Pre-MS, and MS groups

Results of multivariate analysis for independent predictors of NAFLD having elevation of ALT among Non-MS group, Pre-MS group, and MS group are shown in Table 3. In the Non-MS group, BMI, LDL-C, HbA1c, UA and AST were significant independent predictors of increased prevalence of NAFLD having elevation of ALT, whereas HDL-C contributed significantly and independently to decreased prevalence of NAFLD having elevation of ALT. In the Pre-MS group, BMI, AST, and GGT were significant and independent predictors of increased prevalence of NAFLD having elevation of ALT, whereas hypertension contributed significantly and independently to decreased prevalence of NAFLD having elevation of ALT. In the MS group, IGT, AST, and GGT were significant and independent predictors of increased prevalence of NAFLD having elevation of ALT, whereas HDL-C contributed significantly and independently to decreased prevalence of NAFLD having elevation of ALT.

thumbnail
Table 3. Results of multivariate analysis for independent predictors of NAFLD having elevation of ALT among Non-MS, Pre-MS, and MS groups.

https://doi.org/10.1371/journal.pone.0238388.t003

Comparison of baseline characteristics between subjects with and without NAFLD having elevation of ALT in 32 subjects with MS

A comparison of the baseline characteristics between subjects with and without NAFLD having elevation of ALT in 32 subjects with MS are shown in Table 4. The mean age in subjects without NAFLD having elevation of ALT was significantly higher than that in subjects with NAFLD having elevation of ALT (p < 0.05). AST, HOMA-IR, and NAFIC scores in subjects with NAFLD having elevation of ALT were significantly higher than those in subjects without NAFLD having elevation of ALT (p < 0.001, p < 0.05, and p < 0.005, respectively).

thumbnail
Table 4. Comparison of baseline characteristics between subjects with and without NAFLD having elevation of ALT in 32 subjects with MS.

https://doi.org/10.1371/journal.pone.0238388.t004

Comparison of primary metabolites between subjects with and without NAFLD having elevation of ALT in 32 subjects with MS

A comparison of 52 metabolites between subjects with and without NAFLD having elevation of ALT in 32 subjects with MS are shown in Table 5. There were significant differences in three of the 52 metabolites between subjects with and without NAFLD having elevation of ALT. Mean nicotinamide levels in the subjects without NAFLD having elevation of ALT and subjects with NAFLD having elevation of ALT of ALT were 2.860E-04 ± 1.064E-04 and 3.877E-04 ± 1.284E-04, respectively, which was a statistically significant difference (p < 0.05). Mean inosine levels in the subjects without NAFLD having elevation of ALT and subjects with NAFLD having elevation of ALT were 0 and 2.646E-05 ± 4.495E-05, respectively, which was also a statistically significant difference (p < 0.05). Mean acetyl-L-carnitine levels in the subjects without NAFLD having elevation of ALT and subjects with NAFLD having elevation of ALT were 1.013E-01 ± 1.947E-02 and 8.699E-02 ± 1.874E-02, respectively, which was also a statistically significant difference (p < 0.05).

thumbnail
Table 5. Comparison of 52 metabolites between subjects with and without NAFLD having elevation of ALT in 32 subjects with MS.

https://doi.org/10.1371/journal.pone.0238388.t005

Correlations between clinical parameters and significant metabolites for NAFLD having elevation of ALT

Spearman rank coefficients for clinical parameters and metabolites with statistically significant differences between subjects with and without NAFLD having elevation of ALT in MS are shown in Table 6. Niacinamide levels correlated significantly with ALT, NAFIC score, and NAFLD having elevation of ALT (p <0.05 for all). Inosine levels correlated significantly with ALT, HOMA-IR, and NAFLD having elevation of ALT (p < 0.05, p <0.01, and p <0.05, respectively). Acetyl-L-carnitine levels correlated significantly with IGT and NAFLD having elevation of ALT (p < 0.05 for both).

thumbnail
Table 6. Spearman rank coefficients for clinical parameters and metabolites those showed a statistically significant difference between subjects with and without NAFLD having elevation of ALT in MS.

