1
Effect of the rs997509 Polymorphism on the Association Between ENPP1, Metabolic
Syndrome and Impaired Glucose Tolerance in Childhood Obesity.
Nicola Santoro, Grazia Cirillo, Maria Grazia Lepore, Alfonsina Palma, Alessandra Amato, Piera
Savarese, Pierluigi Marzuillo, Anna Grandone, Laura Perrone and Emanuele Miraglia del Giudice.
Department of Pediatrics “F. Fede” Seconda Università degli Studi di Napoli, Via Luigi De
Crecchio 2, 80138, Napoli.
Running title: ENPP1 gene and metabolic syndrome in children
Corresponding Author: Dr. Emanuele Miraglia del Giudice, Dipartimento di Pediatria, Seconda
Università di Napoli, Via Luigi De Crecchio N°2, 80138, Napoli, Italy.
Phone: ++39-081-5665420
Fax: ++39-081-5665427
E-mail: [email protected]
Word Count: 238 (abstract) 3,080 (text); Number of tables and figures: 3 Tables, 2 Figures
Disclosure Statement: The authors have nothing to disclose
Key words: ENPP1, children, metabolic syndrome, IGT, polymorphism.
J Clin Endocrin Metab. First published ahead of print October 21, 2008 as doi:10.1210/jc.2008-1659
Copyright (C) 2008 by The Endocrine Society
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Abstract
Context: Variants on the nucleotide pyrophosphatase/phosphodiesterase-1 (ENPP-1) gene have
been associated with obesity and insulin resistance. Since insulin resistance is a pivotal factor in the
development of metabolic syndrome (MS) and impaired glucose tolerance (IGT), we aimed to test
the association between the K121Q and rs997509 ENPP-1 variants with obesity, MS and IGT in
obese children and adolescents.
Methods: We screened 809 children, 409 obese and 400 lean controls. Obese subjects underwent a
standard oral glucose tolerance test, whole body insulin sensitivity index (WBISI) and homeostasis
model assessment (HOMA) were calculated.
Results: No difference in prevalence for K121Q and rs997509 polymorphisms between obese and
controls (p>0.05) were observed. Obese children carrying the rs997509 rare allele showed higher
insulin (p=0.001), HOMA-IR (p<.001) and lower WBISI values (0.04) compared to common allele
homozygous. A similar observation was done for K121Q variant, with 121Q allele carriers showing
higher insulin (p=0.03) and HOMA (p=0.04) values than 121K homozygotes.
Moreover, subjects carrying the rs997509 rare allele had higher risk of MS (OR 2.4, 95% CI: 1.3-
4.3) and IGT (OR 4.7, 95% CI: 1.9 -11.4) than common allele homozygotes. Evaluating combined
effects of both polymorphisms, which are in strong linkage disequilibrium, we showed that the
effect on insulin sensitivity was due to the rs997509 T variant.
Conclusion: We conclude that the ENPP1 rs997509T allele can predispose obese children to MS
and IGT and that this variant might drive the association between the ENPP1 121Q allele and
insulin resistance.
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Introduction
Children are becoming increasingly vulnerable to overweight and obesity around the world. At
least 155 million school-age children worldwide are overweight or obese, according to the latest
estimates from the International Obesity Task Force (1). One of the most frequent complications of
obesity is the early occurrence of metabolic syndrome, defined as the co-occurrence of
dyslipidaemia, hypertension and impaired glucose homeostasis (2). Insulin resistance represents the
link between obesity and these metabolic alterations (3). A crucial step in the pathogenesis of
insulin resistance is represented by the free fatty acids (FFA) accumulation in the liver, fat cells and,
particularly, skeletal muscle of obese patients, that, interfering with the normal insulin signalling
cascade, appears as the primary determinant of insulin resistance (4). As consequence of insulin
resistance, pancreas needs to increase its insulin production to maintain normal values of glycaemia,
but the progressive fat accumulation in pancreatic beta cells leads to beta cells failure causing a
defective insulin secretion, inadequate to maintain glycaemia in the normal range. This condition
appears as clinically evident when impaired glucose tolerance (IGT) or type 2 diabetes (T2D)
occurs. In fact, along with metabolic syndrome, IGT and T2D are nowadays much more common
that in the past years among obese children and adolescents, with a range of incidence between
0.5% and 4% for T2D and 5% and 25% for IGT (5, 6). The plasma membrane enzyme termed
ENPP1 (ectonucleotide pyrophosphatase phosphodiesterase 1), has been shown to inhibit insulin
receptor function by affecting its tyrosine kinase activity in peripheral tissues, including liver,
muscle and fat (7). It is a class II transmembrane glycoprotein located both on plasma membrane
and in the endoplasmatic reticulum (8). Although its physiological function is not completely
understood, there is evidence that ENPP1 plays a major role in insulin resistance development (9).
