Chapter 2. The Peroxisome Proliferator-Activated Receptor α L162V Mutation Is Associated with Reduced Adiposity.

Yohan Bossé, Jean-Pierre Després, Claude Bouchard, Louis Pérusse, Marie-Claude Vohl.

L’objectif de cette étude était de déterminer l’importance du polymorphisme PPARα L162V sur les variations de plusieurs indices d’adiposité mesurés chez des adultes participant à l’Étude des familles de Québec. Les phénotypes d’adiposité ont été obtenus par des mesures anthropométriques standards, pesé hydrostatique et tomographie axiale. Pour tous les phénotypes d’adiposité, les sujets porteurs de l’allèle V162 avaient de plus faibles valeurs comparativement aux sujets homozygotes L162. Le rapport de cote désignant le risque d’avoir un indice de masse corporelle supérieur à 30 kg/m2 était de 1.77 (1.02 ; 3.07, IC à 95%) pour ces derniers. Sur une base individuelle ce risque peut être considéré modeste. Par contre, étant donné que 85% des sujets sont affectés par ce petit risque, l’impact populationnel est important. Ces résultats suggèrent que le polymorphisme L162V du gène PPARα est associé avec les indices d’adiposité et un risque populationnel substantiel.

The Peroxisome Proliferator-Activated Receptor α L162V Mutation Is Associated with Reduced Adiposity.

Yohan Bossé1, Jean-Pierre Després1,2,3, Claude Bouchard4, Louis Pérusse5 Marie-Claude Vohl1,3.

1- Lipid Research Center, CHUL Research Center; 2- The Quebec Heart Institute; 3- Food Sciences and Nutrition Department, Laval University; 4- Pennington Biomedical Research Center, Baton Rouge, Louisiana, USA; 5- Physical Activity Sciences Laboratory, Kinesiology Division, Department of Social and Preventive Medicine, Laval University, Quebec, Canada.

This study was supported by CIHR.

Short title: Reduced body fatness among carriers of PPARα L162V mutation.

Address all correspondence to: Marie-Claude Vohl, Ph.D., Lipid Research Center, CHUL Research Center, TR-93, 2705, Boul. Laurier, Sainte-Foy, Quebec, G1V 4G2, Canada, Tel: (418) 656-4141 ext. 8280, Fax: (418) 654-2145, e-mail: marie-claude.vohl@crchul.ulaval.ca

Abstract

PPARα is highly expressed in tissues with elevated fatty acid catabolic rates. In rodents, PPARα activation by specific ligands has been shown to prevent high fat diet-induced obesity and to reduce body weight in genetic models of obesity.

Objective : Determine the contribution of the PPARα L162V mutation to the variation of several indices of body fatness obtained from healthy adults who participated in the Quebec Family Study.

Research Methods and Procedures : The presence of the PPARα L162V mutation was determined by a PCR-RFLP based method and subjects were classified into L162 homozygote (HMZ) or V162 carriers. Adiposity phenotypes were obtained by standardized anthropometric measurements, underwater weighing technique and computed tomography (CT) and compared among the two groups after adjustment for age and gender effects.

Results : For all adiposity phenotypes, subjects carrying the V162 allele had lower values compared to L162 HMZ [BMI (kg/m2): 27.8 ± 7.6 vs 26.0 ± 5.6, p < 0.05; percent body fat: 28.5 ± 10.7 vs 25.7 ± 10.1, p < 0.05; waist circumference (cm): 89.0 ± 18.1 vs 85.7 ± 15.8 , p = 0.07; total CT abdominal fat areas (cm2): 406 ± 221 vs 359 ± 192, p = 0.15; means ± SD for L162 HMZ vs V162 carriers respectively]. Differences in cross-sectional abdominal adipose tissue areas and waist circumference were abolished after adjustment for total body fat mass. Similar trends were observed when results were analyzed by gender although associations seemed stronger in women. The odds ratio of having a BMI above 30 kg/m2 reached 1.77 (1.02 ; 3.07, 95% confidence intervals) for L162 HMZ. This risk could be considered marginal on an individual basis, but, since 85% of the subjects are affected by this small risk, the impact on the population is important.

