Journal of Obesity & Metabolic Syndrome

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June, 2024 | Vol.33 No.2

J Obes Metab Syndr 2024; 33(2): 143-154

Published online June 30, 2024 https://doi.org/10.7570/jomes23072

Copyright © Korean Society for the Study of Obesity.

Muscle Quality as a Potential Diagnostic Marker of Advanced Liver Fibrosis in Patients with Non-alcoholic Fatty Liver Disease

Natsumi Oshida1, Sechang Oh2, Bokun Kim3, Ikuru Miura4, Naoyuki Hasegawa5, Shoichi Komine6, Tomonori Isobe5, Junichi Shoda5,*

1Division of Laboratory Medicine, Tsukuba University Hospital, Tsukuba; 2Faculty of Rehabilitation, R Professional University of Rehabilitation, Tsuchiura, Japan; 3Future Convergence Research Institute, Changwon National University, Changwon, Korea; 4Faculty of Sports and Health Science, Fukuoka University, Fukuoka; 5Department of Medical Sciences, Faculty of Medicine, University of Tsukuba, Tsukuba; 6Faculty of Human Care, Teikyo Heisei University, Tokyo, Japan

Correspondence to:
Junichi Shoda
https://orcid.org/0000-0001-9374-994X
Department of Medical Sciences, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8575, Japan
Tel: +81-29-853-3291
Fax: +81-29-853 3291
E-mail: shodaj@md.tsukuba.ac.jp

The first two authors contributed equally to this study.

Received: October 29, 2023; Reviewed : December 22, 2023; Accepted: February 23, 2024

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Background: Muscle–liver crosstalk plays an important role in the development and progression of non-alcoholic fatty liver disease (NAFLD). The measurement of muscle echo-intensity during ultrasonography is a real-time, non-invasive method of assessing muscle quality. In this retrospective study, we investigated the significance of poor muscle quality (namely, a greater mass of non-contractile tissue, including intramuscular fat) as a risk factor for advanced liver fibrosis and considered whether it may represent a useful tool for the diagnosis of advanced liver fibrosis.
Methods: We analyzed data from 307 patients with NAFLD (143 men and 164 women) who visited the University of Tsukuba Hospital between 2017 and 2022. The patients were stratified into the following tertiles of muscle quality according to their muscle echo-intensity on ultrasonography: modest (84.1 arbitrary units [A.U.]), intermediate (97.4 A.U.), and poor (113.6 A.U.). We then investigated the relationships between muscle quality and risk factors for advanced liver fibrosis and calculated appropriate cutoff values.
Results: Patients with poor muscle quality showed a significant, 7.6-fold greater risk of liver fibrosis compared to those with modest muscle quality. Receiver operating characteristic curve analysis showed that muscle quality assessment was as accurate as the fibrosis-4 index and NAFLD fibrosis score in screening for liver fibrosis and superior to the assessment of muscle quantity and strength, respectively. Importantly, a muscle echo-intensity of ≥92.4 A.U. may represent a useful marker of advanced liver fibrosis.
Conclusion: Muscle quality may represent a useful means of identifying advanced liver fibrosis, and its assessment may become a useful screening tool in daily practice.

Keywords: Non-alcoholic fatty liver disease, Non-alcoholic steatohepatitis, Liver cirrhosis, Intramuscular fat, Muscle quality, Sarcopenia, Muscle echo-intensity

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease, affecting an estimated 25% of the global population.1 It can be divided into two subtypes, non-alcoholic fatty liver and non-alcoholic steatohepatitis (NASH), with the latter involving liver inflammation and fibrosis. NASH is a severe liver disease that can progress to cirrhosis and hepatocellular carcinoma. The proportion of patients with NASH among those with NAFLD is predicted to increase in the coming decades, owing to the aging of the population and the predicted associated increase in the prevalence of type 2 diabetes mellitus,2 which in turn suggests that the incidences of both advanced liver disease and liver-related mortality will similarly increase. The development of liver fibrosis is the most important prognostic factor in NASH.3

The concept of muscle–liver crosstalk has recently been reported based on the higher risks of liver fibrosis4 and liver disease-related mortality (from cirrhosis and/or liver cancer) in patients with NAFLD who have low muscle mass.5 We have shown that abnormal body composition, consisting of greater visceral fat mass and lower muscle mass, affects the progression of NASH.6 Liver fibrosis is worse in patients with NAFLD and a decreased ratio of muscle mass to visceral fat area (an index of sarcopenic obesity).7 In addition, longitudinal increases in muscle quantity are associated with an amelioration of NAFLD pathology.8 There is a broad consensus that increasing muscle mass plays an important role in ameliorating liver disease.9

A recent study showed that changes in muscle composition, involving the accumulation of intramuscular fat both inside and outside the muscle fibers, are closely associated with the development of NASH.10 Intramuscular fat can damage muscle fibers through lipotoxicity, leading to lower muscle quality.11 Therefore, muscle quality can be quantified through the assessment of fat degeneration or fat infiltration of the muscle.12 Poor muscle quality can cause insulin resistance, which involves a disruption of muscle cell signaling and impairments in metabolism, glucose uptake by muscle cells, and muscle energy production.13 These changes in muscle metabolism have been linked to the development of NASH,14 but the complex relationship between muscle quality and NASH is not yet fully understood.

