Combined effects of the PNPLA3 rs738409, TM6SF2 rs58542926, and MBOAT7 rs641738 variants on NAFLD severity: a multicenter biopsy-based study
2016; Elsevier BV; Volume: 58; Issue: 1 Linguagem: Inglês
10.1194/jlr.p067454
ISSN1539-7262
AutoresMarcin Krawczyk, Monika Rau, Jörn M. Schattenberg, Heike Bantel, Anita Pathil, Münevver Demir, Johannes Kluwe, Tobias Boettler, Frank Lammert, Andreas Geier,
Tópico(s)Diet, Metabolism, and Disease
ResumoThe PNPLA3 p.I148M, TM6SF2 p.E167K, and MBOAT7 rs641738 variants represent genetic risk factors for nonalcoholic fatty liver disease (NAFLD). Here we investigate if these polymorphisms modulate both steatosis and fibrosis in patients with NAFLD. We recruited 515 patients with NAFLD (age 16–88 years, 280 female patients). Liver biopsies were performed in 320 patients. PCR-based assays were used to genotype the PNPLA3, TM6SF2, and MBOAT7 variants. Carriers of the PNPLA3 and TM6SF2 risk alleles showed increased serum aspartate aminotransferase and alanine transaminase activities (P < 0.05). The PNPLA3 genotype was associated with steatosis grades S2–S3 (P < 0.001) and fibrosis stages F2–F4 (P < 0.001). The TM6SF2 genotype was associated with steatosis (P = 0.003) but not with fibrosis (P > 0.05). The MBOAT7 variant was solely associated with increased fibrosis (P = 0.046). In the multivariate model, variants PNPLA3 (P = 0.004) and TM6SF2 (P = 0.038) were associated with steatosis. Fibrosis stages were affected by the PNPLA3 (P = 0.042) and MBOAT7 (P = 0.021) but not by the TM6SF2 polymorphism (P > 0.05). The PNPLA3, TM6SF2, and MBOAT7 variants are associated with increased liver injury. The TM6SF2 variant seems to modulate predominantly hepatic fat accumulation, whereas the MBOAT7 polymorphism is linked to fibrosis. The PNPLA3 polymorphism confers risk of both increased steatosis and fibrosis. The PNPLA3 p.I148M, TM6SF2 p.E167K, and MBOAT7 rs641738 variants represent genetic risk factors for nonalcoholic fatty liver disease (NAFLD). Here we investigate if these polymorphisms modulate both steatosis and fibrosis in patients with NAFLD. We recruited 515 patients with NAFLD (age 16–88 years, 280 female patients). Liver biopsies were performed in 320 patients. PCR-based assays were used to genotype the PNPLA3, TM6SF2, and MBOAT7 variants. Carriers of the PNPLA3 and TM6SF2 risk alleles showed increased serum aspartate aminotransferase and alanine transaminase activities (P < 0.05). The PNPLA3 genotype was associated with steatosis grades S2–S3 (P < 0.001) and fibrosis stages F2–F4 (P < 0.001). The TM6SF2 genotype was associated with steatosis (P = 0.003) but not with fibrosis (P > 0.05). The MBOAT7 variant was solely associated with increased fibrosis (P = 0.046). In the multivariate model, variants PNPLA3 (P = 0.004) and TM6SF2 (P = 0.038) were associated with steatosis. Fibrosis stages were affected by the PNPLA3 (P = 0.042) and MBOAT7 (P = 0.021) but not by the TM6SF2 polymorphism (P > 0.05). The PNPLA3, TM6SF2, and MBOAT7 variants are associated with increased liver injury. The TM6SF2 variant seems to modulate predominantly hepatic fat accumulation, whereas the MBOAT7 polymorphism is linked to fibrosis. The PNPLA3 polymorphism confers risk of both increased steatosis and fibrosis. Nonalcoholic fatty liver disease (NAFLD) affects more than 30% of adults in developed countries. Given the increasing prevalence of environmental risk factors for this condition (e.g., hypercaloric diets and sedentary lifestyles) (1Marchesini G. Petta S. Dalle Grave R. Diet, weight loss, and liver health in nonalcoholic fatty liver disease: pathophysiology, evidence, and practice.Hepatology. 