Discussion : The PPARα V162 allele is associated with reduced adiposity and has a substantial population attributable risk.

Key words : nuclear receptor, missense mutation, fat mass, population risk

Introduction

Obesity has reached epidemic proportions that have generated a progressive economic burden on medical health care (1-3). However, obesity is a heterogeneous condition which is attenuated or exacerbated by genetic and nongenetic factors and is referred to as a complex multifactorial trait. Understanding the genetic contribution of such trait is of great interest since a large spectrum of susceptibility genes play a role in the development of obesity (4). In order to detect the modest effect of each gene, association studies performed on large population samples are required (5). These additive modest contributions can then be used to predict the risk to become obese or could also be used as molecular targets for pharmacological treatment of this condition. Recently, the peroxisome proliferator-activated receptor alpha (PPARα) gene has emerged as one of these potential genes which could be involved in the etiology of obesity.

PPARα is a nuclear hormone receptor member of the superfamily of nuclear receptors (6) activated by endogenous and xenobiotics ligands (7). This ligand-activated transcription factor is expressed in several tissues but predominantly among those with elevated rates of fatty acid catabolism (8, 9). Since the identification of PPARα a decade ago (10), several ligands for this nuclear receptor have been identified, including fatty acids, particularly polyunsaturated fatty acids, eicosanoids, and hypolipidemic drugs such as fibrates (11-13). After activation by its ligand, the activated PPARα heterodimerizes with the retinoid X receptor (RXR) and this complex then binds to peroxisome proliferator response elements (PPRE) of genes to regulate their expression. PPARα-responsive genes include those encoding crucial enzymes involved in the regulation of intra- and extracellular lipid metabolism (14, 15). Non-exhaustively, PPARα upregulates genes involved in fatty acids uptake and transport, in the β- and ω-oxidation pathways and in ketone body synthesis (16, 17). Thus, PPARα regulates the intracellular fate of fatty acids by increasing fatty acid oxidation, and prevent fat storage into adipocytes which is the long term process leading to obesity. The potential preventing effect of PPARα against obesity development is represented schematically in Figure 1.

Two lines of evidence confirm this theoretical model. Firstly, in rodents PPARα activators were shown to reduce body weight and adiposity in diet-induced obesity (18-20). These results suggest that the activation of PPARα in rodents prevents and reduces obesity. Secondly, PPARα deficient mice were founded to develop late onset obesity despite a stable caloric intake (21). These mice have been proposed as a model of monogenic obesity with a marked sexual dimorphism. In fact, females PPARα deficient mice develop a more pronounced obesity than their male counterpart. Thus, variation in the PPARα gene may play a role in the development of obesity.

Recently, a missense mutation has been identified in the DNA binding domain of the human PPARα gene (22, 23). This mutation is located in exon 5 and results in the substitution of a leucine for a valine at codon 162. In vitro transfection studies revealed that the rarer V162 allele has greater transactivation on the reporter gene construct (23, 24). It was thus of great interest to verify whether the L162V mutation would be associated with adiposity in human. Thus, the objective of the present study was to investigate the contribution of the PPARα L162V mutation on several phenotypes of body fatness obtained from healthy adults who participated in the Quebec Family Study (QFS). accordingly

Methods

Population

Subjects were participants in phases 2 and 3 of the QFS (25). Briefly, the QFS is a population-based study of French-Canadian families living in and around Quebec City area. Subjects were recruited through the media. Only adults (305 men and 393 women), 20 years and older, were considered for the present analyses. The 698 subjects included in this study are members of 253 nuclear families. The mean number of subjects by family is 3.00 ± 1.34 (range 1 to 8). Characteristics of the subjects are presented in Table 1 which indicates that the QFS cohort covered a wide range of body fatness values. The Medical Ethics Committee of Laval University approved the protocol and a written consent was obtained from all the subjects.

