Advertisement

Sarcopenia-related gut microbial changes are associated with the risk of complications in people with cirrhosis

  • Author Footnotes
    # Pei-Chang Lee and Kuei-Chuan Lee contribute equally to this study
    Pei-Chang Lee
    Footnotes
    # Pei-Chang Lee and Kuei-Chuan Lee contribute equally to this study
    Affiliations
    Division of Gastroenterology and Hepatology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan

    School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan

    Department of Health Service Administration, College of Public Health, China Medical University, Taichung, Taiwan
    Search for articles by this author
  • Author Footnotes
    # Pei-Chang Lee and Kuei-Chuan Lee contribute equally to this study
    Kuei-Chuan Lee
    Footnotes
    # Pei-Chang Lee and Kuei-Chuan Lee contribute equally to this study
    Affiliations
    Division of Gastroenterology and Hepatology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan

    School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
    Search for articles by this author
  • Tsung-Chieh Yang
    Affiliations
    Division of Gastroenterology and Hepatology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan

    School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
    Search for articles by this author
  • Hsiao-Sheng Lu
    Affiliations
    Division of Gastroenterology and Hepatology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan

    School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
    Search for articles by this author
  • Tsung-Yi Cheng
    Affiliations
    Division of Gastroenterology and Hepatology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan

    School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
    Search for articles by this author
  • Yu-Jen Chen
    Affiliations
    Division of Gastroenterology and Hepatology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan

    School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
    Search for articles by this author
  • Jen-Jie Chiou
    Affiliations
    Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, Taiwan
    Search for articles by this author
  • Chi-Wei Huang
    Affiliations
    Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, Taiwan
    Search for articles by this author
  • Ueng-Cheng Yang
    Affiliations
    Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, Taiwan
    Search for articles by this author
  • Elise Chia-Hui Tan
    Affiliations
    Department of Health Service Administration, College of Public Health, China Medical University, Taichung, Taiwan
    Search for articles by this author
  • Shih-Hsuan Chou
    Affiliations
    Biotools, Co, Ltd, New Taipei City, Taiwan
    Search for articles by this author
  • Yu-Lun Kuo
    Affiliations
    Biotools, Co, Ltd, New Taipei City, Taiwan
    Search for articles by this author
  • Bernd Schnabl
    Affiliations
    Department of Medicine, University of California San Diego, La Jolla, CA, USA
    Search for articles by this author
  • Yi-Hsiang Huang
    Affiliations
    Division of Gastroenterology and Hepatology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan

    School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan

    Institute of Clinical Medicine; College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
    Search for articles by this author
  • Ming-Chih Hou
    Correspondence
    Corresponding author. Ming-Chih Hou, M.D. Division of Gastroenterology and Hepatology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan. 201 Shih-Pai Road, Sec. 2, Taipei 11217, Taiwan, Tel: 886-2-28757506; Fax: 886-2-28739318;
    Affiliations
    Division of Gastroenterology and Hepatology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan

    School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
    Search for articles by this author
  • Author Footnotes
    # Pei-Chang Lee and Kuei-Chuan Lee contribute equally to this study
Open AccessPublished:October 28, 2022DOI:https://doi.org/10.1016/j.jhepr.2022.100619

      Highlights

      • The composition and biosynthetic functions of gut microbiota are significantly changed in sarcopenic cirrhotic patients.
      • Cirrhotic patients with sarcopenia-related depletion of fecal Ruminococcus 2 and Anaerostipes had more complications.
      • Modifying gut microbiota may improve the clinical outcomes of cirrhotic patients with sarcopenia.

      Abstract

      Background & Aims

      Sarcopenia and gut dysbiosis are common in patients with liver cirrhosis. However, microbial alterations in different muscle conditions, deviated microbial functions and the impact on cirrhotic outcomes are poorly understood. This study aimed to identify muscle-dependent microbial changes and related risks of cirrhotic complications.

      Methods

      From September 2018 to December 2020, 89 cirrhotic patients and 16 healthy volunteers were prospectively enrolled. Muscle and nutritional status, serum amino acids, and fecal microbiota of them were analyzed. The association between microbial signatures of sarcopenia and cirrhotic complications were investigated.

      Results

      Gut microbiota changes with a decline in muscle mass and strength were observed in cirrhotic patients. The greatest microbial dissimilarity was observed between patients with sarcopenia (both decline in muscle mass and strength) and those with normal-muscle status (p = 0.035). Sarcopenic patients had lower serum levels of alanine, valine, leucine, isoleucine, proline, tryptophan and ornithine. Besides, gut microbial functions in the biosynthesis of amino acids were significantly reduced in patients with sarcopenic cirrhotics. Depletion of Dialister, Ruminococcus 2, and Anaerostipes were associated with cirrhotic sarcopenia, and significantly correlated with the serum levels of amino acids. Patients with coexistent depletion of Ruminococcus 2 and Anaerostipes developed more infectious (44.4% vs. 3.0%) and non-infectious complications (74.1% vs. 3.0%), and more hospitalizations (54 vs. 3) than cirrhotic patients with good microbial signatures (all p < 0.001). In contrast, fecal enrichment of Ruminococcus 2 and Anaerostipes independently decreased the risk of 1-year complications.

      Conclusions

      Sarcopenia-related fecal microbial alterations are associated with cirrhotic complications. These findings may facilitate measures to improve the outcomes of cirrhotic patients with sarcopenia by modifying gut microbiota.

      Lay summary

      The composition and biosynthetic functions of gut microbiota are significantly changed in patients with sarcopenic cirrhosis. Patients with a sarcopenia-related poor microbial signature, in which Ruminococcus 2 and Anaerostipes were both depleted, had significantly more infectious and non-infectious complications, as well as more hospitalizations. These findings highlight the therapeutic potential of modifying the gut microbiota of patients with sarcopenic cirrhosis to improve their clinical outcomes.

      Graphical abstract

      Keywords

      Abbreviations:

      AKI (acute kidney injury), AL(S)T (alanine (aspartate) aminotransferase), (A)SMI ((appendicular) skeletal muscle index), AUROC (area under receiver operating characteristic curves), BIA (bioelectrical impedance analysis), BMI (body mass index), DEXA (dual-energy X-ray absorptiometry), HE (hepatic encephalopathy), INR (international ratio), IPAQ-SF (International physical activity questionnaire short form), LDA (Linear discriminant analysis), LEfSe (Linear discriminant analysis with effect size), MET (metabolic equivalent tasks), MNA (mini-nutritional assessment), MUAC (mid upper arm circumference), MUST (Malnutrition universal screening tool), OR (Odds ratio), PCoA (principal coordinate analysis), PICRUSt2 (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States version 2), PT (prothrombin time), SBP (Spontaneous bacterial peritonitis), SGA (subjective global assessment), 6MWD (six-minute walking distance)

      Study highlights

      What is known
      • Sarcopenia and alterations of gut microbiota are common in cirrhotic patients and are correlated with each other.
      • It is not clear whether changes in gut microbiota are dependent on muscle mass or strength. Additionally, the roles of bacterial functional changes in patients with liver cirrhosis remain unknown.
      • Whether muscle-dependent microbial alterations affect cirrhotic complications has not been determined.
      What is new here
      • A spectrum of microbial composition was observed in cirrhotic patients with normal muscular status, muscle wasting, strength reduction and sarcopenia; and a significant dissimilarity was observed between sarcopenic cirrhotic patients and normal-muscle subjects.
      • Serum levels of alanine, valine, leucine, isoleucine, proline, tryptophan, and ornithine, as well as microbial functions in the biosynthesis of amino acids, including branched-chain amino acids, were significantly reduced in patients with sarcopenic cirrhosis.
      • Fecal depletion of Dialister, Ruminococcus 2, and Anaerostipes were independently associated with the development of sarcopenia in cirrhotic patients, and these microbiomes were significantly correlated with serum concentrations of amino acids.
      • Cirrhotic patients with a sarcopenia-related poor microbial signature, in which Ruminococcus 2 and Anaerostipes were both depleted, had significantly more infectious and non-infectious complications and hospitalizations.
      How might it impact on clinical practice in the foreseeable future?
      • These findings highlight the potential therapeutic strategy to improve the clinical outcomes of patients with sarcopenic cirrhosis by modifying the gut microbiota of these patients.
      • We suggest that gut dysbiosis may be responsible for sarcopenia in liver cirrhosis through the decreased biosynthesis of amino acids which could also be modulated and corrected.