https://doi.org/10.1371/journal.pone.0238388.t006

Comparison of sulfur metabolites between subjects with and without NAFLD having elevation of ALT in 32 subjects with MS

A comparison of 17 sulfur metabolites that was associated sulfur metabolic pathways between subjects with and without NAFLD having elevation of ALT in 32 subjects with MS are shown in Table 7. There were no differences in sulfur metabolites between subjects with and without NAFLD having elevation of ALT.

thumbnail
Table 7. Comparison of 17 sulfur metabolites between subjects with and without NAFLD having elevation of ALT in 32 subjects with MS.

https://doi.org/10.1371/journal.pone.0238388.t007

Discussion

The aim of the present study was to clarify the differences in clinical factors associated with NAFLD having elevation of ALT among subjects with Non-MS, Pre-MS, and MS, and to measure differences in metabolites between MS subjects with and without NAFLD having elevation of ALT. The present study showed that the prevalence of NAFLD having elevation of ALT was progressively greater in subjects with Non-MS, Pre-MS, and MS, however, independent predictors for NAFLD having elevation of ALT differed among subjects with MS, Pre-MS, and Non-MS. Additionally, there were significant differences in levels of several metabolites between subjects with and without NAFLD having elevation of ALT in spite of the subjects who belong to same MS. To our knowledge, ours is the first study to clarify the differences in subjects with NAFLD having elevation of ALT at various stage of MS, as well as measuring differences in metabolites with respect to NAFLD having elevation of ALT in the context of medical check-ups.

We demonstrated that values of physical measurements such as BMI and WC, and almost factors related to hypertension, dyslipidemia, and IGT were progressively greater in the Non-MS, Pre-MS, MS groups, in accordance with previous reports that BMI, WC, blood pressure, HOMA-IR, and others increased with the number of MS components [1719]. Liver enzymes such as ALT and AST, and the prevalence of NAFLD and NAFLD having elevation of ALT increased with progression from Non-MS to Pre-MS to MS. These results suggest that the onset of NAFLD and elevation of liver enzyme were strongly associated with MS components such as obesity, including visceral fat and lifestyle-related diseases. Furthermore, the prevalence of NAFLD and NAFLD having elevation of ALT among subjects except the MS group were 25.3% and 8.4%, respectively. This prevalence was not low, and we cannot ignore this fact.

We showed that independent predictors of NAFLD having elevation of ALT varied among Non-MS, Pre-MS, and MS groups. The prevalence of dyslipidemia and IGT in the Non-MS group was lower than that of the MS group; however, LDL, HbA1c, and UA were significant factors of NAFLD having elevation of ALT in the Non-MS group. These results suggest that, even in non-obese individuals, paying attention to dyslipidemia and IGT is necessary. Hyperuricemia is associated with an elevated risk of developing impaired fasting glucose [20]. IGT due to insulin resistance may lead to hyperinsulinemia, which increases uric acid concentrations by reducing renal uric acid secretion and accumulating substrates for uric acid production [21, 22]. Hyperuricemia was reported to be associated with histological liver damage in patients with NAFLD [23]. These findings suggest that our study might indicate that not only HbA1c but also UA are significant risk factors for NAFLD having elevation of ALT in the Non-MS group.

In the MS group, IGT was a significant independent predictor of an increase prevalence of NAFLD having elevation of ALT in accordance with previous reports that DM and insulin resistance are associated with NAFLD [24, 25]. Obesity and visceral adipose tissue are risk factors for insulin resistance. In particular, excessive visceral fat accumulation releases various bioactive substances known as inflammatory adipokines, include interleukin-6, tumor necrosis factor-α, macrophage chemoattractant protein-1, and resistin [26, 27]. Therefore, visceral fat accumulation is thought to play an important role in the development of NAFLD [2833]. These findings support our result that the prevalence of NAFLD and NAFLD having elevation of ALT in MS group were higher than in other groups.

