Steatohepatitis/Metabolic Liver Disease
Variant in the glucokinase regulatory protein (GCKR) gene is associated with fatty liver in obese children and adolescents†
Article first published online: 18 DEC 2011
Copyright © 2011 American Association for the Study of Liver Diseases
Volume 55, Issue 3, pages 781–789, March 2012
How to Cite
Santoro, N., Zhang, C. K., Zhao, H., Pakstis, A. J., Kim, G., Kursawe, R., Dykas, D. J., Bale, A. E., Giannini, C., Pierpont, B., Shaw, M. M., Groop, L. and Caprio, S. (2012), Variant in the glucokinase regulatory protein (GCKR) gene is associated with fatty liver in obese children and adolescents. Hepatology, 55: 781–789. doi: 10.1002/hep.24806
Potential conflict of interest: Nothing to report.
- Issue published online: 23 FEB 2012
- Article first published online: 18 DEC 2011
- Accepted manuscript online: 22 NOV 2011 06:29AM EST
- Manuscript Accepted: 7 NOV 2011
- Manuscript Received: 20 SEP 2011
- the American Hearth Association (AHA). Grant Number: 11CRP5620013
- the National Institutes of Health (NIH). Grant Numbers: R01-HD-40787, R01-HD-28016, K24-HD-01464
Recently, the single nucleotide polymorphism (SNP) identified as rs1260326, in the glucokinase regulatory protein (GCKR), was associated with hypertriglyceridemia in adults. Because accumulation of triglycerides in hepatocytes represents the hallmark of steatosis, we aimed to investigate whether this variant might be associated with fatty liver (hepatic fat content, HFF%). Moreover, because recently rs738409 in the PNPLA3 and rs2854116 in the APOC3 were associated with fatty liver, we explored how the GCKR SNP and these two variants jointly influence hepatosteatosis. We studied 455 obese children and adolescents (181 Caucasians, 139 African Americans, and 135 Hispanics). All underwent an oral glucose tolerance test and fasting lipoprotein subclasses measurement by proton nuclear magnetic resonance. A subset of 142 children underwent a fast gradient magnetic resonance imaging to measure the HFF%. The rs1260326 was associated with elevated triglycerides (Caucasians P = 0.00014; African Americans P = 0.00417), large very low-density lipoprotein (VLDL) (Caucasians P = 0.001; African Americans, P = 0.03), and with fatty liver (Caucasians P = 0.034; African Americans P = 0.00002; and Hispanics P = 0.016). The PNPLA3, but not the APOC3 rs2854116 SNP, was associated with fatty liver but not with triglyceride levels. There was a joint effect between the PNPLA3 and GCKR SNPs, explaining 32% of HFF% variance in Caucasians (P = 0.00161), 39.0% in African Americans (P = 0.00000496), and 15% in Hispanics (P = 0.00342). Conclusion: The rs1260326 in GCKR is associated with hepatic fat accumulation along with large VLDL and triglyceride levels. GCKR and PNPLA3 act together to convey susceptibility to fatty liver in obese youths. (Hepatology 2012)
Triglyceride (TG) accumulation in the liver is the earliest hallmark of nonalcoholic fatty liver disease (NAFLD), which has emerged as the most common cause of chronic liver disease in pediatrics.1, 2 The mechanisms underlying hepatocellular accumulation of TG and its relationship to lipotoxicity are not entirely clear. Recent studies have started to unravel the genetic underpinnings that convey susceptibility to NAFLD. In particular, a common missense variant (rs738409), characterized by a C-to-G substitution encoding an isoleucine-to-methionine substitution at amino acid position 148 (I148M), in the patatin-like phospholipase 3 (PNPLA3) gene has been repeatedly associated with hepatic TG accumulation, hepatocellular injury, and progression of NAFLD in adults.3, 4 This observation has been replicated in children as well.5, 6 More recently, two single nucleotide polymorphisms (SNPs) in the promoter region of the gene encoding apolipoprotein C3 (APOC3), rs2854116 and rs2854117, have been found to be associated with fatty liver in a group of healthy Asian Indian men.7
