- Open Access
Combining I148M and E167K variants to improve risk prediction for nonalcoholic fatty liver disease in Qingdao Han population, China
Lipids in Health and Disease volume 18, Article number: 45 (2019)
PNPLA3 I148M variant and TM6SF2 E167K variant are recognized as the major genetic modifiers of nonalcoholic fatty liver disease (NAFLD). The present study sought to evaluate the potential additive effect of the two variants on the risk of NAFLD in Qingdao Han Population, China.
We genotyped PNPLA3 I148M variant and TM6SF2 E167K variant in a cohort of 512 unrelated NAFLD patients and 451 healthy controls by sequencing and polymerase chain reaction analysis. In addition, serum lipid profiles and liver enzymes were determined by standard clinical laboratory methods.
The minor allele frequencies were 45.48% for PNPLA3 148 locus G allele and 6.69% for TM6SF2 167 locus T allele. The PNPLA3 I148M variant was significantly associated with the risk of NAFLD in an additive model (CG, OR = 2.092, 95% CI: 1.551–2.820, P = 0.000; GG, OR = 4.566, 95% CI: 3.141–6.638, P = 0.000, respectively). And, our data suggested a strong link between the TM6SF2 E167K variant and the risk of NAFLD in a dominant model (CT + TT, OR = 2.327, 95% CI: 1.542–3.513, P = 0.000). In addition, the increasing of the number of risk alleles were associated with the risk of NAFLD (1 risk allele, OR = 1.687, P = 0.001; 2 risk alleles, OR = 4.326, P = 0.000; 3 risk alleles, OR = 6.018, P = 0.027, respectively).
Combining the I148M and E167K variants in a manner of an additive effect could improve risk prediction for NAFLD in a Qingdao Han Population cohort.
Chinese Clinical Trial Register.gov: ChiCTR1800015426.
Nonalcoholic fatty liver disease (NAFLD) is identified as a metabolic stress injury of the liver, as well as a burgeoning public health issue/economic burden with a high global prevalence of up to ~ 25% [1, 2]. The incidence of NAFLD corresponds to the escalation of obesity, type 2 diabetes mellitus and metabolic syndrome . Various evidence has indicated the heritable contribution to the prevalence, development and progression of NAFLD. The last few decades witness the substantial progress in the genetic susceptibility of NAFLD, providing exciting insight in refining the management and treatment of NAFLD patients. A recent prospective twin study performed by Loomba R et al. concluded that hepatic steatosis and hepatic fibrosis have approximately 52% heritability and 50% heritability in multivariable-adjusted models (adjust for sex, age and ethnicity), respectively . However, we cannot clarify the molecular genetic mechanisms of NAFLD by only gene polymorphism .
Notably, two ‘star gene’ variants, PNPLA3 I148M variant and TM6SF2 E167K variant, are recognized as the major genetic modifiers of NAFLD [6,7,8,9,10]. More recently, the EASL-EASD-EASO clinical practice guidelines for the management of NAFLD recommended that carriers of the two ‘star gene’ variants show a higher liver fat content and increased risk of nonalcoholic steatohepatitis . Interestingly, recent studies have demonstrated that PNPLA3 I148M and TM6SF2 E167K variants may have an additive effect in the regulation of lipid metabolism [8, 12,13,14]. However, no study has focused on the aforementioned association in Qingdao Han Population, China, an international city with more than ~ 9.2 million people after the 18th Meeting of the Council of Heads of Member States of the Shanghai Cooperation Organization. The present study sought to investigate the potential additive effect of the two variants on the risk of NAFLD in Qingdao Han Population, China.
Subjects and methods
The present study was conducted in accordance with the principles of the World Medical Association Declaration of Helsinki. All the subjects have signed written informed consent according to the study protocol approved by the Ethics Committee of Qingdao Municipal Hospital before participation (Approval NO.2017–20).
