Dietary food, afteritis digested, absorbed and metabolized through a variety of metabolic pathways in human body, isusuallyturned into building materials or energy for maintaining normal cellular and whole body function. The excessenergy, no matter if it is from carbohydrate, fat or protein, is converted into storage fat, which leads to weight gain. When it is needed, such in the case of fasting or exercise, the storage fat is utilized as the major energy supply, which leads to weight loss. Fat storage and mobilization for energy are highly regulated energy metabolism pathways. PPAR (peroxisome proliferator-activated receptors) genes are master regulators in these processes.
There are 3 PPAR genes in human:PPARA, PPARD and PPARG. The protein product of PPARA isPPARα, which is mainly responsible for liver fatty acid oxidation (fat burningto produce energy) during fasting. The serum triglycerides lowing drug fibrates specifically target this protein. PPARD encodes the protein PPARδ (also known asPPARβ or PPARβ/δ), which promotesfatty acids synthesis in liverwhile activates fat burning in muscle. The protein product of PPARG is PPARγ, which is mainly responsible for lipid synthesisinadipocytes (energy storage) and also serves as the target of the anti-diabetes drug TZDs (thiazolidinediones). Interplay of these three PPARs, modulated by environmental factors such as food, exercise and medicine, playscritical roles in regulatingenergy storage and expenditure. Besides their roles in lipid and glucose metabolism, PPARs are also involved in adipogenesis (fat cell development)and osteogenesis (bone cell development), carcinogenesis, and immune response. Dysfunction of these genes or imbalance of their activities leads to various diseases including metabolic syndrome, T2DM (type 2 diabetes mellitus), obesity, cardiovascular diseases, and inflammation. Polymorphisms among these genes result in altered biochemical activity and differential dietary interaction, ultimately reflected in their risk association with chronic diseases such as metabolic syndrome, T2DM and dyslipidemia. The most common and biologically significant polymorphisms of these genes are PPARγ2 Pro12Ala, PPARα Leu162Val and PPARδ -87T>C (Table 1). Each is associated with risk factors for distinct chronic diseases that are the result of overall energy metabolism imbalance.
The PPARγ2 Pro12Ala polymorphism is highly related to obesity and T2DM. The major allele (Pro) of this polymorphismrepresents one of the “thrift genes” that regulates energy metabolism by converting excess energy intake into body fat for energy storage. It is one of the top genetic factors that are liable for obesity and T2DM caused by long term excess energy intake (positive energy balance). The minor allele(Ala) is less active in its biochemical activity, thus has lost in some degree the function of the “thrift genes”. It reduces the risk forobesity and T2DM. Given the same dietary calorie intake, non-overweight Ala carriers are less likely to gain weight. But once they become overweight, Ala carriers will lose weight much slower than homozygous Pro carriers. Inpopulation with the homozygous Pro/Progenotype, dietary total fat percentage and the P:S (polyunsaturated fatty acid: saturated fatty acids) ratio correlate with weight gain. A higher percentage of fat as the total energy intake normally leads to a higher BMI. A higher P:S ratio normally leads to a lower BMI. In contrast, these correlations do not exist in Ala carriers. Instead, the percentage of MUSF (monounsaturated fatty acids) play important role in dietary response in Ala carriers. A higher percentage of MUSF in dietary intake correlates with lower BMI and this correlation is not observed in the homozygous Pro/Pro genotype carriers. Based on these observations, dietary management recommendations for obesity and T2DM prevention in the Pro/Pro genotype include: 1) Perform calorie count to avoid excessive energy intake; 2) Reduce dietary total fat and 3) Increase the P:S ratio of dietary fat. There are two special dietary recommendations for the minor allele Alacarriers: 1) Perform calorie count to avoid excessive energy intake; 2) Increasethe percentage of MUSF as the total energy in diet.
The PPARα Leu162Val polymorphism is associated withdyslipidemia. The minor allele (Val) is associated increased BMI (body mass index), accompanied by higher level of low density lipoprotein-cholesterol (LDL-C) and other cardiovascular risk factors. In addition to its effect on fasting lipid parameters, the Val carriers also exhibit a higher risk for stage C heart failure. The Leu to Val change at amino acid 162 occurs in the DNA binding domain of the PPARαprotein. This results in altered protein-fatty acids interactions.In the absence or at low fatty acids concentrations,the activity of the Valallele is about a half of the activity of the Leu allele. At high fatty acids concentrations the Val allele activity can be 5-fold higher than the activity of the Leu allele. Dietary PUFA (polyunsaturated fatty acid) intake interacts with the Leu162Val polymorphism, leading to differentially modulated plasma triglycerides levels in the major and minor allele carriers. In the homologous major allele (Leu/Leu) carriers, PUFA intake (as the percentage of total energy) is positively correlated with plasma triglycerides levels. Higher PUFA intake leads to a slightly higher plasma triglyceride level. However, in Val allele carriers this correlation is negative. Higher PUFA intake leads to lower triglyceride level. Since high plasma triglycerides is a risk factor for cardiovascular diseases, a special dietary recommendation for the Val allele carriers of PPARα Leu162Valpolymorphism is to increase PUFA intake to 8% or more of the total energy intake.
