OBJECTIVE—To determine whether the Pro12Ala polymorphism in the PPARγ gene was associated with risk of type 2 diabetes in the Nurses’ Health Study.

RESEARCH DESIGN AND METHODS—The study was a nested case-control study of 387 incident cases of type 2 diabetes and 771 matching control subjects nested within the Nurses’ Health Study, a prospective cohort study. Association between PPARγ genotype and incident type 2 diabetes was estimated using logistic regression.

RESULTS—Carriers of the PPARγ variant 12Ala allele had reduced risk of type 2 diabetes compared with noncarriers. Unadjusted and adjusted odds ratios of type 2 diabetes were 0.74 (95% CI 0.55–1.00) and 0.72 (0.52–0.99), respectively.

CONCLUSIONS—The results of this study provide further support for an inverse association between the PPARγ variant 12Ala allele and risk of type 2 diabetes.

One of the most promising and extensively studied genetic risk factors for type 2 diabetes is a polymorphism in the peroxisome proliferator-activated receptor PPARγ gene. In addition to its role in adipogenesis, PPARγ has a role in insulin signaling, insulin resistance, and development of type 2 diabetes and is the target for the thiazolidinedione class of antidiabetic drugs. The common codon 12 proline to alanine (Pro12Ala) substitution polymorphism produces PPARγ protein with lower transcriptional activity (1,2). Studies suggest that carriers of the 12Ala variant allele are at reduced risk of type 2 diabetes. The aim of the current study was to determine whether PPARγ Pro12Ala polymorphism was associated with reduced risk of type 2 diabetes in the Nurses’ Health Study.

The Nurses’ Health Study began in 1976 with the recruitment of 121,700 female registered nurses between the ages of 30 and 55 years (3). The participants were largely Caucasian (>95%). Samples for the present study were selected from a subcohort of 32,826 women who provided blood between 1989 and 1990 and were free from cardiovascular disease, cancer, and diabetes before giving blood. Incident cases were defined as self-reported diabetes confirmed by supplementary questionnaire and diagnosed at least 1 year after blood collection through 1996. The supplementary questionnaire obtained information on symptoms, diagnostic tests, and hypoglycemic therapy used to define type 2 diabetic cases. Diagnosis of type 2 diabetes was made using criteria consistent with those proposed by the National Diabetes Data Group (NDDG); the validity of this method has been confirmed (4,5). Although type 2 diabetes diagnosis criteria were changed in 1996, nearly all of these cases were diagnosed before 1996 and thus earlier NDDG criteria were used. Two control subjects were selected from the Nurses’ Health study blood cohort and matched to each case on the following variables: age, month and year of blood draw, and fasting status at blood draw. One of the two control subjects was also matched according to BMI (±1 kg/m2). Control subjects were free of any self-reported diabetes, cardiovascular disease, and cancer.

Genomic DNA was genotyped by Pyrosequencing using the following primers: PCR primers, 5′-BIOTIN-TTCACAAATTCTGTTACTTCA-3′ and 5′-TTGTGATATGTTTGCAGACA-3′, sequencing primer, 5′-ATCAGTGAAGGAATCGCTTTCT-3′ (Pyrosequencing AB, Uppsala, Sweden). Replicate quality control samples were included and genotyped with 100% concordance. Genotype frequencies were in Hardy-Weinberg equilibrium (P = 0.99).

Plasma insulin, C-peptide, and proinsulin were determined by radioimmunoassay in the laboratory of Dr. Robert M. Cohen (University of Cincinnati, Cincinnati, OH). Proinsulin and C-peptide were determined as previously described (6), and specific insulin was determined using a radioimmunoassay (Linco Research, St. Charles, MO). Within-individual coefficients of variation among the redundant samples were 13.9, 6.9, and 7.3% for insulin, C-peptide, and proinsulin, respectively.

All statistical analyses were performed using SAS version 6.12 (SAS Institute, Cary, NC). Odds ratios (ORs) were determined using unconditional multivariate logistic regression adjusting for type 2 diabetes risk factors, as indicated.