Body fatness measurements

Body weight, height and waist circumference were measured following standardized procedures (26). Body density was measured by the hydrostatic weighing technique (27). Pulmonary residual volume was assessed before immersion in the hydrostatic tank, using the helium dilution technique of Meneely and Kaltreider (28). Percentage of body fat, fat mass and fat free mass were derived from body density using the Siri equation (29). Finally, a cross-sectional abdominal scan was performed by computed tomography using a Siemens Somatom DRH scanner (Erlanger, Germany) to quantify the adipose tissue areas between L4 and L5 vertebra as described in details elsewhere (30).

DNA analysis

The L162V mutation, caused by a C→G transversion at nucleotide 484 in exon 5, does not alter any restriction site. A mismatch PCR method previously described was then used to genotype individuals of the QFS cohort (22). Briefly, the mismatch PCR was performed with the following primers 5'-GACTCAAGCTGGTGTATGACAAGT-3' and 5'-CGTTGTGTGACATCCCGACAGAAT-3' (note the mismatch nucleotide in the reverse primer is underlined). PCR conditions were as follows: reaction volume was 50 μl, 1.25 unit AmpliTaq Gold polymerase (Perkin-Elmer Cetus) in the buffer recommended by the manufacturer, 2.5 mM MgCl2, 0.2 mM dNTPs, primers at a final concentration of 0.5 μM and 100 ng of template genomic DNA. This products were then digested with Hinf I, electrophoresed through either 12% acrylamide or 4% agarose gel, and stained with ethidium bromide.

Statistical methods

Variables with a skewed distribution were log10-transformed. Means of these variables are given in tables and illustrations with their raw scores (scores before transformation) instead of their geometric means, but the p-values are given from the log10-transformed distributions. Differences between genotypic groups were assessed using the MIXED model procedure for association studies, which takes the nonindependence of family members into account. In this model, age as well as gender, when males and females are considered together, were used as covariates. Logistic regression analyses were used to assess the association between PPARα L162V mutation and obesity. This association was investigated by classifying subjects into two groups using a 30 kg/m2 as the cutoff point. The risk of being obese for subjects that did not carry the mutation was estimated as the relative risk to have a BMI > 30 kg/m2 compared to subjects who had the mutation. Odds were adjusted for the potential confounding effects of age, gender, smoking status and alcohol consumption. Covariates that did not significantly influence BMI were removed from the model. All statistical analyses were performed using the SAS package (SAS Institute, Cary, NC) and statistical significance was set at p < 0.05.

Results

Body fatness and body fat distribution variables according to the PPARα L162V genotypes are presented in Figure 2. In the total group, carriers of the V162 allele had lower BMI compared to L162 HMZ. As for BMI, carriers of the V162 allele tend to have lower body weight. Results from underwater weighing derived phenotypes revealed that the relative amount of adipose tissue was lower among carriers of the V162 allele. However, no difference between the genotypic groups was observed for fat free mass in the overall sample. This finding suggests that the mutation is specifically related to the adipose tissue compartment of the body.

We verified the effect of the mutation on body fat distribution. Carriers of the V162 allele tended to have lower waist circumference compared to L162 HMZ (Figure 2). However, this trend was no longer observed after adjustment for body fat mass suggesting that the mutation was more closely associated with the amount of total fat in the body rather than with its distribution (not shown). Comparison of abdominal adipose tissue distribution indices assessed by computed tomography revealed lower values of total, visceral and subcutaneous cross-sectional areas of adipose tissue for carriers of the V162 allele but the difference did not reach statistical significance (Figure 2). Finally, no difference in the visceral/total adipose tissue areas ratio was observed between carriers and non-carriers of the V162 allele (p = 0.844) which demonstrates again that the mutation is not associated with fat distribution.

Since fat mass and fat distribution differed for men and women, data were also analyzed separately by sex (Table 2). Independently of the gender, carriers of the V162 allele seem to have lower values of adiposity compared to L162 HMZ. Although the genotype difference was not significant, the trends appeared to be stronger in women. Taken all together, subjects carrying the V162 allele had lower obesity indices compared to L162 HMZ. When data were analyzed by gender, similar trends were observed but associations appeared to be stronger in women than in men.

