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Original Studies |
2 P12A and Type 2 Diabetes in Canadian Oji-Cree1
John P. Robarts Research Institute (R.A.H., H.C., C.M.A.) and Centre for Studies in Family Medicine (S.B.H.), University of Western Ontario, London, Ontario, Canada N6A 5K8; and Samuel Lunenfeld Research Institute and Department of Medicine (B.Z., A.J.G.H.), Mount Sinai Hospital, University of Toronto, Ontario, Canada M5G 1X5
Address correspondence and requests for reprints to: Robert A. Hegele, Blackburn Cardiovascular Genetics Laboratory, Robarts Research Institute, 406-100 Perth Drive, London, Ontario, Canada N6A 5K8. E-mail: robert.hegele{at}rri.on.ca
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Abstract |
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Introduction |
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(HNF-1) (1, 2). Individuals with one and two
copies of the HNF1A S319 allele had, respectively, a 2- and
4-fold increased relative risk of having type 2 diabetes (1, 2). Among
subjects whose age-of-onset of diabetes was under 35, almost 50% had
at least one copy of the HNF1A S319 allele. The observation
that a population-specific genetic variant was present in such a high
proportion of affected subjects is unique in the area of the genetics
of diabetes and in the field of complex diseases, in general. However,
more than half of Oji-Cree with early-onset type 2 diabetes did not
carry the HNF1A S319 allele. We have strongly suspected that
variants in other genes determined diabetes susceptibility among the
Oji-Cree with "non-HNF1A S319-associated" type 2
diabetes; in other words, among affected individuals who were
HNF1A G319/G319 homozygotes.
PPARG, on chromosome 3p25, encodes the nuclear receptor
peroxisome proliferator-activated receptor 
(PPAR) (3, 4, 5).
PPARG is an attractive candidate gene for susceptibility to
type 2 diabetes and related phenotypes because its products play a key
role in the modulation of insulin sensitivity, inflammation, and in
adipocyte differentiation and proliferation, through regulation of the
expression of adipocyte-specific developmental genes (3, 4, 5). Two
isoforms, called PPAR1 and -2, are produced from alternative
splicing of the PPARG messenger RNA (3, 4, 5). Pharmacologic
activation of PPAR by thiazolidinediones is associated with
improvement of insulin sensitivity, probably through enhancement of
insulin-stimulated tyrosine phosphorylation of genes involved in
insulin signaling pathways (3, 4, 5).
There is a relatively common PPARG nucleotide sequence
change that encodes a variant form of PPAR2, designated P12A
(6, 7, 8, 9, 10). This nonconservative change is very close to the amino
terminus of the mature protein, and the resulting change in the primary
structure of the ligand-independent activation domain would be expected
to reduce the stability of a putative -helix (6, 7, 8, 9, 10).
PPARG A12 had decreased binding affinity to the cognate PPAR
promoter element and, thus, lower in vitro transactivation
capacity (9). However, PPARG P12, which had greater in
vitro activity than A12, was found to be associated with
metabolically deleterious phenotypes, such as decreased insulin
sensitivity, obesity, and type 2 diabetes in samples taken from
Japanese and Finnish populations (9). This somewhat counterintuitive
observation was reconciled by the investigators’ suggestion that
PPARG A12 produced lower accumulation of adipose tissue due
to less efficient stimulation of PPAR target genes (9). In two other
studies of Caucasians, there was no association of PPARG
P12A with diabetes (8, 10), but one study did report an association of
A12 with increased body mass index (BMI) (8).
We have used a strategy composed of both association and linkage analysis to identify susceptibility genes for type 2 diabetes in Oji-Cree (1, 2, 11). One component of this strategy has been to sequence the coding and 5'- and 3'-untranslated flanking regions of candidate genes in Oji-Cree subjects with and without type 2 diabetes. We now report that PPARG A12 was associated with type 2 diabetes and with an earlier age-of-onset among subjects, particularly women, who were HNF1A G319 homozygotes. PPARG A12 is the second variant associated with diabetes in the Oji-Cree, confirming the earlier impression of genetic heterogeneity in this sample.
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Subjects and Methods |
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The community of Sandy Lake, Ontario, is located about 2000 km northwest of Toronto, in the subarctic boreal forest of central Canada. Seven hundred twenty-eight members (72% of the total population) of this community aged 10 yr and above participated in the Sandy Lake Health and Diabetes Project (1, 2, 11, 12, 13, 14, 15, 16, 17, 18, 19). Several complete clinical descriptions of the entire study sample have already been published (1, 2, 11, 12, 13, 14, 15, 16, 17, 18, 19). The project was approved by The University of Toronto Ethics Review Committee and the Sandy Lake First Nations Band Council.