For the assessment of muscle quality, ultrasonography using the brightness mode, which is a non-invasive and real-time diagnostic technique, offers a convenient means of evaluating skeletal muscle.15 A novel ultrasonographic approach called echo-intensity allows the assessment of muscle quality through the recognition of a higher volume of non-contractile tissue, including intramuscular fat, which manifests as greater muscle echo-intensity. This method enables the identification of fat infiltration in muscle, as demonstrated using magnetic resonance spectroscopy (MRS) (Fig. 1) and muscle biopsy.16 Furthermore, in our previous study,17 leg muscle echo-intensity measured during ultrasonographic imaging and extra- myocellular lipid content measured during MRS (both of which reflect myosteatosis and atrophy) positively correlated with urinary concentrations of titin-N fragment, a biomarker of skeletal muscle deterioration and functional decline.18

In the present retrospective study, we investigated the importance of poor muscle quality (namely, a larger amount of non-contractile tissue, including intramuscular fat) as reflected by the presence of greater muscle echo-intensity on ultrasonography, as a risk factor for advanced liver fibrosis in patients with NAFLD. We also evaluated the utility of such a muscle-quality assessment for use as a screening tool for advanced liver fibrosis in non-obese patients with NAFLD.

Patients

We retrospectively analyzed 307 patients who had been diagnosed with NAFLD (143 men and 164 women) and were first referred to the University of Tsukuba Hospital between January 2017 and December 2022 after fatty liver had been identified through a complete medical examination or examinations performed at other clinics. The diagnosis of NAFLD was made according to the NAFLD Clinical Practice Guidelines, based on at least two of the following abdominal ultrasonographic findings: hepato-renal echo contrast, vascular opacity, and deep echogenic attenuation. The patients were stratified according to tertiles of muscle quality, based on their muscle echo-intensity level on ultrasonography, as having modest, intermediate, or poor muscle quality. The study was approved by the ethics committee of the Graduate School of Medicine, University of Tsukuba (approval nos. H26-18 and H25-154) and complied with the principles of the 1975 Declaration of Helsinki. Written informed consent was obtained from all participants.

Muscle ultrasonography

Muscle echo-intensity was determined as the mean intensity of the pixels within the muscle of interest, usually on a gray scale within a given region of interest. An Aplio500 system (Canon) with an 8- to 12-MHz electronic linear probe was used to complete ultrasonographic imaging. The standardized image-quality conditions included a 90-dB gain, 7-cm depth, 9-MHz frequency, and 69-Hz dynamic range, with the sensitivity time control set in the middle for constant gain. The same examiner conducted all the measurements at the anterior iliac spine and the midpoint of the superior border of the patella of the dominant leg, with the participant in a supine position. Muscle intensity was calculated using the 8-bit grayscale method in Photoshop (Adobe), as previously described.19

Liver stiffness and steatosis

A FibroScan 530 device (Echosens), operated by a single experienced operator, was used to measure liver stiffness and steatosis. Ten measurements were made, and the median value was used in the analysis. If the distance between the body surface and the liver exceeded 25 mm, an XL probe was used, as previously described.6

Anthropometric measurements and muscle strength

An InBody 770 system (InBody) was used to determine body composition, according to previously described methods.6 Hand grip strength was assessed according to a previously described protocol.6

Clinical and laboratory measurements

Blood biochemistry measurements were performed according to previously described methods.20 The NAFLD fibrosis score21 and fibrosis-422 (FIB-4) index were calculated using the blood biochemistry data obtained.

Statistical analyses

Statistical analyses were performed using SPSS version 26.0 (IBM Corp.). Data are presented as mean±standard deviation values or odds ratio and 95% confidence interval (CI) values. One-way analysis of variance was used to compare the means of the three groups, and the Bonferroni post hoc test was performed when analysis of variance revealed significant differences. All the parameters other than the NAFLD fibrosis score and the FIB-4 index were analyzed using analysis of covariance, with adjustment for age. The Jonckheere– Terpstra test was used to identify trends in the values across the three groups (two-tailed, P<0.05). The Jonckheere–Terpstra test generates standardized statistics that indicate the strength of trends in data across groups. The significance of trends in the prevalence and severity of liver fibrosis, according to muscle-quality tertiles, was evaluated using linear-by-linear association. Spearman correlation coefficients were calculated for the relationships between intra- and extra-myocellular fat (myosteatosis), estimated using MRS and muscle echo-intensity on ultrasonography. Logistic regression was used to evaluate the relationship between muscle echo-intensity tertile z-score and liver stiffness >9.7 kPa, which was defined as advanced liver fibrosis by Lomonaco et al.23 Model 1 was adjusted for age, model 2 was adjusted for age and body mass index (BMI), model 3 was adjusted for these variables plus body fat mass, and model 4 was adjusted for these variables plus lean body mass. Receiver operating characteristic (ROC) curves were used to determine the optimal cutoff values for muscle quality, quantity, and strength. Furthermore, the optimal cutoff value for muscle quality, the FIB-4 index, and the NAFLD fibrosis score were used to identify patients with liver stiffness >9.7 kPa. The area under the ROC curve (AUC), sensitivity, and specificity were calculated in each case using MedCalc for Windows version 9.1.0.1 (MedCalc Corp.). In the study, P<0.05 was accepted as indicating statistical significance.

