Uzma Zafar  ( Department of Physiology & Cell Biology, University of Health Sciences, Lahore )
Saba Khaliq  ( Department of Physiology & Cell Biology, University of Health Sciences, Lahore )
Hafiz Usman Ahmad  ( Department of Physiology & Cell Biology, University of Health Sciences, Lahore )
Khalid Pervaiz Lone  ( Department of Physiology & Cell Biology, University of Health Sciences, Lahore )

Objective: To determine the frequency of 34 Cytosine >Guanine (proline 12 alanine) variant of peroxisome proliferator activated receptor gamma, and to associate it with metabolic syndrome, insulin resistance and anthropometric obesity parameters.

Methods: The cross-sectional comparative study was conducted at the University of Health Sciences, Lahore, Pakistan, from September 2016 to 2017, and comprised patients of metabolic syndrome and healthy controls. Blood pressure and anthropometric measurements of all the subjects were recorded. Fasting blood sample of 4ml was taken for biochemical parameter and deoxyribonucleic acid extraction. The frequency of genetic variant was determined by amplification refractory mutation system polymerase chain reaction. Data was analysed using SPSS 22.

Results: Out of 400 subjects, 200 (50%) each were patients and controls. Overall, there were 308 (77%) males and 92 (23%) females. Patients had significantly higher blood pressure, body mass index, waist circumference, waist-to-hip ratio, mid-arm circumference and triceps skinfold thickness compared to the controls (p<0.0001). Insulin resistance was also significantly higher in the patients (p<0.0001) and showed significant correlation with body mass index, waist circumference, waist-to-hip ratio, mid-arm circumference and triceps skinfold thickness (p<0.05).Waist circumference and triceps skinfold thickness were significant predictors of homeostatic model assessment for insulin resistance. Overall, the frequency of homozygous dominant genotype CC of PPAR2 34C>G was 291 (72.75%), heterozygous CG was 93 (23.25%) and homozygous recessive GG was 16 (4%).There was no significant difference in frequency of genotypes between the groups (p=0.216). However, waist circumference and body mass index were significantly lower in GG genotype compared to the CC (p=0.006 versus p=0.02).

Conclusion: Waist circumference and triceps skinfold thickness were found to be the significant predictors of homeostatic model assessment for insulin resistance, while no association was found between 34 C>G variant of peroxisome proliferator activated receptor gamma and metabolic syndrome.
Keywords: PPAR, Proline 12 alanine, Polymorphism, Metabolic
syndrome. (JPMA 69: 1259; 2019)