We recruited a total of 512 unrelated Qingdao Han NAFLD patients determined by liver ultrasonography (a fairly reliable and accurate noninvasive method with sensitivity of 84.8% and specificity of 93.6% ) and 451 healthy controls matched for age and sex in the present study. The healthy controls were performed liver ultrasonography to rule out NAFLD. All the subjects were of Qingdao Han ethnicity, China and included from the health examination center and the Department of Gastroenterology of Qingdao Municipal Hospital. The diagnosis of NAFLD was determined by a same experienced operator in accordance with the guidelines for management of NAFLD of the Chinese Liver Disease Association in 2010 . Other etiologies contributing to fatty liver disease, including alcohol consumption (≥ 20 g/day for females and ≥ 30 g/day for males), hepatitis B infection, hepatitis C infection (genotype 3), autoimmune hepatitis, Wilson’s disease and drug-induced liver injury et al. were excluded .
Blood samples were collected after 12-h fast for serological assays and genetic analysis. Serum concentration of albumin (ALB), fasting plasma glucose (FPG), alanine aminotransferase (ALT), aspartate aminotransferase (AST), γ-glutamyltransferase (GGT), alkaline phosphatase (ALP), triglyceride (TG), total cholesterol (TC), high-density lipoprotein (HDL) and low-density lipoprotein (LDL), uric acid (UA) were obtained using standard methods in the Central Laboratory of Qingdao Municipal Hospital.
Genomic DNA Purification Kit (BioTeke, Biotechnology, Beijing, China) was used to extract genomic DNA according to the manufacturer’s protocol from the noncoagulated blood samples. The genotyping of PNPLA3 I148M variant and TM6SF2 E167K variant was performed by polymerase chain reaction (PCR) with the following primers. Primers for PNPLA3 I148M and TM6SF2 E167K were: 5′- AACTTCTCTCTCCTTTGCTTTCACA -3′ (forward), 5′- GGAGGGATAAGGCCACTGTAGA -3′(reverse); 5′- TGTCTCAGAACAAACAAACAAACAGA -3′ (forward), 5′- GTAGGGGATGGTGAGGAAGAAG -3′ (reverse). The PCR amplification profile was conducted as follows: 95 °C for 10 min, 40 cycles before denaturation at 94 °C for 1 min, annealing at 58 °C for 1 min and elongation 30 s at 70 °C. The PNPLA3 and TM6SF2 genotypes were detected by ABI 3730XL (Foster City, CA, USA) and calculated by Gene Mapper 4.1 software.
SPSS 20.0 statistical software (SPSS Inc., Chicago, IL, USA) was performed for statistical analysis. The baseline characteristics between healthy controls and NAFLD patients were showed as mean ± standard deviation, and the differences were examined using student’s t test or paired samples t test. The Hardy-Weinberg equilibrium was measured using the χ2 test. Genotype and allele frequencies between healthy controls and NAFLD patients were analyzed by chi-square test. The DNA distributions between the two groups were determined by χ2 test and Fisher’s exact test where appropriate. The association between the PNPLA3 I148M and/or TM6SF2 E167K variants and NAFLD was evaluated by the odds ratio (OR) with 95% confidence interval (CI) and performed by logistic regression analysis. In addition, an additive model (by coding the genotypes 0, 1 and 2 for CC, CG and GG, respectively) for PLPLA3 gene and a dominant model (by coding the genotypes 0 and 1 for CC and CT + TT, respectively) for TM6SF2 gene were assumed to assessed the potential additive effect of the two variants. Statistical significance was defined as P-value less than 0.05.
Demographic and clinical characteristics
Demographic and clinical characteristics of healthy controls and NAFLD patients were presented in Table 1. When compared to the healthy controls, NAFLD patients had higher BMI, serum levels of FPG, ALT, AST, GGT, ALP, TG, TC, LDL, UA and decreased ALB, HDL. All the difference reached significance (all P < 0.05).