Conversely, HDL-C was a significant independent predictor of decreased risk for NAFLD having elevation of ALT in the Non-MS and MS groups. Levels of TG, IGT, and HDL-C were significantly different between subjects with and without NAFLD having elevation of ALT in the Non-MS and MS groups. NAFLD is strongly associated with dyslipidemia, including decreased HDL-C levels and increased TG levels [34, 35]. TG is synthesized from free fatty acids. Excess energy, decreased lipolysis in adipose tissue, increased lipogenesis in the liver, and insulin resistance that suppresses lipolysis and increases de novo lipogenesis may induce increased free fatty acid levels [3638]. The main component of very low-density lipoprotein (VLDL) in liver is TG, and increased VLDL and IGT in diabetes causes decreased HDL-C levels [39]. Therefore, our study might show that HDL is a significant independent predictor of decreased prevalence of NAFLD having elevation of ALT.

In the Pre-MS group, hypertension was a significant independent predictor of decreased prevalence of NAFLD having elevation of ALT. However, there was no significant difference in the prevalence of NAFLD having elevation of ALT between subjects without hypertension and subjects having hypertension without medication. In recent reports, angiotensin II receptor blockers may suppress liver fibrosis with NAFLD including non-alcoholic steatohepatitis [4042]. Our results might be affected by use of antihypertensive agents. Further studies are needed to elucidate the association between NAFLD and antihypertensive agents because we did not investigate the type of antihypertensive agents.

Metabolomics involves the measurement of large numbers of low-molecular-weight metabolites, including sugars, amino acids, and hormones. Although several studies have provided insight into the pathogenesis of NAFLD [4346], to date, no specific biomarker that could identify NAFLD has been found using metabolomics. We found that the levels of metabolites such as inosine and nicotinamide were significantly higher in subjects with NAFLD having elevation of ALT than those in subjects without NAFLD having elevation of ALT. Inosine is found in meat and is an organic compound with a nucleoside-like structure. Consuming large amounts of food containing inosine may increase uric acid levels because inosine is metabolized to uric acid. The elevation of uric acid levels is associated with NAFLD in several cohort studies [47, 48]. Nicotinamide is a B-complex vitamin that participates in energy production and metabolism of sugar, lipids, and proteins as a coenzyme of dehydrogenase. High dietary intake of nicotinamide is unfavorable because the accumulation of nicotinamide may cause liver dysfunction [49]. This suggests that elevated serum levels of inosine and nicotinamide may be associated with NAFLD. Conversely, acetyl-L-carnitine levels were significantly lower in subjects with NAFLD having elevation of ALT than those in subjects without NAFLD having elevation of ALT in our study. Acetyl-L-carnitine is an acetylated derivative of L-carnitine that participates in oxidative metabolism. Decreased L-carnitine levels were associated with insulin resistance and L-carnitine supplementation in rats and mice improved metabolic function and NAFLD [50, 51]. Our findings suggest that lower levels of acetyl-L-carnitine may be associated with NAFLD. Recently, reactive sulfur species (RSS) have been recognized to be endogenously produced in abundance in many species [52, 53]. They occur in diverse polysulfide forms with unique redox-active or reactive chemical properties [5456]. Sulfur metabolomics was developed to investigate the sulfur metabolic pathways associated with RSS [52, 53, 57]. Although there was no sulfur metabolite that showed statistically significantly different levels between subjects with and without NAFLD having elevation of ALT in our study, the additional results showed that there was a tendency of difference in levels of S-sulfocysteine between subjects having NAFLD with normal ALT levels and those having NAFLD with elevation of ALT levels (p = 0.072, S1 Table). Although the influence of S-sulfocysteine on the liver is unclear, there is a possibility that sulfites and its derivatives induce oxidative stress [58, 59] and disturb mitochondrial function in rat experiments [60, 61]. Metabolomics in our study identified three metabolites that were significantly correlated with NAFLD having elevation of ALT, and one sulfur metabolite had the possibility of differentiating between subjects having NAFLD with elevation of ALT levels and those having NAFLD with normal ALT levels. These results suggest that metabolomics may become a useful screening test for NAFLD in individuals with MS during medical check-ups in the future.

