Literature DB >> 23666056

Polymorphic genetic variation in immune system genes: a study of two populations of Espirito Santo, Brazil.

Raquel Spinassé Dettogni1, Ricardo Tristão Sá, Thaís Tristão Tovar, Iúri Drumond Louro.   

Abstract

Mapping single nucleotide polymorphisms (SNPs) in genes potentially involved in immune responses may help understand the pathophysiology of infectious diseases in specific geographical regions. In this context, we have aimed to analyze the frequency of immunogenetic markers, focusing on genes CD209 (SNP -336A/G), FCγRIIa (SNP -131H/R), TNF-α (SNP -308A/G) and VDR (SNP Taq I) in two populations of the Espirito Santo State (ES), Brazil: general and Pomeranian populations. Peripheral blood genomic DNA was extracted from one hundred healthy individuals of the general population and from 59 Pomeranians. Polymorphic variant identification was performed by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). SNP genotype frequencies were in Hardy-Weinberg Equilibrium. There was no statistically significant difference in allelic and genotypic distributions between the two populations studied. Statistically significant differences were observed for SNP genotype distribution in genes CD209, TNF-α and VDR when comparing the ES populations with other Brazilian populations. This is the first report of CD209, FcγRIIa, TNF-α and VDR allelic frequencies for the general and Pomeranian populations of ES.

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Year:  2013        PMID: 23666056      PMCID: PMC7088621          DOI: 10.1007/s11033-013-2582-7

Source DB:  PubMed          Journal:  Mol Biol Rep        ISSN: 0301-4851            Impact factor:   2.316


Introduction

Small genetic variations such as SNPs can influence gene expression and change protein structure or function. SNPs located in the promoter or other regulatory regions may affect gene transcription and alter variability in the immune response. The presence of certain alleles may contribute to the susceptibility or host resistance for different infectious diseases caused by viruses [1], bacteria [2] and protozoa [3-5]. SNPs in genes CD209, FcγRIIa, TNF-α and VDR affect the immune response for various infections [1, 6–8]. Gene and protein nomenclature are shown in Table 1.
Table 1

SNPs associated with response to infectious diseases

GeneProteinSNPrs numberReference alleleVariant allele
CD209Dendritic cell-specific−336 A/G4804803AG
FcγRIIaFc gama−131 H/R1801274AG
TNF-αTumor necrosis factor−308 A/G1800629GA
VDRVitamin D receptorTaq I731236TC
SNPs associated with response to infectious diseases Dendritic cell-specific ICAM-3 grabbing non-integrin (DC-SING, encoded by CD209) is mainly expressed in dendritic cells (DC) and plays an important role in some infectious diseases [9-11]. DCs can be targets for pathogens, in an attempt to impair the initial immune response in early infection [12]. Among SNPs in the CD209, the guanine (G) to adenine (A) transition at position 2336 within the CD209 gene promoter (SNP -336 A/G) has been suggested to affect transcriptional activity of DC-SIGN [8]. Association studies have been performed between CD209 gene polymorphisms and pathogens: viruses such as human immunodeficiency virus-1 (HIV-1), hepatitis C virus (HCV), cytomegalovirus, Ebola virus and SARS-coV; bacteria such as Mycobacterium tuberculosis and parasites such as Leishmania and Schistosoma mansoni [13-17]. SNP -336A/G has been associated with the susceptibility to HIV [18], M. tuberculosis [19], HCV [20], and dengue [8]. Fcγ leukocyte receptors are essential for the immune defense against pathogens. Antibody binding to the Fc-receptors causes important biological consequences, e.g. antibody dependent cell-mediated cytotoxicity or inhibition and phagocytosis [21]. FcγRIIa has two co-dominantly expressed alleles, R131 (G at position 494) and H131 (A at position 494), which differ in their ability to bind immunoglobulin G (IgG) subclasses. Cells expressing H131 bind more efficiently to IgG2 and IgG3 than those expressing the R131 variant [22]. This SNP has been associated with susceptibility and severity of some infectious disease such as meningococcal disease, Streptococcus pneumoniae infections, dengue fever and HIV infection [1, 23–25]. RR genotype seems to be associated with protection against intracellular pathogen infections [2, 26, 27]. TNF-α is a pleiotropic pro-inflammatory cytokine, with effects on apoptosis and activation of target cells involved in the amplification of immunological cellular processes [28]. Among several TNF-α gene polymorphisms, the SNP located at nucleotide position 308 (G or A) has been shown to directly affect TNF-α expression [29]. The AA genotype has been significantly associated with higher TNF-α production and in some cases with increased morbidity and mortality in sepsis, malaria, chronic obstructive pulmonary disease (COPD), leishmaniosis, systemic lupus erythematosus (SLE), type 1 autoimmune hepatitis and other immune mediated disorders (asthma and contact dermatitis) [30-34]. The vitamin D receptor (VDR) mediates the immunoregulatory effects of the hormonal form of vitamin D, which includes activating monocytes, stimulating cellular immune responses, suppressing immunoglobulin production and lymphocyte proliferation [35]. The TT genotype of VDR Taq I SNP (substitution of a thymine (T) for a cytosine (C) at position 352) [36] has been recently associated with tuberculoid leprosy, enhanced clearance of hepatitis B infection and resistance to pulmonary tuberculosis [37, 38]. SNP frequency characterization of genes encoding immune mediators may aid in the creation of alternative methods for diagnosis, vaccine development or more effective therapies according to the population genetic profile. SNP frequencies are population specific, reason because we decided to characterize the general population and the Pomeranian subpopulation of ES, Brazil, for 4 SNPs in immune system genes.

