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(Arteriosclerosis, Thrombosis, and Vascular Biology. 2000;20:217.)
© 2000 American Heart Association, Inc.

Atherosclerosis and Lipoproteins

The Private Hepatocyte Nuclear Factor-1 G319S Variant Is Associated With Plasma Lipoprotein Variation in Canadian Oji-Cree

Robert A. Hegele; Henian Cao; Stewart B. Harris; Anthony J. G. Hanley; Bernard Zinman; Philip W. Connelly

	Abstract

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Abstract—We previously showed an extremely strong association between type 2 diabetes and a private polymorphism, namely G319S, in the hepatocyte nuclear transcription factor (HNF)-1. Because HNF-1 is involved in the transcription of several apolipoprotein genes, we tested for an association between the private HNF1A G319S variant and plasma lipoproteins in a sample of 55 unrelated Oji-Cree subjects with type 2 diabetes and 175 unrelated Oji-Cree subjects without type 2 diabetes. In Oji-Cree subjects with type 2 diabetes, we found that the HNF1A G319S genotype was significantly associated with lower plasma concentrations of total cholesterol, low density lipoprotein cholesterol, and apolipoprotein (apo) B. In Oji-Cree subjects without type 2 diabetes, we found that the HNF1A G319S genotype was significantly associated with higher plasma concentrations of high density lipoprotein cholesterol and apo AI. There were no associations with plasma triglycerides or lipoprotein(a). Regression analysis indicated that the HNF1A genotype accounted for 10% of the variation in the apo B–related traits in the diabetic subjects and for 5% of the variation in the apo AI–related traits in the nondiabetic subjects. Furthermore, the regression model indicated that the HNF1A S319 allele affected these traits in a dominant manner in subjects with and without type 2 diabetes. These findings provide the first evidence that a rare variant in a nuclear transcription factor is associated with variation in plasma lipoprotein traits.

Key Words: transcription factors • diabetes • polygenic traits • atherosclerosis

	Introduction

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We previously showed that the Oji-Cree of northern Canada have a private variant in the hepatocyte nuclear transcription factor-1 (HNF1A) gene, namely G319S, which was very strongly associated with early-onset type 2 diabetes mellitus.^{1 2} Subjects with 1 or 2 copies of HNF1A S319 had onset of diabetes 1 or 2 decades earlier, respectively, than did noncarriers.^{1 2} Our findings strongly suggested that HNF1A S319 was a dysfunctional variant that created susceptibility to type 2 diabetes, which then required the presence of a high-fat diet and sedentary lifestyle to be expressed clinically.^{1 2} Other mutations in HNF1A cause a specific, rare form of maturity-onset diabetes of the young, called MODY3.^{3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19} MODY3 is clinically distinct from typical type 2 diabetes and probably results from defective pancreatic insulin secretion.^{3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19} However, the underlying mechanistic relationship with the dysfunctional HNF1A gene product is not fully understood for either MODY3 or type 2 diabetes in the Oji-Cree.^{1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19}

The HNF1A gene has been mapped to chromosome 12q24 and is expressed predominantly in the liver, kidney, and pancreas.^{20 21 22} The HNF1A gene product, HNF-1, is a transcriptional activator of several hepatic genes, including albumin, 1-antitrypsin, and - and ß-fibrinogen.^{21 22} In addition, HNF-1 was shown to enhance transcription of apolipoprotein (apo) B^{23 24 25} and apo(a)²⁶ and to downregulate transcription of apo CIII and apo AI.²⁷ Because it regulates the transcription of several apolipoprotein genes, it is possible that naturally occurring mutations in HNF-1 could affect plasma lipoprotein metabolism. However, there is surprisingly little information regarding the plasma lipoprotein phenotypes in subjects with HNF1A mutations, such as patients with MODY3.²⁸ Because we had determined plasma lipoprotein phenotypes in the Oji-Cree, we could test for an association between the HNF1A G319S genotype and the variation in plasma lipoproteins and apolipoproteins.

