Namuganga et al.

BMC Infectious Diseases (2017) 17:600

DOI 10.1186/s12879-017-2687-z

RESEARCH ARTICLE Open Access

Suitability of saliva for Tuberculosis

diagnosis: comparing with serum
Anna Ritah Namuganga1,3* , Novel N. Chegou2, Paul Mubiri3, Gerhard Walzl2 and Harriet Mayanja-Kizza3,4

Abstract
Background: In the search for fast, simple and better ways for diagnosis of tuberculosis (TB), there is need to
discover and evaluate new biomarkers that are found in samples other than sputum to determine their
effectiveness. This study examined the utility of saliva vis-a-vis serum by evaluating levels of biomarkers found in
saliva and serum from TB suspects.
Methods: Study enrolled tuberculosis suspects. Sputum MGIT was used as the gold standard for active TB.
Quantiferon gold-In tube assay was done to identify exposure to Mycobacterium tuberculosis (M.tb). Multiplex assay
was run for 10 markers using a 10 plex customized kit from Bio-Rad Laboratories.
Results: There was a significant difference between saliva and serum marker levels. Saliva had significantly higher
levels of GM-CSF and VEGF. Serum had higher levels of MIP-1a, b, TNF-a, G-CSF and IFN-g. Serum levels of IL-6,
VEGF and TNF-a were significantly different between participants with active TB disease and those with other
respiratory diseases.
Conclusion: Salivary TB biomarkers are worth the search to evaluate their ability to differentiate between TB
disease states for generation of a non invasive point of care test for TB diagnosis.
Keywords: Biomarkers, Quantiferon, Saliva

Background (IGRA) such as the Quantiferon TB Gold and the T-

Globally, tuberculosis (TB) ranks alongside HIV as the SPOT assays. These tests require a blood draw to evaluate
leading cause of mortality and morbidity [1]. The the body’s T cell response towards Mycobacterium tuber-
diagnosis of the disease remains a major problem, due to culosis (Mtb), as a means to diagnose infection with Mtb
several shortcomings in the currently available diagnos- infection. These assays are based on the principle that in-
tic tests. Smear microscopy, the most widely available dividuals who have previously been exposed to Mtb
TB diagnostic test has poor sensitivity [2]. Sputum habour pre-activated T cells in circulation, which rapidly
culture, the gold standard has a long turnaround time respond with the secretion of IFN-γ after re-challenge in
(up to 42 days) [3], whereas the recently developed vitro, with Mtb specific antigens. IGRAs have been shown
GeneXpert MTB/RIF test (Cepheid Inc., Sunnyvale, to be useful in the diagnosis of Mtb infection especially in
USA), although rapid, is expensive, amongst other limi- comparison with the tuberculin skin test. However, they
tations which hamper its use in resource-poor countries are not able to discriminate with latent Mtb infection and
[4]. All these tests also depend on the quality of sputum active TB disease. This therefore means that the assays are
provided by the patient, to yield reliable results. This is not useful in settings with high prevalence of latent TB.
highly problematic in children who cannot cough, and Another limitation of these assays is the fact that they are
in individuals with extra pulmonary TB. overnight assays, requiring a second visit to the hospital.
Current research has given birth to immunodiagnostic Assays based on ex-vivo samples such as serum, saliva or
tests including the interferon gamma release assays whole blood, may be more beneficial as they may lead
to a more rapid diagnosis, and tests based on such as-
* Correspondence: annamuganga@gmail.com says may be easily converted to point-of-care tests.
1
Joint Clinical Research Centre, Kampala, Uganda
3
Uganda – Case Western Research Collaboration, Mulago-Kampala, Uganda
Full list of author information is available at the end of the article

© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Namuganga et al. BMC Infectious Diseases (2017) 17:600 Page 2 of 11