Materials and methods

This study was approved by the Research Ethics Committee of the Federal University of ES and all patients signed an informed consent (Protocol n°190/11).

Sample

Five milliliters (ml) of peripheral blood were collected from 100 healthy volunteers of the ES general population. As for the 59 healthy Pomeranian volunteers of Santa Maria de Jetibá, ES, 3–5 peripheral blood drops were collected on FTA® Elute Cards (Whatman, USA).

SNP genotyping

Genomic DNA was isolated using phenol/chloroform extraction or following FTA® Elute Card manufacturer’s recommendations (Whatman, USA). CD209, FcγRIIa, TNF-α and VDR alleles were detected by PCR–RFLP. Primer sequences, restriction enzymes and conditions are shown in Table 2.
Table 2

Primer sequences and RFLP conditions

GeneSNPPrimer sequenceProduct sizeRestriction enzymeDigestion patternReference
CD209−336 A/G (rs4804803)

5′-CAGAGCATG GACAGG GAGCAAG-3′

5′- GGATGTACGTCTGCAGTGTG-3′

150 bpMscI

Allele G—19 bp + 131pb

Allele A—150 bp

[8]
FcγRIIa−131 H/R (rs1801274)

5′- GGAAAATCCAGAAATTCTCGC-3′

5′- CAACAGCCTGACTACCTATTACGCGGG-3′

366 bpBstUI

Allele H—343 bp

Allele R—322 bp

[39]
TNF-α−308 A/G (rs1800629)

5′- AGGCAATAGGTTTTGAGGGCCAT-3′

5′- TCCTCCCTGCTCCGATTCCG-3′

107 bpNcoI

Allele A—107 bp

Allele G—87 bp + 20 bp

[40]
VDRTaq I (rs731236)

5′-CAGAGCATGGACAGGGAGCAAG-3′

5′-GGATGTACGTCTGCAGTGTG-3′

340 bpTaqI

Allele T—340 bp

Allele C—293 bp + 47pb

[41]

bp base pairs

Primer sequences and RFLP conditions 5′-CAGAGCATG GACAGG GAGCAAG-3′ 5′- GGATGTACGTCTGCAGTGTG-3′ Allele G—19 bp + 131pb Allele A—150 bp 5′- GGAAAATCCAGAAATTCTCGC-3′ 5′- CAACAGCCTGACTACCTATTACGCGGG-3′ Allele H—343 bp Allele R—322 bp 5′- AGGCAATAGGTTTTGAGGGCCAT-3′ 5′- TCCTCCCTGCTCCGATTCCG-3′ Allele A—107 bp Allele G—87 bp + 20 bp 5′-CAGAGCATGGACAGGGAGCAAG-3′ 5′-GGATGTACGTCTGCAGTGTG-3′ Allele T—340 bp Allele C—293 bp + 47pb bp base pairs