The PPARδ -87T>C polymorphism, also known as PPARδ + 294T>C, is caused by a substitution of major allele T for a minor allele C at the87 nucleotides upstream of the coding region (which is 294 nucleotides downstream of the transcription starting site) of the PPARδ gene. This changeresults in the minor allele havinga higher transcriptional activity than the major allele. The PPARδ -87T>C polymorphism is associated with BMI, HDL-C (high-density lipoprotein cholesterol), and leptin (an appetite and energy expenditure controlling hormone)in a gender-dependent manner. In males, the minor allele associates with lower BMIand leptin, and higherHDL cholesterol levels. Infemales the minor allele associates with an increased BMI anddecreased HDL cholesterol but no association with leptin level. More importantly, the minor allele of this polymorphism is associated with a reduced risk for metabolic syndrome, a constellation of metabolic disorders that features visceral obesity, insulin resistance, dyslipidemia and hypertension.Thereduced risk for metabolic syndrome in the minor allele is only observed inpopulation with lower fat intake (less than 34.4% total fat energy). When the fat intake exceeds 34.4%, the protective effect of the minor allele no longer exists. In the minor allele carriers, HDL level is higher in those who take low-fat diet (total fat < 34.4%) and lower in those who take high-fat diet (>34.4%). In contrast, the total fat intake does not correlates with the HDL in the homozygous major allele (− 87T/T) carriers. Since HDL correlates with lower risk for cardiovascular diseases and MS, it is recommended for the PPARδ -87T>C polymorphism minor allele carriers (-87T/C and -87C/C) to restrict the total fat intake below 34.4% of the total energy to take the advantage of the protective effect against metabolic syndrome.
PPARs are nuclear hormone receptor superfamilytranscription factors, which activatetarget genes through ligand activation. PPARs form heterodimers with RXR (Retinoid X Receptor). The heterodimers bind to a specific DNA sequence called PPRE (peroxisome proliferator response element) located at the promoter region of target genes. Upon binding of different ligands (steroids, hormones, and metabolic intermediates such as fatty acids), the PPAR-RXR heterodimersthen undergo a conformational change, resulting in the recruitment of co-activators or co-repressors to the promoter region, leading to either activation or suppression of the target genes.
There are 3 PPAR genes in human: PPARA on chromosome 22 encodes the protein PPARα, PPARB on chromosome 6 encodes PPARβ (also known as PPARδ), and PPARG on chromosome 3 encodes three splice forms of PPARγ (PPARγ1,PPARγ2,and PPARγ4). The overall functional domain structures of these three PPARs are similar. Each contains aligand-independent activation domain, a DNA-binding domainand a ligand-binding domain (Fig.1).
Figure 1. Functional domains of human peroxisome proliferator-activated receptors PPARα, PPARδ/β, PPARγ (PPARγ1, PPARγ2 and PPARγ4). At the bottom, A/B (purple) represents the ligand-independentactivation domain; C (green)represents the DNA-binding domain(DBD); D (blue) represents the hinge region and E/F representsthe Ligand-binding domain (LBD). Adopted from Azhar, 2010.
These three PPAR proteins share 68-86% homology in their DNA binding domains and ligand-dependent activation domains. Therefore, they bind to common PPREs and interact with common ligands, but with different affinity. In addition, each PPAR also has its own specific ligands (Table 2). The ligand-independent activation domains of these proteins are quite distinct, presumably responsible for the specific interaction with hormones or other transcription cofactors. Differential PPRE and ligand affinity, differential cofactor interaction and differential tissue expression of PPARs dictate which genes to be activated and which ones suppressed.
Table 2. Ligands of three PPARs (Adapted from Desvergne &Wahli, 1999; Yessoufou& Wahli, 2010; Azhar, 2010).
| Ligand Type |
PPARα |
PPARβ/δ |
PPARγ |
| Synthetic |
Fibrate (fenofibrate, clofibrate, and gemfibrozil), fatty acyl-CoA dehydrogenase inhibitors, CPT1 inhibitors |
GW-501516 (GlaxoSmithKline Phase II), Bezafibric acid |
TZDs (thiazolidinediones), including, troglitazone,
pioglitazone, and rosiglitazone; Nonsteroidal anti-inflammatory drugs (indomethacin, flufenamic acid, fenoprofen and ibuprofen) |
| Natural fatty acids |
UPFA (Omega-3 & Omega-6), SFA (palmitic and stearic) |
UPFA (Omega-3 & Omega-6), SFA (palmitic and stearic) |
UPFA (Omega-3 & Omega-6) |
| Endogenous eicosanoids |
15d-PGJ2, PGJ2, PGA1/2, PGB2, Prostacyclin (PGI2), 8-HEPE (hydroxyeicosapentaenoic), Leukotriene B4 |
15d-PGJ2, PGJ2, PGA1/2, PGB2, Prostacyclin (PGI2) |
15d-PGJ2, PGJ2, PGA1/2, PGB2, 9-HODE (9-hydroxyoctadenoic acid), 13-HODE |
With regard to energy metabolism in human body, PPARα target genes promote liver fatty acid oxidation (fat burningto produce energy), PPARβ/δtargets increase lipid synthesis in liverwhile activate fat burning in muscle, and PPARγtargets are mainly involved in lipid synthesisinadipocytes (energy storage). Therefore, interplay of these three PPARs, modulated by environmental factors such as food, exercise and medicine, plays critical roles in energy metabolism (Table 3). Beyond energy metabolism, PPARs also regulates the expression of target genes involved in cell differentiation, chronic inflammation, wound repair, hypertension and atherosclerosis. Several comprehensive review articles on these topics have been published recently (Azhar 2010; Kawai and Rosen 2010;Yessoufou and Wahli, 2010; Wang and DuBois, 2010; Abranches et al, 2011; Varga et al, 2011). This review will introduce these three PPARs in the sequence from the best to the least understood ones.
