We assessed the association of four polymorphisms (promoter P3 −681C>G, P2 −689C>T, Pro12Ala, and 1431C>T) in peroxisome proliferator–activated receptor γ (PPARγ) with the metabolic syndrome risk in a large, French population study (n = 1,155). In this sample, 279 men and women presented with metabolic syndrome according to the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) criteria. When taken individually, none of the polymorphisms was significantly associated with the metabolic syndrome. Haplotype analyses, in contrast, revealed a significant enrichment of the GTGC haplotype frequency (corresponding to the P3 −681C>G, P2 −689C>T, Pro12Ala (C/G), and 1431C>T polymorphisms in this order) among those with metabolic syndrome compared with control subjects. Compared with the most common CCCC haplotype, the adjusted odds ratio (OR) (95% CI) of the metabolic syndrome for bearers of the GTGC haplotype was 2.37 (1.42–3.95; P = 0.002), 1.92 (1.00–3.72; P = 0.05), and 2.47 (1.09–5.62; P = 0.045) in the whole sample of men and women, respectively. Similar results were obtained when using another haplotype (GCCC, GTGT, CCCT, or GCCT) as a reference. Furthermore, when the GTGC haplotype frequency was tested alone (i.e., versus the frequency of the five other haplotypes together), the OR (95% CI) of the metabolic syndrome was 2.30 (1.05–5.00; P = 0.022). These data show that only the frequency of the GTGC haplotype was different between subjects with and without metabolic syndrome. Further analyses stratified on the 1431C>T single nucleotide polymorphism (SNP) indicated that the rare alleles of the P2 −689C>T and Pro12Ala SNPs were associated with an increased risk of the metabolic syndrome when combined to the 1431CC genotype. In conclusion, a specific haplotype of PPARγ polymorphisms is associated with an increased risk of the metabolic syndrome in a French general population.

The metabolic syndrome is a complex disorder (1) characterized by the clustering of several metabolic diseases, such as abdominal obesity, insulin resistance, elevated plasma triglyceride levels, low HDL cholesterol, high blood pressure, and altered glucose homeostasis. In adults, the metabolic syndrome prevalence ranges between 15 and 25%. Environmental factors such as low physical activity and inappropriate dietary habits are strong determinants of the metabolic syndrome. In addition, genetic factors also contribute to the individual susceptibility to the metabolic syndrome (2).

Many studies have investigated the associations between genetic polymorphisms and the various components of the metabolic syndrome. Very few, in contrast, have explored this association with the metabolic syndrome as an entity, i.e., defined according to the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) (3), the World Health Organization (4), the European Group for the Study of Insulin Resistance (5), or the International Diabetes Federation criteria (6). The later investigations have reported significant associations between the metabolic syndrome and polymorphisms in the lamin A/C (7), the peroxisome proliferator–activated receptor γ (PPARγ) (8), the angiotensinogen-1–converting enzyme (9,10), the LDL-related protein-associated protein 1 (11), and the β2-adrenergic receptor (12) genes.

PPARγ is a nuclear receptor implicated in adipocyte differentiation orchestration, fatty acid metabolism, and insulin sensitization and is therefore a good candidate gene for the metabolic syndrome. Loss-of-function mutations of PPARγ confer an extreme phenotype of partial lipodystrophy, early-onset severe insulin resistance, type 2 diabetes, dyslipidemia, hypertension, and hepatic steatosis (rev. in 13). Many studies explored the association between the Pro12Ala polymorphism in PPARγ and obesity, insulin sensitivity, and type 2 diabetes (rev. in 14). It appears that the Ala12 allele confers modest protection against the onset of type 2 diabetes and is also associated with an increased BMI in overweight individuals. In view of reported contradictory associations between PPARγ polymorphisms and obesity and diabetes, we thought to evaluate the possible association between several polymorphisms in PPARγ and the metabolic syndrome in a large, French, population-based study (n = 1,155). Four PPARγ polymorphisms were tested: the promoter P3 −681C>G, P2 −689C>T, Pro12Ala, and 1431C>T in individual and haplotype analyses.

