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PNPLA3 rs738409 C>G Variant Influences the Association Between Visceral Fat and Significant Fibrosis in Biopsy-proven Nonalcoholic Fatty Liver Disease

  • Gang Li1,
  • Liang-Jie Tang1,
  • Pei-Wu Zhu2,
  • Ou-Yang Huang1,
  • Rafael S. Rios1,
  • Kenneth I. Zheng1,
  • Sui-Dan Chen3,
  • Hong-Lei Ma1,
  • Giovanni Targher4,
  • Christopher D. Byrne5,
  • Xiao-Yan Pan6 and
  • Ming-Hua Zheng1,7,8,* 
 Author information
Journal of Clinical and Translational Hepatology 2022;10(3):439-448

DOI: 10.14218/JCTH.2021.00286

Abstract

Background and Aims

Intra-abdominal visceral fat accumulation and patatin-like phospholipase domain containing 3 (PNPLA3) rs738409 G/C gene polymorphism confer a greater susceptibility to nonalcoholic fatty liver disease (NAFLD). We examined whether the relationship between visceral fat accumulation and liver disease severity may be influenced by PNPLA3 rs738409 polymorphism.

Methods

The variant of PNPLA3 rs738409 was genotyped within 523 Han individuals with biopsy-confirmed NAFLD. Visceral fat area (VFA) was measured by bioelectrical impedance. Significant liver fibrosis (SF), defined as stage F ≥2 on histology, was the outcome measure of interest.

Results

The distribution of PNPLA3 genotypes was CC: 27.5%, CG: 48.2%, and GG: 24.3%. Higher VFA was associated with greater risk of having SF (adjusted-odds ratio [OR]: 1.03; 95% confidence interval [CI]: 1.02–1.04, p<0.05), independent of potential confounders. Among subjects with the same VFA level, the risk of SF was greater among carriers of the rs738409 G genotype than among those who did not. Stratified analysis showed that PNPLA3 rs738409 significantly influenced the association between VFA and SF. VFA remained significantly associated with SF only among the rs738409 G-allele carriers (adjusted-OR: 1.05; 95% CI: 1.03–1.08 for the GG group; and adjusted-OR:1.03; 95% CI: 1.01–1.04 for the GC group). There was a significant interaction between VFA and PNPLA3 rs738409 genotype (Pinteraction=0.004).

Conclusions

PNPLA3 rs738409 G allele has a moderate effect on the association between VFA and risk of SF in adult individuals with biopsy-proven NAFLD. Existence of the PNPLA3 rs738409 G allele and VFA interact to increase risk of SF.

Keywords

Nonalcoholic fatty liver disease, Significant fibrosis, Visceral fat area, Single nucleotide polymorphism, Metabolic dysfunction-associated fatty liver disease

Introduction

Nonalcoholic fatty liver disease (NAFLD) is a major health problem that affects up to nearly 30% the world’s adults.1–3 NAFLD refers to a spectrum of progressive liver conditions, ranging from simple steatosis (NAFL) to steatohepatitis (NASH), with varying amounts of fibrosis, and cirrhosis.4,5 Convincing evidence shows that increased intra-abdominal visceral fat accumulation is a strong predictor for the development of significant fibrosis (SF) of the liver in NAFLD.6,7 Unlike subcutaneous adipose tissue, visceral adipose tissue is anatomically related to the liver through the portal vein, and so the liver is directly exposed to higher levels of free fatty acids as well as multiple adipokines/cytokines directly released from expanded visceral adipose tissue within the portal vein, thereby promoting the development of NAFLD. Therefore, visceral fat accumulation is a key target for therapeutic interventions of NAFLD and other metabolic disorders.8

It is known that NAFLD is a complex and heterogeneous disease.9,10 Studies show ∼20% of adults may have NAFLD, in the absence of overweight or obese status.11 The patatin-like phospholipase domain containing-3 (PNPLA3) rs738409 C>G variant (wild-type to mutant) is one of the strongest genetic variants that is related to a greater susceptibility to developing NASH and cirrhosis.12–14 Previous studies show that individuals with NAFLD, who carry the PNPLA3 rs738409 G allele, do not have insulin resistance or other features of metabolic syndrome.13,15,16 Preliminary studies also suggest that the PNPLA3 rs738409 GG genotype is associated with a lower risk of type 2 diabetes and cardiovascular disease;17 this finding supports the notion that the pathophysiology of NAFLD may be different among subjects carrying this genetic variant.

Thus, considering the possible differences in the pathophysiology of metabolic-related vs. PNPLA3-related NAFLD,18 we have tested whether PNPLA3 rs738409 may influence the effect of visceral fat area (VFA) on risk of having SF, and whether there is interaction between visceral fat content and PNPLA3 rs738409 polymorphisms, to affect liver disease severity, within a well-identified cohort of subjects with biopsy-confirmed NAFLD.

Methods

Research population

This is a cross-sectional analysis of our well-characterized Prospective Epidemic Research Specifically Of NASH (PERSONS) cohort of 1,015 ethnic Han adults with suspected NAFLD (mainly based on abnormal serum liver enzyme levels and/or evidence of hepatic steatosis on imaging techniques), who were admitted to the First Affiliated Hospital of Wenzhou Medical University (China) from July 18, 2017 to December 4, 2019, and who accepted the offer to undergo liver biopsy. As detailed in Figure 1, 492 individuals were excluded for the following reasons: (1) hepatocyte steatosis ≤5% on histology (n=80); (2) excessive alcohol intake (>140 g/week for men and >70 g/week for women, respectively) (n=112); (3) other secondary causes for hepatic steatosis (n=228); and (4) missing data for PNPLA-3 rs738409 genotype or Bioimpedance measurements using InBody 720 (n=72). As a consequence of these exclusion criteria, a total of 523 adult individuals with NAFLD were included in the final analysis.