2016; 63: 2032-2043Crossref PubMed Scopus (193) Google Scholar), the frequency of fatty liver is predicted to further increase in the coming years. In addition to environmental triggers, genetic predisposition is known to modulate the degree of steatosis and liver injury (2Anstee Q.M. Day C.P. The genetics of nonalcoholic fatty liver disease: spotlight on PNPLA3 and TM6SF2.Semin. Liver Dis. 2015; 35: 270-290Crossref PubMed Scopus (111) Google Scholar). Conceptually, the term “hepatic steatosis” refers to traits that are governed by multiple variants with modest effects. The major part of the genetic predisposition is, according to current knowledge, related to two common missense SNPs: PNPLA3 p.I148M and TM6SF2 p.E167K. These two polymorphisms, detected in genome-wide (3Romeo S. Kozlitina J. Xing C. Pertsemlidis A. Cox D. Pennacchio L.A. Boerwinkle E. Cohen J.C. Hobbs H.H. Genetic variation in PNPLA3 confers susceptibility to nonalcoholic fatty liver disease.Nat. Genet. 2008; 40: 1461-1465Crossref PubMed Scopus (2213) Google Scholar) and exome-wide (4Kozlitina J. Smagris E. Stender S. Nordestgaard B.G. Zhou H.H. Tybjaerg-Hansen A. Vogt T.F. Hobbs H.H. Cohen J.C. Exome-wide association study identifies a TM6SF2 variant that confers susceptibility to nonalcoholic fatty liver disease.Nat. Genet. 2014; 46: 352-356Crossref PubMed Scopus (749) Google Scholar) association studies in patients with fatty livers, seem to impose different risks on their carriers. The PNPLA3 (patatin-like phospholipase domain containing 3, also known as adiponutrin) p.I148M polymorphism is commonly regarded to be the risk factor for both increased fat accumulation and fibrosis (5Krawczyk M. Portincasa P. Lammert F. PNPLA3-associated steatohepatitis: toward a gene-based classification of fatty liver disease.Semin. Liver Dis. 2013; 33: 369-379Crossref PubMed Scopus (64) Google Scholar, 6Sookoian S. Pirola C.J. 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: 1883-1894Crossref PubMed Scopus (668) Google Scholar). The association with steatosis was demonstrated in several candidate studies, whereas the link between PNPLA3 and liver scarring was substantiated by meta-analyses in patients with chronic hepatitis C virus (HCV) infection (7Fan J.H. Xiang M.Q. Li Q.L. Shi H.T. Guo J.J. PNPLA3 rs738409 polymorphism associated with hepatic steatosis and advanced fibrosis in patients with chronic hepatitis C virus: a meta-analysis.Gut Liver. 2016; 10: 456-463Crossref PubMed Scopus (28) Google Scholar) and in alcoholics (8Salameh H. Raff E. Erwin A. Seth D. Nischalke H.D. Falleti E. Burza M.A. Leathert J. Romeo S. Molinaro A. et al.PNPLA3 gene polymorphism is associated with predisposition to and severity of alcoholic liver disease.Am. J. Gastroenterol. 2015; 110: 846-856Crossref PubMed Scopus (102) Google Scholar). The data concerning the involvement of TM6SF2 (transmembrane 6 superfamily member 2) in liver injury are less definitive. So far, only a few studies investigating the TM6SF2 risk genotype in NAFLD (9Pirola C.J. 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: 1742-1756Crossref PubMed Scopus (108) Google Scholar) and in HCV (10Milano M. Aghemo A. Mancina R.M. Fischer J. Dongiovanni P. De Nicola S. Fracanzani A.L. D'Ambrosio R. Maggioni M. De Francesco R. et al.Transmembrane 6 superfamily member 2 gene E167K variant impacts on steatosis and liver damage in chronic hepatitis C patients.Hepatology. 2015; 62: 111-117Crossref PubMed Scopus (50) Google Scholar) have been published. Liu et al. (11Liu Y.L. Reeves H.L. Burt A.D. Tiniakos D. McPherson S. Leathart J.B. Allison M.E. Alexander G.J. Piguet A.C. Anty R. et al.TM6SF2 rs58542926 influences hepatic fibrosis progression in patients with non-alcoholic fatty liver disease.Nat. Commun. 