Myosteatosis and muscle echo-intensity

Fig. 1 shows the respective correlations of the intra- and extramyocellular fat contents, estimated using MRS, with the muscle echo-intensity, which was assessed using ultrasonography. Notably, there were significant correlations between the intra-myocellular (r=0.325) and extra-myocellular (r=0.604) fat levels, respectively, and the muscle echo-intensity level (P<0.01 for both).

Patient characteristics

Table 1 shows the characteristics of the patients categorized according to the muscle-quality tertiles. For all patients, the post hoc analysis revealed significant differences among the three musclequality groups with respect to height, lean mass, hand grip strength, and platelet count, all of which decreased from the modest to the intermediate and poor muscle-quality groups. In contrast, the age of the patients increased from the modest to the intermediate and poor muscle-quality groups. The body mass of patients in the modest muscle-quality group was significantly greater than that of patients in the poor muscle-quality group. For non-obese patients with NAFLD (n=98), the post hoc analysis showed that the ages of the intermediate and poor muscle-quality groups did not differ, but patients in both of these groups were older than those in the modest muscle-quality group. Finally, the hand grip strength and platelet count of the poor muscle-quality group were lower than those of the modest muscle-quality group.

Prevalence and severity of liver fibrosis, according to muscle-quality tertiles

Fig. 2 displays the prevalence and severity of liver fibrosis in the study population according to the muscle-quality tertiles. Both the prevalence and severity of liver fibrosis increased significantly from the modest to the poor muscle-quality groups, regardless of the presence or absence of obesity (P for trend <0.001 for both the full cohort and non-obese patients) or sex (Supplementary Fig. 1).

Liver fibrosis indices of the patients

Table 2 shows the liver fibrosis index values of the patients categorized according to muscle-quality tertiles. Across the entire cohort, the post hoc analysis showed significant differences in the NAFLD fibrosis score and FIB-4 index among the three groups, which both significantly increased from the modest to the intermediate and poor muscle-quality groups (P for trend <0.001). The liver stiffness and the mac-2–binding protein glycosylation isomer (M2BPGi) of the modest and intermediate muscle-quality groups did not significantly differ, but they were significantly lower in these groups than in the poor muscle-quality group and significantly increased from the modest muscle-quality group to the intermediate and poor muscle-quality groups, respectively (P for trend <0.001). The intermediate muscle-quality group had significantly more liver steatosis than the poor muscle-quality group. Among the non-obese patients, the post hoc analysis revealed no differences in liver stiffness, FIB-4 index, or M2BPGi between the modest and intermediate muscle-quality groups, but the values of each of these were significantly lower than those in the poor muscle-quality group. In addition, the NAFLD fibrosis score did not significantly differ between the intermediate and poor muscle-quality groups, but the values for both groups were significantly greater than those for the modest muscle-quality group. Moreover, the NAFLD fibrosis score significantly increased from the modest muscle-quality group to the intermediate and poor muscle-quality groups (P for trend <0.001).

Relationship between muscle quality and advanced liver fibrosis

Table 3 shows the odds ratios for liver stiffness >9.7 kPa (advanced liver fibrosis, according to Lomonaco et al.23) according to the zscore of the muscle-quality tertile. For the entire cohort, the odds ratios for advanced liver fibrosis were 5.342 (95% CI, 2.342 to 11.736) and 7.584 (95% CI, 3.345 to 17.195) for the intermediate and poor muscle-quality groups, respectively (P<0.001 for both), compared to the modest muscle-quality group, after adjustment for age, remained significant after adjustment for all variables (P<0.001 for all). Among the non-obese patients, the same relationship was identified as that among all patients with NAFLD for the patients with poor muscle echo-intensity z-scores (P<0.05). These findings suggest that muscle quality reflects the extent of liver fibrosis.

ROC curve analysis

Fig. 3A shows the ROC curves for muscle quality, strength, and quantity for patients with liver stiffness >9.7 kPa. In all patients, the optimal cutoff values for muscle quality, quantity, and strength were determined to be 92.4 (P<0.001), 58.0, and 21.0, respectively. The AUC for muscle quality (0.697) was significantly higher than those for muscle strength (P<0.001) and muscle quantity (P<0.01). Among non-obese patients, the optimal cutoff values for muscle quality, quantity, and strength were 104.1, 39.0, and 24.2, respectively (P<0.001 for all). The AUC for muscle quality was highest, but there were no significant differences in muscle quality, quantity, or strength. These results suggest that muscle quality is the most useful marker of advanced liver fibrosis, irrespective of the presence or absence of obesity.