Table 3. Metabolic functions of three PPARs in major tissues (Adapted from Desvergne &Wahli, 1999; Yessoufou& Wahli, 2010; Azhar, 2010).
| Tissues |
PPARα |
PPARβ/δ |
PPARγ |
| Liver |
Increases fatty acid uptake, fatty acid oxidation, and HDL apolipoproteins. |
Increases the pentose phosphate shunt to convert six carbon sugars to five carbon sugars and generate reducing power (NADPH) |
Increases lipogenesis and insulin sensitivity |
| Decreases VLDL production and inflammation |
Decreases glucose production |
|
| Muscle |
Increases fatty acid uptake, fatty acid oxidation, and triglycerides lipolysis |
Increases fatty acid oxidation, transportation and thermogenesis |
Increases insulin sensitivity |
| Decreases glucose utilization |
|
|
| Adipose tissue |
Increases lipolysis during fasting and starvation |
Increases fatty acid oxidation, transportation and thermogenesis |
Increases lipogenesis, insulin sensitivity, adipocyte differentiation, adipocyte survival and adipokine secretion |
| Pancreas |
Increases glucose-stimulated insulin secretion and fatty acid oxidation |
Decreases insulin secretion |
Not expressed |
| Decreases beta-cell lipotoxicity |
|
|
| Blood and vascular system |
Increases reverse cholesterol transportation |
Increases endothelial cell survival |
Increases reverse cholesterol transportation |
| Decreases inflammation response |
Decreases inflammation response |
Decreases inflammation response |
PPARG and T2DM
Introductions.The PPARG gene contains 11 exons spanning more than 100kilobaseson chromosome 3. Alternative splicing of five exons (A1, A2, B, C and D) at the 5′-endin combination of the 6 common exons (exon 1-6) at the 3’-end results in seven mRNA transcripts which are eventually translated into three protein variants PPARγ1, PPARγ2 and PPARγ4(Fig.2). PPARγ1 is expressed in abroad range of tissues including cardiac and skeletal muscle, pancreatic β-cells, spleen, intestine and vascular cells such as endothelial cells, smooth muscle cells and macrophages. PPARγ2 is mainly restricted to adipose tissue whereas PPAR4is expressed in macrophages and adipose tissue.The expression of PPARγ2 mRNA in adipose tissue is regulated by food intake. Higher dietary calorie leads to increased expression of PPARγ2 while lower calorie corresponds to decreased expression. The adipose tissueof obese people presents an increased amount ofPPARγ2 mRNA. In contrast, eating low-calorie diet by overweight individuals leads to a reduced PPARγ2 expression (Vidal-Puig et al, 1997). Increased PPARγ expression promotes the expressionof target genes involved in lipogenesis (such as acetyl-CoAcarboxylase, fatty acid synthase and ATP-citratelyase) and inhibits the expression of target genes involved in lipolysis and fatty acids oxidation. PPARγ2 also regulates glucose homeostasis directly by up-regulates genes such as the insulin dependent glucose transporter GLUT4 and down-regulates genes such as the glucose oxidation inhibitor PDK4. By controlling these target genes, PPARγ2 acts as one of the master regulators in maintaining energy metabolism.
Figure 2. PPARγ mRNA splicing forms and protein variants.Adopted from Azhar, 2010.
PPARG is one of the about 20 genes identified in T2DM susceptibility association studies. A hallmark of T2DM is insulin resistance. It is believed that elevated free fatty acids in blood circulation and accumulation of other lipid metabolites in peripheral tissues are the main causes of insulin resistance. The anti-diabetic drug TZDs (thiazolidinediones) specifically targets PPARγ protein to promote the conversion of free fatty acids to adipose tissue (storage fat).By enhancing the PPARγ activity, TZDs improve whole-body insulin sensitivity by reducing the free fatty acidsin circulation and lipid content in the liver.The interaction between TZDs and PPARγalso leads redistribution of fat from visceral deposits to white adipose tissue. Visceral fat is hazardous due to its insulin resistant property. White adipose tissue, on the other hand, is the natural energy deposit and responses to insulin signaling pathway.
More than 17 mutations in the coding region of PPARG gene have been described. Themajority of them are rare. Most of the heterozygous loss-of-function mutations are associated with the inherited disease familial partial lipodystrophic type 3 (FPLD3), characterized by altered subcutaneous fat distribution, insulin resistance, diabetes,elevated triglycerides, decreased HDL-cholesterol levels, hypertension, and polycystic ovary syndrome (discussed in later sections). A gain-of-function mutation Pro115Glnis associated with obesity, but not insulin resistant; two loss-of-function mutations Val290Met and Pro467Leuassociated with severe insulin resistance but normal body weight. Themost frequent and functionally important variant is in the PPARγ2 Pro12Ala polymorphism (SNP # rs1801282). A C>G substitution in the PPARG gene results in the conversion of proline to alanine at residue 12 of PPARγ2 protein, rendering the minor allele Ala carriers reduced risk for T2DM and a differential dietary fat responsefrom that of the homozygous major allele (Pro) carriers.