Several studies have reported that the locus where ENPP1 gene maps (6q22-q23) is linked to both
insulin resistance and T2D, highlighting the potential role of this gene in modulating susceptibility
to these metabolic issues (9). The most widely investigated ENPP1 polymorphism is the
substitution of a lysine with a glutamine at codon 121 (K121Q), with the 121Q variant associated
4
with type 2 diabetes (9). This aminoacid change is located in the second somatomedin-B-like
domain of ENPP1 and may interfere with protein-protein interactions (10). Human studies
demonstrated that obese adults carrying the Q variant show lower insulin sensitivity than
noncarriers (11). Moreover, association studies have shown that ENPP1 121Q variant may
influence the susceptibility to develop obesity and IGT during childhood (12, 13). Although the
majority of the studies dealing with the ENPP1 gene have focused their attention on the K121Q
variant obtaining discordant results (9), a recent report by Bochenski et al., examining the
associations of tagging single nucleotide polymorphisms (SNPs) and haplotypes of the linkage
disequilibrium block containing K121Q with T2D, showed that another variant, the rs997509, lying
in the intron 1 and consisting in a substitution of a cytosine (C) with a timine (T), had a strong
correlation with T2D (14). The authors suggested that the T allele of the new identified SNP, is
sufficed to distinguish the 121Q carrying haplotype that was significantly more associated with
T2D.
Given these evidences we decided to screen the K121Q and rs997509 in a population of obese
children and adolescents to try to replicate previous results and to verify which relationship
intercourse between the two polymorphisms and the predisposition to obesity and insulin resistance
in our population.
Materials and Methods
Cohort description and clinical evaluation
Four hundred and nine Caucasian obese children and adolescents, referred to our ward (childhood
obesity service) since the 1999 have been enrolled. Subjects between 2 and 16 years of age and with
a BMI exceeding the 97th
percentile for their age and sex were eligible. Subjects using medications
that alter blood pressure, glucose or lipid metabolism were excluded. Moreover, all subjects missing
the complete data set needed for the analysis were excluded. The ethical committee of the Second
5
University of Study of Naples approved the study. Informed consent was obtained by parents and,
where appropriate, by children.
Of the 409 subjects enrolled, 208 were girls. This sample was representative of the 2482 children
referred to our ward from 1999 to 2005; in fact, no differences in mean age, sex distribution and
pubertal stage were observed between the study sample and the sample of excluded subjects.
Weight and height were measured and BMI was calculated. Standard deviations scores for BMI
were calculated by using the LMS method (15). The population mean age was 11.5 ± 3.0 years; the
mean z-score BMI was 3.6 ± 1.0. Systolic blood pressure (SBP) and diastolic blood pressure (DBP)
were measured three times while the subjects were seated and the two last measurements were
averaged for the analysis (16). Pubertal stage was assessed using Tanner criteria (17). Thirty one
percent of children included in the study were pubertal (71 girls). All measurements were taken
twice by the same operator.
To test the ENPP1 allelic distribution a group of controls, composed by 400 (200 girls) lean age and
sex matched children (27% pubertal, 63 girls), was recruited as previously described (18). Briefly,
unrelated lean children who were age and sex matched and belonged to the same geographic area
were recruited as controls (mean age, 10.5 ± 2.3 yr; mean BMI z-score, 0.4 ±
0.4). They consulted
the Department of Pediatrics of the Second University of Naples for presumed diseases and were
found to be normal. Informed consent from parents and assent from children
were obtained before
participation in the study. The dosage of fasting insulin, serum glucose, plasma lipids and blood
pressure measurement has been performed also in 200 controls.
