Neuropeptide Y gene polymorphisms are not associated with ... - Nature

European Journal of Clinical Nutrition (2010) 64, 868–872

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ORIGINAL ARTICLE

Neuropeptide Y gene polymorphisms are not associated with obesity in a South Indian population LVKS Bhaskar1,3, K Thangaraj1, G Pardhasaradhi1, KP Kumar1, L Singh1 and VR Rao2,4 1 Centre for Cellular and Molecular Biology, Hyderabad, India; 2Anthropological Survey of India, Kolkata, India; 3Department of Biomedical Sciences, Sri Ramachandra University, Chennai, India and 4Department of Anthropology, Delhi University, North Campus, Delhi, India

Background/Objectives: Neuropeptide Y (NPY) gene has been shown to have a critical role in the regulation of satiety, reproduction, central endocrine and cardiovascular systems. Among the primary functions associated with NPY are its acute effects on feeding behavior and energy expenditure. The aim of this study is to evaluate the relationship between obesity and NPY gene polymorphisms in a South Indian Population. Subjects/Methods: Three polymorphisms in NPY gene (Leu7Pro, Ser50Ser and A7735G) were analyzed in 263 individuals of an endogamous Kota population. On the basis of body mass index (BMI), they were divided into two groups. Associations were tested using logistic regression and haplotype analyses and linkage disequilibrium (LD). Results: There was no evidence of deviation from Hardy–Weinberg equilibrium. Logistic regression analysis did not reveal significant association with obesity and NPY single-nucleotide polymorphisms (SNPs) in the present study. All three SNPs were in weak LD with low r2 values. Haplotype analysis also did not yield significant association between NPY gene and obesity (global P ¼ 0.756). Conclusions: Our study did not validate the association between previously implicated SNPs in NPY gene and obesity in an Indian population. Population-specific validation of putative associations has far reaching implications for the future personal genomics medicine applications.

European Journal of Clinical Nutrition (2010) 64, 868–872; doi:10.1038/ejcn.2010.74; published online 9 June 2010 Keywords: neuropeptide Y; obesity; Kota population

Introduction Obesity has emerged as a major health problem associated with many metabolic diseases in both developed and developing countries. Although obesity has a genetic etiology, the major causative factor is environmental, mostly related to sedentary lifestyle and causing conservation of energy as body fat (Lev-Ran, 2001; Bell et al., 2005). Body mass index (BMI) correlates with markers of secondary complications of obesity, including current blood pressures, Correspondence: Professor VR Rao, Department of Anthropology, Delhi University, North Campus, Delhi 110 007, India. E-mail: [email protected] Contributors: VRR, KT and LS conceived and designed the study. LVKSB conducted field work, collected blood samples and performed the SNP genotyping and its analysis. KPK and GP participated in SNP genotyping. The paper was written by LVKSB and VRR. In addition, KT and LS actively contributed to discussion of the results of this paper. All authors read and approved the final paper. Received 28 June 2009; revised 10 December 2009; accepted 15 March 2010; published online 9 June 2010

blood lipids and with long-term mortality (Gidding et al., 1995; Whitlock et al., 2009). Although environmental factors such as lifestyle have shown to have a role in obesity, studies carried out on twins and adoption studies show that obesity is a familial trait and a large degree can be ascribed to genetic factors. According to evolutionary models, obesity-causing variants may originally have had an evolutionary benefit, whereas in a modern environment, they pose a risk. Despite a clear genetic cause, the molecular genetic variations underlying common forms of obesity are not clear. Since its discovery in 1982, neuropeptide Y (NPY) receptor has been shown to have a critical role in the regulation of satiety, reproduction, central endocrine and cardiovascular systems (Tatemoto, 1982). Primary among the functions associated with NPY are its acute effects on feeding behavior and energy expenditure. Injection of NPY into mice results in prolonged increases in food and water intake along with the suppression of metabolic rate (Billington et al., 1991; Schwartz et al., 2000). NPY knockout mice surprisingly experience no alterations in feeding behavior, implying a