Further analyses were also performed with the three genotype groups instead of combining V162 HMZ together with L162/V162 HTZ (L162/L162, L162/V162 and V162/V162). Percent body fat, fat mass and total and subcutaneous abdominal fat areas seemed to be lower in V162 HMZ compared to the other groups (data not shown). However results must be interpreted with caution due to the low number of subjects included in the V162 HMZ group (n = between 6 and 12). Since ethanol has been shown to inhibit PPARα activity (31), analyses were also performed after adjustment for alcohol consumption. However, such an adjustment did not influence the results (data not shown). Additional adjustment for smoking status did not modify the results as well.

The risk of having a BMI above 30 kg/m2 for L162 HMZ genotype is shown in Figure 3. The odds ratio is estimated to be approximately 1.46 (p = 0.150) without adjustment for confounding factors. After adjustment for factors that are known to affect obesity such as age, gender and alcohol consumption, the odds ratio reached 1.77 (p = 0.041). Thus, according to these data, the PPARα L162V mutation may appear as having only a modest impact on the adiposity. However, since the prevalence of the elevated risk genotype (L162 HMZ) was found to be very high (a frequency of 85% in our sample), an adjusted genotype relative risk of 1.77 could correspond to a high population attributable risk.

Discussion

Results of the present study suggest that the PPARα L162V mutation may be involved in the pathogenesis of obesity. Indeed, for all adiposity phenotypes, subjects carrying the PPARα V162 allele had lower values compared to L162 HMZ. Similar trends were observed when results were analyzed by gender although associations were stronger in women. On the other hand, the risk of becoming obese in the absence of the mutation was relatively small (OR = 1.77, p = 0.041), suggesting that the PPARα L162V mutation only had a modest impact on an individual basis. However, since the vast majority (85% of individuals in our sample) of whites subjects are exposed to this moderate risk, the effect could translate into a large population-attributable risk.

Given the central role of PPARα in the intra and extracellular lipid metabolism, the L162V mutation has been investigated in the development of several pathologies including type 2 diabetes and obesity. Three independent studies reported no significant difference in the allele frequency between diabetics and nondiabetics, suggesting that this missense mutation does not seem to play a major role in the development of type 2 diabetes (22, 32, 33). However, Evans et al. (33), reported in a group of type 2 diabetes patients (BMI = 29 ± 7) and in a second group of morbid obese subjects (BMI = 51 ± 8) having a fasting glucose ≥ 7 mmol/L, that the frequency of the V162 allele in patients with BMI below the median (28 and 49 kg/m2 in type 2 diabetes and in morbidly obese patients, respectively) was higher compared to subjects above those respective cutoffs. However, the missense mutation was not associated with BMI in subjects without type 2 diabetes. There results suggested that the BMI lowering effect of the V162 allele could be present only among patients with type 2 diabetes. Results of the present study were derived from a relatively “healthy” population. Difference between results of Evan et al. and those of the study could be explained by a greater contribution of the mutation among people in whom an elevated PPARα activation is expected, such as type 2 diabetes. In such case, a smaller study sample may be sufficient to detect an effect. On the other hand, a larger sample size might be required when dealing with subjects free of chronic metabolic diseases.