	Methods

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Study Subjects
The isolated community of Sandy Lake, Ontario, is located 2000 km northwest of Toronto, in the subarctic boreal forest of central Canada. The ancestors of the contemporary residents of this region lived a nomadic, hunting-gathering subsistence typical of other native peoples of the northeastern subarctic. Since the development of the reservation and residential school systems, the lifestyle changed from very physically active to very sedentary. The primary source of food changed from wildlife with roots and berries to processed foods high in animal fats.

Seven hundred twenty-eight members of this community aged 10 years and older participated in a community-wide screening project to determined the prevalence of type 2 diabetes and associated risk factors.^{29 30 31 32} Subjects answered a questionnaire for medical history. Physical examination included determination of body mass index (BMI) defined as weight/height² (kg/m²). No subject took lipid-lowering medications. A small proportion (3.8%) of subjects were taking antihypertensive medications, which were almost all angiotensin-converting enzyme inhibitors. Blood samples were obtained with informed consent after a 10-hour fasting period. Diabetes was diagnosed according to pre-1997 criteria.³³ Exclusion criteria for the current study included a diagnosis of impaired glucose tolerance³⁴ and/or an inadequate blood sample for all determinations. The project was approved by the University of Toronto Ethics Review Committee.

Biochemical and Genetic Analyses
Blood samples for lipoprotein analyses were centrifuged at 2000 rpm for 30 minutes and the plasma was stored at -70°C. Fasting plasma concentrations of glucose, insulin, lipids, lipoproteins, and apolipoproteins, along with postchallenge glucose, were determined as described.^{1 29 35 36} Restriction analysis with BseDI detected the DNA change underlying the HNF1A G319S amino acid variation.^{1 2}

Statistical Analysis
For this analysis, we studied a subset of Oji-Cree aged 18 years and above who were no more closely related than third-degree relatives to one another. This was done to control for artifacts related to the nonindependence of samples that could have arisen from studying closely related subjects, such as members of the same nuclear family.

The distribution of each lipoprotein variable was significantly nonnormal in this dataset. Therefore, for parametric statistical analyses, each variable was transformed and subjected to analysis of normality. Logarithmically transformed total, LDL, and HDL cholesterol; triglycerides (TGs); apo AI; apo B; and Lp(a) had distributions that were not significantly different from normal. The transformed variables were used for statistical analyses, but the nontransformed values are presented in the Tables.

The significance of deviations of observed genotype frequencies from those predicted by the Hardy-Weinberg equation was evaluated with ² analysis. ² analysis was also used to assess differences in proportions of alleles and genotypes between subjects with and without type 2 diabetes. Estimates of relative risk of type 2 diabetes between genotypes were determined by using Mantel-Haenszel odds ratios.³⁷

ANOVA in SAS version 6.12³⁷ was used to determine whether there were statistically significant differences in quantitative traits between subjects with type 2 diabetes and those without. One ANOVA each was performed for age and BMI by using each as the dependent variable and diabetes status as the only independent variable. One ANOVA each was performed for fasting plasma concentrations of total, LDL, and HDL cholesterol; TGs; apo AI and B; Lp(a); and insulin by using the logarithmically transformed fasting plasma value for each as the dependent variable and diabetes status, age, and BMI as the independent variables.

Multivariate regression analysis in SAS version 6.12³⁷ was used to determine the sources of variation for transformed lipoprotein traits in subjects with and without type 2 diabetes. A forward stepwise regression procedure was used to assist in the model building, with the P value for inclusion set at <0.15. The dependent variables in each regression analysis included transformed fasting plasma concentrations of total, LDL and HDL cholesterol; TGs; apo AI and B; and Lp(a). The independent variables in the model for each analysis included HNF1A genotype, with assumption of a dominant effect on each phenotype. This was done by setting the HNF1A genotype variable at 0 for G319/G319 subjects and at 1 for S319/G319 and S319/S319 subjects. Age, sex, BMI, fasting plasma insulin concentration, and medication use were also used as independent variables.

