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. 2015 Mar 20;5:9284. doi: 10.1038/srep09284

Association Between Patatin-Like Phospholipase Domain Containing 3 Gene (PNPLA3) Polymorphisms and Nonalcoholic Fatty Liver Disease: A HuGE Review and Meta-Analysis

Renfan Xu 1, Anyu Tao 1, Shasha Zhang 2, Youbin Deng 1, Guangzhi Chen 2,a
PMCID: PMC4366950  PMID: 25791171

Abstract

We conducted a meta-analysis to assess the association between patatin-like phospholipase domain-containing 3 (PNPLA3) rs738409 polymorphism and nonalcoholic fatty liver disease (NAFLD) and its subtypes simple steatosis(SS) and nonalcoholic steatohepatitis (NASH). The study-specific odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using fixed-effects or random-effects models, with assessment for heterogeneity and publication bias. Twenty-three case-control studies involving 6071 NAFLD patients and 10366 controls were identified. The combined results showed a significant association between NAFLD risk and the rs738409 polymorphism in all genetic models (additive model: OR = 3.41, 95% CI = 2.57–4.52; P < 0.00001). In addition, evidence indicated that the rs738409 polymorphism was significantly associated with NASH in all genetic models (additive model: OR = 4.44, 95% CI = 3.39–5.82; P < 0.00001). The subgroup and sensitivity analyses showed that these changes were not influenced by the ethnicities and ages of subjects or by the source of controls. The rs738409 polymorphism was only significantly associated with risk of simple steatosis in the allele contrast and had no effect in the other genetic models. These findings suggest that the rs738409 polymorphism in PNPLA3 gene confers high cross-ethnicity risk for NAFLD and NASH development.

Nonalcoholic fatty liver disease (NAFLD) is the most common cause of liver disease in western countries, affecting up to 20–35% of the general population1, and has emerged as a major public health issue worldwide2,3. NAFLD has a broad spectrum of manifestations and can be histologically subdivided into simple steatosis and non-alcoholic steatohepatitis (NASH), which include steatosis, lobular inflammation and hepatocyte ballooning with or without fibrosis4. Although simple steatosis is generally considered to have a benign hepatological prognosis, NASH much more frequently progresses to fibrosis, cirrhosis and hepatocellular carcinoma in later years5,6 and will be the leading cause of liver transplantation in the United States by 20207. The precise mechanism responsible for the development and progression of NAFLD has not been elucidated. Some NAFLD patients will progress into NASH with cirrhosis, whereas others do not develop beyond simple steatosis. Currently, there is increasing evidence that genetic8,9,10 as well as environmental factors11 play important roles in the progression of NAFLD.

The human patatin-like phospholipase-3 (PNPLA3) gene is localized on human chromosome 22. The PNPLA3 protein, which is also known as adiponutrin, is expressed in both adipocytes and hepatocytes12. PNPLA3 exhibits lipase activity against triglycerides and acylglycerol transacetylase activity, and its expression is highly responsive in energy mobilization and the storage of lipid droplets13. The PNPLA3 gene is one of the potential candidate genes currently related to NAFLD susceptibility. In 1998, Romeo et al. noted that a single nucleotide polymorphism in residue 148 (I148 M, rs738409), which exhibits a C-to-G transition resulting in an amino acid substitution of isoleucine to methionine, was a strong genetic determinant of NAFLD10. Consistent with this result, some following studies also demonstrated an association between the rs738409 polymorphism and NAFLD risk14,15,16. However, it is unclear whether this polymorphism is associated with simple steatosis only or also associated with NASH. Further studies have also attempted to analyze the association between the rs738409 polymorphism and histological parameters of NAFLD17,18,19, but the results are not consistent, partially because only few studies with a limited number of subjects analyzed the association between the rs738409 polymorphism and NASH or simple steatosis.

There is no approved therapy for NAFLD, and the diagnosis of NASH can only be proven by liver biopsy. In addition, it is important to establish whether the associations differ between different subgroups of NAFLD. To clarify the association between the rs738409 polymorphism and risk of NAFLD, we conducted a systematic review and meta-analysis of the available prospective studies with the specific aims of analyzing NAFLD subgroups, including simple steatosis or NASH, to clarify whether the association differed by histological parameters.

Methods

Search strategy

We conducted an electronic search of the PubMed, EMBASE and Web of Science databases from their inception until December 2014 to identify the association between the rs738409 polymorphism and NAFLD risk using the following search terms: PNPLA3 and (polymorphism or variant or variation) and (NAFLD or NASH or (non-alcoholic fatty liver disease) or (fatty liver) or steatohepatitis). Additional studies not captured by our database search were identified by surveying the references of the originally identified reviews and research reports and by using the MEDLINE option “Related Articles”. The search was confined to human studies without country restrictions. In addition, the publication language was restricted to English.