The “protective” effects of PPARα against the development of obesity have been highlighted. Fibrates are a widely used class of hypolipidemic agents which act through PPARα activation (34). In rodent models, fibrate treatment prevents weight gain and reduces adipose tissue in high fat diet-induced obesity and genetic models of obesity, respectively (18-20). Thus, PPARα activation seems to decrease body weight. In addition the lack of PPARα appears to favor the development of obesity, since PPARα-deficient mice (under the C57BL/6N background) become progressively obese on a regular chow diet (21). The latter conclusion was based on a long term experiment (8 months) demonstrating that the lack of this nuclear receptor in mice caused a progressive onset of obesity. Taken into account the key regulatory enzymes controlled by PPARα, the authors suggested that the onset of obesity in this mouse model may depend upon the impairment of pathways regulating lipid metabolism since they were not hyperphagic. These mice were also characterized by a sexual dimorphism. Indeed, females developed a more pronounced obesity than males, a finding consistent with the greater associations between the PPARα L162V mutation and the body fatness phenotypes observed in the present study. However, in a similar experimental set up (9 months on a chow diet), Akiyama et al. (35) concluded that the weight gain and the average body weight in wild-type and PPARα-null mice were not markedly different between genotypes. Nonetheless, a trend was observed for higher body weight throughout the protocol among PPARα male and female null mice bred on a C57BL/6N background. In addition, adipose tissue stores were significantly greater in PPARα-null mice than in controls. Furthermore, adding WY-14643, a potent PPARα activator, in the diet of the wild-type mice significantly reduced their body weight as well as adipose tissue stores, an effect not observed in PPARα-null mice. Greater weight gain in PPARα-null mice (C57BL/6N) following a chow diet was also reported during a shorter experimental period (four weeks) (36). Taken together these in vivo studies indicate that deactivation of PPARα increases body fatness and its activation does the opposite.

The observation that the PPARα L162V mutation may play a causal role in body fat gain is strengthened by studies on functional differences between the leucine-containing and valine-containing protein products (23, 24). In fact, co-transfection assays have demonstrated that the PPARα V162 allele has an enhanced transactivation activity on the reporter gene construct compared with the PPARα L162 allele in presence of a PPARα ligand. Thus, it is tempting to speculate that the reduced adiposity values observed in subjects carrying the PPARα V162 allele are explained by a greater activity of the valine-containing protein. Therefore, individuals with the PPARα V162 allele would have an enhanced fatty acid oxidation, limiting body fat accumulation.

Obesity is a complex multifactorial trait which involves the additive effect of several gene polymorphisms (4). Association studies are widely anticipated to contribute to the understanding of complex traits (5). However, to be credible an association study must fill several criteria (37). Ideally, such studies require large sample size that allow sufficient power to detect genetic variation having modest effects. Studies with small sample size can often fail to detect true associations. Association studies can be useful if their findings make biological sense and if the allelic variation upon which they are based result in functional biological differences, which is the case in the present study.

In conclusion, the present study reports that the PPARα L162V mutation is associated with several phenotypes of body fatness obtained from healthy adults who participated in the QFS. In addition, the greater risk of being obese associated with the absence of the PPARα V162 allele appears to have a modest impact on an individual basis, but could have a major effect from a general population point of view because of the high frequency of the L162 wild-type allele. The PPARα L162V mutation highlights the potential importance of common alleles with a rather weak effect. We speculate that this effect is mediated by a greater transactivation of the PPARα V162 allele on fatty acid metabolizing enzymes. Further studies will be necessary in order to replicate our results in populations with different genetic backgrounds.

Acknowledgements

This study was supported by the Canadian Institutes of Health and Research. The authors would like to express their gratitude to the subjects for their excellent collaboration and to the staff of the Lipid Research Center and of the Physical Activity Sciences Laboratory for their contribution to the study. Y. Bossé is the recipient of a studentship from the "Fonds pour la formation de chercheurs et l'aide à la recherche (FCAR) et le Fonds de la recherche en santé du Québec (FRSQ)". M.C. Vohl is a research scholar of the FRSQ. J.P. Després is chair professor of human nutrition, lipidology and prevention of cardiovascular disease supported by Provigo and Pfizer Canada. C. Bouchard is partially supported by the George A. Bray Chair in Nutrition.

References

1. Kuczmarski RJ, Flegal KM, Campbell SM, Johnson CL. Increasing prevalence of overweight among US adults. The National Health and Nutrition Examination Surveys, 1960 to 1991. JAMA. 1994; 272:205-11.

2. Flegal KM, Carroll MD, Kuczmarski RJ, Johnson CL. Overweight and obesity in the United States: prevalence and trends, 1960-1994. Int J Obes Relat Metab Disord. 1998; 22:39-47.

3. Thompson D, Brown JB, Nichols GA, Elmer PJ, Oster G. Body mass index and future healthcare costs: a retrospective cohort study. Obes Res. 2001; 9:210-8.

