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Journal of Clinical Endocrinology & Metabolism , doi:10.1210/jc.2006-2275
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The Journal of Clinical Endocrinology & Metabolism Vol. 92, No. 4 1502-1509
Copyright © 2007 by The Endocrine Society

Effects of the Type 2 Diabetes-Associated PPARG P12A Polymorphism on Progression to Diabetes and Response to Troglitazone

Jose C. Florez, Kathleen A. Jablonski, Maria W. Sun, Nick Bayley, Steven E. Kahn, Harry Shamoon, Richard F. Hamman, William C. Knowler, David M. Nathan, David Altshuler for the Diabetes Prevention Program Research Group1

Center for Human Genetic Research (J.C.F., M.W.S., N.B., D.A.) and Department of Medicine (J.C.F., D.M.N., D.A.), Massachusetts General Hospital, Boston, Massachusetts 02114; Departments of Medicine (J.C.F., D.M.N., D.A.) and Genetics (D.A.), Harvard Medical School, Boston, Massachusetts 02115; Program in Medical and Population Genetics (J.C.F., M.W.S., N.B., D.A.), Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts 02142; The Biostatistics Center (K.A.J.), George Washington University, Rockville, Maryland 20852; Division of Metabolism, Endocrinology and Nutrition, Department of Medicine (S.E.K.), VA Puget Sound Health Care System and University of Washington, Seattle, Washington 98108; Division of Endocrinology and Metabolism, Department of Medicine (H.S.), Albert Einstein College of Medicine, Bronx, New York 10461; Department of Preventive Medicine and Biometrics (R.F.H.), University of Colorado at Denver and Health Sciences Center, Denver, Colorado 80262; and Diabetes Epidemiology and Clinical Research Section (W.C.K.), National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona 85014

Address all correspondence and requests for reprints to: Jose C. Florez, Diabetes Prevention Program Coordinating Center, The Biostatistics Center, George Washington University, 6110 Executive Boulevard, Suite 750, Rockville, Maryland 20852. E-mail: jcflorez{at}partners.org and dppmail{at}biostat.bsc.gwu.edu.


   Abstract
Top
 Abstract
Introduction
 Patients and Methods
 Results
 Discussion
 References
 
Context: The common P12A polymorphism in PPARG (a target for thiazolidinedione medications) has been consistently associated with type 2 diabetes.

Objective: We examined whether PPARG P12A affects progression from impaired glucose tolerance to diabetes, or responses to preventive interventions (lifestyle, metformin, or troglitazone vs. placebo).

Patients: This study included 3548 Diabetes Prevention Program participants.

Design: We performed Cox regression analysis using genotype at PPARG P12A, intervention, and their interactions as predictors of diabetes incidence. We also genotyped five other PPARG variants implicated in the response to troglitazone and assessed their effect on insulin sensitivity at 1 yr.

Results: Consistent with prior cross-sectional studies, P/P homozygotes at PPARG P12A appeared more likely to develop diabetes than alanine carriers (hazard ratio, 1.24; 95% confidence interval, 0.99–1.57; P = 0.07) with no interaction of genotype with intervention. There was a significant interaction of genotype with body mass index and waist circumference (P = 0.03 and 0.002, respectively) with the alanine allele conferring less protection in more obese individuals. Neither PPARG P12A nor five other variants significantly affected the impact of troglitazone on insulin sensitivity in 340 participants at 1 yr.

Conclusions: The proline allele at PPARG P12A increases risk for diabetes in persons with impaired glucose tolerance, an effect modified by body mass index. In addition, PPARG P12A has little or no effect on the beneficial response to troglitazone.


   Introduction
Top
 Abstract
 Introduction
Patients and Methods
 Results
 Discussion
 References
 