Biochemical analyses
Plasma samples were obtained with informed consent. Exclusion criteria were an inadequate blood sample available for all biochemical and/or genetic determinations. Subjects gave plasma samples after fasting overnight for 12 h. Blood was centrifuged at 2000 rpm for 30 min, and the plasma was stored at -70 C. Concentrations of fasting plasma glucose and insulin were determined, as described (12). A standard 75-g oral glucose tolerance test (OGTT) was then administered, and a second blood sample was collected after 2 h for plasma glucose determination. Subjects were excluded from the OGTT if they had physician-diagnosed diabetes and/or if they were currently receiving treatment with insulin and/or oral hypoglycemic agents or if they had a fasting blood glucose exceeding 11.1 mmol/L. Subjects who were pregnant at the time of recruitment had their OGTT deferred until three months postpartum. Type 2 diabetes, impaired glucose tolerance (IGT), and normal glucose tolerance (nondiabetic) were diagnosed using pre-1997 criteria (20, 21).
Genetic analyses
We had previously determined genotypes for HNF1A G319S (1, 2). We then screened for candidate gene mutations in subjects without HNF1A S319. The genes that we have sequenced, to date, have included IPF-4, GK, HNF-4, and IAPP. We sequenced the exons and the 5'- and 3'-untranslated regions from the entire PPARG gene in three unrelated subjects with type 2 diabetes, whose age-of-onset was 35 yr or under and whose HNF1A genotype was G319/G319. We also performed sequencing in three unrelated nondiabetic subjects, whose age was 60 yr or older, whose BMI was 30 kg/m2 or greater, and whose HNF1A genotype was G319/G319. We used published sequence information to derive amplification primers for all coding sequences and the 5'- and 3'-untranslated regions from PPARG (22). Amplified products were directly sequenced in both directions with an ABI 377 automated DNA sequencer (PE Applied Biosystems Inc., Mississauga, Ontario, Canada). ABI Sequence Navigator software (PE Applied Biosystems Inc.) was used to align and compare amplified DNA fragments for sequence differences. The only PPARG sequence variant that was found was PPARG P12A. The PPARG A12 allele was observed in two of these subjects with diabetes and in none of the three control subjects. This variant could be detected by amplification of exon 6, followed by restriction digestion with HgaI, as described (7).
Statistical analyses
SAS (Version 6.12) was used for all statistical comparisons
(23). Between-group differences in proportions of alleles or genotypes
were compared using 
2 analysis and a
two-tailed Fisher’s exact test. Estimates of relative risk of type 2
diabetes between genotypes were determined using odds ratios from the
Mantel-Haenszel method. The LIFETEST log rank procedure was used to
determine differences between the genotypes with respect to
age-of-onset or age-at-diagnosis for affected subjects.
For continuous traits, ANOVAs were performed using the general linear models procedure separately in affected and unaffected men and women. All continuous traits had distributions that differed significantly from the normal distribution according to Wilk’s test of normality. After transformation using the natural logarithm (log), each trait had a distribution that was no longer significantly different from normal. ANOVA was used to determine the sources of variation for log fasting plasma glucose, log fasting insulin and C-peptide, and log plasma glucose post challenge. F tests were computed from the type III sums of squares (23). This form of sums of squares is applicable to unbalanced study designs and adjusts the level of significance to account for other independent variables included in the model. Independent variables for each ANOVA were sex, age, BMI, and genotypes.
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Results |
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Baseline attributes for the entire study sample are shown in Table 1
. For the purpose of genetic analysis,
affected subjects were considered to have either definite diabetes or
IGT. In this data set, 47 men had definite type 2 diabetes, 13 men had
IGT, 68 women had definite type 2 diabetes, and 51 women had IGT. As we
previously reported (12), there was a significant difference in the
proportion of affected women and men (42.9% vs. 27.2%,
P < 0.0001). Therefore, for all subsequent analyses,
men and women were studied separately.
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The tables generally report proportions of subjects or means ± SD for the entire study sample and also for the subgroup of subjects who were homozygous for HNF1A G319/G319. However, a priori comparisons of allele frequencies and odds ratios related to PPARG genotypes were performed only for the subgroup of subjects who were homozygous for HNF1A G319/G319.
