This study determined the effects of the peroxisome proliferator–activated receptor (PPAR)-γ2 Pro12Ala variant on body composition and metabolism and the magnitude of weight regain in 70 postmenopausal women (BMI 25–40 kg/m2) who completed 6 months of a hypocaloric diet. At baseline, BMI, percent body fat, intra-abdominal and subcutaneous abdominal fat areas, resting metabolic rate, substrate oxidation, and postprandial glucose and insulin responses were not different between genotypes (Pro/Pro = 56, Pro/Ala and Ala/Ala = 14). The intervention similarly decreased body weight by 8 ± 1% in women homozygous for the Pro allele and by 7 ± 1% in women with the Ala allele (P < 0.0001). Fat oxidation did not change in Pro/Pro women but decreased 19 ± 9% in women with the Ala allele (P < 0.05). Changes in glucose area were not different between groups; however, women with the Ala allele decreased their insulin area more than women homozygous for the Pro allele (P < 0.05). Weight regain during follow-up was greater in women with the Ala allele than women homozygous for the Pro allele (5.4 ± 0.9 vs. 2.8 ± 0.4 kg, P < 0.01). PPAR-γ2 genotype was the best predictor of weight regain (r = 0.50, P < 0.01), followed by the change in fat oxidation (partial r = 0.35, P < 0.05; cumulative r = 0.58). Thus, the Pro12Ala variant of the PPAR-γ2 gene may influence susceptibility for obesity.

Genetic variation in peroxisome proliferator–activated receptor (PPAR)-γ, a nuclear receptor that changes the transcription of many target genes to enhance adipocyte differentiation and improve insulin signaling (1), may influence susceptibility to obesity. PPAR-γ2 is a relatively common gene variant that results in substitution of alanine for proline at amino acid 12 (Pro12Ala), (2) decreases PPAR-γ activity (3,4), and is associated with a higher BMI in several obese populations (5,6,7). However, in nonobese individuals, it is either not related to adiposity (8,9,10) or is associated with a lower BMI (3).

Examination of the effects of the Pro12Ala variant on changes in adiposity in the same individual before and after weight loss would eliminate this confounding effect of initial obesity status and is more likely to identify a subtle effect of a gene by limiting the potential environmental influences on obesity that are present in a cross-sectional study. Therefore, this study determines the effects of the PPAR-γ2 Pro12Ala variant on body composition and metabolic responses to weight loss and on the magnitude of weight regain in obese women during follow-up.

The frequency of the PPAR-γ2 Pro12Ala polymorphism in this population was 11% (Pro/Pro = 56, Pro/Ala = 12, and Ala/Ala = 2), and the observed genotype frequencies were in Hardy-Weinberg equilibrium. There were no significant differences in any measured variable between women who were hetero- and homozygous for the Ala allele; therefore, they were combined and compared with women who were homozygous for the Pro allele. At baseline, women homozygous for the Pro allele were shorter; as a result, they weighed less and had less fat mass and lean mass than women with the Ala allele (P < 0.05) (Table 1). However, there were no differences in BMI, percent body fat, intra-abdominal fat area, or subcutaneous abdominal fat area between genotype groups. Body weight, fat mass, and lean mass did not differ between genotypes after adjustment for height. Maximal aerobic capacity (Vo2max) was not different when expressed relative to body weight. Similarly, average body weight decreased by 8 ± 1% in Pro/Pro women and by 7 ± 1% in women with the Ala allele during a 6-month hypocaloric diet (P < 0.0001 for both) (Table 1). Likewise, there were comparable decreases in fat mass (16 ± 2% in the Pro/Pro group and 13 ± 2% in the Pro/Ala and Ala/Ala groups, P < 0.0001 for both), whereas lean mass was unchanged in both groups. Decreases in intra-abdominal fat area and subcutaneous abdominal fat area and increases in Vo2max were also comparable between genotype groups. Because resting metabolic rate (RMR) was related to lean mass (r = 0.68, P < 0.0001) and age (r = −0.41, P < 0.01) and fat oxidation was related to lean mass (r = 0.34, P < 0.01), group differences in RMR and fat oxidation were determined after adjusting for individual differences in lean mass (RMR and fat oxidation) and age (RMR) using analyses of covariance. There were no differences in RMR or substrate oxidation (expressed on an absolute basis or relative to RMR) between genotype groups at baseline (Table 2).

