Serum Desmosterol Level Reflects Hepatic Inflammation Grade in Patients with Biopsy-Confirmed Metabolic Dysfunction-Associated Steatotic Liver Disease

Abstract

Aim: Desmosterol, a cholesterol precursor, is converted by Δ24-dehydrocholesterol reductase. Hence, desmosterol levels are considered to reflect cholesterol metabolism. This study aimed to evaluate sterols as novel biomarkers of liver condition in Asian moderate obese patients with metabolic dysfunction-associated steatotic liver disease (MASLD).

Methods: In total, 218 patients with MASLD who underwent liver biopsy were prospectively enrolled. Liver biopsy samples were evaluated by a well-versed pathologist according to the criteria. The serum sterols of biopsy-proven patients’, such as desmosterol, sitosterol, and campesterol, of the patients with biopsy-proven MASLD were analyzed using liquid chromatography-mass spectrometry.

Results: Inflammation grade 0/1/2/3 was observed in 8/107/90/12 patients, and fibrosis stage 0/1/2/3/4 was observed in 25/48/64/63/17 patients, respectively. Serum desmosterol levels were significantly different by inflammation grade 0-3 (one-way analysis of variance [ANOVA], p = 0.004), with a beta coefficient of 0.219 (95% confidence interval [CI]: 0.088-0.350, p＜0.01). Ordinal logistic regression analysis data on inflammation grade, adjusted for other parameters, showed that desmosterol had an odds ratio of 3.727 (95% CI 1.422-9.901, p＜0.005). Although desmosterol levels are influenced by statin treatment, in non-statin-treated patients, serum desmosterol levels remained significantly different by inflammation grade (one-way ANOVA, p = 0.041), and the beta coefficient was 0.233 (95% CI: 0.066-0.400, p＜0.01).

Conclusions: Serum desmosterol levels indicated the degree of hepatic inflammatory activity in patients with MASLD. Since desmosterol, a ligand of nuclear receptor LXR, reflects hepatic cholesterol metabolism, we hope that our findings will contribute to establishing a novel biomarker to screen the high-risk patients for cardiovascular diseases in MASLD.

See editorial vol. 33: 20-23

Introduction

Desmosterol and lathosterol are cholesterol synthesis markers. Desmosterol, a cholesterol precursor, is converted by Δ24-dehydrocholesterol reductase (DHCR24) (Fig.1). Hence, desmosterol levels are considered to reflect cholesterol metabolism. Sitosterol and campesterol are also known as cholesterol absorption markers^{1, 2)}. A previous report indicated that cholesterol homeostatic pathways were abnormal, such as increased 3-hydroxy-3-methlgutaryl coenzyme-A (HMG-CoA) reductase expression and decreased low-density lipoprotein (LDL) receptor expression in patients with non-alcoholic fatty liver disease (NAFLD)³⁾. Moreover, serum levels of desmosterol and lathosterol were increased in patients with NAFLD, and among them serum desmosterol level, which was correlated with liver desmosterol level and significantly increased in patients with non-alcoholic steatohepatitis (NASH)⁴⁾. However, it’s important to note that the subjects underwent bariatric surgery and a mean BMI of those was 45.0±6.1 kg/m^{2 2)}. Since those are not common population in Asia, it is valuable to perform a new study in Asian mild to moderate obese patients with MASLD.

Fig.1. A simplified scheme of cholesterol synthesis pathway from acetyl-CoA

In the Bloch pathway, desmosterol is the last precursor of cholesterol, catalyzed by DHCR24. In the Kandutch-Russel pathway, lathosterol is the second to the last precursor of cholesterol. Abbreviations: acetyl-CoA, acetyl coenzyme A; DHCR24, 24-dehydrocholesterol reductase

Previous studies revealed that NAFLD was significantly associated with increased overall mortality, especially NASH, which has a higher risk than simple steatosis, and the fibrosis stage was related to liver-related events^{5, 6)}. Clinically, metabolic dysfunction-associated steatotic liver disease (MASLD) has almost identical prevalence compared with NAFLD, and some studies have shown up some crucial comorbidities, such as cardiovascular disease (CVD) and cancer as well as NAFLD^{7, 8)}.

From this perspective, evaluating liver pathological condition is essential to prevent the progression of MASLD⁹⁾. There are many biomarkers and non-invasive diagnostics for liver steatosis and fibrosis, with the FIB4-index, Mac2-binding protein (Mac2BP), and ultrasound or magnetic resonance elastography being well-known and valuable in clinical settings^10-12). However, no robust biomarkers or non-invasive tools exist to evaluate the liver pathological condition in addition to steatosis or fibrosis.