The first association between the PPARγ2 Pro12Ala polymorphisms and T2DM came from a study in Japanese-Americans, in which a frequency of the Alaallele was 9.3% in subjects with normal glucose tolerance comparing to only 2.2% in patients with T2DM (Deeb et al, 1998). This association was repeated in many subsequent studies. In addition, GWAS studies confirm the major allele of PPARγ2Pro12 as one of about 20 type 2 diabetes susceptibility genes identified. And meta-analysis studies conclude the minor Ala allele is protective against T2DM with an odds ratio 0f 0.86 comparing to wild type genotype (Gouda et al 2010). The analysis of the Pro12Ala polymorphism distribution in relation to T2DM prevalence and the diet lipid content showed a significant inverse relationship between Ala frequency and T2DM prevalence in populations where energy from lipidsexceeded 30% of the total energy intake (Scacchi et al, 2007). The protective effect of this variant has been interpreted as the result of improved insulin sensitivity. It is hypothesized that reduction in transcriptional activity of PPARγ2in adipose tissue, where PPARγ2 is predominantly expressed, decreases the release of insulin-desensitizing free fatty acids, TNFα and resistin and increased release of the insulin-sensitizing hormone adiponectin,leading to improved of insulin sensitivity and ultimately increased glucoseuptake and decreased glucose production (Desvergne & Wahli, 1999; Stumvoll and Häring, 2002). Therefore, in non-diabetes population, PPARγ2 Pro12Ala carriers are protected against type 2 diabetes. Once diabetes has developed (due to many other factors), the protective effect of the Ala allele is lost(Stumvoll and Häring, 2002). These phenomena are consistent with the observations from Pro12Ala knock-in mouse model in which a chow diet (low fat diet)fed Ala/Ala mice were leaner, had improved insulin sensitivity and plasma lipid profiles, and hada longer lifespan than Pro/Pro animals. However, the insulin sensitivity effect was lost in response to high-fat diet(Heikkinen et al, 2009).
PPARγ2 Pro12Ala, BMI and diet interaction. Most studies demonstrate no difference in BMI between Ala allele carriers and homozygote Pro allelecarriers. On theother hand, longitudinal studies in selected populationswith relatively small sample sizes consistently suggestedgreater weight gain in association with the Ala allele. It is now realized that the Ala allele associates with a higher BMI in several obese populations. However, in non-obeseindividuals, it isassociated with a slightly lower BMI (Nicklas et al, 2001; Stumvoll and Häring, 2002).It is hypothesized that the lower gene transcription activation property of PPARG2 Pro12Ala leads to a more free fatty acids oxidation and a less triglycerides synthesis. At the same calorie intake, The Ala allele gains less weight than the Pro allele. But as soon as Ala allele carriers put up with the weight, it becomes more difficult for them to lose it. Therefore, PARRG2 Pro12Ala is considered a risk factor for obesity (Blum et al, 2007).
On the other hand, the interaction of dietary fat with PPARγ polymorphism, as shown bymany cross-sectional studies, does have impact on BMI. In a study involving 2141 women (1637 Pro/Pro, 469 Pro/Ala and 35 Ala/Ala), associationsbetween intake of total fat, fat subtypes and BMI were different in Alaallele carriers compared with non-carriers. A positive trendbetween total fat intake and BMI was observed in Pro/Pro homozygote but not in Ala allele carriers. Intake of saturated fat was directly associated with increasedBMI among individuals of both genotype classes. Intake of MUSF (monounsaturated fat) was not associated with BMI amonghomozygous wild-type women but was inversely associated with BMI among Alaallelecarriers. Interestingly while no trend for intake ofpolyunsaturated fat and BMI was observed for eithergenotype, P:S (polyunsaturated: saturated fatty acids) ratio was directly associated with lower BMIamong Pro/Pro but not among Ala allelecarriers (Fig. 3).The effect of fat intake in response to PPARG2 polymorphisms appears influenced by energy expenditure. It was found thatwomen carrying the Ala allele showed higher energy expenditure in the short term after consuminga high-fat and SFA test meal, suggesting increasedpostprandial fat oxidation (Rosado et al, 2010).
The dietary fat interaction with PPARγ polymorphism is consistent with mouse models in which reducing PPARγ activity, either genetically or pharmacologically, results inanimals with resistance to high-fat diet-induced obesity (Kubota et al, 1999).
Figure 3. The quantity and type of dietary fat intake interact with PPAR-γ polymorphism and affect BMI (body mass index). Blue diamond represents homozygote Pro/Pro genotype carriers. Red square represents Ala carriers (Pro/Ala + Ala/Ala). Data are derived from Memisoglu et al, 2003.
PPARγ2 Pro12Ala and other diseases. The PPARγ2 Pro12Ala polymorphism is also associated with PCOS (polycystic ovary syndrome), a conditionin women characterized byexcess androgen and ovarian abnormalities. It is frequently associated with abdominal adiposity and insulin resistance due to androgen synthesisand secretion stimulated by higher insulin concentration. Since the PPARγ2 Pro12Ala improves insulin sensitivity, it is reasonable to expect the Ala allele confer some protection to PCOS development. Indeed, meta-analysis in a total of 2674 women clearly demonstrated that carrying Ala12 alleles either in homo- or heterozygosiswas associated with a reduced odd ratio of having PCOS to 0.77 (San-Millán & Escobar-Morreale, 2010). The protective effect of Ala allele on PCOS is related to the decreased BMR (basic metabolic rate) in Pro12Ala PCOS women. The BMR in non-overweight women (BMI<25 kg/m2) is about 60% of that in Pro12Pro PCOS women and the reduced BMR is accompanied by higher testosterone level. However, in overweight and obese PCOS women, the protective effect of Pro12Ala polymorphism disappears.ThereforePro12Ala PCOS women are at risk to increasetheir body weight and should restrict their energyintake by diet and enhance their energy expenditure byexercise(Koika et al, 2009).
It is now well established that besides energy metabolism, PPARγ target genes and polymorphism of PPARγ are also involved in cell differentiation, carcinogenesis, and inflammation regulations. However, reports on the direct link between the PPARγ2 Pro12Ala polymorphism and the above diseases are less conclusive. For example, the association of colorectal cancer with Ala allele is contradicting. The association of osteoporosis and Ala allele is far from conclusive. While serum osteoprotegerin (OPG) level, a key inhibitor of osteoclastogenesis, is significantly lower in Ala allele carriers than in Pro/Pro carriers, the bone mass density in both populations are the same (Rhee et al.,2007).