2014; 5: 4309Crossref PubMed Scopus (406) Google Scholar) reported that carriers of the minor allele are at risk of increased steatosis and fibrosis. Interestingly, both PNPLA3 and TM6SF2 variants have been associated with “metabolically silent” NAFLD; i.e., carriers of the risk genotypes seem to develop NAFLD and its severe forms even in the absence of characteristics commonly associated with fatty liver (5Krawczyk M. Portincasa P. Lammert F. PNPLA3-associated steatohepatitis: toward a gene-based classification of fatty liver disease.Semin. Liver Dis. 2013; 33: 369-379Crossref PubMed Scopus (64) Google Scholar, 12Zhou Y. Llaurado G. Oresic M. Hyotylainen T. Orho-Melander M. Yki-Jarvinen H. Circulating triacylglycerol signatures and insulin sensitivity in NAFLD associated with the E167K variant in TM6SF2.J. Hepatol. 2015; 62: 657-663Abstract Full Text Full Text PDF PubMed Scopus (89) Google Scholar). Indeed, numerous genetic studies failed to detect equivocal evidence for the association between TM6SF2 and PNPLA3 variants and traits such as obesity, insulin resistance, or hyperlipidemia. Most recently, the MBOAT7 polymorphism rs641738 was identified as the new risk factor for NAFLD (13Mancina R.M. Dongiovanni P. Petta S. Pingitore P. Meroni M. Rametta R. Boren J. Montalcini T. Pujia A. Wiklund O. et al.The MBOAT7–TMC4 variant rs641738 increases risk of nonalcoholic fatty liver disease in individuals of European descent.Gastroenterology. 2016; 150: 1219-1230 e6Abstract Full Text Full Text PDF PubMed Scopus (382) Google Scholar), also associated with severity of fibrosis in alcoholic liver disease (14Buch S. Stickel F. Trepo E. Way M. Herrmann A. Nischalke H.D. Brosch M. Rosendahl J. Berg T. Ridinger M. et al.A genome-wide association study confirms PNPLA3 and identifies TM6SF2 and MBOAT7 as risk loci for alcohol-related cirrhosis.Nat. Genet. 2015; 47: 1443-1448Crossref PubMed Scopus (324) Google Scholar) and in HCV infection (15Thabet K. Asimakopoulos A. Shojaei M. Romero-Gomez M. Mangia A. Irving W.L. Berg T. Dore G.J. Gronbaek H. Sheridan D. International Liver Disease Genetics Consortium MBOAT7 rs641738 increases risk of liver inflammation and transition to fibrosis in chronic hepatitis C.Nat. Commun. 2016; 7: 12757Crossref PubMed Scopus (81) Google Scholar). Liver biopsy represents the gold-standard method of quantifying the degree of NAFLD (16Chalasani N. Younossi Z. Lavine J.E. Diehl A.M. Brunt E.M. Cusi K. Charlton M. Sanyal A.J. The diagnosis and management of non-alcoholic fatty liver disease: practice guideline by the American Gastroenterological Association, American Association for the Study of Liver Diseases, and American College of Gastroenterology.Gastroenterology. 2012; 142: 1592-1609Abstract Full Text Full Text PDF PubMed Scopus (1310) Google Scholar). Although several noninvasive methods have been developed, liver biopsy represents the only reliable tool to distinguish between nonalcoholic fatty liver and nonalcoholic steatohepatitis. Analysis of liver specimens also provides exact data concerning steatosis, fibrosis, and inflammation. Hence, it is a powerful tool for quantifying the role of inherited predisposition in liver injury. To further elucidate the role of the genetic predisposition in modulation of NAFLD, we performed genetic analyses in a large cohort of patients with fatty liver to analyze the signs of liver injury in combination with the carriage of the PNPLA3 p.I148M, TM6SF2 p.E67K, and MBOAT7 rs641738 variants The frequencies of these variants were related to i) results of liver