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. 2007 Sep 13;584(Pt 3):1011–1017. doi: 10.1113/jphysiol.2007.140673

Regulation of skeletal muscle PPARδ mRNA expression in twins

Emma Nilsson 1, Pernille Poulsen 1, Marketa Sjögren 2, Charlotte Ling 2, Martin Ridderstråle 3, Leif Groop 2, Allan Vaag 1
PMCID: PMC2276995  PMID: 17855759

Abstract

Peroxisome proliferator-activated receptors (PPARs) are nuclear receptors regulating the expression of genes involved in lipid and glucose metabolism in a complex and to some extent unknown manner. Our aim was to study the impact of different factors on PPARδ mRNA expression in human skeletal muscle on one side, and the impact of PPARδ mRNA expression on these factors, including glucose and lipid metabolism, aerobic capacity, fibre type composition and lipid profile, on the other side. PPARδ mRNA levels were quantified by real-time PCR in muscle biopsies from 176 young and elderly monozygotic and dizygotic twins. Young twins had significantly increased PPARδ mRNA levels compared with elderly twins. A 2 h hyperinsulinaemic euglycaemic clamp had no significant effect on PPARδ mRNA levels. Biometric models were calculated for basal PPARδ mRNA expression to estimate the degree of genetic versus environmental influence. In both young and elderly twins there was a substantial genetic component influencing basal PPARδ mRNA levels. In a regression model, the muscle PPARδ mRNA expression was correlated to birth weight, central adiposity and age. The level of PPARδ mRNA was also positively correlated with markers for oxidative muscle fibres. However, in this apparently healthy study population, we found no correlations between PPARδ mRNA expression and aerobic capacity, lipid profile or glucose and lipid metabolism. In conclusion, we provide evidence that mRNA expression of PPARδ in human skeletal muscle is under genetic control but also influenced by factors such as age, birth weight and central adiposity.

The first peroxisome proliferator-activated receptor (PPAR) was discovered in 1990 (Issemann & Green, 1990), giving input to the understanding of peroxisome proliferation in rodents. Since then, knowledge regarding the role of PPARs in health and disease has expanded remarkably. PPARs are nuclear receptors regulating the expression of genes involved in lipid and glucose metabolism in a subtype- and tissue-specific manner. There are three different PPAR isoforms, named -α, -δ and -γ. PPARα and -γ are predominantly expressed in liver and adipose tissue, respectively. The expression of PPARδ is ubiquitous, and it is the most abundant PPAR in muscle tissue. In mice, PPARδ seems to be implicated in the regulation of fatty acid oxidation in skeletal muscle and adipose tissue by controlling the expression of genes involved in β-oxidation and energy uncoupling (Wang et al. 2003). PPARδ is also implicated in the adaptive metabolic response of skeletal muscle to endurance exercise by controlling the number of oxidative myofibres (Wang et al. 2004).

Many areas of the function of PPARδ in humans remain unexplored. To our knowledge there has been no previous extensive study investigating PPARδ expression in humans. In this study, we have quantified PPARδ mRNA levels in muscle biopsies obtained before and after hyperinsulinaemic euglycaemic clamps from 176 young and elderly monozygotic and dizygotic twins. The classical twin approach was used to estimate the relative contributions of genetic versus environmental factors in the control of PPARδ mRNA expression in human skeletal muscle. In addition, six polymorphisms were typed and comparisons between genotypes and expression levels were performed. We also used regression analyses to test the influence of the various aetiological factors on PPARδ mRNA expression on one side, and the impact of PPARδ mRNA expression on these factors, including body composition, aerobic capacity, lipid profile as well as glucose and lipid metabolism, on the other side. Finally, we investigated if the level of PPARδ mRNA in muscle correlates to markers for fibre type composition.

Methods

Subjects

Subjects were identified through The Danish Twin Register and selected as previously described (Poulsen et al. 2002, 2005). The subjects gave written informed consent and volunteered to participate in this study. All procedures were performed according to the Declaration of Helsinki and approved by the regional ethics committees. A total of 98 young (aged 25–32 years) and elderly (aged 58–66 years) twin pairs were included in the clinical examination. We were able to obtain both blood samples and skeletal muscle biopsies from 88 of the twin pairs (31 young monozygotic, 20 young dizygotic, 18 elderly monozygotic and 19 elderly dizygotic, Table 1). Among the elderly twins 74% had normal glucose tolerance (NGT), 22% had impaired glucose tolerance (IGT) and 4% had previously unknown type 2 diabetes. Of the young twins, 98% had NGT and 2% had IGT. Zygosity was determined by polymorphic genetic markers.

