Production of TNF-a, IL-12(p40) and IL-17 Can
Discriminate between Active TB Disease and Latent
Infection in a West African Cohort
Jayne S. Sutherland*, Bouke C. de Jong, David J. Jeffries, Ifedayo M. Adetifa, Martin O. C. Ota
Bacterial Diseases Programme, Medical Research Council Laboratories, Banjul, The Gambia
Abstract
Background: Mycobacterium tuberculosis (MTb) infects approximately 2 billion people world-wide resulting in almost 2
million deaths per year. Determining biomarkers that distinguish different stages of tuberculosis (TB) infection and disease
will provide tools for more effective diagnosis and ultimately aid in the development of new vaccine candidates. The current
diagnostic kits utilising production of IFN-c in response to TB antigens can detect MTb infection but are unable to
distinguish between infection and disease. The aim of this study was to assess if the use of a longer term assay and the
analysis of multiple cytokines would enhance diagnosis of active TB in a TB-endemic population.
Methods: We compared production of multiple cytokines (TNF-a, IFN-c, IL-10, IL-12(p40), IL-13, IL-17 and IL-18) following
long-term (7 days) stimulation of whole-blood with TB antigens (ESAT-6/CFP-10 (EC), PPD or TB10.4) from TB cases (n = 36)
and their Mycobacterium-infected (TST+; n = 20) or uninfected (TST2; n = 19) household contacts (HHC).
Results and Conclusions: We found that TNF-a production following EC stimulation and TNF-a and IL-12(p40) following
TB10.4 stimulation were significantly higher from TB cases compared to TST+ HHC, while production of IFN-c and IL-13 were
significantly higher from TST+ compared to TST- HHC following PPD or EC stimulation. Combined analysis of TNF-a, IL12(p40) and IL-17 following TB10.4 stimulation resulted in 85% correct classification into TB cases or TST+ HHC. 74% correct
classification into TST+ or TST2 HHC was achieved with IFN-c alone following TB10.4 stimulation (69% following EC) and
little enhancement was seen with additional cytokines. We also saw a tendency for TB cases infected with M. africanum to
have increased TNF-a and IL-10 production compared to those infected with M. tuberculosis. Our results provide further
insight into the pathogenesis of tuberculosis and may enhance the specificity of the currently available diagnostic tests,
particularly for diagnosis of active TB.
Citation: Sutherland JS, de Jong BC, Jeffries DJ, Adetifa IM, Ota MOC (2010) Production of TNF-a, IL-12(p40) and IL-17 Can Discriminate between Active TB
Disease and Latent Infection in a West African Cohort. PLoS ONE 5(8): e12365. doi:10.1371/journal.pone.0012365
Editor: Delia Goletti, National Institute for Infectious Diseases L. Spallanzani, Italy
Received January 12, 2010; Accepted July 31, 2010; Published August 24, 2010
Copyright: ß 2010 Sutherland et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was jointly supported by the Bill & Melinda Gates Foundation (Grand Challenges for Global Health 6) (www.gatesfoundation.org) and the
Medical Research Council (UK), The Gambia (www.mrc.gm). The funders had no role in study design, data collection and analysis, decision to publish, or
preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: jsutherland@mrc.gm
cytokines that have been found to be important in control of
MTb infection include TNF-a [5], IL-12(p40) [6], IL-18 [7] and
IL-17 [8]. For example, progression of LTBI to active disease can
occur following TNF-a blocking treatments for chronic inflammatory diseases [5], while genetic defects involving IL-12 (as for
IFN-c [9]) increase susceptibility to development of active TB
disease [6]. Increased Th2 cytokines (IL-4, IL-10) have been
shown to be present in plasma of subjects with more advanced TB
disease [10], while pro-inflammatory cytokines such as IL-6 and
IP-10 are increased in subjects with active TB disease compared to
those with LTBI [11]. In order to generate a biosignature for TB
disease and infection a number of parameters need to be
considered. These include the HIV status and age of the patient
with the majority of diagnostic tests not applicable for either HIVpositive patients or children. Another potential confounder is the
type of TB (pulmonary or extrapulmonary), the extent of disease
and the sample type used for analysis. For instance, a decrease in
Introduction
Close to one-third of the world’s population is infected with
Mycobacterium tuberculosis (MTb), the causative agent of tuberculosis
(TB), with infection rates highest in poverty-stricken countries
throughout Africa and Asia [1]. Interestingly, while 8 million
people develop active TB each year, the majority remain
asymptomatically (latently) infected with the pathogen presumably
due to a protective immune response. Determining what
constitutes protective immunity to TB is critical for development
of new diagnostics, treatment protocols and vaccine candidates.
