DC-SIGN (CD209), pentraxin 3 and vitamin D receptor gene variants associate with pulmonary tuberculosis risk in West Africans

Article (PDF Available)inGenes and Immunity 8(6):456-67 · October 2007with60 Reads
DOI: 10.1038/sj.gene.6364410 · Source: PubMed
We investigated the role of DC-SIGN (CD209), long pentraxin 3 (PTX3) and vitamin D receptor (VDR) gene single nucleotide polymorphisms (SNPs) in susceptibility to pulmonary tuberculosis (TB) in 321 TB cases and 347 healthy controls from Guinea-Bissau. Five additional, functionally relevant SNPs within toll-like receptors (TLRs) 2, 4 and 9 were typed but found, when polymorphic, not to affect host vulnerability to pulmonary TB. We did not replicate an association between SNPs in the DC-SIGN promoter and TB. However, we found that two polymorphisms, one in DC-SIGN and one in VDR, were associated in a nonadditive model with disease risk when analyzed in combination with ethnicity (P=0.03 for DC-SIGN and P=0.003 for VDR). In addition, PTX3 haplotype frequencies significantly differed in cases compared to controls and a protective effect was found in association with a specific haplotype (OR 0.78, 95% CI 0.63-0.98). Our findings support previous data showing that VDR SNPs modulate the risk for TB in West Africans and suggest that variation within DC-SIGN and PTX3 also affect the disease outcome.
DC-SIGN (CD209), pentraxin 3 and vitamin D receptor
gene variants associate with pulmonary tuberculosis risk
in West Africans
R Olesen
, C Wejse
, DR Velez
, C Bisseye
, M Sodemann
, P Aaby
, P Rabna
, A Worwui
, M Diatta
, RA Adegbola
, PC Hill
, L Østergaard
, SM Williams
and G Sirugo
MRC Laboratories, Banjul, The Gambia;
Infectious Diseases Department, Skejby, Aarhus University Hospital, Denmark;
Health Project, INDEPTH Network, Guinea-Bissau and
Center for Human Genetics Research, Vanderbilt University, Nashville, TN,
We investigated the role of DC-SIGN (CD209), long pentraxin 3 (PTX3) and vitamin D receptor (VDR) gene single nucleotide
polymorphisms (SNPs) in susceptibility to pulmonary tuberculosis (TB) in 321 TB cases and 347 healthy controls from Guinea-
Bissau. Five additional, functionally relevant SNPs within toll-like receptors (TLRs) 2, 4 and 9 were typed but found, when
polymorphic, not to affect host vulnerability to pulmonary TB. We did not replicate an association between SNPs in the DC-
SIGN promoter and TB. However, we found that two polymorphisms, one in DC-SIGN and one in VDR, were associated in a
nonadditive model with disease risk when analyzed in combination with ethnicity (P ¼ 0.03 for DC-SIGN and P ¼ 0.003 for
VDR). In addition, PTX3 haplotype frequencies significantly differed in cases compared to controls and a protective effect was
found in association with a specific haplotype (OR 0.78, 95% CI 0.63–0.98). Our findings support previous data showing that
VDR SNPs modulate the risk for TB in West Africans and suggest that variation within DC-SIGN and PTX3 also affect the
disease outcome.
Genes and Immunity (2007) 0, 000–000. doi:10.1038/sj.gene.6364410
Keywords: tuberculosis; genetic susceptibility; DC-SIGN; pentraxin 3; vitamin D receptor; epistasis
Tuberculosis (TB) remains an important cause of death.
Every year more than 8 million people develop TB and 3
million TB patients die, although the causes for the high
mortality are complex.
Nevertheless, while the total
number of subjects infected with Mycobacterium tubercu-
losis (MT) is far larger (approximately 2 billion), the vast
majority of those infected keep the bacterium under
control and never develop a clinical disease. Genetic
variation among individuals could influence the suscept-
ibility to develop active disease.
Innate immunity genes are important in modulating
host susceptibility to TB because the first line of defense
against MT involves the identification and uptake of the
bacterium by macrophages and dendritic cells. Poten-
tially relevant genes for susceptibility to pulmonary TB
that contribute to this immune response include DC-
SIGN/CD209, pentraxin 3 (PTX3), toll-like receptors
(TLRs) 4 and 9 and vitamin D receptor (VDR).
The C-type lectin DC-SIGN is a crucial MT receptor on
dendritic cells.
A recent study by Barreiro et al.
shown that, in a South African population sample of
European and Asian descent, sequence variation in the
DC-SIGN promoter provided protection from TB.
PTX3 is produced by dendritic cells and macrophages
following TLRs engagement and secretion of inflamma-
tory cytokines.
Although the PTX3 relevance to TB
pathogenesis has not yet been determined, its role in
innate immunity, the interaction with mycobacterial wall
and the apparent correlation of expression
with disease activity
make it an attractive candidate for
studies on genetic susceptibility to TB.
TLRs are key players in the innate immune system,
and there is substantial evidence that single nucleotide
polymorphisms (SNPs) in TLRs could impair the way
TLR ligands interact with their receptors and would in
turn impact on the individual susceptibility to either
infectious or inflammatory disease.
TLR2 interacts with
M. tuberculosis cell-wall components to induce cellular
activation, killing of intracellular microbes and apopto-
and coding genomic variation in TLR2 has been
associated with active TB (TLR2).
TLR4 was initially
identified as the mediator of lipopolysaccharide (LPS)
inflammatory responses
and interacts with both a heat-
labile soluble mycobacterial factor and whole viable M.
tuberculosis to trigger innate responses.
