Subscribe
  • Original Article
  • OPEN ACCESS

Dissecting the Contributing Role of Divergent Adipose Tissue to Multidimensional Frailty in Cirrhosis

  • Lihong Mao1,2,#,
  • Chaoqun Li1,3,#,
  • Xiaoyu Wang1,2,
  • Mingyu Sun1,2,
  • Yifan Li1,2,
  • Zihan Yu1,2,
  • Binxin Cui4,
  • Gaoyue Guo1,2,
  • Wanting Yang1,2,
  • Yangyang Hui1,2,
  • Xiaofei Fan1,2,
  • Jie Zhang1,2,
  • Kui Jiang1,2,* and
  • Chao Sun1,2,4,* 
 Author information
Journal of Clinical and Translational Hepatology 2023;11(1):58-66

DOI: 10.14218/JCTH.2022.00027

Abstract

Background and Aims

Emerging evidence has demonstrated that abnormal body composition may potentiate the development of frailty, whereas little work focuses on the role of divergent adipose tissue. Therefore, we aimed to determine the potential contribution of adipose tissue distribution to multidimensional frailty in decompensated cirrhosis.

Methods

We conducted a retrospective cohort study. Divergent adipose tissues were assessed by computed tomography-derived subcutaneous adipose tissue index (SATI), visceral adipose tissue index (VATI) and total adipose tissue index (TATI), respectively. Frailty was identified by our validated self-reported Frailty Index. Multiple binary logistic models incorporating different covariates were established to assess the relationship between adipose tissue distribution and frailty.

Results

The study cohort comprised 245 cirrhotic patients with 45.3% being male. The median Frailty Index, body mass index (BMI) and model for end-stage liver disease (MELD) score were 0.11, 24.3 kg/m2 and 8.9 points, respectively. In both men and women, patients who were frail exhibited lower levels of SATI in comparison with nonfrail patients. SATI inversely correlated with Frailty Index in the entire cohort (rs=−0.1361, p=0.0332). Furthermore, SATI or TATI was independently associated with frail phenotype in several multiple logistic regression models adjusting for age, BMI, presence of ascites, sodium, Child-Pugh class or MELD score in isolation.

Conclusions

In the context of decompensated cirrhosis, low SATI and concomitant TATI were associated with higher risk of being frail. These findings highlight the importance to further apply tissue-specific tools of body composition in place of crude metric like BMI.

Keywords

Frailty, Adipose tissue, Liver cirrhosis, Subcutaneous adipose tissue index

Introduction

In the field of hepatology or liver transplantation, the conceptual frame of frailty mainly concentrates on physical frailty because it is measured in ambulatory and transplant settings.1 For instance, Lai and colleagues developed a feasible and reliable liver frailty index metric based on performance, including handgrip strength, chair stands, and balance, and successfully linked it to various adverse outcomes.2–4 However, a major limitation of these performance-based metrics is the need of active patient participation during the testing process, which is not applicable in acutely ill and severely decompensated cirrhotics who are hospitalized.5 As a matter of fact, the original definition of frailty in the geriatrics indicates a distinct syndrome pertaining to decreased physiological reserve and increased vulnerability to health stressors.6 Multidimensional frailty arises from multiple derangements of one or combined physiological systems including endocrine, musculoskeletal, neurological, cardiovascular, and immune systems. Recently, our research team has revised and obtained an Frailty Index that includes global frail components and we validated the clinical utility of this self-reported scale for prognostication in the context of cirrhosis.7,8 Despite a consistent relationship between both physical and multidimensional frailty and adverse outcomes across populations, gaps remain in identifying risk factors for the development of frailty in advanced chronic liver diseases. It is pivotal to identify risk factors for frailty with the purpose of delineating its pathobiology as well as introducing novel preventive and therapeutic targets.

Unlike sarcopenia, the clinical relevance of adipose tissue has not been well recognized in patients with cirrhosis. Rodrigues et al. found that adipopenia, or a low total adipose tissue index (TATI), was associated with decompensation in patients with cirrhosis.9 Furthermore, low subcutaneous adipose tissue index (SATI) was shown to be independently associated with increased mortality in female cirrhotic patients,10 but no relationship was observed between visceral adipose tissue index (VATI) and waitlist mortality in subjects evaluated for liver transplantation.11 Notably, subcutaneous and visceral adipose tissue, two divergent types of adipose tissue, vary remarkably in anatomical location, adipocyte size, lipolytic ability, insulin sensitivity, and adipokine secretion.12 Intriguingly, Anderson et al. found a nonlinear relationship between VAT and frailty in adult lung transplant candidates.13 On the other hand, computed tomography (CT)-based SAT at the third lumbar vertebra (L3) and body mass index (BMI) were significantly lower in frail men compared with prefrailty in elderly pelvic trauma patients.14 However, the association between adipose tissue distribution and frailty in patients with cirrhosis is unclear. Taken together, we sought to determine the relationship between multidimensional frailty and a diverse panel of measures of body composition, including BMI, waist circumference, skeletal muscle index (SMI), SATI, VATI, TATI, and visceral to subcutaneous adipose tissue area ratio (VSR) in patients with decompensated cirrhosis.