Inclusion and exclusion criteria

Potentially relevant studies were selected based on the following inclusion criteria: (1) studies concerning the association between the PNPLA3 rs738409 polymorphism and risk of NAFLD; (2) case-control studies based on unrelated individuals; (3) studies in which the diagnosis of NAFLD was clear; (4) studies that provide the number of NAFLD cases and controls and the frequency of the rs738409 genotypes; and (5) studies published in English. The major reasons for study exclusion were the following: (1) case-only study or overlapping data; (2) studies with a sample size less than one hundred; (3) studies with abstracts only and reports published as comment and review papers; and (4) studies with secondary causes of steatosis, including alcohol abuse, the use of drugs, surgical procedures and hepatitis B and hepatitis C virus infection.

Data extraction

Two investigators independently selected the trials and extracted the data, and disagreements or uncertainties were resolved by consensus. The following data were extracted: first author, publication year, country of origin, ethnicity of studied population, sex ratio, mean age, diagnostic criteria for NAFLD, number of individuals in the case and control groups, frequency of PNPLA3 genotypes in the cases and controls; and consistency with the Hardy-Weinberg equilibrium(HWEs).

Study quality assessment

The quality of the studies was assessed independently by two investigators according to the quality assessment scores developed from the genetic association studies conducted by Thakkinstian et al. The total scores ranged from 0 (worst) to 13 (best)20. The criteria of the quality assessment used to analyze the studies in this meta-analysis are available in Table S1.

Statistical analysis

The strength of the association between the PNPLA3 polymorphism and NAFLD risk was assessed by the odds ratios (ORs) and 95% confidence interval (CI). The Chi-square test was used to assess the Hardy-Weinberg equilibrium (HWE) in order to analyze the genotype distribution in the control groups. Meta-analyses were performed for four genotype contrasts per outcome: allele contrast (G versus C), dominant model (GG+CG versus CC), recessive model (GG versus CG+CC), and additive model (GG versus CC)21,22. The Cochrane Q statistic and the inconsistency index (I2) were used to calculate the heterogeneity among the studies, and a P value < 0.10 or I2 > 50% was considered to be significant23. If heterogeneity existed among the studies, the random-effect model (the Dersimonian and Laird method) was used to calculate the pooled OR. Otherwise, a fixed-effect model (the Mantel-Haenszel method) was used for outcomes without obvious heterogeneity24. Sensitivity analyses were performed to assess the stability of the results by excluding one study at a time in order to analyze the influence of each study on the overall OR. The publication bias was assessed using funnel plots and Egger's test25.

Three subgroup analyses were additionally carried out by ethnicity (Caucasian, Asian or Hispanics), mean age (pediatric or adult) and source of the controls (hospital based or population based). The statistical analysis was performed with RevMan software version 5 (Cochrane Collaboration) and STATA software version 10.0 (Stata Corporation). A P value < 0.05 was considered to be statistically significant in this trial unless otherwise specified.

Results

Literature search

The search strategy initially identified 419 potentially relevant articles, and 363 articles were determined to be irrelevant after a review of the titles and abstracts. Thus, 56 trials proceeded to a full-text review, and an additional 33 studies were excluded. Finally, 23 articles were ultimately selected for inclusion in the meta-analysis17,18,19,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45. A flow describing the article selection process for this meta-analysis is shown in Figure 1. Of all of the studies included, 10 studies involved Caucasians17,19,26,27,28,29,30,31,32,42, 12 studies investigated Asians18,33,34,35,36,37,38,39,40,43,44,45, and 1 study researched Hispanics41. All of the studies followed a case-control design, 8 studies used population-based controls16,18,28,33,40,41,42,43, and 15 studies used hospital-based controls17,19,26,29,30,31,32,34,35,36,37,38,39,44,45. In addition, 19 studies were conducted in adult patients16,17,18,19,26,28,29,30,31,32,34,35,36,37,38,39,42,44,45, and 4 investigated pediatric patients33,40,41,43. The distribution of genotypes in the controls was consistent with HWE in 21 studies17,18,19,26,27,29,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45 and insufficient in the 2 other studies28,30. The quality score of the included studies ranged from 7 to 11 (Table S1). The characteristics of the included studies are presented in Table 1.

Figure 1. Flowchart of the study selection.

Figure 1

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Table 1. Characteristics of Studies Included in this meta-analysis.

