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BRIEF REPORT |
Department of Endocrinology, Metabolism, Clinical Chemistry, Nephrology, and Angiology (C.T., N.S., S.A.S., F.M., H.S., A.F., H.-U.H.), Medical Clinic, Eberhard-Karls-University, 72076 Tuebingen, Germany; Department of Diagnostic Radiology (J.M., M.B., C.C., F.S.), Section on Experimental Radiology, Eberhard-Karls-University, 72076 Tübingen, Germany; and Department of Medicine, University of Kuopio (M.L.), KI-70210 Kuopio, Finland
Address all correspondence and requests for reprints to: Hans-Ulrich Haring, M.D., Medical Clinic, Department of Internal Medicine IV, Otfried-Müller-Str. 10, 72076 Tübingen, Germany. E-mail: hans-ulrich.haering{at}med.uni-tuebingen.de.
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Abstract |
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gene (PPARD), i.e. rs1053049, rs6902123, and rs2267668, affect the improvement of mitochondrial function, aerobic physical fitness, and insulin sensitivity by lifestyle intervention (LI). Objective: The objective of the study was to determine whether the aforementioned PPARD SNPs influence the change in body composition and ectopic fat storage during LI.
Design: A total of 156 subjects at an increased risk for type 2 diabetes were genotyped for rs1053049, rs6902123, and rs2267668 and participated in a LI program. Body fat depots, ectopic liver fat, and muscle volume of the leg were quantified using magnetic resonance spectroscopy and imaging.
Results: With regard to body composition, carriers of the minor SNP alleles displayed reduced responses to LI, i.e. LI-induced reduction in adipose tissue mass (nonvisceral adipose tissue: rs1053049, P = 0.02; rs2267668, P = 0.04; visceral adipose tissue: rs1053049, P = 0.01) and hepatic lipids (rs1053049, P = 0.04; rs6902123, P = 0.001; independent of changes in adiposity) as well as LI-induced increase in relative muscle volume of the leg (rs1053049, P = 0.003; rs2267668, P = 0.009) were less pronounced in homo- and heterozygous carriers of the minor alleles as compared with homozygous carriers of the major alleles.
Conclusion: SNPs rs1053049, rs6902123, and rs2267668 in PPARD affect LI-induced changes in overall adiposity, hepatic fat storage, and relative muscle mass. Our findings provide a mechanistic explanation for the involvement of these genetic variations in the development of insulin resistance and type 2 diabetes.
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Introduction |
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is an important regulator of lipid and energy metabolism in adipose tissue and skeletal muscle (1, 2). Therefore, PPAR- represents an interesting candidate mediator of metabolic disease and a promising target for its prevention and/or therapy (1).
Genetic variation in the PPAR- gene (PPARD) is reported to affect insulin sensitivity by modifying skeletal muscle glucose uptake (3) and to predict the conversion from impaired glucose tolerance to type 2 diabetes, as demonstrated in the STOP-NIDDM trial (4). Based on PPAR-’s well-documented functions in mitochondrial oxidative pathways (i.e. fatty acid oxidation and oxidative phosphorylation) (5) and muscle fiber composition (6), we hypothesized that genetic variation in PPARD might confer altered susceptibility toward the beneficial effects of aerobic exercise. In accordance with this concept, we could recently demonstrate that single-nucleotide polymorphisms (SNPs) in PPARD predict the response of skeletal muscle aerobic capacity and insulin sensitivity to a physical and dietary lifestyle intervention (LI) program (7), and altered mitochondrial function represents a plausible explanation for this finding.
In this study, we asked whether the PPARD SNPs reported to determine alterations in skeletal muscle’s oxidative capacity and trainability (7) also influence the LI-induced changes on body composition, i.e. changes in body fat, muscle mass, and ectopic fat deposition. To this end, a noninvasive whole-body magnetic resonance (MR) approach including MR imaging and MR spectroscopy was used. This method allows precise quantification of body fat stores, muscle volume, and hepatic lipids and was applied before and after 9 months of LI.
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Subjects and Methods |
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A total of 156 nondiabetic subjects were included in the study. The subjects were at increased risk for type 2 diabetes because they had to have at least one of the following risk factors: overweight [body mass index (BMI) > 27 kg/m2], a first-degree relation to a patient with type 2 diabetes, impaired glucose tolerance, or a history of gestational diabetes. Baseline examinations included an oral glucose tolerance test (OGTT), MR imaging, and MR spectroscopy. Thereafter all subjects started a 9-month exercise and dietary LI program (Tuebingen Lifestyle Intervention Program). Details of this program have been previously described (7, 8). It includes achievement of the goals of the Diabetes Prevention Study (9). During the first 6 months, the participants had eight sessions with their lifestyle educators during which they received individual advice. The local ethics committee had approved all protocols, and all subjects gave informed written consent.
