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The Journal of Clinical Endocrinology and Metabolism logoLink to The Journal of Clinical Endocrinology and Metabolism
. 2008 Nov 18;94(2):449–455. doi: 10.1210/jc.2008-1583

The Association of ENPP1 K121Q with Diabetes Incidence Is Abolished by Lifestyle Modification in the Diabetes Prevention Program

Allan F Moore 1,a, Kathleen A Jablonski 1, Clinton C Mason 1, Jarred B McAteer 1, Richard F Arakaki 1, Barry J Goldstein 1, Steven E Kahn 1, Abbas E Kitabchi 1, Robert L Hanson 1, William C Knowler 1, Jose C Florez 1; for the Diabetes Prevention Program Research Group1,b
PMCID: PMC2646511  PMID: 19017751

Abstract

Context: Insulin resistance is an important feature of type 2 diabetes. Ectoenzyme nucleotide pyrophosphatase phosphodiesterase 1 (ENPP1) inhibits insulin signaling, and a recent meta-analysis reported a nominal association between the Q allele in the K121Q (rs1044498) single nucleotide polymorphism in its gene ENPP1 and type 2 diabetes.

Objective and Intervention: We examined the impact of this polymorphism on diabetes incidence as well as insulin secretion and sensitivity at baseline and after treatment with a lifestyle intervention or metformin vs. placebo in the Diabetes Prevention Program (DPP).

Design, Setting, Participants, and Outcome: We genotyped ENPP1 K121Q in 3548 DPP participants and performed Cox regression analyses using genotype, intervention, and interactions as predictors of diabetes incidence.

Results: Fasting glucose and glycated hemoglobin were higher in QQ homozygotes at baseline (P < 0.001 for both). There was a significant interaction between genotype at rs1044498 and intervention under the dominant model (P = 0.03). In analyses stratified by treatment arm, a positive association with diabetes incidence was found in Q allele carriers compared to KK homozygotes [hazard ratio (HR), 1.38; 95% confidence interval (CI), 1.08–1.76; P = 0.009] in the placebo arm (n = 996). Lifestyle modification eliminated this increased risk. These findings persisted after adjustment for body mass index and race/ethnicity. Association of ENPP1 K121Q genotype with diabetes incidence under the additive and recessive genetic models showed consistent trends [HR, 1.10 (95% CI, 0.99–1.23), P = 0.08; and HR, 1.16 (95% CI, 0.92–1.45), P = 0.20, respectively] but did not reach statistical significance.

Conclusions: ENPP1 K121Q is associated with increased diabetes incidence; the DPP lifestyle intervention eliminates this increased risk.

The ectoenzyme nucleotide pyrophosphate phosphodiesterase (ENPP1) gene K121Q polymorphism is associated with diabetes incidence in the placebo arm of the Diabetes Prevention Program, but the lifestyle intervention eliminates this risk.

Insulin resistance is a common feature of type 2 diabetes (1). Although there is evidence of trait heritability (2), the genes responsible are largely unknown. Recent genomewide association scans have identified and confirmed new genetic variants mostly related to insulin secretion rather than insulin resistance (3).

Ectoenzyme nucleotide pyrophosphatase phosphodiesterase 1 (ENPP1 or PC-1) is a membrane glycoprotein that belongs to an enzyme family responsible for regulating pyrophosphate and nucleotide levels. ENPP1 reduces insulin signaling by direct inhibition of the insulin receptor’s tyrosine kinase activity, leading to decreased signal transduction (4,5). ENPP1 is expressed in multiple tissues including three targets of insulin action—adipose tissue, muscle, and liver (6). ENPP1 is elevated in cultured skin fibroblasts from nonobese, nondiabetic, insulin-resistant subjects when compared with cells from insulin-sensitive subjects (7). In a small study, Stentz and Kitabchi (8) recently extended these findings by demonstrating that expression of ENPP1 was increased 2-fold in T lymphocytes and myocytes of diabetic subjects compared with normal subjects. Furthermore, ENPP1 overexpression in cell culture decreases the cellular response to insulin challenge (9). Animal models transgenically engineered to overexpress ENPP1 become insulin resistant (9,10). There may also be a negative effect of ENPP1 expression on insulin secretion via insulin resistance at the level of the islet (11); recent findings in humans support this hypothesis (12).