Fig. 3B shows the ROC curves for muscle quality, FIB-4 index, and NAFLD fibrosis score for patients with liver stiffness >9.7 kPa. For the entire cohort, the optimal cutoff values for muscle quality, FIB-4 index, and NAFLD fibrosis score were determined to be 92.4, 1.94, and −0.43, respectively (P<0.001 for all). Separately, among the non-obese patients, the optimal cutoff values for muscle quality, FIB-4 index, and NAFLD fibrosis score were determined to be 104.1, 2.76, and −0.41, respectively (P<0.001 for all). There were no significant differences in the AUCs of these three indices in either the entire cohort or among the non-obese patients. These results suggest that muscle quality is an equally good predictor of advanced liver fibrosis as the FIB-4 index or the NAFLD fibrosis score.

The role of muscle quality in NAFLD has been increasingly recognized.10 The present study advances this understanding further by using ultrasonography muscle echo-intensity, which is a more patient-friendly and accessible technique compared to MRS, muscle biopsy, and computed tomography. In this study, muscle echointensity was used to effectively assess muscle quality, and a significant correlation was observed between poor muscle quality and an increased risk of liver fibrosis. Moreover, the findings were supported by the identification of an optimal cutoff value for the detection of advanced liver fibrosis. These results suggest that muscle quality, which is influenced by liver–muscle crosstalk, may serve as a critical marker of advanced liver fibrosis, potentially providing an accessible and valuable tool for early diagnosis and management in clinical practice.

The present study had several key findings. (1) Muscle echo-intensity, assessed during ultrasonography, was closely positively correlated with both intra-myocellular and extra-myocellular fat content (myosteatosis) estimated using MRS. (2) Poor muscle quality reflects an increased risk of liver fibrosis, being associated with 7.6-fold higher risk than relatively high muscle quality. (3) The assessment of muscle quality is an equally useful means of screening patients for liver fibrosis as the FIB-4 index and NAFLD fibrosis score, and it outperforms the assessment of both muscle strength and quantity. (4) Muscle quality, assessed using a muscle echo-intensity cutoff of ≥92.4 arbitrary units (A.U.), may represent a useful marker of advanced liver fibrosis.

In clinical practice, the identification of patients at high risk for worsening liver fibrosis, as experienced in the progression from non-alcoholic fatty liver to NASH, is an urgent issue. The NAFLD fibrosis score and the FIB-4 index are commonly used as indices of liver fibrosis, but the calculation of NAFLD fibrosis score incorporates BMI, which may render it less effective for the screening of non-obese patients with NAFLD. Similarly, the calculation of the FIB-4 index involves age, which may lead to false-positive results in older patients. Muscle quality is primarily a metabolic issue;24 thus, its assessment may be independent of obesity, age, and sex and it may therefore represent a useful skeletal muscle parameter for the screening of patients with NAFLD at high risk for developing liver fibrosis. The evaluation of muscle quantity may be confounded by factors like age, sex, and body mass.25 In addition, muscle strength, which is also used as an indicator of muscle quality, varies substantially according to the size and number of muscle fibers, the efficiency of neuromuscular communication, and the type of muscle contraction.26 While acknowledging the importance of strength and muscle quantity in the context of NAFLD, we would argue that a more direct index of function, such as muscle quality, assessed using the volume of non-contractile tissue, including intramuscular fat, is necessary to fully understand the effects. In the present study, a comparison between patients with advanced fibrosis (measured as >9.7 kPa by elastography) and those without (≤9.7 kPa) revealed a significant difference in muscle quality, but no significant difference in muscle mass or strength was noted between the two groups. This suggests that, while muscle quality varies significantly with the presence of advanced fibrosis, muscle mass and strength do not show a comparable correlation (Supplementary Table 1). We have shown here that muscle quality is equally as useful as the FIB-4 index and the NAFLD fibrosis score for screening patients for liver fibrosis and outperforms the use of muscle mass and strength in all patients with NAFLD and those with NAFLD but no obesity, regardless of sex (Supplementary Figs. 2 and 3). In addition, muscle quality has potential as a diagnostic marker of advanced liver fibrosis, independent of sex (Supplementary Tables 2–4), age, and body composition.