Participants were recruited within the framework of the WHO-MONICA (World Health Organization Multinational Monitoring of Trends and Determinants in Cardiovascular Disease) population survey conducted from 1995 to 1997 in the urban community of Lille in the north of France. The sample included subjects aged 35–64 years, randomly selected from the electoral rolls to obtain 200 participants for each sex and 10-year age-group (15,16). A total of 601 men and 594 women were recruited. To our knowledge, no individuals were related. The ethical committee of Lille University Hospital (Centre Hospitalier Régoinale Universitaire de Lille) approved the protocol.

After signing an informed consent, participants were administered a standard questionnaire, and physical measurements were made by a trained nurse. The level of physical activity was defined as walking or riding ≥15 min/day and/or lifting or carrying heavy objects at work daily and/or doing sports or physical exercise >2 h/week. Current cigarette smokers were defined as subjects reporting at least one cigarette per day. Total alcohol intake was expressed as the sum of millileters of alcohol per week from wine, beer, cider, and spirits.

The anthropometric measurements included body weight and waist and hip circumferences. BMI was calculated according to the Quetelet equation. Blood pressure was measured on the right arm, with the subject in a sitting position and after a minimum 5-min rest, using a standard mercury sphygmomanometer. The mean value of two consecutive blood pressure readings was taken into account.

The metabolic syndrome was defined, according to the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) recommendations (3), by the presence of at least three or more of the following abnormalities: waist girth >102 cm in men or >88 cm in women, triglycerides ≥1.50 g/l or lipid-lowering treatment, HDL cholesterol <40 mg/dl in men or <50 mg/dl in women, blood pressure ≥130/85 mmHg or treatment with blood pressure–lowering medications, and fasting glucose ≥1.10 g/l or treatment for diabetes.

Laboratory methods.

A blood sample of 20 ml was drawn on disodium EDTA after the subjects had fasted for at least 10 h. Lipid and lipoprotein levels were measured in a central laboratory (Purpan Hospital Biochemical Laboratory, Toulouse, France). The quality of biological measures was assessed within the framework of the MONICA Project. Glucose was measured by the glucose oxidase method (DuPont Dimension). Serum triglyceride levels were enzymatically measured (DuPont Dimension). HDL cholesterol was measured after sodium phosphotungstate/magnesium chloride precipitation (Boehringer Mannheim, Mannheim, Germany).

Genotyping.

The genotyping method for the PPARγ polymorphisms has been described elsewhere: P3 −681C>G (17), P2 −689C>T (18), Pro12Ala (19), and 1431C>T (20).

Statistical methods.

χ2 analysis was used to compare genotype and allele distributions between groups. Logistic regression analysis was used to calculate the odds ratio (OR) of the metabolic syndrome associated with a given polymorphism. Adjustment variables were age, alcohol, smoking, and physical activity in analyses in men and women separately or further adjusting on sex in combined men and women analyses. The dominant and recessive models were tested. Analyses were performed with the SAS statistical software release 8 (SAS Institute, Cary, NC). Haplotype analyses were based on the maximum likelihood model described in (21) and linked to the SEM algorithm (22) and performed using the software developed by the Institut National de la Santé et de la Recherche Médicale (INSERM U525), Paris, France.

Table 1 describes the clinical characteristics of the population studied. Table 2 shows the genotype frequencies in the metabolic syndrome and control subjects for the four PPARγ polymorphisms. These frequencies were not different from the expected frequencies under Hardy-Weinberg equilibrium. No significant differences could be observed between the two clinical groups, either in men, in women, or in combined men and women. The corresponding OR of the metabolic syndrome for carriers of the rare allele versus homozygotes for the common allele of the four polymorphisms (dominant model) are presented in Table 3. These ORs varied from 0.75 to 1.39 (all NS). A recessive model was also tested, but no more significant OR could be observed (data not shown).