Author Year Country or Region Ethnicity Source of Control Genotyping method Age Female n (%) NAFLD diagnosis Liver Biopsy(n) Cases Controls Quality Score
Kantartzis et al. 2009 Germany Caucasian H-B TaqMan Adult 200(60.6) H-MRS NA 105 225 10
Sookoian et al. 2009 Argentina Caucasian H-B Allele specific PCR Adult 186(69.9) US and LB 103 172 94 10
Valenti et al. 2010 Italy/United Kingdom Caucasian P-B TaqMan Adult Italy: 114(26.3) UK: 123 (38) LB 574 574 179 11
Rotman et al. 2010 USA Caucasian P-B MassARRAY Sequenome Adult NA LB 766 120 766 7
Speliotes et al. 2010 USA Caucasian H-B MassARRAY Sequenome Adult NA LB 678 678 1405 10
Goran et al. 2010 USA Hispanic P-B TaqMan Pediatric 129 (68.6) DEXA NA 71 188 9
Lin et al. 2010 Taiwan Asian P-B TaqMan Pediatric 174 (33.5) US NA 102 418 11
Hotta et al. 2010 Japan Asian H-B TaqMan Adult 527 (63.4) LB 253 253 575 8
Wang et al. 2011 Taiwan Asian H-B TaqMan Adult 472 (53.7) US NA 156 723 10
Petit et al. 2011 France Caucasian H-B Real-time PCR Adult 120 (51.3) H-MRS NA 149 85 8
Zain et al. 2012 Malaysia Asian H-B TaqMan Adult 180 (52.6) LB 144 144 198 10
Kawaguchi et al. 2012 Japan Asian H-B BeadChip Adult 741 (50.7) LB 529 529 932 10
Valenti et al. 2012 Italian Caucasian H-B Real-time PCR Adult 87 (21.7) LB 144 144 257 9
Li et al. 2012 China Asian H-B TaqMan Adult NA US NA 203 202 10
Peng et al. 2012 China Asian H-B MassARRAY Sequenome Adult 308 (27.8) US NA 553 553 11
Lin et al. 2013 Taiwan Asian P-B TaqMan Pediatric 237 (30.3) US NA 182 599 9
Guichelaar et al. 2013 USA Caucasian H-B TaqMan Adult 122 (84.7) LB 144 132 12 8
Verrijken et al. 2013 Belgium Caucasian H-B TaqMan Adult 331 (70.4) LB 287 208 79 10
Kitamoto et al. 2013 Japan Asian P-B BeadChip Adult 782 (49.6) LB 564 564 1946 11
Musso et al. 2013 Italy Caucasian P-B TaqMan Adult 78 (36.8) US NA 51 161 11
Lin et al. 2014 Taiwan Asian P-B TaqMan Pediatric 242 (30.4) US NA 191 606 11
Niu et al. 2014 China Asian H-B ABI Sequencer Adult 426 (53.3) US NA 390 409 10
Lee et al. 2014 Korea Asian H-B TaqMan Adult 178 (52.5) US NA 155 184 11
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P-B, population-based study; H-B, hospital-based study; H-MRS: hydrogen magnetic resonance (H-MR) spectroscopy, US: liver ultrasonographic examination, LB: liver biopsy, DEXA: dual energy-ray absorptiometry, NA: not available.

Association between rs738409 and risk for NAFLD

All studies

A total of 23 studies with 6071 cases and 10366 controls reported an association between the rs738409 polymorphism and NAFLD risk17,18,19,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41. Overall, the frequency of the G allele was 49.5% in NAFLD and 34.8% in the controls. The Hispanic population bears the highest frequency of the G allele (69.0% cases vs. 41.9% controls), followed by the Asian (54.2% cases vs. 39.9% controls) and Caucasian (42.2% cases vs. 22.7% controls) populations. The distribution of the rs738409 genotypes and alleles is presented in Table 2. Strong evidence of an association between the rs738409 polymorphism and NAFLD risk was found in all genetic models: allele contrast (OR = 2.10, 95% CI = 1.78–2.48, P < 0.00001; heterogeneity test: I2 = 89%, P < 0.00001); dominant model (OR = 2.06, 95% CI = 1.75–2.43, P < 0.00001; heterogeneity test: I2 = 67%, P < 0.00001); recessive model (OR = 2.49, 95% CI = 2.01–3.08, P < 0.00001; heterogeneity test: I2 = 72%, P < 0.0001); and additive model (OR = 3.41, 95% CI = 2.57–4.52, P < 0.00001; heterogeneity test: I2 = 77%, P < 0.00001) (Figure 2). After exclusion of the two articles deviating from HWE in the cases and controls, the results of the relationship was not influenced significantly in all genetic models (Table 3).

