Study of a new PPARγ2 promoter polymorphism and haplotype analysis in a French population

Molecular Genetics and Metabolism 85 (2005) 140–148 www.elsevier.com/locate/ymgme

Study of a new PPAR
2 promoter polymorphism and haplotype analysis in a French population Aline Meirhaeghe a,¤, Michael W.T. Tanck b, Lluis Fajas c, Caroline Janot a, Nicole Helbecque a, Dominique Cottel a, Johan Auwerx d, Philippe Amouyel a,e, Jean Dallongeville a a INSERM, U508, Institut Pasteur de Lille, 1 rue du Pr. Calmette, BP 245, Lille Cedex F-59019, France Department of Clinical Epidemiology and Biostatistics, Academic Medical Center, Amsterdam 1100 DE, The Netherlands c INSERM, U540, Endocrinologie Moléculaire et Cellulaire des Cancers, Montpellier F-34090, France d Institut de Génétique et Biologie Cellulaire et Moléculaire (IGBMC), INSERM, CNRS, ULP, Illkirch F-67400, France e Centre Hospitalier et Universitaire de Lille, Lille 59045, France

b

Received 30 November 2004; received in revised form 8 February 2005; accepted 10 February 2005 Available online 8 March 2005

Abstract Peroxisome proliferator-activated receptor-
(PPAR
) plays a role in adipocyte diVerentiation and insulin sensitization. We identiWed and characterized a new C/T substitution at position ¡689 (¡689C > T) in the P2 promoter of PPAR
in a putative GATA binding site. By electrophoretic mobility shift assay, both GATA2 and GATA3 proteins could bind weakly to the wild-type P2 ¡689 GATA binding site but not to the mutated site. Neither GATA2 nor GATA3 was able to regulate signiWcantly the P2 promoter activity in a reporter-luciferase assay, whatever the allele at position ¡689 was, suggesting that the ¡689 putative GATA site was probably not a functional target for GATAs. However, the presence of the ¡689T allele rendered the P2 promoter less active at the basal state. We genotyped a population of 1155 men and women for the ¡689C > T polymorphism and looked for possible associations with anthropometric and lipid variables. The carriers of the ¡689T allele had elevated body weight and LDL-cholesterol concentrations compared with the homozygous for the common allele. Haplotype analyses including the ¡681C > G (P3 promoter), ¡689C > T (P2 promoter), and Pro12Ala (exon B) polymorphisms were performed. Carriers of the G-T-Ala haplotype (corresponding to the P3 ¡681C > G, P2 ¡689C > T and Pro12Ala polymorphisms in this order) had elevated LDL-cholesterol concentrations and body weight compared with C-C-Pro individuals. In conclusion, we identiWed a new polymorphism in the P2 promoter of PPAR
. The P3 ¡681C > G, P2 ¡689C > T, and Pro12Ala polymorphisms and related haplotypes were associated with higher body weight and plasma LDL-cholesterol concentrations.  2005 Elsevier Inc. All rights reserved. Keywords: Polymorphism; PPAR; Obesity; Atherosclerosis; LDL-cholesterol; Diabetes; Haplotype

Introduction Peroxisome proliferator-activated receptor
(PPAR
) belongs to the nuclear hormone receptor superfamily and heterodimerises with the retinoid X ¤

Corresponding author. Fax: +33 0 3 20 87 78 94. E-mail address: [email protected] Meirhaeghe).

(A.

1096-7192/$ - see front matter  2005 Elsevier Inc. All rights reserved. doi:10.1016/j.ymgme.2005.02.004

receptor (RXR) to regulate target genes involved in adipocyte diVerentiation [1–4] and insulin sensitization [5]. PPAR
also plays a role in macrophage [6] and malignant breast epithelial cell diVerentiation [7], colon cancer cell growth [8], as well as in glucose and lipid homeostasis (reviewed in [9,10]). PPAR
is activated by several fatty acid derivatives such as 15-deoxy-12,14-prostaglandin J2, 9- and 13-HODE, and linoleic acid [11–13]. Furthermore, PPAR
mediates the anti-diabetic eVects of