NPY gene variants and obesity LVKS Bhaskar et al

869 redundancy and/or multistep process in feeding signaling systems (Erickson et al., 1996a). In another study, Erickson et al. (1996b) found that leptin and NPY work synergistically to regulate body fat utilization and storage, as well as hormone release. These findings advocate that the NPY is a prime candidate gene for obesity. The NPY gene is located on chromosome 7q15.1 and is about 8 kb in length with four exons interrupted by three introns of B965, 4300 and 2300 bp in length (Baker et al., 1995). NPY gene produces a precursor protein that includes a signal peptide, mature NPY and a carboxyl terminal flanking peptide (Minth et al., 1984). A functional Leu7Pro polymorphism located in the signal peptide region of the human preproneuropeptide Y (preproNPY) was recently identified (Karvonen et al., 1998). Since then, this polymorphism has been linked to a number of disease conditions, hypertension (Karvonen et al., 2001; Pettersson-Fernholm et al., 2004), increased BMI (Ding et al., 2005; van Rossum et al., 2006), low-density lipoprotein cholesterol (Karvonen et al., 1998; Salminen et al., 2008), serum triglycerides (Karvonen et al., 2000; Pihlajamaki et al., 2003), carotid atherosclerosis (Karvonen et al., 2001) type-I diabetes (Ma et al., 2007) and type-II diabetes (Niskanen et al., 2000; Ukkola and Kesaniemi, 2007). As NPY is a plausible candidate for obesity, we conducted a populationbased case–control study to investigate the association between NPY gene single-nucleotide polymorphisms (SNPs) and obesity. To begin with, we have selected a small population called Kota inhabiting Nilgiri Hills of Tamil Nadu, South India.

TAGAGTGTGCCCTGT-30 ; and primer-II forward: 50 -CCCGG TCATCTTTCACTTCAG-30 , reverse: 50 -GCGAAACGAACCCT GAATCTG-30 , were designed in the intronic regions to amplify exon 2 and exon 4, and to independently amplify 516 and 417 bp PCR products, respectively. All SNPs were analyzed by PCR followed by sequencing. The PCRs were performed with 40 ng of genomic DNA; the PCR products were checked on 2% agarose gels and were directly sequenced using Big Dye Terminator Cycle Sequencing Ready Reaction Kit and the ABI PRISM 3730 DNA analyzer (Applied Biosystems, Foster City, CA, USA).

Statistical analysis Continuous variables were analyzed by independent t-test and were presented as means (s.d.). The allele frequency was obtained by direct gene counting. To test the departure of allele frequency spectrum from the Hardy–Weinberg equilibrium, we employed w2-test with one degree of freedom, besides Monte Carlo simulation test, using the HWSIM program (Cubells et al., 1997). Multivariate regression analysis was carried out to adjust for age and sex. All statistical analyses were performed with SPSS statistical software version 16.0 (SPSS Inc, Chicago, IL, USA) for Windows. P ¼ 0.05 (two-tailed) was considered statistically significant. Haploview software with the default setting was used to assess linkage disequilibrium (LD) between pair of SNPs and also to define haplotype blocks (Barrett et al., 2005). To evaluate haplotype–phenotype association we used Hap-Clustering program (Tzeng et al., 2006).

Materials and methods Subjects We have recruited 263 subjects from the Kota tribe of the Nilgiris of southern India. Among the study population, 93 were defined as cases of obesity (425 BMI) and 170 as controls (o25 BMI) based on the revised standards for adult obesity in Asia and India, proposed by International Obesity Task Force (Low et al., 2009). Body weight was measured by calibrating to the nearest 100 g. Height was measured to the nearest millimeter with subjects standing, back to the stadiometer in bare feet.BMI was calculated as body weight (kg) divided by height squared (m2). After obtaining an written informed consent, venipuncture was performed on each study subject and the blood specimen was collected in EDTA-Vacutainer (Beckton-Dickinson, Franklin Lanes, NJ, USA). Genomic DNA was extracted from all participants using standard procedures (Thangaraj et al., 2002). This study was approved by the institutional review board of the Centre for Cellular and Molecular Biology, Hyderabad.