Metabolic evaluation
After informed consent, a blood sample was drawn from each patient after an overnight fast. The
serum was frozen at -20°C until analysed. Triglycerides and total cholesterol levels were
determined by an enzymatic colorimetric test with lipid clearing factor and HDL-cholesterol (HDL)
6
was measured by precipitation. To underwent an oral glucose tolerance test (OGTT) by assuming
1.75 g of glucose per kilogram of body weight, subjects were evaluated at 8 a.m. after an overnight
fast; they consumed a diet containing at least 250 g of carbohydrates per day for three days before
the study and refrained from vigorous physical activity; insulin and glucose levels were measured
during the OGTT at baseline and later every 30 minutes for 120 minutes.
Given the changes occurring in body composition during growth, to diagnose the metabolic
syndrome the criteria of the National Cholesterol Education Program's Adult Treatment Panel (19)
and the World Health Organization (20) were modified according to Weiss et al (2). Consequently,
children and adolescents in our study were classified as having the metabolic syndrome if they met
three of the following criteria needed to be present: BMI exceeding the 95th
percentile, systolic
and/or diastolic blood pressure exceeding the 95th
percentile, triglycerides levels higher than 110
mg/dl, HDL cholesterol lower than 40 mg/dl for males and 50 mg/dl for females, impaired glucose
tolerance (glucose level greater than 140 mg/dl, but less than 200 mg/dl after two hours from the
beginning of the OGTT).
Insulin resistance was assessed using the homeostasis model assessment (HOMA) as follows:
fasting insulin (pmol/liter) x fasting glucose (mmol/liter)/135. The degree of insulin sensitivity was
assessed by using the whole body insulin sensitivity index (WBISI). The composite WBISI is based
on values of insulin and glucose obtained from the OGTT and the corresponding fasting values, as
originally described (21). It represents good estimates for clamp-derived insulin sensitivity and it
has been demonstrated to be correlated with intramyocellular lipid content (22). It has been
obtained according to the following formula: 10.000/square root of [(fasting insulin X fasting
glycaemia) X (mean insulin concentration during OGTT) X (mean glycaemia during OGTT) (22).
Genotyping
All the patients and controls were genotyped for the K121Q and rs997509 variants. For the
rs997509 C/T substitution the following primers were used, F: 5’-ATTTTTTCCTTCAGTGTATA-
7
3’ and R: 5’-ACACCCTACAACCCCTAAGA-3’. The AciI restriction enzyme was used to identify
the variant, since the T allele eliminates an AciI restriction site. To detect the K121Q variant the
couple of primers used were: F: 5’-GCAATTCTGTGTTCACTTTGG-3’ and R: 5’-
GAGCACCTGTTGACACA-3’. AvaII restriction enzyme was used to detect the variant.
Statistical analysis
Power calculations were performed using the genetic power calculator.
http://pngu.mgh.harvard.edu/~purcell/gpc/. Since previous studies showed an association between
childhood obesity and K121Q variant (12, 13), prior to analyse the association of Q variant with
obesity we calculated that the statistical power in the proband – control data set was 98% at p= 0.05
to detect an association using the control frequencies and Odds Ratios (OR) shown in the German
population (13) (allele frequency 0.11. OR=1.82 for T allele). To reach a statistical power of 98% at
p=0.05 we screened 400 age and sex matched lean controls.
Chi Square test was used to verify whether the genotypes were in Hardy-Weinberg equilibrium and
to compare allele frequencies between obese and non-obese subjects and metabolic syndrome and
IGT prevalence between the different genotypes. Linkage disequilibrium between markers was
assessed as described (23, 24). A general linear model (GLM) was used to evaluate the differences
between groups of genotype and the effect of genotypes interaction on phenotype. Because of the
low prevalence of rare allele homozygotes for the K121Q and rs997509 variants, to test
genotype/phenotype associations rare allele homozygotes and heterozygotes were merged. When
necessary the variables were adjusted for age, sex, BMI and pubertal stage. A logistic regression
was generated to calculate the odds of developing the metabolic syndrome or IGT for a given
genotype. Although raw values are shown, non-normally distributed variables were log-transformed
before performing the analysis. Data are expressed as means and standard deviations. P values <
0.05 were considered statistically significant. The SAS Statistical Software Package version 8.2
(SAS institute, Clary, NC) was used to analyze data.
8
Results
One hundred and forty three (35%) patients (66 girls) showed the criteria to make diagnosis of
metabolic syndrome, three patients (0.7%) showed impaired fasting glucose (IFG) and 23 subjects
(5.6%) had impaired glucose tolerance (IGT); all IFG patients had also IGT. None showed type 2
diabetes. Subjects with metabolic syndrome had higher insulin levels, HOMA, triglycerides, z-score
systolic blood pressure (SBP), z-score diastolic blood pressure (DBP) and lower WBISI and HDL
levels than subjects who did not meet the criteria for the diagnosis of metabolic syndrome (table 1).