A. Meirhaeghe et al. / Molecular Genetics and Metabolism 85 (2005) 140–148

thiazolidinediones, the oral agents used in the treatment of type 2 diabetes [5]. The PPAR
gene produces four diVerently expressed mRNAs by alternative splicing and promoter usage [14– 17] giving rise to two diVerent proteins: PPAR
1, PPAR
3, and PPAR
4 being identical, PPAR
2 having an additional 30 amino acids at the N-terminus [3]. PPAR
1 is ubiquitously expressed, PPAR
2 is restricted to adipose tissue and PPAR
3 seems conWned to macrophages, adipose tissue, and colon. The tissue expression of PPAR
4 has not been explored yet. Few pathogenic mutations in PPAR
have been reported: (i) a very rare German Pro115Gln mutation which renders the protein constitutively active, associated with a severe obesity phenotype [18], and (ii) various heterozygous mutations in the ligand binding domain inducing a complex clinical phenotype called ‘PPAR
ligand resistance (PLR) syndrome’ with partial lipodystrophy, early-onset severe insulin resistance (IR), type 2 diabetes, dyslipidemia (high triglycerides, low HDL-cholesterol), early-onset hypertension, and hepatic steatosis in the carriers [19–22]. We and others, have also studied three common polymorphisms: (i) a ¡681C > G polymorphism in the P3 promoter associated with higher body weight, height, and plasma LDL concentrations [23], (ii) a Pro12Ala substitution in the speciWc exon B of PPAR
2 which contributes to a lower PPAR
2 activity in vitro, associated with decreased type 2 diabetes risk [24–26] and (iii) a silent 1431C > T polymorphism in exon 6 associated with elevated plasma leptin levels in obese subjects [27]. By sequencing t1 kb of the P2 proximal promoter, we detected a new C/T polymorphism at position ¡689 from the PPAR
P2 promoter transcription site [14], in a putative GATA binding site. Because GATA proteins have been shown to suppress PPAR
gene expression in adipocytes and therefore to prevent adipocyte diVerentiation, we explored the possible associations between this new polymorphism and obesity markers as well as plasma glucose, insulin, and lipid-related variables in a Northern France population-based study. Moreover, we also performed haplotype analyses with the P3 ¡681C > G, P2 ¡689C > T, Pro12Ala and 1431C > T polymorphisms to evaluate if a particular combination of alleles could better explain the impact of PPAR
genetic variability than individual polymorphisms do.

141

sample of men (n D 601) and women (n D 594) living in the Urban Community of Lille (northern France). Subjects were randomly sampled from the electoral rolls. To our knowledge, there were no related subjects in our sample. The Ethics Committee of the Centre Hospitalier et Universitaire de Lille approved this study. Each individual signed an informed consent. A detailed questionnaire was Wlled, which included an evaluation of alcohol and smoking consumption and a personal medical history. Body mass index (BMI), waist-to-hip ratio (WHR), and blood pressure were measured. Genomic DNA was available for 1155 subjects. From this sample, 232 subjects were obese (BMI > 30 kg/m2), 113 had type 2 diabetes on the basis of fasting glycaemia 77 mmol/L and/or a medical diagnosis. Sequencing of the PPAR
P2 promoter The PPAR
P2 promoter (1041 bp) was ampliWed using the oligonucleotides: 5⬘-CAC TCA TGT GAC AAG ACC TGC TCC-3⬘ (position ¡1044 from ATG in exon B, referred as LF58) and 5⬘-TTC GGT GTC TAT CCC TGG TTG-3⬘ (position ¡484 from ATG in exon B) (PCR product of 559 bp) and 5⬘-CAG TAG CAT GCT GAT ACC AAC-3⬘ (position ¡595 from ATG in exon B) with 5⬘-GCA TGG AAT ATG GGT TTG CTG TAA TTC AC-3⬘ (position ¡4 from ATG in exon B) (PCR product of 590 bp). These two amplicons were sequenced in 14 individuals of the population to identify potential polymorphisms. Genotyping The P3 ¡681C > G, 1431C > T, and the Pro12Ala polymorphism genotyping methods have been described elsewhere [23,27,30]. The P2 ¡689C > T polymorphism was genotyped using the LF58 oligonucleotide described in the above paragraph and the following reverse primer 5⬘-AAT GAT ACT GAC TGC TAT CT-3⬘ (annealing temperature for the PCR D 52 °C). Denatured PCR products (400 bp) were blotted on nylon membranes. Membranes were hybridized at 42 °C for 1 h with the speciWc oligonucleotides: 5⬘-GCA CTT ATC GTT TAA ACA-3⬘ for the C allele and 5⬘-GCA CTT ATT GTT TAA ACA-3⬘ for the T allele, washed twice in 1£ SSC 10% SDS for 5 min, then in 0.5£ SSC 10% SDS for 5 min, and Wnally in 0.5£ SSC 10% SDS at 45 °C for 3 min.