PPARγ2 Pro12Ala molecular mechanism. The Pro to Alasubstitution is close to the NH2-terminus of the protein in the ligand-independent activation domain, the activity of which is regulated through phosphorylation induced by insulin. In addition, Ala favors the formation of a-helices while Pro prevents it, the Pro to Alasubstitution leads to aless efficient stimulation of PPARG target genes. Twostudies have directly examined the transcriptional activityof the Ala variant of PPARγ2 in cell based assays. In a transient transfection assays, bindingof the PPARγ2 Ala variant to the PPRE (PPAR responsive DNAelements) was weaker than that of PPARγ2 Pro variant. Moreover,PPARγ2 targets genes such as lipoprotein lipase and acyl-CoA oxidase were expressed at a much lower level in cells over-expressing the Ala variant thanin cellsover-expressing the wild-type protein (Stumvoll and Häring, 2002).
The evolution of PPARγ2 Pro12Ala polymorphism. It is assumed thatPPARγ2 Pro variant is the ancestral allele and that the Ala allele emerged subsequently in non-African populations. The ancestral allele, considered as one of the ‘‘thrifty genes”, optimizes thebuilding of fat deposits as energy reserves and thus favored human survival in times when food was either limited, or sporadically available, or poor in quality. Because today’s lifestyle is much more relaxed and sedentary and is characterized by a diet that is rich in carbohydrates and fats and poor in fiber, these once favorable genetic factors have now become detrimental, leading to an increase in the risk of developing chronic diseases such as type 2 diabetes.
The emerging of the Pro12Ala variant, which could have happened about 43,000 years ago and is more favorable to the modern dietary than the wide type (Pro12)could be the result of adaptation to cold climate. In Europe, the Ala allele frequencies are distributed according to a latitudinal trend, with the highest in the northern and centralEuropean populations and the lowest in the Mediterranean populations (Table 4).It is hypothesized that the advantage of Ala variantin cold climates could be its lower ability to store free fatty acids in adipose tissue, making them available as substrate in brown fat thermogenesis. Free fatty acids could activate the UCP1 (uncoupling protein 1) protein, whichcould uncouple the oxidative phosphorylation at mitochondrial level and promote the energy release as heat. It is hypothesized that the brown adipose tissue (BAT) was an important factor for the Neanderthal cold adaptation.Consistently, the highest Ala frequencies among the Bolivian natives are in theinhabitants of higher altitudes (Ala frequency 0.4 comparing to 0.2 of the inhabitants in lower altitudes, Table 1) where the climate is colder, a situation similar to that of northern European populations exposed to harsh climates(Scacchi et al, 2007).
The low frequency of the Ala allele in the Ethiopian and U.S. African-American samples is possibly the result of gene flow from non-African groups. The highly heterogeneous Ala frequency distribution native American population (0.004–0.401) could be the result of genetic drift, a phenomenon occurs in isolated small populations.
Table 4. The PPARγ2 Pro12Ala polymorphism allele distribution in world population (Derived from Scacchi et al, 2007).
| Population |
Ala (minor allele) |
Pro (major allele) |
| African, Beninese |
0.0% |
100.0% |
| African, Ecuadorians |
0.0% |
100.0% |
| African, Americans |
2.2% |
97.8% |
| African, Ethiopians |
3.6% |
96.4% |
| African, Tunisians |
5.5% |
94.5% |
| Asian, Chinese |
4.0% |
96.0% |
| Asian, Indians |
11.9% |
88.1% |
| Asian, Iranian |
7.0% |
93.0% |
| Asian, Japanese |
4.1% |
95.9% |
| Asian, Koreans |
5.3% |
94.7% |
| Asian, Malays |
3.2% |
96.8% |
| Caucasian, Australians |
13.6% |
86.4% |
| Caucasian, Canada |
13.5% |
86.5% |
| Caucasian, Czech |
16.6% |
83.4% |
| Caucasian, Danish |
14.7% |
85.3% |
| Caucasian, Dutch |
12.0% |
88.0% |
| Caucasian, English |
13.3% |
86.7% |
| Caucasian, Finnish |
15.6% |
84.4% |
| Caucasian, French |
12.0% |
88.0% |
| Caucasian, Germans |
13.5% |
86.5% |
| Caucasian, Italian |
7.2% |
92.8% |
| Caucasian, Norwegian |
13.0% |
87.0% |
| Caucasian, Polish |
15.5% |
84.5% |
| Caucasian, Spanish |
8.8% |
91.2% |
| Caucasian, Swedish |
14.6% |
85.4% |
| Caucasian, USA |
11.8% |
88.2% |
| Hispanics, Mexicans |
12.2% |
87.8% |
| Hispanics, USA |
11.5% |
88.5% |
| Indians, Bolivians (high altitudes) |
40.1% |
59.9% |
| Indians, Bolivians (low altitudes) |
21.2% |
78.8% |
| Indians, Ecuadorian Cayapa |
0.4% |
99.6% |
| Indians, Oji-Cree (Canada) |
8.4% |
91.6% |
| Indians, Parkataje (Brazil) |
31.0% |
69.0% |
| Indians, Pima (USA) |
9.0% |
91.0% |
PPARA and dyslipidemia
Introductions. The human PPARAgene spans about 88.5 kb of genomic DNA on chromosome 22. The protein product PPARα is predominantly found in the liver, but is also expressedin cardiac myocytes, skeletal muscle, endothelial and smooth muscle cells, kidney epithelial cells, largeintestine epithelium, macrophages, lymphocytes and granulocytes. A key regulator offatty acidsoxidation in liver, PPARαfunctions as a general sensor of overall fatty acid concentration in circulation. Elevatedlevels of free fatty acids act as PPARαligand to activate the expression of criticalcatabolic enzymes that are responsible forfatty acids oxidation. Consequently, hepatic fatty acid catabolism is enhanced and the availability of fatty acids for the VLDL-TG (triglycerides) assemblyis restricted,leading to reduction of triglycerides level in circulation. In addition, PPARαactivation, by fatty acids as well as the TG lowing drug fibrates,counters hypertriglyceridemia by modulating the expression of certain apolipoproteins and other target genes involved in VLDL-TG assembly and secretion.Dysfunction and polymorphism of PPARα, by affecting various target genes, are major contributors of dyslipidemia.