We then performed haplotype analyses, including the four polymorphisms in the following order: P3 −681C>G, P2 −689C>T, Pro12Ala, and 1431C>T. Of 16 expected haplotypes, 5 were not detected (CCGT, CTCT, CTGC, GCGC, and GTCT) and 5 others (CCGC, CTCC, CTGT, GCGT, and GTCC) were present at a frequency <1%, due to a strong linkage disequilibrium existing between three single nucleotide polymorphisms (SNPs) (−681C>G, −689C>T, and Pro12Ala) (D′ = 0.96). The 1431C>T polymorphism was in linkage disequilibrium at only 66% with the three others. Consequently, only six haplotypes with a frequency >1% could be used in the haplotype analyses. In combined men and women, there was a global significant effect (P = 0.045) of the haplotypes on the metabolic syndrome risk (Table 4). The frequency of the GTGC haplotype was higher in subjects with metabolic syndrome (5%) compared with control subjects (2.2%). The adjusted OR of the metabolic syndrome for the GTGC haplotype bearers was 2.37 (95% CI 1.42–3.95; P = 0.002) (OR adjusted on age, sex, physical activity, smoking, and alcohol consumption) when compared with CCCC haplotype bearers. Similar results were obtained when using another haplotype as a reference: 2.33 (1.40–3.88; P = 0.002), 2.34 (1.41–3.90; P = 0.002), 2.33 (1.40–3.89; P = 0.002), or 2.33 (1.40–3.89; P = 0.002) when using the GCCC, GTGT, CCCT, or GCCT haplotype as a reference, respectively. Furthermore, when the GTGC haplotype frequency was tested alone (i.e., versus the frequency of the five other haplotypes together), the OR (95% CI) of the metabolic syndrome was 2.30 (1.05–5.00; P = 0.022). These data show that only the frequency of the GTGC haplotype was different between subjects with and without metabolic syndrome. When the analyses were performed in men and women separately, similar results were found. The adjusted OR (on age, physical activity, smoking, and alcohol consumption) of the metabolic syndrome for the GTGC haplotype bearers was 1.92 (1.00–3.72; P = 0.05) and 2.47 (1.09–5.62; P = 0.045) in men and women, respectively, when compared with CCCC haplotype bearers. There was no evidence of any statistically significant associations for the other haplotypes.

We tested various criteria available for the metabolic syndrome and were able to confirm an increased risk of the metabolic syndrome in GTGC haplotype bearers whatever the criteria used: OR 2.31 (95% CI 1.30–4.11; P = 0.004) with the European Group for the Study of Insulin Resistance definition (5) (832 control/167 case subjects) and 2.29 (1.37–3.82; P = 0.002) with the International Diabetes Federation definition (6) (712 control/384 case subjects). We could not test the World Health Organization definition in our sample because this definition is principally based on insulin resistance and/or impaired glucose regulation, and these measurements are not available in our sample.

It appeared from Table 4 that the presence of the C1431 allele was necessary to observe a deleterious effect of the rare alleles of the −681C>G, −689C>T, and Pro12Ala SNPs on the metabolic syndrome. Because these three SNPs were in complete linkage disequilibrium, we then analyzed the individual impact of these SNPs on the metabolic syndrome in CC or CT subjects for the 1431C>T SNP to assess the relative contribution of each SNP (Table 5). No significant association could be observed between the −681C>G SNP and the metabolic syndrome in 1431CC or CT subjects, suggesting that the −681C>G SNP had no impact on the metabolic syndrome risk. On the contrary, a significantly higher risk of the metabolic syndrome was observed in −689T (OR 1.95 [95% CI 1.12–3.37]; P = 0.018) or Ala12 (2.48 [1.38–4.44]; P = 0.002) allele bearers if they also carried the 1431CC genotype. No such association was observed in 1431CT bearers.

In a large, French, population-based study, we showed that the GTGC haplotype constituted by the PPARγ P3–681C>G, P2–689C>T, Pro12Ala, and 1431C>T polymorphisms was associated with an increased risk of the metabolic syndrome in both men and women. This association was accounted for by the rare alleles of the P2 −689C>T and Pro12Ala polymorphisms on a PPARγ 1431CC genotype background. These data suggest that PPARγ gene variability may increase the risk of the metabolic syndrome.