Given the essential role that hepatic TG accumulation has in the development of NAFLD, we hypothesized that a common gene variant associated with hypertriglyceridemia might also affect hepatic TG accumulation. We began our search by focusing on a SNP (rs1260326) in the glucokinase regulatory protein (GCKR) gene, previously associated with TG levels in genome-wide association studies (GWAS).8, 9 The GCKR gene product, the glucokinase regulatory protein (GCKRP), regulates glucokinase (GCK) activity competitively with respect to the substrate glucose10, 11 inhibiting GCK activity.12 The rs1260326 is a functionally relevant SNP consisting of a C to T substitution coding for a proline-to-leucine substitution at position 446 (P446L). Clues to the molecular mechanisms driving the association of this variant with high TG levels come from detailed kinetic studies of the human recombinant GCKRP.13 It has been demonstrated that the GCKRP L466 variant results in a protein that has reduced regulation by physiological concentrations of fructose 6 phosphate, thus resulting indirectly in a constant increase in GCK activity. The increased GCK activity in the liver is predicted to enhance the glycolytic flux, thus promoting hepatic glucose metabolism and elevating the concentrations of malonyl coenzyme A (CoA), a substrate for de novo lipogenesis (DNL), which may account for about 26% of fat accumulation in the liver.14 The increase in malonyl CoA will then lead to the inhibition of carnitine-palmitoyl, which in turn blocks fatty acid oxidation.13 Moreover, very recently Speliotes et al.15 have shown that the nonfunctional GCKR rs780094 variant, which is in strong linkage disequilibrium with rs1260326, is associated with hepatic fat content in adult samples of European descent. Based on these premises, in the present study we aimed to determine whether the rs1260326 GCKR gene variant might be associated, along with high TGs, also with hepatic fat accumulation, and to explore the joint effect from the GCKR rs1260326 variant and SNPs previously associated with hepatic fat accumulation in PNPLA3 and APOC3. Moreover, given the potential role of the studied SNPs in TG metabolism, we aimed also to explore whether these three SNPs were associated with large very low-density lipoprotein (VLDL) levels.
Patients and Methods
We studied 455 obese children and adolescents (181 Caucasians, 139 African Americans, and 135 Hispanics; mean age 12.8 ± 2.9 years; mean z-score body mass index [BMI] 2.32 ± 0.51) from the New Haven, Connecticut, area, recruited through the Yale Pediatric Obesity Clinic. Caucasians tended to be older (13.4 ± 2.94 years) than African Americans (12.9 ± 2.83 years) and Hispanics (12.0 ± 2.97 years) (P = 0.002), whereas African Americans tended to show a higher z-score BMI (2.32 ± 0.60) than Caucasians (2.23 ± 0.55) and Hispanics (2.12 ± 0.89) (P = 0.056). Forty-six Caucasians (31 girls), 31 African Americans (22 girls), and 37 Hispanics (23 girls) showed impaired glucose tolerance (IGT), whereas 12 Caucasians (seven girls), 20 African Americans (six girls), and 10 Hispanics (seven girls) showed type 2 diabetes. The prevalence of subjects showing IGT or type 2 diabetes did not differ among the groups (P = 0.15).
The study was approved by the Yale University Human Investigation Committee. Parental informed consent and child assent were obtained from all participants.
Genomic DNA was extracted from peripheral blood leukocytes. Genotyping for GCKR rs1260326 was performed with the use of a matrix-assisted laser desorption-ionization time of flight mass spectrometry on the MassArray platform (Sequenom). To assess the nature of genetic variation across ethnic groups at GCKR and its relationship to the carriers of the functional T-allele at rs1260326 we analyzed multi-SNP haplotypes at the GCKR gene. We genotyped seven more SNPs extending across the 25KB GCKR gene using the Sequenom MassArray (compact) system. Details are shown in the excel Supporting file.