Methods

Study cohort

This retrospective cohort study was approved by the ethnic committee of Tianjin Medical University General Hospital (TJMUGH, IRB2021-YX-136-01) and conducted following the ethical guidelines of the Declaration of Helsinki. We consecutively recruited adult patients diagnosed with cirrhosis by their medical records, biochemical data, radiological findings, or histological results in our department between 2017 and 2021. The following exclusion criteria were adopted: (1) primary hepatocellular carcinoma or extrahepatic malignancies; (2) acute-on-chronic liver failure during hospitalization; (3) severe hepatic encephalopathy precluding finishing Frailty Index questionnaire; (4) liver transplantation, and (5) denial of regular follow-up. A total of 245 patients with decompensated cirrhosis was included in the analysis (Fig. S1). The baseline patient characteristics such as demographics (age, sex), Child-Pugh class, model for end-stage liver disease (MELD) score, laboratory parameters, etiology, anthropometry (weight and height) were retrieved from our hospital’s electronic database. BMI values were estimated on the basis of dry weight as has been previously described, taking into consideration the fluid retention that occurs in a large percentage of cirrhotics.15,16

CT evaluation of body composition

We collected imaging biomarkers of body composition including SMI and several adipose tissues (subcutaneous SAT and visceral VAT). The parameters were measured by analyzing CT images at the L3 level using a noncommercial software based on Matlab version R2010a (Mathworks Inc., Natick, MA, USA). The cross-sectional area of SAT/VAT and skeletal muscles was reported as square meters (m2). Tissue-specific Hounsfield unit (HU) thresholds were applied to discriminate divergent tissue types. The CT thresholds were −190 to −30 for SAT, −150 to −50 for VAT and −29 to 150 HU for quantifying skeletal muscles.9,17,18 All values were normalized to height in m2 and used to calculated indexes such as SMI, SATI, VATI and TATI (cm2/m2). Visceral adiposity was assessed by VSR. All abdominal CT scans were performed within 3 months prior to hospitalization.

Frailty Index evaluation

We have previously described the use of our Frailty Index.7 In brief, this self-reported scale derives from the Carolina Frailty Index with minor modification. The Frailty Index comprises 36 variables including unintentional weight loss, exhaustion, instrumental activities of daily living, physical function, and social activities, etc. A valid questionnaire contained at least 10 fulfilled issues. For instance, a patient would have a score of 0.33 after getting 12 points in the case of finishing all 36 issues (12/36). We regarded patients with an Frailty Index of >0.38 as frail phenotype. All Frailty Index questionnaires were collected within 48 h of the first admission to our department.

Statistical analysis

Continuous variables were reported as medians and interquartile range (IQR) and compared by the Mann–Whitney U test. For categorical variables, descriptive data were reported as frequency or proportion (%) and compared by χ2 or Fisher’s exact test. Correlations between body composition biomarkers and the Frailty Index were determined by the Spearman’s rank correlation coefficient (rs). Multivariate logistic regression analysis was used to estimate the odds ratio (OR) and 95% confidence interval (CI) for each measure of body composition with distinct levels of frailty as the outcome (that is, frailty and nonfrailty). The covariates that we used in the multivariate analysis were chosen on the basis of statistically significant univariate association with frail status and previously established scientific knowledge. We examined all body composition metrics as continuums without dichotomization to better understand the association with frailty. To avoid overfitting and maximize statistical power, we made four multiple regression models incorporating Child-Pugh class or MELD score. A p-value < 0.05 was considered statistically significant. The statistical analysis was performed with SPSS 23.0 (IBM Corp., Armonk, New York, NY, USA) or Graphpad Prism 8.0.1 (La Jolla, CA, USA).

Results

Of the 245 patients with cirrhosis included in the study, 111 were men with an average age of 63 (IQR: 57, 69) years (Table 1). In the entire cohort, the median Frailty Index, BMI, and MELD score were 0.11 (IQR: 0.06, 0.24), 24.3 (IQR: 21.3, 27.3) kg/m2 and 8.9 (IQR: 6.5, 11.7) points, respectively. Frail patients had lower levels of BMI and albumin, higher levels of total bilirubin and creatinine, and greater proportions of Child-Pugh class B and C and ascites. Regarding body composition, SATI, and TATI were lower in patients with cirrhosis and frailty, and no significant differences in VSR or VATI were observed.