In the present study, there was no evidence of a significant impact of individual polymorphisms of PPARγ on the metabolic syndrome risk. In contrast, in the Danish MONICA survey, Frederiksen et al. (8) have found a borderline statistical association between the homozygous Ala/Ala genotype and the metabolic syndrome defined according to the European Group for the Study of Insulin Resistance criteria (294 case/1,951 control subjects). However, this association was based on a very limited number of homozygous Ala12Ala subjects (n = 2), which may hamper the interpretation of the data. In the present study, analyses with the Pro12Ala polymorphism using a recessive model and the European Group for the Study of Insulin Resistance criteria (data not shown) revealed no association between PPARγ Pro12Ala polymorphism and the metabolic syndrome, suggesting that early findings may be spurious. To our knowledge, there has been no other analysis of the relationship between PPARγ SNPs and the metabolic syndrome. Therefore, additional studies are needed to confirm these data.

Haplotype analyses, in contrast, revealed an association between the GTGC haplotype and the metabolic syndrome in both men and women. Further analyses stratifying for the 1431C>T SNP indicated that the P2 –689T and Ala12, but not the P3 –681G rare alleles, accounted for the increased metabolic syndrome risk when present on the 1431CC background. This result is consistent with a previous study (23) that has shown that the Ala12Ala genotype conferred an increased risk of type 2 diabetes when associated with the 1431CC genotype but not the 1431TT genotype. Our study further extends this analysis to the P3 –681C>G and P2 –689C>T SNPs. Other studies (24), in contrast, have reported higher BMI in women carrying both the homozygous Ala12Ala and 1431TT genotypes compared with Pro12Pro/1431CC women. Similarly, the Ala12-1431C haplotype was associated with lower BMI compared with Pro-1431C haplotype carriers in both diabetic and nondiabetic Scottish populations (25), and the 1431C allele conferred a protection against type 2 diabetes (26). The reasons for these discrepancies are not known. One possible explanation may be related to the selection of diabetic or obese patients as opposed to a random population-based sample. Such selection procedures may have introduced a bias in the sample. Other possible explanations may be related to the lack of sufficient statistical power. Finally, possible interactions with other genes as well as uncontrolled environmental factors such as diet may also explain the difference between studies, although these hypotheses need further analyses.

It is quite difficult to provide a potential mechanism by which a particular haplotype of PPARγ could promote susceptibility to the metabolic syndrome. In rodents, supraphysiological activation of PPARγ by thiazolidinediones markedly increases triglyceride content of white adipose tissue, thereby decreasing triglyceride content of liver and muscle, leading to amelioration of insulin resistance at the expense of obesity. In contrast, moderate reduction of PPARγ activity by heterozygous PPARγ deficiency decreases triglyceride content of white adipose tissue, skeletal muscle, and liver due to increased leptin expression and increase in fatty acid combustion and decrease in lipogenesis, thereby ameliorating high-fat diet–induced obesity and insulin resistance (27). From the human point of view, a point mutation leading to the permanent activation of PPARγ is associated with severe obesity (28), whereas dominant-negative mutations in PPARγ lead to a monogenic model of the metabolic syndrome in association with a stereotyped form of partial lipodystrophy (29). The metabolic syndrome we study in our sample is associated with abdominal obesity and not lipodystrophy. Therefore, the PPARγ GTGC haplotype is likely to be associated with higher PPARγ activity, consequently leading to higher adipocyte differentiation, which might explain the fact that the −681C>G, −689C>T, and Pro12Ala polymorphisms are associated with higher body weight and fat mass in our sample. This phenomenon, in turn, induces the storage of triglycerides conducting to insulin resistance and associated disorders (metabolic syndrome).