Over a dozen of polymorphisms resulting in amino acid changes in PPARαprotein have been identified. The only one that has a relatively high frequency and a functionalconsequence is the PPARαLeu162Val polymorphism(SNP # rs1800206).The frequency of the minor allele 162Val is exceptional high in India and Spain and very rare in Africans (Table 5).The minor allele 162Val has been studied extensively and has been associated with increasedTG, body mass index, total cholesterol (TC), and low density lipoprotein-cholesterol (LDL-C).Recently, the 162Val allele was found more frequent in stage C patients than in stage A and B patients and healthy individuals, suggestingit could be a new risk factor in the development of stage C heart failure(Arias et al, 2011).
Table 5. The allele distribution PPARαLeu162Val polymorphism.
| Population |
Val(minor allele) |
Leu(major allele) |
| African, American |
0.6% |
99.4% |
| Asian, Chinese |
5.0% |
95.0% |
| Asian, Indian |
37.3% |
62.7% |
| Asian, Japanese |
5.0% |
95.0% |
| Caucasian, French Canadian |
6.0% |
94.0% |
| Caucasian, Spanish |
16.0% |
84.0% |
| Caucasian, British |
7.0% |
93.0% |
| Caucasian, American |
7.0% |
93.0% |
PPARα Leu162Val and dietinteraction. A significant gene-nutrient interaction between the Leu162Val polymorphism and total PUFA intake modulates plasma triglycerides and apolipoprotein C-III concentrations was reported by Tai et al, 2005. In this report, the allele 162Val was associated with greater TG and apoC-III concentrations only in subjects consuming a low-PUFA diet (below the population mean, 6% of energy). However, when PUFA intake was high, carriers of the 162Val allele had lower TG and apoC-III concentrations. For example,when PUFA intake was less than 4%, 162Val allele carriers had about 28% higher plasma TG than 162Lel homozygotes. But when PUFA intake was 8% or more, plasma TG in 162V allele carriers was 4% lower than that in 162Leu homozygotes. The type of PUFA was irrelevant since similar results were obtained for ω-6 and ω -3 fatty acids.A statistic modeling result predicted a negative correlation between fasting TG and the 162Val allele while a positive one for the major allele 162Leu (Fig.4), suggesting a beneficial effect of higher PUFA intake to 162Val carriers.
Figure 4. Predicted fasting plasma concentrations of TGs in relation to the PPARα Leu162Val polymorphism. Adopted from Tai et al, 2005.
PPARα Leu162Val exerciseresponse. In a unique interventional study, the effect of the PPARα Leu162Val polymorphism on dumb bell lifting exercise was investigated by comparing a trained arm and the untrained arm of the same individual in a Caucasian male university student population. The PPARα 162 valine allele was associated with a higher BMI and a significantly greater (24% to 38%)baseline subcutaneous fat volume in arms than that in the homozygotes Leu/Leu genotype.In response to unilateral arm training exercise, the PPARα 162Valallele was associated with increased fat volume in both the trained and untrained arms, while the Leu/Leu genotypes was associates with decreased subcutaneous fat volume in both arms. These effectssuggest that this PPARα polymorphism had a strong systemic effect on subcutaneous fat metabolism, where the major allele homozygotes showed a beneficial effect of exercise on adiposity, while the manor allele carriers put on weight with exercise (Uthurralt et al, 2007).
PPARα Leu162Val medicine response. The effect of PPARa polymorphisms on response to bezafibrate,a PPARa targeting fibrate drug that also interacts with PPARγ and PPARδ, was reported in one study.Treatment with bezafibrate resulted in a two-fold greater total cholesterol lowering effect in the minor allele 162Val carriers thanthe major allele Leu/Lue homozygotes. This study did not measure the LDL-C fraction but did measure the HDL-C levels which increased more in 162Val carriers (12%) than in the Leu/Luehomozygotes (7%). Therefore, the cholesterol lowing effect was mainly on LDL-C(Flavell et al, 2000).
Molecular mechanism of PPARα Leu162Val. The Leu162Val variant confers an amino acid change in the DNA binding domain of the protein. This change results in a protein with altered ligand dependent PPRE binding activity. In the absence or at low ligand concentrations,the activity of the 162V allele was almost a half of the activity of the 162L allele. At high ligand concentrations the PPRE binding activity of is higher for the 162V isoform (Sapone et al, 2000). As the result, the L162V polymorphism, through interaction with environmental factors, affect the gene expression of PPARa targets differentially. At a particular ligand concentration, some of PPARa target genes are up-regulated, some are down-regulated while others are unchanged. The overall impact is therefore, depending on the identity and concentration of the PPARa interacting ligand.