      Introduction

      Sarcopenia is a common problem in patients with liver cirrhosis, and the prevalence rate is around 30–70%.
      • Dasarathy S.
      • Merli M.
      Sarcopenia from mechanism to diagnosis and treatment in liver disease.
      ,
      • Merli M.
      • Berzigotti A.
      • Zelber-Sagi S.
      • Dasarathy S.
      • Montagnese S.
      • Genton L.
      • et al.
      EASL Clinical Practice Guidelines on nutrition in chronic liver disease.
      Cirrhotic patients with sarcopenia are reported to have a higher risk of complications and mortality.
      • Montano-Loza A.J.
      • Meza-Junco J.
      • Prado C.M.
      • Lieffers J.R.
      • Baracos V.E.
      • Bain V.G.
      • et al.
      Muscle wasting is associated with mortality in patients with cirrhosis.
      • Huguet A.
      • Latournerie M.
      • Debry P.H.
      • Jezequel C.
      • Legros L.
      • Rayar M.
      • et al.
      The psoas muscle transversal diameter predicts mortality in patients with cirrhosis on a waiting list for liver transplantation: A retrospective cohort study.
      • Kang S.H.
      • Jeong W.K.
      • Baik S.K.
      • Cha S.H.
      • Kim M.Y.
      Impact of sarcopenia on prognostic value of cirrhosis: going beyond the hepatic venous pressure gradient and MELD score.
      • Praktiknjo M.
      • Book M.
      • Luetkens J.
      • Pohlmann A.
      • Meyer C.
      • Thomas D.
      • et al.
      Fat-free muscle mass in magnetic resonance imaging predicts acute-on-chronic liver failure and survival in decompensated cirrhosis.
      However, most studies focused only on muscle mass but ignored the muscle strength and performance, which are determinant factors of sarcopenia.
      • Huguet A.
      • Latournerie M.
      • Debry P.H.
      • Jezequel C.
      • Legros L.
      • Rayar M.
      • et al.
      The psoas muscle transversal diameter predicts mortality in patients with cirrhosis on a waiting list for liver transplantation: A retrospective cohort study.
      • Kang S.H.
      • Jeong W.K.
      • Baik S.K.
      • Cha S.H.
      • Kim M.Y.
      Impact of sarcopenia on prognostic value of cirrhosis: going beyond the hepatic venous pressure gradient and MELD score.
      • Praktiknjo M.
      • Book M.
      • Luetkens J.
      • Pohlmann A.
      • Meyer C.
      • Thomas D.
      • et al.
      Fat-free muscle mass in magnetic resonance imaging predicts acute-on-chronic liver failure and survival in decompensated cirrhosis.
      • Ren X.
      • Hao S.
      • Yang C.
      • Yuan L.
      • Zhou X.
      • Zhao H.
      • et al.
      Alterations of intestinal microbiota in liver cirrhosis with muscle wasting.
      Given that sarcopenia has important impacts on cirrhotic outcomes, identification of the risk factors, which could be therapeutically modulated, is considerable to patients with liver cirrhosis.
      Gut microbiota are well known to be associated with metabolism and to play a substantial role in hosts’ nutrition.
      • Chu H.
      • Duan Y.
      • Yang L.
      • Schnabl B.
      Small metabolites, possible big changes: a microbiota-centered view of non-alcoholic fatty liver disease.
      ,
      • Schnabl B.
      • Brenner D.A.
      Interactions between the intestinal microbiome and liver diseases.
      Alteration of microbial composition and function not only correlates with cirrhotic malnutrition, but also contributes and worsens cirrhotic complications.
      • Schnabl B.
      • Brenner D.A.
      Interactions between the intestinal microbiome and liver diseases.
      • Bajaj J.S.
      • Heuman D.M.
      • Hylemon P.B.
      • Sanyal A.J.
      • White M.B.
      • Monteith P.
      • et al.
      Altered profile of human gut microbiome is associated with cirrhosis and its complications.
      • Trebicka J.
      • Macnaughtan J.
      • Schnabl B.
      • Shawcross D.L.
      • Bajaj J.S.
      The microbiota in cirrhosis and its role in hepatic decompensation.
      Besides, gut microbiota may influence muscle physiology by altering amino acid bioavailability, disturbing metabolites, and modulating pro-inflammatory cytokines.
      • Bindels L.B.
      • Delzenne N.M.
      Muscle wasting: the gut microbiota as a new therapeutic target?.
       According to the recent studies, alterations of gut microbiota are observed in cirrhotic patients with sarcopenia.
      • Ren X.
      • Hao S.
      • Yang C.
      • Yuan L.
      • Zhou X.
      • Zhao H.
      • et al.
      Alterations of intestinal microbiota in liver cirrhosis with muscle wasting.
      ,
      • Ponziani F.R.
      • Picca A.
      • Marzetti E.
      • Calvani R.
      • Conta G.
      • Del Chierico F.
      • et al.
      Characterization of the gut-liver-muscle axis in cirrhotic patients with sarcopenia.
      However, it is unclear whether these microbial alterations are dependent on muscle mass or muscle strength. Moreover, whether muscle-dependent microbiomes affect cirrhotic complications remains undetermined. Moreover, the role of these bacterial functions in liver cirrhosis is poorly understood. In this study, we aimed to investigate the impact of sarcopenia-dependent microbiota on cirrhotic complications. In addition, we analyzed alterations of gut microbiota according to the different muscular conditions of cirrhotic patients, microbial functional changes focusing on the biosynthesis of amino acids, and correlations between microbiota and serum amino acids.

      Materials and Methods

      Patients

      From September 2018 to December 2020, 89 patients with liver cirrhosis who had regular follow-up appointments or received medical treatment in Taipei Veterans General Hospital were prospectively enrolled in this study after informed consent. The diagnosis of liver cirrhosis was made according to the ultrasonography, computed tomography, or magnetic resonance imaging together with impaired liver function, or by liver biopsy.
      • Tsochatzis E.A.
      • Bosch J.
      • Burroughs A.K.
      Liver cirrhosis.
      In order to investigate fecal microbiota, patients who were prescribed lactulose, proton pump inhibitors, nonsteroidal anti-inflammatory drugs, antibiotics, probiotics or prebiotics within one month were excluded from this study. The detailed inclusion and exclusion criteria for patient selection are presented in the Supplementary Materials and Methods. In addition, 16 healthy volunteers who did not have any underlying medical disease and visited for health examination were also prospectively enrolled as control. This study was approved by the Institutional Review Board of Taipei Veterans General Hospital (IRB numbers: 2017-09-013C and 2018-07-018C).

      Definitions

      According to the Asian Working Group for Sarcopenia 2019 consensus,
      • Chen L.K.
      • Woo J.
      • Assantachai P.
      • Auyeung T.W.
      • Chou M.Y.
      • Iijima K.
      • et al.
      Asian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia Diagnosis and Treatment.
      sarcopenia was defined as both a decline of muscle strength (handgrip strength < 28 kg for men and < 18 kg for women, measured using a digital hand dynamometer [TKK 5401 Grip-D; Takei Scientific Instruments Co., LTD., Tokyo, Japan]) and reduced muscle mass (appendicular skeletal muscle index < 7.0 kg/m2 in men and < 5.4 kg/m2 in woman, measured by dual-energy X-ray absorptiometry [Hologic Horizon A scanner, Hologic, Inc., Bedford, MA, USA] with APEX system software [version 5.6.0.5]
      • Belarmino G.
      • Gonzalez M.C.
      • Sala P.
      • Torrinhas R.S.
      • Andraus W.
      • D'Albuquerque L.A.C.
      • et al.
      Diagnosing Sarcopenia in Male Patients With Cirrhosis by Dual-Energy X-Ray Absorptiometry Estimates of Appendicular Skeletal Muscle Mass.
      ). The 6-minute walk distance test was used to assess physical performance.
      • Carey E.J.
      • Steidley D.E.
      • Aqel B.A.
      • Byrne T.J.
      • Mekeel K.L.
      • Rakela J.
      • et al.
      Six-minute walk distance predicts mortality in liver transplant candidates.
      On the other hand, the diagnosis and management of cirrhotic complications were made according to the EASL Clinical Practice Guideline.
      • Angeli P.
      • Bernardi M.
      • Villanueva C.
      • Francoz C.
      • Mookerjee R.P.
      • Trebicka J.
      • et al.
      EASL Clinical Practice Guidelines for the management of patients with decompensated cirrhosis.

      Assessment of nutritional status and physical activity

      All enrollees were examined for nutritional status by anthropometric measurements, including body weight, body mass index, mid-upper arm circumference, and tricuspid skinfold thickness as well as conventional serum laboratory data. Malnutrition screening and dietary status were assessed concomitantly upon enrollment by subjective global assessment (SGA), mini-nutritional assessment (MNA), and the malnutrition universal screening tool (MUST).
      • Tandon P.
      • Raman M.
      • Mourtzakis M.
      • Merli M.
      A practical approach to nutritional screening and assessment in cirrhosis.
      The level of physical activity and sitting time were assessed by using the validated Korean version of the International Physical Activity Questionnaire Short Form (IPAQ-SF) which enables the calculation of metabolic equivalent tasks (MET-minutes per week).
      • Bassett Jr., D.R.
      International physical activity questionnaire: 12-country reliability and validity.

      Measurements of serum amino acids

      Serum samples were collected and stored at −80°C until analysis. The serum was de-proteinized by adding the same volume of 10% sulfosalicylic acid containing an internal standard (norvaline 200μM) and centrifuged at 12,000g for 10 minutes at 25–28°C. Derivatization of the supernatant was initiated by adding 20μL of 10mM 6-aminoquinoly-N-hydroxysuccinimidyl carbamate in acetonitrile. After incubation for 10 minutes, the reactant was mixed with an equal volume of Eluent A (20mM ammonium formate, 0.6% formic acid, and 1% acetonitrile) and analyzed by Waters ACQUITY UPLC System (Waters Corp., Milford, MA, USA).
      • Tsai H.I.
      • Lo C.J.
      • Zheng C.W.
      • Lee C.W.
      • Lee W.C.
      • Lin J.R.
      • et al.
      A Lipidomics Study Reveals Lipid Signatures Associated with Early Allograft Dysfunction in Living Donor Liver Transplantation.
      The details are presented in the Supplementary Materials and Methods.

