A Gly482Ser Missense Mutation in the Peroxisome Proliferator-Activated Receptor γ Coactivator-1 Is Associated With Altered Lipid Oxidation and Early Insulin Secretion in Pima Indians

  1. Yunhua Li Muller1,
  2. Clifton Bogardus1,
  3. Oluf Pedersen2 and
  4. Leslie Baier1
  1. 1Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Phoenix, Arizona
  2. 2Steno Diabetes Center, Gentofte, Copenhagen, Denmark

    Abstract

    Peroxisome proliferator-activated receptor γ coactivator-1 (PGC-1) is a transcriptional coactivator of peroxisome proliferator-activated receptor γ and α, which play important roles in adipogenesis and lipid metabolism. A single nucleotide polymorphism within the coding region of the PGC-1 gene predicts a glycine to serine substitution at amino acid 482 and has been associated with type 2 diabetes in a Danish population. In this study, we examined whether this Gly482Ser polymorphism is associated with type 2 diabetes or obesity, or metabolic predictors of these diseases, in Pima Indians. There was no association of the Gly482Ser polymorphism with either type 2 diabetes or BMI (n = 984). However, among nondiabetic Pima Indians (n = 183–201), those with the Gly/Gly genotype had a lower mean insulin secretory response to intravenous and oral glucose and a lower mean rate of lipid oxidation (over 24 h in a respiratory chamber) despite a larger mean subcutaneous abdominal adipocyte size and a higher mean plasma free fatty acid concentration. These data indicate that the Gly482Ser missense polymorphism in PGC-1 has metabolic consequences on lipid metabolism that could influence insulin secretion.

    Peroxisome proliferator-activated receptor(PPAR)-α, -γ, and -δ are members of a nuclear receptor superfamily. PPAR-α is a fatty acid-activated receptor that plays a major role in lipid oxidation (1). PPAR-γ has been shown to be a functional receptor for thiazolidinediones and to be involved in both lipid metabolism and adipocyte differentiation (2). Ligand-dependent activation of PPAR-α and -γ requires the recruitment of a transcriptional coactivator, PPAR-γ coactivator-1 (PGC-1) (35).

    PGC-1 coactivates PPAR-γ and controls gene transcription involved in thermogenesis in skeletal muscle and brown adipose tissue (6). In brown adipose tissue, heart, and liver, PGC-1 also interacts with PPAR-α to regulate mitochondrial fatty acid oxidation enzyme gene expression (2). The role of PGC-1 in oxidative metabolism is further evidenced by its ability to drive the formation of the oxidative muscle fiber type (slow twitch) in transgenic mice (7). PGC-1 has also been reported to upregulate glucose transporter 4 and thereby increase glucose uptake in muscle (8). In addition, PGC-1 is involved in hepatic gluconeogenesis by increasing gene transcription of phosphoenolpyruvate carboxykinase and glucose-6-phosphatase (9).

    We have previously reported linkage between the PGC-1 genomic region on chromosome 4p15.1 and fasting serum insulin concentrations in Pima Indians (10), and others have identified linkage of this region to BMI in Mexican Americans (11). Recently, a Gly482Ser substitution in PGC-1 has been reported to be associated with an increased relative risk (1.34) of type 2 diabetes in the Danish (12) and U.K. populations (13). Variation in PGC-1 has further been reported to be associated with obesity in two independent studies of Caucasians in which the subjects were predominately women (14,15). In contrast to these reports, the Gly482Ser substitution had no major effect on the risk of type 2 diabetes in French Caucasians (16). In the current study, we investigated whether the Gly482Ser polymorphism increased susceptibility to type 2 diabetes or obesity in Pima Indians and whether it was associated with metabolic predictors of these disorders.

    RESEARCH DESIGN AND METHODS

    Subjects.

    The 984 subjects (642 diabetic and 342 nondiabetic), from 264 nuclear families, are participants of our ongoing longitudinal study of the etiology of type 2 diabetes among the Gila River Indian Community in Arizona (17). Diabetes status was determined according to the criteria of the World Health Organization (18).