Weight loss reduced RMR by 3 ± 1% in Pro/Pro women (P < 0.05) but did not significantly change RMR in women with the A allele (changes not different between groups, Table 2). Absolute fat oxidation did not change with weight loss in Pro/Pro women but decreased 19 ± 9% in women with the Ala allele (P < 0.05). The amount of resting energy derived from fat did not change with weight loss in women in the Pro/Pro genotype but decreased 10 ± 2% in women with the Ala allele (P < 0.05). Relative changes in absolute fat oxidation rate (P < 0.05) (Fig. 1) and fat oxidation relative to RMR (P < 0.01) were different between genotype groups. Carbohydrate oxidation did not change significantly in either group with weight loss, but changes in absolute carbohydrate oxidation were different between groups (Pro/Pro = 9 ± 8%, Pro/Ala and Ala/Ala = 52 ± 29%, P = 0.05) (Fig. 1).

There were no differences between genotype groups in fasting glucose or insulin, glucose or insulin areas above basal, or the calculated insulin sensitivity index at baseline (Table 3). Fasting glucose decreased with weight loss by 4 ± 1% in Pro/Pro women (P < 0.01) but did not change significantly in women hetero- or homozygous for the Ala allele (−3 ± 2%, P = NS). Weight loss decreased glucose area during an oral glucose tolerance test by 10 ± 6% in Pro/Pro women (P < 0.01), whereas the 14 ± 11% decrease in women with the Ala allele was not significant (P = 0.16). Changes in fasting glucose and glucose area were not different between genotype groups (Fig. 1).

On average, fasting insulin decreased 6 ± 3% (P < 0.05) and insulin area decreased 29 ± 8% with weight loss in Pro/Pro women (P < 0.01) (Table 3). Although fasting insulin did not change with weight loss in women with the Ala allele, their insulin area decreased 60 ± 10% (P < 0.01). Relative changes in insulin area were different between genotype groups (P < 0.05) (Fig. 1). Similarly, the calculated insulin sensitivity index increased in both genotype groups (P < 0.05), but the relative increase tended to be greater in women with the A allele (130 ± 30%) compared with Pro/Pro women (72 ± 14%) (P = 0.07). Thus, despite similar amounts of total and abdominal fat loss, women with the Ala allele in codon 12 of the PPAR-γ2 gene have a greater increase in insulin sensitivity and fasting carbohydrate oxidation and a greater decrease in fasting lipid oxidation compared with women homozygous for the Pro allele.

Weight regain during a 12-month follow-up was greater in women with the Ala allele (5.4 ± 0.8 kg, 5.2 ± 1.0%) than in women homozygous for the Pro allele of the PPAR-γ2 gene (2.8 ± 0.4 kg, 3.0 ± 0.5%) (P < 0.01) (Fig. 2). PPAR-γ2 genotype was the best predictor of weight regain (r2 = 0.50, P < 0.01), followed by the change in fat oxidation (partial r = 0.35, P < 0.05; cumulative r2 = 0.58).

We can only speculate as to the cellular mechanisms responsible for the effects of the Pro12Ala variant of the PPAR-γ2 gene on insulin sensitivity and substrate oxidation responses to the hypocaloric diet, especially since the molecular mechanisms by which PPAR-γ affects glucose homeostasis and adipogenesis are not entirely clear. It is known that PPAR-γ ligand binding in vitro causes PPAR-γ activation to stimulate transcription of several genes linked to adipocyte differentiation (1). However, whereas high-affinity ligands for PPAR-γ (thiazolidinediones) are known insulin sensitizers in vivo (1), very little is known about PPAR-γ regulation of genes involved in glucose homeostasis. Functional studies of the Pro12Ala variant show that the Ala allele, as a result of a lower binding affinity and a reduced ability to transactivate promotors, is associated with a reduced capacity to activate transcription and mediate adipogenesis (3,4). Thus, it is possible that weight loss may have resulted in less efficient stimulation of PPAR-γ target genes in women with the Ala allele of the PPAR-γ gene, causing less adipogenesis and in turn greater insulin sensitivity. Subsequently, an improvement in insulin sensitivity may have resulted in greater glucose oxidation and a reciprocal decrease in lipid oxidation because glucose and lipid oxidation are inversely related (11).