      Processing and analysis of stool bacterial genomic data

      Microbial genomic DNAs were extracted by using the QIAamp DNA Stool Mini Kit (Qiagen, Hilden, Germany). 12.5 ng of DNA from each specimen was used for the polymerase chain reaction (PCR). The hypervariable V3-V4 regions of bacterial 16S ribosomal RNA genes were amplified by PCR using the primers 341F V3 Illumina (5’-CCTACGGGNGGCWGCAG-3’) and 806R V4 Illumina (5’- GACTACHVGGGTATCTAATCC-3’).
      • Nossa C.W.
      • Oberdorf W.E.
      • Yang L.
      • Aas J.A.
      • Paster B.J.
      • Desantis T.Z.
      • et al.
      Design of 16S rRNA gene primers for 454 pyrosequencing of the human foregut microbiome.
      The PCR product was purified by using AMPure XP beads. Next-generation sequencing was performed by the Illumina MiSeq Desktop Sequencer; and the ZymoBIOMICSTM Microbial Community DNA Standard (catalogue no. D6305, Zymo Research Corp., Irvine, CA, USA) was used as an internal control.
      The 16S rRNA gene sequencing raw reads were processed and denoised using QIIME2 version 2020.11 and DADA2 plugin,
      • Callahan B.J.
      • McMurdie P.J.
      • Rosen M.J.
      • Han A.W.
      • Johnson A.J.
      • Holmes S.P.
      DADA2: High-resolution sample inference from Illumina amplicon data.
      ,
      • Bolyen E.
      • Rideout J.R.
      • Dillon M.R.
      • Bokulich N.A.
      • Abnet C.C.
      • Al-Ghalith G.A.
      • et al.
      Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
      and were annotated with taxonomic classifications based on the Silva 132 database. Alpha diversity indices and principal coordinate analysis (PCoA) of microbiota were calculated and compared by Kruskal-Wallis test and permutational multivariate analysis of variance (PERMANOVA) test with correction for multiple testing using the Benjamini-Hochberg procedure. Linear discriminant analysis (LDA) with effect size (LEfSe) was performed to determine the candidate taxa most likely to explain the differences between groups. Spearman’s rank correlation analysis was performed for the microbial taxa and metabolites. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States version 2 (PICRUSt2) analysis was applied to predict the microbial functions and pathway inferences.
      • Douglas G.M.
      • Maffei V.J.
      • Zaneveld J.R.
      • Yurgel S.N.
      • Brown J.R.
      • Taylor C.M.
      • et al.
      PICRUSt2 for prediction of metagenome functions.
      The details are described in the Supplementary Materials and Methods.

      Statistical analysis

      Continuous variables were expressed as median (interquartile ranges [IQR]) and were compared by Mann-Whitney U test or Kruskal-Wallis test with a Bonferroni correction, while categorical variables were presented as frequencies (percentages) and were compared by Pearson’s Chi-squared analysis or Fisher’s exact test. The optimal cutoff values of microbial abundance to predict cirrhotic complications were assessed using the area under receiver operating characteristic curves (AUROC). The value with the highest Youden’s Index was considered as the optimal cut-off.
      • Fluss R.
      • Faraggi D.
      • Reiser B.
      Estimation of the Youden Index and its associated cutoff point.
      To identify the most important factors that were associated with cirrhotic sarcopenia and 1-year complications, we first performed a univariate logistic regression model to assess the association between each variable and the outcome of interest. Variables with statistical significance (p < 0.2) and clinical relevance were considered as candidates for multivariate logistic regression. We also conducted LASSO logistic regression model to confirm the most useful prognostic risk factors for cirrhotic sarcopenia and 1-year complications. R software version 4.2.1 and the “glmnet” package (R Foundation for Statistical Computing, Vienna, Austria) were used to perform the Lasso logistic regression analysis. Other statistical analyses were performed using Statistical Package for Social Sciences (SPSS 26.0 for Windows, SPSS Inc, Chicago, IL) and GraphPad Prism 9 (GraphPad Software, San Diego, CA). For all analyses, p < 0.05 was considered statistically significant.

      Results

      Baseline characteristics of patients

      Among our cirrhotic patients, 21 (23.6%) had normal muscle mass and strength, 12 (13.5%) had reduced muscle mass (muscle wasting), 27 (30.3%) had reduced muscle strength, and 29 (32.6%) were classified sarcopenic with both reduction of muscle mass and strength. More than half of the patients with sarcopenia (55.2%) or reduced strength (55.5%) were classified at Child-Pugh class B or C. In contrast, most patients who maintained normal muscle strength were within Child-Pugh class A (Table 1). Notably, 28.3% of patients at Child-Pugh class A still had sarcopenia, and the prevalence rate was not significantly lower than that of patients at Child-Pugh B or C (37.2%, p = 0.368). On the other hand, although the prevalence of sarcopenia was higher in patients with ascites (41.3%), 23.3% of patients without ascites still presented with sarcopenia, which should not be overlooked (p = 0.069).
      Table 1Baseline Characteristics of Healthy Subjects and Cirrhotic Patients According to Muscle Status
      CharacteristicsHealthy subjectsCirrhotic patientsCirrhosis Sarcopenia vs. Normal muscle status p value
      Normal Muscle statusNormal Muscle statusDecreased muscle massDecreased muscle strengthSarcopenia
      n = 16n = 21n = 12n = 27n = 29
      Age58.4 (49.6 – 64.5)58.8 (50.9 – 63.6)53.9 (44.8 – 64.0)65.7 (58.9 – 70.4)62.7 (54.3 – 66.5)0.234
      Sex, male13 (81.3)17 (81.0)9 (75.0)18 (66.7)25 (86.2)0.706
      Chronic hepatitis B0 (0)13 (61.9)6 (50.0)12 (44.4)15 (51.7)0.474
      Chronic hepatitis C0 (0)4 (19.0)1 (8.3)8 (29.6)1 (3.4)0.148
      Alcohol consumption0 (0)5 (23.8)4 (33.3)1 (3.7)7 (24.1)0.979
      Body weight, kg65.0 (59.9 – 69.5)75.0 (67.8 – 85.0)62.5 (54.4 – 70.0)72.2 (64.1 – 81.0)61.0 (55.5 – 67.7)< 0.001
      BMI, kg/m223.3 (22.3 – 24.7)27.5 (25.1 – 29.4)21.0 (20.2 – 23.0)27.6 (23.9 – 30.5)22.4 (21.1 – 23.6)< 0.001
      MUAC, cm26.5 (25.0 – 27.8)31.0 (25.1 – 29.4)24.0 (24.0 – 26.7)29.0 (25.0 – 31.3)24.5 (23.5 – 27.0)< 0.001
      Tricuspid skin fold, mm20.0 (12.3 – 27.8)24.0 (19.0 – 30.3)22.0 (15.5 – 23.5)22.5 (15.0 – 28.3)14.0 (10.3 – 18.8)0.002
      MNA score28.3 (27.5 – 28.9)27.0 (25.0 – 28.0)26.5 (25.5 – 27.5)25.5 (24.0 – 27.0)25.0 (23.5 – 26.5)0.005
      MNA score ≤ 23.5, n (%)0 (0)1 (4.8)0 (0)6 (22.2)7 (24.1)0.117
      SGA score0 (0 – 0)1 (0 – 2)1 (0 – 3)3 (1 – 4)3 (1 – 5)0.004
      SGA score > 1, n (%)0 (0)7 (33.4)3 (25.0)20 (74.1)21 (72.4)0.006
      Handgrip strength
       Male, kg35.4 (31.6 – 40.0)30.8 (29.7 – 33.4)30.2 (28.6 – 32.7)22.7 (20.4 – 24.1)21.2 (16.5 – 24.8)< 0.001
       Female, kg24.5 (22.6 – 31.8)21.6 (18.9 – 28.7)18.2 (18.0 – 44.0)12.1 (8.6 – 15.1)10.3 (7.6 – 12.6)0.021
      DEXA
       ASMI, kg/m2 (male)7.53 (7.17 – 7.94)8.03 (7.57 – 8.75)6.71 (6.18 – 6.83)7.97 (7.34 – 8.63)6.15 (5.63 – 6.78)< 0.001
       ASMI, kg/m2 (female)5.48 (3.06 – 5.83)6.40 (6.29 – 6.54)5.05 (4.28 – 5.21)6.03 (5.60 – 7.99)4.57 (4.28 – 4.95)0.034
       SMI, kg/m2 (male)17.50 (16.70 – 18.30)19.30 (18.35 – 20.20)16.10 (15.40 – 17.45)19.50 (18.68 – 20.65)15.90 (14.60 – 16.80)< 0.001
       SMI, kg/m2 (female)12.80 (12.10 – 13.80)16.39 (15.50 – 17.30)12.90 (11.20 – 13.70)15.40 (14.45 – 20.40)13.60 (12.63 – 14.05)0.034
       Fat mass, kg (male)16.39 (14.79 – 20.00)24.56 (21.40 – 27.07)15.09 (13.68 – 18.90)20.09 (15.94 – 26.48)15.67 (13.25 – 17.62)< 0.001
       Fat mass, kg (female)15.29 (14.46 – 20.83)28.11 (21.20 – 33.74)19.32 (18.23 – 19.62)25.16 (18.64 – 32.31)18.68 (10.22 – 25.96)0.157
       Fat-free mass, kg (male)47.98 (46.09 – 51.11)54.46 (51.18 – 60.05)47.01 (43.42 – 51.16)52.74 (49.20 – 55.59)43.56 (40.43 – 47.62)< 0.001
       Fat-free mass, kg (female)32.01 (31.84 – 35.35)41.00 (35.83 – 47.23)32.15 (27.36 – 33.11)41.60 (34.67 – 48.37)31.69 (29.85 – 38.94)0.157
      6MWD, meters512.7 (455.8 – 569.7)467.3 (455.8 – 498.5)455.8 (444.3 – 512.7)398.8 (299.1 – 512.7)341.8 (227.9 – 398.8)0.010
      Presence of ascites, n (%)0 (0)5 (23.8)4 (33.3)13 (48.1)19 (65.5)0.004
      Presence of varices, n (%)0 (0)12 (57.1)6 (50.0)16 (59.3)14 (48.3)0.536
      Child-Pugh score5 (5 – 5)5 (5 – 7)6 (5 – 7)7 (5 – 9)7 (6 – 9)0.003
      Child-Pugh class A/B/C16/ 0/ 0 (100.0/ 0/ 0)14/ 7/ 0 (66.7/ 33.3/ 0)7/ 4/ 1 (58.3/ 33.3 8.3)12/ 13/ 2 (44.4/ 48.1/ 7.4)13/ 12/ 4 (44.8/ 41.4/ 13.8)0.124
      Lab data
       Albumin, g/dL4.7 (4.5 – 4.7)3.8 (3.3 – 4.2)3.8 (3.3 – 4.6)3.5 (2.7 – 3.8)3.5 (3.0 – 3.9)0.078
       Total bilirubin, mg/dL0.55 (0.47 – 0.67)1.52 (1.09 – 2.08)1.50 (0.94 – 3.51)1.46 (0.97 – 2.17)1.88 (1.14 – 3.47)0.163
       ALT, U/L18 (15 – 27)30 (24 – 39)26 (22 – 47)28 (23 – 37)27 (17 – 41)0.360
       AST, U/L22 (18 – 25)42 (26 – 66)40 (30 – 72)33 (27 – 50)35 (27 – 68)0.775
       Creatinine, mg/dL0.85 (0.80 – 0.93)0.85 (0.76 – 0.94)0.90 (0.75 – 1.12)0.97 (0.73 – 1.15)0.82 (0.74 – 1.11)0.992
       Sodium, mmol/L140 (138 – 141)141 (137 – 142)140 (135 – 141)139 (136 – 142)139 (136 – 141)0.268
       Leucocyte, /cumm5200 (4425 – 6450)4600 (3700 – 5050)4050 (3125 – 5350)4000 (3000 – 5500)4600 (3015 – 6350)0.753
       Hemoglobin, g/dL14.9 (13.8 – 15.9)12.3 (10.2 – 14.7)12.6 (10.7 – 14.0)11.3 (9.5 – 13.1)11.3 (10.4 – 13.2)0.783
       Platelet, K/cumm230 (195 – 259)85 (59 – 126)96 ( 49 – 153)71 (42 – 104)88 (47 – 123)0.687
       PT, INR1.03 (0.97 – 1.08)1.24 (1.15 – 1.35)1.20 (1.03 – 1.34)1.36 (1.24 – 1.45)1.30 (1.16 – 1.48)0.208
      Abbreviations: AL(S)T, alanine (aspartate) aminotransferase; (A)SMI, (appendicular) skeletal muscle index; BIA, bioelectrical impedance analysis; BMI, body mass index; DEXA, dual-energy X-ray absorptiometry; INR, international ratio; MNA, mini-nutritional assessment; MUAC, mid upper arm circumference; PT, prothrombin time, SGA, subjective global assessment; 6MWD, six-minute walking distance.
      Continuous variables were expressed as median (interquartile ranges) and were compared by Mann-Whitney U test. Categorical variables were presented as frequencies (percentages) and were compared by Pearson’s Chi-squared test.
      In comparison with cirrhotic patients who maintained normal muscle status, sarcopenic patients had a significantly increased risk of malnutrition (assessed by SGA and MNA score). Sarcopenic patients had significantly worse anthropometric measurements, handgrip strength, skeletal and appendicular skeletal muscle indices, total body fat mass (less significant in females), and physical performance examined by the 6-minute walk test. They were significantly less physically active and spent more time sitting (Table 1 and Supplementary Table 1).