THE PEROXISOME PROLIFERATOR-activated receptor {gamma} (PPAR{gamma}) is a nuclear hormone receptor preferentially expressed in adipose tissue (1). Activation by its ligand causes it to heterodimerize with the retinoid X receptor, bind specific DNA elements, and induce a transcriptional cascade that leads to adipocyte differentiation and increased sensitivity to insulin. The PPAR{gamma} molecule is now recognized as the cognate receptor for thiazolidinediones (2). A proline -> alanine change in codon 12 of its gene PPARG (P12A) has been reproducibly associated with a decreased risk for type 2 diabetes (3, 4, 5, 6, 7, 8, 9, 10, 11, 12); the proline allele confers an approximately 20% increased risk under a recessive model. Because of its high frequency in the population, the population-attributable risk of this variant nears 25% (4). Although some studies have not achieved statistical significance in their attempt to replicate this finding (13, 14, 15, 16, 17, 18, 19, 20, 21), most of them report consistent odds ratios with overlapping 95% confidence intervals (CIs) such that a meta-analysis of all published evidence yields a combined P value that achieves genomewide significance (22). How this molecular change impairs protein function and leads to an increased risk of type 2 diabetes has not been fully elucidated (23).

The risk of type 2 diabetes conferred by PPARG P12A has also been evaluated prospectively. The Finnish Diabetes Prevention Study (24), which randomized 522 subjects with impaired glucose tolerance (IGT) to either placebo or a lifestyle intervention, reported a 2-fold increase in risk of developing type 2 diabetes among alanine carriers in the placebo arm when compared with P/P homozygotes, a result that seemed to contradict the sizeable body of cross-sectional literature described above. On the other hand, the much larger Botnia Prospective Study (n = 2293) (25) documented a hazard ratio (HR) for developing diabetes of 1.7 among P/P homozygotes, a result that was statistically significant. Different ascertainment schemes (IGT vs. a population sample) and analytical methods (logistic regression vs. Cox proportional hazards analysis) may explain some but not all of these discrepancies.

In addition to its role in increasing risk of type 2 diabetes, the P12A variant may also affect therapeutic response; if so, its putative impact on preventive interventions might have clinical utility. In support of this concept, two studies have examined the effect of PPARG P12A on response to thiazolidinediones (26, 27). Blüher et al. (26) treated 131 subjects with pioglitazone for 26 wk; the proportion of responders (defined as > 15% decrease in glycated hemoglobin levels and/or > 20% decrease in fasting blood glucose when compared with baseline after 12 or 26 wk of pioglitazone) did not differ between P/P homozygotes and alanine carriers. Snitker et al. (27) examined 93 Hispanic women with a history of gestational diabetes enrolled in the Troglitazone in Prevention of Diabetes (TRIPOD) study and obtained iv glucose tolerance tests before and 3 months after treatment with troglitazone; genotype at PPARG P12A did not explain the variability in insulin sensitivity derived from an iv glucose tolerance test (SI) observed among these women.

It is possible that these studies were underpowered or that other variants in PPARG may account for the differential therapeutic response. To examine the second possibility, the TRIPOD investigators genotyped a set of 131 common PPARG variants in the same group of 93 Hispanic women and reported that eight PPARG polymorphisms were associated with response to troglitazone, defined as an overrepresentation of the minor allele in the upper two tertiles of insulin sensitivity (SI) after 3 months of troglitazone treatment (28). Two of these single nucleotide polymorphisms (SNPs; rs4135263 and rs1152003) also showed nominal associations with changes in SI as a quantitative trait under recessive genetic models (28).

As a next step in clarifying the conflicting literature and evaluating the effect of PPARG P12A on thiazolidinedione response in a large multiethnic sample, we set out to confirm the predictive power of this variant and assess its impact on the lifestyle and pharmacological interventions used in the Diabetes Prevention Program (DPP) (29). We further examined the five nonredundant SNPs that had shown positive nominal associations with response to troglitazone in the TRIPOD study (28) for a similar effect on troglitazone response in the DPP cohort.


   Patients and Methods
Top
 Abstract
 Introduction
 Patients and Methods
Results
 Discussion
 References
 