Habitual physical activity
At baseline and at follow-up, all subjects completed a standardized self-administered and validated questionnaire to measure physical activity, as formerly described (10).
OGTT
After a 10-h overnight fast, the subjects ingested a solution containing 75 g dextrose, and venous blood samples were obtained at 0, 30, 60, 90, and 120 min for the determination of plasma glucose and insulin. Insulin sensitivity was estimated from the OGTT, as described earlier (11).
Analytical procedures and measurements
Serum insulin was determined with a microparticle enzyme immunoassay (Abbott, Wiesbaden, Germany). Venous plasma glucose was measured using a bedside glucose analyzer (glucose oxidase method; Yellow Springs Instruments, Yellow Springs, OH).
Determination of adipose tissue depots and muscle volume
A whole-body MR imaging protocol as previously described (12) was applied. This allowed quantification of the different fat depots and their calculation in relation to overall body weight. Selecting two threshold values for the MR images allowed quantification of muscle volume (the lower one separating noise from lean tissue and the higher one separating lean tissue from adipose tissue). Muscle volume and fat volume of lower extremities was quantified from the toes up to the head of the femur.
Determination of hepatic lipids
Hepatic fat content was determined by localized STEAM 1H-MR spectroscopy (repetition time = 4 sec, echo time = 10 msec, 32 scans) in the seventh segment of the liver as previously described (13).
Genotyping
The SNPs rs1053049, rs6902123, and rs2267668 in PPARD were genotyped as previously described in detail (7). Linkage disequilibrium statistics (D', r2) are given in the supplementary table (published as supplemental data on The Endocrine Society’s Journals Online Web site at http://jcem.endojournals.org).
Statistical analyses
Quantitative trait data are presented as medians (minimum, maximum). Distribution was tested for normality using Shapiro-Wilk W test. Nonnormally distributed parameters were log transformed to achieve normal distribution before statistical analyses. Multivariate linear regression analyses were performed to adjust the effects of covariates and identify independent relationships. A paired Student’s t test was used to compare variables before and after the LI. A P < 0.05 was considered to be statistically significant. The statistical software package JMP (SAS Institute, Cary, NC) was used.
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Results |
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The effects of LI are shown in Table 1
. In particular, measures of adiposity, such as body weight, BMI, visceral adipose tissue (VAT), and nonvisceral adipose tissue (NVAT) significantly decreased (P < 0.0001, all), and hepatic lipids displayed the most dramatic decline (31%, P < 0.0001). By contrast, relative muscle volume significantly increased (P < 0.0001). The rationale to use relative muscle volume instead of absolute muscle volume is based on data in the literature describing qualitative (14) and quantitative (15) changes in muscle during diet and exercise. As anticipated, measures related to glucose metabolism, such as 2-h plasma glucose, fasting and 2-h plasma insulin as well as insulin sensitivity significantly ameliorated (P 
0.01, all). Furthermore, the change in insulin sensitivity was negatively correlated with the change in hepatic lipids (r = –0.22, P < 0.01) and positively correlated with relative muscle volume (r = 0.23, P < 0.01). In addition, the change in relative muscle volume was negatively associated with the change in hepatic lipids (r = –0.28, P = 0.0004).
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The effects of PPARD SNPs on LI-induced changes are presented in detail in Table 2. Carriers of the minor SNP alleles displayed reduced responses to LI, i.e. they lost less adipose tissue mass (NVAT: rs1053049, P = 0.02; rs2267668, P = 0.04; VAT: rs1053049, P = 0.01) and less hepatic lipids (rs1053049, P = 0.04; rs6902123, P = 0.001; independent of changes in adiposity) and gained less relative muscle volume of the leg (rs1053049, P = 0.003; rs2267668 P = 0.009), compared with homozygous carriers of the major alleles. These marked SNP effects were paralleled by minor effects on changes in insulin sensitivity (rs1053049, P = 0.05), fasting free fatty acids (FFAs) (rs1053049, P = 0.04), and 2-h FFAs (rs6902123, P = 0.001; rs2267668, P = 0.05).
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Discussion |
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In this study, we further demonstrate that genetic variation in PPARD negatively affects the LI-induced changes in relative muscle volume, adiposity, and ectopic fat storage in liver. These data suggest that individuals carrying the minor alleles of the tested PPARD SNPs benefit from exercise and weight loss to a lesser extent, thus providing a mechanistic explanation for these subjects’ reduced aerobic physical fitness and insulin sensitivity (7). Translated into a lifelong situation, it is conceivable that reduced responses toward exercise- and/or weight loss-mediated improvements of metabolic control will result in the described associations of PPARD SNPs with metabolic syndrome and type 2 diabetes (1).