    Clinical tests for nondiabetic subjects.

    Body composition of 201 nondiabetic healthy subjects was estimated by underwater weighing until January 1996 and thereafter by dual-energy X-ray absorptiometry (DPX-1; Lunar Radiation) (19). Glucose tolerance was determined by a 75-g oral glucose tolerance test with measurements of fasting, 30-, 60-, 120-, and 180-min plasma glucose and insulin concentrations (18). To measure acute insulin response, blood samples were collected before a 25-g glucose infusion and at 3, 4, 5, 6, 8, and 10 min after infusion. The acute insulin response was calculated as half the mean increment in plasma insulin concentrations from 3 to 5 min (20).

    Insulin sensitivity was assessed using the hyperinsulinemic-euglycemic clamp technique (20). Briefly, insulin was infused to achieve physiologic and maximally stimulating plasma insulin concentrations (137 ± 3 and 2,394 ± 68 μU/ml, respectively) for 100 min for each step. Plasma glucose concentrations were held constant at ∼100 mg/dl by a variable 20% glucose infusion. Tritiated glucose was infused for 2 h before the insulin infusion to calculate rates of postabsorptive glucose appearance rates and to calculate glucose disappearance rates during the lower dose of insulin infusion. Ventilated-hood indirect calorimetry was used to estimate rates of glucose and lipid oxidation before and during the insulin infusions (21).

    The assessment of adipocyte size has been described elsewhere (22). In brief, an adipocyte suspension was prepared immediately following a percutaneous needle biopsy from the periumbilical region of 112 subjects. The adipocyte size was measured using a Coulter channelizer (model 2B; Coulter Electronics). The average cell volume was calculated as total volume in the channels divided by the number of cells and then converted to μg lipid/cell (0.91 μg lipid/nl cell volume) (22). In addition, plasma free fatty acid concentrations were measured using a colorimetric assay (Wako Chemicals).

    The measurement of energy expenditure and substrate oxidation in the respiratory chamber has been previously described (22). Briefly, data were analyzed from 165 nondiabetic subjects who entered the chamber following an overnight fast and remained in the chamber for 23 h. Subjects were fed calories to maintain energy balance according to previously determined equations, and the rate of energy expenditure was measured continuously, calculated for each 15-min interval, and then extrapolated to 24 h. Carbon dioxide production (VCO2) and oxygen consumption (Vo2) were calculated for every 15-min interval. The 24-h respiratory quotient was calculated as the ratio of 24-h VCO2 and 24-h Vo2. Based on 24-h respiratory quotient, energy expenditure, and urinary nitrogen excretion, the 24-h oxidation rates of fat, carbohydrate, and protein were determined.

    DNA sequencing and genotyping.

    Genomic DNA was extracted from peripheral blood lymphocytes. The coding region of the PGC-1 gene (EMBL#AF106698) and the intron-exon boundaries were PCR amplified and sequenced in DNA from 24 nondiabetic, non-first-degree-related Pima Indians. Sequencing was performed using the Big Dye Terminator chemistry on an automated DNA sequencer (Model 3700; Applied Biosystems). The Gly482Ser (GGT→AGT) polymorphism was genotyped in 984 subjects using an Allelic Discrimination assay performed with an ABI 7700 system (Applied Biosystems) using PCR primers 5′-CACTTCGGTCATCCCAGTCAA-3′ (forward) and 5′-TTATCACTTTCATCTTCGCTGTCATC-3′ (reverse) and TaqMan MGB probes: Fam-5′-AGACAAGACCGGTGAA-3′ and Vic-5′-CAGACAAGACCAGTGAA-3′ (Applied Biosystems)

    Statistical analysis.