The PNPLA3 rs738409 variant was genotyped by automatic sequencing as reported.5 The SNPs in or around the APOC3 gene, rs2854116, and rs2854117 belongs to a larger linkage disequilibrium block spanning the APOA5/APOA4/APOC3/APOA1 gene region on chromosome 11 and are reported to be in linkage disequilibrium.16 Thus, only rs2854116 was genotyped and used to test the associations. Further information concerning the genotyping is provided as Supporting Material.
All metabolic studies were done at the Yale Center for Clinical Investigation (YCCI) at 8.00 AM following a 10 to 12-hour overnight fast.
A standard oral glucose tolerance test (1.75 g/kg body weight, up to 75 g) was performed on all subjects. The Whole Body Insulin Sensitivity index (WBISI) was used to determine insulin sensitivity.
Imaging studies were performed in a subgroup of 142 subjects (67M/75F, 45C/45AA/52H, mean age 12.5 ± 2.6 years; mean z-score BMI 2.22 ± 0.70). Ninety showed a normal glucose tolerance (NGT), 46 showed IGT and six showed type 2 diabetes. This subgroup did not differ from the main cohort for age, sex, race, z-score BMI, and glucose tolerance. Details about the abdominal magnetic resonance imaging studies are provided in Supporting Materials and Methods section.
Plasma glucose was determined using a glucose analyzer by the glucose oxidase method (Beckman Instruments, Brea, CA). Plasma insulin was measured by the Linco RIA, lipid levels using an Auto-Analyzer (model 747-200), liver enzymes, using standard automated kinetic enzymatic assays. To measure large VLDL fasting plasma samples were taken and analyzed utilizing a 400 MHz proton nuclear magnetic resonance analyzer at Liposcience (Raleigh, NC).
The chi-square test was used to assess whether the genotypes were in Hardy-Weinberg equilibrium and to test differences in genotype distribution among different ethnic groups. Prior to analyzing the data all the variables were tested for normality, with nonnormally distributed variables log-transformed to be better approximated by normality, except for hepatic fat content (HFF%), for which a square root transformation was used. Within each ethnic group the association between the genotypes and quantitative traits was evaluated by coding the genotype with an additive model of inheritance, i.e., the genotype is coded with 0, 1, or 2 corresponding to the number of minor alleles carried by each individual; age, sex, z-score BMI, and glucose tolerance status were used as covariates when appropriate.
The partial correlation coefficients (r2) were used to evaluate the degree of variance explained by the genotype and to determine the combined effect of the GCKR and PNPLA3 variants on HFF%. The interaction between two genetic markers was evaluated by adding an interaction term between the two genotypes in a regression model. Unless otherwise specified, for all the data raw means and standard deviations are shown. The power analysis to evaluate whether our dataset was able to distinguish differences in our primary outcomes (TGs, large VLDL, and HFF%) among the genotypes was performed in Quanto, assuming a gene-only effect. Data concerning the power calculations is provided as Supporting Material. A logistic regression was used to assess the odds of showing the metabolic syndrome as defined by Cook et al.17 by GCKR genotype merging all the ethnic groups.
The GCKR SNP rs1260326 minor allele (T) frequency was 0.446 in Caucasians, 0.129 in African Americans, and 0.355 in the Hispanics (P-value for population differences in allelic frequency <0.0001).
The frequency of the PNPLA3 rs738409 minor allele (G) was 0.266 in Caucasians, 0.170 in African Americans, and 0.417 in the Hispanics (P-value for population differences in allelic frequency <0.0001).