Flowchart of the study’s design.
Fig. 1  Flowchart of the study’s design.

The study protocol was approved by the ethics committee of the First Affiliated Hospital of Wenzhou Medical University (protocol number #2016-246, 1 December 2016). All participants signed a written informed consent to participate in this study.

Laboratory and clinical data

Samples of venous blood were collected from all patients after at fast of least 8 h . Biochemical parameters were evaluated by employing an automated analyzer (Abbott AxSYM; Abbott Laboratories, Lake Bluff, IL, USA) centrally. Homeostasis model assessment of resistance of insulin (HOMA-IR) was calculated as follows: fasting insulin (mIU/L)×glucose (mmol/L)/22.5. Body mass index (BMI) was calculated by dividing weight in kilograms by height in meters-squared. Obese/overweight status was identified as BMI ≥25 kg/m2. Diagnostic criteria for hypertension and diabetes have been described in our previous studies.19 VFA was measured within 1 day of liver biopsy. A bioelectrical impedance analyzer (BIA) (InBody 720; Biospace, Seoul, South Korea) was used to measure VFA.20,21 The aforementioned laboratory and anthropometric variables were collected for all participants within 1 day of liver biopsy examinations.

Liver biopsy

Liver biopsy procedures have been described in detail previously.22 Briefly, NAFLD was defined as histological evidence of >5% of steatotic hepatocytes. Subjects with a NAFLD activity score (NAS) ≥5 (having a score of at least 1 for each histological component of hepatic steatosis, lobular inflammation and ballooning) were diagnosed as having definite NASH. Fibrosis stages were graded from 0 to 4, based on the Brunt’s histological criteria.23 SF of the liver was defined as histological stage F ≥2.24

Analysis of PNPLA3 rs738409 polymorphism

As described previously,25 the MassARRAY platform (Agena Bioscience, San Diego, CA, USA) was used to assess genotype of PNPLA3 rs738409. For this genotype, we used ∼20 ng of genomic DNA obtained from peripheral blood leukocytes. Locus-specific PCR as well as primers for detection were designed by the accompanying Assay Design Suite v3.1. Matrix assisted laser desorption ionization-time of flight mass spectrometry was used for detection of allele type, followed by amplification of DNA by multiplex PCR.

Statistical analysis

Continuous variables were expressed as mean±standard deviation or median with interquartile range, based on whether the distribution was normal or skewed, and then compared using the unpaired Student’s t-test or the Mann-Whitney test as appropriate. Categorical variables were expressed as proportions and compared using the chi-squared test or the Fisher’s exact test as appropriate. The chi-squared test was also used to test whether PNPLA3 rs738409 genotypes were in Hardy-Weinberg equilibrium. The association between VFA and presence of SF (defined as stage F ≥2 on liver histology) was tested by binary logistic regression analysis. In these regression models, the association was adjusted for known risk factors and potential confounders, such as sex, age, obese/overweight, hypertension, type 2 diabetes, HOMA-IR, and serum total cholesterol, triglyceride and albumin levels. Stratified and interaction analyses were also performed to examine the effect of PNPLA3 rs738409 polymorphism on the association between VFA and SF. All data were analyzed with the R statistical package (The R Foundation; http://www.r-project.org ; version 3.4.3) and Empower (R) (www.empowerstats.com ; X&Y Solutions, Inc., Boston, MA, USA).

Results

Baseline characteristics

A total of 523 Chinese individuals with biopsy-confirmed NAFLD were enrolled in this study. Subjects had a mean age of 42 years and 73.8% were men. In total, 102 (19.5%) of the subjects had SF (stage F ≥2 on liver histology). The prevalence rates of hypertension and type 2 diabetes were 24.1% and 25.8% respectively. The distribution of PNPLA3 rs738409 genotypes was as follows: 144 (27.5 %) had CC genotype; 252 (48.2%) had GC genotype; and 127 (24.3%) had GG genotype, respectively. This genotype distribution did not deviate from Hardy-Weinberg equilibrium. The frequency of the PNPLA3 rs738409 G variant was 0.48, similar to a previous study from China (0.45).26Table 1 summarizes the baseline characteristics of study participants, stratified by the PNPLA3 rs738409 polymorphism type. Carriers of the PNPLA3 GG genotype had a significantly higher prevalence of severe steatosis and definite NASH. The three groups were well comparable in terms of sex, age, adiposity measures (including VFA), HOMA-IR score and other metabolic parameters. Notably, as shown in Table 2, after stratifying by both PNPLA3 rs738409 polymorphism and SF, values of VFA were significantly greater only among carriers of the G allele, who also had SF.