Table 1

Baseline characteristics of the entire cohort, categorized by sex and multidimensional frail phenotype

CharacteristicAll (n=245)All (n=245)
Men (n=111)
Women (n=134)
Frailty (n=27)Nonfrailty (n=218)pFrailty (n=14)Nonfrailty (n=97)pFrailty (n=13)Nonfrailty (n=121)p
Age, year63 [57,69]65 [57,74]63 [57,68]0.070865 [57,68]59 [50,67]0.154171 [55,76]65 [58,69]0.0804
Height, m1.65 [1.60,1.70]1.65 [1.63,1.70]1.65 [1.60,1.70]0.27311.70 [1.66,1.73]1.71 [1.65,1.76]0.50611.64 [1.60,1.65]1.60 [1.57,1.65]0.0686
Weight, kg65 [57,75]60 [54,73]67 [58,75]0.043767 [55,80]72 [65,82]0.195458 [48,61]64 [53,70]0.0590
BMI, kg/m224.3 [21.3,27.3]22.3 [18.7,26.0]24.6 [21.5,27.3]0.009823.7 [19.0,27.4]24.6 [22.5,27.8]0.355921.3 [18.2,23.4]24.4 [20.6,27.3]0.0065
Waist circumference, cm96.1 [86.8,104.5]97.0 [89.9,109.5]96.1 [86.0,104.3]0.284398.4 [91.8,109.8]98.3 [89.6,107.4]0.716795.1 [88.1,108.1]93.7 [83.2,100.3]0.3354
VSR0.92 [0.68,1.28]1.14 [0.71,1.36]0.91 [0.67,1.28]0.15861.20 [1.07,1.87]1.13 [0.78,1.70]0.41530.87 [0.69,1.14]0.78 [0.59,1.00]0.4206
SMI, cm2/m245.88 [39.03,52.09]45.13 [37.17,50.65]45.93 [38.05,52.30]0.561745.72 [40.26,52.72]49.73 [42.63,55.52]0.272043.58 [36.09,48.56]42.15 [36.78,48.71]0.9817
SATI, cm2/m244.86 [31.79,72.52]34.70 [26.54,42.64]48.69 [32.49,74.27]0.002733.87 [15.57,38.54]38.13 [27.46,55.01]0.058535.14 [28.49,66.85]59.74 [37.41,82.18]0.0329
VATI, cm2/m245.67 [29.75,67.04]41.10 [25.59,55.26]47.45 [30.14,68.97]0.149443.41 [30.29,51.66]49.84 [32.06,73.10]0.241735.17 [25.05,64.48]45.25 [29.75,64.63]0.3626
TATI, cm2/m297.79 [66.22,134.10]77.85 [55.98,95.81]102.00 [67.78,135.40]0.010781.28 [42.01,87.06]96.19 [62.72,125.80]0.053869.65 [56.42,125.10]110.00 [69.99,140.40]0.0771
Frailty Index0.11 [0.06,0.24]0.49 [0.43,0.51]0.09 [0.06,0.17]<0.00010.49 [0.41,0.51]0.08 [0.06,0.17]<0.00010.50 [0.44,0.58]0.10 [0.05,0.18]<0.0001
MELD score8.9 [6.5,11.7]11.7 [9.6,13.2]8.6 [6.2,11.2]0.001211.7 [8.4,13.2]8.4 [5.1,10.6]0.038711.7 [10.0,13.7]8.7 [6.9,11.4]0.0079
INR1.28 [1.16,1.45]1.33 [1.26,1.50]1.27 [1.15,1.44]0.07111.39 [1.26,1.50]1.34 [1.20,1.59]0.70761.30 [1.25,1.45]1.22 [1.12,1.38]0.0598
Albumin, g/L[28 25,32][25 22,28][28 25,32]0.0016[25 22,28][28 25,33]0.0090[25 20,31][29 25,32]0.0554
Total bilirubin, µmol/L21.5 [14.3,37.5]33.2 [21.9,54.3]19.8 [13.9,35.9]0.005632.2 [21.5,55.9]19.9 [13.3,37.9]0.028431.4 [22.1,53.6]19.8 [14.2,34.3]0.0197
Creatinine, µmol/L58 [47,70]63 [57,81]57 [46,69]0.017864 [60,86]64 [56,75]0.665361 [49,79]50 [42,59]0.0267
Sodium, mmol/L141 [138,142]139 [136,142]141 [138,142]0.0751140 [135,142]141 [138,142]0.4383139 [136,141]141 [139,142]0.0885
Child-Pugh class (%)0.00130.04950.0021
  A74 (30.2)2 (7.4)72 (33.0)0 (0.0)30 (30.9)2 (15.4)42 (34.7)
  B131 (53.5)15 (55.6)116 (53.2)10 (71.4)50 (51.5)5 (38.5)66 (54.5)
  C40 (16.3)10 (37.0)30 (13.8)4 (28.6)17 (17.5)6 (46.2)13 (10.7)
Etiology (%)0.56730.72720.3686
  HBV/HCV67 (27.3)4 (14.8)63 (28.9)3 (21.4)26 (26.8)1 (7.7)37 (30.6)
  Alcohol62 (25.3)7 (25.9)55 (25.2)7 (50.0)53 (54.6)0 (0.0)2 (1.7)
  AILD66 (26.9)9 (33.3)57 (26.1)2 (14.3)15 (15.5)7 (53.8)42 (34.7)
  Biliary31 (12.7)2 (7.4)29 (13.3)0 (0.0)2 (2.1)2 (15.4)27 (22.3)
  NAFLD/Cryptogenic49 (20.0)6 (22.2)43 (19.7)2 (14.3)16 (16.5)4 (30.8)27 (22.3)
Ascites (%)<0.00010.00780.0062
  Yes140 (57.1)25 (92.6)115 (52.8)13 (92.9)54 (55.7)12 (92.3)61 (50.4)
  No105 (42.9)2 (7.4)103 (47.2)1 (7.1)43 (44.3)1 (7.7)60 (49.6)

Data are medians (interquartile range) or frequency and proportion (%). p-values were derived from the Mann–Whitney U test or Fisher’s exact test. AILD, auto-immune liver disease; BMI, body mass index; INR, international normalized ratio; MELD, model for end-stage liver disease; NAFLD, nonalcoholic fatty liver disease; SATI, subcutaneous adipose tissue index; SMI, skeletal muscle index; TATI, total adipose tissue index; VATI, visceral adipose tissue index; VSR, visceral to subcutaneous adipose tissue area ratio.