Introduction

Metabolic syndrome (MetS) is a clustering of clinical and biochemical abnormalities including central obesity, hypertension (HTN), hyperglycaemia and impaired lipid profile. All these metabolic derangements lead to type 2 diabetes mell it us ( T 2DM), he patic-stea tos is, atherogenicity and inflammatory states.¹ MetS is a major public health issue with a 35-50% worldwide prevalence. ²  Its pathogenesis is multifactorial involving an interplay of genetic and environmental factors. Impedance to insulin action is a core defect in this entity and is the reason for the name insulin resistance syndrome (IRS). ³  Genetic studies have reported the association of various susceptibility genes with MetS. ⁴  One of the candidate genes, peroxisome proliferator activated receptor gamma (PPAR) is a transcription factor and belongs to the class of nuclear receptor superfamily. Alternate splicing of PPAR results in three functional isoforms 1, 2 and 3, differing in their tissue distribution;PPAR2 dominates in adipocytes, while others have widespread tissue expression. PPAR isoforms have three domains; deoxyribonucleic acid (DNA) binding, ligand-activated, and ligand-independent domain. PPAR2 on heterodimerization with Retinoid X Receptor is involved intranscription of multiple genes involved in lipolysis, lipogenesis, insulin sensitivity and tissue metabolism.5 PPAR2 is also a target of drug class thiazolidinediones which are insulin sensitizers. These transcription factors on ligand activation improve insulin sensitivity by upregulating adiponectin and Glucose transporter type 4(GLUT4) expression, and suppressing tumour necrosis factor-alpha (TNF) and interleukin-6 (IL6) production. PPAR gene is located on chromosome 3p25, extending over 100Kb of genomic DNA and consisting of 9 exons. A missense mutation 34CCA>GCA (rs1801282) at exon 2 of PPAR2 gene results in proline12 alanine substitution. This amino acid change is as sociated with a conformational change in protein structure and altered transcriptional activity of this nuclear receptor.^5,6 PPAR2 is a highly addressed, insulin sensitizing transcription factor and understanding the distribution of its polymorphism and associated factors might help us in early prediction and better therapeutic approach towards MetS. Numerous studies have been conducted to determine the possible association of 34C>GPPAR polymorphism with T2DM and insulin resistance (IR).^7,8 Proline, the wild type allele of PPAR2,showed increased susceptibility to IR traits.^9,10 However, studies conducted on Asian Indians and French population showed that alanine, and not proline, is associated with higher body mass index (BMI), obesity and IR.^11,12 Although this polymorphism has been studied in various populations, its association with IR, T2DM and obesity is still controversial and inconsistent.^7-12 The current study was planned to determine the frequency of PPAR2 34C>G polymorphism in subjects with and without MetS, and to check its association with MetS, IR and selected anthropometric obesity parameters.

Subjects and Methods

The cross-sectional comparative study was conducted at the Department of Physiology and Cell Biology, University of Health Sciences (UHS), Lahore, Pakistan, from September 2016 to 2017, and comprised MetS patients and healthy controls. The sample size was calculated using World Health Organisation (WHO) calculator using the following formula:13 The desired power of the study taken was 90%, level of significance was set at 0.05, proportion of major and minor allele frequency was taken as 0.79 and 0.21 in controls and 0.92 and 0.08 for the cases. ⁹  The subjects were recruited using convenience sampling. Patients of MetS were recruited from the Diabetic Clinic of Sheikh Zayed Hospital, Lahore, as per the International Diabetes Federation (IDF) guidelines.^1,2 All MetS patients having evidence of end-stage renal or liver disease and chronic illness were excluded. Controls matched for age and gender were taken from the general population. For the selection of controls, detailed history was taken regarding T 2DM, HT N drug intake, and clinical examination was also done. Those subjects were selected who were apparently healthy and free of MetS as per IDF guidelines.^1,2 Approval was taken from the institutional review board and informed consent was taken from all the subjects. The weight, height, waist circumference (WC), hip circumference (HC), mid-arm circumference (MAC), triceps skin fold thickness(TSFT) and blood pressure (BP) were recorded by standard methods. Body weight was taken on a standard hospital scale bare footed with minimal clothing. Height was measured by wall-mounted stadiometer. WC was measured by non-stretchable tape midway between iliac crest and lower border of last rib at the end of expiration. MAC was measured midway between acromion and olecranon process at left arm. TSFT was taken by Harpenden caliper over triceps at posterior aspect of arm midway between acromion of scapula and olecranon process of ulna. Body mass index (BMI) was calculated by dividing the weight in kg by height in square meters. Waist-to-hip ratio (WHR) was calculated by dividing WC with HC. ¹⁴  Fasting blood sample of 4 ml was taken from subjects having overnight fast of 8-10 hours to study different biochemical parameters. Blood for DNA extraction was stored at - 80OC and serum was separated and stored at -80OC. Fasting serum glucose and lipid profile, including serum triglyceride (TG), high-density lipoprotein (HDL) and cholesterol were measured by colorimetric method(Randox Kits, United Kingdom). Insulin was measured by human insulin enzyme-linked immunosorbent assay (ELISA) kit (Elabscience, Germany) followed by calculation of insulin resistance(IR ) by homeostatic modelassessment (HOMA-IR). ¹⁵  DNA was extracted using Favor Prep Blood Genomic DNA Extraction Kit (Taiwan, China) according to the manufacturer's guidelines, and the yield was checked by nano drop followed by gel electrophoresis. PPAR genotyping was carried out by amplification refractory mutation system (ARMS-PCR) in25μl reaction mixture containing 2μl (50 ng/μl) of DNA, 2X polumerase chain reaction (PCR) master mixture (Fermetas, USA) and two Forward and two Reverse allelespecific primer sets (Macrogen, Inc. Korea).16 The product was run on 3% agarose gel, the resultant outer PCR product was of 362 bp, product for C allele was 221bp