When a significant genetic contribution to the variation in a biochemical trait was detected for the HNF1A genotype, the general linear models procedure for least-squares means was used to determine the level of significance of differences in pairwise comparisons between genotype classes.³⁷ Least-squares means (also called population marginal means) are the values for class means after adjustment for all covariates included in the model.³⁷ Bonferroni adjustments were made to account for multiple comparisons. For all analyses, the nominal level of statistical significance was taken to be P<0.05.

	Results

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Clinical and Biochemical Features of Study Subjects
The baseline clinical and biochemical attributes of the 55 subjects with type 2 diabetes and the 175 subjects without type 2 diabetes are shown in Table 1. Among the subjects with type 2 diabetes, 44% (24/55) took oral hypoglycemic agents and 7% (4/55) took insulin injections. Subjects with type 2 diabetes had a significantly greater age and BMI than did subjects without type 2 diabetes (both P<0.0001). Among the biochemical traits, after adjustment for age and BMI, only the fasting plasma concentrations of TG and insulin were significantly different between the subjects with and without type 2 diabetes (P=0.0003 and 0.018, respectively).

View this table: [in this window] [in a new window]   Table 1. Baseline Clinical and Biochemical Traits in Unrelated Oji-Cree With and Without Type 2 Diabetes

HNF1A G319S Allele and Genotype Frequencies
In this sample of unrelated Oji-Cree, the HNF1A S319 allele frequency was 0.190 (21/110) in subjects with diabetes and 0.063 (22/350) in subjects without diabetes (²=11.8, P<0.0001). The relative risk of type 2 diabetes was 2.6 (95% confidence interval 1.5 to 4.5) for carriers of at least 1 copy of the HNF1A S319 allele. Among subjects with type 2 diabetes, 37 had the HNF1A G319/G319 genotype, 15 had the S319/G319 genotype, and 3 had the S319/S319 genotype. Among subjects without type 2 diabetes, 153 had the HNF1A G319/G319 genotype, 22 had the S319/G319 genotype, and none had the S319/S319 genotype. Because there were so few HNF1A S319/S319 homozygotes, S319 was treated as a dominant allele for the purposes of subsequent hypothesis testing. Thus, among the subjects with type 2 diabetes, the 3 S319/S319 homozygotes were grouped with the 15 S319/G319 heterozygotes. The HNF1A G319S genotype frequencies in the diabetic and nondiabetic groups did not deviate from Hardy-Weinberg expectations.

Regression Analysis for Sources of Variation in Plasma Lipoproteins
The results of the stepwise multivariate regression analysis in the 55 unrelated Oji-Cree with type 2 diabetes are shown in Table 2. All biochemical traits, except for Lp(a), had at least 1 significantly associated independent variable. The HNF1A G319S genotype was a significant source of variation for log total cholesterol, log LDL cholesterol, and log apo B (P=0.020, 0.007, and 0.029, respectively). In addition, age was significantly associated with log TG, sex was significantly associated with both log HDL cholesterol and log apo AI, and medication use was significantly associated with log HDL cholesterol. Plasma insulin concentration was not significantly associated with any biochemical variable. The proportion of the total variation that was due to HNF1A genotype, as estimated by the partial regression coefficients, was 10%, 14%, and 9% for log total cholesterol, log LDL cholesterol, and log apo B, respectively.

View this table: [in this window] [in a new window]   Table 2. Stepwise Regression Analysis for Sources of Variation in Plasma Lipoproteins in Oji-Cree With Type 2 Diabetes

To determine whether the HNF1A genotype was associated with the variation in LDL composition in the 55 unrelated Oji-Cree with type 2 diabetes, we performed an additional post hoc stepwise multivariate regression analysis. We used the ratio of LDL cholesterol to plasma apo B as the dependent variable. The independent variables in the model for this last analysis included HNF1A genotype, with assumption of a dominant effect on each phenotype as described above. Age, sex, BMI, fasting plasma insulin concentration, and medication use were also used as independent variables. This analysis indicated that the HNF1A G319S genotype was not significantly associated with the LDL cholesterol to apo B ratio (P=0.14). Thus, the HNF1A G319S genotype appeared to be associated with the quantity but not the composition of plasma apo B–containing particles.