This requires the generation of an immune profile (or ‘biosignature’) corresponding to specific stages of TB infection.
IFN-c is a cytokine produced by T cells that has been widely
used for diagnosis of TB infection following stimulation with MTbspecific antigens [2]. However, IFN-c alone is not sufficient to
provide protection against disease progression [3,4]. Other
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Biomarkers for TB
each cytokine, responders were determined based on production
.2SD above the mean level for the corresponding cytokine in the
background sample. Following PPD stimulation there was a
significantly higher proportion of TB cases and TST+ contacts
producing IFN-c, IL-13 and IL-17 compared to TST2 contacts
(p,0.0001 for all; Fig. 1H). Indeed, almost 90% of TB cases and
TST+ contacts were responders based on IFN-c production
(compared to 20% of TST2 contacts). Furthermore, almost 80%
of TB cases and TST+ contacts responded on the basis of IL-13
production compared to ,5% of TST2 cases. Interestingly, while
proportions were very low (,5% responders for both TST+ and
TST2 HHC), IL-18 showed a significant difference in the number
of responders between TB cases and TST+ contacts (p,0.05,
Fig 1H). The proportion of responders based on IL-17 production
was also significantly different between TB cases (.80%) and
TST+ contacts (60%; p,0.05; Fig. 1H).
IFN-c production from peripheral blood cells has been shown to
occur with advanced TB [12] but this may be due to sequestration
of the cells at the site of infection [13].
The cytokine response to TB antigens has been studied
extensively but results have varied due to the genetic background
of the study population, the type and length of antigen stimulation,
the experimental protocol used and the sample type. In addition,
while most studies have shown preferential differentiation between
infected and non-infected individuals, few have detailed differences between infection and active disease, essential for reducing TB
transmission. One reason for this lack of differentiation may be
due to the use of short term assays which will detect effector
memory rather than generation of naive or central memory T cell
responses [14]. Some studies using long-term stimulation have
shown promising results including responses to Erp, an exported
Mycobacterial protein [15] and to the 16kDa antigen Rv2031c
[16], both of which have resulted in differential IFN-c production
in subjects with active disease compared to those with latent
infection. Long-term assays have also been shown to enhance
detection of LTBI and to distinguish between recently acquired
and remote infections [17,18].
In the present study, we used long-term (7 day) stimulation with
PPD, ESAT-6/CFP-10 (EC) and TB10.4 followed by multiplex
cytokine analysis of the supernatants. EC are secreted antigens
encoded within the region of difference 1 (RD1) of the TB genome
[19] and are also the basis of the currently available IFN-c release
assays (IGRA) such as the QuantiFERON-TB Gold [20]. TB10.4
is a recently identified antigen encoded by Rv0288 that has been
found to be essential for the virulence of MTb [21] and thus may
enhance discrimination between active TB and latent infection.
Indeed, we found that combined analysis of TNF-a, IL-12(p40)
and IL-17 production following stimulation with TB10.4 for 7
days resulted in 85% correct classification into subjects with active
disease or those with latent infection. These results, once validated,
may enhance the currently available cytokine-based TB diagnostic
tests.
Pattern of cytokine production following stimulation
with ESAT-6/CFP-10 (EC) fusion protein
The responses seen following EC stimulation were similar to
that following PPD stimulation but at a lower magnitude. For
example, IFN-c levels were (median[IQR]) 477[79–1303] pg/mL
from TB cases and 198[0–1675] from TST+ contacts (compared
to over 2000pg/mL following PPD stimulation) but was still
significantly higher than for TST2 HHC (0[0–19] pg/mL). IL12(p40) and IL-17 levels were also high from TB cases but were
virtually absent from both TST+ and TST2 HHC, particularly
for IL-12(p40) (median[IQR] = 5.1[0–14}, 0[0–30] and 0[0–28]
for TB cases, TST+ and TST2 contacts respectively). Production
of IFN-c and TNF-a were both significantly higher from TB cases
compared to TST2 contacts (p,0.0001 and p = 0.01 respectively;
Figs. 2A and B) while TNF-a was significantly increased from TB
cases compared to TST+ contacts (p = 0.0157; Fig. 2B). In
addition TST+ contacts had significantly higher production of
IFN-c and IL-13 compared to TST2 contacts (p = 0.0009 and
p = 0.0282 respectively; Figs. 2A and E). The proportion of
responders to EC was also lower than following PPD stimulation
but the pattern of differences between the 3 groups was similar. A
significantly higher proportion of TB cases and TST+ contacts
produced both IFN-c (p,0.001 and p,0.05 respectively) and IL17 (p,0.001 and p,0.05 respectively) compared to TST2
contacts (Fig. 2H). In addition, the proportion of TST+ contacts
producing IL-13 was significantly higher than for TST2 contacts
(p,0.05; Fig. 2H). However, no difference in the proportion of
responders was seen between TB cases and TST+ contacts for any
cytokine. Only 55% of TB cases and 35% of TST+ contacts could
be deemed to be responders based on IFN-c production
(compared to almost 90% following PPD stimulation), however,
this was still significantly higher than TST2 contacts with ,5%
producing IFN-c at levels above background (mean+2SD).
