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Association of single nucleotide polymorphisms in GCK, GCKR and PNPLA3 with type 2 diabetes related quantitative traits in Mexican-American population

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Association of single nucleotide polymorphisms in GCK, GCKR and PNPLA3 with type 2 diabetes related quantitative traits in Mexican-American population

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Content 1

Association of Single Nucleotide Polymorphisms
in GCK, GCKR and PNPLA3 with Type 2 Diabetes
Related Quantitative Traits in Mexican-American
Population

Zou, Rui

Applied Biostatistics and Epidemiology
Master of Science
University of Southern California
August 9
th
2016

2

Table of Contents

1. ABSTRACT --------------------------------------------------------------------------------------------------------3
Objectives -----------------------------------------------------------------------------------------------------3
Design ----------------------------------------------------------------------------------------------------------3
Result -----------------------------------------------------------------------------------------------------------3
Conclusion -----------------------------------------------------------------------------------------------------3
2. INTRODUCTION -------------------------------------------------------------------------------------------------4
3. SUBJECTS AND METHODS ------------------------------------------------------------------------------------5
Subject recruitment -----------------------------------------------------------------------------------------5
Clinical protocols ---------------------------------------------------------------------------------------------6
Assays -----------------------------------------------------------------------------------------------------------6
Molecular analysis -------------------------------------------------------------------------------------------6
Data analysis --------------------------------------------------------------------------------------------------6
4. RESULTS -----------------------------------------------------------------------------------------------------------7
Clinical demographics of study population ------------------------------------------------------------7
Associations of SNPs with T2DM quantitative traits -------------------------------------------------9
5. DISCUSSION ------------------------------------------------------------------------------------------------------13
6. ACKNOWLEDGEMENTS ---------------------------------------------------------------------------------------16
7. ABRREVIATIONS ------------------------------------------------------------------------------------------------16
8. REFERENCE ------------------------------------------------------------------------------------------------------ 16
9. APPENDIX --------------------------------------------------------------------------------------------------------20

3

Abstract
Objectives: We investigated the association of 5 single nucleotide polymorphisms (SNPs) in GCK,
GCKR and PNPLA3 genes to determine whether they are associated with type 2 diabetes related
quantitative traits and try to understand the pathogenesis of type 2 diabetes mellitus (T2DM) in
Latino women who developed gestational diabetes mellitus (GDM) during pregnancy. The study
population were 1121 individuals from 547 Mexico-American families of probands with or
without a previous diagnosed GDM and their relatives (cousins and siblings).

Design: Study participants were phenotyped by fasting blood sample (for fasting glucose, insulin
and lipids level), a 75g oral glucose tolerance test (for 30-minute and 120-minute glucose and
insulin level) and frequently sampled intravenous glucose tolerance tests (for insulin sensitivity,
glucose effectiveness, and acute insulin response to glucose). Dual-energy x-ray absorptiometry
scans were also used to assess the body composition (BMI and body fat percent). Five SNPs in
GCK, GCKR and PNPLA3 which may associated with glucose and lipids metabolism in liver cells
were selected as candidate genes. SNPs were then tested for association with T2DM related
phenotypes using a likelihood ratio test of variance-component linkage analysis. Bonferroni
correction was used to correct for multiple testing.

Result: After adjusting for age, sex, alcohol use and chronic illness medication use, the minor
GCKR rs780094 A allele was statistically significantly associated with decreased fasting insulin
level (p=4.1×10
-3
), elevated S G (p=7.9×10
-5
), higher fasting cholesterol level (p=2.6×10
-5
) and
higher fasting triglyceride level (p=9.0×10
-6
). The minor GCK rs4607517 A allele was statistically
significantly associated with decreased OGTT-related 30-minute insulin level (p=0.01) and
marginally associated with higher fasting glucose level (p=0.07). The minor GCK rs1799884 A
allele was marginally associated with decreased BMI (p=0.07). The PNPLA3 rs738409 G allele
was statistically significantly associated with elevated AST (p=1.4×10
-7
) and ALT (p=5.7×10
-3
)
levels. In addition, the minor GCK rs4607517 A allele was associated with higher fasting glucose
level in an interaction with percentage of body fat (p=5.3×10
-3
). The GCK rs1799831 A allele was
associated with higher ALT level in an interaction with percentage of body fat (p=0.045).

Conclusion: Among our study population, the GCKR rs780094 A allele was associated with
increased glucose sensitivity, higher fasting triglyceride level, higher fasting cholesterol level and
decreased fasting insulin level. The GCK rs4607517 A allele was associated with increased fasting
plasma glucose level and decreased OGTT-related 30-minute insulin level. The GCK rs1799831 A
allele was associated with increased ALT level. The PNPLA3 rs738409 G allele was associated
with increased ALT and AST levels. The GCK rs1799884 was marginally associated with
decreased BMI.