biopsy, ii) circulating levels of markers of liver injury, and iii) metabolic traits. Analysis of genotype-phenotype interactions performed in this group of patients demonstrated different effects of the PNPLA3, TM6SF2, and MBOAT7 variants on hepatic steatosis and fibrosis, underscoring the notion that they play distinct roles in NAFLD progression. Patients for the study were recruited in eight German university centers within the framework of the NAFLD Clinical Study Group (NAFLD CSG) project (17Weiss J. Rau M. Bantel H. Bock H. Demir M. Kluwe J. Krawczyk M. Pathil-Warth A. Schattenberg J.M. Tacke F. et al.First data concerning the medical supply of patients with non-alcoholic fatty liver disease in Germany: a survey in university hospital centers of hepatology. [Article in German].Z. Gastroenterol. 2015; 53: 562-567PubMed Google Scholar). In brief, the project was started in 2012 as a multicentric study in Germany and was intended to investigate triggers and modulators of NAFLD development, including common genetic variants. All patients gave written informed consent to participate in these studies. The ethical committees at participating centers approved the study protocol. Ethanol intake (>20 g per day for women and >30 g for men) was regarded as exclusion criterion. NAFLD was diagnosed either by imaging techniques (abdominal sonography, MRI, CT) or by liver biopsy. Liver biopsies were performed percutaneously under ultrasound guidance or intraoperatively. Acquired liver samples were evaluated by experienced local pathologists. The presence of acute and chronic liver diseases other than NAFLD was excluded in all patients. All study subjects underwent a standardized clinical examination. Fasted venous blood samples were drawn for routine biochemical analyses, including liver function tests and DNA genotyping. Liver function tests were determined by clinical-chemical assays in the central laboratories of participating centers. In a subgroup of 320 patients with NAFLD with available histology, hepatic steatosis (grades S0–S3) and fibrosis (grades F0–F4) were quantified according to the Kleiner score (18Kleiner D.E. Brunt E.M. Van Natta M. Behling C. Contos M.J. Cummings O.W. Ferrell L.D. Liu Y.C. Torbenson M.S. Unalp-Arida A. Yeh M. McCullough A.J. Sanyal A.J. Design and validation of a histological scoring system for nonalcoholic fatty liver disease.Hepatology. 2005; 41: 1313-1321Crossref PubMed Scopus (7112) Google Scholar). Genotyping of the PNPLA3 (rs738409), TM6SF2 (rs58542926), and MBOAT7 (rs641738) variants was performed in a central laboratory (Homburg) by a technician blinded to the phenotype of patients. DNA was extracted from peripheral blood mononuclear cells using the DNeasy Blood and Tissue Kit (Qiagen). DNA concentrations were measured using a NanoDrop spectrophotometer. All variants were genotyped using TaqMan assays (19Arslanow A. Stokes C.S. Weber S.N. Grünhage F. Lammert F. Krawczyk M. The common PNPLA3 variant p.I148M is associated with liver fat contents as quantified by controlled attenuation parameter (CAP).Liver Int. 2016; 36: 418-426Crossref PubMed Scopus (25) Google Scholar). The fluorescence data were analyzed with allelic discrimination 7500 Software v.2.0.2. Unless stated otherwise, all statistical analyses were performed with SPSS 20.0 (SPSS, Munich, Germany) or GraphPad Prism 5.0 (GraphPad Software Inc., CA). Quantitative data were expressed as medians and ranges. The association between the PNPLA3, TM6SF2, and MBOAT7 variants and markers of liver injury was tested using ANOVA with post hoc tests. Exact tests were performed to check the consistency of genotyping results in with