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https://doi.org/10.17795/gct-24756

Allele Frequency of D12S1632, D12S329, D12S96, D16S3096 and D16S2624 in four Ethnic Groups and Its Relationship With Metabolic Syndrome in Tehran Lipid and Glucose Study

Author(s):
Maryam Sadat DaneshpourMaryam Sadat Daneshpour1,*, Massoud HoushmandMassoud Houshmand2, Suad AlfadhliSuad Alfadhli3, Maryam ZarkeshMaryam Zarkesh1, Sirous ZeinaliSirous Zeinali4, Mehdi HedayatiMehdi Hedayati1, Fereidoun AziziFereidoun Azizi5
1Cellular and Molecular Endocrine Research Center, Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, IR Iran
2Department of Medical Genetics, National Institute for Genetic Engineering and Biotechnology, Tehran, IR Iran
3Department of Medical Laboratory Sciences, Faculty of Allied Health Sciences, Kuwait University, Kuwait City, Kuwait
4Biotechnology Research Centre, Pasteur Institute of Iran, Teheran, IR Iran
5Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, IR Iran
Gene, Cell and Tissue:Vol. 1, issue 3; e24756
Published online:Oct 14, 2014
Article type:Research Article
Received:Oct 22, 2014
Accepted:Nov 01, 2014
How to Cite:Daneshpour MS, Houshmand M, Alfadhli S, Zarkesh M, Zeinali S, et al. Allele Frequency of D12S1632, D12S329, D12S96, D16S3096 and D16S2624 in four Ethnic Groups and Its Relationship With Metabolic Syndrome in Tehran Lipid and Glucose Study. Gene Cell Tissue. 2014;1(3):e24756. doi: https://doi.org/10.17795/gct-24756

Abstract

Background:

Variation in drug resistance and susceptibility to various diseases may be related to difference in allele frequencies of the variants at the population level.

Objectives:

The present study aimed to investigate the allele frequencies of five short tandem repeats (STR) loci in two different chromosomes of candidates from Tehran Lipid and Glucose Study.

Materials and Methods:

For this study, a representative sample of 563 individuals (130 affected by metabolic syndrome) from Tehran, including four different ethnic groups of Iran, was selected. Five STRs including D12S1632, D12S329, D12S96, D16S3096 and D16S2624 were analyzed using the fragment analysis method. Allele frequency, polymorphism information content (PIC) values, observed and expected heterozygosity, discrimination power, matching probability, power of discrimination, power of exclusion and paternity index were calculated for the whole sample.

Results:

There was no significant deviation in allelic frequencies from Hardy-Weinberg equilibrium for all the studied markers except for D12S1632 and D12S329. The long alleles in D12S329 were significantly more frequent in patients with metabolic syndrome (P < 0.05).

Conclusions:

This study revealed allele frequency of some STRs on chromosome 12 and 16 for the first time in Iran, and indicated differences between subjects with metabolic syndrome and subjects in the control group.

Keywords
Chromosome 12
Chromosome 16
Allele Frequency
Ethnic Groups
Iran

1. Background

Analyzing genome variation is the most popular research in the field of genetic. This variation plays an important role in drug response and prediction of the disease (1). The Iranian population consists of around seventy million individuals consisting of people of many religions and ethnic backgrounds cemented by the Persian culture. Ethnic groups include Persians (51%), Azeris (24%), Gilaki and Mazandarani (8%), Kurds (7%), Arabs (3%), Baluchi (2%), Lurs (2%), Turkmens (2%) and others (1%) (2). These ethnic groups may have variations in their DNA sequences. The study of variations in DNA sequence is valuable when it is performed among individuals within the same population or among different populations. Tehran Lipid and Glucose Study (TLGS) is a prospective study of more than 15000 individuals (3-74 years) that live in the 13th district of Tehran Metropolitan. This study aims to develop population-based measures to alter the life-style and prevent the rising trend of non-communicable diseases. Furthermore, TLGS also aims to identify and tackle the risk factors for non-communicable diseases in a representative sample of individuals residing in Tehran, who were recruited by a stratified cluster sampling method (3, 4). Metabolic syndrome is a combination of medical disorders that increases the risk of developing cardiovascular disease and diabetes (5). The prevalence of the metabolic syndrome is 32% in adults (6) and 10% in adolescents (7). In the present study, we aimed to determine the allele frequency of five microsatellite markers on chromosome 12 and 16, and to observe possible differences in the genetic patterns among several ethnic groups. In addition, this study investigated genetic variation between people with and without the metabolic syndrome.