Associations between PNPLA3 I148M and TM6SF2 E167K variants and NAFLD
The genotypic distribution of PNPLA3 I148M and TM6SF2 E167K were both in Hardy-Weinberg equilibrium in both two groups (P control = 0.243, 0.773; P NAFLD = 0.113, 0.313). The minor allele frequencies of the two single-nucleotide polymorphisms (SNPs) in the whole subjects were 45.48% for PNPLA3 I148M and 6.69% for TM6SF2 E167K, respectively. As listed in Table 2, both the differences in the genotypes and allele frequencies of the PNPLA3 I148M and TM6SF2 E167K reached significance (all P < 0.05). Moreover, Table 3 showed that the PNPLA3 I148M variant was significantly associated with the risk of NAFLD in an additive model (CG, OR = 2.092, 95% CI: 1.551–2.820, P = 0.000; GG, OR = 4.566, 95% CI: 3.141–6.638, P = 0.000, respectively). Interestingly, it suggested a strong link between the TM6SF2 E167K variant and the risk of NAFLD in a dominant model (CT + TT, OR = 2.327, 95% CI: 1.542–3.513, P = 0.000).
Furthermore, Table 4 demonstrated the association between the two variants and clinical features. Subjects with the G allele of PNPLA3 I148M had higher BMI, serum levels of ALT, AST, GGT, ALP, TG, TC, LDL and UA (all P < 0.05). The serum level of HDL did not reached significance (P = 0.967). However, only serum concentrations of some lipid profiles (TG and TC; both P < 0.05) showed inversely strong links between carriers of the T allele of TM6SF2 E167K and the noncarriers. The T allele of TM6SF2 E167K was associated with lower levels of serum TG and TC (P = 0.003, P = 0.006).
Additive effects of PNPLA3 I148M and TM6SF2 E167K variants on the risk of NAFLD
Moreover, the potential additive effect of the two variants on the risk of NAFLD was conducted in the study subjects. We counted risk alleles at the two gene locus (for PNPLA3 148 locus, by coding the genotypes 0, 1 and 2 for CC, CG and GG; for TM6SF2 167 locus, by coding the genotypes 0 and 1 for CC and CT + TT, respectively). The group with 0 risk allele was regarded as the control group. Excitingly, the prevalence of NAFLD increased following with the increase of the number of risk alleles (36.77, 49.53, 71.56 and 77.78% of subjects with 0, 1, 2 and 3 risk alleles, respectively, Fig. 1). In addition, the increasing of the number of risk alleles showed a strong link with the risk of NAFLD (1 risk allele, OR = 1.687, 95% CI: 1.226–2.321, P = 0.001; 2 risk alleles, OR = 4.326, 95% CI: 3.100–6.037, P = 0.000; 3 risk alleles, OR = 6.018, 95% CI: 1.229–29.459, P = 0.027, respectively, Table 5).
Our study aimed to assess the potential additive effect of the PNPLA3 I148M and TM6SF2 E167K variants on the risk of NAFLD in Qingdao Han Population, China. We confirmed the significant association between both the PNPLA3 I148M and TM6SF2 E167K variants and the risk of NAFLD in a cohort consisting of a total of 512 NAFLD patients and 451 age and sex matched healthy controls. Moreover, combining the I148M and E167K variants could improve risk prediction for NAFLD in a Qingdao Han Population.
NAFLD ranked as the most concerned chronic liver disease in the coming decades worldwide, and, nonalcoholic steatohepatitis is recognized as the second leading indication for liver transplantation in the USA [17,18,19]. Notably, there is a genetic susceptibility for NAFLD [1, 3, 11]. Mahdessian H et al. firstly reported that TM6SF2 inhibition induced significant reduction of the expression of PNPLA3 gene in both Huh7 and HepG2 cells, which, to some extent, indicating a joint/additive effect between PNPLA3 gene and TM6SF2 gene in determining lipid metabolism . More recently, a multiethnic study  of obese children and adolescents (including Caucasians, African Americans, and Hispanics) summarized that there is a joint effect among PNPLA3 I148M, TM6SF2 E167K, and GCKR rs1260326 single nucleotide polymorphisms in regulating intrahepatic fat accumulation. Similarly, Wang and colleagues  demonstrated the additive effect of PNPLA3 I148M and TM6SF2 E167K variants on NAFLD in a Chinese cohort. In the present study, we observed that PNPLA3 I148M variant and TM6SF2 E167K variant were both major and independent genetic determinants of NAFLD in a Qingdao Han Population, consistent with previous studies [21, 22]. More importantly, subjects in our study with increasing number of risk alleles (PNPLA3 148 locus G allele and TM6SF2 167 locus T allele) showed an additive effect of the two variants, compared to individuals with 0 risk allele (1 risk allele, OR = 1.687, P = 0.001; 2 risk alleles, OR = 4.326, P = 0.000; 3 risk alleles, OR = 6.018, P = 0.027, respectively). Furthermore, our pilot study  performed a Bayesian analysis and evaluated the additive effect of the two variants on hepatocyte lipid metabolism as well as the underlying mechanism in vitro. Our date suggested that the PNPLA3 I148M and TM6SF2 E167K variants may increase hepatic lipid content by upregulating the expression of sterol regulatory element-binding transcription factor 1c and fatty acid synthase. However, to the best of our knowledge, all other previous studies have not reported the underlying molecular mechanism of this potential additive effect. These encouraging findings provide the potential perspective in new NAFLD classification and the probability of offering a new important tool for risk prediction of NAFLD in the coming years.