M. tuberculo-
sis-induced tumor necrosis factor and nitric-oxide pro-
Journal: Gene Disk used Despatch Date: 13/6/2007
Article : npg_Gene_6364410 Pages: 1–12 Fig 4 col OP: dorthy/pouly
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Template: Ver 1.1.4
Received 23 February 2007; revised 24 May 2007; accepted 29 May
Correspondence: Dr G Sirugo, MRC Laboratories, PO Box 273,
Banjul, The Gambia.
E-mail: gsirugo@mrc.gm
These authors contributed equally to this work.
Genes and Immunity (2007) 00, 1–12
2007 Nature Publishing Group All rights reserved 1466-4879/07
duction can be blocked by the LPS lipid A antagonist
and it has been shown that Tlr4-deficient mice
develops a chronic lung infection resembling human
disease when exposed to aerosolized M. tuberculosis.
TLR4, two nonsynonymous mutations have been re-
ported in the extracellular domain (Asp229Gly and
Thr399Ile) that are associated with hyporesponsiveness
to LPS in alveolar macrophages, epithelial cells and
peripheral blood mononuclear cells,
but could not be
associated with TB in a previous study from West
Variation in TLR9 (which binds bacterial
DNA) is also potentially relevant to the development of
TB: it has been shown that in mice, TLR9 cooperates with
TLR2 in mediating resistance to MT,
and polymorph-
isms were originally identified in the 5
region which
could be affecting the transcriptional regulation of this
Vitamin D is a link between activation of TLRs and
antibacterial responses in innate immunity. It has
recently been shown by Lui et al.
that TLR1 and TLR2
activation of human macrophages upregulates the
expression of the VDR and vitamin D
genes, leading to induction of cathelicidin and to the
killing of intracellular MT. African-Americans with
higher susceptibility to TB have low 25-hydroxyvitamin
D levels, leading to inefficient cathelicidin mRNA
while VDR intragenic polymorphisms have
been associated with active TB disease in West African
population samples and families.
In our study, we analyzed the role of polymorphisms
within DC-SIGN, TLR4, TLR9, PTX3 and VDR in 321
pulmonary TB cases, and 347 healthy controls from
The ethnic composition and other baseline characteristics
of the population sample analyzed in our study are
shown in Table 1. Allele, genotype, haplotype frequen-
cies and linkage disequilibrium (LD) patterns did not
differ significantly between ethnic groups (analyses not
shown). As a result, for the remaining analyses ethnic
groups were pooled. HIV status did not affect the
analyses, as there were no allele, genotype or haplotypic
differences between HIV-positive and HIV-negative
cases (Fisher test, P40.05). The DC-SIGN gene was
analyzed for seven SNPs spanning the complete length
of the gene (7.72 kb, Figure 1a), including the 336
(rs4804803) and 139 (rs2287886) promoter variants. The
PTX3 gene was investigated with five SNPs, spanning
the 6.97 kb length of the gene. Five SNPs within TLRs 2, 4
and 9 were initially genotyped; however, two SNPs
(TLR2 rs5743708 and TLR4 rs4986791) were mono-
morphic. Therefore, only one TLR4 SNP and two TLR9
SNPs effectively remained to investigate the association
with TB (Tables 2 and 3).
Results demonstrated that in the pooled-ethnicities
samples, all genotypes were in Hardy–Weinberg equili-
brium (HWE) with the exception of one PTX3 variant
(rs1840680), but the deviation was not significant after
correction for multiple testing (P ¼ 0.04 uncorrected).
Four SNPs showed significant differences between
cases and controls for both allelic and genotypic
distributions using an uncorrected P-value of 0.05
(rs114465421 in DC-SIGN, rs2305619 and rs1840680 in
PTX3 and rs7975232 in VDR). However, none remained
significant after Bonferroni’s correction (Table 3).
Haplotype frequencies were compared between cases
and controls for each of the genes using all variable SNPs
(Table 4). Results demonstrated one statistically signifi-
cant association in the PTX3 gene (P ¼ 0.002), but no
significant association with any of the remaining genes.
One marginally significant haplotype association was
observed in the DC-SIGN gene (P ¼ 0.055).
Haplotype trend regression analyses were followed by
LD analysis within DC-SIGN, PTX3, TLR9 and VDR
genes, using the HaploView software (Figures 2a–h).
Case LD patterns are shown in Figures 2a, c, e and g and
controls in Figures 2b, d, f and h. Haplotype structure in
DC-SIGN did not differ notably between cases and
healthy controls, and indicated weak LD across the gene
(Figures 2a and b). The SNPs at positions 336 and 139
(rs4804803 and rs2287886), although potentially informa-
tive (heterozygosities of 0.50 and 0.36) and very close to
each other, were not in LD. The haplotypes observed in
these Guinean samples were not marked by significant
blocks, in contrast to the data available from HapMap
Gene : npg
Table 1 Baseline characteristics of the case and control popula-
Cases n ¼ 321 Controls n ¼ 347 P-value
Mean 95% CI mean 95% CI
Age (kg) 37.246
Height (cm) 166 (165–167) 167
Frequency Frequency P-value
Male 0.604 (0.55–0.66) 0.499 (0.45–0.55) o0.01
Female 0.396 (0.34–0.45) 0.501 (0.45–0.55) o0.01
Ethnic distribution
Balanta 0.153 (0.11–0.19) 0.196 (0.15–0.24) 0.14
Fulani 0.150 (0.11–0.19) 0.115 (0.08–0.15) 0.19
Mancanha 0.081 (0.05–0.11) 0.124 (0.09–0.16) 0.07
Mandinka 0.074 (0.46–0.10) 0.075 (0.05–0.10) 0.99
Manjaco 0.190 ( 0.095 (0.06–0.13) o0.01
Papel 0.202 (0.16–0.25) 0.297 (0.25–0.34) o0.01
0.137 (0.10–0.18) 0.098 (0.07–0.13) 0.12
Unknown 0.013 (0.00–0.03) 0 (0.00–0.00) 0.04
HIV status
HIV-1 0.190
HIV-2 0.090
HIV-1 & 2 0.050
HIV negative 0.570
Unknown 0.100
Abbreviation: HIV, human immunodeficiency virus.