Hardy-Weinberg equilibrium (http://ihg.gsf.de/cgi-bin/hw/hwa1.pl). Genotype frequencies were compared in contingency tables. Power analysis was performed using PS: Power and Sample Size Calculation v.3.0 (http://biostat.mc.vanderbilt.edu/wiki/Main/PowerSampleSize). Differences in anthropometric and clinical traits between patients with PNPLA3 and MBOAT7 genotypes were compared using linear regression analysis under an additive genetic model. Comparisons between carriers of the TM6SF2 genotypes were performed under a dominant genetic model (due to the low number of homozygotes for the 167K mutant allele) using linear regression analysis. All models were adjusted for confounding factors (age, gender, BMI, diabetes mellitus, and statin use, as appropriate). The effects of the studied variants, as well as additional risk factors, on hepatic steatosis and fibrosis were analyzed in univariate and multivariate models using logistic regression analysis. A total of 515 German patients with NAFLD (99.9% white) were recruited. Table 1 summarizes the baseline data of this study cohort, and Table 2 presents the results of liver biopsies in 320 biopsied patients. More women (54%) than men (46%) were included. The median age was 50 years. In 320 patients who underwent liver biopsy, 57% had steatosis grades 2 or 3 (Table 2). Fibrosis stage F2 or higher was present in 30% of patients. Patients undergoing liver biopsy had significantly higher alanine transaminase (ALT) and aspartate aminotransferase (AST) (both P < 0.001) but not γ−glutamyl transferase (GGT) activities (P = 0.26) (Table 1). We did not detect any differences in serum glucose, triglyceride, and cholesterol concentrations between biopsied and nonbiopsied patients (all P > 0.05). Individuals presenting with steatosis grade 2 or 3 had significantly higher serum glucose (P = 0.002) and triglyceride (P = 0.025) concentrations as compared with individuals with lower grades of steatosis (Fig. 1A, B). There were no differences in terms of serum cholesterol in relation to hepatic steatosis (P > 0.05) (Fig. 1C).TABLE 1Baseline characteristics and genotype frequencies in the study cohortVariablesEntire cohortBiopsied patientsN (female/male)515 (280/235)320 (186/134)Age (years)50 (16–88)49 (16–88)BMI (kg/m2)32 (17–70)33 (17–69)ALT (U/l)52 (12–279)58 (13–279)aP < 0.001 as compared with nonbiopsied individuals.AST (U/l)38 (5–397)42 (4–397)aP < 0.001 as compared with nonbiopsied individuals.GGT (U/l)61 (4–1,658)67 (4–1,463)Triglycerides (mg/dl)152 (45–770)154 (49–770)Total cholesterol (mg/dl)204 (72–379)206 (107–379)Glucose (mg/dl)98 (55–367)99 (63–286)Incidence of diabetes type 2 (%)24.726.7Statin use (%)10.610.6TM6SF2 p.E167K genotypes (n)[EE]409253[EK]9761[KK]96PNPLA3 p.I148M genotypes (n)[II]215126[IM]222138[MM]7856MBOAT7 rs641738 genotypes (n)[CC]15998[CT]242157[TT]11465E, glutamic acid; I, isoleucine; K, lysine; M, methionine; MBOAT7, membrane bound O-acyltransferase domain containing 7; p, protein (amino acid number); PNPLA3, patatin-like phospholipase domain-containing protein 3; TM6SF2, transmembrane 6 superfamily member 2. Values are given as medians (ranges), unless stated otherwise.a P < 0.001 as compared with nonbiopsied individuals. Open table in a new tab TABLE 2Distribution of steatosis and fibrosis in biopsied individuals with NAFLDBiopsy resultsDistributionGrade of steatosisaData available for 320 patients.0/148%227%325%Grade of fibrosisbData available for 295 patients.0/170%216%37%47%a Data available for 320 patients.b Data available for 295 patients. Open table in a new tab E, glutamic acid; I, isoleucine; K, lysine; M, methionine; MBOAT7, membrane bound O-acyltransferase