Subjects with IGT showed higher serum insulin levels (40.6±32 vs 27.4±18; p<.001), higher
HOMA (9.40±6.2 vs 5.6±3.8; p<.001) and lower WBISI (1.4±0.7 vs 2.5±2.0; p=0.007) than those
with a normal glucose tolerance. None of the lean controls showed dyslipidemia, hypertension or
IGT and the serum insulin levels (8.8±3.3) and the HOMA values (0.9±0.6) were significantly
different from those observed in obese (both p<.001).
The genotype distribution of both the studied variants was in Hardy-Weinberg equilibrium both in
obese and control cohorts (both p>0.05). The K121Q and rs997509 showed a strong linkage
disequilibrium (D’ = 0.9). The allelic distribution of the K121Q polymorphism was similar to that
shown in the Italian population (25) with a prevalence of 121Q variant of about 15%. Allelic
prevalence of the K121Q and rs997509 did not differ between obese and controls. The Q allele was
present in 16% of obese and in the 13% of controls (p> 0.05), the T allele of the rs997509 was
present in 7% of obese and in 6% of controls (p>0.05). Also genotype frequencies were similar in
obese and controls both for K121Q (obese KK 0.72, KQ 0.24, QQ 0.04 - controls KK 0.75, KQ
0.23, QQ 0.02 ; p= 0.3) and rs997509 (obese CC 0.87, CT 0.12, TT 0.01 - controls CC 0.89, CT
0.1 , TT 0.01; p= 0.8 ). The T allele of the rs997509 was present in about the 7% of population,
according to the study by Bochensky et al., performed in a Polish population showing a prevalence
of about 6% (15).
When compared for the clinical features, subjects carrying the 121Q allele showed significantly
higher serum insulin levels and HOMA values than subjects homozygotes for the common allele
9
and subjects carrying the rs997509T allele showed higher serum insulin levels, higher HOMA and
lower WBISI than children homozygotes for the common allele (table 2).
A significant higher prevalence of the metabolic syndrome and IGT in the group of patients
carrying the rs997509 T allele was observed. In fact, the metabolic syndrome was present in 52% of
obese children with this allele (OR: 2.4, 95% CI: 1.3-4.3; p= 0.005) and IGT was present in 13% of
obese children carrying the rs997509 T allele (OR 4.7, 95% CI: 1.9 -11.4; p<.001). Although not
statistically significant, subjects carrying the 121Q allele showed the same trend, with a higher
prevalence of IGT and Metabolic syndrome than those carrying the wild allele (table 3). Moreover,
subjects carrying the rs997509 T allele had significantly higher serum insulin levels during the
curve, showing a trend for higher serum glucose levels (figure 1). Although a similar trend was
evident, no significant differences for serum insulin and glucose levels during the OGTT were
observed for Q121 (all p-values higher than 0.05, except baseline insulin values) (figure 2).
Differences in fasting serum insulin levels and HOMA values according to the rs997509 (serum
insulin = 9.2±4.8 vs. 12.3±5.7, p = 0.6; HOMA = 1.1±0.7 vs. 1.4±1.2 p=0.9) and K121Q (serum
insulin = 8.3±2.6 vs. 8.9±3.5, p = 0.3; HOMA = 0.8±0.7 vs. 1.0±0.6 p=0.5) genotypes were not
observed in 200 subjects of the control group.
When the combined effects of the genotypes was tested, we used a model where, at every turn,
HOMA, insulin or WBISI was the dependent variable and sex, age, pubertal stage, K121Q and
rs997509 were the covariates. The results showed that the major effect on these three variables
(insulin, HOMA and WBISI) was ascribed to the rs997509 variant that appeared to drive also the
association between K121Q variant and insulin resistance (table 3).
Discussion
In vitro and in vivo studies clearly indicate that membrane glycoprotein ENPP1 contributes to the
decreased function of the insulin receptor observed in the insulin resistance. ENPP1 is, in fact,
10
elevated in muscle, fat and other tissues of subjects with insulin resistance (26, 27) and transgenic
mice over-expressing ENPP1 in different tissues are insulin resistant and show type 2 diabetes (9).