Although the HOMA-IR and NAFIC scores effectively discriminated between subjects with and without NAFLD having elevation of ALT in our study, they were within the range of normal in almost all subjects. Therefore, not only persons whose HOMA-IR or NAFIC scores are high but also those whose HOMA-IR or NAFIC scores are within standard values should be carefully assessed during medical check-ups.

The present study had several limitations. First, it was a single-center study, and therefore may be subject to selection bias. For this reason, we instituted strict inclusion and exclusion criteria. Multi-center studies are needed to validate our findings. Second, different results may be found in patients who go to the hospital for NAFLD and those who are found to have NAFLD during medical check-ups because most of the participants in the present study were healthy individuals without symptoms. Further investigations of the differences between these groups are required. Third, we did not obtain information regarding treatments for hypertension and DM, diets (e.g., volume and contents including vegetable and fruits), and total caloric intake. Finally, the number of subjects who were investigated regarding metabolomics was small because metabolomics is not usually included in medical check-ups. Further studies are necessary to resolve these limitations.

In conclusion, we demonstrated that the prevalence of NAFLD having elevation of ALT was progressively higher in Non-MS, Pre-MS and MS groups. Significant independent predictors for NAFLD having elevation of ALT were different among the three groups. Not only liver scoring systems such as the HOMA-IR and NAFIC score but also several metabolites may help identify the risk of NAFLD in individuals with MS.

Supporting information

S1 Table. Comparison of 17 sulfur metabolites between subjects with NAFLD having elevation of ALT and subjects with NAFLD having standard values of ALT in 26 subjects with MS.

https://doi.org/10.1371/journal.pone.0238388.s002

(DOCX)

Acknowledgments

The authors would like to thank all subjects in our study.