Data are not normal distributed (Shapiro–Wi1k test, Po0.01).
P-values are calculated using Wilcoxon Mann–Whitney test for
nonparametric data.
P-values are calculated using two sample proportion tests.
Ethnic groups with a frequency below 5%.
We only obtained HIV status on the cases; however, within TB
cases there were no statistically significant differences between HIV
cases and controls (see Results).
Association of gene variants with pulmonary TB
R Olesen et al
Genes and Immunity
Gene : npg
Figure 1 Gene detail. Gene maps with position of SNPs typed and inter-marker distances.
Association of gene variants with pulmonary TB
R Olesen et al
Genes and Immunity
At the haplotype level, the general LD structure
observed at PTX3 corresponded to the one seen in
Yoruba (HapMap data). A G-A-G haplotype for sites
rs2305619, rs3816527 and rs1840680 was present in 36.5%
of cases and 42.6% of controls (Table 5): this difference in
haplotype frequency is statistically significant
(P ¼ 0.0281) with odds ratio (OR) of 0.782, demonstrating
a protective effect.
The LD between the two SNPs in TLR9 was very weak
in both cases and controls (Figures 2e and f) (D
¼ 0.03 in
cases and D
¼ 0.11 in controls), consistent with HapMap
data in Yoruba. VDR also had weak LD structure
(Figures 2g and h) in cases and controls. The strongest
LD was present between rs731236 and rs1544410 in both
cases (D
¼ 0.89) and controls (D
¼ 0.86), but both values
were not very informative.
In addition to single locus and haplotype analyses,
multilocus analysis was also performed to determine
whether there are interactions that associate with TB.
Ethnic groups and gender were used as variables in the
multifactor dimensionality reduction (MDR) analysis to
detect their effects. No significant multilocus interactions
were detected by MDR between DC-SIGN, PTX3, TLR9
and VDR, and any of the other gene variants tested.
However, one significant interaction between one SNP
(rs7975232, ApaI) in the VDR gene and ethnic groups
was detected (Figure 3). The testing accuracy for this
interaction was 58.6% (P ¼ 0.003) with a cross-validation
consistency of 8/10 and a testing OR of 1.982 (95% CI
1.454–2.70) (Table 6; Figure 3). An interaction dendro-
gram (Figure 4) was generated to assess the relationships
between this marker and ethnicity. The dendrogram
shows a nonadditive interaction between rs7975232 and
ethnic group, as well as an even stronger synergistic
interaction between rs11465391 in DC-SIGN. This latter
interaction is not unexpected as this SNP and ethnic
groups are the two factors in the second-best two-factor
MDR model (P ¼ 0.03), and all three of these factors are
in the best three-factor model.
In this study, we examined variation in candidate genes
with a role in innate immunity and previous associations
with pulmonary TB. The first candidate was the C-type
lectin DC-SIGN. A recent study by Barreiro et al.
indicated an association between two DC-SIGN promo-
ter SNPs (871G and 336A) and a decrease in the risk
of pulmonary TB. These authors investigated a South
African population and concluded that the 871G/
336A combination was largely confined to European
and Asian populations. In our study of a well-character-
ized West African sample analyses of the individual DC-
SIGN SNPs and haplotypes (Tables 3 and 4), however,
did not show any significant association with TB; we
conclude that the DC-SIGN promoter variation does not
have a significant effect on TB in Guineans. This
observation is consistent with what was described by
others, who were not able to replicate an association of
336A with TB in a small Colombia cohort.
Since the
871 SNP is absent in sub-Saharan Africans, our
negative finding can only exclude a causal effect of
336, but we cannot confute a role for the 871/336
haplotype in non-Africans. The apparent conflict of our
data with that of Barreiro et al.
can be explained by
genetic heterogeneity (with different populations having
differences in gene variants affecting risk) and is in
Gene : npg
Table 2 Gene and SNP information
Chromosome location Gene SNP ID (rs) Allele Observed heterozygosity Peptide shift Synonymous change Peptide location (aa)
19p13 DC-SIGN
rs4804803 (336) A/G 0.5
rs2287886 (139) A/G 0.3648
rs8105483 C/G 0.4176
G/A 0.0218 Thr–4Ile No 314
rs11465391 C/G 0.376
rs11465413 T/A 0.4981
rs11465421 C/A 0.396
3q25 PTX3 rs2305619 A/G 0.4896
rs3816527 C/A 0.3271 Ala–4Asp No 48
rs1840680 A/G 0.3454
rs3845978 C/T 0.3553
rs2614 C/T 0.202
4q32 TLR2 rs5743708
A/G NA Gln–4Arg No 753
9q32–33 TLR4 rs4986790 A/G 0.2066 Asp–4Gly No 299
A/G NA Ile–4Thr No 399
3p21.3 TLR9 rs187084 T/C 0.3819
rs5743836 T/C 0.4948
12q12–14 VDR rs10735810 (FokI) A/G 0.3509 Met–4Thr No 1
rs1544410 (BsmI) G/A 0.4442
rs7975232 (ApaI) C/A 0.4958
rs731236 (TaqI) T/C 0.4323 None (Ile) Yes 352
Abbreviations: aa, amino acid; SNP, single nucleotide polymorphisms.
rs number not available.