Table 2. The distribution of alleles and genotypes of PNPLA3 in NAFLD studies.
  Sample size Genotype in cases Genotype in controls Case Control G allele (%) C allele (%)  
First Author Cases Controls GG CG CC GG CG CC G C G C Cases Controls Cases Controls HWE P value
Kantartzis 105 225 13 41 51 18 70 137 67 143 106 344 31.9 23.6 68.1 76.4 YES
Sookoian 103 94 NA NA NA NA NA NA 130 76 63 125 63.1 33.6 36.9 66.4 YES
Valenti 2010 574 179 75 254 245 5 56 118 404 744 66 292 35.2 18.4 64.8 81.6 0.59
Rotman 520 336 NA NA NA NA NA NA 516 524 153 519 49.6 22.8 50.4 77.2 NA
Speliotes 592 1405 NA NA NA NA NA NA 592 592 618 2192 50 22.0 50 78.0 YES
Goran 71 188 34 30 7 19 60 38 98 44 98 136 69 26 31 74 0.56
Lin 2011 102 418 26 52 24 59 192 167 104 100 310 526 51.0 37.1 49.0 62.9 0.75
Hotta 253 575 175 97 111 104 296 175 305 201 504 646 88.3 43.8 11.7 56.2 0.28
Wang 156 723 40 80 36 269 335 119 152 160 573 873 51.3 60.4 48.7 39.6 0.40
Petit 149 85 NA NA 68 NA NA 51 NA NA NA NA NA NA NA NA NA
Zain 144 198 NA NA NA NA NA NA 130 158 95 301 45.1 24.0 54.9 76.0 YES
Kawaguchi 529 932 217 468 247 203 236 88 642 412 902 962 85.2 34.4 14.8 65.6 0.17
Valenti 2012 144 257 21 68 55 16 95 146 110 178 127 387 38.2 24.7 61.8 75.3 0.92
Li 203 202 49 84 70 18 90 94 182 224 126 278 44.8 31.0 55.2 69.0 0.59
Peng 553 553 93 276 183 59 259 235 462 642 377 729 41.8 34.1 58.2 65.9 0.32
Lin 2013 182 599 35 93 54 74 288 237 163 201 436 762 44.8 36.4 55.2 63.6 0.35
Guichelaar 132 12 12 41 79 0 3 9 65 199 3 21 24.6 12.5 75.4 87.5 0.62
Verrijken 208 79 17 83 108 0 23 56 117 299 140 434 20.4 5.5 79.6 94.5 0.13
Kitamoto 564 1946 227 241 96 199 513 300 695 433 911 1113 61.6 23.4 38.4 76.6 0.44
Musso 51 161 14 23 14 21 49 91 51 51 91 231 50 28.3 50 71.7 YES
Lin 191 606 38 95 58 75 293 238 171 211 443 769 44.8 36.6 55.2 63.4 0.30
Niu 390 409 189 153 48 50 176 183 531 249 276 542 68.1 33.7 31.9 66.3 0.45
Lee 155 184 49 75 31 37 92 55 173 137 166 202 55.8 45.1 44.2 54.9 0.90
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NA: not applicable YES: studies have already pointed out that the data was HWE, but the data was not applicable.

Figure 2. Forest plot of NAFLD susceptibility associated with rs738409 polymorphism at additive model (GG vs CC).