Table 1.

Clinical characteristics of twins participating in the study

Young twins Elderly twins P
N (m/f, MZ/DZ) 102 (58/44, 62/40) 74 (32/42, 36/38) 0.07, 0.11
Age (years) 28 ± 2 62 ± 2 < 0.00001
BMI (kg m−2) 24.1 ± 3.2 26.5 ± 4.5 0.00001
WHR 0.84 ± 0.09 0.89 ± 0.10 0.002
Percentage body fat (%) 22.0 ± 7.1 28.5 ± 9.6 < 0.00001
fP-glucose (mmol l−1) 5.4 ± 0.3 5.9 ± 0.7 < 0.00001
fP-insulin (μU ml−1) 5.8 ± 2.6 5.7 ± 3.4 0.4
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Data are mean ±s.d. m/f; males/females, MZ; monozygotic twins, DZ; dizygotic twins, fP; fasting plasma.

Clinical examination

Subjects underwent two sessions of metabolic examinations separated by 1–2 weeks. Day one included a standard 75 g oral glucose tolerance test (OGTT) and anthropometric measures (i.e. body mass index (BMI), waist-to-hip ratio (WHR) and a dual-energy X-ray absorptiometry (DEXA) scanning to determine body composition), as previously described (Poulsen et al. 2002, 2005). On day two subjects underwent a 2 h hyperinsulinaemic euglycaemic clamp preceded by a 30 min intravenous glucose tolerance test (IVGTT) (Poulsen et al. 2002, 2005). Insulin-stimulated rate of glucose disappearance (Rd) was calculated and values were expressed per kilogram lean body mass as determined by DEXA scan. Indirect calorimetry was performed using a computerized flow-through canopy gas analyser system (Deltarac, Datex, Helsinki, Finland) and the rates of fat oxidation were expressed per kilogram lean body mass. Plasma insulin concentrations were analysed as previously described (Poulsen et al. 2002, 2005).

Muscle biopsy

Muscle biopsies were obtained from the vastus lateralis muscle under local anaesthesia using a modified Bergström's needle (including suction) before and after the hyperinsulinaemic euglycaemic clamps. Biopsies were immediately frozen in liquid nitrogen and stored at −80°C for later analysis.

Measurement of PPARδ, MHC7, MHCIIa and MHCIIx/d mRNA using real-time RT-PCR

Extraction of total RNA from the muscle biopsies was performed with the TRI reagent (Sigma-Aldrich, St Louis, MO, USA). cDNA was synthesized using Superscript II RNase H− Reverse Transcriptase (Life Technologies, MD, USA) and random hexamer primers (Life Technologies). Real-time PCR was performed using the ABI PRISM 7900 Sequence Detection System (Applied Biosystems, Foster City, CA, USA) according to the manufacturer's instructions. Primers and probe for PPARδ mRNA quantification were ordered as a ready-to-use mix of primers and a 6-carboxy-fluorescein (FAM) labelled probe (Hs00602622_m1, Applied Biosystems). The following assays from Applied Biosystems were used to quantify the expression levels of markers for fibre type composition: MHC7 (Hs00165276_m1), MHCIIa (Hs00430042_m1) and MHCIIx/d (Hs00428600_m1). Cyclophilin A was used as an endogenous control to standardize the amount of cDNA added to the reactions using a ready-to-use mix of primers and a VIC™ fluorescence probe (Applied Biosystems). All samples were run simplex in duplicate and data were calculated using the standard curve method and expressed as a ratio to the Cyclophilin A reference.

Genotyping

DNA was extracted from blood using a conventional method (Vandenplas et al. 1984). Six single nucleotide polymorphisms (SNPs) were chosen for genotyping after analysing HapMap data using the Tagger program (http://www.broad.mit.edu/mpg/tagger/). The PPARδ tag-SNPs (rs7744392, rs9470001, rs2267665, rs2076169, rs2076168 and rs1053046) were genotyped using allelic discrimination in the ABI PRISM 7900 Sequence Detection System. Primers and probes were ordered as Assay by demand (Applied Biosystems).