Methods

Generation of constructs

Population study

The PPAR
P2 promoter (910 bp upstream the ATG of exon B) was ampliWed from either a CC or a TT homozygous subject using the following oligonucleotides: sense 5⬘-ACT GGT ACC AAC CTA ACA GCG TAAG-3⬘ (containing a KpnI site) and antisense 5⬘-GAT CTC GAG AAC AGC ATG GAA TAT GGG TT-3⬘

Within the framework of the WHO-MONICA (Multinational MONItoring of trends and determinants of CArdiovascular diseases) project [28,29], we constituted in 1995–1997 an age- (35–64 years) and gender-stratiWed

142

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(containing a XhoI site). The PCR was performed using 4 mM MgCl2 and 35 cycles at an annealing temperature of 55 °C. The PCR product was doubly digested by KpnI and XhoI (New England Biolabs, Hertfordshire, UK) and cloned into the KpnI and XhoI restriction sites of the pGL3-enhancer luciferase expression vector (Promega, Madison, WI, USA). The insert identity was conWrmed by sequencing. Expression plasmids containing mGATA3 and hGATA2 [31] were kindly provided by Dr. B Gottgens (CIMR, Cambridge, UK). Transient transfections and luciferase assay COS7 cells (LGC promochem, Molsheim, France) were maintained in DMEM containing 10% FBS, 2 mM glutamine, and 20 IU/ml penicillin/20 g/ml streptomycin (Gibco, Invitrogen, Paisley, UK) in a humidiWed incubator with 10% CO2 at 37 °C. For luciferase promoter activity assays, cells were grown to 70% conXuence in 24-well dishes. Transfections were carried out in serum-free DMEM using the FuGENE transfection reagent (Roche, Meylan, France) according to the manufacturer’s instructions with a 1/3 ratio of DNA/FuGENE. Cells were incubated with 600 ng luciferase reporter vectors (empty pGL3-enhancer or pGL3 P2 CC or pGL3 P2 TT), 300 ng GATA expression plasmids. To normalise for transfection eYciency, 20 ng of pRL-CMV (Renilla luciferase from Promega, Madison WI, USA) was also added. Both Renilla and FireXy luciferase activities were assessed 40 h after transfection using the Dual-Luciferase reporter assay system (Promega, Madison, WI, USA) on 20 l lysate. PPAR
promoter activity of each construct was expressed as the ratio of FireXy/Renilla luciferase activities obtained with the PPAR
promoter construct divided by the same ratio obtained with empty pGL3 enhancer. All transfections were done four times and performed in triplicate. Preparation of protein extracts and electrophoretic mobility shift assays For electrophoretic mobility shift assays (EMSA), COS7 cells were plated in 6-well dishes and transfected 7 h later with 1.5 g of GATA expression plasmids using the FuGENE transfection reagent (Roche, Meylan, France) according to the manufacturer’s instructions with a 1/3 ratio of DNA/FuGENE. Nuclear extracts were prepared from cells previously transfected or not by GATA2 or GATA3 expression plasmids in 6-well plates. After 40 h, cells were washed with 1£ cold PBS (phosphate-buVered saline). They were lysed with 120 l/ plate buVer A (20 mM Hepes, pH 7.9, 100 mM KCl, 0.2 mM EDTA, 1 mM DTT, 1 mM PMSF, 1 mM MgCl2, and 20% glycerol with antiproteases). After 10 min on ice, 120 l/plate NP40 12% was added for 30 min. Cells were then scrapped, collected, and centrifuged for 5 min