The numbers of patients with NAFLD and a BMI of <25 kg/m2 are growing, especially in Asia.27 NAFLD in the absence of obesity is associated with greater liver disease-related mortality than NAFLD accompanied by obesity.28 A cross-sectional study of non-obese patients with NAFLD29 showed that they have a low skeletal muscle index for sarcopenia and accompanying muscle deterioration (low mass, steatosis, and weakness). The mechanisms responsible for the development of liver fibrosis owing to fat accumulation in the liver, despite a normal BMI, remain unclear. Recent studies have suggested an association between sarcopenia and NAFLD, with a decrease in muscle quantity being associated with both the development of NAFLD and greater severity.4

Consistent with the results of our previous study, in the present study, we found that non-obese patients with NAFLD have high muscle echo-intensity, indicative of poor muscle quality, but also show a significant loss of muscle strength and a downward trend in muscle quantity. We have also shown that indices of liver fibrosis, with the exception of liver steatosis, in non-obese patients with NAFLD, indicate a worse pathology, coupled with much greater muscle echo-intensity. This suggests that muscle quantity may not closely reflect muscle quality in such patients, which in turn emphasizes the importance of focusing on improving muscle quality, rather than simply increasing muscle mass, during clinical interventions in non-obese patients with NASH.

The pathophysiological mechanism underlying muscle–liver crosstalk can be explained as follows. Liver fibrosis causes an increase in circulating free fatty acid (FFA) concentrations via a reduction in blood flow, impaired hepatocyte function, and insulin resistance,30,31 which leads to greater expression and activity of FFA transporters in muscle, resulting in uptake of the FFAs by muscle cells.30,31 However, the capacity for FFA oxidation in mitochondria is limited, resulting in the accumulation of FFAs in the extracellular membranes of muscle fibers.24 These FFAs are taken up by muscle cells and stored in the cytoplasm following their binding to FFAbinding proteins before being oxidized in the mitochondria.24,32 Moreover, studies have reported that muscle satellite cells33 and platelet-derived growth factor receptor alpha (PDGFRα)-positive mesenchymal progenitor cells34 can differentiate into adipocytes in muscle tissue, and therefore these cells may be the origin of the extra- myocellular and intra-myocellular lipids. A preclinical study showed that intramuscular fat may accumulate earlier than the occurrence of liver fibrosis onset,35 suggesting that intramuscular fat originating from muscle satellite cells or PDGFRα-positive mesenchymal progenitor cells may promote the progression of liver fibrosis. Owing to the cross-sectional design of the present study, we could not analyze muscle or liver pathology over time, and therefore whether the observed high muscle echo-intensity is a cause or consequence of liver fibrosis is impossible to conclude. As such, further studies are needed to clarify this issue.

Ninety-eight of the patients with NAFLD included in this study were not obese. Sarcopenia is often masked by the coexistence of obesity because body composition in individuals with obesity involves greater skeletal muscle mass, fat, and bone weights than that in normal-weight individuals.36 However, NAFLD patients showed increased muscle echo-intensity levels on ultrasonography compared to non-NAFLD patients. Increased muscle echo-intensity levels imply an increase in non-contractile tissue (adipose tissues and connective tissues in the muscle cell gap) in skeletal muscles. Increased intramuscular fat content (myosteatosis), which is considered to reflect deteriorations in muscle quality,37 is likely observed even before the muscle mass is reduced. Therefore, efforts to quantify the skeletal muscle abnormalities in patients with NAFLD should focus on changes in muscle quality (myosteatosis) rather than muscle quantity (sarcopenia).

The existence of skeletal muscles with deteriorations in quality have been found to promote liver fibrosis in NASH via communication between the skeletal muscle and liver (muscle–liver axis).38 Viewing skeletal muscle as an endocrine organ that secretes various salutary myokines may help to explain its role in the development of liver fibrosis. Myostatin is a 26-kDa glycoprotein belonging to the transforming growth factor β superfamily that is synthesized mainly in skeletal muscles. It is an inhibitor of protein synthesis and regeneration. The myostatin receptor, activin IIbr, has been found in hepatic stellate cells.39 This finding raises the question of whether myosteatosis promotes liver fibrosis in patients with NASH (by myostatin-induced activation of stellate cells). Nishikawa et al.40 found that blood myostatin levels were increased in patients with liver cirrhosis. We also observed that blood levels of myostatin are higher in obese and non-obese patients with NAFLD than in non- NAFLD patients.29 In a quartile analysis, NAFLD patients in the group with the lowest skeletal muscle mass to visceral fat area ratio (g/cm2) had significantly higher blood levels of myostatin and more advanced liver fibrosis as measured by elastography compared to NAFLD patients in the other quartiles.8 Furthermore, in our recent paper,17 we reported that muscle echo-intensity increased with age in NAFLD and non-NAFLD patients, reflecting skeletal muscle deterioration and functional decline. Myostatin levels also tend to increase with age in both NAFLD and non-NAFLD patients, in parallel with increases in muscle echo-intensity.

Muscle echo-intensity is a simple and useful metric for the assessment of skeletal muscle quality that can help identify patients with NASH who are at high risk of liver fibrosis. However, ultrasonographic imaging has limitations when it comes to assessing muscle quality; for one, the measurements obtained may vary according to the system used and the settings. Interoperator measurement variability is also often an issue. To address this, in the present study, we standardized the conditions of the measurement process by using the same equipment and conditions, and only one operator performed the examinations. However, there is still a need to assess the interoperator variation in the data obtained and to standardize the equipment settings for routine examinations.