    Associations were assessed using the statistical analysis system of the SAS institute (Cary, NC). For continuous variables, the general estimating equation procedure was used to adjust for appropriate covariates. These analyses account for the correlation among family members (i.e., siblings). Association studies for diabetes were performed by analysis of contingency tables, where the frequencies of the genotypic groups (Gly/Gly versus Gly/Ser + Ser/Ser) were compared between the diabetic and nondiabetic subjects and adjusted for appropriate covariates.

    RESULTS

    Sequencing of the coding region and intron-exon boundaries of the PGC-1 gene identified three single nucleotidepolymorphisms: Gly482Ser (GGT→AGT), Thr528Thr(ACA→ACG), and IVS4-6T→C (6 bp to the end of intron 4). The frequencies of the glycine (GGT) and serine (AGT) alleles at codon 482 were 0.82 and 0.18, respectively, and the polymorphism was in Hardy-Weinberg equilibrium. In the 24 DNA samples, the Thr528Thr was in 100% linkage disequilibrium with Gly482Ser and the IVS4-6T→C was rare (frequency of C allele = 0.09). Therefore, only the Gly482Ser substitution was further genotyped in 984 DNA samples.

    Since the frequency of the Ser allele was low (0.18), the Ser/Ser were combined with the Gly/Ser and then compared with the common Gly/Gly for statistical analyses. Among the 984 Pima subjects, the Gly482Ser polymorphism was not associated with type 2 diabetes (P = 0.85), even after adjusting for age (P = 0.33) or sex (P = 0.94), nor was the Gly482Ser associated with BMI in 761 nondiabetic subjects. Subjects with a Gly/Gly genotype (n = 500) had a mean BMI of 35.6 ± 0.3 kg/m2, whereas subjects combined for the Gly/Ser and Ser/Ser genotypes (n = 261) had a mean BMI of 36.1 ± 0.5 kg/m2 (P = 0.08, adjusted for age and sex, family membership, and birth year). The polymorphism was further analyzed for several metabolic predictors of type 2 diabetes and obesity (Tables 1 and 2). As shown in Table 1, nondiabetic subjects with Gly/Gly had a lower mean acute insulin response (P = 0.0001, adjusted for age, sex, percent body fat, insulin action during the low-dose insulin infusion, and family membership) and lower 30-min plasma insulin (oral glucose tolerance test) (P = 0.04, adjusted for age, sex, percent body fat, insulin action during the low-dose insulin infusion, 30-min plasma glucose, and family membership) when compared with those with Ser/Ser or Gly/Ser. These associations were also significant among subjects with normal glucose tolerance (P = 0.0006, n = 127 for acute insulin response; P = 0.02, n = 144 for 30-min plasma insulin). In addition, subjects with Gly/Gly had an increased average subcutaneous abdominal adipocyte size (P = 0.04, adjusted for age, sex, percent body fat, and family membership) and increased plasma free fatty acid concentration (P = 0.02, adjusted for age, sex, percent body fat, and family membership) as compared with those with either Gly/Ser or Ser/Ser. There was no difference in insulin action in vivo between the groups. Subjects with Gly/Gly had a lower mean rate of lipid oxidation during the high-dose insulin clamp, but not during the low-dose insulin clamp, when compared with those with Gly/Ser or Ser/Ser (P = 0.02, adjusted for age, sex, percent body fat, and family membership).

    In the respiratory chamber study (Table 2), nondiabetic subjects with Gly/Gly also had a decreased rate of lipid oxidation compared with subjects with either Gly/Ser or Ser/Ser (P < 0.03, adjusted for age, sex, percent body fat, energy balance, and family membership). This resulted in a more positive lipid balance and energy balance in Gly/Gly carriers than in Gly/Ser or Ser/Ser carriers (P = 0.003 and P = 0.01, respectively, adjusted for age, sex, percent body fat, and family membership).

    In the 63 nondiabetic subjects who had measurements of oral glucose tolerance and insulin action in vivo during a hyperinsulinemic-euglycemic clamp, and spent 24 h in the respiratory chamber during the same admission to the research unit, there was a weak positive correlation between 24-h lipid oxidation rate and 30-min plasma insulin concentration (r = 0.37, P = 0.04, adjusted for age, sex, percent body fat, 30-min plasma glucose concentration, insulin action during the low-dose insulin clamp, and family membership). However, this weak correlation was not observed between rate of lipid oxidation and acute insulin response.