When compared to serum, saliva has advantages had cough for at least 2 weeks, in addition to any other
which include; low protein content, easy non invasive TB symptoms including fever, night sweats, uninten-
collection and ease of storage [5–7]. Saliva has previ- tional weight loss, chest pain, haemoptysis and contact
ously been used for molecular DNA testing in diagnosis with an active TB case. These individuals also had no
of systemic diseases like hepatitis [8] HIV, renal diseases, history of TB treatment in the preceding 3 months.
cardiovascular diseases, autoimmune diseases, cancer, Those who gave informed consent to participate in the
diabetes and other infectious diseases [9]. Recently, more study were enrolled, samples collected and stored at
studies have ventured into the search for biomarkers of -80 °C. Of all the PTB suspects enrolled in the bigger
TB in saliva [10, 11]. Compared to blood, saliva has ad- study, only 78 participants were selected. Serum and
vantages as a specimen for TB diagnosis which include saliva samples from these 78 PTB suspects were used
none-invasiveness, no need for skilled personnel for col- for this study. The study received ethical approval from
lection, none clotting ability and ease to handle [12]. A the Uganda National Council of Science and Technology
study by Phalane et al. [13], compared serum with saliva (UNCST), Makerere University College of Health Sciences
and it was shown that some host inflammatory bio- (MU-CHS) as well as the Joint Clinical Research Centre
markers are expressed in much higher concentrations in (JCRC) institutional review boards.
saliva than are in blood. Further studies also showed that All participants had chest x-ray, smear and culture
some of the host markers detected in saliva showed po- done for diagnosis of active pulmonary TB (PTB).
tential as diagnostic biomarkers for TB disease [10, 11]. Sputum samples from all study participants were
However all these previous TB studies have only been cultured using the MGIT method (BD Biosciences) and
done on samples collected from a single study site. It is positive cultures were speciated to confirm Mtb
known from previous immunological studies [14] that complex, regardless of the smear result.
immune responses tend to differ in patients recruited
from different African countries, thereby highlighting Classification of study participants and reference standard
the need for potential immunological based biomarkers Using a combination of clinical, radiological, and labora-
to be investigated in different geographical regions. In tory findings, participants were classified as definite PTB
the present study, we evaluated the expression of host cases, probable TB cases, participants with other respira-
biomarkers in serum in comparison to saliva, and fur- tory diseases (ORD). A positive culture result was used
ther investigated whether any of these biomarkers had to classify study participants as active PTB disease and a
potential in differentiating active TB disease from latent negative culture accompanied by clinical features, radio-
or no TB infection, in individuals with presumed TB logical findings was used to classify those with other
disease, recruited from Mulago hospital study site in respiratory diseases (ORD) as described in the recent
Uganda. Replication of the findings from previous South paper by Chegou et al. [15]. Briefly, ORD cases had a
African studies [10, 11, 13] in the present study would range of other diagnoses, including upper and lower
make the case for further investigation of the candidate respiratory tract infections (viral and bacterial infections,
markers identified so far and other recently identified although attempts to identify organisms by bacterial or
markers in future larger studies and ultimately, the viral cultures were not made), and acute exacerbations
possible development of fiend-friendly TB diagnostic of chronic obstructive pulmonary disease or asthma. In
tests based on such salivary signatures. Furthermore, as assessing the accuracy of host biosignatures in the diag-
saliva is a mucosal/airway linked sample and is relatively nosis of TB disease, all the definite and probable TB
closer to the site of TB disease than peripheral blood, cases were classified as active PTB, and then compared
saliva may be a more informative sample for biomarker to the ORD cases. In addition, those with negative cul-
discovery purposes. ture (ORD) were re classified using the Quantiferon
Gold In Tube assay. The latent TB infection group had
positive quantiferon results while the No TB infection
Methods group had a negative quantiferon result.
Study participants
Participants enrolled in this study were part of a bigger Sample collection and processing
African European Tuberculosis consortium (AETBC) Blood for serum separation was drawn into 8 ml serum
study that started in November 2010 and ended in separation tubes (BD Biosciences) and transported to
December 2012. This study enrolled adults with signs the laboratory at ambient temperature. This was centri-
and symptoms suggestive of TB disease (TB suspects), fuged at 2000×g for 10 min at room temperature. Serum
prior to the establishment of a clinical diagnosis. Ugandan was then harvested, aliquoted and stored at -80 °C until
study participants were recruited from within 25 km of use. Saliva was drawn in salivette tubes (Sarsedt,
Mulago Hospital in Kampala. All study participants had Germany) according to manufacturer’s instruction and
Namuganga et al. BMC Infectious Diseases (2017) 17:600 Page 3 of 11