Table 1

Baseline characteristics of study participants, stratified by PNPLA3 rs738409 polymorphism

All, n=523CC, n=144CG, n=252GG, n=127p
Demographics
  Age in years42.5±12.044.0±12.241.5±12.142.6±11.50.154
  Men381 (72.8)104 (72.2)191 (75.8)86 (67.7)0.244
Metabolic risk factors
  BMI in kg/m226.9±3.727.0±4.527.0±3.526.7±3.20.758
  Overweight/obesity360 (68.8)100 (69.4)174 (69.0%)86 (67.7)0.949
  VFA in cm2102.8±25.9103.9±25.2102.4±25.6102.3±27.50.838
  Type 2 diabetes135 (25.8)41 (28.5)62 (24.6)32 (25.2)0.687
  Hypertension126 (24.1)37 (25.7)54 (21.4)35 (27.6)0.365
Laboratory parameters
  AST in U/L34.0 (25.0–52.5)31.5 (24.0–48.0)34.0 (25.0–54.0)36.0 (26.0–57.0)0.116
  ALT in U/L51.0 (30.0–88.0)44.5 (28.8–73.8)52.0 (30.0–91.2)55.0 (30.5–89.5)0.109
  GGT in U/L52.0 (32.5–84.5)51.5 (30.8–81.2)55.0 (35.0–85.2)49.0 (31.5–83.0)0.491
Total bilirubin in µmol/L12.0 (10.0–16.0)12.0 (9.8–16.0)13.0 (10.0–16.0)12.0 (10.0–16.5)0.730
Albumin in g/L45.9±4.046.2±3.545.9±3.845.7±5.00.589
Glucose in mmol/L5.3 (4.9–6.3)5.4 (5.0–6.4)5.3 (4.9–6.2)5.3 (4.9–6.1)0.281
Insulin in mIU/L14.6 (9.6–21.3)15.2 (9.4–21.3)14.3 (10.0–21.2)14.9 (9.8–21.2)0.949
HOMA-IR3.6 (2.3–5.3)3.6 (2.3–5.5)3.4 (2.4–5.2)3.6 (2.2–5.5)0.879
Total cholesterol in mmol/L5.1 (4.4–5.9)5.1±1.25.2±1.15.2±1.20.516
Triglycerides in mmol/L1.9 (1.4–2.8)2.0 (1.4–3.2)1.9 (1.4–2.8)1.8 (1.4–2.5)0.179
HDL-cholesterol in mmol/L1.0 (0.9–1.1)1.0±0.21.0±0.21.0±0.30.163
LDL-cholesterol in mmol/L3.0 (2.4–3.6)2.9±0.93.1±0.93.1±1.00.055
Liver histology
  Steatosis grade<0.001
    1222 (42.4)83 (57.6)101 (40.1)38 (29.9)
    2193 (36.9)47 (32.6)97 (38.5)49 (38.6)
    3108 (20.7)14 (9.7)54 (21.4)40 (31.5)
  Hepatocyte ballooning0.922
    078 (14.9)22 (15.3)38 (15.1%)18 (14.2)
    1296 (56.6)85 (59.0)141 (56.0%)70 (55.1)
    2149 (28.5)37 (25.7)73 (29.0%)39 (30.7)
  Lobular inflammation0.148
    064 (12.2)25 (17.4)29 (11.5)10 (7.9)
    1306 (58.5)76 (52.8)153 (60.7)77 (60.6)
    2145 (27.7)41 (28.5)68 (27.0)36 (28.3)
    38 (1.5)2 (1.4)2 (0.8)4 (3.1)
  Definite NASH202 (38.6)47 (32.6)95 (37.7)60 (47.2)0.044
  SF (F ≥2 stage)102 (19.5)22 (15.3)49 (19.4)31 (24.4)0.167
Table 2

Baseline characteristics of study participants, stratified by both PNPLA3 rs738409 polymorphism and SF of the liver