4

Introduction
Type 2 diabetes mellitus (T2DM) is a chronic and progressive metabolic disorder characterized
by hyperglycemia, variable degrees of insulin resistance, impaired insulin secretion and
increased hepatic glucose production [1]. Among all the etiological factors, an alternation in the
balance between insulin sensitivity and insulin secretion plays the most important role [2]. In
normal glucose tolerance individuals, the need to respond to progressive states of insulin
resistance is met by increasing insulin production. For insulin-resistant patients, however, the
balance between insulin demand and supply may be broke by the progressive loss of pancreatic
beta-cell function and eventually lead to the onset of T2DM [3]. The increasing T2DM worldwide
is one of the most serious health problems today. The number of patients with diabetes,
estimated to be 415 million in 2015, is expected rise more rapidly in the future as obesity
increases and physical activity levels of most people continue to decrease. In addition to the
T2DM patients, there are 318 million adults with impaired glucose tolerance (IGT), which puts
them at high risk of developing the disease in the future [4]. Gestational diabetes mellitus
(GDM) refers to hyperglycemia that first presents during pregnancy and typically resolves itself
post-partum. The GDM can also put those women at a higher risk for future T2DM [5] so higher
attention should be paid on both IGT and GMD population in prevention of T2DM. Notably,
healthcare costs continue to increase with 12% of global health expenditure dedicated to
diabetes treatment and related complications that account for the majority of the total
expenditure [4]. Potential strategies to reduce the burden of T2DM include implementation of
better treatments for people with established diabetes and development of individualized
preventive methods for people who have risk alleles in their genomes. Both strategies, and the
latter one in particular, require a deeper understanding of the mechanisms that lead to the
symptoms of T2DM on genetic level.

Glucokinase (GCK) is the enzyme that facilitates phosphorylation of glucose to glucose-6-
phosphate, which is the first reaction in the glycolytic pathway. In hepatocyte models, GCK
activity is a major determinant of both glycogen synthesis and glycolysis [6-7]. The activity of
GCK is affected by several factors: In postprandial period, the simultaneous rise in glucose and
insulin increases GCK activity by enhanced gene expression, changes in cellular location, and
interaction with regulatory proteins. Conversely, in fasting period, the decrease in glucose and
insulin concentrations and increase in glucagon concentrations halt GCK activity [8]. GCK was
one of the first candidate genes to be identified as a human "diabetes gene"[9]: inactivating
mutations in GCK cause maturity onset diabetes of the young type 2 [10] whereas activating
mutation in GCK lead to permanent hyperinsulinemic hypoglycemia [11]. GCK is regulated by the
glucokinase regulator protein (GCKR) which is expressed in liver and β-cells. It is a bifunctional
enzyme [12] that inhibits GCK in liver by binding it non-covalently to form an inactive complexes
during periods of fasting, and activates GCK by releasing it back to cytoplasm as glucose and
insulin level rise. GCKR is in a pivotal position to regulate liver glucose balance and glucose-
stimulated insulin secretion [13]. Adenoviral-mediated hepatic overproduction of GKRP
increased GCK activity, lowered fasting blood glucose level[14], improved glucose-stimulated
glycaemia in mice and resulted in a concomitant increase in insulin sensitivity and triglyceride
levels[15]. A large study of Danish white participants confirmed that the rs780094 A allele was
5

associated with increased fasting triglycerides, impaired fasting and OGTT-related insulin
release, reduced homeostasis model assessment of insulin resistance (HOMA-IR), and an
increased risk of dyslipidemia [16]. Another study, combining data from 12 independent cohorts
confirmed that GCKR rs780094 were strongly associated with opposite effects on fasting plasma
triglyceride and glucose concentrations [17]. Subsequently, the MAGIC study conducted a large-
scale meta-analysis based on previous studies and provided us with more convincing evidence
that the GCKR rs780094 A allele was associated with decreased fasting glucose, impaired insulin
level, a lower HOMA-IR index and an elevated fasting triglyceride level [18].