and G allele was 195bp. Primer sequences used were:

PPPAR inner F-5'-

GAAACTCTGGGAGATTCTCCTATTGTCC -3' (28mer),

PPARG inner R-5'-

GTATCAGTGAAGGAATGGCTTTCAGC-3' (26mer),

PPARG outer

F5'GAAACTGATGTCTTGACTCATGGGTGTA-3' (28mer)

PPARG outer R-5'GCAACGAGCTAAGCATTAAAATACTGGA-3'
(28mer)

Data was analysed using SPSS 22. Normal distribution of the data was checked by Shapiro-Wilk's statistics. Mean ± standard deviation(SD) were given for normally distributed quantitative variables and median with interquartile range (IQR) for non-normally distributed quantitative variables. Student's 't' test and Mann- Whitney U test were applied to compare normally and non-normally distributed quantitative variables between the cases and the controls. Spearman correlation and multiple regression analysis were applied to see the relation between anthropometric parameters and HOMA-IR. Genotypic and allelic frequencies were calculated and Hardy Weinberg equilibrium was determined. ¹⁷  In order to study the frequency and association of polymorphisms with study groups, Co-dominant, Dominant, and Recessive genetic models were constructed. Genotype frequencies of the two groups were compared by chisquare test and odds ratio (OR) was calculated. Allelic frequencies of the two groups were compared by Soft pad graphics. Anthropometric parameters of study population in three genotypes were compared by oneway analysis of variance (ANOVA) and comparison between the two models was done by ' t' test.

Results

Out of 400 subjects, 200(50%) each were patients and controls. Overall, there were 308(77%) males and 92(23%) females. Among the patients, 176(88%) were diabetics, 156(78%) were hypertensive and dyslipidaemia was found in 186(93%) subjects or they were on lipidlowering drugs. The patients had significantly higher BP, BMI, WC, WHR, MAC and TSFT along with serum glucose and insulin levels compared to the controls (p<0.0001 each). IR was also significantly higher in the patients than controls (p<0.0001) (Table 1).



HOMA-IR significantly correlated with anthropometric parameters, including BMI, WC, WHR, MAC and TSFT (p<0.05 each). Multiple regression analysis showed that WC and TSFT were significant predictors of HOMA-IR (Table 2; Figures 1-2).







On comparison of mean values of the two genders in the group of patients, systolic BP (p=0.004), BMI (p=0.015), TSFT (p=0.003) and MAC (p=0.001) were significantly higher in females compared to the males. Among the healthy group, TSFT was significantly higher in females than males (p=0.037). There was no significant difference regarding other measurements between the two genders in controls (p>0.05). HOMA-IR was significantly higher in females than males in the healthy group (p=0.035), while difference between the two was not significant in the patients group (p=0.316). Overall, the frequency of homozygous dominant genotype CC of PPAR2 34C>Gwas 291(72.75%), heterozygous CG was 9 3 ( 2 3 . 2 5%) and homozygous recessive GG was 16 (4%). The frequency of C allele was 675(84.37%) and G was 125(15.63%). Genotype frequencies in cases and controls were in Hardy Weinberg equilibrium(p>0.05). On comparison of allelic, co-dominant (CC: CG: GG), dominant (CC: CG+GG) and recessive models (GG: CC+CG), there was no significant difference in frequency of genotypes between the groups (p>0.05) (Table 3).