at 13,000 rpm at 4 °C. Supernatants (cytoplasmic fraction) were collected and the pellets lysed with 300 l/ plate buVer B (20 mM Hepes, pH 7.8, 0.4 M NaCl, 1 mM EDTA, 1 mM EGTA, 1 mM MgCl2, and 1 mM PMSF with antiproteases). The lysate was vigorously vortexed (30 s) and stayed in cold room for 30 min. It was then centrifuged for 2 min at 13,000 rpm at 4 °C. Supernatants (nuclear fraction) were collected. The following single-stranded oligonucleotides were annealed to their respective complementary oligomer to form double-stranded oligonucleotide probes (GATA sites in upper case and polymorphism underlined). For the P2 promoter, we used 5⬘-end digoxigenin (DIG) labelled-tagcacTTATC/TGtttaaaca-3⬘. For the speciWc GATA sequence probes, we used 5⬘-end DIG labelledtacaggagAGATAAgggttgcg-3⬘ (probe 1) and 5⬘-end DIG labelled-tacaggagCGATAAgggttgcg-3⬘ (probe 2) [32]. The same unlabelled (cold) sequences were used for the competition assays. Statistical analyses Genotype associations Allele frequencies were estimated by gene-counting and departure from Hardy–Weinberg equilibrium within the study groups was tested using a 2 test. Single PPAR
polymorphism genotype eVects on body weight, BMI, WHR, and triglyceride, HDL, LDL-cholesterol, ApoA1, ApoB, glucose, and insulin levels were tested by analysis of variance with and without adjustment for covariates. Except for triglyceride, glucose and insulin levels, which were log-transformed, all other variables were normally distributed. Throughout, p < 0.05 were interpreted as signiWcant. All genotype analyses were carried out with the SAS software (version 8, SAS Institute, Cary, NC). Haplotype associations Presence of linkage disequilibrium between the loci was tested using a log-likelihood-ratio test [33] and the amount of disequilibrium was expressed in terms of normalized diVerence D⬘ D D/Dmax or D/Dmin [34]. Haplotype frequencies were estimated with an expectation-maximization algorithm as implemented in the Arlequin software package [35]. The PPAR
haplotype eVects were estimated using a method described by Tanck et al. [36]. In short, haplotype (average) eVects and haplotype frequencies were jointly estimated using an EM-algorithm in which individual haplotypes were handled as missing data.

Results Description of the new polymorphism The P2 promoter corresponding to a segment of 1041 bp located upstream the ATG of exon B was

A. Meirhaeghe et al. / Molecular Genetics and Metabolism 85 (2005) 140–148

143

Fig. 1. Genomic and promoter organization, corresponding mRNA isoforms and polymorphisms of the human PPAR
gene. Exons (A1, A2, B, and 1–6) are represented by boxes, introns by a line. Dashed exons mean untranslated exons. P means promoter. The 4 polymorphisms are indicated with an arrow.

sequenced in 14 individuals and a new common polymorphism was detected in four individuals. This polymorphism corresponded to a C/T substitution located 689 bp upstream the transcription site of the P2 promoter (¡689C > T) (Fig. 1). Using the MatInspector V2.2 software [37], we found that the ¡689C > T polymorphism was located in the core motif of a putative GATA binding site ctTATCgt (mutation underlined) at position ¡689. Functional study of the ¡689C > T polymorphism Because the ¡689C > T polymorphism was located into a putative GATA binding site, we tested whether GATA2 or GATA3 could regulate human PPAR
P2 promoter activity and if the polymorphism could alter this regulation. By electrophoretic mobility shift assay (EMSA) with crude COS7 cells protein extracts, no binding of proteins could be observed on probes previously described as speciWc GATA sites [32]. However, when these cells were previously transfected with a GATA2 expression plasmid, a speciWc shift was observed on the speciWc probes (Fig. 2). Analysis with a probe containing the wild-type P2 ¡689 putative GATA site revealed a binding of GATA2 on this site, although weaker than the binding obtained with the GATA speciWc probes (Fig. 2). This binding was competed with as little as 5£ cold speciWc GATA probes. In contrast, no protein binding could be detected when using the probe containing the mutated P2 ¡689T allele. Similar results were obtained with GATA3 (data not shown). We then cloned the PPAR
P2 promoter carrying the ¡689C or ¡689T allele into the pGL3-enhancer luciferase reporter vector and performed transient transfections in COS7 cells. Cells were cotransfected with both empty pGL3-enhancer or pGL3 P2 CC or pGL3 P2 TT

Fig. 2. EMSA using P2 ¡689 putative GATA binding site. Proteins were extracted from non-transfected (NT) or GATA2-transfected COS7 cells. Three diVerent probes were used: the probes corresponding to the P2 ¡689 putative GATA site (wt C or mut T allele) and two speciWc GATA probes (noted 1 and 2) (see Materials and methods). A competition— symbolised by the triangles—with the cold speciWc GATA probe 1 was performed for the PPAR
P2 probes (5£, 10£) and for the speciWc GATA probes (50£). The last lane indicated ‘free’ correspond to the probe alone without proteins. The shift is indicated by the arrow.