      Gut microbiota changes with different muscle conditions of cirrhosis

      Compared with healthy controls, the abundance of Proteobacteria was significantly increased in cirrhotic patients, especially in those with sarcopenia (Figure 1A). At the family level, apparent increases in Enterobacteriaceae and Streptococcaceae as well as reduced Lachnospiraceae, Ruminococcaceae, and Prevotellaceae were observed in cirrhotic patients, particularly in those with sarcopenia (Figure 1B). The richness and evenness of microbiota measured by Faith’s PD index and Shannon index were significantly decreased in cirrhotic patients regardless of their muscle status in comparison with healthy controls (all p < 0.05). However, no significant differences in alpha diversities were noted between sarcopenic and normal-muscle cirrhotic patients (Figure 1C-D). In contrast, significant microbial dissimilarities measured by un-weighted UniFrac distances were observed not only between healthy subjects and cirrhotic patients (both p = 0.001 for healthy controls vs. sarcopenic or normal-muscle cirrhotic patients), but also between sarcopenic and normal-muscle cirrhotic patients (p = 0.035) (Figure 1E).
      Figure thumbnail gr1
      Figure 1The composition and diversity of gut microbiota in cirrhotic patients with different muscle conditions and healthy controls
      Stacked bar plots of phylogenetic composition of common bacterial taxa (> 0.1% abundance) at the (A) phylum and (B) family level in fecal samples of healthy controls, cirrhotic patients with normal muscle status (C-Normal), muscle mass depletion (C-Low mass), muscle strength weakness measured by handgrip (C-Low HG), and sarcopenic cirrhotic patients (C-Scrp). Alpha diversity indices of gut microbiota measured by (C) Faith’s PD index and (D) Shannon index. (The boxes represent the interquartile range and the bold lines inside the boxes define the median; all p < 0.001 for healthy controls vs. each group of cirrhotic patients, and p > 0.05 between cirrhotic patients with different muscle status by the Kruskal-Wallis test with correction for multiple comparisons by Benjamini-Hochberg procedure) (E) Principal coordinates analysis of gut microbiota measured by un-weighted Unifrac distance metrics. (p = 0.001 for healthy vs. vs. each group of cirrhotic patients; p = 0.035 for C-Scrp vs. C-Normal by permutational multivariate analysis of variance test with correction for multiple comparisons by Benjamini-Hochberg procedure) (F) LDA scores computed for differentially abundant taxa in the fecal microbiome. The length of each bar indicates the effect size associated with a taxon, which is significantly different when comparing to other groups (by the Kruskal-Wallis and Wilcoxon tests)
      To determine the distinct microbiota associated with cirrhotic sarcopenia, the microbial profiles of sarcopenic and normal-muscle cirrhotic patients were further investigated. According to LEfSe analysis, a prominence of Fusobacterium, Micrococcaceae and Rothia (LDA score [log10] > 3) was observed in sarcopenic cirrhotic patients. In contrast, Dialister, Ruminococcus 2, Collinsella, Coriobacteriaceae, Megasphaera, Acidaminococcus, Eubacterium hallii, Dorea, Lachnospiraceae, and Anaerostipes were prominent in cirrhotic patients with normal-muscle status (Figure 1F). On the other hand, no significant microbial dissimilarities were observed according to the consumption of non-selective beta blockers, histamine-2 receptor antagonists, oral anti-diabetic drugs, statins or the underlying etiology of liver cirrhosis (Supplementary Fig. 1).

      Association of amino acids with gut microbiota and microbial functions

      According to PICRUSt2 analysis, the microbial functions associated with the biosynthesis of several amino acids, including L-threonine, L-glutamine, L-glutamate, L-isoleucine, L-valine, L-ornithine, branched-chain amino acids (BCAAs), and so on were significantly decreased in sarcopenic cirrhotic patients (p < 0.001) (Figure 2). Interestingly, the serum levels of BCAAs, including valine, leucine, and isoleucine, as well as alanine, proline, tryptophan and ornithine were significantly reduced in cirrhotic patients with sarcopenia (Figure 3 and Supplementary Table 2). In addition, negative correlations were observed between serum proline, glutamine, threonine and gut microbes which were predominant in sarcopenic cirrhotic patients. In contrast, many amino acids, which are essential to muscle development, were positively correlated with bacteria that were predominant in normal-muscle cirrhotic patients, including Dialister, Anaerostipes, Lachnospiraceae, and Ruminococcus (Figure 4). Taken together, the correlation between sarcopenia-dependent microbiota and the reduction in serum amino acids may indicate an association with the decreased microbial biosynthesis of amino acids.
      Figure thumbnail gr2
      Figure 2The predicted metagenomic functional pathways of gut microbiota with significant differences between cirrhotic patients with different muscle status
      C-Normal, normal muscle-cirrhotic patients; C-Scrp, sarcopenic cirrhotic patients
      All presented pathways are different with statistical significance (bars represent standard deviation; all p < 0.05 by the Mann-Whitney U test).
      Figure thumbnail gr3
      Figure 3Serum amino acids in cirrhotic patients with different muscle status
      Serum levels of amino acids with between cirrhotic patients with normal muscle status (C-Normal) and sarcopenia (C-Scrp). Statistical analysis was performed by the Mann-Whitney U test (The p values with statistical significance are presented in the plot).
      Gly, glycine; Ala, alanine; Val, valine; Ile, isoleucine; Leu, leucine; Met, methionine; Pro, proline; Trp, tryptophan; Tyr, tyrosine; Phe, phenylalanine; Ser, serine; Thr, threonine; Asn, asparagine; Gln, glutamine; Glu, glutamate; Orn, ornithine; Arg, arginine; His, histidine; Lys, lysine; Tau, taurine.
      Figure thumbnail gr4
      Figure 4Heat map of the correlation matrix between abundance of gut microbiota (right panel) and the serum level of amino acids in patients with liver cirrhosis
      Red tones indicate positive correlations between the serum level of amino acids and the abundance of differential intestinal microbes; blue tones indicate negative correlation. The plus sign indicates statistical significance (p < 0.05 by the Spearman’s rank correlation analysis).