References

  1. 1. Caballeria L, Auladell MA, Toran P, Miranda D, Aznar J, Pera G, et al. Prevalence and factors associated with the presence of nonalcoholic fatty liver disease in an apparently healthy adult population in primary care units. BMC Gastroenterol. 2007 Nov;5(7):41.
  2. 2. Amarapurkar DN, Hashimoto E, Lesmana LA, Sollano JD, Chen PJ, Goh KL. How common is non-alcoholic fatty liver disease in the Asia-Pacific region and are there local differences? J Gastroenterol Hepatol. 2007 Jun;22(6):788–93. pmid:17565631
  3. 3. Hamaguchi M, Kojima T, Takeda N, Nakagawa T, Taniguchi H, Fujii K, et al. The metabolic syndrome as a predictor of nonalcoholic fatty liver disease. Ann Intern Med. 2005 Nov 15;143(10):722–8. pmid:16287793
  4. 4. Nishioji K, Sumida Y, Kamaguchi M, Mochizuki N, Kobayashi M, Nishimura T, et al. Prevalence of and risk factors for non-alcoholic fatty liver disease in a non-obese Japanese population, 2011–2012. J Gastroenterol. 2015 Jan;50(1):95–108. pmid:24619537
  5. 5. Eguchi Y, Hyogo H, Ono M, Mizuta T, Ono N, Fujimoto K, et al. Prevalence and associated metabolic factors of nonalcoholic fatty liver disease in the general population from 2009 to 2010 in Japan: a multicenter large retrospective study. J Gastroenterol. 2012 May;47(5):586–95. pmid:22328022
  6. 6. Natarajan Y, Kramer JR, Yu X, Li L, Thrift AP, El-Serag HB, et al. Risk of Cirrhosis and Hepatocellular Cancer in Patients with Non-Alcoholic Fatty Liver Disease and Normal Liver Enzymes. Hepatology. 2020 Feb 5. pmid:32022277
  7. 7. The Examination Committee of Criteria for Metabolic Syndrome. The definition and criteria of metabolic syndrome. J Jpn Soc Intern Med. 2005;94:794–809.
  8. 8. Isokuortti E, Zhou Y, Peltonen M, Bugianesi E, Clement K, Bonnefont-Rousselot D, et al. Use of HOMA-IR to diagnose non-alcoholic fatty liver disease: a population-based and inter-laboratory study. Diabetologia. 2017 Oct;60(10):1873–82. pmid:28660493
  9. 9. European Association for the Study of the Liver (EASL), European Association for the Study of Diabetes (EASD), European Association for the Study of Obesity (EASO) (2016) EASLEASD-EASO clinical practice guidelines for the management of non-alcoholic fatty liver disease. Diabetologia. 2016 Jun;59(6):1121–40. pmid:27053230
  10. 10. Sumida Y, Yoneda M, Hyogo H, Yamaguchi K, Ono M, Fujii H, et al. A simple clinical scoring system using ferritin, fasting insulin, and type IV collagen 7S for predicting steatohepatitis in nonalcoholic fatty liver disease. J Gastroenterol. 2011 Feb;46(2):257–68. pmid:20842510
  11. 11. Sumida Y, Yoneda M, Hyogo H, Itoh Y, Ono M, Fujii H, et al. Validation of the FIB4 index in a Japanese nonalcoholic fatty liver disease population. BMC Gastroenterol. 2012 Jan 5;12:2. pmid:22221544
  12. 12. Sun W, Cui H, Li N, Wei Y, Lai S, Yang Y, et al. Comparison of FIB-4 index, NAFLD fibrosis score and BARD score for prediction of advanced fibrosis in adult patients with non-alcoholic fatty liver disease: A meta-analysis study. Hepatol Res. 2016 Aug;46(9):862–70. pmid:26763834
  13. 13. Saadeh S, Younossi ZM, Remer EM, Gramlich T, Ong JP, Hurley M, et al. The utility of radiological imaging in nonalcoholic fatty liver disease. Gastroenterology. 2002 Sep;123(3):745–50. pmid:12198701
  14. 14. Hamaguchi M, Kojima T, Itoh Y, Harano Y, Fujii K, Nakajima T, et al. The severity of ultrasonographic findings in nonalcoholic fatty liver disease reflects the metabolic syndrome and visceral fat accumulation. Am J Gastroenterol. 2007 Dec;102(12):2708–15. pmid:17894848
  15. 15. Kawano Y, Ohtsu I, Tamakoshi A, Shiroyama M, Tsuruoka A, Saiki K, et al. Involvement of the yciW gene in l-cysteine and l-methionine metabolism in Escherichia coli. J Biosci Bioeng. 2015 Mar;119(3):310–3. pmid:25277519