The fact that the Pro12Ala variant results in a decrease in PPAR-γ function in vitro but an increase in insulin sensitivity in vivo seems contradictory to the known antidiabetic effects of PPAR-γ agonists. However, there are several lines of other evidence to support these results. First, heterozygous knockout mice with reduced expression of PPAR-γ have a greater sensitivity to insulin but no difference in body weight compared with wild-type mice (12). Moreover, heterozygous deficiency of PPAR-γ results in protection from high-fat diet–induced insulin resistance (13). Consistent with these reports are findings in human studies, which show that the Ala allele is associated with a lower BMI, enhanced insulin sensitivity, and less incidence of type 2 diabetes in several populations (3,14,15,16).

On the other hand, Barroso et al. (17) recently reported the discovery of two loss-of-function mutations in the ligand-binding domain of the PPAR-γ gene in three individuals with severe hyperinsulinemia and early-onset diabetes. Although this apparently contradicts our findings, the prevalence of these mutations is very rare (detected in only 3 of 85 insulin-resistant subjects and not at all in 314 control subjects), thereby limiting the clinical significance of their findings. In addition, the Pro12Ala variant only affects the function of the adipocyte-specific γ2 isoform of PPAR-γ. Thus, PPAR-γ function in muscle and other tissues that predominantly express the γ1 isoform would be expected to be unaffected and may explain these divergent results. Ultimately, pharmacological and nutritional intervention studies are needed to clarify the extent to which genetic variation in the PPAR-γ2 gene affects responses to treatments for diabetes and obesity.

Subject selection.

All subjects were healthy, Caucasian, postmenopausal, overweight or obese (BMI 25–40 kg/m2) women. None of the women were on estrogen-replacement therapy or medications affecting lipid or glucose metabolism. The women were sedentary, weight stable (<2.0-kg weight change in the previous year), and had not smoked for at least 5 years. All women provided written informed consent to participate in the study according to the guidelines of the University of Maryland Institutional Review Board for Human Research.

Initial screening evaluations included a medical history, physical examination, fasting blood profile, and 12-lead resting electrocardiogram to exclude subjects with evidence of diabetes (fasting blood glucose >126 mg/dl or a 2-h postprandial glucose >200 mg/dl); hypertension (blood pressure >160/90 mmHg); cancer; liver, renal, or hematological disease; or other medical disorders. The second screening visit included a graded exercise test to exclude women with an abnormal cardiovascular response to exercise. Eligible subjects (n = 98) were enrolled in a 6-month weight loss intervention. We report findings on 70 women who completed the weight loss intervention.

Study design.

Measurements of body composition, Vo2max, RMR, fat oxidation, glucose tolerance, and insulin response to an oral glucose load were performed after at least 2 weeks of weight stability before the weight loss intervention and again after at least 2 weeks of weight maintenance after the weight loss intervention. The indirect calorimetry measurements and oral glucose tolerance test (performed in 47 women) were conducted after a 12-h overnight fast.

During the 6-month weight loss intervention, all women met weekly in a group setting with a registered dietitian for instruction in the principles of a hypocaloric diet (250–350 kcal/day deficit). Women were also encouraged to walk 1 day per week on a treadmill at our exercise facility at 50–60% of heart rate reserve and were instructed to walk 2 days per week on their own. After completion of the weight loss intervention, all women were followed for 12 months. During the first 6 months of follow-up, all women were instructed to maintain their 3 days per week walking program, and they met every other week with the dietitian for instruction in strategies useful for maintaining weight loss. The women were not seen by study personnel during the second 6 months of follow-up until they reported for measurement of body weight. We report the body weights of 53 women who completed the entire 12-month follow-up. There were no differences in any of the measured variables (including genotype) between these women and the 27 women who did not come back for a follow-up measurement of body weight (data not shown).