Figure 2

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Table 3. Association between PNPLA3 polymorphism and NAFLD risk.
Subgroup Inherited model Study number NO. of cases/controls(n/n) Pheterogeneity I2 (%) Pooled OR (95%CI) P valuea
Total studies Allele contrast 22 11838/18552 P < 0.00001 89 2.10 (1.78, 2.48) P < 0.00001
  Dominant model 19 4709/7328 P < 0.0001 67 2.06 (1.75, 2.43) P < 0.00001
  Recessive model 18 4560/7243 P < 0.0001 72 2.49 (2.01, 3.08) P < 0.00001
  Additive model 18 2523/3886 P < 0.00001 77 3.41 (2.57,4.52) P < 0.00001
Studies excluded for DHWE              
  Allele contrast 21 10798/17880 P < 0.00001 89 2.05 (1.74, 2.42) P < 0.00001
  Dominant model 18 4560/7243 P < 0.00001 69 2.02 (1.84, 2.20) P < 0.00001
  Recessive model 18 4560/7243 P < 0.00001 72 2.51 (2.28, 2.77) P < 0.00001
  Additive model 18 2523/3886 P < 0.00001 77 3.32 (2.94, 3.74) P < 0.00001
Ethnicity              
Caucasian Allele contrast 9 4858/5496 P < 0.0001 75 2.56 (2.06, 3.18) P < 0.00001
  Dominant model 7 1363/998 P = 0.60 0 2.21 (1.83, 2.67) P < 0.00001
  Recessive model 6 1214/913 P = 0.35 10 2.68 (1.78, 4.05) P < 0.00001
  Additive model 6 704/617 P = 0.27 22 3.79 (2.35, 6.13) P < 0.00001
Asian Allele contrast 12 6838/12822 P < 0.00001 88 1.82 (1.52,2.18) P < 0.00001
  Dominant model 11 3275/6213 P < 0.00001 78 1.95 (1.56, 2.43) P < 0.00001
  Recessive model 11 3275/6213 P < 0.00001 81 2.33 (1.81, 2.99) P < 0.00001
  Additive model 11 1778/3212 P < 0.00001 84 3.08 (2.21, 4.31) P < 0.00001
Hispanics Allele contrast 1 142/234 NA NA 3.09 (1.99, 4.80) P < 0.00001
  Dominant model 1 71/117 NA NA 4.40 (1.84, 10.51) P = 0.0009
  Recessive model 1 71/117 NA NA 4.74 (2.41, 9.33) P < 0.00001
  Additive model 1 41/57 NA NA 9.71 (3.64, 25.94) P < 0.00001
Control source              
Population based Allele contrast 7 4076/5836 P < 0.00001 90 2.17 (1.60, 2.95) P < 0.00001
  Dominant model 7 2038/2918 P < 0.00001 82 2.47 (2.14, 2.85) P < 0.00001
  Recessive model 7 2038/2918 P < 0.00001 83 3.04 (2.00,4.62) P < 0.00001
  Additive model 7 1139/1542 P < 0.00001 87 4.61 (2.58, 8.23) P < 0.00001
Hospital based Allele contrast 15 7762/12716 P < 0.00001 89 2.07 (1.68, 2.54) P < 0.00001
  Dominant model 12 2671/4410 P = 0.65 0 1.76 (1.57,1.97) P < 0.00001
  Recessive model 11 2522/4325 P = 0.26 19 2.10 (1.78, 2.47) P < 0.00001
  Additive model 11 1384/2344 P = 0.34 11 2.62 (2.20, 3.13) P < 0.00001
Age of participants              
Adult Allele contrast 18 10746/15072 P < 0.00001 90 2.19 (1.82, 2.62) P < 0.00001
  Dominant model 15 4163/5588 P < 0.0001 70 2.10 (1.74, 2.54) P < 0.00001
  Recessive model 14 4014/5503 P < 0.00001 75 2.59 (2.01, 3.34) P < 0.00001
  Additive model 14 2248/2978 P < 0.00001 79 3.54 (2.54, 4.94) P < 0.00001
Pediatric Allele contrast 4 1092/3480 P = 0.01 73 1.73 (1.31, 2.29) P = 0.0001
  Dominant model 4 546/1740 P = 0.09 54 1.89 (1.34, 2.66) P < 0.00001
  Recessive model 4 546/1740 P = 0.07 58 2.18 (1.47, 3.22) P < 0.0001
  Additive model 4 275/908 P = 0.03 66 2.97 (1.75, 5.02) P < 0.0001
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a: Test for overall effect. NA: Not applicable.

Subgroup analyses

Subgroup analyses were conducted to explore the differences between ethnicity, mean age and sources of the controls. In the subgroup analysis by ethnicity, significant association was found between the rs738409 polymorphism and NAFLD risk among the Caucasian, Asian and Hispanic populations. The association between rs738409 polymorphism and NAFLD was most significant in Hispanic population, which followed by Caucasian population, and the association was weakest in Asian population. The analyses also showed that the risk of NAFLD was significantly increased in both adult participants and pediatric subjects. In addition, the G allele was strongly associated with NAFLD susceptibility in hospital-based controls and population-based controls. The results were consistent in all genetic models. More details are presented in Table 3.

Histological Severity of NAFLD

Five eligible studies were used to investigate the association between the rs738409 polymorphism and lobular necroinflammation, including 1978 patients. A statistically significant association was seen between carrying GG genotype and higher inflammation scores (OR = 3.13, 95% CI = 2.76–3.56, P < 0.00001; heterogeneity test: I2 = 0%, P = 0.674) with obvious publication bias (Egger test: P = 0.980) (Figure 3). The six eligible studies with 2552 patients analyze the relationship between rs738409 polymorphism and fibrosis. The analysis pointed out that the GG genotype was significantly associated with fibrosis score (OR = 3.11, 95% CI = 2.66–3.65, P < 0.00001; heterogeneity test: I2 = 18.3%, P = 0.295) and the publication bias was not significant (Egger test: P = 0.457) (Figure 3).

Figure 3.

Figure 3

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(A)The forest plot for the association between rs738409 polymorphism and the risk of necroinflammation (additive model: GG vs CC). (B)The forest plot for the association between rs738409 polymorphism and the risk of fibrosis (additive model: GG vs CC).

Association between rs738409 and risk for simple steatosis

Overall, 7 studies with 387 cases and 2306 controls analyzed the rs738409 polymorphism and risk of simple steatosis17,18,19,28,32,34,36. Interestingly, the frequency of the risk G allele was very close between the cases (38.1%) and controls (38.0%). In Caucasian subjects, the frequency of the G allele was 34.3% in cases and 23.2% in controls, and these values are lower than those found in the Asian population (44.3% cases vs. 42.3% controls) (Table 4). We analyzed the relationship between the G allele and the risk of simple steatosis. No significant association was observed between rs738409 polymorphism and simple steatosis under additive model (OR = 1.34, 95% CI = 0.82–2.20, P = 0.25; heterogeneity test: I2 = 0%, P = 0.58), dominant model and recessive model (Figure 4). However, a significant association was found in allele contrast. A further subgroup analysis based on ethnicity showed no obvious association between the rs738409 polymorphism and simple steatosis in Asian subjects, while a strong association was found in the Caucasian population under the allele contrast instead of the other three genetic models. (Table 5).