A single nucleotide polymorphism in its gene ENPP1 (rs1044498), in which lysine 121 is replaced by glutamine (K121Q), may result in a gain-of-function mutation (5) leading to greater inhibition of the insulin receptor and clinical insulin resistance. Pizzuti et al. (13) first identified the association while studying healthy, nonobese, nondiabetic Sicilian subjects. The authors found that the minor Q allele carriers had a higher risk of being hyperinsulinemic and insulin resistant. These initial findings were supported by subsequent studies of Dominicans (14), Caucasians, and South Asians living in the United States (15). ENPP1 K121Q has also been associated with the earlier onset of type 2 diabetes in Europeans (16) and obese children (17), suggesting that the variant may accelerate disease onset in predisposed individuals.

Conversely, other studies have failed to replicate these results. An association with type 2 diabetes was not replicated in four subsequent large-scale association analyses, including studies performed in 7249 subjects from Denmark (18); 8089 Caucasian subjects from the United Kingdom (19); 8676 Scandinavian, Polish, and North American Caucasian subjects (20); and 911 unrelated Japanese subjects (21). However, a recent meta-analysis of 17,545 cases and 24,861 controls by McAteer et al. (22) found a positive association with type 2 diabetes among populations of European descent under a recessive genetic model [odds ratio, 1.38; 95% confidence interval (CI), 1.10–1.74; P = 0.005]; adjustment for mean body mass index (BMI) among control samples abolished the association (P = 0.50) (22,23). This relationship between ENPP1 K121Q and obesity remains ambiguous. Although there is evidence that ENPP1 is important for adipocyte maturation (24), ENPP1 K121Q has been associated with higher (25,26), lower (27,28), and similar (18) BMI values depending on the population under investigation and the stringency by which authors avoided confounding by occult type 2 diabetes or hyperinsulinemia.

The current study extends these findings and provides the opportunity for new insights into the role of ENPP1 K121Q on obesity and glucose metabolism through the study of 3548 subjects participating in the Diabetes Prevention Program (DPP). Furthermore, it examines the effect that race/ethnicity may have on the role ENPP1 K121Q plays on modulating glycemic parameters, given the significant differences in ENPP1 K121Q risk allele frequency between European and African populations. Finally, by studying subjects at increased risk of diabetes who are receiving placebo, lifestyle modification, or metformin in hopes of preventing hyperglycemia, it provides a unique opportunity to evaluate potential gene-environment interactions on glucose metabolism over time.

Subjects and Methods

Diabetes Prevention Program

The DPP study design has been described in detail in earlier publications (29). The DPP is a multicenter trial that examined whether lifestyle modification or pharmacological intervention prevents progression to diabetes in at-risk subjects. Inclusion criteria included a plasma glucose concentration of 95–125 mg/dl in the fasting state and 140–199 mg/dl after a 2-h, 75-g oral glucose tolerance test. Most participants were overweight or obese. The DPP randomized 3234 subjects to lifestyle modification (≥7% weight loss and ≥150 min of physical exercise weekly), metformin (850 mg twice daily), or placebo (a fourth arm of 585 participants randomized to troglitazone was stopped early because of hepatotoxicity). The primary endpoint of the DPP was cumulative diabetes incidence over the course of the study. At 3 yr, there was a 58% reduction in diabetes incidence in the lifestyle modification group and a 31% reduction in the metformin group compared with placebo (30). The trial was approved by the relevant Institutional Review Boards at the participating sites, and informed consent specific to genetic investigation was obtained for all participants in this study.

Single nucleotide polymorphism selection and genotyping

DNA was extracted from peripheral blood leukocytes in standard fashion. Genotyping was carried out by allele-specific primer extension of multiplex amplified products and detection using matrix-assisted laser desorption ionization-time-of-flight mass spectrometry on a Sequenom iPLEX platform. The genotyping success rate was greater than 99%, and ENPP1 K121Q (rs1044498) was in Hardy Weinberg equilibrium within each self-reported race/ethnic group.

Quantitative glycemic measures

Baseline and 1-yr oral glucose tolerance tests were collected on all subjects and used to calculate the insulin sensitivity index (ISI) as 22.5/[(fasting insulin × fasting glucose)/18.01]; this measure is the reciprocal of insulin resistance by homeostasis model assessment (31). The insulinogenic index was defined as [(insulin at 30 min) − (insulin at 0 min)]/[(glucose at 30 min) − (glucose at 0 min)] (32). Quantitative insulin-related traits were measured at baseline and 1 yr. We chose the 1-yr time point because the greatest effect on obesity measures was observed in the lifestyle modification group at yr 1 and because a significant number of subjects did not complete the yr 3 oral glucose tolerance test due to either development of diabetes or early trial termination.