NPY genotyping Two NPY gene-specific primers, primer-I forward: 50 -CCTG GGTTCTCTCTGCGGGACTG-30 , reverse: 50 -CCCATTTTGTG

Results Table 1 gives the baseline characteristics of the subjects for different parameters. The present study subjects ranged in age from 24 to 80 years, with a mean age of 43.08±13.39 years. The mean age was 42.5±13.6 years for all the controls and 44.2±13.1 years for the entire obese group, and there was no significant difference between control and obese groups (Figure 1; Table 1). The BMI of the present study subjects ranged from 20 to 36 kg/m2, with a mean BMI of 24.09±3.16 kg/m2. The mean BMI was 22.19 þ 1.27 kg/m2 for all the controls and 27.55 þ 2.58 kg/m2 for the entire obese group, and there was a significant difference between

Table 1

Demographic characteristic features of study participants

Sl. no

Characteristics

Cases (n ¼ 93)

Controls (n ¼ 170)

P-value

1 2 3 4

Age Height Weight BMI

44.19 þ 13.085 152.59 þ 8.448 64.28 þ 8.564 27.55 þ 2.580

42.46 þ 13.556 154.17 þ 8.761 52.89 þ 6.595 22.19 þ 1.274

0.318 0.158 0.000 0.000

Abbreviation: BMI, body mass index.

European Journal of Clinical Nutrition


870 control and obese groups (Table 1). We examined three SNPs in the NPY gene. The names of the polymorphisms (rs16139-1128 T4C: Leu7Pro; rs9785023-1258 G4 A: Ser50Ser; rs16475-7735 A4 G) are based on the notation of Karvonen et al. (1998). All SNPs followed Hardy–Weinberg equilibrium in both obese and control groups. The distributions of the NPY genotypes and allele frequencies are shown in Table 2. The minor allele frequencies of the Leu7Pro, Ser50Ser and A7735G were 22.1, 22.1 and 1.8%, respectively, in controls. On logistic regression analysis using age and sex as covariates, we did not find any significant association between the genotypes and obesity for all SNPs. The adjusted odds ratios and 95% confidence interval for obesity are presented in Table 2. No significant LD was observed

between any pair of SNPs. The low r2 value for every pair of SNP indicated that these SNPs cannot be tagged by each other (Leu7Pro–Ser50Ser, D0 ¼ 1, r2 ¼ 0.076; Leu7Pro–A7735G, D0 ¼ 0.011, r2 ¼ 0.03; Ser50Ser–A7735G, D0 ¼ 1, r2 ¼ 0.007). Haplotype analysis using all three SNPs did not show any significant association; the global P-value is 0.756 with adjustment for age and sex (Table 3).

Discussion We examined the association between the three SNPs, which also includes one well-characterized functional polymorphism (Leu7Pro) within the NPY gene and obesity in the Kota tribe of Nilgiri Hills. No statistically significant difference was observed in the frequency of genotype, allele and haplotype distribution of Leu7Pro, Ser50Ser and rs16475 of NPY gene between obesity and controls. Although the role of NPY in regulation of feeding and energy balance is not fully known, there are several studies that unite NPY to human obesity (Bray et al., 2000; Snyder et al., 2004; Yang et al., 2009). The earlier genetic and epidemiological studies indicate that the NPY Leu7Pro allele is a major risk factor for obesity (Ding et al., 2005; van Rossum et al., 2006). In

Table 3 Haplotype association analysis of neuropeptide Y gene polymorphisms with obesity Haplotype (Leu7Pro– Ser50Ser–A7735G)

Figure 1 Percentage of obese and nonobese subjects in different age groups.