The results of the stepwise multivariate regression analysis in the 175 unrelated Oji-Cree without type 2 diabetes are shown in Table 3. All biochemical traits except Lp(a) had at least 1 significantly associated independent variable. The HNF1A G319S genotype was a significant source of variation for log HDL cholesterol and tended to be associated with variation in log apo AI (P=0.042 and 0.07, respectively). In addition, BMI was significantly associated with all variables, age was significantly associated with all variables but log TG, and sex was significantly associated with all variables but log apo AI but tended to be associated with log apo AI (P=0.06). Medication use was significantly associated with log TG. Plasma insulin concentration was not significantly associated with any biochemical variable. The proportion of the total variation due to HNF1A genotype, as estimated by the partial regression coefficients, was 2% each for log HDL and log apo AI.

View this table: [in this window] [in a new window]   Table 3. Stepwise Regression Analysis for Sources of Variation in Plasma Lipoproteins in Nondiabetic Oji-Cree

Biochemical Variables According to HNF1A Genotypes
The clinical and biochemical attributes of the Oji-Cree with type 2 diabetes according to their HNF1A genotypes are shown in Table 4. There was no significant difference in age or BMI between the 2 groups. There were significant differences in total and LDL cholesterol and apo B (all P<0.05). For each variable, the mean concentration was lower in the HNF1A S319 carriers by 10%. There were no significant differences in the remainder of the lipoprotein variables. Also, the mean values for plasma concentrations of fasting and postprandial glucose and fasting insulin were compared between the 2 genotypic classes of diabetic subjects, and no significant differences were found for this study sample (Table 4).

View this table: [in this window] [in a new window]   Table 4. Plasma Lipoprotein Traits in Unrelated Oji-Cree With Type 2 Diabetes According to Genotypes of HNF1A G319S

The clinical and biochemical attributes of the Oji-Cree without type 2 diabetes according to their HNF1A genotypes are shown in Table 5. There was no significant difference in either age or BMI between the 2 groups. There were significant differences in HDL cholesterol and apo AI (both P<0.05). For both variables, the mean concentration was higher in the HNF1A S319 carriers by 5%. There were no significant differences in the remainder of the lipoprotein variables. Also, the mean values for plasma concentrations of fasting and postprandial glucose and fasting insulin were compared between the 2 genotypic classes of diabetic subjects. There was a significantly lower fasting plasma insulin concentration in HNF1A S319/G319 heterozygotes compared with G319/G319 homozygotes (88±30 versus 116±74 U/L, P=0.03) but no other significant differences for this study sample (data not shown).

View this table: [in this window] [in a new window]   Table 5. Plasma Lipoprotein Traits in Unrelated Nondiabetic Oji-Cree According to Genotypes of HNF1A G319S

	Discussion

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In a sample of unrelated Oji-Cree subjects with and without type 2 diabetes, we found significant associations between the private HNF1A G319S polymorphism and variations in plasma lipoprotein concentrations. Specifically, we found (1) lower plasma concentrations of apo B–related traits, namely, total and LDL cholesterol and apo B, in carriers of HNF1A S319 with type 2 diabetes and (2) higher plasma concentrations of apo AI–related traits, namely, HDL cholesterol and apo AI, in HNF1A S319/G319 heterozygotes without type 2 diabetes. There were no associations with plasma TGs or Lp(a). The HNF1A genotype accounted for 10% of the total variation in the apo B–related traits in the subjects with type 2 diabetes. The HNF1A genotype accounted for 5% of the total variation in the apo AI–related traits in the subjects without type 2 diabetes. Furthermore, the regression model indicated that the HNF1A S319 allele had a dominant effect on these traits in Oji-Cree subjects with and without type 2 diabetes. These findings provide the first evidence that a rare variant in a nuclear transcription factor is associated with variations in plasma lipoprotein traits.

The findings in this unrelated Oji-Cree sample confirmed our earlier observation of an extremely strong association of the HNF1A S319 variant with type 2 diabetes.^{1 2} However, among subjects with type 2 diabetes in the current study, there was no significant phenotypic difference between the HNF1A G319S genotype classes in age, BMI, or traits related to glycemia. This suggests that the association of HNF1A S319 with plasma apo B–related traits in subjects with type 2 diabetes was not related to other phenotypic differences between the HNF1A genotype classes.