Statistical analysis

We examined genotype (under dominant, additive, and recessive genetic models), intervention, and genotype-by-intervention interactions as independent predictors of time to onset of diabetes using Cox regression models. The log-log survivor function was used to assess the proportionality of the hazards. Baseline BMI-genotype interactions were also tested. The baseline insulin-related variables, ISI and insulinogenic index, were log-transformed for normality, and the geometric means were compared across genotypic groups (high-risk homozygotes, heterozygotes, and low-risk homozygotes) by general linear models (F test). For glucose-related baseline traits where results reached nominal statistical significance and for insulin-related traits, we further explored dominant and recessive genetic models. We compared the same glycemic variables at 1 yr using general linear models with the independent variables genotype and treatment group adjusted for the baseline glycemic variable with interaction terms of genotype and treatment. We also compared the change in ISI and insulinogenic index over 1 yr after adjusting for differences in baseline values. All analyses were repeated after adjustment for sex, age, self-reported race/ethnicity, and BMI. A P value of 0.05 was considered statistically significant, and the Holm procedure was used to adjust P values for multiple comparisons of the same trait across three genotypes (33).

Results

Baseline characteristics

Baseline characteristics are detailed in Table 1, with demographics listed at the top and baseline glucose-related traits at the bottom. The Q risk allele was the minor allele in the Hispanic (22.3%), Asian/Pacific Islander (15.9%), Caucasian (14.1%), and American Indian (12.4%) populations and the major allele in the African-American population (73.5%). The mean age was 50.5 yr. Mean BMI was higher with increased exposure to the Q allele (P < 0.001). This difference persisted after adjustment for sex but was greatly attenuated when each genotype was adjusted for race/ethnicity (P = 0.02), and it became nonsignificant when examined in Caucasians only. There was a trend toward a higher waist circumference with increased Q allele exposure; however, this finding was not significant. Baseline fasting plasma glucose and glycated hemoglobin levels were higher in the Q risk allele carriers (P < 0.001 for both), but these differences disappeared after adjusting for race/ethnicity.

Table 1.

Baseline characteristics

KK (low risk) KQ QQ (high risk) P Pdom Prec
n (%) 2061 (58.3) 1003 (28.4) 470 (13.3) <0.001
Age (yr) 51.1 (50.7–51.6) 50.2 (49.6–50.9) 50.6 (49.7–51.6) 0.08
Sex (%)
 Male 728 (62.2) 318 (27.2) 124 (10.6) <0.001
 Female 1333 (56.4) 685 (29.0) 346 (14.6) <0.001
Ethnic group (%)
 White 1464 (73.5) 494 (24.8) 35 (1.8) 0.36
 African-American 60 (8.4) 257 (36.2) 394 (55.4) 0.05
 Hispanic 362 (60.9) 199 (33.5) 33 (5.6) 0.42
 Asian/Pacific Islander 108 (71.5) 38 (25.2) <15a 0.47
 American Indian 67 (78.8) 15 (17.7) <15a 0.09
Body mass index (kg/m2) 33.5 (33.2–33.8) 34.5 (34.1–34.9) 35.0 (34.40–35.6) <0.001 <0.001 <0.001
 Adjusted for sex 33.1 (32.8–33.4) 34.0 (33.5–34.4) 34.3 (33.7–34.9) <0.001 <0.001 0.003
 Adjusted for race/ethnicity 33.2 (32.8–33.7) 34.0 (33.4–34.5) 33.7 (32.9–34.5) 0.02 0.008 0.97
Waist circumference (cm) 104.7 (104.0–105.3) 105.4 (104.5–106.3) 106.0 (104.7–107.3) 0.13
Fasting plasma glucose (mg/dl) 106.5 (106.2–106.9) 107.4 (106.9–107.9) 107.1 (106.4–107.8) 0.02 0.005 0.44
 Adjusted for age 106.5 (106.1–106.9) 107.4 (106.9–107.9) 107.1 (106.4–107.9) 0.01 0.004 0.43
 Adjusted for race/ethnicity 105.9 (105.4–106.5) 106.6 (105.9–107.2) 105.7 (104.7–106.7) 0.07 0.11 0.22
2-h postload glucose (mg/dl) 165.1 (164.4–165.9) 164.4 (163.3–165.4) 164.2 (162.7–165.8) 0.39
Glycated hemoglobin (%) 5.83 (5.81–5.84) 5.93 (5.90–5.97) 6.17 (6.12–6.21) <0.001 <0.001 <0.001
 Adjusted for age 5.83 (5.81–5.85) 5.94 (5.91–5.97) 6.17 (6.13–6.21) <0.001 <0.001 <0.001
 Adjusted for race/ethnicity 5.95 (5.91–5.98) 5.97 (5.95–6.01) 6.01 (5.95–6.07) 0.14 0.14 0.11
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Values represent number (percentage) for categorical variables, means (95% CI) for crude continuous variables, and least square means (95% CI) for adjusted continuous variables. P values (additive, dominant, and recessive) are from χ2 tests for categorical variables and F tests for continuous variables. P values associated with the ethnic groups are from tests for Hardy-Weinberg equilibrium. 

