Molecular and Cellular Biochemistry

, Volume 379, Issue 1, pp 77–85

Chromosome 9p21 rs10757278 polymorphism is associated with the risk of metabolic syndrome

Authors

  • Burcu Bayoglu
    • Department of Medical Biology, Cerrahpasa Medical FacultyIstanbul University
  • Huseyin Altug Cakmak
    • Department of Cardiology, Cerrahpasa Medical FacultyIstanbul University
  • Husniye Yuksel
    • Department of Cardiology, Cerrahpasa Medical FacultyIstanbul University
  • Gunay Can
    • Department of Public Health, Cerrahpasa Medical FacultyIstanbul University
  • Bilgehan Karadag
    • Department of Cardiology, Cerrahpasa Medical FacultyIstanbul University
  • Turgut Ulutin
    • Department of Medical Biology, Cerrahpasa Medical FacultyIstanbul University
  • Vural Ali Vural
    • Department of Cardiology, Cerrahpasa Medical FacultyIstanbul University
    • Department of Medical Biology, Cerrahpasa Medical FacultyIstanbul University
Article

DOI: 10.1007/s11010-013-1629-3

Cite this article as:
Bayoglu, B., Cakmak, H.A., Yuksel, H. et al. Mol Cell Biochem (2013) 379: 77. doi:10.1007/s11010-013-1629-3

Abstract

Metabolic syndrome (MetS) is a common multifactorial disorder that involves abdominal obesity, dyslipidemia, hypertension, and hyperglycemia. Genome-wide association studies have identified a major risk locus for coronary artery disease and myocardial infarction on chromosome 9p21. Here, we examined the frequency of single nucleotide polymorphisms (SNPs) on chromosome 9p21 in a sample of Turkish patients with MetS and further investigated the correlation between regional SNPs, haplotypes, and MetS. The real-time polymerase chain reaction (RT-PCR) was used to analyze 4 SNPs (rs10757274 A/G, rs2383207 A/G, rs10757278 A/G, rs1333049 C/G) in 291 MetS patients and 247 controls. Analysis of 4 SNPs revealed a significant difference in the genotype distribution for rs2383207, rs10757278, and rs1333049 between MetS patients and controls (p = 0.041, p = 0.005, p = 0.023, respectively) but not for rs10757274 (p = 0.211). MetS and control allelic frequencies for rs2383207, rs10757278, and rs1333049 were statistically different (p < 0.05). The rs2383207 AG variant, was identified as a MetS risk factor (p = 0.012, OR = 33.271; 95 % CI: 2.193–504.805) and the AA haplotype in block 1 and the GC, AG haplotypes in block 2 were associated with MetS (χ2 = 3.875, p = 0.049; χ2 = 9.334, p = 0.0022; χ2 = 9.134, p = 0.0025, respectively). In this study, we found that chromosome 9p21 SNP rs10757278 and related haplotypes correlate with MetS risk. This is the first report showing an association between a 9p21 variant and MetS and suggests that rs10757278 polymorphism may confer increased risk for disease.

Keywords

Metabolic syndromeChromosome 9p21Genetic variationHaplotype

Introduction

Metabolic syndrome (MetS) is a common multifactorial disorder that involves abdominal obesity, dyslipidemia, hypertension, and hyperglycemia. It is associated with an increased risk of coronary artery disease (CAD) and type 2 diabetes (T2D). The prevalence of MetS is about 30 % worldwide and is on the rise [1]. Family studies show that the different components of the MetS share a common genetic component [2]. Heritability estimates for MetS ranges from 13 to 27 % [24]. Therefore, MetS is considered to be partly heritable. Although some heritability studies revealed an association between SNPs and MetS [58], the molecular pathogenesis of MetS is not well understood. Since MetS refers to a cluster of conditions including obesity, hypertension, hyperglycemia, and dyslipidemia, MetS can be considered a polygenic, multifactorial, and genetically complex disorder.