Table 1 Participant characteristics Mtb infection especially in the patients with ORD and
Variable All PTB No TB QFT results were not used for patient management or
LTBI Uninfected for classification of study participants as TB or ORD. At
No. of participants 78 39 21 18 enrolment, all subjects had 3 ml of blood drawn for
QFT. IFN- γ levels in QFT supernatants were measured
Female 41(53%) 17(22%) 11 (14%) 13 (17%)
using the QFT ELISA. As instructed by the manufac-
HIV positive % 13 (17%) 5 (6%) 2 (3%) 6 (8%)
turer (Cellestis, Australia; now Qiagen, Germany), tests
QFT positive 57 (73%) 36 (46%) 21 (27%) 0 were regarded as positive for TB infection if the differ-
Abnormal X-ray 42 (54%) 34 (44%) 7 (9%) 1 (1%) ence between the TB antigen stimulated and unstimu-
Table 1: The distribution of study participants according to their sputum MGIT lated (Nil) supernatant was greater than or equal to
culture, Quantiferon and X-ray results is shown. All the TB patients were MGIT 0.35 IU/ml but greater than or equal to 25% of the Nil
positive. No TB cases (all MGIT negative) were further classified as LTBI or
uninfected individuals based on Quantiferon In Tube results. LTBI latent TB value. The tests were regarded as negative if that
infection, PTB active pulmonary TB disease difference was <0.35 IU/ml and less than 25% of the Nil
value, provided that the value of mitogen stimulated
transported to the lab on ice. These were centrifuged at supernatant was ≥0.5 IU/ ml after subtraction of the
1000×g for 2 min, aliquoted into labeled tubes and unstimulated value as per the manufacturer’s manual
stored at -80 °C until use. [16]. The QFT analysis software, version 2.50 was used
Sputum samples were collected from all participants and for analysis.
cultured using MGIT method (BD Biosciences). All sam-
ples that demonstrated growth of microorganisms were ex- Luminex immunoassay
amined for acid-fast bacilli using the the Ziehl–Neelsen The levels of 10 host markers were evaluated in serum and
method followed by either Capilia TB testing (TAUNS, saliva samples for all study participants using a 10 plex cus-
Numazu, Japan) or standard molecular methods, to tomized kit from Bio-rad Laboratories (Hercules, CA,
confirm the isolation of organisms of the M.tb complex. USA) on the Bio-Plex platform (Bio Rad). These included
Quantiferon Gold In Tube assay was used to identify interferon gamma (IFN-γ), interleukin (IL) -2, 5, 6, gran-
exposure to Mycobacterium tuberculosis. ulocyte colony stimulating factor (G- CSF), granulocyte
monocyte colony stimulating factor (GM-CSF), macro-
Immunological assays phage inflammatory protein (MIP)-1α and β, vascular
The Quantiferon Gold In Tube assay (QFT) was per- endothelial growth factor (VEGF) and tumor necrosis fac-
formed on all study participants in order to diagnose tor alpha (TNF-α). As recommended by the manufacturer,

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M a r k e r s in s e r u m a n d s a liv a

Fig. 1 Median levels in pg/ml and interquartile ranges for all host markers in all study participants in both serum and saliva samples
Namuganga et al. BMC Infectious Diseases (2017) 17:600 Page 4 of 11