domain containing 7; p, protein (amino acid number); PNPLA3, patatin-like phospholipase domain-containing protein 3; TM6SF2, transmembrane 6 superfamily member 2. Values are given as medians (ranges), unless stated otherwise. The PNPLA3 p.I148M, TM6SF2 p.E167K, and MBOAT7 rs641738 variants were successfully genotyped in all patients. The genotype frequencies (Table 1) do not differ from frequencies presented in previous publications and are localized on the Hardy-Weinberg equilibrium parabola (P > 0.05, exact test), which validates the genotyping quality. Relations of the studied variants to patient baseline characteristics are presented in supplemental Table S1 (for PNPLA3 p.I148M), supplemental Table S2 (for TM6SF2 p.E167K), and supplemental Table S3 (for the MBOAT7 rs641738). As presented in the supplemental materials, the PNPLA3 and TM6SF2 variants were significantly associated with BMI (both P = 0.01). We did not detect any significant association between clinical characteristics and the MBOAT7 polymorphism (supplemental Table S3). In the entire cohort (i.e., 515 patients with NAFLD), the PNPLA3 p.I148M polymorphism was associated with increased serum AST (ANOVA, P < 0.001) (Fig. 2A) and ALT (ANOVA, P = 0.002) (Fig. 2B) but not with GGT activities (ANOVA, P = 0.74) (Fig. 2C). Similarly, the TM6SF2 variant was associated with increased AST (P < 0.001) (Fig. 2D) and ALT (P = 0.011) (Fig. 2E) but not with GGT activities (P = 0.14) (Fig. 2F). We did not detect any significant association between the MBOAT7 polymorphism and liver function tests (all P > 0.05) (Fig. 2G–I). We detected a significant (P < 0.0001) increase of serum AST activities with the increment of risk alleles of either of the genotypes (Fig. 3A). We also detected trends for increased ALT (P = 0.08) and GGT (P = 0.07) levels with increasing risk allele number (Fig. 3B, C).Fig. 3Combined analysis of the PNPLA3 p.I148M, TM6SF2 p.E167K, and MBOAT7 rs641738 risk alleles on liver function tests. The graphs demonstrate median AST (A), ALT (B), and GGT (C) by the number of risk alleles in either of the tested genes. Analyses were performed using trend test. The following frequencies of carriers of risk alleles were detected: zero risk alleles, n = 56; one risk allele, n = 142; two risk alleles, n = 170; three risk alleles, n = 117; four risk alleles, n = 27; five risk alleles, n = 3.View Large Image Figure ViewerDownload Hi-res image Download (PPT) We performed separate analysis of the variants' effects on the risk of developing hepatic steatosis and fibrosis in specimens acquired by liver biopsy. Overall, carriers of the PNPLA3 risk allele (P = 0.043), but not TM6SF2 or MBOAT7 variants (both P > 0.05), were more frequently scheduled for liver biopsy. The PNPLA3 polymorphism was significantly associated with the risk of developing steatosis grades S2 and S3 [common odds ratio (OR) = 1.896; P < 0.001] and fibrosis stages F2–F4 (common OR, 2.348; P < 0.001) (TABLE 3, TABLE 4. Analysis of TM6SF2 genotype frequencies (Tables 5 and 6) reveals that this variant was associated with steatosis (common OR, 1.539; P = 0.003) but had no major effects on fibrosis (P > 0.05). Based on the frequency of the minor allele among individuals with fibrosis grade 0.05), it was significantly associated with the development of liver fibrosis (common OR, 1.446; P = 0.046) (Table 7). We also detected an increase in the number of risk PNPLA3, TM6SF2, and MBOAT7 alleles with increasing hepatic fibrosis (supplemental Fig. S1) and most of all steatosis (supplemental Fig. S2). In the univariate model, PNPLA3 and TM6SF2 polymorphisms, but not MBOAT7, were associated with