Statistical analysis

SNP allele and genotype frequencies were determined by direct counting. P values <0.05 were considered statistically significant. Chi square test was used to determine whether a genotype was at HWE, using Chi square HWE equilibrium test calculator for biallelic markers (http://www.genes.org.uk/software/hardy-weinberg.shtml). Fisher’s exact test was performed using Graphpad Prism version 5.0 (www.graphpad.com).

Results

Representative genotyping results are shown in Figs. 1, 2, 3 and 4.
Fig. 1

CD209 genotypes. a amplified DNA products. b MscI digestion of PCR products. bp base pairs; Ladder: 25 bp molecular weight marker

Fig. 2

FcγRIIa genotypes. a amplified DNA products and BstUI PCR product digestion. bp base pairs; Ladder: 25 bp molecular weight marker

Fig. 3

TNF-α genotypes. a amplified DNA products. b NcoI digestion of PCR products. bp base pairs; Ladder: 25 bp molecular weight marker

Fig. 4

VDR genotypes. a amplified DNA products. b Taq I digestion of PCR products. bp base pairs; Ladder: 25 bp molecular weight marker

CD209 genotypes. a amplified DNA products. b MscI digestion of PCR products. bp base pairs; Ladder: 25 bp molecular weight marker FcγRIIa genotypes. a amplified DNA products and BstUI PCR product digestion. bp base pairs; Ladder: 25 bp molecular weight marker TNF-α genotypes. a amplified DNA products. b NcoI digestion of PCR products. bp base pairs; Ladder: 25 bp molecular weight marker VDR genotypes. a amplified DNA products. b Taq I digestion of PCR products. bp base pairs; Ladder: 25 bp molecular weight marker SNP allele and genotype frequencies for genes CD209, FcγRIIa, TNF-α and VDR in the Pomeranian and general populations of ES are given in Table 3. All polymorphisms were at HWE equilibrium among Pomeranian and non-Pomeranian individuals (p > 0.05, Table 4). Genotype and allele frequencies were not significantly different between the two populations (p > 0.05, Table 5).
Table 3

Allele and genotype SNP frequencies

Allele/genotypeGeneral population (n = 100)Pomeranian population (n = 59)
CD209: −336 A/G
A62.5 (125)80.5 (95)
G37.5 (75)19.5 (23)
AA61 (61)66.1 (39)
AG36 (36)28.8 (17)
GG3 (3)5.1 (3)
FcγRIIa: −131 H/R
H48 (96)50.8 (60)
R52 (104)49.2 (58)
HH21 (21)22 (13)
HR54 (54)57.6 (34)
RR25 (25)20.4 (12)
TNF-α: −308 A/G
A20 (40)17.8 (21)
G80 (160)82.2 (97)
AA5 (5)3.4 (2)
AG30 (30)28.8 (17)
GG65 (65)67.8 (40)
VDR: Taq I
T63.5 (127)66.1 (78)
C36.5 (73)33.9 (40)
TT41 (41)44.07 (26)
TC45 (45)44.07 (26)
CC14 (14)11.9 (7)

Numbers in parenthesis represents allele or genotype counts

Table 4

p- and x2 values for HWE calculations in both populations was performed by x2-test

Gene/SNPX2/p value (General population)X2/p value (pomeranian population)
CD209/−336 A/G0.72/0.400.40/0.53
FcγRIIa/−131 H/R0.67/0.411.38/0.24
TNF-α/−308 A/G0.39/0.530.01/0.92
VDR/Taq I0.09/0.760.02/0.89
Table 5