The Diabetes Prevention Program

The details of the study design and preventive interventions have been described elsewhere (29, 30, 31). The DPP was a 27-center randomized clinical trial that examined whether a lifestyle intervention directed at modifying risk factors for type 2 diabetes (overweight and sedentary lifestyle) or metformin would prevent or delay the development of diabetes in persons at high risk. The DPP enrolled 3234 nondiabetic persons with IGT and elevated fasting glucose and randomized them to placebo, 850 mg metformin twice daily, or a lifestyle intervention program; a fourth arm of 585 subjects assigned to treatment with 400 mg troglitazone daily was stopped 2 yr after the trial commenced because of hepatotoxicity (30). The principal end point was the development of diabetes, confirmed on a second test using American Diabetes Association criteria. The lifestyle and metformin interventions reduced the incidence of diabetes in high-risk individuals by 58% (95% CI, 48–66) and 31% (95% CI, 17–43), respectively, vs. placebo (29). Diabetes incidence rates were 11.0, 7.8, and 4.8 per 100 person-years in the placebo, metformin, and lifestyle groups, respectively; treatment effects were consistent across gender and self-reported ethnicity, and diabetes incidence did not differ across ethnic groups (29). When analyses were restricted to the mean 0.9-yr period of active troglitazone treatment, diabetes incidence rates were 12.0, 6.7, 5.1, and 3.0 per 100 person-years in the placebo, metformin, lifestyle, and troglitazone groups, respectively (P < 0.001, troglitazone vs. placebo) (32).

Participants

The 3548 participants included in this study (92.9% of all DPP participants: 2994 who completed the trial in their originally assigned treatment groups plus 554 originally randomized to troglitazone) provided informed consent specific to genetic investigation. The study was approved by the relevant Institutional Review Boards at the participating sites. Of the participants in this study, 56.4% were Caucasian, 20.2% were African-American, 16.8% were Hispanic, 4.3% were Asian-American, and 2.4% were American Indian by self-report. The participants’ mean age was 51 yr and mean body mass index (BMI) was 34.0 kg/m2. Subjects had semiannual measurements of fasting glucose and glycated hemoglobin and an annual 75-g oral glucose tolerance test (OGTT); given the early termination of the troglitazone arm, 1-yr data were available in only 340 of the participants randomly assigned to troglitazone.

PPARG SNP selection

In addition to P12A (rs1801282), we also genotyped five of the eight SNPs reported by Wolford et al. (28) to have positive nominal associations with response to troglitazone. The TRIPOD investigators found that of those eight SNPs (rs13073869, rs880663, rs4135263, rs1152003, rs6806708, rs13065455, rs13088205, and rs13088214), the first two and the last three were in perfect linkage disequilibrium with each other, respectively (r2 = 1.0); we therefore selected a nonredundant set of five SNPs for our analyses (rs880663, rs4135263, rs1152003, rs6806708, and rs13065455). We confirmed that these SNPs were indeed nonredundant in our five ethnic groups; with the exception of rs6806708 and rs13065455, which were in near-perfect linkage disequilibrium both in the original publication and in our samples (r2 = 0.9–1.0), the other SNPs had pairwise r2 ranging from 0.0 to 0.2 in Caucasians to 0.1 to 0.4 in American Indians.

Genotyping

DNA was extracted from peripheral blood leukocytes through conventional procedures and quantitated by picogreen analysis (Molecular Probes, Eugene, OR). Genotyping of PPARG P12A was performed in the forward and reverse directions by allele-specific primer extension of single-plex amplified products with detection by matrix-assisted laser desorption ionization–time of flight mass spectroscopy on a Sequenom platform as previously described (33); the five other PPARG SNPs were genotyped in the same manner but with single-direction primers only. Our genotyping success rate was 99.8%, and there were no discordant genotypes on forward and reverse primer extension. The allele frequencies of all six SNPs in each of the five ethnic groups were in Hardy-Weinberg equilibrium (P > 0.01).

Quantitative traits

Data from the baseline and 1-yr OGTTs were used to calculate measures of insulin secretion and insulin sensitivity, which were expressed using glucose and insulin measured in conventional units (milligrams per deciliter and microunits per milliliter, respectively) as previously described (34). The insulinogenic index (35) was calculated as [(insulin at 30 min) – (insulin at 0 min)]/[(glucose at 30 min) – (glucose at 0 min)]). The insulin sensitivity index [ISI, reciprocal of insulin resistance by the homeostasis model assessment (Ref. 36)] was calculated as 22.5/[fasting insulin x (fasting glucose/18.01)]. In addition, we examined fasting glucose and 2-h OGTT glucose at baseline and 1 yr.

