Low-Frequency Genetic Variant in the Hepatic Glucokinase Gene Is Associated With Type 2 Diabetes and Insulin Resistance in Chinese Population

Glucokinase (GCK) is a hexokinase isozyme that catalyzes glucose to glucose-6-phosphate (G6P), the first step of both glycolysis and glycogen synthesis. GCK is predominantly expressed in hepatocytes and pancreatic β-cells with different isoforms. The liver isoform plays a central role in regulating glucose uptake and controlling glycogen synthesis, breakdown, and storage (1).

In our previous study (2), we observed that the minor allele frequency (MAF) (0.026) of single nucleotide polymorphism (SNP) rs13306393 in patients with type 2 diabetes (T2D) had an increasing trend in a Chinese population, which had not been evaluated in genome-wide association studies (3–5). Moreover, this SNP is located at the intron near exon 1b, which is exclusively expressed in liver. It would give us a good human genetic model to study the effects of abnormal liver GCK on glucose metabolism.

Thus, we hypothesized that this low-frequency variant of GCK could increase susceptibility for T2D in the Chinese population by specifically affecting the transcription of hepatic GCK. We also evaluated the association of rs13306393 with T2D and prediabetes in a Chinese population.

All subjects aged 25–75 years were from a population-based study of T2D and metabolic syndrome in a rural region of Beijing (Pinggu), China. As previously described (6), this study was performed from March 2012 to May 2013 using two-stage stratified random cluster sampling. All patients with diabetes in sample 1 were screened for the variants of GCK exons, and seven subjects with GCK-maturity-onset diabetes of the young were excluded (2). A 75-g oral glucose tolerance test (OGTT) was performed for the subjects without a history of diabetes, and hemoglobin A_1c (HbA_1c) (reference range 4.0–6.0% [20–42 mmol/mol]) was determined for each subject. A total of 537 subjects with diabetes (fasting plasma glucose [FPG] ≥7.0 mmol/L, 2-h postload plasma glucose [2hPG] ≥11.1 mmol/L, HbA_1c ≥6.5% [48 mmol/mol], or previously diagnosed diabetes), 768 subjects with prediabetes (6.1 mmol/L ≤ FPG < 7.0 mmol/L, 7.8 mmol/L ≤ 2hPG < 11.1 mmol/L, or 6.0% [42 mmol/mol] ≤ HbA_1c < 6.5% [48 mmol/mol]), and 1,912 control subjects were included in the study (Table 1).

All the subjects were recruited from Peking University People’s Hospital in Beijing or nearby communities from October 2006 to December 2018 as the validation cohort. A total of 3,896 subjects with diabetes (FPG ≥7.0 mmol/L, 2hPG ≥11.1 mmol/L, HbA_1c ≥6.5% [48 mmol/mol], or previously diagnosed diabetes), 2,301 subjects with prediabetes (6.1 mmol/L ≤ FPG < 7.0 mmol/L, 7.8 mmol/L ≤ 2hPG < 11.1 mmol/L, or 6.0% [42 mmol/mol] ≤ HbA_1c < 6.5% [48 mmol/mol]), and 868 control subjects were included in sample 2 (Table 1). Of these, 599 control subjects and 464 subjects with prediabetes had no HbA_1c results and were classified only according to FPG or 2hPG.

This study was performed in accordance with the tenets of the Declaration of Helsinki and was approved by the institutional review board at Peking University People’s Hospital. Written informed consent was obtained from all subjects.

OGTT was performed in the morning after >8 h of fasting. Creatinine; FPG; total, HDL, and LDL cholesterol; triglycerides (TGs); and uric acid were examined using an automated biochemical instrument. Insulin was measured by electrochemiluminescence immunoassay. HbA_1c was quantified by high-performance liquid chromatography. HOMA was used to evaluate β-cell function and insulin sensitivity (7). The urinary albumin-to-creatinine ratio (ACR) was determined by C311 analyzer.

In total, 2,468 subjects in sample 1, as described in our previous study (2), underwent Sanger sequencing analysis. The remaining of sample 1 and all sample 2 subjects were genotyped by a TaqMan allelic discrimination assay (primers shown in Supplementary Table 1). Ninety-eight samples with the A allele and 246 samples without the A allele were verified by Sanger sequence; the coincidence rate was 100%. The genotype frequencies in both samples were in accordance with Hardy-Weinberg equilibrium.