Fig. 3. PPAR
P2 promoter activity in the presence or absence of GATA2 and GATA3. COS7 cells were transfected with either empty pGL3-enhancer or pGL3 P2 CC or pGL3 P2 TT, and without GATA (white bars) or with GATA2 (grey bars) or GATA3 (black bars) expression plasmids. pRL-SV40 was also added to normalise for transfection eYciency. PPAR
promoter activity of each construct was expressed as the ratio of FireXy/Renilla luciferase activities obtained with the PPAR
promoter construct divided by the same ratio obtained with empty pGL3-enhancer. All transfections were done four times and performed in triplicate.

and GATA2 or GATA3 expression plasmids (Fig. 3). We could observe that the PPAR
construct with the mutated T allele had a 50% lower basal activity (white

144

A. Meirhaeghe et al. / Molecular Genetics and Metabolism 85 (2005) 140–148

bars) compared with the wild-type C allele construct, suggesting that the ¡689C > T polymorphism decreases basal PPAR
P2 promoter activity. Neither GATA2 nor GATA3 (grey and black bars) was able to modify P2 promoter activity, whatever the allele at position ¡689 was, suggesting that the GATA site at position ¡689 is probably not a functional target for GATAs and that the decreased activity observed with the ¡689T allele is due to other factors than GATAs. Another hypothesis is that other factors need to be present cooperatively with GATAs to promote eVective transcription (e.g., cofactors). Impact of the ¡689C > T polymorphism in the population We genotyped the individuals of our study (n D 1148) for the ¡689C > T polymorphism and the frequency of the ¡689T allele was 12% (Table 1). The observed genotype frequencies were in Hardy–Weinberg equilibrium. The relative genotype frequencies did not diVer signiWcantly between males and females (data not shown). The relative allele frequency was similar in obese subjects (BMI 7 30 kg/m2, n D 231, ¡689T allele frequency D 12%) and in type 2 diabetic patients (n D 103, ¡689T allele frequency D 14%) as in non-obese and non-diabetic subjects. We looked for potential associations between this new polymorphism and anthropo-

metric markers such as body weight, BMI, WHR as well as plasma glucose, insulin, and lipid-related variables. We found that the ¡689T allele was associated with higher body weight (+3 kg, p < 0.05) and plasma LDLcholesterol concentrations (+5%, p < 0.05) (Table 2). Genotype analyses We have previously described the impact of the P3 ¡681C > G, Pro12Ala, and 1431C > T polymorphisms in the same population (Fig. 1) [23,27,30]. Table 1 shows the number of individuals with a given genotype and the relative allele frequencies of these polymorphisms. Table 3 shows the associations between the P3 ¡681C > G, Pro12Ala and 1431C > T polymorphisms and clinical and biological variables. The Pro12Ala polymorphism had a signiWcant impact on weight, WHR, total cholesterol, ApoB, and LDL-cholesterol concentrations. After adjustment for covariates, only weight and LDL-cholesterol remained signiWcantly higher in Ala12 allele bearers. These associations closely resembled those obtained with the ¡689T allele. The P3 ¡681C > G polymorphism had a signiWcant impact on body weight, total cholesterol, ApoB, and LDL-cholesterol concentrations. After adjustment, total cholesterol, ApoB, and LDLcholesterol remained signiWcantly higher in ¡681G allele carriers. There were no signiWcant gender interactions,

Table 1 Number of individuals with a certain genotype and relative allele frequencies of the four PPAR
polymorphisms in the population P2 ¡689C > T CC 895 (78%)

CT 234 (20%)

TT 19 (2%)

¡689T allele 0.12

P3 ¡681C > G CC 638 (56%)

CG 430 (38%)

GG 71 (6%)

¡681G allele 0.25

Pro12Ala ProPro 905 (79%)

ProAla 225 (19%)

AlaAla 19 (2%)

Ala12 allele 0.11

1431C > T CC 863 (75%)

CT 274 (24%)

TT 17 (1%)

1431T allele 0.13

Table 2 Impact of the PPAR
P2 ¡689C > T polymorphism in the population Genotype:

CC

CT

TT

n:

886

228

19

Weight (kg) BMI (kg/m2) WHR TG (mmol/L) Chol. (mmol/L)b LDL-C (mmol/L)b ApoB (g/L)b HDL-C (mmol/L)b ApoA1 (g/L)b Insulin (U/mL)b Glucose (mmol/L)b

73.8 § 15.5 26.5 § 5.0 0.88 § 0.10 1.53 § 2.18 5.87 § 1.08 3.75 § 1.03 1.21 § 0.30 1.50 § 0.48 1.73 § 0.31 12.0 § 8.4 5.58 § 1.60