In contrast, among subjects without type 2 diabetes, there was a significant difference in plasma insulin concentration between the HNF1A G319S genotype classes. In particular, the HNF1A S319/G319 heterozygotes had significantly lower plasma insulin values than did G319/G319 homozygotes. This suggests that the association of HNF1A S319 with plasma apo AI–related traits in subjects without type 2 diabetes might have been related to the between-genotype plasma insulin difference. However, regression analysis indicated that plasma insulin was not a significant determinant of either plasma apo AI or HDL cholesterol in the subjects without type 2 diabetes. This suggests that the relationship between the genotype and the apo AI–related traits in the subjects without type 2 diabetes was not mediated through differences in plasma insulin concentration but possibly through another more direct mechanism.

There are several lines of evidence to indicate that the HNF1A S319 allele encodes a dysfunctional protein product. First and foremost is the genetic evidence. HNF1A S319 is as unique to the Oji-Cree as the sickle cell anemia allele of hemoglobin is to African people.^{1 2} Within the Oji-Cree, we have shown a strong, specific relationship of HNF1A S319 with type 2 diabetes.^{1 2} Subjects with the S319 variant have an increased relative risk of having type 2 diabetes, with odds ratios of 2 and 4 for subjects with 1 and 2 copies of the allele, respectively.^{1 2} The probability values for these associations were <10^-5.^{1 2} Furthermore, there was a strong gene-dosage effect related to the age of onset of type 2 diabetes and other quantitative phenotypes.^{1 2} In addition, the wild-type G319 residue is within the critical proline-rich domain II of the transactivation domain of HNF-1.^{20 21} This residue has been conserved throughout evolution,^{20 21} suggesting that it has an important functional role. We also found no other variant affecting the coding sequence, intron-exon boundaries, or the 5'- and 3'-untranslated regions of HNF1A.^{1 2} These facts taken together support the idea that the HNF1A S319 allele product is dysfunctional.

We are in the process of carrying out in vitro functional experiments to assess whether the HNF1A S319 product loses its ability to regulate gene expression through binding to the cognate HNF-1 recognition sequence. If we could demonstrate that HNF1A S319 has a reduced ability to activate target genes, this could provide a direct mechanistic explanation of the lipoprotein phenotypes. However, it might also be difficult to relate the results of in vitro experiments involving S319, or indeed any other mutation in HNF1A, to the development of diabetes or other in vivo phenotypes. This is because HNF-1 has both wide tissue expression, including the liver and pancreas, and a very wide variety of gene targets.^{19 20} HNF-1 also functions as a dimer,^{19 20} and at least 1 HNF1A mutation appears to act as a dominant-negative because of this.¹⁵ Thus, there are many possible mechanisms through which dysfunctional HNF-1 can lead to abnormal phenotypes. This complexity might cloud any attempt to relate a simple loss of transactivation in vitro to the development of type 2 diabetes.

With the assumption that the HNF1A S319 product is functionally abnormal, how might it produce abnormal lipoprotein phenotypes? The normal actions of HNF-1 include enhancing the transcription of apo B^{23 24 25} and suppressing the transcription of apo AI.²⁷ Thus, in subjects with type 2 diabetes, the lower plasma total and LDL cholesterol and apo B levels would also be consistent with transactivational loss of function of the HNF1A S319 product. Furthermore, in the subjects without type 2 diabetes, the higher plasma HDL cholesterol and apo AI levels would be consistent with a transactivational loss of function of the HNF1A S319 product.