Taking into consideration sex-differences in the distribution of divergent adipose tissue, women store higher levels of SATI and VATI is higher in men in the context of cirrhosis.10 These characteristics are shown separately for men and women in Fig. 1. Intriguingly, frail men had lower levels of SATI (33.87 vs. 38.13 cm2/m2, p=0.0585) and lower TATI (81.28 vs. 96.19 cm2/m2, p=0.0538) that were of borderline statistical significance. In women, lower levels of SATI (35.14 vs. 59.74 cm2/m2, p=0.0329) and a trend favoring lower TATI (69.65 vs. 110.00 cm2/m2, p=0.0771) were observed in frail compared with nonfrail individuals.

Comparison of the VSR (A), SATI (B), VATI (C) and TATI (D) by frailty and sex.
Fig. 1  Comparison of the VSR (A), SATI (B), VATI (C) and TATI (D) by frailty and sex.

SATI, subcutaneous adipose tissue index; TATI, total adipose tissue index; VATI, visceral adipose tissue index; VSR, visceral to subcutaneous adipose tissue area ratio.

Correlation between biomarkers of adipose tissue and Frailty Index

In the entire cohort, Frailty Index positively correlated with VSR (rs=0.1710, p=0.0073) and negatively with SATI (rs=−0.1361, p=0.0332). When stratified by sex, a correlation was also found regarding VSR both in men (rs=0.1896, p=0.0463) and women (rs=0.1777, p=0.0400). No significant correlations were observed between Frailty Index and VATI/TATI across the study cohort (Fig. 2).

Correlation between the Frailty Index, VSR (A), SATI (B), VATI (C) and TATI (D) in the entire cohort and subsettings by sex.
Fig. 2  Correlation between the Frailty Index, VSR (A), SATI (B), VATI (C) and TATI (D) in the entire cohort and subsettings by sex.

rs, Spearman’s rank correlation coefficient; SATI, subcutaneous adipose tissue index; TATI, total adipose tissue index; VATI, visceral adipose tissue index; VSR, visceral to subcutaneous adipose tissue area ratio.

Association between frailty and various measures of body composition

Univariate logistic regression demonstrated that age, BMI, SATI, TATI, albumin, sodium, MELD score, Child-Pugh class, and the presence of ascites were risk factors in relation to frailty (Table 2). To avoid redundancy and to maximize statistical power, we planned to establish four multiple logistic models incorporating MELD score or Child-Pugh class in isolation with distinct panels of measures pertaining to adipose tissue distribution. In model 1, adjusting for BMI and sodium, age (OR=1.059, 95% CI: 1.008–1.113; p=0.024), SATI (OR=0.972, 95% CI: 0.950–0.994; p=0.013), MELD score (OR=1.018, 95% CI: 1.014–1.211; p=0.023), and presence of ascites (OR=6.077, 95% CI: 1.340–27.560; p=0.019) were independent risk factors of frailty. In model 2, accounting for BMI and sodium, age (OR=1.066, 95% CI: 1.017–1.118; p=0.008), TATI (OR=0.987, 95% CI: 0.976–0.998; p=0.019) and Child-Pugh class C (OR=10.773, 95% CI: 2.149–53.997; p=0.004) were independent risk factors of frailty. In model 3, adjusting for BMI and sodium, age (OR=1.065, 95% CI: 1.016–1.117; p=0.009), SATI (OR=0.972, 95% CI: 0.952–0.993; p=0.008), and Child-Pugh class C (OR=10.747, 95% CI: 2.132–54.182; p=0.004) were independent risk factors of frailty. In model 4, accounting for BMI and sodium, age (OR=1.059, 95% CI: 1.008–1.113; p=0.023), TATI (OR=0.986, 95% CI: 0.975–0.997; p=0.016), MELD score (OR=1.106, 95% CI: 1.012–1.209; p=0.027), and presence of ascites (OR=6.525, 95% CI: 1.451–29.343; p=0.014) were independent risk factors of frailty.