76.4 § 15.6 26.9 § 5.1 0.90 § 0.09 1.41 § 1.18 6.01 § 1.08 3.93 § 1.01 1.25 § 0.30 1.49 § 0.46 1.74 § 0.33 11.7 § 6.4 5.47 § 1.22

82.1 § 15.3 29.0 § 6.0 0.91 § 0.10 1.35 § 0.63 6.12 § 0.83 4.00 § 0.86 1.26 § 0.24 1.50 § 0.54 1.75 § 0.34 11.6 § 5.1 5.65 § 1.26

p trend

p trenda

CT + TT

0.003 0.063 0.006 ns 0.048 0.011 0.048 ns ns ns ns

0.007 0.036 0.24 ns 0.25 0.066 0.38 ns ns ns ns

76.8 § 5.6 27.0 § 5.1 0.90 § 0.10 1.41 § 1.15 6.02 § 1.06 3.94 § 1.00 1.25 § 0.30 1.49 § 0.47 1.74 § 0.33 11.6 § 6.3 5.48 § 1.22

pc

pa,c

0.007 ns 0.007 ns 0.052 0.01 0.046 ns ns ns ns

0.04 ns ns ns ns 0.04 0.13 ns ns ns ns

247

Data are means § SD. a Adjusted p values for alcohol consumption, age, sex, school level, income tax, treatment for hypertension, cholesterol or diabetes, and insulin levels or bfor age, sex and BMI. c p values for CT + TT versus CC.

A. Meirhaeghe et al. / Molecular Genetics and Metabolism 85 (2005) 140–148

145

Table 3 Means for diVerent variables of the homozygous wild and the mutant allele carriers at the P3¡681C > G, Pro12Ala and 1431C > T polymorphisms P3 ¡681C > G Genotype:

CC

Pro12Ala

CG + GG

n:

636

497

Weight (kg) BMI (kg/m2) WHR Chol. (mmol/L)b ApoB (mmol/L)b LDL (mmol/L)b

73.5 § 15.6 26.5 § 5.1 0.88 § 0.10 5.83 § 1.09 1.20 § 0.30 3.69 § 1.01

75.5 § 15.4 26.7 § 4.9 0.89 § 0.10 6.00 § 1.06 1.24 § 0.30 3.92 § 1.03

p

pa

0.034 ns ns 0.007 0.007 0.001

ns ns ns 0.02 0.02 0.001

ProPro

1431C > T ProAla + AlaAla

893

240

73.8 § 15.4 26.5 § 5.0 0.88 § 0.10 5.87 § 1.08 1.21 § 0.30 3.75 § 1.03

76.9 § 15.8 27.0 § 5.2 0.90 § 0.09 6.03 § 1.06 1.25 § 0.30 3.95 § 1.01

p

pa

0.006 ns 0.014 0.034 0.050 0.007

0.02 ns ns ns ns 0.03

CC

CT +TT

848

285

74.1 § 15.7 26.6 § 5.0 0.88 § 0.10 5.88 § 1.09 1.21 § 0.30 3.76 § 1.05

75.5 § 15.0 26.8 § 5.0 0.89 § 0.09 5.97 § 1.05 1.23 § 0.29 3.88 § 0.96

p

pa

ns ns ns ns ns ns

ns ns ns ns ns ns

Data are means § SD. a Adjusted p values for alcohol consumption, age, sex, school level, income tax, treatment for hypertension, cholesterol or blood pressure, and insulin levels bor for age, sex, and BMI.

suggesting that the eVects of the PPAR
polymorphisms were similar in males and females (data not shown). No signiWcant diVerences between carriers and non-carriers of the rare alleles were found for BMI, plasma HDLcholesterol, triglyceride, ApoA-I, glucose, and insulin levels for any polymorphisms. The 1431C > T polymorphism was not associated with any of the variables tested. Haplotype analyses Testing for linkage disequilibrium showed that the P3 ¡681C > G, P2 ¡689C > T, and Pro12Ala polymorphisms were tightly linked (D⬘ D 0.94–0.97, Table 4). When all four polymorphisms were included in the haplotype analyses, no eVect could be detected on weight, BMI, WHR, glucose, insulin, and lipid-related variables (data not shown). Given the fact that the 1431C > T polymorphism did not have any independent signiWcant eVect on these variables, we excluded this polymorphism for the haplotype analyses. As a consequence, the number of haplotypes decreased, resulting in increased statistical power of the analyses. These analyses were restricted to weight, BMI, WHR and total cholesterol, LDL-cholesterol, and ApoB concentrations. All eight possible haplotypes were estimated to be present in the population. Three of them (C-C-Pro, G-C-Pro, and G-TAla, corresponding to the alleles of the ¡681C > G, ¡689C > T and Pro12Ala polymorphisms in this order) accounted for 99% of all existing haplotypes; the Wve remaining had an estimated frequency between 0.1 and 0.6%. It is worth noting that the two haplotypes consisting of all common (C-C-Pro) or all rare (G-T-Ala) alleles covered more than 85% of all existing haplotypes. The