The HNF1A allele and genotype frequencies are shown in Table 2. The genotype frequencies for each
group were within Hardy-Weinberg expectations. Consistent with our
previous observations, the overall frequencies of the HNF1A
S319 allele in the affected and unaffected groups were significantly
different (0.173 and 0.087, respectively; P = 0.00012).
In Oji-Cree men, the frequencies of the HNF1A S319 allele in
the affected and unaffected groups were significantly different (0.250
and 0.109, respectively; P = 0.00057). In Oji-Cree
women, the frequencies of the HNF1A S319 allele in the
affected and unaffected groups were significantly different (0.135 and
0.067, respectively; P = 0.011).
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. The genotype frequencies for each
group were within Hardy-Weinberg expectations. Because we were
interested only in the association of the PPARG alleles with
diabetes in subjects who did not have HNF1A-associated
diabetes, we did not perform an a priori analysis on the
entire study sample. However, a post hoc analysis showed
that the overall frequencies of the PPARG A12 allele in the
affected and unaffected groups were not significantly different (0.106
and 0.084, respectively; P = 0.49). In Oji-Cree men,
the frequencies of the PPARG A12 allele in the affected and
unaffected groups were not significantly different (0.075 and 0.099,
respectively; P = 0.10). However, in Oji-Cree women,
the frequencies of the PPARG A12 allele in the affected and
unaffected groups were significantly different (0.122 and 0.070,
respectively; P = 0.018).
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. The genotype frequencies for each
group were within Hardy-Weinberg expectations. In Oji-Cree men, the
frequencies of the PPARG A12 allele in the affected and
unaffected groups were not significantly different (0.106 and 0.106,
respectively; P = 0.99). However, in Oji-Cree women,
the frequencies of the PPARG A12 allele in the affected and
unaffected groups were significantly different (0.146 and 0.068,
respectively; P = 0.0017).
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Among all subjects who were homozygous for PPARG P12/P12, the odd ratios for being affected for carriers of HNF1A S319 was 1.9 (95% CI, 1.4–2.6). For male PPARG P12/P12 homozygotes, this odds ratio was 2.1(95% CI, 1.4–3.2). For female PPARG P12/P12 homozygotes, this odds ratio was 2.3 (95% CI, 1.4–4.0).
Finally, among subjects under age 45, 57.4% of affected subjects had at least one of PPARG A12 or HNF1A S319, compared with 32.2% of unaffected subjects (P = 0.0000006). Among men under age 45, 64.9% of affected subjects had at least one of PPARG A12 or HNF1A S319, compared with 37.2% of unaffected subjects (P = 0.003). Among women under age 45, 54.1% of affected subjects had at least one of PPARG P12 or HNF1A S319, compared with 28.2% of unaffected subjects (P = 0.00002).
Age-of-onset or -diagnosis in affected subjects according to PPARG genotype
Fig. 1 shows a plot of the
cumulative proportion of affected women who were homozygous for
HNF1A G319/G319 with age-of-onset or -diagnosis on the
abscissa, according to PPARG genotype. The curves for the
PPARG P12/P12 homozygotes and A12/P12 heterozygotes were
significantly different (P < 0.05). The curves for the
affected men were not significantly different (data not shown,
P = 0.16).
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Affected and unaffected men and women were evaluated separately
for differences between genotypes in clinical and biochemical traits.
Because the association with PPARG was seen only in females,
the means (±SD) for both the female overall
sample and subgroups of HNF1A G319/G319 homozygotes are
shown in Tables 5 and 6. None of the between-genotype
differences was statistically significant.
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Discussion |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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We recognized previously that, despite the extremely strong evidence for its role in type 2 diabetes susceptibility in the Oji-Cree, HNF1A S319 could not fully explain the genetic component of susceptibility to diabetes. The association with PPARG A12 was identified by analyzing the subgroup of subjects who were homozygous for HNF1A G319/G319. By definition, HNF1A G319/G319 homozygotes could not develop HNF1A S319-associated type 2 diabetes and must have had a different genetic basis for their diabetes. Because these homozygotes constituted about 70% of the affected subjects, we reasoned that this subgroup would be large enough to detect associations with other genetic variants. The association with PPARG A12 could be detected in the overall HNF1A G319/G319 homozygote subgroup, but this was due mainly to the increased frequency of the marker in affected Oji-Cree women, not in affected men.
The association of PPARG A12 with type 2 diabetes seems to
be at variance with the previous observation of an increased odds of
diabetes in Japanese American homozygotes for P12 (9). These
investigators also found that A12 was associated with lower BMI and
improved insulin sensitivity among middle-aged and elderly Finns (9).