Even though ubiquitously expressed, PPAR- expression reaches highest levels in skeletal muscle (1). Therefore, it is likely that SNPs in PPARD exert their effects directly in skeletal muscle and that these SNPs’ effects on fat mass and ectopic liver fat are a consequence of altered muscle metabolism, e.g. altered myocellular β-oxidation. However, we cannot exclude the possibility that these effects are due to direct metabolic changes in other organs. As to adipose tissue, data in the literature suggest that genetic variation in PPARD is associated with obesity (17). However, none of the PPARD SNPs tested in this study revealed significant impact on weight change during LI. This could point to a minor direct role of PPARD SNPs in adipose tissue metabolism, at least with regard to the end points tested herein.
A limitation of our study is that we performed a relatively large number of tests, which may increase the risk for a statistical type 1 error. However, our study was hypothesis driven and based on recent data in the literature (1, 2). Moreover, most traits tested herein were not completely independent from each other, e.g. all anthropometric parameters were strongly interrelated. Taking into account that we analyzed three SNPs for association with anthropometrics (considered as one parameter) and three blood parameters (glucose, insulin, and FFAs), we performed 12 independent statistical tests. Thus, Bonferroni’s correction for multiple comparisons results in 
= 0.0043. Even with regard to this more stringent -level, the effects of SNPs rs1053049 and rs2267668 on relative muscle volume as well as the effects of SNP rs6902123 on hepatic lipids and FFAs remained significant.
In conclusion, using a whole-body magnetic resonance approach, we demonstrate that LI increases relative muscle volume with favorable effects on insulin sensitivity and hepatic lipid content. Furthermore, genetic variation in PPARD was found associated with negative effects on LI-induced changes in body composition, i.e. changes in adiposity, relative muscle volume, and ectopic lipid storage in liver. In the long run, this may favor insulin resistance, hyperlipidemia, and type 2 diabetes.
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Footnotes |
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First Published Online February 5, 2008
Abbreviations: BMI, Body mass index; FFA, free fatty acids; LI, lifestyle intervention; MR, magnetic resonance; NVAT, nonvisceral adipose tissue; OGTT, oral glucose tolerance test; PPAR, peroxisome proliferator-activated receptor; SNP, single-nucleotide polymorphism; VAT, visceral adipose tissue.
Received May 31, 2007.
Accepted January 24, 2008.
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References |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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: a dagger in the heart of the metabolic syndrome. J Clin Invest 116:590–597[CrossRef][Medline] as a therapeutic target for metabolic diseases. Expert Opin Ther Targets 9:861–873[CrossRef][Medline] gene are associated with skeletal muscle glucose uptake. Diabetes 54:3587–3591 induces fatty acid β-oxidation in skeletal muscle and attenuates metabolic syndrome. Proc Natl Acad Sci USA 100:15924–15929. PLoS Biol 2:e294This article has been cited by other articles:
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  E. Ehrenborg and A. Krook Regulation of Skeletal Muscle Physiology and Metabolism by Peroxisome Proliferator-Activated Receptor {delta} Pharmacol. Rev., September 1, 2009; 61(3): 373 - 393. [Abstract] [Full Text] [PDF]
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 K Kantartzis, C Thamer, A Peter, J Machann, F Schick, C Schraml, A Konigsrainer, I Konigsrainer, S Krober, A Niess, et al. High cardiorespiratory fitness is an independent predictor of the reduction in liver fat during a lifestyle intervention in non-alcoholic fatty liver disease Gut, September 1, 2009; 58(9): 1281 - 1288. [Abstract] [Full Text] [PDF]
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 A. Kotronen, H. Yki-Jarvinen, A. Aminoff, R. Bergholm, K. H Pietilainen, J. Westerbacka, P. J Talmud, S. E Humphries, A. Hamsten, B. Isomaa, et al. Genetic variation in the ADIPOR2 gene is associated with liver fat content and its surrogate markers in three independent cohorts Eur. J. Endocrinol., April 1, 2009; 160(4): 593 - 602. [Abstract] [Full Text] [PDF]
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 E. J CHURCH Imaging Diabetes Radiol. Technol., March 1, 2009; 80(4): 340 - 360. [Abstract] [Full Text] [PDF]
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 N. Stefan, K. Kantartzis, and H.-U. Haring Causes and Metabolic Consequences of Fatty Liver Endocr. Rev., December 1, 2008; 29(7): 939 - 960. [Abstract] [Full Text] [PDF]
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