TAA TGA CGA

Frequency

P-value

Global P-value

0.222 0.568 0.209

0.950 0.527 0.492

0.756

Table 2 NPY gene polymorphisms and obesity Control (n (%))

Obese (n (%))

OR (95% CI)

P-value

Leu7Pro TT TC CC Minor allele frequency (%)

104 (61.18) 57 (33.53) 9 (5.29) 22.1

62 (66.67) 27 (29.03) 4 (4.30) 18.8

0.828 (0.469–1.461) 0.796 (0.231–2.745)

0.515 0.718

Ser50Ser GG AG AA Minor allele frequency

106 (62.35) 53 (31.18) 11 (6.47) 22.1

55 (59.14) 34 (36.56) 4 (4.30) 22.6

1.20 (0.692–2.080) 0.626 (0.186–2.106)

0.517 0.449

A7735G AA GA GG Minor allele frequency

164 (96.47) 6 (3.53) 0 (0) 1.8

87 (93.55) 6 (6.45) 0 (0) 3.2

1.932 (0.587–6.355)

0.278

Abbreviations: CI, confidence intervals; NPY, neuropeptide Y; OR, odds ratio. P-values adjusted for age and sex.



871 contrast to this Mattevi et al. (2002) reported a positive association between Leu7Pro and lower BMI in premenopausal women. But the results obtained from this study failed to support the hypothesis of Leu7Pro Polymorphism in the NPY receptor gene associated with obesity. While a comprehensive analysis of 71 SNPs present in several genes of NPY pathway reported small effects (Campbell et al., 2007). Ding (2003) reported that the Pro7 allele might have originated in the north of Europe and then spread to the neighboring regions, and the frequency showed a decreasing north to south gradient and also stated that the highest allele frequencies were found in the Nordic countries. Our earlier study revealed in no significant LD between leu7pro and other polymorphic sites in the Indian populations with varying Pro7 allele (Bhaskar et al., 2007). In fact, Leu7Pro polymorphism results in an amino acid change in the signal peptide of NPY from leucine, which has a hydrophobic aliphatic side chain amino acid, to proline, which has a cyclic structure. Ding et al. (2005) simulated a computer model by introducing proline at position 7 and found that it disrupts the local conformation of the peptide by altering the packaging of the helical bundle and diminishes helix propensity for the sequence. Recent studies revealed that the Pro7 allele causes quite radical change in the tertiary structure of signal sequence of NPY (Pesonen, 2008). Leu7pro polymorphism was found to alter the secretion and packaging of NPY (Mitchell et al., 2008). Furthermore, leu7pro polymorphism was found to increase peptide synthesis and secretion (Mitchell et al., 2008). Among the other two polymorphisms (rs9785023 and rs16475), the rs9785023 is a synonymous variant of G1258A (Ser50Ser), which is quite common in Mexican Americans (Bray et al., 2000) and is not associated with obesity (Ahituv et al., 2007). Lack of significant LD between pairs of loci in the NPY gene region may be attributed to the low frequency of the alleles, as all measures of LD show some allele frequency dependence in finite sample sizes (Mueller, 2004). There are several potential limitations to this study. First, we ascertained obese subjects without considering the variation in body fat distribution, which can considerably differ for the same BMI (WHO, 2000), and across different gender (Han et al., 2009), age (Movsesyan et al., 2003) and ethnic groups (Duncan et al., 2009; Luke, 2009). This may lead to some misclassification of obesity. Second, our relatively small total sample size may have influenced the ability to identify association with between BMI-defined obesity and NPY gene polymorphisms. However, this study is population-based, randomized, with logically well-matched baseline parameters and other possible factors influencing BMI. Our findings are based on a sample of relatively homogeneous genetic background, and, therefore, the results are unlikely to be affected by unmeasured confounding factors of population stratification. In conclusion, the NPY gene does not have a key role in conferring risk for obesity. Additional studies in different populations are necessary to clarify the role of the NPY gene in causing obesity.

Conflict of interest The authors declare no conflict of interest.

Acknowledgements This project was supported by the grant from the Department of Biotechnology, Government of India (grant no. BT/ PR3607/SPD/09/261/2003).

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