Results
Pattern of cytokine production following stimulation
with PPD
Following stimulation with PPD, production of all cytokines
except IL-18 was significantly higher from TB cases compared to
TST2 contacts (Figure 1) while production of IFN-c, IL-13 and
IL-17 were all significantly higher in TST+ compared to TST2
contacts (p = 0.0027; p = 0.0266 and p = 0.0105 respectively;
Figs. 1A, E, F). No differences were seen between TB cases and
TST+ contacts for any cytokine but TB cases had the highest level
of all cytokines compared to TST+ and TST2 HHC with IFN-c
being produced at the greatest amount (median[interquartile
range (IQR)] = 2923[1101–5819]pg/mL for TB cases, 2043[316–
7573]pg/mL for TST+ contacts but only 201[46–496]pg/mL for
TST2 contacts (Fig. 1A). TNF-a production (Fig. 1B) was also
high from TB cases (median[IQR] = 476[117–628]pg/mL compared to 191[31–788]pg/mL for TST+ contacts and only 39[0–
205]pg/mL for TST2 contacts) with production of IL-13 low but
still significantly higher than TST2 HHC (30[12–45]pg/mL
compared to 24[7–51] for TST+ and 8.5[0–16] for TST2 HHC.
Production of IL-18 was very low and was the only cytokine with
no significant difference between any of the three groups
(median[IQR] = 0.5[0–6.3] for TB cases, 0.5[0–3.1] for TST+
contacts and 0[0–6.1] for TST2 contacts (Fig. 1G). Analysis of the
proportion of responders was also performed as this further
contributes to our understanding of the pathogenesis of TB. For
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Pattern of cytokine production following stimulation
with TB10.4
Following stimulation with TB10.4, production of IFN-c, TNF-a
and IL-12(p40) were all significantly higher from TB cases compared
to TST2 contacts (p = 0.0215, p = 0.002 and p = 0.0176 respectively; Figs. 3A, B and D). No significant differences between TST+
and TST2 contacts were seen for any cytokine but production of
TNF-a and IL-12(p40) were both significantly higher from TB cases
compared to TST+ contacts (p = 0.0266 and p = 0.0456 respectively; Figs. 3B and D). The production of these 2 cytokines was actually
greater following TB10.4 stimulation than following PPD stimulation. Median[IQR] levels of TNF-a was 544[172–959], 175[0–
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Figure 1. Cytokine responses following PPD stimulation. Whole blood from TB cases (n = 36), TST+ (n = 20) and TST2 (n = 19) contacts was
stimulated for 7 days with PPD and the supernatant assessed by multiplex cytokine analysis. A) IFN-c. B) TNF-a, C) IL-10, D) IL-12(p40), E) IL-13, F) IL-17
and G) IL-18. Line indicates median. Data were analysed using Tweedie distributions with p-values indicating significant differences after adjustment
for age and sex. H) Percentage of responders producing IFN-c, IL-10, TNF-a, IL-12, IL-13, IL-17, IL-18. Dark bars = cases, grey bars = TST+ contacts, white
bars = TST2 contacts; p-values are indicated and refer to comparison with TST2 contacts.
doi:10.1371/journal.pone.0012365.g001
different to that seen following PPD and EC stimulation. Whereas
for both PPD and EC stimulation the most responders were seen
with IFN-c, IL-13 and IL-17 production, following TB10.4
stimulation the majority of responders was seen with TNF-a
production (80% TB cases, 45% TST2 HHC but ,5% of TST+
HHC). Most other cytokines had less than 50% responders for any
group.