Two reporters, including the SNP and the hepatic GCK (NM_033507) promoter (8) (GCK_{Liver-promoter-Luc-rs13306393T} and GCK_{Liver-promoter-Luc-rs13306393A}), were constructed (shown in Supplementary Fig. 1). Because the transfection efficiency of the human hepatocellular carcinoma HepG2 cell line and normal liver L-02 cell line was too low to be used for luciferase reporter assay in our study, HEK-293T cells had to be used. The transfected HEK-293T cells with GCK_{Liver-promoter-Luc-rs13306393T} or GCK_{Liver-promoter-Luc-rs13306393A} construct were harvested and assayed for luciferase activity. Each transfection experiment was carried out in triplicate on at least three independent occasions.

Statistical analysis was performed using SPSS version 23.0 software. Differences in allele and genotype frequencies were analyzed using Pearson χ² test. Logistic regression analysis was performed to calculate MAF-specific odds ratios (ORs) with 95% CIs. Quantitative trait association analyses were performed using multiple linear regressions. The Genetic Power Calculator (https://zzz.bwh.harvard.edu/gpc) from Harvard University was used for power calculations.

All data sets of this article are available from the corresponding authors upon request.

As shown in Table 2, the allele and genotype distributions between the subjects with T2D or impaired glucose regulation (IGR) and control subjects were significantly different. Logistic analysis showed that the A allele of rs13306393 was associated with T2D (OR 3.076 [95% CI 1.766–5.358], P = 0.000072) or IGR (1.836 [1.132–2.976], P = 0.014), but there was no association with prediabetes (1.131 [0.602–2.125], P = 0.702).

Since the subjects with an HbA_1c level of 5.7–6.0% (39–42 mmol/mol) carried the same risk of developing diabetes over 5 years of follow-up as those with impaired fasting glucose (9), we reclassified 281 subjects with 5.7% (39 mmol/mol) ≤ HbA_1c < 6.0% (42 mmol/mol) in 1,912 control subjects as prediabetes and reanalyzed the data. The ORs were 2.655 (95% CI 1.489–4.734) for T2D (P = 0.001), 0.726 (0.390–1.350) for prediabetes (P = 0.312), and 1.265 (0.777–2.059) for IGR (P = 0.345).

As shown in Table 2, the carrier of the A allele had a higher risk for prediabetes irrespective of age, sex, and BMI (OR 1.668 [95% CI 1.048–2.654], P = 0.031) in sample 2. In a pooled analysis of two case-control samples, the A allele carrier was also associated with T2D (1.570 [1.148–2.145], P = 0.005), prediabetes (1.833 [1.325–2.537], P = 0.000255), and IGR (1.681 [1.258–2.245], P = 0.000439).

When we reclassified 46 subjects with HbA_1c 5.7–6.0% (39–42 mmol/mol) in 868 control subjects as prediabetes in sample 2, the association of the A allele with prediabetes remained significant (OR 1.735 [95% CI 1.072–2.808], P = 0.025). In the pooled analysis of the two samples, OR was 1.441 (1.047–1.982) for T2D (P = 0.025), 1.571 (1.127–2.191) for prediabetes (P = 0.008), and 1.498 (1.114–2.015) for IGR (P = 0.008).

As shown in Table 3, the subjects taking no antidiabetic drugs in sample 1 (1,912 control subjects, 768 subjects with prediabetes, and 330 subjects with T2D) were used for linear regression analysis. The A allele of rs13306393 was positively associated with FPG (P = 0.002), HbA_1c (P = 0.001), and HOMA of insulin resistance (HOMA-IR) (P = 0.016) after adjustment for age, sex, and BMI.

The association with HOMA-IR (P = 0.023) was confirmed in sample 2 (868 control subjects, 2,301 subject with prediabetes, and 410 subjects with T2D). In the pooled samples, associations with 2hPG (P = 0.008), HbA_1c (P = 0.029), HOMA-IR (P = 0.001), and ACR (P = 0.025) were also observed.

As shown in Fig. 1, luciferase activity was significantly lower in cells transfected with GCK_{Liver-promoter-Luc-rs13306393A} than with GCK_{Liver-promoter-Luc-rs13306393T} (P < 0.001).

In the current study, we report that a novel, low-frequency variant located at IVS1b ds+12 (NC_000007.14: g.44159061T>A) of the liver transcript of the GCK gene is associated with T2D in a Chinese population. Its frequency is much higher in East Asian (0.02015 in The Genome Aggregation Database) than other ethnic populations (0.0002). It was positively related not only to glycemic traits (FPG, 2hPG, HbA_1c) but also to insulin resistance (HOMA-IR).

This study included a total of 4,433 subjects with T2D, 3,069 subject with prediabetes, and 2,780 control subjects and had nearly 100% power under a genetics dominant model at P = 0.05 when T2D prevalence was 11.6% (10) and OR 1.7. In our previous genome-wide association study on T2D (5) and others in Chinese subjects (3,4) wherein common variants of GCK had been evaluated, we did not observe linkage disequilibrium relationships between rs13306393 and common variants of GCK associated with T2D and related traits (Supplementary Fig. 2 and Supplementary Table 3). Thus, rs13306393 was an independent locus associated with T2D in Chinese.