a

Per DPP policy, actual figures are not shown when the number of participants per cell is less than 15. 

Diabetes incidence

There was a significant interaction between genotype at rs1044498 and intervention under the dominant model (P = 0.03); therefore, subsequent analysis was stratified by treatment arm. Under a dominant genetic model, stratified analysis of age- and sex-adjusted data by treatment arm revealed an association between Q allele carriers and diabetes incidence in the placebo group [hazard ratio (HR), 1.38 (95% CI, 1.08–1.76); P = 0.009] as shown in Table 2. After further adjusting for race/ethnicity and baseline BMI, the results remained nominally significant [HR, 1.36 (95% CI, 1.02–1.80); P = 0.04]. The direction of effect was consistent in all ethnicities when analyzed separately, although the results did not reach statistical significance. The significant genotype-intervention interaction observed under the dominant genetic model (P = 0.03) suggested varying levels of risk in the different treatment arms according to genotype. This increased risk observed in the placebo group was eliminated by lifestyle modification [HR, 0.89 (95% CI, 0.63–1.25); P = 0.50] and reduced by metformin [HR, 1.08 (95% CI, 0.81–1.43); P = 0.60] as depicted in Fig. 1. Including BMI as a time-dependent variable under a dominant genetic model adjusted for age, sex, and race/ethnicity attenuated the interaction between genotype and intervention (P = 0.06).

Table 2.

HRs for incident diabetes by treatment arm and genotype at ENPP1K121Q

Group Basic model HR (95% CI) P Model with race/ethnicity HR (95% CI) P Model with race/ethnicity + BMI HR (95% CI) P
Placebo 1.38 (1.08–1.76) 0.01 1.38 (1.04–1.83) 0.03 1.36 (1.02–1.80) 0.04
Metformin 1.08 (0.81–1.43) 0.60 1.10 (0.79–1.54) 0.57 1.09 (0.78–1.53) 0.60
Lifestyle 0.89 (0.63–1.25) 0.51 0.81 (0.55–1.21) 0.31 0.83 (0.56–1.24) 0.37
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Estimates of HR are from a dominant genetic model (Q/X vs. K/K). All models are adjusted for age and sex. The interaction between treatment group and rs1044498 was nominally significant with P = 0.03. 

Figure 1.

Figure 1

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Diabetes incidence by treatment arm. Incidence of diabetes per treatment arm and genotype at ENPP1 K121Q in the Diabetes Prevention Program. A, Placebo arm; B, metformin arm; C, lifestyle arm.

Although there was a consistent trend toward increased diabetes incidence among Q allele carriers under the additive [HR, 1.10 (95% CI, 0.99–1.23); P = 0.08] and recessive [HR, 1.16 (95% CI, 0.92–1.45); P = 0.20] genetic models, the association did not reach statistical significance. There was no interaction between baseline BMI and genotype on diabetes incidence, either before or after adjusting for race/ethnicity under any genetic model (all P > 0.05).