1040] and 29[0–543] pg/mL respectively for TB cases, TST+ and
TST2 HHC (compared to 476[117–628]pg/mL for TB cases postPPD stimulation) and for IL-12(p40) was 643[97–1476], 141[0–436]
and 125[0–301]pg/mL for TB cases, TST+ and TST2 HHC
respectively (compared to 261[1.9–493]pg/mL for TB cases postPPD stimulation). Analysis of the proportion of responders within
each group showed significantly more TB cases producing TNF-a,
IL-12(p40), IL-13 and IL-18 compared to TST+ contacts (p,0.001,
p,0.05, p,0.01 and p,0.01 respectively; Fig. 3H) and TNF-a and
IL-18 compared to TST2 contacts (p,0.01 for both; Fig. 3H). No
difference in the proportion of responders between TST+ and
TST2 contacts was observed. The pattern of production was
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Multivariate analysis for classification of TB cases, TST+ or
TST2 contacts
We next used multivariate analysis to attempt to correctly
classify subjects into TB cases, TST+ or TST2 household contacts
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Biomarkers for TB
Figure 2. Cytokine responses following EC stimulation. Whole blood from TB cases (n = 36), TST+ (n = 20) and TST2 (n = 19) contacts was
stimulated for 7 days with ESAT-6/CFP-10 fusion protein and the supernatant assessed by multiplex cytokine analysis. A) IFN-c. B) TNF-a, C) IL-10, D)
IL-12(p40), E) IL-13, F) IL-17 and G) IL-18. Line indicates median. Data were analysed using Tweedie distributions with p-values indicating significant
differences after adjustment for age and sex. H) Percentage of responders (prior to adjustment for age and sex) producing IFN-c, IL-10, TNF-a, IL-12,
IL-13, IL-17, IL-18. Dark bars = cases, grey bars = TST+ contacts, white bars = TST2 contacts; p-values are indicated and refer to comparison with TST2
contacts.
doi:10.1371/journal.pone.0012365.g002
contacts while analysis of TNF-a, IL-12(p40) and IL-17 in
combination increased this to 85% mainly due to an increase in
specificity from 44% to 61% with sensitivity increasing from 92%
to 97%. Thus our data shows enhanced classification if analysis is
performed with multiple cytokines. ROC analysis determined a
cut-off for active TB disease of TNF-a .166pg/mL, IL-12(p40)
.210pg/mL and IL-17 .26pg/mL respectively.
Multivariate analysis was also performed to attempt to classify
TST+ and TST2 HHC. We found that the level of % correct
classification was lower for TST+ and TST2 contacts than for
differentiation between TB cases and TST+ contacts suggesting
that the 7-day assay we used is better for discriminating between
(Table 1). Following PPD stimulation, analysis of IFN-c alone
resulted in 74% correct classification into TB cases and TST+
HHC (Table 1). Combined analysis of IL-12(p40) and IL-13
resulted in lower sensitivity (89% compared to 94% for IFN-c
alone) but increased specificity (56%) resulting in 77% correct
classification (Table 1). Analysis of TNF-a, IL-12(p40) and IL-13
together resulted in 81% correct classification; sensitivity was 94%
and specificity was 56%. Following EC stimulation, analysis of IL12(p40) alone resulted in 81% correct classification and there was
a slight decrease (to 79%) with addition of other cytokines
(Table 1). Following TB10.4 stimulation, analysis of IFN-c alone
resulted in 76% correct classification into TB cases or TST+
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Figure 3. Cytokine responses following TB10.4 stimulation. Whole blood from TB cases (n = 36), TST+ (n = 20) and TST2 (n = 19) contacts was
stimulated for 7 days with TB10.4 and the supernatant assessed by luminex technology for secretion of cytokines. A) IFN-c. B) TNF-a, C) IL-10, D) IL12(p40), E) IL-13, F) IL-17 and G) IL-18. Line indicates median. Data were analysed using Tweedie distributions with p-values indicating significant
differences after adjustment for age and sex. H) Percentage of responders (prior to adjustment for age and sex) producing IFN-c, IL-10, TNF-a, IL-12,
IL-13, IL-17, IL-18. Dark bars = cases, grey bars = TST+ contacts, white bars = TST2 contacts; p-values are indicated and refer to comparison with TST2
contacts.
doi:10.1371/journal.pone.0012365.g003
TST+ or TST2 HHC (74% correct classification) and this was
actually decreased with the addition of other cytokines (Table 1).
active disease and latent infection than between infection and noninfection, at least for the antigens we used. Following PPD
stimulation, analysis of IFN-c, TNF-a or IL-13 all resulted in 70%
correct classification of TST+ or TST2 HHC (Table 1; TNF-a,
IL-13 not shown) with IFN-c and IL-10 together giving 73%
correct classification and this was not increased with addition of
more cytokines (eg IFN-c, IL-10 and IL-12(p40); Table 1).