      Distinct signature of microbiota associated with sarcopenia in liver cirrhosis

      According to the ROC analyses, Fusobacterium, Rothia, Dialister, Ruminococcus 2, Megasphaera, Anaerostipes, and Eubacterium Hallii were probable discriminating microbiota to predict the risk of sarcopenia in liver cirrhosis (AUROC > 0.6). Therefore, the abundances of these microbes and other clinical factors were subjected to LASSO logistic regression analyses. As presented in Table 2 and Supplementary Figs. 2A–B, depleted fecal abundance of Dialister, Ruminococcus 2 and Anaerostipes were selected as predictors of cirrhotic sarcopenia with the odds ratios of 6.823, 4.590, and 4.640, respectively. In addition, significant reduction in Ruminococcus 2 and Anaerostipes were consistently noted in patients with Child B or C liver reserves (Supplementary Figs. 3A–B)
      Table 2Factors Associated with Sarcopenia in Cirrhotic Patients
      CharacteristicsCase numbersUnivariate
      Binary logistic regression analysis
      Multivariate
      Binary logistic regression analysis
      LASSO
      LASSO logistic regression analysis.
      OR95% CIp valueOR95% CIp valueCoefficient
      Age, y> 60 vs. ≤ 6048 / 411.3250.541 – 3.2460.538
      SexMale vs. Female69 / 202.2730.684 – 7.5500.1805.6171.233 – 25.5770.026
      SGA rate> 1 vs. ≤ 151 / 382.6251.006 – 6.8470.049NS
      Etiology of cirrhosisViral vs. Non-viral59 / 300.4870.193 – 1.2240.126NS
      Alcohol consumptionYes vs. No17 / 721.5910.536 – 4.7240.403
      NLR> 4.2 vs. ≤ 4.218 / 712.5500.885 – 7.3510.083NS
      Platelet count≤ 100K vs. > 100K56 / 330.7630.307 – 1.8940.560
      Albumin, g/dL> 3.5 vs. ≤ 3.546 / 430.8170.336 – 1.9840.655
      Prothrombin time, INR> 1.25 vs. ≤ 1.2544 / 451.5160.525 – 4.3720.042NS
      ALT, U/L> 40 vs. ≤ 4019 / 701.6970.597 – 4.8220.321
      AST, U/L> 40 vs. ≤ 4042 / 471.0670.439 – 2.5910.887
      Total bilirubin, mg/dL> 2.0 vs. ≤ 2.034 / 551.8670.755 – 4.6130.176NS
      Presence of varicesYes vs. No48 / 410.7140.293 – 1.7370.457
      Presence of ascitesYes vs. No46 / 432.3220.926 – 5.8230.072NS
      Fecal microbiota
       g FusobacteriumEnriched vs. Depleted33 / 561.6250.656 – 4.0270.294
       g RothiaEnriched vs. Depleted28 / 611.9410.762 – 4.9430.164NS
       g DialisterDepleted vs. Enriched39 /5010.5423.633 – 30.586< 0.0016.8231.978 – 23.5290.0021.034
       g Ruminococcus 2Depleted vs. Enriched49 / 409.3752.895 – 30.360< 0.0014.5901.148 – 18.3570.0310.630
       g MegasphaeraDepleted vs. Enriched57 / 322.9311.043 – 8.2390.041NS
       g AnaerostipesDepleted vs. Enriched34 / 557.3022.718 – 19.618< 0.0014.6401.395 – 15.4310.0120.650
       g Eubacterium HalliiDepleted vs. Enriched56 / 332.4030.891 – 6.8410.083NS
      Abbreviations: AL(S)T, alanine (aspartate) aminotransferase; g, genus; NLR, neutrophil lymphocyte ratio; SGA, subjective global assessment.
      # LASSO logistic regression analysis.
      Binary logistic regression analysis

      Microbiota associated with sarcopenia determined the risk of 1-year cirrhotic complications

      During the median follow-up period of 32.3 months (range: 15.1–35.8 months), 44 patients (49.4%) developed cirrhotic complications within the first year after enrollment. According to the LASSO regression analysis, a higher SGA score and presence of ascites were selected as predictors of 1-year cirrhotic complications. In contrast, hyperalbuminemia and fecal enrichment of genera Ruminococcus 2 and Anaerostipes were independent protectors for 1-year cirrhotic complications with the odds ratios of 0.151, 0.204, and 0.038, respectively (Table 3). On the other hand, the relative fecal abundances of Ruminococcus 2 and Anaerostipes were not significantly different according to the presence of ascites indicating their independent roles (Supplementary Figs. 3C–D).
      Table 3Risk Factors Associated with Development of 1-Year Cirrhotic Complications in Cirrhotic Patients
      CharacteristicsCase numbersUnivariate
      Binary logistic regression analysis.
      Multivariate
      Binary logistic regression analysis.
      LASSO
      LASSO logistic regression model.
      OR95% CIp valueOR95% CIp valueCoefficient
      Age, y> 60 vs. ≤ 6048 / 411.8150.781 – 4.2190.166NS
      SexMale vs. Female69 / 200.7500.276 – 2.0380.573
      SGA score> 1 vs. ≤ 151 / 384.5001.818 – 11.1380.001NS0.437
      Etiology of cirrhosisViral vs. Non-viral59 / 300.6450.266 – 1.5640.332
      Alcohol consumptionYes vs. No17 / 721.1890.413 – 3.4280.748
      NLR> 4.2 vs. ≤ 4.218 / 712.4370.823 – 7.2190.108NS
      Platelet count≤ 100K vs. > 100K56 / 331.2890.544 – 3.0540.564
      Albumin, g/dL> 3.5 vs. ≤ 3.546 / 430.1900.077 – 0.468< 0.0010.1510.037 – 0.6230.009– 0.638
      Prothrombin time, INR> 1.25 vs. ≤ 1.2544 / 452.2500.840 – 6.0280.107NS
      ALT, U/L> 40 vs. ≤ 4019 / 700.9000.326 – 2.4840.839
      AST, U/L> 40 vs. ≤ 4042 / 471.8000.776 – 4.1750.171NS
      Total bilirubin, mg/dL> 2.0 vs. ≤ 2.034 / 551.8450.776 – 4.3880.166NS
      Presence of varicesYes vs. No48 / 411.8150.781 – 4.2190.166NS
      Presence of ascitesYes vs. No46 / 435.9052.363 – 14.753< 0.001NS0.559
      Fecal microbiota
       g FusobacteriumEnriched vs. Depleted33 / 561.3850.584 – 3.2830.460
       g RothiaEnriched vs. Depleted28 / 613.0401.184 – 7.8060.021NS
       g DialisterEnriched vs. Depleted50 / 390.2810.117 – 0.6790.005NS
       g Ruminococcus 2Enriched vs. Depleted40 / 490.0900.033 – 0.246< 0.0010.2040.056 – 0.7400.016– 0.899
       g MegasphaeraEnriched vs. Depleted32 / 570.7000.293 – 1.6720.422
       g AnaerostipesEnriched vs. Depleted55 / 340.0460.014 – 0.152< 0.0010.0380.008 – 0.175< 0.001– 0.208
       g Eubacterium HalliiEnriched vs. Depleted33 / 560.3480.142 – 0.8560.021NS
      Abbreviations: AL(S)T, alanine (aspartate) aminotransferase; CI, confidence interval; g, genus; HBsAg, hepatitis B surface antigen; HCV, hepatitis C; NLR, neutrophil lymphocyte ratio; OR, odds ratio; SGA, subjective global assessment.
      # LASSO logistic regression model.
      Binary logistic regression analysis.
      Subgroup analyses according to the relative abundances of these two taxa are presented in table 4. Patients with poor microbial signatures, in which Ruminococcus 2 and Anaerostipes were both depleted, developed more cirrhotic complications (both infectious and non-infectious events) and had more hospitalizations compared with patients with good microbial signatures (p < 0.001). These findings were consistent not only in patients with good liver reserves, but also among patients who were beyond Child-Pugh class A. Regarding specific complications, significantly more events of hepatic encephalopathy (HE), acute kidney injury (AKI) and spontaneous bacterial peritonitis (SBP) were identified in patients with poor microbial signatures (p < 0.001; p = 0.002 and 0.022, respectively compared with their counterparts), especially in those who were at Child-Pugh class B or C. In cirrhotic patients with ascites, the rates of HE, AKI, total complication events and the number of hospitalizations were also significantly higher in patients with poor microbial signatures than patients with good signatures. The rate of SBP was higher in patients with poor microbial signatures but without statistical significance (Supplementary Table 3).
      Table 4Development of 1-year cirrhotic complications classified by sarcopenia-related gut microbial signatures
      Cirrhotic complicationsAll cirrhotic patientsChild-Pugh class AChild-Pugh class B or C
      Microbial signature
      Gut microbial signatures:Good signature: coexistent enrichment of Ruminococcus 2 and AnaerostipesPoor signature: coexistent depletion of Ruminococcus 2 and AnaerostipesFair signature: only enrichment of Ruminococcus 2 or Anaerostipes
      Microbial signature
      Gut microbial signatures:Good signature: coexistent enrichment of Ruminococcus 2 and AnaerostipesPoor signature: coexistent depletion of Ruminococcus 2 and AnaerostipesFair signature: only enrichment of Ruminococcus 2 or Anaerostipes
      Microbial signature
      Gut microbial signatures:Good signature: coexistent enrichment of Ruminococcus 2 and AnaerostipesPoor signature: coexistent depletion of Ruminococcus 2 and AnaerostipesFair signature: only enrichment of Ruminococcus 2 or Anaerostipes
      GoodFairPoorGoodFairPoorGoodFairPoor
      n = 33n = 29n = 27p valuen = 25n = 11n = 10p valuen = 8n = 18n = 17p value
      Number of patients with events, n (%)
       All complications1 (3.0)20 (69.0)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      23 (85.2)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      < 0.0010 (0)7 (63.6)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      6 (60.0)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      < 0.0011 (12.5)13 (72.2)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      17 (100)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      < 0.001
       Infectious complications1 (3.0)13 (44.8)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      12 (44.4)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      < 0.0010 (0)4 (36.4)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      0 (0)0.0011 (12.5)9 (50.0)12 (70.6)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      0.025
       Non-infectious complications1 (3.0)18 (62.1)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      20 (74.1)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      < 0.0010 (0)6 (54.5)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      6 (60.0)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      < 0.0011 (12.5)12 (66.7)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      14 (82.4)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      0.003
       Specific complications
      Hepatic encephalopathy0 (0)6 (20.7)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      12 (44.4)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      < 0.0010 (0)2 (18.2)0 (0)0.0360 (0)4 (22.2)12 (70.6)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      0.001
      Acute kidney injury0 (0)5 (17.2)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      9 (33.3)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      0.0020 (0)1 (9.1)1 (10.0)0.2870 (0)4 (22.2)8 (47.1)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      0.039
      Spontaneous bacterial peritonitis0 (0)4 (13.8)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      6 (22.2)
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      0.0220 (0)1 (9.1)0 (0)0.1970 (0)3 (16.7)6 (35.3)0.054
      Bacteremia1 (3.0)5 (17.2)4 (14.8)0.1630 (0)2 (18.2)1 (10.0)0.1111 (12.5)3 (16.7)3 (17.6)0.947
      Total number of complication events357
      Kruskal-Wallis test with a Bonferroni correction.
      54
      Kruskal-Wallis test with a Bonferroni correction.
      < 0.001014
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      7
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      < 0.00134347
      Kruskal-Wallis test with a Bonferroni correction.
      0.035
      Total number of hospitalization347
      Kruskal-Wallis test with a Bonferroni correction.
      54
      Kruskal-Wallis test with a Bonferroni correction.
      < 0.001011
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      7
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      < 0.00133647
      Kruskal-Wallis test with a Bonferroni correction.
      0.032
      p < 0.05 compared with patients presented good microbial signature, tested by Pearson’s Chi-squared test or
      $ Kruskal-Wallis test with a Bonferroni correction.
      # Gut microbial signatures:Good signature: coexistent enrichment of Ruminococcus 2 and AnaerostipesPoor signature: coexistent depletion of Ruminococcus 2 and AnaerostipesFair signature: only enrichment of Ruminococcus 2 or Anaerostipes

