A54T polymorphism in the fatty acid binding protein 2 studies in a Saudi population with type 2 diabetes mellitus

  • Khalid Khalaf Alharbi1,

    Affiliated with

    • Imran Ali Khan1Email author,

      Affiliated with

      • Mohammad D Bazzi2,

        Affiliated with

        • Nasser M Al-Daghri3,

          Affiliated with

          • Tarique N Hasan4,

            Affiliated with

            • May Salem Alnbaheen5, 6,

              Affiliated with

              • Fawiziah Khalaf Alharbi7,

                Affiliated with

                • Yazeed A Al-Sheikh1,

                  Affiliated with

                  • Rabbani Syed1 and

                    Affiliated with

                    • Mourad AM Aboul-Soud1

                      Affiliated with

                      Contributed equally
                      Lipids in Health and Disease201413:61

                      DOI: 10.1186/1476-511X-13-61

                      Received: 15 March 2014

                      Accepted: 26 March 2014

                      Published: 1 April 2014

                      Abstract

                      Background

                      Fatty acid-binding protein 2 (FABP2) is an intracellular protein expressed exclusively in the enterocytes of proximal small intestine. FABP2 has a high affinity for saturated and unsaturated long-chain fatty acids and is believed to be involved in the absorption and transport of dietary fatty acids.

                      Methods

                      This is a case–control study conceded in 438 T2DM cases and 460 subjects with normal glucose levels and non-obese considered as healthy controls. Allelic discrimination was performed using TaqMan single-nucleotide polymorphism was carried out by real time-polymerase chain reaction (RT-PCR) assays using purified DNA.

                      Results

                      Clinical data and anthropometric measurements except age, glucose levels and lipid profile of the patients were significantly different from those of the controls (p < 0.05). Statistical analyses failed to show any type of significant association of the polymorphism between cases and controls. However logistic regression analyses was suggests that the TT genotype is significantly associated with male patients (p = 0.001). None of the allele or genotypes of FABP2 A54T was associated with T2DM cases versus the controls (AT genotype, OR = 0.85 (0.64-1.12), p = 0.25; TT genotype, OR = 0.66 (0.39-1.11), p = 0.11; T allele, 0.82 (0.67-1.02), p = 0.08).

                      Conclusion

                      In conclusion, this study suggests that the above named variant in FABP2 gene is not potential contributor to the risk of T2DM and related traits in a Saudi population. However TT genotype is a risk factor for the disease in males.

                      Keywords

                      A54T polymorphism FABP2 gene Type 2 diabetes mellitus Saudi population

                      Introduction

                      Type 2 diabetes mellitus (T2DM) is a chronic degenerative disease, phenotypically and genetically characterized by insulin resistance (IR) in insulin-target tissues, and impaired insulin secretion from pancreatic β-cells [1]. T2DM affects nearly 31.6% individuals in the Kingdom of Saudi Arabia [2]. The interaction of genetic and environmental factors is universally acknowledged as the primary underlying T2DM mechanism. The T2DM risk in the first degree relatives of T2DM patients is 3.62 times that in the common population, so the researchers of various countries make great efforts to explore the T2DM susceptible genes. Once the T2DM susceptible genes are sought out, it means that the T2DM prevention clues have been found. It is an effective measure to screen the T2DM susceptible population and prevent T2DM progress. It is now generally considered that T2DM is not a sole disorder, but a multigenic disorder with extensive heredity heterogeneous, categorized by high levels of glucose and metabolic disorders [3, 4]. Obesity is one of the complication for T2DM and the leading cause of preventable deaths and a serious health complications in the Saudi Arabia [5].

                      Genome Wide Association Studies (GWAS) are powerful tools to identify genetic variants that are associated with common diseases. So far, GWAS identified at least 50–52 genetic loci robustly associated with T2DM [6]. Several genetic markers have now been implicated for T2DM development pathways involved in the disease [7, 8]. Fatty acid binding protein 2 (FABP2) has been studied as one of the marker, due to its role in the uptake, intracellular metabolism and excretion of long chain fatty acids. This gene is located on 4q28-q31 chromosomal region, consist of approximately 3.4 kbs. Many polymorphisms in FABP2 gene have already linked with metabolic phenotypes. The most extensively studies polymorphism was Alanine54threnonine (A54T) substitution at codon 54 of exon 2 that results from G to A nucleotide substitution and affects primary protein structure [9, 10]. This change affects the ability of the protein to transport dietary fatty acids, which may elevate saturated fatty acids level in the serum which might induce endothelial dysfunction leading to increased cardiovascular mortality [11].