Aim

Since the classification of steatotic liver disease was recently revised¹³⁾, we need to validate the relevance of sterols and liver histology in patients with MASLD. This study aimed to evaluate sterols as novel biomarkers of liver condition in Asian moderate obese patients with MASLD.

Methods

Patients

This was a prospective observational study conducted at a single center. A total of 218 patients clinically considered to have metabolic dysfunction-associated steatohepatitis MASLD or metabolic dysfunction-associated steatohepatitis (MASH) were prospectively enrolled between July 2016 and March 2023 at Saga University. All of the subjects have less than 20g (female) -30g (male) alcohol intake. Patients with a desmosterol value greater than seven times the standard deviation were excluded as outliers. Therefore, 217 patients were included in the final analysis. Informed consent was obtained from all patients, and the study was approved by the institutional ethical board (R6-19). The study protocol conforms to the ethical guidelines of the Declaration of Helsinki.

Histopathological Analysis

Liver biopsy was performed in all patients, and the samples were centrally reviewed by an experienced pathologist (S.A.) specializing in liver pathology who was blinded to the patients’ data. Hepatic steatosis, lobular inflammation, and hepatocyte ballooning were evaluated using the NAFLD activity scores¹⁴⁾. The liver fibrosis stage was classified based on reports by Kleiner et al.¹⁴⁾ and Brunt et al.¹⁵⁾.

Measurement of Sterol Species in Serum

Lipids were extracted from the serum samples and the concentrations of sterol species were measured. Serum (20 µL) was saponified with potassium hydroxide and mixed with magnesium sulfate and tert-butyl methyl ether. After the ether layer was extracted, it was dried under the N2 gas stream, dissolved with 40 µL of isopropanol, and used to measure the concentration of sterol species using liquid chromatography and mass spectrometry (LC-MS/MS) at BML, Inc, Japan.

Statistical Analysis

Data are expressed as numbers (%) or mean±standard deviation. The normality of data distribution was tested using the Kolmogorov–Smirnov test. Normal distributions were compared using Student’s t-test. The missing values were obtained using simple imputation. Median and mean imputations were used for non-normal and normal distributions, respectively. One-way analysis of variance (ANOVA) with Tukey’s post-hoc test was used to compare stratified pathological evaluations. Correlation coefficients (CCs) between desmosterol and the other parameters were analyzed using Pearson’s CC (r). Multiple regression analysis was performed to determine the determinants of inflammation grade. Ordinal logistic regression analysis was performed by adjusting for factors related to the objective variable, with multiple imputations for the missing values. Regression analyses were run across 10 imputed datasets with up to 50 iterations, and pooled estimates were reported. A p-value of ＜0.05 was considered statistically significant. All statistical analyses were performed using R version 4.3.1.

Results

Patients’ Characteristics

Patient characteristics are shown in Table 1. Among 217 patients, 86 (39.6%) were men, the mean age was 59.7 years, and the mean body mass index (BMI) was 30.1 kg/m², As for the prevalence of diseases related to CVD risk,127 (58.5%) had diabetes mellitus, and 147 (67.7%) had hypertension. Of the patients, 160 (73.7%) had dyslipidemia with mean values of total cholesterol (T-Cho), triglyceride, low-density-lipoprotein cholesterol (LDL-C), and high-density-lipoprotein cholesterol (HDL-C) of 180 mg/dL, 150 mg/dL, 114 mg/dL, and 49 mg/dL, respectively. The mean levels of aspartate aminotransaminase, alanine aminotransaminase (ALT), and gamma-glutamyltransferase were 58, 66, and 84 U/L, respectively. The mean values of serum desmosterol, sitosterol, and campesterol were 0.89 µg/mL, 2.96 µg/mL, and 5.26 µg/mL, respectively. In terms of liver histology, steatosis grade 0/1/2/3 was observed in 12/135/44/26; inflammation grade 0/1/2/3 in 8/107/90/12; ballooning grade 0/1/2 in 59/99/59; and fibrosis stage 0/1/2/3/4 in 25/48/64/63/17 patients.

