Association of peroxisome proliferator-activated receptor gamma coactivator 1 alpha (PPARGC1A) gene polymorphisms and type 2 diabetes mellitus: a meta-analysis

The rs17782313 polymorphism near MC4R gene confers a high risk of obesity and hyperglycemia, while PGC1α rs8192678 polymorphism is weakly correlated with glucometabolic disorder: a systematic review and meta-analysis

Background

The relationships of the rs17782313 polymorphism near melanocortin 4 receptor gene (MC4R) and the rs8192678 polymorphism in peroxisome proliferator-activated receptor gamma coactivator 1 alpha gene (PGC1α) with metabolic abnormalities have been explored in many populations around the world, but the findings were not all consistent and sometimes even a bit contradictory.

Methods

Electronic databases including Medline, Scopus, Embase, Web of Science, CNKI and Google Scholar were checked for studies that met the inclusion criteria. Data were carefully extracted from eligible studies. Standardized mean differences (SMDs) were calculated by using a random-effects model to examine the differences in the indexes of obesity, glucometabolic disorder and dyslipidemia between the genotypes of the rs17782313 and rs8192678 polymorphisms. Cochran's Q-statistic test and Begg's test were employed to identify heterogeneity among studies and publication bias, respectively.

Results

Fifty studies (58,716 subjects) and 51 studies (18,660 subjects) were respectively included in the pooled meta-analyses for the rs17782313 and rs8192678 polymorphisms. The C-allele carriers of the rs17782313 polymorphism had a higher average level of body mass index (SMD = 0.21 kg/m2, 95% confidence interval [95% CI] = 0.12 to 0.29 kg/m2, p < 0.001), waist circumference (SMD = 0.14 cm, 95% CI = 0.06 to 0.23 cm, p < 0.001) and blood glucose (SMD = 0.09 mg/dL, 95% CI = 0.02 to 0.16 mg/dL, p = 0.01) than the TT homozygotes. Regarding the rs8192678 polymorphism, no significant associations with the indexes of obesity, glucometabolic disorder and dyslipidemia were detected. However, significant correlations between the rs8192678 polymorphism and multiple glucometabolic indexes were observed in subgroup analyses stratified by sex, age, ethnicity and health status.

Conclusion

The meta-analysis demonstrates that the C allele of the MC4R rs17782313 polymorphism confers a higher risk of obesity and hyperglycemia, and the PGC1α rs8192678 polymorphism is weakly correlated with glucometabolic disorder. These findings may partly explain the relationships between these variants and diabetes as well as cardiovascular disease.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42022373543.

Association between PPARγ, PPARGC1A, and PPARGC1B genetic variants and susceptibility of gastric cancer in an Eastern Chinese population

PURPOSE

Previous studies showed that peroxisome proliferator-activated receptor gamma (PPARγ) and PPARγ coactivator1 family (PPARGC1A and PPARGC1B) gene single nucleotide variants (SNVs)were strongly associated with cancer susceptibility. The purpose of this study was to investigate the association of PPARγ, PPARGC1A, and PPARGC1B variants with the risk of gastric cancer (GC).

PATIENTS AND METHODS

We performed a case-control study of 490 GC cases and 1,476 healthy controls from eastern China. PPARγ rs1801282 C > G, rs3856806 C > T, PPARGC1A rs2970847 C > T, rs8192678 C > T and PPARGC1B rs7732671 G > C, rs17572019 G > A SNVs were selected to investigate the association between these SNVs and GC susceptibility. Genotypes of the SNVs were assessed by multiplex fluorescent PCR using a custom-by-design 48-Plex SNPscan^tm Kit.

RESULTS

The PPARγ rs1801282 SNV was associated with a decreased risk for GC (GC vs. CC: odds ratio (OR) = 0.62, 95% confidence interval (95%CI) = 0.42-0.93, adjusted P = 0.019; GC + GG vs. GG: OR = 0.63 95%CI = 0.42-0.93, adjusted P = 0.019; respectively). In addition, stratified analysis revealed that the PPARγ rs1801282 SNV was correlated with the risk of GC in subgroups of age ≥ 61, no smoking, and no alcohol consuming. We also confirmed that the PPARγ rs3856806 C > T SNV promoted the risk of GC in women. The PPARGC1A rs8192678 TT genotype decreased the susceptibility of GC in men. The PPARGC1A rs2970847 C > T SNV decreased the susceptibility of GC in the subgroup of BMI ≥ 24 kg/m². The PPARGC1B rs7732671 G > C and rs17572019 G > A SNVs promoted the risk of GC in the subgroup of BMI ≥ 24 kg/m².

CONCLUSION

This study indicates that the PPARγ, PPARGC1A, and PPARGC1B SNVs may be associated with the susceptibility of GC in eastern Chinese population. Future studies with larger populations, detailed H. pylori infection status for subgroup analysis, and functional study are needed to further clarify the relationship between these SNVs and GC risk.

Influence of Peroxisome Proliferator-Activated Receptor (PPAR)-gamma Coactivator (PGC)-1 alpha gene rs8192678 polymorphism by gender on different health-related parameters in healthy young adults

This study aimed to analyze the influence of the peroxisome proliferator-activated receptor (PPAR)-gamma coactivator (PGC)-1 alpha (PPARGC1A) gene rs8192678 C>T polymorphism on different health-related parameters in male and female young adults. The PPARGC1A gene rs8192678 polymorphism was ascertained by polymerase chain reaction in 74 healthy adults (28 women; 22.72 ± 4.40 years) from Andalusia (Spain). Health-related variables included cardiometabolic risk, anthropometry and body composition, biochemical parameters, insulin sensitivity (QUICKI and HOMA-IR indexes), blood pressure (BP) at rest and after exercise, diet, basal metabolism, physical activity, maximal fat oxidation, and cardiorespiratory fitness. Our results showed differences by PPARGC1A gene rs8192678 C>T polymorphism in body mass (p = 0.002), body mass index (p = 0.024), lean body mass (p = 0.024), body fat (p = 0.032), waist circumference (p = 0.020), and BP recovery ratio (p < 0.001). The recessive model (CC vs. CT/TT) showed similar results but also with differences in basal metabolism (p = 0.045) and total energy expenditure (p = 0.024). A genotype*sex interaction was found in the QUICKI index (p = 0.016), with differences between CC and CT/TT in men (p = 0.049) and between men and women inside the CT/TT group (p = 0.049). Thus, the PPARGC1A gene rs8192678 C>T polymorphism is associated with body composition, basal metabolism, total energy expenditure, and BP recovery, where the CC genotype confers a protective effect. Moreover, our study highlighted sexual dimorphism in the influence of PPARGC1A gene rs8192678 C>T polymorphism on the QUICKI index.