                      The aim of the present study was to investigate the contribution of A54T genetic polymorphism identified by Baier et al [12] in the FABP2 variants to risk of T2DM in a Saudi population, since this polymorphism results in a functionally altered FABP2 protein which confers susceptibility to metabolic disorders like T2DM, thereby to contribute to the personalized prevention of this condition and A54T polymorphism has been associated with T2DM disease in many but not all studies.

                      Materials and methods

                      Selection of subjects

                      This is a case–control study carried out in King Saud University, Riyadh, Saudi Arabia. In this study we have collected in about 900 subjects; 438 T2DM cases and 460 healthy controls from the capital city. All the normal controls were selected from the general population based on normal glucose values and non-obese subjects. The details of the collection of patients, inclusion and exclusion criteria were described in the prior publication [1]. Ethical approval for the study was achieved from the ethics committee, King Saud University. Written informed consent was obtained from each patient. Anthropometric and biochemical measurements of the patients involved in this study has been described in the prior publication [1].

                      DNA extraction and genotyping

                      5 mL of the venous blood was collected into plain (coagulated) and EDTA (anticoaggulated) tubes. Plain vacutainer consist of 3 mL of the serum sample was used to analyze the biochemical parameters and 2 mL of the EDTA sample was used for molecular analysis. Genomic DNA was extracted from peripheral blood leukocytes using Norgen DNA extraction kit (Norgen Biotek corp, Canada). DNA samples were stored at -80°C. The rs1799883 polymorphism was genotyped using a TaqMan® SNP genotyping assay (Assay ID: C_2834835_10) on a 7300HT sequence detection system (Applied Biosystems, USA). Primers and probes were obtained from Applied Biosystems as Assays-by-Design™. Cases and controls were ensured to have even treatment during the assay procedure, and each plate included negative controls (with no DNA). Plates were read on the ABI Prism 7300 using the Sequence Detection Software (Applied Biosystems) using 40 PCR cycles (92°C denaturation for 15 seconds, 60°C annealing/extension for 60 seconds). Measurements were repeated for samples with failed genotypes. Assays that did not show >95% concordance were discarded and replaced with alternative assays with the same tagging properties.

                      Statistical analysis

                      All statistical analysis was carried out using the statistical program i.e. statistical package for social sciences (IBM SPSS 19.0 SPSS Inc., Chicago, USA). The difference of mean age of patients and controls were significantly different (Table 1). Hence in order to overcome the significance difference of mean age, logistic regression was performed and it was found that patients with ages 35 (1 patient), 72 (2 patients), 77 (2 patients), 84 (2 patients), 85 (2 patients) and 86 (2 patients) years were redundant whereas rest all the patient ages were significantly not different from those of controls. Hence those patients were excluded from the further calculations if genotypic and allelic analyses. The sex ratio of patients and controls were also different significantly. So, separate multiple analyses after logistic regressions were performed for patient and controls. The allele and genotype frequencies of FABP2 gene in patients were compared to controls by chi-square analysis. The distribution of the genotypes deviates from Hardy-Weinberg equilibrium (HWE). Clinical characteristics of all the subjects were expressed as mean ± SD. Continuous variables were compared between the groups using two-tailed student t-test. Odds ratios (ORs) and 95% CI, with adjustment for age, sex and BMI were calculated using multiple logistic regression analysis. All tests were conducted at the p < 0.05 level of significance.
                      Table 1

                      Demographic characteristics of the study population

                       

                      Controls (n = 460)

                      T2DM (n = 438)

                      p

                      Age (Years)

                      45.99 ± 7.77

                      53.5 ± 10.78

                      <0.0001

                      Weight (kg)

                      76.61 ± 14.52

                      77.37 ± 13.55

                      0.41

                      Height (cm)