Table 2

Univariate and multivariate logistic regression of frailty in patients with cirrhosis

VariableUnivariate analysis
Multivariate analysis
Model 1#
Model 2#
Model 3#
Model 4#
OR (95%CI)pOR (95% CI)pOR (95% CI)pOR (95% CI)pOR (95% CI)p
Sex1.343 [0.630,2.992]0.470
Age, years1.056 [1.008,1.107]0.0221.059 [1.008,1.113]0.0241.066 [1.017,1.118]0.0081.065 [1.016,1.117]0.0091.059 [1.008,1.113]0.023
BMI, kg/m20.879 [0.793,0.973]0.013
VSR1.520 [0.856,2.696]0.153
SMI, cm2/m20.991 [0.955,1.029]0.649
SATI, cm2/m20.971 [0.952,0.991]0.0050.972 [0.950,0.994]0.0130.972 [0.952,0.993]0.008
VATI, cm2/m20.987 [0.971,1.004]0.134
TATI, cm2/m20.987 [0.977,0.997]0.0120.987 [0.976,0.998]0.0190.986 [0.975,0.997]0.016
INR1.913 [0.477,7.672]0.360
Albumin, g/L0.857 [0.783,0.937]0.001
Total bilirubin, µmol/L1.004 [0.999,1.009]0.095
Creatinine, µmol/L1.007 [0.995,1.019]0.278
Sodium, mmol/L0.886 [0.808,0.971]0.010
MELD score1.102 [1.020,1.189]0.0141.018 [1.014,1.211]0.0231.106 [1.012,1.209]0.027
Child-Pugh Class
  ARefRefRef
  B4.655 [1.034,20.956]0.0453.594 [0.780,16.563]0.1013.581 [0.776,16.532]0.102
  C12.000 [2.480,58.073]0.00210.773 [2.149,53.997]0.00410.747 [2.132,54.182]0.004
Ascites11.196 [2.588,48.431]0.0016.077 [1.340,27.560]0.0196.525 [1.451,29.343]0.014

#Model 1 adjusted for: Age, BMI, SATI, MELD score, ascites, and sodium. #Model 2 adjusted for: Age, BMI, TATI, Child-Pugh class, and sodium. #Model 3 adjusted for: Age, BMI, SATI, Child-Pugh class, and sodium. #Model 4 adjusted for: Age, BMI, TATI, MELD score, ascites, and sodium. BMI, body mass index; INR, international normalized ratio; MELD, model for end-stage liver disease; SATI, subcutaneous adipose tissue index; SMI, skeletal muscle index; TATI, total adipose tissue index; VATI, visceral adipose tissue index; VSR, visceral to subcutaneous adipose tissue area ratio.

Discussion

In this study of patients with decompensated cirrhosis, we found a strong relationship between SAT and frailty. Whilst the biomedical literature has mainly concentrated on the association between sarcopenia and frailty, our findings are in line with a smaller body of work reporting an association between abnormal adipose tissue distribution and frailty in a variety of pathological entities.13,14,19 Of note, patients with either low SATI or concomitant TATI in particular are at increased risk of frailty after controlling for age, conventional predictive scores (Child-Pugh class/MELD score), BMI, and presence of ascites. Although the reasons for negative impact of low SATI are not well known, investigating the mechanisms driving this relationship may help develop strategies to prevent and even treat frailty.

Given the emerging role and clinical relevance of adipose tissue in frailty, the research focus has been identified across different populations. For instance, Hawkins et al. showed that older men with or without HIV infection, with higher VAT, higher waist circumference, sarcopenia, and osteoporosis were more likely to be frail.19 Another study conducted in a cohort of adult lung transplant candidates revealed that both patients with extremely low or high VAT were at increased risk of frailty after adjusting for age, sex, forced vital capacity, BMI, and skeletal muscle mass.13 Furthermore, Laur and colleagues used CT-derived abdominal body composition at the L3 level to determine their association with a diagnosis of frailty in their institution’s pelvic trauma registry.14 They found that SAT was significantly lower in the frail men compared with prefrail men, which is consistent with our findings.

We and others corroborate that frailty is independent of traditional scoring systems and cirrhosis-associated complications like ascites and hepatic encephalopathy in the prediction of mortality.7,20 More recently, Wang et al. found that frailty serves as an independent predictor of disease progression among patients with compensated and decompensated cirrhosis, all of which implicates that frailty may occur at an earlier stage of cirrhosis.5 On the other hand, Rodrigues and colleagues addressed that lower TATI (adipopenia) is associated with 12-month decompensation; fat loss may precede sarcopenia development.9 In addition, the severity of portal hypertension (indicative of hepatic venous pressure gradient) showed significantly inverse correlation with SATI (r=−0.282, p=0.01) and TATI (r=−0.220, p=0.045) but not VATI or SMI. Contextually, our study now adds a small but accumulating body of literature that SAT depletion may instigate the progression of frail phenotype prior to evident muscle depletion in early-decompensated cirrhosis (median MELD score of 8.9 points in our cohort).

Our finding of no relationship between VATI and frailty was unexpected. Actually, VAT is primarily involved in obesity-associated metabolic disturbance.21 Free fatty acids and adipokines released from VAT are delivered directly to the liver via portal vein, where they lead to inflammation and abnormal lipids deposition.12,22 As a consequence, high amount of VAT can exacerbate an existing dysregulated metabolic state in patients with cirrhosis, and thus foster frailty. However, in most patients, SAT represents the metabolically more favorable adipose compartment and is the most abundant of total fat tissue.23 It has been suggested that failure to expand SAT is a major factor potentiating visceral fat accumulation and insulin resistance.24,25 Moreover, preclinical data suggests that removing subcutaneous fat gives rise to visceral fat accumulation, insulin resistance, and expression of TNF-α.26 Taken together, further dedicated studies in this field are warranted to validate our findings, that is, low SATI acts as a sign of abnormal adipose tissue distribution.