Associations of Polymorphisms in the Peroxisome Proliferator-Activated Receptor Gamma Coactivator-1 Alpha Gene With Subsequent Coronary Heart Disease: An Individual-Level Meta-Analysis

Background: The knowledge of factors influencing disease progression in patients with established coronary heart disease (CHD) is still relatively limited. One potential pathway is related to peroxisome proliferator–activated receptor gamma coactivator-1 alpha (PPARGC1A), a transcription factor linked to energy metabolism which may play a role in the heart function. Thus, its associations with subsequent CHD events remain unclear. We aimed to investigate the effect of three different SNPs in the PPARGC1A gene on the risk of subsequent CHD in a population with established CHD.

Methods: We employed an individual-level meta-analysis using 23 studies from the GENetIcs of sUbSequent Coronary Heart Disease (GENIUS-CHD) consortium, which included participants (n = 80,900) with either acute coronary syndrome, stable CHD, or a mixture of both at baseline. Three variants in the PPARGC1A gene (rs8192678, G482S; rs7672915, intron 2; and rs3755863, T528T) were tested for their associations with subsequent events during the follow-up using a Cox proportional hazards model adjusted for age and sex. The primary outcome was subsequent CHD death or myocardial infarction (CHD death/myocardial infarction). Stratified analyses of the participant or study characteristics as well as additional analyses for secondary outcomes of specific cardiovascular disease diagnoses and all-cause death were also performed.

Results: Meta-analysis revealed no significant association between any of the three variants in the PPARGC1A gene and the primary outcome of CHD death/myocardial infarction among those with established CHD at baseline: rs8192678, hazard ratio (HR): 1.01, 95% confidence interval (CI) 0.98–1.05 and rs7672915, HR: 0.97, 95% CI 0.94–1.00; rs3755863, HR: 1.02, 95% CI 0.99–1.06. Similarly, no significant associations were observed for any of the secondary outcomes. The results from stratified analyses showed null results, except for significant inverse associations between rs7672915 (intron 2) and the primary outcome among 1) individuals aged ≥65, 2) individuals with renal impairment, and 3) antiplatelet users.

Conclusion: We found no clear associations between polymorphisms in the PPARGC1A gene and subsequent CHD events in patients with established CHD at baseline.

Candidate Genes of Regulation of Skeletal Muscle Energy Metabolism in Athletes

All biological processes associated with high sports performance, including energy metabolism, are influenced by genetics. DNA sequence variations in such genes, single nucleotide variants (SNVs), could confer genetic advantages that can be exploited to achieve optimal athletic performance. Ignorance of these features can create genetic “barriers” that prevent professional athletes from pursuing a career in sports. Predictive Genomic DNA Profiling reveals single nucleotide variations (SNV) that may be associated with better suitability for endurance, strength and speed sports. (1) Background: To conduct a research on candidate genes associated with regulation of skeletal muscle energy metabolism among athletes. (2) Methods: We have searched for articles in SCOPUS, Web of Science, Google Scholar, Clinical keys, PubMed, e-LIBRARY databases for the period of 2010–2020 using keywords and keywords combinations; (4) Conclusions: Identification of genetic markers associated with the regulation of energy metabolism in skeletal muscles can help sports physicians and coaches develop personalized strategies for selecting children, teenagers and young adults for endurance, strength and speed sports (such as jogging, middle or long distance runs). However, the multifactorial aspect of sport performances, including impact of genetics, epigenetics, environment (training and etc.), is important for personalized strategies for selecting of athletes. This approach could improve sports performance and reduce the risk of sports injuries to the musculoskeletal system.

Selenium supplementation during pregnancy and lactation promotes metabolic changes in Wistar rats' offspring

Epidemiological and animal studies have demonstrated a strong association between selenium (Se) supplementation and metabolic disorders, we aimed to evaluate whether maternal Se supplementation was able to change metabolic parameters in rats' offspring. Moreover, as Se is a deiodinase (DIO) cofactor, we decided to investigate how thyroid hormones (THs) would be involved in such metabolic changes. Thereby, two groups (n = 6, ~250 g) of female Wistar rats underwent isotonic saline or sodium selenite (1 mg/kg, p.o.) treatments. Although there were no significant differences in body weight between groups, the Se treatment during pregnancy and lactation increased milk intake and the visceral white adipose tissue (WAT) in offspring. The rats whose mothers were treated with Se also presented an improvement in the glucose tolerance test and in the glucose-stimulated insulin secretion. Regarding the lipid metabolism, the Se group had a reduction of triglycerides in the liver and in WAT. These metabolic changes were accompanied by an increase in serum triiodothyronine (T₃ ) and in DIO 2 expression in brown adipose tissue (BAT). We further demonstrate an increased expression of peroxisome proliferator-activated receptor-gamma coactivator 1-alpha (PGC-1α) and nuclear respiratory factor-1 (NRF-1) mRNA in the liver. In adulthood offspring, Se supplementation programs thyroid function, glucose homeostasis, and feeding behaviour. Taken together, there is no indication that Se programming causes insulin resistance. Moreover, we conjecture that these metabolic responses are induced by increased thyroxine (T₄ ) to T₃ conversion by DIO2 in BAT and mediated by altered transcription factors expression associated with oxidative metabolism control in the liver.

Correlation Between PPARGC1A Gene Rs8192678 G>A Polymorphism and Susceptibility To Type-2 Diabetes

Objective

To systematically investigate the correlation between the G>A polymorphism of the peroxisome proliferator-activated receptor γ coactivator 1α (PPARGC1A or PGC-1alpha) gene rs8192678 locus and the susceptibility to type-2 diabetes mellitus (T2DM).

Methods

The inclusion and exclusion criteria and retrieval strategies of original literatures were formulated. Then, subjects and free words “PPARGC1A”,”gene polymorphism”, and “T2DM” were retrieved from the PubMed, EMBASE, and Cochrane Library databases. Case-control studies on the G>A polymorphism of the PPARGC1A gene rs8192678 locus and susceptibility to T2DM were included for the meta-analysis.