Table 1.Characteristics of the studied patients

Clinical data (n = 217)	Frequency, values
Sex, male (%)	86 (39.6)
Age (years)	59.7±12.6
BMI (kg/m2)	30.1±6.3
Current smoker (%)	47 (21.7)
Diabetes Mellites (%)	127 (58.5)
Hypertension(%)	147 (67.7)
CoronaryHeart disease (%)	17 (7.8)
Dyslipidemia (%)	160 (73.7)
AST(U/L)	58±34
ALT (U/L)	66±46
γ-GTP(U/L)	84±109
Creatinine (mg/dl)	0.72±0.20
Platelet count (x104/µL)	20.1±6.9
FBS (mg/dl)	113±26
HbA1c (%)	6.3±0.9
T-Cho (mg/dl)	180±34
Triglyceride (mg/dL)	150±72
LDL-C (mg/dl)	114±29
HDL-C (mg/dl)	49±12
Desmosterol (µg/ml)	0.89±0.35
Sitosterol (µg/ml)	2.96±1.37
Campesterol (µg/ml)	5.26±2.40
Treatment	Frequency (%)
Stalin	83 (382)
Ezetimibe	7 (3.2)
Fibrate	15 (6.9)
Pioglitazone	5 (2.3)
GLP-1RA	12 (5.5)
SGLT2-i	31 (14.3)
Histology	Frequency (%)
Steatosis grade
0	12 (6)
1	135 (62)
2	44 (20)
3	26 (12)
Inflammation grade
0	8 (4)
1	107 (49)
2	90 (41)
3	12 (6)
Ballooning grade
0	59 (27)
1	99 (46)
2	59 (27)
Fiorosis stage
0	25 (12)
1	48 (22)
2	64 (29)
3	63 (29)
4	17 (8)

Note: Data are expressed as number (%) or mean±standard deviation. A patient with a value of desmosterol greater than seven times standard deviation was excluded as an outlier. HbA1c was completed with simple imputation (median imputation, 1.8%, 4/217). LDL-C and HDL-C were completed with simple imputation (mean imputation, 1.4%, 3/217, 0.2%, 1/217, respectively).

Abbreviation: γ-GTP, gamma-glutamyl transpeptidase; AST, aspartate transaminase; ALT, alanine transaminase; BMI, body mass index; FBS, fasting blood sugar; GLP-1RA, Glucagon-like Peptide 1 Receptor Agonist; HbA1c, glycated hemoglobin; HDL, High density lipoprotein; LDL-C; Low density lipoprotein cholesterol; SGLT2-i, sodium-glucose co-transporter 2 inhibitor; T-Cho, Total cholesterol

The Value of Desmosterol was Associated with Hepatic Inflammation Grade

As desmosterol is a precursor of cholesterol, we first examined the correlation between serum desmosterol levels and other parameters (Table 2). The CC with desmosterol was analyzed using Pearson’s test. The CCs of T-Cho and LDL-C with desmosterol were 0.546 (p＜0.001) and 0.525 (p＜0.001), respectively, indicating moderate correlations.

Table 2.Correlation with desmosterol

	Correlation Coefficient	p value
T-Cho	0.546	＜0.001
LDL-C	0.525	＜0.001
Triglyceride	0.270	＜0.001
ALT	0.196	＜0.01
Ferritin	0.168	＜0.05
HOMA-R	0.166	＜0.05
Alb	0.112	0.110
AST	0.095	0.163
Weight	0.056	0.418
WBC	0.021	0.768
FBS	0.006	0.930
BUN	0.002	0.973
BMI	0.016	0.816
HDL-C	-0.005	0.940
γ-GTP	-0.008	0.912
ALP	-0.019	0.785
Creatinine	-0.057	0.417
HbA1c	-0.069	0.314
Platelet count	-0.074	0.29
Age	-0.162	＜0.05

Note: Correlation coefficient with desmosterol were analyzed by Pearson’s test. HOMA-R, Ferritin and HbA1c were completed with simple imputation (median imputation, 17.1%, 37/217, 0.9%, 2/217, and 1.8%, 4/217 respectively). In terms of HOMA-R, the data of insulin-treated patients (n = 5) were also dealt with as missing values. LDL-C and HDL-C were also completed with simple imputation (mean imputation, 1.4%, 3/217, 0.2%, 1/217, respectively).