The present study has some strengths and limitations. It was conducted in a large random sample of population, which avoids possible bias due to recruitment in hospitals or clinics and university staff or students. We analyzed four SNPs at the same time, which offers a better biological assessment of the gene variability. Due to the high levels of linkage disequilibrium among the SNPs, haplotype analyses were performed (22), which allowed us to account for covariability. Our results showed that only the GTGC haplotype frequency was different from the frequencies of other haplotypes between subjects with and without metabolic syndrome. The analyses were performed in men and women separately, which is an important advantage with regards to the impact of sex on morphology and the metabolic syndrome. Although the frequency of the GTGC haplotype is low, the finding of consistent statistically significant associations in both men and women further supports the strength of this association. Finally, the association between PPARγ haplotypes and the metabolic syndrome risk was independent of the definition of the metabolic syndrome. These results support the fact that PPARγ might play a role in the occurrence of this syndrome in general populations. The major limitation of the study may be the relative small size of the sample. However, to our knowledge, this is one of the largest studies with metabolic syndrome subjects.

In conclusion, our study highlights the fact that taking into account the combination of several SNPs is essential in characterizing the phenotypic impact of PPARγ. We have shown that the haplotype composed of the P2 –689T, Ala12, and 1431C alleles of PPARγ enhances susceptibility to the metabolic syndrome in a large, population-based population of French men and women.

TABLE 1

Description of the study population by sex

Men
Women
Control subjectsMetabolic syndromePControl subjectsMetabolic syndromeP
n (%) 410 (72.6) 155 (27.4) — 445 (78.2) 124 (21.8) — 
Age (years) 50 ± 9 53 ± 9 0.0003 50 ± 8 55 ± 8 <0.0001 
Physically active 40 30 0.02 29 15 0.003 
Alcohol (ml/week) 316 ± 291 363 ± 315 NS 106 ± 130 153 ± 215 0.003 
Smoker 32 33 NS 18 9 <0.05 
BMI (kg/m2) 25.4 ± 3.4 30.0 ± 4.2 <0.0001 25.0 ± 4.6 31.8 ± 5.9 <0.0001 
Waist (cm) 92.5 ± 9.0 106.3 ± 9.6 <0.0001 81.0 ± 11.3 101.3 ± 11.6 <0.0001 
Glucose (g/l) 0.96 ± 0.10 1.19 ± 0.36 <0.0001 0.91 ± 0.09 1.21 ± 0.45 <0.0001 
Insulin (μU/ml) 9.9 ± 4.9 18.2 ± 14.0 <0.0001 10.4 ± 4.5 15.4 ± 8.2 <0.0001 
SBP (mmHg) 133 ± 19 145 ± 18 <0.0001 126 ± 17 145 ± 18 <0.0001 
DBP (mmHg) 84 ± 11 91 ± 12 <0.0001 79 ± 10 87 ± 10 <0.0001 
Triglycerides (g/l) 1.10 ± 0.70 2.36 ± 1.71 <0.0001 0.83 ± 0.36 1.84 ± 1.37 <0.0001 
Cholesterol (g/l) 2.26 ± 0.40 2.34 ± 0.42 0.033 2.26 ± 0.42 2.40 ± 0.47 0.001 
HDL (g/l) 0.55 ± 0.16 0.41 ± 0.11 <0.0001 0.68 ± 0.18 0.50 ± 0.16 <0.0001 
Men
Women
Control subjectsMetabolic syndromePControl subjectsMetabolic syndromeP
n (%) 410 (72.6) 155 (27.4) — 445 (78.2) 124 (21.8) — 
Age (years) 50 ± 9 53 ± 9 0.0003 50 ± 8 55 ± 8 <0.0001 
Physically active 40 30 0.02 29 15 0.003 
Alcohol (ml/week) 316 ± 291 363 ± 315 NS 106 ± 130 153 ± 215 0.003 
Smoker 32 33 NS 18 9 <0.05 
BMI (kg/m2) 25.4 ± 3.4 30.0 ± 4.2 <0.0001 25.0 ± 4.6 31.8 ± 5.9 <0.0001 
Waist (cm) 92.5 ± 9.0 106.3 ± 9.6 <0.0001 81.0 ± 11.3 101.3 ± 11.6 <0.0001 
Glucose (g/l) 0.96 ± 0.10 1.19 ± 0.36 <0.0001 0.91 ± 0.09 1.21 ± 0.45 <0.0001 
Insulin (μU/ml) 9.9 ± 4.9 18.2 ± 14.0 <0.0001 10.4 ± 4.5 15.4 ± 8.2 <0.0001 
SBP (mmHg) 133 ± 19 145 ± 18 <0.0001 126 ± 17 145 ± 18 <0.0001 
DBP (mmHg) 84 ± 11 91 ± 12 <0.0001 79 ± 10 87 ± 10 <0.0001 
Triglycerides (g/l) 1.10 ± 0.70 2.36 ± 1.71 <0.0001 0.83 ± 0.36 1.84 ± 1.37 <0.0001 
Cholesterol (g/l) 2.26 ± 0.40 2.34 ± 0.42 0.033 2.26 ± 0.42 2.40 ± 0.47 0.001 
HDL (g/l) 0.55 ± 0.16 0.41 ± 0.11 <0.0001 0.68 ± 0.18 0.50 ± 0.16 <0.0001 