Why would the associations differ in subjects with and without type 2 diabetes? The specificity of the associations might be related to the fundamental metabolic differences between the subjects with and without diabetes. For example, the subjects without type 2 diabetes were significantly younger and leaner and had significantly lower plasma insulin concentrations compared with the subjects with type 2 diabetes. This suggests that the loss of suppression of apo AI gene transcription from HNF-1 S319 is expressed on a metabolic background that is relatively unperturbed. Furthermore, the effect appeared to be lost in the context of the highly perturbed metabolic state of type 2 diabetes. This further suggests that factors other than genetic variation in HNF1A are important determinants of plasma apo AI–related traits in the older and heavier Oji-Cree with type 2 diabetes and high plasma insulin concentration. Thus, HNF1A variation appears to be an important determinant of plasma apo AI–related traits in a relatively unperturbed metabolic context.

A complementary mechanism might explain the association of HNF1A S319 with plasma apo B–related traits in subjects with type 2 diabetes. The subjects with type 2 diabetes were significantly older and heavier and had significantly higher plasma insulin concentrations compared with the subjects without type 2 diabetes. This means that the loss of enhancement of apo B gene transcription from the S319 allele occurred on a metabolic background that was highly perturbed. Furthermore, the effect was not seen in the context of the less-perturbed metabolic state of subjects without type 2 diabetes. This could mean that genetic variation in HNF1A is an important determinant of plasma apo B–related traits on the background of a highly perturbed metabolic context, such as diabetes, obesity, and hyperinsulinemia, and a propensity for hypersecretion of apo B–containing lipoproteins. It may be of some interest that subjects with HNF1A S319 tended to have higher plasma fasting and postchallenge glucose levels (Table 4) but also had lower plasma apo B–related traits, suggesting that the metabolic consequences of worsened glycemia are not the basis for the association with lipoprotein traits. In contrast, variation in HNF1A appears not to be an important determinant of the quantity, but not the composition, of plasma apo B–related traits in a relatively unperturbed metabolic context.

HNF-1 also enhances in vitro transcription of apo(a)²⁶ and suppresses in vitro transcription of apo CIII.²⁷ However, we found no association of HNF1A S319 with either plasma Lp(a) or TGs. One explanation for the absence of these associations is that these traits have more important determinants other than variation in HNF1A in the Oji-Cree.

It is also possible that HNF-1 affects the expression of other gene products that are involved in lipoprotein metabolism. If this were the case, our findings would still be consistent with an influence of genetic variation in HNF1A on plasma lipoproteins, albeit through a different mechanism than modulation of the expression of apo AI and apo B. As always, we cannot rule out the possibility that HNF1A was in linkage disequilibrium with a functional variant of another gene on chromosome 12. However, this possibility may prove to be less likely after completion of studies of an in vitro functional impact of the HNF1A S319 product.

In summary, we have detected associations between plasma lipoproteins and genetic variation in a nuclear transcription factor whose targets include some apolipoprotein genes. There is substantial genetic evidence that HNF1A S319 encodes a dysfunctional variant that leads to type 2 diabetes.^{1 2} The data presented herein suggest that the possible dysfunction of HNF1A S319 can affect lipoprotein metabolism. Furthermore, there appear to be differential effects of the genetic variation in HNF1A on specific lipoprotein phenotypes. The associations appear to depend on the background metabolic state of the study subjects. The results are consistent with a loss of suppression of apo AI and HDL production in the nondiabetic state and with a loss of enhancement of apo B and LDL production in the diabetic state. Mechanistic studies might help to better understand these associations.

	Acknowledgments

 
This work was supported by grants from the National Institutes of Health (DK44597-01) and the Ontario Ministry of Health (No. 04307) (to B.Z. and S.B.H.), the Medical Research Council of Canada (MT13430), the Canadian Diabetes Association, the Heart and Stroke Foundation of Ontario (No. 3628), and the Blackburn Group (to R.A.H.). Dr Hegele is a Career Investigator of the Heart and Stroke Foundation of Ontario (No. 2729). Dr Harris is a Career Investigator of the Ontario Ministry of Health. Mr Hanley is supported by Health Canada through a National Health Research and Development Program Research Training Award. We would like to acknowledge the chief and council of the community of Sandy Lake, the Sandy Lake community surveyors, the Sandy Lake nurses, and the staff of the University of Toronto Sioux Lookout program.

Received March 19, 1999; accepted June 22, 1999.

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