      Discussion

      This is the first prospective study to demonstrate a significant association between sarcopenia-related gut microbial alterations and the development of complications in patients with liver cirrhosis. Patients with a sarcopenia-related poor microbial signature, in which Ruminococcus 2 and Anaerostipes were both depleted, had significantly more infectious and non-infectious complications as well as more 1-year hospitalizations. In addition, we found a spectrum of microbial alterations in cirrhotic patients from normal muscular status to muscle wasting, strength reduction and sarcopenia. We also found a significant reduction in microbial functions in the biosynthesis of numerous amino acids in patients with sarcopenic cirrhosis. Moreover, close correlations between serum levels of amino acids and sarcopenia-related gut microbiota were also discovered in cirrhotic patients.
      An association between altered intestinal microbiota and age-related declines of muscle mass, composition, and function has been reported;
      • Grosicki G.J.
      • Fielding R.A.
      • Lustgarten M.S.
      Gut Microbiota Contribute to Age-Related Changes in Skeletal Muscle Size, Composition, and Function: Biological Basis for a Gut-Muscle Axis.
      and the important role of gut-muscle axis in the pathophysiology of sarcopenia has also been suggested.
      • Ticinesi A.
      • Lauretani F.
      • Milani C.
      • Nouvenne A.
      • Tana C.
      • Del Rio D.
      • et al.
      Aging Gut Microbiota at the Cross-Road between Nutrition, Physical Frailty, and Sarcopenia: Is There a Gut-Muscle Axis?.
      In patients with liver cirrhosis, a Chinese study reported that the Shannon index of gut microbiota was significantly decreased, and the abundance of Escherichia coli and Peptostreptococcus stomatis were increased in patients with muscle wasting.
      • Ren X.
      • Hao S.
      • Yang C.
      • Yuan L.
      • Zhou X.
      • Zhao H.
      • et al.
      Alterations of intestinal microbiota in liver cirrhosis with muscle wasting.
      According to another Italian study, Eggerthella was found to be significantly enriched in sarcopenic cirrhotic patients; in contrast, Methanobrevibacter, Prevotella and Akkermansia were significantly reduced.
      • Ponziani F.R.
      • Picca A.
      • Marzetti E.
      • Calvani R.
      • Conta G.
      • Del Chierico F.
      • et al.
      Characterization of the gut-liver-muscle axis in cirrhotic patients with sarcopenia.
      Additionally, a decrease in the abundance of Dialister, Ruminococcus, Eubacterium, Dorea and Collinsella, as well as an increase in Rothia were also noted in sarcopenic cirrhotic patients,
      • Ponziani F.R.
      • Picca A.
      • Marzetti E.
      • Calvani R.
      • Conta G.
      • Del Chierico F.
      • et al.
      Characterization of the gut-liver-muscle axis in cirrhotic patients with sarcopenia.
      which are similar to the findings of our study. Although gut microbiome is considered diverse among different ethnicities, and is critically influenced by environmental factors,
      • Bajaj J.S.
      • Idilman R.
      • Mabudian L.
      • Hood M.
      • Fagan A.
      • Turan D.
      • et al.
      Diet affects gut microbiota and modulates hospitalization risk differentially in an international cirrhosis cohort.
      the microbial compositions in sarcopenic cirrhotic patients are similar between the Italian population and our cohort. In contrast, the effects of taking non-selective beta blockers, histamine-2 receptor antagonists, oral anti-diabetic drugs or statins on microbial composition were not significant in our cirrhotic patients. Besides, the etiology of cirrhosis did not cause obvious microbial dissimilarities. The unvaried causes of liver disease, mainly chronic hepatitis B, and the less potent effects of these drugs on microbiota may be responsible for these findings.
      Interestingly in this study, we identified the important roles of the genera Ruminococcus 2 and Anaerostipes not only in the presence of sarcopenia, but also in the development of complications and hospitalizations in patients with liver cirrhosis. Anaerostipes is a butyrate-producing commensal which appears to be important for maintaining gut barrier function
      • Belzer C.
      • Chia L.W.
      • Aalvink S.
      • Chamlagain B.
      • Piironen V.
      • Knol J.
      • et al.
      Microbial Metabolic Networks at the Mucus Layer Lead to Diet-Independent Butyrate and Vitamin B(12) Production by Intestinal Symbionts.
      and is positively associated with healthier muscle mass and function.
      • Ticinesi A.
      • Nouvenne A.
      • Cerundolo N.
      • Catania P.
      • Prati B.
      • Tana C.
      • et al.
      Gut Microbiota, Muscle Mass and Function in Aging: A Focus on Physical Frailty and Sarcopenia.
      It is also reportedly less abundant in patients with overt HE or alcoholic liver disease.
      • Bloom P.P.
      • Luévano Jr., J.M.
      • Miller K.J.
      • Chung R.T.
      Deep stool microbiome analysis in cirrhosis reveals an association between short-chain fatty acids and hepatic encephalopathy.
      ,
      • Lang S.
      • Fairfied B.
      • Gao B.
      • Duan Y.
      • Zhang X.
      • Fouts D.E.
      • et al.
      Changes in the fecal bacterial microbiota associated with disease severity in alcoholic hepatitis patients.
      On the other hand, Ruminococcus is found to be abundant in people with higher muscle mass but decreased in patients with liver cirrhosis, particularly in those with HE.
      • Bajaj J.S.
      • Heuman D.M.
      • Hylemon P.B.
      • Sanyal A.J.
      • White M.B.
      • Monteith P.
      • et al.
      Altered profile of human gut microbiome is associated with cirrhosis and its complications.
      ,
      • Liu C.
      • Cheung W.H.
      • Li J.
      • Chow S.K.
      • Yu J.
      • Wong S.H.
      • et al.
      Understanding the gut microbiota and sarcopenia: a systematic review.
      • Chen Y.
      • Yang F.
      • Lu H.
      • Wang B.
      • Lei D.
      • Wang Y.
      • et al.
      Characterization of fecal microbial communities in patients with liver cirrhosis.
      • Bajaj J.S.
      • Ridlon J.M.
      • Hylemon P.B.
      • Thacker L.R.
      • Heuman D.M.
      • Smith S.
      • et al.
      Linkage of gut microbiome with cognition in hepatic encephalopathy.
      Besides, the relative abundance of Ruminoccocus is negatively related to systemic inflammation or the MELD score of cirrhotic patients.
      • Bajaj J.S.
      • Ridlon J.M.
      • Hylemon P.B.
      • Thacker L.R.
      • Heuman D.M.
      • Smith S.
      • et al.
      Linkage of gut microbiome with cognition in hepatic encephalopathy.
      Similarly to the results of this study, cirrhotic patients with coexisting depletion of these two microbial genera had significantly more events of HE, acute kidney injury and spontaneous bacterial peritonitis. These findings were consistent in patients within and beyond Child-Pugh class A, suggesting the independent role for sarcopenia-related microbiota in the outcomes of liver cirrhosis. HE could be improved by fecal microbiota transplant from slurries enriched with the microbiota that are deficient in patients with HE.
      • Bajaj J.S.
      • Kassam Z.
      • Fagan A.
      • Gavis E.A.
      • Liu E.
      • Cox I.J.
      • et al.
      Fecal Microbiota Transplant from a Rational Stool Donor Improves Hepatic Encephalopathy: A Randomized Clinical Trial.
      Similarly, supplementation of specific microbiota discovered in this study may also be applied in clinical practice to improve sarcopenia and reduce complications in cirrhotic patients.
      Gut microbiota and their metabolites are suggested to regulate host muscle growth and function via many different pathways.
      • Lahiri S.
      • Kim H.
      • Garcia-Perez I.
      • Reza M.M.
      • Martin K.A.
      • Kundu P.
      • et al.
      The gut microbiota influences skeletal muscle mass and function in mice.
      Microbes were reported to be capable of synthesizing amino acids and making them available to the host.
      • Metges C.C.
      Contribution of microbial amino acids to amino acid homeostasis of the host.
      Besides, it could promote protein anabolism in the host by increasing bioavailability of amino acids and insulin responsiveness in the skeletal muscle.
      • Beaumont M.
      • Portune K.J.
      • Steuer N.
      • Lan A.
      • Cerrudo V.
      • Audebert M.
      • et al.
      Quantity and source of dietary protein influence metabolite production by gut microbiota and rectal mucosa gene expression: a randomized, parallel, double-blind trial in overweight humans.
      According to an animal study, increased production of BCAAs by the intestinal microbiota is associated with improved protein synthesis of the host.
      • Lynch C.J.
      • Adams S.H.
      Branched-chain amino acids in metabolic signalling and insulin resistance.
      In addition, amino acids, particularly glutamine, glutamate, and aspartate, are major energy substrates for the intestinal mucosa that are associated with nutrition status.
      • Wu G.
      Functional amino acids in nutrition and health.
      According to PICRUSt2 analyses in this study, the microbial function in biosynthesis of numerous amino acids, including BCAA, glutamine, glutamate, etc., was significantly declined in cirrhotic patients with sarcopenia. Besides, the decreased serum levels of amino acids in sarcopenic cirrhotic patients were closely correlated with alterations in the microbiota. Given these findings, decreased microbial activities in the biosynthesis of amino acids may have a putative impact on the anabolism of amino acids and the development of cirrhotic sarcopenia.
      This study had some limitations. First, this was an observational study, and we could not determine the causal relationship between differential bacteria and cirrhotic sarcopenia. Fecal amino acids were not analyzed, either considering the bias resulted from the undigested or unabsorbed dietary protein or those from the desquamated epithelial cells.
      • Trommelen J.
      • Tomé D.
      • van Loon L.J.C.
      Gut amino acid absorption in humans: Concepts and relevance for postprandial metabolism.
      As a substitute, we investigated the gut-muscle axis by means of PICRUSt 2 analysis to predict the functional change in amino acids biosynthesis of gut microbiota as well as the correlation analyses to investigate the association between microbial composition and serum amino acids of cirrhotic patients. Second, longitudinal data on microbial composition were lacking for stability assessment. However, we regularly followed our patients to ensure that their lifestyle habits were consistent during the follow-up period. Any medical need was well-documented as a complication. Third, liver cirrhosis in our patients were mainly resulted from chronic hepatitis B. It has to be cautious when applying these results to other populations. Fourth, a validation study, either via another cohort or an animal experiment, is needed to verify our findings.
      In conclusion, alterations in the gut microbial composition and functions in the biosynthesis of amino acids are associated with the development of sarcopenia and complications in patients with liver cirrhosis. Patients with sarcopenia-related poor microbial signatures had significantly poorer clinical outcomes. These findings highlight a potential therapeutic strategy to improve the clinical outcomes of cirrhotic patients with sarcopenia by modifying the gut microbiota of them.