Our current understanding of the development of frailty is in its infancy and under extensive investigation. As the relationship between low SATI/TATI and frailty appears to be a novel finding in the context of cirrhosis, we are obligated to address several potential mechanisms. First, SAT serves to provide energy in a catabolic state and is responsible for uptake and storage of triglycerides and free fatty acids.27 Low SATI and concomitant TATI may reflect a state of protein-energy malnutrition and the absence of energy reserves, while malnutrition and frailty have proved to be inter-related in cirrhosis.28 Second, SAT can result in production of adipokines that regulate lipid metabolism and immune responses.29 Both adipose tissue dysfunction and chronic systemic inflammation are pathobiological factors described in the frailty literature.30 Third, Gioia et al. found that SAT contributed to handle and reduce ammonia levels, raising its role for ammonia and conversion of glutamate to glutamine by glutamine synthase.31 Hyperammonemia results in decreased protein synthesis and increased autophagic proteolysis, and consequent sarcopenia is associated with the development of frailty.32,33 Fourth, the adipose tissue depot is a major organ with microRNA (miRNA), and adipose miRNA profiles corresponding to body composition and functional status and predict adverse clinical outcomes. Chan et al. demonstrated that miRNA-130b expression in adipose tissue decreased from nonfrail to severe frailty (1.01-fold vs. 0.32-fold, p=0.031) and predicted frailty independent of age and serum albumin level in patients with advanced chronic kidney disease.34 It is tempting to conduct in-depth investigations of miRNA perturbation, adipose tissue distribution, and frail phenotype in the context of cirrhosis.

There are several study limitations that should be acknowledged. The first is the study’s observational nature, which does not allow determining whether abnormal adipose tissue distribution acts as a cause, a predisposing factor, or a consequence of frailty. Second, the investigation of the Frailty Index was based on single-center data, and is without external validation. It is possible that the relationship between low SATI and frail phenotype may differ from other metrics to evaluate frailty. However, our results are pivotal for instigating additional multicenter studies linking abnormal adipose tissue distribution to the development of frailty. Third, we arbitrarily dichotomized the study population into frailty and nonfrailty in terms of an established cutoff and performed binary logistic regression to identify independent risk factors. While an option determined by clinical availability rather than a limitation, this can partly explain why SMI values as a continuum lost its predictive value for frailty in contrast to sarcopenia. Fourth, ordinary stepwise regression with the purpose of noncausal prediction may incur overstated significance and relatively narrow confidence intervals. Other approaches, such as change-in-estimate strategies with selection of covariates by how much their control changes estimates of exposure effect can be considered.35 Last, we did not examine nutritional, inflammatory, and metabolic indicators such as leptin, triglycerides, or cholesterol, which are intuitively relevant to abnormal adipose tissue deposition.

In summary, this study is the first to describe a complex and nuanced relationship between divergent adipose tissue and frailty in the context of decompensated cirrhosis, and to suggest that low SATI and concomitant TATI are associated with an increased risk of frailty. The findings highlight the importance of tissue-specific body composition in place of crude metrics like BMI. The novel association between SAT and frailty may assist in delineating the pathobiology of frailty and introducing preventive as well as therapeutic avenue.

Supporting information

Fig. S1

Flow chart of the study population.

ACLF, acute-on-chronic liver failure.

(DOCX)

Click here for additional data file.

Abbreviations

AILD: 

auto-immune liver disease

BMI: 

body mass index

CI: 

confidence interval

CT: 

computed tomography

HU: 

Hounsfield unit

INR: 

international normalized ratio

IQR: 

interquartile range

L3: 

third lumbar vertebra

MELD: 

model for end-stage liver disease

NAFLD: 

nonalcoholic fatty liver disease

OR: 

odds ratio

SATI: 

subcutaneous adipose tissue index

SMI: 

skeletal muscle index

TATI: 

total adipose tissue index

VATI: 

visceral adipose tissue index

VSR: 

visceral to subcutaneous adipose tissue area ratio

Declarations

Data sharing statement

No additional data are available.

Funding

KJ is supported by the Science and Technology Program of Tianjin (Grant 19ZXDBSY00020).

Conflict of interest

CS has been an editorial board member of Journal of Clinical and Translational Hepatology since 2020. The other authors have no conflict of interests related to this publication.

Authors’ contributions

Involved in the conception or design of the work (LM, CL, XW, CS), literature screen and review (MS, YL, ZY), data acquisition and statistical analysis (BC), analysis and interpretation of data (GG, WY, YH, XF), drafted the article (CS). All authors critically revised the article and approved the version to be published.