Patatin-like phospholipase domain-containing protein 3 (PNPLA3), is an adipocyte protein, which
seems to have both lipolytic and lipogenic properties [19-23]. Human PNPLA3 localizes to
cellular membranes of adipocytes. Previous studies indicated that PNPLA3 may be involved in
the balance of energy usage/storage in liver adipocyte, restoration of lipid homeostasis upon
aberrant intracellular lipid accumulation (primary in liver cells) [24] and non-alcoholic fatty liver
disease (NAFLD) [23, 25-26]. The common variant, rs738409 G allele in PNPLA3 associated with
increased quantitative measures of liver fat content, increased risk of hepatic steatosis and
higher serum AST level [27]. PNPLA3 was brought into the spot light of current T2DM research
field since several studies recently showed that not the increase in body fat mass per se, but the
accumulation of fat in the visceral cavity and particularly in the liver are responsible for the
genesis of insulin resistance [28-31]. In humans, it is recognized that T2DM are associated
strongly with NAFLD and the severities of insulin resistance and liver damage parallel each other
[32]. PNPLA3 variations have previously been associated with obesity, insulin secretion level,
insulin resistance, β-cell function and liver cell enzymes levels [33]. Most recently, a genome-
wide association study identified PNPLA3 rs738409 was associated with increased hepatic fat
content, elevated serum liver enzymes and did not correlate with serum lipids and insulin
resistance estimated from fasting glucose and insulin values [34]. Overall, the evidence
mentioned above suggests that GCK, GCKR and PNPLA3 could be critical regulators of glucose
and lipids metabolism in hepatocytes. GCK, GCKR and PNPLA3 are therefore important
candidate genes to help us understand the etiology of T2DM and other metabolic abnormalities.
The aim of present study is to identify whether variants in these genes are associated with
T2DM-related quantitative traits in Mexican-Americans.

Subjects and Methods
Subject recruitment
Selection of original cohort had been described in detail in previous study [5] [35]. Briefly, 1121
subjects who had complete phenotype and genotype data were drawn from the Betagene Study
database and selected as our study population. This cohort consists of 195 Mexican-Americans
probands who had been diagnosed as gestational diabetes mellitus (GDM) within the previous
five years, 145 non-GDM probands who maintained normal blood glucose level during their
pregnancy in the past five years and 781 relatives of these probands who served as NGT
controls. All protocols for BetaGene have been approved by the Institutional Review Boards of
6

participating institutions, and all participants provided written informed consent before
participation. Details regarding subject recruitment have been described in previous study.

Clinical protocols
Phenotyping and genotyping were performed on two separate visits to the University of
Southern California General Clinical Research Center. During the first visit, each participant
completed a standard 75g OGTT after overnight fasting. Blood samples were then drawn at
three time points of the test (0, 30 and 120 minutes) to measure the plasma glucose and insulin
concentrations. The fasting blood samples were also used to measure the liver enzymes (ALT
and AST) and lipids (cholesterol, triglyceride and high-density lipoproteins (HDL)) levels. Physical
examinations were done to measure the height (m) and weight (kg). DNA was extracted from
blood samples to determine genotypes of the participants. Participants in GDM families with
fasting glucose below 126 mg/dL (7.0mmol/L) and non-GDM probands with normal fasting and
2-h glucose levels were invited for a second visit which consisted of a dual-energy x-ray
absorptiometry scan for body composition and a frequently sampled iv glucose tolerance test
(FSIGT) analyzed by minimal model (MINMOD Millennium V5.18; Richard N. Bergman, Los
Angeles, CA) to quantify glucose effectiveness (S
G
), insulin sensitivity (S
I
) and acute insulin
response to glucose (AIR). BMI was calculated as weight (kg)/height
2
(m
2
). Disposition index (DI)
was calculated as S
I
×AIR; 30-minute DI was calculated as S
I
× (30-min insulin – fasting insulin). In
addition, insulinogenic index was calculated as (30-min insulin – fasting insulin)/ (30-min glucose
– fasting glucose) (with serum insulin in μU/mL and plasma glucose in mmol/L).

Assays
In our study, plasma glucose levels were measured on an autoanalyzer using the glucose oxidase
method (YSI Model 2300; Yellow Springs Instruments, Yellow Springs, OH). Plasma insulin levels
were measured by two-site immunoenzymometric assay (TOSOH Corp., San Francisco, CA) that
has less than 0.1% cross-reactivity with proinsulin and intermediate split products.

Molecular analysis
For the purpose of this study, we specifically selected five tag SNPs within GCK, GCKR and
PNPLA3 for genotyping in our BetaGene sample. These SNPs have been associated with T2DM
and related quantitative traits in previous studies among other ethnic populations. They are:
rs780094 G/A (major/minor allele) in GCKR; rs4607517 G/A, rs1799831 G/A and rs1799884 G/A
in GCK; rs738409 C/G in PNPLA3.