the serum and saliva samples were diluted 1:4. Samples Table 3 Median levels of markers were significantly different
from one study participant were tested on the same plate. between saliva and serum for all active pulmonary TB participants
The Bio Plex Manager software, version 6.1 was used for Marker Median (pg/ml) Saliva Median (pg/ml) serum p-value
bead acquisition and analysis of median fluorescent IL-5 3.7 (2.7–4.7) 1.6 (0.6–2.7) <0.0001
intensity. IL-6 5.1 (2.4–9.5) 33.1 (12.9–60.3) <0.0001
G-CSF 0.0 (0.0–40.5) 76.1 (53.2–123.0) <0.0001
Statistical analysis
GM-CSF 257.9 (77.9–428.9) 0.0 (0.0–0.0) <0.0001
Data were analyzed using GraphPad Prism, version 6.01
(GraphPad Soſtware, California, USA) and the statistica MIP-1a 1.9 (1.1–2.6) 6.41 (4.2–35.6) <0.0001
software (StatSoft, USA). Differences in analyte levels MIP-1b 0.0 (0.0–0.0) 178.1 (98.7–245.8) <0.0001
between the TB patients and participants without TB VEGF 1486 (104–1960) 224.6 (93.2–654.9) <0.0001
disease or between the marker levels detected in saliva TNF-a 0.0 (0.0–8.5) 19.6 (7.4–26.6) <0.0001
and serum levels were evaluated by the Mann-Whitney
IFNg 0.0 (0.0–15.6) 43.3 (0.94–74.3) 0.0003
U test for nonparametric data analysis. The diagnostic
Table 3: Shown are the marker levels that are significantly different (median
accuracy of the markers was investigated by receiver levels and inter quartile ranges (in parenthesis) in serum compared to saliva in
operator characteristics (ROC) curve analysis. Optimal cut- only active pulmonary TB participants with Area Under the ROC curve ranging
between 0.73–0.97
off values, sensitivity and specificity were selected based on
the highest likelihood ratio. The General discriminant
analysis technique (GDA) was used to evaluate the accur- (≥0.35 IU/mL). The mean age of all participants was
acy of combinations between different biomarkers for the 32 ± 14 years. Eight of the 39 participants in the ORD
diagnosis of TB disease https://documents.software.dell.- group had abnormal chest X-rays which were consistent
com/statistics/textbook/general-discriminant-analysis. This with active TB (Table 1). A comparison was done to
employed the training and test set approach whereby study evaluate if there was a difference in the markers pro-
participants were randomly split into a 70% training and duced by those participants who had No TB but had
30% test set by the statistical software used in analysis abnormal x-ray (n = 8) and normal x-ray and without
(Statistica) https://documents.software.dell.com/statistics/ TB (n = 31). The 8 participants with abnormal x-ray
textbook/general-discriminant-analysis. Differences between were believed to have other chest infections. There
groups were considered significant if p values were <0.05. were no significant differences in the concentrations
of the host markers between these individuals and
Results other participants without TB disease and with
Study participants normal chest x rays.
Of the 78 participants, 39 (50%) had confirmed PTB by
MGIT, 41 (53%) were females and 13 (16%) were HIV Expression of host markers in serum and saliva samples
positive. Of all participants, 57 (73%) had a positive QFT from all study participants
as per the manufacturer’s recommended cut-off When the concentrations of host markers detected in
serum were compared to the levels detected in saliva in all
Table 2 Median levels of host markers were significantly
different between saliva and serum samples from all
Table 4 Median levels of markers were significantly different
participants, regardless of TB disease status
between saliva and serum for all participants
Marker Median (pg/ml) Saliva Median (pg/ml) serum p-value
Marker Median (pg/ml) Saliva Median (pg/ml) serum p-value
IL-2 0.0 (0.0–46.2) 0.0 (0.0–121.0) 0.03
IL-5 3.6 (2.7–4.7) 1.6 (0.6–2.1) <0.0001
IL-5 1.6 (0.0–25.0) 3.6 (0.6–27.5) <0.0001
IL-6 4.8 (2.1–5.4) 6.9 (5.6–9.9) <0.0001
IL-6 4.9 (2.4–7.8) 10.17 (6.5–36.3) <0.0001
G-CSF 0.0 (0.0–53.2) 72.5 (49.1–97.1) <0.0001
G-CSF 0.0 (0.0–50.1) 72.5 (52.2–103.7) <0.0001
GM-CSF 282.2 (36.3–405.5) 0.0 (0.0–0.0) <0.0001
GM-CSF 261.2 (40.4–409.1) 0.0 (0.0–0.0) <0.0001
MIP-1a 1.9 (1.3–2.3) 7.39 (3.9–35.8) <0.0001
MIP-1a 1.9 (1.1–2.5) 6.7 (4.2–35.6) <0.0001
MIP-1b 0.0 (0.0–0.0) 201.9 (127.5–297.3) <0.0001
MIP-1b 0.0 (0.0–0.0) 187.1 (114.4–260.4) <0.0001
VEGF 1368 (550.5–2020) 57.1 (0–208.6) <0.0001
VEGF 1467.2 (678.4–1975) 154 (0.0–322.2) <0.0001
TNF-a 0.0 (0.0–4.3) 12.7 (8.5–19.1) <0.0001
TNF-a 0.0 (0.0–4.8) 14.8 (8.2–22.5) <0.0001
IFNg 0.0 (0.0–7.7) 15.3 (10.4–52.9) 0.0003
IFNg 0.0 (0.0–13.1 44.3 (8.1–60.6) 0.0003
Table 4: Shown are the marker levels that are significantly different (median
Table 2: Shown are the median marker levels (inter quartile ranges in parenthesis) levels and ranges (in parenthesis) in serum compared to saliva in only
for markers that were significantly different in serum compared to saliva in all participants with other respiratory diseases with Area Under the ROC curve
participants, regardless of TB disease status ranging between 0.74–1
Namuganga et al. BMC Infectious Diseases (2017) 17:600 Page 5 of 11

study participants, significant differences were ob- MIP-1α, MIP-1β, TNF-α) were significantly higher in
served for all host markers, with p values ranging be- serum (Fig. 1, Table 2).
tween <0.0001 and 0.03. Overall, the concentrations When the concentrations of the host markers detected
of IL-2 and IL-5 in all participants were low in saliva were compared to the concentrations obtained
compared to other markers in both serum and saliva in serum, but only in the TB patients, significant differ-
samples regardless of the participants’ TB status. ences were observed for all markers (Table 3).
However, the levels of IL-2 and IL-5 markers were When the values obtained in the two sample types
comparably higher in serum. The concentrations of were compared, but only in the no TB patients,
GM-CSF and VEGF were significantly higher in saliva significant differences were observed for all markers with
in comparison to serum, whereas the concentrations AUCs greater than 0.73 (Table 4) with a p-value ranging
of the other eight markers (IL-2, 5, 6, G-CSF, IFN-γ, between <0.0001 and 0.0003 (Fig. 2).