Following EC stimulation, IFN-c alone resulted in only 67%
correct classification, mainly due to low sensitivity, while analysis
of IFN-c together with IL-17 and IL-18 increased the percent
correctly classified slightly to 72% (Table 1). Analysis of IFN-c
alone following TB10.4 stimulation gave the best classification into
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Comparison of M. africanum versus M. tuberculosis
infection
M. africanum (MA) is a common cause of TB in West Africa and
is thought to be associated with an attenuated response to ESAT-6
[22]. As such we further analysed our results according to infection
of cases with either MTb or MA (Table 2). IFN-c production was
highest for all stimuli regardless of infection type (median[IQR}
for PPD = 2832[822–5679] pg/mL for MTb infection and
2495[1120–6082] pg/mL for MA infection; Table 3). There were
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Biomarkers for TB
Table 1. Multivariate analysis for classification into TB cases, TST+ or TST2 contacts.
Antigen
Cytokines
% Sensitivity
% Specificity
% Correct classification
PPD
IFN-c
94
33
74
IL-12(p40)+IL-13
89
56
77
TB Cases versus TST+ HHC
EC
TB10.4
TNF-a+IL-12(p40)+IL-13
94
56
81
IL-12(p40)
97
44
81
IL-12(p40)+IL-10
91
50
79
IL-12(p40)+TNF-a+IL-17
94
44
79
IFN-c
92
44
76
TNF-a+IL-12(p40)
97
56
83
TNF-a+IL-12(p40)+IL-17
97
61
85
TST+ versus TST2 HHC
PPD
EC
TB10.4
IFN-c
69
71
70
IFN-c+IL-10
69
77
73
IFN-c+IL-10+IL-12(p40)
69
77
73
IFN-c
72
61
67
IFN-c+IL-13
67
72
69
IFN-c+IL-17+IL-18
72
72
72
74
IFN-c
83
65
IFN-c+IL-12(p40)
78
65
71
IFN-c+IL-12(p40)+IL-17
83
59
71
doi:10.1371/journal.pone.0012365.t001
infected (TST+) or non-infected (TST2) household contacts.
Analysis of TNF-a, IL-12(p40) and IL-17 in combination following
TB10.4 stimulation resulted in over 85% correct classification into
active TB disease or latent infection. Analysis of IFN-c resulted in
74% correct classification into TST+ or TST2 HHC and
additional cytokines did not enhance classification indicating that
7-day stimulation is optimal for discriminating between active
disease and latent infection.
IFN-c production following ESAT-6/CFP-10 stimulation is the
basis of the currently available diagnostic tests for determining TB
infection status but can’t differentiate between infection and
disease. The present study we found low sensitivity of IFN-c
production following EC stimulation for differentiating into TST+
or TST2 HHC but good discrimination between infection and
disease following TB10.4 stimulation indicating that a longer-term
stimulation is optimal for detection of active disease. This may also
be antigen-dependent since we only saw this with TB10.4
stimulation and, since TB10.4 is a virulent part of the MTb
genome, it presumably plays an important role with increasing
disease severity [21]. In this study we did not see any differences in
cytokine production based on x-ray scores (data not shown) but
these findings should be validated in a larger cohort where
stratification according to x-ray scores, bacterial load and other
epidemiological factors could be performed.
PPD stimulation resulted in differences in production of most
cytokines between TB cases and TST2 contacts but also a
significantly higher level of IL-17 from TST+ compared to TST2
contacts. IL-17 was also shown to enhance discrimination between
TB cases and TST+ contacts following TB10.4 stimulation.
Recent studies have suggested a role for IL-17 in protection
against disease progression [8] with IFN-c being shown to
contribute to the regulation of the IL-17 producing cells [23].