Data Analysis
SAS 9.4 was used to create residuals for 18 T2DM related quantitative traits adjusted for age,
sex, alcohol use and chronic illness medication use. Given prior evidence that the association
between T2DM-related traits and gene variants may be modified by total body fat [36], we
7

added body fat percent in a second model as adjusting variable. Residuals in two models were
then inverse-normally transformed separately to achieve approximate normal distribution.
Univariate association between SNPs and T2DM-related quantitative traits was then tested
using variance-component linkage analysis [37] under a likelihood ratio framework as
implemented in SOLAR (7.6.4). Specifically, two multivariable models were tested:
Model 1: Trait = β 0 + β 1 Age + β 2 Sex + β 3 alcohol use + β 4 chronic illness medication use;
Model 2: Trait = β 0 + β 1 Age + β 2 Sex + β 3 alcohol use + β 4 chronic illness medication use + β 5
body fat percent.
Bonferroni correction was used to correct for multiple testing. A significant association was
defined as a P value of 0.05, corrected for the numbers of SNPs tested (n=18 in model 1,
p=0.0028; n=17 in model 2 since percent of body fat was used as adjusting variable, p=0.0029).
In all cases, reported P values are Bonferroni corrected for multiple testing unless otherwise
specified.

Results
Clinical demographics of the study population
We report results from 1121 individuals in 547 families for whom both phenotype and genotype
data were available. Subject characteristics are shown in Table 1. In general, GDM probands,
non-GDM probands and their relatives were similar in median age, BMI, and percentage body
fat, although these characteristics tended to be highest in GDM probands. The median BMI
exceeded the threshold for overweight (25kg/m
2
) in all three groups and exceeded the
threshold for obese (30kg/m
2
) only in the GDM probands. The non-GDM probands were of
similar age as GDM probands but were less likely to be obese. This fact may reflect that the
recruitment of non-GDM probands was lagging behind GDM probands to allow for matching as
described above.

8

TABLE Ⅰ. Participants characteristics

GDM
probands
Non-GDM
probands
Relatives
a
of
probands
Females/males (n)
Age (yr)
BMI (kg/m
2
)
Body fat percent (%)
Fasting glucose (mmol/L)
2-h glucose(mmol/L)
Fasting insulin(pmol/L)
30-min insulin(pmol/L)
2-h insulin(pmol/L)
S G (min
-1
)
S I (x10
-5
min
-1
)/(pmol/L)
AIR (pmol/L×10 min)
Disposition Index
30-min Disposition Index
Cholesterol (mmol/L)
HDL (mmol/L)
Triglyceride(mmol/L)
AST(U/L)
ALT(U/L)
Insulinogenic Index
Chronic illness medication
(Yes/No/Unknown, (n))
195/0
34.9 (7.2)
30.3 (8.2)
39.2 (6.7)
5.3 (0.9)
8.5 (3.1)
54 (48)
348 (282)
468 (408)
0.015 (0.007)
4.22 (2.75)
1788 (2282)
7889.8 (7321)
1141.4 (1114)
4.37 (1.11)
1.19 (0.36)
1.12 (0.77)
20.0 (8.0)
30.0 (23.0)
15.7 (14.1)

19/172/4
145/0
34 (6.3)
28.4 (7.5)
38.4 (8.1)
4.8 (0.6)
6.1 (1.8)
36 (30)
354 (306)
234 (294)
0.019 (0.009)
5.57 (3.74)
3460 (2720)
18064.72 (11598)
1705.9 (1152)
4.01 (0.96)
1.24 (0.36)
0.8 (0.52)
18.0 (6.0)
25.0 (17.0)
22.6 (23.2)

12/132/1
478/303
34.4 (12.3)
28.4 (6.9)
34 (13.4)
5.1 (0.7)
7.0 (2.5)
42 (42)
372 (342)
336 (354)
0.017 (0.008)
4.45 (3.29)
2660 (3080)
12265.78 (11610)
1441.0 (1246)
4.42 (1.14)
1.16 (0.36)
1.11 (0.9)
21.0 (10.0)
33.0 (19.0)
18.8 (16.5)

93/684/4
Data are reported as unadjusted median and interquartile range. HDL, High-density lipoprotein.
a
Relatives refer to the cousins and siblings of probands.

9

Associations of SNPs with T2DM quantitative traits
As shown in Table Ⅱ and Ⅲ, after adjusting for age, sex, alcohol use and chronic illness
medication use, GCK rs4607517 A allele was statistically significantly associated with decreased
plasma insulin level at 30 minutes (p=0.01) and marginally associated with higher fasting glucose
level (p=0.07). GCKR rs780094 A allele was statistically significantly associated with impaired
fasting insulin level (p=4.1×10
-3
), elevated S G (p=7.9×10
-5
), higher fasting cholesterol level
(p=2.6×10
-5
) and higher fasting triglyceride level (p=9.0×10
-6
). The PNPLA3 rs738409 G allele was
statistically significantly associated with elevated AST (p=1.4×10
-7
) and ALT (p=5.7×10
-3
) levels.
In addition, GCK rs1799884 A allele was marginally associated with BMI (p=0.07). After we
added body fat percent into model as adjusting variable, most of those results were similar.
Specifically, the significant association between GCKR rs780094 A allele and decreased fasting
insulin level disappeared after adjusting for body fat percent. The significant association
between GCK rs4607517 A allele and decreased 30-minute insulin level disappeared whereas
the association with fasting glucose level became fairly significant (p=5.3×10
-3
). Moreover, GCK
rs1799831 A allele was associated with higher ALT level (p=0.045).
Table Ⅱ. Results of single marker tests of association between SNPs in GCK and T2DM-related
quantitative traits after adjusting for age, sex, medication use and alcohol use.