We additionally investigated the relations between PNPLA3 I148M and TM6SF2 E167K variants and serum concentrations of lipid profiles. Several studies showed inconsistent metabolic associations of NAFLD risk alleles. For instance, some studies demonstrated a strong link between TM6SF2 E167K variant and lower plasma levels of TC, TG and LDL [8, 24,25,26], but the differences in several other studies did not reach the significance [9, 27, 28]. Similarly, the association between the PNPLA3 I148M variant and plasma concentrations of lipid profiles was also inconsistent. [6, 29,30,31]. Our data demonstrated that subjects with the G allele of PNPLA3 I148M had higher serum levels of TG, TC and LDL (all P < 0.05). And, the serum concentrations of some lipid profiles (TG and TC; both P < 0.05) showed inversely strong links between carriers of the T allele of TM6SF2 E167K and the noncarriers. The T allele of TM6SF2 E167K was associated with lower concentrations of serum levels of TG and TC (P = 0.003, P = 0.006). These different findings may inasmuch as the population ethnicity, diagnostic method of NAFLD and demographic and clinical characteristics. Therefore, the relationship between the two ‘star gene’ variants and clinical features of NAFLD population needs further investigation.
This study has some limitations. First one is the perform of ultrasonography to determine NAFLD, instead of magnetic resonance imaging and/or liver biopsy. Notably, liver ultrasonography cannot provide reliable quantitative data . In addition, we conducted the present study in a single center and the findings may have limited application value in other different populations. Furthermore, the size of subjects in the study was not sufficiently large to comprehensively explore the associations.
In conclusion, we confirmed the significant association between both the PNPLA3 I148M and TM6SF2 E167K variants and the risk of NAFLD in a Qingdao Han Population cohort. More importantly, combining the I148M and E167K variants could improve risk prediction for NAFLD in a manner of an additive effect. This study may provide the potential perspective in new NAFLD classification and the identification of high risk NAFLD populations in the future.
- 95% CI:
95% confidence interval
Body mass index
Fasting plasma glucose
Nonalcoholic fatty liver disease
Polymerase chain reaction
Chalasani N, Younossi Z, Lavine JE, Charlton M, Cusi K, Rinella M, et al. The diagnosis and management of nonalcoholic fatty liver disease: practice guidance from the American Association for the Study of Liver Diseases. Hepatology. 2018;67:328–57.
Younossi ZM, Koenig AB, Abdelatif D, Fazel Y, Henry L, Wymer M. Global epidemiology of nonalcoholic fatty liver disease-meta-analytic assessment of prevalence, incidence, and outcomes. Hepatology. 2016;64:73–84.
National Workshop on Fatty Liver and Alcoholic Liver Disease. Chinese Society of Hepatology, Chinese Medical Association; fatty liver expert committee, Chinese medical doctor association. Guidelines of prevention and treatment for nonalcoholic fatty liver disease: a 2018 update. Zhonghua Gan Zang Bing Za Zhi. 2018;26:195–203.
Loomba R, Schork N, Chen CH, Bettencourt R, Bhatt A, Ang B, et al. Heritability of hepatic fibrosis and steatosis based on a prospective twin study. Gastroenterology. 2015;149:1784–93.