We have previously shown that IL-17 is significantly decreased in
no significant differences between the groups, however we did see
a tendency for MA-infected cases to have increased TNF-a
production (529[126–750] compared to 346[83–602]pg/mL;
115[0–137] compared to 44[0–122]pg/mL and 744[414–1924]
compared to 455[154–937] pg/mL following PPD, EC or TB10.4
stimulation respectively; Table 3). In addition MA-infected cases
had higher IL-10 production following PPD and TB10.4
stimulation (Table 3). IL-13, IL-17 and IL-18 production was
similar regardless of infection type but IL-12(p40) showed variable
results depending on the stimulation used (Table 3): following PPD
stimulation levels were lower from MA- compared to MTbinfected cases (152[0–499] compared to 265[14–488] pg/mL) but
higher following both EC and TB10.4 stimulation (74[0–373]
compared to 0[0–103]pg/mL for EC and 939[80–2666] compared to 613[107–943]pg/mL for TB10.4; Table 3).
Discussion
This study assessed cytokine production following 7-day
stimulation of whole blood from TB cases and their latently
Table 2. Subject information.
Case
TST2 Contact TST+ Contact
n=
36
19
20
Age (median[IQR])
25[20–37]
22[18–31]
27[19–39]
Sex (% Male)
73
26
35
Genotype (MA:MTb)
14:21
N/A
N/A
IQR = interquartile range; MA = M. africanum; MTb = M. Tuberculosis.
doi:10.1371/journal.pone.0012365.t002
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Table 3. Comparison of responses in M. Africanum versus M. Tuberculosis infected TB cases.
Stimulation
Group
n=
IFN-c
PPD
TB CASE
21
2832[822–5679]
346[83–602]
97[24–236]
265[14–488]
35[10–45]
118[28–172]
2[0–9]
MA CASE
14
2495[1120–6082]
529[126–750]
152[62–301]
152[0–499]
28[13–49]
116[76–222]
0[0–6]
0[0–0.9]
EC
TB10.4
TNF-a
IL-10
IL-12(p40)
IL-13
IL-17
IL-18
TB CASE
21
440[130–1472]
44[0–122]
7[0–58]
0[0–103]
6[0–19]
57[0–82]
MA CASE
14
360[0–590]
115[0–137]
0[0–13]
74[0–373]
1.2[0–11]
0[0–48]
0[0–0.5]
TB CASE
21
338[120–496]
455[154–937]
73[0–237]
613[107–943]
0[0–5]
0[0–42]
1[0–9]
MA CASE
14
252[0–1930]
744[414–1924]
163[22–406]
939[80–2666]
0[0–10]
0[0–80]
0.7[0–6]
TB = M. tuberculosis, MA = M. africanum. 0 = below limit of detection for assay; after background subtraction, negative values were converted to 0.
doi:10.1371/journal.pone.0012365.t003
saw a tendency towards increased IL-10 and TNF-a production in
TB cases infected with MA compared to MTb, this had no
significant effect on the overall cytokine profiles. Unfortunately we
did not have enough contacts of index cases infected with either
strain of bacteria to accurately assess the differences between them.
Thus, while a similarity between MA and MTb in terms of the
cytokine pattern is interesting, this should be validated in a larger
sample size in order to provide a better platform for multivariate
analyses.
In conclusion, this study shows that analysis of TNF-a, IL12(p40) and IL-17 following long-term stimulation with TB10.4
TB cases compared to household contacts following overnight
stimulation with both EC and PPD [24]. These differences
presumably reflect the generation of a memory response to the TB
antigens in the long-term culture compared to analysis of the
immediate effector functions in overnight cultures. Therefore, in
terms of development of a biosignature for active TB, our results
suggest that long-term culture is required to distinguish between
TB cases and TST+ contacts in a TB-endemic setting where the
TST+ contacts have a relatively large pool of MTb-specific cells.