estimated haplotype frequencies were similar between obese (BMI 7 30) and non-obese (BMI < 30 kg/m2) individuals and in individuals with or without type 2 diabetes (data not shown). No associations between the haplotypes and BMI, WHR, total cholesterol or ApoB concentrations were observed. SigniWcant diVerences in haplotype eVects were found for plasma LDL-cholesterol concentrations (Fig. 4). Compared with the eVect of the most common C-C-Pro haplotype which was set to zero, a copy of either the G-C-Pro or G-T-Ala haplotype led to a signiWcant increase in LDL-cholesterol concentrations of 0.14 § 0.06 (p D 0.028) and 0.21 § 0.06 (p D 0.003) mmol/ L, respectively. Moreover, compared with the eVect of the C-C-Pro (the reference haplotype set to zero) and the G-C-Pro haplotypes (+0.3 § 0.9 kg, ns), the G-T-Ala haplotype was signiWcantly associated with an increase in body weight (+2.9 § 0.9 kg, p D 0.005) (Fig. 5). These results on LDL levels and body weight remained signiWcant after adjustment on covariates (age, sex, and BMI for LDL-cholesterol; alcohol consumption, age, sex, school level, income tax, treatment for hypertension, cholesterol or blood pressure, and insulin levels for body weight). For both LDL-levels and body weight, the average eVects of the Wve less frequent haplotypes did

Table 4 Linkage disequilibrium between the four PPAR
polymorphisms expressed as normalized diVerence D⬘

P2 ¡689C > T P3 ¡681C > G Pro12Ala

P3 ¡681C > G

Pro12Ala

1431C > T

0.97 — —

0.94 0.96 —

0.66 0.66 0.69

Fig. 4. Average eVects (§SE) of the three most frequent PPAR
polymorphism haplotypes (in order: P3 ¡681C > G,P2 ¡689C > T, Pro12Ala) on LDL-cholesterol concentrations (population mean: 3.79 mmol/L). The C-C-Pro haplotype eVect was set to zero.

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Fig. 5. Average eVects (§SE) of the three most frequent PPAR
polymorphism haplotypes (in order: P3 ¡681C > G, P2 ¡689C > T, Pro12Ala) on body weight (population mean: 74.4 § 15.5 kg). The CC-Pro haplotype eVect was set to zero.

not diVer signiWcantly from the eVects of any of the three most frequent haplotypes. It is worth noting that the eVect on plasma LDL-cholesterol concentrations was mainly due to the ¡681C > G polymorphism (see Fig. 4) whereas the eVect on body weight was due to a combined eVect of the ¡689C > T and Pro12Ala polymorphisms (see Fig. 5).

Discussion In this study, we describe and characterize a new C/T polymorphism 689 bp upstream the transcription site of PPAR
P2 promoter, which is associated with elevated body weight and plasma LDL-cholesterol concentrations in our French population sample. Haplotype analyses with the P3 ¡681C > G, P2 ¡689C > T, and Pro12Ala polymorphisms showed that the P2 ¡689C > T and Pro12Ala polymorphisms exerted a combined eVect on body weight whereas the impact on plasma LDL-cholesterol levels was mainly due to the P3 ¡681C > G polymorphism. PPAR
plays an important role in adipose tissue diVerentiation and lipid metabolism. The new polymorphism that we describe herein is located in a putative GATA consensus binding site deWned by cTTATCGt. GATA-2 and GATA-3 are transcription factors belonging to the Cys4 zinc-Wnger family speciWcally expressed in white adipocyte precursors. Down-regulation of GATAs sets the terminal diVerentiation of adipocytes [38]. Moreover, constitutive expression of the GATAs suppressed adipocyte diVerentiation and trapped the cells at the preadipocyte stage. This eVect is mediated, at least in part, through the direct suppression of PPAR
expression [38,39]. Using electrophoretic mobility assays, we showed both GATA2 and GATA3 proteins could bind to the wild-type form of the ¡689 consensus site but very weakly compared with previously described GATA speciWc binding sites. This binding was com-