  16. 16. Kawano Y, Onishi F, Shiroyama M, Miura M, Tanaka N, Oshiro S, et al. Improved fermentative L-cysteine overproduction by enhancing a newly identified thiosulfate assimilation pathway in Escherichia coli. Appl Microbiol Biotechnol. 2017 Sep;101(18):6879–89. pmid:28756590
  17. 17. Golabi P, Otgonsuren M, de Avila L, Sayiner M, Rafiq N, Younossi ZM. Components of metabolic syndrome increase the risk of mortality in nonalcoholic fatty liver disease (NAFLD). Medicine (Baltimore). 2018 Mar;97(13):e0214. pmid:29595666
  18. 18. Grundy SM, Brewer HB Jr, Cleeman JI, Smith SC Jr, Lenfant C; American Heart Association; National Heart, Lung, and Blood Institute. Definition of metabolic syndrome: Report of the National Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related to definition. Circulation. 2004 Jan 27;109(3):433–8. pmid:14744958
  19. 19. Eckel RH, Alberti KG, Grundy SM, Zimmet PZ. The metabolic syndrome. Lancet. 2010 Jan 16;375(9710):181–3. pmid:20109902
  20. 20. Miyake T, Kumagi T, Furukawa S, Hirooka M, Kawasaki K, Koizumi M, et al. Hyperuricemia is a risk factor for the onset of impaired fasting glucose in men with a high plasma glucose level: a community-based study. PLoS One. 2014 Sep 19;9(9):e107882. pmid:25237894
  21. 21. Quiñones Galvan A, Natali A, Baldi S, Frascerra S, Sanna G, Ciociaro D, et al. Effect of insulin on uric acid excretion in humans. Am J Physiol. 1995 Jan;268(1 Pt 1):E1–5. pmid:7840165
  22. 22. Johnson RJ, Perez-Pozo SE, Sautin YY, Manitius J, Sanchez-Lozada LG, Feig DI, et al. Hypothesis: could excessive fructose intake and uric acid cause type 2 diabetes? Endocr Rev. 2009 Feb;30(1):96–116. pmid:19151107
  23. 23. Petta S, Cammà C, Cabibi D, Di Marco V, Craxì A. Hyperuricemia is associated with histological liver damage in patients with non-alcoholic fatty liver disease. Aliment Pharmacol Ther. 2011 Oct;34(7):757–66. pmid:21790685
  24. 24. Nakahara T, Hyogo H, Yoneda M, Sumida Y, Eguchi Y, Fujii H, et al; Japan Study Group of Nonalcoholic Fatty Liver Disease. Type 2 diabetes mellitus is associated with the fibrosis severity in patients with nonalcoholic fatty liver disease in a large retrospective cohort of Japanese patients. J Gastroenterol. 2014 Nov;49(11):1477–84. pmid:24277052
  25. 25. Aller R, Sigüenza R, Pina M, Laserna C, Antolín B, Burgueño B, et al. Insulin resistance is related with liver fibrosis in type 2 diabetic patients with non-alcoholic fatty liver disease proven biopsy and Mediterranean diet pattern as a protective factor. Endocrine. 2020 Apr 1. [Epub ahead of print] pmid:32239453
  26. 26. Moon HU, Ha KH, Han SJ, Kim HJ, Kim DJ. The Association of Adiponectin and Visceral Fat with Insulin Resistance and β-Cell Dysfunction. J Korean Med Sci. 2018 Dec 26;34(1):e7. pmid:30618514
  27. 27. Kahn SE, Hull RL, Utzschneider KM. Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature. 2006 Dec 14;444(7121):840–6. pmid:17167471
  28. 28. Sogabe M, Okahisa T, Hibino S, Yamanoi A. Usefulness of differentiating metabolic syndrome into visceral fat type and subcutaneous fat type using ultrasonography in Japanese males. J Gastroenterol. 2012 Mar;47(3):293–9 pmid:22065161
  29. 29. Eguchi Y, Eguchi T, Mizuta T, Ide Y, Yasutake T, Iwakiri R, et al. Visceral fat accumulation and insulin resistance are important factors in nonalcoholic fatty liver disease. J Gastroenterol. 2006 May;41(5):462–9. pmid:16799888
  30. 30. Koda M, Kawakami M, Murawaki Y, Senda M. The impact of visceral fat in nonalcoholic fatty liver disease: cross-sectional and longitudinal studies. J Gastroenterol. 2007 Nov;42(11):897–903. pmid:18008034