Statistical analysis

Time to onset of diabetes was the primary end point. Because the previous literature consistently reports a recessive model of risk transmission for proline carriers at PPARG P12A, P/A and A/A individuals were grouped into one genotypic category (A/X). We examined Cox regression models with genotype, intervention, and their interactions as the independent variables predicting time to diabetes. These models were also examined with baseline BMI, waist circumference, age, gender, and self-reported ethnicity as covariates. Analyses were repeated in the subset of ethnic groups that had comparable allele frequencies (Caucasians, Hispanics, and Asian-Americans) and in Caucasians only; whether we restricted our analysis to these subgroups or tested for a genotype x ethnicity interaction, we detected no significant effect of self-reported ethnicity in any of our analyses.

For the quantitative trait comparisons, we first obtained baseline measures in the entire cohort according to genotype at PPARG P12A. Differences between means in the two genotypic groups (P/P and A/X) were tested using t tests. For the 1-yr measurements, a general linear model was examined with and without three-way interactions (treatment group, genotype, and baseline value of each trait). Least square means were adjusted for baseline values; two-sided nominal P values are reported. The SAS analysis system version 8.2 was used for all analyses (SAS Institute, Inc., Cary, NC).

To determine the potential effects of genotype on responsiveness to troglitazone, we calculated the ISI in the 340 DPP participants who completed 1 yr of troglitazone treatment at baseline and 1 yr. In accordance with the previous classification (28), we divided this group into tertiles of change in ISI (1-yr ISI minus baseline ISI) and assigned the top two tertiles as "responders" and the bottom tertile as "nonresponders"; we then examined allelic frequency differences between the two groups by {chi}2 analysis. In addition, we compared change in ISI as a quantitative trait according to genotype at all five loci by means of the nonparametric Kruskal-Wallis test; if nominally significant differences were found, pairwise comparisons between genotypic groups were performed with a Wilcoxon test with P values adjusted by the Holm procedure as previously described (37). We also compared 1-yr ISI as a quantitative trait according to genotypic group at all five loci, adjusted for baseline ISI, under the additive and recessive models. Finally, to control for allele frequency differences among populations, we repeated these analyses in the largest group (Caucasians) only.


   Results
Top
 Abstract
 Introduction
 Patients and Methods
 Results
Discussion
 References
 
Allele frequency distribution

For PPARG P12A, the frequency of the minor alanine allele in DPP U.S. Caucasians (0.10) was comparable to that previously reported in other Caucasian populations (4, 6, 8, 16). We found significant differences in minor allele frequencies in African-Americans (0.02) and American Indians (0.19) when compared with Caucasians; therefore, analyses for incidence of diabetes were performed both with and without these two ethnic groups.

At PPARG P12A, genotypic frequencies were equally distributed among the four treatment arms and two gender groups. We found no significant differences in baseline age or BMI, but P/P homozygotes appeared to have a smaller waist circumference (Table 1Go).


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  		TABLE 1. Demographic characteristics and baseline quantitative traits according to genotype at PPARG P12A in the DPP

 
Incidence of diabetes

Consistent with previous cross-sectional case-control results, the DPP showed that individuals who were homozygous for the proline allele appeared to progress more rapidly from IGT to diabetes than alanine carriers (HR, 1.24; 95% CI, 0.99–1.57; P = 0.07). We found no interaction between genotype and intervention (P value for the genotype x metformin interaction, 0.89; P value for the genotype x lifestyle interaction, 0.61). HRs were similar across all treatment arms (Fig. 1Go). In the placebo group, the HR was slightly higher but had wider 95% CIs (HR, 1.28; 95% CI, 0.90–1.82; P = 0.17). When the sample was restricted to the Caucasian group only, the overall HR for all treatment groups combined was statistically indistinguishable, but again with wide 95% CIs possibly as a result of the smaller sample size (HR, 1.18; 95% CI, 0.89–1.57; P = 0.24).


Figure 1
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  		FIG. 1. Incidence of diabetes per treatment arm and genotype at PPARG P12A in the Diabetes Prevention Program. A, All arms; B, placebo; C, metformin; D, lifestyle intervention.

 
When baseline BMI was added to the model, we noted a nominally significant genotype x BMI interaction (P = 0.03) such that alanine carriers were more susceptible to the deleterious effect of BMI on diabetes incidence than proline homozygotes (Fig. 2Go). Addition of the BMI interaction term to the model did not significantly alter the overall effect of genotype. Similar effects were noted for waist circumference (which is highly correlated with BMI in this cohort); there was a nominally significant interaction between genotype and waist circumference (P = 0.002); and in a model adjusting for baseline waist circumference, P/P homozygotes were more likely to progress to diabetes than alanine carriers (HR, 1.27; 95% CI, 1.01–1.60; P = 0.04).