Statistical methods

Since monozygotic twins have identical genotypes, potential differences are theoretically due to environmental factors. Dizygotic twins on average share 50% of their genes. The extents to which monozygotic twins are more alike than dizygotic twins are therefore presumed to reflect a genetic influence on the phenotype in question. Genetic modelling to estimate the degree of genetic versus environmental influence on PPARδ mRNA expression was conducted separately in the two age groups using standard Mx scripts. Standard univariate twin modelling based on linear structural equations was used in the study (Neale & Cardon, 1992). The applied model is based upon the assumption that phenotypic variation can be decomposed into additive genetic, genetic dominance or shared environmental and unique environmental effects. Additive genetic effects result from single gene effects added over multiple loci, whereas dominant genetic factors refer to genetic interaction within the same locus. Common environment refers to environmental factors shared by twins reared in the same family, and unique environment represents the environmental experiences that are unique for the individual twin. The fit for each model was assessed by maximum-likelihood methods and resulted in a χ2 goodness of fit index and probability value, which tested the agreement between the observed and the predicted statistics. With a low χ2 and a high P value there is no significant difference between the observed and expected models and data fit the model. When selecting between non-nested models, the models with the lowest Akaikes Information Criterion (AIC) were preferred.

Intra-twin-pair correlations in all monozygotic twins were made using Spearman statistics. The intra-twin-pair correlations are correlations between within-twin-pair differences, allowing the elimination of common environmental effects (such as maternal and placental environment and common postnatal environmental effects). Importantly, the effects due to genotype can also be eliminated in monozygotic twins, a significant intra-twin-pair correlation between two phenotypes in monozygotic twin pairs is of non-genetic origin. The designation of a member in a twin pair is arbitrary, i.e. there is no consistency in which of the twins in a pair is assigned A, and which is assigned B. To avoid this, the intra-twin-pair correlations were calculated using 2n (Bring & Wernroth, 1999). However, the P value of the correlation coefficient is calculated based only on n pairs of subjects.

Stepwise regression analyses based on backward elimination were performed to test the influence of different factors on PPARδ mRNA expression and the impact of PPARδ mRNA expression on body composition, aerobic capacity, lipid levels as well as glucose and lipid metabolism. Adjustments were made for sex and age (bimodal variable) in each model. The regression model took into consideration that the observations within a twin pair cannot be assumed to be independent and that the dependency effects are different for monozygotic and dizygotic twin pairs. The regression analyses were performed with a stepwise elimination of insignificant covariables until obtaining the final reduced models, in the SAS systems for Windows (SAS Institute, Inc., Cary, NC, USA). The significance level for variable elimination was set at 0.05.

Data are presented as mean ±s.d. (for clinical variables) or mean ±s.e.m. (for PPARδ mRNA expression). The χ2 tests were used to identify significant departures from the Hardy–Weinberg equilibrium, using only one random twin from each pair. Paired comparisons of PPARδ mRNA expression (comparing basal versus post-clamp expression levels and expression in twins discordant for the different genotypes) were performed using non-parametric Wilcoxon statistics (Number Cruncher Statistical Software, NCSS, Kaysville, UT, USA). The comparison of PPARδ mRNA expression between young and elderly individuals was performed with ANOVA using proc mixed in the SAS for Windows system (SAS Institute, Inc.), adjusting for the intra-twin-pair relationship by including a random effect term for twin-pair membership and a fixed effect term for zygosity in the full model. Correlations between PPARδ mRNA expression and PGC-1α, PGC-1β, MHC7, MHCIIa and MHCIIx/d levels were calculated using Spearman correlations. All tests applied were two-tailed and P < 0.05 was considered significant.

Results

The original study population consisted of 98 twin pairs and has previously been described (Poulsen et al. 2002, 2005). We were able to obtain both blood samples and skeletal muscle biopsies from 88 of the twin pairs (Table 1).