The frequency of the APOC3 rs2854116 C allele was 0.371 in Caucasians, 0.692 in African Americans, and 0.394 in the Hispanics (P-value for population differences in allelic frequency <0.0001). The allele frequencies were consistent with those shown in similar ethnic groups in the Allele Frequency Database (ALFRED, http://alfred.med.yale.edu) as well as in HAPMAP (http://hapmap.ncbi.nlm.nih.gov/). Within each ethnic group there was no evidence against the null hypothesis that the genotype distribution was in Hardy-Weinberg equilibrium for all of the variants (all P > 0.05).
GCKR Haplotypes and Frequencies
We also analyzed eight SNP haplotypes extending across the 25-kb GCKR gene in 10 HAPMAP populations and in our three local populations. (The details of these haplotype analyses can be found in the Supporting Materials and in the Supporting excel file.) We found 52 haplotypes with estimated frequencies across these populations and 13 of the 52 carry the functional T-allele. However, a relatively simple underlying pattern prevails in that the nine non-African populations have just one common haplotype that accounts for 93% to 98% of the T-alleles, whereas in the four African populations the same haplotype accounts for 38% to 85% of the individuals carrying the T-allele. In the three studied populations 85% to 94% of the functional T-alleles present are carried on the same common haplotype background at GCKR. Although we acknowledge that the heterogeneity in nearby regulatory variants could, of course, still exist, the remarkable predominance of this one haplotype background at GCKR accounting for carriers of the functional T-allele provides some assurance of the relative genetic homogeneity of the GCKR effects observed in the three populations studied.
Because the analyses we report here primarily involve functional variation at the GCKR gene, we have not carried out analyses estimating and correcting for background population stratification effects that might be present and that are of special concern when trying to understand the validity of associations based on nonfunctional SNPs.
Anthropometrics and Metabolic Phenotypes by Genotype
GCKR rs1260326 (Table 1).
Within each ethnic group there were no differences among the genotypes for age, glucose tolerance status, BMI, z-score BMI, and percent body fat (Table 1). In the Hispanic sample, subjects homozygous for the minor allele showed a higher percentage of girls than boys (P = 0.032), but this was no longer significant after adjustments for multiple comparisons.
|CC (56)||CT (90)||TT (35)||P||CC (104)||CT/TT (34/1)||P||CC (58)||CT (58)||TT (19)||P|
|Body Fat (%)||430±10.4||42.3±8.3||42.6±6.9||0.9||45.9±10.4||45.7±9.0||0.9||39.6±10.9||41.4±9.8||45.1±5.3||0.1|
|Glucose and insulin levels|
|Fasting glucose* (mg/dL)||93.0±10.9||94.6±10.1||93.1±8.5||0.5||96.0±11.8||93.5±8.4||0.3||97.0±9.6||94.4±9.9||91.8±6.9||0.1|
|Glucose 120* (mg/dL)||125.7±31.1||130.2±33.7||134.0±30.4||0.4||131.3±35.8||127.5±26.4||0.6||131.4±27.8||122.2±20.4||135.1±37.9||0.1|
|Fasting insulin* (μU/mL)||39.3±28.6||31.9±16.3||30.4±14.1||0.1||39.0±22.4||35.9±18.7||0.5||37.2±21.5||33.2±22.5||40.9±22.4||0.4|
We did not observe any difference in fasting glucose, fasting insulin, 2 hours glucose, and insulin sensitivity (WBISI) among the genotypes in any of the ethnic groups (Table 1).
Subjects homozygous for the T allele of the GCKR rs1260326 showed higher TG levels than the other genotypes independently of age, gender, z-score BMI, and glucose tolerance (Fig. 1). The GCKR variant explained 8.12% of TG variance in Caucasians (P = 0.00014) and 6.4% in African Americans (P = 0.00417). The differences in TG levels remained statistically significant after adjusting for age, gender, z-score BMI, and glucose tolerance (Caucasians adjusted P = 0.0012; African Americans adjusted P = 0.0048).