SNPs found to be monomorphic in the Guinea-Bissau population sample.
Association of gene variants with pulmonary TB
R Olesen et al
Genes and Immunity
Gene : npg
Table 3 Single locus association analyses of pooled ethnicities
Allele P-value
Genotype P-value
(a) DC-SIGN(CD209)
AA 60 (0.190) 85 (0.250) 0.148 0.186
AG 170 (0.540) 171 (0.503)
GG 85 (0.270) 84 (0.247)
Freq. A 0.460 0.501
0.111 1
AA 17 (0.054) 21 (0.061) 0.736 0.647
AG 123 (0.388) 122 (0.357)
GG 177 (0.558) 199 (0.582)
Freq. A 0.248 0.240
0.552 0.563
CC 153 (0.489) 162 (0.488) 0.901 0.928
CG 132 (0.422) 143 (0.431)
GG 28 (0.089) 27 (0.081)
Freq. G 0.300 0.297
0.897 0.579
CC 312 (0.987) 322 (0.979) 0.369 0.379
CT 4 (0.013) 7 (0.021)
TT 0 (0.000) 0 (0.000)
Freq. T 0.006 0.011
CC 167 (0.534) 192 (0.570) 0.269 0.612
CG 119 (0.380) 121 (0.359)
GG 27 (0.086) 24 (0.071)
Freq. G 0.276 0.251
0.392 0.321
AA 77 (0.244) 72 (0.214) 0.155 0.342
AT 166 (0.527) 171 (0.509)
TT 72 (0.229) 93 (0.277)
Freq. A 0.508 0.469
0.302 0.737
AA 19 (0.061) 22 (0.065) 0.023 0.026
AC 98 (0.316) 141 (0.415)
CC 193 (0.623) 177 (0.521)
Freq. A 0.219 0.272
0.187 0.414
(b) PTX3
GG 40 (0.125) 65 (0.188) 0.019 0.050
GA 153 (0.480) 165 (0.478)
AA 126 (0.395) 115 (0.333)
Freq. G 0.365 0.428
0.552 0.648
AA 175 (0.566) 207 (0.635) 0.114 0.213
AC 117 (0.379) 104 (0.319)
CC 17 (0.055) 15 (0.046)
Freq. C 0.244 0.206
0.751 0.728
GG 167 (0.525) 215 (0.623) 0.043 0.026
AG 130 (0.409) 107 (0.310)
AA 21 (0.066) 23 (0.067)
Freq. A 0.27 0.222
0.578 0.04
CC 207 (0.647) 200 (0.585) 0.100 0.253
CT 102 (0.319) 126 (0.368)
TT 11 (0.034) 16 (0.047)
Freq. T 0.194 0.231
0.859 0.549
CC 247 (0.784) 265 (0.782) 0.957 1.000
CT 65 (0.206) 71 (0.209)
TT 3 (0.010) 3 (0.009)
Freq. T 0.113 0.114
0.566 0.415
(c) TLR4
GG 2 (0.006) 7 (0.021) 0.070 0.141
AG 51 (0.162) 65 (0.193)
AA 262 (0.832) 265 (0.786)
Freq. G 0.087 0.117
1.00 0.187
(d) TLR9
CC 25 (0.079) 21 (0.062) 0.07 0.141
CT 122 (0.384) 132 (0.389)
TT 171 (0.538) 186 (0.549)
Freq. C 0.27 0.257 0.257
0.667 0.771 0.771
CC 62 (0.194) 66 (0.193) 0.114 0.213
CT 154 (0.481) 175 (0.512)
TT 104 (0.325) 101 (0.295)
Freq. C 0.434 0.449
0.642 0.508
(e) VDR
GG 198 (0.619) 207 (0.602) 0.625 0.888
AG 106 (0.331) 118 (0.343)
AA 16 (0.050) 19 (0.055)
Freq. A 0.216 0.227
0.751 0.561
GG 33 (0.103) 38 (0.111) 0.752 0.932
AG 141 (0.441) 152 (0.444)
AA 146 (0.456) 152 (0.444)
Freq. G 0.323 0.333
1 0.907
AA 67 (0.212) 101 (0.300) 0.012 0.028
AC 166 (0.525) 166 (0.493)
CC 83 (0.263) 70 (0.208)
Freq. A 0.475 0.546
0.359 0.913
CC 25 (0.078) 34 (0.099) 0.61 0.65
CT 145 (0.453) 150 (0.435)
Table 3 Continued
Allele P-value
Genotype P-value
(b) PTX3
Association of gene variants with pulmonary TB
R Olesen et al
Genes and Immunity
agreement with the finding that their effect was mainly
confined to people of Eurasian descent. One intronic SNP
(rs11465391) was however observed to interact with
ethnicity in modulating disease risk (Figure 4). The
biological meaning of this interaction is unclear, but it
could be hypothesized that the 336 association de-
scribed by Barreiro et al.
was tagging a marker else-
where in the gene between intron 6 (where rs11465391
lies) and the promoter; further studies are warranted to
investigate the effect of variation in this gene region.