Young twins had significantly higher PPARδ mRNA levels compared with elderly twins both in the basal state (2.5 ± 0.18 (n = 101) versus 1.3 ± 0.08 (n = 73), P < 0.0001) and after the 2 h hyperinsulinaemic euglycaemic clamp (2.6 ± 0.30 (n = 99) versus 1.3 ± 0.08 (n = 72), P = 0.0004) (Fig. 1). The 2 h hyperinsulinaemic euglycaemic clamp had no significant effect on PPARδ mRNA levels in all individuals (2.0 ± 0.12 versus 2.1 ± 0.19, P = 0.4), in the young (P = 0.4) or in elderly twins (P = 0.8) when analysed separately.

Figure 1.

Figure 1

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PPARδ mRNA expression in skeletal muscle obtained before and after a 2 h hyperinsulinaemic euglycaemic clamp from young (n = 101 before and n = 99 post-clamp) and elderly individuals (n = 73 before and n = 72 post-clamp) mRNA levels were quantified with real-time PCR and normalized to the level of endogenous Cyclophilin A. Results are expressed as the mean ±s.e.m.***P < 0.001 after adjusting for intra-twin-pair relationship.

Biometric models were calculated for basal PPARδ mRNA expression to estimate the degree of genetic versus environmental influence (Table 2). In both young (a2 (additive genetic) = 0.59, e2 (unique environment) = 0.41) and elderly twins (a2= 0.63, e2= 0.37) there was a major genetic component influencing PPARδ mRNA expression.

Table 2.

Biometric models for basal PPARδ mRNA expression to estimate the degree of genetic versus environmental influence

Component of variance Goodness of fit tests
Additive genetic (a2) Unique environment (e2) χ2 P AIC
Young twins 0.59 (0.24–0.79) 0.41 (0.21–0.76) 0.00 1.00 −2.00
Elderly twins 0.63 (0.31–0.81) 0.37 (0.19–0.69) 0.00 1.00 −2.00
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Data are presented as proportion of total variance (95% confidence interval). AIC; Akaikes Information Criterion.

Six polymorphisms, suggested to explain most of the variation in the gene, were genotyped. All of the six polymorphisms were found to be in Hardy–Weinberg equilibrium (data not shown). The rare allele frequencies for the PPARδ polymorphisms rs7744392, rs9470001, rs2267665, rs2076169, rs2076168 and rs1053046 were in this population 2%, 2%, 18%, 9%, 17% and 4%, respectively. We analysed differences in basal PPARδ mRNA expression between dizygotic twins discordant for the different genotypes (common versus rare genotype). There were no significant differences in PPARδ mRNA levels between twins discordant for rs7744392 (3.1 ± 0.9 versus 2.3 ± 0.7, n = 2, P = 0.2), rs9470001 (3.0 ± 0.9 versus 2.1 ± 0.6, n = 4, P = 0.08), rs2267665 (2.0 ± 0.4 versus 2.5 ± 0.9, n = 11, P = 0.8), rs2076169 (1.6 ± 0.3 versus 3.2 ± 1.7, n = 6, P = 0.9) and rs1053046 (2.0 ± 0.6 versus 1.5 ± 0.4, n = 5, P = 0.1). However, the twins carrying more common alleles at position rs2076168 had significantly higher PPARδ mRNA expression levels than their co-twins carrying more rare alleles at this position (3.1 ± 0.9 versus 1.8 ± 0.2, n = 12, P = 0.04).

Regression analysis was used to test whether any of the following parameters influence the basal or post-clamp PPARδ mRNA levels in skeletal muscle: zygosity (monozygotic [1] or dizygotic [2]), birth weight (continuous [g]), age (young [1] or elderly [2]), sex (men [1] or women [2]), percentage body fat (continuous [%]), central adiposity (trunkal fat/total fat), total body aerobic capacity (Inline graphic) (continuous [ml kg−1 min−1]). The final models were reached using backward selection regression (Table 3). Basal PPARδ mRNA expression was negatively related to age (P < 0.0001) and central adiposity (P = 0.004), and positively to birth weight (P = 0.03). Post-clamp mRNA expression was negatively related to age (P < 0.002).

Table 3.