In conclusion, poor muscle quality, as indicated by high muscle echo-intensity, is a risk factor for the progression of liver fibrosis. Ultrasonographic assessment of muscle quality is non-invasive and simple, and it can contribute to the identification of patients with NAFLD who are at high risk of progression to liver fibrosis.

We thank all the study participants and staff for their assistance. We thank Charles Jones, Mark Cleasby, PhD, and Carol Wilson, PhD, for editing a draft of this manuscript. This work was supported in part by Grants-in-Aid for Scientific Research, Japan (Grant nos. 20H04119, 21H03010, 21H03372, 22H03527, 21K19694, and 23H03273).

Study concept and design: NO, SO, and JS; acquisition of data: NO, BK, SK, and TI; analysis and interpretation of data: SO, BK, IM, NH, TI, and JS; drafting of the manuscript: SO and IM; critical revision of the manuscript: NH, TI, and JS; and study supervision: JS.

Fig. 1. Correlation coefficients for the relationships between intramycellular lipid (IMCL) and extra-myocellular lipid (EMCL), which were estimated using magnetic resonance spectroscopy, and muscle echointensity, which was assessed using ultrasonography (n=82). Green dots, EMCL; red dots, IMCL. *P<0.01; P<0.001. A.U., arbitrary units; RF, rectus femoris muscle; VI, vastus intermedius muscle.
Fig. 2. Prevalence and severity of liver fibrosis according to muscle-quality tertiles. (A) Entire cohort. (B) Non-obese patients.
Fig. 3. Receiver operating characteristic (ROC) curves. (A) Optimal cutoff values for muscle quality, quantity, and strength. (B) Optimal cutoff values for muscle quality, fibrosis-4 (FIB-4) index, and non-alcoholic fatty liver disease (NAFLD) fibrosis score (NFS) for the identification of advanced liver fibrosis, defined using liver stiffness >9.7 kPa (Lomonaco et al.23). *P<0.001. AUC, area under the ROC curve.

Anthropometric data and NAFLD-related biochemical data for the patients categorized according to muscle-quality tertiles and assessed using muscle echo-intensity