Allele and genotype frequencies, p value calculated by Fischer’s exact test

Genotype/Allele p value (General population vs. Pomeranians)
CD209: −336 A/G
A and G0.32
AA0.61
AG0.39
GG0.67
FcγRIIa: −131 H/R
H and R0.64
HH1.0
HR0.74
RR0.57
TNF-α: −308 A/G
A and G0.66
GG0.86
AG1.0
AA1.0
VDR: Taq I
T and C0.72
TT0.74
TC1.0
CC0.81
Allele and genotype SNP frequencies Numbers in parenthesis represents allele or genotype counts p- and x2 values for HWE calculations in both populations was performed by x2-test Allele and genotype frequencies, p value calculated by Fischer’s exact test

Discussion

This study aimed to characterize the general and Pomeranian populations of ES, Brazil as for 4 SNPs in genes important for the immune response to infections. Allelic frequencies for all SNPs were in HWE equilibrium. There was no statistically significant difference in allelic and genotypic distributions between the two populations. This result confirms data of Stur et al. [42] which reported gene flow between the general and Pomeranian populations of ES. For each SNP, we analyzed the difference in genotype distribution among ES populations and two other populations of different ethnic groups randomly selected and a population of southeast Brazil (Table 6).
Table 6

SNPs frequencies in association studies of various ethnic groups (healthy individuals). P values calculated by Fischer’s exact test

SNPPopulationSample sizeGenotypeFrequency p value (population of column 2 vs. general population of ES) p value (population of column 2 vs. pomeranian population of ES)Reference
CD209: −336 A/GTaiwanese120AA111<0.0001*<0.0001*[43]
AG9<0.0001*0.0004*
GG00.10.03*
South African360AA137<0.0001*<0.0001*[19]
AG1560.210.04*
GG67<0.0001*0.008*
Brazilian (Sao Paulo)32AA180.680.37[44]
AG90.521.0
GG50.02*0.12
FcγRIIa: −131 H/RAfrican American170HH440.380.6[45]
HR730.10.07
RR530.330.13
Caucasian220HH690.060.15
HR970.10.08
RR541.00.6
Brazilian (Sao Paulo)48HH130.410.65[22]
HR250.20.7
RR100.681.0
TNF-α: −308 A/GItalian138GG1090.02*0.1[6]
GA290.130.27
AA00.01*0.09
American (USA)235GG1640.440.75[46]
GA670.791.0
AA40.130.35
Brazilian (Minas Gerais)43GG290.851.0[47]
GA140.840.83
AA00.320.51
VDR: Taq IVietnamese247TT231<0.0001*<0.0001*[1]
TC15<0.0001*<0.0001*
CC1<0.0001*<0.0001*
Indian143TT700.240.54[48]
TC620.891.0
CC110.130.42
Brazilian (Rio de Janeiro)40TT290.001*0.007*[49]
TC70.003*0.009*
CC40.781.0

* Statistically significant values

SNPs frequencies in association studies of various ethnic groups (healthy individuals). P values calculated by Fischer’s exact test * Statistically significant values CD209 gene SNP showed a significant difference in genotype distribution between the ES populations separately, as well as when they were compared with the population of Taiwan and South Africa. Moreover, the GG genotype had a significant difference in distribution between the general ES and Sao Paulo populations. FcγRIIa SNP genotype distribution was not different among ES populations and other populations analyzed. Comparing TNF-α SNP genotype frequencies among ES populations and other 3 populations, there was a statistically significant difference in homozygous genotypes distribution between the general ES population and Italians. VDR SNPs showed a significant difference in genotype distribution among ES populations and populations of Rio de Janeiro and Vietnam. These variations indicate the need to characterize specific populations for SNP composition in genes important for the immune system in various regions of the world. The ES state, as well as the entire southeastern Brazil, presents high prevalence of many infectious diseases. Thus, assessing the genetic diversity of immune system components may generate knowledge relevant to the understanding of how the population responds to infectious diseases such as dengue, tuberculosis, hepatitis, malaria, HIV and others.
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