In Caucasian and African American groups, subjects homozygous for the T allele showed higher levels of large VLDL (P = 0.017 and 0.0016, respectively) than subjects carrying the other genotypes (Fig. 1); in Hispanics, although not statistically significant (P = 0.28), the same trend for the total and the large VLDL levels was observed (Fig. 1). The P-value after adjusting for age, gender, z-score BMI, and glucose tolerance was P = 0.036 for Caucasians and P = 0.0010 for African Americans.
Moreover, subjects homozygous for the T allele had a higher prevalence of the metabolic syndrome as defined by Cook et al.20 (CC = 39.5%; CT = 43.2%; TT = 51.9%. chi-square = 6.38, P = 0.0115) and they also had two times higher odds of showing the features of metabolic syndrome than CC homozygotes (odds ratio [OR] 2.461; 95% confidence interval [CI]: 1.131-5.033, P = 0.0181) after adjustment for age, gender, ethnicity, z-score BMI, and glucose tolerance.
PNPLA3 rs738409 (Supporting Table 1).
The three genotype groups were similar in terms of age, gender, z-score BMI in all the ethnic groups as well as for the other variables listed in Supporting Table 1. As previously reported,3 we did not observe any difference in terms of insulin resistance as measured as WBISI. Subjects homozygous for the minor allele tended to show higher alanine aminotransferase (ALT) levels, but the difference among genotypes was not statistically significant.
APOC3 rs2854116 (Supporting Table 2).
The three genotype groups were similar in all three ethnic groups for age, gender, and z-score BMI. No differences in liver enzymes, fasting glucose and insulin, 2-hour glucose, or WBISI were observed among the APOC3 genotypes. The African Americans carrying the C allele of the APOC3 variant showed a significant reduction in plasma TG levels (P = 0.010) (Fig. 1).
Association Between GCKR rs1260326 and PNPLA3 rs738409 and HFF%
The GCKR rs1260326 was associated with higher hepatic fat content in all the ethnic groups (Fig. 2). The GCKR variant explained 9.2% of the HFF% variance in Caucasians (P = 0.036), 32.5% of variance (P = 0.00002) in African Americans, and 10.4% of variance in Hispanics (P = 0.016). After adjusting for age, gender, z-score BMI, and glucose tolerance this association between the GCKR rs1260326 variant and HFF% showed a P-value of 0.000221 and 0.0159 in African Americans and Hispanics, respectively. Although in Caucasians the association was not significant any more under an additive model after adjusting for the covariates (P-value 0.16), when we tested the recessive inheritance model, which seemed to fit better in this group given the HFF% distribution across the genotypes, after adjusting for the covariates the P-value was 0.0279.
For the PNPLA3 variant, subjects carrying the minor (G) allele showed higher hepatic fat content in all the ethnic groups (Fig. 2). The PNPLA3 variant explained 29.7% of the HFF% variance in Caucasians (P = 0.00009), 6.8% in African Americans (P = 0.0044), and 5.8% in Hispanics (P = 0.0490). This association was statistically significant after adjustment for age, gender, z-score BMI, and glucose tolerance in Caucasians (P = 0.00039) and African Americans (P = 0.00866), the same trend was still observed in Hispanics (P = 0.09).
When we tested the joint effect of the two variants, we could explain 32% of the variance of HFF% in Caucasians (P = 0.00161), 39.0% in African Americans (P = 0.00000496), and 15% in Hispanics (P = 0.00342) (Fig. 3).
There was no association between the APOC3 gene variants and the HFF% in any of the three ethnic groups (Caucasians P = 0.118; African Americans P = 0.804; Hispanics P = 0.488) (Fig. 2).
Because the GCKR and PNPLA3 SNPs were significantly associated with HFF%, we evaluated whether there was any interactive effect between the two variants in each of the three ethnic groups. No statistically significant interaction was observed between these two variants (Caucasian P = 0.773; African American P = 0.194; Hispanic P = 0.826).
Association Between GCKR rs1260326 and PNPLA3 rs738409 with Fatty Liver.