Figure 2
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  		FIG. 2. Interaction of BMI with genotype at PPARG P12A on diabetes risk. The bar plot (left axis) shows incidence of diabetes (cases/100 person-years) in the placebo arm by quintile of baseline BMI for either alanine carriers or proline homozygotes at PPARG P12A. The line plot (right axis) shows the HR (P/P vs. A/X) in the full DPP cohort by quintile of baseline BMI. The protective effect of alanine seems to disappear at BMI more than 34.5 kg/m2.

 
Quantitative traits

At baseline, proline homozygotes and alanine carriers had indistinguishable indices of insulin sensitivity and insulin secretion (Table 1Go). At 1 yr, the lifestyle intervention, metformin, and troglitazone all led to significant improvements in insulin sensitivity as previously reported (32, 34); however, there were no significant differences in the magnitude of these improvements by genotype at PPARG P12A (Table 2Go). Examination of fasting and 2-h glucose levels after OGTT both at baseline and at 1 yr did not reveal significant differences between proline homozygotes and alanine carriers across all treatment groups (Table 1Go and data not shown).


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  		TABLE 2. One-year quantitative glycemic traits according to PPARG P12A genotypes by treatment arm in the DPP

 
Response to troglitazone

In addition to PPARG P12A, we examined the five PPARG SNPs rs880663, rs4135263, rs1152003, rs6806708, and rs13065455 for association with response to troglitazone. The median (25th–75th percentile) ISI (expressed in [(µU/ml) x (mmol/liter)]–1) for participants randomly assigned to troglitazone treatment at baseline was 0.163 (0.119–0.232). After 1 yr of troglitazone treatment, participants in the bottom tertile of change in ISI ("nonresponders") did not show any improvement in ISI (1-yr ISI minus baseline ISI, –0.070 ± 0.088, mean ± SD), whereas "responders" in the middle and upper tertiles did (1-yr ISI minus baseline ISI, +0.047 ± 0.028 and +0.252 ± 0.180, respectively). There were no significant allele frequency differences at any of the five loci between troglitazone "responders" and troglitazone "nonresponders" after 1 yr (Table 3Go).


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  		TABLE 3. Association testing of five PPARG SNPs for response to troglitazone at 1 yr in the DPP

 
When we analyzed change in ISI at 1 yr as a continuous trait, we noted a nominally significant higher change in ISI in rs880663 heterozygotes when compared with homozygotes for either allele (P = 0.02–0.04); no other nominally significant differences were found at any of the four remaining SNPs (Table 3Go). Similar results were obtained when we compared 1-yr ISI (adjusted for baseline ISI) across genotypic groups. Furthermore, in contrast with the results of Wolford et al. (28), homozygotes for the minor allele at all five SNPs had 1-yr ISI levels (adjusted for baseline ISI) indistinguishable from major allele carriers (P = 0.10–0.84). Adjustment for gender, baseline age, baseline BMI, or self-reported ethnicity did not change the results. Analyses restricted to the largest ethnic group (Caucasians only, n = 201) did not reveal any statistically significant differences in the response to troglitazone.


   Discussion
Top
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
References
 
A limited number of common genetic variants have been consistently associated with type 2 diabetes (22); these include PPARG P12A, the E23K polymorphism in the gene encoding the islet ATP-sensitive potassium channel Kir6.2 (KCNJ11) and SNPs in the gene that encodes calpain 10 (CAPN10). More recently, a common allele in the TCF7L2 gene has been convincingly associated with type 2 diabetes with an estimated allelic relative risk of 1.56 and high statistical significance (38). Although these validated associations have usually been tested in case-control samples, few studies have examined them prospectively and/or in regard to their effect on therapeutic interventions.

The DPP is a unique study in which to carry out such analyses. It differs from other diabetes prevention trials (39, 40) in that it included both lifestyle and pharmacological interventions; in addition, its multiethnic design reflects the diversity of the U.S. population. Moreover, its large sample size makes it adequate for genetic studies in which variants are thought to confer modest risk. An important distinction with other large observational trials (25) is the interventional design of the DPP and the exclusive enrollment of individuals with IGT, which suggests the presence of some degree of genetic risk at baseline and may introduce selection bias by imposing constraints at ascertainment. We have recently validated the association of common variants in TCF7L2 with development of diabetes in this cohort (33).