Eslam M, Valenti L, Romeo S. Genetics and epigenetics of NAFLD and NASH: clinical impact. J Hepatol. 2018;68:268–79.
Romeo S, Kozlitina J, Xing C, Pertsemlidis A, Cox D, Pennacchio LA, et al. Genetic variation in PNPLA3 confers susceptibility to nonalcoholic fatty liver disease. Nat Genet. 2008;40:1461–5.
Singal AG, Manjunath H, Yopp AC, Beg MS, Marrero JA, Gopal P, et al. The effect of PNPLA3 on fibrosis progression and development of hepatocellular carcinoma: a meta-analysis. Am J Gastroenterol. 2014;109:325–34.
Kozlitina J, Smagris E, Stender S, Nordestgaard BG, Zhou HH, Tybjærg-Hansen A, et al. Exome-wide association study identifies a TM6SF2 variant that confers susceptibility to nonalcoholic fatty liver disease. Nat Genet. 2014;46:352–6.
Sookoian S, Castaño GO, Scian R, Mallardi P, Fernández Gianotti T, Burgueño AL, et al. Genetic variation in transmembrane 6 superfamily member 2 and the risk of nonalcoholic fatty liver disease and histological disease severity. Hepatology. 2015;61:515–25.
Chen LZ, Xia HH, Xin YN, Lin ZH, Xuan SY. TM6SF2 E167K variant, a novel genetic susceptibility variant, contributing to nonalcoholic fatty liver disease. J Clin Transl Hepatol. 2015;3:265–70.
European Association for the Study of the Liver (EASL). Electronic address: email@example.com; European Association for the Study of diabetes (EASD); European Association for the Study of obesity (EASO). EASL-EASD-EASO clinical practice guidelines for the management of non-alcoholic fatty liver disease. J Hepatol. 2016;64:1388–402.
Goffredo M, Caprio S, Feldstein AE, D'Adamo E, Shaw MM, Pierpont B, et al. Role of TM6SF2 rs58542926 in the pathogenesis of nonalcoholic pediatric fatty liver disease: a multiethnic study. Hepatology. 2016;63:117–25.
Wang XL, Liu ZP, Wang K, Wang ZW, Sun X, Zhong L, et al. Additive effects of the risk alleles of PNPLA3 and TM6SF2 on non-alcoholic fatty liver disease (NAFLD) in a Chinese population. Front Genet. 2016;7:140.
Koo BK, Joo SK, Kim D, Bae JM, Park JH, Kim JH, et al. Additive effects of PNPLA3 and TM6SF2 on the histological severity of non-alcoholic fatty liver disease. J Gastroenterol Hepatol. 2018;33:1277–85.
Hernaez R, Lazo M, Bonekamp S, Kamel I, Brancati FL, Guallar E, et al. Diagnostic accuracy and reliability of ultrasonography for the detection of fatty liver: a meta-analysis. Hepatology. 2011;54:1082–90.
Jian-gao F. Chinese liver disease association. Guidelines for management of nonalcoholic fatty liver disease: an updated and revised edition. Zhonghua Gan Zang Bing Za Zhi. 2010;18:163–6.
Rinella M, Charlton M. The globalization of nonalcoholic fatty liver disease: prevalence and impact on world health. Hepatology. 2016;64:19–22.
Cholankeril G, Wong RJ, Hu M, Perumpail RB, Yoo ER, Puri P, et al. Liver transplantation for nonalcoholic steatohepatitis in the US: temporal trends and outcomes. Dig Dis Sci. 2017;62:2915–22.
Chedid MF. Nonalcoholic steatohepatitis: the secondleading indication for liver transplantation in the USA. Dig Dis Sci. 2017;62:2621–2.
Mahdessian H, Taxiarchis A, Popov S, Silveira A, Franco-Cereceda A, Hamsten A, et al. TM6SF2 is a regulator of liver fat metabolism influencing triglyceride secretion and hepatic lipid droplet content. Proc Natl Acad Sci U S A. 2014;111:8913–8.