80
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M a r k e r s in s e r u m a n d s a liv a in t h e N o T B a n d T B p a r t ic ip a n t s

Fig. 2 Median and inter-quartile ranges (pg/ml) of all 10 markers showing the differences between the active TB group (PTB) and the No PTB
group (those with other respiratory diseases; ORD) in serum and saliva of all the study participants
Namuganga et al. BMC Infectious Diseases (2017) 17:600 Page 6 of 11

Table 5 Median levels of the most promising host markers Table 7 Median markers levels in serum and saliva that were
detected in serum samples from patients with active TB group significantly different between the active TB group (TB), latent
(TB) or ORD group and accuracies in the diagnosis of TB disease TB infection and uninfected (No TB infection) group
Groups TB Vs ORD Groups PTB vs LTBI PTB vs HE LTBI vs HE
Marker IL-6 Serum VEGF Serum Marker IL-6 Serum VEGF Serum IFN-γ saliva
ORD (median pg/ml) 6.9 (5.6–9.9) 57.06 (0–208.6) PTB Median 33.11 224.6 0
pg/ml (12.9–60.3) (93.2–654.9) (0.0–15.6)
PTB (Median pg/ml) 33.11 (12.9–60.2) 224.6 (93.2–654.9)
LTBI 7.6 (5.6–10.7) 57.1 (0.0–230.3) 0 (0–16.7)
p-value <0.0001 0.001
(median pg/ml)
AUC 0.85 0.71 Uninfected 6.7 (4.3–8.7) 69.8 (0.0–198.9) 0.0 (0.0–0.0)
Cut off >36.4 >573.8 (median pg/ml)
Sensitivity 46.15 28.21 p-value <0.0001 0.001 0.03 0.04
Specificity 97.44 97.44 AUC 0.85 0.71 0.65 0.66
Table 5: Shown are the median and ranges (in parenthesis) levels of serum Cut off >36.4 >573.8 <0.47 <0.47
markers that were significantly different between the TB patients and the
group with other respiratory diseases (ORD) and area under the curve (AUC) Sensitivity 46.15 28.21 88.9 88.9
showing the diagnostic performance of the markers Specificity 97.44 97.44 41 43
Table 6: Shown are the median levels of IL-6, VEGF IFN- γ and inter quartile
Abilities of host markers detected in serum and saliva in ranges (in parenthesis) for serum markers that were significantly different
the diagnosis of TB disease between the active PTB, latent tuberculosis infection (LTBI) and the HE (No TB)
When the concentrations of host markers detected in group. Area under the curve (AUC) showing the diagnostic performance
of markers
serum samples were compared between the TB patients
and individuals with ORD with the Mann Whitney U
test, the concentrations of IL-6 and VEGF were signifi- Differences in the expression of host biomarkers in
cantly different between the two groups. The concentra- individuals with TB disease, LTBI and no Mtb infection
tions of IL-6 were significantly higher in active PTB Of the 39 participants in the No TB group, 18 had a
group (p = <0.0001) whereas the concentrations of negative QFT result. We compared the concentrations
VEGF were significantly higher in ORD group of host markers detected in serum and saliva in individ-
(p = 0.001). When the accuracy of the serum biomarkers uals with active PTB, LTBI or no Mtb infection, consid-
were assessed by ROC curve analysis, the potentially ering the QFT positive non-TB patients as LTBI. When
most useful individual host markers, as determined by the concentrations of host markers detected in saliva
area under the ROC curve (AUC >0.70) were IL-6 and were compared between any two groups (PTB vs LTBI
VEGF (Table 5). or PTB vs No Mtb or LTBI vs No Mtb) none of the host
When the concentrations of host markers detected markers investigated (with the exception of IFN-γ
in saliva samples were compared between the active showed significant differences between the two groups
TB group and ORD group, no significant differences (Table 7, Fig. 3).
were observed for all the 10 markers investigated When the concentrations of host markers detected in
(Table 6). serum were compared between any two groups (PTB vs
Table 6 Median marker levels in saliva between the active PTB group and those with other respiratory infections and area under
the curve (AUC) showing diagnostic performance of markers
Marker Median (pg/ml) PTB Median (pg/ml) ORD p-value AUC Sensitivity Specificity Cut off
IL-2 0.0 (0.0–0.0) 0.0 (0.0–0.0) 0.57 0.53 89.74 15.38 <0.38
IL-5 1.6 (0.6–2.1) 1.6 (0.6–2.1) 0.52 0.54 12.82 97.44 <0.12
IL-6 5.11 (2.4–9.5) 4.8 (2.1–6.4) 0.23 0.58 25.64 89.74 <2.1
G-CSF 0.0 (0.0–40.5) 0.0 (0.0–53.2) 0.64 0.53 17.95 92.31 >86.61
GM-CSF 257.9 (77.9–428.9) 282.2 (36.3–405.5) 0.65 0.53 20.51 92.31 <6.53
MIP-1a 1.9 (1.1–2.6) 1.9 (1.3–2.3) 0.69 0.53 7.69 97.44 <0.55
MIP-1b 0.0 (0.0–0.0) 0.0 (0.0–0.0) 0.61 0.51 97.44 7.69 <31.06
VEGF 1486 (1004–1960) 1368 (550.5–2020) 0.24 0.58 28.21 92.31 <571.3
TNF-a 0.0 (0.0–8.5) 0.0 (0.0–4.3) 0.45 0.54 84.62 33.33 <5.32
IFNg 0.0 (0.0–15.6) 0.0 (0.0–7.7 0.18 0.57 71.79 41.03 <0.47
Table 4: Shown are the saliva marker levels (median levels and inter quartile ranges (in parenthesis) comparing active TB (PTB) participants with other respiratory
diseases (ORD) with Area Under the ROC curve ranging between 0.51–0.58
Namuganga et al. BMC Infectious Diseases (2017) 17:600 Page 7 of 11