Abbreviation: γ-GTP, gamma-glutamyl transpeptidase; AST, aspartate transaminase; ALT, alanine transaminase; BMI, body mass index; FBS, fasting blood sugar; HbA1c, glycated hemoglobin; HDL, High density lipoprotein; HOMA-R, homeostasis model assessment insulin resistance; LDL-C; Low density lipoprotein cholesterol; T-Cho, Total cholesterol

The association between serum desmosterol, T-Cho, and LDL-C levels and the pathological grade was analyzed (Fig.2). The value of serum desmosterol was significantly different according to the inflammation grade (one-way ANOVA, p = 0.004) (Fig.2a). In addition, a significant positive correlation was identified between the value of desmosterol and inflammation grade, with a beta coefficient of 0.219 (95% confidence interval [CI]: 0.088-0.350, p＜0.01). However, the value of serum desmosterol was not significantly different across steatosis grades, ballooning grades, and fibrosis stages. In contrast, T-Cho and LDL-C levels were not significantly different among the different inflammation grades (one-way ANOVA, p = 0.504 and 0.648, respectively), and the beta coefficients were 0.075 and 0.078 (p = 0.273 and 0.256, respectively) (Fig.2b and 2c). The T-Cho value was significantly different by the fibrosis stage (ANOVA, p = 0.047), however, Tukey’ s post-hoc test revealed no significant difference in any groups (Fig.2b). The value of serum sitosterol and campesterol were not significantly different according to any pathological grade (Supplementary Fig.1a and 1b).

Fig.2. Serum desmosterol, T-Cho, and LDL-C are stratified with pathological evaluation and analyzed by one-way analysis of variance

(a) Desmosterol values stratified by steatosis grade, inflammation grade, ballooning grade, and fibrosis stage. Linear regression analysis shows significantly positive correlation between desmosterol values and inflammation grade (beta coefficient: 0.2187, 95% confidence interval [CI]: 0.088-0.350, p＜0.01). (b) T-Cho values stratified by steatosis grade, inflammation grade, ballooning grade, and fibrosis stage. Linear regression analysis shows a not significant positive correlation between T-Cho values and inflammation grade (beta coefficient: 0.075, 95% CI: -0.059-0.209, p = 0.273). (c) LDL-C values stratified by steatosis grade, inflammation grade, ballooning grade, and fibrosis stage. Linear regression analysis shows a not significant positive correlation between LDL-C values and inflammation grade (beta coefficient: 0.078, 95% CI: -0.057 to -0.211, p = 0.256). Asterisk means p value of significant difference in Tukey’s post-hoc test (^＊p＜0.05, ^＊＊p＜0.01). Abbreviations: T-Cho, total cholesterol; LDL-C; low-density lipoprotein cholesterol.

Supplementary Fig.1. Serum sitosterol and campesterol are stratified with pathological evaluation and analyzed by one-way analysis of variance

(a) Sitosterol values stratified by steatosis grade, inflammation grade, ballooning grade, and fibrosis stage. There are no significant differences. (b) Campesterol values stratified by steatosis grade, inflammation grade, ballooning grade, and fibrosis stage. There are no significant differences.

Multiple Regression Analyses of Inflammation Grade

Multivariate analysis was performed to investigate the potential influencing factors and included parameters to affect the inflammation grade of the liver. Ordinal logistic regression analysis data on inflammation grade adjusted for serum desmosterol, ALT, T-Cho, LDL-C, Triglyceride, BMI, weight, ferritin and homeostasis model assessment of insulin resistance (HOMA-R), showed that serum desmosterol had an odds ratio (OR) of 3.727 (95% CI 1.422-9.901, p＜0.005) and ALT had an OR of 1.012 (95% CI 1.004-1.020, p＜0.005) for inflammation grade (Table 3). This ordinal logistic regression was conducted after missing values were completed with multiple imputations (LDL-C, 1.4%, 3/217; ferritin, 0.9%, 2/217; HOMA-R, 17.1%, 37/217). The variances inflation factor was ＜10.0.

Table 3.Adjusted odds ratio for Inflammation grades

	Odds ratio	95% Cl	p value
Desmosterol	3.727	[1.422-9.901]	＜0.005
ALT	1.012	[1.004-1.020]	＜0.005
Age	1.036	[1.006-1.066]	＜0.05
HOMA-R	1.057	[0.996-1.126]	0.072
BMI	1.043	[0.942-1.155]	0.417
LDL-C	1.005	[0.988-1.023]	0.577
Triglyceride	1.002	[0.997-1.006]	0.444
Ferritin	0.999	[0.998-1.000]	0.217
T-Cho	0.991	[0.975-1.007]	0.258
Weight	0.988	[0.955-1.022]	0.490

Note: This ordinal logistic regression was done after missing values completed with multiple imputation (LDL-C, 1.4%, 3/217; Ferritin, 0.9%, 2/217; HOMA-R, 17.1%, 37/217).