2. Objectives

This article reports primary results in the form of allele frequency distributions and summary statistics of five different autosomal STR loci.

3. Materials and Methods

Population: based on the frequency of metabolic syndrome, a total of 563 individuals aged 3-87 were randomly selected from the TLGS for analyzing the allele frequency of four microsatellite markers on chromosome eight. All subjects answered a questionnaire covering data on demographic factors, smoking habits and other relevant information. Written informed consent was obtained from each subject. The research council of the Endocrine Research Center of the Shahid Beheshti University of Medical Sciences (M.C) approved this study.

3.1. Ethnic Groups

Four ethnic groups were included: Persian (68%), Turk (18.3%), Mazani/Gilaki (8%) and Kurd/Lur (6.2%). To simplify the analysis, the Mazani and Gilaki (people of northern Iran) and the Lur and Kurd (people of western Iran) were combined.
Metabolic syndrome was defined as a cluster of metabolic risk factors for cardiovascular diseases and type 2 diabetes mellitus. Metabolic syndrome X consists of the following complications, excess abdominal fat, atherogenic dyslipidemia, hypertension, hyperglycemia, insulin resistance, a proinflammatory state and a prothrombotic (thrombosis) state (8).
The following phenotypic measurements were obtained for each subject: body mass, body mass index (BMI), height and blood pressure. Blood samples were collected in EDTA containing tubes and serum in tubes without any anticoagulant. After centrifugation for 10 minutes at 3000 rpm, sera were separated and stored at -70°C in 1.5 mL aliquots. Serum glucose, total cholesterol, high-density lipoprotein-cholesterol (HDL-C) and triglyceride levels were measured immediately from fresh sera as described previously (9). Serum HDL-C levels were measured after precipitation of Apo B containing lipoproteins with dextran-magnesium sulfate (10). Low-density lipoprotein-cholesterol (LDL-C) and very low-density lipoprotein (VLDL) concentrations in samples with serum triglyceride levels < 400 mg/dL were calculated using Friedewald’s equation, and one fifth of triglyceride level, respectively (11). Coefficients of variation (CV) for total cholesterol, HDL-C and triglyceride measurements were below 5%.

3.2. DNA Analysis

When genomic DNA was extracted by the proteinase K and salting out standard method, buffy coats were separated from the non coagulated blood samples and stored at -70°C until processing (12). The GeneAmp PCR System 9700 (ABI USA) was used to simultaneously amplify the five STRs loci including D12S1632, D12S329, D12S96, D16S3096 and D16S2624. The characteristics of STRs loci are presented in Table 1. Four out of five have dinucleotide repeats and one has a tetranucleotide repeat. Amplification was performed using 100 ng of total genomic DNA in a final volume of 25 L containing 5 pmol of each primer and gold mix of Taq polymerase (ABI USA).
The amplification conditions were as follows: 95ËšC for 11 minutes, followed by 30 cycles of 30 seconds at 94ËšC, 60 seconds at 55ËšC and 40 seconds at 72ËšC, and ending with a single 30-minute extension step at 72ËšC. Electrophoresis of the amplification products was performed on an ABI 3100 Genetic Analyzer (Applied Biosystems Co.). The raw data were analyzed by the ABI Data Collection Software and GeneMapper 3.2 (Applied Biosystems). For quality control laboratory internal control standards were used.
Table 1. Characteristics of the Three STRs Loci
LocusLocationRepeats UnitSequence of PrimersPolymorphic Region
D12S9612q13.13[CA]nCCAGTTCAAACCAGTGACCT Labeled with (PET)201-227
TCCATCCTTGTGGGCA
D12S163212q13.2[TG]nGCCTAATCAAGATGTCACCA Labeled with (VIC)208-230
GCTAGGGAGCCAATTCA
D12S32912q14.2[GT]nAAGCAATCAGCCAGCCCT Labeled with (NED)143-171
TGTCAGAACCTAACAACCCAGAAAG
D16S262416q22.3[ATCT]nTGAGGCAATTTGTTACAGAGC Labeled with (6-FAM)130-148
TAATGTACCTGGTACCAAAAACA
D16S309616q23.1[GT]nGATCTGGCTTACGATGATTTCTAAC Labeled with (PET)199-229
CCGTGATGATGTCTGCAAC

3.3. Statistical Analysis

Explanatory statistics were used for population characteristics and data are shown as mean ± standard deviation for normally distributed variables and as percentages for categorical variables. Differences between ethnic groups were evaluated by Student's t-test for normally distributed data. The distribution of the triglycerides was skewed, and a comparison was performed using Mann–Whitney’s U-test. Analysis of categorical variables was performed by Chi-square and Fisher’s exact tests for contingency tables. Allele frequency and polymorphic information content (PIC) values were computed by the PowerMarker software (13, 14). Deviation from Hardy-Weinberg equilibrium, as well as observed and expected heterozygosity, were calculated using the GenePop software Version 3.4 (15). The Excel PowerStats spreadsheet from promega (16) was used to calculate discrimination power, matching probability, power of discrimination, power of exclusion and paternity index.