Data are means ± SD or percent, unless otherwise indicated. DBP, diastolic blood pressure; SBP, systolic blood pressure.

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TABLE 2

Genotype frequencies of the PPARγ polymorphisms in individuals with and without metabolic syndrome

PolymorphismsCombined
Men
Women
Control subjectsMetabolic syndromePControl subjectsMetabolic syndromePControl subjectsMetabolic syndromeP
PPARγ CC 470 (56.4) 143 (53.2)  223 (55.3) 74 (49.3)  247 (57.4) 69 (58.0)  
−681C>G CG 310 (37.2) 109 (40.5) 0.61 159 (39.5) 66 (44.0) 0.43 151 (35.1) 43 (36.1) 0.84 
 GG 53 (6.4) 17 (6.3)  21 (5.2) 10 (6.7)  32 (7.5) 7 (5.9)  
PPARγ CC 655 (78.4) 208 (75.4)  303 (74.6) 114 (74.5)  352 (81.9) 94 (76.4)  
−689C>T CT 169 (20.2) 61 (22.1) 0.36 96 (23.7) 34 (22.2) 0.51 73 (17.0) 27 (22.0) 0.40 
 TT 12 (1.4) 7 (2.5)  7 (1.7) 5 (3.3)  5 (1.1) 2 (1.6)  
PPARγ ProPro 666 (79.5) 207 (75.6)  308 (76.1) 114 (74.5)  358 (82.7) 93 (76.9)  
Pro12Ala ProAla 160 (19.1) 60 (21.9) 0.25 90 (22.2) 34 (22.2) 0.53 70 (16.2) 26 (21.5) 0.35 
 AlaAla 12 (1.4) 7 (2.6)  7 (1.7) 5 (3.3)  5 (1.1) 2 (1.6)  
PPARγ CC 623 (74.1) 210 (76.1)  293 (72.2) 112 (73.2)  330 (75.9) 98 (79.7)  
1431C>T CT 205 (24.4) 62 (22.5) 0.80 108 (26.6) 38 (24.8) 0.76 97 (22.3) 24 (19.5) 0.56 
 TT 13 (1.5) 4 (1.4)  5 (1.2) 3 (2.0)  8 (1.8) 1 (0.8)  
PolymorphismsCombined
Men
Women
Control subjectsMetabolic syndromePControl subjectsMetabolic syndromePControl subjectsMetabolic syndromeP
PPARγ CC 470 (56.4) 143 (53.2)  223 (55.3) 74 (49.3)  247 (57.4) 69 (58.0)  
−681C>G CG 310 (37.2) 109 (40.5) 0.61 159 (39.5) 66 (44.0) 0.43 151 (35.1) 43 (36.1) 0.84 
 GG 53 (6.4) 17 (6.3)  21 (5.2) 10 (6.7)  32 (7.5) 7 (5.9)  
PPARγ CC 655 (78.4) 208 (75.4)  303 (74.6) 114 (74.5)  352 (81.9) 94 (76.4)  
−689C>T CT 169 (20.2) 61 (22.1) 0.36 96 (23.7) 34 (22.2) 0.51 73 (17.0) 27 (22.0) 0.40 
 TT 12 (1.4) 7 (2.5)  7 (1.7) 5 (3.3)  5 (1.1) 2 (1.6)  
PPARγ ProPro 666 (79.5) 207 (75.6)  308 (76.1) 114 (74.5)  358 (82.7) 93 (76.9)  
Pro12Ala ProAla 160 (19.1) 60 (21.9) 0.25 90 (22.2) 34 (22.2) 0.53 70 (16.2) 26 (21.5) 0.35 
 AlaAla 12 (1.4) 7 (2.6)  7 (1.7) 5 (3.3)  5 (1.1) 2 (1.6)  
PPARγ CC 623 (74.1) 210 (76.1)  293 (72.2) 112 (73.2)  330 (75.9) 98 (79.7)  
1431C>T CT 205 (24.4) 62 (22.5) 0.80 108 (26.6) 38 (24.8) 0.76 97 (22.3) 24 (19.5) 0.56 
 TT 13 (1.5) 4 (1.4)  5 (1.2) 3 (2.0)  8 (1.8) 1 (0.8)  