increased steatosis (Table 8). The association remained significant for these two genotypes in the multivariate analysis (Table 8). In the analyses of liver function tests restricted to biopsied patients, the PNPLA3 polymorphism was associated with significantly increased AST (P = 0.013) (supplemental Fig. S3A) but not ALT (P = 0.17) (supplemental Fig. S3B) or GGT (P = 0.13) (supplemental Fig. S3C). Notably, among individuals scheduled for the liver biopsy, the TM6SF2 polymorphism was associated with increased AST (P = 0.005) (supplemental Fig. S3D), ALT (P = 0.025) (supplemental Fig. S3E), and GGT (P = 0.025) (supplemental Fig. S3F). We did not detect any significant association between liver function test and the MBOAT7 polymorphism in biopsied patients (supplemental Fig. S3G-I). Table 9 summarizes the results of regression analyses for factors associated with liver fibrosis in biopsied patients. Of note, in the multivariate model we detect a significant association for PNPLA3 and MBOAT7 genotypes (both P < 0.05) but not for the TM6SF2 polymorphism (P > 0.05).TABLE 3Distribution of alleles and genotypes for PNPLA3 p.I148M and association tests in respect to steatosis gradePNPLA3 p.I148M allele/genotypeCount of alleles/genotypesSteatosis grade <S2 (2N = 306)Steatosis S2–S3 (2N = 334)[I]211 (0.69)197 (0.54)[M]95 (0.31)155 (0.46)[II]73 (0.48)53 (0.31)[IM]65 (0.42)73 (0.44)[MM]15 (0.10)41 (0.25)Association testORP valueArmitage's trend test1.896<0.001OR statisticsOR (95% CI)P value[M] ↔ [I]1.923 (1.391–2.659)<0.001[MM] ↔ [II]3.765 (1.890–7.499)<0.001[MM] ↔ [IM + II]2.994 (1.580–5.671)<0.001[MM + IM] ↔ [II]1.936 (1.246–3.091)0.003I, isoleucine; M, methionine; p, protein (amino acid number); PNPLA3, adiponutrin. [M] represents the steatosis risk allele. Allele and genotype frequency differences were assessed by chi2 test or by Armitage's trend test as appropriate (https://ihg.gsf.de/cgi-bin/hw/hwa1.pl). Open table in a new tab TABLE 4Distribution of alleles and genotypes for PNPLA3 p.I148M and association tests in respect to fibrosis gradePNPLA3p.I148M allele/genotypeCount of alleles/genotypesFibrosis grade <F2 (2N = 410)Fibrosis grade F2–F4 (2N = 180)[I]211 (0.69)197 (0.54)[M]95 (0.31)155 (0.46)[II]95 (0.46)18 (0.20)[IM]83 (0.41)44 (0.49)[MM]27 (0.13)28 (0.31)Association testORP valueArmitage's trend test2.348<0.001OR statisticsOR (95% CI)P value[M] ↔ [I]2.491 (1.740–3.565)<0.001[MM] ↔ [II]5.473 (2.637–11.361)<0.001[MM] ↔ [IM + II]2.977 (1.630–5.439)<0.001[MM + IM] ↔ [II]3.455 (1.925–6.200)<0.001CI, confidence interval; I, isoleucine; M, methionine; p, protein (amino acid number); PNPLA3, adiponutrin. [M] represents the steatosis risk allele. Allele and genotype frequency differences were assessed by chi2 test or by Armitage's trend test as appropriate (https://ihg.gsf.de/cgi-bin/hw/hwa1.pl). Open table in a new tab TABLE 5Distribution of alleles and genotypes for TM6SF2 p.E167K and association tests with respect to steatosis gradeTM6SF2 p.E167K allele/ genotypeCount of alleles/genotypesSteatosis grade <S2 (2N = 306)Steatosis S2–S3 (2N = 334)[E]280 (0.92)287 (0.86)[K]26 (0.08)47 (0.14)[EE]130 (0.85)123 (0.74)[EK]20 (0.13)41 (0.25)[KK]3 (0.02)3 (0.01)Association testORP valueArmitage's trend test1.5390.003OR statisticsOR (95% CI)P value[K] ↔ [E]1.764 (1.063–2.927)0.026[KK] ↔ [EE]1.057 (0.209–5.336)0.946[KK] ↔ [EK + EE]0.915 (0.182–4.601)0.913[KK + EK] ↔ [EE]2.022 (1.153–3.544)0.001CI, confidence interval; E, glutamic acid; K, lysine; p, protein (amino acid number); TM6SF2, transmembrane 6 superfamily member 2. [K] represents the steatosis risk allele. Allele and genotype frequency differences were assessed by chi2 