6000
N o T B ( H e a lt h y c o n tr o ls )

LTBI
4000
PTB

lo g le v e ls o f m a r k e r s
2000

50

40

30

20

10

0
I

I
I

I
I

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H

H
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-1
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IL
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-6

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G
IL
m a r k e r s in s a liv a

6000

4000
lo g le v e ls o f m a r k e r s

2000

100

80

60

40

20

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I

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I

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I
I

I
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T

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L

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T
T

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T
T

T
T

T
T
L

T
T

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P

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L
L

L
L

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-2

-5

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IL

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M a r k e r s in s e r u m

Fig. 3 Median and interquartile ranges of all 10 markers showing the differences between the active TB group (PTB), LTBI and the uninfected
(No TB) group in serum or saliva of all the study participants

LTBI or PTB vs No Mtb or LTBI vs No Mtb) the biosignature comprising of serum IL-6, MIP-1β, VEGF
concentrations of IL-6 and VEGF showed significant and saliva G-CSF and MIP-1α, diagnosed TB disease in
difference between the two groups (Table 7). Except for the training sample set (n = 54; n = 27 TB cases and
IFN-γ (p value 0.04) in saliva (Table 7, Fig. 4), serum n = 27 ORD), with a sensitivity of 81.5% (22/27) and
levels of IL-6 and VEGF were significantly different specificity of 100% (27/27), and with a sensitivity of 50%
between the active TB patients and latent TB infection (6/12) and specificity of 75% (9/12) in the test sample set
or uninfected (No TB individuals) with p-values ranging (n = 24, n = 12 TB cases and n = 12 ORD).
between <0.0001 to 0.01 and area under the ROC curve When only the saliva biomarkers were taken into
ranging between 071 and 0.86 (Table 7, Figs. 4, 5). consideration, a 3-marker model comprising of salivary
G-CSF, TNF-α and VEGF diagnosed TB disease in the
Utility of marker combinations for diagnosis of TB disease training sample set (n = 54; n = 27 TB and n = 27 ORD)
When the general discriminant analysis technique was with a sensitivity of 63% (17/27) and a specificity of 63%
used to assess the predictive abilities of combinations of (17/27). In the test sample set (n = 24; n = 12 TB,
serum and salivary biomarkers for TB disease, a 5-marker n = 12 ORD) however, the sensitivity and specificity of
Namuganga et al. BMC Infectious Diseases (2017) 17:600 Page 8 of 11

search for other biomarkers in TB research on the lead,

150
there’s a need for a non-sputum biological sample and
biomarker [18]. This study evaluated whether saliva
le v e l o f m a r k e r s

could serve as an alternative specimen to serum for TB

100
*** diagnosis. This owes to its non invasive nature of collec-
p g /m l

tion which can be applicable in children and the very ill

groups [19]. Recently, studies evaluating the relevance of
50 salivary host markers have shown promising markers
***
that could be incorporated in a point-of-care test follow-
ing validation [10, 11] and [13]. Overall, the levels of
0 markers were higher in serum for all participants except
for GM-CSF and VEGF. This confirms the findings by
I

Y
B

T
T

L
P

Phalane et al. [13]. This study found increased levels of

L

H
a

a
v

a
v
li

VEGF and IL-6 in serum samples of active PTB patients

li

li
a

a
S

a
S

compared to those with other respiratory diseases. These

-g

-g

-g
N

N
IF

IF

were also identified in previous studies [10, 11] and [13].