Identification of factors influencing PPARδ mRNA expression in skeletal muscle using stepwise regression based on backward elimination

Regression coefficient P
Basal PPARδ mRNA levels
Age (years) −0.91 < 0.0001
Central adiposity (trunkal fat/total fat) −0.04 0.004
Birth weight (g) 0.0005 0.03
Insulin-stimulated PPARδ mRNA levels
Age (years) −1.2 0.002
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Stepwise regression based on backward elimination was also used to test whether basal PPARδ mRNA expression along with any of the other parameters mentioned above influence insulin-stimulated glucose uptake (Rd), fat oxidation, Inline graphic, triglyceride (TG) levels, free fatty acid (FFA) levels, high-density lipoprotein (HDL) cholesterol levels, percentage body fat or central adiposity. However, no significant correlations between PPARδ mRNA expression and any of the variables were observed (data not shown).

The effect of the intrauterine environment (i.e. birth weight) was analysed using intra-twin-pair correlations in monozygotic twins. There was a significant intra-twin-pair correlation between birth weight and PPARδ mRNA expression (r = 0.23, P = 0.04) (Fig. 2).

Figure 2.

Figure 2

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Intra-twin-pair correlation between differences in birth weight and skeletal muscle PPARδ mRNA expression The effect of the intrauterine environment (i.e. birth weight) was analysed using intra-twin-pair correlations in monozygotic twins. There was a significant intra-twin-pair correlation between birth weight and PPARδ mRNA expression (r = 0.23, P = 0.04)

Previously, PGC-1α and PGC-1β mRNA levels have been quantified in this twin population (Ling et al. 2004). Basal PPARδ mRNA expression correlated positively to basal PGC-1α (r = 0.33, P < 0.0001) and PGC-1β mRNA expression (r = 0.32, P < 0.0001). Likewise, post-clamp PPARδ mRNA levels correlated positively to post-clamp PGC1α (r = 0.27, P < 0.001) and PGC1β mRNA expression (r = 0.39, P < 0.000001).

We recently showed that the expression level of PGC1β correlates with markers for oxidative fibre types in human muscle (Ling et al. 2007). Here we find that basal expression levels of PPARδ correlate with basal mRNA expression of markers for slow-twitch (MHC7, r = 0.31, P = 0.00002) and fast-twitch (MHCIIa, r = 0.44, P < 0.0000001) oxidative fibres, respectively. In contrast, there was no correlation between the level of PPARδ mRNA and a marker for fast-twitch glycolytic fibres (MHCIIx/d, r = 0.12, P = 0.12) in muscle from young and elderly twins.

Discussion

Recent work has highlighted a potential role for PPARδ in the regulation of fatty acid metabolism in adipose tissue and skeletal muscle in rodents (Wang et al. 2003, 2004), although its role in humans has been imprecisely defined. In this study, we have investigated the impact of different factors on PPARδ mRNA expression in human skeletal muscle on one side, and the impact of PPARδ mRNA expression on these factors, including glucose and lipid metabolism, aerobic capacity, fibre type composition and lipid profile, on the other side.

Evidence is growing linking muscle insulin resistance with mitochondrial dysfunction. It is also well known that there is an age-related impairment of glucose tolerance. It has been hypothesized that insulin resistance in the elderly is related to increases in intramyocellular fatty acid metabolites that may be a result of an age-associated reduction in mitochondrial function. Rates of mitochondrial oxidative and phosphorylation activity have shown to be reduced by ∼40% in elderly compared with young individuals (Petersen et al. 2003). In our study, we could show that PPARδ mRNA expression was decreased by 50% in the elderly participants compared with the young subjects. The ability of PPARδ to stimulate mitochondrial biogenesis and oxidative function, as observed in rodents, suggests that PPARδ could be important for regulation of insulin resistance during ageing. The fact that PPARδ and PGC-1α both activate thermogenesis in the same tissues by regulating common target genes suggests that PPARδ uses PGC-1α as its predominant co-activator in this pathway (Wang et al. 2003). In support of that, we found a significant positive correlation between PPARδ expression and both PGC-1α and PGC-1β mRNA levels. Also, reduced expression of skeletal muscle PGC-1α and PGC-1β mRNA in elderly compared with young subjects has been previously shown in this particular study material as well as in another population (Patti et al. 2003; Ling et al. 2004).