rs4607517
(A/0.18)
a
Bonferroni-
corrected
Effect
b
P value
c

rs1799884
(A/0.18)
a
Bonferroni-
corrected
Effect
b
P value
c

rs1799831
(A/0.15)
a
Bonferroni-
corrected
Effect
b
P value
c

BMI - 0.9 - 0.07 - 1.0
Body fat percent - 0.7 - 0.6 - 1.0
Fasting glucose - 0.07 - 1.0 - 1.0
2-h glucose - 1.0 - 1.0 - 1.0
Fasting insulin - 0.5 - 0.5 - 1.0
30-min insulin + 0.01 - 0.6 - 0.1
2-h insulin - 1.0 - 1.0 - 0.1
S G - 1.0 - 1.0 - 1.0
S I - 1.0 - 1.0 - 0.2
AIR - 0.3 - 1.0 - 0.08
DI - 1.0 - 1.0 - 1.0
10

30-min DI - 0.8 - 1.0 - 1.0
Cholesterol - 0.6 - 1.0 - 1.0
HDL - 1.0 - 1.0 - 1.0
Triglyceride - 1.0 - 1.0 - 1.0
AST - 1.0 - 1.0 - 1.0
Insulinogenic
index
- 1.0 - 1.0 - 0.1

AIR, acute insulin response to glucose.
DI, disposition index.
30-min DI= S I× (30-min insulin – fasting serum insulin), the insulin levels are OGTT-related insulin level.
HDL, High-density lipoprotein.
a
Minor allele/minor allele frequency.
b
Refers to the directional effect of the minor allele on the quantitative trait based on the regression coefficient and
assuming an additive genetic model.
c
Bonferroni corrected P value. Correction is made for five SNPs and 18 quantitative traits tested. A significant
association was defined as a P value of 0.05, corrected for the numbers of SNPs tested (n=18, p=0.0028)

Table Ⅲ. Results of single marker tests of association between SNPs in GCKR and PNPLA3 and
T2DM-related quantitative traits after adjusting for age, sex, medication use and alcohol use.

GCKR rs780094
(A/0.18)
a
Bonferroni corrected
Effect
b
P value
c

PNPLA3 rs738409

(G/0.18)
a
Bonferroni corrected
Effect
b
P value
c

BMI - 1.0 - 1.0
Body fat percent - 1.0 - 1.0
Fasting glucose - 0.7 - 1.0
2-h glucose - 1.0 - 1.0
Fasting insulin + 4.1×10
-3
- 1.0
30-min insulin - 1.0 - 1.0
2-h insulin - 0.1 - 1.0
S G + 7.9×10
-5
- 1.0
11

S I - 0.2 - 1.0
AIR - 1.0 - 1.0
DI - 0.4 - 1.0
30-min DI - 1.0 - 1.0
Cholesterol + 2.6×10
-5
- 1.0
HDL - 1.0 - 1.0
Triglyceride + 9.0×10
-6
- 1.0
AST - 1.0 + 1.4×10
-7

ALT
Insulinogenic
Index
- 1.0
- 0.1
+

5.7×10
-3

- 1.0

AIR, acute insulin response to glucose.
DI, disposition index.
30-min DI= S I× (30-min insulin – fasting serum insulin), the insulin levels are OGTT-related insulin level.
HDL, High-density lipoprotein.
a
Minor allele/minor allele frequency.
b
Refers to the directional effect of the minor allele on the quantitative trait based on the regression coefficient and
assuming an additive genetic model.
c
Bonferroni corrected P value. Correction is made for five SNPs and 18 quantitative traits tested. A significant
association was defined as a P value of 0.05, corrected for the numbers of SNPs tested (n=18, p=0.0028)

12

Figure 1. The mean triglyceride and cholesterol levels of different rs780094 genotype after
adjustment for age, sex, alcohol use and chronic illness medication use. The minor allele A was
used as the reference allele.