4. Results

The demographic and biochemical parameters of 563 participants consisting of 270 men and 293 women with the mean age of 36 ± 19 are shown in Table 2. There were no statistically significant differences between ethnic groups in biochemical characteristics related to the metabolic syndrome. The allele frequencies for the five STRs loci in 563 unrelated Tehranian samples are presented in Table 3. The most polymorphic marker is D16S2624, this marker has a wide range of size with seven different alleles. Sample populations were observed to be in Hardy-Weinberg Equilibrium (HWE) for all analyzed markers (P < 0.05), except for D12S1632 and D12S329. Some factors such as: matching probability, power of discrimination, power of exclusion and paternity index were calculated for this population. Allele frequency distribution in these five microsatellites in four ethnic groups are presented in Figures 1-2 the details of the allele frequencies, matching probability, power of discrimination, power of exclusion and paternity index in each ethnic group are presented in Table 4.
A) D12S96; B) D12S1632; C) D12S329.
Figure 1.

A) D12S96; B) D12S1632; C) D12S329.

A) D16S3096; B) D16S2624.
Figure 2.

A) D16S3096; B) D16S2624.

For the D12S96 microsatellite, a total of 11 alleles were observed in the 563 subjects. These were named 201-227 (PCR product length), which correspond to 6-32 (CA)n repeats, respectively. The microsatellite length was used to subdivide samples into two groups according their size: [short (≤ 213), long (> 217)]; [short (≤ 207), medium (207-221) and long (≥ 221)] for case-control analysis. For the D12S1632 microsatellite, a total of 10 alleles were observed in 563 subjects. These were named 208-230 (PCR product length), which corresponded to 4-15 (TG)n repeats, respectively. The microsatellite length was used to subdivide samples into two groups according their size: [short (≤ 220), long (> 220)]; [short (≤ 216), medium (218-222), long (≥ 224)] for case-control analysis. For the D12S329 microsatellite, a total of 10 alleles were observed in 563 subjects. These were named 143-171 (PCR product length), which corresponded to 11-25 (GT)n repeats, respectively. The microsatellite length was used to subdivide samples into two groups according their size: [short (≤ 157), long (> 159)]; [short (≤ 153), medium (155-161), long (≥ 163)] for case-control analysis. For the D16S2624 microsatellite, a total of six alleles were observed in 563 subjects. These were named 130-148 (PCR product length), which corresponded to 9.2-14 (ATCT)n repeats, respectively. The microsatellite length was used to subdivide samples into two groups according their size: [short (≤ 136), long (> 140)]; [short (≤ 136), medium (136-140), long (≥ 140)] for case-control analysis. Finally, for the D16S3096 microsatellite, a total of 17 alleles were observed in 563 subjects. These were named 199-229 (PCR product length), which corresponded to 14-29 (GT)n repeats, respectively. The microsatellite length was used to subdivide samples into two groups according their size: [short (≤ 215), long (> 216)]; [short (≤ 209), medium (209-219), long (≥ 219)] for case-control analysis. The allele frequencies of the control and the metabolic syndrome groups were compared for the four microsatellites subdivided in three groups (short, medium and long). In the D12S329, the frequency of long alleles in subjects with metabolic syndrome was significantly higher than the controls (P < 0.05) (Table 5). In Table 6 the allele frequencies of the four different ethnic groups were compared for the five microsatellites in two subdivided groups (short and long) and were significantly different.
Table 2. Demographic and Biochemical Parameters of 563 Participants According to Ethnic Groups a
CharacteristicTotal (n = 563)Persian (n = 380)Turk (n = 103)Mazani/Gilaki (n = 45)Kurd/Lur (n = 35)
Metabolic syndrome130 (28)82 (21.5)23 (22.3)11 (24.5)14 (40)
Age, y36 ± 1935 ± 1937 ± 1938 ± 1839 ± 20
Sex, females, %5251.349.553.368.6
BMI, kg/m2
Women25 ± 626 ± 626 ± 527 ± 726 ± 6
Men25 ± 525 ± 525 ± 525 ± 529 ± 5
Family history of diabetes, %7.38.03.98.98.8
Components of metabolic syndrome
Waist circumference, cm
Women83 ± 1583 ± 1584 ± 1686 ± 1584 ± 16
Men90 ± 1589 ± 1590 ± 1388 ± 14100 ± 12
Fasting plasma glucose, mg/dL95 ± 2995 ± 3092 ± 19100 ± 3793 ± 19
Elevated blood pressure, mmHg
Systolic113 ± 29113 ± 20113 ± 19112 ± 20117 ± 25
Diastolic71 ± 1170 ± 1069 ± 1170 ± 1074 ± 13
Serum triglycerides, mg/dL140 ± 87137 ± 79143 ± 90154 ± 130148 ± 83
HDL cholesterol, mg/dL
Women47 ± 147 ± 1146 ± 1148 ± 1247 ± 12
Men41 ± 941 ± 940 ± 9473 ± 1235 ± 7