Sookoian S, Pirola CJ. Meta-analysis of the influence of I148M variant of patatin-like phospholipase domain containing 3 gene (PNPLA3) on the susceptibility and histological severity of nonalcoholic fatty liver disease. Hepatology. 2011;53:1883–94.
Pirola CJ, Sookoian S. The dual and opposite role of the TM6SF2-rs58542926 variant in protecting against cardiovascular disease and conferring risk for nonalcoholic fatty liver: a meta-analysis. Hepatology. 2015;62:1742–56.
Chen LZ, Du SX, Lu LL, Lin ZH, Jin WW, Hu DD, et al. The additive effects of the TM6SF2 E167K and PNPLA3 I148M polymorphisms on lipid metabolism. Oncotarget. 2017;8:74209–16.
Dongiovanni P, Petta S, Maglio C, Fracanzani AL, Pipitone R, Mozzi E, et al. Transmembrane 6 superfamily member 2 gene variant disentangles nonalcoholic steatohepatitis from cardiovascular disease. Hepatology. 2015;61:506–14.
Scorletti E, West AL, Bhatia L, Hoile SP, McCormick KG, Burdge GC, et al. Treating liver fat and serum triglyceride levels in NAFLD, effects of PNPLA3 and TM6SF2 genotypes: results from the WELCOME trial. J Hepatol. 2015;63:1476–83.
O'Hare EA, Yang R, Yerges-Armstrong LM, Sreenivasan U, McFarland R, Leitch CC, et al. TM6SF2 rs58542926 impacts lipid processing in liver and small intestine. Hepatology. 2017;65:1526–42.
Zhou Y, Llauradó G, Orešič M, Hyötyläinen T, Orho-Melander M, Yki-Järvinen H. Circulating triacylglycerol signatures and insulin sensitivity in NAFLD associated with the E167K variant in TM6SF2. J Hepatol. 2015;62:657–63.
Sookoian S, Pirola CJ. Meta-analysis of the influence of TM6SF2 E167K variant on plasma concentration of aminotransferases across different populations and diverse liver phenotypes. Sci Rep. 2016;6:27718.
Niu TH, Jiang M, Xin YN, Jiang XJ, Lin ZH, Xuan SY. Lack of association between apolipoprotein C3 gene polymorphisms and risk of nonalcoholic fatty liver disease in a Chinese Han population. World J Gastroenterol. 2014;20:3655–62.
Sliz E, Sebert S, Würtz P, Kangas AJ, Soininen P, Lehtimäki T, et al. NAFLD risk alleles in PNPLA3, TM6SF2, GCKR and LYPLAL1 show divergent metabolic effects. Hum Mol Genet. 2018;27:2214–23.
Simons N, Isaacs A, Koek GH, Kuč S, Schaper NC, Brouwers MCGJ. PNPLA3, TM6SF2, and MBOAT7 genotypes and coronary artery disease. Gastroenterology. 2017;152:912–3.
Saadeh S, Younossi ZM, Remer EM, Gramlich T, Ong JP, Hurley M, et al. The utility of radiological imaging in nonalcoholic fatty liver disease. Gastroenterology. 2002;123:745–50.
We would like to thank Ocean University of China, Qingdao Municipal Hospital and all the subjects in the present study for cooperation.
This study was supported by the National Natural Science Foundation of China (NSFC, No.31770837); Qingdao Livelihood, Science and Technology Project, China (Grant No.18–6–1-68-nsh); Innovation research fund for new technologies and new projects of Qingdao Municipal Hospital President (Grant No.ZYZJJ-YJ201817).
Availability of data and materials
Ethics approval and consent to participate
The study protocol was approved by the Ethics Committee of Qingdao Municipal Hospital before participation (Approval NO.2017–20). All the subjects have signed written informed consent.
Consent for publication
The authors declare that they have no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Chen, L., Ding, H., Liu, S. et al. Combining I148M and E167K variants to improve risk prediction for nonalcoholic fatty liver disease in Qingdao Han population, China. Lipids Health Dis 18, 45 (2019) doi:10.1186/s12944-019-0992-9
- Nonalcoholic fatty liver disease
- Additive effect