Quantitative insulin-related traits

To explore the effect of this polymorphism on insulin secretion and action, mean insulin-related quantitative traits were compared across genotypes at baseline and after 1 yr of intervention; we also assessed the absolute change over the same interval. In the age- and sex-adjusted analysis of mean ISI and insulinogenic index values, carriers of the Q high-risk allele had decreased insulin sensitivity compared with KK homozygotes at baseline (P = 0.02) and after 1 yr of intervention (P = 0.03). This finding was attenuated when adjusted for race/ethnicity and abolished when BMI was added to the model. Mean insulinogenic index values were also significantly affected by race/ethnicity: in the age and sex-adjusted analysis, QQ high-risk genotype participants had increased insulin secretion compared with low-risk genotype participants at baseline (P < 0.0001) and at 1 yr (P < 0.001); however, significance was again lost after adjustment for race/ethnicity, with minor effects after further adjustment for BMI (Table 3). Changes in ISI and insulinogenic index values after 1 yr of treatment were not significant in the combined group or stratified by treatment arm (all P > 0.05). There were no significant interactions between genotype and intervention or genotype and BMI on these variables under the dominant genetic model at 1 yr.

Table 3.

Quantitative insulin-related traits

Trait Time point Genotype Basic model P Model with race/ethnicity P Model with race/ethnicity + BMI P
ISI Baseline KK 0.166 (0.162–0.170) 0.06 0.162 (0.156–0.168) 0.06 0.154 (0.149–0.160) 0.08
KQ 0.158 (0.152–0.163) 0.04* 0.157 (0.150–0.164) 0.34* 0.152 (0.146–0.159) 0.93*
QQ 0.164 (0.156–0.172) 0.88** 0.170 (0.158–0.182) 0.05** 0.164 (0.154–0.175) 0.03**
1 yr KK 0.201 (0.196–0.206) 0.04 0.192 (0.185–0.199) 0.34 0.187 (0.180–0.194) 0.38
KQ 0.199 (0.192–0.206) 0.13* 0.191 (0.183–0.200) 0.63* 0.188 (0.180–0.196) 0.89*
QQ 0.188 (0.178–0.197) 0.01** 0.182 (0.170–0.195) 0.14** 0.179 (0.168–0.191) 0.37**
Ins index Baseline KK 1.08 (1.05–1.12) <0.001 1.22 (1.16–1.28) 0.98 1.25 (1.19–1.31) 0.87
KQ 1.13 (1.08–1.19) 0.001* 1.21 (1.15–1.28) 0.85* 1.23 (1.16–1.30) 0.60*
QQ 1.27 (1.19–1.35) <0.001** 1.22 (1.12–1.32) 0.98** 1.24 (1.13–1.34) 0.99**
1 yr KK 1.05 (1.01–1.09) <0.001 1.13 (1.08–1.19) 0.75 1.15 (1.09–1.21) 0.78
KQ 1.11 (1.06–1.17) <0.001* 1.15 (1.08–1.22) 0.56* 1.16 (1.09–1.23) 0.67*
QQ 1.27 (1.19–1.35) <0.001** 1.18 (1.07–1.28) 0.54** 1.19 (1.09–1.30) 0.52**
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ISI and insulinogenic index (Ins index) compared by genotype at baseline or after 1 yr of intervention in the DPP. Least mean squares (95% CI) are shown. The basic model is adjusted for age and sex; subsequent models are further adjusted for race/ethnicity, without or with baseline BMI. One-year variables are also adjusted for the same variable at baseline. P values are from general linear models (F test). P values are shown for the general model, the dominant model (*), and the recessive model (**). 

Discussion

This study demonstrates that carriers of the Q risk allele at ENPP1 K121Q have an increased incidence of diabetes and that the lifestyle or metformin intervention arms of the DPP abolished this effect. These results remained significant after adjustment for sex, age, self-reported race/ethnicity, and BMI. Lifestyle modification eliminated and metformin reduced the increased risk imparted by ENPP1 K121Q in the placebo arm through a mechanism at least partially mediated by a reduction in BMI. These results suggest that carriers of the ENPP1 Q risk allele may benefit disproportionately from lifestyle modification or metformin therapy compared with K allele carriers.