CC
GC
GG
No SF, n=122SF, n=22pNo SF, n=203SF, n=49pNo SF, n=96SF, n=31p
Demographics
  Age in years43.6±12.445.6±11.20.48441.10±11.343.4±15.10.23241.6±10.145.8±14.90.076
  Men91 (74.6)13 (59.1)0.135161 (79.3)30 (61.2)0.00868 (70.8)18 (58.1)0.186
Metabolic risk factors
  BMI in kg/m226.9±4.127.9±6.50.34126.6±3.128.3±4.50.00226.2±2.928.4±3.3<0.001
  Overweight/obesity85 (69.7)15 (68.2)0.889139 (68.5)35 (71.4)0.68859 (61.5)27 (87.1)0.008
  VFA in cm2103.3±26.2107.0±19.30.53499.4±24.3114.7±27.7<0.00195.0±23.7125.0±26.2<0.001
  Type 2 diabetes35 (28.7)6 (27.3)0.89246 (22.7)16 (32.7)0.14519 (19.8)13 (41.9)0.014
  Hypertension34 (27.9)3 (13.6)0.16041 (20.2)13 (26.5)0.33222 (22.9)13 (41.9)0.039
Laboratory parameters
  AST in U/L31.0 (23.2–43.0)52.0 (35.0–75.8)<0.00132.0 (24.0–49.0)54.0 (32.0–76.0)<0.00134.0 (26.0–53.8)50.0 (29.0–65.0)0.040
  ALT in U/L39.0 (27.0–67.5)74.5 (51.2–98.5)<0.00148.0 (28.0–86.5)72.0 (43.0–129.0)0.00653.5 (30.8–87.2)72.0 (32.5–120.0)0.185
  GGT in U/L50.0 (29.2–78.0)68.5 (37.2–118.2)0.05853.0 (32.5–83.0)60.0 (42.0–99.0)0.07447.5 (30.8–74.5)66.0 (32.0–116.0)0.126
  Total bilirubin in µmol/L12.0 (10.0–15.0)14.0 (9.2–17.0)0.56613.0 (10.0–16.0)12.0 (9.0–15.0)0.13512.0 (10.0–16.0)14.0 (11.0–18.0)0.343
  Albumin in g/L46.0±3.647.0±2.80.21446.1±3.745.3±4.10.18545.9±4.845.0±5.50.383
  Glucose in mmol/L5.5 (5.0–6.6)5.3 (4.8–6.0)0.3385.2 (4.8–6.0)5.6 (4.9–7.9)0.0125.2 (4.9–5.8)5.7 (5.0–7.2)0.042
  Insulin in mIU/L15.4 (9.2–21.3)13.9 (10.0–21.6)0.98713.0 (9.2–18.4)21.4 (15.2–32.6)<0.00114.0 (9.8–19.7)16.9 (10.1–23.2)0.268
  HOMA-IR3.7 (2.3–5.4)3.4 (2.2–6.3)0.7693.2 (2.3–4.5)5.3 (4.1–11.1)<0.0013.3 (2.2–5.0)4.3 (2.9–7.4)0.060
  Total cholesterol in mmol/L5.1±1.24.6±1.40.0575.1 ±1.05.4±1.30.0745.2±1.25.4±1.40.347
  Triglycerides in mmol/L2.1 (1.5–3.2)1.7 (1.2–2.4)0.0721.9 (1.4–2.9)2.0 (1.3–2.8)0.9651.8 (1.4–2.4)1.8 (1.4–2.5)0.982
  HDL-cholesterol in mmol/L1.0±0.21.0±0.20.4951.0±0.21.0±0.30.6751.0±0.21.1±0.30.517
  LDL-cholesterol in mmol/L2.9±0.92.6±1.10.1283.0±0.83.2±1.10.2453.1±0.93.2±1.10.530
Liver histology
  Steatosis grade0.003<0.0010.021
    176 (62.3)7 (31.8)87 (42.9)14 (28.6)34 (35.4)4 (12.9)
    238 (31.1)9 (40.9)83 (40.9)14 (28.6)37 (38.5)12 (38.7)
    38 (6.6)6 (27.3)33 (16.3)21 (42.9)25 (26.0)15 (48.4)
  Hepatocyte ballooning0.0440.002<0.001
    021 (17.2)1 (4.5)34 (16.7)4 (8.2)17 (17.7)1 (3.2)
    174 (60.7)11 (50.0)120 (59.1)21 (42.9)60 (62.5)10 (32.3)
    227 (22.1)10 (45.5)49 (24.1)24 (49.0)19 (19.8)20 (64.5)
  Lobular inflammation0.002<0.001<0.001
    024 (19.7)1 (4.5)24 (11.8)5 (10.2)10 (10.4)0 (0.0)
    169 (56.6)7 (31.8)135 (66.5)18 (36.7)69 (71.9)8 (25.8)
    228 (23.0)13 (59.1)43 (21.2)25 (51.0)16 (16.7)20 (64.5)
    31 (0.8)1 (4.5)1 (0.5)1 (2.0)1 (1.0)3 (9.7)
  Definite NASH31 (25.4)16 (72.7)<0.00165 (32.0)30 (61.2)<0.00134 (35.4)26 (83.9)<0.001

PNPLA3 rs738409 polymorphism influences the association between VFA and SF

The smoothing spline curve, obtained by a generalized additive model, showed a linear association between VFA and risk of having SF. As shown in Figure 2, as VFA increased, the likelihood of SF also progressively increased; however, it is worth noting that carriers of the PNPLA3 CC genotype had a lower risk of SF than those carrying the PNPLA3 G allele. Among individuals with the same level of VFA, the risk of SF was higher among carriers of the rs738409 G genotype than among those who did not. The smoothing spline curve clearly suggested that the PNPLA3 rs7387409 G allele increased the probability of SF with increasing levels of VFA. A threshold effect analysis was also performed to examine if the slight fall in the probability of SF in the CC group with increasing levels of VFA was statistically significant. Although there are just 11 subjects in the descending section of the curve (Figure 2), we found that the fall in the probability of SF in the CC group with increasing levels of VFA was not statistically significant.

Association between VFA and SF of the liver in biopsy-proven NAFLD, stratified by <italic>PNPLA3</italic> rs738409 polymorphism.
Fig. 2  Association between VFA and SF of the liver in biopsy-proven NAFLD, stratified by PNPLA3 rs738409 polymorphism.

VFA, visceral fat area; SF, significant fibrosis; NAFLD, nonalcoholic fatty liver disease.

Association between VFA and SF

As demonstrated in Figure 3, within a logistic regression model with the presence or absence of SF as the dependent variable, there was a significant positive association between VFA (included as a continuous variable) and risk of having SF, even after adjustment for sex, age, obese/overweight, hypertension, type 2 diabetes, HOMA-IR, and serum total cholesterol, triglyceride and albumin levels (adjusted-odds ratio [OR]: 1.03, 95% confidence interval [CI]: 1.02–1.04).

Associations between VFA and SF of the liver in different subgroups of individuals.
Fig. 3  Associations between VFA and SF of the liver in different subgroups of individuals.

All data are adjusted for age, sex, type 2 diabetes, hypertension, BMI, levels of serum total cholesterol, triglycerides and albumin, and HOMA-IR (with the exception of the specific variable used for stratifying each patient subgroup). HOMA-IR, homeostatic model assessment for insulin resistance; VFA, visceral fat area; SF, significant fibrosis; OR, odds ratio; CI, confidence interval; BMI, body mass index.