4. Perusse L, Chagnon YC, Weisnagel SJ, et al. The human obesity gene map: the 2000 update. Obes Res. 2001; 9:135-69.

5. Altshuler D, Hirschhorn JN, Klannemark M, et al. The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes. Nat Genet. 2000; 26:76-80.

6. A unified nomenclature system for the nuclear receptor superfamily. Cell. 1999; 97:161-3.

7. Mangelsdorf DJ, Thummel C, Beato M, et al. The nuclear receptor superfamily: the second decade. Cell. 1995; 83:835-9.

8. Braissant O, Foufelle F, Scotto C, Dauca M, Wahli W. Differential expression of peroxisome proliferator-activated receptors (PPARs): tissue distribution of PPAR-alpha, -beta, and -gamma in the adult rat. Endocrinology. 1996; 137:354-66.

9. Auboeuf D, Rieusset J, Fajas L, et al. Tissue distribution and quantification of the expression of mRNAs of peroxisome proliferator-activated receptors and liver X receptor-alpha in humans: no alteration in adipose tissue of obese and NIDDM patients. Diabetes. 1997; 46:1319-27.

10. Issemann I, Green S. Activation of a member of the steroid hormone receptor superfamily by peroxisome proliferators. Nature. 1990; 347:645-50.

11. Forman BM, Chen J, Evans RM. Hypolipidemic drugs, polyunsaturated fatty acids, and eicosanoids are ligands for peroxisome proliferator-activated receptors alpha and delta. Proc Natl Acad Sci U S A. 1997; 94:4312-7.

12. Kliewer SA, Sundseth SS, Jones SA, et al. Fatty acids and eicosanoids regulate gene expression through direct interactions with peroxisome proliferator-activated receptors alpha and gamma. Proc Natl Acad Sci U S A. 1997; 94:4318-23.

13. Krey G, Braissant O, L'Horset F, et al. Fatty acids, eicosanoids, and hypolipidemic agents identified as ligands of peroxisome proliferator-activated receptors by coactivator- dependent receptor ligand assay. Mol Endocrinol. 1997; 11:779-91.

14. Schoonjans K, Martin G, Staels B, Auwerx J. Peroxisome proliferator-activated receptors, orphans with ligands and functions. Curr Opin Lipidol. 1997; 8:159-66.

15. Fruchart JC, Duriez P, Staels B. Peroxisome proliferator-activated receptor-alpha activators regulate genes governing lipoprotein metabolism, vascular inflammation and atherosclerosis. Curr Opin Lipidol. 1999; 10:245-57.

16. Pineda Torra I, Gervois P, Staels B. Peroxisome proliferator-activated receptor alpha in metabolic disease, inflammation, atherosclerosis and aging. Curr Opin Lipidol. 1999; 10:151-9.

17. Aoyama T, Peters JM, Iritani N, et al. Altered constitutive expression of fatty acid-metabolizing enzymes in mice lacking the peroxisome proliferator-activated receptor alpha (PPARalpha). J Biol Chem. 1998; 273:5678-84.

18. Guerre-Millo M, Gervois P, Raspe E, et al. Peroxisome proliferator-activated receptor alpha activators improve insulin sensitivity and reduce adiposity. J Biol Chem. 2000; 275:16638-42.

19. Mancini FP, Lanni A, Sabatino L, et al. Fenofibrate prevents and reduces body weight gain and adiposity in diet- induced obese rats. FEBS Lett. 2001; 491:154-8.

20. Chaput E, Saladin R, Silvestre M, Edgar AD. Fenofibrate and rosiglitazone lower serum triglycerides with opposing effects on body weight. Biochem Biophys Res Commun. 2000; 271:445-50.

21. Costet P, Legendre C, More J, Edgar A, Galtier P, Pineau T. Peroxisome proliferator-activated receptor alpha-isoform deficiency leads to progressive dyslipidemia with sexually dimorphic obesity and steatosis. J Biol Chem. 1998; 273:29577-85.

22. Vohl MC, Lepage P, Gaudet D, et al. Molecular scanning of the human PPARa gene: association of the L162v mutation with hyperapobetalipoproteinemia. J Lipid Res. 2000; 41:945-52.