In the present study we found that the minor allele of the GCKR rs1260326 is associated with fatty liver and with higher serum TGs and large VLDL levels in obese children and adolescents. This association was evident in all three ethnic groups studied and it was independent of age, gender, z-score BMI, and glucose tolerance.
Moreover, we replicated the association between the PNPLA3 rs738409 and HFF% previously described in a small group of children and adolescents.5 We were not able to replicate the association between APOC3 rs2854116 variant and fatty liver reported in male Asian Indian adults by Petersen et al.7
These findings are in agreement with those very recently published by Speliotes et al.15 In that study, based on meta-analysis of GWAS in adult samples of European descent, the authors identified five variants including the GCKR rs780094, which is in strong linkage disequilibrium with rs1260326 examined in this study. Interestingly, Speliotes et al. reported that the variance for HFF% explained by PNPLA3 and GCKR SNPs are 0.2% and 2.41% respectively, whereas the variance for HFF% observed for Caucasians in our study was 9.2% for GCKR rs1260326 and 29.7% PNPLA3 rs738409. This remarkable difference may be due to the fact that our study population is composed exclusively of obese youths. Among obese youths the effect size of each variant on the phenotype may be more pronounced than in adults because of the lack of confounding environmental factors (e.g., alcohol, etc.) that may mask or attenuate the gene variant effect. Furthermore, obese youths showing clinical features once believed to be exclusive of adulthood may be a “genetically enriched” population in which the effect common variants on the phenotype may be more pronounced.
We also observed an additive effect between the GCKR variant and the PNPLA3 rs738409 on HFF%. In fact, the additive effect of these variants explained about 32% of HFF% variance in Caucasians, 39% in African Americans, and 15% in Hispanics. The lower additive effects in Hispanics, the ethnic group with the highest prevalence of hepatic steatosis, suggests that some other genetic or environmental risk factors might account for the majority of their variance in liver fat content.
What is the mechanism by which the rs1260326 GCKR minor allele might lead to hepatic fat accumulation? A recent study has shown that the leucine in position 446 in the GCKRP protein confers a reduced capability to respond to fructose 6 phosphate, resulting indirectly in a constant increase in GCK activity in the liver,13 which leads to higher glycolytic flux and hence increasing the glucose uptake by the liver. The increased glycolysis would raise the levels of malonyl CoA, which in turn may favor the increase in TG levels through two different mechanisms either by serving as a substrate for DNL or by inhibiting carnitine-palmitoyl transferase-1, thus blocking fatty acid oxidation.13 The increase in large VLDL that we observed is actually consistent with this pathway. The increase of large VLDLs, which represent the youngest VLDL, may be probably due to both an increased synthesis of TGs into the liver as a consequence of an increased DNL, whose contribution to the accumulation of fat into the liver in obese adults is well established,14 and a reduced beta oxidation.
The mechanism by which the PNPLA3 variant leads to hepatic fat accumulation is still unclear. Although previous studies suggested that this variant may cause a gain of function of the protein, which would act as a lipogenic factor,18-21 more recent observations support the hypothesis that PNPLA3 plays a role in hydrolysis of glycerolipids and thus that the rs738409 variant causes a loss of this function.22
Association Between GCKR rs1260326 and TGs.