aData are presented as Means ± SD, No. (%) or %.

Table 3. Allele Frequencies for Five STRs Loci in 563 Unrelated Tehranian Samples a
RepeatD16S2624D16S3096D12S1632D12S329D12S96
20.0009
30.0009
40.0333
60.0026
70.0144
80.11800.0212
90.3793
9.20.0111
100.19080.18110.5053
110.32280.12520.0017
120.27850.11440.0362
130.16950.0162
140.02560.00450.0072
150.00170.00090.00900.0693
160.12030.0197
170.03050.0094
180.31420.36220.0097
190.01710.3416
200.00180.0873
210.02960.0771
220.01800.02910.0362
22.10.0036
230.0637
240.10590.2046
250.26210.0026
260.01080.0935
270.0108
280.00360.0309
290.0027
300.0556
320.0044
PIC0.71000.77500.75250.69180.6558
Ho0.83950.80720.79000.77360.6474
He0.75230.79860.77400.73700.6859
MP0.11740.07280.07780.11700.1393
PD0.88260.92720.92220.88300.8607
PE0.65840.63410.56930.53650.3539
PI2.96462.75742.31252.13141.4246
P0.00600.00000.88000.98500.0000

aAbbreviations: Hobs, Observed heterozygosity; Hexp, expected heterozygosity; MP, matching probability; PIC, Polymorphic information content; P, probability value of exact tests of Hardy-Weinberg disequilibrium; PD, discrimination power; PE, power of exclusion; PI, paternity index.

Table 4. Details of Allele Frequencies in Four Ethnic Groups a
PersianAzeriMazani/GilakiKurd/Lur
D12S96
MP0.1330.2020.1520.189
PD0.8670.7980.8480.811
PIC0.6750.5730.6400.579
PE0.3540.2700.4220.412
PI1.431.201.641.61
Allele Frequencies
Homozygotes, %35.141.730.431.0
Heterozygotes, %64.958.369.669.0
Total Alleles7242069258
D12S329
MP0.1160.1490.1050.157
PD0.8840.8510.8950.843
PIC0.7030.6330.6920.681
PE0.5510.4530.5290.643
PI2.211.762.092.83
Allele Frequencies
Homozygotes, %22.728.423.917.6
Heterozygotes, %77.371.676.182.4
Total Alleles7502049268
D12S1632
MP0.0840.0790.1160.090
PD0.9160.9210.8840.910
PIC0.7430.7610.7380.791
PE0.5860.5320.5000.588
PI2.412.111.952.43
Allele Frequencies
Homozygotes, %20.723.725.620.6
Heterozygotes, %79.376.374.479.4
Total Alleles7141948668
D16S2624
MP0.1260.1080.1450.168
PD0.8740.8920.8550.832
PIC0.6950.7390.6740.651
PE0.6430.7790.5290.588
PI2.834.642.092.43
Allele Frequencies
Homozygotes, %17.710.823.920.6
Heterozygotes, %82.389.276.179.4
Total Alleles7582049268
D16S3096
MP0.0760.0830.1110.130
PD0.9240.9170.8890.870
PIC0.7740.7530.7190.666
PE0.6700.5310.5910.510
PI3.082.102.442.00
Allele Frequencies
Homozygotes,%16.223.820.525.0
Heterozygotes, %83.876.279.575.0
Total Alleles7142028856

aAbbreviations: MP, matching probability; PIC, Polymorphic information content; PD, discrimination power; PD, power of discrimination; PE, power of exclusion; PI, paternity index.