Table 4. The distribution of alleles and genotypes of PNPLA3 in SS studies and NASH studies.

  Sample size Genotype in cases Genotype in controls Case Control G allele (%) C allele (%)
First Author Cases Controls GG CG CC GG CG CC G C G C cases controls cases controls
SS                                
Sookoian 40 94 NA NA NA NA NA NA 42 38 63 125 52.5 33.6 48.5 66.4
Rotman 82 336 NA NA NA NA NA NA 85 79 153 519 51.8 22.8 48.2 77.2
Hotta 64 575 19 26 19 104 296 175 64 64 504 646 50 43.8 50 56.2
Zain 33 198 NA NA NA NA NA NA 23 43 95 301 35.0 24.0 65.0 76.0
Guichelaar 60 12 4 13 43 0 3 9 21 99 3 21 17.5 12.5 82.5 87.5
Verrijken 57 79 1 14 42 0 23 56 16 98 23 135 14.0 14.6 86.0 85.4
Kitamoto 51 1012 10 24 17 199 513 300 44 58 911 1113 43.1 45.0 56.9 55.0
Total 387 2306 34 77 121 303 835 540 295 479 1752 2860 38.1 38.0 61.9 62.0
NASH                                
Sookoian 63 94 NA NA NA NA NA NA 88 38 63 125 69.8 33.6 30.2 66.4
Rotman 438 336 NA NA NA NA NA NA 431 445 153 519 49.2 22.8 45.8 77.2
Hotta 189 575 78 85 26 104 296 175 241 137 504 646 63.8 43.8 36.2 56.2
Zain 111 198 NA NA NA NA NA NA 106 116 95 301 48.0 24.0 52.0 76.0
Guichelaar 72 12 8 28 36 0 3 9 44 100 3 21 30.6 12.5 69.4 87.5
Verrijken 151 79 16 69 66 0 23 56 101 201 23 135 33.4 14.6 66.6 85.4
Kitamoto 442 1012 187 183 72 199 513 300 557 327 911 1113 63.0 45.0 37.0 55.0
Total 1466 2306 289 365 200 303 835 540 1568 1364 1752 2860 53.5 38.0 46.5 62.0
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SS: simple steatosis; NASH: nonalcoholic steatohepatitis.

Figure 4. Forest plot of simple steatosis susceptibility associated with rs738409 polymorphism at additive model (GG vs CC).

Figure 4

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Table 5. Association between PNPLA3 polymorphism and simple steatosis risk.

Group Study number(n) NO. of cases/controls(n/n) Pheterogeneity I2 (%) Pooled OR (95%CI) P valuea
SS            
Allele contrast 7 774/4612 P < 0.0001 81 1.59 (1.02, 2.49) P = 0.04
Dominant model 4 232/1678 P = 0.94 0 0.94 (0.66, 1.33) P = 0.73
Recessive model 4 232/1678 P = 0.49 0 1.49 (0.97, 2.30) P = 0.07
Additive model 4 155/843 P = 0.58 0 1.34 (0.82, 2.20) P = 0.25
Caucasian            
Allele contrast 4 478/1042 P = 0.005 76 1.98 (1.05, 3.75) P = 0.04
Dominant model 2 117/91 P = 0.71 0 0.93 (0.48, 1.82) P = 0.84
Recessive model 2 117/91 P = 0.74 0 2.77 (0.30, 25.51) P = 0.37
Additive model 2 90/65 P = 0.75 0 2.69 (0.29, 24.94) P = 0.38
Asian            
Allele contrast 3 296/3570 P = 0.20 37 1.22 (0.89, 1.67) P = 0.22
Dominant model 2 115/1587 P = 0.62 0 0.94 (0.62, 1.42) P = 0.77
Recessive model 2 115/1587 P = 0.16 49 1.44 (0.93, 2.25) P = 0.10
Additive model 2 65/778 P = 0.23 30 1.28 (0.77, 2.14) P = 0.35
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SS: simple steatosis.

a: Test for overall effect.