Results

The number of cases in the T2DM group and control group was 5,607 and 7,596, respectively. The meta-analysis revealed that the PPARGC1A gene rs8192678 locus G>A polymorphism is associated with susceptibility to T2DM. There are differences in each group of genetic models, of which three groups of genetic models are highly significant. In the allele model, OR=1.249, 95% CI: 1.099-1.419, and P=0.001. In the dominant inheritance model, OR=1.364, 95% CI: 1.152-1.614, and P=0.000. In the additive inheritance model, OR=0.828, 95% CI: 0.726-0.945, and P=0.005. And one group is significant, in the recessive inheritance model, OR=1.187, 95% CI: 1.021-1.381, and P=0.026.

Conclusion

In Western Asian, South Asian, European and African populations, the A allele of the PPARGC1A gene rs8192678 locus may be one of the risk factors for T2DM.

Systematic Meta-analysis Revealed an Association of PGC-1α rs8192678 Polymorphism in Type 2 Diabetes Mellitus

Background

Genome-wide association study (GWAS) provides an unprecedented opportunity to reveal substantial genetic contribution to type 2 diabetes mellitus (T2DM) and glycemic identification of allelic heterogeneity and population-specific genetic variants, yet it also faces difficulty due to the vast amount of potential confounding factors and limited availability of clinical data. To identify responsible susceptibility loci and genomic polymorphism for T2DM and glycemic traits, we have systematically investigated a genome-wide association study related to T2DM. Although GWAS has captured many common genetic variations, which are related to T2DM, each risk allele (RA) of single-nucleotide polymorphisms (SNPs) at these loci is not conclusive. Therefore, it is common to present a combination of several SNPs to infer T2DM risk, yet it is still insufficient to be deterministic. To streamline the identification of a deterministic genetic variation in T2DM, we developed this meta-analysis as a showcase to comprehensively identify the association between cumulative RAs and T2DM risk by combining different studies in reported literature and databases. After all, we identified that PGC-1α rs8192678 polymorphism can be considered as a potentially deterministic biomarker in T2DM risk. Previous studies have potentially linked PGC-1α rs8192678 polymorphism to type 2 diabetes mellitus (T2DM) risk, but the results remain inconsistent in different populations and are not conclusive. We developed a new meta-analysis approach to systematically identify the association between PGC-1α rs8192678 polymorphism and T2DM, and we have comprehensively assessed different ethnic groups to validate our findings.

Methods

We performed comprehensive information retrieval and knowledge discovery meta-analysis by searching extensively published literature and different electronic databases to acquire eligible studies for the above association study. We developed a method to use pooled odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) in five genetic models (allelic, dominant, recessive, homozygous, and heterozygous genetic models) to identify the relationship among ethnicity subgroup analyses comprehensively.

Results

We identified 20 eligible studies consisting of 16,182 subjects (8,038 cases and 8,144 controls) in our meta-analysis. PGC-1α rs8192678 polymorphisms of all subjects showed a significant association with T2DM susceptibility under all genetic models: allelic (OR: 1.24, 95% CI: 1.13-1.35), dominant (OR: 1.27, 95% CI: 1.14-1.42), recessive (OR: 1.24, 95% CI: 1.14-1.36), homozygous (OR: 1.40, 95% CI: 1.20-1.64), and heterozygous (OR: 1.20, 95% CI: 1.06-1.35). In the subgroup analysis, we identified a significant association between PGC-1α rs8192678 polymorphism and T2DM in the Caucasian and Indian populations under all genetic models we investigated. This is the most comprehensive study of the subject to date.

Conclusion

Our development of meta-analysis revealed that the minor allele (A) carriers, especially AA genotype carriers, can lead to risk of T2DM in the Caucasian and Indian populations. This is the first report that such risk has been confirmed. Our finding shed new light into the genetic alteration in T2DM.

Association of PPARGC1A Gly428Ser (rs8192678) polymorphism with potential for athletic ability and sports performance: A meta-analysis

Background

Genetics plays a role in determining potential for athletic ability (AA) and sports performance (SP). In this study, AA involves comparing sedentary controls with competitive athletes in power and endurance activities as well as a mix between the two (SP). However, variable results from genetic association studies warrant a meta-analysis to obtain more precise estimates of the association between PPARGC1A Gly482Ser polymorphism and AA/SP.

Methods

Multi-database literature search yielded 14 articles (16 studies) for inclusion. Pooled odds ratios (ORs) and 95% confidence intervals (CI) were used to estimate associations. Summary effects were modified based on statistical power. Subgroup analysis was based on SP (power, endurance and mixed) and race (Caucasians and Asians). Heterogeneity was assessed with the I² metric and its sources examined with outlier analysis which dichotomized our findings into pre- (PRO) and post-outlier (PSO).

Results

Gly allele effects significantly favoring AA/SP (OR > 1.0, P < 0.05) form the core of our findings in: (i) homogeneous overall effect at the post-modified, PSO level (OR 1.13, 95% CI 1.03–1.25, P = 0.01, I² = 0%); (ii) initially homogeneous power SP (ORs 1.22–1.25, 95% CI 1.05–1.44, P = 0.003–0.008, I² = 0%) which precluded outlier treatment; (iii) PRO Caucasian outcomes (ORs 1.29–1.32, 95% CI 1.12–1.54, P = 0.0005) over that of Asians with a pooled null effect (OR 0.99, 95% CI 0.72–1.99, P = 0.53–0.92) and (iv) homogeneous all > 80% (ORs 1.19–1.38, 95% CI 1.05–1.66, P = 0.0007–0.007, I² = 0%) on account of high statistical power (both study-specific and combined). In contrast, none of the Ser allele effects significantly favored AA/SP and no Ser-Gly genotype outcome favored AA/SP. The core significant outcomes were robust and showed no evidence of publication bias.

Conclusion

Meta-analytical applications in this study generated evidence that show association between the Gly allele and AA/SP. These were observed in the overall, Caucasians and statistically powered comparisons which exhibited consistent significance, stability, robustness, precision and lack of bias. Our central findings rest on association of the Gly allele with endurance and power, differentially favoring the latter over the former.

The zinc transporter Slc39a5 controls glucose sensing and insulin secretion in pancreatic β-cells via Sirt1- and Pgc-1α-mediated regulation of Glut2

Zinc levels are high in pancreatic β-cells, and zinc is involved in the synthesis, processing and secretion of insulin in these cells. However, precisely how cellular zinc homeostasis is regulated in pancreatic β-cells is poorly understood. By screening the expression of 14 Slc39a metal importer family member genes, we found that the zinc transporter Slc39a5 is significantly down-regulated in pancreatic β-cells in diabetic db/db mice, obese ob/ob mice and high-fat diet-fed mice. Moreover, β-cell-specific Slc39a5 knockout mice have impaired insulin secretion. In addition, Slc39a5-deficient pancreatic islets have reduced glucose tolerance accompanied by reduced expression of Pgc-1α and its downstream target gene Glut2. The down-regulation of Glut2 in Slc39a5-deficient islets was rescued using agonists of Sirt1, Pgc-1α and Ppar-γ. At the mechanistic level, we found that Slc39a5-mediated zinc influx induces Glut2 expression via Sirt1-mediated Pgc-1α activation. These findings suggest that Slc39a5 may serve as a possible therapeutic target for diabetes-related conditions.