References

  1. Lai JC, Sonnenday CJ, Tapper EB, Duarte-Rojo A, Dunn MA, Bernal W, et al. Frailty in liver transplantation: An expert opinion statement from the American Society of Transplantation Liver and Intestinal Community of Practice. Am J Transplant 2019;19(7):1896-1906 View Article PubMed/NCBI
  2. Lai JC, Covinsky KE, Dodge JL, Boscardin WJ, Segev DL, Roberts JP, et al. Development of a novel frailty index to predict mortality in patients with end-stage liver disease. Hepatology 2017;66(2):564-574 View Article PubMed/NCBI
  3. Serper M, Tao SY, Kent DS, Garren P, Burdzy AE, Lai JC, et al. Inpatient Frailty Assessment Is Feasible and Predicts Nonhome Discharge and Mortality in Decompensated Cirrhosis. Liver Transpl 2021;27(12):1711-1722 View Article PubMed/NCBI
  4. Wang S, Whitlock R, Xu C, Taneja S, Singh S, Abraldes JG, et al. Frailty is associated with increased risk of cirrhosis disease progression and death. Hepatology 2022;75(3):600-609 View Article PubMed/NCBI
  5. Tandon P, Montano-Loza AJ, Lai JC, Dasarathy S, Merli M. Sarcopenia and frailty in decompensated cirrhosis. J Hepatol 2021;75(Suppl 1):S147-S162 View Article PubMed/NCBI
  6. Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56(3):M146-M156 View Article PubMed/NCBI
  7. Deng Y, Lin L, Hou L, Fan X, Zhao T, Mao L, et al. A self-reported Frailty Index predicts long-term mortality in hospitalized patients with cirrhosis. Ann Transl Med 2020;8(19):1217 View Article PubMed/NCBI
  8. Hui Y, Xu L, Wang X, Feng H, Yu Z, Li C, et al. Association between sleep disturbance and multidimensional frailty assessed by Frailty Index in hospitalized cirrhosis. Eur J Gastroenterol Hepatol 2021;33(Suppl S1):e727-e733 View Article PubMed/NCBI
  9. Rodrigues SG, Brabandt B, Stirnimann G, Maurer MH, Berzigotti A. Adipopenia correlates with higher portal pressure in patients with cirrhosis. Liver Int 2019;39(9):1672-1681 View Article PubMed/NCBI
  10. Ebadi M, Tandon P, Moctezuma-Velazquez C, Ghosh S, Baracos VE, Mazurak VC, et al. Low subcutaneous adiposity associates with higher mortality in female patients with cirrhosis. J Hepatol 2018;69(3):608-616 View Article PubMed/NCBI
  11. Montano-Loza AJ, Mazurak VC, Ebadi M, Meza-Junco J, Sawyer MB, Baracos VE, et al. Visceral adiposity increases risk for hepatocellular carcinoma in male patients with cirrhosis and recurrence after liver transplant. Hepatology 2018;67(3):914-923 View Article PubMed/NCBI
  12. Fain JN, Madan AK, Hiler ML, Cheema P, Bahouth SW. Comparison of the release of adipokines by adipose tissue, adipose tissue matrix, and adipocytes from visceral and subcutaneous abdominal adipose tissues of obese humans. Endocrinology 2004;145(5):2273-2282 View Article PubMed/NCBI
  13. Anderson MR, Kolaitis NA, Gao Y, Kukreja J, Greenland J, Hays S, et al. A nonlinear relationship between visceral adipose tissue and frailty in adult lung transplant candidates. Am J Transplant 2019;19(11):3155-3161 View Article PubMed/NCBI
  14. Laur O, Weaver MJ, Bridge C, Chow E, Rosenthal M, Bay C, et al. Computed tomography-based body composition profile as a screening tool for geriatric frailty detection. Skeletal Radiol 2021:1-10 View Article PubMed/NCBI
  15. Tandon P, Low G, Mourtzakis M, Zenith L, Myers RP, Abraldes JG, et al. A Model to Identify Sarcopenia in Patients With Cirrhosis. Clin Gastroenterol Hepatol 2016;14(10):1473-1480.e3 View Article PubMed/NCBI
  16. Feng H, Wang X, Zhao T, Mao L, Hui Y, Fan X, et al. Myopenic obesity determined by visceral fat area strongly predicts long-term mortality in cirrhosis. Clin Nutr 2021;40(4):1983-1989 View Article PubMed/NCBI
  17. Kang SH, Jeong WK, Baik SK, Cha SH, Kim MY. Impact of sarcopenia on prognostic value of cirrhosis: going beyond the hepatic venous pressure gradient and MELD score. J Cachexia Sarcopenia Muscle 2018;9(5):860-870 View Article PubMed/NCBI
  18. Hamaguchi Y, Kaido T, Okumura S, Kobayashi A, Shirai H, Yao S, et al. Preoperative Visceral Adiposity and Muscularity Predict Poor Outcomes after Hepatectomy for Hepatocellular Carcinoma. Liver Cancer 2019;8(2):92-109 View Article PubMed/NCBI
  19. Hawkins KL, Zhang L, Ng DK, Althoff KN, Palella FJ, Kingsley LA, et al. Abdominal obesity, sarcopenia, and osteoporosis are associated with frailty in men living with and without HIV. AIDS 2018;32(10):1257-1266 View Article PubMed/NCBI