At the DC-SIGN locus, the Bissau population seems to
differ from the LD pattern detected in Yoruba (Figures 2a
and b). Although the HapMap data are based on higher
marker density, only one of the SNPs used in our set
(rs8105483) was examined in the HapMap data. No LD
blocks were identified in our study population and cases
Gene : npg
Table 4 Haplotype trend regression results for extended haplotypes
(a) DC-SIGN (CD209) Frequency P-value
rs4804803 rs2287886 rs8105483 DC-SIGN1.-ex6TI rs11465391 rs11465413 rs11465421 TB Control
A A C C C A C 0.037 0.085 0.055
A G C C C A C 0.149 0.141
A G C C C T A 0.059 0.053
A G C C C T C 0.097 0.098
G A C C C A C 0.029 0.015
G G C C C A C 0.045 0.055
G G C C G A C 0.089 0.056
G G G C C T C 0.089 0.063
(b) PTX3 Frequency P-value
rs2305619 rs3816527 rs1840680 rs3845978 rs2614 TB Control
G A G C C 0.172 0.215 0.002
G A G T C 0.19 0.187
A A G C C 0.263 0.253
A A G C T 0.099 0.083
A C A C C 0.237 0.18
(c) TLR9 Frequency P-value
rs187084 rs5743836 TB Control
T T 0.417 0.426 0.746
T C 0.312 0.318
C T 0.148 0.131
C C 0.122 0.125
(d) VDR Frequency P-value
rs10735810 rs1544410 rs7975232 rs731236 TB Control
G G A T 0.087 0.128 0.416
G G C T 0.174 0.142
A G C T 0.052 0.037
G A A C 0.136 0.16
G A A T 0.161 0.14
G A C C 0.085 0.067
G A C T 0.132 0.134
A A A C 0.05 0.06
A A C T 0.051 0.053
Abbreviations: PTX3, pentraxin 3; TB, tuberculosis; TLR9, toll-like receptor 9; VDR, vitamin D receptor.
Figure 2 HaploView figures. Linkage disequilibrium (LD) plots characterizing haplotype blocks in DC-SIGN, PTX3, TLR9 and VDR genes.
In the first column are LD plots for TB cases and in the second column are LD plots for TB controls. D
values are indicated in percentages
within squares in the LD plot, with solid blocks without numbers indicating D
¼ 1 (100%) for the corresponding pair of variants. Strong LD is
indicated by dark gray, while light gray and white indicate uninformative and low confidence values, respectively. LD Blocks were created
with the default algorithm in HaploView that creates 95% confidence bounds on D
considered to be in strong LD where 95% of the
comparisons made are informative. The haplotype blocks were created using HaploView program, version 3.3.
Association of gene variants with pulmonary TB
R Olesen et al
Genes and Immunity
Gene : npg
Association of gene variants with pulmonary TB
R Olesen et al
Genes and Immunity
did not differ from controls in LD structure (Figures 4a
and b). The different DC-SIGN LD pattern compared to
the HaploMap data set would underscore the impor-
tance of specific LD determination in West African
populations, as disequilibrium data from Nigerian
Yoruba are not necessarily applicable to the rest of West
Of the five SNPs analyzed in PTX3, two showed a
significant association with TB disease, and a significant
haplotype association was also identified (P ¼ 0.002). A
Gene : npg
Table 5 PTX3 haplotype block analysis
PTX3 Frequency w
P-value OR 95% CI
rs2305619 Rs3816527 rs1840680 TB Controls
G A G 0.365 0.426 4.822 0.0281 0.782 0.632–0.980
A A G 0.363 0.351 0.196 0.6576 1.048 0.832–1.320
A C A 0.242 0.205 2.619 0.1056 1.241 0.951–1.621
A A A 0.028 0.017 1.634 0.2012 1.635 0.739–3.750
Abbreviations: OR, odds ratio; PTX3, pentraxin 3.
Figure 3 Summary of single-site genotype combinations with ethnicity associated with high risk and low risk for TB individuals. Each
multifactorial cell is labeled as ‘high risk’ or ‘low risk’. For each multifactorial combination, hypothetical distributions of cases (left bar in cell)
and controls (right bar in cell) are shown. Each cell represents a multilocus genotype, which is labeled in the figure. The coding for the groups
are: BA, Balanta; FU, Fulani; MC, Mancanha; MD, Mandinka; MJ, Manjaco; Other and PE, Pepel.
Table 6 Summary of MDR results examining 1–5 way interactions
Number of
Best model for each interaction
Balanced classification
accuracy (%)
1 (Group)
57.5 10/10
2 (Group-rs7975232(ApaI VDR)) 59.3 9/10
3 (Group-rs7975232(ApaI VDR)-rs11465391(DC-SIGN)) 57.9 7/10
4 (Group-rs8105483(DC-SIGN)-rs7975232(ApaI VDR) -rs11465391(DC-SIGN)) 54.2 3/10
5 (Group-rs5743836(TLR9)-rs11465391(DC-SIGN) -rs7975232(ApaI VDR)-
52.6 5/10
Abbreviations: MDR, multifactor dimensionality reduction; VDR, vitamin D receptor.
Best model for each interaction these results reflect the best combination of variable(s) for 1–5 way interactions of the variables, based on
maximum classification accuracy and maximum cross-validation consistency.
Classification accuracy (%) the ability of the MDR model to classify correctly disease status from the data.
Cross-validation consistency (CVC) during the MDR procedure – the original data are partitioned into 10 subsets, each of which is analyzed
by MDR; CVC describes how many of the 10 subsets found the best model at each level of interaction.