The National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) viewed cardiovascular disease (CVD) as the primary clinical outcome of MetS [9]. Moreover, ATP III identified six components of MetS that relate to CVD. These are abdominal obesity, atherogenic dyslipidemia, elevated blood pressure, insulin resistance with or without glucose intolerance, a proinflammatory state, and a prothrombotic state. Together, the combination of these MetS components result in, what NCEP ATP III specifies as, underlying, major, and emerging risk factors. According to ATP III, the underlying risk factors for CVD are obesity, specifically abdominal obesity, physical inactivity, and an atherogenic diet; the major risk factors are cigarette smoking, hypertension, elevated LDL cholesterol, low HDL cholesterol, family history of premature coronary heart disease (CHD), and aging; and the emerging risk factors include elevated triglycerides, small LDL particles, insulin resistance, glucose intolerance, a proinflammatory state, and a prothrombotic state [9, 10].

Recent epidemiological studies found that MetS is associated with cardiovascular disease and all-cause mortality [1113]. Therefore, prevention, early diagnosis, and treatment for MetS are important strategies for reducing CVD. Recent genome-wide association studies (GWAS) have identified various genes that are related to the predisposition of either MetS predisposition [14] or to each MetS component [15, 16]. Additionally, in recent years, GWAS have identified a major locus on chromosome 9p21 that is associated with an increased risk for CAD and myocardial infarction (MI) [1719]. As the most tightly associated SNPs did not map with an annotated gene sequence, the neighboring cyclin-dependent kinase inhibitors 2A and 2B (CDKN2A, CDKN2B) and methylthioadenine phosphorylase (MTAP) genes were initially suggested to be candidate genes for CAD and MI [20]. The two kinase inhibitors, CDKN2A and CDKN2B, are key players in cell proliferation and senescence. They are candidates to mediate these cellular events in cardiovascular pathologies. There is also a newly annotated, large antisense non-coding RNA gene, ANRIL (CDKN2BAS), which is expressed in tissues and cell types affected by atherosclerosis. ANRIL is transcribed from the opposite strand of CDKN2A/CDKN2B and identified as the prime candidate gene for the susceptibility locus on chromosome 9p21 [21]. A dysregulation in the cell cycle may lead to promote pathologic monocytic or vascular proliferation which results an acceleration in atherosclerosis. Thus SNPs on this chromosomal region may have functional effects on cardiovascular disorders.

SNPs on Ch9p21 may also have a role in the development of MetS. Investigating the possible relationship between the SNPs and their haplotypes in this region and MetS may contribute to our understanding of the MetS pathogenesis. The knowledge gained may even be useful in the prevention of the disease. However, as much as we know there have been no studies examining this relationship. Since, T2D, CAD, and MI are themselves risk factors for MetS and as the variations on Ch9p21 showed functionally significant relationship with the MetS risk factors, we decided to determine the frequency of variations and their haplotypes at Ch9p21.3 locus and evaluate their association with the development of the MetS.

Materials and methods

Subjects

This case–control study included a total of 538 Turkish subjects, 291 patients with MetS and 247 non-MetS controls (Table 1). The MetS diagnosed patients and the controls were selected from Istanbul University Cerrahpasa Medical Faculty Cardiology Department. The study was approved by the Local Ethics Committee of the Cerrahpasa Medical Faculty, Istanbul, Turkey. All participants gave their written informed consent prior to participation in the study.
Table 1

Baseline demographic and clinical characteristics of MetS patients and controls

Characteristics

MetS group (n = 291)

Control group (n = 247)

p Value

Age (years)

53.36 ± 7.04

51.11 ± 8.00

0.001

Male/female (n, %)

154/137 (52.9, 47.1 %)

176/71 (71.3, 28.7 %)

<0.001

Height (m)

168.04 ± 7.65

168.85 ± 7.51

0.222

Weight (kg)

78.79 ± 11.02

74.81 ± 11.36

<0.001

BMI (kg/m2)

27.95 ± 3.72

26.11 ± 3.03

<0.001

Waist circumference (cm)

87.26 ± 13.96

80.61 ± 8.96

<0.001

Systolic blood pressure (mmHg)

142.61 ± 18.29

124.85 ± 17.39

<0.001

Diastolic blood pressure (mmHg)

83.04 ± 13.08

75.13 ± 9.91

<0.001

Pulse rate (bpm)

80.08 ± 10.98

76.52 ± 10.35

<0.001

Fasting glucose (mg/dL)