      Data availability statement

      The data that support the findings of this study are available from the corresponding author upon reasonable request. The data are not publicly available due to privacy or ethical restrictions.

      Financial support:

      This study was supported by grants from the Ministry of Science and Technology of Taiwan (MOST 107-2314-B-075-043, MOST 108-2314-B-075-057, MOST 109-2314-B-075 -096, MOST 109-2314-B-075-020-MY3) and Taipei Veterans General Hospital (V108B-021, V109B-021, V110B-024). This study was supported in part by services provided by NIH center P30 DK120515 (B.S.).

      Potential conflicts of interests:

      B.S. has been consulting for Ferring Research Institute, HOST Therabiomics, Intercept Pharmaceuticals, Mabwell Therapeutics, Patara Pharmaceuticals and Takeda. B.S.’s institution UC San Diego has received research support from Axial Biotherapeutics, BiomX, CymaBay Therapeutics, NGM Biopharmaceuticals, Prodigy Biotech and Synlogic Operating Company. B.S. is founder of Nterica Bio. UC San Diego has filed several patents with B.S. as inventor.

      Author’s contributions:

      Study concept and design: PC Lee, KC Lee, MC Hou;
      Acquisition of data: KC Lee, PC Lee, TC Yang, HS Lu, TY Cheng, YJ Chen;
      Analysis and interpretation of data: PC Lee, KC Lee, JJ Chiou, CW Huang, UC Yang, E-CH Tan, SH Chou, YL Kuo, B Schnabl;
      Drafting the manuscript: PC Lee;
      Critical revision: KC Lee, B Schnabl, YH Huang, MC Hou;
      Statistical analysis: PC Lee, JJ Chiou, CW Huang, UC Yang, E-CH Tan;
      Obtained funding: MC Hou, PC Lee, B Schnabl;
      Study supervision: MC Hou, KC Lee.

      Acknowledgement

      We highly appreciate Hiu-Yan Kong, Ying-Chun Xu, Kai-Ting Wang, Yi-Hsin Chang, and Kee-Deng Jou for their excellent technical assistance. We would like to acknowledge the support of the GenoInfo Core Facility (C1) funded by National Core Facility for Biopharmaceuticals (NCFPB) of Ministry of Science and Technology of Taiwan (MOST 110-2740-B-A49A-501) for providing the bioinformatics and microbiome data analysis.

      Appendix A. Supplementary data

      The following is/are the supplementary data to this article:

      References

        • Dasarathy S.
        • Merli M.
        Sarcopenia from mechanism to diagnosis and treatment in liver disease.
        J Hepatol. 2016; 65: 1232-1244
        • Merli M.
        • Berzigotti A.
        • Zelber-Sagi S.
        • Dasarathy S.
        • Montagnese S.
        • Genton L.
        • et al.
        EASL Clinical Practice Guidelines on nutrition in chronic liver disease.
        J Hepatol. 2019; 70: 172-193
        • Montano-Loza A.J.
        • Meza-Junco J.
        • Prado C.M.
        • Lieffers J.R.
        • Baracos V.E.
        • Bain V.G.
        • et al.
        Muscle wasting is associated with mortality in patients with cirrhosis.
        Clin Gastroenterol Hepatol. 2012; 10 (173.e161): 166-173
        • Huguet A.
        • Latournerie M.
        • Debry P.H.
        • Jezequel C.
        • Legros L.
        • Rayar M.
        • et al.
        The psoas muscle transversal diameter predicts mortality in patients with cirrhosis on a waiting list for liver transplantation: A retrospective cohort study.
        Nutrition. 2018; 51-52: 73-79
        • Kang S.H.
        • Jeong W.K.
        • Baik S.K.
        • Cha S.H.
        • Kim M.Y.
        Impact of sarcopenia on prognostic value of cirrhosis: going beyond the hepatic venous pressure gradient and MELD score.
        J Cachexia Sarcopenia Muscle. 2018; 9: 860-870
        • Praktiknjo M.
        • Book M.
        • Luetkens J.
        • Pohlmann A.
        • Meyer C.
        • Thomas D.
        • et al.
        Fat-free muscle mass in magnetic resonance imaging predicts acute-on-chronic liver failure and survival in decompensated cirrhosis.
        Hepatology. 2018; 67: 1014-1026
        • Ren X.
        • Hao S.
        • Yang C.
        • Yuan L.
        • Zhou X.
        • Zhao H.
        • et al.
        Alterations of intestinal microbiota in liver cirrhosis with muscle wasting.
        Nutrition. 2021; 83111081
        • Chu H.
        • Duan Y.
        • Yang L.
        • Schnabl B.
        Small metabolites, possible big changes: a microbiota-centered view of non-alcoholic fatty liver disease.
        Gut. 2019; 68: 359-370
        • Schnabl B.
        • Brenner D.A.
        Interactions between the intestinal microbiome and liver diseases.
        Gastroenterology. 2014; 146: 1513-1524
        • Bajaj J.S.
        • Heuman D.M.
        • Hylemon P.B.
        • Sanyal A.J.
        • White M.B.
        • Monteith P.
        • et al.
        Altered profile of human gut microbiome is associated with cirrhosis and its complications.
        J Hepatol. 2014; 60: 940-947
        • Trebicka J.
        • Macnaughtan J.
        • Schnabl B.
        • Shawcross D.L.
        • Bajaj J.S.
        The microbiota in cirrhosis and its role in hepatic decompensation.
        J Hepatol. 2021; 75: S67-s81
        • Bindels L.B.
        • Delzenne N.M.
        Muscle wasting: the gut microbiota as a new therapeutic target?.
        Int J Biochem Cell Biol. 2013; 45: 2186-2190
        • Ponziani F.R.
        • Picca A.
        • Marzetti E.
        • Calvani R.
        • Conta G.
        • Del Chierico F.
        • et al.
        Characterization of the gut-liver-muscle axis in cirrhotic patients with sarcopenia.
        Liver Int. 2021; 41: 1320-1334
        • Tsochatzis E.A.
        • Bosch J.
        • Burroughs A.K.
        Liver cirrhosis.
        Lancet. 2014; 383: 1749-1761
        • Chen L.K.
        • Woo J.
        • Assantachai P.
        • Auyeung T.W.
        • Chou M.Y.
        • Iijima K.
        • et al.
        Asian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia Diagnosis and Treatment.
        J Am Med Dir Assoc. 2020; 21 (e302): 300-307
        • Belarmino G.
        • Gonzalez M.C.
        • Sala P.
        • Torrinhas R.S.
        • Andraus W.
        • D'Albuquerque L.A.C.
        • et al.
        Diagnosing Sarcopenia in Male Patients With Cirrhosis by Dual-Energy X-Ray Absorptiometry Estimates of Appendicular Skeletal Muscle Mass.
        JPEN J Parenter Enteral Nutr. 2018; 42: 24-36
        • Carey E.J.
        • Steidley D.E.
        • Aqel B.A.
        • Byrne T.J.
        • Mekeel K.L.
        • Rakela J.
        • et al.
        Six-minute walk distance predicts mortality in liver transplant candidates.
        Liver Transpl. 2010; 16: 1373-1378
        • Angeli P.
        • Bernardi M.
        • Villanueva C.
        • Francoz C.
        • Mookerjee R.P.
        • Trebicka J.
        • et al.
        EASL Clinical Practice Guidelines for the management of patients with decompensated cirrhosis.
        J Hepatol. 2018; 69: 406-460
        • Tandon P.
        • Raman M.
        • Mourtzakis M.
        • Merli M.
        A practical approach to nutritional screening and assessment in cirrhosis.
        Hepatology. 2017; 65: 1044-1057
        • Bassett Jr., D.R.
        International physical activity questionnaire: 12-country reliability and validity.
        Med Sci Sports Exerc. 2003; 35: 1396
        • Tsai H.I.
        • Lo C.J.
        • Zheng C.W.
        • Lee C.W.
        • Lee W.C.
        • Lin J.R.
        • et al.
        A Lipidomics Study Reveals Lipid Signatures Associated with Early Allograft Dysfunction in Living Donor Liver Transplantation.
        J Clin Med. 2018; 8: 30
        • Nossa C.W.
        • Oberdorf W.E.
        • Yang L.
        • Aas J.A.
        • Paster B.J.
        • Desantis T.Z.
        • et al.
        Design of 16S rRNA gene primers for 454 pyrosequencing of the human foregut microbiome.
        World J Gastroenterol. 2010; 16: 4135-4144
        • Callahan B.J.
        • McMurdie P.J.
        • Rosen M.J.
        • Han A.W.
        • Johnson A.J.
        • Holmes S.P.
        DADA2: High-resolution sample inference from Illumina amplicon data.
        Nat Methods. 2016; 13: 581-583
        • Bolyen E.
        • Rideout J.R.
        • Dillon M.R.
        • Bokulich N.A.
        • Abnet C.C.
        • Al-Ghalith G.A.
        • et al.
        Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
        Nat Biotechnol. 2019; 37: 852-857
        • Douglas G.M.
        • Maffei V.J.
        • Zaneveld J.R.
        • Yurgel S.N.
        • Brown J.R.
        • Taylor C.M.
        • et al.
        PICRUSt2 for prediction of metagenome functions.
        Nat Biotechnol. 2020; 38: 685-688
        • Fluss R.
        • Faraggi D.
        • Reiser B.
        Estimation of the Youden Index and its associated cutoff point.
        Biom J. 2005; 47: 458-472
        • Grosicki G.J.
        • Fielding R.A.
        • Lustgarten M.S.
        Gut Microbiota Contribute to Age-Related Changes in Skeletal Muscle Size, Composition, and Function: Biological Basis for a Gut-Muscle Axis.
        Calcif Tissue Int. 2018; 102: 433-442
        • Ticinesi A.
        • Lauretani F.
        • Milani C.
        • Nouvenne A.
        • Tana C.
        • Del Rio D.
        • et al.
        Aging Gut Microbiota at the Cross-Road between Nutrition, Physical Frailty, and Sarcopenia: Is There a Gut-Muscle Axis?.
        Nutrients. 2017; 9: 1303
        • Bajaj J.S.
        • Idilman R.
        • Mabudian L.
        • Hood M.
        • Fagan A.
        • Turan D.
        • et al.
        Diet affects gut microbiota and modulates hospitalization risk differentially in an international cirrhosis cohort.
        Hepatology. 2018; 68: 234-247
        • Belzer C.
        • Chia L.W.
        • Aalvink S.
        • Chamlagain B.
        • Piironen V.
        • Knol J.
        • et al.
        Microbial Metabolic Networks at the Mucus Layer Lead to Diet-Independent Butyrate and Vitamin B(12) Production by Intestinal Symbionts.
        mBio. 2017; 8e00770-17
        • Ticinesi A.
        • Nouvenne A.
        • Cerundolo N.
        • Catania P.
        • Prati B.
        • Tana C.
        • et al.
        Gut Microbiota, Muscle Mass and Function in Aging: A Focus on Physical Frailty and Sarcopenia.
        Nutrients. 2019; 11: 1633
        • Bloom P.P.
        • Luévano Jr., J.M.
        • Miller K.J.
        • Chung R.T.
        Deep stool microbiome analysis in cirrhosis reveals an association between short-chain fatty acids and hepatic encephalopathy.
        Ann Hepatol. 2021; 25100333
        • Lang S.
        • Fairfied B.
        • Gao B.
        • Duan Y.
        • Zhang X.
        • Fouts D.E.
        • et al.
        Changes in the fecal bacterial microbiota associated with disease severity in alcoholic hepatitis patients.
        Gut Microbes. 2020; 121785251
        • Liu C.
        • Cheung W.H.
        • Li J.
        • Chow S.K.
        • Yu J.
        • Wong S.H.
        • et al.
        Understanding the gut microbiota and sarcopenia: a systematic review.
        J Cachexia Sarcopenia Muscle. 2021; 12: 1393-1407
        • Chen Y.
        • Yang F.
        • Lu H.
        • Wang B.
        • Lei D.
        • Wang Y.
        • et al.
        Characterization of fecal microbial communities in patients with liver cirrhosis.
        Hepatology. 2011; 54: 562-572
        • Bajaj J.S.
        • Ridlon J.M.
        • Hylemon P.B.
        • Thacker L.R.
        • Heuman D.M.
        • Smith S.
        • et al.
        Linkage of gut microbiome with cognition in hepatic encephalopathy.
        Am J Physiol Gastrointest Liver Physiol. 2012; 302: G168-175
        • Bajaj J.S.
        • Kassam Z.
        • Fagan A.
        • Gavis E.A.
        • Liu E.
        • Cox I.J.
        • et al.
        Fecal Microbiota Transplant from a Rational Stool Donor Improves Hepatic Encephalopathy: A Randomized Clinical Trial.
        Hepatology. 2017; 66: 1727-1738
        • Lahiri S.
        • Kim H.
        • Garcia-Perez I.
        • Reza M.M.
        • Martin K.A.
        • Kundu P.
        • et al.
        The gut microbiota influences skeletal muscle mass and function in mice.
        Sci Transl Med. 2019; 11eaan5662
        • Metges C.C.
        Contribution of microbial amino acids to amino acid homeostasis of the host.
        J Nutr. 2000; 130: 1857s-1864s
        • Beaumont M.
        • Portune K.J.
        • Steuer N.
        • Lan A.
        • Cerrudo V.
        • Audebert M.
        • et al.
        Quantity and source of dietary protein influence metabolite production by gut microbiota and rectal mucosa gene expression: a randomized, parallel, double-blind trial in overweight humans.
        Am J Clin Nutr. 2017; 106: 1005-1019
        • Lynch C.J.
        • Adams S.H.
        Branched-chain amino acids in metabolic signalling and insulin resistance.
        Nat Rev Endocrinol. 2014; 10: 723-736
        • Wu G.
        Functional amino acids in nutrition and health.
        Amino Acids. 2013; 45: 407-411
        • Trommelen J.
        • Tomé D.
        • van Loon L.J.C.
        Gut amino acid absorption in humans: Concepts and relevance for postprandial metabolism.
        Clinical Nutrition Open Science. 2021; 36: 43-55