Interestingly, birth weight and central adiposity were the other factors, apart from age, which were significantly related to basal PPARδ mRNA levels in the multiple regression analysis. Several studies have provided evidence for an association between low birth weight, as a marker for an adverse intrauterine environment, and the development of metabolic disorders later in life (Hales et al. 1991; Barker et al. 2002). The mechanism through which intrauterine malnutrition is linked with type 2 diabetes is not clear but has been thought to include both insulin resistance (Grace et al. 1990; Phillips et al. 1994; Hofman et al. 1997), decreased pancreatic insulin secretion (Swenne et al. 1987; Cook et al. 1993) and elevated hepatic gluconeogenesis (Desai et al. 1996). This is the first study suggesting a relationship between intrauterine environment (i.e. low birth weight) and reduced PPARδ mRNA expression later in life. The significant intra-twin-pair correlation between skeletal muscle PPARδ mRNA levels and birth weight in monozygotic twins suggest that this association is of non-genetic origin. In contrast to the novel association to birth weight, several studies have independently reported that activation of PPARδ (pharmacological activation or transgenic overexpression) functions to protect against obesity in rodents (Barker et al. 2002; Wang et al. 2003, 2004). It has been suggested that PPARδ serves as a regulator of fat oxidation in adipocytes and skeletal muscle. In support of that, we found that PPARδ mRNA expression in human skeletal muscle was negatively correlated to central adiposity, even though we were not able to show a significant association to fat oxidation.

The biological effects induced by PPARδ have been suggested to include improved glucose tolerance and insulin sensitivity, although the exact mechanisms are not fully clear at present. Genetic studies have shown correlations between SNPs in PPARδ and measures of insulin sensitivity (Vänttinen et al. 2005; Hu et al. 2006). Oral administration of a PPARδ agonist to mice for 7 days induced a significant increase in GLUT4 mRNA in skeletal muscle (Tanaka et al. 2003). However, whether PPARδ activation stimulates glucose uptake in skeletal muscle is not yet known. One study reported that treatment of cultured human skeletal muscle myotubes with PPARδ agonists increase glucose uptake, although neither mRNA nor protein expression of GLUT4 were affected (Krämer et al. 2005). In contrast, another study performed using rat skeletal muscle could not show an acute effect of PPARδ activation on glucose transport (Terada et al. 2005). We were not able to show a correlation between PPARδ expression and insulin-stimulated glucose uptake in this apparently healthy population.

Twin studies have been used extensively in medical research to determine the potential role of genes versus environment in the aetiology of human disease. Our unique study population, consisting of monozygotic and dizygotic twins, allowed us to estimate the relative contributions of genetic versus environmental factors in the control of PPARδ mRNA expression in skeletal muscle. The heritability data from this investigation propose that the majority of the variability in PPARδ mRNA expression is due to genetic factors, even if environmental factors also play a role. We genotyped six tag-SNPs and analysed for differences in PPARδ mRNA expression levels between dizygotic twins discordant for the different genotypes. Twins discordant for one of the polymorphisms, the intronic rs2076168, differed significantly in their PPARδ mRNA levels. However, caution is warranted due to the low number of discordant twins.

Skeletal muscle is one of the most important sites of fatty acid catabolism, and fatty acid oxidation is enhanced in this tissue by fasting and exercise. Fasting (Holst et al. 2003) as well as prolonged exercise (Luquet et al. 2003) promote an up-regulation of PPARδ in mouse muscle. In rodents, PPARδ is implicated in the adaptive metabolic response of skeletal muscle to endurance exercise by controlling the number of oxidative myofibres (Wang et al. 2004). Although we were not able to find a significant relationship between Inline graphicand PPARδ mRNA expression, the present study suggests that PPARδ also influences the formation of oxidative fibres in human muscle, since the expression of PPARδ correlated positively with markers for both slow- and fast-twitch oxidative fibres. This is in line with another human study, where mRNA levels of PPARδ correlated with oxidative fibre content (Krämer et al. 2006).

In conclusion, this study provides evidence for a major genetic component in the control of skeletal muscle PPARδ mRNA expression in young and elderly twins. The level of PPARδ mRNA was positively correlated with markers for oxidative muscle fibres. In addition, muscle PPARδ mRNA expression was influenced by factors such as birth weight, central adiposity and age.

Acknowledgments

This investigation was funded by EXGENESIS grant (005272) from the European Union, and the Danish Diabetes Association. We are greatly indebted to the study subjects for their participation. We thank Margareta Svensson and Marianne Modest for excellent technical assistance.

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