Table 5. Allele Frequencies of People with and Without Metabolic Syndrome
Non Metabolic SyndromeMetabolic Syndrome
D12S96
Short allele0.5581 (480)a0.5977 (159)
Medium allele0.2465 (212)0.2481 (66)
Long allele0.1953 (168)0.1541 (41)
D12S329
Short allele0.0887 (79)0.0919 (25)
Medium allele0.8146 (725)b0.7610 (207)
Long allele0.0966 (86)0.1470 (40)
D12S1632
Short allele0.0305 (26)0.0465 (12)
Medium allele0.5176 (441)0.4961 (128)
Long allele0.4518 (385)0.4573 (118)
D16S3096
Short allele0.1662 (140)0.1893 (50)
Medium allele0.2220 (187)0.2234 (59)
Long allele0.6116 (515)0.5871 (155)
D16S2624
Short allele0.5339 (441)0.5233 (135)
Medium allele0.2772 (229)0.2752 (71)
Long allele0.1889 (156)0.2016 (52)

aNumber in parenthesis denote number of subjects

bLong allele frequency vs. medium allele frequency, significance at P < 0.001 by the Chi-square test.

Table 6. Allele Frequencies in Four Ethnic Groups
MarkerPersianAzeriMazani/GilakiKurd/Lur
D12S96a
Short allele0.5360 (387)b0.6747 (139)0.5888 (53)0.5689 (33)
Long allele0.4639 (335)0.3252 (67)0.4111 (37)0.4310 (25)
D12S329
Short allele0.4558 (341)0.4460 (91)0.5333 (48)0.4264 (29)
Long allele0.5441 (407)0.5539 (113)0.4666 (42)0.5735 (39)
D12S1632
Short allele0.5407 (385)0.5721 (111)c0.5714 (48)0.4411 (30)
Long allele0.4592 (327)0.4278 (83)0.4285 (36)0.5588 (38)
D16S3096
Short allele0.4747 (338)d0.5396 (109)e0.4069 (35)f0.6250 (35)
Long allele0.5252 (374)0.4603 (93)0.5930 (51)0.3750 (21)
D16S2624
Short allele0.5489 (415)g0.4754 (97)0.5222 (47)0.5147 (35)
Long allele0.4510 (341)0.5245 (107)0.4777 (43)0.4852 (33)

aNumber in parenthesis denote number of subjects.

bPersian allele frequency vs. Azeri allele frequency, significance at P < 0.001 by the Chi-square test.

cAzeri allele frequency vs. Kurd/Lur allele frequency, significance at P < 0.001 by the Chi-square test.

dPersian allele frequency vs. Kurd/Lur allele frequency, significance at P < 0.001 by the Chi-square test.

eAzeri allele frequency vs. Mazani/Gilaki allele frequency, significance at P < 0.001 by the Chi-square test.

fKurd/Lur allele frequency vs. Mazani/Gilaki allele frequency, significance at P < 0.001 by the Chi-square test.

gPersian allele frequency vs. Azeri frequency, significance at P < 0.001 by the Chi-square test.

5. Discussion

This study is the first allele frequency report related to chromosomes 12 and 16 in the Iranian population. Based on our knowledge there has been no allele frequency data for our selected microsatellite on chromosome 12. To confirm the new allele in D16S2624, the ALFERED database was accessed. Furthermore, in subjects with metabolic syndrome, the long alleles were significantly more frequent in D12S329 (P < 0.05). Between the different ethnic groups there were some differences in short and long allele frequencies. D16S2624 is a tetra nucleotide repeat marker but in this population one new allele (15.2) was seen. The most heterozygote marker in the total population and in different ethnic groups was D16S2624. The power of discrimination ranged from a minimum of 0.798 for D12S96 locus in the Azeri group to a maximum of 0.924 for D16S3096 locus in the Persian group. In the Iranian population, the distribution of the analyzed loci alleles was not previously studied. The present dataset will add to the reference database and will be helpful in population genetics and diversity studies. Differences between medium and long allele frequencies in D12S329 of subjects with metabolic syndrome in comparison with controls may be a sign of association between this region and the presence of the metabolic syndrome. Further analysis with more microsatellites in this region can lead us to the genetic cause of metabolic syndrome. Ethnic groups have some variation in allele frequency but the sample size was not big enough to reach a comprehensive conclusion. In the future the most important markers in this population have to be checked in order to improve knowledge regarding the genetic pattern of the Iranian population.

Acknowledgments

Footnotes

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