Group this variable categorized individuals according to their ethnic group (Balanta, Fulani, Mancanha, Mandinka, Manjaco, Papel or
Association of gene variants with pulmonary TB
R Olesen et al
Genes and Immunity
post hoc inspection of the inferred haplotype frequencies
showed a higher frequency of the ‘G-A-G’ haplotype
corresponding to SNPs rs2305619 to rs1840680 (Table 4)
in the control population compared to cases (46.2 vs
36.5%). This three-site haplotype had an OR of 0.8,
(P ¼ 0.02), and is suggestive of a protective effect relative
to other haplotypes. In addition, the LD structure in
PTX3 appears to differ between cases and controls, with
controls having a smaller block size, suggestive either of
a more recent origin of the case haplotypes or selection
maintaining a larger block structure (Figures 2c and d).
This observation serves to reinforce the notion that cases
and controls differ with respect to PTX3 genomic
variation. Since it has been reported that PTX3 levels
correlate with disease activity in West African subjects,
further investigations are warranted to assess the role of
genomic variation PTX3 in affecting susceptibility to
pulmonary TB.
Our investigation of TLRs 2, 4 and 9 was exclusively
limited to very few SNPs of interest because of their
potential functional relevance and/or previously re-
ported associations with TB. Among the SNPs analyzed
(excluding TLR2 Gln753Arg and TLR4 Thr399Ile which
were not polymorphic), the TLR4 Asp299Gly as well as
the two SNPs located in the 5
regulatory region of TLR9
(Figure 1d) showed no significant association with TB
and no significant LD (Figures 2e and f). Although the
negative association of TB with Asp299Gly confirmed a
previous study from The Gambia,
a thorough study of
the role of TLR2, TLR4 or TLR9 will require a systematic
investigation of polymorphisms and related haplotypes
that are not part of this study.
The VDR gene was investigated with the same set of
SNPs/restriction fragment length polymorphisms
(RFLPS) (FokI-BsmI-ApaI-TaqI; Figure 1e) used by Born-
man and collaborators
to genotype a West African
sample composed of more than 1100 case controls and
300 families. Their case-control analysis showed no
significant association between any of the alleles of the
markers typed and TB, but a significant result was
obtained in the families. The association was across the
region covered by the four RFLPs, but was particularly
significant for the FokI–ApaI combination (P ¼ 0.0063)
due to increased combined transmission of FokI ‘F’ and
ApaI ‘A (or C and T in this study) alleles to the affected
offspring. In our case-control study, no association with
TB was detected either with single markers or haplo-
types (Tables 3e and 4d), consistent with what was
observed by Bornman et al.
However, the LD pattern in
our sample substantially differed from theirs. While we
detected potentially important LD between BsmI and
TaqI, positioned at approximately 1 kb from each other,
we did not observe significant disequilibrium between
any of the other SNPs, including the FokI-ApaI pair
(Figures 2g, h). The lack of LD between ApaI and either
BsmI or Ta qI, flanking ApaI at 998 and 80 bp respectively,
indicates a higher haplotypic diversity than in the
Bornman et al.
study. Such an increase in diversity will
reduce the ability to detect an association using indirect
We also examined possible epistatic effects on suscept-
ibility to pulmonary TB by using an MDR approach.
Within VDR, an ApaI effect (Figure 3) was variable both
within and among Guinean groups, and this could
explain why the only significant VDR variation effect
described by Bornman et al.
was by tracking marker-
segregation in families. If the ApaI interaction with
ethnicity reflects a real effect of VDR variation on risk
modulation, it is evident in Figure 4 that the majority of
the ethnic groups studied can be split in high- and low-
risk subsets, each composed of a low number of subjects.
In this case, very large association studies and accurate
ethnic determination would be necessary to detect a
significant association at the general population level.
Our results would in part confirm what was already
described by Bornman et al.,
that is, VDR variants
impact susceptibility to TB, but suggest that other factors
that were unmeasured in our and their study are at play
in conferring risk. These could include other genetic
factors and/or different environmental factors that
interact in nonadditive ways to affect risk in an
interaction with VDR variants. Therefore, confirming
these results will require large replication studies that
focus on those ethnic groups for which an increase in risk
was predicted.
Materials and methods
Study population
This case-control study was conducted at The Bandim
Health Project (BHP), a demographic surveillance site in
Bissau, the capital of Guinea Bissau. BHP has followed
this population since 1978.
TB incidence in this area is
among the highest in the world (470/100 000).
The area
has a population of 92 000 and is composed of several
ethnic groups including Papel (32%), Manjaco (14%),
Mancanha (10%), Balanta (9%), Fulani (13%), Mandinka
(7%) and others (15%). Patients included in the study
(cases) were residents or long-term guests of Bissau, aged
415 years, newly TB-diagnosed using three sputum
examinations for acid fast bacteria or clinical criteria by
the World Health Organization’s definition of active
pulmonary TB.
No culture of TB was available in
Bissau, during the study period, as facilities were
destroyed during a civil war;
218/321 (68%) were
smear positive. Patients with newly diagnosed TB were
enrolled when they started antitubercular treatment at
local health centers. During the inclusion period from
Gene : npg
Figure 4 Interaction dendrogram. In this figure the closer the color
is to red, the stronger the interaction/synergy between the
variables; and the closer the color is to blue, the more additive/
redundant the relationship between the markers. Ethnic group and
rs11465391 had the strongest interactive relationship. This was
followed by rs795232, which also had a strong interactive effect with
the combined effect of rs11565391 and group. This would suggest
that the two variables in the best MDR model operate with
moderately strong nonadditive interactions.
Association of gene variants with pulmonary TB
R Olesen et al
Genes and Immunity
November 2003 to November 2005, 438 TB patients were
screened at local health centers: 344 subjects met
inclusion criteria and accepted participation, and from
these we could obtain 321 DNA samples. There were no
exclusion criteria.