    DISCUSSION

    PGC-1 facilitates PPAR-γ- and PPAR-α-mediated gene transcription by coactivating these nuclear receptors and is therefore involved in controlling adipogenesis and lipid metabolism. Evidence that PGC-1 may regulate gluconeogenesis and glucose uptake further links this coactivator to type 2 diabetes. Recently, Ek et al. (12) showed that the Gly482Ser polymorphism of PGC-1 was associated with an increased risk of type 2 diabetes in a Danish population. Their finding prompted us to examine the genetic impact of this mutation on susceptibility of developing obesity and type 2 diabetes in Pima Indians. We found that nondiabetic subjects with Gly/Gly alleles had a lower mean lipid oxidation rate and reduced early insulin secretion compared with subjects with Gly/Ser or Ser/Ser alleles.

    In Fig. 1, we hypothesize that a decrease in early insulin secretion, as observed in the Gly allele carriers, may be secondary to an increase in plasma free fatty acids and β-cell lipid accumulation, resulting from a decrease in lipid oxidation mediated by reduced PPAR-α transactivation (23). This hypothesis is supported by the positive correlation between lipid oxidation and early insulin secretion, although it should be noted that a positive correlation was not observed between lipid oxidation and acute insulin response. In parallel, an increase in average adipocyte size in subjects with Gly/Gly may result from a decrease in PGC-1-mediated PPAR-γ activation independent of the decreased lipid oxidation. This hypothesis is supported by evidence that activation of PPAR-γ by troglitazone decreased the average adipocyte size in both obese and lean rats, presumably through increased adipocyte differentiation (24).

    Obesity results from a chronic positive energy balance. Therefore, an increased balance due to a reduced lipid oxidation would predict a greater risk for developing obesity. Similarly, a reduction in early insulin secretion would predict a greater risk for developing type 2 diabetes. However, consistent with the report in French Caucasians (16), we failed to detect a significant direct association of the Gly482Ser substitution with either obesity or type 2 diabetes. Thus, it is likely that additional genetic and/or environmental factors are required for developing type 2 diabetes and obesity in Pima Indians.

    Whenever multiple phenotypes are analyzed, some may differ significantly by chance and therefore result in false positive findings. Due to the rare frequency of the Ser/Ser genotype in Pima Indians, we were unable to determine the mean for metabolic characteristics of this genotypic group. Therefore, further analysis of these phenotypic associations in other populations will be essential to validate or extend these findings in the Pima Indians. In different populations with other genetic backgrounds, the Gly482Ser mutation may have more impact on diabetes and obesity susceptibility.

    FIG. 1.

    Hypothetical mechanism whereby PGC-1 regulates pancreatic β-cell function and adipocyte size. The schematic presentation illustrates a potential physiologic pathway whereby decreased lipid oxidation, mediated by decreased transactivation of PPAR-α, leads to increased fatty acid concentrations, which can inhibit insulin secretion. In parallel, PGC-1 may increase adipocyte size through decreased PPAR-γ activity.

    TABLE 1

    Metabolic characteristics of nondiabetic subjects by Gly482Ser genotypes

    TABLE 2

    Metabolic respiratory chamber measurements of nondiabetic subjects by Gly482Ser genotypes

    Footnotes

    • Address correspondence and reprint requests to Leslie Baier, PhD, Clinical Diabetes and Nutrition Section, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, 4212 N. 16th St., Phoenix, AZ 85016. E-mail: lbaier{at}phx.niddk.nih.gov.

      Received for publication 5 September 2002 and accepted in revised form 9 December 2002.

      PGC-1, peroxisome proliferator-activated receptor γ coactivator-1; PPAR, peroxisome proliferator-activated receptor.

    REFERENCES

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