On comparison of anthropometric parameters in different genotypes, BMI and WC were significantly lower in GG genotypes compared to the others (Table 4).



Discussion

The study found a significant correlation of HOMA-IR with anthropometric obesity markers, including WC, BMI, WHR, MAC and TSFT. In the MetS group, IR and WC correlation persisted, but was not observed with other obesity parameters, while in the healthy group, correlation was there with all anthropometric parameters. This weaning off can be justified as normal body glucose homeostasis disappears in the diseased group. Most of the patients were on anti-diabetics and lipid-lowering agents, and these might interfere with insulin release, circadian rhythm and glucose homeostasis. ¹⁸  In multiple regression model, among all the co-variates, significant regressers of HOMAIR were WC and TSFT. These two measures of adiposity were best predictors of IR and were found to be superior compared to the others. Studies using magnetic resonance imaging (MRI) and computed tomography (CT ) for measurement of total body fat have also revealed that upper body and central fat are the major contributors of metabolic derangements in IR leading to T2DM and related complications. ¹⁴  As per IDF guidelines, central adiposity is mandatory in the diagnosis of MetS and in Asian Indians, cut-off levels of WC, a predictor of central obesity, are lower compared to Euripides as they are more susceptible to metabolic derangements resulting from abdominal fat accumulation leading to insulin impedance.^1,2 Adiposederived cytokines i.e. TNF, IL6 and adiponectin, establish the connection between central fat and IR by modulating insulin secretion and its action at target areas. ¹⁹  Central adipoc ytes are metabolically more ac tive with preponderance of beta2 receptors, resulting in increased release of free fatty acids in portal venous system, thus creating resistance to insulin action at the level of hepatocytes. ²⁰  When anthropometric parameters were compared on gender basis, females had significantly higher obesity-related measurements than males. These findings were supported by another study in Karachi which depicted significantly higher central obesity and body fat in T2DM females compared to the males. ²¹  Literature on the association of PPAR C>G variant with IR, T2DM and related traits has depicted conflicting relations. Risk allele of PPAR 34C>G (rs1801282) also varies in different ethnic groups.^9-12In this study, PPAR C>G(proline 12 alanine) variant was evaluated and there was no significant association found with MetS. However, BMI and WC were significantly lower in CG/GG genotypes compared to the prevalent CC type of PPAR2. In a previous study on Pakistani diabetics, alanine was found to have a protective role in diabetic retinopathy whereas in another study on Pakistanis with rheumatoid arthritis, the results were contradictory; frequency of GG genotype (alanine) was significantly high in cases compared to controls, and G allele was associated with the disease. ^22,23 In a study, alanine was found to be associated with obesity markers like BMI, central fat and skinfold thickness in obese nondiabetic subjects in Asian Indians. ¹¹  Two large metaanalysis concluded that Caucasians and Chinese with GG (alanine) genotype were more sensitive to insulin than those with CC (proline). Hence, the presence of the minor allele G of PPAR2 34 C>G variant was found to be protective andbeneficial. ^24,25 The transcription factor PPAR2 is highly expressed in adipose tissue and master regulator of energy homeostasis. ²⁶  In this study, BMI and WC were significantly less in GG and CG (minor variants) genotypes of PPAR but the intervening connection between the two is missing i.e. levels of PPAR proteins and messenger ribonucleic acid (mRNA) expression were not checked to see the effect of this missense mutation on their levels.

Conclusion

The 34 C>G variant of PPAR was not found to be associated with MetS, but subjects with CG+GG genotype had significantly lower obesity parameters, including WC and BMI, compared to the CC one. Best anthropometric predictors of HOMA-IR were WC and TSFT. Central and upper body fat reduction is to be emphasised as it might result in improving insulin sensitivity and postpone metabolic derangements resulting from insulin impedance.

Disclaimer: The study is part of a PhD thesis.
Conflict of interest: None.
Source of Funding: None.

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