test or by Armitage's trend test as appropriate (https://ihg.gsf.de/cgi-bin/hw/hwa1.pl). Open table in a new tab TABLE 6Distribution of alleles and genotypes for TM6SF2 p.E167K and association tests with respect to fibrosis gradeTM6SF2 p.E167K allele/ genotypeCount of alleles/genotypesFibrosis grade <F2 (2N = 410)Fibrosis grade F2–F4 (2N = 180)[E]366 (0.89)156 (0.87)[K]44 (0.11)24 (0.13)[EE]164 (0.80)68 (0.76)[EK]38 (0.19)20 (0.22)[KK]3 (0.01)2 (0.02)Association testORP valueArmitage's trend test1.2690.370OR statisticsOR (95% CI)P value[K] ↔ [E]1.280 (0.752–2.177)0.362[KK] ↔ [EE]1.608 (0.269–9.838)0.608[KK] ↔ [EK + EE]1.530 (0.251–9.319)0.642[KK + EK] ↔ [EE]1.294 (0.717–2.335)0.391CI, confidence interval; E, glutamic acid; K, lysine; p, protein (amino acid number); TM6SF2, transmembrane 6 superfamily member 2. [K] represents the steatosis risk allele. Allele and genotype frequency differences were assessed by chi2 test or by Armitage's trend test as appropriate (https://ihg.gsf.de/cgi-bin/hw/hwa1.pl). Open table in a new tab TABLE 7Distribution of alleles and genotypes for MBOAT7 rs641738 and association tests in respect to fibrosis gradeMBOAT7 rs641738 allele/genotypeCount of alleles/genotypesFibrosis ade F0 (2N = 206)Fibrosis grade F1–F4 (2N = 384)[C]122 (0.59)194 (0.51)[T]44 (0.41)190 (0.49)[CC]34 (0.33)53 (0.28)[CT]54 (0.52)88 (0.46)[TT]15 (0.15)51 (0.26)Association testORP valueArmitage's trend test1.4460.046OR statisticsOR (95% CI)P value[T] ↔ [C]1.422 (1.010–2.003)0.043[TT] ↔ [CC]2.181 (1.063–4.476)0.031[TT] ↔ [CT + CC]2.122 (0.251–9.319)0.012[TT + CT] ↔ [CC]1.292 (0.770–2.170)0.350CI, confidence interval; p, protein (amino acid number); MBOAT7, membrane bound O-acyltransferase domain containing 7. [T] represents the risk allele. Allele and genotype frequency differences were assessed by chi2 test or by Armitage's trend test as appropriate (https://ihg.gsf.de/cgi-bin/hw/hwa1.pl). Open table in a new tab TABLE 8Risk factors for developing hepatic steatosisFactorOR95% CIP valueUnivariate analysisPNPLA3 p.I148M2.4181.323–4.4190.004TM6SF2 p.E167K4.6221.077–19.8310.039MBOAT7 rs6417381.2600.749–2.1190.384Glucose1.0150.994–1.0370.168BMI0.9660.933–1.0010.055Age (years)1.0050.979–1.0330.692Sex2.0800.933–4.6340.073Presence of diabetes1.2240.504–2.9730.656Triglycerides1.0020.996–1.0070.594Cholesterol0.9970.988–1.0070.539Multivariate analysisPNPLA3 p.I148M2.4241.326–4.4190.004TM6SF2 p.E167K4.7251.093–20.4290.038CI, confidence interval; E, glutamic acid; I, isoleucine; K, lysine; M, methionine; MBOAT7, membrane bound O-acyltransferase domain containing 7; p, protein (amino acid number); PNPLA3, adiponutrin; TM6SF2, transmembrane 6 superfamily member 2. The relationships between steatosis PNPLA3, TM6SF2, and MBOAT7 variants as well as other potentially prosteatotic factors were assessed by univariate and multivariate logistic regression analysis. Genetic analyses were calculated by using either additive (for PNPLA3 and MBOAT7) or dominant (for TM6SF2) models. Open table in a new tab TABLE 9Risk factors for developing hepatic fibrosisFactorOR95% CIP valueUnivariate analysisPNPLA3 p.I148M1.6791.192–2.3670.003TM6SF2 p.E167K1.0600.587–1.9140.846MBOAT7 rs6417381.4101.003–1.9820.048Glucose1.0201.008–1.0330.002BMI0.9890.965–1.0150.413Age (years)1.0201.002–1.0390.027Sex1.0880.671–1.7630.732Presence of diabetes2.0921.136–3.8520.018Triglycerides1.0031.000–1.0070.083Cholesterol0.9970.991–1.0030.314Multivariate analysisPNPLA3 p.I148M1.6761.019–2.7570.042MBOAT7 rs6417381.7661.089–2.8640.021CI, confidence interval; E, glutamic acid; I, isoleucine; K, lysine; M, methionine; MBOA
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