Association between rs738409 and NASH risk

Overall, seven studies with 1466 cases and 2306 controls reported the rs738409 polymorphism and risk of NASH17,18,19,28,32,34,36: four studies conducted in Caucasians and three studies performed in Asian populations. The pooled overall frequency of the risk G allele was 53.5% in the cases and 38.0% in the controls. The G allele varied widely between the different populations: high in the Asian populations (60.9% cases vs.42.3% controls) and lower in the Caucasian subjects (45.9% cases vs. 23.2% controls) (Table 4). Strong evidence of an association was detected between the rs738409 polymorphism and NASH risk under the additive model (OR = 4.44, 95% CI = 3.39–5.82, P < 0.00001; heterogeneity test: I2 = 0%, P = 0.49) (Figure 5). The association was also significant in the other three genetic models, and no evidence of heterogeneity was observed between the studies. Evidence of a strong association between the rs738409 polymorphism and NASH susceptibility was also found in both Asian and Caucasian populations with all genetic models. In addition, Caucasian populations with rs738409 polymorphism are more easily develop into NASH than Asian populations. The results are described in Table 6.

Figure 5. Forest plot of NASH susceptibility associated with rs738409 polymorphism at additive model (GG vs CC).

Figure 5

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Table 6. Association between PNPLA3 Polymorphism and NASH risk.

Group Study number(n) NO. of cases/controls(n/n) Pheterogeneity I2 (%) Pooled OR (95%CI) P valuea
NASH            
Allele contrast 7 2932/4612 P = 0.005 68 2.78 (2.24, 3.44) P < 0.00001
Dominant model 4 854/1678 P = 0.63 0 2.44 (1.95, 3.04) P < 0.00001
Recessive model 4 854/1678 P = 0.63 0 3.15 (2.58, 3.85) P < 0.00001
Additive model 4 489/843 P = 0.49 0 4.44 (3.39, 5.82) P < 0.00001
Caucasian            
Allele contrast 4 1448/1042 P = 0.59 0 3.40 (2.82, 4.09) P < 0.00001
Dominant model 2 223/91 P = 0.95 0 3.11 (1.82, 5.33) P < 0.0001
Recessive model 2 223/91 P = 0.38 0 10.33 (1.42, 75.06) P = 0.02
Additive model 2 126/65 P = 0.36 0 14.28 (1.96, 103.92) P = 0.009
Asian            
Allele contrast 3 1484/3570 P = 0.24 30 2.26 (1.93, 2.65) P < 0.00001
Dominant model 2 631/1587 P = 0.38 0 2.33 (1.83, 2.96) P < 0.00001
Recessive model 2 631/1587 P = 0.79 0 3.05 (2.49, 3.74) P < 0.00001
Additive model 2 363/778 P = 0.41 0 4.22 (3.21, 5.55) P < 0.00001
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a: Test for overall effect.

Sensitivity and Publication Bias

Sensitivity analysis was performed under additive model to evaluate the influence of a specific study on the overall estimate. The corresponding pooled ORs with 95% CIs produced similarly before and after omitting each study at a time, indicating that our results were stable and reliable (Table S2). The funnel plots of the studies were symmetric in the current meta-analysis (Figure 6). Furthermore, the results of Egger's test did not support the existence of publication bias (additive model: NAFLD: P = 0.467; SS: P = 0.611; NASH: P = 0.282).

Figure 6. Publication bias on rs738409 polymorphism under additive model.

Figure 6

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(A) Funnel plot of studies of the rs738409 variant and NAFLD. (B) Funnel plot of studies of the rs738409 variant and simple steatosis. (C) Funnel plot of studies of the rs738409 variant and NASH.

Discussion

The current meta-analysis provided a systematic assessment of the association between the PNPLA3 rs738409 polymorphism and susceptibility to NAFLD, including its subtypes simple steatosis and NASH. Our results suggested that rs738409 polymorphism exerted a significant influence not only on NAFLD risk, but also on histological severity of NAFLD. In addition, a further analysis showed that individuals with the rs738409 polymorphism experienced a significantly increased risk for NASH. However, our meta-analysis did not show a definite association of rs738409 polymorphism with simple steatosis.

Our results are consistent with those from a previous meta-analysis conducted by Sookoian et al.14, which showed a significant association between the rs738409 polymorphism and NAFLD (OR = 3.26, 95% CI = 2.73–3.89, P < 0.00001) and a significant association between the rs738409 polymorphism and NASH (OR = 3.26, 95% CI = 2.14–4.95, P < 0.00001), similar to the results reported in this manuscript. In the present meta-analysis, analysis of the rs738409 polymorphism revealed a significantly increased NAFLD risk in all genetic models. When the data were stratified by subject ethnicity, a significant correlation was found in all three populations, suggesting that the susceptibility genes may be a strong indicator across different races. In the population-based and hospital-based control studies, a significant correlation was also observed in all genetic models, suggesting that our results were not influenced by the source of controls. In addition, the association between the rs738409 polymorphism and NAFLD risk was also significant in both adult and children populations, indicating that the results are highly stable and not influenced by ethnicity, source of the controls and age of participants.