1.174
1.281
1.676
0
0.5
1
1.5
2
2.5
3
3.5
GG AG AA
The adjusted mean triglyceride levels
(mmol/L)
4.399
4.471
4.692
0.00
1.00
2.00
3.00
4.00
5.00
6.00
GG AG AA
The adjusted mean cholesterol levels
(mmol/L)
13

Figure 2. The mean liver enzyme levels of different rs738409 genotype after adjustment for
age, sex, alcohol and chronic illness medication use. The minor allele G was used as the
reference allele.

Discussion
In this long-term, prospective, observational study of Mexican-American families, we
investigated the association of 5 SNPs in GCK, GCKR and PNPLA3 to find whether they are
associated with type 2 diabetes related quantitative traits in Mexican-American women who
21.875
22.431
26.11
0
5
10
15
20
25
30
35
40
45
CC CG GG
The adjusted mean AST levels
(U/L)
33.434 33.936
42.079
0
10
20
30
40
50
60
70
80
CC CG GG
The adjusted mean ALT levels
(U/L)
14

developed gestational diabetes mellitus (GDM) during pregnancy. Our analysis revealed that
genomic loci of GCK, GCKR and PNPLA3 associated with T2DM-related quantitative traits in a
large Mexican-American population. To our knowledge, this is the first report in which variations
at GCK, GCKR and PNPLA3 were comprehensively tested for association with such traits in
Mexican-American populations.

The associations of GCKR rs780094 A allele with elevated fasting triglyceride level, decreased
fasting glucose level and fasting insulin release have been replicated in many studies of different
ethnic populations [38-41]. For example, Sparso et al [39] showed that the minor GCKR A-allele
of rs780094 was associated with an increased level of fasting serum triacylglycerol and impaired
fasting and OGTT-related insulin release. In addition, Qi et al [42] found that the GCKR rs780094
A allele was significantly associated with increased fasting triacylglycerol level and decreased
fasting glucose level. Our study confirmed the association between GCKR rs780094 A allele and
decreased fasting insulin level and increased triglyceride level again in a Mexican-American
population. In addition, we found that this allele was associated with increased fasting
cholesterol level. A potential explanation for these associations is that the GCK regulation by
GCKR is altered in the liver: increased GCK activity was associated with increased glucose
utilization in the liver. With such increase, GCK, phosphofructokinase and fatty acid synthase are
upregulated, whereas phosphoenolpyruvate carboxykinase and glucose-6-phossphatase are
downregulated [43]. These changes may decrease the hepatic glucose output, which results in
lower fasting insulin level, and facilitate de novo lipogenesis that leading to the increased fasting
cholesterol and triglyceride levels. The association between GCKR rs780094 A allele and
decreased fasting insulin level disappeared after adjusting for body fat percent. This pattern of
association we observed suggests another possible explanation: variation in GCKR may have
direct effects on adipose tissues, which may elicit secondary effects on insulin secretion and β-
cell function. We didn’t find an association with decreased fasting glucose level, instead, we got
a significant association between GCKR rs780094 A allele and an elevated glucose effectiveness
(S
G
). This finding is consistent with previous studies that the GCKR rs780094 A allele was
associated with decreased risk of T2DM [42] since S G indicates the ability of glucose per se, to
increase glucose uptake and suppress endogenous output which is another pathway to reduce
the fasting glucose concentration.

PNPLA3 rs738409 G allele was previously shown to be associate with NAFLD [26], insulin
resistance [23, 25] and insulin secretion level [33]. In our study, we found PNPLA3 rs738409 G
allele was associated with elevated AST and ALT concentrations after adjustment for age, sex,
alcohol use and chronic illness medication use. The associations remained significant after
adjusting for body fat percent. The elevated liver enzyme levels can be treated as a proxy of liver
damage due to hepatic steatosis. In that case, the association we found in our study may
suggest the PNPLA3 rs738409 G allele carriers may have decreased lipolytic ability of adipocytes.
Another possible explanation should be PNPLA3 rs738409 G allele may be involved in
restoration of lipid homeostasis upon aberrant intracellular lipid accumulation [24]. The lipid
droplets are then more likely to be stored in liver cells than break down as fatty acids and
15

release into circulation. Given the previous knowledge that the PNPLA3 could influence insulin
secretion by altering the load of fatty acids in the circulation [44], the PNPLA3 variant may elicit
secondary effects on the ability of GCK, GCKR and liver glucose metabolism since they are
sensitive to insulin concentration [8].