123.89 ± 36.82

104.53 ± 24.13

<0.001

Total chol (mg/dL)

178.44 ± 43.01

167.08 ± 33.55

0.001

HDL(mg/dL)

38.67 ± 10.81

48.03 ± 39.02

<0.001

LDL(mg/dL)

123.62 ± 34.64

107.82 ± 27.09

<0.001

TAG(mg/dL)

174.62 ± 68.54

123.19 ± 29.59

<0.001

HT n (±), (%)

201/90, (69.1 %/30.9 %)

70/177 (28.3, 71.7 %)

<0.001

T2D n (±), (%)

95/196, (32.6, 67.4 %)

24/223 (9.7, 90.3 %)

<0.001

HPL n (±), (%)

111/180, (38.1, 61.9 %)

51/196 (20.6, 79.4 %)

<0.001

Smoking status n (±), (%)

152/139, (52.2, 47.8 %)

78/169 (31.6, 68.4 %)

<0.001

T test and χ2 test were performed. Data presented as mean ± SD

TAG triacylglycerol, HT hypertension, T2D type 2 diabetes, HPL hyperlipidemia

Each subject underwent a cardiovascular examination. The diagnosis of the MetS was done by clinicians according to the NCEP ATP III criteria which is an acceptable and well-recognized criterion for MetS diagnosis [9]. According to the NCEP ATP III criteria, patients who have three or more of the following five risk factors are identified as MetS. These five risk factors are, abdominal obesity with a waist circumference >102 cm for men and >88 cm for women; triglycerides ≥150 mg/dL; HDL cholesterol <40 mg/dL for men and <50 mg/dL for women; blood pressure ≥130/≥85 mmHg and fasting glucose ≥110 mg/dL. Of the MetS patients, 68.72 and 32.64 % were diagnosed with CAD and T2D, respectively. The mean age of the MetS group was 53.36 ± 7.04 years (range 23–67) and 137 (47.1 %) of the 291 patients were women.

Control subjects presenting with the absence of the MetS did not have three of the five risk factors explained above and identified for the MetS according to NCEP ATP III criteria. The selection criteria of the controls were that all control subjects were from the same geographical area with a similar socioeconomic and ethnic backgrounds and were admitted to outpatient clinic and also age and gender were consistent with the MetS patients. The socioeconomic background was identified by the information obtained from the patient and the controls through a health questionnaire. All the patients and controls were in the middle-income status. The mean age of the control group was 51.11 ± 8.00 years (range 31–71) and 71 (28.7 %) of the 247 subjects were women. Exclusion criteria for selecting control subjects were, autoimmune disease, severe kidney and hepatic diseases, cancer, and pregnancy.

Blood samples and DNA isolation

Venous blood samples were obtained from the patient and control groups and collected into EDTA tubes. After collection, whole blood was stored in aliquots at −20 °C until use. Genomic DNA was extracted from whole blood using a High Pure PCR Template Preparation Kit (Roche Diagnostics GmbH, Mannheim, Germany) according to the manufacturer’s instructions.

Genotyping of chromosome 9p21 SNPs rs10757274, rs2383207, rs10757278, and rs1333049

In the screening phase, since the information on the genomic variation of chromosome 9p21 SNPs was not available on MetS, we selected 4 SNPs (rs1333049, rs2383207, rs10757274, and rs10757278) which show the strongest association with CAD, MI, and T2D in previous GWAS conducted on European and Caucasian populations [1618]. Also, the linkage disequilibrium (LD) data for some 9p21 SNPs for both Caucasian and European populations were reviewed from the HapMap database (International HapMap Consortium 2005). The LightCycler 1.5® system was used to perform SNP genotyping using hybridization probes consisting of 3′- fluorescein and a 5′-LightCycler® Red labeled pair of oligonucleotide probes (TIB MOLBIOL, GmbH, Berlin, Germany). Genotyping was performed in a 20 μL volume containing 2.0 μL of LightCycler® FastStart DNA Master HybProbe (Roche Diagnostics GmbH, Mannheim, Germany), 1.0 μL Reagent Mix, 3.0 mM MgCl2, and 50 ng of genomic DNA. The quality of SNP genotyping was assured by independently replicating the genotyping of randomly selected samples.