Relationship of PPARG, PPARGC1A, and PPARGC1B polymorphisms with susceptibility to hepatocellular carcinoma in an eastern Chinese Han population

Background

PPARG, PPARGC1A, and PPARGC1B polymorphisms may be implicated in the development of cancer.

Participants and methods

In this study, we selected PPARG rs1801282 C>G and rs3856806 C>T, PPARGC1A rs2970847 C>T, and PPARGC1B rs7732671 G>C and rs17572019 G>A single-nucleotide polymorphisms to explore the relationship between these polymorphisms and hepatocellular carcinoma (HCC) risk. A total of 584 HCC patients and 923 controls were enrolled.

Results

We found that PPARG rs1801282 C>G polymorphism was correlated with a decreased susceptibility of HCC (CG vs CC, adjusted OR 0.47, 95% CI 0.27-0.82, P=0.007; CG/GG vs CC, adjusted OR 0.52, 95% CI 0.31-0.88, P=0.015). However, PPARG rs3856806 C>T polymorphism was a risk factor for HCC (TT vs CC, adjusted OR 2.33, 95% CI 1.25-4.36, P=0.008; TT vs CT/CC, adjusted OR 2.26, 95% CI 1.22-4.17, P=0.010). In a subgroup analysis by chronic hepatitis B virus (HBV)-infection status, age, sex, alcohol use, and smoking status, a significant association between PPARG rs1801282 C>G polymorphism and a decreased risk of HCC in male, ≥53 years, never-smoking, never-drinking, and nonchronic HBV-infection-status subgroups was found. However, we found PPARG rs3856806 C>T polymorphism increased the risk of HCC in never-smoking, never-drinking, and nonchronic HBV-infection-status subgroups. Haplotype-comparison analysis indicated that C_rs1801282T_rs3856806C_rs2970847G_rs7732671G_rs17572019, C_rs1801282T_rs3856806T_rs2970847G_rs7732671G_rs17572019, and C_rs1801282C_rs3856806C_rs2970847C_rs7732671A_rs17572019 haplotypes increased the risk of HCC. PPARG C_rs1801282T_rs3856806 and G_rs1801282C_rs3856806 haplotypes also influenced the risk of HCC.

Conclusion

In conclusion, our findings suggest PPARG polymorphisms may influence the susceptibility of HCC. The PPARG, PPARGC1A, and PPARGC1B haplotypes might be associated with HCC risk.

Transcriptional regulation of metabolism in disease: From transcription factors to epigenetics

Every cell in an individual has largely the same genomic sequence and yet cells in different tissues can present widely different phenotypes. This variation arises because each cell expresses a specific subset of genomic instructions. Control over which instructions, or genes, are expressed is largely controlled by transcriptional regulatory pathways. Each cell must assimilate a huge amount of environmental input, and thus it is of no surprise that transcription is regulated by many intertwining mechanisms. This large regulatory landscape means there are ample possibilities for problems to arise, which in a medical context means the development of disease states. Metabolism within the cell, and more broadly, affects and is affected by transcriptional regulation. Metabolism can therefore contribute to improper transcriptional programming, or pathogenic metabolism can be the result of transcriptional dysregulation. Here, we discuss the established and emerging mechanisms for controling transcription and how they affect metabolism in the context of pathogenesis. Cis- and trans-regulatory elements, microRNA and epigenetic mechanisms such as DNA and histone methylation, all have input into what genes are transcribed. Each has also been implicated in diseases such as metabolic syndrome, various forms of diabetes, and cancer. In this review, we discuss the current understanding of these areas and highlight some natural models that may inspire future therapeutics.

NFE2L2, PPARGC1α, and pesticides and Parkinson's disease risk and progression

OBJECTIVE

To investigate three expression-altering NFE2L2 SNPs and four PPARGC1α previously implicated SNPs and pesticides on Parkinson's disease (PD) risk and symptom progression.

METHODS

In 472 PD patients and 532 population-based controls, we examined variants and their interactions with maneb and paraquat (MB/PQ) pesticide exposure on PD onset (logistic regression) and progression of motor symptoms and cognitive decline (n = 192; linear repeated measures).

RESULTS

NFE2L2 rs6721961 T allele was associated with a reduced risk of PD (OR = 0.70, 95% CI = 0.53, 0.94) and slower cognitive decline (β = 0.095; p = 0.0004). None of the PPARGC1α SNPs were marginally associated with PD risk. We estimate statistical interactions between MB/PQ and PPARGC1α rs6821591 (interaction p = 0.009) and rs8192678 (interaction p = 0.05), such that those with high exposure and the variant allele were at an increased risk of PD (OR ≥ 1.30, p ≤ 0.05). PPARGC1α rs6821591 was also associated with faster motor symptom progression as measured with the UPDRS-III (β = 0.234; p = 0.001).

CONCLUSION

Our study provides support for the involvement of both NFE2L2 and PPARGC1α in PD susceptibility and progression, marginally and through pathways involving MB/PQ exposure.

PPARGC1A rs3736265 G>A polymorphism is associated with decreased risk of type 2 diabetes mellitus and fasting plasma glucose level

It has been reported that peroxisome proliferator-activated receptor gamma (PPARG) and peroxisome proliferator-activated receptor gamma co-activator 1 (PPARGC1) family (e.g. PPARGC1A and PPARGC1B) are key agents in the development and pathophysiology of type 2 diabetes mellitus (T2DM). In this study, we designed a case-control study and selected PPARG rs1801282 C>G, PPARG rs3856806 C>T, PPARGC1A rs8192678 C>T, PPARGC1A rs2970847 C>T, PPARGC1A rs3736265 G>A, PPARGC1B rs7732671 G>C and PPARGC1B rs17572019 G>A polymorphisms to assess the relationship between these polymorphisms and T2DM using the SNPscan method. A total of 502 T2DM patients and 784 non-diabetic controls were enrolled. We found that PPARGC1A rs3736265 G>A polymorphism was correlated with a borderline decreased susceptibility of T2DM. In a subgroup analysis by age, sex, alcohol use, smoking status and body mass index, a significantly decreased risk of T2DM in <65 years and female groups was found. Haplotype comparison analysis indicated that CTTCGGG and CTCTGGG haplotypes with the order of PPARG rs1801282 C>G, PPARG rs3856806 C>T, PPARGC1A rs8192678 C>T, PPARGC1A rs2970847 C>T, PPARGC1A rs3736265 G>A, PPARGC1B rs7732671 G>C and PPARGC1B rs17572019 G>A polymorphisms in gene position significantly increased the risk of T2DM. However, CCCCACA haplotype conferred a decreased risk to T2DM. We also found that PPARGC1A rs3736265 A allele decreased the level of fasting plasma glucose (FPG), while increased the level of Triglyceride. In conclusion, Our findings suggest that variants of PPARGC1A rs3736265 G>A polymorphism decrease the level of FPG, improving the expectation of study in individual's prevention strategies to T2DM.