  31. 31. Browning JD, Horton JD. Molecular mediators of hepatic steatosis and liver injury. J Clin Invest. 2004 Jul;114(2):147–52. pmid:15254578
  32. 32. Schaffler A, Scholmerich J, Buchler C. Mechanisms of disease: adipocytokines and visceral adipose tissue: emerging role in nonalcoholic fatty liver disease. Nat Clin Pract Gastroenterol Hepatol. 2005 Jun;2(6):273–80. pmid:16265231
  33. 33. Stranges S, Dorn JM, Muti P, Freudenheim JL, Farinaro E, Russell M, et al. Body fat distribution, relative weight, and liver enzyme levels: a population-based study. Hepatology. 2004 Mar;39(3):754–63. pmid:14999694
  34. 34. Speliotes EK, Massaro JM, Hoffmann U, Vasan RS, Meigs JB, Sahani DV, et al. Fatty liver is associated with dyslipidemia and dysglycemia independent of visceral fat: the Framingham Heart Study. Hepatology. 2010 Jun;51(6):1979–87. pmid:20336705
  35. 35. Tomizawa M, Kawanabe Y, Shinozaki F, Sato S, Motoyoshi Y, Sugiyama T, et al. Triglyceride is strongly associated with nonalcoholic fatty liver disease among markers of hyperlipidemia and diabetes. Biomed Rep. 2014 Sep;2(5):633–636. pmid:25054002
  36. 36. Donnelly KL, Smith CI, Schwarzenberg SJ, Jessurun J, Boldt MD, Parks EJ. Sources of fatty acids stored in liver and secreted via lipoproteins in patients with nonalcoholic fatty liver disease. J Clin Invest. 2005 May;115(5):1343–51. pmid:15864352
  37. 37. Sanyal AJ, Campbell-Sargent C, Mirshahi F, Rizzo WB, Contos MJ, Sterling RK, et al. Nonalcoholic steatohepatitis: association of insulin resistance and mitochondrial abnormalities. Gastroenterology. 2001 Apr;120(5):1183–92. pmid:11266382
  38. 38. Lambert JE, Ramos-Roman MA, Browning JD, Parks EJ. Increased de novo lipogenesis is a distinct characteristic of individuals with nonalcoholic fatty liver disease. Gastroenterology. 2014 Mar;146(3):726–35. pmid:24316260
  39. 39. Fukuda Y, Hashimoto Y, Hamaguchi M, Fukuda T, Nakamura N, Ohbora A, et al. Triglycerides to high-density lipoprotein cholesterol ratio is an independent predictor of incident fatty liver; a population-based cohort study. Liver Int. 2016 May;36(5):713–20. pmid:26444696
  40. 40. Yokohama S, Yoneda M, Haneda M, Okamoto S, Okada M, Aso K, et al. Therapeutic efficacy of an angiotensin II receptor antagonist in patients with nonalcoholic steatohepatitis. Hepatology. 2004 Nov;40(5):1222–5. pmid:15382153
  41. 41. Georgescu EF, Ionescu R, Niculescu M, Mogoanta L, Vancica L. Angiotensin-receptor blockers as therapy for mild-to-moderate hypertension-associated non-alcoholic steatohepatitis. World J Gastroenterol. 2009 Feb 28;15(8):942–54. pmid:19248193
  42. 42. Sawada Y, Kawaratani H, Kubo T, Fujinaga Y, Furukawa M, Saikawa S, et al. Combining probiotics and an angiotensin-II type 1 receptor blocker has beneficial effects on hepatic fibrogenesis in a rat model of non-alcoholic steatohepatitis. Hepatol Res. 2019 Mar;49(3):284–295. pmid:30365236
  43. 43. Khusial RD, Cioffi CE, Caltharp SA, Krasinskas AM, Alazraki A, Knight-Scott J, et al. Development of a Plasma Screening Panel for Pediatric Nonalcoholic Fatty Liver Disease Using Metabolomics. Hepatol Commun. 2019 Aug 13;3(10):1311–21. pmid:31592078
  44. 44. Hartley A, Santos Ferreira DL, Anderson EL, Lawlor DA. Metabolic profiling of adolescent non-alcoholic fatty liver disease. Version 2. Wellcome Open Res. 2019 Sep 19 [revised 2019 Sep 19];3:166. 14974.2. eCollection 2018. pmid:30687796
  45. 45. Tokushige K, Hashimoto E, Kodama K, Tobari M, Matsushita N, Kogiso T, et al. Serum metabolomic profile and potential biomarkers for severity of fibrosis in nonalcoholic fatty liver disease. J Gastroenterol. 2013 Dec;48(12):1392–400. pmid:23478936