23. Flavell DM, Pineda Torra I, Jamshidi Y, et al. Variation in the PPARalpha gene is associated with altered function in vitro and plasma lipid concentrations in Type II diabetic subjects. Diabetologia. 2000; 43:673-80.

24. Sapone A, Peters JM, Sakai S, et al. The human peroxisome proliferator-activated receptor alpha gene: identification and functional characterization of two natural allelic variants. Pharmacogenetics. 2000; 10:321-33.

25. Bouchard C. Genetic epidemiology, association, and sib-pair linkage: results from the Quebec Family Study. in: Bray GA, Ryan DH, eds. Molecular and genetic aspects of obesity. Baton Rouge, LA: Louisiana State University Press. 1996;5:47-81.

26. The Airlie (VA) Consensus Conference. in: Lohman T, Roche A, Martorel R, eds. Standardization of anthropometric measurements. Champaign, IL: Human Kinetics. 1988;39-80.

27. Behnke AR, Wilmore JH. Evaluation and regulation of body build and composition. Englewood Cliffs, NJ, Prentice-Hall, 1974.

28. Meneely GR, Kaltreider NL. Volume of the lung determined by helium dilution. J Clin Invest. 1949; 28:129-139.

29. Siri WE. The gross composition of the body. Adv Biol Med Phys. 1956; 4:239-280.

30. Despres JP, Prud'homme D, Pouliot MC, Tremblay A, Bouchard C. Estimation of deep abdominal adipose-tissue accumulation from simple anthropometric measurements in men. Am J Clin Nutr. 1991; 54:471-7.

31. Galli A, Pinaire J, Fischer M, Dorris R, Crabb DW. The transcriptional and DNA binding activity of peroxisome proliferator- activated receptor alpha is inhibited by ethanol metabolism. A novel mechanism for the development of ethanol-induced fatty liver. J Biol Chem. 2001; 276:68-75.

32. Lacquemant C, Lepretre F, Pineda Torra I, et al. Mutation screening of the PPARalpha gene in type 2 diabetes associated with coronary heart disease. Diabetes Metab. 2000; 26:393-401.

33. Evans D, Aberle J, Wendt D, Wolf A, Beisiegel U, Mann WA. A polymorphism, L162V, in the peroxisome proliferator-activated receptor alpha (PPARalpha) gene is associated with lower body mass index in patients with non-insulin-dependent diabetes mellitus. J Mol Med. 2001; 79:198-204.

34. Staels B, Dallongeville J, Auwerx J, Schoonjans K, Leitersdorf E, Fruchart JC. Mechanism of action of fibrates on lipid and lipoprotein metabolism. Circulation. 1998; 98:2088-93.

35. Akiyama TE, Nicol CJ, Fievet C, et al. Peroxisome proliferator-activated receptor-alpha regulates lipid homeostasis, but is not associated with obesity: studies with congenic mouse lines. J Biol Chem. 2001; 276:39088-93.

36. Peters JM, Park Y, Gonzalez FJ, Pariza MW. Influence of conjugated linoleic acid on body composition and target gene expression in peroxisome proliferator-activated receptor alpha- null mice. Biochim Biophys Acta. 2001; 1533:233-42.

37. Freely associating. Nat Genet. 1999; 22:1-2.

Table 1. Characteristics of the Subjects.

Table 2. Body Fatness and Body Fat Distribution Phenotypes by PPARα L162V Genotype for Men and Women Separately.

Figure 1. The potential mechanism by which PPARα may reduce body fat accumulation.

Figure 2. Body fatness and body fat distribution phenotypes by PPARα L162V genotypes. Number of subjects is indicated within each bar. P values are adjusted for age and gender. AT, indicates adipose tissue.

Figure 3. Odds ratio, with the 95% confidence intervals, of having a BMI > 30 kg/m2 for L162 HMZ individuals. The risk is shown without adjustment for confounding factors (bottom, p = 0.150) and after adjustment for age, gender and alcohol consumption (top, p = 0.041).