PPARD and Metabolic Syndrome
Introductions. The human PPARDgene spans about85.6 kb of genomic DNA on chromosome 6. The protein product PPARδ differs from the othertwo PPARs (PPARα and PPARγ) by its more widespread tissue-specific expression pattern and its distinct metabolic functions in liver where it promote de novo free fatty acids synthesis (converting excess energy to fat) and muscle(both skeletal and cardiac) where it activates lipid catabolism (fat burning). Other functions of PPARδinclude anti-inflammation and wound healing. PPARδknockout mice mostly die in uterus and the survivors are smallerthan wild type animals. Over-expression of constitutively active PPARδ in skeletal muscledecreases weight gain, fat mass and skeletal muscle TG content, improves glycemic controlin mice maintained on a high-fat diet. None of the agonists specifically targeting PPARδhas been approved by FDA (Food and Drug Administration). Nevertheless, several potent PPARδ agonists (for example GW-501516) in various phases of clinical trials have been employed in the mechanistic studies and yielded valuable information about this protein. PPARδ agonistscauseweight loss, improve type 2 diabetes and skeletal musclefunction and increase leptin secretion in adipose tissue explantsin mice. In healthy human subjects, treatment with PPARδ agonist lowers triglycerides and increasedHDL cholesterol and modulates inflammatory responses of macrophages.
PPARδ cooperates with PPARα and PPARγ to maintain a balanced lipid and glucose homeostasis, controlling energy flow in response to environmental factors such as food, medicine and exercise. Dysfunction of PPARδ leads to an emerging chronic disease metabolic syndrome(MS, not multiple sclerosis). MS, also known as syndrome X or MetS, is a constellation of metabolic disorders that features visceral obesity, insulin resistance, dyslipidemia and hypertension. Approximately 9% adolescents, 24% adult and 44% of 50 years or older Americans have MS, which accounts for 6–7% of all-cause mortality in the United States. Moreover, MS is associated with a twofold increase risk for cardiovascular diseases and a fivefold increased risk for T2DM (Seedorf and Aberle, 2007; Azhar, 2010). Genetic polymorphism of PPARδ and its interaction with dietary intake are important factors in preventing or managing of MS (Fig. 5).
Figure 5. Association of PPARδ with the metabolic syndrome. An important abnormality of the metabolic syndrome relates toincreased secretion of fatty acids from adipose tissue and glucose from the liver. All three PPAR subtypes cooperate in counteracting adverse effects on lipid andglucose metabolism resulting from elevated free fatty acids and glucose in the blood stream. Themost important role of PPARδ most likely is to significantly increase the capacity of skeletal and heart muscle for utilizing fatty acids for their energy metabolism.Furthermore, PPARδ together with PPARα inhibits glucose and VLDL secretion from the liver. These effects are very important for preserving normal FFA,triglyceride and HDL levels as well as insulin sensitivity in the presence of high dietary fat intake. Adopted from Seedorf & Aberle, 2007.
PPARδ polymorphisms. More than 15 SNPs spanning the 5’ UTR to 3’ UTR region of PPARδ gene have been identified. Only one of them, the PPARδ -87T>C (SNP# rs2016520) has a relatively high frequency and is associated with biological consequences. This polymorphism is also known as + 294T>C (294 nucleotides downstream of the transcription starting site). The nucleotide switch alters the affinity for binding of the SP1 transcription factor with carriers of the minor allele having higher transcriptional activity than the major allele (Skogsberg et al (2003a). The overall minor allele frequency is between 16%-34.5% world wise with highest found in Israel and lowest in Sweden(Table 6).
Table 6. The allele distributionof PPARδ -87T>C polymorphism.
| Population |
C (minor allele) |
T (major allele) |
| African, American |
29.0% |
71.0% |
| African, Tunisian |
19.0% |
81.0% |
| Asian, Chinese |
28.0% |
72.0% |
| Asian, Korean |
24.0% |
76.0% |
| Caucasian, British |
21.0% |
79.0% |
| Caucasian, French Canadian |
20.0% |
80.0% |
| Caucasian, Israeli |
34.5% |
65.5% |
| Caucasian, Sweden |
16.0% |
84.0% |
PPARδ -87T>C polymorphismand MS association. In normal weight human population (BMI < 25), the minor C allele is associated with increased BMI, LDL and Apo B and decreased HDL (Skogsberg et al, 2003a, b; Aberle et al, 2006), suggesting unfavorable effects of the minor allele on metabolic and coronary heart diseases. However in overweight (BMI around 28) population, Robitaille et al (2007) found that the minor C allele was associated with a lower risk to metabolic syndromeafter excluding the subjects diagnosed with type 2 diabetes, type III dysbetalipoproteinemia, familial hypercholesterolemia and familial combined hyperlipidemia.In addition, the data showed this association was influenced by dietary fat intake. The protective effect for the MS seen for carriers of the –87C allele is observed mainly in individuals consuming less than 34.4% of energy from fat and this apparent protective effect is not observed in individuals consuming more than 34.4% of energy from fat. The age- and sex-adjusted odds ratio of exhibiting three or more features of the metabolic syndrome when carrying the − 87C allele was 0.62 compared to − 87T/T. However, in subjects consuming a low proportion of energy from fat (34.4% or less), the odds ratio in carriers of the − 87C allele was 0.42. Therefore, the C allele was found to be protective against MS in overweight population who take low-fat diet.
Another recently published study (Burch et al, 2010) involving 11,074 individuals (5850 overweight non-diabetic and 5224 obese diabetic) showedthe PPARδ -87T>C polymorphismassociated with BMI, high-density lipoprotein cholesterol, leptin, and TNFα in a gender-dependent and diabetes-independent manner. In males, the minor allele associated with lower BMI, leptin, andTNFα, and higherHDL cholesterol levels. Infemales the minor allele associates with an increased BMI anddecreased HDL cholesterol but not with leptin andTNFα levels.The results suggest differential effects of PPARδ in males and females (Fig. 6).