These previously reported findings were somewhat counterintuitive
because the A12 allele showed decreased binding affinity to the cognate
promoter element and reduced ability to transactivate responsive
promoters (9). Our finding of an association between PPARG
A12 and more deleterious phenotypes would be more consistent with the
demonstrated loss of function of the PPAR A12 variant at the
cellular level.
The disparities between association studies may be related to differences in ethnic background, study design, phenotype studied, and secondary factors, such as the effects of age, BMI, and gender. As always in association studies, there is the possibility that the marker under study, while having a proven in vitro functional consequence, may simply be in linkage disequilibrium with the true causative genomic variant within or proximal to the study locus. There may be differences in linkage disequilibrium relationships between study samples, which could also explain the differences in the observed associations.
Although PPAR seems to be important in modulating insulin
sensitivity, our results indicate that there are no
between-PPARG genotype differences in fasting plasma insulin
or C-peptide concentrations, for either men or women, with or without
diabetes. This implies that the plasma insulin in subjects with
PPARG A12 is insufficient to prevent the development of
diabetes. Whether this is related to increased peripheral insulin
resistance among carriers of PPARG A12 remains to be
determined by cellular and/or in vivo physiological
studies.
The findings also indicate that the association of PPARG A12
with type 2 diabetes in the Oji-Cree differs between men and women. One
factor underlying this apparent gender difference could be the
relatively lower burden of obesity among Oji-Cree men compared with
women (12). Because obesity contributes to insulin resistance, it is
possible that the general tendency for earlier-onset obesity among
Oji-Cree women would result in more insulin resistance at younger ages
in women compared with men. However, there were no between-genotype
differences in BMI, suggesting that variation in PPAR activity was
not a primary determinant of obesity. Another factor could be the
higher serum concentration of leptin in Oji-Cree women compared with
men (24), which could modulate several other intermediate metabolic
pathways related to development of diabetes. Whatever the mechanism,
the findings suggest that gender should be accounted for in future
research analyses and possibly in predictive diagnosis and clinical
decision-making in the Oji-Cree.
The findings also confirm the earlier impression that the diabetes in the Oji-Cree had more than one genetic determinant. Of the 179 overall affected subjects in the present study, 55 (30.7%) had HNF1A S319 and an additional 32 (17.9%) had PPARG A12. Thus, almost 50% of all affected subjects and more than 60% of young affected subjects had either PPARG A12 or HNF1A S319. In addition, the odds of being affected for a subject who carried at least one of these markers was about twice as high as for a subject who carried neither. Furthermore, the odds of being unaffected for a subject who carried neither marker are about twice as high as for a subject who carried at least one. These relationships suggest the potential of diagnostic utility for this combination of markers. There are still obviously gaps in diagnostic specificity and sensitivity, since many affected subjects had neither marker and some unaffected subjects had at least one. These gaps might be narrowed by further research into the genetic and nongenetic factors that underlie type 2 diabetes in the Oji-Cree.
In summary, we report the association between type 2 diabetes in the Oji-Cree of Sandy Lake with PPARG A12, which represents the second associated candidate gene variant in this population. This suggests that the diabetes susceptibility among Sandy Lake Oji-Cree is at least oligogenic. The association with affected status was more significant for women than men. Also, the presence of the PPARG A12 allele was associated with significant differences in the age-of-onset of diabetes in women and in the overall study sample. The observed gender specificity could have been related to the general tendency of Oji-Cree women to develop obesity at younger ages than men or to other gender-specific factors. It would be important to define the mechanistic basis for the association of diabetes with both HNF1A S319 and PPARG A12 through cellular and/or physiological experiments. The ability to stratify Oji-Cree subjects according to their HNF1A and/or PPARG genotype could be helpful in future prospective clinical studies of the natural history and interventions for diabetes.
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Acknowledgments |
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Footnotes |
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2 Career Investigator of the Heart and Stroke Foundation of Ontario.
3 Career Investigator of the Ontario Ministry of Health.
4 Supported by Health Canada through a National Health Research and
Development Program Research Training Award.
Received October 28, 1999.
Revised January 19, 2000.
Accepted January 24, 2000.
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References |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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G319S variant is
associated with early onset type 2 diabetes in Canadian Oji-Cree. J Clin Endocrinol Metab. 84:1077–1082. G319S: a private mutation in Oji-Cree associated with
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