                      161.25 ± 8.79

                      161.10 ± 9.30

                      0.80

                      Body mass index (kg/m2)

                      29.22 ± 5.58

                      29.9 ± 5.89

                      0.95

                      Sex: Male/Female

                      (52.6%)/(47.4%)

                      (56.8%)/(43.2%)

                      0.0002

                      SBP (mmHg)

                      114.80 ± 8.04

                      125.83 ± 9.96

                      <0.0001

                      DBP (mmHg)

                      75.81 ± 6.20

                      81.25 ± 4.82

                      0.0001

                      Waist (cms)

                      89.75 ± 14.19

                      95.3 ± 18.96

                      <0.0001

                      Hips (cms)

                      101.75 ± 14.72

                      99.64 ± 16.52

                      0.61

                      FBS (mmol/L)

                      5.23 ± 0.61

                      12.92 ± 4.60

                      <0.0001

                      Triglycerides (mmol/L)

                      1.62 ± 0.86

                      2.24 ± 1.62

                      <0.0001

                      Cholesterol (mmol/L )

                      5.04 ± 0.96

                      5.61 ± 1.26

                      <0.0001

                      HDL-C (mmol/L )

                      0.64 ± 0.23

                      0.84 ± 0.37

                      <0.0001

                      LDL-C (mmol/L)

                      3.66 ± 0.85

                      3.76 ± 1.05

                      0.0008

                      Glucose (mmol/L)

                      5.7 ± 1.2

                      9.4 ± 1.5

                      0.0002

                      Insulin (μU/mL)

                      12.5 ± 1.8

                      16.2 ± 2.2

                      0.0002

                      HOMA-IR

                      3.15 ± 1.9

                      6.8 ± 2.4

                      0.00008

                      Note: Data represented as mean ± SD for continuous variables, pValues for independent t-test are given. A p-value significant at <0.05. NA, Not Analyzed/Not Applicable.

                      Results

                      Clinical characteristics

                      In this case–control study, we have carried out in almost 900 subjects; 438 patients with T2DM (216 females and 244 males, 45.99±7.77 years old) and 460 normal control subjects (200 female and 238 male, 53.5 ± 10.78 years old). The mean age was 60 years for patients and 59 years for the control group. Clinical and anthropometric data are revealed in Table 1 for T2DM patients and control subjects. The results show that T2DM subjects were significantly older than controls but anthropometric measurements and hip were not significant (p > 0.05). T2DM subjects appear to have higher levels of SBP, DBP, fasting glucose, insulin, HOMA-IR and lipid profile and waist (p < 0.05).

                      Genotype frequencies

                      Results for the genotypic distribution of FABP2 A54T polymorphism and the frequency of A and T alleles in patients and controls have been tabulated in Table 2. The genotype distribution for A54T polymorphism showed no deviation from HWE in both the case and control groups (χ 2 = 0.37, p = 0.54). Genotyping of the A54T polymorphism in the FABP2 gene revealed that the allelic frequency of T allele was 0.285 in cases and 0.248 in controls (OR-0.82 (95% CI = 0.67-1.02); p = 0.08). There were no significant differences in both the genotypic and allelic frequencies between the cases as well as controls. However upon multiple logistic regression analysis TT genotype was found to be associated with male patients (OR = 1.24 95% CI = 0.09-0.60, p = 0.001) (Tables 3 and 4). FABP2 genotypic frequencies of A54A, A54T, and T54T were 56.5%, 37.2%, and 6.3% in the control group, 51.52%, 39.81% and 8.66% in the T2DM group; allelic frequencies of Ala and Thr were 0.75 and 0.25 for the control group, 0.71 and 0.29 for the T2DM group. The odds ratio for any genotype of A54T SNP was not significantly related with the risk of developing T2DM in this studied population (for AA + AT vs TT; OR-0.7 (95% CI = 0.42-1.17); p = 0.12 and for TT + AT vs AA; OR-1.22 (95% CI = 0.93-1.59); p = 0.25) from the Saudi population.
                      Table 2

                      Distribution of FABP2 A54T genotypes and alleles of this study

                            Genotype

                      Patients’ n(%)

                      Controls n(%)

                      OR (CI = 95%)

                      P value

                         χ2

                      1 d. f.