Variable Muscle quality Post hoc test SS* P for trend*
Modest (M) Intermediate (I) Poor (P) M vs. I M vs. P I vs. P
All patients (n = 307)
Number 103 101 103
Men 66 (64.1) 45 (44.6) 32 (31.1)
Echo-intensity (A.U.) 84.1 ± 9.6 97.4 ± 2.6 113.6 ± 11.3 < 0.001 < 0.001 < 0.001 18.54 < 0.001
Age (yr) 47.7 ± 14.6 55.4 ± 14.6 61.0 ± 12.8 < 0.001 < 0.001 < 0.050 6.32 < 0.001
Height (cm) 165.7 ± 9.4 162.2 ± 10.1 158.5 ± 9.3 < 0.050 < 0.001 < 0.050 −5.38 < 0.001
Body mass (kg) 78.6 ± 21.1 75.2 ± 18.5 68.8 ± 17.5 0.638 < 0.010 0.053 −4.14 < 0.001
BMI (kg/m2) 28.3 ± 5.6 28.4 ± 5.7 27.4 ± 5.6 > 0.999 0.892 0.577 −1.65 0.099
Subcutaneous fat thickness (cm) 11.5 ± 4.5 11.7 ± 4.4 11.6 ± 5.1 > 0.999 > 0.999 > 0.999 −0.01 0.989
Visceral fat area (cm2) 121.8 ± 45.4 127.6 ± 45.3 125.2 ± 50.7 > 0.999 > 0.999 > 0.999 0.34 0.731
Body fat mass (kg) 26.5 ± 11.9 27.1 ± 11.5 25.3 ± 11.5 > 0.999 > 0.999 0.739 −1.09 0.276
%Body fat 33.0 ± 8.0 35.1 ± 8.6 35.7 ± 8.6 0.207 0.075 > 0.999 2.00 < 0.050
Lean mass (kg) 52.0 ± 12.3 48.0 ± 10.6 43.7 ± 9.4 < 0.050 < 0.001 < 0.050 −5.32 < 0.001
Hand grip strength (kg) 34.8 ± 9.4 30.9 ± 8.5 27.1 ± 8.4 < 0.010 < 0.001 < 0.010 −6.00 < 0.001
AST (IU/L) 39.9 ± 25.4 37.8 ± 20.6 42.1 ± 33.0 > 0.999 > 0.999 0.739 −0.25 0.801
ALT (IU/L) 62.8 ± 52.0 51.1 ± 40.3 47.5 ± 49.2 0.255 0.066 > 0.999 −2.88 < 0.010
Platelet count (104/μL) 245.6 ± 56.5 224.5 ± 65.3 199.8 ± 71.8 0.062 < 0.001 < 0.050 −5.05 < 0.001
FPG (mg/dL) 113.4 ± 26.0 115.4 ± 23.8 119.5 ± 29.8 > 0.999 0.318 0.916 1.69 0.092
Ferritin (ng/dL) 180.8 ± 217.4 139.1 ± 120.4 134.1 ± 144.0 0.255 0.156 > 0.999 −2.28 < 0.050
Triglycerides (mg/dL) 140.6 ± 84.6 129.5 ± 73.4 128.2 ± 73.9 > 0.999 0.778 > 0.999 −1.19 0.193
Non-obese patients (n = 98)
Number 33 33 32
Men 18 (54.5) 17 (51.5) 10 (31.2)
Echo-intensity (A.U.) 81.1 ± 10.6 98.3 ± 3.5 120.3 ± 15.5 < 0.001 < 0.001 < 0.001 10.44 < 0.001
Age (yr) 52.2 ± 15.4 62.9 ± 13.1 67.3 ± 9.3 < 0.010 < 0.001 0.523 4.24 < 0.001
Height (cm) 162.5 ± 10.2 161.1 ± 10.8 156.6 ± 9.0 > 0.999 0.059 0.230 −2.43 < 0.050
Body mass (kg) 61.0 ± 10.4 59.6 ± 10.4 56.3 ± 7.6 > 0.999 0.154 0.530 −2.29 < 0.050
BMI (kg/m2) 22.9 ± 2.0 22.8 ± 1.8 22.9 ± 1.3 > 0.999 > 0.999 > 0.999 −0.74 0.458
Subcutaneous fat thickness (cm) 9.8 ± 3.8 9.0 ± 2.7 8.6 ± 3.1 0.932 0.402 > 0.999 −1.23 0.220
Visceral fat area (cm2) 88.2 ± 22.8 88.5 ± 30.9 84.8 ± 23.6 > 0.999 > 0.999 > 0.999 −0.57 0.570
Body fat mass (kg) 16.5 ± 3.9 16.8 ± 4.1 16.5 ± 3.2 > 0.999 > 0.999 > 0.999 0.07 0.948
%Body fat 27.5 ± 6.5 27.9 ± 7.1 29.8 ± 5.7 > 0.999 0.463 0.734 1.42 0.155
Lean mass (kg) 44.6 ± 10.1 42.7 ± 9.5 39.7 ± 7.6 > 0.999 0.105 0.579 −2.24 < 0.050
Hand grip strength (kg) 30.9 ± 8.8 29.3 ± 8.5 25.4 ± 7.7 > 0.999 < 0.050 0.211 −2.62 < 0.010
AST (IU/L) 31.6 ± 21.7 28.7 ± 11.8 39.6 ± 25.9 > 0.999 0.355 0.105 1.85 0.065
ALT (IU/L) 44.1 ± 41.5 30.3 ± 20.3 43.1 ± 45.6 0.411 > 0.999 0.516 −0.01 0.992
Platelet count (104/μL) 251.9 ± 66.1 213.6 ± 60.6 177.7 ± 65.8 0.052 < 0.001 0.080 −4.51 < 0.001
FPG (mg/dL) 113.1 ± 33.8 116.3 ± 24.2 112.8 ± 20.7 1.000 1.000 1.000 0.89 0.372
Ferritin (ng/dL) 123.6 ± 104.3 119.3 ± 99.7 147.4 ± 200.2 1.000 1.000 1.000 −0.26 0.796
Triglycerides (mg/dL) 123.4 ± 85.4 121.8 ± 77.1 111.2 ± 65.6 1.000 1.000 1.000 −0.56 0.578

Values are presented as number (%) or mean±standard deviation. The sample sizes (n) for each of the four variables were as follows: All patients: hand grip strength (M: 102, I: 101, P: 100); FPG (M: 101, I: 98, P: 98); ferritin (M: 99, I: 99, P: 95); triglycerides (M: 98, I: 98, P: 100); non-obese patients: hand grip strength (M: 32, I: 33, P: 29); FPG (M: 31, I: 29, P: 30); ferritin (M: 32, I: 32, P: 27); triglycerides (M: 30, I: 32, P: 30). The ranges of muscle echo-intensity for each tertile were as follows: All patients: modest, 40.8−93.0 A.U., intermediate, 93.1–102.2 A.U., poor, 102.2–182.4 A.U., and non-obese patients: modest, 43.3−92.4 A.U., intermediate, 93.0–105.6 A.U., poor, 105.9–182.4 A.U. One-way analysis of variance (ANOVA) was used to compare the means of the three tertile groups, and the Bonferroni post hoc test was used when ANOVA revealed significant differences (P<0.05; not significant).

*The Jonckheere–Terpstra test was used to identify trends in the values across the three groups (two-tailed, P<0.05). NAFLD, non-alcoholic fatty liver disease; M, modest muscle quality; I, intermediate muscle quality; P, poor muscle quality; SS, standardized statistic; A.U., arbitrary units; BMI, body mass index; AST, aspartate transferase; ALT, alanine transaminase; FPG, fasting plasma glucose.