Statistical analysis

Statistical analysis for comparison of variables between the groups of the cases and the controls such as age, systolic and diastolic blood pressure (SBP, DBP), pulse rate, serum glucose level, body mass index (BMI), and plasma lipid levels were performed using the Student’s t test. Data are expressed as mean ± standard deviation (SD). The Chi square (χ2) test was used for categorical variables. The χ2 test was also used to compare the association between the genotypes and alleles in relation to the cases and controls, and to test for deviation of genotype distribution from Hardy–Weinberg equilibrium (HWE). p < 0.05 was considered statistically significant. The odds ratio (OR) and their 95 % confidence intervals (CIs) were calculated to determine the strength of the association between genotypic alleles and the cases and controls. OR and 95 % CI for the SNPs were also estimated by multiple logistic regression analysis with adjustment for age, sex, and smoking habits. Bonferroni adjustments for multiple comparisons were made for the p value. All statistical analyses were performed using the SPSS for Windows software (Version 15.0). Additionally, power analyses were performed with PS:Power and sample size calculation Version 3.0 (2009) (Vanderbilt University, TN, USA) [22]. The statistical power ranged from 0.42 to 0.958. The linkage disequilibrium (LD), whereby genetic variants are associated between the tested SNPs was calculated by the Haploview software (version 4.1) [23].

Results

Demographic data of the patients and controls

The study included 291 cases with the MetS and 247 controls. The demographic and clinical characteristics of the patients and controls are shown in Table 1. An extremely significant difference was observed between the age, gender, weight, BMI, SBP, DBP, pulse rate, fasting glucose, total cholesterol, LDL, HDL, TAG and waist circumference of the patients and controls (p < 0.001). There was also an extremely significant difference between observed hypertension, T2D, and hyperlipidemia status of the patients and controls (p < 0.001).

HWE for the SNPs rs10757274, rs2383207, rs10757278, and rs1333049 on chromosome 9p21

The distributions of the genotype for the SNPs, rs10757274, rs2383207, rs10757278, and rs1333049 are presented in Table 2. The distributions of rs10757274, rs2383207, rs10757278, and rs1333049 genotypes were consistent with the HWE expectation among the patients (p = 0.47, p = 0.43, p = 0.41, and p = 0.64, respectively) and controls (p = 0.87, p = 0.713, p = 0.174, and p = 0.40, respectively). The frequencies of each genotype were consistent with the HWE in the whole sample (p > 0.05).
Table 2

The distribution of SNPs rs10757274, rs2383207, rs10757278, and rs1333049 genotype and allele frequencies among MetS patients and controls

Genotype/allele

MetS patients n (%)

Controls n (%)

p Value

rs10757274

 AA

52 (17.9)

52 (21.1)

 

 AG

135 (46.4)

124 (50.2)

 

 GG

104 (35.7)

71 (28.7)

0.211

 A allele frequency

0.41

0.46

 

 G allele frequency

0.59

0.54

0.093

rs2383207

 AA

36 (12.4)

39 (15.8)

 

 AG

124 (42.6)

123 (49.8)

 

 GG

131 (45.0)

85 (34.4)

0.041

 A allele frequency

0.34

0.41

 

 G allele frequency

0.66

0.59

0.017

rs10757278

 AA

46 (15.8)

67 (27.1)

 

 AG

147 (50.5)

114 (46.2)

 

 GG

98 (33.7)

66 (26.7)

0.005

 A allele frequency

0.41

0.50

 

 G allele frequency

0.59

0.50

0.002

rs1333049

 CC

96 (33.0)

64 (25.9)

 

 CG

145 (49.8)

118 (47.8)

 

 GG

50 (17.2)

65 (26.3)

0.023

 C allele frequency

0.58

0.50

 

 G allele frequency

0.42

0.50

0.007

χ2 test was performed. n (%) was described

Comparison of the genotypic frequencies of the SNPs rs10757274, rs2383207, rs10757278, and rs1333049 on chromosome 9p21