A large population-based study that involved 9229 multiethnic population, including African-Americans, Hispanics and European-Americans, revealed that patients with the rs738409 polymorphism are associated with a higher risk of NAFLD compared with normal controls10. These findings are generally consistent with individual published reports because 70–90% of the trials showed an association between the rs738409 polymorphism and NAFLD risk27,38,41. The underlying mechanism for how PNPLA3 genotype increases NAFLD susceptibility remains to be elucidated. The questions that have been raised are whether the I148M polymorphism increases liver damage favoring the accumulation of fatty acids in lipid droplets or increases the susceptibility to progress into NASH and fibrogenesis.

It should be noted that rs738409 polymorphism was only significantly associated with increased simple steatosis risk under allelic model, but not under the other three genetic models. When stratified by ethnicity, we only detect a significant association in the Asian subgroup under allele contrast, but failed to detect a significant association in the Caucasion population under all genetic models. This meta-analysis of the associations of the rs738409 polymorphism with NASH showed a significant relation. In the subgroup analysis stratified by ethnicity, similar correlations were observed in both Caucasian and Asian populations. The results from the allele contrast were consistent with those from the other genetic models. The sensitivity analysis revealed that no single study qualitatively changed the pooled odds ratios. These findings suggested that rs738409 polymorphism was strongly associated with NASH.

In our meta-analysis, it appears that the rs738409 polymorphism is more likely to increase the NASH risk instead of simple steatosis. Consistent with our results, animal studies have revealed that, although PNPLA3 has triglyceride lipase activity and is responsible for the transalkylation of acylglycerol, knockout of PNPLA3 has no effect on liver steatosis or insulin resistance46. Further epidemiological studies have also noted that this G allele variation did not affect the main risk factors for steatosis, including insulin resistance, LDL, HDL, total cholesterol and glucose levels29. Other polymorphisms, such as CD14 rs2569190 and GCLC rs4140528, are also regarded to increase the risk of NASH instead of simple steatosis47. There are some possible reasons to explain this phenomenon. First, the effect of the rs738409 G allele may be involved in the differential expression and function of variant PNPLA3 instead of resulting in a loss of function of the wild-type protein. Second, there may be some gene-gene interactions. It is possible that the difference in phenotypes may be caused by some other genetic variant that is strongly linked to rs738409. Third, although NASH and simple steatosis are currently regarded as two histological subtypes along the unique spectrum of NAFLD, evidence suggests that these two conditions may be not only different from the histological syndrome but also varied from pathophysiological standpoints. The results that the association between NASH risk and the rs738409 genotype is independent of simple steatosis might suggest that simple steatosis may not be the essential condition for the progressive damage. Simple steatosis and NASH are likely to be two independent conditions in the NAFLD spectrum.

Despite the inevitable limitations of this meta-analysis, we believe that our research provides useful information. First, the individual sample size of each study included in our meta-analysis was too small to obtain a definite association between rs738409 polymorphisms and NAFLD risk, but the pooled odds ratios generated from the 23 studies significantly increased the statistical power of the analysis compared to that obtained with a single study. Moreover, the protocol of this meta-analysis has been well-designed with explicit criteria and methods for study selection, data extraction and data analysis, which allowed reliable inferences about causality. Third, there was no significant publication bias in this meta-analysis, and the results of the sensitivity analysis support the stability of the results.

However, some limitations of this meta-analysis should be addressed. First, the retrieved literature may not be sufficiently comprehensive. Only published case-control studies were included in this meta-analysis. Second, most of the study subjects were of Caucasian and Asian ancestry, and the Hispanic subgroup was very limited in this meta-analysis. Thus, potential selective bias and publication bias may have occurred. Third, because NAFLD was a multifactor disease, the potential effects of gene-gene and gene-environment interactions should be considered. Fourth, the sample size of NASH in this meta-analysis was so small that the statistical power for making a definitive conclusion regarding the possible risk of the rs738409 polymorphism was limited.

In conclusion, results from this meta-analysis showed that the G allele at PNPLA3 gene was a risk factor for NAFLD and its subtype NASH, especially in Asian, Caucasian and Hispanic populations. However, no association was observed between the rs738409 polymorphism and simple steatosis risk. Further studies with higher quality, more participants and various ethnicities are needed to obtain a more precise estimate of the genetic effects.

Author Contributions

R.-F.X. and G.-Z.C. conceived the study design, and wrote the manuscript; A.-Y.T., S.-S.Z. and Y.-B.D. performed the analyses. All authors read and approved the final manuscript.

Supplementary Material

Supplementary Information

Supplementary information

srep09284-s1.pdf (131.3KB, pdf)

Acknowledgments

The present study was supported by the National Natural Science Foundation of China (No. 81400369).

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Supplementary Materials

Supplementary Information

Supplementary information

srep09284-s1.pdf (131.3KB, pdf)

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