Data are n (%).

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TABLE 3

ORs of the metabolic syndrome according to PPARγ polymorphisms

PolymorphismsCombined
Men
Women
OR (95% CI)POR (95% CI)POR (95% CI)P
PPARγ        
 CC vs. CG+GG 1.11 (0.83–1.47) 0.48 1.27 (0.86–1.86) 0.23 0.91 (0.59–1.41) 0.68 
−681C>G        
PPARγ        
 CC vs. CT+TT 1.18 (0.86–1.63) 0.30 1.01 (0.66–1.54) 0.98 1.39 (0.86–2.26) 0.18 
−689C>T        
PPARγ        
 CC vs. CG+GG 1.15 (0.83–1.61) 0.40 1.03 (0.66–1.60) 0.91 1.20 (0.72–2.02) 0.49 
Pro12Ala        
PPARγ        
 CC vs. CT+TT 0.86 (0.62–1.19) 0.37 0.92 (0.60–1.42) 0.70 0.75 (0.45–1.26) 0.28 
1431C>T        
PolymorphismsCombined
Men
Women
OR (95% CI)POR (95% CI)POR (95% CI)P
PPARγ        
 CC vs. CG+GG 1.11 (0.83–1.47) 0.48 1.27 (0.86–1.86) 0.23 0.91 (0.59–1.41) 0.68 
−681C>G        
PPARγ        
 CC vs. CT+TT 1.18 (0.86–1.63) 0.30 1.01 (0.66–1.54) 0.98 1.39 (0.86–2.26) 0.18 
−689C>T        
PPARγ        
 CC vs. CG+GG 1.15 (0.83–1.61) 0.40 1.03 (0.66–1.60) 0.91 1.20 (0.72–2.02) 0.49 
Pro12Ala        
PPARγ        
 CC vs. CT+TT 0.86 (0.62–1.19) 0.37 0.92 (0.60–1.42) 0.70 0.75 (0.45–1.26) 0.28 
1431C>T        
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TABLE 4