In past decades, a few of population-specific genetic variants, such as p.Gly319Ser of HNF1A in the Oji-Cree population (11), p.Glu508Lys of HNF1A in the Latino population (12), and p.Arg1420His of ABCC8 in Southwest American Indians (13), had been reported to increase the risk for T2D. In fact, many T2D genetic loci initially discovered in the European descent Caucasian population had not been replicated in the Chinese population and vice versa. The risk allele frequency at some genetic loci among ethnic populations varies greatly (14). Thus, the low-frequency variant at rs13306393 may be a unique genetic factor in East Asians.

To our knowledge, there has been no reliable study to date showing that GCK variants increase insulin resistance. In contrast to subjects with GCK-maturity-onset diabetes of the young who present with both primary reduced insulin secretion as a result of impaired GCK function of pancreatic β-cell (15), the A allele of rs13306393 might affect liver GCK function rather than islet GCK, and hyperglycemia and diabetes should be attributed to insulin resistance and secondary β-cell dysfunction.

It is also worth noting that the A allele of rs13306393 positively associates with ACR, the biomarker of early kidney disease. This finding might be due to the insulin resistance that resulted from this variant. Similarly, in liver-specific GCK knockout mice, hyperglycemia, diabetes, weight gain, insulin resistance, and renal complication were observed (16).

Interestingly, the phenotypes of rs13306393A were very similar to variants of GCK regulation protein (GCKR), which controls GCK activity specifically in liver. Many studies have demonstrated that variants of GCKR related to deceased GCK activity are associated with increased levels of FPG, 2hPG, HbA_1c, T2D, and HOMA-IR; low levels of TGs; and chronic kidney disease (17–19). In fact, we observed that the allele distributions of the GCKR variant (rs780094) (20), which was reported to associate with T2D, were very similar between the subjects with (n = 81) or without (n = 162) the A allele of rs13306393 (Supplementary Table 2). These results suggest that this variant is involved in the development of T2D, liver insulin resistance, and renal complications independently of GCKR variants.

The association of rs13306393 with T2D and IGR in a Chinese population has potential clinical implications. Approximately 2% of people in the Chinese population carry the A allele, and these individuals have reduced liver GCK activity and are the most appropriate population for GCK activators (GKAs). Further studies are warranted to validate the hypothesis that the patients carrying the A allele of rs13306393 could greatly benefit from GKAs.

Our study has some limitations. First, although the in vitro study showed that the A allele of rs13306393 might reduce the transcription level of the GCK gene, we could not make a firm conclusion. With the lack of appropriate animal and cell models, functional study of a variant at a nonconservative region in an intron is difficult. New advanced techniques, such as gene editing that is based on human pluripotent stem cells, are needed in the future. Second, the dates, methods, and numbers for recruiting study subjects were different between two independent case-control samples. Sample 1 subjects were from a community, and most subjects with prediabetes and diabetes had mild hyperglycemia and were diagnosed according to a single FPG, 2hPG, or HbA_1c measurement. However, most subjects in sample 2 were recruited from hospitals, and they usually had histories of hyperglycemia. These differences might explain the inconsistent ORs of prediabetes between samples 1 and 2. Additionally, some patients might have been misclassified into the control groups owing to a lack of HbA_1c results, which might increase the chance of negative results. Further studies with larger sample sizes, more homogeneous populations, and more proper criteria of classification for glucose tolerance are needed.

In conclusion, we identified a low-frequency variant in liver GCK that might be unique to East Asians. This variant was associated with an increased risk of T2D, IGR, and insulin resistance. Further studies are warranted to validate the hypothesis that patients carrying rs13306393A could greatly benefit from GKAs.

Acknowledgments. The authors thank all the study subjects for their contributions. The authors acknowledge all the principal investigators. The authors also thank all research staff for collection of data.

Funding. National Key Research and Development Program of China (2016YFC1304901), Beijing Science and Technology Committee Funding (Z141100007414002 and D131100005313008), and the National High-Technology Research and Development Program of China (863 Program 2012AA02A509).

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

Contributions. Y.M. contributed to the research, data collection, data analysis, and writing of the manuscript and performed the literature review. Y.Lu. and S.G. contributed to the research, data collection, data analysis, and review of the manuscript. X.Zho., Y.Li, W.L., S.Z., X.C., Q.R., L.Z., X.Zha., Y.W., X.Hu., X.G., and M.H. helped to collect the data and reviewed the manuscript. X.Ha. and L.J. designed the study, contributed to the discussion, and reviewed and edited the manuscript. All authors approved the final draft. L.J. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.