  20. Lai JC, Rahimi RS, Verna EC, Kappus MR, Dunn MA, McAdams-DeMarco M, et al. Frailty Associated With Waitlist Mortality Independent of Ascites and Hepatic Encephalopathy in a Multicenter Study. Gastroenterology 2019;156(6):1675-1682 View Article PubMed/NCBI
  21. Pou KM, Massaro JM, Hoffmann U, Lieb K, Vasan RS, O’Donnell CJ, et al. Patterns of abdominal fat distribution: the Framingham Heart Study. Diabetes Care 2009;32(3):481-485 View Article PubMed/NCBI
  22. Girard J, Lafontan M. Impact of visceral adipose tissue on liver metabolism and insulin resistance. Part II: Visceral adipose tissue production and liver metabolism. Diabetes Metab 2008;34(5):439-445 View Article PubMed/NCBI
  23. Caan BJ, Cespedes Feliciano EM, Kroenke CH. The Importance of Body Composition in Explaining the Overweight Paradox in Cancer-Counterpoint. Cancer Res 2018;78(8):1906-1912 View Article PubMed/NCBI
  24. Saponaro C, Gaggini M, Carli F, Gastaldelli A. The Subtle Balance between Lipolysis and Lipogenesis: A Critical Point in Metabolic Homeostasis. Nutrients 2015;7(11):9453-9474 View Article PubMed/NCBI
  25. Johannsen DL, Tchoukalova Y, Tam CS, Covington JD, Xie W, Schwarz JM, et al. Effect of 8 weeks of overfeeding on ectopic fat deposition and insulin sensitivity: testing the “adipose tissue expandability” hypothesis. Diabetes Care 2014;37(10):2789-2797 View Article PubMed/NCBI
  26. Ishikawa K, Takahashi K, Bujo H, Hashimoto N, Yagui K, Saito Y. Subcutaneous fat modulates insulin sensitivity in mice by regulating TNF-alpha expression in visceral fat. Horm Metab Res 2006;38(10):631-638 View Article PubMed/NCBI
  27. Ibrahim MM. Subcutaneous and visceral adipose tissue: structural and functional differences. Obes Rev 2010;11(1):11-18 View Article PubMed/NCBI
  28. Bunchorntavakul C, Reddy KR. Review article: malnutrition/sarcopenia and frailty in patients with cirrhosis. Aliment Pharmacol Ther 2020;51(1):64-77 View Article PubMed/NCBI
  29. Minocci A, Savia G, Lucantoni R, Berselli ME, Tagliaferri M, Calò G, et al. Leptin plasma concentrations are dependent on body fat distribution in obese patients. Int J Obes Relat Metab Disord 2000;24(9):1139-1144 View Article PubMed/NCBI
  30. Stout MB, Justice JN, Nicklas BJ, Kirkland JL. Physiological Aging: Links Among Adipose Tissue Dysfunction, Diabetes, and Frailty. Physiology (Bethesda) 2017;32(1):9-19 View Article PubMed/NCBI
  31. Gioia S, Ridola L, Cristofaro L, Merli M, Faccioli J, Riggio O, et al. The improvement in body composition including subcutaneous and visceral fat reduces ammonia and hepatic encephalopathy after transjugular intrahepatic portosystemic shunt. Liver Int 2021;41(12):2965-2973 View Article PubMed/NCBI
  32. Qiu J, Thapaliya S, Runkana A, Yang Y, Tsien C, Mohan ML, et al. Hyperammonemia in cirrhosis induces transcriptional regulation of myostatin by an NF-κB-mediated mechanism. Proc Natl Acad Sci U S A 2013;110(45):18162-18167 View Article PubMed/NCBI
  33. Feng H, Wang X, Mao L, Yu Z, Cui B, Lin L, et al. Relationship between sarcopenia/myosteatosis and frailty in hospitalized patients with cirrhosis: a sex-stratified analysis. Ther Adv Chronic Dis 2021;12:20406223211026996 View Article PubMed/NCBI
  34. Chan GC, Than WH, Kwan BC, Lai KB, Chan RC, Ng JK, et al. Adipose expression of miR-130b and miR-17-5p with wasting, cardiovascular event and mortality in advanced chronic kidney disease patients. Nephrol Dial Transplant 2021:gfab287 View Article PubMed/NCBI
  35. Greenland S, Pearce N. Statistical foundations for model-based adjustments. Annu Rev Public Health 2015;36:89-108 View Article PubMed/NCBI

Copyright © 2022 Authors. This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial 4.0 License (CC BY-NC 4.0), permitting all non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

  • Journal of Clinical and Translational Hepatology
  • pISSN 2225-0719
  • eISSN 2310-8819

Download PDF

Metrics

Article accesses:
6982

Citation

Order Reprints
  • Copyright © 2022 JCTH. All Rights Reserved.
  • Published by Xia & He Publishing Inc.
  • Address: 14090 Southwest Freeway, Suite 300, Sugar Land, Texas 77478, USA
  • Email: service@xiahepublishing.com