Linking Metabolic Disease With the PGC-1α Gly482Ser Polymorphism

Peroxisome proliferator-activated receptor γ coactivator 1-α (PGC-1α) is a highly conserved transcriptional coactivator enriched in metabolically active tissues including liver, adipose, pancreas, and muscle. It plays a role in regulating whole body energy metabolism and its deregulation has been implicated in type 2 diabetes (T2D). A single nucleotide variant of the PPARGC1A gene (rs8192678) is associated with T2D susceptibility, relative risk of obesity and insulin resistance, and lower indices of β cell function. This common polymorphism is within a highly conserved region of the bioactive protein and leads to a single amino acid substitution (glycine 482 to serine). Its prevalence and effects on metabolic parameters appear to vary depending on factors including ethnicity and sex, suggesting important interactions between genetics and cultural/environmental factors and associated disease risk. Interestingly, carriers of the serine allele respond better to some T2D interventions, illustrating the importance of understanding functional impacts of genetic variance on PGC-1α when targeting this pathway for personalized medicine. This review summarizes a growing body of literature surrounding possible links between the PGC-1α Gly482Ser single nucleotide polymorphism and diabetes, with focus on key clinical findings, affected metabolic systems, potential molecular mechanisms, and the influence of geographical or ethnic background on associated risk.

Haplotype-based interaction of the PPARGC1A and UCP1 genes is associated with impaired fasting glucose or type 2 diabetes mellitus

The aim of this study is to evaluate the effect of single-nucleotide polymorphisms (SNPs) of the PPARGC1A and UCP1 genes on impaired fasting glucose (IFG) or type 2 diabetes mellitus (T2DM) and the haplotype-based interaction between these genes.A cross-sectional study was conducted by cluster sampling in Henan province, China. Based on the level of fasting plasma glucose (FPG) and the history of T2DM, the participants were divided into 2 groups; 83 individuals were in the IFG+DM group (those with IFG or T2DM) and 445 individuals were in the NFPG group (those with normal FPG). Kernel canonical correlation analysis (KCCA), a haplotype-based gene-gene interaction method, which can increase the biological interpretability and extract nonlinear characteristics of SNPs, was used to analyze the correlation and interaction between PPARGC1A and UCP1 genes.The age, BMI, total cholesterol and triglycerides were statistically different between 2 groups (P ≤ .001). Haplotype analysis showed no significant difference in frequency distribution between the 2 groups when the PPARGC1A or UCP1 gene was tested (P > .05). KCCA analysis showed that the maximum kernel canonical correlation coefficient of the PPARGC1A and UCP1 genes was 0.9977 and 0.9995 in the IFG+DM and NPFG groups, respectively. A haplotype-based gene-gene interaction was observed significantly (U = -6.28, P < .001), indicating the possibility of an interaction between haplotype AAG of the PPARGC1A gene and haplotypes CTCG (odds ratio [OR] = 1.745, 95% confidence interval [95% CI] 1.069-2.847) and CTCA (OR = 0.239, 95% CI 0.060-0.958) of the UCP1 gene.Haplotype-based interaction between the PPARGC1A and UCP1 genes is associated with IFG or T2DM among residents in Henan, China.

THE PPARGC1A - GLY482SER POLYMORPHISM (RS8192678) AND THE METABOLIC SYNDROME IN A CENTRAL ROMANIAN POPULATION

Background

The peroxisome proliferator-activated receptor-γ co-activator 1-α (PPARGC1A), a key transcription factor involved in the control of metabolism and energy homeostasis, is an important biological and positional candidate of the metabolic syndrome. Association studies of its polymorphisms, however, yielded inconsistent sometimes conflicting results, pointing to important ethnic differences, which call for replication in various populations.

Objective

In order to study its most common - potentially functional - polymorphism Gly482Ser (rs8192678), we carried out a case-control study in a central Romanian population.

Material and methods

Two hundred and ninety six patients affected by the metabolic syndrome diagnosed according to the International Diabetes Federation proposed criteria and 166 middle-aged control subjects have been investigated. Genotyping was done by PCR-RFLP, using the restriction enzyme MspI.

Results

While the G(Gly)/A(Ser) allele frequencies (66.89/33.11 vs. 71.68/28.31 %) and GG/GA/AA genotype distribution (45.27-43.24-11.48 vs. 54.21-34.93-10.84 %) differed in the metabolic syndrome and control group, the risk of developing the metabolic syndrome did not reach the limit of statistical significance (OR=1.43; p=0.06, CI 95%: 0.97-2.09). Metabolic parameters in the two study groups did not show significant differences according to the genotype (p>0.05).

Conclusion

rs8192678 could be a functional polymorphism contributing to the development of the metabolic syndrome, but probably its effect is minor, and might depend on gene-gene and gene-environment interactions. Clarification of very small effects would require larger sample sizes.

The Gly482Ser polymorphism of the peroxisome proliferator-activated receptor-γ coactivator-1α (PGC-1α) is associated with type 2 diabetes in Tunisian population

BACKGROUND AND AIMS

Peroxisome proliferator-activated receptor-γ co-activator-1α (PGC-1α) is a transcriptional co-activator involved in adaptive thermogenesis, skeletal muscle metabolism, fatty acid oxidation, and gluconeogenesis. Several studies have suggested that the common PGC-1α polymorphism Gly482Ser (rs8192678) may be associated with risk of type 2 diabetes (T2D), with conflicting results. The aim of this study was to analyze whether the Gly482Ser variant is a risk factor for development of T2D in Tunisian population.