Along with the increase of liver fat content and TG levels, subjects carrying the T allele showed larger VLDL size and a greater prevalence of the metabolic syndrome. Thus, this phenotype might suggest that rs1260326 SNP increases the future cardiovascular risk in these obese children and adolescents. Recent studies in two large adult populations have shown that although the rs1260326 SNP is clearly associated with high TG levels, it does not seem to be associated with an increased risk to develop myocardial infarction and ischemic heart disease.23, 24 In only one study, an association between the rs1260326 minor allele and an increased intima-media thickness in a group of 455 subjects with metabolic syndrome was observed,25 whereas the association between rs780094, which is in strong linkage disequilibrium with rs1260326, was not observed in a large group of patients enrolled in the ARIC study.26 Thus, whether the rs1260326 variant confers an increased risk to develop cardiovascular disease in the long term is still unclear. Considering that subjects homozygous for the T allele also have fatty liver, as indicated by the elevated hepatic fat content fraction, makes the whole scenario even more complex. Indeed, hepatic steatosis per se is a strong risk factor for insulin resistance in both adults and children27 and it is associated with an adverse cardiovascular lipoprotein profile.28 Moreover, recent reports have clearly shown that nonalcoholic fatty liver disease (NAFLD), of which steatosis represents the first step, in overweight and obese children is associated with multiple cardiovascular risk factors29 and that children with NAFLD may develop endstage liver disease with the consequent need for liver transplantation.2 How might we explain that an SNP that causes an increase in TG levels and hepatic fat accumulation does not seem to be associated with long-term adverse cardiovascular risk? The answer may lie in the effect of rs1260326 on glucose metabolism. As stated earlier, the P446L variant is predicted to cause a permanent increase of GCK activity leading to an increase in glycolysis, which in turn will cause a lowering of plasma glucose. Several studies have, in fact, shown that subjects homozygous for the GCKR rs1260326 minor allele have lower plasma glucose levels, lower serum insulin, and lower homeostasis model assessment of insulin resistance (HOMA-IR) than the other genotypes. With these observations in mind, one could speculate that the beneficial effect of the GCKR rs1260326 on insulin resistance would balance out the increase in TGs and in general the adverse cardiovascular profile.
In the present study we did not observe any effects of the variants on glucose or insulin levels in the different ethnic groups. This finding is in agreement with a recent meta-analysis of over 6,000 children by Barker et al.,30 who have shown a lower effect estimates of the GCKR rs780094 (which is in strong linkage disequilibrium with rs1260326) on the glucose levels than that seen in adults. Thus, the possibility exists that association of these variants with glucose might increase with age.30
Lack of Association Between APOC3 rs2854116 and Hepatic Fat Content.
Consistent with recent reports,31-33 but in contrast with the study of Petersen et al.,7 we did not observe any association between the APOC3 variant and fatty liver. The lack of an association between the APOC3 genotype and the hepatic fat content may be due to the different ethnic background of the studied groups. Moreover, the effect of the APOC3 variant seems to be driven by insulin resistance,7 but our population was composed by obese children and adolescents all of whom show some degree of insulin resistance. Thus, the presence of obesity induced insulin resistance may mask the effect of the APOC3 variant on hepatic fat accumulation, thus explaining the difference between studies.
We are aware that this study has some limitations. The small sample size represents probably the main pitfall of the study, raising the possibility of false-negative results. Moreover, the lack of histological data did not allow us to explore whether rs1290329 might be implicated in the progression of liver damage and in particular in the development of a clinically relevant state such as liver fibrosis. This latter, indeed, does not depend only on liver fat accumulation, but on other factors such as insulin resistance, that may play a pivotal role in its development.34
In conclusion, the rs1260326 SNP in the GCKR gene is associated with hepatic fat accumulation and particle size of VLDL. These results suggest that the GCKR variant may lead to hepatic fat accumulation through an increased hepatic TG production. The presence of both the GCKR and PNLPA3 genetic variants act together to confer susceptibility to fatty liver in obese youths.
- 8Diabetes Genetics Initiative of Broad Institute of Harvard and MIT, Lund University, and Novartis Institutes of BioMedical Research, , , , , , , et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science 2007; 316: 1331-1336.
Additional Supporting Information may be found in the online version of this article.
|HEP_24806_sm_SuppTab1.doc||50K||Supporting Table 1. Clinical Characteristics of the subjects stratified by ethnicity and PNPLA3 rs738409 genotype|
|HEP_24806_sm_SuppTab2.doc||52K||Supporting Table 2. Clinical Characteristics of the subjects stratified by ethnicity and APOC3 genotype|
Please note: Wiley Blackwell is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.