Additionally, we found significant association between SNPs in GCK and T2DM-related
quantitative traits: The rs4607517 A allele was marginally associated with elevated fasting
glucose level and significantly associated with decreased 30-minute OGTT related insulin release
after adjustment for age, sex, alcohol and medication use. With each copy of A allele, there was
0.035mmol/L increase in fasting glucose level, and 18.79 рmol/L decrease in 30-minute OGTT-
related insulin level (data not shown). After adjustment for body fat percent, the association
with elevated fasting glucose level became fairly significant. This may indicate that the GCK
rs4607517 A allele has an opposite effect on GCK function regardless of age, sex, liver cell
functions and amount of adipose tissues. The rs1799831 A allele was associated with elevated
ALT concentration. With each copy of A allele, there is 1.147U/L increase in blood ALT
concentration. This result may indicate that the rs1799831 A allele of GCK can also influence the
lipids metabolism in liver cells and a possible predictor of T2DM. In our research, however, we
didn’t find any SNP associated with DI or 30-minute DI, which were used in this study as
measures of β-cell compensation for insulin resistance. This result is acceptable since GCK, GCKR
and PNPLA3 are mostly expressed and exerting their functions in liver cells.

We recognize several limitations in the present study. First, the sample size is relatively modest
and further replication is necessary. Second, GDM women may differ from those with T2DM and
therefore our results may not be widely generalizable. Third, for the purpose of variance-
component linkage analysis, we created residuals for 18 T2DM-related quantitative traits and
inversely transformed these residuals to make the quantitative traits data approximately
normally distributed. This transformation made the residuals in to ranks so the βs we got from
SOLAR were not quite interpretable. As a result, we only have P values indicate whether the
association between the SNP and T2DM-related trait was statistically significant. Finally, further
functional studies are needed to investigate the biological significance underlying the SNPs-
T2DM-related quantitative traits.

In conclusion, we determined that 5 SNPs within GCK, GCKR and PNPLA3 were associated with
T2DM-related quantitative traits in a large Mexican-American population. The GCKR rs780094 A
allele was associated with increased glucose sensitivity, higher fasting triglyceride level, higher
fasting cholesterol level and decreased fasting insulin level. The GCK rs4607517 A allele was
associated with increased fasting plasma glucose level and decreased 30-minute serum insulin
level. The GCK rs1799831 A allele was associated with increased ALT level. The PNPLA3 rs738409
G allele was associated with increased ALT and AST levels. The GCK rs1799884 A allele was
associated with elevated BMI. The present study may improve our understanding of the etiology
of T2DM and provides insights into the pleotropic effects of T2DM-related genomic loci.
16

Acknowledgements
We thank the families who participated in the BetaGene study and are grateful for the support
of the University of Southern California (USC) General Clinical Research Center. We also
acknowledge the efforts of our recruiting and technical staff.

Abbreviations
GCK: glucokinase GCKR: glucokinase regulatory protein SNP: single nucleotide polymorphism
HDL: high density lipoprotein cholesterol BMI: body mass index SI: insulin sensitivity
SG: glucose sensitivity AIR: acute insulin response (to glucose) DI: disposition index GDM:
gestational diabetes mellitus NGT: normal glucose tolerance

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Appendix
Supplement table Ⅰ. Results of single marker tests of association between tag SNPs in GCK and
18 T2DM-related quantitative traits after adjusting for age, sex, medication use, alcohol use and
body fat percent.

rs4607517
a
(A/0.18)

Bonferroni
corrected
Effect
b
P value
c

rs1799884
a
(A/0.18)

Bonferroni
corrected
Effect
b
P value
c

rs1799831
a
(A/0.15)

Bonferroni
corrected
Effect
b
P value
c

BMI - 1.0 - 1.0 - 0.2
Fasting glucose + 5.3×10
-3
- 0.3 - 0.3
2-h glucose - 1.0 - 1.0 - 1.0
Fasting insulin - 1.0 - 1.0 - 1.0
30-min insulin - 0.1 - 1.0 - 0.1
2-h insulin - 1.0 - 1.0 - 0.2
S G - 1.0 - 1.0 - 1.0
S I - 1.0 - 1.0 - 0.8
AIR - 0.7 - 1.0 - 0.2
DI - 0.5 - 1.0 - 1.0
30-min DI - 0.2 - 1.0 - 1.0
Cholesterol - 1.0 - 1.0 - 1.0
HDL - 1.0 - 1.0 - 1.0
Triglyceride - 1.0 - 1.0 - 1.0
AST - 1.0 - 1.0 - 1.0
21

ALT
Insulinogenic-
Index
- 1.0
- 1.0
- 1.0
- 1.0
+ 0.045
- 0.2

AIR, acute insulin response to glucose.
DI, disposition index.
30-min DI= S I× (30-min insulin – fasting serum insulin), the insulin levels are OGTT-related insulin
level.
HDL, High-density lipoprotein.
a
Minor allele/minor allele frequency.
b
Refers to the directional effect of the minor allele on the quantitative trait based on the
regression coefficient and assuming an additive genetic model.
c
Bonferroni corrected P value. Correction is made for five SNPs and 17 quantitative traits tested.
A significant association was defined as a P value of 0.05, corrected for the numbers of SNPs
tested (n=17, p=0.0029).