Association between VFA and SF in different subgroups

We examined the association between VFA and risk of having SF in individuals who were stratified either by different PNPLA3 genotypes (additive or dominant models) or by other established risk factors for SF (i.e. sex, age, BMI, hypertension, diabetes and HOMA-IR). As shown in Figure 3, the significant association between VFA and SF persisted in the PNPLA3 rs738409 GG and GC subgroups even after adjustment for potential confounders (adjusted-OR: 1.03, 95% CI: 1.01–1.04 in the GC group; adjusted-OR: 1.05, 95% CI: 1.03–1.08 in the GG group) but not in the CC group (adjusted-OR: 1.01, 95% CI: 0.99–1.03). It should be noted, there was a significant interaction of PNPLA3 rs738409 genotypes on the association between VFA and risk of SF (Pinteraction=0.004). When this association was assessed in a dominant genetic model, the association between VFA and SF remained statistically significant after controlling for potential confounding variables in the GC+GG group (adjusted-OR: 1.03, 95% CI: 1.02–1.05) but not in the CC group (adjusted-OR: 1.01, 95% CI: 0.99–1.03). In addition, there was a significant association between VFA and SF when we stratified subjects into two groups, i.e. the GG vs. GC+CC subgroups. Interestingly, there was an interaction between PNPLA3 rs738409 GG and VFA (Pinteraction=0.004). These results suggested that the PNPLA3 rs738409 G allele and VFA interacted to moderately increase the risk of having SF.

Stratified analyses according to sex

We examined the association between VFA with SF, stratified by a PNPLA3 rs738409 dominant model, in men and in women separately. As described in Table 3, in the unadjusted models, VFA was associated with an increased risk of having SF in both sexes. After adjustment for age, overweight/obese, type 2 diabetes and hypertension, levels of serum total cholesterol, triglycerides and albumin, and HOMA-IR (adjusted model 2), the association between VFA and SF remained statistically significant for both men and women (adjusted-OR: 1.03, 95% CI: 1.01–1.04 for men; adjusted-OR: 1.02, 95% CI: 1.0–1.05 for women). However, as also shown in Table 3, after further stratification by PNPLA3 rs738409 genotypes (CC vs. GC+GG groups), the significant association between VFA and SF disappeared among carriers of the rs738409 CC genotype (adjusted-OR: 1.01 95% CI: 0.99–1.04 for men; adjusted-OR: 0.98, 95% CI: 0.95–1.02 for women). In contrast, the association between VFA and SF remained significant among carriers of the rs738409 G allele, even after adjustment for potential confounders in both sexes (adjusted-OR: 1.03, 95% CI: 1.02–1.05 for men; adjusted-OR: 1.04, 95% CI: 1.01–1.07 for women).

Table 3

Associations between VFA and SF of the liver in participants with different PNPLA3 genotypes, stratified by sex

All
CC
GC+GG
OR (95% CI)pOR (95% CI)pOR (95% CI)p
Menn=381n=104n=277
  Unadjusted model1.03 (1.02, 1.04)<0.0011.01 (0.99, 1.04)0.2231.03 (1.02, 1.04)<0.001
  Adjusted model 11.03 (1.02, 1.04)<0.0011.01 (0.99, 1.04)0.2421.03 (1.02, 1.04)<0.001
  Adjusted model 21.03 (1.01, 1.04)<0.0011.01 (0.99, 1.04)0.3251.03 (1.02, 1.05)<0.001
Womenn=142n=40n=102
  Unadjusted model1.02 (1.01, 1.04)0.0020.99 (0.96, 1.02)0.6021.04 (1.02, 1.06)<0.001
  Adjusted model 11.03 (1.01, 1.04)0.0020.98 (0.95, 1.01)0.3121.04 (1.01, 1.06)0.002
  Adjusted model 21.03 (1.01, 1.04)0.0040.98 (0.95, 1.02)0.3801.04 (1.01, 1.07)0.003

Discussion

In this large cross-sectional study of ethnic Han individuals with biopsy-confirmed NAFLD, we found that intra-abdominal VFA was significantly associated with greater risk of having SF, on liver histology. Notably, this significant association persisted even after adjusting for potential confounding variables, such as sex, age, obese/overweight status, hypertension, diabetes, HOMA-IR, and levels of plasma lipids and albumin. Furthermore, after further stratification by PNPLA3 rs738409 polymorphism type, the association between VFA and SF remained significant only among carriers of the PNPLA3 rs738409 G allele but not among those carrying the CC genotype, thereby suggesting that the PNPLA3 rs738409 G allele and VFA can interact to moderately increase the risk of having SF. Furthermore, with the same level of VFA, the risk of having SF was significantly lower among carriers of the rs738409 CC genotype than among those carrying the rs738409 G allele.

In the last decade, the close inter-relationship between intra-abdominal VFA and SF in people with NAFLD has drawn increasing attention.6,7 Unlike subcutaneous fat in the abdomen, intra-abdominal visceral fat accumulation (being connected directly to the liver via the portal vein) is closely related to the development and progression of NAFLD.8,27 In our study, we found that VFA was associated with greater risk of SF, independent of pre-existing diabetes or other metabolic syndrome features, especially among carriers of the PNPLA3 CG or GG genotypes. The precise mechanisms underpinning the association between increased VFA and greater risk of SF are not fully understood. However, in accordance with the so-called “portal theory”, it has been proposed that expanded and dysfunctional visceral adipose tissue may release higher amounts of free fatty acids as well as multiple adipokines and pro-inflammatory cytokines into the liver via portal vein, thus promoting the development and progressions of NAFLD.28–31

We found that compared to NAFLD subjects carrying the PNPLA3 rs738409 CC genotype, VFA was independently related to a greater risk of having SF only among those carrying the PNPLA3 rs738409 G-allele. It is known that the PNPLA3 rs738409 C>G variant (wild-type to mutant), leading to an isoleucine to methionine substitution at position 148 of the protein (I148M), is strongly associated with an increased risk of NAFLD progression. As a liver lipase with triglyceride hydrolase enzyme activity, this genetic variant leads to loss of function, thereby reducing the remodeling of polyunsaturated fatty acids and monounsaturated fatty acids, leading to their retention within the liver.32 Therefore, it is conceivable that the combination of increased VFA and PNPLA3 rs738409 C>G variant may promote the progression of NAFLD from simple steatosis to NASH and cirrhosis.