METHODS

In a case-control study 487 unrelated patients with type 2 diabetes and 402 apparently healthy controls were recruited from January 2008 to August 2010. The Gly482Ser polymorphism was determined by PCR-RFLP analysis.

RESULTS

A significant difference in genotypes distribution was observed between patients (Gly/Gly: 34.1%; Gly/Ser: 47.1%; Ser/Ser: 18.5%) and controls (Gly/Gly: 43.8%; Gly/Ser: 42.3%; Ser/Ser: 13.9%) (χ(2)=9.44, p=0.009). The T2D patient group showed a significant higher frequency of the Ser allele compared to the controls (43% vs. 34%; OR: 1.35, 95% [CI]: 1.11-1.65, p=0.002). The association between the Gly482Ser polymorphism and T2D remained significant after adjustment for other well-established cardiovascular risk factors.

CONCLUSIONS

In the current study, a significant and independent association between the Gly482Ser polymorphism (rs8192678) of the PGC-1α gene and T2D in the Tunisian population was found.

PGC-1 coactivators in β-cells regulate lipid metabolism and are essential for insulin secretion coupled to fatty acids

Objectives

Peroxisome proliferator-activated receptor γ coactivator 1 (PPARGCA1, PGC-1) transcriptional coactivators control gene programs important for nutrient metabolism. Islets of type 2 diabetic subjects have reduced PGC-1α expression and this is associated with decreased insulin secretion, yet little is known about why this occurs or what role it plays in the development of diabetes. Our goal was to delineate the role and importance of PGC-1 proteins to β-cell function and energy homeostasis.

Methods

We investigated how nutrient signals regulate coactivator expression in islets and the metabolic consequences of reduced PGC-1α and PGC-1β in primary and cultured β-cells. Mice with inducible β-cell specific double knockout of Pgc-1α/Pgc-1β (βPgc-1 KO) were created to determine the physiological impact of reduced Pgc1 expression on glucose homeostasis.

Results

Pgc-1α and Pgc-1β expression was increased in primary mouse and human islets by acute glucose and palmitate exposure. Surprisingly, PGC-1 proteins were dispensable for the maintenance of mitochondrial mass, gene expression, and oxygen consumption in response to glucose in adult β-cells. However, islets and mice with an inducible, β-cell-specific PGC-1 knockout had decreased insulin secretion due in large part to loss of the potentiating effect of fatty acids. Consistent with an essential role for PGC-1 in lipid metabolism, β-cells with reduced PGC-1s accumulated acyl-glycerols and PGC-1s controlled expression of key enzymes in lipolysis and the glycerolipid/free fatty acid cycle.

Conclusions

These data highlight the importance of PGC-1s in coupling β-cell lipid metabolism to promote efficient insulin secretion.

•

Loss of Pgc-1s in adult β-cells decreases insulin secretion in response to glucose/palmitate.

•

Pgc-1α/β is not required to maintain basal mitochondrial mass or oxidative capacity in mature β-cells.

•

Pgc-1α/β regulates expression of the lipolytic enzymes HSL and ATGL in β-cells.

•

Reduced β-cell Pgc-1 causes accumulation of intracellular acyl-glycerols and cholesterol esters.

Association between PGC-1alpha gene polymorphisms and type 2 diabetes risk: a case-control study of an Iranian population

OBJECTIVE

The peroxisome proliferator-activated receptor gamma coactivator-1alpha (PGC-1alpha) gene could play a role in the onset of type 2 diabetes mellitus. The aim of this study was to explore the possible associations among polymorphisms Gly482Ser, Thr394Thr and Thr528Thr of the PGC-1alpha gene and the risk of type 2 diabetes in Kurdish-Iranians.

METHODS

DNA specimens from all 173 type 2 diabetes subjects and 173 normoglycemic subjects were genotyped by the polymerase chain reaction-restriction fragment length polymorphism method. Genotypic and allelic frequencies were analyzed in each group. Serum lipids, fasting glucose, fasting serum insulin, homeostasis model assessment of insulin resistance and glycated hemoglobin levels were determined using the conventional methods. The data were analyzed using SPSS software.

RESULTS

The GA genotype of Gly482Ser was associated with a significant susceptibility for type 2 diabetes (odds ratio 5.23, p<0.000). Furthermore, the GA genotype of Thr528Thr had a higher risk for type 2 diabetes (odds ratio 2.37, p<0.002). Normoglycemic persons carrying the GA+AA genotypes of Gly482Ser variation had significantly lower high-density lipoprotein cholesterol in comparison with persons having GG genotype. In comparison with GG genotype carriers, normoglycemic subjects carrying the GA+AA genotypes of Thr394Thr variation had significantly higher fasting blood sugar, fasting serum insulin and homeostasis model assessment of insulin resistance. Normoglycemic subjects with the GA+AA genotypes of Thr528Thr variation had significantly higher levels of low-density lipoprotein cholesterol compared with subjects having the GG genotype. Type 2 diabetes subjects carrying the GA+AA genotypes of this polymorphism had significantly higher waist-hip ratio in comparison with the GG genotype carriers. We also found that haplotype 394-GG/482-GA/528-GG of PGC-1alpha was significantly associated with higher risk of type 2 diabetes.

CONCLUSIONS

Our findings revealed significant associations between PGC-1alpha Gly482Ser and Thr528Thr polymorphisms and type 2 diabetes in Kurdish-Iranians.

Impact of the PPARGC1A Gly482Ser polymorphism on left ventricular structural and functional abnormalities in patients with hypertension

The Gly482Ser polymorphism in the peroxisome proliferator-activated receptor gamma coactivator-1α (PPARGC1A) has been reported to contribute to the development of left ventricular (LV) hypertrophy. Little is known, however, about its possible impact on cardiac dysfunction. Enhanced myocardial fibrosis accompanying increased LV mass might represent a link with coexisting functional abnormalities. We investigated the association between the PPARGC1A Gly482Ser polymorphism and LV morphology and performance in essential hypertension, with special consideration of fibrosis intensity. A total of 205 hypertensive patients (60±8 years) underwent echocardiography with assessment of cardiac morphology, LV systolic (strain and strain rate) and diastolic function (peak early diastolic mitral flow velocity/peak late diastolic mitral flow velocity (E/A) ratio, peak early diastolic myocardial velocity (Em), and E/e' ratio (where e' is the peak early diastolic mitral annular velocity)), evaluation of serum procollagen type III amino-terminal propeptide (PIIINP) and procollagen type I carboxy-terminal propeptide (PICP)-markers of fibrosis and the PPARGC1A Gly482Ser genotyping. Subjects with the Ser-Ser genotype demonstrated more profound LV hypertrophy and diastolic function impairment, and higher PICP/PIIINP than the Ser-Gly and Gly-Gly groups. In multivariable analysis, the presence of the Ser-Ser allele was an independent correlate of E/e' (β=0.17, P<0.02), Em (β=-0.18, P<0.01) and LV mass index (β=0.28, P<0.001). In conclusion, in hypertensive patients, the PPARGC1A Gly482Ser polymorphism is associated with LV hypertrophy and diastolic dysfunction, with the presence of the Ser-Ser allele promoting these abnormalities. One of the possible mechanisms mediating the adverse effect on diastolic performance might be a relative increase in the anabolism of rigid collagen type I over that of the more elastic collagen type III, as indicated by an increased ratio of PICP to PIIINP.