Conflicting results exist concerning the role played in humans by ENPP1 variants and particularly
the K121Q polymorphism in predisposing to the quantitative traits related to insulin resistance:
obesity and type 2 diabetes (9). We did not show any association between obesity and K121Q. This
observation is in contrast with several studies ruled out in Europe and in USA (12, 13, 28, 29), but it
is consistent with three recent large multicentric studies in European and African-American
individuals (30-32). Although it is difficult to establish the reasons of these different results, it has
been suggested that differences in the genetic and/or environmental background and in recruitment
procedures may have played a role (9).
Another important clinical outcome we examined was the occurrence of insulin resistance, IGT and
MS according to K121Q and rs997509, the latter being a polymorphism which has been suggested
to drive the association between K121Q and diabetes. Particularly, Bochenski et al., by studying
five ENPP1 gene variants identified a risk haplotype for developing type 2 diabetes. The haplotype
contained both the rs997509 T allele and the 121Q allele. The authors observed that when the
carriers of the T allele of rs997509 were excluded from the analysis, the frequency of the remaining
121Q carriers was not different in the type 2 diabetic cases and controls (14).
We report that rs997509 variant has an effect on glucose metabolism and MS independently of the
presence of 121Q and that the highest degree of insulin resistance in our population was apparent
only when the rs997509 T allele was present (table 3). Our results suggest that rs997509 T allele is
strongly associated with insulin resistance and related abnormalities in obese children and
adolescents and that the T allele drives also the 121Q allele association with insulin resistance. In
fact, the association observed between 121Q and insulin resistance disappeared when we compared
only subjects not carrying the rs997509 T allele. This observation can be ascribed to the strong
linkage disequilibrium existing between the two variants and can explain why contrasting results
concerning the association between K121Q and type 2 diabetes have been reported. Moreover, the
11
observation that this association was not present in lean subjects means that obesity is essential for
revealing the phenotype, with variant’s effect being noticed only when, as usually happens in obese
children, an increasing insulin production in response to fat accumulation is required.
Remarkably, in obese subjects, the higher degree of insulin resistance seemed to influence also
serum glucose levels and consequently insulin secretion during OGTT. Subjects carrying the
rs997509 T allele, in fact, showed during the curve constantly higher glucose levels and
consequently higher insulin secretion than C homozygotes. The progressive inadequateness of
insulin response to hyperglicemia of subjects carrying rs997509 T allele is documented also by the
higher prevalence of IGT in this group of patients respect to obese subjects homozygotes for the C
allele. Children with the T allele, in fact, showed, not only a higher prevalence of IGT, but also of
metabolic syndrome, that is consequent to insulin resistance (3). Likely, in subjects carrying the
rs997509 T allele, hyperinsulinemia causes not only the worsening of the metabolic status, but also
a progressive impairment of beta cell function, via fat deposition in the pancreas.
Unfortunately, functional studies exploring the effect of the rs997509 variant on ENPP1 synthesis
and function are not available. The rs997509 is located in the 3’ end of intron 1 in a region
containing a regulatory element, as reported previously (14) and suggested by the Five Regulatory
track of the University of California Santa Cruz genome browser (14). Moreover, another
polymorphism, rs9493114, which is in complete linkage disequilibrium with the rs997509, has been
described in intron 8 and may be the functional responsible of this association, although other in
vivo and in vitro reports on this variant, at our knowledge, do not exist (14).
In conclusion, consistently with previous reports this study supports a genetic link between ENPP1
gene variants and metabolic abnormalities in obese children. Moreover, we suggest that the ENPP1
rs997509 variant is strongly associated with insulin resistance, metabolic syndrome and IGT in
obese children and adolescents and that it drives the known association between the 121Q variant
and insulin resistance.
12
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Figures legends.
Figure 1: Serum insulin levels (A) and serum glucose levels (B) during OGTT according to the
rs997509 SNP genotype. The squares represent the rare allele carriers, the circle represent the
common allele homozygotes. Data are shown as means and deviation scores.
Figure 2: Serum insulin levels (A) and serum glucose levels (B) during OGTT according to the
K121Q genotype. The squares represent the rare allele carriers, the circle represent the common
allele homozygotes. Data are shown as means and deviation scores.
Table1 Clinical features of obese subjects according to the occurrence of Metabolic Syndrome.