Healthy controls were recruited from the study area
from May 2005 to November 2005. A random sample of
200 houses was selected from the database of all subjects
living in the study area, and houses with a recorded case
of TB within the past 2 years were excluded from the
sampling. Exclusion criteria for controls included the
presence of cough for more than 2 weeks, history of TB
and TB in the household within the last 2 years to avoid
households with a high-risk of active TB. As shown in
Table 1, the composition of the case and control samples
was different in terms of sex and ethnicity. These
differences are due to the sampling strategy as controls
were derived from healthy nuclear families; hence more
healthy married couples were collected, whereas TB
patients are more often males. The ethnic differences are
due to willingness of healthy subjects to give blood,
which was not the same across the ethnic groups,
whereas most TB patients accepted to be part of the
study regardless of their ethnic background. All subjects
were interviewed by field assistants, using a standar-
dized questionnaire on ethnicity, environmental factors
and prior exposure to TB. Permission to perform HIV
tests for the controls was not asked, as accepting HIV
testing would have negatively impacted participation in
the study. Venous blood samples (4 ml in ethylenedia-
minetetraacetic acid) were collected from the control
subjects, and from these, 347 DNA samples were
obtained that were archived, along with the 321 DNAs
obtained from cases, in the National Gambian DNA
Ethical approval was granted by the ‘Unidade de
Coordenacao de Estudos e Pesquisas em material de
Saude’ (Ministry of Health) in Guinea-Bissau. All adults
and children’s guardians signed an informed consent to
the study.
DNA extraction and genotyping
All DNA samples were extracted using a standard
salting-out procedure. DNA purities were estimated
spectrophotometrically, and final concentrations were
determined by PicoGreen. Samples (4 ng of DNA) were
genotyped by TaqMan SNP assays (Applied Biosystems)
in 10 ml reaction volume, using the Rotor-Gene 3000
(Corbett Research) and the ABI 7500 real-time PCR
systems. Fluorescence curves were analyzed with the
Rotor-Gene Software version 6 and the 7500 Sequence
Detection Software version 1.2.1 for allelic discrimina-
All samples were analyzed for 21 SNPs (seven in DC-
SIGN, five in PTX3, one in TLR2, two in TLR4, two in
TLR9 and four in VDR). Of these 21 variants, two coding
SNPs, TLR2 Arg753Gln and TLR4 Thr399Ile, were found
to be monomorphic in Guineans and as a result were
dropped from the analyses (Table 2).
Statistical analysis
Single locus analysis. Single site allele frequency, geno-
type frequency and HWE analyses were performed
using Powermarker statistical software (http://statgen.-
Statistical significance was
determined using Fisher’s exact tests.
Haplotype analysis. Haplotype analyses were per-
formed, using Powermarker
and HaploView version
statistical softwares. Both use an expectation-
maximization algorithm to determine haplotype fre-
quency distributions when phase is unknown and
measure LD. Haplotype-trait associations were assessed
by the haplotype trend analysis in Powermarker.
approach can be applied to both quantitative traits and
dichotomous traits. The test for association uses an F-test
for a specialized additive model. Haplotype block
structure was determined using the method of Gabriel
et al.
with the HaploView software, and color coding of
the LD is based on the confidence of the LD values with
dark gray indicating strong evidence of LD, light gray
being uninformative and white indicating low confi-
dence of LD.
MDR analysis. Multilocus analysis was performed
using MDR analysis
(available at www.epistasis.org).
MDR exhaustively searches all single site and all multi-
locus combinations of genetic data and then categorizes
each multilocus genotype cell into either high-risk or
low-risk genotypes on the basis of the ratio of cases to
controls (T) in each cell. The ratio (T) for the present
analyses was (321 TB cases/347 TB controls) 0.928. Any
ratio larger than this baseline was considered high risk,
for example, more TB cases were observed than expected
at random from the data set. Cross-validation and
classification accuracy was used to choose the single
best model. Classification accuracy is the proportion of
individuals classified correctly in a testing subset of the
data, based on a model generated using the rest of the
data (a training set).
Statistical significance was determined empirically for
the single best model by permutation testing. The case-
control status of each subject was permuted 1000 times,
and the distribution of testing accuracies was used to
determine the probability of chance observations. The
null hypothesis of no association was rejected if actual
data fell within upper 5.0% of the permuted data. The
MDR procedure has been shown to be effective in several
studies, including studies of sporadic breast cancer,
essential hypertension,
atrial fibrillation,
type II
and multiple sclerosis.
The OR for the best multifactor model was calculated
by comparing the genotypes of high-risk and low-risk
cells, categorizing high-risk genotypes as exposed and
low-risk genotypes as nonexposed. The calculations were
performed, using MDR software (www.epistasis.org).
Interaction dendrograms
were created to view
graphical representation of interactions between vari-
ables and to assess the statistical nature of relationship
between markers (redundant, additive or synergistic).
This study was funded by the MRC award G0000690 to
GS, and by Grants from the Danish Medical Research
Council, the Danish society of respiratory medicine, the
Danish Council of Development Research to RO, CW, MS
and LO.
Gene : npg
Association of gene variants with pulmonary TB
R Olesen et al
Genes and Immunity
Disclosure/conflict of interests
The authors declare no conflict of interests.