We believe that the presence of an interaction effect of PNPLA3 rs738409 G allele and VFA to moderately increase risk of SF, and the observed dissociation of VFA and SF among the carriers of the PNPLA3 rs738409 CC genotype are two interesting findings of our study. However, the specific reasons for these results are not entirely known. In particular, the effect as well as role of the PNPLA3 rs738409 G variant within adipose tissue are poorly understood. Recently, it has been shown that PNPLA3 mRNA was expressed abundantly within the liver and clearly detectable within the subcutaneous adipose tissue of individuals with severe obesity.33 Other investigators confirmed that PNPLA3 protein was found not just within the liver but also within adipose tissue. It has been reported that the PNPLA3 rs738409 C>G variant may alter lipid composition of adipose tissue in a similar way to that observed in the liver.34,35 An experimental study also suggested that overexpression of the PNPLA3 rs738409 G variant lead to greater VFA and insulin resistance compared to the wild-type protein in mice.36 Although it remains uncertain how the PNPLA3 rs738409 polymorphism may interact with VFA to increase hepatic fibrogenesis, our results support the existence of a cross-talk between VFA and PNPLA3 rs738409 polymorphism in risk of NAFLD progression.34

In our study, we enrolled patients with biopsy-proven NAFLD who also had measurement of VFA and PNPLA3 single nucleotide polymorphism status. There was a significant trend for patients with more SF (stage 2 or more) to have increased VFA or be a carrier for the G allele. Consequently, we thought it would also be a valuable point if those with negative biopsies were analyzed to understand if the VFA was significantly different in this population as well as the status of PNPLA3. Unfortunately, we did not enroll such patients in our cohort. Further studies are required to address and resolve this point in the future.

There are several essential limitations within our investigation. First, the mutation rates for PNPLA3 rs738409 polymorphism vary among different ethnic populations, with the highest rates being in Asian and American individuals, intermediate rates in northern European Whites, and lowest rates in Blacks. For example, according to a previous study, the risk allele mutation for PNPLA3 was in 49% among Hispanics, followed by non-Hispanic Caucasians (23%) and African Americans (17%).16,37 As the participants in our study were all ethnic Han Chinese individuals, the findings of our study might not be generalizable to other ethnic groups.38–40 Second, the cross-sectional design of our study does not allow any firm conclusions about causality. However, since PNPLA3 rs738409 polymorphism is inherited, reverse causation does not apply. Third, VFA was not measured with computed tomography (CT) scan. However, VFA estimated by BIA has a good correlation with VFA measured with CT scaning.41 Finally, we did not have detailed information on physical activity levels and diet regimens of these participants. The beneficial effect of different exercise regimes, without caloric restriction, on VFA is well known for overweight or obese individuals.42

In conclusion, our research showed that VFA is associated with greater risk of having SF, independent of potential confounding factors, especially among carriers of the PNPLA3 rs738409 G-allele, and there is an interaction of PNPLA3 rs738409 polymorphism and VFA to increase risk of SF in Chinese individuals with biopsy-proven NAFLD. Our gene-visceral fat interaction study suggests that the PNPLA3 rs738409 G-allele may moderately modulate the adverse effects of VFA on risk of SF in NAFLD. However, further research is needed to further corroborate these findings in other different cohorts of NAFLD patients.

Abbreviations

BMI: 

body mass index

CI: 

confidence interval

CT: 

computed tomography

HOMA-IR: 

homeostatic model assessment for insulin resistance

NAFLD: 

nonalcoholic fatty liver disease

NAS: 

NAFLD activity score

NASH: 

nonalcoholic steatohepatitis

OR: 

odds ratio

PERSONS: 

Prospective Epidemic Research Specifically Of NASH

PNPLA3: 

patatin-like phospholipase domain-containing protein 3

SF: 

significant fibrosis

VFA: 

visceral fat area

Declarations

Ethics approval

The study was approved by the local ethics committee of our hospital.

Patient consent

Written informed consent was obtained from all study participants. Personal information and identifying record data were omitted and de-identified prior to analysis.

Data sharing statement

The data underlying the results of this study are available upon request because they contain potentially sensitive information. Interested researchers can contact the corresponding author for data access requests via email (zhengmh@wmu.edu.cn). This work is a part of the PERSONS study.

Funding

This work was supported by grants from the National Natural Science Foundation of China (82070588), High Level Creative Talents from Department of Public Health in Zhejiang Province (S2032102600032), and the Project of New Century 551 Talent Nurturing in Wenzhou. GT was supported in part by grants from the University School of Medicine of Verona, Verona, Italy. CDB was supported in part by the Southampton NIHR Biomedical Research Centre (IS-BRC-20004), UK.

Conflict of interest

MHZ has been an associate editor of Journal of Clinical and Translational Hepatology since 2013.Other authors have no conflict of interests related to this publication.