                      AA

                      220 (51.52)

                      260 (56.52)

                      1 (reference)

                      1 (reference)

                       

                      AT

                      170 (39.81)

                      171 (37.17)

                      0.85 (0.64-1.12)

                      0.25

                      1.12

                      TT

                      37 (8.66)

                      29 (6.30)

                      0.66 ( 0.39-1.11)

                      0.11

                      2.43

                      A

                      610 (71.42)

                      691 (75.10)

                      1 (reference)

                      1 (reference)

                      T

                      224 (28.57)

                      229 (24.89)

                      0.82 (0.67-1.02)

                      0.08

                      3.06

                      AA + AT vs TT

                        

                      0.7 (0.42-1.17)

                      0.18

                      1.79

                      TT + AT vs AA

                        

                      1.22 (0.93-1.59)

                      0.13

                      2.22

                      The genotypic and allelic frequencies and dominant as recessive models of patients are significantly not different from controls.

                      Table 3

                      Genotypic distribution according to sex

                      Patients

                         
                       

                      AA

                      AT

                      TT

                      Male

                      122

                      95

                      31

                      Female

                      98

                      86

                      6

                      Total

                      220

                      181

                      37

                      Controls

                         

                      Male

                      136

                      95

                      13

                      Female

                      124

                      76

                      16

                      Total

                      260

                      171

                      29

                      Table 4

                      Calculation for the association of A54T genotypes with T2DM patients and control in male and female sexes

                         

                      OR

                      95% CI

                      P Value

                      Patients

                           
                       

                      Genotypes

                         
                       

                      AT

                          
                        

                      Male

                      1 (reference)

                       
                        

                      Female

                       1.1

                      (0.74-1.65)

                      0.62

                       

                      TT

                          
                        

                      Male

                      1 (reference)

                       
                        

                      Female

                       1.24

                      (0.09-0.60)

                      0.001

                      Controls

                           
                       

                      Genotypes

                         
                       

                      AT

                          
                        

                      Male

                      1 (reference)

                       
                        

                      Female

                       0.87

                      (0.59-1.29)

                      0.5

                       

                      TT

                          
                        

                      Male

                         
                        

                      Female

                       1.35

                      (0.62-2.91)

                      0.44

                      OR, Odds ratio, 95% CI-95% confidence interval; multiple logistic regression calculated by SPSS v.19, AA genotype was set as zero because redundancy

                      Discussion

                      FABP2 is an intracellular protein expressed in the villus tips of the small intestine, has a high affinity for saturated and unsaturated long-chain fatty acids and is believed to be involved in the absorption and transport of dietary fatty acids [13]. The association between fatty acid metabolism and IR is well known, and the FABP2 gene has been suggested as a possible candidate gene in the development of IR and T2DM [14]. A54T polymorphism in FABP2 was investigated as a possible genetic factor associated with T2DM and Obesity. Studies examining the association of A54T polymorphism with IR, T2DM and Obesity are contradictory and inconclusive [10]. The product of T allele of FABP2 possesses a greater affinity for long-chain FA than the A allele [15]. In addition, individuals with the T allele of this polymorphism were more insulin resistant than were those with the A allele [12]. The T allele was also shown to be associated with higher plasma levels of LDL-C [16] and dyslipidemia (high plasma concentration of triglycerides and low concentration of HDL-C) [17]. In addition, the T allele of A54T polymorphism has previously been associated with atherothrombotic cerebral infarction in individuals with metabolic syndrome [18] and a parental history of stroke in the Swedish population [19]. Moreover, it was associated with a 2- to 3.5- fold increase in cardiovascular risk in dyslipidemic men with diabetes compared with their dyslipidemic nondiabetic counterparts [20]. We have now shown that A54T polymorphism was not significantly associated with T2DM, with the minor allele representing the risk factor for this condition.

                      In the present study we investigated the association of FABP2 A54T polymorphism with T2DM in a Saudi population. To the best of our knowledge, this is the first study investigating the association of A54T polymorphism in a Saudi population. The frequency of T allele of A54T polymorphism was 0.29 similar to Greek and Caucasian population [2123]. A54T polymorphism was identified via linkage disequilibrium map, as a haploblock spanning 50 kb that includes 22 SNPs. However, the T54 allele is present in only one of six possibilities among the frequent haplotypes (>2%). It is interesting that in this haploblock, there are no other known or putative genes except for FABP2[24].