Testing procedures.

Percent body fat, lean mass, and fat mass were measured using dual-energy X-ray absorptiometry (DXA, Model DPX-L; Lunar Radiation, Madison, WI). A single-slice computed tomography scan was taken midway between the fourth and fifth lumbar to measure intra-abdominal and subcutaneous fat area as previously described (18). Vo2max was measured on a motor-driven treadmill (Quinton) during a progressive exercise test to voluntary exhaustion as previously described (18).

In the early morning after a 12-h fast, RMR and rates of substrate oxidation were measured by indirect calorimetry using the ventilated hood technique (Deltatrac Metabolic Monitor; SensorMedics, Yorba Linda, CA) as previously described (18).

After an overnight fast, a 20-gauge polyethylene catheter was placed in an antecubital vein to facilitate blood sampling. Samples were drawn at 10 and 5 min before oral ingestion of 75 g glucose. Subsequent samples were drawn at 30, 60, 90, 120, 150, and 180 min after the ingestion of the glucose. The plasma was separated by centrifugation, and glucose and insulin concentrations were measured in duplicate using the glucose oxidase method (Beckman Glucose Analyzer; Beckman, Fullerton, CA) and radioimmunoassay with an insulin-specific antibody (cross-reactivity with proinsulin <0.2%) (Linco, St. Louis, MO). Glucose and insulin areas above basal were calculated by the trapezoidal method. An index of insulin sensitivity was calculated from the fasting and 2-h glucose and insulin values as described by Avignon et al. (19). This index of insulin sensitivity correlates highly with insulin sensitivity, measured using the insulin-modified, frequently sampled intravenous glucose tolerance test in normal glucose-tolerant and impaired glucose-tolerant subjects (19).

Genomic DNA was extracted from whole blood using Qiagen miniprep columns (Qiagen, Valencia, CA) according to the manufacturer’s recommendations and was used to genotype women for the PPAR-γ2 Pro12Ala polymorphism as previously described (2). Because DNA analysis was performed after the intervention, the subjects and research personnel were blinded to genotype.

Statistics.

Statistical analyses were performed with a Macintosh Statview program (Abacus Concepts, Berkeley, CA). Data were first tested for normal distribution using the Shapiro-Wilk test for normality, and only insulin data were not normally distributed. Log transformation normalized the distribution of the insulin data, and the logarithm of the insulin values were used for parametric statistical analyses. Differences among variables before and after weight loss were determined using a paired Student’s t test within genotype groups. Student’s t test was used to test for statistically significant differences between groups at baseline, after weight loss, and for changes with weight loss. Analysis of covariance was used to compare differences between groups for RMR after adjusting for individual differences in age and lean mass and for fat oxidation after adjustment for individual differences in lean mass. A stepwise multiple regression analysis was used to determine statistically significant predictors of weight regain. All data are presented as means ± SE, and the level of significance was set at P < 0.05 for all analyses.

FIG. 1.

Relative changes in substrate oxidation and glucose and insulin areas in women homozygous for the Pro allele (▪) and women hetero- and homozygous for the Ala allele (□) of the Pro12Ala PPAR-γ2 gene variant.

FIG. 1.

Relative changes in substrate oxidation and glucose and insulin areas in women homozygous for the Pro allele (▪) and women hetero- and homozygous for the Ala allele (□) of the Pro12Ala PPAR-γ2 gene variant.

FIG. 2.

Body weight changes before and after a 6-month weight loss intervention and after 12 months of follow-up in women homozygous for the Pro allele (▪) and women hetero- and homozygous for the Ala allele (□) of the Pro12Ala PPAR-γ2 gene variant.

FIG. 2.

Body weight changes before and after a 6-month weight loss intervention and after 12 months of follow-up in women homozygous for the Pro allele (▪) and women hetero- and homozygous for the Ala allele (□) of the Pro12Ala PPAR-γ2 gene variant.