Abbreviation: ALT, alanine transaminase; BMI, body mass index; HOMA-R, homeostasis model assessment insulin resistance; LDL-C; Low density lipoprotein cholesterol; T-Cho, Total cholesterol

Association of Desmosterol and Lipid-Lowering Agents

Desmosterol levels may be affected by statins. Hence, comparing serum desmosterol levels between statin-treated and non-statin-treated patients, it was significantly decreased by approximately 34 % in statin-treated patients (p＜0.0001) (Fig.3a). Therefore, we performed further tests intended for only non-statin-treated patients. We confirmed an association between desmosterol levels and inflammation grade in non-statin-treated patients. The value of serum desmosterol remained significantly different by inflammation grade (one-way ANOVA, p = 0.041), and the beta coefficient was 0.233 (95% CI: 0.066-0.400, p＜0.01) (Fig.3b). In addition, ezetimibe is the inhibitor of Niemann-Pick C1-Like 1 (NPC1L1) and we tested data from non-ezetimibe-treatment patients. There is no significant difference in desmosterol levels with ezetimibe-treated and non-ezetimibe-treated patients (Supplementary Fig.2).

Fig.3. Desmosterol decreases with statin treatment

(a) The serum level of desmosterol is significantly decreased in statin-treated patients (Student’s t-test, p＜0.0001). (b) The value of serum desmosterol of non-statin-treated patients remains significantly different by inflammation grade (ANOVA, p = 0.041). Linear regression analysis still shows a significantly positive correlation between desmosterol values and inflammation grade (beta coefficient: 0.233, 95% CI: 0.066-0.400, p＜0.01). Asterisk means p value of significant difference in Tukey’s post-hoc test (^＊p＜0.05).

Supplementary Fig.2. Desmosterol levels with ezetimibe treatment

The serum level of desmosterol is not significantly different with ezetimibe-treated and non-ezetimibe-treated patients (Student’s t-test, p = 0.45).

Discussion

The present study demonstrated that the serum desmosterol level was significantly different among the stratified inflammation grades of liver pathological evaluation. We also found that serum desmosterol was an independent determinant of inflammation grade with a high odds ratio. Hence, serum desmosterol could stratify the inflammation grade of the liver and may be an ideal biomarker for understanding the liver condition. Recently, Kamada et al. reported that the prevalence of MASLD has reached approximately 20% in Japan, and 99% of patients with MASLD and 97% of patients with NAFLD were overlapping patients¹⁶⁾. Similar to those with NAFLD, patients with MASLD have some crucial comorbidities, such as CVD and, non-hepatic cancer^{7, 8)}. Given the large gap in mortality or incidence ratio of CVD between simple steatosis and steatohepatitis, non-invasive tests to identify these conditions are urgently needed. In terms of the prediction of liver condition in patients with MASLD, some biomarkers, such as Mac2BP and cytokeratin 18 (CK18) fragments, are clinically used. Mac2BP is a reliable value for assessing liver fibrosis stage⁹⁾. CK18 fragment is a novel noninvasive diagnostic marker of MASH and reflects the progression and improvement of MASH¹⁷⁾.

As desmosterol is a precursor of cholesterol in the Bloch pathway, the level of desmosterol decreases with statin treatment, which is an inhibitor of 3-hydroxy-3-methlgutaryl coenzyme-A reductase. Therefore, we performed further tests divided by statin-treated or non-statin-treated patients. In non-statin-treated patients, an association between serum desmosterol levels and inflammation grade remained. In statin-treated patients, serum desmosterol levels also tended to increase with the degree of inflammation, which was not significant owing to the small sample size. Further evaluation will be required.

In the severely obese patients who underwent bariatric surgery with a mean BMI of 45.0±6.1 kg/m², Simonen et al. reported that serum desmosterol level was associated with liver cholesterol level, and serum desmosterol was significantly elevated in patients with NASH compared with those without⁴⁾. However, our study population has a mean BMI of 30.1±6.3 kg/m², which was approximately the same as the median BMI of 29.6 kg/m² of Asian patients with obesity and NAFLD in a meta-analysis¹⁸⁾. In the present study, we determined that serum desmosterol levels could reflect the degree of liver inflammation in Asian patients with moderate but not severe obesity. A previous paper analyzing noncholesterol sterol in 667,718 patients reported that serum desmosterol levels were higher in younger men than women²⁾. For clinical application, it will be required to determine cutoff value depending on age and gender in the future study. Moreover, it would be valuable if the cutoff was determined to identify individuals at high risk for atherosclerotic cardiovascular disease.