The use of short-term assays will preferentially detect IFN-c
production by primed T cells [25], thus will show increased levels
for both subjects with active disease and those individuals who
have recently acquired infection thereby providing a potential
explanation for lack of discrimination of active disease based on
IFN-c production following short-term antigenic stimulation. This
is not to say that short-term assays won’t be beneficial for detection
of active disease in future, and indeed, are more clinically desirable
than longer assays. Preliminary data from a recent study in South
Africa did show differentiation between active disease and latent
infection using short-term stimulation by analysing multiple
cytokine/chemokine markers [26] but this will need to be
validated in a larger cohort and at different sites in Africa due
to genetic differences seen in response to TB antigens [27]. Our
data shows that TB10.4 stimulation followed by multi-cytokine
analysis allows discrimination between active disease and latent
infection and should enhance classification of subjects, particularly
those who are difficult to diagnose (ie HIV-positive or extrapulmonary TB) and at sites which lack x-ray and/or culture facilities
(Fig. 4). Development of field-friendly, rapid diagnostics is essential
in the fight against TB and analysis of cytokine responses following
TB10.4 stimulation is promising; however it firstly needs to be
validated in a short-term assay (Fig. 4). The relative use of
peripheral blood IGRAs for diagnosis of active TB does appear to
depend not only on the extent of pulmonary involvement but on
the disease severity with low levels of cytokines (at least IFN-c)
present in more advanced disease [12]. While this may indicate
less reactivity, it is more likely that the cytokine producing cells are
simply required at the site of infection thus reducing the benefits of
blood as a tool for diagnostics. Clearly more work is required but
our results and others indicate the importance of generating an
algorithm incorporating multiple factors that can accurately
determine the TB status of an individual [28].
Due to the prevalence of M. africanum infection in The Gambia,
we analysed whether this resulted in any differences in the host
immune response. This is important since the progression from
latent infection to active disease is increased in contacts of index
cases infected with M. tuberculosis compared to M. africanum
indicating a potential role for the bacteria in determining the
outcome of the host immune response [29,30]. However, while we
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Figure 4. Flow chart demonstrating how cytokine production
following TB10.4 stimulation will improve diagnosis of active
TB. At the moment, patients with suspected TB may be confirmed by
analysis of chest x-ray (CXR) plus sputum culture positivity in
laboratories which have these capabilities. Analysis of TNF-a, IL12(p40) and IL-17 production following TB10.4 stimulation should
enhance classification into active disease or latent infection in
laboratories without culture facilities and also for patients with
suspected TB but smear/culture negative results (such as HIV-positive
patients or extrapulmonary TB patients). These findings should be
further validated in a short-term assay and in difficult to diagnose
patient groups.
doi:10.1371/journal.pone.0012365.g004
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Biomarkers for TB
results in 85% correct classification into TB cases and TST+
contacts and should be validated further for potential use in the
next generation of immunodiagnostics.
added to each well and incubated for 10 min. The plate was again
washed and resuspended in 125ml of assay buffer, sealed, mixed
and immediately read on the Bio-plex analyser using Bioplex
manager software (version 4.0) and a low PMT (photomultiplier
tube) setting. The cytokine ranges were as follows (pg/mL). IL-10:
1.6–25201; IL-12(p40): 1.8–28172; IL-13: 0.3–4625; IL-17: 1.9–
29871; IL-18: 2.1–31981; IFN-c: 1.9–30205 and TNF-a: 5.9–
92920.
Methods
Ethics statement
This study was conducted according to the principles expressed
in the Declaration of Helsinki. Ethical approval was obtained from
the Gambia Government/Medical Research Council Joint Ethics
Committee. All patients provided written informed consent for the
collection of samples and subsequent analysis.
Mycobacteriology
Sputum samples were stained with auramine and the ZiehlNielsen (ZN) method. Sputum was decontaminated using N-acetyl
cysteine (NALC)-NaOH before culture in Bactec vials (Becton
Dickinson) and on paired Lowenstein-Jensen slopes. Positive
cultures were confirmed by ZN smear and stored in glycerol at
270uC.
Participants
36 HIV-negative sputum smear-positive TB cases and 39 of
their Mycobacterium-exposed household contacts were consecutively
recruited as part of ongoing tuberculosis case-contact studies at the
MRC (UK) unit in The Gambia and the Gates Grand Challenge
6, Biomarkers for TB. Subject information is presented in Table 2.
Ethical approval was obtained from the joint Gambia Government/Medical Research Council Ethics committee and all
subjects gave informed consent. All cases and contacts underwent
a clinical assessment, including a screen for malaria and intercurrent illness. Of the confirmed pTB cases, 2.5% had Grade I (+),
27.5% Grade 2 (++) and 70% Grade 3 (+++) smears (taken as
highest grade out of 2 consecutively positive smears). Tuberculin
skin tests (TST; 2 tuberculin units [TU], PPD RT23, SSI,
Denmark) were performed in order to classify the household
contacts into TST+ (n = 20) and TST2 (n = 19). Due to the
influence of prior BCG vaccination and environmental mycobacterial in this TB-endemic setting, subjects with skin test induration
of $10mm diameter were categorised as TST positive. TB cases
were further classified according to the degree of pulmonary
involvement seen by chest x-ray into subjects with minimal disease
(13/36; 36%), moderate disease (22%) and advanced disease
(42%). Other clinical data such as night sweats, cough duration
and weight loss were obtained from the TB cases where possible.