A significant difference was observed between the genotype frequencies of rs2383207, rs10757278, and rs1333049 polymorphisms between MetS patients and the control group (Table 2). However, no significant difference was observed between the genotype frequencies of rs10757274 between patients and controls. After Bonferroni correction for multiple testing, the association of rs10757278 remained significant (p = 0.02). However, the association of rs2383207 and rs1333049 was not maintained (p = 0.164 and p = 0.092, respectively). Besides, a significant difference was observed between the allelic frequencies of rs2383207, rs10757278, and rs1333049 (χ2 = 5.64, p = 0.017; χ2 = 9.0, p = 0.002; χ2 = 7.07, p = 0.007, respectively). No statistically significant difference was observed between the allelic frequency of rs10757274 in patients and controls (χ2 = 2.82, p = 0.093) (Table 2).

Analysis of SNPs rs10757274, rs2383207, rs10757278, and rs1333049 SNPs with regards to MetS risk factors

We also explored the potential selective effects of polymorphisms on patients by analyzing the SNPs rs10757274, rs2383207, rs10757278, and rs1333049 with multiple logistic regression analysis with adjustment for some MetS risk factors. Increased age, smoking, and female gender were found to be significant risk factors with the investigated SNPs for MetS (p = 0.006, p ≤ 0.001, p ≤ 0.001, respectively). AG variant of rs10757274 was found to exert protective effects against MetS (p = 0.042, OR = 0.336; 95 % CI:0.117–0.963). However, AG variants of rs2383207 were found to be a significant risk factor for MetS development (p = 0.012, OR = 33.271; 95 % CI: 2.193–504.805) (Table 3). When the combined effects of the homozygous mutant and heterozygous genotypes were analyzed to minimize the statistical error for the possible risk factor for MetS, rs10757274 variant AA was found to be a significant genetic risk factor for MetS development (p = 0.039, OR = 2.971; 95 % CI: 1.057–8.351). Also, for rs2383207 combined AG+GG genotypes were found to be a significant risk factor for MetS (p = 0.015, OR = 17.957; 95 % CI: 1.766–182.626) (Table 4).
Table 3

Chromosome 9p21 genotypes and their association with MetS risk

 

p Value

Exp (B)

95.0 % CI

Lower

Upper

Age

0.006

1.036

1.010

1.062

Non-smoker

 

1

  

Smoker

<0.001

2.649

1.816

3.862

Male

 

1

  

Female

<0.001

2.247

1.530

3.302

rs10757274

 

1

  

 AA

 AG

0.042

0.336

0.117

0.963

 GG

0.097

0.334

0.092

1.218

rs2383207

 AA

 AG

0.012

33.271

2.193

504.805

 GG

0.117

7.584

0.603

95.413

rs10757278

 AA

 

1

  

 AG

0.855

1.086

0.447

2.639

 GG

0.174

2.097

0.721

6.100

rs1333049

 CC

 

1

  

 CG

0.288

0.356

0.053

2.392

 GG

0.380

2.899

0.269

31.190

 Constant

0.006

0.021

  

Adjustments for age, gender and smoking status were performed

Exp (B) exponentiation of the B coefficient, 95.0 %CI difference of means at 95 % confidence interval

Table 4

Combined genotypes of Chromosome 9p21 and their association with MetS risk

 

p Value

Exp (B)

95.0 % CI

Lower

Upper

 Age

0.008

1.034

1.009

1.060

Non-smoker

Smoker

<0.001

2.592

1.784

3.766

Male

Female

<0.001

2.271

1.551

3.326

rs10757274

AG+GG

AA

0.039

2.971

1.057

8.351

rs2383207

AA

AG+GG

0.015

17.957

1.766

182.626

rs10757278

AA

AG+GG

0.679

1.203

0.501

2.892

rs1333049

CG+CC

GG

0.205

4.213

0.455

38.989

Constant

<0.001

0.005

  

Adjustments for age, gender, and smoking status were performed

Exp (B) exponentiation of the B coefficient, 95.0 % CI difference of means at 95 % confidence interval