Glutathione peroxidase mimic ebselen improves glucose-stimulated insulin secretion in murine islets

AIMS

Glutathione peroxidase (GPX) mimic ebselen and superoxide dismutase (SOD) mimic copper diisopropylsalicylate (CuDIPs) were used to rescue impaired glucose-stimulated insulin secretion (GSIS) in islets of GPX1 and(or) SOD1-knockout mice.

RESULTS

Ebselen improved GSIS in islets of all four tested genotypes. The rescue in the GPX1 knockout resulted from a coordinated transcriptional regulation of four key GSIS regulators and was mediated by the peroxisome proliferator-activated receptor gamma coactivator 1 alpha (PGC-1α)-mediated signaling pathways. In contrast, CuDIPs improved GSIS only in the SOD1 knockout and suppressed gene expression of the PGC-1α pathway.

INNOVATION

Islets from the GPX1 and(or) SOD1 knockout mice provided metabolically controlled intracellular hydrogen peroxide (H2O2) and superoxide conditions for the present study to avoid confounding effects. Bioinformatics analyses of gene promoters and expression profiles guided the search for upstream signaling pathways to link the ebselen-initiated H2O2 scavenging to downstream key events of GSIS. The RNA interference was applied to prove PGC-1α as the main mediator for that link.

CONCLUSION

Our study revealed a novel metabolic use and clinical potential of ebselen in rescuing GSIS in the GPX1-deficient islets and mice, along with distinct differences between the GPX and SOD mimics in this regard. These findings highlight the necessities and opportunities of discretional applications of various antioxidant enzyme mimics in treating insulin secretion disorders. REBOUND TRACK: This work was rejected during standard peer review and rescued by Rebound Peer Review (Antioxid Redox Signal 16: 293-296, 2012) with the following serving as open reviewers: Regina Brigelius-Flohe, Vadim Gladyshev, Dexing Hou, and Holger Steinbrenner.

Association and interaction analysis of PPARGC1A and serum uric acid on type 2 diabetes mellitus in Chinese Han population

BACKGROUND

Peroxisome proliferator-activated receptor gamma coactivator-1α (PPARGC1A/ PGC-1α) is a ligand-activated transcription factor belonging to the nuclear hormone receptor superfamily. The activity of PGC-1α or genetic variations in the gene encoding the enzyme may contribute to individual variations in mitochondrial function and insulin resistance or diabetes. The objective of this study was to assess the extent to which PPARGC1A (rs8192678) and serum uric acid (UA) and its interaction impact on T2DM susceptibility in Chinese Han population.

METHOD

We conducted a study in a cohort that included 1166 T2DM patients and 1135 controls, and was genotyped for the presence of the PPARGC1A rs8192678 polymorphisms. Genotyping was performed by iPLEX technology. The association between rs8192678 or UA and T2DM was assessed by univariate and multivariate logistic regression (MLR) analysis controlling for confounders. The interaction between rs8192678 and UA for T2DM susceptibility was also assessed by MLR analysis.

RESULTS

The generalized linear regression analysis failed to show an association between the PPARGC1A rs8192678 polymorphisms and T2DM. Interestingly, the present study provided data suggesting that the minor A-allele of PPARGC1A (rs8192678) had a protective effect against T2DM in subjects with higher level of UA (ORint =1.50 95% CI: 1.06-2.12 for allele and P = 0.02, ORint =1.63 95% CI: 1.17-2.26 for genotype and P = 0.004).

CONCLUSION

The combination of higher level of UA and PPARGC1A (rs8192678) was an independent predictor for T2DM.

Polymorphisms in PPAR Genes (PPARD, PPARG, and PPARGC1A) and the Risk of Chronic Kidney Disease in Japanese: Cross-Sectional Data from the J-MICC Study

Chronic kidney disease (CKD) is well known as a strong risk factor for both end stage renal disease and cardiovascular disease. To clarify the association of polymorphisms in the PPAR genes (PPARD, PPARG, and PPARGC1A) with the risk of CKD in Japanese, we examined this association among the Japanese subjects using the cross-sectional data of J-MICC (Japan Multi-Institutional Collaborative Cohort) Study. The subjects for this analysis were 3,285 men and women, aged 35–69 years, selected from J-MICC Study participants; genotyping was conducted by multiplex polymerase chain reaction-based Invader assay. The prevalence of CKD was determined for CKD stages 3–5 (defined as eGFR < 60 ml/min/1.73 m²). Participants with CKD accounted for 17.3% of the study population. When those with PPARD T-842C T/T were defined as reference, those with PPARD T-842C T/C and C/C demonstrated the OR for CKD of 1.26 (95%CI 1.04–1.53) and 1.31 (95%CI 0.83–2.06), respectively. There were no significant associations between the polymorphisms in other PPAR genes and the risk of CKD. The present study found a significantly increased risk of CKD in those with the C allele of PPARD T-842C, which may suggest the possibility of personalized risk estimation of this life-limiting disease in the near future.

The role of genetic variants in CYP2C8, LPIN1, PPARGC1A and PPARγ on the trough steady-state plasma concentrations of rosiglitazone and on glycosylated haemoglobin A1c in type 2 diabetes

OBJECTIVE

The aim of this study was to examine the effect of single nucleotide polymorphisms in CYP2C8, LPIN1, PPARGC1A and PPARγ on rosiglitazone's (i) trough steady-state plasma concentration (C(ss,min)), (ii) on glycosylated haemoglobin A1c (HbA1c) and (iii) the risk of developing adverse events, mainly oedema, in patients with type 2 diabetes mellitus (T2D).

METHODS

The data used in this study were obtained from the South Danish Diabetes Study including 371 T2D patients with a focus on the 187 patients who were treated with rosiglitazone. The study was a placebo-controlled, partly blinded and multicentre clinical trial. The C(ss,min) of rosiglitazone and HbA1c was determined and the genotype of the patients was identified.