Haplotype frequencies in individuals with or without a metabolic syndrome

HaplotypesCombined
Men
Women
Control subjectsMetabolic syndromePControl subjectsMetabolic syndromePControl subjectsMetabolic syndromeP
CCCC (ref.) 0.713 0.700  0.716 0.682  0.707 0.723  
GCCC 0.118 0.121  0.097 0.117  0.140 0.125  
   0.045*   0.19*   0.18* 
GTGT 0.084 0.072  0.092 0.084  0.076 0.058  
   0.002†   0.05‡   0.045§ 
CCCT 0.034 0.028  0.028 0.029  0.039 0.025  
GTGC 0.022 0.050  0.027 0.053  0.018 0.047  
GCCT 0.017 0.017  0.019 0.027  0.016 0.006  
HaplotypesCombined
Men
Women
Control subjectsMetabolic syndromePControl subjectsMetabolic syndromePControl subjectsMetabolic syndromeP
CCCC (ref.) 0.713 0.700  0.716 0.682  0.707 0.723  
GCCC 0.118 0.121  0.097 0.117  0.140 0.125  
   0.045*   0.19*   0.18* 
GTGT 0.084 0.072  0.092 0.084  0.076 0.058  
   0.002†   0.05‡   0.045§ 
CCCT 0.034 0.028  0.028 0.029  0.039 0.025  
GTGC 0.022 0.050  0.027 0.053  0.018 0.047  
GCCT 0.017 0.017  0.019 0.027  0.016 0.006  
*

P value for haplotype global effect.

†

OR 2.37 (95% CI 1.42–3.95) for GTGC vs. CCCC haplotype.

‡

OR 1.92 (95% CI 1.00–3.72) for GTGC vs. CCCC haplotype.

§

OR 2.47 (1.09–5.62) for GTGC vs. CCCC haplotype. P values were adjusted on age, sex, physical activity, smoking, and alcohol consumption in the combined sample or on age, physical activity, smoking, and alcohol consumption in men and women separately. Order of the SNPs in the haplotype analysis: P3 −618C>G, P2 − 689C>T, Pro12Ala, and 1431C>T. Boldface text indicates GTGC haplotype frequency.

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TABLE 5

ORs of the metabolic syndrome according to the −681C>G, −689C>T, and Pro12Ala polymorphisms stratified on the 1431C>T polymorphism

C1431TP3 −681C>G Case/control subjectsPP2 −689C>T Case/control subjectsPPro12Ala Case/control subjectsP
CC       
 205/613; 1.25 (0.89–1.76) for −681G bearers 0.20 205/613; 1.95 (1.12–3.37) for −689T bearers 0.018 205/613; 2.48 (1.38–4.44) for Ala12 bearers 0.002 
CT       
 59/201; 1.03 (0.48–2.18) for −681G bearers 0.95 59/201; 0.81 (0.43–1.51) for −689T bearers 0.50 59/201; 0.86 (0.46–1.61) for Ala12 bearers 0.63 
TT       
 4/13 not calculable; complete separation of data points detected — 4/13 not calculable; complete separation of data points detected — 4/13 not calculable; complete separation of data points detected — 
C1431TP3 −681C>G Case/control subjectsPP2 −689C>T Case/control subjectsPPro12Ala Case/control subjectsP
CC       
 205/613; 1.25 (0.89–1.76) for −681G bearers 0.20 205/613; 1.95 (1.12–3.37) for −689T bearers 0.018 205/613; 2.48 (1.38–4.44) for Ala12 bearers 0.002 
CT       
 59/201; 1.03 (0.48–2.18) for −681G bearers 0.95 59/201; 0.81 (0.43–1.51) for −689T bearers 0.50 59/201; 0.86 (0.46–1.61) for Ala12 bearers 0.63 
TT       
 4/13 not calculable; complete separation of data points detected — 4/13 not calculable; complete separation of data points detected — 4/13 not calculable; complete separation of data points detected — 

Data are OR (95% CI) and n. OR and P values were adjusted on age, sex, physical activity, smoking, and alcohol consumptions.

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The WHO-MONICA population study developed in the North of France was supported by grants from the Conseil Régional du Nord-Pas de Calais, the Fondation pour la Recherche Médicale, ONIVINS, the Parke-Davis Laboratory, the Mutuelle Générale de l’Education Nationale, the Réseau National de Santé Publique, the Direction Générale de La Santé, the Institut National de la Santé Et de la Recherche Médicale (INSERM), the Institut Pasteur de Lille, and the Unité d’Evaluation du Centre Hospitalier et Universitaire de Lille.

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