The PPARγ Pro/Pro homozygote, Pro/Ala heterozygote, and Ala/Ala homozygote genotype frequencies were 75.5% (n = 582), 23.0% (177), and 1.6% (12) among control subjects and 80.6% (n = 312), 18.6% (72), and 0.8% (3) among incident cases. Compared with Pro/Pro homozygotes, crude ORs were 0.76 (0.56–1.03) and 0.47 (0.13–1.67) for Pro/Ala heterozygotes and Ala/Ala homozygotes, respectively (P for trend = 0.04). Due to the low number of Ala/Ala individuals (15) and for consistency with published reports, Pro/Ala and Ala/Ala individuals were considered one group and compared with Pro/Pro individuals in all subsequent analyses. 12Ala PPARγ variant allele carriers did not differ appreciably from noncarriers with regard to the following diabetes risk factors: age, BMI, alcohol consumption, physical activity, and smoking (Table 1). PPARγ variant allele carriers had a reduced risk of type 2 diabetes with an unadjusted OR of 0.74 (0.55–1.00) (Table 2). Adjustment for age in addition to other type 2 diabetes risk factors (alcohol consumption, menopause status, BMI, physical activity, and smoking) did not substantially change the reduced diabetes risk associated with carrying the variant 12Ala PPARγ allele (Table 2).

Among control subjects, no association was detected between Pro12Ala polymorphism and plasma fasting insulin (mean value 12.0 and 11.3 μU/ml for Pro/Pro and 12Ala allele carriers, respectively, P = 0.68), C-peptide (mean value 0.63 and 0.56 pmol/ml for Pro/Pro and 12Ala allele carriers, respectively, P = 0.30) or proinsulin (mean value 12.1 and 10.5 fmol/ml for Pro/Pro and 12Ala allele carriers, respectively, P = 0.31).

The data presented here support an inverse association between 12Ala PPARγ allele and type 2 diabetes. In contrast to case-control studies that address the role of Pro12Ala PPARγ polymorphism, the current study is prospective. It has been argued that case-control studies, in general, are vulnerable to bias resulting from population stratification (7,8). In the current nested case-control study design, both incident cases and control subjects were chosen from the same largely Caucasian cohort assembled prospectively before disease incidence and thus control selection is less likely to be biased. The consistency observed between the current prospective study and previous reports suggests that population stratification did not appreciably bias the previous case-control studies. Although the present study shows a marginally significant association, when data from multiple association studies are considered collectively, the inverse association between the 12Ala variant PPARγ allele and type 2 diabetes is convincing. PPARγ Pro12Ala polymorphism is the most consistent genetic predictor of type 2 diabetes to date. Given the increasing incidence of type 2 diabetes, identification of genetically susceptible individuals may be particularly important for the success of early diagnosis, prevention, and intervention.

Table 1—

Descriptive characteristics of subjects by PPARγ genotype status

FactorPro/Pro homozygotesAla allele carriersP
n 894 264  
Age (years) 54.8 ± 7.0 54.2 ± 6.9 0.20* 
BMI (kg/m229.0 ± 5.9 28.7 ± 6.0 0.42* 
Alcohol    
 Nondrinkers (%) 23.9 24.0  
 Mean intake among drinkers (g/day) 8.1 ± 11.5 6.5 ± 8.0 0.35* 
Activity (metabolic units/week) 13.4 ± 16.6 14.7 ± 17.0 0.15* 
Smoking status    
 Never smoked 396 (44.4) 121 (46.0) 0.70 
 Former smoker 378 (42.4) 108 (41.1)  
 1–14 cigarettes/day 37 (4.2) 14 (5.3)  
 15–25 cigarettes/day 46 (5.2) 9 (3.4)  
 >25 cigarettes/day 34 (3.8) 11 (4.2)  
Family history of diabetes    
 No 611 (68.3) 192 (72.7) 0.18 
 Yes 283 (31.7) 72 (27.3)  
FactorPro/Pro homozygotesAla allele carriersP
n 894 264  
Age (years) 54.8 ± 7.0 54.2 ± 6.9 0.20* 
BMI (kg/m229.0 ± 5.9 28.7 ± 6.0 0.42* 
Alcohol    
 Nondrinkers (%) 23.9 24.0  
 Mean intake among drinkers (g/day) 8.1 ± 11.5 6.5 ± 8.0 0.35* 
Activity (metabolic units/week) 13.4 ± 16.6 14.7 ± 17.0 0.15* 
Smoking status    
 Never smoked 396 (44.4) 121 (46.0) 0.70 
 Former smoker 378 (42.4) 108 (41.1)  
 1–14 cigarettes/day 37 (4.2) 14 (5.3)  
 15–25 cigarettes/day 46 (5.2) 9 (3.4)  
 >25 cigarettes/day 34 (3.8) 11 (4.2)  
Family history of diabetes    
 No 611 (68.3) 192 (72.7) 0.18 
 Yes 283 (31.7) 72 (27.3)  