Genetic studies in multiethnic cohorts raise the issue of population stratification (41). We have addressed this possible confounder by repeating the analyses in the ethnic groups that have comparable allele frequencies, further restricting the analyses to the largest ethnic group alone, and explicitly testing for a genotype x ethnicity interaction. In addition, we note that in the short interval and high-risk population studied in the DPP, there were no significant differences in diabetes incidence across ethnic groups (29); thus, it is unlikely that differences in allele frequencies across populations have confounded our phenotypic results.

In agreement with both the Botnia Prospective Study (25) and the preponderance of the cross-sectional literature [and in contrast with the Finnish Diabetes Prevention Study (24)], we also observed a modest genetic risk conferred by the homozygous P/P genotype at PPARG P12A. Although the P values we obtained do not quite reach conventional statistical significance, the very high prior probability that PPARG P12A increases risk of type 2 diabetes makes us believe that the HRs we have noted here represent a real effect. Possible reasons for its lower magnitude in the DPP include the initial high-risk characteristics of the DPP cohort and the limited 3-yr window of the IGT-to-diabetes transition examined during this study. It is also possible that this variant may exert a stronger effect on the transition from normoglycemia to IGT rather than in the progression from IGT to diabetes.

By detecting a strong genotype x obesity interaction, we have been able to clarify some of the heterogeneity found in the literature, in which studies conducted in leaner populations tend to report higher odds ratios for risk associated with the P/P genotype (3, 5). Our data show that the protective effect of the alanine allele disappears at BMIs above approximately 35 kg/m2. Indeed, this might partially explain the apparent lack of a protective effect of the alanine allele in the Finnish Diabetes Prevention Study (24), in which A/A homozygotes were more obese than P/P homozygotes at baseline [BMI 33.0 ± 6.3 vs. 31.1 ± 4.4 kg/m2 (mean ± SD), respectively]. This interaction of PPARG P12A with BMI is also consistent with the increased skeletal muscle glucose uptake seen in lean but not obese (BMI > 27 kg/m2) alanine carriers when compared with P/P homozygotes (42).

Despite the well-documented effect that this missense polymorphism (in a gene that encodes the molecular target for thiazolidinedione medications) has on type 2 diabetes, we have been unable to detect a discernible impact of this variant on quantitative glycemic traits such as fasting glucose, 2-h glucose after an OGTT, or validated measures of insulin secretion and insulin sensitivity. In addition, both a lifestyle intervention and troglitazone treatment for 1 yr improved insulin sensitivity in proline homozygotes and alanine carriers to a similar degree. Our findings support similar results reported in smaller groups of 131 German subjects with type 2 diabetes treated with pioglitazone for 26 wk (26) or 93 Hispanic women with a history of gestational diabetes treated with troglitazone for 3 months (27), although the length of exposure to thiazolidinediones was modest for all three studies. If the small nonsignificant differences we observed between genotypic groups are real, we estimate that at least 3995 subjects would be needed to have 80% power to detect this difference at an {alpha} of 0.05, which in turn raises the question of its clinical relevance.

It is possible that other genetic variants at PPARG may affect thiazolidinedione response, although none of them has been convincingly associated with type 2 diabetes. Recently, a comprehensive set of common variants in PPARG was genotyped in the TRIPOD group of 93 Hispanic women with a history of gestational diabetes and examined for their impact on response to troglitazone. Allele frequencies at eight PPARG SNPs differed between the 63 responders and 30 nonresponders, although the sample was small and the P values modest (28). We have been unable to reproduce these findings of association for five of those SNPs in our larger cohort of 340 subjects. This lack of replication may be the result of the differences in duration of troglitazone treatment (3 months in TRIPOD vs. 1 yr in the DPP) differing estimates of insulin sensitivity (SI from iv glucose tolerance test vs. ISI from OGTT), phenotypic heterogeneity (gestational diabetes vs. IGT), ethnic variation, or statistical fluctuations; nevertheless, because the 95% CIs between both studies overlap, we cannot exclude that the results are mutually consistent. The nominally significant higher change in ISI at 1 yr in rs880663 heterozygotes in the DPP does not conform with the published data and does not follow a clear genetic model; given the multiple tests performed, this finding likely represents a false-positive result. The next logical step will be to test comprehensively all common variation at PPARG in the various ethnic groups of the DPP.