Haplotype analysis

The linkage disequilibrium (LD) was assessed using Haploview with blocks graphically identified from the LD intensity expressed in D′ [23]. Haplotype associations are shown in Table 5. The AA haplotype in block 1 was found to be associated with MetS (χ2 = 3.875, p = 0.049). The GC and AG haplotypes in block 2 were also found to be associated with MetS (χ2 = 9.334, p = 0.0022 and χ2 = 9.134, p = 0.0025). In block 1, the haplotypes of rs10757274 and rs2383207 have the frequencies of 55.9 % GG, 0.8 % GA, 36.3 % AA, and 7.0 % AG (D′ = 0.962, LOD = 134.35 and r2 = 0.714). In block 2, the haplotypes of rs10757278 and rs1333049 have frequencies of 53.6 % GC, 1.5 % GG, 44.4 % AG, and 0.5 % AC (D′ = 0.981, LOD = 202.47 and r2 = 0.923) (Fig. 1).
Table 5

Haplotype associations of SNPs rs10757274, rs2383207, rs10757278, and rs1333049

Haplotype

Frequency

Case, control ratios

Χ2

p Value

Haplotype associations

Block 1 (19 kb) (rs10757274, rs2383207)

 GG

0.559

0.585, 0.528

3.6

0.0578

 AA

0.363

0.336, 0.394

3.875

0.049

 AG

0.070

0.074, 0.065

0.335

0.563

Block 2 (1 kb) (rs10757278, rs1333049)

 GC

0.536

0.579, 0.486

9.334

0.0022

 AG

0.444

0.402, 0.494

9.134

0.0025

 GG

0.015

0.019, 0.010

1.4

0.2367

χ2 test was performed

https://static-content.springer.com/image/art%3A10.1007%2Fs11010-013-1629-3/MediaObjects/11010_2013_1629_Fig1_HTML.gif
Fig. 1

Linkage disequilibrium (LD) of SNPs rs10757274, rs2383207, rs10757278, and rs1333049 on chromosome 9p21

Discussion

Various studies have shown the existence of associations between the variations on chromosome 9p21 and CVD [1719]. The 9p21 region has also been associated with calcium score [17, 24], severe premature atherosclerosis [17], the prevalence of angiographic CAD [25, 26], and the progression of carotid atherosclerosis [27]. In our study, all the examined subjects were genotyped for chromosome 9p21 SNPs to analyze the possible influence of the genetic variations on susceptibility to MetS. We found that rs2383207, rs10757278, and rs1333049 polymorphisms may be associated with susceptibility to MetS. However, rs10757274 polymorphism was not associated with MetS risk. After Bonferroni correction for multiple testing, the association of rs10757278 remained significant (p = 0.02). However, the association of rs2383207 and rs1333049 was not maintained (p = 0.164 and p = 0.092, respectively). Additionally, in the haplotype analysis, the AA haplotype in block 1 and the GC, AG haplotypes in block 2 were found to be associated with MetS.

To our knowledge, this is the first study investigating the relationship between chromosome 9p21 variants and the prevalence of MetS. Our main finding was that rs10757278 polymorphism on chromosome 9p21 may be associated with a higher risk of MetS. Also, the AG variant of rs2383207 was associated with a higher risk of MetS when adjusted for age, smoking, and gender status. Our findings are consistent with published data that report an association between chromosome 9p21 rs10757278 and rs2383207 polymorphisms and CAD and MI, which are the risk factors for MetS [18]. In that study, it was shown that rs10757278 risk allele G and rs2383207 risk allele G are higly associated with MI risk in a large cohort of US and Icelandic groups, respectively. The same study also demonstrated that the G variant of rs10757278 is found to be associated with CAD. In addition, a more recent study [28] demonstrated that the rs10757278 G variant at the 9p21 locus is significantly associated with the risk of CAD in Western India populations. Consistent with these findings, in our study, rs10757278 G variant is found to be associated with MetS risk, which is a cluster of CVD. Also, in the combined effects of the polymorphisms, the combination of rs2383207 AG and GG genotypes may increase the risk of MetS development.

A gender-specific relationship was also identified in this study. The females were more susceptible than males for MetS risk. This finding is in contrast with those of the previous studies that examined the relation between SNP rs10757274, heart failure [29] and abdominal aorta stiffness [30]. In contrast, these studies identified a relationship between these SNPs and risk in males. Our findings may be due to the fact that Turkish adults, particularly females, have higher abdominal/central adiposity [31], which is a known determinant of insulin resistance.