Concerning the association of desmosterol and liver inflammation, desmosterol, which is converted by DHCR24 into cholesterol, has the role of endogenous liver X receptor (LXR) agonist with anti-inflammatory effects. In contrast, LXR agonists cause hypertriglyceridemia by inducing the expression of sterol regulatory element-binding protein (SREBP)1c and downstream genes that induce fatty acid biosynthesis¹⁹⁾. In macrophage, when the levels of desmosterol and upstream sterol intermediates were reduced, LXR activation was decreased and inflammasome activation was increased. In contrast, increasing desmosterol leads to an appropriate homeostatic response of LXRs and SREBPs, indicating that desmosterol has an anti-inflammatory effect^{20, 21)}. As regard this fact, DHCR24 has gained more attention recently, which is the enzyme catalyzing conversion of desmosterol into cholesterol, because its inhibitor could increase desmosterol with restricting SREBPs in hepatocytes, decrease hepatic lipids, and reduce hepatic inflammation in vivo^22-24).

The present study has limitations. First, this was a single-center observational study with a relatively small sample size, leading to limited statistical power. Second, since this is a prospective observational study, it is difficult to examine whether high serum desmosterol predicts the future development of liver-related disease, non-liver-related malignancies, cardiovascular disease, or death. Third, the method used to measure serum desmosterol levels was not common. Desmosterol has a chemical structure similar to that of cholesterol; therefore, it is difficult to measure using common general enzyme immunoassays. Therefore, gas chromatography-mass spectrometry (GC-MS) and LC-MS were employed. LC-MS is more useful than GC-MS because it can measure a larger number of samples. However, LC-MS/MS remains unfamiliar in the clinical setting. Finally, our results were obtained during the observational period. Hence, we must follow the prognoses of these patients to determine the associations between serum desmosterol and MASLD, as well as its comorbidities.

Conclusions

Our results showed that serum desmosterol levels reflected the degree of liver inflammation in the histological condition of MASLD, implicating that cholesterol metabolism played an important role in the inflammation of steatotic liver disease. Since cholesterol metabolism is also associated with atherosclerotic cardiovascular disease, our findings may contribute to establishing a novel biomarker to screen high-risk patients for cardiovascular diseases in MASLD.

Acknowledgments

We would like to thank Editage (www.editage.jp) for English language editing.

Funding Statement

This study was supported by the Japan Society for the Promotion of Science KAKENHI (grant number: 22K08670, 23K07968) and the Japan Agency for Medical Research and Development (AMED) (grant number J230705536; 23rea522010h0001).

Etics Approval Statement

Approval of the research protocol: The study protocol conformed to the ethical guidelines of the World Medical Association Declaration of Helsinki and received ethical approval from the Institutional Review Board of Saga University Hospital (R6-19).

Informed consent: The study was exempt from informed consent requirements as pre-existing data were used.

Registry and the registration no. of the study/trial: N/A.

Animal studies: N/A.

Conflict of Interest Statement

M.K., H.T, Y.K., and H.Y. received a lecture fee. H.Y. received fees for promotional materials from the Kowa Company Ltd. and Denka Company Ltd. M.K. was supported by a research grant from the Kowa Company, Ltd. H.T. was supported by a research grant from the Takeda Pharmaceutical Company, Ltd. T.O (Omatsu)., K.I., A.S., H.S., K.T., H.I., T.O (Okada)., M.N., S.A. and Y.S. declare no competing interests.

Abbreviations:

ALT, alanine transaminase; ANOVA, analysis of variance; BMI, body mass index; CC, correlation coefficient; CI, confidence interval; GC-MS, gas chromatography-mass spectrometry; HOMA-R, homeostasis model assessment of insulin resistance; LC-MS/MS, liquid chromatography-mass spectrometry; LDL-C; low density lipoprotein cholesterol; MASLD, metabolic dysfunction associated steatotic liver disease; MASH, metabolic dysfunction associated steatohepatitis; NAFLD, non-alcoholic fatty liver disease; NASH, non-alcoholic steatohepatitis; T-Cho, total cholesterol

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