RESULTS

The mean C(ss,min) of rosiglitazone was 21.3 ng/ml (95% confidence interval 18.8; 24.2 ng/ml), with observations ranging from 1 to 296 ng/ml. Carriers of CYP2C8*3 (n=32) (rs10509681 and rs11572080) had a statistically significantly lower mean C(ss,min) than wild types (n=106), and they also had a statistically significantly lower mean absolute difference in HbA1c during rosiglitazone treatment. Finally, the carriers of CYP2C8*3 had a lower odds ratio of developing oedema.

CONCLUSION

We showed that CYP2C8*3 was associated with lower plasma levels of rosiglitazone and hence a reduced therapeutic response but also a lower risk of developing oedema during treatment with rosiglitazone. Individualized treatment with rosiglitazone on the basis of the CYP2C8 genotype may therefore be possible.

Genome-wide association analyses suggest NELL1 influences adverse metabolic response to HCTZ in African Americans

Hydrochlorothiazide (HCTZ) is one of the most widely prescribed antihypertensive medications. Although it is well known that HCTZ is associated with hyperglycemia and hypertriglyceridemia, the mechanisms underlying these adverse effects are not well understood. We performed a genome-wide association study and meta-analysis of the change in fasting plasma glucose and triglycerides in response to HCTZ from two different clinical trials: the Pharmacogenomic Evaluation of Antihypertensive Responses and the Genetic Epidemiology of Responses to Antihypertensive studies. Two single-nucleotide polymorphisms (rs12279250 and rs4319515 (r²=0.73)), located at 11p15.1 in the NELL1 gene, achieved genome-wide significance for association with change in fasting plasma triglycerides in African Americans, whereby each variant allele was associated with a 28 mg dl⁻¹ increase in the change in triglycerides. NELL1 encodes a cytoplasmic protein that contains epidermal growth factor-like repeats and has been shown to represses adipogenic differentiation. These findings may represent a novel mechanism underlying HCTZ-induced adverse metabolic effects.

Influence of SNPs in nutrient-sensitive candidate genes and gene–diet interactions on blood lipids: the DiOGenes study

Blood lipid response to a given dietary intervention could be determined by the effect of diet, gene variants or gene–diet interactions. The objective of the present study was to investigate whether variants in presumed nutrient-sensitive genes involved in lipid metabolism modified lipid profile after weight loss and in response to a given diet, among overweight European adults participating in the Diet Obesity and Genes study. By multiple linear regressions, 240 SNPs in twenty-four candidate genes were investigated for SNP main and SNP–diet interaction effects on total cholesterol, LDL-cholesterol, HDL-cholesterol and TAG after an 8-week low-energy diet (only main effect), and a 6-monthad libitumweight maintenance diet, with different contents of dietary protein or glycaemic index. After adjusting for multiple testing, a SNP–dietary protein interaction effect on TAG was identified for lipin 1 (LPIN1) rs4315495, with a decrease in TAG of − 0·26 mmol/l per A-allele/protein unit (95 % CI − 0·38, − 0·14,P= 0·000043). In conclusion, we investigated SNP–diet interactions for blood lipid profiles for 240 SNPs in twenty-four candidate genes, selected for their involvement in lipid metabolism pathways, and identified one significant interaction betweenLPIN1rs4315495 and dietary protein for TAG concentration.

Quantitative assessment of the associations between four polymorphisms (FokI, ApaI, BsmI, TaqI) of vitamin D receptor gene and risk of diabetes mellitus

The vitamin D receptor (VDR) gene polymorphisms have been suggested to be involved in the development of diabetes mellitus, including type 1 diabetes (T1DM) and type 2 diabetes (T2DM). However, the results have been inconsistent. In this study, we performed a meta-analysis to investigate the associations. Literature was retrieved from PubMed, ISI Web of Science and Chinese databases. Pooled odds ratios (ORs) with 95 % confidence intervals (CIs) were calculated using a random or fixed effect model. 79 studies (FokI: 22 studies; BsmI: 25 studies; ApaI: 17 studies; TaqI: 15 studies) on T1DM and 44 studies (FokI: 10 studies; BsmI: 10 studies; ApaI: 14 studies; TaqI: 10 studies) on T2DM were included. The results indicated that BsmI polymorphism was associated with an increased risk of T1DM (B vs. b: OR 1.31, 95 % CI 1.10-1.55, P = 0.002), especially in East Asians (B vs. b: OR 2.57, 95 % CI: 1.55-4.24, P < 0.001); FokI polymorphism was associated with an increased risk of T2DM (f vs. F: OR 1.30, 95 % CI: 1.17-1.45, P < 0.001), especially in East Asians (f vs. F: OR 1.36, 95 % CI: 1.21-1.54, P < 0.001). However, no significant association was observed between ApaI or TaqI polymorphism and diabetes risk with the exception of significant association between ApaI polymorphism and T1DM risk in East Asians. Thus, the authors found BsmI polymorphism in the VDR gene may increase the risk of T1DM in East Asians and the FokI polymorphism may increase the risk of T2DM in East Asians.

Associations between polymorphisms in genes involved in fatty acid metabolism and dietary fat intakes

BACKGROUND

Obesity prevalence is growing in our population. Twin studies have estimated the heritability of dietary intakes to about 30%. The objective of this study was to verify whether polymorphisms in genes involved in fatty acid metabolism are associated with dietary fat intakes.

METHODS

Seven hundred participants were recruited. A validated food frequency questionnaire was used to assess dietary intakes. PCR-RFLP and TAQMAN methodology were used to genotype PPARα Leu162Val, PPARγ Pro12Ala, PPARδ -87T>C, PPARGC1α Gly482Ser, FASN Val1483Ile and SREBF1 c.*619C>G. Statistical analyses were executed with SAS statistical package.

RESULTS

Carriers of the Ala12 allele of PPARγ Pro12Ala polymorphism had higher intakes of total fat (p = 0.04). For FASN Val1483Ile polymorphism, significant gene-sex interaction effects were found for total fat and saturated fat intakes (p = 0.02 and p = 0.002, respectively). No significant difference in fat intakes was observed for PPARα Leu162Val, PPARδ -87T>C, PPARGC1α Gly482Ser and SREBF1 c.*619C>G polymorphisms.

CONCLUSIONS

Polymorphisms in PPARγ and FASN seem to be associated with dietary fat intakes. Genetic variants are important to take into account when studying dietary intakes.