In summary, we have confirmed the modest protection from type 2 diabetes conferred by the alanine allele at PPARG P12A, we have shown a significant interaction of this variant with BMI and waist circumference; and in examining the largest cohort studied to date, we have not detected any significant effect of genotype at PPARG P12A in response to troglitazone.


   Acknowledgments
 
We thank Santica Marcovina and Greg Strylewicz for careful processing of the DNA samples and Mark Daly, Noël Burtt, and our colleagues at the Broad Institute Genetic Analysis Platform for excellent assistance. The investigators also gratefully acknowledge the commitment and dedication of the participants of the DPP.


   Footnotes
 
The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) of the National Institutes of Health (NIH) provided funding to the clinical centers and the Coordinating Center for the design and conduct of the study; and the collection, management, analysis, and interpretation of the data. The Southwestern American Indian Centers were supported directly by the NIDDK and the Indian Health Service. The General Clinical Research Center Program, National Center for Research Resources supported data collection at many of the clinical centers. Funding for data collection and participant support was also provided by the Office of Research on Minority Health, the National Institute of Child Health and Human Development, the National Institute on Aging, the Centers for Disease Control and Prevention, Office of Research on Women’s Health, and the American Diabetes Association. Bristol-Myers Squibb and Parke-Davis provided medication. This research was also supported, in part, by the intramural research program of the NIDDK. LifeScan Inc., Health O Meter, Hoechst Marion Roussel, Inc., Merck-Medco Managed Care, Inc., Merck and Co., Nike Sports Marketing, Slim Fast Foods Co., and Quaker Oats Co. donated materials, equipment, or medicines for concomitant conditions. McKesson BioServices Corp., Matthews Media Group, Inc., and the Henry M. Jackson Foundation provided support services under subcontract with the Coordinating Center. The opinions expressed are those of the investigators and do not necessarily reflect the views of the Indian Health Service or other funding agencies. A complete list of centers, investigators, and staff can be found in Ref. 30 . J.C.F. is supported by NIH Research Career Award 1 K23 DK65978-03. This work was supported, in part, by a Pilot and Feasibility Grant Award from the Boston Area Diabetes Endocrinology Research Center (BADERC) to J.C.F.

Disclosure Statement: The authors have nothing to declare.

First Published Online January 9, 2007

1 Members of the Diabetes Prevention Program Research Group are listed in the Appendix, published as supplemental data on The Endocrine Society’s Journals Online web site at http://jcem.endojournals.org. Back

Abbreviations: BMI, Body mass index; CI, confidence interval; DPP, Diabetes Prevention Program; HR, hazard ratio; IGT, impaired glucose tolerance; ISI, insulin sensitivity index; OGTT, oral glucose tolerance test; PPAR{gamma}, peroxisome proliferator-activated receptor {gamma}; SI, insulin sensitivity derived from an iv glucose tolerance test; SNP, single nucleotide polymorphism; TRIPOD, Troglitazone in Prevention of Diabetes.

Received October 18, 2006.

Accepted December 29, 2006.


   References
Top
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 

  1. Spiegelman BM 1998 PPAR-{gamma}: adipogenic regulator and thiazolidinedione receptor. Diabetes 47:507–514[Abstract]
  2. Lehmann JM, Moore LB, Smith-Oliver TA, Wilkison WO, Willson TM, Kliewer SA 1995 An antidiabetic thiazolidinedione is a high affinity ligand for peroxisome proliferator-activated receptor {gamma} (PPAR{gamma}). J Biol Chem 270:12953–12956[Abstract/Free Full Text]
  3. Deeb SS, Fajas L, Nemoto M, Pihlajamaki J, Mykkanen L, Kuusisto J, Laakso M, Fujimoto W, Auwerx J 1998 A Pro12Ala substitution in PPAR{gamma}2 associated with decreased receptor activity, lower body mass index and improved insulin sensitivity. Nat Genet 20:284–287[CrossRef][Medline]
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