TABLE 1

Physical characteristics before and after weight loss by PPAR-γ2 genotype

Pro/Pro (n = 56)
Pro/Ala and Ala/Ala (n = 14)
BeforeAfterBeforeAfter
Age (years) 61 ± 1 — 57 ± 1* — 
Height (cm) 161 ± 1 — 165 ± 1* — 
Weight (kg) 82.7 ± 1.5 74.3 ± 1.5 90.9 ± 3.9* 83.3 ± 3.7 
BMI (kg/m231.8 ± 0.6 28.6 ± 0.6 33.3 ± 1.3 30.6 ± 1.3 
Body fat (%) 46.7 ± 0.7 42.2 ± 0.8 47.7 ± 1.9 44.9 ± 1.9 
Fat mass (kg) 37.0 ± 1.1 31.0 ± 1.1 42.2 ± 3.0* 37.6 ± 2.9 
Lean mass (kg) 39.3 ± 0.5 39.2 ± 0.5 42.6 ± 1.4* 42.3 ± 1.4 
IAF area (cm2155 ± 7 127 ± 6 161 ± 13 136 ± 11 
SAF area (cm2436 ± 17 362 ± 15 469 ± 30 390 ± 30 
Vo2max (l/min) 1.61 ± 0.03 1.69 ± 0.04 1.81 ± 0.08* 1.87 ± 0.09 
Vo2max (ml · kg−1 · min−120.1 ± 0.4 23.1 ± 0.4 20.1 ± 1.1 22.1 ± 1.3 
Pro/Pro (n = 56)
Pro/Ala and Ala/Ala (n = 14)
BeforeAfterBeforeAfter
Age (years) 61 ± 1 — 57 ± 1* — 
Height (cm) 161 ± 1 — 165 ± 1* — 
Weight (kg) 82.7 ± 1.5 74.3 ± 1.5 90.9 ± 3.9* 83.3 ± 3.7 
BMI (kg/m231.8 ± 0.6 28.6 ± 0.6 33.3 ± 1.3 30.6 ± 1.3 
Body fat (%) 46.7 ± 0.7 42.2 ± 0.8 47.7 ± 1.9 44.9 ± 1.9 
Fat mass (kg) 37.0 ± 1.1 31.0 ± 1.1 42.2 ± 3.0* 37.6 ± 2.9 
Lean mass (kg) 39.3 ± 0.5 39.2 ± 0.5 42.6 ± 1.4* 42.3 ± 1.4 
IAF area (cm2155 ± 7 127 ± 6 161 ± 13 136 ± 11 
SAF area (cm2436 ± 17 362 ± 15 469 ± 30 390 ± 30 
Vo2max (l/min) 1.61 ± 0.03 1.69 ± 0.04 1.81 ± 0.08* 1.87 ± 0.09 
Vo2max (ml · kg−1 · min−120.1 ± 0.4 23.1 ± 0.4 20.1 ± 1.1 22.1 ± 1.3 

Data are means ± SE.

*

P < 0.05 baseline differences between groups;

P < 0.001;

P < 0.01 compared with baseline. IAF, intra-abdominal fat; SAF, subcutaneous abdominal fat.