Authors’ contributions

Study concept and design (GL, MHZ), acquisition of data (GL, HLM, LJT, OYH, XYP, PWZ, RSR, KIZ), pathology analysis (SDC), drafting of the manuscript (GL, MHZ), critical revision of the manuscript (GT, CDB), statistical analysis (GL), study supervision (MHZ). All authors contributed to the manuscript for important intellectual content and approved the submission.

References

  1. Targher G, Day C, Bonora E. Risk of cardiovascular disease in patients with nonalcoholic fatty liver disease. N Engl J Med 2010;363(14):1341-1350 View Article PubMed/NCBI
  2. Zheng K, Eslam M, George J, Zheng M. When a new definition overhauls perceptions of MAFLD related cirrhosis care. Hepatobiliary Surg Nutr 2020;9(6):801-804 View Article PubMed/NCBI
  3. Byrne C, Targher G. NAFLD: a multisystem disease. J Hepatol 2015;62:S47-64 View Article PubMed/NCBI
  4. Satapathy S, Sanyal A. Epidemiology and Natural History of Nonalcoholic Fatty Liver Disease. Semin Liver Dis 2015;35(3):221-235 View Article PubMed/NCBI
  5. Pais R, Maurel T. Natural History of NAFLD. J Clin Med 2021;10(6):1161 View Article PubMed/NCBI
  6. Nobarani S, Alaei-Shahmiri F, Aghili R, Malek M, Poustchi H, Lahouti M, et al. Visceral Adipose Tissue and Non-alcoholic Fatty Liver Disease in Patients with Type 2 Diabetes. Dig Dis Sci 2021 View Article PubMed/NCBI
  7. Hsieh Y, Joo S, Koo B, Lin H, Kim W. Muscle alterations are independently associated with significant fibrosis in patients with nonalcoholic fatty liver disease. Liver Int 2021;41(3):494-504 View Article PubMed/NCBI
  8. van der Poorten D, Milner K, Hui J, Hodge A, Trenell M, Kench J, et al. Visceral fat: a key mediator of steatohepatitis in metabolic liver disease. Hepatology 2008;48(2):449-457 View Article PubMed/NCBI
  9. Younossi Z. Non-alcoholic fatty liver disease - A global public health perspective. J Hepatol 2019;70(3):531-544 View Article PubMed/NCBI
  10. Cohen J, Horton J, Hobbs H. Human fatty liver disease: old questions and new insights. Science 2011;332(6037):1519-1523 View Article PubMed/NCBI
  11. Fan J, Kim S, Wong V. New trends on obesity and NAFLD in Asia. J Hepatol 2017;67(4):862-873 View Article PubMed/NCBI
  12. Rotman Y, Koh C, Zmuda J, Kleiner D, Liang T. The association of genetic variability in patatin-like phospholipase domain-containing protein 3 (PNPLA3) with histological severity of nonalcoholic fatty liver disease. Hepatology 2010;52(3):894-903 View Article PubMed/NCBI
  13. Sookoian S, Castaño G, Burgueño A, Gianotti T, Rosselli M, Pirola C. A nonsynonymous gene variant in the adiponutrin gene is associated with nonalcoholic fatty liver disease severity. J Lipid Res 2009;50(10):2111-2116 View Article PubMed/NCBI
  14. Trépo E, Romeo S, Zucman-Rossi J, Nahon P. PNPLA3 gene in liver diseases. J Hepatol 2016;65(2):399-412 View Article PubMed/NCBI
  15. Lallukka S, Sevastianova K, Perttilä J, Hakkarainen A, Orho-Melander M, Lundbom N, et al. Adipose tissue is inflamed in NAFLD due to obesity but not in NAFLD due to genetic variation in PNPLA3. Diabetologia 2013;56(4):886-892 View Article PubMed/NCBI
  16. Romeo S, Kozlitina J, Xing C, Pertsemlidis A, Cox D, Pennacchio L, et al. Genetic variation in PNPLA3 confers susceptibility to nonalcoholic fatty liver disease. Nat Genet 2008;40(12):1461-1465 View Article PubMed/NCBI
  17. Meffert P, Repp K, Völzke H, Weiss F, Homuth G, Kühn J, et al. The PNPLA3 SNP rs738409:G allele is associated with increased liver disease-associated mortality but reduced overall mortality in a population-based cohort. J Hepatol 2018;68(4):858-860 View Article PubMed/NCBI
  18. Mancina R, Spagnuolo R. Cross talk between liver and adipose tissue: A new role for PNPLA3?. Liver Int 2020;40(9):2074-2075 View Article PubMed/NCBI
  19. Li G, Rios R, Wang X, Yu Y, Zheng K, Huang O, et al. Sex influences the association between appendicular skeletal muscle mass to visceral fat area ratio and non-alcoholic steatohepatitis in patients with biopsy-proven non-alcoholic fatty liver disease. Br J Nutr 2021:1-8 View Article PubMed/NCBI
  20. Hernández-Conde M, Llop E, Carrillo C, Tormo B, Abad J, Rodriguez L, et al. Estimation of visceral fat is useful for the diagnosis of significant fibrosis in patients with non-alcoholic fatty liver disease. World J Gastroenterol 2020;26(42):6658-6668 View Article PubMed/NCBI
  21. Shi Y, Chen X, Qiu H, Jiang W, Zhang M, Huang Y, et al. Visceral fat area to appendicular muscle mass ratio as a predictor for nonalcoholic fatty liver disease independent of obesity. Scand J Gastroenterol 2021;56(3):312-320 View Article PubMed/NCBI