In recent years, some chromosome 9p21 SNPs have been widely discussed in the context of cardiovascular diseases [1719, 2527]. SNPs on the chromosome 9p21 neighboring CDKN2A, CDKN2B, and MTAP genes play a role in cell cycle regulation. Evidence from previous GWAS implicate variants of the cyclin-dependent kinase 5 regulatory subunit associated protein 1-like 1 gene (CDKAL1) and CDKN2A/B genes in T2D predisposition, thus suggesting that cell cycle dysregulation may be a common pathogenetic mechanism in T2D [3234]. Meanwhile, one study did identify an association between SNP rs10757274 and CHD in six independent Caucasian samples [17]. In that study, a significant association was found between rs10757274 and CHD in a large cohort of Caucasians. Homozygotes for the risk allele were found to be present in 20–25 % of Caucasians and resulted in a 30–40 % increased risk of CHD [17]. In our study, we found rs10757274 heterozygote for the AG variant has a protective effect on MetS development. However, with combined polymorphisms, the AA variant was found to be a risk factor for MetS as compared with AG+GG in combined genotypes. This may be due to the fact that MetS is a more complex disease than CHD since various components influence the development of MetS.

A 58-kilobase interval on chromosome 9p21 region, which is located near the CDKN2A and CDKN2B genes, contains no annotated genes and is not associated with established CHD risk factors such as plasma lipoproteins, hypertension, or diabetes [17]. The 9p21 locus also harbors a long non-coding RNA called ANRIL and its functions remain partially unclear. The most remarkable finding is that this region does not include any of the genes related to CAD, but interestingly, having risk variants of SNPs on this region, may result in more dramatic conditions. The ANRIL locus, which has been recently highlighted by several reports, may give rise to a pathogenetic mechanism. The 9p21 locus SNPs may affect the expression of ANRIL, which regulates the expression of CDKN2A/B through pathways independent from CDKN2A/B [35]. ANRIL gene expression profilings suggest that ANRIL splice variants play a role in coordinating tissue remodeling by modulating the expression of genes with a wide variety of cellular functions such as cell proliferation, apoptosis, extra-cellular matrix remodeling, and inflammatory response [36]. So the 9p21 locus may lead to susceptibility to a variety of pathologies because of this regulatory region.

To conclude, although a larger sample size is required for more definite conclusions, this is the first study to evaluate the possible association between chromosome 9p21 SNPs, rs10757274, rs2383207, rs10757278, and rs1333049 and MetS development. Our results indicate that SNP rs10757278, and their related haplotypes on chromosome 9p21, may contribute to individual susceptibility to MetS. Also, the risk allele G of rs2383207 and rs10757278, and the risk allele C of rs1333049 are significantly associated with MetS. Utilizing multiple comparison tests with adjustment for increased age, smoking, and gender, we found the risk factors to be significantly associated with the investigated SNPs. Multiple logistic regression results with adjustment confirmed the risk for MetS with the rs2383207 AG variant, and also the protective effect of the rs10757274 AG variant. In combined genotypes, the AA variant of rs10757274 was found to be a risk factor for MetS development. Additionally, rs2383207 combined AG+GG genotypes were found to be a significant risk factor for MetS development. The χ2 test for SNPs followed by haplotype analysis validated the relationship between the block 2 haplotypes and allele frequencies with MetS development. The allele frequency results were consistent with the haplotype blocks. However, further studies with a larger sample size are required to validate these results.

GWAS results hold the promise of revealing the chromosome 9p21 locus as a potential locus for genetically complex disorders via its regulatory regions. Furthermore, future work should focus on the tissue-specific expression of the non-coding RNA ANRIL as it relates to locus variants and haplotypes, which may lead to new pathogenic genetic mechanisms of MetS.

Acknowledgments

This work was supported by Scientific Research Projects Coordination Unit of Istanbul University. Project number 4060. The preliminary findings of this study were presented at the 4th International Congress of Molecular Medicine, June 27–30, 2011, Istanbul, Turkey [37].

Conflict of interest

The authors declare that there are no conflicts of interest.

Copyright information

© Springer Science+Business Media New York 2013