pletely absent when using the probe containing the ¡689T allele. By transient transfections in COS7 cells, the presence of the mutated ¡689T allele in the PPAR
P2 promoter rendered the promoter less active (by 50%), at the basal state, than the one containing the ¡689C allele. Neither GATA2 nor GATA3 modiWed PPAR
P2 promoter activity, whatever the ¡689 allele was. The weak binding of GATAs on the wild-type ¡689 consensus site observed by EMSA was probably not suYcient to create any transcriptional activity modiWcation. Or it is likely that other transcription/cotranscription factors are needed to promote eYcient transcription. The molecular origin of the basal decreased activity observed with the mutated ¡689T allele is not understood at the moment but a lower activity of PPAR
might indeed lead to a dysregulation of adipocyte diVerentiation control and eventually to weight gain, which could partly explain the present association of PPAR
polymorphisms with elevated body weight. The P2 ¡689C > T polymorphism is the second polymorphism reported in PPAR
promoters. We have previously characterized the ¡681C > G polymorphism in the P3 promoter as well as the coding Pro12Ala polymorphism located in exon B of the PPAR
2 isoform. These three polymorphisms were associated with elevated body weight and plasma LDL-cholesterol levels in our French population [23,30]. The ¡681C > G polymorphism is located in a binding consensus site for the signal transducer and activator of transcription (STAT) proteins [40]. We have shown that STAT5B, when activated by growth hormone, binds to the ¡681 STAT site and transactivates the P3 promoter in a luciferase reporter-based assay [23]. The presence of the G nucleotide at position ¡681 in the consensus site prevents the STAT5B binding and consequently the transactivation of the promoter. The Pro12Ala polymorphism has been extensively studied. This polymorphism reduces the transcriptional activity of PPAR
in vitro [24] leading to decreased target gene expression or activity such as the lipoprotein lipase [41]. The Ala12 allele is associated with reduced risk for type 2 diabetes and higher BMI in overweight individuals ([42] for review). Therefore, three PPAR
polymorphisms appear to be associated with similar eVects on body weight and LDL-cholesterol levels. The existence of a tight linkage disequilibrium between these polymorphisms and the fact PPAR
2 and PPAR
3 isoforms are both expressed in adipose tissue, probably explain these similar associations. This led us to test whether the eVects on body weight and LDL-cholesterol concentrations were related to a speciWc haplotype. This strategy was further supported by the observation that, in multivariate analysis, the eVects of the diVerent alleles were not independent (data not shown). The results showed a signiWcant diVerence between the C-C-Pro and G-T-Ala haplotypes on body weight and plasma LDL-cholesterol concentrations. The increase in LDL-cholesterol was

A. Meirhaeghe et al. / Molecular Genetics and Metabolism 85 (2005) 140–148

mainly due to the P3 ¡681C > G polymorphism, whereas for body weight, a single mutant allele at the ¡681C > G polymorphism had no apparent eVect. Whether the observed eVects on body weight were caused by the P2 ¡689C > T, or the Pro12Ala polymorphism, a combination of both or an undetected polymorphism could not be determined based on the present results. In conclusion, we have shown strong associations between individual polymorphisms in PPAR
gene and body weight or plasma LDL-cholesterol concentrations. These associations were also observed when comparing the C-C-Pro and G-T-Ala haplotypes; the eVects on LDL-cholesterol levels appeared to be due to the ¡681C > G polymorphism, whereas for body weight the observed eVects appeared to be due to the P2 ¡689C > T or Pro12Ala polymorphism, a combination of both or an undetected polymorphism. All these results suggest that the PPAR
-mediated body weight control follows a complex system composed of multiple genetic variations in promoter and coding regions inducing multiple subtle transcriptional regulation changes, probably themselves modulated by gene–environment interactions.

Acknowledgments M.W.T.T. is supported by the Netherlands Heart Foundation (Grant No. 2000.125). Dr. Bertie Gottgens is acknowledged for the gift of the GATA expression plasmids. 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 ParkeDavis Laboratory, the Mutuelle Générale de l’Education Nationale (MGEN), 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. The Fondation de France, the CNRS and the Hopitaux Universitaires de Strasbourg are also acknowledged.

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