Blood samples were taken from both TB cases and their contacts
at recruitment. Of the TB cases, 35 had genotyped isolates, of
which 14 (40%) were identified as M. africanum and the remainder
as M. tuberculosis.
Mycobacterial genotyping
Stored isolates were grown in Middlebrook 7H9 broth with
OADC (oleic acid, albumin, dextrose, and catalase) supplement
for DNA extraction. 10ng of DNA was used for spoligotype
analysis with commercially available membranes (Isogen Biosciences, The Netherlands). Spoligotype films were scanned and
classified using software designed in Matlab (Mathworks, USA),
followed by manual editing and confirmation. Each spoligotype
pattern was classified into a binary code and the result was entered
in a Microsoft Access database (Redmond, USA). For isolates that
could not be reliably classified as M. tuberculosis or M. africanum
based on spoligotype analysis alone, the presence or absence of
lineage defining large sequence polymorphisms RD702 and TbD1
was assessed, as previously described [30].
Statistical analysis
Antigen-specific samples had background subtracted (unstimulated results) and negative values were adjusted to zero. The 3
groups of subjects were compared using generalised linear
regression assuming a Tweedie distribution, which allows the
zero inflation (caused by non-responders) to be modeled [31].
This allows adjustment for age and sex and results in greater
power than can be achieved using standard non-parametric tests.
Univariate logistic regression was also performed. Significance
was tested at 5% and quoted p-values are adjusted for multiplicity
using Bonferroni correction. For each cytokine, responders were
defined as those producing levels .2SD from the mean of the
unstimulated samples for each group (cases, TST+ and TST2).
Multivariate discrimination was tested using a support vector
machine [32], with testing and training sets selected using
holdout cross-validation with half the data allocated to each
training set. ROC analysis was also performed to determine cutoff levels and likelihood ratios for each analyte. M. africanum
versus M. tuberculosis results were analysed using Mann-Whitney
U tests. All analyses were performed following background
subtraction of the samples using STATA version 9.1 (Stata
Corporation, USA) and Matlab version 7.6 (Mathworks,
Natwick, 2008).
Whole blood antigen stimulation
Blood was diluted 1:10 in RPMI and added to wells containing
antigen in triplicate. Antigens used were PPD (SSI; final
concentration 10mg/mL), ESAT-6/CFP-10 fusion protein (EC;
final concentration 10mg/mL) and TB10.4 (SSI; final concentration 10mg/mL). Unstimulated wells were used as a control for nonspecific cytokine production. Plates were incubated at 37uC, 5%
CO2 for 7 days. Approximately 90ml of culture supernatant was
removed from triplicate wells, mixed in a single well in a new plate
and stored at 220uC prior to multi-plex cytokine analysis.
Multi-plex analysis for cytokine production
Culture supernatants were analysed using a Bio-Rad custom
made 7-plex kit containing IL-10, IL-12(p40), IL-13, IL-17, IL-18,
IFN-c and TNF-a according to the manufacturer’s instructions.
Following pre-wetting of the filter plate, 50ml of bead suspension
was added to each well and washed twice. 50ml of samples (tested
singly) and standards (in duplicate) were then added, the plate
sealed and shaken for 30 sec at 1100rpm then incubated for
1 hour at 300rpm. The plate was washed 3 times then 25ml of
detection antibody added and the plate shaken and incubated for
30 min. at 300rpm. After washing, 50ml of 16streptavidin-PE was
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Acknowledgments
We thank Prof. Tom Ottenhoff and Dr. Kees Franken for provision of
ESAT-6/CFP10 fusion protein, all study participants, Mr. Simon Donkor
for data management, field workers for sample collection, the TB
Immunology laboratory staff, TB diagnostic laboratory staff and the
Gambian National Tuberculosis and Leprosy Control programme for
continuing collaboration.
8
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Biomarkers for TB
spoligotyping: BCdJ. Statistical analysis: DJJ. Recruited all subjects: IMA.
Intellectual input with design of experiments and writing of the manuscript:
MOO.
Author Contributions
Conceived and designed the experiments: JSS MOCO. Performed the
experiments: JSS. Analyzed the data: JSS DJJ. Contributed reagents/
materials/analysis tools: BCdJ. Wrote the paper: JSS MOCO. Performed
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