Presence of Metabolic
Syndrome (n 143 )
Absence of Metabolic
Syndrome (n 266)
P
Age (years) 11.3±3.0 11.6±3.0 0.3
Pubertal subjects (%) 37 % 28 % 0.05
BMI (Kg/m2) 34 ±6 32±5 0.01
z-score BMI 3.9±0.9 3.4±1.3 0.01
Insulin (µµµµU/L)1 35.1±24.2 24.6± 16.2 <0.001
HOMA1 7.5±5.2 5.3±3.3 <0.001
WBISI1 1.9±1.7 2.7±2.0 0.001
HDL (mg/dl)1 37±5.9 50±8.9 <0.001
Triglycerides (mg/dl)1 114±41 86±72 <0.001
SBP (mmHg)2 121±13 116±14 <0.001
z-score SBP 1.2±1.2 0.8±1.0 0.007
DBP (mmHg)2 73±8 61±13 <0.001
z-score DBP 1.4±0.9 1.0±0.9 0.008
1 Adjusted for age, sex and pubertal stage. 2 Adjusted for age, sex and height.
K121Q rs997509
KK (297) KQ (97) + QQ (15) P CC (357) CT (48) + TT (4) P
Age (years) 11.2±3 11.5±2 0.5 11.7 ± 2.7 11.2 ± 2.9 0.2
Pubetal subjects (%) 30 33 0.4 30 35 0.5
BMI (Kg/m2) 32.6±5 33.0 ± 6 0.5 32.2 ± 5.4 33 ± 6.7 0.2
z-score BMI 3.1±0.9 2.9±0.9 0.4 3.0 ± 0.7 2.9 ± 0.4 0.8
Plasma glucose (mg/dl) 1 79.7±12 79.8±7 0.9 79.8 ± 8.9 81.5 ± 9.1 0.2
Insulin (µµµµU/l) 1 31.2±18.0 35.7±25.1 0.03 31.0±19.2 39.8±22.3 0.003
HOMA 1 6.2±3.7 7.2±5.4 0.04 6.2 ± 4.1 8.3 ± 5.2 <0.001
WBISI 1 2.5±2.0 2.3±1.5 0.09 2.5 ± 2.0 2.0 ± 1.5 0.04
HDL (mg/dl) 1
45±9.8 44±13 0.2 44±12 41±17 0.1
Triglycerides (mg/dl) 1
93±67 96±72 0.7 92±51 104±58 0.08
SBP (mmHg)2 118±18 120±31 0.4 117±19 120±33 0.2
z-score SBP 1.0±0.7 1.1±0.3 0.1 0.9±0.8 1.1±0.9 0.07
DBP (mmHg)2 67±14 69±21 0.2 64±17 69±35 0.09
z-score DBP 1.1±0.8 1.2±0.9 0.06 1.0±0.7 1.3±1.0 0.04
metabolic syndrome (%) 27 37 0.1 31 52 0.005
IGT (%) 3 7 0.06
4 13 <0.001
Before comparison the variable were log transformed, but geometric means are shown. When the general linear model was run
age, sex, BMI, pubertal stage (1) and height (
2) were used as covariates, the p-value shown are those obtained after adjustment.
Table 2 Clinical features of the obese subjects according to the K121Q and rs997509 genotypes
K121Q rs997509 subjects Insulin HOMA WBISI
KK CC 292 32.2±16.7 6.4±3.3 2.4-±1.3
KQ+QQ CC 65 31.9±19.3 6.4±4.1 2.5±1.6
KQ+QQ CT+TT 47 42.0±25.0 8.9±4.4 1.8±0.9
KK CT+TT 5 41.9±17.0 8.7±2.0 1.9±0.2
P-value 0.001 0.002 0.03
When the effect of both genotypes was tested with a general linear model, we used a model where, at every turn, HOMA,
insulin or WBISI was the dependent variable and sex, age, pubertal stage, K121Q and rs997509 were the covariates. The
results showed that the major effect on these three variables (insulin, HOMA and WBISI) was ascribed to the rs997509
variant that appeared to drive also the association between K121Q variant and insulin resistance. The data are presented as
mean +/- standard deviation.
Table 3: Association between parameters of glucose and insulin metabolism with a combined evaluation of the ENPP1
rs997509 and K121Q polymorphisms
0
50
100
150
200
250
0 30 60 90 120
AµU/L
time
0
20
40
60
80
100
120
140
160
180
0 30 60 90 120
mg/dl
time
B
Insulin
Plasma glucose
*
**
*
*
*
Figure 1
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