Liver fibrosis trend indices of the patients categorized according to muscle-quality tertiles and assessed using muscle echo-intensity

Variable Muscle quality Post hoc test SS* P for trend*
Modest (M) Intermediate (I) Poor (P) M vs. I M vs. P I vs. P
All patients (n = 307)
Number 103 101 103
Men 66 (64.1) 45 (44.6) 32 (31.1)
Liver stiffness 6.44 ± 3.15 8.90 ± 6.21 12.06 ± 11.99 0.085 < 0.001 < 0.050 4.68 < 0.001
Liver steatosis 293.51 ± 50.86 295.90 ± 42.93 278.28 ± 54.28 > 0.999 0.085 < 0.050 −2.22 < 0.050
NFS −2.25 ± 1.40 −1.37 ± 1.58 −0.61 ± 1.68 < 0.001 < 0.001 < 0.010 6.96 < 0.001
FIB-4 index 1.13 ± 0.70 1.65 ± 1.20 2.41 ± 1.88 < 0.050 < 0.001 < 0.001 7.04 < 0.001
M2BPGi* 0.79 ± 0.51 0.90 ± 1.13 1.37 ± 1.21 1.000 < 0.010 < 0.010 3.68 < 0.001
Non-obese patients (n = 98)
Number 33 33 32
Men 18 (54.5) 17 (51.5) 10 (31.2)
Liver stiffness 5.09 ± 1.63 6.33 ± 4.93 11.88 ± 11.09 > 0.999 < 0.010 < 0.010 3.77 < 0.001
Liver steatosis 261.70 ± 47.31 269.12 ± 38.47 252.59 ± 45.37 > 0.999 > 0.999 0.397 −0.85 0.395
NFS −2.62 ± 1.66 −1.23 ± 1.47 −0.52 ± 1.63 < 0.010 < 0.001 0.235 4.76 < 0.001
FIB-4 index 1.21 ± 0.80 1.89 ± 1.37 3.08 ± 2.32 0.267 < 0.001 < 0.050 5.18 < 0.001
M2BPGi* 0.75 ± 0.61 0.74 ± 0.53 1.48 ± 0.77 > 0.999 < 0.010 < 0.010 3.60 < 0.001

Values are presented as number (%) or mean±standard deviation. The ranges of muscle echo-intensity for each tertile were as follows: all patients: modest, 40.8–93.0 A.U., intermediate, 93.1–102.2 A.U., poor, 102.2–182.4 A.U.; and non-obese patients: modest, 43.3–92.4 A.U., intermediate, 93.0– 105.6 A.U., poor, 105.9–182.4 A.U.

*The Jonckheere–Terpstra test was used to identify trends in the values across the three groups (two-tailed, P<0.05).

M, modest muscle quality; I, intermediate muscle quality; P, poor muscle quality; SS, standardized statistic; NFS, non-alcoholic fatty liver disease (NAFLD) fibrosis score; FIB-4, fibrosis-4; M2BPGi, mac-2–binding protein glycosylation isomer.

Odds ratios for advanced liver fibrosis, defined as liver stiffness >9.7 kPa,23 according to muscle quality assessed using the zscore of muscle echo-intensity

Variable Muscle quality
Modest Intermediate Poor
All patients
Model 1 Ref. 5.342 (2.432–11.736)* 7.584 (3.345–17.195)*
Model 2 5.473 (2.478–12.098)* 7.985 (3.446–18.502)*
Model 3 4.932 (2.154–11.294)* 7.565 (3.127–18.303)*
Model 4 4.898 (2.143–11.194)* 7.713 (3.190–18.649)*
Model 5 4.925 (2.152–11.270)* 7.634 (3.153–18.487)*
Non-obese patients
Model 1 Ref. 2.312 (0.371–14.390) 9.878 (1.795–54.366)
Model 2 2.376 (0.349–16.157) 8.959 (1.493–53.743)
Model 3 2.539 (0.376–17.172) 8.623 (1.466–50.705)
Model 4 3.017 (0.433–21.040) 10.579 (1.767–63.337)
Model 5 3.412 (0.441–26.373) 12.259 (1.822–82.478)

Values are presented as odds ratio (95% confidence interval). The 307 patients in the entire cohort (143 men and 164 women), which included 98 non-obese patients (45 men and 53 women), were grouped according to tertiles of muscle echo-intensity. Logistic regression was used to evaluate the relationship between muscle echo-intensity tertile z-score and liver stiffness >9.7 kPa, which was used to define advanced liver fibrosis by Lomonaco et al.23 Model 1 was adjusted for age; model 2 was adjusted for age and body mass index; model 3 was adjusted for these variables plus body fat mass; and model 4 was adjusted for these variables plus lean body mass. The ranges of muscle echo-intensity for each tertile were as follows: All patients: modest, 40.8–93.0 arbitrary units (A.U.), intermediate, 93.1–102.2 A.U., poor, 102.2–182.4 A.U.; and nonobese patients: modest, 43.3–92.4 A.U., intermediate, 93.0–105.6 A.U., poor, 105.9–182.4 A.U.

*P<0.001; P<0.01; P<0.05.

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