TABLE 2

RMR and substrate oxidation before and after weight loss by PPARγ2 genotype

Pro/Pro (n = 56)
Pro/Ala and Ala/Ala (n = 14)
BeforeAfterBeforeAfter
RMR (kcal/day) 1,433 ± 14 1,397 ± 17* 1,445 ± 234 1,425 ± 45 
RQ 0.82 ± 0.01 0.83 ± 0.01 0.81 ± 0.01 0.83 ± 0.01 
Fat oxidation (g/day) 70 ± 3 71 ± 3 77 ± 5 63 ± 8* 
Fat oxidation (% of RMR) 44 ± 2 45 ± 2 49 ± 3 39 ± 5* 
CHO oxidation (g/day) 125 ± 8 124 ± 7 119 ± 15 156 ± 22 
CHO oxidation (% of RMR) 35 ± 2 35 ± 2 33 ± 4 43 ± 6 
Pro/Pro (n = 56)
Pro/Ala and Ala/Ala (n = 14)
BeforeAfterBeforeAfter
RMR (kcal/day) 1,433 ± 14 1,397 ± 17* 1,445 ± 234 1,425 ± 45 
RQ 0.82 ± 0.01 0.83 ± 0.01 0.81 ± 0.01 0.83 ± 0.01 
Fat oxidation (g/day) 70 ± 3 71 ± 3 77 ± 5 63 ± 8* 
Fat oxidation (% of RMR) 44 ± 2 45 ± 2 49 ± 3 39 ± 5* 
CHO oxidation (g/day) 125 ± 8 124 ± 7 119 ± 15 156 ± 22 
CHO oxidation (% of RMR) 35 ± 2 35 ± 2 33 ± 4 43 ± 6 

Data are means ± SE.

*

P < 0.05 compared with baseline. CHO, carbohydrate RQ, respiratory quotient. RMR adjusted for individual differences in lean mass and age using analysis of covariance. Fat oxidation adjusted for individual differences in lean mass using analysis of covariance.

TABLE 3

Glucose tolerance and insulin sensitivity before and after weight loss by PPAR-γ2 genotype

Pro/Pro (n = 37)
Pro/Ala and Ala/Ala (n = 10)
BeforeAfterBeforeAfter
Fasting glucose (mmol/l) 95 ± 1 91 ± 1* 95 ± 2 92 ± 2 
3-h Glucose area (mmol · min/l) 9,210 ± 679 7,790 ± 548 8,343 ± 1603 7,011 ± 1765 
Fasting insulin (pmol/l) 70 ± 4 65 ± 4 73 ± 12 67 ± 9 
3-h Insulin area (pmol · min/l) 61,998 ± 5151 52,531 ± 5349* 68,055 ± 12,255 43,269 ± 7723* 
Insulin sensitivity index (108 · mg−1 · μU−1 · ml) 1.14 ± 0.14 1.96 ± 0.31* 0.96 ± 0.22 2.17 ± 0.63 
Pro/Pro (n = 37)
Pro/Ala and Ala/Ala (n = 10)
BeforeAfterBeforeAfter
Fasting glucose (mmol/l) 95 ± 1 91 ± 1* 95 ± 2 92 ± 2 
3-h Glucose area (mmol · min/l) 9,210 ± 679 7,790 ± 548 8,343 ± 1603 7,011 ± 1765 
Fasting insulin (pmol/l) 70 ± 4 65 ± 4 73 ± 12 67 ± 9 
3-h Insulin area (pmol · min/l) 61,998 ± 5151 52,531 ± 5349* 68,055 ± 12,255 43,269 ± 7723* 
Insulin sensitivity index (108 · mg−1 · μU−1 · ml) 1.14 ± 0.14 1.96 ± 0.31* 0.96 ± 0.22 2.17 ± 0.63 

Data are means ± SE.

*

P < 0.01, compared with baseline;

P < 0.05 compared with baseline.

This study was supported by National Institutes of Health Grants RO1 NR03514, R29 AG14066, K01 AG00685, K01 AG00747, and K24 DK02673 and by the Department of Veterans Affairs Baltimore Geriatric Research, Education and Clinical Center.

The authors are grateful to Linda Bunyard, RD, MS, and Naomi Tomoyasu, PhD, for their assistance with data collection and dietary counseling and to Adeola Dosumu and Agnes Kohler, MA, for the hormone assays. They also thank the nursing and technical staff of the Division of Gerontology and Geriatric Research, Education and Clinical Center for their assistance in conducting this project. Finally, the authors especially thank all of the women who volunteered to participate in this study.

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Address correspondence and reprint requests to Barbara J. Nicklas, PhD, Division of Gerontology, Baltimore V.A. Medical Center, 10 N. Greene St., Baltimore, MD 21201. E-mail: bnicklas@umaryland.edu.

Received for publication 31 October 2000 and accepted in revised form 15 June 2001.

PPAR, peroxisome proliferator–activated receptor; RMR, resting metabolic rate.