                      Previous studies of A54T polymorphisms investigated lipid related diseases such as coronary artery disease (CAD) [25]. Canani et al [26] showed that A54T polymorphism confers susceptibility to renal disease in T2DM patients. There are very few reports on the association of this polymorphism with T2DM. Several studies from non-European ethnic backgrounds have reported a positive association between FABP2 variants and T2DM. A54T polymorphism was carried out in relation to multiple diseases and the reports are summarize in Table 5, which shows positive association with T2DM and a combination of other diseases like chronic kidney disease, Microalbminuria, postprandial fatty acids and with the glyburide therapy. In our study, we have examined only T2DM (n = 438) samples and that have not examined its association with other disease.
                      Table 5

                      Association Studies of FABP2 A54T gene polymorphism on different ethnic groups

                      S. No

                      Population

                      Cases

                      Controls

                      Association

                      Disease

                      1

                      Germany

                      -

                      68

                      No

                      Obesity

                      2

                      Japan

                      228

                      813

                      Yes

                      MI + chronic kidney disease

                      3

                      Japan

                      636

                      1106

                      Yes

                      Chronic kidney disease + T2DM

                      4

                      Japan

                      313

                      971

                      Yes

                      Atherothrombic cerebral infarction

                      5

                      Brazil

                      72

                      37

                      Yes

                      T2DM + microalbminuria

                      6

                      Mexico

                      -

                      131

                      No

                      Lipid metabolism

                      7

                      Brazil

                      513

                      529

                      Yes

                      Renal disease + T2DM

                      8

                      Brazil

                      26

                      529

                      Yes

                      Postprandial fatty acids + T2DM

                      9

                      Spain

                      108

                      101

                      Yes

                      Hypercholesterolemic

                      10

                      Present Study

                      438

                      460

                      No

                      T2DM

                      There are several studies denote no association of the T allele with T2DM [2729] and our study is supporting the above mentioned studies. In some studies, subjects were distributed in homozygous for the A allele (AA) and T allele carriers (AT and TT), mainly because there were only few subjects homozygous for the variant [23, 30]. We observed the association of A54T polymorphism with T2DM according to all possible genetic models (i.e. additive, dominant and recessive). No association of A54T polymorphism was found with T2DM according to any genetic model used, a finding shared by other studies that examined such an association [31]. There are limitations to the study design as it is a case–control observational study rather than cross sectional or prospective study. We have chosen only one SNP (A54T) to study the T2DM disease.

                      In conclusion, the present study provides no evidence of any association between A54T polymorphism (rs1799883) in FABP2 gene and T2DM, suggesting that A54T polymorphism is not a major risk factor for the T2DM. Overall, this study indicates that A54T polymorphism could not affect directly the presence of T2DM due to the differential absorption of long chain fatty acids in the presence of the T allele. This is the first study finding the interaction between FABP2 and T2DM in Saudi population. Further functional studies as well as well-characterized larger molecular epidemiological studies are necessary to confirm our findings.

                      Notes

                      Declarations

                      Acknowledgement

                      The author would like to extend their sincere appreciation to the Deanship of Scientific Research at King Saud University for its funding of this research through the Research Group Project no RGP-VPP-244.

                      Authors’ Affiliations

                      (1)
                      Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Saud University
                      (2)
                      Department of Biochemistry, College of Science, King Saud University
                      (3)
                      Biomarkers research programme, Department of Biochemistry, College of Science, King Saud University
                      (4)
                      Department of Food Science and Nutrition, College of Food and Agricultural Sciences, King Saud University
                      (5)
                      Stem Cell unit, Department of Anatomy, College of Medicine, King Khalid University Hospital
                      (6)
                      Prepratory Year, Saudi Electronic University
                      (7)
                      Department of Biology Science, College of Science and Arts, Al-Qassim University

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                      This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://​creativecommons.​org/​licenses/​by/​4.​0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated.

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