Figure 6. Gender-dependent association of BMI and HDL-C with PPARδ SNP rs2016520 in overweight non-diabetics subjects. The trend is the same in diabetic subjects (Adapted from Burch et al, 2010).
PPARδ -87T>C polymorphismis also associated with reduced birth weight and reduced body height. In a meta-analysis of about 48,000 objects, it was estimated that the minor C allele had an overall effect of 0.5cm height reduction per minor allele.This association stands in all age population tested and was more evident (about 1.1 cm per minor allele) in prepubescent children. The reduced body height was highly correlated with birth weight, which was 56 g in heterozygote individuals and 118 g lighter in homozygote minor allele carriers(Burch et al, 2009). The exact mechanism of this polymorphism leading to reduced birth weight and reduced stature is not clear. It has been hypothesized to be the results of altered PPARδfunction in glucose and lipid metabolism, or skeletal muscle or osteoclast development. The connection between body height and MS is not clearlyunderstood at this moment.
PPARδ -87T>C and dietary response. Gene–environment interactions with the PPARδ-87T>C polymorphism have been previously investigated. Neitheralcohol intake nor smoking habits influenced the relationshipbetween the PPARδ-87T>C polymorphism andrisk of CHD in a case–control study of men. However, a striking interaction with total fat intake was detected. Among carriers of the -87C allele, plasma HDL-C levels werelower in subjects who consumed more than 34.4% of energyfrom fat whereas in -87T/T homozygotes plasma HDL-C levels were similar irrespective of the amount of fatconsumed. Similarresults were observed with the total cholesterol/HDL-Cratio. Carriers of the -87C allele who had a diet rich in fathad an increased ratio whereas in -87T/T homozygotes, theratio was similar in both subgroups (Fig. 7).
Figure 7. Interaction between the PPARδ -87T>C polymorphism andfat intake on plasma HDL-C levels (a) and the total cholesterol/HDL-C ratio(b). Fat intake is stratified according to the median value (34.4% of the energyintake). Black bars present subjects who consumed less than 34.4% of energyfrom fat whereas open bars present subjects who ate more than 34.4% ofenergy from fat. The –87C carriers group includes both –87 C/C and –87 T/C genotypes.The number within each bar identifies each subgroup whereas the numberabove the standard error indicates the significant difference with the correspondingsubgroup. Adopted from Robitaille et al, 2007.
PPARδ -87T>C and exercise response. It is known in mouse models, over-expressingskeletal muscle PPARδ exhibit an enhanced endurance capacity and greatly increased levelsof endurance of type I oxidative/slow twitch muscle fibers. However, the literature is inconsistent regarding the possiblerole of the PPARδ -87T>C polymorphism in enduranceperformance in human population. While Akhmetov et al. (2007) suggestedan association between the minor allele and eliteendurance performance, Hautala et al (2007) illustrated that the minor allele homozygotesCC had smaller training-induced increases in maximal oxygenuptake and maximal workload than the CT and TTcarriers, respectively. Eynon et al (2009) found no differences in the PPARδ -87T>C allele frequency distribution among 155Israeli athletes (endurance athletes and sprinters) and 240 healthy control subjects. However, an interaction of this polymorphisms with a polymorphism of PPARGC1A gene was detected. The PPARDCC+PPARGC1A Gly/Gly genotypes were more frequently found in the elite endurance athletesthan in national-level endurance athletes. In the cohort of endurance athletes,the odds ratio of the ‘optimal genotype’ for endurance athletes (PPARD CC+PPARGC1AGly/Gly+PPARGC1A Gly/Ser) being an elite-level athlete was 8.32. In conclusion, a higher frequency of the PPARGC1A Gly/Gly+PPARD CCgenotype is associated with elite-level endurance athletes.
PPARδ -87T>C and medicineresponse. In a subgroup analysis of obese and diabetic subjects on statin therapy (n=5133), thehomozygous minor allele(CC) individuals were about 2-fold less likely to achieve target total cholesterol concentrations (4 mmol/liter) and LDLcholesterol concentrations (2 mmol/liter) than the homozygous major allele (TT) individuals. There wasno association with baseline cholesterol or LDL cholesterollevels, and adjustment for other lipid-lowering drugs anddiabetes status had no effect on this association.Therefore, individuals bearing the C allele wereresistant to statin therapy in terms of the minimum total cholesterol and minimum triglyceridelevels achieved on statin therapy (Burch et al, 2010).
PPARδ molecular mechanisms
The ubiquitous transcription factor SP1 is one of the factors that control the expression of PPARδ. There are two SP-1 binding sites in the promoter region of PPARD gene. The minor allele of the PPARδ -87T>C polymorphism creates the third SP1 biding site at the PPARD gene promoter. As the result, the affinity for binding of the SP1 transcription factor and the expression of PPARδ is higher in the minor allele than in the major allele (Skogsberg et al, 2003a).
The gender effect on PPARδis probably caused by apotent endogenous PPAR ligand prostacyclin, an eicosanoid that is highly is stimulated by estrogens.
Summary
Highly coordinated actions of PPARs maintain a balanced energy flow in human body by controlling various aspects in lipid and glucose metabolism. Excess energy is converted into fat and stored. During fasting or exercise, the storage fat is mobilized and spent. Polymorphisms of PPARs have great impact on these processes and interact with dietary, medicine and exercise. Knowing your genes is therefore a great advantage in preventing and managing energy imbalance induced chronic diseases such as T2DM, dyslipidemia and MS.
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