  46. 46. Qi S, Huang S, Chen X, Huo Q, Xie N, Xia J. Liver tissue metabolic profiling and pathways of non-alcoholic steatohepatitis in rats. Hepatol Res. 2017 Dec;47(13):1484–93. pmid:28224688
  47. 47. Di Bonito P, Valerio G, Licenziati MR, Miraglia Del Giudice E, Baroni MG, Morandi A, et al. J Endocrinol Invest. 2020 Apr;43(4):461–468. pmid:31637675
  48. 48. Klisic A, Kavaric N, Ninic A. Predictive Values of Serum Uric Acid and Alanine-aminotransferase for Fatty Liver Index in Montenegrin Population. J Med Biochem. 2019 Mar 26;38(4):407–17. pmid:31496904
  49. 49. Knip M, Douek IF, Moore WP, Gillmor HA, McLean AE, Bingley PJ, et al; European Nicotinamide Diabetes Intervention Trial Group. Safety of high-dose nicotinamide: a review. Diabetologia. 2000 Nov;43(11):1337–45. pmid:11126400
  50. 50. Mollica G, Senesi P, Codella R, Vacante F, Montesano A, Luzi L, et al. L-carnitine supplementation attenuates NAFLD progression and cardiac dysfunction in a mouse model fed with methionine and choline-deficient diet. Dig Liver Dis. 2019 Oct 10. pii: S1590–8658(19)30792-3.
  51. 51. Salic K, Gart E, Seidel F, Verschuren L, Caspers M, van Duyvenvoorde W, et al. Combined Treatment with L-Carnitine and Nicotinamide Riboside Improves Hepatic Metabolism and Attenuates Obesity and Liver Steatosis. Int J Mol Sci. 2019 Sep 5;20(18). pii: E4359. pmid:31491949
  52. 52. Ida T, Sawa T, Ihara H, Tsuchiya Y, Watanabe Y, Kumagai Y, et al. Reactive cysteine persulfides and S-polythiolation regulate oxidative stress and redox signaling. Proc Natl Acad Sci U S A. 2014 May 27;111(21):7606–11. pmid:24733942
  53. 53. Akaike T, Ida T, Wei FY, Nishida M, Kumagai Y, Alam MM, et al. Cysteinyl-tRNA synthetase governs cysteine polysulfidation and mitochondrial bioenergetics. Nat Commun. 2017 Oct 27;8(1):1177. pmid:29079736
  54. 54. Nishida M, Sawa T, Kitajima N, Ono K, Inoue H, Ihara H, et al. Hydrogen sulfide anion regulates redox signaling via electrophile sulfhydration. Nat Chem Biol. 2012 Aug;8(8):714–24. pmid:22772154
  55. 55. Shimizu T, Shen J, Fang M, Zhang Y, Hori K, Trinidad JC, et al. Sulfide-responsive transcriptional repressor SqrR functions as a master regulator of sulfide-dependent photosynthesis. Proc Natl Acad Sci U S A. 2017 Feb 28;114(9):2355–60. pmid:28196888
  56. 56. Fukuto JM, Ignarro LJ, Nagy P, Wink DA, Kevil CG, Feelisch M, et al. Biological hydropersulfides and related polysulfides—a new concept and perspective in redox biology. FEBS Lett. 2018 Jun;592(12):2140–52. pmid:29754415
  57. 57. Hamid HA, Tanaka A, Ida T, Nishimura A, Matsunaga T, Fujii S, et al. Polysulfide stabilization by tyrosine and hydroxyphenyl-containing derivatives that is important for a reactive sulfur metabolomics analysis. Redox Biol. 2019 Feb;21:101096. pmid:30634125
  58. 58. Chiarani F, Bavaresco CS, Dutra-Filho CS, Netto CA, Wyse AT. Sulfite increases lipoperoxidation and decreases the activity of catalase in brain of rats. Metab Brain Dis. 2008 Mar;23(1):123–32. pmid:18034293
  59. 59. Abedinzadeh Z. Sulfur-centered reactive intermediates derived from the oxidation of sulfur compounds of biological interest. Can J Physiol Pharmacol. 2001 Feb;79(2):166–70. pmid:11233565
  60. 60. Zhang X, Vincent AS, Halliwell B, Wong KP. A mechanism of sulfite neurotoxicity: direct inhibition of glutamate dehydrogenase. J Biol Chem. 2004 Oct 8;279(41):43035–45. pmid:15273247
  61. 61. Grings M, Moura AP, Parmeggiani B, Marcowich GF, Amaral AU, de Souza Wyse AT, et al. Disturbance of brain energy and redox homeostasis provoked by sulfite and thiosulfate: potential pathomechanisms involved in the neuropathology of sulfite oxidase deficiency. Gene. 2013 Dec 1;531(2):191–8. pmid:24035933