IF

In t e r f e r o n g a m m a le v e ls in S a liv a Increased VEGF in serum of patients with active TB

makes it a useful prognostic indicator in granulomatous
800
diseases, such as TB as identified by [20]. This suggests
its role in pathogenesis of pulmonary TB in the develop-
le v e l o f m a r k e r s

600 ment of the chronic inflammatory reaction.

In line with a study by Phalane et al. [13], increased
p g /m l

400
saliva levels of GM-CSF in this study are relevant to en-
*** hance T cell responses, regulate phagocytosis and innate
immune responses in alveolar macrophages [21]. High
200 GM-CSF levels have also been identified in saliva of
***
patients with oral squamous cell carcinoma [22].
0 Serum levels of MIP-1α, IL-6, TNF-α, IFN-γ and G-
CSF were noticeably higher than were in saliva. IL-6 and
I
I

B
B

B
B

T
T

T
T

TNF-α are pro-inflammatory cytokines which have a

P
P

L
L

m
m

m
m

role in granuloma formation [23]. MIP-1α and β are im-

ru
ru

ru
ru

e
e

e
e

S
S

S
S

portant chemo attractants for lymphocytes to the site of

-6
F

-6
F
G

IL
G

TB infection leading to suppression of Mycobacterium

IL
E

E
V

M a r k e r s in s e r u m
growth [24]. Findings by other investigators [25, 26] also
identified MIP-1α and β to be produced in high amounts
Fig. 4 Top: Levels of markers significantly different in the serum
samples of pulmonary TB cases and latent TB disease, and below:
in TB disease. IFN-γ on the other hand is important in
Level of markers that were significantly different the different TB promoting antigen presentation and recruiting T helper
disease in saliva and cytotoxic T cells involved in killing the bacilli. In
combination with TNF-α, they activate macrophages in
order to kill intracellular pathogens and induce produc-
the 3-marker salivary biomarker model were only 42% tion of reactive nitrogen intermediates [27]. Serum levels
(5/12) and 75% (9/12) respectively. of markers are insufficient to base on for Mtb complex
The most frequently occurring markers in the TB diagnosis as we can’t pin their origin entirely to one
disease predictive combinations comprised of serum immune condition such as PTB [28]. For this reason,
IL-6, VEGF, and MIP-1β as well as salivary G-CSF salivary markers are being evaluated for their use in PTB
and MIP-1α (Fig. 6). disease diagnosis.
When salivary marker levels were evaluated for their
Discussion ability to differentiate between active TB disease from
The search for biomarkers of TB disease and infection No TB disease, there was no significant difference
requires the investigation and research on non-sputum between the individual marker levels. Comparing with
samples for TB diagnosis [17]. Early in biomarker re- serum, the concentrations of IL-6 and VEGF were
search, IFN-γ took the lead as a relevant TB biomarker. significantly different between the active TB disease
It has however shown not to be a reliable biomarker if group and the ORD group. This may suggest that
not used in conjunction with other markers. With the salivary biomarkers may not be very useful individually
Namuganga et al. BMC Infectious Diseases (2017) 17:600 Page 9 of 11

150 150
p - v a lu e = < 0 .0 0 0 1 p -v a lu e = 0 .0 5
A U C = 0 .8 5
A U C = 0 .6 3
S e n s itiv ity

S e n s itiv ity
100 100

50 50

0 0
0 50 100 150 0 50 100 150
( IL - 6 S e r u m ) 1 0 0 % - S p e c if ic it y % ( T N F - a S e r u m ) 1 0 0 % - S p e c if ic it y %

150 150
p -v a lu e = 0 .0 5
p -v a lu e = 0 .0 0 1
A U C = 0 .6 5
A U C = 0 .7 1

S e n s itiv ity
S e n s itiv ity

100 100

50 50

0 0
0 50 100 150 0 50 100 150
( V E G F S e r u m ) 1 0 0 % - S p e c if ic it y % ( IF N -g s a liv a ) 1 0 0 % - S p e c if ic it y %