Data are mean ± SD or n (%).

*

P value from Wilcoxon rank-sum test;

P value from χ2 test.

Table 2—

OR for carriers of the variant Ala allele

Wild-type homozygotesVariant allele carriersP
Control subjects 582 189 — 
Cases 312 75 — 
Unadjusted* 1.0 0.74 (0.55–1.00) 0.05 
Multivariate 1.0 0.72 (0.52–0.99) 0.05 
Wild-type homozygotesVariant allele carriersP
Control subjects 582 189 — 
Cases 312 75 — 
Unadjusted* 1.0 0.74 (0.55–1.00) 0.05 
Multivariate 1.0 0.72 (0.52–0.99) 0.05 
*

Unconditional logistic regression with genotype as the only predictor;

Unconditional logistic regression adjusting for age, alcohol consumption, physical activity, smoking, and BMI.

Supported by National Institute of Health grants CA49449, DK058845, and DK046519. A.M. was supported by a postdoctoral training grant from the National Cancer Institute (CA09001).

1.
Yen CJ, Beamer BA, Negri C, Silver K, Brown KA, Yarnall DP, Burns DK, Roth J, Shuldiner AR: Molecular scanning of the human peroxisome proliferator activated receptor gamma (hPPAR gamma) gene in diabetic Caucasians: identification of a Pro12Ala PPAR gamma 2 missense mutation.
Biochem Biophys Res Commun
241
:
270
–274,
1997
2.
Deeb SS, Fajas L, Nemoto M, Pihlajamaki J, Mykkanen L, Kuusisto J, Laakso M, Fujimoto W, Auwerx J: A Pro12Ala substitution in PPARgamma2 associated with decreased receptor activity, lower body mass index and improved insulin sensitivity.
Nat Genet
20
:
284
–287,
1998
3.
Colditz GA, Manson JE, Hankinson SE: The Nurses’ Health Study: 20-year contribution to the understanding of health among women.
J Womens Health
6
:
49
–62,
1997
4.
Manson JE, Rimm EB, Stampfer MJ, Colditz GA, Willett WC, Krolewski AS, Rosner B, Hennekens CH, Speizer FE: Physical activity and incidence of non-insulin-dependent diabetes mellitus in women.
Lancet
338
:
774
–778,
1991
5.
National Diabetes Data Group: Classification and diagnosis of diabetes mellitus and other categories of glucose intolerance.
Diabetes
28
:
1039
–1057,
1979
6.
Cohen RM, Nakabayashi T, Blix PM, Rue PA, Shoelson SE, Root MA, Frank BH, Revers RR, Rubenstein AH: A radioimmunoassay for circulating human proinsulin.
Diabetes
34
:
84
–91,
1985
7.
Devlin B, Roeder K, Bacanu SA: Unbiased methods for population-based association studies.
Genet Epidemiol
21
:
273
–284,
2001
8.
Reich DE, Goldstein DB: Detecting association in a case-control study while correcting for population stratification.
Genet Epidemiol
20
:
4
–16,
2001

A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.