At baseline, fasting plasma glucose and glycated hemoglobin levels both appeared to be highest in the high-risk QQ genotype group, in a direction consistent with the effects of genotype on diabetes risk. This is in agreement with Stolerman et al. (34) who recently reported that the ENPP1 121Q allele was associated with increased fasting plasma glucose, hemoglobin A1C, fasting insulin, and insulin resistance in the Framingham Heart Study. However, these differences disappeared after adjustment for race/ethnicity in the DPP. The remainder of our quantitative trait analysis was largely negative: although we initially identified significant changes in insulin sensitivity and secretion by genotype in the crude analysis of mean values, this finding was also lost when adjusted for race/ethnicity and BMI. Likewise, the adjusted analysis of changes over time in ISI and insulinogenic index after 1 yr of intervention was not significant in either the combined cohort or the stratified treatment arms. We may not have had enough power to identify a modest influence of ENPP1 genotype on insulin sensitivity and secretion. The specific enrollment characteristics of the DPP cohort, where participants were known to have impaired glucose tolerance with a truncated fasting glucose level to increase risk as well as increased weight at baseline (and therefore as a group had reduced variance around these traits), may have precluded us from detecting the same associations.

The apparent association of the ENPP1 K121Q polymorphism with baseline BMI in the DPP was significantly attenuated after adjustment for race/ethnicity and disappeared when analyses were stratified by race/ethnic group. This is also in agreement with Stolerman et al. (34) who found no association of K121Q with obesity in Framingham, although the effect of the Q risk allele on fasting plasma glucose and insulin resistance was stronger in obese subjects.

Because this polymorphism displays large allele frequency differences across populations, a particular association may be apparent merely because the putative risk allele tracks with ancestry rather than with the endpoint of interest. However, in the short interval and high-risk population studied in the DPP, there were no significant differences in diabetes incidence across ethnic groups (30); thus, it is unlikely that differences in allele frequencies across populations have confounded our incidence results. Indeed, when diabetes incidence was stratified by race/ethnicity, the direction of effect was consistent across all groups. On the other hand, the quantitative trait findings were abolished when controlled for race/ethnicity. This may be a result of differing allele frequencies in the various ethnicities, or it may be a result of different, as yet poorly understood, pathophysiological derangements induced by ENPP1 genotype that are unique to individual ethnicities. This study may also lack the statistical power to distinguish subtle differences in glycemic traits in single ethnic groups. Further investigation is required to understand better how race/ethnicity influences the impact of this variant on quantitative glycemic traits.

In summary, we have identified a positive association of ENPP1 K121Q with diabetes incidence in the multiethnic cohort of the DPP, a unique study that allows insight into potential genotype-intervention interactions in a cohort of subjects at risk for developing type 2 diabetes. The association is strongest in the placebo-treated group, suggesting that lifestyle modification or metformin therapy may be beneficial to subjects with the K121Q polymorphism. This is consistent with the previously reported interaction of this variant with BMI in conferring risk (26,35,36). This study adds more evidence to the growing body of literature suggesting that ENPP1 may play an important role in the pathophysiology of insulin resistance in genetically predisposed subjects; however, additional studies are required to clarify further the pathophysiology of ENPP1 K121Q and its relationship to type 2 diabetes, insulin resistance and secretion, obesity, and response to therapeutic intervention.

Supplementary Material

[Supplemental Data]
jc.2008-1583_index.html (813B, html)

Acknowledgments

The investigators gratefully acknowledge the commitment and dedication of all participants in the Diabetes Prevention Program, without whom this work would not have been possible.

Footnotes

This work was funded by Grant R01 DK072041 from the National Institutes of Health (to J.C.F. and K.A.J.). J.C.F. is supported by NIH Research Career Award K23 DK65978-05.

Present address for B.J.G.: Clinical Research, Department of Metabolism, Merck Research Laboratories, RY34-A212, PO Box 2000, 126 East Lincoln Avenue, Rahway, NJ 07065-0900.

The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) of the National Institutes of Health provided funding to the clinical centers and the Coordinating Center for the design and conduct of the study and for 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 the Appendix (published as supplemental data on The Endocrine Society’s Journals Online web site at http://jcem.endojournals.org).

Disclosure Statement: A.F.M., K.A.J., C.C.M., J.B.M., R.F.A., B.J.G., S.E.K., A.E.K., R.L.H., and W.C.K. have nothing to declare. J.C.F. has previously consulted for Merck, Publicis HealthCare, and BioStrategies.

First Published Online November 18, 2008

Abbreviations: BMI, Body mass index; CI, confidence interval; DPP, Diabetes Prevention Program; ENPP1, ectoenzyme nucleotide pyrophosphatase phosphodiesterase 1; HR, hazard ratio; ISI, insulin sensitivity index.

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