Supplement table Ⅱ. Results of single marker tests of association between tag SNPs in GCKR
and PNPLA3 and T2DM-related quantitative traits after adjusting for age, sex, medication use,
alcohol use and body fat percent.

GCKR rs780094

(A/0.18)
a

Bonferroni corrected
Effect
b
P value
c

PNPLA3 rs738409

(G/0.18)
a

Bonferroni corrected
Effect
b
P value
c

BMI - 1.0 - 1.0
Fasting glucose - 1.0 - 1.0
2-h glucose - 1.0 - 1.0
Fasting insulin - 0.1 - 1.0
30-min insulin - 1.0 - 1.0
2-h insulin - 1.0 - 1.0
S G + 6.3×10
-4
- 1.0
22

S I - 1.0 - 1.0
AIR - 1.0 - 0.4
DI - 0.9 - 1.0
30-min DI - 1.0 - 1.0
Cholesterol +

1.62×10
-5
- 1.0
HDL - 1.0 - 1.0
Triglyceride + 1.2×10
-6
- 1.0
AST - 1.0 + 4.8×10
-7

ALT
Insulinogenic-
Index
- 1.0
- 1.0
+

9.9×10
-3

- 1.0

AIR, acute insulin response to glucose.
DI, disposition index.
30-min DI= S I× (30-min insulin – fasting serum insulin), the insulin levels are OGTT-related insulin
level.
HDL, High-density lipoprotein.
a
Minor allele/minor allele frequency.
b
Refers to the directional effect of the minor allele on the quantitative trait based on the
regression coefficient and assuming an additive genetic model.
c
Bonferroni corrected P value. Correction is made for five SNPs and 17 quantitative traits tested.
A significant association was defined as a P value of 0.05, corrected for the numbers of SNPs
tested (n=17, p=0.0029).

Abstract (if available)

Abstract Objectives: We investigated the association of 5 single nucleotide polymorphisms (SNPs) in GCK, GCKR and PNPLA3 genes to determine whether they are associated with type 2 diabetes related quantitative traits and try to understand the pathogenesis of type 2 diabetes mellitus (T2DM) in Latino women who developed gestational diabetes mellitus (GDM) during pregnancy. The study population were 1121 individuals from 547 Mexico-American families of probands with or without a previous diagnosed GDM and their relatives (cousins and siblings). ❧ Design: Study participants were phenotyped by fasting blood sample (for fasting glucose, insulin and lipids level), a 75g oral glucose tolerance test (for 30-minute and 120-minute glucose and insulin level) and frequently sampled intravenous glucose tolerance tests (for insulin sensitivity, glucose effectiveness, and acute insulin response to glucose). Dual-energy x-ray absorptiometry scans were also used to assess the body composition (BMI and body fat percent). Five SNPs in GCK, GCKR and PNPLA3 which may associated with glucose and lipids metabolism in liver cells were selected as candidate genes. SNPs were then tested for association with T2DM related phenotypes using a likelihood ratio test of variance-component linkage analysis. Bonferroni correction was used to correct for multiple testing. ❧ Result: After adjusting for age, sex, alcohol use and chronic illness medication use, the minor GCKR rs780094 A allele was statistically significantly associated with decreased fasting insulin level (p=4.1×10⁻³), elevated SG (p=7.9×10⁻⁵), higher fasting cholesterol level (p=2.6×10⁻⁵) and higher fasting triglyceride level (p=9.0×10⁻⁶). The minor GCK rs4607517 A allele was statistically significantly associated with decreased OGTT-related 30-minute insulin level (p=0.01) and marginally associated with higher fasting glucose level (p=0.07). The minor GCK rs1799884 A allele was marginally associated with decreased BMI (p=0.07). The PNPLA3 rs738409 G allele was statistically significantly associated with elevated AST (p=1.4×10⁻⁷) and ALT (p=5.7×10⁻³) levels. In addition, the minor GCK rs4607517 A allele was associated with higher fasting glucose level in an interaction with percentage of body fat (p=5.3×10⁻³). The GCK rs1799831 A allele was associated with higher ALT level in an interaction with percentage of body fat (p=0.045). ❧ Conclusion: Among our study population, the GCKR rs780094 A allele was associated with increased glucose sensitivity, higher fasting triglyceride level, higher fasting cholesterol level and decreased fasting insulin level. The GCK rs4607517 A allele was associated with increased fasting plasma glucose level and decreased OGTT-related 30-minute insulin level. The GCK rs1799831 A allele was associated with increased ALT level. The PNPLA3 rs738409 G allele was associated with increased ALT and AST levels. The GCK rs1799884 was marginally associated with decreased BMI.

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