  22. Zhou Y, Ye F, Li Y, Pan X, Chen Y, Wu X, et al. Individualized risk prediction of significant fibrosis in non-alcoholic fatty liver disease using a novel nomogram. United European Gastroenterol J 2019;7(8):1124-1134 View Article PubMed/NCBI
  23. Brunt E, Janney C, Di Bisceglie A, Neuschwander-Tetri B, Bacon B. Nonalcoholic steatohepatitis: a proposal for grading and staging the histological lesions. Am J Gastroenterol 1999;94(9):2467-2474 View Article PubMed/NCBI
  24. Newsome P, Sasso M, Deeks J, Paredes A, Boursier J, Chan W, et al. FibroScan-AST (FAST) score for the non-invasive identification of patients with non-alcoholic steatohepatitis with significant activity and fibrosis: a prospective derivation and global validation study. Lancet Gastroenterol Hepatol 2020;5(4):362-373 View Article PubMed/NCBI
  25. Sun D, Zheng K, Xu G, Ma H, Zhang H, Pan X, et al. PNPLA3 rs738409 is associated with renal glomerular and tubular injury in NAFLD patients with persistently normal ALT levels. Liver Int 2020;40(1):107-119 View Article PubMed/NCBI
  26. Li Y, Xing C, Cohen J, Hobbs H. Genetic variant in PNPLA3 is associated with nonalcoholic fatty liver disease in China. Hepatology 2012;55(1):327-328 View Article PubMed/NCBI
  27. Tiniakos D, Vos M, Brunt E. Nonalcoholic fatty liver disease: pathology and pathogenesis. Annu Rev Pathol 2010;5:145-171 View Article PubMed/NCBI
  28. Kuk J, Katzmarzyk P, Nichaman M, Church T, Blair S, Ross R. Visceral fat is an independent predictor of all-cause mortality in men. Obesity 2006;14(2):336-341 View Article PubMed/NCBI
  29. Freedland E. Role of a critical visceral adipose tissue threshold (CVATT) in metabolic syndrome: implications for controlling dietary carbohydrates: a review. Nutr Metab (Lond) 2004;1(1):12 View Article PubMed/NCBI
  30. Yoo H, Park M, Lee C, Yang S, Kim T, Lim K, et al. Cutoff points of abdominal obesity indices in screening for non-alcoholic fatty liver disease in Asians. Liver Int 2010;30(8):1189-1196 View Article PubMed/NCBI
  31. Tarantino G, Citro V, Capone D. Nonalcoholic Fatty Liver Disease: A Challenge from Mechanisms to Therapy. J Clin Med 2019;9(1):15 View Article PubMed/NCBI
  32. Huang Y, Cohen J, Hobbs H. Expression and characterization of a PNPLA3 protein isoform (I148M) associated with nonalcoholic fatty liver disease. J Biol Chem 2011;286(43):37085-37093 View Article PubMed/NCBI
  33. Wieser V, Adolph T, Enrich B, Moser P, Moschen A, Tilg H. Weight loss induced by bariatric surgery restores adipose tissue PNPLA3 expression. Liver Int 2017;37(2):299-306 View Article PubMed/NCBI
  34. Qadri S, Lallukka-Brück S, Luukkonen P, Zhou Y, Gastaldelli A, Orho-Melander M, et al. The PNPLA3-I148M variant increases polyunsaturated triglycerides in human adipose tissue. Liver Int 2020;40(9):2128-2138 View Article PubMed/NCBI
  35. Luukkonen P, Zhou Y, Sädevirta S, Leivonen M, Arola J, Orešič M, et al. Hepatic ceramides dissociate steatosis and insulin resistance in patients with non-alcoholic fatty liver disease. J Hepatol 2016;64(5):1167-1175 View Article PubMed/NCBI
  36. Liu Z, Zhang Y, Graham S, Wang X, Cai D, Huang M, et al. Causal relationships between NAFLD, T2D and obesity have implications for disease subphenotyping. J Hepatol 2020;73(2):263-276 View Article PubMed/NCBI
  37. Chen L, Xin Y, Geng N, Jiang M, Zhang D, Xuan S. PNPLA3 I148M variant in nonalcoholic fatty liver disease: demographic and ethnic characteristics and the role of the variant in nonalcoholic fatty liver fibrosis. World J Gastroenterol 2015;21(3):794-802 View Article PubMed/NCBI
  38. Diehl A, Day C. Cause, Pathogenesis, and Treatment of Nonalcoholic Steatohepatitis. N Engl J Med 2017;377(21):2063-2072 View Article PubMed/NCBI
  39. Sayiner M, Koenig A, Henry L, Younossi Z. Epidemiology of Nonalcoholic Fatty Liver Disease and Nonalcoholic Steatohepatitis in the United States and the Rest of the World. Clin Liver Dis 2016;20(2):205-214 View Article PubMed/NCBI
  40. Winkler T, Günther F, Höllerer S, Zimmermann M, Loos R, Kutalik Z, et al. A joint view on genetic variants for adiposity differentiates subtypes with distinct metabolic implications. Nat Commun 2018;9(1):1946 View Article PubMed/NCBI
  41. Ogawa H, Fujitani K, Tsujinaka T, Imanishi K, Shirakata H, Kantani A, et al. InBody 720 as a new method of evaluating visceral obesity. Hepatogastroenterology 2011;58(105):42-44 View Article PubMed/NCBI
  42. Vissers D, Hens W, Taeymans J, Baeyens J, Poortmans J, Van Gaal L. The effect of exercise on visceral adipose tissue in overweight adults: a systematic review and meta-analysis. PloS one 2013;8(2):e56415 View Article PubMed/NCBI
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