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    • "These discrepancies are further highlighted by a recent study showing no benefit of 25(OH) D supplementation on response to therapy in an Indian population [25] although it may limit lung pathology and thus reduce disability-associated life-years (DALYs) in vulnerable populations [26]. In West Africa, there appears to be a role for VDR haplotypes rather than genotypes in susceptibility to TB [18], although another study in Guinea Bissau showed VDR polymorphisms when analysed together with ethnicity were associated with increased risk of TB disease [27]. Interestingly, there also appears to be an influence of variation within the gene encoding Vitamin D binding protein (VDBP) and Serum 25(OH) D levels in Gambian children [28], which has implications for interpretation of 25(OH) D status across different groups. "
    [Show abstract] [Hide abstract] ABSTRACT: Background Vitamin D is essential in the host defence against tuberculosis (TB) as an immune modulator. The aim of this study was to determine the level of 25-hydroxyvitamin D (25 (OH) D) from adult TB index cases before and after treatment and their exposed household contacts (HHC) in The Gambia. Methods Serum from adult index TB cases and their TB-exposed household contacts (HHC) was analysed for 25(OH) D and Vitamin D binding protein (VDBP) concentrations. Tuberculin skin test (TST) status was used as a measure of Mycobacterium tuberculosis (Mtb) infectivity in the HHC. In addition, HHC who later progressed to active TB (incident cases) were assessed alongside non-progressors to determine the influence of 25 (OH) D levels on TB risk. Results Eighty-three TB cases, 46 TST+ and 52 TST− HHC were analysed. Generally levels of 25(OH) D were considered insufficient in all subjects. However, median levels of 25(OH) D and VDBP were significantly higher in TB cases compared to both TST+ and TST− HHC at recruitment and were significantly reduced after TB therapy (p < 0.0001 for all). In addition, levels of serum 25(OH) D at recruitment were significantly higher in TB progressors compared to non-progressors (median (IQR): 25.0(20.8–29.2) in progressors and 20.3 (16.3–24.6) ng/ml in non-progressors; p = 0.007). Conclusion In The Gambia, an equatorial country, 25(OH) D levels are higher in serum of TB progressors and those with active disease compared to latently infected and uninfected subjects. These results contrast to findings in non-equatorial countries.
    Full-text · Article · Mar 2016
    • "Mechanistically, PTX3 acts as an opsonin, which not only enhances phagocytosis and killing of pathogens but also promotes dendritic cell maturation and polarization, thereby contributing to the activation of the adaptive immune response (Bottazzi et al., 2010). Intriguingly, polymorphisms in the PTX3 gene are associated with risk for pulmonary tuberculosis and P. aeruginosa infections in cystic fibrosis (Olesen et al., 2007; Chiarini et al., 2010). Furthermore, PTX3 mediates a variety of antiviral activities against influenza viruses, including inhibition of virus-induced hemagglutination and viral neuramidase activity, as well as neutralization of virus infectivity in vitro (Reading et al., 2008). "
    [Show abstract] [Hide abstract] ABSTRACT: Although innate immunity came into the research spotlight in the late 1990s when its instructive role in the adaptive immune response was recognized, innate humoral defense factors have a much older history. The exocrine secretions of the body contain a plethora of distinct soluble factors (lysozyme, lactoferrin, peroxidases, proline-rich proteins, histatins, etc.) that protect the body from mucosal microbial pathogens. More recent studies have established that the humoral arm of innate immunity contains a heterogeneous group of pattern-recognition molecules (e.g., pentraxins, collectins, and ficolins), which perform diverse host-defense functions, such as agglutination and neutralization, opsonization, control of inflammation, and complement activation and regulation. These pattern-recognition molecules, which act as functional predecessors of antibodies ("ante-antibodies"), and the classic soluble innate defense factors form an integrated system with complementary specificity, action, and tissue distribution, and they are the subject of this chapter.
    Article · Dec 2015 · Tuberculosis
    • "among different genotyping of pentraxin 3 showed that the carriers of the AA genotype at the rs2305619 SNP had the higher amount of PTX3 in the blood compared to the AG and GG carriers, while GG genotyping is associated with the lower value of plasma PTX3. These results are matched with the study of Barbati et al. [24] who stated that carriers for AA rs2305619 (vs.AG and GG genotypes) had higher PTX3 levels, while GG genotyping has been previously associated with a protective effect against pulmonary tuberculosis in West Africans [40] and Pseudomonas aeruginosa colonization in Italian cystic fibrosis patients [41]. The mechanism by which PTX3 SNPs affect PTX3 plasma levels is still to be clarified but possibly the rs2305619 genetic variant is in linkage with a regulatory region, perhaps the PTX3 promoter. "
    [Show abstract] [Hide abstract] ABSTRACT: Objective The aim of the study was to investigate the association of serum Pentraxin 3 and genotyping with the risk of developing AMI and its severity. Patients and methods Fifty patients admitted to the coronary care unit presented with STEMI (acute ST segment myocardial infarction) at the Cardiology Department, Menoufia University Hospital in the period from October 2014 to April 2015 and another 20 subjects age- and gender-matched were taken as the control group. All patients and control groups were subjected to the following: Full history taking, complete clinical examination. ECG and echocardiography and Laboratory investigation including: estimation of lipid profile, urea and creatinine, CKMB, troponin I, serum pentraxin 3 and Genotyping of pentraxin 3 A/G SNP (rs2305619). Results The patients with myocardial infarction had significantly higher levels of pentraxin 3 than the controls. The cut-off values for PTX3 and troponin I were 4.35 ng/ml and 0.34 μg/l respectively. Pentraxin 3 showed the highest diagnostic accuracy of coronary artery disease (96%), with sensitivity (96%) and specificity (95%). The highest serum pentraxin 3 levels were in the AA mutant homozygous type. Conclusion PTX3 is one of the earliest biomarkers for detecting acute coronary syndrome. rs2305619 AA genotyping of the pentraxin 3 gene might be a candidate risk factor for development of coronary artery disease, presumably by increased pentraxin 3 levels.
    Full-text · Article · Nov 2015
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