Fig. 5 ROC curves with p values and Area Under the Curve (AUC) values for those markers that were significantly different in active TB disease
and No TB disease

in the diagnosis of TB disease. This may however, only findings also suggest that Interleukin-6 as noted by pre-
apply to the markers investigated in the current study as vious studies by Jacobs et al., [10] and Phalane et al.,
previous reports identified salivary biomarkers which [13] may be relevant for TB diagnosis. IL-6 appeared in
showed potential in the diagnosis of TB disease (Phalane predictive combinations and is known to stimulate the
et al., [13] Jacobs et al., [10] Jacobs et al. [11]). When secretion of IFN-γ, a crucial cytokine in the activation of
biomarkers were used in combinations however, a macrophages infected with M.tb [31]. This correlates
biosignatures containing salivary biomarkers and combi- with findings by [24] who identified increased serum
nations between saliva and serum markers showed levels of IL-6 in active TB patients. IL-2 on the other
potential. This correlates with findings by [29] and [30] hand was below detectable levels for both serum and
which reported high VEGF levels in active TB. Our saliva. It is a relevant T cell growth factor, macrophage

a b 20
25
No of observations
No ofobservations

20 15

15
10
10
5
5

0 0
Sa d
M Trim ed
-5 GC Se d
IL Sal SF rum

-1 M Tri ed

-g um S d
Tr um

ru rim va

a
ru Trim m

ed
a
a
liv
-1 me
e

liv

liv
liv
u
Se a T ali

m
IL mm

IF S -1 m

m
m er

er

Sa

Sa
Sa
b IP m

im
S
ru F S

F
SF
6

N er b

Tr
F-
-

G
Se EG

m
m

IP

a
VE
TN
-5 iv

liv
G
V

Se

Sa
-6

-6
IL
IL

IL
IP
M

Markers
Markers
Fig. 6 (a) Bar graph showing frequency of analytes in the GDA models generated from combining saliva and serum samples, (b) frequency of
analytes in models generated when the data obtained from the host markers detected in saliva only
Namuganga et al. BMC Infectious Diseases (2017) 17:600 Page 10 of 11

activator [23] and contributes to T cell memory. Previ- Availability of data and materials
ous studies found IL-2 production to be reduced among All data supporting the conclusions of this article is included within this
article. We have no additional, unpublished data. Data shown in the
active PTB patients [32]. This may explain the low IL-2 manuscript is available on request from ARN and HMK.
levels shown given that all samples used were baseline
from TB suspects. Authors’ contributions
ARN; conceptualization, methodology, statistical analysis and writing original
More investigations are required including studies draft, NNC; conceptualization, methodology, statistical analysis and
done on biomarkers other than the ones investigated in manuscript review, PM; data analysis GW and HMK; writing up of the
the current study, given the potential that a diagnostic protocol, clinical classification of study participants, provided material for all
experiments, advised on statistical analysis, supervision, funding acquisition
tool based on saliva may contribute to the management and manuscript review. All authors read and approved the final manuscript.
of TB disease in all patient types especially those with
difficulty in providing sputum samples such as children. Ethics approval and consent to participate
Such future studies should focus on the identification of This study used subjects who gave informed consent to participate in a larger
African European Tuberculosis consortium (AETBC) study. Ethical approval was
biosignatures, rather than individual biomarkers given obtained from Uganda National Council of Science and Technology, Makerere
that these inflammatory biomarkers may not be highly University, College of Health Sciences and the Joint Clinical Research Centre
specific for TB, especially when used alone. Validated Institutional review Boards.

salivary biosignatures could then be incorporated into Consent for publication

point-of-care tests for the diagnosis of TB disease Not applicable.
(Sutherland et al. [33]).
Competing interests
The authors declare that they have no competing interests.
Conclusion
In conclusion, saliva may be an important alternative
Publisher’s Note
diagnostic sample for PTB diagnosis and biomarker dis- Springer Nature remains neutral with regard to jurisdictional claims in
covery. Our findings suggest that biosignatures compris- published maps and institutional affiliations.
ing of combinations between different host markers
Author details
detected in saliva may be useful for the diagnosis of PTB 1
Joint Clinical Research Centre, Kampala, Uganda. 2Division of Molecular
disease. We confirmed that there are highly significant Biology and Human Genetics, Department of Biomedical Sciences, DST/NRF
differences in the concentrations of some biomarkers Centre of Excellence for Biomedical Tuberculosis Research and SAMRC
Centre for Tuberculosis Research, Faculty of Medicine and Health Sciences,
expressed in saliva in comparison to serum levels and Stellenbosch University, Cape Town, South Africa. 3Uganda – Case Western
therefore biomarkers that do not show potential in Research Collaboration, Mulago-Kampala, Uganda. 4College of Health
serum samples may not necessarily yield the same re- Sciences, Makerere University, Kampala, Uganda.
sults in saliva. Therefore saliva warrants further explor- Received: 29 September 2016 Accepted: 16 August 2017
ation as a sample for biomarker TB biomarker discovery
given that it is a very easily accessible sample and can be
collected from all patient types, and immunological as- References
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